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Background: Aggressive non-Hodgkin lymphoma (aNHL) commonly occurs in older adults. However, geriatric assessments (GAs), which are associated with both survival and treatment-related toxicity, are infrequently performed due to logistical constraints. In this study, we examined how the brief, self-reported Vulnerable Elders Survey-13 (VES-13) screening tool and a comprehensive GA relate to clinical outcomes in this population. Methods: We conducted a longitudinal study of 105 adults aged ≥65 years who were initiating upfront chemoimmunotherapy for aNHL at 2 academic medical centers and their community affiliates between September 2020 and January 2023. Baseline frailty was evaluated using the Fondazione Italiana Linfomi (FIL) GA, which classifies patients as fit, unfit, or frail. The VES-13 was assessed both continuously and by categorizing patients as vulnerable (score ≥3). Using logistic regression controlling for covariates, we examined the association of VES-13 with grade ≥3 nonhematologic toxicity (toxicity), unplanned hospitalization within 6 months of treatment initiation, decline in quality of life (QoL) 1 year after therapy initiation, and death within 1 year of treatment initiation. In addition, we calculated the sensitivity and specificity of both the VES-13 and the FIL GA in identifying patients at risk for these outcomes. Results: The median patient age was 73 years (range, 64–99 years), with 42% aged ≥75 years. GA classified 40% of patients as fit, 10% as unfit, and 51% as frail, while 46% of patients had a VES-13 score ≥3, indicating vulnerability. VES-13 score was significantly associated with toxicity (odds ratio [OR], 1.18; P =.026), unplanned hospitalization (OR, 1.16; P =.043), QoL decline at 1 year (OR, 1.22; P =.027), and death within 1 year (OR, 1.49; P =.010). Using the VES-13 to define vulnerability (score ≥3), sensitivity and specificity were 59% and 61% for predicting toxicity, and 100% and 59% for predicting death within 1 year, respectively. FIL GA frailty had a sensitivity of 63% and specificity of 56% for predicting toxicity, and 100% sensitivity and 54% specificity for predicting death within 1 year. Conclusions: We found that VES-13 score was associated with survival, toxicity, health care utilization, and QoL decline, demonstrating similar sensitivity and specificity to the FIL GA. These findings underscore the potential utility of VES-13 as a screening instrument to identify older patients with aNHL at risk for adverse clinical outcomes.

BACKGROUND: Bicuspid aortic valve (BAV) is a frequent congenital heart defect with a high heritability. Despite this, only a limited number of genes have been associated with the disease, and the molecular mechanisms remain unexplained in most cases. This study aimed to further understand the genetic architecture of BAV. METHODS: A genome-wide association study meta-analysis including 9631 cases among 65 677 participants was performed. Genes were prioritized using transcriptomic analyses based on RNA sequencing in relevant tissues, including human fetal and adult aortic valves. The impact of the knockdown or knockout of 4 candidate genes on cardiac development was verified in zebrafish. A polygenic risk score was developed, its association with BAV was evaluated in an independent cohort, and its association with a wide range of phenotypes (n=976) was evaluated in UK Biobank (n=355 618 individuals). RESULTS: Thirty-six genomic loci were identified, including 32 that were not described previously. Among the prioritized genes, KANK2 and ERBB4 were identified as potentially causal through transcriptomic analyses, colocalization, and Mendelian randomization based on gene expression in human aortic valves (n=484), whereas PRDM6 and STRN were prioritized using similar analyses from aortic (n=326) and left ventricular tissues (n=326), respectively. Targeting 4 candidate genes ( WNT4 , LEF1 , STRN , and KANK2 ) in zebrafish led to disruption in cardiac development. A polygenic risk score was associated with an odds ratio of 2.07 (95% CI, 1.90–2.25; P =5.43×10 -62 ) per SD for BAV and significantly associated with thoracic aortic aneurysm and atrial fibrillation in UK Biobank. CONCLUSIONS: This study supports a significant polygenic contribution to BAV, where the combination of multiple common variants in genes involved in heart morphogenesis disrupts aortic valve development.

Abstract Enhancer is a critical epigenetic feature in head and neck squamous cell carcinoma (HNSCC), yet the functional roles of individual enhancers remain poorly understood. Here, we conducted an integrative multi-omics analysis based on publicly available ATAC-seq, H3K27ac ChIP-seq, transcriptomic profiling, and genetic association datasets to systematically map HNSCC-associated enhancers and their target genes. Integrating ATAC-seq and H3K27ac ChIP-seq, we identified 20,362 enhancers and 18,040 enhancer-associated genes, highlighting widespread regulatory complexity. Functional characterization of the TERT -associated enhancer GH05J001312 (GRCh38/hg38: chr5:1312099-1317743) revealed strong transcriptional activity in HNSCC. CRISPR-mediated deletion of a core sequence significantly reduced TERT expression, impaired cellular proliferation in vitro , and suppressed tumor growth in vivo , confirming its role as a key cis-regulatory element. RNA-seq analysis of enhancer-edited cells uncovered 742 differentially expressed genes enriched in cancer-related pathways, including MAPK and IL-17 signaling, indicating a broad transcriptional impact. Collectively, our findings establish GH05J001312 as a functional enhancer driving oncogenic programs in HNSCC and suggest enhancer-targeted strategies as a potential therapeutic avenue.

ABSTRACT Tumorigenesis and metastasis are frequently attributed to the intricate interplay between cancer cells and the tumor microenvironment (TME). Comprehending the mechanisms and key regulators of cancer‐immune crosstalk in the TME is imperative for developing efficacious immunotherapy. Through a series of in vivo CRISPR screens, we identified tumor‐intrinsic ITGB1 as a critical regulator of triple‐negative breast cancer (TNBC) development and deciphered its underlying mechanisms. Tumoral ITGB1 facilitated the establishment of pro‐tumorigenic TME by orchestrating tumor‐associated myeloid populations. Suppressing ITGB1 favored the enrichment of anti‐tumorigenic myeloid cells and enhanced infiltration of CD4 and CD8 T cells, culminating in superior antitumor effects. CRISPR scanning pinpointed a previously unrecognized functional domain essential for ITGB1's pro‐tumorigenic activity. This domain is distinct from all known ligand‐binding sites in ITGB1. An antibody capable of sterically blocking this domain significantly impaired TNBC progression. These findings position tumoral ITGB1 as a promising therapeutic target for reprogramming the TME from a pro‐ to an anti‐tumorigenic state, thereby effectively inhibiting TNBC development. Our study uncovers a novel mechanism of TNBC development and provides a unique therapeutic strategy for targeting ITGB1 in TNBC treatment.

Abstract High-grade gliomas (HGGs) are aggressive tumors with poor outcomes and limited treatment options. Here, we combined genomic and transcriptomic tumor profiling with drug testing in a patient-derived 3-dimensional culture model to identify individualized treatments and predictive biomarkers. Activity of single agents targeting frequently dysregulated glioma pathways was relatively poor ex vivo and generally reflected historical patient data. However, compounds targeting PI3K, epigenetic, and survival/senescence signaling were effective in some cases. Drug sensitivity correlated with transcriptional rather than genomic features and suggested heterogeneity as a resistance mechanism. Bromodomain and extraterminal domain inhibition was particularly effective in tumors enriched in the mesenchymal transcriptional subtype, promoted proneural transition, and was overcome by upregulated PI3K signaling. Notably, combinations were largely effective, with 6 strategies exhibiting stronger efficacy than corresponding single agents in most cases (58-77%). This study identifies HGG vulnerabilities and associated biomarkers, resistance mechanisms, and effective combination strategies that warrant further clinical validation. Graphical Abstract

Thiopurine methyltransferase (TPMT) and Nudix hydrolase 15 (NUDT15) are key enzymes that catabolize thiopurines. Decreased or no‐function alleles in TPMT and NUDT15 are associated with reduced or no enzyme activity and predictive of pronounced adverse effects, including severe myelosuppression, that may occur among individuals treated with standard doses of thiopurines. Genetic variants in these genes are present in all world populations; however, their frequency varies by ancestry. In this updated guideline, we provide recommendations for adjusting starting doses of mercaptopurine, thioguanine, and azathioprine based on TPMT and NUDT15 genotypes, including for individuals with variants in both genes (updates on www.clinpgx.org ).

Abstract Background Electronic health record (EHR)–based prognostic modeling is increasingly used in oncology, yet incorporating pharmacogenomic (PGx) knowledge derived from experimental systems into clinical prediction frameworks remains challenging. This gap is driven by fundamental mismatches between controlled drug–mutation assays and heterogeneous, incomplete real-world clinical data. Methods We propose a representation transfer framework that integrates PGx embeddings learned from large-scale in vitro pharmacogenomic screens into patient-level EHR models. A frozen pharmacogenomic encoder is used to generate interaction-aware embeddings from patient mutation profiles and administered therapies, which are aggregated into a fixed-length PGx Complementarity Representation. These representations are incorporated into multimodal survival prediction models alongside standard clinical features. Performance was evaluated using systematic modality ablation analyses, attribution analyses, and exploratory unsupervised representation analyses. Results Integrating PGx embeddings yielded consistent performance improvements across all evaluated modality combinations. Relative gains were largest in modality-sparse settings, where baseline EHR features encode limited biological context, and were attenuated—but remained significant—in biologically enriched configurations. Attribution analyses indicated that PGx embeddings contributed non-redundant predictive signal beyond standard clinical features. Exploratory unsupervised analyses further demonstrated that the learned representations exhibit interpretable association patterns aligned with known therapeutic exposures and pathway-level associations. Conclusion These findings suggest that externally learned pharmacogenomic representations can be transferred into real-world EHR models as a context-dependent, non-redundant augmentation. By framing PGx knowledge as an interaction-aware representation rather than a mechanistic model, this work provides an informatics framework for integrating experimental pharmacogenomic data into clinical prediction tasks in a reproducible and interpretable manner.

Background Fenestrated and branched endovascular aneurysm repair can be complicated by branch vessel occlusion in the absence of structural stenosis. We hypothesized that computational flow simulation could identify adverse hemodynamic features associated with postfenestrated and branched endovascular aneurysm repair branch occlusion. Methods Patients undergoing 4‐vessel fenestrated and branched endovascular aneurysm repair for Extent II to IV thoracoabdominal aortic aneurysms were retrospectively reviewed. Branches that occluded without identifiable kinking or stenosis on computed tomography were included, along with an equal cohort of anatomy‐matched patent controls. Patient‐specific pulsatile rigid‐wall simulations were performed using SimVascular with individualized geometries and boundary conditions. Abnormal time‐averaged wall shear stress (TAWSS) was defined as <10 or >70 dynes/cm 2 . Results Nine patients (36 target vessels) experienced 10 branch occlusions. Postoperative pressure and flow did not differ significantly between occluded and patent renal or mesenteric branches. However, occluded renal and mesenteric branches demonstrated significantly larger postoperative areas of abnormal TAWSS compared with controls (renal: 14.5% versus 5.9%, P =0.003; mesenteric: 17.7% versus 9.9%, P =0.035). Logistic generalized estimating equation modeling showed abnormal TAWSS to be a significant predictor of renal branch occlusion ( P =0.0085). Model estimates suggested occlusion probabilities of 1.1%, 31%, and 94% at 0%, 10%, and 20% abnormal TAWSS surface area, respectively. A cluster‐bootstrapped receiver operating characteristic curve (area under the curve, 0.876) identified a >10.2% threshold that correctly classified 92% of renal occlusions. Abnormal TAWSS frequently localized to distal stent–artery interfaces. Conclusions Elevated abnormal TAWSS within stented renal branches is associated with subsequent branch occlusion after fenestrated and branched endovascular aneurysm repair. Computational flow simulation‐derived TAWSS thresholds may help identify high‐risk branches before failure, warranting prospective validation.