Abstract
Background: Most of the patients with Pancreatic Ductal Adenocarcinoma (PDA) are not eligible for a curative surgical resection. For this reason there is an urgent need for personalized therapies. PDA is the result of complex interactions between tumor molecular profile and metabolites produced by its microenvironment. Despite recent studies identified PDA molecular subtypes, its metabolic classification is still lacking.Methods: We applied an integrative analysis on transcriptomic and genomic data of glycolytic genes in PDA. Data were collected from public datasets and molecular glycolytic subtypes were defined using hierarchical clustering. The grade of purity of the cancer samples was assessed estimating the different amount of stromal and immunological infiltrate among the identified PDA subtypes. Analyses of metabolomic data from a subset of PDA cell lines allowed us to identify the different metabolites produced by the metabolic subtypes. Sera of a cohort of 31 PDA patients were analyzed using Q-TOF mass spectrometer to measure the amount of metabolic circulating proteins present before and after chemotherapy.Results: Our integrative analysis of glycolytic genes identified two glycolytic and two non-glycolytic metabolic PDA subtypes. Glycolytic patients develop disease earlier, have poor prognosis, low immune-infiltrated tumors, and are characterized by a gain in chr12p13 genomic region. This gain results in the over-expression of GAPDH, TPI1, and FOXM1. PDA cell lines with the gain of chr12p13 are characterized by an higher lipid uptake and sensitivity to drug targeting the fatty acid metabolism. Our sera proteomic analysis confirms that TPI1 serum levels increase in poor prognosis gemcitabine-treated patients.Conclusions: We identify four metabolic PDA subtypes with different prognosis outcomes which may have pivotal role in setting personalized treatments. Moreover, our data suggest TPI1 as putative prognostic PDA biomarker.
Highlights
Pancreatic Ductal Adenocarcinoma (PDA) is one of the deadliest cancer with patients presenting advanced metastatic disease at diagnosis [1]
To identify the candidate PDA glycolysis subtypes, we performed an integrative analysis of expression and Copy Number Variations (CNVs) of 38 glycolytic genes using RNA-Seq and whole genome sequencing data from 176 TCGA PDA samples
Basing on this clustering analysis, Gly tumors can be further subdivided into two subtypes defined as High Glycolytic (HG, n = 32) and Very High Glycolytic (VHG, n = 26)
Summary
Pancreatic Ductal Adenocarcinoma (PDA) is one of the deadliest cancer with patients presenting advanced metastatic disease at diagnosis [1]. PDA develops over decades without clinical relevant symptoms and it accumulates mutations in oncogenic drivers (i.e., KRAS) and Copy Number Variations (CNVs). These genomic alterations will reflect in several changes at genes expression level [1, 3]. The hypoxic regions of PDA tumors have an increased expression level of the lactate exporter monocarboxylate transporter 4 (MCT4). Most of the patients with Pancreatic Ductal Adenocarcinoma (PDA) are not eligible for a curative surgical resection. For this reason there is an urgent need for personalized therapies. Despite recent studies identified PDA molecular subtypes, its metabolic classification is still lacking
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