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PubMed2026

Integrative transcriptomic, spatial and functional-genomic analysis identifies a UFMylation-related vascular-stromal program and prioritizes WWTR1 in glioblastoma.

Glioblastoma (GBM) contains spatially organized stress-adaptive and vascular niches. Because transcript abundance does not measure UFM1 conjugation, we asked whether a UFMylation-related transcriptional axis identifies a reproducible tissue program and alters candidate prioritization. In 518 unique primary TCGA-GBM tumors profiled on the Affymetrix HT Human Genome U133A array, weighted gene co-expression network analysis of 8,000 variable genes yielded 12 modules. The 278-gene green module ranked first across nine prespecified traits (mean |r|=0.637). Direct overlap comprised 1/3 measurable UFMylation-core, 5/19 ER-stress/UPR, and 2/15 proteostasis genes; after excluding overlapping genes, correlations with the green eigengene remained significant (r = 0.373, 0.831, 0.639, and 0.699 for UFMylation-core, ER-stress/UPR, proteostasis, and composite scores, respectively). The green score was associated with overall survival per standard-deviation increase (HR 1.17, 95% CI 1.07-1.28), although clinical adjustment attenuated the estimate. In a 10-sample single-cell dataset, sample-level scores were higher in pericytes and endothelial cells than in malignant cells. Donor-aware IvyGAP analysis supported regional organization, whereas one Visium section showed stronger concordance with ER-stress/UPR and mesenchymal scores than with the UFMylation-core score. CellChat indicated pathway-selective rather than global remodeling of inferred vascular communication. Layer ablation moved WWTR1 from rank 48 using WGCNA alone to rank 4 overall and rank 1 among non-common-essential genes after cross-platform integration. These findings define an ER-stress/mesenchymal-weighted, UFMylation-related vascular-stromal transcriptional association and nominate WWTR1 for experimental testing.

Humans↗

PubMed2026

highSpaClone enables copy number alteration inference and tumor subclone analysis for high-resolution spatial transcriptomics.

High-resolution spatially resolved transcriptomics (SRT) offers unprecedented opportunities to investigate tumor heterogeneity but poses substantial computational and analytical challenges. Here, we present highSpaClone, a computational framework for copy number alteration (CNA) inference and tumor subclone identification from high-resolution SRT data across multiple spatial scales. By integrating spatial constraints into CNA estimation and clonal clustering, highSpaClone enables neighboring spatial locations to share information, thereby improving the robustness of genomic signals and the accuracy of subclone delineation. Across multiple Xenium and Visium HD datasets, highSpaClone revealed unique transcriptional programs, clonal evolutionary trajectories, and distinct tumor-microenvironment interactions. Furthermore, in human colorectal cancer samples, highSpaClone detected CNA events in histologically normal epithelial regions, highlighting early genomic alterations associated with field cancerization. These findings establish highSpaClone as a scalable framework for studying clonal architecture and tumor evolution.

CP: cancer biology↗

PubMed2026

Characterization and analysis of the full-length transcriptome of Frankliniella occidentalis (Thysanoptera: Thripidae).

BACKGROUND: Frankliniella occidentalis, an insect belonging to the order Thysanoptera, causes severe damage to agricultural and horticultural crops, resulting in significant economic losses worldwide. The development of molecular and sequencing technologies has helped elucidate the molecular mechanisms regulating its growth and development as well as its damaging activity. However, much remains to be explored. To further investigate the molecular complexity of this species, we sequenced the full-length transcriptome of mixed samples obtained from specimens at all developmental stages. RESULTS: Of all transcripts, 89.04% matched with the reference genome; additionally, 29,750 alternative splicing events, 2,342 genes with poly(A) sites, and 153 candidate fusion transcript events were identified, and 4,235 long noncoding RNAs were discovered. CONCLUSIONS: This is the first full-length transcriptome of F. occidentalis reported to date. This study greatly contributes to the understanding of the molecular complexity and diversity of this insect, providing a basis to develop specific molecular targets as well as resources for gene function studies in other insects.

Animals↗

PubMed2026

Transcriptomic responses to developmental temperature in two field-collected Spodoptera exigua populations from Korea.

The beet armyworm, Spodoptera exigua, is a polyphagous insect whose development and seasonal occurrence are strongly influenced by temperature. However, transcriptomic responses to developmental thermal regimes remain insufficiently characterized in field-collected populations. In this study, we compared two Korean field-collected populations of S. exigua: a Haenam population collected in May and initially maintained at 15 ± 1 °C (HN), and a Jeju population collected in July and initially maintained at 27 ± 1 °C (JJ). F1 larvae from each population were reared under three fluctuating developmental temperature regimes: low (15-21 °C), middle (21-27 °C), and high (27-33 °C), followed by RNA-seq analysis. Differential expression analysis revealed population-associated variation in transcriptomic responses across developmental temperatures. HN exhibited a larger number of differentially expressed genes under the high-temperature regime, suggesting stronger transcriptomic sensitivity to elevated developmental temperature. Functional enrichment analyses identified population-associated differences in pathways related to heat response, oxidative metabolism, cytoskeletal organization, cuticle-associated processes, lipid metabolism, and immune-related functions. In JJ, heat-response and cuticle-related expression patterns were more prominent under warmer developmental conditions, whereas HN showed broader changes in stress- and metabolism-associated pathways under high temperature. Overall, this study provides a comparative transcriptomic analysis of two field-collected S. exigua populations under different developmental temperature regimes and identifies RNA-seq-based molecular response patterns associated with population-specific thermal response profiles.

Animals↗

PubMed2026

Optics-free spatial genomics for mapping mammalian brain aging by IRISeq.

Spatial transcriptomics has emerged as a transformative approach for in situ mapping of cellular heterogeneity and interactions, yet existing methods often compromise throughput, cost and tissue coverage. Here we introduce Imaging Reconstruction using Indexed Sequencing (IRISeq): an optics-free, cost-effective platform that leverages spatial interaction mapping by indexed sequencing to profile tissues at adjustable sizes and resolutions (5-50 µm). We applied IRISeq to map gene expression across more than 70 coronal sections from both adult and aged mouse brains, including wild-type and two lymphocyte-deficient models (Rag1 and Prkdc mutants) and generated more than 460,000 spatial transcriptome profiles. Our integrated analysis with 783,264 single-cell transcriptomes revealed region-specific aging signatures that are lymphocyte dependent, notably a downregulation of interferon signaling and inflammation in ventricular regions upon lymphocyte depletion, alongside mutant-specific upregulation of senescence pathways. Furthermore, lymphocyte deficiency was linked to preserved abundance of ependymal cells that line the brain's ventricles and to distinct microglial state dynamics, highlighting a key role for lymphocytes in driving inflammatory processes during brain aging. Overall, IRISeq provides a high-throughput and cost-effective solution for spatially resolved transcriptomic profiling, opening new avenues for elucidating region-specific cellular mechanisms underlying aging and identifying potential therapeutic targets to preserve brain homeostasis.

Animals↗

PubMed2026

Single-cell and spatial transcriptomic technologies for lung cancer tumor microenvironment analysis.

Lung cancer remains one of the leading causes of cancer-related mortality worldwide; beyond its rising incidence, its marked molecular heterogeneity and complex tumor microenvironment (TME) hinder treatment response and drive resistance, contributing directly to its high mortality rate. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) provide complementary approaches for dissecting these features. scRNA-seq enables high-resolution analysis of cellular diversity and transcriptional states but requires tissue dissociation and therefore loses spatial context. In contrast, ST preserves tissue architecture and provides insights into how gene-expression programs within the TME are organized, although no currently available spatial platform combines whole-transcriptome coverage with true single-cell resolution over large tissue areas. Together, these technologies have enabled detailed mapping of tumor, immune and stromal populations and of their spatial interactions, revealing functionally distinct cellular niches that contribute to immune evasion, metastasis and response to therapy. In this narrative review we organize the primary literature around a single question, how spatially structured cellular ecosystems, rather than individual cell types, determine therapeutic response and resistance in lung cancer - and we explicitly separate observations that are reproducible across independent cohorts and platforms from those that remain confined to single studies. We further summarize the technical, analytical and logistic barriers that currently prevent spatially resolved signatures from entering routine diagnostic pathology. Understanding dysregulated pathways and spatially constrained intercellular communication within the TME helps identify candidate biomarkers and may support the identification of therapeutic approaches directed at tumor-intrinsic programs as well as at microenvironment-driven resistance mechanisms.

Cell-cell communication↗

PubMed2025

A small cationic probe for accurate, punctate discovery of RNA tertiary structure.

RNA molecules fold into intricate three-dimensional tertiary structures that are central to their biological functions. Yet reliably discovering new motifs that form true tertiary interactions remains a major challenge. Here we show that RNA tertiary folding occasionally generates electronegative motifs that react selectively with the small, positively-charged probe trimethyloxonium (TMO). Sites with enhanced reactivity to TMO, compared with the neutral reagent dimethyl sulfate (DMS), are indicative of tertiary structure and define T-sites. These positions share a structural signature in which a reactive nucleobase is adjacent to non-bridging phosphate oxygens, creating localized regions of negative charge. T-sites consistently map to the cores of higher-order structural interactions and functional centers across diverse RNAs, including distinct states in conformational ensembles. In the 10,723-nt dengue virus genome, three strong T-sites were detected, each within a complex structure required for viral replication. Cation-based covalent chemistry enables high-confidence discovery and analysis of functional RNA tertiary motifs across long and complex RNAs, opening new opportunities for transcriptome-wide structural analysis.

RNA electrostatics↗

PubMed2026

Single-cell expression quantitative trait locus Mendelian randomization reveals immune cell-specific causal regulatory networks and actionable targets in polycystic ovary syndrome.

ObjectiveTo systematically investigate whether the pathogenesis of polycystic ovary syndrome (PCOS) is causally related to dysregulated gene expression in specific immune cell subsets, and to evaluate the potential of these causal genes as actionable drug targets.MethodsThis study employed a two-sample Mendelian randomization (MR) framework using publicly available genome-wide association study (GWAS) summary statistics. The participant data included 797 PCOS cases and 140,558 controls (no direct patient recruitment was involved). Instrumental variables were derived from high-resolution immune cell-specific single-cell expression quantitative trait locus (sc-eQTL) data (OneK1K project) across 14 immune cell types. Primary analyses utilized the inverse-variance weighted (IVW) method. Shared causal variants were validated using Bayesian colocalization. Phenome-wide association analysis (PheWAS), external transcriptomic dataset validation (GSE8157), and DrugBank database screening were conducted for pleiotropy assessment and drug repositioning.ResultsMR analysis revealed genome-wide significant causal associations for GLIPR1 in non-classical monocytes (Mono NC) and XBP1 in CD4+ effector memory T cells (CD4 ET) with PCOS risk. Higher GLIPR1 expression was associated with a decreased PCOS risk (OR = 0.669, P = 4.34×10-6), whereas higher XBP1 expression was associated with an increased risk (OR = 1.406, P = 9.53×10-8). Colocalization analysis confirmed that GLIPR1 shares a causal variant with PCOS (PP.H4 = 96.73%). PheWAS and external validation confirmed the safety profile and significant upregulation (P = 0.03) of GLIPR1. Drug repositioning identified SOT-107, a Phase III protein therapy drug, as a potential interacting agent for GLIPR1.ConclusionsThis sc-eQTL MR study reveals immune cell-specific causal regulatory networks in PCOS. GLIPR1 in non-classical monocytes represents a high-confidence protective target, while XBP1 provides suggestive evidence for immune-mediated pathogenesis. The candidate drug SOT-107 highlights theoretical repositioning opportunities, though rigorous preclinical validation remains required.

Female↗

PubMed2025

Dual genetic loci and flavonoid metabolism orchestrate fruiting body coloration in Flammulina filiformis: a multi-omic roadmap for fungal pigmentation.

BACKGROUND: The fruiting bodies of macrofungi exhibit diverse coloration, traditionally attributed to melanin and carotenoid biosynthesis. This study is the first to reveal that flavonoids, rather than these classical pigments, are the predominant contributors to yellow pigmentation in the Flammulina filiformis. OBJECTIVE: To uncover the genetic basis and key regulatory genes involved in pigment formation in F. filiformis fruiting bodies, and to establish a model framework for studying color genetics in macrofungi. METHODS: Metabolomic profiling was conducted on yellow and white F. filiformis fruiting bodies to identify key pigment components. A segregating population was constructed, followed by integrated multi-omics analyses-including bulk segregant analysis (BSA), genome-wide association study (GWAS), and transcriptomics-to map regulatory loci and candidate genes. Functional roles were validated via genetic transformation and protein structural modeling. RESULTS: Flavonoid accumulation was identified as the biochemical hallmark of pigmented fruiting bodies. Genetic analysis revealed a dual regulatory mechanism: a qualitative locus governing pigmentation presence and a quantitative trait determining color intensity. Combined BSA and GWAS pinpointed a major locus, Ffcrs, within a recombination-suppressed region. Transcriptomic analysis identified two key regulators, Ffakr (a transcriptional activator) and Ffpal (encoding phenylalanine ammonia-lyase). Functional verification via transformation, structural modeling, and metabolite profiling in transgenic lines confirmed their essential roles in flavonoid biosynthesis and pigmentation. CONCLUSION: This study uncovers a flavonoid-based pigmentation mechanism in F. filiformis and elucidates a complex genetic architecture shaped by both qualitative and quantitative loci, providing a new paradigm for understanding pigment formation in macrofungi. The identified regulatory factors establish a molecular foundation for the precise manipulation of economically important pigmentation traits in edible mushroom.

Flavonoids↗

PubMed2025

Spatial Genomic Approaches to Investigate HOX Genes in Mouse Brain Tissues.

Spatial transcriptomic tools are an upcoming and powerful way to investigate targeted gene expression patterns within tissues. These tools offer the unique advantage of visualizing and understanding gene expression while preserving tissue integrity, thereby maintaining the spatial context of genes. Curio is a robust spatial transcriptomic tool that facilitates high throughput comprehensive spatial gene expression analysis across the entir e transcriptome with high efficiency. Here, we present a bioinformatics protocol for performing whole transcriptome gene expression analysis of mouse brain tissue using Curio. Specifically, we demonstrate using computational techniques to visualize expression patterns of various HOX genes in the mouse brain.

Animals↗

PubMed2026

Proteogenomic features define subtypes of mantle cell lymphoma.

Mantle cell lymphoma (MCL) is a biologically heterogeneous B-cell malignancy. Although genomics and transcriptomics have delineated parts of the MCL disease spectrum, proteomics remains largely unexplored. Here, we conducted a comprehensive proteogenomic analysis integrating genomics, transcriptomics, and proteomics on peripheral blood samples from 27 patients with MCL and 4 healthy donors to investigate the translational and posttranslational dimensions of MCL. Our study identified 1296 downregulated and 468 upregulated proteins in MCL cells. The splicing pathways were significantly upregulated at both the mRNA and protein levels, suggesting a critical role for aberrant RNA splicing in MCL pathogenesis. Integration of proteomic data with genetic aberrations revealed immunoglobulin heavy chain variable mutational status and CCND1 mutation are associated with distinctive transcriptomic and proteomic profiles, which correspond to significant differences in clinical outcomes. A multiomics molecular stratification model incorporating proteomic data showed superior predictive power for patient survival compared with single-omics models (concordance index, 0.83 vs 0.74). This study provides, to our knowledge, the first comprehensive proteogenomic profile of MCL, offering novel insights into its molecular mechanisms and clinical behavior. The identification of molecular subtypes and prognostic protein signatures underscores the potential of proteomics to guide precision medicine strategies for MCL.

Humans↗

PubMed2026

BCL11B enhancer hijacking by t(14;16)(q32;q24) translocation defines a novel high-risk subtype of T-ALL.

The molecular classification of T-cell acute lymphoblastic leukemia (T-ALL) remains incomplete, limiting risk stratification and the development of targeted therapies. Enhancer hijacking is a critical oncogenic mechanism that deregulates proto-oncogenes by repositioning cisregulatory regions via structural variants. Here, we performed an integrated analysis of pediatric and adult T-ALL and mixed-phenotype acute leukemias (MPALs), using whole-genome and whole-transcriptome sequencing. This analysis identified a group of 14 patients with predominantly T-lineage neoplasms driven by a t(14;16)(q32;q24) translocation, harboring universal GATA3 mutations and CDKN2A/B deletions. Mechanistically, this translocation repositions the ThymoD locus downstream of BCL11B, causing monoallelic, ectopic overexpression of FENDRR and mesenchymal transcription factor genes FOXF1 and FOXC2 and activating epithelial-mesenchymal transition transcription signatures. Immunophenotypic and single-cell RNA sequencing analyses revealed marked lineage ambiguity with myeloid and B-cell differentiation potentials specific to this subtype. Furthermore, functional analyses in CD34+ cord blood cells demonstrated that FOXF1 overexpression promotes myeloid differentiation while suppressing T-cell differentiation, serving as a key factor for lineage specification. Clinically, this subtype was detected in 0.15% to 4.0% of T-ALL/MPAL cases depending on the cohort, showing a median age of 15 years and enrichment in adolescents and young adults. Importantly, patients with t(14;16)(q32;q24) have an extremely poor prognosis, showing a trend toward worse outcomes than high-risk groups such as KMT2A-rearranged early T-cell progenitor-like, SPI1-rearranged, and LMO2 γδ-like T-ALLs. The unique molecular landscape and poor prognosis of patients with the t(14;16)(q32;q24) translocation underscore the need for the development of novel subtype-specific therapeutic approaches.

Humans↗

PubMed2026

From transcriptomic profiling to precision oncology: a bibliometric analysis of RNA sequencing in acute myeloid leukemia.

BACKGROUND: RNA sequencing (RNA-seq) has become an important tool for investigating the molecular heterogeneity of acute myeloid leukemia (AML); however, the global development and thematic evolution of this field remain inadequately characterized. OBJECTIVE: To map the global landscape of AML RNA-seq research and identify major knowledge domains, emerging themes, and temporal changes in research priorities. METHODS: Publications indexed in the Web of Science Core Collection and Scopus between January 1, 2007, and August 18, 2025, were retrieved. After database filtering, merging, and deduplication, 3,460 articles and reviews were included. CiteSpace, VOSviewer, the bibliometrix R package, and Microsoft Excel were used to analyze publication trends, collaboration networks, co-citation structures, keyword evolution, and citation bursts. RESULTS: Publication output increased steadily, accelerating after 2014. China contributed the largest number of publications (n = 547, 15.8%), whereas the United States had the highest total citation count. Major publication outlets spanned hematology, oncology, genomics, and molecular biology. Co-citation analysis identified prominent themes involving next-generation sequencing, gene mutations, KMT2A rearrangements, epigenetic dysregulation, leukemia-initiating cells, drug resistance, biomarkers, T-cell biology, and single-cell sequencing. Earlier literature emphasized sequencing technologies, gene expression profiling, and molecular alterations, whereas recent publications show increasing representation of cellular heterogeneity, single-cell transcriptomics, drug resistance, biomarker applications, immune-related research, and computational interpretation. CONCLUSION: While molecular characterization remains foundational, AML RNA-seq research has broadened to encompass increasingly prominent cellular, functional, computational, and translational dimensions. This study provides a structured overview of the field; nevertheless, bibliometric prominence should not be interpreted as direct evidence of clinical utility.

RNA sequencing↗

PubMed2026

REACTOR: REgulon Activity analysis and Comparison Tool for single-cell transcriptOmics Research.

SUMMARY: We introduce REACTOR, a computational tool designed to detect differential activity of transcriptional regulators and their target genes (regulons) in single-cell RNA-sequencing data. It expands the currently available framework for regulon analysis by introducing a robust statistical test to detect differential regulon activity between conditions, such as disease versus control, with multiple replicates. By contrasting different conditions, REACTOR enables identification of key condition- and cell type-specific regulons. To demonstrate the use of REACTOR, we illustrate its performance in a publicly available COVID-19 dataset. AVAILABILITY: REACTOR R-package together with an implementation vignette are available at https://www.github.com/elolab/REACTOR.

Regulon↗

PubMed2026

Characterization of carbon metabolism in a highly adhesive bacterium Acinetobacter sp. Tol 5 capable of assimilating diverse hydrocarbons and aromatic compounds.

Sustainable bioproduction requires developing robust microbial chassis with broad metabolic versatility and suitability for industrial applications. Acinetobacter sp. Tol 5 is a highly adhesive bacterium capable of utilizing various hydrocarbons, making it a promising chassis candidate for immobilized whole-cell catalysis. In this study, we characterized the carbon metabolism of Tol 5 by reconstructing metabolic pathway maps from its genomic data and analyzing the transcriptomes of cells grown on ethanol, hexadecane, toluene, and phenol. Genomic analysis revealed that Tol 5 has limited capacity for sugar utilization but possesses a wide range of metabolic pathways for alkane and aromatic compounds, including five distinct aromatic degradation routes that expand the known metabolic diversity of the genus Acinetobacter. Transcriptome analysis identified the specific pathway genes induced in response to each carbon source. During growth on phenol, alkylbenzene degradation genes were upregulated alongside phenol monooxygenase genes, suggesting possible substrate-dependent cross-regulation between aromatic degradation pathways. Gene disruption experiments indicated that phenol monooxygenase is required for phenol assimilation, whereas toluene dioxygenase may contribute to earlier entry into exponential growth while potentially limiting final biomass accumulation. These findings provide a comprehensive view of the carbon metabolism of Tol 5 and a basis for assessing its potential in bioprocesses using non-sugar carbon sources.

Acinetobacter↗

PubMed2025

Dynamic allelic expression in mouse mammary glands across the adult developmental cycle.

The mammary gland, which primarily develops postnatally, undergoes significant changes during pregnancy and lactation to facilitate milk production. Through the generation and analysis of 480 transcriptomes, we provide the most detailed allelic expression map of the mammary gland, cataloguing cell-type-specific expression from ex-vivo purified cell populations over 10 developmental stages, enabling comparative analysis. The work identifies genes involved in the mammary gland cycle, parental-origin-specific and genetic background-specific expression at cellular and temporal resolution, genes associated with human lactation disorders and breast cancer. Genomic imprinting, a mechanism regulating gene expression based on parental origin, is crucial for controlling gene dosage and stem cell potential throughout development. The analysis identified 25 imprinted genes monoallelically expressed in the mammary gland, with several showing allele-specific expression in distinct cell types. No novel imprinted genes were identified and the absence of biallelically expressed imprinted genes suggests that, unlike in brain, selective absence of imprinting does not regulate gene dosage in the mammary gland. This research highlights transcriptional dynamics within mammary gland cells and identifies novel candidate genes potentially significant in the tissue during pregnancy and lactation. Overall, this comprehensive atlas represents a valuable resource for future studies on expression and transcriptional dynamics in mammary cells.

Animals↗

PubMed2025

Rare variants in MIR184 are a novel genetic cause of Fuchs endothelial corneal dystrophy.

PURPOSE: To identify novel genetic causes of Fuchs endothelial corneal dystrophy (FECD) within a genetically unsolved patient cohort lacking repeat expansions in the TCF4 gene (Exp-). METHODS: A rare variant analysis framework (CoCoRV) was applied to exome data, in combination with in silico modeling, luciferase reporter, and RNA-seq analysis to characterize transcriptome-wide consequences of identified variants. RESULTS: A gene burden analysis identified MIR184, a microRNA encoding gene, to be enriched for rare pathogenic variants within the studied Exp- FECD cohort. In total, 2 noncoding rare variants were identified in 4 unrelated FECD probands: NR_029705.1:n.58G>A and n.73G>T. Both variants altered highly conserved mature sequence residues, were predicted to induce hairpin structural changes, and were experimentally determined to disrupt microRNA-mRNA interactions. RNA-seq of transfected human corneal endothelial cells revealed that the mutants elicited distinct transcriptomic profiles. Enriched KEGG pathways included PI3K-Akt signaling, focal adhesion, and immune response, revealing shared pathogenic mechanisms between MIR184-associated FECD and the more common TCF4 repeat expansion-mediated form of disease. CONCLUSION: MIR184 variants are a novel rare genetic cause of FECD, and common pathways of transcriptomic dysregulation are shared across genetically distinct subtypes of the disease. These pathways may serve as future gene agnostic targets for therapeutic interventions.

Humans↗

PubMed2025

Radiogenomic MRI biomarkers for noninvasive prediction of GPC3 expression and tumor microenvironment in hepatocellular carcinoma.

BACKGROUND: Glypican-3 (GPC3) is frequently overexpressed in hepatocellular carcinoma (HCC) and plays a key role in immune and metabolic remodeling of the tumor microenvironment. Reliable noninvasive biomarkers for predicting GPC3 status could improve patient stratification and support precision immunotherapy. METHODS: This multicenter retrospective study included 274 patients with pathologically confirmed hepatocellular carcinoma from three institutions, 34 external cases with MRI from The Cancer Imaging Archive, and 363 transcriptomic profiles from The Cancer Genome Atlas. Contrast-enhanced T1-weighted imaging and diffusion-weighted imaging were analyzed. Tumor and peritumoral regions were segmented manually and radiomic features extracted using PyRadiomics. Feature selection was performed with correlation filtering and least absolute shrinkage and selection operator regression. Machine learning classifiers including logistic regression, random forest, support vector machine, k-nearest neighbor, and decision tree were trained with 10-fold cross-validation and tested on independent external cohorts. A radiomics score was calculated for each patient. Radiogenomic analysis correlated radiomics scores with transcriptomic data using weighted gene co-expression network analysis. Hub genes and enriched pathways were identified, and immune infiltration and predicted immunotherapy response were assessed using computational methods. RESULTS: The random forest model using contrast-enhanced T1-weighted imaging achieved an area under the curve of 0.966 in training and 0.935 in internal validation. The integrated contrast-enhanced T1-weighted imaging plus diffusion-weighted imaging model reached an internal validation area under the curve of 0.979. In external testing, the best performance was obtained with a support vector machine model (area under the curve 0.756). Radiomics scores were significantly correlated with GPC3 expression (R = 0.78, p < 0.05). Transcriptomic analysis identified a 10-gene signature enriched in hypoxia and lipid metabolism pathways that stratified patients into prognostic subgroups (concordance index 0.720, hazard ratio 4.07, p < 0.0001). High-risk patients had greater immune infiltration and a lower predicted immune evasion score, suggesting a potential benefit from immunotherapy. CONCLUSIONS: MRI-based radiomics models can noninvasively predict GPC3 expression in hepatocellular carcinoma. Radiomics scores reflect underlying hypoxia and lipid metabolism pathways and stratify patients by prognosis and predicted immunotherapy response. These findings support radiogenomics as a translational approach to imaging-guided precision treatment in hepatocellular carcinoma.

Humans↗