Proteogenomic systems analysis identifies targeted therapy resistance mechanisms in EGFR-mutated lung cancer.
Int J Cancer
; 144(3): 545-557, 2019 02 01.
Article
em En
| MEDLINE
| ID: mdl-30183078
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.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Carcinoma Pulmonar de Células não Pequenas
/
Inibidores de Proteínas Quinases
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Neoplasias Pulmonares
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Proteínas de Neoplasias
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article