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Comprehensive transcriptomics and proteomics analysis of neointima formation in human saphenous vein: implications for bypass graft disease.

Human saphenous veins (SVs) are widely used as grafts in coronary artery bypass (CABG) surgery but often fail due to neointima formation. Little is known, however, regarding the cellular, transcriptomic, and proteomic dynamics of neointima formation in human veins. Here, we performed transcriptomics and proteomics analysis in an ex vivo tissue culture model of neointima formation in human SVs procured for CABG surgery. Histological examination demonstrated significant elastin degradation and neointima formation (indicated by increased neointima area and neointima-to-media ratio) in SVs subjected to tissue culture. Analysis of data from 72 patients suggests that the progression of SV remodeling and neointima formation differs according to sex and body mass index, which is negatively associated with neointima formation in males only. RNA sequencing demonstrated upregulation of proinflammatory and proliferation-related genes during neointima formation and identified novel processes, including increased cellular stress and DNA damage responses, reflecting tissue trauma associated with vein harvesting. Proteomic analysis identified upregulated extracellular matrix-related and coagulation/thrombosis proteins and downregulated metabolic proteins. Spatial transcriptomics, used to infer regionally enriched gene expression, suggested dynamic alterations in fibroblast and vascular smooth muscle cell (VSMC) states during neointima formation. Specifically, we identified the emergence of HES1+ and matrix metalloproteinase 2- and 14-positive (MMP2+/MMP14+) expression in VSMCs and fibroblasts, respectively, during neointima formation. Furthermore, our data suggest that MIR647, identified through screening, maintains VSMC contractile gene expression. Our findings suggest dynamic transcriptomic and proteomic changes during neointima formation in human veins and provide useful mechanistic information for the pathogenesis of SV graft disease.NEW & NOTEWORTHY Using multiomics and spatial transcriptomics, we uncover dynamic molecular and cellular changes driving neointima proliferation in human saphenous veins, the most common conduit for bypass surgery. Our study highlights sex- and body mass index-associated differences, novel fibroblast and smooth muscle cell states, and a role for microRNA-647 in preserving vascular contractile phenotype. These findings provide new insight into the mechanisms of vein graft failure and may guide future strategies to improve coronary bypass outcomes.

Humans

A nucleolar stress gene signature enables quantitative scoring across multi-omics contexts.

The nucleolus is essential for ribosome biogenesis and cellular homeostasis, and its dysfunction can induce nucleolar stress, a process implicated in cancer and other diseases. However, nucleolar stress is commonly inferred from morphological changes or a limited set of functional assays, and quantitative approaches based on gene expression profiles remain lacking. Here, we integrate literature curation with multi-dataset screening to define a nucleolar stress gene signature and develop a nucleolar stress score (NuS) applicable to bulk transcriptomics, single-cell transcriptomics, proteomics, and spatial transcriptomics. Using this framework, we show in colorectal cancer models that oxaliplatin induces nucleolar stress, suppresses nascent rRNA synthesis, and activates p53 signaling, whereas these responses are attenuated in oxaliplatin-resistant cells. Combined with a ribosome biogenesis activity score (RiboSis), NuS captures related but distinct dimensions of nucleolar function and stratifies tumors into functional states associated with clinical outcomes. NuS-based analysis of perturbational transcriptomes further prioritizes compounds with putative nucleolar stress-inducing activity. Collectively, this study provides a quantitative framework for evaluating nucleolar stress and illustrates its applications in disease stratification and drug mechanism discovery.

Cell Nucleolus

SIGEL: a context-aware genomic representation learning framework for spatial genomics analysis.

Spatial transcriptomics (ST) integrates spatial information into genomics, yet methods for generating spatially-informed gene representations are limited and computationally intensive. We present SIGEL, a cost-effective framework that derives gene manifolds from ST data by exploiting spatial genomic context. The resulting SIGEL-generated gene representations (SGRs) are context-aware, biologically meaningful, and robust across samples, making them highly effective for key downstream tasks, including imputing missing genes, detecting spatial expression patterns, identifying disease-related genes and interactions, and improving spatial clustering. Extensive experiments across diverse ST datasets validate SIGEL's effectiveness and highlight its potential in advancing spatial genomics research.

Genomics

Multiancestry genome-wide association and multiomics analyses elucidate spatiocellular features of multiple sclerosis genetics.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by demyelination disseminated in space and time. Here we performed a genome-wide association study (GWAS) using 688 MS cases and 205,199 controls from the Japanese population and identified significant associations in the major histocompatibility complex region and a population-specific risk variant in 11q24. Through cross-population GWAS meta-analyses using a total of 29,374 cases and 1,843,563 controls from 4 ancestral populations, we identified 22 novel susceptibility loci. Integration of GWAS and single-cell and single-nucleus RNA sequencing of peripheral blood mononuclear cells and subcortical lesions from patients with MS revealed enrichment of genetic risk factors for MS in CD4+ T helper cell lineage and regulatory T cells, as well as in endothelial cells. Furthermore, spatial transcriptomics of subcortical lesions demonstrated spatial and temporal heterogeneity in associations with MS genetic risk. Our study demonstrates the value of investigation of spatiocellular features of disease genetics across diverse populations and omics modalities.

Humans

Multiomics analysis reveals that senescent CXCL16+ macrophages promote lung adenocarcinoma progression through TGF-β signalling.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer and remains a leading cause of cancer-related mortality worldwide. Although, immunotherapy has become a cornerstone of first-line treatment, only 20-30% of patients achieve a durable clinical benefit, largely because of the complexity and heterogeneity of the tumour immune microenvironment. Emerging evidence indicates that cellular senescence, particularly within immune cells, contributes to tumour progression by impairing antitumour immunity; however, its mechanistic role in LUAD remains incompletely understood. METHODS: We performed an integrative multiomics analysis incorporating genome-wide association studies (GWASs), bulk RNA sequencing, single-cell RNA sequencing, and spatial transcriptomics to characterize immune heterogeneity in LUAD. Cellular senescence was validated by performing staining for senescence-associated β-galactosidase and the canonical markers p16 and p21. SHAP analysis was applied to evaluate the contribution of CXCL16+ macrophages. Functional roles were assessed using coculture assays, in vitro and in vivo tumour models, orthotopic tumour implantation, and multiplex immunofluorescence staining of clinical specimens. RESULTS: A summary data-based on Mendelian randomization analysis integrating GWAS and TCGA data identified CXCL16 as a senescence-associated gene that is causally linked to the LUAD risk. Single-cell RNA sequencing revealed that CXCL16 is predominantly expressed in macrophages, and the pseudotime analysis together with β-galactosidase staining confirmed its association with macrophage senescence. Spatial transcriptomics and immunofluorescence staining showed the marked enrichment of CXCL16+ macrophages in LUAD tissues. The cell-cell communication analysis further revealed a strong association between the number of CXCL16+ macrophages and the activation of the TGF-β signalling pathway within the tumour microenvironment. Functionally, CXCL16+ macrophages promoted LUAD progression via TGF-β signalling, as validated in vitro and in subcutaneous and orthotopic tumour models. Molecular dynamics simulations additionally suggested that LUAD patients with high levels of CXCL16+ macrophage infiltration may exhibit increased sensitivity to bosutinib. CONCLUSIONS: CXCL16 promotes macrophage senescence, and senescent CXCL16+ macrophages drive LUAD progression through TGF-β signalling. These findings identify CXCL16+ macrophages as a biologically and therapeutically relevant immune cell population, highlighting a potential target for precision intervention in LUAD.

Humans

Pan-cancer analysis identifies APOC1 as a TAM-derived modulator of adaptive immune resistance and predictor of therapeutic response.

BACKGROUND: Apolipoprotein C1 (APOC1) has been implicated in several malignancies, yet its expression patterns, clinical significance, and immunomodulatory roles across cancer types remain poorly characterized. METHODS: We performed a comprehensive multi-omic analysis of APOC1 across 33 cancer types integrating transcriptomic, proteomic, genomic, epigenomic, and pharmacogenomic data from TCGA, GTEx, CPTAC, and multiple independent external cohorts. Immune infiltration was assessed using seven complementary algorithms. Spatial transcriptomics and single-cell RNA sequencing were employed to determine the cellular source of APOC1 expression. RESULTS: APOC1 upregulation in most cancers was associated with cancer type-specific prognosis. After adjustment for clinical covariates and macrophage infiltration, high APOC1 remained an independent adverse factor in KIRC, LGG, and STAD. APOC1 expression positively correlated with genomic instability hallmarks, including homologous recombination deficiency and aneuploidy, with these associations largely independent of immune infiltration; in contrast, associations with tumor mutational burden were substantially confounded by macrophage abundance. Immune infiltration analysis revealed a pattern consistent with adaptive immune resistance: APOC1 correlated positively with immune-activating signatures (STAT1, MHC-II, TCR signaling) and immunosuppressive M2 macrophages and Tregs, yet negatively with anti-tumor effectors (activated NK cells, dendritic cells). Spatial transcriptomics and single-cell RNA sequencing identified tumor-associated macrophages (TAMs) as the primary cellular source of APOC1, with transcripts co-localizing with CD68 in tissue sections. APOC1 expression correlated with multiple immune checkpoint molecules and was elevated in responders to immune checkpoint blockade, consistent with an inflamed yet regulated tumor microenvironment. Pharmacogenomic analyses revealed that APOC1-high tumors display distinct drug response profiles, characterized by resistance to MAPK pathway inhibitors and potential sensitivity to the HDAC inhibitor Entinostat. CONCLUSION: This pan-cancer analysis establishes APOC1 as a context-dependent biomarker and a TAM-derived modulator of adaptive immune resistance, with prognostic and therapeutic implications across malignancies. APOC1-expressing TAMs represent a potential target for combination immunotherapy strategies.

APOC1

Spatially defined microenvironmental niches are associated with clinical outcome and tumor ecosystem diversity in head and neck cancer.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) exhibits substantial biological heterogeneity that is not fully explained by human papillomavirus (HPV) status. The spatial organization of tumor, immune, and stromal cell populations and its relationship to clinical outcome remain incompletely understood. METHODS: We performed single-cell spatial transcriptomic and proteomic profiling of 44 primary HNSCC tumors, generating a spatial atlas of 19,471,501 cells across whole-slide tissue sections. Spatial niches and ecosystem states were identified through integrated computational analyses and evaluated for associations with tumor programs, clinicopathologic features, and patient outcomes. FINDINGS: HPV-negative tumors were enriched for fibroblast-rich, immune-poor niches associated with epithelial-mesenchymal transition and hypometabolic tumor programs, whereas HPV-positive tumors displayed more diverse immune, stromal, and vascular niche combinations and were enriched for immunogenic ecosystem states. Approximately 20% of HPV-positive tumors exhibited fibroblast-rich ecosystem architectures resembling HPV-negative disease and were associated with less favorable outcomes than other HPV-positive tumors of similar stage. In patient-derived co-culture models, extracellular matrix-associated fibroblasts were associated with epithelial-mesenchymal transition (EMT)-like tumor states, CD8+ T cell dysfunction, and chemotherapy resistance-associated phenotypes. CONCLUSIONS: Spatial ecosystem architecture is associated with clinically relevant heterogeneity beyond conventional HPV-based classification. Fibroblast-rich, immune-poor ecosystem states characterize a high-risk subset of HPV-positive tumors and may provide a framework for improved biological classification and risk stratification in HNSCC. FUNDING: This work was supported by the National Institutes of Health (R01CA291607 and R21CA267527-01) and the Feldstein Medical Foundation.

Humans

Spatiotemporal mapping of tertiary lymphoid structure heterogeneity shapes immune niches and clinical outcomes in intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy with limited therapeutic options. The spatial architecture and functional diversity of tertiary lymphoid structures (TLSs) in iCCA remain unclear. Here, we present a multimodal spatial atlas of TLSs and identified intratumoral TLSs (iTLSs) as independent prognostic markers. Bulk proteomic profiling of 214 discovery and 155 validation cases identified a four-tier TLS-based tumor microenvironment classification system and supported development of a TLS-predictive random forest classifier. Imaging mass cytometry revealed that iTLS+ tumors harbor structured immune architectures, where M1-like tissue-resident macrophages (RTMs), dendritic cells, and CXCL13+ CD4+ T cells colocalize to form antigen-presenting neighborhoods (apc-CNs) spatially coupled to TLS core regions (TLScore-CNs). Single-cell spatial transcriptomics further resolved 61 TLSs into 14 spatial niches and defined a pseudotemporal maturation continuum: aggregated, activated, and postactivated. Intraniche communication, primarily mediated by ifnCAFs, iCAFs, and CXCL12+ macrophages, evolved dynamically with maturation. Single-nucleus RNA sequencing combined with Tangram-based spatial mapping revealed CXCL12+ macrophages and iCAFs forming a peripheral band in aggregated TLSs, whereas ifnCAFs infiltrated TLS interiors during activation. These findings define TLS heterogeneity and provide insights for stroma-directed immunotherapy.

Cholangiocarcinoma

Targeting USP22 reprograms the tumor microenvironment and sensitizes KRAS/p53-driven lung cancer to anti-PD-1 immunotherapy.

RATIONALE: Ubiquitin-specific peptidase 22 (USP22), a deubiquitinase and component of the "Death-from-Cancer" 11-gene signature, is overexpressed in multiple malignancies and linked to recurrence, therapy resistance, and poor prognosis. Its role in KRAS/p53-driven lung cancer and the response to immune checkpoint inhibitors (ICIs) remains poorly defined. Here, we investigated USP22 as a potential therapeutic target in KRAS/p53-driven lung cancer. METHODS: A conditional Usp22 knockout (Usp22-KO) was generated in the KRASG12D; p53-/- (KP) mouse model. Cancer progression was monitored by micro-computed tomography (micro-CT). Multiplex immunofluorescence (mIF), RNA sequencing, and spatial transcriptomics profiled cancer and tumor microenvironment (TME) changes. Responses to anti-PD-1/PD-L1 therapies were compared between KP and Usp22-KO KP (KPU-) lung cancers. RESULTS: USP22 was highly expressed in early-stage KRAS/p53-driven mouse lung cancers and strongly correlated with proliferation marker Ki67. Usp22 deletion suppressed cancer growth, prolonged survival, and promoted cancer differentiation. Spatial transcriptomics and mIF revealed reduced CD206+ M2 macrophages, myeloid-derived suppressor cells (MDSCs), TGF-β1, and angiogenesis, along with increased functional CD8+ T cells. Mechanistically, USP22 regulated gene expression and protein stability, reducing c-Myc, PD-L1, TGF-β1, and SPARC upon Usp22 loss. Compared with KP cancer, KPU- and SPARC-knockdown KP cancers showed reduced macrophage chemotaxis and impaired basal- and TGF-β1-induced M2 polarization of RAW264.7 cells, suggesting that TGF-β1 and SPARC downregulation partially contributes to decreased M2 macrophage infiltration in KPU- cancers. Notably, Usp22 loss enhanced the efficacy of anti-PD-L1 and anti-PD-1 therapies in orthotopic and subcutaneous KP lung cancer models, respectively. USP22 and SPARC expression were also strongly correlated in human lung cancers. CONCLUSIONS: USP22 promotes progression and immune evasion in KRAS/p53-driven lung cancer. Targeting USP22 reprograms the TME, suppresses oncogenic signaling, and sensitizes tumors to ICI, establishing USP22 as a promising therapeutic target.

Animals

Cardiomyocyte-Specific Plakophilin-2 Loss Is Sufficient to Induce Aging and Senescence of Nonmyocytes: Relevance to Arrhythmogenic Cardiomyopathy.

BACKGROUND: Pathogenic variants in PKP2 are the most common cause of familial arrhythmogenic right ventricular cardiomyopathy. This study tests whether plakophilin-2 (PKP2) deficiency only in cardiomyocytes is sufficient to provoke premature aging and proinflammatory senescence in nonmyocyte, cardiac resident cells. METHODS: We studied mice with cardiomyocyte-specific, tamoxifen-activated loss of PKP2 (cardiomyocyte-specific conditional knockout of plakophilin-2) using conventional and multiplex imaging, cytokine arrays, epigenetic clocks, spatial transcriptomics, expansion and structured illumination microscopy, and correlative data analysis. We examined nonmyocytes and cardiomyocytes for premature aging and senescence. RESULTS: We observed senescence-associated heterochromatin foci in nonmyocytes, predominantly in cells positive for α-smooth muscle actin staining. Cytokines in media of nonmyocyte cells were consistent with senescence-associated secretory phenotype. Epigenetic clocks identified premature aging. Multiplex immunohistochemistry showed nonmyocyte cells in niches, intermingled with cardiomyocytes. Spatial transcriptomics showed overrepresentation of senescence-associated secretory phenotype-related transcripts, predominantly in myocyte-rich areas of the left ventricle. Senescence-associated heterochromatin foci and increased epigenetic age were not found in cardiomyocytes from cardiomyocyte-specific conditional knockout of plakophilin-2 hearts, although we observed structural features associated with premature aging. Cross-reference analysis showed correlation between the cardiomyocyte-specific conditional knockout of plakophilin-2 cardiac proteome and that of mice 5 or 6 times their chronological age, as well as transcriptional signatures of neurodegenerative diseases. CONCLUSIONS: Loss of PKP2 expression only in adult cardiac myocytes is sufficient to induce proinflammatory senescence in nonmyocytes, and overall premature cardiac aging. This is the first study to intersect cellular senescence and premature aging with desmosomal arrhythmogenic cardiomyopathies. We speculate that cell-agnostic molecular signatures, biomarkers, and pharmacology of senescence and of neurodegenerative diseases may be relevant to diagnose or treat PKP2 arrhythmogenic right ventricular cardiomyopathy.

Animals

Transcriptomic landscape of microglia in mouse models of social dysfunction and oxytocin-mediated recovery.

Atypical sociability is a hallmark of neurodevelopmental disorders arising from genetic susceptibility and prenatal environmental perturbations that can affect diverse brain cell types. Using single-cell transcriptomics, we previously identified selective vulnerability of parvocellular oxytocin (OT) neurons in the paraventricular hypothalamus (PVH) following embryonic exposure to valproic acid (VPA), a teratogen that induces social deficits. Neonatal chemogenetic activation of OT neurons rescued these behavioral abnormalities and partially restored dysregulated gene expression. However, the effects of VPA exposure and OT neuron stimulation on non-neuronal PVH cells remained unclear. Here, we show that VPA induces transcriptional abnormalities in PVH microglia. Spatial transcriptomics revealed altered distributions of PVH microglial subtypes. Notably, neonatal OT neuron stimulation reversed a subset of VPA-induced microglial gene downregulation, while pharmacological manipulation of microglia normalized aberrant OT gene expression in putative parvocellular OT neurons. These findings support bidirectional OT neuron-microglia interactions that may underlie social dysfunction following embryonic VPA exposure.

autism spectrum disorder

Exploring the transcriptional crosstalk between adipose tissue and locoregional recurrence in breast cancer using independent component analysis.

Locoregional recurrence (LRR) poses a persistent clinical challenge in breast cancer, with emerging evidence implicating the tumor-associated adipose tissue in modulating recurrence risk. This study investigates shared transcriptional programs between adipose tissue and breast tumors and examines their association with disease-free survival (DFS), particularly in the context of reconstructive surgery where adipose tissue from different body compartments are commonly used. We analyzed bulk gene expression data from 5,691 breast tumors and 978 human adipose tissue samples from different body compartments using consensus-independent component analysis (c-ICA) to identify transcriptional components (TCs). Gene set enrichment analysis (GSEA) and copy number alteration profiling were used for biological annotation. Associations between TCs and DFS were evaluated through univariate Cox regression. Key findings were validated using spatial transcriptomic and single-cell RNA sequencing datasets. Among the 411 TCs identified, 332 showed biological enrichment, and 35 were significantly associated with DFS. Four DFS-associated TCs (TC257, TC350, TC371, TC400) were enriched for adipogenesis-related genes and exhibited heightened activity in high-grade, triple-negative tumors and in patients with elevated BMI. Notably, TC350 was highly active in adipose tissue from common reconstructive donor sites (abdomen, omentum, subcutis) but not in native breast adipose tissue. Spatial transcriptomic and single-cell analyses confirmed the increased activity of these adipogenesis-related TCs in tumor regions and adipose cells. TC350 included FABP4, a gene previously linked to poor prognosis in breast cancer and considered as a potential new therapeutic target. Adipose tissue-derived transcriptional programs influence breast cancer prognosis and this seems to differ by tissue origin. These findings generate a hypothesis that donor site selection for adipose tissue in reconstructive surgery may impact LRR risk through adipogenesis-associated mechanisms. Further research is warranted to elucidate the biological and clinical implications of adipose-tumor transcriptional interactions.

Humans

A Phase I and Biodistribution Study of Ifabotuzumab, a Humanized Agonistic EphA3-Targeted Antibody, in Patients with Recurrent Glioblastoma.

PURPOSE: To conduct a phase I and biodistribution study of the EphA3 antibody ifabotuzumab and zirconium-89-labeled ifabotuzumab (89Zr-ifabotuzumab) in patients with glioblastoma (GBM). PATIENTS AND METHODS: This multisite study was conducted in adults with recurrent GBM whose tumors were measurable according to Response Assessment in Neuro-Oncology (RANO) criteria and whose Eastern Cooperative Oncology Group performance status was 0 to 1. Patients underwent a biodistribution study with PET scans with 89Zr-ifabotuzumab, followed by three infusions of ifabotuzumab at either 3.5 or 5.25 mg/kg before undergoing a second study with 89Zr-ifabotuzumab PET scans. Resected patient diagnostic tumor samples were collected for multiplex immunofluorescence and spatial transcriptomics analyses. RESULTS: Twelve patients were recruited, of which six were treated with 3.5 mg/kg and six with 5.25 mg/kg of ifabotuzumab. 89Zr-ifabotuzumab and associated PET scanning were well tolerated, as was ifabotuzumab. There were no objective responses, but one patient had prolonged stable disease. In addition, two patients showed changes in peritumor edema that were suggestive of modulation of tumor vasculature. 89Zr-ifabotuzumab scans showed highly specific tumor uptake in all patients concordant with disease sites on MRI and PET imaging, without evidence of nonspecific binding. Spatial transcriptomics and immunofluorescence analyses of the patient's archival tissue specimens showed that EphA3 was expressed in the tumor microenvironment in all patients and tumor cells with different transcriptional states. CONCLUSIONS: Targeting EphA3 with ifabotuzumab in patients with GBM is safe and attractive, showing chronologic stable expression across both tumor compartments (particularly in cells with a mesenchymal phenotype) and nontumor compartments (particularly the vascular compartment) with evidence of target modulation.

Humans

RECQL correlates with immune infiltration and serves as a prognostic biomarker and therapeutic predictor in gastric cancer.

BACKGROUND: RecQ-like helicase (RECQL), a member of the RecQ-like DNA helicase family, plays a crucial role in maintaining genomic stability. However, its relevance in gastric cancer (GC) has not been fully investigated. This study aimed to explore the clinical significance, biological functions, and potential role of RECQL in the tumor immune microenvironment of GC through comprehensive bioinformatics analyses and in vitro experiments. METHODS: Weighted gene co-expression network analysis (WGCNA), differential expression analysis, and least absolute shrinkage and selection operator (LASSO) regression were performed using public datasets [The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD), GSE150290] to identify key genes associated with GC progression. Subsequently, key pathways were identified through functional enrichment analysis, while immune infiltration and spatial transcriptomic analyses were conducted to characterize RECQL expression and its association with the tumor immune microenvironment. Finally, the effects of RECQL knockdown on the biological function of GC cells were assessed through Cell Counting Kit-8 (CCK-8), colony formation, scratch, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays. RESULTS: RECQL was significantly upregulated in GC tissues and correlated with advanced clinical stage and poor prognosis. Gene set enrichment analysis (GSEA) revealed a strong association between high RECQL expression and DNA repair pathway. Immune infiltration analysis indicated significant enrichment of M2 macrophages in the high-RECQL group, along with upregulation of immune checkpoint molecules including PDCD1, CTLA4, and CD274. Spatial transcriptomics further demonstrated co-localization of RECQL with myeloid cell-enriched regions in tumor parenchymal areas. Furthermore, in vitro experimental results indicated that RECQL was highly expressed in GC cell lines, and its knockdown effectively inhibited the viability, proliferation, and migration capabilities of HGC-27 cells, while enhancing their apoptosis. CONCLUSIONS: RECQL serves as a promising biomarker and potential therapeutic target in GC.

DNA repair

EGFR-Mutant Non-Small Cell Lung Cancer With Small Cell Transformation: Clinicopathological Features, Treatment Landscape, and Biomarker Profiles.

INTRODUCTION: Transformed small-cell lung cancer (tSCLC) is a clinically important resistance mechanism to EGFR tyrosine kinase inhibitors in EGFR-mutant non-small cell lung cancer. This study characterizes clinical features, treatment outcomes, and biomarker profiles in patients with tSCLC. METHODS: Data from 45 patients with EGFR-mutant NSCLC who developed tSCLC between 2014 and 2023 were analyzed. Demographic characteristics, treatment histories, and delta-like ligand 3 (DLL3) and B7-H3 expression were collected. Objective response rate, progression-free survival (PFS), and posttransformation survival (PTS) were assessed. Spatial transcriptomic profiling was performed in selected cases. RESULTS: Most patients were women (60%) and never-smokers (75.6%). Exon 19 deletion was the predominant EGFR mutation (57.8%). Median PFS and PTS were 3.3 and 9.2 months, respectively. Etoposide plus platinum (EP) was the predominant first-line regimen (69.8%), with 23.2% of the patients receiving EP plus immune checkpoint or tyrosine kinase inhibitors. EP-based combination regimens yielded a numerically higher objective response rate and a significantly longer PFS than EP alone (7.5 versus 2.8 months, p = 0.002). PTS was longer with EP-based regimens than with other regimens (10.4 versus 6.4 months, p = 0.035). DLL3 and B7-H3 were expressed in 87.5% and 66.7% of tumors, respectively, without prognostic significance. Multivariable analysis identified brain metastasis and liver progression at transformation as adverse prognostic factors. Spatial transcriptomic analysis revealed neuroendocrine lineage reprogramming, stromal depletion, and immune exclusion. CONCLUSIONS: tSCLC remains an aggressive resistance phenotype with poor outcomes. EP-based combination strategies may provide clinical benefit, whereas frequent DLL3 expression supports further evaluation of targeted therapies.

Delta-like ligand 3

DPAS-Graph: adaptive spatial-feature relation learning for spatial RNA-to-protein prediction and virtual protein profiling.

Paired spatial multi-omics provides a supervised basis for learning RNA-protein correspondence in situ, but predicting protein abundance from spatial transcriptomic data alone remains challenging across tissue contexts and protein panels. Here, we present DPAS-Graph, an adaptive relation-learning framework for spatial RNA-to-protein prediction. Rather than directly merging spatial proximity and transcriptomic similarity as fixed graph priors, DPAS-Graph represents them as two relation channels on a shared edge support and updates their contributions during representation learning for protein prediction. Its Niche-Coupled Field Encoder combines layer-wise edge-relation modeling, intra-branch relation refinement, and cross-branch residual correction to learn spot representations for protein abundance prediction. In a leave-one-dataset-out benchmark across seven paired spatial multi-omics datasets, DPAS-Graph achieved lower aggregate prediction errors and improved spot-level agreement of protein expression profiles, with gains mainly reflected in error-based metrics and PCC-Spot. Spatial autocorrelation and protein-derived domain agreement analyses were further used to characterize the spatial behavior of the predicted protein maps. When applied to external RNA-only spatial sections, DPAS-Graph generated qualitatively interpretable marker-level virtual protein maps, illustrating its use as a complementary tool for protein-level interpretation of transcriptomics-only spatial data.

RNA

Spatiotemporal transcriptomic analysis during cold ischemic injury to the murine kidney reveals compartment-specific changes.

BACKGROUND: Kidney transplantation is the preferred treatment strategy for end-stage kidney disease. Deceased donor kidneys usually undergo cold storage until kidney transplantation, leading to cold ischemia injury that may contribute to poor graft outcomes. However, the molecular characterization of potential mechanisms of cold ischemia injury remains incomplete. RESULTS: To bridge this knowledge gap, we leverage 10x Visium spatial transcriptomic technology to perform full transcriptome profiling of murine kidneys subject to varying durations of cold ischemia typical in a deceased donor kidney transplant setting. We develop a computational workflow to identify and compare spatiotemporal transcriptomic changes that accompany the injury pathophysiology in a tissue compartment-specific manner. We identify proportional enrichment of oxidative phosphorylation (OXPHOS) genes with increasing duration of cold ischemia injury within the oxygen-lean inner medulla region, suggestive of atypical metabolic presentation. This is distinct in cold ischemia injury tissue compared to warm ischemia-reperfusion kidney injury tissue. Spatiotemporal trends are validated by qPCR and immunofluorescence in a larger cohort of mice. CONCLUSIONS: Altogether, our spatiotemporal transcriptomic analysis identifies coordinated molecular changes within metabolic pathways such as OXPHOS deep within the cold ischemic kidney, highlighting the need for increased attention to the inner medulla and potential opportunities for new insights beyond those available from superficial biopsy-focused tissue examination.

Animals

Spatial Omics in High-Grade Gliomas: Mapping Immune-Tumor Niches for Precision Therapy.

High-grade gliomas (HGGs), particularly glioblastoma (GBM), remain among the most lethal human cancers despite decades of molecular profiling and therapeutic innovation. A primary reason for treatment failure is that HGG biology is spatial: malignant cell states, immune suppression, metabolic stress, and therapeutic resistance are organized into distinct anatomical and functional niches. Spatial omics technologies now enable high-dimensional mapping of gene expression, protein signaling, immune architecture, and metabolic activity within intact tumor tissue. These approaches reveal how proneural and mesenchymal transcriptional states coexist yet localize to distinct regions, alongside hypoxic, invasive, and stem-enriched niches. Spatial analyses show that key clinical determinants, including O6-methylguanine-DNA methyltransferase (MGMT)-associated temozolomide resistance, radiotherapy tolerance in hypoxic regions, and immunotherapy failure driven by myeloid-dominated immune exclusion, are influenced not only by molecular programs but also by cellular location. Beyond biological insight, spatial omics is reshaping clinical paradigms by enabling region-specific patient stratification, early assessment of treatment response, and identification of therapy-resistant reservoirs that seed recurrence. Prior bulk and single-cell studies defined HGG cell states and pathways but often treated resistance as tumor-wide. This review presents a spatially explicit framework that synthesizes spatial transcriptomic and immune-profiling studies to identify tumor-immune niches and spatial bottlenecks that drive therapeutic failure and recurrence.

Humans