Dataset Information

E-MTAB-2770

ABSTRACT: RNA-seq of 1019 human cancer cell lines from the Cancer Cell Line Encyclopedia

DISEASE(S): Adult T Acute Lymphoblastic Leukemia,Hilar Cholangiocarcinoma,Childhood B Acute Lymphoblastic Leukemia,Ovarian Granulosa Cell Tumour,Ovarian Mucinous Adenocarcinoma,Ovarian Serous Cystadenocarcinoma,Metastatic Melanoma,Askin Tumor,Fibrosarcoma,Endometrium Adenocarcinoma,Adult B Acute Lymphoblastic Leukemia,Childhood Acute Myeloid Leukemia,Duodenal Adenocarcinoma,Basaloid Squamous Cell Carcinoma,Uterine Sarcoma,Mycosis Fungoides,Papillary Renal Cell Carcinoma,Gliosarcoma,Ovarian Mucinous Cystadenocarcinoma,Pharyngeal Squamous Cell Carcinoma,Papillary Lung Adenocarcinoma,Uterine Carcinosarcoma,Esophageal Squamous Cell Carcinoma,Erythroleukemia,Bladder Transitional Cell Carcinoma,Gallbladder Carcinoma,Primitive Neuroectodermal Tumor,Cutaneous Melanoma,Squamous Cell Lung Carcinoma,T-cell Acute Lymphoblastic Leukemia,Vulvar Leiomyosarcoma,Thyroid Gland Sarcoma,Atypical Teratoid Rhabdoid Tumor,Gastric Tubular Adenocarcinoma,Ovarian Cystadenocarcinoma,Pancreatic Somatostatinoma,Sarcomatoid Mesothelioma,Ovarian Endometrioid Adenocarcinoma,Medulloblastoma,Normal Cell Line,Thyroid Gland Squamous Cell Carcinoma,Adult Acute Myeloid Leukemia,Rectosigmoid Adenocarcinoma,Mucinous Gastric Adenocarcinoma,Childhood T Acute Lymphoblastic Leukemia,Breast Adenocarcinoma,Childhood Acute Megakaryoblastic Leukemia,Bronchoalveolar Adenocarcinoma,Squamous Cell Breast Carcinoma, Acantholytic Variant,Pancreatic Carcinoma,Gastric Adenosquamous Carcinoma,Childhood Acute Monocytic Leukemia,Hereditary Thyroid Gland Medullary Carcinoma,Adult Acute Megakaryoblastic Leukaemia,Pancreatic Adenosquamous Carcinoma,Acute Promyelocytic Leukemia,Endometrial Endometrioid Adenocarcinoma, Variant With Squamous Differentiation,Non-small Cell Lung Carcinoma,Astrocytoma,Ovarian Adenocarcinoma,Hepatocellular Carcinoma,Ovarian Clear Cell Adenocarcinoma,Papillary Thyroid Carcinoma,Intrahepatic Cholangiocarcinoma,Rhabdoid Tumor Of The Kidney,Endometrial Adenosquamous Carcinoma,Cecum Adenocarcinoma,Leiomyoma, Epithelioid,Adult T-cell Leukemia/lymphoma,Adrenal Gland Neuroblastoma,Hodgkins Lymphoma,Malignant Epithelioid Mesothelioma,Esophageal Adenocarcinoma,Amelanotic Melanoma,Endometrial Stromal Sarcoma,Primary Effusion Lymphoma,Bronchogenic Carcinoma,Cervical Squamous Cell Carcinoma,Meningioma,Endometrial Carcinoma,Chondrosarcoma,Breast Carcinoma,Myelodysplastic Syndrome,Adenosquamous Lung Carcinoma,Undifferentiated Carcinoma,Mesothelioma,Colon Carcinoma,Bone Giant Cell Tumor,Epstein-barr Virus-related Burkitt Lymphoma,Pancreatic Ductal Adenocarcinoma,Multiple Endocrine Neoplasia,Chronic Lymphocytic Leukemia,Thyroid Gland Undifferentiated (anaplastic) Carcinoma,Large Cell Lung Carcinoma,Lung Carcinoid Tumor,Renal Cell Adenocarcinoma,Colon Adenocarcinoma,Renal Cell Carcinoma,Ovarian Serous Adenocarcinoma,B-cell Non-hodgkins Lymphoma,Childhood T Lymphoblastic Lymphoma,Malignant Rhabdoid Tumour,Multiple Myeloma,Uterine Leiomyosarcoma,Invasive Lobular Carcinoma,Hypopharyngeal Squamous Cell Carcinoma,Cervical Adenocarcinoma,Ampulla Of Vater Adenocarcinoma,Tongue Squamous Cell Carcinoma,Embryonal Rhabdomyosarcoma,Melanoma,B-cell Prolymphocytic Leukemia,Small Cell Lung Carcinoma,Breast Ductal Adenocarcinoma,Gastric Small Cell Neuroendocrine Carcinoma,Oral Squamous Cell Carcinoma,Alveolar Rhabdomyosarcoma,Ureter Urothelial Carcinoma,Blast Phase Chronic Myelogenous Leukemia, Bcr-abl1 Positive,Burkitts Lymphoma,Barrett Adenocarcinoma,Desmoplastic Medulloblastoma,Pulmonary Mucoepidermoid Carcinoma,Pancreatic Adenocarcinoma,Gastric Adenocarcinoma,Rhabdomyosarcoma,Glioblastoma,Bladder Squamous Cell Carcinoma,Chronic Myelogenous Leukemia,Anaplastic Astrocytoma,Neuroblastoma,Squamous Papilloma,Laryngeal Squamous Cell Carcinoma,Malignant Ovarian Brenner Tumor,Signet Ring Cell Gastric Adenocarcinoma,Colorectal Carcinoma,Acute Myeloid Leukemia,Gastric Carcinoma,Invasive Ductal Carcinoma,Extrarenal Rhabdoid Tumor,Adult Acute Monocytic Leukemia,Osteosarcoma,Cutaneous T-cell Lymphoma,Ovarian Carcinoma,Pleural Mesothelioma,Salivary Gland Squamous Cell Carcinoma,Head And Neck Squamous Cell Carcinoma,Cholangiocarcinoma,Hepatoblastoma,Childhood Acute Myeloid Leukemia With Maturation,Lung Adenocarcinoma,Bladder Carcinoma,Bronchioloalveolar Carcinoma,Transitional Cell Carcinoma Of Kidney,Diffuse Large B-cell Lymphoma,Rectal Adenocarcinoma,Unclassified Pleomorphic Sarcoma,Oligodendroglioma,Follicular Thyroid Carcinoma,Anaplastic Large Cell Lymphoma,Prostate Carcinoma,Lung Giant Cell Carcinoma,Mantle Cell Lymphoma,Chronic Eosinophilic Leukemia,Ewing Sarcoma,High Grade Ovarian Serous Adenocarcinoma,B-cell Acute Lymphoblastic Leukemia,Ovarian Leiomyosarcoma,Clear Cell Renal Carcinoma

PROVIDER: E-MTAB-2770 | ExpressionAtlas | 2025-01-23

REPOSITORIES: ExpressionAtlas

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			Action	DRS
	E-MTAB-2770-analysis-methods.tsv	Tabular
	E-MTAB-2770-analysis-methods.tsv~	Tabular
	E-MTAB-2770-atlasExperimentSummary.Rdata	Rdata
	E-MTAB-2770-coexpressions.tsv.gz	Tabular
	E-MTAB-2770-configuration.xml	Xml

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Project description:Bordel2018 - GSMM for Human Metabolic Reactions (HMR database) This model is described in the article: Constraint based modeling of metabolism allows finding metabolic cancer hallmarks and identifying personalized therapeutic windows Sergio Bordel Oncotarget. 2018; 9:19716-19729 Abstract: In order to choose optimal personalized anticancer treatments, transcriptomic data should be analyzed within the frame of biological networks. The best known human biological network (in terms of the interactions between its different components) is metabolism. Cancer cells have been known to have specific metabolic features for a long time and currently there is a growing interest in characterizing new cancer specific metabolic hallmarks. In this article it is presented a method to find personalized therapeutic windows using RNA-seq data and Genome Scale Metabolic Models. This method is implemented in the python library, pyTARG. Our predictions showed that the most anticancer selective (affecting 27 out of 34 considered cancer cell lines and only 1 out of 6 healthy mesenchymal stem cell lines) single metabolic reactions are those involved in cholesterol biosynthesis. Excluding cholesterol biosynthesis, all the considered cell lines can be selectively affected by targeting different combinations (from 1 to 5 reactions) of only 18 metabolic reactions, which suggests that a small subset of drugs or siRNAs combined in patient specific manners could be at the core of metabolism based personalized treatments. This model is hosted on BioModels Database and identified by: MODEL1707250000. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

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E-MTAB-2770

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