Novel Long Non-coding RNA and LASSO Prediction Model to Better Identify Pulmonary Tuberculosis: A Case-Control Study in China

IntroductionThe insufficient understanding and misdiagnosis of clinically diagnosed pulmonary tuberculosis (PTB) without an aetiological evidence is a major problem in the diagnosis of tuberculosis (TB). This study aims to confirm the value of Long non-coding RNA (lncRNA) n344917 in the diagnosis of PTB and construct a rapid, accurate, and universal prediction model.MethodsA total of 536 patients were prospectively and consecutively recruited, including clinically diagnosed PTB, PTB with an aetiological evidence and non-TB disease controls, who were admitted to West China hospital from Dec 2014 to Dec 2017. The expression levels of lncRNA n344917 of all patients were analyzed using reverse transcriptase quantitative real-time PCR. Then, the laboratory findings, electronic health record (EHR) information and expression levels of n344917 were used to construct a prediction model through the Least Absolute Shrinkage and Selection Operator algorithm and multivariate logistic regression.ResultsThe factors of n344917, age, CT calcification, cough, TBIGRA, low-grade fever and weight loss were included in the prediction model. It had good discrimination (area under the curve = 0.88, cutoff = 0.657, sensitivity = 88.98%, specificity = 86.43%, positive predictive value = 85.61%, and negative predictive value = 89.63%), consistency and clinical availability. It also showed a good replicability in the validation cohort. Finally, it was encapsulated as an open-source and free web-based application for clinical use and is available online at https://ziruinptb.shinyapps.io/shiny/.ConclusionCombining the novel potential molecular biomarker n344917, laboratory and EHR variables, this web-based prediction model could serve as a user-friendly, accurate platform to improve the clinical diagnosis of PTB.

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IIMLP: integrated information-entropy-based method for LncRNA prediction

BMC Bioinformatics ◽

10.1186/s12859-020-03884-w ◽

2021 ◽

Vol 22 (S3) ◽

Author(s):

Junyi Li ◽

Huinian Li ◽

Xiao Ye ◽

Li Zhang ◽

Qingzhe Xu ◽

...

Keyword(s):

Machine Learning ◽

Dna Sequences ◽

Information Entropy ◽

Area Under The Curve ◽

Prediction Method ◽

Machine Learning Algorithms ◽

Reading Frame ◽

Non Coding Rna ◽

The One ◽

Long Non Coding Rna

Abstract Background The prediction of long non-coding RNA (lncRNA) has attracted great attention from researchers, as more and more evidence indicate that various complex human diseases are closely related to lncRNAs. In the era of bio-med big data, in addition to the prediction of lncRNAs by biological experimental methods, many computational methods based on machine learning have been proposed to make better use of the sequence resources of lncRNAs. Results We developed the lncRNA prediction method by integrating information-entropy-based features and machine learning algorithms. We calculate generalized topological entropy and generate 6 novel features for lncRNA sequences. By employing these 6 features and other features such as open reading frame, we apply supporting vector machine, XGBoost and random forest algorithms to distinguish human lncRNAs. We compare our method with the one which has more K-mer features and results show that our method has higher area under the curve up to 99.7905%. Conclusions We develop an accurate and efficient method which has novel information entropy features to analyze and classify lncRNAs. Our method is also extendable for research on the other functional elements in DNA sequences.

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Long Non-coding RNA GAS5 Worsens Coronary Atherosclerosis Through MicroRNA-194-3p/TXNIP Axis

Molecular Neurobiology ◽

10.1007/s12035-021-02332-x ◽

2021 ◽

Author(s):

Yanbing Li ◽

Yu Geng ◽

Boda Zhou ◽

Xuejiao Wu ◽

Ou Zhang ◽

...

Keyword(s):

Endothelial Cells ◽

Coronary Atherosclerosis ◽

Growth Arrest ◽

Interacting Protein ◽

Expression Levels ◽

Thioredoxin Interacting Protein ◽

Non Coding Rna ◽

Proliferation And Apoptosis ◽

Regulatory Effects ◽

Long Non Coding Rna

AbstractIt is formerly conducted that long non-coding RNA growth arrest-specific 5 (GAS5) is involved in the process of coronary atherosclerosis (AS). The regulatory effects of GAS5 on the microRNA (miR)-194-3p/thioredoxin-interacting protein (TXNIP) axis in AS have been insufficiently explored yet. Thereafter, this work is started from GAS5/miR-194-3p/TXNIP axis in AS. AS rats were modeled to obtain their coronary vascular tissues and endothelial cells (ECs), in which GAS5, miR-194-3p, and TXNIP expression were tested. ECs were identified by immunohistochemistry. The mechanism among GAS5, miR-194-3p, and TXNIP was determined. ECs were transfected with inhibited GAS5 or overexpressed miR-194-3p to decipher their functions in proliferation and apoptosis of ECs in AS. Raised GAS5 and TXNIP and degraded miR-194-3p expression levels exhibited in AS. GAS5 bound to miR-194-3p while miR-194-3p targeted TXNIP. Depleting GAS5 or restoring miR-194-3p enhanced proliferation and depressed apoptosis of ECs in AS. This work clearly manifests that inhibited GAS5 facilitates the growth of ECs through miR-194-3p-targeted TXNIP in AS, consolidating the basal reference to the curing for AS.

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Endogenous intronic antisense long non-coding RNA, MGAT3-AS1, and kidney transplantation

Scientific Reports ◽

10.1038/s41598-019-51409-0 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 1

Author(s):

Subagini Nagarajah ◽

Shengqiang Xia ◽

Marianne Rasmussen ◽

Martin Tepel

Keyword(s):

Kidney Transplantation ◽

Predictive Value ◽

Graft Function ◽

Deceased Donor ◽

Delayed Graft Function ◽

Transplant Recipients ◽

Donor Kidney ◽

Non Coding Rna ◽

Deceased Donor Kidney ◽

Long Non Coding Rna

Abstract β-1,4-mannosylglycoprotein 4-β-N-acetylglucosaminyltransferase (MGAT3) is a key molecule for the innate immune system. We tested the hypothesis that intronic antisense long non-coding RNA, MGAT3-AS1, can predict delayed allograft function after kidney transplantation. We prospectively assessed kidney function and MGAT3-AS1 in 129 incident deceased donor kidney transplant recipients before and after transplantation. MGAT3-AS1 levels were measured in mononuclear cells using qRT-PCR. Delayed graft function was defined by at least one dialysis session within 7 days of transplantation. Delayed graft function occurred in 22 out of 129 transplant recipients (17%). Median MGAT3-AS1 after transplantation was significantly lower in patients with delayed graft function compared to patients with immediate graft function (6.5 × 10−6, IQR 3.0 × 10−6 to 8.4 × 10−6; vs. 8.3 × 10−6, IQR 5.0 × 10−6 to 12.8 × 10−6; p < 0.05). The median preoperative MGAT3-AS1 was significantly lower in kidney recipients with delayed graft function (5.1 × 10−6, IQR, 2.4 × 10−6 to 6.8 × 10−6) compared to recipients with immediate graft function (8.9 × 10−6, IQR, 6.8 × 10−6 to 13.4 × 10−6; p < 0.05). Receiver-operator characteristics showed that preoperative MGAT3-AS1 predicted delayed graft function (area under curve, 0.83; 95% CI, 0.65 to 1.00; p < 0.01). We observed a positive predictive value of 0.57, and a negative predictive value of 0.95. Long non-coding RNA, MGAT3-AS1, indicates short-term outcome in patients with deceased donor kidney transplantation.

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Long non-coding RNA XIST predicts worse prognosis in digestive system tumors: a systemic review and meta-analysis

Bioscience Reports ◽

10.1042/bsr20180169 ◽

2018 ◽

Vol 38 (3) ◽

Cited By ~ 7

Author(s):

Xuefang Liu ◽

Xinliang Ming ◽

Wei Jing ◽

Ping Luo ◽

Nandi Li ◽

...

Keyword(s):

Overall Survival ◽

Cancer Patients ◽

Digestive System ◽

Meta Analysis ◽

Predictive Biomarker ◽

Systemic Review ◽

Cochrane Library ◽

Expression Levels ◽

Non Coding Rna ◽

Long Non Coding Rna

Increasing studies are indicating that long non-coding RNA (lncRNA) X-inactive specific transcript (XIST) is associated with the prognosis of cancer patients. However, the results have been disputed. Therefore, we aimed to further explore the prognostic value and clinical significance of XIST in various types of cancers. Then, we focussed our research on the comparison of the predictive value of XIST between digestive system tumors and non-digestive system tumors. We performed a systematic search by looking up PubMed, Embase, Cochrane Library, Web of Science, and Medline (up to 3 January 2018). Fifteen studies which matched our inclusion criteria with a total of 920 patients for overall survival and 867 patients for clinicopathological characteristics were included in this meta-analysis. Pooled hazard ratios (HR) and odds ratios (ORs) with their corresponding 95% confidence intervals (95% CIs) were calculated to summarize the effects. Our results suggested that high expression levels of XIST were associated with unfavorable overall survival in cancer patients (pooled HR = 1.81, 95% CI: 1.45–2.26). Additionally, we found that XIST was more valuable in digestive system tumors (pooled HR = 2.24, 95% CI: 1.73–2.92) than in non-digestive system tumors (pooled HR = 1.22, 95% CI: 0.60–2.45). Furthermore, elevated expression levels of XIST were connected with distant metastasis and tumor stage. XIST was correlated with poor prognosis, which suggested that XIST might serve as a novel predictive biomarker for cancer patients, especially for patients of digestive system tumors.

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The Role of Long Non-Coding RNA NNT-AS1 in Neoplastic Disease

Cancers ◽

10.3390/cancers12113086 ◽

2020 ◽

Vol 12 (11) ◽

pp. 3086

Author(s):

Cong Zhou ◽

Shiwei Duan

Keyword(s):

Cancer Progression ◽

Cisplatin Resistance ◽

Malignant Tumors ◽

Human Cancer ◽

Neoplastic Disease ◽

Expression Levels ◽

Cancer Breast ◽

Non Coding Rna ◽

Non Coding Rnas ◽

Long Non Coding Rna

Studies have shown that non-coding RNAs (ncRNAs), especially long non-coding RNAs (lncRNAs), play an important regulatory role in the occurrence and development of human cancer. Nicotinamide nucleotide transhydrogenase-antisense 1 (NNT-AS1) is a newly-discovered cytoplasmic lncRNA. Many studies have shown that it has abnormally-high expression levels in malignant tumors, but there are also a few studies that have reported low expression levels of NNT-AS1 in gastric cancer, breast cancer, and ovarian cancer. At present, the regulatory mechanism of NNT-AS1 as a miRNA sponge, which may be an important reason affecting tumor cell proliferation, invasion, metastasis, and apoptosis is being studied in-depth. In addition, NNT-AS1 has been found to be related to cisplatin resistance. In this review, we summarize the abnormal expression of NNT-AS1 in a variety of neoplastic diseases and its diagnostic and prognostic value, and we explain the mechanism by which NNT-AS1 regulates cancer progression by competing with miRNAs. In addition, we also reveal the correlation between NNT-AS1 and cisplatin resistance and the potential clinical applications of NNT-AS1.

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Long Non-Coding RNA Landscape in Prostate Cancer Molecular Subtypes: A Feature Selection Approach

International Journal of Molecular Sciences ◽

10.3390/ijms22042227 ◽

2021 ◽

Vol 22 (4) ◽

pp. 2227

Author(s):

Simona De Summa ◽

Antonio Palazzo ◽

Mariapia Caputo ◽

Rosa Maria Iacobazzi ◽

Brunella Pilato ◽

...

Keyword(s):

Prostate Cancer ◽

Feature Selection ◽

Molecular Subtypes ◽

Genomic Alteration ◽

Low Grade ◽

Non Coding Rna ◽

Selection Approach ◽

Tcga Dataset ◽

Feature Selection Approach ◽

Long Non Coding Rna

Prostate cancer is one of the most common malignancies in men. It is characterized by a high molecular genomic heterogeneity and, thus, molecular subtypes, that, to date, have not been used in clinical practice. In the present paper, we aimed to better stratify prostate cancer patients through the selection of robust long non-coding RNAs. To fulfill the purpose of the study, a bioinformatic approach focused on feature selection applied to a TCGA dataset was used. In such a way, LINC00668 and long non-coding(lnc)-SAYSD1-1, able to discriminate ERG/not-ERG subtypes, were demonstrated to be positive prognostic biomarkers in ERG-positive patients. Furthermore, we performed a comparison between mutated prostate cancer, identified as “classified”, and a group of patients with no peculiar genomic alteration, named “not-classified”. Moreover, LINC00920 lncRNA overexpression has been linked to a better outcome of the hormone regimen. Through the feature selection approach, it was found that the overexpression of lnc-ZMAT3-3 is related to low-grade patients, and three lncRNAs: lnc-SNX10-87, lnc-AP1S2-2, and ADPGK-AS1 showed, through a co-expression analysis, significant correlation values with potentially druggable pathways. In conclusion, the data mining of publicly available data and robust bioinformatic analyses are able to explore the unknown biology of malignancies.

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Long non-coding RNA PVT1 indicates a poor prognosis of glioma and promotes cell proliferation and invasion via target EZH2

Bioscience Reports ◽

10.1042/bsr20170871 ◽

2017 ◽

Vol 37 (6) ◽

Cited By ~ 18

Author(s):

Anqiang Yang ◽

Handong Wang ◽

Xiaobing Yang

Keyword(s):

Cell Lines ◽

Molecular Mechanisms ◽

Malignant Tumors ◽

Glioma Cells ◽

Migration And Invasion ◽

Human Glioma ◽

Expression Levels ◽

Non Coding Rna ◽

Long Non Coding Rna ◽

Proliferation And Invasion

Human glioma is one of the malignant tumors of the central nervous system (CNS). Its prognosis is poor, which is due to its genetic heterogeneity and our poor understanding of its underlying molecular mechanisms. The present study aimed to assess the relationship between plasmacytoma variant translocation 1 (PVT1) and enhancer of zeste homolog 2 (EZH2), and their effects on the proliferation and invasion of glioma cells. The expression levels of PVT1 and EZH2 in human glioma tissues and cell lines were measured using quantitative RT-PCR (qRT-PCR). Then, after siRNA-PVT1 and entire PVT1 sequence vector transfection, we determined the regulation roles of PVT1 in the proliferation, apoptosis, migration, and invasion of glioma cells. We found that the expression levels of both PVT1 and EZH2 were up-regulated in human glioma tissues and cell lines, and positively correlated with glioma malignancy. And, silencing of PVT1 expression resulted in decreased proliferation, increased apoptosis, and decreased migration and invasion. In addition, exogenous PVT1 led to increased EZH2 expression and increased proliferation and induced proliferation and invasion. These data inferred that long non-coding RNA PVT1 could be served as an indicator of glioma prognosis, and PVT1–EZH2 regulatory pathway may be a novel therapeutic target for treating glioma.

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Long Non-Coding RNA-MALAT1 Mediates Retinal Ganglion Cell Apoptosis Through the PI3K/Akt Signaling Pathway in Rats with Glaucoma

Cellular Physiology and Biochemistry ◽

10.1159/000484231 ◽

2017 ◽

Vol 43 (5) ◽

pp. 2117-2132 ◽

Cited By ~ 28

Author(s):

Hai-Bo Li ◽

Qi-Sheng You ◽

Li-Xin Xu ◽

Li-Xin Sun ◽

Aman Shah Abdul Majid ◽

...

Keyword(s):

Ganglion Cell ◽

Signaling Pathway ◽

Akt Signaling ◽

The Other ◽

Retinal Ganglion ◽

Akt Signaling Pathway ◽

Expression Levels ◽

Non Coding Rna ◽

Lncrna Malat1 ◽

Long Non Coding Rna

Background/Aims: The aim of the present study is to investigate the effect of long non-coding RNA-MALAT1 (LncRNA-MALAT1) on retinal ganglion cell (RGC) apoptosis mediated by the PI3K/Akt signaling pathway in rats with glaucoma. Methods: RGCs were isolated and cultured, and monoclonal antibodies (anti-rat Thy-1, Brn3a and RBPMS) were examined by immunocytochemistry. An overexpression vector MALAT1-RNA activation (RNAa), gene knockout vector MALAT1-RNA interference (RNAi), and control vector MALAT1-negative control (NC) were constructed. A chronic high intraocular pressure (IOP) rat model of glaucoma was established by episcleral vein cauterization. The RGCs were divided into the RGC control, RGC pressure, RGC pressure + MALAT1-NC, RGC pressure + MALAT1-RNAi and RGC pressure + MALAT1-RNAa groups. Sixty Sprague-Dawley (SD) rats were randomly divided into the normal, high IOP, high IOP + MALAT1-NC, high IOP + MALAT1-RNAa and high IOP + MALAT1-RNAi groups. qRT-PCR and western blotting were used to detect the expression levels of LncRNA-MALAT1 and PI3K/Akt. Terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) and flow cytometry were used to detect RGC apoptosis. Results: Immunocytochemistry revealed that the cultured RGCs reached 90% purity. Compared with the RGC pressure + MALAT1-NC group, the RGC pressure + MALAT1-RNAa group exhibited elevated expression levels of MALAT1, lower total protein levels of PI3K and Akt and decreased RGC apoptosis, while these expression levels were reversed in the RGC pressure + MALAT1-RNAi group. RGC numbers and PI3K/Akt expression levels in the high IOP model groups were lower than those in the normal group. In the high IOP + MALAT1-RNAa group, the mRNA and protein expression levels of PI3K/Akt were reduced but higher than those in the other three high IOP model groups. Additionally, RGC numbers in the high IOP + MALAT1-RNAa group were lower than those in the normal group but higher than those in the other three high IOP model groups. Conclusion: Our study provides evidence that LncRNA-MALAT1 could inhibit RGC apoptosis in glaucoma through activation of the PI3K/Akt signaling pathway.

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Comparative analysis of RNA enrichment methods for preparation of Cryptococcus neoformans RNA sequencing libraries

10.1101/2021.03.01.433483 ◽

2021 ◽

Author(s):

Calla L. Telzrow ◽

Paul J. Zwack ◽

Shannon Esher Righi ◽

Fred S. Dietrich ◽

Cliburn Chan ◽

...

Keyword(s):

Cryptococcus Neoformans ◽

Rna Sequencing ◽

Rnase H ◽

Rrna Genes ◽

Rna Seq ◽

Protein Coding ◽

Expression Levels ◽

Non Coding Rna ◽

Long Non Coding Rna ◽

Enrichment Methods

ABSTRACTRibosomal RNA (rRNA) is the major RNA constituent of cells, therefore most RNA sequencing (RNA-Seq) experiments involve removal of rRNA. This process, called RNA enrichment, is done primarily to reduce cost: without rRNA removal, deeper sequencing would need to be performed to balance the sequencing reads wasted on rRNA. The ideal RNA enrichment method would remove all rRNA without affecting other RNA in the sample. We have tested the performance of three RNA enrichment methods on RNA isolated from Cryptococcus neoformans, a fungal pathogen of humans. We show that the RNase H depletion method unambiguously outperforms the commonly used Poly(A) isolation method: the RNase H method more efficiently depletes rRNA while more accurately recapitulating the expression levels of other RNA observed in an unenriched “gold standard”. The RNase H depletion method is also superior to the Ribo-Zero depletion method as measured by rRNA depletion efficiency and recapitulation of protein-coding gene expression levels, while the Ribo-Zero depletion method performs moderately better in preserving non-coding RNA (ncRNA). Finally, we have leveraged this dataset to identify novel long non-coding RNA (lncRNA) genes and to accurately map the C. neoformans mitochondrial rRNA genes.ARTICLE SUMMARYWe compare the efficacy of three different RNA enrichment methods for RNA-Seq in Cryptococcus neoformans: RNase H depletion, Ribo-Zero depletion, and Poly(A) isolation. We show that the RNase H depletion method, which is evaluated in C. neoformans samples for the first time here, is highly efficient and specific in removing rRNA. Additionally, using data generated through these analyses, we identify novel long non-coding RNA genes in C. neoformans. We conclude that RNase H depletion is an effective and reliable method for preparation of C. neoformans RNA-Seq libraries.

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