A 13-gene risk score system and a nomogram survival model for predicting the prognosis of clear cell renal cell carcinoma

BackgroundRenal cell carcinoma (RCC) is the second common malignant tumor in the urinary system, and 85% of RCC cases are clear cell RCC (ccRCC). This study is designed to build a risk score system for ccRCC.MethodsThe gene methylation and expression data of ccRCC samples were downloaded from The Cancer Genome Atlas database (training set) and ArrayExpress database (validation set). The differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified by limma package, and their intersecting genes with negative Pearson correlation coefficients were remained using cor.test function. Prognosis-associated genes were identified by survival package, and the optimal DMGs were obtained using penalized package. After risk score system was built, nomogram survival model was constructed using rms package. Additionally, pathways were enriched for the DEGs between high- and low-risk groups using Gene Set Enrichment Analysis.ResultsThere were 3,638 DMGs and 2,702 DEGs between tumor and normal samples. Among the 312 intersecting genes, 43 prognosis-associated genes were identified. A total of 13 optimal DMGs (BTBD19, ADAM8, BGLAP, TNFRSF13C, JPH4, BEST1, GNRH2, UBE2QL1, CHODL, GDF9, UPB1, KCNH3; and ADAMTSL4) were obtained for building the risk score system. After pathological M, pathological T, platelet qualitative, and RS status were revealed to be independent prognostic factors, a nomogram survival model was constructed. For the 920 DEGs between the high- and low-risk samples, 6 significant pathways were enriched.ConclusionThe 13-gene risk score system and the nomogram survival model might be used for prognostic prediction of ccRCC patients.     

KCNN4 is a potential prognostic marker and critical factor affecting the immune status of the tumor microenvironment in kidney renal clear cell carcinoma

BackgroundThe tumor microenvironment (TME) has emerged as a crucial factor in cancer development and progression. Recent findings have indicated that tumor-infiltrating immune cells (TICs) in the TME may predict cancer prognosis and response to treatment. Herein, we sought to identify critical modulators of the kidney renal clear cell carcinoma (KIRC) TME.MethodsKIRC datasets from The Cancer Genome Atlas (TCGA) were analyzed using the ESTIMATE algorithm to determine the ImmuneScore and StromalScore. By profiling the differentially expressed genes (DEGs) in the ImmuneScore and StromalScore, we finally identified the immune- and stromal-related DEGs of the cases, through which we then performed intersection analysis to determine the immune-related genes (IRGs). Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used to identify critical IRGs and construct a prognostic model. The CIBERSORT algorithm was used to calculate the relative content of 22 immune cell types. Finally, the datasets from the Gene Expression Omnibus (GEO) database were analyzed to validate results from the above analyses. Experimental validation was used on KIRC tissues by quantitative polymerase chain reaction (qPCR) and western blot.ResultsWe found that the ImmuneScore was negatively correlated with patients’ prognosis. Intersection analysis of the ImmuneScore and StromalScore identified 118 IRGs that were enriched in immune-related functions. Following IRGs screening by Cox and LASSO regression analyses, six genes were identified and used to construct a KIRC prognostic model. Intersection analysis of these six genes and protein-protein interaction (PPI) were performed and obtained the most critical gene: Potassium Calcium-Activated Channel Subfamily N Member 4 (KCNN4). Further analysis showed that KCNN4 expression was higher in tumor samples relative to normal controls, and was negatively correlated with prognosis. CIBERSORT analysis revealed significant correlation between KCNN4 expression and multiple types of TICs, demonstrating that KCNN4 may affect KIRC prognosis by influencing the TME immune status. Ultimately, the GEO datasets and validation experiments confirmed that KCNN4 was highly expressed in tumor tissues compared to the corresponding normal tissues.ConclusionsOur study demonstrated that KCNN4 might be a potential prognostic marker in KIRC, offering a novel therapeutic avenue.     

Individualized immune-related gene signature predicts immune status and oncologic outcomes in clear cell renal cell carcinoma patients

ObjectiveTo develop an individualized immune-related gene signature that predicts oncologic outcomes and immune status of clear cell renal cell carcinoma (ccRCC).Materials and MethodsThe immune-related gene pair (IGP) index was constructed and validated based on pairwise comparison in 634 ccRCC patients. Association with overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS) was evaluated by Kaplan-Meier analysis, univariate and multivariate cox regression survival analysis. Prognostic values of different risk models were compared using Harrell's C-index.ResultsThe IGP index of 17 gene pairs was an adverse independent risk factor in multivariate analyses for OS (hazard ratio [HR], 1.718; P = 0.001), PFI (HR, 1.550; P = 0.006), and DSS (HR, 2.201; P = 0.001) in ccRCC patients. It showed comparable prognostic accuracy with ccA/ccB signature (C-index for OS, 0.657 vs. 0.640; P = 0.686) and better intratumor homogeneity. Immunosuppressive immune cell, markers, and pathways were all enriched in high immune-risk tumors. The integrated immune-clinical prognostic score outperformed ccA/ccB signature and University of California Integrated Staging System risk model in terms of C-index for estimation of OS, PFI, and DSS (P < 0.001).ConclusionsThe proposed IGP index is a robust and promising biomarker for estimating oncologic outcomes in ccRCC. High immune-risk tumors are immunosuppressive.     

Identification of a novel immune-related microRNA prognostic model in clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is a type of kidney cancer, and one of the most common malignant tumors. Many studies have shown that certain microRNAs (miRNAs) play an important role in the occurrence and development of ccRCC. Nevertheless, the prognosis of ccRCC patients is very rarely based on these “immuno-miRs”. Our aim was thus to determine the relationship between immune-related miRNA signatures and ccRCC.MethodsWe downloaded the miRNA expression data from 521 KIRC and 71 normal tissues in The Cancer Genome Atlas (TCGA). We used “limma” package and univariate Cox regression analysis to identify differentially expressed miRNAs (DEMs) that related to overall survival (OS). We applied lasso and multivariate Cox regression analyses to construct a prognostic model based on immuno-miRs. We evaluated the performance of model by using the Kaplan-Meier method. Furthermore, Cox regression analysis was used to determine independent prognostic signatures in ccRCC.ResultsA total of 59 significant immuno-miRs were identified. We use univariate Cox regression analysis to acquire 18 immune-related miRNAs which were markedly related to OS of ccRCC patients in the training set. We then constructed the 9-immune-related-miRNA prognostic model (miR-21, miR-342, miR-149, miR-130b, miR-223, miR-365a, miR-9-1, and miR-146b) by using lasso and multivariate Cox regression. Further analysis suggested that the immune-related prognostic model could be an independent prognostic indicator for patients with ccRCC. The prognostic performance of the 9-immune-related-miRNA prognostic model was further validated successfully in the testing set.ConclusionsWe established a novel immune-based prognostic model of ccRCC based on potential prognostic immune-related miRNAs. Our results indicated that the 9-miRNA signature could be a practical and reliable prognostic tool for ccRCC.     

免疫相关LncRNA与肾透明细胞癌预后关系分析及预测评分模型建立

目的:探讨肾透明细胞癌(clear cell renal cell carcinoma,ccRCC)中免疫相关LncRNA表达与肿瘤预后的关系,并构建预后相关的预测评分模型.方法:从TCGA数据中下载537例ccRCC转录组测序数据及相应的临床预后信息,采用R软件和Perl软件利用生物信息学方法提取ccRCC免疫相关L...     

Enhancement of Siglec-8 expression predicts adverse prognosis in patients with clear cell renal cell carcinoma

Purpose

Sialic acid-binding immunoglobulin-like lectins (siglecs) family has important functions in tumor progression. The purpose of our study is to figure out the correlation between the expression level of Siglec-8 and prognosis of patients with clear cell renal cell carcinoma (ccRCC), and then to predict the overall survival (OS) via a novel nomogram.

铜死亡相关基因在肝细胞癌中的表达及其临床意义

背景与目的：肝细胞癌（HCC）是一种全球常见的恶性肿瘤，具有高复发率和高病死率。铜死亡是一种新型的程序性细胞死亡，涉及肿瘤细胞的增殖和生长、血管生成和转移。因此，本研究探讨铜死亡相关基因（CRGs）在HCC中的表达与预后的关系，并建立预后相关的列线图模型以及分析CRGs与HCC免疫细胞浸润的关系。方法：使用R语言“limma”包对TCGA数据库下载的HCC组织与正常组织的数据中CRGs进行差异表达分析；“clusterProfiler”包进行GO和KEGG分析；单因素Cox回归分析筛选与预后相关的CRGs,LassoCox回归分析构建HCC中CRGs相关预后评分模型；“ggsurvplot”包以总生存（OS）为结局绘制Kaplan-Meier生存曲线；“survival ROC”包绘制ROC曲线评估预后评分的准确性；“regplot”和“rms”包绘制列线图和校准曲线；利用TIMER数据库分析CRGs的表达与6种免疫细胞丰度之间的关系。结果：与正常组织相比，HCC组织19个CRGs中的16个有差异表达（上调：PDHB、PDHA1、MTF1、LIPT1、LIPT2、LIAS、GLS、DL...     

Immune inactivation by CD47 expression predicts clinical outcomes and therapeutic responses in clear cell renal cell carcinoma patients

BackgroundCD47 has been identified as a phagocytosis checkpoint conferring poor clinical outcomes in various cancer types. A flurry of clinical trials designed to evaluate agents that block CD47 have been initiated. We aimed to explore the clinical significance of CD47 and its correlation with immune infiltration and molecular features in clear cell renal cell carcinoma (ccRCC).Methods235 tumor tissue microarray specimens of ccRCC patients from Zhongshan Hospital, 530 ccRCC patients from The Cancer Genome Atlas and 726 ccRCC patients from JAVELIN Renal 101 study were analyzed. CD47 expression and immune contexture were examined by immunohistochemistry and CIBERSORT algorithm. Survival analyses were conducted through Kaplan-Meier curves and Cox regression model.ResultsWe demonstrated that ccRCC patients with high CD47 expression exhibited inferior overall survival and recurrence-free survival. CD47 expression associated with heavily immune infiltrated but immunosuppressed microenvironment. CD8⁺ T cells infiltration had discordant prognostic value based on CD47 expression, where high CD8⁺ T cell infiltration was associated with worse clinical outcome in CD47^hi patients and with favorable prognosis in CD47^lo patients. Patients with mutated PBRM1 and SETD2 correlated with decreased CD47 mRNA expression. Patients with higher CD47 expression possessed improved PFS in ICI + VEGFR TKI combination therapy.ConclusionsCD47 expression was an independent prognosticator of clinical outcome for ccRCC patients. CD47 expression correlated with ccRCC molecular classification and response to combination therapy. The phagocytosis checkpoint CD47 could be applied as an attractive candidate for immunotherapeutic approach in ccRCC.     

Identification of genes that correlate clear cell renal cell carcinoma and obesity and exhibit potential prognostic value

BackgroundRenal cell carcinoma (RCC) is a common urologic malignancy. Although the relationship between clear cell RCC (ccRCC) and obesity has been well-established by several large-scale retrospective studies, the molecular mechanisms and genetic characteristics behind this correlation remains unclear. In the current study, several bioinformatics tools were used to identify the key genes in ccRCC related to obesity.MethodsMicroarray data comparing ccRCC with normal renal tissues in patients with and without obesity were downloaded from the GEO database for screening of differentially expressed genes (DEGs). The DEGs were verified with expression level and survival analysis using several online bioinformatics tools.ResultsIn the current study, the differential expression of five genes correlated with both ccRCC and obesity; IGHA1 and IGKC as oncogenes, and MAOA, MUC20 and TRPM3 as tumor suppressor genes. These genes were verified by comparing the relationship between the expression levels and survival outcomes from open-source data in The Cancer Genome Atlas (TCGA) dataset.ConclusionsIn conclusion, the five genes differentially expressed in ccRCC and obesity are related to disease progression and prognosis, and therefore could provide prognostic value for patients with ccRCC.     

Development and validation of a nomogram for predicting survival of advanced breast cancer patients in China

BackgroundThere is a lack of prognostic models predicting the overall survival (OS) of advanced breast cancer (ABC) patients in China.MethodsData from the China National Cancer Center database that recorded 4039 patients diagnosed with breast cancer between 1987 and 2019 were extracted and a total of 2263 ABC participants were enrolled in this study, which were further randomized 3:1 and divided into training (n = 1706) and validation (n = 557) groups. The nomogram was built based on independent predictors identified by univariate and multivariate cox regression analyses. The discriminatory and predictive capacities of the nomogram were assessed by Harrell’s concordance index (C-index) and calibration plots.ResultsUnivariate and multivariate analyses found that age, Eastern Cooperative Oncology Group (ECOG) score, T-stage, N-stage, tumor subtype, the presence of distant lymph node (DLN)/liver/brain metastasis, local therapy, efficacy of first-line therapy and metastatic-free interval (MFI) were significantly related to OS (all P < 0.05). These variables were incorporated into a nomogram to predict the 2-year and 3-year OS of ABC patients. The C-indexes of the nomogram were 0.700 (95% confidence interval [CI]: 0.683–0.717) for the training set and 0.686 (95% CI: 0.652–0.719) for the validation set. The calibration curves revealed satisfactory consistency between actual survival and nomogram prediction in both the internal and external validations. The nomogram was capable of stratifying patients into different risk cohorts.ConclusionsWe constructed and validated a nomogram that might serve as an efficient tool to provide prognostic prediction for ABC patients and guide the physicians to make personalized treatment decisions.     

Identification and validation of a five apoptosis-related genes signature for prediction of disease-free survival for testicular germ cell tumors

BackgroundMore and more studies have paid attention to the role of apoptosis in tumorigenesis. A variety of apoptosis-related genes (ARGs) are related to tumor progression and resistance to chemotherapy drugs. Therefore, this study aims to establish a prognostic marker for ARG-based testicular germ cell tumors (TCGT).MethodsTCGT sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database and GEO database. The sequencing data of normal tissues came from the GTEx database. Through univariate COX, LASSO, and multiple COX regression analyses, we screened out key ARGs related to prognosis and constructed a risk signature and a prognostic nomogram. Finally, we performed internal and external verification to verify the signature we have established.ResultsFive ARGs, including CHGA, LPCAT1, PPP1CA, PSMB5, UBR2 were selected out and utilized to establish a novel signature. Based on this signature, TCGT patients were divided into high-risk groups and low-risk groups. The results showed that the disease-free survival (DFS) of patients in the high-risk group was lower than that in the low-risk group (P=0.02268). The subsequent univariate and multivariate Cox regression analysis further proved that the features we established are valuable independent prognostic factors (P<0.05). Also, a prognostic nomogram was created to visualize the relationship between various prognostic-related factors and the 1-, 3-, and 5-year DFS of TCGT in the TCGA cohort.ConclusionsWe constructed a new nomogram based on ARGs to predict the risk of testicular tumor recurrence. It can help clinicians better and more intuitively predict the survival of patients.     

肝癌铜死亡相关基因及其与预后、免疫浸润的关系分析

背景与目的 肝癌是消化道恶性肿瘤之一,发病率高、病死率高。铜死亡是一种铜依赖、新型的细胞死亡方式,继发于铜过载诱发的线粒体功能受损。铜死亡在多种肿瘤中扮演重要作用,但其与肝癌的关系尚不清楚。因此,本研究探讨铜死亡相关基因在肝癌中的表达特征,以及与肝癌预后及免疫浸润的关系。方法 从TCGA和GTEx数据库下载肝癌和正常肝脏组织转录组数据进行差异表达和突变分析。采用R语言“clusterProfiler”包进行GO和KEGG富集分析。采用LASSO、单因素和多因素回归分析筛选影响肝癌患者预后的基因并构建风险因子图。使用R包“rms”构建列线图。使用UALCAN数据库分析铜死亡相关基因与肝癌临床病理特征的关系并验证。使用Spearman相关性分析铜死亡相关基因与免疫细胞浸润和免疫检查点的相关性。采用TIMER2.0数据库分析铜死亡相关基因表达与肿瘤相关成纤维细胞（CAF）浸润的相关性,采用TISDB数据库分析CDKN2A和DLAT表达与髓源抑制性细胞（MDSC）浸润丰度的相关性。结果 与正常肝脏组织比较,9个铜死亡相关基因在肝癌中表达显著升高,CDKN2A突变频率最高。铜死亡相关基因主要参与蛋白质脂酰化、三羧酸循环、柠檬酸循环等生物过程。基于LASSO、单因素与多因素回归分析筛选出影响肝癌患者总体生存率（OS）的基因CDKN2A和DLAT,并以此构建风险因子图,时间依赖性受试者工作特征曲线显示其具有较好的预测能力。通过单因素和多因素回归分析筛选出CDKN2A、DLAT、T分期和肿瘤状态是影响肝癌患者OS的独立预后因素,基于上述因素构建了列线图,校正曲线显示该列线图预测和实际观察之间有很好的一致性。UALCAN数据库分析发现CDKN2A、DLAT与肝癌临床分期、肿瘤分级有关,且GEO数据库、HPA数据库及肝癌细胞中的验证结果与之一致。相关性分析显示,CDKN2A和DLAT表达与免疫细胞浸润和免疫检查点表达相关;TIMER2.0数据库分析显示,DLAT表达与CAF浸润明显正相关;TISDB数据库分析显示,CDKN2A和DLAT表达与MDSC浸润丰度无相关性。结论 铜死亡相关基因CDKN2A、DLAT可能是肝癌新的预后生物标志物和免疫治疗的新靶点。     

Clinical significance of tumor-derived IL-1β and IL-18 in localized renal cell carcinoma: Associations with recurrence and survival

PurposeInterleukin-1β (IL-1β) and IL-18 are products of activated inflammasomes that play central roles in innate immunity and inflammation. This study was aimed to determine the effect of tumor-derived IL-1β and IL-18 on recurrence and survival of patients with localized clear cell renal cell carcinoma (ccRCC) following surgery.MethodsWe retrospectively enrolled 267 patients with localized ccRCC undergoing nephrectomy at a single center. Clinicopathologic features, recurrence-free survival (RFS), and overall survival (OS) were recorded. IL-1β and IL-18 levels were assessed by immunohistochemistry in tumor tissues. The Kaplan-Meier method was used to compare survival curves. Cox regression models were used to analyze the effect of prognostic factors on RFS and OS. Concordance index was calculated to assess predictive accuracy.ResultsBoth high IL-1β and high IL-18 levels were associated with increased risk of recurrence (P<0.001 and P<0.001, respectively) and reduced survival (P<0.001 and P = 0.001, respectively). The combination of IL-1β and IL-18 expression (IL-1β/IL-18 signature) could further refine prognostic stratification. Multivariate analyses confirmed that IL-1β/IL-18 signature was an independent prognostic factor for RFS and OS (P = 0.005 and P = 0.044, respectively). The predictive accuracy of well-established prognostic models improved when the IL-1β/IL-18 signature was added. Notably, the improvement in prediction was mainly observed in patients with low-risk disease.ConclusionsThe combined high expression of IL-1β and IL-18 is an independent predictor for poor prognosis in patients with localized ccRCC, and the prognostic value is more pronounced in patients with low-risk disease.     

Assessment of the prognostic value of SPOCK1 in clear cell renal cell carcinoma: a bioinformatics analysis

BackgroundClear cell renal cell carcinoma (ccRCC) is one of the most common urological malignancies, and once metastasis occurs, it often has a poor prognosis and lacks effective treatment. Therefore, there is an urgent need to screen some new biomarkers and explore their molecular mechanisms to improve the early clinical diagnosis and targeted therapy of ccRCC. SPOCK1 (SPARC/osteonectin, CWCV and Kazal-like domains proteoglycan 1) is a conserved multi-domain proteoglycan that plays an important role in the development of multiple cancer types; however, its prognostic value in ccRCC has not been investigated. The study of the prognostic value of SPOCK1 in ccRCC is a good complement to the study of ccRCC biomarkers.MethodsDatabases of this study included Oncomine, Kaplan-Meier Plotter, GEPIA, GeneMANIA, cBioPortal, and TIMER. Student’s t-test was used to analyze the differences in SPOCK1 expression in ccRCC tissues compared with tumor-adjacent normal tissues. Kaplan-Meier curves for survival analysis were used to assess the correlation between the expression of SPOCK1 and the prognostic outcomes. Correlation module drew the expression scatterplots between SPOCK1 and immune cell infiltration in ccRCC, together with the Spearman’s rho value and estimated statistical significance.ResultsThe SPOCK1 mRNA expression was significantly higher in ccRCC tissues (mean expression ± SD: 920.2±195.2) than in normal tissues (mean expression ± SD: 358.4±29.1, P=0.008), and high SPOCK1 expression significantly and positively correlated with the pathological stage of ccRCC patients (F value =10.2, P<0.001). Higher expression of SPOCK1 was also associated with significantly shorter overall survival (OS) and disease-free survival (DFS) in ccRCC patients (GEPIA: P=0.046, P<0.001, respectively; Kaplan-Meier Plotter: P=0.002, P=0.0022, respectively). The function of SPOCK1 is mainly related to tumor development and extracellular matrix remodeling, and it may participate in the epithelial-mesenchymal transition process. SPOCK1 expression significantly and positively correlated with infiltration of several immune cells in ccRCC, including cancer-associated fibroblasts (CAFs) (Rho =0.333, P=2.16×10⁻¹³), tumor-associated macrophages (TAMs) (Rho =0.18, P=1.02×10⁻⁴), and tumor-associated neutrophils (TANs) (Rho =0.165, P=3.83×10⁻⁴). Conversely, there was a significant and negative correlation between SPOCK1 expression and infiltration of CD4⁺ T cells (Rho =−0.113, P=0.015).ConclusionsSPOCK1 may be a potential prognostic biomarker in ccRCC.     

High expression of CXC chemokine receptor 6 associates with poor prognosis in patients with clear cell renal cell carcinoma

Purpose

Accumulating evidence indicates that CXC chemokine receptor 6 (CXCR6) has a crucial role in cancer development and progression, however, its role in clear cell renal cell carcinoma (ccRCC) remains obscure. The aim of this study is to investigate the prognostic value of CXCR6 expression in patients with ccRCC following surgery.