Promising Epigenetic Biomarkers Associated With Cancer-Associated-Fibroblasts for Progression of Kidney Renal Clear Cell Carcinoma.
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SUBMITTER: You Y
PROVIDER: S-EPMC8495159 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:In recent decades, substantial advancements in epigenetics have unveiled a profound understanding of its mechanisms in tumorigenesis and have offered promising strategies for epigenetic therapy in cancer patients. In our study, through bioinformatics analysis, we discovered a significant downregulation and hypermethylation of FOXI2 in clear cell renal cell carcinoma (ccRCC), while the expression in chromophobe cell carcinoma (chRCC) exhibited the opposite trend. Moreover, we established a strong correlation between FOXI2 expression levels and the prognosis of ccRCC. Gene enrichment analysis and cell function experiments unequivocally demonstrate that FOXI2 possesses the capability to induce cell cycle arrest and inhibit cell proliferation. Our research findings demonstrate that the expression of FOXI2 in ccRCC is under the regulation of promoter hypermethylation. Furthermore, in vitro experiments have conclusively shown that the overexpression of FOXI2 induces cell cycle arrest and inhibits cell proliferation.
| S-EPMC11016964 | biostudies-literature
Project description:Clear cell renal cell carcinoma (ccRCC) is a common genitourinary malignancy. The molecular pathogenesis of ccRCC remains unclear and biomarkers for daily practice were still limited. We performed an integrative analysis of two public ccRCC microarray datasets, E-GEOD-22541 and E-MTAB-1050, The candidate differential expression genes (DEG) were then confirmed in the E-GEOD-53757 dataset. In addition, an independent cohort of 50 ccRCC and 36 non-tumor kidney tissues were analyzed to examine the selected DGEs by qRT-PCR. We identified and validated two DEGs, namely GFOD1 and peejar, which were significantly up-regulated in ccRCC compared with normal renal tissues (p < 0.001). Moreover, the expression of these two genes are related to histological grade and stage and decrease of their expression correlated with disease progression (p < 0.05). Furthermore, we found the expression of peejar was positively correlated with the expression of GFOD1 in ccRCC tissue, with Pearson correlation coefficiency reaching 0.939 (p < 0.001). GFOD1 and peejar were novel genes correlated with ccRCC disease progression and patients' poor prognosis.
| S-EPMC5122367 | biostudies-literature
Project description:Kidney renal clear cell carcinoma (KIRC) is the most prevalent subtype of renal tumor. The underlying mechanisms governing KIRC initiation and progression are less known. The present study aimed to reveal novel hub genes associated with the initiation and progression of KIRC, which may be utilized as novel molecular biomarkers and therapeutic targets for the treatment of KIRC. The GSE6344 dataset from the Gene Expression Omnibus (GEO) database was integrated to identify differentially expressed genes (DEGs) using the limma package. Then, hub genes were identified and UALCAN, GEPIA, OncoDB, DriverDBv3, GENT2, and HPA databases were employed for the expression, survival, and methylation analyses. cBioPortal tool was used to investigate the genetic alterations, while CancerSEA, TIMER, DAVID, ENCORI, DrugBank, and GSCAlite were utilized to explore a few more hub gene-associated parameters. Finally, targeted bisulfite sequencing (bisulfite-seq), and RT-qPCR techniques were used to validate the expression and methylation level of the hub genes using Human RCC cell line 786-O, A-498, and normal renal tubular epithelial cell line HK-2. In total, 7299 DEGs were found between KIRC and normal samples in the GSE6344 dataset. Using STRING and Cytohubba analysis, four hub genes including VEGFA (vascular endothelial growth factor), ALB (Albumin), ENO2 (enolase 2), and CAVI1 (Caveolin 1) were selected as the hub genes. Further, it was validated through extensive analysis of TCGA datasets that these VEGA, ENO2, and CAV1 hub genes were significantly up-regulated, while ALB was significantly down-regulated in KIRC samples compared to controls. The dysregulation of these genes was found to be associated with the overall survival (OS) of the KIRC patients. Moreover, this study also revealed some novel links between VEGA, ALB, ENO2, and CAV1 expression and genetic alterations, promoter methylation status, immune cell infiltration, miRNAs, gene enrichment terms, and various chemotherapeutic drugs. The present study revealed a panel of four hub genes, which contributed to improving our understanding of the underlying molecular mechanisms of KIRC development and can be utilized as promising novel biomarkers for KIRC diagnosis, prognosis, and treatment.
| S-EPMC10560940 | biostudies-literature
Project description:ObjectivesClear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma. Cancer-associated fibroblasts (CAFs) as the primary components of cancer stroma can affect tumor progression by secreting exosomes, while exosomes are carriers for proteins, nucleic acids, and other agents that responsible for delivery of biological information. Given this, exosomes derived from CAFs are emerging as promising biomarkers in clinical cancer diagnosis. Nevertheless, their role in clear cell renal cell carcinoma (ccRCC) remains poorly understood.MethodsHere, we separated fibroblasts from ccRCC tissue, extracted exosomes, observed their morphology, and detected the expression of exosome marker proteins including Hsp70, CD9, and CD63. In the meantime, we labeled exosomes and performed coculture experiment to verify the delivery of miR-224-5p from CAFs to 769-P cells with exosomes as a carrier, so as to clarify the effect of CAF-derived exosomes on ccRCC cell malignant behaviors, as well as to discuss how miR-224-5p involves in above regulation.ResultsTransmission electron microscopy was firstly applied, and it was noted that the exosomes we isolated were in normal range. Besides, Western blot also confirmed the presence of exosome marker proteins Hsp70, CD9, and CD63. Furthermore, coculture experiments were performed and the CAF-derived exosomes were observed to be able to facilitate the malignant behaviors of ccRCC cells, and the exosomal miR-224-5p could be internalized by ccRCC cells to participate in regulation of cell proliferation, migration, invasion, and apoptosis.ConclusionTo sum up, miR-224-5p can enter ccRCC cells via CAF-derived exosomes, in turn, promoting the malignant behaviors of ccRCC cells, which indicates that miR-224-5p has the potential severing as a therapeutic target for ccRCC.
| S-EPMC8169240 | biostudies-literature
Project description:BackgroundKidney renal clear cell carcinoma (KIRC) is the most common subtype of renal tumor. However, the molecular mechanisms of KIRC pathogenesis remain little known. The purpose of our study was to identify potential key genes related to the occurrence and prognosis of KIRC, which could serve as novel diagnostic and prognostic biomarkers for KIRC.MethodsThree gene expression profiles from gene expression omnibus database were integrated to identify differential expressed genes (DEGs) using limma package. Enrichment analysis and PPI construction for these DEGs were performed by bioinformatics tools. We used Gene Expression Profiling Interactive Analysis (GEPIA) database to further analyze the expression and prognostic values of hub genes. The GEPIA database was used to further validate the bioinformatics results. The Connectivity Map was used to identify candidate small molecules that could reverse the gene expression of KIRC.ResultsA total of 503 DEGs were obtained. The PPI network with 417 nodes and 1912 interactions was constructed. Go and KEGG pathway analysis revealed that these DEGs were most significantly enriched in excretion and valine, leucine, and isoleucine degradation, respectively. Six DEGs with high degree of connectivity (ACAA1, ACADSB, ALDH6A1, AUH, HADH, and PCCA) were selected as hub genes, which significantly associated with worse survival of patients. Finally, we identified the top 20 most significant small molecules and pipemidic acid was the most promising small molecule to reverse the KIRC gene expression.ConclusionsThis study first uncovered six key genes in KIRC which contributed to improving our understanding of the molecular mechanisms of KIRC pathogenesis. ACAA1, ACADSB, ALDH6A1, AUH, HADH, and PCCA could serve as the promising novel biomarkers for KIRC diagnosis, prognosis, and treatment.
| S-EPMC6503072 | biostudies-literature
Project description:The outcome of kidney renal clear cell carcinoma (KIRC) differs even among individuals with similar clinical characteristics. DNA methylation is regarded as a regulator of gene expression in cancers, which may be a molecular marker of prognosis. In this study, we aimed to mine novel methylation markers of the prognosis of KIRC. We revealed a total of 2793 genes differentially methylated in their promoter regions (DMGs) and 2979 differentially expressed genes (DEGs) in KIRC tissues compared with normal tissues using The Cancer Genome Atlas datasets. Then, we detected 57 and 34 subpathways enriched among the DMGs and DEGs, respectively, using the R package iSubpathwayMiner. We retained 56 subpathways related to both aberrant methylation and expression based on a hypergeometric test for further analysis. An integrated gene regulatory network was constructed using the regulatory relationships between genes in the subpathways. Using the top 15% of the nodes from the network ranked by degree, survival analysis was performed. We validated four DNA methylation signatures (RAC2, PLCB2, VAV1, and PARVG) as being highly correlated with prognosis in KIRC. These findings suggest that DNA methylation might become a prognostic predictor in KIRC and could supplement histological prognostic prediction.
| S-EPMC5354907 | biostudies-literature
Project description:BackgroundKidney renal clear cell carcinoma (KIRC) is the most common type of kidney cancer in adults, and it is responsible for approximately 90-95% of cases. Although extensive evidence has suggested that many immune- and inflammation-related genes could serve as effective biomarkers in KIRC, the potential associations among immune-, inflammation- and KIRC-related genes has not been sufficiently understood.MethodsHere, we integrated multiple levels of data to construct an immune-, inflammation- or KIRC-directed neighbour network (IIKDN network) and a KIRC-related gene-directed network (KIRCD network).ResultsOur analysis suggested that immune- and inflammation-related genes in the network have special topological characteristics and expression patterns related to KIRC. We further identified five core clusters that showed a tighter network structure and stronger correlation of expression from the KIRCD network. Specifically, multiple-level molecular characteristics were systematically portrayed, including somatic mutation, copy-number variant and DNA methylation for the genes in five core clusters. We discovered that the genes showed strong correlation with respect to the expression and methylation levels in these five core clusters. These five core clusters could become special prognostic biomarkers for KIRC, and functional analysis showed that they were associated with activation of the immune and inflammation systems and cancer progression.ConclusionsOur findings highlighted the novel role of the immune and inflammation genes in KIRC.
| S-EPMC6537414 | biostudies-literature
Project description:BackgroundClear cell renal cell cancer (ccRCC), the 8th leading cause of cancer-related death in the US, is challenging to treat due to high level intratumoral heterogeneity (ITH) and the paucity of druggable driver mutations. CcRCC is unusual for its high frequency of epigenetic regulator mutations, such as the SETD2 histone H3 lysine 36 trimethylase (H3K36me3), and low frequency of traditional cancer driver mutations. In this work, we examined epigenetic level ITH and defined its relationships with pathologic features, aspects of tumor biology, and SETD2 mutations.ResultsA multi-region sampling approach coupled with EPIC DNA methylation arrays was conducted on a cohort of normal kidney and ccRCC. ITH was assessed using DNA methylation (5mC) and CNV-based entropy and Euclidian distances. We found elevated 5mC heterogeneity and entropy in ccRCC relative to normal kidney. Variable CpGs are highly enriched in enhancer regions. Using intra-class correlation coefficient analysis, we identified CpGs that segregate tumor regions according to clinical phenotypes related to tumor aggressiveness. SETD2 wild-type tumors overall possess greater 5mC and copy number ITH than SETD2 mutant tumor regions, suggesting SETD2 loss contributes to a distinct epigenome. Finally, coupling our regional data with TCGA, we identified a 5mC signature that links regions within a primary tumor with metastatic potential.ConclusionTaken together, our results reveal marked levels of epigenetic ITH in ccRCC that are linked to clinically relevant tumor phenotypes and could translate into novel epigenetic biomarkers.
| S-EPMC10149001 | 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:Background:Aurora kinase B (AURKB) is an important carcinogenic factor in various tumors, while its role in clear cell renal cell carcinoma (ccRCC) still remains unclear. This study aimed to investigate its prognostic value and mechanism of action in ccRCC. Methods:Gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. R software was utilized to analyze the expression and prognostic role of AURKB in ccRCC. Gene set enrichment analysis (GSEA) was used to analyze AURKB related signaling pathways in ccRCC. Results:AURKB was expressed at higher levels in ccRCC tissues than normal kidney tissues. Increased AURKB expression in ccRCC correlated with high histological grade, pathological stage, T stage, N stage and distant metastasis (M stage). Kaplan-Meier survival analysis suggested that high AURKB expression patients had a worse prognosis than patients with low AURKB expression levels. Multivariate Cox analysis showed that AURKB expression is a prognostic factor of ccRCC. GSEA indicated that genes involved in autoimmune thyroid disease, intestinal immune network for IgA production, antigen processing and presentation, cytokine-cytokine receptor interaction, asthma, etc., were differentially enriched in the AURKB high expression phenotype. Conclusions:AURKB is a promising biomarker for predicting prognosis of ccRCC patients and a potential therapeutic target. In addition, AURKB might regulate progression of ccRCC through modulating intestinal immune network for IgA production and cytokine-cytokine receptor interaction, etc. signaling pathways. However, more research is necessary to validate the findings.
| S-EPMC6752188 | biostudies-literature