Citations

Abstract Introduction Distinct temperature patterns have long been recognized to correlate with fevers of differing etiologies. While the use of wearable sensors for high-frequency temperature monitoring (HFTM) on a near minute-by-minute basis has been shown to detect fevers earlier than standard-of-care nursing vital sign assessments in hospitalized patients, leveraging these high-resolution datasets to computationally identify unique digital signatures for real-time diagnosis of underlying fever etiology has not been widely explored. Diagnostic uncertainty is common in patients undergoing hematopoietic stem cell transplantation (HCT), with only 20–30% of febrile neutropenic episodes being microbiologically documented. We hypothesized that unique temperature patterns extracted from HFTM data collected during episodes of febrile neutropenia could be used to develop a supervised machine learning classifier capable of accurately predicting underlying fever etiology in HCT patients. Methods We analyzed 68 clinically independent fever episodes recorded in HCT patients (n=90) outfitted with an FDA-cleared wireless temperature sensor (TempTraq®, BlueSpark Technologies) that measured axillary temperature every 2 minutes throughout hospitalization. Time-series features were extracted from temperature traces spanning 1 hour before to 3 hours after fever onset and used to train a suite of machine-learning models to distinguish engraftment fevers from other fever etiologies. Model training and evaluation were performed using repeated stratified 5-fold patient-level cross-validation, yielding 100 train-test evaluations. Results Among all classification models, the logistic regression classifier provided the best overall performance and interpretability, achieving 94% specificity (95% CI, 0.84–1.0) for identifying engraftment fevers with a mean AUROC of 0.88 ± 0.10. Feature importance analysis demonstrated that both clinical variables and HFTM-derived temperature dynamics contributed to model performance, with a strong reliance on time-series features captured within the first 4 hours of fever onset. Conclusion Our study provides a demonstration that continuous temperature data collected from patients outfitted with wearable sensors can be leveraged not only for early fever detection but also for machine learning–based diagnosis of fever etiology. These findings suggest that dynamic temperature patterns contain clinically meaningful physiologic information that with further studies could support real-time diagnostic decision-making and guide safe de-escalation of empiric antibiotics during febrile neutropenia in patients undergoing intensive cancer therapy.

Abstract Polygenic risk scores (PRSs), which quantify inherited susceptibility to complex traits and diseases, have emerged as valuable tools for risk stratification and precision medicine. Despite their promise, PRS developed on European cohorts often demonstrate substantially reduced predictive accuracy in non-European populations, due to differences in genetic architecture. The disproportionate representation of European ancestry cohorts in genome-wide association studies (GWAS) leads to inequitable deployment of PRS technologies across diverse populations. Here, we introduce PRANA (Polygenic Risk Adaptation via Neural-network Architecture), a deep learning framework that adapts an existing PRS developed on one population to other ancestries. Unlike methods that require large-scale GWAS in the target population, PRANA leverages pre-trained PRS models derived from European cohorts and adapts them using modestly sized cohorts from the target population. We evaluated PRANA on seven complex traits in South Asian, East Asian and Ashkenazi Jewish populations, as well as in selected smaller East Asian subpopulations where the scarcity of training data poses a particular challenge. PRANA mostly improved predictive performance of the baseline PRS models by 5%-20% in terms of effect size (β) and Nagelkerke’s R², and, in most cases, outperformed existing cross-ancestry multi-PRS approaches. These results highlight PRANA as a scalable and practical strategy to reduce disparities in genomic risk prediction and advance the equitable application of PRS in diverse populations.

Abstract Endocytosis regulates receptor trafficking and signaling, yet its role in colorectal cancer (CRC) remains unclear. We analyzed transcriptomic data from 15,025 CRC tumors to evaluate gene expression in clathrin-mediated endocytosis (CME) and the endosomal sorting complexes required for transport (ESCRT) pathway. Pathway-level signatures were compared across consensus molecular subtypes (CMS) and examined in relation to oncogenic signaling programs, while individual endocytosis-related genes were evaluated for associations with clinical outcomes in an independent randomized trial cohort. Expression of CME and ESCRT pathways varied by CMS, with the highest expression in CMS4 and the lowest in CMS3. Endocytosis signatures correlated with multiple oncogenic signaling pathways, including MAPK, TGF-β, WNT, PI3K, NOTCH, and angiogenesis, suggesting broad links between endocytic activity and tumor biology. In the randomized phase III CALGB/SWOG 80405 trial, low expression of AP2M1 —a core adaptor in the CME complex—was significantly associated with longer overall survival and progression-free survival in patients treated with anti-EGFR agents, but not in those receiving anti-VEGF agents. These findings suggest that endocytic trafficking may be associated with oncogenic signaling and differential therapeutic benefit in patients with metastatic CRC. The endocytosis pathway reflects biologically relevant heterogeneity in CRC and may help guide therapeutic stratification.

Autonomous robotic-assisted surgery (RAS) has emerged as a promising objective in biomedical technology, further enhanced by miniaturization toward microrobotic-assisted surgery (μ-RAS). This reduction in scale promises minimally invasive, partially or fully automated surgical procedures, with the potential to reduce patient recovery times, lower medical costs, and enable previously unavailable procedural options. This perspective highlights the specific advances in RAS that potentially map to the microscale (μ-RAS), organized across five surgical domains: endovascular, endoluminal, laparoscopic, ophthalmic, and orthopedic. We examine both clinical demands and technological advances in surgical robotics and identify the key innovations required for progress across these surgical fields. Our contribution is distinct in combining the perspectives of both surgical experts and bioengineering innovators, outlining a roadmap for the advancement and eventual integration of autonomous RAS and μ-RAS into mainstream surgical practice.

4122 Background: BTCs are rare and aggressive malignancies. The first-line standard of care regimen for advanced BTC (aBTC) is gemcitabine (GEM), cisplatin, and an immune checkpoint inhibitor. Although FOLFOX is a preferred second-line treatment, it is limited by neuropathy. Nal-IRI contains IRI free base in liposome nanoparticles, which shelter IRI from conversion to its active metabolite (SN-38) and increase intratumoral SN-38 compared with IRI alone. The NAPOLI-1 trial of FU/LV/nal-IRI vs. FU/LV in second-line advanced pancreatic adenocarcinoma showed an overall survival (OS) benefit. The NIFTY trial (South Korea) demonstrated median OS (mOS) benefit of FU/LV/nal-IRI over FU/LV in a second-line aBTC population (8.6 vs. 5.3 months [mo], HR 0.68, 95% CI 0.48-0.95); however, the NALIRICC trial (Germany) did not (6.9 vs. 8.2 mo, HR 1.08, 95% CI 0.68-1.72). We sought to characterize second-line FU/LV/nal-IRI efficacy in US patients (pts) with second-line aBTC. Methods: This was a single-arm, open-label, multicenter phase II study of pts with aBTC previously treated with GEM/platinum chemotherapy. Pts received nal-IRI 70 mg/m 2 IV over 90 minutes, LV 400 mg/m 2 IV over 30 minutes every 14 days, and FU 2400 mg/m 2 IV over 46 hours every 14 days. The primary objective was to determine progression-free survival rate at 4 mo (PFS 4mo ) using RECIST v. 1.1 criteria. Median PFS reported for pts receiving second-line 5-FU doublet chemotherapy was 3 mo with a PFS of 30%. FU/LV/nal-IRI was of interest if it could increase the PFS 4mo to 50% or higher. Using a one-sided α of 0.05 and 80% power, 17 of 39 evaluable pts had to be progression-free at 4 mo to detect a difference in PFS 4mo between 30% and 50%. Results: Forty-eight pts were enrolled: median age 64.5 years; 69% women; 27% gallbladder primary; 54% intra- and 19% extrahepatic. Ten pts came off study due to toxicity without disease progression before 4 mo on study and were replaced to evaluate the PFS 4mo endpoint. Of 38 evaluable pts, 18 pts (PFS 4mo 47%) were alive and progression-free at 4 mo, meeting the primary endpoint. With a median follow-up of 7.1 mo, median time to disease progression or study discontinuation due to toxicity for all pts was 2.3 mo (95% CI 1.8-4.6, PFS 4mo 38%), and for pts evaluable for the primary endpoint, median PFS was 3.5 mo (95% CI 1.8-5.5). Five pts (10%) had PFS beyond 12 mo. mOS for all pts was 7.9 mo (95% CI 5.7-11.7). Of 41 evaluable pts, the response rate was 2% (1 PR), and the disease control rate was 54%. Adverse events (AEs) were consistent with known toxicities from the FU/LV/nal-IRI regimen. Conclusions: FU/LV/nal-IRI is an effective second-line regimen for aBTC in US pts. There was significant early toxicity as 21% of pts came off study due to AEs before 4 mo. Correlative studies, including longitudinal analyses of circulating tumor DNA using banked blood specimens, are planned (NCT04005339). Clinical trial information: NCT04005339 .

OBJECTIVE Protocols for intraoperative mapping during awake craniotomy vary widely. The aim of this study was to evaluate how the number and type of intraoperative neuropsychological paradigms administered via NeuroMapper, a tablet-based platform, during awake glioma surgery affect positive mapping rates, return to work (RTW), and oncological outcomes. Factors associated with the operative duration and early postoperative neurological deficits were of additional interest. METHODS This single-center retrospective study included patients with diffuse low- and high-grade gliomas who underwent awake craniotomy with NeuroMapper-guided mapping between 2018 and 2024. Primary outcomes were RTW, progression-free survival (PFS), and overall survival (OS); operative duration and early postoperative deficits were secondary outcomes. Covariate balancing propensity score (CBPS) analysis was used to address confounding by tumor grade, with all postweighting standardized mean differences < 0.10. A weighted logistic regression model assessed RTW, and CBPS-weighted Cox models assessed PFS and OS. Linear regression was used to analyze intraoperative variables, operative duration, and early postoperative deficits. RESULTS Of 189 patients included in the analysis, 65 had LGG (median age 39 years) and 124 had HGG (median age 56 years). Mapping complexity varied, with 1–6 tasks used (median 4). Weighted multivariate logistic regression analysis identified the following independent predictors of RTW: preoperative Karnofsky Performance Status score ≥ 80 (OR 1.37, p = 0.039), absence of recurrent disease (OR 0.30, p < 0.001), use of 5–6 paradigms (OR 1.54, p = 0.047), positive mapping (OR 2.41, p = 0.017), and subtotal resection (OR 4.43, p = 0.002). Intraoperative seizure, early postoperative deficit, and the resection technique were not significant. IDH mutation status was associated with improved PFS (HR 0.15, p < 0.001), while subtotal resection was associated with worsened PFS (HR 3.00, p < 0.001). Positive mapping was associated with better OS (HR 0.57, p = 0.04). The operative duration was unaffected by mapping variables but was longer in patients with obesity (β = 0.28, p = 0.038). CONCLUSIONS Positive NeuroMapper-guided mapping of more diverse linguistic functions was associated with RTW and longer OS. Additionally, mapping complexity did not prolong surgery times, supporting potential standardization.

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.

ABSTRACT The World Health Organization (WHO) 5th Edition and International Consensus Classification (ICC) have continued to delineate more genetically defined acute leukemias. Both recognize genetic aberrations associated with myelodysplastic syndromes/neoplasms (MDS) as defining MDS‐related AML (AML‐MR). Mutations in RUNX1 are included in this category in the ICC, but not WHO. The current classifications are unclear on how acute leukemias with ambiguous lineage (ALAL), including those of mixed lineage (MPAL) and those without a defined lineage (AUL), should be categorized in the presence of such mutations. Our multi‐institutional study aims to determine the significance of RUNX1 mutation in ALAL compared to de novo AML. Newly diagnosed MPAL, AUL, and AML with RUNX1 mutations were collected. ALAL with MDS‐related cytogenetics, BCR::ABL1 , KMT2A rearrangements, or ZNF384 or BCL11b abnormalities were excluded. We analyzed 17 cases of ALAL and 71 cases of AML that met inclusion criteria. ALAL‐ RUNX1 and AML‐ RUNX1 showed overlapping mutational landscapes with frequent comutations in MDS‐associated genes. No ALAL‐ RUNX1 or AML‐ RUNX1 cases showed concomitant TP53 mutation. ALAL‐ RUNX1 had more bone marrow blasts and more karyotypic abnormalities; however, neither impacted survival, nor did RUNX1 variant allele frequency (VAF). Survival analysis revealed similarly poor outcomes between them. AML‐directed therapies and allogeneic hematopoietic stem cell transplant trended toward improved survival in ALAL‐ RUNX1; however, it did not reach significance. Our results suggest ALAL‐ RUNX1 is associated with younger age, higher blasts, and more karyotypic abnormalities, but has similar clinical and genetic features and outcomes to AML‐ RUNX1 . Our findings suggest, like other MR mutations, RUNX1 ‐mutated ALALs should be included within AML‐MR.