Proteomic profiling of the cancer cell secretome: informing clinical research. (2nd September 2017)

• Record Type: Journal Article
• Authors: Hsiao, Yung-Chin; Chu, Lichieh Julie; Chen, Jeng-Ting; Yeh, Ta-Sen; Yu, Jau-Song
• Is Part Of: Expert review of proteomics. Volume 14:Number 9(2017)
• Page Start: 737
• Page End: 756
• Publication Date: 2017-09-02
• Subjects: Cancer cell secretome -- biomarker -- therapeutic target -- low-molecular-mass protein -- cancer microenvironments -- clinical trial; Proteins -- Biotechnology -- Periodicals; Proteomics -- Periodicals; 572.6
• DOI: 10.1080/14789450.2017.1353913
• Languages: English
• ISSNs: 1478-9450

Abstract

ABSTRACT: Introduction : Cancer represents one of the major causes of human deaths. Identification of proteins as biomarkers for early detection of cancer and therapeutic targets for cancer treatment are important issues in precision medicine. Secretome of cancer cells represents the collection of proteins secreted or shed from cancer cells. Proteomic profiling of the cancer cell secretome has been proven to be a convenient and efficient way to discover cancer biomarker and/or therapeutic targets. Areas covered : There have been numerous reviews describing the history and application of secretome analysis in cancer biomarker/therapeutic target research. The present review focuses on the technological advancement for profiling low-molecular-mass proteins in secretome, the latest information regarding the new candidate biomarkers and molecular mechanisms discovered on the basis of cancer cell secretome analysis, as well as the previously discovered candidate biomarkers that enter into clinical trials. Expert commentary : Current technologies for protein sample preparation/separation and MS-based protein identification have allowed in-depth analysis of cancer cell secretome. Future efforts should focus on the comprehensiveness of cancer cell secretome, meta-analysis of different secretome datasets and integrated analysis via combining other omics datasets, as well as the incorporation of MS-based biomarker verification pipeline into both preclinical studies and clinical trials.