Clonal tracing reveals diverse patterns of response to immune checkpoint blockade

Author:

Gu Shengqing Stan,Wang Xiaoqing,Hu Xihao,Jiang Peng,Li Ziyi,Traugh Nicole,Bu Xia,Tang Qin,Wang Chenfei,Zeng Zexian,Fu Jingxin,Meyer Cliff,Zhang Yi,Cejas Paloma,Lim Klothilda,Wang Jin,Zhang Wubing,Tokheim Collin,Sahu Avinash Das,Xing Xiaofang,Kroger Benjamin,Ouyang Zhangyi,Long Henry,Freeman Gordon J.,Brown Myles,Liu X. ShirleyORCID

Abstract

Abstract Background Immune checkpoint blockade (ICB) therapy has improved patient survival in a variety of cancers, but only a minority of cancer patients respond. Multiple studies have sought to identify general biomarkers of ICB response, but elucidating the molecular and cellular drivers of resistance for individual tumors remains challenging. We sought to determine whether a tumor with defined genetic background exhibits a stereotypic or heterogeneous response to ICB treatment. Results We establish a unique mouse system that utilizes clonal tracing and mathematical modeling to monitor the growth of each cancer clone, as well as the bulk tumor, in response to ICB. We find that tumors derived from the same clonal populations showed heterogeneous ICB response and diverse response patterns. Primary response is associated with higher immune infiltration and leads to enrichment of pre-existing ICB-resistant cancer clones. We further identify several cancer cell-intrinsic gene expression signatures associated with ICB resistance, including increased interferon response genes and glucocorticoid response genes. These findings are supported by clinical data from ICB treatment cohorts. Conclusions Our study demonstrates diverse response patterns from the same ancestor cancer cells in response to ICB. This suggests the value of monitoring clonal constitution and tumor microenvironment over time to optimize ICB response and to design new combination therapies. Furthermore, as ICB response may enrich for cancer cell-intrinsic resistance signatures, this can affect interpretations of tumor RNA-seq data for response-signature association studies.

Funder

National Institutes of Health

Publisher

Springer Science and Business Media LLC

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