{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Rao AD"],"funding":["U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)","U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI)","Cancer Prevention and Research Institute of Texas (Cancer Prevention Research Institute of Texas)","Victorian Cancer Agency (VCA)","NCI NIH HHS","Department of Health | National Health and Medical Research Council (NHMRC)","Dermatology Foundation (DF)","Doris Duke Charitable Foundation (DDCF)","Howard Hughes Medical Institute (HHMI)"],"pagination":["1703-1713"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12373500"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["7(8)"],"pubmed_abstract":["Patient-derived xenografts (PDXs) are frequently used as preclinical models, but their recapitulation of tumour metabolism in patients has not been closely examined. We developed a parallel workflow to analyse [U-<sup>13</sup>C]glucose tracing and metabolomics data from patient melanomas and matched PDXs. Melanomas from patients have substantial TCA cycle labelling, similar to levels in human brain tumours. Although levels of TCA cycle labelling in PDXs were similar to those in the original patient tumours, PDXs had higher labelling in glycolytic metabolites. Through metabolomics, we observed consistent alterations of 100 metabolites among PDXs and patient tumours that reflected species-specific differences in diet, host physiology and microbiota. Despite these differences, most of nearly 200 PDXs retained a 'metabolic fingerprint' largely durable over six passages and often traceable back to the patient tumour of origin. This study identifies both high- and low-fidelity metabolites in the PDX model system, providing a resource for cancer metabolism researchers."],"journal":["Nature metabolism"],"pubmed_title":["Conservation and divergence of metabolic phenotypes between patient tumours and matched xenografts."],"pmcid":["PMC12373500"],"funding_grant_id":["R35CA220449","N/A","T32AR065969-08","U01 CA228608","U01CA228608","RP240494","2023-0237","RP180778","2P50CA196516","1K08CA279757","RP210041","5P50CA070907","2038731","R01CA285336"],"pubmed_authors":["Wix SN","Walsdorf RE","DeBerardinis RJ","Homsi J","Cai L","Kim J","Santos Patricio J","Mathews TP","Brown AB","Morrison SJ","Solmonson A","Zacharias LG","Muh S","Faubert B","Sharma R","Gard G","Gu W","Tillman B","Vandergriff TW","Li X","Gill JG","Rao AD","Martin Sandoval M","Snyman M","Heimdal KA"],"additional_accession":[]},"is_claimable":false,"name":"Conservation and divergence of metabolic phenotypes between patient tumours and matched xenografts.","description":"Patient-derived xenografts (PDXs) are frequently used as preclinical models, but their recapitulation of tumour metabolism in patients has not been closely examined. We developed a parallel workflow to analyse [U-<sup>13</sup>C]glucose tracing and metabolomics data from patient melanomas and matched PDXs. Melanomas from patients have substantial TCA cycle labelling, similar to levels in human brain tumours. Although levels of TCA cycle labelling in PDXs were similar to those in the original patient tumours, PDXs had higher labelling in glycolytic metabolites. Through metabolomics, we observed consistent alterations of 100 metabolites among PDXs and patient tumours that reflected species-specific differences in diet, host physiology and microbiota. Despite these differences, most of nearly 200 PDXs retained a 'metabolic fingerprint' largely durable over six passages and often traceable back to the patient tumour of origin. This study identifies both high- and low-fidelity metabolites in the PDX model system, providing a resource for cancer metabolism researchers.","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Aug","modification":"2026-05-09T10:47:12.763Z","creation":"2026-04-08T00:49:05.893Z"},"accession":"S-EPMC12373500","cross_references":{"pubmed":["40731149"],"doi":["10.1038/s42255-025-01338-2"]}}