Pirfenidone reduces immune-suppressive capacity of cancer-associated fibroblasts through targeting CCL17 and TNF-beta.

IF 1.5 4区 生物学 Q4 CELL BIOLOGY
Hamidreza Aboulkheyr Es, Sareh Zhand, Jean Paul Thiery, Majid Ebrahimi Warkiani
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引用次数: 23

Abstract

Various factors in the tumor microenvironment (TME) regulate the expression of PD-L1 in carcinoma cells. The cancer-associated fibroblasts (CAFs) play a crucial role in regulating and rewiring TME to enhance their immune suppressive function and to favor the invasion of the malignant cells. Tumor progression may be retarded by targeting CAFs in the TME. Various studies highlighted the ability of targeting CAF with pirfenidone (PFD), leading to increased efficacy of chemotherapy. However, its potential for the reduction of immune-suppression capacity of CAFs remains to be elusive. Here, we assessed the effect of PFD on the expression of PD-L1 on CAF cells. Besides migration inhibitory effects of PFD on CAFs, the expression level of PD-L1 reduced in CAFs after treatment with PFD. The downstream analysis of released cytokines from CAFs showed that PFD significantly dropped the secretion of CCL17 and TNF-β, where a positive association between PFD-targeted proteins and PD-L1 was observed. These data suggest that the treatment of CAF within TME through the PFD may reduce the acquisition of CAF-mediated invasive and immune-suppressive capacity of breast carcinoma cells.

吡非尼酮通过靶向CCL17和tnf - β降低癌症相关成纤维细胞的免疫抑制能力。
肿瘤微环境(tumor microenvironment, TME)中的多种因素调控PD-L1在癌细胞中的表达。癌症相关成纤维细胞(CAFs)在调节和重新布线TME中发挥关键作用,以增强其免疫抑制功能并有利于恶性细胞的侵袭。靶向TME中的CAFs可能会延缓肿瘤进展。各种研究强调了吡非尼酮(PFD)靶向CAF的能力,从而提高了化疗的疗效。然而,其降低CAFs免疫抑制能力的潜力仍然是难以捉摸的。在这里,我们评估了PFD对CAF细胞PD-L1表达的影响。除了PFD对CAFs的迁移抑制作用外,PFD治疗后CAFs中PD-L1的表达水平降低。对CAFs释放的细胞因子的下游分析显示,PFD显著降低了CCL17和TNF-β的分泌,其中PFD靶向蛋白与PD-L1之间存在正相关。这些数据表明,通过PFD治疗TME内的CAF可能会降低乳腺癌细胞获得CAF介导的侵袭和免疫抑制能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Integrative Biology
Integrative Biology 生物-细胞生物学
CiteScore
4.90
自引率
0.00%
发文量
15
审稿时长
1 months
期刊介绍: Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems. Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity. Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.
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