PO.TB10.08 · 肿瘤生物学

空间转录组谱分析揭示促纤维增生性小圆细胞肿瘤的异质性

Spatial transcriptomic profiling reveals heterogeneity in desmoplastic small round cell tumor

海报缩略图:空间转录组谱分析揭示促纤维增生性小圆细胞肿瘤的异质性
编号 4958 展板 15 时间 4/21 09:00–12:00 区域 Section 31 主讲 Elana Sverdlik, B Eng
分会场 Spatial Niches and Functional Boundaries within the Tumor Microenvironment 1
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作者与单位 Authors & Affiliations

Elana Sverdlik1, Jeffrey Quinn2, Jiayi Fan2, Christopher Tosh2, Tamar Feinberg2, Melania Franchini3, Jovana Pavisic2, Shanita Li2, Andoyo Ndengu2, Glorymar Ibanez Sanchez2, Emily Stockfisch2, Filemon Dela Cruz2, Andrew L. Kung4, Joshua Honeyman2, Emily Slotkin2, Wesley Tansey2

1Gerstner Sloan Kettering - Graduate School of Biomedical Sciences, New York, NY,2Memorial Sloan Kettering Cancer Center, New York, NY,3Herbert Irving Comprehensive Cancer Ctr., New York, NY,4Chief, Division of Pediatric Hematology/, Memorial Sloan Kettering Cancer Center, New York, NY

摘要 Abstract

中文摘要
促纤维增生性小圆细胞肿瘤(DSRCT)是一种罕见、侵袭性的软组织肉瘤,由嵌合融合蛋白EWSR1-WT1驱动,该蛋白调控DSRCT肿瘤细胞中的致癌基因表达程序。尽管有此明确的分子驱动因素,DSRCT患者之间的治疗反应和生存结局差异巨大(5年生存率约15%)。我们假设治疗结局的差异反映了肿瘤细胞表型状态、微环境结构和信号网络的异质性。在此,我们使用Xenium 5K空间转录组学在组织微阵列上对来自4例DSRCT患者的7个腹膜和淋巴结转移瘤部位进行了谱分析(1,383,406个细胞)。我们整合了来自15份DSRCT样本(251,087个细胞)的snRNA-seq数据用于细胞类型注释,通过逐患者Leiden聚类(分辨率=0.2)识别患者特异性肿瘤亚型,并通过标志基因评分识别CAF亚型。这揭示了14种患者特异性肿瘤亚型(每位患者3-4种)、三种CAF亚型(apCAFs、myCAFs、iCAFs)、巨噬细胞、T细胞和内皮细胞。
查看英文原文 English abstract
Desmoplastic small round cell tumor (DSRCT) is a rare, aggressive soft tissue sarcoma driven by the chimeric fusion protein EWSR1-WT1 that modulates oncogenic gene expression programs in DSRCT tumor cells. Despite this defined molecular driver, treatment response and survival outcomes vary substantially between DSRCT patients (5-year survival ~ 15%). We hypothesize that treatment outcome variability reflects heterogeneity in tumor cell phenotypic states, microenvironmental architecture, and signaling networks. Here we profiled seven peritoneal and lymph node metastatic tumor sites across four DSRCT patients using Xenium 5K spatial transcriptomics on tissue microarrays (1,383,406 cells). We integrated snRNA-seq data from 15 DSRCT samples (251,087 cells) for cell type annotation, identifying patient-specific tumor subtypes through per-patient Leiden clustering (resolution=0.2) and CAF subtypes through marker gene scoring. This revealed 14 patient-specific tumor subtypes (3-4 per patient), three CAF subtypes (apCAFs, myCAFs, iCAFs), macrophages, T cells, and endothelial cells.
利益披露 Disclosure
E. Sverdlik, None.

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