Citations

BACKGROUND: Defining qualitative grades of echocardiographic metrics of right heart chamber size and function is critical for screening, clinical assessment, and measurement of therapeutic response in individuals with pulmonary vascular disease (PVD). In a population enriched for PVD, we sought to establish qualitative grades and prognostic value of right heart chamber size and function. METHODS: We investigated 1053 study participants in PVDOMICS (Redefining Pulmonary Hypertension Through the PVD Phenomics Program) to determine clinical and echocardiographic differences associated with increasing pulmonary vascular resistance severity. Right heart chamber size and function were qualitatively assessed using a percentile-based approach above the median values to create a clinical grading system for right heart adaptation. The relationship between echocardiographic categories and all-cause mortality was examined using survival analyses adjusted for potential confounders. RESULTS: A stepwise increase in adverse right heart remodeling was observed with a concomitant decrease in functional parameters by pulmonary vascular resistance strata ( P <0.001 for all). Mild, moderate, and severe categories of right heart chamber size and dysfunction were defined using a percentile-based approach across the spectrum of PVD. During a median follow-up of 2.07 years (interquartile range, 1.23–3.01 years), 130 participants died (11.4%). Progressive pulmonary vascular resistance increase and 2DE evidence of right heart dysfunction inclusive of fractional area change, and right ventricular global longitudinal strain were independently associated with increased all-cause mortality risk in multivariate analysis adjusted for age, disease duration, and male sex. CONCLUSIONS: In this well-characterized sample of adults with diverse etiologies and varying PVD severity, we define categories of abnormal right heart chamber size and function. Further, we demonstrate a stepwise relationship between these categories of abnormal morphology and function and all-cause mortality. Defining grades of right ventricular dysfunction in individuals with known PVD has important clinical implications for monitoring disease progression and response to therapies.

Adaptive radiotherapy (ART) workflows are increasingly adopted to achieve dose escalation and tissue sparing under dynamic anatomical conditions. However, recontouring and time constraints hinder the implementation of real-time ART workflows. Various auto-segmentation methods, including deformable image registration, atlas-based segmentation, and deep learning-based segmentation (DLS), have been developed to address these challenges. Despite the potential of DLS methods, clinical implementation remains difficult due to the need for large, high-quality datasets to ensure model generalizability. This study introduces an InterVision framework for segmentation. The InterVision framework can interpolate or create intermediate visuals between existing images to generate specific patient characteristics. The InterVision model is trained in two steps: (1) generating a general model using the dataset, and (2) tuning the general model using the dataset generated from the InterVision framework. The InterVision framework generates intermediate images between existing patient image slides using deformable vectors, effectively capturing unique patient characteristics. By creating a more comprehensive dataset that reflects these individual characteristics, the InterVision model demonstrates the ability to produce more accurate contours compared to general models. Models are evaluated using the volumetric dice similarity coefficient (VDSC) and the Hausdorff distance 95% (HD95%) for 18 structures in 20 test patients. As a result, the Dice score was 0.81 ± 0.05 for the general model, 0.82 ± 0.04 for the general fine-tuning model, and 0.85 ± 0.03 for the InterVision model. The Hausdorff distance was 3.06 ± 1.13 for the general model, 2.81 ± 0.77 for the general fine-tuning model, and 2.52 ± 0.50 for the InterVision model. The InterVision model showed the best performance compared to the general model. The InterVision framework presents a versatile approach adaptable to various tasks where prior information is accessible, such as in ART settings. This capability is particularly valuable for accurately predicting complex organs and targets that pose challenges for traditional deep learning algorithms.

Abstract Introduction Pancreatic adenocarcinoma (PDA) will be the second leading cause of cancer related death by 2030 and patient response to chemotherapy is poor with a strong likelihood of cancer recurrence. While past studies have investigated pre- and post-chemotherapy patient samples, there is a paucity of studies looking at fresh, patient matched samples which allow us to observe interpatient heterogeneity in chemotherapy response. Methods Here, we study the effects of chemotherapy on five different patients using sc-RNA sequencing of matched treatment naïve and post treatment tissue biopsies to compare the effects of chemotherapy, not only on the tumor cells, but also on the tumor microenvironment – a key contributor to tumor survival and proliferation. We utilized the Seurat v4 pipeline and CellChat v2 to observe transcriptomic differences in epithelial cells, myeloid cells, t-Cells, and fibroblasts and their corresponding putative interactions in pre- and post- treatment states. Results Unsurprisingly, we found insufficient tumor epithelial cells post-treatment to perform further analysis on due to the intended cytotoxic effects of chemotherapy. Therefore, we turned our focus to the tumor microenvironment, where we had sufficient numbers of stromal and immune cells, to investigate the effects of chemotherapy. We identified that fibroblasts changed the most consistently across all patients in response to chemotherapy. The fibroblasts clustered into three distinct groups: an immunomodulatory group, a myofibroblastic and neurotropic group, as well as a mixed group expressing genes from all three categories. Interestingly, the neurotropic fibroblast signature was universally enriched after chemotherapy in all five patients, despite having a small and clinically heterogeneous cohort. Conclusions Through an analysis of each fibroblast group in the treatment naïve and post treatment categories, we observed that a specific set of fibroblasts become less myofibroblastic and increasingly neurotropic following treatment, leading us to posit that fibroblasts altered by exposure to chemotherapy may potentially contribute to a ‘pro-tumor’ environment that supports recurrence. To test this in vitro, we treated patient derived fibroblasts with Gemcitabine and used RTPCR to analyze their relative changes in gene expression. We specifically probed for genes that were definitive of myofibroblasts and neurotropic fibroblasts and saw that post-chemotherapy exposure, neurotropic genes such as NEGR1 and NFIA were upregulated. This validated our scRNA conclusions that fibroblasts become increasingly neurotropic following treatment and then differentially interact with their surrounding environment. In future studies, we will further analyze the role these neurotropic fibroblasts play in chemoresponse and tumor recurrence. Matched samples are critical to studies of chemotherapy effects on PDA due to the fact that they allow us to deconvolute one aspect of PDA heterogenity - interpatient heterogeneity - which is a large limitation in studies of this disease. Citation Format: Aylin Z Henstridge, Padma Kadiyala, Ahmed M Elhossiny, Jianhua Liu, Vaibhav Sahai, Nicole Peterson, Jorge Machicado, Richard Kwon, Allison Schulman, Erik Wamsteker, George Philips, Martin Fernandez-Zapico, Mark Truty, Costas Lyssiotis, Timothy Frankel, Filip Bednar, Marina Pasca di Magliano, Eileen S Carpenter. Neurotropic fibroblast population increases following exposure to chemotherapy in pancreatic adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A062.

INTRODUCTION: Prophylactic pancreatic stent placement (PSP) is effective for preventing pancreatitis after endoscopic retrograde cholangiopancreatography (ERCP) in high-risk cases, but the optimal technical approach to this intervention remains uncertain. METHODS: In this secondary analysis of 787 clinical trial patients who underwent successful stent placement, we studied the impact of (i) whether pancreatic wire access was achieved for the sole purpose of PSP or naturally during the conduct of the case, (ii) the amount of effort expended on PSP, (iii) stent length, (iv) stent diameter, and (v) guidewire caliber. We used logistic regression models to examine the adjusted association between each technical factor and post-ERCP pancreatitis (PEP). RESULTS: Ninety-one of the 787 patients experienced PEP. There was no clear association between PEP and whether pancreatic wire access was achieved for the sole purpose of PSP (vs occurring naturally; odds ratio [OR] 0.82, 95% confidence interval [CI] 0.37–1.84), whether substantial effort expended on stent placement (vs nonsubstantial effort; OR 1.58, 95% CI 0.73–3.45), stent length (>5 vs ≤5 cm; OR 1.01, 95% CI 0.63–1.61), stent diameter (≥5 vs <5 Fr; OR 1.13, 95% CI 0.65–1.96), or guidewire caliber (0.035 vs 0.025 in; 0.83, 95% CI 0.49–1.41). DISCUSSION: The 5 modifiable technical factors studied in this secondary analysis of large-scale randomized trial data did not appear to have a strong impact on the benefit of prophylactic PSP in preventing PEP after high-risk ERCP. Within the limitations of post hoc subgroup analysis, these findings may have important implications in procedural decision making and suggest that the benefit of PSP is robust to variations in technical approach.

Abstract Aims In the Phase 3 trial, RHAPSODY, rilonacept effectively resolved active pericarditis recurrences, and long-term treatment led to sustained pericarditis recurrence risk reduction. Prior analysis suggested association between higher late gadolinium enhancement (LGE) at baseline and more rapid recurrence upon rilonacept suspension after 12 weeks of treatment. This subgroup analysis assessed the utility of longitudinal serial cardiac magnetic resonance (CMR) imaging for tracking clinical improvement and predicting post-treatment cessation outcomes to help guide clinical decision-making. Methods and results At an 18-month decision milestone (18MDM) in the RHAPSODY long-term extension, investigators decided if patients would continue rilonacept, suspend rilonacept for off-treatment observation, or discontinue the study. Pericardial thickness, pericardial oedema (T2-short tau inversion recovery, T2-STIR), and LGE were determined at baseline and 18MDM by an imaging core lab blinded to clinical data, and pericarditis recurrence was investigator-assessed. CMR results in patients with data at both baseline and 18MDM (n = 13) showed that pericardial thickness, T2-STIR, and LGE were reduced during rilonacept treatment. Among patients with CMR data who suspended rilonacept at the 18MDM (n = 7), five (71%) had a pericarditis recurrence within 1–4 months of rilonacept suspension, despite all having had none/trace LGE (n = 7) and negative T2-STIR (n = 7) at the 18MDM and two having received prophylactic colchicine. Conclusion Continued clinical improvement during prolonged rilonacept treatment corresponded with improvement on CMR, including reduced pericardial thickness, resolution of pericardial oedema, and resolution of LGE. However, none/trace LGE at 18MDM while on treatment did not predict absence of pericarditis recurrence upon subsequent rilonacept suspension in this size-limited subgroup.

INTRODUCTION: Early neoplastic progression of Barrett's esophagus (BE) is often treated with endoscopic therapy. Although effective, some patients are refractory to therapy or recur after apparent eradication of the BE. The goal of this study was to determine whether genomic alterations within the treated BE may be associated with persistent or recurrent disease. METHODS: We performed DNA sequencing on pre-treatment esophageal samples from 45 patients who were successfully treated by endoscopic therapy and did not recur as well as pre-treatment and post-treatment samples from 40 patients who had persistent neoplasia and 21 patients who had recurrent neoplasia. The genomic alterations were compared between groups. RESULTS: The genomic landscape was similar between all groups. Patients with persistent disease were more likely to have pre-treatment alterations involving the receptor tyrosine kinase pathway ( P = 0.01), amplifications of oncogenes ( P = 0.01), and deletions of tumor suppressor genes ( P = 0.02). These associations were no longer significant after adjusting for patient age and BE length. More than half of patients with persistent (52.5%) or recurrent (57.2%) disease showed pre-treatment and post-treatment samples that shared at least 50% of their driver mutations. DISCUSSION: Pre-treatment samples were genomically similar between those who responded to endoscopic therapy and those who had persistent or recurrent disease, suggesting there is not a strong genomic component to treatment response. Although it was expected to find shared driver mutations in pre-treatment and post-treatment samples in patients with persistent disease, the finding that an equal number of patients with recurrent disease also showed this relation suggests that many recurrences represent undetected minimal residual disease.

Diploid human cells contain two non-identical genomes, and differences in their regulation underlie human development and disease. We present Fiber-seq Inferred Regulatory Elements (FIRE) and show that FIRE provides a more comprehensive and quantitative snapshot of the accessible chromatin landscape across the 6 Gbp diploid human genome, overcoming previously unrecognized biases in existing regulatory element catalogs. FIRE enables comprehensive detection of haplotype-selective chromatin accessibility (HSCA), exposing novel imprinted elements lacking underlying parent-of-origin CpG methylation differences, and gene regulatory modules that permit genes to escape X chromosome inactivation. We uncover that the human leukocyte antigen (HLA) locus harbors the most HSCA in immune cells, where we resolve specific transcription factor (TF) binding events disrupted by disease-associated variants. Finally, we demonstrate that the regulatory landscape of a cell is littered with autosomal somatic chromatin epimutations that are propagated by clonal expansions to create mitotically stable and non-genetically deterministic chromatin alterations.

Abstract Graft-versus-host disease (GVHD) is a major cause of nonrelapse mortality (NRM) after allogeneic hematopoietic cell transplantation. Algorithms containing either the gastrointestinal (GI) GVHD biomarker amphiregulin (AREG) or a combination of 2 GI GVHD biomarkers (suppressor of tumorigenicity-2 [ST2] + regenerating family member 3 alpha [REG3α]) when measured at GVHD diagnosis are validated predictors of NRM risk but have never been assessed in the same patients using identical statistical methods. We measured the serum concentrations of ST2, REG3α, and AREG by enzyme-linked immunosorbent assay at the time of GVHD diagnosis in 715 patients divided by the date of transplantation into training (2004-2015) and validation (2015-2017) cohorts. The training cohort (n = 341) was used to develop algorithms for predicting the probability of 12-month NRM that contained all possible combinations of 1 to 3 biomarkers and a threshold corresponding to the concordance probability was used to stratify patients for the risk of NRM. Algorithms were compared with each other based on several metrics, including the area under the receiver operating characteristics curve, proportion of patients correctly classified, sensitivity, and specificity using only the validation cohort (n = 374). All algorithms were strong discriminators of 12-month NRM, whether or not patients were systemically treated (n = 321). An algorithm containing only ST2 + REG3α had the highest area under the receiver operating characteristics curve (0.757), correctly classified the most patients (75%), and more accurately risk-stratified those who developed Minnesota standard-risk GVHD and for patients who received posttransplant cyclophosphamide-based prophylaxis. An algorithm containing only AREG more accurately risk-stratified patients with Minnesota high-risk GVHD. Combining ST2, REG3α, and AREG into a single algorithm did not improve performance.