Kazusamycin

Background: Cervical cancer is the most common malignant tumor in the female reproductive system, while the efficacy of routine screening strategy is unsatisfied. New molecular tests need to be developed. miRNAs participate in many pathologic processes, and circulating miRNAs are promising non-invasive biomarkers in tumors. Objectives: This study aimed to identify the circulating miRNAs associated with both cervical cancer and cervical intraepithelial neoplasia (CIN), and establish a non-invasive classifier for cervical lesions using circulating miRNAs. Methods: This study consisted of 5 steps: miRNAs screening, miRNAs validation, classifier establishment, independent validation and in silico analyses. Three cohorts were included in our study: In screening stage, 24 samples including 14 cases and 10 controls were retrieved; In validation stage, 380 samples including 200 cases and 180 controls were recruited; In independent validation stage, 47 samples comprising 26 cases and 21 controls were included. miRNAs were quantified by RT-qPCR. A classifier was built with random forest algorithm using validation samples and selected miRNAs, which were then validated in an independent cohort. To explore the function of selected miRNAs, in silico analyses were performed. Target genes of selected miRNAs were predicted by the overlap of three online tools. Enrichment analyses were executed with predicted target genes. Differential analysis of target genes was carried out with open access expression assay datasets of cervical tissues. Results: 6 miRNAs (hsa-miR-26b-5p, hsa-miR-146b-5p, hsa-miR-191-5p, hsa-miR-484, hsa-miR-574-3p, hsa-miR-625-3p) were screened out from 754 miRNAs. They were associated with cervical lesions and were selected to establish a classifier. The accuracy of the classifier were 0.7218 (0.7117, 0.7319) in validation samples, which was 0.7021 in the independent cohort. 958 target genes were predicted and enriched in 23 pathways (MAPK, human papillomavirus infection and Wnt signaling pathway, etc.). 55 genes were identified as the most likely target genes by differential analysis. Conclusion: The 6 circulating miRNAs were related to cervical lesions and could serve as non-invasive biomarkers.

Prostate cancer (PCa) is the second most frequent cancer and the fifth leading cause of cancer-related death in men while the mechanisms remain unclear.

Differentially expressed mRNAs (DEmRNAs) and miRNAs (DEmiRNAs) between PCa and non-tumor controls were identified by using microarray analysis. Functional annotation of DEmRNAs, construction of protein-protein interaction (PPI) network and prediction of upstream transcription factors and downstream target DEmRNAs of DEmiRNAs were conducted to further research functions of key DEmRNAs and DEmiRNAs. Validation of selected DEmRNAs and survival analysis were conducted by using The Cancer Genome Atlas (TCGA).

Total of 91 DEmRNAs and 62 DEmiRNAs were obtained. Thrombospondin-4 precursor (THBS4) was the most significantly up-regulated DEmRNA whose product was predicted to interact with the hub protein of the PCa-specific PPI network, collagen type I alpha 1 chain (COL1A1). Both ATP binding cassette subfamily C member 4 (ABCC4) and endothelin receptor type B (EDNRB) have great prognostic value for PCa. Thrombospondin type 1 domain containing 4 (THSD4) was a down-regulated DEmRNA regulated by several cancer-related miRNAs including has-miR-107, hsa-miR-3175 and hsa-miR-484. Two miRNAs (hsa-miR-428 and hsa-miR-4284) involve in PCa by regulating BMP5-BAMBI interaction and TGF-beta signaling pathway. The expression of selected DEmRNAs between PCa and non-tumor controls in TCGA was consistent with that in our microarray analysis, generally.

Key DEmRNAs and DEmiRNAs between PCa and non-tumor controls were identified in this study which provided clues for exploring the molecular mechanism and developing potential biomarkers and therapeutic target sites for PCa.