J Robert O'Neill, Marcos Yébenes Mayordomo, Goran Mitulović, Sofian Al Shboul, Georges Bedran, Jakub Faktor, Lenka Hernychova, Lukas Uhrik, Maria Gómez-Herranz, Mikołaj Kocikowski, Vicki Save, Bořivoj Vojtěšek, Mark J Arends, Ted Hupp, Javier Antonio Alfaro
{"title":"食管腺癌的多组学分析发现了候选治疗靶点和癌症选择性转录后调控。","authors":"J Robert O'Neill, Marcos Yébenes Mayordomo, Goran Mitulović, Sofian Al Shboul, Georges Bedran, Jakub Faktor, Lenka Hernychova, Lukas Uhrik, Maria Gómez-Herranz, Mikołaj Kocikowski, Vicki Save, Bořivoj Vojtěšek, Mark J Arends, Ted Hupp, Javier Antonio Alfaro","doi":"10.1016/j.mcpro.2024.100764","DOIUrl":null,"url":null,"abstract":"<p><p>Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and therapeutic targets. Despite extensive efforts to understand the somatic mutations associated with EAC over the past decade, a gap remains in understanding how the atlas of genomic aberrations in this cancer impacts the proteome and which somatic variants are of importance for the disease phenotype. We performed a quantitative proteomic analysis of 23 EACs and matched adjacent normal esophageal and gastric tissues. We explored the correlation of transcript and protein abundance using tissue-matched RNA-seq and proteomic data from seven patients and further integrated these data with a cohort of EAC RNA-seq data (n = 264 patients), EAC whole-genome sequencing (n = 454 patients), and external published datasets. We quantified protein expression from 5879 genes in EAC and patient-matched normal tissues. Several biomarker candidates with EAC-selective expression were identified, including the transmembrane protein GPA33. We further verified the EAC-enriched expression of GPA33 in an external cohort of 115 patients and confirm this as an attractive diagnostic and therapeutic target. To further extend the insights gained from our proteomic data, an integrated analysis of protein and RNA expression in EAC and normal tissues revealed several genes with poorly correlated protein and RNA abundance, suggesting posttranscriptional regulation of protein expression. These outlier genes, including SLC25A30, TAOK2, and AGMAT, only rarely demonstrated somatic mutation, suggesting post-transcriptional drivers for this EAC-specific phenotype. AGMAT was demonstrated to be overexpressed at the protein level in EAC compared to adjacent normal tissues with an EAC-selective, post-transcriptional mechanism of regulation of protein abundance proposed. Integrated analysis of proteome, transcriptome, and genome in EAC has revealed several genes with tumor-selective, posttranscriptional regulation of protein expression, which may be an exploitable vulnerability.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"100764"},"PeriodicalIF":6.1000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11245951/pdf/","citationCount":"0","resultStr":"{\"title\":\"Multi-Omic Analysis of Esophageal Adenocarcinoma Uncovers Candidate Therapeutic Targets and Cancer-Selective Posttranscriptional Regulation.\",\"authors\":\"J Robert O'Neill, Marcos Yébenes Mayordomo, Goran Mitulović, Sofian Al Shboul, Georges Bedran, Jakub Faktor, Lenka Hernychova, Lukas Uhrik, Maria Gómez-Herranz, Mikołaj Kocikowski, Vicki Save, Bořivoj Vojtěšek, Mark J Arends, Ted Hupp, Javier Antonio Alfaro\",\"doi\":\"10.1016/j.mcpro.2024.100764\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and therapeutic targets. Despite extensive efforts to understand the somatic mutations associated with EAC over the past decade, a gap remains in understanding how the atlas of genomic aberrations in this cancer impacts the proteome and which somatic variants are of importance for the disease phenotype. We performed a quantitative proteomic analysis of 23 EACs and matched adjacent normal esophageal and gastric tissues. We explored the correlation of transcript and protein abundance using tissue-matched RNA-seq and proteomic data from seven patients and further integrated these data with a cohort of EAC RNA-seq data (n = 264 patients), EAC whole-genome sequencing (n = 454 patients), and external published datasets. We quantified protein expression from 5879 genes in EAC and patient-matched normal tissues. Several biomarker candidates with EAC-selective expression were identified, including the transmembrane protein GPA33. 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Multi-Omic Analysis of Esophageal Adenocarcinoma Uncovers Candidate Therapeutic Targets and Cancer-Selective Posttranscriptional Regulation.
Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and therapeutic targets. Despite extensive efforts to understand the somatic mutations associated with EAC over the past decade, a gap remains in understanding how the atlas of genomic aberrations in this cancer impacts the proteome and which somatic variants are of importance for the disease phenotype. We performed a quantitative proteomic analysis of 23 EACs and matched adjacent normal esophageal and gastric tissues. We explored the correlation of transcript and protein abundance using tissue-matched RNA-seq and proteomic data from seven patients and further integrated these data with a cohort of EAC RNA-seq data (n = 264 patients), EAC whole-genome sequencing (n = 454 patients), and external published datasets. We quantified protein expression from 5879 genes in EAC and patient-matched normal tissues. Several biomarker candidates with EAC-selective expression were identified, including the transmembrane protein GPA33. We further verified the EAC-enriched expression of GPA33 in an external cohort of 115 patients and confirm this as an attractive diagnostic and therapeutic target. To further extend the insights gained from our proteomic data, an integrated analysis of protein and RNA expression in EAC and normal tissues revealed several genes with poorly correlated protein and RNA abundance, suggesting posttranscriptional regulation of protein expression. These outlier genes, including SLC25A30, TAOK2, and AGMAT, only rarely demonstrated somatic mutation, suggesting post-transcriptional drivers for this EAC-specific phenotype. AGMAT was demonstrated to be overexpressed at the protein level in EAC compared to adjacent normal tissues with an EAC-selective, post-transcriptional mechanism of regulation of protein abundance proposed. Integrated analysis of proteome, transcriptome, and genome in EAC has revealed several genes with tumor-selective, posttranscriptional regulation of protein expression, which may be an exploitable vulnerability.
期刊介绍:
The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action.
The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data.
Scope:
-Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights
-Novel experimental and computational technologies
-Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes
-Pathway and network analyses of signaling that focus on the roles of post-translational modifications
-Studies of proteome dynamics and quality controls, and their roles in disease
-Studies of evolutionary processes effecting proteome dynamics, quality and regulation
-Chemical proteomics, including mechanisms of drug action
-Proteomics of the immune system and antigen presentation/recognition
-Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease
-Clinical and translational studies of human diseases
-Metabolomics to understand functional connections between genes, proteins and phenotypes