Role of miR-15b/16–2 cluster network in endometrial cancer: An in silico pathway and prognostic analysis

Anoop Kallingal, Sanu Thankachan, Thejaswini Venkatesh, Shama Prasada Kabbekodu, Padmanaban S. Suresh

Research output: Contribution to journalArticlepeer-review


Endometrial cancer (EC) is the second most common cancer in women. A large number of human cancers exhibit dysregulation of microRNA expression including EC. MiR-15b/16–2 is one of the best-known miRNA clusters that is expressed in many types of cancer tissues. Herein, we analyzed the expression of individual miR-15b/16–2 cluster members, its paralogues, and their target network analysis, as well as their prognostic significance in EC. UALCAN and GEPIA2 were used to analyze the expression of the individual members of the cluster. The gene target was predicted through miRTarBase, and the genes were then compared through the TCGA-UCEC dataset. The differential gene expression and network analysis identified 175 DEGs associated with critical cancer-related pathways. The prognostic significance and metastatic prediction were carried out using GEPIA2 and HCMDB tools. In UCEC patient samples, miR- 15b/16–2 cluster expression is negatively correlated with the overall survival of the patients. The uterus-specific miRNA-lncRNA, miRNA-circRNA, and miRNA-sncRNA networks of miR- 15b/16–2 cluster contain 1164 edges and nodes consisting of 5 sncRNA, 124 circRNA, and 1552 genes. The DEGs analysis led to the identification of SIPA1L2, PDCD1, CCNJ, ENTPD7, PLEKHA5, NPAS3, DPH5, BTF3, NPAS3, SENP2, and CCND3 as a significant predictor of overall survival in UCEC patients. The analysis of metastasis found 24 genes significantly associated with brain and lymph node metastasis. The analysis of drug-gene interactions revealed 267 FDA-approved drugs for treating cancers. Our data provided novel insight on the miR-15b/16–2 cluster role in EC and prioritized the findings for experimental verification. Besides, more comprehensive clinical and mechanistic studies are needed to confirm our findings in endometrial cancer.

Original languageEnglish
Article number101018
JournalMeta Gene
Publication statusPublished - 02-2022

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)


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