Irina Heid, Corinna Münch, Sinan Karakaya, Smiths S Lueong, Alina M Winkelkotte, Sven T Liffers, Laura Godfrey, Phyllis F Y Cheung, Konstantinos Savvatakis, Geoffrey J Topping, Florian Englert, Lukas Kritzner, Martin Grashei, Andrea Tannapfel, Richard Viebahn, Heiner Wolters, Waldemar Uhl, Deepak Vangala, Esther M M Smeets, Erik H J G Aarntzen, Daniel Rauh, Wilko Weichert, Jörg D Hoheisel, Stephan A Hahn, Franz Schilling, Rickmer Braren, Marija Trajkovic-Arsic, Jens T Siveke
{"title":"Functional noninvasive detection of glycolytic pancreatic ductal adenocarcinoma.","authors":"Irina Heid, Corinna Münch, Sinan Karakaya, Smiths S Lueong, Alina M Winkelkotte, Sven T Liffers, Laura Godfrey, Phyllis F Y Cheung, Konstantinos Savvatakis, Geoffrey J Topping, Florian Englert, Lukas Kritzner, Martin Grashei, Andrea Tannapfel, Richard Viebahn, Heiner Wolters, Waldemar Uhl, Deepak Vangala, Esther M M Smeets, Erik H J G Aarntzen, Daniel Rauh, Wilko Weichert, Jörg D Hoheisel, Stephan A Hahn, Franz Schilling, Rickmer Braren, Marija Trajkovic-Arsic, Jens T Siveke","doi":"10.1186/s40170-022-00298-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Pancreatic ductal adenocarcinoma (PDAC) lacks effective treatment options beyond chemotherapy. Although molecular subtypes such as classical and QM (quasi-mesenchymal)/basal-like with transcriptome-based distinct signatures have been identified, deduced therapeutic strategies and targets remain elusive. Gene expression data show enrichment of glycolytic genes in the more aggressive and therapy-resistant QM subtype. However, whether the glycolytic transcripts are translated into functional glycolysis that could further be explored for metabolic targeting in QM subtype is still not known.</p><p><strong>Methods: </strong>We used different patient-derived PDAC model systems (conventional and primary patient-derived cells, patient-derived xenografts (PDX), and patient samples) and performed transcriptional and functional metabolic analysis. These included RNAseq and Illumina HT12 bead array, in vitro Seahorse metabolic flux assays and metabolic drug targeting, and in vivo hyperpolarized [1-<sup>13</sup>C]pyruvate and [1-<sup>13</sup>C]lactate magnetic resonance spectroscopy (HP-MRS) in PDAC xenografts.</p><p><strong>Results: </strong>We found that glycolytic metabolic dependencies are not unambiguously functionally exposed in all QM PDACs. Metabolic analysis demonstrated functional metabolic heterogeneity in patient-derived primary cells and less so in conventional cell lines independent of molecular subtype. Importantly, we observed that the glycolytic product lactate is actively imported into the PDAC cells and used in mitochondrial oxidation in both classical and QM PDAC cells, although more actively in the QM cell lines. By using HP-MRS, we were able to noninvasively identify highly glycolytic PDAC xenografts by detecting the last glycolytic enzymatic step and prominent intra-tumoral [1-<sup>13</sup>C]pyruvate and [1-<sup>13</sup>C]lactate interconversion in vivo.</p><p><strong>Conclusion: </strong>Our study adds functional metabolic phenotyping to transcriptome-based analysis and proposes a functional approach to identify highly glycolytic PDACs as candidates for antimetabolic therapeutic avenues.</p>","PeriodicalId":9418,"journal":{"name":"Cancer & Metabolism","volume":"10 1","pages":"24"},"PeriodicalIF":6.0000,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737747/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer & Metabolism","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40170-022-00298-5","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Pancreatic ductal adenocarcinoma (PDAC) lacks effective treatment options beyond chemotherapy. Although molecular subtypes such as classical and QM (quasi-mesenchymal)/basal-like with transcriptome-based distinct signatures have been identified, deduced therapeutic strategies and targets remain elusive. Gene expression data show enrichment of glycolytic genes in the more aggressive and therapy-resistant QM subtype. However, whether the glycolytic transcripts are translated into functional glycolysis that could further be explored for metabolic targeting in QM subtype is still not known.
Methods: We used different patient-derived PDAC model systems (conventional and primary patient-derived cells, patient-derived xenografts (PDX), and patient samples) and performed transcriptional and functional metabolic analysis. These included RNAseq and Illumina HT12 bead array, in vitro Seahorse metabolic flux assays and metabolic drug targeting, and in vivo hyperpolarized [1-13C]pyruvate and [1-13C]lactate magnetic resonance spectroscopy (HP-MRS) in PDAC xenografts.
Results: We found that glycolytic metabolic dependencies are not unambiguously functionally exposed in all QM PDACs. Metabolic analysis demonstrated functional metabolic heterogeneity in patient-derived primary cells and less so in conventional cell lines independent of molecular subtype. Importantly, we observed that the glycolytic product lactate is actively imported into the PDAC cells and used in mitochondrial oxidation in both classical and QM PDAC cells, although more actively in the QM cell lines. By using HP-MRS, we were able to noninvasively identify highly glycolytic PDAC xenografts by detecting the last glycolytic enzymatic step and prominent intra-tumoral [1-13C]pyruvate and [1-13C]lactate interconversion in vivo.
Conclusion: Our study adds functional metabolic phenotyping to transcriptome-based analysis and proposes a functional approach to identify highly glycolytic PDACs as candidates for antimetabolic therapeutic avenues.
期刊介绍:
Cancer & Metabolism welcomes studies on all aspects of the relationship between cancer and metabolism, including: -Molecular biology and genetics of cancer metabolism -Whole-body metabolism, including diabetes and obesity, in relation to cancer -Metabolomics in relation to cancer; -Metabolism-based imaging -Preclinical and clinical studies of metabolism-related cancer therapies.