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Cancer Proliferation Gene Discovery Through Functional Genomics

Cancer Proliferation Gene Discovery Through Functional Genomics.

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Cancer Proliferation Gene Discovery Through Functional Genomics

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  1. Cancer Proliferation Gene Discovery Through Functional Genomics Michael R. Schlabach, Ji Luo, Nicole L. Solimini, Guang Hu, Qikai Xu, Mamie Z. Li, Zhenming Zhao, Agata Smogorzewska, Mathew E. Sowa, Xiaolu L. Ang, Thomas F. Westbrook, Anthony C. Liang, Kenneth Chang, Jennifer A. Hackett, J. Wade Harper, Gregory J. Hannon, Stephen J. Elledge FEBRUARY 2008, SCIENCE

  2. BACKGROUND • Geneticists have identified various genes that are normally present and genes vital for thegrowth and survival of specific cancers. • Genome sequencing studies are costlyand require extensive analysis to identify mutationsthat cause cancers, from those which are present by chance. • Researchers then proposed a “non-oncogene addiction” idea: that a tumor relies heavily on certain normal cell pathways, and that drugs disabling gene products in those pathways could be deadly to cancer. • Therefore, a more FUNCTIONAL approach – by studying cancer cells behaviorin response to certain molecular triggers, can be a quicker path tonew cancer drugs.

  3. METHODS They then studied genes which are central regulators of signaling pathways in human DLD-1 and HCT116 colon cancer cells, human HCC1954 breast cancer cells, and also normal human mammary epithelial cells.

  4. FINDINGS • They found that most shRNAsshowed little changes in their abundance over time. However, a small fraction (1-10%)of shRNAs showed depletion. • The two colon cancer cell lines were more similar to each other than to the breast cancer line.

  5. FINDINGS Study showed components of core cellular modules are essential for all cell lines. They validated the genes EIF3S10 and RBX1 (essential for viabilityin all 4 cell lines) using shRNAs to the genes. All shRNAs gave antiproliferative phenotypes. Thus, these phenotypes are likely due to target gene knockdown rather than to off-target effects.

  6. FINDINGS • A – C - Distinct, genetic context–dependent vulnerabilities exist between DLD-1 and HCC1954 tumor cell lines. • D & E - Tetraploid HCC1954 cells may rely more heavily than diploid HMECs on the spindle checkpoint (BUB1 gene) to maintain genomic stability. • This dependency is an example of “non-oncogene addiction” where cancer cells are highly dependent for growth and survival on functions of non-oncogenes.

  7. CONCLUSIONS • This functional genetic approach is an alternative method to sequencing-based approaches such as the Cancer Genome Atlas (which focus identifying mutations of the cancer genome). • The advantages of the functional genetic method are – • It is a FUNCTIONAL approach • Cheaper • Easier, and • A quicker path to new cancer drugs. • Researchers can screen the entire human genome with ~3 shRNAs per gene using a pool of ~100,000 shRNAs in ~100 million cells. • Thus, researchers can generate cancer lethality signatures for different cancer types and thus identifying cancer type–specific lethal genes representing potential drug targets.

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