Roth Heidi E, Powers Robert
Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA.
Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA.
Cancers (Basel). 2022 Aug 18;14(16):3992. doi: 10.3390/cancers14163992.
Clinical metabolomics is a rapidly expanding field focused on identifying molecular biomarkers to aid in the efficient diagnosis and treatment of human diseases. Variations in study design, metabolomics methodologies, and investigator protocols raise serious concerns about the accuracy and reproducibility of these potential biomarkers. The explosive growth of the field has led to the recent availability of numerous replicate clinical studies, which permits an evaluation of the consistency of biomarkers identified across multiple metabolomics projects. Pancreatic ductal adenocarcinoma (PDAC) is the third-leading cause of cancer-related death and has the lowest five-year survival rate primarily due to the lack of an early diagnosis and the limited treatment options. Accordingly, PDAC has been a popular target of clinical metabolomics studies. We compiled 24 PDAC metabolomics studies from the scientific literature for a detailed meta-analysis. A consistent identification across these multiple studies allowed for the validation of potential clinical biomarkers of PDAC while also highlighting variations in study protocols that may explain poor reproducibility. Our meta-analysis identified 10 metabolites that may serve as PDAC biomarkers and warrant further investigation. However, 87% of the 655 metabolites identified as potential biomarkers were identified in single studies. Differences in cohort size and demographics, -value choice, fold-change significance, sample type, handling and storage, data collection, and analysis were all factors that likely contributed to this apparently large false positive rate. Our meta-analysis demonstrated the need for consistent experimental design and normalized practices to accurately leverage clinical metabolomics data for reliable and reproducible biomarker discovery.
临床代谢组学是一个迅速发展的领域,专注于识别分子生物标志物,以辅助人类疾病的高效诊断和治疗。研究设计、代谢组学方法以及研究人员方案的差异引发了对这些潜在生物标志物的准确性和可重复性的严重担忧。该领域的爆炸式增长导致近期有大量重复的临床研究可供使用,这使得评估跨多个代谢组学项目所识别的生物标志物的一致性成为可能。胰腺导管腺癌(PDAC)是癌症相关死亡的第三大原因,其五年生存率最低,主要是由于缺乏早期诊断以及治疗选择有限。因此,PDAC一直是临床代谢组学研究的热门目标。我们从科学文献中收集了24项PDAC代谢组学研究进行详细的荟萃分析。这些多项研究中的一致识别使得PDAC潜在临床生物标志物得以验证,同时也突出了研究方案中的差异,这些差异可能解释了可重复性差的原因。我们的荟萃分析确定了10种可能作为PDAC生物标志物的代谢物,值得进一步研究。然而,在被确定为潜在生物标志物的655种代谢物中,87%是在单项研究中被识别出来的。队列规模和人口统计学、P值选择、倍数变化显著性、样本类型、处理和储存、数据收集以及分析等方面的差异都是可能导致这一明显高假阳性率的因素。我们的荟萃分析表明,需要一致的实验设计和标准化操作,以便准确利用临床代谢组学数据进行可靠且可重复的生物标志物发现。