目的:对病例对照和队列人类研究进行系统综述和荟萃分析,评估使用高通量代谢组学技术鉴定的食管癌(EC)代谢物标志物,胃食管交界处癌(GEJ),血液和组织中的胃癌(GC)。
背景:上消化道癌症(UGC),主要是EC,GEJ,和GC,是具有高发病率和死亡率的恶性肿瘤类型。近年来,许多研究都集中在UGC的代谢组学分析上。在这篇系统综述和荟萃分析中,我们提供了关于与EC相关的代谢物和代谢组学分析的先前发现的集体总结,GEJ和GC。
方法:按照PRISMA程序,对四个数据库的系统搜索(Embase,PubMed,MEDLINE,和WebofScience)用于EC代谢组学概况的分子流行病学研究,GEJ和GC在PROSPERO(CRD42023486631)进行并注册。纽卡斯尔-渥太华量表(NOS)用于病例对照和队列研究的偏倚风险基准。quadomics,QUADAS-2(诊断准确性质量评估)工具的改编,用于对诊断准确性研究进行评分。包括比较有和没有UGC的患者之间代谢物模式的原始文章。两名调查员独立完成标题和摘要筛选,数据提取,和质量评估。尽可能进行Meta分析。我们使用随机效应模型来研究代谢物水平与UGC之间的关联。
结果:共纳入66项符合所需标准的原始研究,涉及7267例患者。在44例GC中,与健康患者相比,有169种代谢物在UGC患者中的分布差异。9GEJ,和25项EC研究,包括参与糖酵解的代谢物,无氧呼吸,三羧酸循环,和脂质代谢。磷脂酰胆碱,类花生酸,三磷酸腺苷是最常见的脂质和细胞呼吸代谢产物,而BCAA,赖氨酸,和天冬酰胺是最常报道的氨基酸之一。先前鉴定的脂质代谢物包括饱和和不饱和游离脂肪酸和酮。然而,不同研究的关键发现是不一致的,可能是由于样本量有限,而且大多数是基于医院的病例对照分析,缺乏独立的复制组。
结论:到目前为止,代谢组学研究为筛查提供了新的机会,病因因素,和UGC的生物标志物,支持在早期癌症诊断中应用代谢组学分析的潜力。根据我们的荟萃分析结果,尤其是BCAA和TMAO以及某些磷脂酰胆碱应被纳入UGC患者的诊断程序。我们设想代谢组学将显著增强我们对UGC的致癌和进展过程的理解,并可能最终促进UGC的精确肿瘤和患者定制管理。
OBJECTIVE: To conduct a systematic review and meta-analysis of case-control and cohort human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on esophageal cancer (EC), cancer of the gastroesophageal junction (GEJ), and gastric cancer (GC) in blood and tissue.
BACKGROUND: Upper gastrointestinal cancers (UGC), predominantly EC, GEJ, and GC, are malignant tumour types with high morbidity and mortality rates. Numerous studies have focused on metabolomic profiling of UGC in recent years. In this systematic review and meta-analysis, we have provided a collective summary of previous findings on metabolites and metabolomic profiling associated with EC, GEJ and GC.
METHODS: Following the PRISMA procedure, a systematic search of four databases (Embase, PubMed, MEDLINE, and Web of Science) for molecular epidemiologic studies on the metabolomic profiles of EC, GEJ and GC was conducted and registered at PROSPERO (CRD42023486631). The Newcastle-Ottawa Scale (NOS) was used to benchmark the risk of bias for case-controlled and cohort studies. QUADOMICS, an adaptation of the QUADAS-2 (Quality Assessment of Diagnostic Accuracy) tool, was used to rate diagnostic accuracy studies. Original articles comparing metabolite patterns between patients with and without UGC were included. Two investigators independently completed title and abstract screening, data extraction, and quality evaluation. Meta-analysis was conducted whenever possible. We used a random effects model to investigate the association between metabolite levels and UGC.
RESULTS: A total of 66 original studies involving 7267 patients that met the required criteria were included for review. 169 metabolites were differentially distributed in patients with UGC compared to healthy patients among 44 GC, 9 GEJ, and 25 EC studies including metabolites involved in glycolysis, anaerobic respiration, tricarboxylic acid cycle, and lipid metabolism. Phosphatidylcholines, eicosanoids, and adenosine triphosphate were among the most frequently reported lipids and metabolites of cellular respiration, while BCAA, lysine, and asparagine were among the most commonly reported amino acids. Previously identified lipid metabolites included saturated and unsaturated free fatty acids and ketones. However, the key findings across studies have been inconsistent, possibly due to limited sample sizes and the majority being hospital-based case-control analyses lacking an independent replication group.
CONCLUSIONS: Thus far, metabolomic studies have provided new opportunities for screening, etiological factors, and biomarkers for UGC, supporting the potential of applying metabolomic profiling in early cancer diagnosis. According to the results of our meta-analysis especially BCAA and TMAO as well as certain phosphatidylcholines should be implicated into the diagnostic procedure of patients with UGC. We envision that metabolomics will significantly enhance our understanding of the carcinogenesis and progression process of UGC and may eventually facilitate precise oncological and patient-tailored management of UGC.