Here are some of his recent papers:
The future of cancer management: translating the genome, transcriptome, and proteome. Yeatman TJ. Ann Surg Oncol. 2003 Jan-Feb;10(1):7-14.
Department of Surgery, H. Lee Moffitt Cancer Center, University of South Florida, Tampa, Florida 33612, USA. yeatman@moffitt.usf.edu
Predicting who will develop cancer and how the cancer will behave and respond to therapy after diagnosis are some of the potential benefits of the ongoing genetic revolution that can be envisioned within the next decade. Translational applications of genomic-based research efforts may actually precede the development of effective therapeutic agents that can exploit the vast amounts of data derived from these efforts. In the future, understanding the wealth of information generated by high-throughput molecular efforts and how it can be applied to clinical problems will likely be critical to the surgeon who guides the multidisciplinary care of the cancer patient. This review will discuss the advances in our understanding of the human genome (DNA), its derived transcriptome (RNA), and its translated proteome (proteins) and will focus on the translation of this information into routine clinical practice. In particular, we will focus on the potential for clinical application of microarray-based gene-expression profiling to the diagnosis, prognosis, and therapy of malignancies.
The future of clinical cancer management: one tumor, one chip. Yeatman TJ. Am Surg. 2003 Jan;69(1):41-4.
Department of Surgery, H. Lee Moffitt Cancer Center, University of South Florida, 12902 Magnolia Drive, Tampa, Florida 33612, USA.
Recent advances in gene expression profiling technology have now made it feasible to consider using microarray technology in the routine management of the cancer patient. Microarray chips are now capable of interrogating up to 48,000 or more different genes in a single experiment using multiple platforms. Sophisticated data analysis has already demonstrated that multiple tumor types can be distinguished on the basis of their gene expression patterns. These analyses have led to the detection of new tumor markers and markers of tumor progression. Gene expression arrays have also been demonstrated to be capable of predicting the survival of patients with breast cancer, lung cancer, brain cancer, and acute lymphocytic leukemia. The future holds great promise for the rapid development of molecular medicine with diagnosis, prognosis, and even therapy being based on a single microarray chip. These developments signal a significant paradigm shift in the clinical management of human cancer.
Osteopontin and colon cancer progression. Yeatman TJ, Chambers AF. Clin Exp Metastasis. 2003;20(1):85-90.
H. Lee Moffitt Cancer Center, Tampa, Florida 33612, USA. Yeatman@moffitt.usf.edu
Human colon cancer affects nearly 150,000 patients and results in 60,000 deaths in the United States per year. Despite significant advances in the management of the colon cancer patient, little change in survival rates has been appreciated over the past 50 years. The primary cause of death relates to the development of distant metastases to organs such as the liver and lungs. Colon cancer represents an important disease to study in order to better understand tumor progression and metastasis primarily because there is almost a stepwise advancement of the disease that is marked by measurable genetic and associated phenotypic alterations. Metastasis appears to be the end product of the development of 'Herculean' cell clones capable of independent growth, invasion, adhesion, avoidance of apoptosis, and angiogenesis. Although significant progress has been made in understanding the sequential genetic events leading to the development of cancer, the precise genes and the associated molecular pathways underlying the development of metastatic potential are still poorly understood. Moreover, our enhanced genetic knowledge has had relatively little trickle down effect on our clinical management of this deadly disease. For this reason, we undertook a comprehensive study to develop a molecular encyclopedia of new tumor markers and markers of tumor progression, some of which will hopefully prove useful in the clinical management of colon cancer patients by means of their capacity to detect and predict the stage and disease burden. This review will focus on the application of gene expression profiling technology to the problem of identifying new tumor markers and progression markers, and the discovery of osteopontin as the leading candidate clinical marker derived from a screen of approximately 12,000 named genes.
Multi-platform, multi-site, microarray-based human tumor classification. Bloom G, Yang IV, Boulware D, Kwong KY, Coppola D, Eschrich S, Quackenbush J, Yeatman TJ. Am J Pathol. 2004 Jan;164(1):9-16.
H. Lee Moffitt Cancer Center, University of South Florida, Tampa, Florida 33612-9497, USA.
The introduction of gene expression profiling has resulted in the production of rich human data sets with potential for deciphering tumor diagnosis, prognosis, and therapy. Here we demonstrate how artificial neural networks (ANNs) can be applied to two completely different microarray platforms (cDNA and oligonucleotide), or a combination of both, to build tumor classifiers capable of deciphering the identity of most human cancers. First, 78 tumors representing eight different types of histologically similar adenocarcinoma, were evaluated with a 32k cDNA microarray and correctly classified by a cDNA-based ANN, using independent training and test sets, with a mean accuracy of 83%. To expand our approach, oligonucleotide data derived from six independent performance sites, representing 463 tumors and 21 tumor types, were assembled, normalized, and scaled. An oligonucleotide-based ANN, trained on a random fraction of the tumors (n = 343), was 88% accurate in predicting known pathological origin of the remaining fraction of tumors (n = 120) not exposed to the training algorithm. Finally, a mixed-platform classifier using a combination of both cDNA and oligonucleotide microarray data from seven performance sites, normalized and scaled from a large and diverse tumor set (n = 539), produced similar results (85% accuracy) on independent test sets. Further validation of our classifiers was achieved by accurately (84%) predicting the known primary site of origin for an independent set of metastatic lesions (n = 50), resected from brain, lung, and liver, potentially addressing the vexing classification problems imposed by unknown primary cancers. These cDNA- and oligonucleotide-based classifiers provide a first proof of principle that data derived from multiple platforms and performance sites can be exploited to build multi-tissue tumor classifiers.
Correlation of osteopontin protein expression and pathological stage across a wide variety of tumor histologies. Coppola D, Szabo M, Boulware D, Muraca P, Alsarraj M, Chambers AF, Yeatman TJ. Clin Cancer Res. 2004 Jan 1;10(1 Pt 1):184-90.
Department of Pathology, University of South Florida College of Medicine, Tampa, Florida, USA.
PURPOSE: Osteopontin (OPN) is an integrin-binding protein overexpressed in various experimental models of malignancy and appears to be involved in tumorigenesis and metastasis. Although various studies have assessed OPN protein levels in several tumor types, a broad survey of OPN expression in human neoplasia under the same experimental conditions has not been carried out. EXPERIMENTAL DESIGN: We used immunohistochemistry to detect OPN in a selection of 350 human tumors and 113 normal tissues, from a variety of body sites, using stage-oriented human cancer tissue arrays. Tumors included malignancies from breast (26), ovary (22), endometrium (14), esophagus (10), stomach (11), pancreas (16), bile duct (1), liver (9), colon (20), kidney (53), bladder (33), prostate (28), head and neck (60), salivary glands (14), lung (17), skin (6), and brain (10). RESULTS: High cytoplasmic OPN staining was observed in 100% of gastric carcinomas, 85% of colorectal carcinomas, 82% of transitional cell carcinomas of the renal pelvis, 81% of pancreatic carcinomas, 72% of renal cell carcinomas, 71% of lung and endometrial carcinomas, 70% of esophageal carcinomas, 58% of squamous cell carcinomas of the head and neck, and 59% of ovarian carcinomas. Although OPN expression was identified in a good number of bladder, prostate, and brain tumors, the majority of 6 skin cancers, 11 of 14 salivary gland cancers, 2 thyroid carcinomas, and 23 of 26 breast cancers revealed low OPN positivity or were negative. When considering all sites, OPN expression significantly correlated with tumor stage (Spearman's correlation coefficient, P = 0.0002). OPN score and stage were also significantly correlated for specific cancer sites including bladder (P = 0.01), colon (P = 0.004), kidney (P = 0.0001), larynx (P = 0.035), mouth (P = 0.046), and salivary gland (P = 0.011). CONCLUSIONS: This study reports the broad distribution of OPN in human tumors from different body sites, suggesting involvement of this protein in tumor formation. The strong correlation between pathological stage and OPN across multiple tumor types suggests a role for OPN in tumor progression.
Osteopontin identified as colon cancer tumor progression marker. Agrawal D, Chen T, Irby R, Quackenbush J, Chambers AF, Szabo M, Cantor A, Coppola D, Yeatman TJ. C R Biol. 2003 Oct-Nov;326(10-11):1041-3.
Department of Cell Biology, H. Lee Moffitt Cancer Center, University of South Florida, Tampa, FL, USA.
Identifying molecular markers for colon cancer is a top priority. Using a pooled sample approach with Affymetrix GeneChip technology, we assayed colon cancers derived from a series of clinical stages to identify molecular markers of potential prognostic value. Of 12000 genes assessed, osteopontin emerged as the leading candidate tumor progression marker. Osteopontin is a secreted glycoprotein known to bind integrins and CD44. Its actual molecular function remains elusive but its increased expression correlates strongly with tumor progression.
