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突变预测免疫检查点抑制剂的疗效:从 NSCLC 到多种癌症。

mutation predicts the effect of immune checkpoint inhibitor: From NSCLC to multiple cancers.

机构信息

Shanghai Lung Cancer Center, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

出版信息

Front Immunol. 2022 Nov 3;13:955800. doi: 10.3389/fimmu.2022.955800. eCollection 2022.

DOI:10.3389/fimmu.2022.955800
PMID:36405701
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9669061/
Abstract

BACKGROUND

The emergence of immune checkpoint inhibitors (ICIs) is one of the most promising breakthroughs for the treatment of multiple cancer types, but responses vary. Growing evidence points to a link between developmental signaling pathway-related genes and antitumor immunity, but the association between the genomic alterations in these genes and the response to ICIs still needs to be elucidated.

METHODS

Clinical data and sequencing data from published studies and our cohort were collected to analyze the association of the mutation status of with the efficacy of ICI therapy in the non-small cell lung cancer (NSCLC) cohort and the pan-cancer cohort. Furthermore, the correlation between mutation and immunotherapeutic biomarkers such as immune cell infiltration, immune-related genes, and underlying signaling pathways was analyzed. Three mutant plasmids were transfected into cells to explore the mutation status in the context of its expression and cell growth.

RESULT

In the NSCLC discovery cohort, the median progression-free survival in the mutant (SMO_MUT) was longer than that in the wild type (SMO_WT) (23.0 vs. 3.8 months, adjusted  = 0.041). This finding was further confirmed in the NSCLC validation cohort (8.7 vs. 5.1 months, adjusted  = 0.013). In the pan-cancer cohort ( = 1,347), a significant overall survival advantage was observed in patients with mutations [not reached (NR) vs. 18 months, adjusted  = 0.024]. In the subgroup analysis, the survival advantage of SMO_MUT against SMO_WT was prominent and consistent across genders, ages, treatment types, cancer types, and the tumor mutation burden (TMB) status (all  > 0.05). In an experiment, we found that both the mutant and wild-type plasmids can promote the expression of , but the mutant plasmid had lower mRNA and protein levels than the wild type. In CCK-8 experiments, we found that SMO_MUT plasmids can improve the growth of Calu-1 and PC-9 cells, but this capability varied between different mutations and cells. Upon further exploration, the mutation status was found to be related to a higher TMB, more neoantigen load, more DNA damage repair (DDR) mutations, higher microsatellite instability (MSI) score, and higher CD8 T-cell infiltration.

CONCLUSIONS

The mutation status is an independent prognostic factor that can be used to predict better clinical outcomes of ICI treatment across multiple cancer types.

摘要

背景

免疫检查点抑制剂(ICIs)的出现是治疗多种癌症类型最有希望的突破之一,但反应各不相同。越来越多的证据表明,发育信号通路相关基因与抗肿瘤免疫之间存在联系,但这些基因的基因组改变与对 ICI 治疗的反应之间的关系仍需阐明。

方法

收集已发表研究和我们队列的临床数据和测序数据,以分析非小细胞肺癌(NSCLC)队列和泛癌队列中 突变状态与 ICI 治疗疗效的关系。此外,还分析了 突变与免疫治疗生物标志物(如免疫细胞浸润、免疫相关基因和潜在信号通路)之间的相关性。将三个 突变质粒转染到细胞中,以研究在其表达和细胞生长情况下 突变状态。

结果

在 NSCLC 发现队列中, 突变(SMO_MUT)患者的中位无进展生存期长于野生型(SMO_WT)患者(23.0 与 3.8 个月,调整 = 0.041)。这一发现在 NSCLC 验证队列中得到了进一步证实(8.7 与 5.1 个月,调整 = 0.013)。在泛癌队列中( = 1347),突变患者的总生存期有显著优势[未达到(NR)与 18 个月,调整 = 0.024]。在亚组分析中,SMO_MUT 对 SMO_WT 的生存优势在性别、年龄、治疗类型、癌症类型和肿瘤突变负担(TMB)状态方面均显著且一致(均 > 0.05)。在一项实验中,我们发现突变型和野生型质粒均能促进 的表达,但突变型质粒的 mRNA 和蛋白水平均低于野生型。在 CCK-8 实验中,我们发现 SMO_MUT 质粒可改善 Calu-1 和 PC-9 细胞的生长,但这种能力因不同的突变和细胞而异。进一步探索发现, 突变状态与更高的 TMB、更多的新抗原负荷、更多的 DNA 损伤修复(DDR)突变、更高的微卫星不稳定性(MSI)评分和更高的 CD8 T 细胞浸润有关。

结论

突变状态是一个独立的预后因素,可用于预测多种癌症类型的 ICI 治疗的临床结局更好。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/aabca0decfe9/fimmu-13-955800-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/116fa13c033b/fimmu-13-955800-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/9dd66d80cf65/fimmu-13-955800-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/f7e90cf2fd22/fimmu-13-955800-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/23224d80a5f0/fimmu-13-955800-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/da2abe6206b2/fimmu-13-955800-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/aabca0decfe9/fimmu-13-955800-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/116fa13c033b/fimmu-13-955800-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/ec1985ec3297/fimmu-13-955800-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/c3f7d20ae902/fimmu-13-955800-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/9dd66d80cf65/fimmu-13-955800-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/f7e90cf2fd22/fimmu-13-955800-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/23224d80a5f0/fimmu-13-955800-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/da2abe6206b2/fimmu-13-955800-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b27/9669061/aabca0decfe9/fimmu-13-955800-g008.jpg

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