Related Experiment Video
Updated: Apr 1, 2026
Development of Compendium for Esophageal Squamous Cell Carcinoma
Published on: April 12, 2024
Prognostic Biomarkers and Immunotherapeutic Insights of Circulating Tumor DNA Analysis in Advanced Esophageal
Yuqing Duan1,2, Tadayoshi Hashimoto1,3, Taro Shibuki1,4
1Translational Research Support Office, National Cancer Center Hospital East, Kashiwa, Japan.
Purpose:
Advanced esophageal squamous cell carcinoma (ESCC) has a poor prognosis, and current treatments provide limited survival benefits. This study aimed to identify prognostic biomarkers and therapeutic targets by genomic profiling of advanced ESCC using circulating tumor DNA (ctDNA).
Methods:
The SCRUM-MONSTAR GOZILA study is a nationwide, plasma-based molecular profiling project using Guardant360, involving 31 core cancer institutions in Japan. We evaluated the genomic landscape of advanced ESCC and investigated associations between specific alterations and overall survival (OS). The correlation between blood tumor mutation burden (bTMB) and clinical outcomes in patients with PD-1 inhibitors was also assessed using multiple cutoff values (2, 4, 6, 8, and 10 mutations/Mb).
Results:
Among 313 patients, alterations predominantly consisted of single nucleotide variants (SNVs, 68.9%) and copy number alterations (20.7%). TP53 was the most frequent alterations (88.5%), followed by PIK3CA (36.4%), NFE2L2 (24.3%), CCND1 (22.4%), and EGFR (20.1%). Amplifications in PIK3CA, FGFR1, CCND1, and EGFR, as well as mutations in NFE2L2, FGFR1, and RB1 were associated with worse OS (any P < .05). Multivariable analysis confirmed mutations in NFE2L2 or FGFR1 and amplifications in EGFR or PIK3CA as independent poor prognostic factors (all P < .05). In 142 patients treated with PD-1 inhibitors, no significant differences in objective response rate or progression-free survival were observed at different bTMB cutoff values (all P > .1).
Conclusion:
ctDNA analysis identified key genomic alterations linked to poor outcomes in advanced ESCC, revealing potential prognostic biomarkers and therapeutic targets. In contrast, bTMB did not show predictive value for the efficacy of PD-1 inhibitors in this study.
