The implication of long non-coding RNA expression profile in rheumatoid arthritis: Correlation with treatment response to tumor necrosis factor inhibitor.

OBJECTIVE: This study aimed to investigate the linkage of long non-coding RNA (lncRNA) expression profile with etanercept response in rheumatoid arthritis (RA) patients. METHODS: Peripheral blood mononuclear cell (PBMC) samples were collected from 80 RA patients prior to etanercept treatment. Samples from eight responders and eight non-responders at week 24 (W24) were proposed to RNA-sequencing, then 10 candidate lncRNAs were sorted and their PBMC expressions were validated by reverse transcription quantitative chain reaction (RT-qPCR) in 80 RA patients. Subsequently, clinical response by lncRNA (CRLnc) prediction model was established. RESULTS: RNA-sequencing identified 254 up-regulated and 265 down-regulated lncRNAs in W24 responders compared with non-responders, which were enriched in immune or joint related pathways such as B-cell receptor signaling, osteoclast differentiation and T-cell receptor signaling pathways, etc. By reverse transcription quantitative chain reaction (RT-qPCR) validation: Two lncRNAs were correlated with W4 response, three lncRNAs were correlated with W12 response, seven lncRNAs were correlated with W24 response. Subsequently, to construct and validate CRLnc prediction model, 80 RA patients were randomly divided into test set (n = 40) and validation set (n = 40). In the test set, lncRNA RP3-466P17.2 (OR = 9.743, P = .028), RP11-20D14.6 (OR = 10.935, P = .007), RP11-844P9.2 (OR = 0.075, P = .022), and TAS2R64P (OR = 0.044, P = .016) independently related to W24 etanercept response; then CRLnc prediction model integrating these four lncRNAs presented a good value in predicting W24 etanercept response (Area Under Curve (AUC): 0.956, 95%CI: 0.896-1.000). However, in the validation set, the CRLnc prediction model only exhibited a certain value in predicting W24 etanercept response (AUC: 0.753, 95%CI: 0.536-0.969). CONCLUSIONS: CRLnc prediction model is potentially a useful tool to instruct etanercept treatment in RA patients.

A landscape of circulating long non-coding RNA (lncRNA) expression profile and the predictive value of candidate lncRNAs for disease risk of knee osteoarthritis.

BACKGROUND: This study aimed to investigate the plasma long non-coding RNA (lncRNA) expression profile in knee osteoarthritis (KOA) patients and the value of candidate lncRNAs for predicting KOA risk. METHODS: Plasma was obtained for RNA sequencing (RNA-seq) in eight KOA patients and eight healthy controls (Ctrls). Ten candidate lncRNAs were then selected from the differentially expressed (DE) lncRNAs according to the rank of absolute value of Log2 (fold change). Afterward, RT-qPCR was used to examine 10 candidate lncRNAs expressions in plasma of 100 KOA patients and 100 Ctrls. RESULTS: In eight KOA patients and eight Ctrls, principal component analysis and heatmap plots disclosed that lncRNA and mRNA expression profile could distinguish KOA patients from Ctrls. Then Volcano plot identified 418 upregulated lncRNAs, 347 downregulated lncRNAs, 521 upregulated mRNAs, and 333 downregulated mRNAs in KOA patients compared to Ctrls. Next, enrichment analyses revealed that DE lncRNAs were mainly enriched in biological processes, molecular functions, and signaling pathways related to inflammation and bone formation. In 100 KOA patients and 100 Ctrls, eight candidate lncRNAs were dysregulated in KOA patients compared to Ctrls, including lncRNA ABCF2P2, lncRNA RP13-16H11.7, lncRNA CTC-340A15.2, lncRNA RP4-735C1.6, lncRNA RP11-293G6-B.8, lncRNA RP11-1246C19.1, lncRNA RP11-303E16.6, and lncRNA RP5-882C2.2. Receiver operating characteristic curve analysis revealed that these eight candidate lncRNAs presented with values for predicting KOA risk. Furthermore, multivariate logistic regression elucidated that six candidate lncRNAs could independently predict KOA risk. CONCLUSION: We disclosed a landscape of circulating lncRNA expression profile in KOA patients, and discovered several specific lncRNAs which could assist in KOA management.

[Effects of ozone sub-chronic exposure on lncRNA expression profiles in rat heart].

Objective: This article aims to observe the changes in long noncoding RNA (lncRNA) expression profiles in rat hearts after ozone sub-chronic exposure. To provide scientific data to explore the role and mechanism of differentially expressed lncRNA in damaged hearts caused by ozone sub-chronic exposure. Methods: Eighteen Wistar rats were randomly divided into filtered air and ozone exposure groups, with nine rats in each group. The rats in filtered air group were exposed to filtered air, while the rats in ozone exposure group were exposed to ozone at 0.5 ppm(0.980 mg/m3)for 90 days at a frequency of 6 hours per day. After ozone exposure, cardiac tissues were collected and the total RNA was extracted. The expression level of lncRNA in the hearts of two groups was detected by microarray and qRT-PCR method and the potential functions of the differentially expressed lncRNA were analyzed by bioinformatics. Results: Compared with the filtered air group, lncRNA's expression profile was significantly altered in the rat hearts of ozone exposure group. A total of 167 lncRNA were up-regulated significantly and 64 lncRNA were down-regulated significantly. GO analysis indicated that the up-regulated lncRNA might involve in the process of regulating growth and development, and the down-regulated lncRNA might participate in nutrient catabolic. KEGG results showed that the up-regulated lncRNA might be involved in regulating the PI3K-Akt signaling pathway. The down-regulated lncRNA might regulate the metabolic processes of various vitamins and main energy-supplying substances. Conclusion: Ozone sub-chronic exposure can cause changes in the expression profile of lncRNA in rat hearts, which may regulate the effects of ozone sub-chronic exposure on the heart through the metabolism of energy and nutrients.

Targeting the lncRNA DUXAP8/miR-29a/PIK3CA Network Restores Doxorubicin Chemosensitivity via PI3K-AKT-mTOR Signaling and Synergizes With Inotuzumab Ozogamicin in Chemotherapy-Resistant B-Cell Acute Lymphoblastic Leukemia.

Purpose: This study aimed to determine the expression profiles of long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA in chemotherapy-resistant B-cell acute lymphoblastic leukemia (B-ALL). Methods: LncRNA, miRNA, and mRNA profiles were assessed by RNA-seq in diagnostic bone marrow samples from 6 chemotherapy-resistant and 6 chemotherapy-sensitive B-ALL patients. The lncRNA DUXAP8/miR-29a/PIK3CA signaling network was identified as the most dysregulated in chemoresistant patient samples, and its effect on cellular phenotypes, PI3K-AKT-mTOR signaling, and chemosensitivity of doxorubicin (Dox)-resistant Nalm-6 (N6/ADR), and Dox-resistant 697 (697/ADR) cells were assessed. Furthermore, its synergy with inotuzumab ozogamicin treatment was investigated. Results: 1,338 lncRNAs, 75 miRNAs, and 1620 mRNAs were found to be dysregulated in chemotherapy-resistant B-ALL in comparison to chemotherapy-sensitive B-ALL patient samples. Through bioinformatics analyses and RT-qPCR validation, the lncRNA DUXAP8/miR-29a/PIK3CA network and PI3K-AKT-mTOR signaling were identified as significantly associated with B-ALL chemotherapy resistance. In N6/ADR and 697/ADR cells, LncRNA DUXAP8 overexpression and PIK3CA overexpression induced proliferation and inhibited apoptosis, and their respective knockdowns inhibited proliferation, facilitated apoptosis, and restored Dox chemosensitivity. MiR-29a was shown to affect the lncRNA DUXAP8/PIK3CA network, and luciferase reporter gene assay showed direct binding between lncRNA DUXAP8 and miR-29a, as well as between miR-29a and PIK3CA. Targeting lncRNA DUXAP8/miR-29a/PIK3CA network synergized with inotuzumab ozogamicin's effect on N6/ADR and 697/ADR cells. Conclusion: Targeting the lncRNA DUXAP8/miR-29a/PIK3CA network not only induced an apoptotic effect on Dox-resistant B-ALL and restored Dox chemosensitivity via PI3K-AKT-mTOR signaling but also showed synergism with inotuzumab ozogamicin treatment.

Analyses of long non-coding RNAs and mRNA profiling through RNA sequencing of MDBK cells at different stages of bovine viral diarrhea virus infection.

BACKGROUND: Bovine viral diarrhea virus (BVDV) infection is a dynamic and complex process that leads to significant economic losses in the dairy and cattle industries. However, our understanding of the protective and pathological mechanism underlying host infection is limited. METHODS: To determine whether BVDV regulates specific activities of the host cell, the expression of long non-coding RNA (lncRNA) during BVDV NADL infection was studied by deep sequencing. RESULTS: A total of 1236 lncRNA transcripts and 3261 mRNA transcripts were differentially regulated at 2h, 6h, and 18h post-infection. The lncRNAs shared same characteristics with other mammals in terms of exon length, number, expression level, and conservation. The Gene Ontology (GO) enrichment and KEGG pathway analyses showed that lncRNAs regulate immune reaction during BVDV infection. Thirteen differentially expressed genes in 18 hpi were selected and independently validated by reverse-transcription qPCR. CONCLUSIONS: The present study is the first to provide insights into the biological connection of lncRNAs and BVDV, which can be further explored for the development of antiviral prevention strategies and in understanding persistent infection between viral and host components.

Distinct temporal changes in host cell lncRNA expression during the course of an adenovirus infection.

The deregulation of cellular long non-coding RNA (lncRNA) expression during a human adenovirus infection was studied by deep sequencing. Expression of lncRNAs increased substantially following the progression of the infection. Among 645 significantly expressed lncRNAs, the expression of 398 was changed more than 2-fold. More than 80% of them were up-regulated and 80% of them were detected during the late phase. Based on the genomic locations of the deregulated lncRNAs in relation to known mRNAs and miRNAs, they were predicted to be involved in growth, structure, apoptosis and wound healing in the early phase, cell proliferation in the intermediate phase and protein synthesis, modification and transport in the late phase. The most significant functions of cellular RNA-binding proteins, previously shown to interact with the deregulated lncRNAs identified here, are involved in RNA splicing, nuclear export and translation events. We hypothesize that adenoviruses exploit the lncRNA network to optimize their reproduction.