Dis Colon Rectum 2021 Feb 1. Epub 2021 Feb 1.
Department of General Surgery & Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, 510515, China. School of Science, Jimei University, Xiamen, Fujian, 361021, China. Department of Radiology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, China. Key Laboratory of OptoElectronic Science and Technology for Medicine of the Ministry of Education & Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, Fujian, 350007, China.
Background: The current clinicopathological risk factors do not accurately predict disease recurrence in patients with T4N0M0 colon cancer. We hypothesized that the collagen signature combined with clinicopathological risk factors (new model) had a better prognostic value than clinicopathological risk factors alone (clinicopathological model).
Objective: This study aimed to establish a collagen signature in the tumor microenvironment and to validate its role in predicting the recurrence of T4N0M0 colon cancer.
Design: This was a retrospective study.
Settings: This study took place at a tertiary medical center.
Patients: Patients with T4N0M0 colon cancer who underwent surgery at our center between 2009 and 2015 (n=416) were included.
Intervention: A total of 142 collagen features were analyzed in the tumor microenvironment in specimens of colon cancer using second harmonic generation imaging. A collagen signature was constructed using a LASSO Cox regression model.
Main Outcome Measures: Disease-free survival and overall survival.
Results: The training and testing cohorts consisted of 291 and 125 randomly assigned samples, with recurrence rates of 19.9% and 22.4%, respectively. A 3-feature-based collagen signature predicted the recurrence risk at 1, 3, and 5 years, with the area under the receiver-operating characteristic curves of 0.808, 0.832, and 0.791 in the training cohort and 0.836, 0.807, and 0.794 in the testing cohort, respectively. Multivariate analysis revealed that the collagen signature could independently predict the disease-free survival (HR=7.17, p<0.001) and overall survival rates (HR=5.03, p<0.001). The new model had a better prognostic value than the clinicopathological model, which included four clinicopathological risk factors: obstruction or perforation, lymphovascular invasion, tumor budding, and no chemotherapy.
Limitations: This study was limited by its retrospective design.
Conclusions: The collagen signature in the tumor microenvironment may be a new prognostic marker that can effectively predict the recurrence and survival of patients with T4N0M0 colon cancer. See Video Abstract at http://links.lww.com/DCR/B503 .