Cell-free DNA copy number variations predict efficacy of immune checkpoint inhibitor-based therapy in hepatobiliary cancers. Issue 5 (10th May 2021)

• Record Type: Journal Article
• Authors: Yang, Xu; Hu, Ying; Yang, Keyan; Wang, Dongxu; Lin, Jianzhen; Long, Junyu; Xie, Fucun; Mao, Jinzhu; Bian, Jin; Guan, Mei; Pan, Jie; Huo, Li; Hu, Ke; Yang, Xiaobo; Mao, Yilei; Sang, Xinting; Zhang, Jiao; Wang, Xi; Zhang, Henghui; Zhao, Haitao
• Is Part Of: Journal for immunotherapy of cancer. Volume 9:Issue 5(2021)
• Publication Date: 2021-05-10
• Subjects: immunotherapy -- liver neoplasms -- tumor biomarkers; Cancer -- Immunotherapy -- Periodicals; Cancer -- Immunological aspects -- Periodicals; Tumors -- Immunological aspects -- Periodicals; Immunotherapy -- Periodicals; 616.99406105
• DOI: 10.1136/jitc-2020-001942
• Languages: English
• ISSNs: 2051-1426

Abstract

Abstract : Background: This study was designed to screen potential biomarkers in plasma cell-free DNA (cfDNA) for predicting the clinical outcome of immune checkpoint inhibitor (ICI)-based therapy in advanced hepatobiliary cancers. Methods: Three cohorts including 187 patients with hepatobiliary cancers were recruited from clinical trials at the Peking Union Medical College Hospital. Forty-three patients received combination therapy of programmed cell death protein 1 (PD-1) inhibitor with lenvatinib (ICI cohort 1), 108 patients received ICI-based therapy (ICI cohort 2) and 36 patients received non-ICI therapy (non-ICI cohort). The plasma cfDNA and blood cell DNA mutation profiles were assessed to identify efficacy biomarkers by a cancer gene-targeted next-generation sequencing panel. Results: Based on the copy number variations (CNVs) in plasma cfDNA, the CNV risk score model was constructed to predict survival by using the least absolute shrinkage and selection operator Cox regression methods. The results of the two independent ICI-based therapy cohorts showed that patients with lower CNV risk scores had longer overall survival (OS) and progression-free survival (PFS) than those with high CNV risk scores (log-rank p<0.01). In the non-ICI cohort, the CNV risk score was not associated with PFS or OS. Furthermore, the results indicated that 53% of patients with low CNV risk scores achieved durable clinical benefit; in contrast, 88% of patients with high CNV risk scores could not benefit from combination therapy (p<0.05). Conclusions: The CNVs in plasma cfDNA could predict the clinical outcome of the combination therapy of PD-1 inhibitor with lenvatinib and other ICI-based therapies in hepatobiliary cancers.