OA06-LBA01.4. A Multimodal Classifier to Stratify Response to Neoadjuvant Chemoimmunotherapy in Locally Advanced Esophageal Squamous Cell Carcinoma Based on RCT-HCHTOG1909

Abstract Topic Esophageal Cancer: Adjuvant and Neo-Adjuvant Therapies Background The predictive utility of the PD-L1 combined positive score (CPS) for neoadjuvant immuno-chemotherapy in locally advanced esophageal squamous cell carcinoma (ESCC) remains suboptimal, highlighting a critical unmet need for better patient stratification. Methods we performed bulk RNA sequencing (RNA-seq), whole-exome sequencing (WES), and shallow whole-genome sequencing (sWGS) on pretreatment tumor samples from 102 patients enrolled in the HCHTOG1909 trial. Additionally, for a subset of these patients (N=80) for whom matched posttreatment samples available, we conducted a paired longitudinal analysis to investigate therapy-induced molecular changes. Through this approach, we identified baseline predictive biomarkers, including a gene expression signature and genomic alterations (CNVs/SNVs), and investigated therapy-induced dynamic changes associated with treatment response. Results By integrating these molecular features with macroscopic type and PD-L1 status, we developed the esophageal cancer multimodal immuno-chemotherapy classifier (EMIC), which effectively stratifies patients into two groups with distinct therapeutic responses: EMIC1 (predicted to benefit from combined immuno-chemotherapy) and EMIC2 (predicted to have equivalent outcomes with chemotherapy alone), providing a rationale for personalized treatment de-escalation. Conclusion In conclusion, by integrating bulk RNA-seq, whole-exome sequencing, and shallow whole-genome sequencing data from pretreatment tumor samples of 102 patients in the HCHTOG1909 trial, we have identified robust baseline predictive biomarkers. This multi-omics framework enables precise stratification of neoadjuvant chemotherapy patients who do not require addition of PD-1 antibody(EMIC2), allowing them to avoid the burden of ineffective treatment and immune-related adverse events. Future external validation and prospective clinical assessment will be essential to translate these integrative biomarkers into routine practice for personalized treatment decision-making.