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Serum Mass Spectrometry Proteomics and Protein Set Identification in Response to FOLFOX-4 in Drug-Resistant Ovarian
Domenico D'Arca1, Leda Severi2, Stefania Ferrari2
1Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, 41125 Modena, Italy.
Abstract:
Ovarian cancer is a highly lethal gynecological malignancy. Drug resistance rapidly occurs, and different therapeutic approaches are needed. So far, no biomarkers have been discovered to predict early response to therapies in the case of multi-treated ovarian cancer patients. The aim of our investigation was to identify a protein panel and the molecular pathways involved in chemotherapy response through a combination of studying proteomics and network enrichment analysis by considering a subset of samples from a clinical setting. Differential mass spectrometry studies were performed on 14 serum samples from patients with heavily pretreated platinum-resistant ovarian cancer who received the FOLFOX-4 regimen as a salvage therapy. The serum was analyzed at baseline time (T0) before FOLFOX-4 treatment, and before the second cycle of treatment (T1), with the aim of understanding if it was possible, after a first treatment cycle, to detect significant proteome changes that could be associated with patients responses to therapy. A total of 291 shared expressed proteins was identified and 12 proteins were finally selected between patients who attained partial response or no-response to chemotherapy when both response to therapy and time dependence (T0, T1) were considered in the statistical analysis. The protein panel included APOL1, GSN, GFI1, LCATL, MNA, LYVE1, ROR1, SHBG, SOD3, TEC, VPS18, and ZNF573. Using a bioinformatics network enrichment approach and metanalysis study, relationships between serum and cellular proteins were identified. An analysis of protein networks was conducted and identified at least three biological processes with functional and therapeutic significance in ovarian cancer, including lipoproteins metabolic process, structural component modulation in relation to cellular apoptosis and autophagy, and cellular oxidative stress response. Five proteins were almost independent from the network (LYVE1, ROR1, TEC, GFI1, and ZNF573). All proteins were associated with response to drug-resistant ovarian cancer resistant and were mechanistically connected to the pathways associated with cancer arrest. These results can be the basis for extending a biomarker discovery process to a clinical trial, as an early predictive tool of chemo-response to FOLFOX-4 of heavily treated ovarian cancer patients and for supporting the oncologist to continue or to interrupt the therapy.
Insights
Researchers identified a 12-protein panel and key molecular pathways to predict chemotherapy response in ovarian cancer patients. This discovery offers a potential early biomarker for guiding treatment decisions in heavily pretreated cases.
Area of Science:
- Gynecological Oncology
- Proteomics
- Bioinformatics
Background:
- Ovarian cancer is a lethal malignancy with rapid development of drug resistance.
- Current therapeutic strategies lack early biomarkers to predict treatment response in multi-treated patients.
- Novel approaches are needed to personalize salvage chemotherapy for platinum-resistant ovarian cancer.
Purpose of the Study:
- To identify a protein signature in serum predictive of chemotherapy response.
- To elucidate molecular pathways involved in treatment response using proteomics and network analysis.
- To evaluate the potential of identified biomarkers for early prediction of FOLFOX-4 regimen efficacy.
Main Methods:
- Differential mass spectrometry analysis of serum samples from 14 heavily pretreated, platinum-resistant ovarian cancer patients.
- Serum samples collected at baseline (T0) and before the second FOLFOX-4 cycle (T1).
- Proteomics combined with bioinformatics network enrichment and metanalysis for pathway identification.
Main Results:
- A panel of 12 proteins (APOL1, GSN, GFI1, LCATL, MNA, LYVE1, ROR1, SHBG, SOD3, TEC, VPS18, ZNF573) was selected based on differential expression and response.
- Identified key biological processes linked to ovarian cancer chemo-resistance: lipoprotein metabolism, apoptosis/autophagy modulation, and oxidative stress response.
- Proteins were mechanistically connected to cancer arrest pathways, suggesting their role in drug resistance and therapeutic response.
Conclusions:
- The identified 12-protein panel shows promise as an early predictive biomarker for FOLFOX-4 response in heavily treated ovarian cancer.
- These findings support the development of a clinical tool to aid oncologists in treatment continuation or interruption decisions.
- Further validation in clinical trials is warranted to establish this panel as a reliable predictive biomarker.
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