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Predicting drug susceptibility of non–small cell lung cancers based on genetic lesions
Martin L. Sos, … , Kwok-Kin Wong, Roman K. Thomas
Martin L. Sos, … , Kwok-Kin Wong, Roman K. Thomas
Published May 18, 2009
Citation Information: J Clin Invest. 2009;119(6):1727-1740. https://doi.org/10.1172/JCI37127.
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Technical Advance Oncology

Predicting drug susceptibility of non–small cell lung cancers based on genetic lesions

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Abstract

Somatic genetic alterations in cancers have been linked with response to targeted therapeutics by creation of specific dependency on activated oncogenic signaling pathways. However, no tools currently exist to systematically connect such genetic lesions to therapeutic vulnerability. We have therefore developed a genomics approach to identify lesions associated with therapeutically relevant oncogene dependency. Using integrated genomic profiling, we have demonstrated that the genomes of a large panel of human non–small cell lung cancer (NSCLC) cell lines are highly representative of those of primary NSCLC tumors. Using cell-based compound screening coupled with diverse computational approaches to integrate orthogonal genomic and biochemical data sets, we identified molecular and genomic predictors of therapeutic response to clinically relevant compounds. Using this approach, we showed that v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations confer enhanced Hsp90 dependency and validated this finding in mice with KRAS-driven lung adenocarcinoma, as these mice exhibited dramatic tumor regression when treated with an Hsp90 inhibitor. In addition, we found that cells with copy number enhancement of v-abl Abelson murine leukemia viral oncogene homolog 2 (ABL2) and ephrin receptor kinase and v-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (avian) (SRC) kinase family genes were exquisitely sensitive to treatment with the SRC/ABL inhibitor dasatinib, both in vitro and when it xenografted into mice. Thus, genomically annotated cell-line collections may help translate cancer genomics information into clinical practice by defining critical pathway dependencies amenable to therapeutic inhibition.

Authors

Martin L. Sos, Kathrin Michel, Thomas Zander, Jonathan Weiss, Peter Frommolt, Martin Peifer, Danan Li, Roland Ullrich, Mirjam Koker, Florian Fischer, Takeshi Shimamura, Daniel Rauh, Craig Mermel, Stefanie Fischer, Isabel Stückrath, Stefanie Heynck, Rameen Beroukhim, William Lin, Wendy Winckler, Kinjal Shah, Thomas LaFramboise, Whei F. Moriarty, Megan Hanna, Laura Tolosi, Jörg Rahnenführer, Roel Verhaak, Derek Chiang, Gad Getz, Martin Hellmich, Jürgen Wolf, Luc Girard, Michael Peyton, Barbara A. Weir, Tzu-Hsiu Chen, Heidi Greulich, Jordi Barretina, Geoffrey I. Shapiro, Levi A. Garraway, Adi F. Gazdar, John D. Minna, Matthew Meyerson, Kwok-Kin Wong, Roman K. Thomas

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