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

From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction

Pancreatic ductal adenocarcinoma (PDAC) is recognized as one of the most lethal malignancies, characterized by late-stage diagnosis and limited therapeutic options. Risk stratification has traditionally been performed using epidemiological studies and genetic analyses, through which key risk factors, including smoking, diabetes, chronic pancreatitis, and inherited predispositions, have been identified. However, the multifactorial nature of PDAC has often been insufficiently addressed by these methods, leading to limited precision in individualized risk assessments. Advances in artificial intelligence (AI) have been proposed as a transformative approach, allowing the integration of diverse datasets-spanning genetic, clinical, lifestyle, and imaging data into dynamic models capable of uncovering novel interactions and risk profiles. In this review, the evolution of PDAC risk stratification is explored, with classical epidemiological frameworks compared to AI-driven methodologies. Genetic insights, including genome-wide association studies and polygenic risk scores, are discussed, alongside AI models such as machine learning, radiomics, and deep learning. Strengths and limitations of these approaches are evaluated, with challenges in clinical translation, such as data scarcity, model interpretability, and external validation, addressed. Finally, future directions are proposed for combining classical and AI-driven methodologies to develop scalable, personalized predictive tools for PDAC, with the goal of improving early detection and patient outcomes.

Genomic instability, DNA damage response and telomere homeostasis in pancreatic cancer

Pancreatic cancer (PC) is becoming one of the most serious health problems at present, but its causes and risk factors are still unclear. One of the drivers in pancreatic carcinogenesis is altered genomic (DNA) integrity with subsequent genomic instability in cancer cells. The latter comprises a) DNA damage response and DNA repair mechanisms, b) DNA replication and mitosis, c) epigenetic regulation, and d) telomere maintenance. In our review we addressed the above aspects in relation to the most abundant and severe form of PC, pancreatic ductal adenocarcinoma (PDAC). In summary, the interactions between the DNA damage response, telomere homeostasis and mitotic regulation are not comprehensively understood at present, including the epigenetic factors entering the trait of genomic stability maintenance. In addition, the complexity of telomere homeostasis in relation to PDAC risk, prognosis and prediction also warrants further investigations.

The exposome and pancreatic cancer, lifestyle and environmental risk factors for PDAC

Pancreatic cancer (PC), particularly pancreatic ductal adenocarcinoma (PDAC), is a significant global health issue with high mortality rates. PDAC, though only 3 % of cancer diagnoses, causes 7 % of cancer deaths due to its severity and asymptomatic early stages. Risk factors include lifestyle choices, environmental exposures, and genetic predispositions. Conditions like new-onset type 2 diabetes and chronic pancreatitis also contribute significantly. Modifiable risk factors include smoking, alcohol consumption, non-alcoholic fatty pancreatic disease (NAFPD), and obesity. Smoking and heavy alcohol consumption increase PC risk, while NAFPD and obesity, particularly central adiposity, contribute through chronic inflammation and insulin resistance. Refined sugar and sugar-sweetened beverages (SSBs) are also linked to increased PC risk, especially among younger individuals. Hormonal treatments and medications like statins, aspirin, and metformin have mixed results on PC risk, with some showing protective effects. The gut microbiome influences PC through the gut-pancreas axis, with disruptions leading to inflammation and carcinogenesis. Exposure to toxic substances, including heavy metals and chemicals, is associated with increased PC risk. Glycome changes, such as abnormal glycosylation patterns, are significant in PDAC development and offer potential for early diagnosis. Interactions between environmental and genetic factors are crucial in PDAC susceptibility. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) linked to PDAC, but gene-environment interactions remain largely unexplored. Future research should focus on polygenic risk scores (PRS) and large-scale studies to better understand these interactions and their impact on PDAC risk.

Allelic effects on KLHL17 expression underlie a pancreatic cancer genome-wide association signal at chr1p36.33

Pancreatic Ductal Adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in the U.S. Both rare and common germline variants contribute to PDAC risk. Here, we fine-map and functionally characterize a common PDAC risk signal at chr1p36.33 (tagged by rs13303010) identified through a genome wide association study (GWAS). One of the fine-mapped SNPs, rs13303160 (OR = 1.23 (95% CI 1.15-1.32), P-value = 2.74×10-9, LD r2 = 0.93 with rs13303010 in 1000 G EUR samples) demonstrated allele-preferential gene regulatory activity in vitro and binding of JunB and JunD in vitro and in vivo. Expression Quantitative Trait Locus (eQTL) analysis identified KLHL17 as a likely target gene underlying the signal. Proteomic analysis identified KLHL17 as a member of the Cullin-E3 ubiquitin ligase complex with vimentin and nestin as candidate substrates for degradation in PDAC-derived cells. In silico differential gene expression analysis of high and low KLHL17 expressing GTEx pancreas samples suggested an association between lower KLHL17 levels (risk associated) and pro-inflammatory pathways. We hypothesize that KLHL17 may mitigate cell injury and inflammation by recruiting nestin and vimentin for ubiquitination and degradation thereby influencing PDAC risk.

Discordant risk factors between pancreatic neuroendocrine neoplasms and pancreatic ductal adenocarcinoma

Pancreatic neuroendocrine neoplasm (panNEN) is a rare malignancy and the second most common type of pancreatic cancer after pancreatic ductal adenocarcinoma (PDAC), but its etiology is poorly understood. We investigated whether the risk factors of panNEN are concordant with those known for PDAC. We performed the largest case-control study to date on panNENs, comprising 927 sporadic nonfunctional panNEN cases and 1807 frequency-matched controls, using data from the Mayo Clinic Biospecimen Resource for Pancreas Research. We assessed associations for obesity, first-degree family history of pancreatic cancer, cigarette smoking, overall type II diabetes mellitus (T2DM), new-onset T2DM (<1 year before panNEN diagnosis), longstanding T2DM (≥5 years), alcohol intake and aspirin use. Multivariable logistic regression was used to calculate odds ratios and 95% confidence intervals (CIs). Our results show that overall T2DM (OR = 1.71, 95% CI: 1.37-2.14) and new-onset T2DM (OR = 2.65, 95% CI: 1.92-3.69) are associated with higher odds of panNEN, but not longstanding T2DM (OR = 1.29, 95% CI: 0.94-1.75). A non-significant elevated odds of panNEN was observed among participants with a positive family history of pancreatic cancer (OR = 1.44, 95% CI: 0.96-2.14). Alcohol use was inversely related to panNEN (OR = 0.52, 95% CI: 0.42-0.66, ever-vs-never). No association was observed for smoking, obesity or aspirin use. These findings indicate that overall T2DM and new-onset T2DM are associated with higher odds of panNEN. Unlike PDAC, alcohol use was inversely related to panNEN, and we found no associations for cigarette smoking, obesity or aspirin use. These results indicate differences in the risk factor profiles of panNEN and PDAC.

Explainable machine learning identifies a polygenic risk score as a key predictor of pancreatic cancer risk in the UK Biobank

BACKGROUND

Predicting the risk of developing pancreatic ductal adenocarcinoma (PDAC) is of paramount importance, given its high mortality rate. Current PDAC risk prediction models rely on a limited number of variables, do not include genetics, and have a modest accuracy.

AIM

This study aimed to develop an interpretable PDAC risk prediction model, based on machine learning (ML).

METHODS

Five ML models (Adaptive Boosting, eXtreme Gradient Boosting, CatBoost, Deep Forest and Random Forest) built on 56 exposome variables and a polygenic risk score (PRS) were tested in 654 PDAC cases and 1,308 controls of the UK Biobank. Additionally, SHapley Additive exPlanation (SHAP) and Global model Interpretation via the Recursive Partitioning (Girp) were employed to explain the models.

RESULTS

All models provided similar performance, but based on recall the best was CatBoost (77.10 %). SHAP highlighted age and the PRS as primary contributors across all models. Girp developed rules to discern cases from controls, identifying age, PRS, and pancreatitis in most of the rules.

CONCLUSION

The predictive models tested have exhibited good performance, indicating their potential application in the clinical field in the near future, with the PRS playing a key role in identifying high-risk individuals as demonstrated by the explainers.

Long or short? Telomere length and pancreatic cancer and its precursor lesions, a narrative review

Pancreatic ductal adenocarcinoma (PDAC) is the most common and lethal form of pancreatic cancer, with a survival approaching only 11% at 5 years after diagnosis. In the last 15 years, telomere length (TL) measured in leukocyte (LTL) has been studied in relation to PDAC risk. The majority of the studies reported an association between short LTL and increased PDAC risk, but the results are heterogeneous. Genome-wide association studies have identified several single-nucleotide polymorphisms (SNPs) in the telomerase reverse transcriptase (TERT) gene as susceptibility loci for PDAC. Polygenic risk scores computed using SNPs associated with LTL have been tested in relation to PDAC susceptibility with various methods and giving contrasting results. The aim of this review is to analyze all publications carried out specifically on LTL, considering LTL measured with qPCR and with genetic proxies, and PDAC risk. Additionally, we will give an overview of the most relevant associations between SNPs in telomere-associated genes and PDAC, to answer the question shorter or longer? Which one of the two is associated with PDAC risk?

A pleiotropy scan to discover new susceptibility loci for pancreatic ductal adenocarcinoma

Pleiotropic variants (i.e. genetic polymorphisms influencing more than one phenotype) are often associated with cancer risk. A scan of pleiotropic variants was successfully conducted 10 years ago in relation to pancreatic ductal adenocarcinoma susceptibility. However, in the last decade, genetic association studies performed on several human traits have greatly increased the number of known pleiotropic variants. Based on the hypothesis that variants already associated with a least one trait have a higher probability of association with other traits, 61 052 variants reported to be associated by at least one genome-wide association study with at least one human trait were tested in the present study consisting of two phases (discovery and validation), comprising a total of 16 055 pancreatic ductal adenocarcinoma (PDAC) cases and 212 149 controls. The meta-analysis of the two phases showed two loci (10q21.1-rs4948550 (P = 6.52 × 10-5) and 7q36.3-rs288762 (P = 3.03 × 10-5) potentially associated with PDAC risk. 10q21.1-rs4948550 shows a high degree of pleiotropy and it is also associated with colorectal cancer risk while 7q36.3-rs288762 is situated 28,558 base pairs upstream of the Sonic Hedgehog (SHH) gene, which is involved in the cell-differentiation process and PDAC etiopathogenesis. In conclusion, none of the single nucleotide polymorphisms (SNPs) showed a formally statistically significant association after correction for multiple testing. However, given their pleiotropic nature and association with various human traits including colorectal cancer, the two SNPs showing the best associations with PDAC risk merit further investigation through fine mapping and ad hoc functional studies.

Life's Essential 8, genetic susceptibility, and risk of incident pancreatic cancer: A prospective cohort study

The association between the American Heart Association (AHA) Life's Essential 8 (LE8) and the risk of pancreatic cancer (PC) remains unclear. Our goal was to assess the relationships between LE8, genetic susceptibility, and PC risk. This cohort consisted of 234,102 participants from the UK Biobank. The components of LE8 include diet, nicotine exposure, sleep, physical activity, blood glucose, body mass index, blood lipids, and blood pressure. LE8 is classified into three categories: low cardiovascular health (CVH), moderate CVH, and high CVH. Measurements were made using Cox proportional risk models to estimate impact of associations between LE8, genetic susceptibility, and incidence of PC in participants. Compared to participants with low LE8 scores, those with moderate and high LE8 scores had a 53% (HR, 0.47; 95% CI, 0.39-0.57) and 70% (HR, 0.30; 95% CI, 0.22-0.41) lower risk of developing PC, respectively. Interestingly, among individuals with high genetic risk, high LE8 scores were associated with greater benefits (HR, 0.24; 95% CI, 0.15-0.40), whereas the protective effect was weaker among those with low genetic risk (HR, 0.40; 95% CI, 0.21-0.75). Participants with a high LE8 score and a low polygenic risk score (PRS) had the lowest risk of PC (HR, 0.19; 95% CI: 0.11-0.33). Furthermore, we observed a significant additive interaction between LE8 and PRS. A higher LE8 score is associated with a lower risk of PC, especially for participants with a high PRS. These findings have important implications for participants most genetically predisposed to PC and for targeted strategies for PC prevention.

Genetic landscape for screening and early diagnosis of pancreatic ductal adenocarcinoma: is there a signature?

The last 15 years have seen unprecedent advancement in genomics techniques such as dense single nucleotide variants (SNVs) arrays or next generation Sequencing. In parallel, new analytical methodologies have been developed to streamline data understanding and integration. These advances have been instrumental in identifying common genetic variants associated with pancreatic ductal adenocarcinoma (PDAC) risk. The role of the individual variants is rather small, and they have no clinical utility for screening or early detection. However, their combined effect computed though polygenic risk scores (PGS) are showing promising potentiality in PDAC risk prediction. There still caveats, and limitations that need to be properly addressed however it is foreseeable that the genetic background will become a powerful tool in PDAC prediction, leveraging the advantage that it has compared to other biomarkers: germline genetics is invariable from birth to death.

Leveraging epigenetic alterations in pancreatic ductal adenocarcinoma for clinical applications

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by late detection and poor prognosis. Recent research highlights the pivotal role of epigenetic alterations in driving PDAC development and progression. These changes, in conjunction with genetic mutations, contribute to the intricate molecular landscape of the disease. Specific modifications in DNA methylation, histone marks, and non-coding RNAs are emerging as robust predictors of disease progression and patient survival, offering the potential for more precise prognostic tools compared to conventional clinical staging. Moreover, the detection of epigenetic alterations in blood and other non-invasive samples holds promise for earlier diagnosis and improved management of PDAC. This review comprehensively summarises current epigenetic research in PDAC and identifies persisting challenges. These include the complex nature of epigenetic profiles, tumour heterogeneity, limited access to early-stage samples, and the need for highly sensitive liquid biopsy technologies. Addressing these challenges requires the standardisation of methodologies, integration of multi-omics data, and leveraging advanced computational tools such as machine learning and artificial intelligence. While resource-intensive, these efforts are essential for unravelling the functional consequences of epigenetic changes and translating this knowledge into clinical applications. By overcoming these hurdles, epigenetic research has the potential to revolutionise the management of PDAC and improve patient outcomes.

Multi-omic markers of intraductal papillary mucinous neoplasms progression into pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal and common form of pancreatic cancer, it has no specific symptoms, and most of the patients are diagnosed when the disease is already at an advanced stage. Chemotherapy typically has only a modest effect, making surgery the most effective treatment option. However, only a small percentage of patients are amenable to surgery. One viable strategy to reduce PDAC death burden associated with the disease is to focus on precursor lesions and identify markers able to predict who will evolve into PDAC. While most PDACs are believed to be preceded by pancreatic intraepithelial neoplasms (PanINs), 5-10 % arise from Intraductal papillary mucinous neoplasms (IPMNs), which are mass-forming cystic lesions that are very common in the general population. IPMNs offer an invaluable model of pancreatic carcinogenesis for researchers to analyse, as well as a target population for PDAC early detection by clinicians. The evolution of IPMN into cancer is a complex and multistep process, therefore the identification of individual markers will not be the solution. In recent years, multiple omics technologies have been instrumental to identify possible biomarkers of IPMN progression and carcinogenesis. The only foreseeable strategy will be to integrate multi-omics data, alongside clinical and morphological features, into a progression score or signature using either standard epidemiologic tools or artificial intelligence. The aim of this manuscript is to review the current knowledge on genetic biomarkers and to briefly mention also additional omics, such as metabolomics, the exposome, the miRNome and epigenomics of IPMNs.

The known genetic variants of BRCA1, BRCA2 and NOD2 in pancreatitis and pancreatic cancer risk assessment

The single nucleotide polymorphism in NOD2 (rs2066847) is associated with conditions that may predispose to the development of gastrointestinal disorders, as well as the known BRCA1 and BRCA2 variants classified as risk factors in many cancers. In our study, we analyzed these variants in a group of patients with pancreatitis and pancreatic cancer to clarify their role in pancreatic disease development. The DNA was isolated from whole blood samples of 553 patients with pancreatitis, 83 patients with pancreatic cancer, 44 cases of other pancreatic diseases, and 116 healthy volunteers. The NOD2 (rs2066847), BRCA1 (rs80357914) and BRCA2 (rs276174813) were genotyped. The statistically significant 3-fold increased risk of pancreatic cancer was detected among the patients with rs2066847 polymorphism (OR = 2.77, p-value = 0.019). We did not find the studied polymorphisms in BRCA1 (rs80357914) and BRCA2 (rs276174813). However, the adjacent polymorphisms have been detected only in patients with pancreatic diseases. The studied variant in NOD2 occurs more frequently in pancreatic patients and significantly increases the risk of pancreatic cancer. It can be considered as a genetic risk factor that predisposes to cancer development. The analyzed regions in BRCA1 and BRCA2 may be a potential target in further search for a genetic marker of pancreatic diseases.

Utility of Polygenic Risk Scores (PRSs) in Predicting Pancreatic Cancer: A Systematic Review and Meta-Analysis of Common-Variant and Mixed Scores with Insights into Rare Variant Analysis

Pancreatic adenocarcinoma is the most common histological subtype of pancreatic cancer, representing approximately 85% of all cases [...].

HNF1B polymorphisms and endometrial cancer risk: validation of identified loci and evaluation of novel variants

BACKGROUND

This study aimed to validate HNF1B single nucleotide polymorphisms (SNPs) associated with endometrial cancer risk in a Chinese Han population and explore novel SNPs. Our findings enhance the understanding of genetic components and are crucial for detection strategies and personalized medicine.

METHODS

We genotyped four HNF1B SNPs in 637 patients and 667 controls using Agena MassARRAY. Logistic regression calculated odds ratios (ORs) and 95% CI. Forest plots visualize stratified analyses. Multiple comparisons tested genetic loci-clinical indicator associations.

RESULTS

The study confirmed that rs4430796 (A>G) reduced endometrial cancer risk (OR = 0.83, 95% CI: 0.70-0.99, p = 0.041). Additionally, novel HNF1B mutations were associated with endometrial cancer risk: rs7405776 in individuals under the age of 55 (OR = 047, 95% CI: 0.25-0.91, p = 0.025) and nonsmokers (OR = 0.42, 95% CI: 0.23-0.75, p = 0.004), and rs11651755 in drinkers (OR = 0.39, 95% CI: 0.17-0.90, p = 0.027) and nonsmokers (OR = 0.43, 95% CI: 0.23-0.81, p = 0.009). The SNP rs4430796 was also associated with the CA125 level (p < 0.05).

CONCLUSION

HNF1B polymorphisms influence endometrial cancer risk in the Chinese Han population. Further studies are needed to explore the functional roles and clinical practicality of these SNPs.

Genetic Variants and Haplotype Structures in the CASC Gene Family to Predict Cancer Risk: A Bioinformatics Study

Background and Aims

The cancer susceptibility (CASC) gene family of long noncoding RNAs (lncRNAs) plays an important role in cancer. The aim of this study was to identify genetic variants and haplotype structures of CASC genes associated with cancer risk.

Methods

Genome-wide association studies (GWAS) significant variants (p ≤ 5 × 10-8) on CASC family genes were identified from the GWAS Catalog-EMBL-EBI, and then cancer-associated variants on CASC genes were extracted. These variants were functionally analyzed, including lncRNA:miRNA binding sites, Regulomedb scores, and eQTL. The 1000 Genome Project genotyping data Phase III were used to identify haplotypic blocks. Finally, the genes associated with them were examined for expression and gene-gene correlation analyses using OncoDB.

Results

There were six haplotypic blocks in four genes. The GC, TA, and AGAC haplotypes are located in the CASC8 gene and increase the risk of prostate cancer, breast cancer, and colorectal cancer, respectively. The CA haplotype in the CASC15 gene increases the risk of neuroblastoma, AA haplotype in the CASC16 gene increases the risk of breast cancer, and ACGATG haplotype in the CASC17 gene increases the risk of prostate cancer (p ≤ 5 × 10-8). Their genes are interrelated and their expression is increased in these cancers. The rs2294214 is associated with skin cancer and has positive effects on five CASC15:miRNA binding sites. The rs3803662 is located in CASC16:miRNA binding sites, which has positive effects on hsa-miR-4475 and hsa-miR-7845-5p and negative effects on hsa-miR-4524a-3p and hsa-miR-4524b-3p.

Conclusion

These haplotypic structures and lncRNA:miRNA:SNP interactions on CASC family lncRNAs reveal novel genetic associations between CASC genes and various cancers.

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.

Genetically predicted gut bacteria, circulating bacteria-associated metabolites and pancreatic ductal adenocarcinoma: a Mendelian randomisation study

Pancreatic ductal adenocarcinoma (PDAC) has high mortality and rising incidence rates. Recent data indicate that the gut microbiome and associated metabolites may play a role in the development of PDAC. To complement and inform observational studies, we investigated associations of genetically predicted abundances of individual gut bacteria and genetically predicted circulating concentrations of microbiome-associated metabolites with PDAC using Mendelian randomisation (MR). Gut microbiome-associated metabolites were identified through a comprehensive search of Pubmed, Exposome Explorer and Human Metabolome Database. Single Nucleotide Polymorphisms (SNPs) associated by Genome-Wide Association Studies (GWAS) with circulating levels of 109 of these metabolites were collated from Pubmed and the GWAS catalogue. SNPs for 119 taxonomically defined gut genera were selected from a meta-analysis performed by the MiBioGen consortium. Two-sample MR was conducted using GWAS summary statistics from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including a total of 8,769 cases and 7,055 controls. Inverse variance-weighted MR analyses were performed along with sensitivity analyses to assess potential violations of MR assumptions. Nominally significant associations were noted for genetically predicted circulating concentrations of mannitol (odds ratio per standard deviation [ORSD] = 0.97; 95% confidence interval [CI]: 0.95-0.99, p = 0.006), methionine (ORSD= 0.97; 95%CI: 0.94-1.00, p = 0.031), stearic acid (ORSD= 0.93; 95%CI: 0.87-0.99, p = 0.027), carnitine = (ORSD=1.01; 95% CI: 1.00-1.03, p = 0.027), hippuric acid (ORSD= 1.02; 95%CI: 1.00-1.04, p = 0.038) and 3-methylhistidine (ORSD= 1.05; 95%CI: 1.01-1.10, p = 0.02). Two gut microbiome genera were associated with reduced PDAC risk; Clostridium sensu stricto 1 (OR: 0.88; 95%CI: 0.78-0.99, p = 0.027) and Romboutsia (OR: 0.87; 95%CI: 0.80-0.96, p = 0.004). These results, though based only on genetically predicted gut microbiome characteristics and circulating bacteria-related metabolite concentrations, provide evidence for causal associations with pancreatic carcinogenesis.

Potential association between PSCA rs2976395 functional variant and pancreatic cancer risk

Correlated regions of systemic interindividual variation (CoRSIV) represent a small proportion of the human genome showing DNA methylation patterns that are the same in all human tissues, are different among individuals, and are partially regulated by genetic variants in cis. In this study we aimed at investigating single-nucleotide polymorphisms (SNPs) within CoRSIVs and their involvement with pancreatic ductal adenocarcinoma (PDAC) risk. We analyzed 29,099 CoRSIV-SNPs and 133,615 CoRSIV-mQTLs in 14,394 cases and 247,022 controls of European and Asian descent. We observed that the A allele of the rs2976395 SNP was associated with increased PDAC risk in Europeans (p = 2.81 × 10-5). This SNP lies in the prostate stem cell antigen gene and is in perfect linkage disequilibrium with a variant (rs2294008) that has been reported to be associated with risk of many other cancer types. The A allele is associated with the DNA methylation level of the gene according to the PanCan-meQTL database and with overexpression according to QTLbase. The expression of the gene has been observed to be deregulated in many tumors of the gastrointestinal tract including pancreatic cancer; however, functional studies are needed to elucidate the function relevance of the association.

A MR-PheWAS and bidirectional Mendelian randomization study: Exploring for causal relationships of pancreatic cancer

It is unknown what causes pancreatic cancer. We conducted a phenome-wide Mendelian randomization analysis (MR-pheWAS), a bidirectional Mendelian study, and a systematic review of research in order to thoroughly investigate any causal association between pancreatic cancer and Atlas. We used phenome-wide Mendelian randomization analysis to test for associations between pancreatic cancer and 776 phenotypes (n = 452,264) of Atlas in the UK Biobank. Causality is confirmed by two-sample Mendelian randomization (MR) analysis using correlation found by false discovery rate correction. Simultaneously, a comprehensive evaluation of pancreatic cancer MR studies was conducted in order to complement our findings and harmonize the existing evidence. According to the inverse-variance-weighted model, a total of 41 out of 776 phenotypes had a nominal significance level (P < .05) genetic prediction association with pancreatic cancer. Only genetically predicted pancreatic cancer was shown to be linked with elevated eosinophil counts following false discovery rate correction (P = .031) when several tests were taken into account. Pancreatic cancer and eosinophils were shown to be positively causally associated to one another, establishing a self-loop, according to two-sample MR validation in the IEU database (OR = 1.011, 95% CI: 1.002-1.020, P = .010) (OR = 1.229, 95% CI: 1.037-1.458, P = .017). Although MR-pheWAS found a strong causal relationship between eosinophils and pancreatic cancer, it also found a negative exclusion value for each phenotype and a significant number of suggestive association phenotypes that offered guidance for further research.

EIF4A3-mediated oncogenic circRNA hsa_circ_0001165 advances esophageal squamous cell carcinoma progression through the miR-381-3p/TNS3 pathway

Esophageal squamous cell carcinoma (ESCC) remains a major clinical challenge due to its poor prognosis and the scarcity effective therapeutic targets. Circular RNAs (circRNAs) are crucial in cancer progression. In this study, high-throughput sequencing was employed to profile ESCC tissues, revealing that hsa_circ_0001165 is notably elevated in both ESCC tumor samples and cell lines, with its expression is positively associated with patients' TNM staging. Knockdown of hsa_circ_0001165 resulted in reduced malignant biological behavior of ESCC cells in vitro and also inhibited tumor growth in vivo. Mechanism experimental analysis found that hsa_circ_0001165 expression is positively enhanced by eukaryotic translation initiation factor 4A3 (EIF4A3). Hsa_circ_0001165 acts as a miRNA sponge for miR-381-3p, increasing the expression of tensin-3 (TNS3) through a series of related mechanism assays include dual-luciferase reporter gene, RNA Immunoprecipitation and RNA-pulldown. The downregulation in miR-381-3p expression was observed in ESCC tissues, and the cell proliferation, invasion, and migration of ESCC were suppressed. The upregulated expression of hsa_circ_0001165 modulates the miR-381-3p/TNS3 axis and promotes aggressive phenotypes of ESCC. Hsa_circ_0001165 is regarded as a encouraging biomarker and potential therapeutic target for ESCC, presenting innovative options for both diagnostic and treatment approaches.

Analysis of Pancreatic Cancer Genetic Risk Factors in a Multi-Ethnic Population Sample

Background

Pancreatic cancer (PC) has one of the highest mortality to incidence ratio of all cancers. Early identification of at-risk individuals should permit early diagnosis. Genome-wide association studies showed the association of several genetic variants with PC risk in multi-ethnic populations. Our objective was to examine the association of these genetic variants with PC in a population sample from Kuwait.

Methods

DNA samples from 103 pancreatic ductal adenocarcinoma (PDAC) specimens and 132 healthy controls were used for genotyping ABO rs505922, BCAR1 rs7190458, LINC-PINT rs6971499, HNF1B rs4795218, VDR rs2228570 rs731236, and PRSS1 rs111033565 rs111033568 rs387906698 and rs267606982 using TaqMan genotyping assays, and VDR expression was performed by immunocytochemistry.

Results

ABO rs505922C and VDR rs2228570A were associated with PDAC risk (odds ratio (OR): 1.55, 95% confidence interval (CI): 1.07 - 2.24, P = 0.027; OR: 1.64, 95% CI: 1.09 - 2.48, P = 0.024; respectively). An unweighted polygenic risk score (ABO rs505922, BCAR1 rs7190458, LINC-PINT rs6971499, and HNF1B rs4795218) was significantly associated with PDAC risk (β: -0.11, 95% CI: -0.15 to -0.05, P < 0.001). VDR expression was downregulated or absent in most PDAC specimens regardless of VDR haplotype.

Conclusion

ABO rs505922C and VDR rs2228570A are PDAC genetic risk factors in our population. Ethnicity influences the association of reported genetic PDAC risk factors and should be adjusted for when performing PDAC genetic risk estimations. Investigation of these genetic risk factors in other ethnic populations is a necessity to evaluate their PDAC risk prediction potential.

Large-scale multi-omic analysis identifies noncoding somatic driver mutations and nominates ZFP36L2 as a driver gene for pancreatic ductal adenocarcinoma

Identification of somatic driver mutations in the noncoding genome remains challenging. To comprehensively characterize noncoding driver mutations for pancreatic ductal adenocarcinoma (PDAC), we first created genome-scale maps of accessible chromatin regions (ACRs) and histone modification marks (HMMs) in pancreatic cell lines and purified pancreatic acinar and duct cells. Integration with whole-genome mutation calls from 506 PDACs revealed 314 ACRs/HMMs significantly enriched with 3,614 noncoding somatic mutations (NCSMs). Functional assessment using massively parallel reporter assays (MPRA) identified 178 NCSMs impacting reporter activity (19.45% of those tested). Focused luciferase validation confirmed negative effects on gene regulatory activity for NCSMs near CDKN2A and ZFP36L2. For the latter, CRISPR interference (CRISPRi) further identified ZFP36L2 as a target gene (16.0 - 24.0% reduced expression, P = 0.023-0.0047) with disrupted KLF9 binding likely mediating the effect. Our integrative approach provides a catalog of potentially functional noncoding driver mutations and nominates ZFP36L2 as a PDAC driver gene.

Allelic effects on KLHL17 expression likely mediated by JunB/D underlie a PDAC GWAS signal at chr1p36.33

Pancreatic Ductal Adenocarcinoma (PDAC) is the third leading cause of cancer-related deaths in the U.S. Both rare and common germline variants contribute to PDAC risk. Here, we fine-map and functionally characterize a common PDAC risk signal at 1p36.33 (tagged by rs13303010) identified through a genome wide association study (GWAS). One of the fine-mapped SNPs, rs13303160 (r2=0.93 in 1000G EUR samples, OR=1.23, P value=2.74x10-9) demonstrated allele-preferential gene regulatory activity in vitro and allele-preferential binding of JunB and JunD in vitro and in vivo. Expression Quantitative Trait Locus (eQTL) analysis identified KLHL17 as a likely target gene underlying the signal. Proteomic analysis identified KLHL17 as a member of the Cullin-E3 ubiquitin ligase complex in PDAC-derived cells. In silico differential gene expression analysis of the GTExv8 pancreas data suggested an association between lower KLHL17 (risk associated) and pro-inflammatory pathways. We hypothesize that KLHL17 may mitigate inflammation by recruiting pro-inflammatory proteins for ubiquitination and degradation thereby influencing PDAC risk.

Predictive Prioritization of Enhancers Associated with Pancreas Disease Risk

Genetic and epigenetic variations in regulatory enhancer elements increase susceptibility to a range of pathologies. Despite recent advances, linking enhancer elements to target genes and predicting transcriptional outcomes of enhancer dysfunction remain significant challenges. Using 3D chromatin conformation assays, we generated an extensive enhancer interaction dataset for the human pancreas, encompassing more than 20 donors and five major cell types, including both exocrine and endocrine compartments. We employed a network approach to parse chromatin interactions into enhancer-promoter tree models, facilitating a quantitative, genome-wide analysis of enhancer connectivity. With these tree models, we developed a machine learning algorithm to estimate the impact of enhancer perturbations on cell type-specific gene expression in the human pancreas. Orthogonal to our computational approach, we perturbed enhancer function in primary human pancreas cells using CRISPR interference and quantified the effects at the single-cell level through RNA FISH coupled with high-throughput imaging. Our enhancer tree models enabled the annotation of common germline risk variants associated with pancreas diseases, linking them to putative target genes in specific cell types. For pancreatic ductal adenocarcinoma, we found a stronger enrichment of disease susceptibility variants within acinar cell regulatory elements, despite ductal cells historically being assumed as the primary cell-of-origin. Our integrative approach-combining cell type-specific enhancer-promoter interaction mapping, computational models, and single-cell enhancer perturbation assays-produced a robust resource for studying the genetic basis of pancreas disorders.

Genome-Wide Analysis to Assess if Heavy Alcohol Consumption Modifies the Association between SNPs and Pancreatic Cancer Risk

BACKGROUND

Pancreatic cancer is a leading cause of cancer-related death globally. Risk factors for pancreatic cancer include common genetic variants and potentially heavy alcohol consumption. We assessed if genetic variants modify the association between heavy alcohol consumption and pancreatic cancer risk.

METHODS

We conducted a genome-wide interaction analysis of single-nucleotide polymorphisms (SNP) by heavy alcohol consumption (more than three drinks per day) for pancreatic cancer in European ancestry populations from genome-wide association studies. Our analysis included 3,707 cases and 4,167 controls from case-control studies and 1,098 cases and 1,162 controls from cohort studies. Fixed-effect meta-analyses were conducted.

RESULTS

A potential novel region of association on 10p11.22, lead SNP rs7898449 (interaction P value (Pinteraction) = 5.1 × 10-8 in the meta-analysis; Pinteraction = 2.1 × 10-9 in the case-control studies; Pinteraction = 0.91 in the cohort studies), was identified. An SNP correlated with this lead SNP is an expression quantitative trait locus for the neuropilin 1 gene. Of the 17 genomic regions with genome-wide significant evidence of association with pancreatic cancer in prior studies, we observed suggestive evidence that heavy alcohol consumption modified the association for one SNP near LINC00673, rs11655237 on 17q25.1 (Pinteraction = 0.004).

CONCLUSIONS

We identified a novel genomic region that may be associated with pancreatic cancer risk in conjunction with heavy alcohol consumption located near an expression quantitative trait locus for neuropilin 1, a protein that plays an important role in the development and progression of pancreatic cancer.

IMPACT

This work can provide insights into the etiology of pancreatic cancer, particularly in heavy drinkers.

The role of aspirin in the prevention of pancreatic cancer: A nested case-control study in the UK Biobank

BACKGROUND

Aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) usage has been associated with pancreatic ductal adenocarcinoma (PDAC) prevention, though epidemiological data have not reliably demonstrated this. The aim of this study is to identify if aspirin and other NSAIDs are effective in the primary prevention of PDAC in a large UK prospective cohort.

METHODS

A nested case-control study was conducted using the UK Biobank cohort. Incident PDAC cases (n = 1129 of whom 239 (21.2 %) were using aspirin) were age and sex-matched with cancer-free controls (n = 8822 of whom 1752 (19.9 %) were using aspirin). Conditional logistic regression models were used to generate odds ratios (ORs) and 95 % confidence intervals (CI) for risk of PDAC with and without regular use of aspirin, non-aspirin NSAIDs and all NSAIDs respectively. Exploratory analyses were carried out assessing interactions with diabetes mellitus (DM) as a condition with increased pancreatic cancer risk.

RESULTS

Regular aspirin use at initial recruitment was independently associated with a decreased risk of PDAC (OR [95 % CI] = 0.80 [0.68-0.95] P = 0.01). Regular non-aspirin NSAID use was not associated with a risk reduction of PDAC (OR [95 % CI] = 1.01 [0.84-1.23] P = 0.88). Exploratory analyses showed that in those with DM; regular aspirin use reduced risk of PDAC (OR [95 % CI] = 0.60 [0.42-0.85] P = 0.004) compared to non-use.

DISCUSSION

Regular aspirin use is associated with a reduction in risk of PDAC. The reduced risk is more apparent in participants with DM.

Large-Scale Alternative Polyadenylation-Wide Association Studies to Identify Putative Cancer Susceptibility Genes

Alternative polyadenylation (APA) modulates mRNA processing in the 3'-untranslated regions (3' UTR), affecting mRNA stability and translation efficiency. Research into genetically regulated APA has the potential to provide insights into cancer risk. In this study, we conducted large APA-wide association studies to investigate associations between APA levels and cancer risk. Genetic models were built to predict APA levels in multiple tissues using genotype and RNA sequencing data from 1,337 samples from the Genotype-Tissue Expression project. Associations of genetically predicted APA levels with cancer risk were assessed by applying the prediction models to data from large genome-wide association studies of six common cancers among European ancestry populations: breast, ovarian, prostate, colorectal, lung, and pancreatic cancers. A total of 58 risk genes (corresponding to 76 APA sites) were associated with at least one type of cancer, including 25 genes previously not linked to cancer susceptibility. Of the identified risk APAs, 97.4% and 26.3% were supported by 3'-UTR APA quantitative trait loci and colocalization analyses, respectively. Luciferase reporter assays for four selected putative regulatory 3'-UTR variants demonstrated that the risk alleles of 3'-UTR variants, rs324015 (STAT6), rs2280503 (DIP2B), rs1128450 (FBXO38), and rs145220637 (LDHA), significantly increased the posttranscriptional activities of their target genes compared with reference alleles. Furthermore, knockdown of the target genes confirmed their ability to promote proliferation and migration. Overall, this study provides insights into the role of APA in the genetic susceptibility to common cancers. Significance: Systematic evaluation of associations of alternative polyadenylation with cancer risk reveals 58 putative susceptibility genes, highlighting the contribution of genetically regulated alternative polyadenylation of 3'UTRs to genetic susceptibility to cancer.

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.

Sleep, physical activity, and sedentary behaviors in relation to overall cancer and site-specific cancer risk: A prospective cohort study

Large prospective studies are required to better elucidate the associations of physical activity, sedentary behaviors (SBs), and sleep with overall cancer and site-specific cancer risk, accounting for the interactions with genetic predisposition. The study included 360,271 individuals in UK Biobank. After a median follow-up of 12.52 years, we found higher total physical activity (TPA) level and higher sleep scores were related to reduced risk of cancer while higher SB level showed a positive association with cancer. Compared with high TPA-healthy sleep group and low SB-healthy sleep group, low TPA-poor sleep group and high SB-poor sleep group had the highest risk for overall cancer, breast cancer, and lung cancer. Adherence to a more active exercise pattern was associated with a lower risk of cancer irrespective of genetic risk. Our study suggests that improving the quality of sleep and developing physical activity habits might yield benefits in mitigating the cancer risk.

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.

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.