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Comparative study and meta-analysis of meta-analysis studies for the correlation of genomic markers with early cancer detection

A large number of common disorders, including cancer, have complex genetic traits, with multiple genetic and environmental components contributing to susceptibility. A literature search revealed that even among several meta-analyses, there were ambiguous results and conclusions. In the current study...

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Autores principales: Lanara, Zoi, Giannopoulou, Efstathia, Fullen, Marta, Kostantinopoulos, Evangelos, Nebel, Jean-Christophe, Kalofonos, Haralabos P, Patrinos, George P, Pavlidis, Cristiana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3686617/
https://www.ncbi.nlm.nih.gov/pubmed/23738773
http://dx.doi.org/10.1186/1479-7364-7-14
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author Lanara, Zoi
Giannopoulou, Efstathia
Fullen, Marta
Kostantinopoulos, Evangelos
Nebel, Jean-Christophe
Kalofonos, Haralabos P
Patrinos, George P
Pavlidis, Cristiana
author_facet Lanara, Zoi
Giannopoulou, Efstathia
Fullen, Marta
Kostantinopoulos, Evangelos
Nebel, Jean-Christophe
Kalofonos, Haralabos P
Patrinos, George P
Pavlidis, Cristiana
author_sort Lanara, Zoi
collection PubMed
description A large number of common disorders, including cancer, have complex genetic traits, with multiple genetic and environmental components contributing to susceptibility. A literature search revealed that even among several meta-analyses, there were ambiguous results and conclusions. In the current study, we conducted a thorough meta-analysis gathering the published meta-analysis studies previously reported to correlate any random effect or predictive value of genome variations in certain genes for various types of cancer. The overall analysis was initially aimed to result in associations (1) among genes which when mutated lead to different types of cancer (e.g. common metabolic pathways) and (2) between groups of genes and types of cancer. We have meta-analysed 150 meta-analysis articles which included 4,474 studies, 2,452,510 cases and 3,091,626 controls (5,544,136 individuals in total) including various racial groups and other population groups (native Americans, Latinos, Aborigines, etc.). Our results were not only consistent with previously published literature but also depicted novel correlations of genes with new cancer types. Our analysis revealed a total of 17 gene-disease pairs that are affected and generated gene/disease clusters, many of which proved to be independent of the criteria used, which suggests that these clusters are biologically meaningful.
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spelling pubmed-36866172013-06-25 Comparative study and meta-analysis of meta-analysis studies for the correlation of genomic markers with early cancer detection Lanara, Zoi Giannopoulou, Efstathia Fullen, Marta Kostantinopoulos, Evangelos Nebel, Jean-Christophe Kalofonos, Haralabos P Patrinos, George P Pavlidis, Cristiana Hum Genomics Primary Research A large number of common disorders, including cancer, have complex genetic traits, with multiple genetic and environmental components contributing to susceptibility. A literature search revealed that even among several meta-analyses, there were ambiguous results and conclusions. In the current study, we conducted a thorough meta-analysis gathering the published meta-analysis studies previously reported to correlate any random effect or predictive value of genome variations in certain genes for various types of cancer. The overall analysis was initially aimed to result in associations (1) among genes which when mutated lead to different types of cancer (e.g. common metabolic pathways) and (2) between groups of genes and types of cancer. We have meta-analysed 150 meta-analysis articles which included 4,474 studies, 2,452,510 cases and 3,091,626 controls (5,544,136 individuals in total) including various racial groups and other population groups (native Americans, Latinos, Aborigines, etc.). Our results were not only consistent with previously published literature but also depicted novel correlations of genes with new cancer types. Our analysis revealed a total of 17 gene-disease pairs that are affected and generated gene/disease clusters, many of which proved to be independent of the criteria used, which suggests that these clusters are biologically meaningful. BioMed Central 2013-06-05 /pmc/articles/PMC3686617/ /pubmed/23738773 http://dx.doi.org/10.1186/1479-7364-7-14 Text en Copyright © 2013 Lanara et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Primary Research
Lanara, Zoi
Giannopoulou, Efstathia
Fullen, Marta
Kostantinopoulos, Evangelos
Nebel, Jean-Christophe
Kalofonos, Haralabos P
Patrinos, George P
Pavlidis, Cristiana
Comparative study and meta-analysis of meta-analysis studies for the correlation of genomic markers with early cancer detection
title Comparative study and meta-analysis of meta-analysis studies for the correlation of genomic markers with early cancer detection
title_full Comparative study and meta-analysis of meta-analysis studies for the correlation of genomic markers with early cancer detection
title_fullStr Comparative study and meta-analysis of meta-analysis studies for the correlation of genomic markers with early cancer detection
title_full_unstemmed Comparative study and meta-analysis of meta-analysis studies for the correlation of genomic markers with early cancer detection
title_short Comparative study and meta-analysis of meta-analysis studies for the correlation of genomic markers with early cancer detection
title_sort comparative study and meta-analysis of meta-analysis studies for the correlation of genomic markers with early cancer detection
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3686617/
https://www.ncbi.nlm.nih.gov/pubmed/23738773
http://dx.doi.org/10.1186/1479-7364-7-14
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