Proteomics

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Proteogenomic systems analysis identifies targeted therapy resistance mechanisms in EGFR-mutated lung cancer


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 non-small 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 anti-proliferative 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.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Lung, Epithelial Cell

DISEASE(S): Non-small Cell Lung Carcinoma

SUBMITTER: Daniel Heim  

LAB HEAD: Frederick Klauschen

PROVIDER: PXD009996 | Pride | 2018-07-02

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
D131128_002_131128173215.raw Raw
D131128_003.raw Raw
D131128_005.raw Raw
D131128_006.raw Raw
D140207_007.raw Raw
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Publications

Proteogenomic systems analysis identifies targeted therapy resistance mechanisms in EGFR-mutated lung cancer.

Treue Denise D   Bockmayr Michael M   Stenzinger Albrecht A   Heim Daniel D   Hester Svenja S   Klauschen Frederick F  

International journal of cancer 20181108 3


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 t  ...[more]

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