前列腺癌
生物标志物发现
过度诊断
前列腺
癌症
医学
前列腺切除术
生物标志物
蛋白质组学
计算生物学
蛋白质组
癌症生物标志物
肿瘤科
生物信息学
计算机科学
内科学
生物
基因
生物化学
作者
Ammara Muazzam,Davide Chiasserini,Janet Kelsall,Nophar Geifman,Anthony D. Whetton,Paul A. Townsend
出处
期刊:Cancers
[Multidisciplinary Digital Publishing Institute]
日期:2021-11-08
卷期号:13 (21): 5580-5580
被引量:8
标识
DOI:10.3390/cancers13215580
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.
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