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胃胰肠神经内分泌肿瘤中肿瘤间谱系多样性和免疫抑制转录程序。

Intertumoral lineage diversity and immunosuppressive transcriptional programs in well-differentiated gastroenteropancreatic neuroendocrine tumors.

机构信息

Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA.

Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.

出版信息

Sci Adv. 2023 Sep 29;9(39):eadd9668. doi: 10.1126/sciadv.add9668. Epub 2023 Sep 27.

Abstract

Neuroendocrine tumors (NETs) are rare cancers that most often arise in the gastrointestinal tract and pancreas. The fundamental mechanisms driving gastroenteropancreatic (GEP)-NET growth remain incompletely elucidated; however, the heterogeneous clinical behavior of GEP-NETs suggests that both cellular lineage dynamics and tumor microenvironment influence tumor pathophysiology. Here, we investigated the single-cell transcriptomes of tumor and immune cells from patients with gastroenteropancreatic NETs. Malignant GEP-NET cells expressed genes and regulons associated with normal, gastrointestinal endocrine cell differentiation, and fate determination stages. Tumor and lymphoid compartments sparsely expressed immunosuppressive targets commonly investigated in clinical trials, such as the programmed cell death protein-1/programmed death ligand-1 axis. However, infiltrating myeloid cell types within both primary and metastatic GEP-NETs were enriched for genes encoding other immune checkpoints, including (VISTA), (TIM3), (Gal-9), and . Our findings highlight the transcriptomic heterogeneity that distinguishes the cellular landscapes of GEP-NET anatomic subtypes and reveal potential avenues for future precision medicine therapeutics.

摘要

神经内分泌肿瘤(NETs)是一种罕见的癌症,大多数起源于胃肠道和胰腺。驱动胃肠胰腺(GEP)-NET 生长的基本机制仍不完全清楚;然而,GEP-NET 的异质性临床行为表明,细胞谱系动力学和肿瘤微环境都影响肿瘤的病理生理学。在这里,我们研究了来自胃肠胰腺 NET 患者的肿瘤和免疫细胞的单细胞转录组。恶性 GEP-NET 细胞表达与正常胃肠道内分泌细胞分化和命运决定阶段相关的基因和调控子。肿瘤和淋巴区稀疏表达在临床试验中经常研究的免疫抑制靶点,如程序性细胞死亡蛋白 1/程序性死亡配体 1 轴。然而,在原发性和转移性 GEP-NET 中浸润的髓样细胞类型富含编码其他免疫检查点的基因,包括 (VISTA)、 (TIM3)、 (Gal-9)和 。我们的研究结果突出了区分 GEP-NET 解剖亚型细胞景观的转录组异质性,并揭示了未来精准医学治疗的潜在途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7822/10530100/331f71e2620f/sciadv.add9668-f1.jpg

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