ArticleBiochemistry research international2019
Integrated Analysis of Oncogenic Networks in Colorectal Cancer Identifies GUCA2A as a Molecular Marker.
Article in Biochemistry research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Guanylate cyclase-C Signaling Axis as a theragnostic target in colorectal cancer: a systematic review of literature.Frontiers in oncology · 2023Pooled it
- Integrated Bioinformatics Identification and Multi-Dimensional Characterization of Diagnostic Hub Genes in Colorectal Cancer.Current issues in molecular biology · 2026Article
- GUCA2A dysregulation as a promising biomarker for accurate diagnosis and prognosis of colorectal cancer.Clinical and experimental medicine · 2024Article
- Identification of modules and key genes associated with breast cancer subtypes through network analysis.Scientific reports · 2024Article
- Identification of GUCA2A and COL3A1 as prognostic biomarkers in colorectal cancer by integrating analysis of RNA-Seq data and qRT-PCR validation.Scientific reports · 2023Article
- Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents.BMC medical genomics · 2023Article
- Alterations in Gene Pair Correlations as Potential Diagnostic Markers for Colon Cancer.International journal of molecular sciences · 2022Article
- Genome-wide DNA methylation and gene expression patterns of androgenetic haploid tiger pufferfish (Takifugu rubripes) provide insights into haploid syndrome.Scientific reports · 2022Article
- Reference Module-Based Analysis of Ovarian Cancer Transcriptome Identifies Important Modules and Potential Drugs.Biochemical genetics · 2022Article
- Identification of Down-Regulated ADH1C is Associated With Poor Prognosis in Colorectal Cancer Using Bioinformatics Analysis.Frontiers in molecular biosciences · 2022Article
- Exploring Immune-Related Prognostic Signatures in the Tumor Microenvironment of Colon Cancer.Frontiers in genetics · 2022Article
- Employing bioinformatics analysis to identify hub genes and microRNAs involved in colorectal cancer.Medical oncology (Northwood, London, England) · 2021Article
- Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer.International journal of molecular sciences · 2021Article
- Integrated transcriptomics explored the cancer-promoting genes CDKN3 in esophageal squamous cell cancer.Journal of cardiothoracic surgery · 2021Article
- The Importance of Sex in the Discovery of Colorectal Cancer Prognostic Biomarkers.International journal of molecular sciences · 2021Article
- Immune infiltration and prognostic and diagnostic use of LGALS4 in colon adenocarcinoma and bladder urothelial carcinoma.American journal of translational research · 2021Article
- Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder.Biomolecules · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) is one of the most common and deadly malignancies in the world. In China, the morbidity rate of CRC has increased during the period 2000 to 2011. Biomarker detection for early CRC diagnosis can effectively reduce the mortality of patients with CRC. To explore the underlying mechanisms of effective biomarkers and identify more of them, we performed weighted correlation network analysis (WGCNA) on a GSE68468 dataset generated from 378 CRC tissue samples. We screened the gene set (module), which was significantly associated with CRC histology, and analyzed the hub genes. The key genes were identified by obtaining six colorectal raw data (i.e., GSE25070, GSE44076, GSE44861, GSE21510, GSE9348, and GSE21815) from the GEO database (https://www.ncbi.nlm.nih.gov/geo). The robust differentially expressed genes (DEGs) in all six datasets were calculated and obtained using the library "RobustRankAggreg" package in R 3.5.1. An integrated analysis of CRC based on the top 50 downregulated DEGs and hub genes in the red module from WGCNA was conducted, and the intersecting genes were screened. The Kaplan-Meier plot was further analyzed, and the genes associated with CRC prognosis based on patients from the TCGA database were determined. Finally, we validated the candidate gene in our clinical CRC specimens. We postulated that the candidate genes screened from the database and verified by our clinical pathological data may contribute to understanding the molecular mechanisms of tumorigenesis and may serve as potential biomarkers for CRC diagnosis and treatment.
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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.