Lung cancer is the leading cause of death globally. Geographic disparities in rates of lung cancer may be explained by the variation and intensity of risk factors within a given area. This study aims to advance the literature on how community-level contextual factors (i.e., environmental exposures, lung disease prevalence, and socioeconomic status) contribute to the development of lung cancer. If contextual risk factors for lung cancer can be identified, interventions can be implemented early to reduce geographic disparities of lung cancer.

This study utilizes town-level lung cancer prevalence data representing 100% of traditional Medicare beneficiaries in Connecticut, Massachusetts, New Hampshire, and Rhode Island to 1) analyze geospatial trends of lung cancer and 2) identify associated community-level risk factors. Following a series of spatial-based analyses (e.g., Moran's I, Getis-Ord Gi*), a series of spatial regression models estimated the association of selected risk factors with lung cancer prevalence. All analyses were conducted in STATA 18 and ArcMap 10.8.

A total of n = 49 towns were identified as lung cancer hot spots at the 95th and 99th percentiles (p < 0.001). In regression modeling, historic releases of chromium from TRI facilities and ozone emissions, prevalence of asthma and chronic obstructive pulmonary disease (COPD), and median house values significantly predicted increased lung cancer prevalence in our sample.

This study found that the prevalence of lung cancer across communities can be explained, in part, by levels of environmental emissions, selected health, demographics and socioeconomic indicators.

Distinguishing intestinal inflammation from colorectal cancer remains challenging using non-invasive biomarkers. tRNA-derived fragments have been implicated in cancer, but their role in Crohn's disease activity and their ability to differentiate inflammatory from malignant intestinal conditions remain unclear. This study evaluated circulating tRF-Gly-GCC in patients with active Crohn's disease (n = 20), inactive Crohn's disease (n = 20), colorectal cancer (n = 24), and healthy controls (n = 21). Serum tRF-Gly-GCC expression levels showed a directional increase across disease states, from controls to inactive Crohn's disease, active disease, and colorectal cancer. A Jonckheere-Terpstra test formally confirmed a significant monotonic increase (z = 7.896, p < 0.001). The marker distinguished colorectal cancer from controls with high sensitivity (95.8%) and specificity (95.2%), and differentiated colorectal cancer from Crohn's disease with sensitivity of 95.8% and specificity of 80.0%. It also distinguished active from inactive Crohn's disease with 90% sensitivity and 90% specificity. In Crohn's disease, tRF-Gly-GCC correlated with disease activity indices but not with fecal calprotectin. These findings suggest that circulating tRF-Gly-GCC reflects intestinal inflammatory activity and may serve as a non-invasive biomarker for disease assessment and differentiation between inflammatory and malignant conditions.

Nonsteroidal anti-inflammatory drugs (NSAIDs) are recommended for mild cancer pain and can be combined with opioids for moderate-to-severe pain. The efficacy of switching from prior NSAIDs to transdermal diclofenac in patients with cancer has not been fully evaluated, however.

We conducted a retrospective observational study at the Cancer Institute Hospital, Ariake, Japan, from May 21, 2021, to May 20, 2023. Hospitalized of patients with cancer who were switched from prior NSAIDs to transdermal diclofenac were included. Patients were excluded if they never applied the patch, could not continue treatment for ≥7 days, or had dementia/delirium precluding pain assessment. The primary endpoint was change in numerical rating scale (NRS) score from baseline (Day 0) to Day 8. Statistical analyses were performed using the Wilcoxon signed-rank test, with p<0.05 considered indicative of statistically significant differences.

A total of 72 patients were included. The median age was 67 years, and 46 were female. Prior NSAIDs included loxoprofen, flurbiprofen, naproxen, and celecoxib. Concomitant opioids were used in 55 patients. Mean NRS score decreased from 3.8 to 2.4 by Day 8 (p<0.001). Forty-six patients (64%) showed reduced NRS scores. Rescue medication use decreased in 13 patients (18%), remained unchanged in 39 (54%), and increased in 20 (28%). One patient reported mild pruritus; no treatment discontinuation occurred.

Switching to transdermal diclofenac effectively reduced pain in patients with cancer and may serve as a useful alternative when oral or prior NSAID therapy is difficult to continue.

The Cirrhosis Outcome Risk Estimator (CORE) score is a novel model designed to predict the risk of liver disease. However, data regarding the prognostic utility of the CORE score in patients with resectable pancreatic ductal adenocarcinoma (R-PDAC) remain scarce. This study aimed to evaluate the utility of the CORE score as a prognostic stratification tool for R-PDAC.

We retrospectively analyzed 242 patients who underwent pancreatectomy for R-PDAC between January 2009 and December 2023. Patients were stratified into two groups based on their preoperative CORE scores. Multivariate analyses were performed to identify independent predictors of recurrence-free survival (RFS) and overall survival (OS), comparing perioperative outcomes between the groups.

Of the 242 patients, 73 (30.2%) were classified into the high CORE score group (score >0.9). Patients in the high CORE score group exhibited significantly worse five-year RFS (18.0% vs. 40.1%, p=0.001) and OS (25.9% vs. 51.0%, p=0.001) than those in the low CORE score group. Multivariate analyses identified a low CORE score as an independent predictor of RFS [hazard ratio (HR)=1.53, p=0.014] and OS (HR=1.70, p=0.004).

The CORE score is a robust, simple preoperative predictor of survival following pancreatectomy for R-PDAC.

Minimally invasive surgery (MIS), including laparoscopic and robotic approaches, is increasingly used for rectal cancer but evidence of multivisceral resection (MVR) for cT4b disease by MIS is limited. This study compared short- and long-term outcomes between patients who underwent MIS or open MVR for advanced rectal cancer.

We retrospectively analyzed 32 patients with cT4b rectal cancer who underwent rectal resection with MVR at six institutions between 2011 and 2023 (open, n=9; MIS, n=23). Operative invasiveness, postoperative complications, and 3-year survival were evaluated.

Intraoperative blood loss was lower in the MIS group than in the open group (median: 220 vs. 2,500 ml; p<0.0001). After excluding those with stage IV disease (open, n=9; MIS, n=20), pathological outcomes and 3-year survival did not differ between groups.

MIS may reduce invasiveness without compromising oncological outcomes in selected patients with cT4b rectal cancer requiring MVR.

Autonomous Robotic Ultrasound Systems (ARUS) enable standardized breast cancer screening, but accurate breast localization and the nonlinear deformation of soft tissue hinder stable contact-force control.

We propose a framework integrating visual perception with compliant control. An adaptive gradient-based edge detector extracts the nipple position, and a Variable Damping Admittance Control based on a Breast Biomechanical Model (VDAC-BBM) is developed, which compensates for tissue deformation via a biomechanical prior and dynamically tunes the damping parameter in real time to suppress force error.

Phantom and human experiments showed force tracking error ≤ 0.4 N, with disturbance recovery speed improved by 16.5%-21.3% over conventional admittance control across the tested target forces.

Embedding a biomechanical prior into the control strategy enhances force compliance and stability during robotic scanning of deformable soft tissue, providing a technical basis for clinical translation.

Realizing the promise of precision medicine will require the highest standards of accuracy in genome sequencing and analysis. Here we describe challenges and opportunities for the field through the lens of genome data quality. We present recommendations in the context of specific areas of application for genomic sequencing in which isolated standards have arisen: germline sequencing, tumour sequencing, cell-free DNA testing, and sequencing for quality control in genetic therapy. Despite these distinct clinical contexts, technical challenges are often similar; for example, accurately detecting low-frequency genetic variants in tumour sequencing or gene-edited cells. We call for increased synchronization among these communities to establish new medical genome standards that promote confidence in genomic diagnostics and genetic therapies in a time of rapid technology-driven change. We suggest practical approaches for implementing these genome standards across contexts, and identify key areas that require further development.

Artificial intelligence has transformed digital pathology by enabling biomarker prediction from high-resolution whole-slide images. However, current methods are computationally inefficient, processing thousands of redundant tiles per slide and requiring complex aggregation models. We introduce EAGLE (Efficient Approach for Guided Local Examination), a deep learning framework that emulates pathologists by selectively analyzing informative regions. EAGLE combines task-agnostic tile selection with detailed feature extraction and is benchmarked against leading slide- and tile-level foundation models across 43 tasks from nine cancer types spanning morphology, biomarker prediction, treatment response and prognosis. EAGLE outperforms patch aggregation methods by up to 23% and achieves the highest overall classification performance. It processes one slide in 2.27 s, reducing computational time by more than 99% compared with existing models. This efficiency supports rapid and auditable workflows by enabling review of the exact tiles used for each prediction and reducing dependence on high-performance computing. By reliably identifying informative regions and minimizing artifacts, EAGLE provides robust and auditable outputs, supported by systematic negative controls and attention concentration analyses. Its unified embedding enables rapid slide search, integration into multi-omics pipelines and emerging clinical foundation models.

Osimertinib, a third-generation EGFR tyrosine kinase inhibitor (TKI), has improved outcomes in non-small cell lung cancer (NSCLC) patients harboring the T790M mutation; however, emerging clinical evidence indicates a risk of cardiotoxicity. Here, we establish the first in vivo preclinical model of osimertinib-induced cardiotoxicity using transverse aortic constriction (TAC) in mice. Osimertinib treatment resulted in cardiac dysfunction, impaired hypertrophic remodeling, and increased markers of heart failure and fibrosis. Unbiased transcriptomic profiling revealed a myocardial stress response characterized by activation of p53-associated cell death pathways, mitochondrial dysfunction, and negative enrichment of histone acetyltransferase (HAT) complexes, indicating epigenetic repression. Mechanistically, osimertinib-treated hearts exhibited increased expression of multiple histone deacetylase (HDAC) isoforms, reduced acetylation of histones, and enhanced cardiomyocyte apoptosis via Bax/caspase-mediated pathways. There was a minimal, transient effect on inflammation, supporting a type I, cell-autonomous cardiotoxic mechanism. Consistent with this, in vitro and in vivo analyses demonstrated suppression of prosurvival ERK/AKT signaling, mitochondrial dysfunction, and activation of intrinsic apoptotic pathways. Given the central role of HDAC activation, we tested whether pharmacologic HDAC inhibition could mitigate osimertinib-induced cardiotoxicity. Treatment with the FDA-approved HDAC inhibitor vorinostat (SAHA) restored histone acetylation, attenuated p53 activation, reduced cardiomyocyte death, and rescued cardiac function in osimertinib-treated mice. Translational studies in human NSCLC-derived PC9 cells further demonstrated that SAHA enhances osimertinib antitumor efficacy while alleviating cardiotoxicity. Collectively, these findings define HDAC-dependent epigenetic repression as a key mechanism underlying osimertinib-induced cardiotoxicity and identify HDAC inhibition as a therapeutically actionable strategy to improve both cardiac safety and cancer treatment efficacy.

Mitochondrial Fission Regulator 1 (MTFR1) plays a critical regulatory role in various malignancies; however, its specific function and clinical significance in breast cancer (BRCA) remain unexplored. This study systematically characterised MTFR1 by integrating multi-omics data, spatial transcriptomics, and single-cell sequencing, followed by in vitro experimental validation. MTFR1 was significantly overexpressed in BRCA tissues and predominantly localised to malignant cells. Functionally, MTFR1 was closely associated with cell cycle progression; in vitro knockdown significantly suppressed cell proliferation and induced cell cycle arrest. Clinically, high MTFR1 expression served as an independent predictor of poor prognosis and was linked to chemotherapy resistance. Cross-cancer immunotherapy analyses revealed that MTFR1 exhibited improved predictive performance for anti-PD-1 response during the on-treatment phase compared with pretreatment settings. This study elucidates the multidimensional role of MTFR1 as a putative oncogene in BRCA, highlighting it as a promising prognostic biomarker and therapeutic target.