scholarly journals A Risk Assessment Model of Immune-Associated lncRNA to Predict the Prognosis and Immune Landscape of Renal Clear Cell Carcinoma

2021 ◽  
Author(s):  
Tiantian Ma ◽  
Cuiwen Zhu ◽  
Yiping Duan ◽  
Lingyue Chen ◽  
Jiacui Liu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Characteristic Curve ◽  
Univariate Analysis ◽  
Risk Groups ◽  
Renal Clear Cell Carcinoma ◽  
Assessment Model ◽  
Cell Renal Cell Carcinoma

Abstract Renal cell carcinoma (RCC) is one of the most common malignancies of the urinary system, accounting for 3% of adult malignancies. Long non-coding RNA (lncRNA) is abnormally regulated in many cancers and can be used as a molecular marker for early diagnosis and prognosis of RCC. Here, original lncRNA datas were retrieved from TCGA, differential co-expression analysis was performed to classify immune-related lncRNA (irlncRNA) with differential expression, and the improved 0 or 1 matrix cyclic single pairing method was used to verify lncRNA pairs. Then, we performed a univariate analysis in combination with an improved Lasso penalty regression that included cross-validation, multiple repetitions, and random stimulus procedures to determine different expression irlncRNA (DEirlncRNA) pairs. AUC values under Receiver Operating Characteristic curve (ROC) were calculated to obtain the optimal model, and AIC values of each point on AUC were calculated to obtain the optimal cut-off point to distinguish the high and low risk groups of Clear-cell renal cell carcinoma (ccRCC) patients. Finally, we evaluated the new model in a variety of clinical settings including survival, clinicopathological features, tumor-infiltrating immune cells, chemotherapy, and checkpoint related biomarkers, all showing promising clinical application.

scholarly journals A CT-Based Radiomics Approach for the Differential Diagnosis of Sarcomatoid and Clear Cell Renal Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xiaoli Meng ◽  
Jun Shu ◽  
Yuwei Xia ◽  
Ruwu Yang
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Characteristic Curve ◽  
Univariate Analysis ◽  
Image Features ◽  
Regression Method ◽  
Cell Renal Cell Carcinoma ◽  
Significant Difference

This study was aimed at building a computed tomography- (CT-) based radiomics approach for the differentiation of sarcomatoid renal cell carcinoma (SRCC) and clear cell renal cell carcinoma (CCRCC). It involved 29 SRCC and 99 CCRCC patient cases, and to each case, 1029 features were collected from each of the corticomedullary phase (CMP) and nephrographic phase (NP) image. Then, features were selected by using the least absolute shrinkage and selection operator regression method and the selected features of the two phases were explored to build three radiomics approaches for SRCC and CCRCC classification. Meanwhile, subjective CT findings were filtered by univariate analysis to construct a radiomics model and further selected by Akaike information criterion for integrating with the selected image features to build the fifth model. Finally, the radiomics models utilized the multivariate logistic regression method for classification and the performance was assessed with receiver operating characteristic curve (ROC) and DeLong test. The radiomics models based on the CMP, the NP, the CMP and NP, the subjective findings, and the combined features achieved the AUC (area under the curve) value of 0.772, 0.938, 0.966, 0.792, and 0.974, respectively. Significant difference was found in AUC values between each of the CMP radiomics model (0.0001≤p≤0.0051) and the subjective findings model (0.0006≤p≤0.0079) and each of the NP radiomics model, the CMP and NP radiomics model, and the combined model. Sarcomatoid change is a common pathway of dedifferentiation likely occurring in all subtypes of renal cell carcinoma, and the CT-based radiomics approaches in this study show the potential for SRCC from CCRCC differentiation.

Hypoxia-related lncRNA Signature to Predict the Survival of Patients with Clear Cell Renal Cell Carcinoma

2022 ◽  
Author(s):  
Fu Liu ◽  
Xinyuan Li ◽  
Xiang Zhou ◽  
Hang Tong ◽  
Xin Gou
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Risk Group ◽  
Clear Cell Carcinoma ◽  
Risk Groups ◽  
Renal Clear Cell Carcinoma ◽  
Low Risk ◽  
Cell Renal Cell Carcinoma

Abstract Background: Renal cell carcinoma is the most common aggressive tumor of the genitourinary system. The main pathological subtype is clear cell renal cell carcinoma (ccRCC), and its treatment options are very limited. Therefore, identifying specific markers of renal clear cell carcinoma is of great significance for diagnosis and prognosis.Methods: From the TCGA database, we obtained information on 611 patients with renal clear cell carcinoma to analyze the relationship between hypoxia-related lncRNAs and overall survival. According to the coexpression of hypoxia genes and lncRNAs, genes related to hypoxia were identified. Difference analysis and Cox regression analysis were applied to assess survival-related risk factors. According to the median risk score of hypoxia-related genes, patients were divided into high-risk and low-risk groups. According to these gene characteristics and clinical parameters, a nomogram map was built, and GSEA was used for gene function annotation. RT-qRCR, Western Blot and Flow Cytometry were used to determine the role of SNHG19 in RCC cells.Results: By analyzing the coexpression of hypoxia genes and lncRNAs, 310 hypoxia-related genes were obtained. Six sHRlncRs were significantly correlated with the clinical outcomes of patients with ccRCC. Four sHRlncRs (AC011445.2, PTOV1-AS2, AP004609.3, and SNHG19) with the highest prognostic values were included in the group to construct the HRRS model. The high-risk group had a shorter OS than the low-risk group. HR-lncRNAs were considered to be an independent prognostic factor and associated with OS. The high- and low-risk groups showed different pathways in GSEA. Experiments showed that SNHG19 plays essential roles in autophagy and apoptosis of RCC cells.Conclusion: Our research shows that we established and verified a hypoxia-related lncRNA model that accurately correlates with ccRCC patients. This study also provides novel insights into hypoxia-based mechanisms and provides new biomarkers for the poor prognosis of ccRCC patients.

scholarly journals LRRC19—A Bridge between Selenium Adjuvant Therapy and Renal Clear Cell Carcinoma: A Study Based on Datamining

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 440
Author(s):  
Yitong Zhang ◽  
Jiaxing Wang ◽  
Xiqing Liu
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Independent Risk Factor ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Cell Renal Cell Carcinoma ◽  
Low Expression

Kidney renal clear cell carcinoma (KIRC) is the most common and fatal subtype of renal cancer. Antagonistic associations between selenium and cancer have been reported in previous studies. Selenium compounds, as anti-cancer agents, have been reported and approved for clinical trials. The main active form of selenium in selenoproteins is selenocysteine (Sec). The process of Sec biosynthesis and incorporation into selenoproteins plays a significant role in biological processes, including anti-carcinogenesis. However, a comprehensive selenoprotein mRNA analysis in KIRC remains absent. In the present study, we examined all 25 selenoproteins and identified key selenoproteins, glutathione peroxidase 3 (GPX3) and type 1 iodothyronine deiodinase (DIO1), with the associated prognostic biomarker leucine-rich repeat containing 19 (LRRC19) in clear cell renal cell carcinoma cases from The Cancer Genome Atlas (TCGA) database. We performed validations for the key gene expression levels by two individual clear cell renal cell carcinoma cohorts, GSE781 and GSE6344, datasets from the Gene Expression Omnibus (GEO) database. Multivariate survival analysis demonstrated that low expression of LRRC19 was an independent risk factor for OS. Gene set enrichment analysis (GSEA) identified tyrosine metabolism, metabolic pathways, peroxisome, and fatty acid degradation as differentially enriched with the high LRRC19 expression in KIRC cases, which are involved in selenium therapy of clear cell renal cell carcinoma. In conclusion, low expression of LRRC19 was identified as an independent risk factor, which will advance our understanding concerning the selenium adjuvant therapy of clear cell renal cell carcinoma.

A robust ferroptosis-related gene signature predicts overall survival in clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Li Canxuan ◽  
Long Dan
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Risk Groups ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Entire Group ◽  
Cell Renal Cell Carcinoma

Aims: To investigate the prognostic values and potential mechanisms of ferroptosis-related genes in clear cell renal cell carcinoma. Methods: Univariate Cox, least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were employed to identify prognosis-related hub ferroptosis-related genes and establish a prognostic model. Results: The authors established a novel clinical predictive model based on seven hub ferroptosis-related genes in The Cancer Genome Atlas training cohort (n = 374) that was verified in the testing cohort (n = 156) and the entire group (n = 530). Functional analysis indicated that several carcinogenic pathways were enriched. Tumor-infiltrating cells and immunosuppressive molecules were significantly different between the two risk groups. Conclusion: Collectively, the authors successfully constructed a novel ferroptosis-related risk signature that was significantly associated with the prognosis of clear cell renal cell carcinoma.

scholarly journals Comparative effectiveness of adrenal sparing radical nephrectomy and non-adrenal sparing radical nephrectomy in clear cell renal cell carcinoma: Observational study of survival outcomes

2015 ◽  
Vol 9 (9-10) ◽  
pp. 583 ◽  
Author(s):  
Gregory J. Nason ◽  
Leon G. Walsh ◽  
Ciaran E. Redmond ◽  
Niall P. Kelly ◽  
Barry B. McGuire ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Observational Study ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Radical Nephrectomy ◽  
Clear Cell ◽  
Risk Groups ◽  
Survival Outcomes ◽  
Cell Renal Cell Carcinoma

Introduction: We compare the survival outcomes of patients with clear cell renal cell carcinoma (RCC) treated with adrenal sparing radical nephrectomy (ASRN) and non-adrenal sparing radical nephrectomy (NASRN).Methods: We conducted an observational study based on a composite patient population from two university teaching hospitals who underwent RN for RCC between January 2000 and December 2012. Only patients with pathologically confirmed RCC were included. We excluded patients undergoing cytoreductive nephrectomy, with loco-regional lymph node involvement. In total, 579 patients (ASRN = 380 and NASRN = 199) met our study criteria. Patients were categorized by risk groups (all stage, early stage and locally advanced RCC). Overall survival (OS) and cancer-specific survival (CSS) were analyzed for risk groups. Survival analysis was performed using Kaplan-Meier curves and Cox proportional hazards regression.Results: The median follow-up was 41 months (range: 12–157). There were significant benefits in OS (ASRN 79.5% vs. NASRN 63.3%; p = 0.001) and CSS (84.3% vs.74.9%; p = 0.001), with any differences favouring ASRN in all stage. On multivariate analysis, there was a trend towards worse OS (hazard ratio [HR] 1.759, 95% confidence interval [CI] 0.943–2.309, p = 0.089) and CSS (HR 1.797, 95% CI 0.967–3.337, p = 0.064) in patients with NASRN (although not statistically significant). Of these patients, only 11 (1.9%) had adrenal involvement.Conclusions: The inherent limitations in our study include the impracticality of conducting a prospective randomized trial in this scenario. Our observational study with a 13-year follow-up suggests ASRN leads to better survival than NASRN. ASRN should be considered the gold standard in treating patients with RCC, unless it is contraindicated.

scholarly journals Clear-cell Renal Cell Carcinoma: Molecular Characterization of IMDC Risk Groups and Sarcomatoid Tumors

2019 ◽  
Vol 17 (5) ◽  
pp. e981-e994 ◽  
Author(s):  
Annelies Verbiest ◽  
Inne Renders ◽  
Stefano Caruso ◽  
Gabrielle Couchy ◽  
Sylvie Job ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Molecular Characterization ◽  
Renal Cell ◽  
Clear Cell ◽  
Risk Groups ◽  
Cell Renal Cell Carcinoma

scholarly journals Prognostic significance and tumor-immune infiltration of mTOR in clear cell renal cell carcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11901
Author(s):  
Na Li ◽  
Jie Chen ◽  
Qiang Liu ◽  
Hongyi Qu ◽  
Xiaoqing Yang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Univariate Analysis ◽  
Prognostic Significance ◽  
Clinical Role ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Specific Survival ◽  
Immune Infiltration

Mammalian target of rapamycin (mTOR), a serine/threonine kinase involved in cell proliferation, survival, metabolism and immunity, was reportedly activated in various cancers. However, the clinical role of mTOR in renal cell carcinoma (RCC) is controversial. Here we detected the expression and prognosis of total mTOR and phosphorylated mTOR (p-mTOR) in clear cell RCC (ccRCC) patients, and explored the interactions between mTOR and immune infiltrates in ccRCC. The protein level of mTOR and p-mTOR was determined by western blotting (WB), and their expression was evaluated in 145 ccRCC and 13 non-tumor specimens by immunohistochemistry (IHC). The relationship to immune infiltration of mTOR was further investigated using TIMER and TISIDB databases, respectively. WB demonstrated the ratio of p-mTOR to mTOR was higher in ccRCC than adjacent specimens (n = 3), and IHC analysis elucidated that p-mTOR expression was positively correlated with tumor size, stage and metastasis status, and negatively correlated with cancer-specific survival (CSS). In univariate analysis, high grade, large tumor, advanced stage, metastasis, and high p-mTOR expression were recognized as prognostic factors of poorer CSS, and multivariate survival analysis elucidated that tumor stage, p-mTOR and metastasis were of prognostic value for CSS in ccRCC patients. Further TIMER and TISIDB analyses uncovered that mTOR gene expression was significantly associated with numerous immune cells and immunoinhibitors in patients with ccRCC. Collectively, these findings revealed p-mTOR was identified as an independent predictor of poor survival, and mTOR was associated with tumor immune infiltrates in ccRCC patients, which validated mTOR could be implicated in the initiation and progression of ccRCC.

scholarly journals Genomic Analysis Reveals Novel Specific Metastatic Mutations in Chinese Clear Cell Renal Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Hui Meng ◽  
Xuewen Jiang ◽  
Jianfeng Cui ◽  
Gang Yin ◽  
Benkang Shi ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Genomic Analysis ◽  
Renal Clear Cell Carcinoma ◽  
Genomic Feature ◽  
Cell Renal Cell Carcinoma ◽  
Hybridization Capture ◽  
Significant Difference

Clear cell renal cell carcinoma (ccRCC) accounts for more than 75% of renal cell carcinoma. Nearly 25% of ccRCC patients were diagnosed with metastasis. Though the genomic profile of ccRCC has been widely studied, the difference between localized and metastatic ccRCC was not clarified. Primary tumor samples and matched whole blood were collected from 106 sporadic patients diagnosed with renal clear cell carcinoma at Qilu Hospital of Shandong University from January 2017 to November 2019, and 17 of them were diagnosed with metastasis. A hybridization capture-based next-generation sequencing of 618 cancer-related genes was performed to investigate the somatic and germline variants, tumor mutation burden (TMB), and microsatellite instability (MSI). Five genes with significantly different prevalence were identified in the metastatic group, especially TOP1 (17.65% vs. 0%) and SNCAIP (17.65% vs. 0%). The altered frequency of PBRM1 (0% vs. 27%) and BAP1 (24% vs. 10%) differed between the metastatic and nonmetastatic groups, which may relate to the prognosis. Of these 106 patients, 42 patients (39.62%) had at least one alteration in DNA damage repair (DDR) genes, including 58.82% of metastatic ccRCC patients and 35.96% of ccRCC patients without metastasis. Ten pathogenic or likely pathogenic (P/LP) variants were identified in 11 sporadic clear cell renal cell carcinoma patients (10.38%), including rarely reported ATM (n=1), MUTYH (n=1), NBN (n=1), RAD51D (n=1), and BRCA2 (n=1). No significant difference in the ratio of P/LP variant carriers or TMB was identified between the metastatic and nonmetastatic groups. We found a unique genomic feature of Chinese metastatic ccRCC patients with a higher prevalence of alterations in DDR, TOP1, and SNCAIP. Further investigated studies and drug development are needed in the future.

scholarly journals Visceral Adiposity as a Significant Predictor of Sunitinib-Induced Dose-Limiting Toxicities and Survival in Patients with Metastatic Clear Cell Renal Cell Carcinoma

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3602
Author(s):  
Jee Soo Park ◽  
Kyo Chul Koo ◽  
Doo Yong Chung ◽  
Sun Il Kim ◽  
Jeongho Kim ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Body Composition ◽  
Adipose Tissue ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Univariate Analysis ◽  
Progression Free Survival ◽  
Visceral Adiposity ◽  
Cell Renal Cell Carcinoma

Sunitinib is a first-line treatment for metastatic renal cell carcinoma (mRCC). Little is known about the predictive factors of sunitinib-induced dose-limiting toxicity (DLT) in Asian populations. We investigated whether body composition predicts sunitinib-induced DLT. We retrospectively reviewed sunitinib-treated Korean patients with clear cell mRCC from eight institutions. Body composition was measured using computed tomography. DLT was defined as any adverse event leading to dose reduction or treatment discontinuation. Univariate analysis was used to compare body composition indices, and logistic regression analyses were performed for factors predicting early DLT. Overall, 111/311 (32.5%) of patients experienced DLT. Significant differences were observed in the subcutaneous adipose tissue index (SATI; p = 0.001) and visceral adipose tissue index (VATI; p < 0.001) between patients with and without DLT. Multivariate analyses revealed that VATI (odds ratio: 1.013; p = 0.029) was significantly associated with early DLT. Additionally, 20% of patients who had a body mass index (BMI) greater than 23 kg/m2 and a low VATI experienced DLT, whereas 34.3% of the remaining groups had DLT (p = 0.034). Significant differences were observed for median progression-free survival (13.0 vs. 26.0 months, respectively; p = 0.006) between patients with low and high VATI. Visceral adiposity was a significant predictor of sunitinib-associated DLT and survival. Patients with a low VATI and a BMI greater than 23 kg/m2 experienced lower DLTs.

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