NIHR Liverpool Pancreatic Biomedical Research Unit

PURPOSE: To evaluate the ability of a new combined biomechanical index called the Corvis Biomechanical Index (CBI) based on corneal thickness profile and deformation parameters to separate normal from keratoconic patients. METHODS: Six hundred fifty-eight patients (329 eyes in each database) were included in this multicenter retrospective study. Patients from two clinics located on different continents were selected to test the capability of the CBI to separate healthy and keratoconic eyes in more than one ethnic group using the Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany). Logistic regression was employed to determine, based on Database 1 as the development dataset, the optimal combination of parameters to accurately separate normal from keratoconic eyes. The CBI was subsequently independently validated on Database 2. RESULTS: The CBI included several dynamic corneal response parameters: deformation amplitude ratio at 1 and 2 mm, applanation 1 velocity, standard deviation of deformation amplitude at highest concavity, Ambrósio's Relational Thickness to the horizontal profile, and a novel stiffness parameter. The receiver operating characteristic curve analysis of the training database showed an area under the curve of 0.983. With a cut-off value of 0.5, 98.2% of the cases were correctly classified with 100% specificity and 94.1% sensitivity. In the validation dataset, the same cut-off point correctly classified 98.8% of the cases with 98.4% specificity and 100% sensitivity. CONCLUSIONS: The CBI was shown to be highly sensitive and specific to separate healthy from keratoconic eyes. The presence of an external validation dataset confirms this finding and suggests the possible use of the CBI in everyday clinical practice to aid in the diagnosis of keratoconus. [J Refract Surg. 2016;32(12):803-810.].

Background and aims The role of GATA factors in cancer has gained increasing attention recently, but the function of GATA6 in pancreatic ductal adenocarcinoma (PDAC) is controversial. GATA6 is amplified in a subset of tumours and was proposed to be oncogenic, but high GATA6 levels are found in well-differentiated tumours and are associated with better patient outcome. By contrast, a tumour-suppressive function of GATA6 was demonstrated using genetic mouse models. We aimed at clarifying GATA6 function in PDAC. Design We combined GATA6 silencing and overexpression in PDAC cell lines with GATA6 ChIP-Seq and RNA-Seq data, in order to understand the mechanism of GATA6 functions. We then confirmed some of our observations in primary patient samples, some of which were included in the ESPAC-3 randomised clinical trial for adjuvant therapy. Results GATA6 inhibits the epithelial–mesenchymal transition (EMT) in vitro and cell dissemination in vivo. GATA6 has a unique proepithelial and antimesenchymal function, and its transcriptional regulation is direct and implies, indirectly, the regulation of other transcription factors involved in EMT. GATA6 is lost in tumours, in association with altered differentiation and the acquisition of a basal-like molecular phenotype, consistent with an epithelial-to-epithelial (ET 2 ) transition. Patients with basal-like GATA6 low tumours have a shorter survival and have a distinctly poor response to adjuvant 5-fluorouracil (5-FU)/leucovorin. However, modulation of GATA6 expression in cultured cells does not directly regulate response to 5-FU. Conclusions We provide mechanistic insight into GATA6 tumour-suppressive function, its role as a regulator of canonical epithelial differentiation, and propose that loss of GATA6 expression is both prognostic and predictive of response to adjuvant therapy.

BACKGROUND: Nrf2 is a key transcriptional regulator of a battery of genes that facilitate phase II/III drug metabolism and defence against oxidative stress. Nrf2 is largely regulated by Keap1, which directs Nrf2 for proteasomal degradation. The Nrf2/Keap1 system is dysregulated in lung, head and neck, and breast cancers and this affects cellular proliferation and response to therapy. Here, we have investigated the integrity of the Nrf2/Keap1 system in pancreatic cancer. RESULTS: Keap1, Nrf2 and the Nrf2 target genes AKR1c1 and GCLC were detected in a panel of five pancreatic cancer cell lines. Mutation analysis of NRF2 exon 2 and KEAP1 exons 2-6 in these cell lines identified no mutations in NRF2 and only synonomous mutations in KEAP1. RNAi depletion of Nrf2 caused a decrease in the proliferation of Suit-2, MiaPaca-2 and FAMPAC cells and enhanced sensitivity to gemcitabine (Suit-2), 5-flurouracil (FAMPAC), cisplatin (Suit-2 and FAMPAC) and gamma radiation (Suit-2). The expression of Nrf2 and Keap1 was also analysed in pancreatic ductal adenocarcinomas (n = 66 and 57, respectively) and matching normal benign epithelium (n = 21 cases). Whilst no significant correlation was seen between the expression levels of Keap1 and Nrf2 in the tumors, interestingly, Nrf2 staining was significantly greater in the cytoplasm of tumors compared to benign ducts (P < 0.001). CONCLUSIONS: Expression of Nrf2 is up-regulated in pancreatic cancer cell lines and ductal adenocarcinomas. This may reflect a greater intrinsic capacity of these cells to respond to stress signals and resist chemotherapeutic interventions. Nrf2 also appears to support proliferation in certain pancreatic adenocarinomas. Therefore, strategies to pharmacologically manipulate the levels and/or activity of Nrf2 may have the potential to reduce pancreatic tumor growth, and increase sensitivity to therapeutics.

PURPOSE: Biomarkers for the early detection of pancreatic cancer are urgently needed. The primary objective of this study was to evaluate whether increased levels of serum CA19-9, CA125, CEACAM1, and REG3A are present before clinical presentation of pancreatic cancer and to assess the performance of combined markers for early detection and prognosis. EXPERIMENTAL DESIGN: This nested case-control study within the UKCTOCS included 118 single and 143 serial serum samples from 154 postmenopausal women who were subsequently diagnosed with pancreatic cancer and 304 matched noncancer controls. Samples were split randomly into independent training and test sets. CA19-9, CA125, CEACAM1, and REG3A were measured using ELISA and/or CLIA. Performance of markers to detect cancers at different times before diagnosis and for prognosis was evaluated. RESULTS: At 95% specificity, CA19-9 (>37 U/mL) had a sensitivity of 68% up to 1 year, and 53% up to 2 years before diagnosis. Combining CA19-9 and CA125 improved sensitivity as CA125 was elevated (>30 U/mL) in approximately 20% of CA19-9-negative cases. CEACAM1 and REG3A were late markers adding little in combined models. Average lead times of 20 to 23 months were estimated for test-positive cases. Prediagnostic levels of CA19-9 and CA125 were associated with poor overall survival (HR, 2.69 and 3.15, respectively). CONCLUSIONS: CA19-9 and CA125 have encouraging sensitivity for detecting preclinical pancreatic cancer, and both markers can be used as prognostic tools. This work challenges the prevailing view that CA19-9 is upregulated late in the course of pancreatic cancer development.

OBJECTIVES: The aim of this national survey was to explore the impact of COVID-19 public health measures on access to social support services and the effects of closures of services on the mental well-being of older people and those affected by dementia. METHODS: A UK-wide online and telephone survey was conducted with older adults, people with dementia, and carers between April and May 2020. The survey captured demographic and postcode data, social support service usage before and after COVID-19 public health measures, current quality of life, depression, and anxiety. Multiple linear regression analysis was used to explore the relationship between social support service variations and anxiety and well-being. RESULTS: -tests showed that the mean hour of weekly social support service usage and the number of people having accessed various services was significantly reduced post COVID-19. Multiple regression analyses showed that higher variations in social support service hours significantly predicted increased levels of anxiety in people with dementia and older adults, and lower levels of mental well-being in unpaid carers and older adults. CONCLUSIONS: Being unable to access social support services due to COVID contributed to worse quality of life and anxiety in those affected by dementia and older adults across the UK. Social support services need to be enabled to continue providing support in adapted formats, especially in light of continued public health restrictions for the foreseeable future.

PURPOSE: Noninvasive biomarkers for early detection of pancreatic ductal adenocarcinoma (PDAC) are currently not available. Here, we aimed to identify a set of urine proteins able to distinguish patients with early-stage PDAC from healthy individuals. EXPERIMENTAL DESIGN: Proteomes of 18 urine samples from healthy controls, chronic pancreatitis, and patients with PDAC (six/group) were assayed using GeLC/MS/MS analysis. The selected biomarkers were subsequently validated with ELISA assays using multiple logistic regression applied to a training dataset in a multicenter cohort comprising 488 urine samples. RESULTS: LYVE-1, REG1A, and TFF1 were selected as candidate biomarkers. When comparing PDAC (n = 192) with healthy (n = 87) urine specimens, the resulting areas under the receiver-operating characteristic curves (AUC) of the panel were 0.89 [95% confidence interval (CI), 0.84-0.94] in the training (70% of the data) and 0.92 (95% CI, 0.86-0.98) in the validation (30% of the data) datasets. When comparing PDAC stage I-II (n = 71) with healthy urine specimens, the panel achieved AUCs of 0.90 (95% CI, 0.84-0.96) and 0.93 (95% CI, 0.84-1.00) in the training and validation datasets, respectively. In PDAC stage I-II and healthy samples with matching plasma CA19.9, the panel achieved a higher AUC of 0.97 (95% CI, 0.94-0.99) than CA19.9 (AUC = 0.88; 95% CI, 0.81-0.95, P = 0.005). Adding plasma CA19.9 to the panel increased the AUC from 0.97 (95% CI, 0.94-0.99) to 0.99 (95% CI, 0.97-1.00, P = 0.04), but did not improve the comparison of stage I-IIA PDAC (n = 17) with healthy urine. CONCLUSIONS: We have established a novel, three-protein biomarker panel that is able to detect patients with early-stage pancreatic cancer in urine specimens.

OBJECTIVE: Non-oxidative metabolism of ethanol (NOME) produces fatty acid ethyl esters (FAEEs) via carboxylester lipase (CEL) and other enzyme action implicated in mitochondrial injury and acute pancreatitis (AP). This study investigated the relative importance of oxidative and non-oxidative pathways in mitochondrial dysfunction, pancreatic damage and development of alcoholic AP, and whether deleterious effects of NOME are preventable. DESIGN: Intracellular calcium ([Ca(2+)](C)), NAD(P)H, mitochondrial membrane potential and activation of apoptotic and necrotic cell death pathways were examined in isolated pancreatic acinar cells in response to ethanol and/or palmitoleic acid (POA) in the presence or absence of 4-methylpyrazole (4-MP) to inhibit oxidative metabolism. A novel in vivo model of alcoholic AP induced by intraperitoneal administration of ethanol and POA was developed to assess the effects of manipulating alcohol metabolism. RESULTS: Inhibition of OME with 4-MP converted predominantly transient [Ca(2+)](C) rises induced by low ethanol/POA combination to sustained elevations, with concurrent mitochondrial depolarisation, fall of NAD(P)H and cellular necrosis in vitro. All effects were prevented by 3-benzyl-6-chloro-2-pyrone (3-BCP), a CEL inhibitor. 3-BCP also significantly inhibited rises of pancreatic FAEE in vivo and ameliorated acute pancreatic damage and inflammation induced by administration of ethanol and POA to mice. CONCLUSIONS: A combination of low ethanol and fatty acid that did not exert deleterious effects per se became toxic when oxidative metabolism was inhibited. The in vitro and in vivo damage was markedly inhibited by blockade of CEL, indicating the potential for development of specific therapy for treatment of alcoholic AP via inhibition of FAEE generation.

OBJECTIVE: To provide evidence-based recommendations for the management of exocrine pancreatic insufficiency (EPI) after pancreatic surgery. BACKGROUND: EPI is a common complication after pancreatic surgery but there is certain confusion about its frequency, optimal methods of diagnosis, and when and how to treat these patients. METHODS: Eighteen multidisciplinary reviewers performed a systematic review on 10 predefined questions following the GRADE methodology. Six external expert referees reviewed the retrieved information. Members from Spanish Association of Pancreatology were invited to suggest modifications and voted for the quantification of agreement. RESULTS: These guidelines analyze the definition of EPI after pancreatic surgery, (one question), its frequency after specific techniques and underlying disease (four questions), its clinical consequences (one question), diagnosis (one question), when and how to treat postsurgical EPI (two questions) and its impact on the quality of life (one question). Eleven statements answering those 10 questions were provided: one (9.1%) was rated as a strong recommendation according to GRADE, three (27.3%) as moderate and seven (63.6%) as weak. All statements had strong agreement. CONCLUSIONS: EPI is a frequent but under-recognized complication of pancreatic surgery. These guidelines provide evidence-based recommendations for the definition, diagnosis, and management of EPI after pancreatic surgery.

BACKGROUND: The lockdown imposed in the UK on the 23rd of March and associated public health measures of social distancing are likely to have had a great impact on care provision. The aim of this study was to explore the decision-making processes of continued paid home care support for dementia in the time of COVID-19. METHODS: Unpaid carers caring for a person living with dementia (PLWD) who were accessing paid home care before COVID-19 and residing in the UK were eligible to take part. Participants were interviewed over the phone and asked about their experiences of using paid home care services before and since COVID-19, and their decision-making processes of accessing paid home care since the outbreak and public health restrictions. RESULTS: Fifteen unpaid carers, who were also accessing paid care support for the PLWD before COVID-19, were included in the analysis. Thematic analysis identified three overarching themes: (1) Risk; (2) Making difficult choices and risk management; and (3) Implications for unpaid carers. Many unpaid carers decided to discontinue paid carers entering the home due to the risk of infection, resulting in unpaid carers having to pick up the care hours to support the person living with dementia. CONCLUSIONS: This is the first study to report on the impact of COVID-19 on paid home care changes in dementia. Findings raise implications for providing better Personal Protective Equipment for paid carers, and to support unpaid carers better in their roles, with the pandemic likely to stay in place for the foreseeable future.

Cell communication is central to the integration of cell function required for the development and homeostasis of multicellular animals. Proteins are an important currency of cell communication, acting locally (auto-, juxta-, or paracrine) or systemically (endocrine). The fibroblast growth factor (FGF) family contributes to the regulation of virtually all aspects of development and organogenesis, and after birth to tissue maintenance, as well as particular aspects of organism physiology. In the West, oncology has been the focus of translation of FGF research, whereas in China and to an extent Japan a major focus has been to use FGFs in repair and regeneration settings. These differences have their roots in research history and aims. The Chinese drive into biotechnology and the delivery of engineered clinical grade FGFs by a major Chinese research group were important enablers in this respect. The Chinese language clinical literature is not widely accessible. To put this into context, we provide the essential molecular and functional background to the FGF communication system covering FGF ligands, the heparan sulfate and Klotho co-receptors and FGF receptor (FGFR) tyrosine kinases. We then summarise a selection of clinical reports that demonstrate the efficacy of engineered recombinant FGF ligands in treating a wide range of conditions that require tissue repair/regeneration. Alongside, the functional reasons why application of exogenous FGF ligands does not lead to cancers are described. Together, this highlights that the FGF ligands represent a major opportunity for clinical translation that has been largely overlooked in the West.

// Mingfeng Zhang 1 , Zhaoming Wang 2,3,100 , Ofure Obazee 4 , Jinping Jia 1 , Erica J. Childs 5 , Jason Hoskins 1 , Gisella Figlioli 4 , Evelina Mocci 5 , Irene Collins 1 , Charles C. Chung 2,3 , Christopher Hautman 1 , Alan A. Arslan 6,7,8 , Laura Beane-Freeman 2 , Paige M. Bracci 9 , Julie Buring 10,11 , Eric J. Duell 12 , Steven Gallinger 13 , Graham G. Giles 14,15,16 , Gary E. Goodman 17 , Phyllis J. Goodman 18 , Aruna Kamineni 19 , Laurence N. Kolonel 20 , Matthew H. Kulke 21 , N&uacute;ria Malats 22 , Sara H. Olson 23 , Howard D. Sesso 24,10,11 , Kala Visvanathan 25 , Emily White 17,26 , Wei Zheng 27,28 , Christian C. Abnet 2 , Demetrius Albanes 2 , Gabriella Andreotti 2 , Lauren Brais 21 , H. Bas Bueno-de-Mesquita 29,30,31 , Daniela Basso 32 , Sonja I. Berndt 2 , Marie-Christine Boutron-Ruault 33,34,35 , Maarten F. Bijlsma 36 , Hermann Brenner 37,38,39 , Laurie Burdette 2,3 , Daniele Campa 40 , Neil E. Caporaso 2 , Gabriele Capurso 41 , Giulia Martina Cavestro 42 , Michelle Cotterchio 43,44 , Eithne Costello 45 , Joanne Elena 46 , Ugo Boggi 47 , J. Michael Gaziano 10,11,48 , Maria Gazouli 49 , Edward L. Giovannucci 24,50,51 , Michael Goggins 52,53,54 , Myron Gross 55 , Christopher A. Haiman 56 , Manal Hassan 57 , Kathy J. Helzlsouer 46 , Nan Hu 2 , David J. Hunter 58,59,60 , Elzbieta Iskierka-Jazdzewska 61 , Mazda Jenab 62 , Rudolf Kaaks 63 , Timothy J. Key 64 , Kay-Tee Khaw 65 , Eric A. Klein 66 , Manolis Kogevinas 67,68,69 , Vittorio Krogh 70 , Juozas Kupcinskas 71 , Robert C. Kurtz 72 , Maria T. Landi 2 , Stefano Landi 40 , Loic Le Marchand 20 , Andrea Mambrini 73 , Satu Mannisto 74 , Roger L. Milne 14,15 , Rachel E. Neale 75 , Ann L. Oberg 76 , Salvatore Panico 77 , Alpa V. Patel 78 , Petra H. M. Peeters 79,30 , Ulrike Peters 17,26 , Raffaele Pezzilli 80 , Miquel Porta 68,81,82 , Mark Purdue 2 , J. Ram&oacute;n Quiros 83 , Elio Riboli 30 , Nathaniel Rothman 2 , Aldo Scarpa 84 , Ghislaine Scelo 62 , Xiao-Ou Shu 27,28 , Debra T. Silverman 2 , Pavel Soucek 85 , Oliver Strobel 86 , Malin Sund 87 , Ewa Małecka-Panas 88 , Philip R. Taylor 2 , Francesca Tavano 89 , Ruth C. Travis 64 , Mark Thornquist 17 , Anne Tj&oslash;nneland 90 , Geoffrey S. Tobias 2 , Dimitrios Trichopoulos 24,91,92 , Yogesh Vashist 93 , Pavel Vodicka 94 , Jean Wactawski-Wende 95 , Nicolas Wentzensen 2 , Herbert Yu 20 , Kai Yu 2 , Anne Zeleniuch-Jacquotte 7,8 , Charles Kooperberg 17 , Harvey A. Risch 96 , Eric J. Jacobs 78 , Donghui Li 57 , Charles Fuchs 21,50 , Robert Hoover 2 , Patricia Hartge 2 , Stephen J. Chanock 2 , Gloria M. Petersen 97 , Rachael S. Stolzenberg-Solomon 2 , Brian M. Wolpin 21 , Peter Kraft 24,98 , Alison P. Klein 5,99 , Federico Canzian 4 and Laufey T. Amundadottir 1 1 Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA 2 Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA 3 Cancer Genomics Research Laboratory, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA 4 Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany 5 Department of Oncology, the Johns Hopkins University School of Medicine, Baltimore, Maryland, USA 6 Department of Obstetrics and Gynecology, New York University School of Medicine, New York, New York, USA 7 Department of Environmental Medicine, New York University School of Medicine, New York, New York, USA 8 New York University Cancer Institute, New York, New York, USA 9 Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA 10 Division of Preventive Medicine, Department of Medicine, Brigham and Women&rsquo;s Hospital and Harvard Medical School, Boston, Massachusetts, USA 11 Division of Aging, Department of Medicine, Brigham and Women&rsquo;s Hospital and Harvard Medical School, Boston, Massachusetts, USA 12 Unit of Nutrition and Cancer, Cancer Epidemiology Research Program, Bellvitge Biomedical Research Institute (IDIBELL), Catalan Institute of Oncology (ICO), Barcelona, Spain 13 Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada 14 Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia 15 Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia 16 Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia 17 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA 18 Southwest Oncology Group Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA 19 Group Health Research Institute, Seattle, Washington, USA 20 Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, USA 21 Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA 22 Genetic and Molecular Epidemiology Group, CNIO-Spanish National Cancer Research Centre, Madrid, Spain 23 Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA 24 Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA 25 Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA 26 Department of Epidemiology, University of Washington, Seattle, Washington, USA 27 Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA 28 Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA 29 Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands 30 Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom 31 Department of Social &amp; Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia. 32 Department of Laboratory Medicine, University Hospital of Padova, Padua, Italy 33 Inserm, Centre for Research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women&rsquo;s Health Team, F-94805, Villejuif, France 34 University Paris Sud, UMRS 1018, F-94805, Villejuif, France 35 IGR, F-94805, Villejuif, France 36 Laboratory for Experimental Oncology and Radiobiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands 37 Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany 38 Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany 39 German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany 40 Department of Biology, University of Pisa, Pisa, Italy 41 Digestive and Liver Disease Unit, &lsquo;Sapienza&rsquo; University of Rome, Rome, Italy 42 Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy 43 Prevention and Cancer Control, Cancer Care Ontario, Toronto, Ontario, Canada 44 Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada 45 National Institute for Health Research Liverpool Pancreas Biomedical Research Unit, University of Liverpool, Liverpool, United Kingdom 46 Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA 47 Department of Surgery, Unit of Experimental Surgical Pathology, University Hospital of Pisa, Pisa, Italy 48 Massachusetts Veteran&rsquo;s Epidemiology, Research, and Information Center, Geriatric Research Education and Clinical Center, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA 49 Department of Basic Medical Sciences, Laboratory of Biology, Medical School, National and Kapodistrian University of Athens, Athens, Greece 50 Channing Division of Network Medicine, Department of Medicine, Brigham and Women&rsquo;s Hospital, and Harvard Medical School, Boston, Massachusetts, USA 51 Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA 52 Department of Pathology, Sidney Kimmel Cancer Center and Johns Hopkins University, Baltimore, Maryland, USA 53 Department of Medicine, Sidney Kimmel Cancer Center and Johns Hopkins University, Baltimore, Maryland, USA 54 Department of Oncology, Sidney Kimmel Cancer Center and Johns Hopkins University, Baltimore, Maryland, USA 55 Laboratory of Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, USA 56 Preventive Medicine, University of Southern California, Los Angeles, California, USA 57 Department of Gastrointestinal Medical Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA 58 Department of Medicine, Brigham and Women&rsquo;s Hospital and Harvard Medical School, Boston, Massachusetts, USA 59 Harvard School of Public Health, Boston, Massachusetts, USA 60 Harvard Medical School, Boston, Massachusetts, USA 61 Department of Hematology, Medical University of Łodz, Łodz, Poland 62 International Agency for Research on Cancer (IARC), Lyon, France 63 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany 64 Cancer Epidemiology Unit, University of Oxford, Oxford, United Kingdom 65 School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom 66 Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio, USA 67 Centre de Recerca en Epidemiologia Ambiental (CREAL), CIBER Epidemiolog&iacute;a y Salud P&uacute;blica (CIBERESP), Spain 68 Hospital del Mar Institute of Medical Research (IMIM), Barcelona, Spain 69 National School of Public Health, Athens, Greece 70 Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy 71 Department of Gastroenterology, Lithuanian University of Health Sciences, Kaunas, Lithuania 72 Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York, USA 73 Oncology Department, ASL1 Massa Carrara, Massa Carrara, Italy 74 National Institute for Health and Welfare, Department of Chronic Disease Prevention, Helsinki, Finland 75 Department of Population Health, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia 76 Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA 77 Dipartimento di Medicina Clinica E Chirurgia, Federico II Univeristy, Naples, Italy 78 Epidemiology Research Program, American Cancer Society, Atlanta, Georgia, USA 79 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands 80 Pancreas Unit, Department of Digestive Diseases and Internal Medicine, Sant&rsquo;Orsola-Malpighi Hospital, Bologna, Italy 81 School of Medicine, Universitat Aut&ograve;noma de Barcelona, Barcelona, Spain 82 CIBER de Epidemiolog&iacute;a y Salud P&uacute;blica (CIBERESP), Madrid, Spain 83 Public Health and Participation Directorate, Asturias, Spain 84 ARC-NET: Centre for Applied Research on Cancer, University and Hospital Trust of Verona, Verona, Italy 85 Laboratory of Pharmacogenomics, Biomedical Center, Faculty of Medicine in Pilsen, Charles University in Prague, Pilsen, Czech Republic 86 Department of General Surgery, University Hospital Heidelberg, Heidelberg, Germany 87 Department of Surgical and Peroperative Sciences, Ume&aring; University, Ume&aring;, Sweden 88 Department of Digestive Tract Diseases, Medical University of Łodz, Łodz, Poland 89 Division of Gastroenterology and Research Laboratory, IRCCS Scientific Institute and Regional General Hospital &ldquo;Casa Sollievo della Sofferenza&rdquo;, San Giovanni Rotondo, Italy 90 Institute of Cancer Epidemiology, Danish Cancer Society, Copenhagen, Denmark 91 Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece 92 Hellenic Health Foundation, Athens, Greece 93 Department of General, Visceral and Thoracic Surgery, University Hamburg-Eppendorf, Hamburg, Germany 94 Department of Molecular Biology of Cancer, Institute of Experimental Medicine, Academy of Sciences of the Czech Republic, Prague, Czech Republic 95 Department of Social and Preventive Medicine, University at Buffalo, Buffalo, New York, USA 96 Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, USA 97 Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA 98 Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA 99 Department of Epidemiology, the Bloomberg School of Public Health, Baltimore, Maryland, USA 100 Department of Computational Biology, St. Jude Children&rsquo;s Research Hospital, Memphis, Tennessee, USA Correspondence: Laufey T. Amundadottir, email: // Keywords : pancreatic cancer, GWAS, fine-mapping, imputation, NR5A2 Received : May 16, 2016 Accepted : July 01, 2016 Published : August 01, 2016 Abstract Genome-wide association studies (GWAS) have identified common pancreatic cancer susceptibility variants at 13 chromosomal loci in individuals of European descent. To identify new susceptibility variants, we performed imputation based on 1000 Genomes (1000G) Project data and association analysis using 5,107 case and 8,845 control subjects from 27 cohort and case-control studies that participated in the PanScan I-III GWAS. This analysis, in combination with a two-staged replication in an additional 6,076 case and 7,555 control subjects from the PANcreatic Disease ReseArch (PANDoRA) and Pancreatic Cancer Case-Control (PanC4) Consortia uncovered 3 new pancreatic cancer risk signals marked by single nucleotide polymorphisms (SNPs) rs2816938 at chromosome 1q32.1 (per allele odds ratio (OR) = 1.20, P = 4.88x10 -15 ), rs10094872 at 8q24.21 (OR = 1.15, P = 3.22x10 -9 ) and rs35226131 at 5p15.33 (OR = 0.71, P = 1.70x10 -8 ). These SNPs represent independent risk variants at previously identified pancreatic cancer risk loci on chr1q32.1 ( NR5A2 ), chr8q24.21 ( MYC ) and chr5p15.33 ( CLPTM1L - TERT ) as per analyses conditioned on previously reported susceptibility variants. We assessed expression of candidate genes at the three risk loci in histologically normal ( n = 10) and tumor ( n = 8) derived pancreatic tissue samples and observed a marked reduction of NR5A2 expression (chr1q32.1) in the tumors (fold change -7.6, P = 5.7x10 -8 ). This finding was validated in a second set of paired ( n = 20) histologically normal and tumor derived pancreatic tissue samples (average fold change for three NR5A2 isoforms -31.3 to -95.7, P = 7.5x10 -4 -2.0x10 -3 ). Our study has identified new susceptibility variants independently conferring pancreatic cancer risk that merit functional follow-up to identify target genes and explain the underlying biology.

BACKGROUND: There is relatively little methylation array data available specifically for oral squamous cell carcinoma (OSCC). This study aims to compare the DNA methylome across a large cohort of tumour/normal pairs. METHODS: DNA was extracted from 44 OSCCs and paired normal mucosa. DNA methylation analysis employed the Illumina GoldenGate high-throughput array comprising 1505 CpG loci selected from 807 epigenetically regulated genes. This data was correlated with extracapsular spread (ECS), human papilloma virus (HPV) status, recurrence and 5-year survival. RESULTS: Differential methylation levels of a number of genes distinguished the tumour tissue sample from the matched normal. Putative methylation signatures for ECS and recurrence were identified. The concept of concordant methylation or CpG island methylator phenotype (CIMP) in OSCC is supported by our data, with an association between 'CIMP-high' and worse prognosis. Epigenetic deregulation of NOTCH4 signalling in OSCC was also observed, as part of a possible methylation signature for recurrence, with parallels to recently discovered NOTCH mutations in HNSCC. Differences in methylation in HPV-driven cases were seen, but are less significant than that has been recently proposed in other series. CONCLUSION: Although OSCC seems as much an 'epigenetic' as a genetic disease, the translational potential of cancer epigenetics has yet to be fully exploited. This data points to the application of epigenetic biomarkers and targets available to further the development of therapy in OSCC.

OBJECTIVE: The impact of glia cells during GI carcinogenesis and in cancer pain is unknown. Here, we demonstrate a novel mechanism how Schwann cells (SCs) become activated in the pancreatic cancer (PCa) microenvironment and influence spinal activity and pain sensation. DESIGN: Human SCs were exposed to hypoxia, to pancreatic cancer cells (PCCs) and/or to T-lymphocytes. Both SC and intrapancreatic nerves of patients with PCa with known pain severity were assessed for glial intermediate filament and hypoxia marker expression, proliferation and for transcriptional alterations of pain-related targets. In conditional PCa mouse models with selective in vivo blockade of interleukin (IL)-6 signalling (Ptf1a-Cre;LSL-Kras(G12D)/KC interbred with IL6(-/-) or sgp130(tg) mice), SC reactivity, abdominal mechanosensitivity and spinal glial/neuronal activity were quantified. RESULTS: Tumour hypoxia, PCC and/or T-lymphocytes activated SC via IL-6-signalling in vitro. Blockade of the IL-6-signalling suppressed SC activation around PCa precursor lesions (pancreatic intraepithelial neoplasia (PanIN)) in KC;IL6(-/-) (32.06%±5.25% of PanINs) and KC;sgp130(tg) (55.84%±5.51%) mouse models compared with KC mice (78.27%±3.91%). Activated SCs were associated with less pain in human PCa and with decreased abdominal mechanosensitivity in KC mice (von Frey score of KC: 3.9±0.5 vs KC;IL6(-/-) mice: 5.9±0.9; and KC;sgp130(tg): 10.21±1.4) parallel to attenuation of spinal astroglial and/or microglial activity. Activated SC exhibited a transcriptomic profile with anti-inflammatory and anti-nociceptive features. CONCLUSIONS: Activated SC in PCa recapitulate the hallmarks of 'reactive gliosis' and contribute to analgesia due to suppression of spinal glia. Our findings propose a mechanism for how cancer might remain pain-free via the SC-central glia interplay during cancer progression.

BACKGROUND: Diabetes mellitus is frequently observed in pancreatic cancer patients and is both a risk factor and an early manifestation of the disease. METHODS: We analysed the prognostic impact of diabetes on the outcome of pancreatic cancer following resection and adjuvant chemotherapy using individual patient data from three European Study Group for Pancreatic Cancer randomised controlled trials. Analyses were carried out to assess the association between clinical characteristics and the presence of preoperative diabetes, as well as the effect of diabetic status on overall survival. RESULTS: In total, 1105 patients were included in the analysis, of whom 257 (23%) had confirmed diabetes and 848 (77%) did not. Median (95% confidence interval (CI)) unadjusted overall survival in non-diabetic patients was 22.3 (20.8-24.1) months compared with 18.8 (16.9-22.1) months for diabetic patients (P=0.24). Diabetic patients were older, had increased weight and more co-morbidities. Following adjustment, multivariable analysis demonstrated that diabetic patients had an increased risk of death (hazard ratio: 1.19 (95% CI 1.01, 1.40), P=0.034). Maximum tumour size of diabetic patients was larger at randomisation (33.6 vs 29.7 mm, P=0.026). CONCLUSIONS: Diabetes mellitus was associated with increased tumour size and reduced survival following pancreatic cancer resection and adjuvant chemotherapy.

BACKGROUND: We investigated whether combinations of serum cytokines, used with logistic disease predictor models, could facilitate the detection of pancreatic ductal adenocarcinoma (PDAC). METHODS: The serum levels of 27 cytokines were measured in 241 subjects, 127 with PDAC, 49 with chronic pancreatitis, 20 with benign biliary obstruction and 45 healthy controls. Samples were split randomly into independent training and test sets. Cytokine biomarker panels were selected by identifying the top performing cytokines in best fit logistic regression models during multiple rounds of resampling from the training dataset. Disease prediction by logistic models, built using the resulting cytokine panels, was evaluated with training and test sets and further examined using resampled performance evaluation. RESULTS: For the discrimination of PDAC patients from patients with benign disease, a panel of IP-10, IL-6, PDGF plus CA19-9 offered improved diagnostic performance over CA19-9 alone in the training (AUC 0.838 vs. 0.678) and independent test set (AUC 0.884 vs. 0.798). For the discrimination of PDAC from CP, a panel of IL-8, CA19-9, IL-6 and IP-10 offered improved diagnostic performance over CA19-9 alone with the training (AUC 0.880 vs. 0.758) and test set (AUC 0.912 vs. 0.848). Finally, for the discrimination of PDAC in the presence of jaundice from benign controls with jaundice, a panel of IP-10, IL-8, IL-1b and PDGF demonstrated improvement over CA19-9 in the training (AUC 0.810 vs. 0.614) and test set (AUC 0.857 vs. 0.659). CONCLUSIONS: These findings support the potential role for cytokine panels in the discrimination of PDAC from patients with benign pancreatic diseases and warrant additional study.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by very early metastasis, suggesting the hypothesis that metastasis-associated changes may occur prior to actual tumor formation. In this study, we identified miR-192 as an epigenetically regulated suppressor gene with predictive value in this disease. miR-192 was downregulated by promoter methylation in both PDAC and chronic pancreatitis, the latter of which is a major risk factor for the development of PDAC. Functional studies in vitro and in vivo in mouse models of PDAC showed that overexpression of miR-192 was sufficient to reduce cell proliferation and invasion. Mechanistic analyses correlated changes in miR-192 promoter methylation and expression with epithelial-mesenchymal transition. Cell proliferation and invasion were linked to altered expression of the miR-192 target gene SERPINE1 that is encoding the protein plasminogen activator inhibitor-1 (PAI-1), an established regulator of these properties in PDAC cells. Notably, our data suggested that invasive capacity was altered even before neoplastic transformation occurred, as triggered by miR-192 downregulation. Overall, our results highlighted a role for miR-192 in explaining the early metastatic behavior of PDAC and suggested its relevance as a target to develop for early diagnostics and therapy. Cancer Res; 76(14); 4149-59. ©2016 AACR.

A small number of common susceptibility loci have been identified for pancreatic cancer, one of which is marked by rs401681 in the TERT-CLPTM1L gene region on chromosome 5p15.33. Because this region is characterized by low linkage disequilibrium, we sought to identify whether additional single nucleotide polymorphisms (SNPs) could be related to pancreatic cancer risk, independently of rs401681. We performed an in-depth analysis of genetic variability of the telomerase reverse transcriptase (TERT) and the telomerase RNA component (TERC) genes, in 5,550 subjects with pancreatic cancer and 7,585 controls from the PANcreatic Disease ReseArch (PANDoRA) and the PanScan consortia. We identified a significant association between a variant in TERT and pancreatic cancer risk (rs2853677, odds ratio = 0.85; 95% confidence interval = 0.80-0.90, p = 8.3 × 10(-8)). Additional analysis adjusting rs2853677 for rs401681 indicated that the two SNPs are independently associated with pancreatic cancer risk, as suggested by the low linkage disequilibrium between them (r(2) = 0.07, D' = 0.28). Three additional SNPs in TERT reached statistical significance after correction for multiple testing: rs2736100 (p = 3.0 × 10(-5) ), rs4583925 (p = 4.0 × 10(-5) ) and rs2735948 (p = 5.0 × 10(-5) ). In conclusion, we confirmed that the TERT locus is associated with pancreatic cancer risk, possibly through several independent variants.

There is strong epidemiologic evidence indicating that common genetic variability could be implicated in pancreatic cancer risk and, to date, various loci have been proposed. In particular, there is increasing evidence of the involvement of ABO gene variability and pancreatic cancer risk. In a large multicentric study of 1,028 pancreatic ductal adenocarcinoma cases and 2,257 controls in the context of the PANcreatic Disease ReseArch (PANDoRA) consortium, we investigated the suggested association with increased risk for carriers of single nucleotide polymorphisms (SNPs) determining the A or B allele in comparison with the O allele, which encodes for a non-functional enzyme. Since glycosyltransferase activity, encoded by ABO, is higher for the A1 variant compared with the A2 variant, we investigated the hypothesis that A1 carriers were at an increased risk of pancreatic cancer. In our analysis, carriers of the A1 were indeed at greater risk of developing the disease. In addition, we investigated the possible influence that genetic variability at the ABO locus may have in pancreatic cancer survival, but we observed no effect in our population.

• Disruption of Ca 2+ homeostasis causes mitochondrial dysfunction and pancreatic damage. • The role of oxidative stress in acute pancreatitis (AP) is unclear. • Inhibition of acinar cell Ca 2+ overload protects mitochondria and ameliorates AP. • Prevention of MPTP formation is protective in AP. • Clinical evaluation of new therapeutic strategies imminent. Disruption of Ca 2+ homeostasis can lead to severe damage of the pancreas, resulting in premature activation of digestive enzymes, vacuolisation and necrotic cell death, features typical of acute pancreatitis (AP). Therefore a fine balance between Ca 2+ release from internal stores, Ca 2+ entry and extrusion mechanisms is necessary to avoid injury. Precipitants of AP induce Ca 2+ overload of the pancreatic acinar cell that causes mitochondrial dysfunction, via formation of the mitochondrial permeability transition pore (MPTP), loss of ATP production and consequent necrosis. Oxidative stress has been shown to occur in the development of AP and may modify Ca 2+ signalling events in the acinar cell. However, the precise pathophysiological involvement is currently unclear and antioxidant therapy in the clinic has largely proved ineffective. Possible reasons for this are discussed, including evidence that ROS generation may determine cell death patterns. In contrast, recent evidence has indicated the potential for AP therapy via the prevention of Ca 2+ -dependent mitochondrial damage. Multiple approaches are indicated from preclinical findings; 1) inhibition of Ca 2+ release by IP 3 R blockade, 2) inhibition of Ca 2+ entry through Orai1 blockade and 3) prevention of MPTP formation. Clinical trials of drugs which prevent mitochondrial dysfunction induced by Ca 2+ overload of pancreatic acinar cells are imminent and may provide patient benefit for a disease that currently lacks specific therapy.

BACKGROUND: The aims of our study were to identify serum biomarkers that distinguish pancreatic cancer (pancreatic ductal adenocarcinoma, PDAC) patients from benign pancreatic disease patients and healthy subjects, and to assess the effects of jaundice on biomarker performance. METHODS: Isobaric tags for relative and absolute quantification were used to compare pooled serum and pancreatic juice samples from a test set of 59 and 25 subjects, respectively. Validation was undertaken in 113 independent subjects. RESULTS: Candidate proteins Complement C5, inter-α-trypsin inhibitor heavy chain H3, α1-β glycoprotein and polymeric immunoglobulin receptor were elevated in cancer, as were the reference markers CA19-9 and Reg3A. Biliary obstruction had a significant effect on the performance of the markers, in particular within the PDAC group where the presence of jaundice was associated with a significant increase in the levels of all six proteins (P<0.01). Consequently, in the absence of jaundice, proteins showed reduced sensitivity for PDAC patients over benign subjects and healthy controls (HCs). Similarly, in the presence of jaundice, markers showed reduced specificity for PDAC patients over benign subjects with jaundice. Combining markers enabled improved sensitivity for non-jaundiced PDAC patients over HCs and improved specificity for jaundiced PDAC patients over jaundiced benign disease subjects. CONCLUSIONS: The presence-absence of jaundice in the clinical scenario severely impacts the performance of biomarkers for PDAC diagnosis and has implications for their clinical translation.