Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China.
Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China.
J Transl Med. 2024 Jan 20;22(1):69. doi: 10.1186/s12967-023-04765-5.
The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor's immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory.
Here, we applied a visualizing method termed 'cancer immunogram' to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes.
We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by 'hot' and 'exhausted' features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of 'cold' tumor. Immunogram-II was characterized by 'cold' and 'radical' features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by 'cold' and 'recognizable' features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by 'cold' and 'inert' features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype.
Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies.
癌症免疫周期（CI 周期）提供了一个理论框架，用于说明抗肿瘤免疫反应的过程。最近，CI 周期理论的更新强调了肿瘤免疫表型的重要性。然而，基于 CI 周期理论的泛癌症免疫表型尚缺乏研究。
在这里，我们应用了一种可视化方法，称为“癌症免疫组图”，来可视化 TCGA 队列中 8460 个实体瘤的 CI 周期状态。使用非负矩阵分解（NMF）分析对癌症免疫组图进行无监督聚类。我们应用了一种进化基因组学方法（dN/dS 比）来评估具有不同免疫组图亚型的肿瘤的克隆选择模式。
我们使用癌症免疫组图方法定义了 32 种癌症类型中的 4 种主要 CI 周期模式。免疫组图-I 表现出“热”和“耗竭”特征，提示预后良好。引人注目的是，免疫组图-II、免疫组图-III 和免疫组图-IV 代表了“冷”肿瘤的不同免疫抑制模式。免疫组图-II 的特征是“冷”和“激进”，表现为免疫抑制分子表达增加和高水平的正选择，提示预后最差。免疫组图-III 的特征是“冷”和“可识别”，并且 MHC I 分子表达上调。免疫组图-IV 的特征是“冷”和“惰性”，表现为整体免疫抑制、免疫编辑和正选择水平较低，以及积累更多的肿瘤新抗原。特别是，转移性膀胱癌患者在接受免疫检查点抑制剂（ICI）治疗后，具有免疫组图-I 和免疫组图-IV 特征时，总体生存率较好。同时，转移性胃癌患者中具有免疫组图-I 表型时，对 ICI 治疗的反应率较高。
我们的研究结果为免疫与癌症进化之间的相互作用提供了新的见解，这可能有助于优化免疫治疗策略。
