[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-346511-105":59,"doc-detail-346511-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","plasma-metabolomic-signatures-of-all-and-cause-specific-cancers-a-multi-platform-population-based-study","Plasma metabolomic signatures of all and cause-specific cancers - a multi-platform population-based study","","Early cancer detection is essential to improve patient outcomes, and metabolomics has demonstrated value for cancer detection and understanding metastatic burden. This study tests whether plasma metabolomic profiles can distinguish individuals with and without cancer at the population level, while uncovering novel biomarkers reflecting cancer metabolic biology. Using baseline samples from the Rotterdam Study, 1,386 metabolites were measured across two platforms and analyzed with regression and competing-risk models.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/plasma-metabolomic-signatures-of-all-and-cause-specific-cancers-a-multi-platform-population-based-study/346511/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/plasma-metabolomic-signatures-of-all-and-cause-specific-cancers-a-multi-platform-population-based-study/346511.png","ImageObject",300,407,{"name":92,"@type":93},"Finn","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-23","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the study’s main objective?","Question",{"text":112,"@type":113},"To determine whether metabolomics data can differentiate people with and without cancer at the population level, while uncovering new biomarkers and clarifying cancer metabolism.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were metabolites measured and analyzed?",{"text":117,"@type":113},"A total of 1,386 metabolites were measured in baseline plasma using two platforms (Nightingale and Metabolon). Logistic regression and competing risk Cox proportional hazards models assessed associations with prevalent and incident cancers.",{"name":119,"@type":110,"acceptedAnswer":120},"What were the study’s key findings?",{"text":121,"@type":113},"Several plasma metabolites were significantly associated with prevalent and incident cancers. The number of significant metabolites varied by cancer type, and some metabolites were associated with both prevalent and incident blood and colorectal cancers.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},346511,1790158492,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":41},34359740700684,"https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487","Metabolomics (2026) 22:27  \n[https://doi.org/10.1007/s1](https://doi.org/10.1007/s1) 1306-026-02397-6  \nORIGINAL ARTICLE  \nPlasma metabolomic signatures of all and cause-specific cancers: a multi-platform population-based study  \nYu Shuai1 · Rikje Ruiter1,2 · Bruno H. Stricker1 · M. Arfan Ikram1 · Mohsen Ghanbari1  \nReceived: 4 June 2025 / Accepted: 13 January 2026 / Published online: 20 February 2026 © The Author(s) 2026  \nAbstract  \nIntroduction Early diagnosis of cancer is essential for improving patient outcomes. Metabolomics analysis has shown promise in detecting cancer and distinguishing its metastatic burdens in previous studies.  \nObjectives We hypothesized that metabolomics data can differentiate between people with and without cancer at a population level, uncovering new biomarkers and deepening our understanding of cancer metabolism.  \nMethods A total of 1,386 metabolites were measured by two commonly used metabolomics platforms: Nightingale and Metabolon, in baseline plasma samples from participants in the population-based Rotterdam Study, with sample sizes of 2,538 and 5,057, respectively. Logistic regression and competing risk Cox proportional hazards models were employed to examine associations between these metabolites and both baseline prevalent and incident during follow-up of all and causespecific cancers. Statistical significance was defined by a false discovery rate (FDR) \u003C 0.05.  \nResults There were 654 cancer cases at baseline, and 618 new cases also occurred during follow-up of nearly 10 years. In the cross-sectional study, 68, 7, and 10 metabolites were significantly associated with prevalent blood, colorectal, and all cancer, after multivariate adjustment. In the longitudinal study, 19, 11, 2, 3, and 1 metabolites were significantly associated with incident blood, colorectal, lung, prostate, and all cancer, respectively. Among these, 17 and 2 metabolites were associated with both prevalent and incident blood and colorectal cancer.  \nConclusions This study indicates several circulating metabolites that are associated with different cancers. These metabolites may contribute to better understanding of the metabolic pathways of cancer and serve as biomarkers for early cancer diagnosis.  \nKeywords Metabolomic signatures · Circulating metabolites · Biomarker · All cancers · Cause-specific cancers · Population-based study  \nAbbreviations  \nFDR False discovery rate  \nRS Rotterdam study  \nSD Standard deviation  \nCIs Confidence intervals  \nBMI Body mass index PFOS Perfluorooctanesulfonate PFOA Perfluorooctanoate  \n􀀍 Mohsen Ghanbari[m.ghanbari@erasmusmc.nl](m.ghanbari@erasmusmc.nl)  \n1 Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands  \n2 Department of Internal Medicine, Maasstad hospital, Rotterdam, Netherlands  \nCE Cholesteryl esters  \nTG Triglyceride  \nTC Total cholesterol  \nHDL High-density lipoprotein  \nHDL-C High-density lipoprotein cholesterol  \n1 Introduction  \nMetabolomics analysis aims to detect, identify, and quantify a diverse range of low molecular weight biochemicals present in biological fluids, tissues, and cells (Johnson et al., 2016) . It reflects end-stage alterations in the genome, transcriptome, and proteome, thereby offering more insights into the pathological processes underlying diseases (Adam et al., 2021; Li et al., 2020; Liu et al., 2022) . Substantial  \nevidence suggests that the reprogramming of cellular energy metabolism is a central characteristic of cancer, effectively supporting the demands of uncontrolled tumor proliferation (Schiliro & Firestein, 2021) . This metabolic dysregulation gives rise to a characteristic metabolic phenotype, emerging as a novel diagnostic approach for various human cancers, including breast (Xiao et al., 2022), liver (Liu et al., 2022), and colorectal (Yachida et al., 2019) cancers, among others (Wang et al., 2021) . Moreover, it can aid in tumor staging and prognosis, or serve as a biomarker for therapeutic ","cbCailoLJePhzcQ3","https://ap.wps.com/l/cbCailoLJePhzcQ3","pdf",1926919,12,"English","# Abstract\n## Introduction\n## Objectives\n## Methods\n## Results\n## Conclusions\n# Keywords","[{\"question\":\"What is the study’s main objective?\",\"answer\":\"To determine whether metabolomics data can differentiate people with and without cancer at the population level, while uncovering new biomarkers and clarifying cancer metabolism.\"},{\"question\":\"How were metabolites measured and analyzed?\",\"answer\":\"A total of 1,386 metabolites were measured in baseline plasma using two platforms (Nightingale and Metabolon). Logistic regression and competing risk Cox proportional hazards models assessed associations with prevalent and incident cancers.\"},{\"question\":\"What were the study’s key findings?\",\"answer\":\"Several plasma metabolites were significantly associated with prevalent and incident cancers. The number of significant metabolites varied by cancer type, and some metabolites were associated with both prevalent and incident blood and colorectal cancers.\"}]","Plasma metabolomic signatures of all and cause-specific cancers - a multi-platform population-based study | PDF",1790061751]