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Integrating Genetics, Genomics and Biology to Gain Clinical Insights into Cancer
Jeffrey Trent
October 15, 2003
http://www.mcli.dist.maricopa.edu/honors/forum.php?yr=0304&id=2
Jeffrey Trent, Ph.D. is the president and chief scientific officer of the new Translational Genomics Research Institute and scientific director for the International Genomics Consortium in Phoenix, Arizona. Dr. Trent graduated from Arcadia High School and earned a B.A. from Indiana University before receiving a Ph.D. from the University of Arizona.
Dr. Trent was scientific director of the cancer genetics branch and senior investigator and chief of intramural research at the National Human Genome Research Institute in Bethesda, MD. His laboratory focuses on the study of genetic changes related to cancer predisposition and progression. Recently his research has focused on the genetic susceptibility to human prostate cancer. Other work in his laboratory has been focused upon relating the recent advances in both molecular biology and cancer genetics and the valuable tools of the Human Genome Project for the study of human oncogenesis. This has included the development of technologies for analyzing the expression patterns of genes using cDNA microarray technology
Tony will be coming out with another PR before the meeting I just feel it in me bones
Dnap goin going gone
Sorry about the last post
Wow great news out today Dnap will soon be snoring.
Molecular Expressions photo Gallery - http://micro.magnet.fsu.edu/micro/gallery.html
Take a look nice site for History of Visualization of Biological Macromolecules - http://www.umass.edu/microbio/rasmol/history.htm
Molecular modeling-defined - http://www.netsci.org/Science/Compchem/feature01.html
DNAPrint Upgrades DNAWitness(TM) 2.5; New Information Technology for Better Physical Profiling
Thursday July 22, 11:29 am ET
SARASOTA, Fla., July 22 /PRNewswire-FirstCall/ -- DNAPrint genomics (OTC Bulletin Board: DNAP - News; the "Company") announces today that it has upgraded its DNAWitness(TM) 2.5 product for physical profiling from DNA with a proprietary database designed to help investigators learn what their results say, or don't say, about physical appearance.
The DNAWitness(TM) 2.5 genome test allows forensics investigators to employ objective science, empiricism and statistical analysis in the reconstruction of a physical profile or "fuzzy photo" from DNA left at a crime scene. It employs the world's first molecular genetics test for the inference of BioGeographical Ancestry (BGA) admixture. For example, DNA at a crime scene may indicate that a person is of 90% East Asian, 10% European mix. BGA is obviously related to physical appearance, and individuals with fewer admixtures tend to have more accentuated anthropometric characteristics (those that vary from race to race). Investigators who obtain a result such as 100% East Asian typically have little difficulty interpreting the result, but investigators who, for example, obtain a result such as 70% European, 30% East Asian usually ask whether the person's physical appearance would reveal the East Asian admixture. Communicating how BGA relates to physical appearance is difficult to do with words in a scientific way, but the advance announced today is the first solution for this problem.
To project what a person may look like from knowledge of their DNA, DNAPrint has developed the DNAWitness(TM) 2.5 database of individual BGA admixture results. The database contains information on how individuals previously tested have self-defined in terms of ethnicity (called the "geopolitical" arm of the database) as well as their digital photographs. By querying the database using a specific BGA admixture result, investigators can see for themselves what the range of variability is corresponding to that result for various features, such as skin shade, hair texture, nose shape, epicanthal eye folding, etc. Whether or not, for example, individuals of 70% European, 30% East Asian admixture tend to show no East Asian features, would be apparent from the database query. Statistical tools soon to be added will allow investigators to use Analysis of Molecular Variance to determine whether there is a systematic difference in the expression of an anthropometric trait that can be measured from the photograph in one database sample set versus the international average, or versus another group. DNAPrint has already filed patent applications on the use of digital photograph databases and databases of biographical data with BioGeographical Ancestry admixture data.
Last week, the Company provided a mid-Atlantic customer access to this database for the first time; all DNAWitness(TM) 2.5 customers from today forward will enjoy its use.
About DNAPrint genomics, Inc.
DNAPrint genomics, Inc. uses proprietary human genome research methods to develop genomic-based services and products. The Company introduced AncestryByDNA in the consumer market and DNAWitness(TM) in the forensic market in 2003. DNAPrint is developing products in the pharmacogenomic market and has a disease gene discovery program. The Company is traded on the Nasdaq OTC Bulletin Board under the ticker symbol: DNAP. For more information about the company, please visit http://www.dnaprint.com.
All statements in this press release that are not historical are forward- looking statements within the meaning of Section 21E of the Securities Exchange Act as amended. Such statements are subject to risks and uncertainties that could cause actual results to differ materially from those projected, including, but not limited to, uncertainties relating to technologies, product development, manufacturing, market acceptance, cost and pricing of DNAPrint's products, dependence on collaborations and partners, regulatory approvals, competition, intellectual property of others, and patent protection and litigation. DNAPrint genomics, Inc. expressly disclaims any obligation or undertaking to release publicly any updates or revisions to any forward-looking statements contained herein to reflect any change in DNAPrint's expectations with regard thereto or any change in events, conditions, or circumstances on which any such statements are based.
Media and Press Contact
Richard Gabriel
DNAPrint genomics, Inc.
CEO/President
(941) 366-3400
Dr. Jeffrey Trent see Post # 15783
NHGRI Scientific Director Departing To Lead New Genomics Consortium
June 26, 2002
BETHESDA, Md.- The National Human Genome Research Institute's Intramural Scientific Director, Dr. Jeffrey Trent, formally announced that he would be leaving the institute to lead the private, non-profit Translational Genomics Research Institute (TGRI) in Phoenix, Arizona. Dr. Trent will remain NHGRI's Scientific Director while a national search is conducted to find his replacement.
Prepared Statement of Dr. Francis S. Collins
Director, National Human Genome Research Institute
"Jeff will be very much missed. He has been a terrific leader of genomic research on the NIH campus. He was instrumental in creating the intramural program of NHGRI and leading it to become one of the strongest programs in genetics and genomics in the world. His own research on cancer genetics, especially prostate cancer, melanoma, and breast cancer, has been groundbreaking.
"With the sequence of the human genome and a host of other research resources and technologies now available, the opportunities to translate basic science into clinical medicine are unprecedented. I am sure that the new TGRI will play an important role in the exciting new era."
"Jeff is not only a terrific scientist and a remarkably talented leader but a close friend as well. I am sad to see him leave NIH, but he clearly has a vision for what he wants to do in this next chapter of his life. He and his wife Dee have strong and deep roots in Arizona, and I know they are looking forward to going back home. All of us at NHGRI would like to extend our best wishes for success and happiness in their new endeavors."
OH I wonder who this is what could he have to do with Dnap Hmmmm - Jeffrey M. Trent - http://www.gcit.az.gov/members/Jeffrey_Trent.html
Jeffrey M. Trent, Ph.D. is President and Scientific Director of the newly formed Translational Genomics Research Institute (TGen) in Phoenix, Arizona. Dr. Trent was formerly the Scientific Director of the National Human Genome Research Institute (NHGRI) at the National Institutes of Health (NIH) and served as Chief of its Cancer Genetics Branch. He received his undergraduate degree from Indiana University, Bloomington, and M.S. and Ph.D. degrees in Genetics from the University of Arizona, Tucson. Dr. Trent was the Emanuel N. Maisel Professor of Oncology and Professor of Radiation Oncology and Human Genetics at the University of Michigan, Ann Arbor. He also served as Director of the Division of Cancer Biology, and Director of Basic Sciences in the University of Michigan Comprehensive Cancer Center. In 1993, Dr. Trent went to the NHGRI to establish and direct its Division of Intramural Research. Under his guidance, the division became a major research center in human genetics. Dr. Trent’s research specializes in integrating technologies from the Human Genome Project (e.g., cDNA microarrays, high throughput genotyping, etc.) to study molecular changes related to the predisposition to, and progression of human cancers<
Below is just a few places that are working one way or another with Dnap Now these people are not the types to play around with a comp. thats going no where.
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Wistar institute;University of Pennsylvania School of Medicine; Queensland Cancer Fund Laboratories; Queensland Institute of Medical Research;Department of Pathology, University of Queensland, Brisbane, Queensland, Australia; and Centre for Drug Design and Development, University of Queensland, St. Lucia, Queensland, Australia ;Ludwig Institute for Cancer Research, Austin Hospital
Heidelberg, Australia;Saarland University Medical School Homburg, Germany; Department of Biochemistry, La Trobe University, Victoria 3086, Australia ;Felsenstein Medical Research Center, Sackler School of Medicine, Tel Aviv University, Beilinson Campus, Petach Tikva 49100, Israel ;Chemistry Department, Bar Ilan University, Ramat Gan 52900, Israel;Genetic Epidemiology Group
Professor of Metabolic and Genetic Epidemiology: ;
Meenhard Herlyn Research Laboratory - http://www.wistar.upenn.edu/herlyn/
"Wistar institute" a name that lurks in the back ground But also is a Big Player with Dr. Sturm - http://www.wistar.upenn.edu/research_facilities/mherlyn/research.htm
Meenhard Herlyn, D.V.M.
Professor and Program Leader
Molecular and Cellular Oncogenesis Program
215-898-3950, Office
215-898-0980, Fax
herlynm@wistar.upenn.edu
www.wistar.upenn.edu/herlyn
Introduction
Research in the laboratory of Meenhard Herlyn centers on the basic mechanisms that govern normal cell function, or homeostasis. Knowing how cells and tissues orchestrate their intertwined purposes helps researchers establish what happens when things go awry, such as in cancerous tumors.
Research Summary
Cells in normal tissues maintain a life-long homeostatic balance, in which growth, differentiation, and cell death are dynamically regulated. To establish and maintain normal organ structure and function, they must remain within their predestined locations within each organ. The delicate balance among cells within the scaffolding of matrix proteins is disturbed during tumor development. Transformed cells escape from homeostasis and destroy normal tissue architecture. Our laboratory is interested in defining normal tissue homeostasis and understanding pathological changes during cancer development and progression in order to develop new strategies for therapy.
Recent Scientific Advances
Intercellular crosstalk in normal skin and melanoma (Steve Kazianis, Ph.D., Mizuho Fukunaga M.D. Ph.D., Nikolas Haass, M.D., Ling Li, M.D., Akihiro Yoneta, M.D., Ronan McDaid, B.S., Bernard Herlyn): Using a three-dimensional model of normal human skin in vitro and in vivo, we are investigating how melanocytes and keratinocytes communicate with each other, how melanocytes transform when driven by growth factors and UVB, how melanoma cells have switched partners from keratinocytes to fibroblasts and endothelial cells and how we can establish new therapeutic strategies by forcing the malignant cells back under the control of normal keratinocytes.
Signaling in melanoma and therapeutic strategies (Keiran Smalley, Ph.D., Patricia Brafford, M.S.): We are defining the signal transduction pathways that are constitutively activate in melanoma cells through autocrine and paracrine growth factors (bFGF, ET-3, SCF, IGF-1, HGF, TGF-ß). Three-dimensional models are being developed to investigate tumor-to-fibroblast crosstalk in a tissue context. Through RNAi approaches we are selecting those genes in tumor cells and stromal fibroblasts that are potential targets for therapy. Artificial skin/melanoma and esophagus/carcinoma models are used for selecting small molecules as antagonists.
Stem cells, transformation, and microenvironment (Dong Fang, M.D., Ph.D., Rena Finko, M.S., Kim Leishear, B.S., Nga Nguyen, B.S., Angela Kulp): Human embryonic stem cells are differentiated into melanocytes to test the hypothesis that melanocyte progenitor cells are more prone to transformation than fully differentiated cells and that neighboring cells and matrix in the microenvironment play critical roles in differentiation and transformation. Bone marrow-derived stem cells give rise to hematopoietic, mesenchymal, endothelial cells, and, as in the case of multipotent adult progenitor cells (MAPCs), to a variety of ectodermal and neuroectodermal cells. We are investigating the biological significance for tumor progression of fibroblasts and endothelial cells derived from the bone marrow stem cell pool hypothesizing that rapidly expanding tumors attract stem cells to meet their needs for new vessels and matrix. We are also testing whether we can differentiate other skin cells from human bone marrow and embryonic stem cells.
The vascular phenotype in melanoma (Zhao-Jun Liu, M.D., Ph.D, Chelsea Pinnix, Klara Balint, M.D., Haiyan Chen, M.D., Cheeyong Pang): Active angiogenesis is one of the hallmarks of melanoma. We are interested in elucidating the molecular mechanisms of neovascularization in melanoma and are focusing on signaling through cell surface molecules including Notch, a v b3 integrin, and Mel-CAM (CD146). We are investigating their involvement in differentiation of bone marrow-derived stem cells into endothelial cells and their contribution to tumor angiogenesis. All three molecules are prototypes for expression on both melanoma and endothelial cells and we hypothesize that they play major roles in metastasis by regulating endothelial-melanoma cell interactions.
Cell-cell adhesion for normal tissue homeostasis:
Skin – Keratinocytes in the epidermis of the skin control proliferation of melanocytes and dictate which cell surface molecules are expressed for adhesion and migration. The lab’s working hypothesis is that melanocyte proliferation is possible if they decouple from keratinocytes by down-regulating E-cadherin and its co-receptor desmoglein-1, which will interrupt gap junctions formed through connexin 43 molecules. Dwon-regulation of expression of the cell-cell communication molecules is mediated through the production of HGF, ET-1, and PDGF. The melanocytes then retract their dendrites that had connected them to keratinocytes of the suprabasal layers by activating rac and rho genes. Cell division is likely initiated through activation by keratinocyte-derived growth factors such as bFGF, SCF, ET-1 or by fibroblast-derived factors such as HGF, IGF-1, or ET-3. After cell division, melanocytes separate and glide over the basement membrane using integrins such as alpha6ß1 or alpha7ß1 before repositioning singly among basal layer keratinocytes. Using the three-dimensional organotypic culture model of human skin consisting of dermis and epidermis we are retracing each step in the proliferation cascade of melanocytes to better understand dysregulation of growth and cell-cell communication in melanoma. The lab uses adenoviral and lentiviral vectors to transfer genes for overexpressing or inhibiting a function of interest. The unique model of human skin reconstruction in vitro and in vivo allows us to investigate signaling between melanocytes and keratinocytes for tissue homeostasis and its dysregulation during transformation to nevi and melanomas.Melanoma cells have escaped from keratinocytes by downregulating E-cadherin and upregulating N-cadherin. The cadherin switch allows a cell partner change because now melanoma cells can adhere through N-cadherin to fibroblasts and endothelial cells. Overexpression of E-cadherin in melanoma cells allows keratinocytes to adhere to them and regain control over proliferation and the expression of cell surface molecules, so the malignant cells revert to a non-malignant phenotype. The team expects in the next few years to identify and characterize transcriptional activators or repressors in normal melanocytes that are non-functional in melanoma cells but can be reactivated to control growth and invasion.
Esophagus – The squamous epithelium of the normal human esophagus follows a similar differentiation pattern compared to the normal epidermis except that different keratins are expressed. To better understand homeostasis in the normal esophagus the lab is overexpressing growth factors and disrupt/activate receptor function in either fibroblasts or esophageal keratinocytes. This is done by embedding the stromal cells in a three-dimensional collagen matrix and exposing overlayed keratinocytes to air to allow multi-layer formation and differentiation. The lab tests the hypothesis that continuous activation of keratinocytes through the local production of growth factors can induce a transformed phenotype. The lab hypothesizes that the EGF and TGF-ß receptor systems are dominant for maintaining the homeostatic balance in the normal esophageal mucosa and their dysfunction is critical for tumor development and progression and that fibroblasts and endothelial cells are recruited during tumor progression from the bone marrow stem cell pool.
Endothelium – Long-term objectives in this area include understanding the dynamic changes in gene expression during dysregulation of homeostasis in cancer and chronic wounds. The laboratory has developed an in vitro vessel reconstruction model that demonstrates the importance of fibroblasts for endothelial cell migration and differentiation. We can now systematically dissect the processes of blood vessel formation and tumor-stimulated angiogenesis by regulating gene expression in either fibroblasts or endothelial cells. The emphasis is on those growth factor and adhesion receptors that are shared between activated endothelial cells and melanoma cells including VEGFR2, VEGFR-1, a vß3, Mel-CAM (CD146), Notch-1, and EphA2.
Experimental transformation of melanocytes: The critical difference between uncontrolled and controlled melanocyte proliferation in skin is their permanent de-coupling from keratinocytes, the ability of cells to communicate with stromal cells and the constitutive production of growth factors. The lab hypothesizes that the growth factor bFGF needs to be activated if the melanocytes are to survive when they de-couple from the keratinocytes and migrate into the dermis. bFGF can transform melanocytes in a human skin graft model, when the skin is irradiated at the same time with UVB. If three growth factors -- bFGF, SCF and ET-3 -- are combined for overexpression in the dermis and the skin is irradiated with UVB, melanoma-like lesions are induced within three to four weeks. This unique carcinogenesis model allows the team to retrace the different steps of melanoma development from healthy epidermal melanocytes; to establish molecular markers for melanoma diagnosis and prognosis; and better investigate the most critical signaling pathways for transformation. It is becoming apparent that the MAP kinase signaling pathway is constitutively activated, either through autocrine and paracrine growth factors or through activating mutations of the BRAF and n-ras genes.
Tumor-stroma interactions during tumor progression and metastasis: The unique RGP and VGP primary and metastatic melanoma cell lines that have been established in the last 20 years in the Herlyn laboratory are being used to investigate the roles of growth factors and adhesion receptors in tumor-stroma interactions,. The tumor stroma is composed of fibroblasts, blood vessels, inflammatory cells and matrix proteins such as collagens, fibronectin, laminins, and proteoglycans. Melanoma cells produce bFGF and HGF for autocrine (self) stimulation whereas PDGF, VEGF and TGF-ß are produced for stimulation of the tumor stroma. Stromal fibroblasts in turn provide growth factors such as IGF-1 or HGF for positive feed back (stimulation) of the malignant cells. The laboratory is developing for each stromal cell type – that is, fibroblasts, endothelial cells, monocytes, and neutrophils -- regulatory circuits for positive and negative cross talk to the malignant cells. Endothelial cells and fibroblasts in the tumor stroma are apparently derived from two separate pools, the resident pool recruited from tissues adjacent to the tumor, and the precursor pool that has migrated from bone marrow and peripheral blood. The team does not know how the precursor cells are recruited or the signals needed for differentiation, but expects that tumor cells provide appropriate signals and so are testing this hypothesis in melanoma, and esophageal carcinoma.
The plastic phenotype in metastasis: multiple roles for cell-cell and cell-matrix adhesion receptors for invasion and metastasis: Primary melanomas have numerous abnormalities within their genetic make-up, suggesting considerable genomic instability. No major additional genomic changes appear necessary for metastasis, because VGP melanomas are easily adapted to a metastatic phenotype by culture in growth factor-free medium and by induction of invasion through basement membrane-like matrix material. The lab is testing the hypothesis that micro-environmental changes in cell-matrix and cell-cell signaling are critical for the metastatic phenotype. One of the main players is the cell-cell adhesion molecule of the CAM family -- MUC18/Mel-CAM -- which is expressed by all melanoma cells and binds to an as-yet-unknown ligand also found on melanomas. Mel-CAM is one of at least six CAM -- ALCAM, VCAM-1, ICAM-1, CEA1-CAM, L1-CAM -- shared between melanoma and endothelial cells and we are delineating their biological functions for metastasis. Similarly, activated endothelial and melanoma cells share the integrin alphavß3 and cadherins N-cadherin and VE-cadherin, so understanding the contribution of these to the metastatic phenotype is also important. Based on preliminary studies it is also likely that the tumor-infiltrating endothelial cells are being recruited from the bone marrow stem cell pool. Thus another current experiment tests whether differentiating stem cells express unique molecules that can be targeted for therapy.
Selected Publications
Schaider, H.,* Oka, M., * Bogenrieder, T., Nesbit, M., Satyamoorthy, K., Berking, C., Matsushima, K., and Herlyn, M. Differential response of primary and metastatic melanomas to neutrophils attracted by IL-8. Int. J. Cancer 103: 335-343, 2003.* Equal contribution.
Gruss, C.J., Satyamoorthy, K., Berking, C., Lininger, J., Nesbit, M., Schaider, H., Liu, Z.-J., Oka, M., Hsu, M-Y., Shirakawa, T., Li, G., Bogenrieder, T., Carmeliet, P., El-Deiry, W.S., Eck, S.L., Rao, J.S., Baker, A.H., Bennett, J.T., Crombleholme, T.M., Velazquez, O., Karmacharya, J., Margolis, D.J., Wilson, J.M., Detmar, M., Skobe, M., Robbins, P.D., Buck, C., and Herlyn, M. Stroma formation and angiogenesis by induced expression of growth factors, cytokines, and proteolytic enzymes in human skin grafted to SCID mice. J. Invest. Derm. 120: 683-692, 2003.
Liu, Z.-J., Shirakawa, T., Li, Y., Souma, A., Oka , M., Dotto, G.P., Fairman, R., Velazquez, O.C., and Herlyn, M. Regulation of notch1 and dll4 by vascular endothelial growth factor in arterial endothelial cells: implications for modulating arteriogenesis and angiogenesis. Mol. Cell Biol. 23: 14-25, 2003.
Satyamoorthy, K.,* Li, G.,* Gerrero, M.R., Brose, M.R., Volpe, P., Weber, B.L., Van Belle, P.A., Elder, D.E., and Herlyn, M. Constitutive mitogen-activated protein kinase activation in melanoma by both BRAF mutations and autocrine growth factor stimulation. Cancer Res. 63: 756-759, 2003. *Equal contribution
Kalabis, J., Patterson, M.J., Gimotty, P., Enders, G.H., Marian, B., Iozzo, R.V., Rogler, G., and Herlyn, M. Stimulation of human colonic epithelial cells by leukemia inhibitory factor is dependent on collagen-embedded fibroblasts in organotypic culture. FASEB J. 17: 1115-1117, 2003.
Li, G., Kalabis, J., Xu, X., Meier, F., Oka, M., Bogenrieder, T., Herlyn, M. Reciprocal regulation of MelCAM and AKT in melanoma. Oncogene 22: 6891-6899, 2003.
Berking, C., Takemoto, R., Satyamoorthy, K., Eskandarpour, M., Shirakawa, T, Hanson, J., vanBelle, P.A., Elder, D.E., Herlyn, M: Induction of melanoma phenotypes in human skin by growth factors and ultraviolet B. Cancer Res., 64: 807-811, 2004.
Reviews
Velazquez, O., and Herlyn, M. The vascular phenotype of melanoma metastasis. Clin. Exp. Met. 20 : 229-235, 2003. (R)
Li, G., Meier, F., Berking, C., Satyamoorthy, K., Bogenrieder, T., and Herlyn, M. Function and regulation of melanoma-stromal fibroblast interactions: when seeds meet soil. Oncogene 22: 3162-3171, 2003. (R)
Tuveson, D. A., Weber, B.L., and Herlyn, M. BRAF as a potential therapeutic target in melanoma and other malignancies. Cancer Cell 4 :95-8, 2003 (R).
Liu, Z.-J., and Herlyn, M. Slit-Robo: Neuronal guides signal tumor angiogenesis. Cancer Cell 4: 1-2, 2003 (R).
Bogenrieder, T., Elder, D.E., and Herlyn, M. Molecular and cellular biology. In: Cutaneous Melanoma, 4 th edition, C. M. Balch, A.N. Houghton, A.J. Sober, S-j Soong, eds., Quality Medical Publ., St Louis, MO, pp. 713-751, 2003 (R).
Bogenrieder, T., and Herlyn, M. Axis of evil: Molecular mechanisms of cancer metastasis. Oncogene 42 : 6524-6536, 2003 (R).
Satyamoorthy, K., and Herlyn, M. p16 INK4A and familial melanoma. Methods Mol. Biol. 222: 185-195, 2003. (R).
Hsu, M-Y., Ling, L., and Herlyn, M. Cultivation of normal human epidermal melanocytes in the absence of phorbol esters. In: Methods in Molecular Medicine: Human Cell Culture Protocols (G.E. Jones ed.). Humana Press, Inc., Totowa, NJ, in press.
Perlis, C., and Herlyn, M: Recent advances in melanoma biology. Oncologist, in press, 2004 (R).
Smalley, K.S., and Herlyn, M. The great escape: Another way for melanoma to leave physiological control? J. Invest. Dermatol. 121: ix, 2003 (R).
Liu, X.-J., and Herlyn, M. Molecular biology of cutaneous melanoma. In: 7 th edition of Cancer: Principles and Practice of Oncology, (V.T. DeVita, Jr., S. Hellman, S.A. Rosenberg, eds.). Lippincott Williams &Wilkins, Philadelphia, PA, in press. (R)
Herlyn, M., and Guerry, D. IV. Meeting Report: First International Melanoma Research Congress. Cancer Biol. Therapy 2: 721-724 , 2003. (R)
Haass, N.K., Smalley, K. S. M, and Herlyn, M: The role of altered cell-cell communication in melanoma progression. J. Mol. Histo., in press. (R)
Dr. Bhavesh Vaidya -
Insulin-like Growth Factor-I-induced Migration of Melanoma Cells Is Mediated by Interleukin-8 Induction1
Kapaettu Satyamoorthy2,3, Gang Li2, Bhavesh Vaidya, Jiri Kalabis and Meenhard Herlyn4
Wistar Institute [K. S., G. L., B. V., J. K., M. H.] and the University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104 [G. L., M. H.]
Abstract
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Abstract
Introduction
Results
Discussion
Materials and Methods
References
Successive events of growth factor-induced autocrine and paracrine activation promote tumor growth and metastasis. Insulin-like growth factor-I (IGF-I) stimulates melanoma cells to grow, survive, and migrate. Interleukin-8 (IL-8) is produced by melanoma cells and has been correlated with melanoma metastasis, but the biological functions of this cytokine have not been elucidated. We show here that IGF-I-induced migration of melanoma cells could be inhibited by neutralizing antibody against IL-8. IGF-I overexpression induced IL-8 production in melanoma cells, especially in biologically early melanomas by accelerating its transcription rate via activation of mitogen-activated protein kinase pathway. IGF-I treatment phosphorylated c-Jun and stimulated the binding of AP-1 but not NF-B to the IL-8 promoter. These data identify IL-8 as a new target of IGF-I in melanoma and suggest that some of the biological functions of IGF-I are mediated by IL-8.
Introduction
TOP
Abstract
Introduction
Results
Discussion
Materials and Methods
References
Melanoma arises through disruption of homeostatic events of normal melanocytes. During the progression from RGP5 (1) to VGP and metastatic melanoma, melanoma cells produce a variety of growth factors and cytokines that enables them to progress to a more aggressive phenotype (1) . Besides autocrine stimulation, the cross-talk between melanoma cells and their microenvironment via growth factors and cytokines modulates cell proliferation, differentiation, adhesion, migration, invasion, apoptosis, stromal formation, and angiogenesis (2 , 3) . Many growth factors/cytokines are involved in this intricate network. Primarily among them are basic fibroblast growth factor, IGF-I, PDGF-A and -B, transforming growth factor- and -ß, IL-8, VEGF, and hepatocyte growth factor/scatter factor (for review, see Ref. 3 ).
In human skin, IGF-I is mainly produced by stromal fibroblasts that are activated by melanoma-derived PDGF (4) . Previously, it has been shown that IGF-I is critical for survival, growth, and motility of biologically early melanoma cells (5, 6, 7, 8, 9, 10) . These actions are apparently mediated by the type 1 IGF-IR (11) , which is expressed by all melanocytic cells (10) , and the expression increases with progression (12) . Down-regulation of IGF-IR with antisense oligonucleotides inhibited melanoma growth in vivo (13) . Mice transgenic for IGF-I under a keratin 1 promoter showed marked thickening of the dermis and hypodermis and prone to transformation (14) , suggesting that IGF-I is a critical factor in tumor development and progression.
IL-8 is not expressed by normal melanocytes (15, 16, 17) but by all human melanoma cells with the nontumorigenic RGP melanoma cells secreting significantly lower levels of IL-8, compared with VGP or metastatic melanoma cells (15) . IL-8 may sustain an autocrine effect because melanoma cells express its receptors IL-8RA and IL-8RB (18) . In certain cancer types, IL-8 can stimulate growth (19) , migration (20) , proteolysis (21 , 22) , and angiogenesis (23 , 24) ; however, the functions of IL-8 in melanoma have not been well studied.
In the present study, we demonstrate a new nexus between paracrine and autocrine effects of IGF-I and IL-8. IL-8 was transcriptionally induced by IGF-I in melanoma cells. IGF-I-induced migration of melanoma cells could be inhibited by neutralizing antibody against IL-8, suggesting that some of the biological functions of IGF-I are mediated by IL-8.
Results
TOP
Abstract
Introduction
Results
Discussion
Materials and Methods
References
IGF-I is critical for survival, growth, and motility of melanocytic cells (5 , 10) , and its multiple roles in melanoma progression might be mediated by a number of downstream pathways and effectors. In a modified Boyden chamber assay, SBcl2 melanoma cells were allowed to migrate through 8-µm pores of polycarbonate filters after treatment with IGF-I and compared with control cells. IGF-I was able to induce 3-fold increase in the migration (Fig. 1A) . This migratory effect was inhibited by >90% by neutralizing antibodies to either IGF-I or IL-8 (Fig. 1A) , suggesting that the pro-migratory effect of IGF-I is mediated by secreted IL-8. The specificity of the blocking experiments was checked by including a nonspecific antibody, which showed no effect on IGF-I-stimulated migration. In support of this observation, we evaluated the expression of IL-8 receptors, IL-8RA and IL-8RB, by Western blotting. All melanoma cells examined expressed both receptors in comparable amounts (Fig. 1B) , suggesting a role of IL-8 as an autocrine factor.
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Fig. 1. IGF-I-induced cell migration is mediated by IL-8. In A, SBcl2 cells with or without IGF-I treatment were tested for migration using NeuroProbe chamber as described in "Materials and Methods." Neutralizing antibodies against IGF-I (10 µg/ml) or IL-8 (20 µg/ml) was included to determine the functional contribution of individual molecules on cell migration. Nonspecific antibody was used to determine the blocking specificity. Data were gathered from five independent assays for each treatment. B, expression of IL-8 receptor in melanoma cells. Total cell extracts were revolved on 12% SDS-PAGE gel, and monoclonal antibodies against IL-8RA and IL-8RB were used to detect both receptors.
By comparing mRNA expression profile of IGF-I-treated SBcl2 cells with untreated cells using cDNA microarray analysis, we identified IL-8 as one of the genes whose mRNA levels were substantially increased (15-fold) after IGF-I treatment. Along with IL-8, VEGF expression was also increased after IGF-I treatment (data not shown), which has been shown in other cell types (25, 26, 27) . To confirm the microarray results, SBcl2 cells were treated with IGF-I either by IGF-I adenoviral transduction at 20 pfu/cell (Fig. 2) or using recombinant IGF-I added to culture media at 100 ng/ml (Fig. 3) . Our previous studies showed that under either condition, the same signaling pathways were activated, and the same biological effects were observed (10) . Increased expression of IL-8 was detected at both mRNA (Fig. 2, A and B) and protein (Fig. 2C) levels after IGF-I adenoviral transduction. The increased IL-8 expression was maintained for >96 h (Fig. 2C) because of continuous stimulation by IGF-I adenoviruses. mRNA induction was also observed in recombinant IGF-I-treated (100 ng/ml) SBcl2 cells (Fig. 3A) . A concentration of IGF-I as low as 10 ng/ml induced 2-fold increase in IL-8 production after 24 h, whereas 100 ng/ml IGF-I induced 8-fold increase over endogenous level (Fig. 3B) . However, 500 ng/ml IGF-I did not substantially induce more IL-8 than 100 ng/ml, possibly because of saturation effect.
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Fig. 2. Induction of IL-8 by IGF-I adenoviral transduction in melanoma. In A, SBcl2 melanoma cells were transduced with IGF-I or LacZ adenoviruses at 20 pfu/cell. Total RNA was isolated at 0, 12, 24, 48, and 72 h after gene transduction. Total RNA (10 µg/lane) was separated on a formaldehyde-agarose gel, transferred to nylon membrane, and probed with radiolabeled IL-8 and GAPDH cDNA. In B, the data in A were quantitated using a densitometer and are reported in arbitrary units relative to IL-8 mRNA expression at time 0. Densities were corrected for loading differences by normalizing for variances in GAPDH expression. In C, time course of IL-8 secretion was tested by ELISA. SBcl2 melanoma cells with different treatments were cultured in PF media for indicated times. The supernatants in triplicates were collected, and IL-8 released into the medium was measured by ELISA. Control, no treatment; IGF-I, IGF-I/Ad5 at 20 pfu/cell; LacZ, LacZ/Ad5 at 20 pfu/cell.
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Fig. 3. Induction of IL-8 by recombinant IGF-I in melanoma. In A, SBcl2 melanoma cells were treated with recombinant IGF-I (100 ng/ml) or vehicle. Total RNA was isolated at 0, 4, and 24 h. Total RNA (10 µg/lane) was separated on a formaldehyde-agarose gel, transferred to nylon membrane, and probed with radiolabeled IL-8. GAPDH and 28S rRNA were used as loading control. In B, concentration dependence of IL-8 induction. SBcl2 cells were incubated with various concentrations of IGF-I for 24 h. IL-8 secretion in triplicates was quantitated by ELISA.
To exclude the possibility that IL-8 induction by IGF-I is restricted to SBcl2 cells, conditioned media (24 h) from seven melanoma cell lines treated with IGF-I (100 ng/ml) were measured by ELISA (Fig. 4) . The cell lines used included primary RGP/VGP melanoma (SBcl2, WM1552C, and WM35) and metastatic melanoma (WM852, WM1158, WM9, and 1205Lu). Endogenously secreted IL-8 levels ranged from 1 to 35 ng/105cells/24 h, and there was no clear correlation between levels of IL-8 secretion and progression stages (Fig. 4 , dotted bars). RGP melanoma cells (SBcl2, WM1552C, and WM35) responded to IGF-I treatment and induced the secretion of IL-8 levels 2–4-fold after 24 h (Fig. 4 , shaded bars). On the contrary, VGP and metastatic melanoma cells did not respond to IGF-I treatment with the exception of WM9.
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Fig. 4. IL-8 induction by IGF-I in melanoma cell lines. Melanoma cells were treated with IGF-I (100 ng/ml) or vehicle (Control). IL-8 levels were measured in triplicates after 24 h by ELISA.
It has been shown that IGF-I exert its effects through both MAP kinase and phosphatidylinositol 3'-kinase pathways (28) . To test which of the two pathways is involved in IL-8 induction, specific inhibitors were included in the assays. As shown in Fig. 5 , in SBcl2 cells, the induction of IL-8 secretion can be completely inhibited by MAP kinase inhibitor PD98059 but not by phosphatidylinositol 3'-kinase inhibitor Wortmannin. Similar effects were observed in WM35 RGP primary melanoma cell line (data not shown). Noticeably, PD98059 inhibited basal level of IL-8, suggesting that besides IGF-I, another MAP kinase-dependent process is responsible for basal expression of IL-8. To determine whether IL-8 induction is a specific effect of IGF-I, we also tested the ability of basic fibroblast growth factor and PDGF to induce IL-8. Neither of them could increase IL-8 production (data not shown).
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Fig. 5. Effect of Wortmannin and PD98059 on IGF-I-induced IL-8 expression. SBcl2 cells were transduced with IGF-I (20 pfu/cell) or LacZ (20 pfu/cell) and treated with indicated drugs (Wortmannin, 40 µM; PD98059, 10 µM) for 24 h, and IL-8 levels were measured by ELISA and expressed in percentages of IL-8 secretion by cells without adenoviral treatment.
The mechanisms by which IGF-I increased IL-8 expression were then defined. To examine whether IGF-I affected the stability of IL-8 mRNA, SBcl2 cells were exposed to 100 ng/ml IGF-I or vehicle for 16 h before addition of 5 µg/ml actinomycin D. Total RNA was extracted from the cells at various times and subject to Northern blotting. As shown in Fig. 6A , the half-life of IL-8 mRNA was not significantly different in IGF-I treated cells from the control, suggesting that increased IL-8 production is not because of increased IL-8 mRNA stability. Nuclear run-on assay was then used to determine whether IGF-I increased the rate of transcription for IL-8 mRNA (Fig. 6B) . IGF-I induced IL-8 mRNA transcription rate by 4-fold within 4 h. Thereafter, the rate remained significantly above the control levels. Similar observations were also made in WM35 cells (data not shown). These data suggest that induction of IL-8 by IGF-I is transcriptionally controlled.
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Fig. 6. Induction of IL-8 mRNA by IGF-I is dependent on increased transcription. In A, IGF-I treatment does not change stability of IL-8 mRNA. SBcl2 cells were exposed to 100 ng/ml IGF-I or vehicle (Control) for 16 h before the addition of 5 µg/ml actinomycin D. Total RNA was extracted from the cells at the indicated times after actinomycin D administration, fractionated by agarose gel electrophoresis, and transferred to a nylon membrane. The Northern blot was then hybridized to cDNA probes for IL-8 and GAPDH (loading control). The corrected densities are expressed as percentages of the value at time 0 and plotted on a logarithmic scale. One representative of three replicates is shown. B, nuclear run-on assay. After a 24-h serum starvation, SBcl2 cells were treated with or without IGF-I (100 ng/ml). Cells were harvested at different time points. Nuclei were purified from the cells, and nuclear run-on assays were carried out as described in "Materials and Methods." The resulting autoradiographs were quantitated using a densitometer and represented as arbitrary units.
Because it has been shown that IL-8 expression is mediated by differential activation and binding of inducible transcription factors, such as AP-1 and NF-B, to the promoter of the IL-8 gene (29) , the involvement of AP-1 and NF-B in IGF-I-mediated IL-8 induction was tested by EMSA. As shown in Fig. 7A , AP-1 binding was considerably increased in IGF-I-treated SBcl2 cells compared with control. On the other hand, 1205Lu cells constitutively showed high binding capacity to AP-1, which correlated with high levels of endogenous IL-8 production, and did not show significant changes between the groups in binding to the AP-1 element. Previous studies have shown that AP-1-induced transcription is dependent on phosphorylation of serine residues in the transactivation domain of c-Jun (30) . Interestingly, 1205Lu cells showed constitutive phosphorylation of c-Jun proteins regardless of IGF-I treatment, whereas in SBcl2 cells, IGF-I induced phosphorylation of c-Jun (Fig. 7B) . These data suggest that induction of AP-1 DNA-binding activity is mediated by the phosphorylation of c-Jun in SBcl2 cells. In contrast to AP-1, no difference in the binding pattern of NF-B was observed in either SBcl2 (Fig. 7C) or 1205Lu cells (data not shown) after IGF-I treatment.
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Fig. 7. EMSA analyses of AP-1 and NF-B binding to IL-8 promoter elements. In A, nuclear proteins from SBcl2 and 1205Lu melanoma cells were extracted from control or IGF-I-treated (100 ng/ml, 30 min) cells. Radiolabeled AP-1 binding element was incubated with the nuclear extracts, separated on a 5% nondenaturing polyacrylamide gel, and analyzed by autoradiography. Unlabeled wild-type AP-1-binding element (wtAP-1) was used to confirm the specificity of the protein-DNA binding. B, c-Jun phosphorylation after IGF-I treatment. SBcl2 and 1205Lu cells were serum starved for 24 h and treated with IGF-I (100 ng/ml) for 30 min, and equal amounts of protein extracts were separated on 10% SDS-polyacrylamide gel. Western blotting was performed using phosphorylation-specific c-Jun antibody and total c-Jun antibody. ß-Actin was probed as loading control. In C, nuclear extracts were analyzed by EMSA for NF-B-binding activity after IGF-I treatment. SBcl2 and 1205Lu showed the same pattern of mobility shift; therefore, only SBcl2 is shown. NS, nonspecific binding.
Discussion
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Abstract
Introduction
Results
Discussion
Materials and Methods
References
Oncogenic transformation appears as the result of multiple mechanisms by which growth, differentiation, and apoptosis pathways are perturbed and deregulated. Sequential activation of growth factors is crucial for melanoma growth and invasion and may provide growth advantage by interacting with the microenvironment. In this study, we describe a role for IGF-I in the regulation of IL-8 in human melanoma cells. We show that: (a) IGF-I induces IL-8 expression in various melanoma cells, especially in early stage melanomas; (b) the induction is because of increased transcription rate, not enhanced stability; (c) IGF-I functions through MAP kinase/c-Jun-NH2-terminal kinase/c-Jun/AP-1 pathway; and (d) IL-8 is one of the major downstream effectors that are responsible for pro-migratory effects of IGF-I in melanoma cells.
IGF-I and IL-8 are both critical proteins in melanoma progression. Whereas IGF-I imparts its mitogenic, motogenic, and antiapoptotic effects through paracrine actions, IL-8 functions through autocrine mechanisms. We have observed that although melanoma cells do not secrete IGF-I, they possess functional IGF-IR, which can be triggered to subsequently activate extracellular signal-regulated kinase 1 and 2 and Akt/protein kinase B via phosphorylation (10) . The precise effects of IL-8 on tumor progression are only beginning to be understood. Melanoma cells express IL-8 receptors IL-8RA and IL-8RB, both of which are G-protein linked seven-transmembrane molecules. Melanoma cells, but not normal melanocytes, synthesize IL-8 (16 , 31) , which can be further stimulated by IGF-I. The convergence of signaling pathways of IL-8 and IGF-I may provide integrated cellular responses, such as proliferation, survival, and tumor angiogenesis. In fact, it has been shown that IGF-I and IL-8 have parallel mitogenic (5 , 19) , motogenic (9 , 20 , 22 , 32) , angiogenic (25 , 33) , and pro-proteolytic (22 , 34) functions in various cancers, including melanoma.
On the basis of the facts that IGF-I increases expression of IL-8 and that IGF-I and IL-8 have extensive parallel functions, we proposed that IL-8 is the downstream effector of IGF-I and is, in part, responsible for the biological actions of IGF-I. In this study, we provide evidence that antibody blockage of IL-8 signaling could abolish IGF-I-induced cell migration, suggesting that the motility effect of IGF-I on melanoma is mediated by subsequent events of IL-8 induction and autocrine stimulation. Thus, the present investigation adds a new and important activity to the IGF-I repertoire.
Angiogenesis has been shown to be a significant prognostic factor (24 , 35, 36, 37) and a major requirement for tumor outgrowth and metastasis in melanoma (15 , 38, 39, 40) . Whether angiogenic effect of IGF-I is mediated by IL-8 induction remains unknown. However, the facts that both IGF-I and IL-8 are angiogenic (15 , 23 , 25 , 33 , 41) and that IGF-I increases expression of IL-8 point to this possibility. Alternatively, the angiogenic activity of IGF-I could also be mediated by induction of VEGF (25, 26, 27) or by induction of both IL-8 and VEGF, as detected by our microarray profiling. The involvement of multiple angiogenic factors has been a major obstacle in antiangiogenic treatment of malignant melanoma, and efficient treatment may require identification and blockage of common functional features or common signaling cascades of multiple angiogenic factors. Our study suggests that IGF-I might be a master regulator of migration and angiogenesis in melanoma and justifies targeting IGF-I signaling pathway as a potential therapeutic approach to reverse melanocytic malignancy.
Materials and Methods
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Abstract
Introduction
Results
Discussion
Materials and Methods
References
Reagents.
MCDB153, L15, and insulin were purchased from Sigma Chemical Co. (St. Louis, MO). FBS was from Hyclone (Logan, UT). Recombinant IGF-I, anti-IGF-I, and anti-IGF-IR antibodies, PD98059, and Wortmannin were obtained from Calbiochem (San Diego, CA). IL-8 antibody was from R&D Systems, Inc. (Minneapolis, MN). IL-8RA and IL-8RB antibodies were purchased from Santa Cruz Biotechnology (Santa Cruz, CA). Antiphospho-c-Jun (Ser 63) antibody was from New England Biolabs (Beverly, MA).
Cell Culture.
The following melanoma cell lines were used, which have been described before (42) : WM1552C, SBcl2, WM115, WM1341D, 1205Lu, WM852, WM9, and WM1158. Melanoma cells were maintained in "2% Tumor" medium composed of MCDB153:L15 (4:1) supplemented with 2% FBS and 5 µg/ml insulin, unless otherwise stated. When a specific growth factor was tested, FBS and insulin were omitted from the medium ("PF medium").
Adenoviruses.
The generation of IGF-I adenovirus has been described (10) . Control adenoviral vector containing the LacZ cDNA (LacZ/Ad5) was provided by the Vector Core at the Institute for Human Gene Therapy, University of Pennsylvania (Philadelphia, PA). Adenoviruses were purified by CsCl density centrifugation and tittered on 293 cells using agar overlay technique (43) .
ELISA.
IL-8 protein in the culture supernatants was measured with an ELISA kit (Biosource International, Camarillo, CA), according to manufacturer’s protocol. All experiments were repeated three times.
Northern Blotting.
Total RNA was isolated using Tri Reagent (MRC, Inc., Cincinnati, OH), separated on 1.2% formaldehyde-agarose gel and transferred on to nylon membranes (MSI, Westboro, MA). Radioactive probes were prepared using High Prime DNA labeling Kit (Roche Diagnostics, Indianapolis, IN) and hybridized overnight to the membranes at 65°C. The membranes were visualized by autoradiography and quantitated using NIH Image software.
Nuclear Run-on Assay.
Melanoma cells were grown to 90% confluence in 60-mm dishes. After 24-h starvation in PF medium, cells were treated with IGF-I (100 ng/ml) or left untreated. Cells were harvested at different times, and nuclei were purified from these cells using run-on lysis buffer [10 mM Tris-HCl (pH 7.4), 10 mM NaCl, 3 mM MgCl2, and 0.5% NP40 in DEPC-H2O]. The purity of the nuclei was examined by microscopy. The nuclei were resuspended in 200 µl of storage buffer [50 mM Tris-HCl (pH 8.3), 40% glycerol, 5 mM MgCl2, and 0.1 mM EDTA in DEPC- H2O] and kept at -70°C until use. For each reaction, 100 µl of thawed nuclei were mixed with 30 µl of 5 x run-on buffer [25 mM Tris-HCl (pH 8.0), 12.5 mM MgCl2, 750 mM KCl, and 1.25 mM each of ATP, GTP, and CTP], supplemented with 100 µCi of -32P-UTP and 0.06% Sarkosyl, to a final volume of 150 µl. The reaction mixtures were incubated for 30 min at 30°C, followed by the addition of 15U DNase I and incubation for another 15 min. TRIzol was used to extract total RNA from the reaction mixtures. The extracted probes were then hybridized to nylon membrane slot-blotted with IL-8 cDNA (0.5 µg/dot). After hybridization, the signals were captured by X-ray films and quantified using NIH Image software.
mRNA Stability.
Melanoma cells were grown to 90% confluence in 60-mm dishes. After a 16-h incubation in PF medium with or without recombinant IGF-I (100 ng/ml), actinomycin D (5 µg/ml) was added to block transcription. Cells were then harvested 0, 1, 2, 4, 6, and 8 h after the addition of actinomycin D, and Northern blotting was performed for IL-8 mRNA expression. To correct for differences in loading, GAPDH probe was hybridized to the same blot. The corrected densities were calculated as percentages of the value at time 0 and plotted on a logarithmic scale.
Western Blotting.
Cell lysates were prepared using radioimmunoprecipitation assay buffer. Protein estimation was performed using bicinchoninic acid protein assay reagent (Pierce, Rockford, IL). Equal amounts of proteins were loaded onto 10% SDS-polyacrylamide gel, transferred to polyvinylidene difluoride membranes (MSI), and probed with primary and secondary antibodies. Signals were developed by enhanced chemiluminescence kit (Amersham, Farmington, IL).
EMSA.
Cells were starved in PF medium for 24 h and treated with 100 ng/ml IGF-I for 30 min. Nuclear and cytoplasmic fractions were isolated by hypotonic solution followed by nuclear protein extraction (44) . Oligonucleotides derived from IL-8 promoter used in this study are AP-1 (wild type) 5'-AGT GTG ATG ACT CAG GTT TG-3'; AP-1 (mutant) 5'-AGT GTG TAT CTC AGG TTT G- 3'; NF-B (wild type) 5'-ATC GTG GAA TTT CCT CTG ACA-3'; and NF-B (mutant) 5'-ATC GTT AAC TTT CCT CTG ACA-3'. Oligonucleotides were end labeled with -32P-ATP. The reaction mixture consisted of 10 mM HEPES (pH 7.6), KCl (60 mM), 1 mM DTT, protease inhibitors (1 µg/ml leupeptin, pepstatin, and aprotinin and 10 µM phenylmethylsulfonyl fluoride), and 1 µg of poly (dI-dC). The reaction mixture was incubated at room temperature for 20 min with radiolabeled oligonucleotides. The preincubation with the antibodies for supershift analysis was performed using anti-p65 and anti-p50 antibodies obtained from Santa Cruz Biotechnology. After the incubation, the reaction mixtures were separated in 0.5XTBE in a 5% nondenaturing polyacrylamide gel, dried, and exposed for autoradiography. Specificity of the complexes was examined using 40-fold higher concentrations of cold wild-type, as well as mutated, oligonucleotides.
Migration Assay.
Chamber assembly (48 wells; AC48) from NeuroProbe, Inc. (Gaithersburg, MD) was used for migration analysis. Fifty µl (106cells/ml) was placed in the upper chamber and 30 µl of PF medium containing 0.1% BSA (control), or PF medium containing recombinant IGF-I (200 ng/ml) in the lower chamber, separated by an 8-µm polycarbonate filter paper. Antibodies were included in the upper chamber where mentioned. The chamber assembly was kept in 37°C for 4 h. The filter was then removed, fixed, and stained using Diff-Quick (Baxter, Miami, FL) and mounted on slide. Numbers of cells were counted in five fields at x40 magnification.
Footnotes
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
1 Supported in part by NIH Grants CA25874, CA47159, CA76674, and CA10815.
2 K. S. and G. L. contributed equally to this study.
3 Current address: Center for Molecular and Cellular Biology, MAHE, Manipal, India.
4 To whom requests for reprints should be addressed, at The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104. Phone: (215) 898-3950; Fax: (215) 898-0980; E-mail: herlynm@wistar.upenn.edu.
5 The abbreviations used are: RGP, radial growth phase; EMSA, electromobility shift assay; IGF, insulin-like growth factor; IL, interleukin; MAP, mitogen-activated protein; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; FBS, fetal bovine serum; VEGF, vascular endothelial growth factor; VGP, vertical growth phase; PDGF, platelet-derived growth factor; pfu, plaque-forming unit(s); PF, protein-free; IGF-IR, IGF-I receptor.
Received for publication 10/ 8/01. Revision received 11/26/01. Accepted for publication 12/ 7/01.
References
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Abstract
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Discussion
Materials and Methods
References
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Here's Dr. Bhavesh Vaidya a big player also working with Dr. Sturm - {look at the Universitys involved always the same one's} - http://cancerres.aacrjournals.org/cgi/content/abstract/61/19/7318
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Tumor Biology
Insulin-like Growth Factor-1 Induces Survival and Growth of Biologically Early Melanoma Cells through Both the Mitogen-activated Protein Kinase and ß-Catenin Pathways1
Kapaettu Satyamoorthy, Gang Li, Bhavesh Vaidya, Dipa Patel and Meenhard Herlyn2
The Wistar Institute [K. S., G. L., B. V., D. P., M. H.], and Program of Cell and Molecular Biology, Biomedical Graduate Studies, University of Pennsylvania School of Medicine [G. L.], Philadelphia, Pennsylvania 19104
Melanoma cells produce growth factors for autocrine growth control and for stimulating fibroblasts and endothelial cells in the tumor stroma. Activated stromal fibroblasts can in turn secrete growth factors that support tumor growth. We studied this feedback from fibroblasts to melanoma cells by overexpressing insulin-like growth factor 1 (IGF-1) with an adenoviral vector. Melanoma cells do not produce IGF-1. IGF-1 enhanced survival, migration, and growth of cells from biologically early lesions, but not from biologically late primary or metastatic lesions. Early melanoma cells were activated by IGF-1 to phosphorylate Erk1 and -2 of the mitogen-activated protein kinase pathway. IGF-1 also activated Akt, inhibited its down-stream effector GSK3-ß, and stabilized ß-catenin. Late primary and metastatic melanoma cells did not respond to growth stimulation by IGF-1 because of a constitutive activation of the mitogen-activated protein kinase pathway and a higher level of stabilized ß-catenin. These studies demonstrate that fibroblast-derived growth factors from the tumor environment can provide the malignant cells with a positive feedback through multiple mechanisms but that this stimulation is required only for cells from early and not late stages of tumor progression.
YOU THINK Tony IS NOT HANGING AROUND THE RIGHT PEOPLE ! Here's another Big Player who is working with Dr.Sturm - Dr. Peter G. Parsons - http://www.molbiolcell.org/cgi/content/abstract/11/6/2069
Vol. 11, Issue 6, 2069-2083, June 2000
Histone Deacetylase Inhibitors Trigger a G2 Checkpoint in Normal Cells That Is Defective in Tumor Cells
Ling Qiu,* Andrew Burgess,* David P. Fairlie, Helen Leonard,* Peter G. Parsons,* and Brian G. Gabrielli*§
*Queensland Cancer Fund Laboratories, Queensland Institute of Medical Research, and Joint Experimental Oncology Program, Department of Pathology, University of Queensland, Brisbane, Queensland, Australia; and Centre for Drug Design and Development, University of Queensland, St. Lucia, Queensland, Australia
Important aspects of cell cycle regulation are the checkpoints, which respond to a variety of cellular stresses to inhibit cell cycle progression and act as protective mechanisms to ensure genomic integrity. An increasing number of tumor suppressors are being demonstrated to have roles in checkpoint mechanisms, implying that checkpoint dysfunction is likely to be a common feature of cancers. Here we report that histone deacetylase inhibitors, in particular azelaic bishydroxamic acid, triggers a G2 phase cell cycle checkpoint response in normal human cells, and this checkpoint is defective in a range of tumor cell lines. Loss of this G2 checkpoint results in the tumor cells undergoing an aberrant mitosis resulting in fractured multinuclei and micronuclei and eventually cell death. This histone deacetylase inhibitor-sensitive checkpoint appears to be distinct from G2/M checkpoints activated by genotoxins and microtubule poisons and may be the human homologue of a yeast G2 checkpoint, which responds to aberrant histone acetylation states. Azelaic bishydroxamic acid may represent a new class of anticancer drugs with selective toxicity based on its ability to target a dysfunctional checkpoint mechanism in tumor cells.
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These authors contributed equally to this work.
§ Corresponding author: Department of Pathology, University of Queensland Medical School, Herston, Queensland 4006, Australia. E-mail address: briang@mailbox.uq.edu.au.
Here's another BIG BOY working with Dr. Sturm - Dr. Con Panousis - http://www.cancerresearch.org/immune99/christoph_renner.html
Christoph Renner, Con Panousis, Andrew Scott
Ludwig Institute for Cancer Research, Austin Hospital
Heidelberg, Australia
Frank Hartmann, Michael Pfreundschuh
Saarland University Medical School Homburg, Germany
Antibody Mediated Recruitment of Cytotoxic Effector Cells for Tumor Therapy
Among many immunotherapeutical approaches for the treatment of malignant diseases, monoclonal antibodies (Mab) were one of the first ones to confirm their efficacy in clinical trials. The success of treating colorectal cancers in an adjuvant setting or relapsed low-grade lymphoma with antibodies demonstrates the clinical potential of therapeutic strategies that redirect humoral and cellular effector functions to tumor cells. The major handicap of native monoclonal antibodies is their variable and usually low cytotoxic potential. Bispecific antibodies (Bi-mAbs) may overcome this limitation as they can be designed to recruit human effector cells to tumour cells and induce their lysis, respectively. Over the last three years, we performed two subsequent phase I/II clinical trials with an NK-cell activating (anti-CD16/anti-CD30) bispecific antibody in patients with relapsed Hodgkin’s disease. A total of 31 patients were included in both trials. Treatment was well tolerated and resulted in an overall response rate of 30% with some responses lasting up to 18 month. Infusion regimens aiming for constant antibody levels over a four day period seemed to be favorable as patients could be treated for multiple cycles without developing significant allergic reactions or human-anti-mouse antibodies (HAMA). An increase in NK-cell activity could be demonstrated in almost 40% of all patients under treatment. However, this increase in NK-cell activity was short-lived indicating that no long-term activation of cytotoxic effector cells was achieved. Therefore, we established a second set of bispecific antibodies redirecting and activating human T-lymphocytes towards tumour cells. T-cells activated by bispecific antibodies have the advantage that they can destroy tumour cells in a MHC unrestricted fashion, thus creating a large pool of potential killer cells.
In SCID mice, the in-vivo administration of both anti-CD3/anti-CD30 and antiCD28/anti-CD30 Bi-mAbs resulted in the specific activation of xenotransplanted, resting human T-cells infiltrating the CD30-positive Hodgkin‘s tumour. Bi-mAb treatment initiated the enhanced expression of cytokines such as interleukin-1b, interleukin-2, tumor necrosis factor type a and activation markers including Ki-67, CD25 and CD45RO in tumor infiltrating lymphocytes. This antigen-dependent, local T-cell stimulation led to the activation of the cytolytic machinery in T-lymphocytes, determined by the upregulation of m-RNA encoding perforin and the cytotoxic serine-esterases granzyme A and B. Bi-mAb induced generation of cytotoxic T-lymphocytes depended on the presence of the CD30-antigen and the combined application of both Bi-mAbs. Our findings suggest that the combined application of T-cell-activating Bi-mAbs is able to achieve a tumor site specific activation of the T-cell cytolytic machinery in vivo. The fact that these cytotoxic cells do not home in tumour-antigen-negative tissue and do not enter circulation might explain our previous observation of a high cure rate of xenotransplanted Hodgkin’s tumours in SCID mice. In addition, work from other groups could prove that the broad and MHC unrestricted activation of T-cells by bispecific antibodies resulted finally in the induction and expansion of tumour specific T-cell clones. Therefore, T-cell targeting bispecific antibodies might have a dual function: firstly, to activate a large pool of resting T-cells randomly within in days and secondly, to initiate the induction and expansion of a tumour specific T-cell clone with long term activity
More of Dr. Cutts - what Israel is involved -
http://cancerres.aacrjournals.org/cgi/content/full/61/22/8194
Molecular Basis for the Synergistic Interaction of Adriamycin with the Formaldehyde-releasing Prodrug Pivaloyloxymethyl Butyrate (AN-9)1
Suzanne M. Cutts, Ada Rephaeli, Abraham Nudelman, Inesa Hmelnitsky and Don R. Phillips2
Department of Biochemistry, La Trobe University, Victoria 3086, Australia [S. M. C., D. R. P.]; Felsenstein Medical Research Center, Sackler School of Medicine, Tel Aviv University, Beilinson Campus, Petach Tikva 49100, Israel [A. R.]; and Chemistry Department, Bar Ilan University, Ramat Gan 52900, Israel [A. N., I. H.]
ABSTRACT
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INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
The interaction of Adriamycin and pivaloyloxymethyl butyrate (AN-9) was investigated in IMR-32 neuroblastoma and MCF-7 breast adenocarcinoma cells. Adriamycin is a widely used anticancer drug, whereas AN-9 is an anticancer agent presently undergoing Phase II clinical trials. The anticancer activity of AN-9 has been attributed to its ability to act as a butyric acid prodrug, although it also releases formaldehyde and pivalic acid. Adriamycin and AN-9 in combination display synergy when exposed simultaneously to cells or when AN-9 treatment is up to 18 h after Adriamycin administration. However, the reverse order of addition results in antagonism. These interactions have been established using cell viability assays and classical isobologram analysis. To understand the molecular basis of this synergy, the relative levels of Adriamycin-DNA adducts were determined using various treatment combinations. Levels of Adriamycin-DNA adducts were enhanced when treatment combinations known to be synergistic were used and were diminished using those treatments known to be antagonistic. The relative timing of the addition of Adriamycin and AN-9 was critical, with a 20-fold enhancement of Adriamycin-DNA adducts occurring when AN-9 was administered 2 h after the exposure of cells to Adriamycin. The enhanced levels of these adducts and the accompanying decreased cell viability were directly related to the esterase-dependent release of formaldehyde from AN-9, providing evidence for the formaldehyde-mediated activation of Adriamycin.
INTRODUCTION
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ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
Adriamycin is a widely used drug in current chemotherapy regimes because it is effective against a broad range of neoplasms. It is used as a single agent but is more commonly used in combinations with other anticancer agents. The selection of these additional agents is not usually based on known synergistic interactions between the drugs but rather on complimenting mechanisms of action. The major drawbacks associated with the use of Adriamycin are its dose-dependent cardiotoxicity and the emergence of tumor resistance to the drug (1) .
Although Adriamycin is a known topoisomerase II inhibitor, this mechanism of action does not fully explain its broad-spectrum anticancer activity (1 , 2) . In recent years, it has been shown that Adriamycin induces adducts with DNA, and these occur predominantly at 5'-GC sequences (3 , 4) . Chemical characterization of this structure has revealed that the 3' aminosugar of Adriamycin is covalently bound to the N2 of guanine via a formaldehyde-derived bridge (5 , 6) . Two-dimensional NMR3 analysis of the structure showed that adducts at GC sequences are also virtual cross-links, because the Adriamycin monoadduct is stabilized by the complementary strand of DNA by intercalation and H-bonding (7) . This structure of the virtual cross-link explains why the apparent Adriamycin cross-links are unstable. DNA cross-link formation by various anthracycline derivatives (including Adriamycin) has been correlated with cytotoxicity in HeLa cells (8) , and more recently in MCF-7 cells, at sufficiently high levels to account for the cytotoxic response (9) .
A new drug, doxoform, has been designed recently to take advantage of the fact that Adriamycin can be activated by formaldehyde (10) . This complex of Adriamycin with formaldehyde is dramatically (200-fold) more cytotoxic than Adriamycin, and this appears to be attributable to enhanced formation of DNA adducts.
BA is an agent that induces differentiation primarily because of its ability to function as a histone deacetylase inhibitor (11) . In human tumor cells in vitro, it displays growth arrest, decreased clonogenicity, and induction of morphological and biochemical changes resulting in antitumor activity (12 , 13) . However, BA is not clinically effective because of rapid metabolism and, to a lesser extent, excretion (14) . To achieve a reduction in the clearance rate of BA, a panel of BA-releasing prodrugs were synthesized and screened for antitumor activity (15 , 16) . AN-9 is the best studied prodrug, and it affects cancer cells at 10-fold lower concentrations and at least 100-fold faster than BA. Moreover, it penetrates 100-fold faster than BA into cancer cells in vitro (17) . Derivatization of BA improves its permeability across cell membranes and enables efficient intracellular delivery of BA.
AN-9 belongs to a well-established family of acyloxyalkyl ester prodrugs of carboxylic acids (18, 19, 20) whose expected esterase-dependent intracellular hydrolytic degradation products are BA, pivalic acid, and formaldehyde (Fig. 1) . Whereas pivalic acid does not contribute to the activity elicited by the prodrug, the role of the released formaldehyde remains unclear, and it also cannot be excluded that the intact AN-9 has some intrinsic activity. The pivaloyloxymethyl derivatives of propionic, valeric, and pivalic acids (analogues of AN-9 that lack a BA fragment) were found to have significantly lower antitumor activity in cancer cells (16) . This suggests that the biological activity of AN-9 stems mostly from the released BA moiety. AN-9 was shown to inhibit the proliferation of a variety of cancer cell lines and primary human tumors (15 , 16 , 21) . AN-9 displayed low toxicity in mice and was effective in prolonging survival of mice bearing melanoma, lung carcinoma, and monocytic leukemia (15 , 16 , 22) . It induced transient hyperacetylation of histones (23) , leading to relaxation of the chromatin structure, which allowed access of transcription factors to the DNA (24) . This activity is likely to be an important mechanism by which AN-9 exerts its effect on gene modulation. AN-9 modulates the expression of the early regulatory genes c-myc and c-jun and the tumor suppressor gene RB as well as the antiapoptotic gene bcl-2 in WEHI and HL-60 cells (20 , 25, 26, 27) . AN-9 induces differentiation and/or apoptosis depending on the concentrations and timing of the drug used (27) . AN-9 formulated in lipid emulsion (PIVANEX), displayed low toxicity in a Phase I clinical study and was reported to have an estimated maximum tolerated dose of 2.7 g/m2/day (28) . It is presently in Phase II clinical trials with non-small cell lung carcinoma and hepatoma patients.
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Fig. 1. Synthesis and hydrolysis of AN-9.
Synergistic effects between AN-9 and DNA-disrupting agents have been observed in murine monocytic leukemia cells. Furthermore, it has been shown that combination of the BA/formaldehyde-releasing prodrug AN-9 with daunorubicin led to a significant increase in survival of mice inoculated with acute monocytic leukemia cells (22) . However, the molecular interactions responsible for this marked effect were unknown. We show here that AN-9 dramatically increases the level of Adriamycin-DNA adducts in IMR-32 and MCF-7 cells and that this effect is largely attributable to the release of formaldehyde. The formaldehyde is subsequently involved in the chemical activation of Adriamycin, resulting in the formation of Adriamycin-DNA adducts. The ultimate outcome of this work is improved understanding of the factors that govern the anticancer activity of Adriamycin. Exploitation of this knowledge to improve the use of Adriamycin as an anticancer agent is discussed.
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MATERIALS AND METHODS
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DISCUSSION
REFERENCES
Radiochemicals and Molecular Biology Reagents.
[14-14C]Adriamycin hydrochloride (57 mCi/mmol) and the radionucleotides [-32P]dCTP and [-32P]UTP (2500 Ci/mmol) were obtained from Amersham Pharmacia Biotech UK Ltd., Buckinghamshire, United Kingdom. QIAamp blood kits for genomic DNA isolation were purchased from Qiagen, and restriction enzymes and random primed labeling kits were from Roche Molecular Biochemicals.
Cell Lines.
IMR-32 neuroblastoma cells were kindly supplied by S. Bordow, M. Haber, and C. M. Ireland (Children’s Cancer Research Institute, Sydney Children’s Hospital, New South Wales, Australia). IMR-32 cells and MCF-7 breast adenocarcinoma cells were maintained in DMEM (Trace Scientific) and 10% fetal bovine serum (Life Technologies, Inc.), supplemented with 0.1 mg/ml streptomycin and 100 units/ml penicillin.
Compounds.
Adriamycin was a gift from Farmitalia Carlo Erba (Milan, Italy), and barminomycin was provided by Dr. Ken-ichi Kimura (Research Institute of Life Science, Snow Brand Milk Products Co. Ltd., Tochigi, Japan). Semicarbazide was purchased from Sigma Chemical Co. Aldrich. AN-9, isobutyroyloxymethyl pivalate (AN-37), and valeroyloxymethyl pivalate (AN-38) were synthesized as described previously (15 , 16) . AN-158 was prepared as described for AN-9 from 1-chloroethylbutyrate and pivalic acid. 1H NMR (CDCl3, ): 0.92 (t, J = 7.5 Hz, 3H, MeCH2), 1.16 (s, 9H, t-Bu), 1.45 (d, J = 5.5 Hz, 3H, MeCH), 1.67 (sextet, J = 7.5 Hz, 2H, MeCH2), 2.3 (t, J= 7.5 Hz, 2H, CH2CO), 6.86 (q, J = 5.5 Hz, 1H, OCH2O). Ethylidene dipropionate (AN-188) was prepared from acetaldehyde and propionic anhydrate as described previously. 1H NMR (CDCl3, ): 6.86 (q, 1H, CH, J = 5 Hz), 2.32 (q, 4H, CH2Me x 2, J = 7.54 Hz), 1.43 (d, 3H, CHMe, J = 5 Hz), 1.11 (t, 6H, MeCH2 x 2, J = 7.54 Hz).
Preparation of Probes for Southern Hybridization.
The plasmid pBH31R1.8 was provided by Dr. V. A. Bohr (National Institute of Aging, NIH, Baltimore, MD). A 1.8-kb EcoRI fragment containing exons I and II of the human DHFR gene (29) was isolated from pBH31R1.8 and radiolabeled with [-32P]dCTP using a random primed labeling kit. The mitochondrial probe pCRII-H1 was a gift from Dr. C. A. Filburn (National Institute of Aging, NIH). The strand-specific human mitochondrial probe (corresponding to nucleotides 652-3226) was prepared by generating run-off transcripts from the T7 promoter in the presence of [-32P]UTP.
Drug Treatment of Cells.
Cells were seeded in 10-cm Petri dishes (Interpath) at a density of 1.5 x 106 cells/dish (IMR-32 cells) or 2.5 x 106 cells/dish (MCF-7 cells). Cells were incubated with differing concentrations of Adriamycin (dissolved in H2O) or AN-9 (dissolved in DMSO) in 10 ml of complete medium, typically for 2–6 h. The final concentration of DMSO in the medium did not exceed 0.5%. IMR-32 cells were subsequently removed from Petri dishes by gently mixing with medium and washing three times in PBS after pelleting. MCF-7 cells were washed twice in PBS, trypsinized, and then were pelleted and washed once more in PBS. Pellets were stored at -80°C until required. All experiments were performed at least in duplicate. Genomic DNA was isolated using a QIAamp blood kit with two modifications; cell lysis was conducted at 50°C for 30 min (to minimize the loss of heat-labile adducts), and an RNase A digestion step was included.
Detection of Adducts by Cross-Linking Assay.
Genomic DNA was quantitated by agarose electrophoresis and subsequent comparison to genomic DNA of known concentrations. Amounts of 2.5 µg were restriction digested with BamHI (to linearize the mitochondrial genome), whereas 7.5 µg amounts were restriction digested with HindIII for 90 min at 37°C (to produce a 22-kb genomic fragment of DHFR). The DNA was then subjected to a cleanup procedure consisting of one phenol extraction, one chloroform extraction, and subsequent ethanol precipitation using glycogen as an inert carrier of the DNA. Pellets were washed in 70% ethanol and vacuum dried at room temperature in a Speed Vac concentrator (Savant). The pellet was resuspended in 10 µl of Tris-EDTA and 20 µl of loading buffer containing 90% formamide, 10 mM EDTA, 0.1% xylene cyanol, and 0.1% bromphenol blue (final formamide concentration, 60%). Samples were denatured at 60°C for 5 min, quenched on ice, and resolved on 0.5% agarose gels in 1 x Tris-acetate EDTA by overnight electrophoresis at 30 V.
The DNA was then probed using a Southern hybridization procedure that involved transfer onto Hybond N+ nylon membranes in 0.4 M NaOH. For detection of the mitochondrial genome, membranes were hybridized overnight in 5 x Denhardt’s, 0.5% SDS, 5 x SSPE, and 100 µg/ml salmon sperm DNA. For detection of the DHFR fragment, membranes were prehybridized in 10 ml of Hybrisol I (Oncor) containing 100 µg/ml salmon sperm DNA at 52°C. Membranes were washed and then exposed to Phosphor plates for 4 h (mitochondrial probe) or overnight (DHFR), and images were captured and quantitated using a PhosphorImager (model 400B; Molecular Dynamics, Sunnyvale, CA).
Detection of 14C Adducts.
IMR-32 cells were seeded into 3.5-cm Petri dishes at a density of 7.5 x 105 cells/dish. Cells were incubated with varying concentrations of [14C]Adriamycin and AN-9. Cells were harvested, and the genomic DNA was isolated as described above. Samples were then extracted twice with phenol and once with chloroform, and DNA was selectively precipitated from RNA by ammonium acetate precipitation. DNA pellets were resuspended in 100 µl of Tris-EDTA buffer, and the concentration was determined using a Cary 118 spectrophotometer. Aliquots of the genomic DNA (50 µl) were each added to 1 ml of Optiphase Hisafe scintillation mixture, and the incorporation of 14C-labeled drug into the DNA was monitored using a Wallac 1410 Liquid Scintillation Counter.
Cytotoxicity Assays.
IMR-32 cells, 100 µl at a density of 5 x 104 cells/ml were seeded in tissue culture 96-well plates (in triplicate) for 48 h. They were exposed to different concentrations of the drugs at the specified ratio and times. The viability was measured after 48 h by neutral-red assay as described (30) . When drugs were added sequentially, the second drug was added 18 h after the first, and viability was assessed 30 h later. The mean value obtained from three wells was calculated, and IC50s were derived from linear regression of the adjusted Y (% control viability) and X values of log concentration of the compounds.
RESULTS
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ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
Synergy/Antagonism.
Initial experiments established that AN-9 and Adriamycin were more cytotoxic in combination than either agent alone. This interaction has been established previously to be synergistic (22) . The effect of treatment of IMR-32 cells with Adriamycin and AN-9 as single agents and in combination was analyzed according to the classical isobologram equation:
where Dx is the dose of one compound alone required to produce an effect, and (D)1 and (D)2 are the doses of both compounds that produce the same effect. From this analysis, the combined effects of two drugs can be assessed as either additive (or zero) interaction indicated by CI = 1, synergism as indicated by CI < 1, or antagonism indicated as CI > 1. CI values that describe the interaction between Adriamycin and AN-9 in IMR-32 cells are shown in Table 1 . It is apparent that synergy is observed where both Adriamycin and AN-9 are administered simultaneously or where AN-9 is administered 18 h after Adriamycin. The most profound synergy is obtained in the case of simultaneous drug treatment. In contrast, when AN-9 is administered 18 h prior to Adriamycin, antagonism is observed.
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Table 1 Interaction of Adriamycin and AN-9 in IMR-32 cells
Detection of Adducts.
On the basis of this synergistic interaction and the knowledge that Adriamycin induces DNA adducts, we sought to establish whether the levels of adducts in human tumor cells could account for this synergy. A concentration-dependent study was therefore initiated. A ratio of AN-9:Adriamycin of 25:1 was chosen on the basis of the IC50 data because this ratio showed good synergy (Table 1) . Exposure of both MCF-7 and IMR-32 cells to Adriamycin alone (0–10 µM) resulted in barely detectable levels of adducts (Fig. 2) , where adducts were detected as virtual interstrand DNA cross-links using a gene-specific interstrand cross-linking assay (9) . However, when in combination with AN-9, high levels of adducts were induced, and in many of the treatments, these levels were the maximum that can be detected by the gene-specific cross-linking assay (i.e., 100% cross-linked DNA). Results are presented as percentage of cross-links rather than adducts per 10 kb because the Poisson distribution used to calculate the levels of adducts is not meaningful for values approaching 100% cross-linked DNA (31) . Table 2 provides a conversion guideline that relates the percentage of cross-linked DNA (20–80%) to the approximate number of adducts per 10 kb.
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Fig. 2. Potentiation of Adriamycin-DNA adducts by AN-9. IMR-32 cells (A, C, and D) and MCF-7 cells (B, E, and F) were treated with Adriamycin alone for 4 h (0–10 µM as shown) or Adriamycin followed by an additional 2-h incubation with a 25-fold excess of AN-9 (Adriamycin/AN-9) or AN-9 for 2 h, followed by an additional 4-h incubation with Adriamycin (AN-9/Adriamycin). Genomic DNA was isolated and treated for Southern analysis as described. A and B are representative Southern blots for IMR-32 cells and MCF-7 cells, respectively, where BamHI-digested DNA has been probed for mtDNA. DS, double-strand DNA; SS, single-strand DNA. Phosphorimage analysis was used to quantitate Adriamycin adducts in the mtDNA of IMR-32 cells (C) and MCF-7 cells (E) and also in the DHFR gene of IMR-32 cells (D) and MCF-7 cells (F). Adducts formed in the Adriamycin/AN-9 incubation () are compared with the levels formed with the AN-9/Adriamycin incubation (). Data were derived from each of two separate blots of two biological experiments, and the values are the means; bars, SE.
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Table 2 Conversion table
In both the mitochondrial genome and DHFR gene of IMR-32 cells, 50% cross-linked DNA for the Adriamycin/AN-9 combination (i.e., Adriamycin added 2 h prior to AN-9) was observed at 3.5 µM Adriamycin but at 5.5 µM for the AN-9/Adriamycin combination (i.e., AN-9 added 2 h prior to Adriamycin). Similarly, in MCF-7 cells, 50% cross-linked DNA was detected in mitochondrial and nuclear genomes at 4 µM Adriamycin for the Adriamycin/AN-9 treatment but at 7 µM for the reverse sequence of addition. In both cell lines and for both DNA probes, the level of maximal cross-linking was achieved at low Adriamycin concentrations (6 µM) for the Adriamycin/AN-9 treatment; however, this did not occur, even at 10 µM for the reverse schedule. When AN-9 was used as a single compound, cross-links were not observed, even at the highest concentrations used (250 µM; see for example Fig. 4 , last lanes of A and B).
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Fig. 4. Conditions that antagonize adduct formation. IMR-32 cells were exposed to 6 µM Adriamycin for 4 h. However, 125 µM AN-9 was added at varying times from 24 h prior to Adriamycin addition (-24) to 2 h after Adriamycin. Results are also shown for Adriamycin treatment alone (Ad) and AN-9 treatment alone (AN9). Genomic DNA was extracted from cells and then processed for Southern analysis. A, probing of mtDNA; B, probing of the DHFR gene. Phosphorimage analysis was used for quantitation of the adducts in mtDNA (C) and the DHFR gene (D). Bars, SE.
To compare the rate of AN-9 facilitated adduct formation to that observed using Adriamycin alone in previous studies, a time course of adduct formation was conducted (data not shown). Both drugs were added to cells simultaneously, and at various times DNA was isolated and then analyzed for adduct formation. Adriamycin was used at a concentration of 4 µM with the same 25-fold excess of AN-9 as used previously. The number of adducts reached a plateau at between 5 and 8 h for both the mtDNA and DHFR gene and showed that maximal cross-linking attainable was 60% under these conditions of simultaneous treatment with both Adriamycin and AN-9.
Optimal Timing of AN-9 Addition.
To further understand the complexity of the relative time of addition of Adriamycin and AN-9, a subsequent time course experiment was performed. However, in this case, the time of exposure of cells to 4 µM Adriamycin was constant (a short incubation of 4 h to ensure that the cells did not have sufficient time to undergo replication, because this would result in underestimation of total cross-links obtained). The time of addition of AN-9 was varied to establish the optimal time for maximal cross-link formation, and this is shown in Fig. 3 . For a 4-h Adriamycin treatment, maximal cross-links (80%) were obtained when AN-9 was administered 2 h after Adriamycin. Therefore, when compared with simultaneous treatment, it is clear that the potential maximum of Adriamycin cross-links is >60% because the optimal time of addition of AN-9 can actually significantly elevate the level of cross-links formed.
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Fig. 3. Conditions for optimal adduct formation. IMR-32 cells were exposed to 4 µM Adriamycin for 4 h. However, 100 µM AN-9 was added at varying times from 2 h before Adriamycin addition (-2) to 4 h after Adriamycin addition. Genomic DNA was extracted from the cells and then processed for Southern analysis. A, mtDNA probing; B, probing of the DHFR gene. Phosphorimage analysis was used to quantitate the fraction of double-stranded DNA (adduct formation) at each of the treatment conditions and results are shown in C for the mtDNA and D for the DHFR gene.
Another time course was then initiated to establish conditions where adduct formation was severely compromised. As for previous studies, the level of Adriamycin was held constant, and the time of addition of AN-9 was varied. However, in this experiment, the addition of AN-9 was from 24 h prior to and up to 2 h after treatment by Adriamycin (Fig. 4) . The time course established that adduct levels did not increase significantly until AN-9 was administered 3 h prior to Adriamycin and increased for up to 2 h after Adriamycin addition.
Involvement of Formaldehyde and Butyric Acid.
It was then critical to establish which of the components of AN-9 was responsible for the dramatic enhancement of these DNA adducts. Because AN-9 has been shown previously to release formaldehyde, BA, and pivalic acid, an alternative prodrug, AN-158, was used as a control. This prodrug, which releases acetaldehyde, BA, and pivalic acid, was used with Adriamycin in a variety of combinations and was shown to have no effect on the adduct levels induced in mtDNA and DHFR gene by Adriamycin (data not shown), consistent with the assumed requirement for formaldehyde.
To further confirm the mechanism of enhanced Adriamycin cross-linking by AN-9, it was relevant to investigate the effect of AN-9 on cross-links induced by barminomycin. Barminomycin is an anthracycline compound that does not require activation by formaldehyde to induce DNA cross-links (32) . Cells were therefore exposed to barminomycin and AN-9 in a series of combinations. Despite incubating barminomycin with up to a 12,500-fold excess of AN-9, there was no effect on the level of barminomycin-induced cross-links in either the mtDNA or DHFR gene. Varying the time of addition of AN-9 also had no effect on cross-linking in either the mtDNA or DHFR gene (data not shown).
[14C]Adriamycin was then used to confirm that the adducts formed in the presence of AN-9 actually contained the Adriamycin chromophore and also used to accurately estimate the levels of adducts induced in the various treatment schedules (Fig. 5) . Drug treatment conditions chosen were identical to those presented in Fig. 4 . The adduct levels follow the same trend indicated by the gene-specific cross-linking assay. For example, there was a high level of adducts when AN-9 and Adriamycin treatments were simultaneous (41 adducts/10 kb) but an even higher level where AN-9 was added 2 h after Adriamycin (63 adducts/10 kb), and adduct levels decreased with longer preincubation with AN-9 (1.7 adducts/10 kb for the 16-h pretreatment). The adduct levels induced by Adriamycin as a single compound (2.8/10 kb) were higher than the AN-9/Adriamycin combination, where AN-9 pretreatment was for 16 h.
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Fig. 5. [14C]Adriamycin incorporation into adducts. IMR-32 cells were exposed to 6 µM [14C]Adriamycin alone for 4 h (Adr) or together with 125 µM AN-9 at varying times: 16 h prior (-16), 2 h prior (-2), simultaneously (0), and 2 h after Adriamycin addition (2). The remaining treatments were Adriamycin with 0.5% DMSO (DM), 250 µM AN-158 (158), or with sodium butyrate (1 mM) at varying times: 16 h prior (b-16), 2 h prior (b-2), simultaneously (b), and 2 h after Adriamycin (b+2). Genomic DNA was extracted from the cells, and incorporation of radiolabeled drug was determined by scintillation counting as described in "Materials and Methods" to determine the level of 14C adducts per 10 kb. Bars, SE.
It is interesting to note that adduct levels obtained by the 14C analysis method is 60-fold higher than the gene-specific cross-linking assay. A similar difference was noted in a previous study and shown to be attributable mainly to the loss of adducts by the additional procedures required for the preparation of genomic DNA for the gene-specific cross-linking assay, compared with the quicker and more direct 14C assay (9) . Overall, the use of [14C]Adriamycin confirms the enhancement of drug-DNA adduct levels by AN-9 and also provides direct evidence for the incorporation of the Adriamycin molecule into these adducts. Control experiments (Fig. 5) showed that there was no potentiation of adducts by DMSO or sodium butyrate when added at various times.
A series of prodrugs related to AN-9, which upon intracellular metabolic hydrolysis released either formaldehyde or acetaldehyde, and low molecular weight fatty acids were used in conjunction with [14C]Adriamycin (Table 3) . Of the four formaldehyde-releasing drugs assessed, all significantly increased adduct levels above that observed with Adriamycin alone (Fig. 6) . In contrast, all of the acetaldehyde-releasing drugs yielded only background levels of adducts, demonstrating that the ability to enhance adduct formation was limited to those prodrugs that release formaldehyde.
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Table 3 Structure of prodrugs
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Fig. 6. Potentiation of adduct formation by formaldehyde-releasing prodrugs. IMR-32 cells were treated simultaneously with 2 µM [14C]Adriamycin (Adr) and 100 µM of the indicated prodrug for 4 h. Cells were harvested, genomic DNA was extracted, and incorporation of radiolabeled drug was determined by scintillation counting. Bars, SE.
Abrogation of Responses by Sequestering Formaldehyde.
Because formaldehyde has been shown to be a critical element in the formation of DNA adducts, it was important to establish whether these adducts were responsible for the enhanced cytotoxicity displayed by the Adriamycin/AN-9 combination. Formaldehyde was sequestered by the addition of high concentrations of semicarbazide (33) . As expected, the level of DNA adducts was dramatically reduced by incubation of cells with increasing ratios of semicarbazide (Table 4) . Little difference was observed between adding semicarbazide at the same time as Adriamycin or at the same time as AN-9 (2 h later). Cell viability assays were used to measure the effect of semicarbazide inclusion on the interaction displayed by the Adriamycin/AN-9 combination. Incubation of Adriamycin and AN-9 with increasing concentrations of semicarbazide resulted in increasing levels of protection from the drug combination, and at the highest semicarbazide concentration (1 mM), cell viability was similar to that displayed by Adriamycin alone.
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Table 4 Interaction of semicarbazide with Adriamycin/AN-9
It should be noted that because the drug reaction conditions used for adduct formation and cytotoxicity experiments were quite different, adduct formation cannot be directly compared with relative survival in Table 4 . For instance, the AN-9:semicarbazide ratios differ, drug treatment times were markedly different, and in cell survival experiments, the Adriamycin concentrations were varied at a fixed concentration of AN-9 and semicarbazide.
DISCUSSION
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
The objective of this study was to quantitate the level of DNA adducts induced by Adriamycin in the presence of AN-9 and to establish whether increased adduct formation was a critical component of the Adriamycin/AN-9 synergy. The rationale for measuring adducts as an indicator of increased cytotoxicity comes from the studies of Skladanowski and Konopa (8) , who showed a strong correlation between the cytotoxicity of a series of anthracycline derivatives and their ability to cross-link DNA. From the time course data with varying times of administration of Adriamycin and AN-9 (Fig. 3 4 5 ), in comparison with the IC50 data (Table 1) , it is clear that drug treatments that are most synergistic parallel the conditions where the highest levels of adducts are observed. This is evidenced by good synergy when Adriamycin and AN-9 are administered simultaneously, where there are 15-fold more adducts than with Adriamycin alone and 20-fold more adducts when AN-9 treatment is 2 h after Adriamycin. The critical role of formaldehyde was also confirmed by reversal of formaldehyde-mediated effects by semicarbazide, which reduced adduct formation and also abolished the cytotoxicity resulting from the interaction of AN-9 with Adriamycin. It is therefore clear that the formation of adducts is at least in part associated with (or responsible for) the synergy displayed by the AN-9/Adriamycin combination.
Because the [14C]Adriamycin chromophore was present in adducts and AN-9 alone does not induce the formation of cross-linked DNA, the adducts (detected as interstrand cross-links) were likely to be of a similar composition to those induced by Adriamycin in cell-free systems (3, 4, 5) . Furthermore, in IMR-32 cells, AN-9-induced Adriamycin-DNA adducts demonstrated 5'-GC sequence specificity, were unstable at elevated temperatures, and decayed slowly at 37°C.4 These characteristics are the same as those observed with formaldehyde-mediated adducts in cell-free systems (3, 4, 5 , 34) .
It should be noted that the Adriamycin concentrations used in our cell culture assays exceeded intracellular concentrations that are routinely achieved in the clinic. It is unknown whether sufficient levels of adducts (to induce a cytotoxic response) can occur when Adriamycin is used as a single agent. However, because the use of formaldehyde-releasing prodrugs significantly elevate adduct levels, it is likely that the clinical use of these prodrugs would facilitate high levels of adducts at clinically relevant Adriamycin concentrations. Because of the instability of adducts, the only sensitive means of detection at present is the 14C assay (9) .
Previously, it was shown that a combination of AN-9 and daunorubicin (but not BA and daunorubicin) exhibited synergy against mouse Mm-A cells. When mice were inoculated with these cells, the combined treatment was responsible for a 16-day increase in the median survival time of animals (22) . However, this observation could not account for the synergy that occurred with AN-9 but was not observed with BA. It was therefore difficult to attribute the synergistic effect to the inhibition of histone deacetylase by BA released from AN-9, leading to transient hyperacetylation of histones and a corresponding "open" configuration of chromatin, thereby potentially modulating the accessibility of drugs to DNA (11) . A recent study has attributed the potentiation of Adriamycin by AN-9 to suppression of microsomal glycosidic activity, leading to inhibition of metabolic degradation of Adriamycin (35) . However, this may also be because of fixation of Adriamycin to DNA by formaldehyde, thus protecting the drug from degradation. The finding that the synergistic effect was prominent for anthracyclines with a daunosamine moiety (35) is consistent with the present results because formaldehyde-mediated adduct formation has an absolute requirement for this structural element (36) . From the present study, it is apparent that a major part of the synergistic effect is attributable to a dramatic increase in the level of anthracycline-DNA adducts. Ultimate confirmation of this in mouse models is still required.
The release of BA by AN-9 is significant because the expression of BA causes accumulation of multiacetylated forms of histones H3 and H4, leading to an alteration of chromatin structure (11) . This altered chromatin structure is more sensitive to DNase I and is a favorable configuration for transcription, and as a consequence gene regulation is changed at this level. This is accompanied by an increased accessibility to DNA by agents such as acridine orange, actinomycin D, and cisplatin (37 , 38) . Conversely, acetylation of histones can also lead to a greater exposure of damaged DNA to repair enzymes (39) . AN-9 has been shown to induce histone acetylation in HL-60 cells, and this effect is transient because the basal level of acetylation is reestablished 6 h after the exposure to AN-9 (23) . A similar scenario in the present experiments would mean that inhibition of histone deacetylation must occur within the time frame of the drug treatments. However, it is also not known at this stage what effect Adriamycin has on the ability of AN-9 to release BA or on the inhibition of histone deacetylase itself. Early studies suggested that sodium butyrate and Adriamycin were synergistic in mouse neuroblastoma cells (40) , although experiments by Kasukabe et al. (22) showed that the interaction is additive. Determining the nature of the interaction of Adriamycin and sodium butyrate (if any) is the subject of ongoing work.
There is now a wide range of evidence from the present results to show that formaldehyde (and not BA) plays a major role in potentiating Adriamycin-DNA adduct formation in cells.
(a) Prodrugs that release acetaldehyde (rather than formaldehyde) did not enhance adduct formation (Fig. 6) .
(b) Sequestration of formaldehyde by semicarbazide diminished adduct formation and reversed AN-9 induced cytotoxicity (Table 4) .
(c) Formaldehyde-releasing prodrugs had no effect on barminomycin, a drug that functions as a preactivated form of Adriamycin.
(d) Sodium butyrate did not lead to any increases in the level of [14C]Adriamycin adducts, regardless of the time of addition of this drug (Fig. 5) .
(e) Similar levels of adducts form in both mitochondrial and nuclear genomes, indicating that the status of histone acetylation in nuclear chromatin does not play a major role in adduct formation.
The mechanism of Adriamycin adduct formation is inherently dependent on formaldehyde as a critical step (5) . The most likely scenario is that Adriamycin accumulation in the nucleus and mitochondria and subsequent DNA intercalation represent the rate-limiting steps in this process. A 2-h incubation of cells with Adriamycin overcomes this limitation. Subsequent addition of AN-9 leads to rapid esterase-dependent release of formaldehyde that can complex to Adriamycin closely associated (reversibly bound) with DNA. AN-9 is rapidly taken up by cells and is retained in vivo because of its sequestration by lipophilic tissues (20) . The decreasing effectiveness of AN-9 with increasing time of preincubation may be attributable to a rapid release of formaldehyde, which is known to be detoxified by a number of cellular mechanisms (41) , thereby becoming less available by the time of delayed administration of Adriamycin. However, it is also possible that the antagonism is mechanistically related to the BA released during the pretreatment.
These data provide compelling evidence of the cytotoxicity induced by Adriamycin-DNA adducts. However, the contribution from other mechanisms of AN-9-facilitated cytotoxicity (such as lipid peroxidation and butyrate-mediated mechanisms) has yet to be established. At this stage, it is known that AN-9 does not affect the cellular uptake of Adriamycin and has no effect on the level of topoisomerase II-mediated cleavable complexes (35) . It also appears that Adriamycin-induced topoisomerase cleavable complexes are not related to Adriamycin-DNA adducts because these lesions occur at different DNA sequences (3 , 42) .
The observed molecular effects of AN-9 as a single agent (i.e., inhibition of histone deacetylation, induction of differentiation and/or apoptosis) are consistent with effects produced by BA (15) . However, the results presented in this study suggest that when the drug is combined with Adriamycin, the release of formaldehyde has an important contribution to the overall observed activity because of activation of Adriamycin to form adducts with DNA. The formation of these adducts, combined with the inhibition of metabolic degradation of Adriamycin by AN-9 (35) and the known ability of Adriamycin and AN-9 to function as single agents through other mechanisms (e.g., Adriamycin-induced impairment of topoisomerase II), may all contribute to the highly effective combination of AN-9 and Adriamycin.
Determination of the contribution of each of these factors to the efficacy of the combination is now the subject of continuing studies. The combination of Adriamycin with formaldehyde and/or BA released from AN-9 could lead to selective targeting of tumors, enabling dramatic dose reductions of Adriamycin. This is especially important in view of cardiotoxicity, which is the major side effect caused by cumulative administration of Adriamycin (43) . It is also significant to examine the potential of Adriamycin-prodrug combinations to overcome various forms of resistance to anthracyclines, using a variety of drug-resistant tumor models.
In conclusion, our investigations provide a new modality for the use of AN-9 and other formaldehyde-releasing drugs as biological response modifiers to dramatically enhance the anticancer activity of Adriamycin.
ACKNOWLEDGMENTS
We thank Dr. Ken-ichi Kimura for the gift of barminomycin.
FOOTNOTES
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
1 This work was carried out with the support of the Australian Research Council (to S. M. C. and D. R. P.), Grant 542/0 from the Israel Science Foundation, a project grant from the Israel Cancer Research Fund (to A. R. and A. N.), and the Marcus Center for Pharmaceutical and Medicinal Chemistry and the Bronia and Samuel Hacker Fund for Scientific Instrumentation at Bar Ilan University.
2 To whom requests for reprints should be addressed, at Department of Biochemistry, La Trobe University, Victoria 3086, Australia.
3 The abbreviations used are: NMR, nuclear magnetic resonance; BA, butyric acid; AN-9, pivaloyloxymethyl butyrate; AN-158, 1-pivaloyloxyethyl butyrate; DHFR, dihydrofolate reductase; CI, combination index.
4 Cutts, S. M., Swift, L., Rephaeli, A., Nudelman, A., and Phillips, D. R., unpublished results.
Received 2/22/01; accepted 9/19/01.
REFERENCES
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
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Phillips D. R., Cullinane C. Adriamycin Creighton T. E. eds. . Encyclopedia of Molecular Biology, Vol. 1: 68-72, John Wiley and Sons New York 1999.
Cullinane C., Phillips D. R. Induction of stable transcriptional blockage sites by Adriamycin: GpC specificity of apparent Adriamycin-DNA adducts and dependence on iron(III) ions. Biochemistry, 29: 5638-5646, 1990.[Medline]
Cutts S. M., Phillips D. R. Use of oligonucleotides to define the site of interstrand cross-links induced by Adriamycin. Nucleic Acids Res., 23: 2450-2456, 1995.[Abstract]
Taatjes D. J., Guadiano G., Resing K., Koch T. H. Redox pathway leading to the alkylation of DNA by the anthracycline, antitumor drugs Adriamycin and daunomycin. J. Med. Chem., 40: 1276-1286, 1997.[Medline]
Wang A. H., Gao Y. G., Liaw Y. C., Li Y. K. Formaldehyde cross-links daunorubicin and DNA efficiently: HPLC and X-ray diffraction studies. Biochemistry, 30: 3812-3815, 1991.[Medline]
Zeman S. M., Phillips D. R., Crothers D. M. Characterization of covalent Adriamycin-DNA adducts. Proc. Natl. Acad. Sci. USA, 95: 11561-11565, 1998.[Abstract/Free Full Text]
Skladanowski A., Konopa J. Relevance of interstrand DNA crosslinking induced by anthracyclines for their biological activity. Biochem. Pharmacol., 47: 2279-2287, 1994.[Medline]
Cullinane C., Cutts S. M., Panousis C., Phillips D. R. Interstrand cross-linking by Adriamycin in nuclear and mitochondrial DNA of MCF-7 cells. Nucleic Acids Res., 28: 1019-1025, 2000.[Abstract/Free Full Text]
Fenick D. J., Taatjes D. J., Koch T. H. Doxoform, and Daunoform: anthracycline-formaldehyde conjugates toxic to resistant tumor cells. J. Med. Chem., 40: 2452-2461, 1997.[Medline]
Vidali G., Boffa L. C., Bradbury E. M., Allfrey V. G. Butyrate suppression of histone deacetylation leads to accumulation of multiacetylated forms of histones H3 and H4 and increased Dnase-1 sensitivity of the associated DNA sequences. Proc. Natl. Acad. Sci. USA, 75: 2239-2243, 1978.[Medline]
Prasad K. N. Butyric acid: a small fatty acid with diverse biological functions. Life Sci., 27: 1351-1358, 1980.[Medline]
Januszewicz E., Rabizadeh E., Novogrodsky A., Shaklai M. Butyric acid: inhibition of non-leukemic and chronic myeloid leukemia granulocyte macrophage clonal growth. Med. Oncol. Tumor Pharmacother., 5: 259-263, 1988.[Medline]
Miller A. A., Kurschel E., Osieka R., Schmidt C. G. Clinical pharmacology of sodium butyrate in patients with acute leukemia. Eur. J. Cancer Clin. Oncol., 23: 1283-1287, 1987.[Medline]
Nudelman A., Ruse M., Aviram A., Rabizadeh E., Shaklai M., Zimra Y., Rephaeli A. Novel anticancer prodrugs of butyric acid. J. Med. Chem., 35: 687-694, 1992.[Medline]
Rephaeli A., Rabizadeh E., Aviram A., Shaklai M., Ruse M., Nudelman A. Derivatives of butyric acid as potential anti-neoplastic agents. Int. J. Cancer, 49: 66-72, 1991.[Medline]
Zimra Y., Nudelman A., Zhuk R., Rabizadeh E., Shaklai M., Aviram A., Rephaeli A. Uptake of pivaloyloxymethyl butyrate into leukemic cells and its intracellular esterase-catalyzed hydrolysis. J. Cancer Res. Clin. Oncol., 126: 693-698, 2000.[Medline]
Roholt K., Nielsen B., Kristensen E. Pharmacokinetic studies with mecillinam and pivmecillinam. Chemotherapy, 21: 146-166, 1975.[Medline]
Bundgaard H., Nielsen N. M. Esters of N,N-disubstituted 2-hydroxyacetamides as a novel highly biolabile prodrug type for carboxylic acid agents. J. Med. Chem., 30: 451-454, 1987.[Medline]
Rabizadeh E., Shaklai M., Eisenbach L., Nudelman A., Rephaeli A. Esterase inhibitors diminish the modulation of gene expression by butyric acid derivative, pivaloyloxymethyl butyrate (AN-9). Israel J. Med. Sci., 32: 1186-1191, 1996.[Medline]
Siu L. L., Von Hoff D. D., Rephaeli A., Izbicka E., Cerna C., Gomez L., Rowinsky E. K., Eckhardt S. G. Activity of pivaloyloxymethyl butyrate, a novel anticancer agent, on primary human tumor colony-forming units. Investig. New Drugs, 16: 113-119, 1998.[Medline]
Kasukabe T., Rephaeli A., Honma Y. An anti-cancer derivative of butyric acid (pivalyloxymethyl-butyrate) and daunorubicin cooperatively prolong survival of mice inoculated with monocytic leukemia cells. Br. J. Cancer, 75: 850-854, 1997.[Medline]
Aviram A., Zimrah Y., Shaklai M., Nudelman A., Rephaeli A. Comparison between the effect of butyric acid and its prodrug pivaloyloxymethyl butyrate on histones hyperacetylation in an HL-60 leukemic cell line. Int. J. Cancer, 56: 906-909, 1994.[Medline]
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Rabizadeh E., Shaklai M., Nudelman A., Eisenbach L., Rephaeli A. Rapid alteration of c-myc and c-jun expression in leukemic cells induced to differentiate by a butyric acid prodrug. FEBS Lett., 328: 225-229, 1993.[Medline]
Aviram A., Rephaeli A., Shaklai M., Nudelman A., Ben-Dror I., Maron L., Rabizadeh E. Effect of the cytostatic butyric acid pro-drug, pivaloyloxymethyl butyrate, on the tumorigenicity of cancer cells. J. Cancer Res. Clin. Oncol., 123: 267-271, 1997.[Medline]
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Vos J. M. Analysis of psoralen monoadducts and interstrand crosslinks in defined genomic sequences Friedberg E. C. Hanawalt P. C. eds. . DNA Repair: A Laboratory Manual of Research Procedures, Vol. 3: 367-398, Marcel Dekker New York 1988.
Perrin L. C., Cullinane C., Kimura K., Phillips D. R. Barminomycin forms GC-specific adducts and virtual interstrand crosslinks with DNA. Nucleic Acids Res., 27: 1781-1787, 1999.[Abstract/Free Full Text]
O’Connor P. M., Fox B. W. Isolation and characterization of proteins cross-linked to DNA by the antitumor agent methylene dimethanesulfonate and its hydrolytic product formaldehyde. J. Biol. Chem., 264: 6391-6397, 1989.[Abstract/Free Full Text]
Cutts S. M., Parker B. S., Swift L. P., Kimura K-I., Phillips D. R. Structural requirements for the formation of anthracycline-DNA adducts. Anti-Cancer Drug Design, 15: 373-386, 2000.[Medline]
Niitsu N., Kasukabe T., Yokoyama A., Okabe-Kado J., Yamamoto-Yamaguchi Y., Umeda M., Honma Y. Anticancer derivative of butyric acid (pivalyloxymethyl butyrate) specifically potentiates the cytotoxicity of doxorubicin and daunorubicin through the suppression of microsomal glycosidic activity. Mol. Pharmacol., 58: 27-36, 2000.[Abstract/Free Full Text]
Leng F., Savkur R., Fokt I., Przewloka T., Priebe W., Chaires J. B. Base specific and regioselective chemical crosslinking of daunorubicin to DNA. J. Am. Chem. Soc., 118: 4731-4738, 1996.
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Bubley G. J., Xu J., Kupiec N., Sanders D., Foss F., O’Brien M., Emi Y., Teicher B. A., Patierno S. R. Effect of DNA conformation on cisplatin adduct formation. Biochem. Pharmacol., 51: 717-721, 1996.[Medline]
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Capranico G., Kohn K. W., Pommier Y. Local sequence requirements for DNA cleavage by mammalian topoisomerase II in the presence of doxorubicin. Nucleic Acids Res., 18: 6611-6619, 1990.[Abstract]
Severs N. J., Twist V. W., Powell T. Acute effects of Adriamycin on the macromolecular organization of the cardiac muscle cell plasma membrane. Cardioscience, 2: 35-45, 1991.[Medline]
Here's Dr.Cutts who works with Dr. Sturm - Molecular Basis for the Synergistic Interaction of Adriamycin with the Formaldehyde-releasing Prodrug Pivaloyloxymethyl Butyrate (AN-9)1
Suzanne M. Cutts, Ada Rephaeli, Abraham Nudelman, Inesa Hmelnitsky and Don R. Phillips2
Department of Biochemistry, La Trobe University, Victoria 3086, Australia [S. M. C., D. R. P.]; Felsenstein Medical Research Center, Sackler School of Medicine, Tel Aviv University, Beilinson Campus, Petach Tikva 49100, Israel [A. R.]; and Chemistry Department, Bar Ilan University, Ramat Gan 52900, Israel [A. N., I. H.]
The interaction of Adriamycin and pivaloyloxymethyl butyrate (AN-9) was investigated in IMR-32 neuroblastoma and MCF-7 breast adenocarcinoma cells. Adriamycin is a widely used anticancer drug, whereas AN-9 is an anticancer agent presently undergoing Phase II clinical trials. The anticancer activity of AN-9 has been attributed to its ability to act as a butyric acid prodrug, although it also releases formaldehyde and pivalic acid. Adriamycin and AN-9 in combination display synergy when exposed simultaneously to cells or when AN-9 treatment is up to 18 h after Adriamycin administration. However, the reverse order of addition results in antagonism. These interactions have been established using cell viability assays and classical isobologram analysis. To understand the molecular basis of this synergy, the relative levels of Adriamycin-DNA adducts were determined using various treatment combinations. Levels of Adriamycin-DNA adducts were enhanced when treatment combinations known to be synergistic were used and were diminished using those treatments known to be antagonistic. The relative timing of the addition of Adriamycin and AN-9 was critical, with a 20-fold enhancement of Adriamycin-DNA adducts occurring when AN-9 was administered 2 h after the exposure of cells to Adriamycin. The enhanced levels of these adducts and the accompanying decreased cell viability were directly related to the esterase-dependent release of formaldehyde from AN-9, providing evidence for the formaldehyde-mediated activation of Adriamycin.
Professor of Metabolic and Genetic Epidemiology: Paul McKeigue - http://www.lshtm.ac.uk/ncdeu/genetics/index.html
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Genetic Epidemiology Group
Professor of Metabolic and Genetic Epidemiology: Paul McKeigue, PhD, FFPHM
Clinical Lecturer: Mariam Molokhia, MRCGP
Research Fellow: Clive Hoggart, PhD
Contents of this page
Current research
ADMIXMAP program
EUDRAGENE
Other Software
Recent Publications
Current research
The main focus of our research is on admixture mapping. This is a novel approach to finding genes that underlie ethnic variation in disease risk, based on studying populations of mixed descent. Admixture mapping is based on the same principles as linkage analysis of an experimental cross between inbred strains. Using panels of markers that are chosen to be highly informative for ancestry, it is possible in principle to extend this approach to admixed human populations where the history of admixture is not under experimental control and the ancestral populations are not inbred strains [19]. Our work in this area is an extension of earlier work on the epidemiology of ethnic variation in risk of cardiovascular disease and diabetes.
The advantage of admixture mapping, in comparison with conventional approaches to localizing disease genes based on family linkage studies, is that in principle it has far greater power than family linkage studies to detect genes of modest effect. This is because admixture mapping is a based on a direct (fixed effects) comparison, whereas family linkage studies are based on an indirect (random effects) statistical comparison. Applying admixture mapping to search the genome requires development of statistical methods that can be applied to phenotypic traits and marker data to extract the information about genetic linkage that is generated by admixture. We have developed a first working version of ADMIXMAP, a statistical analysis program that can be used to model admixture and to test for linkage. This program is based on a Bayesian approach in which the posterior distribution of parental admixture and individual ancestry at each locus is generated by Markov chain Monte Carlo simulation [8].
Our research on admixture mapping is supported by the US National Institutes of Health, the UK Medical Research Council, the Arthritis Research Campaign, and GlaxoSmithKline. We are working closely with the Department of Anthropology, Penn State University on the application of admixture mapping to African-American populations, and on the development of marker sets for admixture mapping. We are collaborating with other researchers in the Caribbean region.
ADMIXMAP program
This is a general-purpose program for modelling admixture, using marker genotypes and trait data on a sample of individuals from an admixed population (such as African-Americans), where the markers have been chosen to have extreme differentials in allele frequencies between two or more of the ancestral populations between which admixture has occurred. The main difference between ADMIXMAP and classical programs for estimation of admixture such as ADMIX is that ADMIXMAP is based on a multilevel model for the distribution of individual admixture in the population and the stochastic variation of ancestry on hybrid chromosomes. This makes it possible to model the associations of ancestry between linked marker loci, and the association of a trait with individual admixture or with ancestry at a linked marker locus.
Possible uses of the ADMIXMAP program
Modelling the distribution of individual admixture values and the history of admixture (inferred by modelling the stochastic variation of ancestry along chromosomes).
Case-control, cross-sectional or cohort studies that test for a relationship between disease risk and individual admixture
Localizing genes underlying ethnic differences in disease risk by admixture mapping
Controlling for population structure (variation in individual admixture) in genetic association studies so as to eliminate associations with unlinked genes
Reconstructing the genetic structure of an ancestral population where unadmixed modern descendants are not available for study
ADMIXMAP can model admixture between more than two populations, and can use data from multi-allelic or biallelic marker polymorphisms. The program has been developed for application to admixed human populations, but can also be used to model admixture in livestock or for fine mapping of quantitative trait loci in outbred stocks of mice.
A manual for the program is available which describes the statistical model in more detail. Downloads of the program compiled for various platforms are also available. We recommend that before trying to run the program, you consult us first about your requirements.
Download ADMIXMAP
ADMIXMAP documentation
Download ADMIXMAP for Linux admix-1.2-linux.tar.gz
Download ADMIXMAP for Windows
ADMIXMAP tutorial for Windows
ADMIXMAP tutorial (HTML) (pdf)
EUDRAGENE: European collaboration to establish a case-control DNA collection for studying the genetic basis of adverse drug reactions
The specific objectives of this proposed collection is to establish a freely-shared case-control collection of DNA samples as a resource for studying genetic predictors of adverse drug reactions. Identifying genetic variants that influence susceptibility to adverse reactions will advance understanding of the molecular basis of adverse drug reactions and may also lead to the development of tests that can predict individual susceptibility to adverse reactions, with obvious benefits to human health. This study has received infrastructure funding for 3 years (starting Jan 03) from the EC 5th Framework Quality of Life Program.
Adverse drug reactions (ADRs) are important causes of morbidity and mortality, limit the usefulness of many otherwise effective drugs, and are under strong genetic influence. Identifying genetic variants that influence susceptibility to ADRs has obvious practical applications, and more generally will contribute to understanding of the molecular basis of adverse drug reactions. Research in this area is hampered by the lack of a resource in which to study genetic determinants of susceptibility to ADRs. As most such ADRs are rare, a case-control design is the only feasible approach, and a multicentre European collaboration is necessary as no single country will generate enough cases of any given ADR within a reasonable time.
We propose to establish a freely-shared resource consisting of clinical data and DNA samples from cases of ADRs, together with a control group. In the first year we plan to select for study an initial set of six ADRs that are important because they cause serious illness in a small minority of those exposed to drugs that are otherwise more effective than any alternative, and that are easily identified because they have distinctive manifestations that are not related to the disease for which the drug was prescribed. At least 500 cases of each ADR will be collected, together with an equal number of controls. The collection will be extended to include more ADRs after the first 1-2 years, based on problems of current concern.
Other Software
prepKbio1.1.zip - Windows program for: concatenating multiple Kbioscience results into a single file, reordering the loci into the order they appear on the chromosome, and adding pedigree information to the Kbioscience results. SnpViewer can then be used to turn this single set of results into text file in the pedfile format, which is a data format required by many genetic analysis programs. Full instructions on how to use prepKbio come with the program. If you have any problems email: Richard.Sharplshtm.ac.uk
Recent publications
Hoggart CJ, Parra EJ, Shriver MD, Bonilla C, Kittles RA, Clayton DG, McKeigue PM. Control of confounding of genetic associations in stratified populations. Am J Hum Genet. 2003, in press.
Colhoun HM, McKeigue PM, Davey Smith G. Problems of reporting genetic associations with complex outcomes. Lancet. 2003 Mar 8;361(9360):865-72. Review.
Shriver MD, Parra EJ, Dios S, Bonilla C, Norton H, Jovel C, Pfaff C, Jones C, Massac A, Cameron N, Baron A, Jackson T, Argyropoulos G, Jin L, Hoggart CJ, McKeigue PM, Kittles RA. Skin pigmentation, biogeographical ancestry and admixture mapping. Hum Genet. 2003 Apr;112(4):387-99.
Molokhia M, Hoggart C, Patrick AL, Shriver M, Parra E, Ye J, Silman AJ, McKeigue PM. Relation of risk of systemic lupus erythematosus to west African admixture in a Caribbean population. Hum Genet. 2003 Mar;112(3):310-8.
Reynolds RM, Chapman KE, Seckl JR, Walker BR, McKeigue PM, Lithell HO. Skeletal muscle glucocorticoid receptor density and insulin resistance. JAMA. 2002 May 15;287(19):2505-6.
Clayton D, McKeigue PM. Epidemiological methods for studying genes and environmental factors in complex diseases. Lancet. 2001 Oct 20;358(9290):1356-60. Review.
Molokhia M, McKeigue PM, Cuadrado M, Hughes G. Systemic lupus erythematosus in migrants from west Africa compared with Afro-Caribbean people in the UK. Lancet. 2001 May 5;357(9266):1414-5.
McKeigue PM, Carpenter JR, Parra EJ, Shriver MD. Estimation of admixture and detection of linkage in admixed populations by a Bayesian approach: application to African-American populations. Ann Hum Genet. 2000 Mar;64(Pt 2):171-86.
Parra EJ, Kittles RA, Argyropoulos G, Pfaff CL, Hiester K, Bonilla C et al. Ancestral proportions and admixture dynamics in geographically defined African-Americans living in South Carolina. American Journal of Physical Anthropology 2001;114:18-29.
Pfaff CL, Parra EJ, Bonilla C, Hiester K, McKeigue PM, Kamboh MI, Hutchinson RG, Ferrell RE, Boerwinkle E, Shriver MD. Population structure in admixed populations: effect of admixture dynamics on the pattern of linkage disequilibrium. Am J Hum Genet. 2001 Jan;68(1):198-207.
McKeigue PM. Multipoint admixture mapping. Genet Epidemiol. 2000 Dec;19(4):464-7.
Molokhia M, McKeigue P. Risk for rheumatic disease in relation to ethnicity and admixture. Arthritis Res. 2000;2(2):115-25. Review.
McKeigue PM. Efficiency of estimation of haplotype frequencies: use of marker phenotypes of unrelated individuals versus counting of phase-known gametes. Am J Hum Genet. 2000 Dec;67(6):1626-7.
Aitman TJ, Cooper LD, Norsworthy PJ, Wahid FN, Gray JK, Curtis BR, McKeigue PM, Kwiatkowski D, Greenwood BM, Snow RW, Hill AV, Scott J. Malaria susceptibility and CD36 mutation. Nature. 2000 Jun 29;405(6790):1015-6.
Zoratti R, Godsland IF, Chaturvedi N, Crook D, Crook D, Stevenson JC, McKeigue PM. Relation of plasma lipids to insulin resistance, nonesterified fatty acid levels, and body fat in men from three ethnic groups: relevance to variation in risk of diabetes and coronary disease. Metabolism. 2000 Feb;49(2):245-52.
Davey G, Ramachandran A, Snehalatha C, Hitman GA, McKeigue PM. Familial aggregation of central obesity in Southern Indians. Int J Obes Relat Metab Disord. 2000 Nov;24(11):1523-7.
Forouhi N, Jenkinson G, Thomas EL, Mierisova S, Bhonsle J, McKeigue PM et al. Relation of triglyceride stores in skeletal muscle cells to central obesity and insulin sensitivity in South Asian and European men. Diabetologia 1999;42:932-5.
McKeigue PM. Ethnic variation in insulin resistance and risk of Type 2 diabetes. In: Reaven G, Laws A, eds. Insulin Resistance, Totowa, NJ: Humana, 1999: 35-51.
Al-Mahroos F, McKeigue PM. High prevalence of diabetes mellitus in Bahrainis: associations with ethnicity and raised plasma cholesterol. Diabetes Care 1998; 21: 936-42.
McKeigue PM. Mapping genes that underlie ethnic differences in disease risk: methods for detecting linkage in admixed populations by conditioning on parental admixture. American Journal of Human Genetics 1998; 63: 241-51.
McKeigue PM. Mapping genes underlying ethnic differences in disease risk by linkage disequilibrium in recently admixed populations. American Journal of Human Genetics 1997; 60: 188-96.
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You going to like this one on the Dr. Sturm - http://genepi.qimr.edu.au/staff/nick_pdf/CV345.pdf
A Gel Mobility Shift Assay for Probing the Effect of Drug–DNA Adducts on DNA-Binding Proteins
Suzanne M. Cutts, Andrew Masta, Con Panousis, Peter G. Parsons, Richard A. Sturm, and Don R. Phillips
Heres more on the Dr. - http://www.wistar.upenn.edu/herlyn/sup_pdfs/Rick_Sturm_Cancer_Res.pdf
Check this out on Dr. Sturm - http://genepi.qimr.edu.au/staff/nick_pdf/CV364.pdf
More on Dr Sturm - Gu Zhu, David M. Evans, David L. Duffy, Grant W. Montgomery, Sarah E. Medland, Nathan A. Gillespie, Kelly R. Ewen, Mary Jewell, Yew Wah Liew, Nicholas K. Hayward, Richard A. Sturm, Jeffrey M. Trent, Nicholas G. Martin. A genome scan for eye colour in 502 twin families: most variation is due to a QTL on chromosome 15q. Twin Research
Variants in pigmentation gene found to be risk factors for skin cancers
Last Updated: 2000-10-09 18:36:01 EDT (Reuters Health) - Three normal variants of the melanocortin-1 receptor (MC1R) gene have been found to be strongly associated with susceptibility to skin cancers in the Australian population, according to research presented here at the American Society of Human Genetics annual meeting.
These variant alleles occur among people whose phenotype makes them appear similar in pigmentation, and may help explain why some people go on to develop melanoma, basal cell carcinoma, or squamous cell carcinoma during life in a sunny environment while others do not, said Dr. Richard Sturm of the University of Queensland, Australia.
The three variant alleles on the MC1R gene (R151C, R160W and D294H) are associated with fair skin, red hair and ultraviolet sensitivity, but one or two ma to be sun aware," he said. "If you've got the variant, you have to be extra aware."
The Australian population has one of the highest skin cancer rates in the world, with a lifetime risk of developing melanoma of 1 in 17. This is attributed to the many fair-complexioned people from the British Isles who populate the country, parts of which receive sun exposure comparable to that of northern Africa.
Link to Susceptibility to Skin Cancer Found
By Karla Harby
PHILADELPHIA (Reuters Health) - Three normal variants of the melanocortin-1 receptor (MC1R) gene have been found to be strongly associated with susceptibility to skin cancers in the Australian population, according to research presented here at the American Society of Human Genetics annual meeting.
These variant alleles occur among people whose phenotype makes them appear similar in pigmentation, and may help explain why some people go on to develop melanoma, basal cell carcinoma, or squamous cell carcinoma during life in a sunny environment while others do not, said Dr. Richard Sturm of the University of Queensland, Australia.
The three variant alleles on the MC1R gene (R151C, R160W and D294H) are associated with fair skin, red hair and ultraviolet sensitivity, but one or two may appear in Caucasians with medium, olive or dark complexions, according to Dr. Sturm.
Among medium-, olive- or dark-skinned Australians, Dr. Sturm and colleagues found that those who carried one variant allele had a two-fold increased risk of melanoma, while those who carried two variants had a four-fold increased risk. In essence, Dr. Sturm explained, an unfavorable genotype can partly negate the protection normally provided by darker skin pigmentation.
How such genetic information might be used to augment current public health campaigns to limit sun exposure in Australia is unclear, he said. He emphasized that those whose genotype is relatively protective from sun exposure would be ill-advised to increase their time in the sun as a consequence. "I'd tell everyone, you've got to be sun aware," he said. "If you've got the variant, you have to be extra aware."
The Australian population has one of the highest skin cancer rates in the world, with a lifetime risk of developing melanoma of 1 in 17. This is attributed to the many fair-complexioned people from the British Isles who populate the country, parts of which receive sun exposure comparable to that of northern Africa.
DNA LEFT AT CRIME SCENE WILL REVEAL SKIN COLOUR
http://www.telegraph.co.uk/connected/main.jhtml?xml=/connected/2004/06/23/ecndna22.xml&sSheet=/c...
DNA left at crime scene will reveal skin colour
By Roger Highfield, Science Editor
(Filed: 22/06/2004)
Scientists have found a way to tell the eye and skin colour of a suspect from the DNA left at the scene of a crime, they report today.
They will soon be able to help police even further by using the same technology to predict hair colour.
The colour of eyes is influenced by the interaction of several genes, according to the study published in the journal Trends in Genetics by Dr Richard Sturm of Queensland University and Dr Tony Frudakis of the company Dnaprint Genomics, Florida.
Using special markers called AIMs that can identify the genetic differences between different populations they have identified the DNA sequences that explain most of the variations in eye colour in Europeans.
"Aside from the Forensic Science Service in Britain, which has a red hair test, there are no other genetic tests for physical characteristics commercially available yet," said Dr Sturm.
The research also questions the wisdom of many school biology textbooks.
Children are usually taught that brown is dominant, so if one parent has brown eyes so does their offspring, while two blue-eyed parents always have a blue-eyed child.
But the team found that, though uncommon, blue-eyed parents can have children with brown eyes. "This is because eye colour is determined by several interacting genes," said Dr Sturm.
WHAT ELSE HAS DR. STRUM BEEN WORKING ON:
http://hmg.oupjournals.org/cgi/content/abstract/13/4/447
Human Molecular Genetics, 2004, Vol. 13, No. 4 447-461
DOI: 10.1093/hmg/ddh043
Interactive effects of MC1R and OCA2 on melanoma risk phenotypes
David L. Duffy1, Neil F. Box2, Wei Chen2, James S. Palmer1,2, Grant W. Montgomery1, Michael R. James1, Nicholas K. Hayward1, Nicholas G. Martin1 and Richard A. Sturm2,*
1Queensland Institute of Medical Research, Brisbane, Australia and 2Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
Received October 21, 2003; Accepted December 11, 2003
The relationships between MC1R gene variants and red hair, skin reflectance, degree of freckling and nevus count were investigated in 2331 adolescent twins, their sibs and parents in 645 twin families. Penetrance of each MC1R variant allele was consistent with an allelic model where effects were multiplicative for red hair but additive for skin reflectance. Of nine MC1R variant alleles assayed, four common alleles were strongly associated with red hair and fair skin (Asp84Glu, Arg151Cys, Arg160Trp and Asp294His), with a further three alleles having low penetrance (Val60Leu, Val92Met and Arg163Gln). These variants were separately combined for the purposes of this analysis and designated as strong ‘R’ (OR=63.3; 95% CI 31.9–139.6) and weak ‘r ’ (OR=5.1; 95% CI 2.5–11.3) red hair alleles. Red-haired individuals are predominantly seen in the R/R and R/r groups with 67.1 and 10.8%, respectively. To assess the interaction of the brown eye color gene OCA2 on the phenotypic effects of variant MC1R alleles we included eye color as a covariate, and also genotyped two OCA2 SNPs (Arg305Trp and Arg419Gln), which were confirmed as modifying eye color. MC1R genotype effects on constitutive skin color, freckling and mole count were modified by eye color, but not genotype for these two OCA2 SNPs. This is probably due to the association of these OCA2 SNPs with brown/green not blue eye color. Amongst individuals with a R/R genotype (but not R/r), those who also had brown eyes had a mole count twice that of those with blue eyes. This suggests that other OCA2 polymorphisms influence mole count and remain to be described.
* To whom correspondence should be addressed at: Institute for Molecular Bioscience, University of Queensland, Brisbane, Qld 4072, Australia. Tel: +61 733462038; Fax: +61 733462101; Email: r.sturm@imb.uq.edu.au
Eye colour: portals into pigmentation genes and ancestry.
Sturm RA, Frudakis TN. Eye colour: portals into pigmentation genes and ancestry. Trends Genet. 2004 Aug;20(8):327-32.
Institute for Molecular Bioscience, University of Queensland, Brisbane, Qld 4072, Australia.
Several recent papers have tried to address the genetic determination of eye colour via microsatellite linkage, testing of pigmentation candidate gene polymorphisms and the genome wide analysis of SNP markers that are informative for ancestry. These studies show that the OCA2 gene on chromosome 15 is the major determinant of brown and/or blue eye colour but also indicate that other loci will be involved in the broad range of hues seen in this trait in Europeans.
DNAPRINT CHANGING GENETICS TEXTS?
http://www.guardian.co.uk/life/dispatch/story/0,12978,1245589,00.html
Throw out those genetics books
Thursday June 24, 2004
The Guardian
Everything you learned in school is wrong, when it comes to eye colour at least. Despite what textbooks say, the genetic inheritance of eye colour is not a simple matter, argue geneticists Richard Sturm and Tony Frudakis. Several genes are involved and, occasionally, two blue-eyed parents can produce dark-eyed children.
"There is a predominant gene for blue or brown eye colour but it is not an absolute determinant," says Sturm, of the University of Queensland. "There are subtleties of eye colour and a range of hues that we cannot yet fully explain."
Eye colour is down to the distribution of melanocyte cells, which produce the melanin pigment and are much more common in brown eyes. "Blue eye colour is actually due to a light scattering effect, similar to the blue of the sky, of the packaged melanin," Sturm says.
Frudakis, of the US company DNAprint, hopes to develop the research into a forensic test to predict a criminal's eye colour from DNA left at a crime scene. The results appear in the August issue of Trends in Genetics.
And this article explains it in a little better detail:
Eye colour, pigmentation genes and ancestry
Monday, 28 June 2004
New research from UQ’s Institute for Molecular Bioscience (IMB) demonstrates that one of the classic examples of genetic inheritance taught in schools is wrong.
No longer is it true to say there is a single gene influencing the colour of our eyes according to IMB’s Dr Rick Sturm and DNAprint Genomics’ Dr Tony Frukadis in their review article published in the respected journal Trends in Genetics.
Using special DNA markers (called AIMs) to identify the genetic differences between different populations, scientists have now identified the gene sequences explaining variable eye colour in Europeans.
Dr Sturm said the concept commonly taught in schools was that brown eye colour is always dominant to blue and two blue-eyed parents always produce a blue-eyed child.
“This is simplistic and does not convey the complexities of real life. Although it is not very common, there are instances of two blue eyed parents having darker eyed children, demonstrating the interaction of several genes,” Dr Sturm said.
"There is a predominant gene for blue/brown eye colour called OAC2 but it is not an absolute determinant. Many other genes influence the type of eye colour we find in the European population.
“We cannot yet fully explain the range and subtleties of eye colour,” he said.
The physical basis of eye colour is determined by the distribution and pigment content of melanocyte cells (the specialised cells that produce melanin, the factor responsible for pigmentation) in the eye. Brown eyes have the same number of melanocytes as blue eyes but they produce an abundance of melanin, while blue eyes do not produce as much.
“Newborn children have blue eyes because they have not yet made much melanin, this occurs as the eyes mature during the first year of life," he said.
“The colour of our eyes, hair and skin are all linked, in that the same genes affect the production of melanin in all of these tissues, however certain genes will have more influence on one tissue than another.
“The genetics of eye colour are similar to the genetics of skin colour – darker traits tend to go together but we do see individuals with blue eyes and black hair.
“There are as many hues of eye colour as there are of skin colour but because we often simplify these traits into either light and dark or blue and brown we don’t do justice to all the shades that exist in the population,” Dr Sturm said.
A future application of this work may include using AIMs to develop a method to determine eye colour from a DNA sample found at crime scenes.
Guess we'll get a better idea what's up with Retinome soon. Generally, one might expect the August issue of "Trends in Genetics" to be out sometime in July...
A must read -
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http://biz.yahoo.com/bw/040719/195663_1.html
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NewMarket Technology Inc: New Name, New Symbol, New CUSIP
Monday July 19, 11:07 am ET
Setting Standard in High-Tech Micro-Cap Market While Defending Shareholder Value From Suspicious Trading
CEO Reaffirms 2004 Forecast for $50 Million in Annualized Revenue and $20 Million in Booked Revenue; Encourages Shareholders to Request Paper Certificates
DALLAS--(BUSINESS WIRE)--July 19, 2004-- NewMarket Technology Inc. (OTCBB:NMKT - News) today released a letter to shareholders to introduce the recent NewMarket name change and corresponding symbol change on the OTCBB. The letter reaffirms the 2004 corporate plan to achieve $50 million in annualized revenue and updates shareholders on recent progress to identify and act against specific illegal trading activity. The letter is included in this press release in its entirety.
ADVERTISEMENT
Dear Fellow Shareholders,
On Friday, July 16, the OTCBB Exchange changed our ticker symbol to reflect our recent Corporate name change from IPVoice Communications Inc. (OTCBB:IPVO - News) to NewMarket Technology Inc. (OTCBB:NMKT - News). The name change has been part of our overall long-term plan to expand our business model to include Internet technologies beyond just VoIP. However, we may get more benefit from this name change than just re-branding our expanded business model.
As shareholders you all own stock, though most of you have never seen a stock certificate. You have an electronic report in the form of your account statement that reflects your stock ownership. Some of you may not realize that paper certificates even exist, but they do.
The Depository Trust Company (DTC) is charged with the responsibility of insuring that your electronic report of stock ownership corresponds to an actual paper stock certificate representing shares owned. This is no easy task, given the high volume of daily trades, let alone the fact that a single share may trade hands multiple times in any given hour. Introduce the practice of short selling and the correlation of electronic certificates to paper certificates arguably becomes almost an impossibility.
I am sure many of you understand naked short selling practices, but some of you may not be familiar with the strategy. Naked short selling is simply the sale of a share that does not exist in hopes that the price will go down allowing the short seller to buy stock at a lower price to fill his short order. In the event of a short sale, there are more electronic certificates than paper certificates until the short seller buys stock to fill their short sale. If the stock price goes up, the short seller loses money, just like you may lose money if you bought stock and the price goes down.
Short selling, within certain rules, is not illegal. However, when a short seller coordinates his efforts with posting false claims about Company operations on the Terra Lycos Raging Bull online bulletin board, then a law has been broken. Such a short seller is attempting to manipulate the share price down in order to benefit from their short sale. We have tracked many Raging Bull posters and we have discovered individuals employed by investment banking firms. We are taking action accordingly and will continue in our efforts to track other suspicious Raging Bull posters.
Some short sellers never intend to buy stock to fill their short sales. Technically, to sell a share short a share must first be borrowed so that in the event the share price goes up, the borrowed share can be collected to fill the short order. Naked short sellers take advantage of foreign brokers outside the close scrutiny of United States regulators to borrow against shares that might not exist in order to make short sales. This is where the Berlin Stock Exchange may be an issue. The Berlin Stock Exchange has been very uncooperative in working with us to mitigate the potential of any issue. The Berlin Exchange has recognized in writing the ability for their Exchange to be utilized to support naked short selling in the United States, but has nevertheless refused our repeated requests to be de-listed in what they believe to be the best interest of German shareholders. We have made an offer to coordinate a purchase of all stock traded on the Berlin Exchange and ostensibly held by German shareholders in combination with a de-listing of our stock on the Berlin Exchange. The Berlin Stock Exchange has not taken our offer. We have engaged German legal representation and will take the necessary legal actions.
What can we do in addition to pursuing message board posters and the Berlin Stock exchange in court? Request your broker to send you the paper certificates for your stock. This will force a reconciliation of paper and electronic certificates and uncover any open short positions so that regulators can deal with the naked shorters accordingly.
With the name change and ticker symbol change, new paper stock has been created with a new CUSIP number. CUSIP stands for Committee on Uniform Securities Identification Procedures. A CUSIP number identifies stocks of all registered U.S. and Canadian companies. The CUSIP system is owned by the American Bankers Association and operated by Standard & Poor's. Technically, all existing paper certificates, either in a safe at the DTC or in a safe at your broker's, should be exchanged for a new paper certificate with the new CUSIP number. The exchange of all old paper certificates for new paper certificates would effect a reconciliation of all paper certificates with all electronic certificates and all short positions would be uncovered. This process however is not well regulated. By each legitimate shareholder demanding a paper certificate, the electronic reconciliation can be essentially effected by shareholder mandate.
Do not let your broker deny you the right to "order out" a stock certificate. You may find resistance from your broker when you make this request. You have the right to receive paper certificates. Do not take no for an answer.
An artificial supply of Company stock may be the cause of our recent share price decline. Basic economics tells us if supply is plentiful, then the price declines. However, if through an electronic share reconciliation we discover that the supply is truly artificial and that actually a scarcity of stock exists, then basic economics will work to increase the share price.
Please do not hesitate to contact the Company with any questions regarding a request for a paper certificate. We also want to hear about any resistance you encounter in your request.
While we are working diligently to manage the current suspicious trading activity, the majority of our time is dedicated to continuing to grow the Company accordingly to plan. We recently announced a $1 million dollar organic sales contract and anticipate closing similar deals in the near future. We are beginning to realize notable sales traction with an improved opportunity to sign larger contracts. We are closing the books for the second quarter now and will announce the second quarter results and the forecast for the balance of 2004 in early August. We are on track to meet our corporate goal of an annual revenue run rate of $50 million by year end with $20 million in booked revenue. In spite of the recent suspicious stock trading activity, the Company is in better operational condition then ever.
Thank you for your ongoing support.
Philip Verges
CEO
NewMarket Technology Inc.
About NewMarket Technology Inc. (www.newmarkettechnology.com)
In 2002, NewMarket (formerly IPVoice Communications Inc.) launched a business plan to continuously introduce emerging communication technologies to market. The plan included a financing model for early technologies and an approach to creating economies of scale through a specialized service and support organization intended specifically for the emerging technology industry. The Company posted six consecutive profitable quarters through 2003 and established an annualized $15 million in revenue. In 2003, NewMarket acquired Infotel Technologies in Singapore and IP Global Voice, led by CEO Peter Geddis, a former Executive Vice President and Chief Operating Officer of Qwest Communications (NYSE:Q - News). In 2004, the Company diversified its communications technology offering into the healthcare and homeland security industries with the respective acquisitions of Medical Office Software Inc. and Digital Computer Integration Corp. RKM IT Solutions of Caracas, Venezuela, was also recently acquired as NewMarket's entry into the Latin American market.
This press release contains statements (such as projections regarding future performance) that are forward-looking statements as defined in the Private Securities Litigation Reform Act of 1995. Actual results may differ materially from those projected as a result of certain risks and uncertainties, including but not limited to those detailed from time to time in the Company's filings with the Securities and Exchange Commission.
--------------------------------------------------------------------------------
Contact:
NewMarket Technology, Inc., Dallas
Investor Relations, 972-386-3372 ext. 211
ir@ipvoice.com
www.newmarkettechnology.com
www.ipvoice.com
or
LC Group
Rick Lutz, 404-261-1196
lcgroup@mindspring.com
Some more of IBM research - The work of the Bioinformatics & Pattern Discovery Group focuses on a number of theoretical and applied problems that are of relevance to computational molecular biology. During the last several years we have been working on the the following:
pattern and association discovery in event streams;
multiple sequence alignment;
new approaches for similarity searching in
protein/dna databases;
the analysis of gene expression data
the parallelization of our algorithms on both
shared-memory and message-passing architectures
establishing lower bounds on the number of irredundant
motifs contained in a given database as well as algorithms
for finding these motifs
the automated annotation of proteins directly from sequence;
the discovery of genes in prokarytotic genomes using
dictionary-driven approaches
the characterization and prediction of local
3D structure directly from sequence;
the discovery of tandem repeats in DNA sequences;
the automated classification of protein sets into families;
the automatic generation of composite descriptors
for arbitrary collections of biological sequences;
new techniques for principal component analysis with
application to rational drug design, gene expression
analysis, and other problems;
the determination of archaea-, bacteria- and eukaryota-
specific signatures,
comparative genomics
and other.
We have also compiled the Bio-Dictionary(TM) an exhaustive collection of 1-dimensional patterns (which we refer to as seqlets - for 'small sequences') by processing the GenPept and SwissProt & TrEMBL databases with Teiresias. This collection allows us to fully characterize the sequence space of natural proteins - to the extent allowed by the sampling provided by the sequences in the processed databases. We have shown that the seqlets the Bio-Dictionary(TM) contains capture conserved functional and structural signatures both within and across family boundaries.
We continuously produce metadata (i.e. 'content') from public databases of biological sequences. Recently, we began making available annotations of complete genomes
Partial 'Blue Gene' Systems Are Now Two of the Top Ten Most Powerful Supercomputers on Earth
June 21, 2004--For the first time, two IBM Blue Gene/L prototype systems appear on the Top 10 list of supercomputers. The Blue Gene/L prototype represents a radical new design for supercomputing. At 1/20th the physical size of existing machines of comparable power, Blue Gene/L enables dramatic reductions in power consumption, cost and space requirements for businesses requiring immense computing power. For a new architecture to produce so much compute power in such a small package is a stunning achievement, and provides a glimpse of the future of supercomputing.
The number four-ranked Blue Gene/L DD1 Prototype, with a sustained speed of 11.68 teraflops and a peak speed of 16 teraflops, uses more than 8,000 PowerPC processors packed into just four refrigerator-sized racks. This ground breaking system is only 1/16 of its planned final capacity and has skyrocketed to the 4th place from the 73rd spot on the list in November 2003. The eighth-ranked Blue Gene/L DD2 Prototype has a sustained speed of 8.66 teraflops and a peak speed of 11.47 teraflops. The DD2 system is based on the second generation of the Blue Gene/L chips, which are more powerful than those used in the DD1 prototype.
About IBM's Blue Gene Supercomputing Project
Blue Gene is an IBM supercomputing project dedicated to building a new family of supercomputers optimized for bandwidth, scalability and the ability to handle large amounts of data while consuming a fraction of the power and floor space required by today's fastest systems. The full Blue Gene/L machine is being built for the Lawrence Livermore National Laboratory in California, and will have a peak speed of 360 teraflops. When completed in 2005, IBM expects Blue Gene/L to lead the Top500 supercomputer list. A second Blue Gene/L machine is planned for ASTRON, a leading astronomy organization in the Netherlands. IBM and its partners are currently exploring a growing list of applications including hydrodynamics, quantum chemistry, molecular dynamics, climate modeling and financial modeling.
IBM Surges Past HP To Lead in Global Supercomputing
Partial 'Blue Gene' Systems Are Now Two of the Top Ten Most Powerful Supercomputers on Earth - New Era In Supercomputing Arrives
ARMONK, N.Y. -- June 20, 2004 -- An independent study released today named IBM as the world's leading provider of both installed supercomputing systems (with 224 systems) as well as total aggregate supercomputing power (with a record total 407 teraflops, or trillions of calculations per second). According to analysis from the TOP500 List of Supercomputers, IBM is the leader in global supercomputing with 50 percent of the total processing power, which is two and a half times more processing power than its closest rival, runner up Hewlett Packard with 19 percent.
For the first time, two IBM Blue Gene/L prototype systems appear on the Top 10 list of supercomputers. The Blue Gene/L prototype represents a radical new design for supercomputing. At 1/20th the physical size of existing machines of comparable power, Blue Gene/L enables dramatic reductions in power consumption, cost and space requirements for businesses requiring immense computing power. For a new architecture to produce so much compute power in such a small package is a stunning achievement, and provides a glimpse of the future of supercomputing.
The number four-ranked Blue Gene/L DD1 Prototype, with a sustained speed of 11.68 teraflops and a peak speed of 16 teraflops, uses more than 8,000 PowerPC processors packed into just four refrigerator-sized racks. This ground breaking system is only 1/16 of its planned final capacity and has skyrocketed to the 4th place from the 73rd spot on the list in November 2003. The eighth-ranked Blue Gene/L DD2 Prototype has a sustained speed of 8.66 teraflops and a peak speed of 11.47 teraflops. The DD2 system is based on the second generation of the Blue Gene/L chips, which are more powerful than those used in the DD1 prototype.
"By giving our clients access to innovative, affordable and flexible supercomputing power like Blue Gene and the Deep Computing Capacity on Demand Center, we are providing new resources to drive breakthroughs in business, science and industry," said Dave Turek, vice president, Deep Computing, IBM. "Whether we are talking about improving the accuracy of weather forecasts, designing better automobiles or improving disease research, we are seeing the advent of a new supercomputing age."
Other key indicators of IBM supercomputing leadership:
IBM has 224 supercomputer systems installed, most of any vendors (44.8 percent of the list are IBM systems)
IBM has most installed computing power with over 407 Teraflops. (50 percent of the total power on the list belongs to IBM)
IBM has the most supercomputers in the Top10 (3)
IBM has the most supercomputers in the Top20 (10)
IBM has the most supercomputers in the Top100 (68)
IBM has the most Linux clusters on the TOP500 List (150)
The "TOP500 List Supercomputing Sites" is compiled and published by supercomputing experts Jack Dongarra from the University of Tennessee, Erich Strohmaier and Horst Simon of NERSC/Lawrence Berkeley National Laboratory and Hans Meuer of the University of Mannheim (Germany). The entire list can be viewed at http://www.top500.org.
About IBM's Blue Gene Supercomputer Project
Blue Gene is an IBM supercomputing project dedicated to building a new family of supercomputers optimized for bandwidth, scalability and the ability to handle large amounts of data while consuming a fraction of the power and floor space required by today's fastest systems. The full Blue Gene/L machine is being built for the Lawrence Livermore National Laboratory in California, and will have a peak speed of 360 teraflops. When completed in 2005, IBM expects Blue Gene/L to lead the Top500 supercomputer list. A second Blue Gene/L machine is planned for ASTRON, a leading astronomy organization in the Netherlands. IBM and its partners are currently exploring a growing list of applications including hydrodynamics, quantum chemistry, molecular dynamics, climate modeling and financial modeling.
About IBM
IBM is the world's largest information technology company, with 80 years of leadership in helping businesses innovate. Drawing on resources from across IBM and key Business Partners, IBM offers a wide range of services, solutions and technologies that enable customers, large and small, to take full advantage of the new era of e-business. For more information about IBM, visit www.ibm.com.
Photos of Blue Gene/L available at:
http://domino.research.ibm.com/Comm/bios.nsf/pages/bluegene-2004. html(Due to the length of this URL, it may be necessary to copy and paste this hyperlink into your Internet browser's URL address field. You may also need to remove an extra space in the URL if one exists.)
Dont forget Timothy Yeatman MD is the Principle Investigator with Dnap as well.You dont think these are all seperate.Read Moffit's game plan !!! There is no way Clinomics will not be working side by side with Dnap IBM and Affymetrix,Mayo,and all the rest.
Cytomyx Holdings PLC Announces Clinomics BioSciences, Cytomyx' US Subsidiary, in Research Collaboration with Moffitt Cancer Center
http://www.primezone.com/newsroom/news_releases.mhtml?d=60687
CAMBRIDGE, U.K. and ALBANY, New York, July 13, 2004 (PRIMEZONE) -- Clinomics Biosciences, Inc., the wholly owned US subsidiary of Cytomyx Holdings plc (AIM:CYX), a leading provider of drug discovery products and services, has signed a collaboration agreement with the H. Lee Moffitt Cancer Center and Research Institute, one of the leading cancer research centers in the US, to jointly develop new technologies for use in cancer research.
Known as Tissue MicroArrays, Clinomics' proprietary technology allows the identification of gene and protein expression patterns in tumors on a high-throughput basis. This data will be used to generate "molecular signatures", for more precisely defining cancer patient sub-groups which, in turn will lead to improved cancer diagnosis and treatment.
The initial phase of the research program will focus on the use of Tissue MicroArray methodologies to improve the diagnosis and classification of primary tumors, with the goal of improving treatment outcomes. The joint research will be conducted in the laboratories of the Moffitt Cancer Center, in Tampa, Florida.
Stephen Turner, Clinomics' CEO, said: "We are pleased to be collaborating with Moffitt, a leading, national cancer institute with a substantial molecular characterization program involved in cancer. Together with Clinomics, which has built the world's most extensive database of highly characterized human biology samples, we believe that an important new capability for classifying tumors will result from our collaboration with the goal of creating whole genome datasets on tumor samples and developing the leading gene expression database for pharmaceutical development."
Principle Investigator for the project is Timothy Yeatman MD, Associate Center Director, Clinical Investigations, at the Moffitt Cancer Center. Dr. Yeatman commented: "This is the beginning of an exciting new age in molecular medicine where cancer therapy will now be directed by a comprehensive molecular analysis of gene expression. Molecular signatures may be able to identify and predict the future biological behavior of different tissues or tumor types."
About Clinomics BioSciences, Inc.
Clinomics BioSciences, Inc., (www.clinomicsbio.com), based in Albany, New York, is a wholly owned subsidiary of Cytomyx Holdings plc, offering database products for the biological characterization of gene and protein targets for use in drug discovery research. The company has a collection of more than 200,000 highly characterized human and biology samples and its proprietary Tissue MicroArray technology allows hundreds of individual tissue samples to be arrayed on microscope slides for use in gene and protein characterization studies.
About H. Lee Moffitt Cancer Center and Research Institute
The H. Lee Moffitt Cancer Center and Research Institute is located in Tampa, Florida. In 2001 the National Cancer Institute awarded Moffitt the status of a Comprehensive Cancer Center in recognition of its excellence in research and contributions to clinical trials, prevention and cancer control. Additionally, Moffitt is a member of the National Comprehensive Cancer Network, a prestigious alliance of the USA's leading cancer centers, and is listed in the U.S. News & World Report as one of the top cancer hospitals in America. Moffitt's sole mission is to contribute to the prevention and cure of cancer.
About Cytomyx Holdings plc
Cytomyx Holdings plc (www.cytomyx-holdings.com) is a rapidly growing life science company based in Cambridge, UK. Its four operating subsidiaries -- Cytomyx Ltd, Clinomics BioSciences, Inc., Cambridge Bioscience Ltd and Cytocell Technologies Ltd -- develop and market a wide range of products and services to the pharmaceutical, diagnostics and academic research markets. Cytomyx is listed on the London Stock Exchange's Alternative Investment Market (AIM).
About Tissue MicroArrays
Clinomics BioSciences has pioneered the development of the emerging new technology known as Tissue MicroArrays (TMAs). These enable researchers to simultaneously study hundreds of individual tissue samples in parallel to establish the relative levels of protein expression in those samples and thereby draw conclusions as to the relevance of these proteins in disease. The Company currently has three granted US patents in this field.
TMAs overcome an important bottleneck in drug discovery, namely the high-throughput evaluation of proteins in human tissue samples. TMAs consist of up to 1000 tiny cylindrical tissue samples (usually 0.6mm in diameter) that are assembled in a paraffin block from which sections (thin slices) are then cut and attached to glass microscope slides.
TMA sections allow the simultaneous analysis of expression of a protein of interest in up to 1000 tissue samples in a single experiment. They are, therefore, cost-efficient and offer an unprecedented degree of standardization as all tissue samples are subjected to exactly the same experimental conditions. TMAs can be constructed from virtually all kinds of tissues, including formalin-fixed and fresh frozen tissue.
Pharmaceutical industry researchers can use TMA technology to link the presence of a particular protein to the progression of a disease. Another major application for the technology is in the development of therapeutic antibody products where they can be used to demonstrate that such antibodies are found only to bind to the protein to which they are intended to be directed.
TMA technology represents one of the most promising new approaches in the fields of proteomics and drug discovery. TMA use is growing rapidly among histology labs and recent reports indicate that the number of users has at least doubled each year over the past two years. The market for TMAs is expected to grow at more than 40% per year to reach over $150 million by 2008.
I just got home and i dont know what you all are smoking but can i have some.Man. LOL
I dont think IBM's Blue Gene supercomputer has this problem. Dnap is working with.
Want to buy some Dna pins - http://www.kerchner.com/dnapin.htm