CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Focal hotspot and diffuse immune subtypes of tumor-infiltrating lymphocytes: AI-powered spatial clustering classification and its clinical relevance to HER2 expression in triple-negative breast cancer.
Focal hotspot and diffuse immune subtypes of tumor-infiltrating lymphocytes: AI-powered spatial clustering classification and its clinical relevance to HER2 expression in triple-negative breast cancer.
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本研究区分了 TNBC 中 TIL 的局灶性热点型和弥漫性免疫亚型,二者具有不同的临床意义。弥漫性免疫亚型与增强的 NAC 反应和良好预后相关,尤其是在 HER2-low TNBC 中。这些发现凸显了空间免疫结构作为一种有前景的生物标志物,可用于优化治疗分层并加深我们对 HER2-low TNBC 免疫异质性的理解。
本研究旨在利用人工智能(AI)驱动的分析方法定义TIL(肿瘤浸润淋巴细胞)的空间免疫亚型,并探讨其与三阴性乳腺癌(TNBC)中不同人表皮生长因子受体-2(HER2)表达水平、新辅助化疗(NAC)反应及患者生存结局的关联。
我们开展了一项多中心研究,纳入接受NAC的TNBC患者,并将其分为HER2-0、HER2-ultralow和HER2-low亚组。采用基于AI的细胞分类器从病理图像中识别TILs(AI-TILs)并提取空间坐标。利用无监督学习的空间聚类分析识别免疫亚型。将AI模型的性能与四位经验丰富的病理学家进行基准比较。系统评估了TILs空间亚型、HER2状态、NAC反应(包括病理完全缓解(pCR)和残余癌症负荷(RCB))以及生存结局之间的关联。
AI-TILs与两位资深病理学家均表现出高度一致性,无监督聚类揭示了两种空间亚型:局灶热点亚型和弥漫免疫亚型,后者表现出更广泛的TIL热点区域、更低的峰值密度、更高的pCR率以及显著延长的无病生存期(DFS)。RCB-III状态与弥漫免疫亚型呈负相关,提示弥漫免疫亚型与良好的NAC反应之间存在关联。绝经后状态与局灶热点模式独立相关。尽管HER2表达与TILs空间亚型相关,但并非独立影响因素。在HER2-low亚组中,弥漫亚型与更好的pCR和更低的RCB评分显著相关,而在HER2-0或HER2-ultralow组中未观察到这种关系。冲积图和标准化残差分析进一步验证了局灶热点/HER2-low肿瘤富集于RCB-III(残差 = 3.26),而弥漫/HER2-low肿瘤富集于RCB-0(残差 = 1.30),提示免疫架构与化疗反应性存在不同的演变轨迹。
This study aimed to define spatial immune subtypes of tumor-infiltrating lymphocytes (TILs) using artificial intelligence (AI)-powered analysis and investigate their association with distinct human epidermal growth factor receptor-2 (HER2) expression levels, response to neoadjuvant chemotherapy (NAC), and patient survival outcomes in triple-negative breast cancer (TNBC).
We conducted a multicenter study involving TNBC patients receiving NAC, stratified into HER2-0, HER2-ultralow, and HER2-low subgroups. An AI-based cell classifier was employed to identify TILs (AI-TILs) and extract spatial coordinates from pathology images. Using unsupervised learning of spatial clustering analysis to identify immune subtypes. The performance of the AI model was benchmarked against four experienced pathologists. Associations among TILs spatial subtypes, HER2 status, NAC response including pathologic complete response (pCR) and residual cancer burden (RCB), and survival outcomes were systematically evaluated.
AI-TILs demonstrated strong agreement with both senior pathologists, and unsupervised clustering revealed two spatial subtypes: the focal hotspot subtype and the diffuse immune subtype, the latter exhibited broader TIL hotspot areas, lower peak densities, higher pCR rates, and significantly prolonged disease-free survival (DFS). RCB-III status was inversely associated with the diffuse immune subtype, suggesting a link between diffuse immune subtype and good NAC response. Postmenopausal status was independently linked to the focal hotspot pattern. Although HER2 expression was associated with TILs spatial subtypes, it was not an independent influencing factor. In the HER2-low subgroup, the diffuse subtype was significantly associated with better pCR and lower RCB scores, whereas no such relationship was observed in HER2-0 or HER2-ultralow groups. Alluvial and standardized residual analysis further validated that focal hotspot/HER2-low tumors were enriched in RCB-III (residual = 3.26), while diffuse/HER2-low tumors were enriched in RCB-0 (residual = 1.30), suggesting divergent trajectories of immune architecture and chemoresponsiveness.
This study distinguished focal hotspot and diffuse immune subtypes of TILs with distinct clinical implications in TNBC. The diffuse immune subtype correlated with enhanced NAC response and favorable prognosis, particularly in HER2-low TNBC. These findings highlighted the spatial immune architecture as a promising biomarker to refine treatment stratification and deepen our understanding of immune heterogeneity in HER2-low TNBC.
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