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Association of ABC gene profiles with time to progression and resistance in ovarian cancer revealed by bioinformatics analyses

K. Seborova, R. Vaclavikova, P. Soucek, K. Elsnerova, A. Bartakova, P. Cernaj, J. Bouda, L. Rob, M. Hruda, P. Dvorak,

. 2019 ; 8 (2) : 606-616. [pub] 20190122

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc20006626

Grantová podpora
NV17-28470A MZ0 CEP - Centrální evidence projektů

INTRODUCTION: Ovarian cancer (OC) represents a serious disease with high mortality and lack of efficient predictive and prognostic biomarkers. ATP-binding cassette (ABC) proteins constitute a large family dedicated to active transmembrane transport including transport of xenobiotics. MATERIALS AND METHODS: mRNA level was measured by quantitative RT-PCR in tumor tissues from OC patients. Bioinformatics analyses were applied to two gene expression datasets (60 primary tumors and 29 peritoneal metastases). Two different approaches of expression data normalization were applied in parallel, and their results were compared. Data from publically available cancer datasets were checked to further validate our conclusions. RESULTS: The results showed significant connections between ABC gene expression profiles and time to progression (TTP), chemotherapy resistance, and metastatic progression in OC. Two consensus ABC gene profiles with clinical meaning were documented. (a) Downregulation of ABCC4, ABCC10, ABCD3, ABCE1, ABCF1, ABCF2, and ABCF3 was connected with the best sensitivity to chemotherapy and TTP. (b) Oppositely, downregulation of ABCB11 and upregulation of ABCB1 and ABCG2 were connected with the worst sensitivity to chemotherapy and TTP. Results from publicly available online databases supported our conclusions. CONCLUSION: This study stressed the connection between two well-documented ABC genes and clinicopathological features-ABCB1 and ABCG2. Moreover, we showed a comparable connection also for several other ABC genes-ABCB11, ABCC4, ABCC10, ABCD3, ABCE1, ABCF1, ABCF2, and ABCF3. Our results add new clinically relevant information to this oncology field and can stimulate further exploration.

Citace poskytuje Crossref.org

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$a INTRODUCTION: Ovarian cancer (OC) represents a serious disease with high mortality and lack of efficient predictive and prognostic biomarkers. ATP-binding cassette (ABC) proteins constitute a large family dedicated to active transmembrane transport including transport of xenobiotics. MATERIALS AND METHODS: mRNA level was measured by quantitative RT-PCR in tumor tissues from OC patients. Bioinformatics analyses were applied to two gene expression datasets (60 primary tumors and 29 peritoneal metastases). Two different approaches of expression data normalization were applied in parallel, and their results were compared. Data from publically available cancer datasets were checked to further validate our conclusions. RESULTS: The results showed significant connections between ABC gene expression profiles and time to progression (TTP), chemotherapy resistance, and metastatic progression in OC. Two consensus ABC gene profiles with clinical meaning were documented. (a) Downregulation of ABCC4, ABCC10, ABCD3, ABCE1, ABCF1, ABCF2, and ABCF3 was connected with the best sensitivity to chemotherapy and TTP. (b) Oppositely, downregulation of ABCB11 and upregulation of ABCB1 and ABCG2 were connected with the worst sensitivity to chemotherapy and TTP. Results from publicly available online databases supported our conclusions. CONCLUSION: This study stressed the connection between two well-documented ABC genes and clinicopathological features-ABCB1 and ABCG2. Moreover, we showed a comparable connection also for several other ABC genes-ABCB11, ABCC4, ABCC10, ABCD3, ABCE1, ABCF1, ABCF2, and ABCF3. Our results add new clinically relevant information to this oncology field and can stimulate further exploration.
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$a Vaclavikova, Radka $u Toxicogenomics Unit, National Institute of Public Health, Prague, Czech Republic. Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic.
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$a Soucek, Pavel $u Toxicogenomics Unit, National Institute of Public Health, Prague, Czech Republic. Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic.
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$a Elsnerova, Katerina $u Toxicogenomics Unit, National Institute of Public Health, Prague, Czech Republic. Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic. Third Faculty of Medicine, Charles University, Prague, Czech Republic.
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$a Bartakova, Alena $u Department of Gynecology and Obstetrics, Faculty of Medicine and University Hospital in Pilsen, Charles University, Pilsen, Czech Republic.
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$a Cernaj, Petr $u Department of Gynecology and Obstetrics, Faculty of Medicine and University Hospital in Pilsen, Charles University, Pilsen, Czech Republic.
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$a Bouda, Jiri $u Department of Gynecology and Obstetrics, Faculty of Medicine and University Hospital in Pilsen, Charles University, Pilsen, Czech Republic.
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$a Rob, Lukas $u Department of Gynecology and Obstetrics, Third Faculty of Medicine and Faculty Hospital Kralovske Vinohrady, Charles University, Prague, Czech Republic.
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$a Hruda, Martin $u Department of Gynecology and Obstetrics, Third Faculty of Medicine and Faculty Hospital Kralovske Vinohrady, Charles University, Prague, Czech Republic.
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$a Dvorak, Pavel $u Biomedical Center, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic. Department of Biology, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic.
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