RNA Sequencing Data Analysis

Supplementary Methods

RNA Sequencing data analysis

Total RNA was first isolated from 5 samples using Trizol reagent (Invitrogen Life Technologies, Carlsbad, CA, USA). The cDNA libraries were prepared using the ScriptSeq Complete Kit (Epicentre). We performed paired-end sequencing (100bp) using HiSeq2000 sequencing instruments at WuXiAppTec (Shanghai, China). The low-quality reads were removed by in-house scripts. The remaining paired reads were mapped to the human reference genome hg19 and Refseq mRNA sequences release 60 using SOAPaligner version 2.21 (1). We counted the reads number for per gene based on the gff annotation file from Refseq andnormalizedthe gene expression level by RPKM (reads per kilobase per million mapped reads).

Small RNA sequencing data analysis

Total RNA was used to generate a small RNA sequencing library using reagents and methods provided with TruSeq Small RNA Sample Prep Kit (Illumina, San Diego, USA). We performed the small RNA sequencing along with the RNA-seq.We trimmed the 5’ and 3’ adapters, filtered the low quality reads and kept the 18~30nt reads. The reads were mapped to hg19 with bwa(2). Non-miRNA reads were filtered based on the sequences downloaded from fRNAdb(3), NONCODE(4) and Rfam(5) databases. The remaining reads were mapped to human pre-miRNAsmiRBase release 20 (6) with miRExpress 2.0 (7). The expression level of miRNA was normalized with RPM (reads per million mapped reads).

Gene Ontology (GO) enrichment analysis

GO functional enrichment analysis, in the categories molecular function and biological process, was performed for the differentially expressed genes. The hypergeometric distribution was used to test the significance of enriched GO terms. The false discovery rate (FDR) was obtained by adjusting the raw p value with the BenjaminiHochberg method. FDR lower than 0.001 was considered significant. The GO terms at or higher than level 3 were considered.

Construction of miRNA and TF regulatory network

To construct the miRNA and TF regulatory network, their targets were obtained firstly. We extracted the verified miRNA targets from mir2disease, miRecords, miRTarBase and TarBase version 6.0(8-11). We also downloaded the predicted miRNA targets from miRanda(12) and Targetscan 6.0(13) databases and set their intersection as the final predicted miRNA targets. For the TFs, we obtained the verified TF targets from TRANSFAC 2013 and TransmiR(14) databases. We also extracted the human TF targets from all the available ChIP-seq data downloaded from ENCODE(15) and GEO datasets. The known TF binding site motifs were downloaded from databases TRANSFAC, JASPAR(16) and HOCOMOCO version 9.0(17). We predicted the potential TF targets through searching the binding sites of these motifs in promoter regions of human genome. To reduce the false positive, we filtered these binding sites with their conservation in human, mouse and rat genome. The regulatory network were constructed with differentially expressed miRNAs, TFs and cancer related genes based on these regulatory relationships and the cancer genes were grouped into different pathways. To further research the regulation of miRNAs and TFs to cell cycle, DNA repair and Notch pathway, the feed-forward loops and feed-back loops formed by miRNA, TFs and genes were used to construct the regulatory networks. The edges of these specific regulatory networks were filtered with the expression correlation of TFs/miRNAs and target genes.

Luciferase assays

The 3′-UTR fragments containing the predicted target sequence of miR-146b-5p were amplified by RT-PCR. Primers used for amplification of specific cDNA probes are given below. The fragments were inserted into the psi-CHECK2 vector (XhoI and NotI restriction enzyme sites; Promega). HEK-293T cells were transfected with psiCHECK/mRNA-3′ UTR construct using Lipofectamine 2000 (Invitrogen, USA) and the appropriate miR-146b-5p or negative control. Cells were collected after 48h transfection, and luciferase activity was measured using a dual-luciferase reporter assay system (Promega). All experiments were performed in triplicate and at least four times independently.

Real-time PCR

Total RNA was extracted with an E.Z.N.A.™ Blood RNA Kit (Omega Biotek Inc.). For reverse transcription, 2 μg total RNA was primed with a random hexamer mixture as the primer using MoloneyMurine Leukemia Virus Reverse Transcriptase (Promega, Madison, WI, USA). Real-time was performed with 10 μl SYBR Green PCR Master Mix (Applied Biosystems Inc., Foster City, CA, USA), 2 μl primers (Invitrogen, Carlsbad, CA, USA), 6.5 μlRNase-free H2O and 1.5 μlcDNA as a template in a final reaction volume of 20 μl. Fluorescence intensity was measured using a Stratagene Mx3000P™ QPCR System.

Western blot

50μg protein samples for each well were separated by sodium dodecyl sulfate–polyacrylamide gel electrophoresis and transferred to nitrocellulose membranes. The membranes were blocked with 5% non-fat milk and incubated overnight with monoclonal antibody (1:500) at 4°C. Blots were developed using a horseradish peroxidase–conjugated rabbit anti-human secondary antibody (1:500) and a chemiluminescent detection kit (Amersham Biosciences, Piscataway, NJ, USA).

DNA breaks in recipient cells

DNA double-strand breaks (DSBs) were assessed by agarose gel electrophoresis using genomic DNA isolated from recipient cells. Briefly, cells were washed, trypsinized, and centrifuged at 1,500 ×g for 5 min. After 3 h incubation at 50°C, samples were treated with RNase A for 1 h at 37°C. The DNA was extracted with phenol:chloroform, and precipitated with 0.3 mol/l sodium acetate and ethanol at -20°C. DNA samples (10 μg) were separated on a 2% agarose gel containing 5 μg/ml ethidium bromides and analyzed by autoradiography.

Intracellular reactive oxygen species

Intracellular reactive oxygen species (ROS) were detected using a Reactive Oxygen Species Assay Kit (S0033, Biyuntian Inc., Beijing, China) and measured with a multimode plate reader (EnSpire, U.S.A.). All procedures were conducted in accordance with the manufacturer’s instructions.

Statistical analysis

SPSS 10.0 was used for statistical analysis. Non-parametric and unpaired t-test comparisons were used to compare groups and the relapse rate between groups was compared by the chi-square test. Two-sided P < 0.05 was defined as being statistically significant.

Primers of Luciferase assays

NUMB-wt HF: 5’-TCCATACCAGACAGGGAGCA-3’

NUMB-wt HR: 5’-GAGGTCAAGAGGCTGCAACT-3’

NUMB-mut MR: 5’-TATCTCTCTTGAATTTAAAATATTCTAAATGCAT-3’

NUMB-mut MF: 5’-TAAATTCAAGAGAGATATTAAGAAGTTGTATGAG-3’

Primers of Real-time PCR

β-Actin

β-Actin forward (F): 5′-CACGATGGAGGGGCCGGACTCATC-3′

β-Actin reverse (R): 5′-TAAAGACCTCTATGCCAACACAGT-3′

NUMB

homo NUMB (F): 5’-AGCCCATACTGCTCTAGCACCCG-3’

homo NUMB (R):5’-AGGCAGCACCAGAAGATTGACCC-3’

AICDA

homo AICDA (F): 5′-CGTAGTGAAGAGGCGTGACA-3′

homo AICDA (R): 5′-TCAGACTGAGGTTGGGGTTC-3′

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