Anurag Singh, Ph.D.

Assistant Professor of Pharmacology and Medicine

Principal Investigator: Laboratory of Cancer Pharmacogenomics

Section of Hematology and Medical Oncology and Member, The Cancer Center

Research Interests

Dr. Singh’s laboratory studies deregulated signal transduction networks that contribute to the pathophysiology of lung, pancreatic and colon cancers. Adenocarcinomas that arise in these tissues frequently harbor mutations in the KRAS oncogene or components of the KRAS signaling pathway, such as BRAF or PI3K. The core KRAS signaling pathway has been very well characterized but the precise mechanisms governing tumor maintenance in KRAS mutant cancers remain to be fully elucidated. Through comparative whole genome expression profiling, Dr. Singh has previously shown that KRAS mutant cancers can be classified into discrete molecular subtypes based on a phenotypic dichotomy of KRAS oncogene “addiction” or dependency. He derived tissue or lineage-specific KRAS dependency gene expression signatures that reflect differing modes of KRAS-mediated signal transduction in lung versus pancreatic versus colon cancers. Therefore, Dr. Singh hypothesizes that context-specificity is critical in the analysis of KRAS signaling networks.

Current research in the Singh lab is focused on exploiting the various lineage-specific KRAS dependency signatures to reveal mechanisms by which oncogenic KRAS maintains tumor cell survival in a context-dependent manner. In colon cancer, Dr. Singh has identified the TGF-b activated kinase as a component of a Wnt-driven proinflammatory signaling network that promotes tumor cell survival in KRAS dependent colon cancer cells. In lung and pancreatic cancers, Dr. Singh’s lab is studying the molecular basis for the relationship between the developmental epithelial-mesenchymal transition (EMT) program and KRAS oncogene dependency, as well as a role for non-coding microRNAs in mediating this relationship. The lab uses computational methods to derive genomic profiles in cancer cell lines and human primary tumors. These profiles reveal differentially expressed gene modules that can be built into systems-level signaling network models of KRAS-driven tumor cell survival signaling. Components of these network models are functionally validated and tested by cell and molecular methodologies using cancer cell lines in vitro as well as xenografted tumors in mice.