Evidence map›Paper›PMID 38077476›Full record

ArticleInternational journal of general medicine2023

Identification and Validation of Key miRNAs for Colon Cancer Based on miRNA-Gene Integration Analysis.

Yi Ji, Jialin Gu, Hongqun Zhang, Houxi Xu

Abstract read
In one paragraph

Article in International journal of general medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yi Ji *Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210028, People's Republic of China.
Jialin Gu *Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210028, People's Republic of China.
Hongqun ZhangAffiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210028, People's Republic of China.
Houxi XuKey Laboratory of Acupuncture and Medicine Research of Ministry of Education, Nanjing University of Chinese Medicine, Nanjing, 210046, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: MicroRNAs (miRNAs) plays an essential role in the pathogenesis of colon cancer. This study aims to identify and verify key miRNAs that may serve as potential biomarkers for early diagnosis and treatment of colon cancer. Methods: Two miRNA microarray datasets (GSE53339 and GSE126093) were downloaded from the Gene Expression Omnibus (GEO) database, and the common differentially expressed miRNAs (DEMis) of both were identified by the "limma" package and the intersect function in R. Then, the miRwalk online tool was used to predict the target genes of the common DEMis and perform Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on those DEMis. The miRNA-gene network was constructed using Cytoscape software to identify key miRNAs and validated using quantitative real-time PCR (qRT-PCR) and The Cancer Genome Atlas (TCGA) dataset information for experimental and external database validation, respectively. In addition, we explored the correlation between key miRNAs and infiltrating immune cells and immunotherapy biomarkers. Results: Fourteen common DEMis were identified from the GEO database, and five targeted genes were predicted. A microRNA-gene network was subsequently constructed to identify three key miRNAs (miR-363-3p, miR-520e, and miR-330-5p). Both qRT-PCR and external database validation confirmed our findings. In addition, we found that miR-520e was significantly associated with infiltrating immune cells and established immune checkpoints. Conclusion: Our study identified three key miRNAs that influence the development of colon cancer. In addition, further studies suggest that infiltrating immune cells may play an essential role in the pathogenesis of colon cancer. These findings assist in early diagnosis and precision-targeted therapies.

Indexed as

colon cancerGEOimmune cell infiltrationmiRNAqRT-PCR

Identifiers

PMID38077476
PMCPMC10710248

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.