scholarly journals The Immune-Related Gene HCST as a Novel Biomarker for the Diagnosis and Prognosis of Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Yongying Zhou ◽  
Xiao Wang ◽  
Weibing Zhang ◽  
Huiyong Liu ◽  
Daoquan Liu ◽  
...  

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney tumor worldwide. Analysis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases showed that the immune-related gene (IRG) hematopoietic cell signal transducer (HCST) could provide guidance for the diagnosis, prognosis, and treatment of ccRCC. The RNA-seq data of ccRCC tissues were extracted from two databases: TCGA (https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga) and GEO (https://www.ncbi.nlm.nih.gov/geo/). Corresponding clinical information was downloaded from TCGA. Immune-related gene data were extracted from the IMMPORT website (https://www.immport.org/). Differential analysis with R software (https://www.r-project.org/) was used to obtain a prognosis model of ccRCC IRGs. The differences were combined with the clinical data to assess the usefulness of the HCST as a prognostic biomarker. Based on data obtained from the Oncomine (https://www.oncomine.org/), Human Protein Atlas (https://www.proteinatlas.org/), and PubMed (https://pubmed.ncbi.nlm.nih.gov/) databases, the expression levels of the HCST in ccRCC, clinical-pathological indicators of relevance, and influence on prognosis were analyzed. Regulation of the HCST gene in ccRCC was assessed by gene set enrichment analysis (GSEA). In TCGA/GEO databases, the high HCST expression in tumor tissues was significantly correlated to the TMN stage, tumor grade, invasion depth, and lymphatic metastasis (p < 0.05). The overall survival (OS) of patients with high HCST gene expression was significantly lower than that of patients with low HCST gene expression (p < 0.001). Multivariate Cox regression analysis suggested that the HCST expression level [hazard ratio (HR) = 1.630, 95% confidence interval (CI) = 1.042–2.552], tumor cell grade (HR = 1.829, 95% CI = 1.115–3.001), and distant metastasis (HR = 2.634, 95%, CI = 1.562–4.442) were independent risk factors affecting the OS of ccRCC patients (all, p < 0.05). The GSEA study showed that there was significant enrichment in cell adhesion, tumorigenesis, and immune and inflammatory responses in HCST high expression samples. Hematopoietic cell signal transducer expression was closely associated with the levels of infiltrating immune cells around ccRCC tissues, especially dendritic cells (DCs). In conclusion, the present study suggested that the HCST was interrelated to the clinicopathology and poor prognosis of ccRCC. High HCST expression was also closely correlated with the levels of tumor-infiltrating immune cells, especially DCs.

2011 ◽  
Vol 186 (5) ◽  
pp. 2071-2077 ◽  
Author(s):  
Weiqi Tan ◽  
Michelle A.T. Hildebrandt ◽  
Xia Pu ◽  
Maosheng Huang ◽  
Jie Lin ◽  
...  

2010 ◽  
Author(s):  
Weiqi Tan ◽  
Michelle AT Hildebrandt ◽  
Xia Pu ◽  
Maosheng Huang ◽  
Pheroze Tamboli ◽  
...  

2016 ◽  
Vol 11 (6) ◽  
pp. 4095-4098 ◽  
Author(s):  
XIANG-HUI NING ◽  
TENG LI ◽  
YAN-QING GONG ◽  
QUN HE ◽  
QI SHEN ◽  
...  

2021 ◽  
Author(s):  
Yi Zhang ◽  
Xiaoliang Hua ◽  
Haoqiang Shi ◽  
Li Zhang ◽  
HaiBing Xiao ◽  
...  

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.


PLoS ONE ◽  
2019 ◽  
Vol 14 (5) ◽  
pp. e0216793 ◽  
Author(s):  
Agnieszka M. Borys ◽  
Michał Seweryn ◽  
Tomasz Gołąbek ◽  
Łukasz Bełch ◽  
Agnieszka Klimkowska ◽  
...  

2019 ◽  
Vol 121 (3) ◽  
pp. 2571-2581 ◽  
Author(s):  
Shiyi Liu ◽  
Saijiao Li ◽  
Yanqing Wang ◽  
Feiyan Wang ◽  
Li Zhang ◽  
...  

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