Dataset Information

Single-cell analysis reveals metastatic cell heterogeneity in clear cell renal cell carcinoma.

ABSTRACT: 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.

SUBMITTER: Liu K

PROVIDER: S-EPMC8093989 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Bilateral renal clear cell carcinoma (BRCC) is a rare type of renal cell carcinoma (RCC) that accounts for only 1-5% of RCC cases and has a poor clinical prognosis. The origin, tumor microenvironment, cellular molecular features, and intra-tumoral heterogeneity of BRCC are still unclear. We downloaded BRCC single-cell transcriptome sequencing data from the gene expression omnibus database biochip GSE171306, containing 3,575 cells from left-sided clear cell renal cell carcinoma (ccRCC) and 3,568 cells from right-sided ccRCC, and used a series of R packages for data quality control (QC) and subsequent analysis of BRCC single-cell transcriptome data, including the use of the R packages Seurat and scCancer for cell QC, identification of major cell types, and cell annotation; R package scran for calculation of cell cycle scores; R package infercnv for malignancy scoring of tumor cells; R package ReactomeGSA for functional enrichment analysis; R package Monocle 2 for the analysis of cell differentiation trajectories; and R package CellphoneDB for the analysis of intercellular interactions. In this study, by analyzing the high-quality single-cell transcriptome data of BRCC, we identified 18 cell types and found that left- and right-sided ccRCC were approximately the same in terms of cell type and the number of each cell but differed significantly in terms of tumor cell malignancy score, tumor microenvironment, and cell stemness score. In the cell differentiation trajectory analysis of BRCC, we found that endothelial cells and macrophages play an extremely important role in its tumor progression. Further cell communication analysis was performed, and we found that it may signal through ligand-receptors, such as vascular endothelial growth factor-vascular endothelial growth factor receptor1 (VEGF-VEGFR1), MIF-(CD74-CXCR4), and growth arrest-specific protein 6-AXL, to influence the development of BRCC. The analysis of single-cell transcriptomic data of human BRCC suggests that left- and right-sided ccRCC may be of the same tumor origin, but the left-sided ccRCC is more malignant and has a better immune response.

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.

Project description:Clear cell renal cell carcinoma (ccRCC) is a highly heterogeneous cancer that poses great challenge to clinical treatment and prognostic prediction. Characterizing the cellular landscape of ccRCC in a single-cell dimension can help better understand the tumor heterogeneity and molecular mechanisms of ccRCC. This study analyzed single-cell profiles in ccRCC samples and para-tumor samples from Gene Expression Omnibus and identified a highly heterogeneous subcluster of renal tubule cells. Single-cell regulatory network inference and clustering analyses and cell communication analysis were performed to develop transcription factor-target gene regulatory networks and cell-cell interactions. Additionally, the distribution and prognostic risk of renal tubule cells from spatial transcriptome data (GSM6415706) and The Cancer Genome Atlas-Kidney Clear Cell Carcinoma data were analyzed. A total of 10 cell types were identified in ccRCC and para-tumor samples. The ccRCC renal tubule cells showed a high expression of the oncogene nicotinamide N-methyltransferase and a significantly high degree of tumor heterogeneity. We further identified 6 cell subclusters with specific expression of BEX2, PTHLH, SFRP2, KLRB1, ADGRL4, and HGF from the ccRCC renal tubule cells. ADGRL4+ renal tubule cells had highly metastatic and angiogenesis-inducing characteristics, with more ADGRL4+ renal tubule cells indicating a worse survival. ADGRL4+ renal tubule cells regulated the metastasis of other renal tubule cells through metastasis-related receptor-ligand communication. We also found that ADGRL4+ renal tubule cells clustered around the glomeruli but the rest of the renal tubule cell subclusters rarely localized in ccRCC tissues. ETS1 and ELK3 -dominant GRNs were remarkably activated in ADGRL4+ renal tubule cells, functionally, knockdown of ELK3 in A498 significantly disturbedaffected the cell migration and invasion. ADGRL4+ renal tubule cells, which were highly metastatic and invasive, might be an essential cell subcluster for ccRCC, and ADGRL4 could be used a novel therapeutic target.

Dataset Information

Single-cell analysis reveals metastatic cell heterogeneity in clear cell renal cell carcinoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets