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Identification and validation of a miRNA-based prognostic signature for cervical cancer through an integrated bioinformatics approach.

ABSTRACT: 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.

SUBMITTER: Qi Y

PROVIDER: S-EPMC7747620 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Identification and validation of a miRNA-based prognostic signature for cervical cancer through an integrated bioinformatics approach.

Qi Yumei Y Lai Yo-Liang YL Shen Pei-Chun PC Chen Fang-Hsin FH Lin Li-Jie LJ Wu Heng-Hsiung HH Peng Pei-Hua PH Hsu Kai-Wen KW Cheng Wei-Chung WC

Scientific reports 20201217 1

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 c ...[more]

PMID: 33335254

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Dataset Information

Identification and validation of a miRNA-based prognostic signature for cervical cancer through an integrated bioinformatics approach.

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Identification and validation of a miRNA-based prognostic signature for cervical cancer through an integrated bioinformatics approach.

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