PO.MCB09.02 · 分子与细胞生物学

与透明细胞肾细胞癌免疫微环境特征相关的肿瘤代谢物相关转录组学特征

Transcriptomic features associated with tumoral metabolites characterizing the immune microenvironment in clear cell renal cell carcinoma

编号 7339 展板 25 时间 4/22 09:00–12:00 区域 Section 23 主讲 Sei Naito, MD;PhD
分会场 Metabolic Vulnerabilities in Pancreatic, Hepatic, and Renal Cancers
该海报暂无可下载的资料 AACR 官方页面

作者与单位 Authors & Affiliations

Sei Naito, Takafumi Narisawa, Hiromi Ito, Norihiko Tschiya

Urology, Yamagata University Faculty of Medicine, Yamagata, Japan

摘要 Abstract

中文摘要
摘要:目的:既往研究表明,代谢环境在塑造癌组织免疫格局中发挥关键作用。本研究旨在结合瘤内代谢物水平表征透明细胞肾细胞癌(ccRCC)的免疫微环境。 方法:对来自31例ccRCC手术病例的冷冻肿瘤样本及其配对的福尔马林固定石蜡包埋(FFPE)标本进行代谢组学和转录组学分析。定量并比较了此前被认为参与免疫调节的五种代谢物——乳酸、谷氨酰胺、腺苷、精氨酸和色氨酸——与转录组谱之间的关系,采用预排序基因集富集分析(GSEA)。分析纳入了标志基因集(h.all.v2025.1.Hs.symbols)和免疫相关基因集(c7.immunesigdb.v2025.1.Hs.symbols)。 结果:乳酸水平与糖酵解、缺氧、干扰素γ反应和未折叠蛋白反应相关基因集呈正相关,也与源自受甲型流感病毒和HPV抗原刺激的单核细胞和树突状细胞的免疫特征呈正相关。观察到与有丝分裂纺锤体和氧化磷酸化通路呈负相关。谷氨酰胺与糖酵解、Th17极化条件下的RORγt缺陷CD4+ T细胞、SPHK1敲除炎症反应以及I型干扰素处理的内皮细胞呈正相关,而与凝血呈负相关。腺苷与糖酵解、缺氧、异生物质代谢、mTORC1信号转导和活性氧通路呈正相关,也与涉及记忆CD4+ T细胞、IL-4刺激和单核细胞活化的免疫特征呈正相关。负相关包括有丝分裂纺锤体、FOXP3突变的Tconv细胞和浆细胞样树突状细胞反应。精氨酸与反映单核细胞培养动态、记忆CD8+ T细胞分化和胸腺细胞成熟的基因集呈正相关。 结论:这些发现凸显了ccRCC中与特定代谢物相关的不同转录组程序,提示瘤内代谢状态——尤其是升高的乳酸和腺苷——与免疫抑制和炎症转录谱相关联。源自病毒刺激背景的免疫基因集的富集意味着肿瘤代谢可能模拟或调节通常在感染中所见的免疫激活通路。总体而言,这种整合的代谢组学-转录组学方法为理解ccRCC中的代谢重编程如何促进塑造免疫微环境提供了见解,对免疫治疗策略和代谢靶向具有潜在意义。
查看英文原文 English abstract
Abstract: Objectives: Previous studies have demonstrated that the metabolic milieu plays a pivotal role in shaping the immunological landscape of cancer tissues. This study aimed to characterize the immune microenvironment of clear cell renal cell carcinoma (ccRCC) in relation to intratumoral metabolite levels. Methods: Metabolomic and transcriptomic analyses were performed on frozen tumor samples and their paired formalin-fixed paraffin-embedded (FFPE) specimens from 31 ccRCC surgical cases. Five metabolites previously implicated in immune modulation-lactate, glutamine, adenosine, arginine, and tryptophan-were quantified and compared against transcriptomic profiles using pre-ranked gene set enrichment analysis (GSEA). The analysis incorporated hallmark gene sets (h.all.v2025.1.Hs.symbols) and immune-related gene sets (c7.immunesigdb.v2025.1.Hs.symbols). Results: Lactate levels positively correlated with gene sets related to glycolysis , hypoxia , interferon gamma response , and unfolded protein response , as well as immune signatures derived from monocytes and dendritic cells stimulated by influenza A virus and HPV antigens. Negative correlations were observed with mitotic spindle and oxidative phosphorylation pathways. Glutamine showed positive associations with glycolysis , RORgammat-deficient CD4+ T cells under Th17-polarizing conditions , SPHK1 knockout inflammatory responses , and type I interferon-treated endothelial cells , while negatively correlating with coagulation . Adenosine was positively linked to glycolysis , hypoxia , xenobiotic metabolism , mTORC1 signaling , and reactive oxygen species pathways , as well as immune signatures involving memory CD4+ T cells, IL-4 stimulation, and monocyte activation. Negative correlations included mitotic spindle , FOXP3-mutant Tconv cells , and plasmacytoid dendritic cell responses . Arginine was positively associated with gene sets reflecting monocyte culture dynamics, memory CD8+ T cell differentiation, and thymocyte maturation. Conclusions: These findings highlight distinct transcriptomic programs associated with specific metabolites in ccRCC, suggesting that intratumoral metabolic states-particularly elevated lactate and adenosine-are linked to immunosuppressive and inflammatory transcriptional profiles. The enrichment of immune gene sets derived from viral stimulation contexts implies that tumor metabolism may mimic or modulate immune activation pathways typically seen in infection. Overall, this integrative metabolomic-transcriptomic approach provides insight into how metabolic reprogramming in ccRCC contributes to shaping the immune microenvironment, with potential implications for immunotherapeutic strategies and metabolic targeting.
利益披露 Disclosure
S. Naito, None.. T. Narisawa, None.. H. Ito, None.. N. Tschiya, None.

← 返回 AACR 2026 检索