Immuno-genomic profiling of biopsy specimens predicts neoadjuvant chemotherapy response in esophageal squamous cell carcinoma

• Published in: Cell reports. Medicine Vol. 3; no. 8; p. 100705
• Main Authors: Sasagawa, Shota, Kato, Hiroaki, Nagaoka, Koji, Sun, Changbo, Imano, Motohiro, Sato, Takao, Johnson, Todd A., Fujita, Masashi, Maejima, Kazuhiro, Okawa, Yuki, Kakimi, Kazuhiro, Yasuda, Takushi, Nakagawa, Hidewaki
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 16.08.2022; Elsevier
• Subjects: chemotherapy; Chemotherapy response; copy-number variants; esophageal squamous cell carcinoma; machine learning; neutrophils; Chemotherapy response; esophageal squamous cell carcinoma; machine learning; copy-number variants; neutrophils; chemotherapy
• ISSN: 2666-3791; 2666-3791
• DOI: 10.1016/j.xcrm.2022.100705

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive cancers and is primarily treated with platinum-based neoadjuvant chemotherapy (NAC). Some ESCCs respond well to NAC. However, biomarkers to predict NAC sensitivity and their response mechanism in ESCC remain unclear. We perform whole-genome sequencing and RNA sequencing analysis of 141 ESCC biopsy specimens before NAC treatment to generate a machine-learning-based diagnostic model to predict NAC reactivity in ESCC and analyzed the association between immunogenomic features and NAC response. Neutrophil infiltration may play an important role in ESCC response to NAC. We also demonstrate that specific copy-number alterations and copy-number signatures in the ESCC genome are significantly associated with NAC response. The interactions between the tumor genome and immune features of ESCC are likely to be a good indicator of therapeutic capability and a therapeutic target for ESCC, and machine learning prediction for NAC response is useful. [Display omitted] •Four different immune subtypes from RNA-seq of ESCC biopsy specimen•Neutrophils within tumors are associated with tumor sensitivity to NAC•Specific copy-number changes and signatures in ESCC are associated with NAC response•Machine learning prediction for NAC response using immunogenomics of ESCC is useful Sasagawa et al. show immunogenomic profiles of esophageal cancer biopsy specimens before chemotherapy and suggest interactions between tumor copy-number variants and immunity related with chemotherapy response. Neutrophils infiltration plays an important role in the response to chemotherapy. Machine learning using these immunogenomic large data can predict chemotherapy response.