MiR22 is a master regulator of genes predictive of patient survival in clear cell renal cell carcinoma
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA475462 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7287360.fastq.gz | Fastqsanger.gz | |||
| SRR7287357.fastq.gz | Fastqsanger.gz | |||
| SRR7287358.fastq.gz | Fastqsanger.gz | |||
| SRR7287359.fastq.gz | Fastqsanger.gz |
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Project description:Mononuclear phagocytes moderate tissue repair, immune activation and tolerance. In the renal tubulo-interstitium, specialized DCs help maintain homeostasis and protect tubuli from immune injury. Human renal cell carcinoma is immunogenic; yet immunotherapies that target T-cell dysfunction show limited clinical efficacy suggesting additional mechanisms of immunoinhibition. We previously described “enriched-in-renal cell carcinoma” (erc)DCs. In tumor tissue, they are found in tight contact with T cells which are dysfunctional. Here we describe that ercDCs exhibit a distinct polarization state imparted by tissue-specific signals characteristic for ccRCC and renal tissue homeostasis. The resulting mosaic transcript signature includes features associated with host defense activity, angiogenesis/invasion and T-cell inhibition. An ercDC-specific profile was predictive for patient survival and suggests potential therapeutic targets for improved immunotherapy.
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Project description:BackgroundRecently, increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC).MethodsWe used the DNA methylation dataset of The Cancer Genome Atlas (TCGA) database to construct a 31-CpG-based signature which could accurately predict the overall survival of ccRCC. Meanwhile, we constructed a nomogram to predict the prognosis of patients with ccRCC.ResultThrough LASSO Cox regression analysis, we obtained the 31-CpG-based epigenetic signature which were significantly related to the prognosis of ccRCC. According to the epigenetic signature, patients were divided into two groups with high and low risk, and the predictive value of the epigenetic signature was verified by other two sets. In the training set, hazard ratio (HR) = 13.0, 95% confidence interval (CI) 8.0-21.2, P < 0.0001; testing set: HR = 4.1, CI 2.2-7.7, P < 0.0001; entire set: HR = 7.2, CI 4.9-10.6, P < 0.0001, Moreover, combined with clinical indicators, the prediction of 5-year survival of ccRCC reached an AUC of 0.871.ConclusionsOur study constructed a 31-CpG-based epigenetic signature that could accurately predicted overall survival of ccRCC and staging progression of ccRCC. At the same time, we constructed a nomogram, which may facilitate the prediction of prognosis for patients with ccRCC.
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Project description:Clear cell Renal Cell Carcinoma (ccRCC) is among the 10 most common cancers and causes more than 140,000 deaths worldwide every year. In order to elucidate the underlying molecular mechanisms orchestrated by phosphorylation modifications, we performed a comprehensive quantitative phosphoproteomics characterization of ccRCC tumor and normal adjacent tissues. Here, we identified 16,253 phosphopeptides, of which more than 9,000 were quantified. Our in-depth analysis revealed 1,336 phosphopeptides to be differentially regulated between tumor and normal tissues. Moreover, our data reveals that significantly up-regulated phosphoproteins are associated with cytoskeletal re-organization which suggests migratory and invasive behavior of renal tumors. This is supported by a pronounced mesenchymal profile of ccRCC phosphorylation events. Our rigorous characterization of the renal phosphoproteome also revealed that both EGFR and VEGFR are the most important mediators of phospho signaling in RCC pathogenesis. Furthermore, we determined the kinases PAK2, CDK1, Erk1 and Erk2 to be master kinases that are responsible for phosphorylations of many substrates associated with cell proliferation, inflammation and migration. These master kinases are targetable by inhibitory FDA-approved drugs such as fostamatinib and minocycline, which can serve as novel therapeutic agents for ccRCC treatment.
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Project description:The transcription factor EVI1 plays an oncogenic role in several types of neoplasms by promoting aggressive cancer features. EVI1 contributes to epigenetic regulation and transcriptional control, and its overexpression has been associated with enhanced PI3K-AKT-mTOR signaling in some settings. These observations raise the possibility that EVI1 influences the prognosis and everolimus-based therapy outcome of clear cell renal cell carcinoma (ccRCC). Here, gene expression and protein immunohistochemical studies of ccRCC show that EVI1 overexpression is associated with advanced disease features and with poorer outcome-particularly in the CC-e.3 subtype defined by The Cancer Genome Atlas. Overexpression of an oncogenic EVI1 isoform in RCC cell lines confers substantial resistance to everolimus. The EVI1 rs1344555 genetic variant is associated with poorer survival and greater progression of metastatic ccRCC patients treated with everolimus. This study leads us to propose that evaluation of EVI1 protein or gene expression, and of EVI1 genetic variants may help improve estimates of prognosis and the benefit of everolimus-based therapy in ccRCC.
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Project description:Detailed genetic profiling of clear cell Renal Cell Carcinoma (ccRCC) has shown that these tumors are characterized by large genetic heterogeneity with some genomic regions commonly affected by structural changes. Loss on chromosomes 3p and 14q, and gain on 5q and 7 are examples of alterations commonly reported in ccRCC. However, there is no consensus regarding the potential prognostic information carried by the identified alterations. We report on poorer outcome for patients with gain on 5q and 7, and loss on 9p, 9q and 14q. These aberrations were in addition found more frequently in metastasized tumors, suggesting that they are markers for advanced disease. Furthermore, the presence of ≥ 4 common aberrations was associated with decreased survival time. Shorter relative telomere length (RTL) has been associated with loss of chromosomal regions in ccRCC tumors, but we found no significant associations between tumor RTL and chromosomal deletions. However, significantly lower tumor-to-nontumor (T/N) RTL ratio was detected for patients with loss on 4q and 9p. Finally, we found a minimum region (MR) of genetic loss of 1.4 Mbp on chromosome 9p and this region contains only one gene, the tumor suppressor candidate 1 gene (TUSC1). TUSC1 has been implicated in lung carcinogenesis and our result further strengthens its role in tumorigenesis.
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Project description:ObjectivesTo investigate the role of DNA methylation regulators in the prognosis of clear cell renal cell carcinoma (ccRCC) and to construct a DNA methylation regulator-based signature for predicting patient outcome.MethodsData from the TCGA dataset were downloaded and analyzed to identify differentially expressed DNA methylation regulators and their interaction as well as correlation. Consensus clustering was used to establish groups of ccRCC with distinct clinical outcomes. A prognostic signature based on two sets of DNA methylation regulators was established and validated in an independent cohort.ResultsOur analysis revealed that the expression levels of DNMT3B, MBD1, SMUG1, DNMT1, DNMT3A, TDG, TET3, MBD2, UHRF2, MBD3, UHRF1, and TET2 were significantly upregulated in ccRCC samples, while UNG, ZBTB4, TET1, ZBTB38, and MECP2 were markedly downregulated. UHRF1 was identified as a hub gene in the DNA methylation regulator interaction network. Significant differences were found regarding overall survival, gender, tumor status, and grade between ccRCC patients in the two risk groups. The prognostic signature, based on two sets of DNA methylation regulators, was an independent prognostic indicator, and these findings were validated in an external, independent cohort.ConclusionsThe study provides evidence that DNA methylation regulators play a significant role in the prognosis of ccRCC and the developed DNA methylation regulator-based signature could effectively predict patient outcome.
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