4.3 Article

Gastric cancer-associated microRNA expression signatures: integrated bioinformatics analysis, validation, and clinical significance

期刊

ANNALS OF TRANSLATIONAL MEDICINE
卷 9, 期 9, 页码 -

出版社

AME PUBL CO
DOI: 10.21037/atm-21-1631

关键词

miRNA; gastric cancer (GC); robust rank aggregation; biomarkers

资金

  1. National Natural Science Foundation of China [71964021]
  2. National Natural Science Foundation of Gansu Province [17JR5RA260]
  3. Science and Technology Development Guiding Plan Project of Lanzhou [2019-ZD-39]

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This study identified potential biomarkers for early diagnosis of gastric cancer by integrating analysis of miRNAs from the GEO database. While these miRNAs showed promise as diagnostic biomarkers in gastric cancer tissues, there were variations between tissue and peripheral blood analysis results. Ectopic expression of these miRNAs was associated with clinicopathological characteristics of gastric cancer, but poor prognosis in patients was more strongly linked to age, metastasis, and histological grade.
Background: Gastric cancer (GC) is one of the common gastrointestinal malignancy worldwide and exhibits a poor prognosis. Increasing studies have indicated that microRNAs play critical roles in the cancer progression and have shown great potential as useful biomarkers. The search for potential diagnostic and prognostic biomarkers of gastric cancer (GC) with integrated bioinformatics analyses has been undertaken in previous studies. Methods: In this study, the robust rank aggregation (RRA) method was used to perform an integrated analysis of differentially expressed miRNAs (DEMs) from five microarray datasets in the Gene Expression Omnibus (GEO) database to find robust biomarkers for GC. Ultimately, seven miRNAs were filtered from fourteen primary miRNAs using the validation set of The Cancer Genome Atlas (TCGA) database. Based on these results, diagnostic and survival analyses were performed, and logistic regression and Cox regression were used to determine the clinicopathological characteristics of the DEM expression and overall survival. Results: Nine eligible miRNA datasets related to GC were selected from the GEO database for integrated analysis in this study. Diagnostic analysis implied that these miRNAs could be regarded as promising candidate diagnostic biomarkers in GC tissues, but whether the results of the tissue analysis are consistent with those of peripheral blood analysis requires further validation. The logistic regression indicated that the ectopic expression of these DEMs was relevant to the histological type, anatomical region, and pathological grade of GC. However, the survival and Cox regression analyses suggested that the poor prognosis of GC patients was not strongly dependent on the ectopic expression of the seven miRNAs, but rather, a poor prognosis was associated with age, metastasis, and histological grade. Conclusions: Based on the results presented in this study it can be concluded that these miRNAs (miR-455-3p, miR-135b-5p, let-7a-3p, miR-195-5p, miR-204-5p, miR-149-5p, and miR-143-3p) might be potential biomarkers for the early diagnosis of GC patients, but this finding should be regarded with caution. A large-scale, prospective, and multicenter cohort study should be performed.

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