Pancreatic cancer epidemiology: understanding the role of lifestyle and inherited risk factors

Bartoli M., Barat M., Dohan A., Gaujoux S., Coriat R., Hoeffel C., Cassinotto C., Chassagnon G., Soyer P.

Radiomics is a relatively new approach for image analysis. As a part of radiomics, texture analysis, which consists in extracting a great amount of quantitative data from original images, can be used to identify specific features that can help determining the actual nature of a pancreatic lesion and providing other information such as resectability, tumor grade, tumor response to neoadjuvant therapy or survival after surgery. In this review, the basic of radiomics, recent developments and the results of texture analysis using computed tomography and magnetic resonance imaging in the field of pancreatic tumors are presented. Future applications of radiomics, such as artificial intelligence, are discussed.

Yuan C., Babic A., Khalaf N., Nowak J.A., Brais L.K., Rubinson D.A., Ng K., Aguirre A.J., Pandharipande P.V., Fuchs C.S., Giovannucci E.L., Stampfer M.J., Rosenthal M.H., Sander C., Kraft P., et. al.

Importance Pancreatic cancer is the third-leading cause of cancer death in the United States; however, few high-risk groups have been identified to facilitate early diagnosis strategies. Objective To evaluate the association of diabetes duration and recent weight change with subsequent risk of pancreatic cancer in the general population. Design, Setting, and Participants This cohort study obtained data from female participants in the Nurses’ Health Study and male participants in the Health Professionals Follow-Up Study, with repeated exposure assessments over 30 years. Incident cases of pancreatic cancer were identified from self-report or during follow-up of participant deaths. Deaths were ascertained through reports from the next of kin, the US Postal Service, or the National Death Index. Data collection was conducted from October 1, 2018, to December 31, 2018. Data analysis was performed from January 1, 2019, to June 30, 2019. Exposures Duration of physician-diagnosed diabetes and recent weight change. Main Outcome and Measures Hazard ratios (HRs) for subsequent development of pancreatic cancer. Results Of the 112 818 women (with a mean [SD] age of 59.4 [11.7] years) and 46 207 men (with a mean [SD] age of 64.7 [10.8] years) included in the analysis, 1116 incident cases of pancreatic cancers were identified. Compared with participants with no diabetes, those with recent-onset diabetes had an age-adjusted HR for pancreatic cancer of 2.97 (95% CI, 2.31-3.82) and those with long-standing diabetes had an age-adjusted HR of 2.16 (95% CI, 1.78-2.60). Compared with those with no weight loss, participants who reported a 1- to 4-lb weight loss had an age-adjusted HR for pancreatic cancer of 1.25 (95% CI, 1.03-1.52), those with a 5- to 8-lb weight loss had an age-adjusted HR of 1.33 (95% CI, 1.06-1.66), and those with more than an 8-lb weight loss had an age-adjusted HR of 1.92 (95% CI, 1.58-2.32). Participants with recent-onset diabetes accompanied by weight loss of 1 to 8 lb (91 incident cases per 100 000 person-years [95% CI, 55-151]; HR, 3.61 [95% CI, 2.14-6.10]) or more than 8 lb (164 incident cases per 100 000 person-years [95% CI, 114-238]; HR, 6.75 [95% CI, 4.55-10.00]) had a substantially increased risk for pancreatic cancer compared with those with neither exposure (16 incident cases per 100 000 person-years; 95% CI, 14-17). Incidence rates were even higher among participants with recent-onset diabetes and weight loss with a body mass index of less than 25 before weight loss (400 incident cases per 100 000 person-years) or whose weight loss was not intentional judging from increased physical activity or healthier dietary choices (334 incident cases per 100 000 person-years). Conclusions and Relevance This study demonstrates that recent-onset diabetes accompanied by weight loss is associated with a substantially increased risk for developing pancreatic cancer. Older age, previous healthy weight, and no intentional weight loss further elevate this risk.

Lin Y., Nakatochi M., Hosono Y., Ito H., Kamatani Y., Inoko A., Sakamoto H., Kinoshita F., Kobayashi Y., Ishii H., Ozaka M., Sasaki T., Matsuyama M., Sasahira N., Morimoto M., et. al.

Pancreatic cancer is the fourth leading cause of cancer-related deaths in Japan. To identify risk loci, we perform a meta-analysis of three genome-wide association studies comprising 2,039 pancreatic cancer patients and 32,592 controls in the Japanese population. Here, we identify 3 (13q12.2, 13q22.1, and 16p12.3) genome-wide significant loci (P < 5.0 × 10−8), of which 16p12.3 has not been reported in the Western population. The lead single nucleotide polymorphism (SNP) at 16p12.3 is rs78193826 (odds ratio = 1.46, 95% confidence interval = 1.29-1.66, P = 4.28 × 10−9), an Asian-specific, nonsynonymous glycoprotein 2 (GP2) gene variant. Associations between selected GP2 gene variants and pancreatic cancer are replicated in 10,822 additional cases and controls of East Asian origin. Functional analyses using cell lines provide supporting evidence of the effect of rs78193826 on KRAS activity. These findings suggest that GP2 gene variants are probably associated with pancreatic cancer susceptibility in populations of East Asian ancestry. Previous genome-wide association studies have identified risk loci for pancreatic cancer but were centered on individuals of European ancestry. Here the authors identify GP2 gene variants associated with pancreatic cancer susceptibility in populations of East Asian ancestry.

Zhong J., Jermusyk A., Wu L., Hoskins J.W., Collins I., Mocci E., Zhang M., Song L., Chung C.C., Zhang T., Xiao W., Albanes D., Andreotti G., Arslan A.A., Babic A., et. al.

Abstract Background Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. Methods To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74–421 samples). Results We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate &lt; .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. Conclusions By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.

Blackford A.L., Canto M.I., Klein A.P., Hruban R.H., Goggins M.

Abstract Background Rapid access to pancreatic imaging and regular pancreatic surveillance may help identify stage I pancreatic cancer. We investigated recent trends in the stage of newly diagnosed pancreatic ductal adenocarcinoma (PDACs), age at diagnosis, and survival. Methods Trends in age-adjusted incidence of stage IA PDAC between 2004 and 2016 were determined from the National Cancer Institute’s Surveillance, Epidemiology and End Results database. All tests were two-sided. Results The incidence of stage IA PDAC cases diagnosed increased statistically significantly from 2004 to 2016 (annual percent change = 14.5, 95% confidence interval [CI] = 11.4 to 17.7; P &lt; .001). During the study period, average age at diagnosis for stage IA and IB casesAQ3 declined by 3.5 years (95% CI = 1.2 to 5.9; P = .004) and 5.5 years (95% CI = 3.4 to 7.6; P &lt; .001), whereas average age increased for higher-stage cases (by 0.6 to 1.4 years). Among stage IA cases, the proportion of blacks was smaller (10.2% vs 12.5%), and the proportion of other non-Caucasians was higher compared with higher-stage cases (11.9% vs 8.4%; P &lt; .001). Stage IA cases were more likely to carry insurance (vs Medicaid or none) than higher-stage cases (cases aged younger than 65 years; odds ratio = 2.45, 95% CI = 1.96 to 3.06; P &lt; .001). The 5-year overall survival for stage IA PDAC improved from 44.7% (95% CI = 31.4 to 63.7) in 2004 to 83.7% (95% CI = 78.6% to 89.2%) in 2012; 10-year survival improved from 36.7% (95% CI = 24.1 to 55.8) in 2004 to 49.0% (95% CI = 37.2% to 64.6%) in 2007. Conclusions In recent years, the proportion of patients diagnosed with stage IA PDAC has increased, their average age at diagnosis has decreased, and their overall survival has improved. These trends may be the result of improved early diagnosis and early detection.

Siegel R.L., Miller K.D., Jemal A.

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2016) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2017) were collected by the National Center for Health Statistics. In 2020, 1,806,590 new cancer cases and 606,520 cancer deaths are projected to occur in the United States. The cancer death rate rose until 1991, then fell continuously through 2017, resulting in an overall decline of 29% that translates into an estimated 2.9 million fewer cancer deaths than would have occurred if peak rates had persisted. This progress is driven by long-term declines in death rates for the 4 leading cancers (lung, colorectal, breast, prostate); however, over the past decade (2008-2017), reductions slowed for female breast and colorectal cancers, and halted for prostate cancer. In contrast, declines accelerated for lung cancer, from 3% annually during 2008 through 2013 to 5% during 2013 through 2017 in men and from 2% to almost 4% in women, spurring the largest ever single-year drop in overall cancer mortality of 2.2% from 2016 to 2017. Yet lung cancer still caused more deaths in 2017 than breast, prostate, colorectal, and brain cancers combined. Recent mortality declines were also dramatic for melanoma of the skin in the wake of US Food and Drug Administration approval of new therapies for metastatic disease, escalating to 7% annually during 2013 through 2017 from 1% during 2006 through 2010 in men and women aged 50 to 64 years and from 2% to 3% in those aged 20 to 49 years; annual declines of 5% to 6% in individuals aged 65 years and older are particularly striking because rates in this age group were increasing prior to 2013. It is also notable that long-term rapid increases in liver cancer mortality have attenuated in women and stabilized in men. In summary, slowing momentum for some cancers amenable to early detection is juxtaposed with notable gains for other common cancers.

Pourshams A., Sepanlou S.G., Ikuta K.S., Bisignano C., Safiri S., Roshandel G., Sharif M., Khatibian M., Fitzmaurice C., Nixon M.R., Abbasi N., Afarideh M., Ahmadian E., Akinyemiju T., Alahdab F., et. al.

Worldwide, both the incidence and death rates of pancreatic cancer are increasing. Evaluation of pancreatic cancer burden and its global, regional, and national patterns is crucial to policy making and better resource allocation for controlling pancreatic cancer risk factors, developing early detection methods, and providing faster and more effective treatments.Vital registration, vital registration sample, and cancer registry data were used to generate mortality, incidence, and disability-adjusted life-years (DALYs) estimates. We used the comparative risk assessment framework to estimate the proportion of deaths attributable to risk factors for pancreatic cancer: smoking, high fasting plasma glucose, and high body-mass index. All of the estimates were reported as counts and age-standardised rates per 100 000 person-years. 95% uncertainty intervals (UIs) were reported for all estimates.In 2017, there were 448 000 (95% UI 439 000-456 000) incident cases of pancreatic cancer globally, of which 232 000 (210 000-221 000; 51·9%) were in males. The age-standardised incidence rate was 5·0 (4·9-5·1) per 100 000 person-years in 1990 and increased to 5·7 (5·6-5·8) per 100 000 person-years in 2017. There was a 2·3 times increase in number of deaths for both sexes from 196 000 (193 000-200 000) in 1990 to 441 000 (433 000-449 000) in 2017. There was a 2·1 times increase in DALYs due to pancreatic cancer, increasing from 4·4 million (4·3-4·5) in 1990 to 9·1 million (8·9-9·3) in 2017. The age-standardised death rate of pancreatic cancer was highest in the high-income super-region across all years from 1990 to 2017. In 2017, the highest age-standardised death rates were observed in Greenland (17·4 [15·8-19·0] per 100 000 person-years) and Uruguay (12·1 [10·9-13·5] per 100 000 person-years). These countries also had the highest age-standardised death rates in 1990. Bangladesh (1·9 [1·5-2·3] per 100 000 person-years) had the lowest rate in 2017, and São Tomé and Príncipe (1·3 [1·1-1·5] per 100 000 person-years) had the lowest rate in 1990. The numbers of incident cases and deaths peaked at the ages of 65-69 years for males and at 75-79 years for females. Age-standardised pancreatic cancer deaths worldwide were primarily attributable to smoking (21·1% [18·8-23·7]), high fasting plasma glucose (8·9% [2·1-19·4]), and high body-mass index (6·2% [2·5-11·4]) in 2017.Globally, the number of deaths, incident cases, and DALYs caused by pancreatic cancer has more than doubled from 1990 to 2017. The increase in incidence of pancreatic cancer is likely to continue as the population ages. Prevention strategies should focus on modifiable risk factors. Development of screening programmes for early detection and more effective treatment strategies for pancreatic cancer are needed.Bill & Melinda Gates Foundation.

Klein A.P.

Goggins M., Overbeek K.A., Brand R., Syngal S., Del Chiaro M., Bartsch D.K., Bassi C., Carrato A., Farrell J., Fishman E.K., Fockens P., Gress T.M., van Hooft J.E., Hruban R.H., Kastrinos F., et. al.

Background and aimThe International Cancer of the Pancreas Screening Consortium met in 2018 to update its consensus recommendations for the management of individuals with increased risk of pancreatic cancer based on family history or germline mutation status (high-risk individuals).MethodsA modified Delphi approach was employed to reach consensus among a multidisciplinary group of experts who voted on consensus statements. Consensus was considered reached if ≥75% agreed or disagreed.ResultsConsensus was reached on 55 statements. The main goals of surveillance (to identify high-grade dysplastic precursor lesions and T1N0M0 pancreatic cancer) remained unchanged. Experts agreed that for those with familial risk, surveillance should start no earlier than age 50 or 10 years earlier than the youngest relative with pancreatic cancer, but were split on whether to start at age 50 or 55. Germline ATM mutation carriers with one affected first-degree relative are now considered eligible for surveillance. Experts agreed that preferred surveillance tests are endoscopic ultrasound and MRI/magnetic retrograde cholangiopancreatography, but no consensus was reached on how to alternate these modalities. Annual surveillance is recommended in the absence of concerning lesions. Main areas of disagreement included if and how surveillance should be performed for hereditary pancreatitis, and the management of indeterminate lesions.ConclusionsPancreatic surveillance is recommended for selected high-risk individuals to detect early pancreatic cancer and its high-grade precursors, but should be performed in a research setting by multidisciplinary teams in centres with appropriate expertise. Until more evidence supporting these recommendations is available, the benefits, risks and costs of surveillance of pancreatic surveillance need additional evaluation.

Riquelme E., Zhang Y., Zhang L., Montiel M., Zoltan M., Dong W., Quesada P., Sahin I., Chandra V., San Lucas A., Scheet P., Xu H., Hanash S.M., Feng L., Burks J.K., et. al.

Most patients diagnosed with resected pancreatic adenocarcinoma (PDAC) survive less than 5 years, but a minor subset survives longer. Here, we dissect the role of the tumor microbiota and the immune system in influencing long-term survival. Using 16S rRNA gene sequencing, we analyzed the tumor microbiome composition in PDAC patients with short-term survival (STS) and long-term survival (LTS). We found higher alpha-diversity in the tumor microbiome of LTS patients and identified an intra-tumoral microbiome signature (Pseudoxanthomonas-Streptomyces-Saccharopolyspora-Bacillus clausii) highly predictive of long-term survivorship in both discovery and validation cohorts. Through human-into-mice fecal microbiota transplantation (FMT) experiments from STS, LTS, or control donors, we were able to differentially modulate the tumor microbiome and affect tumor growth as well as tumor immune infiltration. Our study demonstrates that PDAC microbiome composition, which cross-talks to the gut microbiome, influences the host immune response and natural history of the disease.

Koyanagi Y.N., Ito H., Matsuo K., Sugawara Y., Hidaka A., Sawada N., Wada K., Nagata C., Tamakoshi A., Lin Y., Takeuchi T., Kitamura Y., Utada M., Sadakane A., Mizoue T., et. al.

Abstract Background: Detailed prospective evaluation of cigarette smoking associated with pancreatic cancer risk in large Asian populations is limited. The aim of this study was to examine this association in a Japanese population, with a particular focus on evaluating sex differences. Methods: We performed a pooled analysis of 10 population-based cohort studies. We calculated study-specific HRs and 95% confidence intervals (CI) using Cox proportional hazards regression, and then estimated summary HRs by pooling these estimates with a random effects model. Results: During 4,695,593 person-years of follow-up in 354,154 participants, 1,779 incident pancreatic cancer cases were identified. We observed an increased pancreatic cancer risk for current smoking compared with never smoking in both males [HR (95% CI), 1.59 (1.32–1.91)] and females [HR (95% CI), 1.81 (1.43–2.30)]. Significant risk elevations for former smoking and small cumulative dose of ≤20 pack-years (PY) were observed only among females, regardless of environmental tobacco smoke exposure. Trend analysis indicated significant 6% and nonsignificant 6% increases in pancreatic cancer risk for every 10 PYs in males and females, respectively. Risk became comparable with never smokers after 5 years of smoking cessation in males. In females, however, we observed no risk attenuation by smoking cessation. Conclusions: This study supports the well-known association between smoking and pancreatic cancer and indicates potential sex differences in a Japanese population. Quitting smoking would be beneficial for pancreatic cancer prevention, especially in males. Impact: Pancreatic cancer risk is increased with cumulative smoking exposure and decreased with smoking cessation, with potential sex differences.

Konings I.C., Canto M.I., Almario J.A., Harinck F., Saxena P., Lucas A.L., Kastrinos F., Whitcomb D.C., Brand R.E., Lachter J., Malleo G., Paiella S., Syngal S., Saltzman J.R., Stoffel E.M., et. al.

Chen F., Childs E.J., Mocci E., Bracci P., Gallinger S., Li D., Neale R.E., Olson S.H., Scelo G., Bamlet W.R., Blackford A.L., Borges M., Brennan P., Chaffee K.G., Duggal P., et. al.

Abstract Background: Pancreatic cancer is the fourth-leading cause of cancer death in both men and women in the United States. The currently identified common susceptibility loci account for a small fraction of estimated heritability. We sought to estimate overall heritability of pancreatic cancer and partition the heritability by variant frequencies and functional annotations. Methods: Analysis using the genome-based restricted maximum likelihood method (GREML) was conducted on Pancreatic Cancer Case-Control Consortium (PanC4) genome-wide association study (GWAS) data from 3,568 pancreatic cancer cases and 3,363 controls of European Ancestry. Results: Applying linkage disequilibrium- and minor allele frequency-stratified GREML (GREML-LDMS) method to imputed GWAS data, we estimated the overall heritability of pancreatic cancer to be 21.2% (SE = 4.8%). Across the functional groups (intronic, intergenic, coding, and regulatory variants), intronic variants account for most of the estimated heritability (12.4%). Previously identified GWAS loci explained 4.1% of the total phenotypic variation of pancreatic cancer. Mutations in hereditary pancreatic cancer susceptibility genes are present in 4% to 10% of patients with pancreatic cancer, yet our GREML-LDMS results suggested these regions explain only 0.4% of total phenotypic variance for pancreatic cancer. Conclusions: Although higher than previous studies, our estimated 21.2% overall heritability may still be downwardly biased due to the inherent limitation that the contribution of rare variants in genes with a substantive overall impact on disease are not captured when applying these commonly used methods to imputed GWAS data. Impact: Our work demonstrated the importance of rare and common variants in pancreatic cancer risk.

Camargo J., Pumarega J.A., Alguacil J., Sanz-Gallén P., Gasull M., Delclos G.L., Amaral A.F., Porta M.

Some occupations potentially entailing exposure to cadmium, arsenic, lead, selenium, nickel, and chromium have been associated with an increased risk of exocrine pancreatic cancer (EPC), but no studies have assessed whether body concentrations of such compounds differed among subjects occupationally exposed and unexposed. No studies which found that exposure to such metals increased the risk of EPC assessed whether past occupations were the source of exposure.The aim was to analyse the relationship between toenail concentrations of trace elements and occupational history in EPC patients.The study included 114 EPC cases personally interviewed on occupational history and lifestyle factors. Occupations were coded according to the International Standard Classification of Occupations 1988. Selected occupational exposures were assessed by two industrial hygienists and with the Finnish job-exposure matrix (Finjem). Concentrations of 12 trace elements were determined in toenail samples by inductively coupled plasma mass spectrometry. Adjusted geometric means (aGMs) and 95% confidence intervals (95% CI) were calculated.Patients occupationally exposed to aromatic hydrocarbon solvents (AHs) had higher concentrations of cadmium, manganese, lead, iron and vanadium. The aGM of cadmium concentrations for cases exposed to any pesticide was 0.056 μg/g [95% CI: 0.029-0.108], and, for unexposed cases, 0.023 μg/g [0.017-0.031]. Patients occupationally exposed to pesticides had higher concentrations of cadmium and manganese. Higher concentrations of vanadium, lead and arsenic were related to exposure to formaldehyde. Vanadium and lead were also associated with exposure to chlorinated hydrocarbon solvents, and arsenic was related to exposure to polycyclic aromatic hydrocarbons (PAHs).Patients occupationally exposed to AHs, pesticides, chlorinated hydrocarbon solvents, formaldehyde, volatile sulphur compounds and PAHs had higher concentrations of several metals. These elements may account for some of the occupational risks previously reported for pancreatic cancer.

Chu L.C., Park S., Kawamoto S., Fouladi D.F., Shayesteh S., Zinreich E.S., Graves J.S., Horton K.M., Hruban R.H., Yuille A.L., Kinzler K.W., Vogelstein B., Fishman E.K.

OBJECTIVE. The objective of our study was to determine the utility of radiomics features in differentiating CT cases of pancreatic ductal adenocarcinoma (PDAC) from normal pancreas. MATERIALS AND METHODS. In this retrospective case-control study, 190 patients with PDAC (97 men, 93 women; mean age ± SD, 66 ± 9 years) from 2012 to 2017 and 190 healthy potential renal donors (96 men, 94 women; mean age ± SD, 52 ± 8 years) without known pancreatic disease from 2005 to 2009 were identified from radiology and pathology databases. The 3D volume of the pancreas was manually segmented from the preoperative CT scans by four trained researchers and verified by three abdominal radiologists. Four hundred seventy-eight radiomics features were extracted to express the phenotype of the pancreas. Forty features were selected for analysis because of redundancy of computed features. The dataset was divided into 255 training cases (125 normal control cases and 130 PDAC cases) and 125 validation cases (65 normal control cases and 60 PDAC cases). A random forest classifier was used for binary classification of PDAC versus normal pancreas of control cases. Accuracy, sensitivity, and specificity were calculated. RESULTS. Mean tumor size was 4.1 ± 1.7 (SD) cm. The overall accuracy of the random forest binary classification was 99.2% (124/125), and AUC was 99.9%. All PDAC cases (60/60) were correctly classified. One case from a renal donor was misclassified as PDAC (1/65). The sensitivity was 100%, and specificity was 98.5%. CONCLUSION. Radiomics features extracted from whole pancreas can be used to differentiate between CT cases from patients with PDAC and healthy control subjects with normal pancreas.

Daniel N., Farinella R., Belluomini F., Fajkic A., Rizzato C., Souček P., Campa D., Hughes D.J.

Farinella R., Felici A., Peduzzi G., Testoni S.G., Costello E., Aretini P., Blazquez-Encinas R., Oz E., Pastore A., Tacelli M., Otlu B., Campa D., Gentiluomo M.

Sun G., Wu Y., Li J., Yang M., Xu H., Li Y., Tong P., Shao R., Liu Y., Kong X.

Murray K., Oldfield L., Stefanova I., Gentiluomo M., Aretini P., O’Sullivan R., Greenhalf W., Paiella S., Aoki M.N., Pastore A., Birch-Ford J., Rao B.H., Uysal-Onganer P., Walsh C.M., Hanna G.B., et. al.

Ren Z., Gao W., Li X., Jing Y., Liu Z., Li X., Zhang T., Han X.

Yang C., Ji S., Shen S., Yu H., Deng C.

Kryklyva V., Pflüger M.J., Ouchene H., Volleberg-Gorissen H., Mensenkamp A.R., Jonker M.A., van de Water C., Nagtegaal I.D., Ligtenberg M.J., Brosens L.A.

Ferguson L.P., Tuveson D.A.

Pancreatic cancer is a notoriously deadly disease characterized by many challenges in clinical management. Despite important advances in our understanding of pancreatic cancer progression and its underlying molecular biology over the last decades, there is a long road ahead if we aim to meaningfully improve patient outcomes in this difficult disease. Treatment options remain limited, and patient prognosis, although improving, remains bleak. As we build toward the future, we propose a framework for targeting the seven deadly hallmarks of pancreatic cancer in an effort to cure this disease. The high mortality and aggressive nature of pancreatic cancer can be largely ascribed to (a) diagnostic deficiencies, (b) chronic inflammation, (c) desmoplastic stroma, (d) early metastasis, (e) KRAS signaling, (f) metabolism, and (g) rapid deconditioning. Here, we outline the challenges presented by each of these disease hallmarks and highlight ongoing research to tackle each one.

Du X., Ma Y., Wang K., Zhong X., Wang J., Tian X., Wang X., Yang Y.

AbstractPurposeTo assess the predictive capability of CT radiomics features for early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC).MethodsPostoperative PDAC patients were retrospectively selected, all of whom had undergone preoperative CT imaging and surgery. Both patients with resectable or borderline‐resectable pancreatic cancer met the eligibility criteria in this study. However, owing to the differences in treatment strategies and such, this research mainly focused on patients with resectable pancreatic cancer. All patients were subject to follow‐up assessments for a minimum of 9 months. A total of 250 cases meeting the inclusion criteria were included. A clinical model, a conventional radiomics model, and a deep‐radiomics model were constructed for ER prediction (defined as occurring within 9 months) in the training set. A model based on the TNM staging was utilized as a baseline for comparison. Assessment of the models' performance was based on the area under the receiver operating characteristic curve (AUC). Additionally, precision‐recall (PR) analysis and calibration assessments were conducted for model evaluation. Furthermore, the clinical utility of the models was evaluated through decision curve analysis (DCA), net reclassification improvement (NRI), and improvement of reclassification index (IRI).ResultsIn the test set, the AUC values for ER prediction were as follows: TNM staging, ROC‐AUC = 0.673 (95% CI: 0.550, 0.795), PR‐AUC = 0.362 (95% CI: 0.493, 0.710); clinical model, ROC‐AUC = 0.640 (95% CI: 0.504, 0.775), PR‐AUC = 0.481 (95% CI: 0.520, 0.735); radiomics model, ROC‐AUC = 0.722 (95% CI: 0.604, 0.839), PR‐AUC = 0.575 (95% CI: 0.466, 0.686); and deep‐radiomics model, which exhibited the highest ROC‐AUC of 0.895 (95% CI: 0.820, 0.970), PR‐AUC = 0.834 (95% CI: 0.767, 0.923). The difference in both ROC‐AUC and PR‐AUC for the deep‐radiomics model was statistically significant when compared to the other scores (all p < 0.05). The DCA curve of the deep‐radiomics model outperformed the other models. NRI and IRI analyses demonstrated that the deep‐radiomics model significantly enhances risk classification compared to the other prediction methods (all p < 0.05).ConclusionThe predictive performance of deep features based on CT images exhibits favorable outcomes in predicting early recurrence.

Liao Z., Dai T., Yuan F., Li K., Wang G.

Background: Disulfide-dependent cell death, known as disulfide death, plays a pivotal regulatory role in the onset and progression of various cancers including pancreatic cancer. Despite its significance, little attention has been given to the study of disulfide death-related long non-coding RNAs (lncRNAs) in pancreatic cancer development and progression. Methods: This study utilized data from the Cancer Genome Atlas Project (TCGA) to analyze the transcriptome of pancreatic cancer. Co-expression analysis of genes associated with disulfide death was performed and six lncRNAs closely linked to disulfide death were identified through univariate and multivariate analysis. These lncRNAs were used to develop clinical prognostic models. The prognostic value of this model was then analyzed and further investigations included pathway enrichment analysis, tumor mutation load analysis, immune cell infiltration analysis, analysis of the tumor microenvironment (TME), and drug sensitivity analysis. Results: The developed prognostic model based on disulfide-associated lncRNAs exhibited significant prognostic value, allowing for reliable predictions of patient outcomes in pancreatic adenocarcinoma (PAAD). The analysis revealed that the six identified lncRNAs serve as independent prognostic factors, significantly correlating with patient survival and recurrence rates. Additionally, findings indicated notable differences in immune cell infiltration and drug sensitivity between high-risk and low-risk patient groups, suggesting potential therapeutic targets for enhancing treatment efficacy. Conclusions: Our findings revealed six disulfide death-associated lncRNAs with independent prognostic value, offering a crucial indicator for predicting the prognosis of pancreatic adenocarcinoma (PAAD) patients. Additionally, the analysis of tumor immune invasion and drug sensitivity provides a novel avenue for controlling tumor invasion and metastasis as well as reducing drug tolerance.

Zhang J., Tan Q., Fan Y., Xiao L., Zheng Z., Li K., Jing W., Song H., Liu X., Tan C., Wang X.

Stoop T.F., Javed A.A., Oba A., Koerkamp B.G., Seufferlein T., Wilmink J.W., Besselink M.G.

Zhu W., Chen L., Aphinyanaphongs Y., Kastrinos F., Simeone D.M., Pochapin M., Stender C., Razavian N., Gonda T.A.

Abstract Early detection of pancreatic cancer (PC) remains challenging largely due to the low population incidence and few known risk factors. However, screening in at-risk populations and detection of early cancer has the potential to significantly alter survival. In this study, we aim to develop a predictive model to identify patients at risk for developing new-onset PC at two and a half to three year time frame. We used the Electronic Health Records (EHR) of a large medical system from 2000 to 2021 (N = 537,410). The EHR data analyzed in this work consists of patients’ demographic information, diagnosis records, and lab values, which are used to identify patients who were diagnosed with pancreatic cancer and the risk factors used in the machine learning algorithm for prediction. We identified 73 risk factors of pancreatic cancer with the Phenome-wide Association Study (PheWAS) on a matched case–control cohort. Based on them, we built a large-scale machine learning algorithm based on EHR. A temporally stratified validation based on patients not included in any stage of the training of the model was performed. This model showed an AUROC at 0.742 [0.727, 0.757] which was similar in both the general population and in a subset of the population who has had prior cross-sectional imaging. The rate of diagnosis of pancreatic cancer in those in the top 1 percentile of the risk score was 6 folds higher than the general population. Our model leverages data extracted from a 6-month window of time in the electronic health record to identify patients at nearly sixfold higher than baseline risk of developing pancreatic cancer 2.5–3 years from evaluation. This approach offers an opportunity to define an enriched population entirely based on static data, where current screening may be recommended.

Hu H., Li K., Han L., Gu Y., Ji Z.

ABSTRACTAdipose tissue activation plays a positive role in breast cancer outcomes, consistent with the improved outcomes observed through exercise and weight loss mediated by brown and beige fat. However, the underlying mechanism of this process remains unclear. C‐terminal fragment of Slit2 (Slit2‐C), endogenously produced by brown or beige adipose cells could increase the thermogenic process of adipose cells in autocrine and paracrine manners. Here, we show that Slit2‐C dominantly reduces breast cancer cell invasion through cAMP/PKA mediated inhibition of epithelial‐mesenchymal transition. In the process, Slit2‐C plays a vital role as a positive regulator of cAMP/PKA signaling in breast cancer. As a result, the overexpression of Slit2‐C leads to a reduction in cancer cell invasion and an increase in both the epithelial phenotype and thermogenesis. Besides, inhibiting PKA phosphorylation with H89 reversed the reduced invasion process seen in human breast cancer cells overexpressing Slit2‐C, which suggests that the effect of Slit2‐C on reducing invasion is mediated through the activation of PKA signaling. Taken together, our study suggests that the modulation of the Slit2‐C/cAMP/PKA axis might be a potential targeting therapeutic intervention in aggressive breast cancers.

Yan F., Yu L., Liu Z., Qi J., Wang L., Zhou M., Yin P.