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

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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.", "claims": [{"id": "claim-method", "statement": "Random Forests (RF) were used to choose features, with data split 70:30 (training/testing) and ntree set to 1000 (Rstudio version 4.0.2).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34771740", "locator": "sections[16] \"4.8. 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Reviewer account details are as follows: Username: reviewer_pxd028651@ebi.ac.uk and Password: 4kYGKQF6."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study created a comprehensive prostate cancer serum spectral library containing 114,684 transitions, 18,479 peptides, and 1227 proteins, and its use in an independent cohort identified 404 proteins at a 1% false discovery rate.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34771740", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The spectral library contains 114,684 transitions, which equates to 18,479 peptides translated into 1227 proteins."}, {"asset": "source:pmid:34771740", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "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."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The study created a comprehensive prostate cancer serum spectral library containing 114,684 transitions, 18,479 peptides, and 1227 proteins, and its use in an independent cohort identified 404 proteins at a 1% false discovery rate.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34771740"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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