scholarly journals Identification of a New Prognostic Risk Signature of Clear Cell Renal Cell Carcinoma Based on N6-Methyladenosine RNA Methylation Regulators

2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Yan Zhang ◽  
Yao Yao ◽  
Xiaochen Qi ◽  
Jianyi Li ◽  
Meihong Liu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Regression Analysis ◽  
Roc Curve ◽  
Cox Regression ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

As the most prevalent internal eukaryotic modification, N6-methyladenosine (m6A) is installed by methyltransferases, removed by demethylases, and recognized by readers. However, there are few studies on the role of m6A in clear cell renal cell carcinoma (ccRCC). In this study, we researched the RNA-seq transcriptome data of ccRCC in the TCGA dataset and used bioinformatics analyses to detect the relationship between m6A RNA methylation regulators and ccRCC. First, we compared the expression of 18 m6A RNA methylation regulators in ccRCC patients and normal tissues. Then, data from ccRCC patients were divided into two clusters by consensus clustering. LASSO Cox regression analysis was used to build a risk signature to predict the prognosis of patients with ccRCC. An ROC curve, univariate Cox regression analysis, and multivariate Cox regression analysis were used to verify this risk signature’s predictive ability. Then, we internally validated this signature by random sampling. Finally, we explored the role of the genes in the signature in some common pathways. Gene distribution between the two subgroups was different; cluster 2 was gender-related and had a worse prognosis. IGF2BP3, IGF2BP2, HNRNPA2B1, and METTL14 were chosen to build the risk signature. The overall survival of the high- and low-risk groups was significantly different ( p = 7.47 e − 12 ). The ROC curve also indicated that the risk signature had a decent predictive significance ( AUC = 0.72 ). These results imply that the risk signature has a potential value for ccRCC treatment.

scholarly journals Expression Status and Prognostic Value of m6A RNA Methylation Regulators in Lung Adenocarcinoma

2020 ◽  
Author(s):  
Rui Wang ◽  
Zian Feng ◽  
Jie Hu ◽  
Xiaodong He ◽  
Zuojun Shen
Keyword(s):  
Regression Analysis ◽  
Survival Analysis ◽  
Roc Curve ◽  
Cox Regression ◽  
Risk Group ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
Prediction Efficiency

Abstract Background: N6-methyladenosine (m6A) RNA modification is the most abundant modification method in mRNA, and it plays an important role in the occurrence and development of many cancers. However, data on the role of m6A RNA methylation regulators in lung adenocarcinoma (LUAD) are still lacking. This paper mainly discusses the role of m6A RNA methylation regulators in LUAD, to identify novel prognostic biomarkers.Methods: The gene expression data of 19 m6A methylation regulator in LUAD patients and its relevant clinical parameters were extracted from The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm were performed to construct a risk signature and evaluated its prognostic prediction efficiency by using the receiver operating characteristic (ROC) curve. The risk score of each patient was calculated according to the risk signature, and LUAD patients were divided into high-risk group and low-risk group. Kaplan-Meier survival analysis and Cox regression analysis were used to identify the independent prognostic significance of risk signature. Finally, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were used to explore the differential signaling pathways and cellular processes between the two groups.Results: The expression of 15 m6A RNA methylation regulators in LUAD tissues was significantly different than that in normal tissues. YTHDF3, YTHDF2, KIAA1429, HNRNPA2B1, RBM15, METTL3, HNRNPC, YTHDF1, IGF2BP2, IGF2BP3, IGF2BP1 were significantly up-regulated in LUAD, and the expressions of FTO, ZC3H13, WTAP, and METL14 were significantly down-regulated. We selected IGF2BP1, HNRNPC, and HNRNPA2B1 to construct the risk signature. ROC curve indicated the area under the curve (AUC) was 0.659, which means the risk signature had a good prediction efficiency. The results of Kaplan-Meier survival analysis and Cox regression analysis showed that the risk score can be used as an independent prognostic factor for LUAD.Conclusions: The m6A RNA methylation regulators IGF2BP1, HNRNPC, and HNRNPA2B1 have a significant correlation with the clinicopathological characteristics of LUAD, which may be a promising prognostic feature and clinical treatment target.

scholarly journals Expression Status and Prognostic Value of m6A RNA Methylation Regulators in Lung Adenocarcinoma

Life ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 619
Author(s):  
Xiuhong Li ◽  
Zian Feng ◽  
Rui Wang ◽  
Jie Hu ◽  
Xiaodong He ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
M6a Rna Methylation ◽  
Prediction Efficiency

N6-methyladenosine (m6A) RNA modification is the most abundant modification method in mRNA, and it plays an important role in the occurrence and development of many cancers. This paper mainly discusses the role of m6A RNA methylation regulators in lung adenocarcinoma (LUAD) to identify novel prognostic biomarkers. The gene expression data of 19 m6A methylation regulators in LUAD patients and its relevant clinical parameters were extracted from The Cancer Genome Atlas (TCGA) database. We selected three significantly differentially expressed m6A regulators in LUAD to construct the risk signature, and evaluated its prognostic prediction efficiency using the receiver operating characteristic (ROC) curve. Kaplan–Meier survival analysis and Cox regression analysis were used to identify the independent prognostic significance of the risk signature. The ROC curve indicated that the area under the curve (AUC) was 0.659, which means that the risk signature had a good prediction efficiency. The results of the Kaplan–Meier survival analysis and Cox regression analysis showed that the risk score can be used as an independent prognostic factor for LUAD. In addition, we explored the differential signaling pathways and cellular processes related to m6A methylation regulators in LUAD.

scholarly journals Prognostic value and immunological role of AXL gene in clear cell renal cell carcinoma associated with identifying LncRNA/RBP/AXL mRNA networks

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yi Wang ◽  
Ye Tian ◽  
Shouyong Liu ◽  
Zengjun Wang ◽  
Qianwei Xing
Keyword(s):  
Renal Cell Carcinoma ◽  
Regression Analysis ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis ◽  
Tcga Dataset

Abstract Backgrounds This article aimed to explore the prognostic and immunological roles of AXL gene in clear cell renal cell carcinoma (ccRCC) for overall survival (OS) and to identify the LncRNA/RBP/AXL mRNA networks. Methods AXL-related gene expression matrix and clinical data were obtained from The Cancer Genome Atlas (TCGA) dataset and AXL-related pathways were identified by gene set enrichment analysis (GSEA). We performed univariate/multivariate Cox regression analysis to evaluate independent prognostic factors and the relationships between AXL and immunity were also investigated. Results The outcomes of us indicated that the AXL mRNA expression was up-regulated in ccRCC samples and high expression of AXL was associated with worse OS in TCGA dataset (P < 0.01). Further external verification results from HPA, UALCAN, ICGC dataset, GSE6344, GSE14994, and qRT-PCR remained consistent (all P < 0.05). AXL was also identified as an independent prognostic factor for ccRCC by univariate/multivariate Cox regression analysis (both P < 0.05). A nomogram including AXL expression and clinicopathological factors was established by us and GSEA results found that elevated AXL expression was associated with the JAK-STAT, P53, WNT, VEGF and MAPK signaling pathways. In terms of immunity, AXL was dramatically linked to tumor microenvironment, immune cells, immune infiltration, immune checkpoint molecules and tumor mutational burden (TMB). As for its potential mechanisms, we also identified several LncRNA/RBP/AXL mRNA axes. Conclusions AXL was revealed to play prognostic and immunological roles in ccRCC and LncRNA/RBP/AXL mRNA axes were also identified by us for its potential mechanisms.

The effect of m6A RNA methylation regulators on tumor microenvironment in clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Shuaishuai Huang ◽  
Xiaodong Qing ◽  
Qiuzi Lin ◽  
Qiaoling Wu ◽  
Xue Wang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Immune Checkpoint ◽  
Renal Cell ◽  
Clear Cell ◽  
Gene Signature ◽  
Consensus Clustering ◽  
Cell Renal Cell Carcinoma ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background: m6A RNA methylation and tumor microenvironment (TME) have been reported to play important roles in the progression and prognosis of clear cell renal cell carcinoma (ccRCC). However, whether m6A RNA methylation regulators affect TME in ccRCC remains unknown. Thus, the current study is designed to comprehensively evaluate the effect of m6A RNA methylation regulators on TME in ccRCC.Methods: Transcriptome data of ccRCC was obtained from The Cancer Genome Atlas (TCGA) database. Consensus clustering analysis was conducted based on the expressions of m6A RNA methylation regulators. Survival differences were evaluated by Kaplan-Meier (K-M) analysis between the clusters. DESeq2 package was used to analyze the differentially expressed genes (DEGs) between the clusters. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were analyzed by ClusterProfiler R package. Immune, stromal and ESTIMATE scores were assessed by ESTIMATE algorithm. CIBERSORT algorithm was applied to evaluate immune infiltration. The expressions of human leukocyte antigen (HLA), immune checkpoint molecules, and Th1/IFNγ gene signature associated with TME were also compared between the clusters. TIDE algorithm and subclass mapping were used to analyze the clinical response of different clusters to PD-1 and CTLA-4 blockade. Results: The expressions of fifteen m6A regulators were significantly different between ccRCC and normal kidney tissues. Based on the expressions of those fifteen m6A regulators, two clusters were identified by consensus clustering, in which cluster 1 had better overall survival (OS). A total of 4,429 DEGs were found between the two clusters, and were enriched into immune-related biological processes. Further analysis of the two clusters’ TME showed that cluster 1 had lower immune and ESTIMATE scores, higher expressions of HLA and lower expressions of immune checkpoint molecules. Besides, immune infiltration and the expressions of Th1/IFNγ gene signature also have significant differences between two clusters. Conclusions: Our study revealed that m6A regulators were important participants in the development of ccRCC, with a close relationship with TME.

scholarly journals N6-Methyladenosine-Related Long Non-coding RNA Signature Associated With Prognosis and Immunotherapeutic Efficacy of Clear-Cell Renal Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Tianming Ma ◽  
Xiaonan Wang ◽  
Jiawen Wang ◽  
Xiaodong Liu ◽  
Shicong Lai ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differential Expression ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis

Increasing evidence suggests that N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) play important roles in cancer progression and immunotherapeutic efficacy in clear-cell renal cell carcinoma (ccRCC). In this study, we conducted a comprehensive ccRCC RNA-seq analysis using The Cancer Genome Atlas data to establish an m6A-related lncRNA prognostic signature (m6A-RLPS) for ccRCC. Forty-four prognostic m6A-related lncRNAs (m6A-RLs) were screened using Pearson correlation analysis (|R| &gt; 0.7, p &lt; 0.001) and univariable Cox regression analysis (p &lt; 0.01). Using consensus clustering, the patients were divided into two clusters with different overall survival (OS) rates and immune status according to the differential expression of the lncRNAs. Gene set enrichment analysis corroborated that the clusters were enriched in immune-related activities. Twelve prognostic m6A-RLs were selected and used to construct the m6A-RLPS through least absolute shrinkage and selection operator Cox regression. We validated the differential expression of the 12 lncRNAs between tumor and non-cancerous samples, and the expression levels of four m6A-RLs were further validated using Gene Expression Omnibus data and Lnc2Cancer 3.0 database. The m6A-RLPS was verified to be an independent and robust predictor of ccRCC prognosis using univariable and multivariable Cox regression analyses. A nomogram based on age, tumor grade, clinical stage, and m6A-RLPS was generated and showed high accuracy and reliability at predicting the OS of patients with ccRCC. The prognostic signature was found to be strongly correlated to tumor-infiltrating immune cells and immune checkpoint expression. In conclusion, we established a novel m6A-RLPS with a favorable prognostic value for patients with ccRCC. The 12 m6A-RLs included in the signature may provide new insights into the tumorigenesis and allow the prediction of the treatment response of ccRCC.

scholarly journals Metabolic genes show excellent prognostic ability for clear cell renal cell carcinoma

2020 ◽  
Author(s):  
Chengjian Ji ◽  
Yichun Wang ◽  
Liangyu Yao ◽  
Jiaochen Luan ◽  
Rong Cong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Cell Carcinoma ◽  
Regression Analysis ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Expression Profiles ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis ◽  
Metabolic Genes

Abstract Background Renal cell carcinoma (RCC) is one of the major malignant tumors of the urinary system, with a high mortality rate and a poor prognosis. Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC. Although the diagnosis and treatment methods have been significantly improved, the incidence and mortality of ccRCC are high and still increasing. The occurrence and development of ccRCC are closely related to the changes of classic metabolic pathways. This article aims to explore the relationship between metabolic genes and the prognosis of patients with ccRCC. Patients and methods: Gene expression profiles of 63 normal kidney tissues and 446 ccRCC tissues from TCGA database and gene expression profiles of 39 ccRCC tissues from GEO database were used to obtain differentially expressed genes (DEGs) in ccRCC. Through the the KEGG gene sets of GSEA database, we obtained metabolic genes (MGs). Univariate Cox regression analysis was used to identify prognostic MGs. Lasso regression analysis was used to eliminate false positives because of over-fitting. Multivariate Cox regression analysis was used to established a prognostic model. Gene expression data and related survival data of 101 ccRCC patients from ArrayExpress database were used for external validation. Survival analysis, ROC curve analysis, independent prognostic analysis and clinical correlation analysis were performed to evaluate this model. Results We found that there were 479 abnormally expressed MGs in ccRCC tissues. Through univariate Cox regression analysis, Lasso regression analysis and multivariate Cox regression analysis, we identified 4 prognostic MGs (P4HA3, ETNK2, PAFAH2 and ALAD) and established a prognostic model (riskScore). Whether in the training cohort, the testing cohort or the entire cohort, this model could accurately stratify patients with different survival outcomes. The prognostic value of riskScore and 4 MGs was also confirmed in the ArrayExpress database. Results of GSEA analysis show that DEGs in patients with better prognosis were enriched in metabolic pathways. Then, a new Nomogram with higher prognostic value was constructed to better predict the 1-year OS, 3-year OS and 5-year OS of ccRCC patients. In addition, we successfully established a ceRNA network to further explain the differences in the expression of these MGs between high-risk patients and low-risk patients Conclusion We have successfully established a risk model (riskScore) based on 4 MGs, which could accurately predict the prognosis of patients with ccRCC. Our research may shed new light on ccRCC patients' prognosis and treatment management.

scholarly journals The ceRNA Network Has Potential Prognostic Value in Clear Cell Renal Cell Carcinoma: A Study Based on TCGA Database

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Haosheng Liu ◽  
Zhaowen Zhu ◽  
Jianxiong Fang ◽  
Tianqi Liu ◽  
Zhenhui Zhang ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Molecular Mechanisms ◽  
Kidney Development ◽  
Cox Regression ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Cox Regression Analysis ◽  
Cerna Network

Clear cell renal cell carcinoma (ccRCC) is a very common cancer in urology. Many evidences suggest that complex changed pathways take a nonnegligible part in the occurrence and development of ccRCC. Nevertheless, the underlying mechanism is not clear. In this study, the expression data between ccRCC and normal tissue samples in TCGA database were compared to distinguish differentially expressed genes (DEGs: mRNAs, miRNAs, and lncRNAs). Afterwards, we used GO enrichment and KEGG pathway enrichment analyses to explore the functions of these DEGs. We also found the correlation between three RNAs and created a competing endogenous RNA (ceRNA) network. Moreover, we used univariate Cox regression analysis to select DEGs that are connected with overall survival (OS) of ccRCC patients. We found 1652 mRNAs, 1534 lncRNAs, and 173 miRNAs that were distinguished in ccRCC compared with normal tissues. According to GO analysis, the maladjusted mRNAs are mainly concentrated in immune cell activation and kidney development, while according to KEGG, they are mainly concentrated in pathways related to cancer. A total of 5 mRNAs, 1 miRNA, and 4 lncRNAs were connected with patients’ OS. In this article, a network of lncRNA-miRNA-mRNA was established; it is expected to be able to indicate possible molecular mechanisms for initial of ccRCC and provide a new viewpoint for diagnosis of ccRCC.

scholarly journals Prognostic role of PHYH for overall survival (OS) in clear cell renal cell carcinoma (ccRCC)

2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Qiu Zhengqi ◽  
Guo Zezhi ◽  
Jiang Lei ◽  
Qiu He ◽  
Pan Jinyao ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cox Regression ◽  
Clear Cell ◽  
Regression Analyses ◽  
Prognostic Role ◽  
Pyruvate Metabolism ◽  
Cell Renal Cell Carcinoma ◽  
Pathologic Features

AbstractThis study attempts to evaluate the prognostic role of PHYH for overall survival (OS) in clear cell renal cell carcinoma (ccRCC) by means of publicly available data from The Cancer Genome Atlas (TCGA). Clinical pathologic features and PHYH expression were downloaded from the TCGA database and relationships between them were analyzed by univariate and multivariate Cox regression analyses. Gene Set Enrichment Analysis (GSEA) and gene–gene interactions were also performed between tissues with different PHYH expression levels. PHYH expression levels were significantly lower in patient with ccRCC compared with normal tissues (p = 1.156e−19). Kaplan–Meier survival analysis showed that high expression of PHYH had a better prognosis than low expression (p = 9e−05). Moreover, PHYH expression was also significantly associated with high grade (G2-4, p = 0.025), high stage (StageIII & IV, p = 5.604e−05), and high level of stage_T (T3-4, p = 4.373e−05). Univariate and multivariate Cox regression analyses indicated that PHYH could be acted as an independent prognostic factor (p < 0.05). Nomogram including clinical pathologic features and PHYH expression were also provided. GSEA revealed that butanoate metabolism, histidine metabolism, propanoate metabolism, pyruvate metabolism, tryptophan metabolism, PPAR signalling pathway, and renin–angiotensin system were differentially enriched in PHYH high-expression phenotype. ICGC database was utilized to verify the expression level and survival benefit of PHYH (both p < 0.05). We suspect that elevated PHYH expression may be served as a potential prognostic molecular marker of better survival in ccRCC. Besides, alpha-oxidation was closely regulated by PHYH, and PPAR signalling, pyruvate metabolism, butanoate metabolism, and RAS might be the key pathways regulated by PHYH in CCRC.

scholarly journals Bim Expression in Peritumoral Lymphocytes is Associated with Survival in Patients with Metastatic Clear Cell Renal Cell Carcinoma

Kidney Cancer ◽  
2021 ◽  
pp. 1-7
Author(s):  
Bimal Bhindi ◽  
Elizabeth Bearrick ◽  
John C. Cheville ◽  
Christine M. Lohse ◽  
Ross J. Mason ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cox Regression ◽  
Clear Cell ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Specific Survival ◽  
Immunohistochemistry Staining ◽  
Multivariable Adjustment

Background: Bim (BCL-2-interacting mediator of cell death) is a downstream pro-apoptotic signaling molecule activated by the PD-1 pathway. Objective: We sought to determine if Bim expression in peritumoral T-lymphocytes (PTLs) is associated with survival in patients with metastatic clear cell renal cell carcinoma (ccRCC). Methods: Immunohistochemistry staining for Bim was performed on paraffin-embedded tumor tissue blocks from patients with metastatic ccRCC who underwent nephrectomy between 1990-2004. Associations of Bim expression with cancer-specific survival (CSS) and overall survival (OS) from date of metastasis were evaluated using multivariable Cox regression models, adjusting for age, sex, and metastases-score. Results: 525 patients with metastatic ccRCC, of whom 169 (32%) had metastases at time of nephrectomy were studied. After multivariable adjustment, high Bim expression remained associated with worse CSS (HR = 1.31; 95%CI 1.07–1.59; p = 0.008) and OS (HR = 1.28; 95%CI 1.06–1.55; p = 0.01). The interaction between Bim and PD-L1 was not statistically significant for CSS (p = 0.68) or OS (p = 0.57), suggesting that the associations between Bim and survival outcomes were not significantly different based on tumor PD-L1 expression. Conclusion: High Bim expression in PTLs at nephrectomy is prognostic of worse CSS and OS in patients with metastatic ccRCC, irrespective of tumor PD-L1 expression. The role of earlier PD-1/PD-L1-directed therapy warrants evaluation in these patients.

scholarly journals The Significance of Fibrosis Quantification as a Marker in Assessing Pseudo-Capsule Status and Clear Cell Renal Cell Carcinoma Prognosis

Diagnostics ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 895
Author(s):  
Caipeng Qin ◽  
Huaqi Yin ◽  
Huixin Liu ◽  
Feng Liu ◽  
Yiqing Du ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cox Regression ◽  
Clear Cell ◽  
Progression Free Survival ◽  
Cell Renal Cell Carcinoma ◽  
Free Survival ◽  
Pathological Characteristics ◽  
Kaplan Meier

Fibrosis plays an important role in tumor growth and progression, and thus, we aimed to determine whether renal fibrosis is correlated with the clinical and pathological characteristics and prognosis of clear cell renal cell carcinoma (ccRCC). Fibrosis, including intra-tumoral fibrosis (ITF), pseudo-capsule (PC) fibrosis and adjacent normal renal interstitial fibrosis, was evaluated in 73 pairs of ccRCC specimens using second harmonic generation combined with two-photon excitation fluorescence (SHG/TPEF). The clinical and pathological characteristics of the patients who were eligible for the present study were recorded. The associations between fibrosis and clinicopathological parameters were analyzed using a Mann-Whitney U test or logistic regression analysis. Progression-free survival (PFS) was analyzed using the Kaplan-Meier method and a Cox regression model. High-resolution images of fibrosis were captured from unstained slides using the SHG/TPEF approach. Both ITF and PC fibrosis were associated with tumor progression in ccRCC. Multivariate logistic regression analysis revealed a significant inverse association between the PC collagen proportional area (CPA) and PC invasion (p < 0.05), suggesting that PC CPA is an independent risk factor or marker for PC invasion. A significant decrease in progression-free survival (PFS), determined by Kaplan-Meier curves, was observed for patients with higher PC CPA status compared with those with lower PC CPA status (p < 0.05). Similar results were observed in patients with PC invasion. In multivariate Cox regression analysis, PC invasion and intra-tumoral necrosis were identified as independent prognostic factors for PFS. Our data suggest that ITF and PC fibrosis are associated with ccRCC progression. In addition, PC fibrosis may act as a marker of PC invasion and an effective quantitative measurement for assessing prognosis.

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