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Related Concept Videos

Proteomics01:33

Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Phosphopeptide Enrichment Coupled with Label-free Quantitative Mass Spectrometry to Investigate the Phosphoproteome in Prostate Cancer
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A Prostate Cancer Proteomics Database for SWATH-MS Based Protein Quantification.

Ammara Muazzam1,2, Davide Chiasserini3, Janet Kelsall2

  • 1Manchester 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.

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|November 13, 2021
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Summary

This study developed a comprehensive prostate cancer serum spectral library to identify protein biomarkers in blood. The library aids in distinguishing between pre- and post-treatment groups, improving prostate cancer diagnosis.

Keywords:
SWATH-MSblood proteomicsmass spectrometrypeptideprostate cancerproteinspectral library

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Area of Science:

  • Proteomics
  • Biomarker Discovery
  • Cancer Research

Background:

  • Prostate cancer is the most common cancer in men, with current screening methods like PSA testing leading to overdiagnosis.
  • There is a need for improved methods to identify and characterize protein biomarkers for accurate prostate cancer diagnosis and management.

Purpose of the Study:

  • To create a comprehensive serum spectral library for targeted proteome analysis in prostate cancer.
  • To identify and validate protein biomarkers for prostate cancer detection and monitoring using blood samples.

Main Methods:

  • A prostate cancer serum spectral library was constructed using data-dependent acquisition (DDA) mass spectrometry (MS) data from 504 patients and in silico assays.
  • The library contains 114,684 transitions, representing 18,479 peptides and 1227 proteins.
  • Spectral library robustness and accuracy were validated on an independent cohort, identifying 404 proteins.

Main Results:

  • A spectral library of 1227 proteins was generated from 504 prostate cancer patients and controls.
  • Validation identified 404 proteins, demonstrating the library's accuracy for prostate cancer biomarker discovery.
  • A 17-protein signature effectively distinguished pre- and post-treatment groups in a validation cohort.

Conclusions:

  • The developed spectral library is a valuable resource for researchers investigating prostate cancer protein biomarkers in blood.
  • This approach enhances the identification and quantification of potential diagnostic and prognostic markers for prostate cancer.
  • The study demonstrates the potential of targeted proteome analysis for clinical applications in prostate cancer management.