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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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025. Published by Elsevier Ltd.)

Pancreatic cancer (PC), particularly its most common form, pancreatic ductal adenocarcinoma (PDAC), is relatively rare but highly lethal. Knowledge about PC risk factors could in the long term contribute to early diagnosis and mortality reduction. We review the current status of research on germline genetic factors for PC risk. Genome-wide association studies (GWAS) successfully identified common loci convincingly associated with PC risk, an endeavor that is still ongoing. The function of only a handful of risk loci has being thoroughly characterized so far. Secondary analyses of existing GWAS data are being used to discover novel loci. GWAS data have also been used to study additional risk factors with a Mendelian randomization approach. Polygenic/multifactorial risk scores show much larger risks than individual variants, but their use for risk stratification in the population is not warranted yet. At the other end of the spectrum of inherited PC risk factors, rare high-penetrance variants co-segregating with the disease have been observed in familial cancer syndromes that include PC, or in families with multiple recurrence of PC alone. Rare variants predicted to have a deleterious effect on function are studied also with a case-control approach, by resequencing candidate genes or whole-exomes/whole-genomes. Telomere length and mitochondrial DNA copy number are useful additional DNA-based markers of PC susceptibility. The role of common variants in prognosis of PC patients has also been explored, albeit with more limited success than risk. Finally, genetics of pancreatic neuroendocrine tumors (PNET), a rarer and heterogeneous form of PC, is still understudied., (Copyright © 2020. Published by Elsevier Ltd.)