Overall Survival In ccRCC Research Articles

Overexpression of cyclin F/CCNF as an independent prognostic factor for poor survival in clear cell renal cell carcinoma

Cyclin F (encoded by CCNF gene) has been reported to be implicated in the pathobiology of several human cancers. However, its potential clinical significance in clear cell renal cell carcinoma (ccRCC) remains unknown. The present study aimed to evaluate the potential significance of cyclin F, assessed by immunohistochemical (IHC) staining and molecular (bioinformatics) techniques, as a prognostic marker in ccRCC in relation to clinicopathological features and outcomes. IHC staining was performed using two independent ccRCC tissue array cohorts, herein called tissue macroarray (TMA)_1 and tissue microarray (TMA)_2, composed of 108 ccRCCs and 37 histologically normal tissues adjacent to the tumor (NAT) and 192 ccRCCs and 16 normal kidney samples, respectively. The mRNA expression data were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) public datasets, followed by bioinformatics analysis of biological mechanisms underlying prognosis. The relationship between immune cell infiltration level and CCNF expression in ccRCC was investigated using the Tumor Immune Estimation Resource 2.0 (TIMER2) and Gene Expression Profiling Interactive Analysis 2 (GEPIA2). Cyclin F expression was significantly elevated in ccRCC lesions compared to both NAT and normal renal tissues. Likewise, CCNF mRNA was markedly increased in ccRCCs relative to non-cancerous tissues. In all analyzed cohorts, tumors with features of more aggressive behavior were more likely to display cyclin F/CCNF-high expression than low. Furthermore, patients with high cyclin F/CCNF expression had shorter overall survival (OS) times than those with low expression. In addition, multivariable analysis revealed that cyclin F/CCNF-high expression was an independent prognostic factor for poor OS in ccRCC. Enrichment analysis for mechanistically relevant processes showed that CCNF and its highly correlated genes initiate the signaling pathways that eventually result in uncontrolled cell proliferation. CCNF expression was also correlated with immune cell infiltration and caused poor outcomes depending on the abundance of tumor-infiltrating immune cells in ccRCC. Our findings suggest that cyclin F/CCNF expression is likely to have an essential role in ccRCC pathobiology through regulating multiple oncogenic signaling pathways and affecting the tumor immune microenvironment and may serve as prognostic biomarker and promising therapeutic target in ccRCC.

Metabolic Reprogramming of Cancer Stem Cells and a Novel Eight-Gene Metabolism-Related Risk Signature in Clear Cell Renal Carcinoma

Background:: Clear cell renal carcinoma (ccRCC) is one of the most common urological tumors worldwide and metabolic reprogramming is its distinguishing feature. A systematic study on the role of the metabolism-related genes in ccRCC cancer stem cells (CSCs) is still lacking. Moreover, an effective metabolism-related prediction signature is urgently needed to assess the prognosis of ccRCC patients. Methods:: Gene expression profiles of GSE48550 and GSE84546 were analyzed for the role of metabolism-related gene in ccRCC-CSCs. The GSE22541 dataset were used to construct and validate an effective metabolism-related prediction signature to assess the prognosis of ccRCC patients. Results:: For glycolytic metabolism, we found that HKDC1, PFKM and LDHB were significantly upregulated in ccRCC-CSCs in GSE84546. For TCA cycle, ACO1, SDHA and MDH1 were significantly downregulated in ccRCC-CSCs in both GSE48550 and GSE84546. For fatty acid metabolism, CPT1A and ACACB were significantly upregulated in ccRCC-CSCs in GSE84546. It is worth noting that SCD was significantly downregulated in both GSE48550 and GSE84546. For glutamine metabolism, SLC1A5, GLS and GOT1 were significantly upregulated in GSE84546. An eight-gene CSCs metabolism-related risk signature including HKDC1, PFKM, LDHB, IDH1, OGDH, SDHA, GLS and GLUL were constructed to predict the overall survival (OS) of ccRCC patients. Patients could be separated into two groups, and the patients with lower risk scores had longer survival time. Conclusion:: Our study indicated that metabolic reprogramming, including glycolytic metabolism, TCA cycle, fatty acid metabolism and glutamine metabolism, is more obvious in CD105+ renal cells (GSE84546) than CD133+ renal cells (GSE48550). An eight-gene metabolismrelated risk signature including HKDC1, PFKM, LDHB, IDH1, OGDH, SDHA, GLS and GLUL can effectively predict OS in ccRCC.

Genome sequencing-based prognosis, mutational analysis, and survival rate of clear cell renal cell carcinoma.

e16543 Background: The clear cell renal cell carcinoma (ccRCC) is the most prevalent genitourinary cancer, and carries a poor prognosis. Information regarding whole genome sequencing, a prognostic prediction system, and overall survival in ccRCC is limited. While loss of VHL is commonly implicated in ccRCC, two genes indicated in other cancers, SDHD and ARID1A, have limited literature on their correlation to ccRCC. Hence, we aimed to analyze the genomic profile, epidemiological characteristics and overall survival of ccRCC. Methods: We utilized cBioPortal cancer genomics [The Cancer Genome Atlas (TCGA) PanCancer Atlas, TCGA Firehose Legacy, and TCGA Nature 2013] to study the genetic mutations associated with ccRCC. Epidemiological characteristics and genetic profiles were evaluated, and a query was generated to calculate 5 year and 10 year survival rate with the most common mutations. Log-rank test and Kaplan–Meier estimator were used in analyzing the survival function. Patients with two or more overlapping mutations (72) were excluded. Results: We identified 761 patients with ccRCC, out of which 442 had primary ccRCC with all demographic details available. 65.8% were males, 58.1% were Caucasian, and 7.2% were African American. Majority of patients (199) were between the ages of 50-65 years. 286 (64.7%) were alive and 156 (35.3%) were deceased. The common mutations associated with reduced survival were VHL, BAP1, SDHA, SDHD, and ARID1A. Median survival of patients with VHL, BAP1, SDHA, SDHD, ARID1A mutations was 118.85, 93.04, 40.70, 2.04, and 6.02 months respectively in comparison with unaltered mutation group (78.44 months) (p < 0.0001). (Table 1) Survival was lowest amongst SDHD [2.04 months] and ARID1A [6.02 months]. (p = 3.26e-10). In survival analysis, SDHD and ARID1A were associated with lowest survival after initial diagnosis at 60 months (Figure 1) and 120 months (Figure 2). (p = 2.592e-3). Conclusions: Our study found that SDHD, ARID1A, and SDHA genes were associated with the worst prognosis in ccRCC with median survival of 2.04, 6.02, and 40.70 months. This study may provide insight for targeted therapies for ccRCC and improve the prognosis of these patients. [Table: see text]

Upregulated X-C motif chemokine ligand 2 (XCL2) is associated with poor prognosis and increased immune infiltration in clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is one of the most popular malignant carcinomas in the genitourinary system. As a novel tumor-related gene, X-C Motif Chemokine Ligand 2 (XCL2) was up-regulated in ccRCC. The current study aims to reveal the functional activity of XCL2 in ccRCC. MethodsThe transcriptome profiling, clinical parameters, and simple nucleotide variation profiles of ccRCC samples were obtained from the Cancer Genome Atlas (TCGA) database. The survival analysis, multivariate/univariate Cox analysis, correlation analysis, gene set enrichment analysis (GSEA), and tumor mutation burden (TMB) analysis were performed. Next, immune cell infiltration and immune functions were analyzed. Finally, the functions of XCL2 were investigated in Caki-1 and 786-O cells. ResultsUpregulated XCL2 was associated with worse overall survival of ccRCC and correlated to age, grade, stage, and T stage. Age, grade, and XCL2 were independent prognostic factors. Significant enrichment in apoptosis, DNA replication, and immune response was demonstrated by GSEA. XCL2 was not only tightly associated with immune cell infiltration, but also significantly linked with several immune functions. Moreover, patients, who had higher XCL2 expression, owned higher levels of TMB. Interestingly, XCL2 was positively correlated with common immune checkpoints. In vitro, XCL2 could inhibit apoptosis, and promote proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) of Caki-1 and 786-O cells. ConclusionsIn general, the current study suggested that XCL2 may participate in the progression of ccRCC. Importantly, XCL2 may be a potential new target of immunotherapy.

Comprehensive analysis of a homeobox family gene signature in clear cell renal cell carcinoma with regard to prognosis and immune significance

The homeobox (HOX) family genes have been linked to multiple types of tumors, while their effect on malignant behaviors of clear cell renal cell carcinoma (ccRCC) and clinical significance remains largely unknown. Here, we comprehensively analyzed the expression profiles and prognostic value of HOX genes in ccRCC using datasets from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. We developed a prognostic signature comprising eight HOX genes (HOXB1, HOXA7, HOXB5, HOXD8, HOXD9, HOXB9, HOXA9, and HOXA11) for overall survival prediction in ccRCC and it allowed patients to be subdivided into high- and low-risk groups. Kaplan-Meier survival analysis in all the internal and external cohorts revealed significant difference in clinical outcome of patients in different risk groups, indicating the satisfactory predictive power of the signature. Additionally, we constructed a prognostic nomogram by integrating signature-derived risk score and clinical factors such as gender, age, T and M status, which might be helpful for clinical decision-making and designing tailored management schedules. Immunological analysis revealed that the regulatory T cells (Tregs) infiltrated differently between the two subgroups in both TCGA and ICGC cohorts. ssGSEA method showed that the enrichment scores for mast cells were significantly lower in high-risk group compared with the low-risk group, which was consistent in both TCGA and ICGC cohorts. As for the related immune function, the enrichment scores of APC co-inhibition, para-inflammation, and type II IFN response were consistently lower in high-risk group in both cohorts. Of the eight HOX genes, the mRNA and protein levels of HOXD8 were downregulated in ccRCC than that in normal tissues, and decreased expression of HOXD8 was associated with increased tumor grade and stage, and lymph node metastasis. Survival analysis revealed that lower expression of HOXD8 predicted worse overall survival in ccRCC. In conclusion, our HOX gene-based signature was a favorable indicator to predict the prognosis of ccRCC cases and associated with immune cell infiltration. HOXD8 might be a tumor suppressor gene in ccRCC and a potential predictor of tumor progression.

A pyroptosis-associated signature plays a role in prognosis prediction in clear cell renal cell carcinoma.

BackgroundApproximately 90% of renal malignancies are RCCs (renal cell carcinomas), and the primary subtype in histology is ccRCC (clear cell RCC). In recent years, pyroptosis has been considered a kind of inflammation-related programmed cell death that participates in the invasion, metastasis, and proliferation of tumour cells, thereby influencing tumour prognosis. Nonetheless, the expression level of pyroptosis-associated genes in RCCs and their relationship with prognosis remain obscure.ResultsIn our research, 44 regulators of pyroptosis that were differentially expressed between normal kidney and ccRCC tissues were identified. ccRCC cases were categorized into 2 subgroups according to prognostic-related DEGs (differentially expressed genes), and there was a significant difference in OS (overall survival) between them. The prognostic value of pyroptosis-associated genes was assessed as a signature based on a cohort from TCGA (The Cancer Genome Atlas). Following Cox regression with DEGs and LASSO (least absolute shrinkage and selection operator), a 6-gene signature was established, and all ccRCC cases in the cohort from TCGA were categorized into an LR (low-risk) or HR (high-risk) group (P < 0.001). In combination with clinical features, risk scores were considered a predictive factor of OS in ccRCC. KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) analyses suggest increased immunity and enrichment of genes related to immunity in the HR group.ConclusionsOur findings indicate that genes related to pyroptosis have an important role in tumour immunity and may be used to predict the prognosis of ccRCC.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12920-022-01339-0.

Construction and validation of a ferroptosis-related long noncoding RNA signature in clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is characterized by the accumulation of lipid-reactive oxygen species. Ferroptosis, due to the lipid peroxidation, has been reported to be strongly correlated with tumorigenesis and progression. However, the functions of the ferroptosis process in ccRCC remain unclear.MethodsAfter sample cleaning, data integration, and batch effect removal, we used the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases to screen out the expression and prognostic value of ferroptosis-related lncRNAs and then performed the molecular subtyping using the K-means method. Then, the functional pathway enrichment and immune microenvironment infiltration between the different clusters were carried out. The results showed a significant difference in immune cell infiltration between the two clusters and the associated marker responded to individualized differences in treatment. Then, least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish a prognostic signature based on 5 lncRNAs. This signature could accurately predicted patient prognosis and served as an independent clinical risk factor. We then combined significant clinical parameters in multivariate Cox regression and the prognostic signature to construct a clinical predictive nomogram, which provides appropriate guidance for predicting the overall survival of ccRCC patients.ResultsThe prognostic differentially expressed ferroptosis-related LncRNAs (DEFRlncRNAs) were found, and 5 lncRNAs were finally used to establish the prognostic signature in the TCGA cohort, with subsequently validation in the internal and external cohorts. Moreover, we conducted the molecular subtyping and divided the patients in the TCGA cohort into two clusters showing differences in Hallmark pathways, immune infiltration, immune target expression, and drug therapies. Differences between clusters contributed to individualizing treatment. Furthermore, a nomogram was established to better predict the clinical outcomes of the ccRCC patients.ConclusionsOur study conducted molecular subtyping and established a novel predictive signature based on the ferroptosis-related lncRNAs, which contributed to the prognostic prediction and individualizing treatment of ccRCC patients.

CD103+ Tissue Resident T-Lymphocytes Accumulate in Lung Metastases and Are Correlated with Poor Prognosis in ccRCC.

Simple SummaryClear cell renal cell carcinoma (ccRCC) is a highly immunogenic tumor, with highly heterogeneous responses to immune checkpoint inhibition therapy. The role of immune cells infiltrating distant metastases and their impact on prognosis and response to immunotherapy are still unclear. To elucidate the prognostic value of immune cell subtypes, we analyzed the immune cell infiltrate in ccRCC primary tumors and paired distant metastases. We hypothesized that specific subtypes of immune cells may be involved in the control of metastases and may have an impact on the prognosis of ccRCC.Clear cell renal cell carcinoma (ccRCC) is a highly immunogenic tumor with variable responses to immune checkpoint therapy. The significance of the immune cell infiltrate in distant metastases, their association with the immune infiltrate in the primary tumors and their impact on prognosis are poorly described. We hypothesized that specific subtypes of immune cells may be involved in the control of metastases and may have an impact on the prognosis of ccRCC. We analyzed the immune microenvironment in ccRCC primary tumors with distant metastases, paired distant metastases and non-metastasized ccRCC (n = 25 each group) by immunohistochemistry. Confirmatory analyses for CD8+ and CD103+ cells were performed in a large ccRCC cohort (n = 241) using a TCGA-KIRC data set (ITGAE/CD103). High immune cell infiltration in primary ccRCC tumors was significantly correlated with the development of distant tumor metastasis (p < 0.05). A high density of CD103+ cells in ccRCC was more frequent in poorly differentiated tumors (p < 0.001). ccRCCs showed high levels of ITGAE/CD103 compared with adjacent non-neoplastic tissue. A higher density of CD103+ cells and a higher ITGAE/CD103 expression were significantly correlated with poor overall survival in ccRCC (log rank p < 0.05). Our results show a major prognostic value of the immune pattern, in particular CD103+ cell infiltration in ccRCC, and highlight the importance of the tumor immune microenvironment.

Identification of Survival-Specific Genes in Clear Cell Renal Cell Carcinoma Using a Customized Next-Generation Sequencing Gene Panel.

Purpose: Although mutations are associated with carcinogenesis, little is known about survival-specific genes in clear cell renal cell carcinoma (ccRCC). We developed a customized next-generation sequencing (NGS) gene panel with 156 genes. The purpose of this study was to investigate whether the survival-specific genes we found were present in Korean ccRCC patients, and their association with clinicopathological findings. Materials and Methods: DNA was extracted from the formalin-fixed, paraffin-embedded tissue of 22 ccRCC patients. NGS was performed using our survival-specific gene panel with an Illumina MiSeq. We analyzed NGS data and the correlations between mutations and clinicopathological findings and also compared them with data from the Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) and Renal Cell Cancer-European Union (RECA-EU). Results: We found a total of 100 mutations in 37 of the 156 genes (23.7%) in 22 ccRCC patients. Of the 37 mutated genes, 11 were identified as clinicopathologically significant. Six were novel survival-specific genes (ADAMTS10, CARD6, NLRP2, OBSCN, SECISBP2L, and USP40), and five were top-ranked mutated genes (AKAP9, ARID1A, BAP1, KDM5C, and SETD2). Only CARD6 was validated as an overall survival-specific gene in this Korean study (p = 0.04, r = −0.441), TCGA-KIRC cohort (p = 0.0003), RECA-EU (p = 0.0005). The 10 remaining gene mutations were associated with clinicopathological findings; disease-free survival, mortality, nuclear grade, sarcomatoid component, N-stage, sex, and tumor size. Conclusions: We discovered 11 survival-specific genes in ccRCC using data from TCGA-KIRC, RECA-EU, and Korean patients. We are the first to find a correlation between CARD6 and overall survival in ccRCC. The 11 genes, including CARD6, NLRP2, OBSCN, and USP40, could be useful diagnostic, prognostic, and therapeutic markers in ccRCC.

Upregulation of ARNTL2 is associated with poor survival and immune infiltration in clear cell renal cell carcinoma

BackgroundAryl hydrocarbon receptor nuclear translocator like 2 (ARNTL2) is a member of the PAS superfamily. Previous studies explored the carcinogenic roles of transcription factor ARNTL2 in human malignancies. However, its roles in ccRCC have not been elucidated. This study sought to explore the roles of ARNTL2 in ccRCC and determine its correlations with tumor immunity.MethodsThe expression of ARNTL2 was analyzed using the GEO, TCGA and GTEx database, and verified in ccRCC tissue samples and cell lines by qRT-PCR and western blot analysis. Kaplan–Meier survival curve analysis, Cox regression analysis (including univariate and multivariate analysis) was utilized to evaluate the prognostic values of ARNTL2. Potential biological mechanisms of ARNTL2 were explored using GSEA method. Colony formation and wound healing assays were conducted to explore the oncogenic role of ARNTL2 in ccRCC. ssGSEA and xCell algorithm were used to explore the correlation between ARNTL2 expression and tumor immune microenvironment (TIME).ResultsARNTL2 was significantly upregulated in ccRCC tissues and cell lines compared to normal kidney tissues and cell line. Enhanced expression of ARNTL2 was strongly linked to advanced clinical stage and unfavorable overall survival in ccRCC. ARNTL2 was determined as an independent prognostic marker through cox regression analysis. A prognostic nomogram was constructed to predict 1-, 3- and 5-year overall survival of ccRCC patients by integrating ARNTL2 expression with other clinicopathologic variables. GSEA analysis showed that focal adhesion, T cell receptor, cell cycle, and JAK-STAT signaling pathway were significantly enriched in high ARNTL2 samples. Silencing of ARNTL2 suppressed the colony formation ability and wound healing efficacy of ccRCC cell lines. xCell analysis showed that high expression level of ARNTL2 exhibited an immune infiltration status similar to CD8 + inflamed ccRCC subtype, which was characterized by high infiltration level of CD8 + T cell and high expression level of the immune escape biomarkers such as PD-L1, PD-L2, PD1 and CTLA4.ConclusionARNTL2 is an independent adverse predictor of ccRCC patient survival. High expression level of ARNTL2 is associated with immune infiltration, and may be a novel therapeutic target in ccRCC.

Leibovich score is the optimal clinico-pathological system associated with recurrence of non-metastatic clear cell renal cell carcinoma

PurposeTo determine the optimal post-operative risk stratification system associated with survival following surgery for clear cell renal cell carcinoma (ccRCC): tumour grade, tumour stage, Leibovich 2003, Leibovich 2018, Kattan, Stage, size, grade and necrosis (SSIGN) or UCLA Integrated Staging System (UISS) scores. Methods542 patients with non-metastatic ccRCC who underwent nephrectomy 2008−2018 were reviewed. Primary outcome was recurrence-free survival (RFS), with secondary outcomes cancer-specific survival (CSS) and overall survival (OS). ResultsAll systems were significantly associated with RFS, CSS and OS by Kaplan-Meier and unadjusted Cox-regression. ROC analysis identified that Leibovich 2003, Leibovich 2018A or B and SSIGN were optimally association with 5year RFS (AUC (Area under curve) 0.87, 0.86, 0.86 and 0.86), but Leibovich 2003 or 2018A offered additional information on adjusted regression analysis (HR 1.24, P = 0.02; HR 1.17, P = 0.04). ROC analysis identified that Leibovich 2018B, Leibovich 2003, SSIGN and UISS were equally associated with 5 year OS (AUC 0.76, 0.74, 0.73 and 0.72). UISS added additional explanation of the variance in OS on adjusted regression analysis (HR 1.96, P = 0.002). A novel combination of Leibovich 2003 score and Eastern Co-operative Oncology Group (ECOG) performance status improved 5 year OS association compared to the Leibovich 2003 alone (AUC 0.78, P = 0.001), without affecting association with 5year RFS (AUC 0.87, P = 0.75). ConclusionsAll systems were robust tools associated with RFS, CSS and OS in ccRCC. In our cohort, the Leibovich 2003 and Leibovich 2018A scores may be better associated with RFS compared to other strategies. The UISS, Leibovich 2018B or Leibovich 2003 combined with ECOG performance status may stratify OS better than other modalities.

Global Characterization of Immune Infiltration in Clear Cell Renal Cell Carcinoma.

BackgroundImmunotherapy has revolutionized the treatment of clear cell renal cell carcinoma (ccRCC). However, the therapy is constrained by drug resistance. Therefore, further characterization of immune infiltration in ccRCC is needed to improve its efficacy.MethodsHere, we adopted the CIBERSORT method to analyze the level of 22 immune cells, and analyzed the correlation of immune cells and clinical parameters in ccRCC in The Cancer Genome Atlas. We used consensus clustering to cluster ccRCC and identified differently expressed genes (DEGs) between hot and cold tumors using the “Limma” package, and then performed enrichment analysis of DEGs. Finally, we constructed and validated a Cox regression model using the “survival”, “glmnet”, and “survivalROC” packages, implemented in R.ResultsRegulatory T cells upregulated in tumor tissue increased during tumor progression, and correlated with poor overall survival in ccRCC. Consensus clustering identified four clusters of ccRCC. To elucidate the underlying mechanisms of immune cell infiltration, we subdivided these four clusters into two major types, immune hot and cold, and identified DEGs between them. The results revealed different transcription profiles in the two tumor types, with hot tumors being enriched in immune-related signaling, whereas cold tumors were enriched in extracellular matrix remodeling and the phosphatidylinositol 3-kinase–AKT (PI3K/AKT) pathway. We further identified hub genes and prognostic-related genes from the DEGs, and constructed a Cox regression model for predicting the overall survival of patients with ccRCC. The areas under the receiver operating characteristics curve for the risk model for the training, testing, and external Zhengzhou validation cohorts were 0.834, 0.733, and 0.812, respectively. Notably, gene sets in the prediction model could also predict the overall survival of patients receiving immunotherapy.ConclusionThese findings provide a comprehensive characterization of immune infiltration in ccRCC, while the constructed model can be used effectively to predict the overall survival of ccRCC patients.

Low expression of ferritinophagy-related NCOA4 gene in relation to unfavorable outcome and defective immune cells infiltration in clear cell renal carcinoma

BackgroundClear cell renal cell carcinoma is susceptible to ferroptosis, and immunotherapy is recently recommended as a priority for the initial treatment of metastatic clear cell renal carcinoma. Increased ferroptosis and immune activation can synergistically reinforce each other in killing cancer cells. NCOA4 depletion can eliminate iron accumulation and thus weaken ferroptosis. Here, we aim to identify and validate the association between NCOA4 expression, clinicopathologic characteristics, and overall survival in ccRCC by using The Cancer Genome Atlas and Gene Expression Omnibus databases. We further analyze the interacted proteins of NCOA4 and infiltrated immune cells via TIMER and GEPIA databases.MethodsNCOA4 expression in clear cell renal carcinoma (ccRCC) tissues and normal adjacent tissues in The Cancer Genome Atlas (TCGA) data were primarily screened, and further validated in another independent cohort from the gene expression omnibus (GEO) database and human protein atlas. The relationships of NCOA4 expression and clinicopathologic parameters and overall survival (OS) were assessed using multivariate methods and Kaplan-Meier survival curves. And the proteins network with which NCOA4 interacted were also built using the online STRING website. Meanwhile, we use TIMER and GEPIA databases to investigate the relationships between NCOA4 expression and infiltrated immune cells and their corresponding gene marker sets.ResultsContrast to normal tissue, NCOA4 expression was lower in ccRCC tumor tissue(p < 0.05). Lower NCOA4 expression was closely associated with high-grade malignancy and advanced TNM stage. Univariate and multivariate analysis indicated the overall survival of ccRCC cases with low NCOA4 level is shorter than those of patients with high NCOA4 expression (p < 0.05). FTL and FTH1 were the important proteins interacting with NCOA4. ccRCC with NCOA4 deficiency presented the paucity of infiltrated immune cells and their matching marker sets, including CD8+ T cells.ConclusionDeficient NCOA4 expression was related to disease progression and poor prognosis, as well as impaired infiltration of immune cells in ccRCC.

Nucleolar protein NOP2 could serve as a potential prognostic predictor for clear cell renal cell carcinoma

ABSTRACT As an indispensable part for cancer precision medicine, biomarkers and signatures for predicting cancer prognosis and therapeutic benefits were urgently required. The purpose of this study was to investigate the prognostic roles of NOP2 in renal clear cell carcinoma (ccRCC) for overall survival (OS) and its relationships with immunity. NOP2-related gene expression matrix associated with clinical information was obtained from the Cancer Genome Atlas (TCGA) ccRCC dataset and NOP2-related pathways were identified by gene set enrichment analysis (GSEA). Associations among the NOP2 expression and MSI, TMB, TNB, and immunity were also explored. Both the NOP2 mRNA and protein/phosphoprotein had a higher expression in ccRCC tumor tissues than in normal kidney tissues (both P < 0.001) and elevated NOP2 expression was associated with poor OS (P < 0.001). Logistic regression analysis revealed the NOP2 expression was significantly linked to stage, age, grade, N stage, T stage, and M stage (all P < 0.05). Univariate/multivariate Cox hazard regression analysis results indicated that NOP2 was an independent prognostic factor for OS in ccRCC and GSEA revealed five NOP2-related signaling pathways. Nomogram based on NOP2 and eight clinical characteristic parameters (grade, age, stage, gender, T stage, race, M stage, N stage) was constructed and carefully evaluated. Furthermore, NOP2 gene expression was also found to be significantly related to MSI, TMB, and immunity. Our findings revealed that NOP2 might be a potential prognostic factor for OS in ccRCC and it was significantly associated with immunity, MSI, and TMB.

Epigenetic signature predicts overall survival clear cell renal cell carcinoma

BackgroundRecently, increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC).MethodsWe 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.ResultThrough 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.ConclusionsOur 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.

Construction of a Novel Multigene Panel Potently Predicting Poor Prognosis in Patients with Clear Cell Renal Cell Carcinoma.

Simple SummaryClear cell renal cell carcinoma (ccRCC) is the predominant cause of kidney cancer death attributed to its prevalence (70%) and its nature being the most aggressive form of kidney cancer. Most ccRCC deaths are resulted from metastasis. It is essential to know which ccRCCs are at risk of metastasis and the development to lethal disease; however, our capacity for such analysis remains poor. To improve this diagnostic capacity, we have examined a comprehensive ccRCC dataset containing 512 patients and have produced a 9-gene signature. This signature is novel; all its 9 components genes are unknown to be related to ccRCC. Importantly, all 9 individual genes possess significant ability in diagnosis of ccRCC metastasis and fatality; the combination of these genes or this signature predicts deadly ccRCCs at an impressive efficiency. This research will open new avenues in ccRCC research and will have a major impact in reducing ccRCC-associated deaths.We observed associations of IQGAP1 downregulation with poor overall survival (OS) in clear cell renal cell carcinoma (ccRCC). Differentially expressed genes (DEGs, n = 611) were derived from ccRCCs with (n = 111) and without IQGAP1 (n = 397) reduction using the TCGA PanCancer Atlas ccRCC dataset. These DEGs exhibit downregulations of immune response and upregulations of DNA damage repair pathways. Through randomization of the TCGA dataset into a training and testing subpopulation, a 9-gene panel (SigIQGAP1NW) was derived; it predicts poor OS in training, testing, and the full population at a hazard ratio (HR) 2.718, p < 2 × 10−16, p = 1.08 × 10−5, and p < 2 × 10−16, respectively. SigIQGAP1NW independently associates with poor OS (HR 1.80, p = 2.85 × 10−6) after adjusting for a set of clinical features, and it discriminates ccRCC mortality at time-dependent AUC values of 70% at 13.8 months, 69%/31M, 69%/49M, and 75.3%/71M. All nine component genes of SigIQGAP1NW are novel to ccRCC. The inclusion of RECQL4 (a DNA helicase) in SigIQGAP1NW agrees with IQGAP1 DEGs enhancing DNA repair. THSD7A affects kidney function; its presence in SigIQGAP1NW is consistent with our observed THSD7A downregulation in ccRCC (n = 523) compared to non-tumor kidney tissues (n = 100). Collectively, we report a novel multigene panel that robustly predicts poor OS in ccRCC.

PTPRO predicts patient prognosis and correlates with immune infiltrates in human clear cell renal cell carcinoma.

BackgroundThe tumor-suppressive role of protein tyrosine phosphatase receptor type O (PTPRO) has been described in a variety of human cancers; however, the clinical significance of PTPRO in human clear cell renal cell carcinoma (ccRCC) remains unclear.MethodsPTPRO expression in renal cell carcinoma (RCC) was analyzed via the Oncomine database, Gene Expression Omnibus (GEO) datasets, and The Cancer Genome Atlas (TCGA) datasets. The Kaplan-Meier curves and Cox proportional hazards model were used to evaluate the relationship of PTPRO with overall survival in ccRCC. Gene ontology (GO) analysis and gene set enrichment analysis (GSEA) were performed to explore the signaling pathways in which PTPRO may be involved. The correlation between PTPRO and immune infiltrates in ccRCC was investigated via Tumor Immune Estimation Resource (TIMER) database. The association between PTPRO mRNA expression and its methylation in RCC was analyzed using the Cancer Cell Line Encyclopedia (CCLE) dataset, GEO dataset, and cBioPortal database. The impact of PTPRO methylation on overall survival was estimated by the MethSurv database.ResultsWe showed that the expression of PTPRO was significantly lower in human RCC. Moreover, the lower expression of PTPRO was associated with worse overall survival in ccRCC, particularly in the advanced stage patients. Multivariate Cox regression analysis revealed the expression of PTPRO as an independent prognostic predictor for overall survival of ccRCC. Of note, PTPRO was found to be associated with the activation of immune signaling and immune cell infiltration. Furthermore, methylation of PTPRO was prevalently observed in ccRCC, and methylation of PTPRO predicted the poor outcome of ccRCC.ConclusionsOur findings suggested that PTPRO at both RNA and DNA methylation levels had the potential as a prognostic biomarker for predicting prognosis, and PTPRO expression was closely associated with immune infiltration in ccRCC patients.

A-kinase interacting protein 1 high expression correlates with advanced tumor stage and poor overall survival in surgical patients with clear cell renal cell carcinoma.

The present study aimed to detect the A-kinase interacting protein 1 (AKIP1) expression in clear cell renal cell carcinoma (ccRCC) tumor tissues and adjacent tissues, and further investigate the correlation of tumor AKIP1 expression with clinicopathological features and survival profile in ccRCC patients.Totally 210 ccRCC patients who underwent resection were retrospectively reviewed, and their tumor and adjacent tissue specimens were acquired for immunohistochemical detection of AKIP1 expression. The survival data of patients were collected for overall survival (OS) assessment.AKIP1 was upregulated in ccRCC tumor tissues compared with adjacent tissues (P < .001). Tumor AKIP1 expression was positively associated with T stage (P = .019), N stage (P = .032), and TNM stage (P = .005) in ccRCC patients. According to AKIP1 expression in tumor tissues, all patients were grouped as AKIP1 low and high expression (AKIP1 high expression were further divided into AKIP1 high+, high++, and high+++ expression). OS was the lowest in the patients with AKIP1 high+++ expression, followed by those with AKIP1 high++ expression and AKIP1 high+ expression, and then patients with AKIP1 low expression (P < .001). Furthermore, multivariate Cox regression exhibited tumor AKIP1 high expression (P = .017), age (>60 years) (P = .030), pathological grade (G2/G3 vs G1) (P = .037), and TNM stage (II/III vs I) (P < .001) were independent predictive factors for decreased OS in ccRCC patients.AKIP1 presents potency to be a novel biomarker for tumor progression and prognosis surveillance in ccRCC.

Abstract A80: Mapping immune landscape in clear cell renal carcinoma by single-cell genomics

Abstract Human clear cell renal cell carcinoma (ccRCC) is one of the most immunologically distinct tumor types due to high levels of tumor-infiltrating immune cells including T cells, yet not every patient responds to immunotherapy. Interestingly, in contrast to other cancers, infiltration with cytotoxic CD8+ T cells is associated with poorer overall survival in ccRCC, suggesting that subpopulations of CD8+ and other immune cells may underlie this observation. To characterize the tumor immune microenvironment of ccRCC, we applied single-cell RNA sequencing along with T-cell receptor sequencing to map the transcriptomic heterogeneity of 25,688 individual CD45+ lymphoid and myeloid cells in matched tumor and blood from patients with ccRCC. We identified multiple and distinct immune cell phenotypes for B and T (CD4 and CD8) lymphocytes, natural kill (NK) cells, and myeloid cells. Evaluation of T-cell receptor (TCR) sequences revealed limited shared clonotypes between patients, whereas tumor-infiltrating T-cell clonotypes were frequently found in peripheral blood, albeit in lower abundance. Evaluation of myeloid subsets revealed unique gene programs defining monocytes, dendritic cells, and tumor-associated macrophages. In summary, here we have leveraged scRNA-seq to refine our understanding of the relative abundance, diversity, and complexity of the immune landscape of ccRCC. This report represents the first such characterization of the ccRCC immune landscape using scRNA-seq. With further characterization and functional validation, these findings may identify novel subpopulations of immune cells amenable to therapeutic intervention. Citation Format: Ajaykumar Vishwakarma, Nick Bocherding, Michael Chimenti, Purshottam Vishwakarma, Kenneth Nepple, Aliasger Salem, Russell W. Jenkins, Weizhou Zhang, Yousef Zakharia. Mapping immune landscape in clear cell renal carcinoma by single-cell genomics [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2019 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(3 Suppl):Abstract nr A80.

Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer.

Background To elucidate the correlations between tumor microenvironment and clinical characteristics as well as prognosis in clear cell renal cell cancer (ccRCC) and investigate the immune-associated genes by a comprehensive analysis of The Cancer Genome Atlas (TCGA) database. Methods We collected mRNA expression profiles of 537 ccRCC samples from the TCGA database. Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. The differentially expressed genes (DEGs) were screened between high immune/stromal score and low immune/stromal score groups by the cutoff of |log (fold change)| > 1, P value <0.05 by using package “limma” in R. Functional enrichment analysis was performed by DAVID, and the protein-protein interaction network of intersected DEGs between stromal score and immune score groups was conducted using the STRING database. The Kaplan–Meier method was used to explore DEGs with predictive values in overall survival, and the prognostic DEGs were further validated in a Gene Expression Omnibus (GEO) dataset GSE29609. Results A higher immune score was associated with T3/4 (vs. T1/2, P < 0.001), N1 (vs. N0, P=0.05), M1 (vs. M0, P=0.004), G3/4 (vs. G1/2, P < 0.001), advanced AJCC stage (P < 0.001), and shorter overall survival (P=0.04). Intersected DEGs between immune and stromal score groups were 48 upregulated and 47 downregulated genes, with 43 DEGs associated with overall survival in ccRCC. After validation by a cohort of 39 ccRCC cases with detailed follow-up information from GSE29609, six immune-associated DEGs including CASP5, HSD11B1, VSIG4, HMGCS2, HSD11B2, and OGDHL were demonstrated to be predictive of prognosis in ccRCC. Conclusions Our study elucidated tight associations between immune score and clinical characteristics as well as prognosis in ccRCC. Moreover, six DEGs were explored and validated to exert predictive values in overall survival of ccRCC.