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趋化因子表达可预测实体癌中T细胞炎症反应,并通过检查点抑制改善生存率。

Chemokine expression predicts T cell-inflammation and improved survival with checkpoint inhibition across solid cancers.

作者信息

Romero Joan Miguel, Titmuss Emma, Wang Yifan, Vafiadis James, Pacis Alain, Jang Gun Ho, Zhang Amy, Golesworthy Bryn, Lenko Tatiana, Williamson Laura M, Grünwald Barbara, O'Kane Grainne M, Jones Steven J M, Marra Marco A, Wilson Julie M, Gallinger Steven, Laskin Janessa, Zogopoulos George

机构信息

Research Institute of the McGill University Health Centre, Montréal, QC, Canada.

Rosalind and Morris Goodman Cancer Institute of McGill University, Montréal, QC, Canada.

出版信息

NPJ Precis Oncol. 2023 Aug 9;7(1):73. doi: 10.1038/s41698-023-00428-2.

Abstract

Immune checkpoint inhibitors (ICI) are highly effective in specific cancers where canonical markers of antitumor immunity are used for patient selection. Improved predictors of T cell-inflammation are needed to identify ICI-responsive tumor subsets in additional cancer types. We investigated associations of a 4-chemokine expression signature (c-Score: CCL4, CCL5, CXCL9, CXCL10) with metrics of antitumor immunity across tumor types. Across cancer entities from The Cancer Genome Atlas, subgroups of tumors displayed high expression of the c-Score (c-Score) with increased expression of immune checkpoint (IC) genes and transcriptional hallmarks of the cancer-immunity cycle. There was an incomplete association of the c-Score with high tumor mutation burden (TMB), with only 15% of c-Score tumors displaying ≥10 mutations per megabase. In a heterogeneous pan-cancer cohort of 82 patients, with advanced and previously treated solid cancers, c-Score tumors had a longer median time to progression (103 versus 72 days, P = 0.012) and overall survival (382 versus 196 days, P = 0.038) following ICI therapy initiation, compared to patients with low c-Score expression. We also found c-Score stratification to outperform TMB assignment for overall survival prediction (HR = 0.42 [0.22-0.79], P = 0.008 versus HR = 0.60 [0.29-1.27], P = 0.18, respectively). Assessment of the c-Score using the TIDE and PredictIO databases, which include ICI treatment outcomes from 10 tumor types, provided further support for the c-Score as a predictive ICI therapeutic biomarker. In summary, the c-Score identifies patients with hallmarks of T cell-inflammation and potential response to ICI treatment across cancer types, which is missed by TMB assignment.

摘要

免疫检查点抑制剂(ICI)在使用抗肿瘤免疫的经典标志物进行患者选择的特定癌症中具有高度有效性。需要改进T细胞炎症的预测指标,以识别其他癌症类型中对ICI有反应的肿瘤亚群。我们研究了一种4趋化因子表达特征(c评分:CCL4、CCL5、CXCL9、CXCL10)与不同肿瘤类型的抗肿瘤免疫指标之间的关联。在来自癌症基因组图谱的各种癌症实体中,肿瘤亚组显示出c评分(c-Score)的高表达,同时免疫检查点(IC)基因的表达增加以及癌症免疫循环的转录特征。c评分与高肿瘤突变负担(TMB)之间的关联并不完全,只有15%的c评分肿瘤每兆碱基显示≥10个突变。在一个由82例患有晚期且先前接受过治疗的实体癌患者组成的异质性泛癌队列中,与c评分低表达的患者相比,c评分肿瘤在开始ICI治疗后的中位进展时间更长(103天对72天,P = 0.012),总生存期更长(382天对196天,P = 0.038)。我们还发现,在总生存期预测方面,c评分分层优于TMB分类(HR分别为0.42 [0.22 - 0.79],P = 0.008对HR为0.60 [0.29 - 1.27],P = 0.18)。使用TIDE和PredictIO数据库评估c评分,这两个数据库包含10种肿瘤类型的ICI治疗结果,进一步支持了c评分作为预测ICI治疗生物标志物的作用。总之,c评分能够识别出具有T细胞炎症特征且可能对跨癌症类型的ICI治疗有反应的患者,而TMB分类则无法做到这一点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b922/10412582/ed10414aaccb/41698_2023_428_Fig1_HTML.jpg

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