Citations

Summary Long-read nanopore sequencing enables simultaneous detection of germline variation and native DNA base modifications on individual DNA molecules, providing a unique opportunity to investigate allele-specific epigenetic regulation. Here, we performed whole-genome nanopore sequencing on normal and tumor prostate tissues to characterize differential methylation, methylation entropy, and allele-specific methylation (ASM) associated with noncoding genetic variants. Genome-wide analysis identified extensive cancer-associated differentially methylated regions (DMRs), with hypermethylated DMRs significantly enriched near transcription start sites and transcriptional regulatory regions. Integration with transcriptomic datasets revealed strong inverse relationships between promoter methylation and gene expression, while 5-hydroxymethylcytosine (5hmC) levels positively correlated with transcriptional activity across gene bodies. Using fragment-level methylation patterns enabled by long-read sequencing, we further quantified methylation entropy incorporating both 5mCG and 5hmCG states. Cancer-hypermethylated DMRs exhibited markedly reduced entropy, consistent with clonal fixation of methylation states during tumor progression. Entropy profiling across chromatin annotations demonstrated maximal epigenetic heterogeneity at partially modified enhancer-associated regions. To investigate cis-regulatory genetic effects, we developed a simple ASM framework (nanoASM) that can partition sequencing reads by allelic state and identifies allele-specific DMRs directly from long-read data. Compared with conventional population-level mQTL analysis, ASM demonstrated substantially improved statistical efficiency by leveraging within-individual contrasts and reducing sample-level heterogeneity. Although germline single nucleotide polymorphisms (SNPs) were largely shared between normal and tumor tissues, ASM patterns differed substantially, with tumor-associated ASM regions displaying significantly larger genomic span and stronger allelic methylation differences. Comparative analysis with TCGA prostate mQTL and GTEx prostate eQTL datasets demonstrated substantial concordance between ASM directionality and downstream transcriptional effects, particularly for variants located within DMRs and near transcription start sites. At the IRX4 prostate cancer risk locus, ASM identified an androgen-responsive regulatory domain overlapping AR ChIP-seq and H3K27ac peaks, nominating rs6885084 as a candidate functional variant. At the PSCA locus, ASM anchored by rs4736369 was associated with allele-specific methylation, chromatin activation, transcript abundance, and isoform usage. Together, these findings establish nanopore-based ASM analysis as a powerful approach for resolving functional noncoding variants and their regulatory domains they control in prostate cancer.

Abstract Introduction: Underlying tumor biology in metastatic castration-resistant prostate cancer (mCRPC) is highly complex and heterogeneous. To date, mCRPC state biomarker-enriched clinical trial designs incorporating either prognostic or predictive biomarkers are limited to alterations in homologous recombination repair pathway genes. In this study, we use an integrated clinico-molecular prognostic score in mCRPC that combines plasma prognostic proteins with a plasma-based copy number alteration (CNA) risk algorithm (PMID: 40036789; PMID: 36230636) to simulate a biomarker-enriched clinical trial design. Methods: A plasma cell-free DNA (cfDNA) prognostic risk algorithm from eight CNAs (gains in AR, MYC, PIK3CA, PIK3CB; deletions in NKX3-1, TMPRSS2, TP53, ZBTB16) is combined with clinical prognostic proteins (alkaline phosphatase, lactate dehydrogenase) to generate a prognostic risk-score (RS) in three independent treatment-naïve mCRPC cohorts. Using the RS classifier, we estimate the number of high-RS patients (pts) required to be screened from an unselected mCRPC population and the number needed for enrollment to achieve adequate statistical power in a randomized trial for a predefined effect size (Hazard Ratio- 0.70; 80% power). The trial design aims to enrich High-RS pts for targeting lethal mCRPC. Trade-offs are evaluated between number of pts screened and enrolled under varying RS enrichment thresholds and degrees of enrichment. Results: The range of RS distribution in 561 mCRPC pts from three pooled datasets was 0.362-11.737. The median overall survival (OS) (months; 95% Confidence Intervals) based on risk stratification for Low-RS (≤0.8) is 46.2 (38.8-55.4); “Intermediate-risk” (RS: 0.8-2.6) is 27.1(24.3-31.5); High-Risk (RS: >2.6) is 14.9 (11.9-17.6). For a 2-year OS mCRPC endpoint, a biomarker-enriched trial restricted to pts with RS ≥2, which corresponds to the 65th percentile of the RS distribution, would require enrollment of 398 pts, after screening 1,101 mCRPC pts to achieve 80% power to detect a 0.7 treatment vs. control hazard ratio (HR). In contrast, a traditional non-enrichment clinical trial (no molecular classifier) would require 574 pts to achieve to achieve 80% power and still not achieve adequate power to detect strong treatment by risk interactions. As a pragmatic alternative, we evaluated a hybrid enrichment strategy enrolling 50% of pts from the general mCRPC population and 50% of pts with RS ≥1 (41st percentile). This biomarker enriched design which takes 50% pts with a RS of 1.0 (or more) in a trial with 24-month follow-up will require a sample size 525 patients for which 676 pts will be screened to achieve an 80% power to detect a 0.7 treatment vs. control hazard ratio. Conclusion: A plasma-based molecular classifier can be used to design an enrichment trial in biologically defined lethal mCRPC, incorporating 50% of pts with High-RS and yet balance the required sample size and number of pts to be screened enabling an adequately powered molecular classifier-based biomarker-enriched clinical trial. Citation Format: Manish Kohli, Liang Wang, Aik C. Tan, Muhammad Zaki Fadlullah, Anushka Shankar, Sumithra Mandrekar, Benjamin Haaland. Clinico-Genomic Risk Score-Based Biomarker Enrichment Clinical Trial Designs in Poor Prognosis Metastatic Castrate Resistant Prostate Cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr B039.

Abstract The progression of osteoarthritis (OA) is fundamentally characterized by the aberrant transformation of chondrocytes into a fibrotic phenotype, although the precise molecular mechanisms involved remain inadequately understood. In this study, the interplay between epigenetic modifications and metabolic reprogramming during the activation of fibrocartilage cells in osteoarthritis was investigated. The findings demonstrate that FSTL1 markedly upregulates key glycolytic enzymes, including LDHA, HK2, and PKM, in chondrocytes, triggering a “glycolytic burst” that results in elevated intracellular lactate levels. This accumulated lactate acts as a precursor for epigenetic modifications, specifically promoting the lactylation of histone H3 lysine 18 (H3K18la) in fibrocartilage cells, thereby facilitating the transcriptional activation of critical fibrosis‐related genes such as Itga6, Cxcl10, and Parp16. Notably, pharmacological inhibition of the PI3K/mTOR pathway or lactate dehydrogenase significantly diminishes H3K18la levels and markers of chondrocyte fibrosis, while exogenous lactate supplementation can counteract this effect. In summary, this study unveils the core mechanism by which FSTL1 reshapes the epigenetic landscape of chondrocytes and drives the fibrotic process through the activation of the “glycolysis‐lactate‐H3K18la” cascade axis, offering a dual‐target intervention strategy for OA involving metabolic reprogramming and epigenetic modification.

ABSTRACT The insulin‐like growth factor‐1 (IGF‐1) signaling pathway is known as a potent aging modifier, disruption of which consistently associates with lifespan extension across diverse species. Despite this established association, the mechanisms by which IGF‐1 signaling modulates organ aging remain poorly understood. In this study, we assessed age‐related changes in IGF‐1 expression across multiple organs in mice and identified a more prominent increase in skin IGF‐1 levels with aging—a phenomenon also observed in human skin. To explore the consequences of elevated IGF‐1, we developed transgenic mice ectopically expressing human IGF‐1 in the epidermis, driven by the bovine keratin 5 promoter (IGF‐1 Tg). These mice exhibited premature aging of hair follicles, as evidenced by accelerated hair graying and loss. Single‐cell RNA sequencing analyses of dorsal skin highlighted an upsurge in cellular senescence markers and the senescence‐associated secretory phenotype (SASP) in hair follicle stem cells (HFSCs), alongside a decline in hair growth and HFSC exhaustion. Our findings indicate that excessive IGF‐1 triggers HFSC senescence, thereby disrupting hair follicle homeostasis. Remarkably, interventions in IGF‐1 signaling via downstream mechanisms—specifically blocking Ac‐p53 activation via SIRT1 overexpression or senolytic treatment for senescent cell clearance, or reducing IGF‐1 through dietary restriction—significantly reduced senescence markers, mitigated premature hair follicle aging phenotypes, and restored the stem cell pool. Our findings provide fundamental insights into the biological processes of hair aging and highlight the therapeutic promise of targeted interventions to rejuvenate aged HFSCs and promote hair follicle health.

BackgroundVariable flip angle (VFA) and modified Look–Locker inversion recovery (MOLLI) are frequently used for noninvasive evaluation of renal interstitial fibrosis (IF) in chronic kidney disease (CKD). However, controversy remains over which method is preferred.PurposeTo compare the diagnostic efficacy of VFA and MOLLI for T1 mapping in evaluating renal IF.Study TypeProspective.SubjectsFifty‐one participants with CKD (CKD stage 1–5, 35 males) and 18 healthy volunteers (eight males).Field Strength/Sequence3.0 T, three‐dimensional gradient echo sequence for B1+ VFA, and two‐dimensional gradient echo sequence for MOLLI.AssessmentImage quality was assessed on a five‐point scale. Cortex and medulla T1 values (cT1 and mT1), corticomedullary T1 value difference (ΔT1, medulla − cortex), and corticomedullary T1 value ratio (ratio T1, cortex:medulla) were compared between VFA and MOLLI as well as between IF grade (0–4) based on biopsy.Statistical TestsIntraclass correlation coefficient, Bland–Altman analysis, analysis of variance, Kruskal–Wallis test, correlation analysis, and receiver operating characteristics analysis with the area under the curve (AUC). P‐value <0.05 was considered significant.ResultsMOLLI provided significantly better image quality compared to VFA. cT1 and mT1 values significantly differed between VFA and MOLLI (cT1‐VFA: 1771.4 ± 139.4 msec vs. cT1‐MOLLI: 1729.9 ± 132.1 msec; mT1‐VFA: 2076.0 [interquartile range (IQR): 2045.9–2129.9] msec vs. mT1‐MOLLI: 2039.2 [IQR: 1997.8–2071.6] msec). ΔT1 and ratio T1 values were not different between VFA and MOLLI (ΔT1: 300.8 ± 71.4 vs. 306.0 ± 78.4, respectively, P = 0.33 and ratio T1: 0.85 ± 0.038 vs. 0.85 ± 0.041, respectively, P = 0.064). No difference was observed between T1 variables and T1 mapping methods in diagnosing IF.Data ConclusionΔT1 and ratio T1 were not different between VFA and MOLLI. Both VFA and MOLLI are effective for noninvasive assessment of renal IF.Level of Evidence2Technical EfficacyStage 2

Abstract Introduction Men with African ancestry have the highest incidence and mortality rates of prostate cancer (PCa) worldwide. Methods This study aimed to identify differentially methylated genes between tumor vs. adjacent normal and aggressive vs. indolent PCa in 121 African American patients. Epigenome‐wide DNA methylation patterns in tumor DNA were assessed using the human Illumina Methylation EPIC V1 array. Results Around 5,139 differentially methylated CpG‐sites (q < 0.01, lΔβl > 0.2) were identified when comparing normal vs. tumor, with an overall trend of hypermethylation in prostate tumors. Multiple representative differentially methylated regions (DMRs), including immune‐related genes, such as CD40 , Galectin3 , OX40L , and STING , were detected in prostate tumors when compared to adjacent normal tissues. Based on an epigenetic clock model, we observed that tumors’ total number of stem cell divisions and the stem cell division rate were significantly higher than adjacent normal tissues. Regarding PCa aggressiveness, 2,061 differentially methylated CpG‐sites (q < 0.05, lΔβl > .05) were identified when the grade group (GG)1 was compared with GG4/5. Among these 2,061 CpG sites, 155 probes were consistently significant in more than one comparison. Among these genes, several immune system genes, such as COL18A1 , S100A2 , ITGA4 , HLA‐C , and ADCYAP1 , have previously been linked to tumor progression in PCa. Conclusion Several differentially methylated genes involved in immune‐oncologic pathways associated with disease risk or aggressiveness were identified. In addition, 261 African American‐specific differentially methylated genes related to the risk of PCa were identified. These results can shedlight on potential mechanisms contributing to PCa disparities in the African American Population.

260 Background: NGS to identify HRR mutations (mut) is indicated in advanced prostate cancer (aPC); samples for testing may be tissue or plasma. In a large real-world (RW) database, we determined concordance between plasma ctDNA and primary tumor tissue (PT) and/or metastatic tissue (MT) for BRCA1, BRCA2, and ATM mut in PC patients (pts) who received both LB and tissue NGS any time during standard of care (SOC) management. The study objective was to assess the utility of LB to detect actionable mut in these HRR genes and demonstrate the utility of combined LB and tissue testing. Methods: We examined de-identified data from pts who had NGS using both Tempus xF (105 genes-LB) and Tempus xT (648 genes-tissue) during SOC for aPC. Analyses included 1) PT and LB and 2) MT and LB. The results from the pts’ earliest PT or MT and earliest LB were used for paired analyses. The prevalence of a pathogenic/likely pathogenic germline and/or somatic mut in BRCA1, BRCA2, or ATM was reported as N (%), 95% CI. The sensitivity of the LB to identify observed HRR mut in tissue was also reported as N (%), 95% CI. Concordance between pairs was evaluated by Cohen’s kappa statistic with 95% CI. Results: HRR results are show for 1074 PC pts who had NGS performed on PT and LB and 451 PC pts with NGS on both MT and LB. In the PT and LB analysis, HRR mut were found in 6.2% (95% CI: 4.9%-7.9%) of LB and 8.8% (95% CI: 7.2%-11%) of PT. The sensitivity of LB to detect HRR mut in the PT was 53% (95% CI: 43%-64%). Cohen’s kappa statistic was 0.59, 95% CI=0.50-0.68, between PT and LB. In the MT and LB analysis, HRR mut were found in 10% (95% CI 7.8%-14%) of LB and 10% (7.6%-13%) of MT. The sensitivity of LB to detect HRR mut in the MT was 70% (95% CI: 54%-82%). Cohen’s kappa statistic was 0.65, 95% CI=0.54-0.77, between MT and LB. Conclusions: In this large RW dataset, plasma ctDNA-based analysis of BRCA1, BRCA2, and ATM mut showed greater concordance between LB and MT than LB and PT, and may be used as an initial tool for HRR mut detection. When LB results are negative, further exploration with tissue-based testing may identify HRR mut to guide clinical decisions. [Table: see text]

Prostate cancer (PCa) accounted for more than 34,000 deaths in US males [...]