Gene expression profiling of microdissected pancreatic ductal carcinomas using high-density DNA microarrays

Positive feedback regulation between glycolysis and histone lactylation drives oncogenesis in pancreatic ductal adenocarcinoma

BACKGROUND

Metabolic reprogramming and epigenetic alterations contribute to the aggressiveness of pancreatic ductal adenocarcinoma (PDAC). Lactate-dependent histone modification is a new type of histone mark, which links glycolysis metabolite to the epigenetic process of lactylation. However, the role of histone lactylation in PDAC remains unclear.

METHODS

The level of histone lactylation in PDAC was identified by western blot and immunohistochemistry, and its relationship with the overall survival was evaluated using a Kaplan-Meier survival plot. The participation of histone lactylation in the growth and progression of PDAC was confirmed through inhibition of histone lactylation by glycolysis inhibitors or lactate dehydrogenase A (LDHA) knockdown both in vitro and in vivo. The potential writers and erasers of histone lactylation in PDAC were identified by western blot and functional experiments. The potential target genes of H3K18 lactylation (H3K18la) were screened by CUT&Tag and RNA-seq analyses. The candidate target genes TTK protein kinase (TTK) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were validated through ChIP-qPCR, RT-qPCR and western blot analyses. Next, the effects of these two genes in PDAC were confirmed by knockdown or overexpression. The interaction between TTK and LDHA was identified by Co-IP assay.

RESULTS

Histone lactylation, especially H3K18la level was elevated in PDAC, and the high level of H3K18la was associated with poor prognosis. The suppression of glycolytic activity by different kinds of inhibitors or LDHA knockdown contributed to the anti-tumor effects of PDAC in vitro and in vivo. E1A binding protein p300 (P300) and histone deacetylase 2 were the potential writer and eraser of histone lactylation in PDAC cells, respectively. H3K18la was enriched at the promoters and activated the transcription of mitotic checkpoint regulators TTK and BUB1B. Interestingly, TTK and BUB1B could elevate the expression of P300 which in turn increased glycolysis. Moreover, TTK phosphorylated LDHA at tyrosine 239 (Y239) and activated LDHA, and subsequently upregulated lactate and H3K18la levels.

CONCLUSIONS

The glycolysis-H3K18la-TTK/BUB1B positive feedback loop exacerbates dysfunction in PDAC. These findings delivered a new exploration and significant inter-relationship between lactate metabolic reprogramming and epigenetic regulation, which might pave the way toward novel lactylation treatment strategies in PDAC therapy.

HOXC6 drives a therapeutically targetable pancreatic cancer growth and metastasis pathway by regulating MSK1 and PPP2R2B

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, which lacks effective therapies. Here, we demonstrate that the transcription factor, homeobox C6 (HOXC6), is overexpressed in most PDACs, and its inhibition blocks PDAC tumor growth and metastasis. HOXC6 transcriptionally activates tumor-promoting kinase MSK1 and suppresses tumor-inhibitory protein PPP2R2B in PDAC. HOXC6-induced PPP2R2B suppression causes mammalian target of rapamycin (mTOR) pathway activation, which facilitates PDAC growth. Also, MSK1 upregulation by HOXC6 is necessary for PDAC growth because of its ability to suppress apoptosis via its substrate DDX17. Combinatorial pharmacological inhibition of MSK1 and mTOR potently suppressed PDAC tumor growth and metastasis in PDAC mouse models. PDAC cells with acquired resistance to MSK1/mTOR-inhibitors displayed activated insulin-like growth factor 1 receptor (IGF1R) signaling and were successfully eradicated by IGF1R inhibitor. Furthermore, MEK inhibitor trametinib enhanced the efficacy of dual MSK1 and mTOR inhibition. Collectively, these results identify therapeutic vulnerabilities of PDAC and an approach to overcome acquired drug resistance to prolong therapeutic benefit.

Multianalyte Serum Biomarker Panel for Early Detection of Pancreatic Adenocarcinoma

PURPOSE

We determined whether a large, multianalyte panel of circulating biomarkers can improve detection of early-stage pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

We defined a biologically relevant subspace of blood analytes on the basis of previous identification in premalignant lesions or early-stage PDAC and evaluated each in pilot studies. The 31 analytes that met minimum diagnostic accuracy were measured in serum of 837 subjects (461 healthy, 194 benign pancreatic disease, and 182 early-stage PDAC). We used machine learning to develop classification algorithms using the relationship between subjects on the basis of their changes across the predictors. Model performance was subsequently evaluated in an independent validation data set from 186 additional subjects.

RESULTS

A classification model was trained on 669 subjects (358 healthy, 159 benign, and 152 early-stage PDAC). Model evaluation on a hold-out test set of 168 subjects (103 healthy, 35 benign, and 30 early-stage PDAC) yielded an area under the receiver operating characteristic curve (AUC) of 0.920 for classification of PDAC from non-PDAC (benign and healthy controls) and an AUC of 0.944 for PDAC versus healthy controls. The algorithm was then validated in 146 subsequent cases presenting with pancreatic disease (73 benign pancreatic disease and 73 early- and late-stage PDAC cases) and 40 healthy control subjects. The validation set yielded an AUC of 0.919 for classification of PDAC from non-PDAC and an AUC of 0.925 for PDAC versus healthy controls.

CONCLUSION

Individually weak serum biomarkers can be combined into a strong classification algorithm to develop a blood test to identify patients who may benefit from further testing.

Therapeutic Targets and Prognostic Biomarkers Among CXC Chemokines in Pancreatic Ductal Adenocarcinoma Microenvironment

OBJECTIVES

Pancreatic ductal adenocarcinoma (PDAC) is characterized by occult onset, rapid progression, and poor prognosis. CXC chemokines play an important role in tumor microenvironment and development. However, the potential mechanistic values of CXC chemokines as clinical biomarkers and therapeutic targets in PDAC have not been fully clarified.

METHODS

The altered expression, interaction network, and clinical data of CXC chemokines in patients with PDAC were analyzed by the data from the Gene Expression Omnibus and the Tumor Cancer Genome Atlas.

RESULTS

CXCL5 transcriptional level was significantly elevated in PDAC tissues. A significant correlation was found between the expression of CXC1/3/5/8 and the pathological stage of PDAC patients. The PDAC patients with low transcriptional levels of CXCL5/9/10/11/17 were associated with a significantly better prognosis. The functions of differentially expressed CXC chemokines are primarily related to the chemokine signaling pathway, cytokine-cytokine receptor interaction, and viral protein interaction with cytokine and cytokine receptor. RELA, NFKB1, and SP1 are key transcription factors for CXC chemokines, and the SRC family of tyrosine kinases, mitogen-activated protein kinases, CDK5, PRKCQ, ROCK1, ITK, IKBKE, JAK3, and NTRK2 are CXC chemokine targets.

CONCLUSIONS

The results indicated that CXC chemokines might serve as therapeutic targets and prognostic biomarkers in PDAC.

CD9 mediates the uptake of extracellular vesicles from cancer-associated fibroblasts that promote pancreatic cancer cell aggressiveness

In pancreatic ductal adenocarcinoma (PDAC), signaling from stromal cells is implicated in metastatic progression. Tumor-stroma cross-talk is often mediated through extracellular vesicles (EVs). We previously reported that EVs derived from cancer-associated stromal fibroblasts (CAFs) that are abundant in annexin A6 (ANXA6⁺ EVs) support tumor cell aggressiveness in PDAC. Here, we found that the cell surface glycoprotein and tetraspanin CD9 is a key component of CAF-derived ANXA6⁺ EVs for mediating this cross-talk. CD9 was abundant on the surface of ANXA6⁺ CAFs isolated from patient PDAC samples and from various mouse models of PDAC. CD9 colocalized with CAF markers in the tumor stroma, and CD9 abundance correlated with tumor stage. Blocking CD9 impaired the uptake of ANXA6⁺ EVs into cultured PDAC cells. Signaling pathway arrays and further analyses revealed that the uptake of CD9⁺ANXA6⁺ EVs induced mitogen-activated protein kinase (MAPK) pathway activity, cell migration, and epithelial-to-mesenchymal transition (EMT). Blocking either CD9 or p38 MAPK signaling impaired CD9⁺ANXA6⁺ EV-induced cell migration and EMT in PDAC cells. Analysis of bioinformatic datasets indicated that CD9 abundance was an independent marker of poor prognosis in patients with PDAC. Our findings suggest that CD9-mediated stromal cell signaling promotes PDAC progression.

Biological Characterization and Clinical Value of OAS Gene Family in Pancreatic Cancer

Background

OAS gene family plays an important role in antiviral process, but its role in pancreatic cancer has not yet been studied.

Methods

We analyzed the expression, prognostic value and biological function of the OAS gene family in human pancreatic cancer through comprehensive bioinformatic analysis and cellular level validation.

Results

OAS family was highly expressed in pancreatic cancer, and this high expression significantly affected the clinical stage and prognosis of the tumor. OAS gene family was closely related to the immune infiltration of pancreatic cancer, especially neutrophils and dendritic cells, and many immune-related factors and pathways are enriched in the tumor, such as type I interferon signaling pathway and NOD-like receptor signaling pathway.

Conclusion

Taken together, high expression of OAS family is closely related to poor prognosis of pancreatic cancer. OAS gene family may serve as the biomarker and even therapeutic target of pancreatic cancer.

Transcriptional ITPR3 as potential targets and biomarkers for human pancreatic cancer

Inositol 1,4,5-Triphosphate Receptor Family (ITPRs) are necessary intracellular Ca2+-release channel encoders and participate in mammalian cell physiological and pathological processes. Previous studies have suggested that ITPRs participate in tumorigenesis of multiple cancers. Nevertheless, the diverse expression profiles and prognostic significance of three ITPRs in pancreatic cancer have yet to be uncovered. In this work, we examined the expression levels and survival dates of ITPRs in patients with pancreatic cancer. As a result, we identified that ITPR1 and ITPR3 expression levels are significantly elevated in cancerous specimens. Survival data revealed that over-expression of ITPR2 and ITPR3 resulted in unfavourable overall survival and pathological stage. The multivariate Cox logistic regression analysis showed that ITPR3 could be an independent risk factor for PAAD patient survival. Moreover, to investigate how ITPRs work, co-expressed genes, alterations, protein-protein interaction, immune infiltration, methylation, and functional enrichment of ITPRs were also analyzed. Then, we evaluated these findings in clinical samples. Moreover, the gain and loss of function of ITPR3 were also conducted. The electron microscope assay was employed to explore the role of ITPR3 in pancreatic cancer cell lines' endoplasmic reticulum stress. In summary, our findings demonstrated that ITPR3 has the potential to be drug targets and biomarkers for human pancreatic cancer.

Comprehensive Landscape of STEAP Family Members Expression in Human Cancers: Unraveling the Potential Usefulness in Clinical Practice Using Integrated Bioinformatics Analysis

The human Six-Transmembrane Epithelial Antigen of the Prostate (STEAP) family comprises STEAP1-4. Several studies have pointed out STEAP proteins as putative biomarkers, as well as therapeutic targets in several types of human cancers, particularly in prostate cancer. However, the relationships and significance of the expression pattern of STEAP1-4 in cancer cases are barely known. Herein, the Oncomine database and cBioPortal platform were selected to predict the differential expression levels of STEAP members and clinical prognosis. The most common expression pattern observed was the combination of the over- and underexpression of distinct STEAP genes, but cervical and gastric cancer and lymphoma showed overexpression of all STEAP genes. It was also found that STEAP genes’ expression levels were already deregulated in benign lesions. Regarding the prognostic value, it was found that STEAP1 (prostate), STEAP2 (brain and central nervous system), STEAP3 (kidney, leukemia and testicular) and STEAP4 (bladder, cervical, gastric) overexpression correlate with lower patient survival rate. However, in prostate cancer, overexpression of the STEAP4 gene was correlated with a higher survival rate. Overall, this study first showed that the expression levels of STEAP genes are highly variable in human cancers, which may be related to different patients’ outcomes.

Off-the-Shelf Prostate Stem Cell Antigen-Directed Chimeric Antigen Receptor Natural Killer Cell Therapy to Treat Pancreatic Cancer

BACKGROUND & AIMS

Pancreatic cancer (PC) is the third leading cause of cancer-related death with a 5-year survival rate of approximately 10%. It typically presents as a late-stage incurable cancer and chemotherapy provides modest benefit. Here, we demonstrate the feasibility, safety, and potency of a novel human natural killer (NK) cell-based immunotherapy to treat PC.

METHODS

The expression of prostate stem cell antigen (PSCA) was evaluated in primary PC at messenger RNA and protein levels. The processes of retroviral transduction, expansion, activation, and cryopreservation of primary human NK cells obtained from umbilical cord blood were optimized, allowing us to develop frozen, off-the-shelf, allogeneic PSCA chimeric antigen receptor (CAR) NK cells. The safety and efficacy of PSCA CAR NK cells also expressing soluble (s) interleukin 15 (PSCA CAR_s15 NK cells) were evaluated in vitro and in vivo.

RESULTS

PSCA was elevated in primary human PC compared with the adjacent or other normal tissues. PSCA CAR_s15 NK cells displayed significant tumor-suppressive effects against PSCA(+) PC in vitro before and after 1 cycle of freeze-thaw. The viability of frozen PSCA CAR_s15 NK cells persisted more than 90 days in vivo after their last infusion and significantly prolonged the survival of mice engrafted with human PC.

CONCLUSIONS

PSCA CAR_s15 NK cells showed therapeutic efficacy in human metastatic PC models without signs of systematic toxicity, providing a strong rationale to support clinical development.

Comprehensive analysis of expression profile and prognostic significance of interferon regulatory factors in pancreatic cancer

BACKGROUND

Pancreatic cancer (PC) is a highly lethal disease and an increasing cause of cancer-associated mortality worldwide. Interferon regulatory factors (IRFs) play vital roles in immune response and tumor cellular biological processes. However, the specific functions of IRFs in PC and tumor immune response are far from systematically clarified. This study aimed to explorer the expression profile, prognostic significance, and biological function of IRFs in PC.

RESULTS

We observed that the levels of IRF2, 6, 7, 8, and 9 were elevated in tumor compared to normal tissues in PC. IRF7 expression was significantly associated with patients' pathology stage in PC. PC patients with high IRF2, low IRF3, and high IRF6 levels had significantly poorer overall survival. High mRNA expression, amplification and, deep deletion were the three most common types of genetic alterations of IRFs in PC. Low expression of IRF2, 4, 5, and 8 was resistant to most of the drugs or small molecules from Genomics of Drug Sensitivity in Cancer. Moreover, IRFs were positively correlated with the abundance of tumor infiltrating immune cells in PC, including B cells, CD8+ T cells, CD4+ T cells, macrophages, Neutrophil, and Dendritic cells. Functional analysis indicated that IRFs were involved in T cell receptor signaling pathway, immune response, and Toll-like receptor signaling pathway.

CONCLUSIONS

Our results indicated that certain IRFs could serve as potential therapeutic targets and prognostic biomarkers for PC patients. Further basic and clinical studies are needed to validate our findings and generalize the clinical application of IRFs in PC.

Comprehensive Analysis of Myoferlin in Human Pancreatic Cancer via Bioinformatics

Pancreatic cancer is the fourth leading cause of cancer-related death and urgently needs biomarkers for clinical diagnosis and prognosis. It has been reported that myoferlin (MYOF) is implicated in the regulation of proliferation, invasion, and migration of tumor cells in many cancers including pancreatic cancer. To confirm the prognostic value of MYOF in pancreatic cancer, a comprehensive cancer versus healthy people analysis was conducted using public data. MYOF mRNA expression levels were compared in many kinds of cancers including pancreatic cancer via the Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA) databases. The results have shown that MYOF mRNA expression levels were upregulated in most types of cancers, especially in pancreatic cancer, compared with healthy people's tissues. Data from the Cancer Cell Line Encyclopedia (CCLE) and European Bioinformatics Institute (EMBL-EML) database also revealed that MYOF mRNA is highly expressed in most cancer cells, particularly in pancreatic cancer cell lines. Furthermore, the prognostic value of MYOF was evaluated using GEPIA and Long-term Outcome and Gene Expression Profiling Database of pan-cancers (LOGpc) database. Higher expression of MYOF was associated with poorer overall survival, especially in the lower stage and lower grade. Coexpressed genes, possible regulators, and the correlation between MYOF expressions were analyzed via the GEPIA and LinkedOmics database. Nineteen coexpressed genes were identified, and most of these genes were related to cancer. The Tumor Immune Estimation Resource (TIMER) database was used to analyze the correlation between MYOF and immune response. Notably, we found that MYOF might have a potential novel immune regulatory role in tumor immunity. These results support that MYOF is a candidate prognostic biomarker for pancreatic cancer, which calls for further genomics research of pancreatic cancer and deeply functional studies on MYOF.

Long intergenic non-protein coding RNA 960 regulates cancer cell viability, migration and invasion through modulating miR-146a-5p/interleukin 1 receptor associated kinase 1 axis in pancreatic ductal adenocarcinoma

Long non-coding RNAs (lncRNAs) are considered as crucial regulatory factors in cancer biology. However, the biological function of long intergenic non-protein coding RNA 960 (LINC00960) in the tumorigenesis of pancreatic ductal adenocarcinoma (PDAC) is still unknown. The goal of this study is to investigate the role of LINC00960 in PDAC. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to examine the expression levels of LINC00960 in PDAC tissues and cell lines. After transfection, the loss-of-function models of LINC00960 or interleukin 1 receptor-associated kinase 1 (IRAK1) were established with BxPC-3 cells and Colo357 cells, and the malignant phenotypes of BxPC-3 cells and Colo357 cells were detected by CCK-8 assay, BrdU assay and Transwell assay, respectively. The interactions among LINC00960, miR-146a-5p and IRAK1 were predicted by bioinformatics analysis, and verified by luciferase reporter assay, RNA immunoprecipitation assay and RNA pull-down assay. The regulatory functions of LINC00960 and miR-146a-5p on IRAK1 were detected by Western blot. We demonstrated that the LINC00960 expression was increased in PDAC tissues and cell lines. Knocking down LINC00960 or IRAK1 could repress the viability, migration, and invasion of BxPC-3 and Colo357 cells. LINC00960 functioned as a molecular sponge for miR-146a-5p, and IRAK1 was verified as a target gene of miR-146a-5p. Additionally, LINC00960 could up-regulate IRAK1 expression via repressing miR-146a-5p, and the oncogenic properties of LINC00960 were partly reversed by miR-146a-5p. Our findings reveal that LINC00960 is a promoter of PDAC progression through regulating miR-146a-5p/IRAK1axis.

Potential Prognostic Biomarkers of OSBPL Family Genes in Patients with Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal malignancy with poor survival outcomes. In addition, oxysterol-binding protein-like (OSBPL) family members are reported to be involved in lipid binding and transport and play critical roles in tumorigenesis. However, relationships between PDAC and OSBPL family members have not comprehensively been elucidated. In this study, we used the Oncomine and GEPIA 2 databases to analyze OSBPL transcription expressions in PDAC. The Kaplan–Meier plotter and TIMER 2.0 were used to assess the relationships between overall survival (OS) and immune-infiltration with OSBPL family members. Co-expression data from cBioPortal were downloaded to assess the correlated pathways with OSBPL gene family members using DAVID. The expressions of OSBPL3, OSBPL8, OSBPL10, and OSBPL11 were found to be highly upregulated in PDAC. Low expressions of OSBPL3, OSBPL8, and OSBPL10 indicated longer OS. The functions of OSBPL family members were mainly associated with several potential signaling pathways in cancer cells, including ATP binding, integrin binding, receptor binding, and the renin-angiotensin system (RAS) signaling pathway. The transcription levels of OSBPL gene family members were connected with several immune infiltrates. Collectively, OSBPL family members are influential biomarkers for the early diagnosis of PDAC and have prognostic value, with the promise of precise treatment of PDAC in the future.

Longitudinal Analysis of Human Pancreatic Adenocarcinoma Development Reveals Transient Gene Expression Signatures

Previous transcriptome studies of human pancreatic ductal adenocarcinoma (PDAC) compare non-cancerous pancreatic intraepithelial neoplasias (PanIN) with late-stage PDAC obtained from different patients, thus have limited ability to discern network dynamics that contribute to the disease progression. We demonstrated previously that the 10-22 cell line, an induced pluripotent stem cell-like line reprogrammed from late-stage human PDAC cells, recapitulated the progression from PanINs to PDAC upon transplantation into NOD/LtSz-scid/IL2R-gamma^null mice. Herein, we investigated the transition from precursor to PDAC using the isogenic model. We analyzed transcriptomes of genetically tagged 10-22 cells progressing from PanINs to PDAC in mice and validated the results using The Cancer Genome Atlas PDAC dataset, human clinical PanIN and PDAC tissues, and a well-established murine PDAC model. We functionally studied candidate proteins using human normal (H6C7) and cancerous (Miapaca2, Aspc1) pancreatic ductal epithelial cell lines. 10-22 cell-derived PDAC displayed the molecular signature of clinical human PDAC. Expression changes of many genes were transient during PDAC progression. Pathways for extracellular vesicle transport and neuronal cell differentiation were derepressed in the progression of PanINs to PDAC. HMG-box transcription factor 1 (HBP1) and BTB domain and CNC homolog 1 (BACH1) were implicated in regulating dynamically expressed genes during PDAC progression, and their expressions inversely correlated with PDAC patients' prognosis. Ectopic expression of HBP1 increased proliferation and migration of normal and cancerous pancreatic cells, indicating that HBP1 may confer the cell dissemination capacity in early PDAC progression. This unique longitudinal analysis provides insights into networks underlying human PDAC progression and pathogenesis. IMPLICATIONS: Manipulation of HBP1, BACH1, and RUN3 networks during PDAC progression can be harnessed to develop new targets for treating PDAC.

Identification of Novel Molecular Therapeutic Targets and Their Potential Prognostic Biomarkers Among Kinesin Superfamily of Proteins in Pancreatic Ductal Adenocarcinoma

Background

Kinesin superfamily of proteins (KIFs) has been broadly reported to play an indispensable role in the biological process. Recently, emerging evidence reveals its oncogenic role in various cancers. However, the prognostic, oncological, and immunological values of KIFs have not been comprehensively explored in pancreatic ductal adenocarcinoma (PDAC) patients. We aimed to illustrate the relationship between KIFs and pancreatic ductal adenocarcinoma by using bioinformatical analysis.

Methods

We use GEPIA, Oncomine datasets, cBioPortal, LOGpc, TIMER, and STRING bioinformatics tools and web servers to investigate the aberrant expression, prognostic values, and oncogenic role of KIFs. The two-gene prognostic model and the correlation between KIFs and KRAS and TP53 mutation were performed using an R-based computational framework.

Results

Our results demonstrated that KIFC1/2C/4A/11/14/15/18A/18B/20B/23 (we name it prognosis-related KIFs) were upregulated and associated with unfavorable clinical outcome in pancreatic cancer patients. KIF21B overexpression is associated with better clinical outcome. The KIFC1/2C/4A/11/14/15/18A/18B/20B/23 profiles were significantly increased compared to grade 1 and grade 2/3. Besides, KIFC1/2C/4A/11/14/15/18A/18B/20B/23 was significantly associated with the mutation status of KRAS and TP53.Notably, most prognosis-related KIFs have strong correlations with tumor growth and myeloid-derived suppressor cells infiltration (MDSCs). A prognostic signature based on KIF20B and KIF21B showed a reliable predictive performance. Receiver operating characteristic (ROC) curve was employed to assess the predictive power of two-gene signature. Consequently, the gene set enrichment analysis (GSEA) showed that KIF20B and KIF21B’s overexpression was associated with the immunological and oncogenic pathway activation in pancreatic cancer. Finally, real-time quantitative PCR (RT-qPCR) was utilized to investigate the expression pattern of KIF20B and KIF21B in pancreatic cancer cell lines and normal pancreatic cell.

Conclusions

Knowledge of the expression level of the KIFs may provide novel therapeutic molecular targets and potential prognostic biomarkers to pancreatic cancer patients.

Prognostic Biomarkers and Immunotherapeutic Targets Among CXC Chemokines in Pancreatic Adenocarcinoma

Background

Pancreatic cancer is one of the principal causes of tumor-related death worldwide. CXC chemokines, a subfamily of functional chemotactic peptides, affect the initiation of tumor cells and clinical outcomes in several human malignant tumors. However, the specific biological functions and clinical significance of CXC chemokines in pancreatic cancer have not been clarified.

Methods

Bioinformatics analysis tools and databases, including ONCOMINE, GEPIA2, the Human Protein Atlas, DAVID, GeneMANIA, cBioPortal, STRING, DGidb, MethSurv, TRRUST, SurvExpress, SurvivalMeth, and TIMER, were utilized to clarify the clinical significance and biological functions of CXC chemokine in pancreatic cancer.

Results

Except for CXCL11/12, the transcriptional levels of other CXC chemokines in PAAD tissues were significantly elevated, and the expression level of CXCL16 was the highest among these CXC chemokines. Our findings also suggested that all of the CXC chemokines were linked to tumor-immune dysfunction involving the abundance of immune cell infiltration, and the Cox proportional hazard model confirmed that dendritic and CXCL3/5/7/8/11/17 were significantly associated with the clinical outcome of PAAD patients. Furthermore, increasing expressions of CXCL5/9/10/11/17 were related to unfavorable overall survival (OS), and only CXCL17 was a prognostic factor for disease-free survival (DFS) in PAAD patients. The expression pattern and prognostic power of CXC chemokines were further validated in the independent GSE62452 dataset. For the prognostic value of single CpG of DNA methylation of CXC chemokines in patients with PAAD, we identified 3 CpGs of CXCL1, 2 CpGs of CXCL2, 2 CpGs of CXCL3, 3 CpGs of CXCL4, 10 CpGs of CXCL5, 1 CpG of CXCL6, 1 CpG of CXCL7, 3 CpGs of CXCL12, 3 CpGs of CXCL14, and 5 CpGs of CXCL17 that were significantly associated with prognosis in PAAD patients. Moreover, the prognostic value of CXC chemokine signature in PAAD was explored and tested in two independent cohort, and results indicated that the patients in the low-risk group had a better OS compared with the high-risk group. Survival analysis of the DNA methylation of CXC chemokine signature demonstrated that PAAD patients in the high-risk group had longer survival times.

Conclusions

These findings reveal the novel insights into CXC chemokine expression and their biological functions in the pancreatic cancers, which might serve as accurate prognostic biomarkers and suitable immunotherapeutic targets for patients with pancreatic cancer.

Identification of hub genes and their novel diagnostic and prognostic significance in pancreatic adenocarcinoma

OBJECTIVE

The main reasons for the poor prognoses of pancreatic adenocarcinoma (PA) patients are rapid early-stage progression, advanced stage metastasis, and chemotherapy resistance. Identification of novel diagnostic and prognostic biomarkers of PA is therefore urgently needed.

METHODS

Three mRNA microarray datasets were obtained from the Gene Expression Omnibus database to select differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for hub genes were performed using DAVID. Correlations between expression levels of hub genes and cancer-infiltrating immune cells were investigated by TIMER. Cox proportional hazard regression analyses were also performed. Serum hub genes were screened using the HPA platform and verified for diagnostic value using ELISAs.

RESULTS

We identified 59 hub genes among 752 DEGs. GO analysis indicated that these 59 hub genes were mainly involved in the defense response to viruses and the type I interferon signaling pathway. We also discovered that RSAD2 and SMC4 were associated with immune cell infiltration in the PA microenvironment. Additionally, DLGAP5 mRNA might be used as an independent risk factor for the prognoses of PA patients. Furthermore, the protein encoded by ISG15, which exists in peripheral blood, was validated as a potential diagnostic biomarker that distinguished PA patients from healthy controls (area under the curve: 0.902, 95% confidence interval: 0.819-0.961).

CONCLUSIONS

Our study suggested that RSAD2 and SMC4 were associated with immune cell infiltration in the PA microenvironment, while DLGAP5 mRNA expression might be an independent risk factor for the survival prognoses of PA patients. Moreover, ELISAs indicated that serum ISG15 could be a potential novel diagnostic biomarker for PA.

HELLS serves as a poor prognostic biomarker and its downregulation reserves the malignant phenotype in pancreatic cancer

BACKGROUND

SMARCAs, belonged to SWI/SNF2 subfamilies, are critical to cellular processes due to their modulation of chromatin remodeling processes. Although SMARCAs are implicated in the tumor progression of various cancer types, our understanding of how those members affect pancreatic carcinogenesis is quite limited and improving this requires bioinformatics analysis and biology approaches.

METHODS

To address this issue, we investigated the transcriptional and survival data of SMARCAs in patients with pancreatic cancer using ONCOMINE, GEPIA, Human Protein Atlas, and Kaplan-Meier plotter. We further verified the effect of significant biomarker on pancreatic cancer in vitro through functional experiment.

RESULTS

The Kaplan-Meier curve and log-rank test analyses showed a positive correlation between SMARCA1/2/3/SMARCAD1 and patients' overall survival (OS). On the other hand, mRNA expression of SMARCA6 (also known as HELLS) showed a negative correlation with OS. Meanwhile, no significant correlation was found between SMARCA4/5/SMARCAL1 and tumor stages and OS. The knockdown of HELLS impaired the colony formation ability, and inhibited pancreatic cancer cell proliferation by arresting cells at S phase.

CONCLUSIONS

Data mining analysis and cell function research demonstrated that HELLS played oncogenic roles in the development and progression of pancreatic cancer, and serve as a poor prognostic biomarker for pancreatic cancer. Our work laid a foundation for further clinical applications of HELLS in pancreatic cancer.

The Immunohistochemical Expression of MCM-3, -5, and -7 Proteins in the Uterine Fibroids

Uterine fibroids are the most common mesenchymal uterine neoplasms; their prevalence is estimated in 40%–60% of women under 35 and in 70%–80% of women over 50 years of age. The current research aims to focus on the etiopathogenesis of uterine fibroids, the factors that affect their growth, and markers with diagnostic and prognostic properties. The MCM (minichromosome maintenance) protein family consists of peptides whose primary function is participation in the molecular mechanism of creating replication forks while regulating DNA synthesis. The aim of this work was to determine the proliferative potential of uterine fibroid cells based on the expression of the Ki-67 antigen and the MCMs—i.e., MCM-3, MCM-5, and MCM-7. In addition, the expression of estrogen (ER) and progesterone (PgR) receptors was evaluated and correlated with the expression of the abovementioned observations. Ultimately, received results were analyzed in terms of clinical and pathological data. Materials and methods: In forty-four cases of uterine fibroids, immunohistochemical reactions were performed. A tissue microarray (TMA) technique was utilized and analyzed cases were assessed in triplicate. Immunohistochemistry was performed using antibodies against Ki-67 antigen, ER, PgR, MCM-3, MCM-5, and MCM-8 on an automated staining platform. Reactions were digitalized by a histologic scanner and quantified utilizing dedicated software for nuclear analysis. Assessment was based on quantification expression of the three histiospots, each representing one case in TMA. Results: In the study group (uterine fibroids), statistically significant stronger expression of all the investigated MCMs was observed, as compared to the control group. In addition, moderate and strong positive correlations were found between all tested proliferative markers. The expression of the MCM-7 protein also correlated positively with ER and PgR. With regard to clinical and pathological data, there was a negative correlation between the expression of MCMs and the number of both pregnancies and births. Significant reductions in MCM-5 and MCM-7 expression were observed in the group of women receiving oral hormonal contraceptives, while smoking women showed an increase in MCM-7, ER, and PgR. Conclusions: Uterine fibroid cells have greater proliferative potential, as evaluated by expression of the Ki-67 antigen and MCMs, than unaltered myometrial cells of the uterine corpus. The expression of MCM-7 was found to have strong or moderate correlations in all assessed relations. In the context of the clinical data, as well evident proliferative potential of MCMs, further studies are strongly recommended.

GLI1: A Therapeutic Target for Cancer

GLI1 is a transcriptional effector at the terminal end of the Hedgehog signaling (Hh) pathway and is tightly regulated during embryonic development and tissue patterning/differentiation. GLI1 has low-level expression in differentiated tissues, however, in certain cancers, aberrant activation of GLI1 has been linked to the promotion of numerous hallmarks of cancer, such as proliferation, survival, angiogenesis, metastasis, metabolic rewiring, and chemotherapeutic resistance. All of these are driven, in part, by GLI1’s role in regulating cell cycle, DNA replication and DNA damage repair processes. The consequences of GLI1 oncogenic activity, specifically the activity surrounding DNA damage repair proteins, such as NBS1, and cell cycle proteins, such as CDK1, can be linked to tumorigenesis and chemoresistance. Therefore, understanding the underlying mechanisms driving GLI1 dysregulation can provide prognostic and diagnostic biomarkers to identify a patient population that would derive therapeutic benefit from either direct inhibition of GLI1 or targeted therapy towards proteins downstream of GLI1 regulation.

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.

Identification of Prognostic and Therapeutic Biomarkers among FAM83 Family Members for Pancreatic Ductal Adenocarcinoma

Family with sequence similarity 83 (FAM83) members were shown recently to have oncogenic effect in a variety of cancer types, but the biological roles and prognostic value of FAM83 family in pancreatic ductal adenocarcinoma remain unknown. In the current study, the clinical significance and molecular function of the FAM83 family were assessed by multiple bioinformatics analysis. Besides, potential associations between differentially expressed genes (DEGs) of FAM83 family and antitumor immunity were evaluated using TIMER and TISIDB analyses. As the results show, FAM83A, FAM83D, FAM83E, and FAM83H were significantly upregulated in PDAC and were identified as DEGs. Higher expression of FAM83A, FAM83B, FAM83D, FAM83E, and FAM83H were associated with advanced tumor stage or worse patient prognosis. Importantly, the overexpression of DEGs was found to be significantly correlated with activated KRAS and loss of SMAD4, which are important drivers for PDAC. Further, FAM83A, FAM83D, and FAM83H were associated with CD8⁺ T cell, Gamma Delta T cell, and CD4⁺ T cell infiltration in PDAC and FAM83H was found closely correlated with some immunomodulators including immunoinhibitors, immunostimulators, and MHC molecules. In conclusion, FAM83A, FAM83D, FAM83E, and FAM83H have significant prognostic value in PDAC and they may play important roles in regulating tumor progression and the immune cell infiltration.

Identification of novel hub genes and lncRNAs related to the prognosis and progression of pancreatic cancer by microarray and integrated bioinformatics analysis

BACKGROUND

Pancreatic cancer (PC) is one of the most invasive and metastatic neoplasms among the fatal malignancies of the digestive system. Abnormal expression of genes and long non-coding RNAs (lncRNAs) are reportedly linked to multiple cancers. However, the lncRNA-mRNA expression profiles and their molecular mechanisms in PC progression are poorly known. This study aimed to map the hub genes and lncRNAs which might play core roles in the development of PC.

METHODS

This study used microarray expression analysis to screen for both differentially expressed genes (DEGs) and differentially expressed lncRNAs (DElncRNAs) between PC and matched adjacent non-tumor (AN) tissues. In order to clarify the functional classification of DEGs, we conducted GO and KEGG pathway enrichment analyses via the Enrichr database. LncRNA-mRNA co-expressed networks were also constructed to explore the probable core regulating DEGs and DElncRNAs. Subsequently, the hub genes and lncRNAs were validated via the ONCOMINE and GEPIA databases and the co-expressed networks.

RESULTS

By analyzing an mRNA-lncRNA microarray, we identified 943 mRNAs and 1,138 lncRNAs differentially expressed in PC tumors compared with the matched AN tissues. GO analysis confirmed that both up-regulated and down-regulated DEGs were enriched in multiple terms. The KEGG pathways enrichment analyses revealed that DEGs were mostly enriched in the focal adhesion and glutathione metabolism pathways, amongst others. Co-expressed networks were established to reveal the differential interactions between DEGs and DElncRNAs, and to indicate the core regulatory factors located at the core nodes of the co-expressed networks. The expression levels of potential core-regulating DEGs were validated by the GEPIA and ONCOMINE databases, and the relationship between overall survival and tumor stage and the potential core-regulating DEGs was analyzed using the GEPIA database. As a result, five genes and sixteen lncRNAs were finally considered as the hub transcripts in PC.

CONCLUSIONS

This study identified DEGs and DElncRNAs between PC tumors and matched AN tissues, and these transcripts were connected with malignant phenotypes in PC through different BPs and signaling pathways. Furthermore, five hub genes and sixteen lncRNAs were identified, which are expected to represent candidate diagnostic biomarkers or potential therapeutic targets for PC.

GPRC5A: An emerging prognostic biomarker for predicting malignancy of Pancreatic Cancer based on bioinformatics analysis

Background: Pancreatic cancer (PaCa) is a highly lethal malignancy. The treatment options for PaCa lack efficacy. The study aimed to explore the molecular biomarkers for predicting survival of PaCa and identify the potential carcinogenic mechanisms of the selected gene.

Methods: Based on public databases of PaCa, differentially expressed genes (DEGs) were identified using Networkanalyst. Survival analyses were exerted on GEPIA. Oncomine and The Human Protein Atlas were used for verifying the expression on mRNA and protein levels. Enrichment analyses were generated on Metascape and gene set enrichment analysis (GSEA). Univariate analyses were performed to determine the clinical factors associated with the expression of GPRC5A.

Results: GPRC5A was identified as the most valuable gene in predicting survival of PaCa patients. Patients with high expression of GPRC5A showed larger tumor size, higher TNM stages, higher tumor grade, and more positive resection margin. In mutant KRAS, TP53, CDKN2A and SMAD4 group, the expression of GPRC5A was higher than non-mutant group. Mechanistically, GPRC5A may promote metastasis of PaCa mainly via regulating epithelial-mesenchymal transition (EMT) and neuroactive ligand-receptor interaction.

Conclusion: GPRC5A may act as an oncogene in the progression of PaCa and could be a prognostic biomarker in predicting survival of PaCa.

Comprehensive Analysis of Prognostic and Immune Infiltrates for E2F Transcription Factors in Human Pancreatic Adenocarcinoma

Background

E2F transcription factors (E2Fs) are a group of genes encoding a family of transcription factors in higher eukaryotes. They are involved in a variety of cellular functions and are up-regulated in many tissues and organs. However, the expression level, genetic variation, molecular mechanism, and biological function of different E2Fs in PAAD and its relationship with the prognosis and immune infiltration in patients with PAAD have not been fully elucidated.

Methods

In this study, we investigated the mRNA expression level, genetic variation, prognostic value and gene–gene interaction network of E2Fs in PAAD using the Oncomine, GEPIA, Kaplan Meier plotter, cBioPortal, GeneMANIA, STRING and Metascape database. Then, the relationship between E2Fs expression and tumor immune invasion was studied by using the TIMER database. Finally, we confirmed the expression of E2Fs in PAAD by IHC.

Results

The transcription levels of E2F1/3/5/8 are obviously up-regulated in PAAD and the high expression of E2F2/3/6/8 was apparently associated with the tumor stage of patients with PAAD. The abnormal expression of E2F1/2/3/4/5/7/8 in PAAD patients is related to the clinical outcome of PAAD patients. We also found that PAAD tissues have higher expression levels of E2F1/3/5/8 compared with adjacent normal tissues. The function of E2Fs and its neighboring genes is mainly related to the transcription initiation of the RNA polymerase II promoter. The functions of E2Fs and its neighboring proteins are mainly related to cell cycle, virus carcinogenesis, FoxO signaling pathway, TGF-β signaling pathway, transcriptional disorders in cancer and Wnt signaling pathway. We also found that the expression of E2Fs was significantly correlated with immune infiltrates, including B cells, CD8+ T cells, CD4+T cells, neutrophils, macrophages, and dendritic cells.

Conclusions

Our study may provide new insights into the choice of immunotherapy targets and prognostic biomarkers in PAAD patients.

The role of phosphoprotein phosphatases catalytic subunit genes in pancreatic cancer

Compelling evidence suggests that phosphoprotein phosphatases (PPPs) are involved in a large spectrum of physiological and pathological processes, but little is known about their roles in pancreatic cancer. We investigated the expression level, prognostic value, and potential function of PPPs with data from Oncomine, GEPIA, THPA, and TCGA databases and an independent cohort of patients with pancreatic cancer. Among all the PPP catalytic subunits (PPPcs), the transcription levels of PPP1CA, PPP1CB, PPP3CA, PPP3CB, and PPP4C were higher in pancreatic cancer than in normal pancreas (P<0.01, fold change > 2). Kaplan–Meier analysis showed that high transcription levels of PPP1CA, PPP1CB, PPP2CA, PPP2CB, PPP3CA, and PPP4C correlated with poorer survival. In contrast, patients with high levels of PPP3CB, PPP3CC, PPP5C, PPP6C, and PPEF2 had much better prognoses. Data from THPA and patients with pancreatic cancer enrolled in our hospital also confirmed the prognostic value of PPP1CA, PPP1CB, PPP2CA, PPP2CB, PPP3CA, PPP3CB, and PPP6C at the protein level. In addition, the Pearson Chi-square test showed that PPP3CB level was significantly correlated with T and N stages. GO and KEGG analyses showed that the genes and pathways related to the pathogenesis and progression of pancreatic cancer were greatly affected by alterations in PPPcs. Results of the present study suggest that PPP1CA, PPP1CB, PPP2CA, PPP2CB, and PPP3CA have deleterious effects but PPP3CB, PPP5C, and PPP6C have beneficial effects on pancreatic cancer.

Expression and prognostic analyses of the insulin-like growth factor 2 mRNA binding protein family in human pancreatic cancer

BACKGROUND

Despite advances in early diagnosis and treatment, cancer remains the leading cause of mortality worldwide. The insulin-like growth factor 2 mRNA binding protein (IGF2BP) family has been reported to be involved in a variety of human malignant tumours. However, little is known about their expression and prognostic value in human pancreatic cancer. Therefore, we performed a detailed cancer versus normal differential analysis.

METHODS

The Cancer Genome Atlas (TCGA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases were used to analyse the mRNA expression levels of the IGF2BP family in various cancers, including pancreatic cancer. Then, the LinkedOmics and GEPIA databases were used to assess the relation between the expression levels of IGF2BPs and overall survival (OS). Then, univariate and multivariate Cox regression analyses were performed, and subgroups based on grade and stage were analysed. The signalling pathways associated with IGF2BP2 and IGF2BP3 were then investigated via gene set enrichment analysis (GSEA).

RESULTS

IGF2BP2 and IGF2BP3 were associated with each subset of OS based on grade and stage. Further clinical correlation analysis of IGF2BP2 and IGF2BP3 confirmed that IGF2BP2 and IGF2BP3 are fundamental factors in promoting pancreatic cancer progression.

CONCLUSION

IGF2BP2 and IGF2BP3 are key factors in promoting the progression of pancreatic cancer and are closely related to overall survival.

Upregulation of CENPM facilitates tumor metastasis via the mTOR/p70S6K signaling pathway in pancreatic cancer

Pancreatic cancer is a severe disease with high morbidity and mortality. However, the primary molecular mechanisms of pancreatic tumor formation and progression remain unclear. The present study using sequencing technology revealed that the centromere protein M (CENPM) gene was overexpressed in pancreatic cancer tissues. CENPM is one of the components of a complex that plays a central role in kinetochore protein assembly, mitotic progression and chromosome segregation. However, the biological function of CENPM in pancreatic cancer has yet to be determined. Hence, two effective siRNAs were designed to knock down CENPM. Notably, downregulation of CENPM inhibited pancreatic cancer cell proliferation, altered the cell cycle and limited pancreatic cancer cell migration and invasion via the mTOR/p70S6K signaling pathway. This research provides new evidence that CENPM overexpression plays a significant role in the progression of pancreatic cancer. Overall, the present findings indicated that CENPM may be a significant biomarker for predicting the development and progression of pancreatic malignancy.

KLF7 promotes pancreatic cancer growth and metastasis by up-regulating ISG expression and maintaining Golgi complex integrity

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with a dismal prognosis. Currently, there is no effective therapy for PDAC, and a detailed molecular and functional evaluation of PDACs is needed to identify and develop better therapeutic strategies. Here we show that the transcription factor Krüppel-like factor 7 (KLF7) is overexpressed in PDACs, and that inhibition of KLF7 blocks PDAC tumor growth and metastasis in cell culture and in mice. KLF7 expression in PDACs can be up-regulated due to activation of a MAP kinase pathway or inactivation of the tumor suppressor p53, two alterations that occur in a large majority of PDACs. ShRNA-mediated knockdown of KLF7 inhibits the expression of IFN-stimulated genes (ISGs), which are necessary for KLF7-mediated PDAC tumor growth and metastasis. KLF7 knockdown also results in the down-regulation of Discs Large MAGUK Scaffold Protein 3 (DLG3), resulting in Golgi complex fragmentation, and reduced protein glycosylation, leading to reduced secretion of cancer-promoting growth factors, such as chemokines. Genetic or pharmacologic activation of Golgi complex fragmentation blocks PDAC growth and metastasis similar to KLF7 inhibition. Our results demonstrate a therapeutically amenable, KLF7-driven pathway that promotes PDAC growth and metastasis by activating ISGs and maintaining Golgi complex integrity.

Cysteine depletion induces pancreatic tumor ferroptosis in mice

Ferroptosis is a form of cell death that results from the catastrophic accumulation of lipid reactive oxygen species (ROS). Oncogenic signaling elevates lipid ROS production in many tumor types and is counteracted by metabolites that are derived from the amino acid cysteine. In this work, we show that the import of oxidized cysteine (cystine) via system x_C ^- is a critical dependency of pancreatic ductal adenocarcinoma (PDAC), which is a leading cause of cancer mortality. PDAC cells used cysteine to synthesize glutathione and coenzyme A, which, together, down-regulated ferroptosis. Studying genetically engineered mice, we found that the deletion of a system x_C ^- subunit, Slc7a11, induced tumor-selective ferroptosis and inhibited PDAC growth. This was replicated through the administration of cyst(e)inase, a drug that depletes cysteine and cystine, demonstrating a translatable means to induce ferroptosis in PDAC.

SCNrank: spectral clustering for network-based ranking to reveal potential drug targets and its application in pancreatic ductal adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) is the most common pancreatic malignancy. Due to its wide heterogeneity, PDAC acts aggressively and responds poorly to most chemotherapies, causing an urgent need for the development of new therapeutic strategies. Cell lines have been used as the foundation for drug development and disease modeling. CRISPR-Cas9 plays a key role in every step-in drug discovery: from target identification and validation to preclinical cancer cell testing. Using cell-line models and CRISPR-Cas9 technology together make drug target prediction feasible. However, there is still a large gap between predicted results and actionable targets in real tumors. Biological network models provide great modus to mimic genetic interactions in real biological systems, which can benefit gene perturbation studies and potential target identification for treating PDAC. Nevertheless, building a network model that takes cell-line data and CRISPR-Cas9 data as input to accurately predict potential targets that will respond well on real tissue remains unsolved.

Methods

We developed a novel algorithm ‘Spectral Clustering for Network-based target Ranking’ (SCNrank) that systematically integrates three types of data: expression profiles from tumor tissue, normal tissue and cell-line PDAC; protein-protein interaction network (PPI); and CRISPR-Cas9 data to prioritize potential drug targets for PDAC. The whole algorithm can be classified into three steps: 1. using STRING PPI network skeleton, SCNrank constructs tissue-specific networks with PDAC tumor and normal pancreas tissues from expression profiles; 2. With the same network skeleton, SCNrank constructs cell-line-specific networks using the cell-line PDAC expression profiles and CRISPR-Cas 9 data from pancreatic cancer cell-lines; 3. SCNrank applies a novel spectral clustering approach to reduce data dimension and generate gene clusters that carry common features from both networks. Finally, SCNrank applies a scoring scheme called ‘Target Influence score’ (TI), which estimates a given target’s influence towards the cluster it belongs to, for scoring and ranking each drug target.

Results

We applied SCNrank to analyze 263 expression profiles, CRPSPR-Cas9 data from 22 different pancreatic cancer cell-lines and the STRING protein-protein interaction (PPI) network. With SCNrank, we successfully constructed an integrated tissue PDAC network and an integrated cell-line PDAC network, both of which contain 4414 selected genes that are overexpressed in tumor tissue samples. After clustering, 4414 genes are distributed into 198 clusters, which include 367 targets of FDA approved drugs. These drug targets are all scored and ranked by their TI scores, which we defined to measure their influence towards the network. We validated top-ranked targets in three aspects: Firstly, mapping them onto the existing clinical drug targets of PDAC to measure the concordance. Secondly, we performed enrichment analysis to these drug targets and the clusters there are within, to reveal functional associations between clusters and PDAC; Thirdly, we performed survival analysis for the top-ranked targets to connect targets with clinical outcomes. Survival analysis reveals that overexpression of three top-ranked genes, PGK1, HMMR and POLE2, significantly increases the risk of death in PDAC patients.

Conclusion

SCNrank is an unbiased algorithm that systematically integrates multiple types of omics data to do potential drug target selection and ranking. SCNrank shows great capability in predicting drug targets for PDAC. Pancreatic cancer-associated gene candidates predicted by our SCNrank approach have the potential to guide genetics-based anti-pancreatic drug discovery.

The A818-6 system as an in-vitro model for studying the role of the transportome in pancreatic cancer

Background

The human pancreatic cancer cell line A818–6 can be grown in vitro either as a highly malignant, undifferentiated monolayer (ML) or as three-dimensional (3D) single layer hollow spheres (HS) simulating a benign, highly differentiated, duct-like pancreatic epithelial structure. This characteristic allowing A818–6 cells to switch from one phenotype to another makes these cells a unique system to characterize the cellular and molecular modifications during differentiation on one hand and malignant transformation on the other hand. Ion channels and transport proteins (transportome) have been implicated in malignant transformation. Therefore, the current study aimed to analyse the transportome gene expression profile in the A818–6 cells growing as a monolayer or as hollow spheres.

Methods & Results

The study identified the differentially expressed transportome genes in both cellular states of A818–6 using Agilent and Nanostring arrays and some targets were validated via immunoblotting. Additionally, these results were compared to a tissue Affymetrix microarray analysis of pancreatic adenocarcinoma patients’ tissues. The overall transcriptional profile of the ML and HS cells confirmed the formerly described mesenchymal features of ML and epithelial nature of HS which was further verified via high expression of E-cadherin and low expression of vimentin found in HS in comparison to ML. Among the predicted features between HS and ML was the involvement of miRNA-9 in this switch. Importantly, the bioinformatics analysis also revealed substantial number (n = 126) of altered transportome genes. Interestingly, three genes upregulated in PDAC tissue samples (GJB2, GJB5 and SLC38A6) were found to be also upregulated in ML and 3 down-regulated transportome genes (KCNQ1, TRPV6 and SLC4A) were also reduced in ML.

Conclusion

This reversible HS/ML in vitro system might help in understanding the pathophysiological impact of the transportome in the dedifferentiation process in pancreatic carcinogenesis. Furthermore, the HS/ML model represents a novel system for studying the role of the transportome during the switch from a more benign, differentiated (HS) to a highly malignant, undifferentiated (ML) phenotype.

Potential functional variants in SMC2 and TP53 in the AURORA pathway genes and risk of pancreatic cancer

The AURORA pathway participates in mitosis and cell division, and alterations in mitosis and cell division can lead to carcinogenesis. Therefore, genetic variants in the AURORA pathway genes may be associated with susceptibility to pancreatic cancer. To test this hypothesis, we used three large publically available pancreatic cancer genome-wide association study (GWAS) datasets (PanScan I, II/III and PanC4) to assess the associations of 7168 single nucleotide polymorphisms (SNPs) in a set of 62 genes of this pathway with pancreatic cancer risk in 8477 cases and 6946 controls of European ancestry. We identify 15 significant pancreatic cancer risk-associated SNPs in three genes (SMC2, ARHGEF7 and TP53) after correction for multiple comparisons by a false discovery rate < 0.20. Through further linkage disequilibrium analysis, SNP functional prediction and stepwise logistic regression analysis, we focused on three SNPs: rs3818626 in SMC2, rs79447092 in ARHGEF7 and rs9895829 in TP53. We found that these three SNPs were associated with pancreatic cancer risk [odds ratio (OR) = 1.12, 95% confidence interval (CI) = 1.07-1.17 and P = 2.20E-06 for the rs3818626 C allele; OR = 0.76, CI = 0.66-0.88 and P = 1.46E-04 for the rs79447092 A allele and OR = 0.82, CI = 0.74-0.91 and P = 1.51E-04 for the rs9895829 G allele]. Their joint effect as the number of protective genotypes also showed a significant association with pancreatic cancer risk (trend test P ≤ 0.001). Finally, we performed an expression quantitative trait loci analysis and found that rs3818626 and rs9895829 were significantly associated with SMC2 and TP53 messenger RNA expression levels in 373 lymphoblastoid cell lines, respectively. In conclusion, these three representative SNPs may be potentially susceptibility loci for pancreatic cancer and warrant additional validation.

Synthesis of 1-benzyl-1H-benzimidazoles as galectin-1 mediated anticancer agents

In our pursuit to develop novel non-carbohydrate small molecule Galectin-1 Inhibitors, we have designed a series of 1-benzyl-1H-benzimidazole derivatives and demonstrated their anticancer activity. The compound 6g, 4-(1-benzyl-5-chloro-1H-benzo[d]imidazol-2-yl)-N-(4-hydroxyphenyl) benzamide was found to be most potent with an IC₅₀ of 7.01 ± 0.20 µM and arresting MCF-7 cell growth at G2/M phase and S phase. Induction of apoptosis was confirmed by morphological changes like cell shrinkage, blebbing and cell wall deformation, dose dependent increase in the mitochondrial membrane potential (ΔΨm) and ROS levels. Further, dose dependent decrease in Gal-1 protein levels proves Gal-1 mediated apoptosis by 6g. Molecular docking studies were performed to understand the Gal-1 interaction with compound 6g. In addition, RP-HPLC studies showed 85.44% of 6g binding to Gal-1. Binding affinity studies by fluorescence spectroscopy and Surface Plasmon Resonance (SPR) showed that 6g binds to Gal-1 with binding constant (K_a) of 1.2 × 10⁴ M^-1 and equilibrium constant K_D value of 5.76 × 10^-4 M respectively.

S100A10, a novel biomarker in pancreatic ductal adenocarcinoma

Pancreatic cancer is arguably the deadliest cancer type. The efficacy of current therapies is often hindered by the inability to predict patient outcome. As such, the development of tools for early detection and risk prediction is key for improving outcome and quality of life. Here, we introduce the plasminogen receptor S100A10 as a novel predictive biomarker and a driver of pancreatic tumor growth and invasion. We demonstrated that S100A10 mRNA and protein are overexpressed in human pancreatic tumors compared to normal ducts and nonductal stroma. S100A10 mRNA and methylation status were predictive of overall survival and recurrence-free survival across multiple patient cohorts. S100A10 expression was driven by promoter methylation and the oncogene KRAS. S100A10 knockdown reduced surface plasminogen activation, invasiveness, and in vivo growth of pancreatic cancer cell lines. These findings delineate the clinical and functional contribution of S100A10 as a biomarker in pancreatic cancer.

Pancreatic cancer subtypes: a roadmap for precision medicine

Pancreatic ductal adenocarcinoma (PDAC) is projected to become the second cause of cancer-related deaths by 2020. Although it has traditionally been approached as a disease, accumulated evidences point to the clinical heterogeneity of this disease, which translate into disparity in outcomes among the patients. Much emphasis has been put into patient classification introducing a platform for more tailored therapies. In the last 10 years, there have been important advances in the understanding of the molecular pathogenesis of PDAC, which has culminated with a comprehensive integrated genomic analysis from RNA expression profiles. Bailey et al. defined four subtypes and the different transcriptional networks underlying them. Firstly, we briefly describe and compare different subtyping approaches, which are mostly based on tissue mRNA expression analysis. We propose that these latest approaches to disease classification embrace not only those patients that are surgically resectable (20%), but even patients ineligible for surgery. Such considerations will include possible reclassification of these specific subtypes, enabling more personalized diagnosis and individualized treatment. The ultimate goal of this review is to identify current challenges in this area and summarize current efforts in developing clinical modalities that can effectively identify these subtypes in order to advance Precision Medicine. KEY MESSAGES   • Pancreatic cancer can no longer be considered as one disease.   • The heterogeneity underlying pancreatic cancer patients makes therapeutic options based on one-size-fits-all approach ineffective.   • Identifying patients that could benefit from a specific treatment would help to avoid futile therapy approaches and to improve outcomes and quality of life of those whose long-term survival is unpromising.

Large-scale clinical validation of biomarkers for pancreatic cancer using a mass spectrometry-based proteomics approach

We performed an integrated analysis of proteomic and transcriptomic datasets to develop potential diagnostic markers for early pancreatic cancer. In the discovery phase, a multiple reaction monitoring assay of 90 proteins identified by either gene expression analysis or global serum proteome profiling was established and applied to 182 clinical specimens. Nine proteins (P < 0.05) were selected for the independent validation phase and quantified using stable isotope dilution-multiple reaction monitoring-mass spectrometry in 456 specimens. Of these proteins, four proteins (apolipoprotein A-IV, apolipoprotein CIII, insulin-like growth factor binding protein 2 and tissue inhibitor of metalloproteinase 1) were significantly altered in pancreatic cancer in both the discovery and validation phase (P < 0.01). Moreover, a panel including carbohydrate antigen 19-9, apolipoprotein A-IV and tissue inhibitor of metalloproteinase 1 showed better performance for distinguishing early pancreatic cancer from pancreatitis (Area under the curve = 0.934, 86% sensitivity at fixed 90% specificity) than carbohydrate antigen 19-9 alone (71% sensitivity).

Overall, we present the panel of robust biomarkers for early pancreatic cancer diagnosis through bioinformatics analysis that combined transcriptomic and proteomic data as well as rigorous validation on a large number of independent clinical samples.

Rewiring carbohydrate catabolism differentially affects survival of pancreatic cancer cell lines with diverse metabolic profiles

An increasing body of evidence suggests that targeting cellular metabolism represents a promising effective approach to treat pancreatic cancer, overcome chemoresistance and ameliorate patient's prognosis and survival. In this study, following whole-genome expression analysis, we selected two pancreatic cancer cell lines, PANC-1 and BXPC-3, hallmarked by distinct metabolic profiles with specific concern to carbohydrate metabolism. Functional comparative analysis showed that BXPC-3 displayed a marked deficit of the mitochondrial respiratory and oxidative phosphorylation activity and a higher production of reactive oxygen species and a reduced NAD⁺/NADH ratio, indicating their bioenergetic reliance on glycolysis and a different redox homeostasis as compared to PANC-1. Both cell lines were challenged to rewire their metabolism by substituting glucose with galactose as carbon source, a condition inhibiting the glycolytic flux and fostering full oxidation of the sugar carbons. The obtained data strikingly show that the mitochondrial respiration-impaired-BXPC-3 cell line was unable to sustain the metabolic adaptation required by glucose deprivation/substitution, thereby resulting in a G2\M cell cycle shift, unbalance of the redox homeostasis, apoptosis induction. Conversely, the mitochondrial respiration-competent-PANC-1 cell line did not show clear evidence of cell sufferance. Our findings provide a strong rationale to candidate metabolism as a promising target for cancer therapy. Defining the metabolic features at time of pancreatic cancer diagnosis and likely of other tumors, appears to be crucial to predict the responsiveness to therapeutic approaches or coadjuvant interventions affecting metabolism.

Identification and Validation of a Diagnostic and Prognostic Multi-Gene Biomarker Panel for Pancreatic Ductal Adenocarcinoma

Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clustering on co-expression values revealed four distinct clusters with genes originating from exocrine/endocrine pancreas, stromal and tumor cells. Three clusters were strongly associated with survival of PDAC patients based on TCGA database underlining the prognostic potential of the identified genes. With the added information of impact of survival and the robustness within the meta-analysis, we extracted a 17-gene subset for further validation. We show that it did not only discriminate PDAC from non-tumor tissue and stroma in fresh-frozen as well as formalin-fixed paraffin embedded samples, but also detected pancreatic precursor lesions and singled out pancreatitis samples. Moreover, the classifier discriminated PDAC from other cancers in the TCGA database. In addition, we experimentally validated the classifier in PDAC patients on transcript level using qPCR and exemplify the usage on protein level for three proteins (AHNAK2, LAMC2, TFF1) using immunohistochemistry and for two secreted proteins (TFF1, SERPINB5) using ELISA-based protein detection in blood-plasma. In conclusion, we present a novel robust diagnostic and prognostic gene signature for PDAC with future potential applicability in the clinic.

Tumor-reducing effect of the clinically used drug clofazimine in a SCID mouse model of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) represents the most common form of pancreatic cancer with rising incidence in developing countries. Unfortunately, the overall 5-year survival rate is still less than 5%. The most frequent oncogenic mutations in PDAC are loss-of function mutations in p53 and gain-of-function mutations in KRAS. Here we show that clofazimine (Lamprene), a drug already used in the clinic for autoimmune diseases and leprosy, is able to efficiently kill in vitro five different PDAC cell lines harboring p53 mutations. We provide evidence that clofazimine induces apoptosis in PDAC cells with an EC₅₀ in the μM range via its specific inhibitory action on the potassium channel Kv1.3. Intraperitoneal injection of clofazimine resulted in its accumulation in the pancreas of mice 8 hours after administration. Using an orthotopic PDAC xenotransplantation model in SCID beige mouse, we show that clofazimine significantly and strongly reduced the primary tumor weight. Thus, our work identifies clofazimine as a promising therapeutic agent against PDAC and further highlights ion channels as possible oncological targets.

The emerging role of galectins in high-fatality cancers

Although we witnessed considerable progress in the prevention and treatment of cancer during the past few decades, a number of cancers remain difficult to treat. The main reasons for this are a lack of effective biomarkers necessary for an early detection and inefficient treatments for cancer that are diagnosed at late stages of the disease. Because of their alarmin-like properties and their protumorigenic role during cancer progression, members of the galectin family are uniquely positioned to provide information that could be used for the exploration of possible avenues for the treatment of high fatality cancer (HFC). A rapid overview of studies that examined the expressions and functions of galectins in cancer cells reveals that they play a central role in at least three major features that characterize HFCs: (1) induction of systemic and local immunosuppression, (2) chemoresistance of cancer cells, and (3) increased invasive behavior. Defining the galectinome in HFCs will also lead to a better understanding of tumor heterogeneity while providing critical information that could improve the accuracy of biomarker panels for a more personalized treatment of HFCs. In this review, we discuss the relevance of the galectinome in HFC and its possible contribution to providing potential solutions.

Prognostic value of PDL1 expression in pancreatic cancer

Pancreatic cancer is one of the most aggressive human cancers. PD1/PDL1-inhibitors recently showed promising results in different cancers with correlation between PDL1 tumor expression and responses. Expression of programmed cell death receptor ligand 1 (PDL1) has been scarcely studied in pancreatic cancer. In this retrospective study, we analyzed PDL1 mRNA expression in 453 clinical pancreatic cancer samples profiled using DNA microarrays and RNASeq. Compared to normal pancreatic samples, PDL1 expression was upregulated in 19% of cancer samples. Upregulation was not associated with clinicopathological features such as patients' age and sex, pathological type, tumor size, lymph node status, and grade, but was associated with shorter disease-free survival and overall survival in multivariate analyses. Analysis of correlations with biological parameters showed that PDL1 upregulation was associated with some degree of lymphocyte infiltration and signs of anti-tumor T-cell response, but to a lesser extent than what has been reported in breast cancer and GIST. PDL1-up pancreatic cancers displayed profiles of lymphocyte exhaustion, were more enriched in inhibitory molecules and pro-tumor populations (Tregs with upregulation of FOXP3 and IL10, myeloid-derived suppressor cells with upregulation of CD33 and S100A8/A9), and demonstrated a down-modulation of most MHC class I members (HLA-A/B/C, HLA-E/F/G) suggestive of a defect in antigen processing and presentation. In conclusion, our results suggest that PDL1 expression might refine the prediction of metastatic relapse in operated pancreatic cancer, and that PD1/PDL1 inhibitors might reactivate inhibited T-cells to increase the anti-tumor immune response in PDL1-upregulated tumors.

Ten hub genes associated with progression and prognosis of pancreatic carcinoma identified by co-expression analysis

Since the five-year survival rate is less than 5%, pancreatic ductal adenocarcinoma (PDAC) remains the 4th cause of cancer-related death. Although PDAC has been repeatedly researched in recent years, it is still predicted to be the second leading cause of cancer death by year 2030. In our study, the differentially expressed genes in dataset GSE62452 were used to construct a co-expression network by WGCNA. The yellow module related to grade of PDAC was screened. Combined with co-expression network and PPI network, 36 candidates were screened. After survival and regression analysis by using GSE62452 and TCGA dataset, we identified 10 real hub genes (CCNA2, CCNB1, CENPF, DLGAP5, KIF14, KIF23, NEK2, RACGAP1, TPX2 and UBE2C) tightly related to progression of PDAC. According to Oncomine database and The Human Protein Atlas (HPA), we found that all real hub genes were overexpressed in pancreatic carcinoma compared with normal tissues on transcriptional and translational level. ROC curve was plotted and AUC was calculated to distinguish recurrent and non-recurrent PDAC and every AUC of the real hub gene was greater than 0.5. Finally, functional enrichment analysis and gene set enrichment (GSEA) was performed and both of them showed the cell cycle played a vital role in PDAC.

ITGA1 is a pre-malignant biomarker that promotes therapy resistance and metastatic potential in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) has single-digit 5-year survival rates at <7%. There is a dire need to improve pre-malignant detection methods and identify new therapeutic targets for abrogating PDAC progression. To this end, we mined our previously published pseudopodium-enriched (PDE) protein/phosphoprotein datasets to identify novel PDAC-specific biomarkers and/or therapeutic targets. We discovered that integrin alpha 1 (ITGA1) is frequently upregulated in pancreatic cancers and associated precursor lesions. Expression of ITGA1-specific collagens within the pancreatic cancer microenvironment significantly correlates with indicators of poor patient prognosis, and depleting ITGA1 from PDAC cells revealed that it is required for collagen-induced tumorigenic potential. Notably, collagen/ITGA1 signaling promotes the survival of ALDH1-positive stem-like cells and cooperates with TGFβ to drive gemcitabine resistance. Finally, we report that ITGA1 is required for TGFβ/collagen-induced EMT and metastasis. Our data suggest that ITGA1 is a new diagnostic biomarker and target that can be leveraged to improve patient outcomes.

Paraoxonase 2 Facilitates Pancreatic Cancer Growth and Metastasis by Stimulating GLUT1-Mediated Glucose Transport

Metabolic deregulation is a hallmark of human cancers, and the glycolytic and glutamine metabolism pathways were shown to be deregulated in pancreatic ductal adenocarcinoma (PDAC). To identify new metabolic regulators of PDAC tumor growth and metastasis, we systematically knocked down metabolic genes that were overexpressed in human PDAC tumor samples using short hairpin RNAs. We found that p53 transcriptionally represses paraoxonase 2 (PON2), which regulates GLUT1-mediated glucose transport via stomatin. The loss of PON2 initiates the cellular starvation response and activates AMP-activated protein kinase (AMPK). In turn, AMPK activates FOXO3A and its transcriptional target, PUMA, which induces anoikis to suppress PDAC tumor growth and metastasis. Pharmacological or genetic activation of AMPK, similar to PON2 inhibition, blocks PDAC tumor growth. Collectively, our results identify PON2 as a new modulator of glucose transport that regulates a pharmacologically tractable pathway necessary for PDAC tumor growth and metastasis.

Contribution of galectin-1, a glycan-binding protein, to gastrointestinal tumor progression

Gastrointestinal cancer is a group of tumors that affect multiple sites of the digestive system, including the stomach, liver, colon and pancreas. These cancers are very aggressive and rapidly metastasize, thus identifying effective targets is crucial for treatment. Galectin-1 (Gal-1) belongs to a family of glycan-binding proteins, or lectins, with the ability to cross-link specific glycoconjugates. A variety of biological activities have been attributed to Gal-1 at different steps of tumor progression. Herein, we summarize the current literature regarding the roles of Gal-1 in gastrointestinal malignancies. Accumulating evidence shows that Gal-1 is drastically up-regulated in human gastric cancer, hepatocellular carcinoma, colorectal cancer and pancreatic ductal adenocarcinoma tissues, both in tumor epithelial and tumor-associated stromal cells. Moreover, Gal-1 makes a crucial contribution to the pathogenesis of gastrointestinal malignancies, favoring tumor development, aggressiveness, metastasis, immunosuppression and angiogenesis. We also highlight that alterations in Gal-1-specific glycoepitopes may be relevant for gastrointestinal cancer progression. Despite the findings obtained so far, further functional studies are still required. Elucidating the precise molecular mechanisms modulated by Gal-1 underlying gastrointestinal tumor progression, might lead to the development of novel Gal-1-based diagnostic methods and/or therapies.

ZNF281 Promotes Growth and Invasion of Pancreatic Cancer Cells by Activating Wnt/β-Catenin Signaling

BACKGROUND

Zinc finger protein 281 (ZNF281) has been identified to be involved in embryonic stem cell differentiation and tissue development. Also, ZNF281 was found in various types of cancers. However, its biological functions and clinical significance in pancreatic cancer remain elusive.

AIMS

To explore the role of ZNF281 in pancreatic cancer cells proliferation and invasion.

METHODS

ZNF281 expression was examined in public database Oncomine and cBioPortal. The correlation between ZNF281 and clinicopathological features was measured, and Kaplan-Meier method was used to measure the overall survival and recurrence-free survival in the TCGA cohort. Ectopic expression and knockdown of ZNF281 were performed to measure the impact on cell proliferation and invasion. Western blot and immunoprecipitation were further used to identify the ZNF281 interacting proteins. Topflash luciferase assay was used to detect the Wnt/β-catenin signaling activation.

RESULTS

ZNF281 was predominantly up-regulated in pancreatic cancer tissues and significantly associated with advanced stage. Meanwhile, the high expression of ZNF281 indicated shorter overall survival and recurrence-free survival and ZNF281 could be an independent prognostic factor of pancreatic cancer. ZNF281 promoted cell proliferation and invasion in vitro. Mechanically, ZNF281 activated Wnt/β-catenin signaling and induced the downstream gene expression by directly binding with β-catenin and decreasing the polyubiquitination.

CONCLUSIONS

ZNF281 promotes pancreatic cancer cells proliferation and invasion by interacting and up-regulating β-catenin, highlighting the role of ZNF281 in pancreatic cancer progression.

Molecular Subtyping of Pancreatic Cancer: Translating Genomics and Transcriptomics into the Clinic

Pancreatic cancer remains one of the most lethal malignancies, and insights into both personalized diagnosis and intervention of this disease are urgently needed. The rapid development of sequencing technologies has enabled the successive completion of a series of genetic and epigenetic sequencing studies of pancreatic cancer. The mutational landscape of pancreatic cancer is generally portrayed in terms of somatic mutations, structural variations, epigenetic alterations and the core signaling pathways. In recent years, four significant molecular subtype classifications of pancreatic cancer have been proposed based on the expression of transcription factors and downstream targets or the distribution of structural rearrangements. Increasing researches focus on the identification of somatic mutations and other genetic aberrations that drive pancreatic cancer has led to a new era of precision medicine based on molecular subtyping. However, few known molecular classifications are used to guide clinical strategies. Specific scientific, regulatory and ethical challenges must be overcome before genomic and transcriptomic discoveries can be translated into the clinic.

The G Protein-Coupled Receptor RAI3 Is an Independent Prognostic Factor for Pancreatic Cancer Survival and Regulates Proliferation via STAT3 Phosphorylation

Pancreatic Ductal Adenocarcinoma (PDAC) is one of the deadliest tumors worldwide. Understanding the function of gene expression alterations is a prerequisite for developing new strategies in diagnostic and therapy. GPRC5A (RAI3), coding for a seven transmembrane G protein-coupled receptor is known to be overexpressed in pancreatic cancer and might be an interesting candidate for therapeutic intervention. Expression levels of RAI3 were compared using a tissue microarray of 435 resected patients with pancreatic cancer as well as 209 samples from chronic pancreatitis (CP), intra-ductal papillary mucinous neoplasm (IPMN) and normal pancreatic tissue. To elucidate the function of RAI3 overexpression, siRNA based knock-down was used and transfected cells were analyzed using proliferation and migration assays. Pancreatic cancer patients showed a statistically significant overexpression of RAI3 in comparison to normal and chronic pancreatitis tissue. Especially the loss of apical RAI3 expression represents an independent prognostic parameter for overall survival of patients with pancreatic cancer. Suppression of GPRC5a results in decreased cell growth, proliferation and migration in pancreatic cancer cell lines via a STAT3 modulated pathway, independent from ERK activation.