scholarly journals Comprehensive profiling of aberrant prognostic alternative splicing signatures in clear cell renal cell carcinoma: a retrospective study based on large-scale sequencing data

2020 ◽  
Author(s):  
Dong Zhang ◽  
Zhao Zhang ◽  
Yi Duan ◽  
Guangxu Ji ◽  
Hongliang Wu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Alternative Splicing ◽  
Renal Cell ◽  
Large Scale ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Sequencing Data ◽  
Cell Renal Cell Carcinoma

Abstract Backgroud: Clear cell renal cell carcinoma(ccRCC) is the most common type with poor prognosis in kidney tumor. Growing evidence has indicated that aberrant alternative splicing (AS) events are efficacious signatures for tumor prognosis predicting and therapeutic targets. Systematic and comprehensive analysis of AS in ccRCC is in urgent need.Methods: Level 3 RNA-seq data were acquired from TCGA data portal and the AS profiles were performed with assistance of SpliceSeq software. Univariate cox regression analysis was applied for screening prognosis-related AS events. Gene functional enrichment analysis revealed the pathways enriched by prognosis-related AS. The final AS panel was developed by LASSO-penalized method for predicting prognosis and compared with traditional clinical factors. The potential regulatory network was analyzed via Spearman correlation between splicing factors (SFs).Results: A total of 2100 survival-associated AS events were filtered from 1666 parent genes. Gene functional enrichment analysis suggested that the regulation of autophagy could be a potential mechanism of splicing regulatory in ccRCC. 17 aberrant AS events formed the final AS panel which can estimate OS probability in ccRCC patients. The AUC values of ROC curves for the final AS panel can keep above 0.7 spanning 1 year to 5 years.Conclusion: We developed a robust and individualized predictive model based on large-scale sequencing data. The identified vital AS events and splicing networks may be valuable in deciphering the potential mechanisms of AS on tumorigenesis of ccRCC.

scholarly journals A novel ferroptosis-related gene signature associated with cell cycle for prognosis prediction in patients with clear cell renal cell carcinoma

BMC Cancer ◽  
2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Siteng Chen ◽  
Encheng Zhang ◽  
Tuanjie Guo ◽  
Jialiang Shao ◽  
Tao Wang ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Renal Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Related Gene ◽  
Cell Renal Cell Carcinoma ◽  
Prognosis Model

Abstract Background It is of great urgency to explore useful prognostic markers for patients with clear cell renal cell carcinoma (ccRCC). Prognostic models based on ferroptosis-related gene (FRG) in ccRCC is poorly reported for now. Methods Comprehensive analysis of 22 FRGs were performed in 629 ccRCC samples from two independent patient cohorts. We carried out least absolute shrinkage and selection operator analysis to screen out prognosis-related FRGs and constructed prognosis model for patients with ccRCC. Weighted gene co-expression network analysis was also carried out for potential functional enrichment analysis. Results Based on the TCGA cohort, a total of 11 prognosis-associated FRGs were selected for the construction of the prognosis model. Significantly differential overall survival (hazard ratio = 3.61, 95% CI: 2.68–4.87, p < 0.0001) was observed between patients with high and low FRG score in the TCGA cohort, which was further verified in the CPTAC cohort with hazard ratio value of 5.13 (95% CI: 1.65–15.90, p = 0.019). Subgroup survival analysis revealed that our FRG score could significantly distinguish patients with high survival risk among different tumor stages and different tumor grades. Functional enrichment analysis illustrated that the process of cell cycle, including cell cycle-mitotic pathway, cytokinesis pathway and nuclear division pathway, might be involved in the regulation of ccRCC through ferroptosis. Conclusions We developed and verified a FRG signature for the prognosis prediction of patients with ccRCC, which could act as a risk factor and help to update the tumor staging system when integrated with clinicopathological characteristics. Cell cycle-related pathways might be involved in the regulation of ccRCC through ferroptosis.

scholarly journals Construction of an Immune-related Gene Model for Predicting Prognosis and Immune Infiltration in Clear Cell Renal Cell Carcinoma

2022 ◽  
Author(s):  
Fengping Ji ◽  
Xin Liu ◽  
Yanping Zhang ◽  
Erpeng Liu ◽  
Jianguo Wen
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Immune Checkpoint ◽  
Renal Cell ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Renal Cell Carcinoma ◽  
Immune Infiltration

Abstract Background: Clear cell renal cell carcinoma (ccRCC) is a common pathological type of kidney cancer with high immune infiltration that has been proven to be treatable with immune checkpoint inhibitor (ICI) therapy. However, the role of immunity in ccRCC remains poorly understood. Therefore, this paper aimed to develop and validate a novel immune-related prognostic marker to predict both the overall survival rate (OS) of ccRCC patients and the response to ICI therapy.Methods: Based on the transcriptome and clinicopathological data of ccRCC from The Cancer Genome Atlas (TCGA) dataset and immune-related genes (IRGs) from immune datasets, IRGs related to prognosis were screened to construct an IRG prognostic index (IRGPI) via coexpression analysis and Cox regression. After verifying that IRGPI was a prognostic indicator independent of clinical parameters, a nomogram was established. In addition, functional enrichment analysis, the CIBERSORT algorithm and single-sample gene set enrichment analysis (ssGSEA) were performed to compare the molecular and immune characteristics of IRGPI-defined subgroups. Finally, the expression of immunosuppressive genes, tumor mutational burden (TMB) and the TIDE algorithm were used to predict the response of ICI therapy in different IRGPI subgroups. Results: A total of 11 IRGs (IFNG, XCL1, APOBEC3G, CD86, CXCR3, IL10RA, IL2RG, CD244, SH2D1A, CD3D and FCER1G) were included in the IRGPI module. IRGPIhigh patients had a worse OS and had poorer clinical pathological status than IRGPIlow patients. A nomogram containing clinical features and IRGPI scores may guide the clinical practice of ccRCC. Chemokine signaling pathways were mainly involved in functional enrichment analysis. Furthermore, the IRGPI could effectively reflect the immune characteristics and immune checkpoint gene expression of ccRCC and the response to ICI therapy.Conclusions: The IRGPI is a promising biomarker for determining prognosis and has the potential to be used to predict immunotherapy response in ccRCC.

Systematic exploration of prognostic alternative splicing events related to immune microenvironment of Clear Cell Renal Cell Carcinoma

2021 ◽  
Author(s):  
Youyuan Deng ◽  
Jianguo Wang ◽  
Yanrui Pang ◽  
Jingyong Li ◽  
Huaixiao Zhang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Alternative Splicing ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Functional Enrichment ◽  
Immune Microenvironment ◽  
Cell Renal Cell Carcinoma ◽  
Systematic Exploration ◽  
Immune Score

Abstract Background Clear cell renal cell carcinoma (ccRCC) accounts for almost 75% of all renal cancers, with high heterogeneity and poor prognosis. There is increasing evidence that alternative splicing (AS) is associated with tumorigenesis and immune microenvironment. However, studies on the relationship between AS events and immunity in ccRCC are still few but needed. Methods The transcriptional data and clinicopathological information of ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. We grouped patients according to the ESTIMATE algorithm and identified for differentially expressed AS events (DEASs). The functional enrichment analysis and unsupervised consensus analysis were performed to investigate the association between AS events and immune features. The regulatory network of survival-related AS events and intersection SFs was used to explore potential mechanisms. Results In total, 515 ccRCC patients were included in the present study. The low immune-score group had longer overall survival (OS) than the high low immune-score group. 861 AS events were identified as DEASs, and they were enriched in immune-related pathways. Unsupervised clustering analysis revealed that AS-based clusters significantly corelated with prognosis and immune features of ccRCC. Finally, MBNL1 was identified as a hub SF, and it was shown to inhibit proliferation and metastasis, promote apoptosis, and block cells in G2/M phase in 786O and A498 cells. Conclusion The present systematic exploration elaborated that not only some critical AS events were related to prognosis and immune microenvironment of ccRCC, but also the hub SF, such as MBNL1, could affect the development and progression of ccRCC.

scholarly journals Data Mining of Prognostic Microenvironment-Related Genes in Clear Cell Renal Cell Carcinoma: A Study with TCGA Database

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Bin Chen ◽  
Wei Chen ◽  
Jing Jin ◽  
Xueping Wang ◽  
Yifang Cao ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Value ◽  
Clear Cell ◽  
Enrichment Analysis ◽  
Cancer Prognosis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent kidney malignancies. The tumor microenvironment (TME) is highly related to the oncogenesis, progress, and prognosis of ccRCC. The aim of this study was to infer the level of infiltrating stromal and immune cells and assess the prognostic value of them. The gene expression profile was obtained from TCGA and used for calculating the stromal and immune scores. Based on a cut-off value, patients were divided into low- and high-stromal/immune score groups. Survival analysis was performed to evaluate the prognostic value of stromal and immune scores. Moreover, differentially expressed genes (DEGs) that are highly related to TME were determined and applied for functional enrichment analysis and protein-protein interaction (PPI) network. The Kaplan-Meier plot demonstrated that patients with high-immune scores and stromal scores had poorer clinical outcome. In addition, a total of 89 DEGs were identified and mainly involved in 5 pathways. The top 5 degree genes were extracted from the PPI network; among them, IL10 and XCR1 were highly associated with prognosis of ccRCC. The results of the present study demonstrated that ESTIMATE algorithm-based stromal and immune scores may be a credible indicator of cancer prognosis and IL10 along with XCR1 may be a potential key regulator for the TME of ccRCC.

Exploiting Synthetic Lethal Network for Precision Treatment of Clear Cell Renal Cell Carcinoma

2021 ◽  
Author(s):  
Zhicheng Liu ◽  
Dongxu Lin ◽  
Linmeng Zhang ◽  
Chen Yang ◽  
Bin Guo ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Large Scale ◽  
Target Genes ◽  
Clear Cell ◽  
Therapeutic Potential ◽  
Synthetic Lethality ◽  
Treatment Modalities ◽  
Cell Renal Cell Carcinoma

Abstract Background The emerging of targeted therapies has revolutionized the treatment modalities of advanced clear cell renal cell carcinoma (ccRCC) over the past fifteen years. However, lack of personalized treatment limits the development of effective clinical guidelines and improvement of patient prognosis. In this study, large-scale genomic profiles of ccRCC cohorts were exploited for conducting an integrative analysis. Method Based on synthetic lethality (SL), a concept that simultaneous losses of two genes cause cell death while a single loss does not, we sought to develop a computational pipeline to infer potential SL partners of ccRCC. Drug response prediction were received from three pharmacological databases to select agents which are likely to be effective in precisely treating patients with target gene mutation. Results We developed a credible method to identify SL pairs and determined a list of 72 candidate pairs which might be utilized to selectively eliminate tumors with genetic aberrations through SL partners of specific mutations. Further analysis identified BRD4 and PRKDC as novel medicine targets for patients with BAP1 mutations. After mapping these target genes to comprehensive drug datasets, two agents (BI-2536 and PI-103) were found to have considerable therapeutic potential in BAP1 mutant tumors. Conclusion Overall, our findings provide insight into the overview of ccRCC mutation patterns and offer novel opportunities for improving individualized cancer treatment.

scholarly journals Development and Interpretation of a Genomic Instability Derived lncRNAs Based Risk Signature as a Predictor of Prognosis for Clear Cell Renal Cell Carcinoma Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Huiying Yang ◽  
Xiaoling Xiong ◽  
Hua Li
Keyword(s):  
Renal Cell Carcinoma ◽  
High Risk ◽  
Cell Carcinoma ◽  
Genomic Instability ◽  
Renal Cell ◽  
Clear Cell ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Cell Renal Cell Carcinoma ◽  
Prognosis Prediction

BackgroundClear cell renal cell carcinoma (ccRCC) is a kind of frequently diagnosed cancer, leading to high death rate in patients. Genomic instability (GI) is regarded as playing indispensable roles in tumorigenesis and impacting the prognosis of patients. The aberrant regulation of long non-coding RNAs (lncRNAs) is a main cause of GI. We combined the somatic mutation profiles and expression profiles to identify GI derived lncRNAs (GID-lncRNAs) in ccRCC and developed a GID-lncRNAs based risk signature for prognosis prediction and medication guidance.MethodsWe decided cases with top 25% cumulative number of somatic mutations as genomically unstable (GU) group and last 25% as genomically stable (GS) group, and identified differentially expressed lncRNAs (GID-lncRNAs) between two groups. Then we developed the risk signature with all overall survival related GID-lncRNAs with least absolute shrinkage and selection operator (LASSO) Cox regression. The functions of the GID-lncRNAs were partly interpreted by enrichment analysis. We finally validated the effectiveness of the risk signature in prognosis prediction and medication guidance.ResultsWe developed a seven-lncRNAs (LINC00460, AL139351.1, AC156455.1, AL035446.1, LINC02471, AC022509.2, and LINC01606) risk signature and divided all samples into high-risk and low-risk groups. Patients in high-risk group were in more severe clinicopathologic status (higher tumor grade, pathological stage, T stage, and more metastasis) and were deemed to have less survival time and lower survival rate. The efficacy of prognosis prediction was validated by receiver operating characteristic analysis. Enrichment analysis revealed that the lncRNAs in the risk signature mainly participate in regulation of cell cycle, DNA replication, material metabolism, and other vital biological processes in the tumorigenesis of ccRCC. Moreover, the risk signature could help assess the possibility of response to precise treatments.ConclusionOur study combined the somatic mutation profiles and the expression profiles of ccRCC for the first time and developed a GID-lncRNAs based risk signature for prognosis predicting and therapeutic scheme deciding. We validated the efficacy of the risk signature and partly interpreted the roles of the seven lncRNAs composing the risk signature in ccRCC. Our study provides novel insights into the roles of genomic instability derived lncRNAs in ccRCC.

Systematic Analyses of The Role of Prognostic And Immunological of EIF3A, A Reader Protein, In Clear Cell Renal Cell Carcinoma

2021 ◽  
Author(s):  
Yi Zhang ◽  
Xiaoliang Hua ◽  
Haoqiang Shi ◽  
Li Zhang ◽  
HaiBing Xiao ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Immune Cells ◽  
Renal Cell ◽  
Clear Cell ◽  
Multivariate Analyses ◽  
Enrichment Analysis ◽  
Marker Genes ◽  
Cell Renal Cell Carcinoma

Abstract Background: Eukaryotic initiation factor 3a, EIF3A, as a “reader” protein for RNA methylation, has been found to be related to promote tumorigenesis in different variety of cancers. The impaction of EIF3A in clear cell renal cell carcinoma (ccRCC) has yet to be expounded. This study aimed to identify the prognostic value of EIF3A in ccRCC and investigate the relationship between expression and immune infiltration.Methods: We collected 29 m6a related mRNA data and clinicopathological parameters from Cancer Genmoe Atlas (TCGA) database. Logistic regression analyses were used to analyze the correlation between EIF3A expression and clinical characteristics. Immunohistochemistry (IHC) were applied to examine EIF3A levels in normal and ccRCC tissues. Univariate and multivariate analyses were conducted to recognize forcefully independent factor in associated with overall survival (OS) and diseases free survival (DFS). Nomogram was aim at predicting the 1-, 3-and 5-year survival probabilities. Gene set enrichment analysis (GSEA) was carried out to the potential function and related signaling pathways of EIF3A expression. To investigate EIF3A of co-expressed genes, we used LinkedOmics and its result was undertaken enrichment analysis. Simultaneously, to employ LinkedOmics and STRING dataset drew a conclusion that EIF3A co-expressed genes and visualized via Cytoscape. Finally, we evaluated that EIF3A expression correlated between with infiltration of immune cells and the expression of marker genes in ccRCC by Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA).Result: EIF3A expression was significantly different between ccRCC tissues and normal tissues. EIF3A expression was connected with poor prognostic clinicopathological factors, and K–M analyses revealed that low EIF3A expression was correlated with poor prognosis. The result of univariate and multivariate analyses proved that EIF3A was a prognostic factor in ccRCC patients. GSEA results indicated that high expression was enriched in renal cell carcinoma pathway and so on. EIF3A expression was significantly positively correlated with B cells, CD8+T cells, CD4+T cells, neutrophils, macrophages, and dendritic cells. Furthermore, EIF3A expression was associated with most of marker genes of immune cells.Conclusions: EIF3A could serve as potential biomarkers for prognostic and diagnostic stratification factor for ccRCC and is related with immune cells infiltrates.

The Significance of INHBE Expression in the Cancer Cells of Clear-Cell Renal Cell Carcinoma

2021 ◽  
pp. 1-11
Author(s):  
Zi-Bin Xu ◽  
Mei-Fu Gan ◽  
Hong-Yuan Yu ◽  
Li-Cai Mo ◽  
Yu-Hui Xia ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Cancer Cells ◽  
Renal Cell ◽  
Tumor Tissue ◽  
Transforming Growth Factor ◽  
Clear Cell ◽  
Tumor Promoter ◽  
Sequencing Data ◽  
Cell Renal Cell Carcinoma

<b><i>Background:</i></b> Activins and inhibins are structurally related dimeric glycoprotein hormones belonging to the transforming growth factor-β superfamily but whether they are also involved in malignancy is far from clear. No study has reported the expression of INHBE in kidney cancer. The purpose of this study was to examine the expressions of INHBE in the tumor tissue of patients with clear-cell renal cell carcinoma (ccRCC) and to explore the pathologic significance. <b><i>Methods:</i></b> The INHBE mRNA expression in the tumor tissue of ccRCC patients was analyzed by using RNA sequencing data from the TCGA database. To examine the expression of inhibin βE protein, 241 ccRCC patients were recruited and immunohistochemistry was performed on the tumor tissue of these patients along with 39 normal renal samples. The association between the inhibin βE expression level and patient’s clinicopathological indices was evaluated. <b><i>Results:</i></b> In the normal renal tissue, inhibin βE was found to be expressed mainly by renal tubular epithelial cells. In the tumor tissue, inhibin βE was expressed mainly in cancer cells. The expressions of INHBE mRNA and protein in the tumor tissue of ccRCC patients increased significantly compared with those in normal renal samples. There was a significant correlation between the level of inhibin βE in the tumor tissue and tumor grade. Patients with a lower inhibin βE expression in the tumor tissue were found to have a longer overall survival and disease-specific survival. <b><i>Conclusions:</i></b> INHBE might be involved in the pathogenesis of ccRCC and function as a tumor promoter.

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