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PubMed2025

Transcriptomic profile induced by calcitriol in CaSki human cervical cancer cell line.

The vitamin D endocrine system, primarily mediated by its main metabolite calcitriol and the vitamin D receptor (VDR), plays a critical role in numerous human physiological processes, ranging from calcium metabolism to the prevention of various tumors, including cervical cancer. In this study, we comprehensively investigated the genomic regulatory effects of calcitriol in a cervical cancer model. We examined the transcriptional changes induced by calcitriol in CaSki cells, a cervical cell line harboring multiple copies of HPV16, the primary causal agent of cervical cancer. Our microarray findings, revealed that calcitriol regulated over 1000 protein-coding genes, exhibiting a predominantly repressive effect on the CaSki cell transcriptome by suppressing twice as many genes as it induced. Calcitriol decreased EPHA2 and RARA expression while inducing KLK6 and CYP4F3 expression in CaSki cells, as validated by qPCR and Western blot. Functional analysis demonstrated that calcitriol effectively inhibited key processes involved in cancer progression, including cell proliferation and migration. This was further supported by the significant downregulation of MMP7 and MMP13 mRNA levels. Our microarray results also showed that, in addition to its effects on protein-coding genes, calcitriol significantly regulates non-coding RNAs, altering the expression of approximately 400 non-coding RNAs, including 111 microRNA precursors and 29 mature microRNAs, of which 17 were upregulated and 12 downregulated. Notably, among these calcitriol-regulated microRNAs are some involved in cervical cancer biology, such as miR-6129, miR-382, miR-655, miR-211, miR-590, miR-130a, miR-301a, and miR-1252. Collectively, these findings suggest that calcitriol exhibits a significant antitumor effect in this advanced cervical cancer model by blocking critical processes for tumor progression, underscoring the importance of maintaining adequate vitamin D nutritional status.

Humans↗

PubMed2026

Transcriptomic and proteomic signatures following AS03-adjuvanted Influenza A/H7N9 vaccine.

INTRODUCTION: Vaccines targeting avian influenza virus A/H7N9 are poorly immunogenic. While the immune responses can be improved with oil-in-water emulsion adjuvants such as Adjuvant System 03 (AS03), the cellular mechanisms underpinning the adjuvant effect are incompletely characterized and poorly understood. METHODS: We enrolled 30 healthy adult participants and used RNA sequencing and quantitative proteomics to characterize the response to two doses of the influenza A/H7N9 vaccine, with and without AS03, in six immune cell types. These responses were compared to those seen after administration of an unadjuvanted seasonal in uenza A/H3N2 variant vaccine to identify signatures unique to adjuvanted influenza vaccines and correlated with later antibody responses. Transcriptomic and proteomic analyses revealed that. RESULTS: AS03-adjuvanted vaccine was associated with upregulation of immune pathways in innate immune cells within 24h following vaccination for phagocytosis, antigen presentation and processing, inflammasome activation, NK-cell mediated cytotoxicity, IgA production, and interferon-response pathways. Moreover, while major histocompatibility complex (MHC I and II) upregulation was observed across multiple immune cell types, MHCII gene transcription was also increased in the neutrophil compartment, generating the hypothesis that neutrophils may play a more important role in antigen presentation than previously understood. DISCUSSION: Taken together, these data provide a more complete mechanistic understanding of oil-in-water adjuvants and their role in enhancing the immune response for pandemic influenza preparedness. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/study/NCT02921997?term=NCT02921997&viewType, idientifier NCT02921997.

Adult↗

PubMed2026

Primary Tumor Epigenetic and Transcriptomic Alterations Associated with Nodal Burden and Metastatic Risk in ER+/HER2- Breast Cancer.

De-escalation of axillary surgery has resulted in the loss of pathologic nodal information, yet the extent of lymph node involvement remains an important determinant of treatment decisions in estrogen receptor-positive (ER+)/HER2- disease. We examined whether primary tumors differed molecularly according to the extent of this regional dissemination. Genome-wide DNA methylation profiling of primary ER+/HER2- tumors from 47 patients with pN1 (n = 29) vs. >pN1 (n = 18) disease showed differences concentrated at promoters of developmental and cell-adhesion genes. By integrating methylomes with transcriptomes from the TCGA-BRCA cohort (n = 148) and clinical outcomes from KM Plotter (RFS, n = 1154; OS, n = 442; DMFS, n = 423), we identified four genes (ARL10, RIC3, CXCL14, KCNH2) showing concordant molecular and clinical associations, from which we derived the Lymph-node Involvement Outcome Numerator (LION) score. Lower LION scores were observed in metastatic lesions from the AURORA US cohort (n = 45). In SCAN-B (n = 3969), lower scores were associated with shorter distant recurrence-free intervals (HR = 0.38; 95% CI 0.23-0.62); this association persisted after adjustment for age, nodal and tumor category but was lost after adjustment for histological grade (HR = 0.83; 95% CI 0.48-1.44), indicating that the score and grade capture overlapping biology. These findings suggest that primary tumors already display coordinated epigenetic and transcriptional alterations associated with the extent of metastatic dissemination.

Humans↗

PubMed2026

A Practical Workflow for Spatial Transcriptomics Data Analysis: From Data Acquisition to Advanced Analyses.

Spatial transcriptomics (ST) profiles genome-wide gene expression while preserving the two-dimensional spatial context of mRNA molecules within tissue sections, enabling studies of tissue architecture and microenvironment-associated biology. However, ST analysis remains challenging because data import, quality control, integration, deconvolution, spatial statistics, and visualization often require multiple software environments and reproducible parameter choices. This protocol presents a practical computational workflow for public ST datasets in R, beginning with data acquisition and software setup and proceeding through Seurat-based data loading, quality control, normalization, multi-sample integration, clustering, and spatially variable gene analysis. The workflow then applies complementary deconvolution strategies, including reference-guided SPOTlight analysis and unsupervised STdeconvolve topic modeling, followed by Giotto-based spatial cell-cell communication analysis and interactive region-of-interest (ROI) selection using a custom Python Dash application. By emphasizing script-based execution, explicit parameter rationales, expected outputs, and troubleshooting checkpoints, the protocol provides an adaptable framework for standard array-based ST datasets and related platforms after dataset- and platform-specific parameter evaluation.

Spatial Transcriptomics↗

PubMed2026

Multistage Genetic, Transcriptomic, and Single-Cell Evidence Prioritizes MAP1LC3A among Ferroptosis-Related Genes in Glioblastoma.

Glioblastoma (GBM) remains a highly aggressive malignancy, and the contribution of ferroptosis-related genes to disease susceptibility remains incompletely understood. A genetically anchored, multistage framework was applied to prioritize ferroptosis-related genes associated with GBM. Among 483 genes curated from FerrDb V2, 315 had candidate cis-expression quantitative trait loci (cis-eQTLs) in eQTLGen, 250 retained at least three independent instruments after linkage disequilibrium clumping, and 226 yielded valid inverse-variance weighted (IVW) Mendelian randomization estimates using a GBM genome-wide association study comprising 6,183 cases and 18,169 controls. Thirty-four genes met the exploratory discovery criteria of P < 0.05 and a Benjamini-Hochberg false discovery rate (BH-FDR) < 0.20, with directionally concordant Bayesian weighted Mendelian randomization (BWMR) estimates. Replication-stage Mendelian randomization using GTEx V10 whole-blood cis-eQTLs supported four genes: ATG7, RPTOR, MAP1LC3A, and CHMP6. Evaluation across three independent tumor-control transcriptomic cohorts demonstrated that MAP1LC3A was consistently downregulated in tumor tissue and showed a significant random-effects pooled estimate (log₂ fold change, -1.273; 95% confidence interval, -1.625 to -0.920; false discovery rate = 0.016), whereas the other three genes lacked comparable cross-cohort statistical support. Single-cell virtual knockout analysis was subsequently performed in a patient-balanced subset of 2,400 malignant cells selected from 4,916 eligible cells across 20 adult IDH-wild-type GBM tumors. Across five independently seeded runs, 3, 15, 4, and 7 robust downstream genes were identified for ATG7, RPTOR, MAP1LC3A, and CHMP6, respectively. The resulting consensus sets comprised 17 unique genes, with RND3 shared across all four targets. Gene Ontology analysis indicated enrichment of cell-adhesion and cell-surface processes, whereas no KEGG or Reactome pathways remained significant after multiple-testing correction. Collectively, these findings prioritize MAP1LC3A for future experimental investigation while distinguishing genetic association, tumor-expression concordance, and computational perturbation from definitive evidence of causality or mechanism.

Humans↗

PubMed2026

Distinct periarticular muscle transcriptomes: inflammation in rheumatoid arthritis versus metabolic dysregulation in osteoarthritis.

OBJECTIVES: Periarticular skeletal muscle abnormalities are recognised in rheumatoid arthritis (RA) and osteoarthritis (OA), but their divergent molecular pathologies are poorly defined. This study aimed to elucidate and directly compare the transcriptomic profiles of periarticular muscle in patients with RA and OA. METHODS: We performed bulk RNA sequencing of periarticular skeletal muscle samples collected during total joint arthroplasty from RA (n=6) and OA (n=4) patients. Differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), pathway enrichment, and gene set variation analyses were conducted to identify disease-specific molecular features and their clinical associations. RESULTS: The two conditions showed fundamentally distinct profiles. RA muscle exhibited a pronounced inflammatory signature, characterised by upregulation of cytokine-responsive genes including FOS, EGR1, and CXCL2, and enrichment of tumour necrosis factor-α and interleukin-6 (IL-6)/JAK-STAT3 signalling. In contrast, OA muscle was characterised by metabolic dysregulation, with upregulation of genes linked to adipogenesis (PCK1, SFRP4) and significant enrichment of epithelial-to-mesenchymal transition (EMT) signalling. These divergent profiles were further supported by WGCNA, which identified distinct modules reflecting heightened innate immune and complement activation in RA, and disrupted metabolic processes in OA. Notably, in RA, the IL-2-STAT5 signalling pathway was unique among those tested in showing a strong positive correlation with DAS28-ESR (r=0.94, p=0.019). CONCLUSIONS: This study reveals distinct molecular pathologies in the periarticular muscle of RA and OA. RA muscle shows an intense inflammatory profile potentially linked to cachexia, whereas OA muscle displays features of metabolic disease and pro-fibrotic remodelling.

Humans↗

PubMed2026

Phenotypic and transcriptomic characterization of biallelic RNU2-2 developmental and epileptic encephalopathy.

OBJECTIVE: A significant proportion of individuals with suspected genetic developmental and epileptic encephalopathies (DEEs) remain unsolved following whole genome sequencing (WGS). Here we describe biallelic RNU2-2 variants causing a recently reported, severe, recessive DEE. METHODS: We screened individuals who have received WGS analyses at the Genomic Medicine Centre Karolinska for Rare Diseases for biallelic RNU2-2 variants. Deep phenotyping was performed through reviewing entire medical histories and phenotypic traits were transcribed to their corresponding Human Phenotype Ontology (HPO) term. HPO terms were used to generate pairwise phenotypic similarity scores and assess for significantly shared phenotype enrichment in the RNU2-2 sub-cohort. RNA sequencing analyses were performed in fibroblast and blood tissues to compare splicing events between RNU2-2 individuals and two independent control groups. RESULTS: We identified 14 individuals from nine families with 12 ultra-rare biallelic RNU2-2 variants clustering in the conserved 5' domains. Genotype data from 13 of 14 individuals has been reported previously as part of a larger cohort. All individuals presented with a highly concordant, severe DEE, characterized by severe to profound intellectual disability, inability to walk or communicate, hyperkinesia, and refractory seizures. Infantile spasms and tonic seizures were the predominant seizure types and a Lennox-Gastaut syndrome-like phenotype was common. These individuals had a significantly similar phenotypic signature when compared with 703 individuals with complex pediatric epilepsies (two-sided Monte Carlo permutation test, p = .005). RNA sequencing analyses showed aberrant splicing, with the most pronounced effects in fibroblast tissues in mutually exclusive exon and alternate 3' splice-site events, which were not detectable in blood. SIGNIFICANCE: We present deep phenotyping data and transcriptomic analyses that provide support for rare, 5' clustering biallelic RNU2-2 variants causing this novel, severe DEE. We propose an RNA sequencing methodology on fibroblast tissue for future validation of RNU2-2 variants.

autosomal recessive disease↗

PubMed2026

Synthesis of Padina boergesenii-Derived Zinc Oxide Nanoparticles and their Therapeutic Potential Against Oral Squamous Cell Carcinoma: A Transcriptomic and in Vitro Evaluation.

Cancer remains a major health challenge, with oral squamous cell carcinoma (OSCC) being an high aggressive subtype of head and neck squamous cell carcinoma that lacks effective therapeutic options. Current study integrates the synthesis of zinc oxide nanoparticles (ZnO-NPs) from the marine brown algae Padina boergesenii with the OSCC gene expression profile to evaluate their potential therapeutic effects against OSCC. Herein, the ZnO-NPs from Padina boergesenii were prepared through the green synthesis method. The obtained ZnO-NPs were characterized through spectroscopic methods, the UV spectrophotometer shows maximum absorbance at 372 nm, FT-IR presents Zn-O functional band at 516 cm- 1, HR-TEM confirms average particle size of 55.70 nm and the Zetasizer shows zeta potential of + 12.9 mV, indicating colloidal stability. The cytotoxicity assay with ZnO-NPs against oral cancer cell lines exhibited a reduction in cell viability at IC₅₀ value of 20 µg/mL. Meanwhile, the transcriptome analysis of OSCC highlights that MYC, STAT3, BRCA1, and AKT1 are the OSCC therapeutic targets involved in proliferation, immune evasion, genomic instability, and cancer signalling pathways. Further, qRT-PCR based gene expression analysis demonstrates significant down-regulation of these targets upon ZnO-NPs treatment in KB cell lines. Overall, this study emphasizes the anticancer potential of Padina boergesenii-derived ZnO-NPs that could effectively modulate the therapeutic targets and may benefit the treatment of OSCC cancer.

Cytotoxicity↗

PubMed2026

Uncovering hub genes and key pathways responsive to drought stress in rice via meta-analysis of transcriptomic data.

Drought stress presents a formidable threat to global rice cultivation, triggering complex molecular responses that impact plant growth and productivity. To decipher the underlying gene expression dynamics, we performed a comprehensive meta-analysis of transcriptomic datasets derived from drought-tolerant rice genotypes. Via microarray data from three independent studies, we identified a set of consistently expressed differentially expressed genes (DEGs) under drought conditions. Integration of functional annotation tools, including GO and KEGG pathway enrichment, revealed key biological processes and signaling cascades involved in stress mitigation, such as ABA signaling, protein folding, and photosynthesis suppression. Protein-protein interaction (PPI) network construction, followed by hub gene identification via maximal clique centrality (MCC), highlighted pivotal regulators including LEA proteins, dehydrins, HSP70, and several transcription factors. Machine learning approaches further prioritize potential biomarkers, with Random Forest models achieving high classification accuracy and pinpointing key predictive genes. Chromosomal localization analysis provided spatial insights into the distribution of these hub genes, whose expression patterns were further compared against qRT-PCR data from previously published studies. This integrative approach identifies candidate genomic markers and mechanistic insights that may support future breeding strategies for drought-tolerant rice, pending experimental validation.

Cytoscape↗

PubMed2026

Deciphering novel targets in salivary gland pleomorphic adenoma by integrating plasma proteomics and parotid transcriptomics analyses.

BACKGROUND/PURPOSE: Pleomorphic adenoma (PA) is the most common salivary gland benign tumor, with its molecular drivers elusive due to a lack of experimental models. This study aimed to decipher novel targets in PA by systematically integrating plasma protein quantitative trait loci (pQTL)-based Mendelian randomization (MR) with multi-omics profiling of parotid gland tissues. MATERIALS AND METHODS: We performed two-sample MR using 5450 plasma pQTLs and genome-wide association study summary for benign or broader salivary gland diseases from FinnGen consortium. Bulk RNA-sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) comparing PA to normal tissue were used for transcriptomic validation. Immunohistochemistry (IHC) was applied for protein-level validation in human PA, adenoid cystic carcinoma (ACC), and murine inflammatory lesions. RESULTS: MR identified 12 plasma proteins associated with benign salivary gland tumor risk. Transmembrane serine protease 6 (TMPRSS6) was the only protein significantly risk-increasing for both benign and broader salivary gland diseases. Strikingly, mitogen-activated protein kinase kinase 4 (MAP2K4) showed opposite MR effects between benign and all-lesion outcomes. Bulk RNA-seq showed limited concordance with MR findings, while scRNA-seq revealed a unique plastic epithelium and partially validated candidates at cellular resolution. Critically, IHC confirmed MAP2K4 protein overexpression specifically in human PA, but not in ACC or inflammatory lesions, while TMPRSS6 was downregulated in established pathologies despite its genetic risk association. CONCLUSION: By integrating plasma proteome-based causal inference with parotid tissue multi-omics, this study unveils MAP2K4 as a potential PA-specific driver. This integrative framework provides novel, context-specific targets for further functional investigation in salivary gland tumorigenesis.

Gene expression profiling↗

PubMed2026

Genomic and transcriptomic quality control for an autologous iPSC-derived cell therapy for Parkinson's disease.

Toward development of an autologous, induced pluripotent stem cell (iPSC)-based cell therapy for Parkinson's disease (PD), we demonstrate successful, reproducible genomic and transcriptomic qualification of patient-derived dopaminergic neuron precursor cells (DANPCs) across multiple donors. Our analysis includes whole-genome sequencing data from fibroblasts, iPSCs, and DANPCs and the development of NeuriTest, an RNAseq-based bioinformatic analysis of DANPCs designed to predict cell quality based on empirical animal data. Autologous cell therapies are immune matched to the patient, potentially augmenting durability of benefit compared to allogeneic cells while negating the need for immunosuppression and accompanying side effects. Patient-specific iPSCs are an autologous cell source that can be differentiated to dopaminergic neurons, the cell type lost in PD. We report here our preclinical manufacturing strategy and results demonstrating efficacy in a PD rodent model and safety in a 9-month GLP toxicology study.

Parkinson’s disease↗

PubMed2026

Dynamic evolution of chaperone-mediated autophagy is associated with tumor microenvironment remodeling and prognostic stratification in lung adenocarcinoma: insights from single-cell transcriptomics, ensemble machine learning, and experimental validation.

BACKGROUND: Lung adenocarcinoma (LUAD) shows prognostic heterogeneity, and tumor-node-metastasis (TNM) staging is limited for individualized management. Chaperone-mediated autophagy (CMA) maintains proteostasis, but its role during adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA)-invasive adenocarcinoma (IAC) progression remains unclear. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE189357 and bulk transcriptomes from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) cohorts were integrated. CMA activity, cell-cell communication, weighted gene co-expression network analysis (WGCNA), tumor-normal differential expression, machine-learning survival modeling, tumor microenvironment (TME) features, drug sensitivity, and EPC1 function were analyzed. RESULTS: CMA-high tumor epithelial cells increased from AIS (58.1%) to MIA (65.7%) but declined in IAC (44.4%; p < 0.001). CMA-low cells preferentially received fibroblast-derived extracellular matrix cues. A CMA-negatively correlated module identified 69 core genes. Random survival forest (RSF) performed best among 117 machine-learning combinations (mean concordance index > 0.873). High-risk patients had worse survival across cohorts, and the risk score was independently associated with overall survival (hazard ratio = 16.013, 95% confidence interval: 9.579-26.768, p < 0.001). High-risk tumors showed proliferative activation and M0 macrophage enrichment, whereas low-risk tumors showed stronger immune-related signaling. EPC1 overexpression suppressed malignant phenotypes in A549 cells. CONCLUSION: CMA dynamics are associated with stromal and immune remodeling during LUAD progression. A CMA-based model provides robust prognostic stratification and may offer a basis for future TME-guided studies.

Chaperone-mediated autophagy↗

PubMed2026

Genetic dissection of cardiac iron regulation using transcriptome network analysis and systems genetics in BXD mice.

Cardiac iron homeostasis is essential for myocardial energy metabolism and contractile function, yet the genetic and molecular mechanisms governing iron levels within the heart remain poorly understood. We used a systems genetics approach to dissect the transcriptional regulation of cardiac iron homeostasis. Myocardial iron level varies substantially across BXD strains (40-112 μg/g) and is under heritable genetic control (H2 = 0.38). Elevated cardiac iron is associated with reduced ventricular mass, increased ventricular ectopy, and prolonged atrioventricular conduction in the BXD population. Weighted gene co-expression network analysis of the BXD heart transcriptome identified a co-expression module that was significantly and negatively correlated with cardiac iron levels in both young and old BXD mice and enriched for pathways related to metabolic regulation, cyclic AMP (cAMP) signaling, circadian entrainment, and cardiovascular physiology. The module showed substantial overlap with a curated cardiac iron gene set, and cross-species enrichment analysis confirmed its conservation in human cardiomyopathy differentially expressed genes (enrichment ratio = 1.49; false discovery rate [FDR] = 0.0342). Quantitative trait locus (QTL) mapping of the first principal component of the overlapping module iron genes (n = 38), corroborated by individual gene mapping, identified trans-eQTL hotspots on multiple chromosomes, implicating Fcho2, Gcc2, and Rmdn1 as candidate upstream regulators operating through sequential steps of intracellular iron trafficking. Together, these findings establish a systems-level map of cardiac iron gene regulation, identify candidate genetic regulators, and provide a molecular framework linking disruption of iron-related transcriptional networks to structural and electrical cardiac dysfunction with implications for iron-related heart diseases.

BXD mouse population↗

PubMed1997

Characterization of the yeast transcriptome.

We have analyzed the set of genes expressed from the yeast genome, herein called the transcriptome, using serial analysis of gene expression. Analysis of 60,633 transcripts revealed 4,665 genes, with expression levels ranging from 0.3 to over 200 transcripts per cell. Of these genes, 1981 had known functions, while 2684 were previously uncharacterized. The integration of positional information with gene expression data allowed for the generation of chromosomal expression maps identifying physical regions of transcriptional activity and identified genes that had not been predicted by sequence information alone. These studies provide insight into global patterns of gene expression in yeast and demonstrate the feasibility of genome-wide expression studies in eukaryotes.

Cell Cycle↗

PubMed2026

A single-nucleus transcriptomic atlas of human inner ear development.

Hearing and balance rely on coordinated activity of multiple inner ear cell types, yet the mechanisms governing their development and specification in humans remain unclear. Consequently, this limits our understanding of how disease genes affect cell type formation and function, limiting the development of targeted treatments, including gene therapies. Here we present the Human Inner Ear Development snRNA-seq Atlas (HIEDRA), a single-nucleus transcriptomic atlas of the human inner ear spanning the first and second trimesters. HIEDRA maps sensory and nonsensory epithelia, neurons and mesenchyme-associated populations, including undercharacterized secretory cells required for ion homeostasis. We identify selective vulnerability in sensory and secretory lineages to disease-associated genes, infer regulatory networks and show that Hedgehog signaling suppression is required for secretory cell specification. We validate this mechanism in human inner ear organoids, expanding the model to include all major cell types. Altogether, these findings provide insights into human inner ear cell type specification, improve in vitro models and establish HIEDRA as a resource for investigating human inner ear development.

Journal Article↗

PubMed2000

Shotgun sequencing of the human transcriptome with ORF expressed sequence tags.

Theoretical considerations predict that amplification of expressed gene transcripts by reverse transcription-PCR using arbitrarily chosen primers will result in the preferential amplification of the central portion of the transcript. Systematic, high-throughput sequencing of such products would result in an expressed sequence tag (EST) database consisting of central, generally coding regions of expressed genes. Such a database would add significant value to existing public EST databases, which consist mostly of sequences derived from the extremities of cDNAs, and facilitate the construction of contigs of transcript sequences. We tested our predictions, creating a database of 10,000 sequences from human breast tumors. The data confirmed the central distribution of the sequences, the significant normalization of the sequence population, the frequent extension of contigs composed of existing human ESTs, and the identification of a series of potentially important homologues of known genes. This approach should make a significant contribution to the early identification of important human genes, the deciphering of the draft human genome sequence currently being compiled, and the shotgun sequencing of the human transcriptome.

Animals↗

PubMed2025

Genome topology analysis and transcriptomics of human osteoclasts reveals enhancer-promoter interactions at loci for bone traits and diseases.

Genome-wide association studies (GWAS) relevant to osteoporosis have identified hundreds of loci; however, understanding how these variants influence the phenotype is complicated because most reside in non-coding DNA sequence that serves as transcriptional enhancers and repressors. To advance knowledge on these regulatory elements in osteoclasts (OCs), we performed Micro-C analysis, which informs on the genome topology of these cells and integrated the results with transcriptome and GWAS data to further define loci linked to BMD. Using blood cells isolated from 4 healthy participants aged 31-61 yr, we cultured OC in vitro and generated a Micro-C chromatin conformation capture dataset. We characterized chromatin loops (CLs) in OC from among more than 69 million chromatin interactions identified in the genome. Of the CL identified in OC, >16 000 were unique compared to precursor cells. When sentinel single nucleotide polymorphisms from osteoporosis and bone-related GWAS and those in linkage disequilibrium at r 2 > 0.6 were mapped to CL for OC, 12 588 of these variants were observed within chromatin contact regions. Notable in differential gene ontology enrichment analyses of the topology data for OC and precursors were pathways regulating pluripotency of stem cells, Wnt signaling, nucleotide-binding oligomerization domain (NOD)-like receptor signaling and chemokine signaling. These data, in combination with other 3D genome architecture and epigenetic data (eg, histone modifications and chromatin accessibility), will be useful in modeling to predict genome-wide, which enhancers regulate which genes in OC. This data will therefore also be informative for resolving GWAS hits. In conclusion, we have generated a high-resolution genome topology dataset for human OC and have used this to identify CLs relevant to studies of the genetics of osteoporosis. This data will serve as a powerful resource to inform future functional studies of OC biology.

BMD↗

PubMed2026

Genomic and Transcriptomic Correlates of Deep PSA Response in Patients with Metastatic Androgen Pathway Modulation-Sensitive Prostate Cancer.

BACKGROUND: Despite advances in metastatic androgen pathway modulation-sensitive prostate cancer (mAPMS) treatment, outcomes remain heterogeneous. Achieving a post-treatment undetectable prostate specific antigen (PSA) is a strong prognostic marker. We aimed to identify genomic and transcriptomic determinants of PSA response in a real-world clinical-genomic cohort. PATIENTS AND METHODS: Patients with mAPMS who underwent DNA (Tempus xT) and, in a subset, RNA (Tempus xR) sequencing were identified from the Tempus Lens database. Inclusion required stage IV disease within 90 days of sample collection and samples obtained within 12 months before or 3 months after treatment initiation. Patients with PSA at 6 months (n = 525) were classified as PSA-low (<0.1 ng/mL, n = 240) or PSA-high (≥0.1 ng/mL, n = 285). Overall survival (OS) was assessed by 6-month landmark analysis with delayed-entry adjustment. Logistic and Cox models were adjusted for clinical variables. Sensitivity analyses used a relative definition of > 95% PSA decline from baseline. RESULTS: Baseline PSA was lower in PSA-low versus PSA-high patients (24 vs 36 ng/mL, p = 0.01). SPOP (17% vs 11%) and ZFHX3 (2.5% vs 6%) alterations differed between groups, but neither persisted after adjustment. Using the relative definition, ZMYM3 and JAK1 alterations were independently associated with failure to achieve a deep PSA response. Expression of PSMA, TROP2, B7-H3, and STEAP1 did not differ between groups. PSA-low status was independently associated with improved OS, as was deep relative response. CONCLUSION: Deep PSA response at 6 months correlates with improved OS in mAPMS. Integrating molecular markers with PSA response may inform treatment intensification or de-escalation strategies.

Biomarkers↗