{"id":"W4376272496","doi":"10.1016/j.jtho.2023.05.007","title":"Combination Therapy With MDM2 and MEK Inhibitors Is Effective in Patient-Derived Models of Lung Adenocarcinoma With Concurrent Oncogenic Drivers and MDM2 Amplification","year":2023,"lang":"en","type":"article","venue":"Journal of Thoracic Oncology","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Marie-Josée and Henry R. Kravis Center for Molecular Oncology; Loxo Oncology; National Cancer Institute; National Institutes of Health; Royal College of Physicians and Surgeons of Canada; Helsinn; Janssen Pharmaceuticals; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb","keywords":"Trametinib; Mdm2; Medicine; Cancer research; Adenocarcinoma; Lung cancer; Targeted therapy; MAPK/ERK pathway; MEK inhibitor; Cancer; Oncology; Internal medicine; Kinase; Gene; Biology; Genetics","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":[0.0002799939,0.0005482485,0.0007186034,0.0004143866,0.0002802094,0.0006764177,0.0004534104,0.0005217283,0.001822345],"category_scores_gemma":[0.0001817835,0.0002225137,0.0004939465,0.0002944691,0.0003361313,0.0004113545,0.0002020822,0.001708515,0.0003520308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000452664,"about_ca_system_score_gemma":0.0005983844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001006776,"about_ca_topic_score_gemma":0.004485682,"domain_scores_codex":[0.9997311,0.00005599859,0.00001995005,0.00004089784,0.00007649816,0.00007550771],"domain_scores_gemma":[0.9998158,0.00003441133,0.00003060295,0.00002690757,0.00001338145,0.00007898248],"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":[0.008421011,0.005305869,0.002862954,0.0002808745,0.0002791127,0.0005418057,0.000100602,0.00355947,0.9459471,0.0008603238,0.003716799,0.02812409],"study_design_scores_gemma":[0.001707047,0.03492359,0.01677293,0.0000354575,0.0003804556,0.002110657,0.0002534475,0.008037199,0.9178264,0.0004830015,0.01741109,0.00005880847],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990681,0.002252689,0.001393669,0.0004638189,0.0002826367,0.0001597045,0.001213715,0.0001794697,0.003373371],"genre_scores_gemma":[0.994806,0.0009716144,0.001196388,0.00008710512,0.00002413393,0.00007829758,0.0009245602,0.00001679756,0.001895064],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001822345,"threshold_uncertainty_score":0.006096363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01762607695905787,"score_gpt":0.3820243639162987,"score_spread":0.3643982869572408,"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."}}