PO.TB10.08 · 肿瘤生物学
KIT外显子9与外显子11突变在胃肠道间质瘤中形成独特的空间及表型免疫微环境
KIT exon 9 versus exon 11 mutations imprint distinct spatial and phenotypic immune microenvironments in gastrointestinal stromal tumors
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摘要 Abstract
中文摘要
背景：
肿瘤微环境（TME）是胃肠道间质瘤（GIST）进展和治疗反应的关键决定因素。不同外显子的致癌性KIT突变（外显子9与外显子11）具有临床相关性，但它们对原位免疫和间质结构的影响仍认识不足。我们假设KIT外显子9和外显子11突变驱动独特的空间转录程序和免疫细胞组成。
方法：
对KIT突变GIST（外显子9和外显子11）的FFPE样本采用NanoString GeoMx® 全转录组图谱（18,695个蛋白编码基因）进行分析。每例在肿瘤和瘤周区域选择11个照明区域，并分割为CD45⁺（免疫富集）和CD45⁻（肿瘤/间质）区室。CD45⁺区段中的细胞类型丰度用SpatialDecon估计。同时，将三个多重免疫荧光（mIF）面板（DOG1/CD11c/CD11b/CD68/CD45/HLA-DR；DOG1/CD45RO/CD56/CD4/CD8/CD20；DOG1/CD45/CD16/CD56）应用于独立的回顾性GIST队列（n=170），并使用基于QuPath的分割和类FACS表型分析对肿瘤和间质区室中的细胞密度进行定量。
结果：
GeoMx分析在外显子9和外显子11肿瘤之间的CD45⁺肿瘤区域中识别出2315个差异表达基因，表明存在外显子特异性的免疫转录程序。SpatialDecon解卷积显示，外显子11突变肿瘤表现出更高的NK细胞评分（校正后p≈6×10⁻⁶），而外显子9突变肿瘤显示更高的成纤维细胞（校正后p≈6×10⁻⁶）和CD8⁺记忆T细胞信号（校正后p≈1.9×10⁻⁴）。在大型mIF队列中，对DOG1门控肿瘤区域的无监督分析证实了全部三个面板稳健的技术表现，并显示出基因型分离的TME模式：KIT突变病例，以及其中的外显子9与外显子11肿瘤，在PCA空间中占据不同区域，外显子11肿瘤显示更高的CD56⁺（NK/NKT）和髓系（CD11b⁺/CD68⁺/HLA-DR⁺）密度，而CD8⁺CD45RO⁺记忆T细胞在外显子9肿瘤中更丰富，且独立于PDGFRA突变GIST。在各面板中，这些表型差异与GeoMx得出的外显子11肿瘤NK细胞富集和外显子9肿瘤CD8⁺记忆T细胞富集相一致。
结论：
整合的空间转录组学和多重免疫荧光证明，KIT外显子9和外显子11突变与GIST中不同的免疫和间质微环境相关，其特征为外显子11肿瘤呈现NK细胞富集、髓系细胞增多、成纤维细胞和CD8⁺记忆T细胞较少的生态位，而外显子9肿瘤呈现相反模式。这些数据支持这一概念：KIT突变的具体外显子会塑造TME，在设计基因型适配的激酶抑制与免疫治疗联合方案时应予以考虑。
查看英文原文 English abstract
Background:
The tumor microenvironment (TME) is a key determinant of progression and treatment response in gastrointestinal stromal tumors (GIST). Oncogenic KIT mutations in different exons (exon 9 vs exon 11) are clinically relevant, but their impact on immune and stromal architecture in situ remains insufficiently understood. We hypothesized that KIT exon 9 and exon 11 mutations drive distinct spatial transcriptional programs and immune cell compositions.
Methods:
FFPE samples from KIT‑mutated GIST (exon 9 and exon 11) were profiled using the NanoString GeoMx® Whole Transcriptome Atlas (18,695 protein‑coding genes). Eleven areas of illumination per case were selected in tumor and peritumoral regions and segmented into CD45⁺ (immune‑enriched) and CD45⁻ (tumor/stromal) compartments. Cell‑type abundances in CD45⁺ segments were estimated with SpatialDecon. In parallel, three multiplex immunofluorescence (mIF) panels (DOG1/CD11c/CD11b/CD68/CD45/HLA‑DR; DOG1/CD45RO/CD56/CD4/CD8/CD20; DOG1/CD45/CD16/CD56) were applied to independent retrospective GIST cohorts (n=170), and cell densities were quantified in tumor and stromal compartments using QuPath‑based segmentation and FACS‑like phenotyping.
Results:
GeoMx analysis identified 2315 differentially expressed genes in CD45⁺ tumor regions between exon 9 and exon 11 tumors, indicating exon‑specific immune transcriptional programs. SpatialDecon deconvolution revealed that exon 11-mutant tumors exhibited higher NK‑cell scores (adjusted p≈6×10⁻⁶), whereas exon 9-mutant tumors showed higher fibroblast (adjusted p≈6×10⁻⁶) and CD8⁺ memory T‑cell signals (adjusted p≈1.9×10⁻⁴). In the large mIF cohorts, unsupervised analyses of DOG1‑gated tumor regions confirmed robust technical performance of all three panels and demonstrated genotype‑segregated TME patterns KIT-mutant cases, and within them exon 9 vs exon 11 tumors, occupied distinct regions in PCA space, with exon 11 tumors showing higher CD56⁺ (NK/NKT) and myeloid (CD11b⁺/CD68⁺/HLA-DR⁺) densities, whereas CD8⁺CD45RO⁺ memory T cells were more abundant in exon 9 tumors, independently of PDGFRA-mutant GIST. Across panels, these phenotypic differences aligned with the GeoMx‑derived enrichment of NK cells in exon 11 tumors and of and CD8⁺ memory T cells in exon 9 tumors.
Conclusions:
Integrated spatial transcriptomics and multiplex IF demonstrate that KIT exon 9 and exon 11 mutations are associated with distinct immune and stromal microenvironments in GIST, characterized by an NK‑cell-enriched, myeloid cells , less fibroblast‑ and CD8⁺ memory T‑cell-dense niche in exon 11 tumors and the converse pattern in exon 9 tumors. These data support the concept that the precise KIT exon mutated imprints the TME and should be considered when designing genotype‑adapted combinations of kinase inhibition and immunotherapy.
利益披露 Disclosure
A. Italiano, None.