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肿瘤突变负荷高的乳腺癌中免疫反应性肿瘤微环境的并发预测因子。

Concurrent predictors of an immune responsive tumor microenvironment within tumor mutational burden-high breast cancer.

作者信息

Sammons Sarah, Elliott Andrew, Barroso-Sousa Romualdo, Chumsri Saranya, Tan Antoinette R, Sledge George W, Tolaney Sara M, Torres Evanthia T Roussos

机构信息

Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States.

Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, MA, United States.

出版信息

Front Oncol. 2023 Aug 11;13:1235902. doi: 10.3389/fonc.2023.1235902. eCollection 2023.


DOI:10.3389/fonc.2023.1235902
PMID:37637072
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10457522/
Abstract

BACKGROUND: Data supporting high tumor mutational burden (TMB-H) as a lone biomarker for an immune-responsive tumor microenvironment (TME) in metastatic breast cancer (MBC) are weak, yet tumor agnostic approval in TMB-H advanced tumors provides immune checkpoint inhibition (ICI) as a clinical option. We evaluated concurrent predictors of immune-responsive and non-responsive TME within MBC. METHODS: Tumor samples from patients with MBC (N=5621) were analyzed by next-generation sequencing of DNA (592-gene panel or whole exome) and RNA (whole transcriptome) at Caris Life Sciences (Phoenix, AZ). TMB-H threshold was set to ≥ 10 muts/Mb. PDL-1 was evaluated using SP142 antibody. Gene expression profiling and RNA deconvolution were used to estimate immune and stromal cell population abundance in the TME, and transcriptomic signature of immunotherapy response (T cell-inflamed score). RESULTS: 461 (8.2%) TMB-H MBC samples were identified. Consistent with prior studies, TMB-H tumors exhibited significant dMMR/MSI-H enrichment (7 vs. 0%, p<0.0001) and PD-L1+ expression (36 vs. 28%, p<0.05) compared to TMB-L. Across all samples, T cell-inflamed scores were weakly correlated with TMB. TMB-H was not associated with significantly increased immune responsive cell types (CD8+ T-cells, NK cells, or B cells) or immune response gene signatures (e.g. antigen presentation), yet positive trends were observed, while immunosuppressive fibroblasts were significantly decreased in TMB-H tumors (0.84-fold change compared to TMB-L, P<0.05). HR+/HER2- breast cancer was the only subtype in which TMB-H tumors exhibited increased T cell-inflamed scores vs. TMB-L. Concurrent PD-L1+ or dMMR/MSI-H with TMB-H was associated with high T cell-inflamed scores in both HR+/HER2- and TNBC. Among several associated biomarkers, mutations and amplifications were positively associated with T-cell inflamed scores in TMB-H tumors; and mutations were negatively associated. CONCLUSION: High TMB alone does not strongly correlate with immune infiltrate or immune-related gene signatures in MBC. TMB-H predicts T-cell inflamed signature compared to TMB-L in HR+/HER2- tumors only. Along with MSI-H and PD-L1+, several biomarkers, including mutation and amplification, may help predict ICI benefit amongst TMB-H tumors. Co-occurring biomarkers within TMB-H breast cancer warrant evaluation in larger cohorts for response or resistance to ICI to develop composite predictive biomarkers in MBC.

摘要

背景:支持高肿瘤突变负荷(TMB-H)作为转移性乳腺癌(MBC)中免疫反应性肿瘤微环境(TME)的唯一生物标志物的数据较为薄弱,但TMB-H晚期肿瘤的泛肿瘤批准提供了免疫检查点抑制(ICI)作为一种临床选择。我们评估了MBC中免疫反应性和非反应性TME的并发预测指标。 方法:在Caris生命科学公司(亚利桑那州凤凰城),对MBC患者(N = 5621)的肿瘤样本进行DNA(592基因 panel或全外显子组)和RNA(全转录组)的下一代测序分析。TMB-H阈值设定为≥10个突变/Mb。使用SP142抗体评估PDL-1。基因表达谱分析和RNA反卷积用于估计TME中免疫细胞和基质细胞群体的丰度,以及免疫治疗反应的转录组特征(T细胞炎症评分)。 结果:共鉴定出461例(8.2%)TMB-H MBC样本。与先前研究一致,与TMB-L相比,TMB-H肿瘤显示出显著的错配修复缺陷(dMMR)/微卫星高度不稳定(MSI-H)富集(7%对0%,p<0.0001)和PD-L1+表达(36%对28%,p<0.05)。在所有样本中,T细胞炎症评分与TMB呈弱相关。TMB-H与免疫反应性细胞类型(CD8+ T细胞、NK细胞或B细胞)或免疫反应基因特征(如抗原呈递)的显著增加无关,但观察到了正向趋势,而TMB-H肿瘤中免疫抑制性成纤维细胞显著减少(与TMB-L相比变化倍数为0.84,P<0.05)。HR+/HER2-乳腺癌是唯一一种TMB-H肿瘤与TMB-L相比T细胞炎症评分增加的亚型。TMB-H同时伴有PD-L1+或dMMR/MSI-H与HR+/HER2-和三阴乳腺癌(TNBC)的高T细胞炎症评分相关。在几个相关生物标志物中, 突变和 扩增与TMB-H肿瘤中的T细胞炎症评分呈正相关; 突变和 突变呈负相关。 结论:单独的高TMB与MBC中的免疫浸润或免疫相关基因特征没有强烈关联。仅在HR+/HER2-肿瘤中,TMB-H与TMB-L相比可预测T细胞炎症特征。连同MSI-H和PD-L1+,包括 突变和 扩增在内的几个生物标志物可能有助于预测TMB-H肿瘤中ICI的获益情况。TMB-H乳腺癌中共存的生物标志物值得在更大的队列中进行评估,以确定对ICI的反应或抵抗情况,从而在MBC中开发复合预测生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/a50acf3a91db/fonc-13-1235902-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/220ab71d5e7b/fonc-13-1235902-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/4f79528d8ba2/fonc-13-1235902-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/6eca23b30c71/fonc-13-1235902-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/a0d0317ced9a/fonc-13-1235902-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/a50acf3a91db/fonc-13-1235902-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/220ab71d5e7b/fonc-13-1235902-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/4f79528d8ba2/fonc-13-1235902-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/6eca23b30c71/fonc-13-1235902-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/a0d0317ced9a/fonc-13-1235902-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf71/10457522/a50acf3a91db/fonc-13-1235902-g005.jpg

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