Upregulation of lncRNA NR_046683 Serves as a Prognostic Biomarker and Potential Drug Target for Multiple Myeloma

Dong, Hang; Jiang, Siyi; Fu, Yunfeng; Luo, Yanwei; Gui, Rong; Liu, Jing

doi:10.3389/fphar.2019.00045

Cited by 18 publications

(18 citation statements)

References 32 publications

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“…The aberrant expression of urothelial cancer associated 1 lncRNA affords it the ability to promote proliferation and inhibits apoptosis by regulating miR-1271-5p and hepatocyte growth factor in MM cells ( Yang and Chen, 2019 ). Abnormally expressed lncRNA NR_046683 in patients of different MM subtypes and stages indicated that it could be used as a new indicator for potential drug target and prognosis ( Dong et al, 2019 ). Although several lncRNA prognostic models have been identified in uterine corpus endometrial carcinoma ( Ouyang et al, 2019 ), hepatocellular carcinoma ( Sun et al, 2019b ), cervical cancer ( Wu et al, 2019 ), and lung adenocarcinoma ( Zhou et al, 2019 ), the clinical implication of most lncRNAs in MM remains unclear.…”

Section: Introductionmentioning

confidence: 99%

Integrated Analysis of a Risk Score System Predicting Prognosis and a ceRNA Network for Differentially Expressed lncRNAs in Multiple Myeloma

et al. 2020

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Long non-coding RNAs (lncRNAs) are non-protein-coding RNAs longer than 200 nucleotides. Accumulating evidence demonstrates that lncRNA is a potential biomarker for cancer diagnosis and prognosis. However, there are no prognostic biomarkers and lncRNA models for multiple myeloma (MM). Hence, it is necessary to screen novel lncRNA that can potentially participate in the initiation and progression of MM and consequently construct a risk score system for the disease. Raw microarray datasets were obtained from the Gene Expression Omnibus website. Weighted gene co-expression network analysis and principal component analysis identified 12 lncRNAs of interest. Then, univariate, least absolute shrinkage and selection operator Cox regression and multivariate Cox hazard regression analysis identified two lncRNAs (LINC00996 and LINC00525) that were formulated to construct a risk score system to predict survival. Receiver operating characteristic analysis certificated the superior performance in predicting 3-year overall survival (area under the curve = 0.829). The similar prognostic values of the two-lncRNA signature were also observed in the tested The Cancer Genome Atlas dataset. Furthermore, two other lncRNAs (LINC00324 and LINC01128) were differentially expressed between CD138+ plasma cells from normal donors and MM patients and were verified to be associated with cancer stage in the Gene Expression Omnibus dataset. A lncRNA-mediated competing endogenous RNA network, including 2 lncRNAs, 12 mitochondrial RNAs, and 103 target messenger RNAs, was constructed. In conclusion, we developed a two-lncRNA expression signature to predict the prognosis of MM and constructed a key lncRNA-based competing endogenous RNA network in MM. These lncRNAs were associated with survival and are probably involved in the occurrence and progression of MM.

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Section: Introductionmentioning

confidence: 99%

Integrated Analysis of a Risk Score System Predicting Prognosis and a ceRNA Network for Differentially Expressed lncRNAs in Multiple Myeloma

et al. 2020

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“…21 Pathologically, malignant MM usually evolves from asymptomatic monoclonal gammopathy of underdetermined significance along with bone marrow microenvironment changes, genetic and cytogenetic abnormalities, which resulted in end-organ damage, renal insufficiency, anemia, elevated bone marrow angiogenesis, and osteolytic bone lesions. 3,22 Due to the genetic clonal heterogeneity of MM, treatment of patients remains as one of the main challenges. 6 Therefore, it is urgent to explore the biomarkers for disease development and progression.…”

Section: Discussionmentioning

confidence: 99%

“…Multiple myeloma (MM), the second most common hematological malignancy, is characterized by abnormal proliferation of monoclonal plasma cells in bone marrow and overproduction of monoclonal immunoglobulin in serum and/or urine with an estimated 159 985 new cases and 106 105 deaths worldwide in 2018 1,2 . The typical symptoms of MM are bone pain, hypercalcemia, anemia, and renal insufficiency 3 . Over the last two decades, the introduction of immunomodulatory agents, proteasome inhibitors, monoclonal antibodies, and histone deacetylase inhibitor has improved the depth and duration of treatment responses and prolonged survival in patients with MM 4,5 .…”

Section: Introductionmentioning

confidence: 99%

“…1,2 The typical symptoms of MM are bone pain, hypercalcemia, anemia, and renal insufficiency. 3 Over the last two decades, the introduction of immunomodulatory agents, proteasome inhibitors, monoclonal antibodies, and histone deacetylase inhibitor has improved the depth and duration of treatment responses and prolonged survival in patients with MM. 4,5 Unfortunately, a considerable number of patients eventually suffer from disease recurrence and/or respond poorly to these treatments.…”

Section: Introductionmentioning

confidence: 99%

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Long non‐coding RNA T‐cell factor 7 in multiple myeloma: A potential biomarker for deteriorated clinical features and poor prognosis

Zhang¹,

Chu²,

Fan³

et al. 2020

Clinical Laboratory Analysis

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Background This study aimed to investigate the correlation of long non‐coding RNA T‐cell factor 7 (lnc‐TCF7) with clinical features and prognosis in patients with multiple myeloma (MM). Methods Totally, 216 newly diagnosed symptomatic MM patients and 60 healthy controls (HCs) were enrolled. Bone marrow samples were collected from patients before treatment and from HCs on donation to detect lnc‐TCF7 expression in plasma cells by reverse transcription quantitative polymerase chain reaction. Besides, clinical response, progression‐free survival (PFS), and overall survival (OS) of patients were assessed. Results Lnc‐TCF7 expression was increased in patients with MM compared with HCs. Lnc‐TCF7 expression was highest in international staging system (ISS) stage III patients, followed by ISS stage II patients, and then ISS stage I patients, while lnc‐TCF7 expression was similar in patients with different immunoglobulin subtypes and Durie‐Salmon stages. Regarding chromosomal abnormalities, lnc‐TCF7 expression positively correlated with t(4; 14) and Del(17p), whereas no correlation of lnc‐TCF7 expression with t(14; 16), 1q21 amplification, Del(13q), or hyperdiploid was observed in patients with MM. Furthermore, lnc‐TCF7 expression positively correlated with serum creatinine, beta‐2‐microglobulin, and lactate dehydrogenase in patients. Besides, lnc‐TCF7 was negatively associated with complete response but not overall response rate in patients. Additionally, patients with lnc‐TCF7 high expression exhibited shorter PFS and OS compared to patients with lnc‐TCF7 low expression. Conclusion Lnc‐TCF7 might have clinical value in aiding disease management and prognosis prediction of MM.

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“…The expression levels of several lncrnas have been reported in multiple myeloma (MM); their clinical significance, biological functions and potential molecular mechanisms in the disease have also been investigated (14)(15)(16). MM is the second most frequent hematological malignancy, and accounts for ~10% of all such malignancies (17)(18)(19)(20)(21)(22).…”

Section: Introductionmentioning

confidence: 99%

Construction of a prognosis‑associated long noncoding RNA‑mRNA network for multiple myeloma based on microarray and bioinformatics analysis

Zhu

Wang

Ye³

et al. 2020

Mol Med Report

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at present, t he associat ion bet we en prognosis-associated long noncoding rnas (lncrnas) and mrnas is yet to be reported in multiple myeloma (MM). The aim of the present study was to construct prognostic models with lncrnas and mrnas, and to map the interactions between these lncrnas and mrnas in MM. lncrna and mrna data from 559 patients with MM were acquired from the Genome expression omnibus (dataset GSe24080), and their prognostic values were calculated using the survival package in r. Multivariate Cox analysis was used on the top 20 most significant prognosis-associated mrnas and lncrnas to develop prognostic signatures. The performances of these prognostic signatures were tested using the survivalroc package in r, which allows for time-dependent receiver operator characteristic (roc) curve estimation. Weighted correlation network analysis (WGcna) was conducted to investigate the associations between lncrnas and mrnas, and a lncrna-mrna network was constructed using cytoscape software. univariate cox regression analysis identified 39 lncRNAs and 1,445 mRNAs that were significantly associated with event-free survival of MM patients. The top 20 most significant survival-associated lncrnas and mrnas were selected as candidates for analyzing independent MM prognostic factors. Both signatures could be used to separate patients into two groups with distinct outcomes. The areas under the ROC curves were 0.739 for the lncRNA signature and 0.732 for the mRNA signature. In the lncRNA-mRNA network, a total of 143 mRNAs were positively or negatively associated with 23 prognosis-associated lncRNAs. NCRNA00201, LOC115110 and RP5-968J1.1 were the most dominant drivers. The present study constructed a model that predicted prognosis in MM and formed a network with the corresponding prognosis-associated mrnas, providing a novel perspective for the clinical diagnosis and treatment of MM, and suggesting novel directions for interpreting the mechanisms underlying the development of MM.

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Upregulation of lncRNA NR_046683 Serves as a Prognostic Biomarker and Potential Drug Target for Multiple Myeloma

Cited by 18 publications

References 32 publications

Integrated Analysis of a Risk Score System Predicting Prognosis and a ceRNA Network for Differentially Expressed lncRNAs in Multiple Myeloma

Integrated Analysis of a Risk Score System Predicting Prognosis and a ceRNA Network for Differentially Expressed lncRNAs in Multiple Myeloma

Long non‐coding RNA T‐cell factor 7 in multiple myeloma: A potential biomarker for deteriorated clinical features and poor prognosis

Construction of a prognosis‑associated long noncoding RNA‑mRNA network for multiple myeloma based on microarray and bioinformatics analysis

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