Proteogenomics: decoding cancer in multiple dimensions

Qian Liu1, Yimin Chen2,3, Hu Zhou4,5,6

  • 1Analytical Research Center for Organic and Biological Molecules, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China. liuqian@simm.ac.cn.

Medscience
|April 20, 2026
PubMed

Insights

Precision oncology faces challenges linking genomics to protein function. Proteogenomics, integrating mass spectrometry-based proteomics with other

Area of Science:

  • Proteomics and Genomics
  • Cancer Biology
  • Mass Spectrometry

Background:

  • Genomic analyses in precision oncology struggle to predict protein expression and function, crucial for targeted therapies.
  • Precise quantification of proteins and post-translational modifications (PTMs) is needed to bridge this gap.
  • Mass spectrometry (MS)-based proteomics offers large-scale, quantitative characterization of proteins and PTMs in tumors.

Purpose of the Study:

  • To review advancements in MS-based proteomics for cancer research.
  • To highlight key discoveries in cancer proteogenomics.
  • To discuss the potential of proteogenomics in understanding cancer complexity.

Main Methods:

  • Integration of proteomic data (including PTMs) with genomic, epigenomic, and transcriptomic information.
  • Utilizing mass spectrometry for large-scale, quantitative protein and PTM characterization.
  • Reviewing recent literature on MS-based proteomics and cancer proteogenomics.

Main Results:

  • MS-based proteomics enables quantitative characterization of proteins and PTMs in tumor tissues.
  • Proteogenomics integrates multi-omics data for a deeper understanding of cancer biology.
  • Recent advancements facilitate linking genomic aberrations to cancer phenotypes.

Conclusions:

  • Proteogenomics offers a comprehensive approach to decoding cancer complexity at multiple biological levels.
  • This integrated field has transformative potential for precision oncology.
  • Advancements in MS-based proteomics are key drivers of progress in cancer proteogenomics.

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