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PubMed2026

A pan-cancer analysis of MEX3D in human tumors.

BACKGROUND: MEX3D, a member of the MEX3 RNA-binding protein family, has emerged as a potential regulatory molecule in cancer. However, its role across different tumor types remains largely unexplored. METHODS: We conducted a pan-cancer analysis of MEX3D using transcriptomic and proteomic data from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Expression patterns, clinical correlations, survival outcomes, genetic alterations, RNA modification associations, immune infiltration, and functional enrichment were systematically evaluated. RESULTS: MEX3D was significantly dysregulated in numerous cancers at both mRNA and protein levels. Its expression correlated with tumor stage in ACC, LIHC, OV, SKCM, and THCA. Elevated MEX3D expression was associated with poor overall survival (OS) and disease-specific survival (DSS) in multiple malignancies, including ACC, LGG, LUAD, and MESO. Genetic alteration analysis revealed frequent amplifications and mutations, particularly in SARC and OV. MEX3D was positively correlated with RNA modification-related genes (m1A, m5C, m6A) and immune regulatory genes such as CD276, TGFB1, VEGFA, and ICOSLG. Additionally, MEX3D expression showed significant associations with tumor mutational burden (TMB), microsatellite instability (MSI), and cancer-associated fibroblast infiltration. Functional enrichment analyses indicated that MEX3D-related genes are involved in reproductive cellular processes, RNA binding, the Hippo signaling pathway, and microRNA-related oncogenic pathways. CONCLUSION: This pan-cancer analysis highlights the heterogeneous expression and cancer-specific prognostic significance of MEX3D. MEX3D is associated with immune infiltration, immune regulatory genes, RNA modification-related genes, TMB/MSI, and pathways involved in gene regulation and tumor progression. These findings suggest that MEX3D may participate in cancer-specific post-transcriptional and microenvironmental regulatory networks.

Biomarker↗

PubMed2006

The analysis of RCAS1 and DFF-45 expression in nasal polyps with respect to immune cells infiltration.

BACKGROUND: Nasal polyp constitutes a benign growth process in the nasal and sinus mucosa. RCAS1 (receptor-binding cancer antigen expressed on SiSo cells) is a protein expressed mainly by various human cancer cells. It is not only the marker of cancer process and its expression can also be observed in physiological processes. It is responsible for the regulation of immune cells activity. DFF45 (DNA fragmenting factor) has been described as a substrate for caspase-3. DFF45 seems to play an important role in the onset of apoptotic process by acting probably through the regulation of DNA fragmentation. The aim of the study was to evaluate the ability of nasal polyps to regulate the cytotoxic immune response and to determine their resistance to apoptosis. RESULTS: The higher RCAS1 level was identified in lymphocytic nasal polyps, the medium one in eosinophilic while the lowest was identified in neutrophilic. DFF-45 expression was higher in eosinophilic than in neutrophilic and lymphocytic nasal polyps. CONCLUSION: The changes in DFF-45 level in nasal polyps might indicate a different resistance to apoptosis mediated by immune cells. The alterations in RCAS1 expression indicate that nasal polyps have the ability to regulate the cytotoxic immune response. The breaking of resistance to immune mediated apoptosis in nasal polyps might have a new therapeutic impact.

Adult↗

PubMed2025

Identifying key palmitoylation-associated genes in endometriosis through genomic data analysis.

BACKGROUND: Palmitoylation, a post-translational lipid modification, has garnered increasing attention for its role in inflammatory processes and tumorigenesis. Emerging evidence suggests a potential association between palmitoylation and inflammatory responses in the pathogenesis of endometriosis. However, the precise mechanistic interplay remains elusive, necessitating further investigation. METHODS: This study integrated transcriptomic analysis and Mendelian randomization (MR) to identify a causal gene set implicated in endometriosis. Differentially expressed genes (DEGs) were first identified in the training dataset using the limma package in R. Weighted gene co-expression network analysis (WGCNA) was subsequently performed, leveraging Single Sample Gene Set Enrichment Analysis (ssGSEA)-derived scores of palmitoylation-related genes (PRGs) as phenotypic traits to identify key modular genes. The intersection of these key modular genes with DEGs yielded a refined gene set. Machine learning algorithms were then applied to further optimize gene selection, followed by external validation, immune infiltration analysis, RNA network construction, and exploration of potential targeted drug candidates. RESULTS: Through a rigorous screening process, VRK1, GALNT12, and RMI1 emerged as key genes associated with palmitoylation, exhibiting significant downregulation in endometriosis samples (P < 0.05), indicative of a potential protective role. Immune infiltration analysis further revealed strong correlations between these genes and M2 macrophages as well as resting Natural Killer (NK) cells. Additionally, investigations into the targeted RNA network and drug association profiling provided novel insights, laying the groundwork for future high-quality validation studies. CONCLUSIONS: This study employed a comprehensive analytical framework to identify palmitoylation-associated key genes in endometriosis. The integration of immunoinfiltration analysis, RNA network construction, and drug association profiling offers valuable insights for advancing clinical diagnostics, disease monitoring, and therapeutic development in endometriosis.

Humans↗

PubMed2025

Identification of potential biomarkers and mechanisms for keloid disorder based on comprehensive bioinformatics analysis and machine learning algorithms.

BACKGROUND: Keloid disorder (KD) encompasses a spectrum of fibroproliferative dermal conditions, the pathogenesis remains complex and incompletely understood. This study sought to identify biomarkers and potential therapeutic targets for KD through an integrative bioinformatics approach and machine learning analysis of RNA sequencing data. METHODS: RNA sequencing was performed on skin tissue samples from 13 patients with KD and 14 healthy controls. Using weighted gene co-expression network analysis and differential expression analysis revealed differentially expressed key module genes, and the CytoHubba plugin identified candidate genes. Subsequently analyzed using least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) methods to pinpoint feature genes associated with KD. Following this, biomarkers were determined through expression level validation, enrichment analysis, and immune infiltration analysis. RESULTS: A total of 420 differentially expressed key module genes were identified, and the top 10 genes with DMNC values were selected as candidate genes. Five feature genes were selected through LASSO and SVM-RFE, with NID2, MFAP2, COL8A1, and P4HA3 showing significant expression differences between KD and control samples, along with consistent expression patterns across datasets, identified as potential biomarkers. These four biomarkers were proved to possess high diagnostic potential, and they were found to exhibit significant positive correlations with one another. Functional enrichment analysis indicated that the primary KEGG pathways associated with these biomarkers included "steroid hormone biosynthesis" and "cytokine-cytokine receptor interaction." Moreover, immune infiltration analysis revealed that the four biomarkers were negatively correlated with type 17 T helper cells and positively correlated with 15 immune cell types, including activated B cells and central memory CD4 T cells. CONCLUSION: In conclusion, NID2, MFAP2, COL8A1, and P4HA3 were identified as key biomarkers for KD, offering new avenues for more targeted and effective diagnostic and therapeutic strategies for managing this condition.

Humans↗

PubMed1997

A role for P-selectin in neutrophil and platelet infiltration in immune complex glomerulonephritis.

P-selectin is one of the key early mediators of leukocyte adhesion in inflammatory conditions. This report examines the role of P-selectin in a neutrophil- and platelet-mediated model of glomerulonephritis (the concanavalin A [con A] model). The administration of neutralizing anti-P-selectin antibody (PB 1.3) reduced the platelet influx at 10 min (P < 0.05) and was associated with a 60% reduction in the neutrophil infiltrate and a 50% reduction in the number of oxidant-producing cells at 3 h within glomeruli. No effect on glomerular monocyte-macrophage accumulation was observed, and proteinuria was reduced by 20% but did not reach significance. It is concluded that P-selectin plays an important role in mediating the neutrophil and platelet accumulation in this model and likely has a role in mediating the glomerular injury.

Animals↗

PubMed2026

Metabolism pathway-based subtyping in pancreatic adenocarcinoma: an integrated study by bulk RNA-sequence and machine learning algorithms.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) is highly aggressive, and its tumor microenvironment has significant metabolic and immune microenvironment complexity and genomic instability. In this study, by integrating the metabolic pathway activity score and clinical data, we constructed a novel risk assessment model to reveal the unique biological behavior and clinical significance behind different PAAD subtypes. METHODS: In this study, the transcriptome and clinical data of TCGA and GSE57495 databases were integrated to explore the interaction between metabolic pathways. Based on unsupervised clustering analysis of pathway activity and survival prognosis, patients with PAAD were classified into metabolic subtypes with significant prognostic differences. Subsequently, we assessed the heterogeneity of these subtypes in terms of clinical outcomes, genomic characteristics, and immune microenvironment composition. Based on the differentially expressed genes (DEGs) among metabolic subtypes, a clinical prognostic risk model and nomogram were constructed, which were double-validated by GSE57495-independent cohort and GSE57495 + TCGA-PAAD combined cohort. Finally, the correlations between risk scores (RSs) and signaling pathway activity and tumor immune microenvironment characteristics were evaluated. RESULTS: Based on metabolic pathway correlation and prognostic information, 240 patients in the TCGA-PAAD and GSE57495 datasets were divided into three subgroups. There were significant differences between subgroups in gene expression, pathway activity, clinical prognosis, and immune infiltration characteristics among the subtypes. Using machine learning algorithms, an RS model was constructed from DEGs among the subgroups, with the random forest method showing the best performance. A nomogram integrating the RS and clinical indicators demonstrated excellent predictive accuracy for 1-, 3-, and 5-year survival rates, confirming the RS as an independent prognostic factor. High- and low-risk groups exhibited significant differences in immune infiltration, pathway activity, and gene mutations. Drug sensitivity analysis showed that the high-risk group was more sensitive to AZD6244, ABT737, and other drugs. CONCLUSION: This study stratified patients with PAAD into three subgroups based on metabolic pathways and prognostic information, revealing significant differences in clinical outcomes, immune characteristics, and genetic mutations. The robust RS model developed from these findings demonstrated strong predictive power for patient survival and identified promising therapeutic strategies, providing valuable insights for advancing precision medicine in PAAD.

immune microenvironment↗

PubMed2024

Systematic analysis of cuproptosis abnormalities and functional significance in cancer.

BACKGROUND: Cuproptosis is a recently discovered type of cell death, but the role and behavior of cuproptosis-related genes (CuRGs) in cancers remain unclear. This paper aims to address these issues by analyzing the multi-omics characteristics of cancer-related genes (CuRGs) across various types of cancer. METHOD: To investigate the impact of somatic copy number alterations (SCNA) and DNA methylation on CRG expression, we will analyze the correlation between these factors. We developed a cuproptosis index (CPI) model to measure the level of cuproptosis and investigate its functional roles. Using this model, we assessed the clinical prognosis of colorectal cancer patients and analyzed genetic changes and immune infiltration features in different CPI levels. RESULTS: The study's findings indicate that the majority of cancer-related genes (CuRGs) were suppressed in tumors and had a positive correlation with somatic copy number alterations (SCNA), while having a negative correlation with DNA methylation. This suggests that both SCNA and DNA methylation have an impact on the expression of CuRGs. The CPI model is a reliable predictor of survival outcomes in patients with colorectal cancer and can serve as an independent prognostic factor. Patients with a higher CPI have a worse prognosis. We conducted a deeper analysis of the genetic alterations and immune infiltration patterns in both CPI positive and negative groups. Our findings revealed significant differences, indicating that CuRGs may play a crucial role in tumor immunity mechanisms. Additionally, we have noticed a positive correlation between CuRGs and various crucial pathways that are linked to the occurrence, progression, and metastasis of tumors. CONCLUSIONS: Overall, our study systematically analyzes cuproptosis and its regulatory genes, emphasizing the potential of using cuproptosis as a basis for cancer therapy.

Humans↗

PubMed1998

Expression and localization of insulin-like growth factor-1 in normal and post-burn hypertrophic scar tissue in human.

The migration of epithelial cells from dermal appendages toward the wound surface is essential for re-epithelialization of partial thickness burn injuries. This study provides evidence that these cells in vivo synthesize a mitogenic and fibrogenic factor, insulin-like growth factor-1 (IGF-1), which may promote the development of the post-burn fibroproliferative disorder, hypertrophic scarring (HSc). An evaluation of 7 post-burn hypertrophic scars, 7 normal skin samples obtained from the same patients and 4 mature scars revealed that IGF-1 expressing cells from the disrupted sweat glands tend to reform small sweat glands of 4-10 cells/gland in post-burn HSc. The number of these cells increases with time and the glands become larger in mature scar. Other epithelial cells such as those found in sebaceous glands and basal and suprabasal keratinocytes, also express IGF-1 protein and mRNA as detected by Northern and RT-PCR analysis of RNA obtained from whole skin and separated epidermis and dermis. However, cultured keratinocytes did not express mRNA for IGF-1. Histological comparisons between normal and HSc sections show no mature sebaceous glands in dermal fibrotic tissues but the number of IGF-1 producing cells including infiltrated immune cells was markedly higher in the dermis of hypertrophic scar tissues relative to that of the normal control. In these tissues, but not in normal dermis, IGF-1 protein was found associated with the extracellular matrix. By in situ hybridization, IGF-1 mRNA was localized to both epithelial and infiltrated immune cells. Collectively, these findings suggest that in normal skin, fibroblasts have little or no access to diffusible IGF-1 expressed by epithelial cells of the epidermis, sweat and sebaceous glands; while following dermal injury when these structures are disrupted, IGF-1 may contribute to the development of fibrosis through its fibrogenic and mitogenic functions. Reformation of sweat glands during the later stages of healing may, therefore, limit this accessibility, and lead to scar maturation.

Adolescent↗

PubMed2026

IL1RAP Is Associated With an Inflammation-Immunity-Related State in Skin Cutaneous Melanoma: Integrative Evidence From Pan-Cancer Data and Melanoma Immunotherapy Cohorts.

BACKGROUND: The crosstalk between inflammation and immunity plays a central role in tumor progression, immune evasion, and therapeutic response. Interleukin-1 receptor accessory protein (IL1RAP) is a key adaptor in inflammatory signaling, yet its immunological relevance and clinical implications in skin cutaneous melanoma (SKCM) remain largely unexplored. METHODS: We performed an integrative analysis combining pan-cancer and melanoma-focused datasets. Bulk transcriptomic, single-cell, spatial transcriptomic, genomic alteration, pharmacogenomic, and clinical survival data were obtained from TCGA, GTEx, GEO, ENA, and other public resources. IL1RAP expression was evaluated across cancer types in relation to diagnostic performance, immune subtypes, survival outcomes, functional pathway activity, immune-genomic states, somatic alterations, and drug-response metrics. Melanoma-focused analyses examined immune infiltration, methylation-derived tumor-infiltrating lymphocyte (MeTIL) scores, and exploratory survival associations in five treatment cohorts; the survival groups were defined using cohort-specific optimal cutoffs rather than median splits. RESULTS: IL1RAP expression differed between tumor and normal tissues in multiple cancers, although the direction and magnitude varied by cancer type. Pan-cancer survival associations were likewise context dependent. Single-cell and spatial transcriptomic resources indicated cell-type and spatial heterogeneity of IL1RAP expression within tumor microenvironments. Pathway, immune-genomic, and pharmacogenomic analyses identified exploratory associations with functional states, genomic features, and drug-response metrics. In SKCM, IL1RAP expression was associated with several immune-infiltration estimates and higher MeTIL scores. Across five melanoma immunotherapy cohorts, the direction and magnitude of the overall survival associations varied substantially. CONCLUSIONS: This retrospective integrative analysis suggests that IL1RAP may mark an inflammation-immunity-related state in SKCM. The heterogeneous associations across cancers and melanoma treatment cohorts support further validation but do not establish IL1RAP as a causal regulator, a treatment-response predictor, or a therapeutic target.

IL1RAP↗

PubMed2026

Pan-cancer analysis identifies KANSL2 as a cell-cycle-associated regulator of tumor progression and immunity in liver hepatocellular carcinoma.

KANSL2, a core component of the NSL histone acetyltransferase complex, has been implicated in tumorigenesis. However, its pan-cancer relevance and functional role in liver hepatocellular carcinoma (LIHC) remain unclear. Multi-omics data from TCGA, GEO, and HPA were integrated to systematically evaluate KANSL2 expression, clinical significance, genomic alterations, and immune associations across cancers. Functional enrichment, immune infiltration analyses, and single-cell transcriptomics were performed. In vitro assays were conducted to validate the biological effects of KANSL2 in LIHC cells. KANSL2 is broadly upregulated across cancers and exhibits strong diagnostic performance. Elevated KANSL2 expression correlates with unfavorable prognosis, particularly in LIHC. Mechanistically, KANSL2 and its co-expressed genes are enriched in cell-cycle progression. KANSL2 expression is also closely associated with immune infiltration and immunoregulatory signaling within the tumor microenvironment, with single-cell data indicating preferential expression in proliferative T-cell subsets. Functional experiments demonstrate that KANSL2 silencing suppresses proliferation, migration, and invasion, and induces G2/M phase arrest in LIHC cells. Notably, its effects on apoptosis are limited, suggesting that KANSL2 primarily drives tumor progression through cell-cycle-dependent mechanisms. This study identifies KANSL2 as a key regulator of tumor progression and immune remodeling in LIHC. By promoting malignancy predominantly via cell-cycle control, KANSL2 represents a promising biomarker for diagnosis and prognosis, and a potential therapeutic target.

Carcinoma, Hepatocellular↗

PubMed2026

Analysis and validation of abnormal signaling pathways and immune cell infiltration characteristics in digestive system cancers based on peroxisome-related genes.

BACKGROUND: Although emerging evidence suggests a role for peroxisomes in tumorigenesis, their functions in digestive cancers remain unclear. This study aims to investigate the association between peroxisomes and digestive tract tumors. METHODS: To systematically investigate peroxisomal functions in digestive cancers, we first constructed and validated tumor-specific prognostic signatures based on peroxisome-related genes (PRGs) through univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. We then characterized the tumor immune microenvironment (TIME) with CIBERSORT, X-CELL, and EPIC algorithms, and identified tumor-specific and common signalings via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). Focusing on hepatocellular carcinoma (HCC), we experimentally validated peroxisome-related therapeutic responses by profiling signature genes in radioresistant cells and an orthotopic transarterial chemoembolization (TACE) rat model. PEX13 knockdown further assessed peroxisomal role in radiosensitivity and targeted therapy response. Clinical relevance of PEX13 was evaluated in HCC cohort. Single-cell RNA sequencing dataset and lipidomics further revealed peroxisomal mechanisms in HCC progression. Finally, peroxisomal function in colorectal cancer (CRC) was validated in vitro. RESULTS: Novel peroxisome-related prognostic signatures demonstrated strong predictive power in HCC, colon adenocarcinoma, rectal adenocarcinoma, pancreatic adenocarcinoma, gastric adenocarcinoma, esophageal adenocarcinoma, esophageal squamous cell carcinoma, and cholangiocarcinoma. High-risk patients displayed an immunosuppressive microenvironment, characterized by increased infiltration of regulatory T cells, M2 macrophages, Th2 cells, or cancer-associated fibroblasts, or Th1 cells' reduction. Peroxisomes engaged in several distinct yet convergent pathways, most notably "positive regulation of response to stimuli". HCC prognostic genes were dynamically regulated in response to therapeutic stimuli, including radiotherapy, targeted therapy, and TACE. Clinically, the expression of PEX13 was markedly upregulated in tumor tissues from therapy-resistant HCC patients. Mechanistically, peroxisomal dysfunction induced by silencing PEX13 in HCC or UBE2D2 in CRC may overcome therapeutic resistance (radiotherapy/ lenvatinib resistance in HCC, radioresistance in CRC) through reprogramming lipid metabolism. CONCLUSIONS: Peroxisomes act as pivotal regulators of digestive cancer progression by modulating signaling pathways, the TIME, therapeutic resistance, and lipid metabolism. Targeting peroxisomal function, particularly in high-risk subgroups of HCC and CRC, warrants further exploration as a promising therapeutic strategy.

Peroxisomes↗

PubMed2026

Integrated Bioinformatics Analysis Revealing that the NSDHL Gene Might Be Associated with the Progression of Western HFD/SW-Induced Hepatocellular Carcinoma.

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) remains a significant global health concern. However, the etiology and pathogenesis of HCC have yet to be fully elucidated. Previous studies have indicated a close association between obesity and the occurrence and progression of HCC. The objective of this study was to employ bioinformatics strategies in order to explore key genes associated with the clinical diagnosis and prognosis of HCC induced by a Western high-fat diet and sugar water (HFD/SW). MATERIALS AND METHODS: We obtained the expression profile chip data GSE197884 from the Gene Expression Omnibus (GEO) database. Subsequently, “DESeq” and “Limma” R packages were employed to identify differentially expressed genes (DEGs) while constructing a co-expressed gene network using weighted gene co-expression analysis (WGCNA). Functional enrichment analyses were then carried out, followed by the construction of a protein-protein interaction (PPI) network to uncover core genes. The core genes were confirmed through data retrieved from The Cancer Genome Atlas (TCGA) database in order to determine their status as hub genes. Finally, survival and tumor immune infiltration analyses were performed to unveil the prognostic significance of these hub genes. RESULTS: In total, 126 intersection targets were retrieved through the Venn diagram. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that the DEGs were primarily related to the proliferation and apoptosis of HCC cells, the digestion and metabolism of liver cells, the HCC tumor microenvironment, and immune response. The PPI network analysis identified 11 core targets, among which seven hub genes, including NSDHL, MVK, SQLW, GCAT, ALAS2, GLDC, and AGXT, were obtained after TCGA database validation. Furthermore, it was found that NSDHL was closely associated with the clinical diagnosis and prognosis of HCC induced by HFD/SW and also affected the cellular immune infiltration in the HCC tumor microenvironment. CONCLUSION: The present study demonstrated a significantly elevated expression of NSDHL in HCC tissues, suggesting its potential as a specific biomarker for precise clinical diagnosis and prognosis assessment of HCC induced by HFD/SW.

Computational Biology↗

PubMed2026

Oxidative Stress Associated LncRNAs as Potential Biomarkers for Prognosis and Immune Responses in Lung Squamous Cell Carcinoma Patients.

Long-chain non-coding RNA (lncRNA) significantly influences lung squamous cell carcinoma's (LUSC) prognostic value and immune infiltration. This study aimed to demonstrate how oxidative stress-related lncRNAs impact lung squamous cell carcinoma (SCC). The Cancer Genome Atlas (TCGA) dataset gathered transcriptome information and related clinical data for LUSC. To build a prognostic model, 10 prognostic-related genes were identified using a series of bioinformatics analyses that compared the OS gene's aberrant expression in tumor and healthy tissues, as well as its association with malignancy. Subjects were stratified into high- and low-risk groups based on the median risk score derived from the 10-gene signature. While the mathematical risk model demonstrated limited independent predictive performance in the validation cohort (AUC ~ 0.5), functional and immunological evaluations revealed significant differences in the tumor microenvironment (TME) across risk strata. Specifically, high-risk patients exhibited distinct immune infiltration profiles and altered immunological scores relative to their low-risk counterparts. Therefore, rather than serving as a direct clinical prediction tool, this oxidative stress-related lncRNA signature provides valuable biological insights into the immune landscape of LUSC and highlights potential therapeutic targets for further mechanistic investigation.

Humans↗

PubMed2025

Identification and validation of prognostic genes associated with mitochondrial nuclear genes in gastric cancer.

Mitochondrial-related nuclear genes (MNGs) have shown great importance in cancer diagnosis and prognosis, but their role in gastric cancer (GC) remains unclear. GC-related transcriptome data from the gene expression omnibus and cancer genome atlas databases were analyzed to identify differentially expressed MNGs. A prognostic risk model was constructed through univariate Cox and least absolute shrinkage and selection operator regression, validated by Kaplan-Meier (K-M) survival curve and receiver operating characteristic curve. This was followed by immune infiltration analysis, independent prognostic analysis, functional enrichment analysis, drug sensitivity analysis, drug prediction, molecular docking and construction of regulatory networks. Three prognostic genes (ATP8A2, COX15 and TARS2) were identified. The expression of TARS2 and COX15 was positively correlated with CNV, while ATP8A2 was unaffected. The risk model and nomogram, integrating risk score and clinicopathological factors, exhibited excellent predictive performance. A significant correlation was observed between prognostic genes and differential immune cells, such as T cells, B cells, and NK cells. BMS-754807, Gefitinib, JQ1, Lapatinib, and Sapitinib exhibited significant differences in sensitivity between the high-risk group and the low-risk group. The results of molecular docking showed TP8A2 has stable binding ability with cytosine, COX15 with indomethacin, and TARS2 with bisacodyl. RT-qPCR revealed downregulation of ATP8A2 and upregulation of COX15 and TARS2 in GC samples. MNGs, including ATP8A2, COX15, and TARS2, demonstrated significant associations with immune infiltration, CNV, and prognostic outcomes of GC.

Humans↗

PubMed2026

Integrated transcriptome analysis and machine learning to construct a homeostatic model of acetylation for bladder cancer and validate the key gene CES1.

BACKGROUND: Bladder cancer (BLCA) is one of the most common malignant tumors of the urinary system. Protein acetylation (PA) plays a critical role in regulating multiple biological processes (BPs), cellular homeostasis, and cancer-related signaling pathways. This study aimed to construct a homeostatic model of acetylation for BLCA using integrated transcriptome analysis and machine learning and to validate the key gene CES1. METHODS: RNA sequencing (RNA-seq) and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Acetylation-related differentially expressed genes (DEGs) in BLCA were screened using differential expression analysis (DEA). An acetylation homeostatic model was constructed via univariate, machine learning-based least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses, followed by validation in multiple cohorts. Single-cell RNA-seq analysis was used to explore gene expression patterns in diverse cell types. Enrichment analysis (EA), immune infiltration, and drug sensitivity analysis (DSA) were performed to characterize molecular features of different risk groups. Finally, the biological function of CES1 as the key gene was verified by in vitro knockdown experiments. RESULTS: We established a robust acetylation homeostatic model consisting of five genes, which effectively predicted overall survival (OS) and served as an independent prognostic factor in BLCA. High-risk patients showed significantly poorer prognosis, distinct immune infiltration profiles, and differential drug sensitivity. CES1 was identified and validated as the key gene in this model, which was highly expressed in BLCA and associated with poor prognosis. Knockdown of CES1 markedly suppressed cell proliferation, invasion, and migration, and reduced intracellular coenzyme A (CoA) levels, thereby regulating PA homeostasis. CONCLUSIONS: We developed and validated a novel acetylation homeostatic model for survival stratification and personalized treatment guidance in BLCA, based on integrated transcriptome analysis and machine learning. CES1 is closely associated with intracellular CoA levels and the malignant progression of BLCA. Its potential association with PA homeostasis requires further mechanistic validation, and it may act as a candidate therapeutic biomarker for BLCA.

Bladder cancer (BLCA)↗

PubMed2006

Lymphocytic infiltration and immune activation in metallothionein promoter-exendin-4 (MT-Exendin) transgenic mice.

Glucagon-like peptide 1 (GLP-1) exhibits considerable potential for the treatment of type 2 diabetes because of its effects on stimulation of insulin secretion and the inhibition of gastric emptying, appetite, and glucagon secretion. However, native GLP-1 undergoes rapid enzymatic inactivation, prompting development of long-acting degradation-resistant GLP-1 receptor agonists such as exendin-4 (Ex-4). To study the consequences of sustained exposure to Ex-4, we generated metallothionein promoter-exendin-4 (MT-Exendin) mice that continuously express a proexendin-4 transgene in multiple murine tissues. We now report that MT-Exendin mice develop extensive tissue lymphocytic infiltration with increased numbers of CD4(+) and CD8a(+) cells in the liver and/or kidney and increased numbers of B220(+) cells present in the pancreas and liver. MT-Exendin mice generate antibodies directed against Ex-4, exendin NH(2)-terminal peptide (ENTP), and proexendin-4 as well as antibodies that cross-react with native GLP-1. Furthermore, lymphocytes isolated from MT-Exendin mice proliferate in response to proexendin-4 but not after exposure to Ex-4 or ENTP. These findings demonstrate that expression of a proexendin-4 transgene may be associated with activation of humoral and cellular immune responses in mice.

Animals↗

PubMed2026

Radiomics-based gradient boosting model on contrast-enhanced MRI for non-invasive prediction of epidermal growth factor receptor expression and therapeutic response to EGFR-targeted antibody-drug conjugates in high-grade glioma organoid models.

BACKGROUND: Epidermal growth factor (EGF) and its receptor EGF(EGFR) play crucial roles in glioblastoma (GBM) prognosis. However, non-invasive assessment of their expression remains challenging. This study aimed to determine whether radiomics features extracted from contrast-enhanced MRI could predict EGFR expression in high-grade gliomas (HGG) and to explore their associations with immune infiltration and therapeutic response of EGFR-Targeted antibody drug conjugates(EGFR-ADCs). METHODS: We extracted radiomic features from contrast-enhanced MRI of 298 GBM patients from The Cancer Imaging Archive (TCIA) and matched them with RNA-seq data from The Cancer Genome Atlas (TCGA). Feature selection was performed using minimum redundancy maximum relevance (mRMR) and recursive feature elimination (RFE). Machine learning models were built to predict EGF/EGFR expression. Radiogenomic associations were validated by immune infiltration analysis. Patient-Derived Tumor-Like Cell Clusters (PTC) were used to compare the antitumor efficacy of EGFR- ADCs and temozolomide. RESULTS: Elevated EGF/EGFR expression correlated with poor prognosis and increased infiltration of M2 macrophages, regulatory T cells, and CD4⁺ memory T cells. Pathway analysis demonstrated significant enrichment of the mechanistic target of rapamycin (mTOR) and Mitogen-Activated Protein Kinase (MAPK) signaling cascades. Radiomics-based prediction models achieved robust performance (AUC > 0.85) in stratifying EGFR expression status. In EGFR-positive tumor tissues, EGFR-ADCs exerted antitumor efficacy similar to that of temozolomide. CONCLUSIONS: EGF/EGFR expression is associated with immunosuppressive microenvironments and adverse outcomes in HGG. Radiomics may provide a non-invasive approach for estimating EGFR expression, although model performance requires external validation and EGFR-ADCs showed partial inhibitory activity within the tested range, though potency remains to be defined.These findings suggest a framework into radiogenomic stratification and targeted therapy in GBM.

Radiomics↗

PubMed1988

Immunological aspects of acute ureteral obstruction: immune cell infiltrate in the kidney.

Kidneys from rats subjected to bilateral ureteral obstruction (BUO), unilateral ureteral obstruction (UUO) and UUO with subsequent release were analyzed for leukocyte infiltration. A time-dependent influx of leukocytes, predominantly macrophages and suppressor T lymphocytes, occurred in both the cortex and medulla following obstruction, and disappeared with release of the obstruction. Glomerular macrophages declined following obstruction but increased to levels above control following release. The influx of leukocytes following obstruction was paralleled by an increase in thromboxane B2 excretion by the kidney and coincided with a decrease in glomerular filtration rate (GFR). This would suggest that an influx of immune cells is a prominent feature of the acute renal response to ureteral obstruction. These cells may modulate some of the post-obstructive alterations in renal function via the production of vasoactive substances, such as thromboxane A2.

Acute Disease↗