Citations

Abstract Background: While cancer immunotherapies have revolutionized treatment, their efficacy remains limited for most patients, highlighting tumors' capacity to evade immune detection. Epigenetic modifications, particularly DNA methylation, play a pivotal role in silencing immune-related pathways, thereby facilitating immune escape. By modulating gene expression, methylation disrupts immune activation, contributing to reduced tumor immunogenicity. This study examines the methylation landscape of co-stimulatory and immune checkpoint genes across various cancers to elucidate how these changes influence immune responses. Methods: Using The Cancer Genome Atlas (TCGA), we analyzed methylation and gene expression profiles across diverse cancer types. Data from 8,186 solid tumors and 745 adjacent normal tissues were processed via t-distributed stochastic neighbor embedding (t-SNE) with 247 probes targeting 20 immune-related genes. Principal component analysis (PCA) was applied to capture methylation variability across 8,931 tumor and normal samples. To explore the effects of methylation on immune gene expression, we analyzed data from 26 epithelial cancer cell lines treated with 5-azacitidine, a demethylating agent, using the GSE57342 dataset. Post-treatment changes in gene expression were assessed, and survival analyses from prior studies were used to explore clinical correlations. Results: We identified distinct methylation patterns in immune synapse genes, differentiating tumors from adjacent normal tissues. Co-stimulatory genes such as CD40 were hypermethylated in tumors, correlating with decreased expression, whereas immune checkpoint genes like PDL1 and HHLA2 were hypomethylated, correlating with increased expression. This inverse relationship between methylation and gene expression underscores the transcriptional regulatory role of DNA methylation. Treatment with 5-azacitidine reversed hypermethylation in co-stimulatory genes, including CD40, potentially enhancing immune recognition. Methylation levels of these genes were also associated with T cell infiltration into the tumor microenvironment and predicted better outcomes in melanoma patients, underscoring their clinical relevance. Conclusion: This study demonstrates that DNA methylation of immune synapse genes contributes to tumor immune evasion by modulating immune gene expression. Targeting these epigenetic alterations represents a promising strategy to restore tumor immunogenicity and improve immunotherapy outcomes, particularly when combined with immune checkpoint inhibitors. Reversing methylation-driven immune suppression could strengthen the immune response and enhance clinical outcomes for cancer patients. Citation Format: Imene Hamaidi, Anders Berglund, Matthew Mills, Ryan M. Putney, James J. Mulé, Sungjune Kim. DNA methylation of immune synapse genes drives tumor immune evasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4831.

Abstract Despite advances in surgery and chemotherapy, patients with resectable pancreatic ductal adenocarcinoma (PDAC) face high recurrence rates (40-60%). Total neoadjuvant therapy (TNT) seeks to enhance margin-negative resections (R0) and address micrometastatic disease, with potential survival benefits. Yet, TNT still results in high recurrence rates, with 1-, 2-, and 3-year disease-free survival (DFS) at 65%, 48%, and 32%, respectively. Residual cancer extent is a key prognostic factor in PDAC after TNT. Tumor response scores show favorable outcomes only for patients achieving near-complete or complete pathologic response. In a cohort of 511 PDAC patients treated with TNT and surgery (2015-2022), improved DFS was only found in those with a complete pathologic response (pCR, 7.8%). This highlights the limited use of current response scoring in stratifying post-TNT patient risk, underscoring the need to better understand disease persistence and relapse. Here we developed a quantitative method to assess residual cancer. Using a digital pathology H&E library from 2180 PDAC cases (2000-2022), an AI platform segmented tissue into cancer epithelium, stroma, and normal regions. For 202 TNT-treated cases without pCR, we calculated a ratio of cancer area to stromal area from representative slides. Modeled after the histologic tumor regression grade (HTRG) system, cases were classified into <5%, 5-50%, or >50% cancer-to-stroma ratios. However, this measure alone showed no difference in DFS, suggesting tumor burden cannot fully explain differences in clinical outcomes. We hypothesized that the spatial organization of the tumor microenvironment (TME) is a determinant of patient outcomes. Drawing from landscape ecology, which studies spatial properties of ecosystems, we applied similar principles to analyze tissue architecture. Using an AI-based two-class segmentation of whole-slide images, we assessed spatial features like patch area, perimeter, density, and Shannon diversity. Python’s ‘pylandstats’ package calculated 21 spatial metrics, reduced via stepwise Cox regression using the Akaike information criterion (AIC). The final model included mean Shannon diversity, mean and standard deviation of stromal patch areas, and stromal patch density. Kaplan-Meier analysis of 202 samples stratified model predictions into quartiles, correlating with high (mean DFS 10.85 months), medium (19.32 months), and low risk (25.92 months) groups. These findings aligned with model expectations, underscoring the potential of spatial TME analysis to predict outcomes. Citation Format: Andrea V. Maraone, Zafar Siddiqui, Luis H. Cisneros, Merih D. Toruner, Mark Truty, Cornelius Thiels, Robert R. McWilliams, Steven R. Alberts, Rondell P. Graham, Carlo Maley, Qian Shi, Martin E. Fernandez-Zapico, Ryan M. Carr. Tumor spatial configuration predicts pancreatic cancer recurrence risk after total neoadjuvant therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5070.

Background: Multicellular programs in the tumor microenvironment (TME) drive cancer pathogenesis and response to therapy but remain challenging to identify and profile clinically. Here, we present Spatial EcoTyper, a multimodal machine learning framework for large-scale profiling of spatially dependent cell states and multicellular ecosystems, termed spatial ecotypes (SEs). Methods and Findings: By integrating five million single-cell and spot-level spatial transcriptomes from 10 diverse human neoplasms, including carcinomas and melanomas, we identified a rich tapestry of conserved regional plasticity across nine TME cell types. We then applied Spatial EcoTyper to deeply dissect these data, revealing nine novel SEs with broad conservation - each with unique biology, TME cell states, geospatial features, and clinical outcome associations. SEs were linked to specific biogeographic domains, including the tumor core, margin, and adjacent stroma, and were remarkably well-validated in 235 held-out tumor samples profiled by either single-cell RNA sequencing, sequencing-based spatial transcriptomics (10x Visium), or high-resolution imaging-based spatial transcriptomics (Vizgen MERSCOPE and NanoString CosMx). By deconvolving SEs from over 1,200 bulk tumor RNA-seq profiles, we discovered striking associations between SE levels and response to immune checkpoint inhibitors (ICIs), outperforming nearly 40 potential correlates of ICI response, including previously described signatures of tertiary lymphoid structures and tumor tissue PD-L1 expression. Notably, baseline levels of a proinflammatory SE - localized to the tumor core and defined by a hub of unique T cell, macrophage, fibroblast, and endothelial cell states - strongly forecasted ICI benefit, while another SE - localized to the tumor margin and defined by myofibroblast and hypoxia-associated endothelial cell states - portended ICI resistance. Conclusion: Our data reveal fundamental units of TME organization and demonstrate a platform for large-scale profiling of spatial cellular ecosystems in any tissue, with implications for improved forecasting of immunotherapy response and the development of novel therapeutic strategies. Citation Format: Wubing Zhang,Erin L. Brown,Abul Usmani,Noah Earland,Hyun Soo Jeon,Irfan Alahi,Nicholas P. Semenkovich,Janella C. Schwab,Chloé B. Steen,Chloe M. Sachs,Bilge Gungoren,Faridi Qaium,Peter K. Harris,Jacqueline Mudd,Qingyuan Cai,Antonella Bacchiocchi,Ryan C. Fields,Mario Sznol,Ruth Halaban,David Y. Chen,Aadel A. Chaudhuri,Aaron M. Newman. High-resolution profiling of the tumor microenvironment with spatial ecotypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 153.

Abstract SWI/SNF chromatin remodeling complexes are frequently mutated across human cancers, including cholangiocarcinoma (CCA). Dysregulation of this complex due to loss of function mutations in AT-rich interaction domain-1A (ARID1A) and polybromo-1 (PBRM1) occur in up to 18% and 10% of cases respectively. SWI/SNF subunit mutations frequently co-occur alongside PI3K/AKT pathway activation. Preexisting literature suggests altered gene expression and protein synthesis contribute to CCA oncogenesis, but our understanding of these mechanisms remains immature. Genetically accurate preclinical models are needed to define the roles of ARID1A and PBRM1 in CCA and identify therapeutic targets. We developed novel murine models of CCA with either ARID1A, PBRM1 or dual ARID1A/PBRM1 (APAC) knockout in the context of AKT activation, utilizing a surgical biliary transfection method for somatic gene editing with CRISPR/Cas9. Within 8 months, mice formed numerous liver tumors, predominantly CCA and mixed CCA/HCC. Knockout of ARID1A and PBRM1 was confirmed through genomic PCR, qRT-PCR, and immunoblot assays. Histologically, murine APAC tumors displayed phenotypic similarities to human CCA, including dense cancer-associated fibroblast infiltration and variable CD45+ immune cell infiltration. A novel, syngeneic CCA cell line was isolated from a dual ARID1A/PBRM1 knockout tumor (APAC-2). RNA-sequencing of primary tumors and the APAC-2 cell line versus a non-invasive cholangiocyte cell line with AKT activation only (AC), was performed to identify differentially expressed genes (DEGs) of interest in ARID1A and PBRM1-deficient CCA. Periostin (Postn) was among the top upregulated genes in the APAC-2 cell line. POSTN is a secreted glycoprotein that is upregulated in human CCA and may be therapeutically targetable. Knockdown of periostin inhibited the in vitro growth of APAC-2 cells and a human CCA cell line with ARID1A mutation and periostin overexpression (HuH-28). These studies serve to characterize and validate a genetically relevant murine model of epigenetic dysregulation in ARID1A and PBRM1-deficient CCA. This model can be used for identification and validation of potential drug targets. Ongoing work focuses on studying multiple dysregulated pathways and testing dependence on genes of interest, including periostin, as potential treatment strategies for CCA. Citation Format: Jayla Millender, Jennifer Tomlinson, Ryan Watkins, Danielle Carlson, Jack Sample, Nathan Werneburg, Rory Smoot, Keith Robertson, Gregory Gores, Caitlin Conboy. Novel murine models of epigenetic dysregulation in SWI/SNF-mutated cholangiocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2741.

Abstract Background We aimed to evaluate the effectiveness and safety of risankizumab (RZB) for Crohn’s disease (CD) in routine clinical practice. Methods We performed a retrospective review of a multicenter consortium of CD patients treated with RZB. Co-primary outcomes were week 12 clinical remission (Harvey Bradshaw Index [HBI] score of ≤4 or physician global assessment in those without HBI or with ileostomy) and 6-month endoscopic remission (Simplified Endoscopic Mucosal Assessment for Crohn’s Disease of 0-1 or absence of ulcers). Secondary outcomes included steroid-free clinical remission, clinical response, radiographic response, cumulative clinical and endoscopic remission rates at 6 and 12 months, and adverse events. Results A total of 309 patients were included (median disease duration 14 years [IQR, 6-24]; median follow-up 7.1 months [IQR, 4.1-10.3]). Most patients (85.8%) were advanced therapy (AT)-exposed, and 169 (54.7%) had prior ustekinumab (UST) exposure. Week 12 clinical remission rates were 49.7% (98/197) overall, and 44.2% (50/113) vs 57.1% (48/84) in UST-exposed vs naïve patients (P = .073). Among those with active disease on baseline endoscopy (n = 122) who had an available follow-up at 6 months, 52.4% (22/42) achieved endoscopic remission. Cumulative rates of clinical and endoscopic remission at 12 months were 65.0% and 49.5%, respectively. Cumulative 12-month endoscopic remission was 33.9% (19/56) in UST-exposed and 68.1% (32/47) in UST-naïve patients (P < .001). Risankizumab was well-tolerated with no new safety signals identified. Conclusions In this large multicenter cohort of patients with CD, RZB was well-tolerated and effective in achieving favorable clinical and endoscopic outcomes in both AT-exposed and naïve populations, including those with exposure to UST.

Objective: Over 3 million Americans have heart failure with preserved ejection fraction (HFpEF). Effective guideline directed medical treatments (GDMT) are increasingly available but patients with HFpEF are likely under-detected (particularly women) and not receiving GDMT. Limited data are available informing the extent of HFpEF under-detection in the community. Hypothesis: Among patients with undifferentiated dyspnea and a high risk for unrecognized HFpEF, fewer than 50% will receive a HFpEF diagnosis during two years of follow-up; underrecognition will be greater among women. Methods: We identified 22,134 patients aged ≥30 in the Rochester Epidemiology Project (a medical records linkage system comprising a 27-county region of southeastern Minnesota and western Wisconsin) with evidence of unexplained dyspnea (≥2 ICD codes for dyspnea separated by >1 day) without prior documented etiology including HF or lung disease, during the time period 2018-2022. We calculated the recently validated HFpEF-Age-BMI-Atrial Fibrillation (HFpEF-ABA) score to estimate the probability of underlying HFpEF. Cox proportional hazards models regressed risk for incident HFpEF diagnosis on HFpEF-ABA score (dichotomized as ≥80% vs. <80%) with multivariable adjustment for sex, race and ethnicity. HRs(95%CIs) are presented. Results: Patients were 59±16 yrs, 50.8% women, 88.6% white, 3.1% Black, 3.7% other race, 4.6% Hispanic. Atrial fibrillation prevalence was 9.4% and mean BMI=31.4±7.8. Prevalence of HFpEF-ABA≥80% was 22.4%(n=4,958): 22.7% among women and 22.1% among men. The cumulative incidence of clinically-recognized HFpEF diagnosis at two years follow-up was 9.7% among women and 12.8% among men (log-rank p<0.01). HFpEF incidence was elevated with high HFpEF-ABA scores(≥80%): HR(95%CI) among women=3.72 (3.35, 4.14), and men=3.42 (3.11, 3.76). Among those with clinically diagnosed HFpEF during follow-up, mean time from date of first dyspnea ICD code to HFpEF diagnosis was 1.26 years overall: 1.31 and 1.21 years in women and men, respectively (p=0.05). Conclusions: One in five patients with undifferentiated dyspnea have probable undiagnosed HFpEF, and of that group, only 30% receive a clinical diagnosis, requiring an average of over 1 year to be recognized. The rate of diagnosis is even lower among women than men. Further study is warranted to implement evidence-based algorithms supporting detection of undiagnosed HFpEF in the community, especially in women.

Background: Despite the availability of effective vaccines and a recent decrease in annual deaths, coronavirus disease-2019 (COVID-19) remains a leading cause of death. Serological studies of anti-nucleocapsid (N) antibody response to infection provide insights into host immunobiology of adaptive immune response, which holds promise for identifying high-risk individuals for adverse acute and chronic COVID-19 outcomes. Hypothesis: Among participants previously infected with SARS-CoV-2, traditional vascular disease risk factors are associated with higher anti-N antibodies while vaccination is associated with lower anti-N antibodies. Methods: Among previously infected participants, anti-N antibodies were measured from dried blood spots collected between February 2021-February 2023 among 1,419 Collaborative Cohort of Cohorts for COVID-19 Research (C4R) participants with prior SARS-CoV-2 infection. We measured anti-N IgG antibodies reported as median fluorescence intensity (MFI) units; reactivity (i.e., seropositivity) was defined based on MFI above a validated threshold. Vascular disease risk factors were assessed via pre-pandemic in-person examination, questionnaires, and medical record review. Multivariable generalized linear models regressed anti-N reactivity (modified Poisson) or LN transformed MFI (linear). Results: Among 1,419 participants with prior infection, mean age (standard deviation) was 65.8(12.1) years, 61% were women, and 42.8% were self-reported from a race/ethnicity minority group. Participant reactivity to nucleocapsid peaked at 69% by 4 months post-infection and waned to only 44% ≥12 months after infection. After multivariable adjustment, higher anti-N antibody response was associated with older age, Hispanic (vs. White) or American Indian (vs. White) race/ethnicity, lower income and education, former smoking, and higher anti-spike antibody levels. Asian race (vs. White) and vaccination ( even after infection ) were associated with lower nucleocapsid reactivity; common cardiometabolic co-morbidities were not associated with anti-N reactivity or levels (Figures 1 and 2). Conclusions: Among participants previously infected with SARS-CoV-2, select sociodemographic and behavioral risk factors were associated with higher anti-N antibody levels while vaccination was associated with lower anti-N antibody levels. The observation that vaccination, even after infection, is related to lower anti-N antibody levels merits further investigation.

Background: Thrombo-inflammation is a hallmark of acute Covid-19, with higher thrombo-inflammatory markers during infection associated with adverse outcomes. We hypothesized that higher pre-pandemic biomarkers, reflecting a higher thrombo-inflammatory setpoint, might identify people at greater risk of severe manifestations of Covid-19. Hypothesis: Pre-pandemic inflammation markers are associated with risk of hospitalized or fatal (hereafter, “severe”) Covid-19 in a multi-ethnic US sample. Methods: From 2020-2023, C4R harmonized pre-pandemic measures and ascertained Covid-19 across 14 longstanding cohort studies. In 12 cohorts, we assessed biomarker data and covariates from the study visit closest to the pandemic for 6 analytes shown in the Table. HRs of severe Covid-19 by pre-pandemic biomarkers were estimated using cause-specific Cox regression, treating non-severe Covid-19 as a competing risk, and adjusting for pre-pandemic sociodemographic and clinical characteristics. Results: Biomarkers were measured a mean of 20 years before the pandemic with different sample sizes for each (Table footnote). Mean age at the start of the pandemic was in the 60s or 70s depending on the biomarker. The most represented race or ethnic groups were White and Black. The largest sample was for C-reactive protein, and there were 1,001 severe Covid-19 cases among 38,784 participants. In the adjusted models, considered individually, higher CRP, leukocyte count, factor VIII and fibrinogen, but not other markers, were associated with greater risk of severe Covid-19 (Table).Associations were robust across subgroups and time since biomarker measurement (example for C-reactive protein in Figure). Conclusions: In this prospective multi-study analysis of a multi-ethnic population, higher basal levels of thrombo-inflammation markers were associated with greater risk of severe Covid-19. Since we considered non-severe Covid-19 as a competing risk, associations may reflect factors related to progression to more serious Covid-19 illness.

Abstract Rationale Increased risk of coronavirus disease (COVID-19) hospitalization and death has been reported among patients with clinical lung disease. Objectives To test the association of objective measures of prepandemic lung function and structure with COVID-19 outcomes in U.S. adults. Methods Prepandemic obstruction (FEV1/FVC &lt; 0.70) and restriction (FEV1/FVC ⩾ 0.7, FVC &lt; 80%) were defined based on the most recent spirometry exam conducted in 11 prospective U.S. general population–based cohorts. Severe obstruction was classified by FEV1 &lt; 50%. Percentage emphysema, percentage high-attenuation areas, and interstitial lung abnormalities were defined on computed tomography in a subset. Incident COVID-19 was ascertained via questionnaires, serosurvey, and medical records from 2020 to 2023 and classified as severe (hospitalized or fatal) or nonsevere. Cause-specific hazard models were adjusted for sociodemographics, anthropometry, smoking, comorbidities, and COVID-19 vaccination status. Measurements and Main Results Among 29,323 participants (mean age, 67 yr), there were 748 severe incident COVID-19 cases over median follow-up of 17.3 months from March 1, 2020. Greater hazards of severe COVID-19 were associated with severe obstruction (vs. normal; adjusted hazard ratio [aHR], 2.11; 95% confidence interval [CI], 1.02–1.27), restriction (vs. normal; aHR, 1.40; 95% CI, 1.12–1.76), and percentage emphysema (highest vs. lowest quartile; aHR, 1.64; 95% CI, 1.03–2.61), but not greater high-attenuation areas or interstitial lung abnormalities. COVID-19 vaccination provided greater absolute risk reduction in these groups. Results were similar in participants without smoking, obesity, or clinical cardiopulmonary disease. Conclusions Prepandemic severe spirometric obstruction, spirometric restriction, and greater percentage emphysema lung on computed tomography were associated with risk of severe COVID-19. These findings support enhanced COVID-19 risk mitigation for individuals with impaired lung health and warrant further mechanistic studies on interactions of lung function, structure, and vulnerability to acute respiratory illnesses.

Background: Artificial intelligence (AI) platforms can potentially enhance clinical decision-making (CDM) in primary care settings. OpenEvidence (OE), an AI tool, draws from trusted sources to generate evidence-based medicine (EBM) recommendations to address clinical questions. However, its effectiveness in real-world primary care cases remains unknown. Objective: To evaluate the performance of OE in providing EBM recommendations for five common chronic conditions in primary care: hypertension, hyperlipidemia, diabetes mellitus type 2, depression, and obesity. Methods: Five patient cases were retrospectively analyzed. Physicians posed specific clinical questions, and OE responses were evaluated on clarity, relevance, evidence support, impact on CDM, and overall satisfaction. Four independent physicians provided ratings using a 0 to 4 scale. Results: OE provided accurate, evidence-based recommendations in all cases, aligning with physician plans. OE was scored on a scale of zero to four, where zero was very unclear, and four was very clear. Mean scores across cases were clarity (3.55 ± 0.60), relevance (3.75 ± 0.44), support (3.35 ± 0.49), and satisfaction (3.60 ± 0.60). However, the impact on CDM was limited (1.95 ± 1.05), as OE primarily reinforced rather than modified plans. Conclusion: OE was rated high in clarity, relevance, and evidence-based support, reinforcing physician decisions in common chronic conditions. While the impact on CDM was minimal due to the study’s retrospective nature, OE shows promise in augmenting the primary care physician. Prospective trials are needed to evaluate its utility in complex cases and multidisciplinary settings.