ObjectiveMicroRNAs (miRNAs) play a vital role in pathogenesis and progression of many cancers, including cervical cancer. However, importance of serum level of miR-101 in cervical cancer has rarely been studied. In the present study, clinical significance and prognostic value of serum miR-101 for cervical cancer was investigated.MethodsAssociation between miR-101 level in cervical cancer tissues and prognosis of patients was analyzed by using data retrieved from The Cancer Genome Atlas (TCGA) database, which was followed with our clinical study in which miR-101 serum level comparison between cervical cancer patients and healthy controls was conducted by real-time quantitative polymerase chain reaction (PCR).ResultsTCGA database demonstrated that miR-101 was down-regulated in cervical cancer tissues compared with normal cervical tissues, and univariate Cox regression analysis indicated that decreased miR-101 expression was a highly significant negative risk factor. Similar trend was found in the serum miR-101. Serum level of miR-101 was associated with International Federation of Gynecology and Obstetrics (FIGO) stage (p=0.003), lymph node metastasis (p=0.001), and serum squamous cell carcinoma antigen (SCC-Ag) level >4 (p=0.007). The overall survival time of cervical cancer patients with a higher level of serum miR-101 was significantly longer than that of patients with a lower level of serum miR-101. Moreover, multivariate Cox regression analysis indicated that the down-regulated serum level of miR-101 was an independent predictor for the unfavorable prognosis of cervical cancer.ConclusionSerum level of miR-101 is closely associated with metastasis and prognosis of cervical cancer; and, hence could be a potential biomarker and prognostic predictor for cervical cancer.

ABSTRACT. Annotation of prostate cancer (PC) genomes provides a foundation for discoveries that can improve the understanding and treatment of the disease. Therefore, in the present study, we used the Student t-test to identify differentially expressed PC-related mRNAs and microRNAs (miRNAs). Then, we performed interrelated mapping of miRNA target genes between abnormally expressed mRNAs and miRNAs, and explored mRNA-target miRNA interrelated pairs to explain the biological functions of miRNA during the progression of PC, thus revealing the occurrence of miRNA-mediated PC. After Gene Set Functional Similarity analysis, we obtained 20 abnormal PC-related candidate miRNAs, including hsa-miR-26a, hsa-miR-152, hsa-miR19a, hsa-miR-30c, hsa-miR-19b, and hsa-miR-146b-5p, among others. These results suggest that it may be possible to predict the clinical behavior of prostate cancer based on gene expression analysis.