Processes 2018, 6,42
apoptosis caspase-3 cleaves DFFA resulting in DNA fragmentation [46]. As misexpression of an
apoptotic contributor can have significant ramifications in terms of tumor development, the differential
regulation of DFFA by miR-140 between our two cell lines is highly intriguing, especially as numerous
reports have previously implicated a role for miR-140 in breast malignancy [47–49]. That said, the two
cell lines involved in this study, MCF-7 and MDA-MB-231, have very distinct characteristics in terms
of morphology, invasiveness, and physiological responses. While they are both adenocarcinomas
(cancers of the breast epithelium tissue that originated in the mammary gland), the MCF-7 line
was derived from an in situ carcinoma where the cancerous cells had not yet invaded surrounding
tissues. These cells are weakly invasive, luminal epithelial-like, and are hormone responsive, requiring
noticeably less aggressive therapies [50]. In contrast, the highly-invasive, fibroblast-like MDA-MB-231
line was derived from a metastatic carcinoma and is a triple-negative breast cancer making it highly
chemoresistant and, thus, significantly more difficult to treat [51]. When taken in conjunction with
reports of elevated ADAR activity in many breast cancers, it is feasible to assume that RNA editing
could contribute to some of the characteristic phenotypic differences observed between these two
cell lines. Excitingly, we suggest the work presented here strongly supports this as we find ADAR
editing directly mediates the regulation of DFFA in MCF-7s whereas the absence of DFFA editing in
MDA-MB-231 conversely disallows DFFA regulation by miR-140-3p in these cells. Simply put, we
find miR-140 is able to bind and regulate DFFA due to editing in MCF-7s, so inhibition of the miRNA
increases growth. As it is unable to bind in MDA-MB-231, no effect is seen. As such, it is tempting
to speculate that the differential regulation of DFFA by miR-140-3p between these two breast cancer
lines directly contributes to their observed differences in cellular proliferation and cellular survival
(Figure 6). That said, miR-140-3p undoubtedly regulates multiple mRNAs and the observed effects on
cellular growth may be mediated through more than DFFA restriction alone. Of note, Salem et al. [52]
recently demonstrated that transfecting several breast cancer cell lines with miR-140-3p isoform mimics
commonly resulted in a decrease in breast cancer cell viability (nicely complementing the increased
cellular growth we observe in MCF-7s following transfection of miR-140-3p inhibitor). Additionally,
and also in agreement with our findings, this group similarly observed no change in MDA-MB-231
viability following manipulation of miR-140-3p levels via transfection of a miR-140-3p mimic.
While this work represents the first direct indication of a contributory role for A-to-I editing in
modulating miRNA targeting in malignancy, we suggest the repeated observation of a correlation
between altered ADAR activity and various pathologies suggests altered miRNA regulations due to
alterations in A-to-I profiles may represent a significant currently underappreciated contributor to
an array of pathologies. Perhaps of broader importance. However, our findings lead us to believe
that many miRNA targets can only be identified by analyzing expressed sequences, and that accurate
miRNA target prediction may ultimately require analyzing transcriptomes and not genomes.
Supplementary Materials: The following are available online at http://www.mdpi.com/2227-9717/6/5/42/s1,
Table S1: Comprehensive list of unique edit sites identified. To be considered a probable edit, at least 10% of
transcriptome reads were required to differ from the reference genome at the edit position (with a minimum
of 30 total reads). In all, 19,462 unique edit sites were identified in MCF-7 and 35,090 sites were found in
MDA-MB-231. Chr, chromosome; Edit Location, bp position; Reference Base, expected nucleotide; Alternate Base,
unexpected nucleotide; Quality Score, as in SAMtools(36); Info, as in SAMtools(36); Freq, Alternate Base/Reference
Base %. Table S2: List of 86 miRNAs representing 72 unique seeds where ADAR editing of mRNA transcripts
alters complementarity to their seed region and creates novel target sites for regulation. MiRNA information was
obtained from miRBase, ‘RC’ indicates the seed is reverse complemented, ‘Edited Targets’ is the total number of
seed matches when the transcripts are edited whereas ‘Unedited Targets” indicates the number of seed matches
in the absence of editing activity. ‘Expected Targets’ is the average number of seed matches found within the
windows flanking the edit site. Table S3: List of 120 miRs representing 93 unique seeds where ADAR editing of
mRNA transcripts destroys complementarity to miR seed regions and effectively inhibits regulation. MiRNA
information was obtained from miRBase, ‘RC’ indicates the seed is reverse complemented, ‘Edited Targets’ is the
total number of seed matches when the transcripts are edited whereas ‘Unedited Targets” indicates the number of
seed matches in the absence of editing activity. ‘Expected Targets’ is the average number of seed matches found
within the windows flanking the edit site.
140
apoptosis caspase-3 cleaves DFFA resulting in DNA fragmentation [46]. As misexpression of an
apoptotic contributor can have significant ramifications in terms of tumor development, the differential
regulation of DFFA by miR-140 between our two cell lines is highly intriguing, especially as numerous
reports have previously implicated a role for miR-140 in breast malignancy [47–49]. That said, the two
cell lines involved in this study, MCF-7 and MDA-MB-231, have very distinct characteristics in terms
of morphology, invasiveness, and physiological responses. While they are both adenocarcinomas
(cancers of the breast epithelium tissue that originated in the mammary gland), the MCF-7 line
was derived from an in situ carcinoma where the cancerous cells had not yet invaded surrounding
tissues. These cells are weakly invasive, luminal epithelial-like, and are hormone responsive, requiring
noticeably less aggressive therapies [50]. In contrast, the highly-invasive, fibroblast-like MDA-MB-231
line was derived from a metastatic carcinoma and is a triple-negative breast cancer making it highly
chemoresistant and, thus, significantly more difficult to treat [51]. When taken in conjunction with
reports of elevated ADAR activity in many breast cancers, it is feasible to assume that RNA editing
could contribute to some of the characteristic phenotypic differences observed between these two
cell lines. Excitingly, we suggest the work presented here strongly supports this as we find ADAR
editing directly mediates the regulation of DFFA in MCF-7s whereas the absence of DFFA editing in
MDA-MB-231 conversely disallows DFFA regulation by miR-140-3p in these cells. Simply put, we
find miR-140 is able to bind and regulate DFFA due to editing in MCF-7s, so inhibition of the miRNA
increases growth. As it is unable to bind in MDA-MB-231, no effect is seen. As such, it is tempting
to speculate that the differential regulation of DFFA by miR-140-3p between these two breast cancer
lines directly contributes to their observed differences in cellular proliferation and cellular survival
(Figure 6). That said, miR-140-3p undoubtedly regulates multiple mRNAs and the observed effects on
cellular growth may be mediated through more than DFFA restriction alone. Of note, Salem et al. [52]
recently demonstrated that transfecting several breast cancer cell lines with miR-140-3p isoform mimics
commonly resulted in a decrease in breast cancer cell viability (nicely complementing the increased
cellular growth we observe in MCF-7s following transfection of miR-140-3p inhibitor). Additionally,
and also in agreement with our findings, this group similarly observed no change in MDA-MB-231
viability following manipulation of miR-140-3p levels via transfection of a miR-140-3p mimic.
While this work represents the first direct indication of a contributory role for A-to-I editing in
modulating miRNA targeting in malignancy, we suggest the repeated observation of a correlation
between altered ADAR activity and various pathologies suggests altered miRNA regulations due to
alterations in A-to-I profiles may represent a significant currently underappreciated contributor to
an array of pathologies. Perhaps of broader importance. However, our findings lead us to believe
that many miRNA targets can only be identified by analyzing expressed sequences, and that accurate
miRNA target prediction may ultimately require analyzing transcriptomes and not genomes.
Supplementary Materials: The following are available online at http://www.mdpi.com/2227-9717/6/5/42/s1,
Table S1: Comprehensive list of unique edit sites identified. To be considered a probable edit, at least 10% of
transcriptome reads were required to differ from the reference genome at the edit position (with a minimum
of 30 total reads). In all, 19,462 unique edit sites were identified in MCF-7 and 35,090 sites were found in
MDA-MB-231. Chr, chromosome; Edit Location, bp position; Reference Base, expected nucleotide; Alternate Base,
unexpected nucleotide; Quality Score, as in SAMtools(36); Info, as in SAMtools(36); Freq, Alternate Base/Reference
Base %. Table S2: List of 86 miRNAs representing 72 unique seeds where ADAR editing of mRNA transcripts
alters complementarity to their seed region and creates novel target sites for regulation. MiRNA information was
obtained from miRBase, ‘RC’ indicates the seed is reverse complemented, ‘Edited Targets’ is the total number of
seed matches when the transcripts are edited whereas ‘Unedited Targets” indicates the number of seed matches
in the absence of editing activity. ‘Expected Targets’ is the average number of seed matches found within the
windows flanking the edit site. Table S3: List of 120 miRs representing 93 unique seeds where ADAR editing of
mRNA transcripts destroys complementarity to miR seed regions and effectively inhibits regulation. MiRNA
information was obtained from miRBase, ‘RC’ indicates the seed is reverse complemented, ‘Edited Targets’ is the
total number of seed matches when the transcripts are edited whereas ‘Unedited Targets” indicates the number of
seed matches in the absence of editing activity. ‘Expected Targets’ is the average number of seed matches found
within the windows flanking the edit site.
140