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Results for “Molecular phenotypes”

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PubMed2026

Tahoe-100M: Mapping drug-induced molecular phenotypes at single-cell resolution.

We present Tahoe-100M, a giga-scale single-cell perturbation atlas comprising 100 million transcriptomes from 50 diverse cancer cell lines treated with 1,100 drug-dose conditions. This parallel profiling of thousands of perturbations at single-cell resolution with minimal batch effects is enabled by the Mosaic platform, which multiplexes genetically distinct cell models into balanced "cell villages." Beyond cataloging transcriptomic shifts, Tahoe-100M systematically quantifies cellular phenotypes, including proliferation, cytotoxicity, lineage-specific vulnerabilities, and cell-cycle changes. It captures population-level transcriptomic heterogeneity, characterizing whether drug responses drive cells toward divergent fates or convergent states. Pathway-based signatures define drug-induced expression programs, classify mechanisms of action, reveal off-target activities, and expose adaptive stress responses associated with resistance. By unifying cellular and molecular readouts, this broadly applicable perturbation atlas advances our ability to model gene regulation, drug response, and network dynamics. Its public release enables the training of AI frameworks to advance predictive models of cell behavior.

Humans↗

PubMed2025

Neuroimaging PheWAS and molecular phenotyping implicate PSMC3 in Alzheimer's Disease.

INTRODUCTION: Neuroimaging genetics have advanced Alzheimer's disease (AD) research, yet frameworks mechanistically connecting genes to neurological outcomes via functional genomics are needed to elucidate genetic associations. To address this challenge, we assessed relationships between AD-associated variants and disease via their impact on gene expression and neuroimaging phenotypes. METHODS: We mapped established AD genes to neuroimaging traits using NeuroimaGene atlas and predicted transcript-driven AD neurological features by comparing gene-derived neuroimaging features to clinical neuroimaging data. Genetic correlation and covariance analyses characterized shared genetic architecture between AD endophenotypes and neuroimaging features and identified neuroimaging features associated with dementia family history. RESULTS: Our analyses implicate PSMC3 expression as a strong contributor to AD pathophysiology and indicate AD endophenotypes, including dementia family history, linked to frontal cortex thickness, volume, and cerebrospinal fluid volume changes. DISCUSSION: Our findings prioritize AD genes whose regulation is associated with vulnerable brain regions, offering a potential mechanistic framework for downstream functional validation.

Alzheimer’s Disease↗

PubMed2022

A multi-omic analysis of MCF10A cells provides a resource for integrative assessment of ligand-mediated molecular and phenotypic responses.

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix proteins. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods ( synapse.org/LINCS_MCF10A ). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes. Beyond these analyses, this dataset will serve as a resource for the broader scientific community to mine for biological insights, to compare signals carried across distinct molecular modalities, and to develop new computational methods for integrative data analysis.

Epidermal Growth Factor↗

PubMed1978

Phenotypic and molecular expression of albumin in rat hepatoma x L cell hybrids.

Explore the source record for details and available documents.

Albumins↗

PubMed2025

Distinct immune-metabolic phenotypes underlie poor coronary collateral circulation.

BACKGROUND: Coronary collateral circulation (CCC) significantly impacts myocardial perfusion and clinical outcomes in coronary artery disease patients, yet the underlying molecular heterogeneity remains inadequately characterized. OBJECTIVE: To identify distinct molecular phenotypes in patients with poor CCC, validate these phenotypes using clinical parameters, and evaluate their prognostic implications. METHODS: This study enrolled 149 patients (80 with good CCC and 69 with poor CCC) for high-throughput proteomic profiling. Unsupervised consensus clustering identified molecular subtypes within poor CCC patients, followed by differential expression analysis and KEGG pathway enrichment. Boruta feature selection was implemented, and multiple machine learning algorithms were tested on clinical data, with XGBoost optimization (accuracy 80.0%, F1-score 80.31%) and SHAP value interpretation. External validation was performed using the MIMIC database. Kaplan-Meier analysis and Cox regression models assessed major adverse cardiovascular events (MACE). RESULTS: Two distinct phenotypes emerged among poor CCC patients: Cluster 1 (n = 39, Complement-Driven Vascular Remodeling [CDVR]) and Cluster 2 (n = 30, Immuno-Thrombotic Myocardial Dysfunction [ITMD]). An XGBoost model incorporating fasting glucose, eosinophil percentage, and HbA1c achieved excellent discrimination (AUC > 0.91). External validation confirmed the phenotype-specific clinical patterns. Notably, Cluster 2 demonstrated significantly higher MACE incidence compared to Cluster 1 (Log-rank p < 0.05), with KEGG analysis revealing significant upregulation of platelet activation, diabetic cardiomyopathy, and metabolic pathways in the ITMD phenotype. CONCLUSION: Poor CCC encompasses distinct immune-metabolic phenotypes that can be accurately classified using integrated proteomic-clinical modeling. This classification enables more precise risk stratification and may guide personalized therapeutic strategies for coronary artery disease patients with inadequate collateralization.

Humans↗

PubMed2025

Isolation of a novel human prion strain from a PRNP codon 129 heterozygous vCJD patient.

The epizootic prion disease of cattle, bovine spongiform encephalopathy (BSE), caused variant Creutzfeldt-Jakob disease (vCJD) in humans following dietary exposure. Codon 129 polymorphism of the human prion protein gene (PRNP), encoding either methionine (M) or valine (V), dictates the propagation of distinct human prion strains and up to now all but one neuropathologically confirmed vCJD patients have had a 129MM genotype. Concordant with this genetic association, transgenic modelling has established that human PrP 129V is incompatible with the vCJD prion strain and that depending on codon 129 genotype, primary human infection with BSE prions may, in addition to vCJD, result in sporadic CJD-like or novel phenotypes. In 2016 we saw the first neuropathologically confirmed case of vCJD in a patient with a codon 129MV genotype. This patient's neuropathology and molecular strain type were pathognomonic of vCJD but their clinical presentation and neuroradiological features were more typical of sporadic CJD, suggestive of possible co-propagation of another prion strain. Here we report the transmission properties of prions from the brain and lymphoreticular tissues of the 129MV vCJD patient. Primary transmissions into transgenic mice expressing human PrP with different codon 129 genotypes mainly produced neuropathological and molecular phenotypes congruent to those observed in the same lines of mice challenged with prions from 129MM vCJD patient brain, indicative that the vCJD prion strain was the dominant propagating prion strain in the patient's brain. Remarkably however, some transgenic mice challenged with 129MV vCJD patient brain propagated a novel prion strain type which at secondary passage was uniformly lethal in mice of all three PRNP codon 129 genotypes after similar short mean incubation periods. These findings establish that cattle BSE prions can trigger the co-propagation of distinct prion strains in humans.

Animals↗

PubMed2026

Matrix Mechanics Governs Mechano-Metabolic Adaptation across Cancer Grades in Bladder Spheroids.

Extracellular matrix (ECM) mechanics is pivotal regulators of tumor progression, yet how viscoelasticity and matrix architecture converge to shape metabolic and invasive adaptation remains insufficiently defined. We postulate that mechanical stimuli from the ECM induce coordinated changes in adhesive and metabolic pathways, and that the nature of this independent mechano-metabolic pathway is conserved across benign, low-invasive, and high-invasive bladder cancer phenotypes. Therefore, we engineered collagen-hyaluronan hydrogels with tunable stiffness to recapitulate soft and rigid tumor microenvironments and profiled bladder cancer spheroids representing benign, low-invasive, and highly invasive states. Integrating hydraulic force spectroscopy, rheology, and molecular phenotyping, we show that matrix stiffening differentially reprograms spheroid architecture, motility, and adhesion- and metabolism-related gene expression. Spheroid behavior emerged from the interplay between intrinsic mechanical properties, matrix rheology, and molecular adaptation. HCV29 spheroids formed rigid, compact structures, relying on cell-matrix adhesion rather than metabolic or proteolytic remodeling. HT1376 spheroids activated glycolysis (HK2) and MMP-2-dependent ECM remodeling in soft matrices, but remained largely nonmigratory, indicating decoupling of invasive priming from motility. T24 spheroids were soft, deformable, and highly migratory in compliant matrices, integrating metabolic reprogramming, adhesion remodeling (E-/N-cadherin, SDC4), and radial collagen fiber alignment to drive invasion. Notably, canonical FAK/AKT/mTOR signaling was absent across all spheroids, while pS6 ribosomal protein and ILK indicated noncanonical, SDC4/integrin-ILK-dependent mechanotransduction supporting cytoskeletal dynamics, metabolism, and ECM remodeling. Collagen organization further differed across spheroid types, with dense, radially aligned fibers in HT1376, intermediate architecture in HCV29, and loose, disorganized networks in T24, closely matching their distinct migratory behaviors and cell-ECM interactions. These findings reveal stage-specific mechanometabolic strategies in bladder cancer, demonstrating how ECM mechanics and architecture jointly guide invasion, metabolic adaptation, and local immune modulation, including the regulation of immune cell infiltration and tumor immune evasion.

Humans↗

PubMed2024

Genetic evidence for predisposition to acute leukemias due to a missense mutation (p.Ser518Arg) in ZAP70 kinase: a case-control study.

BACKGROUND: The apparent lack of additional missense mutations data on mixed-phenotype leukemia is noteworthy. Single amino acid substitution by these non-synonymous single nucleotide variations can be related to many pathological conditions and may influence susceptibility to disease. This case-control study aimed to unravel whether the ZAP70 missense variant (rs104893674 (C > A)) underpinning mixed-phenotype leukemia. METHODS: The rs104893674 was genotyped in clients who were mixed-phenotype acute leukemia-, acute lymphoblastic leukemia- and acute myeloid leukemia-positive and matched healthy controls, which have been referred to all major urban hospitals from multiple provinces of country- wide, IRAN, from February 11' 2019 to June 10' 2023, by amplification refractory mutation system-polymerase chain reaction method. Direct sequencing for rs104893674 of the ZAP70 gene was performed in a 3130 Genetic Analyzer. RESULTS: We found that the AC genotype of individuals with A allele at this polymorphic site (heterozygous variant-type) contribute to the genetic susceptibility to acute leukemia of both forms, acute myeloid leukemia and acute lymphoblastic leukemia as well as with a mixed phenotype. In other words, the ZAP70 missense variant (rs104893674 (C > A)) increases susceptibility of distinct cell populations of different (myeloid and lymphoid) lineages to exhibiting cancer phenotype. The results were all consistent with genotype data obtained using a direct DNA sequencing technique. CONCLUSION: Of special interest are pathogenic missense mutations, since they generate variants that cause specific molecular phenotypes through protein destabilization. Overall, we discovered that the rs104893674 (C > A) variant chance in causing mixed-phenotype leukemia is relatively high.

Humans↗

PubMed2024

Construction of a molecular diagnostic system for neurogenic rosacea by combining transcriptome sequencing and machine learning.

Patients with neurogenic rosacea (NR) frequently demonstrate pronounced neurological manifestations, often unresponsive to conventional therapeutic approaches. A molecular-level understanding and diagnosis of this patient cohort could significantly guide clinical interventions. In this study, we amalgamated our sequencing data (n = 46) with a publicly accessible database (n = 38) to perform an unsupervised cluster analysis of the integrated dataset. The eighty-four rosacea patients were partitioned into two distinct clusters. Neurovascular biomarkers were found to be elevated in cluster 1 compared to cluster 2. Pathways in cluster 1 were predominantly involved in neurotransmitter synthesis, transmission, and functionality, whereas cluster 2 pathways were centered on inflammation-related processes. Differential gene expression analysis and WGCNA were employed to delineate the characteristic gene sets of the two clusters. Subsequently, a diagnostic model was constructed from the identified gene sets using linear regression methodologies. The model's C index, comprising genes PNPLA3, CUX2, PLIN2, and HMGCR, achieved a remarkable value of 0.9683, with an area under the curve (AUC) for the training cohort's nomogram of 0.9376. Clinical characteristics from our dataset (n = 46) were assessed by three seasoned dermatologists, forming the NR validation cohort (NR, n = 18; non-neurogenic rosacea, n = 28). Upon application of our model to NR diagnosis, the model's AUC value reached 0.9023. Finally, potential therapeutic candidates for both patient groups were predicted via the Connectivity Map. In summation, this study unveiled two clusters with unique molecular phenotypes within rosacea, leading to the development of a precise diagnostic model instrumental in NR diagnosis.

Humans↗

PubMed2024

Proteomic Heterogeneity of the Extracellular Matrix Identifies Histologic Subtype-Specific Fibroblast in Gastric Cancer.

Gastric cancer (GC) is a highly heterogeneous disease regarding histologic features, genotypes, and molecular phenotypes. Here, we investigate extracellular matrix (ECM)-centric analysis, examining its association with histologic subtypes and patient prognosis in human GC. We performed quantitative proteomic analysis of decellularized GC tissues that characterizes tumorous ECM, highlighting proteomic heterogeneity in ECM components. We identified 20 tumor-enriched proteins including four glycoproteins, serpin family H member 1 (SERPINH1), annexin family (ANXA3/4/5/13), S100A family (S100A6/8/9), MMP14, and other matrisome-associated proteins. In addition, histopathological characteristics of GC reveals differential expression in ECM composition, with the poorly cohesive carcinoma-not otherwise specified (PCC-NOS) subtype being distinctly demarcated from other histologic subtypes. Integrating ECM proteomics with single-cell RNA sequencing, we identified crucial molecular markers in the PCC-NOS-specific stroma. PCC-NOS-enriched matrisome proteins and gene expression signatures of adipogenic cancer-associated fibroblasts (CAFadi) are closely linked, both associated with adverse outcomes in GC. Using tumor microarray analysis, we confirmed the CAFadi surface marker, ATP binding cassette subfamily A member 8 (ABCA8), predominantly present in PCC-NOS tumors. Our ECM-focused analysis paves the way for studies to determine their utility as biomarkers for patient stratification, offering valuable insights for linking molecular and histologic features in GC.

Humans↗

PubMed2026

Phenotypic and phylogenomic characterization of Lactococcus garvieae isolates from rainbow trout (Oncorhynchus mykiss) in Türkiye.

Lactococcosis is an important bacterial disease of farmed fish and causes substantial economic losses in rainbow trout (Oncorhynchus mykiss) aquaculture. In this study, Lactococcus garvieae isolates recovered from rainbow trout farms in Türkiye were characterized using phenotypic, molecular, and phylogenomic methods. Among 32 presumptive Lactococcus isolates recovered from 127 dead rainbow trout, four were confirmed as L. garvieae and exhibited identical biochemical characteristics, Pulsed Field Gel Electrophoresis (PFGE) profiles, and broad growth tolerance across different pH, salinity, and temperature conditions. All isolates were presumptively classified as resistant to ciprofloxacin and florfenicol, while remaining susceptible to tetracycline and penicillin. Based on the AMR profiles, strain LG2, which exhibited the most susceptible antimicrobial profile among the isolates, was selected for whole-genome sequencing (WGS). WGS of the representative isolate LG2 generated a single 2,214,687-bp chromosomal contig with 38.5% GC content and 99.0% BUSCO completeness. In silico PCR assigned LG2 to serotype I, and the genome contained an intact capsule-associated cps/kps locus. The chromosomal lsa(D) determinant and an mdt(A)-like efflux-associated gene were detected, whereas no plasmid replicons or acquired quinolone or florfenicol resistance genes were identified, indicating discordance between the phenotypic and genomic AMR results. Taxonomic verification of 236 publicly available Lactococcus assemblies yielded 41 verified public L. garvieae genomes, which, together with LG2, formed a 42-genome within-species dataset. LG2 was most closely related to the Turkish isolate OS-37, sharing 99.96% ANI and differing by three core SNPs; both belonged to ST109, whereas the other Turkish isolates belonged to ST139. cgMLST identified a conserved genomic backbone, while pan-genome analysis identified 5,655 gene clusters and an open pan-genome characterized by a large cloud-gene fraction. These findings demonstrate the importance of species verification in Lactococcus population genomics and reveal substantial accessory-genome diversity within L. garvieae. The genomic features of LG2 provide a basis for future pathogenicity and immunogenicity studies, although experimental validation is required. Overall, these findings highlight the importance of local genomic surveillance for understanding L. garvieae population structure and provide a genomic framework for future region-specific vaccine research.

Animals↗

PubMed2026

A human lysosomal storage disorder toolkit for decoding proteome landscapes in cortical-like and dopaminergic-like induced neurons.

Lysosomes maintain cellular homeostasis by degrading proteins delivered via endocytosis and autophagy and by recycling building blocks for organelle biogenesis. Lysosomal storage disorders (LSDs) comprise a group of diseases affecting diverse lysosomal functions. To facilitate molecular phenotyping across diverse LSD gene classes, we are developing a library of human embryonic stem cells engineered to lack individual LSD genes as a resource for the field. Here, we report our initial stem cell toolkit lacking one of 23 LSD genes, including the majority of genes associated with sphingolipidoses and neuronal ceroid lipofuscinoses, and its use in the generation of a proteomic resource for induced cortical-like and midbrain dopaminergic-like neurons. In-depth abundance and correlation profiling across organelles and suborganelle components revealed potential vulnerabilities that reflect distinct patterns of proteome alterations across both genotypes and neuronal cell types. We characterize alterations in the mitochondrial proteome associated with GBA1 and ASAH1 deficiency and identify synaptic and mitochondrial defects in ASAH1-/- induced neurons that correlate with defects in neuronal firing rates. Moreover, we developed an informatic pipeline for proteome-wide identification of individual protein-protein interactions and protein complexes that may be disrupted as a result of LSD gene deficiency. Finally, we visualized structural alterations of ASAH1-deficient endolysosomes in situ using cryoelectron tomography, revealing swollen organelles that were largely devoid of dense internal membranes characteristic of wild-type cells, but containing numerous intralumenal vesicle compartments. This toolkit and associated proteomic landscapes provide a resource for defining molecular signatures associated with LSD gene dysfunction and organelle vulnerability.

Humans↗

PubMed2025

Integrated Multiomics Analyses of the Molecular Landscape of Sarcopenia in Alcohol-Related Liver Disease.

BACKGROUND: Skeletal muscle is a major target for ethanol-induced perturbations, leading to sarcopenia in alcohol-related liver disease (ALD). The complex interactions and pathways involved in adaptive and maladaptive responses to ethanol in skeletal muscle are not well understood. Unlike hypothesis-driven experiments, an integrated multiomics-experimental validation approach provides a comprehensive view of these interactions. METHODS: We performed multiomics analyses with experimental validation to identify novel regulatory mechanisms of sarcopenia in ALD. Studies were done in a comprehensive array of models including ethanol-treated (ET) murine and human-induced pluripotent stem cell-derived myotubes (hiPSCm), skeletal muscle from a mouse model of ALD (mALD) and human patients with alcohol-related cirrhosis and controls. We generated 13 untargeted datasets, including chromatin accessibility (assay for transposase accessible chromatin), RNA sequencing, proteomics, phosphoproteomics, acetylomics and metabolomics, and conducted integrated multiomics analyses using UpSet plots and feature extraction. Key findings were validated using immunoblots, redox measurements (NAD+/NADH ratio), imaging and senescence-associated molecular phenotype (SAMP) assays. Mechanistic studies included mitochondrial-targeted Lactobacillus brevis NADH oxidase (MitoLbNOX) to increase redox ratio and MitoTempo as a mitochondrial free radical scavenger. RESULTS: Multiomics analyses revealed enrichment in mitochondrial oxidative function, protein synthesis and senescence pathways consistent with the known effects of hypoxia-inducible factor 1α (HIF1α) during normoxia. Across preclinical and clinical models, HIF1α targets (n = 32 genes) and signalling genes (n > 100 genes) (n = 3 ATACseq, n = 65 phosphoproteomics, n = 10 acetylomics, n = 6 C2C12 proteomics, n = 106 C2C12 RNAseq, n = 64 hiPSC RNAseq, n = 30 hiPSC proteomics, n = 3 mouse proteomics, n = 25 mouse RNAseq, n = 8 human RNAseq, n = 3 human proteomics) were increased. Stabilization of HIF1α (C2C12, 6hEtOH 0.24 ± 0.09; p = 0.043; mALD 0.32 ± 0.074; p = 0.005; data shown as mean difference ± standard error mean) was accompanied by enrichment in the early transient and late change clusters, -log(p-value) = 1.5-3.8, of the HIF1α signalling pathway. Redox ratio was reduced in ET myotubes (C2C12: 15512 ± 872.1, p < 0.001) and mALD muscle, with decreased expression of electron transport chain components (CI-V, p < 0.05) and Sirt3 (C2C12: 0.067 ± 0.023, p = 0.025; mALD: 0.41 ± 0.12, p = 0.013). Acetylation of mitochondrial proteins was increased in both models (C2C12: 107364 ± 4558, p = 0.03; mALD: 40036 ± 18 987, p = 0.049). Ethanol-induced SAMP was observed across models (P16: C2C12: 0.2845 ± 0.1145, p < 0.05; hiPSCm: 0.2591, p = 0.041). MitoLbNOX treatment reversed redox imbalance, HIF1α stabilization, global acetylation and myostatin expression (p < 0.05). CONCLUSIONS: An integrated multiomics approach, combined with experimental validation, identifies HIF1α stabilization and accelerated post-mitotic senescence as novel mechanisms of sarcopenia in ALD. These findings show the complex molecular interactions leading to mitochondrial dysfunction and progressive sarcopenia in ALD.

Sarcopenia↗

PubMed2026

RETRACTION: Loss-of-Function CARS1 Variants in a Patient With Microcephaly, Developmental Delay, and a Brittle Hair Phenotype.

C. Del Greco, M. E. Kuo, D. E. C. Smith, M. I. Mendes, G. S. Salamons, M. Nemcovic, R. Kodrikova, S. Sestak, M. Stancheva, and A. Antonellis, "Loss-of-Function CARS1 Variants in a Patient With Microcephaly, Developmental Delay, and a Brittle Hair Phenotype," Molecular Genetics & Genomic Medicine 13, no. 2 (2025): e70078, https://doi.org/10.1002/mgg3.70078. The above article, published online on 18 February 2025 in Wiley Online Library (https://onlinelibrary.wiley.com/), has been retracted by agreement between the authors; the journal Editor-in-Chief, Paraminder Dhillon; and Wiley Periodicals, LLC. The retraction has been agreed upon due to the lack of appropriate authorization for the publication of the CARS1 variants related to the specific patient described in this clinical report. In addition, written consent for publication was not obtained from the child's legal guardian.

Journal Article↗

PubMed2026

Integrating histology and spatial transcriptomics via multimodal transformers and contrastive representation learning for accurate gene expression prediction.

Predicting spatial gene expression from Histological images is a fundamental task in understanding tissue organization and molecular phenotypes. However, existing methods often rely on single-model representations or lack effective alignment between image and transcriptomic features. To address these limitations, we propose a unified multimodal learning framework that integrates histological imaging and spatial transcriptomics through a shared latent representation space. Specifically, histological H&E images are encoded by a ResNet50-based convolutional stem and a MobileViT Transformer backbone to extract hierarchical visual representations. Both modalities are projected into a shared latent space via linear-GELU-dropout transformation blocks, enabling cross-modal alignment through a contrastive learning objective that maximizes agreement between the corresponding image and the spot embeddings. Experimental results on the 10x Genomics Visium dataset of human liver tissue demonstrate that MViTGene achieves significantly higher prediction accuracy than existing methods across multiple gene subsets, with improvements of 20%, 33%, and 12% in predicting marker genes, highly expressed genes, and highly variable genes, respectively. The significant improvement in relevance indicates that the model can more accurately capture the true correspondence between tissue morphology and gene expression, therefore enabling more reliable biological interpretation. It provides a computational tool for high-throughput spatial gene expression prediction that balances performance and interpretability.

Humans↗

PubMed2026

Clinical and Molecular Evaluation of HER2-Low and HER2-Ultralow Breast Cancer in the Penelope-B Clinical Trial Cohort.

The DestinyBreast (DB)04 and DB06 trials have shown clinical activity of trastuzumab-deruxtecan (T-DXd) in HER2-low and HER2-ultralow metastatic breast cancer. The identification of HER2-low and HER2-ultralow breast cancer is therefore essential for personalized therapy with T-DXd. We evaluated 723 residual tumors from the Penelope-B trial (NCT01864746) and correlated different levels of HER2 protein expression with prognosis and messenger RNA (mRNA) profiles, including HER2 transcripts. In Penelope-B, 57.68% (n = 417) of 723 residual tumors were HER2 low. The HER2-ultralow category was assigned to 109 (15.08%) tumors, and 197 (27.25%) tumors were completely HER2 negative (HER2 0). In Kaplan-Meier analysis, there were no survival differences among these 3 subgroups. There was no significant difference in HER2 mRNA expression between HER2-0 and HER2-ultralow tumors (P = .08). In contrast, there was a highly significant difference in HER2 mRNA expression between HER2-ultralow and HER2-low tumors (P < .0001) and between HER2-low and HER2-positive tumors (P < .0001). The extracellular protease cathepsin L, which has been suggested as a biomarker for extracellular cleavage of T-DXd, was detectable in all HER2-related subgroups and was a negative prognostic factor for invasive disease-free survival and overall survival (P = .0001) in preneoadjuvant core biopsies. In our study, we were able to characterize HER2 low as a clinically relevant and molecular defined tumor group with significantly increased HER2 expression. In contrast, for HER2 ultralow, we did not observe a defined molecular phenotype, despite the clinically relevant regulatory approval of T-DXd also in the ultralow subgroup. Additional investigations are needed to identify biomarkers beyond HER2 for T-DXd response as a basis for refined criteria for treatment eligibility.

Adult↗

PubMed2025

ORCO: Ollivier-Ricci Curvature-Omics-an unsupervised method for analyzing robustness in biological systems.

MOTIVATION: Although recent advanced sequencing technologies have improved the resolution of genomic and proteomic data to better characterize molecular phenotypes, efficient computational tools to analyze and interpret large-scale omic data are still needed. RESULTS: To address this, we have developed a network-based bioinformatic tool called Ollivier-Ricci curvature for omics (ORCO). ORCO incorporates omics data and a network describing biological relationships between the genes or proteins and computes Ollivier-Ricci curvature (ORC) values for individual interactions. ORC is an edge-based measure that assesses network robustness. It captures functional cooperation in gene signaling using a consistent information-passing measure, which can help investigators identify therapeutic targets and key regulatory modules in biological systems. ORC has identified novel insights in multiple cancer types using genomic data and in neurodevelopmental disorders using brain imaging data. This tool is applicable to any data that can be represented as a network. AVAILABILITY AND IMPLEMENTATION: ORCO is an open-source Python package and is publicly available on GitHub at https://github.com/aksimhal/ORC-Omics.

Software↗

PubMed2026

Pathogenic POLRMT variants in mice impair mtDNA transcription and affect perinatal survival.

Mitochondrial gene expression is essential for oxidative phosphorylation that generates the bulk of the cellular ATP, and mitochondrial dysfunction is a common cause of human metabolic diseases. Recently, the first pathogenic variants in the only known mitochondrial RNA polymerase (POLRMT) were described in patients presenting with a wide variety of clinical manifestations, including hypotonia, short stature, and developmental delay. Here, we modeled two human pathogenic POLRMT variants by creating the corresponding substitutions in mice: the dominant S582F and the recessive R984C variant. Mice homozygous for the R984C variant showed perinatal lethality without apparent embryonic developmental defects, a finding consistent with a failure to adapt to the metabolic transition to oxidative metabolism at birth. Mice carrying the S582F variant were viable and exhibited decreased mitochondrial transcript levels due to impaired de novo transcription. However, mtDNA levels and in organello mtDNA replication remained normal, which recapitulates the molecular phenotypes observed in patients. Altogether, our findings indicate that the conserved arginine near the active site is essential for POLRMT function, while the serine in the intercalating hairpin of the N-terminal domain is required for near-genome length transcription but not primase activity. This study highlights genotype-phenotype differences and provides new insights into POLRMT function.

Animals↗