肿瘤细胞治疗研究
英文原题：Immunoscore and beyond: evolution and clinical integration of immune contexture-based biomarkers across solid tumours.
IS 及相关免疫背景分类器构成了一个具有生物学基础的框架，连接了肿瘤免疫学与临床肿瘤学。
肿瘤免疫微环境日益被认为是癌症进展、预后和治疗反应的关键决定因素，对以解剖学为基础的分期系统（如 TNM）的充分性提出了挑战。Immunoscore（IS）最初在结直肠癌中得到验证，提供了一种标准化的、空间分辨的评估方法，用于评估肿瘤核心（TC）和浸润边缘（IM）内的 CD3+ 和 CD8+ T 细胞。在这一框架的基础上，改良和修改的 IS 模型，以及基于计算和影像学的替代指标，已在多种实体恶性肿瘤中进行了研究，包括非小细胞肺癌、肝细胞癌、头颈部癌、胃癌、黑色素瘤和膀胱癌。本综述综合了当前证据，强调基于 IS 方法的转化潜力和方法学异质性。高 IS 或改良评分通常与生存改善相关，并可能完善风险分层，补充传统 TNM 分期。然而，研究间的变异性限制了可比性和可重复性。回顾性设计、单中心队列、有限的外部验证以及计算模型中潜在的过拟合进一步限制了证据强度。生物学背景依赖性、免疫排斥表型以及肿瘤免疫景观的动态演变使解读复杂化，强调高免疫细胞密度并不普遍等同于有效的抗肿瘤免疫。总体而言，IS 及相关免疫结构分类器构成了一个具有生物学基础的框架， bridging 肿瘤免疫学与临床肿瘤学。尽管前景广阔，但广泛的临床实施需要方法学统一、前瞻性验证，以及与基因组、全身和影像生物标志物的整合。通过强调成就和当前局限性，本综述为将基于免疫微环境的指标转化为精准肿瘤学的潜力和挑战提供了平衡的视角。
The tumour immune microenvironment is increasingly recognised as a critical determinant of cancer progression, prognosis, and therapeutic response, challenging the sufficiency of anatomy-based staging systems such as TNM. The Immunoscore (IS), originally validated in colorectal cancer, provides a standardised, spatially resolved assessment of CD3 + and CD8 + T cells within the tumour core (TC) and invasive margin (IM). Expanding upon this framework, adapted and modified IS models, as well as computational and imaging-based surrogates, have been investigated across multiple solid malignancies, including non-small-cell lung cancer, hepatocellular carcinoma, head and neck cancers, gastric cancer, melanoma, and bladder cancer. This review synthesises the current evidence, emphasising both the translational potential and methodological heterogeneity of IS-based approaches. High IS or adapted scores generally correlate with improved survival and may refine risk stratification, complementing conventional TNM staging. However, inter-study variability limits comparability and reproducibility. Retrospective designs, single-centre cohorts, limited external validation, and potential overfitting in computational models further constrain the strength of evidence. Biological context dependency, immune-exclusion phenotypes, and the dynamic evolution of the tumour immune landscape complicate interpretation, underscoring that high immune cell density does not universally equate to effective antitumour immunity. Overall, the IS and related immune-contexture classifiers constitute a biologically grounded framework that bridges tumour immunology and clinical oncology. While promising, widespread clinical implementation requires methodological harmonisation, prospective validation, and integration with genomic, systemic, and imaging biomarkers. By highlighting both achievements and current limitations, this review provides a balanced perspective on the potential and challenges of translating immune contexture-based metrics into precision oncology.
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