Dataset Information

Comparison of Stage 4 and Stage 4s Neuroblastoma Identifies Autophagy-Related Gene and LncRNA Signatures Associated With Prognosis.

ABSTRACT: Background: The spontaneous regression of neuroblastoma (NB) is most prevalent and well-documented in stage 4s NB patients. However, whether autophagy plays roles in the spontaneous regression of NB is unknown. Objective: This study aimed to identify autophagy-related genes (ARGs) and autophagy-related long non-coding RNAs (lncRNAs) differentially expressed in stage 4 and stage 4s NB and to build prognostic risk signatures on the basis of the ARGs and autophagy-related lncRNAs. Methods: One RNA-sequence (RNA-Seq) dataset (TARGET NBL, n = 153) was utilized as discovery cohort, and two microarray datasets (n = 498 and n = 223) were used as validation cohorts. Differentially expressed ARGs were identified by comparing stage 4s and stage 4 NB samples. An ARG signature risk score and an autophagy-related lncRNA signature risk score were constructed. The receiver operating characteristic (ROC) curve analyses were used to evaluate the survival prediction ability of the two signatures. Gene function annotation and Gene Set Enrichment Analysis (GSEA) were performed to clarify the autophagic biological processes enriched in different risk groups. Results: Nine ARGs were integrated into the ARG signature. Patients in the high-risk group of the ARG signature had significantly poorer overall survival (OS) than patients in the low-risk group. The ROC curves analyses revealed that the ARG signature performed very well in predicting OS [5-year area under the curve (AUC) = 0.81]. Seven autophagy-related lncRNAs were integrated into the autophagy-related lncRNA signature. Patients in the high-risk group of the lncRNA signature had significantly poorer OS than patients in the low-risk group. The ROC curve analyses also revealed that the lncRNA signature performed well in predicting OS (5-year AUC = 0.77). Both the ARG signature and lncRNA signature are independent with other clinical risk factors in the multivariate Cox regression survival analyses. GSEAs revealed that autophagy-related biological processes are enriched in low-risk groups. Conclusions: Autophagy-related genes and lncRNAs are differentially expressed between stage 4 and stage 4s NB. The ARG signature and autophagy-related lncRNA signature successfully stratified NB patients into two risk groups. Autophagy-related biological processes are highly enriched in low-risk NB groups.

SUBMITTER: Meng X

PROVIDER: S-EPMC7466450 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparison of Stage 4 and Stage 4s Neuroblastoma Identifies Autophagy-Related Gene and LncRNA Signatures Associated With Prognosis.

Meng Xinyao X Li Honglin H Fang Erhu E Feng Jiexiong J Zhao Xiang X

Frontiers in oncology 20200819

Background: The spontaneous regression of neuroblastoma (NB) is most prevalent and well-documented in stage 4s NB patients. However, whether autophagy plays roles in the spontaneous regression of NB is unknown. Objective: This study aimed to identify autophagy-related genes (ARGs) and autophagy-related long non-coding RNAs (lncRNAs) differentially expressed in stage 4 and stage 4s NB and to build prognostic risk signatures on the basis of the ARGs and autophagy-related lncRNAs. ...[more]

PMID: 32974147

Similar Datasets

Project description:BackgroundCuproptosis, a novel form of programmed cell death, plays an essential role in various cancers. However, studies of the function of cuproptosis lncRNAs (CRLs) in colorectal cancer (CRC) remain limited. Thus, this study aims to identify the cuprotosis-related lncRNAs (CRLs) in CRC and to construct the potential prognostic CRLs signature model in CRC.MethodsFirst, we downloaded RNA-Seq data and clinical information of CRC patients from TCGA database and obtained the prognostic CRLs based on typical expression analysis of cuproptosis-related genes (CRGs) and univariate Cox regression. Then, we constructed a prognostic model using the Least Absolute Shrinkage and Selection Operator algorithm combined with multiple Cox regression methods (Lasso-Cox). Next, we generated Kaplan-Meier survival and receiver operating characteristic curves to estimate the performance of the prognostic model. In addition, we also analysed the relationships between risk signatures and immune infiltration, mutation, and drug sensitivity. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT -PCR) to verify the prognostic model.ResultLasso-Cox analysis revealed that four CRLs, SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, were related to CRC prognosis. Receiver operating characteristic (ROC) and Kaplan-Meier analysis curves indicated that this model performs well in prognostic predictions of CRC patients. The DCA results also showed that the model included four gene signatures was better than the traditional model. In addition, GO and KEGG analyses revealed that DE-CRLs are enriched in critical signalling pathway, such as chemical carcinogenesis-DNA adducts and basal cell carcinoma. Immune infiltration analysis revealed significant differences in immune infiltration cells between the high-risk and low-risk groups. Furthermore, significant differences in somatic mutations were noted between the high-risk and low-risk groups. Finally, we also validated the expression of four CRLs in FHCs cell lines and CRC cell lines using qRT-PCR.ConclusionThe signature composed of SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, which has better performance in predicting colorectal cancer prognosis and are promising biomarkers for prognosis prediction of CRC.

Project description:ObjectiveAutophagy and long noncoding RNAs (lncRNAs) have been the focus of research on the pathogenesis of melanoma. However, the autophagy network of lncRNAs in melanoma has not been reported. The purpose of this study was to investigate the lncRNA prognostic markers related to melanoma autophagy and predict the prognosis of patients with melanoma.MethodsWe downloaded RNA sequencing data and clinical information of melanoma from the Cancer Genome Atlas. The coexpression of autophagy-related genes (ARGs) and lncRNAs was analyzed. The risk model of autophagy-related lncRNAs was established by univariate and multivariate Cox regression analyses, and the best prognostic index was evaluated combined with clinical data. Finally, gene set enrichment analysis was performed on patients in the high- and low-risk groups.ResultsAccording to the results of the univariate Cox analysis, only the overexpression of LINC00520 was associated with poor overall survival, unlike HLA-DQB1-AS1, USP30-AS1, AL645929, AL365361, LINC00324, and AC055822. The results of the multivariate Cox analysis showed that the overall survival of patients in the high-risk group was shorter than that recorded in the low-risk group (p < 0.001). Moreover, in the receiver operating characteristic curve of the risk model we constructed, the area under the curve (AUC) was 0.734, while the AUC of T and N was 0.707 and 0.658, respectively. The Gene Ontology was mainly enriched with the positive regulation of autophagy and the activation of the immune system. The results of the Kyoto Encyclopedia of Genes and Genomes enrichment were mostly related to autophagy, immunity, and melanin metabolism.ConclusionThe positive regulation of autophagy may slow the transition from low-risk patients to high-risk patients in melanoma. Furthermore, compared with clinical information, the autophagy-related lncRNA risk model may better predict the prognosis of patients with melanoma and provide new treatment ideas.

Dataset Information

Comparison of Stage 4 and Stage 4s Neuroblastoma Identifies Autophagy-Related Gene and LncRNA Signatures Associated With Prognosis.

Publications

Comparison of Stage 4 and Stage 4s Neuroblastoma Identifies Autophagy-Related Gene and LncRNA Signatures Associated With Prognosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets