Dataset Information

Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma.

ABSTRACT: Clear cell renal cell carcinoma (ccRCC) has been previously classified into putative discrete prognostic subtypes by gene expression profiling. To investigate the robustness of these proposed subtype classifications, we evaluated 12 public datasets, together with a new dataset of 265 ccRCC gene expression profiles. Consensus clustering showed unstable subtype and principal component analysis (PCA) showed a continuous spectrum both within and between datasets. Considering the lack of discrete delineation and continuous spectrum observed, we developed a continuous quantitative prognosis score (Continuous Linear Enhanced Assessment of RCC, or CLEAR score). Prognostic performance was evaluated in independent cohorts from The Cancer Genome Atlas (TCGA) (n?=?414) and EMBL-EBI (n?=?53), CLEAR score demonstrated both superior prognostic estimates and inverse correlation with anti-angiogenic tyrosine-kinase inhibition in comparison to previously proposed discrete subtyping classifications. Inverse correlation with high-dose interleukin-2 outcomes was also observed for the CLEAR score. Multiple somatic mutations (VHL, PBRM1, SETD2, KDM5C, TP53, BAP1, PTEN, MTOR) were associated with the CLEAR score. Application of the CLEAR score to independent expression profiling of intratumoral ccRCC regions demonstrated that average intertumoral heterogeneity exceeded intratumoral expression heterogeneity. Wider investigation of cancer biology using continuous approaches may yield insights into tumor heterogeneity; single cell analysis may provide a key foundation for this approach.

SUBMITTER: Wei X

PROVIDER: S-EPMC5544702 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma.

Wei Xiaona X Choudhury Yukti Y Lim Weng Khong WK Anema John J Kahnoski Richard J RJ Lane Brian B Ludlow John J Takahashi Masayuki M Kanayama Hiro-Omi HO Belldegrun Arie A Kim Hyung L HL Rogers Craig C Nicol David D Teh Bin Tean BT Tan Min-Han MH

Scientific reports 20170804 1

Clear cell renal cell carcinoma (ccRCC) has been previously classified into putative discrete prognostic subtypes by gene expression profiling. To investigate the robustness of these proposed subtype classifications, we evaluated 12 public datasets, together with a new dataset of 265 ccRCC gene expression profiles. Consensus clustering showed unstable subtype and principal component analysis (PCA) showed a continuous spectrum both within and between datasets. Considering the lack of discrete del ...[more]

PMID: 28779136

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Project description:Background Cell–cell communications of various cell populations within tumor microenvironment play an essential role in primary tumor growth, metastasis evolution, and immune escape. Nevertheless, comprehensive investigation of cell–cell communications in the ccRCC (Clear cell renal carcinoma) microenvironment and how this interplay affects prognosis still remains limited. Methods Intercellular communications were characterized by single-cell data. Firstly, we employed “CellChat” package to characterize intercellular communications across all types of cells in microenvironment in VHL mutated and non-mutated samples from 8 patients, respectively. And pseudotime trajectory analyses were performed with monocle analyses. Finally clinical prognosis and immunotherapy efficacy with different landscapes of intercellular interplay are evaluated by TCGA-KIRC and immunotherapy cohort. Results Firstly, the VHL phenotype may be related to the intercellular communication landscape. And trajectory analysis reveals the potential relationship of cell–cell communication molecules with T cells and Myeloid cells differentiation. Furthermore, those molecules also correlate with the infiltration of T cells and Myeloid cells. A tumor cluster with highly expressed ligands was defined by quantitative analysis and transcription factor enrichment analysis, which was identified to be pivotal for intercellular communications in tumor microenvironment. Finally, bulk data indicates bulk that different clusters with different intercellular communications have significant predictive value for prognosis and distinguished immunotherapy efficiency. Conclusions The intercellular communication landscapes of VHL wild and VHL mutant ccRCC vary. Intercellular communications within the tumor microenvironment also influence T cell and myeloid cell development and infiltration, as well as predict clinical prognosis and immunotherapy efficacy in ccRCC. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03858-x.

Project description:Renal cell carcinoma (RCC) is one of the leading causes of cancer-related death worldwide. Tumour metastasis and heterogeneity lead to poor survival outcomes and drug resistance in patients with metastatic RCC (mRCC). In this study, we aimed to assess intratumoural heterogeneity (ITH) in mRCC cells by performing a combined analysis of bulk data and single-cell RNA-sequencing data, and develop novel biomarkers for prognosis prediction on the basis of the potential molecular mechanisms underlying tumorigenesis. Eligible single-cell cohorts related to mRCC were acquired using the Gene Expression Omnibus (GEO) dataset to identify potential mRCC subpopulations. We then performed gene set variation analysis to understand the differential function in primary RCC and mRCC samples. Subsequently, we applied weighted correlation network analysis to identify coexpressing gene modules that were related to the external trait of metastasis. Protein-protein interactions were used to screen hub subpopulation-difference (sub-dif) markers (ACTG1, IL6, CASP3, ACTB and RAP1B) that might be involved in the regulation of RCC metastasis and progression. Cox regression analysis revealed that ACTG1 was a protective factor (HR < 1), whereas the other four genes (IL6, CASP3, ACTB and RAP1B) were risk factors (HR > 1). Kaplan-Meier survival analysis suggested the potential prognostic value of these sub-dif markers. The expression of sub-dif markers in mRCC was further evaluated in clinical samples by immunohistochemistry (IHC). Additionally, the genetic features of sub-dif marker expression patterns, such as genetic variation profiles, correlations with tumour-infiltrating lymphocytes (TILs), and targeted signalling pathway activities, were assessed in bulk RNA-seq datasets. In conclusion, we established novel subpopulation markers as key prognostic factors affecting EMT-related signalling pathway activation in mRCC, which could facilitate the implementation of a treatment for mRCC patients.

Project description:BackgroundIntratumor molecular heterogeneity has been reported for primary clear cell renal cell carcinoma (ccRCC) tumors; however, heterogeneity in metastatic ccRCC tumors has not been explored.ObjectiveTo evaluate intra- and intertumor molecular heterogeneity in resected metastatic ccRCC tumors.Design, setting, and participantsWe identified 111 patients who had tissue available from their primary tumor and at least one metastasis. ClearCode34 genes were analyzed for all tumors.Outcome measurements and statistical analysisPrimary and metastatic tumors were classified as clear cell type A (ccA) or B (ccB) subtypes. Logistic and Cox regression were used to evaluate associations with pathologic features and survival.Results and limitationsIntratumor heterogeneity of ccA/ccB subtypes was observed in 22% (95% confidence interval [CI] 3-60%) of metastatic tumors. Subtype differed across longitudinal metastatic tumors from the same patient in 23% (95% CI 10-42%) of patients and across patient-matched primary and metastatic tumors in 43% (95% CI 32-55%) of patients. Association of subtype with survival was validated in primary ccRCC tumors. The ccA/ccB subtype in metastatic tumors was significantly associated with metastatic tumor location, metastatic tumor grade, and presence of tumor necrosis. A limitation of this study is that we only analyzed patients who had both a nephrectomy and metastasectomy.ConclusionsApproximately one quarter of metastatic tumors displayed intratumor heterogeneity; a similar rate of heterogeneity was observed across longitudinal metastatic tumors. Thus, for biomarker studies it is likely adequate to analyze a single sample per metastatic tumor provided that pathologic review is incorporated into the study design. Subtypes across patient-matched primary and metastatic tumors differed 43% of the time, suggesting that the primary tumor is not a good surrogate for the metastatic tumor.Patient summaryPrimary and secondary/metastatic cancers of the kidney differed in nearly one half of ccRCC patients. The pattern of this relationship may affect tumor growth and the most suitable treatment.

Dataset Information

Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma.

Publications

Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma.

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