Proteomic signatures of 16 major types of human cancer reveal universal and cancer-type-specific proteins for the identi
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RESEARCH
Proteomic signatures of 16 major types of human cancer reveal universal and cancer‑type‑specific proteins for the identification of potential therapeutic targets Yangying Zhou1† , T. Mamie Lih1†, Jianbo Pan1, Naseruddin Höti1, Mingming Dong1, Liwei Cao1, Yingwei Hu1, Kyung‑Cho Cho1, Shao‑Yung Chen1,2, Rodrigo Vargas Eguez1, Edward Gabrielson1,3, Daniel W. Chan1, Hui Zhang1,2,3,4* and Qing Kay Li1,3*
Abstract Background: Proteomic characterization of cancers is essential for a comprehensive understanding of key molecu‑ lar aberrations. However, proteomic profiling of a large cohort of cancer tissues is often limited by the conventional approaches. Methods: We present a proteomic landscape of 16 major types of human cancer, based on the analysis of 126 treatment-naïve primary tumor tissues, 94 tumor-matched normal adjacent tissues, and 12 normal tissues, using mass spectrometry-based data-independent acquisition approach. Results: In our study, a total of 8527 proteins were mapped to brain, head and neck, breast, lung (both small cell and non-small cell lung cancers), esophagus, stomach, pancreas, liver, colon, kidney, bladder, prostate, uterus and ovary cancers, including 2458 tissue-enriched proteins. Our DIA-based proteomic approach has characterized major human cancers and identified universally expressed proteins as well as tissue-type-specific and cancer-type-specific proteins. In addition, 1139 therapeutic targetable proteins and 21 cancer/testis (CT) antigens were observed. Conclusions: Our discoveries not only advance our understanding of human cancers, but also have implications for the design of future large-scale cancer proteomic studies to assist the development of diagnostic and/or therapeutic targets in multiple cancers. Keywords: Proteomic analysis, Data-independent acquisition, Tissue-enriched proteins, Cancer-associated proteins, Cancer therapeutic targets
*Correspondence: [email protected]; [email protected] † Yangying Zhou and T. Mamie Lih have contributed equally to this work 1 Department of Pathology, Johns Hopkins Medical Institutions, Baltimore, MD 21231, USA Full list of author information is available at the end of the article
Introduction Great efforts have been made to construct a comprehensive genomic landscape of human cancers using largescale genomic data [1, 2]. These studies, particularly the Cancer Genome Atlas (TCGA) project, focus on the discovery of the cellular origin and oncogenic processes of cancers [3–6]. These greatly advance our knowledge in
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