Identification of metastamirs as metastasis-associated microRNAs in clear cell renal cell carcinomas
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE37989 | GEO | 2013/02/26
SECONDARY ACCESSION(S): PRJNA166875
REPOSITORIES: GEO
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Project description:Background/Objective: MicroRNAs (miRNAs) play a pivotal role in cancerogenesis and cancer progression, but their specific role in metastasis of clear cell renal cell carcinomas (ccRCCs) as so-called metastamirs is still limited. Based on microRNA microarray analyses from normal (n=12) and cancerous (n=12) samples of ccRCC specimens and from bone metastases (n=9) of ccRCC patients, we identified a set of 57 differentially expressed microRNAs between those three sample groups of ccRCC. A selected panel of 33 miRNAs, including miRNAs reported in the literature as differentially expressed in non-metastatic RCC, was validated by RT-qPCR on 57 clinical samples. 30 of the 33 examined miRNAs were confirmed to be deregulated. A stepwise down-regulated miRNA expression from normal over primary tumor to metastatic tissue samples was found to be typical. 23 miRNAs (miR-10b/-19a/-19b/-20a/-29a/-29b/-29c/-100/-101/-126/-127/-130/-141/-143/-145/-148a/-192/-194/-200c/-210/-215/-370/-514) were down-regulated in metastatic tissue samples in comparison to normal tissue. This down-regulated expression in metastatic tissue was also present in 21 miRNAs except for miR-127 and miR-370. The altered miRNA profiles including the newly identified metastasis-associated miRNAs, the compiled predicted miRNA-target interactions, and the significant correlations of miRNAs which were either lost or newly appeared in the studied sample groups afford a solid basis for further functional analyses of individual miRNAs. In this study, microarray-based profiling was performed from 9 bone metastatic tissue samples from 9 patients with clear cell renal cell carcinoma (ccRCC). For controls, 2 bone metastatic samples from two patients with prostate carcinoma and 5 total RNA pools (2 different pools of total RNAs isolated from malignant renal tissue samples derived from different ccRCC patients; 1 pool from non-malignant renal tissue of ccRCC patients; 2 pools of total RNA both from malignant and non-malignant prostate cancer tissue) were used. In addition, matched malignant (e.g., malignant NC2) and non-malignant (e.g., non-malignant NN1) samples from two independent 12 ccRCC sets were profiled (these samples were previously analyzed on a different Platform in GSE12105). The 2002 TNM System and the 2004 WHO classification was used for staging and grading.
2013-02-26 | E-GEOD-37989 | biostudies-arrayexpress
Project description:Clear cell renal cell carcinomas (ccRCC) are characterized by arm-wide chromosomal alterations. Loss at 14q is associated with disease aggressiveness in ccRCC, which responds poorly to chemotherapeutics. The 14q locus contains one of the largest miRNA clusters in the human genome; however, little is known about the contribution of these miRNAs to ccRCC pathogenesis. In this regard, we investigated the expression pattern of selected miRNAs at the 14q32 locus in TCGA kidney tumors and in ccRCC cell lines. We validated that the miRNA cluster is downregulated in ccRCC (and cell lines) as well as in papillary kidney tumors relative to normal kidney tissues and primary renal proximal tubule epithelial (RPTEC) cells. We demonstrated that agents modulating expression of DNMT1 (e.g., 5-Aza-deoxycytidine) could modulate miRNA expression in ccRCC cell lines. Lysophosphatidic acid (LPA, a Lysophospholipid mediator elevated in ccRCC) not only increased labile iron content but also modulated expression of 14q32 miRNAs. Through an overexpression approach targeting a subset of 14q32 miRNAs (specifically at subcluster A: miR-431, miR-432, miR-127, and miR-433) in 769-P cells, we uncovered changes in cellular viability and claudin-1, a tight junction marker. A global proteomic approach was implemented using these miRNA overexpressing cell lines which uncovered ATXN2 as a highly downregulated target, which has a role in chronic kidney disease pathogenesis. Collectively, these findings support a contribution of miRNAs at 14q32 in ccRCC pathogenesis.
2023-05-10 | PXD036428 | Pride
Project description:MicroRNAs (miRNAs) are short single stranded RNAs that are associated with gene regulation at the transcriptional and translational level. Changes in their expression were found in a variety of human cancers. Because of the lack of corresponding data in clear renal cell carcinoma (ccRCC) we have performed genome-wide expression profiling of miRNAs using microarray analysis and quantification of specific miRNAs by TaqMan real-time RT-PCR. Matched malignant and non-malignant tissue samples from two independent 12 ccRCC sets were profiled. The microassay-based experiments identified 14 overexpressed and 20 downregultaed miRNAs in malignant samples. Expression in ccRCC tissue samples compared to matched non-malignant samples measured by RT-PCR was increased by 2.7 to 28fold for the hsa-mir-16, -452, -224, -155, and -210, but decreased by 6.2 to 96fold for hsa-mir-200b, -363, , -429, -200c, -514, and -141. No significant associations between these differentially expressed miRNAs and the clinico-pathological factors tumor stage, grade, and survival rate were found. Nevertheless, malignant and non-malignant tissue could clearly be differentiated by their miRNA profile . A combination of miR-141 and miR-155 resulted in a 96% overall correct classification of samples. The presented differential miRNA pattern provides a solid basis for further validation including functional studies.
2008-10-01 | GSE12105 | GEO
Project description:The majority of metastatic clear cell renal cell carcinoma (ccRCC) patients are treated with tyrosine kinase inhibitors (TKIs) in first line, however, a fraction are refractory to these drugs. MicroRNAs (miRNA) are regulatory molecules that have proven to be accurate biomarkers in cancer. Here we identified miRNA predictive of progressive disease under TKI treatment. Whole miRNA expression was quantified by deep-sequencing in a discovery set of 74 metastatic ccRCC cases uniformly treated with TKIs. Twenty nine miRNAs were found to be differentially expressed in the tumors of patients who progressed under TKI therapy. Among six miRNAs selected for validation, an over-expression of miR-1307-3p, miR-155-5p, miR-221-3p, miR-425-5p and miR-222-3p was confirmed in patients with progressive disease as best response. A 2 miRNA-based classifier could discriminate individuals with progressive disease upon TKI treatment with a better predictive value than clinicopathological risk factors commonly used. miRNAs significantly associated with progression-free survival and overall survival were identified, and 7 miRNAs were found to overlap as predictive for early progressive disease, PFS and OS.
2017-08-23 | GSE74174 | GEO
Project description:Renal cell carcinoma (RCC) is the most common neoplasm of the adult kidney. Currently, there are no biomarkers for the diagnostic, prognostic, or predictive applications in RCC. MicroRNAs (miRNAs) are short non protein-coding RNAs that negatively regulate gene expression and have been shown to be involved in cancer. We analyzed a total of 70 matched pairs of clear cell RCC (ccRCC) and normal kidney tissues from the same patients by microarray analysis and validated our results by quantitative real time PCR. We identified 166 miRNAs significantly dysregulated in ccRCC. MiR-122, miR-155 and miR-210 had the highest fold changes of overexpression while miR-200c, miR-335, and miR-218 were the most downregulated. We performed extensive bioinformatics analysis including a combinatorial analysis of previously reported miRNAs dysregulated in RCC and extensive target prediction analysis. Many miRNAs were predicted to target a number of genes involved in RCC pathogenesis. Our results showed that miRNA dysregulation in RCC can be attributed in part, to chromosomal aberrations, the co-regulation of miRNA clusters, and co-expression with host genes. We also correlated miRNA expression with clinical characteristics and found miR-155 expression was correlated with ccRCC tumor size. In conclusion, our analysis showed that a number of miRNAs are dysregulated in ccRCC and may contribute to kidney cancer pathogenesis by targeting more than one key molecule. We identified mechanisms that may contribute to miRNA dysregulation in ccRCC. Dysregulated miRNAs represent potential biomarkers for kidney cancer. We preformed a miRNA microarray on 20 pairs of matched primary clear cell renal cell carcinoma (ccRCC) and normal kidney tissue from the same patient (St. Michael's Hospital, Toronto, Canada). One matched pair was used per array for a total of 20 arrays. Microarray results were validated by quantitative real time PCR using an independent set of 50 matched pairs of ccRCC and normal kidney tissue from the same patient.
2010-07-22 | E-GEOD-23085 | biostudies-arrayexpress
Project description:We surveyed miRNA expression in intact airway smooth muscle tissue to evaluate candidate miRNA for further studies. We found 60 miRNA expressed at a detectable level in all four donors and another 118 miRNA expressed in three of the four donors. There were 18 miRNAs with expression levels > 2-fold above normalized expression values. These consisted of 12 described human miRNA, including let-7c, miR-16, -23b, -24, -26a, -125b, -143, -145, -200c and -205; 3 mouse miRNAs including miR-99a, -140* and -370; and 3 novel miRNA termed abi-13143, -13232 and -13268.
2009-07-22 | GSE16586 | GEO
Project description:MicroRNAs (miRNAs) are short single stranded RNAs that are associated with gene regulation at the transcriptional and translational level. Changes in their expression were found in a variety of human cancers. Because of the lack of corresponding data in clear renal cell carcinoma (ccRCC) we have performed genome-wide expression profiling of miRNAs using microarray analysis and quantification of specific miRNAs by TaqMan real-time RT-PCR. Matched malignant and non-malignant tissue samples from two independent 12 ccRCC sets were profiled. The microassay-based experiments identified 14 overexpressed and 20 downregultaed miRNAs in malignant samples. Expression in ccRCC tissue samples compared to matched non-malignant samples measured by RT-PCR was increased by 2.7 to 28fold for the hsa-mir-16, -452, -224, -155, and -210, but decreased by 6.2 to 96fold for hsa-mir-200b, -363, , -429, -200c, -514, and -141. No significant associations between these differentially expressed miRNAs and the clinico-pathological factors tumor stage, grade, and survival rate were found. Nevertheless, malignant and non-malignant tissue could clearly be differentiated by their miRNA profile . A combination of miR-141 and miR-155 resulted in a 96% overall correct classification of samples. The presented differential miRNA pattern provides a solid basis for further validation including functional studies. The study was performed with two independent sample sets. For each set 12 kidney tissue sample pairs were derived from adult patients undergoing radical nephrectomy at the University Hospital Charité. All tumor types were clear renal cell carcinoma. Tumor classification and stage were established according to the 2002 TNM System and the 2004 WHO Classification. Matched malignant (#NC (e.g. 2NC)) and non-malignant (#NN (e.g. 1NN)) tissue samples from two independent 12 ccRCC sets were profiled.
2010-06-25 | E-GEOD-12105 | biostudies-arrayexpress
Project description:Background: Newer 3D culturing approaches are a promising way to better mimic the in vivo tumor microenvironment and to study the interactions between the heterogeneous cell populations of glioblastoma multiforme. Like many other tumors, glioblastoma uses extracellular vesicles as an intercellular communication system to prepare surrounding tissue for invasive tumor growth. However, little is known about the effects of 3D culture on extracellular vesicles. The aim of this study was to comprehensively characterise extracellular vesicles in 3D organoid models and compare them to conventional 2D cell culture systems.Methods: Primary glioblastoma cells were cultured as 2D and 3D organoid models. Extracellular vesicles were obtained by precipitation and immunoaffinity, with the latter allowing targeted isolation of the CD9/CD63/CD81 vesicle subpopulation. Comprehensive vesicle characterisation was performed and miRNA expression profiles were generated by smallRNA-sequencing. In silico analysis of differentially regulated miRNAs was performed to identify mRNA targets and corresponding signaling pathways. The tumor cell media and extracellular vesicle proteome were analysed by high-resolution mass spectrometry.Results: We observed an increased concentration of extracellular vesicles in 3D organoid cultures. Differential gene expression analysis further revealed the regulation of twelve miRNAs in 3D tumor organoid cultures (with nine miRNAs down and three miRNAs upregulated). MiR-23a-3p, known to be involved in glioblastoma invasion, was significantly increased in 3D. MiR-7-5p, which counteracts glioblastoma malignancy, was significantly decreased. Moreover, we identified four miRNAs (miR- 323a-3p, miR-382-5p, miR-370-3p, miR-134-5p) located within the DLK1-DIO3 domain, a cancer associated genomic region, suggesting a possible importance of this region in glioblastoma progression. Overrepresentation analysis identified alterations of extracellular vesicle cargo in 3D organoids, including representation of several miRNA targets and proteins primarily implicated in the immune response.Conclusion: Our results show that 3D glioblastoma organoid models secrete extracellular vesicles with an altered cargo compared to corresponding conventional 2D cultures. Extracellular vesicles from 3D cultures were found to contain signaling molecules associated with the immune regulatory signaling pathways and as such could potentially change the surrounding microenvironment towards tumor progression and immunosuppressive conditions. These findings suggest the use of 3D glioblastoma models for further clinical biomarker studies as well as investigation of new therapeutic options.
2024-04-09 | PXD047328 | Pride
Project description:Few have characterized miRNA expression during the transition from injury to neural repair and secondary neurodegeneration following stroke in humans. We compared expression of 754 miRNAs from plasma samples collected 5, 15, and 30 days post-ischemic stroke from a discovery cohort (n=55) and 15-days post-ischemic stroke from a validation cohort (n=48) to healthy control samples (n=55 and 48 respectively) matched for age, sex, race and cardiovascular comorbidities using qRT-PCR. Eight miRNAs remained significantly altered across all time points in both cohorts including many described in acute stroke. The number of significantly dysregulated miRNAs more than doubled from post-stroke day 5 (19 miRNAs) to days 15 (50 miRNAs) and 30 (57 miRNAs). Twelve brain-enriched miRNAs were significantly altered at one or more time points (decreased expression, stroke versus controls: miR-107; increased expression: miR-99-5p, miR-127-3p, miR-128-3p, miR-181a-3p, miR-181a-5p, miR-382-5p, miR-433-3p, miR-491-5p, miR-495-3p, miR-874-3p, and miR-941). Many brain-enriched miRNAs were associated with apoptosis over the first month post-stroke whereas other miRNAs suggested a transition to synapse regulation and neuronal protection by day 30. These findings suggest that a program of decreased cellular proliferation may last at least 30 days post-stroke, and points to specific miRNAs that could contribute to neural repair in humans.
2023-10-04 | GSE244632 | GEO
Project description:Renal cell carcinoma (RCC) is one of the most common cancers worldwide with nearly non-symptomatic course till advanced stage of disease. RCC can be distinguished into three subtypes: papillary (pRCC), chromophobe (chRCC) and clear cell renal cell carcinoma (ccRCC) representing up to 75% of all RCC cases. Detection and RCC monitoring tools are limited to standard imaging techniques, in combination with non-RCC specific morphological and biochemical read-outs. RCC subtype identification relays mainly on results of pathological examination of tumor slides. Molecular, clinically applicable and ideally non-invasive tools aiding RCC management are still non-existent, although molecular characterization of RCC is relatively advanced. Hence many research efforts concentrate on identification of molecular markers that will assist with RCC sub-classification and monitoring. Due to stability and tissue-specificity miRNAs are promising candidates for such biomarkers. Here we performed a meta-analysis study, utilized seven available NGS and seven microarray RCC studies in order to identify subtype-specific expression of miRNAs. We concentrated on four potentially oncocytoma-specific miRNAs (miRNA-424-5p, miRNA-146b-5p, miRNA-183-5p, miRNA-218-5p), two pRCC (miRNA-127-3p, miRNA-139-5p) and eight ccRCC specific miRNAs (miRNA-200c-3p, miRNA-362-5p, miRNA-363-3p and miRNA-204-5p, 21-5p, miRNA-224-5p, miRNA-155-5p, miRNA-210-3p) and validated their expression in an independent sample set. Additionally, we found ccRCC-specific miRNAs to be differentially expressed in ccRCC Fuhrman grades and identified alterations in their isoform composition in tumor tissue. Our results revealed that changes in expression of selected miRNA might be potentially utilized as a tool aiding ccRCC subclass discrimination and propose a miRNA panel aiding RCC subtype distinction.
2021-02-01 | GSE151423 | GEO