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Searching for potential biomarkers of cisplatin resistance in human ovarian cancer using a label‐free LC/MS‐based protein quantification method

Dawn P. G. Fitzpatrick, Jinsam You, Kerry G. Bemis, Jean‐Pierre Wery, J. Richard Ludwig, Mu Wang

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Abstract

Platinum-based chemotherapy, such as cisplatin, is the primary treatment for ovarian cancer. However, drug resistance has become a major impediment to the successful treatment of ovarian cancer. To date, the molecular mechanisms of resistance to platinum-based chemotherapy remain unclear. In this study, we applied an LC/MS-based protein quantification method to examine the global protein expression of two pairs of ovarian cancer cell lines, A2780/A2780-CP (cisplatin-sensitive/cisplatin-resistant) and 2008/2008-C13*5.25 (cisplatin-sensitive/cisplatin-resistant). We identified and quantified over 2000 proteins from these cell lines and 760 proteins showed significant expression changes with a false discovery rate of less than 5% between paired groups. Based on the results we obtained, we suggest several potential pathways that may be involved in cisplatin resistance in human ovarian cancer. This study provides not only a new proteomic platform for large-scale quantitative protein analysis, but also important information for discovery of potential biomarkers of cisplatin resistance in ovarian cancer. Furthermore, these results may be clinically relevant for diagnostics, prognostics, and therapeutic improvement for ovarian cancer treatment.

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Platinum-based chemotherapy, such as cisplatin, is the primary treatment for ovarian cancer. However, drug resistance has become a major impediment to the successful treatment of ovarian cancer. To date, the molecular mechanisms of resistance to platinum-based chemotherapy remain unclear. In this study, we applied an LC/MS-based protein quantification method to examine the global protein expression of two pairs of ovarian cancer cell lines, A2780/A2780-CP (cisplatin-sensitive/cisplatin-resistant) and 2008/2008-C13*5.25 (cisplatin-sensitive/cisplatin-resistant). We identified and quantified over 2000 proteins from these cell lines and 760 proteins showed significant expression changes with a false discovery rate of less than 5% between paired groups. Based on the results we obtained, we suggest several potential pathways that may be involved in cisplatin resistance in human ovarian cancer. This study provides not only a new proteomic platform for large-scale quantitative protein analysis, but also important information for discovery of potential biomarkers of cisplatin resistance in ovarian cancer. Furthermore, these results may be clinically relevant for diagnostics, prognostics, and therapeutic improvement for ovarian cancer treatment.

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Available abstract

Platinum-based chemotherapy, such as cisplatin, is the primary treatment for ovarian cancer. However, drug resistance has become a major impediment to the successful treatment of ovarian cancer. To date, the molecular mechanisms of resistance to platinum-based chemotherapy remain unclear. In this study, we applied an LC/MS-based protein quantification method to examine the global protein expression of two pairs of ovarian cancer cell lines, A2780/A2780-CP (cisplatin-sensitive/cisplatin-resistant) and 2008/2008-C13*5.25 (cisplatin-sensitive/cisplatin-resistant). We identified and quantified over 2000 proteins from these cell lines and 760 proteins showed significant expression changes with a false discovery rate of less than 5% between paired groups. Based on the results we obtained, we suggest several potential pathways that may be involved in cisplatin resistance in human ovarian cancer. This study provides not only a new proteomic platform for large-scale quantitative protein analysis, but also important information for discovery of potential biomarkers of cisplatin resistance in ovarian cancer. Furthermore, these results may be clinically relevant for diagnostics, prognostics, and therapeutic improvement for ovarian cancer treatment.

Key concepts: Cisplatin, Ovarian cancer, Chemotherapy, Drug resistance, Oncology, Cancer research, Cancer, Proteomics

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