| First Author | Sos ML | Year | 2009 |
| Journal | Proc Natl Acad Sci U S A | Volume | 106 |
| Issue | 43 | Pages | 18351-6 |
| PubMed ID | 19805051 | Mgi Jnum | J:153701 |
| Mgi Id | MGI:4366123 | Doi | 10.1073/pnas.0907325106 |
| Citation | Sos ML, et al. (2009) Identifying genotype-dependent efficacy of single and combined PI3K- and MAPK-pathway inhibition in cancer. Proc Natl Acad Sci U S A 106(43):18351-6 |
| abstractText | In cancer, genetically activated proto-oncogenes often induce 'upstream' dependency on the activity of the mutant oncoprotein. Therapeutic inhibition of these activated oncoproteins can induce massive apoptosis of tumor cells, leading to sometimes dramatic tumor regressions in patients. The PI3K and MAPK signaling pathways are central regulators of oncogenic transformation and tumor maintenance. We hypothesized that upstream dependency engages either one of these pathways preferentially to induce 'downstream' dependency. Therefore, we analyzed whether downstream pathway dependency segregates by genetic aberrations upstream in lung cancer cell lines. Here, we show by systematically linking drug response to genomic aberrations in non-small-cell lung cancer, as well as in cell lines of other tumor types and in a series of in vivo cancer models, that tumors with genetically activated receptor tyrosine kinases depend on PI3K signaling, whereas tumors with mutations in the RAS/RAF axis depend on MAPK signaling. However, efficacy of downstream pathway inhibition was limited by release of negative feedback loops on the reciprocal pathway. By contrast, combined blockade of both pathways was able to overcome the reciprocal pathway activation induced by inhibitor-mediated release of negative feedback loops and resulted in a significant increase in apoptosis and tumor shrinkage. Thus, by using a systematic chemo-genomics approach, we identify genetic lesions connected to PI3K and MAPK pathway activation and provide a rationale for combined inhibition of both pathways. Our findings may have implications for patient stratification in clinical trials. |
