Related Experiment Video
Updated: May 26, 2026
Development of Compendium for Esophageal Squamous Cell Carcinoma
Published on: April 12, 2024
Integrating genetic and transcriptomics data to predict neoadjuvant chemoradiotherapy for patients with esophageal
Tingyu Li1, Hongjun Li2, Xinyi Ye3
1Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China.
Background:
Esophageal squamous cell carcinoma (ESCC) exhibits heterogeneous responses to neoadjuvant chemoradiotherapy (nCRT) and understanding the molecular features of ESCC could improve patient management. This study aimed to investigate the differences in somatic mutations and gene expression profiles among esophageal cancer patients exhibiting varying responses to nCRT.
Methods:
A prospective cohort of 30 patients with ESCC undergoing nCRT was enrolled. Tumor and blood samples were collected prior to the initiation of nCRT. Following transcriptome profiling and identification of differentially expressed genes, the singscore algorithm was applied to construct a response prediction model, and its predictive performance was assessed.
Results:
The singscore method generated a unique score for each case. The score range of patients with Tumor Regression Score (TRS) 0-1 was -0.59 to 1. The area under the receiver operating characteristic (ROC) curve was 0.888 [95% confidence interval (CI): 0.773-1], with singscore =0 identified as the optimal cutoff value of the score (sensitivity: 80.0%, specificity: 78.9%, positive predictive value: 88.2%, negative predictive value: 69.2%). Singscore score was positively correlated with better overall survival (hazard ratio: 0.14, 95% CI: 0-0.374, P=0.01).
Conclusions:
In this exploratory study, the singscore model demonstrated promising predictive performance for nCRT response in ESCC, with singscore =0 as the optimal cutoff in our cohort. However, these findings require validation in larger, multi-center studies before clinical application can be considered.
