Dataset Information

Disease-related cellular protein networks differentially affected under different EGFR mutations in lung adenocarcinoma.

ABSTRACT: It is unclear how epidermal growth factor receptor EGFR major driver mutations (L858R or Ex19del) affect downstream molecular networks and pathways. This study aimed to provide information on the influences of these mutations. The study assessed 36 protein expression profiles of lung adenocarcinoma (Ex19del, nine; L858R, nine; no Ex19del/L858R, 18). Weighted gene co-expression network analysis together with analysis of variance-based screening identified 13 co-expressed modules and their eigen proteins. Pathway enrichment analysis for the Ex19del mutation demonstrated involvement of SUMOylation, epithelial and mesenchymal transition, ERK/mitogen-activated protein kinase signalling via phosphorylation and Hippo signalling. Additionally, analysis for the L858R mutation identified various pathways related to cancer cell survival and death. With regard to the Ex19del mutation, ROCK, RPS6KA1, ARF1, IL2RA and several ErbB pathways were upregulated, whereas AURK and GSKIP were downregulated. With regard to the L858R mutation, RB1, TSC22D3 and DOCK1 were downregulated, whereas various networks, including VEGFA, were moderately upregulated. In all mutation types, CD80/CD86 (B7), MHC, CIITA and IFGN were activated, whereas CD37 and SAFB were inhibited. Costimulatory immune-checkpoint pathways by B7/CD28 were mainly activated, whereas those by PD-1/PD-L1 were inhibited. Our findings may help identify potential therapeutic targets and develop therapeutic strategies to improve patient outcomes.

SUBMITTER: Nishimura T

PROVIDER: S-EPMC7331587 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Disease-related cellular protein networks differentially affected under different EGFR mutations in lung adenocarcinoma.

Nishimura Toshihide T Nakamura Haruhiko H Yachie Ayako A Hase Takeshi T Fujii Kiyonaga K Koizumi Hirotaka H Naruki Saeko S Takagi Masayuki M Matsuoka Yukiko Y Furuya Naoki N Kato Harubumi H Saji Hisashi H

Scientific reports 20200702 1

It is unclear how epidermal growth factor receptor EGFR major driver mutations (L858R or Ex19del) affect downstream molecular networks and pathways. This study aimed to provide information on the influences of these mutations. The study assessed 36 protein expression profiles of lung adenocarcinoma (Ex19del, nine; L858R, nine; no Ex19del/L858R, 18). Weighted gene co-expression network analysis together with analysis of variance-based screening identified 13 co-expressed modules and their eigen p ...[more]

PMID: 32616892

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Project description:Epidermal growth factor receptor EGFR major driver mutations may affect downstream molecular networks and pathways, which would influence treatment outcomes of non-small cell lung cancer (NSCLC). This study aimed to unveil profiles of mutant proteins expressed in lung adenocarcinomas of 36 patients harboring representative driver EGFR mutations (Ex19del, nine; L858R, nine; no Ex19del/L858R, 18). Surprisingly, the orthogonal partial least squares discriminant analysis performed for identified mutant proteins demonstrated the profound differences in distance among the different EGFR mutation groups, suggesting that cancer cells harboring L858R or Ex19del emerge from cellular origins different from L858R/Ex19del-negative cells. Weighted gene coexpression network analysis, together with over-representative analysis, identified 18 coexpressed modules and their eigen proteins. Pathways enriched differentially for both the L858R and Ex19del mutations included carboxylic acid metabolic process, cell cycle, developmental biology, cellular responses to stress, mitotic prophase, cell proliferation, growth, epithelial to mesenchymal transition (EMT), and immune system. The IPA causal network analysis identified the highly activated networks of PARPBP, HOXA1, and APH1 under the L858R mutation, whereas those of ASGR1, APEX1, BUB1, and MAPK10 were highly activated under the Ex19del mutation. Interestingly, the downregulated causal network of osimertinib intervention showed the highest significance in overlap p-value among most causal networks predicted under the L858R mutation. We also identified the causal network of MAPK interacting serine/threonine kinase 1/2 (MNK1/2) highly activated differentially under the L858R mutation. Tumor-suppressor AMOT, a component of the Hippo pathways, was highly inhibited commonly under both L858R and Ex19del mutations. Our results could identify disease-related protein molecular networks from the landscape of single amino acid variants. Our findings may help identify potential therapeutic targets and develop therapeutic strategies to improve patient outcomes.

Dataset Information

Disease-related cellular protein networks differentially affected under different EGFR mutations in lung adenocarcinoma.

Publications

Disease-related cellular protein networks differentially affected under different EGFR mutations in lung adenocarcinoma.

Similar Datasets

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