Citations

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.

AbstractBiliary tract cancer (BTC) is a rare and aggressive malignancy with increasing incidence. Most BTC cases are diagnosed with metastatic disease which carries a 5‐year survival rate of <5%. Physical activity, diet, and obesity might be associated with BTC risk, but studies have been limited particularly in African descendants. We addressed this knowledge gap by evaluating associations of BTC risk with obesity, physical activity, and dietary intakes in 723,326 adult participants in four cohort studies conducted in China, the United Kingdom, and the United States. Cox regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) in each cohort; results were combined using meta‐analysis. All cohorts had ≥11 median follow‐up years with 839 incident BTC cases combined. BTC risk was positively associated with body mass index (BMI) and waist‐to‐hip ratio (WHR) whereas physical activity, fruit intake, and fish intake were inversely associated. HR and (95% CI) comparing BMI >35.0 to 18.5–24.9: 1.71 (1.26, 2.31), p‐trend <.0001; comparing BMI‐adjusted WHR top to bottom quartile: 1.20 (0.94, 1.53), p‐trend = .05; comparing ≥15–0 metabolic equivalent task‐hours/week 0.76 (0.61, 0.94), p‐trend = .009; comparing highest to lowest intake tertile for fruit and fish 0.79 (0.66, 0.95), p‐trend = .01; 0.82 (0.68, 0.98), p‐trend = .04, respectively. Associations were, in general, similar across ancestry groups. Our study provides strong evidence for important roles of obesity, diet, and physical activity in BTC etiology and stresses the need for lifestyle modification to combat the rising incidence of this fatal malignancy.

Abstract Myocardial fibrosis is a pathological hallmark of cardiovascular disease (CVD), and excessive fibrosis can lead to new-onset heart failure and increased mortality. Currently, pharmacological therapies for myocardial fibrosis are limited, highlighting the need for novel therapeutic approaches. The particulate guanylyl cyclase B (GC-B) receptor possesses beneficial antifibrotic actions through the binding of its natural ligand C-type natriuretic peptide (CNP) and the generation of the intracellular second messenger, cyclic guanosine 3′,5′-monophosphate (cGMP). These actions include the suppression of fibroblast proliferation and reduction in collagen synthesis. With its abundant expression on fibroblasts, the GC-B receptor has emerged as a key molecular target for innovative CVD therapeutics. However, small molecules that can bind and potentiate the GC-B/cGMP pathway have yet to be discovered. From a cell-based high-throughput screening initiative of the NIH Molecular Libraries Small Molecule Repository and hit-to-lead evolution based on a series of structure–activity relationships, we report the successful discovery of MCUF-42, a GC-B-targeted small molecule that acts as a positive allosteric modulator (PAM). Studies herein support MCUF-42's ability to enhance the binding affinity between GC-B and CNP. Moreover, MCUF-42 potentiated cGMP levels induced by CNP in human cardiac fibroblasts (HCFs) and notably also enhanced the inhibitory effect of CNP on HCF proliferation. Together, our findings highlight that MCUF-42 is a small molecule that can modulate the GC-B/cGMP signaling pathway, potentially enhancing the antifibrotic actions of CNP. Thus, these data underscore the continued development of GC-B small molecule PAMs as a novel therapeutic strategy for targeting cardiac fibrosis and CVD.

5008 Background: [177Lu]Lu-PSMA-617 (177Lu-PSMA-617) prolonged radiographic progression-free survival (rPFS) versus androgen receptor pathway inhibitor (ARPI) change in taxane-naive patients with metastatic castration-resistant prostate cancer (mCRPC) in PSMAfore (NCT04689828). In this exploratory analysis, associations between baseline circulating tumor DNA (ctDNA) and outcomes were assessed. Methods: Patients were randomized 1:1 to 177Lu-PSMA-617 (7.4 GBq Q6W; 6 cycles) or ARPI change (abiraterone/enzalutamide). Patients known to have actionable mutations (e.g. BRCA) were excluded. The primary endpoint was rPFS. Baseline plasma ctDNA was analyzed using a customized 585-gene sequencing assay. ctDNA fraction was assessed in all samples passing quality control. Alterations in key prostate cancer drivers (prevalent in >10% participants) were assessed in samples with ctDNA fraction >1%. Univariate Cox regression (reference: ARPI change) was used to assess association of ctDNA fraction or alterations with rPFS, prostate-specific antigen response (≥50% decline; PSA50) and RECIST response (RR) at the June 21, 2023 data cutoff. Results: Of 360 samples from 468 patients, 255 passed quality control and 156 had ctDNA fraction >1% (median 5.85%; range 0–85). Detection of ctDNA alterations was comparable between arms and with published data. Median rPFS was shorter for patients with ctDNA fraction > versus ≤1% (HR 2.753; 95% CI 1.957–3.872; p<0.0001) (Table); ctDNA fraction >1% was also associated with worse RR and PSA50 response. Median rPFS was shorter for patients with detected versus undetected AR(HR 1.954; 95% CI 1.333–2.865; p<0.001), TP53(1.655; 1.13–2.426; p<0.01) and PTEN(1.62; 1.018–2.578; p<0.05) alterations. Median rPFS was longer with 177Lu-PSMA-617 versus ARPI change in patients with detected AR, TP53, PTEN(Table) , PI3K pathway and DNA repair pathway alterations. There was no significant association between ctDNA alterations and PSA50 or RR. Conclusions: ctDNA fraction >1% and AR, TP53and PTENalterations were associated with worse outcomes in PSMAfore regardless of treatment. Nonetheless, patients with these negative prognostic biomarkers did better with 177Lu-PSMA-617 than with ARPI change. Clinical trial information: NCT04689828 . [Table: see text]

5006 Background: The PRESTO trial (NCT03009981) showed that in patients with biochemically relapsed prostate cancer following radical prostatectomy with a PSA doubling time of ≤ 9 months and without evidence of metastatic disease by conventional imaging, intensified androgen receptor blockade for 52 weeks (androgen deprivation therapy [ADT] plus apalutamide [Apa], or ADT plus Apa and abiraterone acetate [Abi] plus prednisone) prolonged PSA progression-free survival compared to ADT alone (Aggarwal et al, JCO 2024). Here we report the HRQOL results. Methods: HRQOL measures included the Hot Flash Related Daily Interference Scale (HFRDIS), Expanded Prostate Cancer Index Composite (EPIC)-26 Sexual domain, PROMIS Fatigue Short Form and EQ-5D-5L, which assesses overall HRQOL in the 504 randomized patients. Published minimally important difference thresholds for these HRQOL measures are: HFRDIS 1.66 points, EPIC Sexual 10-12, PROMIS Fatigue 3-5, and EQ-5D-5L 0.06. General linear mixed modeling was used to estimate between-arm mean differences in HRQOL according to an intent-to-treat approach. Results: Mean changes from baseline to end of treatment (EOT) for each arm and for each HRQOL measure are summarized in Table. No statistically significant mean difference was reported between intensified androgen receptor blockade (Arm B, Arm C) vs ADT alone (Arm A) in any HRQOL measure. Further, numerical differences across arms for all HRQOL measures are below published minimally clinically important difference thresholds. Conclusions: Intensified androgen receptor blockade with Apa or Apa/Abi added to 52 weeks of ADT improves PSA progression-free survival without negatively affecting HRQOL. These HRQOL results add further support to intensification of androgen blockade in patients with high-risk biochemically recurrent prostate cancer. Clinical trial information: NCT03009981 . [Table: see text]

Abstract Objectives Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for healthcare professionals. The current treatment strategies, largely derived from population based evidence, often fail to consider the unique characteristics of individual patients, resulting in suboptimal outcomes. This study aims to develop computational models that are patient-specific in predicting treatment outcomes, by utilizing a large Electronic Health Records (EHR) database. The goal is to improve drug response predictions by identifying specific HF patient subgroups that are likely to benefit from existing HF medications. Materials and Methods A novel, graph-based model capable of predicting treatment responses, combining Graph Neural Network and Transformer was developed. This method differs from conventional approaches by transforming a patient's EHR data into a graph structure. By defining patient subgroups based on this representation via K-Means Clustering, we were able to enhance the performance of drug response predictions. Results Leveraging EHR data from 11 627 Mayo Clinic HF patients, our model significantly outperformed traditional models in predicting drug response using NT-proBNP as a HF biomarker across five medication categories (best RMSE of 0.0043). Four distinct patient subgroups were identified with differential characteristics and outcomes, demonstrating superior predictive capabilities over existing HF subtypes (best mean RMSE of 0.0032). Discussion These results highlight the power of graph-based modeling of EHR in improving HF treatment strategies. The stratification of patients sheds light on particular patient segments that could benefit more significantly from tailored response predictions. Conclusions Longitudinal EHR data have the potential to enhance personalized prognostic predictions through the application of graph-based AI techniques.

AbstractBackgroundAbsent “organic” disease, dyspeptic symptoms may arise from abnormal gastric sensation, accommodation, motility or emptying (GE). Extensive gastric sensorimotor evaluation is rarely undertaken because testing is prolonged, invasive, poorly tolerated or unavailable.AimsTo investigate whether gastric antral motor function, evaluated with scintigraphy, predicts GE. To explore whether motor testing with symptom recording predicts day‐to‐day symptoms in patients with dyspepsia.MethodsGE was determined using a scintigraphic solid‐meal protocol (296 kcal, 35% fat). Antral motility was estimated from 10 min of scintigraphic time‐activity curves acquired 40 min after meal consumption. An antral motility index (MI) was derived from contraction amplitude and frequency. Intra‐gastric distribution of the meal on scintograms at 1 h (IGD1) was determined. Meal‐induced symptoms were evaluated by questionnaire. Patients completed the Gastroparesis Cardinal Symptom Index Daily Diary (GCSI‐DD) for 14 days.ResultsTwelve healthy participants and 23 prospectively recruited patients completed the study. Nine patients had delayed, and 2 had rapid, GE. In univariate analysis MI explained 42% of GE half‐time. In multivariate analysis MI and GE half‐time explained 25% of the variance in meal‐induced symptoms. While scintigraphic evaluation of gastric motor function with symptom recording explained 80% of the variance in the GCSI‐DD, meal‐induced symptoms were the only significant predictor. However, among patients with delayed GE, MI, GE half‐time, IGD1, and meal‐induced symptoms all significantly predicted GCSI‐DD.ConclusionsAntral motility predicts GE. In exploratory analyses, only meal‐induced symptoms predicted daily symptoms among patients with dyspepsia. However, motor function also predicted symptoms in patients with delayed GE.