Dataset Information

Long non-coding RNA NEAT1 serves as a novel biomarker for treatment response and survival profiles via microRNA-125a in multiple myeloma.

ABSTRACT: BACKGROUND:The present study aimed to explore the association of long non-coding RNA nuclear paraspeckle assembly transcript 1 (lncRNA NEAT1) with multiple myeloma (MM) risk and further investigate its correlation with clinical features, treatment response, survival profiles, and its interaction with microRNA-125a (miR-125a) in MM patients. METHODS:Totally, 114 de novo symptomatic MM patients and 30 healthy donors (as controls) were recruited. Their bone marrow samples were collected before treatment (MM patients) and at enrollment (healthy donors), respectively. Subsequently, plasma cells were isolated from bone marrow for detection of lncRNA NEAT1 and miR-125a expression via reverse transcription quantitative polymerase chain reaction. RESULTS:lncRNA NEAT1 was upregulated in MM patients compared with healthy donors and presented with excellent value in distinguishing MM patients from healthy donors. In MM patients, lncRNA NEAT1 positively associated with International Staging System (ISS) stage, beta-2 microglobulin (?2-MG), and lactate dehydrogenase (LDH), but not correlated with core cytogenetics and other clinical features. Furthermore, lncRNA NEAT1 negatively associated with complete remission (CR), overall remission rate (ORR), progression-free survival (PFS), and overall survival (OS). Moreover, lncRNA NEAT1 negatively associated with miR-125a in MM patients. MiR-125a was downregulated in MM patients compared with healthy donors, and it negatively associated with ISS stage, ?2-MG, and LDH, but positively correlated with CR, ORR, PFS, and OS in MM patients. CONCLUSION:lncRNA NEAT1 might interact with miR-125a, and serves as a novel biomarker for treatment response and survival profiles in MM, indicating its clinical value for MM management.

SUBMITTER: Yu H

PROVIDER: S-EPMC7521229 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Long non-coding RNA NEAT1 serves as a novel biomarker for treatment response and survival profiles via microRNA-125a in multiple myeloma.

Yu Haifeng H Peng Shuailing S Chen Xi X Han Shuiyun S Luo Jialin J

Journal of clinical laboratory analysis 20200701 9

<h4>Background</h4>The present study aimed to explore the association of long non-coding RNA nuclear paraspeckle assembly transcript 1 (lncRNA NEAT1) with multiple myeloma (MM) risk and further investigate its correlation with clinical features, treatment response, survival profiles, and its interaction with microRNA-125a (miR-125a) in MM patients.<h4>Methods</h4>Totally, 114 de novo symptomatic MM patients and 30 healthy donors (as controls) were recruited. Their bone marrow samples were collec ...[more]

PMID: 32608537

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Project description:BackgroundMicroRNAs are small RNA species that regulate gene expression post-transcriptionally and are aberrantly expressed in many cancers including hematological malignancies. However, the role of microRNAs in the pathogenesis of multiple myeloma (MM) is only poorly understood. We therefore used microarray analysis to elucidate the complete miRNome (miRBase version 13.0) of purified tumor (CD138+) cells from 33 patients with MM, 5 patients with monoclonal gammopathy of undetermined significance (MGUS) and 9 controls.ResultsUnsupervised cluster analysis revealed that MM and MGUS samples have a distinct microRNA expression profile from control CD138+ cells. The majority of microRNAs aberrantly expressed in MM (109/129) were up-regulated. A comparison of these microRNAs with those aberrantly expressed in other B-cell and T-cell malignancies revealed a surprising degree of similarity (~40%) suggesting the existence of a common lymphoma microRNA signature. We identified 39 microRNAs associated with the pre-malignant condition MGUS. Twenty-three (59%) of these were also aberrantly expressed in MM suggesting common microRNA expression events in MM progression. MM is characterized by multiple chromosomal abnormalities of varying prognostic significance. We identified specific microRNA signatures associated with the most common IgH translocations (t(4;14) and t(11;14)) and del(13q). Expression levels of these microRNAs were distinct between the genetic subtypes (by cluster analysis) and correctly predicted these abnormalities in > 85% of cases using the support vector machine algorithm. Additionally, we identified microRNAs associated with light chain only myeloma, as well as IgG and IgA-type MM. Finally, we identified 32 microRNAs associated with event-free survival (EFS) in MM, ten of which were significant by univariate (logrank) survival analysis.ConclusionsIn summary, this work has identified aberrantly expressed microRNAs associated with the diagnosis, pathogenesis and prognosis of MM, data which will prove an invaluable resource for understanding the role of microRNAs in this devastating disease.

Project description:Background and objectiveLiver cancer is a malignancy with a poor prognosis. G protein signaling modulator 2 is mainly related to cell division and cell cycle regulation. In this review, the relationship between G protein signaling modulator 2 and clinical characteristics of patients with liver cancer has been explored, especially with respect to its prognostic value.MethodsG protein signaling modulator 2 messenger RNA expression and clinicopathological characteristics of patients with liver cancer were obtained from The Cancer Genome Atlas. The expression level of G protein signaling modulator 2 RNA-Seq was validated by using Gene Expression Omnibus. Chi-square test was performed to evaluate the relationship between G protein signaling modulator 2 expression and clinical characteristics. The threshold value of G protein signaling modulator 2 in the diagnosis of liver cancer was evaluated by a receiver-operating characteristic curve. Cox regression analysis and Kaplan-Meier curves were performed to evaluate the relationship between G protein signaling modulator 2 and liver cancer prognosis, which included overall and residual-free survival, and explored the prognostic value of G protein signaling modulator 2. Liver cancer survival analyses were validated by using the data of G protein signaling modulator 2 RNA-Seq from the International Cancer Genome Consortium.ResultsThe expression level of G protein signaling modulator 2 messenger RNA was remarkably higher in liver cancer than that in healthy tissues (P < 2.2 × e-16), which was also validated by data from the GSE14520 database. In addition, high G protein signaling modulator 2 expression significantly correlated with histological grade (P = .020), vital status (P < .001), clinical (P = .001), and T stage (P = .001). The receiver-operating characteristic curves showed G protein signaling modulator 2 to be an advantageous diagnostic molecule for liver cancer (area under curve = 0.893). Furthermore, the results of Cox analysis and Kaplan-Meier curves suggested that the upregulation of G protein signaling modulator 2 expression is linked to poor prognosis and G protein signaling modulator 2 messenger RNA could be an independent predictor for liver cancer, which was validated by data from the International Cancer Genome Consortium database.ConclusionsG protein signaling modulator 2 messenger RNA was overexpressed in liver cancer, and G protein signaling modulator 2 is an independent prognostic factor. G protein signaling modulator 2 is expected to be a treatment target for cancer.

Dataset Information

Long non-coding RNA NEAT1 serves as a novel biomarker for treatment response and survival profiles via microRNA-125a in multiple myeloma.

Publications

Long non-coding RNA NEAT1 serves as a novel biomarker for treatment response and survival profiles via microRNA-125a in multiple myeloma.

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