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全面描绘肾癌的代谢相关亚型,以辅助临床治疗。

Comprehensive Characterization of Metabolism-Associated Subtypes of Renal Cell Carcinoma to Aid Clinical Therapy.

机构信息

Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.

Department of Urology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

出版信息

Oxid Med Cell Longev. 2022 Feb 27;2022:9039732. doi: 10.1155/2022/9039732. eCollection 2022.

DOI:10.1155/2022/9039732
PMID:35265267
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8898770/
Abstract

Renal cell carcinoma (RCC) is a disease characterized by excessive administration complexity because it exhibits extraordinary nonuniformity among distinct molecular subtypes. We herein intended to delineate the metabolic aspects of clear cell RCC (ccRCC) in terms of the gene expression profile. Recent studies have revealed that metabolic variations within tumors are related to the responsiveness to immune checkpoint inhibitor (ICI) therapy and patient prognosis. We used 100 previously reported metabolic (MTB) pathways to quantify the metabolic landscape of the 729 ccRCC patients. Three MTB subtypes were established, and the MTB scores were calculated using principal component analysis (PCA). The high MTB score group had better overall survival (OS) and was associated with higher expression of immune-checkpoint and immune-activity signatures. The opposite was true of the low MTB score group, which may explain the poor prognosis of these patients. Three ICI-treated cohorts or tyrosine kinase inhibitor (TKI) treated cohort proved that patients with higher MTB scores exhibited notable therapeutic benefits and clinical gains. This research explained that the MTB score could be applied as a powerful prognostic indicator and predictive of ICI or TKI therapy. Assessing the MTB scores in a more extended group will facilitate our perception of tumor metabolism and provide guidance for studies on targeted approaches for ccRCC patients.

摘要

肾细胞癌(RCC)是一种疾病,其特点是给药复杂性过高,因为它在不同的分子亚型之间表现出非凡的非均匀性。在此,我们旨在根据基因表达谱描绘透明细胞 RCC(ccRCC)的代谢方面。最近的研究表明,肿瘤内的代谢变化与对免疫检查点抑制剂(ICI)治疗的反应性和患者预后有关。我们使用了 100 个先前报道的代谢(MTB)途径来量化 729 名 ccRCC 患者的代谢景观。建立了三种 MTB 亚型,并使用主成分分析(PCA)计算了 MTB 分数。高 MTB 分数组的总生存率(OS)更好,与免疫检查点和免疫活性特征的高表达相关。低 MTB 分数组则相反,这可能解释了这些患者预后不良的原因。三个接受 ICI 治疗的队列或酪氨酸激酶抑制剂(TKI)治疗队列证明,MTB 评分较高的患者表现出显著的治疗益处和临床获益。这项研究表明,MTB 评分可以作为一种强大的预后指标,并预测 ICI 或 TKI 治疗的效果。在更广泛的患者群体中评估 MTB 评分将有助于我们了解肿瘤代谢,并为 ccRCC 患者的靶向治疗研究提供指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0d/8898770/a765a73d4720/OMCL2022-9039732.006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0d/8898770/a765a73d4720/OMCL2022-9039732.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0d/8898770/13216c54b380/OMCL2022-9039732.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0d/8898770/08fb23d75af1/OMCL2022-9039732.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0d/8898770/23ecc9ad302f/OMCL2022-9039732.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0d/8898770/a0adb17535c9/OMCL2022-9039732.004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d0d/8898770/a765a73d4720/OMCL2022-9039732.006.jpg

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