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Expression of an estrogen-regulated variant transcript of the peroxisomal branched chain fatty acid oxidase ACOX2 in breast carcinomas.
BACKGROUND: Alternate transcripts from a single gene locus greatly enhance the combinatorial flexibility of the human transcriptome. Different patterns of exon usage have been observed when comparing normal tissue to cancers, suggesting that variant transcripts may play a role in the tumor phenotype. METHODS: Ribonucleic acid-sequencing (RNA-seq) data from breast cancer samples was used to identify an intronic start variant transcript of Acyl-CoA oxidase 2, ACOX2 (ACOX2-i9). Difference in expression between Estrogen Receptor (ER) positive and ER negative patients was assessed by the Wilcoxon rank sum test, and the findings validated in The Cancer Genome Atlas (TCGA) breast cancer dataset (BRCA). ACOX2-i9 expression was also assessed in cell lines using both quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) and Western blot analysis. Knock down by short hairpin RNA (shRNA) and colony formation assays were used to determine whether ACOX2-i9 expression would influence cellular fitness. The effect of ACOX2-i9 expression on patient survival was assessed by the Kaplan-Meier survival function, and association to clinical parameters was analyzed using a Fisher exact test. RESULTS: The expression and translation of ACOX2-i9 into a 25 kDa protein was demonstrated in HepG2 cells as well as in several breast cancer cell lines. shRNA knock down of the ACOX2-i9 variant resulted in decreased cell viability of T47D and MDA-MB 436 cells. Moreover, expression of ACOX2-i9 was shown to be estrogen regulated, being induced by propyl pyrazoletriol and inhibited by tamoxifen and fulvestrant in ER+ T47D and Mcf-7 cells, but not in the ER- MDA-MB 436 cell line. This variant transcript showed expression predominantly in ER-positive breast tumors as assessed in our initial set of 53 breast cancers and further validated in 87 tumor/normal pairs from the TCGA breast cancer dataset, and expression was associated with better outcome in ER positive patients. CONCLUSIONS: ACOX2-i9 is specifically enriched in ER+ breast cancers where expression of the variant is associated with improved outcome. These data identify variant ACOX2 as a potential novel therapeutic biomarker in ER+ breast tumors.
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A comprehensive meta-analysis of tissue resident memory T cells and their roles in shaping immune microenvironment and patient prognosis in non-small cell lung cancer.
Tissue-resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, the impact of TRM-related immunosurveillance on the tumor-immune microenvironment (TIME) and tumor progression across various non-small-cell lung cancer (NSCLC) patient populations is yet to be elucidated. Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we inferred the abundance of TRM in NSCLC. We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in the TIME. In addition, TRM signatures are strongly associated with immune checkpoint and stimulatory genes and the prognosis of NSCLC patients. A TRM-based machine learning model to predict patient survival was validated and an 18-gene risk score was further developed to effectively stratify patients into low-risk and high-risk categories, wherein patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the Cancer Genome Atlas Program (TCGA) dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell immunity, nature killer cell activation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. However, the TRM signature revealed low TRM abundance and a lack of prognostic association among lung squamous cell carcinoma patients in contrast to adenocarcinoma, indicating that the two NSCLC subtypes are driven by distinct TIMEs. Altogether, this study provides valuable insights into the complex interactions between TRM and TIME and their impact on NSCLC patient prognosis. The development of a simplified 18-gene risk score provides a practical prognostic marker for risk stratification.
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Single-Nucleus Transcriptomic Atlas of Human Pericoronary Epicardial Adipose Tissue in Normal and Pathological Conditions.
BACKGROUND: Pericoronary epicardial adipose tissue (EAT) is a unique visceral fat depot that surrounds the adventitia of the coronary arteries without any anatomic barrier. Clinical studies have demonstrated the association between EAT volume and increased risks for coronary artery disease (CAD). However, the cellular and molecular mechanisms underlying the association remain elusive. METHODS: We performed single-nucleus RNA sequencing on pericoronary EAT samples collected from 3 groups of subjects: patients undergoing coronary bypass surgery for severe CAD (n=8), patients with CAD with concomitant type 2 diabetes (n=8), and patients with valvular diseases but without concomitant CAD and type 2 diabetes as the control group (n=8). Comparative analyses were performed among groups, including cellular compositional analysis, cell type-resolved transcriptomic changes, gene coexpression network analysis, and intercellular communication analysis. Immunofluorescence staining was performed to confirm the presence of CAD-associated subclusters. RESULTS: Unsupervised clustering of 73 386 nuclei identified 15 clusters, encompassing all known cell types in the adipose tissue. Distinct subpopulations were identified within primary cell types, including adipocytes, adipose stem and progenitor cells, and macrophages. CD83high macrophages and FOSBhigh adipocytes were significantly expanded in CAD. In comparison to normal controls, both disease groups exhibited dysregulated pathways and altered secretome in the primary cell types. Nevertheless, minimal differences were noted between the disease groups in terms of cellular composition and transcriptome. In addition, our data highlight a potential interplay between dysregulated circadian clock and altered physiological functions in adipocytes of pericoronary EAT. ANXA1 (annexin A1) and SEMA3B (semaphorin 3B) were identified as important adipokines potentially involved in functional changes of pericoronary EAT and CAD pathogenesis. CONCLUSIONS: We built a complete single-nucleus transcriptomic atlas of human pericoronary EAT in normal and diseased conditions of CAD. Our study lays the foundation for developing novel therapeutic strategies for treating CAD by targeting and modifying pericoronary EAT functions.
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Dual inhibition of EGR1/STAT3 transcriptional hubs suppresses macrophage-driven liver fibrosis: A multi-omics-guided drug repurposing strategy.
Liver fibrosis (LF), driven by dysregulated macrophage polarization and extracellular matrix remodeling, represents a critical and unmet therapeutic challenge in chronic liver diseases. Despite decades of research, the lack of agents targeting core transcriptional regulators of fibrogenesis underscores the urgent need for mechanism-based interventions. An integrative analysis of three single-cell transcriptomic atlases identified Early Growth Response 1 (EGR1) and Signal Transducer and Activator of Transcription 3 (STAT3) as central transcriptional regulators that orchestrate pro-fibrotic macrophage polarization and the downstream activation of fibrogenic effectors such as Arginase 1 (Arg1), Fibronectin 1 (Fn1), Osteopontin (Spp1), and Thrombospondin 1 (Thbs1). By leveraging computer-aided drug design (CADD), multi-precision virtual screening of both the FDA-approved drug library and the TCMSP drug database identified Cidofovir and Pioglitazone as novel inhibitors selectively targeting EGR1 and STAT3, respectively. Molecular dynamics simulations confirmed stable binding interactions at their DNA-binding domains. Functional validation in macrophages showed that Cidofovir suppressed EGR1 signaling and downstream fibrotic gene expression, while Pioglitazone inhibited STAT3 activity and M2 macrophage polarization. In a murine LF model, dual therapy synergistically reduced collagen deposition and hepatic stellate cell activation, exhibiting superior efficacy compared to monotherapy. This study pioneers the therapeutic repositioning of Cidofovir and Pioglitazone as dual-target transcriptional inhibitors, disrupting the EGR1/STAT3-Fn1/Spp1/Thbs1 axis to attenuate fibrotic niche formation. Our "multi-omics to bedside" framework, empowered by computer-aided drug design, not only deciphers macrophage-centric fibrogenic networks but also delivers clinically translatable candidates, bridging the gap between computational drug discovery and precision antifibrotic therapy.
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Clonal expansion of resident memory T cells in peripheral blood of patients with non-small cell lung cancer during immune checkpoint inhibitor treatment.
BACKGROUND: Immune checkpoint inhibitors (ICIs) are an essential treatment for non-small cell lung cancer (NSCLC). Currently, the tumor-related intrinsic factors in response to ICIs have mostly been elucidated in tissue samples. However, tissue immune status and changes in the immune microenvironment can also be reflected and monitored through peripheral blood. METHODS: Single-cell RNA and T cell receptor (scTCR) sequencing were conducted using peripheral blood mononuclear cells (PBMCs) from 60 patients with stage IV NSCLC. Those samples were prospectively acquired from patients treated with anti-PD(L)-1 therapy for advanced lung cancer. Based on the clinical outcomes, samples were classified as durable clinical benefit (DCB) and non-durable clinical benefit (NCB). The samples constituted paired longitudinal samples, consisting of pre-treatment and on-treatment. Additionally, PBMC samples from 60 healthy donors from the Asian Immune Diversity Atlas project were used as a control. RESULTS: The dynamic changes in major cell types between pre-treatment and on-treatment PBMCs were associated with an increase in proliferating T cells and NK cells in both DCB and NCB groups. Among T cell subtypes, effector memory CD8+ T cells (CD8+ TEM_GZMK_PDCD1) were increased after ICI treatment in both DCB and NCB. From the lineage trajectory analysis, effector memory CD8+ T cells resided at the bifurcation point, which has the potential to differentiate into lineages with precursor exhausted CD8+ T cells (CD8+ TCM cells) assumed to be related to the ICI response. From the scTCR-seq, effector memory CD8+ T cells along with T cells recognizing unknown antigen expanded and composed of novel clones skewed toward dysfunctional status, especially in on-treatment samples of the DCB group. The extent of immunophenotype conversion capabilities of the TCR with effector memory CD8+ T cells showed remarkable variation in the on-treatment sample in the DCB group. CONCLUSION: A transitioning T cell subtype identified in PBMCs might be related to the prolonged ICI response. From our study, expansion of effector memory CD8+ T cells with novel TCRs in PBMCs after ICI treatment could contribute to a better clinical outcome in patients with NSCLC. This proof-of-concept research strengthens the use of non-invasive PBMCs in studying systemic changes of immune reactions related to the ICI treatment.
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ITGAX is associated with poor prognosis and an immune-inflammatory microenvironment in clear cell renal cell carcinoma.
BACKGROUND: Integrin alpha X (ITGAX, CD11c) functions as a leukocyte adhesion molecule vital for immune cell activation, antigen presentation, and inflammatory responses. However, the expression profile, clinical relevance, immunoregulatory functions, and underlying mechanisms of ITGAX in clear cell renal cell carcinoma (ccRCC) remain incompletely elucidated. METHODS: ITGAX expression and its association with clinicopathological characteristics were examined using The Cancer Genome Atlas (TCGA)-kidney renal clear cell carcinoma (KIRC) dataset. Survival outcomes were analyzed using Kaplan-Meier and Cox regression methodologies. However, diagnostic efficacy was assessed via receiver operating characteristic (ROC) curve analysis. Immune cell infiltration, tumor purity, and immune checkpoint gene expression were evaluated using various computational algorithms. To elucidate the molecular features associated with ITGAX, functional enrichment and protein-protein interaction analyses were conducted. A KIRC single-cell RNA sequencing dataset was used to ascertain the cellular localization of ITGAX within the tumor microenvironment. In vitro validation involved the use of the ccRCC cell lines 786-O and Caki-1, alongside the normal renal epithelial cell line HK-2. ITGAX knockdown, functional assays, Western blotting, and AKT reactivation with SC79 were used to study cell phenotypes and the AKT/mTOR signaling pathway. RESULTS: ITGAX expression was markedly upregulated in TCGA-KIRC tissues and positively correlated with adverse clinicopathological characteristics, poorer overall survival, and favorable diagnostic efficacy, as evidenced by ROC curve analysis. Various computational algorithms indicated a strong association between ITGAX expression and immune cell infiltration, reduced tumor purity, elevated immune scores, and increased immune checkpoint gene expression. Functional enrichment analysis revealed that genes associated with ITGAX were predominantly involved in immune-related and microenvironment-associated pathways. Single-cell analysis demonstrated that ITGAX was predominantly enriched in myeloid cell populations, particularly monocytes/macrophages and dendritic cells, within the KIRC tumor microenvironment. In vitro experiments confirmed the relative elevation of ITGAX in ccRCC cell lines compared to HK-2 cells and revealed that ITGAX knockdown led to reduced cell proliferation, migration, invasion, and clonogenicity. ITGAX silencing was also associated with decreased AKT/mTOR phosphorylation, whereas AKT reactivation partially mitigated these phenotypic changes. CONCLUSIONS: This study suggests that ITGAX is associated with unfavorable clinical characteristics, a myeloid-enriched immune contexture, and AKT/mTOR-associated malignant phenotypes in ccRCC. These results suggest that ITGAX is a potential immune-related biomarker of ccRCC; however, additional clinical, spatial, and in vivo validation is necessary.
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GART expression is associated with a proliferative and purine-metabolic ISC-like epithelial state in ulcerative colitis.
OBJECTIVE: To characterize the epithelial state associated with GART expression in ulcerative colitis (UC) and determine whether this association reflects a GART-specific program or a broader proliferative and purine-metabolic phenotype. METHODS: Four independent bulk transcriptomic cohorts were analyzed and synthesized by random-effects meta-analysis. Human colonic scRNA-seq datasets (GSE214695 and SCP259) were integrated, with principal comparisons repeated using donor-aware pseudobulk or mixed-effects approaches and adjustment for sequencing depth, gene detection, and cell-cycle covariates. GART detection was defined from raw counts and tested using alternative thresholds. Pseudotime, scTenifoldKnk, CellChat/LIANA, and transcriptional-network analyses were used as exploratory analyses. Spatial transcriptomics (GSE189184), human colonic multiplex immunofluorescence, and acute DSS-induced colitis tissues were used for tissue-level localization. RESULTS: Across the four bulk cohorts, GART expression showed an overall increase in UC (pooled Hedges' g = 0.743, 95% CI 0.239-1.248; P = 0.0183). In the single-cell atlas, GART detection localized preferentially to an ISC-like epithelial compartment, although the magnitude of the UC-associated detection difference varied between cohorts. Within UC ISC-like cells, donor-paired pseudobulk analyses identified proliferative and nucleotide-metabolic transcriptional differences associated with GART detection. Across the broader ISC-like epithelial atlas, donor-aware module analyses showed positive associations of GART detection with purine-biosynthesis, DNA-replication, DNA-repair, and mitotic programs, and these associations remained positive within cell-cycle strata. Comparison with other de novo purine-synthesis enzymes did not support a uniquely GART-specific alteration. Exploratory network analyses linked the GART-associated state to proliferative and nucleotide-metabolic programs but did not establish functional dependence. In seven independent spatial donors, the single-cell-derived epithelial program was consistently higher in GART-detected than GART-undetected epithelial regions (mean within-donor difference = 0.0262, 95% CI 0.0140-0.0407; exact P = 0.0156). Human tissue immunofluorescence further showed co-enrichment of GART with OLFM4-positive ISC-like, MYBL2/Ki67-positive proliferative, and MIF/CD74-associated inflammatory regions across the corresponding panel-specific participant sets. CONCLUSION: GART identifies a proliferative and purine-metabolic ISC-like epithelial state in UC but is not established as a specific driver of epithelial regeneration. The findings support an association between GART detection, nucleotide-demand programs, proliferative epithelial activity, and the inflammatory tissue context, providing a framework for future direct functional studies.
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Construction and Validation of Prognostic Regulation Network Based on RNA-Binding Protein Genes in Lung Squamous Cell Carcinoma.
Lung squamous cell carcinoma (LUSC) is a common histologic subtype of non-small cell lung cancer with a poor prognosis. RNA-binding proteins (RBPs) are key modulators in the posttranscriptional regulation and RBP alterations are commonly found in various cancer types. However, its roles in predicting the tumorigenesis and prognosis have not been identified in LUSC. To identify the roles of RBPs in the tumorigenesis and prognosis of LUSC, the RNA sequencing data of patients with LUSC were retrieved from The Cancer Genome Atlas (TCGA) databases. The differential expressed genes (DEGs) were evaluated and identified. The intersection of manually curated RBPs and tumorigenesis-related DEGs was filtered to the univariate Cox regression analysis. The intersection genes with prognostic value were defined as prognostic RNA-binding protein genes (PRBPGs). Based on them, the predicted model was constructed. Its accuracy was tested by the area under the curve (AUC) of the receiver operator characteristic curve and the risk score. In addition, to explore the key regulatory network, the relationship among PRBPGs, target RNA, and absolute quantification of 50 hallmarks of cancer was also identified by Pearson correlation analysis. A total of 311 genes were filtered as the intersection of 1542 manually curated RBPs and tumorigenesis-related DEGs and the results revealed 17 PRBPGs. Based on them, we constructed the predict model with a relatively high accuracy (AUC: 0.739). The Kaplan-Meier survival curve showed the significant prognostic value of risk score (p < 0.001). Moreover, we uncovered the regulatory networks of PHF5A-TOMM22-oxidative phosphorylation, TLR3-CTSO inflammation-related pathway, SECISBP2L-targeted RNA (ADGRF5, TGFBR2, CD302, AC096921.2, AHCYL2, RPS6KA2, SLC34A2, and SFTPB) angiogenesis, and SECISBP2L-AKAP13 signaling (DNA repair, MTORC1 signaling, and MYC targets). The regulation mechanisms and cellular location of key PRBPGs were validated by assay for targeting accessible chromatin with high-throughput sequencing and single-cell RNA sequencing. Our study identifies PRBPGs as reliable indexes in predicting the tumorigenesis and prognosis of patients with LUSC and provides a well-applied model for predicting the overall survival for patients with LUSC. Besides, we also identified the regulatory network among PRBPGs, target RNA, and cancer gene sets in mediating the LUSC tumorigenesis.
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CKAP5: Unraveling Its Crucial Function in Liver Hepatocellular Carcinoma Progression and Prognosis.
BACKGROUND: Liver hepatocellular carcinoma (LIHC) remains a leading cause of cancer-related mortality worldwide, with limited therapeutic options for advanced stages. Cytoskeleton-associated protein 5 (CKAP5), a key regulator of microtubule dynamics, has emerged as a potential oncogene in multiple cancers, yet its precise role and clinical relevance in LIHC pathogenesis and tumor immunity are not fully understood. METHODS: We systematically evaluated CKAP5 expression patterns using multi-omics data from TCGA, GEO, and the Human Protein Atlas. Prognostic significance was assessed through Kaplan-Meier survival analysis, Cox regression, and ROC curves. The association between CKAP5 and the tumor immune microenvironment was investigated via immune cell infiltration analysis, immune checkpoint correlation, and single-cell RNA sequencing. Mechanistic insights were explored through gene set enrichment analysis (GSEA), transcription factor activity inference, and protein-protein interaction network construction. Functional validation was performed using CRISPR-Cas9-mediated CKAP5 knockdown in HepG2 cells, followed by comprehensive assays measuring proliferation, migration, and invasion capabilities. RESULTS: CKAP5 was significantly overexpressed in LIHC tissues at both mRNA and protein levels, and its elevated expression correlated strongly with advanced tumor stage, poor differentiation, and unfavorable patient survival. CKAP5 expression was associated with distinct immune cell infiltration patterns and positively correlated with key immune checkpoint molecules (PD1, PDL1, and CTLA4). Bioinformatic analyses further revealed a potential mechanistic link between CKAP5 and immunosuppressive signaling pathways, including JAK-STAT and NF-κB. Functional studies demonstrated that CKAP5 depletion markedly suppressed LIHC cell proliferation, colony formation, migration, and invasion. CONCLUSIONS: Our integrated analysis establishes CKAP5 as a critical promoter of LIHC progression and a modulator of the tumor immune microenvironment. These findings nominate CKAP5 as a promising prognostic biomarker and a potential therapeutic target, providing new insights into LIHC pathogenesis and future treatment strategies.
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Radiomics-Inferred Immune Programs Map Therapeutic Contexts in Glioblastoma.
RATIONALE AND OBJECTIVES: To develop and evaluate a noninvasive radiogenomic framework linking multiregional magnetic resonance imaging radiomics to glioblastoma immune microenvironment states and mechanism-based therapeutic hypotheses. MATERIALS AND METHODS: The internal University of California San Francisco-Preoperative Diffuse Glioma MRI dataset (UCSF-PDGM) cohort included 223 patients, divided into training (n = 156) and validation (n = 67) sets; 98 The Cancer Genome Atlas glioblastoma dataset (TCGA-GBM) patients formed an independent external cohort. A block/atom-based ensemble radiomics model was developed for overall survival prediction. Matched bulk RNA sequencing from 88 external-cohort patients underwent non-negative least-squares deconvolution using a GSE84465-derived single-cell reference, pathway analysis, and single-cell-supported interpretation. Exploratory Hot, Warm, and Cold states were defined by K-means clustering of direct T-cell-marker expression and interferon-gamma-response single-sample gene set enrichment analysis scores. Therapeutic candidates were organized by immune state and mechanism without assigning efficacy scores. RESULTS: The radiomics model achieved C-indices of 0.787 (95% confidence interval [CI], 0.741-0.826), 0.701 (95% CI, 0.612-0.777), and 0.702 (95% CI, 0.638-0.760) in the training, validation, and external cohorts, respectively; corresponding mean time-dependent areas under the curve were 0.857, 0.773, and 0.805. The ensemble prognostic score remained independently associated with overall survival in all cohorts. In external testing, the radiomics-plus-clinical model showed a higher C-index than the clinical-only model (0.730 vs 0.639). Transcriptomic analyses indicated heterogeneous tumor-microenvironment composition and compartment-restricted immune programs. The final classification comprised 12 Hot (13.6%), 23 Warm (26.1%), and 53 Cold (60.2%) tumors and showed bootstrap stability (adjusted Rand index, 0.86). Immune-state-specific therapeutic assignments were interpreted as hypothesis-generating. CONCLUSIONS: This framework links magnetic resonance imaging-derived prognostic phenotypes to exploratory immune states and mechanism-based therapeutic hypotheses in glioblastoma. Independent radiogenomic and prospective validation is required before clinical application.