Improving the overall survival prognosis prediction accuracy: A 9‐gene signature in CRC patients

• Main Authors: Wenbo Zheng, Yijia Lu, Xiaochuang Feng, Chunzhao Yang, Ling Qiu, Haijun Deng, Qi Xue, Kai Sun
• Format: Article
• Language: English
• Published: Wiley 2021-09-01
• Series: Cancer Medicine
• Subjects: CRC; nomogram; prognosis; survival‐related genes; WGCNA
• Online Access: https://doi.org/10.1002/cam4.4104

Abstract Colorectal cancer (CRC) is a malignant tumor and morbidity rates are among the highest in the world. The variation in CRC patients' prognosis prompts an urgent need for new molecular biomarkers to improve the accuracy for predicting the CRC patients' prognosis or as a complement to the traditional TNM staging for clinical practice. CRC patients' gene expression data of HTSeq‐FPKM and matching clinical information were downloaded from The Cancer Genome Atlas (TCGA) datasets. Patients were randomly divided into a training dataset and a test dataset. By univariate and multivariate Cox regression survival analyses and Lasso regression analysis, a prediction model which divided each patient into high‐or low‐risk group was constructed. The differences in survival time between the two groups were compared by the Kaplan–Meier method and the log‐rank test. The weighted gene co‐expression network analysis (WGCNA) was used to explore the relationship between all the survival‐related genes. The survival outcomes of patients whose overall survival (OS) time were significantly lower in the high‐risk group than that in the low‐risk group both in the training and test datasets. Areas under the ROC curves which termed AUC values of our 9‐gene signature achieved 0.823 in the training dataset and 0.806 in the test dataset. A nomogram was constructed for clinical practice when we combined the 9‐gene signature with TNM stage and age to evaluate the survival time of patients with CRC, and the C‐index increased from 0.739 to 0.794. In conclusion, we identified nine novel biomarkers that not only are independent prognostic indexes for CRC patients but also can serve as a good supplement to traditional clinicopathological factors to more accurately evaluate the survival of CRC patients.