A proteogenomics data-driven knowledge base of human cancer.

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Cell Systems Pub Date : 2023-09-20 Epub Date: 2023-08-23 DOI:10.1016/j.cels.2023.07.007
Yuxing Liao, Sara R Savage, Yongchao Dou, Zhiao Shi, Xinpei Yi, Wen Jiang, Jonathan T Lei, Bing Zhang
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引用次数: 1

Abstract

By combining mass-spectrometry-based proteomics and phosphoproteomics with genomics, epi-genomics, and transcriptomics, proteogenomics provides comprehensive molecular characterization of cancer. Using this approach, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has characterized over 1,000 primary tumors spanning 10 cancer types, many with matched normal tissues. Here, we present LinkedOmicsKB, a proteogenomics data-driven knowledge base that makes consistently processed and systematically precomputed CPTAC pan-cancer proteogenomics data available to the public through ∼40,000 gene-, protein-, mutation-, and phenotype-centric web pages. Visualization techniques facilitate efficient exploration and reasoning of complex, interconnected data. Using three case studies, we illustrate the practical utility of LinkedOmicsKB in providing new insights into genes, phosphorylation sites, somatic mutations, and cancer phenotypes. With precomputed results of 19,701 coding genes, 125,969 phosphosites, and 256 genotypes and phenotypes, LinkedOmicsKB provides a comprehensive resource to accelerate proteogenomics data-driven discoveries to improve our understanding and treatment of human cancer. A record of this paper's transparent peer review process is included in the supplemental information.

Abstract Image

人类癌症的蛋白基因组学数据驱动知识库。
通过将基于质谱的蛋白质组学和磷酸蛋白质组学与基因组学、表基因组学和转录组学相结合,蛋白基因组学提供了癌症的全面分子表征。使用这种方法,临床蛋白质组肿瘤分析联合会(CPTAC)已经鉴定了1000多个原发肿瘤,涵盖10种癌症类型,其中许多具有匹配的正常组织。在这里,我们展示了LinkedOmicsKB,这是一个蛋白基因组学数据驱动的知识库,通过约40000个以基因、蛋白质、突变和表型为中心的网页,向公众提供一致处理和系统预计算的CPTAC泛癌蛋白基因组学数据。可视化技术有助于对复杂的、相互关联的数据进行有效的探索和推理。通过三个案例研究,我们阐明了LinkedOmicsKB在提供对基因、磷酸化位点、体细胞突变和癌症表型的新见解方面的实用性。LinkedOmicsKB预计算了19701个编码基因、125969个磷酸位点和256种基因型和表型的结果,为加速蛋白基因组学数据驱动的发现提供了全面的资源,以提高我们对人类癌症的理解和治疗。本文的透明同行评审过程记录包含在补充信息中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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