The long non-coding RNA lnc277 mediates a repressive gene signature in Ewing's sarcoma and is required for oncogenesis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE60891 | GEO | 2014/11/01
SECONDARY ACCESSION(S): PRJNA259749
REPOSITORIES: GEO
Similar Datasets
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2014-11-01 | E-GEOD-60891 | biostudies-arrayexpress
Project description:The long non-coding RNA lnc277 mediates a repressive gene signature in Ewing's sarcoma and is required for oncogenesis
| PRJNA259749 | ENA
Project description:The aim of this study was to construct a new immune-associated long non-coding RNA (lncRNA) signature to predict the prognosis of Ewing sarcoma (ES) and explore its molecular mechanisms. We downloaded transcriptome and clinical prognosis data from the Gene Expression Omnibus (GSE17679, which included 88 ES samples and 18 matched normal skeletal muscle samples), and used it as a training set to identify immune-related lncRNAs with different expression levels in ES. Univariable Cox regression was used to screen immune-related lncRNAs related to ES prognosis, and an immune-related lncRNA signature was constructed based on machine learning iterative lasso regression. An external verification set was used to confirm the predictive ability of the signature. Clinical feature subgroup analysis was used to explore whether the signature was an independent prognostic factor. In addition, CIBERSORT was used to explore immune cell infiltration in the high- and low-risk groups, and to analyze the correlations between the lncRNA signature and immune cell levels. Gene set enrichment and variation analyses were used to explore the possible regulatory mechanisms of the immune-related lncRNAs in ES. We also analyzed the expression of 17 common immunotherapy targets in the high- and low-risk groups to identify any that may be regulated by immune-related lncRNAs. We screened 35 immune-related lncRNAs by univariate Cox regression. Based on this, an immune-related 11-lncRNA signature was generated by machine learning iterative lasso regression. Analysis of the external validation set confirmed its high predictive ability. DPP10 antisense RNA 3 was negatively correlated with resting dendritic cell, neutrophil, and γδ T cell infiltration, and long intergenic non-protein coding RNA 1398 was positively correlated with resting dendritic cells and M2 macrophages. These lncRNAs may affect ES prognosis by regulating GSE17721_CTRL_VS_PAM3CSK4_12H_BMDC_UP, GSE2770_IL4_ACT_VS_ACT_CD4_TCELL_48H_UP, GSE29615_CTRL_VS_DAY3_ LAIV_IFLU_VACCINE_PBMC_UP, complement signaling, interleukin 2-signal transducer and activator of transcription 5 signaling, and protein secretion. The immune-related 11-lncRNA signature may also have regulatory effects on the immunotherapy targets CD40 molecule, CD70 molecule, and CD276 molecule. In conclusion, we constructed a new immune-related 11-lncRNA signature that can stratify the prognoses of patients with ES.
| S-EPMC8187926 | biostudies-literature
Project description:BackgroundLong non-coding RNAs (lncRNAs) are a class of non-coding RNAs with unique characteristics. These RNA can regulate cancer cells' survival, proliferation, invasion, metastasis, and angiogenesis and are potential diagnostic and prognostic markers. We identified a seven-lncRNA signature related to the overall survival (OS) of patients with Ewing's sarcoma (EWS).MethodsWe used an expression profile from the Gene Expression Omnibus (GEO) database as a training cohort to screen out the OS-associated lncRNAs in EWS and further established a seven-lncRNA signature using univariate Cox regression, the least absolute shrinkage, and selection operator (LASSO) regression analysis. The prognostic lncRNA signature was validated in an external dataset from the International Cancer Genome Consortium (ICGC) as a validation cohort.ResultsWe obtained 10 survival-related lncRNAs from the Kaplan-Meier and ROC curve analysis (log-rank test P < 0.05; AUC >0.6). Univariate Cox regression and LASSO regression analyses confirmed seven key lncRNAs and we established a lncRNA signature to predict an EWS prognosis. EWS patients in the training cohort were categorized into a low-risk group or a high-risk group based on their median risk score. The high-risk group's survival time was significantly shorter than the low-risk group's. This seven-lncRNA signature was further confirmed by the validation cohort. The area under the curve (AUC) for this lncRNA signature was up to 0.905 in the training group and 0.697 in the 3-year validation group. The nomogram's calibration curves demonstrated that EWS probability in the two cohorts was consistent between the nomogram prediction and actual observation.ConclusionWe screened a seven-lncRNA signature to predict the EWS patients' prognosis. Our findings provide a new reference for the current prognostic evaluation of EWS and new direction for the diagnosis and treatment of EWS.
| S-EPMC8214847 | biostudies-literature
Project description:Most Ewing's sarcomas harbor chromosomal translocations that encode fusions between EWS and ETS family members. The most common fusion, EWS/FLI, consists of an EWSR1-derived strong transcriptional activation domain fused, in-frame, to the DNA-binding domain-containing portion of FLI1. EWS/FLI functions as an aberrant transcription factor to regulate genes that mediate the oncogenic phenotype of Ewing's sarcoma. One of these regulated genes, NR0B1, encodes a corepressor protein, and likely plays a transcriptional role in tumorigenesis. However, the genes that NR0B1 regulates and the transcription factors it interacts with in Ewing's sarcoma are largely unknown. We used transcriptional profiling and chromatin immunoprecipitation to identify genes that are regulated by NR0B1, and compared these data to similar data for EWS/FLI. Although the transcriptional profile overlapped as expected, we also found that the genome-wide localization of NR0B1 and EWS/FLI overlapped as well, suggesting that they regulate some genes coordinately. Further analysis revealed that NR0B1 and EWS/FLI physically interact. This protein-protein interaction is likely to be relevant for the development of Ewing's sarcoma because mutations in NR0B1 that disrupt the interaction have transcriptional consequences and also abrogate oncogenic transformation. Taken together, these data suggest that EWS/FLI and NR0B1 physically interact, coordinately modulate gene expression, and mediate the transformed phenotype of Ewing's sarcoma.
| S-EPMC2789197 | biostudies-other
Project description:To date, the main criterion by which long ncRNAs (lncRNAs) are discriminated from mRNAs is based on the capacity of the transcripts to encode a protein. However, it becomes important to identify non-ORF-based sequence characteristics that can be used to parse between ncRNAs and mRNAs. In this study, we first established an extremely selective workflow to define a highly refined database of lncRNAs which was used for comparison with mRNAs. Then using this highly selective collection of lncRNAs, we found the CG dinucleotide frequencies were clearly distinct. In addition, we showed that the bias in CG dinucleotide frequency was conserved in human and mouse genomes. We propose that this sequence feature will serve as a useful classifier in transcript classification pipelines. We also suggest that our refined database of "bona fide" lncRNAs will be valuable for the discovery of other sequence characteristics distinct to lncRNAs.
| S-EPMC4158813 | biostudies-other
Project description:ObjectiveBy combining the expression profiles of metabolism-related genes (MRGS) with clinical information, the expression quantities of MRGS and the influence on development and prognosis were systematically analyzed, so as to provide a theoretical basis for the clinical study on the prognosis of Ewing's sarcoma.MethodsMRGs expression profiles of 64 patients with Ewing's sarcoma were obtained from GEO dataset. Univariate Cox regression analysis was used to identify metabolization-related differentially expressed genes (DEGs) related with prognosis in Ewing's sarcoma patients. Then, multivariate Cox analysis was used to calculate novel prognostic markers based on metabolism-related DEGs. Besides, We validate the model using ICGC datasets. Finally, the new prognostic index was verified on the basis of the prognostic models.ResultsMultivariate Cox regression analysis identified 74 metabolization-related DEGs, 25 of which were associated with Ewing's sarcoma patients' overall survival. Subsequently, we used 25 DEGs to construct metabolism-related prognostic signature for patients with Ewing's sarcoma. Based on the 18 DEGs regression coefficient, we propose the formula of each patient's risk score, and then divided the patients into high-risk group and low-risk group. The results indicated that the survival rate and survival time were higher in the low-risk group and lower in the high-risk group. Multivariate Cox analysis showed that risk score index was an independent prognostic factor for Ewing's sarcoma.ConclusionThe experimental results suggest that the 18 metabolism-related DEGs marker may be effective in predicting the prognosis of Ewing's sarcoma to some extent, helping to individualize treatment of patients at different risks.
| S-EPMC8461378 | biostudies-literature
Project description:EWS/FLI is a master regulator of Ewing's sarcoma formation. Gene expression studies in A673 Ewing's sarcoma cells have demonstrated that EWS/FLI downregulates more genes than it upregulates, suggesting that EWS/FLI, and/or its targets, function as transcriptional repressors. One critical EWS/FLI target, NKX2.2, is a transcription factor that contains both transcriptional activation and transcriptional repression domains, raising the possibility that it mediates portions of the EWS/FLI transcriptional signature. We now report that microarray analysis demonstrated that the transcriptional profile of NKX2.2 consists solely of downregulated genes, and overlaps with the EWS/FLI downregulated signature, suggesting that NKX2.2 mediates oncogenic transformation via transcriptional repression. Structure-function analysis revealed that the DNA binding and repressor domains in NKX2.2 are required for oncogenesis in Ewing's sarcoma cells, while the transcriptional activation domain is completely dispensable. Furthermore, blockade of TLE or HDAC function, two protein families thought to mediate the repressive function of NKX2.2, inhibited the transformed phenotype and reversed the NKX2.2 transcriptional profile in Ewing's sarcoma cells. Whole genome localization studies (ChIP-chip) revealed that a significant portion of the NKX2.2-repressed gene expression signature was directly mediated by NKX2.2 binding. These data demonstrate that the transcriptional repressive function of NKX2.2 is necessary, and sufficient, for the oncogenic phenotype of Ewing's sarcoma, and suggest a therapeutic approach to this disease.
| S-EPMC2291578 | biostudies-literature
Project description: Not available
| S-EPMC6984994 | biostudies-literature
Project description:Refractory and/or recurrent Ewing's sarcoma (EWS) remains a clinical challenge because the disease's resistance to therapy makes it difficult to achieve durable results with standard treatments that include chemotherapy, radiation, and surgery. Recently, insulin-like-growth-factor-1-receptor (IGF1R) antibodies have been shown to have a modest single-agent activity in EWS. Patient selection using biomarkers and understanding response and resistance mechanisms in relation to IGF1R and mammalian target of rapamycin pathways are areas of active research. Since EWS has a unique tumor-specific EWS-FLI1 t(11;22) translocation and oncogenic fusion protein, inhibition of EWS-FLI1 transcription, translation, and/or protein function may be key to eradicating EWS at the stem-cell level. Recently, a small molecule that blocks the protein-protein interaction of EWS-FLI1 with RNA helicase A has been shown in preclinical models to inhibit EWS growth. The successful application of this first-in-class protein-protein inhibitor in the clinic could become a model system for translocation-associated cancers such as EWS.
| S-EPMC2968715 | biostudies-literature