PO.TB10.01 · 肿瘤生物学

利用同一切片RNA-蛋白联合检测与荧光H&E对胃癌前期进展进行三维多模态空间分析

3D multimodal spatial profiling of pre-gastric cancer progression using same-slide RNA-protein and fluorescent H&E

海报缩略图:利用同一切片RNA-蛋白联合检测与荧光H&E对胃癌前期进展进行三维多模态空间分析
编号 2254 展板 3 时间 4/20 09:00–12:00 区域 Section 33 主讲 Eric Sha, BA
分会场 Tumorigenesis and Early Microenvironmental Trajectories
查看 PDF 下载 PDF 🔒 查看 / 下载完整 PDF 需登录并开通下载套餐 · 查看套餐 / 开通 AACR 官方页面

作者与单位 Authors & Affiliations

Eric Sha1, Seock-Jin Chung2, Jean R. Clemenceau2, Sunho Park2, Minji Kim2, Inyeop Jang2, Youngwon Cho2, Seunghyi Kook2, Soonyoung Lee3, Jongseong Jang3, Eunyoung Choi2, Tae Hyun Hwang2

1Vanderbilt University, Nashville, TN,2Vanderbilt University Medical Center, Nashville, TN,3LG AI Research, Seoul, Korea, Republic of

摘要 Abstract

中文摘要
背景:胃癌通过肠上皮化生到异型增生再到浸润性腺癌的级联过程发生,但仅有一部分癌前腺体会进展。区分进展性与非进展性微环境的空间特征尚不明确。我们采用一种多模态平台,将G4X空间测序仪上同一切片的亚细胞RNA与蛋白检测同荧光H&E(fH&E)及三维全息断层成像(HT)相结合,以表征胃癌前期(pre-GC)微环境及其向癌转化的过程。 方法:来自12例患者的FFPE胃组织(38个感兴趣区域)在G4X流动池上使用定制的358基因胃癌/癌前病变panel、16重蛋白panel以及同一切片的fH&E进行检测。我们对空间转录组、形态学和蛋白特征进行多模态聚类和分类,以定义细胞状态及相关微环境。对于配对区域,采用来自同一组织的三维HT,将二维分子定义的状态嵌入其腺体和黏膜背景中,以评估pre-GC状态是否在腺体单元间共享或分隔、是否延伸至黏膜深部,以及免疫细胞群在三维空间中如何围绕其分布。通过将亚细胞G4X坐标与HT体积对齐,该方法使我们能够可视化单个细胞内转录本的x-y-z定位,从而提供肿瘤-基质-免疫微环境的分子水平三维模型。 结果:对整合的RNA、蛋白和形态学数据进行多模态分析,在癌前组织中解析出不同的上皮、基质和免疫区室,而癌变区域则显示上皮和免疫状态的扩张以及区室边界的改变。在上皮层内,化生和异型增生区域定位于富含肠型或胃型基因特征的离散的腺体相关区带。同一切片的RNA-蛋白检测使我们能够绘制CD4⁺辅助性T细胞和CD8⁺细胞毒性T细胞相对于胃上皮的分布图。结合三维HT,我们得以研究二维定义的pre-GC病灶是代表连续性病变还是独立的腺体,并在三维空间中沿腺体轴细化了病变范围和免疫接近程度的估计。 结论:这一具备三维能力、结合fH&E、RNA转录本检测和16重蛋白panel的同一切片G4X平台,生成了pre-GC和胃癌微环境的多尺度图谱。尤其是三维空间多模态建模改善了对癌前上皮程序和免疫定位的解读,并支持发现超越传统二维组织学、与进展风险相关的三维微环境特征。 生成式AI的辅助仅限于对本摘要的语言编辑。科学内容、解读和结论由作者独自负责,作者已审阅并批准最终版本。
查看英文原文 English abstract
Background: Gastric cancer arises through a cascade from intestinal metaplasia to dysplasia and invasive adenocarcinoma, but only a subset of precancerous glands progress. The spatial features that distinguish progressing from non-progressing niches are unknown. We applied a multimodal platform that combines same-slide, subcellular RNA and protein profiling on the G4X Spatial Sequencer with fluorescent H&E (fH&E) and 3D holotomography (HT) to characterize pre-gastric cancer (pre-GC) niches and their transition toward carcinoma. Methods: FFPE gastric tissues from 12 patients (38 regions of interest) were profiled on G4X flow cells using a custom 358-gene gastric cancer/pre-cancer panel, a 16-plex protein panel, and fH&E on the same slide. We used multimodal clustering and classification of spatial transcriptomic, morphology, and protein features to define cell states and associated niches. For matched regions, 3D HT from the same tissues was used to embed 2D molecularly defined states into their gland and mucosal context and to assess whether pre-GC states share or segregate across glandular units, extend through the mucosal depth, and how immune populations are positioned around them in 3D. By aligning subcellular G4X coordinates with HT volumes, this method enables us to visualize the x-y-z localization of transcripts within individual cells, providing a molecular level 3D model of the tumor-stroma-immune microenvironment. Results: Multimodal analysis of integrated RNA, protein, and morphology data resolved distinct epithelial, stromal, and immune compartments in precancerous tissue, whereas cancerous regions showed expansion of epithelial and immune states and altered compartment boundaries. Within the epithelial layer, regions of metaplasia and dysplasia localized to discrete gland-associated zones enriched for intestinal or gastric gene signatures. Same-slide RNA-protein measurements enabled mapping of CD4⁺ helper and CD8⁺ cytotoxic T-cell distributions relative to the gastric epithelium. Incorporating 3D HT enabled us to investigate whether 2D-defined pre-GC foci represented continuous lesions or separate glands and refined estimates of lesion extent and immune proximity along the gland axis in 3D. Conclusions: This 3D-enabled, same-slide G4X platform with fH&E, RNA transcript profiling, and a 16-plex protein panel generates multi-scale maps of pre-GC and gastric cancer niches. In particular, 3D spatial multimodal modeling improves interpretation of pre-cancer epithelial programs and immune positioning and supports discovery of 3D niche features linked to progression risk beyond conventional 2D histology. Generative AI assistance was limited to language editing of this abstract. The scientific content, interpretation, and conclusions are the sole responsibility of the authors, who have reviewed and approved the final version.
利益披露 Disclosure
E. Sha, None.. S. Chung, None.. J. R. Clemenceau, None.. S. Park, None.. I. Jang, None.. Y. Cho, None.. S. Kook, None. S. Lee, LG AI Research Employment. J. Jang, LG AI Research Employment. E. Choi, None. T. Hwang, Kure.ai Therapeutics Other, Co-founder. Kure.s Other, Co-founder. IQVIA Has received consulting fees from company.

← 返回 AACR 2026 检索