Multi‐omics analysis of tumor mutation burden combined with immune infiltrates in bladder urothelial carcinoma

Zhang, Chuanjie; Shen, Lu-Ping; Qi, Feng; Wang, Jincheng; Luo, Jun

doi:10.1002/jcp.29279

Cited by 44 publications

(33 citation statements)

References 57 publications

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“…Zhu et al found that the EP300 mutation was related to the TMB and promoted anti-tumor immunity in bladder cancer [27]. Zhang et al reported that immune genes such as CES1 and CSAG1 could be used as biomarkers for predicting the effects of immunotherapy through a multi-omics analysis [28]. Similarly, Pan et al discovered that Laylin is a prognostic marker of survival and is associated with immune in ltration in gastric and colon cancer [29].…”

Section: Discussionmentioning

confidence: 99%

Identification of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma Based on Multi-Omics Analysis

Yin

Zhou

2020

Preprint

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Background: We aimed to explore the tumor mutational burden (TMB) and immune infiltration in HCC and investigate new biomarkers for immunotherapy.Methods: Transcriptome and gene mutation data were downloaded from the GDC portal, including 374 HCC samples and 50 matched samples. Furthermore, we divided the samples into high and low TMB groups, and analyzed the differential genes between them with GO, KEGG, and GSEA. Cibersort was used to assess the immune cell infiltration in the samples. Finally, univariate and multivariate Cox regression analyses were performed to identify differential genes related to TMB and immune infiltration, and a risk prediction model was constructed.Results: We found 10 frequently mutated genes, including TP53, TTN, CTNNB1, MUC16, ALB, PCLO, MUC, APOB, RYR2, and ABCA. Pathway analysis indicated that these TMB-related differential genes were mainly enriched in PI3K-AKT. Cibersort analysis showed that memory B cells (P=0.02), CD8+ T cells (P=0.09), CD4+ memory activated T cells (P=0.07), and neutrophils (P=0.06) demonstrated a difference in immune infiltration between high and low TMB groups. On multivariate analysis, GABRA3 (P=0.05), CECR7 (P<0.001), TRIM16 (P=0.003), and IL7R (P=0.04) were associated with TMB and immune infiltration. The risk prediction model had an area under the curve (AUC) of 0.69, suggesting that patients with low risk had better survival outcomes.Conclusions: Our study demonstrated for the first time that CECR7, GABRA3, IL7R, and TRIM16L mutations were associated with TMB and promoted antitumor immunity in HCC.

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Section: Discussionmentioning

confidence: 99%

Identification of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma Based on Multi-Omics Analysis

Yin

Zhou

2020

Preprint

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“…Based on the above conclusions, we speculated that TMB may play a crucial role in predicting the prognosis of endometrial cancer. Zhang et al (2019) performed a multi-omics analysis of TMB and immune in ltration in bladder urothelial carcinoma on the TCGA public platform, demonstrating that TMB may be an independent biomarker for survival prediction of bladder cancer (26). In this study, a similar methodology was utilized to analyze the relationship between TMB level and survival status in endometrial cancer.…”

Section: Discussionmentioning

confidence: 98%

“…With the continuous development of bioinformatics, we have the opportunity to obtain helpful resources about genomics and therapeutic responses from various public databases. Zhang C et al performed a multi-omics analysis of TMB and immune in ltration in bladder urothelial carcinoma using the Cancer Genome Atlas (TCGA) database (26). Given the impressive results achieved by immunotherapies, especially ICIs in the treatment of UCEC, we performed this study to explore the prognostic role of TMB and its potential association with immune in ltration in UCEC.…”

Section: Introductionmentioning

confidence: 99%

Biological Omics Analysis of Tumor Mutation Burden Combined with Immune Infiltrates in Uterine Corpus Endometrial Carcinoma

Zhuang

Liu

Huang

et al. 2020

Preprint

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Background: In various malignancies, whether tumor mutation burden (TMB) is associated with improved survival outcomes or enhanced immunotherapy remains controversial. We are committed to exploring the prognosis of TMB and its potential association with immune infiltration of uterine corpus endometrial cancer (UCEC).Methods: We downloaded transcriptome data and somatic mutation data from the Cancer Genome Atlas (TCGA) database, and visualized the mutation profiles using the "maftools" package. TMB was calculated and the samples were divided into two groups by the median. Kaplan-Meier analysis and Wilcoxon test were used to compare the differences in survival and clinicopathological characteristics. Furthermore, we performed functional enrichment analysis to screen for significant contributing pathways. The "CIBERSORT" package was used to estimate the abundance of immune components. Differential analysis was performed using the "limma" package to compare gene expression profiles. Multivariate analysis was used to identify risk genes related to TMB. Based on these genes, a risk model was established, and the receiver operating characteristic (ROC) curve was drawn to assess the predictive accuracy. Finally, we evaluated the relationship between risk genes and immune infiltration using the Timer database.Results: The mutation data included 542 UCEC patients. The waterfall plot summarized the specific mutation information. Higher TMB levels indicated improved overall survival (OS) (p =0.048) and were associated with advanced grades. Pathway analysis showed that the differential signals were enriched in multiple immune-related crosstalks. We screened 108 differentially expressed genes in two TMB groups and identified four risk-related genes. The model based on these four risk genes had good predictive value, the area under the curve (AUC) = 0.670, and patients with higher risk scores showed worse OS (p <0.001). Additionally, CD8 T cells memory-activated, CD4 T cells, and M1 macrophages in the high TMB group showed higher infiltrates, while regulatory T cells (Tregs) and M2 macrophages showed lower infiltrates.Conclusions: Higher TMB was associated with better survival outcomes and increased the immune infiltration in the tumor microenvironment of UCEC.

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“…Notably, ECM modi cation could not only promote tumor cells to escape, but also help generate and maintain the cancer stem cell niche [29]. Moreover, high in ltration of memory activated CD4 + T cell subsets were associated with prolonged OS and reduced risk of tumor recurrence in bladder cancer [30]. Chobrutskiy et al demonstrated that lower CDR3 region isoelectric point in T cell receptor was associated with better survival outcomes in bladder cancer [31].…”

Section: Discussionmentioning

confidence: 99%

Development and verification of immune-related long non-coding RNA prognostic signature in bladder cancer

Lai¹,

Wu²,

Li³

et al. 2020

Preprint

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Background: Bladder cancer is the second most common malignant tumor in urogenital system. The research aimed to investigate the prognostic role of immune-related long non-coding RNA (lncRNA) in bladder cancer. Methods: We extracted 411 bladder cancer samples from The Cancer Genome Atlas database. Single-sample gene set enrichment analysis was employed to assess the immune cell infiltration of these samples. We recognized differentially expressed lncRNAs between tumors and paracancerous tissues, and differentially expressed lncRNAs between the high and low immune cell infiltration groups. Venn diagram analysis detected differentially expressed lncRNAs that intersected the above groups. LncRNAs with prognostic significance were identified by regression analysis and survival analysis. Multivariate Cox analysis was used to establish the risk score model. The nomogram was established and evaluated by receiver operating characteristic (ROC) curve analysis, concordance index (C-index) analysis, calibration chart, and decision curve analysis (DCA). Additionally, we performed gene set enrichment analysis to explore the potential functions of the screened lncRNAs in tumor pathogenesis.Results: Three hundred and twenty differentially expressed lncRNAs were recognized. We randomly divided patients into the training data set and the testing data set at a 2: 1 ratio. In the training data set, 9 immune-related lncRNAs with prognostic significance were identified. The risk score model was constructed to classify patients as high- and low-risk cohorts. Patients in the low-risk cohort had better survival outcomes than those in the high-risk cohort. The nomogram was established based on the indicators including age, gender, TNM stage, and risk score. The model’s predictive performance was confirmed by ROC curve analysis, C-index analysis, calibration chart, and DCA. The testing data set also achieved similar results. Bioinformatics analysis suggested that the 9-lncRNA signature was involved in modulation of various immune responses, antigen processing and presentation, and T cell receptor signaling pathway.Conclusions: The immune-related lncRNAs have the potential to predict the prognosis of bladder cancer and may play a key role in bladder cancer biology.Trial registration: It was a retrospective study and the gene expression data were obtained from the TCGA database. Trial registration was not needed.

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Multi‐omics analysis of tumor mutation burden combined with immune infiltrates in bladder urothelial carcinoma

Cited by 44 publications

References 57 publications

Identification of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma Based on Multi-Omics Analysis

Identification of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma Based on Multi-Omics Analysis

Biological Omics Analysis of Tumor Mutation Burden Combined with Immune Infiltrates in Uterine Corpus Endometrial Carcinoma

Development and verification of immune-related long non-coding RNA prognostic signature in bladder cancer

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