International Journal of Biotechnology and Computational Science

Characterizing CA125 Isoforms in Ovarian Cancer Using Proteomics, Phosphoproteomics and Consensus Clustering

Authors
  • Israa M Shamkh

    Chief Computational Chemistry Department EBO Bio Solution Company, London, EC1V2NX, United Kingdom
    Author
  • Ihosvany Camps

    Full Professor. Department of Physics, Federal University of Alfenas, Alfenas, MG, Brazil
    Author
Keywords:
consensus clustering, TP53, BRCA1, PIK3CA, AKT1, KRAS, MUC16, ovarian cancer, CA125, proteomics, phosphoproteomics
Abstract

The development of chemoresistance and late-stage detection of ovarian cancer pose a considerable therapeutic challenge. Although there are many isoforms of CA125 and post-translational changes, it is still the accepted biomarker for ovarian cancer. Using mass spectrometry-based proteomics and phosphoproteomics techniques, our goal in this work is to characterize CA125 isoforms and phosphorylation sites. Using liquid chromatography-tandem mass spectrometry, plasma samples from thirty patients with ovarian cancer and thirty healthy controls were examined. The known ovarian cancer hub genes TP53, BRCA1, PTEN, PIK3CA, AKT1, KRAS, and MUC16 were among the more than 500 proteins found, along with a number of CA125 isoforms. On CA125, phosphorite localization revealed more than 100 phosphorylation sites. Patients were categorized into categories connected with stage, grade, and survival outcomes using consensus clustering. Our findings provide new light on the connection between ovarian cancer biology and CA125 heterogeneity. Distinct biological pathways underlying the course of illness are suggested by the differential expression of hub genes amongst subgroups. By focusing on disrupted hub genes and pathways, additional study of CA125 isoforms and phosphosites may provide more precise biomarkers, better early detection techniques, and precision medicine for ovarian cancer.

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Published
08/19/2025
Section
Research Articles
License

This work is licensed under a Creative Commons Attribution 4.0 International License.


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How to Cite

Characterizing CA125 Isoforms in Ovarian Cancer Using Proteomics, Phosphoproteomics and Consensus Clustering. (2025). International Journal of Biotechnology and Computational Science , 1(1). https://doi.org/10.63850/ijbtcs.v1.i1.a7