ArticleJournal of gastrointestinal oncology2023
Identification of key modules and micro RNAs associated with colorectal cancer via a weighted gene co-expression network analysis and competing endogenous RNA network analysis.
Article in Journal of gastrointestinal oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
- Integrated single-cell and spatial transcriptomic analyses reveal malignant epithelial glycolytic heterogeneity and spatial niche remodeling during colorectal cancer progression.Functional & integrative genomics · 2026Article
- DDX21 functions as a potential novel oncopromoter in pancreatic ductal adenocarcinoma: a comprehensive analysis of the DExD box family.Discover oncology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide, and the incidence of CRC has increased rapidly in recent years. Due to the high invasiveness of colonoscopy and the low accuracy of alternative diagnostic methods, the diagnosis of CRC remains a serious problem. Thus, molecular biomarkers for CRC need to be identified. Methods: In this study, RNA-sequencing data from The Cancer Genome Atlas (TCGA) database were used to identify the long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), and micro RNAs (miRNAs) that were differentially expressed between the CRC and normal tissues. Based on the gene expression and clinical features, the results of the weighted gene co-expression network analysis (WGCNA) and the binding relationships between miRNAs and lncRNAs and mRNAs were used to establish a CRC-related competing endogenous RNA (ceRNA) network. Results: The core miRNAs (i.e., mir-874, mir-92a-1, and mir-940) in the network were identified. Among them, mir-874 was negatively correlated with the overall survival (OS) of patients. The protein-coding genes in the ceRNA network included Conclusions: In conclusion, this study established a network of the co-expressed ceRNAs associated with CRC and identified the genes and miRNAs related to the prognosis of CRC patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.