Citations

Abstract Anthracycline-induced cardiotoxicity (AIC) remains a dose-limiting complication of cancer treatment, often leading to irreversible heart failure, yet effective cardioprotective therapies remain limited. Graph-driven drug repurposing offers a rapid pathway to identify cardioprotective therapies, but different computational models often generate divergent candidate lists that exceed experimental validation capacity. We applied a novel "Union-then-Filter" framework to prioritize therapeutics for AIC using AI-based approaches and evaluated candidates in zebrafish models. Three state-of-the-art graph learning models (TxGNN, CompGCN, and RLR) were trained on the PrimeKG to generate an initial candidate pool. A Large Language Model (LLM) agent automated evidence synthesis across 4,286 PubMed abstracts for the top 50 drugs from each model. Candidates were stratified using dual decision criteria and filtered against existing clinical trials. The pipeline narrowed 150 initial candidates to four novel candidates: Cysteine, Dasatinib, Tranilast, and Tretinoin. Prospective in vivo validation was subsequently conducted using an adult AIC (aAIC) zebrafish model. Phenotypic screening via echocardiography revealed that Cysteine, Tranilast, and Tretinoin significantly restored ejection fraction (EF) (overall one-way ANOVA: \(\:F\left(\text{4,95}\right)=47.66,\:\:p<0.0001\); Tukey's post hoc: \(\:\:\:p<0.01\) for all three treatments vs. DOX+ control) and normalized cardiac remodeling markers in doxorubicin-treated subjects (Kruskal-Wallis: \(\:{\chi\:}^{2}\left(4\right)=17.21,\:\:p=0.0018\); Dunn’s post hoc: \(\:\:\:p<0.01\) for all three comparisons vs. DOX control). This study demonstrates the translational utility of an LLM-integrated AI pipeline for drug repurposing and highlights zebrafish AIC as an efficient bridge between in silico prediction and in vivo phenotypic validation in cardio-oncology.

BACKGROUND: Anthracyclines are a widely used and effective class of chemotherapy. However, a major limitation for their use is cardiotoxicity, manifesting as systolic dysfunction, congestive heart failure, and arrhythmias. The objective of this study was to identify genes and genetic risk variants for doxorubicin-induced arrhythmia. METHODS: We performed genome-wide association studies and meta-analysis across 2 independent nonoverlapping, genetically homogenous data sets from the Molecular Epidemiology Resource (cases N=77, controls N=1184) and Tapestry (cases N=13, controls N=172). Doxorubicin-related arrhythmia was the primary cardiac outcome, followed by investigation of a broader phenotype of cardiac events. Effects of doxorubicin on top-associated genes were assessed by quantitative polymerase chain reaction on RNA extracted from human cardiomyocytes following treatment with doxorubicin and by echocardiography in a zebrafish model of doxorubicin-induced cardiomyopathy. RESULTS: In the meta-analysis, rs12151014 at the KCTD15 locus was associated with doxorubicin-related arrhythmia at the genome-wide significance (minor allele frequency in Molecular Epidemiology Resource cases 0.195 versus 0.069 in controls; Tapestry cases 0.192 versus 0.079 in controls) P =9.01×10 −9 ; odds ratio, 3.61. MMP 16 rs1094199 was associated with the broader phenotype of arrhythmia and heart failure (minor allele frequency in Molecular Epidemiology Resource cases 0.079 versus 0.019 in controls; Tapestry cases 0.038 versus 0.015) P =1.98×10 − 8 ; odds ratio=6.15. In human cardiomyocytes, MMP16 and KCTD15 gene expression was significantly downregulated by doxorubicin, and in a zebrafish MMP16 knockout was protective of doxorubicin-induced decline in left ventricular ejection fraction. CONCLUSIONS: Genetic variants at KCTD15 and MMP16 are associated with doxorubicin-related arrhythmia and cardiac events. MMP16 is a potential cardioprotective therapeutic target.

Abstract Purpose: B7-H3 (CD276) represents a promising therapeutic target tested in high-risk localized and treatment-refractory metastatic prostate cancer. To guide therapeutic development and treatment strategies, we examined prostate tumors and evaluated expression, molecular features, and overall survival (OS), accounting for tissue site, hormone sensitivity status, and race. Experimental Design: A total of 8,157 prostate cancer samples with paired DNA/RNA were analyzed based on annotations by tissue site, self-reported race, and disease state: hormone-sensitive prostate cancer (HSPC), castration-resistant prostate cancer (CRPC), or neuroendocrine prostate cancer (NEPC). Expression quartiles were B7-H3–high (&gt;75th percentile) or B7-H3–low (&lt;25th percentile). The OS was evaluated using Kaplan–Meier and Cox proportional hazards models. Results: B7-H3 expression was broadly maintained but varied by tumor site, hormone sensitivity status, and race. High expression aligned with AR-associated transcription factors (HOXB13 and FOXA1), AR-associated pathogenic dysregulations (AR-V7, SPOP, FOXA1, and TMPRSS2:ERG fusions), and actionable surface antigens (TROP2 and NECTIN-4). Weak correlations were found for lineage-plastic program regulators (EZH2, SOX2, and ASCL1) and NEPC-associated surface antigens (DLL3 and CEACAM5). High B7-H3 expression in primary tumors and HSPCs portended adverse OS [hazard ratio (HR), 1.342 and 1.30; confidence interval (CI), 1.19–1.512 and 1.15–1.46; q &lt; 0.0001] although it was favorable in metastatic tumors (HR, 0.823; CI, 0.719–0.942; q = 0.0048). No significant differences in OS were observed among CRPCs and NEPCs, although OS varied by race, with the poorest survival in Asian/Pacific Islander patients with metastatic prostate cancer (HR, 3.72; CI, 1.49–9.29; q = 0.012). Conclusions: Maintained B7-H3 expression in various prostate cancer settings supports its viability as a target. The associations with AR-related molecular factors, surface antigens, and investigative targets for cell therapy or antibody–drug conjugates suggest potential dual-targeting strategies. See related article by Sharma et al., p. 3365

382 Background: Androgen receptor signaling drives prostate cancer (PC) progression, and genes involved in androgen production, uptake, and conversion (APUC) are key therapeutic targets. We previously defined a 6-APUC gene set ( HSD3B1, HSD3B2, CYP3A43, CYP11A1, CYP11B1, and CYP17A1 ), that identified metastatic PC with favorable prognosis and predict docetaxel benefit. However, the expression landscape and clinical relevance of APUC genes have not been interrogated in localized PC. Methods: We analyzed the expression of 21 APUC genes in 55,329 radical prostatectomy tumor samples that underwent Decipher prostate genomic classifier (GC) testing (Veracyte Inc) between 2016-2024. Baseline clinical/pathologic factors were retrieved from Decipher GRID database (NCT02609269). Associations between gene expression quartiles with PathoGenomic Risk Factors (PGRF) including Very High Decipher score >0.85 (VHD), Grade Group (GG) 4-5, LNI and SVI were examined. Associations with distant metastatic (DM) outcomes and metastasis free survival (MFS) were evaluated using logistic regression in Mayo545 and Cox regression in Meta855 RP cohorts, respectively. Results: High expression of SRD5A2 was associated with favorable PGRF (lower odds ratio (OR), p<0.0001), lower rate of development of DM (OR 0.36, p<0.05), and longer MFS (Hazard ratio (HR) 0.51, p<0.05). HSD17B6 showed similar results for PGRF (lower OR, p<0.0001), DM (OR 0.58, p<0.05) and longer MFS (HR 0.39, p<0.05) despite being associated with GG4-5 and SVI+ in samples with VHD. In contrast, high expression of SRD5A3 and HSD17B10 had high OR for PGRFs (p<0.0001). High expression of SLCO2B1 , an androgen uptake gene, had the strongest association with GG4-5 and SVI/LNI (p<0.001 for both). We noted that SRD5A2 lacked correlation with SRD5A1 and SRD5A3 , which instead correlated with each other. Compared to all APUC genes, SRD5A2 had limited correlations with almost all APUC genes, including ones that exhibited robust cross correlation with each other . Similar to our prior finding, most APUC genes demonstrated negative correlation with AR expression and AR activity signatures. Key outcomes were validated based on transcriptomic data from 492 samples from TCGA database. Conclusions: Comprehensive analysis of 21 APUC genes in over 55,000 PC identified distinct, context-dependent associations with metastatic outcomes and clinical and molecular risk factors. Notably, high SRD5A2 expression was associated with lower odds of high-risk features and metastatic outcomes, whereas SRD5A1 and SRD5A3 linked to adverse outcomes, suggesting critical yet divergent roles among 5-alpha-reductase family members. These findings underscoring androgen-metabolic heterogeneity and highlighting SRD5A2 as a potential biomarker of indolent biology in localized prostate cancer.

Abstract Alzheimer’s Disease (AD) 1 is a progressive neurodegenerative disorder with limited therapeutic options, driving interest in drug repurposing to accelerate treatment discovery. Drug repurposing has emerged as a promising strategy to accelerate therapeutic discovery by repositioning existing drugs for new clinical indications. Recent computational repurposing approaches, including knowledge graph reasoning, transcriptomic signature analysis, and integrative literature mining, have demonstrated strong predictive capabilities 2 . However, these methods often yield divergent drug rankings, which makes it difficult to decide which candidates to advance for experimental follow-up and results in substantial gaps between computational predictions and feasible in vivo validation 2 .To bridge this computational-experimental gap, we proposed an advanced prioritization framework leveraging large language models (LLMs). Our method systematically evaluated three state-of-the-art (SOTA) and representative computational methods (TxGNN 3 , Composition-based Graph Convolutional Network (CompGCN) 4 , and a regularized logistic regression (RLR) 5 , to analyze both their predictive performance and pharmaceutical class distributions. By integrating the strengths and divergences of these models, we generated a unified, streamlined list of 90 candidate drugs for further prioritization. We then utilized an LLM-based agent to perform evidence synthesis from biomedical literature abstracts for each candidate. This process mimics expert manual curation but significantly reduces human effort and time by efficiently distilling vast textual data into actionable insights. Applying consistent and transparent selection criteria, we obtained a refined and prioritized list of drug candidates suitable for subsequent in vivo experimental validation. The robustness and clinical relevance of our framework were validated using real-world data from Alzheimer’s patient cohorts, clinical trial registries, and expert pharmacological reviews. This comprehensive validation confirmed that our LLM-driven approach enhances efficiency, consistency, scalability, and generalizability. By integrating computational predictions with scalable evidence synthesis and multifaceted validation, our framework facilitated rapid and informed prioritization of repurposed drugs. Our framework can potentially accelerate the translational pathway toward viable AD therapeutics. Moreover, the versatility of our framework can also be applied to drug repurposing efforts for other diseases beyond AD.

Key Points ift140 -deficient zebrafish exhibited phenotypes observed in mammals, including skeletal defects and kidney cysts. Beyond ciliogenesis, ift140 also regulated cell polarity and intracellular microtubule stability, potentially contributing to cystogenesis. Microhomology-mediated end joining–induced mosaic ift140 crispants enabled evaluation of cystogenesis in adult fish and F0-based screening for modifiers of kidney cysts. Background Genetic modifiers are believed to play an important role in the onset and severity of polycystic kidney disease, but identifying these modifiers has been challenging due to the lack of effective methodologies. Methods We generated zebrafish mutants of IFT140 , a skeletal ciliopathy gene and newly identified autosomal dominant polycystic kidney disease gene, to examine skeletal development and kidney cyst formation in larval and juvenile mutants. In addition, we used ift140 crispants, generated through efficient microhomology-mediated end joining–based genome editing, to compare phenotypes with mutants and conduct a pilot genetic modifier screen. Results ift140 mutants developed kidney cysts and bone defects similar to those seen in mammalian models. ift140 crispants recapitulated mutant phenotypes while bypassing the early lethality of the mutants, enabling the analysis of kidney cyst formation in adult fish. In addition to cilia defects, we identified nonciliary phenotypes, including disrupted cell polarity and aberrant cytoplasmic microtubule stabilization in kidney epithelial cells, as potential contributors to ift140 -associated cystogenesis. The ability to detect ift140 -associated kidney cysts with ease allowed us to develop an F0-based genetic screen to identify potential protective modifiers. A pilot screen of 16 genes previously implicated in dysregulated signaling pathways in autosomal dominant polycystic kidney disease revealed both known and novel modifiers, including mtor and ulk1a . We further found that inhibition of mtor and ulk1a reversed both cilia-related and non–cilia-related abnormalities in the kidney. Conclusions By establishing a zebrafish model of ift140 -associated cystic kidney disease, we recapitulated ift140 ’s ciliary role and uncovered a nonciliary function in kidney cystogenesis. Importantly, we demonstrated the feasibility of using ift140 mosaic crispants to evaluate cystogenesis in adult fish and to perform F0-based screening for identifying genetic modifiers of kidney cysts.

ABSTRACT While BAG3 has been identified as a causative gene for dilated cardiomyopathy, the major pathological events in BAG3‐ related cardiomyopathy that could be targeted for therapeutic benefit remain to be discovered. Here, we aim to uncover novel pathological events through genetic studies in a zebrafish bag3 cardiomyopathy model. Given the known cardioprotective effects of mtor inhibition and the fact that transcription factor EB (tfeb ) encodes a direct downstream phosphorylation target of mTOR signaling, we generated a cardiomyocyte‐specific transgenic line overexpressing tfeb ( Tg[cmlc2:tfeb] ). This overexpression was sufficient to restore defective proteostasis and rescue cardiac dysfunction in the bag3 cardiomyopathy model. Importantly, we detected accelerated cardiac senescence in the bag3 cardiomyopathy model, which can be mitigated by Tg(cmlc2:tfeb) . We compared cardiac transcriptomes between the Tg(cmlc2:tfeb) transgenic fish and the mtor xu015/+ mutant and found that inhibition of the fatty acid binding protein a ( fabp7a ) gene exerts therapeutic effects. Consistent with this genetic evidence, we detected elevated fabp7a expression in the bag3 cardiomyopathy model, whereas cardiomyocyte‐specific overexpression of fabp7a induced dysregulated proteostasis, accelerated cardiac senescence, and cardiac dysfunction. To elucidate the functions of Fabp7a in normative cardiac aging, we turned to the African Turquoise Killifish. We noted elevated Fabp7a expression in the hearts of aged killifish, and pharmacological inhibition of Fabp7a mitigated the cardiac aging process. Together, this study uncovered accelerated cardiac senescence as a key pathological event in bag3 cardiomyopathy and reveals that manipulating the mTOR‐Tfeb‐Fabp7a axis can mitigate this pathology and confer cardioprotective effects.

Abstract Background: The trajectory of metastatic castration-sensitive prostate cancer varies based on disease presentation and biology. While proteomic profiling studies of primary prostate tissue have linked protein expression with metastatic progression and prognosis, few studies have explored biological changes after treatment and their associations with response. Therefore, we conducted proteomic profiling of patients with oligometastatic castration-sensitive prostate cancer (omCSPC) treated with stereotactic ablative radiotherapy (SABR) or observation in the ORIOLE phase 2 randomized clinical trial (RCT). Methods Plasma from omCSPC patients in the ORIOLE trial was collected at baseline (day 1), day 90, and day 180. Protein abundance was quantified using the Olink Explore Assay. Differential expression from baseline to day 90 or 180 in each treatment arm was analyzed using a 2-sided t-test with Benjamini-Hochberg correction. Changes in protein expression at day 90 and 180 were compared with a Pearson correlation. Pathway enrichment was performed via gene set enrichment analysis (GSEA) using Reactome, KEGG, and Hallmark gene sets. Associations with progression-free survival (PFS) were analyzed using Kaplan-Meier and log-rank tests. Results In total, 1,472 proteins were assayed across 130 samples from 46 patients over 3 time points. Significant changes in expression post-SABR were noted at day 90 and 180 compared to baseline (using adjusted p-value cutoff of 0.05). At day 90, four proteins (FCRL1, CD22, TCL1A, FCER2) were downregulated; at day 180, only FCRL1, a Fc receptor-like gene family preferentially expressed in B cells, remained downregulated. No significant expression changes were found in the observation arm. Differential expression of proteins during follow-up were associated with PFS. In particular, LTO1, a maturation factor of ABCE1 important for ribosomal biogenesis and translation, was overexpressed at both day 90 and 180 post-SABR, and overexpression was associated with improved PFS at day 90 (median 24.5 mo vs 6 mo; p=0.017) and day 180 (median 33 mo vs 6 mo; p=0.043). These associations were absent in the observation arm. For proteins differentially expressed in the SABR arm at day 90, several signaling pathways were significantly enriched for patients with prolonged PFS, including positive enrichment of unfolded protein response (UPR) (p=0.008) and IL-4/IL-13 (p=0.009). At 180 days, several pathways were enriched for patients with prolonged PFS including negative enrichment of CTLA4 inhibitory signaling (p=0.005) and CD28 co-stimulation (p=0.008). Conclusion Proteomic analysis in omCSPC patients from the ORIOLE trial reveals significant expression changes at days 90 and 180 after SABR. B-cell signaling proteins were selectively downregulated in the SABR arm, and pathways associated with protein translation and immune response were enriched post-SABR for patients with prolonged PFS. Further research will explore connections to genomic and transcriptomic changes, with additional validation needed. Citation Format: Jarey H. Wang, Amol Shetty, Yang Song, Noura Radwan, Soha Bazyar, Xiaolei Shi, Theodore L. DeWeese, Daniel Y. Song, Ryan M. Phillips, Matthew P. Deek, Philip Sutera, Ana P. Kiess, Phuoc T. Tran. Proteomic profiling of oligometastatic castration-sensitive prostate cancer treated with stereotactic ablative radiotherapy. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr B031.

Abstract Genetic modifiers are believed to play an important role in the onset and severity of polycystic kidney disease (PKD), but identifying these modifiers has been challenging due to the lack of effective methodologies. In this study, we investigated zebrafish mutants of IFT140 , a newly identified ADPKD gene, and observed phenotypes similar to those seen in mammalian models, including kidney cysts and bone defects. Using efficient microhomology-mediated end joining (MMEJ)-based genome editing technology, we demonstrated that ift140 CRISPRants recapitulate mutant phenotypes while bypassing the early lethality of the mutants to allow for renal cyst analysis in adult fish. In addition to cilia defects, non-cilia phenotypes, such as disrupted cell polarity and aberrant microtubule stabilization in kidney epithelial cells, may also contribute to ift140 -associated cystogenesis. Importantly, the ability to detect ift140 -associated renal cysts with ease allowed us to develop an F0-based genetic screen to identify potential protective modifiers. A pilot screen of sixteen genes previously linked to dysregulated signaling pathways in ADPKD revealed both known and novel modifiers, including mtor and ulk1a . Inhibition of mtor and ulk1a reversed both cilia-related and non-cilia-related abnormalities. In summary, our study underscores the potential of using zebrafish as a model for the efficient discovery of genetic modifiers of kidney cysts.