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.

scholarly journals Systematic analyses of the role of prognostic and immunological EIF3A, a reader protein, in clear cell renal cell carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yi Zhang ◽  
Xiaoliang Hua ◽  
Haoqiang Shi ◽  
Li Zhang ◽  
Haibing Xiao ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Immune Cells ◽  
Renal Cell ◽  
Clear Cell ◽  
Multivariate Analyses ◽  
Enrichment Analysis ◽  
Marker Genes ◽  
Cell Renal Cell Carcinoma ◽  
Coexpressed Genes

Abstract Background Eukaryotic initiation factor 3a (EIF3A), a “reader” protein for RNA methylation, has been found to be involved in promoting tumorigenesis in a variety of cancers. The impact of EIF3A in clear cell renal cell carcinoma (ccRCC) has yet to be reported. This study aimed to identify the prognostic value of EIF3A in ccRCC and investigate the relationship between EIF3A expression and immune infiltration. Methods We collected 29 m6A-related mRNA data and clinicopathological parameters from The Cancer Genome Atlas (TCGA) database. Logistic regression analyses were used to analyse the correlation between EIF3A expression and clinical characteristics. Immunohistochemistry (IHC) was applied to examine EIF3A levels in normal and ccRCC tissues. Univariate and multivariate analyses were conducted to recognize independent factors associated with overall survival (OS) and disease-free survival (DFS). The nomogram aimed to predict the 1-, 3- and 5-year survival probabilities. Gene set enrichment analysis (GSEA) was carried out to determine the potential functions and related signalling pathways of EIF3A expression. To investigate EIF3A of coexpressed genes, we used LinkedOmics, and the results were subjected to enrichment analysis. Simultaneously, LinkedOmics and STRING datasets were used to identify EIF3A coexpressed genes that were visualized via Cytoscape. Finally, we evaluated whether EIF3A expression correlated with the infiltration of immune cells and the expression of marker genes in ccRCC by Tumour 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 correlated with poor prognostic clinicopathological factors, and K–M analyses revealed that low EIF3A expression was correlated with a poor prognosis. The results of univariate and multivariate analyses proved that EIF3A was a prognostic factor in ccRCC patients. GSEA results indicated that EIF3A high expression was enriched in the renal cell carcinoma pathway. 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 marker genes of immune cells. Conclusions EIF3A could serve as a potential biomarker for prognostic and diagnostic stratification of ccRCC and is related to immune cell infiltrates.

Tumor infiltrating and peripheral CD4+ILT2+ T cells are a cytotoxic subset selectively inhibited by HLA-G in clear cell renal cell carcinoma patients

2021 ◽  
Author(s):  
Alix Jacquier ◽  
Tiphaine Lambert ◽  
Jean-François Delattre ◽  
Malika Djouadou ◽  
Jérôme Vérine ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma

Tumor-infiltrating CD8+ T cells recognize a heterogeneously expressed functional neoantigen in clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Masahiro Matsuki ◽  
Yoshihiko Hirohashi ◽  
Munehide Nakatsugawa ◽  
Aiko Murai ◽  
Terufumi Kubo ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Cd8 T Cells ◽  
Renal Cell ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma

scholarly journals Determinants of anti-PD1 response and resistance in clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Lewis Au ◽  
Emine Hatipoglu ◽  
Marc Robert de Massy ◽  
Kevin Litchfield ◽  
Andrew Rowan ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Cd8 T Cells ◽  
Renal Cell ◽  
Clear Cell ◽  
Endogenous Retrovirus ◽  
Human Endogenous Retrovirus ◽  
Cell Renal Cell Carcinoma ◽  
Pre Treatment

Antigen recognition and T-cell mediated cytotoxicity in clear-cell renal cell carcinoma (ccRCC) remains incompletely understood. To address this knowledge gap, we analysed 115 multiregion tumour samples collected from 15 treatment-naive patients pre- and post-nivolumab therapy, and at autopsy in three patients. We performed whole-exome sequencing, RNAseq, TCRseq, multiplex immunofluorescence and flow cytometry analyses and correlated with clinical response. We observed pre-treatment intratumoural TCR clonal expansions suggesting pre-existing immunity. Nivolumab maintained pre-treatment expanded, clustered TCR clones in responders, suggesting ongoing antigen-driven stimulation of T-cells. T-cells in responders were enriched for expanded TCF7+CD8+ T-cells and upregulated GZMK/B upon nivolumab-binding. By contrast, nivolumab promoted accumulation of new TCR clones in non-responders, replacing pre-treatment expanded clonotypes. In this dataset, mutational features did not correlate with response to nivolumab and human endogenous retrovirus expression correlated indirectly. Our data suggests that nivolumab potentiates clinical responses in ccRCC by binding pre-existing expanded CD8+ T-cells to enhance cytotoxicity.

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.

Prognostic value of infiltrating immune cells in clear cell renal cell carcinoma (ccRCC)

2019 ◽  
Vol 121 (3) ◽  
pp. 2571-2581 ◽  
Author(s):  
Shiyi Liu ◽  
Saijiao Li ◽  
Yanqing Wang ◽  
Feiyan Wang ◽  
Li Zhang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Immune Cells ◽  
Renal Cell ◽  
Prognostic Value ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma

scholarly journals Tumor-Infiltrating T Cells From Clear Cell Renal Cell Carcinoma Patients Recognize Neoepitopes Derived From Point and Frameshift Mutations

2020 ◽  
Vol 11 ◽  
Author(s):  
Ulla Kring Hansen ◽  
Sofie Ramskov ◽  
Anne-Mette Bjerregaard ◽  
Annie Borch ◽  
Rikke Andersen ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Frameshift Mutations

scholarly journals Identification and validation of dichotomous immune subtypes based on intratumoral immune cells infiltration in clear cell renal cell carcinoma patients

2020 ◽  
Vol 8 (1) ◽  
pp. e000447
Author(s):  
Ying Xiong ◽  
Zewei Wang ◽  
Quan Zhou ◽  
Han Zeng ◽  
Hongyu Zhang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Treatment Response ◽  
Immune Cells ◽  
Renal Cell ◽  
Immune Cell ◽  
Clear Cell ◽  
Biological Pathways ◽  
Cell Renal Cell Carcinoma ◽  
Free Survival

BackgroundIncreasing evidence has elucidated the clinical significance of tumor infiltrating immune cells in predicting outcomes and therapeutic efficacy. In this study, we comprehensively analyze the tumor microenvironment (TME) immune cell infiltrations in clear cell renal cell carcinoma (ccRCC) and correlated the infiltration patterns with anti-tumor immunity and clinical outcomes.MethodsWe analyzed immune cell infiltrations in four independent cohorts, including the KIRC cohort of 533 patients, the Zhongshan ccRCC cohorts of 259 patients, the Zhongshan fresh tumor sample cohorts of 20 patients and the Zhongshan metastatic ccRCC cohorts of 87 patients. Intrinsic patterns of immune cell infiltrations were evaluated for associations with clinicopathological characteristics, underlying biological pathways, genetic changes, oncological outcomes and treatment responses.ResultsUnsupervised clustering of tumor infiltrating immune cells identified two microenvironment subtypes, TMEcluster-A and TMEcluster-B. Gene markers and biological pathways referring to immune evasion were upregulated in TMEcluster-B. TMEcluster-B associated with poor overall survival (p<0.001; HR 2.629) and recurrence free survival (p=0.012; HR 1.870) in ccRCC validation cohort. TMEcluster-B cases had worse treatment response (p=0.009), overall survival (p<0.001; HR 2.223) and progression free survival (p=0.015; HR 2.7762) in metastatic ccRCC cohort. The predictive accuracy of International Metastatic Database Consortium risk score was improved after incorporation of TME clusters.ConclusionsTMEcluster-A featured increased mast cells infiltration, prolonged survival and better treatment response. TMEcluster-B was a heavily infiltrated but immunosuppressed phenotype enriched for macrophages, CD4+T cells, Tregs, CD8+T cells and B cells. TMEcluster-B predicted dismal survival and worse treatment response in clear cell renal cell carcinoma patients.

scholarly journals A Novel Immune-Related lncRNA-Based Model for Survival Prediction in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-37
Author(s):  
Zedan Zhang ◽  
Yanlin Tang ◽  
Yanjun Liu ◽  
Hongkai Zhuang ◽  
Enyu Lin ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Functional Enrichment ◽  
Clinical Parameters ◽  
Training Set ◽  
Cell Renal Cell Carcinoma

Background. Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer whose incidence and mortality rate are increasing. Identifying immune-related lncRNAs and constructing a model would probably provide new insights into biomarkers and immunotherapy for ccRCC and aid in the prognosis prediction. Methods. The transcription profile and clinical information were obtained from The Cancer Genome Atlas (TCGA). Immune-related gene sets and transcription factor genes were downloaded from GSEA website and Cistrome database, respectively. Tumor samples were divided into the training set and the testing set. Immune-related differentially expressed lncRNAs (IDElncRNAs) were identified from the whole set. Univariate Cox regression, LASSO, and stepwise multivariate Cox regression were performed to screen out ideal prognostic IDElncRNAs (PIDElncRNAs) from the training set and develop a multi-lncRNA signature. Results. Consequently, AC012236.1, AC078778.1, AC078950.1, AC087318.1, and AC092535.4 were screened to be significantly related to the prognosis of ccRCC patients, which were used to establish the five-lncRNA signature. Its wide diagnostic capacity was revealed in different subgroups of clinical parameters. Then AJCC-stage, Fuhrman-grade, pharmaceutical, age, and risk score regarded as independent prognostic factors were integrated to construct a nomogram, whose good performance in predicting 3-, 5-, and 7-year overall survival of ccRCC patients was revealed by time-dependent ROC curves and verified by the testing sets and ICGC dataset. The calibration plots showed great agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis showed the signature and each lncRNA were mainly enriched in pathways associated with regulation of immune response. Several kinds of tumor-infiltrating immune cells like regulatory T cells, T follicular helper cells, CD8+ T cells, resting mast cells, and naïve B cells were significantly correlated with the signature. Conclusion. Therefore, we constructed a five-lncRNA model integrating clinical parameters to help predict the prognosis of ccRCC patients. The five immune-related lncRNAs could potentially be therapeutic targets for immunotherapy in ccRCC in the future.

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