Telomere-related gene risk model for prognosis prediction in colorectal cancer
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed a telomere-related gene biomarker to predict colorectal cancer (CRC) survival and treatment response. The model accurately identifies high-risk patients and guides therapy selection for better outcomes.
Area Of Science
- Oncology
- Genetics
- Bioinformatics
Background
- Colorectal cancer (CRC) is a leading global cancer.
- Telomeres play a role in CRC development and progression.
- The prognostic impact of telomere-related genes (TRGs) in CRC remains unclear.
Purpose Of The Study
- To investigate the prognostic value of TRGs in colorectal cancer.
- To develop a predictive model for CRC patient survival and treatment response.
Main Methods
- Retrospective analysis of CRC patient expression profiles and clinical data.
- Development of a telomere-related risk model using LASSO regression.
- Validation of the model using survival analysis, immune cell infiltration, and drug sensitivity assessments.
Main Results
- A ten-gene telomere-related risk model demonstrated high predictive accuracy for survival in CRC patients.
- High-risk patients showed advanced TNM stages, altered immune cell profiles, and reduced drug sensitivity.
- Expression of key TRGs (e.g., ACACB, TPX2, CD36, MMP1) was validated in CRC cells.
Conclusions
- A novel telomere-related biomarker effectively predicts CRC prognosis and treatment response.
- This biomarker can aid in selecting appropriate drug therapies for CRC patients.
- The findings offer potential guidance for personalized treatment strategies in CRC.
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