PO.BCS01.04 · 生物信息与计算
单细胞多组学实现胃癌亚型的分子解析
Single cell multi-omics enables molecular dissection of gastric cancer subtypes
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
胃癌(GC)具有不同的组织病理学亚型，包括肠型、弥漫型和混合型。这些亚型根据组织学细胞形态进行鉴定，且具有临床指导意义，其临床价值高于分子亚型。也就是说，组织学亚型在预后、转移率和治疗反应方面存在差异。然而，关于区分各组织学亚型的基因组特征仍存在许多疑问。由于技术变异，在分子层面整合单细胞数据集尤其具有挑战性。我们开发了一个整合性数据集，结合了自有和公共的多组学数据集——包括bulk测序、scRNA-seq、空间转录组学和蛋白质组学。scRNA-seq数据包括来自118名患者的208个肿瘤。该单细胞数据经过协调处理以减少批次变异性的影响。在分析中，我们开发了一个计算流程，纳入了广义线性模型、用于元程序识别的非负矩阵分解、样本水平的伪聚合以及基于网络的基因表达分析。该流程实现了基因层面的解析、以通路为中心的恶性转录程序解读，以及跨整合队列的细胞状态动态的系统性量化。我们鉴定出各亚型之间不同的肿瘤内在基因表达程序。肠型和混合型肿瘤表达免疫相关程序，而MSI肿瘤相较于MSS表现出细胞周期信号的升高。在肿瘤微环境中，弥漫型亚型表现出B细胞分化减少但树突状细胞丰度增加，而肠型亚型则富集T细胞亚群，包括具有免疫抑制潜能的调节性T细胞。从单细胞结果中，我们确定TIGIT在CD8和调节性T细胞中的表达显著升高。这一结果在一组独立的142例GC样本上通过多重免疫荧光染色得到证实。成纤维细胞驱动的相互作用在弥漫型肿瘤中占主导，而肠型和混合型肿瘤则表现出免疫介导的"热肿瘤"表型。
总体而言，我们的研究表明，对来自GC的整合、协调后的单细胞数据进行分析，揭示了区分各亚型的恶性程序和微环境程序。我们的结果提供了一些亚型特异性的脆弱点，并为潜在的未来治疗靶点提供了见解。
查看英文原文 English abstract
Gastric cancer (GC) has different histopathological subtypes that include intestinal, diffuse, and mixed. These subtypes are identified based on histologic cell morphology and are clinically informative, more so than molecular subtypes. Namely, histologic subtypes differ in prognosis, rates of metastasis and treatment response. However, many questions remain about the genomic features that distinguish each histologic subtype. Integrating single-cell datasets is particularly challenging at the molecular level due to technical variation. We developed an integrative data set combining in-house and public multi-omics datasets - they include bulk sequencing, scRNA-seq, spatial transcriptomics, and proteomics. The scRNA-seq data included 208 tumors from 118 patients. This single cell data was harmonized to reduce the effects of batch variability. For analysis, we developed a computational pipeline incorporating generalized linear models, non-negative matrix factorization for meta-program identification, sample-level pseudo-aggregation and network-based gene expression analysis. This pipeline enabled gene-wise dissection, pathway-centric interpretation of malignant transcriptional programs and systematic quantification of cell state dynamics across integrated cohorts. We identified distinct tumor-intrinsic gene expression programs across subtypes. The intestinal and mixed tumors expressed immune-associated programs, while the MSI tumors exhibited elevated cell-cycle signaling compared to MSS. In the tumor microenvironment, the diffuse subtype showed reduced B-cell differentiation but increased dendritic cell abundance, whereas intestinal subtype was enriched for T-cell subtypes, including regulatory T cells with immunosuppressive potential. From the single cell results, we determined that TIGIT expression was significantly elevated among CD8 and regulatory T cells. This result was confirmed with multiplexed immunofluorescence staining on an independent set of 142 GCs. Fibroblast-driven interactions dominated diffuse tumors, while intestinal and mixed tumors displayed immune-mediated “hot tumor” phenotypes.
Overall, our study showed that the analysis of an integrated, harmonized single-cell data from GC revealed malignant and microenvironmental programs distinguishing subtypes. Our results provided some subtype-specific vulnerabilities and provides insight into potential future therapeutic targets.
利益披露 Disclosure
J. Cha, None..
Y. Wang, None..
S. M. Grimes, None.