Proteomic and Bioinformatic Studies for the Characterization of Response to Pemetrexed in Platinum Drug Resistant Ovarian Cancer

• Main Authors: Leda Severi (Author), Lorena Losi (Author), Sergio Fonda (Author), Laura Taddia (Author), Gaia Gozzi (Author), Gaetano Marverti (Author), Fulvio Magni (Author), Clizia Chinello (Author), Martina Stella (Author), Jalid Sheouli (Author), Elena I. Braicu (Author), Filippo Genovese (Author), Angela Lauriola (Author), Chiara Marraccini (Author), Alessandra Gualandi (Author), Domenico D'Arca (Author), Stefania Ferrari (Author), Maria P. Costi (Author)
• Format: Book
• Published: Frontiers Media S.A., 2018-05-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1663-9812; 10.3389/fphar.2018.00454
• Keywords: pemetrexed; folate pathway; drug resistance; ovarian cancer; proteomics; mass spectrometry; Therapeutics. Pharmacology; RM1-950
• Source: Frontiers in Pharmacology, Vol 9 (2018)

Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuest™ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.