Citations

Abstract Cancer remains one of the most complex and devastating diseases, in part because tumors are not static entities but dynamic ecosystems that evolve in real time. Over the decades, researchers have proposed two major frameworks toexplain tumor development: 1) the clonal evolution model, which emphasizes the stepwise accumulation of mutations insingle cells, and 2) the cancer stem cell model, which posits a hierarchical tumor structure driven by a small population of stem-like cells capable of self-renewal and tumor initiation. In brain tumors, as in other cancer types, the presence of cancer stem cells has been demonstrated; however, their evolutionary role in glioblastoma, the most aggressive primary brain tumor, remains poorly understood. A key unanswered question is how cancer stem cells in the brain evolve intomalignant populations and how evolutionary processes shape this transition. Since Darwin, evolutionary biologists have sought to understand how traits evolve across lineages and have developed several tools to address questions regarding how lineages, species and populations have evolved through time. In recent years there has been an increase in the use of evolutionary statistical methods to study cancer evolution. These approaches remain niche in a few tumor types (e.g., blood and lung cancer), but the rapid growth of sequencing technologies and large-scale datasets has created new opportunities to address evolutionary questions across cancer types that have been understudied (e.g., brain tumor). Researchers are now using whole-genome, exome, single-cell, spatial, and multi-omic data to reconstruct tumor histories, test adaptive hypotheses, and in few cases, quantify rates and modes of evolution within tumors and between tumor types. However, there is not yet a consolidated framework for which evolutionary analyses are most appropriate to test cancer evolution, nor accessible guidance on how to implement these approaches in oncological datasets. We synthesize evolutionary statistical methods currently used in brain cancer research and propose additional approaches for future studies. We identify more than 30 evolutionary tools developed to study trait evolution, diversification, and lineage dynamics in biological systems, of which only one has been applied to brain cancer. We argue that adapting these methods offers a powerful opportunity to investigate cancer stem cell dynamics and tumor progression in glioblastoma and other understudied cancers. By bridging evolutionary biology and cancer genomics, this work provides a roadmap for expanding the evolutionary toolkit used to study tumor evolution and for generating testable hypotheses about malignant transformation. Citation Format: Jhan C. Salazar Salazar, Sean W. McHugh, Maria F. Gonzalez-Aponte, Hugo Guerrero-Cazares. From healthy brain to cancer cells: Understanding the origins of glioblastoma through the lens of Darwinian evolution [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 B017.

Abstract Background: High-grade astrocytoma with piloid features (HGAP) is a recently defined tumor type that is not well-understood. Prognostic factors of clinical outcome are not well-established. Methods: Samples were processed at the National Cancer Institute (NCI) Laboratory of Pathology, and published samples were included (n=421). Methylation classifier scores of ≥0.90 to the HGAP class on the NCI-Bethesda classifier were included. Clinical features were collected from the medical record. Kaplan-Meier survival analysis as well as Cox-proportional hazards was performed. Results: The cohort comprised 421 patients. There was a high rate of ATRX alteration (62%), CDKN2A/B loss (78%) and MGMT promoter methylation (53%). MAPK alterations were identified in 74% of samples. The median age was 46 years, and posterior fossa location was predominant (52%). The median overall survival (OS) was 88 months. Older age (p = 0.01) and the presence of an ATRX alteration (p = 0.04) were found to be poorly prognostic. The presence of cystic features on magnetic resonance imaging (MRI) was found to be favorably prognostic (p = 0.01). Factors that were not significantly associated with survival included histologic anaplasia, CDKN2A/B homozygous deletion, MGMT promoter methylation and surgery type. Conclusions: Utilizing a relatively large cohort of HGAP cases, this work establishes relative frequencies of several important markers, and additionally suggests older age, the presence of an ATRX alteration, and cystic features on MRI as prognostic. Our work may aid in identifying treatment regiments for patients with this tumor type. Citation Format: Shuodan Zhang, Omkar Singh, Karen Dazelle, HGAP manuscript co-authors, Kenneth Aldape. High-grade astrocytoma with piloid features: a clinical and genomic analysis of prognostic factors using a large cohort [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 A057.

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.

The results underscore a multifaceted interaction among cardiopulmonary hemodynamics, right heart pressures, ventilatory response, and autonomic regulation. In particular, altered RV-PA coupling correlated with heightened sympathetic drive, indicating that cardiopulmonary efficiency and hemodynamics may influence central autonomic outputs. This suggests that mechanical stress or overload in the right heart could modulate sympathovagal balance, thereby contributing to altered autonomic responses during exercise in patients with cardiopulmonary disorders.

Abstract Purpose: The Pancreatic Cancer Detection Consortium (PCDC) performed a blinded Early Detection Research Network–defined phase II biomarker bakeoff study of blood-based biomarker panels. The aims were to evaluate panel performance, to compare the panels’ performance with that of cancer antigen 19-9 (CA19-9) alone, and to evaluate the performance of new combinations of the individual biomarkers. Experimental Design: Ten biomarkers representing eight biomarker panels and CA19-9 were evaluated using plasma, serum, and germline DNA from 140 stage I to IV pancreatic ductal adenocarcinoma (PDAC) cases and 140 controls from three tertiary care institutions, with controls frequency matched to cases on age and sex. LASSO regression was employed to explore new biomarker combinations. The primary metric was area under the receiver operating characteristic curve (AUC). Results: The study population was 51% female, with median age 67.3 (minimum: 45, maximum: 90) years. Biomarker panel AUCs ranged from 89.9 to 96.3; the AUC for serum CA19-9 alone was 91.7 [95% confidence interval (CI), 87.8–95.6]. Two panels had significantly higher AUCs than serum CA19-9 alone, the CA19-9/FUT2/3 panel (AUC = 96.3, P = 0.002), and the tissue factor pathway inhibitor/tenascin C (TFPI/TNC-FNIII-C) panel (AUC = 95, P = 0.01). Exploratory models to recombine biomarkers retained all but two biomarkers [optimism-corrected AUC = 96.4 (94–98.9)]. Conclusions: The CA19-9/FUT2/3 panel was the best performing panel in this biomarker bakeoff. Its evaluation in larger studies is warranted. Biomarker bakeoffs are an effective strategy for comparing the performance of promising biomarkers for pancreatic cancer early detection, and the PCDC is well poised to conduct such studies. Recommendations for performing such studies are provided.

OBJECTIVE: Accurate assessment of skin and skin changes across diverse populations is critical for patient health. To promote the knowledge and skills nurses need in practice to identify skin changes, nurse educators must include content on assessment of diverse skin tones in nursing education programs. This study’s objective was to develop and pilot education modules about the assessment of diverse skin tones to be part of an undergraduate nursing course. METHODS: In this quality improvement project, modules highlighted the importance of skin assessment and appropriate techniques for assessing erythema, pallor, cyanosis, and jaundice on diverse skin tones. Undergraduate nursing students completed a questionnaire evaluating the modules and their learning experience. RESULTS: The majority of students (≥70%) agreed or highly agreed that the modules were interesting, informative, engaging, and increased their knowledge. Comments to open-ended questions supported their evaluation ratings. CONCLUSIONS: Undergraduate nursing students positively received education modules on assessing patients with diverse skin tones. Students perceived the modules as having the potential to enhance their learning and assessment skills to prevent and detect skin changes associated with pressure injury. The modules serve as an example of a strategy to integrate education content about diverse skin tones into nursing curricula.

ABSTRACT Predicting delayed graft function (DGF) relies on donor, recipient, and perioperative factors. Despite the growing recognition that DGF duration strongly influences patient outcomes, no models currently address or predict its impact—highlighting an important gap in current research and clinical practice. This study aimed to develop an ensemble‐based machine learning model using perioperative data to predict DGF occurrence and duration. The gradient‐boosted decision trees model was trained and validated on 2725 patients, with k‐fold cross‐validation in an external cohort of 284 patients. Model performance was evaluated based on accuracy, ROC‐AUC, and other metrics using R and Python libraries. The binary DGF prediction model achieved a ROC‐AUC of 0.77, while the DGF duration classification model had an accuracy of 79.2%. DGF duration AUC values by time interval were 0.76 for 0–1 weeks, 0.81 for >1–2 weeks, 0.80 for >2–3 weeks, and 0.87 for >3 weeks; the overall macro‐averaged AUC was 0.81. The mean Brier score for multi‐class predictions was 0.14. External validation showed a 78% accuracy for DGF duration prediction. Acute kidney injury (AKI) and donor donation after circulatory death (DCD) status were key DGF predictors. The use of gradient‐boosted decision trees (GBDT) improves the prediction of both the likelihood and duration of DGF, addressing a current gap in kidney transplant patient care. By facilitating personalized transplant care, this model supports more effective perioperative planning and timely interventions, which may contribute to better patient outcomes.

Abstract Background & Aims Stricturing Crohn’s disease (CD) is a significant problem, and no selective anti-fibrotic therapies are available. Anti-inflammatory approaches are the mainstay of medical treatment. However, data on the efficacy of ustekinumab (USTE) in ileal stricturing CD are lacking. Our aim was to assess its efficacy in this setting. Methods We performed an international multicenter observational cohort study evaluating adult CD patients who received USTE within 6 months of imaging-confirmed symptomatic stricturing small bowel disease. Outcomes were rates of endoscopic balloon dilation (EBD), surgery, intervention (defined as the composite need for EBD or surgery), recurrent obstructive symptoms, and USTE persistence. Results Fifty-seven patients were included (51% female, median age 43 years). Median follow-up was 17 months. Intervention rates were 35%, 45%, and 69% of patients, at 12, 24, and 48 months, respectively. USTE persistence was 78%, 76%, and 52% at 12, 24, and 48 months. Estimated obstructive symptoms rates were 31% and 49% at 12 and 24 months, respectively. EBD within 6 months prior to starting USTE was associated with an increased risk of intervention. Increased bowel wall thickness on imaging, prior biologic use, and obstructive symptom duration were associated with USTE discontinuation. Occurrence of obstructive symptoms during treatment was associated with prior biologic use, EBD within 6 months of starting USTE, and a lower BMI. Conclusions USTE appears to be an appropriate medical option in biologic-experienced CD patients with ileal strictures. Further prospective data are needed to better define outcomes and predictors of response in this setting.