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N6-methyladenosine (m6A) RNA methylation regulator SNRPC is a prognostic biomarker and is correlated with immunotherapy in hepatocellular carcinoma.
BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world, and due to its complex pathogenic factors, its prognosis is poor. N6-methyladenosine (m6A) RNA methylation plays an important role in the tumorigenesis, progression, and prognosis of many tumors. The m6A RNA methylation regulator small nuclear ribonucleoprotein polypeptide C (SNRPC), which encodes one of the specific protein components of the U1 small nuclear ribonucleoprotein (snRNP) particle, has been proven to be related to the prognosis of patients with HCC. However, the effect of SNRPC on the tumor microenvironment and immunotherapy in HCC remains unclear. CASE PRESENTATION: The HCC RNA-seq profiles in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, including 421 LIHC and 440 LIRI-JP samples, respectively, were used in this study. Both the expression of SNRPC in HCC was upregulated in the TCGA and ICGC databases compared to normal tissues. Next, the expression of SNRPC was validated as a risk factor for prognosis by Kaplan-Meier analysis and employed to establish a nomogram with T pathologic stage. By gene set variation (GSVA) analysis and gene set enrichment (GSEA) analysis, we found that SNRPC was mainly related to protein metabolism and the immune process. Furthermore, the estimation of stromal and immune cells in malignant tumor tissues using expression (ESTIMATE), microenvironment cell population counter (MCP-counter), and single sample GSEA (ssGSEA) algorithms revealed that the high-SNRPC group had a lower stromal score, lower abundance of endothelial cells and fibroblasts, and lower immune infiltration. Ultimately, a tumor immune dysfunction and exclusion (TIDE) analysis revealed that patients in the low-SNRPC group may be more sensitive to immune checkpoint inhibitor therapy. CONCLUSION: SNRPC could serve as a promising prognostic and immunotherapeutic marker in HCC and might contribute to new directions and strategies for HCC treatment.
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NCBP2 predicts the prognosis and the immunotherapy response of cancers: a pan-cancer analysis.
BACKGROUND: The cap-binding complex (CBC) plays a crucial role in facilitating gene expression by safeguarding mRNA from nonsense-mediated decay, promoting mRNA splicing, 3'-end processing, and facilitating nuclear export. Nevertheless, the precise biological functions and clinical implications of CBC in cancer remain ambiguous, necessitating further investigation for clarification. METHODS: The present study utilized the cBioPortal database to investigate the genetic alterations of nuclear cap binding protein subunit 2 (NCBP2) in pan-cancer. The Cancer Genome Atlas (TCGA) and online web tools were employed to analyze the correlation between NCBP2 and prognosis, genome instability, immune infiltration, immune response, cancer stemness, and chemotherapeutic efficacy in pan-cancer. Furthermore, the expression of NCBP2 was confirmed by immunohistochemistry (IHC) and functional analysis at the single-cell level was conducted using the CancerSEA database. RESULTS: NCBP2 exhibited distinct genetic alterations in pan-cancer with an increased expression in 24/32, while decreased expression in 3/32, types of cancers. IHC confirmed the aberrant expression of NCBP2 in lung squamous cell carcinoma (LUSC), pancreatic adenocarcinoma (PAAD), kidney renal papillary cell carcinoma (KIRP) and kidney renal clear cell carcinoma (KIRC). NCBP2 was correlated with overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) in various cancers. Importantly, it was identified as a risk factor for OS, DSS and PFS in PAAD and uterine corpus endometrial carcinoma (UCEC). Gene Set Enrichment Analysis (GSEA) demonstrated that elevated NCBP2 was linked to immune and proliferation related pathways across multiple cancer types. Furthermore, a negative association between NCBP2 and stromal score, immune score, and ESTIMATE score was detected, and a positive correlation was observed between NCBP2 and diverse immune cells as well as stemness-indexes in the majority of cancer types. Drug sensitivity analysis revealed that drugs associated with NCBP2 primarily targeted DNA replication, chromatin histone methylation, ABL signaling, cell cycle, and PI3K signaling. Additionally, an examination at the single-cell level indicated that NCBP2 was positively correlated with cell cycle progression, DNA damage, DNA repair, invasion, and stemness in most cancer types, while negatively correlated with apoptosis, inflammation, and hypoxia in certain cancers. CONCLUSION: In this study, we revealed the correlation of NCBP2 with prognosis, microenvironment and stemness, indicating that NCBP2 might be a potential therapeutic target for more effective and personalized therapy strategies in pan-cancer.
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Identification of prognostic biomarkers for endometrioid endometrial carcinoma based on the miRNA and mRNA co-expression network regulated by estradiol.
BACKGROUND: Endometrioid Endometrial Carcinoma (EEC), an estradiol-related disease, remains a serious health threat to women because of its high incidence and trend of rejuvenation. Accumulating evidence has highlighted that microRNAs (miRNAs) and messenger RNAs (mRNAs) play important roles in various biological processes involved in the pathogenesis of EEC. This study aimed to identify the potential prognostic biomarkers associated with EEC regulated by estradiol. METHODS: RNA expression profiles of EEC were obtained from The Cancer Genome Atlas database (n = 408) and the original sequencing, which was performed on endometrial cancer Ishikawa cells treated with 250 nM estradiol (n = 3), 50 nM estradiol (n = 3) or control (n = 3). The TargetScan database was used to predict the target genes of prognosis-related differentially expressed miRNAs (DEMs). Subsequently, functional enrichment analysis and topological analysis were performed on the overlaps of target genes and differentially expressed mRNAs (DEGs). Kaplan-Meier analysis was used to predict prognosis-related target genes to identify prognostic biomarkers and cell population landscapes, and gene expression analysis was performed to locate prognosis-related DEGs based on single-cell transcriptomic sequencing data from the NCBI Sequence Read Archive database. RESULTS: Four estradiol-related DEGs were associated with prognosis, and 235 overlapping target DEGs were screened and incorporated into the functional enrichment analysis and protein-protein interaction network visualization studies. Additionally, SACS and GPR157 were identified as potential biomarkers for EEC prognosis through survival analyses. Furthermore, single-cell transcriptome data were analyzed to show changes in gene expression levels in specific cell types. CONCLUSIONS: This study demonstrates that miR-142-5p-SACS and miR-30a-5p-GPR157, which are regulated by estradiol, may hold promise as diagnostic and prognostic biomarkers and novel therapeutic targets for EEC.
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Development and validation of a prognostic model for efferocytosis-associated genes in cervical squamous cell carcinoma.
BACKGROUND: Genes associated efferocytosis play a critical role in tumor invasion, metastasis, and clinical outcomes in several malignancies. However, their prognostic relevance in cervical squamous carcinoma (CESC) is currently unclear. METHODS: Data from the Cancer Genome Atlas (TCGA) database were used to create the TCGA-CESC cohort. Additional CESC-related datasets (GSE44001 and GSE168652) were retrieved from the Gene Expression Omnibus database. Single-cell analysis of the GSE168652 dataset was conducted to identify differentially expressed genes (DEGs), associated with efferocytosis (ER-DEGs). CESC samples from the TCGA cohort were classified into clusters, and prognosis-related DEGs (PR-DEGs) were identified by comparing these clusters. The intersection of ER-DEGs and PR-DEGs generated a subset of prognosis-efferocytosis related DEGs (PER-DEGs). Subsequently, a risk model was developed using univariate Cox regression and least absolute shrinkage and selection operator analysis. Independent prognostic factors were further analyzed using Cox regression analysis. Functional pathways were examined through gene set enrichment analysis. RESULTS: A total of 15 cell clusters were identified from the GSE168652 dataset and categorized into seven distinct cell types. Comparative analysis indicated 774 ER-DEGs between groups with high and low ERG expression levels. From these, 332 PER-DEGs were identified. A prognostic risk model was constructed based on seven characteristic genes: ITGA5, SNRPF, EGLN1, NDUFB7, NDUFA2, SRGAP3, and PCNA. Risk score and pathologic-N emerged as independent prognostic factors. These genes were found to be associated with multiple pathways implicated in the pathogenesis of CESC. CONCLUSION: Seven efferocytosis-related prognostic genes were identified as prognostic markers for CESC, providing a scientific basis for further research on their role in disease progression.
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Metabolic reprogramming and prognostic insights in molecular landscapes driven by glycolysis in ovarian cancer.
Ovarian cancer (OC) is a highly fatal gynecological malignancy primarily attributable to late-stage detection and restricted treatment options. Aberrant glycolysis, exemplified by the Warburg effect, facilitates tumor development, immunological evasion, and alteration of the microenvironment. Identifying glycolysis-related biomarkers could provide novel insights into prognosis and potential therapeutic targets for OC.The transcriptomic and clinical information of OC patients were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases. Differentially expressed glycolysis-related genes (GRGs) were identified and analyzed for their prognostic significance. Consensus clustering was employed to identify glycolysis subtypes, followed by pathway enrichment and immune infiltration analyses. A ten-gene GRG signature was developed with LASSO-Cox regression and verified in various cohorts. Single-cell RNA sequence and drug susceptibility analysis were performed to explore tumor microenvironment heterogeneity and potential therapeutic agents.A total of 457 differentially expressed GRGs were discovered, of which 30 were substantially linked with OC prognosis. Three molecular subtypes were characterized, with cluster C exhibiting the worst prognosis and activation of tumor-associated pathways. A prognostic model comprising ten genes (LMCD1, L1CAM, MYCN, GALT, IDO1, RPL18, XBP1, LPAR3, RUNX3, PLCG1) was developed and validated, demonstrating robust predictive efficacy across various cohorts. Immune analysis revealed substantial disparities in immune infiltration among risk groups, whereas single-cell analysis identified several critical genes essential for metabolism, proliferation, and interactions within the tumor microenvironment.This work highlights the prognostic and therapeutic significance of GRGs in OC. The ten-gene GRG signature serves as a reliable framework for risk assessment and the formulation of individualized treatment regimens. Nonetheless, further experimental validation and extensive clinical research are necessary to enable the application of these findings in clinical practice. These results highlight the potential of targeting glycolytic pathways as a promising approach to improve the management and treatment outcomes of OC.
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Single-cell transcriptional profiling reveals cell type-specific responses to duck reovirus infection in the Bursa of Fabricius of Cairna moschata.
Duck reovirus (DRV) is a universal waterfowl virus that causes significant economic losses in the duck industry. However, the role of the host innate immune response of the Bursa of Fabricius to DRV infection is largely unknown. In the present study, we constructed a single-cell resolution transcriptomic atlas of the Bursa of Fabricius of Cairna moschata after infection with HN10 (a novel DRV). Ten cell-type marker genes were used to annotate the cell type, indicating a high degree of cell heterogeneity in the Bursa of Fabricius. Most of the innate and adaptive immune system-related genes were highly expressed in T cells, B cells, neutrophils, macrophages, and DCs. In the Bursa of Fabricius, the proportions of DCs and macrophages were largely increased by HN10 infection at 14 d, suggesting that DCs and macrophages play important roles in the long-term viral response. Notably, a number of innate and adaptive immune system-related genes were highly expressed at 24 h after HN10 infection, indicating that the Bursa of Fabricius has a very strong immune function even in the early developmental stage. In the immune system, the NOD-like receptor signaling pathway and RIG-I-like receptor signaling pathway were significantly activated at the early stage of HN10 infection, while the Toll-like receptor signaling pathway was significantly activated at the late stage. Enrichment analysis suggested that different immune signaling pathways play roles in specific developmental stages. Our data provide an opportunity to reveal the immune response to DRV infection at the single-cell level.
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Comprehensive analysis of CXCL14 uncovers its role during liver metastasis in colon cancer.
BACKGROUND: The most common cause of death for colon cancer patients is liver metastasis. METHODS: All the data enrolled in this study were downloaded from two public databases, The Cancer Genome Atlas Program, the TCGA-COAD project and Gene Expression Omnibus, GSE41258 project. All the analysis was performed in R software. RESULTS: In our study, we systematically explored the molecules involved in the liver metastasis process of colon cancer. The biological role of these molecules was identified through the GO and KEGG analysis. Moreover, we identified that the molecules SERPINA3, SERPINA1, MMP3, ALDH1A3, PBK and CXCL14 were the independent factors for patients survival. The CXCL14 was selected for further analysis for its most significant P value. Single-cell analysis showed that the CXCL14 was mainly expressed in the fibroblasts. Meanwhile, the biological role of fibroblasts in the colon cancer microenvironment was investigated. Further, the clinical role of CXCL14 in colon cancer was also explored. The result showed that the CXCL14 is a protective factor against colon cancer independent of other clinical parameters like age, gender, clinical stage, and TNM classifications. Then, biological enrichment analysis indicated that the CXCL14 is predominantly involved in the activating of the WNT/β/catenin pathway, pancreas beta cells, peroxisome and bile acid metabolism. Immune infiltration analysis showed that for the patients with high CXCL14 levels, the plasma B cells, CD8 + T cells, neutrophil and NK cells might infiltrate more, in contrast to B cells, monocyte and macrophages. Furthermore, we found that the patients with low CXCL14 expression might be more sensitive to etoposide, rapamycin and sunitinib. CONCLUSIONS: Our result could improve the understanding of the liver metastasis process in colon cancer. Also, CXCL14 was identified as an underlying therapeutic target for colon cancer.
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Machine learning- and WGCNA-mediated double analysis based on genes associated with disulfidptosis, cuproptosis and ferroptosis for the construction and validation of the prognostic model for breast cancer.
BACKGROUND: Disulfidptosis, a recently discovered cellular death mechanism, has not been extensively studied in relation to breast cancer (BC). Specifically, no previous research has integrated disulfidptosis-related genes (DRGs), cuproptosis-related genes (CRGs), and ferroptosis-related genes (FRGs) to construct a prognostic signature for BC. METHODS: DRGs, CRGs and FRGs with prognostic potential were identified through Cox regression analysis. A predictive model was constructed by intersecting the core genes obtained from unsupervised cluster analysis and weighted correlation network analysis (WGCNA). Differences in chemotherapy drug sensitivity, immune checkpoint levels were analyzed according to different risk score groups. The expression of the core disulfidptosis gene, SLC7A11, was analyzed using immunofluorescence. RESULTS: Single-cell RNA sequencing analysis revealed differential expression of DRGs in the BC tumor microenvironment. We developed a prognostic model, consisting of six genes, based on machine learning which included unsupervised cluster analysis and Lasso-Cox analysis. An internal training set and a validation set, both derived from the Cancer Genome Atlas-Breast Cancer (TCGA-BRCA) database, GSE20685 and GSE42568 as external validation sets all verified the model's validity. The low-risk group exhibited increased sensitivity to paclitaxel. Additionally, the high-risk group demonstrated significantly higher expression of tumor mutation burden and microsatellite instability compared to the low-risk group. A nomogram confirmed that the risk score can be an independent risk factor for BC. Notably, our findings highlighted the impact of SLC7A11 on the BC tumor microenvironment. Immunofluorescence analysis revealed significantly higher expression of SLC7A11 in BC tissues compared to paracancerous tissues. CONCLUSION: Multiplex analysis based on DRGs, CRGs and FRGs correlated strongly with BC, providing new insights for developing clinical prognostic tools and designing immunotherapy regimens for BC patients.
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Multi-omics pan-cancer study of cuproptosis core gene FDX1 and its role in kidney renal clear cell carcinoma.
BACKGROUND: The mechanism of copper-induced cellular death was newly discovered and termed cuproptosis. Inducing cuproptosis in cancer cells is well anticipated for its curative potential in treating tumor diseases. However, ferredoxin 1 (FDX1), the core regulatory gene in cuproptosis, is rarely studied, and the regulation of FDX1 in tumor biology remains obscure. A comprehensive pan-cancer analysis of FDX1 is needed. METHODS: Thirty-three types of tumors were included with paired normal tissues in The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets. The interaction between transcription, protein, phosphorylation, and promoter methylation levels was analyzed. Survival, immune infiltration, single-cell FDX1 expression, FDX1-related tumor mutational burden (TMB), microsatellite instability (MSI), stemness, tumor immune dysfunction and exclusion (TIDE), and immunotherapy-related analyses were performed. FDX1 protein expression was assessed by kidney renal clear cell carcinoma (KIRC) tissue microarray immunohistochemistry. The function of FDX1 in KIRC was further explored by experiments in 786-O cell lines in vitro. RESULTS: FDX1 is highly expressed in 15 tumor types and lowly expressed in 11 tumor types. The corresponding changes in protein expression, phosphorylation, and promoter methylation level of FDX1 have been described in several tumors. Survival analysis showed that FDX1 was related to favorable or poor overall survival in eight tumors and progression-free survival in nine tumors. Immune infiltration and single-cell analysis indicated the indispensable role of FDX1 expression in macrophages and monocytes. Multiple established immunotherapy cohorts suggested that FDX1 may be a potential predictor of treatment effects for tumor patients. Tissue microarray analysis showed decreased FDX1 expression in KIRC patients' tumor tissues. Knockdown of FDX1 resulted in the downregulation of cuproptosis in kidney renal clear tumor cells. Mechanistically, the FDX1-associated gene expression signature in KIRC is related to the enrichment of genes involved in the tricarboxylic acid (TCA) cycle, NOTCH pathway, etc. Several NOTCH pathway genes were differentially expressed in the high- and low-FDX1 groups in KIRC. CONCLUSION: Our analysis showed that the central regulatory gene of cuproptosis, FDX1, has differential expression and modification levels in various tumors, which is associated with cellular function, immune modulation, and disease prognosis. Thus, FDX1-dependent cuproptosis may serve as a brand-new target in future therapeutic approaches against tumors.
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PLEK2 Gene Upregulation Might Independently Predict Shorter Progression-Free Survival in Lung Adenocarcinoma.
OBJECTIVE: This study aimed to explore PLEK2 expression profile, its prognostic value, and the potential genomic alterations associated with its dysregulation in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). MATERIALS AND METHODS: Data from The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx), and Kaplan-Meier plotter were used in combination for bioinformatic analysis. RESULTS: PLEK2 mRNA was significantly upregulated in both LUAD and LUSC compared with their respective normal controls. PLEK2 upregulation showed independent prognostic value in progression-free survival (PFS) (HR: 1.169, 95%CI: 1.033 -1.322, p = 0.014). PLEK2 mRNA expression was positively correlated with invasion, cell cycle, DNA damage, and DNA repair of LUAD cells at the single-cell level. Genomic analysis showed that gene-level amplification might not directly lead to increased PLEK2 expression. Methylation profile analysis found 4 CpG sites (cg12199376, cg14437634, cg17641252, and cg06724236) had at least a weakly negative correlation with PLEK2 expression, among which cg12199376, cg14437634 and cg17641252 locate around the first exon of the gene. CONCLUSIONS: Increased PLEK2 expression might be a specific prognostic biomarker of poor PFS in LUAD patients. Its expression had significant positive correlations with invasion, cell cycle, DNA damage, and DNA repair of LUAD cells at the single-cell level. Promoter hypomethylation might be a potential mechanism leading to its upregulation.