Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer

Analysis of exposome and genetic variability suggests stress as a major contributor for development of pancreatic ductal adenocarcinoma

BACKGROUND

The current knowledge on pancreatic ductal adenocarcinoma (PDAC) risk factors is limited and no study has comprehensively tested the exposome in combination with the genetic variability in relation to the disease susceptibility.

AIM

The aim of this study was to analyze the exposome and its interaction with known genetic susceptibility loci, in relation to PDAC risk.

METHODS

A case-control study nested in UK Biobank cohort was conducted on 816 PDAC cases and 302,645 controls. A total of 347 exposure variables, and a polygenic risk score (PRS) were analyzed through logistic regression. Gene-environment interaction analyses were conducted.

RESULTS

A total of 52 associations under the Bonferroni corrected threshold of p < 1.46 × 10-4 were observed. Known risk factors such as smoking, pancreatitis, diabetes, PRS, heavy alcohol drinking and overweight were replicated in this study. As for novel associations, a clear indication for length and intensity of mobile phone use and the stress-related factors and stressful events with increase of PDAC risk was observed. Although the PRS was associated with PDAC risk (P = 2.09 × 10-9), statistically significant gene-exposome interactions were not identified.

CONCLUSION

In conclusion, our results suggest that a stressful lifestyle and sedentary behaviors may play a major role in PDAC susceptibility independently from the genetic background.

Large-scale integration of omics and electronic health records to identify potential risk protein biomarkers and therapeutic drugs for cancer prevention and intervention

Identifying risk protein targets and their therapeutic drugs is crucial for effective cancer prevention. Here, we conduct integrative and fine-mapping analyses of large genome-wide association studies data for breast, colorectal, lung, ovarian, pancreatic, and prostate cancers, and characterize 710 lead variants independently associated with cancer risk. Through mapping protein quantitative trait loci (pQTL) for these variants using plasma proteomics data from over 75,000 participants, we identify 365 proteins associated with cancer risk. Subsequent colocalization analysis identifies 101 proteins, including 74 not reported in previous studies. We further characterize 36 potential druggable proteins for cancers or other disease indications. Analyzing >3.5 million electronic health records, we uncover five drugs (Haloperidol, Trazodone, Tranexamic Acid, Haloperidol, and Captopril) associated with increased cancer risk and two drugs (Caffeine and Acetazolamide) linked to reduced colorectal cancer risk. This study offers novel insights into therapeutic drugs targeting risk proteins for cancer prevention and intervention.

radioGWAS links radiome to genome to discover driver genes with somatic mutations for heterogeneous tumor image phenotype in pancreatic cancer

Addressing the significant level of variability exhibited by pancreatic cancer necessitates the adoption of a systems biology approach that integrates molecular data, biological properties of the tumors, medical images, and clinical features of the patients. In this study, a comprehensive multi-omics methodology was employed to examine a distinctive collection of patient dataset containing rapid autopsy tumor and normal tissue samples as well as longitudinal imaging with a focus on pancreatic cancer. By performing a whole exome sequencing analysis on tumor and normal tissues to identify somatic gene variants and a radiomic feature analysis to tumor CT images, the genome-wide association approach established a connection between pancreatic cancer driver genes and relevant radiomic features, enabling a thorough and quantitative assessment of the heterogeneity of pancreatic tumors. The significant association between sets of genes and radiomic features revealed the involvement of genes in shaping tumor morphological heterogeneity. Some results of the association established a connection between the molecular level mechanism and their outcomes at the level of tumor structural heterogeneity. Because tumor structure and tumor structural heterogeneity are related to the patients' overall survival, patients who had pancreatic cancer driver gene mutations with an association to a certain radiomic feature have been observed to experience worse survival rates than cases without these somatic mutations. Furthermore, the association analysis has revealed potential gene mutations and radiomic feature candidates that warrant further investigation in future research endeavors.

Identifying therapeutic targets for cancer among 2074 circulating proteins and risk of nine cancers

Circulating proteins can reveal key pathways to cancer and identify therapeutic targets for cancer prevention. We investigate 2,074 circulating proteins and risk of nine common cancers (bladder, breast, endometrium, head and neck, lung, ovary, pancreas, kidney, and malignant non-melanoma) using cis protein Mendelian randomisation and colocalization. We conduct additional analyses to identify adverse side-effects of altering risk proteins and map cancer risk proteins to drug targets. Here we find 40 proteins associated with common cancers, such as PLAUR and risk of breast cancer [odds ratio per standard deviation increment: 2.27, 1.88-2.74], and with high-mortality cancers, such as CTRB1 and pancreatic cancer [0.79, 0.73-0.85]. We also identify potential adverse effects of protein-altering interventions to reduce cancer risk, such as hypertension. Additionally, we report 18 proteins associated with cancer risk that map to existing drugs and 15 that are not currently under clinical investigation. In sum, we identify protein-cancer links that improve our understanding of cancer aetiology. We also demonstrate that the wider consequence of any protein-altering intervention on well-being and morbidity is required to interpret any utility of proteins as potential future targets for therapeutic prevention.

Understanding familial risk of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease that is the result of an accumulation of sequential genetic alterations. These genetic alterations can either be inherited, such as pathogenic germline variants that are associated with an increased risk of cancer, or acquired, such as somatic mutations that occur during the lifetime of an individual. Understanding the genetic basis of inherited risk of PDAC is essential to advancing patient care and outcomes through improved clinical surveillance, early detection initiatives, and targeted therapies. In this review we discuss factors associated with an increased risk of PDAC, the prevalence of genetic variants associated with an increased risk in patients with PDAC, estimates of PDAC risk in carriers of pathogenic germline variants in genes associated with an increased risk of PDAC. The role of common variants in pancreatic cancer risk will also be discussed.

Genetic and other risk factors for pancreatic ductal adenocarcinoma (PDAC)

Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at an advanced stage, resulting in poor prognosis and low 5-year survival rates. While early evidence suggests increased long-term survival in those with screen-detected resectable cancers, surveillance imaging is currently only recommended for individuals with a lifetime risk of PDAC ≥ 5%. Identification of risk factors for PDAC provides opportunities for early detection, risk reducing interventions, and targeted therapies, thus potentially improving patient outcomes. Here, we summarize modifiable and non-modifiable risk factors for PDAC. We review hereditary cancer syndromes associated with risk for PDAC and their implications for patients and their relatives. In addition, other biologically relevant pathways and environmental and lifestyle risk factors are discussed. Future work may focus on elucidating additional genetic, environmental, and lifestyle risk factors that may modify PDAC risk to continue to identify individuals at increased risk for PDAC who may benefit from surveillance and risk reducing interventions.

Identification of Pancreatic Cancer Germline Risk Variants With Effects That Are Modified by Smoking

PURPOSE

Pancreatic cancer (PC) is a deadly disease most often diagnosed in late stages. Identification of high-risk subjects could both contribute to preventative measures and help diagnose the disease at earlier timepoints. However, known risk factors, assessed independently, are currently insufficient for accurately stratifying patients. We use large-scale data from the UK Biobank (UKB) to identify genetic variant-smoking interaction effects and show their importance in risk assessment.

METHODS

We draw data from 15,086,830 genetic variants and 315,512 individuals in the UKB. There are 765 cases of PC. Crucially, robust resampling corrections are used to overcome well-known challenges in hypothesis testing for interactions. Replication analysis is conducted in two independent cohorts totaling 793 cases and 570 controls. Integration of functional annotation data and construction of polygenic risk scores (PRS) demonstrate the additional insight provided by interaction effects.

RESULTS

We identify the genome-wide significant variant rs77196339 on chromosome 2 (per minor allele odds ratio in never-smokers, 2.31 [95% CI, 1.69 to 3.15]; per minor allele odds ratio in ever-smokers, 0.53 [95% CI, 0.30 to 0.91]; P = 3.54 × 10-8) as well as eight other loci with suggestive evidence of interaction effects (P < 5 × 10-6). The rs77196339 region association is validated (P < .05) in the replication sample. PRS incorporating interaction effects show improved discriminatory ability over PRS of main effects alone.

CONCLUSION

This study of genome-wide germline variants identified smoking to modify the effect of rs77196339 on PC risk. Interactions between known risk factors can provide critical information for identifying high-risk subjects, given the relative inadequacy of models considering only main effects, as demonstrated in PRS. Further studies are necessary to advance toward comprehensive risk prediction approaches for PC.

Elucidating the role of blood metabolites on pancreatic cancer risk using two-sample Mendelian randomization analysis

Pancreatic ductal adenocarcinoma (PDAC) is an uncommon but highly fatal malignancy. Identifying causal metabolite biomarkers offers an opportunity to facilitate effective risk assessment strategies for PDAC. In this study, we performed a two-sample Mendelian randomization (MR) study to characterize the potential causal effects of metabolites in plasma on PDAC risk. Genetic instruments were determined for a total of 506 metabolites from one set of comprehensive genome-wide association studies (GWAS) involving 913 individuals of European ancestry from the INTERVAL/EPIC-Norfolk cohorts. Another set of genetic instruments was developed for 483 metabolites from an independent GWAS conducted with 8299 individuals of European ancestry from the Canadian Longitudinal Study on Aging (CLSA) cohort. We analyzed GWAS data of the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), comprising 8275 PDAC cases and 6723 controls of European ancestry. The association of metabolites with PDAC risk was assessed using the inverse-variance weighted (IVW) method, and complemented with sensitivity analyses of MR-Egger and MR-PRESSO tests. Potential side effects of targeting the identified metabolites for PDAC intervention were further evaluated by a phenome-wide MR (Phe-MR) analysis. Forty-four unique metabolites were identified to be significantly associated with PDAC risk, of which four top-ranking metabolites (X: 12798, X: 11787, X: 11308 and X: 19141) showed replication evidence when using instruments developed from both two cohorts. Our results highlight novel blood metabolites related to PDAC risk, which may help prioritize metabolic features for PDAC mechanistic research and further evaluation of their potential role in PDAC risk assessment.

Evidence for a causal link between intra-pancreatic fat deposition and pancreatic cancer: A prospective cohort and Mendelian randomization study

Prior observational studies suggest an association between intra-pancreatic fat deposition (IPFD) and pancreatic ductal adenocarcinoma (PDAC); however, the causal relationship is unclear. To elucidate causality, we conduct a prospective observational study using magnetic resonance imaging (MRI)-measured IPFD data and also perform a Mendelian randomization study using genetic instruments for IPFD. In the observational study, we use UK Biobank data (N = 29,463, median follow-up: 4.5 years) and find that high IPFD (>10%) is associated with PDAC risk (adjusted hazard ratio [HR]: 3.35, 95% confidence interval [95% CI]: 1.60-7.00). In the Mendelian randomization study, we leverage eight out of nine IPFD-associated genetic variants (p < 5 × 10-8) from a genome-wide association study in the UK Biobank (N = 25,617) and find that genetically determined IPFD is associated with PDAC (odds ratio [OR] per 1-standard deviation [SD] increase in IPFD: 2.46, 95% CI: 1.38-4.40) in the Pancreatic Cancer Cohort Consortium I, II, III (PanScan I-III)/Pancreatic Cancer Case-Control Consortium (PanC4) dataset (8,275 PDAC cases and 6,723 non-cases). This study provides evidence for a potential causal role of IPFD in the pathogenesis of PDAC. Thus, reducing IPFD may lower PDAC risk.

[Hereditary and familial forms of pancreatic adenocarcinoma: Genetic determinism, patients eligible for systematic screening, screening methods and results]

Systematic screening for pancreatic cancer in high risk individuals is justified by the poor prognosis of the majority of cases diagnosed at a symptomatic stage that are mostly advanced and unresectable Individual risk assessment is based on both genetic data and family history. The screening of a panel of susceptibiility genes should be offered to any affected individual when a genetic predisposition is suspected. An international consortium has proposed a definition of the at risk population, candidate for screening, and there is a consensus on the target lesions of this screening: early adenocarcinoma and benign lesions with a high potential for malignant transformation: Intraductal Papillary Mucinous Neopasm (IPMN) and Pancreatic Intraepithelial Neoplasia (PanIN) with high-grade dysplasia. Its modalities currently consist of an annual pancreatic MRI and/or endoscopic ultrasound (EUS), associated with screening for diabetes mellitus. The main limitation of screening, the effectiveness of which has not yet been demonstrated, is its lack of sensitivity, which results in a non-negligible rate of interval cancers and sometimes advanced diagnoses. Insufficient specificity is also imperfect, in particular with regard to benign lesions with a low potential for degeneration, and can lead to the proposal of unjustified surgeries. This situation makes the future integration of new imaging techniques and promising new biological approaches that are being explored highly desirable.

Healthy dietary patterns, genetic risk, and gastrointestinal cancer incident risk: a large-scale prospective cohort study

BACKGROUND

Dietary patterns have been associated with several cancers, especially gastrointestinal cancer (GIC). However, whether a healthy dietary pattern could modify the risk of GIC among people with different genetic backgrounds is not clear.

OBJECTIVE

The objective of the study was to investigate how dietary patterns and genetic susceptibility contribute to the risk of GIC independently and jointly.

METHODS

This large-scale prospective cohort study included 105,463 participants in UK Biobank who were aged 40-72 y and cancer-free at baseline. Dietary intake (Oxford WebQ) was used to calculate dietary pattern scores including dietary approach to stop hypertension (DASH) score and healthful plant-based diet index (hPDI). Genetic risk was quantified by a polygenic risk score (PRS) comprising 129 known GIC-associated loci. Cox proportional hazards regression was performed to estimate the associations of dietary patterns and PRS with GIC incidence after adjusting for potential confounders.

RESULTS

Over a median follow-up of 11.70 y, 1,661 participants were diagnosed with GIC. DASH and hPDI were associated with 20% and 36% reductions, respectively, in GIC risk. Low PRS was associated with a 30 % decrease in GIC risk (HR: 0.70; 95% CI: 0.62, 0.79). Participants with healthy dietary scores at high-genetic risk had a lower GIC risk with HR of 0.77 (95% CI: 0.60, 0.98) for DASH and 0.66 (95% CI: 0.52, 0.84) for hPDI than those with unhealthy dietary score. Participants with both high-dietary score and low-genetic risk showed the lowest risk of GIC, with HR of 0.58 (95% CI: 0.45, 0.75) for DASH and 0.45 (95% CI: 0.34, 0.58) for hPDI.

CONCLUSIONS

Adherence to DASH and hPDI were associated with a lower risk of some gastrointestinal cancers, and these 2 dietary patterns may partly compensate for genetic predispositions to cancer. Our results advance the development of precision medicine strategies that consider both dietary patterns and genetics to improve gastrointestinal health.

Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC.

SIGNIFICANCE

PDAC is a notoriously difficult-to-treat malignancy, and our limited understanding of causal protein markers hampers progress in developing effective early detection strategies and treatments. Our study identifies novel causal proteins using genetic instruments and subsequently functionally validates selected novel proteins. This dual approach enhances our understanding of PDAC etiology and potentially opens new avenues for therapeutic interventions.

Splicing transcriptome-wide association study to identify splicing events for pancreatic cancer risk

A large proportion of the heritability of pancreatic cancer risk remains elusive, and the contribution of specific mRNA splicing events to pancreatic cancer susceptibility has not been systematically evaluated. In this study, we performed a large splicing transcriptome-wide association study (spTWAS) using three modeling strategies (Enet, LASSO and MCP) to develop alternative splicing genetic prediction models for identifying novel susceptibility loci and splicing introns for pancreatic cancer risk by assessing 8275 pancreatic cancer cases and 6723 controls of European ancestry. Data from 305 subjects of whom the majority are of European descent in the Genotype-Tissue Expression Project (GTEx) were used and both cis-acting and promoter-enhancer interaction regions were considered to build these models. We identified nine splicing events of seven genes (ABO, UQCRC1, STARD3, ETAA1, CELA3B, LGR4 and SFT2D1) that showed an association of genetically predicted expression with pancreatic cancer risk at a false discovery rate ≤0.05. Of these genes, UQCRC1 and LGR4 have not yet been reported to be associated with pancreatic cancer risk. Fine-mapping analyses supported likely causal associations corresponding to six splicing events of three genes (P4HTM, ABO and PGAP3). Our study identified novel genes and splicing events associated with pancreatic cancer risk, which can improve our understanding of the etiology of this deadly malignancy.

Association of genetic risk and lifestyle with pancreatic cancer and their age dependency: a large prospective cohort study in the UK Biobank

BACKGROUND

Pancreatic cancer (PC) is influenced by both genetic and lifestyle factors. However, further research is still needed to comprehensively clarify the relationships among lifestyle, genetic factors, their combined effect on PC, and how these associations might be age-dependent.

METHODS

We included 340,631 participants from the UK Biobank. Three polygenic risk score (PRS) models for PC were applied, which were derived from the previous study and were categorized as low, intermediate, and high. Two healthy lifestyle scores (HLSs) were constructed using 9 lifestyle factors based on the World Cancer Research Fund/American Institute of Cancer Research (WCRF/AICR) lifestyle score and the American Cancer Society (ACS) guidelines and were categorized as unfavorable, intermediate, and favorable. Data were analyzed using Cox proportional hazards models.

RESULTS

There were 1,129 cases of incident PC during a median follow-up of 13.05 years. Higher PRS was significantly associated with an increased risk of PC (hazard ratio [HR], 1.58; 95% confidence intervals [CI], 1.47-1.71). Adhering to a favorable lifestyle was associated with a lower risk (HR, 0.48; 95% CI, 0.41-0.56). Participants with an unfavorable lifestyle and a high PRS had the highest risk of PC (HR, 2.84; 95% CI, 2.22-3.62). Additionally, when stratified by age, a favorable lifestyle was most pronounced associated with a lower risk of PC among participants aged ≤ 60 years (HR, 0.35; 95% CI, 0.23-0.54). However, the absolute risk reduction was more pronounced among those aged > 70 years (ARR, 0.19%, 95% CI, 0.13%-0.26%). A high PRS was more strongly associated with PC among participants aged ≤ 60 years (HR, 1.89; 95% CI, 1.30-2.73). Furthermore, we observed a significant multiplicative interaction and several significant additive interactions.

CONCLUSIONS

A healthy lifestyle was associated with a lower risk of PC, regardless of the participants' age, sex, or genetic risk. Importantly, our findings indicated the age-dependent association of lifestyle and genetic factors with PC, emphasizing the importance of early adoption for effective prevention and potentially providing invaluable guidance for setting the optimal age to start preventive measures.

A scan of all coding region variants of the human genome, identifies 13q12.2-rs9579139 and 15q24.1-rs2277598 as novel risk loci for pancreatic ductal adenocarcinoma

Coding sequence variants comprise a small fraction of the germline genetic variability of the human genome. However, they often cause deleterious change in protein function and are therefore associated with pathogenic phenotypes. To identify novel pancreatic ductal adenocarcinoma (PDAC) risk loci, we carried out a complete scan of all common missense and synonymous SNPs and analysed them in a case-control study comprising four different populations, for a total of 14 538 PDAC cases and 190 657 controls. We observed a statistically significant association between 13q12.2-rs9581957-T and PDAC risk (P = 2.46 × 10-9), that is in linkage disequilibrium (LD) with a deleterious missense variant (rs9579139) of the URAD gene. Recent findings suggest that this gene is active in peroxisomes. Considering that peroxisomes have a key role as molecular scavengers, especially in eliminating reactive oxygen species, a malfunctioning URAD protein might expose the cell to a higher load of potentially DNA damaging molecules and therefore increase PDAC risk. The association was observed in individuals of European and Asian ethnicity. We also observed the association of the missense variant 15q24.1-rs2277598-T, that belongs to BBS4 gene, with increased PDAC risk (P = 1.53 × 10-6). rs2277598 is associated with body mass index and is in LD with diabetes susceptibility loci. In conclusion, we identified two missense variants associated with the risk of developing PDAC independently from the ethnicity highlighting the importance of conducting reanalysis of genome-wide association studies (GWASs) in light of functional data.

An Integrative Pancreatic Cancer Risk Prediction Model in the UK Biobank

Pancreatic cancer (PaCa) is a lethal cancer with an increasing incidence, highlighting the need for early prevention strategies. There is a lack of a comprehensive PaCa predictive model derived from large prospective cohorts. Therefore, we have developed an integrated PaCa risk prediction model for PaCa using data from the UK Biobank, incorporating lifestyle-related, genetic-related, and medical history-related variables for application in healthcare settings. We used a machine learning-based random forest approach and a traditional multivariable logistic regression method to develop a PaCa predictive model for different purposes. Additionally, we employed dynamic nomograms to visualize the probability of PaCa risk in the prediction model. The top five influential features in the random forest model were age, PRS, pancreatitis, DM, and smoking. The significant risk variables in the logistic regression model included male gender (OR = 1.17), age (OR = 1.10), non-O blood type (OR = 1.29), higher polygenic score (PRS) (Q5 vs. Q1, OR = 2.03), smoking (OR = 1.82), alcohol consumption (OR = 1.27), pancreatitis (OR = 3.99), diabetes (DM) (OR = 2.57), and gallbladder-related disease (OR = 2.07). The area under the receiver operating curve (AUC) of the logistic regression model is 0.78. Internal validation and calibration performed well in both models. Our integrative PaCa risk prediction model with the PRS effectively stratifies individuals at future risk of PaCa, aiding targeted prevention efforts and supporting community-based cancer prevention initiatives.

radioGWAS: link radiome to genome to discover driver genes with somatic mutations for heterogeneous tumor image phenotype in pancreatic cancer

Addressing the significant level of variability exhibited by pancreatic cancer necessitates the adoption of a systems biology approach that integrates molecular data, biological properties of the tumors, and clinical features of the patients. In this study, a comprehensive multi-omics methodology was employed to examine a distinctive collection patient dataset containing rapid autopsy tumor and normal tissue samples as well as longitudinal imaging with a focus on pancreatic cancer. By performing a whole exome sequencing analysis on tumor and normal tissues to identify somatic gene variants and a radiomics feature analysis to tumor CT images, the genome-wide association approach established a connection between pancreatic cancer driver genes and relevant radiomics features, enabling a thorough and quantitative assessment of the heterogeneity of pancreatic tumors. The significant association between sets of genes and radiomics features revealed the involvement of genes in shaping tumor morphological heterogeneity. Some results of the association established a connection between the molecular level mechanism and their outcomes at the level of tumor structural heterogeneity. Because tumor structure and tumor structural heterogeneity are related to the patients' overall survival, patients who had pancreatic cancer driver gene mutations with an association to a certain radiomics feature have been observed to experience worse survival rates than cases without these somatic mutations. Furthermore, the outcome of the association analysis has revealed potential gene mutations and radiomics feature candidates that warrant further investigation in future research endeavors.

Diagnosis and prognosis of pancreatic cancer with immunoglobulin heavy constant delta blood marker

BACKGROUND

Pancreatic cancer (PC) is highly malignant and difficult to detect, while few blood markers are currently available for diagnosing PC.

METHODS

We obtained differential expression genes (DEGs) from GEO (gene expression omnibus) database and assessed by quantitative real-time polymerase chain reaction (qRT-PCR), receiver operating characteristic (ROC), univariate and multifactorial regression analysis, and survival analysis in our clinic center. Through the TCGA (the cancer genome atlas) database, we analyzed functional enrichment, different risk groups with survival analysis, immunological features, and the risk score established by the Cox regression model and constructed a nomogram.

RESULT

Immunoglobulin heavy constant delta (IGHD) was remarkably upregulated in peripheral blood from PC patients, and IGHD was a potential independent biomarker for PC diagnosis (ROC sensitivity, 76.0%; specificity, 74.2%; area under the curve (AUC) = 0.817; univariate logistic regression analysis: odds ratio (OR) 1.488; 95% confidence interval (CI) 1.182-1.872; P < 0.001; multiple logistic: OR 2.097; 95% CI 1.276-3.389, P = 0.003). In addition, the IGHD expression was remarkably reduced after resectioning the primary tumor. High IGHD expression indicated higher lymphocyte infiltration and increased activities of immunological pathways in PC patients. KRAS and SMAD were observed with a prominent difference among top mutated genes between the two groups. The risk score predicted reliable clinical prognosis and drug responses. Furthermore, a nomogram with the risk score and clinical characteristics was constructed, showing a better predictive performance.

CONCLUSION

IGHD is a valuable PC diagnosis, prognosis, and therapeutic response marker.

Do Polygenic Risk Scores Add to Clinical Data in Predicting Pancreatic Cancer? A Scoping Review

BACKGROUND

Polygenic risk scores (PRS) summarize an individual's germline genetic risk, but it is unclear whether PRS offer independent information for pancreatic cancer risk prediction beyond routine clinical data.

METHODS

We searched 8 databases from database inception to March 10, 2023 to identify studies evaluating the independent performance of pancreatic cancer-specific PRS for pancreatic cancer beyond clinical risk factors.

RESULTS

Twenty-one studies examined associations between a pancreatic cancer-specific PRS and pancreatic cancer. Seven studies evaluated risk factors beyond age and sex. Three studies evaluated the change in discrimination associated with the addition of PRS to routine risk factors and reported improvements (AUCs: 0.715 to 0.745; AUC 0.791 to 0.830; AUC from 0.694 to 0.711). Limitations to clinical applicability included using source populations younger/healthier than those at risk for pancreatic cancer (n = 10), exclusively of European ancestry (n = 13), or controls without relevant exposures (n = 1).

CONCLUSIONS

While most studies of pancreatic cancer-specific PRS did not evaluate the independent discrimination of PRS for pancreatic cancer beyond routine risk factors, three that did showed improvements in discrimination.

IMPACT

For pancreatic cancer PRS to be clinically useful, they must demonstrate substantial improvements in discrimination beyond established risk factors, apply to diverse ancestral populations representative of those at risk for pancreatic cancer, and use appropriate controls.

Polymorphic variants involved in methylation regulation: a strategy to discover risk loci for pancreatic ductal adenocarcinoma

INTRODUCTION

Only a small number of risk factors for pancreatic ductal adenocarcinoma (PDAC) has been established. Several studies identified a role of epigenetics and of deregulation of DNA methylation. DNA methylation is variable across a lifetime and in different tissues; nevertheless, its levels can be regulated by genetic variants like methylation quantitative trait loci (mQTLs), which can be used as a surrogate.

MATERIALS AND METHODS

We scanned the whole genome for mQTLs and performed an association study in 14 705 PDAC cases and 246 921 controls. The methylation data were obtained from whole blood and pancreatic cancer tissue through online databases. We used the Pancreatic Cancer Cohort Consortium and the Pancreatic Cancer Case-Control Consortium genome-wide association study (GWAS) data as discovery phase and the Pancreatic Disease Research consortium, the FinnGen project and the Japan Pancreatic Cancer Research consortium GWAS as replication phase.

RESULTS

The C allele of 15q26.1-rs12905855 showed an association with a decreased risk of PDAC (OR=0.90, 95% CI 0.87 to 0.94, p=4.93×10-8 in the overall meta-analysis), reaching genome-level statistical significance. 15q26.1-rs12905855 decreases the methylation of a 'C-phosphate-G' (CpG) site located in the promoter region of the RCCD1 antisense (RCCD1-AS1) gene which, when expressed, decreases the expression of the RCC1 domain-containing (RCCD1) gene (part of a histone demethylase complex). Thus, it is possible that the rs12905855 C-allele has a protective role in PDAC development through an increase of RCCD1 gene expression, made possible by the inactivity of RCCD1-AS1.

CONCLUSION

We identified a novel PDAC risk locus which modulates cancer risk by controlling gene expression through DNA methylation.

Genetic and non-genetic risk factors for early-onset pancreatic cancer

BACKGROUND

Early-onset pancreatic cancer (EOPC) represents 5-10% of all pancreatic ductal adenocarcinoma (PDAC) cases, and the etiology of this form is poorly understood. It is not clear if established PDAC risk factors have the same relevance for younger patients. This study aims to identify genetic and non-genetic risk factors specific to EOPC.

METHODS

A genome-wide association study was performed, analysing 912 EOPC cases and 10 222 controls, divided into discovery and replication phases. Furthermore, the associations between a polygenic risk score (PRS), smoking, alcohol consumption, type 2 diabetes and PDAC risk were also assessed.

RESULTS

Six novel SNPs were associated with EOPC risk in the discovery phase, but not in the replication phase. The PRS, smoking, and diabetes affected EOPC risk. The OR comparing current smokers to never-smokers was 2.92 (95% CI 1.69-5.04, P = 1.44 × 10-4). For diabetes, the corresponding OR was 14.95 (95% CI 3.41-65.50, P = 3.58 × 10-4).

CONCLUSION

In conclusion, we did not identify novel genetic variants associated specifically with EOPC, and we found that established PDAC risk variants do not have a strong age-dependent effect. Furthermore, we add to the evidence pointing to the role of smoking and diabetes in EOPC.

Design and quality control of large-scale two-sample Mendelian randomization studies

Background

Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors.

Methods

We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set.

Results

We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls.

Conclusions

In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

Genetic Susceptibility to Nonalcoholic Fatty Liver Disease and Risk for Pancreatic Cancer: Mendelian Randomization

BACKGROUND

There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer.

METHODS

Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes.

RESULTS

No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88-1.22; MR-Egger OR, 0.89; 95% CI, 0.65-1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90-1.27; MR-Egger OR, 0.93; 95% CI, 0.67-1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample.

CONCLUSIONS

Genetic predisposition to NAFLD is not associated with pancreatic cancer risk.

IMPACT

Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer.

Investigating the tissue specificity and prognostic impact of cis-regulatory cancer risk variants

The tissue-specific incidence of cancers and their genetic basis are poorly understood. Although prior studies have shown global correlation across tissues for cancer risk single-nucleotide polymorphisms (SNPs) identified through genome-wide association studies (GWAS), any shared functional regulation of gene expression on a per SNP basis has not been well characterized. We set to quantify cis-mediated gene regulation and tissue sharing for SNPs associated with eight common cancers. We identify significant tissue sharing for individual SNPs and global enrichment for breast, colorectal, and Hodgkin lymphoma cancer risk SNPs in multiple tissues. In addition, we observe increasing tissue sharing for cancer risk SNPs overlapping with super-enhancers for breast cancer and Hodgkin lymphoma providing further evidence of tissue specificity. Finally, for genes under cis-regulation by breast cancer SNPs, we identify a phenotype characterized by low expression of tumor suppressors and negative regulators of the WNT pathway associated with worse freedom from progression and overall survival in patients who eventually develop breast cancer. Our results introduce a paradigm for functionally annotating individual cancer risk SNPs and will inform the design of future translational studies aimed to personalize assessment of inherited cancer risk across tissues.

Relationship between ABO Blood Group Alleles and Pancreatic Cancer Is Modulated by Secretor (FUT2) Genotype, but Not Lewis Antigen (FUT3) Genotype

BACKGROUND

In Western populations, pancreatic ductal adenocarcinoma (PDAC) risk has been found to be greater among individuals with non-O blood types than those with O blood type. However, the association has not been fully evaluated with respect to FUT2 (determining secretor status) and FUT3 (determining Lewis antigens) status, two biologically important genes in the expression of ABO blood groups with PDAC.

METHODS

We examined interactions in data from 8,027 cases and 11,362 controls in large pancreatic cancer consortia (PanScan I-III and PanC4) by using genetic variants to predict ABO blood groups (rs505922 and rs8176746), secretor status (rs601338), and Lewis antigens (rs812936, rs28362459, and rs3894326). Multivariable logistic regression was used to estimate ORs and 95% confidence intervals (CI) of the risk of PDAC adjusted for age and sex. We examined multiplicative interactions of ABO with secretor status and Lewis antigens by considering each product term between ABO and secretor and between ABO and Lewis antigens individually.

RESULTS

We found that the increased risk associated with non-O blood groups was somewhat stronger among secretors than nonsecretors [ORs, 1.28 (95% CI, 1.15-1.42) and 1.17 (95% CI, 1.03-1.32) respectively; Pinteraction = 0.002]. We did not find any interactions between ABO and Lewis antigens.

CONCLUSIONS

Our large consortia data provide evidence of effect modification in the association between non-O blood type and pancreatic cancer risk by secretor status.

IMPACT

Our results indicate that the association between ABO blood type and PDAC risk may vary by secretor status, but not by Lewis antigens.

Genome-wide Association Study of Bladder Cancer Reveals New Biological and Translational Insights

BACKGROUND

Genomic regions identified by genome-wide association studies (GWAS) for bladder cancer risk provide new insights into etiology.

OBJECTIVE

To identify new susceptibility variants for bladder cancer in a meta-analysis of new and existing genome-wide genotype data.

DESIGN, SETTING, AND PARTICIPANTS

Data from 32 studies that includes 13,790 bladder cancer cases and 343,502 controls of European ancestry were used for meta-analysis.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSES

Log-additive associations of genetic variants were assessed using logistic regression models. A fixed-effects model was used for meta-analysis of the results. Stratified analyses were conducted to evaluate effect modification by sex and smoking status. A polygenic risk score (PRS) was generated on the basis of known and novel susceptibility variants and tested for interaction with smoking.

RESULTS AND LIMITATIONS

Multiple novel bladder cancer susceptibility loci (6p.22.3, 7q36.3, 8q21.13, 9p21.3, 10q22.1, 19q13.33) as well as improved signals in three known regions (4p16.3, 5p15.33, 11p15.5) were identified, bringing the number of independent markers at genome-wide significance (p < 5 × 10-8) to 24. The 4p16.3 (FGFR3/TACC3) locus was associated with a stronger risk for women than for men (p-interaction = 0.002). Bladder cancer risk was increased by interactions between smoking status and genetic variants at 8p22 (NAT2; multiplicative p value for interaction [pM-I] = 0.004), 8q21.13 (PAG1; pM-I = 0.01), and 9p21.3 (LOC107987026/MTAP/CDKN2A; pM-I = 0.02). The PRS based on the 24 independent GWAS markers (odds ratio per standard deviation increase 1.49, 95% confidence interval 1.44-1.53), which also showed comparable results in two prospective cohorts (UK Biobank, PLCO trial), revealed an approximately fourfold difference in the lifetime risk of bladder cancer according to the PRS (e.g., 1st vs 10th decile) for both smokers and nonsmokers.

CONCLUSIONS

We report novel loci associated with risk of bladder cancer that provide clues to its biological underpinnings. Using 24 independent markers, we constructed a PRS to stratify lifetime risk. The PRS combined with smoking history, and other established risk factors, has the potential to inform future screening efforts for bladder cancer.

PATIENT SUMMARY

We identified new genetic markers that provide biological insights into the genetic causes of bladder cancer. These genetic risk factors combined with lifestyle risk factors, such as smoking, may inform future preventive and screening strategies for bladder cancer.

Lipidomics and pancreatic cancer risk in two prospective studies

Pancreatic ductal carcinoma (PDAC) is highly fatal with limited understanding of mechanisms underlying its carcinogenesis. We comprehensively investigated whether lipidomic measures were associated with PDAC in two prospective studies. We measured 904 lipid species and 252 fatty acids across 15 lipid classes in pre-diagnostic serum (up to 24 years) in a PDAC nested-case control study within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO, NCT00002540) with 332 matched case-control sets including 272 having serial blood samples and Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (ATBC, NCT00342992) with 374 matched case-control sets. Controls were matched to cases by cohort, age, sex, race, and date at blood draw. We used conditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals (CI) per one-standard deviation increase in log-lipid concentrations within each cohort, and combined ORs using fixed-effects meta-analyses. Forty-three lipid species were associated with PDAC (false discovery rate, FDR ≤ 0.10), including lysophosphatidylcholines (LPC, n = 2), phosphatidylethanolamines (PE, n = 17), triacylglycerols (n = 13), phosphatidylcholines (PC, n = 3), diacylglycerols (n = 4), monoacylglycerols (MAG, n = 2), cholesteryl esters (CE, n = 1), and sphingomyelins (n = 1). LPC(18:2) and PE(O-16:0/18:2) showed significant inverse associations with PDAC at the Bonferroni threshold (P value < 5.5 × 10-5). The fatty acids LPC[18:2], LPC[16:0], PC[15:0], MAG[18:1] and CE[22:0] were significantly associated with PDAC (FDR < 0.10). Similar associations were observed in both cohorts. There was no significant association for the differences between PLCO serial lipidomic measures or heterogeneity by follow-up time overall. Results support that the pre-diagnostic serum lipidome, including 43 lipid species from 8 lipid classes and 5 fatty acids, is associated with PDAC.

Genetically proxied impaired GIPR signaling and risk of 6 cancers

Preclinical and genetic studies suggest that impaired glucose-dependent insulinotropic polypeptide receptor (GIPR) signaling worsens glycemic control. The relationship between GIPR signaling and the risk of cancers influenced by impaired glucose homeostasis is unclear. We examined the association of a variant in GIPR, rs1800437 (E354Q), shown to impair long-term GIPR signaling and lower circulating glucose-dependent insulinotropic peptide concentrations, with risk of 6 cancers influenced by impaired glucose homeostasis (breast, colorectal, endometrial, lung, pancreatic, and renal) in up to 235,698 cases and 333,932 controls. Each copy of E354Q was associated with a higher risk of overall and luminal A-like breast cancer and this association was consistent in replication and colocalization analyses. E354Q was also associated with higher postprandial glucose concentrations but diminished insulin secretion and lower testosterone concentrations. Our human genetics analysis suggests an adverse effect of the GIPR E354Q variant on breast cancer risk, supporting further evaluation of GIPR signaling in breast cancer prevention.

The molecular and clinical role of Tensin 1/2/3 in cancer

Tensin 1 was originally described as a focal adhesion adaptor protein, playing a role in extracellular matrix and cytoskeletal interactions. Three other Tensin proteins were subsequently discovered, and the family was grouped as Tensin. It is now recognized that these proteins interact with multiple cell signalling cascades that are implicated in tumorigenesis. To understand the role of Tensin 1-3 in neoplasia, current molecular evidence is categorized by the hallmarks of cancer model. Additionally, clinical data involving Tensin 1-3 are reviewed to investigate the correlation between cellular effects and clinical phenotype. Tensin proteins commonly interact with the tumour suppressor, DLC1. The ability of Tensin to promote tumour progression is directly correlated with DLC1 expression. Members of the Tensin family appear to have tumour subtype-dependent effects on oncogenesis; despite numerous data evidencing a tumour suppressor role for Tensin 2, association of Tensins 1-3 with an oncogenic role notably in colorectal carcinoma and pancreatic ductal adenocarcinoma is of potential clinical relevance. The complex interplay between these focal adhesion adaptor proteins and signalling pathways are discussed to provide an up to date review of their role in cancer biology.

Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions

BACKGROUND

The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci.

METHODS

We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci.

RESULTS

We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci.

CONCLUSIONS

Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

Role of pancreatic ductal adenocarcinoma risk factors in intraductal papillary mucinous neoplasm progression

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is lethal due to its late diagnosis and lack of successful treatments. A possible strategy to reduce its death burden is prevention. Intraductal papillary mucinous neoplasms (IPMNs) are precursors of PDAC. It is difficult to estimate the incidence of IPMNs because they are asymptomatic. Two recent studies reported pancreatic cysts in 3% and 13% of scanned subjects. The possibility of identifying a subgroup of IPMN patients with a higher probability of progression into cancer could be instrumental in increasing the survival rate. In this study, genetic and non-genetic PDAC risk factors were tested in a group of IPMN patients under surveillance.

Methods

A retrospective study was conducted on 354 IPMN patients enrolled in two Italian centres with an average follow-up of 64 months. With the use of DNA extracted from blood, collected at IPMN diagnosis, all patients were genotyped for 30 known PDAC risk loci. The polymorphisms were analysed individually and grouped in an unweighted polygenic score (PGS) in relation to IPMN progression. The ABO blood group and non-genetic PDAC risk factors were also analysed. IPMN progression was defined based on the development of worrisome features and/or high-risk stigmata during follow-up.

Results

Two genetic variants (rs1517037 and rs10094872) showed suggestive associations with an increment of IPMN progression. After correction for multiple testing, using the Bonferroni correction, none of the variants showed a statistically significant association. However, associations were observed for the non-genetic variables, such as smoking status, comparing heavy smokers with light smokers (HR = 3.81, 95% 1.43-10.09, p = 0.007), and obesity (HR = 2.46, 95% CI 1.22-4.95, p = 0.012).

Conclusion

In conclusion, this study is the first attempt to investigate the presence of shared genetic background between PDAC risk and IPMN progression; however, the results suggest that the 30 established PDAC susceptibility polymorphisms are not associated with clinical IPMN progression in a sample of 354 patients. However, we observed indications of cigarette smoking and body mass index (BMI) involvement in IPMN progression. The biological mechanism that could link these two risk factors to progression could be chronic inflammation, of which both smoking and obesity are strong promoters.

The PANcreatic Disease ReseArch (PANDoRA) consortium: Ten years' experience of association studies to understand the genetic architecture of pancreatic cancer

Pancreatic cancer has an incidence that almost matches its mortality. Only a small number of risk factors and 33 susceptibility loci have been identified. so Moreover, the relative rarity of pancreatic cancer poses significant hurdles for research aimed at increasing our knowledge of the genetic mechanisms contributing to the disease. Additionally, the inability to adequately power research questions prevents small monocentric studies from being successful. Several consortia have been established to pursue a better understanding of the genetic architecture of pancreatic cancers. The Pancreatic disease research (PANDoRA) consortium is the largest in Europe. PANDoRA is spread across 12 European countries, Brazil and Japan, bringing together 29 basic and clinical research groups. In the last ten years, PANDoRA has contributed to the discovery of 25 susceptibility loci, a feat that will be instrumental in stratifying the population by risk and optimizing preventive strategies.

Tensins in Kidney Function and Diseases

Tensins are focal adhesion proteins that regulate various biological processes, such as mechanical sensing, cell adhesion, migration, invasion, and proliferation, through their multiple binding activities that transduce critical signals across the plasma membrane. When these molecular interactions and/or mediated signaling are disrupted, cellular activities and tissue functions are compromised, leading to disease development. Here, we focus on the significance of the tensin family in renal function and diseases. The expression pattern of each tensin in the kidney, their roles in chronic kidney diseases, renal cell carcinoma, and their potentials as prognostic markers and/or therapeutic targets are discussed in this review.

Dissecting the genetic heterogeneity of gastric cancer

BACKGROUND

Gastric cancer (GC) is clinically heterogenous according to location (cardia/non-cardia) and histopathology (diffuse/intestinal). We aimed to characterize the genetic risk architecture of GC according to its subtypes. Another aim was to examine whether cardia GC and oesophageal adenocarcinoma (OAC) and its precursor lesion Barrett's oesophagus (BO), which are all located at the gastro-oesophageal junction (GOJ), share polygenic risk architecture.

METHODS

We did a meta-analysis of ten European genome-wide association studies (GWAS) of GC and its subtypes. All patients had a histopathologically confirmed diagnosis of gastric adenocarcinoma. For the identification of risk genes among GWAS loci we did a transcriptome-wide association study (TWAS) and expression quantitative trait locus (eQTL) study from gastric corpus and antrum mucosa. To test whether cardia GC and OAC/BO share genetic aetiology we also used a European GWAS sample with OAC/BO.

FINDINGS

Our GWAS consisting of 5816 patients and 10,999 controls highlights the genetic heterogeneity of GC according to its subtypes. We newly identified two and replicated five GC risk loci, all of them with subtype-specific association. The gastric transcriptome data consisting of 361 corpus and 342 antrum mucosa samples revealed that an upregulated expression of MUC1, ANKRD50, PTGER4, and PSCA are plausible GC-pathomechanisms at four GWAS loci. At another risk locus, we found that the blood-group 0 exerts protective effects for non-cardia and diffuse GC, while blood-group A increases risk for both GC subtypes. Furthermore, our GWAS on cardia GC and OAC/BO (10,279 patients, 16,527 controls) showed that both cancer entities share genetic aetiology at the polygenic level and identified two new risk loci on the single-marker level.

INTERPRETATION

Our findings show that the pathophysiology of GC is genetically heterogenous according to location and histopathology. Moreover, our findings point to common molecular mechanisms underlying cardia GC and OAC/BO.

FUNDING

German Research Foundation (DFG).

Abdominal obesity is a more important causal risk factor for pancreatic cancer than overall obesity

Obesity and type 2 diabetes (T2D) are associated with increased risk of pancreatic cancer. Here we assessed the relationship between pancreatic cancer and two distinct measures of obesity, namely total adiposity, using BMI, versus abdominal adiposity, using BMI adjusted waist-to-hip ratio (WHRadjBMI) by utilising polygenic scores (PGS) and Mendelian randomisation (MR) analyses. We constructed z-score weighted PGS for BMI and WHRadjBMI using publicly available data and tested for their association with pancreatic cancer defined in UK biobank (UKBB). Using publicly available summary statistics, we then performed bi-directional MR analyses between the two obesity traits and pancreatic cancer. PGS_BMI was significantly (multiple testing-corrected) associated with pancreatic cancer (OR[95%CI] = 1.0804[1.025-1.14], P = 0.0037). The significance of association declined after T2D adjustment (OR[95%CI] = 1.073[1.018-1.13], P = 0.00904). PGS_WHRadjBMI association with pancreatic cancer was at the margin of statistical significance (OR[95%CI] = 1.047[0.99-1.104], P = 0.086). T2D adjustment effectively lost any suggestive association of PGS_WHRadjBMI with pancreatic cancer (OR[95%CI] = 1.039[0.99-1.097], P = 0.14). MR analyses showed a nominally significant causal effect of WHRadjBMI on pancreatic cancer (OR[95%CI] = 1.00095[1.00011-1.0018], P = 0.027) but not for BMI on pancreatic cancer. Overall, we show that abdominal adiposity measured using WHRadjBMI, may be a more important causal risk factor for pancreatic cancer compared to total adiposity, with T2D being a potential driver of this relationship.

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories

Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we applied artificial intelligence methods to clinical data from 6 million patients (24,000 pancreatic cancer cases) in Denmark (Danish National Patient Registry (DNPR)) and from 3 million patients (3,900 cases) in the United States (US Veterans Affairs (US-VA)). We trained machine learning models on the sequence of disease codes in clinical histories and tested prediction of cancer occurrence within incremental time windows (CancerRiskNet). For cancer occurrence within 36 months, the performance of the best DNPR model has area under the receiver operating characteristic (AUROC) curve = 0.88 and decreases to AUROC (3m) = 0.83 when disease events within 3 months before cancer diagnosis are excluded from training, with an estimated relative risk of 59 for 1,000 highest-risk patients older than age 50 years. Cross-application of the Danish model to US-VA data had lower performance (AUROC = 0.71), and retraining was needed to improve performance (AUROC = 0.78, AUROC (3m) = 0.76). These results improve the ability to design realistic surveillance programs for patients at elevated risk, potentially benefiting lifespan and quality of life by early detection of this aggressive cancer.

Genetic Evidence Causally Linking Pancreas Fat to Pancreatic Cancer: A Mendelian Randomization Study

Background & Aims

Pancreatic ductal adenocarcinoma (PDAC) is highly lethal, and any clues to understanding its elusive etiology could lead to breakthroughs in prevention, early detection, or treatment. Observational studies have shown a relationship between pancreas fat accumulation and PDAC, but the causality of this link is unclear. We therefore investigated whether pancreas fat is causally associated with PDAC using two-sample Mendelian randomization.

Methods

We leveraged eight genetic variants associated with pancreas fat (P<5×10 ^-8 ) from a genome-wide association study (GWAS) in the UK Biobank (25,617 individuals), and assessed their association with PDAC in the Pancreatic Cancer Cohort Consortium I-III and the Pancreatic Cancer Case-Control Consortium dataset (8,275 PDAC cases and 6,723 non-cases). Causality was assessed using the inverse-variance weighted method. Although none of these genetic variants were associated with body mass index (BMI) at genome-wide significance, we further conducted a sensitivity analysis excluding genetic variants with a nominal BMI association in GWAS summary statistics from the UK Biobank and the Genetic Investigation of Anthropometric Traits consortium dataset (806,834 individuals).

Results

Genetically determined higher levels of pancreas fat using the eight genetic variants was associated with increased risk of PDAC. For one standard deviation increase in pancreas fat levels (i.e., 7.9% increase in pancreas fat fraction), the odds ratio of PDAC was 2.46 (95%CI:1.38-4.40, P=0.002). Similar results were obtained after excluding genetic variants nominally linked to BMI (odds ratio:3.79, 95%CI:1.66-8.65, P=0.002).

Conclusions

This study provides genetic evidence for a causal role of pancreas fat in the pathogenesis of PDAC. Thus, reducing pancreas fat could lower the risk of PDAC.

Artificial Intelligence in the Diagnosis and Treatment of Pancreatic Cystic Lesions and Adenocarcinoma

Pancreatic cancer is projected to become the second leading cause of cancer-related mortality in the United States by 2030. This is in part due to the paucity of reliable screening and diagnostic options for early detection. Amongst known pre-malignant pancreatic lesions, pancreatic intraepithelial neoplasia (PanIN) and intraductal papillary mucinous neoplasms (IPMNs) are the most prevalent. The current standard of care for the diagnosis and classification of pancreatic cystic lesions (PCLs) involves cross-sectional imaging studies and endoscopic ultrasound (EUS) and, when indicated, EUS-guided fine needle aspiration and cyst fluid analysis. However, this is suboptimal for the identification and risk stratification of PCLs, with accuracy of only 65-75% for detecting mucinous PCLs. Artificial intelligence (AI) is a promising tool that has been applied to improve accuracy in screening for solid tumors, including breast, lung, cervical, and colon cancer. More recently, it has shown promise in diagnosing pancreatic cancer by identifying high-risk populations, risk-stratifying premalignant lesions, and predicting the progression of IPMNs to adenocarcinoma. This review summarizes the available literature on artificial intelligence in the screening and prognostication of precancerous lesions in the pancreas, and streamlining the diagnosis of pancreatic cancer.

Downregulation of circ-STK39 suppresses pancreatic cancer progression by sponging mir-140-3p and regulating TRAM2-mediated epithelial-mesenchymal transition

BACKGROUND

Pancreatic cancer (PC) is amongst the most lethal gastrointestinal tumors, which is the seventh leading reason of cancer-related mortality worldwide. Previous studies have indicated that circular RNAs (circRNAs), which is a new type of endogenous noncoding RNA (ncRNA), can mediate tumor progression in diverse tumor types including PC. Whereas precise roles regarding circRNAs and their underlying regulatory mechanisms in PC remain unknown.

METHODS

In the current study, we employed next generation sequencing (NGS) to characterize abnormally expressed circRNAs among PC tissues. Next, we assessed expression levels of one identified circRNA, circ-STK39, in PC cell lines and tissues. Then, using bioinformatics analysis, luciferase reporter, Transwell migration, EdU and CCK-8 assays, we examined the regulatory mechanisms and targets of circ-STK39. Finally, our group explored the circ-STK39 role in PC tumor growth and metastasis in vivo.

RESULTS

Our team discovered that circ-STK39 expression increased in PC tissues and cells, suggesting that circ-STK39 may have a role in PC progression. Downregulation of circ-STK39 inhibited PC proliferation and migration. Bioinformatics and luciferase reporter outcomes demonstrated that TRAM2 and miR-140-3p were circ-STK39 downstream targets. TRAM2 overexpression reversed the miR-140-3p overexpression effects upon migration, proliferation and the epithelial-mesenchymal transition (EMT).

CONCLUSION

In this regard, we showed that circ-STK39 downregulation led to decreased migration, proliferation and the EMT of PC via the miR-140-3p/TRAM2 axis.

Circulating Cell-Free Nucleic Acids as Biomarkers for Diagnosis and Prognosis of Pancreatic Cancer

A lack of reliable early diagnostic tools represents a major challenge in the management of pancreatic cancer (PCa), as the disease is often only identified after it reaches an advanced stage. This highlights the urgent need to identify biomarkers that can be used for the early detection, staging, treatment monitoring, and prognosis of PCa. A novel approach called liquid biopsy has emerged in recent years, which is a less- or non-invasive procedure since it focuses on plasmatic biomarkers such as DNA and RNA. In the blood of patients with cancer, circulating tumor cells (CTCs) and cell-free nucleic acids (cfNAs) have been identified such as DNA, mRNA, and non-coding RNA (miRNA and lncRNA). The presence of these molecules encouraged researchers to investigate their potential as biomarkers. In this article, we focused on circulating cfNAs as plasmatic biomarkers of PCa and analyzed their advantages compared to traditional biopsy methods.

Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases: Workshop Proceedings

The Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases workshop was a 1.5-day scientific conference at the National Institutes of Health (Bethesda, MD) that engaged clinical and basic science investigators interested in diseases of the pancreas. This report provides a summary of the proceedings from the workshop. The goals of the workshop were to forge connections and identify gaps in knowledge that could guide future research directions. Presentations were segregated into six major theme areas, including 1) pancreas anatomy and physiology, 2) diabetes in the setting of exocrine disease, 3) metabolic influences on the exocrine pancreas, 4) genetic drivers of pancreatic diseases, 5) tools for integrated pancreatic analysis, and 6) implications of exocrine-endocrine cross talk. For each theme, multiple presentations were followed by panel discussions on specific topics relevant to each area of research; these are summarized here. Significantly, the discussions resulted in the identification of research gaps and opportunities for the field to address. In general, it was concluded that as a pancreas research community, we must more thoughtfully integrate our current knowledge of normal physiology as well as the disease mechanisms that underlie endocrine and exocrine disorders so that there is a better understanding of the interplay between these compartments.

HNF1A regulates oxaliplatin resistance in pancreatic cancer by targeting 53BP1

DNA double‑strand break repair is critically involved in oxaliplatin resistance in pancreatic ductal adenocarcinoma (PDAC). Hepatocyte nuclear factor 1 homeobox A (HNF1A) has received increased attention regarding its role in cancer progression. The present study explored the role of HNF1A in oxaliplatin resistance in PDAC. The results revealed that HNF1A expression was negatively associated with oxaliplatin chemoresistance in PDAC tissues and cell lines. HNF1A inhibition promoted the proliferation, colony formation and stemness of PDAC cells, and suppressed their apoptosis. Furthermore, HNF1A inhibition switched nonhomologous end joining to homologous recombination, thereby enhancing genomic stability and oxaliplatin resistance. Mechanistically, HNF1A transcriptionally activates p53‑binding protein 1 (53BP1) expression by directly interacting with the 53BP1 promoter region. Upregulation of HNF1A and 53BP1 induced significant inhibition of PDAC growth and oxaliplatin resistance in patient‑derived PDAC xenograft models and orthotopic models. In conclusion, the findings of the present study suggested that HNF1A/53BP1 may be a promising PDAC therapeutic target for overcoming oxaliplatin resistance.

Pancreatic Cancer: Changing Epidemiology and New Approaches to Risk Assessment, Early Detection, and Prevention

Pancreatic cancer usually results in poor survival with limited options for treatment, as most affected individuals present with advanced disease. Early detection of preinvasive pancreatic neoplasia and identifying molecular therapeutic targets provide opportunities for extending survival. Although screening for pancreatic cancer is currently not recommended for the general population, emerging evidence indicates that pancreatic surveillance can improve outcomes for individuals in certain high-risk groups. Changes in the epidemiology of pancreatic cancer, experience from pancreatic surveillance, and discovery of novel biomarkers provide a roadmap for new strategies for pancreatic cancer risk assessment, early detection, and prevention.

Immunogenetic Determinants of Susceptibility to Head and Neck Cancer in the Million Veteran Program Cohort

Increasing rates of human papillomavirus (HPV)-driven oropharyngeal cancer (OPC) have largely offset declines in tobacco-associated head and neck squamous cell carcinoma (HNSCC) at non-OPC sites. Host immunity is an important modulator of HPV infection, persistence, and clearance, and also of immune evasion in both virally- and nonvirally-driven cancers. However, the association between collective known cancer-related immune gene variants and HNSCC susceptibility has not been fully characterized. Here, we conducted a genetic association study in the multiethnic Veterans Affairs Million Veteran Program cohort, evaluating 16,050 variants in 1,576 immune genes in 4,012 HNSCC cases (OPC = 1,823; non-OPC = 2,189) and 16,048 matched controls. Significant polymorphisms were further examined in a non-Hispanic white (NHW) validation cohort (OPC = 1,206; non-OPC = 955; controls = 4,507). For overall HNSCC susceptibility in NHWs, we discovered and validated a novel 9q31.1 SMC2 association and replicated the known 6p21.32 HLA-DQ-DR association. Six loci/genes for overall HNSCC susceptibility were selectively enriched in African-Americans (6p21.32 HLA-G, 9q21.33 GAS1, 11q12.2 CD6, 11q23.2 NCAM1/CD56, 17p13.1 CD68, 18q22.2 SOCS6); all 6 genes function in antigen-presenting regulation and T-cell activation. Two additional loci (10q26 DMBT1, 15q22.2 TPM1) were uncovered for non-OPC susceptibility, and three loci (11q24 CRTAM, 16q21 CDH5, 18q12.1 CDH2) were identified for HPV-positive OPC susceptibility. This study underscores the role of immune gene variants in modulating susceptibility for both HPV-driven and non-HPV-driven HNSCC. Additional large studies, particularly in racially diverse populations, are needed to further validate the associations and to help elucidate other potential immune factors and mechanisms that may underlie HNSCC risk.

SIGNIFICANCE

Several inherited variations in immune system genes are significantly associated with susceptibility to head and neck cancer, which could help improve personalized cancer risk estimates.

GWAS Explorer: an open-source tool to explore, visualize, and access GWAS summary statistics in the PLCO Atlas

The Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial is a prospective cohort study of nearly 155,000 U.S. volunteers aged 55-74 at enrollment in 1993-2001. We developed the PLCO Atlas Project, a large resource for multi-trait genome-wide association studies (GWAS), by genotyping participants with available DNA and genomic consent. Genotyping on high-density arrays and imputation was performed, and GWAS were conducted using a custom semi-automated pipeline. Association summary statistics were generated from a total of 110,562 participants of European, African and Asian ancestry. Application programming interfaces (APIs) and open-source software development kits (SKDs) enable exploring, visualizing and open data access through the PLCO Atlas GWAS Explorer website, promoting Findable, Accessible, Interoperable, and Re-usable (FAIR) principles. Currently the GWAS Explorer hosts association data for 90 traits and >78,000,000 genomic markers, focusing on cancer and cancer-related phenotypes. New traits will be posted as association data becomes available. The PLCO Atlas is a FAIR resource of high-quality genetic and phenotypic data with many potential reuse opportunities for cancer research and genetic epidemiology.

Screening for pancreatic cancer has the potential to save lives, but is it practical?

INTRODUCTION

Most patients with pancreatic cancer present with advanced stage, incurable disease. However, patients with high-grade precancerous lesions and many patients with low-stage disease can be cured with surgery, suggesting that early detection has the potential to improve survival. While serum CA19.9 has been a long-standing biomarker used for pancreatic cancer disease monitoring, its low sensitivity and poor specificity have driven investigators to hunt for better diagnostic markers.

AREAS COVERED

This review will cover recent advances in genetics, proteomics, imaging, and artificial intelligence, which offer opportunities for the early detection of curable pancreatic neoplasms.

EXPERT OPINION

From exosomes, to circulating tumor DNA, to subtle changes on imaging, we know much more now about the biology and clinical manifestations of early pancreatic neoplasia than we did just five years ago. The overriding challenge, however, remains the development of a practical approach to screen for a relatively rare, but deadly, disease that is often treated with complex surgery. It is our hope that future advances will bring us closer to an effective and financially sound approach for the early detection of pancreatic cancer and its precursors.

Dysregulation of HNF1B/Clusterin axis enhances disease progression in a highly aggressive subset of pancreatic cancer patients

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy and is largely refractory to available treatments. Identifying key pathways associated with disease aggressiveness and therapeutic resistance may characterize candidate targets to improve patient outcomes. We used a strategy of examining the tumors from a subset of PDAC patient cohorts with the worst survival to understand the underlying mechanisms of aggressive disease progression and to identify candidate molecular targets with potential therapeutic significance. Non-negative matrix factorization (NMF) clustering, using gene expression profile, revealed three patient subsets. A 142-gene signature specific to the subset with the worst patient survival, predicted prognosis and stratified patients with significantly different survival in the test and validation cohorts. Gene-network and pathway analysis of the 142-gene signature revealed dysregulation of Clusterin (CLU) in the most aggressive patient subset in our patient cohort. Hepatocyte nuclear factor 1 b (HNF1B) positively regulated CLU, and a lower expression of HNF1B and CLU was associated with poor patient survival. Mechanistic and functional analyses revealed that CLU inhibits proliferation, 3D spheroid growth, invasiveness and epithelial-to-mesenchymal transition (EMT) in pancreatic cancer cell lines. Mechanistically, CLU enhanced proteasomal degradation of EMT-regulator, ZEB1. In addition, orthotopic transplant of CLU-expressing pancreatic cancer cells reduced tumor growth in mice. Furthermore, CLU enhanced sensitivity of pancreatic cancer cells representing aggressive patient subset, to the chemotherapeutic drug gemcitabine. Taken together, HNF1B/CLU axis negatively regulates pancreatic cancer progression and may potentially be useful in designing novel strategies to attenuate disease progression in PDAC patients.

Risk of Pancreatic Cancer in the Long-Term Prospective Follow-Up of Familial Pancreatic Cancer Kindreds

BACKGROUND

A family history of pancreatic cancer is associated with increased pancreatic cancer risk. However, risk estimates for individuals in kindreds with an aggregation of pancreatic cancer (>1 relative) are imprecise because of small samples sizes or potentially impacted by biases inherent in retrospective data.

OBJECTIVE

The objective of this study is to determine the age-specific pancreatic cancer risk as a function of family history using prospective data.

METHODS

We compared pancreatic cancer incidence (n = 167) in 21 141 individuals from 4433 families enrolled in the National Familial Pancreatic Cancer Registry with that expected based on Surveillance Epidemiology and End Results data and estimated the cumulative probability of pancreatic cancer using competing risk regression.

RESULTS

Familial pancreatic kindred members (kindreds with pancreatic cancer in 2 first-degree relatives [FDRs] or a pathogenic variant) had a standardized incidence ratio of 4.86 (95% confidence interval [CI] = 4.01 to 5.90), and sporadic kindred members (kindreds not meeting familial criteria) had a standardized incidence ratio of 2.55 (95% CI = 1.95 to 3.34). Risk in familial pancreatic cancer kindreds increased with an increasing number of FDRs with pancreatic cancer, with a standardized incidence ratio of 3.46 (95% CI = 2.52 to 4.76), 5.44 (95% CI = 4.07 to 7.26), and 10.78 (95% CI = 6.87 to 16.89) for 1, 2, and 3 or more FDRs with pancreatic cancer, respectively. Risk was also higher among individuals with a family history of young-onset (aged younger than 50 years) pancreatic cancer.

CONCLUSION

Pancreatic cancer risk is strongly dependent on family history, including both the degree of relationship(s) and age of onset of pancreatic cancer in relatives. These risk estimates will help inform the design of early detection studies and the risk and benefit analysis of screening trials.

An integrated analysis of the cancer genome atlas data discovers a hierarchical association structure across thirty three cancer types

Cancer cells harbor molecular alterations at all levels of information processing. Genomic/epigenomic and transcriptomic alterations are inter-related between genes, within and across cancer types and may affect clinical phenotypes. Despite the abundant prior studies of integrating cancer multi-omics data, none of them organizes these associations in a hierarchical structure and validates the discoveries in extensive external data. We infer this Integrated Hierarchical Association Structure (IHAS) from the complete data of The Cancer Genome Atlas (TCGA) and compile a compendium of cancer multi-omics associations. Intriguingly, diverse alterations on genomes/epigenomes from multiple cancer types impact transcriptions of 18 Gene Groups. Half of them are further reduced to three Meta Gene Groups enriched with (1) immune and inflammatory responses, (2) embryonic development and neurogenesis, (3) cell cycle process and DNA repair. Over 80% of the clinical/molecular phenotypes reported in TCGA are aligned with the combinatorial expressions of Meta Gene Groups, Gene Groups, and other IHAS subunits. Furthermore, IHAS derived from TCGA is validated in more than 300 external datasets including multi-omics measurements and cellular responses upon drug treatments and gene perturbations in tumors, cancer cell lines, and normal tissues. To sum up, IHAS stratifies patients in terms of molecular signatures of its subunits, selects targeted genes or drugs for precision cancer therapy, and demonstrates that associations between survival times and transcriptional biomarkers may vary with cancer types. These rich information is critical for diagnosis and treatments of cancers.