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Identification and validation of a miRNA-based prognostic signature for cervical cancer through an integrated bioinformatics approach.
Qi, Yumei; Lai, Yo-Liang; Shen, Pei-Chun; Chen, Fang-Hsin; Lin, Li-Jie; Wu, Heng-Hsiung; Peng, Pei-Hua; Hsu, Kai-Wen; Cheng, Wei-Chung.
Afiliación
  • Qi Y; Department of Obstetrics and Gynecology, Suzhou BenQ Medical Center, The Affiliated BenQ Hospital, Nanjing Medical Medical University, Suzhou, 215010, Jiangsu, China.
  • Lai YL; Graduate Institute of Biomedical Science, China Medical University, Taichung, 40403, Taiwan, ROC.
  • Shen PC; Department of Radiation Oncology, China Medical University Hospital, Taichung, 40403, Taiwan, ROC.
  • Chen FH; Research Center for Cancer Biology, China Medical University, Taichung, 40403, Taiwan, ROC.
  • Lin LJ; Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, 33302, Taiwan, ROC.
  • Wu HH; Department of Radiation Oncology, Chang Gung Memorial Hospital at Linkou, Taoyuan, 33302, Taiwan, ROC.
  • Peng PH; Institute for Radiological Research, Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, 33302, Taiwan, ROC.
  • Hsu KW; The Ph.D. Program for Cancer Biology and Drug Discovery, China Medical University and Academia Sinica, Taichung, 40403, Taiwan, ROC.
  • Cheng WC; Graduate Institute of Biomedical Science, China Medical University, Taichung, 40403, Taiwan, ROC.
Sci Rep ; 10(1): 22270, 2020 12 17.
Article en En | MEDLINE | ID: mdl-33335254
Cervical cancer is the fourth most common cancer in women worldwide. Increasing evidence has shown that miRNAs are related to the progression of cervical cancer. However, the mechanisms that affect the prognosis of cancer are still largely unknown. In the present study, we sought to identify miRNAs associated with poor prognosis of patient with cervical cancer, as well as the possible mechanisms regulated by them. The miRNA expression profiles and relevant clinical information of patients with cervical cancer were obtained from The Cancer Genome Atlas (TCGA). The selection of prognostic miRNAs was carried out through an integrated bioinformatics approach. The most effective miRNAs with synergistic and additive effects were selected for validation through in vitro experiments. Three miRNAs (miR-216b-5p, miR-585-5p, and miR-7641) were identified as exhibiting good performance in predicting poor prognosis through additive effects analysis. The functional enrichment analysis suggested that not only pathways traditionally involved in cancer but also immune system pathways might be important in regulating the outcome of the disease. Our findings demonstrated that a synergistic combination of three miRNAs may be associated, through their regulation of specific pathways, with very poor survival rates for patients with cervical cancer.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias del Cuello Uterino / MicroARNs Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Female / Humans Idioma: En Revista: Sci Rep Año: 2020 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias del Cuello Uterino / MicroARNs Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Female / Humans Idioma: En Revista: Sci Rep Año: 2020 Tipo del documento: Article País de afiliación: China