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Updated: Mar 12, 2026
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
How may targeted proteomics complement genomic data in breast cancer?
Mathilde Guerin1,2, Anthony Gonçalves1,2, Yves Toiron2
1a Aix Marseille Univ, CNRS, INSERM, Institut Paoli-Calmettes, CRCM, Marseille Protéomique , Marseille , France.
Introduction:
Breast cancer (BC) is the most common female cancer in the world and was recently deconstructed in different molecular entities. Although most of the recent assays to characterize tumors at the molecular level are genomic-based, proteins are the actual executors of cellular functions and represent the vast majority of targets for anticancer drugs. Accumulated data has demonstrated an important level of quantitative and qualitative discrepancies between genomic/transcriptomic alterations and their protein counterparts, mostly related to the large number of post-translational modifications. Areas covered: This review will present novel proteomics technologies such as Reverse Phase Protein Array (RPPA) or mass-spectrometry (MS) based approaches that have emerged and that could progressively replace old-fashioned methods (e.g. immunohistochemistry, ELISA, etc.) to validate proteins as diagnostic, prognostic or predictive biomarkers, and eventually monitor them in the routine practice. Expert commentary: These different targeted proteomic approaches, able to complement genomic data in BC and characterize tumors more precisely, will permit to go through a more personalized treatment for each patient and tumor.
Insights
Novel proteomics technologies offer a more precise understanding of breast cancer (BC) by analyzing proteins, which are key drug targets. These advanced methods complement genomic data for personalized BC treatment.
Area of Science:
- Oncology
- Proteomics
- Biomarker Discovery
Background:
- Breast cancer (BC) is the most prevalent female cancer globally, with molecular subtypes identified.
- Genomic and transcriptomic data often show discrepancies with protein expression due to post-translational modifications.
- Proteins are crucial for cellular functions and represent primary targets for anticancer drugs.
Purpose of the Study:
- To review novel proteomics technologies for breast cancer biomarker validation.
- To highlight the potential of these technologies in complementing genomic data for precise tumor characterization.
Main Methods:
- Discussion of Reverse Phase Protein Array (RPPA) and mass-spectrometry (MS) based proteomics.
- Comparison with traditional methods like immunohistochemistry and ELISA.
- Focus on targeted proteomic approaches.
Main Results:
- Proteomics offers a more accurate reflection of cellular functions compared to genomics alone.
- Novel MS and RPPA technologies provide enhanced capabilities for protein analysis.
- These methods can validate proteins as diagnostic, prognostic, and predictive biomarkers.
Conclusions:
- Targeted proteomic approaches are essential for precise breast cancer characterization.
- Complementing genomic data with proteomics enables more personalized treatment strategies.
- Advanced proteomics can facilitate the routine monitoring of biomarkers in clinical practice.
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