There is marked disparity with a slight overlap among prognosis-predictive signatures reported thus far for lung cancers. In this study, we aimed at linking poor prognosis with particular pathways and/or functions of the gene sets involved to better understand the underlying molecular characteristics associated with the prognosis of lung adenocarcinomas. Gene set enrichment analysis identified a gene set down-regulated by rapamycin as the most significant, whereas several others responsive to withdrawal of glucose or amino acids, which are related to signaling converging onto mammalian target of rapamycin (mTOR), were also shown to be significantly associated, in addition to those related to DNA damage response and cell cycle progression. We also used connectivity map (C-MAP) analysis, an independent bioinformatics approach, to search for Food and Drug Administration-approved drugs that potentially transform an unfavorable signature to a favorable one. Those results identified inhibitors of phosphatidylinositol 3-kinase (PI3K) and mTOR, as well as unexpected drugs such as phenothiazine antipsychotics and resveratrol as potential candidates. Experimental validation revealed that the latter unexpected agents also inhibited signaling converging onto mTORand exhibited antitumor activities. In addition, deregulation of multiple signaling converging onto mTORwas shown to be significantly associated with sensitivity to PI-103, a dual specificity PI3K/mTORinhibitor that is not contained in the C-MAP database, lending further support for the connection. Our results clearly show the existence of gene set-definable, intrinsic heterogeneities in lung adenocarcinomas, which seem to be related to both clinical behavior and sensitivity to agents affecting the identified pathways.
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