Prognostic Value In Pancreatic Cancer Research Articles

Aberrant expression of CKS2 induced by ELK1 contributes to malignant progression of pancreatic cancer.

Cyclin-dependent kinase subunit 2 (CKS2) has been reported to promote various malignancies. This study investigated the functional role of CKS2 in pancreatic cancer (PC). An analysis of abnormally expressed genes and their prognostic value for PC was performed by using the Gene Expression Profiling Interactive Analysis (GEPIA) database and performing immunohistochemical staining on 64 samples of tumor tissue. CCK-8 assays, EdU staining, colony formation assays, flow cytometry, and a xenograft tumor model were used to analyze the biological function of CKS2 in PC. Our results revealed that CKS2 was expressed at significantly higher levels in PC tissues than in adjacent normal tissues, and a high level of CKS2 expression was associated with a poor prognosis for patients with PC. Moreover, functional assays revealed that CKS2 knockdown suppressed cell proliferation, induced cell cycle S phase, G2/M phase arrest, and apoptosis in vitro, and also reduced tumor growth in vivo. In addition, CKS2 knockdown increased the levels of Bax, caspase-3, P53, P21, and GADD45α expression, but decreased Bcl-2, Cyclin B1, CDK1, Cyclin A, and Cdc25C expression. CKS2 overexpression produced the opposite effects of CKS2 knockdown. Furthermore, we found that ELK1 protein regulated transcription of the CKS2 gene. In conclusion, our findings suggest that CKS2 expression is regulated by ELK1, which could possibly serve as prognostic indicator and therapeutic target for PC.

Aquaporins Transcripts with Potential Prognostic Value in Pancreatic Cancer.

Pancreatic cancer is anticipated to be the second leading cause of cancer-related death by 2030. Aquaporins (AQPs), a family of water channel proteins, have been linked to carcinogenesis. The aim of this study was to determine AQP gene expression in pancreatic cancer tissues and to validate aquaporins as possible diagnosis and/or prognosis genes. The relative gene expression levels of AQP1, AQP3, AQP5, and AQP9 were analyzed using real-time quantitative PCR (RT-qPCR) in 24 paired pancreatic tumors and adjacent healthy tissues according to variables such as age, gender, and tumor invasiveness and aggressiveness. AQPs transcripts were detected in both healthy and tumor tissues. While AQP1 was downregulated in the tumor samples, AQP3 was particularly overexpressed in low-grade invasive tumors. Interestingly, most of the strong positive Pearson correlation coefficients found between AQPs in healthy tissues were lost when analyzing the tumor tissues, suggesting disruption of the coordinated AQP-gene expression in pancreatic cancer.

Bioinformatic analysis of FOXN3 expression and prognostic value in pancreatic cancer.

In most cancers, forkhead box N3 (FOXN3) acts as a transcriptional inhibitor to suppress tumor proliferation, but in pancreatic cancer, the opposite effect is observed. To confirm and investigate this phenomenon, FOXN3 expression in various carcinomas was determined using GEPIA2 and was found to be highly expressed in pancreatic cancer. Kaplan-Meier plotter was then used for survival analysis, revealing that high FOXN3 expression in pancreatic cancer might be associated with a poor prognosis. Similarly, clinical samples collected for immunohistochemical staining and survival analysis showed consistent results. The RNA-seq data of pancreatic cancer patients from the TCGA were then downloaded, and the differential expression gene set was obtained using R for gene set enrichment analysis (GSEA). The intersection of the above gene sets and FOXN3-related genes was defined as related differentially expressed gene sets (DEGs), and enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, we analyzed the relationship between FOXN3 and immune infiltration in pancreatic cancer. Collectively, our findings reveal that FOXN3 is involved in the occurrence and progression of pancreatic cancer and may be useful as a prognostic tool in pancreatic cancer immunotherapy.

GABRP is a potential prognostic biomarker and correlated with immune infiltration and tumor microenvironment in pancreatic cancer.

BackgroundPancreatic cancer is one of the most commonly diagnosed and lethal malignancies worldwide and has few good biomarkers and therapeutic targets. GABRP is the π subunit of the gamma-aminobutyric acid (GABA) A receptor, which is expressed in a number of non-neuronal tissues. GABRP is significantly upregulated in pancreatic cancer, but its biological and immunological role as well as its clinical diagnostic and prognostic value in pancreatic cancer is still incompletely known.MethodsIn this study, pancreatic adenocarcinoma (PAAD) cohorts from TCGA and GEO datasets were used to compare GABRP mRNA levels in cancerous and normal tissues and protein expression was evaluated using immunohistochemistry. The Kaplan-Meier plotter and GEPIA2 database were used to analyze the correlation between GABRP expression, overall survival, and disease-free survival in pancreatic cancer patients. Gene set enrichment analysis (GSEA) was performed with the Linked Omics database to explore the molecular mechanisms of GABRP in pancreatic cancer. And the correlation between GABRP expression and immune infiltration was explored using the TIMER database, CIBERSORT database and ESTIMATE algorithm.ResultsGABRP mRNA was significantly overexpressed in TCGA-PAAD cohorts (P<0.0001) and enhanced GABRP expression predicted poorer overall survival according to Kaplan-Meier plotter database (P=0.0024) and GEPIA2 (P=0.038). Hypomethylation of promoter (P<0.01) and the regulation of hsa-miR-3655 may contribute to the overexpression of GABRP in pancreatic cancer. GSEA analysis revealed that GABRP played an important role in the immune response. GABRP expression was also correlated with immune infiltration and immune cell markers. Higher GABRP expression was significantly associated with greater infiltration of immune cells and stromal cells into pancreatic cancer microenvironments as well as higher expression of six important immune check point genes including PDCD1 (P<0.05), CD274 (P<0.05), CTLA4 (P<0.01), PDCD1LG2 (P<0.01), TIGHT (P<0.01) and TIM3 (P<0.01).ConclusionsGABRP is a potential prognostic biomarker and is correlated with immune infiltration and tumor microenvironment in pancreatic cancer. This suggests that GABRP may serve as a potential prognostic biomarker and therapeutic target in pancreatic cancer as well as a possible regulator of tumor microenvironment affecting the efficacy of immunotherapy. Further studies are needed to elucidate the molecular mechanism of the immunoregulatory role of GABRP.

Prognostication of Pancreatic Cancer Using The Cancer Genome Atlas Based Ferroptosis-Related Long Non-Coding RNAs.

Background: Long non-coding RNAs (lncRNAs) are key regulators of pancreatic cancer development and are involved in ferroptosis regulation. LncRNA transcript levels serve as a prognostic factor for pancreatic cancer. Therefore, identifying ferroptosis-related lncRNAs (FRLs) with prognostic value in pancreatic cancer is critical. Methods: In this study, FRLs were identified by combining The Cancer Genome Atlas (TCGA) and FerrDb databases. For training cohort, univariate Cox, Lasso, and multivariate Cox regression analyses were applied to identify prognosis FRLs and then construct a prognostic FRLs signature. Testing cohort and entire cohort were applied to validate the prognostic signature. Moreover, the nomogram was performed to predict prognosis at different clinicopathological stages and risk scores. A co-expression network with 76 lncRNA-mRNA targets was constructed. Results: Univariate Cox analysis was performed to analyze the prognostic value of 193 lncRNAs. Furthermore, the least absolute shrinkage and selection operator and the multivariate Cox analysis were used to assess the prognostic value of these ferroptosis-related lncRNAs. A prognostic risk model, of six lncRNAs, including LINC01705, AC068620.2, TRAF3IP2-AS1, AC092171.2, AC099850.3, and MIR193BHG was constructed. The Kaplan Meier (KM) and time-related receiver operating characteristic (ROC) curve analysis were performed to calculate overall survival and compare high- and low-risk groups. There was also a significant difference in survival time between the high-risk and low-risk groups for the testing cohort and the entire cohort, with AUCs of .723, .753, respectively. Combined with clinicopathological characteristics, the risk model was validated as a new independent prognostic factor for pancreatic adenocarcinoma through univariate and multivariate Cox regression. Moreover, a nomogram showed good prediction. Conclusion: The signature of six FRLs had significant prognostic value for pancreatic adenocarcinoma. They may be a promising therapeutic target in clinical practice.

Commentary: Identification of IFN-Induced Transmembrane Protein 1 With Prognostic Value in Pancreatic Cancer Using Network Module-Based Analysis

Commentary: Identification of IFN-Induced Transmembrane Protein 1 With Prognostic Value in Pancreatic Cancer Using Network Module-Based Analysis

P-14 The predictive value of alkaline phosphatase and lactate dehydrogenase for overall survival in patients with pancreatic cancer

The elevation of alkaline phosphatase (ALP) and lactate dehydrogenase (LDH) has been demonstrated to predict worse prognosis in various malignancies, however, their prognostic value in pancreatic cancer has not been well studied.

The Neutrophil-to-Monocyte Ratio and Platelet-to-White Blood Cell Ratio Represent Novel Prognostic Markers in Patients with Pancreatic Cancer.

Background Inflammation plays an important role in the development of tumors. Several serum based-markers and ratios have been investigated for their prognostic value in pancreatic cancer. However, the prognostic value of the neutrophil-to-monocyte ratio (NMR) and platelet-to-white blood cell ratio (PWR) for patients with pancreatic cancer has scarcely been investigated. Methods From October 2013 to November 2018, a retrospective cohort study was performed on 269 pancreatic cancer patients without treatment. Receiver operating characteristic curves were generated, and areas under the curve were compared for the evaluation of the discriminatory ability of inflammation-based prognostic scoring systems. Kaplan-Meier curves and the Cox proportional hazard model were employed to analyze the relationships among NMR, PWR, and overall survival (OS). Results The optimal cutoff values of NMR and PWR were 48 and 6, respectively. In univariate analysis, the survival time of NMR > 48 and PWR ≤ 6 was shorter than that of NMR ≤ 48 and PWR > 6 in patients with pancreatic cancer (P < 0.001). In Cox univariate and multivariate analyses, NMR (hazard ratio (HR), 9.095; 95% confidence interval (CI), 3.64–22.72; P < 0.001) and PWR (HR, 8.230; 95% CI, 3.32–20.43; P < 0.001) were significantly correlated with OS. Conclusions The current study demonstrated that NMR and PWR may serve as novel and promising inflammatory prognostic scores for patients with pancreatic cancer. Elevated NMR (>48) and depressed PWR (<6) were independently associated with poor prognosis in patients with pancreatic cancer.

Correlations between tumor mutation burden and immune infiltrates and their prognostic value in pancreatic cancer by bioinformatic analysis

PurposeWe aimed to investigate the patterns and prognostic roles of tumor mutation burden and immune microenvironment in pancreatic cancer. MethodsThe somatic mutation data, transcriptome profiles and clinical information were downloaded from the Cancer Genome Atlas database. Gene expression difference, Gene ontology, KEGG, gene set enrichment analyses and “CIBERSORT” algorithm were performed to screen differentially expressed genes, enriched functions or pathways and immune infiltrates differences between high and low TMB groups. Single sample gene set enrichment and unsupervised consensus clustering analyses were used for immunity grouping. Immune cell infiltration and expressions of HLA and checkpoint genes were investigated. Finally, a nomogram model integrating TMB and immune infiltration was established. ResultsA total of 608 differentially expressed genes were identified between high and low TMB groups, KEGG base excision repair and DNA replication pathways were enriched in high TMB group. Infiltration levels of M0 macrophages were higher and dendritic resting cells were lower in high TMB group. The risk model based on TMB-related immune genes, FAM19A2 and SLC22A17 was established and high risk scores indicated poorer prognosis. The expressions of HLA genes and immune checkpoint genes were higher in high immunity group. The nomogram showed remarkable ability for individualized survival estimation with good AUC values (0.794 and 0.800, respectively) for 3- and 5-year survival rates prediction. ConclusionsThe characteristics of tumor mutation burden and immune infiltration in pancreatic cancer provide new insights into the tumor microenvironment, immunotherapies and a novel prognostic nomogram model for pancreatic cancer patients.

Identification of IFN-Induced Transmembrane Protein 1 With Prognostic Value in Pancreatic Cancer Using Network Module-Based Analysis.

Despite improvements reported in diagnosis and treatments in recent decades, pancreatic cancer is still characterized by poor prognosis and low survival rate among solid tumors. Intensive interests have grown in exploring novel predictive biomarkers, aiming to enhance the efficiency in early detection and treatment prognosis. In this study, we identified the differentially expressed genes (DEGs) in pancreatic cancer by analyzing five gene expression profiles and established the functional modules according to the functional interaction (FI) network between the DEGs. A significant upregulation of the selected DEG, interferon (IFN)-induced transmembrane protein 1 (IFITM1), was evaluated in several bioinformatics online tools and verified with immunohistochemistry staining from samples of 90 patients with pancreatic cancer. Prognostic data showed that high expression of IFITM1 associated with poor survival, and multivariate Cox regression analysis showed IFITM1 was one of the independent prognostic factors for overall survival. Meanwhile, significant correlations of the expression of IFITM1 and the infiltration of immune cells were found by TIMER. Furthermore, a higher level of IFITM1 was assessed in pancreatic cancer cell lines compared to normal human pancreatic duct epithelial cells, and silencing IFITM1 in tumor cells remarkedly inhibited cancer tumorigenicity. Collectively, our findings suggested that IFITM1 might have promising utility for pancreatic cancer.

Increased SPHK1 and HAS2 Expressions Correlate to Poor Prognosis in Pancreatic Cancer.

Objective SPHK1 and HAS2 have been reported to play important roles in tumorigenesis and development. However, their expression and prognostic value in pancreatic cancer (PC) remain unclear. This study is aimed at investigating the expression of SPHK1 and HAS2 on the prognosis of pancreatic cancer. Materials and Methods The expression of SPHK1 and HAS2 in pancreatic cancer tissues was analyzed through TCGA and GTEx databases and validated by qRT-PCR and Western blot in pancreatic cancer cell lines. χ2 test was used to explore the correlation of the SPHK1 and HAS2 expressions with clinical characteristics. Kaplan-Meier survival analysis and ROC curve were used to evaluate the prognostic and diagnostic roles of SPHK1 and HAS2 in pancreatic cancer. Additionally, Spearman correlation analysis was applied to assess the correlation between the SPHK1 and HAS2 in pancreatic cancer. GO analysis and KEGG analysis were applied to explore the possible signaling pathway that SPHK1 and HAS2 coregulated genes mediated. Results The expression of SPHK1 and HAS2 was markedly upregulated in pancreatic cancer tissue and cell lines, respectively. Furthermore, there was a significant positive correlation between SPHK1 and HAS2 expressions. ROC curves showed that SPHK1 combine with HAS2 has good diagnostic value in pancreatic cancer patients with 85% sensitivity and 99.4% specificity. Kaplan-Meier analysis showed that increased expression of SPHK1 and HAS2 was significantly associated with short overall survival (OS) of pancreatic cancer patients. GO and KEGG results revealed that SPHK1 and HAS2 mainly involved cell proliferation and invasion mediated by extracellular matrix- (ECM-) receptor interaction, focal adhesion, and PI3K-AKT signaling pathways. Conclusions Overexpression of SPHK1 and HAS2 could be important markers for the prognosis of pancreatic cancer.

Overexpressed CA12 has prognostic value in pancreatic cancer and promotes tumor cell apoptosis via NF-κB signaling.

Pancreatic adenocarcinoma (PAAD) is among the deadliest forms of cancer globally. Carbonic anhydrase 12 (CA12) is known to play central roles in regulating many cancers, but its function in the context of PAAD is rarely discussed. This study was, therefore, designed to assess the expression of CA12 in PAAD and to explore its underlying mechanistic role in this cancer type. Immunohistochemical staining was used to measure CA12 expression in PAAD samples. The functionality of pancreatic cancer cells expressing varying levels of CA12 was assessed through wound healing, Transwell, and CCK-8 assays. In addition, flow cytometry was used to measure apoptosis and cell cycle progression in these same cells, while Western blotting was used to analyze the expression of proteins associated with the NF-κB signaling pathway. PAAD tissue samples exhibited significant CA12 downregulation (P < 0.001), and lower CA12 expression was, in turn, associated with poorer overall survival (P < 0.001). CA12 overexpression significantly impaired the proliferation of PAAD cell lines, instead inducing their apoptotic death and G0/G1 phase cell cycle arrest (P < 0.05). We additionally found that CA12 may exert its tumor suppressive roles via modulating the NF-κB signaling pathway. These results indicate that CA12 functions as a tumor suppressor in PAAD and may thus be a novel therapeutic target that can be used to guide PAAD patient treatment.

Dyslipidemia in Chinese Pancreatic Cancer Patients: A Two-Center Retrospective Study.

Background: Pancreatic cancer (PC) is one of the most aggressive and lethal malignancies in the world. High cholesterol intake may have a certain association with an elevated risk of PC, though dyslipidemia in PC patients has rarely been reported. In this study, we compared serum lipids levels between PC and non-PC tumor patients and assessed their prognostic value in PC.Methods: 271 patients treated at Wuhan Union Hospital from January 2012 to December 2016 and 204 individuals at Shanghai General Hospital from January 2018 to December 2019 were recruited. Their demographic parameters, laboratory data, pathological information, and clinical outcomes were extracted and analyzed. The mRNA expressions of related lipoprotein, low density lipoprotein receptor (LDLR) and high density lipoprotein binding protein (HDLBP), in PC tissues and paired noncancerous tissues and follow-up information were assessed based on the GEO database (GSE15471 and GSE62165) and TCGA database.Results: A total of 172 non-PC tumor patients and 260 PC patients were finally eligible for our analysis. PC patients exhibited higher levels of serum triglyceride, cholesterol, and low-density lipoprotein (LDL) and a lower serum high-density lipoprotein (HDL) level on admission versus the non-PC tumor group. In PC patients, LDLR mRNA expression was upregulated, and HDLBP mRNA expression was downregulated in cancerous tissues compared to these levels in paired noncancerous tissues. The survival analysis revealed that dyslipidemia had a non-significant association with a poor prognosis, but PC patients with a high LDLR level were at risk of poor survival.Conclusion: Dyslipidemia is detected in PC patients but has a non-significant relation to PC prognosis. However, LDLR may be a potential predictive marker for PC prognosis.

Individualized prognostic signature for pancreatic carcinoma validated by integrating immune-related gene pairs (IRGPs)

ABSTRACT Increasingly attention is being given to immune molecules in pancreatic cancer. The purpose of this study was to understand the potential clinical application of immune-regulated genes (IRGs) in the stratification of prognosis and to facilitate the development of personalized prognostic information for pancreatic cancer patients. We systematically used public data to comprehensively analyze immune-regulated gene pair (IRGP) expression profiles and clinical data. In our study, IRGP signature was identified to predict the overall survival (OS) of pancreatic cancer patients. We suggested that immune genes are enriched in different risk groups. In the high-risk group, M1 macrophages and resting NK cells were significantly enriched, while the percentages of naïve B cells, resting dendritic cells, CD8 T cells and regulatory T cells (Tregs) were significantly higher in the low-risk group, and we verified these results with immunohistochemical experiments. Gene ontology (GO) analysis confirmed that the IRGP index (IRGPI) signature genes in the cohort were mostly party to sensory perception of a chemical stimulus and the adaptive immune response. The identification of these pathways provides a basis for studying the molecular mechanisms of IRGPI signaling to predict the prognosis of pancreatic cancer. Our study effectively constructed a robust IRGP signature with prognostic value for pancreatic cancer, presenting a conceivable method for deciding on a preoperative treatment.

Systematic Analysis of the Expression and Prognostic Significance of P4HA1 in Pancreatic Cancer and Construction of a lncRNA-miRNA-P4HA1 Regulatory Axis.

Objectives Prolyl 4-hydroxylase subunit alpha 1 (P4HA1) plays a crucial role in modulating extracellular matrix component and promoting tumor progression by changing tumor adhesion, migration, and other biological behaviors in some cancers. However, its expression pattern, biological function, and underlying mechanism in pancreatic cancer remain largely unclear. Materials and Methods In this study, a set of bioinformatics tools were used to analyze the expression of P4HA1 and its prognostic value in pancreatic cancer. In addition, the mechanism through which P4HA1 promotes the progression of pancreatic cancer was explored by constructing a competing endogenous RNA (ceRNA) regulatory axis. Results It was found that the mRNA and protein expression of P4HA1 was significantly higher in pancreatic cancer tissues than in normal tissues. Its high P4HA1 expression correlated with poor clinicopathological features (T stage: P = 0.0078; N stage: P = 0.0124; TNM stage: P = 0.0013; pathological grade: P = 0.0108) and poor prognosis [OS: HR = 1, 95% CI (1-1.01), P = 0.00028; DSS: HR = 1, 95% CI (1-1.01), P = 0.00049; PFI: HR = 1.01, 95% CI (1.01-1.02), P = 0.0057; and DFI: HR = 1, 95% CI (1-1.01), P = 0.0034]. The LINC01503/miR-335-5p/P4HA1 axis might mediate the effects of P4HA1 in promoting the progression on pancreatic cancer. Conclusions Collectively, our findings suggest that high expression of P4HA1 may be used as a promising prognostic biomarker and could be considered for the development of a novel therapeutic strategy for pancreatic cancer in the future.

A two-gene-based prognostic signature for pancreatic cancer.

The purpose of this study was to identify a vital gene signature that has prognostic value for pancreatic cancer based on gene expression datasets from the Cancer Genome Atlas and Gene Expression Omnibus. A total of 34 genes were obtained by the univariate analysis, which were significantly associated with the overall survival of PC patients. After further analysis, Anillin (ANLN) and Histone H1c (HIST1H1C) were identified and considered to be the most significant prognostic genes among the 34 genes. A prognostic model based on these two genes was constructed, and successfully distinguished pancreatic cancer survival into high-risk and low-risk groups in the training set and testing set. Subsequently, independent predictive factors, including the age, margin condition and risk score, were then employed to construct the nomogram model. The area under curve for the nomogram model was 0.826 at 0.5 years and 0.726 at 1 year, and the C-index of the nomogram model was 0.664 higher than the others variables alone. These findings have indicated that high expression of ANLN and HIST1H1C predicted poor outcomes for patients with pancreatic cancer. The nomogram model based on the expression of two genes could be valuable for the guidance of clinical treatment.

Reduced expression of CDH1 and its prognostic value in pancreatic cancer: a meta-analysis

IntroductionIn this study, we aimed to focus on reduced expression of E-cadherin (CDH1) and its prognostic value in pancreatic cancer (PC) using a meta-analysis.Material and methodsFor this purpose, the PubMed and EMBASE databases were searched from inception until September 1, 2018. Hazard ratio (HR) and 95% confidence interval (CI) were pooled to evaluate the association between CDH1 expression and overall survival (OS); also, odds ratio (OR) and 95% CI were used to assess the correlation between clinicopathological features and CDH1 expression in PC patients. Data from a total of 1805 patients from 16 articles were used in this meta-analysis.ResultsPC patients with decreased expression of CDH1 had a shorter OS (HR = 1.25, 95% CI: 1.09–1.41), without a significant heterogeneity (I2 = 27.1%, p = 0.151). The down-regulated expression of CDH1 was strongly associated with tumour grade (OR = 1.80, 95% CI: 1.07–3.03).ConclusionsDown-regulated expression of CDH1 has potential as a predictive marker of poor prognosis in PC patients. However, further high-quality and large-scale clinical studies are required to validate our findings.

PLS3 predicts poor prognosis in pancreatic cancer and promotes cancer cell proliferation via PI3K/AKT signaling.

Plastin-3 plays a key role in cancer cell proliferation and invasion, but its prognostic value in pancreatic cancer (PACA) remains poorly defined. In this study, we show that PLS3 messenger RNA is overexpressed in PACA tissue compared with normal tissue. We accumulated 207 cases of PACA specimens to perform immunohistochemical analysis and demonstrated that PLS3 levels correlate with T-classification (p < .001) and pathology (p < .001). Furthermore, overall survival rates (p < .001) in tumors with high PLS3 expression were poor, as assessed through Kaplan-Meier survival analysis. PLS3 was found to be an independent prognostic factor for PACA through multivariate Cox regression analysis. Moreover, we found that PLS3 enhances the proliferation and invasion of tumor cells as assessed through Cell Counting Kit-8, wounding healing assays, and Transwell assays. The upregulation of PLS3 also led to enhanced phosphatidylinositol-3 kinase/protein kinase B signaling in PACA cells. These data suggest that PLS3 is a biomarker to estimate PACA progression and represents a molecular target for PACA therapy.

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.

Systematic review: exosomal microRNAs associated with pancreatic cancer for early detection and prognosis.

Pancreatic cancer (PC) is one of the most common malignant tumors of the digestive system with a high degree of malignancy. Currently, there have been many studies on exosomal microRNAs (miRNAs) discovery in pancreatic cancer. This systematic review aimed to give an overview about known exosomal miRNAs and discuss their diagnostic performance, as well as prognostic value in PC. PubMed and Web of Science were used for systematic literature research for this review. This literature research was mainly to identify studies that performed plasmatic and serological testing for exosomal miRNAs in pancreatic cancer patients and controls. Two independent reviewers separately extracted data on study characteristics and results. In total, nine prior studies were included in this review. Of which, eleven different single exosomal miRNAs and three exosomal miRNA panels were reported. When single exosomal miRNA was used as a diagnostic tool, the specificity is generally high, but the sensitivity is commonly low. When multiple of exosomal miRNAs were used simultaneously, higher sensitivities can be obtained at relatively reasonable specificity levels with certain miRNA combinations. Developing a combination of miRNA markers may be a promising approach for early detection of pancreatic cancer.