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PubMed2026

Integrative pan-cancer analysis of transferrin reveals context-dependent prognostic associations and links to immune and metabolic disease-related programs.

BACKGROUND: Iron metabolism is closely linked to tumor biology, yet the pan-cancer significance of transferrin (TF), the major circulating iron-transport protein, remains insufficiently defined. Although TF has been implicated in cancer-related processes, its prognostic relevance, immune associations, and broader disease-related transcriptional context have not been systematically characterized across tumor types. OBJECTIVE: This study aimed to perform an integrative pan-cancer analysis of TF to characterize its expression patterns, clinical associations, immune context, pathway features, and pharmacogenomic correlations, and to explore whether TF-related signals extend to selected metabolic and chronic organ injury settings. METHODS: We used multiple public databases, including The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), Gene Expression Omnibus (GEO), and Cancer Cell Line Encyclopedia (CCLE), to integrate transcriptomic, proteomic, and clinical data across 33 tumor types and selected non-malignant conditions. TF expression was evaluated across normal tissues, tumors, and cell lines, followed by survival analysis, immune infiltration analysis, TMB/MSI and methylation assessment, pathway enrichment, and drug-response correlation. Independent GEO cohorts of non-alcoholic steatohepatitis (NASH), heart failure (HF), and liver cirrhosis (LC) were used for cross-disease extension. Selected findings were further explored in OA/PA-treated hepatocytes, 786-O renal carcinoma cells, and AC16 cardiomyocytes. RESULTS: TF showed pronounced tissue specificity and cancer-type-dependent dysregulation. Across pan-cancer cohorts, the most consistent adverse survival associations were observed in kidney renal clear cell carcinoma (KIRC) and stomach adenocarcinoma (STAD), where TF remained associated with overall survival (OS) in multivariable analyses. TF expression was also correlated with cancer-type-specific immune infiltration patterns and selected drug-response profiles. Across independent NASH, HF, and LC datasets, TF expression was elevated and TF-associated pathways partially overlapped with those observed in cancer. In vitro experiments provided preliminary support that TF modulation is associated with proliferative phenotypes in KIRC cells and stress- and metabolism-related phenotypes in hepatocyte and cardiomyocyte models. CONCLUSION: These findings support TF as a context-dependent biomarker candidate in cancer, with the most consistent prognostic relevance observed in KIRC and STAD. Rather than establishing a unified mechanism across diseases, this study provides an integrative framework suggesting that TF is associated with malignant behavior, immune context, and selected metabolic stress-related programs, and warrants further mechanistic investigation.

Iron metabolism↗

PubMed2026

Pan-cancer Bioinformatics Analysis Combined with Colon Cancer Experimental Validation: A Study on TMED3 as a Diagnostic and Prognostic Biomarker.

Transmembrane Emp24 Protein Transport Domain 3 (TMED3), a member of the p24 protein family, has been implicated in tumor proliferation, invasion, and migration. This study aimed to evaluate the expression patterns, prognostic significance, immune associations, and potential biological functions of TMED3 across multiple cancer types using pan-cancer bioinformatics analysis combined with immunohistochemical (IHC) validation in colon cancer. Multiomics datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, UALCAN, Human Protein Atlas, and cBioPortal databases were analyzed to investigate TMED3 expression and genetic alterations in pan-cancer. Immunohistochemistry was performed to evaluate TMED3 protein expression in colon cancer tissues. Kaplan-Meier survival analysis and Cox regression analysis were used to assess the prognostic value of TMED3. Spearman correlation analysis was conducted to evaluate the associations of TMED3 with tumor mutational burden, microsatellite instability (MSI), immune cell infiltration, and immune checkpoints. Gene Set Enrichment Analysis was performed to investigate potential biological pathways associated with TMED3 in colon cancer. TMED3 expression was elevated in most tumor types and was associated with unfavorable overall survival and disease-specific survival in adrenocortical carcinoma, colon adenocarcinoma, and uveal melanoma. The greatest frequency of TMED3 genetic alterations was identified in mesothelioma, with amplification representing the predominant alteration type. In addition, TMED3 expression showed significant correlations with tumor mutational burden and microsatellite instability in kidney renal clear cell carcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma. TMED3 expression was also associated with immune infiltration and immune checkpoint expression in several tumors. IHC analysis demonstrated increased TMED3 expression in colon cancer tissues compared with normal colon tissues and showed an association with T stage. Functional enrichment analysis identified pathways related to ribosome, antigen processing and presentation, oxidative phosphorylation, and pentose phosphate. These findings indicate that TMED3 may represent a promising biomarker for the diagnosis and prognostic evaluation of colon cancer as well as other tumor types.

Humans↗

PubMed2026

NPLOC4 Constructs Tumor Immunosuppressive Microenvironment in Pan-cancer and Hepatocellular Carcinoma.

INTRODUCTION: NPLOC4 (nuclear protein localization 4 homolog) is mainly involved in DNA damage, cell cycle, and ubiquitination promotion. Nonetheless, the role of NPLOC4 in the tumor immune microenvironment (TIME) and its potential as a promising tumor therapeutic target remains unclear. METHODS: Therefore, analyses of NPLOC4 mRNA and protein expression, RNA subcellular localization, and patient prognosis associated with NPLOC4 expression were conducted across multiple tumor types. Additionally, the correlations between NPLOC4 and immune cells, non-immune cells, and immune molecules within the tumor immune microenvironment (TIME) were investigated. These analyses utilized data from various public resources, including the Genotype-Tissue Expression (GTEx) project, The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), The Human Protein Atlas (HPA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), TIMER2.0, KM-Plotter, The University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), and Tumor Immune Single-cell Hub 2 (TISCH2). Subsequently, we utilized hepatocellular carcinoma (HCC) patients' cancer and adjacent tissues plus tumor cell lines to verify the differential RNA and protein expression of NPLOC4 via qRT-PCR and immunohistochemistry (IHC). Then, the relationship of NPLOC4 expression level with immune infiltration score, infiltration of effector immune cells, suppressive immune cells, and several vital immune checkpoints was analyzed in HCC immune microenvironment. Furthermore, the distribution of expression of NPLOC4 in various cells in the HCC microenvironment was determined through single-cell sequencing analysis. RESULTS: We discovered that NPLOC4 was up-regulated in a variety of tumors and was correlated with poor prognosis. NPLOC4 not only had the potential as a tumor prognostic marker and therapeutic target but also was strongly linked to immune cells, immune checkpoints, and immune-related molecules and pathways in HCC immune microenvironment. CONCLUSION: In summary, NPLOC4 may serve as a promising target for immunotherapy.

Humans↗

PubMed2026

Integrated Immunotherapy Target Atlas for Ewing Sarcoma.

BACKGROUND/AIM: Ewing sarcoma is a fusion-driven malignancy with low tumor mutational burden, making recurrent tumor-associated antigens with favorable tumor-to-normal contrast central to immunotherapy development. We converted the Deng et al.-defined 32-gene Ewing Sarcoma Specific Signature (ESS32) into a practical target atlas by integrating tumor RNA expression with normal-tissue context, protein evidence, subcellular localization, and therapeutic accessibility. MATERIALS AND METHODS: A 38-gene set was analyzed, including ESS32 and six comparator antigens (STEAP1, LINGO1, PRAME, CD99, CD276/B7-H3, and ENPP1). Eight Gene Expression Omnibus datasets (n=854 samples) were assigned predefined roles spanning tumor-versus-skeletal-muscle comparison, broad normal-organ context, EWSR1::FLI1 perturbation, tumor-only support cohorts, cell-line models, and cross-sarcoma comparison. Results were overlaid with Human Protein Atlas and published proteomic/surfaceome evidence. RESULTS: In GSE17674, the strongest tumor-enriched transcripts included NKX2-2, NPY1R, STEAP1, RBM11, RNF182, LIPI, CD99, STEAP2, LOXHD1, and DCDC2. Normal-tissue and compartment data substantially reordered RNA-only ranking. NKX2-2 showed the strongest Ewing-associated signal but encodes a nuclear transcription factor, favoring peptide-HLA/T-cell receptor (TCR) or vaccine development. RBM11 and LIPI emerged as high-interest intracellular/secretome-associated candidates, with an explicit epididymal/male reproductive caveat for LIPI. CD99 and NPY1R illustrated normal-cell reservoir and receptor-distribution constraints. CONCLUSION: ESS32 should be interpreted as an EWSR1::FLI1-associated RNA discovery set, not as a pre-validated target panel. Practical nomination requires integration of RNA enrichment, normal-tissue distribution, protein evidence, cellular compartment, and modality compatibility before nomination of TCR, vaccine, antibody-drug conjugate (ADC), chimeric antigen receptor (CAR), radioligand, or validation-first candidates.

Humans↗

PubMed2026

Integrated pan-cancer profiling highlights OSR2 as a prognostic indicator and immune-associated biomarker.

BACKGROUND: Odd-skipped-related 2 (OSR2), encoded by the OSR2 gene, has been reported to function as a checkpoint associated with CD8⁺ T-cell exhaustion in the tumor microenvironment of solid malignancies, suggesting its potential as a therapeutic target to improve immunotherapeutic responses. Nevertheless, the molecular and clinical significance of OSR2 across diverse cancer types has not yet been systematically investigated, and its pan-cancer expression profile, prognostic implications, and associations with tumor immunity remain to be fully elucidated. METHODS: In this study, we integrated datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) portal, and the Human Protein Atlas to construct a systematic pan-cancer profile of OSR2. The prognostic value of OSR2 was comprehensively assessed using univariate Cox regression, survival analysis, and receiver operating characteristic (ROC) curve analysis. In addition, we performed an in-depth analysis of the relationships between OSR2 and multiple molecular and immunological features, including copy number variation (CNV), DNA methylation, tumor mutational burden (TMB), microsatellite instability (MSI), immune-related gene expression, immune cell infiltration, and drug sensitivity, with the aim of exploring its potential immunological associations with the tumor microenvironment. RESULTS: OSR2 expression was significantly upregulated or downregulated in the majority of tumor tissues relative to normal counterparts and exhibited distinct cancer-type-specific patterns across clinical stages. CNV alterations and aberrant DNA methylation were closely associated with abnormal OSR2 mRNA expression in multiple cancers. Prognostic analyses indicated that OSR2 expression was significantly associated with overall survival, disease-specific survival, disease-free interval, and progression-free interval across multiple cancer types, showing either risk-associated or protective associations in a tumor-context-dependent manner. Furthermore, OSR2 expression showed strong associations with immune cell infiltration, particularly T-cell subsets, and was significantly correlated with the expression of multiple immune checkpoint-related genes across diverse malignancies. OSR2 expression was also closely associated with TMB, MSI, and sensitivity to multiple anticancer agents. CONCLUSION: Taken together, these findings suggest that OSR2 is associated with prognosis and immune-related features across multiple cancer types. OSR2 may be linked to features of the tumor immune microenvironment through its relationships with immune cell infiltration, immune checkpoint gene expression, and genomic instability, and thus may serve as a candidate biomarker for further investigation in cancer immunotherapy.

CD8⁺ T-cell↗

PubMed2026

Overexpression of TCF7L2 promotes the viability and migration of MHCC-97H human hepatocellular carcinoma cells by upregulating MT-ND4L.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly aggressive cancer with high metabolic adaptability. TCF7L2, a transcription factor implicated in type 2 diabetes and cancer, is overexpressed in HCC. However, its specific role in HCC metabolic reprogramming is not well defined. We aimed to elucidate the previously unrecognized molecular mechanisms through which TCF7L2 impacts HCC progression. METHODS: To investigate the function of TCF7L2, a stable MHCC-97H cell line with TCF7L2 overexpression was established via lentiviral transduction. Cell viability and migration were assessed by Cell Counting Kit-8 (CCK-8) and Transwell assays. Transcriptomic profiling [RNA sequencing (RNA-seq)] was performed to identify differentially expressed genes (DEGs). Functional enrichment analysis [Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA)] and bioinformatics promoter analysis (the JASPAR CORE database) were conducted. Clinical correlations, survival analysis, and tumor microenvironment (TME) interrogation were performed using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and single-cell datasets [Human Protein Atlas (HPA), CellChat]. Drug sensitivity was predicted via the Genomics of Drug Sensitivity in Cancer (GDSC) database. RESULTS: TCF7L2 overexpression significantly promoted HCC cell proliferation and migration. Transcriptomic analysis revealed that TCF7L2 drives a profound metabolic shift, with key enrichments in lipid homeostasis, fatty acid β-oxidation, and the PI3K/Akt pathway. Mechanistically, TCF7L2 directly binds to the promoter of CPT1A, the rate-limiting enzyme of fatty acid oxidation, and indirectly upregulates the mitochondrial gene MT-ND4Lvia a strong positive correlation with the mitochondrial transcription factor TFAM. In clinical cohorts, TCF7L2 was overexpressed in HCC and its expression correlated positively with MT-ND4L, MKI67, and SNAI1, and served as a predictor of poor overall survival (OS). Furthermore, TCF7L2-high tumors were enriched in hepatic progenitor cell (HPC)-like niches, mediated by enhanced ANGPTL4 signaling. High TCF7L2 expression predicted increased sensitivity to PI3K/mTOR pathway inhibitors. CONCLUSIONS: TCF7L2 acts as a master metabolic regulator in HCC, coordinating lipid catabolism and mitochondrial biogenesis to drive aggressive tumor behavior. It further remodels the TME towards an HPC-like state and predicts sensitivity to metabolic-targeted therapies. These findings identify TCF7L2 as a key prognostic biomarker and a promising therapeutic target.

MHCC-97H hepatocellular carcinoma cells (MHCC-97H ↗

PubMed2026

ARHGAP22 as a Potential Prognostic Biomarker in Clear Cell Renal Cell Carcinoma: Insights into Tumor Immunity and Co-Expression Networks.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer and is characterized by substantial clinical heterogeneity, highlighting the need for reliable prognostic biomarkers. This study evaluated the expression pattern, prognostic relevance, and immune-related associations of ARHGAP22 in ccRCC using transcriptomic and clinical data from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) cohort, together with external validation data and protein-expression information from the Human Protein Atlas (HPA). ARHGAP22 expression was compared between tumor and adjacent normal tissues, and its associations with overall survival, clinicopathological characteristics, tumor microenvironment scores, and estimated immune-cell fractions were assessed. Co-expression and functional-enrichment analyses were also performed to characterize potential biological associations. ARHGAP22 was significantly upregulated in ccRCC tissues at the transcriptomic level, with corresponding differences observed in immunohistochemical images. High ARHGAP22 expression was associated with shorter overall survival, advanced clinicopathological features, and higher ImmuneScore, StromalScore, and ESTIMATEScore values. CIBERSORT-based analysis showed that the high-expression group had higher estimated fractions of M2 macrophages and regulatory T cells and lower estimated fractions of naïve B cells, resting mast cells, and activated dendritic cells after false discovery rate correction. Functional-enrichment analyses linked ARHGAP22-associated genes to immune-related processes, cell migration, and chemokine- and cytokine-mediated signaling pathways. These findings suggest that ARHGAP22 may represent a potential prognostic and immune-related biomarker in ccRCC, although further independent clinical and experimental validation is required.

Humans↗

PubMed2026

A novel lactylation-related gene signature deciphers the immunosuppressive microenvironment and stratifies precision therapy in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer mortality, largely due to the heterogeneity of the tumor microenvironment (TME) and the limited efficacy of immunotherapy in microsatellite stable (MSS) tumors. Histone lactylation, a post-translational modification derived from the Warburg effect, serves as a critical bridge linking metabolic reprogramming to gene regulation and immune evasion; however, its specific prognostic value and clinical implications in CRC remain to be fully elucidated. METHODS: In this study, we systematically analyzed transcriptome profiling data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, supplemented by single-cell RNA sequencing (scRNA-seq) analysis and Human Protein Atlas (HPA) protein-level validation. By integrating univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) analysis, and multivariate Cox regression, we constructed a novel lactylation-related gene (LRG) risk signature. We extensively evaluated the association between this risk signature and patient prognosis, immune infiltration patterns, somatic mutations, and therapeutic sensitivity. RESULTS: A robust 9-gene prognostic signature (DHRS7, SPR, MBD2, RBM17, CSRP2, S100A4, TMSB4X, TKT, COPS4) was identified and corroborated at the protein level. Patients with high risk scores exhibited significantly worse overall survival (OS) across the training and two independent validation cohorts. Immunogenomic and scRNA-seq analyses revealed that high-risk tumors were characterized by an immunosuppressive and stromal-dense microenvironment-with stromal cells exhibiting the highest lactylation risk scores-enriched with regulatory T cells (Tregs), and frequently harbored PIK3CA mutations. Differential expression analysis indicated that this immune exclusion is structurally maintained by enriched extracellular matrix (ECM) organization and TGF-β signaling. Conversely, low-risk tumors displayed an inflamed phenotype with active antitumor immunity. Pharmacogenomic prediction identified distinct therapeutic stratifications: low-risk patients exhibited significant sensitivity to standard chemotherapeutics (fluorouracil, oxaliplatin) and EGFR/HER2 inhibitors (e.g., lapatinib, erlotinib). In contrast, high-risk patients showed specific vulnerabilities to novel targeted agents, including PI3K pathway inhibitors (TG-100-115, XL765), microenvironment-modulating agents (sildenafil, GANT-61), and epigenetic inhibitors (UNC0638). CONCLUSION: We established a novel lactylation-related risk signature that effectively stratifies CRC patients by prognosis and TME characteristics. By elucidating the crosstalk between metabolic dysregulation, stromal barriers, and immune exclusion, this study provides potential biomarkers and stratified therapeutic strategies-ranging from standard chemotherapy to targeted metabolic and stromal interventions-to optimize precision medicine for CRC patients.

Colorectal cancer↗

PubMed2026

Integrative analysis of the roles and prognostic value of RNA-binding proteins in papillary renal cell carcinoma.

RNA-binding proteins (RBPs) serve essential roles in various cancer types, but their functions in papillary renal cell carcinoma (pRCC) have not been elucidated to date. In our work, differentially expressed RBPs in pRCC were identified after acquisition of RNA-sequencing and clinical data related to pRCC from The Cancer Genome Atlas database(TCGA). Functional enrichment analysis and protein interaction network analysis, along with univariate and multivariate Cox regression analyses, were performed to uncover potential biological effects of the identified RBPs and screen the hub RBPs for pRCC prognosis. We identified 251 up-regulated and 129 down-regulated RBPs, and filtered out seven hub RBPs, namely, SRSF8, CD3EAP, HBS1L, ELAC2, MRPL34, NOP2 and IGF2BP2, for their prognostic relevance. A prognostic risk score model for overall survival of pRCC patients was constructed based on the seven hub RBPs. Further analysis showed that the low-risk group had higher survival rate than the high-risk group in both training and validation cohorts. The predictive accuracy was verified in the Human Protein Atlas database.In addition, we introduced the GSE15641 dataset from the Gene Expression Omnibus (GEO) database for independent external validation, and confirmed the expression levels of HBS1L, MRPL34 and IGF2BP2 through real-time quantitative PCR (RT-qPCR) and Western blotting (WB) using human renal tubular epithelial cell line HK-2 and human papillary renal cell carcinoma cell line Caki-2. In pRCC, CD3EAP was significantly elevated, while ELAC2, IGF2BP2, MRPL34, SRSF8 and HBS1L were significantly reduced. There was no significant difference between tumor and normal tissues in NOP2 expression. Risk score and tumor grade were independent prognostic factors associated with overall survival. In addition, we established a nomogram based on the seven prognostic RBPs to help predict overall survival at 1-3 years. In conclusion, seven differentially expressed hub RBPs were identified as potential prognostic biomarkers for pRCC. Our prognostic model might serve as a support for better treatment decision-making. Our work could provide potential new ideas for diagnosis and research on targeted drugs for pRCC.

Bioinformatics↗

PubMed2026

SHMT2: a Metabolic and Immune Biomarker of Aggressive Lung Adenocarcinoma.

Serine/glycine-one-carbon (SGOC) metabolism is frequently altered in lung adenocarcinoma (LUAD), but its relationship to tumor behavior and predicted immunotherapy responsiveness remains incompletely defined. Metabolomic profiling of 23 paired LUAD and adjacent normal lung tissues was performed using internal extractive electrospray ionization mass spectrometry. Transcriptomic and clinical data from The Cancer Genome Atlas LUAD cohort (TCGA-LUAD) were analyzed to assess SHMT2 expression, prognosis, differentially expressed genes, and immune-related features. Predicted response to immune checkpoint blockade was evaluated using Tumor Immune Dysfunction and Exclusion (TIDE) and The Cancer Immunome Atlas (TCIA), and drug sensitivity was inferred using oncoPredict. Single-cell RNA-seq data were used to examine the cellular distribution of SHMT2. Experimental validation included quantitative reverse-transcription PCR (RT-qPCR), western blotting, Human Protein Atlas (HPA) immunohistochemistry, and short hairpin RNA (shRNA)-mediated SHMT2 knockdown followed by proliferation, wound-healing and colony formation assays. Metabolomic analysis identified glycine, serine, and threonine metabolism as a prominently altered pathway in LUAD. SHMT2 was upregulated in LUAD and associated with worse overall survival and adverse clinicopathological features. SHMT2-high tumors displayed enrichment of cell-cycle and SGOC-related transcriptional programs, lower immune and stromal scores, and reduced predicted responsiveness to immunotherapy. Single-cell analysis showed relative enrichment of SHMT2 expression in B cell populations. In vitro, SHMT2 was overexpressed in LUAD cells, and its knockdown suppressed proliferation, migration, and clonogenic growth. Collectively, SHMT2 is associated with SGOC metabolic reprogramming, aggressive tumor phenotypes, and an immune-disadvantaged state in LUAD, supporting its potential relevance as a biomarker; therapeutic targeting requires additional pharmacologic and in vivo validation.

Humans↗

PubMed2026

TCGA-based identification of prognostic biomarkers and candidate traditional Chinese medicine compounds in papillary thyroid carcinoma: An observational study.

This study aimed to identify prognostic genes associated with papillary thyroid carcinoma (PTC) and explore candidate traditional Chinese medicine (TCM) compounds using integrated bioinformatics and molecular docking. In this observational study, PTC gene expression profiles and clinical data were obtained from The Cancer Genome Atlas. Differentially expressed genes were screened using differential-expression sequencing (DESeq2), followed by protein-protein interaction network analysis to identify hub genes. Their expression, diagnostic value, immune relevance, prognostic significance, protein-level validation, and single-cell distribution were assessed using gene expression profiling interactive analysis, receiver operating characteristic analysis, immune infiltration analysis, Kaplan-Meier survival analysis, the human protein atlas, and single-cell RNA-sequencing data. Candidate TCM compounds were predicted using symptom mapping (SymMap) and the TCM Systems Pharmacology Database and Analysis Platform, and molecular docking was performed to evaluate potential ligand-target interactions. Five hub genes, colony-stimulating factor 2, apolipoprotein E, fibronectin 1 (FN1), collagen type I alpha 1 chain (COL1A1), and intercellular adhesion molecule 1, were identified and found to be significantly upregulated in PTC tissues, with diagnostic value in receiver operating characteristic analysis. Immune infiltration analysis showed associations with macrophages, dendritic cells, and T helper 1 cells, whereas single-cell analysis demonstrated heterogeneous expression across immune and stromal cell populations, including fibroblasts. Higher FN1 and COL1A1 expression was associated with poorer outcomes. Immunohistochemistry supported the expression patterns, while single-cell analysis provided exploratory cell-type-level context for the cellular distribution of selected genes. Ginseng and Smilax glabra were predicted as common candidate TCMs, and docking suggested favorable binding between their active compounds and selected hub targets. Colony-stimulating factor 2, apolipoprotein E, FN1, COL1A1, and intercellular adhesion molecule 1 may be biologically relevant hub genes in PTC, while FN1 and COL1A1 may have prognostic value. Predicted TCM compounds provide preliminary computational evidence for possible compound-target interactions, requiring experimental and clinical validation.

Female↗

PubMed2025

COL5A1 in the tumor microenvironment predicts the prognosis of head and neck cancer.

ObjectivesThis study aims to investigate the significance of tumor microenvironment (TME)-related genes and signal transduction pathways in head and neck cancer (HNC).MethodsGene expression and clinical data of HNC patients were obtained from the Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened through a multi-step filtration approach to obtain candidate predictors. The biological role of COL5A1 in HNC was verified through rigorous bioinformatic analysis, experimental validation using quantitative real-time PCR (qRT-PCR), immunohistochemical (IHC) analysis from HNC samples, and IHC data from the Human Protein Atlas (HPA) database.ResultsCOL5A1 was significantly upregulated in HNC tissues and cell lines. High COL5A1 expression was significantly associated with advanced tumor grade (P < .05) and shorter survival (TCGA: P < .001; GSE42743: P = .004). COL5A1 was an independent prognostic indicator (univariate analysis: HR = 1.324, P = .001; Multivariate analysis: HR = 1.326, P = .005). It was enriched in pathways related to tumor invasion and immune responses, and its expression was associated with decreased levels of CD8+ T cells and increased levels of macrophages and neutrophils. Spatial distribution analysis revealed higher expression at the tumor's leading edge (vs. tumor core: P < .001). COL5A1 expression is associated with tumor stage, with more pronounced expression in advanced-stage tumors.ConclusionCOL5A1 represented a novel potential prognostic indicator and therapeutic target in an HNC database sample, as its expression is closely linked to tumor progression, immune cell infiltration, and adverse clinical outcomes. These findings, primarily derived from squamous cell carcinoma-dominated cohorts, warrant further functional validation.

Humans↗

PubMed2025

A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma.

BACKGROUND: Kidney Renal Clear Cell Carcinoma (KIRC) is a prevalent urinary malignancies worldwide. Glycosylation is a key post-translational modification that is essential in cancer progression. However, its relationship with prognosis, tumour microenvironment (TME), and treatment response in KIRC remains unclear. METHOD: Expression profiles and clinical data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering, Cox regression, and LASSO regression analyses were conducted to develop an optimal glycogene-related signature. The prognostic relevance of this molecular signature was rigorously analyzed, along with its connections to tumour microenvironment (TME), tumour mutation burden, immune checkpoint activity, cancer-immunity cycle regulation, immunomodulatory gene expression patterns, and therapeutic response profiles. Validation was performed using real-world clinical specimens, quantitative PCR (qPCR), and immunohistochemistry (IHC), supported by cohort analyses from the Human Protein Atlas (HPA) database. RESULTS: A glycogene-associated prognostic scoring system was established to categorize patients into risk-stratified subgroups. Patients in the high-risk cohort exhibited significantly poorer survival outcomes (p < 0.001). By incorporating clinicopathological variables into this framework, we established a predictive nomogram demonstrating strong calibration and a concordance index (C-index) of 0.78. The high-risk subgroup displayed elevated immune infiltration scores (p < 0.001), upregulated expression of immune checkpoint-related genes (p < 0.05), and an increased frequency of somatic mutations (p = 0.043). The risk score positively correlated with cancer-immunity cycle activation and immunotherapy-related signals. The high-risk groups also showed associations with T cell exhaustion, immune-activating genes, chemokines, and receptors. Drug sensitivity analysis revealed that low-risk patients were more sensitive to sorafenib, pazopanib, and erlotinib, whereas high-risk individuals responded better to temsirolimus (p < 0.01). qPCR and IHC analyses consistently revealed distinct expression patterns of MX2 and other key genes across the risk groups, further corroborated by the HPA findings. CONCLUSION: This glycogene-based signature provides a robust tool for predicting prognosis, TME characteristics, and therapeutic responses in KIRC, offering potential clinical utility in patient management.

Humans↗

PubMed2026

PSMA1, PSMA5, and PSMB2 serve as prognostic biomarkers and are correlated with tumor-infiltrating leukocytes in HCC.

Hepatocellular carcinoma (HCC) ranks as the third leading cause of cancer-related death. Proteasome (PSM) is the main intracellular proteolytic system in higher eukaryotic cells. It has been reported to be involved in the tumor's onset, metabolism, and survival, and it has been recognized as a therapeutic target for many human cancers. The 20S proteasome subunits, specifically proteasome 20S subunit alpha 1 (PSMA1), proteasome 20S subunit alpha 5 (PSMA5), and proteasome 20S subunit beta 2 (PSMB2), are overexpressed in various malignancies, including HCC. Nevertheless, the exact role of these genes in HCC prognosis remains only partially understood. Moreover, a reliable predictive biomarker for HCC is essential for supporting the implementation of personalized therapies. Therefore, this study employed a comprehensive bioinformatics approach, integrating data from cBioPortal, Human Protein Atlas (HPA), Oncomine, STRING Viruses, Kaplan-Meier plotter, and other established high-throughput databases and tools. The current study thoroughly examined the expression levels, methylation, and genomic alterations of PSM and their correlation with tumor-infiltrating leukocytes. PSMA1, PSMA5, and PSMB2 are overexpressed in various cancers, including HCC, and their expression levels are associated with tumor grade and stage. The abundance of these genes is linked to diminished DNA methylation levels and genome alterations. Moreover, there was a significant association between the expression levels of these genes and poor prognosis and immune cell infiltration. In conclusion, this study proposes PSMA1, PSMA5, and PSMB2 as biomarkers for HCC.

Humans↗

PubMed2026

High NKAP expression predicts poor prognosis of breast cancer patients.

NF-κB activating protein (NKAP) plays important roles in various cancers, including breast cancer. However, its expression and prognosis value in breast cancer remains uncertain. Gene expression profiling interactive analysis, Human protein atlas database, and University of Alabama at Birmingham Cancer data analysis portal database were used to predict the expression and prognostic value of NKAP in breast cancer. Immunohistochemistry, quantitative real time polymerase chain reaction (qRT-PCR) and western blot were performed to detect NKAP expression. The effects of NKAP on cell proliferation, migration and drug sensitivity were investigated in MDA-MB-231 and SK-BR-3 cells. NKAP protein expression differed in breast cancer tissues and paraneoplastic tissues based on the cancer genome atlas data. The high NKAP expression was significantly correlated with a poor prognosis in breast cancer patients. The results of immunohistochemistry, western blot assay, and qRT-PCR proved that NKAP was highly expressed in breast cancer tissues compared with paraneoplastic tissues. In addition, qRT-PCR results showed that high expression of NKAP was significantly correlated with the larger tumor size and higher TNM stage. Moreover, knockdown of NKAP significantly inhibited the proliferation, migration, and enhanced drug sensitivity of MDA-MB-231 and SK-BR-3 cells. NKAP is highly expressed in breast cancer tissues, and its high expression is closely associated with poor prognosis. NKAP also promotes proliferation, migration, and inhibits drug sensitivity of breast cancer cells.

Humans↗

PubMed2026

Human Wings Apart-Like Protein as a Serum Diagnostic Biomarker in Cervical Cancer: An Integrative Bioinformatics Analysis with Serum Validation.

Cervical cancer remains a major threat to women's health worldwide, and reliable serum biomarkers for early detection and therapeutic stratification remain limited. Human wings-apart-like (hWAPL) protein has been implicated in cervical carcinogenesis, but its diagnostic and clinical value has not been fully elucidated. To address this gap, this study integrated public multi-omics datasets, including The Cancer Genome Atlas, GEPIA2, the Human Protein Atlas, and single-cell transcriptomic data, to characterize hWAPL expression, clinicopathological associations, immune infiltration, co-expression networks, post-translational modifications, and drug sensitivity predictions. These findings were evaluated in an independent single-center serum cohort comprising 89 patients with histologically confirmed cervical squamous cell carcinoma and 89 healthy female controls. Serum hWAPL and squamous cell carcinoma antigen (SCC) levels were measured, and diagnostic performance was assessed by receiver operating characteristic curve analysis. In silico, hWAPL was broadly upregulated across multiple malignancies, particularly cervical cancer, enriched in malignant epithelial cells and monocytes/macrophages, and associated with shorter progression-free interval, predicted reduced sensitivity to cisplatin, paclitaxel, and 5-fluorouracil, and predicted sensitivity to MCL-1 and Wee1 inhibitors. In the serum cohort, hWAPL levels were significantly higher in patients than controls and discriminated cervical cancer with an area under the curve of 0.961, exceeding SCC alone. Combining hWAPL with SCC further improved diagnostic performance (area under the curve, 0.974; sensitivity, 93.3%; specificity, 95.5%). These findings suggest that serum hWAPL is a potential novel diagnostic biomarker for cervical squamous cell carcinoma whose performance is enhanced by SCC, whereas the observed associations with chemoresistance and immune microenvironment remodeling are hypothesis-generating and require experimental confirmation.

Humans↗

PubMed2026

Spatial proteomic mapping of the human and mouse retina using IBEX.

We generated a comparative spatial proteomic atlas of the human and mouse retina using a highly multiplexed immunohistochemistry technique called iterative bleaching extends multiplexity (IBEX). We refined the IBEX workflow by integrating an antibody dissociation option alongside chemical bleaching. This dual strategy enabled removal of the entire antibody complex, permitting the flexible use of antibodies from the same host species across iterative cycles. We coupled this workflow with super-resolution imaging via deconvolution and applied it to the retina of healthy humans and WT mice and the Crb1rd8 mouse model. We successfully imaged over 25 protein markers on human and mouse tissue sections, generating spatial atlases of the major retinal cell populations. Cross-species protein expression was compared to scRNA-seq datasets to identify protein and transcript disparities. Super-resolution IBEX delineated the ultrastructural features of the outer limiting membrane (OLM), identifying CD44 as a core structural component tightly colocalized with a highly organized F-actin belt within Müller glial endfeet. Using the Crb1rd8 mouse model, disruption of this complex was spatially associated with rosette formation and OLM structural failure. In summary, spatial proteomic atlases of the human and mouse retina were used to reveal insights into the arrangement of major retinal cell populations and OLM structure.

Animals↗

PubMed2026

GWAS Meta-analysis Identifies Novel Associated Loci and Points to Causal Tissues in Central Serous Chorioretinopathy.

OBJECTIVE: To define CSC genetic architecture and identify implicated ocular tissues, cell types, genes, and circulating proteins. DATA SOURCES: Genome-wide data were assembled from FinnGen, All of Us, Mass General Brigham Biobank, Million Veteran Program, and a Dutch chronic CSC cohort. Serum protein quantitative trait loci, human single-cell ocular atlases, and UK Biobank macular optical coherence tomography (OCT) imaging were used for downstream analyses. STUDY SELECTION: Five European-ancestry cohorts with genome-wide data and cohort-specific CSC case-control definitions were included, comprising 2,584 cases and 1,044,455 controls. Variants present in at least 2 cohorts were meta-analyzed. DATA EXTRACTION AND SYNTHESIS: Cohort-level GWASs were adjusted for age, age squared, sex, genotyping array or batch, and 10 genetic principal components, then combined using fixed-effects inverse-variance meta-analysis. Post-GWAS analyses included gene prioritization, colocalization, Mendelian randomization, single-cell disease-relevance scoring, and testing of a CSC genetic risk score in UK Biobank OCT images. MAIN OUTCOMES AND MEASURES: Genome-wide significant CSC loci, effector genes and proteins, tissue and cell-type enrichment, and CSC-relevant OCT abnormalities. RESULTS: Across 11,068,938 variants, 10 loci reached genome-wide significance (P < 5 × 10-8), including 3 novel loci near TGFB1, LINC00551, and LOC105375630 and 7 replicated loci near CFH, CD46, NOTCH4, PREX1, PTPRB, GATA5, and TNFRSF10A. Integrative analyses prioritized 10 candidate effector genes. Colocalization and Mendelian randomization implicated circulating TNFRSF10A, TGFB1, and CASP10 levels. Single-cell analyses localized genetic risk to sclera (P = 2.0 × 10-4) and vascular endothelial cells (P = 4.0 × 10-4), with fibroblast enrichment. In UK Biobank, OCT abnormalities were more frequent in the top vs bottom 1% of CSC genetic risk (18 of 109 [16.5%] vs 8 of 134 [6.0%]; odds ratio, 4.05; 95% CI, 1.65-10.87; P = .002). CONCLUSIONS AND RELEVANCE: In this GWAS meta-analysis, CSC susceptibility localized predominantly to scleral and vascular biology rather than primary retinal pigment epithelial dysfunction. These findings support CSC as a sclerovascular disorder and nominate complement regulation, endothelial signaling, and extracellular matrix pathways for future study.

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