Predictors of immunotherapy benefit in Merkel cell carcinoma

默克尔细胞癌免疫治疗获益的预测因素

阅读:1

Abstract

Merkel cell carcinoma is a rare cancer for which immune checkpoint blockade is standard-of-care for recurrent/metastatic disease. However, not all patients benefit from immunotherapy. A greater understanding of molecular mechanisms and predictive biomarkers are unmet needs. We retrospectively analyzed electronic health records and next-generation sequencing data of 45 patients treated at our institution from 2013 to 2020 to understand clinical and genomic correlates of benefit from immunotherapy. Our cohort predominantly included individuals with stage III disease at primary disease diagnosis and individuals with stage IV disease at recurrent/metastatic disease diagnosis. Most received immunotherapy as first-line treatment. 43% experienced objective response (median duration of response 24.2 months, 95% confidence interval 8.8-not reached). Median overall survival was 15.5 months (95% confidence interval 9.0-28.7) (median follow-up 25.2 months). Less advanced stage at primary disease diagnosis and shorter disease-free interval between completion of initial treatment and recurrence were each associated with greater odds of response (odds ratio of 0.06, p = 0.04 for stage; odds ratio 0.75, p = 0.05 for disease-free interval). Single-nucleotide variants in ARID2 and NTRK1 were associated with response (p = 0.05, without Bonferroni correction), while none of Merkel cell polyomavirus status, total mutational burden, ultraviolet mutational signatures, and copy-number alterations predicted outcomes. Patients with shorter disease-free interval may be particularly suitable immunotherapy candidates. Our molecular findings point to ARID2 and NTRK1 as potential predictive markers and/or therapeutic targets (e.g., with Trk inhibitors), although this association needs to be confirmed in a larger sample.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。