Citations

Morel-Lavallee lesions (MLLs) are traumatic closed degloving injuries with operative intervention (OI), especially excisional debridement, remaining the mainstay of treatment. However, high-quality evidence describing operative techniques and outcomes remains limited. This study aimed to characterize current OI practices and associated outcomes, especially among patients undergoing excisional debridement, hypothesizing an increased risk of wound complications with this approach for MLLs. Methods This prospective (2021-2024), multicenter, observational study was conducted across 15 trauma centers and included patients diagnosed with MLL who underwent OI. The association between operative technique (eg, excisional debridement) and the primary outcome of wound complications was evaluated. Wound complications were defined as cellulitis, deep wound infection, skin necrosis, necrotizing soft tissue infection (NSTI), and/or organized hematoma. Results Of 88 MLL patients undergoing OI, 36 (40.9%) had excisional debridement, with 4 (11.1%) limited excision to skin, 20 (55.6%) extended to subcutaneous tissue, and 12 (33.3%) down to muscle. Excisional debridement had higher rates of skin necrosis (22.2% vs. 1.9%, P = .002). Although overall rates of wound complications were statistically similar between cohorts (33.3% vs. 17.3%, P = .098), univariate analysis demonstrated excisional debridement had increased risk of wound complications (OR 2.52, CI 1.07-5.97, P = .035). Conclusion This prospective multicenter study over three years demonstrated that a fifth of MLLs undergoing excisional debridement developed postoperative skin necrosis. Excisional debridement also had a more than two-fold increased risk of wound complications compared to other OIs. These findings underscore the importance of investigating alternative operative techniques, such as incision and drainage or minimally invasive debridement methods.

PURPOSE Since 2012, several states have implemented mandatory paid sick leave (PSL) policies. PSL can provide patients time and income continuity to undergo screening and/or timely diagnostic workup for new cancer-related symptoms and complete lengthy and expensive cancer treatment courses. This study aimed to examine the association between mandatory PSL policies and cancer stage at diagnosis and overall survival (OS). METHODS Adults age 18-64 years diagnosed with cancer were identified from the Surveillance, Epidemiology, and End Results program registries between 2010 and 2019. Difference-in-differences (DID) analyses were used to compare absolute changes in stage I and stage IV diagnoses and 1-year OS before and after policy implementation in states that enacted mandatory PSL relative to states that did not enact such policies. RESULTS A total of 1,052,307 patients with cancer were included. In adjusted DID analyses, there were a 0.83 (95% CI = –1.49 to –0.16, P = .014) PP decrease in stage IV diagnoses and a 0.63 (95% CI = 0.10 to 1.17, P = .021) PP increase in 1-year OS associated with implementation of mandatory PSL policies. In exploratory analyses, males and individuals with lung cancer experienced the greatest shifts in policy-associated changes in stage at diagnosis and OS. CONCLUSION PSL policy implementation is associated with decreased late-stage diagnoses and improved OS in patients with cancer. Policies that improve opportunities to receive medical care may facilitate earlier cancer detection and ultimately contribute to better patient outcomes.

Abstract Introduction: Clinical staging of multifocal non-small cell lung cancer (NSCLC) is facilitated by comparative genomic analysis of separate tumor nodules, but the role of genome-wide copy number profiling for this purpose is uncertain. Methods: We analyzed single nucleotide variants (SNVs), gene fusions, small copy number variants (gene amplifications and homozygous deletions) (sCNVs), and large-scale copy number variants (lCNVs) in a retrospective cohort of 34 patients with >1 lung cancer nodule tested on a previously validated tumor-only 515-gene next generation sequencing (NGS) panel (MayoComplete Solid Tumor Panel). For patients with <2 shared SNVs, a Bayesian approach was formulated to calculate the probability of shared versus independent events occurring in different tumor nodules in the same patient. The prevalence of specific lCNVs in NSCLC was derived from an independent dataset of 100 NSCLC peers tested by the same panel, and the prevalence of SNVs, fusions, and sCNVs in NSCLC was derived from publicly available data. Alterations unique to different tumor nodules and suspected germline alterations were excluded from the Bayesian analysis. Results: There were 54 total comparisons for 34 patients. Eleven of the patients (32.4%) had >=2 shared SNVs along with one or more shared lCNVs also identified in each patient. Eight patients (23.5%) had no shared SNVs, gene fusions, sCNVs, or lCNVs. Using the Bayesian approach for the remaining fifteen (44.1%) patients with at least one shared alteration (SNVs, sCNVs, and lCNVs), the probability of clonal relatedness ranged from 73% for a shared whole arm or whole chromosome lCNV to >99% for tumors with two or more shared alterations including multiple or complex lCNVs and SNVs. Whole chromosome or whole arm lCNVs were sometimes shared between tumor nodules with different driver SNVs. Conclusions: Incorporating lCNVs into comparative genomic analysis provides additional evidence of clonal relatedness in a subset of multifocal NSCLCs. However, differences in bioinformatics pipelines for calling lCNVs, concerns over the imprecision of genome-wide copy number profiling, and uncertainty regarding the temporal relationship between lCNVs and carcinogenesis (including somatic events possibly related to “field cancerization”) create challenges for integrating lCNVs into comparative genomic analysis with standard clinical workflows for tumor-only NGS on paraffin embedded tissue sections. Our simplified approach mitigates some of the uncertainty introduced by incorporating lCNVs into clonality determination. Citation Format: Claire Teigen, Ying-Chun Lo, Sounak Gupta, Stephanie Smoley, Beth Pitel, Hussam Al Kateb, Gopi Sivasankaran, Benjamin Kipp, Ande Rumilla, Gang Zheng, Kevin Halling, Katherine Geiersbach, . A Bayesian framework for evaluating somatic copy number variants into comparative genomic analysis of multifocal non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5423.

ABSTRACT In normal health, the liver and lungs enjoy a close anatomic, physiologic, and functional relationship. In the context of pulmonary vascular disease, however, there is accumulating evidence that the interplay between the gut microbiome, hepatic system, and pulmonary vasculature (so‐called “gut‐liver‐lung” axis) plays an important role in driving disease pathogenesis and determining clinical outcomes. Despite recognizing the importance of the gut‐liver‐lung axis in pulmonary vascular disease however, little is known about the clinical characteristics, circulating factors, and physiologic pathways that mediate this important axis of communication. In this clinical and translationally focused review, we provide an overview of liver‐lung communication in normal physiology, and contrast this with gut‐liver‐lung derangements in pulmonary arterial hypertension, portopulmonary hypertension, and hepatopulmonary syndrome. We conclude with identifying key gaps in knowledge that will need to be addressed in order to manipulate the gut‐liver‐lung axis to prevent worsening pulmonary vascular disease, develop novel therapeutics, and improve patient outcomes.

PURPOSE Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. The higher incidence and earlier onset of HCC in sub-Saharan Africa suggest a potential role for a genetic predisposition. This study evaluated the association of TERT -rs2242652-(A), a variant linked to lower HCC risk, with HCC in populations from Ghana, Nigeria, and Cameroon, compared with a population from the United States. METHODS The study included 537 patients with HCC: United States (n = 348), Ghana (n = 79), Nigeria (n = 43), and Cameroon (n = 67). The control group had 2,872 cancer-free individuals: United States (n = 2,399), Ghana (n = 323), Nigeria (n = 85), and Cameroon (n = 65). Whole-exome sequencing was conducted using germline DNA, and data for TERT -rs2242652 were analyzed. Odds ratios (ORs) and 95% CIs were calculated using unconditional logistic regression. Chi-square tests assessed protective allele frequencies. RESULTS In the US cohort, TERT -rs2242652 was significantly associated with lower HCC risk (OR, 0.75 [95% CI, 0.58 to 0.96]; P = .02), with an allele frequency of 18.8% (15.4% in HCC cases v 19.3% in controls). In the combined sub-Saharan African population, no significant association was observed, but there was a trend toward decreased HCC risk (OR, 0.80 [95% CI, 0.53 to 1.22]; P = .29), with an allele frequency of 12.2% (10.6% in HCC cases v 12.9% in controls). Separate analyses of Ghanaian, Nigerian, and Cameroonian populations showed similar nonsignificant trends. The protective allele frequency in the combined African populations was significantly lower than in the US cohort ( P < .0001). CONCLUSION In sub-Saharan African populations, there was a lower frequency of the HCC protective allele TERT -rs2242652 compared with European Americans. These findings underscore the importance of multiethnic genetic studies in understanding population differences in HCC risk and developing prevention strategies.

PURPOSE Artificial intelligence (AI) has been rapidly evolving in medicine. While there are existing data about the perceptions and concerns of health care workers regarding AI, those of the hematology and oncology (HemOnc) workforce remain unknown. We assessed opinions of physicians (faculty and fellows), advanced practice providers (APPs), and nurses in HemOnc on integrating AI in medical education (MedEd) and clinical practice (CP). METHODS Group-specific electronic surveys were developed. The HemOnc workforce from the three Mayo Clinic sites was invited to participate. Participation was anonymous, with data collection between November 7, 2024, and January 20, 2025. Results were reported as proportions, with 95% binomial CI when appropriate. RESULTS A total of 344 participants responded, 118 physicians (77 faculty, 41 fellows), 49 APPs, and 177 nurses. Most had used AI although less than half felt very or moderately knowledgeable about it. A total of 95% of fellows, 97% of faculty physicians, 96% of APP, and 92% of nurses believe that AI will be integrated in MedEd. A total of 94% of physicians and 88% of nonphysicians believe that this integration would be beneficial. In CP, 98% of fellows, 96% of faculty physicians, 100% of APPs, and 92% of nurses believe in AI's integration. However, 51% of physicians and 68% of nonphysicians had some concerns, including technology time, medical costs, and burnout. Nonetheless, 85% of fellows, 94% of faculty physicians, 98% of APPs, and 86% of nurses would embrace AI. CONCLUSION The majority of this single health system HemOnc's workforce endorsed AI integration into MedEd and CP but highlighted relevant concerns. Proper education, effective partnership among all stakeholders, and well-organized integration are essential for optimizing AI's incorporation into HemOnc's MedEd and CP and ensuring that it fully supports the mission of providing high-quality patient care.

Abstract In many cancers, a major barrier to effective immunotherapy is the dominance of tumor-associated myeloid cells (TAMs), which establish a profoundly immunosuppressive tumor microenvironment (TME). This challenge is particularly pronounced in glioblastoma (GBM), where myeloid cells represent the predominant immune population and actively suppress antitumor immunity. Identifying targets that can reprogram TAMs from an immunosuppressive state toward a pro-inflammatory, antigen-presenting phenotype remains a critical unmet need. Here, we identify the voltage-gated proton channel Hv1 as an immune-restricted regulator of glioma-associated macrophage function. Hv1 is notable not only for its immune-specific expression but also for its established roles in central nervous system (CNS) pathologies, where Hv1 depletion alters microglial and macrophage polarization, reduces myeloid accumulation, dampens inflammatory cytokine production, and limits secondary tissue damage. However, Hv1’s role in shaping the GBM immune landscape—particularly in vivo—has remained poorly understood due to low Hvcn1 transcript abundance and the lack of reliable antibodies and genetic tools. Given the dominance of myeloid cells in GBM and their central role in tumor immune regulation, we sought to define Hv1 function within this highly immunosuppressive brain TME. Analysis of patient datasets revealed that elevated Hv1 expression correlates with poor clinical prognosis. Consistently, Hv1 loss significantly prolonged survival in multiple murine glioma models. Using in vivo two-photon imaging and spectral flow cytometry, we show that Hv1 depletion reprograms TAMs toward an anti-tumor phenotype characterized by enhanced tumor cell phagocytosis, improved antigen presentation, and increased T cell infiltration. By generating new Hv1 reporter and conditional mouse lines, we further demonstrate that tumor-associated microglia and infiltrating macrophages are the principal sources of Hv1 and markedly upregulate its expression in response to glioma. Notably, selective deletion of Hv1 in infiltrating macrophages phenocopied the survival benefit observed with global Hv1 loss. Mechanistically, using mass spectrometry and genetic models, we identify the Stimulator of Interferon Genes (STING) as a previously unrecognized binding partner of Hv1, placing Hv1 within the STING signaling pathway, a central regulator of innate and adaptive immune responses. Together, these findings fill a critical gap in understanding myeloid Hv1 function in GBM and identify Hv1 as a promising target for reprogramming the tumor immune microenvironment. Citation Format: Jiaying Zheng, Lingxiao Wang, Shunyi Zhao, Katayoun Ayasoufi, Meijie Wang, Praveen N. Pallegar, Peter R. Strege, Langni Liu, Yushan Wan, Wenjing Zhang, Emma N. Goddery, Manling Xie, Arthur Beyder, Aaron J. Johnson, Long-Jun Wu. Myeloid Hv1-STING axis tunes glioma immunity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr A016.

Abstract Models that estimate the probability of an adverse clinical outcome require an operational cutoff to translate continuous estimated probabilities into discrete labels that can trigger clinical action. Although statistical methods identify ‘optimal’ cut-offs, threshold selection ultimately reflects value judgments regarding harm tolerance, resource allocation, and workflow feasibility. We describe a governance-informed approach to selecting a deployment threshold for an asthma exacerbation (AE) prediction model integrated into clinical workflows. Using prevalence-adjusted performance metrics and real-world provider capacity modeling, we evaluated multiple candidate thresholds and quantified downstream workload and missed-event trade-offs. We demonstrate that statistically optimal thresholds may produce operationally infeasible alert volumes or unacceptable miss rates. We propose a structured threshold governance framework integrating statistical performance, clinical utility, stakeholder input, and human oversight safeguards. This case illustrates how threshold decisions should be treated as organizational governance processes rather than purely technical optimizations.

PURPOSE For patients with advanced biliary tract cancer (BTC), cancer-related time spent in health care systems, time toxicity, represents a critical but understudied burden affecting quality of life. This study aimed to quantify time toxicity in patients receiving first-line systemic therapy and evaluate whether the addition of durvalumab to gemcitabine plus cisplatin (GC) increases health care contact time. METHODS This international, multicenter, retrospective cohort study included patients with advanced BTC seen between January 2019 and April 2024 at Mayo Clinic Enterprise (US), and between January 2021 and April 2024 at Kyorin University Hospital (Japan), and Hospital Israelita Albert Einstein (Brazil). Patients received GC plus durvalumab (GCD) or GC. Time toxicity was recorded from treatment initiation until discontinuation or last follow-up during first-line systemic therapy. Multiple regression analysis identified factors associated with high time toxicity. RESULTS Among 193 patients (102 GCD, 91 GC; median age 65 years; 50% male; 49% Eastern Cooperative Oncology Group performance status [PS] 0), median time on treatment (TOT) was 156 days (95% CI, 122 to 190). The median proportion of total time toxicity was 14.4% (IQR, 10.9-20.6). Planned visits accounted for 11.9%, while unplanned visits were infrequent (1.8%). Time toxicity strongly correlated with TOT ( r = 0.824) and progression-free survival ( r = 0.827). Despite longer treatment in the GCD group than the GC group (212 v 134 days; P = .027), total time toxicity was similar (27 v 18 days; P = .19). Younger age and poor PS were independent factors of higher time toxicity. CONCLUSION Time toxicity represents a meaningful metric that allows for more comprehensive integration of the net benefit in patients with advanced BTC with a limited lifespan.

Background Suicidal behaviour shows notable sex differences, and understanding whether genetic factors contribute to these differences is critical for identifying at-risk individuals and prevention. Objective We aim to investigate the genetic contribution to suicide attempts and examine whether genetics account for sex differences in incidence. Methods This population-based cohort study includes 3.1 million individuals born 1963–1998 and followed through Swedish National Registers, including hospitals and specialist outpatient diagnoses and cause of death data. Suicide attempts were identified using ICD codes, indicating intentional self-harm, self-harm using lethal methods or leading to hospitalisation, or resulting in death. Familial aggregation, coaggregation, pedigree heritability and genetic correlations were estimated using genealogical data. For sex-specific analyses, we examined mother–daughter, female sibling, father–son and male sibling pairs, separately. Findings Suicide attempts were more common among females than males (3.3% vs 2.6%). In both sexes, risk aggregated within families (ORs ranged 1.6–3.4 across relative types) and was higher in first-degree than second-degree relatives. Familial aggregation was stronger in females than in males, and in same-sex first degree relatives compared with cross-sex pairs. Pedigree heritability was 41.9% (95% CI 36.0 to 48.4%) and did not differ significantly by sex (female 51.4% (95% CI 40.1% to 58.6%), male 45.1% (95% CI 32.3% to 52.5%), Bootstrap p value 0.40). Suicide attempt showed moderate to high pedigree genetic correlations with psychiatric disorders, strongest with substance use disorders (SUD, r g =0.85 (95% CI 0.83 to 0.96)), with no significant sex differences. The genetic correlation between female and male suicide attempts was high (0.85 (95% CI 0.80 to 0.99)), suggesting a substantial genetic overlap. Conclusions Suicide attempt has a moderate heritable component that largely overlaps between females and males and with other psychiatric disorders, particularly SUD. Stronger familial aggregation in females and in same-sex pairs highlights the potential role of sex-specific environmental or social factors. Future research should focus on non-genetic contributors and their potential interaction with genetic factors to better understand and address sex disparities in suicidal behaviour Clinical implications Genetic risk for suicide attempt is substantial but does not fully explain sex differences in incidence. Clinicians should, therefore, consider non-genetic, including sex-specific environmental and social factors, alongside family history and psychiatric comorbidity when assessing suicidal risk.