Proteogenomic systems analysis identifies targeted therapy resistance mechanisms in EGFR‐mutated lung cancer. Issue 3 (8th November 2018)

• Record Type: Journal Article
• Authors: Treue, Denise; Bockmayr, Michael; Stenzinger, Albrecht; Heim, Daniel; Hester, Svenja; Klauschen, Frederick
• Is Part Of: International journal of cancer. Volume 144:Issue 3(2019)
• Page Start: 545
• Page End: 557
• Publication Date: 2018-11-08
• Subjects: lung cancer -- proteomic -- system biology -- drug resistance; Cancer -- Periodicals; Cancer -- Prevention -- Periodicals; 616.994
• DOI: 10.1002/ijc.31845
• Languages: English
• ISSNs: 0020-7136

Abstract

Abstract : Cancer precision medicine largely relies on knowledge about genetic aberrations in tumors and next‐generation‐sequencing studies have shown a high mutational complexity in many cancers. Although a large number of the observed mutations is believed to be not causally linked with cancer, the functional effects of many rare mutations but also of combinations of driver mutations are often unknown. Here, we perform a systems analysis of a model of EGFR‐mutated nonsmall cell lung cancer resistant to targeted therapy that integrates whole exome sequencing, global time‐course discovery phosphoproteomics and computational modeling to identify functionally relevant molecular alterations. Our approach allows for a complexity reduction from over 2, 000 genetic events potentially involved in mediating resistance to only 44 phosphoproteins and 35 topologically close genetic alterations. We perform single‐ and combination‐drug testing against the predicted phosphoproteins and discovered that targeting of HSPB1, DBNL and AKT1 showed potent antiproliferative effects overcoming resistance against EGFR‐inhibitory therapy. Our approach may therefore be used to complement mutational profiling to identify functionally relevant molecular aberrations and propose combination therapies across cancers. Abstract : What's new? While some drug resistance mutations occur in genes with functional relevance, the role of additional or rarer mutations in cancer therapy resistance is largely unclear. Here the authors used a systems biology approach to assess the role of molecular alterations in a model of drug‐resistant non‐small cell lung cancer. The approach reduced the complexity from over 2, 000 genetic events potentially involved in resistance to less than 44 phosphoproteins and 35 topologically close genetic alterations, a method that in the future may help identify combination therapies across cancers.