Metabolic rewiring of pancreatic ductal adenocarcinoma: New routes to follow within the maze

Olivares, O. Porta; Vasseur, Sophie

doi:10.1002/ijc.29501

Cited by 22 publications

(30 citation statements)

References 94 publications

(199 reference statements)

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“…It has been reported that the one-carbon metabolism and proline metabolism pathways interconnect with glycolysis and pentose phosphate pathway to provide ATP, and NADH and NADPH (mediators of electron transfer for energy, reductive biosynthesis and redox defense) [8, 9, 42]. (Pink indicates upregulated pathways in MSKCC subset; grey indicates other heterogeneous pathways).…”

Section: Discussionmentioning

confidence: 99%

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Metabolic heterogeneity signature of primary treatment-naïve prostate cancer

Lin

Ettinger

et al. 2017

Oncotarget

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To avoid over- or under-treatment of primary prostate tumours, there is a critical need for molecular signatures to discriminate indolent from aggressive, lethal disease. Reprogrammed energy metabolism is an important hallmark of cancer, and abnormal metabolic characteristics of cancers have been implicated as potential diagnostic/prognostic signatures. While genomic and transcriptomic heterogeneity of prostate cancer is well documented and associated with tumour progression, less is known about metabolic heterogeneity of the disease. Using a panel of high fidelity patient-derived xenograft (PDX) models derived from hormone-naïve prostate cancer, we demonstrated heterogeneity of expression of genes involved in cellular energetics and macromolecular biosynthesis. Such heterogeneity was also observed in clinical, treatment-naïve prostate cancers by analyzing the transcriptome sequencing data. Importantly, a metabolic gene signature of increased one-carbon metabolism or decreased proline degradation was identified to be associated with significantly decreased biochemical disease-free patient survival. These results suggest that metabolic heterogeneity of hormone-naïve prostate cancer is of biological and clinical importance and motivate further studies to determine the heterogeneity in metabolic flux in the disease that may lead to identification of new signatures for tumour/patient stratification and the development of new strategies and targets for therapy of prostate cancer.

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Section: Discussionmentioning

confidence: 99%

“…The cycling of proline catabolism and proline synthesis acts as a redox shuttle between the mitochondria and cytosol to maintain redox homeostasis [41, 42]. Furthermore, increased proline biosynthesis contributes to cancer cell growth by providing NAD+/NADP+ molecules to the pentose phosphate pathway and to glycolysis [40].…”

Section: Discussionmentioning

confidence: 99%

Metabolic heterogeneity signature of primary treatment-naïve prostate cancer

Lin

Ettinger

et al. 2017

Oncotarget

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“…The drivers of PDAC metabolic preference are likely reflective of both oncogenic signaling pathways and the unique desmoplastic stromal microenvironment [13, 18–20]. It has been proposed that poor vascularization and hypoxia contribute to metabolic features of PDAC, while others have recently demonstrated that stromal diversity (activated vs .…”

Section: Introductionmentioning

confidence: 99%

Unique metabolic features of pancreatic cancer stroma: relevance to the tumor compartment, prognosis, and invasive potential

et al. 2016

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Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis. The aggressiveness and therapeutic recalcitrance of this malignancy has been attributed to multiple factors including the influence of an active desmoplastic stroma. How the stromal microenvironment of PDAC contributes to the fatal nature of this disease is not well defined. In the analysis of clinical specimens, we observed diverse expression of the hypoxic marker carbonic anhydrase IX and the lactate transporter MCT4 in the stromal compartment. These stromal features were associated with the epithelial to mesenchymal phenotype in PDAC tumor cells, and with shorter patient survival. Cultured cancer-associated fibroblasts (CAFs) derived from primary PDAC exhibited a high basal level of hypoxia inducible factor 1a (HIF1α) that was both required and sufficient to modulate the expression of MCT4. This event was associated with increased transcription and protein synthesis of HIF1α in CAFs relative to PDAC cell lines, while surprisingly the protein turnover rate was equivalent. CAFs utilized glucose predominantly for glycolytic intermediates, whereas glutamine was the preferred metabolite for the TCA cycle. Unlike PDAC cell lines, CAFs were resistant to glucose withdrawal but sensitive to glutamine depletion. Consistent with the lack of reliance on glucose, CAFs could survive the acute depletion of MCT4. In co-culture and xenograft studies CAFs stimulated the invasive potential and metastatic spread of PDAC cell lines through a mechanism dependent on HIF1α and MCT4. Together, these data indicate that stromal metabolic features influence PDAC tumor cells to promote invasiveness and metastatic potential and associate with poor outcome in patients with PDAC.

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“…This may indicate that when cancer has already developed, amino acid exhaustion results in the reduction of these amino acids. Glucose and glutamine metabolism is one of the most disturbed pathways in PC and has been intensively investigated for its potential therapeutic value [7, 19, 20]. Glutamine-dependent metabolism is critical for PC cell growth [21].…”

Section: Discussionmentioning

confidence: 99%

Serum metabolomics differentiating pancreatic cancer from new-onset diabetes

Zhong

Wang

et al. 2017

Oncotarget

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To establish a screening strategy for pancreatic cancer (PC) based on new-onset diabetic mellitus (NO-DM), serum metabolomics analysis and a search for the metabolic pathways associated with PC related DM were performed. Serum samples from patients with NO-DM (n = 30) and patients with pancreatic cancer and NO-DM were examined by liquid chromatography-mass spectrometry. Data were analyzed using principal components analysis (PCA) and orthogonal projection to latent structures (OPLS) of the most significant metabolites. The diagnostic model was constructed using logistic regression analysis. Metabolic pathways were analyzed using the web-based tool MetPA. PC patients with NO-DM were older and had a lower BMI and shorter duration of DM than those with NO-DM. The metabolomic profiles of patients with PC and NO-DM were significantly different from those of patients with NO-DM in the PCA and OPLS models. Sixty two differential metabolites were identified by the OPLS model. The logistic regression model using a panel of two metabolites including N_Succinyl_L_diaminopimelic_acid and PE (18:2) had high sensitivity (93.3%) and specificity (93.1%) for PC. The top three metabolic pathways associated with PC related DM were valine, leucine and isoleucine biosynthesis and degradation, primary bile acid biosynthesis, and sphingolipid metabolism. In conclusion, screening for PC based on NO-DM using serum metabolomics in combination with clinic characteristics and CA19-9 is a potential useful strategy. Several metabolic pathways differed between PC related DM and type 2 DM.

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Metabolic rewiring of pancreatic ductal adenocarcinoma: New routes to follow within the maze

Cited by 22 publications

References 94 publications

Metabolic heterogeneity signature of primary treatment-naïve prostate cancer

Metabolic heterogeneity signature of primary treatment-naïve prostate cancer

Unique metabolic features of pancreatic cancer stroma: relevance to the tumor compartment, prognosis, and invasive potential

Serum metabolomics differentiating pancreatic cancer from new-onset diabetes

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