Identification of a hypoxia-associated long non-coding RNA signature and nomogram as a prognostic target for clear cell renal cell carcinoma

Abstract Background To develop a hypoxia-associated long non-coding (lncRNA) signature for risk stratification in clear cell renal cell carcinoma (ccRCC). Methods The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA KIRC) dataset was downloaded and analyzed. Results Four prognostic hypoxia-associated lncRNAs were used for signature construction. The four lncRNAs were downregulated in high grade, advanced stage, and high-risk ccRCC. ccRCC patients in the high-risk group had a worse prognosis than those in the low-risk group. And the risk score was significantly higher in high grade and advanced stage. The signature had an independent and long-standing prognosis prediction ability up to 10-year follow-up. Notably, the risk score was significantly positively correlated with the infiltration abundances of six immune cells from the Tumor IMmune Estimation Resource (TIMER). The gene set enrichment analysis (GSEA) also suggested that the signature was involved in the metabolism and tumorigenesis, which were closely related to the hypoxic tumor microenvironment. Ultimately, a nomogram was built to predict the individual long-term survival possibility. Conclusions We have developed a new hypoxia-associated lncRNA signature, representing a promising tool for risk stratification tool in ccRCC. It might serve as a prognostic index to facilitate personalized counseling for treatment.

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A Mitochondrial Dysfunction and Oxidative Stress Pathway-Based Prognostic Signature for Clear Cell Renal Cell Carcinoma

Oxidative Medicine and Cellular Longevity ◽

10.1155/2021/9939331 ◽

2021 ◽

Vol 2021 ◽

pp. 1-32

Author(s):

Yue Wu ◽

Xi Zhang ◽

Xian Wei ◽

Huan Feng ◽

Bintao Hu ◽

...

Keyword(s):

Oxidative Stress ◽

Renal Cell Carcinoma ◽

High Risk ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Risk Group ◽

Prognostic Significance ◽

Individual Risk ◽

Cell Renal Cell Carcinoma

Mitochondria not only are the main source of ATP synthesis but also regulate cellular redox balance and calcium homeostasis. Its dysfunction can lead to a variety of diseases and promote cancer and metastasis. In this study, we aimed to explore the molecular characteristics and prognostic significance of mitochondrial genes (MTGs) related to oxidative stress in clear cell renal cell carcinoma (ccRCC). A total of 75 differentially expressed MTGs were analyzed from The Cancer Genome Atlas (TCGA) database, including 46 upregulated and 29 downregulated MTGs. Further analysis screened 6 prognostic-related MTGs (ACAD11, ACADSB, BID, PYCR1, SLC25A27, and STAR) and was used to develop a signature. Kaplan-Meier survival and receiver operating characteristic (ROC) curve analyses showed that the signature could accurately distinguish patients with poor prognosis and had good individual risk stratification and prognostic potential. Stratified analysis based on different clinical variables indicated that the signature could be used to evaluate tumor progression in ccRCC. Moreover, we found that there were significant differences in immune cell infiltration between the low- and high-risk groups based on the signature and that ccRCC patients in the low-risk group responded better to immunotherapy than those in the high-risk group (46.59% vs 35.34%, P = 0.008 ). We also found that the expression levels of these prognostic MTGs were significantly associated with drug sensitivity in multiple ccRCC cell lines. Our study for the first time elucidates the biological function and prognostic significance of mitochondrial molecules associated with oxidative stress and provides a new protocol for evaluating treatment strategies targeting mitochondria in ccRCC patients.

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Development and validation of a VHL-associated immune prognostic signature for clear cell renal cell carcinoma

Cancer Cell International ◽

10.1186/s12935-020-01670-5 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Jin Zhang ◽

Aiting Yan ◽

Wei Cao ◽

Honglei Shi ◽

Kai Cao ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

High Risk ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Risk Group ◽

Functional Enrichment ◽

Differentially Expressed ◽

Cell Renal Cell Carcinoma ◽

Cox Analysis

Abstract Background VHL mutation is the most common mutation in clear cell renal cell carcinoma (ccRCC). Here, we developed and validated an immune-related signature to predict the prognosis of ccRCC with VHL mutations. Methods VHL mutation status and RNA expression were analysed in the TCGA datasets and our cohort. LASSO Cox analysis was performed to develop an immune-related signature. Candidate genes for the immune-related signature were differentially expressed between VHLwt and VHLmut ccRCC patients. Results VHL mutations resulted in the downregulation of the immune response in ccRCC. To develop an immune-related signature, LASSO Cox analysis was constructed by immune-related genes that were differentially expressed between VHLwt (WHL wild type) and VHLmut (VHL mutation) ccRCC patients. The signature was developed and validated in the TCGA and our own cohort to classify patients into groups based on having a low or high risk of poor survival. Functional enrichment analysis showed that the immune-related pathway represented the major function and pathway. In addition, patients in the high-risk group had a positive correlation with low fractions of CD4 + T cells and dendritic cells and presented a lower expression of CTLA-4 and PD-1 than the low-risk group. Conclusion In this study, we proposed a novel immune-related signature, which is a feasible biomarker for predicting the overall survival in VHLmut patients with ccRCC.

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A Metastasis-Related lncRNA Signature Correlates With the Prognosis in Clear Cell Renal Cell Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.692535 ◽

2021 ◽

Vol 11 ◽

Author(s):

Qian Dou ◽

Shun Gao ◽

Hua Gan ◽

Zhao Kang ◽

Han Zhang ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

High Risk ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Risk Group ◽

Low Risk ◽

Gene Set Enrichment Analysis ◽

Migration And Invasion ◽

Cell Renal Cell Carcinoma

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.

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Bioinformatics profiling integrating a three immune-related long non-coding RNA signature as a prognostic model for clear cell renal cell carcinoma

10.21203/rs.3.rs-17499/v2 ◽

2020 ◽

Author(s):

Yuanbin Jiang ◽

Xin Gou ◽

Zongjie Wei ◽

Jianyu Tan ◽

Haitao Yu ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

High Risk ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Risk Group ◽

High Risk Group ◽

Low Risk ◽

Cell Renal Cell Carcinoma ◽

Immune Score

Abstract Background: Renal cell carcinoma (RCC) is one of the most common aggressive malignant tumors in urogenital system, and the clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinoma. Immune related long non-coding RNAs (IRlncRs) plentiful in immune cells and immune microenvironment (IME) are potential in evaluating prognosis and assessing the effects of immunotherapy. A completed and meaningful IRlncRs analysis based on abundant ccRCC gene samples from The Cancer Genome Atlas (TCGA) will provide insight in this field. Methods: Based on the TCGA dataset, we integrated the expression profiles of IRlncRs and overall survival (OS) in the 611 ccRCC patients. The immune score of each sample was calculated based on the expression level of immune-related genes and used to identify the most meaningful IRlncRs. Survival-related IRlncRs (sIRlncRs) was estimated by calculating the algorithm of difference and COX regression analysis in ccRCC patients. Based on the median immune-related risk score (IRRS) developed from the screened sIRlncRs, the high-risk and low-risk components were distinguished. Functional annotation was detected by gene set enrichment analysis (GSEA) and principal component analysis (PCA), and the immune composition and purity of the tumor was evaluated by microenvironment cell population records. The expression levels of three sIRlncRs were verified in various tissues and cell lines.Results: A total of 39 IRlncRs were collected by Pearson correlation analyses among immune score and the lncRNA expression. A total of 7 sIRlncRs were significantly associated with the clinical outcomes of ccRCC patients. Three sIRlncRs (ATP1A1-AS1, IL10RB-DT and MELTF-AS1) with the most significant prognostic values were enrolled to build the IRRS model in which the OS of in the high-risk group was shorter than that in the low-risk group. The IRRS was identified as an independent prognosis factor and correlated with the OS. The high-risk group and low-risk group illustrated different distributions in PCA and different immune status in GSEA. Besides, we found the more significant expression in certain ccRCC cell lines and tumor tissues of ccRCC patients compared with the HK-2 and adjacent tissues respectively. Additionally, the expression levels of lncR-MELTF-AS1 and IL10RB-DT were remarkably enhanced along the more advanced T-stages, but the lncR-ATP1A1-AS1 showed the inverse gradient.Conclusion: Our results demonstrate some sIRlncRs with remark clinical relevance show the latent monitoring and prognosis values for ccRCC patients and may provide new insight in immunological researches and treatment strategies of ccRCC patients.

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Bioinformatics profiling intergrating a three immune-related long non-coding RNA signature as a prognostic model for clear cell renal cell carcinoma

10.21203/rs.3.rs-17499/v1 ◽

2020 ◽

Author(s):

Xiang Zhou ◽

Xin Gou ◽

Zongjie Wei ◽

Jianyu Tan ◽

Haitao Yu ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

High Risk ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Risk Group ◽

High Risk Group ◽

Low Risk ◽

Cell Renal Cell Carcinoma ◽

Immune Score

Abstract Background: Immune related long non-coding RNAs (IRlncRs) plentiful in immune cells and immune microenvironment (IME) are potential in evaluating prognosis and assessing the effects of immunotherapy. A complete and meaningful IRlncRs analysis based on abundant clear cell renal cell carcinoma (ccRCC) gene samples from The Cancer Genome Atlas (TCGA) will provide insight in this field. Methods: Based on the TCGA dataset, we integrated the expression profiles of IRlncRs and overall survival (OS) in the 611 ccRCC patients. The immune score of each sample was calculated based on the expression level of immune-related genes and used to identify the most meaningful IRlncRs. Survival-related IRlncRs (sIRlncRs) was estimated by calculating the algorithm of difference and COX regression analysis in ccRCC patients. Based on the median immune-related risk score (IRRS) developed from the screened sIRlncRs, the high-risk and low-risk components were distinguished. Functional annotation was detected by gene set enrichment analysis (GSEA) and principal component analysis (PCA), and the immune composition and purity of the tumor was evaluated by microenvironment cell population records. The expression levels of three sIRlncRs were verified in various tissues and cell lines. Results: A total of 39 IRlncRs were collected by Pearson correlation analyses among immune score and the lncRNA expression. A total of 7 sIRlncRs were significantly associated with the clinical outcomes of ccRCC patients. Three sIRlncRs (ATP1A1-AS1, IL10RB-DT and MELTF-AS1) with the most significant prognostic values were enrolled to build the IRRS model in which the OS of in the high-risk group was shorter than that in the low-risk group. The IRRS was identified as an independent prognosis factor and correlated with the OS. The high-risk group and low-risk group illustrated different distributions in PCA and different immune status in GSEA. Besides, we found the more significant expression in certain ccRCC cell lines and tumor tissues of ccRCC patients compared with the HK-2 and adjacent tissues respectively. Additionally, the expression levels of lncR-MELTF-AS1 and IL10RB-DT were remarkably enhanced along the more advanced T-stages, but the lncR-ATP1A1-AS1 showed the inverse gradient. Conclusion: Our results demonstrated some sIRlncRs with remark clinical relevance shown the latent monitoring and prognosis value of ccRCC patients and may provide new insight for immunological research and treatment strategies in ccRCC patients.

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

Frontiers in Oncology ◽

10.3389/fonc.2021.678253 ◽

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.

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