胃肠道神经内分泌癌免疫微环境的初步研究。
A pilot study of the immune microenvironment of GI neuroendocrine carcinoma.
发表日期:2024 Oct 01
作者:
Andrew McDonald, Vaidehi Avadhani, Gabriela Oprea-Ilies, Katerina Zakka, Gregory B Lesinski, Olumide B Gbolahan, Olatunji Alese
来源:
ENDOCRINE-RELATED CANCER
摘要:
胃肠胰高级别 (HG) 神经内分泌癌 (GEP-NEC) 是一种侵袭性恶性肿瘤,治疗选择有限,但在美国发病率不断增加。由于癌症的罕见性和原发肿瘤位置的异质性,有关 GEP-NEC 肿瘤发生及其与宿主免疫系统相互作用的数据有限。更好地了解 GEP-NEC 及其肿瘤微环境 (TME) 将有利于开发更有效的靶向疗法并合理调整免疫疗法以适应这种疾病。在本研究中,我们使用 NanoString nCounter PanCancer IO 360 平台,使用来自 GEP-NEC 患者的 21 个活检样本,分析了 770 个独特基因的表达。我们的结果显示了 GEP-NEC TME 中明显的几个趋势。年龄<60 岁的患者和总生存期 (OS) 较高的患者的 TME 中存在更多指示免疫细胞浸润的基因表达。与胰腺 NEC 相比,非胰腺 NEC 患者的肿瘤 MHCII 表达减少,表明胰腺 GEP-NEC 亚型具有更显着的适应性免疫反应。与生存率较差的患者相比,OS > 6 个月的患者的肿瘤 NK 细胞基因特征升高。此外,分析揭示了许多基于患者年龄、肿瘤位置、治疗反应和 OS 的差异表达基因,这些基因值得未来验证以评估与患者临床结果的关系。
Gastroenteropancreatic high-grade (HG) neuroendocrine carcinoma (GEP-NEC) is an aggressive malignancy with limited treatment options and increasing incidence in the United States. Due to the rarity of the cancer and heterogeneity of the primary tumor location, data on GEP-NEC oncogenesis and its interaction with the host immune system are limited. A greater understanding of GEP-NEC and its tumor microenvironment (TME) would benefit efforts to develop more effective targeted therapies and rationally adapt immunotherapy to this disease. In this study, we profiled the expression of 770 unique genes using 21 biopsy samples from patients with GEP-NEC using the NanoString nCounter PanCancer IO 360 platform. Our results show several trends evident within the GEP-NEC TME. Greater expression of genes indicative of immune cell infiltration was present within the TME of patients <60 years of age and in patients with greater overall survival (OS). Tumors from patients with non-pancreatic NEC had diminished MHCII expression compared to pancreatic NEC, suggesting more prominent adaptive immune responses in the pancreatic GEP-NEC subtype. Patients with a >6 months OS had tumors with elevated NK cell gene signatures compared to patients with poor survival. Further, the analysis revealed numerous differentially expressed genes based on patient age, tumor location, response to treatment, and OS, which warrant future validation for assessing the relationship with clinical outcomes in patients.