Citations

Abstract Background: Melanoma brain metastases (MBM) represent a biologically distinct and clinically aggressive subset of melanoma. Comprehensive molecular characterization focused on intracranial disease remains limited. We aimed to define the genomic landscape of MBM and compare these findings with public melanoma datasets. Methods: We retrospectively identified 166 patients with histologically confirmed MBM across Mayo Clinic tri-sites (2011-2025). Molecular testing was performed in 123 patients (74.1%). Comprehensive next-generation sequencing (NGS; ≥300-gene platforms including Tempus, FoundationOne, Caris, NeoGenomics, and MayoComplete Solid Tumor Panel) was available in 41 patients (24.7%). Intermediate-depth profiling using the MayoComplete Melanoma Panel (17 genes) was performed in 21 patients (12.7%), and a targeted 5-gene melanoma driver panel (BRAF, NRAS, KIT, GNAQ, GNA11) in 52 patients (31.3%). cfDNA-based NGS was available in 12 patients (7.2%). Genomic alterations were summarized and benchmarked against TCGA-SKCM and MSK-IMPACT datasets via cBioPortal. We considered assay heterogeneity, as Mayo panels varied in sequencing depth and CNV coverage, and hybrid-capture platforms often under-detect TERT promoter hotspots. Results: Patients had a median age of 67 years, and 63% were male. BRAF mutations occurred in 48.8% (BRAF V600E/K 41.6%; non-V600 7.2%). Additional MAPK alterations included NRAS (17.5%), KIT (5.4%), GNAQ (1.2%), and GNA11 (0.6%). In the comprehensive NGS subset, tumor-suppressor alterations included CDKN2A (17.5%), PTEN (7.8%), NF1 (9.0%), TP53 (8.4%), and TERT promoter mutations (22.9%). Median TMB was 11.55 mut/Mb (IQR 5.0-25.5). Co-alterations included BRAF+CDKN2A (7.2%), BRAF+PTEN (4.2%), NRAS+CDKN2A (4.2%), NRAS+PTEN (1.2%), and CDKN2A+PTEN (3.6%); overall, 18.1% harbored MAPK driver + tumor-suppressor co-alterations. Compared with TCGA and MSK cohorts, MBM showed similar MAPK driver frequencies but fewer MAPK + tumor-suppressor co-alterations and lower CDKN2A, PTEN, and TP53 disruption, alongside a more prevalent of TERT promoter mutations (22.9% vs 7% and 2.1%), which may partly reflect coverage differences. Conclusion: MBM exhibit a distinct genomic profile characterized by reduced tumor-suppressor loss, fewer MAPK-tumor-suppressor co-alterations, and higher prevalence of TERT promoter mutations. While assay heterogeneity limits direct cross-cohort comparisons, these patterns suggest potentially distinct biological features of intracranial melanoma and underscore the need for harmonized, MBM-specific molecular studies to guide therapeutic development. Citation Format: Dina Elantably, Joseph B. Parker, Jakob Hamilton, Ahmed Abdelhakeem, Oluwatayo Adeoye, Saivaishnavi Kamatham, Winston Tan, Arkadiusz Z. Dudek, Anastasios Dimou, Matthew S. Block, Robert McWilliams, Svetomir Markovic, Mahesh Seetharam, Roxana Dronca, Ruqin Chen. Genomic landscape of melanoma brain metastases: Real-world analysis and comparison with public melanoma cohorts [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 2107.

Abstract Background: Digital Drug Assignment (DDA) is a computational reasoning model that scores cancer therapies based on the complete molecular profile of a tumor, and stratifies them by predicted efficacy (Petak et al., 2021). In a prior study of 111 lung cancer patients, DDA-derived high-score molecularly targeted agents (MTAs) were associated with improved clinical outcomes (Dirner et al., 2025). Here, we extend this analysis to the GENIE BPC NSCLC cohort to assess the broader clinical validity of DDA. Methods: From the GENIE BPC NSCLC cohort data available on Synapse, we included 1,078 patients with a single-sample genomic profile, available primary treatment data and survival outcomes (total 2,103 treatment lines, therapies included: afatinib, erlotinib, osimertinib, crizotinib, nivolumab, pembrolizumab, atezolizumab, bevacizumab+chemo, ramucirumab+chemo; and chemotherapy alone). DDA scores were generated for all cases, and the individual score of the administered MTAs (incl. immune checkpoint inhibitors) was used to stratify outcomes into low (<0), intermediate, and high DDA-score (≥1000) tiers. Progression-free survival (PFS, by imaging) and overall survival (OS) were analyzed using Kaplan-Meier statistics. Results: Median PFS and OS differed significantly across DDA score tiers, increasing with higher scores (see table). Intermediate-tier drugs had similar mPFS values as chemotherapies (3.9 vs 4.2 months). Six-month PFS and twelve-month OS rates increased with DDA-tiers and were all significantly different by χ2 test. DDA-high therapies provided greater benefit across treatment types than lower-score counterparts. Conclusions: Across a large, real-world NSCLC cohort, DDA effectively distinguished therapies with higher clinical efficacy based on the full molecular profile of each patient. These results reinforce the potential of DDA to enhance personalized treatment selection based on NGS diagnostics in precision oncology. Citation Format: Barbara Vodicska, Eniko Kispeter, Dora Lakatos, Gabor Gy Kalmar, Robert Doczi, Dora Gorog-Tihanyi, Anna Dirner, Reka Szalkai-Denes, William T. Beck, Arkadiusz Z. Dudek, Christophe Le Tourneau, Istvan Petak. Molecularly-informed prediction of treatment efficacy in the GENIE BPC NSCLC cohort using computational reasoning [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 7.

Abstract Background: Despite the decline in overall mortality and incidence of cancer in the US population, the burden of cancer is still high, especially in underserved and under-researched populations. A major contributor to poor cancer outcomes is the absence of dedicated efforts utilizing scientifically rigorous approaches and implementation strategies to optimize participant enrollment and accrual in clinical trials. The Connecting Patient Populations to Clinical Trials (CP2CT) program implements innovative multilevel interventions to enhance clinical trial awareness and optimize referral pathways that facilitate patient enrollment. The CP2CT Data, Evaluation, and Coordinating Center (DECC) supports its data and evaluation activities, and coordinates a learning collaborative towards mitigating the key barriers of cancer burden in all populations. Methods: Using an implementation science-informed approach, the DECC deployed coordinated strategies over three years: (1) administrative structuring through streamlined governance, centralized reporting, and stakeholder integration; (2) data standardization via Common Data Elements (CDEs), a cross-network REDCap system, and a multi-institution Data Transfer Agreement (DTA); (3) evaluation infrastructure through a Network Logic Model, evaluation plan, standardized constructs, and a Process Evaluation Plan with tools; (4) learning supports through an internal website and expanded Speaker Series; and (5) site-level implementation facilitation through structured visits. Results: In collaboration with the CP2CT Network and NCI, the DECC’s achievements span four domains: (1) Administrative: built infrastructure, deployed centralized reporting platforms, coordinated key meetings, and strengthened community integration. (2) Data: standardized collection, secured network-wide data sharing through the DTA, enabled harmonized multi-site reporting, and advanced groundwork for interoperability and scientific value. (3) Program Evaluation: linked CP2CT activities to measurable outcomes through a Network-wide Logic Model, guided evaluation, established shared evaluation language, and launched a transferable Process Evaluation framework. (4) Learning Collaborative: developed a centralized resource hub, expanded the Speaker Series, and advanced authorship transparency with the CP2CT Publication Policy. < Conclusion: The CP2CT DECC has established a sustainable, scalable infrastructure that integrates administrative coordination, standardized data collection, robust program evaluation, and a collaborative learning environment. These efforts enhance clinical trial awareness, optimize referral pathways, and provide a transferable model for improving participant enrollment and scientific rigor across national research networks, ultimately addressing disparities in cancer outcomes. Citation Format: Laura E. Lectora, Cristina J. Orozco, Holly A. Thorson, Timethia Bonner, Robert R. Freimuth, Jennifer G. Le-Rademacher, Folakemi T. Odedina. Building a national network coordination center for clinical trials: Early implementation outcomes from the CP2CT DECC [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 899.

Abstract Background: Multidisciplinary research networks often face challenges in harmonizing metrics and measures across participating sites, limiting the ability to aggregate data and generate generalizable insights. To address this barrier within the Connecting Patient Populations to Clinical Trials (CP2CT) Network, the Data, Evaluation, and Coordinating Center (DECC) coordinated the establishment of a unified framework that supports comparable evaluation and enhances the scientific impact of network-wide activities. Methods: Consensus was developed through a structured, iterative, and collaborative process: (1) drafting initial constructs, metrics, measures, and benchmarks informed by Network site materials and relevant literature; (2) soliciting qualitative and quantitative feedback from Network sites via Basecamp, an innovative online collaborative workspace for construct development; (3) conducting open dialogue sessions followed by systematic review and integration of site feedback; and (4) refining all elements through repeated feedback cycles until no further modifications were requested. Each iteration strengthened the clarity, coherence, and scientific precision of the final constructs. Results: A total of seven constructs were incorporated into the consensus-development process: clinical trials referral, clinical trials accrual, participants’ awareness of clinical trials, participants’ knowledge of clinical trials, providers’ awareness of NCI-supported clinical trials, providers’ engagement with NCI-supported clinical trials, and providers’ referral to NCI-supported clinical trials. For each construct, the Network established a conceptual definition (broad description of the construct), an operational definition (specification of how the construct is measured or observed), benchmarks (standards for assessing performance), metrics (quantitative indicators of performance), and measures (tools used to quantify inputs, processes, or outcomes). Common measures were developed for two constructs—clinical trials accrual and participants’ knowledge of clinical trials. Although full consensus was not achieved across all four Network sites for every construct, at least three sites reached consensus for the remaining five constructs. Conclusion: This consensus-building initiative resulted in the development of a unified, scientifically grounded framework. By harmonizing key elements related to clinical trial referral, accrual, awareness, knowledge, and provider engagement, the Network has established foundational tools that enable cross-site data comparability and facilitate more rigorous assessment of efforts to connect diverse patient populations to clinical trials. This framework positions the Network to inform strategies that improve equitable clinical trial participation. Citation Format: Folakemi T. Odedina, Jennifer Le-Rademacher, Robert Freimuth, Cristina Orozco, Laura Lectora, Timethia Bonner, Holly Thorson, Connecting Patient Populations to Clinical Trials(CP2CT) Program Evaluation Work Group, Connecting Patient Populations to Clinical Trials(CP2CT) Steering Committee. Development of and consensus building towards shared metrics, measures and benchmarks for the connecting patient populations to clinical trials (CP2CT) [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 860.

Abstract Background: Primary Cardiac Lymphoma (PCL) is an exceptionally rare malignancy. While clinical case reports have postulated an association with human immunodeficiency virus (HIV), large-scale epidemiological data corroborating this link are limited. Objective: To determine whether HIV is associated with increased prevalence of PCL in a large, nationally representative sample of US hospitalizations. Methods: We performed a retrospective, cross-sectional analysis using the Healthcare Cost and Utilization Project National Inpatient Sample from 2016 to 2019, representing approximately 35 million unweighted hospitalizations. Hospitalizations were identified using a proxy definition for PCL, requiring ICD-10-CM codes for both cardiomyopathy (I42.*) and extranodal non-Hodgkin lymphoma (i.e., C83.39, C85.99). HIV status was identified using codes B20-B24 and Z21. We compared the prevalence of PCL in hospitalizations with versus without HIV and calculated odds ratios using Fisher’s Exact Test, reporting corresponding 95% confidence intervals (CI) and p-values. Results: We identified 569 hospitalizations meeting our operational definition for PCL out of 34,955,252 total discharges. The prevalence of PCL was significantly higher among hospitalizations with HIV (6.2 per 100,000) compared with those without HIV (1.6 per 100,000; p < 0.0001). HIV was associated with a 3.86-fold increased odds of PCL (OR: 3.86; 95% CI: 2.23-6.70; p < 0.0001). Conclusion: In this nationwide analysis of 35 million hospitalizations, HIV was strongly associated with a higher prevalence of PCL. Hospitalizations with HIV had nearly 4-fold higher odds of PCL, as defined by co-occurrence of cardiomyopathy and extranodal lymphoma, compared with hospitalizations without HIV. This population-level finding evinces the association previously suggested in clinical case reports. Citation Format: Omar Hozayen, Jay Hozayen, Benjamin Behers, Christoph Stephenson-Moe, Maha Hameed, Matthew Miller, Laura De Jesus Herrera, Anas Abu Jad, Rheiner Kammer, Mohab Idriss, Ahmed Aboutaleb, Bashar Roumia, Patricia Riano, Nicolas Riveros Neira, Brooke Hartenstein, Robert Taylor, Manuel Rosario Espinal, Brett M. Behers, Alya Hozayen, Mohamed Ibrahim, Karen Hamad. Primary cardiac lymphoma and HIV: A nationwide analysis of hospitalizations [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 215.

Abstract Cholesterol has long been viewed as a structural component of cellular membranes, yet its role in DNA damage response remains poorly defined. Here, we show that ionizing radiation (IR) induces broad transcriptional upregulation of cholesterol biosynthesis, transport, and storage pathways, leading to sustained intracellular accumulation of cholesterol. BODIPY-cholesterol imaging, Filipin III staining, and quantitative subcellular fractionation confirmed selective nuclear enrichment of cholesterol following IR, coinciding with extensive chromatin remodeling. Proteomic profiling of cholesterol-interacting proteins revealed a strong enrichment of chromatin-associated factors, suggesting a previously unrecognized lipid-chromatin interface in irradiated cells. Functionally, cholesterol accumulation promoted chromatin compaction and repressive histone modification patterns, impairing DNA damage sensing and checkpoint activation despite increased underlying DNA lesions. These alterations facilitated aberrant mitotic entry, formation of cytoplasmic chromatin fragments (CCFs), and activation of cGAS-STING-NF-κB signaling. Cholesterol exposure ultimately diverted damaged cells toward a senescent fate, marked by Lamin B1 loss, p21 induction, and a robust senescence-associated secretory phenotype (SASP) enriched for IL-1 and TNF family cytokines. In vivo, dietary cholesterol exacerbated radiation-induced inflammation and weakened systemic anti-tumor immunity. Transcriptomic analyses of immunotherapy-treated patients revealed that tumors enriched for cholesterol import and senescence signatures were associated with poor response to PD-L1 blockade and worse survival. Together, these findings identify a cholesterol-chromatin-senescence axis that links metabolic remodeling to defective DNA damage signaling and immune suppression after radiation, highlighting cholesterol metabolism as a potential therapeutic vulnerability in cancer therapy. Citation Format: Yiqun Han, Yaobin Ouyang, Shouhai Zhu, Hangcheng Xu, Bin Chen, Ping Yin, Qin Zhou, Jinzhou Huang, Kuntian Luo, Zheming Wu, Huaping Xiao, Xinyi Tu, Jake A. Kloeber, Jiajun Jing, Xiaofeng Huang, Meng Xu Welliver, Zhenkun Lou, Robert Mutter. Cholesterol triggers chromatin stress to drive senescence and inflammation [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 539.

Biological heterogeneity among different breast cancer (BC) subtypes results in markedly varying clinical outcomes. Identification and analysis of key gene biomarkers that are differentially regulated during radiation therapy (RT) may pose multiple clinical challenges for BC treatment. The purpose of the study is to identify and analyze the expression of key gene biomarkers and their networks that are differentially regulated after hypofractionated RT. Patients with BC (cT0-T2, N0, M0) were treated with hypofractionated whole breast RT 25 Gy in five fractions, 4 to 8 weeks before breast conservation surgery (BCS). Biopsy (pre-RT; n = 5) and surgical (post-RT; n = 14 or 15) BC tumor samples were used for NanoString targeted sequencing. We identified 165 and 244 differentially expressed genes (DEGs; p < 0.05) in BC tumor samples from BC patients post-RT using the nCounter BC360 and IO360 panels, respectively. Gene networks and pathway analysis revealed that RT increases the gene signature of tumor inflammation (TIS), cytotoxicity, and apoptosis, while downregulating the gene signatures of tumor cell proliferation, differentiation, and cell adhesion, and increases the claudin-low gene score. RT-induced mammary stemness and enhanced infiltration of stroma, mast, and macrophage cells in the BC tumor microenvironment (TME). Further, the nCounter IO360 (immuno-oncology) panel analysis validated the findings of BC360 and demonstrated that RT increased the myeloid inflammation signature and chemokine expression, modulated B, T, NK, and DC cell activities, and enhanced residual cancer burden (RCB) in BC tumors, thus creating an immunosuppressive TME. Collectively, RT sensitized BC tumors by increasing the gene signature of TIS, cytotoxicity, apoptosis, and mammary stemness. RT facilitated an immunosuppressive environment and increased RCB, suggesting that the therapeutic potential of RT is highly individualized for each patient based on their unique tumor biology, genetic makeup, and TME.

Abstract Adipose‐derived cellular therapies (AD‐CTs) are increasingly used in orthopedics, yet the field lacks a standardized framework for classifying these heterogeneous products. Although prior efforts have standardized platelet‐rich plasma and bone marrow‐derived mesenchymal stromal cells, AD preparations remain inconsistently defined and poorly characterized. AD‐CTs encompass a range of products including enzymatically derived stromal vascular fraction, culture‐expanded adipose‐derived mesenchymal stromal cells (AD‐MSCs), and mechanically processed adipose tissue (AD‐MPT),each with distinct regulatory, cellular, and structural profiles. Unlike stromal vascular fraction and AD‐MSCs, which can be quantified using conventional assays, the intact extracellular matrix in AD‐MPTs complicates objective characterization. This paper introduces the Mechanical Processing (Harvesting) of Adipose Tissue classification system as a novel framework for standardizing the reporting of AD‐MPT harvesting and processing techniques that provides a structured approach to nomenclature and reporting. The system aims to enhance study comparability, facilitate research replication, and support the responsible advancement of adipose‐based therapies in musculoskeletal medicine.