Table_1_Pan-Cancer Analysis of Glycolytic and Ketone Bodies Metabolic Genes: Implications for Response to Ketogenic Dietary Therapy.xls

BackgroundThe Warburg effect, also termed “aerobic glycolysis”, is one of the most remarkable and ubiquitous metabolic characteristics exhibited by cancer cells, representing a potential vulnerability that might be targeted for tumor therapy. Ketogenic diets (KDs), composed of high-fat, moderate-protein and low carbohydrates, are aimed at targeting the Warburg effect for cancer treatment, which have recently gained considerable attention. However, the efficiency of KDs was inconsistent, and the genotypic contribution is still largely unknown.
MethodsThe bulk RNA-seq data from The Cancer Genome Atlas (TCGA), single cell RNA sequencing (scRNA-seq), and microarray data from Gene Expression Omnibus (GEO) and Cancer Cell Line Encyclopedia (CCLE) were collected. A joint analysis of glycolysis and ketone bodies metabolism (KBM) pathway was performed across over 10,000 tumor samples and nearly 1,000 cancer cell lines. A series of bioinformatic approaches were combined to identify a metabolic subtype that may predict the response to ketogenic dietary therapy (KDT). Mouse xenografts were established to validate the predictive utility of our subtypes in response to KDT.
ResultsWe first provided a system-level view of the expression pattern and prognosis of the signature genes from glycolysis and KBM pathway across 33 cancer types. Analysis by joint stratification of glycolysis and KBM revealed four metabolic subtypes, which correlated extensively but diversely with clinical outcomes across cancers. The glycolytic subtypes may be driven by TP53 mutations, whereas the KB-metabolic subtypes may be mediated by CTNNB1 (β-catenin) mutations. The glycolytic subtypes may have a better response to KDs compared to the other three subtypes. We preliminarily confirmed the idea by literature review and further performed a proof-of-concept experiment to validate the predictive value of the metabolic subtype in liver cancer xenografts.
ConclusionsOur findings identified a metabolic subtype based on glycolysis and KBM that may serve as a promising biomarker to predict the clinical outcomes and therapeutic responses to KDT.

Background 瓦伯格效应（Warburg effect）又称“有氧糖酵解”，是癌细胞最为显著且普遍存在的代谢特征之一，其作为肿瘤治疗的潜在靶向脆弱点具有重要研究价值。生酮饮食（Ketogenic diets, KDs）以高脂、适量蛋白、低碳水为核心构成原则，旨在通过靶向瓦伯格效应开展癌症治疗，近年来获得了广泛的研究关注。然而，生酮饮食的治疗效率并不统一，其基因型层面的贡献仍在很大程度上未知。
Methods 本研究收集了癌症基因组图谱（The Cancer Genome Atlas, TCGA）的批量RNA测序（bulk RNA-seq）数据、单细胞RNA测序（single cell RNA sequencing, scRNA-seq）数据，以及基因表达综合数据库（Gene Expression Omnibus, GEO）与癌细胞系百科全书（Cancer Cell Line Encyclopedia, CCLE）的微阵列数据。针对超过10000份肿瘤样本与近1000株癌细胞系的糖酵解与酮体代谢（ketone bodies metabolism, KBM）通路开展联合分析。结合一系列生物信息学方法，本研究鉴定出可预测生酮饮食疗法（ketogenic dietary therapy, KDT）响应的代谢亚型。通过构建小鼠异种移植模型，验证了该代谢亚型对生酮饮食疗法响应的预测效能。
Results 本研究首先系统展示了33种癌症中糖酵解与KBM通路特征基因的表达模式及预后价值。通过对糖酵解与酮体代谢通路进行联合分层分析，共鉴定出四种代谢亚型，这些亚型在不同癌症中与临床结局广泛且多样地相关。其中，糖酵解亚型可能由TP53突变驱动，而酮体代谢亚型可能由CTNNB1（β-连环蛋白）突变介导。相较于其余三种亚型，糖酵解亚型对生酮饮食的响应效果更佳。本研究通过文献综述初步验证了这一观点，并进一步开展概念验证实验，在肝癌异种移植模型中验证了该代谢亚型的预测价值。
Conclusions 本研究鉴定出基于糖酵解与酮体代谢的代谢亚型，其有望作为预测临床结局及生酮饮食疗法治疗响应的潜在生物标志物。