{"database":"EGA","file_versions":[],"scores":null,"additional":{"omics_type":["Genomics"],"study_type":["Other"],"full_dataset_link":["https://ega-archive.org/studies/EGAS00001006461"],"host":["EGA"],"description":["EGA study EGAS00001006461"],"dataset_title":["High-resolution lung adenocarcinoma expression subtypes"],"repository":["EGA"],"category":["restricted"],"name_synonyms":["bronchogenic lung adenocarcinoma, Adenocarcinoma, l(2)k06503, Lung, 2-amino-4-(methylsulfanyl)butanoic acid, E 920, Hgfr, 5830411I20, xcdk4, L-Zystein, 5730555F13Rik, cdk4/6, Pk?7, HGF, HGFR, PDCD1L1, cdk, F15E12.6, 2-amino-3-mercaptopropanoic acid, Cystein, RCCP2, B7-H1, CD274, C, Programmed death ligand 1, F15E12_6, MUB3_18, scatter factor receptor, cisteina, CG5072, M, E-920, LUAD, plstire, PSK-J3, Hcys, PD-L1, MUB3.18, AUTS9, cdk4, 2-amino-4-(methylthio)butanoic acid, CYSTEINE, CMM3, dCdk4, FREE CYSTEINE, CDK4, AI838057, (2R)-2-amino-3-mercaptopropanoic acid, RG7MT1, metionina, Racemethionine, l(2)05428, AI504062, PDL1, proto-oncogene c-Met, DL-Methionine, PRO, 2-Amino-4-(methylthio)butyric acid, MCPH12, 9130215G10Rik, Adenocarcinomas, CYS, Cys, l(2)s4639, adenocarcinoma of the lung, PDCD1LG1, Methionin, PDCD1 ligand 1, Hmet, (2R)-2-amino-3-sulfanylpropanoic acid, and GLY protein 2, DmCdk4, Zystein, Met, MET, ATCMPG1, ATCMPG2, Lung Adenocarcinomas, HGF receptor, HGF/SF receptor, B7H1, B7 homolog 1, and GLY protein 1, B7-H., 2-amino-3-sulfanylpropanoic acid, adenocarcinoma of lung, tyrosine-protein kinase Met, L-2-Amino-3-mercaptopropionic acid, non-small cell lung adenocarcinoma, (R)-2-amino-3-mercaptopropanoic acid, Cdk4/6, Crk2, Crk3, hCMT1c, DmelCG5072, c-Met, 2-Amino-3-mercaptopropionic acid, L-Cystein, nonsmall cell adenocarcinoma, 8-6, Lung Adenocarcinoma, CDK4/6, PLSTIRE, lung adenocarcinoma, alpha-amino-gamma-methylmercaptobutyric acid, l(2)0671, E920, Pk53C, Par4, 5730455C01Rik, l(2)sh0671, SF receptor"],"description_synonyms":["bronchogenic lung adenocarcinoma, Adenocarcinoma, Biological Markers, Viral Marker, Lung, Surrogate Endpoints, Clinical Markers, Laboratory, Individualized Medicine, Clinical Marker, Neoplasms, Benign Neoplasm, Biochemical, Endpoint, Development, Tumor, Serum, Malignant, Surrogate End Points, Surrogate Markers, Laboratory Markers, Biological, responsivity, Consensus, Line, Precision, treatment, Biomarker, reactivity, Clinical, Individualized, Malignancy, LUAD, Biological Marker, Neoplasias, Immunologic Markers, Immune, Markers, malignant neoplasm, Viral Markers, Clients, disease management, Therapies, Medicine, Malignancies, Consensus Development, Predictive, Immunologic Marker, Biologic, Cancer, Tumors, Therapy, Viral, Malignant Neoplasm, Surrogate Endpoint, Predictive Medicine, Serum Markers, Cell Lines, Immunotherapies., End Point, Biochemical Markers, Personalized, Biologic Marker, Adenocarcinomas, Client, Cell, Immune Marker, adenocarcinoma of the lung, MT, Benign, Marker, Surrogate End Point, Personalized Medicine, Neoplasm, Biologic Markers, Lines, Lung Adenocarcinomas, primary cancer, Serum Marker, End Points, Surrogate, adenocarcinoma of lung, Endpoints, common, Benign Neoplasms, non-small cell lung adenocarcinoma, Theranostic, patient, Cancers, Immunologic, Laboratory Marker, malignant tumor, Treatments, Surrogate Marker, Malignant Neoplasms, nonsmall cell adenocarcinoma, Lung Adenocarcinoma, lung adenocarcinoma, Therapeutic, P-Health, Patient, Biochemical Marker, Theranostics, Treatment, P Health, response, Neoplasia, Immune Markers"],"additional_accession":[]},"is_claimable":false,"name":"High-resolution lung adenocarcinoma expression subtypes identify tumors with dependencies on MET, CDK4, CDK6, and PD-L1","description":"Lung adenocarcinoma is one of the most common cancer types with various treatment modalities. However, better biomarkers to predict therapeutic response are still needed to improve precision medicine. We utilized a consensus hierarchical clustering approach on 509 LUAD cases from TCGA to identify five robust LUAD expression subtypes. We then integrated genomic (patient and cell line) and proteomic data to help define biomarkers of response to targeted therapies and immunotherapies. This approach defined subtypes with unique proteogenomic and dependency\nprofiles.","dates":{"updated":"2022-09-09 10:59:10"},"accession":"EGAS00001006461","cross_references":{"TAXONOMY":["9606"],"EGA":["EGAD00001009339","EGAC00001002853"]}}