Citations

Abstract Pancreatic adenocarcinoma remains one of the most lethal malignancies, primarily due to its robust resistance to genotoxic therapies, such as chemotherapy and radiotherapy. Understanding the mechanisms underlying this resistance is essential to improve clinical outcomes. In this study, we identified trimethylguanosine synthase 1 (TGS1), previously known for its role in RNA modification, as a critical mediator of homologous recombination (HR) repair that specifically contributes to resistance in pancreatic adenocarcinoma. TGS1 was significantly overexpressed in pancreatic adenocarcinoma tissues, correlating strongly with advanced disease stages, therapy resistance, and poor patient prognosis. Following DNA damage, ATM kinase phosphorylated TGS1 at serine residues S389 and S531, which mediated its direct interaction with BRCA1 and subsequent recruitment of BRCA1 to DNA damage sites. The phosphorylation-dependent interaction enhanced HR repair efficiency, enabling cancer cells to survive genotoxic stress. Depletion or pharmacologic inhibition of TGS1 induced HR deficiency and markedly enhanced sensitivity to DNA-damaging agents, particularly PARP inhibitors, in pancreatic adenocarcinoma cell lines in vitro and in both cell line– and patient-derived xenograft models in vivo. Collectively, these findings uncover an ATM–TGS1–BRCA1 signaling axis that promotes DNA repair and resistance to genotoxic therapies in pancreatic cancer, positioning TGS1 as a promising predictive biomarker and therapeutic target to enhance treatment efficacy. Significance: The ATM–TGS1–BRCA1 signaling axis is a critical regulator of DNA repair that can be targeted to overcome genotoxic therapy resistance, providing a promising therapeutic strategy that could transform pancreatic cancer treatment.

Background The Woven EndoBridge (WEB) device represents an innovative solution for cerebral aneurysm occlusion, particularly for challenging wide-neck bifurcation aneurysms. However, factors affecting sustained occlusion remain poorly understood. We utilized machine learning to attempt to identify predictors of favorable long-term outcomes following WEB treatment. Methods In this multicenter retrospective study, we collected patient demographics, aneurysm characteristics, procedural details, and clinical outcomes. The primary endpoint was improvement in occlusion status, defined as maintained Raymond-Roy Occlusion Classification (RROC) grade 1, or improvement from grade 2 to 1, or from grade 3 to either 2 or 1 on final angiographic follow up. The dataset was split into training (75%) and validation (25%) sets. The CatBoost algorithm was selected based on performance metrics, with Shapley Additive exPlanations (SHAP) values calculated to determine feature importance. Furthermore, a multivariable binomial logistic regression model was performed to validate machine learning findings. Results Among 720 aneurysms from 36 hospitals, 84% showed improvement in occlusion at follow up. Both machine learning and multivariable logistic regression identified aneurysm height as the most consistent correlate of nonimprovement (odds ratio (OR) 0.90 per mm, p = 0.022). In the CatBoost model, the highest-ranking features by SHAP included aneurysm height, patient age, treatment acuity, ACom location, WEB-SLS device, bifurcation anatomy, aneurysm multiplicity, baseline modified Rankin Scale, access route, and partial thrombosis. Conclusions Machine-learning and regression analyses identified consistent predictors of occlusion improvement after WEB treatment, with aneurysm height most strongly linked to nonimprovement. These insights may guide patient selection and follow up. Findings require cautious interpretation and external validation in larger cohorts.

Acute exposure to hypoxia will induce right ventricular (RV) hemodynamic changes and may increase the degree of right-to-left shunting, which can contribute to dyspnea at altitude. In this retrospective study, 125 patients (median age 66 years; 50.4% women) with unexplained dyspnea at altitude underwent hypoxic simulation testing (HST) with transthoracic echocardiography (TTE). During simulated hypoxia (mode (Min-Max) altitude: 8000 (6000–18,000) ft, were observed a significant decrease in oxygen saturation (97% (95–98) vs. 88% (82–92), p < 0.001) and RV free wall longitudinal strain (−19.6 ± 3.99% vs. −17.3 ± 4.17%, p < 0.01), an increase in RV systolic pressure (RVSP: 26 (23–30.5) vs. 29 (25–36.5) mmHg, p < 0.001). No significant changes were observed in TAPSE (20 (18–23) vs. 20 (19–24) mm) or S wave (0.12 (0.11–0.14) vs. 0.13 (0.12–0.14) m/s). Right-to-left shunting was present in 47.2% of patients and 11.9% exhibited inducible shunting only under hypoxia. However, under hypoxia, there were no significant differences in RV hemodynamic parameters or saturation between those with and without shunting. TTE with HST is useful to characterize both cardiopulmonary response and the dynamic changes in right-to-left shunt behavior under hypoxic stress.

Background This narrative review establishes the current state of the art of machine learning approaches for prediction of migraine attacks. Related concepts are highlighted including the identification of triggers or premonitory symptoms and methods for evaluating prediction models. Existing efforts at machine learning prediction of individual migraine headaches and attacks are reviewed in detail. Challenges in this task are discussed. Results A variety of input data and modeling approaches have been used. It is consistently found that individualized models provide better results compared to a generalized model and achievable performance varies considerably between individuals. Patient needs should be assessed to discover what a valuable prediction looks like. The field should develop common standards for evaluating migraine prediction algorithms. Conclusions/Interpretations While the problem is far from solved there is great potential and reason to believe that feasible solutions that improve the quality of life of those with migraine are within our grasp.

Abstract Purpose: Relapse is a major cause of failure in human papillomavirus–independent head and neck squamous cell carcinoma. Clinicopathologic criteria for adjuvant treatment remain imprecise and have not changed for decades. We investigated whether ctDNA in lymphatic exudate collected via surgical drains (“lymph”) 24 hours after surgery identified molecular residual disease (MRD) and compared its performance with time-matched plasma. Experimental Design: Using an ultra-sensitive tumor-informed sequencing approach, tumor variants were called in lymph and plasma to classify patients as ctDNA positive or ctDNA negative, trained in an initial cohort of 36 patients, and replicated in an independent cohort of 37 patients. Progression-free survival was compared in ctDNA(+) versus ctDNA(–) patients. Results: Lymph identified MRD in two independent multi-site cohorts (initial cohort sensitivity = 76% and specificity = 63%; log-rank P = 0.01; replication cohort sensitivity = 65% and specificity = 70%; log-rank P = 0.04). Lymph performance was enhanced in locoregional relapse (sensitivity = 78% and specificity = 67%; log-rank P = 0.0004) and generalized to early-stage patients. Analysis of matched plasma collected at this early timepoint was not predictive of recurrence (sensitivity = 35% and specificity = 72%; log-rank P = 0.7). In patients with intermediate-risk pathology, lymph ctDNA was associated with recurrence (sensitivity = 88% and specificity = 67%; log-rank P = 0.0008), suggesting an opportunity for improved stratification of patients who may benefit from additional adjuvant treatment. Conclusions: Postoperative lymph is a novel, proximal, and early source of MRD with the potential to introduce more precision into adjuvant therapy decision-making and improve outcomes, especially for patients with intermediate-risk human papillomavirus–independent head and neck squamous cell carcinoma.

Importance Validation of prognostic tools is an essential component of their integration into clinical practice. Objective To validate 4 delirium risk stratification tools in an independent emergency department (ED) cohort. Design, Setting, and Participants This prognostic study included a retrospective cohort of patients 65 years or older who presented to an academic ED between January 1, 2021, and December 31, 2024. Data were analyzed from February 10 to August 21, 2025. Exposure Delirium screening included the Delirium Triage Screen followed by the brief Confusional Assessment Method as part of the standard of care. Four delirium risk scores were obtained, including the Kennedy rule, the Zucchelli rule, the Mayo Delirium Prediction (MDP) tools, and the Recognizing Delirium in Emergency Medicine (REDEEM) score. Main Outcomes and Measures Main outcomes included risk score performances and diagnostic test accuracy measured using the area under the receiver operating characteristics curve (AUROC), sensitivity, specificity, negative (NPV) and positive (PPV) predictive values, and positive and negative likelihood ratios (LRs) with 95% CIs. Secondary outcomes were discriminative and calibration measures. Results A total of 44 578 patients were included, of whom 1701 (3.8%) were diagnosed with delirium. The median age was 80.0 (IQR, 75.0-85.0) years, and 22 786 patients (51.1%) were female. The Kennedy rule had an AUROC of 0.777 (95% CI, 0.766-0.789). At a cutoff of 5, sensitivity was 0.55 (95% CI, 0.52-0.57); specificity, 0.85 (95% CI, 0.84-0.85); positive LR, 3.54 (95% CI, 3.37-3.72); negative LR, 0.54 (95% CI, 0.51-0.57); PPV, 0.12 (95% CI, 0.12-0.13); and NPV, 0.98 (95% CI, 0.98-0.98). The Zucchelli tool had an AUROC of 0.701 (95% CI, 0.686-0.713). At a cutoff of 5, sensitivity was 0.68 (95% CI, 0.66-0.70); specificity, 0.66 (95% CI, 0.65-0.66); positive LR, 1.99 (95% CI, 1.92-2.06); negative LR, 0.49 (95% CI, 0.45-0.52); PPV, 0.07 (95% CI, 0.07-0.08); and NPV, 0.98 (95% CI, 0.98-0.98). The MDP tool had an AUROC of 0.898 (95% CI, 0.891-0.905). At a 30% cutoff, sensitivity was 0.51 (95% CI, 0.48-0.53); specificity, 0.95 (95% CI, 0.95-0.95); positive LR, 9.69 (95% CI, 9.11-10.31); negative LR, 0.52 (95% CI, 0.50-0.55); PPV, 0.28 (95% CI, 0.26-0.29); and NPV, 0.98 (95% CI, 0.98-0.98). The REDEEM score demonstrated the highest AUROC at 0.921 (95% CI, 0.914-0.929). Using a cutoff of 11 or greater, sensitivity was 0.83 (95% CI, 0.81-0.85); specificity, 0.92 (95% CI, 0.91-0.92), negative LR, 0.18 (95% CI, 0.17-0.20); positive LR, 9.91 (95% CI, 9.54-10.29); PPV, 0.28 (95% CI, 0.27-0.29); and NPV, 0.99 (95% CI, 0.99-0.99). Conclusions and Relevance In this prognostic study comparing 4 delirium tools to improve delirium detection and identify high-risk patients, the REDEEM score and the MDP tool had better performance for delirium detection in the ED. These findings lay the groundwork for integrating validated risk stratification into ED workflows to improve early delirium detection and inform prevention strategies for high-risk older adults.

The goal in selecting these recent articles was to help identify literature that may change the clinical practice of women’s health for practitioners in the primary care setting. Articles were identified by reviewing the high-impact medical and women’s health journals, national guidelines, ACP JournalWise, and NEJM Journal Watch. In this Clinical Update, we selected recent publications relevant to the cardiovascular health of women.

Importance The Breast Cancer Index (BCI) previously identified premenopausal patients with tumors in which the ratio of expression of HOXB13 relative to IL17BR (hereafter, BCI [H/I]–low tumors) as likely to derive greatest benefit from ovarian function suppression (OFS)–containing adjuvant therapy in the Suppression of Ovarian Function Trial (SOFT) trial. Objectives To assess BCI as a predictive biomarker of benefit from exemestane plus OFS vs tamoxifen plus OFS and to validate BCI as a prognostic biomarker for premenopausal patients. Design, Setting, and Participants This prognostic study used a prospective-retrospective translational design within the Tamoxifen and Exemestane (TEXT) and SOFT trials (enrolled November 2003 to April 2011). Blinded BCI testing in all available tumor samples was completed in March 2024. Premenopausal women with hormone receptor–positive breast cancer randomized to tamoxifen plus OFS or exemestane plus OFS who had BCI assessed were included. Analysis occurred from March to August 2024. Exposure 5 years of adjuvant tamoxifen plus OFS or exemestane plus OFS. Main Outcomes and Measures The primary outcomes were breast cancer-free interval (BCFI) for predictive analyses and distant recurrence-free interval (DRFI) for prognostic analyses after a median follow-up of 13 years in the TEXT cohort. Secondary objectives examined the predictive performance of BCI (H/I) in the combined TEXT and SOFT cohort overall and in prespecified clinical subgroups. Results Of 1782 patients in the TEXT study, 1034 (58.0%) had BCI (H/I)–low tumors; 915 (51.3%) of patients had N0 disease and 1077 (60.4%) were younger than 45 years. Patients with BCI (H/I)–low tumors had a 6.6% absolute benefit in 12-year BCFI (HR, 0.61; 95% CI, 0.44-0.85) for exemestane plus OFS vs tamoxifen plus OFS, while those with BCI (H/I)–high tumors had a 6.3% absolute benefit (HR, 0.78; 95% CI, 0.57-1.07; P for interaction = .29). Results were consistent in the combined TEXT plus SOFT cohort (2896 patients) and adjusting for clinicopathological variables. Clinical subgroup analyses consistently showed benefit of exemestane plus OFS vs tamoxifen plus OFS for BCI (H/I)–low tumors, and more variable relative treatment effects among BCI (H/I)–high tumors, including by age. Post hoc exploratory time-varying estimates suggested the treatment × BCI associations may differ in years 0 to 5 vs greater than 5 years. BCI and BCI N+ as continuous indices were prognostic for distant recurrence in N0 (HR, 1.27; 95% CI, 1.11-1.44; P &amp;lt; .001) and N1 (HR, 1.58; 95% CI, 1.21-2.05; P &amp;lt; .001) cancers. The 12-year DRFI was 96.3%, 90.3%, and 84.9% for BCI low-, intermediate-, and high-risk N0 cancers, respectively. Conclusions and Relevance In this study of premenopausal women with hormone receptor–positive breast cancer, BCI (H/I) status did not clearly predict greater benefit of adjuvant exemestane plus OFS vs tamoxifen plus OFS for women with BCI (H/I)–low tumors than for those with BCI (H/I)–high tumors; BCI continuous indices were reconfirmed as prognostic for premenopausal women. These findings support prior results of SOFT, which compared tamoxifen-alone vs OFS with either exemestane or tamoxifen, indicating premenopausal patients with BCI (H/I)–low tumors may benefit from more intensive endocrine therapy.

Importance Primary brain and central nervous system cancer (collectively referred to as CNS cancer) comprises 2% of all human cancers and poses significant health and economic challenges in the United States. Objective To analyze CNS cancer burden in the US, stratified by time, location (state and division), sex, age group, and Sociodemographic Index (SDI). Design, Setting, and Participants This cross-sectional study involved a repeated analysis of Global Burden of Disease Study (GBD) 2021 data in 2024. Using data from 183 sources, CNS cancer metrics in the US were estimated across states and years. US CNS cancer metrics across all sexes and age groups were included in the GBD. Exposure CNS cancer diagnosis. Main Outcomes and Measures Overall and age-standardized estimates of the incidence, prevalence, mortality, disability-adjusted life-years (DALYs), years of life lost, and years lived with disability per 100 000 population, including 95% uncertainty intervals (UIs), and time trends. Results In 2021, for all age groups and sexes across the US, there were 31 780 incident cases (95% UI, 29971.1 to 32843.9). Age-standardized incidence, DALYs, and mortality rates per 100 000 population were 6.91 (95% UI, 6.58 to 7.12), 134.38 (95% UI, 129.83 to 137.95), and 4.1 (95% UI, 3.87 to 4.22), respectively. Despite no significant change observed in the overall incidence between 1990 and 2021, DALY and mortality rates decreased by 15.77% (95% UI, −17.75% to −13.68%) and 8.41% (95% UI, −11.09% to −6.22%), respectively. Substantial geographic variability was noted. Mississippi, Alabama, Kentucky, and Kansas (West North Central and East South Central divisions) and West Virginia faced persistently high burdens over the past 30 years. Sex differences were evident; disease burden was consistently higher in males compared with females. Age-specific estimates showed a bimodal distribution: the youngest group (&amp;lt;5 years) showed a significant decrease in incidence rate (−34.42% to −11.56%), whereas older age groups (&amp;gt;70 years) experienced increasing trends. DALYs and mortality rates were negatively correlated with SDI (ρ = −0.6860 and ρ = −0.6391; P &amp;lt; .001). Conclusions and Relevance These findings provide valuable insights into the CNS cancer burden across the US by age, sex, location, and SDI, enabling better public health status assessments, health care policy restructuring, and resource redistribution for improved care.

Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case–control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62–1.64, AUC = 0.551–0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94–0.99, AUC = 0.523–0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.