ID	Duplex structure	Position	Score	MFE
1	miRNA 3' gacgccUUUCUC-UUCGUGCACc 5' | :||| |: |||| Target 5' aaaaccATGGAGTCTGTTCGTGa 3'	292 - 314	96.00	-9.10
2	miRNA 3' gacGCCU-UUC---UCU-UCGUGCACc 5' | || ||| ||| :|| | || Target 5' cctCAGAGAAGACTAGAGGGCTCTTGg 3'	120 - 146	91.00	-11.60
3	miRNA 3' gacgccuuucucuucGUGCACc 5' | |||| Target 5' ctggttcattgcgtcCTCGTGt 3'	212 - 233	88.00	-6.29

Mutant ID	Mutant Position	Mutant Source
COSN30146005	21	COSMIC
COSN30167295	45	COSMIC
COSN30167292	52	COSMIC
COSN8892484	52	COSMIC
COSN31554264	72	COSMIC
COSN30180009	116	COSMIC
COSN7883409	124	COSMIC
COSN1333306	138	COSMIC
COSN9783646	215	COSMIC
COSN31597939	306	COSMIC
COSN21118710	308	COSMIC

Mutant ID	Mutant Position	Mutant Source
rs549735297	4	dbSNP
rs1470788479	5	dbSNP
rs1156464765	9	dbSNP
rs770402396	13	dbSNP
rs776244826	20	dbSNP
rs1435571231	21	dbSNP
rs763364038	24	dbSNP
rs1444471469	25	dbSNP
rs960688191	26	dbSNP
rs1329286685	31	dbSNP
rs1435657727	32	dbSNP
rs990858416	37	dbSNP
rs769262107	41	dbSNP
rs774519663	42	dbSNP
rs762300885	46	dbSNP
rs1219150765	47	dbSNP
rs1266498722	50	dbSNP
rs200598911	52	dbSNP
rs960718932	62	dbSNP
rs1466357923	68	dbSNP
rs916822556	69	dbSNP
rs952412804	70	dbSNP
rs1483456599	72	dbSNP
rs1198905126	75	dbSNP
rs1427471606	80	dbSNP
rs746012779	81	dbSNP
rs908039200	84	dbSNP
rs11539710	86	dbSNP
rs939754513	87	dbSNP
rs769986587	105	dbSNP
rs563158533	107	dbSNP
rs1036735356	112	dbSNP
rs985150581	123	dbSNP
rs1458694520	125	dbSNP
rs909125462	137	dbSNP
rs943233576	140	dbSNP
rs775423514	151	dbSNP
rs1322177720	152	dbSNP
rs761845940	155	dbSNP
rs922396230	157	dbSNP
rs748949522	167	dbSNP
rs538083015	171	dbSNP
rs974529045	177	dbSNP
rs1371801413	180	dbSNP
rs1375998240	185	dbSNP
rs1309848669	189	dbSNP
rs531969033	205	dbSNP
rs551974650	213	dbSNP
rs1447674818	219	dbSNP
rs921363526	221	dbSNP
rs1292069772	224	dbSNP
rs934037859	225	dbSNP
rs933642164	230	dbSNP
rs772025291	231	dbSNP
rs778570621	233	dbSNP
rs1420418836	235	dbSNP
rs1264653509	239	dbSNP
rs945396130	243	dbSNP
rs186362573	252	dbSNP
rs534257314	253	dbSNP
rs1214129341	255	dbSNP
rs946641583	258	dbSNP
rs34086946	260	dbSNP
rs1002399296	268	dbSNP
rs1242219508	269	dbSNP
rs1033825510	274	dbSNP
rs1339215511	282	dbSNP
rs41274910	290	dbSNP
rs1275739161	292	dbSNP
rs547572768	300	dbSNP
rs902351896	306	dbSNP
rs567692482	307	dbSNP
rs1360279765	308	dbSNP
rs1035099991	311	dbSNP
rs536237679	312	dbSNP
rs1375444186	318	dbSNP
rs1266984340	319	dbSNP
rs1433443452	323	dbSNP
rs1270656973	334	dbSNP
rs896594834	336	dbSNP
rs556068488	340	dbSNP
rs1487876850	341	dbSNP
rs1286381591	356	dbSNP
rs571710655	360	dbSNP
rs1206834121	368	dbSNP

- Breast cancer research and treatment, 2014

miRNAs regulate the expression of genes in both normal physiology and disease. While miRNAs have been demonstrated to play a pivotal role in aspects of cancer biology, these reports have generally focused on the regulation of single genes. Such single-gene approaches have significant limitations, relying on miRNA expression levels and heuristic predictions of mRNA-binding sites. This results in only circumstantial evidence of miRNA-target interaction and typically leads to large numbers of false positive predictions. Here, we used a genome-wide approach (high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation, HITS-CLIP) to define direct miRNA-mRNA interactions in three breast cancer subtypes (estrogen receptor positive, Her2 amplified, and triple negative). Focusing on steroid receptor signaling, we identified two novel regulators of the ER pathway (miR-9-5p and miR-193a/b-3p), which together target multiple genes involved in ER signaling. Moreover, this approach enabled the definition of miR-9-5p as a global regulator of steroid receptor signaling in breast cancer. We show that miRNA targets and networks defined by HITS-CLIP under physiologic conditions are predictive of patient outcomes and provide global insight into miRNA regulation in breast cancer.

- Neoplasia (New York, N.Y.), 2016

MicroRNA (miRNA) deregulation in prostate cancer (PCa) contributes to PCa initiation and metastatic progression. To comprehensively define the cancer-associated changes in miRNA targeting and function in commonly studied models of PCa, we performed photoactivatable ribonucleoside-enhanced cross-linking immunoprecipitation of the Argonaute protein in a panel of PCa cell lines modeling different stages of PCa progression. Using this comprehensive catalogue of miRNA targets, we analyzed miRNA targeting on known drivers of PCa and examined tissue-specific and stage-specific pathway targeting by miRNAs. We found that androgen receptor is the most frequently targeted PCa oncogene and that miR-148a targets the largest number of known PCa drivers. Globally, tissue-specific and stage-specific changes in miRNA targeting are driven by homeostatic response to active oncogenic pathways. Our findings indicate that, even in advanced PCa, the miRNA pool adapts to regulate continuing alterations in the cancer genome to balance oncogenic molecular changes. These findings are important because they are the first to globally characterize miRNA changes in PCa and demonstrate how the miRNA target spectrum responds to staged tumorigenesis.