Base de dados : MEDLINE
Pesquisa : G05.360.340.024.340.375 [Categoria DeCS]
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[PMID]:28453687
[Au] Autor:Spainhour JCG; Lim J; Qiu P
[Ad] Endereço:Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.
[Ti] Título:GDISC: a web portal for integrative analysis of gene-drug interaction for survival in cancer.
[So] Source:Bioinformatics;33(9):1426-1428, 2017 May 01.
[Is] ISSN:1367-4811
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:Summary: Survival analysis has been applied to The Cancer Genome Atlas (TCGA) data. Although drug exposure records are available in TCGA, existing survival analyses typically did not consider drug exposure, partly due to naming inconsistencies in the data. We have spent extensive effort to standardize the drug exposure data, which enabled us to perform survival analysis on drug-stratified subpopulations of cancer patients. Using this strategy, we integrated gene copy number data, drug exposure data and patient survival data to infer gene-drug interactions that impact survival. The collection of all analyzed gene-drug interactions in 32 cancer types are organized and presented in a searchable web-portal called gene-drug Interaction for survival in cancer (GDISC). GDISC allows biologists and clinicians to interactively explore the gene-drug interactions identified in the context of TCGA, and discover interactions associated to their favorite cancer, drug and/or gene of interest. In addition, GDISC provides the standardized drug exposure data, which is a valuable resource for developing new methods for drug-specific analysis. Availability and Implementation: GDISC is available at https://gdisc.bme.gatech.edu/. Contact: peng.qiu@bme.gatech.edu.
[Mh] Termos MeSH primário: Antineoplásicos/farmacologia
Interação Gene-Ambiente
Genes Neoplásicos/efeitos dos fármacos
Neoplasias/genética
Software
Análise de Sobrevida
[Mh] Termos MeSH secundário: Antineoplásicos/uso terapêutico
Biologia Computacional/métodos
Seres Humanos
Neoplasias/tratamento farmacológico
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Antineoplastic Agents)
[Em] Mês de entrada:1801
[Cu] Atualização por classe:180308
[Lr] Data última revisão:
180308
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170429
[St] Status:MEDLINE
[do] DOI:10.1093/bioinformatics/btw830


  2 / 2595 MEDLINE  
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[PMID]:29295995
[Au] Autor:Schubert M; Klinger B; Klünemann M; Sieber A; Uhlitz F; Sauer S; Garnett MJ; Blüthgen N; Saez-Rodriguez J
[Ad] Endereço:European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, CB10 1SD, UK.
[Ti] Título:Perturbation-response genes reveal signaling footprints in cancer gene expression.
[So] Source:Nat Commun;9(1):20, 2018 01 02.
[Is] ISSN:2041-1723
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:Aberrant cell signaling can cause cancer and other diseases and is a focal point of drug research. A common approach is to infer signaling activity of pathways from gene expression. However, mapping gene expression to pathway components disregards the effect of post-translational modifications, and downstream signatures represent very specific experimental conditions. Here we present PROGENy, a method that overcomes both limitations by leveraging a large compendium of publicly available perturbation experiments to yield a common core of Pathway RespOnsive GENes. Unlike pathway mapping methods, PROGENy can (i) recover the effect of known driver mutations, (ii) provide or improve strong markers for drug indications, and (iii) distinguish between oncogenic and tumor suppressor pathways for patient survival. Collectively, these results show that PROGENy accurately infers pathway activity from gene expression in a wide range of conditions.
[Mh] Termos MeSH primário: Expressão Gênica
Genes Neoplásicos
Genômica/métodos
Neoplasias/genética
[Mh] Termos MeSH secundário: Linhagem Celular Tumoral
Resistência a Medicamentos Antineoplásicos
Células HEK293
Seres Humanos
Mutação
Neoplasias/mortalidade
[Pt] Tipo de publicação:EVALUATION STUDIES; JOURNAL ARTICLE; RESEARCH SUPPORT, NON-U.S. GOV'T
[Em] Mês de entrada:1802
[Cu] Atualização por classe:180212
[Lr] Data última revisão:
180212
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:180104
[St] Status:MEDLINE
[do] DOI:10.1038/s41467-017-02391-6


  3 / 2595 MEDLINE  
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[PMID]:29253611
[Au] Autor:Guan L; Tan J; Li H; Jin X
[Ad] Endereço:Department of Hepatobiliary Surgery, China-Japan Union Hospital of Jilin University, Changchun, Jilin, China.
[Ti] Título:Biomarker identification in clear cell renal cell carcinoma based on miRNA-seq and digital gene expression-seq data.
[So] Source:Gene;647:205-212, 2018 Mar 20.
[Is] ISSN:1879-0038
[Cp] País de publicação:Netherlands
[La] Idioma:eng
[Ab] Resumo:This study aimed to explore the underlying microRNA (miRNA) targets in clear cell renal cell carcinoma (ccRCC). The expression profile with accession number GSE24952 was downloaded from the Gene Expression Omnibus database. Based on the dataset, the differentially expressed genes (DEGs) and miRNAs in ccRCC tissues and matched normal adjacent tissues were analyzed. The target genes of the differentially expressed miRNAs were then predicted. Expression levels of several key miRNAs and genes were detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR). A total of 168 up- and 288 downregulated DEGs, and 26 up- and 54 downregulated differentially expressed miRNAs were identified. The target genes of miRNA-429 (TGFB1, CCND1, EGFR, and LAMC1) and miRNA-206 (CCND1 and EGFR) were upregulated. Based on the tumor suppressor (TS) gene and tumor-associated gene (TAG) databases, miRNA-142-5p was selected from the upregulated miRNAs. miRNA-429, miRNA-422a, miRNA-206, miRNA-132-3p, and miRNA-184 were selected from the downregulated miRNAs. Moreover, the miRNA regulation network revealed that CCND1 was the common target gene of miRNA-429, miRNA-206, and miRNA-184, and ATP1B1 was the common target gene of miRNA-140-3p and miRNA-142-5p. qRT-PCR revealed that the expression levels of miR-140-3p and CCND1 significantly increased, while that of ATP1B1 significantly decreased in 786-O cells compared with those in human renal tubular epithelial cells, which was in accordance with the predicted results of bioinformatic analysis. In conclusion, miRNA-429, miRNA-206, and miRNA-184 and their target gene CCND1, as well as miRNA-140-3p and miRNA-142-5p and their target gene ATP1B1, might play key roles in ccRCC progression and could be useful biomarkers during ccRCC development.
[Mh] Termos MeSH primário: Biomarcadores Tumorais/genética
Carcinoma de Células Renais/genética
Regulação Neoplásica da Expressão Gênica/genética
Expressão Gênica/genética
Neoplasias Renais/genética
MicroRNAs/genética
[Mh] Termos MeSH secundário: Linhagem Celular Tumoral
Biologia Computacional/métodos
Regulação para Baixo/genética
Perfilação da Expressão Gênica/métodos
Genes Neoplásicos/genética
Seres Humanos
Regulação para Cima/genética
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Biomarkers, Tumor); 0 (MicroRNAs)
[Em] Mês de entrada:1802
[Cu] Atualização por classe:180209
[Lr] Data última revisão:
180209
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171219
[St] Status:MEDLINE


  4 / 2595 MEDLINE  
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[PMID]:28459449
[Au] Autor:Roper J; Tammela T; Cetinbas NM; Akkad A; Roghanian A; Rickelt S; Almeqdadi M; Wu K; Oberli MA; Sánchez-Rivera FJ; Park YK; Liang X; Eng G; Taylor MS; Azimi R; Kedrin D; Neupane R; Beyaz S; Sicinska ET; Suarez Y; Yoo J; Chen L; Zukerberg L; Katajisto P; Deshpande V; Bass AJ; Tsichlis PN; Lees J; Langer R; Hynes RO; Chen J; Bhutkar A; Jacks T; Yilmaz ÖH
[Ad] Endereço:The David H. Koch Institute for Integrative Cancer Research at MIT, Cambridge, Massachusetts, USA.
[Ti] Título:In vivo genome editing and organoid transplantation models of colorectal cancer and metastasis.
[So] Source:Nat Biotechnol;35(6):569-576, 2017 06.
[Is] ISSN:1546-1696
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:In vivo interrogation of the function of genes implicated in tumorigenesis is limited by the need to generate and cross germline mutant mice. Here we describe approaches to model colorectal cancer (CRC) and metastasis, which rely on in situ gene editing and orthotopic organoid transplantation in mice without cancer-predisposing mutations. Autochthonous tumor formation is induced by CRISPR-Cas9-based editing of the Apc and Trp53 tumor suppressor genes in colon epithelial cells and by orthotopic transplantation of Apc-edited colon organoids. ApcΔ/Δ;Kras ;Trp53Δ/Δ (AKP) mouse colon organoids and human CRC organoids engraft in the distal colon and metastasize to the liver. Finally, we apply the orthotopic transplantation model to characterize the clonal dynamics of Lgr5 stem cells and demonstrate sequential activation of an oncogene in established colon adenomas. These experimental systems enable rapid in vivo characterization of cancer-associated genes and reproduce the entire spectrum of tumor progression and metastasis.
[Mh] Termos MeSH primário: Neoplasias Colorretais/genética
Modelos Animais de Doenças
Edição de Genes/métodos
Genes Neoplásicos/genética
Neoplasias Hepáticas/genética
Neoplasias Hepáticas/secundário
Transplante de Órgãos/métodos
[Mh] Termos MeSH secundário: Animais
Carcinogênese/genética
Linhagem Celular Tumoral
Repetições Palindrômicas Curtas Agrupadas e Regularmente Espaçadas/genética
Feminino
Masculino
Camundongos
Camundongos Transgênicos
Metástase Neoplásica
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1708
[Cu] Atualização por classe:180207
[Lr] Data última revisão:
180207
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170502
[St] Status:MEDLINE
[do] DOI:10.1038/nbt.3836


  5 / 2595 MEDLINE  
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[PMID]:29369605
[Au] Autor:Prokofyeva DS; Mingajeva ET; Bogdanova NV; Faiskhanova RR; Sakaeva DD; Dörk T; Khusnutdinova EK
[Ti] Título:[The search for new candidate genes involved in ovarian cancer pathogenesis by exome sequencing].
[So] Source:Genetika;52(10):1215-21, 2016 Oct.
[Is] ISSN:0016-6758
[Cp] País de publicação:Russia (Federation)
[La] Idioma:rus
[Ab] Resumo:Ovarian cancer is one of the most insidious of tumors among gynecological cancers in the world. BRCA1 and BRCA2 mutations are associated with high risk of ovarian cancer; however, they are causative only in a fraction of cases. The search for new genes would expand our understanding of the mechanisms underlying malignant ovarian tumors and could help to develop new methods of early diagnosis and treatment of the disease. The present study involved exome sequencing of eight DNA samples extracted from the blood of ovarian cancer patients. As a result of the study, 53057 modifications in one sample were identified on average. Of them, 222 nucleotide sequence modifications in DNA located in exons and splice sites of 203 genes were selected. On the basis of the function of these genes in the cell and their involvement in carcinogenesis, 40 novel candidate genes were selected. These genes are involved in cell cycle control, DNA repair, apoptosis, regulation of cell invasion, proliferation and growth, transcription, and also immune response and might be involved in development of ovarian cancer.
[Mh] Termos MeSH primário: Genes Neoplásicos
Neoplasias Ovarianas/genética
Sequenciamento Completo do Exoma
[Mh] Termos MeSH secundário: Feminino
Seres Humanos
Neoplasias Ovarianas/patologia
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1802
[Cu] Atualização por classe:180205
[Lr] Data última revisão:
180205
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:180126
[St] Status:MEDLINE


  6 / 2595 MEDLINE  
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[PMID]:28459450
[Au] Autor:O'Rourke KP; Loizou E; Livshits G; Schatoff EM; Baslan T; Manchado E; Simon J; Romesser PB; Leach B; Han T; Pauli C; Beltran H; Rubin MA; Dow LE; Lowe SW
[Ad] Endereço:Weill Cornell Medicine/Rockefeller University/Sloan Kettering Tri-Institutional MD-PhD Program, New York, New York, USA.
[Ti] Título:Transplantation of engineered organoids enables rapid generation of metastatic mouse models of colorectal cancer.
[So] Source:Nat Biotechnol;35(6):577-582, 2017 Jun.
[Is] ISSN:1546-1696
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Colorectal cancer (CRC) is a leading cause of death in the developed world, yet facile preclinical models that mimic the natural stages of CRC progression are lacking. Through the orthotopic engraftment of colon organoids we describe a broadly usable immunocompetent CRC model that recapitulates the entire adenoma-adenocarcinoma-metastasis axis in vivo. The engraftment procedure takes less than 5 minutes, shows efficient tumor engraftment in two-thirds of mice, and can be achieved using organoids derived from genetically engineered mouse models (GEMMs), wild-type organoids engineered ex vivo, or from patient-derived human CRC organoids. In this model, we describe the genotype and time-dependent progression of CRCs from adenocarcinoma (6 weeks), to local disseminated disease (11-12 weeks), and spontaneous metastasis (>20 weeks). Further, we use the system to show that loss of dysregulated Wnt signaling is critical for the progression of disseminated CRCs. Thus, our approach provides a fast and flexible means to produce tailored CRC mouse models for genetic studies and pre-clinical investigation.
[Mh] Termos MeSH primário: Neoplasias Colorretais/genética
Modelos Animais de Doenças
Edição de Genes/métodos
Genes Neoplásicos/genética
Neoplasias Hepáticas/genética
Neoplasias Hepáticas/secundário
Transplante de Órgãos/métodos
[Mh] Termos MeSH secundário: Animais
Carcinogênese/genética
Linhagem Celular Tumoral
Repetições Palindrômicas Curtas Agrupadas e Regularmente Espaçadas/genética
Feminino
Masculino
Camundongos
Camundongos Transgênicos
Metástase Neoplásica
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Em] Mês de entrada:1708
[Cu] Atualização por classe:180116
[Lr] Data última revisão:
180116
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170502
[St] Status:MEDLINE
[do] DOI:10.1038/nbt.3837


  7 / 2595 MEDLINE  
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[PMID]:29059177
[Au] Autor:Roman T; Xie L; Schwartz R
[Ad] Endereço:Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
[Ti] Título:Automated deconvolution of structured mixtures from heterogeneous tumor genomic data.
[So] Source:PLoS Comput Biol;13(10):e1005815, 2017 Oct.
[Is] ISSN:1553-7358
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:With increasing appreciation for the extent and importance of intratumor heterogeneity, much attention in cancer research has focused on profiling heterogeneity on a single patient level. Although true single-cell genomic technologies are rapidly improving, they remain too noisy and costly at present for population-level studies. Bulk sequencing remains the standard for population-scale tumor genomics, creating a need for computational tools to separate contributions of multiple tumor clones and assorted stromal and infiltrating cell populations to pooled genomic data. All such methods are limited to coarse approximations of only a few cell subpopulations, however. In prior work, we demonstrated the feasibility of improving cell type deconvolution by taking advantage of substructure in genomic mixtures via a strategy called simplicial complex unmixing. We improve on past work by introducing enhancements to automate learning of substructured genomic mixtures, with specific emphasis on genome-wide copy number variation (CNV) data, as well as the ability to process quantitative RNA expression data, and heterogeneous combinations of RNA and CNV data. We introduce methods for dimensionality estimation to better decompose mixture model substructure; fuzzy clustering to better identify substructure in sparse, noisy data; and automated model inference methods for other key model parameters. We further demonstrate their effectiveness in identifying mixture substructure in true breast cancer CNV data from the Cancer Genome Atlas (TCGA). Source code is available at https://github.com/tedroman/WSCUnmix.
[Mh] Termos MeSH primário: Neoplasias da Mama/genética
Mapeamento Cromossômico/métodos
Dosagem de Genes/genética
Genes Neoplásicos/genética
Sequenciamento de Nucleotídeos em Larga Escala/métodos
Análise de Sequência de DNA/métodos
[Mh] Termos MeSH secundário: Interpretação Estatística de Dados
Feminino
Perfilação da Expressão Gênica/métodos
Seres Humanos
Reprodutibilidade dos Testes
Sensibilidade e Especificidade
[Pt] Tipo de publicação:COMPARATIVE STUDY; EVALUATION STUDIES; JOURNAL ARTICLE; VALIDATION STUDIES
[Em] Mês de entrada:1711
[Cu] Atualização por classe:171113
[Lr] Data última revisão:
171113
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171024
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pcbi.1005815


  8 / 2595 MEDLINE  
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[PMID]:29025590
[Au] Autor:Qian Y; Mancini-DiNardo D; Judkins T; Cox HC; Brown K; Elias M; Singh N; Daniels C; Holladay J; Coffee B; Bowles KR; Roa BB
[Ad] Endereço:Myriad Genetic Laboratories, Inc., 320 Wakara Way, Salt Lake City, UT 84108, USA.
[Ti] Título:Identification of pathogenic retrotransposon insertions in cancer predisposition genes.
[So] Source:Cancer Genet;216-217:159-169, 2017 Oct.
[Is] ISSN:2210-7762
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Cancer risks have been previously reported for some retrotransposon element (RE) insertions; however, detection of these insertions is technically challenging and very few oncogenic RE insertions have been reported. Here we evaluate RE insertions identified during hereditary cancer genetic testing using a comprehensive testing strategy. Individuals who had single-syndrome or pan-cancer hereditary cancer genetic testing from February 2004 to March 2017 were included. RE insertions were identified using Sanger sequencing, Next Generation Sequencing, or multiplex quantitative PCR, and further characterized using targeted PCR and sequencing analysis. Personal cancer history, ancestry, and haplotype were evaluated. A total of 37 unique RE insertions were identified in 10 genes, affecting 211 individuals. BRCA2 accounted for 45.9% (17/37) of all unique RE insertions. Several RE insertions were detected with high frequency in populations of conserved ancestry wherein up to 100% of carriers shared a high degree of haplotype conservation, suggesting founder effects. Our comprehensive testing strategy resulted in a substantial increase in the number of reported oncogenic RE insertions, several of which may have possible founder effects. Collectively, these data show that the detection of RE insertions is an important component of hereditary cancer genetic testing and may be more prevalent than previously reported.
[Mh] Termos MeSH primário: Genes Neoplásicos
Predisposição Genética para Doença
Mutagênese Insercional/genética
Neoplasias/genética
Retroelementos/genética
[Mh] Termos MeSH secundário: Elementos Alu/genética
Sequência de Bases
Efeito Fundador
Haplótipos/genética
Seres Humanos
Mutação/genética
Fatores de Risco
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Retroelements)
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171030
[Lr] Data última revisão:
171030
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:171014
[St] Status:MEDLINE


  9 / 2595 MEDLINE  
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[PMID]:28957313
[Au] Autor:Voigt A; Nowick K; Almaas E
[Ad] Endereço:Network Systems Biology Group, Department of Biotechnology, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.
[Ti] Título:A composite network of conserved and tissue specific gene interactions reveals possible genetic interactions in glioma.
[So] Source:PLoS Comput Biol;13(9):e1005739, 2017 Sep.
[Is] ISSN:1553-7358
[Cp] País de publicação:United States
[La] Idioma:eng
[Ab] Resumo:Differential co-expression network analyses have recently become an important step in the investigation of cellular differentiation and dysfunctional gene-regulation in cell and tissue disease-states. The resulting networks have been analyzed to identify and understand pathways associated with disorders, or to infer molecular interactions. However, existing methods for differential co-expression network analysis are unable to distinguish between various forms of differential co-expression. To close this gap, here we define the three different kinds (conserved, specific, and differentiated) of differential co-expression and present a systematic framework, CSD, for differential co-expression network analysis that incorporates these interactions on an equal footing. In addition, our method includes a subsampling strategy to estimate the variance of co-expressions. Our framework is applicable to a wide variety of cases, such as the study of differential co-expression networks between healthy and disease states, before and after treatments, or between species. Applying the CSD approach to a published gene-expression data set of cerebral cortex and basal ganglia samples from healthy individuals, we find that the resulting CSD network is enriched in genes associated with cognitive function, signaling pathways involving compounds with well-known roles in the central nervous system, as well as certain neurological diseases. From the CSD analysis, we identify a set of prominent hubs of differential co-expression, whose neighborhood contains a substantial number of genes associated with glioblastoma. The resulting gene-sets identified by our CSD analysis also contain many genes that so far have not been recognized as having a role in glioblastoma, but are good candidates for further studies. CSD may thus aid in hypothesis-generation for functional disease-associations.
[Mh] Termos MeSH primário: Neoplasias Encefálicas/genética
Perfilação da Expressão Gênica
Regulação Neoplásica da Expressão Gênica
Genes Neoplásicos/genética
Predisposição Genética para Doença/genética
Glioma/genética
Modelos Genéticos
[Mh] Termos MeSH secundário: Animais
Simulação por Computador
Seres Humanos
Proteínas de Neoplasias/genética
[Pt] Tipo de publicação:JOURNAL ARTICLE
[Nm] Nome de substância:
0 (Neoplasm Proteins)
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171031
[Lr] Data última revisão:
171031
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170929
[St] Status:MEDLINE
[do] DOI:10.1371/journal.pcbi.1005739


  10 / 2595 MEDLINE  
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[PMID]:28934488
[Au] Autor:Alcaraz N; List M; Batra R; Vandin F; Ditzel HJ; Baumbach J
[Ad] Endereço:Department of Mathematics and Computer Science, University of Southern Denmark, 5230 Odense, Denmark.
[Ti] Título:De novo pathway-based biomarker identification.
[So] Source:Nucleic Acids Res;45(16):e151, 2017 Sep 19.
[Is] ISSN:1362-4962
[Cp] País de publicação:England
[La] Idioma:eng
[Ab] Resumo:Gene expression profiles have been extensively discussed as an aid to guide the therapy by predicting disease outcome for the patients suffering from complex diseases, such as cancer. However, prediction models built upon single-gene (SG) features show poor stability and performance on independent datasets. Attempts to mitigate these drawbacks have led to the development of network-based approaches that integrate pathway information to produce meta-gene (MG) features. Also, MG approaches have only dealt with the two-class problem of good versus poor outcome prediction. Stratifying patients based on their molecular subtypes can provide a detailed view of the disease and lead to more personalized therapies. We propose and discuss a novel MG approach based on de novo pathways, which for the first time have been used as features in a multi-class setting to predict cancer subtypes. Comprehensive evaluation in a large cohort of breast cancer samples from The Cancer Genome Atlas (TCGA) revealed that MGs are considerably more stable than SG models, while also providing valuable insight into the cancer hallmarks that drive them. In addition, when tested on an independent benchmark non-TCGA dataset, MG features consistently outperformed SG models. We provide an easy-to-use web service at http://pathclass.compbio.sdu.dk where users can upload their own gene expression datasets from breast cancer studies and obtain the subtype predictions from all the classifiers.
[Mh] Termos MeSH primário: Biomarcadores Tumorais/genética
Neoplasias da Mama/genética
Perfilação da Expressão Gênica/métodos
[Mh] Termos MeSH secundário: Biomarcadores Tumorais/metabolismo
Neoplasias da Mama/classificação
Neoplasias da Mama/metabolismo
Metilação de DNA
Feminino
Genes Neoplásicos
Seres Humanos
[Pt] Tipo de publicação:JOURNAL ARTICLE; VALIDATION STUDIES
[Nm] Nome de substância:
0 (Biomarkers, Tumor)
[Em] Mês de entrada:1710
[Cu] Atualização por classe:171024
[Lr] Data última revisão:
171024
[Sb] Subgrupo de revista:IM
[Da] Data de entrada para processamento:170922
[St] Status:MEDLINE
[do] DOI:10.1093/nar/gkx642



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