Julia Kovacova1, Jaroslav Juracek1, Alexandr Poprach2, Tomas Buchler3, Jindrich Kopecky4, Ondrej Fiala5,6, Marek Svoboda2, Ondrej Slaby7. 1. Central European Institute of Technology, Masaryk University, Brno, Czech Republic. 2. Department of Comprehensive Cancer Care, Masaryk Memorial Cancer Institute, Brno, Czech Republic. 3. Department of Oncology, First Faculty of Medicine, Charles University and Thomayer Hospital, Prague, Czech Republic. 4. Department of Clinical Oncology and Radiotherapy, University Hospital in Hradec Kralove, Hradec Kralove, Czech Republic. 5. Department of Oncology and Radiotherapeutics, Medical School and Teaching Hospital, Faculty of Medicine, Charles University, Pilsen, Czech Republic. 6. Biomedical Center, Faculty of Medicine, Charles University, Pilsen, Czech Republic. 7. Central European Institute of Technology, Masaryk University, Brno, Czech Republic on.slaby@gmail.com.
Abstract
BACKGROUND/AIM: Targeted therapy with the tyrosine kinase inhibitor sunitinib is used in the first line of metastatic renal cell carcinoma (mRCC) treatment. The aim of the present study was independent validation of microRNAs (miRNAs) identified in previous studies as biomarkers predicting response to sunitinib therapy. MATERIALS AND METHODS: Based on a literature search, 10 miRNAs were chosen from six relevant studies as candidates for validation: miR-155, miR-484, miR-221, miR-222, miR-425, miR-133, miR-410, miR-141, miR-628 and miR-942. Validation of these miRNAs was performed on cohort of 56 patients with mRCC with extremely good or poor response responses to sunitinib treatment using quantitative reverse transcription-polymerase chain reaction. Patients were divided into either responding (n=24) or non-responding (n=32) groups to sunitinib treatment according to Response Evaluation Criteria in Solid Tumors and progression-free survival (PFS). All patients in the responding group had PFS longer than 18 months, PFS of non-responders was shorter than 6 months in all cases. RESULTS: miR-942 and miR-133 were confirmed as being differentially expressed in tumors of responding and non-responding patients. It was not possible to validate the predictive value of other tested miRNAs, however, expression of miR-221 and miR-425 tended to be positively associated with therapeutic response (p<0.1). We further developed a model based on the combination of miR-942 and miR-133 expression, that enabled identification of non-responding patients with mRCC with sensitivity of 78% and specificity of 79% (area under the curve=0.8071). CONCLUSION: Following further independent validation, detection of these miRNAs may prevent unnecessary and costly approaches to therapy in non-responding patients with mRCC. Copyright
BACKGROUND/AIM: Targeted therapy with the tyrosine kinase inhibitor sunitinib is used in the first line of metastatic renal cell carcinoma (mRCC) treatment. The aim of the present study was independent validation of microRNAs (miRNAs) identified in previous studies as biomarkers predicting response to sunitinib therapy. MATERIALS AND METHODS: Based on a literature search, 10 miRNAs were chosen from six relevant studies as candidates for validation: miR-155, miR-484, miR-221, miR-222, miR-425, miR-133, miR-410, miR-141, miR-628 and miR-942. Validation of these miRNAs was performed on cohort of 56 patients with mRCC with extremely good or poor response responses to sunitinib treatment using quantitative reverse transcription-polymerase chain reaction. Patients were divided into either responding (n=24) or non-responding (n=32) groups to sunitinib treatment according to Response Evaluation Criteria in Solid Tumors and progression-free survival (PFS). All patients in the responding group had PFS longer than 18 months, PFS of non-responders was shorter than 6 months in all cases. RESULTS:miR-942 and miR-133 were confirmed as being differentially expressed in tumors of responding and non-responding patients. It was not possible to validate the predictive value of other tested miRNAs, however, expression of miR-221 and miR-425 tended to be positively associated with therapeutic response (p<0.1). We further developed a model based on the combination of miR-942 and miR-133 expression, that enabled identification of non-responding patients with mRCC with sensitivity of 78% and specificity of 79% (area under the curve=0.8071). CONCLUSION: Following further independent validation, detection of these miRNAs may prevent unnecessary and costly approaches to therapy in non-responding patients with mRCC. Copyright
Authors: Julia Kovacova; Jaroslav Juracek; Alexandr Poprach; Jindrich Kopecky; Ondrej Fiala; Marek Svoboda; Pavel Fabian; Lenka Radova; Petr Brabec; Tomas Buchler; Ondrej Slaby Journal: Cancer Genomics Proteomics Date: 2019 Sep-Oct Impact factor: 4.069