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Abstract Pancreatic cancer (PC) is a clinically challenging tumor to combat due to its advanced stage at diagnosis as well as its resistance to currently available therapies. The absence of early symptoms and known detectable biomarkers renders this disease incredibly difficult to detect/manage. Recent advances in the understanding of PC biology have highlighted the importance of cancer-immune cell interactions, not only in the tumor micro-environment but also in distant systemic sites, like the bone marrow, spleen and circulating immune cells, the so-called macro-environment. The response of the macro-environment is emerging as a determining factor in tumor development by contributing to the formation of an increasingly immunogenic micro-environment promoting tumor homeostasis and progression. We will summarize the key events associated with the feedback loop between the tumor immune micro-environment (TIME) and the tumor immune macroenvironment (TIMaE) in pancreatic precancerous lesions along with how it regulates disease development and progression. In addition, liquid biopsy biomarkers capable of diagnosing PC at an early stage of onset will also be discussed. A clearer understanding of the early crosstalk between micro-environment and macro-environment could contribute to identifying new molecular therapeutic targets and biomarkers, consequently improving early PC diagnosis and treatment.

Abstract Pancreatic cancer is a malignant tumor of the digestive system. It is highly aggressive, easily metastasizes, and extremely difficult to treat. This study aimed to analyze the genes that might regulate pancreatic cancer migration to provide an essential basis for the prognostic assessment of pancreatic cancer and individualized treatment. A CRISPR knockout library directed against 915 murine genes was transfected into TB 32047 cell line to screen which gene loss promoted cell migration. Next-generation sequencing and PinAPL.py- analysis was performed to identify candidate genes. We then assessed the effect of serine/threonine kinase 11 (STK11) knockout on pancreatic cancer by wound-healing assay, chick agnosia (CAM) assay, and orthotopic mouse pancreatic cancer model. We performed RNA sequence and Western blotting for mechanistic studies to identify and verify the pathways. After accelerated Transwell migration screening, STK11 was identified as one of the top candidate genes. Further experiments showed that targeted knockout of STK11 promoted the cell migration and increased liver metastasis in mice. Mechanistic analyses revealed that STK11 knockout influences blood vessel morphogenesis and is closely associated with the enhanced expression of phosphodiesterases (PDEs), especially PDE4D, PDE4B, and PDE10A. PDE4 inhibitor Roflumilast inhibited STK11-KO cell migration and tumor size, further demonstrating that PDEs are essential for STK11-deficient cell migration. Our findings support the adoption of therapeutic strategies, including Roflumilast, for patients with STK11-mutated pancreatic cancer in order to improve treatment efficacy and ultimately prolong survival.

Interleukin (IL)-3 has long been known for its hematopoietic properties. However, recent evidence has expanded our understanding of IL-3 function by identifying IL-3 as a critical orchestrator of inflammation in a wide array of diseases. Depending on the type of disease, the course of inflammation, the cell or the tissue involved, IL-3 promotes either pathologic inflammation or its resolution. Here, we describe the cell-specific functions of IL-3 and summarize its role in diseases. We discuss the current treatments targeting IL-3 or its receptor, and highlight the potential and the limitations of targeting IL-3 in clinics.

Abstract Background Integrating multi-omics data is fast becoming a powerful approach for predicting disease progression and treatment outcomes. In light of that, we introduce a modified version of the NetRank algorithm, a network-based algorithm for biomarker discovery that incorporates the protein associations, co-expressions, and functions with its phenotypic association to differentiate different types of cancer. NetRank is introduced here as a robust feature selection method for biomarker selection in cancer prediction. We assess the robustness and suitability of the RNA gene expression data through scanning genomic data for 19 cancer types with more than 3000 patients from The Cancer Genome Atlas (TCGA). Results The results of evaluating different cancer type profiles from the TCGA data demonstrate the strength of our approach to identifying interpretable biomarker signatures for cancer outcome prediction. NetRank’s biomarkers segregate most cancer types with an area under the curve (AUC) above 90% using compact signatures. Conclusion In this paper we provide a fast and efficient implementation of NetRank, with a case study from The Cancer Genome Atlas, to assess the performance. We incorporated complete functionality for pre and post-processing for RNA-seq gene expression data with functions for building protein-protein interaction networks. The source code of NetRank is freely available (at github.com/Alfatlawi/Omics-NetRank) with an installable R library. We also deliver a comprehensive practical user manual with examples and data attached to this paper.

Abstract Background The prognosis of pancreatic ductal adenocarcinoma (PDAC) is one of the most dismal of all cancers and the median survival of PDAC patients is only 6–8 months after diagnosis. While decades of research effort have been focused on early diagnosis and understanding of molecular mechanisms, few clinically useful markers have been universally applied. To improve the treatment and management of PDAC, it is equally relevant to identify prognostic factors for optimal therapeutic decision-making and patient survival. Compelling evidence have suggested the potential use of extracellular vesicles (EVs) as non-invasive biomarkers for PDAC. The aim of this study was thus to identify non-invasive plasma-based EV biomarkers for the prediction of PDAC patient survival after surgery. Methods Plasma EVs were isolated from a total of 258 PDAC patients divided into three independent cohorts (discovery, training and validation). RNA sequencing was first employed to identify differentially-expressed EV mRNA candidates from the discovery cohort (n = 65) by DESeq2 tool. The candidates were tested in a training cohort (n = 91) by digital droplet polymerase chain reaction (ddPCR). Cox regression models and Kaplan–Meier analyses were used to build an EV signature which was subsequently validated on a multicenter cohort (n = 83) by ddPCR. Results Transcriptomic profiling of plasma EVs revealed differentially-expressed mRNAs between long-term and short-term PDAC survivors, which led to 10 of the top-ranked candidate EV mRNAs being tested on an independent training cohort with ddPCR. The results of ddPCR enabled an establishment of a novel prognostic EV mRNA signature consisting of PPP1R12A, SCN7A and SGCD for risk stratification of PDAC patients. Based on the EV mRNA signature, PDAC patients with high risk displayed reduced overall survival (OS) rates compared to those with low risk in the training cohort (p = 0.014), which was successfully validated on another independent cohort (p = 0.024). Interestingly, the combination of our signature and tumour stage yielded a superior prognostic performance (p = 0.008) over the signature (p = 0.022) or tumour stage (p = 0.016) alone. It is noteworthy that the EV mRNA signature was demonstrated to be an independent unfavourable predictor for PDAC prognosis. Conclusion This study provides a novel and non-invasive prognostic EV mRNA signature for risk stratification and survival prediction of PDAC patients.

Abstract Pancreatic Ductal Adenocarcinoma (PDAC) is estimated to become the second leading cause of cancer-related deaths by 2030 with mortality rates of up to 93%. Standard of care chemotherapeutic treatment only prolongs the survival of patients for a short timeframe. Therefore, it is important to understand events driving treatment failure in PDAC as well as identify potential more effective treatment opportunities. PDAC is characterized by a high-density stroma, high interstitial pressure and very low oxygen tension. The aim of this study was to establish a PDAC platform that supported the understanding of treatment response of PDAC organoids in mono-, and co-culture with pancreatic stellate cells (PSCs) under hypoxic and normoxic conditions. Cultures were exposed to Gemcitabine in combination with molecules targeting relevant molecular programs that could explain treatment specific responses under different oxygen pressure conditions. Two groups of treatment responses were identified, showing either a better effect in monoculture or co-culture. Moreover, treatment response also differed between normoxia and hypoxia. Modulation of response to Gemcitabine was also observed in presence of a Hypoxia-inducible factor (HIF) prolyl hydroxylase (PHD) inhibitor and HIF inhibitors. Altogether this highlights the importance of adjusting experimental conditions to include relevant oxygen levels in drug response studies in PDAC.

IntroductionImmune checkpoint inhibitors (ICI), e.g., targeting programmed cell death protein 1-ligand 1 (PD-L1) or its receptor PD-1, have markedly improved the therapy of many cancers but so far failed in pancreatic ductal adenocarcinoma (PDAC). Macrophages represent one of the most abundant immune cell populations within the tumor microenvironment (TME) of PDAC being able to either support or restrain tumor progression depending on their phenotype. To better understand treatment failure of PD-L1/PD-1 inhibitors in PDAC, this study examined PD-L1 expression in the context of a dynamic TME in PDAC with a particular focus on the impact of macrophages.MethodsFormalin-fixed and paraffin embedded tissue samples of primary PDAC tissues and corresponding liver metastases were used for immunohistochemical analyses. Serial sections were stained with antibodies detecting Pan-Cytokeratin, CD68, CD163, CD8, and PD-L1.To investigate whether the PD-1/PD-L1 axis and macrophages contribute to immune escape of PDAC cells, a stroma enriched 3D spheroid coculture model was established in vitro, using different PDAC cell lines and macrophages subtypes as well as CD8+ T cells. Functional and flow cytometry analyses were conducted to characterize cell populations.ResultsImmunohistochemical analyses revealed that PD-L1 is mainly expressed by stroma cells, including macrophages and not PDAC cells in primary PDAC tissues and corresponding liver metastases. Notably, high local abundance of macrophages and strong PD-L1 staining were commonly found at invasion fronts of tumoral lesions between CD8+ T cells and tumor cells. In order to investigate whether PD-L1 expressing macrophages impact the response of PDAC cells to treatment with PD-L1/PD-1 inhibitors, we developed a spheroid model comprising two different PDAC cell lines and different ratios of in vitro differentiated primary M1- or M2-like polarized macrophages. In line with our in situ findings, high PD-L1 expression was observed in macrophages rather than PDAC cells, which was further increased by the presence of PDAC cells. The effector phenotype of co-cultured CD8+ T cells exemplified by expression of activation markers and release of effector molecules was rather enhanced by PDAC macrophage spheroids, particularly with M1-like macrophages compared to mono-culture spheroids. However, this was not associated with enhanced PDAC cell death. ICI treatment with either Durvalumab or Pembrolizumab alone or in combination with Gemcitabine hardly affected the effector phenotype of CD8+ T cells along with PDAC cell death. Thus, despite strong PD-L1 expression in macrophages, ICI treatment did not result in an enhanced activation and cytotoxic phenotype of CD8+ T cells.ConclusionOverall, our study revealed novel insights into the interplay of PDAC cells and macrophages in the presence of ICI.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with a dismal prognosis. Although combined treatment with gemcitabine and albumin-bound paclitaxel has improved the prognosis of PDAC, both intrinsic and acquired chemoresistance remain as severe hurtles towards improved prognosis. Thus, new therapeutic targets and innovative strategies are urgently needed. Methods In this study, we used the KPC mouse model-derived PDAC cell line TB32047 to perform kinome-wide CRISPR-Cas9 loss-of-function screening. Next-generation sequencing and MAGeCK-VISPR analysis were performed to identify candidate genes. We then conducted cell viability, clonogenic, and apoptosis assays and evaluated the synergistic therapeutic effects of cyclin-dependent kinase 7 (CDK7) depletion or inhibition with gemcitabine (GEM) and paclitaxel (PTX) in a murine orthotopic pancreatic cancer model. For mechanistic studies, we performed genome enrichment analysis (GSEA) and Western blotting to identify and verify the pathways that render PDAC sensitive to GEM/PTX therapy. Results We identified several cell cycle checkpoint kinases and DNA damage-related kinases as targets for overcoming chemoresistance. Among them, CDK7 ranked highly in both screenings. We demonstrated that both gene knockout and pharmacological inhibition of CDK7 by THZ1 result in cell cycle arrest, apoptosis induction, and DNA damage at least predominantly through the STAT3-MCL1-CHK1 axis. Furthermore, THZ1 synergized with GEM and PTX in vitro and in vivo, resulting in enhanced antitumor effects. Conclusions Our findings support the application of CRISPR-Cas9 screening in identifying novel therapeutic targets and suggest new strategies for overcoming chemoresistance in pancreatic cancer.

Abstract The inherent heterogeneity of individual cells in cell populations plays significant roles in disease development and progression, which is critical for disease diagnosis and treatment. Substantial evidences show that the majority of traditional gene profiling methods mask the difference of individual cells. Single cell sequencing can provide data to characterize the inherent heterogeneity of individual cells, and reveal complex and rare cell populations. Different microfluidic technologies have emerged for single cell researches and become the frontiers and hot topics over the past decade. In this review article, we introduce the processes of single cell sequencing, and review the principles of microfluidics for single cell analysis. Also, we discuss the common high-throughput single cell sequencing technologies along with their advantages and disadvantages. Lastly, microfluidics applications in single cell sequencing technology for the diagnosis of cancers and immune system diseases are briefly illustrated.

Abstract Background The identification of novel targets is of paramount importance to develop more effective drugs and improve the treatment of non-small cell lung cancer (NSCLC), the leading cause of cancer-related deaths worldwide. Since cells alter their metabolic rewiring during tumorigenesis and along cancer progression, targeting key metabolic players and metabolism-associated proteins represents a valuable approach with a high therapeutic potential. Metabolic fitness relies on the functionality of heat shock proteins (HSPs), molecular chaperones that facilitate the correct folding of metabolism enzymes and their assembly in macromolecular structures. Methods Gene fitness was determined by bioinformatics analysis from available datasets from genetic screenings. HSPD1 expression was evaluated by immunohistochemistry from formalin-fixed paraffin-embedded tissues from NSCLC patients. Real-time proliferation assays with and without cytotoxicity reagents, colony formation assays and cell cycle analyses were used to monitor growth and drug sensitivity of different NSCLC cells in vitro. In vivo growth was monitored with subcutaneous injections in immune-deficient mice. Cell metabolic activity was analyzed through extracellular metabolic flux analysis. Specific knockouts were introduced by CRISPR/Cas9. Results We show heat shock protein family D member 1 (HSPD1 or HSP60) as a survival gene ubiquitously expressed in NSCLC and associated with poor patients’ prognosis. HSPD1 knockdown or its chemical disruption by the small molecule KHS101 induces a drastic breakdown of oxidative phosphorylation, and suppresses cell proliferation both in vitro and in vivo. By combining drug profiling with transcriptomics and through a whole-genome CRISPR/Cas9 screen, we demonstrate that HSPD1-targeted anti-cancer effects are dependent on oxidative phosphorylation and validated molecular determinants of KHS101 sensitivity, in particular, the creatine-transporter SLC6A8 and the subunit of the cytochrome c oxidase complex COX5B. Conclusions These results highlight mitochondrial metabolism as an attractive target and HSPD1 as a potential theranostic marker for developing therapies to combat NSCLC.

Pancreatic ductal adenocarcinoma (PDAC) is the most aggressive digestive malignancy due to frequent late-stage diagnosis, rapid progression and resistance to therapy. With increasing PDAC incidence worldwide, there is an urgent need for new prognostic biomarkers and therapy targets. Recently, RNA methylation has emerged as a new tumorigenic mechanism in different cancers. 5-methylcytosine (m5C) is one of the most frequent RNA modifications and occurs on a variety of RNA species including mRNA, thereby regulating gene expression. Here we investigated the prognostic role of m5C-regulator-associated transcriptional signature in PDAC. We evaluated m5C-regulator status and expression in 239 PDAC samples from publicly available datasets. We used unsupervised consensus clustering analyses to classify PDACs based on m5C-regulator expression. From the resulting signature of differentially expressed genes (DEGs), we selected prognosis-relevant DEGs to stratify patients and build a scoring signature (m5C-score) through LASSO and multivariate Cox regression analyses. The m5C-score represented a highly significant independent prognostic marker. A high m5C-score correlated with poor prognosis in different PDAC cohorts, and was associated with the squamous/basal subtype as well as activated cancer-related pathways including Ras, MAPK and PI3K pathways. Furthermore, the m5C-score correlated with sensitivity to pathway-specific inhibitors of PARP, EGFR, AKT, HER2 and mTOR. Tumors with high m5C-score were characterized by overall immune exclusion, low CD8+ T-cell infiltration, and higher PD-L1 expression. Overall, the m5C-score represented a robust predictor of prognosis and therapy response in PDAC, which was associated with unfavorable molecular subtypes and immune microenvironment.

Cancer becomes one of the main causes of human deaths in the world due to the high incidence and mortality rate and produces serious economic burdens. With more and more attention is paid on cancer, its therapies are getting more of a concern. Previous research has shown that the occurrence, progression, and treatment prognosis of malignant tumors are closely related to genetic and gene mutation. CRISPR/Cas9 has emerged as a powerful method for making changes to the genome, which has extensively been applied in various cell lines. Establishing the cell and animal models by CRISPR/Cas9 laid the foundation for the clinical trials which possibly treated the tumor. CRISPR-Cas9-mediated genome editing technology brings a great promise for inhibiting migration, invasion, and even treatment of tumor. However, the potential off-target effect limits its clinical application, and the effective ethical review is necessary. The article reviews the molecular mechanisms of CRISPR/Cas9 and discusses the research and the limitation related to cancer clinical trials.

With the continuous development of drug screening technology, new screening methodologies and technologies are constantly emerging, driving drug screening into rapid, efficient and high-throughput development. Microfluidics is a rising star in the development of innovative approaches in drug discovery. In this article, we summarize the recent years' progress of microfluidic chip technology in drug screening, including the developmental history, structural design, and applications in different aspects of microfluidic chips on drug screening. Herein, the existing microfluidic chip screening platforms are summarized from four aspects: chip structure design, sample injection and drive system, cell culture technology on a chip, and efficient remote detection technology. Furthermore, this review discusses the application and developmental prospects of using microfluidic chips in drug screening, particularly in screening natural product anticancer drugs based on chemical properties, pharmacological effects, and drug cytotoxicity.

Pancreatic ductal adenocarcinoma (PDAC) is a hostile solid malignancy coupled with an extremely high mortality rate. Metastatic disease is already found in most patients at the time of diagnosis, resulting in a 5-year survival rate below 5%. Improved comprehension of the mechanisms leading to metastasis is pivotal for the development of new targeted therapies. A key field to be improved are modeling strategies applied in assessing cancer progression, since traditional platforms fail in recapitulating the complexity of PDAC. Consequently, there is a compelling demand for new preclinical models that mirror tumor progression incorporating the pressure of the immune system, tumor microenvironment, as well as molecular aspects of PDAC. We suggest the incorporation of 3D organoids derived from genetically engineered mouse models or patients as promising new tools capable to transform PDAC pre-clinical modeling and access new frontiers in personalized medicine.

Objective: MicroRNAs (miRNAs) play an integral role in maintaining beta cell function and identity. Deciphering their targets and precise role, however, remains challenging. In this study, we aimed to identify miRNAs and their downstream targets involved in the regeneration of islet beta cells following partial pancreatectomy in mice. Methods: RNA from laser capture microdissected (LCM) islets of partially pancreatectomized and sham-operated mice were profiled with microarrays to identify putative miRNAs implicated in beta cell regeneration. Altered expression of the selected miRNAs, including miR-132, was verified by RT-PCR. Potential targets of miR-132 were selected through bioinformatic data mining. Predicted miR-132 targets were validated for their changed RNA, protein expression levels, and signaling upon miR-132 knockdown and/or overexpression in mouse MIN6 and human EndoC-βH1 insulinoma cells. The ability of miR-132 to foster beta cell proliferation in vivo was further assessed in pancreatectomized miR-132−/− and control mice. Results: Partial pancreatectomy significantly increased the number of BrdU+/insulin+ islet cells. Microarray profiling revealed that 14 miRNAs, including miR-132 and -141, were significantly upregulated in the LCM islets of the partially pancreatectomized mice compared to the LCM islets of the control mice. In the same comparison, miR-760 was the only downregulated miRNA. The changed expression of these miRNAs in the islets of the partially pancreatectomized mice was confirmed by RT-PCR only in the case of miR-132 and -141. Based on previous knowledge of its function, we focused our attention on miR-132. Downregulation of miR-132 reduced the proliferation of MIN6 cells while enhancing the levels of pro-apoptotic cleaved caspase-9. The opposite was observed in miR-132 overexpressing MIN6 cells. Microarray profiling, RT-PCR, and immunoblotting of the latter cells demonstrated their downregulated expression of Pten with concomitant increased levels of pro-proliferative factors phospho-Akt and phospho-Creb and inactivation of pro-apoptotic Foxo3a via its phosphorylation. Downregulation of Pten was further confirmed in the LCM islets of pancreatectomized mice compared to the sham-operated mice. Moreover, overexpression of miR-132 correlated with increased proliferation of EndoC-βH1 cells. The regeneration of beta cells following partial pancreatectomy was lower in the miR-132/212−/− mice than the control littermates. Conclusions: This study provides compelling evidence about the critical role of miR-132 for the regeneration of mouse islet beta cells through the downregulation of its target Pten. Hence, the miR-132/Pten/Akt/Foxo3 signaling pathway may represent a suitable target to enhance beta cell mass. Keywords: miR-132, β cell regeneration, Apoptosis, Pten/Akt/Foxo3a, Pancreatectomy

Exosomes are lipid-bilayer enclosed vesicles with diameters of 30–150 nm, which play a pivotal role in cell communication by transporting their cargoes such as proteins, lipids, and genetic materials. In recent years, exosomes have been under intense investigation, as they show great promise in numerous areas, especially as bio-markers in liquid biopsies. However, due to the high heterogeneity and the nano size of exosomes, the separation of exosomes is not easy. This review will deliver an outline of the conventional methods and the microfluidic-based technologies for exosome separation. Particular attention is devoted to microfluidic devices, highlighting the efficiency of exosome isolation by these methods. Additionally, this review will introduce advances made in the integrated microfluidics technologies that enable the separation and analysis of exosomes.

Background: Cytosolic 5′-nucleotidase 1A (NT5C1A) dephosphorylates non-cyclic nucleoside monophosphates to produce nucleosides and inorganic phosphates. Here, we investigate NT5C1A expression in pancreatic ductal adenocarcinoma (PDAC) and its impact on gemcitabine metabolism and therapeutic efficacy. Methods: NT5C1A expression was determined by semiquantitative immunohistochemistry using tissue microarrays. Gemcitabine metabolites and response were assessed in several human and murine PDAC cell lines using crystal violet assays, Western blot, viability assays, and liquid chromatography tandem mass-spectrometry (LC-MS/MS). Findings: NT5C1A was strongly expressed in tumor cells of a large subgroup of resected PDAC patients in two independent patient cohorts (44–56% score 2 and 8–26% score 3, n = 414). In contrast, NT5C1A was expressed at very low levels in the tumor stroma, and neither stromal nor tumoral expression was a prognostic marker for postoperative survival. In vitro, NT5C1A overexpression increased gemcitabine resistance by reducing apoptosis levels and significantly decreased intracellular amounts of cytotoxic dFdCTP in +NT5C1A tumor cells. Co-culture experiments with conditioned media from +NT5C1A PSCs improved gemcitabine efficacy in tumor cells. In vivo, therapeutic efficacy of gemcitabine was significantly decreased and serum levels of the inactive gemcitabine metabolite dFdU significantly increased in mice bearing NT5C1A overexpressing tumors. Interpretation: NT5C1A is robustly expressed in tumor cells of resected PDAC patients. Moreover, NT5C1A mediates gemcitabine resistance by decreasing the amount of intracellular dFdCTP, leading to reduced tumor cell apoptosis and larger pancreatic tumors in mice. Further studies should clarify the role of NT5C1A as novel predictor for gemcitabine treatment response in patients with PDAC. Keywords: Cytosolic 5′-nucleotidase 1A, Chemotherapeutic resistance, Gemcitabine, Pancreatic cancer

Pancreatic cancer is the fourth leading cause for cancer-related death, and early diagnosis is one key to improve the survival rate of this disease. Molecular biomarkers are an important method for diagnostic use in pancreatic cancer. We used data from three mRNA microarray datasets and a microRNA dataset (GSE16515, GSE15471, GSE28735, and GSE41372) to identify potential key genes. Differentially expressed genes (DEGs) and microRNAs (DEMs) were identified. Functional, pathway enrichment, and protein-protein interaction analyses were performed on common DEGs across all datasets. The target genes of the DEMs were identified. DEMs targets that were also DEGs were further scrutinized using overall survival analysis. A total of 236 DEGs and 21 DEMs were identified. There were a total of four DEGs (ECT2, NR5A2, NRP2, and TGFBI), which were also predicted target genes of DEMs. Overall survival analysis showed that high expression levels of three of these genes (ECT2, NRP2, and TGFBI) were associated with poor overall survival for pancreatic cancer patients. The basic expression of DEGs in pancreas stood lower level in various organ tissues. The expression of ECT2 and NRP2 was higher in different pancreatic cancer cell lines than normal pancreas cell line. Knockout of ECT2 by Crispr Cas9 gene editing system decreased proliferation and migration ability in pancreatic cancer cell line MiaPaCa2. In conclusion, we think that data mining method can do well in biomarker screening, and ECT2 and NRP2 can play as potential biomarker or therapy target by Crispr Cas9 in pancreatic cancer.

Pancreatic cancer is now becoming a common cause of cancer death with no significant change in patient survival over the last 10 years. The main treatment options for pancreatic cancer patients are surgery, radiation therapy and chemotherapy, but there is now considerable effort to develop new and effective treatments. In recent years, CRISPR/Cas9 technology has emerged as a powerful gene editing tool with promise, not only as an important research methodology, but also as a new and effective method for targeted therapy. In this review, we summarize current advances in CRISPR/Cas9 technology and its application to pancreatic cancer research, and importantly as a means of selectively targeting key drivers of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Developing biomarkers for early detection and chemotherapeutic response prediction is crucial to improve the dismal prognosis of PDAC patients. However, molecular cancer signatures based on transcriptome analysis do not reflect intratumoral heterogeneity. To explore a more accurate stratification of PDAC phenotypes in an easily accessible matrix, plasma metabolome analysis using MxP® Global Profiling and MxP® Lipidomics was performed in 361 PDAC patients. We identified three metabolic PDAC subtypes associated with distinct complex lipid patterns. Subtype 1 was associated with reduced ceramide levels and a strong enrichment of triacylglycerols. Subtype 2 demonstrated increased abundance of ceramides, sphingomyelin and other complex sphingolipids, whereas subtype 3 showed decreased levels of sphingolipid metabolites in plasma. Pathway enrichment analysis revealed that sphingolipid-related pathways differ most among subtypes. Weighted correlation network analysis (WGCNA) implied PDAC subtypes differed in their metabolic programs. Interestingly, a reduced expression among related pathway genes in tumor tissue was associated with the lowest survival rate. However, our metabolic PDAC subtypes did not show any correlation to the described molecular PDAC subtypes. Our findings pave the way for further studies investigating sphingolipids metabolisms in PDAC.

The ampulla of Vater is a complex cellular environment from which adenocarcinomas arise to form a group of histopathologically heterogenous tumors. To evaluate the molecular features of these tumors, 98 ampullary adenocarcinomas were evaluated and compared to 44 distal bile duct and 18 duodenal adenocarcinomas. Genomic analyses revealed mutations in the WNT signaling pathway among half of the patients and in all three adenocarcinomas irrespective of their origin and histological morphology. These tumors were characterized by a high frequency of inactivating mutations of ELF3, a high rate of microsatellite instability, and common focal deletions and amplifications, suggesting common attributes in the molecular pathogenesis are at play in these tumors. The high frequency of WNT pathway activating mutation, coupled with small-molecule inhibitors of β-catenin in clinical trials, suggests future treatment decisions for these patients may be guided by genomic analysis.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers principally because of early invasion and metastasis. The epidermal growth factor receptor (EGFR) is essential for PDAC development even in the presence of Kras, but its inhibition with erlotinib gives only a modest clinical response, making the discovery of novel EGFR targets of critical interest. Here, we revealed by mining a human pancreatic gene expression database that the metastasis promoter Na+/H+ exchanger (NHE1) associates with the EGFR in PDAC. In human PDAC cell lines, we confirmed that NHE1 drives both basal and EGF-stimulated three-dimensional growth and early invasion via invadopodial extracellular matrix digestion. EGF promoted the complexing of EGFR with NHE1 via the scaffolding protein Na+/H+ exchanger regulatory factor 1, engaging EGFR in a negative transregulatory loop that controls the extent and duration of EGFR oncogenic signaling and stimulates NHE1. The specificity of NHE1 for growth or invasion depends on the segregation of the transient EGFR/Na+/H+ exchanger regulatory factor 1/NHE1 signaling complex into dimeric subcomplexes in different lipid raftlike membrane domains. This signaling complex was also found in tumors developed in orthotopic mice. Importantly, the specific NHE1 inhibitor cariporide reduced both three-dimensional growth and invasion independently of PDAC subtype and synergistically sensitized these behaviors to low doses of erlotinib.

Pancreatic cancer is characterized by a high degree of resistance to chemotherapy. Epidermal growth factor receptor (EGFR) inhibition using the small-molecule inhibitor erlotinib was shown to provide a small survival benefit in a subgroup of patients. To identify kinases whose inhibition acts synergistically with erlotinib, we employed a kinome-wide small-interfering RNA (siRNA)-based loss-of-function screen in the presence of erlotinib. Of 779 tested kinases, we identified several targets whose inhibition acted synergistically lethal with EGFR inhibition by erlotinib, among them the S6 kinase ribosomal protein S6 kinase 2 (RPS6KA2)/ribosomal S6 kinase 3. Activated RPS6KA2 was expressed in approximately 40% of 123 human pancreatic cancer tissues. RPS6KA2 was shown to act downstream of EGFR/RAS/mitogen-activated protein kinase kinase (MEK)/extracellular-signal regulated kinase (ERK) signaling and was activated by EGF independently of the presence of KRAS mutations. Knockdown of RPS6KA2 by siRNA led to increased apoptosis only in the presence of erlotinib, whereas RPS6KA2 activation or overexpression rescued from erlotinib- and gemcitabine-induced apoptosis. This effect was at least in part mediated by downstream activation of ribosomal protein S6. Genetic as well as pharmacological inhibition of RPS6KA2 by the inhibitor BI-D1870 acted synergistically with erlotinib. By applying this synergistic lethality screen using a kinome-wide RNA interference-library approach, we identified RPS6KA2 as potential drug target whose inhibition synergistically enhanced the effect of erlotinib on tumor cell survival. This kinase therefore represents a promising drug candidate suitable for the development of novel inhibitors for pancreatic cancer therapy.

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.

INTRODUCTION: WNT5A belongs to the Wnt family of secreted signaling molecules. Using transcriptional profiling, we previously identified WNT5A as target of the antiapoptotic transcription factor CUX1 and demonstrated high expression levels in pancreatic cancer. However, the impact of WNT5A on drug resistance and the signaling pathways employed by WNT5A remain to be elucidated. OBJECTIVES: This project aims to decipher the impact of WNT5A on resistance to apoptosis and the signaling pathways employed by WNT5A in pancreatic cancer. METHODS: The impact of WNT5A and its downstream effectors on tumor growth and drug resistance was studied in vitro and in xenograft models in vivo. Tissue microarrays of pancreatic cancer specimens were employed for immuno-histochemical studies. RESULTS: Knockdown of WNT5A results in a significant increase in drug-induced apoptosis. In contrast, overexpression of WNT5A or addition of recombinant WNT5A mediates resistance to apoptosis in vitro. In our attempt to identify downstream effectors of WNT5A, we identified the transcription factor nuclear factor of activated T cells c2 (NFATc2) as transcriptional target of WNT5A signaling. NFATc2 confers a strong antiapoptotic phenotype mediating at least in part the effects of WNT5A on drug resistance and tumor cell survival. In vivo, WNT5A expression leads to resistance to gemcitabine-induced apoptosis in a xenograft model, which is paralleled by up-regulation of NFATc2. Both WNT5A and NFATc2 proteins are highly expressed in human pancreatic cancer tissues and their expression levels correlated significantly. CONCLUSION: We identified the WNT5A-NFATc2 axis as important mediator of drug resistance in pancreatic cancer.

Cancers originating from epithelial cells are the most common malignancies. No common expression profile of solid tumors compared to normal tissues has been described so far. Therefore we were interested if genes differentially expressed in the majority of carcinomas could be identified using bioinformatic methods. Complete data sets were downloaded for carcinomas of the prostate, breast, lung, ovary, colon, pancreas, stomach, bladder, liver, and kidney, and were subjected to an expression analysis using SAM. In each experiment, a gene was scored as differentially expressed if the q value was below 25%. Probe identifiers were unified by comparing the respective probe sequences to the Unigene build 155 using BIastN. To obtain differentially expressed genes within the set of analyzed carcinomas, the number of experiments in which differential expression was observed was counted. Differential expression was assigned to genes if they were differentially expressed in at least eight experiments of tumors from different origin. The identified candidate genes ADRM1, EBNA1BP2, FDPS, FOXM1, H2AFX, HDAC3, IRAK1, and YY1 were subjected to further validation. Using this comparative approach, 100 genes were identified as upregulated and 21 genes as downregulated in the carcinomas.

Pancreatic ductal adenocarcinoma (PDAC) remains an important cause of malignancy-related death and is the eighth most common cancer with the lowest overall 5-year relative survival rate. To identify new molecular markers and candidates for new therapeutic regimens, we investigated the gene expression profile of microdissected cells from 11 normal pancreatic ducts, 14 samples of PDAC, and 4 well-characterized pancreatic cancer cell lines using the Affymetrix U133 GeneChip set. RNA was extracted from microdissected samples and cell lines, amplified, and labeled using a repetitive in vitro transcription protocol. Differentially expressed genes were identified using the significance analysis of microarrays program. We found 616 differentially expressed genes. Within these, 140 were also identified in PDAC by others, such as Galectin-1, Galectin-3, and MT-SP2. We validated the differential expression of several genes (e.g., CENPF, MCM2, MCM7, RAMP, IRAK1, and PTTG1) in PDAC by immunohistochemistry and reverse transcription polymerase chain reaction. We present a whole genome expression study of microdissected tissues from PDAC, from microdissected normal ductal pancreatic cells and pancreatic cancer cell lines using highdensity microarrays. Within the panel of genes, we identified novel differentially expressed genes, which have not been associated with the pathogenesis of PDAC before.

Adenocarcinomas of the ampulla of Vater are classified as biliary cancers, though the exact epithelium of origin for these cancers is not known. We sought to molecularly classify ampullary adenocarcinomas in comparison to known adenocarcinomas of the pancreas, bile duct, and duodenum by gene expression analysis.We analyzed 32 fresh-frozen resected, untreated periampullary adenocarcinomas (8 pancreatic, 2 extrahepatic biliary, 8 duodenal, and 14 ampullary) using the Affymetrix U133 Plus 2.0 genome array. Unsupervised and supervised hierarchical clustering identified two subtypes of ampullary carcinomas that were molecularly and histologically characterized.Hierarchical clustering of periampullary carcinomas segregated ampullary carcinomas into two subgroups, which were distinctly different from pancreatic carcinomas. Non-pancreatic periampullary adenocarcinomas were segregated into two subgroups with differing prognoses: 5 year RFS (77% vs. 0%, p = 0.007) and 5 year OS (100% vs. 35%, p = 0.005). Unsupervised clustering analysis of the 14 ampullary samples also identified two subgroups: a good prognosis intestinal-like subgroup and a poor prognosis biliary-like subgroup with 5 year OS of 70% vs. 28%, P = 0.09. Expression of CK7+/CK20- but not CDX-2 correlated with these two subgroups. Activation of the AKT and MAPK pathways were both increased in the poor prognostic biliary-like subgroup. In an independent 80 patient ampullary validation dataset only histological subtype (intestinal vs. pancreaticobiliary) was significantly associated with OS in both univariate (p = 0.006) and multivariate analysis (P = 0.04).Gene expression analysis discriminated pancreatic adenocarcinomas from other periampullary carcinomas and identified two prognostically relevant subgroups of ampullary adenocarcinomas. Histological subtype was an independent prognostic factor in ampullary adenocarcinomas.

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice.

The classical somatic mutation theory (SMT) of carcinogenesis and metastasis postulates that malignant transformation occurs in cells that accumulate a sufficient amount of mutations in the appropriate oncogenes and/or tumor suppressor genes. These mutations result in cell-autonomous activation of the mutated cell and a growth advantage relative to neighboring cells. However, the SMT cannot completely explain many characteristics of carcinomas. Contrary to the cell-centered view of the SMT with respect to carcinogenesis, recent research has revealed evidence that the tumor microenvironment plays a role in carcinogenesis as well. In this review, we present a new model that accommodates the role of the tumor microenvironment in carcinogenesis and complements the classical SMT. Our "feedback" model emphasizes the role of an altered spatiotemporal communication between epithelial and stromal cells during carcinogenesis: a dysfunctional intracellular signaling in tumorigenic epithelial cells leads to inappropriate cellular responses to stimuli from associated stromal or inflammatory cells. Thus, a positive feedback loop of the information flow between parenchymal and stromal cells results. This constant communication between the stromal cells and the tumor cells causes a perpetually activated state of tumor cells analogous to resonance disaster.

BackgroundPancreatic ductal adenocarcinoma (PDAC) remains an important cause of cancer death. Changes in apoptosis signaling in pancreatic cancer result in chemotherapy resistance and aggressive growth and metastasizing. The aim of this study was to characterize the apoptosis pathway in pancreatic cancer computationally by evaluation of experimental data from high-throughput technologies and public data bases. Therefore, gene expression analysis of microdissected pancreatic tumor tissue was implemented in a model of the apoptosis pathway obtained by computational protein interaction prediction.Methodology/principal findingsApoptosis pathway related genes were assembled from electronic databases. To assess expression of these genes we constructed a virtual subarray from a whole genome analysis from microdissected native tumor tissue. To obtain a model of the apoptosis pathway, interactions of members of the apoptosis pathway were analysed using public databases and computational prediction of protein interactions. Gene expression data were implemented in the apoptosis pathway model. 19 genes were found differentially expressed and 12 genes had an already known pathophysiological role in PDAC, such as Survivin/BIRC5, BNIP3 and TNF-R1. Furthermore we validated differential expression of IL1R2 and Livin/BIRC7 by RT-PCR and immunohistochemistry. Implementation of the gene expression data in the apoptosis pathway map suggested two higher level defects of the pathway at the level of cell death receptors and within the intrinsic signaling cascade consistent with references on apoptosis in PDAC. Protein interaction prediction further showed possible new interactions between the single pathway members, which demonstrate the complexity of the apoptosis pathway.Conclusions/significanceOur data shows that by computational evaluation of public accessible data an acceptable virtual image of the apoptosis pathway might be given. By this approach we could identify two higher level defects of the apoptosis pathway in PDAC. We could further for the first time identify IL1R2 as possible candidate gene in PDAC.

BACKGROUND:Colorectal cancer (CRC) is the second leading cause of cancer deaths despite the fact that detection of this cancer in early stages results in over 90% survival rate. Currently less than 45% of at-risk individuals in the US are screened regularly, exposing a need for better screening tests. We performed two case-control studies to validate a blood-based test that identifies methylated DNA in plasma from all stages of CRC. METHODOLOGY/PRINCIPAL FINDINGS:Using a PCR assay for analysis of Septin 9 (SEPT9) hypermethylation in DNA extracted from plasma, clinical performance was optimized on 354 samples (252 CRC, 102 controls) and validated in a blinded, independent study of 309 samples (126 CRC, 183 controls). 168 polyps and 411 additional disease controls were also evaluated. Based on the training study SEPT9-based classification detected 120/252 CRCs (48%) and 7/102 controls (7%). In the test study 73/126 CRCs (58%) and 18/183 control samples (10%) were positive for SEPT9 validating the training set results. Inclusion of an additional measurement replicate increased the sensitivity of the assay in the testing set to 72% (90/125 CRCs detected) while maintaining 90% specificity (19/183 for controls). Positive rates for plasmas from the other cancers (11/96) and non-cancerous conditions (41/315) were low. The rate of polyp detection (>1 cm) was approximately 20%. CONCLUSIONS/SIGNIFICANCE:Analysis of SEPT9 DNA methylation in plasma represents a straightforward, minimally invasive method to detect all stages of CRC with potential to satisfy unmet needs for increased compliance in the screening population. Further clinical testing is warranted.