Identifying pancreatic cancer‑associated miRNAs using weighted gene co‑expression network analysis

Lyu,Pengfei; Hao,Zhengwen; Zhang,Haoruo; Li,Jun

doi:10.3892/ol.2022.13417

Identifying pancreatic cancer‑associated miRNAs using weighted gene co‑expression network analysis

Authors:
- Pengfei Lyu
- Zhengwen Hao
- Haoruo Zhang
- Jun Li
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Affiliations: Department of General Surgery, Shanxi Tumor Hospital, Taiyuan, Shanxi 030000, P.R. China
Published online on: July 5, 2022 https://doi.org/10.3892/ol.2022.13417
Article Number: 297

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Abstract

Pancreatic cancer is a common type of gastrointestinal tumour throughout the world and is characterised by high malignancy rates and poor prognosis. Studies indicated that early and effective diagnosis is key to prolonging patients' overall survival, particularly in the case of fluid biopsy. Given this, the present study was designed to evaluate the expression profile arrays of patients with pancreatic cancer from the Gene Expression Omnibus database in an effort to identify differentially expressed microRNAs (miRNAs/miRs) that may be suitable for application in liquid biopsy‑based diagnostics. Suitable miRNA candidates were identified using a weighted correlation network analysis (WGCNA) and key differentially expressed miRNAs were verified using reverse transcription‑quantitative PCR. WGCNA identified 11 differentially expressed miRNAs (miR‑155‑5p, miR‑4668‑5p, miR‑3613‑3p, miR‑3201, miR‑548ac, miR‑486‑5p, miR‑548a‑3p, miR‑8084, miR‑455‑3p, miR‑6068 and miR‑1246). Of these, miR‑4668‑5p was indicated to have the highest number of associated modules, making it most likely to be of diagnostic value. Thus, the present analysis identified 11 miRNAs associated with pancreatic cancer and further identified miR‑4668‑5p as a potential biomarker for pancreatic cancer diagnosis.

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