ArticleJournal of gastrointestinal oncology2022
Construction of a co-expression network and prediction of metastasis markers in colorectal cancer patients with liver metastasis.
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 11 papers.
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- Proteomic profiling of colorectal liver metastases reveals histopathological response-specific molecular signatures of chemotherapy efficacy.Journal of translational medicine · 2026Article
- Integrate bulk RNA and single-cell sequencing to identify prognostic genes associated with dietary restriction and circadian rhythm in colorectal cancer and conduct experimental verification.Clinical and experimental medicine · 2025Article
- SLC38A4 as a prognostic biomarker and correlated with immune infiltration in colorectal liver metastasis.Discover oncology · 2025Article
- Liver Tumor Prediction using Attention-Guided Convolutional Neural Networks and Genomic Feature Analysis.MethodsX · 2025Article
- Comprehensive Proteogenomic Profiling Reveals the Molecular Characteristics of Colorectal Cancer at Distinct Stages of Progression.Cancer research · 2024Article
- An unusual presentation of solitary ovarian metastasis from colorectal cancer in an elderly woman: a case report.Journal of gastrointestinal oncology · 2024Article
- New treatment alternatives for primary and metastatic colorectal cancer by an integrated transcriptome and network analyses.Scientific reports · 2024Article
- Establishing a carcinoembryonic antigen-associated competitive endogenous RNA network and forecasting an important regulatory axis in colon adenocarcinoma patients.Journal of gastrointestinal oncology · 2024Article
- Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach.Scientific reports · 2023Article
- 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.Journal of gastrointestinal oncology · 2023Article
- ANGPTL2+cancer-associated fibroblasts and SPP1+macrophages are metastasis accelerators of colorectal cancer.Frontiers in immunology · 2023Article
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Colorectal cancer (CRC) is a common global malignancy associated with high invasiveness, high metastasis, and poor prognosis. CRC commonly metastasizes to the liver, where the treatment of metastasis is both difficult and an important topic in current CRC management. Methods: Microarrays data of human CRC with liver metastasis (CRCLM) were downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database to identify potential key genes. Differentially expressed (DE) genes (DEGs) and DEmiRNAs of primary CRC tumor tissues and metastatic liver tissues were identified. Microenvironment Cell Populations (MCP)-counter was used to estimate the abundance of immune cells in the tumor micro-environment (TME), and weighted gene correlation network analysis (WGCNA) was used to construct the co-expression network analysis. Gene Ontology and Kyoto Encyclopaedia of Gene and Genome (KEGG) pathway enrichment analyses were conducted, and the protein-protein interaction (PPI) network for the DEGs were constructed and gene modules were screened. Results: Thirty-five pairs of matched colorectal primary cancer and liver metastatic gene expression profiles were screened, and 610 DEGs (265 up-regulated and 345 down-regulated) and 284 DEmiRNAs were identified. The DEGs were mainly enriched in the complement and coagulation cascade pathways and renin secretion. Immune infiltrating cells including neutrophils, monocytic lineage, and cancer-associated fibroblasts (CAFs) differed significantly between primary tumor tissues and metastatic liver tissues. WGCN analysis obtained 12 modules and identified 62 genes with significant interactions which were mainly related to complement and coagulation cascade and the focal adhesion pathway. The best subset regression analysis and backward stepwise regression analysis were performed, and eight genes were determined, including Conclusions: Our study implies complement and coagulation cascade and the focal adhesion pathway play a significant role in the development and progression of CRCLM, and
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