Title:Identification of Ferroptosis-Related Prognostic Models and FDFT1
as a Potential Ferroptosis Driver in Colorectal Cancer
Volume: 33
Issue: 1
Author(s): Lili Duan, Lu Cao, Jinqiang Liu, Zixiang Wang, Jie Liang, Fan Feng*, Jian Zhang*, Liu Hong*Jianyong Zheng*
Affiliation:
- Department of Gastrointestinal Surgery, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China
- Department of Biochemistry and Molecular
Biology, Air Force Medical University, Xi'an, 710032, China
- Innovation Research Institute, Xijing
Hospital, Air Force Medical University, Xi’an, 710032, China
- Department of Gastrointestinal Surgery, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China
- Department of Gastrointestinal Surgery, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China
Keywords:
Colorectal cancer, ferroptosis, bioinformatics, prognosis, FDFT1, disease-free survival.
Abstract:
Aims: We aimed to develop Ferroptosis-Related Gene (FRG) signatures to predict
overall survival (OS) along with disease-free survival (DFS) in individuals with colorectal
cancer (CRC).
Background: Prediction of CRC prognosis is challenging. Ferroptosis constitutes a newly
reported kind of cell death, and its association with CRC prognosis remains unexplored.
Objective: This research endeavored to establish a prognostic risk signature for colorectal
cancer by leveraging ferroptosis-related genes (FRGs), with the objective of refining prognostic
precision in clinical settings.
Methods: The clinical data and mRNA expression profiles were obtained from The Cancer
Genome Atlas (TCGA) colorectal cancer cohorts. The Lasso algorithm was employed to develop
the overall survival (OS) and disease-free survival (DFS) prediction models. These
models were subsequently validated using independent data from GSE38832.
Results: Our research unveiled a significant difference in the expression levels of 85% of ferroptosis-
related genes (FRGs) between CRC tissues and paracancer tissues. Out of these, 11
prognostic genes were pinpointed through univariate Cox analysis. By employing two models,
patients were stratified into low- and high-risk groups based on predicted risk scores,
which were subsequently validated as independent prognostic factors via multivariate Cox
analysis. The robustness of these models was further confirmed through Receiver Operating
Characteristic (ROC) curve analysis. Functional enrichment analysis indicated a predominance
of cancer-associated pathways in the high-risk group, including WNT signaling, along
with variations in immune status between the two risk categories. Leveraging the Connectivity
Map (CMap) database, a total of sixteen potential therapeutic drugs were identified. Additionally,
in vitro experiments corroborated that Farnesyl-Diphosphate Farnesyltransferase 1
(FDFT1) was underexpressed in CRC and exhibited tumor suppressive properties. More specifically,
FDFT1 may augment ferroptosis in CRC by modulating the expression of the Iron--
Sulfur Cluster Assembly Enzyme (ISCU).
Conclusion: Our study highlighted the significance of ferroptosis-related genes in the pathogenesis
of CRC and underscored the potential of ferroptosis-related gene-based risk signatures
as valuable tools for improving prognostic accuracy and tailoring therapeutic strategies.
However, the validity of these predictive models required further validation through real-
world studies to ensure their reliability and applicability.
