Supplementary Figure and Table Legends
Supplementary Table 1. Oligonucleotide sequences used in these studies. Primers sequences are
listed 5’-3’.
Supplementary Figure 1. Comparison of microRNA expression profiles between primary PC and
normal prostate patient samples. A-C. Bioinformatic analysis of prostate datasets GSE36803
(matched Primary PC and benign prostate tissue from 21 patients), GSE45604 (normal prostate tissue
from 21 patients and Primary PC tissue from 50 patients) and GSE6636 (adjacent normal tissue from 10
patients and Primary PC tissue from 23 patients) confirmed that the expression of twelve, nine and
eleven SiM-miRNAs were also downregulated in primary PC in the respective datasets. * indicates p
values less than 0.01; ** indicates p values less than 0.001; *** indicates p values less than 0.0001 as
determined by t-test. D.-E. Percentage of copy number deletions of host genes for SiM miRNAs in two
metastatic prostate cancer datasets (Taylor et al., 2010 and Grasso et al.). MIB1 is the host gene for miR1 and miR-133a. RMST is the host gene for miR-135a-5p. TRPM3 is the host gene for miR-204.
MIR205HG is the host gene for miR-205. C9orf3 is the host gene for miR-24-1. MIR31HG is the host
gene for miR-31. F. Frequency of SiM-miRNA locus deletion and suppression of SiM-miRNA
expression in 14 metastatic specimens from the Taylor et al cohort17 where both CNA and SiM-miRNA
expression data were available. G. As part of routine pathology reports, prognosis of PC patients is
evaluated using the Gleason score. Bioinformatics analysis was performed to determine if the SiMmiRNAs associated closely with the Gleason score, or if they can provide additional insight. Only 2 out
14 SiM-miRNAs associate with the Gleason score (one way ANOVA, p<0.05), indicating that SiMmiRNAs can yield additional information regarding PC prognosis.
Supplementary Figure 2. Expression of SiM-miRNAs and clinical outcomes in prostate cancer. We
ranked the 99 primary PC patient samples of the Taylor et al cohort (GSE21036, (19)) according to their
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individual miRNA z-score (compared to normal prostate tissue) for each SiM-miRNA. We then
compared the biochemical recurrence (BCR)-free survival between the bottom quartile and the top 3
quartiles of the ranked specimens using the log-rank test. As shown, there was no statistically significant
association between expression of miR-143-5p, miR-204, miR143-3p, miR-24-1-5p and BCR-free
survival (p> 0.05).
Supplementary Figure 3. Restoration of expression of SiM-miRNAs alters multiple cell cycle
pathways in PC cells. LNCaP cells were transfected with SiM-miRNA mimetics for 48 hours, followed
by RPPA. Pathway analysis was run on the identified target protein changes utilizing the CPDB
database with a minimum threshold of 4 recurrent SiM-miRNAs per pathway (p<0.05). The most
frequently altered pathway is G1/S transition.
Supplementary Figure 4. Proteomic analysis of PC cells following restoration of expression of
SiM microRNAs. A. Enlarged, higher resolution version of Main Fig. 4A (diagrammatic and pie chart
representation of cell cycle G1/S transition and mTOR signaling proteins and pathways altered by
expression of the 12 prostate cancer-relevant miR mimetics in LNCaP cells). It is provided in this
Supplement to allow the reader to review it in higher resolution. B-M. Heat maps of the proteins
significantly altered (as assessed by RPPA) by expression of the 12 prostate cancer-relevant microRNA
mimetics in LNCaP cells. Please note that Supplementary Figure 4 B is an enlarged, higher resolution
version of Main Fig. 4D. It is provided in this Supplement to allow the reader to review it in higher
resolution.
Supplementary Table 2. Evaluation of direct SiM-miRNA effects on the proteomic changes
assayed via RPPA. We evaluated the potential for direct miRNA effects on the proteins measured via
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RPPA by using a union of five leading prediction algorithms: TargetScan, miRanda, PicTar, DianaLab,
and miRDB. A protein change could be explained by direct SiM-miRNA effects if it was downregulated and predicted to the targeted of a SiM-miRNA by at least one out of the five algorithms. Out
of 466 observed significant protein changes (both up- and down-regulated), only 56 (12.01%) could be
explained as direct effects of the SiM-miRNAs, suggesting that the vast majority (87.99%) were the
results of indirect effects.
Supplementary Table 3. Proteomic signature for 12 Sim-MiRNAs transfected into LNCaP cells.
Combined proteomic signatures for 12 Sim-MiRNAs transfected into LNCaP cells for 48 hours.
Columns correspond to Sim-MiRNA transfection experiments, and rows correspond to RPPA
antibodies; both antibody full names and the protein names are shown. For each pair of SiM-MiRNA
and the significantly changed antibody, we show in the corresponding cell the fold change (log2transformed) if q<0.05 , otherwise an empty cell is used.
Supplementary Table 4. Prediction of SiM-miRNAs on steroid receptor coactivators. Using a union
of five leading prediction algorithms: TargetScan, miRanda, PicTar, DianaLab, and miRDB, we queried
whether the SiM miRNAs could target SRC1, SRC2 and SRC3. Table shows that SRC1 is predicted by
3 algorithms to be targeted by miR-135a-5p.
Supplementary Table 5. Evidence of SiM-miRNA/mRNA interaction in AGO HITS-CLIP and
AGO PAR-CLIP datasets. Publicly available Argonaute (AGO) HITS-CLIP and PAR-CLIP datasets
were interrogated using the Starbase compendium (http://starbase.sysu.edu.cn). Enriched regions were
intersected with the genes of interest: AR, SRC1 (NCOA1), SRC2 (NCOA2), SRC3 (NCOA3), and
ROCK1 using BEDTools. MicroRNA seeds were matched to the peak regions using miRanda. Typically
miRNA-mRNA prediction algorithms focus on 3’UTR to reduce the false positives. However, 5’UTR
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and coding regions miRNA/mRNA bindings have been published and experimentally validated with
Argonaute HITS-CLIP and PAR-CLIP sequencing. Table shows that AR can be targeted by miR-133a
in BT474 cells; BT474 expresses AR at low levels; AR protein was significantly suppressed by
treatment of LNCaP cells with miR-133a-5p. Perhaps due to the role of p160 steroid receptor
coactivators SRC1, SRC2, and SRC3 as pleiotropic transcription regulators, SiM-miRNAs are predicted
to target them via HITS-CLIP or PAR-CLIP in multiple samples. Specifically, we found on SRC1
targets of miR-135a-5p, miR-1-5p, miR-221-5p, and miR-24-1-5p in BCBL-1 and DG75 cells, and by
miR-143-5p in HEK293 cells, BC-1 cells, Epstein-Barr virus B95.8-infected lymphoblastoid cell lines;
interestingly, miR-135a-5p, miR-1-5p, and miR-143-5p were predicted to target SRC1 3’UTR via
multiple miRNA/mRNA prediction algorithms as well. On SRC2, we found targets of miR-205, miR31, miR-221-5p, and miR-221-3 in BCBL-1 and DG75 cells, of miR-143-5p and miR-204 in HeLa cells,
of miR-1-5p in human embryonic stem cells WA09, and of miR-143-5p in MCF7 cells. miRNA/mRNA
prediction algorithms suggested only miR-1 has binding to SRC2. Overlapping these data with SRC3,
we observed that SRC3 was a target of miR-133a-5p in BCBL-1 and DG75 cells and in BT474 cells; of
miR-205 in HeLa cells, and of miR-31 in MCF7 cells. MiR-205 was only predicted to target SRC3
using the miRNA/mRNA prediction algorithms. As a positive control for the AGO CLIP analysis, we
found evidence for miR-135a-5p binding to the ROCK1 gene in HeLa cells, confirming the regulation
reported by Kroiss et al., 2014. Alignment score, Energy (kCal/Mol), Alignment length, Alignment %
(miRNA seed) and Alignment % (CLIP peak) were obtained using the miRanda algorithm. References
for GEO studies are also listed in Supplementary Table 5.
Supplementary Figure 5. Re-expression of miR-135a-5p depletes SRC1 but not AR, SRC2, or
SRC3 in prostate cancer cells. LNCaP (A) and LAPC4 (B) cells were transfected with miR-NT or
miR-135a-5p mimic for 48 hours. Following this, total RNA was isolated and reverse transcribed.
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Quantitative PCR was performed for the expression levels of AR, SRC1, SRC2, and SRC3. The relative
expression of each mRNA was normalized to the expression levels of β-Actin mRNA in the cells. Bars,
s.e.
Supplementary Figure 6. Correlation between SiM-miRNA expression and AR transcriptional
activity in PC tissues. A. We utilized mRNA and miRNA expression data from the primary PC samples
of the Taylor et al cohort dataset (GSE21036) and applied a transcriptomic signature derived from
LNCaP cells treated with 2 different AR siRNAs. We computed gene signature activity for each
specimen, then computed the Pearson correlation coefficient (PCC, p<0.05) with each of the 12 SiMmiRNAs. We observed that for 11 out of the 12 SiM-miRNAs, the miRNA levels are positively
correlated with the presence of a gene signature generated by silencing AR (i.e. inversely correlated with
AR transcriptional activity), further supporting the role of SiM-miRNAs in the regulation of the AR axis
in PC. The only exception was miR-135a (NS: non-significant). B-C. Scatterplots for siAR-A and siARB gene signature compared to the miRNA expression levels in Taylor et al cohort dataset. MicroRNA
expression levels positively correlate with the presence of a gene signature generated by silencing AR
with 2 different siRNAs (i.e. inversely correlated with AR transcriptional activity). D. Utilizing publicly
available data and GSEA, we integrated a transcriptome footprint from LNCaP cells after re-expressing
the miR-135a microRNAs contributed by Kroiss et al ( GSE45620), and determined that AR-induced
genes (down-regulated by AR) are significantly enriched (NES ranging from -2.54 to -1.94, q <0.02).
Supplementary Figure 7. Re-expression of miR-135a-5p suppresses genes related to metastasis in
PC cells. Gene Set Enrichment Analysis (GSEA) of the miR-135a transcriptome profile in LNCaP PC
cells demonstrated that genes upregulated in metastatic PC are suppressed by re-expression of miR135a-5p in LNCaP cells (NES -1.88, q<0.09).
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Supplementary Figure 8. Androgen induces miR-135a-5p expression in PC cells. A. LAPC4 cells
were plated in media supplemented with 10% charcoal stripped FBS for 48 hours. Then, R1881 (1 nM)
was added and the cells were incubated for an additional 24 hours. At the end of treatment, total RNA
was isolated by the Trizol method and reverse transcribed. Stem loop-mediated reverse transcription of
mRNA was performed with 250 ng of total RNA for miR-135a-5p and RNU6B. Relative expression of
miR-135a-5p in each cell line was determined by quantitative PCR and normalized to RNU6B. Bars, s.e.
Supplementary Table 6. Comparison of H3K4Me3 and H3K27Me3 signal at the miR-135a-5p,
miR-221-5p, miR-1, and miR-31 loci. To establish the background distribution, we determined the
number of reads within a genomic window both 50-kb upstream and downstream; this approach is
similar to the one used by the MACS2 algorithm for ChIP-Seq peak calling. For each locus and SiMmiRNA we calculated the ratio [reads at regulation site, defined by enrichment of either H3k4Me3 or
h3k27Me3]/[reads within 50 kbp of the locus in both directions]. Significance of difference in binding
between PrEC and LNCaP was established using Fisher's exact test (p<0.05). Locations of sites for
epigenomic comparisons are given with respect to UCSC hg19/NCBI 37 human genome builds.
Supplementary Figure 9. Epigenetic features and chromatin structure determines expression and
accessibility of miR-1, miR-31 and miR-221-5p in aggressive PC versus normal prostate epithelial
cells. We examined ChIP-Seq datasets for H3K4Me3 and H3K27Me3 from PrEC and LNCaP cells.
Chromatin mark profiles were visualized utilizing the IGV browser. For each cell line and each ChIP
track, the intensity of the peak height is noted in the left hand corner of each IGV track. The direction of
the host gene expression and the microRNA expression are noted with black arrows. A. Chromatin mark
profiles for H3K4Me3 and H3K27Me3 at the miR221/miR-222 cluster in PrEC and LNCaP cells. B.
The MIB1 gene, the host gene for miR-133a and miR-1, shows strong signal for the permissive
H3K4Me3 chromatin mark in PrEC, whereas this chromatin mark is much less prevalent at MIB1 in
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LNCaP cells. C. IGV tracks of H3K4Me3 and H3K27Me3 in PrEC and LNCaP cells. The region
upstream of the miR-31 host gene also exhibits significant signal for the permissive H3K4Me3
chromatin mark in PrEC cells while this chromatin mark is nearly absent in the LNCaP cells. The miR31 host gene exhibits stronger signal for the repressive chromatin mark H3K27Me3 in LNCaP than in
PrEC cells. The direction of expression of the host gene and corresponding miRNA is indicated with
block arrows.
Supplementary
Figure
10.
Treatment
with
pan-histone
deacetylase
inhibitor,
DNA
methyltransferase (DNMT1) inhibitor and EZH2 siRNA reactivates miR-135a-5p expression in
PC cells. A-B. VCaP cells were treated as indicated for 24 hours with vorinostat (VS, A) or 96 hours
with the DNMT1 inhibitor, 5-azacitidine (5-Aza, B). Total RNA was isolated and reverse transcribed
utilizing a stem loop-mediated reverse transcription kit for miR-135a-5p, miR-1, and miR-221-5p.
Relative expression of each miR was determined by quantitative PCR and normalized to RNU6B. Bars,
s.e. C. LAPC4 cells were transfected with si-NT or two different EZH2 siRNAs for 48 hours. At the end
of treatment, total RNA was isolated by the Trizol method. Stem loop-mediated reverse transcription of
miR-135a-5p was performed with 250 ng of total RNA. Relative expression of miR-135a-5p was
determined by quantitative PCR and normalized to RNU6B. Bars, s.e.
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