scholarly journals Dysregulation of the miRNA biogenesis components DICER1, DROSHA, DGCR8 and AGO2 in clear cell renal cell carcinoma in both a Korean cohort and the cancer genome atlas kidney clear cell carcinoma cohort

2019 ◽  
Author(s):  
Sang Lee ◽  
Hyeonji Min ◽  
Ji Ha ◽  
Byung Kim ◽  
Mi Choi ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Mirna Biogenesis ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals The long noncoding RNA urothelial carcinoma-associated 1 overexpression as a poor prognostic biomarker in clear cell renal cell carcinoma

Tumor Biology ◽  
2017 ◽  
Vol 39 (5) ◽  
pp. 101042831769837 ◽  
Author(s):  
Yang Wang ◽  
Wen Gao ◽  
Jiali Xu ◽  
Yizhi Zhu ◽  
Lingxiang Liu
Keyword(s):  
Renal Cell Carcinoma ◽  
Urothelial Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Noncoding Rna ◽  
Clear Cell ◽  
The Cancer Genome Atlas ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Long noncoding RNA urothelial carcinoma-associated 1 has previously played important roles in cancer. However, its role is still unknown in clear cell renal cell carcinoma. We utilized the most recent molecular and clinical data of clear cell renal cell carcinoma from The Cancer Genome Atlas project, and the relationship between urothelial carcinoma-associated 1 expression and the clinicopathological features was analyzed. Our results indicated that urothelial carcinoma-associated 1 overexpression was associated with male ( p = 0.003), wild-type PBRM1 ( p = 0.021), and BAP1 mutation ( p = 0.022) in clear cell renal cell carcinoma, although lower expression was found in tumors compared with normal controls, validated in tumor tissues from The Cancer Genome Atlas and 21 clear cell renal cell carcinoma patients at our hospital. Moreover, urothelial carcinoma-associated 1 overexpression indicated poor prognosis independently (Hazard Ratio [HR]: 1.92, p = 0.000) in clear cell renal cell carcinoma; it might be a potential detrimental gene considered as a predictive biomarker involved in clear cell renal cell carcinoma.

scholarly journals Caspase 4 Overexpression in Clear Cell Renal Cell Carcinoma and Its Prognostic Role

2020 ◽  
Author(s):  
Lingfeng Meng ◽  
Zijian Tian ◽  
Xingbo Long ◽  
Tongxiang Diao ◽  
Maolin Hu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
The Cancer Genome Atlas ◽  
Cell Renal Cell Carcinoma ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Background: Caspase 4 (CASP4) dysregulation is related to the occurrence, development, and outcome of many malignant tumors, but its role in clear cell renal cell carcinoma (ccRCC) is unclear. This study was conducted to investigate the expression level of CASP4 in tumor tissues and its relationship with clinical prognosis of patients with ccRCC. Methods: First, the Oncomine and The Cancer Genome Atlas databases were used to determine CASP4 mRNA expression in ccRCC and its association with ccRCC prognosis. We then performed immunohistochemical staining and evaluation of 30 paired ccRCC and adjacent normal tissues to confirm these results. The correlation between CASP4 expression and ccRCC prognosis was evaluated using Kaplan-Meier analysis, and related genes and pathways were obtained from The Cancer Genome Atlas database by gene set enrichment analysis and gene set variation analysis. Finally, we explored the co-expression of genes with CASP4 in ccRCC. Results: CASP4 mRNA expression in ccRCC was significantly higher than that in normal tissues (p < 0.001). Kaplan-Meier analysis showed that the overall survival of patients with ccRCC showing high CASP4 expression was significantly reduced (p < 0.001). We then used external datasets (Gene Expression Omnibus database and patients from our center) to verify the level of CASP4 expression and survival differences (all p < 0.05). We also found that differential expression levels of CASP4 were correlated with pathological grade and clinical TNM stage (all p < 0.05). Conclusions: Overall, our study shows that CASP4 is highly expressed in ccRCC and is an important factor affecting prognosis. Thus, CASP4 may be a potential prognostic biomarker of ccRCC.

Prognostic value of genomic signatures in metastatic Clear Cell Renal Cell Carcinoma (mRCC) using The Cancer Genome Atlas (TCGA) data.

2015 ◽  
Vol 33 (15_suppl) ◽  
pp. 4560-4560
Author(s):  
Guillermo de Velasco ◽  
Andre Poisl Fay ◽  
Aedin Culhane ◽  
A. Ari Hakimi ◽  
Martin Henner Voss ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Value ◽  
Clear Cell ◽  
The Cancer Genome Atlas ◽  
Cell Renal Cell Carcinoma ◽  
Genomic Signatures ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals Ferroptosis-Related Gene-Based Prognostic Model and Immune Infiltration in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Guo-Jiang Zhao ◽  
Zonglong Wu ◽  
Liyuan Ge ◽  
Feilong Yang ◽  
Kai Hong ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Renal Cell ◽  
Clear Cell ◽  
The Cancer Genome Atlas ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Genome Atlas ◽  
Score Model ◽  
Genome Atlas

Clear cell renal cell carcinoma (ccRCC) is one of the most common tumors in the urinary system. Ferroptosis plays a vital role in ccRCC development and progression. We did an update of ferroptosis-related multigene expression signature for individualized prognosis prediction in patients with ccRCC. Differentially expressed ferroptosis-related genes in ccRCC and normal samples were screened using The Cancer Genome Atlas. Univariate and multivariate Cox regression analyses and machine learning methods were employed to identify optimal prognosis-related genes. CARS1, CD44, FANCD2, HMGCR, NCOA4, SLC7A11, and ACACA were selected to establish a prognostic risk score model. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that these genes were mainly enriched in immune-related pathways; single-sample Gene Set Enrichment Analysis revealed several immune cells potentially related to ferroptosis. Kaplan–Meier survival analysis demonstrated that patients with high-risk scores had significantly poor overall survival (log-rank P = 7.815 × 10–11). The ferroptosis signature was identified as an independent prognostic factor. Finally, a prognostic nomogram, including the ferroptosis signature, age, histological grade, and stage status, was constructed. Analysis of The Cancer Genome Atlas-based calibration plots, C-index, and decision curve indicated the excellent predictive performance of the nomogram. The ferroptosis-related seven-gene risk score model is useful as a prognostic biomarker and suggests therapeutic targets for ccRCC. The prognostic nomogram may assist in individualized survival prediction and improve treatment strategies.

Association of mutations in chromatin modifiers with poor survival in clear cell renal cell carcinoma: Analysis of the Cancer Genome Atlas Project.

2013 ◽  
Vol 31 (6_suppl) ◽  
pp. 360-360 ◽  
Author(s):  
A. Ari Hakimi ◽  
Irina Ostrovnaya ◽  
Martin Henner Voss ◽  
Robert John Motzer ◽  
Paul Russo ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Competing Risk ◽  
The Cancer Genome Atlas ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Specific Survival ◽  
Epigenetic Modifiers ◽  
Cancer Genome Atlas ◽  
Genome Atlas

360 Background: We have previously shown that mutations in the epigenetic modifiers PBRM1, BAP1, SETD2 and KDM5C are associated with adverse tumor characteristics and, in some cases, worse cancer specific survival in clear cell renal cell carcinoma (ccRCC). We analyzed publically available data from the Cancer Genome Atlas Project (TCGA), to assess the impact of mutations in these genes on cancer-specific survival. Methods: We analayzed the genomic and clinical data from the TCGA cohort of 424 patients with primary ccRCC. The Kaplan-Meier method was used to estimate the survival probabilities, and log-rank test was used to test the univariate association between mutation status and overall survival. Cancer specific survival (CSS) was analyzed using the competing risk method. Multivariate Cox proportional hazard regression and competing risk models were also fitted to adjust for the validated Mayo Clinic SSIGN prognostic score. Results: Mutations in these epigenetic modifiers are frequent (PBRM1, 33.7%; SETD2, 11.6%; BAP1, 9.7%, KDM5C, 5.7%). BAP1 (p=0.002, HR 2.21 [1.34-3.62]), SETD2 (p=0.036, HR 1.68 [1.03-2.72]) and KDM5C (p=0.016, HR 2.18 [1.16-4.11]) are associated with worse CSS by competing risk. When adjusting for the prognostic SSIGN score, only mutations in KDM5C remain significant (p<0.0001 HR 4.03 [2.1-7.9]). On the contrary, PBRM1 mutations, the second most common gene mutations of ccRCC, have no impact on CSS. Conclusions: BAP1, SETD2 and KDM5C mutations are associated with worse CSS, suggesting their roles in disease progression. PBRM1 mutations do not impact CSS, implicating its principal role in the tumor initiation. Future efforts should focus on therapeutic interventions and further clinical, pathologic and molecular interrogation of this novel class of tumor suppressors.

scholarly journals A Novel Prognostic Model for Clear Cell Renal Cell Carcinoma with Differentially Expressed Immune-related lncRNA Pairs Based on the Cancer Genome Atlas

2021 ◽  
Author(s):  
Chen Zhao ◽  
Kewei Xiong ◽  
Fengming Liu ◽  
Xiangpan Li
Keyword(s):  
Renal Cell Carcinoma ◽  
Renal Cell ◽  
Prognostic Model ◽  
Cox Regression ◽  
Clear Cell ◽  
Risk Group ◽  
The Cancer Genome Atlas ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Objective: To construct a novel prognostic model of immune-related lncRNA (irlncRNA) pairs in clear cell renal cell carcinoma (ccRCC). Methods: RNA-seq and clinical data were retrieved from The Cancer Genome Atlas (TCGA). Differentially expressed irlncRNAs (DEirlncRNAs) were obtained by co-expression strategy with immune genes. A 0-1 matrix was constructed according to DEirlncRNAs relevant expression levels. Univariate cox regression was used to select potential target pairs. Lasso regression with cross validation and multivariate cox regression were carried out to extract the final biomarker pairs for risk score calculation. Through calculating the optimal cutoff of AUCs, patients were divided into high and low risk group. Model validation was conducted by independent prognostic analysis, survival analysis, tumor-infiltrating and chemosensitivity analysis. Results: A total of 42 DEirlncRNAs were identified and 12 target pairs were included to construct the final model. The risk score were both significantly different according to univariate (p<0.001, HR=1.391, 95%CI [1.313–1.475]) and multivariate cox regression (p<0.001, HR=1.3104, 95%CI [1.227-1.399]). The AUC reached 0.765 at 1-year, 0.724 at 3-year and 0.785 at 5-year. Patients in the high-risk group had significantly poor survival, higher level of CD8+T infiltration, lower drug sensitivity of sunitinib and temsirolimus but higher sensitivity of lapatinib and pazopanib.Conclusion: The novel prognostic model constructed by paring irlncRNAs showed an effective clinical prediction in ccRCC patients.

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