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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.
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A Novel Ferroptosis-Related Gene Model for Overall Survival Predictions of Bladder Urothelial Carcinoma Patients.
INTRODUCTION: Bladder cancer is the most common urinary tract malignancy, and 90% of bladder tumors are urothelial cell carcinomas. Ferroptosis is a new form of cell death discovered in recent years, which is an iron-dependent form of cell death characterized by the lethal intracellular accumulation of lipid-based reactive oxygen species. Ferroptosis is considered to be a double-edged sword for cancer and cancer therapy. MATERIALS AND METHODS: In the current study, expression profiles of bladder cancer (BLCA) specimens were obtained from The Cancer Genome Atlas (TCGA) RNA-Seq database. Ferroptosis-related genes were downloaded from the FerrDb website. The ferroptosis-related differentially expressed genes (DEGs) which were related to overall survival (OS) were first identified. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression methods were utilized to develop a ferroptosis-related prognostic model (FRPM). In addition, a nomogram model based on FRPM and clinicopathological features was successfully constructed and validated. In addition, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) methods were utilized in this study in order to compare the DEGs between the high-risk and low-risk groups. This study also adopted RT-qPCR, CCK-8 assay, and scratch assay methods to perform experimental verification processes. RESULTS AND DISCUSSION: A 7-gene FRPM was constructed in this research investigation in order to stratify the patients into two groups according to their risk scores. The results of this study's survival analysis and time-dependent receiver operating characteristic (ROC) analysis demonstrated that the model had achieved a stable performance level. This multivariate Cox regression results revealed that the FRPM was an independent prognostic predictor for the OS of BLCA patients and the results were displayed using a nomogram. In addition, the ROC analysis, concordance index (C-index), calibration plots, and decision curve analysis (DCA) curves further indicated that this study's nomogram method enabled valuable prediction results. The functional enrichment analysis results suggested that the DEGs between the high- and low-risk groups played vital roles in the progression of the ferroptosis. Also, the ssGSEA indicated that the immune status was different between the two groups. This study found that the RT-qPCR results had confirmed the differential expressions of DEGs in the tissue samples, and the CCK-8 assay and scratch assay results confirmed the promoting effects of SCD on the proliferation and migration of tumor cells. CONCLUSIONS: This study defined a novel prognostic model of seven ferroptosis-related genes, which proved to be independently associated with the OS of BLCA. A nomogram method was developed for the purpose of providing further insight into the accurate predictions of BLCA prognoses.
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Prognostic value and immunotherapy analysis of immune cell-related genes in laryngeal cancer.
BACKGROUND: Laryngeal cancer (LC) is a prevalent head and neck carcinoma. Extensive research has established a link between immune cells in the tumor microenvironment (TME) and cancer progression, as well as responses to immunotherapy. This study aims to develop a prognostic model based on immune cell-related genes and examine the TME in LC. METHODS: RNA-seq data for LC were sourced from The Cancer Genome Atlas (TCGA), and GSE27020 and GSE51985 datasets were retrieved from the Gene Expression Omnibus (GEO) database. Key genes were identified through the intersection of differentially expressed genes (DEGs) between normal and LC samples and module genes derived from weighted gene co-expression network analysis (WGCNA), followed by functional enrichment analysis. The prognostic risk model was constructed using univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) analyses. Gene Set Variation Analysis (GSVA) was subsequently performed for hallmark and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses in high- and low-risk groups. Immune infiltration analysis between risk groups was conducted via Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and single sample gene set enrichment analysis (ssGSEA). Finally, the relationship between the risk model and immunotherapy response was explored. RESULTS: A total of 124 key genes were identified through the overlap analysis, predominantly enriched in GO terms such as defense response to viruses and regulation of response to biotic stimuli, as well as KEGG pathways related to phagosome and Epstein-Barr virus infection. Machine learning indicated that the optimal prognostic model was constructed from two biomarkers, RENBP and OLR1. GSVA revealed that in the high-risk group, epithelial-mesenchymal transition and ECM-receptor interaction were the most significantly enriched pathways, while autoimmune thyroid disease, ribosome, and oxidative phosphorylation predominated in the low-risk group. Additionally, the stromal score was significantly higher in the high-risk group, while CD8+ T cells, cytolytic activity, inflammation promotion, and T cell co-stimulation were elevated in the low-risk group. Tumor Immune Dysfunction and Exclusion (TIDE) analysis showed higher TIDE and exclusion scores in the high-risk group, whereas the CD8 score was higher in the low-risk group. Finally, CD274 (PD-L1) expression was significantly elevated in the low-risk group. CONCLUSIONS: This study identified two key prognostic biomarkers, RENBP and OLR1, and characterized TME differences across risk groups, offering novel insights into the diagnosis and treatment of LC.
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Induction of the p21/CDK6 pathway and alteration of the immune microenvironment by the stem cell marker CBX3 in melanoma.
BACKGROUND: As one of the stem cell markers, chromobox protein homolog 3 (CBX3) participates in multiple signaling pathways that affect the progression of various tumors. However, the role of CBX3 in melanoma remains unclear, and the mechanisms by which CBX3 may regulate immunotherapy outcome remain largely unknown. METHODS: We used the Cancer Genome Atlas, Genotype-Tissue Expression portal, and Gene Expression Omnibus database to estimate CBX3 expression and its prognostic effect in melanoma. The role of CBX3 in proliferation and migration of melanoma cells were examined using the CCK8, cloning, wound healing, and transwell assays. The effect of CBX3 on melanoma tumorigenesis was assessed using an in vivo animal model. The role of CBX3 in cell cycle was examined using flow cytometry, and expression levels of cell cycle-related genes and proteins in cells with altered CBX3 levels were analyzed using qPCR and western blotting. The function of CBX3 in the immune microenvironment of melanoma was studied using single-cell RNA sequencing and public databases. RESULTS: We found that CBX3 was highly expressed in melanoma with poor prognosis. CBX3 promoted the proliferation and migration of melanoma cells in vivo and in vitro. Functional analysis revealed that CBX3 regulates cell cycle, as it accelerated the G1 to S transition, decreased p21 expression, and increased CDK6 expression. Finally, single-cell sequencing and immune-related assays showed that CBX3 is immunogenic and can change the immune microenvironment of melanoma. CONCLUSIONS: We conclude that the stem cell marker, CBX3 activates the p21/CDK6 pathway and alters the immune microenvironment in melanoma.
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Biological Functions and Prognostic Value of Ferroptosis-Related Genes in Bladder Cancer.
Background: Every year, nearly 170,000 people die from bladder cancer worldwide. A major problem after transurethral resection of bladder tumor is that 40-80% of the tumors recur. Ferroptosis is a type of regulatory necrosis mediated by iron-catalyzed, excessive oxidation of polyunsaturated fatty acids. Increasing the sensitivity of tumor cells to ferroptosis is a potential treatment option for cancer. Establishing a diagnostic and prognostic model based on ferroptosis-related genes may provide guidance for the precise treatment of bladder cancer. Methods: We downloaded mRNA data in Bladder Cancer from The Cancer Genome Atlas and analyzed differentially expressed genes based on and extract ferroptosis-related genes. We identified relevant pathways and annotate the functions of ferroptosis-related DEGs using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and Gene Ontology functions. On the website of Search Tool for Retrieving Interacting Genes database (STRING), we downloaded the protein-protein interactions of DEGs, which were drawn by the Cytoscape software. Then the Cox regression analysis were performed so that the prognostic value of ferroptosis-related genes and survival time are combined to identify survival- and ferroptosis-related genes and establish a prognostic formula. Survival analysis and receiver operating characteristic curvevalidation were then performed. Risk curves and nomograms were generated for both groups to predict survival. Finally, RT-qPCR was applied to analyze gene expression. Results: Eight ferroptosis-related genes with prognostic value (ISCU, NFE2L2, MAFG, ZEB1, VDAC2, TXNIP, SCD, and JDP2) were identified. With clinical data, we established a prognostic model to provide promising diagnostic and prognostic information of bladder cancer based on the eight ferroptosis-related genes. RT-qPCR revealed the genes that were differentially expressed between normal and cancer tissues. Conclusion: This study found that the ferroptosis-related genes is associated with bladder cancer, which may serve as new target for the treatment of bladder cancer.
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THAP3 recruits SMYD3 to OXPHOS genes and epigenetically promotes mitochondrial respiration in hepatocellular carcinoma.
Mitochondria harbor the oxidative phosphorylation (OXPHOS) system to sustain cellular respiration. However, the transcriptional regulation of OXPHOS remains largely unexplored. Through the cancer genome atlas (TCGA) transcriptome analysis, transcription factor THAP domain-containing 3 (THAP3) was found to be strongly associated with OXPHOS gene expression. Mechanistically, THAP3 recruited the histone methyltransferase SET and MYND domain-containing protein 3 (SMYD3) to upregulate H3K4me3 and promote OXPHOS gene expression. The levels of THAP3 and SMYD3 were altered by metabolic cues. They collaboratively supported liver cancer cell proliferation and colony formation. In clinical human liver cancer, both of them were overexpressed. THAP3 positively correlated with OXPHOS gene expression. Together, THAP3 cooperates with SMYD3 to epigenetically upregulate cellular respiration and liver cancer cell proliferation.
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Pan-cancer profiling of FZD2 as a prognostic biomarker: integrative multi-omics analysis with experimental validation and functional characterization in gastric cancer.
BACKGROUND: Frizzled class receptor 2 (FZD2), is a critical protein in the Wnt signaling pathway, which plays significant roles in various cancers. However, its role in cancer progression, prognosis, and diagnosis remains largely unexplored. This study investigates the correlation between FZD2 expression and clinical outcomes, as well as its underlying molecular mechanisms in pan-cancer. METHODS: A comprehensive bioinformatic analysis was performed using pan-cancer data from The Cancer Genome Atlas (TCGA), which included 33 cancer types. Gene set enrichment analysis (GSEA) was conducted to explore functional pathways, while a protein-protein interaction (PPI) network was constructed to further elucidate the role of FZD2 in tumor biology. The relationship between FZD2 expression and immune cell infiltration across 22 categories was assessed using CIBERSORT. Additionally, single-cell analysis was employed to examine FZD2 expression levels across different cell types. To investigate the functional impact of FZD2, loss-of-function experiments were carried out in gastric cancer cell lines using siRNA-mediated knockdown. Subsequent assays, including Polymerase Chain Reaction (PCR), Western blotting (WB), Cell Counting Kit-8 (CCK8), Flow Cytometry, wound healing, and transwell migration and invasion assays, were performed to assess cellular responses. A subcutaneous gastric cancer xenograft model was established in nude mice to investigate the effect of FZD2 knockdown on tumor growth in vivo. RESULTS: Our analysis revealed significant upregulation of FZD2 in multiple malignancies, including stomach adenocarcinoma (STAD), bladder cancer (BLCA), and cholangiocarcinoma (CHOL). FZD2 expression was correlated with various cancer characteristics, including stemness score, matrix score, immune score, tumor mutational burden (TMB), microsatellite instability (MSI), RNA modification genes, and drug sensitivity. Notably, FZD2 was associated with altered sensitivity to several anticancer agents, suggesting its role in modulating treatment responses. FZD2 knockdown was demonstrated by both in vitro and in vivo experiments to suppress tumor cell proliferation, migration, and invasion in gastric cancer cell lines, indicating its critical role in tumor progression. Furthermore, FZD2 exhibited significant correlations with other Wnt pathway genes (e.g., Wnt2, Wnt4, Wnt5B), indicating a complex interaction network contributing to tumorigenesis. CONCLUSION: FZD2 is widely upregulated in various tumor types, with its expression closely associated with key clinical outcomes, including overall survival, disease-specific survival, disease-free interval, as well as tumor mutations, drug sensitivity, immune cell infiltration, and immunotherapy-related biomarkers such as TMB and MSI. These findings highlight the pivotal role of FZD2 in cancer prognosis and treatment, offering potential for novel therapeutic approaches and the development of personalized medicine strategies in oncology.
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Identification and Characterization of Key Differentially Expressed Genes Associated With Metronomic Dosing of Topotecan in Human Prostate Cancer.
Repetitive, low-dose (metronomic; METRO) drug administration of some anticancer agents can overcome drug resistance and increase drug efficacy in many cancers, but the mechanisms are not understood fully. Previously, we showed that METRO dosing of topotecan (TOPO) is more effective than conventional (CONV) dosing in aggressive human prostate cancer (PCa) cell lines and in mouse tumor xenograft models. To gain mechanistic insights into METRO-TOPO activity, in this study we determined the effect of METRO- and CONV-TOPO treatment in a panel of human PCa cell lines representing castration-sensitive/resistant, androgen receptor (+/-), and those of different ethnicity on cell growth and gene expression. Differentially expressed genes (DEGs) were identified for METRO-TOPO therapy and compared to a PCa patient cohort and The Cancer Genome Atlas (TCGA) database. The top five DEGs were SERPINB5, CDKN1A, TNF, FOS, and ANGPT1. Ingenuity Pathway Analysis predicted several upstream regulators and identified top molecular networks associated with METRO dosing, including tumor suppression, anti-proliferation, angiogenesis, invasion, metastasis, and inflammation. Further, the top DEGs were associated with increase survival of PCa patients (TCGA database), as well as ethnic differences in gene expression patterns in patients and cell lines representing African Americans (AA) and European Americans (EA). Thus, we have identified candidate pharmacogenomic biomarkers and novel pathways associated with METRO-TOPO therapy that will serve as a foundation for further investigation and validation of METRO-TOPO as a novel treatment option for prostate cancers.