Local and Systemic Cytokine Profiling for Pancreatic Ductal Adenocarcinoma to Study Cancer Cachexia in an Era of Precision Medicine

Cancer cachexia is a debilitating condition seen frequently in patients with pancreatic ductal adenocarcinoma (PDAC). The underlying mechanisms driving cancer cachexia are not fully understood but are related, at least in part, to the immune response to the tumor both locally and systemically. We hypothesize that there are unique differences in cytokine levels in the tumor microenvironment and systemic circulation between PDAC tumors and that these varying profiles affect the degree of cancer cachexia observed. Patient demographics, operative factors, oncologic factors, and perioperative data were collected for the two patients in the patient derived xenograft (PDX) model. Human pancreatic cancer PDX were created by implanting fresh surgical pancreatic cancer tissues directly into immunodeficient mice. At PDX end point, mouse tumor, spleen and muscle tissues were collected and weighed, muscle atrophy related gene expression measured, and tumor and splenic soluble proteins were analyzed. PDX models were created from surgically resected patients who presented with different degrees of cachexia. Tumor free body weight and triceps surae weight differed significantly between the PDX models and control (P < 0.05). Both PDX groups had increased atrophy related gene expression in muscle compared to control (FoxO1, Socs3, STAT3, Acvr2b, Atrogin-1, MuRF1; P < 0.05). Significant differences were noted in splenic soluble protein concentrations in 14 of 15 detected proteins in tumor bearing mice when compared to controls. Eight splenic soluble proteins were significantly different between PDX groups (P < 0.05). Tumor soluble proteins were significantly different between the two PDX groups in 15 of 24 detected proteins (P < 0.05). PDX models preserve the cachectic heterogeneity found in patients and are associated with unique cytokine profiles in both the spleen and tumor between different PDX. These data support the use of PDX as a strategy to study soluble cachexia protein markers and also further efforts to elucidate which cytokines are most related to cachexia in order to provide potential targets for immunotherapy.

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Aspartate β-hydroxylase promotes pancreatic ductal adenocarcinoma metastasis through activation of SRC signaling pathway

Journal of Hematology & Oncology ◽

10.1186/s13045-019-0837-z ◽

2019 ◽

Vol 12 (1) ◽

Cited By ~ 5

Author(s):

Kosuke Ogawa ◽

Qiushi Lin ◽

Le Li ◽

Xuewei Bai ◽

Xuesong Chen ◽

...

Keyword(s):

Pancreatic Cancer ◽

Pancreatic Ductal Adenocarcinoma ◽

Stem Cell Marker ◽

Ductal Adenocarcinoma ◽

Physical Interaction ◽

Pancreatic Cancer Cells ◽

Ecm Degradation ◽

Invadopodia Formation ◽

Pdx Models

Abstract Background Signaling pathways critical for embryonic development re-emerge in adult pancreas during tumorigenesis. Aspartate β-hydroxylase (ASPH) drives embryonic cell motility/invasion in pancreatic development/differentiation. We explored if dysregulated ASPH is critically involved in pancreatic cancer pathogenesis. Methods To demonstrate if/how ASPH mediates malignant phenotypes, proliferation, migration, 2-D/3-D invasion, pancreatosphere formation, immunofluorescence, Western blot, co-immunoprecipitation, invadopodia formation/maturation/function, qRT-PCR, immunohistochemistry (IHC), and self-developed in vitro metastasis assays were performed. Patient-derived xenograft (PDX) models of human pancreatic ductal adenocarcinoma (PDAC) were established to illustrate in vivo antitumor effects of the third-generation small molecule inhibitor specifically against ASPH’s β-hydroxylase activity. Prognostic values of ASPH network components were evaluated with Kaplan-Meier plots, log-rank tests, and Cox proportional hazards regression models. Results ASPH renders pancreatic cancer cells more aggressive phenotypes characterized by epithelial–mesenchymal transition (EMT), 2-D/3-D invasion, invadopodia formation/function as demonstrated by extracellular matrix (ECM) degradation, stemness (cancer stem cell marker upregulation and pancreatosphere formation), transendothelial migration (mimicking intravasation/extravasation), and sphere formation (mimicking metastatic colonization/outgrowth at distant sites). Mechanistically, ASPH activates SRC cascade through direct physical interaction with ADAM12/ADAM15 independent of FAK. The ASPH-SRC axis enables invadopodia construction and initiates MMP-mediated ECM degradation/remodeling as executors for invasiveness. Pharmacologic inhibition of invadopodia attenuates in vitro metastasis. ASPH fosters primary tumor development and pulmonary metastasis in PDX models of PDAC, which is blocked by a leading compound specifically against ASPH enzymatic activity. ASPH is silenced in normal pancreas, progressively upregulated from pre-malignant lesions to invasive/advanced stages of PDAC. Expression profiling of ASPH-SRC network components independently/jointly predicts clinical outcome of PDAC patients. Compared to a negative-low level, a moderate-very high level of ASPH, ADAM12, activated SRC, and MMPs correlated with curtailed overall survival (OS) of pancreatic cancer patients (log-rank test, ps < 0.001). The more unfavorable molecules patients carry, the more deleterious prognosis is destinated. Patients with 0–2 (n = 4), 3–5 (n = 8), 6–8 (n = 24), and 9–12 (n = 73) unfavorable expression scores of the 5 molecules had median survival time of 55.4, 15.9, 9.7, and 5.0 months, respectively (p < 0.001). Conclusion Targeting the ASPH-SRC axis, which is essential for propagating multi-step PDAC metastasis, may specifically/substantially retard development/progression and thus improve prognosis of PDAC.

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Meta-analysis of 1,200 transcriptomic profiles identifies a prognostic model for pancreatic ductal adenocarcinoma

10.1101/355602 ◽

2018 ◽

Cited By ~ 2

Author(s):

Vandana Sandhu ◽

Knut Jorgen Labori ◽

Ayelet Borgida ◽

Ilinca Lungu ◽

John Bartlett ◽

...

Keyword(s):

Gene Expression ◽

Pancreatic Cancer ◽

Overall Survival ◽

Pancreatic Ductal Adenocarcinoma ◽

Prognostic Model ◽

Meta Analysis ◽

Early Death ◽

Receiver Operating Curve ◽

Ductal Adenocarcinoma ◽

Survival Predictor

ABSTRACTBackgroundWith a dismal 8% median 5-year overall survival (OS), pancreatic ductal adenocarcinoma (PDAC) is highly lethal. Only 10-20% of patients are eligible for surgery, and over 50% of these will die within a year of surgery. Identify molecular predictors of early death would enable the selection of PDAC patients at high risk.MethodsWe developed the Pancreatic Cancer Overall Survival Predictor (PCOSP), a prognostic model built from a unique set of 89 PDAC tumors where gene expression was profiled using both microarray and sequencing platforms. We used a meta-analysis framework based on the binary gene pair method to create gene expression barcodes robust to biases arising from heterogeneous profiling platforms and batch effects. Leveraging the largest compendium of PDAC transcriptomic datasets to date, we show that PCOSP is a robust single-sample predictor of early death (≤1 yr) after surgery in a subset of 823 samples with available transcriptomics and survival data.ResultsThe PCOSP model was strongly and significantly prognostic with a meta-estimate of the area under the receiver operating curve (AUROC) of 0.70 (P=1.9e-18) and hazard ratio (HR) of 1.95(1.6-2.3) (P=2.6e-16) for binary and survival predictions, respectively. The prognostic value of PCOSP was independent of clinicopathological parameters and molecular subtypes. Over-representation analysis of the PCOSP 2619 gene-pairs (1070 unique genes) unveiled pathways associated with Hedgehog signalling, epithelial mesenchymal transition (EMT) and extracellular matrix (ECM) signalling.ConclusionPCOSP could improve treatment decision by identifying patients who will not benefit from standard surgery/chemotherapy and may benefit from alternate approaches.AbbreviationsAUROCArea under the receiver operating curveGOGene annotationOSOverall survivalPCOSPPancreatic cancer overall survival predictorPDACPancreatic ductal adenocarcinomaTSPTop scoring pairs.

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Identify key genes and pathways in pancreatic ductal adenocarcinoma via bioinformatics analysis

10.21203/rs.3.rs-16813/v1 ◽

2020 ◽

Author(s):

Huatian Luo ◽

Da-qiu Chen ◽

Jing-jing Pan ◽

Zhang-wei Wu ◽

Can Yang ◽

...

Keyword(s):

Gene Expression ◽

Pancreatic Cancer ◽

Pancreatic Ductal Adenocarcinoma ◽

Bioinformatics Analysis ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Gene Expression Omnibus ◽

Ductal Adenocarcinoma ◽

Hub Genes ◽

Expression Levels

Abstract Background: Pancreatic cancer has many pathologic types, among which pancreatic ductal adenocarcinoma (PDAC) is the most common one. Bioinformatics has become a very common tool for the selection of potentially pathogenic genes. Methods: Three data sets containing the gene expression profiles of PDAC were downloaded from the gene expression omnibus (GEO) database. The limma package of R language was utilized to explore the differentially expressed genes (DEGs). To analyze functions and signaling pathways, the Database Visualization and Integrated Discovery (DAVID) was used. To visualize the protein-protein interaction (PPI) of the DEGs ,Cytoscape was performed under the utilization of Search Tool for the Retrieval of Interacting Genes (STRING). With the usage of the plug-in cytoHubba in cytoscape software, the hub genes were found out. To verify the expression levels of hub genes, Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Last but not least, UALCAN analysis online tool was implemented to analyze the overall survival. Results: The 376 DEGs were highly enriched in biological processes including signal transduction, apoptotic process and several pathways, mainly associated with Protein digestion and absorption and Pancreatic secretion pathway. The expression levels of nucleolar and spindle associated protein 1 (NUSAP1) and SHC binding and spindle associated 1 (SHCBP1) were discovered highly expressed in pancreatic ductal adenocarcinoma tissues. NUSAP1 and SHCBP1 had a high correlation with prognosis. Conclusions: The findings of this bioinformatics analysis indicate that NUSAP1 and SHCBP1 may be key factors in the prognosis and treatment of pancreatic cancer.

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The systemic activin response to pancreatic cancer: Implications for effective cancer cachexia therapy

10.1101/343871 ◽

2018 ◽

Author(s):

Xiaoling Zhong ◽

Marianne Pons ◽

Christophe Poirier ◽

Yanlin Jiang ◽

Jianguo Liu ◽

...

Keyword(s):

Pancreatic Cancer ◽

Weight Loss ◽

Pancreatic Ductal Adenocarcinoma ◽

Conditioned Medium ◽

Tumor Cells ◽

Stromal Cells ◽

Cancer Cachexia ◽

Dominant Negative ◽

Prolonged Survival ◽

Ductal Adenocarcinoma

AbstractPancreatic ductal adenocarcinoma (PDAC) is a particularly lethal malignancy with high rates of cachexia. Serum activin correlates with PDAC cachexia and mortality, while activin administration causes cachexia in mice. We studied activin in human tumors and in mice with orthotopic or genetic PDAC. Cachexia severity correlated with activin expression in tumor lines. Activins were expressed in both cancer and tumor stromal cells, but also in organs in murine PDAC cachexia. Tumor cells expressed activin-βA, or Inhba, while organs expressed both activin-βA and activin-βB, or Inhbb. PDAC elicits activin expression; PDAC conditioned medium induced activin and atrophy of myotubes. Treatment with the activin trap, ACVR2B/Fc, reduced cachexia and prolonged survival in mice with activin-low tumors, and reduced cachexia in activin-high tumors, without affecting activin expression in organs. Mice expressing dominant negative ACVR2B in muscle were protected for weight loss but not survival. Overall our results indicate that PDAC induces a systemic activin response, leading to cachexia, and that activin targets might include organs beyond muscle. Targeting of both tumor-derived and host-derived activins could improve cachexia therapy.

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Immune responses in pancreatic cancer may be restricted by prevalence of activated regulatory T-cells, dysfunctional and senescent T-cells

10.1101/2020.06.20.163071 ◽

2020 ◽

Author(s):

Shivan Sivakumar ◽

Enas Abu-Shah ◽

David J Ahern ◽

Edward H Arbe-Barnes ◽

Nagina Mangal ◽

...

Keyword(s):

Pancreatic Cancer ◽

T Cells ◽

T Cell ◽

Single Cell ◽

Pancreatic Ductal Adenocarcinoma ◽

Regulatory T Cell ◽

Rational Design ◽

Tumour Microenvironment ◽

Human Pancreatic Cancer ◽

Ductal Adenocarcinoma

AbstractObjectivePancreatic cancer has the worst prognosis of any human malignancy and leukocyte infiltration is a major prognostic marker of the disease. As current immunotherapies confer negligible survival benefits, there is a need to better characterise leukocytes in pancreatic cancer to identify better therapeutic strategies.DesignIn this study, a multi-parameter mass-cytometry analysis was performed on 32,000 T-cells from eight human pancreatic cancer patients. Single-cell RNA sequencing dataset analysis was performed on a cohort of 24 patients. Multiplex immunohistochemistry imaging and spatial analysis were performed to map immune infiltration into the tumour microenvironment.ResultsRegulatory T-cell populations demonstrated highly immunosuppressive states with high TIGIT, ICOS and CD39 expression. CD8+ T-cells were found to be either in senescence or an exhausted state. The exhausted CD8 T-cells had low PD-1 expression but high TIGIT and CD39 expression. These findings were corroborated in an independent pancreatic cancer single-cell RNA dataset from 24 patients.ConclusionsThese data suggest that T-cells are major players in the suppressive microenvironment of pancreatic cancer. Our work identifies novel therapeutic targets that should form the basis for rational design of a new generation of clinical trials in pancreatic ductal adenocarcinoma.Statement of SignificanceThis study elucidates the T-cell phenotypes in pancreatic ductal adenocarcinoma (PDAC). T-cells potentiate immune-suppression through an activated regulatory T-cell population expressing high TIGIT, ICOS and CD39. CD8+ T-cells were primarily senescent or TIGIT+ exhausted, but with minimal PD-1 expression. These findings propose new immunotherapy targets for PDAC.

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Usp9x Promotes Survival in Human Pancreatic Cancer and Its Inhibition Suppresses Pancreatic Ductal Adenocarcinoma In Vivo Tumor Growth

Neoplasia ◽

10.1016/j.neo.2017.11.007 ◽

2018 ◽

Vol 20 (2) ◽

pp. 152-164 ◽

Cited By ~ 7

Author(s):

Anupama Pal ◽

Michele Dziubinski ◽

Marina Pasca Di Magliano ◽

Diane M. Simeone ◽

Scott Owens ◽

...

Keyword(s):

Pancreatic Cancer ◽

Tumor Growth ◽

Pancreatic Ductal Adenocarcinoma ◽

Human Pancreatic Cancer ◽

Ductal Adenocarcinoma

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Influence of IP-10/CXCL10 induction in human pancreatic cancer stroma on lymphocytes recruitment and correlation with survival.

Journal of Clinical Oncology ◽

10.1200/jco.2015.33.3_suppl.290 ◽

2015 ◽

Vol 33 (3_suppl) ◽

pp. 290-290 ◽

Cited By ~ 1

Author(s):

Thomas B Brunner ◽

Serena Lunardi ◽

Nigel B Jamieson ◽

Su Yin Lim ◽

Kristin L Griffiths ◽

...

Keyword(s):

Pancreatic Cancer ◽

T Cells ◽

Pancreatic Ductal Adenocarcinoma ◽

Cancer Patients ◽

Mononuclear Cells ◽

Pancreatic Stellate Cells ◽

Human Pancreatic Cancer ◽

Ductal Adenocarcinoma ◽

Pancreatic Tumors ◽

Pancreatic Cancer Cells

290 Background: Pancreatic ductal adenocarcinoma is characterized by an abundant desmoplastic reaction driven by pancreatic stellate cells (PSCs) that contributes to tumor progression. Here we sought to characterize the interactions between pancreatic cancer cells (PCCs) and PSCs that affect the inflammatory and immune response in pancreatic tumors. Methods: Conditioned media from mono- and cocultures of PSCs and PCCs were assayed for expression of cytokines, chemokines and growth factors. Gene expression analysis of human pancreatic ductal adenocarcinoma samples was used to verify expression of cytokines and their correlation with markers of immunoresponse and with clinical outcome. Finally, we tested chemotaxis of leukocytes isolated from peripheral blood mononuclear cells of pancreatic cancer patients. Results: IP-10/CXCL10 was the most highly induced chemokine in coculture of PSCs and PCCs. Its expression was induced in the PSCs by PCCs. IP-10 expression was consistently upregulated in human pancreatic cancer specimens, and positively correlated with high stroma content. Furthermore, expression of IP-10 and its receptor CXCR3 were significantly associated with the intratumoral presence of regulatory T cells (Tregs). In an independent cohort of 48 patients with resectable pancreatic ductal adenocarcinoma, the survival of patients with high IP-10 levels was 18.1 months less than those with low IP-10 levels (HR=2.14, 95% CI 1.05 -4.42). Importantly, IP-10 stimulated the ex vivo recruitment of CXCR3+ effector T cells as well as CXCR3+ Tregs derived from patients with pancreatic cancer. Conclusions: Our findings suggest that, in pancreatic cancer patients, CXCR3+ Tregs are recruited by IP-10 expressed by PSCs in the tumor stroma, leading to immunosuppressive and tumor-promoting effects.

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ITGA2, LAMB3, and LAMC2 may be the potential therapeutic targets in pancreatic ductal adenocarcinoma: an integrated bioinformatics analysis

Scientific Reports ◽

10.1038/s41598-021-90077-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Shajedul Islam ◽

Takao Kitagawa ◽

Byron Baron ◽

Yoshihiro Abiko ◽

Itsuo Chiba ◽

...

Keyword(s):

Gene Expression ◽

Pancreatic Cancer ◽

Pancreatic Ductal Adenocarcinoma ◽

Bioinformatics Analysis ◽

Therapeutic Targets ◽

Ductal Adenocarcinoma ◽

Integrin Subunit ◽

Hub Genes ◽

Cancerous Tissue ◽

Tissue Samples

AbstractPancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer with an abysmal prognosis rate over the last few decades. Early diagnosis and prevention could effectively combat this malignancy. Therefore, it is crucial to discover potential biomarkers to identify asymptomatic premalignant or early malignant tumors of PDAC. Gene expression analysis is a powerful technique to identify candidate biomarkers involved in disease progression. In the present study, five independent gene expression datasets, including 321 PDAC tissues and 208 adjacent non-cancerous tissue samples, were subjected to statistical and bioinformatics analysis. A total of 20 differentially expressed genes (DEGs) were identified in PDAC tissues compared to non-cancerous tissue samples. Gene ontology and pathway enrichment analysis showed that DEGs were mainly enriched in extracellular matrix (ECM), cell adhesion, ECM–receptor interaction, and focal adhesion signaling. The protein–protein interaction network was constructed, and the hub genes were evaluated. Collagen type XII alpha 1 chain (COL12A1), fibronectin 1 (FN1), integrin subunit alpha 2 (ITGA2), laminin subunit beta 3 (LAMB3), laminin subunit gamma 2 (LAMC2), thrombospondin 2 (THBS2), and versican (VCAN) were identified as hub genes. The correlation analysis revealed that identified hub genes were significantly interconnected. Wherein COL12A1, FN1, ITGA2, LAMB3, LAMC2, and THBS2 were significantly associated with PDAC pathological stages. The Kaplan–Meier survival plots revealed that ITGA2, LAMB3, and LAMC2 expression were inversely correlated with a prolonged patient survival period. Furthermore, the Human Protein Atlas database was used to validate the expression and cellular origins of hub genes encoded proteins. The protein expression of hub genes was higher in pancreatic cancer tissue than in normal pancreatic tissue samples, wherein ITGA2, LAMB3, and LAMC2 were exclusively expressed in pancreatic cancer cells. Pancreatic cancer cell-specific expression of these three proteins may play pleiotropic roles in cancer progression. Our results collectively suggest that ITGA2, LAMB3, and LAMC2 could provide deep insights into pancreatic carcinogenesis molecular mechanisms and provide attractive therapeutic targets.

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Identify key genes and pathways in pancreatic ductal adenocarcinoma via bioinformatics analysis

10.21203/rs.3.rs-19826/v1 ◽

2020 ◽

Author(s):

Huatian Luo ◽

Da-qiu Chen ◽

Jing-jing Pan ◽

Zhang-wei Wu ◽

Can Yang ◽

...

Keyword(s):

Gene Expression ◽

Pancreatic Cancer ◽

Pancreatic Ductal Adenocarcinoma ◽

Bioinformatics Analysis ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Gene Expression Omnibus ◽

Ductal Adenocarcinoma ◽

Hub Genes ◽

Expression Levels

Abstract Background: Pancreatic cancer has many pathologic types, among which pancreatic ductal adenocarcinoma (PDAC) is the most common one. Bioinformatics has become a very common tool for the selection of potentially pathogenic genes.Methods: Three data sets containing the gene expression profiles of PDAC were downloaded from the gene expression omnibus (GEO) database. The limma package of R language was utilized to explore the differentially expressed genes (DEGs). To analyze functions and signaling pathways, the Database Visualization and Integrated Discovery (DAVID) was used. To visualize the protein-protein interaction (PPI) of the DEGs ,Cytoscape was performed under the utilization of Search Tool for the Retrieval of Interacting Genes (STRING). With the usage of the plug-in cytoHubba in cytoscape software, the hub genes were found out. To verify the expression levels of hub genes, Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Last but not least, UALCAN analysis online tool was implemented to analyze the overall survival.Results: The 376 DEGs were highly enriched in biological processes including signal transduction, apoptotic process and several pathways, mainly associated with Protein digestion and absorption and Pancreatic secretion pathway. The expression levels of nucleolar and spindle associated protein 1 (NUSAP1) and SHC binding and spindle associated 1 (SHCBP1) were discovered highly expressed in pancreatic ductal adenocarcinoma tissues. NUSAP1 and SHCBP1 had a high correlation with prognosis.Conclusions: The findings of this bioinformatics analysis indicate that NUSAP1 and SHCBP1 may be key factors in the prognosis and treatment of pancreatic cancer.

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An Integrated Meta-Analysis of Secretome and Proteome Identify Potential Biomarkers of Pancreatic Ductal Adenocarcinoma

Cancers ◽

10.3390/cancers12030716 ◽

2020 ◽

Vol 12 (3) ◽

pp. 716

Author(s):

Grasieli de Oliveira ◽

Paula Paccielli Freire ◽

Sarah Santiloni Cury ◽

Diogo de Moraes ◽

Jakeline Santos Oliveira ◽

...

Keyword(s):

Gene Expression ◽

Pancreatic Cancer ◽

Pancreatic Ductal Adenocarcinoma ◽

Prognostic Value ◽

Meta Analysis ◽

The Cancer Genome Atlas ◽

Secreted Proteins ◽

Ductal Adenocarcinoma ◽

Public Data ◽

Potential Biomarkers

Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis, and there are no biomarkers for early detection of the disease or identification of individuals at high risk for morbidity or mortality. The cellular and molecular complexity of PDAC leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. The tumor secretome, a potential source of biomarkers in PDAC, plays a crucial role in cell proliferation and metastasis, as well as in resistance to treatments, which together contribute to a worse clinical outcome. The massive amount of proteomic data from pancreatic cancer that has been generated from previous studies can be integrated and explored to uncover secreted proteins relevant to the diagnosis and prognosis of the disease. The present study aimed to perform an integrated meta-analysis of PDAC proteome and secretome public data to identify potential biomarkers of the disease. Our meta-analysis combined mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we predicted the secreted proteins using seven in silico tools or databases, which identified 39 secreted proteins shared between the secretome and proteome data. Notably, the expression of 31 genes of these secretome-related proteins was upregulated in PDAC samples from The Cancer Genome Atlas (TCGA) when compared to control samples from TCGA and The Genotype-Tissue Expression (GTEx). The prognostic value of these 39 secreted proteins in predicting survival outcome was confirmed using gene expression data from four PDAC datasets (validation set). The gene expression of these secreted proteins was able to distinguish high- and low-survival patients in nine additional tumor types from TCGA, demonstrating that deregulation of these secreted proteins may also contribute to the prognosis in multiple cancers types. Finally, we compared the prognostic value of the identified secreted proteins in PDAC biomarkers studies from the literature. This analysis revealed that our gene signature performed equally well or better than the signatures from these previous studies. In conclusion, our integrated meta-analysis of PDAC proteome and secretome identified 39 secreted proteins as potential biomarkers, and the tumor gene expression profile of these proteins in patients with PDAC is associated with worse overall survival.

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