PancPRO: risk assessment for individuals with a family history of pancreatic cancer

Association between prediagnostic serum metabolites and pancreatic ductal adenocarcinoma risk in two prospective cohorts

Pancreatic ductal adenocarcinoma (PDAC) is highly fatal, with incidence rising worldwide. Metabolomics may provide insight into etiology and mechanisms contributing to pancreatic carcinogenesis. We examined associations between 1483 prediagnostic (up to 24 years) serum metabolites and PDAC in nested case-control studies within a cohort of male Finnish smokers and another of American men and women (n = 732 matched pairs). We used conditional logistic regression to calculate odds ratios (OR) and 95% confidence intervals per standard deviation increase in log-metabolite level within each cohort and combined using fixed-effect meta-analyses. We performed elastic net regression (EN) to select metabolites and calculated area under the curve (AUC) for established PDAC risk factors (smoking, diabetes, and overweight/obesity), selected metabolites, and their combination. Sixty-six metabolites were associated with PDAC at false discovery rate <0.05, with 26 below Bonferroni threshold (p < 3.4 × 10-5) and 38 not reported previously. Notable findings include fibrinopeptide B (1-9); 13 modified, di- or poly-peptides; 11 tobacco-chemical related xenobiotics; glycolysis-gluconeogenesis-tricarboxylic acid (TCA) cycle metabolites (aspartate, glutamate, lactate, α-ketoglutarate, and pyruvate); and four secondary and two primary bile acids that were positively (OR = 1.18-1.58) and five fibrinogen cleavage peptides that were inversely (OR = 0.70-0.84) associated with PDAC. AUCs for combined metabolites-risk factors outperformed known risk factors (p ≤ .01) but not metabolites (p ≥ .31) alone. Systemic metabolism is prospectively associated with PDAC. New metabolite associations include those related to immune response, tobacco, microbiome, glycolysis-gluconeogenesis and TCA cycle, and adiposity or diabetes. The EN selected metabolites were more sensitive indicators of prediagnostic metabolic processes and exposures associated with PDAC than established risk factors.

Impacts of sample weighting on transferability of risk prediction models across EHR-Linked biobanks with different recruitment strategies

OBJECTIVE

To evaluate whether using poststratification weights when training risk prediction models enhances transferability when the external test cohort has a different sampling strategy, a commonly encountered scenario when analyzing electronic health record (EHR)-linked biobanks.

METHODS

PS weights were calculated to align a health system-based biobank, the Michigan Genomics Initiative (MGI; n = 76,757), with a nationally recruited biobank, All of Us (AOU; n = 226,764), which oversamples underrepresented groups. Basic PS weights (PSBASIC) captured age, sex, and race/ethnicity; full PS weights (PSFULL) additionally included smoking, alcohol consumption, BMI, depression, hypertension, and the Charlson Comorbidity Index. Models for esophageal, liver, and pancreatic cancers were developed using EHR data from MGI at 0, 1, 2, and 5 years prior to diagnosis. Phenotype risk scores (PheRS) were constructed using six methods (e.g., regularized regression, random forest) and evaluated alongside covariates, risk factors, and symptoms. Evaluation metrics included the odds ratio (OR) for the top decile vs. the middle 40th-60th percentiles of the risk score distribution and the area under the receiver operating curve (AUC) evaluated in the AOU test cohort when models are trained with and without weighting.

RESULTS

Elastic net and random forest methods generally performed well in risk stratification, but no single PheRS construction method consistently outperformed others. Applying PS weights did not consistently improve risk stratification performance. For example, in liver cancer risk stratification at t = 1, unweighted random forest PheRS yielded an OR of 13.73 (95 % CI: 8.97, 21.01), compared to 14.55 (95 % CI: 9.45, 22.42) with PSBASIC and 13.62 (95 % CI: 8.90, 20.85) with PSFULL.

CONCLUSION

PS weights do not significantly enhance risk model transferability between biobanks. EHR-based PheRS are crucial for risk stratification and should be integrated with other multimodal data for improved risk prediction. Identifying high-risk populations for diseases like liver cancer early through health history mining shows promise.

Automated detection of cervical spondylotic myelopathy: harnessing the power of natural language processing

Background

The objective of this study was to develop machine learning (ML) algorithms utilizing natural language processing (NLP) techniques for the automated detection of cervical spondylotic myelopathy (CSM) through the analysis of positive symptoms in free-text admission notes. This approach enables the timely identification and management of CSM, leading to optimal outcomes.

Methods

The dataset consisted of 1,214 patients diagnosed with cervical diseases as their primary condition between June 2013 and June 2020. A random ratio of 7:3 was employed to partition the dataset into training and testing subsets. Two machine learning models, Extreme Gradient Boosting (XGBoost) and Bidirectional Long Short Term Memory Network (LSTM), were developed. The performance of these models was assessed using various metrics, including the Receiver Operating Characteristic (ROC) curve, Area Under the Curve (AUC), accuracy, precision, recall, and F1 score.

Results

In the testing set, the LSTM achieved an AUC of 0.9025, an accuracy of 0.8740, a recall of 0.9560, an F1 score of 0.9122, and a precision of 0.8723. The LSTM model demonstrated superior clinical applicability compared to the XGBoost model, as evidenced by calibration curves and decision curve analysis.

Conclusions

The timely identification of suspected CSM allows for prompt confirmation of diagnosis and treatment. The utilization of NLP algorithm demonstrated excellent discriminatory capabilities in identifying CSM based on positive symptoms in free-text admission notes complaint data. This study showcases the potential of a pre-diagnosis system in the field of spine.

Pathogenic germline variants in Chinese pancreatic adenocarcinoma patients

Putting pancreatic adenocarcinoma (PAAD) screening into perspective for high-risk individuals could significantly reduce cancer morbidity and mortality. Previous studies have profiled somatic mutations in PAAD. In contrast, the prevalence of mutations in PAAD predisposition genes has not been defined, especially in the Asian population. Using a multi-tier cohort design and whole genome/exome sequencing, we create a comprehensive germline mutation map of PAAD in 1,123 Chinese cancer patients in comparison with 11 pan-ethnic studies. For well-known pathogenic/likely pathogenic germline variants, Chinese patients exhibit overlapping but distinct germline mutation patterns comparing with Western cohorts, highlighted by lower mutation rates in known PAAD genes including BRCA1, BRCA2, ATM, CDKN2A, and CHEK2, and distinct mutations in CFTR, RAD51D, FANCA, ERCC2, and GNAS exclusive to Chinese patients. CFTR emerges as a top candidate gene following loss of heterozygosity analysis. Using an integrative multi-omics and functional validation paradigm, we discover that deleterious variants of uncertain significance may compromise CFTR's tumor suppressor function, and demonstrate the clinical relevance by using patient derived organoids for drug screen. Our multifaceted approach not only deepens the knowledge of population differences in PAAD germline mutations but also unveils potential avenues for targeted therapeutic interventions.

Pancreatic Cancer: Screening and Early Detection

Pancreatic cancer, often diagnosed at advanced stages, has poor survival rates. Effective screening aims to detect the disease early, improving outcomes. Current guidelines recommend screening high-risk groups, including those with a family history or genetic predispositions, using methods like endoscopic ultrasound and MRI. The American Gastroenterological Association and other organizations advise annual surveillance for high-risk individuals, typically starting at the age of 50 or 10 years younger than the youngest affected relative. For certain genetic syndromes, such as Peutz-Jeghers syndrome or hereditary pancreatitis, screening may begin as early as the age of 35 to 40 years.

Advancements in Early Detection and Screening Strategies for Pancreatic Cancer: From Genetic Susceptibility to Novel Biomarkers

Pancreatic cancer is a rare but lethal cancer due to its biologically aggressive nature, advanced stage at the time of diagnosis, and poor response to oncologic therapies. The risk of pancreatic cancer is significantly higher to 5% in certain high-risk individuals with inherited genetic susceptibility. Screening for pancreatic cancer in these individuals from high-risk groups can help with the early detection of pancreatic cancer as well as the detection of precursor lesions leading to early surgical resection and improved overall outcomes. The advancements in radiological imaging as well as advanced endoscopic procedures has made a significant impact on the early diagnosis, surveillance, and staging of pancreatic cancer. There is also a significant advancement in the development of biomarkers for the early detection of pancreatic cancer, which has also led to the development of liquid biopsy, allowing for microRNA detection in serum and circulating tumor cells. Various societies and organizations have provided guidelines for pancreatic cancer screening and surveillance in high-risk individuals. In this review, we aim to discuss the hereditary risk factors for developing pancreatic cancer, summarize the screening recommendations by different societies, and discuss the development of novel biomarkers and areas for future research in pancreatic cancer screening for high-risk individuals.

The Italian registry of families at risk for pancreatic cancer (IRFARPC): implementation and evolution of a national program for pancreatic cancer surveillance in high-risk individuals

Screening programs for early detection and treatment of pancreatic cancer (PC) and its precursor lesions are increasingly implemented worldwide to reduce disease-specific lethality. Given the relatively low prevalence of the disease, the ideal target of such approaches is an enriched cohort of individuals harboring a lifetime risk of developing PC significantly higher compared to the general population, given either a substantial aggregation of PC cases in their family (i.e. familial pancreatic cancer) or a genomic landscape enriched with pathogenic variants associated with pancreatic carcinogenesis (i.e. mutation carriers). In Italy, a national registry for the census and surveillance of high-risk individuals for PC was launched in 2015, enrolling some 1200 subjects as of today. In this perspective, the scientific background, multi-level structure, and evolution of IRFARPC are outlined, as well as its long-term results, future developments, and areas for improvement.

Bile Acids in Pancreatic Carcinogenesis

Pancreatic cancer (PC) is a dangerous digestive tract tumor that is becoming increasingly common and fatal. The most common form of PC is pancreatic ductal adenocarcinoma (PDAC). Bile acids (BAs) are closely linked to the growth and progression of PC. They can change the intestinal flora, increasing intestinal permeability and allowing gut microbes to enter the bloodstream, leading to chronic inflammation. High dietary lipids can increase BA secretion into the duodenum and fecal BA levels. BAs can cause genetic mutations, mitochondrial dysfunction, abnormal activation of intracellular trypsin, cytoskeletal damage, activation of NF-κB, acute pancreatitis, cell injury, and cell necrosis. They can act on different types of pancreatic cells and receptors, altering Ca2+ and iron levels, and related signals. Elevated levels of Ca2+ and iron are associated with cell necrosis and ferroptosis. Bile reflux into the pancreatic ducts can speed up the kinetics of epithelial cells, promoting the development of pancreatic intraductal papillary carcinoma. BAs can cause the enormous secretion of Glucagon-like peptide-1 (GLP-1), leading to the proliferation of pancreatic β-cells. Using Glucagon-like peptide-1 receptor agonist (GLP-1RA) increases the risk of pancreatitis and PC. Therefore, our objective was to explore various studies and thoroughly examine the role of BAs in PC.

Use of multi-gene panels in patients at high risk of hereditary digestive cancer: position statement of AEG, SEOM, AEGH and IMPaCT-GENÓMICA consortium

This position statement, sponsored by the Asociación Española de Gastroenterología, the Sociedad Española de Oncología Médica, the Asociación Española de Genética Humana and the IMPaCT-Genómica Consortium aims to establish recommendations for use of multi-gene panel testing in patients at high risk of hereditary gastrointestinal and pancreatic cancer. To rate the quality of the evidence and the levels of recommendation, we used the methodology based on the GRADE system (Grading of Recommendations Assessment, Development and Evaluation). We reached a consensus among experts using a Delphi method. The document includes recommendations on clinical scenarios where multi-gene panel testing is recommended in colorectal cancer, polyposis syndromes, gastric and pancreatic cancer, as well as the genes to be considered in each clinical scenario. Recommendations on the evaluation of mosaicisms, counseling strategies in the absence of an index subject and, finally, constitutional analysis after identification of pathogenic tumor variants are also made.

Risk perception and surveillance uptake in individuals at increased risk for pancreatic ductal adenocarcinoma

BACKGROUND

Surveillance for pancreatic ductal adenocarcinoma (PDAC) is recommended for high-risk individuals with genetic variants in PDAC-associated genes and/or family history. Surveillance uptake and adherence may depend on the perception of PDAC risk and cancer worry. We aimed to determine PDAC risk perception in at-risk individuals and assess factors associated with PDAC surveillance uptake.

METHODS

At-risk individuals identified from a prospective academic registry were sent a survey electronically. PDAC risk perception, cancer worry and surveillance uptake were surveyed. Factors associated with increased risk perception and surveillance were assessed. Five-year PDAC risk was calculated using the PancPRO risk assessment model, and correlation with subjective risk assessment was assessed.

RESULTS

The overall survey response rate was 34% (279/816). The median perceived PDAC risk was twofold (IQR 1-4) above respondents' estimates of general population risk. Factors significantly associated with higher perceived PDAC risk included non-Hispanic white race, post-graduate education level, PDAC-affected first-degree relative, genetic variants and lack of personal cancer history. Cancer worry had a very weak correlation across PDAC risk estimates (r=0.16). No correlation between perceived PDAC risk and 5-year calculated PDAC risk was found. Older age, having a first-degree relative with PDAC, meeting with a medical provider about PDAC cancer risk and awareness of surveillance modalities were significant predictors of undergoing PDAC surveillance.

CONCLUSIONS

Individuals at risk for PDAC do not report risk perception that correlates with calculated risk. This presents an opportunity for counselling of at-risk patients to individualise management and improve surveillance uptake for eligible individuals.

LFSPROShiny: An Interactive R/Shiny App for Prediction and Visualization of Cancer Risks in Families With Deleterious Germline TP53 Mutations

PURPOSE

LFSPRO is an R library that implements risk prediction models for Li-Fraumeni syndrome (LFS), a genetic disorder characterized by deleterious germline mutations in the TP53 gene. To facilitate the use of these models in clinics, we developed LFSPROShiny, an interactive R/Shiny interface of LFSPRO that allows genetic counselors (GCs) to perform risk predictions without any programming components and further visualize the risk profiles of their patients to aid the decision-making process.

METHODS

LFSPROShiny implements two models that have been validated on multiple LFS patient cohorts: a competing risk model that predicts cancer-specific risks for the first primary and a recurrent-event model that predicts the risk of a second primary tumor. Starting with a visualization template, we keep regular contact with GCs, who ran LFSPROShiny in their counseling sessions, to collect feedback and discuss potential improvement. On receiving the family history as input, LFSPROShiny renders the family into a pedigree and displays the risk estimates of the family members in a tabular format. The software offers interactive overlaid side-by-side bar charts for visualization of the patients' cancer risks relative to the general population.

RESULTS

We walk through a detailed example to illustrate how GCs can run LFSPROShiny in clinics from data preparation to downstream analyses and interpretation of results with an emphasis on the utilities that LFSPROShiny provides to aid decision making.

CONCLUSION

Since December 2021, we have applied LFSPROShiny to over 100 families from counseling sessions at the MD Anderson Cancer Center. Our study suggests that software tools with easy-to-use interfaces are crucial for the dissemination of risk prediction models in clinical settings, hence serving as a guideline for future development of similar models.

Global, regional, and national burdens of early onset pancreatic cancer in adolescents and adults aged 15-49 years from 1990 to 2019 based on the Global Burden of disease study 2019: A cross-sectional study

BACKGROUND

Early-onset pancreatic cancer (EOPC) in younger populations (age≤50 y) is likely to be a more aggressive phenotype characterized by poor differentiation. The emerging analysis of the global burden of EOPC is limited and outdated.

AIM

To systematically investigate the burden and trend of EOPC based on global populations.

METHODS

In this systematic analysis based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we present the number of cases, age-standardized rates (ASRs) per 100,000 population, and risk factors for 204 countries and territories. The average annual percentage changes (AAPCs) for the incidence, mortality, and disability-adjusted life-years (DALYs) of EOPC were calculated using joinpoint regression analysis.

RESULTS

According to the GBD 2019 estimates, there were 36,852 new cases of EOPC and 32,004 related deaths. East Asia had the highest number of cases, with 11,401 incidences and 10,149 deaths. The ASRs were 0.94 per 100,000 individuals for incidence and 0.81 per 100,000 for mortality. From 1990 to 2019, the age-standardized incidence increased by 46.9%, mortality increased by 44.6%, and DALYs increased by 41.9% globally. In trend analysis, the global incidence (AAPC, 1.26), mortality (AAPC, 1.24), and DALYs (AAPC, 1.25) of EOPC showed an increasing pattern. The ASRs of incidence, mortality, and DALYs of EOPC in Africa, America, and Asia exhibited a continuous upward trend, while the trend in Europe was fluctuating. Asian males exhibited the fastest growth in incidence (AAPC, 2.15) and mortality (AAPC, 2.13), whereas males in the Americas experienced the slowest increase in new cases (AAPC, 0.72) and deaths (AAPC, 0.67). A certain proportion of EOPC DALYs were attributable to known risk factors: tobacco smoking (13.3%), high body-mass index (BMI, 5.6%), and high fasting plasma glucose (FPG, 3.2%). Integrating the socio-demographic index (SDI), ASRs of incidence and mortality initially increased with rising SDI, reaching a peak in central Europe (1.5 per 100,000

CONCLUSIONS

The findings offer valuable insights into the global distribution and magnitude of the EOPC burden. The burden is increasing at a rapid pace worldwide, particularly in Asia, and is notably high in central and eastern Europe. This highlights the need for additional preventive control efforts targeting high-risk populations.

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Key Words

• early-onset pancreatic cancer
• epidemiology
• incidence
• mortality
• risk factor
• trend in global burden

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MESH Headings Collapse

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Affiliation(s)

Zheng Li
Xiaojie Zhang
Chongyuan Sun
Zefeng Li
He Fei
Dongbing Zhao Department of Pancreatic and Gastric Surgical Oncology, National Cancer Center/National Clinical Research for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China

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Collaborators Collapse

LFSPROShiny: an interactive R/Shiny app for prediction and visualization of cancer risks in families with deleterious germline TP53 mutations

Purpose

LFSPRO is an R library that implements risk prediction models for Li-Fraumeni syndrome (LFS), a genetic disorder characterized by deleterious germline mutations in the TP53 gene. To facilitate the use of these models in clinics, we developed LFSPROShiny, an interactive R/Shiny interface of LFSPRO that allows genetic counselors (GCs) to perform risk predictions without any programming components, and further visualize the risk profiles of their patients to aid the decision-making process.

Methods

LFSPROShiny implements two models that have been validated on multiple LFS patient cohorts: a competing-risk model that predicts cancer-specific risks for the first primary, and a recurrent-event model that predicts the risk of a second primary tumor. Starting with a visualization template, we keep regular contact with GCs, who ran LFSPROShiny in their counseling sessions, to collect feedback and discuss potential improvement. Upon receiving the family history as input, LFSPROShiny renders the family into a pedigree, and displays the risk estimates of the family members in a tabular format. The software offers interactive overlaid side-by-side bar charts for visualization of the patients' cancer risks relative to the general population.

Results

We walk through a detailed example to illustrate how GCs can run LFSPROShiny in clinics, from data preparation to downstream analyses and interpretation of results with an emphasis on the utilities that LFSPROShiny provides to aid decision making.

Conclusion

Since Dec 2021, we have applied LFSPROShiny to over 100 families from counseling sessions at MD Anderson Cancer Center. Our study suggests that software tools with easy-to-use interfaces are crucial for the dissemination of risk prediction models in clinical settings, hence serving as a guideline for future development of similar models.

Variant-specific Mendelian Risk Prediction Model

Many pathogenic sequence variants (PSVs) have been associated with increased risk of cancers. Mendelian risk prediction models use Mendelian laws of inheritance to predict the probability of having a PSV based on family history, as well as specified PSV frequency and penetrance (agespecific probability of developing cancer given genotype). Most existing models assume penetrance is the same for any PSVs in a certain gene. However, for some genes (for example, BRCA1/2), cancer risk does vary by PSV. We propose an extension of Mendelian risk prediction models to relax the assumption that risk is the same for any PSVs in a certain gene by incorporating variant-specific penetrances and illustrating these extensions on two existing Mendelian risk prediction models, BRCAPRO and PanelPRO. Our proposed BRCAPRO-variant and PanelPRO-variant models incorporate variant-specific BRCA1/2 PSVs through the region classifications. Due to the sparsity of the variant information we classify BRCA1/2 PSVs into three regions; the breast cancer clustering region (BCCR), the ovarian cancer clustering region (OCCR), and an other region. Simulations were conducted to evaluate the performance of the proposed BRCAPRO-variant model compared to the existing BRCAPRO model which assumes the penetrance is the same for any PSVs in BRCA1 (and respectively BRCA2). Simulation results showed that the BRCAPRO-variant model was well calibrated to predict region-specific BRCA1/2 carrier status with high discrimination and accuracy on the region-specific level. In addition, we showed that the BRCAPRO-variant model achieved performance gains over the existing risk prediction models in terms of calibration without loss in discrimination and accuracy. We also evaluated the performance of the two proposed models, BRCAPRO-variant and PanelPRO-variant, on a cohort of 1,961 families from the Cancer Genetics Network (CGN). We showed that our proposed models provide region-specific PSV carrier probabilities with high accuracy, while the calibration, discrimination and accuracy of gene-specific PSV carrier probabilities were comparable to the existing gene-specific models. As more variant-specific PSV penetrances become available, we have shown that Mendelian risk prediction models can be extended to integrate the additional information, providing precise variant or region-specific PSV carrier probabilities and improving future cancer risk predictions.

Identification of individuals at high-risk for pancreatic cancer using a digital patient-input tool combining family cancer history screening and new-onset diabetes

Capturing family history might be a valuable tool for identification of individuals at increased risk of pancreatic cancer, which would allow enrollment into pancreatic surveillance programs. In addition, weight loss and concurrent new-onset diabetes may be utilized as an early marker for pancreatic cancer. This study evaluates the yield of combining family history and the Enriching New-Onset Diabetes for Pancreatic Cancer (ENDPAC) model to identify individuals who could benefit from pancreatic surveillance. A novel questionnaire and digital input tool was created that combined questions on family cancer history and criteria of the ENDPAC model. Individuals meeting ENDPAC criteria were enrolled directly in the high-risk pancreatic clinic. Individuals who met the criteria for a significant family history of cancer were offered referral to a genetic counselor. The questionnaire was completed by 453 patients. Of those, 25.8% (117/453) had significant familial risk factors. Eighteen individuals (15.4%) completed genetic testing previously, of whom five had a pathogenic variant. Thirty-four (29.9%) out of 117 individuals with a strong family history - flagged by the questionnaire - underwent genetic testing. Four (11.8%) of these patients harbored a pathogenic variant. Additionally, through cascade family testing, two siblings were found to carry pathogenic variants. Four (0.9%) of the 453 patients matched ENDPAC criteria. Two were diagnosed with pancreatic cancer and the others were enrolled in the surveillance program. In conclusion, identification of high-risk individuals for pancreatic cancer can be achieved by combining family history screening and the ENDPAC model to facilitate referral to genetic counseling and high-risk clinics.

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.

Statistical methods for Mendelian models with multiple genes and cancers

Risk evaluation to identify individuals who are at greater risk of cancer as a result of heritable pathogenic variants is a valuable component of individualized clinical management. Using principles of Mendelian genetics, Bayesian probability theory, and variant-specific knowledge, Mendelian models derive the probability of carrying a pathogenic variant and developing cancer in the future, based on family history. Existing Mendelian models are widely employed, but are generally limited to specific genes and syndromes. However, the upsurge of multigene panel germline testing has spurred the discovery of many new gene-cancer associations that are not presently accounted for in these models. We have developed PanelPRO, a flexible, efficient Mendelian risk prediction framework that can incorporate an arbitrary number of genes and cancers, overcoming the computational challenges that arise because of the increased model complexity. We implement an 11-gene, 11-cancer model, the largest Mendelian model created thus far, based on this framework. Using simulations and a clinical cohort with germline panel testing data, we evaluate model performance, validate the reverse-compatibility of our approach with existing Mendelian models, and illustrate its usage. Our implementation is freely available for research use in the PanelPRO R package.

Current status of inherited pancreatic cancer

Background

It is estimated that about 10% of pancreatic cancer cases have a genetic background. People with a familial predisposition to pancreatic cancer can be divided into 2 groups. The first is termed hereditary pancreatic cancer, which occurs in individuals with a known hereditary cancer syndrome caused by germline single gene mutations (e.g., BRCA1/2, CDKN2A). The second is considered as familial pancreatic cancer, which is associated with several genetic factors responsible for the more common development of pancreatic cancer in certain families, but the precise single gene mutation has not been found.

Aim

This review summarizes the current state of knowledge regarding the risk of pancreatic cancer development in hereditary pancreatic cancer and familial pancreatic cancer patients. Furthermore, it gathers the latest recommendations from the three major organizations dealing with the prevention of pancreatic cancer in high-risk groups and explores recent guidelines of scientific societies on screening for pancreatic cancers in individuals at risk for hereditary or familial pancreatic cancer.

Conclusions

In order to improve patients’ outcomes, authors of current guidelines recommend early and intensive screening in patients with pancreatic cancer resulting from genetic background. The screening should be performed in excellence centers. The scope, extent and cost-effectiveness of such interventions requires further studies.

Is Biannual Surveillance for Pancreatic Cancer Sufficient in Individuals With Genetic Syndromes or Familial Pancreatic Cancer?

BACKGROUND

Individuals with a family history of pancreatic adenocarcinoma (PC) or with a germline mutation in a PC susceptibility gene are at increased risk of developing PC. These high-risk individuals (HRIs) may benefit from PC surveillance.

METHODS

A PC surveillance program was developed to evaluate the detection of premalignant lesions and early-stage PCs using biannual imaging and to determine whether locally advanced or metastatic PCs develop despite biannual surveillance. From January 2013 to April 2020, asymptomatic HRIs were enrolled and followed with alternating MRI and endoscopic ultrasound every 6 months.

RESULTS

Of 75 HRIs, 43 (57.3%) had a germline mutation in a PC susceptibility gene and 32 (42.7%) had a familial pancreatic cancer (FPC) pedigree. Branch-duct intraductal papillary mucinous neoplasms (BD-IPMNs) were identified in 26 individuals (34.7%), but only 2 developed progressive lesions. One patient with Peutz-Jeghers syndrome (PJS) developed locally advanced PC arising from a BD-IPMN. Whole-genome sequencing of this patient's PC and of a second patient with PJS-associated PC from the same kindred revealed biallelic inactivation of STK11 in a KRAS-independent manner. A review of 3,853 patients from 2 PC registries identified an additional patient with PJS-associated PC. All 3 patients with PJS developed advanced PC consistent with the malignant transformation of an underlying BD-IPMN in <6 months. The other surveillance patient with a progressive lesion had FPC and underwent resection of a mixed-type IPMN that harbored polyclonal KRAS mutations.

CONCLUSIONS

PC surveillance identifies a high prevalence of BD-IPMNs in HRIs. Patients with PJS with BD-IPMNs may be at risk for accelerated malignant transformation.

Pancreatic cancer evolution and heterogeneity: integrating omics and clinical data

Pancreatic ductal adenocarcinoma (PDAC), already among the deadliest epithelial malignancies, is rising in both incidence and contribution to overall cancer deaths. Decades of research have improved our understanding of PDAC carcinogenesis, including characterizing germline predisposition, the cell of origin, precursor lesions, the sequence of genetic alterations, including simple and structural alterations, transcriptional changes and subtypes, tumour heterogeneity, metastatic progression and the tumour microenvironment. These fundamental advances inform contemporary translational efforts in primary prevention, screening and early detection, multidisciplinary management and survivorship, as prospective clinical trials begin to adopt molecular-based selection criteria to guide targeted therapies. Genomic and transcriptomic data on PDAC were also included in the international pan-cancer analysis of approximately 2,600 cancers, a milestone in cancer research that allows further insight through comparison with other tumour types. Thus, this is an ideal time to review our current knowledge of PDAC evolution and heterogeneity, gained from the study of preclinical models and patient biospecimens, and to propose a model of PDAC evolution that takes into consideration findings from varied sources, with a particular focus on the genomics of human PDAC.

Molecular Features and Clinical Management of Hereditary Pancreatic Cancer Syndromes and Familial Pancreatic Cancer

Hereditary pancreatic cancers are caused by several inherited genes. Familial pancreatic cancer is defined as pancreatic cancer arising in a patient with at least two first-degree relatives with pancreatic cancer in the absence of an identified genetic cause. Hereditary pancreatic cancer syndromes and familial pancreatic cancers account for about 10% of pancreatic cancer cases. Germline mutations in BRCA1, BRCA2, ATM, PALB2, CDKN2A, STK11, and TP53 and mismatch repair genes (MLH1, MSH2, MSH6, PMS2, and EPCAM) are among the well-known inherited susceptibility genes. Currently available targeted medications include poly (ADP-ribose) polymerase inhibitors (PARP) for cases with mutant BRCA and immune checkpoint inhibitors for cases with mismatch repair deficiency. Loss of heterozygosity of hereditary pancreatic cancer susceptibility genes such as BRCA1/2 plays a key role in carcinogenesis and sensitivity to PARP inhibitors. Signature 3 identified by whole genome sequencing is also associated with homologous recombination deficiency and sensitivity to targeted therapies. In this review, we summarize molecular features and treatments of hereditary pancreatic cancer syndromes and surveillance procedures for unaffected high-risk cases. We also review transgenic murine models to gain a better understanding of carcinogenesis in hereditary pancreatic cancer.

The unfolded protein response: An emerging therapeutic target for pancreatitis and pancreatic ductal adenocarcinoma

Pancreatitis is a debilitating disease involving inflammation and fibrosis of the exocrine pancreas. Recurrent or chronic forms of pancreatitis are a significant risk factor for pancreatic ductal adenocarcinoma. While genetic factors have been identified for both pathologies, environmental stresses play a large role in their etiology. All cells have adapted mechanisms to handle acute environmental stress that alters energy demands. A common pathway involved in the stress response involves endoplasmic reticulum stress and the unfolded protein response (UPR). While rapidly activated by many external stressors, in the pancreas the UPR plays a fundamental biological role, likely due to the high protein demands in acinar cells. Despite this, increased UPR activity is observed in response to acute injury or following exposure to risk factors associated with pancreatitis and pancreatic cancer. Studies in animal and cell cultures models show the importance of affecting the UPR in the context of both diseases, and inhibitors have been developed for several specific mediators of the UPR. Given the importance of the UPR to normal acinar cell function, efforts to affect the UPR in the context of disease must be able to specifically target pathology vs. physiology. In this review, we highlight the importance of the UPR to normal and pathological conditions of the exocrine pancreas. We discuss recent studies suggesting the UPR may be involved in the initiation and progression of pancreatitis and PDAC, as well as contributing to chemoresistance that occurs in pancreatic cancer. Finally, we discuss the potential of targeting the UPR for treatment.

A risk prediction tool for individuals with a family history of breast, ovarian, or pancreatic cancer: BRCAPANCPRO

INTRODUCTION

Identifying families with an underlying inherited cancer predisposition is a major goal of cancer prevention efforts. Mendelian risk models have been developed to better predict the risk associated with a pathogenic variant of developing breast/ovarian cancer (with BRCAPRO) and the risk of developing pancreatic cancer (PANCPRO). Given that pathogenic variants involving BRCA2 and BRCA1 predispose to all three of these cancers, we developed a joint risk model to capture shared susceptibility.

METHODS

We expanded the existing framework for PANCPRO and BRCAPRO to jointly model risk of pancreatic, breast, and ovarian cancer and validated this new model, BRCAPANCPRO on three data sets each reflecting the common target populations.

RESULTS

BRCAPANCPRO outperformed the prior BRCAPRO and PANCPRO models and yielded good discrimination for differentiating BRCA1 and BRCA2 carriers from non-carriers (AUCs 0.79, 95% CI: 0.73-0.84 and 0.70, 95% CI: 0.60-0.80) in families seen in high-risk clinics and pancreatic cancer family registries, respectively. In addition, BRCAPANCPRO was reasonably well calibrated for predicting future risk of pancreatic cancer (observed-to-expected (O/E) ratio = 0.81 [0.69, 0.94]).

DISCUSSION

The BRCAPANCPRO model provides improved risk assessment over our previous risk models, particularly for pedigrees with a co-occurrence of pancreatic cancer and breast and/or ovarian cancer.

Evaluation of biomarkers, genetic mutations, and epigenetic modifications in early diagnosis of pancreatic cancer

BACKGROUND

Pancreatic cancer (PC) is one of the deadliest malignancies with an alarming mortality rate. Despite significant advancement in diagnostics and therapeutics, early diagnosis remains elusive causing poor prognosis, marred by mutations and epigenetic modifications in key genes which contribute to disease progression.

AIM

To evaluate the various biological tumor markers collectively for early diagnosis which could act as prognostic biomarkers and helps in future therapeutics of PC in Kashmir valley.

METHODS

A total of 50 confirmed PC cases were included in the study to evaluate the levels of carbohydrate antigen 19-9 (CA 19-9), tissue polypeptide specific antigen (TPS), carcinoembryonic antigen (CEA), vascular endothelial growth factor-A (VEGF-A), and epidermal growth factor receptor (EGFR). Mutational analysis was performed to evaluate the mutations in Kirsten rat sarcoma (KRAS), Breast cancer type 2 (BRCA-2), and deleted in pancreatic cancer-4 (DPC-4) genes. However, epigenetic modifications (methylation of CpG islands) were performed in the promoter regions of cyclin-dependent kinase inhibitor 2A (p16; CDKN2A), MutL homolog 1 (hMLH1), and Ras association domain-containing protein 1(RASSF1A) genes.

RESULTS

We found significantly elevated levels of biological markers CA 19-9 (P ≤ 0.05), TPS (P ≤ 0.05), CEA (P ≤ 0.001), and VEGF (P ≤ 0.001). Molecular genetic analysis revealed that KRAS gene mutation is predominant in codon 12 (16 subjects, P ≤ 0.05), and 13 (12 subjects, P ≤ 0.05). However, we did not find a mutation in DPC-4 (1203G > T) and BRCA-2 (617delT) genes. Furthermore, epigenetic modification revealed that CpG methylation in 21 (P ≤ 0.05) and 4 subjects in the promoter regions of the p16 and hMLH1 gene, respectively.

CONCLUSION

In conclusion, CA 19-9, TPS, CEA, and VEGF levels were significantly elevated and collectively have potential as diagnostic and prognostic markers in PC. Global data of mutation in the KRAS gene commonly in codon 12 and rare in codon 13 could augment the predisposition towards PC. Additionally, methylation of the p16 gene could also modulate transcription of genes thereby increasing the predisposition and susceptibility towards PC.

Advances in the epidemiology of pancreatic cancer: Trends, risk factors, screening, and prognosis

Pancreatic cancer is a malignancy with poor prognosis and high mortality. The recent increase in pancreatic cancer incidence and mortality has resulted in an increased number of studies on its epidemiology. This comprehensive and systematic literature review summarizes the advances in the epidemiology of pancreatic cancer, including its epidemiological trends, risk factors, risk prediction models, screening modalities, and prognosis. The risk factors for pancreatic cancers can be categorized as those related to individual characteristics, lifestyle and environment, and disease status. Several prediction models for pancreatic cancer have been developed in populations with new-onset diabetes or a family history of pancreatic cancer; however, these models require further validation. Despite recent progress in pancreatic cancer screening, the quantity and quality of related studies are also unsatisfactory, especially with respect to the identification of high-risk populations and development of effective screening modality. Apart from the populations with familial genetic risk and those at a high risk of sporadic pancreatic cancer, risk factors such as new-onset diabetes may be a new direction for timely intervention. We hope this work will provide new ideas for further prevention and treatment of pancreatic cancer.

Utilization of breast cancer risk prediction models by cancer genetic counselors in clinical practice predominantly in the United States

Risk assessment in cancer genetic counseling is essential in identifying individuals at high risk for developing breast cancer to recommend appropriate screening and management options. Historically, many breast cancer risk prediction models were developed to calculate an individual's risk to develop breast cancer or to carry a pathogenic variant in the BRCA1 or BRCA2 genes. However, how or when genetic counselors use these models in clinical settings is currently unknown. We explored genetic counselors' breast cancer risk model usage patterns including frequency of use, reasons for using or not using models, and change in usage since the adoption of multi-gene panel testing. An online survey was developed and sent to members of the National Society of Genetic Counselors; board-certified genetic counselors whose practice included cancer genetic counseling were eligible to participate in the study. The response rate was estimated at 23% (243/1,058), and respondents were predominantly working in the United States. The results showed that 93% of all respondents use at least one breast cancer risk prediction model in their clinical practice. Among the six risk models selected for the study, the Tyrer-Cuzick (IBIS) model was used most frequently (95%), and the BOADICEA model was used least (40%). Determining increased or decreased surveillance and breast MRI eligibility were the two most common reasons for most model usage, while time consumption and difficulty in navigation were the two most common reasons for not using models. This study provides insight into perceived benefits and limitations of risk models in clinical use in the United States, which may be useful information for software developers, genetic counseling program curriculum developers, and currently practicing cancer genetic counselors.

Burden of Pancreatic Cancer: From Epidemiology to Practice

Pancreatic cancer is the seventh leading cause of cancer-related deaths worldwide with 432,242 related deaths in 2018. Unlike other cancers, the incidence of pancreatic cancer continues to increase, with little improvement in survival rates. We review the epidemiologic features of pancreatic cancer, covering surveillance and early detection in high-risk persons. We summarize data on worldwide incidence and mortality and analyze the 1975-2016 data from 9 registries of the National Cancer Institute's Surveillance, Epidemiology, and End Results study, on the overall burden of pancreatic cancer as well as age-, sex-, and race-specific incidence, survival rates and trends. It is important to increase our knowledge of the worldwide and regional epidemiologic features of and risk factors for pancreatic cancer, to identify new approaches for prevention, surveillance, and treatment.

Familial pancreatic cancer: who should be considered for genetic testing?

BACKGROUND

Determining how many female patients who underwent breast imaging meet the eligibility criteria for genetic testing for familial pancreatic cancer (FPC).

METHODS

A total of 42,904 patients seen at the Newton-Wellesley Hospital between 2007 and 2009 were retrospectively reviewed. The first four categories were based on pancreatic cancer-associated syndromes: (1) hereditary breast and ovarian cancer (HBOC), (2) Lynch syndrome (LS), (3) familial atypical multiple mole melanoma (FAMMM), and (4) family history of FPC (FH-FPC). PancPRO (5) and MelaPRO (6) categories were based on risk scores from Mendelian risk prediction tool.

RESULTS

Exactly 4445 of 42,904 patients were found to be in at least one of the six risk categories. About 5.7% of patients were classified as being at high risk for HBOC, 2.3% as being at high risk for LS, 0.1% as being at high risk for FAMMM, 0.1% as being at high risk for FH-FPC, 2.7% as being at high risk based on PancPRO, and 0.2% as being at high risk based on MelaPRO.

CONCLUSION

About 10.4% of the female patients were classified as being at high risk for FPC. This finding emphasizes the importance of applying criteria to the general population, in order to ensure that individuals with high risk are identified early.

Should This Patient Be Screened for Pancreatic Cancer? : Grand Rounds Discussion From Beth Israel Deaconess Medical Center

Because pancreatic cancer is typically advanced at the time of diagnosis, it has a very low 5-year survival rate and may become the second leading cause of cancer death in the United States. A screening program to find early-stage pancreatic cancer is needed but has been challenging to develop because of the lack of an effective screening test. In 2019, the U.S. Preventive Services Task Force performed an evidence review and updated its guidance, confirming its 2004 "D" recommendation against routine screening for average-risk patients. Here, 2 experts review the updated guideline and recent evidence and discuss whether a patient with a family history of pancreatic cancer should undergo screening.

The genetics of ductal adenocarcinoma of the pancreas in the year 2020: dramatic progress, but far to go

The publication of the "Pan-Cancer Atlas" by the Pan-Cancer Analysis of Whole Genomes Consortium, a partnership formed by The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC), provides a wonderful opportunity to reflect on where we stand in our understanding of the genetics of pancreatic cancer, as well as on the opportunities to translate this understanding to patient care. From germline variants that predispose to the development of pancreatic cancer, to somatic mutations that are therapeutically targetable, genetics is now providing hope, where there once was no hope, for those diagnosed with pancreatic cancer.

A likelihood-based approach to assessing frequency of pathogenicity among variants of unknown significance in susceptibility genes

Commercialized multigene panel testing brings unprecedented opportunities to understand germline genetic contributions to hereditary cancers. Most genetic testing companies classify the pathogenicity of variants as pathogenic, benign, or variants of unknown significance (VUSs). The unknown pathogenicity of VUSs poses serious challenges to clinical decision-making. This study aims to assess the frequency of VUSs that are likely pathogenic in disease-susceptibility genes. Using estimates of probands' probability of having a pathogenic mutation (ie, the carrier score) based on a family history probabilistic risk prediction model, we assume the carrier score distribution for probands with VUSs is a mixture of the carrier score distribution for probands with positive results and the carrier score distribution for probands with negative results. Under this mixture model, we propose a likelihood-based approach to assess the frequency of pathogenicity among probands with VUSs, while accounting for the existence of possible pathogenic mutations on genes not tested. We conducted simulations to assess the performance of the approach and show that under various settings, the approach performs well with very little bias in the estimated proportion of VUSs that are likely pathogenic. We also estimate the positive predictive value across the entire range of carrier scores. We apply our approach to the USC-Stanford Hereditary Cancer Panel Testing cohort, and estimate the proportion of probands that have VUSs in BRCA1/2 that are likely pathogenic to be 10.12% [95%CI: 0%, 43.04%]. This approach will enable clinicians to target high-risk patients who have VUSs, allowing for early prevention interventions.

Italian registry of families at risk of pancreatic cancer: AISP Familial Pancreatic Cancer Study Group

Pancreatic cancer is one of the main causes of cancer-related death worldwide, with a survival rate around 9%. In Italy 13,500 new cases of pancreatic cancer occurred in 2019. It is estimated that at least 5% have a hereditary background. Surveillance is advisable for healthy individuals with specific genetic syndromes with or without family history of pancreatic cancer or members of families with multiple cases of pancreatic cancer, irrespective of genetic syndromes. In 2010 the Italian Association for the Study of the Pancreas (AISP) defined criteria to include individuals in such surveillance programs with the first-round results published in 2019. In order to include other categories at high-risk and increase the diagnostic yield of surveillance, these criteria have recently been modified. The present position paper presents the updated criteria of the Italian Registry of Families at Risk of Pancreatic Cancer (IRFARPC) with their diagnostic yield calculation. Also, AISP priority projects concerning: (a) increasing awareness of citizens and primary care physicians through a dedicated App; (b) increasing access to germline testing to personalize surveillance; (c) measuring psychological impact of surveillance; (d) investigating the role of risk-modifiers and (e) evaluating the cost-effectiveness and ability to save lives of the program are briefly presented.

A pedigree-based prediction model identifies carriers of deleterious de novo mutations in families with Li-Fraumeni syndrome

De novo mutations (DNMs) are increasingly recognized as rare disease causal factors. Identifying DNM carriers will allow researchers to study the likely distinct molecular mechanisms of DNMs. We developed Famdenovo to predict DNM status (DNM or familial mutation [FM]) of deleterious autosomal dominant germline mutations for any syndrome. We introduce Famdenovo.TP53 for Li-Fraumeni syndrome (LFS) and analyze 324 LFS family pedigrees from four US cohorts: a validation set of 186 pedigrees and a discovery set of 138 pedigrees. The concordance index for Famdenovo.TP53 prediction was 0.95 (95% CI: [0.92, 0.98]). Forty individuals (95% CI: [30, 50]) were predicted as DNM carriers, increasing the total number from 42 to 82. We compared clinical and biological features of FM versus DNM carriers: (1) cancer and mutation spectra along with parental ages were similarly distributed; (2) ascertainment criteria like early-onset breast cancer (age 20-35 yr) provides a condition for an unbiased estimate of the DNM rate: 48% (23 DNMs vs. 25 FMs); and (3) hotspot mutation R248W was not observed in DNMs, although it was as prevalent as hotspot mutation R248Q in FMs. Furthermore, we introduce Famdenovo.BRCA for hereditary breast and ovarian cancer syndrome and apply it to a small set of family data from the Cancer Genetics Network. In summary, we introduce a novel statistical approach to systematically evaluate deleterious DNMs in inherited cancer syndromes. Our approach may serve as a foundation for future studies evaluating how new deleterious mutations can be established in the germline, such as those in TP53.

Familial Pancreatic Cancer: Current Perspectives

Pancreatic cancer (PC) is a highly lethal disease, mostly incurable when detected. Thus, despite advances in PC treatments, only around 7% of patients survive 5-years after diagnosis. This morbid outcome is secondary to multifactorial reasons, such as late-stage diagnosis, rapid progression and minimal response to chemotherapy. Based on these factors, it is of special relevance to identify PC high-risk individuals in order to establish preventive and early detection measures. Although most PC are sporadic, approximately 10% cases have a familial basis. No main causative gene of PC has been identified but several known germline pathogenic mutations are related with an increased risk of this tumor. These inherited cancer syndromes represent 3% of all PC. On the other hand, in 7% of cases of PC, there is a strong family history without a causative germline mutation, a situation known as familial pancreatic cancer (FPC). In recent years, there is increasing evidence supporting the benefit of genetic germline analysis in PC patients, and periodic pancreatic screening in PC high-risk patients (mainly those with a lifetime risk greater than 5%), although there is no general agreement in the group of patients and individuals to study and screen. In the present review, we expose an update in the field of hereditary and FPC, with the aim of describing the current strategies and implications in genetic counseling, surveillance and therapeutic interventions.

Current epidemiology of pancreatic cancer: Challenges and opportunities

Pancreatic cancer (PC) is an increasingly common disease worldwide. Having a better understanding of worldwide and regional epidemiologic features and risk factors of PC is essential to identify new approaches for prevention, early diagnosis, surveillance, and treatment. In this article, we review the epidemiologic features and risk factors for PC and discuss opportunities and challenges of PC future treatment.

Development of PancRISK, a urine biomarker-based risk score for stratified screening of pancreatic cancer patients

Background

An accurate and simple risk prediction model that would facilitate earlier detection of pancreatic adenocarcinoma (PDAC) is not available at present. In this study, we compare different algorithms of risk prediction in order to select the best one for constructing a biomarker-based risk score, PancRISK.

Methods

Three hundred and seventy-nine patients with available measurements of three urine biomarkers, (LYVE1, REG1B and TFF1) using retrospectively collected samples, as well as creatinine and age, were randomly split into training and validation sets, following stratification into cases (PDAC) and controls (healthy patients). Several machine learning algorithms were used, and their performance characteristics were compared. The latter included AUC (area under ROC curve) and sensitivity at clinically relevant specificity.

Results

None of the algorithms significantly outperformed all others. A logistic regression model, the easiest to interpret, was incorporated into a PancRISK score and subsequently evaluated on the whole data set. The PancRISK performance could be even further improved when CA19-9, commonly used PDAC biomarker, is added to the model.

Conclusion

PancRISK score enables easy interpretation of the biomarker panel data and is currently being tested to confirm that it can be used for stratification of patients at risk of developing pancreatic cancer completely non-invasively, using urine samples.

Genetic counselling and personalised risk assessment in the Australian pancreatic cancer screening program

Background

Pancreatic cancer (PC) is an aggressive disease with a dismal 5-year survival rate. Surveillance of high-risk individuals is hoped to improve survival outcomes by detection of precursor lesions or early-stage malignancy.

Methods

Since 2011, a national high-risk cohort recruited through St Vincent’s Hospital, Sydney, has undergone prospective PC screening incorporating annual endoscopic ultrasound, formal genetic counselling and mutation analysis as appropriate. PancPRO, a Bayesian PC risk assessment model, was used to estimate 5-year and lifetime PC risks for familial pancreatic cancer (FPC) participants and this was compared to their perceived chance of pancreatic and other cancers. Genetic counselling guidelines were developed to improve consistency. Follow-up questionnaires were used to assess the role of genetic counselling and testing.

Results

We describe the Australian PC screening program design and recruitment strategy and the results of the first 102 individuals who have completed at least one-year of follow-up. Seventy-nine participants met the FPC criteria (≥ two first-degree relatives affected), 22 individuals had both a BRCA2 pathogenic variant and a close relative with PC and one had a clinical diagnosis of Peutz-Jeghers syndrome. Participants reported a high perceived chance of developing PC regardless of their genetic testing status. PancPRO reported FPC participants’ mean 5-year and lifetime PC risks as 1.81% (range 0.2–3.2%) and 10.17% (range 2.4–14.4%), respectively. Participants’ perceived PC chance did not correlate with their PancPRO 5-year (r = − 0.17, p = 0.128) and lifetime PC risks (r = 0.19, p = 0.091). Two-thirds felt that current genetic testing would help them, and 91% of tested participants were glad to have undergone genetic testing. Overall, 79% of participants found genetic counselling to be helpful, and 88% reported they would recommend counselling to their relatives.

Conclusions

Participants reported multiple benefits of genetic counselling and testing but continue to seek greater clarification about their individual PC risk. Extension of PancPRO is required to enable personalised PC risk assessment for all high-risk sub-groups. More detailed discussion of PC risk for BRCA2 pathogenic variant carriers, providing a written summary in all cases and a plan for genetics review were identified as areas for improvement.

PPCD: Privacy-preserving clinical decision with cloud support

With the prosperity of machine learning and cloud computing, meaningful information can be mined from mass electronic medical data which help physicians make proper disease diagnosis for patients. However, using medical data and disease information of patients frequently raise privacy concerns. In this paper, based on single-layer perceptron, we propose a scheme of privacy-preserving clinical decision with cloud support (PPCD), which securely conducts disease model training and prediction for the patient. Each party learns nothing about the other's private information. In PPCD, a lightweight secure multiplication is presented and introduced to improve the model training. Security analysis and experimental results on real data confirm the high accuracy of disease prediction achieved by the proposed PPCD without the risk of privacy disclosure.

Pancreatic Cancer Prediction Through an Artificial Neural Network

Early detection of pancreatic cancer is challenging because cancer-specific symptoms occur only at an advanced stage, and a reliable screening tool to identify high-risk patients is lacking. To address this challenge, an artificial neural network (ANN) was developed, trained, and tested using the health data of 800,114 respondents captured in the National Health Interview Survey (NHIS) and Pancreatic, Lung, Colorectal, and Ovarian cancer (PLCO) datasets, together containing 898 patients diagnosed with pancreatic cancer. Prediction of pancreatic cancer risk was assessed at an individual level by incorporating 18 features into the neural network. The established ANN model achieved a sensitivity of 87.3 and 80.7%, a specificity of 80.8 and 80.7%, and an area under the receiver operating characteristic curve of 0.86 and 0.85 for the training and testing cohorts, respectively. These results indicate that our ANN can be used to predict pancreatic cancer risk with high discriminatory power and may provide a novel approach to identify patients at higher risk for pancreatic cancer who may benefit from more tailored screening and intervention.

A Review of Pancreatic Cancer: Epidemiology, Genetics, Screening, and Management

Pancreatic cancer ranks among the causes of cancer-related deaths. The average size of pancreatic cancer during diagnosis is about 31 mm and has not changed significantly over the past 30 years. Poor early diagnosis of a tumour has been attributed to the late-presenting symptoms. Over the years, improvement in the diagnosis of pancreatic cancer has been observed, and this can be linked to advancement in imaging techniques as well as the increasing knowledge of cancer history and genetics. Magnetic Resonance Imaging, Endoscopic Ultrasound, and Computer Topography are the approved imaging modalities utilised in the diagnosing of pancreatic cancer. Over the years, the management of patients with pancreatic cancer has seen remarkable improvement as reliable techniques can now be harnessed and implemented in determining the resectability of cancer. However, only about 10% of pancreatic adenocarcinomas are resectable at the time of diagnosis and will highly benefit from a microscopic margin-negative surgical resection. Overall, the failure of early tumour identification will result in considerable morbidity and mortality.

A review of lifestyle, metabolic risk factors, and blood-based biomarkers for early diagnosis of pancreatic ductal adenocarcinoma

We aimed to review the epidemiologic literature examining lifestyle and metabolic risk factors, and blood-based biomarkers including multi-omics (genomics, proteomics, and metabolomics) and to discuss how these predictive markers can inform early diagnosis of pancreatic ductal adenocarcinoma (PDAC). A search of the PubMed database was conducted in June 2018 to review epidemiologic studies of (i) lifestyle and metabolic risk factors for PDAC, genome-wide association studies, and risk prediction models incorporating these factors and (ii) blood-based biomarkers for PDAC (conventional diagnostic markers, metabolomics, and proteomics). Prospective cohort studies have reported at least 20 possible risk factors for PDAC, including smoking, heavy alcohol drinking, adiposity, diabetes, and pancreatitis, but the relative risks and population attributable fractions of individual risk factors are small (mostly < 10%). High-throughput technologies have continued to yield promising genetic, metabolic, and protein biomarkers in addition to conventional biomarkers such as carbohydrate antigen 19-9. Nonetheless, most studies have utilized a hospital-based case-control design, and the diagnostic accuracy is low in studies that collected pre-diagnostic samples. Risk prediction models incorporating lifestyle and metabolic factors as well as other clinical parameters have shown good discrimination and calibration. Combination of traditional risk factors, genomics, and blood-based biomarkers can help identify high-risk populations and inform clinical decisions. Multi-omics investigations can provide valuable insights into disease etiology, but prospective cohort studies that collect pre-diagnostic samples and validation in independent studies are warranted.

Genomic Features and Clinical Management of Patients with Hereditary Pancreatic Cancer Syndromes and Familial Pancreatic Cancer

Pancreatic cancer (PC) is one of the most devastating malignancies; it has a 5-year survival rate of only 9%, and novel treatment strategies are urgently needed. While most PC cases occur sporadically, PC associated with hereditary syndromes or familial PC (FPC; defined as an individual having two or more first-degree relatives diagnosed with PC) accounts for about 10% of cases. Hereditary cancer syndromes associated with increased risk for PC include Peutz-Jeghers syndrome, hereditary pancreatitis, familial atypical multiple mole melanoma, familial adenomatous polyposis, Lynch syndrome and hereditary breast and ovarian cancer syndrome. Next-generation sequencing of FPC patients has uncovered new susceptibility genes such as PALB2 and ATM, which participate in homologous recombination repair, and further investigations are in progress. Previous studies have demonstrated that some sporadic cases that do not fulfil FPC criteria also harbor similar mutations, and so genomic testing based on family history might overlook some susceptibility gene carriers. There are no established screening procedures for high-risk unaffected cases, and it is not clear whether surveillance programs would have clinical benefits. In terms of treatment, poly (ADP-ribose) polymerase inhibitors for BRCA-mutated cases or immune checkpoint inhibitors for mismatch repair deficient cases are promising, and clinical trials of these agents are underway.

Development of a high risk pancreatic screening clinic using 3.0 T MRI

Selective screening for pancreatic cancer (PC) has been proposed. We describe the establishment of a comprehensive multidisciplinary screening program using 3.0 T MRI. Criteria for screening included the presence of PC in: ≥ 2 first degree relatives (FDR), 1 FDR and 1 s degree relative (SDR), ≥ 3 any degree relatives (ADR), or any known hereditary cancer syndrome with increased PC risk. Imaging with 3.0 T MRI was performed routinely and endoscopic ultrasound was used selectively. Screening was completed in 75 patients (pts). Hereditary cancer syndromes were present in 42 (56%) of the 75 pts: BRCA2 (18), ATM (8), BRCA1 (6), CDKN2A (4), PALB2 (3), Lynch (2), and Peutz-Jeghers (1). A family history of PC was present in ≥ 2 FDR in 12 (16%) pts, 1 FDR and 1 SDR in 5 (7) pts, and ≥ 3 ADR in 16 (21%) pts. Of the 65 pts who received screening MRI, 28 (43%) pts had pancreatic cystic lesions identified, including 1 (1%) patient in whom a cholangiocarcinoma was diagnosed as well. No patient underwent surgical resection. Using a 3.0 T MRI to screen patients at high risk for developing PC identified radiographic abnormalities in 43% of patients, which were stable on subsequent surveillance. Specific guidelines for the frequency of surveillance and indications for surgery remain areas of active investigation as the global experience with high risk screening continues to mature.

Identification of Cystic Lesions by Secondary Screening of Familial Pancreatic Cancer (FPC) Kindreds Is Not Associated with the Stratified Risk of Cancer

OBJECTIVES

Intraductal papillary mucinous neoplasms (IPMNs) are associated with risk of pancreatic ductal adenocarcinoma (PDAC). It is unclear if an IPMN in individuals at high risk of PDAC should be considered as a positive screening result or as an incidental finding. Stratified familial pancreatic cancer (FPC) populations were used to determine if IPMN risk is linked to familial risk of PDAC.

METHODS

This is a cohort study of 321 individuals from 258 kindreds suspected of being FPC and undergoing secondary screening for PDAC through the European Registry of Hereditary Pancreatitis and Familial Pancreatic Cancer (EUROPAC). Computerised tomography, endoscopic ultrasound of the pancreas and magnetic resonance imaging were used. The risk of being a carrier of a dominant mutation predisposing to pancreatic cancer was stratified into three even categories (low, medium and high) based on: Mendelian probability, the number of PDAC cases and the number of people at risk in a kindred.

RESULTS

There was a median (interquartile range (IQR)) follow-up of 2 (0-5) years and a median (IQR) number of investigations per participant of 4 (2-6). One PDAC, two low-grade neuroendocrine tumours and 41 cystic lesions were identified, including 23 IPMN (22 branch-duct (BD)). The PDAC case occurred in the top 10% of risk, and the BD-IPMN cases were evenly distributed amongst risk categories: low (6/107), medium (10/107) and high (6/107) (P = 0.63).

CONCLUSIONS

The risk of finding BD-IPMN was independent of genetic predisposition and so they should be managed according to guidelines for incidental finding of IPMN.

Diagnostic Yield From Screening Asymptomatic Individuals at High Risk for Pancreatic Cancer: A Meta-analysis of Cohort Studies

BACKGROUND & AIMS

There have been few studies of abdominal imaging screening of individuals at high risk for pancreatic cancer (based on family history or genetic variants). We performed a meta-analysis of prospective cohort studies to determine the diagnostic yield and outcomes of abdominal imaging screening for asymptomatic individuals at high risk.

METHODS

Through a systematic review of multiple electronic databases and conference proceedings through July 2017, we identified prospective cohort studies (>20 patients) of asymptomatic adults determined to be at high-risk of pancreatic cancer (lifetime risk >5%, including specific genetic-associated conditions) who were screened by endoscopic ultrasound (EUS) and/or magnetic resonance imaging (MRI) to detect pancreatic lesions. Our primary outcome was identification of high-risk pancreatic lesions (high-grade pancreatic intraepithelial neoplasia, high-grade dysplasia, or adenocarcinoma) at initial screening, and overall incidence during follow up. Summary estimates were reported as incidence rates per 100 patient-years.

RESULTS

We identified 19 studies comprising 7085 individuals at high risk for pancreatic cancer; of these, 1660 patients were evaluated by EUS and/or MRI. Fifty-nine high-risk lesions were identified (43 adenocarcinomas: 28 during the initial exam and 15 during follow-up surveillance) and 257 patients underwent pancreatic surgery. Based on our meta-analysis, the overall diagnostic yield screening for high-risk pancreatic lesions was 0.74 (95% CI, 0.33-1.14), with moderate heterogeneity among studies. The number needed to screen to identify 1 patient with a high-risk lesion was 135 (95% CI, 88-303). The diagnostic yield was similar for patients with different genetic features that increased risk, and whether patients were screened by EUS or MRI.

CONCLUSIONS

Based on meta-analysis, 135 patients at high-risk for pancreatic cancer must be screened to identify 1 patient with a high-risk pancreatic lesion. Further studies are needed to determine whether screening reduces mortality and is cost effectiveness for individuals at high-risk of pancreatic cancer.

New Developments in the Molecular Mechanisms of Pancreatic Tumorigenesis

Pancreatic cancer is an aggressive disease with a dismal prognosis in dire need of novel diagnostic and therapeutic approaches. The past decade has witnessed an explosion of data on the genetic alterations that occur in pancreatic cancer, as comprehensive next-generation sequencing analyses have been performed on samples from large cohorts of patients. These studies have defined the genomic landscape of this disease and identified novel candidates whose mutations contribute to pancreatic tumorigenesis. They have also clarified the genetic alterations that underlie multistep tumorigenesis in precursor lesions and provided insights into clonal evolution in pancreatic neoplasia. In addition to these important insights into pancreatic cancer biology, these large scale genomic studies have also provided a foundation for the development of novel early detection strategies and targeted therapies. In this review, we discuss the results of these comprehensive sequencing studies of pancreatic neoplasms, with a particular focus on how their results will impact the clinical care of patients with pancreatic cancer.

Utility of Endoscopic Ultrasonography Screening for Small Pancreatic Cancer and Proposal for a New Scoring System for Screening

OBJECTIVES

This study aimed to evaluate the utility of endoscopic ultrasonography screening for small pancreatic cancer (PC) and propose a new simple scoring system for selecting individuals who should be screened.

METHODS

Risk factors or symptoms related to PC were tentatively divided into high- and low-grade risk groups based mainly on reported relative risk values. Numbers of risk factors were designated as risk scores. Endoscopic ultrasonography screening was performed for 632 individuals. We analyzed scores for PC detection prospectively, and risk factors and scores of PC patients retrospectively.

RESULTS

We detected 10 small malignant pancreatic neoplasms (size ≤20 mm; 8 PCs; 9 Tis or T1) and 14 advanced PCs. All small PCs and 95.5% of PCs were found in individuals with low-grade risk scores of at least 3 points (P) or high-grade risk scores of at least 1P. Both average risk scores were significantly higher in patients with small PCs (P ≤ 0.04). Cutoffs for low- and high-grade risk scores implying the presence of small PC and all PC were 3P and 1P, respectively. When subjects having one or both cutoff scores were screened, sensitivity and specificity were 100% and 64.4% for small PCs and 95.5% and 64.4% for all PCs.

CONCLUSION

Endoscopic ultrasonography screening combining new scoring is effective for detecting small PC.

Pancreatic Cancer Diagnosis and Management: Has the Time Come to Prick the Bubble?

Pancreatic cancer (PC) is associated with poor prognosis and very dismal survival rates. The most effective possibility of cure is tumor resection, which is only possible in about 15% of patients diagnosed at early stages of disease progression. Recent whole-genome sequencing studies pointed genetic alterations in 12 core signaling pathways in PC. These observations hint at the possibility that the initial mutation in PC might appear nearly 20 years before any symptoms occur, suggesting that a large window of opportunity may exist for early detection. Biomarkers with the potential to identify pre-neoplastic disease or very early stages of cancer are of great promise to improve patient survival. The concept of liquid biopsy refers to a minimally invasive sampling and analysis of liquid biomarkers that can be isolated from body fluids, primarily blood, urine and saliva. A myriad of circulating molecules may be useful as tumor markers, including cell-free DNA (cfDNA), cell-free RNA (cfRNA), circulating tumor cells (CTC), circulating tumor proteins, and extracellular vesicles, more specifically exosomes. In this review, we discuss with more detail the potential role of exosomes in several aspects related to PC, from initiation to tumor progression and its applicability in early detection and treatment. Exosomes are small circulating extracellular vesicles of 50-150 nm in diameter released from the plasma membrane by almost all cells and exhibit some advantages over other biomarkers. Exosomes are central players of intercellular communication and they have been implicated in a series of biological process, including tumorigenesis, migration and metastasis. Several exosomal microRNAs and proteins have been observed to distinguish PC from benign pancreatic diseases and healthy controls. Besides their possible role in diagnosis, understanding exosomes functions in cancer has clarified the importance of microenvironment in PC progression as well as its influence in proliferation, metastasis and resistance to chemotherapy. Increasing knowledge on cancer exosomes provides valuable insights on new therapeutic targets and can potentially open new strategies to treat this disease. Continuous research is needed to ascertain the reliability of using exosomes and their content as potential biomarkers, so that, hopefully, in the near future, they will provide the opportunity for early diagnosis, treatment intervention and increase survival of PC patients.