Dataset Information

Identification of New Potential LncRNA Biomarkers in Hirschsprung Disease.

ABSTRACT: Hirschsprung disease (HSCR) is a neurocristopathy defined by intestinal aganglionosis due to alterations during the development of the Enteric Nervous System (ENS). A wide spectrum of molecules involved in different signaling pathways and mechanisms have been described in HSCR onset. Among them, epigenetic mechanisms are gaining increasing relevance. In an effort to better understand the epigenetic basis of HSCR, we have performed an analysis for the identification of long non-coding RNAs (lncRNAs) by qRT-PCR in enteric precursor cells (EPCs) from controls and HSCR patients. We aimed to test the presence of a set lncRNAs among 84 lncRNAs in human EPCs, which were previously related with crucial cellular processes for ENS development, as well as to identify the possible differences between HSCR patients and controls. As a result, we have determined a set of lncRNAs with positive expression in human EPCs that were screened for mutations using the exome data from our cohort of HSCR patients to identify possible variants related to this pathology. Interestingly, we identified three lncRNAs with different levels of their transcripts (SOCS2-AS, MEG3 and NEAT1) between HSCR patients and controls. We propose such lncRNAs as possible regulatory elements implicated in the onset of HSCR as well as potential biomarkers of this pathology.

SUBMITTER: Torroglosa A

PROVIDER: S-EPMC7432910 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Identification of New Potential LncRNA Biomarkers in Hirschsprung Disease.

Torroglosa Ana A Villalba-Benito Leticia L Fernández Raquel María RM Luzón-Toro Berta B Moya-Jiménez María José MJ Antiñolo Guillermo G Borrego Salud S

International journal of molecular sciences 20200802 15

Hirschsprung disease (HSCR) is a neurocristopathy defined by intestinal aganglionosis due to alterations during the development of the Enteric Nervous System (ENS). A wide spectrum of molecules involved in different signaling pathways and mechanisms have been described in HSCR onset. Among them, epigenetic mechanisms are gaining increasing relevance. In an effort to better understand the epigenetic basis of HSCR, we have performed an analysis for the identification of long non-coding RNAs (lncRN ...[more]

PMID: 32748823

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Project description:BackgroundDysregulated long non-coding RNAs (lncRNAs) have been found to have oncogenic and/or tumor suppressive roles in the development and progression of cancer, implying their potentials as novel independent biomarkers for cancer diagnosis and prognosis. However, the prognostic significance of expression profile-based lncRNA signature for outcome prediction in patients with multiple myeloma (MM) has not yet been investigated.MethodsLncRNA expression profiles of a large cohort of patients with MM were obtained and analyzed by repurposing the publically available microarray data. An lncRNA-focus risk score model was developed from the training dataset, and then validated in the testing and another two independent external datasets. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic performance for survival prediction. The biological function of prognostic lncRNAs was predicted using bioinformatics analysis.ResultsFour lncRNAs were identified to be significantly associated with overall survival (OS) of patients with MM in the training dataset, and were combined to develop a four-lncRNA prognostic signature to stratify patients into high-risk and low-risk groups. Patients of training dataset in the high-risk group exhibited shorter OS than those in the low-risk group (HR = 2.718, 95 % CI = 1.937-3.815, p <0.001). The similar prognostic values of four-lncRNA signature were observed in the testing dataset, entire GSE24080 dataset and another two independent external datasets. Multivariate Cox regression and stratified analysis showed that the prognostic power of four-lncRNA signature was independent of clinical features, including serum beta 2-microglobulin (Sβ2M), serum albumin (ALB) and lactate dehydrogenase (LDH). ROC analysis also demonstrated the better performance for predicting 3-year OS. Functional enrichment analysis suggested that these four lncRNAs may be involved in known genetic and epigenetic events linked to MM.ConclusionsOur results demonstrated potential application of lncRNAs as novel independent biomarkers for diagnosis and prognosis in MM. These lncRNA biomarkers may contribute to the understanding of underlying molecular basis of MM.

Dataset Information

Identification of New Potential LncRNA Biomarkers in Hirschsprung Disease.

Publications

Identification of New Potential LncRNA Biomarkers in Hirschsprung Disease.

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