The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong, China.
Guangdong Provincial Key Laboratory of Digestive Cancer Research, Shenzhen, Guangdong, China.
Front Immunol. 2023 Apr 28;14:1142862. doi: 10.3389/fimmu.2023.1142862. eCollection 2023.
Although many efforts have been devoted to identify biomarkers to predict the responsiveness of immune checkpoint inhibitors, including expression of programmed death-ligand 1 (PD-L1) and major histocompatibility complex (MHC) I, microsatellite instability (MSI), mismatch repair (MMR) defect, tumor mutation burden (TMB), tertiary lymphoid structures (TLSs), and several transcriptional signatures, the sensitivity of these indicators remains to be further improved.
Here, we integrated T-cell spatial distribution and intratumor transcriptional signals in predicting the response to immune checkpoint therapy in MMR-deficient tumors including tumors of Lynch syndrome (LS).
In both cohorts, MMR-deficient tumors displayed personalized tumor immune signatures, including inflamed, immune excluded, and immune desert, which were not only individual-specific but also organ-specific. Furthermore, the immune desert tumor exhibited a more malignant phenotype characterized by low differentiation adenocarcinoma, larger tumor sizes, and higher metastasis rate. Moreover, the tumor immune signatures associated with distinct populations of infiltrating immune cells were comparable to TLSs and more sensitive than transcriptional signature gene expression profiles (GEPs) in immunotherapy prediction. Surprisingly, the tumor immune signatures might arise from the somatic mutations. Notably, patients with MMR deficiency had benefited from the typing of immune signatures and later immune checkpoint inhibition.
Our findings suggest that compared to PD-L1 expression, MMR, TMB, and GEPs, characterization of the tumor immune signatures in MMR-deficient tumors improves the efficiency of predicting the responsiveness of immune checkpoint inhibition.
尽管已经投入了许多努力来识别预测免疫检查点抑制剂反应的生物标志物，包括程序性死亡配体 1（PD-L1）和主要组织相容性复合体（MHC）I、微卫星不稳定性（MSI）、错配修复（MMR）缺陷、肿瘤突变负担（TMB）、三级淋巴结构（TLS）和几个转录特征，但这些指标的敏感性仍有待进一步提高。
在这里，我们整合了 T 细胞空间分布和肿瘤内转录信号，以预测包括林奇综合征（LS）肿瘤在内的 MMR 缺陷型肿瘤对免疫检查点治疗的反应。
在两个队列中，MMR 缺陷型肿瘤显示出个性化的肿瘤免疫特征，包括炎症、免疫排斥和免疫荒漠，这些特征不仅是个体特异性的，而且是器官特异性的。此外，免疫荒漠型肿瘤表现出更恶性的表型，其特征为低分化腺癌、更大的肿瘤大小和更高的转移率。此外，与浸润免疫细胞不同群体相关的肿瘤免疫特征与 TLS 相当，并且比免疫治疗预测中的转录特征基因表达谱（GEP）更敏感。令人惊讶的是，肿瘤免疫特征可能源自体细胞突变。值得注意的是，MMR 缺陷的患者受益于免疫特征的分型和随后的免疫检查点抑制。
我们的研究结果表明，与 PD-L1 表达、MMR、TMB 和 GEP 相比，MMR 缺陷型肿瘤的肿瘤免疫特征的特征化提高了预测免疫检查点抑制反应的效率。
