Pan-cancer secreted proteome and skeletal muscle regulation: insight from a proteogenomic data-driven knowledge base

IF 3.9 4区 生物学 Q1 GENETICS & HEREDITY Functional & Integrative Genomics Pub Date : 2025-01-15 DOI:10.1007/s10142-024-01524-7
Traci L. Parry, L. Anne Gilmore, Andy V. Khamoui
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Abstract

Large-scale, pan-cancer analysis is enabled by data driven knowledge bases that link tumor molecular profiles with phenotypes. A debilitating cancer-related phenotype is skeletal muscle loss, or cachexia, which occurs partly from tumor products secreted into circulation. Using the LinkedOmicsKB knowledge base assembled from the Clinical Proteomics Tumor Analysis Consortium proteogenomic analysis, along with catalogs of human secretome proteins, ligand-receptor pairs and molecular signatures, we sought to identify candidate pan-cancer proteins secreted to blood that could regulate skeletal muscle phenotypes in multiple solid cancers. Tumor proteins having significant pan-cancer associations with muscle were referenced against secretome proteins secreted to blood from the Human Protein Atlas, then verified as increased in paired tumor vs. normal tissues in pan-cancer manner. This workflow revealed seven secreted proteins from cancers afflicting kidneys, head and neck, lungs and pancreas that classified as protein-binding activity modulator, extracellular matrix protein or intercellular signaling molecule. Concordance of these biomarkers with validated molecular signatures of cachexia and senescence supported relevance to muscle and cachexia disease biology, and high tumor expression of the biomarker set associated with lower overall survival. In this article, we discuss avenues by which skeletal muscle and cachexia may be regulated by these candidate pan-cancer proteins secreted to blood, and conceptualize a strategy that considers them collectively as a biomarker signature with potential for refinement by data analytics and radiogenomics for predictive testing of future risk in a non-invasive, blood-based panel amenable to broad uptake and early management.

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泛癌分泌蛋白质组和骨骼肌调节:洞察从蛋白质基因组数据驱动的知识库
通过将肿瘤分子图谱与表型联系起来的数据驱动知识库,可以实现大规模的泛癌症分析。一种使人衰弱的癌症相关表型是骨骼肌损失,或恶病质,部分原因是肿瘤产物分泌到循环系统中。利用临床蛋白质组学肿瘤分析联盟蛋白质基因组学分析的LinkedOmicsKB知识库,以及人类分泌组蛋白目录,配体-受体对和分子特征,我们试图确定可调节多种实体癌症骨骼肌表型的候选泛癌蛋白分泌到血液中。将与肌肉具有显著泛癌相关性的肿瘤蛋白与人类蛋白质图谱中分泌到血液中的分泌组蛋白进行比较,然后验证在配对肿瘤组织中与正常组织相比以泛癌方式增加。该工作流程揭示了7种来自肾脏、头颈部、肺部和胰腺癌症的分泌蛋白,它们被归类为蛋白质结合活性调节剂、细胞外基质蛋白或细胞间信号分子。这些生物标志物与恶病质和衰老的有效分子特征的一致性支持了肌肉和恶病质疾病生物学的相关性,以及生物标志物组的高肿瘤表达与较低的总生存率相关。在本文中,我们讨论了骨骼肌和恶病质可能被这些候选泛癌蛋白分泌到血液中的途径,并概念化了一种策略,该策略将它们共同视为一种生物标志物特征,具有通过数据分析和放射基因组学进行改进的潜力,可以在非侵入性、基于血液的小组中对未来风险进行预测测试,从而适用于广泛摄取和早期管理。
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来源期刊
CiteScore
3.50
自引率
3.40%
发文量
92
审稿时长
2 months
期刊介绍: Functional & Integrative Genomics is devoted to large-scale studies of genomes and their functions, including systems analyses of biological processes. The journal will provide the research community an integrated platform where researchers can share, review and discuss their findings on important biological questions that will ultimately enable us to answer the fundamental question: How do genomes work?
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