Identification of lncRNA, miRNA and mRNA expression profiles and ceRNA Networks in small cell lung cancer

Abstract

Background: Small cell lung cancer (SCLC) is a highly lethal malignant tumor. It accounts for approximately 15% of newly diagnosed lung cancers. Long non-coding RNAs (lncRNAs) can regulate gene expression and contribute to tumorigenesis through interactions with microRNAs (miRNAs). However, there are only a few studies reporting the expression profiles of lncRNAs, miRNAs, and mRNAs in SCLC. Also, the role of differentially expressed lncRNAs, miRNAs, and mRNAs in relation to competitive endogenous RNAs (ceRNA) network in SCLC remain unclear.

Results: In the present study, we first performed next generation sequencing (NGS) with six pairs of SCLC tumors and adjacent non-cancerous tissues obtained from SCLC patients. Overall, 29 lncRNAs, 48 miRNAs, and 510 mRNAs were found to be differentially expressed in SCLC samples (|log₂[fold change] |> 1; P < 0.05). Bioinformatics analysis was performed to predict and construct a lncRNA-miRNA-mRNA ceRNA network, which included 9 lncRNAs, 11 miRNAs, and 392 mRNAs. Four up-regulated lncRNAs and related mRNAs in the ceRNA regulatory pathways were selected and validated by quantitative PCR. In addition, we examined the role of the most upregulated lncRNA, TCONS_00020615, in SCLC cells. We found that TCONS_00020615 may regulate SCLC tumorigenesis through the TCONS_00020615-hsa-miR-26b-5p-TPD52 pathway.

Conclusions: Our study provided the comprehensive analysis of the expression profiles of lncRNAs, miRNAs, and mRNAs of SCLC tumors and adjacent non-cancerous tissues. We constructed the ceRNA networks which may provide new evidence for the underlying regulatory mechanism of SCLC. We also found that the lncRNA TCONS_00020615 may regulate the carcinogenesis of SCLC.

Keywords: RNA-sequencing (RNA-Seq); Small cell lung cancer (SCLC); TCONS_00020615; ceRNA network; lncRNA; mRNA; miRNA.

Fig. 1

Distribution of lncRNAs, miRNAs, and mRNAs in SCLC tumor tissues and paired adjacent normal tissues. a, the lncRNAs identified in this study were compared with previously reported lncRNAs. b, length distribution of lncRNAs. c, length distribution of miRNAs. d, chromosomal distributions of differentially expressed mRNAs and lncRNAs

Fig. 2

Flow chart of the study design. MRE, miRNA response element

Fig. 3

Expression Profiles of lncRNAs, miRNAs, and mRNAs. Heatmap of differently expressed lncRNAs, miRNAs, and mRNAs in the 6 pairs of SCLC tumor tissues and adjacent normal tissues

Fig. 4

Predicted ceRNA networks based on the RNA expression profiles in SCLC tumors. a, lncRNA-miRNA-mRNA network. The nodes highlighted in red indicate upregulation and the nodes highlighted in green indicate downregulation of expression. The RNA species lncRNAs, miRNAs, and mRNAs are represented by diamonds, circles, and squares, respectively. b, KEGG pathway and c, GO analysis for the mRNAs in the lncRNA-miRNA-mRNAs network

Fig. 5

qRT-PCR validation of the top three upregulated and downregulated lncRNAs and mRNAs. a-c, upregulated lncRNAs. d-f, downregulated lncRNAs. g-i, upregulated mRNAs. j-l, downregulated mRNAs. Expression of all the twelve transcripts had significant changes in SCLC tissues. m, expression fold changes of these dysregulated lncRNAs and mRNAs. *, p < 0.05; **, p < 0.01; ***, p < 0.001

Fig. 6

qRT-PCR validation of the dysregulated lncRNAs and mRNAs in the predicted ceRNA network. a-d, lncRNAs TCONS_00020615, TCONS_00055555, TCONS_00106091, and TCONS_00130858. e-l, cancer-related mRNAs CDCA3, DIAPH3, MCM7, NCAPG2, TPD52, KIF22, PRC1, and SETD6 were all significantly upregulated in SCLC tissues. m, levels of all differently expressed lncRNAs and mRNAs. RNA expression levels were normalized to those of β-actin. **, p < 0.01; ***, p < 0.001

Fig. 7

Diagnostic values of the qRT-PCR validated lncRNAs and mRNAs. Leave-one-out cross-validation was performed with the qRT-PCR results of the four lncRNAs and eight mRNAs in the sixteen paired SCLC and normal tissues, and the AUC values of the four lncRNAs and eight mRNAs were shown

Fig. 8

Inhibition of TCONS_00020615 hampers proliferation and migration of SCLC cells. a, expression levels of TCONS_00020615 in H1688 cells transfected with shTCONS_00020615. b, cell viability as assessed by MTT assay. c, colony formation assay and quantification analysis for evaluating cell proliferative ability. d, wound healing assay and quantification analysis for monitoring cell migration in H1688 cells. e, matrigel invasion assay and quantification analysis for evaluating invasive ability of H1688 cells

Fig. 9

TCONS_00020615–hsa-miR-26b-5p–TPD52 axis is considered as a potential pathway linked to SCLC. a-c, pearson’s correlation scatter plot of expression levels of TCONS_00020615 and TPD52, NCAPG2, DIAPH3. d, potential binding site of TCONS_00020615 and miR-26b-5p. RNAhybrid database (https://bibiserv.cebitec.uni-bielefeld.de/rnahybrid/). e, potential binding site of miR-26b-5p and TPD52. f, the potential binding site of miR-26b-5p and TPD52 is broadly conserved among vertebrates. e and f are the analysis data from Targetscan databse (https://www.targetscan.org/vert_80/)