Prognostic Biomarker For Pancreatic Cancer Research Articles

Pancreatic Cancer Meets Human Microbiota: Close Encounters of the Third Kind.

Simple SummaryThe microorganisms colonizing the epithelial surfaces of the human body, called microbiota, have been shown to influence the initiation, progression and response to therapy of many solid tumors, including pancreatic ductal adenocarcinoma, the most prominent form of pancreatic cancer. Here, we summarize the current knowledge about the influence of oral, gut and intratumoral microbiota on pancreatic ductal adenocarcinoma development and chemoresistance.Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal types of cancer with a dismal prognosis. The five-year survival rate has not changed significantly in over 40 years. Current first-line treatments only offer a modest increase in overall survival in unselected populations, and there is an urgent need to personalize treatment in this aggressive disease and develop new therapeutic strategies. Evolving evidence suggests that the human microbiome impacts cancerogenesis and cancer resistance to therapy. The mechanism of action and interaction of microbiome and PDAC is still under investigation. Direct and indirect effects have been proposed, and the use of several microbiome signatures as predictive and prognostic biomarkers for pancreatic cancer are opening new therapeutic horizons. In this review, we provide an overview for the clinicians of studies describing the influence and associations of oral, gastrointestinal and intratumoral microbiota on PDAC development, progression and resistance to therapy and the potential use of microbiota as a diagnostic, prognostic and predictive biomarker for PDAC.

Exosomes as Pleiotropic Players in Pancreatic Cancer.

Pancreatic cancer (PC) incidence is rising and due to late diagnosis, combined with unsatisfactory response to current therapeutic approaches, this tumor has an extremely high mortality rate. A better understanding of the mechanisms underlying pancreatic carcinogenesis is of paramount importance for rational diagnostic and therapeutic approaches. Multiple lines of evidence have showed that exosomes are actively involved in intercellular communication by transferring their cargos of bioactive molecules to recipient cells within the tumor microenvironment and systemically. Intriguingly, exosomes may exert both protumor and antitumor effects, supporting or hampering processes that play a role in the pathogenesis and progression of PC, including shifts in tumor metabolism, proliferation, invasion, metastasis, and chemoresistance. They also have a dual role in PC immunomodulation, exerting immunosuppressive or immune enhancement effects through several mechanisms. PC-derived exosomes also induce systemic metabolic alterations, leading to the onset of diabetes and weight loss. Moreover, exosomes have been described as promising diagnostic and prognostic biomarkers for PC. Their potential application in PC therapy as drug carriers and therapeutic targets is under investigation. In this review, we provide an overview of the multiple roles played by exosomes in PC biology through their specific cargo biomolecules and of their potential exploitation in early diagnosis and treatment of PC.

CCL26 is upregulated by nab-paclitaxel in pancreatic cancer–associated fibroblasts and promotes PDAC invasiveness through activation of the PI3K/AKT/mTOR pathway

Recently, the combined use of FOLFIRINOX (leucovorin and fluorouracil plus irinotecan and oxaliplatin) and gemcitabine plus nab-paclitaxel has significantly improved the prognosis of patients with pancreatic cancer. However, there is still a high proportion of patients who develop metastatic pancreatic cancer in the course of chemotherapy or within a short period after chemotherapy. Previous reports have shown that chemotherapy-driven cytokine storms or the direct effects of certain chemotherapeutics on stromal and/or immune cells collectively change the microenvironment of the primary tumor, thus indirectly promoting metastasis. However, the mechanism underlying chemotherapy-induced metastasis in the course of chemotherapy, and afterwards, remains elusive in pancreatic cancer. In the present study, we aimed to determine the expression of CCL26 in the pancreatic cancer-associated fibroblasts (CAFs) after nab-paclitaxel treatment and to explore the role of CCL26 in the pancreatic adenocarcinoma (PDAC) invasion. Our results showed that nab-paclitaxel increased CCL26 mRNA and protein expression levels in a dose- and time-dependent manner. Subsequently, PDAC cell lines were treated with recombinant CCL26 for 48 h. The transwell migration assay showed that recombinant CCL26 enhanced the invasion of PDAC cells. Western blot analysis showed that the protein expression levels of phospho-(p-)PI3K, p-AKT, and p-mTOR were increased by CCL26 in PDAC cells. CCL26 expressions in 95 PDAC tissues and adjacent normal tissues were evaluated using reverse transcription-quantitative polymerase chain reaction and immunohistochemistry. CCL26 was found to be overexpressed in PDAC samples, and upregulated CCL26 expression was significantly associated with advanced perineural invasion, lymph node metastasis, and poor differentiation. In summary, our results showed that nab-paclitaxel increased the expression of CCL26 in CAFs, and CCL26 enhanced the invasive potential of pancreatic cancer cells by activating the PI3K/AKT/mTOR axis. Thus, CCL26 may be a potential prognostic biomarker for pancreatic cancer.

In silico investigation and functional enrichment analysis of the human major intrinsic proteins and voltage-gated chloride channel proteins reveal eleven prognostic biomarkers for pancreatic cancer

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is associated with poor prognosis. In this context, the identification of biomarkers regarding the PDAC diagnosis, monitoring, and prognosis is crucial. The purpose of the present study was to investigate the differential gene expression profile of the major intrinsic proteins and chloride channel proteins in patients with PDAC, in order to suggest novel biomarkers.

Interferon alpha-inducible protein 27 (IFI27) is a prognostic marker for pancreatic cancer based on comprehensive bioinformatics analysis

ABSTRACT Accurate biomarkers to predict the genesis and progression of pancreatic adenocarcinoma (PAAD) are needed in the fight against this deadly disease. Here, we combined multiple datasets (GEO, TCGA and GTEx) to conduct a comprehensive analysis of pancreatic cancer. Through an in-depth analysis, we discovered that the expression of the gene encoding interferon alpha-inducible protein 27 (IFI27) was significantly higher in pancreatic cancer tissues than that in normal tissues, and that higher expression of IFI27 was negatively correlated with the overall survival rate of pancreatic cancer patients. The functional annotation of IFI27 demonstrated relationships to cellular immunity and metabolism, especially glycolysis. Analysis of infiltrating immune cells displayed that higher expression of IFI27 expression correlates with decreased CD8 + T cells and increased M2 macrophages in the tumor immune microenvironment (TIME), then biochemical analyses of a mouse model and immunohistochemical (IHC) staining verified that glycolytic enzymes and M2 macrophages increased significantly in pancreatic cancer tissues. We speculate that IFI27 may affect the tumor microenvironment (TME) of PAAD by regulating cellular immunity and metabolism, thereby promoting the progression of pancreatic carcinoma and worsening the prognosis. These findings of our present study are solid evidence that IFI27 is a potential prognostic biomarker of pancreatic cancer and that it affects the tumor immune microenvironment.

Downregulation of GSTM2 enhances gemcitabine chemosensitivity of pancreatic cancer in vitro and in vivo

Glutathione-S-transferases (GSTs) not only show cytoprotective role and their involvement in the development of anticancer drug resistance, but also transmit signals that control cell proliferation and apoptosis. However, the role of GST isoforms in chemotherapy resistance remains elusive in pancreatic cancer. Here, we demonstrated that gemcitabine treatment increased the GSTM2 expression in pancreatic cancer cell lines. Knockdown of GSTM2 by siRNA elevated apoptosis and decreased viability of pancreatic cancer cells treated with gemcitabine. Moreover, in vivo experiments further showed that shRNA induced GSTM2 downregulation enhanced drug sensitivity of gemcitabine in orthotopic pancreatic tumor mice. We also found that GSTM2 levels were lower in tumor tissues than in non-tumor tissues and higher GSTM2 expression was significantly associated with longer overall survival. In conclusion, our findings indicate that GSTM2 expression is essential for the survival of pancreatic cancer cells undergoing gemcitabine treatment and leads to chemo resistance. Downregulation of GSTM2 in pancreatic cancer may benefit gemcitabine treatment. GSTM2 expression in patients also shows significant correlation with overall survival. Thus, our study suggests that GSTM2 is a potential target for chemotherapy optimization and prognostic biomarker of pancreatic cancer.

Identification of Immune-Related Prognostic Biomarkers in Pancreatic Cancer

Immunotherapy for pancreatic cancer (PC) faces significant challenges. It is urgent to find immunerelated genes for targeted therapy. We aimed to identify immune-related messenger ribonucleic acids (mRNAs) with multiple methods of comprehensive immunoenrichment analysis in predicting survival of PC. PC genomics and clinical data were downloaded from TCGA. We analyzed relative enrichment of 29 immune cells using ssGSEA and classified PC samples into three immuneinfiltrating subgroups. Immune cell infiltration level and pathways were evaluated by ESTIMATE data and KEGG. Independent risk factors were derived from the combined analysis of WGCNA, LASSO regression and Cox regression analyses. Immune risk score was calculated according to four mRNAs to identify its value in predicting survival. PPI analysis was used to analyze the connections and potential pathways among genes. Finally, PC samples were classified into three immuneinfiltrating subgroups. Immunity high subgroup had higher immune score, soakage of immune cells, HLA/PD-L1 expression level, immune-related pathways enrichment and better survivability. Four potential prognostic immune-related genes (ITGB7, RAC2, DNASE1L3, and TRAF1) were identified. Immune risk score could be a potential survival prediction indictor with high sensitivity and specificity (AUC values = 0.708, HR = 1.445). A PPI network with seven nodes and five potential targeted pathways were generated. In conclusion, we estimated the state of immune infiltration in the PC tumor microenvironment by calculating stromal and immune cells enrichment with ssGSEA algorithms, and identified four prognostic immune-related genes that affect the proportion and distribution of immune cells infiltration in the tumor microenvironment. They lay a theoretical foundation to be important immunity targets of individual treatment in PC.

Expression Profile of GINS Complex Predicts the Prognosis of Pancreatic Cancer Patients.

BackgroundThe GINS complex has been implicated in the prognosis of various cancers. It comprises four subunits, encoded by GINS1, GINS2, GINS3, and GINS4 genes. Based on the current understanding, no report exists on the role of the GINS complex in pancreatic cancer.MethodsWe employed various bioinformatics databases including GEPIA, UALCAN, GEPIA2, and Kaplan Meier Plotter to identify the expression profile of the four genes (GINS1, GINS2, GINS3, and GINS4), their correlation with pancreatic cancer grade as well as their prognostic value of in pancreatic cancer. Western blotting and qRT-PCR analyses were conducted to verify the expression profiles of the four genes in pancreatic cancer. CCK8 and EdU cell experiments were conducted to reveal the role played by the four genes in pancreatic cancer cell proliferation.ResultsBased on GEPIA, Western blotting, and qRT-PCR analyses, all the four genes in the GINS complex were overexpressed in pancreatic cancer. Notably, the expression of each member was significantly associated with pancreatic cancer grade. The prognostic analysis revealed that not only the whole GINS complex but also each individual were prognostic biomarkers for pancreatic cancer. CCK8 and EdU experiments demonstrated that inhibition of the expression of each GINS member lowered pancreatic cancer cell proliferation.ConclusionThis work implicated GINS1, GINS2, GINS3, and GINS4 genes as critical prognostic markers for pancreatic cancer.

Comprehensive Analysis of Immunoinhibitors Identifies LGALS9 and TGFBR1 as Potential Prognostic Biomarkers for Pancreatic Cancer.

Pancreatic cancer (PC) is one of the most deadly cancers worldwide. To uncover the unknown novel biomarker used to indicate early diagnosis and prognosis in the molecular therapeutic field of PC is extremely of importance. Accumulative evidences indicated that aberrant expression or activation of immunoinhibitors is a common phenomenon in malignances, and significant associations have been noted between immunoinhibitors and tumorigenesis or progression in a wide range of cancers. However, the expression patterns and exact roles of immunoinhibitors contributing to tumorigenesis and progression of pancreatic cancer (PC) have not yet been elucidated clearly. In this study, we investigated the distinct expression and prognostic value of immunoinhibitors in patients with PC by analyzing a series of databases, including TISIDB, GEPIA, cBioPortal, and Kaplan-Meier plotter database. The mRNA expression levels of IDO1, CSF1R, VTCN1, KDR, LGALS9, TGFBR1, TGFB1, IL10RB, and PVRL2 were found to be significantly upregulated in patients with PC. Aberrant expression of TGFBR1, VTCN1, and LGALS9 was found to be associated with the worse outcomes of patients with PC. Bioinformatics analysis demonstrated that LGALS9 was involved in regulating the type I interferon signaling pathway, interferon-gamma-mediated signaling pathway, RIG-I-like receptor signaling pathway, NF-kappa B signaling pathway, cytosolic DNA-sensing pathway, and TNF signaling pathway. And TGFB1 was related to mesoderm formation, cell matrix adhesion, TGF-beta signaling pathway, and Hippo signaling pathway. These results suggested that LGALS9 and TGFBR1 might serve as potential prognostic biomarkers and targets for PC.

PD-L1 Expression Level Displays a Positive Correlation with Immune Response in Pancreatic Cancer.

The expression of PD-L1 could be a novel biomarker which predicts that patients are more likely to respond to immunotherapy. Our study investigated the relationship among clinicopathological characteristics, prognosis, PD-L1 expression levels, and FOXP3+ Treg infiltration. In addition, the relationship among clinicopathological characteristics, prognosis, PD-L1 expression levels, and FOXP3+ Treg infiltration was explored. Furthermore, the relationship between PD-L1 expression and FOXP3+ Treg infiltration was examined. We found that 41.3% of pancreatic cancer patients had PD-L1-positive staining; both PD-L1 expression levels and FOXP3+ Treg infiltration were significantly associated with depth of invasion, lymph node metastasis, distant metastasis, and pTNM. In addition, PD-L1 expression and FOXP3+ Treg infiltration also could be prognostic biomarkers for pancreatic cancer.

Prognostic Significance of Tumor-infiltrating Lymphocytes on Survival Outcomes of Patients With Resected Pancreatic Ductal Adenocarcinoma: A Systematic Review and Meta-Analysis.

Tumor-infiltrating lymphocytes (TILs) play an important role in mediating treatment response in pancreatic cancer. This meta-analysis investigated the prognostic significance of TIL subsets on overall survival (OS) and disease-free survival (DFS) of patients with pancreatic cancer. Studies were gathered via search of PubMed, Google Scholar, and Cochrane Library databases up to August 1, 2019. Using Review Manager version 5.3.5, pooled hazard ratios and 95% confidence intervals (CIs) were calculated using random or fixed-effects models, depending on the heterogeneity of studies. A total of 11 studies comprising 1760 patients were included in the meta-analysis. Pooled analysis revealed that high CD8 TILs were associated with improved OS [hazard ratio (HR)=0.59, 95% CI=0.51-0.69, P<0.00001] and DFS (HR=0.60, 95% CI=0.50-0.73, P<0.00001). Similarly, high CD3 TILs correlated with better OS (HR=0.64, 95% CI=0.54-0.75, P<0.00001) and DFS (HR=0.53, 95% CI=0.31-0.92, P<0.0001). In contrast, high FoxP3 TILs were associated with worse OS (HR=1.39, 95% CI=1.03-1.88, P=0.03). Finally, high CD4 TILs showed significant improvement in OS (HR=0.74, 95% CI=0.63-0.86, P=0.0001). TILs are a promising prognostic biomarker in pancreatic cancer. Prospective studies evaluating TILs are recommended as well as the establishment of standards in the assessment of TILs.

A Prognostic Prediction Model Developed Based on Four CpG Sites and Weighted Correlation Network Analysis Identified DNAJB1 as a Novel Biomarker for Pancreatic Cancer.

BackgroundThe prognosis of pancreatic cancer, which is among the solid tumors associated with high mortality, is poor. There is a need to improve the overall survival rate of patients with pancreatic cancer.Materials and MethodsThe Cancer Genome Atlas (TCGA) dataset with 153 samples and the International Cancer Genome Consortium (ICGC) dataset with 235 samples were used as the discovery and validation cohorts, respectively. The least absolute shrinkage and selection operator regression was used to construct the prognostic prediction model based on the DNA methylation markers. The predictive efficiency of the model was evaluated based on the calibration curve, concordance index, receiver operating characteristic curve, area under the curve, and decision curve. The xenograft model and cellular functional experiments were used to investigate the potential role of DNAJB1 in pancreatic cancer.ResultsA prognostic prediction model based on four CpG sites (cg00609645, cg13512069, cg23811464, and cg03502002) was developed using TCGA dataset. The model effectively predicted the overall survival rate of patients with pancreatic cancer, which was verified in the ICGC dataset. Next, a nomogram model based on the independent prognostic factors was constructed to predict the overall survival rate of patients with pancreatic cancer. The nomogram model had a higher predictive value than TCGA or ICGC datasets. The low-risk group with improved prognosis exhibited less mutational frequency and high immune infiltration. The brown module with 247 genes derived from the WGCNA analysis was significantly correlated with the prognostic prediction model, tumor grade, clinical stage, and T stage. The bioinformatic analysis indicated that DNAJB1 can serve as a novel biomarker for pancreatic cancer. DNAJB1 knockdown significantly inhibited the proliferation, migration, and invasion of pancreatic cancer cells in vivo and in vitro.ConclusionThe prognostic prediction model based on four CpG sites is a new method for predicting the prognosis of patients with pancreatic cancer. The molecular characteristic analyses, including Gene Ontology, Gene Set Enrichment Analysis, mutation spectrum, and immune infiltration of the subgroups, stratified by the model provided novel insights into the initiation and development of pancreatic cancer. DNAJB1 may serve as diagnostic and prognostic biomarkers for pancreatic cancer.

MicroRNA-1469-5p promotes the invasion and proliferation of pancreatic cancer cells via direct regulating the NDRG1/NF-κB/E-cadherin axis.

Numerous studies demonstrated that microRNAs (miRNAs) were highly involved in pancreatic cancer development. However, the functional roles of many miRNAs remain elusive in pancreatic cancer. In the present study, we analyzed previous published microarray data and found that miR-1469-5p was one of top upregulated miRNAs in pancreatic tumors. Our further study showed that miR-1469-5p was highly expressed in collected pancreatic tumors and its upregulation was associated with lymph node metastasis and tumors of advanced TNM stage. Functional analysis with miR-1469-5p inhibitor showed that downregulation of miR-1469-5p repressed pancreatic cancer cell proliferation and invasion. Mechanistically, miR-1469-5p directly interacted with metastasis suppressor NDRG1 mRNA and downregulated expression of NDRG1 to activate NF-κB pathway in pancreatic cancer cells. It was also found that miR-1469-5p decreased expression of E-cadherin, a metastasis related gene repressed by NF-κB pathway, in pancreatic cancer cells. Transfection of NDRG1 small interference RNA (siRNA) attenuated the function of miR-1469-5p inhibitor in pancreatic cancer cells. Moreover, miR-1469-5p expression was negatively associated with NDRG1 and E-cadherin mRNA levels in pancreatic tumors. Taken together, miR-1469-5p may exert its oncogenic potential in pancreatic cancer via regulating a NDRG1/NF-κB/E-cadherin axis, suggesting that it may be clinically valuable as a prognostic biomarker of pancreatic cancer.

P-24 Neutrophil and lymphocyte ratio as a prognostic biomarker in pancreatic cancer

The prognosis of locally advanced or metastatic pancreatic cancer (LAMPC) is dismal. There is a need for rapid intervention given its quick progression and ability to metastasize. Since there are limited resources in the public health system, it is imperative to find a biomarker that could assess and identify patients with worse outcomes and provide a means for early intervention. Understanding the role between neutrophil and lymphocytes (N/L) and worse outcomes in LAMPC patients will allow for earlier intervention and minimize costs in a collapsing public health system.

Cytokines as a prognostic biomarker of overall survival in pancreatic cancer.

e16753 Background: Pancreatic cancer is an aggressive malignancy with a dismal 5-year survival rate of only 9%. Novel biomarkers are urgently needed to improve the survival outcomes of patients with this dreaded disease. Cytokines serve a key role in tumor development and metastasis in pancreatic cancer, with each cytokine demonstrating unique functionality in the tumor microenvironment. This meta-analysis examined the role of cytokines in prognosticating overall survival (OS) of pancreatic cancer patients. Methods: Relevant literature were identified via electronic search of PubMed, EMBASE, Google Scholar and Cochrane Library databases up to January 1, 2020. Employing Review Manager 5.3, pooled hazard ratios and 95% confidence intervals were computed. Results: A total of 18 studies comprising 1920 patients were included. Pooled analysis showed worse OS among patients with high T-helper 1 (Th1) cytokines, with a hazard ratio of 1.48 (95% CI 1.27-1.74, p &lt; 0.00001). High T-helper 2 (Th2) cytokines also demonstrated significant association with poor OS, with a hazard ratio of 1.62 (95% CI 1.12–2.34, p = 0.01). In terms of individual cytokines, high IL-6 correlated with inferior OS, with a hazard ratio of 2.73 (95% CI 2.18-3.43, p &lt; 0.00001). Similarly, high IL-12 were linked with worse OS, with a hazard ratio of 1.85 (95% CI 1.26-2.72, p = 0.002). Other individual cytokines were not significantly associated with OS. Conclusions: Cytokines show promise as a prognostic biomarker in pancreatic cancer. Th1 and Th2 cytokines portend worse overall survival outcomes. In particular, high levels of IL-6 and IL-12 can potentially prognosticate patients with poor overall survival. Further prospective studies are encouraged to delineate the role of cytokines in mediating treatment outcomes in this deadly disease.

The miR-1224-5p/ELF3 Axis Regulates Malignant Behaviors of Pancreatic Cancer via PI3K/AKT/Notch Signaling Pathways.

PurposeAberrant expression of microRNAs contributes to the progression of pancreatic cancer by targeting downstream genes. A novel regulatory axis, miR-1224-5p/ELF3, was identified by bioinformatic analysis and experimental verification. Studies of the underlying molecular mechanisms behind this axis lead to a better understanding of the development of pancreatic cancer.Materials and MethodsThe differential expression of miR-1224-5p and ELF3 was verified based on Gene Expression Omnibus (GEO) datasets and clinical samples. The relationship between miR-1224-5p and ELF3 was demonstrated by luciferase assay and Western blot. The related signaling pathways of the miR-1224-5p/ELF3 axis in pancreatic cancer were investigated by gene set enrichment analysis (GSEA) and verified by Western blot. An analysis between ELF3 expression and immune infiltration was performed. Cellular and animal experiments were utilized to explore the effects of miR-1224-5p and ELF3 in pancreatic cancer.ResultsSuppressed expression of miR-1224-5p in pancreatic tumor tissues and cancer cells was identified first. Furthermore, miR-1224-5p is correlated with clinicopathological features, and decreased expression of miR-1224-5p indicates poor prognosis. miR-1224-5p serves as a tumor suppressor and inhibits malignant behaviors of pancreatic cancer based on in vivo and in vitro assays. The putative target gene ELF3 was predicted by bioinformatic analysis and confirmed by dual-luciferase reporter assay. Overexpression of ELF3 can improve the malignant behaviors of pancreatic cancer and demonstrates poor prognosis and advanced clinical stage. The inhibitory role of miR-1224-5p in pancreatic cancer is manifested by its direct targeting of ELF3. A negative correlation between ELF3 expression and immune cell infiltration was identified, suggesting an immunosuppressive state resulting from ELF3 overexpression. The PI3K/AKT/Notch signaling pathways and epithelial-to-mesenchymal transition (EMT) are important underlying mechanisms.ConclusionThe miR-1224-5p/ELF3 axis may serve as a new diagnostic, therapeutic, and prognostic biomarker in pancreatic cancer. The related PI3K/AKT/Notch/EMT signaling pathways greatly promote the elucidation of the progression of pancreatic cancer.

Circulating tumor DNA as specific biomarkers for early diagnosis and prognosis of pancreatic cancer

Pancreatic adenocarcinoma is considered one of the most aggressive cancers with high mortality and low 5-year survival rate. This is mainly due to its late detection. Complex anatomical location creates certain difficulties for imaging and puncture biopsy methods, while standard tumor markers do not have high sensitivity and specificity. Thus, the search for specific biomarkers for early diagnosis and prognosis of the disease, as well as monitoring patients with pancreatic cancer during treatment, is a priority to improve patient survival in this terminal disease. Liquid biopsy, which has recently gained a lot of attention including the study of free-circulating tumor DNA (ctDNA) in plasma or serum, is a promising additional method of research. In this review, we will consider the latest findings from the ctDNA study as early and prognostic biomarkers for pancreatic cancer and monitoring the disease during treatment.

YAP1 is an independent prognostic marker in pancreatic cancer and associated with extracellular matrix remodeling

BackgroundPancreatic cancer is a major cause of cancer-related mortality. The identification of effective biomarkers is essential in order to improve management of the disease. Yes-associated protein 1 (YAP1) is a downstream effector of the Hippo pathway, a signal transduction system implicated in tissue repair and regeneration, as well as tumorigenesis. Here we evaluate the biomarker potential of YAP1 in pancreatic cancer tissue.MethodsYAP1 was selected as a possible biomarker for pancreatic cancer from global protein sequencing of fresh frozen pancreatic cancer tissue samples and normal pancreas controls. The prognostic utility of YAP1 was evaluated using mRNA expression data from 176 pancreatic cancer patients in The Cancer Genome Atlas (TCGA), as well as protein expression data from immunohistochemistry analysis of a local tissue microarray (TMA) cohort comprising 140 pancreatic cancer patients. Ingenuity Pathway Analysis was applied to outline the interaction network for YAP1 in connection to the pancreatic tumor microenvironment. The expression of YAP1 target gene products was evaluated after treatment of the pancreatic cancer cell line Panc-1 with three substances interrupting YAP–TEAD interaction, including Super-TDU, Verteporfin and CA3.ResultsMass spectrometry based proteomics showed that YAP1 is the top upregulated protein in pancreatic cancer tissue when compared to normal controls (log2 fold change 6.4; p = 5E−06). Prognostic analysis of YAP1 demonstrated a significant correlation between mRNA expression level data and reduced overall survival (p = 0.001). In addition, TMA and immunohistochemistry analysis suggested that YAP1 protein expression is an independent predictor of poor overall survival [hazard ratio (HR) 1.870, 95% confidence interval (CI) 1.224–2.855, p = 0.004], as well as reduced disease-free survival (HR 1.950, 95% CI 1.299–2.927, p = 0.001). Bioinformatic analyses coupled with in vitro assays indicated that YAP1 is involved in the transcriptional control of target genes, associated with extracellular matrix remodeling, which could be modified by selected substances disrupting the YAP1-TEAD interaction.ConclusionsOur findings indicate that YAP1 is an important prognostic biomarker for pancreatic cancer and may play a regulatory role in the remodeling of the extracellular matrix.

An Integrated Microarray Analysis Reveals Significant Diagnostic and Prognostic Biomarkers in Pancreatic Cancer

BackgroundPancreatic cancer (PAC) is a lethal cancer and it is essential to develop accurate diagnostic and prognostic biomarkers for PAC.Material/MethodsAn integrated microarray analysis of PAC was conducted to identify differentially expressed genes (DEGs) between PAC and non-tumor controls. Expression of DEGs were further confirmed by The Cancer Genome Atlas and the Genotype-Tissue Expression. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and protein–protein integration network construction were performed to further research the biological functions of DEGs. Receiver-operating characteristic analysis and survival analysis were used to evaluate the diagnostic and prognostic value of DEGs for PAC.ResultsSeventeen microarray datasets were downloaded from Gene Expression Omnibus to conduct the integrated microarray analysis. A total of 1136 DEGs (596 upregulated and 540 downregulated DEGs) in PAC tissues compared with non-tumor controls were identified. Pancreatic secretion (Kegg: 04972), insulin signaling pathway (Kegg: 04910), and several cancer-related pathways including pathways in cancer (Kegg: 05200), MAPK signaling pathway (Kegg: 04010), and pancreatic cancer (Kegg: 05212) were enriched for DEGs in PAC. Seven DEGs (AHNAK2, CDH3, IFI27, ITGA2, LAMB3, SLC6A14, and TMPRSS4) were found to have both great diagnostic and prognostic value for PAC. High expression of these 7 DEGs were significantly associated with poor prognosis of patients with PAC.ConclusionsThese 7 DEGs might be potential diagnostic and prognostic biomarkers for PAC and help uncovering the mechanism of PAC.

The potential role of heat shock protein 27 as a prognostic marker in pancreatic ductal adenocarcinoma

Background: At present no realiable prognostic biomarkers for pancreatic cancer exist. A role of heat shock protein 27 as a potential biomarker is controversial discussed. Heat shock protein 27 occurs as non-phosphorylated (HSP27) and phosphorylated forms (pHSP27) and studies considering all of these forms are lacking. Our study evaluates the significance of non-phosphorylated and phosphorylated forms regarding Serin-site 15, 78 and 82 as a prognostic marker in the biggest patients group by now. Material/Methods: Immunohistochemistry and immunofluorescence was used to determine the expression of HSP27 and pHSP27. We investigated 94 patients with pancreatic ductal adenocarcinoma who went trough surgery at Hospital Barmbek. Furthermore, we evaluated the expression in liver metastasis (n=20) of metastatic patients. Staining was performed using paraffin-embedded tissue with following antibodies: anti-HSP27, anti-pHSP-Ser15, anti-pHSP-Ser78 and anti-pHSP-Ser82. We established a three-graded-system from 0 (no staining) to +2 (maximum staining) for evaluation. All procedures were approved by the local Ethics Committee in Hamburg, Germany. Results: Total expression of HSP27, pHSP27-Ser15, pHSP27-Ser78 or pHSP27-Ser82 was not significantly associated with overall survival (p=0,76 / 0,594 / 0,685 / 0,71). However, we investigated a significant lower HSP27 and pHSP27-Ser82 expression in metastatic patients than in non-metastatic patients (p=0,001 / 0,018). In addition, we found specific patterns regarding the phosphorylated forms of HSP27 with a significant higher expression of pHSP-Ser82 compared to pHSP-Ser15 and –Ser78 (p=5,4×10-11). Same specific patterns exist in liver metastasis (p=0,001). Conclusion: In view of our study, non-phosphorylated HSP27 and all phosphorylated forms of HSP27 cannot serve as a prognostic marker. Interestingly, our Results show a significant lower HSP27 and pHSP-Ser82 expression in patients with presence of metastasis indicating that HSP27 plays a major role in metastatic invasion. The role should be investigated in further studies to elucidate the significance of HSP27 in formation of metastasis.