Citations

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.

Abstract Introduction: Breast cancer genome-wide association studies (GWAS) have identified over 200 susceptibility loci, many replicated in diverse populations. However, cross-ancestry evaluation of breast cancer genetic architecture remains limited. We examined breast cancer genetic architecture using GWAS summary results from European (EUR; cases (ca) = 188,474, controls (co) = 96,201), East Asian (EAS; ca = 20,393, co = 86,329), African American (AA; ca = 9,235, co = 10,184), and US Hispanic/Latina and Latin American (H/L; ca = 2,396, co =7,468) studies. Methods: GWAS results were derived from the Breast Cancer Association Consortium, the African Ancestry Breast Cancer Genetics Consortium (AABCG), Biobank Japan, and a meta-analysis of five studies of H/L women with breast cancer. Linkage disequilibrium (LD) scores were generated for EUR, EAS, and AMR using the 1000 Genomes Project, while AA LD scores were derived from a subset of AABCG controls. Heritability was estimated for each ancestry group using LD score regression. Genetic correlations between populations were assessed via Popcorn. Polygenicity was analyzed using GENESIS; however, due to the limited sample size in the H/L studies, these estimates were restricted to AA, EAS, and EUR. Enrichment of heritability across regulatory elements was evaluated using stratified LD score regression across all populations. Results: The logit-scale heritability and corresponding standard error (SE) were 0.466 (0.066) for EAS, 0.501 (0.050) for EUR, 0.588 (0.360) for H/L, and 0.614 (0.095) for AA. The estimated number of independent susceptibility loci was 4,446 for EAS, 5,235 for EUR, and 8,308 for AA. Using a clumping and thresholding approach, an optimal set of common variants were projected to explain 38.6% (EUR), 39.4% (EAS), and 26.2% (AA) of genetic variance for samples of 100,000 cases and 100,000 controls with AUCs from corresponding estimated polygenic risk scores (PRSs) of 0.621 (EUR), 0.634 (EAS), and 0.611 (AA). Genetic correlations were strongest between EUR and EAS (ρ = 0.79, SE = 0.08) and EUR and H/L (ρ = 0.68, SE = 0.21), and weakest between AA and EAS (ρ = 0.42, SE = 0.14) and AA and H/L (ρ = 0.26, SE = 0.24). Among 73 genomic features, we found significant (P < 0.05/73) enrichment in heritability in EUR for ‘ancient promoter’ regions, transcription factor binding sites, H3K4me3, ‘super-enhancers’, H3K4me1, H3K27ac; in EAS for ‘super-enhancers’; and in AA for H3K27ac. No genomic features were significantly enriched in H/L, likely due to limited power. Conclusion: These findings suggest a shared breast cancer genetic architecture across diverse populations, as well as the potential for a similar level of breast cancer risk stratification by PRS in these populations. Expanding GWAS in underrepresented populations is essential to improve genetic risk predictions and foster equitable cancer prevention. Citation Format: James L. Li, Maria Zanti, Jacob Williams, Om Jahagirdar, Guochong Jia, Qiang Hu, Jean-Tristan Brandenburg, Li Yan, Weang-Kee Ho, Jingmei Li, José P. Miranda, Devika Godbole, Julie-Alexia Dias, Leila Dorling, Wenlong C. Chen, Nicholas Boddicker, Ying Wang, Alicia Martin, Martin J. Zhang, Yan Zhang, Joe Dennis, Esther M. John, Gabriela Torres-Mejia, Larry Kushi, Jeffrey Weitzel, Susan L. Neuhausen, Luis Carvajal-Carmona, Christopher Haiman, Elad Ziv, Laura Fejerman, Wei Zheng, Dezheng Huo, Douglas Easton, Nilanjan Chatterjee, Peter Kraft, Montserrat Garcia-Closas, Wendy Wong, Kyriaki Michailidou, Qianqian Zhu, Diptavo Dutta, Thomas U. Ahearn, Haoyu Zhang. Genetic architecture of breast cancer across diverse populations: Assessing heritability, genetic correlation, and polygenicity [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 2282.

Background Severe alcohol-associated hepatitis (sAH) is a life-threatening condition with high mortality, where corticosteroid use is the only treatment that has shown short-term benefits. Pentoxifylline, an anti-tumour necrosis factor-alpha agent, has been proposed for its potential to improve outcomes, especially in patients with acute kidney injury (AKI). We aimed to evaluate the impact of pentoxifylline on mortality in patients with sAH and AKI in a well-characterised global cohort. Methods We conducted a retrospective, registry-based study including patients meeting the National Institute on Alcohol Abuse and Alcoholism clinical criteria for sAH and AKI. Mortality was the primary endpoint, with liver transplantation as a competing risk. Statistical analysis included Cox regression and Kaplan-Meier survival estimates. Results We included 525 patients from 20 centres across eight countries. The median age was 48 years, with 26.1% females, and 76.9% had a history of cirrhosis. Multivariable Cox regression models showed that pentoxifylline use was not associated with survival (HR 1.20, 95% CI 0.85 to 1.69, p=0.291). Factors associated with mortality included age (HR 1.23, 95% CI 1.10 to 1.36, p<0.001), Model for End-Stage Liver Disease score at admission (HR 1.06, 95% CI 1.04 to 1.08, p<0.001) and renal replacement therapy use (HR 1.39, 95% CI 1.05 to 1.84, p=0.019). The main causes of death were multiple organ failure (42%), infections (10%), oesophageal varices bleeding (7%) and renal failure (6%). Conclusion Pentoxifylline showed no significant benefit on mortality in patients with sAH and AKI. Further studies are needed to refine treatment strategies for this high-risk group.

Abstract This study explores parallels between systemic hypoxia adaptation in high-altitude populations and tumorigenesis. We identified EPAS1, a gene critical for hypoxia adaptation in populations such as Tibetans and Sherpas, as playing a similar adaptive role in tumors arising under hypoxic conditions. Tumors from patients with chronic hypoxia displayed impaired DNA repair and frequent emergence of EPAS1 variants, with frequencies reaching up to 90%, echoing the positive selection seen in high-altitude dwellers. Mechanistically, EPAS1 gain-of-function mutations promote COX4I2 expression, reducing cellular oxygen consumption and supporting tumor proliferation in hypoxia. Analysis of clinical data from patients with hypoxia revealed tissue-specific and time-sensitive tumorigenic effects, particularly impacting oxygen-sensitive cells in the postnatal period. Our findings suggest that EPAS1-driven adaptation mechanisms in high-altitude populations provide a model for understanding tumor evolution under hypoxic stress, highlighting how genetic adaptations to diverse stressors in natural populations may yield insights into tumorigenesis and cancer progression. Significance: This study reveals a broad convergence in genetic adaptation to hypoxia between natural populations and tumors, suggesting that insights from natural populations could enhance our understanding of cancer biology and identify novel therapeutic targets. See related commentary by Lee, p. 875

Abstract Acute kidney injury (AKI) is a syndrome that entails a rapid decline in kidney function with or without injury. The consequences of AKI among acutely ill patients are dire and lead to higher mortality, morbidity, and healthcare cost. To prevent AKI and its short and long‐term repercussions, understanding its pathophysiology is essential. Depending on the baseline kidney histology and function reserves, the number of kidney insults, and the intensity of each insult, the clinical presentation of AKI may differ. While many factors are capable of inducing renal injury, they can be categorized into a few processes. The three primary processes reported in the literature are hemodynamic changes, inflammatory reactions, and nephrotoxicity. The majority of patients with AKI will suffer from more than one during their development and/or progression of AKI. Moreover, the development of one usually leads to the instigation of another. Thus, the interactions and progression between these mechanisms may determine the severity and duration of the AKI. Other factors such as organ crosstalk and how our concurrent therapies interact with these mechanisms complicate the pathophysiology of the progression of the AKI even further. In this narrative review article, we describe these three main pathophysiological processes that lead to the development and progression of AKI. © 2022 American Physiological Society. Compr Physiol 12: 3767–3780, 2022.

INTRODUCTION: The recent US Food and Drug Administration approval of resmetirom for treating metabolic dysfunction-associated steatohepatitis in patients necessitates patient selection for significant fibrosis or higher (≥F2). No existing vibration-controlled transient elastography (VCTE) algorithm targets ≥F2. METHODS: The mAchine Learning ADvanceD fibrosis and rIsk metabolic dysfunction-associated steatohepatitis Novel predictor (ALADDIN) study addressed this gap by introducing a machine-learning-based web calculator that estimates the likelihood of significant fibrosis using routine laboratory parameters with and without VCTE. Our study included a training set of 827 patients, a testing set of 504 patients with biopsy-confirmed metabolic dysfunction-associated steatotic liver disease from 6 centers, and an external validation set of 1,299 patients from 9 centers. Five algorithms were compared using area under the curve (AUC) in the test set: ElasticNet, random forest, gradient boosting machines, XGBoost, and neural networks. The top 3 (random forest, gradient boosting machines, and XGBoost) formed an ensemble model. RESULTS: In the external validation set, the ALADDIN-F2-VCTE model, using routine laboratory parameters with VCTE (AUC 0.791, 95% confidence interval [CI]: 0.764–0.819), outperformed VCTE alone (0.745, 95% CI 0.717–0.772, P < 0.0001), FibroScan-aspartate aminotransferase (0.710, 0.679–0.748, P < 0.0001), and Agile-3 model (0.740, 0.710–0.770, P < 0.0001) regarding the AUC, decision curve analysis, and calibration. The ALADDIN-F2-Lab model, using routine laboratory parameters without VCTE, achieved an AUC of 0.706 (95% CI: 0.668–0.749) and outperformed Fibrosis-4, steatosis-associated fibrosis estimator, and LiverRisk scores. DISCUSSION: Along with the steatosis-associated fibrosis estimator model developed to target significant fibrosis or higher, ALADDIN-F2-VCTE (https://aihepatology.shinyapps.io/ALADDIN1) uniquely supports a refined noninvasive approach to patient selection for resmetirom without the need for liver biopsy. In addition, ALADDIN-F2-Lab (https://aihepatology.shinyapps.io/ALADDIN2) offers an effective alternative when VCTE is unavailable.

Background: Severe alcohol-associated hepatitis (sAH) is a well-characterized disease with high short-term mortality. However, there is limited research on those with a “less severe condition” (moderate AH). This study aims to characterize in-depth patients with moderate AH (mAH), including the performance of mortality scoring systems, key prognostic factors, and survival over time. Methods: A multicenter retrospective cohort study (2009–2019) included patients with mAH (MELD score ≤20 at admission). Cox regression and receiver operating characteristic curves with AUC were used for analysis. Results: We included 1845 patients with AH (20 centers, 8 countries) between 2009 and 2019. mAH was defined as a MELD score ≤20 at admission. Twenty-four percent met the criteria for an mAH episode. Patients with mAH tend to be older and have a higher proportion of females, with a median MELD of 17 (15–19), Maddrey discriminant function (mDF) of 33 (22–40), the trajectory of serum bilirubin of 0.83 (0.60–1.21), and neutrophil-to-lymphocyte ratio (NLR) of 5 (2.96–8.60). The primary causes of death in mAH included multiple organ failure (34.1%) and infections (16.6%). The cumulative survival rates at 30, 90, and 180 days were 94.3%, 90.4%, and 88.2%, respectively. In multivariable analysis, age was the only significant predictor of 30-day mortality (HR 1.49, 95% CI: 1.27–1.76, p <0.001). Mortality prediction models showed poor performance, with AUC for MELD (0.671), mDF (0.726), trajectory of serum bilirubin (0.733), and NLR (0.697). Conclusions: Patients with moderate AH exhibited a mortality of 11.8% at 6 months, primarily driven by multiple organ failure and infections. These patients also exhibit a different clinical profile compared to those with sAH. Tailored models and therapeutic strategies are needed to improve long-term outcomes in mAH.

Importance Neoadjuvant systemic therapy (NST) has been associated with pathologic complete response (pCR) in up to 60% of breast cancers (BCs). The findings of this trial question the necessity of surgery. Objective To report preplanned 5-year efficacy outcomes evaluating radiotherapy alone without breast surgery in patients selected with image-guided vacuum assisted biopsy (VAB). Design, Setting, and Participants This single-arm, prospective, phase 2 nonrandomized clinical trial was conducted at 7 US medical centers and included women 40 years or older with cT1-2N0-1M0 ERBB2 -positive (formerly HER2 -positive) or triple-negative invasive BC who showed residual breast lesions after NST of less than 2 cm on imaging. Enrollment was from March 6, 2017, to November 9, 2021. Data analysis was from October to December 2024. Intervention Image-guided VAB of the tumor bed (9G with a minimum of 12 cores) was performed after standard NST. Patients with clinically node-negative disease at diagnosis and no residual cancer in the breast on post-NST VAB underwent whole-breast radiotherapy with a boost without breast or axillary surgery. Patients with initial documented nodal disease and a breast pCR on VAB underwent targeted axillary dissection, while those with residual cancer when undergoing VAB had standard breast and axillary surgery. Patients were monitored with physical examinations and mammography every 6 months. Main Outcome Measures The primary outcome was ipsilateral breast tumor recurrence. Results Fifty patients (median [IQR] age, 62 [55-77] years) were enrolled and underwent post-NST VAB. Twenty-nine (58%) and 21 (42%) patients had ERBB2 -positive and triple-negative invasive BC, respectively. Breast pCR on VAB was identified in 31 patients (62%; 95% CI, 47.2%-75.34%), and axillary pCR was identified among all 8 patients with initial nodal metastases and breast pCR on VAB who underwent targeted axillary dissection. At a median follow-up of 55.4 (IQR, 44.0-63.5) months, the ipsilateral breast tumor recurrence rate was 0%, and disease-free and overall survival rates were 100% for patients without breast surgery. Conclusions and Relevance The results of this nonrandomized clinical trial that reported preplanned 5-year outcomes suggest that omission of breast surgery in select patients after NST may be feasible, with no recurrences seen. More confirmatory studies are necessary before this new approach alters surgical practice. Trial Registration ClinicalTrials.gov Identifier: NCT02945579

ACE2 protein binds heme, which we reasoned would promote heme entry into the kidney and, accordingly, heme protein-mediated acute kidney injury. Our findings support this hypothesis. This study is the first to demonstrate the biological relevance of ACE2-heme binding, uncover a new pathway of heme-dependent kidney injury, and identify myoglobin and heme as novel determinants of ACE2 expression. Our study explains why plasma levels of myoglobin and heme predict poor outcomes in patients with COVID-19.