Dr. Yeatman’s research focuses on developing and validating molecular prognostic signatures in cancer, primarily in colon, lung and breast. Initial work with mRNA expression arrays expanded to include analysis of miRNA arrays with samples from many of the same tissues. In colon cancer, gene expression changes between Duke’s stage A and D were used to define the prognosis in Duke’s stage B and C.A validation study characterized the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas; the study supported combined use of clinical and molecular information when building prognostic models for early stage lung cancer.Staging inadequately predicts metastatic risk in colon cancer patients. His team used a gene expression profile derived from invasive, murine colon cancer cells highly metastatic in an immunocompetent mouse model, to identify colon cancer patients at risk of recurrence. The profile was refined with comparative functional genomics in the VMC gene expression profiles to identify a 34-gene classifier associated with high risk of metastasis and death from colon cancer.In research to identify the source of unknown primary tumors, Dr. Yeatman and colleagues developed a two-tiered classification scheme based on gene expression data that initially assigns a tumor to one of the four subclasses of carcinoma: adenocarcinoma, squamous cell carcinoma, neuroendocrine carcinoma, or urothelial carcinoma. The second tier uses one of four additional classifiers to assign the primary site of origin to the tumor.