Effect of MAP3K8 on Prognosis and Tumor-Related Inflammation in Renal Clear Cell Carcinoma

Hao, Jiatao; Cao, Yumeng; Yu, Hui; Zong, Lu; An, Ruifang; Xue, Yan

doi:10.3389/fgene.2021.674613

Cited by 7 publications

(11 citation statements)

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“…The XCELL ( Aran et al, 2017 ), TIMER ( Li et al, 2017 ), QUANTISEQ ( Hao et al, 2021 ), MCP-counter ( Becht et al, 2016 ), EPIC ( Racle and Gfeller, 2020 ), CIBERSORT−ABS ( Xu Q. et al, 2021 ), and CIBERSORT ( Chen et al, 2018 ) algorithms were used to assess the levels of various tumor-infiltrating immune cells: endothelial cells, hematopoietic stem cells, common myeloid progenitors, macrophages, activated mast cells, monocytes, central memory CD4 + T cells, neutrophils, memory B cells, cancer-associated fibroblasts, plasma B cells, M0 macrophages, M1 macrophages, activated natural killer (NK) cells, nonregulatory CD4 + T cells, activated memory CD4 + T cells, and so on.…”

Section: Methodsmentioning

confidence: 99%

Predicting prognosis and immune responses in hepatocellular carcinoma based on N7-methylguanosine-related long noncoding RNAs

et al. 2022

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Background: Hepatocellular carcinoma (HCC), which has high rates of recurrence and metastasis and is the main reason and the most common tumor for cancer mortality worldwide, has an unfavorable prognosis. N7-methylguanosine (m7G) modification can affect the formation and development of tumors by affecting gene expression and other biological processes. In addition, many previous studies have confirmed the unique function of long noncoding RNAs (lncRNAs) in tumor progression; however, studies exploring the functions of m7G-related lncRNAs in HCC patients has been limited.Methods: Relevant RNA expression information was acquired from The Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov), and m7G-related lncRNAs were identified via gene coexpression analysis. Afterward, univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate regression analyses were implemented to construct an ideal risk model whose validity was verified using Kaplan–Meier survival, principal component, receiver operating characteristic (ROC) curve, and nomogram analyses. In addition, the potential functions of lncRNAs in the novel signature were explored through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) analyses and gene set enrichment analysis (GSEA). At last, in both risk groups and subtypes classified based on the expression of the risk-related lncRNAs, we analyzed the immune characteristics and drug sensitivity of patients.Results: After rigorous screening processes, we built a model based on 11 m7G-related lncRNAs for predicting patient overall survival (OS). The results suggested that the survival status of patients with high-risk scores was lower than that of patients with low-risk scores, and a high-risk score was related to malignant clinical features. Cox regression analysis showed that the m7G risk score was an independent prognostic parameter. Moreover, immune cell infiltration and immunotherapy sensitivity differed between the risk groups.Conclusion: The m7G risk score model constructed based on 11 m7G-related lncRNAs can effectively assess the OS of HCC patients and may offer support for making individualized treatment and immunotherapy decisions for HCC patients.

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Section: Methodsmentioning

confidence: 99%

Predicting prognosis and immune responses in hepatocellular carcinoma based on N7-methylguanosine-related long noncoding RNAs

et al. 2022

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“…In recent years, many studies have found that inflammatory cells and factors play an important role in the development, transformation and metastasis of tumors, including inflammatory cells, chemokines, their receptors and downstream signaling pathways 31–34 . ccRCC is a typical immunogenic tumor with abundant immune cell infiltration 35 .…”

Section: Discussionmentioning

confidence: 99%

Transcriptome mapping of renal clear cell carcinoma revealed by machine learning algorithm based on enhanced computed tomography images

Huang

Liang

2023

The Journal of Gene Medicine

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Background: A growing number of studies have shown that inflammation-related components of the tumor microenvironment (TME) affect the clinical outcomes of cancer patients, and advances in radiomics may help predict survival and prognosis.Methods: We performed a systematic analysis of inflammation-related genes (IRGs) in clear cell renal cell carcinoma (ccRCC) from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus and mapped their interaction network to assess the specific relationship between these differentially expressed inflammation-related genes (DEIRGs) and inflammation. The association between DEIRGs and prognosis was discussed and further validated using consensus cluster analysis. Next, we constructed IRGs-related risk score from the collected information and validated the prognostic value of the model using Kaplan-Meier survival analysis and receiver operating characteristic analysis. Computed tomographic images corresponding to the TCGA-ccRCC cohort were obtained from the Cancer Imaging Archive database for radiomics signature extraction. Results:We screened for prognostic IRGs and found that they were positively correlated with inflammatory cells in the tumor microenvironment associated with tumor progression and metastasis, such as activated CD8+ cells, myeloid-derived suppressor cells and neutrophils. The impact of IRGs on the prognosis of ccRCC patients was also verified. Using these differentially expressed genes, we successfully constructed a risk signature and validated its good prognosis assessment for patients. Furthermore, radiomics-based prognostic models performed better than those using risk signatures or clinical characteristics.Conclusions: IRG-related risk scores play an important role in assessing the prognosis and improving the management of patients with ccRCC. Through this feature, the infiltration of immune cells in the TME can be predicted. Furthermore, non-invasive radiomics signatures showed satisfactory performance in predicting ccRCC prognosis.

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“…We explored the association between the KDM6B expression and immune infiltration across all tumors in TCGA with TIMER2.0. CIBERSORT, CIBERSORT-ABS, TIMER, quanTIseq, MCP-counter, xCell, and EPIC algorithms ( Hao et al, 2021 ) were applied to evaluate the immune infiltration data in all tumors across all immune cells in TIMER2.0, including monocytes, mast cells, macrophages, CD4 + T cells, CD8 + T cells, Treg, follicular helper T cells, NK T cells, NK cells, neutrophils, common lymphoid progenitors, hematopoietic stem cells, common myeloid progenitors, endothelial cells, DCs (dendritic cells), granulocyte–monocyte progenitors, myeloid-derived suppressor cells, eosinophils, and cancer-associated fibroblasts. The purity-adjusted Spearman’s rank correlation test was used to obtain the p -values and sectional correlation values.…”

Section: Methodsmentioning

confidence: 99%

A Pan-Cancer Analysis Revealing the Dual Roles of Lysine (K)-Specific Demethylase 6B in Tumorigenesis and Immunity

Ding

et al. 2022

Front. Genet.

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Introduction: Epigenetic-targeted therapy has been increasingly applied in the treatment of cancers. Lysine (K)-specific demethylase 6B (KDM6B) is an epigenetic enzyme involved in the coordinated control between cellular intrinsic regulators and the tissue microenvironment whereas the pan-cancer analysis of KDM6B remains unavailable.Methods: The dual role of KDM6B in 33 cancers was investigated based on the GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas) databases. TIMER2 and GEPIA2 were applied to investigate the KDM6B levels in different subtypes or stages of tumors. Besides, the Human Protein Atlas database allowed us to conduct a pan-cancer study of the KDM6B protein levels. GEPIA2 and Kaplan–Meier plotter were used for the prognosis analysis in different cancers. Characterization of genetic modifications of the KDM6B gene was analyzed by the cBioPortal. DNA methylation levels of different KDM6B probes in different TCGA tumors were analyzed by MEXPRESS. TIMER2 was applied to determine the association of the KDM6B expression and immune infiltration and DNA methyltransferases. Spearman correlation analysis was used to assess the association of the KDM6B expression with TMB (tumor mutation burden) and MSI (microsatellite instability). The KEGG (Kyoto encyclopedia of genes and genomes) pathway analysis and GO (Gene ontology) enrichment analysis were used to further investigate the potential mechanism of KDM6B in tumor pathophysiology.Results: KDM6B was downregulated in 11 cancer types and upregulated across five types. In KIRC (kidney renal clear cell carcinoma) and OV (ovarian serous cystadenocarcinoma), the KDM6B level was significantly associated with the pathological stage. A high level of KDM6B was related to poor OS (overall survival) outcomes for THCA (thyroid carcinoma), while a low level was correlated with poor OS and DFS (disease-free survival) prognosis of KIRC. The KDM6B expression level was associated with TMB, MSI, and immune cell infiltration, particularly cancer-associated fibroblasts, across various cancer types with different correlations. Furthermore, the enrichment analysis revealed the relationship between H3K4 and H3K27 methylation and KDM6B function.Conclusion: Dysregulation of the DNA methyltransferase activity and methylation levels of H3K4 and H3K27 may involve in the dual role of KDM6B in tumorigenesis and development. Our study offered a relatively comprehensive understanding of KDM6B’s dual role in cancer development and response to immunotherapy.

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Effect of MAP3K8 on Prognosis and Tumor-Related Inflammation in Renal Clear Cell Carcinoma

Cited by 7 publications

References 50 publications

Predicting prognosis and immune responses in hepatocellular carcinoma based on N7-methylguanosine-related long noncoding RNAs

Predicting prognosis and immune responses in hepatocellular carcinoma based on N7-methylguanosine-related long noncoding RNAs

Transcriptome mapping of renal clear cell carcinoma revealed by machine learning algorithm based on enhanced computed tomography images

A Pan-Cancer Analysis Revealing the Dual Roles of Lysine (K)-Specific Demethylase 6B in Tumorigenesis and Immunity

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