IL17A critically shapes the transcriptional program of fibroblasts in pancreatic cancer and switches on their protumorigenic functions.

A hallmark of cancer, including pancreatic ductal adenocarcinoma (PDA), is a massive stromal and inflammatory reaction. Many efforts have been made to identify the anti- or protumoral role of cytokines and immune subpopulations within the stroma. Here, we investigated the role of interleukin-17A (IL17A) and its effect on tumor fibroblasts and the tumor microenvironment. We used a spontaneous PDA mouse model (KPC) crossed to IL17A knockout mice to show an extensive desmoplastic reaction, without impaired immune infiltration. Macrophages, especially CD80+ and T cells, were more abundant at the earlier time point. In T cells, a decrease in FoxP3+ cells and an increase in CD8+ T cells were observed in KPC/IL17A-/- mice. Fibroblasts isolated from IL17A+/+ and IL17A-/- KPC mice revealed very different messenger RNA (mRNA) and protein profiles. IL17A-/- fibroblasts displayed the ability to restrain tumor cell invasion by producing factors involved in extracellular matrix remodeling, increasing T cell recruitment, and producing higher levels of cytokines and chemokines favoring T helper 1 cell recruitment and activation and lower levels of those recruiting myeloid/granulocytic immune cells. Single-cell quantitative PCR on isolated fibroblasts confirmed a very divergent profile of IL17A-proficient and -deficient cells. All these features can be ascribed to increased levels of IL17F observed in the sera of IL17A-/- mice, and to the higher expression of its cognate receptor (IL17RC) specifically in IL17A-/- cancer-associated fibroblasts (CAFs). In addition to the known effects on neoplastic cell transformation, the IL17 cytokine family uniquely affects fibroblasts, representing a suitable candidate target for combinatorial immune-based therapies in PDA.

A Comprehensive Search of Non-Canonical Proteins in Non-Small Cell Lung Cancer and Their Impact on the Immune Response.

There is substantial interest in mining neoantigens for cancer applications. Non-canonical proteins resulting from frameshift mutations have been identified as neoantigens in cancer. We investigated the landscape of non-canonical proteins in non-small cell lung cancer (NSCLC) and their induced immune response in the form of autoantibodies. A database of cryptoproteins was computationally constructed and comprised all alternate open reading frames (altORFs) and ORFs identified in pseudogenes, noncoding RNAs, and untranslated regions of mRNAs that did not align with known canonical proteins. Proteomic profiles of seventeen lung adenocarcinoma (LUAD) cell lines were searched to evaluate the occurrence of cryptoproteins. To assess the immunogenicity, immunoglobulin (Ig)-bound cryptoproteins in plasmas were profiled by mass spectrometry. The specimen set consisted of plasmas from 30 newly diagnosed NSCLC cases, pre-diagnostic plasmas from 51 NSCLC cases, and 102 control plasmas. An analysis of LUAD cell lines identified 420 cryptoproteins. Plasma Ig-bound analyses revealed 90 cryptoproteins uniquely found in cases and 14 cryptoproteins that had a fold-change >2 compared to controls. In pre-diagnostic samples, 17 Ig-bound cryptoproteins yielded an odds ratio ≥2. Eight Ig-bound cryptoproteins were elevated in both pre-diagnostic and newly diagnosed cases compared to controls. Cryptoproteins represent a class of neoantigens that induce an autoantibody response in NSCLC.

The length of the receiver operating characteristic curve and the two cutoff Youden index within a robust framework for discovery, evaluation, and cutoff estimation in biomarker studies involving improper receiver operating characteristic curves.

During the early stage of biomarker discovery, high throughput technologies allow for simultaneous input of thousands of biomarkers that attempt to discriminate between healthy and diseased subjects. In such cases, proper ranking of biomarkers is highly important. Common measures, such as the area under the receiver operating characteristic (ROC) curve (AUC), as well as affordable sensitivity and specificity levels, are often taken into consideration. Strictly speaking, such measures are appropriate under a stochastic ordering assumption, which implies, without loss of generality, that higher measurements are more indicative for the disease. Such an assumption is not always plausible and may lead to rejection of extremely useful biomarkers at this early discovery stage. We explore the length of a smooth ROC curve as a measure for biomarker ranking, which is not subject to directionality. We show that the length corresponds to a ϕ divergence, is identical to the corresponding length of the optimal (likelihood ratio) ROC curve, and is an appropriate measure for ranking biomarkers. We explore the relationship between the length measure and the AUC of the optimal ROC curve. We then provide a complete framework for the evaluation of a biomarker in terms of sensitivity and specificity through a proposed ROC analogue for use in improper settings. In the absence of any clinical insight regarding the appropriate cutoffs, we estimate the sensitivity and specificity under a two-cutoff extension of the Youden index and we further take into account the implied costs. We apply our approaches on two biomarker studies that relate to pancreatic and esophageal cancer.

Mass spectrometric analysis reveals O-methylation of pyruvate kinase from pancreatic cancer cells.

Pyruvate kinase (PK) is an important glycolytic enzyme that catalyzes the dephosphorylation of phosphoenolpyruvate to pyruvate. Human PK isozyme M2 (PKM2), a splice variant of M1, is overexpressed in many cancer cells, and PKM2 has been investigated as a potential tumor marker for diagnostic assays and as a target for cancer therapy. To facilitate identification and characterization of PK, we studied the enzyme from pancreatic cancer cells and normal pancreatic duct cells by electrophoresis and mass spectrometry, and identified multiple O-methylated residues from PK. These findings advance our knowledge of the biochemical properties of PK and will be important in understanding its biological function in cells.

Tumor-Associated and Systemic Autoimmunity in Pre-Clinical Breast Cancer among Post-Menopausal Women.

Autoantibodies to tumor-associated antigens (anti-TAA) are potential biomarkers for breast cancer, but their relationship systemic autoimmunity as ascertained though antinuclear antibodies (ANA) is unknown and warrants consideration given the common occurrence of autoimmunity and autoimmune diseases among women. The relationship between anti-TAAs and ANA among women who were later diagnosed with breast cancer and others who remained cancer free in the Women's Health Initiative cohort. The study sample included 145 post-menopausal women with baseline ANA data. A total of 37 ANA-positive women who developed breast cancer (i.e., cases; mean time to diagnosis 6.8 years [SE 3.9]) were matched to a random sample of 36 ANA-negative cases by age and time to diagnosis. An age-matched control sample was selected including 35 ANA-positive and 37 ANA-negative women who did not develop breast cancer (i.e., controls; follow-up time ~13 years [SE 3]). Baseline sera were assessed for Immunoglobulin G (IgG) antibodies, measured by custom microarray for 171 breast and other cancer-associated TAA. We used linear regression to estimate cross-sectional associations of ANA with log-transformed anti-TAA among cases and controls. Most anti-TAA did not vary by ANA status. Two anti-TAA were elevated in ANA-positive compared to ANA-negative cases: anti-PGM3 (p = 0.004) and anti-TTN (p = 0.005, especially in cases up to 7 years before diagnosis, p = 0.002). Anti-TAA antibodies were not generally related to ANA, a common marker of systemic autoimmunity. Associations of ANA with particular antigens inducing autoimmunity prior to breast cancer warrant further investigation.

Proteomic analysis reveals Warburg effect and anomalous metabolism of glutamine in pancreatic cancer cells.

In this present work, we characterized the proteomes of pancreatic ductal adenocarcinoma (PDAC) cell line PANC-1 and normal pancreatic duct cells by mass spectrometry using LTQ-Orbitrap and identified more than 1700 proteins from each sample. On the basis of the spectra count label-free quantification approach, we identified a large number of differentially expressed metabolic enzymes and proteins involved in cytoskeleton, cell adhesion, transport, transcription, translation, and cell proliferation as well. The data demonstrated that metabolic pathways were altered in PANC-1, consistent with the Warburg effect. In addition, the comparative MS analysis unveiled anomalous metabolism of glutamine, suggesting that glutamine was largely consumed as a nitrogen donor in nucleotide and amino acid biosynthesis in PANC-1. Our analysis provides a potentially comprehensive picture of metabolism in PANC-1, which may serve as the basis of new diagnostics and treatment of PDAC.

MS analysis reveals O-methylation of L-lactate dehydrogenase from pancreatic ductal adenocarcinoma cells.

L-lactate dehydrogenase (LDH) converts pyruvate to lactate when oxygen is absent or in short supply, and the enzyme plays a crucial role in cancer metabolism. The functions of many mammalian proteins are modulated by posttranslational modifications (PTMs), and it has been reported that LDH was subjected to several PTMs, including phosphorylation, acetylation, and methylation. In this present work, we characterized the PTMs of LDH from pancreatic ductal adenocarcinoma (PDAC) cells by electrophoresis and mass spectrometry, and identified 13 O-methylated residues from the enzyme. In addition, our qualitative analysis revealed differential methylation of LDH from normal duct cells. The preliminary findings from this study provide important biochemical information toward further understanding of the LDH modifications and their functional significance in pathophysiological processes of pancreatic cancer.

Proteomic Profiling of the Tumor Microenvironment.

The tumor microenvironment forms a complex pro-tumorigenic milieu constituted by extracellular matrix, surrounding stroma, infiltrating cell populations, and signaling molecules. Proteomic studies have the potential to reveal how individual cell populations within the tumor tissue modulate the microenvironment through protein secretion and consequently alter their protein expression and localization to adapt to this milieu. As a result, proteomic approaches have uncovered how these dynamic components communicate and promote tumor development and progression. The characterization of these mechanisms is relevant for the identification of clinically targetable pathways and for the development of diagnostic tools. Here we describe a method based on the isolation of individual cell compartments and the chromatographic fractionation of intact proteins, followed by enzymatic digestion of individual fractions, and mass-spectrometry analysis, for the profiling of tumor microenvironment cell populations.

CES2 sustains HNF4α expression to promote pancreatic adenocarcinoma progression through an epoxide hydrolase-dependent regulatory loop.

OBJECTIVE: Intra-tumoral expression of the serine hydrolase carboxylesterase 2 (CES2) contributes to the activation of the pro-drug irinotecan in pancreatic ductal adenocarcinoma (PDAC). Given other potential roles of CES2, we assessed its regulation, downstream effects, and contribution to tumor development in PDAC. METHODS: Association between the mRNA expression of CES2 in pancreatic tumors and overall survival was assessed using The Cancer Genome Atlas. Cell viability, clonogenic, and anchorage-independent growth assays as well as an orthotopic mouse model of PDAC were used to evaluate the biological relevance of CES2 in pancreatic cancer. CES2-driven metabolic changes were determined by untargeted and targeted metabolomic analyses. RESULTS: Elevated tumoral CES2 mRNA expression was a statistically significant predictor of poor overall survival in PDAC patients. Knockdown of CES2 in PDAC cells reduced cell viability, clonogenic capacity, and anchorage-independent growth in vitro and attenuated tumor growth in an orthotopic mouse model of PDAC. Mechanistically, CES2 was found to promote the catabolism of phospholipids resulting in HNF4α activation through a soluble epoxide hydrolase (sEH)-dependent pathway. Targeting of CES2 via siRNA or small molecule inhibitors attenuated HNF4α protein expression and reduced gene expression of classical/progenitor markers and increased basal-like markers. Targeting of the CES2-sEH-HNF4α axis using small molecule inhibitors of CES2 or sEH reduced cell viability. CONCLUSIONS: We establish a novel regulatory loop between CES2 and HNF4α to sustain the progenitor subtype and promote PDAC progression and highlight the potential utility of CES2 or sEH inhibitors for the treatment of PDAC as part of non-irinotecan-containing regimens.

Proteomic analysis of pancreatic ductal adenocarcinoma cells reveals metabolic alterations.

In this present work, we characterized the proteomes of pancreatic ductal adenocarcinoma (PDAC) cells and normal pancreatic duct cells by mass spectrometry using LTQ-Orbitrap, and identified more than 1200 proteins from each sample. On the basis of spectra count label-free quantification approach, we identified a large number of differentially expressed metabolic enzymes and proteins involved in cytoskeleton, cell adhesion, transport, transcription, translation, and cell proliferation as well. The data demonstrated that metabolic pathways were altered in PDAC, consistent with Warburg effect. Our analysis provides a potentially comprehensive picture of metabolism in PDAC, which may serve as the basis of new diagnostic and treatment of PDAC.

Circulating autoantibodies to phosphorylated α-enolase are a hallmark of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis and no diagnostic markers have, as of yet, been defined. In PDAC patients, α-enolase (ENOA) is up-regulated and elicits the production of autoantibodies. Here, we analyzed the autoantibody response to post-translational modifications of ENOA in PDAC patients. ENOA isolated from PDAC tissues and cell lines was characterized by two-dimensional electrophoresis (2-DE) Western blot (WB), revealing the expression of six different isoforms (named ENOA1,2,3,4,5,6) whereas only 4 isoforms (ENOA3,4,5,6) were detectable in normal tissues. As assessed by 2-DE WB, 62% of PDAC patients produced autoantibodies to the two more acidic isoforms (ENOA1,2) as opposed to only 4% of controls. Mass spectrometry showed that ENOA1,2 isoforms were phosphorylated on serine 419. ROC analysis demonstrated that autoantibodies to ENOA1,2 usefully complement the diagnostic performance of serum CA19.9 levels, achieving approximately 95% diagnostic accuracy in both advanced and resectable PDAC. Moreover, the presence of autoantibodies against ENOA1,2 correlated with a significantly better clinical outcome in advanced patients treated with standard chemotherapy. In conclusion, our results demonstrate that ENOA phosphorylation is associated with PDAC and induces specific autoantibody production in PDAC patients that may have diagnostic value.

Mass spectrometry analysis of the post-translational modifications of alpha-enolase from pancreatic ductal adenocarcinoma cells.

Enolase is a key glycolytic enzyme that catalyzes the dehydration of 2-phosphoglycerate to phosphoenolpyruvate. Recently, enolase was revealed as an important protein in pathophysiological processes since it was found on the surface of hematopoietic cells and overexpressed in several tumor cells. Our previous studies demonstrated that alpha-enolase is up-regulated in pancreatic ductal adenocarcinoma (PDAC). In this present work, we further characterized the alpha-enolase from PDAC and normal pancreatic duct cells by mass spectrometry using LTQ-Orbitrap and identified multiple post-translational modifications of alpha-enolase, such as phosphorylation, acetylation, and methylation. The result showed that more acetylated lysines, methylated aspartic acids, and glutamic acids were found in PDAC cells than that of normal pancreatic duct cells.

Effectiveness and Selectiveness of Traps and Baits for Catching the Invasive Hornet Vespa velutina.

Vespa velutina is an invasive hornet that is colonising several countries worldwide, with detrimental effects on multiple components but primarily affecting honey bees and native insect species. Traps for wasps and hornets are commonly used for trapping V. velutina, both for monitoring and control purposes. In this study, we compared the performances of two typologies of traps and baits widely used for trapping this invasive hornet, by evaluating their effectiveness and selectiveness in trapping V. velutina in two sites during two different periods of the year, spring and autumn. The performance of the traps changed in relation to (i) the trap's model, (ii) the bait's typology and (iii) the period of the year. In spring, traps with common beer as bait were more effective and more selective independently of trap's model than the commercial bait that has been tested. On the contrary, in autumn, just one combination of trap and attractant (the commercial trap and bait) achieved higher effectiveness and selectiveness. Despite the underlined variations among traps and baits, overall catches of V. velutina were scanty compared to bycatches of non-target insects, since best performing traps either in term of effectiveness and selectiveness caught 3.65% of the target species in spring and 1.35% in autumn upon the total trapped insects. This highlights the urgent necessity of developing more selective trapping methods for monitoring and particularly for controlling purposes.

Plasma-Derived Extracellular Vesicles Convey Protein Signatures that Reflect Pathophysiology in Lung and Pancreatic Adenocarcinomas.

Using a combination of mass-spectrometry and aptamer array-based proteomics, we characterized the protein features of circulating extracellular vesicles (EVs) in the context of lung (LUAD) and pancreatic ductal (PDAC) adenocarcinomas. We profiled EVs isolated from conditioned media of LUAD and PDAC cell lines to identify EV-associated protein cargoes released by these cancer cell types. Analysis of the resulting data identified LUAD and PDAC specific and pan-adenocarcinoma EV protein signatures. Bioinformatic analyses confirmed enrichment of proteins annotated to vesicle-associated processes and intracellular compartments, as well as representation of cancer hallmark functions and processes. Analysis of upstream regulator networks indicated significant enrichment of TP53, MYC, TGFB1 and KRAS-driven network effectors (p = 1.69 × 10-77-2.93 × 10-49) manifest in the adenocarcinoma sEV protein cargoes. We extended these findings by profiling the proteome of EVs isolated from lung (N = 15) and pancreatic ductal (N = 6) adenocarcinoma patient plasmas obtained at time of diagnosis, along with EVs derived from matched healthy controls (N = 21). Exploration of these proteomic data revealed abundant protein features in the plasma EVs with capacity to distinguish LUAD and PDAC cases from controls, including features yielding higher performance in the plasma EV isolates relative to unfractionated plasmas.

Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients.

Pancreatic Ductal Adenocarcinoma (PDA) is an aggressive malignancy with a very poor outcome. Although chemotherapy (CT) treatment has poor efficacy, it can enhance tumor immunogenicity. Tumor-Associated Antigens (TAA) are self-proteins that are overexpressed in tumors that may induce antibody production and can be PDA theranostic targets. However, the prognostic value of TAA-antibody association as Circulating Immune Complexes (CIC) has not yet been elucidated, mainly due to the lack of techniques that lead to their identification. In this study, we show a novel method to separate IgG, IgM, and IgA CIC from sera to use them as prognostic biomarkers of CT response. The PDA Immune-Complexome (IC) was identified using a LTQ-Orbitrap mass spectrometer followed by computational analysis. The analysis of the IC of 37 PDA patients before and after CT revealed differential associated antigens (DAA) for each immunoglobulin class. Our method identified different PDA-specific CIC in patients that were associated with poor prognosis patients. Finally, CIC levels were significantly modified by CT suggesting that they can be used as effective prognostic biomarkers to follow CT response in PDA patients.

Association Between Plasma Diacetylspermine and Tumor Spermine Synthase With Outcome in Triple-Negative Breast Cancer.

BACKGROUND: MYC is an oncogenic driver of development and progression in triple-negative breast cancer (TNBC). Ornithine decarboxylase, the rate-limiting enzyme in polyamine metabolism, is a transcriptional target of MYC. We therefore hypothesized that a plasma polyamine signature may be predictive of TNBC development and progression. METHODS: Using liquid chromatography mass spectrometry, polyamine levels were determined in plasma samples from newly diagnosed patients with TNBC (n = 87) and cancer-free controls (n = 115). Findings were validated in plasma samples from an independent prospective cohort of 54 TNBC, 55 estrogen receptor negative (ER-) and progesterone receptor negative (PR-) and HER2 positive (HER2+), and 73 ER+ case patients, and 30 cancer-free control subjects. Gene expression data and clinical data for 921 and 2359 breast cancer tumors were obtained from The Cancer Genome Atlas repository and the Oncomine database, respectively. Relationships between plasma diacetylspermine (DAS) and tumor spermine synthase (SMS) mRNA expression with metastasis-free survival and overall survival were determined using Cox proportional hazard models; Fisher exact tests were used to assess risk of distant metastasis in relation to tumor SMS mRNA expression. RESULTS: An increase in plasma DAS, a catabolic product of spermine mediated through SMS, was observed in the TNBC subtype of breast cancer. Plasma levels of DAS in TNBC associated with increased risk of metastasis (plasma DAS value ≥ 1.16, hazard ratio = 3.06, 95% confidence interval [CI] = 1.15 to 8.13, two-sided P = .03). SMS mRNA expression in TNBC tumor tissue was also found to be predictive of poor overall survival (top 25th percentile hazard ratio = 2.06, 95% CI = 1.04 to 4.08, one-sided P = .04) and increased risk of distant metastasis in TNBC (comparison of lowest SMS quartile [reference] to highest SMS quartile relative risk = 1.90, 95% CI = 0.97 to 4.06, one-sided Fisher exact test P=.03). CONCLUSIONS: Metabolomic profiling identified plasma DAS as a predictive marker for TNBC progression and metastasis.

CES2 Expression in Pancreatic Adenocarcinoma Is Predictive of Response to Irinotecan and Is Associated With Type 2 Diabetes.

PURPOSE: The combination chemotherapy of fluorouracil, leucovorin, irinotecan, and oxaliplatin (FOLFIRINOX) has provided clinically meaningful improvement for pancreatic ductal adenocarcinoma (PDAC). We previously uncovered a role for the serine hydrolase carboxylesterase 2 (CES2) in mediating intratumoral activation of the prodrug irinotecan, a constituent of FOLFIRINOX. We aimed to further test the predictive value of CES2 for response to irinotecan using patient-derived xenograft (PDX) models and to elucidate the determinants of CES2 expression and response to FOLFIRINOX treatment among patients with PDAC. METHODS: PDXs were engrafted subcutaneously into nude mice and treated for 4 weeks with either saline control or irinotecan. CES2 and hepatocyte nuclear factor 4 alpha (HNF4A) expression in PDAC tissues was evaluated by immunohistochemical and Western blot analysis. Kaplan-Meier and Cox regression analyses were applied to assess the association between overall survival and hemoglobin A1C (HbA1C) levels in patients who underwent neoadjuvant FOLFIRINOX treatment. RESULTS: High CES2 activity in PDAC PDXs was associated with increased sensitivity to irinotecan. Integrated gene expression, proteomic analyses, and in vitro genetic experiments revealed that nuclear receptor HNF4A, which is upregulated in diabetes, is the upstream transcriptional regulator of CES2 expression. Elevated CES2 protein expression in PDAC tissues was positively associated with a history of type 2 diabetes (odds ratio, 4.84; P = .02). High HbA1C levels were associated with longer overall survival in patients who received neoadjuvant FOLFIRINOX treatment (P = .04). CONCLUSION: To our knowledge, we provide, for the first time, evidence that CES2 expression is associated with a history of type 2 diabetes in PDAC and that elevated HbA1C, by predicting tumor CES2 expression, may represent a novel marker for stratifying patients most likely to respond to FOLFIRINOX therapy.

Measuring human carboxylesterase 2 activity in pancreatic cancer patient-derived xenografts using a ratiometric fluorescent chemosensor.

Irinotecan-based therapy is a common treatment for pancreatic cancer. To elicit its anticancer activity, the drug requires first the hydrolysis action of the enzyme human carboxylesterase 2 (hCES2). It has been established that pancreatic cancer patients have various levels of hCES2, whereby patients having low levels respond poorer to Irinotecan than patients with higher levels, suggesting that hCES2 can be used to predict response. However, current methods that measure hCES2 activity are inaccurate, complex or lengthy, thus being incompatible for use in a clinical setting. Here, we developed a small molecule ratiometric fluorescent chemosensor that accurately measures hCES2 activity in a single-step within complex mixtures. Our chemosensor is highly selective for hCES2 over hCES1, cell permeable and can measure hCES2 activity in pancreatic cancer patient-derived xenografts. Given the simplicity, accuracy and tissue compatibility of our assay, we anticipate our chemosensor can be used to predict patient response to Irinotecan-based therapy.

A plasma protein derived TGFß signature is a prognostic indicator in triple negative breast cancer.

We investigated the potential of in-depth quantitative plasma proteome analysis to uncover proteins predictive of progression and metastasis in triple negative breast cancer (TNBC). Analysis of samples from 24 pre-menopausal and 24 post-menopausal women with newly diagnosed TNBC who subsequently developed metastasis or remained metastasis free were utilized in the proteomic discovery set, which resulted in 43 proteins associated with tumor progression. These proteins were found to form a hierarchical network with TGFß. The signature was further confirmed and refined by integrating plasma protein data from a murine TNBC model that encompassed mice with rapid- versus slow-growing tumors. Three genes consisting of CLIC1, MAPRE1, and SERPINA3 in the refined TGFß signature significantly stratified overall survival (log-rank p = 0.0141) in a larger validation cohort irrespective of menopausal status, tumor stage, grade, and size.

Integrative Analysis of Novel Metabolic Subtypes in Pancreatic Cancer Fosters New Prognostic Biomarkers.

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.