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PubMed2025

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Understanding the tumor immune microenvironment (TIME) is crucial towards personalized therapeutic strategies. OBJECTIVES: This study aims to systematically characterize the heterogeneity and complexity of the TIME in Lu-NECs by integrating proteomic, transcriptomic, and genomic data. METHODS: We performed comprehensive immune-proteomic profiling of 76 Lu-NECs across diverse histopathological subtypes to elucidate intra-tumoral TIME heterogeneity at the proteomic level. Validation was conducted in multiple independent cohorts, including 112 Lu-NECs using immunohistochemistry, 147 Lu-NECs, and 17 small cell lung carcinoma samples using transcriptomics. We integrated proteomic, transcriptomic, genomic, and clinical data to assess molecular, immunological, and clinical features, as well as therapeutic vulnerabilities across different immune subtypes. RESULTS: We delineated the immuno-proteomic landscape of Lu-NECs and identified two major immuno-proteomic clusters with distinct immunological, molecular, and clinical characteristics. IPC1 was characterized by high immune cell infiltration, while IPC2 exhibited sparse immune cell presence. Genomic analysis revealed distinct mutational patterns, with IPC1 showing a higher incidence of APOBEC-associated mutation signatures and IPC2 being enriched for mutations associated with defective DNA mismatch repair and tobacco-related mutagens. Functional analyses indicated that IPC1 was related to immune and oncogenic signaling activity, whereas IPC2 was associated with cancer stemness and proliferation-related features. Furthermore, IPC1 and IPC2 demonstrated histological subtype-specific clinical benefits from postoperative chemotherapy. Finally, we developed a machine learning model (iPROM) to predict Lu-NECs immune classification and improve risk stratification, which was validated across multiple independent cohorts. CONCLUSIONS: This study advances the understanding of the tumor immune microenvironment in Lu-NECs through multi-omics characterization and highlights potential personalized therapeutic vulnerabilities tailored to the specific immune landscapes of Lu-NECs.

Humans↗

PubMed2026

Evaluation of the clinical and mechanistic role of MCM2 expression in the prediction of meningioma recurrence after radiotherapy.

OBJECTIVE: Postoperative radiotherapy is an effective treatment for meningiomas; however, treatment response varies among patients. In addition, practical methods for predicting tumor recurrence after radiotherapy have not been well established. Minichromosome maintenance protein 2 (MCM2), a key regulator of DNA replication licensing, was recently implicated in highly proliferative molecular subtypes of meningioma. In this study, the authors evaluated whether MCM2 immunohistochemical expression predicts response to radiotherapy in patients with meningiomas. METHODS: The authors retrospectively analyzed the records of patients with WHO grade 1-3 meningiomas treated with resection followed by radiotherapy at a single institution between July 2003 and November 2023. The MCM2 labeling index was assessed immunohistochemically, and patients were stratified into MCM2-high and -low groups using a cutoff of 35%. Progression-free survival (PFS) was defined as the interval from the completion of radiation therapy to postoperative radiological tumor recurrence or regrowth. Patients who showed no progression were censored at their last follow-up. PFS was estimated using Kaplan-Meier analysis and subsequently evaluated with Cox proportional hazards models. To further investigate the biological mechanisms associated with MCM2 expression, comprehensive transcriptomic analyses, including gene set enrichment analysis, was performed to elucidate the molecular processes that occur within MCM2-high tumors. RESULTS: The study population included 15 men (42%) and 21 women (58%), with a mean age of 63 years. Ten tumors (28%) were classified as MCM2-high meningiomas and 26 (72%) as MCM2-low meningiomas. High MCM2 expression was significantly associated with WHO grades 2-3 histology and higher Ki-67 labeling indices. During a median follow-up of 2.52 years, tumor progression after radiotherapy occurred in 47% of the patients. High MCM2 expression (HR 8.34, p = 0.03) was significantly associated with shorter PFS and remained an independent predictor of recurrence after adjustment for WHO grade, tumor size, and Ki-67 labeling index. Transcriptomic analyses of MCM2-high tumors revealed upregulation of cell proliferation-related pathways, accompanied by increased signaling through the E2F8-CHEK1 axis associated with radiation resistance and suppression of the TNF-α signaling pathway implicated in radiosensitivity. CONCLUSIONS: In meningiomas, high MCM2 expression is associated with early recurrence following radiotherapy. The study findings suggest that this association is driven by diverse biological mechanisms related to cell cycle regulation and radioresistance. Immunohistochemical assessment of MCM2 expression may serve as a practical and accessible biomarker for risk stratification and may support the future development of individualized postoperative radiotherapy strategies.

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↗

PubMed2026

A weakly supervised deep learning-based recurrence prediction and risk stratification of lung adenocarcinoma from pathology whole-slide images.

BACKGROUND: Accurate prediction of postoperative recurrence in lung adenocarcinoma (LUAD) is essential for guiding clinical decision-making and improving patient outcomes. Although various predictive models have been developed, most rely on complex genomic analyses and high-dimensional clinical data. The complexity of these approaches substantially limits their feasibility for routine clinical use. To address this clinical challenge, this study aims to predict postoperative recurrence using routinely available hematoxylin and eosin (H&E)-stained images and characterize the associated biological features. METHODS: A total of 329 patients who underwent curative resection at the First Affiliated Hospital of Wenzhou Medical University (FHWMU) were retrospectively enrolled and randomly assigned to training and internal validation cohorts in a 7:3 ratio. An independent external validation cohort comprising 70 patients from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) was included. Three patch-level feature extractors (Inception_V3, ResNet18, and DenseNet121) were evaluated within a weakly supervised multiple-instance learning (MIL) framework incorporating automated region-of-interest (ROI) detection on segmented whole-slide images (WSIs). Model performance was assessed using the area under the receiver operating characteristic curve (AUC), Kaplan-Meier (KM) survival analysis, and multivariable Cox proportional hazards regression. Transcriptomic profiling and gene set enrichment analysis (GSEA) were conducted to investigate biological differences between risk groups. RESULTS: The model achieved AUCs of 0.923 in the training cohort, 0.891 in the internal validation cohort, and 0.847 in the external validation cohort. The model effectively stratified patients into high- and low-risk groups with significantly different recurrence-free survival (RFS) across all cohorts (all P < 0.001) and retained prognostic value within AJCC stages I-III. Transcriptomic analyses revealed consistent enrichment of cell cycle-related pathways and neutrophil extracellular trap (NET) formation in high-risk patients across both institutional and CPTAC cohorts, aligning with distinct biological profiles of the model-derived risk stratification. CONCLUSIONS: This weakly supervised deep learning framework enables accurate and externally validated prediction of postoperative recurrence in LUAD using routinely available histopathological images, and integration of histopathological features with molecular analyses enhances biological interpretability. This work provides a clinically accessible and cost-effective tool for postoperative risk assessment in LUAD patients.

Humans↗

PubMed2025

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

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

BMD↗

PubMed2026

Elevated intron retention implicates neuroinflammation in brains of individuals with alcohol use disorder.

Intron retention, a form of alternative RNA splicing, can occur as part of normal gene regulation or result from disruption of the splicing machinery. Retained introns can potentially form double-stranded RNA, activating innate immune sensors and inflammation. This mechanism has been implicated in cancer but has not been studied in neuropsychiatric diseases like alcohol use disorder. We systematically analysed transcriptome-wide intron retention events in post-mortem brain tissue from 142 individuals (66 with alcohol use disorder and 76 controls), encompassing 320 region-specific samples from the superior frontal cortex, nucleus accumbens, central nucleus and basolateral amygdala. Analyses were adjusted for demographic, technical and biological covariates. Validation was performed in alcohol-preferring (P) rats using long-read sequencing. In complementary experiments, immunofluorescent staining was used to detect double-stranded RNA in rat brain tissue, while single-cell RNA-sequencing was performed to test activation of double-stranded RNA-sensing pathways in human brains. Brains from individuals with alcohol use disorder showed significantly higher total intron retention compared with controls, independent of age, with females showing greater increases than males. A total of 368 introns were positively associated with alcohol use disorder, and these introns were significantly longer and had weaker splice acceptor sites compared with non-associated introns. Genes harbouring these intron retention events were enriched in Purkinje neurons, visual cortex neurons and oligodendrocytes. Computational predictions indicated these long introns could form duplex RNA structures. Increased double-stranded RNA was confirmed experimentally in multiple brain regions of alcohol-consuming rats, where it co-localized primarily with neuronal nuclei and dendrites. In individuals with alcohol use disorder, we found that multiple pathways including double-stranded RNA responses, neuroinflammation, interferon and NF-κB signalling, adaptive immunity and apoptosis were activated. In addition, NeuN-positive neuronal counts significantly decreased in both the prefrontal and visual cortices. Furthermore, single-cell analysis demonstrated upregulation of TICAM1, the target of double-stranded RNA sensor TLR3, in oligodendrocytes, as well as widespread activation of downstream inflammatory pathways across glial and neuronal cell types. These findings provide the first evidence that chronic alcohol consumption promotes an overall increase of intron retention in the brain and is associated with the presence of double-stranded RNA. Furthermore, the double-stranded RNA may contribute to neuronal loss and brain pathology by activating a neuroinflammatory response.

alcohol use disorder↗

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↗

PubMed2026

COVID-19 multi-omics reveal organ-specific responses and biomarkers.

OBJECTIVE: Post-COVID-19 syndrome is characterised by persistent immune dysfunction and multi-organ sequelae. This study aimed to characterise the systemic blood molecular landscape induced by SARS-CoV-2 infection and identify prognostic markers linked to skeletal muscle mass loss, a key driver of poor outcomes. METHODS: We enrolled 30 healthy controls and 307 COVID-19 patients, collecting 422 plasma samples for integrated proteomic and metabolomic profiling to investigate organ-specific molecular alterations in COVID-19. RESULTS: We comprehensively mapped the molecular landscape of COVID-19, encompassing immune, tissue-specific, and metabolic perturbations, and delineated their interactions. Focusing on organ-damage-related molecular patterns associated with disease progression and mortality, we found that skeletal muscle mass loss contributed to poor clinical outcomes of COVID-19 (p < 0.0001). Dysregulated arginine metabolism emerged as a key metabolic signature in fatal COVID-19 cases, with GLUL, GOT1, and citrulline showing significant correlation with skeletal muscle mass loss. Longitudinal analyses further revealed that reduced citrulline levels underlie the poor outcome of COVID-19 patients with muscle mass loss. These findings were robustly supported through multiple approaches: Mendelian randomization confirmed causal relationships between citrulline depletion, sarcopenia/fat-free mass loss, and COVID-19 mortality (p < 0.05), transcriptomic analyses of SARS-CoV-2-infected golden hamsters (GSE231910) provided additional support in enrichment of arginine biosynthesis (FDR < 0.05), and in vitro experiments further demonstrated that citrulline depletion promotes pro-inflammatory M1 macrophage polarisation — a key immunological feature of critical COVID-19. Leveraging these insights, we developed a skeletal muscle loss-specific prognostic prediction model for COVID-19 using GLUL, GOT1, and citrulline. This model effectively stratified patients into high- and low-risk groups (p = 0.035). CONCLUSION: Our study advances the understanding of COVID-19-induced organ pathophysiology and provides a foundation for developing targeted therapeutic strategies for post-COVID sequelae.

COVID-19↗

PubMed2006

Tumor transcriptome reveals the predictive and prognostic impact of lysosomal protease inhibitors in non-small-cell lung cancer.

PURPOSE: Insight into clinical response to platinum-based chemotherapy (PBC) in non-small-cell lung cancer (NSCLC). METHODS: Matched tumor and nontumor lung tissues from PBC-treated NSCLC patients (four nonresponders and four responders) and tumor tissue from an independent test set (four nonresponders and four responders), were profiled using microarrays. Lysosomal protease inhibitors SerpinB3 and cystatin C were highly correlated with clinical response and were further evaluated by immunohistochemistry in PBC-treated patients (36 prechemotherapy and 13 postchemotherapy). Investigation of the pathogenic and prognostic significance of SerpinB3 was performed in 251 primary tumors, with 64 regional lymph node pairs, from chemotherapy-naïve NSCLC patients using immunohistochemistry. RESULTS: Bioinformatic analyses of gene expression in the training set identified a gene set (n = 17) that separated all patients in the training and test sets (n = 16) according to response in hierarchical clustering. Transcriptome profiling revealed that SerpinB3 mRNA was highly correlated with degree of response (r = -0.978; P < .0001) and was a clear outlier (nonresponders:responders > 50-fold). SerpinB3 protein expression was correlated with clinical response in PBC-treated NSCLC patients (P = .045). Expression of SerpinB3 and cystatin C, relative to the target, protease cathepsin B, was independently predictive of response (odds ratio, 17.8; 95% CI, 2.0 to 162.4; P = .01), with an accuracy of 72%. High SerpinB3 expression levels, invariably associated with chemoresistance, had contrasting prognostic impact in untreated squamous cell carcinomas (hazard ratio [HR], 0.43; 95% CI, 0.18 to 0.93) or adenocarcinomas (HR, 2.09; 95% CI, 1.03 to 4.72). CONCLUSION: This provides the first comprehensive molecular characterization of clinical responsiveness to PBC in NSCLC and reveals the predictive and prognostic impact of two lysosomal protease inhibitors, potentially representing novel targets for NSCLC therapeutics.

Aged↗

PubMed2025

Prognostic and immunological implications of sialylation-associated gene signatures in hepatocellular carcinoma.

OBJECTIVE: The absence of effective biomarkers continues to limit early diagnostic accuracy and prognostic evaluation in patients with hepatocellular carcinoma (HCC). Aberrant sialylation (SI) has been demonstrated to contribute to therapeutic resistance and tumor progression. The aim of this investigation was to identify a sialylation-related gene (SRG) signature, evaluate its prognostic significance, and investigate associated immunological characteristics in HCC. METHODS: Transcriptomic profiles and corresponding clinical data for patients with HCC were obtained from UCSC Xena, the International Cancer Genome Consortium (ICGC), and the Molecular Signatures Database (MsigDB). Differential expression analysis, Cox regression analysis modeling, and least absolute shrinkage and selection operator (LASSO) regression analysis were applied to identify independent prognostic markers and develop predictive models. The tumor immune microenvironment and its relationship with the identified SRGs were assessed by evaluating immune infiltration patterns. A gene co-expression network for the prognostic SRGs was constructed using GeneMANIA to identify potentially targetable signaling pathways. RESULTS: Four SRGs (ST6GALNAC4, B4GALT5, B4GALNT1, and NEU1) were significantly associated with the prognosis of patients with HCC. Prognostic models constructed using these genes demonstrated strong predictive performance. Notable differences were observed in immune cell populations and immune checkpoint expression between the high-risk and low-risk groups. Additionally, the half-maximal inhibitory concentration values for 101 therapeutic compounds varied between these groups. Lipopolysaccharide and sphingolipid metabolism were identified as key biological processes linked to tumor progression and modulation of the immune microenvironment. CONCLUSION: The four identified SRGs were significantly associated with clinical outcomes and immunological features in HCC. These findings provide a foundation for advancing early diagnostic strategies, refining prognostic assessments, and guiding personalized therapeutic approaches for patients with HCC.

Humans↗

PubMed2026

Immature Neutrophil Programs Associate With Burn Mortality and Extend Across Critical Illnesses.

Severe burns provoke a systemic "genomic storm," yet cell states associated with divergent outcomes remain unclear. We profiled blood cells by single-cell RNA-Sequencing (73 014 cells) from adult patients with burn injuries within postburn day 17 (n = 4) and healthy donors (n = 5), integrated data with bulk signatures of burn size, inhalation injury, and mortality, and evaluated clinical associations in the American Burn Association National Burn Repository. Burn was associated with emergency hematopoiesis marked by expansion of hematopoietic stem/progenitor-like cells, immature neutrophils, and plasmablast/plasma cell states, alongside depletion of naïve CD4+/CD8+ T cells and dendritic cells. Larger burns (>20% TBSA) showed enrichment of humoral transcriptional programs, including plasmablast/plasma cell activation and suppression of cytotoxic CD8+ T-cell states. In multivariable models, inhalation injury was a stronger predictor of death (adjusted odds ratio [OR] 1.9) than burn size (adjusted OR 1.1) and shared greater overlap with the most perturbed single cells in non-survivors; 55% of co-perturbed cells were neutrophils, implicating granulocyte dysregulation as a common lethal axis. We identified a neutrophil-specific 5-gene panel (OLFM4, RETN, LCN2, ARG1, and BTNL3) that discriminated survivors vs non-survivors after burns (area under the curve [AUC] > 0.9) and generalized to trauma (n = 158; AUC 0.81) and intensive care unit COVID-19 (n = 103; AUC 0.75), providing information orthogonal to conventional biomarkers and severity scores. Cytomorphology corroborated transcriptomic immaturity, with ~2-fold higher band neutrophils and larger neutrophil size in a fatal case. Computational drug-reversal analysis highlighted galectin-1 inhibition as a candidate modulator of mortality-associated neutrophil programs. Together, our findings suggest that immature neutrophils represent a shared immune feature across severe burns and other forms of critical illness.

Humans↗

PubMed2005

The lacrimal gland transcriptome is an unusually rich source of rare and poorly characterized gene transcripts.

PURPOSE: To sequence and comprehensively analyze human and mouse lacrimal gland transcriptomes as part of the NEIBank project. METHODS: cDNA libraries generated from normal human and mouse lacrimal glands were sequenced and analyzed by PHRED, RepeatMasker, BLAST, and GRIST. Human "lacrimal-preferred genes" and putative gene regulatory elements were respectively identified in UniGene and ConSite, and gene clustering was analyzed by chromosomal mapping. "Hypothetical proteins," identified by keyword search, were verified by genomic alignment and queried in the Conserved Domain database and GEO Profiles. RESULTS: The top six transcripts in human and mouse differed, revealing a previously unappreciated molecular divergence. The human transcriptome is enriched with transcripts from 29 lacrimal-preferred genes and a content of poorly characterized hypothetical proteins, proportionally greater than in all other tissues. Only 45% of lacrimal preferred, but 71% of hypotheticals, have mouse orthologs. Many of the latter display apparently altered cancer expression in the CGAP SAGE library collection-often in keeping with predicted WD40, protein kinase, Src homology 2 and 3, RhoGEF, and pleckstrin homology domains involved in cell signaling. At the genomic level, lacrimal-expressed genes show some evidence of clustering, particularly on human chromosomes 9 and 12. Binding sites for TFAP2A, FOXC1, and other transcription factors are predicted. CONCLUSIONS: Interspecies divergence cautions against use of mouse models of human dry eye syndromes. Lacrimal preferred and hypothetical proteins, gene clustering, and putative gene regulatory elements together provide new clues for a molecular understanding of lacrimal gland function and mechanisms of coordinated tissue-specific transcriptional regulation.

Aged↗

PubMed2026

An integrated single-cell and spatial transcriptomic atlas of thyroid cancer progression identifies prognostic fibroblast subpopulations.

Although well-differentiated thyroid carcinoma (WDTC) is characterized by a robust treatment response, aggressive subtypes, such as anaplastic thyroid carcinoma (ATC), remain highly lethal. To understand thyroid cancer evolution in both children and adults, we analyzed single-cell transcriptomes of 423,733 cells from 81 samples and spatially resolved key tumor and microenvironment populations across 28 tumors with spatial transcriptomics, including rare and unique composite WDTC/ATC tumors and pediatric diffuse sclerosing thyroid carcinomas. Additionally, we identified gene signatures of stromal cell populations in 5 large thyroid cancer bulk RNA-sequencing cohorts. Through this multi-institutional effort, we defined a population of POSTN+ myofibroblast cancer-associated fibroblasts (myCAFs) that are intimately associated with invasive tumor cells and correlate with poor prognosis, lymph node metastasis, and disease progression in thyroid carcinoma. We also revealed a population of inflammatory CAFs that are distant to tumor cells and are found in the inflammatory stromal microenvironment of autoimmune thyroiditis. Together, our study provides spatial profiling of thyroid cancer evolution in samples with mixed WDTC/ATC histopathology and identifies a prognostic myCAF subtype with potential clinical utility in predicting aggressive disease in both children and adults.

Humans↗

PubMed2025

Comprehensive proteomic and pathological profiling identifies PRAS40 as a novel biomarker and mediator of primary immune checkpoint blockade resistance in non-small cell lung cancer.

BACKGROUND: Immune checkpoint blockade (ICB) has revolutionized the treatment landscape of non-small cell lung cancer (NSCLC), yet primary resistance remains a significant clinical challenge. Recent evidence implicates PRAS40 (AKT1S1) in regulating cellular survival and immune responses, but its role in immunotherapy resistance is not fully understood. METHODS: Transcriptomic data from TCGA and GTEx cohorts were analyzed to assess PRAS40 expression. Prognostic value was evaluated using Cox regression. Immune microenvironment features were characterized with CIBERSORT and TIMER. Predictive efficacy for ICB response was examined using TIDE and IPS. Plasma PRAS40 levels in 66 NSCLC patients receiving ICB were quantified by proximity extension assay (PEA), and multiplex immunohistochemistry assessed associations among PRAS40, PD-L1, and CD8+ T cells in tumor tissues. RESULTS: High PRAS40 expression was associated with poor prognosis, reduced CD8+ T cell infiltration, and downregulation of immune checkpoint genes. Elevated circulating PRAS40 predicted primary ICB resistance and shorter progression-free survival, independent of PD-L1 or CD8+ T cell status. CONCLUSION: PRAS40 is strongly associated with primary ICB resistance in NSCLC and may serve as a novel predictive biomarker. These findings support its potential to guide personalized immunotherapy in lung cancer.

Humans↗

PubMed2026

Urinary clusterin as a biomarker of human kidney disease progression and response to the endothelin receptor antagonist atrasentan: An exploratory analysis from the SONAR trial.

The endothelin receptor antagonist atrasentan improved kidney outcomes in the SONAR trial for type 2 diabetes and chronic kidney disease (NCT01858532), though individual responses varied. To identify molecular biomarkers of atrasentan response and outcome, we conducted a nested case-control proteomics study (N = 180) within the SONAR trial population and identified urinary clusterin (uCLU) as the top candidate. Transcriptomic analyses of human kidney biopsies at tissue and single cell level from independent cohorts revealed higher CLU mRNA levels associated with worse kidney function and outcomes. An endothelin signaling activation score derived from pathway genes was reduced by atrasentan in mice with diabetic kidney disease. In the SONAR trial (N = 3,060) population, higher uCLU predicted worse outcomes, while atrasentan reduced uCLU by 42.6% over six weeks. Early uCLU changes independently predict improved kidney outcomes. In summary, uCLU is associated with kidney disease progression and response to atrasentan treatment, supporting its potential as a pharmacodynamic biomarker to target therapy.

Humans↗

PubMed2026

POU2F3 expression in lung squamous cell carcinoma: transcriptomic and immunohistochemical profiling with prognosis.

BACKGROUND: Lung squamous cell carcinoma (LUSC) lacks well-defined molecular targets. This study investigated the clinical and biological relevance of POU class 2 homeobox 3 (POU2F3), a tuft cell-associated transcription factor, in LUSC. METHODS: RNA sequencing data of patients with LUSC from The Cancer Genome Atlas (TCGA cohort, n = 190) was analysed and compared to a cohort of surgically resected cases analyzed via immunohistochemistry (IHC cohort, n = 137). Prognostic impact was assessed via survival analyses. Transcriptomic features, pathway enrichment, and immune profiles were evaluated via differentially expressed gene analysis, Gene Set Enrichment Analysis, and CIBERSORTx. RESULTS: High POU2F3 expression independently predicted poor overall survival in the TCGA cohort (HR = 2.06, 95% CI: 1.04-4.08, P = 0.039). In contrast, POU2F3 expression was not prognostic in the IHC cohort (P = 0.995). Morphologically, POU2F3-positive tumours were enriched for non-keratinizing and poorly differentiated subtypes. Transcriptomic analysis showed suppression of proliferation and immune-related pathways (FDR < 0.001), with suggestive enrichment of the TGF-β (FDR = 0.143) and p53 (FDR = 0.229) signaling pathways. On immune deconvolution, POU2F3-high tumours showed a nominal increase in activated dendritic cells, which did not withstand multiple testing correction. POU2F3 protein was detected in 12.4% of tumours and was significantly associated with p53 or RB1 abnormalities (single or double) (P = 0.028). CONCLUSIONS: POU2F3 marks a transcriptionally distinct, early-stage subtype of LUSC with keratinization-related features. Its prognostic relevance appears context-dependent and requires prospective validation in uniformly treated cohorts.

Humans↗

PubMed2026

Integrated Bulk and Single-Cell RNA-Seq Analysis Reveals Transcriptional Activation of PTGS2 by FOS in Progression From T2DM to T2DM-Associated NAFLD.

Type 2 diabetes mellitus (T2DM) and nonalcoholic fatty liver disease (NAFLD) frequently coexist, exacerbating disease burden. However, the molecular mechanisms underlying the progression from T2DM to T2DM-associated NAFLD remain unclear. This study investigated the regulatory function of FOS-mediated PTGS2 activation in this transition. We integrated bulk RNA-seq data from GEO, single-cell transcriptomic data and transcriptomes from patients with T2DM-associated NAFLD. Differentially expressed genes were identified using the limma package, and T2DM-related gene modules were defined by weighted gene co-expression network analysis. LASSO regression and random forest identified 14 candidate genes, with PTGS2 and FOS prioritised. Single-cell analysis showed increased FOS and PTGS2 expression in monocytes, CD8+ T cells and Kupffer cells. Transcription factor prediction and dual-luciferase assays confirmed that FOS directly binds the PTGS2 promoter and drives its transcription. In vitro, FOS silencing decreased PTGS2 expression, cytokine secretion and apoptosis under high-glucose and free fatty acid conditions, whereas PTGS2 overexpression exacerbated inflammation and apoptosis independently of FOS expression. These findings demonstrate that FOS transcriptionally activates PTGS2, contributing to hepatic inflammation and apoptosis during the progression from T2DM to NAFLD. PTGS2 may serve as a promising biomarker and therapeutic target for T2DM-associated NAFLD.

Single-Cell Gene Expression Analysis↗

PubMed2026

Evolution of tumor subclones and T-cell dynamics underlie variable ibrutinib responses in Waldenström macroglobulinemia.

To elucidate the molecular basis underlying differential responses and resistance to ibrutinib in Waldenström macroglobulinemia (WM), we conducted a prospective phase 2 trial of ibrutinib monotherapy in treatment-naïve patients. A total of 74 sequential bone marrow (BM) aspirates from 17 patients, collected from baseline through 48 treatment cycles, were profiled using single-cell multiomics. BM cells were segregated primarily into B-cell/plasma cell and T-cell compartments. Longitudinal clonal tracking of malignant B cells/plasma cells identified 3 distinct evolutionary patterns: evolution (early clone contraction with late clone expansion and increasing genomic complexity), devolution (early clone expansion with late clone contraction and genomic simplification), and no evolution (stable clonal architecture). The evolution pattern was strongly associated with disease progression, whereas devolution correlated with durable clinical response. Transcriptomic profiling of resistant clones enabled development and validation of the Waldenström ibrutinib prediction (WIP) score, which predicted treatment response at baseline. Within the WIP signature, LYN emerged as a key regulator; LYN knockdown or inhibition significantly increased WM cell sensitivity to ibrutinib, suggesting a rational combination strategy. In parallel, GZMB+ CD8+ effector-memory T cells expanded after treatment in patients with progressive disease and coexisted with tumor evolution. These cells exhibited persistently impaired cytotoxic programs (eg, GNLY), a dedifferentiated memory-like state, elevated PDCD1 expression, and reduced T-cell receptor diversity. Together, this study provides, to our knowledge, the first single-cell framework of tumor clonal evolution and T-cell dysfunction under ibrutinib in WM, introduces the WIP score as a predictive biomarker for treatment response, and identifies actionable tumor-intrinsic and immune mechanisms driving resistance. This trial was registered at www.ClinicalTrials.gov as NCT02604511.

Aged↗