Citations

Neuromodulation is becoming a common treatment strategy for patients with drug-resistant epilepsy who are not candidates for resective surgery. Responsive neurostimulation can effectively reduce seizure burden, however it remains unclear which neural signals are most important for triggered stimulation. Furthermore, the high-dimensional parameter space remains systematically underexamined. As more patients become candidates for neurostimulation, clinical teams will need to decide on the optimal site and stimulation program for therapeutic neuromodulation. In this review, we highlight how recent insight into the biological rhythms of epilepsy may pair with personalization protocols in the emerging field of neuropsychiatric neuromodulation. Finally, we discuss future directions for epilepsy neuromodulation, specifically how machine learning can offer clinical teams actionable feedback on neuromodulation efficacy.

BACKGROUND We constructed multi-trait polygenic risk scores (PRSs) predicting chronic obstructive pulmonary disease (COPD) and exacerbations, validated their performance in diverse cohorts, and identified PRS-related proteins for potential therapeutic targeting. METHODS PRSmix + , a multi-trait PRS framework, is used to train a composite PRS (PRS multi ) in COPDGene non-Hispanic White participants ( n = 6,647). Associations of PRS multi with COPD status (GOLD 2–4 vs. GOLD 0 or ICD) and exacerbation frequency were tested in COPDGene African American ( n = 2,466), ECLIPSE ( n = 1,858), Mass General Brigham Biobank ( n = 15,152), and All of Us ( n = 118,566). Protein prediction models were applied to GWAS summary statistics from traits contributing to PRS multi and were validated with proteomic data in COPDGene ( n = 5,173) and UK Biobank ( n = 5,012). RESULTS PRSmix + selected 7 traits for PRS multi . In multivariable models, PRS multi was associated with COPD status (meta-analysis random effects [RE] OR 1.58 [95% CI: 1.28–1.94]) and exacerbation frequency (meta-analysis RE β 0.21 [95% CI: 0.11–0.31]), with higher effect sizes observed in smoking-enriched cohorts. PRS multi outperformed traditional single-trait PRS in all tested cohorts. Using protein prediction models, we identified 73 proteins associated with the PRSs that were also validated with measured protein levels in COPDGene and UK Biobank. Of these proteins, 25 were linked to approved or investigational drugs. Notable targets include RAGE/sRAGE, IL1RL1, and SCARF2, all implicated in COPD pathogenesis and exacerbations. CONCLUSIONS Multi-trait PRS improves prediction of COPD and exacerbation risk. Integration with proteomic data identifies druggable protein targets, offering a promising avenue for precision medicine in COPD management. TRIAL REGISTRATION COPDGene: ClinicalTrials.gov NCT00608764; ECLIPSE: ClinicalTrials.gov NCT00292552.

Abstract Background Proton pencil beam scanning (PBS) enables highly conformal dose distributions; however, its lateral dose fall‐off (penumbra) can be compromised by the use of range shifters (RSs) and increased air gaps. In PBS for head and neck regions, where critical organs at risk (OARs) are frequently adjacent to the target, penumbra degradation may lead to increased OAR doses or suboptimal target coverage. The integration of a dynamic multi‐leaf collimator (dMLC), which adjusts leaf positions at each energy layer, has been shown to improve dose conformity in single‐field uniform dose (SFUD) delivery. In parallel, intensity‐modulated proton therapy (IMPT) offers enhanced dose shaping over SFUD by modulating beam intensity across multiple fields and does not require a single beam to encompass the entire target volume, providing greater flexibility in utilizing dMLC capabilities. Purpose This study integrates dMLC into IMPT for head and neck cancer and proposes a novel leaf positioning strategy. We evaluate the dosimetric impact of this approach and assess its potential clinical benefits in terms of target coverage and OAR sparing. Methods Treatment plans were retrospectively created for five patients with head and neck cancer. For each patient, IMPT plans with three beam angles were generated using three techniques: (1) uncollimated PBS, (2) dMLC cover , in which the MLC encloses the target cross‐section at each energy layer, and (3) dMLC block , in which the MLC actively blocks OARs and their distal regions. Dose‐volume histogram (DVH) metrics for the clinical target volume (CTV) and OARs were evaluated, including a total of 21 perturbed scenarios that combined ± 2 mm setup uncertainties (7 scenarios) and ± 3.5% range uncertainties (3 scenarios). The accuracy of dose calculations was validated by comparing calculated and measured lateral dose distributions at the isocenter plane in water using two‐dimensional gamma analysis with a 2%/2 mm criterion. Results The integration of dMLC with IMPT significantly reduced the dose to surrounding OARs while maintaining comparable target coverage and robustness relative to uncollimated PBS. Notably, dMLC block demonstrated an enhanced dose‐sparing effect than dMLC cover , particularly for OARs surrounded by the target. While maintaining comparable CTV D98% across three techniques, dMLC cover achieved the greatest reduction in the mean doses to the eyeballs and optic nerves, as well as in the D2% to the optic chiasm, brain, and brainstem in most cases. The gamma passing rate between calculated and measured doses for dMLC block exceeded 95% for all beams, confirming the accuracy of dose calculations involving complex leaf positions. Conclusions The combination of IMPT and dMLC provides notable dosimetric advantages, supporting its potential for clinical applications. Further validation across a broader range of cases is necessary to comprehensively assess its efficacy and safety, particularly with respect to leaf positioning accuracy and potential variations in biological effectiveness.

This cohort study examines the association of bruton tyrosine kinase inhibitor therapy in B-cell malignant disease with increased risk of pericardial effusion and cardiovascular outcomes.

Importance Brain metastases are common in patients with cancer, and radiation is often used for management. Among patients with more than 4 brain metastases, the effects of stereotactic radiation targeting only individual tumors, compared with whole brain radiation with hippocampal avoidance, which radiates both tumors and normal brain, remain unknown. Objective To determine whether stereotactic radiation improves symptom severity and interference with daily functioning, compared with whole brain radiation with hippocampal avoidance. Design, Setting, and Participants Phase 3, open-label, randomized clinical trial conducted at 4 United States–based centers. Eligible patients had 5 to 20 brain metastases and no prior brain-directed radiation. Enrollment occurred between April 11, 2017, and May 17, 2024 (final follow-up, March 18, 2025). Intervention Stereotactic radiation, compared with whole brain radiation with hippocampal avoidance. Main Outcomes and Measures Mean weighted patient-reported symptom severity and interference score change over 6 months postbaseline relative to baseline using the MD Anderson Symptom Inventory–Brain Tumor instrument (scale, 0-10; score change range, −10 to 10; −10 = best). A clinically meaningful Δ was defined as 0.98. Results Of 196 randomized patients (mean age, 61 years; 129 [66%] female; 176 [90%] White; median number of brain metastases, 14 [IQR, 11-18]; 49 [25%] with prior neurosurgical resection), 83 (42%) completed the 6-month assessment. For the primary outcome, between baseline and postbaseline assessments through the 6-month follow-up, stereotactic radiation changed the weighted composite MD Anderson Symptom Inventory–Brain Tumor score from 2.69 to 2.37 (mean change, −0.32) and hippocampal-avoidance whole brain radiation changed the score from 2.29 to 3.03 (mean change, 0.74) (mean difference, −1.06 [95% CI, −1.54 to −0.58]; P < .001). Related grade 3-5 adverse events occurred in 12 patients (12%) in the stereotactic radiation group and 13 patients (13%) in the hippocampal-avoidance whole brain radiation group; grade 1-3 fatigue was most frequent (27 [28%] vs 43 [44%], respectively). Conclusions and Relevance In patients with 5 to 20 brain metastases, these findings support stereotactic radiation over hippocampal-avoidance whole brain radiation to improve symptoms and interference with daily functioning, key components of quality of life. Trial Registration ClinicalTrials.gov Identifier: NCT03075072

Abstract Background While immune checkpoint inhibitors (ICIs) provide durable clinical benefit in a subset of patients, current biomarkers to predict response lack accuracy. Ex vivo cytokine profiling has shown promise for improved accuracy but has been mostly limited to ICIs targeting PD-1 [Voabil et al, 2021]. This poses the question of whether ICIs beyond αPD-1 – such as CTLA4 blockade, which has been reported to act within the draining lymph node – would be amenable to similar approaches. The Elephas platform characterizes response to ICIs in live tumor fragments (LTFs) from core needle biopsies (CNBs) and resections using longitudinal cytokine profiling. Using a panel of 7 clinically relevant ICI regimens, we demonstrate cytokine responses across diverse tumor types, characterize similarities and differences in cytokine response profiles across different ICIs, and explore specimen variability in responses across ICI treatments. Methods CNBs were collected through 3 observational clinical trials (NCT05478538, NCT05520099, NCT0634962) and a biobank collection study, while resections were procured from NCI CHTN. LTFs were generated using an automated cutting device and encapsulated in hydrogel. LTFs were treated with mono (αPD-1, αPD-L1, αCTLA4, αLAG-3) or combination therapy (αPD-1/αCTLA4, αPD-1/αLAG-3, αPD-L1/αCTLA4) using a sequential treatment strategy in which isotype control followed by ICI were added to the same tissue in a single well. This approach enabled the comparison of control and treatment conditions while mitigating the effects of tumor heterogeneity. Production rates for 46 cytokines were measured using a multiplex assay. Remaining T-cell reactivity was also evaluated at the end of the assay to better understand the presence of functional T cells in LTFs. Results Unsupervised hierarchical clustering of cytokine profiling data from CNB LTFs across 129 patients identified defined responder and non-responder clusters. Within the response cluster, 4 subclusters with distinct immune phenotypes were identified. While tight clustering of samples treated with the same ICI was not observed, some enrichment of samples treated with combination ICIs was observed within individual subclusters. Further, cytokine responses to αCTLA4 monotherapy were observed, suggesting that CTLA4 blockade may act beyond the draining lymph node. LTFs from resections enabled the characterization of cytokine response profiles across treatment conditions within individual specimens, including the magnitude of cytokine response and variability in cytokine response profiles. Evaluation of T-cell reactivity provided further insight into the presence of functional T-cells in LTFs and the extent of T-cell activation achieved by ICI treatment. Conclusions This study demonstrates the platform’s ability to recapitulate diverse mechanisms of immune activation ex vivo, enabling the characterization of cytokine responses to clinically relevant ICI mono or combination therapy in live tumor tissue and supporting future efforts to improve ICI response prediction beyond αPD-1. Citation Format: Pichet Adstamongkonkul, Pierre Cunin, Santanu Bhattacharya, Tanmay Kulkarni, Amreen Nasreen, Nathan Marhefke, Nina Chen, T S. Ramasubramanian, Laura Hrycyniak, Julie Zweng, Erika von Euw, Christina Vivelo, Sean Caenepeel, Debabrata Mukhopadhyay, Hinco Gierman, Hilario Ramos. Characterization of αPD1, αPD-L1, αCTLA4, and αLAG3 as mono and combination therapy in live tumor fragments using an ex vivo cytokine profiling platform [abstract]. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr B032.

Sudden cardiac arrest (CA) is a leading cause of death in the United States, with coexisting chronic obstructive pulmonary disease (COPD) recognized as an independent risk factor. National trends in mortality among individuals with both conditions remain unclear. Using Centers for Disease Control and Prevention’s Wide-ranging Online Data for Epidemiologic Research (multiple cause-of-death data, we conducted a retrospective cross-sectional analysis of deaths with International Classification of Diseases, Tenth Revision codes for COPD (J41–J44) and CA (I46). Age-adjusted mortality rates (AAMRs) were calculated and stratified by race, sex, age group, census region, urbanization level, and place of death. Temporal trends were assessed using Joinpoint regression, reporting annual percent change (APC), and average annual percent change. From 1999 to 2023, a total of 853,773 deaths were recorded, with AAMRs declining from 35.48 to 22.77. The decline was steepest from 1999 to 2006 (APC: –2.77), followed by a more gradual reduction through 2021 (APC: –0.84), and a marked acceleration between 2021 and 2023 (APC: –5.52). Males consistently had higher AAMRs than females (35.41 vs 23.32). Racial disparities persisted, with non-Hispanic (NH) White (29.5) and NH Black individuals (28.16) experiencing the highest rates, followed by NH American Indians (26.17), Hispanics (22.2), and NH Asian/Pacific Islanders (17.82). Mortality was also highest in nonmetropolitan areas (31.37) and the Western region (39.68). Notably, home deaths increased following the coronavirus disease 2019 pandemic. Overall, CA-related mortality in individuals with COPD has declined over the past 25 years, with sharper reductions observed in the post-coronavirus disease period. Despite these improvements, persistent and widening disparities underscore the need for targeted interventions in high-risk populations.

Advances in cancer therapeutics have substantially improved survival across multiple malignancies but have concurrently increased the burden of cancer therapy–related cardiovascular toxicity, establishing cardio-oncology as an essential discipline situated at the interface of oncology and cardiovascular medicine. Despite growing incorporation of cardiac imaging and circulating cardiac biomarkers into surveillance strategies, current approaches remain limited by modest specificity, heterogeneous risk profiles, and inconsistent translation into effective cardioprotective interventions. This review synthesizes contemporary evidence on the biological mechanisms underlying cancer therapy–related cardiovascular toxicity and critically evaluates the current role and limitations of established cardiac biomarkers, including high-sensitivity cardiac troponins and natriuretic peptides, in risk stratification and early injury detection. We further examine why many cardioprotective clinical trials have yielded neutral or modest results, highlighting signal dilution arising from low-risk populations, endpoint heterogeneity, and timing mismatches between injury biology and intervention. This review advances a precision cardio-oncology framework by integrating tumor-derived liquid biopsy platforms—such as circulating tumor DNA, tissue-specific cell-free DNA, and extracellular vesicles—with cardiac biomarkers to provide a biologically contextualized assessment of cardiovascular risk. Tumor-derived biomarkers may reflect treatment intensity, systemic inflammatory burden, and cardiotoxic susceptibility, thereby enhancing the interpretation of cardiac biomarker signals and refining patient selection for targeted cardioprotective strategies.

Abstract Advancements in the understanding of chronic lymphocytic leukemia (CLL) have transformed patient care, leading to the development of novel targeted therapies. Traditionally, patient fitness for treatment was based on the tolerability of chemoimmunotherapy such as fludarabine–cyclophosphamide–rituximab. As the CLL patient population is predominantly older, age has historically been a major factor in how a physician selects a patient's treatment. However, as a patient's fitness goes beyond age, the definition of patient fitness should also evolve. Here, we provide suggestions for the current best practice on assessing fitness for treating CLL. Considerations for treatment include assessment of polypharmacy, history of infections, cardiovascular and renal comorbidities, functional status, cognitive and psychological status, nutritional status, and social support. The flow of assessments can start with a typical clinical evaluation followed by geriatric, cardiovascular, and renal reviews, if needed, and include collecting a patient's full history to evaluate their risk of complications with specific CLL treatments. The severity of a patient's cardiovascular profile can range from low to high risk; for those at high risk, collaboration with a cardiologist is recommended. Geriatric assessment is advised to determine baseline frailty and resilience to tolerate treatments, to avoid inappropriate treatment or undertreating patients based on chronological age, and to align the patient's fitness status with the most optimal treatment. Continuous monitoring and assessment, regardless of therapy, are recommended. Patient preferences are also integral to this decision‐making process. Looking beyond a patient's age and basing treatment selection on their fitness is key in the new era of treatment in CLL.