ArticleJournal of gastrointestinal oncology2022
Comprehensive bioinformatics analysis of functional molecules in colorectal cancer.
Article in Journal of gastrointestinal oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The trial behind it
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Neddylation related gene signature for prognostic biomarkers in colorectal cancer with integrated bioinformatics and experimental analysis.Discover oncology · 2025Article
- Decision tree-based machine learning methods for identifying colorectal cancer-associated microRNA signatures and their regulatory networks.Scientific reports · 2025Article
- Exploring the multifaceted roles of glutamate oxaloacetate transaminase 1 as a biomarker and therapeutic target in colorectal cancer and pan-cancer analyses.Discover oncology · 2025Article
- Identification of hsa-miR-193a-5p-SURF4 axis related to the gut microbiota-metabolites- cytokines in lung cancer based on Mendelian randomization study and bioinformatics analysis.Discover oncology · 2024Article
- IRAK2, an Immune and Radiation-Response Gene, Correlates with Advanced Disease Features but Predicts Higher Post-Irradiation Local Control in Non-Metastatic and Resected Oral Cancer Patients.International journal of molecular sciences · 2023Article
- LOXL2 reduces 5-FU sensitivity through the Hedgehog/BCL2 signaling pathway in colorectal cancer.Experimental biology and medicine (Maywood, N.J.) · 2023Article
- Identification and verification of a prognostic signature based on a miRNA-mRNA interaction pattern in colon adenocarcinoma.Frontiers in cell and developmental biology · 2023Article
- Circulating miRNA Expression Profiles and Machine Learning Models in Association with Response to Irinotecan-Based Treatment in Metastatic Colorectal Cancer.International journal of molecular sciences · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Colorectal cancer (CRC) is the 3rd most common cancer and the 2nd leading cause of cancer-related death. Numerous studies have found that aberrations in cellular molecules play an important role in the development of tumors. Studying and determining the interactions between these molecules can contribute to the diagnosis, treatment, and prognosis of tumors. Methods: The GSE151021, GSE156720, and GSE156719 data sets were analyzed to screen the differentially expressed messenger RNAs (DEmRNAs), long non-coding RNAs (DElncRNAs), and microRNAs (DEmiRNAs) in CRC. Database for Annotation, Visualization and Integrated Discovery (DAVID) and the Search Tool for the Retrieval of Interacting Genes/Proteins software were used to examine gene enrichment and the hub genes. Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and UALCAN was used to verify the expression of the hub genes. To analyze the overall survival (OS) of the hub genes, Kaplan-Meier plotter (KM plotter) was performed. Finally, the miRCancer database, TargetScan, and GSE156719 were used to identify the targets of the identified miRNAs. To predict the lncRNA-miRNA interactions, we used DIANA-LncBase v2 and GSE156720. Finally, the visualization protein‑protein interaction (PPI), competitive endogenous RNA (ceRNA) network was constructed using Cytoscape v3.1. Results: By analyzing GSE151021 and GSE156720, 23 upregulated mRNAs and 10 downregulated mRNAs were identified as sharing the differentially expressed genes (DEGs) between CRC and adjacent tissues. Furthermore, nucleolar protein 14 ( Conclusions: We identified a series of DElncRNAs, DEmRNAs, and DEmiRNAs in CRC that might be considered potential biomarkers in understanding the complex molecular pathways leading to CRC development.
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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.