Integrative genomic analysis of sporadic clear cell Renal Cell Carcinoma
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PROVIDER: S-DIXA-D-1085 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description:Human clear cell renal cell carcinoma (ccRCC) is a common cancer of the kidney. We applied an integrated approach to identify important factors that influence carcinogenesis in ccRCC.
2011-12-01 | GSE27852 | GEO
Project description:Human clear cell renal cell carcinoma (ccRCC) is a common cancer of the kidney. We applied an integrated approach to identify important factors that influence carcinogenesis in ccRCC. 33 frozen ccRCC samples were subject to copy number analysis. The data was analyzed to identify factors affecting tumorigenesis. The samples were also stained for HIF-1alpha and HIF-2alpha expression. The tumors were subtyped based on HIF expression and investigated for differences in genetic aberrations.
2011-12-01 | E-GEOD-27852 | biostudies-arrayexpress
Project description:Sporadic clear cell renal cell carcinoma (ccRCC), the most common type of adult kidney cancer, is often associated with genomic copy number aberrations on chromosomes 3p and 5q. Aberrations on chromosome 3p are associated with inactivation of the tumor suppressor gene von-Hippel Lindau (VHL), which activates the hypoxia-inducible factors HIF1? and HIF2?. In contrast, ccRCC genes on chromosome 5q remain to be defined. In this study, we conducted an integrated analysis of high-density copy number and gene expression data for 54 sporadic ccRCC tumors that identified the secreted glycoprotein STC2 (stanniocalcin 2) and the proteoglycan VCAN (versican) as potential 5q oncogenes in ccRCCs. In functional assays, STC2 and VCAN each promoted tumorigenesis by inhibiting cell death. Using the same approach, we also investigated the two VHL-deficient subtypes of ccRCC, which express both HIF1? and HIF2? (H1H2) or only HIF2? (H2). This analysis revealed a distinct pattern of genomic aberrations in each group, with the H1H2 group displaying, on average, a more aberrant genome than the H2 group. Together our findings provide a significant advance in understanding ccRCCs by offering a molecular definition of two subtypes with distinct characteristics as well as two potential chromosome 5q oncogenes, the overexpression of which is sufficient to promote tumorigenesis by limiting cell death.
| S-EPMC3251639 | biostudies-literature
Project description:In cancer, both histopathologic images and genomic signatures are used for diagnosis, prognosis, and subtyping. However, combining histopathologic images with genomic data for predicting prognosis, as well as the relationships between them, has rarely been explored. In this study, we present an integrative genomics framework for constructing a prognostic model for clear cell renal cell carcinoma. We used patient data from The Cancer Genome Atlas (n = 410), extracting hundreds of cellular morphologic features from digitized whole-slide images and eigengenes from functional genomics data to predict patient outcome. The risk index generated by our model correlated strongly with survival, outperforming predictions based on considering morphologic features or eigengenes separately. The predicted risk index also effectively stratified patients in early-stage (stage I and stage II) tumors, whereas no significant survival difference was observed using staging alone. The prognostic value of our model was independent of other known clinical and molecular prognostic factors for patients with clear cell renal cell carcinoma. Overall, this workflow and the shared software code provide building blocks for applying similar approaches in other cancers. Cancer Res; 77(21); e91-100. ©2017 AACR.
| S-EPMC7262576 | biostudies-literature
Project description: Not available
| S-EPMC9882438 | biostudies-literature
Project description:Background and objectivePrevious germline studies on renal cell carcinoma (RCC) have usually pooled clear and non-clear cell RCCs and have not adequately accounted for population stratification, which might have led to an inaccurate estimation of genetic risk. Here, we aim to analyze the major germline drivers of RCC risk and clinically relevant but underexplored germline variant types.MethodsWe first characterized germline pathogenic variants (PVs), cryptic splice variants, and copy number variants (CNVs) in 1436 unselected RCC patients. To evaluate the enrichment of PVs in RCC, we conducted a case-control study of 1356 RCC patients ancestry matched with 16 512 cancer-free controls using approaches accounting for population stratification and histological subtypes, followed by characterization of secondary somatic events.Key findings and limitationsClear cell RCC patients (n = 976) exhibited a significant burden of PVs in VHL compared with controls (odds ratio [OR]: 39.1, p = 4.95e-05). Non-clear cell RCC patients (n = 380) carried enrichment of PVs in FH (OR: 77.9, p = 1.55e-08) and MET (OR: 1.98e11, p = 2.07e-05). In a CHEK2-focused analysis with European participants, clear cell RCC (n = 906) harbored nominal enrichment of low-penetrance CHEK2 variants-p.Ile157Thr (OR: 1.84, p = 0.049) and p.Ser428Phe (OR: 5.20, p = 0.045), while non-clear cell RCC (n = 295) exhibited nominal enrichment of CHEK2 loss of function PVs (OR: 3.51, p = 0.033). Patients with germline PVs in FH, MET, and VHL exhibited significantly earlier age of cancer onset than patients without germline PVs (mean: 46.0 vs 60.2 yr, p < 0.0001), and more than half had secondary somatic events affecting the same gene (n = 10/15, 66.7%). Conversely, CHEK2 PV carriers exhibited a similar age of onset to patients without germline PVs (mean: 60.1 vs 60.2 yr, p = 0.99), and only 30.4% carried somatic events in CHEK2 (n = 7/23). Finally, pathogenic germline cryptic splice variants were identified in SDHA and TSC1, and pathogenic germline CNVs were found in 18 patients, including CNVs in FH, SDHA, and VHL.Conclusions and clinical implicationsThis analysis supports the existing link between several RCC risk genes and RCC risk manifesting in earlier age of onset. It calls for caution when assessing the role of CHEK2 due to the burden of founder variants with varying population frequency. It also broadens the definition of the RCC germline landscape of pathogenicity to incorporate previously understudied types of germline variants.Patient summaryIn this study, we carefully compared the frequency of rare inherited mutations with a focus on patients' genetic ancestry. We discovered that subtle variations in genetic background may confound a case-control analysis, especially in evaluating the cancer risk associated with specific genes, such as CHEK2. We also identified previously less explored forms of rare inherited mutations, which could potentially increase the risk of kidney cancer.
| S-EPMC10940785 | biostudies-literature
Project description:Clear cell renal cell carcinoma (ccRCC) is a heterogeneous disease with features that vary by ethnicity. A systematic characterization of the genomic landscape of Chinese ccRCC is lacking, and features of ccRCC associated with tumor thrombus (ccRCC-TT) remain poorly understood. Here, we applied whole-exome sequencing on 110 normal-tumor pairs and 42 normal-tumor-thrombus triples, and transcriptome sequencing on 61 tumor-normal pairs and 30 primary-thrombus pairs from 152 Chinese patients with ccRCC. Our analysis reveals that a mutational signature associated with aristolochic acid (AA) exposure is widespread in Chinese ccRCC. Tumors from patients with ccRCC-TT show a higher mutational burden and genomic instability; in addition, mutations in BAP1 and SETD2 are highly enriched in patients with ccRCC-TT. Moreover, patients with/without TT show distinct molecular characteristics. We reported the integrative genomic sequencing of Chinese ccRCC and identified the features associated with tumor thrombus, which may facilitate ccRCC diagnosis, prognosis and treatment.
| S-EPMC7005298 | biostudies-literature
Project description:Sirtuins, class III histone deacetylases, are involved in multiple biological processes in cancer initiation and progression. However, the diverse expression patterns and prognostic values of sirtuins in cancers have yet to be elucidated. In this study, we first evaluated the expression and prognostic values of sirtuins in multiple cancer cohorts using publicly available TCGA pan-cancer datasets. Pan-cancer survival analysis indicated that 6 out of 7 sirtuin family members were significant associated with prognosis of clear cell renal cell carcinoma (KIRC) patients. SIRT1, SIRT3, SIRT4, and SIRT5 were associated with favorable prognosis of KIRC patients, while SIRT6 and SIRT7 were associated with unfavorable prognosis. The expression levels of SIRT4 and SIRT5 in KIRC tissues were lower than that in normal tissues, while SIRT6 and SIRT7 were higher in KIRC tissues. The expression levels of SIRT1, SIRT3, SIRT5, SIRT6, and SIRT7 were significantly correlated with tumor stage and histological grade. DNA methylation may contribute to the dysregulation of sirtuins. Finally, GSEA was conducted to predict the potential functions of sirtuins in KIRC. Our results may provide novel insights for the development of sirtuins-based cancer therapy in KIRC.
| S-EPMC7052292 | biostudies-literature
Project description:Kidney cancer encompasses a range of primary cancers, such as clear cell renal cell carcinoma (ccRCC) and papillary renal cell carcinoma (pRCC). Our knowledge about the tumor microenvironment (TME) of kidney cancer is still limited. Therefore, we comprehensively assessed the TME of kidney cancers (including ccRCC and pRCC) using the ESTIAMTE, and CIBERSORT algorithms, and conducted distinct functional and correlation analyses with data from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), Gene Expression Omnibus (GEO), Connectivity map and CellMiner database. Next, we identified two immune-related hub genes, IGLL5 and IL2RA, which play essential roles in the TME as well as on survival in ccRCC and pRCC. Furthermore, ccRCC and pRCC samples from our medical center were collected to verify the clinical application value of these two immune-related genes. A specific enrichment analysis of immune cells related to IGLL5 and IL2RA was also conducted in two types of renal cell cancer. Based on selected genes, we predicted the drug response and uncovered novel drug candidate for RCC treatment. Considering the unfavorable outcomes of kidney cancer and emerging interest in TME-targeted treatments, our results may offer insights into immune-related molecular mechanisms and possible targets to control the kidney cancer.
| S-EPMC8650138 | biostudies-literature
Project description:ObjectivesTo assess the feasibility of predicting molecular characteristics by computed tomography (CT) radiomics features, and predicting overall survival (OS) using combination of omics data in clear cell renal cell carcinoma (ccRCC).MethodsGenetic data of 207 ccRCC patients was retrieved from The Cancer Genome Atlas (TCGA) and matched contrast-enhanced CT images were obtained from The Cancer Imaging Archive (TCIA). Another cohort of 175 ccRCC patients from West China Hospital was used as external validation. We first applied radiomics features and machine learning algorithms to predict genetic mutations and mRNA-based molecular subtypes. Next, we established predictive models for OS based on single omics, combined omics (radiomics+genomics, radiomics+transcriptomics, radiomics+proteomics) and all features (multi-omics).ResultsUsing radiomics features, random forest algorithm showed good capacity to identify the mutations VHL (AUC=0.971), BAP1 (AUC=0.955), PBRM1 (AUC=0.972), SETD2 (AUC=0.949), and molecular subtypes m1 (AUC=0.973), m2 (AUC=0.968), m3 (AUC=0.961), m4 (AUC=0.953). The TCGA cohort was divided into training (n=104) and validation (n=103) sets. The radiomics model had promising prognostic value for OS in validation set (5-year AUC=0.775) and external validation set (5-year AUC=0.755). In the validation set, the radiomics+omics models enhanced predictive accuracy than single-omics models, and the multi-omics model made further improvement (5-year AUC=0.846). High-risk group of validation set predicted by multi-omics model showed significantly poorer OS (HR=6.20, 95%CI: 3.19-8.44, p<0.0001).ConclusionsCT radiomics might be a feasible approach to predict genetic mutations, molecular subtypes and OS in ccRCC patients. Integrative analysis of radiogenomics may improve the survival prediction of ccRCC patients.
| S-EPMC8064160 | biostudies-literature