APOBEC-mediated mutagenesis is a favorable predictor of prognosis and immunotherapy for bladder cancer patients: evidence from pan-cancer analysis and multiple databases

Shi, Run; Wang, Xin; Wu, Yang; Xu, Bin; Zhao, Tianyu; Trapp, Christian; Wang, Xuanbin; Unger, Kristian; Zhou, Cheng; Lü, Shun; Büchner, Alexander; Schulz, Gerald Bastian; Cao, Fengjun; Belka, C.; Su, Chuan; Li, Minglun; Shu, Yongqian

doi:10.7150/thno.73235

Cited by 31 publications

(27 citation statements)

References 59 publications

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“…Therefore, screening novel biomarkers to help develop patient-specific therapies and improve prognosis remains critical and urgent. Distinct from bulk RNA-seq focusing on the average expression level of genes in cells, scRNA-seq has emerged as a useful tool for transcriptional stratification to define the cell subpopulations and realize specific biomarkers and heterogeneity among different cell types in various cancers, including BLCA [ 28 ]. Therefore, in this study, we conducted a comprehensive analysis of bulk RNA-seq and scRNA-seq to develop a risk model that exhibited excellent prognostic and predictive efficacy for immunotherapy response in BLCA.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model

et al. 2023

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Background The prognostic management of bladder cancer (BLCA) remains a great challenge for clinicians. Recently, bulk RNA-seq sequencing data have been used as a prognostic marker for many cancers but do not accurately detect core cellular and molecular functions in tumor cells. In the current study, bulk RNA-seq and single-cell RNA sequencing (scRNA-seq) data were combined to construct a prognostic model of BLCA. Methods BLCA scRNA-seq data were downloaded from Gene Expression Omnibus (GEO) database. Bulk RNA-seq data were obtained from the UCSC Xena. The R package "Seurat" was used for scRNA-seq data processing, and the uniform manifold approximation and projection (UMAP) were utilized for downscaling and cluster identification. The FindAllMarkers function was used to identify marker genes for each cluster. The limma package was used to obtain differentially expressed genes (DEGs) affecting overall survival (OS) in BLCA patients. Weighted gene correlation network analysis (WGCNA) was used to identify BLCA key modules. The intersection of marker genes of core cells and genes of BLCA key modules and DEGs was used to construct a prognostic model by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) analyses. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and chemotherapeutic drug sensitivity between the high and low-risk groups were also investigated. Results scRNA-seq data were analyzed to identify 19 cell subpopulations and 7 core cell types. The ssGSEA showed that all 7 core cell types were significantly downregulated in tumor samples of BLCA. We identified 474 marker genes from the scRNA-seq dataset, 1556 DEGs from the Bulk RNA-seq dataset, and 2334 genes associated with a key module identified by WGCNA. After performing intersection, univariate Cox, and LASSO analysis, we obtained a prognostic model based on the expression levels of 3 signature genes, namely MAP1B, PCOLCE2, and ELN. The feasibility of the model was validated by an internal training set and two external validation sets. Moreover, patients with high-risk scores are predisposed to experience poor OS, a larger prevalence of stage III-IV, a greater TMB, a higher infiltration of immune cells, and a lesser likelihood of responding favorably to immunotherapy. Conclusion By integrating scRNA-seq and bulk RNA-seq data, we constructed a novel prognostic model to predict the survival of BLCA patients. The risk score is a promising independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics.

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Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model

et al. 2023

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“…For instance, PD 1 or PD L1 monoclonal blocking antibodies are applied on PD L1-positive tumors to correct the immunosuppression of T cells in TME (Lei et al, 2020). Researchers are also exploring the relevance of gene mutations to immune in ltration (Shi et al, 2022). Our results showed that ZWINT expression was negatively correlated with the in ltration values of T cell CD4 + central memory, T cell CD4 + effector cells and tumor-associated broblasts, and positively correlated with the in ltration values of T cell CD4 + Th2 cells and MDSCs.…”

Section: Discussionmentioning

confidence: 99%

ZWINT is a cancer prognosis and immune infiltration-related biomarker from pan-cancer analysis

wang

Chen

et al. 2023

Preprint

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ZWINT plays an important role in regulating the mitotic checkpoint and cell cycle, and is closely associated with tumor proliferation and migration. Recent studies have shown that high ZWINT expression is associated with poor prognosis in patients with lung adenocarcinoma(LUAD) and Glioblastoma (GBM). Previous analyses of ZWINT were limited to a certain type of cancer, but there has not been a systematic pan-cancer study of ZWINT. We used the TCGA (The Cancer Genome Atlas) project and GTEx data (Genotype-Tissue Expression) to analyze ZWINT expression levels and the correlation with cancer survival prognosis. To understand the underlying biological mechanisms of ZWINT and its relevance to immune infiltration, we systematically analyzed ZWINT-associated genetic alterations, immune infiltration and gene enrichment analysis with different bioinformatics methods. Our study showed that ZWINT mRNA expression was elevated in most human tumors and was significantly increased in the early stages of cancer compared to ZWINT expression in normal tissues.ZWINT high expression is significantly correlated with poor prognosis in most tumors. ZWINT is extensively involved in immune infiltration of tumors. Single cell sequencing data showed that ZWINT was significantly associated with cell cycle, DNA repair, DNA damage, and proliferation. Thus, ZWINT expression correlates with prognosis and immune infiltration in tumor patients. ZWINT may be a potential biomarker for prognosis and an important target for tumor immunotherapy.

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“…Fewer T-reg, Th2, and TAM cells Mouse [ 164 ] 3B Activating More tumor-infiltrating lymphocytes Patient [ 165 ] 3B Activating Immune activation in pan-cancer analysis Patient [ 162 ] 3C-H Activating More CD8+ T-cells with greater receptor diversity and cytolytic activity Patient [ 48 ] Bladder 3B Activating Enrichment of immune-related signatures, including IFN-γ Patient [ 46 ] Mutation burden Activating Higher neoantigen loads, activated CD4+ T cells, CD8+ T cells, and M1 cells. Fewer MDSCs and naïve CD4+ T cells Patient [ 160 ] 3B Activating More cytotoxic T-cells with a higher CD8+/CD3+ ratio Patient [ 35 ] Glioma 3B, 3C, 3D, 3F, 3G, 3H Activating Increased myeloid cell infiltration, IFN-γ signaling, and PD-L1/2 expression Patient [ 51 ] Lung 3B Activating More activated CD4+ T cells, CD8+ T cells, and NK cells. Fewer regulatory T cells Patient [ …”

Section: Impact Of Apobec3s Through Mutagenic and Non-mutagenic Pathwaysmentioning

confidence: 99%

APOBEC3-mediated mutagenesis in cancer: causes, clinical significance and therapeutic potential

Butler

Banday

2023

J Hematol Oncol

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Apolipoprotein B mRNA-editing enzyme, catalytic polypeptides (APOBECs) are cytosine deaminases involved in innate and adaptive immunity. However, some APOBEC family members can also deaminate host genomes to generate oncogenic mutations. The resulting mutations, primarily signatures 2 and 13, occur in many tumor types and are among the most common mutational signatures in cancer. This review summarizes the current evidence implicating APOBEC3s as major mutators and outlines the exogenous and endogenous triggers of APOBEC3 expression and mutational activity. The review also discusses how APOBEC3-mediated mutagenesis impacts tumor evolution through both mutagenic and non-mutagenic pathways, including by inducing driver mutations and modulating the tumor immune microenvironment. Moving from molecular biology to clinical outcomes, the review concludes by summarizing the divergent prognostic significance of APOBEC3s across cancer types and their therapeutic potential in the current and future clinical landscapes.

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APOBEC-mediated mutagenesis is a favorable predictor of prognosis and immunotherapy for bladder cancer patients: evidence from pan-cancer analysis and multiple databases

Cited by 31 publications

References 59 publications

Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model

Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model

ZWINT is a cancer prognosis and immune infiltration-related biomarker from pan-cancer analysis

APOBEC3-mediated mutagenesis in cancer: causes, clinical significance and therapeutic potential

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