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Research Paper|Volume 13, Issue 18|pp 22361—22374

Identification of clinical trait-related small RNA biomarkers with weighted gene co-expression network analysis for personalized medicine in endocervical adenocarcinoma

Zhiwen Shi1,2, Xinyu Qu1,2, Chenyan Guo1,2, Lihong Zhang1, Chuyue Peng3, Zhu Xie3, Keqin Hua1,2, Junjun Qiu1,2
  • 1Obstetrics and Gynecology Hospital, Fudan University, Shanghai 200011, China
  • 2Shanghai Key Laboratory of Female Reproductive Endocrine Related Diseases, Institute of Metabolism and Integrative Biology, Institutes of Biomedical Sciences, Fudan University, Shanghai 200433, China
  • 3State Key Laboratory of Genetic Engineering, MOE Key Laboratory of Contemporary Anthropology, and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China
* Equal contribution
Received: April 8, 2021Accepted: August 31, 2021Published: September 20, 2021
https://doi.org/10.18632/aging.203543

Copyright: © 2021 Shi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Endocervical adenocarcinoma (EAC) is an aggressive type of endocervical cancer. At present, molecular research on EAC mainly focuses on the genome and mRNA transcriptome, the investigation of small RNAs in EAC has not been fully described. Here, we systematically explored small RNAs in 14 EAC patients with different subtypes using small RNA sequencing. MiRNAs and tRNA-derived RNAs (tDRs) accounted for the majority of mapped reads and the total number of miRNAs and tDRs maintained a relative balance. To explore the correlations between small RNAs expression and EAC with different clinical characteristics, we performed the weighted gene co-expression network analysis (WGCNA) and screened for hub small RNAs. From the key modules, we identified 9 small RNAs that were significantly related to clinical characteristics in EAC patients. Gene ontology and pathway analyses revealed that these molecules were involved in the pathogenesis of EAC. Our work provided new insights into EAC pathogenesis and successfully identified several small RNAs as candidate biomarkers for diagnosis and prognosis of EAC.