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Updated: Apr 22, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
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.
Abstract:
A key challenge in cancer precision oncology is the limited ability of genomic analyses to accurately predict changes in protein expression or function, even though proteins serve as the main targets of numerous modern therapies. Bridging this gap necessitates precise quantification of proteins and their post-translational modifications (PTMs). Recent advances in mass spectrometry (MS)-based proteomics now enable large-scale, quantitative characterization of proteins and PTMs in tumor tissues. To link genomic aberrations to cancer phenotypes, the emerging field of proteogenomics integrates proteomic data, including PTMs, with genomic, epigenomic, and transcriptomic information. This comprehensive approach offers a deeper understanding of cancer biology at multiple levels. This review highlights recent advancements in MS-based proteomics, key discoveries in cancer proteogenomics, and the transformative potential of this field in decoding the complexities of cancer across diverse dimensions.
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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