Large-scale prediction of long non-coding RNA functions in a coding-non-coding gene co-expression network

Identification and Characterization of lncRNA and mRNA in Testes of Landrace and Hezuo Boars

Simple Summary

Precocious puberty is an excellent reproductive trait in domestic animals, which can generate higher breeding benefits in livestock production. However, regulators associated with this sexual maturation process remain largely unknown. Chinese Hezuo (HZ) boars are known for their early sexual maturity. In this work, the characteristics of precocious puberty in HZ pigs were confirmed by histological analysis, and some important long noncoding RNA (lncRNA) and mRNA were identified in the testes of immature (30-day-old) and mature (120-day-old) HZ boars, which could play a key role in precocious puberty. These results will provide a theoretical basis for further research on the regulatory mechanism of precocious puberty, which is important for accelerating the breeding process of highly fertile animals.

Abstract

Chinese HZ boars are typical plateau miniature boars characterized by precocious puberty, which is closely related to testicular development and spermatogenesis. Accumulating evidence indicates that lncRNA is involved in the testicular development and regulation of spermatogenesis. However, little is known about the lncRNA precocious regulation in testicular development and spermatogenesis on early sexual maturity of HZ boars. Thus, we investigated the expression and characterization of lncRNA and mRNA in 30-day-old and 120-day-old HZ boar testes using transcriptome to explore precocious puberty. Landrace (LC) boar was treated as the control. Histological analyses indicated that HZ boar underwent puberty development at an earlier stage than LC boar and had achieved sexual maturity at 120 days old. RNA-Seq yielded a total of 187 lncRNAs and 984 mRNAs; these molecules were identified as possible candidates for precocious puberty. GO terms and KEGG pathways enrichment analyses revealed that the differentially expressed lncRNA and their targeted genes were involved in metabolic pathways regulating testis development and spermatogenesis, such as the PI3K-Akt, TGF-beta and Wnt pathways. Further screening, some lncRNA (such as LOC102166140, LOC110259451, and MSTRG.15011.2), and mRNA (such as PDCL2, HSD17B4, SHCBP1L, CYP21A2, and SPATA3) were found to be possibly associated with precocious puberty, which would add to our understanding of the molecular regulatory mechanisms of precocious puberty. This study provided valuable information for further study of the role of lncRNA and mRNA in the process of precocious puberty.

ncFANs v2.0: an integrative platform for functional annotation of non-coding RNAs

Increasing evidence proves the essential regulatory roles of non-coding RNAs (ncRNAs) in biological processes. However, characterizing the specific functions of ncRNAs remains a challenging task, owing to the intensive consumption of the experimental approaches. Here, we present an online platform ncFANs v2.0 that is a significantly enhanced version of our previous ncFANs to provide multiple computational methods for ncRNA functional annotation. Specifically, ncFANs v2.0 was updated to embed three functional modules, including ncFANs-NET, ncFANs-eLnc and ncFANs-CHIP. ncFANs-NET is a new module designed for data-free functional annotation based on four kinds of pre-built networks, including the co-expression network, co-methylation network, long non-coding RNA (lncRNA)-centric regulatory network and random forest-based network. ncFANs-eLnc enables the one-stop identification of enhancer-derived lncRNAs from the de novo assembled transcriptome based on the user-defined or our pre-annotated enhancers. Moreover, ncFANs-CHIP inherits the original functions for microarray data-based functional annotation and supports more chip types. We believe that our ncFANs v2.0 carries sufficient convenience and practicability for biological researchers and facilitates unraveling the regulatory mechanisms of ncRNAs. The ncFANs v2.0 server is freely available at http://bioinfo.org/ncfans or http://ncfans.gene.ac.

Single-cell Long Non-coding RNA Landscape of T Cells in Human Cancer Immunity

The development of new biomarkers or therapeutic targets for cancer immunotherapies requires deep understanding of T cells. To date, the complete landscape and systematic characterization of long noncoding RNAs (lncRNAs) in T cells in cancer immunity are lacking. Here, by systematically analyzing full-length single-cell RNA sequencing (scRNA-seq) data of more than 20,000 libraries of T cells across three cancer types, we provided the first comprehensive catalog and the functional repertoires of lncRNAs in human T cells. Specifically, we developed a custom pipeline for de novotranscriptome assembly and obtained a novel lncRNA catalog containing 9433 genes. This increased the number of current human lncRNA catalog by 16% and nearly doubled the number of lncRNAs expressed in T cells. We found that a portion of expressed genes in single T cells were lncRNAs which had been overlooked by the majority of previous studies. Based on metacell maps constructed by the MetaCell algorithm that partitions scRNA-seq datasets into disjointed and homogenous groups of cells (metacells), 154 signature lncRNA genes were identified. They were associated with effector, exhausted, and regulatory T cell states. Moreover, 84 of them were functionally annotated based on the co-expression networks, indicating that lncRNAs might broadly participate in the regulation of T cell functions. Our findings provide a new point of view and resource for investigating the mechanisms of T cell regulation in cancer immunity as well as for novel cancer-immune biomarker development and cancer immunotherapies

Long Non-Coding RNA LINC01410 Promoted Tumor Progression via the ErbB Signaling Pathway by Targeting STAT5 in Gallbladder Cancer

Objectives

Long non-coding RNAs (lncRNAs) have been recently emerging as crucial molecules in multiple human cancers. However, their expression patterns, roles as well as the underlying mechanisms in gallbladder cancer (GBC) remain largely unclear.

Materials and Methods

The expression of lncRNAs in GBC was downloaded from GEO database. Quantitative real-time polymerase chain reaction (qRT-PCR) and RNA in situ hybridization (ISH) were used to detect the expression of lncRNAs in GBC tissues. The full-sequence of LINC01410 was determined by RACE assay. Subcellular distribution of LINC01410 was examined by nuclear/cytoplasmic RNA fractionation analysis. Loss- and gain-of-function experiments were conducted to explore the biological functions of LINC01410 in vitro and in vivo. RNA pull-down, RNA immune-precipitation (RIP), and Western blot assay were conducted to investigate the mechanisms underlying the biological function of LINC01410 in GBC.

Results

LINC01410 was significantly upregulated in the GBC tissues compared to adjacent non-tumor tissues. High LINC01410 expression was significantly associated with poor prognosis of GBC patients. We identified LINC01410 to be 2,877 bp in length and mainly localized in the cytoplasm of GBC cells. Overexpression of LINC01410 promoted GBC cell proliferation, migration, and invasion in vitro and GBC progression in vivo, whereas LINC01410 downregulation rescued these effects in vitro. From RNA pull-down and RIP assay, we identified that STAT5 was a critical downstream target of LINC01410. Furthermore, ErbB signaling pathway was involved in the malignant phenotypes of GBC mediated by LINC01410.

Conclusions

Our results suggested that LINC01410 was an important lncRNA that promoted GBC progression via targeting STAT5 and activating ErbB signaling pathway.

The Novel Non-coding Transcriptional Regulator Gm18840 Drives Cardiomyocyte Apoptosis in Myocardial Infarction Post Ischemia/Reperfusion

BACKGROUND

Ischemia/reperfusion-mediated myocardial infarction (MIRI) is a major pathological factor implicated in the progression of ischemic heart disease, but the key factors dysregulated during MIRI have not been fully elucidated, especially those essential non-coding factors required for cardiovascular development.

METHODS

A murine MIRI model and RNA sequencing (RNA-seq) were used to identify key lncRNAs after myocardial infarction. qRT-PCR was used to validate expression in cardiac muscle tissues and myocardial cells. The role of Gm18840 in HL-1 cell growth was determined by flow cytometry experiments in vitro. Full-length Gm18840 was identified by using a rapid amplification of cDNA ends (RACE) assay. The subcellular distribution of Gm18840 was examined by nuclear/cytoplasmic RNA fractionation and qRT-PCR. RNA pulldown and RNA immunoprecipitation (RIP)-qPCR assays were performed to identify Gm18840-interacting proteins. Chromatin isolation by RNA purification (ChIRP)-seq (chromatin isolation by RNA purification) was used to identify the genome-wide binding of Gm18840 to chromatin. The regulatory activity of Gm18840 in transcriptional regulation was examined by a luciferase reporter assay and qRT-PCR.

RESULTS

Gm18840 was upregulated after myocardial infarction in both in vivo and in vitro MIRI models. Gm18840 was 1,471 nt in length and localized in both the cytoplasm and the nucleus of HL-1 cells. Functional studies showed that the knockdown of Gm18840 promoted the apoptosis of HL-1 cells. Gm18840 directly interacts with histones, including H2B, highlighting a potential function in transcriptional regulation. Further ChIRP-seq and RNA-seq analyses showed that Gm18840 is directly bound to the cis-regulatory regions of genes involved in developmental processes, such as Junb, Rras2, and Bcl3.

CONCLUSION

Gm18840, a novel transcriptional regulator, promoted the apoptosis of myocardial cells via direct transcriptional regulation of essential genes and might serve as a novel therapeutic target for MIRI.

GLIDR promotes the progression of glioma by regulating the miR-4677-3p/MAGI2 axis

Gliomas are the most common and fatal primary brain tumors. Growing evidence suggests that long non-coding RNAs (lncRNAs) constitute novel and potential therapeutic targets for glioma. However, the biological role of glioblastoma down-regulated RNA (GLIDR) in glioma remains largely elusive. In the current study, we used quantitative real-time polymerase chain reaction (qRT-PCR) to detect GLIDR expression in glioma cells. Cell counting kit 8 (CCK-8) assay, colony formation assay, JC-1 staining, and flow cytometry were used to evaluate the role of GLIDR in proliferation and apoptosis of glioma cells. Western blotting was performed to assess the effect of GLIDR on the level of apoptosis-related proteins. In addition, bioinformatics prediction, RNA immunoprecipitation (RIP), RNA pull-down, and luciferase reporter gene assays were used to study the regulatory mechanisms of GLIDR in glioma. GLIDR was found to be highly expressed in glioma cells and silencing of GLIDR inhibited cell proliferation and promoted apoptosis. Functionally, GLIDR bound to miR-4677-3p that directly targeted membrane-associated guanylate kinase, WW, and PDZ domain-containing protein 2 (MAGI2). Our data showed that GLIDR affects the proliferation and apoptosis of glioma cells by targeting miR-4677-3p to regulate the expression of MAGI2. In conclusion, our study determined the oncogenic role of GLIDR in glioma, which may provide a new perspective for the treatment of glioma.

Integrative Transcriptomic Analysis Reveals the Immune Mechanism for a CyHV-3-Resistant Common Carp Strain

Anti-disease breeding is becoming the most promising solution to cyprinid herpesvirus-3 (CyHV-3) infection, the major threat to common carp aquaculture. Virus challenging studies suggested that a breeding strain of common carp developed resistance to CyHV-3 infection. This study illustrates the immune mechanisms involved in both sensitivity and anti-virus ability for CyHV3 infection in fish. An integrative analysis of the protein-coding genes and long non-coding RNAs (lncRNAs) using transcriptomic data was performed. Tissues from the head kidney of common carp were extracted at days 0 (the healthy control) and 7 after CyHV-3 infection (the survivors) and used to analyze the transcriptome through both Illumina and PacBio sequencing. Following analysis of the GO terms and KEGG pathways involved, the immune-related terms and pathways were merged. To dig out details on the immune aspect, the DEGs were filtered using the current common carp immune gene library. Immune gene categories and their corresponding genes in different comparison groups were revealed. Also, the immunological Gene Ontology terms for lncRNA modulation were retained. The weighted gene co-expression network analysis was used to reveal the regulation of immune genes by lncRNA. The results demonstrated that the breeding carp strain develops a marked resistance to CyHV-3 infection through a specific innate immune mechanism. The featured biological processes were autophagy, phagocytosis, cytotoxicity, and virus blockage by lectins and MUC3. Moreover, the immune-suppressive signals, such as suppression of IL21R on STAT3, PI3K mediated inhibition of inflammation by dopamine upon infection, as well as the inhibition of NLRC3 on STING during a steady state. Possible susceptible factors for CyHV-3, such as ITGB1, TLR18, and CCL4, were also revealed from the non-breeding strain. The results of this study also suggested that Nramp and PAI regulated by LncRNA could facilitate virus infection and proliferation for infected cells respectively, while T cell leukemia homeobox 3 (TLX3), as well as galectin 3 function by lncRNA, may play a role in the resistance mechanism. Therefore, immune factors that are immunogenetically insensitive or susceptible to CyHV-3 infection have been revealed.

LINC02535 promotes cell growth in poorly differentiated gastric cancer

Background

Abnormal long non‐coding RNA (lncRNA) expression plays important roles in gastric cancer. However, the functions of many lncRNAs in poorly differentiated gastric cancer (PDGC) remain unknown.

Methods

Three sets of paired tissues from patients with PDGC were used, and transcriptome sequencing was performed, followed by the construction and sequencing of a library and mapping of the reads. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein‐protein interaction (PPI) networks were analysed, and canonical pathway significance was calculated among the differentially expressed genes (DEGs; p < 0.05). Gene expression in 30 paired PDGC specimens and four cell lines was validated through quantitative PCR. Cell proliferation, migration, invasion, apoptosis, and wound healing were analysed.

Results

A total of 499 upregulated DEGs and 627 downregulated DEGs were identified between peritumoral and gastric cancer tissues. The proportions of positive and negative correlations between LINC02535 and the DEGs were 98.40% and 92.66%, respectively, while the Spearman's correlation coefficient was greater than 0.5. The PPI network showed that approximately 73.15% of the top five genes were directly correlated with LINC02535 according to the STRING database. Based on KEGG analysis, the functions of LINC02535 target genes were enriched in signalling pathways related to cancer cell growth. Furthermore, cell function studies showed that LINC02535 upregulation contributed to cell proliferation, migration, invasion, and wound healing and that its inhibition facilitated cell apoptosis.

Conclusion

LINC02535 expression was upregulated in PDGC and contributed to cell proliferation, migration, invasion and wound healing, whereas its inhibition in PDGC facilitated cell apoptosis.

Loc680254 regulates Schwann cell proliferation through Psrc1 and Ska1 as a microRNA sponge following sciatic nerve injury

Peripheral nerve injury triggers sequential phenotype alterations in Schwann cells, which are critical for axonal regeneration. Long noncoding RNAs (lncRNAs) are long transcripts without obvious coding potential. It has been reported that lncRNAs participate in diverse biological processes and diseases. However, the role of lncRNA in Schwann cells and peripheral nerve regeneration is unclear. Here, we identified an lncRNA, loc680254, which is upregulated in rat sciatic nerve after peripheral nerve injury. The loc680254 knockdown inhibits Schwann cell proliferation, enhances apoptosis, and hinders cell cycle, while loc680254 overexpression has the opposite effect. Mechanically, we found that loc680254 might act as a microRNA sponge to regulate the expression of mitosis-related gene, spindle and kinetochore associated complex subunit 1 (Ska1) and proline/serine-rich coiled-coil 1 (Psrc1). Silencing of Psrc1 or Ska1 attenuates the effect of loc680254 overexpression on Schwann cell proliferation. Finally, we repaired the rat sciatic nerve gap with chitosan scaffolds loaded with loc680254-overexpressing Schwann cells and evaluated axon regeneration and functional recovery. Our results indicated that loc680254 is a new potential modulator for Schwann cell proliferation, which could be targeted to develop novel therapeutic strategies for peripheral nerve repair.

Investigation of lncRNA-mRNA co-expression network in ETV6-RUNX1-positive pediatric B-cell acute lymphoblastic leukemia

ETV6/RUNX1 gene fusion is the most common chromosomal translocation abnormality occurred in pediatric B-cell acute lymphoblastic leukemia (B-ALL). Compared with ETV6-RUNX1-negative patients, ETV6-RUNX1-positive patients possess more improved treatment strategies but higher risk to relapse. In this research, the potential gene interaction networks were constructed intending for elucidating the pathogenesis of B-ALL. We performed the weighted gene co-expression network analysis (WGCNA) to assess the involvement of lncRNA-mRNA pairs in B-ALL patients consisting of 24 ETV6-RUNX1-positive patients and 18 ETV6-RUNX1-negative patients and found a module that was significantly associated with positive/negative trait. Gene Ontology analysis showed that mRNAs in this module were enriched in the positive regulation of MAPK cascade, positive regulation of JNK cascade, and myeloid cell differentiation pathway. To further investigate the relationship between lncRNAs and mRNAs in this significant module, we constructed the lncRNA-mRNA co-expression network. 3 lncRNAs (RP11-170J3.2, RP11-135F9.1 and RP1-151B14.9) were found at the core of the lncRNA-mRNA co-expression network, which had the most co-expression connections with mRNAs. And several related mRNAs (ACTN1, TNFRSF21 and NLRP3) had a significant correlation with the patient survival prediction. Our findings may explicate the pathogenesis of B-ALL, and the disease-associated genes could provide clues to find novel biomarkers for prognosis.

Transcriptome Analysis Reveals Differentially Expressed Genes and Long Non-coding RNAs Associated With Fecundity in Sheep Hypothalamus With Different FecB Genotypes

Small-tailed Han sheep, with different FecB genotypes, manifest distinct ovulation rates and fecundities, which are due to differences in reproductive hormones secreted by the hypothalamic-pituitary-ovarian axis. Nevertheless, the function of the hypothalamus against a FecB mutant background on increasing ovulation rate is rarely reported. Therefore, we determined the expression profiles of hypothalamus tissue collected from six wild-type (WW) and six FecB mutant homozygous (BB) ewes at the follicular and luteal phases by whole-transcriptome sequencing. We identified 53 differentially expressed mRNAs (DEGs) and 40 differentially expressed long non-coding RNAs (DELs) between the two estrus states. Functional annotation analysis revealed that one of the DEGs, PRL, was particularly enriched in the hypothalamic function, hormone-related, and reproductive pathways. The lncRNA-target gene interaction networks and KEGG analysis in combination suggest that the lncRNAs LINC-676 and WNT3-AS cis-acting on DRD2 and WNT9B in different phases may induce gonadotropin-releasing hormone (GnRH) secretion. Furthermore, there were differences of regulatory elements and WNT gene family members involved in the follicular-luteal transition in the reproductive process between wild-type (WNT7A) and FecB mutant sheep (WNT9B). We combined the DEG and DEL data sets screened from different estrus states and genotypes. The overlap of these two sets was identified to select the mRNAs and lncRNAs that have major effects on ovulation. Among the overlapping molecules, seven DEGs and four DELs were involved in the follicular-luteal transition regulated by FecB mutation. Functional annotation analysis showed that two DEGs (FKBP5 and KITLG) were enriched in melanogenesis, oxytocin, and GnRH secretion. LINC-219386 and IGF2-AS were highly expressed in the BB ewes compared with WW ewes, modulating their target genes (DMXL2 and IGF2) to produce more GnRH during follicular development, which explains why mutated ewes produced more mature follicles. These results from expression profiling of the hypothalamus with the FecB mutation at different estrus states provide new insights into how the hypothalamus regulates ovulation under the effect of the FecB mutation.

Gene expression profile and long noncoding RNA analysis in Candida albicans insoluble β-glucan-stimulated CD14+ monocytes and THP-1 cells

Emerging evidence suggests that long noncoding RNAs (lncRNAs) play important roles in disease development. However, the roles of lncRNAs in the pathogenesis of Candida albicans (C. albicans) remain unclear. Our study aimed to investigate and characterize the mRNA and lncRNA transcriptomes of CD14⁺ monocytes and THP-1 cells stimulated with insoluble β-glucan by RNA-seq. We identified a total of 10788 differentially expressed (DE) mRNAs and 2021 DE lncRNAs in CD14⁺ monocytes, while 3349 DE mRNAs and 291 DE lncRNAs were observed in THP-1 cells. A total of 808 DE mRNAs and 51 DE lncRNAs overlapped between the two groups. We examined five collectively DE mRNAs and lncRNAs in both cells using quantitative real-time PCR, validating the reliability of the RNA-seq results. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that the 808 DE mRNAs were mostly enriched in the inflammatory response and NF-kappa B signaling pathway, respectively. Next, lncRNA-mRNA coexpression analysis was performed for the 51 DE lncRNAs and the 808 DE mRNAs in the two groups. We chose the common network pairs of the two groups to construct the coexpression network and revealed 97 network pairs comprising 8 dysregulated lncRNAs and 60 dysregulated mRNAs. We found that lncRNA lnc-CCL3L3-1:1 might be involved in the NF-kappa B signaling pathway in C. albicans infection. In conclusion, the aberrantly expressed lncRNAs might play a role in the pathogenesis of C. albicans infection and could be used as therapeutic targets in the future.

LINC00467 Promotes Prostate Cancer Progression via M2 Macrophage Polarization and the miR-494-3p/STAT3 Axis

Background

The long non-coding RNA LINC00467 plays a vital role in many malignancies. Nevertheless, the role of LINC00467 in prostate carcinoma (PC) is unknown. Herein, we aimed to explore the mechanism by which LINC00467 regulates PC progression.

Methods

We used bioinformatics analyses and RT-qPCR to investigate the expression of LINC00467 in PC tissues and cells. The function of LINC00467 in the progression of PC was confirmed by loss-of-function experiments. PC cell proliferation was assessed by CCK-8 and EdU assays. The cell cycle progression of PC cells was examined by flow cytometry. Moreover, Transwell assays were used to investigate the migration and invasion of PC cells. Western blot assays were used to detect the expression of factors associated with epithelial–mesenchymal transition. The interactions of LINC00467 with prostate cancer progression and M2 macrophage polarization were confirmed by RT-qPCR. The subcellular localization of LINC00467 was investigated via the fractionation of nuclear and cytoplasmic RNA. Bioinformatics data analysis was used to predict the correlation of LINC00467 expression with miR-494-3p expression. LINC00467/miR-494-3p/STAT3 interactions were identified by using a dual-luciferase reporter system. Finally, the influence of LINC00467 expression on PC progression was investigated with an in vivo nude mouse model of tumorigenesis.

Results

We established that LINC00467 expression was upregulated in PC tissues and cells. Downregulated LINC00467 expression inhibited PC cell growth, cell cycle progression, migration, and invasion. Downregulated LINC00467 expression similarly inhibited PC cell migration via M2 macrophage polarization. Western blot analysis showed that LINC00467 could regulate the STAT3 pathway. We established that LINC00467 is mainly localized to the cytoplasm. Bioinformatics analysis and rescue experiments indicated that LINC00467 promotes PC progression via the miR-494-3p/STAT3 axis. Downregulated LINC00467 expression was also able to suppress PC tumor growth in vivo.

Conclusions

Our study reveals that LINC00467 promotes prostate cancer progression via M2 macrophage polarization and the miR-494-3p/STAT3 axis.

Correlation AnalyzeR: functional predictions from gene co-expression correlations

BACKGROUND

Co-expression correlations provide the ability to predict gene functionality within specific biological contexts, such as different tissue and disease conditions. However, current gene co-expression databases generally do not consider biological context. In addition, these tools often implement a limited range of unsophisticated analysis approaches, diminishing their utility for exploring gene functionality and gene relationships. Furthermore, they typically do not provide the summary visualizations necessary to communicate these results, posing a significant barrier to their utilization by biologists without computational skills.

RESULTS

We present Correlation AnalyzeR, a user-friendly web interface for exploring co-expression correlations and predicting gene functions, gene-gene relationships, and gene set topology. Correlation AnalyzeR provides flexible access to its database of tissue and disease-specific (cancer vs normal) genome-wide co-expression correlations, and it also implements a suite of sophisticated computational tools for generating functional predictions with user-friendly visualizations. In the usage example provided here, we explore the role of BRCA1-NRF2 interplay in the context of bone cancer, demonstrating how Correlation AnalyzeR can be effectively implemented to generate and support novel hypotheses.

CONCLUSIONS

Correlation AnalyzeR facilitates the exploration of poorly characterized genes and gene relationships to reveal novel biological insights. The database and all analysis methods can be accessed as a web application at https://gccri.bishop-lab.uthscsa.edu/correlation-analyzer/ and as a standalone R package at https://github.com/Bishop-Laboratory/correlationAnalyzeR .

Identification of crucial long non-coding RNAs and mRNAs along with related regulatory networks through microarray analysis in esophageal carcinoma

Esophageal carcinoma (EC) is a tremendous threat to human health and life worldwide. Long non-coding RNAs (lncRNAs) have been identified as crucial players in carcinomas including EC. An in-depth understanding on regulatory networks of lncRNAs contributes to the better management of EC. In this text, 2052 lncRNAs and 3240 mRNAs were found to be differentially expressed in 5 EC tumor tissues versus adjacent normal tissues by microarray analysis. Moreover, 297 carcinoma-related genes were screened out according to pathway and disease annotation analyses. In addition, 410 potential lncRNA-mRNA cis-regulation pairs and 395 lncRNA-mRNA trans-regulation pairs were screened out. Among these genes, 14 trans-regulated and 19 cis-regulated genes were found to be related with carcinomas. Additionally, 42 possible lncRNA-mRNA trans-regulation pairs and 26 cis-regulation pairs were found to be related with carcinomas. Also, 4 differentially expressed transcription factors in EC and lncRNAs possibly regulated by these transcription factors were screened out. Moreover, plenty of common upregulated or downregulated lncRNAs and mRNAs in EC were identified by comparative analysis for our microarray outcomes and previous high-throughput data. Furthermore, we demonstrated that ENST00000437781.1 knockdown inhibited cell proliferation and facilitated cell apoptosis by downregulating SIX homeobox 4 (SIX4) and ENST00000524987.1 knockdown had no influence on anoctamin 1 calcium activated chloride channel (ANO1) expression in EC cells. In conclusion, we identified some crucial lncRNAs and genes along with potential regulatory networks of lncRNAs/genes, deepening our understanding on pathogenesis of EC.

Integrative Analysis of DNA Methylation Data and Transcriptome Data Identified a DNA Methylation-Dysregulated Four-LncRNA Signature for Predicting Prognosis in Head and Neck Squamous Cell Carcinoma

Increasing evidence has demonstrated the crosstalk between DNA epigenetic alterations and aberrant expression of long non-coding RNAs (lncRNAs) during carcinogenesis. However, epigenetically dysregulated lncRNAs and their functional and clinical roles in Head and Neck Squamous Cell Carcinoma (HNSCC) are still not explored. In this study, we performed an integrative analysis of DNA methylation data and transcriptome data and identified a DNA methylation-dysregulated four-lncRNA signature (DNAMeFourLncSig) from 596 DNA methylation-dysregulated lncRNAs using a machine-learning-based feature selection method, which classified the patients of the discovery cohort into two risk groups with significantly different survival including overall survival, disease-specific survival, and progression-free survival. Then the DNAMeFourLncSig was implemented to another two HNSCC patient cohorts and showed similar prognostic values in both. Results from multivariable Cox regression analysis revealed that the DNAMeFourLncSig might be an independent prognostic factor. Furthermore, the DNAMeFourLncSig was substantially correlated with the complete response rate of chemotherapy and may predict chemotherapy response. Functional in silico analysis found that DNAMeFourLncSig-related mRNAs were mainly enriched in cell differentiation, tissue development and immune-related pathways. Overall, our study will improve our understanding of underlying transcriptional and epigenetic mechanisms in HNSCC carcinogenesis and provided a new potential biomarker for the prognosis of patients with HNSCC.

LncRNA MALAT1 Functions as a Competing Endogenous RNA to Regulate BMI1 Expression by Sponging miR-200c/miR-203 in the Control of the Differentiation of Pulp Cells

BACKGROUND

Long non-coding RNAs (lncRNAs) and miRNAs (microRNAs) are considered as key regulators of several biological processes, including dental development. In this study, we explored the lncRNAs and miRNAs which are involved in dental development.

METHOD

Real-time PCR was performed to identify the candidate lncRNAs and miRNAs involved in dental development. Bioinformatics analysis and luciferase assay were carried out to establish the regulatory relationships between MALAT1, miR-203 and miR-200c in dental development.

RESULTS

Among all candidate lncRNAs, only MALAT1 was highly expressed in differentiated human dental pulp cells (hDPCs), and among all candidate miRNAs which are down-regulated in differentiated hDPCs, miR-203, and miR-200c are most decreased. Furthermore, MALAT1 was up-regulated while miR-203 and miR-200c were down-regulated in differentiated hDPCs in a time-dependent manner. MiR-203 and miR-200c were proved to bind to MALAT1. Moreover, BMI1 was identified as a target gene of miR-203 or miR-200c, and BMI1 was time-dependently decreased in hDPCs cultured with odontogenic medium. On the contrary, dentin sialophosphoprotein (DSPP), dentin matrix protein-1 (DMP-1), osteocalcin (OCN), and alkaline phosphatase (ALP), were time-dependently increased in hDPCs cultured with odontogenic medium. Finally, the overexpression of MALAT1 and the knockdown of miR-203/miR-200c both significantly increased the levels of BMI1, DSPP, DMP-1, OCN, and ALP, while the effect of knockdown of miR-203/miR-200c was much stronger than that of the overexpression of MALAT1.

CONCLUSION

Our results demonstrated that MALAT1 functions as a competing endogenous RNA of miR-203 and miR-200c and accordingly promotes BMI1 expression. Therefore, MALAT1 may serve as a biomarker for dental development.

Long non-coding RNAs ENST00000429730.1 and MSTRG.93125.4 are associated with metabolic activity in tuberculosis lesions of sputum-negative tuberculosis patients

Accurate diagnosis of complete inactivation of tuberculosis lesions is still a challenge with respect to sputum-negative tuberculosis. RNA-sequencing was conducted to uncover potential lncRNA indicators of metabolic activity in tuberculosis lesions. Lung tissues with high metabolic activity and low metabolic activity demonstrated by fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography were collected from five sputum-negative tuberculosis patients for RNA-sequencing. Differentially-expressed mRNAs and lncRNAs were identified. Their correlations were evaluated to construct lncRNA-mRNA co-expression network, in which lncRNAs and mRNAs with high degrees were confirmed by quantitative real-time PCR using samples collected from 11 patients. Prediction efficiencies of lncRNA indicators were assessed by receiver operating characteristic curve analysis. Bioinformatics analysis was performed for potential lncRNAs. 386 mRNAs and 44 lncRNAs were identified to be differentially expressed. Differentially-expressed mRNAs in lncRNA-mRNA co-expression network were significantly associated with fibrillar collagen, platelet-derived growth factor binding, and leukocyte migration involved in inflammatory response. Seven mRNAs (C1QB, CD68, CCL5, CCL19, MMP7, HLA-DMB, and CYBB) and two lncRNAs (ENST00000429730.1 and MSTRG.93125.4) were validated to be significantly up-regulated. The area under the curve of ENST00000429730.1 and MSTRG.93125.4 was 0.750 and 0.813, respectively. Two lncRNAs ENST00000429730.1 and MSTRG.93125.4 might be considered as potential indicators of metabolic activity in tuberculosis lesions for sputum-negative tuberculosis.

Identification and analysis of spinal cord injury subtypes using weighted gene co-expression network analysis

Background

Spinal cord injury (SCI) has an immediate and devastating impact on the control over various movements and sensations. However, no effective therapies for SCI currently exist.

Methods

To identify and analyze SCI subtypes, we obtained the expression profile data of the 1,057 genes (889 intersection genes) in GSE45550 using weighted gene co-expression network analysis (WGCNA), and 14 co-expression gene modules were identified. Next, we filtered out the network degree top 10 (degree >80) genes, considered the final key SCI genes. A multifactor regulatory network (105 interaction pairs), consisting of messenger RNAs (mRNAs), long non-coding RNAs (lncRNAs), and transcription factors (TFs) was constructed. This network was involved in the co-expression of key genes. We selected the top 10 regulatory factors (degree >4) as core regulators in the multifactor regulatory network.

Results

The results of functional enrichment analysis of the target gene expressing the core regulatory factor [1,059] showed that these target genes were enriched in pathways for human cytomegalovirus infection, chronic myeloid leukemia, and pancreatic cancer. Further, we used the key genes in the co-expression network to categorize the SCI samples in GSE45550. The expression levels of the top 6 genes (CCNB2, CCNB1, CKS2, COL5A1, KIF20A, and RACGAP1) may act as potential marker genes for different SCI subtypes. On the basis of these different subtypes, 8 SCI core gene CDK1-associated drugs were also found to provide potential therapeutic options for SCI.

Conclusions

These results may provide a novel therapeutic strategy for the treatment of SCI.

Identification of long noncoding RNAs involved in resistance to downy mildew in Chinese cabbage

Brassica downy mildew, a severe disease caused by Hyaloperonospora brassicae, can cause enormous economic losses in Chinese cabbage (Brassica rapa L. ssp. pekinensis) production. Although some research has been reported recently concerning the underlying resistance to this disease, no studies have identified or characterized long noncoding RNAs involved in this defense response. In this study, using high-throughput RNA sequencing, we analyzed the disease-responding mRNAs and long noncoding RNAs in two resistant lines (T12-19 and 12-85) and one susceptible line (91-112). Clustering and Gene Ontology analysis of differentially expressed genes (DEGs) showed that more DEGs were involved in the defense response in the two resistant lines than in the susceptible line. Different expression patterns and proposed functions of differentially expressed long noncoding RNAs among T12-19, 12-85, and 91-112 indicated that each has a distinct disease response mechanism. There were significantly more cis- and trans-functional long noncoding RNAs in the resistant lines than in the susceptible line, and the genes regulated by these RNAs mostly participated in the disease defense response. Furthermore, we identified a candidate resistance-related long noncoding RNA, MSTRG.19915, which is a long noncoding natural antisense transcript of a MAPK gene, BrMAPK15. Via an agroinfiltration-mediated transient overexpression system and virus-induced gene silencing technology, BrMAPK15 was indicated to have a greater ability to defend against pathogens. MSTRG.19915-silenced seedlings showed enhanced resistance to downy mildew, probably because of the upregulated expression of BrMAPK15. This research identified and characterized long noncoding RNAs involved in resistance to downy mildew, laying a foundation for future in-depth studies of disease resistance mechanisms in Chinese cabbage.

Novel lncRNAs Co-Expression Networks Identifies LINC00504 with Oncogenic Role in Luminal A Breast Cancer Cells

Long non-coding RNAs (lncRNAs) are functional transcripts with more than 200 nucleotides. These molecules exhibit great regulatory capacity and may act at different levels of gene expression regulation. Despite this regulatory versatility, the biology of these molecules is still poorly understood. Computational approaches are being increasingly used to elucidate biological mechanisms in which these lncRNAs may be involved. Co-expression networks can serve as great allies in elucidating the possible regulatory contexts in which these molecules are involved. Herein, we propose the use of the pipeline deposited in the RTN package to build lncRNAs co-expression networks using TCGA breast cancer (BC) cohort data. Worldwide, BC is the most common cancer in women and has great molecular heterogeneity. We identified an enriched co-expression network for the validation of relevant cell processes in the context of BC, including LINC00504. This lncRNA has increased expression in luminal subtype A samples, and is associated with prognosis in basal-like subtype. Silencing this lncRNA in luminal A cell lines resulted in decreased cell viability and colony formation. These results highlight the relevance of the proposed method for the identification of lncRNAs in specific biological contexts.

Identification of Infertility-Associated Topologically Important Genes Using Weighted Co-expression Network Analysis

Endometriosis has been associated with a high risk of infertility. However, the underlying molecular mechanism of infertility in endometriosis remains poorly understood. In our study, we aimed to discover topologically important genes related to infertility in endometriosis, based on the structure network mining. We used microarray data from the Gene Expression Omnibus (GEO) database to construct a weighted gene co-expression network for fertile and infertile women with endometriosis and to identify gene modules highly correlated with clinical features of infertility in endometriosis. Additionally, the protein–protein interaction network analysis was used to identify the potential 20 hub messenger RNAs (mRNAs) while the network topological analysis was used to identify nine candidate long non-coding RNAs (lncRNAs). Functional annotations of clinically significant modules and lncRNAs revealed that hub genes might be involved in infertility in endometriosis by regulating G protein-coupled receptor signaling (GPCR) activity. Gene Set Enrichment Analysis showed that the phospholipase C-activating GPCR signaling pathway is correlated with infertility in patients with endometriosis. Taken together, our analysis has identified 29 hub genes which might lead to infertility in endometriosis through the regulation of the GPCR network.

Dynamic changes of transcriptome of fifth-instar spodoptera litura larvae in response to insecticide

Spodoptera litura is a major insect with a cosmopolitan distribution and strong resistance to multiple insecticides. Determining the molecular basis and key candidate genes of the insecticide resistance of S. litura may help in managing this insect. In this study, fifth-instar S. litura larvae were subjected to transcriptome analysis at 6, 12, 24, 48, and 72 h after feeding on an LC20 dose of avermectin. The result showed that genes responding to avermectin changed dynamically with different gene counts and resistance mechanisms at the fifth instar based on a metabolic pathway map. These responses included degrading the insecticide by a series of P450 and glutathione-S-transferase enzymes starting at the 12 h time point, with subsequent increases in the number of genes involved and shifts to TOLL and immune deficiency (IMD) pathways at 48 h after feeding the insecticide. Weighted correlation network analysis (WGCNA) determined a co-expression module related to the avermectin response at 12 and 24 h (r = 0.403, p = 0.0371; r = 0.436, p = 0.023), in which a hub gene (LOC111358940) related to metalloproteinase activity was identified. In addition, Analysis of the genes in the co-expression module further revealed that eight genes encoding UDP-glucuronosyltransferases were directly associated with insecticide response in S. litura. These results provide better understanding of the avermectin response mechanism of S. litura and may be useful in developing improved control strategies for this species.

SUPPLEMENTARY INFORMATION

The online version of this article (10.1007/s13205-021-02651-9) contains supplementary material, which is available to authorized users.

Expression Signature of lncRNAs and mRNAs in Sevoflurane-Induced Mouse Brain Injury: Implication of Involvement of Wide Molecular Networks and Pathways

Sevoflurane, one of the most commonly used pediatric anesthetics, was found to cause developmental neurotoxicity. To understand specific risk groups and develop countermeasures, a better understanding of its mechanisms is needed. We hypothesize that, as in many other brain degeneration pathways, long non-coding RNAs (lncRNAs) are involved in the sevoflurane-induced neurotoxicity. Postnatal day 7 (PD7) mice were exposed to 3% sevoflurane for 6 h. To quantify neurotoxicity in these mice, we (1) detected neural apoptosis through analysis of caspase 3 expression level and activity and (2) assessed long-term learning ability via the Morris water maze at PD60. To elucidate specific mechanisms, profiles of 27,427 lncRNAs and 18,855 messenger RNAs (mRNAs) in mouse hippocampi were analyzed using microarray assays. Sevoflurane-induced abnormal lncRNA and mRNA expression-associated function pathways were predicted by bioinformatic analysis. We found that sevoflurane induced significant neurotoxicity, causing acute neuroapoptosis and abnormal expression of 148 mRNAs and 301 lncRNAs on PD7 in mouse hippocampus. Additionally, exposed mice exhibited impaired memory on PD60. Bioinformatic analysis predicted that the dysregulated mRNAs, which are highly correlated with their co-expressed dysregulated lncRNAs, might be involved in 34 neurodegenerative signaling pathways (e.g., brain cell apoptosis and intellectual developmental disorder). Our study reveals for the first time that neonatal exposure to 3% sevoflurane induces abnormal lncRNA and mRNA expression profiles. These dysregulated lncRNAs/mRNAs form wide molecular networks that might contribute to various functional neurological disease pathways in the hippocampus, resulting in the observed acute apoptosis and impaired long-term memory.

HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine

Pharmacotranscriptomics has become a powerful approach for evaluating the therapeutic efficacy of drugs and discovering new drug targets. Recently, studies of traditional Chinese medicine (TCM) have increasingly turned to high-throughput transcriptomic screens for molecular effects of herbs/ingredients. And numerous studies have examined gene targets for herbs/ingredients, and link herbs/ingredients to various modern diseases. However, there is currently no systematic database organizing these data for TCM. Therefore, we built HERB, a high-throughput experiment- and reference-guided database of TCM, with its Chinese name as BenCaoZuJian. We re-analyzed 6164 gene expression profiles from 1037 high-throughput experiments evaluating TCM herbs/ingredients, and generated connections between TCM herbs/ingredients and 2837 modern drugs by mapping the comprehensive pharmacotranscriptomics dataset in HERB to CMap, the largest such dataset for modern drugs. Moreover, we manually curated 1241 gene targets and 494 modern diseases for 473 herbs/ingredients from 1966 references published recently, and cross-referenced this novel information to databases containing such data for drugs. Together with database mining and statistical inference, we linked 12 933 targets and 28 212 diseases to 7263 herbs and 49 258 ingredients and provided six pairwise relationships among them in HERB. In summary, HERB will intensively support the modernization of TCM and guide rational modern drug discovery efforts. And it is accessible through http://herb.ac.cn/.

Screening of disease-related biomarkers related to neuropathic pain (NP) after spinal cord injury (SCI)

BACKGROUND

Based on the molecular expression level, this paper compares lncRNA and mRNA expressions respectively in peripheral blood samples of the patients after SCI with NP and without NP, and screens disease-related biomarkers related to NP after SCI in peripheral blood samples of patients.

METHOD

The expression spectrum of 25 human peripheral blood samples (12 samples of refractory NP patients after SCI) was downloaded and data were normalized. Screening of GO annotations significantly associated with significant differentially expressed mRNAs and significant involvement of the KEGG pathway. The WGCNA algorithm was used to screen for modules and RNAs that were significantly associated with disease characterization. A co-expression network was constructed to extract the genes involved in the disease pathway from the co-expression network, construct a network of SCI pain-related pathways, and screen important disease-related biomarkers. Quantitative real-time PCR was used to detect the mRNA expression of hub genes.

RESULTS

Data were normalized and re-annotated by detection of platform information, resulting in a total of 289 lncRNA and 18197 mRNAs. Screening resulted in 338 significant differentially expressed RNAs that met the threshold requirements. Differentially expressed RNAs were significantly enriched with the brown and magenta modules. Six KEGG signaling pathways were screened in the co-expression network, and three KEGG pathways with direct neuropathic pain were identified. The expression levels of E2F1, MAX, MITF, CTNNA1, and ADORA2B in the disease group were all significantly upregulated (p < 0.01). Compared with the normal group, the expression of OXTR was upregulated.

CONCLUSION

We speculate that there are 7 genes and 2 lncRNAs directly involved in the pain pathway: E2F1, MAX, MITF, CTNNA1, ADORA2B, GRIK3, OXTR, LINC01119, and LINC02447. These molecules may be important for NP after SCI.

NONCODEV6: an updated database dedicated to long non-coding RNA annotation in both animals and plants

NONCODE (http://www.noncode.org/) is a comprehensive database of collection and annotation of noncoding RNAs, especially long non-coding RNAs (lncRNAs) in animals. NONCODEV6 is dedicated to providing the full scope of lncRNAs across plants and animals. The number of lncRNAs in NONCODEV6 has increased from 548 640 to 644 510 since the last update in 2017. The number of human lncRNAs has increased from 172 216 to 173 112. The number of mouse lncRNAs increased from 131 697 to 131 974. The number of plant lncRNAs is 94 697. The relationship between lncRNAs in human and cancer were updated with transcriptome sequencing profiles. Three important new features were also introduced in NONCODEV6: (i) updated human lncRNA-disease relationships, especially cancer; (ii) lncRNA annotations with tissue expression profiles and predicted function in five common plants; iii) lncRNAs conservation annotation at transcript level for 23 plant species. NONCODEV6 is accessible through http://www.noncode.org/.

Integrated analysis of lncRNA and mRNA transcriptomes reveals the potential regulatory role of lncRNA in kiwifruit ripening and softening

Kiwifruit has gained increasing attention worldwide for its unique flavor and high nutritional value. Rapid softening after harvest greatly shortens its shelf-life and reduces the commercial value. Therefore, it is imperative and urgent to identify and clarify its softening mechanism. This study aimed to analyze and compare the long noncoding RNA (lncRNA) and mRNA expression patterns in ABA-treated (ABA) and room temperature (RT)-stored fruits with those in freshly harvested fruits (CK) as control. A total of 697 differentially expressed genes (DEGs) and 81 differentially expressed lncRNAs (DELs) were identified while comparing ABA with CK, and 458 DEGs and 143 DELs were detected while comparing RT with CK. The Kyoto Encyclopedia of Genes and Genomes analysis of the identified DEGs and the target genes of DELs revealed that genes involved in starch and sucrose metabolism, brassinosteroid biosynthesis, plant hormone signal transduction, and flavonoid biosynthesis accounted for a large part. The co-localization networks, including 38 DEGs and 31 DELs in ABA vs. CK, and 25 DEGs and 25 DELs in RT vs. CK, were also performed. Genes related to fruit ripening, such as genes encoding β-galactosidase, mannan endo-1,4-β-mannosidase, pectinesterase/pectinesterase inhibitor, and NAC transcription factor, were present in the co-localization network, suggesting that lncRNAs were involved in regulating kiwifruit ripening. Notably, several ethylene biosynthesis- and signaling-related genes, including one 1-aminocyclopropane-1-carboxylic acid oxidase gene and three ethylene response factor genes, were found in the co-localization network of ABA vs. CK, suggesting that the promoting effect of ABA on ethylene biosynthesis and fruit softening might be embodied by increasing the expression of these lncRNAs. These results may help understand the regulatory mechanism of lncRNAs in ripening and ABA-induced fruit softening of kiwifruit.

Predicting lincRNA-Disease Association in Heterogeneous Networks Using Co-regularized Non-negative Matrix Factorization

Long intergenic non-coding ribonucleic acids (lincRNAs) are critical regulators for many complex diseases, and identification of disease-lincRNA association is both costly and time-consuming. Therefore, it is necessary to design computational approaches to predict the disease-lincRNA associations that shed light on the mechanisms of diseases. In this study, we develop a co-regularized non-negative matrix factorization (aka Cr-NMF) to identify potential disease-lincRNA associations by integrating the gene expression of lincRNAs, genetic interaction network for mRNA genes, gene-lincRNA associations, and disease-gene associations. The Cr-NMF algorithm factorizes the disease-lincRNA associations, while the other associations/interactions are integrated using regularization. Furthermore, the regularization does not only preserve the topological structure of the lincRNA co-expression network, but also maintains the links “lincRNA → gene → disease.” Experimental results demonstrate that the proposed algorithm outperforms state-of-the-art methods in terms of accuracy on predicting the disease-lincRNA associations. The model and algorithm provide an effective way to explore disease-lncRNA associations.

The landscape of lncRNAs in Cydia pomonella provides insights into their signatures and potential roles in transcriptional regulation

Background

Long noncoding RNAs (lncRNAs) have emerged as an important class of transcriptional regulators in cellular processes. The past decades have witnessed great progress in lncRNA studies in a variety of organisms. The codling moth (Cydia pomonella L.) is an important invasive insect in China. However, the functional impact of lncRNAs in this insect remains unclear. In this study, an atlas of codling moth lncRNAs was constructed based on publicly available RNA-seq datasets.

Results

In total, 9875 lncRNA transcripts encoded by 9161 loci were identified in the codling moth. As expected, the lncRNAs exhibited shorter transcript lengths, lower GC contents, and lower expression levels than protein-coding genes (PCGs). Additionally, the lncRNAs were more likely to show tissue-specific expression patterns than PCGs. Interestingly, a substantial fraction of the lncRNAs showed a testis-biased expression pattern. Additionally, conservation analysis indicated that lncRNA sequences were weakly conserved across insect species, though additional lncRNAs with homologous relationships could be identified based on synteny, suggesting that synteny could be a more reliable approach for the cross-species comparison of lncRNAs. Furthermore, the correlation analysis of lncRNAs with neighbouring PCGs indicated a stronger correlation between them, suggesting potential cis-acting roles of these lncRNAs in the regulation of gene expression.

Conclusions

Taken together, our work provides a valuable resource for the comparative and functional study of lncRNAs, which will facilitate the understanding of their mechanistic roles in transcriptional regulation.

Global Profiling of lncRNAs Expression Responsive to Allopolyploidization in Cucumis

Long non-coding RNAs (lncRNAs) play critical regulatory roles in various biological processes. However, the presence of lncRNAs and how they function in plant polyploidy are still largely unknown. Hence, we examined the profile of lncRNAs in a nascent allotetraploid Cucumis hytivus (S₁₄), its diploid parents, and the F₁ hybrid, to reveal the function of lncRNAs in plant-interspecific hybridization and whole genome duplication. Results showed that 2206 lncRNAs evenly transcribed from all 19 chromosomes were identified in C. hytivus, 44.6% of which were from intergenic regions. Based on the expression trend in allopolyploidization, we found that a high proportion of lncRNAs (94.6%) showed up-regulated expression to varying degrees following hybridization. However, few lncRNAs (33, 2.1%) were non-additively expressed after genome duplication, suggesting the significant effect of hybridization on lncRNAs, rather than genome duplication. Furthermore, 253 cis-regulated target genes were predicted for these differentially expressed lncRNAs in S₁₄, which mainly participated in chloroplast biological regulation (e.g., chlorophyll synthesis and light harvesting system). Overall, this study provides new insight into the function of lncRNAs during the processes of hybridization and polyploidization in plant evolution.

Transcribed ultraconserved region uc.242 is a novel regulator of cardiomyocyte hypertrophy induced by angiotensin II

Cardiomyocyte hypertrophy is a response to stress or hormone stimulation and is characterized by an increase of cardiomyocyte size. Abnormal long non-coding RNA (lncRNA) expression profile has been identified in various cardiovascular diseases. Though some lncRNAs had been reported to participate in regulation of cardiac hypertrophy, the universal lncRNA profile of cardiomyocyte hypertrophy had not been established. In the present study, we aimed to identify the differentially expressed lncRNA-mRNA network in angiotensin II-stimulated cardiomyocytes, and screen the potential lncRNAs involved in regulation of cardiomyocyte hypertrophy. The hypertrophic cardiomyocytes were induced by angiotensin II (0.1 μmol/L) for 48 hours. High-throughput microarray analysis combined with quantitative real-time PCR assay were then performed to screen the differentially expressed lncRNAs and mRNAs. A total of 1577 lncRNAs and 496 mRNAs transcripts were identified differentially expressed in hypertrophic cardiomyocytes. Among them, 59 transcribed ultraconserved non-coding RNAs (T-UCRs) were found by evolutionary conservation analysis. Subsequently, the lncRNA-mRNA coexpression network was constructed based on Pearson's correlation analysis results, including 4 T-UCRs and 215 mRNAs. The results revealed that uc.242 was positively interacted with prohypertrophic genes (Hgf and Tnc). Functional study showed that inhibition of uc.242 dramatically decreased hypertrophic marker expression levels and cardiomyocyte surface area under the condition of angiotensin II stimulation. The expression of Hgf and Tnc was also decreased in cardiomyocytes after silencing of uc.242. Summarily, the present study provided crucial clues to explore therapeutic targets for pathological cardiac hypertrophy.

Prognostic effect of a novel long noncoding RNA signature and comparison with clinical staging systems for patients with hepatitis B virus-related hepatocellular carcinoma after hepatectomy

OBJECTIVES

We aimed to establish a novel prognostic long noncoding RNA (lncRNA) signature for hepatitis B virus-related hepatocellular carcinoma (HBV-HCC) patients after hepatectomy and to validate its prognostic efficacy compared with other clinical staging systems.

METHODS

Expression data of 374 HCC samples were retrieved from The Cancer Genome Atlas (TCGA) database. Cox regression analyses were performed to develop the lncRNA model. The expression levels of lncRNAs were detected by qualitative real-time polymerase chain reaction (qRT-PCR) in HBV-HCC. Then the qRT-PCR-based signature and nomogram were constructed and compared with those of other clinical staging systems in a clinical cohort and qRT-PCR, RNA fluorescent in situ hybridization and comprehensive bioinformatics analyses were conducted.

RESULTS

The signature containing five lncRNAs was constructed through TCGA. This model showed the highest predictive efficacy in patients with HBV-HCC. Compared with normal liver tissues, all lncRNAs were highly expressed in HBV-HCC. A four-lncRNA signature containing LINC01116, DDX11-AS1, LUCAT1 and FIRRE was developed based on the qRT-PCR data in a clinical HBV-HCC patient cohort. A Kaplan-Meier analysis indicated that the low-risk group had significantly longer overall survival than the high-risk group. Additionally, the qRT-PCR-based four-lncRNA formula was an independent prognostic factor and had better predictive efficacy for survival (area under the receiver operating characteristic curve 0.875) compared with other clinical staging systems in HBV-HCC. The lncRNA-mRNA co-expression and enrichment analyses revealed the potential regulatory mechanisms of the lncRNA identified.

CONCLUSION

The four-lncRNA model may be an effective prognostic signature and provides potential prognostic biomarkers and therapeutic targets for HBV-HCC.

Non-coding RNA Expression Patterns of Two Different Teleost Gonad Maturation Stages

Non-coding RNAs (ncRNAs) are involved in several different regulatory pathways including reproduction. In teleost fish, efficacious reproduction is heavily dependent on the completion of the reproductive cycle. The presence of ncRNA, however, and their expression dynamics and putative regulatory role in mature and immature gonads have not yet been extensively explored. Therefore, the abundance of ncRNAs in mature and immature female sharpsnout seabream (Diplodus puntazzo) was investigated. The sharpsnout seabream is a rudimentary hermaphrodite which, in captivity, displays dysfunctions in the gonad maturation process. Our analyses revealed a gonad specific read length distribution with two main peaks representing miRNAs (21-26 nt) and PIWI RNA (27-34 nt). Besides, distinct expression patterns for several ncRNA biotypes including microRNAs (miRNAs), PIWI RNAs (piRNAs), and ribosomal RNAs (rRNAs) were detected. Identified miRNA accounted to 938, corresponding to ~ 13% of obtained transcripts. Among the differential expressed ncRNAs, 10 (~ 7%) were annotated as miRNA, out of which 2 were found in higher abundance in immature gonads (miR-125c and miR-24) and 8 (miR-451, miR-7a, miR-122-1, miR190a, miR129, ENSGACT00000029608, ENSGACT00000029489, and ENSGACT00000029667) were found to be higher expressed in mature gonads. Putative miRNA targets, including long non-coding RNAs (lncRNAs) and genes, are proposed. Target genes are involved in several processes of fish oocyte development, such as steroidogenesis, proteolysis, and apoptosis, and may explain hormone regulation. This study demonstrates a gonad maturation biased ncRNA profile which in turn may support the role of ncRNAs in ovarian physiology and reproductive performance of fish, stressing the specific function of each RNA biotype in oocyte development.

Reconstruction of lncRNA-miRNA-mRNA network based on competitive endogenous RNA reveals functional lncRNAs in skin cutaneous melanoma

BACKGROUND

Human skin cutaneous melanoma is the most common and dangerous skin tumour, but its pathogenesis is still unclear. Although some progress has been made in genetic research, no molecular indicators related to the treatment and prognosis of melanoma have been found. In various diseases, dysregulation of lncRNA is common, but its role has not been fully elucidated. In recent years, the birth of the "competitive endogenous RNA" theory has promoted our understanding of lncRNAs.

METHODS

To identify the key lncRNAs in melanoma, we reconstructed a global triple network based on the "competitive endogenous RNA" theory. Gene Ontology and KEGG pathway analysis were performed using DAVID (Database for Annotation, Visualization, and Integration Discovery). Our findings were validated through qRT-PCR assays. Moreover, to determine whether the identified hub gene signature is capable of predicting the survival of cutaneous melanoma patients, a multivariate Cox regression model was performed.

RESULTS

According to the "competitive endogenous RNA" theory, 898 differentially expressed mRNAs, 53 differentially expressed lncRNAs and 16 differentially expressed miRNAs were selected to reconstruct the competitive endogenous RNA network. MALAT1, LINC00943, and LINC00261 were selected as hub genes and are responsible for the tumorigenesis and prognosis of cutaneous melanoma.

CONCLUSIONS

MALAT1, LINC00943, and LINC00261 may be closely related to tumorigenesis in cutaneous melanoma. In addition, MALAT1 and LINC00943 may be independent risk factors for the prognosis of patients with this condition and might become predictive molecules for the long-term treatment of melanoma and potential therapeutic targets.

Designing a general method for predicting the regulatory relationships between long noncoding RNAs and protein-coding genes based on multi-omics characteristics

MOTIVATION

Long noncoding RNA (lncRNA) has been verified to interact with other biomolecules especially protein-coding genes (PCGs), thus playing essential regulatory roles in life activities and disease development. However, the inner mechanisms of most lncRNA-PCG relationships are still unclear. Our study investigated the characteristics of true lncRNA-PCG relationships and constructed a novel predictor with machine learning algorithms.

RESULTS

We obtained the 307 true lncRNA-PCG pairs from database and found that there are significant differences in multiple characteristics between true and random lncRNA-PCG sets. Besides, 3-fold cross-validation and prediction results on independent test sets show the great AUC values of LR, SVM and RF, among which RF has the best performance with average AUC 0.818 for cross-validation, 0.823 and 0.853 for two independent test sets, respectively. In case study, some candidate lncRNA-PCG relationships in colorectal cancer were found and HOTAIR-COMP interaction was specially exemplified. The proportion of the reported pairs in the predicted positive results was significantly higher than that in negative results (P < 0.05).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Single-cell profiling of long noncoding RNAs and their cell lineage commitment roles via RNA-DNA-DNA triplex formation in mammary epithelium

Long noncoding RNAs (lncRNAs), which are crucial for organ development, exhibit cell-specific expression. Thus, transcriptomic analysis based on total tissue (bulk-seq) cannot accurately reflect the expression pattern of lncRNAs. Here, we used high-throughput single-cell RNA-seq data to investigate the role of lncRNAs using the hierarchical model of mammary epithelium. With our comprehensive annotation of the mammary epithelium, lncRNAs showed much greater cell-lineage specific expression than coding genes. The lineage-specific lncRNAs were functionally correlated with lineage commitment through the coding genes via the cis- and trans-effects of lncRNAs. For the working mechanism, lncRNAs formed a triplex structure with the DNA helix to regulate downstream lineage-specific marker genes. We used lncRNA-Carmn as an example to validate the above findings. Carmn, which is specifically expressed in mammary gland stem cells (MaSCs) and basal cells, positively regulated the Wnt signaling ligand Wnt10a through formation of a lncRNA-DNA-DNA triplex, and thus controlled the stemness of MaSCs. Our study suggests that lncRNAs play essential roles in cell-lineage commitment and provides an approach to decipher lncRNA functions based on single-cell RNA-seq data.

Network analysis of KLF5 targets showing the potential oncogenic role of SNHG12 in colorectal cancer

BACKGROUND

KLF5 is a member of the Kruppel-like factor, subfamily of zinc finger proteins that are involved in cancers. KLF5 functions as a transcription factor and regulates the diverse protein-coding genes (PCGs) in colorectal cancer (CRC). However, the long non-coding RNAs (lncRNAs) regulated by KLF5 in CRC are currently unknown.

METHODS

In this study, we first designed a computational pipeline to determine the PCG and lncRNA targets of KLF5 in CRC. Then we analyzed the motif pattern of the binding regions for the lncRNA targets. The regulatory co-factors of KLF5 were then searched for through bioinformatics analysis. We also constructed a regulatory network for KLF5 and annotated its functions. Finally, one of the KLF5 lncRNA targets, SNHG12, was selected to further explore its expression pattern and functions in CRC.

RESULTS

We were able to identify 19 lncRNA targets of KLF5 and found that the motifs of the lncRNA binding sites were GC-enriched. Next, we pinpointed the transcription factors AR and HSF1 as the regulatory co-factors of KLF5 through bioinformatics analysis. Then, through the analysis of the regulatory network, we found that KLF5 may be involved in DNA replication, DNA repair, and the cell cycle. Furthermore, in the cell cycle module, the SNHG12 up-regulating expression pattern was verified in the CRC cell lines and tissues, associating it to CRC invasion and distal metastasis. This indicates that SNHG12 may play a critical part in CRC tumorigenesis and progression. Additionally, expression of SNHG12 was found to be down-regulated in CRC cell lines when KLF5 expression was knocked-down by siRNA; and a strong correlation was observed between the expression levels of SNHG12 and KLF5, further alluding to their regulatory relationship.

CONCLUSIONS

In conclusion, the network analysis of KLF5 targets indicates that SNHG12 may be a significant lncRNA in CRC.

lncRNAs-mRNAs Co-Expression Network Underlying Childhood B-Cell Acute Lymphoblastic Leukaemia: A Pilot Study

Simple Summary

Acute lymphoblastic leukemia (ALL) is one of the most common childhood cancers. The ALL onset involves abnormal proliferation and arrest of differentiation of B or T cell progenitors. Recently, long non–coding RNAs (lncRNAs) gained great interest in the B–ALL leukemogenesis, however, so far few “omic” studies investigate lncRNAs and protein–coding gene networks. In our retrospective study, we conceived an integrated bioinformatic approach, by using NGS platform, to discover lncRNAs strongly correlated with aberrantly expressed protein–coding genes. We provided dysregulated lncRNA–mRNA pairs potentially underlying B–ALL pathogenesis. Diagnosis incidence peak of ALL appears approximatively between 1 and 19 years old. lncRNAs may be of clinical utility as non–invasive biomarker for B–ALL onset or therapy response in support of precision medicine. The identification of lncRNA as key regulators in B–ALL could lead to the identification of the altered pathways able to sustain the leukemic growth.

Abstract

Long non–coding RNAs (lncRNAs) are emerging as key gene regulators in the pathogenesis and development of various cancers including B lymphoblastic leukaemia (B–ALL). In this pilot study, we used RNA–Seq transcriptomic data for identifying novel lncRNA–mRNA cooperative pairs involved in childhood B–ALL pathogenesis. We conceived a bioinformatic pipeline based on unsupervised PCA feature extraction approach and stringent statistical criteria to extract potential childhood B–ALL lncRNA signatures. We then constructed a co–expression network of the aberrantly expressed lncRNAs (30) and protein–coding genes (754). We cross–validated our in–silico findings on an independent dataset and assessed the expression levels of the most differentially expressed lncRNAs and their co–expressed mRNAs through ex vivo experiments. Using the guilt–by–association approach, we predicted lncRNA functions based on their perfectly co–expressed mRNAs (Spearman’s correlation) that resulted closely disease–associated. We shed light on 24 key lncRNAs and their co–expressed mRNAs which may play an important role in B–ALL pathogenesis. Our results may be of clinical utility for diagnostic and/or prognostic purposes in paediatric B–ALL management.

Transcriptomic and functional analyses uncover the regulatory role of lncRNA000170 in tomato multicellular trichome formation

Trichomes are universal specific structures originating from nearly all terrestrial plants. Although quantities of long non-coding RNAs (lncRNAs) have been identified in many plant species, the role of lncRNAs in trichome formation still remains unknown. Here, we identified a total of 1303 lncRNAs in the young stems of woolly mutant LA3560 (Wo) and its non-woolly segregants (WT). Out of these lncRNAs, 86 lncRNAs were obviously upregulated in Wo and 110 lncRNAs were downregulated. We determined that seven lncRNAs were highly expressed in stem trichomes compared to trichome-free stems and several other tissues of LA3560 by a quantitative reverse transcriptase-polymerase chain reaction, including lncRNA000746, lncRNA000170, lncRNA000277, lncRNA000774, lncRNA000756, lncRNA000100, and lncRNA000898. Transgenic experiments revealed that overexpression of lncRNA000170 inhibited type I trichome formation on the lower stems of the adult transgenic plants. We further determined that lncRNA000170 was transcribed from the complementary strand of Solyc10g006360, for which expression can be induced by lncRNA000170 in its overexpression lines and woolly mutants. Solyc10g006360 overexpression also caused type I trichome decrease. In addition, several trichome regulators, such as Wo, H, SlCycB2, and SlCycB3, were markedly downregulated in lncRNA000170 overexpression lines. These findings demonstrate that lncRNA000170 may be involved in the regulatory pathway mediated by these trichome regulators.

Long Non-coding RNA Derived from lncRNA-mRNA Co-expression Networks Modulates the Locust Phase Change

Long non-coding RNAs (lncRNAs) regulate various biological processes ranging from gene expression to animal behavior. Although protein-coding genes, microRNAs, and neuropeptides play important roles in the regulation of phenotypic plasticity in migratory locust, empirical studies on the function of lncRNAs in this process remain limited. Here, we applied high-throughput RNA-seq to compare the expression patterns of lncRNAs and mRNAs in the time course of locust phase change. We found that lncRNAs responded more rapidly at the early stages of phase transition. Functional annotations demonstrated that early changed lncRNAs employed different pathways in isolation and crowding phases to cope with changes in the population density. Two overlapping hub lncRNA loci in the crowding and isolation networks were screened for functional verification. One of them, LNC1010057, was validated as a potential regulator of locust phase change. This work offers insights into the molecular mechanism underlying locust phase change and expands the scope of lncRNA functions in animal behavior.

Clinical significance of long non-coding RNA DUXAP8 and its protein coding genes in hepatocellular carcinoma

Backgrounds: Hepatocellular carcinoma (HCC) is a lethal malignancy worldwide that is difficult to diagnose during the early stages and its tumors are recurrent. Long non-coding RNAs (lncRNAs) have increasingly been associated with tumor biomarkers for diagnosis and prognosis. This study attempts to explore the potential clinical significance of lncRNA DUXAP8 and its co-expression related protein coding genes (PCGs) for HCC.

Method: Data from a total of 370 HCC patients from The Cancer Genome Atlas were utilized for the analysis. DUXAP8 and its top 10 PCGs were explored for their diagnostic and prognostic implications for HCC. A risk score model and nomogram were constructed for prognosis prediction using prognosis-related genes and DUXAP8. Molecular mechanisms of DUXAP8 and its PCGs involved in HCC initiation and progression were investigated. Then, potential target drugs were identified using genome-wide DUXAP8-related differentially expressed genes in a Connectivity Map database.

Results: The top 10 PCGs were identified as: RNF2, MAGEA1, GABRA3, MKRN3, FAM133A, MAGEA3, CNTNAP4, MAGEA6, MALRD1, and DGKI. Diagnostic analysis indicated that DUXAP8, MEGEA1, MKRN3, and DGKI show diagnostic implications (all area under curves ≥0.7, p≤0.05). Prognostic analysis indicated that DUXAP8 and RNF2 had prognostic implications for HCC (adjusted p=0.014 and 0.008, respectively). The risk score model and nomogram showed an advantage for prognosis prediction. A total of 3 target drugs were determined: cinchonine, bumetanide and amiprilose and they may serve as potential therapeutic targets for HCC.

Conclusion: Functioning as an oncogene, DUXAP8 is overexpressed in tumor tissue and may serve as both a diagnostic and prognosis biomarker for HCC. MEGEA1, MKRN3, and DGKI maybe potential diagnostic biomarkers and DGKI may also be potentially prognostic biomarkers for HCC.

Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection

Introduction

Peripheral blood (PB) molecular patterns characterizing the different effector immune pathways driving distinct kidney rejection types remain to be fully elucidated. We hypothesized that transcriptome analysis using RNA sequencing (RNAseq) in samples of kidney transplant patients would enable the identification of unique protein-coding and noncoding genes that may be able to segregate different rejection phenotypes.

Methods

We evaluated 37 biopsy-paired PB samples from the discovery cohort, with stable (STA), antibody-mediated rejection (AMR), and T cell-mediated rejection (TCMR) by RNAseq. Advanced machine learning tools were used to perform 3-way differential gene expression analysis to identify gene signatures associated with rejection. We then performed functional in silico analysis and validation by Fluidigm (San Francisco, CA) in 62 samples from 2 independent kidney transplant cohorts.

Results

We found 102 genes (63 coding genes and 39 noncoding genes) associated with AMR (54 upregulated), TCMR (23 upregulated), and STA (25 upregulated) perfectly clustered with each rejection phenotype and highly correlated with main histologic lesions (ρ = 0.91). For the genes associated with AMR, we found enrichment in regulation of endoplasmic reticulum stress, adaptive immunity, and Ig class-switching. In the validation, we found that the SIGLEC17P pseudogene and 9 SIGLEC17P-related coding genes were highly expressed among AMR but not in TCMR and STA samples.

Conclusions

This analysis identifies a critical gene signature in PB in kidney transplant patients undergoing AMR, sufficient to differentiate them from patients with TCMR and immunologically quiescent kidney allografts. Our findings provide the basis for new studies dissecting the role of noncoding genes in the pathophysiology of kidney allograft rejection and their potential value as noninvasive biomarkers of the rejection process.

Identification and characterization of long noncoding RNAs provide insight into the regulation of gene expression in response to heat stress in rainbow trout (Oncorhynchus mykiss)

Rainbow trout are typical cold-water fish species. However, with the intensification of global warming, high temperatures have severely restricted the development of aquaculture during the summer. Understanding the molecular regulatory mechanisms of rainbow trout responses to heat stress will be beneficial for alleviating heat stress-related damage. In this study, we performed RNA-seq of liver tissues from rainbow trout under heat stress (24 °C) and control conditions (18 °C) to identify lncRNAs and target genes by strand-specific library. Changes in nonspecific immune parameters revealed that a strong stress response occurred in rainbow trout at 24 °C. More than 658 million filtered reads and 5916 lncRNAs were identified from six libraries. A total of 927 novel lncRNAs were identified, and 428 differentially expressed lncRNAs were screened with stringent thresholds. The RNA-seq results were verified by RT-qPCR. In addition, a regulatory network of lncRNA-mRNA functional interactions was constructed, and the potential antisense, cis and trans targets of lncRNAs were predicted. GO and KEGG enrichment analyses showed that many target genes involved in maintenance of homeostasis or adaptation to stress and stimuli were highly induced under heat stress. Several regulatory pathways were also found to be involved in heat stress, including the thyroid hormone signaling pathway, the PI3K-Akt signaling pathway, and the estrogen signaling pathway, among others. These results broaden our understanding of lncRNAs associated with heat stress and provide new insights into the lncRNA mediated regulation of the rainbow trout heat stress response.

CORAZON: a web server for data normalization and unsupervised clustering based on expression profiles

Objective

Data normalization and clustering are mandatory steps in gene expression and downstream analyses, respectively. However, user-friendly implementations of these methodologies are available exclusively under expensive licensing agreements, or in stand-alone scripts developed, reflecting on a great obstacle for users with less computational skills.

Results

We developed an online tool called CORAZON (Correlations Analyses Zipper Online), which implements three unsupervised learning methods to cluster gene expression datasets in a friendly environment. It allows the usage of eight gene expression normalization/transformation methodologies and the attribute’s influence. The normalizations requiring the gene length only could be performed to RNA-seq, meanwhile the others can be used with microarray and/or NanoString data. Clustering methodologies performances were evaluated through five models with accuracies between 92 and 100%. We applied our tool to obtain functional insights of non-coding RNAs (ncRNAs) based on Gene Ontology enrichment of clusters in a dataset generated by the ENCODE project. The clusters where the majority of transcripts are coding genes were enriched in Cellular, Metabolic, Transports, and Systems Development categories. Meanwhile, the ncRNAs were enriched in the Detection of Stimulus, Sensory Perception, Immunological System, and Digestion categories. CORAZON source-code is freely available at https://gitlab.com/integrativebioinformatics/corazon and the web-server can be accessed at http://corazon.integrativebioinformatics.me.

Identification of functional long non-coding RNAs in gastric cancer by bioinformatics analysis

Long non-coding RNAs (lncRNAs) have been proven to play important roles in various cancers, including gastric cancer (GC). However, detailed knowledge about lncRNAs in GC is limited. Therefore we carried out an in-depth study of public data and found 83 differently expressed lncRNAs in GC. To further confirm the target genes of these lncRNAs, we constructed a co-expression network between lncRNAs and mRNAs and found three lncRNAs (MBNL1-AS1, HAND2-AS1 and MIR100HG) were at the core of the network. By coalition analysis of clinical information and the three lncRNAs' expression level from The Cancer Genome Atlas (TCGA) and GSE15459 data sets, we found MIR100HG could be a potential prognostic factor. Clinical samples showed patients with higher MIR100HG expression had poorer prognosis, and further experiments demonstrated that MIR100HG was associated with proliferation, migration and invasion of GC cells. Hopefully, MIR100HG might be considered as a novel prognostic factor and biomarker for GC.

Comprehensive Analysis of Differentially Expressed lncRNAs in Gastric Cancer

Gastric cancer (GC) is the fourth most common malignant tumor. The mechanism underlying GC occurrence and development remains unclear. Previous studies have indicated that long non-coding RNAs (lncRNAs) are significantly associated with gastric cancer, but a systematic understanding of the role of lncRNAs in gastric cancer is lacking. In recent years, with the development of next-generation sequencing technology, tens of thousands of lncRNAs have been discovered. However, a large number of unannotated lncRNAs remain unidentified in different tissues, including potential gastric cancer-related lncRNAs. In this study, RNA sequencing (RNA-seq) data from 16 samples of eight gastric cancer patients were obtained and analyzed. A total of 1,854 previously unannotated lncRNAs were identified by ab initio assembly, and 520 differentially expressed lncRNAs were validated in the TCGA expression dataset. Methylation and copy number variation (CNV) array data from the same sample were integrated in the analysis. Changes in DNA methylation levels and CNVs may be responsible for the differential expression of 91 lncRNAs. Differentially expressed lncRNAs were enriched in coexpressed clusters of genes related to functions such as cell signaling, cell cycle, immune response, metabolic processes, angiogenesis, and regulation of retinoic acid (RA) receptors. Finally, a differentially expressed lncRNA, AC004510.3, was identified as a potential biomarker for the prediction of the overall survival of gastric cancer patients.

Identification of a prognostic LncRNA signature for ER-positive, ER-negative and triple-negative breast cancers

PURPOSE

The development of multi-gene signatures has led to improvements in identification of breast cancer patients at high risk of recurrence. The prognostic power of commercially available gene signatures is mostly restricted to estrogen receptor (ER)-positive breast cancer. On the contrary, immune-related gene signatures predict prognosis only in ER-negative breast cancer. This study aimed to develop a better prognostic signature for breast cancer.

METHODS

The expressions of long non-coding RNA (lncRNA) genes from 30 independent microarray datasets with a total of 4813 samples were analyzed. A prognostic lncRNA signature was developed based on likelihood-ratio Cox regression analysis. Survival analysis was used to compare the prognostic efficiencies of our signature and 10 previously reported prognostic gene signatures.

RESULTS

Cox regression analysis on 30 independent datasets showed that the 6-lncRNA signature identified in this study performed as well as five commercially available signatures in recurrence prediction for ER-positive breast cancer. In ER-negative breast cancer, this lncRNA signature was as prognostic as three immune-related gene signatures. Moreover, our lncRNA signature also demonstrated a good capacity to predict recurrence risk for triple-negative breast cancer. Function analysis showed that several lncRNAs in this signature were probably involved in cell proliferation and immune processes.

CONCLUSIONS

A six-LncRNA signature was identified that is prognostic for ER-positive, ER-negative, and triple-negative breast cancers and thus deserves further validation in prospective studies.

Construction and analysis of a lncRNA-miRNA-mRNA network based on competitive endogenous RNA reveal functional lncRNAs in oral cancer

Background

A growing evidence suggests that long non-coding RNAs (lncRNAs) can function as a microRNA (miRNA) sponge in various diseases including oral cancer. However, the pathophysiological function of lncRNAs remains unclear.

Methods

Based on the competitive endogenous RNA (ceRNA) theory, we constructed a lncRNA-miRNA-mRNA network in oral cancer with the human expression profiles GSE74530 from the Gene Expression Omnibus (GEO) database. We used topological analysis to determine the hub lncRNAs in the regulatory ceRNA network. Then, function enrichment analysis was performed using the clusterProfiler R package. Clinical information was downloaded from The Cancer Genome Atlas (TCGA) database and survival analysis was performed with Kaplan-Meier analysis.

Results

A total of 238 potential co-dysregulated competing triples were obtained in the lncRNA-associated ceRNA network in oral cancer, which consisted of 10 lncRNA nodes, 41 miRNA nodes and 122 mRNA nodes. Additionally, we found lncRNA HCG22 exhibiting superior potential as a diagnostic and prognostic marker of oral cancer.

Conclusions

Our findings provide novel insights to understand the ceRNA regulation in oral cancer and identify a novel lncRNA as a potential molecular biomarker.

LncRNA and mRNA expression profiles reveal the potential roles of lncRNA contributing to regulating dural penetration in clival chordoma

Chordoma is a rare bone cancer originating from embryologic notochordal remnants. Clival chordomas show different dural penetration ability, with serious dural penetration exhibiting poorer prognosis. The molecular mechanism of dural penetration is not clear. We analyzed lncRNA and mRNA profiles in 12 chordoma patients with different degrees of dural penetration using expression microarrays. The differentially expressed lncRNAs and mRNAs were used to construct a lncRNA-mRNA co-expression network. LncRNAs were classified into lincRNA, enhancer-like lncRNA, or antisense lncRNA. Biological functions for lncRNAs were predicted according to the lncRNA-mRNA network and adjacent coding genes by pathway analysis. The 2760 lncRNAs and 3988 mRNAs were differentially expressed in chordomas between two groups of patients with and without dural penetration. Possible pathway involvement of the significance among the 55 lncRNAs located in the lncRNA-mRNA network, 24 lincRNAs, 7 enhancer-like lncRNAs, and 14 antisense lncRNAs include cell adhesion, metastasis, invasion, proliferation, and apoptosis. Expression of 10 lncRNAs and mRNAs, and epidermal growth factor mRNA with two identified lncRNAs were subsequently verified by qRT-PCR in chordoma tissues. Our report predicts the biological functions of many lncRNAs which may be used as diagnostic and prognostic biomarkers as well as therapeutic targets during the process of dural penetration in chordoma.