ABSTRACT
Background: More than 700 million people worldwide suffer from diseases of the pancreas, such as diabetes, pancreatitis and pancreatic cancer. Often dysregulation of potassium (K+) channels, co-transporters and pumps can promote development and progression of many types of these diseases. The role of K+ transport system in pancreatic cell homeostasis and disease development remains largely unexplored. Potassium isotope analysis (δ41K), however, might have the potential to detect minute changes in metabolic processes relevant for pancreatic diseases. Methods: We assessed urinary K isotope composition in a case-control study by measuring K concentrations and δ41K in spot urines collected from patients diagnosed with pancreatic cancer (n=18), other pancreas-related diseases (n=14) and compared those data to healthy controls (n=16). Results: Our results show that urinary K+ levels for patients with diseased pancreas (benign and pancreatic cancer) are significantly lower than the healthy controls. For δ41K, the values tend to be higher for individuals with pancreatic cancer (mean δ41K = -0.58 ± 0.33) than for healthy individuals (mean δ41K = -0.78 ± 0.19) but the difference is not significant (p=0.08). For diabetics, urinary K+ levels are significantly lower (p=0.03) and δ41K is significantly higher (p=0.009) than for the healthy controls. These results suggest that urinary K+ levels and K isotopes can help identify K disturbances related to diabetes, an associated factors of all-cause mortality for diabetics. Conclusion: Although the K isotope results should be considered exploratory and hypothesis-generating and future studies should focus on larger sample size and δ41K analysis of other K-disrupting diseases (e.g., chronic kidney disease), our data hold great promise for K isotopes as disease marker.
Subject(s)
Diabetes Mellitus , Pancreatic Neoplasms , Potassium , Humans , Pancreatic Neoplasms/urine , Male , Female , Case-Control Studies , Middle Aged , Aged , Potassium/urine , Diabetes Mellitus/urine , Diabetes Mellitus/metabolism , Adult , Pancreas/metabolism , Isotopes/urineABSTRACT
The median age of patients with pancreatic ductal adenocarcinoma (PDAC) at diagnosis is 71 years; however, around 10% present with early-onset pancreatic cancer (EOPC), i.e., before age 50. The molecular mechanisms underlying such an early onset are unknown. We assessed the role of common PDAC drivers (KRAS, TP53, CDKN2A and SMAD4) and determined their mutational status and protein expression in 90 formalin-fixed, paraffin-embedded tissues, including multiple primary and matched metastases, from 37 EOPC patients. KRAS was mutated in 88% of patients; p53 was altered in 94%, and p16 and SMAD4 were lost in 86% and 71% of patients, respectively. Meta-synthesis showed a higher rate of p53 alterations in EOPC than in late-onset PDAC (94% vs. 69%, P = 0.0009) and significantly higher loss of SMAD4 (71% vs. 44%, P = 0.0025). The majority of EOPC patients accumulated aberrations in all four drivers; in addition, high tumour heterogeneity was observed across all tissues. The cumulative effect of an exceptionally high rate of alterations in all common PDAC driver genes combined with high tumour heterogeneity suggests an important mechanism underlying the early onset of PDAC.
Subject(s)
Carcinoma, Pancreatic Ductal , Pancreatic Neoplasms , Humans , Aged , Middle Aged , Tumor Suppressor Protein p53/genetics , Tumor Suppressor Protein p53/metabolism , Proto-Oncogene Proteins p21(ras)/genetics , Proto-Oncogene Proteins p21(ras)/metabolism , Pancreatic Neoplasms/pathology , Carcinoma, Pancreatic Ductal/genetics , Carcinoma, Pancreatic Ductal/pathology , Mutation/geneticsABSTRACT
The correlation between pancreatic ductal adenocarcinoma (PDAC) and diabetes-related mechanisms support the hypothesis that early therapeutic strategies targeting diabetes can contribute to PDAC risk reduction and treatment improvement. A systematic review was conducted, using PubMed, Embase and Cochrane Library databases, to evaluate the current evidence from clinical studies qualitatively examining the efficacy of four natural products: Curcumin-Curcuma longa L.; Thymoquinone-Nigella sativa L.; Genistein-Glycine max L.; Ginkgo biloba L.; and a low-carbohydrate ketogenic diet in type 2 diabetes (T2D) and PDAC treatment. A total of 28 clinical studies were included, showing strong evidence of inter-study heterogeneity. Used as a monotherapy or in combination with chemo-radiotherapy, the studied substances did not significantly improve the treatment response of PDAC patients. However, pronounced therapeutic efficacy was confirmed in T2D. The natural products and low-carbohydrate ketogenic diet, combined with the standard drugs, have the potential to improve T2D treatment and thus potentially reduce the risk of cancer development and improve multiple biological parameters in PDAC patients.
ABSTRACT
The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is mainly attributed to late diagnosis. We assessed the predictive performance of our previously reported urine biomarker panel for earlier detection of PDAC (LYVE1, REG1B and TFF1) in prediagnostic samples, alone and in combination with plasma CA19-9. This nested case-control study included 99 PDAC cases with urine samples prospectively collected up to 5 years prior to PDAC diagnosis and 198 matched controls. The samples were obtained from the Shanghai Women's Health Study (SWHS), the Shanghai Men's Health Studies (SMHS) and the Southern Community Cohort Study (SCCS). The urine biomarkers were measured by ELISA. Plasma CA19-9 was quantified by Luminex. Multiple logistic regression and Wilcoxon rank-sum and Mann-Whitney test were used for analysis. The internal validation approach was applied and the validated AUC estimators are reported on. The algorithm of urinary protein panel, urine creatinine and age named PancRISK, displayed similar AUC as CA19-9 up to 1 year before PDAC diagnosis (AUC = 0.79); however, the combination enhanced the AUCs to 0.89, and showed good discriminative ability (AUC = 0.77) up to 2 years. The combination showed sensitivity (SN) of 72% at 90% specificity (SP), and SP of 59% at 90% SN up to 1 year and 60% SN with 80% SP and 53% SP with 80% SN up to 2 years before PDAC diagnosis. Adding the clinical information on BMI value resulted in the overall improvement in performance of the PancRISK score. When combined with CA19-9, the urinary panel reached a workable model for detecting PDAC cases up to 2 years prior to diagnosis.
Subject(s)
Carcinoma, Pancreatic Ductal , Pancreatic Neoplasms , Male , Humans , Female , Case-Control Studies , CA-19-9 Antigen , Cohort Studies , Biomarkers, Tumor , China/epidemiology , Pancreatic Neoplasms/pathology , Carcinoma, Pancreatic Ductal/pathologyABSTRACT
Worldwide, lung cancer (LC) is the most common cause of cancer death, and any delay in the detection of new and relapsed disease serves as a major factor for a significant proportion of LC morbidity and mortality. Though invasive methods such as tissue biopsy are considered the gold standard for diagnosis and disease monitoring, they have several limitations. Therefore, there is an urgent need to identify and validate non-invasive biomarkers for the early diagnosis, prognosis, and treatment of lung cancer for improved patient management. Despite recent progress in the identification of non-invasive biomarkers, currently, there is a shortage of reliable and accessible biomarkers demonstrating high sensitivity and specificity for LC detection. In this review, we aim to cover the latest developments in the field, including the utility of biomarkers that are currently used in LC screening and diagnosis. We comment on their limitations and summarise the findings and developmental stages of potential molecular contenders such as microRNAs, circulating tumour DNA, and methylation markers. Furthermore, we summarise research challenges in the development of biomarkers used for screening purposes and the potential clinical applications of newly discovered biomarkers.
ABSTRACT
OBJECTIVES: Extracellular vesicles (EVs) are lipid bound vesicles secreted by cells into the extracellular environment. Studies have implicated EVs in cell proliferation, epithelial-mesenchymal transition, metastasis, angiogenesis, and mediating the interaction of tumor cells and microenvironment. A systematic characterization of EVs from pancreatic cancer cells and cancer-associated fibroblasts (CAFs) would be valuable for studying the roles of EV proteins in pancreatic tumorigenesis. METHODS: Proteomic and functional analyses were applied to characterize the proteomes of EVs released from 5 pancreatic cancer lines, 2 CAF cell lines, and a normal pancreatic epithelial cell line (HPDE). RESULTS: More than 1400 nonredundant proteins were identified in each EV derived from the cell lines. The majority of the proteins identified in the EVs from the cancer cells, CAFs, and HPDE were detected in all 3 groups, highly enriched in the biological processes of vesicle-mediated transport and exocytosis. Protein networks relevant to pancreatic tumorigenesis, including epithelial-mesenchymal transition, complement, and coagulation components, were significantly enriched in the EVs from cancer cells or CAFs. CONCLUSIONS: These findings support the roles of EVs as a potential mediator in transmitting epithelial-mesenchymal transition signals and complement response in the tumor microenvironment and possibly contributing to coagulation defects related to cancer development.
Subject(s)
Cancer-Associated Fibroblasts , Extracellular Vesicles , Pancreatic Neoplasms , Humans , Proteome/metabolism , Cancer-Associated Fibroblasts/metabolism , Proteomics , Extracellular Vesicles/metabolism , Extracellular Vesicles/pathology , Pancreatic Neoplasms/pathology , Cell Transformation, Neoplastic/metabolism , Tumor Microenvironment , Pancreatic NeoplasmsABSTRACT
Anterior gradient 2, AGR2, is a small, 20 kDa protein that plays a vital role in oxidative protein folding in the endoplasmic reticulum. AGR2 is involved in several signal transduction pathways that are essential for cell survival. It was initially discovered in the African clawed frog, Xenopus laevis, where it plays an important function in embryonic development. Akin to several other developmental genes, it is also frequently deregulated in cancer, where it plays a decisive role in tumor initiation, progression and metastasis. In this review, we have summarized currently known AGR2 functions, its expression and function in embryonic and cancer development, as well as its potential as a candidate tumor biomarker and promising new target for cancer immunotherapy.
ABSTRACT
OBJECTIVES: To facilitate exploring a link between pancreatic ductal adenocarcinoma (PDAC) and diabetes mellitus, we constructed a novel 3-dimensional (3D) in vitro coculturing system for studying interactions between PDAC and islet cells. METHODS: Adopting a 3D rotary cell culture system, we have cocultured several PDAC cell lines and MIN6 islet ß cells. The cellular morphology and viability of both cell types were investigated by time-lapse imaging, confocal and scanning electron microscopy, and immunohistochemistry. RESULTS: The developed coculture method enabled the formation of 3D PDAC and ß-cell spheroids (pseudo islets). We showed that surface morphology and growth of cultured cells mimicked their in vivo appearance. In addition, the coculture demonstrated the affinity of the PDAC cells to grow around and invade the pseudo islets. CONCLUSIONS: Using rotary cell culture system, we have established a simple in vitro 3D pancreatic model. It is a flexible culture system that can easily be expanded with the addition of various stromal/neural components to further mimic in vivo conditions, thus enabling holistic investigation of the endocrine and exocrine pancreas.
Subject(s)
Carcinoma, Pancreatic Ductal/metabolism , Cell Communication , Cell Culture Techniques, Three Dimensional/methods , Coculture Techniques/methods , Insulin-Secreting Cells/metabolism , Pancreatic Neoplasms/metabolism , Animals , Carcinoma, Pancreatic Ductal/pathology , Cell Line, Tumor , Cell Survival , Humans , Immunohistochemistry , Insulin-Secreting Cells/pathology , Mice , Microscopy, Confocal , Microscopy, Electron, Scanning , Pancreatic Neoplasms/pathology , Spheroids, Cellular/metabolism , Spheroids, Cellular/pathology , Spheroids, Cellular/ultrastructure , Time-Lapse Imaging/methodsABSTRACT
Pancreatic ductal adenocarcinoma (PDAC) carries a deadly diagnosis, due in large part to delayed presentation when the disease is already at an advanced stage. CA19-9 is currently the most commonly utilized biomarker for PDAC; however, it lacks the necessary accuracy to detect precursor lesions or stage I PDAC. Novel biomarkers that could detect this malignancy with improved sensitivity (SN) and specificity (SP) would likely result in more curative resections and more effective therapeutic interventions, changing thus the present dismal survival figures. The aim of this study was to systematically and comprehensively review the scientific literature on non-invasive biomarkers in biofluids such as blood, urine and saliva that were attempting earlier PDAC detection. The search performed covered a period of 10 years (January 2010-August 2020). Data were extracted using keywords search in the three databases: MEDLINE, Web of Science and Embase. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied for study selection based on establishing the risk of bias and applicability concerns in Patient Selection, Index test (biomarker assay) and Reference Standard (standard-of-care diagnostic test). Out of initially over 4000 published reports, 49 relevant studies were selected and reviewed in more detail. In addition, we discuss the present challenges and complexities in the path of translating the discovered biomarkers into the clinical setting. Our systematic review highlighted several promising biomarkers that could, either alone or in combination with CA19-9, potentially improve earlier detection of PDAC. Overall, reviewed biomarker studies should aim to improve methodological and reporting quality, and novel candidate biomarkers should be investigated further in order to demonstrate their clinical usefulness. However, challenges and complexities in the path of translating the discovered biomarkers from the research laboratory to the clinical setting remain and would have to be addressed before a more realistic breakthrough in earlier detection of PDAC is achieved.
ABSTRACT
Pancreatic ductal adenocarcinoma (PDAC), characterized by dense desmoplastic stroma laid down by pancreatic stellate cells (PSC), has no reliable diagnostic biomarkers for timely detection. A multi-center cohort of PDAC patients and controls (chronic pancreatitis, intra-ductal papillary neoplasms, gallstones and otherwise healthy) donated serum in an ethically approved manner. Serum PTX3 above 4.34 ng/mL has a higher sensitivity (86%, 95% confidence interval (CI): 65-97%) and specificity (86%, 95% CI: 79-91%), positive predictive value (97%) and likelihood ratio (6.05), and is superior when compared to serum CA19-9 and CEA for detection of PDAC. In vitro and ex vivo analyses of PTX3, in human PDAC samples, PSCs, cell lines and transgenic mouse model for PDAC, suggest that PTX3 originates from stromal cells, mainly PSC. In activated PSC, PTX3 secretion could be downregulated by rendering PSC quiescent using all-trans-retinoic acid (ATRA). PTX3 organizes hyaluronan in conjunction with tumor necrosis factor-stimulated gene 6 (TSG-6) and facilitates stellate and cancer cell invasion. In SCALOP clinical trial (ISRCTN96169987) testing chemo-radiotherapy without stromal targeting, PTX3 had no prognostic or predictive role. However, in STARPAC clinical trial (NCT03307148), stromal modulation by ATRA even at first dose is accompanied with serum PTX3 response in patients who later go on to demonstrate disease control but not those in whom the disease progresses. PTX3 is a putative stromally-derived biomarker for PDAC which warrants further testing in prospective, larger, multi-center cohorts and within clinical trials targeting stroma.
ABSTRACT
OBJECTIVES: To characterise the association between type 2 diabetes mellitus (T2DM) subtypes (new-onset T2DM (NODM) or long-standing T2DM (LSDM)) and pancreatic cancer (PC) risk, to explore the direction of causation through Mendelian randomisation (MR) analysis and to assess the mediation role of body mass index (BMI). DESIGN: Information about T2DM and related factors was collected from 2018 PC cases and 1540 controls from the PanGenEU (European Study into Digestive Illnesses and Genetics) study. A subset of PC cases and controls had glycated haemoglobin, C-peptide and genotype data. Multivariate logistic regression models were applied to derive ORs and 95% CIs. T2DM and PC-related single nucleotide polymorphism (SNP) were used as instrumental variables (IVs) in bidirectional MR analysis to test for two-way causal associations between PC, NODM and LSDM. Indirect and direct effects of the BMI-T2DM-PC association were further explored using mediation analysis. RESULTS: T2DM was associated with an increased PC risk when compared with non-T2DM (OR=2.50; 95% CI: 2.05 to 3.05), the risk being greater for NODM (OR=6.39; 95% CI: 4.18 to 9.78) and insulin users (OR=3.69; 95% CI: 2.80 to 4.86). The causal association between T2DM (57-SNP IV) and PC was not statistically significant (ORLSDM=1.08, 95% CI: 0.86 to 1.29, ORNODM=1.06, 95% CI: 0.95 to 1.17). In contrast, there was a causal association between PC (40-SNP IV) and NODM (OR=2.85; 95% CI: 2.04 to 3.98), although genetic pleiotropy was present (MR-Egger: p value=0.03). Potential mediating effects of BMI (125-SNPs as IV), particularly in terms of weight loss, were evidenced on the NODM-PC association (indirect effect for BMI in previous years=0.55). CONCLUSION: Findings of this study do not support a causal effect of LSDM on PC, but suggest that PC causes NODM. The interplay between obesity, PC and T2DM is complex.
Subject(s)
Diabetes Mellitus, Type 2/complications , Obesity/complications , Pancreatic Neoplasms/etiology , Aged , Body Mass Index , C-Peptide/blood , Case-Control Studies , Causality , Diabetes Mellitus, Type 2/etiology , Diabetes Mellitus, Type 2/genetics , Educational Status , Female , Glycated Hemoglobin/analysis , Humans , Male , Mediation Analysis , Middle Aged , Obesity/genetics , Pancreatic Neoplasms/complications , Pancreatic Neoplasms/genetics , Polymorphism, Single Nucleotide/genetics , Risk Factors , Sex Factors , Smoking/adverse effectsABSTRACT
Pancreatic ductal adenocarcinoma (PDAC) is a particularly challenging cancer, with very low 5-year survival rates. This low survival rate is linked to late stage diagnosis, associated with the lack of approved biomarkers. One approach that is receiving considerable attention is the use of volatile organic compounds (VOCs) that emanate from biological waste as biomarkers for disease. In this study, we used urine as our biological matrix and two VOC analysis platforms: gas chromatography - ion mobility spectrometry (GC-IMS) and GC time-of-flight mass spectrometry (GC-TOF-MS). We measured the urinary headspace of samples from patients with PDAC, chronic pancreatitis (CP) and healthy controls. In total, 123 samples were tested from these groups. Results indicate that both GC-IMS and GC-TOF-MS were able to discriminate PDAC from healthy controls with high confidence and an AUC (area under the curve) in excess of 0.85. However, both methods struggled to separate CP from PDAC, with the best result of AUC 0.58. This indicates that both conditions produce similar biomarkers in the urinary headspace. Chemical identification suggests that 2,6-dimethyl-octane, nonanal, 4-ethyl-1,2-dimethyl-benzene and 2-pentanone play an important role in separating these groups. Therefore, both techniques validate this approach in identifying subjects for further investigation in a clinical setting.
Subject(s)
Pancreatic Neoplasms , Volatile Organic Compounds , Gas Chromatography-Mass Spectrometry , Humans , Ion Mobility Spectrometry , Mass Spectrometry , Pancreatic Neoplasms/diagnosis , Volatile Organic Compounds/analysisABSTRACT
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with around 9% of patients surviving >5 years. Asymptomatic in its initial stages, PDAC is mostly diagnosed late, when already a locally advanced or metastatic disease, as there are no useful biomarkers for detection in its early stages, when surgery can be curative. We have previously described a promising biomarker panel (LYVE1, REG1A, and TFF1) for earlier detection of PDAC in urine. Here, we aimed to establish the accuracy of an improved panel, including REG1B instead of REG1A, and an algorithm for data interpretation, the PancRISK score, in additional retrospectively collected urine specimens. We also assessed the complementarity of this panel with CA19-9 and explored the daily variation and stability of the biomarkers and their performance in common urinary tract cancers. METHODS AND FINDINGS: Clinical specimens were obtained from multiple centres: Barts Pancreas Tissue Bank, University College London, University of Liverpool, Spanish National Cancer Research Center, Cambridge University Hospital, and University of Belgrade. The biomarker panel was assayed on 590 urine specimens: 183 control samples, 208 benign hepatobiliary disease samples (of which 119 were chronic pancreatitis), and 199 PDAC samples (102 stage I-II and 97 stage III-IV); 50.7% were from female individuals. PDAC samples were collected from patients before treatment. The samples were assayed using commercially available ELISAs. Statistical analyses were performed using non-parametric Kruskal-Wallis tests adjusted for multiple comparisons, and multiple logistic regression. Training and validation datasets for controls and PDAC samples were obtained after random division of the whole available dataset in a 1:1 ratio. The substitution of REG1A with REG1B enhanced the performance of the panel to detect resectable PDAC. In a comparison of controls and PDAC stage I-II samples, the areas under the receiver operating characteristic curve (AUCs) increased from 0.900 (95% CI 0.843-0.957) and 0.926 (95% CI 0.843-1.000) in the training (50% of the dataset) and validation sets, respectively, to 0.936 in both the training (95% CI 0.903-0.969) and the validation (95% CI 0.888-0.984) datasets for the new panel including REG1B. This improved panel showed both sensitivity (SN) and specificity (SP) to be >85%. Plasma CA19-9 enhanced the performance of this panel in discriminating PDAC I-II patients from controls, with AUC = 0.992 (95% CI 0.983-1.000), SN = 0.963 (95% CI 0.913-1.000), and SP = 0.967 (95% CI 0.924-1.000). We demonstrate that the biomarkers do not show significant daily variation, and that they are stable for up to 5 days at room temperature. The main limitation of our study is the low number of stage I-IIA PDAC samples (n = 27) and lack of samples from individuals with hereditary predisposition to PDAC, for which specimens collected from control individuals were used as a proxy. CONCLUSIONS: We have successfully validated our urinary biomarker panel, which was improved by substituting REG1A with REG1B. At a pre-selected cutoff of >80% SN and SP for the affiliated PancRISK score, we demonstrate a clinically applicable risk stratification tool with a binary output for risk of developing PDAC ('elevated' or 'normal'). PancRISK provides a step towards precision surveillance for PDAC patients, which we will test in a prospective clinical study, UroPanc.
Subject(s)
Biomarkers, Tumor/urine , Carcinoma, Pancreatic Ductal/diagnosis , Early Detection of Cancer , Pancreatic Neoplasms/diagnosis , Adult , Aged , Aged, 80 and over , Antigens, Tumor-Associated, Carbohydrate/blood , Carcinoma, Pancreatic Ductal/blood , Carcinoma, Pancreatic Ductal/urine , Europe , Female , Humans , Lithostathine/urine , Male , Middle Aged , Pancreatic Neoplasms/blood , Pancreatic Neoplasms/urine , Predictive Value of Tests , Reproducibility of Results , Retrospective Studies , Trefoil Factor-1/urine , Urinalysis , Vesicular Transport Proteins/urine , Young AdultABSTRACT
S100P, a calcium-binding protein, is known to advance tumor progression and metastasis in pancreatic and several other cancers. Herein is described the in silico identification of a putative binding pocket of S100P to identify, synthesize and evaluate novel small molecules with the potential to selectively bind S100P and inhibit its activation of cell survival and metastatic pathways. The virtual screening of a drug-like database against the S100P model led to the identification of over 100 clusters of diverse scaffolds. A representative test set identified a number of structurally unrelated hits that inhibit S100P-RAGE interaction, measured by ELISA, and reduce in vitro cell invasion selectively in S100P-expressing pancreatic cancer cells at 10 µM. This study establishes a proof of concept in the potential for rational design of small molecule S100P inhibitors for drug candidate development.
Subject(s)
Antineoplastic Agents/pharmacology , Drug Design , Pancreatic Neoplasms/pathology , S100 Proteins/antagonists & inhibitors , Small Molecule Libraries/pharmacology , Antineoplastic Agents/chemistry , Cell Line, Tumor , Dose-Response Relationship, Drug , Gene Expression Regulation, Neoplastic/drug effects , Humans , Neoplasm Invasiveness , Small Molecule Libraries/chemistryABSTRACT
Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest types of cancer. Its high mortality rate is attributed largely to the difficulty of early diagnosis. Analysis of urine is an excellent non-invasive approach to trace changes in biochemical reactions due to cancer development. Here we show remarkable differences in concentration of several essential metals: significantly lower levels of urinary calcium and magnesium and increased levels of copper and zinc in PDAC when compared to healthy controls, and demonstrate that a combined analysis of these essential metals are accurate indicators (sensitivity = 99.5%) for metal dyshomeostasis in PDAC. In addition, natural stable zinc isotope composition (δ66/64Zn) in urine reveals the preferential excretion of isotopically light zinc in PDAC (δ66/64Znmedian = -0.15) compared to healthy controls (δ66/64Znmedian = +0.02), likely supporting the dysregulation of metalloproteins. These findings demonstrate for the first time that metallomics is a promising approach for discovery of biomarkers for detection of patients with PDAC, completely non-invasively, using urine samples.
Subject(s)
Biomarkers, Tumor/urine , Carcinoma, Pancreatic Ductal/diagnosis , Metals/urine , Pancreatic Neoplasms/diagnosis , Carcinoma, Pancreatic Ductal/urine , Case-Control Studies , Humans , Pancreatic Neoplasms/urine , PrognosisABSTRACT
BACKGROUND: Despite smoking being a well-established risk factor for pancreatic cancer, there is a need to further characterize pancreatic cancer risk according to lifespan smoking patterns and other smoking features, such as tobacco type. Our aim was to deeply investigate them within a large European case-control study. METHODS: Tobacco smoking habits and other relevant information were obtained from 2,009 cases and 1,532 controls recruited in the PanGenEU study using standardized tools. Multivariate logistic regression analysis was performed to evaluate pancreatic cancer risk by smoking characteristics and interactions with other pancreatic cancer risk factors. Fractional polynomials and restricted cubic splines were used to test for nonlinearity of the dose-response relationships and to analyze their shape. RESULTS: Relative to never-smokers, current smokers [OR = 1.72; 95% confidence interval (95% CI), 1.39-2.12], those inhaling into the throat (OR = 1.48; 95% CI, 1.11-1.99) or chest (OR = 1.33; 95% CI, 1.12-1.58), and those using nonfiltered cigarettes (OR = 1.69; 95% CI, 1.10-2.61), were all at an increased pancreatic cancer risk. Pancreatic cancer risk was highest in current black tobacco smokers (OR = 2.09; 95% CI, 1.31-3.41), followed by blond tobacco smokers (OR = 1.43; 95% CI, 1.01-2.04). Childhood exposure to tobacco smoke relative to parental smoking was also associated with increased pancreatic cancer risk (OR = 1.24; 95% CI, 1.03-1.49). Dose-response relationships for smoking duration, intensity, cumulative dose, and smoking cessation were nonlinear and showed different shapes by tobacco type. Effect modification by family history of pancreatic cancer and diabetes was likely. CONCLUSIONS: This study reveals differences in pancreatic cancer risk by tobacco type and other habit characteristics, as well as nonlinear risk associations. IMPACT: This characterization of smoking-related pancreatic cancer risk profiles may help in defining pancreatic cancer high-risk populations.
Subject(s)
Pancreatic Neoplasms/epidemiology , Tobacco Smoke Pollution/statistics & numerical data , Tobacco Smoking/epidemiology , Aged , Case-Control Studies , Diabetes Mellitus/epidemiology , Europe/epidemiology , Female , Humans , Male , Medical History Taking/statistics & numerical data , Middle Aged , Non-Smokers/statistics & numerical data , Odds Ratio , Risk Factors , Smokers/statistics & numerical data , Time Factors , Tobacco Smoke Pollution/adverse effects , Tobacco Smoking/adverse effectsABSTRACT
BACKGROUND: An accurate and simple risk prediction model that would facilitate earlier detection of pancreatic adenocarcinoma (PDAC) is not available at present. In this study, we compare different algorithms of risk prediction in order to select the best one for constructing a biomarker-based risk score, PancRISK. METHODS: Three hundred and seventy-nine patients with available measurements of three urine biomarkers, (LYVE1, REG1B and TFF1) using retrospectively collected samples, as well as creatinine and age, were randomly split into training and validation sets, following stratification into cases (PDAC) and controls (healthy patients). Several machine learning algorithms were used, and their performance characteristics were compared. The latter included AUC (area under ROC curve) and sensitivity at clinically relevant specificity. RESULTS: None of the algorithms significantly outperformed all others. A logistic regression model, the easiest to interpret, was incorporated into a PancRISK score and subsequently evaluated on the whole data set. The PancRISK performance could be even further improved when CA19-9, commonly used PDAC biomarker, is added to the model. CONCLUSION: PancRISK score enables easy interpretation of the biomarker panel data and is currently being tested to confirm that it can be used for stratification of patients at risk of developing pancreatic cancer completely non-invasively, using urine samples.
Subject(s)
Biomarkers, Tumor/urine , Carcinoma, Pancreatic Ductal/urine , Models, Statistical , Pancreatic Neoplasms/urine , Aged , Algorithms , Carcinoma, Pancreatic Ductal/diagnosis , Carcinoma, Pancreatic Ductal/pathology , Case-Control Studies , Creatinine/urine , Early Detection of Cancer/methods , Humans , Lithostathine/urine , Logistic Models , Machine Learning , Middle Aged , Neoplasm Staging , Pancreatic Neoplasms/diagnosis , Pancreatic Neoplasms/pathology , Predictive Value of Tests , Risk , Trefoil Factor-1/urine , Vesicular Transport Proteins/urineABSTRACT
Anterior gradient 2 (AGR2), a protein disulfide isomerase, shows two subcellular localizations: intracellular (iAGR2) and extracellular (eAGR2). In healthy cells that express AGR2, the predominant form is iAGR2, which resides in the endoplasmic reticulum. In contrast, cancer cells secrete and express eAGR2 on the cell surface. We wanted to test if AGR2 is a cancer-specific tumor-associated antigen. We utilized two AGR2 antibodies, P3A5 and P1G4, for in vivo tumor localization and tumor growth inhibition. The monoclonal antibodies recognized both human AGR2 and mouse Agr2. Biodistribution experiments using a syngeneic mouse model showed high uptake of P3A5 AGR2 antibody in xenografted eAgr2+ pancreatic tumors, with limited uptake in normal tissues. In implanted human patient-derived eAGR2+ pancreatic cancer xenografts, tumor growth inhibition was evaluated with antibodies and Gemcitabine (Gem). Inhibition was more potent by P1G4 + Gem combination than Gem alone or P3A5 + Gem. We converted these two antibodies to human:mouse chimeric forms: the constructed P3A5 and P1G4 chimeric mVLhCκ and mVHhCγ (γ1, γ2, γ4) genes were inserted in a single mammalian expression plasmid vector, and transfected into human 293F cells. Expressed human:mouse chimeric IgG1, IgG2 and IgG4 antibodies retained AGR2 binding. Increase in IgG yield by transfected cells could be obtained with serial transfection of vectors with different drug resistance. These chimeric antibodies, when incubated with human blood, effectively lysed eAGR2+ PC3 prostate cancer cells. We have, thus, produced humanized anti-AGR2 antibodies that, after further testing, might be suitable for treatment against a variety of eAGR2+ solid tumors.
ABSTRACT
The molecular mechanisms leading to aryl hydrocarbon receptor interacting protein (AIP) mutation-induced aggressive, young-onset growth hormone-secreting pituitary tumors are not fully understood. In this study, we have identified that AIP-mutation-positive tumors are infiltrated by a large number of macrophages compared to sporadic tumors. Tissue from pituitary-specific Aip-knockout (AipFlox/Flox;Hesx1Cre/+) mice recapitulated this phenotype. Our human pituitary tumor transcriptome data revealed the "epithelial-to-mesenchymal transition (EMT) pathway" as one of the most significantly altered pathways in AIPpos tumors. Our in vitro data suggest that bone marrow-derived macrophage-conditioned media induces more prominent EMT-like phenotype and enhanced migratory and invasive properties in Aip-knockdown somatomammotroph cells compared to non-targeting controls. We identified that tumor-derived cytokine CCL5 is upregulated in AIP-mutation-positive human adenomas. Aip-knockdown GH3 cell-conditioned media increases macrophage migration, which is inhibited by the CCL5/CCR5 antagonist maraviroc. Our results suggest that a crosstalk between the tumor and its microenvironment plays a key role in the invasive nature of AIP-mutation-positive tumors and the CCL5/CCR5 pathway is a novel potential therapeutic target.