Hsa-miR-154 expression in breast cancer tissues. We explored hsa-miR-154 sequence abundance in breast cancer tissues. For that purpose, we used the YM500 database (18) which contains more than eight thousand small RNA sequencing (smRNA-seq) data sets and provides integrated analysis results for several cancer miRNome studies via multiple interactive interfaces (Expression, Novel miRNAs, isomiRs and thousands of smRNA-Seq datasets). The YM500 database also provides information about miRNA isoforms and arm switching discovery, however, there are limited miRNA editing analyses in different tissues and cancer types.
We also analyzed the hsa-miR-154 data available through the OncomiR Cancer Database (OMCD)( www.oncomir.umn.edu/omcd) (19). OMCD was developed at the University of Minnesota. This database was designed to allow systematic comparative genomic analyses of miRNA sequencing data derived from > 9500 cancer patients tissue samples available in the Cancer Genome Atlas (TCGA). Data were checked for equal variance and normal distribution via F test and Shapiro Wilk tests respectively in R Studio. Statistical comparisons between two groups were conducted by unpaired Student’s t-test; one-way analysis of variance (ANOVA) was performed when the dataset contained more than two groups. P < 0.05 was considered to be statistically significant.
Hsa-miR-154 expression and survival of breast cancer patients. To explore the effect of hsa-miR-154 expression on the survival rate of breast cancer patients, we used the Kaplan Meier plotter (KMplotter) tool (20). Data of solid tumors including lung, liver, pancreatic, ovarian, gastric, and breast cancers are available in this database. Cohorts of patients were split by median expression values through auto select best cut-off. Clinical data, including human epidermal growth factor receptor 2 (HER2), estrogen receptor, progesterone receptor status, lymph node status, tumor pathological grade, intrinsic subtype were displayed. A database was established using gene expression data and survival information of 2622 patients. The KMplotter MiRNA gene expression datasets used in the study were downloaded from gene expression omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo/), TCGA (http://cancergenome.nih.gov/), European genome-phenome archive (EGA) (https://ega.crg.eu/), and PubMed (http://www.pubmed.com).
Cell lines and cell culture. Human breast cancer cells MCF-7 and normal breast epithelial cells MCF-10A were purchased from the American Type Culture Collection (ATCC) (Manassas, VA, USA). MCF-10A cells were maintained in MEGM (Life Technologies, CA, USA) supplemented with 100 ng/mL cholera toxin. MCF-7 cells were cultured in DMEM (Life Technologies, CA, USA) supplemented with 10% fetal bovine serum, 1% penicillin-streptomycin. The cells were cultured at 37ºC in a humidified atmosphere consisting of 5% CO2. The culture medium was changed once every 2 days.
RNA isolation and detection of Hsa-miR-154. Total RNA was isolated from two human breast tissue cell lines (MCF7 as breast cancer) and (MCF10A as a non-cancer) using the miRNeasy Mini Kit (reference 217004, Qiagen, CA). A complementary DNA (cDNA) conversion for each of the cell lines was done using an NCode kit (Invitrogen™ MIRQ100). To determine levels of mature micro RNA, polyadenylated mature micro RNA sequences were first generated and converted to cDNA using the NCode miRNA First-Strand cDNA Synthesis Kit (Invitrogen). The cDNA was then amplified using a custom hsa-miR-154 specific forward primer. Sequences for the forward and reverse primers used to detect hsa-miR-154 precursors were 50- AGC AGC ATT GTA CAG GGC TAT CA-30 and 50 - TAG GTT ATC CGT GTT GCC TTC G-30 respectively. A universal reverse primer targeting on the polyadenylated region of the miRNA was also used. Mature miRNA levels in cancer cell lines relative to normal cells were assessed using the delta delta CT (2-ΔΔCT ) method with normalization to U6B in which ∆∆CT = (CT miRNA − CT U6) target − (CT miRNA − CT U6) control (21). All quantitative PCR reactions were conducted in triplicate on an ABI 7500 Fast Real-Time PCR instrument (Applied Biosystems) using the QuantiFast SYBR Green PCR Kit (QIAGEN). The qPCR was run in two stages. Initial denaturation was 3 min at 95 degrees Celsius. Denaturation was 40 cycles of 3 seconds at 95 degrees Celsius and annealing and elongation (data collection) was 40 cycles of 30 seconds at 60 degrees Celsius. A dissociation step was added to check for primer-dimer activity.
Cell proliferation assay. A 4-day hsa-miR-154 transfection cell proliferation assay was done in triplicate for both the MCF-7 breast cancer cell line and MCF-10a normal breast cell line. MCF-7 cells were cultured in Dublecco’s Modified Eagle Medium supplemented with 10% heat-inactivated Fetal Bovine Serum. MCF10-a cells were cultured with Mammary Epithelial cell Growth Medium. Cells were transfected with a hsa-miR-154 mimic, or a scrambled negative control (Qiagen) using the Lipofectamine RNAiMAX transfection reagent (Invitrogen), according to the manufacturer’s protocol. Briefly, 4 µl of 10 µM hsa-miR-154 mimic, or negative control was mixed with 0.1 µl of RNAiMAX reagent in 20 µl of OPTI-MEM (Invitrogen) and was used for each well. The complex was then added into a 98-well plate and incubated for 20 minutes at room temperature. Approximately 100 µl of 30 cells/µl were then seeded into each well dish for a total volume of 120 µl. 20 µl of MTS solution per well was then added in the dark room hood and incubated for 2 hours at 37° C before measuring a baseline cell concentration. MTS was similarly added to a new row every day for 4 days.
Bioinformatic search for Hsa-miR-154 binding sites in circadian genes. A target screening was completed using miRecords software to observe likely interactions by screening potential untranslated region (UTR) binding sites between 58 miRNA identified in the differential screen and the ten core circadian clock genes CLOCK, CRY1, CRY2, PER1, PER2, PER3, BMAL1, NPAS2, CSNK1E and TIMELESS (22). Seven target prediction algorithms were originally used to obtain the results: DIANA-microT, miRanda, MirTarget2, PicTar, PITA, NB MiRTar, Targetscan, and RNAhybrid. Prospective binding sites were predicted according to the number of base pair matches to the 50 miRNA seed region, the degree of compensatory 30 nonseed matches, and the number and nature of mismatched pairs (miRanda, TargetScan/TargetScanS, and PITA), as well as thermodynamic stability (miRanda and RNAhybrid). Results from RNAhybrid were excluded from the dataset because they were almost universally positive. Of the identified 58 micro RNAs, 12 were not recognized by the miRecords database.