Dataset Information

Metabolic phenotypes in pancreatic cancer.

ABSTRACT:

Introduction

The aim of present study was to profile the glucose-dependent and glutamine- dependent metabolism in pancreatic cancer.

Methods

We performed Immunohistochemical staining of GLUT1, CAIX, BNIP3, p62, LC3, GLUD1, and GOT1. Based on the expression of metabolism-related proteins, the metabolic phenotypes of tumors were classified into two categories, including glucose- and glutamine-dependent metabolism. There were Warburg type, reverse Warburg type, mixed type, and null type in glucose-dependent metabolism, and canonical type, non-canonical type, mixed type, null type in glutamine-dependent metabolism.

Results

Longer overall survival was associated with high expression of BNIP3 in tumor (p = 0.010). Shorter overall survival was associated with high expression of GLUT1 in tumor (P = 0.002) and GOT1 in tumor (p = 0.030). Warburg type of glucose-dependent metabolism had a highest percentage of tumors with nerve infiltration (P = 0.0003), UICC stage (P = 0.0004), and activated autophagic status in tumor (P = 0.0167). Mixed type of glucose-dependent metabolism comprised the highest percentage of tumors with positive marginal status (P<0.0001), lymphatic invasion (P<0.0001), and activated autophagic status in stroma (P = 0.0002). Mixed type and Warburg type had a significant association with shorter overall survival (P = 0.018). Non-canonical type and mixed type of glutamine-dependent metabolism comprised the highest percentage of tumors with vascular invasion (p = 0.0073), highest percentage of activated autophagy in tumors (P = 0.0034). Moreover, these two types of glutamine-dependent metabolism were significantly associated with shorter overall survival (P<0.001). Further analysis suggested that most of tumors were dependent on both glucose- and glutamine-dependent metabolism. After dividing the tumors according to the number of metabolism, we found that the increasing numbers of metabolism subtypes inversely associated with survival outcome.

Conclusion

Warburg type, non-canonical type and mixed types of glucose- and glutamine-dependent metabolism comprised of more metabolically active, biologically aggressive and poor prognostic tumors. Moreover, the increasing subtypes and categories of the metabolism in each tumor significantly associated with poor prognosis.

SUBMITTER: Yu M

PROVIDER: S-EPMC4342019 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Metabolic phenotypes in pancreatic cancer.

Yu Min M Zhou Quanbo Q Zhou Yu Y Fu Zhiqiang Z Tan Langping L Ye Xiao X Zeng Bing B Gao Wenchao W Zhou Jiajia J Liu Yimin Y Li Zhihua Z Lin Ye Y Lin Qing Q Chen Rufu R

PloS one 20150226 2

<h4>Introduction</h4>The aim of present study was to profile the glucose-dependent and glutamine- dependent metabolism in pancreatic cancer.<h4>Methods</h4>We performed Immunohistochemical staining of GLUT1, CAIX, BNIP3, p62, LC3, GLUD1, and GOT1. Based on the expression of metabolism-related proteins, the metabolic phenotypes of tumors were classified into two categories, including glucose- and glutamine-dependent metabolism. There were Warburg type, reverse Warburg type, mixed type, and null t ...[more]

PMID: 25719198

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Project description: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.

Dataset Information

Metabolic phenotypes in pancreatic cancer.

Introduction

Methods

Results

Conclusion

Publications

Metabolic phenotypes in pancreatic cancer.

Similar Datasets

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