scholarly journals Development and Validation of a Prognostic Gene Signature in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Chuanchuan Zhan ◽  
Zichu Wang ◽  
Chao Xu ◽  
Xiao Huang ◽  
Junzhou Su ◽  
...  

Clear cell renal cell carcinoma (ccRCC), one of the most common urologic cancer types, has a relatively good prognosis. However, clinical diagnoses are mostly done during the medium or late stages, when mortality and recurrence rates are quite high. Therefore, it is important to perform real-time information tracking and dynamic prognosis analysis for these patients. We downloaded the RNA-seq data and corresponding clinical information of ccRCC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A total of 3,238 differentially expressed genes were identified between normal and ccRCC tissues. Through a series of Weighted Gene Co-expression Network, overall survival, immunohistochemical and the least absolute shrinkage selection operator (LASSO) analyses, seven prognosis-associated genes (AURKB, FOXM1, PTTG1, TOP2A, TACC3, CCNA2, and MELK) were screened. Their risk score signature was then constructed. Survival analysis showed that high-risk scores exhibited significantly worse overall survival outcomes than low-risk patients. Accuracy of this prognostic signature was confirmed by the receiver operating characteristic curve and was further validated using another cohort. Gene set enrichment analysis showed that some cancer-associated phenotypes were significantly prevalent in the high-risk group. Overall, these findings prove that this risk model can potentially improve individualized diagnostic and therapeutic strategies.

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qianwei Xing ◽  
Tengyue Zeng ◽  
Shouyong Liu ◽  
Hong Cheng ◽  
Limin Ma ◽  
...  

Abstract Background The role of glycolysis in tumorigenesis has received increasing attention and multiple glycolysis-related genes (GRGs) have been proven to be associated with tumor metastasis. Hence, we aimed to construct a prognostic signature based on GRGs for clear cell renal cell carcinoma (ccRCC) and to explore its relationships with immune infiltration. Methods Clinical information and RNA-sequencing data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and ArrayExpress datasets. Key GRGs were finally selected through univariate COX, LASSO and multivariate COX regression analyses. External and internal verifications were further carried out to verify our established signature. Results Finally, 10 GRGs including ANKZF1, CD44, CHST6, HS6ST2, IDUA, KIF20A, NDST3, PLOD2, VCAN, FBP1 were selected out and utilized to establish a novel signature. Compared with the low-risk group, ccRCC patients in high-risk groups showed a lower overall survival (OS) rate (P = 5.548Ee-13) and its AUCs based on our established signature were all above 0.70. Univariate/multivariate Cox regression analyses further proved that this signature could serve as an independent prognostic factor (all P < 0.05). Moreover, prognostic nomograms were also created to find out the associations between the established signature, clinical factors and OS for ccRCC in both the TCGA and ArrayExpress cohorts. All results remained consistent after external and internal verification. Besides, nine out of 21 tumor-infiltrating immune cells (TIICs) were highly related to high- and low- risk ccRCC patients stratified by our established signature. Conclusions A novel signature based on 10 prognostic GRGs was successfully established and verified externally and internally for predicting OS of ccRCC, helping clinicians better and more intuitively predict patients’ survival.


Author(s):  
Daojun Lv ◽  
Xiangkun Wu ◽  
Ming Wang ◽  
Wenzhe Chen ◽  
Shuxin Yang ◽  
...  

BackgroundClear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma whose pathogenesis is not well understood. We aimed at identifying novel immune-related biomarkers that could be valuable in the diagnosis and prognosis of ccRCC.MethodsThe Robust Rank Aggregation (RRA) method was used to integrate differently expressed genes (DEGs) of 7 Gene Expression Omnibus (GEO) datasets and obtain robust DEGs. Weighted gene co-expression network analyses (WGCNA) were performed to identify hub genes associated with clinical traits in The Cancer Genome Atlas (TCGA) database. Comprehensive bioinformatic analyses were used to explore the role of hub genes in ccRCC.ResultsFour hub genes IFI16, LMNB1, RHBDF2 and TACC3 were screened by the RRA method and WGCNA. These genes were found to be up-regulated in ccRCC, an upregulation that could be due to their associations with late TNM stages and tumor grades. The Receiver Operating Characteristic (ROC) curve and Kaplan-Meier survival analysis showed that the four hub genes had great diagnostic and prognostic values for ccRCC, while Gene Set Enrichment Analysis (GSEA) showed that they were involved in immune signaling pathways. They were also found to be closely associated with multiple tumor-infiltrating lymphocytes and critical immune checkpoint expressions. The results of Quantitative Real-time PCR (qRT-PCR) and immunohistochemical staining (IHC) analysis were consistent with bioinformatics analysis results.ConclusionThe four hub genes were shown to have great diagnostic and prognostic values and played key roles in the tumor microenvironment of ccRCC.


PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e4065 ◽  
Author(s):  
Lei Wang ◽  
Zhiqiang Peng ◽  
Kaizhen Wang ◽  
Yijun Qi ◽  
Ying Yang ◽  
...  

Background Clear cell renal cell carcinoma (ccRCC) is the most common and lethal cancer of the adult kidney. However, its pathogenesis has not been fully understood till now, which hinders the therapeutic development of ccRCC. NADH dehydrogenase (ubiquinone) 1 alpha subcomplex 4-like 2 (NDUFA4L2) was found to be upregulated and play an important role in ccRCC. We aimed to further investigate the underlying mechanisms by which NDUFA4L2 exerted function and its expression level was upregulated. Methods The Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data were mined to verify the change of NDUFA4L2 expression level in ccRCC tissues. The correlation between expression level of NDUFA4L2 and cell proliferation/apoptosis was explored by Gene Set Enrichment Analysis (GSEA). Protein-protein interaction (PPI) network of NDUFA4L2 was constructed. Biological process and involved pathways of NDUFA4L2 were analyzed by gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The transcription factors (TFs) which can induce the expression of NDUFA4L2 were explored in clinical samples by correlation analysis and its regulation on the expression of NDUFA4L2 was verified by knockdown experiment. Results NDUFA4L2 was verified to be overexpressed in ccRCC tissues and its expression level was increased accordingly as the American Joint Committee on Cancer (AJCC) stage progressed. A high NDUFA4L2 level predicted the poor prognosis of ccRCC patients and correlated with enhanced cell proliferation and anti-apoptosis. NDUFA4L2 may interact with 14 tumor-related proteins, participate in growth and death processes and be involved in ccRCC-related pathways, such as insulin-like growth factor 1 (IGF-1), mammalian target of Rapamycin (mTOR) and phosphoinositide 3 kinase serine/threonine protein kinase (PI3K/AKT). ETS domain-containing protein ELK1 level positively correlated with the level of NDUFA4L2 in ccRCC tissues and ELK1 could regulate the expression of NDUFA4L2 in ccRCC cells. Discussion NDUFA4L2 upregulation was associated with ccRCC malignancy. NDUFA4L2 expression was regulated by ELK1 in ccRCC cells. Our study provided potential mechanisms by which NDUFA4L2 affected ccRCC occurrence and progression.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yejinpeng Wang ◽  
Liang Chen ◽  
Lingao Ju ◽  
Kaiyu Qian ◽  
Xinghuan Wang ◽  
...  

Abstract Background Recently, increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC). Methods We used the DNA methylation dataset of The Cancer Genome Atlas (TCGA) database to construct a 31-CpG-based signature which could accurately predict the overall survival of ccRCC. Meanwhile, we constructed a nomogram to predict the prognosis of patients with ccRCC. Result Through LASSO Cox regression analysis, we obtained the 31-CpG-based epigenetic signature which were significantly related to the prognosis of ccRCC. According to the epigenetic signature, patients were divided into two groups with high and low risk, and the predictive value of the epigenetic signature was verified by other two sets. In the training set, hazard ratio (HR) = 13.0, 95% confidence interval (CI) 8.0–21.2, P < 0.0001; testing set: HR = 4.1, CI 2.2–7.7, P < 0.0001; entire set: HR = 7.2, CI 4.9–10.6, P < 0.0001, Moreover, combined with clinical indicators, the prediction of 5-year survival of ccRCC reached an AUC of 0.871. Conclusions Our study constructed a 31-CpG-based epigenetic signature that could accurately predicted overall survival of ccRCC and staging progression of ccRCC. At the same time, we constructed a nomogram, which may facilitate the prediction of prognosis for patients with ccRCC.


2021 ◽  
Vol 10 ◽  
Author(s):  
Yongfeng Wang ◽  
Ci Yin ◽  
Lele Geng ◽  
Weiyang Cai

The malignant phenotypes of cancer are defined not only by its intrinsic tumor cells but also by the tumor infiltrating immune cells (TIICs) recruited to the cancer microenvironment. Clear cell renal cell carcinoma (ccRCC) immune microenvironment plays an important role in the tumorigenesis. This research investigated the characteristics of immune cell invasion of renal cell carcinoma and provided clues for future clinical implementation. Retrospectively, ccRCC gene expression was analyzed with appropriate clinicopathological data from the Cancer Genome Atlas (TCGA) and GEO database up to December 2019. The CIBERSORT algorithm, meta-analysis, principal component analysis (PCA), Single-Sample Gene Set Enrichment Analysis (ssGSEA) and hierarchical agglomerative clustering were used to measure and evaluate the respective proportions of 22 cell types of immune infiltration using normalized gene expression data. We also focused on evaluating the association with TIICs subpopulations and clinical features and molecular subtypes. TIICs subpopulation, especially Macrophages subgroup, T follicular helper (Tfh) cells and CD8 T cells, all contribute to tumorigenesis. Unsupervised clustering analysis revealed that there existed two distinct TIICs subgroups with different survival patterns. TIICs are extensively involved in the pathogenesis and development of the ccRCC. Characterizing the composition of TIICs influences the metabolism of tumors, activity, level, stage, and survival of patients. Collectively, the TIIC analysis has the potential to assist in the assessment and selection of ccRCC prognosis and treatment.


2021 ◽  
Vol 11 ◽  
Author(s):  
Qian Dou ◽  
Shun Gao ◽  
Hua Gan ◽  
Zhao Kang ◽  
Han Zhang ◽  
...  

To explore the role of metastasis-related long noncoding RNA (lncRNA) signature for predicting the prognosis of clear cell renal cell carcinoma (ccRCC) patients. Firstly, metastasis-associated genes were identified to establish a metastasis-related lncRNA signature by statistical analysis. Secondly, the ccRCC patients were grouped into high-risk or low-risk group according to the established signature, and the different pathways between the 2 groups were identified by gene set enrichment analysis (GSEA). Finally, investigations involving PCR, transwell migration and invasion assay were carried out to further confirm our findings. The metastasis-related lncRNA signature was successfully constructed according to 7-metastasis-related genes (ADAM12, CD44, IL6, TFPI2, TGF-β1, THBS2, TIMP3). The diagnostic efficacy and the clinically predictive capacity of the signature were evaluated. Most of the values of the area under the time‐dependent receiver‐operating characteristic (ROC) were greater than 0.70. The nomogram constructed by integrating clinical data and risk scores confirmed that the risk score calculated from our signature was a good prognosis predictor. GSEA analysis showed that some tumor-related pathways were enriched in the high-risk group, while metabolism-related pathways were enriched in the low-risk group. In carcinoma tissues, the SSR3-6, WISP1-2 were highly expressed, but the expression of UBAC2-6 was low there. Knocking down SSR3-6 decreased the ability of migration and invasion in ccRCC cells. In conclusion, we successfully constructed a metastasis-related lncRNA signature, which could accurately predict the survival and prognosis of ccRCC patients.


2022 ◽  
Vol 11 ◽  
Author(s):  
Xi Zhang ◽  
Xiyi Wei ◽  
Yichun Wang ◽  
Shuai Wang ◽  
Chengjian Ji ◽  
...  

BackgroundIt is well known that chronic inflammation can promote the occurrence and progression of cancer. As a type of proinflammatory death, pyroptosis can recast a suitable microenvironment to promote tumor growth. However, the potential role of pyroptosis in clear cell renal cell carcinoma (ccRCC) remains unclear.MethodsThe transcriptome expression profile and mutation profile data of ccRCC with clinical characteristics included in this study were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Consensus clustering was used for clustering. Gene set enrichment analysis (GSEA) analysis were applied to evaluate the biological mechanisms. Single sample gene set enrichment analysis (ssGSEA) was applied for evaluating the proportion of various immune infiltrating cells. The ESTIMATE algorithm was involved to compute the immune microenvironment scores.ResultsAmong the 17 pyroptosis regulators, a total of 15 pyroptosis regulators were differential expressed between tumor and normal tissues, in which 12 of them emerged strong correlations with prognoses. According to the pyroptosis components, the ccRCC patients were divided into four pyroptosis subtypes with different clinical, molecular, and pathway characteristics. Compared with other clusters, cluster B showed the pyroptosis heat phenotype, while cluster D represented the pyroptosis cold phenotype with poor overall survival. In addition, we performed principal component analysis (PCA) on the differential genes between clusters to construct the pyroptosis index. Furthermore, the pyroptosis index was significantly correlated with survival in different tumor mutation statuses and different grades and stages. Besides, the expression of pyroptosis-related regulators was related to the infiltration of immune cells and the expression of immune checkpoints, among which AIM2 was considered as the most significant immune-related pyroptosis regulator. Ultimately, we found that AIM2 was related to the immune activation pathway and was significantly overexpressed in tumor tissues.ConclusionThis study revealed that pyroptosis regulators and pyroptosis index played an important role in the development and prognoses of ccRCC. Moreover, AIM2 can be used as a predictor of the response of immunotherapy. Assessing the pyroptosis patterns may help evaluate the tumor status and guide immunotherapy strategies.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jazmine Arévalo ◽  
David Lorente ◽  
Enrique Trilla ◽  
María Teresa Salcedo ◽  
Juan Morote ◽  
...  

AbstractClear cell renal cell carcinoma (ccRCC) is the most frequent and aggressive subtype of renal carcinoma. So far, the basis of its oncogenesis remains unclear resulting in a deficiency of usable and reliable biomarkers for its clinical management. Previously, we showed that nuclear expression of the signal transducer and activator of transcription 3 (STAT3), phosphorylated at its serine 727 (pS727), was inversely proportional to the overall survival of ccRCC patients. Therefore, in the present study, we validated the value of pS727-STAT3 as a clinically relevant biomarker in ccRCC. This work is a retrospective study on 82 ccRCC patients treated with nephrectomy and followed-up for 10 years. Immunohistochemical expression of pS727-STAT3 was analyzed on a tissue microarray and nuclear and cytosolic levels were correlated with clinical outcome of patients. Our results showed that pS727-STAT3 levels, whether in the nucleus (p = 0.002; 95% CI 1.004–1.026) or the cytosol (p = 0.040; 95% CI 1.003–1.042), significantly correlate with patients’ survival in an independent-manner of clinicopathological features (Fuhrman grade, risk group, and tumor size). Moreover, we report that patients with high pS727-STAT3 levels who undergone adjuvant therapy exhibited a significant stabilization of the disease (~ 20 months), indicating that pS727-STAT3 can pinpoint a subset of patients susceptible to respond well to treatment. In summary, we demonstrated that high pS727-STAT3 levels (regardless of their cellular location) correlate with low overall survival of ccRCC patients, and we suggested the use of pS727-STAT3 as a prognostic biomarker to select patients for adjuvant treatment to increase their survival.


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