Human Breast Cancer Xenograft Model Implicates Peroxisome Proliferator-activated Receptor Signaling as Driver of Cancer-induced Muscle Fatigue

人乳腺癌异种移植模型表明过氧化物酶体增殖物激活受体信号通路是癌症诱导肌肉疲劳的驱动因素

阅读:1

Abstract

PURPOSE: This study tested the hypothesis that a patient-derived orthotopic xenograft (PDOX) model would recapitulate the common clinical phenomenon of breast cancer-induced skeletal muscle (SkM) fatigue in the absence of muscle wasting. This study additionally sought to identify drivers of this condition to facilitate the development of therapeutic agents for patients with breast cancer experiencing muscle fatigue. EXPERIMENTAL DESIGN: Eight female BC-PDOX-bearing mice were produced via transplantation of tumor tissue from 8 female patients with breast cancer. Individual hind limb muscles from BC-PDOX mice were isolated at euthanasia for RNA-sequencing, gene and protein analyses, and an ex vivo muscle contraction protocol to quantify tumor-induced aberrations in SkM function. Differentially expressed genes (DEG) in the BC-PDOX mice relative to control mice were identified using DESeq2, and multiple bioinformatics platforms were employed to contextualize the DEGs. RESULTS: We found that SkM from BC-PDOX-bearing mice showed greater fatigability than control mice, despite no differences in absolute muscle mass. PPAR, mTOR, IL6, IL1, and several other signaling pathways were implicated in the transcriptional changes observed in the BC-PDOX SkM. Moreover, 3 independent in silico analyses identified PPAR signaling as highly dysregulated in the SkM of both BC-PDOX-bearing mice and human patients with early-stage nonmetastatic breast cancer. CONCLUSIONS: Collectively, these data demonstrate that the BC-PDOX model recapitulates the expected breast cancer-induced SkM fatigue and further identify aberrant PPAR signaling as an integral factor in the pathology of this condition.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。