ArticleBMC medical genomics2024
Identification and analysis of key genes related to efferocytosis in colorectal cancer.
Article in BMC medical genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Review
- Association of Serum ELMO-3 Levels with Metastatic Status and Survival Outcomes in Non-Small Cell Lung Cancer.Current issues in molecular biology · 2026Article
- Construction of a Mitochondria-Related Gene Diagnostic Model Based on Integrated Multiomics Data and Functional Validation of ANK2 as a Key Regulator in Colorectal Cancer.International journal of genomics · 2026Article
- Tumor Microenvironment Responsive and Platelet Membrane Coated Polydopamine Nanoparticles for Cancer Radiosensitization by Inducing Cuproptosis.International journal of nanomedicine · 2025Article
- TMOD2 and DOCK4 as Novel Gut Microbiota-Associated Biomarkers for Colorectal Adenoma: Integrated Transcriptomic Analysis and Therapeutic Target Identification.Mediators of inflammation · 2025Article
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8 authors.
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Abstract
The impact of efferocytosis-related genes (ERGs) on the diagnosis of colorectal cancer (CRC) remains unclear. In this study, efferocytosis-associated biomarkers for the diagnosis of CRC were identified by integrating data from transcriptome sequencing and public databases. Finally, the expression of biomarkers was validated by real-time quantitative polymerase chain reaction (RT-qPCR). Our study may provide a reference for CRC diagnosis.
backgroundIt has been shown that some efferocytosis related genes (ERGs) are associated with the development of cancer. However, it is still uncertain how ERGs may influence the diagnosis of colorectal cancer (CRC).
methodsIn our study, the CRC cohorts were gained from transcriptome sequencing and the gene expression omnibus (GEO) database (GSE71187). Efferocytosis related biomarkers with diagnostic utility for CRC were identified through combining differentially expressed analysis, machine learning algorithms, and receiver operating characteristic (ROC) analysis. Then, infiltration abundance of immune cells between CRC and control was evaluated. The regulatory networks (including mRNA-miRNA-lncRNA and miRNA/transcription factors (TF)-mRNA networks) were created. Finally, the expression of biomarkers was validated via real-time quantitative polymerase chain reaction (RT-qPCR).
resultsThere were 3 biomarkers (ELMO3, P2RY12, and PDK4) related diagnosis for CRC patients gained. ELMO3 was highly expressed in CRC group, while P2RY12 and PDK4 was lowly expressed. Besides, the infiltrating abundance of 3 immune cells between CRC and control groups was significantly differential, namely activated CD4 memory T cells, macrophages M0, and resting mast cells. We then constructed a mRNA-miRNA-lncRNA network containing 3 mRNAs, 33 miRNAs, and 22 lncRNAs, and a miRNA/TF-mRNA network including 3 mRNAs, 33 miRNAs, and 7 TFs. Additionally, RT-qPCR results revealed that the expression trends of all biomarkers were consistent with the transcriptome sequencing data and GSE71187.
conclusionTaken together, this study provides three efferocytosis related biomarkers (ELMO3, P2RY12, and PDK4) for diagnosis of CRC, providing a scientific reference for further studies of CRC.
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