Cell cultures and treatments
The human retinoblastoma cell line Y79 was obtained from the Cancer Hospital of the Chinese Academy of Medical Sciences and was cultured in RPMI-1640 medium (Thermo Fisher Scientific, Waltham, MA, USA) with 20% (v/v) fetal bovine serum (Thermo Fisher Scientific, Waltham, MA, USA), penicillin G (100 U/mL) and streptomycin (100 μg/mL) under a humidified atmosphere of 5% CO2 at 37°C. Y79/EDR cells were maintained by treating parental Y79 human retinoblastoma cells with a tolerance concentration of etoposide (Sigma-Aldrich, MO, USA) as previously described.
Detection of drug resistance
Cell Counting Kit-8 (CCK-8) (Dojindo, Kumamoto, Japan) was used to detect drug resistance. Y79/EDR and parental Y79 cells were seeded at a density of 2.0 × 104 cells per well with 200 μL of medium in 96-well plates and treated with different concentrations of etoposide (Sigma-Aldrich, MO, USA), carboplatin (Sigma-Aldrich, MO, USA) and vincristine (Sigma-Aldrich, MO, USA) for 48 h, respectively. Cells treated with phosphate-buffered saline (PBS) served as the controls. Then, 20 μL of CCK-8 solution was added to each well and incubated for 4 h at 37℃. The absorbance was measured at 450 nm using a microplate reader (BioTek, Vermont, USA). GraphPad Prism 5 was used to plot the drug concentration-cell survival curves. SigmaPlot 10.0 was used to calculate IC50, and resistance index (RI) was calculated according to IC50 as the following formula:
RI=IC50 (Y79/EDR) / IC50 (Y79)
Total RNA was extracted from Y79/EDR and parental cells with TRIzol (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer's protocol and purified with a NucleoSpin RNA Clean-up kit (Macherey-Nagel, NucleoSpin®, Germany). RNA degradation and contamination were assessed on 1% agarose gels. RNA purity and concentrations were detected using a NanoPhotometer spectrophotometer (Implen, CA, USA) and a Qubit RNA Assay Kit in a Qubit 2.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA, USA), respectively. RNA integrity was assessed using the RNA 6000 Nano Kit of the Agilent Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA).
Library construction for RNA sequencing
A total of 1 μg of RNA per sample was used as input material for RNA sample preparation. All procedures for cDNA library construction were performed using an NEBNext UltraTM RNA Library Prep Kit for Illumina (NEB, Ipswich, MA, USA) following the manufacturer’s recommendations. Sequencing of the libraries was carried out on an Illumina HiSeq 2500 platform, and paired-end reads were generated (raw data).
Sequencing data analysis
Quality control of the raw data was performed, including removal of reads containing adapter and poly-N sequences and removal of low-quality reads, to obtain clean data. In addition, the quality score and GC content of the clean reads were calculated. Clean reads with a perfect match or only one mismatch were mapped to the Genome Reference Consortium assembly GRCh37 using TopHat2 for further analysis and annotation. Quantification of gene expression levels was estimated based on fragments per kilobase of transcript per million fragments mapped (FPKM) with the following formula: FPKM = cDNA fragments/mapped fragments (millions)×transcript length (kb). We performed RNAseq analysis on the platform BMKCloud (www.biocloud.net).
Determination and clustering analysis of DEGs
Prior to differential gene expression analysis, for each sequenced library, the read counts were adjusted with the edgeR program package through one scaling normalized factor. Differential expression analysis of two samples was performed using the DESeq (2010) R package. P values were adjusted using q values. Fold change (FC) ≥ 2 and q value < 0.005 were set as the threshold for significant DEGs.
Pathway enrichment analysis
Gene Ontology (GO) enrichment analysis of DEGs was executed with the R package GOseq based on Wallenius’ noncentral hypergeometric distribution，which can adjust for gene length bias in DEGs. Terms with KS value < 0.05 (Kolmogorov–Smirnov) were considered significantly enriched. The Kyoto Encyclopedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg/) was used to predict the enriched pathways of the DEGs. KOBAS software was used to test the statistical enrichment of DEGs in KEGG pathways.
Real-time quantitative reverse transcription polymerase chain reaction (real time QRT-PCR) validation
To validate the expression levels of the DEGs obtained from RNAseq, we selected 7 genes for real time QRT-PCR analysis. Total RNA from parental Y79 and Y79/EDR cells was isolated with TRIzol reagent (Thermo Fisher Scientific, Waltham, MA, USA), and then cDNA was synthesized with a Transcriptor First Strand cDNA Synthesis Kit (Roche, Mannheim, Germany). Real time QRT-PCR was conducted with a SYBR® Premix Ex Taq™ II kit (TaKaRa, Kusatsu, Japan). All procedures were performed according to the manufacturer’s instructions. The 2-ΔΔCt method was used to determine relative expression levels with the GAPDH gene as an internal control. To further calculate log2 FC (fold change) between Y79/EDR and Y79 cell lines from real time QRT-PCR, an equation of log2 [2-ΔΔCt (Y79/EDR)/ 2-ΔΔCt (Y79)] was used to compare with that from RNAseq. The primers used are listed in Additional file 1: Table S1.
Transfection and RNA interference of selected genes
To explore the relationship between the 7 identified genes and etoposide resistance, we knocked down these genes in parental Y79 cells to determine their effects on drug sensitivity. Three short interfering RNA (siRNA) sequences targeting different regions of each gene were transiently transfected at a concentration of 100 nM into parental Y79 cells with Lipofectamine RNAiMAX (Thermo Fisher Scientific, Waltham, MA, USA). The siRNA sequences are listed in Additional file 2: Table S2. Scrambled siRNA was used as a negative control (RiboBio, Guangzhou China). Then, some of the cells were collected 6-8 h after transfection and seeded into 96-well plates for drug sensitivity analysis, while others were harvested for real time QRT-PCR after 48 h.
Parental Y79 cells transfected with siRNA of 7 candidate genes were seeded in 96-well plates, respectively, and treated with different concentrations of etoposide, carboplatin and vincristine for 48 h. Then, CCK-8 was used to analyse changes of drug sensitivity after knockdown of candidate genes.
To observe drug-induced changes in ARHGAP9 mRNA expression, parental Y79 cells were seeded at a density of 5.0 × 105cells per well with 2 mL of medium into 6-well plates and treated with IC50 of carboplatin and etoposide for 24 h, following with detection of ARHGAP9 mRNA expression by real time QRT-PCR.
Statistical analyses of the transcriptome profiles were described in above subsections, respectively. The rest analyses were conducted using Student’s t-test for functional validation studies. The quantitative data were presented as mean ± SEM.