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Identification of an EMT-related Gene Signature Predicting Recurrence in Stage II/III Colorectal Cancer: A
Haoyu Ren1, Florian Bösch1,2, Elise Pretzsch1
1Department of General, Visceral, and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany.
Objective:
To identify a prognostic significant gene signature for predicting colorectal cancer (CRC) recurrence.
Background:
Traditional prognostic risk assessment in stage II/III CRC patients remains controversial. Epithelial-mesenchymal transition is thought to be closely related to the malignant progression of tumors. Thus, it is promising to establish a prognostic model based on epithelial-mesenchymal transition-related gene (ERG) signature.
Materials And Methods:
We retrospectively analyzed transcriptome profiles and clinical information of 1780 stage II/III CRC patients from 15 public datasets. Coefficient variant analysis was used to select reference genes for normalizing gene expression levels. Univariate, LASSO, and multivariate Cox regression analyses were combined to develop the ERG signature predicting disease-free survival (DFS). The patients were divided into high-risk and low-risk based on the ERG signature recurrence risk score. The survival analysis was performed in different CRC cohorts.
Results:
The proposed ERG signature contained 7 cancer-related ERGs and 3 reference genes. The ERG signature recurrence risk score was prognostically relevant in all cohorts ( P <0.05) and proved as an independent prognostic factor in the training cohort. In the pooled cohort, high-risk CRC patients exhibited worse DFS ( P <0.0001) and overall survival ( P =0.0058) than low-risk patients. The predictive performance of the ERG signature was superior to Oncotype DX colon cancer. An integrated decision tree and nomogram were developed to improve prognosis evaluation.
Conclusions:
The identified ERG signature is a promising and powerful biomarker predicting recurrence in CRC patients. Moreover, the presented ERG signature might help to stratify patients according to their tumor biology and contribute to personalized treatment.
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