A novel epithelial‐mesenchymal transition molecular signature predicts the oncological outcomes in colorectal cancer

• Published in: Journal of cellular and molecular medicine Vol. 25; no. 7; pp. 3194 - 3204
• Main Authors: Shan, Zezhi, Wu, Wen, Yan, Xuebing, Yang, Yongzhi, Luo, Dakui, Liu, Qi, Li, Xinxiang, Goel, Ajay, Ma, Yanlei
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.04.2021; John Wiley and Sons Inc
• Subjects: Clustering; Colorectal cancer; Colorectal carcinoma; Epithelial cells; epithelial‐Mesenchymal Transition; Gene expression; Growth factors; immunity; Lymph nodes; Medical prognosis; Mesenchyme; Metastases; Metastasis; Microenvironments; Multivariate analysis; Nomograms; Original; Patients; Principal components analysis; Prognosis; Regression analysis; risk score model; Software; Statistical analysis; Transcription factors; Tumor microenvironment; Tumors; colorectal cancer; immunity; risk score model; prognosis; epithelial-Mesenchymal Transition
• ISSN: 1582-1838; 1582-4934; 1582-4934
• DOI: 10.1111/jcmm.16387

Epithelial‐mesenchymal transition (EMT), a biological process involving the transformation of epithelial cells into mesenchymal cells, promotes tumour initiation and metastasis. The aim of this study was to construct an EMT molecular signature for predicting colorectal cancer (CRC) prognosis and evaluate the efficacy of the model. The risk scoring system, constructed by log‐rank test and multivariate Cox regression analysis according to EMT‐related gene expression in CRC patients from TCGA database, demonstrated the highest correlation with prognosis compared with other parameters in CRC patients. The risk scores were significantly correlated with more lymph node metastasis, distal metastasis and advanced clinical stage of CRC. The model was further successfully validated in two independent external cohorts from GEO database. Furthermore, we developed a nomogram to integrate the EMT signature with the pathological stage of CRC, which was found to perform well in predicting the overall survival. Additionally, this risk scoring model was found to be associated with immune cell infiltration, implying a potential role of EMT involved in immunity regulation in tumour microenvironment. Taken together, our novel EMT molecular model may be useful in identifying high‐risk patients who need an intensive follow‐up and more aggressive therapy, finally contributing to more precise individualized therapeutic strategies.