A miR-SNP biomarker linked to an increased lung cancer survival by miRNA-mediated down-regulation of FZD4 expression and Wnt signaling

Through a new hypothesis-driven and microRNA-pathway-based SNP (miR-SNP) association study we identified a novel miR-SNP (rs713065) in the 3′UTR region of FZD4 gene linked with decreased risk of death in early stage NSCLC patients. We determined biological function and mechanism of action of this FZD4-miR-SNP biomarker in a cellular platform. Our data suggest that FZD4-miR-SNP loci may significantly influence overall survival in NSCLC patients by specifically interacting with miR-204 and modulating FZD4 expression and cellular function in the Wnt-signaling-driven tumor progression. Our findings are bridging the gap between the discovery of epidemiological SNP biomarkers and their biological function and will enable us to develop novel therapeutic strategies that specifically target epigenetic markers in the oncogenic Wnt/FZD signaling pathways in NSCLC.

FBS was added to the lower chamber. After incubation for 24 h, cells remaining on the upper surface of the filter membrane were stained with PI, and cells on the lower surfaces were stained with DAPI. Images were captured using a DXM1200 microscope (Nikon, Japan).
Dual-Luciferase Assay. H1299 cells were transfected with Dual-Luc-SNP-3′UTR or Dual-Luc-WT-3′UTR reporter plasmids. 48 h after transfection, cells were lysed to measure firefly and Renilla luciferase activities by the Dual-Luciferase Reporter Assay System (Promega). Relative luciferase activity was calculated by normalizing firefly luciferase activity to Renilla luciferase activity. Each experiment was repeated three times.
SLA-RT-PCR Assay. Total mRNA was isolated using TRIzol reagent (Invitrogen, Carlsbad, CA); additional phenol:chloroform extraction was performed before ethanol precipitation according to the manufacturer's instructions. The mRNAs were treated briefly with 0.04 U/µL RNase-free DNase I (New England Biolabs, Ipswich, MA). The mRNA was reverse-transcribed by using a High Capacity Reverse Transcription Kit (Life Technologies, Carlsbad, CA) in combination with ST-RT-primer. 20 µL of the RT reaction contained 50 ng of total RNA, 5x10 -12 mol of SLA-RT primer, 2 µL of 10X RT buffer, 1 µL of MultiScribe Reverse Transcriptase, and 0.8 µL of 100 mM dNTPs. The nucleotide sequences of the SLA-RT primers are listed in Fig. 2B. To increase reverse transcription efficiency, a pulsed RT reaction was performed on a DNAEngine Peltier Thermal Cycler (Bio-Rad) with 60 cycles of 18°C for 1 min and 37°C for 1 s, followed by 60 cycles of 20°C for 1 min, 37°C for 1 s, 37°C for 30 min, 42°C for 20 min and 85°C for 10 min, and then holding at 4°C. RT products were then subjected to further PCR evaluation. The PCR primer sequence was as follows: Sense Primer: 5′-TCCTACAAGGATCAGATACTGGAG-3′. Antisense primer: 5′-GTGCGGGTCCGAGGTATTC-3′. The PCR was run at 95°C for 5 min, followed by 35 cycles of 95°C for 30 s, 60°C for 30 s, and 72°C for 30 s. PCR products were analyzed by agarose gel electrophoresis in 1X Tris-borate-EDTA (TBE) buffer. Electrophoresis was performed at 100 volts for 60 min. The gel was stained in an ethidium bromide bath for 10 min before visualization with a UV transilluminator (AlphaImager HP, Protein Simple, San Jose, CA). The principle and applications of SLA-RT-PCR method was described in detailed. (32,40) Real-Time PCR Assay. Total mRNA was reverse-transcribed into cDNA by using an oligo (dT) primer and High Capacity Reverse Transcription Kit (Life Technologies). To quantify FZD4 mRNA, PCR was performed in triplicate in 10 µL reaction volumes with TaqMan Universal PCR Mix (Applied Biosystem, Foster City, CA). Reactions were incubated at 95°C for 10 min, followed by 40 cycles of 95°C for 30 s, 60°C for 30 s, and 72°C for 30 s. Ct values were determined by setting a fixed threshold. The relative amount of FZD4 mRNA was normalized to GAPDH using the 2 -ΔΔCt method as instructed by the manufacturer.
NanoString Analysis. Tumor cells were harvested by centrifugation at designated time points and 10,000 cells were re-suspended in 1.0 μL of Qiagen RLT lysis buffer and hybridized at 65°C for 16 h to a custom-designed CodeSet to quantitatively measure expression of 209 Wnt and EMT signaling-related genes (see Supplemental Table 1 for the gene list). Testing samples were purified using an nCounter Prep Station and scanned on an nCounter Digital Analyzer; data were extracted using an nCounter RCC Collector (NanoString Technologies, Seattle, WA). Analysis of raw mRNA counts was performed using nSolver software. Data were normalized against 6 positive control oligonucleotides, 8 negative control oligonucleotides, and 5 housekeeping genes. All target gene expression were analyzed using the DE (differential expression) call model (NanoString), derived from a large experiment in which multiple technical replicates were run on numerous samples and CodeSets, creating a rule mapping any given raw expression value to the 95% of technical variability of genes at that expression level.
Images are representative of two independent experiments, each performed three times.
Statistical Analysis. Quantitative variables were reported as median ± SD. Differentially expressed genes between two groups were analyzed by two sided t tests. Benjamini-Hochberg method was used to adjust for multiple hypothesis testing, and generate false discovery rate (FDR q values). Top genes (corresponding FDR q values range from 0.029 to 0.493, p values range from 0.0001 to 0.0738) were selected for pathway analysis using Ingenuity Pathway Analysis (IPA) software (http://www.ingenuity.com/). Summaries of IPA are presented in Supplemental Table   2 and 3. Data analyses were performed using R packages (https://www.r-project.org/), a publically available statistical computing tool.    Figure S1, Full Length Western-blot images for Fig. 1E. A and B show images for anti-Flag with different intensities and C for anti--Actin from the same Western-blot. Images were obtained by a LI-COR Odyssey Imaging system with equipped imaging analysis software (LI-COR Biotechnology, Lincoln, NE).

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