A Prostate Cancer Proteomics Database for SWATH-MS Based Protein Quantification

Cancers

Davide Chiasserini¹  Nophar Geifman²  Anthony D. Whetton³  Ammara Muazzam³  Paul A. Townsend³  Janet Kelsall⁴ 

[1] Department of Medicine and Surgery, Section of Physiology and Biochemistry, University of Perugia, 06132 Perugia, Italy;Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK;Manchester Cancer Research Centre, Division of Cancer Sciences, Faculty of Biology, School of Medical Sciences, Medicine and Health, University of Manchester, Wilmslow Road, Manchester M20 4GJ, UK;Stoller Biomarker Discovery Centre, Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK;

关键词: prostate cancer;    spectral library;    blood proteomics;    protein;    peptide;    mass spectrometry;   

DOI  :  10.3390/cancers13215580

来源: DOAJ

【 摘 要 】

Prostate cancer is the most frequent form of cancer in men, accounting for more than one-third of all cases. Current screening techniques, such as PSA testing used in conjunction with routine procedures, lead to unnecessary biopsies and the discovery of low-risk tumours, resulting in overdiagnosis. SWATH-MS is a well-established data-independent (DI) method requiring prior knowledge of targeted peptides to obtain valuable information from SWATH maps. In response to the growing need to identify and characterise protein biomarkers for prostate cancer, this study explored a spectrum source for targeted proteome analysis of blood samples. We created a comprehensive prostate cancer serum spectral library by combining data-dependent acquisition (DDA) MS raw files from 504 patients with low, intermediate, or high-grade prostate cancer and healthy controls, as well as 304 prostate cancer-related protein in silico assays. The spectral library contains 114,684 transitions, which equates to 18,479 peptides translated into 1227 proteins. The robustness and accuracy of the spectral library were assessed to boost confidence in the identification and quantification of prostate cancer-related proteins across an independent cohort, resulting in the identification of 404 proteins. This unique database can facilitate researchers to investigate prostate cancer protein biomarkers in blood samples. In the real-world use of the spectrum library for biomarker detection, using a signature of 17 proteins, a clear distinction between the validation cohort’s pre- and post-treatment groups was observed. Data are available via ProteomeXchange with identifier PXD028651.

【 授权许可】

Unknown