Identification of Ferroptosis-Related Prognostic Models and FDFT1 as a Potential Ferroptosis Driver in Colorectal Cancer
- Lili Duan 1,2, Lu Cao 3, Jinqiang Liu 1, Zixiang Wang 4, Jie Liang 5, Fan Feng 1, Jian Zhang 6,7, Liu Hong 1, Jianyong Zheng 1
- Lili Duan 1,2, Lu Cao 3, Jinqiang Liu 1
- 1Department of Gastrointestinal Surgery, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
- 2State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases, and Xijing Hospital of Digestive Diseases, Air Force Medical University, Xi'an, 710032, China.
- 3Department of Biomedical Engineering, Air Force Medical University, Xi'an, 10032, China.
- 4Department of Medical Oncology, Affiliated Jinling Hospital, Medical School, Nanjing University, Nanjing, 210000, China.
- 5The Eastern Theater Air Force Hospital, Nanjing, 210000, China.
- 6Department of Biochemistry and Molecular Biology, Air Force Medical University, Xi'an, 710032, China.
- 7Innovation Research Institute, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
- 0Department of Gastrointestinal Surgery, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China.
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed ferroptosis-related gene (FRG) signatures to predict survival in colorectal cancer (CRC) patients. These signatures show promise for improving prognostic accuracy and guiding treatment strategies in CRC.
Area Of Science
- Oncology
- Molecular Biology
- Genetics
Background
- Prognostic prediction in colorectal cancer (CRC) remains a significant clinical challenge.
- Ferroptosis, a distinct form of cell death, has emerged as a potential factor in cancer progression, but its role in CRC prognosis is largely unexplored.
Purpose Of The Study
- To develop and validate ferroptosis-related gene (FRG) signatures for predicting overall survival (OS) and disease-free survival (DFS) in colorectal cancer (CRC) patients.
- To establish a robust prognostic risk signature for CRC to enhance clinical prognostic precision.
Main Methods
- Utilized The Cancer Genome Atlas (TCGA) colorectal cancer (CRC) cohorts for clinical data and mRNA expression profiles.
- Employed the Lasso algorithm to construct OS and DFS prediction models based on FRGs.
- Validated the predictive models using independent datasets (GSE38832) and assessed their robustness via multivariate Cox and ROC analyses.
Main Results
- Identified significant differential expression of 85% of FRGs between CRC and adjacent normal tissues, pinpointing 11 prognostic genes.
- Developed two risk models stratifying patients into low- and high-risk groups, validated as independent prognostic factors.
- Functional analysis revealed associations with cancer pathways (e.g., WNT signaling) and immune status variations; identified 16 potential therapeutic drugs and confirmed FDFT1's tumor-suppressive role in CRC.
Conclusions
- Ferroptosis-related genes play a crucial role in CRC pathogenesis, and FRG-based risk signatures offer potential for improved prognostic accuracy.
- The developed signatures can aid in tailoring therapeutic strategies for colorectal cancer patients.
- Further validation in real-world clinical studies is necessary to confirm the reliability and applicability of these predictive models.
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