Background
Lung cancer is the leading cause of cancer-related death worldwide [
1], and ~ 50% of these cancers are adenocarcinomas [
2]. Despite improvements in diagnosis and treatment, the 5-year survival rate for lung cancer is approximately 18%, mainly because most patients are diagnosed at an advanced stage [
3]. Therefore, discovering accurate and sensitive biomarkers is imperative and will be beneficial for the early diagnosis of lung adenocarcinoma (LUAD).
Circular RNAs (circRNAs), which have a circular covalently closed structure, are derived from precursor mRNA back-splicing of thousands of eukaryotic genes, endowing circRNAs with higher tolerance to exonuclease digestion [
4]. Over the past few years, numerous potential functions of circRNAs have been discovered, such as acting as miRNA sponges, modulating transcription and interacting with RNA-binding proteins (RBPs) [
5]. In addition, previous research showed that circRNAs were involved in autophagy, apoptosis, the cell cycle and proliferation, suggesting that circRNAs might have great significance for human disease [
6]. Moreover, increasing studies have suggested that circRNAs are closely associated with different cancers, including lung cancer [
7,
8], gastric cancer [
9], colorectal cancer [
10], hepatocellular carcinoma [
11,
12] and breast cancer [
13].
Recently, circRNAs have emerged as novel biomarkers due to their characteristics of abundance, stability, conservation, and specificity [
6,
14,
15]. Moreover, circRNAs can steadily subsist not only in cancer tissues but also in exosomes and the blood [
16,
17]. A liquid biopsy is more convenient and less invasive than traditional biopsy for analysis of biomarkers in tumor tissues. Hence, circulating circRNAs may be suitable for use as potential biomarkers for cancer diagnosis. Tan et al. [
18] and Hang et al. [
19] confirmed that plasma circRNAs might be potential biomarkers for non-small cell lung cancer (NSCLC) patients. However, little is known about the expression of plasma circRNAs in LUAD patients.
In the present study, we aimed to identify and validate potential plasma circRNA biomarkers for the diagnosis of LUAD. We performed bioinformatics analysis to select candidate LUAD-related circRNAs and validated the expression of these circRNAs in LUAD plasma and cells using quantitative real-time PCR (qRT-PCR). CircRNAs have been proposed to act as competing endogenous RNAs (ceRNAs) [
6]. CeRNAs can function as miRNA sponges through their binding sites to modulate miRNA activity on target genes [
5]. To predict the possible mechanisms and function of circRNAs in LUAD, a ceRNA network was constructed and a functional analysis was performed.
Methods
Selection of candidate circRNAs
CircRNA expression profiles for LUAD were searched in the Gene Expression Omnibus (GEO) database, and GSE101586 was selected. Normalized microarray data were re-analyzed using the GEO2R tool for comparison between LUAD tissues and paired nontumor tissues. The CircBase [
20] database was used to find host genes related to the circRNAs, and the CSCD [
21] database was used to select LUAD-specific circRNAs. Furthermore, the expression levels of their host genes were analyzed in The Cancer Genome Atlas (TCGA)-LUAD dataset downloaded from the Cancer Browser (
https://xena.ucsc.edu/welcome-to-ucsc-xena/), and their prognostic value in LUAD was assessed using the Kaplan–Meier plotter [
22].
Patients and samples
Peripheral blood was collected from 153 LUAD patients at the Qilu Hospital of Shandong University between April and July 2018 for plasma isolation. The patients we assayed were in different TNM stages of LUAD, of which 83 were in stage I, 13 in stage II, 30 in stage III, and 25 in stage IV. The diagnosis of each case was confirmed through histological examination. None of the patients had a prior history of other cancers or metastatic cancer from other sites or had received chemotherapy or radiotherapy prior to plasma collection. Paired preoperative and postoperative blood samples (n = 54) were collected from the same patients before surgery and on the seventh day after resection. The 54 healthy controls without a history of any cancer were individually matched to the LUAD cases by age and gender. This study was approved by the Ethics Committee of Qilu Hospital of Shandong University (KYLL-2013-097; 25 February 2014), and written informed consent was obtained from all patients or their guardians.
RNA isolation and reverse transcription
Total RNA was extracted from the patients’ plasma using the TRIzol™ LS Reagent (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. Whereas total RNA from the cells was isolated with the TRIzol Reagent (Invitrogen). The purity and concentration of the total RNA were evaluated with the NanoDrop Lite spectrophotometer (Thermo Scientific). The total RNA was subjected to cDNA synthesis using the PrimeScript™ RT Reagent Kit (Takara, Dalian, Liaoning, China). Briefly, 1000 ng of total RNA was reverse transcribed into cDNA with random primers in a final volume of 20 μL.
qRT-PCR
The qRT-PCR was performed using the TB Green™ Premix Ex Taq™ II (TaKaRa) on the Applied Biosystems StepOnePlus Real-Time PCR System (Thermo Fisher Scientific). The PCR conditions were 95 °C for 30 s, followed by 40 cycles at 95 °C for 5 s and 60 °C for 30 s for each specific primer. Melting curves were generated at the end of amplification to ensure the specificity of the PCR products. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used as a reference gene, and the relative expression levels of the circRNAs were calculated using the 2−ΔΔCT method. The divergent primers for these circRNAs were obtained from BioSune Corporation (Shanghai, China).
Cell culture and transfection
All cell lines (A549, NCI-H1299, HCC827 and 16HBE) were purchased from Procell Life Science & Technology Co., Ltd. (Wuhan, China) and confirmed by short tandem repeat (STR) profiling. HCC827 is a LUAD cell line with an acquired mutation in the EGFR tyrosine kinase domain (E746-A750 deletion), and 16HBE is a human bronchial epithelial cell line. The A549, NCI-H1299 and HCC827 cells were cultured in RPMI-1640 medium (Gibco, Invitrogen, Carlsbad, CA), and the 16HBE cells were cultured in DMEM (Gibco) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin. All cell lines were grown in humidified air at 37 °C with 5% CO2. The siRNA (si-hsa_circ_0005962, 5′-GAGACAACUUGACAUCUCUTT-3′) targeting the back-splice junction of hsa_circ_0005962 was synthesized by GenePharma (Shanghai, China). The A549 and H1299 cells were transfected with the siRNA using the Lipofectamine® 2000 Reagent (Invitrogen) according to the manufacturer’s instructions. After transfection, the cells were processed to assess the knockdown activity by qRT-PCR or used for other experiments.
Cell proliferation assay
To measure whether hsa_circ_0005962 was involved in cell proliferation, we performed the CCK8 assay. A549 and H1299 cells were seeded into 96-well plates at a density of 5 × 103 cells per well after transfection and cultured for 24 h. Cell proliferation was assessed using the Cell Counting Kit-8 (CCK-8; Beyotime, Shanghai, China). The CCK-8 reagent was added to each well, and the cells were incubated at 37 °C for 2 h. The proliferation rates were determined at 0, 24, 48, 72, and 96 h. The optical density was measured by a microplate reader set at 450 nm. All experiments were repeated three times.
CeRNA network analysis and function annotation
Potential interactions between the circRNAs and miRNAs were predicted using CircInteractome [
23] based on the TargetScan algorithm. In addition, miRNA–target interactions were predicted with TargetScan [
24] and miRTarBase [
25]. The circRNA-miRNA-mRNA network was constructed and visualized with the Cytoscape [
26] software. To gain further insight into the functions, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for the target genes using DAVID v6.8 [
27], The significant enrichment results were accepted at a threshold ≥ 2 gene counts with a
P value < 0.05.
Statistical analysis
All statistical data were analyzed using SPSS 22.0 (SPSS, Chicago, IL, USA), GraphPad 7.0 (GraphPad Software, San Diego, CA, USA) and the R software 3.5.1. The differences between the tumor and normal groups were evaluated using the nonparametric Mann–Whitney U test. A paired t test or Wilcoxon matched-pairs signed rank test was applied to compare differences in circRNA expression between the preoperative and postoperative groups. A Chi square test was used to analyze the associations between circRNA expression and clinicopathological factors in the LUAD patients. Logistic regression analysis was performed to establish a LUAD diagnostic panel consisting of two circRNAs. Receiver operating characteristic (ROC) curve analysis and the area under the ROC curve (AUC) were used to assess the diagnostic value of the circRNAs. The cutoff value of the circRNAs was calculated using the Youden index (specificity + sensitivity − 1). P values < 0.05 were considered statistically significant.
Discussion
Early diagnosis has great significance for the treatment and prognosis of LUAD. Unlike linear RNAs, circRNAs are expected to be novel candidates for biomarker detection, since they are more abundant and stable in body fluids (including serum exosomes, plasma and saliva) [
16,
28,
29]. Recently, an increasing number of studies has noted that circRNAs can be used as biomarkers for cancer diagnosis [
6]. Hence, in this study, we aimed to identify circulating circRNAs that could be used as biomarkers for the diagnosis of LUAD.
CircRNAs are derived from linear RNAs, most of which are produced by back splicing of exons [
30]. A previous study demonstrated that most circRNAs were associated with their linear RNA expression during tumorigenesis [
31]. In this study, we used a GEO dataset to investigate DEcircRNAs in LUAD and then selected the DEcircRNAs whose host genes were differentially expressed in TCGA-LUAD data and associated with the prognosis as candidate circRNAs. We speculated that these candidate DEcircRNAs might be involved in LUAD pathogenesis.
Furthermore, we validated the expression of the candidate circRNAs in the LUAD patient plasma. To the best of our knowledge, this report is the first on hsa_circ_0005962 and hsa_circ_0086414 expression in the plasma of patients with cancer. Our study utilized plasma samples due to their advantages of availability and noninvasiveness. Zhu et al. [
32] found differential expression of plasma hsa_circ_0013958 between LUAD patients and healthy controls. However, their sample size was relatively small (30 LUAD cases and 30 healthy controls). In the present study, we verified the plasma circRNA expression levels in a relatively larger sample set (153 LUAD and 54 normal samples). We found that both hsa_circ_0005962 and hsa_circ_0086414 were differentially expressed in the plasma of LUAD patients and that the combination of these two molecules improved the diagnostic accuracy for LUAD. In addition, we found that hsa_circ_0005962 and hsa_circ_0086414 were differentially dysregulated in the early stage of LUAD, suggesting that they may be the promising diagnostic biomarkers for the early stage of LUAD. Although the other two candidate circRNAs showed no significantly differential expression in the plasma, we attributed this discrepancy to differences in the testing methods (microarray analysis vs qRT-PCR), sample types (tissue vs plasma) and sample sizes. The above results suggested that the two-circRNA signature could be used as a potential noninvasive biomarker for diagnosis of LUAD.
Zhou et al. [
31] detected a large number of circRNAs in plasma of cervical cancer patients showing differential expression before and after surgery, and some of these circRNAs were indicated as prognostic markers, suggesting that these plasma circRNAs may be associated with cancer progression. Li et al. [
33] confirmed that the changes in plasma hsa_circ_0001017 and hsa_circ_0061276 expression before and after surgery were independent monitoring indicators for gastric cancer recurrence. In this study, we observed that hsa_circ_0005962 expression was decreased in postoperative LUAD patients compared to that in the preoperative patients, suggesting that it may be associated with the progression of LUAD. This decrease may be due to the decreasing release of tumor-derived nucleic acids after tumor resection [
34], resulting in significant changes in the plasma hsa_circ_0005962 levels before and after surgery. However, no significant difference in hsa_circ_0086414 expression was found between the preoperative and postoperative stages. It had been reported that the co-precipitation of circRNA with exosomes might be a possible mechanism for circRNA clearance [
35]. Therefore, we may attribute this result to the increasing clearance of circRNA through exosomes, so that the expression of hsa_circ_0086414 was not significantly increased after surgery.
EGFR, which is the epidermal growth factor receptor, is a member of the ERBB receptor tyrosine kinase family that promotes cell survival, proliferation and invasion [
36]. Mutations in EGFR are important drivers of NSCLC, and EGFR-targeted therapy can effectively improve the prognosis of patients with advanced NSCLC [
37]. EGFR mutations occur mainly in adenocarcinoma, younger women, and never-smokers [
38]. Surprisingly, we found that hsa_circ_0086414 was highly expressed in EFGR mutant patients compared to EGFR wild-type patients (
P < 0.01, Additional file
1. Figure S1A), and was more highly expressed in female patients than male patients (
P < 0.05, Additional file
1. Figure S1B). Previous studies showed that miRNAs could be involved in the development of EGFR mutations in LUAD [
39‐
41]. Therefore, we hypothesized that hsa_circ_0086414 might contribute to EGFR mutation by binding miRNAs. To explore the possible mechanism, bioinformatics analysis identified 9 miRNAs might be the targets of hsa_circ_0086414, which were differentially expressed in patients with and without EGFR mutations (Additional file
2). Among the 9 miRNAs, hsa-miR-103a-3p was reported to inhibit the EGFR expression via EGFR/KRAS pathway [
42]. However, the exact mechanism should be performed in the future study.
CircRNAs have been reported to regulate mRNA expression by competing for miRNAs [
4]. For instance, circRNA ciRS-7 [
43] and CDR1as [
44] can bind to miR-7 and function as miRNA sponges. In this study, the CCK8 assay suggested that hsa_circ_0005962 might promote cell proliferation in LUAD. To further study this possibility, we predicted the hsa_circ_0005962-miRNA-target network and performed a functional enrichment analysis. As a result, 4 miRNAs (hsa-miR-626, hsa-miR-326, hsa-miR-1265, and hsa-miR-622) and their 203 target genes were identified. Previous studies showed that hsa-miR-326 inhibited SMO expression in glioma cancer and CD34(+) chronic myeloid leukemia cells and acted as a tumor suppressor miRNA by inhibiting the PI3 kinase pathway in glioblastomas [
45‐
47]. In addition, hsa-miR-326 was reported to regulate lung cancer metastasis and invasion [
48,
49]. Research confirmed that hsa-miR-622 was downregulated in hepatocellular carcinoma, resulting in dysregulation of CXCR4 and KRAS [
50,
51]. Interestingly, YWHAZ, which is the host gene of hsa_circ_0005962, was predicted to be the target of hsa-miR-1265. Moreover, bioinformatics analysis showed that YWHAZ was upregulated in LUAD and associated with the prognosis. Previous research certified that YWHAZ (also known as 14-3-3zeta) was overexpressed in NSCLC and promoted cancer progression [
52,
53]. These findings supported the hypothesis that hsa_circ_0005962 might function as a sponge for hsa-miR-1265, thus increasing expression levels of YWHAZ and promoting tumorigenesis of LUAD. Functional enrichment analysis revealed that its target genes were involved in several cancer-related pathways, including the p53 signaling pathway, pathways in cancer, PI3K-Akt signaling pathway, small cell lung cancer, chronic myeloid leukemia and cell cycle. This evidence indicated that hsa_circ_0005962 might act as a miRNA sponge to promote the development of LUAD and further research on its mechanism is worthwhile.
Finally, to better understand the clinical application of circRNAs, we searched the clinical trials using the term “circRNAs” from the website
https://clinicaltrials.gov/, and
https://www.who.int/ictrp/en/. Interestingly, there were recruiting clinical trial for circRNAs as biomarkers for prostate cancer (ChiCTR1800019529), acute myocardial infarction (ChiCTR1800019218) and acute lung injury (NCT03766204) in the year 2018. However, there were no ongoing clinical trials for circRNAs biomarker for lung cancer. Our present study provided the evidence for circulating circRNAs as noninvasive biomarkers for lung cancer.
Authors’ contributions
X-XL designed the research, performed the experiments, analyzed the data, and wrote the paper; Y-HY and RL provided the patient samples; XL and M-YZ performed the data analysis and interpreted the data; Y-QQ assisted with the study design and revised the manuscript. All authors read and approved the final manuscript.