{"id":"W2811135418","doi":"10.1038/s41467-018-04864-8","title":"Targeting EZH2 reactivates a breast cancer subtype-specific anti-metastatic transcriptional program","year":2018,"lang":"en","type":"article","venue":"Nature Communications","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital; McGill University and Génome Québec Innovation Centre; McGill Genome Centre; McGill University; McGill University Health Centre","funders":"Congressionally Directed Medical Research Programs; Canadian Institutes of Health Research; Canada Excellence Research Chairs, Government of Canada; McGill University; U.S. Department of Defense","keywords":"EZH2; Epigenetics; Epigenomics; Breast cancer; Histone; Cancer research; Reprogramming; Cancer; Biology; Metastasis; Histone methyltransferase; PRC2; DNA methylation; Bioinformatics; Medicine; Gene; Genetics; Gene expression","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001302738,0.0001864601,0.0002498911,0.0001190357,0.0000809593,0.0002381881,0.0001217761,0.0001705747,0.001151452],"category_scores_gemma":[0.0001093648,0.00008796783,0.0001244607,0.0000830611,0.000175289,0.0001124694,0.0001506396,0.0004152364,0.0002138044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001676417,"about_ca_system_score_gemma":0.0001977842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004690058,"about_ca_topic_score_gemma":0.001382722,"domain_scores_codex":[0.9999286,0.000008997759,0.000005861423,0.00001564984,0.00002037924,0.00002049263],"domain_scores_gemma":[0.9999396,0.00001229001,0.00001582946,0.000009598432,0.000006121359,0.00001660046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001142295,0.00002481426,0.000277472,0.0000207636,0.000006828347,0.00002131204,0.000005941953,0.00006635321,0.9971692,0.00008209531,0.00006550929,0.002145567],"study_design_scores_gemma":[0.00003030616,0.0005412116,0.005173993,0.000002162034,0.00001755649,0.000248256,0.0000188335,0.0007279579,0.9901782,0.00005330754,0.003005124,0.000003014622],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941993,0.00135748,0.002001509,0.0001743693,0.00003396511,0.00002269757,0.0001962383,0.0001251115,0.0018893],"genre_scores_gemma":[0.9967484,0.0005783822,0.000668626,0.00006072597,0.000009262454,0.00001072922,0.0001796775,0.00001650619,0.001727641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001151452,"threshold_uncertainty_score":0.00385195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02322784581562181,"score_gpt":0.3274370353252389,"score_spread":0.3042091895096171,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}