CBFA2T2 is associated with a cancer stem cell state in renal cell carcinoma.
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ABSTRACT:
SUBMITTER: Chen DC
PROVIDER: S-EPMC5686942 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Renal cell carcinoma (RCC) is a common form of urologic tumor that originates from the highly heterogeneous epithelium of renal tubules. Over the last decade, targeting therapies to renal cancer cells have transformed clinical care for RCC. Recently, it was proposed that renal cancer stem cells (CSCs) isolated from renal carcinomas were responsible for driving tumor growth and resistance to conventional chemotherapy and radiotherapy, according to the theory of CSCs; this has provided the rationale for therapies targeting this aggressive cell population. Precise identification of renal CSC populations and the complete cell hierarchy will accurately inform characterization of disease subtypes. This will ultimately contribute to more personalized and targeted therapies. Here, we summarize potential targeting strategies for renal cancer cells and renal CSCs, including tyrosine kinase inhibitors, mammalian target of rapamycin inhibitors (mTOR), interleukins, CSC marker inhibitors, bone morphogenetic protein-2, antibody drug conjugates, and nanomedicine. In conclusion, targeting therapies for RCC represent new directions for exploration and clinical investigation and they plant a seed of hope for advanced clinical care.
| S-EPMC5103413 | biostudies-literature
Project description:Urine-derived stem cells (USC) are isolated from voided urine and have demonstrated potential for use in tissue engineering and regenerative medicine therapies. Clear cell renal cell carcinoma (ccRCC) is a common urological malignancy that originates in the kidney. Since USC also originate in the kidney, the objective of this study was to investigate any biological differences between USC isolated from healthy patients and those isolated from ccRCC patients (rc-USC). We found that USC can be isolated from the voided urine of ccRCC patients (rc-USC) and have a morphology and function similar to those isolated from healthy donors. However, the rc-USC showed greater proliferation and invasion capacity than USC, and possessed some features of cancer cells; but the rc-UC were not able to form xenografts when implanted in vivo. We further performed RNA sequencing of rc-USC and USC and found several differentially expressed lncRNAs and mRNAs; however subsequent GO and KEGG enrichment analysis showed few pathway differences between these cells. Bioinformatic analyses and RT-PCR showed the expression of several known ccRCC-related genes in rc-USC expressed, as compared to USC derived from healthy donors. This study demonstrates that rc-USC displayed several cellular and genetic features of ccRCC cells, which suggests that this population of cells could provide a non-invasive approach for for the diagnosis, predication, disease modeling and therapeutic strategies targeting ccRCC.
| S-EPMC8129396 | biostudies-literature
Project description:Although cancers are widely considered to be maintained by stem cells, the existence of stem cells in renal cell carcinoma (RCC) has seldom been reported, in part due to the lack of unique surface markers. We here identified cancer stem cell-like cells with side population (SP) phenotype in five human RCC cell lines. Flow cytometry analysis revealed that 769P, a human clear cell RCC cell line, contained the largest amount of SP cells as compared with other four cell lines. These 769P SP cells possessed characteristics of proliferation, self-renewal, and differentiation, as well as strong resistance to chemotherapy and radiotherapy that were possibly related to the ABCB1 transporter. In vivo experiments with serial tumor transplantation in mice also showed that 769P SP cells formed tumors in NOD/SCID mice. Taken together, these results indicate that 769P SP cells have the properties of cancer stem cells, which may play important roles in tumorigenesis and therapy-resistance of RCC.
| S-EPMC3708929 | biostudies-literature
Project description:BackgroundRelevant markers of CSCs may serve as prognostic biomarkers of RCC. However, their actual prognostic significance remains inconclusive. Thus, a meta-analysis was performed to reevaluate the association of CSCs-relevant markers (CXCR4, CD133, CD44, CD105) expression with RCC prognosis more precisely.MethodsPubMed and Embase were searched to look for eligible studies. The pooled hazard ratios (HR) with 95% confidence intervals (95% CI) were used to reassess the association of CSCs markers expression and RCC prognosis of overall survival (OS), cancer-specific survival (CSS), disease-free survival (DFS), and progression-free survival (PFS).ResultsThere were 25 relevant articles, encompassing 2673 RCC patients, eligible for meta-analysis. Overall pooled analysis suggested that high CSCs markers expression predicted poor OS (HR, 2.10, 95% CI: 1.73-2.55) and DFS (HR, 3.77, 95% CI: 2.30-6.19). High CXCR4 expression predicted worse OS (HR, 2.57, 95% CI: 1.95-3.40), CSS (HR,1.97, 95% CI: 1.50-2.59), and DFS (HR, 5.82, 95% CI: 3.01-11.25). CD44 over-expression correlated with a poor OS(HR,1.58, 95% CI: 1.14-2.18), CSS (HR, 2.58, 95% CI: 1.27-5.23), and DFS (HR, 4.49, 95% CI: 2.12-9.53) in RCC patients. CD133 was an independent favorable prognostic factor for CSS (HR, 0.4, 95% CI: 0.29-0.54).ConclusionsThe presence of CSCs markers correlates with poor RCC outcome. CSCs may be potentially utilized as prognostic markers to stratify RCC patients, probably representing also a novel potential therapeutic target.
| S-EPMC5323198 | biostudies-literature
Project description:Rare cancer stem cells (CSC) are proposed to be responsible for tumour propagation and re-initiation and are functionally defined by identifying tumour-initiating cells (TICs) using the xenotransplantation limiting dilution assay (LDA). While TICs in clear cell renal cell carcinoma (ccRCC) appeared rare in NOD/SCID/IL2Rγ(-/-) (NSG) mice, xenografts formed more efficiently from small tumour fragments, indicating the LDA underestimated ccRCC TIC frequency. Mechanistic interrogation of the LDA identified multiple steps that influence ccRCC TIC quantitation. For example, tissue disaggregation destroys most ccRCC cells, common assays significantly overestimate tumour cell viability, and microenvironmental supplementation with human extracellular factors or pharmacological inhibition of anoikis increase clonogenicity and tumourigenicity of ccRCC cell lines and primary tumour cells. Identification of these previously uncharacterized concerns that cumulatively lead to substantial underestimation of TICs in ccRCC provides a framework for development of more accurate TIC assays in the future, both for this disease and for other cancers.
| S-EPMC4848484 | biostudies-literature
Project description:BackgroundKidney renal clear cell carcinoma (KIRC) is a renal cortical tumor. KIRC is the most common subtype of kidney cancer, accounting for 70%-80% of kidney cancer. Early identification of the risk of KIRC patients can facilitate more accurate clinical treatment, but there is a lack of effective prognostic markers. We aimed to identify new prognostic biomarkers for KIRC on the basis of the cancer stem cell (CSC) theory.MethodsRNA-sequencing (RNA-seq) data and related clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Weighted gene co-expression network analysis (WGCNA) was used to identify significant modules and hub genes, and predictive hub genes were used to construct prognostic characteristics.ResultsThe messenger RNA expression-based stemness index (mRNAsi) in tumor tissues of patients in the TCGA database is higher than that of the corresponding normal tissues. In addition, some clinical features and results are highly correlated with mRNAsi. WGCNA found that the green module is the most prominent module associated with mRNAsi; the genes in the green module are mainly concentration in Notch binding, endothelial cell development, Notch signaling pathway, and Rap 1 signaling pathway. A protein-protein interaction (PPI) network showed that the top 10 central genes were significantly associated with the transcriptional level. Moreover, the 10 hub genes were up-regulated in KIRC. Regarding survival analysis, the nomogram of the prognostic markers of the seven pivotal genes showed a higher predictive value. The classical receiver operating characteristic (ROC) curve analysis showed that risk score biomarkers had the highest accuracy and specificity with an area under the curve (AUC) value of 0.701.ConclusionsmRNAsi-related genes may be good prognostic biomarkers for KIRC.
| S-EPMC8421844 | biostudies-literature
Project description:Targeted therapy has greatly changed the way in which metastatic renal cell carcinoma (RCC) is treated. Agents that inhibit the vascular endothelial growth factor and mammalian target of rapamycin pathways that otherwise lead to angiogenesis have now become the standard of care. Much research into the sequence and combination of these agents is ongoing, and new anti-angiogenic agents are being developed. This overview covers the standard treatment of metastatic rcc with targeted therapy, immunotherapy, and surgery. Future directions and ongoing clinical trials are also discussed.
| S-EPMC2687801 | biostudies-literature
Project description:BackgroudCancer stemness is associated with metastases in kidney renal clear cell carcinoma (KIRC) and negatively correlates with immune infiltrates. Recent stemness evaluation methods based on the absolute expression have been proposed to reveal the relationship between stemness and cancer. However, we found that existing methods do not perform well in assessing the stemness of KIRC patients, and they overlooked the impact of alternative splicing. Alternative splicing not only progresses during the differentiation of stem cells, but also changes during the acquisition of the stemness features of cancer stem cells. There is an urgent need for a new method to predict KIRC-specific stemness more accurately, so as to provide help in selecting treatment options.MethodsThe corresponding RNA-Seq data were obtained from the The Cancer Genome Atlas (TCGA) data portal. We also downloaded stem cell RNA sequence data from the Progenitor Cell Biology Consortium (PCBC) Synapse Portal. Independent validation sets with large sample size and common clinic pathological characteristics were obtained from the Gene Expression Omnibus (GEO) database. we constructed a KIRC-specific stemness prediction model using an algorithm called one-class logistic regression based on the expression and alternative splicing data to predict stemness indices of KIRC patients, and the model was externally validated. We identify stemness-associated alternative splicing events (SASEs) by analyzing different alternative splicing event between high- and low- stemness groups. Univariate Cox and multivariable logistic regression analysisw as carried out to detect the prognosis-related SASEs respectively. The area under curve (AUC) of receiver operating characteristic (ROC) was performed to evaluate the predictive values of our model.ResultsHere, we constructed a KIRC-specific stemness prediction model with an AUC of 0.968,and to provide a user-friendly interface of our model for KIRC stemness analysis, we have developed KIRC Stemness Calculator and Visualization (KSCV), hosted on the Shiny server, can most easily be accessed via web browser and the url https://jiang-lab.shinyapps.io/kscv/ . When applied to 605 KIRC patients, our stemness indices had a higher correlation with the gender, smoking history and metastasis of the patients than the previous stemness indices, and revealed intratumor heterogeneity at the stemness level. We identified 77 novel SASEs by dividing patients into high- and low- stemness groups with significantly different outcome and they had significant correlations with expression of 17 experimentally validated splicing factors. Both univariate and multivariate survival analysis demonstrated that SASEs closely correlated with the overall survival of patients.ConclusionsBasing on the stemness indices, we found that not only immune infiltration but also alternative splicing events showed significant different at the stemness level. More importantly, we highlight the critical role of these differential alternative splicing events in poor prognosis, and we believe in the potential for their further translation into targets for immunotherapy.
| S-EPMC8204412 | biostudies-literature
Project description:BackgroundRecent advancement in cancer research has shown that tumors are highly heterogeneous, and multiple phenotypically different cell populations are found in a single tumor. Cancer development and tumor growth are driven by specific types of cells-stem cell-like cancer cells (SCLCCs)-which are also responsible for metastatic spread and drug resistance. This research was designed to verify the presence of SCLCCs in renal cell cancer cell lines. Subsequently, we aimed to characterize phenotype and cell biology of CD105+ cells, defined previously as renal cell carcinoma tumor-initiating cells. The main goal of the project was to describe the gene-expression profile of stem cell-like cancer cells of primary tumor and metastatic origin.Materials and methodsReal-time PCR analysis of stemness genes (Oct-4, Nanog and Ncam) and soft agar colony formation assay were conducted to check the stemness properties of renal cell carcinoma (RCC) cell lines. FACS analysis of CD105+ and CD133+ cells was performed on RCC cells. Isolated CD105+ cells were verified for expression of mesenchymal markers-CD24, CD146, CD90, CD73, CD44, CD11b, CD19, CD34, CD45, HLA-DR and alkaline phosphatase. Hanging drop assay was used to investigate CD105+ cell-cell cohesion. Analysis of free-floating 3D spheres formed by isolated CD105+ was verified, as spheres have been hypothesized to contain undifferentiated multipotent progenitor cells. Finally, CD105+ cells were sorted from primary (Caki-2) and metastatic (ACHN) renal cell cancer cell lines. Gene-expression profiling of sorted CD105+ cells was performed with Agilent's human GE 4x44K v2 microarrays. Differentially expressed genes were further categorized into canonical pathways. Network analysis and downstream analysis were performed with Ingenuity Pathway Analysis.ResultsMetastatic RCC cell lines (ACHN and Caki-1) demonstrated higher colony-forming ability in comparison to primary RCC cell lines. Metastatic RCC cell lines harbor numerous CD105+ cell subpopulations and have higher expression of stemness genes (Oct-4 and Nanog). CD105+ cells adopt 3D grape-like floating structures under handing drop conditions. Sorted CD105+ cells are positive for human mesenchymal stem cell (MSC) markers CD90, CD73, CD44, CD146, and alkaline phosphatase activity, but not for CD24 and hematopoietic lineage markers CD34, CD11b, CD19, CD45, and HLA-DR. 1411 genes are commonly differentially expressed in CD105+ cells (both from primary [Caki-2] and metastatic RCC [ACHN] cells) in comparison to a healthy kidney epithelial cell line (ASE-5063). TGF-β, Wnt/β-catenine, epithelial-mesenchymal transition (EMT), Rap1 signaling, PI3K-Akt signaling, and Hippo signaling pathway are deregulated in CD105+ cells. TGFB1, ERBB2, and TNF are the most significant transcriptional regulators activated in these cells.ConclusionsAll together, RCC-CD105+ cells present stemlike properties. These stem cell-like cancer cells may represent a novel target for therapy. A unique gene-expression profile of CD105+ cells could be used as initial data for subsequent functional studies and drug design.
| S-EPMC5094751 | biostudies-literature
Project description:Clear cell renal cell carcinoma (ccRCC) is the most common kidney cancer and is often caused by mutations in the oxygen-sensing machinery of kidney epithelial cells. Due to its pseudo-hypoxic state, ccRCC recruits extensive vasculature and other stromal components. Conventional cell culture methods provide poor representation of stromal cell types in primary cultures of ccRCC, and we hypothesized that mimicking the extracellular environment of the tumor would promote growth of both tumor and stromal cells. We employed proteomics to identify the components of ccRCC extracellular matrix (ECM) and found that in contrast to healthy kidney cortex, laminin, collagen IV, and entactin/nidogen are minor contributors. Instead, the ccRCC ECM is composed largely of collagen VI, fibronectin, and tenascin C. Analysis of single cell expression data indicates that cancer-associated fibroblasts are a major source of tumor ECM production. Tumor cells as well as stromal cells bind efficiently to a nine-component ECM blend characteristic of ccRCC. Primary patient-derived tumor cells bind the nine-component blend efficiently, allowing to us to establish mixed primary cultures of tumor cells and stromal cells. These miniature patient-specific replicas are conducive to microscopy and can be used to analyze interactions between cells in a model tumor microenvironment.
| S-EPMC8657052 | biostudies-literature