ArticleOncology letters2016
Microarray analysis of differentially-expressed genes and linker genes associated with the molecular mechanism of colorectal cancer.
Article in Oncology letters, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 23 citations in OpenAlex.
- Identification and evaluation of metabolic mRNAs and key miRNAs in colorectal cancer liver metastasis.Cancer cell international · 2025Article
- Downregulation of UDP-glucose 6-dehydrogenase predicts adverse outcomes in patients with colorectal cancer and promotes tumorigenesis.Scientific reports · 2025Article
- Review
- Aldehyde Dehydrogenase 2 Family Member (ALDH2) Is a Therapeutic Index for Oxaliplatin Response on Colorectal Cancer Therapy with Dysfunction p53.BioMed research international · 2022Article
- A merged microarray meta-dataset for transcriptionally profiling colorectal neoplasm formation and progression.Scientific data · 2021Article
- Article
- Molecular docking and machine learning analysis of Abemaciclib in colon cancer.BMC molecular and cell biology · 2020Article
- Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis.Oncology letters · 2020Article
- High expression of FABP4 and FABP6 in patients with colorectal cancer.World journal of surgical oncology · 2019Article
- Identification and Interaction Analysis of Molecular Markers in Colorectal Cancer by Integrated Bioinformatics Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2018Article
- Collagen IV-conveyed signals can regulate chemokine production and promote liver metastasis.Oncogene · 2018Article
- Upregulation of ALDH1B1 promotes tumor progression in osteosarcoma.Oncotarget · 2018Article
- Microarray analyses reveal genes related to progression and prognosis of esophageal squamous cell carcinoma.Oncotarget · 2017Article
- Analysis of long non-coding RNA expression profiles in ovarian cancer.Oncology letters · 2017Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide and remains the third leading cause of cancer-associated mortality. The present study aimed to fully elucidate the pathogenesis of CRC and identify associated genes in tumor development. Microarray GSE44076, GSE41328 and GSE44861 datasets were downloaded from the Gene Expression Omnibus database and integrated with meta-analysis. Differentially-expressed genes (DEGs) were identified from CRC samples compared with adjacent non-cancerous controls using the Limma package in R, followed by functional analysis using the Database for Annotation, Visualization, and Integrated Discovery online tool. A protein-protein interaction (PPI) network of DEGs and linker genes was constructed using NetBox software and modules were also mined. Functional annotation was performed for modules with a maximum number of nodes. Subsequent to meta-analysis to pool the data, one dataset that included 327 samples involved in 11,081 genes was obtained. A total of 697 DEGs were identified between CRC samples and adjacent non-cancerous controls. In the PPI network, modules 1 and 5 contained the maximum number of nodes. Collagen, type I, α1 (
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