PO.IM02.03 · 免疫学
高脂饮食对肿瘤生长的影响取决于脂肪酸组成和肿瘤类型
The impact of high fat diet on tumor growth is dependent on fatty acid composition and tumor type
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
饮食是塑造肠道微生物组、全身代谢和免疫功能的关键因素。然而,特定的宏量营养素如何改变宿主生理以及与肿瘤进展和免疫检查点抑制剂(ICI)免疫治疗应答相关的肿瘤-免疫相互作用,仍不清楚。因此,我们试图研究宏量营养素来源和组成各异的高脂饮食(HFD)如何影响代谢、肠道微生物组和抗肿瘤免疫。在接种同基因癌细胞系之前,将C57BL/6小鼠喂以标准饲料(CD)、高脂(HF)/高糖(HS)-Copha或HF-Lard饮食2周或7周。值得注意的是,这些饮食具有不同的脂肪酸组成;基于Copha(植物)的HFD含有较多的MCFA,而以LCFA为主的基于猪油(动物)的HFD则相反。与CD和HF/HS-Copha相比,在饮食2周和7周后,HF-Lard组小鼠表现出糖耐量受损和胰岛素敏感性降低。然而,只有长期喂食HF-Lard的小鼠同时出现空腹血糖和胰岛素升高。对小鼠肠道微生物组的分析显示,两种HFD均迅速诱导以多样性降低为特征的肠道菌群失调,尽管与HF-Lard相比,HF/HS-Copha富含代谢有益的物种Blautia coccoides、Parabacteroides merdae和Bacteroides acidifaciens。值得注意的是,HF-Lard加速了B16-F10和YUMM3.3-UVR黑色素瘤的生长,而两种HFD均加速了MC38结直肠腺癌的生长。在短期研究中观察到相似的结果,但B16-F10除外,其在各饮食组间未观察到差异。这表明这种加速独立于肥胖,但可能受肿瘤免疫原性或内在胰岛素敏感性的影响。对肠系膜淋巴结(MLN)、脾脏、肿瘤引流淋巴结(tdLN)和肿瘤中免疫细胞的光谱流式分析揭示了各饮食间不同的免疫特征。与CD相比,两种HFD在tdLN中的浆细胞、cDC1和CD8 T细胞均较低。然而,HF-Lard组小鼠的单核细胞频率以及Th17细胞和RORgt+ Treg的频率均较高,表明除了抗肿瘤启动受损外,还向抑制性表型极化。这伴随着HF-Lard组小鼠肿瘤中CD8 T细胞耗竭的增强。综上所述,这表明以LCFA为主的HFD与代谢功能障碍以及微生物组和免疫表型的改变相关,这可能促成黑色素瘤肿瘤生长的加速。它还强调,肿瘤类型/遗传学是饮食-肠道轴影响肿瘤生长方式的重要因素。正在进行的工作将侧重于理解特定脂肪来源和饮食持续时间如何影响ICI治疗,并最终为设计更具特异性的饮食干预以增强治疗疗效提供依据。
查看英文原文 English abstract
Diet is a key factor that shapes the gut microbiome, systemic metabolism and immune function. However, how specific macronutrients alter host physiology and tumor-immune interactions relevant to tumor progression and response to immune checkpoint inhibitor (ICI) immunotherapy remains unclear. We therefore sought to investigate how high fat diets (HFDs) varying in macronutrient source and composition influence metabolism, the gut microbiome and anti-tumor immunity. C57BL/6 mice were fed either a standard chow (CD), high fat (HF)/high sugar (HS)-Copha or HF-Lard diet for 2 or 7 weeks prior to inoculation with a syngeneic cancer cell line. These diets notably have differing fatty acid compositions; the copha-based (plant) HFD has more MCFAs compared to the lard-based (animal) HFD that is dominated by LCFAs. Mice on HF-Lard exhibited impaired glucose tolerance and reduced insulin sensitivity compared to CD and HF/HS-Copha after 2 and 7 weeks on diets. However, only mice on HF-Lard longer term had both elevated fasting glucose and insulin. Profiling the gut microbiomes of mice revealed both HFDs rapidly induced gut dysbiosis characterized by reduced diversity, although HF/HS-Copha compared to HF-Lard were enriched with metabolically beneficial species Blautia coccoides , Parabacteroides merdae and Bacteroides acidifaciens . Notably, HF-Lard accelerated the growth of B16-F10 and YUMM3.3-UVR melanomas while both HFDs accelerated the growth of MC38 colorectal adenocarcinomas. Similar results were observed in the short-term study except for B16-F10 where no differences between diets were observed. This suggests the acceleration is independent of obesity though may be influenced by the immunogenicity or intrinsic insulin sensitivity of the tumor. Spectral flow analysis of immune cells across the mesenteric lymph nodes (MLN), spleen, tumor draining LN (tdLN) and tumor revealed divergent immune profiles across diets. Both HFDs had lower plasma cells, cDC1s and CD8 T cells in the tdLN compared to CD. However, HF-Lard mice had higher frequencies of monocytes, and both Th17 cells and RORgt+ Tregs, indicating polarization towards suppressive phenotypes in addition to impaired anti-tumor priming. This was accompanied by enhanced exhaustion across CD8 T cells in the tumors of HF-Lard mice.Together this suggests that HFDs dominated by LCFAs are associated with metabolic dysfunction, and altered microbiome and immune phenotypes, which could contribute to accelerated tumor growth for melanoma. It also highlights that tumor type/genetics are important factors in how the diet-gut axis influences tumor growth. Ongoing work will focus on understanding how specific fat sources and diet durations impact ICI treatment and ultimately inform the design of more specific dietary interventions to enhance the efficacy of treatment.
利益披露 Disclosure
R. C. Simpson, None..
F. E. R. Edge, None..
J. W. Conway, None..
H. Tseng, None..
M. Okada, None..
I. Camaya, None..
L. Smith, None..
A. Ramanathan, None..
O. K. Fuller, None..
S. W. C. Masson, None..
J. Tiffen, None.
G. V. Long,
Agenus Other, consultant advisor.
AstraZeneca Other, consultant advisor.
Bayer Other, consultant advisor.
Boehringer Ingelheim Other, consultant advisor.
BioNTech Other, consultant advisor.
Bristol Myers Squibb Other, consultant advisor.
Evaxion Other, consultant advisor.
Fortiva Biologics Other, consultant advisor.
GI Innovation Other, consultant advisor.
Highlight Therapeutics Other, consultant advisor.
Immunocore Other, consultant advisor.
Innovent Biologics USA Other, consultant advisor.
IOBiotech Other, consultant advisor.
Iovance Biotherapeutics Other, consultant advisor.
MSD Other, consultant advisor.
Novartis Other, consultant advisor.
Pierre Fabre consultant advisor.
Regeneron Other, consultant advisor.
Scancell Other, consultant advisor.
SkylineDX B.V. Other, consultant advisor.
E. R. Shanahan, None.