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Experimental gene expression analysis of 12 cancer cell lines

ABSTRACT: The accurate choice of anti-cancer drugs is important problem of modern medicine. We developed a new method for the selection of targeted drugs based on detection of specific intracellular signaling and metabolic pathways in the bioinformatic system termed OncoFinder before the treatment. We obtained transcriptomic data 12 human cancer cell lines (NT2/D1, Tera-1, NGP, HepG2, BT474, Skov-3, T3M4, HeLa, A549, MCF-7, Jurkat, BxPc1) before a treatment. In our research for gene expression quantile normalization of the experimental data of all 12 cell lines together, we used separately eleven gene expression datasets corresponding to different normal human tissues profiled on Illumina HT-12v3-4 platform, 4-33 samples per dataset (from GEO). Normalization datasets used for the processing of the experimental transcriptomic data: GSE17822 (GSM444688, GSM444689, GSM444690, GSM444691, GSM444692, GSM444693), GSE26852 (GSM661123, GSM661124, GSM661125, GSM661126, GSM661127, GSM661128, GSM661130), GSE32124 (GSM796359, GSM796360, GSM796361, GSM796362, GSM796363, GSM796364, GSM796365, GSM796366, GSM796367, GSM796368, GSM796369, GSM796370, GSM796371, GSM796372, GSM796373, GSM796374, GSM796375, GSM796376, GSM796377, GSM796378, GSM796379, GSM796380, GSM796381, GSM796382, GSM796383, GSM796384, GSM796385, GSM796386, GSM796387, GSM796388, GSM796389, GSM796390, GSM796391), GSE34074 (GSM841415, GSM841419, GSM841423, GSM841427, GSM841431, GSM841435), GSE37013 (GSM908514, GSM908515, GSM908516, GSM908517, GSM908518, GSM908519, GSM908520), GSE40645 (GSM998797, GSM998798, GSM998799, GSM998800, GSM998801, GSM998802, GSM998803, GSM998804, GSM998805, GSM998806, GSM998807, GSM998808, GSM998809, GSM998810), GSE42656 (GSM1047460, GSM1047462, GSM1047463, GSM1047467), GSE52130 (GSM1260102, GSM1260103, GSM1260104, GSM1260105, GSM1260106, GSM1260107, GSM1260108), GSE54563 (GSM1318920, GSM1318921, GSM1318922, GSM1318923, GSM1318924, GSM1318925, GSM1318926, GSM1318927, GSM1318928, GSM1318929, GSM1318930, GSM1318931, GSM1318932, GSM1318933, GSM1318934, GSM1318935, GSM1318936, GSM1318937, GSM1318938, GSM1318939, GSM1318940, GSM1318941, GSM1318945, GSM1318946, GSM1318947), GSE57218 (GSM1380887, GSM1380888, GSM1380956, GSM1380957, GSM1380958, GSM1380959), GSE60709 (GSM1486145, GSM1486146, GSM1486160, GSM1486161, GSM1486162, GSM1486163, GSM1486164, GSM1486165, GSM1486166, GSM1486167, GSM1486168, GSM1486169, GSM1486170, GSM1486171, GSM1486172, GSM1486173). Normalization of the 12 new cell line data was performed independently 11 times together with the data from the GSM ID numbers listed above. For GSM1486145, data for replicate samples 34 and 35 were used. For sample GSM1486146, data for replicate sample 36 was used.

ORGANISM(S): Homo sapiens

PROVIDER: GSE65314 | GEO | 2015/01/27

SECONDARY ACCESSION(S): PRJNA273662

REPOSITORIES: GEO

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Project description:The accurate choice of anti-cancer drugs is important problem of modern medicine. We developed a new method for the selection of targeted drugs based on detection of specific intracellular signaling and metabolic pathways in the bioinformatic system termed OncoFinder before the treatment. We obtained transcriptomic data 12 human cancer cell lines (NT2/D1, Tera-1, NGP, HepG2, BT474, Skov-3, T3M4, HeLa, A549, MCF-7, Jurkat, BxPc1) before a treatment. In our research for gene expression quantile normalization of the experimental data of all 12 cell lines together, we used separately eleven gene expression datasets corresponding to different normal human tissues profiled on Illumina HT-12v3-4 platform, 4-33 samples per dataset (from GEO). Normalization datasets used for the processing of the experimental transcriptomic data: GSE17822 (GSM444688, GSM444689, GSM444690, GSM444691, GSM444692, GSM444693), GSE26852 (GSM661123, GSM661124, GSM661125, GSM661126, GSM661127, GSM661128, GSM661130), GSE32124 (GSM796359, GSM796360, GSM796361, GSM796362, GSM796363, GSM796364, GSM796365, GSM796366, GSM796367, GSM796368, GSM796369, GSM796370, GSM796371, GSM796372, GSM796373, GSM796374, GSM796375, GSM796376, GSM796377, GSM796378, GSM796379, GSM796380, GSM796381, GSM796382, GSM796383, GSM796384, GSM796385, GSM796386, GSM796387, GSM796388, GSM796389, GSM796390, GSM796391), GSE34074 (GSM841415, GSM841419, GSM841423, GSM841427, GSM841431, GSM841435), GSE37013 (GSM908514, GSM908515, GSM908516, GSM908517, GSM908518, GSM908519, GSM908520), GSE40645 (GSM998797, GSM998798, GSM998799, GSM998800, GSM998801, GSM998802, GSM998803, GSM998804, GSM998805, GSM998806, GSM998807, GSM998808, GSM998809, GSM998810), GSE42656 (GSM1047460, GSM1047462, GSM1047463, GSM1047467), GSE52130 (GSM1260102, GSM1260103, GSM1260104, GSM1260105, GSM1260106, GSM1260107, GSM1260108), GSE54563 (GSM1318920, GSM1318921, GSM1318922, GSM1318923, GSM1318924, GSM1318925, GSM1318926, GSM1318927, GSM1318928, GSM1318929, GSM1318930, GSM1318931, GSM1318932, GSM1318933, GSM1318934, GSM1318935, GSM1318936, GSM1318937, GSM1318938, GSM1318939, GSM1318940, GSM1318941, GSM1318945, GSM1318946, GSM1318947), GSE57218 (GSM1380887, GSM1380888, GSM1380956, GSM1380957, GSM1380958, GSM1380959), GSE60709 (GSM1486145, GSM1486146, GSM1486160, GSM1486161, GSM1486162, GSM1486163, GSM1486164, GSM1486165, GSM1486166, GSM1486167, GSM1486168, GSM1486169, GSM1486170, GSM1486171, GSM1486172, GSM1486173). Normalization of the 12 new cell line data was performed independently 11 times together with the data from the GSM ID numbers listed above. For GSM1486145, data for replicate samples 34 and 35 were used. For sample GSM1486146, data for replicate sample 36 was used. Total RNA obtained from NT2/D1, Tera-1, NGP, HepG2, BT474, Skov-3, T3M4, HeLa, A549, MCF-7, Jurkat, BxPc1 cell lines.

Project description:Reed2003 - Genome-scale metabolic network of Escherichia coli (iJR904) This model is described in the article: An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Reed JL, Vo TD, Schilling CH, Palsson BO. Genome Biol. 2003; 4(9): R54 Abstract: BACKGROUND: Diverse datasets, including genomic, transcriptomic, proteomic and metabolomic data, are becoming readily available for specific organisms. There is currently a need to integrate these datasets within an in silico modeling framework. Constraint-based models of Escherichia coli K-12 MG1655 have been developed and used to study the bacterium's metabolism and phenotypic behavior. The most comprehensive E. coli model to date (E. coli iJE660a GSM) accounts for 660 genes and includes 627 unique biochemical reactions. RESULTS: An expanded genome-scale metabolic model of E. coli (iJR904 GSM/GPR) has been reconstructed which includes 904 genes and 931 unique biochemical reactions. The reactions in the expanded model are both elementally and charge balanced. Network gap analysis led to putative assignments for 55 open reading frames (ORFs). Gene to protein to reaction associations (GPR) are now directly included in the model. Comparisons between predictions made by iJR904 and iJE660a models show that they are generally similar but differ under certain circumstances. Analysis of genome-scale proton balancing shows how the flux of protons into and out of the medium is important for maximizing cellular growth. CONCLUSIONS: E. coli iJR904 has improved capabilities over iJE660a. iJR904 is a more complete and chemically accurate description of E. coli metabolism than iJE660a. Perhaps most importantly, iJR904 can be used for analyzing and integrating the diverse datasets. iJR904 will help to outline the genotype-phenotype relationship for E. coli K-12, as it can account for genomic, transcriptomic, proteomic and fluxomic data simultaneously. This model is hosted on BioModels Database and identified by: MODEL1507180060. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. 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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Experimental gene expression analysis of 12 cancer cell lines

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