Citations

Abstract Currently, the role of DNA methylation in the immunoglobulin M (IgM) monoclonal gammopathy disease spectrum remains poorly understood. In the present study, a multiomics prospective analysis was conducted integrating DNA methylation, RNA sequencing (RNA-seq), and whole-exome sequencing data in 34 subjects (23 with Waldenström macroglobulinemia [WM], 6 with IgM monoclonal gammopathy of undetermined significance [MGUS], and 5 normal controls). Analysis was focused on defining differences between IgM gammopathies (WM/IgM-MGUS) compared with controls, and specifically between WM and IgM-MGUS. Between groups, genome-wide DNA methylation analysis demonstrated a significant number of differentially methylated regions that were annotated according to genomic region. Next, integration of RNA-seq data was performed to identify potentially epigenetically deregulated pathways. We found that pathways involved in cell cycle, metabolism, cytokine/immune signaling, cytoskeleton, tumor microenvironment, and intracellular signaling were differentially activated and potentially epigenetically regulated. Importantly, there was a positive enrichment of the CXCR4 signaling pathway along with several interleukin (interleukin 6 [IL-6], IL-8, and IL-15) signaling pathways in WM compared with IgM-MGUS. Further assessment of known tumor suppressor genes and oncogenes uncovered differential promoter methylation of several targets with concordant change in gene expression, including CCND1 and CD79B. Overall, this report defines how aberrant DNA methylation in IgM gammopathies may play a critical role in the epigenetic control of oncogenesis and key cellular functions.

e19049 Background: Acala and zanu are 2nd generation Bruton tyrosine kinase inhibitors (BTKis) that have demonstrated improved safety profiles vs 1st generation BTKi ibrutinib in clinical trials. While head-to-head comparison of zanu vs acala is lacking, a recent meta-analysis of clinical trials provided a comprehensive, indirect comparison of the AE profiles in B-cell malignancies (Hwang, Hemasphere. 2023;7(S3):1134). This study aims to evaluate costs and impacts on quality of life (QoL) for zanu vs acala using their AE profiles. Methods: A health economic model was developed to determine cost and QoL associated with AE management for zanu and acala. The incidence rates ( IRs) of all grade and grade ≥3 AEs of interest (n=21, including bleeding events, hypertension, atrial fibrillation, cytopenias, infections, headache, arthralgia, diarrhea) were taken from the meta-analysis. Additional model inputs, such as disutility, average duration of AE, and unit cost of each AE were sourced from published literature and publicly available cost databases in consultation with clinical experts. The model was developed from the US perspective, considering Medicare costs, inflated to 2023 USD. Model outcomes were AE management cost (= IR * unit cost) and quality-adjusted life years (QALYs) lost due to AE (= IR * Disutility * Duration/365.25). Results: In the base-case scenario (considering all AEs), treating a hypothetical cohort of 1000 patients (pts) with zanu instead of acala yielded cost savings of $124K and 3.7 QALY gains (i.e., 3.7 years extra in full health). Subgroup analysis for severe (grade ≥3) and non-severe AEs (grade 1-2) demonstrated similar trends. A sensitivity analysis limited to AEs significantly different between zanu and acala (n=13) yielded consistent results. Additionally, a probabilistic sensitivity analysis, conducted with 1000 iterations to account for uncertainty in model parameters, confirmed robustness of the model, indicating stable conclusions across a wide range of parameter uncertainties. Conclusions: This analysis suggested that zanu is cost-saving and associated with added health benefits compared to acala in terms of AE management in pts with B-cell malignancies. Should these results derived from meta-analysis of clinical trial data be applicable to real-world pt populations across different indications, the potential cost savings could be considerable. These results could be further improved if the differences in efficacy of zanu vs acala are also incorporated. [Table: see text]

AbstractBackgroundSeveral organizations have proposed guidelines or clinical decision tools for the management of patients with disorders of gut‐brain interactions (DGBI) affecting the lower digestive tract including irritable bowel syndrome and chronic idiopathic constipation. Such algorithms are based on sequential therapeutic trials and modifying the treatment strategy based on efficacy and adverse events.PurposeThe aims of this review are to evaluate the evidence for efficacy of second‐ and third‐line pharmacotherapies and to assess the evidence for the alternative option to manage subgroups of patients with symptoms suggestive of lower DGBI based on diagnostic tests or documented dysfunctions. The preeminent tests to identify such subgroups that present with symptoms that overlap with lower DGBI are detailed: digital rectal examination as well as anorectal manometry and balloon expulsion for evacuation disorders, detailed measurements of colonic transit, and diagnosis of bile acid diarrhea or carbohydrate malabsorption based on biochemical measurements. The review also addresses the cost implications of screening to exclude alternative diagnoses and the costs of therapy associated with the therapeutic options following an algorithmic approach to treatment from the perspective of society, insurer, or patient. Finally, the costs of the diagnostic tests to identify actionable biomarkers and the evidence of efficacy of individualized therapy based on formal diagnosis or documentation of abnormal functions are detailed in the review.

Abstract Objectives The surge in patient portal messages (PPMs) with increasing needs and workloads for efficient PPM triage in healthcare settings has spurred the exploration of AI-driven solutions to streamline the healthcare workflow processes, ensuring timely responses to patients to satisfy their healthcare needs. However, there has been less focus on isolating and understanding patient primary concerns in PPMs—a practice which holds the potential to yield more nuanced insights and enhances the quality of healthcare delivery and patient-centered care. Materials and Methods We propose a fusion framework to leverage pretrained language models (LMs) with different language advantages via a Convolution Neural Network for precise identification of patient primary concerns via multi-class classification. We examined 3 traditional machine learning models, 9 BERT-based language models, 6 fusion models, and 2 ensemble models. Results The outcomes of our experimentation underscore the superior performance achieved by BERT-based models in comparison to traditional machine learning models. Remarkably, our fusion model emerges as the top-performing solution, delivering a notably improved accuracy score of 77.67 ± 2.74% and an F1 score of 74.37 ± 3.70% in macro-average. Discussion This study highlights the feasibility and effectiveness of multi-class classification for patient primary concern detection and the proposed fusion framework for enhancing primary concern detection. Conclusions The use of multi-class classification enhanced by a fusion of multiple pretrained LMs not only improves the accuracy and efficiency of patient primary concern identification in PPMs but also aids in managing the rising volume of PPMs in healthcare, ensuring critical patient communications are addressed promptly and accurately.

ObjectivesThere have been significant advances in the management of large (≥20 mm) laterally spreading tumors (LSTs) or nonpedunculated colorectal polyps; however, there is a lack of clear consensus on the management of these lesions with significant geographic variability especially between Eastern and Western paradigms. We aimed to provide an international consensus to better guide management and attempt to homogenize practices.MethodsTwo experts in interventional endoscopy spearheaded an evidence‐based Delphi study on behalf of the World Endoscopy Organization Colorectal Cancer Screening Committee. A steering committee comprising six members devised 51 statements, and 43 experts from 18 countries on six continents participated in a three‐round voting process. The Grading of Recommendations, Assessment, Development and Evaluations tool was used to assess evidence quality and recommendation strength. Consensus was defined as ≥80% agreement (strongly agree or agree) on a 5‐point Likert scale.ResultsForty‐two statements reached consensus after three rounds of voting. Recommendations included: three statements on training and competency; 10 statements on preresection evaluation, including optical diagnosis, classification, and staging of LSTs; 14 statements on endoscopic resection indications and technique, including statements on en bloc and piecemeal resection decision‐making; seven statements on postresection evaluation; and eight statements on postresection care.ConclusionsAn international expert consensus based on the current available evidence has been developed to guide the evaluation, resection, and follow‐up of LSTs. This may provide guiding principles for the global management of these lesions and standardize current practices.

8617 Background: Dato-DXd is an antibody-drug conjugate (ADC) composed of an anti-TROP2 monoclonal antibody linked to a potent topoisomerase I inhibitor payload. We report updated findings from TROPION-Lung02 (NCT04526691) evaluating Dato-DXd plus pembro with or without Pt-CT as 1L therapy for aNSCLC. Methods: Patients (Pts) received Dato-DXd (4 or 6 mg/kg) plus pembro 200 mg alone (doublet) or with Pt-CT (triplet; cisplatin 75 mg/m2 or carboplatin AUC 5) Q3W across 6 cohorts. Pts in the expansion stage were primarily treatment (tx)-naïve. PD-L1 expression was evaluated by tumor proportion score (TPS < 50% or ≥50%) using immunohistochemistry (22C3 assay). The primary objectives were safety and tolerability, with efficacy a secondary objective. Results: 96 pts were treated with doublet (n = 42) or triplet (n = 54) therapy in the 1L setting. At data cutoff (Oct 31, 2023), 45% and 20% of pts receiving doublet or triplet tx were ongoing. Median age was 66 years in both subgroups. Median treatment durations were 6.6 and 5.8 months. Across doublet and triplet tx, the most common any-grade (Gr) treatment-emergent adverse events (TEAEs) were stomatitis (57%, 33%) and nausea (40%, 46%), mainly Gr 1–2. Gr ≥3 TEAEs were seen in 57% and 76% of pts; serious TEAEs in 38% and 44%. TEAEs associated with Dato-DXd discontinuation occurred in 29% and 39% of pts receiving doublet or triplet tx. TEAEs associated with death were seen in 2% and 9%, none considered related to study drug. Efficacy outcomes, including ORR and preliminary PFS, in the 1L setting overall and by PD-L1 status are summarized in the Table. Conclusions: As 1L therapy for aNSCLC, Dato-DXd plus pembro with or without Pt-CT continues to demonstrate durable antitumor activity. Efficacy was observed regardless of PD-L1 expression. Tolerability of the combinations was as expected based on known profiles of the individual agents, with no new safety signals observed. To date, this is the largest dataset reported for any ADC combined with an anti-PD-1/L1 agent in the 1L setting for aNSCLC. Clinical trial information: NCT04526691 . [Table: see text]

Abstract Background Few antiviral therapies have been studied in patients with coronavirus disease 2019 (COVID-19) and kidney impairment. Herein, the efficacy, safety, and pharmacokinetics of remdesivir, its metabolites, and sulfobutylether-β-cyclodextrin excipient were evaluated in hospitalized patients with COVID-19 and severe kidney impairment. Methods In REDPINE, a phase 3, randomized, double-blind, placebo-controlled study, participants aged ≥12 years hospitalized for COVID-19 pneumonia with acute kidney injury, chronic kidney disease, or kidney failure were randomized 2:1 to receive intravenous remdesivir (200 mg on day 1; 100 mg daily up to day 5) or placebo (enrollment from March 2021 to March 2022). The primary efficacy end point was the composite of the all-cause mortality rate or invasive mechanical ventilation rate through day 29. Safety was evaluated through day 60. Results Although enrollment concluded early, 243 participants were enrolled and treated (remdesivir, n = 163; placebo, n = 80). At baseline, 90 participants (37.0%) had acute kidney injury (remdesivir, n = 60; placebo, n = 30), 64 (26.3%) had chronic kidney disease (remdesivir, n = 44; placebo, n = 20), and 89 (36.6%) had kidney failure (remdesivir, n = 59; placebo, n = 30); and 31 (12.8%) were vaccinated against COVID-19. Composite all-cause mortality or invasive mechanical ventilation rates through day 29 were 29.4% and 32.5% in the remdesivir and placebo group, respectively (P = .61). Treatment-emergent adverse events were reported in 80.4% for remdesivir versus 77.5% for placebo, and serious adverse events in 50.3% versus 50.0%, respectively. Pharmacokinetic plasma exposure to remdesivir was not affected by kidney function. Conclusions Although the study was underpowered, no significant difference in efficacy was observed between treatment groups. REDPINE demonstrated that remdesivir is safe in patients with COVID-19 and severe kidney impairment. Clinical Trials Registration EudraCT 2020-005416-22; Clinical Trials.gov NCT04745351.

AbstractBackgroundIntensity Modulated Proton Therapy (IMPT) is a sophisticated radiation treatment allowing for precise dose distributions. However, conventional spot selection strategies in IMPT face challenges, particularly with minimum monitor unit (MU) constraints, affecting planning quality and efficiency.PurposeThis study introduces an innovative Two‐Stage Mixed Integer Linear Programming (MILP) method to optimize spot intensity in IMPT with Lower Bound (LB) constraints. This method seeks to improve treatment planning efficiency and precision, overcoming limitations of existing strategies.MethodsOur approach evaluates prevalent IMPT spot selection strategies, identifying their limitations, especially concerning MU constraints. We integrated LB constraints into a MILP framework, using a novel three‐phase strategy for spot pool selection, to enhance performance over traditional heuristic methods and L1 + L∞ strategies. The method's efficacy was tested in eight study cases, using Dose‐Volume Histograms (DVHs), spot selection efficiency, and computation time analysis for benchmarking against established methods.ResultsThe proposed method showed superior performance in DVH quality, adhering to LB constraints while maintaining high‐quality treatment plans. It outperformed existing techniques in spot selection, reducing unnecessary spots and balancing precision with efficiency. Cases studies confirmed the method's effectiveness in producing clinically feasible plans with enhanced dose distributions and reduced hotspots, especially in cases with elevated LB constraints.ConclusionsOur Two‐Stage MILP strategy signifies a significant advancement in IMPT treatment planning. By incorporating LB constraints directly into the optimization process, it achieves superior plan quality and deliverability compared to current methods. This approach is particularly advantageous in clinical settings requiring minimum spot number and high MU LB constraints, offering the potential for improved patient outcomes through more precise and efficient radiation therapy plans.

3588 Background: The brain-gut axis, a bidirectional network between the central and enteric nervous systems, plays a critical role in modulating the gastrointestinal tract function. Increasing evidence suggests that neuronal signaling molecules can promote gastrointestinal cancers; however, the mechanisms remain unclear. Gamma-aminobutyric acid (GABA) is a major inhibitory neurotransmitter and dysregulated GABA signaling has been found in CRC, affecting both tumor and tumor microenvironment. Here, we investigated the association between tumor GABA pathway gene expression and first-line treatment outcomes in mCRC. Methods: We evaluated the impact of the expression of 25 genes in the GABA pathway ( GABBR1, GABBR2, GABRA1, GABRA2, GABRA4, GABRA5, GABRA6, GABRB1, GABRB3, GABRD, GABRE, GABRG1, GABRG2, GABRG3, GABRQ, GABRR1, GABRR2, ABAT, ALDH5A1, GAD1, GAD2, SLC6A1, SLC6A13, SLC6A11, SLC6A12) on treatment outcomes (overall survival: OS; progression free survival: PFS) of 433 pts enrolled in the randomized, phase III CALGB/SWOG 80405 trial. RNA extracted from FFPE tumor samples was sequenced using the HiSeq 2500 (Illumina). The associations between gene expression (continuous, per standard deviation increase) and outcomes were assessed via the multivariable Cox proportional framework, with hazard ratios (HR) and 95% confidence intervals (CI) computed. The likelihood ratio test was used for interaction tests. False discovery rate (FDR) was controlled at 5% with the Benjamini-Hochberg method. Results: Overall, low GAD1 (encoding for glutamate decarboxylase 1, the enzyme responsible for catalyzing the production of GABA from L-glutamic acid) was associated with longer PFS (HR: 1.26, 95% CI [1.13, 1.41], P = 3.2E-05) and OS (HR 1.27 [1.13, 1.43], P = 5.9E-05) across all treatment arms. High ABAT (encoding for the aminotransferase responsible for GABA catabolism) was also associated with longer OS (HR 0.81 [0.72, 0.91], P = 6E-04). To evaluate the predictive value, interactions with targeted therapies bevacizumab (n = 226) vs cetuximab (n = 207) were tested. We found significant interactions for PFS with ABAT ( P= 0.0017) and OS with SLC6A13 ( P= 0.0014 ).In pts treated with cetuximab, high ABAT expression was significantly associated with longer PFS (HR 0.73 [0.61, 0.87], P = 2.8E-04), and high SLC6A13 was marginally associated with worse OS (HR 1.18 [1.00, 1.39], P = 0.052). We did not observe similar associations in pts treated with bevacizumab. Conclusions: Our results highlight a potential role for GABA signaling in affecting mCRC treatment outcomes, suggesting that GABA pathway genes may be promising novel predictive and prognostic biomarkers and supporting the rationale to investigate GABA as a target for drug development. ClinicalTrials.gov Identifier: NCT00265850