Bamlet, William R

Abstract Purpose: The Pancreatic Cancer Detection Consortium (PCDC) performed a blinded Early Detection Research Network–defined phase II biomarker bakeoff study of blood-based biomarker panels. The aims were to evaluate panel performance, to compare the panels’ performance with that of cancer antigen 19-9 (CA19-9) alone, and to evaluate the performance of new combinations of the individual biomarkers. Experimental Design: Ten biomarkers representing eight biomarker panels and CA19-9 were evaluated using plasma, serum, and germline DNA from 140 stage I to IV pancreatic ductal adenocarcinoma (PDAC) cases and 140 controls from three tertiary care institutions, with controls frequency matched to cases on age and sex. LASSO regression was employed to explore new biomarker combinations. The primary metric was area under the receiver operating characteristic curve (AUC). Results: The study population was 51% female, with median age 67.3 (minimum: 45, maximum: 90) years. Biomarker panel AUCs ranged from 89.9 to 96.3; the AUC for serum CA19-9 alone was 91.7 [95% confidence interval (CI), 87.8–95.6]. Two panels had significantly higher AUCs than serum CA19-9 alone, the CA19-9/FUT2/3 panel (AUC = 96.3, P = 0.002), and the tissue factor pathway inhibitor/tenascin C (TFPI/TNC-FNIII-C) panel (AUC = 95, P = 0.01). Exploratory models to recombine biomarkers retained all but two biomarkers [optimism-corrected AUC = 96.4 (94–98.9)]. Conclusions: The CA19-9/FUT2/3 panel was the best performing panel in this biomarker bakeoff. Its evaluation in larger studies is warranted. Biomarker bakeoffs are an effective strategy for comparing the performance of promising biomarkers for pancreatic cancer early detection, and the PCDC is well poised to conduct such studies. Recommendations for performing such studies are provided.

Abstract Purpose: Pancreatic ductal adenocarcinoma (PDAC) is typically detected too late for useful therapeutic interventions; hence, we sought blood biomarkers to detect early-stage disease. Experimental Design: Using mass spectrometry and ELISA on plasma pools from the University of Pennsylvania (Penn) and the Mayo Clinic (Mayo), we identified aminopeptidase N (ANPEP) and polymeric immunoglobulin receptor (PIGR) as increased in early-stage (stage I/II) PDAC plasma compared with controls. We tested ANPEP and PIGR, along with prior data for thrombospondin 2 (THBS2) and carbohydrate antigen 19-9 (CA19-9), in retrospective phase II studies using separate cohorts of PDAC plasmas at different stages versus healthy or nonmalignant disease controls (DC) from Penn (n = 135) and Mayo (n = 537). Results: Comparing healthy controls with stage I/II PDAC, we obtained area under the receiver-operating characteristic curves (AUC) of 0.78 [95% confidence interval (CI), 0.68–0.86]/0.80 (95% CI, 0.74–0.85; ANPEP) and 0.81 (95% CI, 0.70–0.88)/0.86 (95% CI, 0.82–0.90; PIGR) for the Penn/Mayo phase II studies, respectively. In multivariable models, CA19-9/THBS2/ANPEP, CA19-9/THBS2/PIGR, and CA19-9/THBS2/ANPEP/PIGR elicited AUC of 0.94 to 0.96 for Penn and 0.97 for Mayo. Notably, the four-marker panel elicited AUC of 0.87 for the Mayo stage I/II versus DC and 0.91 for stages I to IV versus DC. At a specificity of 95%, a plasma biomarker panel composed of CA19-9 (≥35 U/mL), THBS2 (≥42 ng/mL), ANPEP (≥2,995 ng/mL), and PIGR (≥1,800 ng/mL) yielded a sensitivity of 91.9% for PDAC stages I to IV and 87.5% for PDAC stage I/II. Conclusions: Adding ANPEP and PIGR to a plasma biomarker panel of CA19-9 and THBS2 enhances the detection of early-stage PDAC when comparing cancer versus healthy or nonmalignant DC. Given the concordance of our data in two retrospective phase II studies, assessments in prediagnostic cases are warranted.

Abstract Aberrant activation of GLI transcription factors has been implicated in the pathogenesis of different tumor types including pancreatic ductal adenocarcinoma. However, the mechanistic link with established drivers of this disease remains in part elusive. In this study, using a new genetically engineered mouse model overexpressing constitutively active mouse form of GLI2 and a combination of genome-wide assays, we provide evidence of a novel mechanism underlying the interplay between KRAS, a major driver of pancreatic ductal adenocarcinoma development, and GLI2 to control oncogenic gene expression. These mice, also expressing KrasG12D, show significantly reduced median survival rate and accelerated tumorigenesis compared with the KrasG12D only expressing mice. Analysis of the mechanism using RNA sequencing demonstrate higher levels of GLI2 targets, particularly tumor growth–promoting genes, including Ccnd1, N-Myc, and Bcl2, in KrasG12D mutant cells. Furthermore, chromatin immunoprecipitation sequencing studies showed that in these cells KrasG12D increases the levels of trimethylation of lysine 4 of the histone 3 (H3K4me3) at the promoter of GLI2 targets without affecting significantly the levels of other major active chromatin marks. Importantly, Gli2 knockdown reduces H3K4me3 enrichment and gene expression induced by mutant Kras. In summary, we demonstrate that Gli2 plays a significant role in pancreatic carcinogenesis by acting as a downstream effector of KrasG12D to control gene expression.

Abstract Background: Pancreatic cancer is a leading cause of cancer-related death globally. Risk factors for pancreatic cancer include common genetic variants and potentially heavy alcohol consumption. We assessed if genetic variants modify the association between heavy alcohol consumption and pancreatic cancer risk. Methods: We conducted a genome-wide interaction analysis of single-nucleotide polymorphisms (SNP) by heavy alcohol consumption (more than three drinks per day) for pancreatic cancer in European ancestry populations from genome-wide association studies. Our analysis included 3,707 cases and 4,167 controls from case–control studies and 1,098 cases and 1,162 controls from cohort studies. Fixed-effect meta-analyses were conducted. Results: A potential novel region of association on 10p11.22, lead SNP rs7898449 (interaction P value (Pinteraction) = 5.1 × 10−8 in the meta-analysis; Pinteraction = 2.1 × 10−9 in the case–control studies; Pinteraction = 0.91 in the cohort studies), was identified. An SNP correlated with this lead SNP is an expression quantitative trait locus for the neuropilin 1 gene. Of the 17 genomic regions with genome-wide significant evidence of association with pancreatic cancer in prior studies, we observed suggestive evidence that heavy alcohol consumption modified the association for one SNP near LINC00673, rs11655237 on 17q25.1 (Pinteraction = 0.004). Conclusions: We identified a novel genomic region that may be associated with pancreatic cancer risk in conjunction with heavy alcohol consumption located near an expression quantitative trait locus for neuropilin 1, a protein that plays an important role in the development and progression of pancreatic cancer. Impact: This work can provide insights into the etiology of pancreatic cancer, particularly in heavy drinkers.

Abstract Background: There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer. Methods: Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes. Results: No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88–1.22; MR-Egger OR, 0.89; 95% CI, 0.65–1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90–1.27; MR-Egger OR, 0.93; 95% CI, 0.67–1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample. Conclusions: Genetic predisposition to NAFLD is not associated with pancreatic cancer risk. Impact: Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer.

Background: Deciphering hypoplastic left heart syndrome (HLHS) pathogenesis is confounded by its genetic heterogeneity and oligogenic underpinnings. Methods: Whole genome sequences were analyzed by 3 independent strategies to identify HLHS gene candidates, ranked by variant, gene, and disease-level metrics. Results: First, a genome-wide association study of 174 cases and 853 controls revealed suggestive association with a MYO18B intron 33 variant (rs2269628-G; frequency=0.55 versus 0.39; OR, 1.97 [95% CI, 1.54–2.52]; P =6.70×10 − 8 ). Second, transmission disequilibrium testing of 161 HLHS proband-parent trios revealed overrepresentation of a MYO18B intron 42 variant (rs73154186-A; frequency=0.05; OR, 24 [95% CI, 3.2–177.4]; P =4.23×10 − 6 ). Third, rare, predicted-damaging variants were filtered in 2 multiplex families. In 141H, 2 fifth-degree relatives with HLHS shared a paternally-inherited MYO5A missense variant (p.Arg801Trp; frequency=0.00003; combined annotation-dependent depletion score=29), each with a maternally-inherited or de novo candidate modifier variant in a MYO5A-interacting conventional myosin. In 442H, a HLHS proband was compound heterozygous for MYO15A variants—a maternally-inherited pathogenic stop-gain variant co-segregating with tetralogy of Fallot and bicuspid aortic valve in maternal relatives (p.Tyr2819Ter; frequency=0.00003) and a paternally-inherited intronic variant altering a canonical transcription factor binding site (rs1277068603; frequency=0.00001; position weight matrix score=0.98). Conclusions: Collectively, these findings suggest that common and rare alleles within unconventional myosin genes are associated with HLHS susceptibility. The identified candidate MYO18B regulates cardiac sarcomerogenesis, supporting the hypothesis of intrinsic myogenic perturbation in arrested left heart development.

Background: Whole-genome sequencing in families enables deciphering of congenital heart disease causes. A shared genetic basis for familial bicuspid aortic valve (BAV) and hypoplastic left heart syndrome (HLHS) was postulated. Methods: Whole-genome sequencing was performed in affected members of 6 multiplex BAV families, an HLHS cohort of 197 probands and 546 relatives, and 813 controls. Data were filtered for rare, predicted-damaging variants that cosegregated with familial BAV and disrupted genes associated with congenital heart disease in humans and mice. Candidate genes were further prioritized by rare variant burden testing in HLHS cases versus controls. Modifier variants in HLHS proband-parent trios were sought to account for the severe developmental phenotype. Results: In 5 BAV families, missense variants in 6 ontologically diverse genes for structural ( SPTBN1 , PAXIP1 , and FBLN1 ) and signaling ( CELSR1 , PLXND1 , and NOS3 ) proteins fulfilled filtering metrics. CELSR1 , encoding cadherin epidermal growth factor laminin G seven-pass G-type receptor, was identified as a candidate gene in 2 families and was the only gene demonstrating rare variant enrichment in HLHS probands ( P =0.003575). HLHS-associated CELSR1 variants included 16 missense, one splice site, and 3 noncoding variants predicted to disrupt canonical transcription factor binding sites, most of which were inherited from a parent without congenital heart disease. Filtering whole-genome sequencing data for rare, predicted-damaging variants inherited from the other parent revealed 2 cases of CELSR1 compound heterozygosity, one case of CELSR1 - CELSR3 synergistic heterozygosity, and 4 cases of CELSR1 - MYO15A digenic heterozygosity. Conclusions: CELSR1 is a susceptibility gene for familial BAV and HLHS, further implicating planar cell polarity pathway perturbation in congenital heart disease.

Abstract Background: ABO blood group is associated with pancreatic cancer risk. Whether ABO blood group alone or when combined with inherited mutation status of index pancreatic cancer cases (probands) can enhance pancreatic cancer risk estimation in first-degree relatives (FDR) is unclear. We examined FDRs' risk for pancreatic cancer based on probands' ABO blood group and probands' cancer susceptibility gene mutation status. Methods: Data on 23,739 FDRs, identified through 3,268 pancreatic cancer probands, were analyzed. Probands' ABO blood groups were determined serologically or genetically, and 20 cancer susceptibility genes were used to classify probands as “mutation-positive” or “mutation-negative.” SIRs and 95% confidence intervals (CI) were calculated, comparing observed pancreatic cancer cases in the FDRs with the number expected in SEER-21 (reference population). Results: Overall, FDRs had 2-fold risk of pancreatic cancer (SIR = 2.00; 95% CI = 1.79–2.22). Pancreatic cancer risk was higher in FDRs of mutation-positive (SIR = 3.80; 95% CI = 2.81–5.02) than mutation-negative (SIR = 1.79; 95% CI = 1.57–2.04) probands (P < 0.001). The magnitude of risk did not differ by ABO blood group alone (SIRblood-group-O = 1.57; 95% CI = 1.20–2.03, SIRnon-O = 1.83; 95% CI = 1.53–2.17; P = 0.33). Among FDRs of probands with non-O blood group, pancreatic cancer risk was higher in FDRs of mutation-positive (SIR = 3.98; 95% CI = 2.62–5.80) than mutation-negative (SIR = 1.66; 95% CI = 1.35–2.03) probands (P < 0.001), but risk magnitudes were statistically similar when probands had blood group O (SIRmutation-positive = 2.65; 95% CI = 1.09–5.47, SIRmutation-negative = 1.48; 95% CI = 1.06–5.47; P = 0.16). Conclusions: There is a range of pancreatic cancer risk to FDRs according to probands' germline mutation status and ABO blood group, ranging from 1.48 for FDRs of probands with blood group O and mutation-negative to 3.98 for FDRs of probands with non-O blood group and mutation-positive. Impact: Combined ABO blood group and germline mutation status of probands can inform pancreatic cancer risk estimation in FDRs.

Abstract Purpose: We have previously identified tissue methylated DNA markers (MDMs) associated with pancreatic ductal adenocarcinoma (PDAC). In this case–control study, we aimed to assess the diagnostic performance of plasma MDMs for PDAC. Experimental Design: Thirteen MDMs (GRIN2D, CD1D, ZNF781, FER1L4, RYR2, CLEC11A, AK055957, LRRC4, GH05J042948, HOXA1, PRKCB, SHISA9, and NTRK3) were identified on the basis of selection criteria applied to results of prior tissue experiments and assays were optimized in plasma. Next, 340 plasma samples (170 PDAC cases and 170 controls) were assayed using target enrichment long-probe quantitative amplified signal method. Initially, 120 advanced-stage PDAC cases and 120 healthy controls were used to train a prediction algorithm at 97.5% specificity using random forest modeling. Subsequently, the locked algorithm derived from the training set was applied to an independent blinded test set of 50 early-stage PDAC cases and 50 controls. Finally, data from all 340 patients were combined, and cross-validated. Results: The cross-validated area under the receiver operating characteristic curve (AUC) for the training set was 0.93 (0.89–0.96) for the MDM panel alone, 0.91 (95% confidence interval, 0.87–0.96) for carbohydrate antigen 19-9 (CA19-9) alone, and 0.99 (0.98–1) for the combined MDM-CA19-9 panel. In the test set of early-stage PDAC, the AUC for MDMs alone was 0.84 (0.76–0.92), CA19-9 alone was 0.87 (0.79–0.94), and combined MDM-CA19-9 panel was 0.90 (0.84–0.97) significantly better compared with either MDMs alone or CA19-9 alone (P = 0.0382 and 0.0490, respectively). At a preset specificity of 97.5%, the sensitivity for the combined panel in the test set was 80% (28%–99%) for stage I disease and 82% (68%–92%) for stage II disease. Using the combined datasets, the cross-validated AUC was 0.9 (0.86–0.94) for the MDM panel alone and 0.89 for CA19-9 alone (0.84–0.93) versus 0.97 (0.94–0.99) for the combined MDM-CA19-9 panel (P ≤ 0.0001). Overall, cross-validated sensitivity of MDM-CA19-9 panel was 92% (83%–98%), with an observed specificity of 92% at the preset specificity of 97.5%. Conclusions: Plasma MDMs in combination with CA19-9 detect PDAC with significantly higher accuracy compared with either biomarker individually.

Abstract Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10–8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82–0.93; former smokers 1.00, 95% CI, 0.91–1.07; current smokers 1.25, 95% CI 1.12–1.40, Pinteraction = 3.08 × 10–9). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 (r2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. Significance: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention.