Investigator
Institute Of Biomedical Chemistry
Advancing Plasma Proteomics for the Discovery of Ovarian Cancer Biomarkers
The development of ultrasensitive proteomic methods for detecting potential protein tumor biomarkers remains a key challenge in modern biomedicine. We integrated data from classical reference proteomic methods─both panoramic (DDA-Shotgun LC-MS/MS) and targeted (MRM)─with a novel AFM-based enrichment approach coupled to mass spectrometry (AFM-MS), providing lower detection limits. This integrated strategy enabled the compilation of an expanded list of proteins associated with ovarian cancer progression. We identified a panel of previously unreported, ovarian cancer-specific candidate markers. A total of 371 proteins were found to be potentially involved in the pathological process, with 33% detected exclusively by the ultrasensitive AFM-MS method and 26% discovered through metabolomic associations. Notably, 6% of the identified proteins correspond to previously recognized ovarian cancer-specific markers, validating our multiplatform approach. Nine potential biomarkers are proposed for the first time, including ATRN, CPN1, APOF, TGM3, and CRNN. Immunoglobulin variable region peptides were reclassified as low-specificity background signals due to their high abundance and inflammation dependence. The identified biomarkers are present in blood at concentrations ranging from 10
Ovarian Cancer: Multi-Omics Data Integration
This study focuses on the systematization and integration of ovarian cancer multi-omics data, revealing patterns in the application of different omics-based approaches and assessing factors that affect the identification of potential biomarkers. An integrative analysis of 51 publications revealed 1649 potential biomarkers. The findings emphasized the molecular diversity of ovarian cancer. They demonstrated the importance of performing the comprehensive integration of molecular and clinical data to search for diagnostic alternatives and molecular patterns underlying ovarian cancer. The heterogeneity of data sources, differences in data acquisition and analysis protocols, and the lack of uniform standards affect the reproducibility of the results of genomic and post-genomic profiling. Multi-omics studies are more promising than mono-omics-based ones. Despite technological advances, researchers continue to focus on results obtained over a decade ago, which may hinder the scientific community from exploring new horizons in ovarian cancer research.
