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Functional genomics to decipher cancer dependencies and mechanisms
Author(s) -
Hahn William C
Publication year - 2012
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.26.1_supplement.464.1
Subject(s) - decipher , computational biology , genome , cancer , biology , genomics , functional genomics , gene , human genome , cancer genome sequencing , genetics
Recent advances in genomics now make it possible to consider enumerating all of the genetic lesions in specific cancers. While these approaches will yield critical information regarding the identify, number, and types of alterations found in human tumors, a complementary approach to decipher the molecular basis of malignant transformation depends upon the application of genome scale tools to annotate the function of genes involved in cancer initiation and progression. Over the past several years, we have developed genome scale RNAi libraries and open reading frame expression libraries that permit a systematic evaluation of genes involved in cancer initiation and maintenance. Using these libraries, we have now performed screens in a panel of human cancer cell lines to systematically identify cancer vulnerabilities. By combining these functional approaches with information derived from mapping the structural abnormalities present in cancer genomes, we have identified several new oncogenes that contribute to cancer development. In pilot studies, we have identified several genes that act as synthetic lethal partners to known oncogenes or mediate resistance to targeted therapies. In recent work, we have expanded the scale of these experiments to genome scale in more than 100 cell lines. Recent insights from these efforts will be discussed. Taken together, these studies suggest that combining forward and reverse genetic approaches with information derived from the cancer genome characterization projects will yield a comprehensive list of cancer vulnerabilities and establish a general approach for the rational identification of oncogenic and co‐dependent pathways in cancer.