Mitochondrial mutations and metabolic adaptation in pancreatic cancer Journal Article


Author(s): Hardie, Rae-Anne; van Dam, Ellen; Cowley, Mark; Han, Ting-Li; Balaban, Seher; Pajic, Marina; Pinese, Mark; Iconomou, Mary; Shearer, Robert F; McKenna, Jessie; Miller, David; Waddell, Nicola; Pearson, John V; Grimmond, Sean M; Sazanov, Leonid; Biankin, Andrew V; Villas-Boas, Silas; Hoy, Andrew J; Turner, Nigel; Saunders, Darren N
Article Title: Mitochondrial mutations and metabolic adaptation in pancreatic cancer
Affiliation IST Austria
Abstract: Background: Pancreatic cancer has a five-year survival rate of ~8%, with characteristic molecular heterogeneity and restricted treatment options. Targeting metabolism has emerged as a potentially effective therapeutic strategy for cancers such as pancreatic cancer, which are driven by genetic alterations that are not tractable drug targets. Although somatic mitochondrial genome (mtDNA) mutations have been observed in various tumors types, understanding of metabolic genotype-phenotype relationships is limited. Methods: We deployed an integrated approach combining genomics, metabolomics, and phenotypic analysis on a unique cohort of patient-derived pancreatic cancer cell lines (PDCLs). Genome analysis was performed via targeted sequencing of the mitochondrial genome (mtDNA) and nuclear genes encoding mitochondrial components and metabolic genes. Phenotypic characterization of PDCLs included measurement of cellular oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) using a Seahorse XF extracellular flux analyser, targeted metabolomics and pathway profiling, and radiolabelled glutamine tracing. Results: We identified 24 somatic mutations in the mtDNA of 12 patient-derived pancreatic cancer cell lines (PDCLs). A further 18 mutations were identified in a targeted study of ~1000 nuclear genes important for mitochondrial function and metabolism. Comparison with reference datasets indicated a strong selection bias for non-synonymous mutants with predicted functional effects. Phenotypic analysis showed metabolic changes consistent with mitochondrial dysfunction, including reduced oxygen consumption and increased glycolysis. Metabolomics and radiolabeled substrate tracing indicated the initiation of reductive glutamine metabolism and lipid synthesis in tumours. Conclusions: The heterogeneous genomic landscape of pancreatic tumours may converge on a common metabolic phenotype, with individual tumours adapting to increased anabolic demands via different genetic mechanisms. Targeting resulting metabolic phenotypes may be a productive therapeutic strategy.
Keywords: Genome; Mitochondria; Glutamine; lipid; metabolomics; pancreas
Journal Title: Cancer & Metabolism
Volume: 5
Issue 2
ISSN: 2049-3002
Publisher: BioMed Central  
Date Published: 2017-01-30
Copyright Statement: CC BY 4.0
DOI: 10.1186/s40170-017-0164-1
Notes: This research was supported by funding from the National Health and Medical Research Council of Australia (NHMRC 1052963, 631701, 535903, 427601); Mostyn Family Foundation; Patricia Helen Guest Fellowship; New South Wales Office of Science and Medical Research, Cancer Institute New South Wales (09/CDF/2-39, 10/ECF/2-26; 10/CRF/1-01, 08/RSA/1-15, 07/CDF/1-28, 10/FRL/2-03, 06/RSA/1-05, 09/RIG/1-02, 10/TPG/1-04, 11/REG/1-10, 11/CDF/3-26); University of NSW; University of Sydney; Beth Yarrow Memorial Award in Medical Science; Australian Research Council (ARC) Future Fellowship; Australian Government Department of Innovation, Industry, Science and Research (DIISR); Australian Cancer Research Foundation (ACRF); Queensland Government (NIRAP); University of Queensland; Cancer Council NSW (SRP06-01); Philip Hemstritch Foundation.
Open access: yes (OA journal)