Construction of an immune predictive model and identification of TRIP6 as a prognostic marker and therapeutic target of CRC by integration of single-cell and bulk RNA-seq data
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed a molecular immune prediction model for colorectal cancer (CRC) using RNA sequencing. The model accurately predicts patient outcomes and identifies TRIP6 as a potential therapeutic target for CRC.
Area Of Science
- Oncology
- Immunology
- Genomics
Background
- Limited understanding of colorectal cancer (CRC) immunology and outcome prediction using bulk RNA sequencing.
- Need for robust methods to identify immune status and prognostic signatures in CRC.
Purpose Of The Study
- To identify the immune status of colorectal cancer (CRC) patients.
- To construct a prognostic model using bulk and single-cell RNA sequencing (scRNA-seq).
- To identify prognostic gene signatures for CRC.
Main Methods
- Utilized scRNA-seq and bulk RNA-seq data from CRC patients.
- Performed differential gene expression, functional enrichment, and random forest analyses.
- Developed a logistic regression-based immune prediction model using LASSO feature selection.
Main Results
- Identified seven major cell subtypes via scRNA-seq.
- Constructed a molecular immune predictive model correlating risk scores with overall survival, stage, and immune infiltration.
- Confirmed TRIP6 upregulation in CRC and demonstrated its role in inhibiting proliferation, migration, and invasion in vitro.
Conclusions
- The developed molecular predictive model effectively distinguishes CRC patient immune status.
- TRIP6 is identified as a potential oncogene in CRC, showing promise for targeted therapy and as a prognostic marker.
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