Long Non-coding RNA Expression Research Articles

Role of Long Non-Coding RNAs in Human-Induced Pluripotent Stem Cells Derived Megakaryocytes: A p53, HOX Antisense Intergenic RNA Myeloid 1, and miR-125b Interaction Study.

Megakaryocytes (MKs) are rare polyploid cells found in the bone marrow and produce platelets. Platelets are small cell fragments that are essential during wound healing and vascular hemostasis. In vitro differentiation of MKs from human-induced pluripotent stem cell-derived CD34+ hematopoietic stem cells (hiPSC-HSCs) could provide an alternative treatment option for thrombocytopenic patients as a platelet source. In this approach, we developed a method to produce functional MKs from hiPSC-HSCs using a xeno-free and feeder-free condition and minimize the variation and risk from animal-derived products in cell culture. We have also investigated the genome-wide expression as well as functional significance of long noncoding RNAs (lncRNAs) in hiPSC-HSC-derived MKs to get insight into MK biology. We have performed lncRNAs expression profiling by using the Human LncProfilers qPCR Array Kit and identified 26 differentially regulated lncRNAs in hiPSC-HSC-derived MKs as compared with those in hiPSC-HSCs. HOX antisense intergenic RNA myeloid 1 (HOTAIRM1) was the most highly upregulated lncRNA in hiPSC-HSC-derived MKs and phorbol 12-myristate 13-acetate (PMA)-induced megakaryocytic-differentiating K562 cells. Furthermore, we have studied the potential mechanism of HOTAIRM1 based on the interactions between HOTAIRM1, p53, and miR-125b in PMA-induced K562 cells. Our results demonstrated that during MK maturation, HOTAIRM1 might be associated with the transcriptional regulation of p53 via acting as a decoy for miR-125b. Thus, the interaction between HOTAIRM1, p53, and miR-125b is likely involved in controlling cell cycling (cyclin D1), reactive oxygen species production, and apoptosis to support terminal maturation of MKs. SIGNIFICANCE STATEMENT: In vitro generation of megakaryocytes (MKs) from human-induced pluripotent stem cell-derived hematopoietic stem cells (hiPSC-HSCs) could provide an alternative source of platelets for treating thrombocytopenic patients. This study has investigated the functional significance of long non-coding RNAs in hiPSC-HSC-derived MKs, which remains unclear. This study's findings suggest that the regulatory role of HOX antisense intergenic RNA myeloid 1 (HOTAIRM1) in p53-mediated regulation of cyclin D1 during megakaryocytopoiesis is to promote MK maturation by decoying miR-125b.

Suppression of lncRNA Snhg1 inhibits high glucose-induced inflammation and proliferation in mouse mesangial cells

Diabetic nephropathy (DN) is the direct cause of end-stage renal disease, and nephritic inflammation plays a role in its growth and advancement. Aberrant expression of long non-coding RNAs (lncRNAs) correlates with many diseases, including DN. In this study, we investigated whether lncRNA small nucleolar RNA host gene 1 (Snhg1) was mechanistically involved in inflammation and mesangial cell (MC) proliferation in DN. We found that Snhg1 was significantly upregulated in DN renal tissues and high glucose (HG)-treated MCs. Overexpression of Snhg1 promoted inflammatory cytokine expression in MCs and MC proliferation under low-glucose conditions; meanwhile, Snhg1 knockdown suppressed inflammatory cytokine production and MC proliferation under HG conditions. Mechanistically, Snhg1 was found to directly bind miR-27b, thereby preventing the miRNA from binding its target KDM6B mRNA. Furthermore, miR-27b overexpression recapitulated the inhibitory effects of Snhg1 knockdown, whereas restoration of Snhg1 expression attenuated the function of miR-27b in MCs under HG conditions. Taken together, these results indicate that suppression of Snhg1 inhibited HG-induced inflammation and proliferation of MCs by regulating the miR-27b/KDM6B axis.

A novel melanoma prognostic model based on the ferroptosis-related long non-coding RNA.

Ferroptosis is an iron-dependent programmed cell death related to the biological process of many kinds of tumors. Long noncoding RNAs (LncRNA) have been found to play essential roles in the tumor, and their functions in the ferroptosis of tumor cells have been partially discovered. However, there is no summary of ferroptosis-related LncRNA and its functions in melanoma. In the present study, we aim to explore the expression profile of ferroptosis-related LncRNA genes and their value in melanoma prognosis by bioinformatics analysis. The expression of ferroptosis-related gene (FRG) from melanoma clinical data was extracted based on the Cancer Genome Atlas (TCGA) database. By screening the RNA expression data of 472 cases of melanoma and 810 cases of normal skin, eighteen ferroptosis-related differential genes were found to be related to the overall survival rate. Furthermore, 384 ferroptosis-related LncRNAs were discovered through constructing the mRNA-LncRNA co-expression network, and ten of them were found with prognostic significance in melanoma by multivariate Cox analysis. Risk assessment showed that the high expression of LncRNA00520 is associated with poor prognosis, while the increased expression of the other LncRNA is beneficial to the prognosis of patients with melanoma. From univariate and multivariate Cox regression analysis, there were ten ferroptosis-related LncRNA risk models towards to be significant independent prognostic factors for patients with melanoma and valuable predictive factors for overall survival (OS)(P<0.05). The ROC curve further suggested that the risk score has relatively reliable predictive ability (AUC=0.718). The protein level of ferroptosis-related genes was verified by the HPA database and IHC test, leading to the discovery that the expressions of ALOX5, PEBP1, ACSL4, and ZEB1 proteins up-regulated in tumor tissues, and existed differences between tumor tissues and normal tissues. In conclusion, we identified ten ferroptosis-related LncRNA and constructed a prognosis model base.

Constructed the ceRNA network and predicted a FEZF1-AS1/miR-92b-3p/ZIC5 axis in colon cancer.

The purpose of this study was to identify the role of FEZF1-AS1 in colon cancer and predicted the underlying mechanism. We extracted sequencing data of colon cancer patients from The Cancer Genome Atlas database, identified the differential expression of long noncoding RNA, microRNA, and messenger RNA, constructed a competitive endogenous RNA network, and then analyzed prognosis. Then, we used the enrichment analysis databases for functional analysis. Finally, we studied the FEZF1-AS1/miR-92b-3p/ZIC5 axis. We detected the expression of FEZF1-AS1, miR-92b-3p, and ZIC5 via quantitative reverse transcription-PCR, transfected colon cancer cell RKO with lentivirus and conducted FEZF1-AS1 knockdown, and performed cancer-related functional assays. It indicated that many RNA in the competitive endogenous RNA network, such as ZIC5, were predicted to be related to overall survival of colon cancer patients, and enrichment analysis showed cancer-related signaling pathways, such as PI3K/AKT signaling pathway. The expression of FEZF1-AS1 and ZIC5 was significantly higher and that of miR-92b-3p was lower in the colon cancer than in the normal colon tissues. FEZF1-AS1 promoted the migration, proliferation, as well as invasion of RKO. According to the prediction, FEZF1-AS1 and ZIC5 might competitively bind to miR-92b-3p, leading to the weakening of the inhibitory impact of miR-92b-3p on ZIC5 and increasing expression of ZIC5, thus further activating the PI3K/AKT signaling pathway, which led to the occurrence and development of colon cancer. The study suggested that FEZF1-AS1 might be an effective diagnosis biomarker for colon cancer.

270 (PB050) - Comparative pan-cancer transcriptomics reveals that aberrant expression of long non-coding RNAs define cancers, tumor progression and immune cell exclusion

Background: Long non-coding RNAs (lncRNAs) are emerging targets for the diagnosis and therapeutic treatment of cancer. LncRNAs are non-protein-coding transcripts that regulate gene expression through epigenetic mechanisms mediated through binding of DNA, small RNAs and proteins. They exhibit high tissue- and context-specific expression, marking them as attractive biomarkers for cancer treatment or detection. Of the over 18 000 lncRNAs identified in the genome, the vast majority remain completely uncharacterized, limiting our understanding of the role of this group of non-coding RNAs in cancer.

Expression of Long Non-Coding RNAs in Activated Human Retinal Vascular Endothelial Cells

ABSTRACT Purpose Retinal endothelial cell activation is a central event in non-infectious posterior uveitis. There is recent interest in long non-coding (lnc)RNA-targeted therapeutics for retinal diseases. We aimed to identify human retinal endothelial cell lncRNAs that might be involved in activation. Methods Eleven candidate lncRNAs were identified: GAS5, KCNQ1OT1, LINC00294, MALAT1, MEG3, MIR155HG, NEAT1, NORAD, OIP5-AS1, SENCR, TUG1. Expression was assessed by RT-PCR in human retinal endothelial cells, at baseline and following activation with interleukin (IL)-1β and tumor necrosis factor (TNF)-α. Results IL-1β significantly upregulated MEG3 and SENCR at 4 and 24 hours; LINC00294, NORAD, OIP5-AS1 and TUG1 at 24 hours; and MIR155HG at 4, 24 and 48 hours; but downregulated GAS5 at 24 and 48 hours. TNF-α significantly upregulated KCNQ1OT1, LINC00294, MEG3, NORAD and SENCR at 4 hours; SENCR and TUG1 at 24 hours; and MIR155HG at all time points. Conclusions Future studies involving manipulation of MIR155HG may be warranted to explore potential therapeutic applications for non-infectious posterior uveitis.

Comparing the long non-coding RNA expression profiles of skeletal muscle and kidney tissues from patients with diabetes.

BackgroundDiabetes causes the dysregulation of several organs, and these effects are often closely associated with changes in the expression of long non-coding RNAs (lncRNAs), a group of non-coding RNAs, within these tissues. Previous studies have described a variety of changes in the expression profile of several lncRNAs from different organs in response to the pathogenesis of diabetes. However, none of these studies compared the expression profiles of these lncRNAs between these organs. This study was designed to identify common and specific lncRNAs involved in the progression of diabetes in the skeletal muscles and kidneys.MethodsPublicly available RNA sequencing data of diabetic patients was obtained from the Gene Expression Omnibus database. By analyzing the expression of lncRNAs in these datasets, differentially expressed lncRNAs in each tissue between non-diabetic and diabetic patients were identified. To identify any lncRNAs changed in common in both kidney and muscle tissues, those lncRNAs that are significantly dysregulated in both datasets were selected.ResultsThese evaluations identified a series of novel lncRNAs unique to each organ and several transcripts that were common to both skeletal muscle and kidney tissues in these patients. Interestingly, the genomic location of these lncRNAs suggests that they reside in close proximity to several protein-coding genes known to be related to diabetes suggesting that these lncRNAs may have a regulatory relationship with their neighboring genes.ConclusionThese results offer valuable insights into the role of lncRNAs during the pathogenesis of diabetes.

Reliable assessment of telomere maintenance mechanisms in neuroblastoma

BackgroundTelomere maintenance mechanisms (TMM) are a hallmark of high-risk neuroblastoma, and are conferred by activation of telomerase or alternative lengthening of telomeres (ALT). However, detection of TMM is not yet part of the clinical routine, and consensus on TMM detection, especially on ALT assessment, remains to be achieved.MethodsWhole genome sequencing (WGS) data of 68 primary neuroblastoma samples were analyzed. Telomere length was calculated from WGS data or by telomere restriction fragment analysis (n = 39). ALT was assessed by C-circle assay (CCA, n = 67) and detection of ALT-associated PML nuclear bodies (APB) by combined fluorescence in situ hybridization and immunofluorescence staining (n = 68). RNA sequencing was performed (n = 64) to determine expression of TERT and telomeric long non-coding RNA (TERRA). Telomerase activity was examined by telomerase repeat amplification protocol (TRAP, n = 15).ResultsTumors were considered as telomerase-positive if they harbored a TERT rearrangement, MYCN amplification or high TERT expression (45.6%, 31/68), and ALT-positive if they were positive for APB and CCA (19.1%, 13/68). If all these markers were absent, tumors were considered TMM-negative (25.0%, 17/68). According to these criteria, the majority of samples were classified unambiguously (89.7%, 61/68). Assessment of additional ALT-associated parameters clarified the TMM status of the remaining seven cases with high likelihood: ALT-positive tumors had higher TERRA expression, longer telomeres, more telomere insertions, a characteristic pattern of telomere variant repeats, and were associated with ATRX mutations.ConclusionsWe here propose a workflow to reliably detect TMM in neuroblastoma. We show that unambiguous classification is feasible following a stepwise approach that determines both, activation of telomerase and ALT. The workflow proposed in this study can be used in clinical routine and provides a framework to systematically and reliably determine telomere maintenance mechanisms for risk stratification and treatment allocation of neuroblastoma patients.

Potential biomarkers for predicting the overall survival outcome of kidney renal papillary cell carcinoma: an analysis of ferroptosis-related LNCRNAs

BackgroundKidney renal papillary cell carcinoma (KIRP) is a dangerous cancer, which accounts for 15–20% of all kidney malignancies. Ferroptosis is a rare kind of cell death that overcomes medication resistance. Ferroptosis-related long non-coding RNAs (LNCRNAs) in KIRP, remain unknown.MethodWe wanted to express how ferroptosis-related LNCRNAs interact with immune cell infiltration in KIRP. Gene set enrichment analysis in the GO and KEGG databases were used to explore gene expression enrichment. The prognostic model was constructed using Lasso regression. In addition, we also analyzed the modifications in the tumor microenvironment (TME) and immunological association.ResultThe expression of LNCRNA was closely connected to the ferroptosis, according to co-expression analyses. CASC19, AC090197.1, AC099850.3, AL033397.2, LINC00462, and B3GALT1-AS1 were found to be significantly increased in the high-risk group, indicating that all of these markers implicates the malignancy processes for KIRP patients and may be cancer-promoting variables. LNCTAM34A and AC024022.1 were shown to be significantly elevated in the low-risk group; these might represent as the KIRP tumor suppressor genes. According to the TCGA, CCR, and inflammation-promoting genes were considered to be significantly different between the low-risk and high-risk groups. The expression of CD160, TNFSF4, CD80, BTLA, and TNFRSF9 was different in the two risk groups.ConclusionLNCRNAs associated with ferroptosis were linked to the occurrence and progression of KIRP. Ferroptosis-related LNCRNAs and immune cell infiltration in the TME may be potential biomarkers in KIRP that should be further investigated.

In Vitro and In Vivo Comparative Analysis of Differentially Expressed Genes and Signaling Pathways in Breast Cancer Cells on Interaction with Mesenchymal Stem Cells.

The interaction of breast cancer cells (BCC) with mesenchymal stem cells (MSC) plays a vital role in influencing the gene expression in breast cancer cells and thereby its uncontrolled proliferation, metastasis, and drug resistance. The extent of MSC governing the BCC or the extent of BCC influencing the MSC is a complex process, and the interaction strongly depends upon conditions such as the presence or absence of other cell types and in vivo tumor microenvironment or simple in vitro conditions. Hence, understanding this interaction through gene expression profiling may provide key insights about potential genes which can be targeted for breast cancer treatment. In the current study, in vitro microarray dataset and in vivo RNA-seq dataset of BCC on interaction with the MSC were downloaded from NCBI GEO database and analyzed for differentially expressed genes (DEGs), gene ontology (GO) term enrichment, and Reactome pathway analysis. To target the genes which have similar effect on both in vitro and in vivo, a comparative analysis was performed, 24 genes were commonly upregulated in both in vitro and in vivo datasets, while no common downregulated genes were observed. Out of which, 16 significant genes based upon fold change (logFC > 2) are identified for manipulating the interactions between MSC and BCC. Among them, 6 of the identified genes (FSTL1, LOX, SERPINE1, INHBA, FN1, and VEGFA) have already been reported to be upregulated in BCC on interaction with MSC by various studies. Further experiments need to be conducted to understand the role of remaining 10 identified genes (EFEMP1, IGFBP3, EDIL3, IFITM1, IGFBP4, ITGA5, SLC3A2, HRH1, PPP1R15A, and NNMT) in MSC-BCC interaction. In addition to the reported significant genes and its associated pathways, the expression of long non-coding RNA identified in this study may increase our understanding about the way MSC interacts with BCC and accelerate MSC-based treatment strategies for breast cancer.

Identification and ultrasensitive photoelectrochemical detection of LncNR_040117: a biomarker of recurrent miscarriage and antiphospholipid antibody syndrome in platelet-derived microparticles

The abnormal expression of long non-coding RNAs (LncRNAs) in platelet-derived microparticles (PMPs) is closely related to immune disorders and may lead to antiphospholipid antibody syndrome and recurrent miscarriage. To understand the association between the LncRNAs in PMPs and RM/APS, the differences in the expression of LncRNAs in RM/APS patients and healthy controls were analyzed. Microarray analysis and RT-qPCR detection proved that RM/APS patient exhibited high levels of LncNR_040117 expression. The lentiviral silent expression transfection of HTR-8/SVneo cells indicated that LncNR_040117 downregulation decreased the activity of HTR-8/SVneo cells and inhibited the MAPK signaling pathway, further confirming the biomarker proficiency of LncNR_040117 for RM/APS. After that, we proposed a β-In2S3@g-C3N4 nanoheterojunction-based photoelectrochemical (PEC) biosensor to achieve the ultrasensitive detection of LncNR_040117. The nanoheterojunction aids in the effective separation of photogenerated carriers and significantly improve the photocurrent response of the biosensor. The conjugation of LncNR_040117 onto the PEC biosensing platform increased the steric hindrance between electrolyte and electrode, subsequently decreasing the photocurrent signal. The PEC biosensor showed a wide detection range of 0.1–106 fM and a low limit of detection of 0.025 fM. For clinical sample testing, the results of the PEC and RT-qPCR were highly consistent. Overall, LncNR_040117 in PMPs was identified as an effective biomarker for RM/APS and could be accurately detected by the proposed PEC biosensor, which is expected to provide a reliable diagnostic platform for RM/APS.

Disrupted expression of long non-coding RNAs in the human oocyte: the possible epigenetic culprits leading to recurrent oocyte maturation arrest.

To depict the lncRNA expression during human oocyte maturation and explore the lncRNAs leading to recurrent oocyte maturation arrest. LncRNA sequencing was performed on pooled RNA from 20 oocytes of each group (recurrent oocyte maturation arrest (ROMA), ofgerminal vesicle (GV), metaphase I (MI),or metaphase II (MII)stages. Bioinformatics software was deployed to compare the lncRNA differential expression between the normal and ROMA oocytes. The co-expression of lncRNA/mRNA was illustrated with the Cytoscape software. The pooled RNA from every 10 oocytes of each group (ROMA, GV, MI, MII) was extracted for further qPCR validation. There were 17 downregulated and 3 upregulated lncRNAs in the ROMA oocyte. Among them, co-expression analysis indicated that NEAT1 and NORAD were both downregulated. Basing on the KEGG enrichment analysis, PRCKA and JAK3 might be the target genes in the PI3K-Akt pathway and modulated by NEAT1 and NORAD. As validated by qPCR, the expressional levels of lncRNA candidates (NEAT1 and NORAD) and their target genes (PRKCA and JAK3) were confirmed to be extremely lower in the ROMA oocyte than in the normal oocyte. By targeting the PI3K-Akt pathway genes PRKCA and JAK3, the abnormal expression of NEAT1 and NORAD is suggested to impede oocyte maturation and impair oocyte genome integrity.

LINC00665 affects the malignant biological behavior of ovarian cancer via the miR-148b-3p/KLF5

This study investigated the expression and clinical significance of long intergenic noncoding RNA 00665 (LINC00665) in ovarian cancer (OC), as well as its effect on the malignant biological behavior of OC cells. The expression of LINC00665, miR-148b-3p, and Krüppel-like factor 5 (KLF5) in OC tissues and cells were determined by RT-qPCR. Western blot was used to detect the protein expression of KLF5. The expression patterns of LINC00665 in nuclear and cytoplasm fractions were undertaken using RT-qPCR. In addition, CCK-8 assay, clone formation assay, transwell, scratch test, and flow cytometry were respectively used to detect the cell activity, proliferation, invasiveness, healing of cells, and apoptosis rate of OC cells. Furthermore, the interactions between LINC00665 and miR-148b-3p and between miR-148b-3p and KLF5 were verified by the luciferase reporter assay, and the correlations among these three genes were analyzed. LINC00665 expression was upregulated both in OC cell lines and tissues. Si-LINC00665 inhibited cell proliferation, invasion, and migration and induced apoptosis to a certain extent. The subcellular fraction assay revealed LINC00665 to be located mainly in the cytoplasm. miR-148b-3p was a target of LINC00665, and KLF5 was directly targeted by miR-148b-3p. Si-LINC00665 inhibited KLF5 expression, miR-148b-3p inhibitor promoted KLF5 expression, and si-KLF5 inhibited LINC00665 expression. Interestingly, the expression of LINC00665 was reversely associated with miR-148b-3p expression but positively correlated with KLF5. Furthermore, miR-148b-3p expression was negatively correlated with KLF5. In addition, si-KLF5 inhibited the malignant biological behavior of OC cells, whereas miR-148b-3p inhibitor had the opposite effect. Most importantly, the si-LINC00665 could reverse the promotion effect of the miR-148b-3p inhibitor on the malignant biological behavior of OC cells. LINC00665 can be used as an effective prognostic indicator of OC, which has the potential to be a new therapeutic target.

Geometric complement heterogeneous information and random forest for predicting lncRNA-disease associations.

More and more evidences have showed that the unnatural expression of long non-coding RNA (lncRNA) is relevant to varieties of human diseases. Therefore, accurate identification of disease-related lncRNAs can help to understand lncRNA expression at the molecular level and to explore more effective treatments for diseases. Plenty of lncRNA-disease association prediction models have been raised but it is still a challenge to recognize unknown lncRNA-disease associations. In this work, we have proposed a computational model for predicting lncRNA-disease associations based on geometric complement heterogeneous information and random forest. Firstly, geometric complement heterogeneous information was used to integrate lncRNA-miRNA interactions and miRNA-disease associations verified by experiments. Secondly, lncRNA and disease features consisted of their respective similarity coefficients were fused into input feature space. Thirdly, an autoencoder was adopted to project raw high-dimensional features into low-dimension space to learn representation for lncRNAs and diseases. Finally, the low-dimensional lncRNA and disease features were fused into input feature space to train a random forest classifier for lncRNA-disease association prediction. Under five-fold cross-validation, the AUC (area under the receiver operating characteristic curve) is 0.9897 and the AUPR (area under the precision-recall curve) is 0.7040, indicating that the performance of our model is better than several state-of-the-art lncRNA-disease association prediction models. In addition, case studies on colon and stomach cancer indicate that our model has a good ability to predict disease-related lncRNAs.

Construction of prognostic signature of patients with oral squamous cell carcinoma based on pyroptosis-related long non-coding RNAs.

Background and objectiveOral squamous cell carcinoma (OSCC) is the most common malignant tumor in the head and neck, and its morbidity and mortality are increasing year by year. Changes in key genes are thought to be closely related to the occurrence and development of OSCC. Pyroptosis is an inflammatory form of programmed cell death that has been implicated in malignancies and inflammatory diseases. Changes in the expression of long noncoding RNAs may also affect tumorigenesis and progression. In this study, our main objective was to evaluate the association between pyroptosis-related lncRNAs and prognosis in patients with OSCC.MethodsThe RNA-seq data and clinicopathological data of OSCC patients are from The Cancer Genome Atlas database. The pyroptosis gene set is obtained from Gene Set Enrichment Analysis database. Univariate COX, Lasso and multivariate COX regression analyses were used for the construction of risk prognostic models of OSCC, eight lncRNAs were incorporated into prognostic models. The Kaplan-Meier method and log-rank test were used to evaluate the differences of overall survival between patients in high-risk and low-risk groups. The reliability of predictions across the dataset was analyzed by receiver operating characteristic (ROC) curves. The immune signature score was calculated using the single-sample gene set enrichment analysis.ResultsEight pyroptosis-related lncRNAs were used to construct prognostic signature of OSCC, including AC136475.2, AC024075.2, JPX, ZFAS1, TNFRSF10A-AS1, LINC00847, AC099850.3 and IER3-AS1. According to this prognostic signature, patients with OSCC were divided into high-risk and low-risk groups. Kaplan-Meier survival analysis showed that the survival rate of the high-risk group was significantly lower than the low-risk group. ROC area for risk score was 0.716, and ROC area of the 8 lncRNAs are all between 0.5 and 1, implied that these lncRNAs had high accuracy in predicting the prognosis of OSCC patients. Immune Infiltration findings suggested that these lncRNAs affected immune responses in the microenvironment of OSCC.ConclusionThe prognostic signature based on pyroptosis-related lncRNAs potentially serves as an independent prognostic indicator for OSCC patients. And this signature facilitates research on targeted diagnosis and treatment of patients diagnosed with OSCC.

The interplay of long noncoding RNAs and hepatitis B virus.

Hepatitis B Virus (HBV) infections remain a major global health burden with an estimated 296 million people living with a chronic infection and 884,000 HBV-related deaths annually. Notably, patients with a chronic hepatitis B (CHB) infection are at a 30-fold greater risk of developing hepatocellular carcinoma (HCC), the most common type of primary liver cancer, which is the 3rd deadliest cancer worldwide. Several groups have assessed HBV-related aberrant expression of host-cell long noncoding RNAs (lncRNAs) and how altered expression of specific lncRNAs affects HBV replication and progression to associated disease states. Given the challenges in establishing effective HBV models and analyzing transcriptomic data, this review focuses on lncRNA expression data primarily collected from clinical patient samples and primary human hepatocytes,with the subsequent mechanism of action analysis in cell lines or other model systems. Ultimately, understanding HBV-induced lncRNA-expression dysregulation could lead to new treatments and biomarkers for HBV infection and its associated diseases.

LncRNA pair as candidate diagnostic signature for colorectal cancer based on the within-sample relative expression levels.

BackgroundEarly diagnosis of colorectal cancer could significantly improve the prognosis and reduce mortality. However, indeterminate diagnosis is often met in pathology diagnosis in biopsy samples. Abnormal expression of long non-coding RNA (lncRNA) is associated with the initiation and progression of colorectal cancer. It is of great value and clinical significance to explore lncRNAs as candidate diagnostic biomarkers in colorectal cancer.MethodsBased on the within-sample relative expression levels of lncRNA pairs, we identified a group of candidate diagnostic biomarkers for colorectal cancer. In addition, we validated it in independent datasets produced by different laboratories and different platforms. We also tested it in colorectal cancer tissue samples using quantitative real-time polymerase chain reaction (RT-qPCR).ResultsA biomarker consisting of six lncRNA pairs including nine lncRNAs was identified for the diagnosis of colorectal cancer. For a total of 950 cancer samples and 247 non-cancer samples, both of the sensitivity and specificity could achieve approximately 90%. For adenoma samples, the accuracy could achieve 73%. For normal tissues from inflammatory bowel disease patients, 93% (14/15) were correctly classified as non-cancer. Furthermore, the lncRNA pair biomarker showed excellent performance in all clinical stages; even in the early stage, the accuracy could achieve 87% and 82% in stage I and II. Meanwhile, the biomarker was also robust to the microsatellite instability status. More importantly, we measured the biomarker in 35 colorectal cancer and 30 cancer-adjacent tissue samples using quantitative real-time polymerase chain reaction (RT-qPCR). The accuracy could achieve 93.3% (70/75). Specially, even in early-stage tumors (I and II), the accuracy could also achieve 90.9% (30/33). The enrichment analysis revealed that these lncRNAs were involved in highly associated cancer pathways and immune-related pathways. Immune analysis showed that these marker lncRNAs were associated with multiple immune cells, implying that they might be involved in the regulation of immune cell functions in colorectal cancer. Most of the biomarker lncRNAs were also differentially expressed between the mutant group and wild-type group of colorectal cancer driver genes.ConclusionWe identified and validated six lncRNA pairs including nine lncRNAs as a biomarker for assisting in the diagnosis of colorectal cancer.

Identification of Long Non-Coding RNA MIR4435-2HG as a Prognostic Biomarker in Bladder Cancer.

The abnormal expression of long non-coding RNAs(lncRNAs) is closely related to the prognosis of patients. This finding may indicate a new target for the treatment of malignant tumors. Non-muscle invasive bladder cancer (NMIBC) is the most common subtype of bladder cancer, and BCG intravesical therapy is the first-line treatment for NMIBC, but about half of NMIBC patients relapse within two years after BCG treatment. Therefore, it is necessary to screen out lncRNAs related to the prognosis and treatment of BGC-resistant patients. Here, we performed differential expression analysis of lncRNAs in the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, and screened MIR4435-2HG as the only BCG-response-related lncRNA. Then, the prognosis value of MIR4435-2HG was validated in several publicly available cohorts, and confirmed its prognostic value in bladder cancer of different stages. In addition, we also analyzed its genetic alterations, clinical relevance, function enrichment, and association with other biomarkers. Further validation of the expression of MIR4435-2HG might be helpful to instruct NMIBC prognosis and treatment.

A Study on the Expression of Messenger RNAs and Long Noncoding RNA in Keloid Fibroblasts Based on Gene Expression Omnibus Microarray Data Mining.

The purpose of this study was to find the coding RNA [messenger RNA (mRNA)] and long noncoding RNA (lncRNA) expressed in keloid through the analysis of Gene Expression Omnibus microarray chip of keloid fibroblasts. Gene Expression Omnibus database GSE7890 database was downloaded with selection of keloids and normal scar group data. The data were analyzed by R language combined with online database. The log2FC>1, P value <0.01 was chosen as screening criteria, and the differentially expressed mRNAs were screened for GO and KEGG function analysis. One hundred fifty-five mRNA expression in the keloid group was significantly different from that in the normal group, including 31 groups with upregulated mRNA expression and 124 groups with down-regulated mRNA expression. Meanwhile, 8 lncRNAs were changed in the keloid group, including 3 upregulated (Rp11-420a23.1, Rp11-522b15.3, and Rp11-706j10.1) and 5 down-regulated (LINC00511, LINC00327, Hoxb-as3, Rp11-385n17.1, and Rp3-428l16.2). Quantitative polymerase chain reaction analysis of DElncRNAs in keloid fibroblasts showed that the expression of all DElncRNAs except for RP11-385N17.1 was increased in the keloid group compared with the control group. Moreover, the differences in LINC00511 and RP11-706J10.1 were statistically significant. The noncoding RNA information of Gene Expression Omnibus chip data can be deeply mined through bioinformatics, and the potential epigenomic mechanism affecting keloid formation can be found from the existing database.

Identification of a pyroptosis-related lncRNA signature in the regulation of prognosis, metabolism signals and immune infiltration in lung adenocarcinoma.

Pyroptosis is a cell death pathway that plays a significant role in lung adenocarcinoma (LUAD). Also, studies regarding the correlation between the expression of long non-coding RNAs (lncRNAs) and the mechanism of LUAD has aroused concern around the world. The purpose of this paper is to explore the underlying relationship of differentially expressed lncRNAs and pyroptosis-related genes. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression were applied to construct a prognostic risk score model from the TCGA database. A pyroptosis-related five-lncRNA signature (CRNDE, HHLA3, MIR193BHG, LINC00941, LINC01843) was considered to be correlated to the prognosis and immune response of LUAD patients. In addition, the cytological experiments revealed that aberrantly expressed HHLA3 displayed a proliferation promotion role in LUAD cells A549 and H460. Next, the forest and nomogram plots have shown this lncRNA signature could be served as an independent prognostic factor for LUAD. The ROC curves further identified the prognostic value of the five-lncRNA signature. The infiltration of immune cells, such as T cells CD8, T cells CD4 memory resting, T cells CD4 memory activated and M0 macrophages were greatly different between the high-risk group and the low-risk group. It implicated that the signature is significantly effective in immunotherapy of LUAD patients. This study has supplied a novel pyroptosis-related lncRNA signature and provided a predictive model for prognosis and immune response of LUAD patients.