彭布罗利珠单抗
放射治疗
乳腺癌
医学
免疫疗法
三阴性乳腺癌
仿形(计算机编程)
肿瘤科
生物
计算生物学
内科学
癌症
癌症研究
计算机科学
操作系统
作者
Stephen L. Shiao,Kenneth Gouin,Nathan Ing,Alice Y. Ho,Reva Basho,Aagam Shah,Richard H. Mebane,David Zitser,Andrew Martinez,Natalie-Ya Mevises,Bassem Ben-Cheikh,Regina M. Henson,Monica Mita,Philomena F. McAndrew,Scott Karlan,Armando E. Giuliano,Alice Chung,Farin Amersi,Catherine Dang,Heather Richardson
出处
期刊:Cancer Cell
[Cell Press]
日期:2024-01-01
卷期号:42 (1): 70-84.e8
被引量:28
标识
DOI:10.1016/j.ccell.2023.12.012
摘要
Summary
Strategies are needed to better identify patients that will benefit from immunotherapy alone or who may require additional therapies like chemotherapy or radiotherapy to overcome resistance. Here we employ single-cell transcriptomics and spatial proteomics to profile triple negative breast cancer biopsies taken at baseline, after one cycle of pembrolizumab, and after a second cycle of pembrolizumab given with radiotherapy. Non-responders lack immune infiltrate before and after therapy and exhibit minimal therapy-induced immune changes. Responding tumors form two groups that are distinguishable by a classifier prior to therapy, with one showing high major histocompatibility complex expression, evidence of tertiary lymphoid structures, and displaying anti-tumor immunity before treatment. The other responder group resembles non-responders at baseline and mounts a maximal immune response, characterized by cytotoxic T cell and antigen presenting myeloid cell interactions, only after combination therapy, which is mirrored in a murine model of triple negative breast cancer.
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