Identification of Novel Prognostic Long Non-coding RNAs in Lung Adenocarcinoma Using WGCNA Analysis

Long non-coding RNAs play crucial role in the tumorigenesis of lung adenocarcinoma (LUAD). However, the function of a large number of lncRNAs in LUAD has not been investigated yet. Weighted gene correlation network analysis (WGCNA) was applied to construct the co-expression module in the TCGA-LUAD cohort. Protein-protein interaction (PPI) network was used to explore the relationship of genes in the key module. The function of the key module on the prognosis in LUAD was analyzed using GO and KEGG analysis. Finally, we constructed the mRNA-lncRNA co-expression network in the key module to identify the hub lncRNAs that play crucial role in the prognosis in LUAD. The most highly expressed 2500 mRNAs and 2500 lncRNAs in the TCGA-LUAD cohort were clustered into 21 modules. After analyzing the correlation between the module and prognostic clinical traits, the Tan module, consisting of 130 genes, was selected as the key module on the prognosis in LUAD. And then, we found that genes in the key module were majorly enriched in ten multiple signaling pathways. Subsequently, we constructed the mRNA-lncRNA co-expression network based on the genes in the key module. Finally, we identified three lncRNAs and nineteen mRNAs that could be the promising prognostic biomarkers for LUAD. We identified three lncRNAs (MIR99AHG, ADAMTS9-AS2, and AC037459.2) and nineteen mRNAs as potential prognostic biomarkers in LUAD, which provided new insight for prognosis monitoring and therapy development in LUAD.

Expression profile analysis of LncRNAs and mRNAs in pre-receptive endometrium of women with polycystic ovary syndrome undergoing in vitro fertilization-embryo transfer

BACKGROUND

To compare the expression levels of long non-coding RNA (lncRNA) and messenger RNA (mRNA) in pre-receptive endometrium between patients with Polycystic Ovary Syndrome (PCOS)and normal ovulation undergoing in vitro fertilization-embryo transfer (IVF-ET).

METHODS

Endometrial tissues were collected with endometrial vacuum curette in pre-receptive phase (3 days after oocytes retrieval) from PCOS and control groups. LncRNAs and mRNAs of endometrium were identified via RNA sequencing and alignments. A subset of 9 differentially expressed lncRNAs and 11 mRNAs were validated by quantitative reverse transcription polymerase chain reaction(qRT-PCR)in 22 PCOS patients and 18 ovulation patients. The function of mRNAs with differential expression patterns were explored using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG).

RESULTS

We found out 687 up-regulated and 680 down-regulated mRNAs, as well as 345 up-regulated and 63 down-regulated lncRNAs in the PCOS patients in contrast to normal ovulation patients. qRT-PCR was used to detect the expression of 11 mRNAs, and validated that the expression of these 6 mRNAs CXCR4, RABL6, OPN3, SYBU, IDH1, NOP10 were significantly elevated among PCOS patients, and the expression of ZEB1 was significantly decreased. qRT-PCR was performed to detect the expression of 9 lncRNAs, and validated that the expression of these 7 lncRNAs IDH1-AS1, PCAT14, FTX, DANCR, PRKCQ-AS1, SNHG8, TPT1-AS1 were significantly enhanced among PCOS patients. Bioinformatics analysis showed that differentially expressed genes (DEGs) involved KEGG pathway were tyrosine metabolism, PI3K-Akt pathway, metabolic pathway, Jak-STAT pathway, pyruvate metabolism, protein processing in endoplasmic reticulum, oxidative phosphorylation and proteasome. The up-regulation of GO classification was involved in ATP metabolic process, oxidative phosphorylation, RNA catabolic process, and down-regulation of GO classification was response to corticosteroid, steroid hormone, and T cell activation.

CONCLUSION

Our results determined the characteristics and expression profile of endometrial lncRNAs and mRNAs in PCOS patients in pre-receptive phase, which is the day 3 after oocytes retrival. The possible pathways and related genes of endometrial receptivity disorders were found, and those lncRNAs may be developed as a predictive biomarker of endometrium in pre-receptive phase.

A Co-Expression Network Reveals the Potential Regulatory Mechanism of lncRNAs in Relapsed Hepatocellular Carcinoma

Background

The mechanistic basis for relapsed hepatocellular carcinoma (HCC) remains poorly understood. Recent research has highlighted the important roles of long non-coding RNAs (lncRNAs) in HCC. However, there are only a few studies on the association between lncRNAs and HCC relapse.

Methods

Differentially expressed lncRNAs and mRNAs between a primary HCC group and relapsed HCC group were identified using the edge R package to analyze the GSE101432 dataset. The differentially expressed lncRNAs and mRNAs were used to construct a lncRNA–mRNA co-expression network. Weighted gene co-expression network analysis followed by Gene Ontology (GO) enrichment analyses were conducted on the database. Furthermore, correlation and survival analyses were performed using The Cancer Genome Atlas database, and expression in the clinical samples was verified by qRT-PCR. Thereafter, we inputted the genes from the two groups into the HCC TNM stage and tumor grade database from TCGA. Finally, we performed Kaplan–Meier survival analysis on the lncRNAs related to relapsed HCC.

Results

In this study, lncRNAs and mRNAs associated with HCC relapse were identified. Two gene modules were found to be closely linked to this. The GO terms in the yellow and black modules were related to cell proliferation, differentiation, and survival, as well as some transcription-related biological processes. Through qRT-PCR, we found that the expression levels of LINC00941 and LINC00668 in relapsed HCC were higher than those in primary HCC. Further, mRNA levels of LOX, OTX1, MICB, NDUFA4L2, BAIAP2L2, and KCTD17 were changed in relapsed HCC compared to levels in primary HCC. In addition, we verified that these genes could predict the overall survival and recurrence-free survival of HCC. Moreover, we found that LINC00668 and LINC00941 could affect tumor grade and TNM stages. In total, we identified and validated two lncRNAs (LINC00941 and LINC00668) and six mRNAs (LOX, MICB, OTX1, BAIAP2L2, KCTD17, NDUFA4L2) associated with HCC relapse.

Conclusion

In summary, we identified the key gene modules and central genes associated with relapsed HCC and constructed lncRNA–mRNA networks related to this. These genes are likely to have potential prognostic value for relapsed HCC and might shed new light on novel biomarkers or diagnostic targets for relapsed HCC.

Identification of Key Modules and Hub Genes Involved in Esophageal Squamous Cell Carcinoma Tumorigenesis Using WCGNA

Introduction:

The mechanistic basis for the development of esophageal squamous cell carcinoma (ESCC) remains poorly understood. The goal of the present study was thus to characterize mRNA and long noncoding RNA (lncRNA) expression profiles associated with ESCC in order to identify key hub genes associated with the pathogenesis of this cancer.

Materials and Methods:

The GSE26866 and GSE45670 datasets from the Gene Expression Omnibus (GEO) database were used to conduct a weighted gene co-expression network analysis (WGCNA), after which Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Cytoscape was additionally used to construct lncRNA-mRNA networks, after which hub genes were identified and validated through the assessment of TCGA datasets and clinical samples.

Results:

Two gene modules were found to be closely linked to ESCC tumorigenesis. These genes were enriched in cell cycle, MAPK signaling, JAK-STAT signaling, pyrimidine metabolism, arachidonic acid metabolism, and P53 signaling pathway activity, all of which are directly linked with the development of cancer. In total, we identified and validated 9 hub genes associated with ESCC (DDX18, DNMT1, NCAPG, WDHD1, PRR11, VOPP1, ZKSCAN5, LC35C2, and PHACTR2).

Conclusion:

In summary, we identified key gene modules and hub genes associated with ESCC development, and we constructed a lncRNA-mRNA network pertaining to this cancer type. These results provide a foundation for future research regarding the mechanistic basis of ESCC.

A Newly Identified lncBCAS1-4_1 Associated With Vitamin D Signaling and EMT in Ovarian Cancer Cells

Long noncoding RNAs (lncRNAs) were identified rapidly due to their important role in many biological processes and human diseases including cancer. 1α,25-dihydroxyvitamin D3 [1α,25(OH)₂D₃] and its analogues are widely applied as preventative and therapeutic anticancer agents. However, the expression profile of lncRNAs regulated by 1α,25(OH)₂D₃ in ovarian cancer remains to be clarified. In the present study, we found 606 lncRNAs and 102 mRNAs that showed differential expression (DE) based on microarray data. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the DE genes were mainly enriched in TGF-β, MAPK, Ras, PI3K-Akt, and Hippo signaling pathways, as well as the vitamin D-related pathway. We further assessed the potential lncRNAs that linked vitamin D signaling with EMT, and lncBCAS1-4_1 was identified in the first time. Moreover, we found that the most upregulated lncBCAS1-4_1 showed 75% same transcripts with CYP24A1 (metabolic enzyme of 1α,25(OH)₂D₃). Finally, the lncBCAS1-4_1 gain-of-function cell model was established, which demonstrated that the knockdown of lncBCAS1-4_1 inhibited the proliferation and migration of ovarian cancer cells. Furthermore, lncBCAS1-4_1 could resist the antitumor effect of 1α,25(OH)₂D₃, which was associated with upregulated ZEB1. These data provide new evidences that lncRNAs served as a target for the antitumor effect of 1α,25(OH)₂D₃.

Identification and expression analysis of lncRNA in seven organs of Rhinopithecus roxellana

Long non-coding RNA (lncRNA) represents a new direction to identify expression profiles and regulatory mechanisms in various organisms. Here, we report the first dataset of lncRNAs of the golden snub-nosed monkey (GSM), including 12,557 putative lncRNAs identified from seven organs. Compared with mRNA, GSM lncRNA had fewer exons and isoforms, and longer length. LncRNA showed more obvious tissue-specific expression than mRNA. However, for the top ten most abundant genes in each organ, mRNAs expression was more tissue-specific than lncRNAs. By identification of specifically expressed lncRNAs and mRNAs in each organ, it indicates that the expression of SEG-lncRNA (specifically expressed lncRNA) and SEG-mRNA (specifically expressed mRNA) had high correlation. In particular, combined our lncRNA and mRNA data, we identified 92 heart SEG-lncRNAs targeted ten mRNA genes in the oxidative phosphorylation pathway and upregulated the expression of these target genes such as ND4, ATP6, and ATP8. These may contribute to GSM adaption to its high-elevation environment. We also identified 171 liver SEG-lncRNAs, which targeted 27 genes associated with the metabolism of xenobiotics and leaded to high expression of these target genes in liver. These lncRNAs may play important roles in GSM adaptation to a folivory diet.

Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer

The molecular mechanism of bone metastasis in breast cancer is largely unknown. Herein, we aimed to identify the key genes and long non-coding RNAs (lncRNAs) related to the bone metastasis of breast cancer using a bioinformatics approach. We screened differentially expressed genes and lncRNAs between normal breast and breast cancer bone metastasis samples using the GSE66206 dataset from the Gene Expression Omnibus. We also constructed a differentially expressed lncRNA-mRNA interaction network and analyzed the node degrees to identify the driving genes. After finding potential pathogenic modules of breast cancer bone metastasis, we identified breast cancer bone metastasis-related modules and functional enrichment analysis of the genes and lncRNAs in the modules. Based on the above analysis, we constructed a differentially expressed lncRNA-mRNA network related to bone metastasis in breast cancer and identified core driver genes, including BNIP3 and the lncRNA RP11-317-J19.1. The role of core driver genes and lncRNAs in the network implies their biological functions in regulating bone development and remodeling. Thus, targeting the core driver genes and lncRNAs in the network may be a promising therapeutic strategy to manage bone metastasis.

Integrated analysis of long noncoding RNAs and mRNA expression profiles reveals the potential role of lncRNAs in early stage of post-peripheral nerve injury in Sprague-Dawley rats

The regulatory role of lncRNAs in the early stage post peripheral nerve injury (PNI) is not yet clear. In this study, next-generation sequencing was used to perform deep sequencing on normal sciatic nerves (control) and lesional tissues derived on the 4th (D4) and 7th days (D7) after sciatic nerve injury in rats. Time-point unique differentially expressed lncRNAs (DElncRNAs) were analyzed for functional enrichment. The results showed that 776 DElncRNAs were unique to D4, and their functions were mainly enriched in wound healing, phosphatase binding and MAPK signaling pathways; 317 DElncRNAs were unique to D7, and their functions were mainly enriched in ion transmembrane transporter channel activity; 579 DElncRNAs were shared by these two days, and their functions were mainly enriched in axongenesis, the PI3K-Akt signaling pathway and cell cycle. Furthermore, lncRNA-mRNA interaction networks were constructed in functions or pathways with a high enrichment rate. Finally, 3 mRNAs and 4 lncRNAs in the axongenesis interaction network were selected, and their expression levels were verified by RT-qPCR. This study preliminarily revealed the regulatory role of lncRNAs at different time points in the early stage post PNI, which provides potential targets for basic research and clinical treatment of PNI.

Dihydroartemisinin-regulated mRNAs and lncRNAs in chronic myeloid leukemia

Chronic myelocytic leukemia (CML) is characterized by increased and unregulated growth of predominantly myeloid cells in the bone marrow, and accumulation of these cells in blood. We investigated the effects of an anti-malarial drug, dihydroartemisinin (DHA), on K562 CML cells. We identified 34 mRNAs and eight lncRNAs dysregulated following DHA treatment in pure and hemin-induced K562 cells. Up- or downregulation of these potential DHA targets increased with increasing DHA concentration. We also constructed and analyzed a DHA-related mRNA-lncRNA regulation network in K562 cells, and found that four DHA-modulated mRNAs regulated by four lncRNAs participated in the steroid biosynthesis pathway. Some estrogen-related drugs, such as tamoxifen, shared common targets with DHA. We inferred that DHA exerted anti-cancer effects on K562 cells by influencing estrogen levels. Our findings indicate that DHA has potential not only as an anti-malarial drug, but also as an anti-CML chemotherapeutic.