TIICs are critical components of the TME and are used to estimate prognostic and treatment responses in many malignancies. TIICs in the tumor microenvironment are assessed and quantified by categorizing immune cells into three subtypes: CD66b+ tumor-associated neutrophils (TANs), FoxP3+ regulatory T cells (Tregs), and CD163+ tumor-associated macrophages (TAMs). In addition, many cancers have tumor-infiltrating M1 and M2 macrophages, neutrophils (Neu), CD4+ T cells (T-helper), CD8+ T cells (T-cytotoxic), eosinophils, and mast cells. A variety of clinical treatments have linked tumor immune cell infiltration (ICI) to immunotherapy receptivity and prognosis. To improve the therapeutic effectiveness of immune-modulating drugs in a wider cancer patient population, immune cells and their interactions in the TME must be better understood. This study examines the clinicopathological effects of TIICs in overcoming tumor-mediated immunosuppression to boost antitumor immune responses and improve cancer prognosis. We successfully analyzed the predictive and prognostic usefulness of TIICs alongside TMB and ICI scores to identify cancer’s varied immune landscapes. Traditionally, immune cell infiltration was quantified using flow cytometry, immunohistochemistry, gene set enrichment analysis (GSEA), CIBERSORT, ESTIMATE, and other platforms that use integrated immune gene sets from previously published studies. We have also thoroughly examined traditional limitations and newly created unsupervised clustering and deconvolution techniques (SpatialVizScore and ProTICS). These methods predict patient outcomes and treatment responses better. These models may also identify individuals who may benefit more from adjuvant or neoadjuvant treatment. Overall, we think that the significant contribution of TIICs in cancer will greatly benefit postoperative follow-up, therapy, interventions, and informed choices on customized cancer medicines.
肿瘤浸润免疫细胞是肿瘤微环境的关键组成部分，可用于评估多种恶性肿瘤的预后及治疗反应。通过对免疫细胞进行亚型分类——CD66b+肿瘤相关中性粒细胞、FoxP3+调节性T细胞及CD163+肿瘤相关巨噬细胞，可实现对肿瘤微环境中免疫浸润的评估与量化。此外，多种癌症中还存在着M1/M2型巨噬细胞、中性粒细胞、CD4+辅助T细胞、CD8+细胞毒性T细胞、嗜酸性粒细胞及肥大细胞等浸润群体。大量临床治疗实践表明，肿瘤免疫细胞浸润与免疫治疗应答率及预后存在显著关联。为提升免疫调节药物在更广泛癌症患者群体中的疗效，必须深入理解肿瘤微环境中的免疫细胞及其相互作用机制。本研究通过探讨肿瘤浸润免疫细胞在克服肿瘤介导的免疫抑制、增强抗肿瘤免疫反应及改善癌症预后方面的临床病理学效应，成功结合肿瘤突变负荷与免疫细胞浸润评分体系，系统分析了肿瘤浸润免疫细胞在预测预后方面的应用价值，从而揭示癌症免疫景观的异质性特征。传统上主要通过流式细胞术、免疫组化、基因集富集分析、CIBERSORT及ESTIMATE等平台，利用已发表研究中的整合免疫基因集对免疫细胞浸润进行量化。本研究同时深入探讨了传统方法的局限性，并系统评估了新兴的无监督聚类与反卷积技术（SpatialVizScore与ProTICS）。这些创新方法能更精准预测患者预后及治疗反应，还可识别可能从辅助治疗或新辅助治疗中获益的特定人群。总体而言，我们认为肿瘤浸润免疫细胞在癌症研究中的重要贡献，将为术后随访、治疗方案制定、临床干预措施以及个体化抗癌药物的精准选择提供重要依据。
肿瘤(癌症)患者之家