Dataset Information

Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis.

ABSTRACT: To understand drug combination effect, it is necessary to decipher the interactions between drug targets-many of which are signaling molecules. Previously, such signaling pathway models are largely based on the compilation of literature data from heterogeneous cellular contexts. Indeed, de novo reconstruction of signaling interactions from large-scale molecular profiling is still lagging, compared to similar efforts in transcriptional and protein-protein interaction networks. To address this challenge, we introduce a novel algorithm for the systematic inference of protein kinase pathways, and applied it to published mass spectrometry-based phosphotyrosine profile data from 250 lung adenocarcinoma (LUAD) samples. The resulting network includes 43 TKs and 415 inferred, LUAD-specific substrates, which were validated at >60% accuracy by SILAC assays, including "novel' substrates of the EGFR and c-MET TKs, which play a critical oncogenic role in lung cancer. This systematic, data-driven model supported drug response prediction on an individual sample basis, including accurate prediction and validation of synergistic EGFR and c-MET inhibitor activity in cells lacking mutations in either gene, thus contributing to current precision oncology efforts.

SUBMITTER: Bansal M

PROVIDER: S-EPMC6322741 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis.

Bansal Mukesh M He Jing J Peyton Michael M Kustagi Manjunath M Iyer Archana A Comb Michael M White Michael M Minna John D JD Califano Andrea A

PloS one 20190107 1

To understand drug combination effect, it is necessary to decipher the interactions between drug targets-many of which are signaling molecules. Previously, such signaling pathway models are largely based on the compilation of literature data from heterogeneous cellular contexts. Indeed, de novo reconstruction of signaling interactions from large-scale molecular profiling is still lagging, compared to similar efforts in transcriptional and protein-protein interaction networks. To address this cha ...[more]

PMID: 30615629

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Project description:BackgroundLung adenocarcinoma (LUAD) is the predominant histological subtype of lung cancer and the leading cause of cancer-related mortality. Identifying effective drug targets is crucial for advancing LUAD treatment strategies.MethodsThis study employed proteome-wide Mendelian randomization (MR) and colocalization analyses. We collected data on 1394 plasma proteins from a protein quantitative trait loci (pQTL) study involving 4907 individuals. Genetic associations with LUAD were derived from the Transdisciplinary Research in Cancer of the Lung (TRICL) study, including 11,245 cases and 54,619 controls. We integrated pQTL and LUAD genome-wide association studies (GWASs) data to identify candidate proteins. MR utilizes single nucleotide polymorphisms (SNPs) as genetic instruments to estimate the causal effect of exposure on outcome, while Bayesian colocalization analysis determines the probability of shared causal genetic variants between traits. Our study applied these methods to assess causality between plasma proteins and LUAD. Furthermore, we employed a two-step MR to quantify the proportion of risk factors mediated by proteins on LUAD. Finally, protein-protein interaction (PPI) analysis elucidated potential links between proteins and current LUAD medications.ResultsWe identified nine plasma proteins significantly associated with LUAD. Increased levels of ALAD, FLT1, ICAM5, and VWC2 exhibited protective effects, with odds ratios of 0.79 (95% CI 0.72-0.87), 0.39 (95% CI 0.28-0.55), 0.91 (95% CI 0.72-0.87), and 0.85 (95% CI 0.79-0.92), respectively. Conversely, MDGA2 (OR, 1.13; 95% CI 1.08-1.19), NTM (OR, 1.12; 95% CI 1.09-1.16), PMM2 (OR, 1.35; 95% CI 1.18-1.53), RNASET2 (OR, 1.15; 95% CI 1.08-1.21), and TFPI (OR, 4.58; 95% CI 3.02-6.94) increased LUAD risk. Notably, none of the nine proteins showed evidence of reverse causality. Bayesian colocalization indicated that RNASET2, TFPI, and VWC2 shared the same variant with LUAD. Furthermore, NTM and FLT1 demonstrated interactions with targets of current LUAD medications. Additionally, FLT1 and TFPI are currently under evaluation as therapeutic targets, while NTM, RNASET2, and VWC2 are potentially druggable. These findings shed light on LUAD pathogenesis, highlighting the tumor-promoting effects of RNASET2, TFPI, and NTM, along with the protective effects of VWC2 and FLT1, providing a significant biological foundation for future LUAD therapeutic targets.ConclusionsOur proteome-wide MR analysis highlighted RNASET2, TFPI, VWC2, NTM, and FLT1 as potential drug targets for further clinical investigation in LUAD. However, the specific mechanisms by which these proteins influence LUAD remain elusive. Targeting these proteins in drug development holds the potential for successful clinical trials, providing a pathway to prioritize and reduce costs in LUAD therapeutics.

Project description:BackgroundChronic Lymphocytic Leukemia (CLL) pathogenesis has been linked to the prolonged survival and/or apoptotic resistance of leukemic B cells in vivo, and is thought to be due to enhanced survival signaling responses to environmental factors that protect CLL cells from spontaneous and chemotherapy-induced death. Although normally associated with cell migration, the chemokine, CXCL12, is one of the factors known to support the survival of CLL cells. Thus, the signaling pathways activated by CXCL12 and its receptor, CXCR4, were investigated as components of these pathways and may represent targets that if inhibited, could render resistant CLL cells more susceptible to chemotherapy.Methodology/principal findingsTo determine the downstream signaling targets that contribute to the survival effects of CXCL12 in CLL, we took a phosphoproteomics approach to identify and compare phosphopeptides in unstimulated and CXCL12-stimulated primary CLL cells. While some of the survival pathways activated by CXCL12 in CLL are known, including Akt and ERK1/2, this approach enabled the identification of additional signaling targets and novel phosphoproteins that could have implications in CLL disease and therapy. In addition to the phosphoproteomics results, we provide evidence from western blot validation that the tumor suppressor, programmed cell death factor 4 (PDCD4), is a previously unidentified phosphorylation target of CXCL12 signaling in all CLL cells probed. Additionally, heat shock protein 27 (HSP27), which mediates anti-apoptotic signaling and has previously been linked to chemotherapeutic resistance, was detected in a subset (approximately 25%) of CLL patients cells examined.Conclusions/significanceSince PDCD4 and HSP27 have previously been associated with cancer and regulation of cell growth and apoptosis, these proteins may have novel implications in CLL cell survival and represent potential therapeutic targets. PDCD4 also represents a previously unknown signaling target of chemokine receptors; therefore, these observations increase our understanding of alternative pathways to migration that may be activated or inhibited by chemokines in the context of cancer cell survival.

Project description:BackgroundA growing body of evidence indicates that long non-coding RNAs (lncRNAs) can act as competitive endogenous RNAs (ceRNAs) to bind to microRNAs (miRNAs), thereby affecting and regulating the expression of target genes. The lncRNA-miRNA-mRNA ceRNA network has been theorized to play an indispensable role in many types of tumors. However, the role of the lncRNA-related ceRNA regulatory network in lung adenocarcinoma (LUAD) remains unclear.MethodsWe downloaded the RNAseq and miRNAseq data of LUAD from The Cancer Genome Atlas (TCGA) data portal and identified differentially expressed lncRNAs (DElncRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) between LUAD and corresponding paracancerous tissues by using the edgeR package of R software. We constructed the lncRNA-miRNA-mRNA ceRNA network by using Cytoscape (version 3.7.2) on the basis of the interaction generated from the miRcode, miRTarBase, miRDB, and TargetScan databases. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed with DAVID 6.8 bioinformatics resources and plotted by using the ggplot2 package in R. The effect of genes on LUAD prognosis was assessed by applying the survival package in R in accordance with the Kaplan-Meier curve.ResultsIn total, 1645 DElncRNAs, 117 DEmiRNAs, and 2729 DEmRNAs were identified in LUAD. The LUAD-specific ceRNA network was composed of 157 nodes and 378 edges (329 DElncRNA-DEmiRNA interactions and 49 DEmiRNA-DEmRNA interactions). GO and KEGG pathway annotations suggested that the LUAD-specific ceRNA network was related to tumor-related molecular functions and pathways. Seven lncRNAs (DISC1-IT1, SYNPR-AS1, H19, LINC00460, LINC00518, DSCR10, and STEAP2-AS1), one miRNA (hsa-mir-31), and 16 mRNAs (ATAD2, OSCAR, KIF23, E2F7, PFKP, MCM4, CEP55, CBX2, CCNE1, CLSPN, CCNB1, CDC25A, EZH2, CHEK1, SLC7A11, and PBK) were revealed to be significantly correlated with overall survival.ConclusionIn this study, we described the potential regulatory mechanism of the progression of LUAD. We proposed a new lncRNA-miRNA-mRNA ceRNA network that could help further explore the molecular mechanisms of LUAD.

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Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis.

Publications

Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis.

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