LncRNA AC079630.4 expression associated with the progression and prognosis in lung cancer

Data and sample collection

Microarray data of GSE19188 (n=156), GSE31210 (n=226) and GSE30219 (n=293) and related clinicopathological features were downloaded from the database of Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/). All datasets were originated from the GPL570 microarray platform ([HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array). The dataset GSE19188 contained a total of 91 tumor- and 65 adjacent normal lung tissue samples, including the NSCLC subtypes of adenocarcinoma (ADC), large cell carcinoma (LCC) and squamous cell carcinoma (SCC). The dataset GSE31210 contained 226 samples of pathological stage I-II ADC and 20 adjacent normal tissue samples. The dataset GSE30219 contained 293 lung cancer samples.

Furthermore, 10 pairs of lung cancer and adjacent normal tissues (surgical resection) were collected and frozen at -70° C. This study was funded by Science and Technology Plan Project of Jiangxi Provincial Health and Family Planning Commission (20177255).

Probe re-annotation

In the Affymetrix microarray platform, a set of 11~22 probes represented each gene. However, much information about the long non-coding RNAs (lncRNA) was covered with the update of the human genome and annotation files. Thus, we discarded the original probe-set definitions, and re-annotated the probe sets by mapping each probe via their sequence to the reference sequence (hg38) using the previous method [8–10]. Finally, the transcript representing lncRNA AC079630.4 (probe ID: 236065_at) was identified according to the following criteria: (i) detected by more than three probes; (ii) each probe was mapped without mismatch; (iii) each probe was matched to only one transcript in probe-transcript pairs. In the probe-set of 236065_at, seven out of eleven probes could map to AC079630.4 without any mismatch (Figures 1, 2).

Figure 1. Flowchart of the whole procedures. DEG, differentially expressed gene.

Figure 2. List of the probes matched to AC079630.4 in the probe-set of 236065_at.

Gene set enrichment analysis (GSEA)

In the datasets of GSE31210 and GSE30219, all samples were divided into two groups according to the median value of AC079630.4 expression. GSEA was performed between the high- and low-expression groups to identify potential function of AC079630.4, and the annotation file of c2.cp.kegg.v5.2.symbols.gmt was chosen as the reference gene set. A false discovery rate (FDR) of less than 0.05 was selected as the cut-off.

Gene ontology (GO) analysis

To investigate the potential function of AC079630.4, we performed GO analysis of related biological processes on its related genes using the online tool of ToppFun (https://toppgene.cchmc.org/enrichment.jsp). An FDR of less than 0.05 was selected as the cut-off.

Cell culture and transfection

The human lung cancer cell lines (H1299 and H520) were purchased from Shanghai Institutes of Biochemistry and Cell Biology (Shanghai, China). All cells were cultured in RPMI-1640 (Thermo Fisher, USA) supplemented with 10% bovine serum (Thermo Fisher, USA) in a 5% CO₂ incubator at 37° C. Then, H1299 and H520 cells were seeded into 6-well plates, and transfected with the AC079630.4 over-expression plasmid (pcDNA3.1-AC079630.4) or the negative control (pcDNA3.1-NC) provided by GenePharma (Shanghai, China) using lipofectamine 2000 reagent according to the manufacturer's protocol (Thermo Fisher, USA).

RNA extraction and quantitative RT-PCR

Total RNA was extracted using TRIzol reagent (Invitrogen, USA), and then synthesized into first-strand cDNA using a synthesis kit (Thermo Fisher, USA). Gene expression levels were subsequently detected by the Applied Biosystems 7500 real-time PCR system (Thermo Fisher, USA) using the SYBR Green master mix (Thermo Fisher, USA). Relative expression levels were calculated using the 2^−ΔΔCt method. Each sample was performed in triplicate.

Western blot analysis

Total protein was isolated using the extraction kits (BestBio Science, China). The protein samples were separated by SDS-PAGE (Sigma, USA), transferred electrophoretically to the PVDF membrane (Millipore, USA) and blocked with 5% BSA. Then, the membranes were incubated with primary and secondary antibodies (ProScience, USA). Immunoblots were visualized by the enhanced chemiluminescent kits (Sigma, USA). The grey density of β-actin band was used as an internal control to normalize the densities of target proteins.

Cell proliferation assay

Cells were seeded into 96-well plates at a density of 1x10⁵ cells/well, and incubated at 37° C for 24, 48 and 72h. Subsequently, 10μl solution of Cell Counting Kit-8 (CCK-8) solution (Beyotime, China) was added to each well and incubated for 2h. The absorbance at 450nm was measured in each well using a microplate reader (Bio-Rad, USA).

Colony forming assay

1000 cells were incubated in 6-well plate for 12 days at 37° C. Then, cells were fixed with 4% paraformaldehyde and stained with 0.1% crystal violet. Colonies were quantified under a light microscope (magnification, x100).

Statistical analysis

Continuous variables were presented as mean ± standard deviation (SD) and compared using one-way ANOVA analysis. For paired data, paired t test was conducted. Categorical variables were described by percentages and compared via Chi-Squared tests. Cox proportional hazards regression analysis was used to evaluate the association between AC079630.4 expression and the prognosis.

Down-regulation of lncRNA AC079630.4 expression in lung cancer and its subtypes

The dataset GSE19188 contained a total of 91 tumor- and 65 adjacent normal lung tissue samples, including the NSCLC subtypes of ADC, LCC and SCC. After probe re-annotation and differentially expressed gene analysis, we identified 169 differentially expressed lncRNAs (Supplementary Figure 1 and Supplementary Table 1). Compared with the adjacent normal tissues, AC079630.4 was significantly down-regulated in lung cancer tissues (Figure 3). When considering the subtypes, it was also lowly expressed in ADC, LCC and SCC. The dataset GSE31210 included 226 samples of pathological stage I-II ADC and 20 adjacent normal tissue samples. AC079630.4 was significantly down-regulated in both the patients with and without EGFR mutation. Moreover, the patients with EGRF mutation showed a lower AC079630.4 expression than those without EGRF mutation. These indicated that AC079630.4 might act as a protective gene in lung cancer. In the clinical validation of 10 paired cancer and adjacent normal tissues, AC079630.4 was also obviously down-regulated in lung cancer.

Figure 3. Down-regulation of AC079630.4 expression in lung cancer and its subtypes. *P<0.05, **P<0.01, ***P<0.001.

Association between AC079630.4 expression and clinicopathological features of lung cancer

The dataset GSE31210 contained 226 samples of pathological stage I-II ADC (Table 1). All samples were divided into two groups according to the median value of AC079630.4 expression. Comparably, patients with high AC079630.4 expression had a better TNM stage (P<0.001) and a lower incidence of EGFR mutation (P=0.002).

The dataset GSE30219 contained 293 lung cancer samples (Table 2). Comparably, patients with high AC079630.4 expression had a better T stage (P<0.001), N stage (P<0.001) and M stage (P=0.031).

Association between AC079630.4 expression and lung cancer prognosis

The 226 samples in the dataset GSE31210 were divided into two groups according to the AC079630.4 expression, and the patients with high AC079630.4 expression showed a better prognosis (Hazard ratio (HR): 0.48, 95% confidence interval (CI): 0.24~0.97; P=0.036) (Figure 4). In the 293 samples of dataset GSE30219, the patients with high AC079630.4 expression showed a better prognosis (HR: 0.73, 95% confidence interval (CI): 0.55~0.98; P=0.033). We also searched the K-M Plotter database which contained 1144 samples from 7 datasets (http://kmplot.com/analysis/index.php), and the patients with high AC079630.4 expression also showed a better prognosis (HR: 0.64, 95% confidence interval (CI): 0.54~0.76; P<0.001).

Figure 4. Association between AC079630.4 expression and lung cancer prognosis.

Potential biological processes associated with AC079630.4

GSEA was conducted on the datasets of GSE31210 and GSE30219 respectively. The KEGG pathway of apoptosis was identified as the common biological process associated with the genes enriched in the samples with high AC079630.4 expression (Figure 5A). Furthermore, top 10 apoptosis-enriched genes identified by GSEA were chosen for GO analysis (Figure 5B). These genes showed a significant association with apoptosis and TRAIL signaling pathway (Figure 5C).

Figure 5. Potential biological processes associated with AC079630.4. (A) The KEGG pathway of apoptosis was identified by gene set enrichment analysis (GSEA) as the common AC079630.4-related biological pathway based on the datasets of GSE31210 and GSE30219. (B) Top 10 apoptosis-enriched genes identified by GSEA. (C) Gene ontology (GO) analysis of the top 10 genes.

Experimental validation

After plasmid transfection, the expression of AC079630.4 were up-regulated significantly in the cell lines of both H1299 and H520 (P<0.001) (Figure 6A). In cell proliferation assay, the AC079630.4 over-expression group (pcDNA3.1-AC079630.4) had a lower survival rate than the negative control group (pcDNA3.1-NC) (P<0.001) (Figure 6B). The over-expression group also had a less number of colonies than the control group (P<0.001) (Figure 6C). In the over-expression group, the receptors of TRAIL signaling pathway (TRAIL-R1 and TRAIL-R2) were significantly up-regulated (Figure 6D). These indicated that AC079630.4 over-expression might promote the apoptosis by activating the TRAIL signaling pathway.

Figure 6. Experimental validation of the effects of AC079630.4 over-expression on lung cancer cells. (A) Transfection efficiency of AC079630.4 over-expression plasmid. (B) Survival curves of transfected cells with AC079630.4 over-expression plasmid (pcDNA3.1-AC079630.4) or the negative control (pcDNA3.1-NC). (C) Cell proliferation assay analysis of transfected cells with AC079630.4 over-expression plasmid or the negative control. (D) Effect of AC079630.4 over-expression on the expression of TRAIL-R1 and TRAIL-R2. *P<0.05, **P<0.01, ***P<0.001.

To investigate the effects of AC079630.4 over-expression on others apoptotic genes, we also detect the expression of CASP-3 and CASP-8. After AC079630.4 over-expression, both CASP-3 and CASP-8 were up-regulated in HT1299 and HT520 (Supplementary Figure 2). In comparison, CASP-3 and CASP-8 were more significantly up-regulated in HT1299 and HT520 after incubating with 50~100 ng/mL TRAIL for 24h.