Gene Co-Expression in Breast Cancer: A Matter of Distance

Gene regulatory and signaling phenomena are known to be relevant players underlying the establishment of cellular phenotypes. It is also known that such regulatory programs are disrupted in cancer, leading to the onset and development of malignant phenotypes. Gene co-expression matrices have allowed...

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Autores principales:	Alfredo González-Espinoza, Jose Zamora-Fuentes, Enrique Hernández-Lemus, Jesús Espinal-Enríquez
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	eigenvalue decomposition gene co-expression clustering loss of long-distance co-expression co-expression matrices breast cancer molecular subtypes Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/d497c37a8dc7469fac2ddec516d424a2
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spelling	oai:doaj.org-article:d497c37a8dc7469fac2ddec516d424a22021-11-17T13:00:35ZGene Co-Expression in Breast Cancer: A Matter of Distance2234-943X10.3389/fonc.2021.726493https://doaj.org/article/d497c37a8dc7469fac2ddec516d424a22021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fonc.2021.726493/fullhttps://doaj.org/toc/2234-943XGene regulatory and signaling phenomena are known to be relevant players underlying the establishment of cellular phenotypes. It is also known that such regulatory programs are disrupted in cancer, leading to the onset and development of malignant phenotypes. Gene co-expression matrices have allowed us to compare and analyze complex phenotypes such as breast cancer (BrCa) and their control counterparts. Global co-expression patterns have revealed, for instance, that the highest gene-gene co-expression interactions often occur between genes from the same chromosome (cis-), meanwhile inter-chromosome (trans-) interactions are scarce and have lower correlation values. Furthermore, strength of cis- correlations have been shown to decay with the chromosome distance of gene couples. Despite this loss of long-distance co-expression has been clearly identified, it has been observed only in a small fraction of the whole co-expression landscape, namely the most significant interactions. For that reason, an approach that takes into account the whole interaction set results appealing. In this work, we developed a hybrid method to analyze whole-chromosome Pearson correlation matrices for the four BrCa subtypes (Luminal A, Luminal B, HER2+ and Basal), as well as adjacent normal breast tissue derived matrices. We implemented a systematic method for clustering gene couples, by using eigenvalue spectral decomposition and the k–medoids algorithm, allowing us to determine a number of clusters without removing any interaction. With this method we compared, for each chromosome in the five phenotypes: a) Whether or not the gene-gene co-expression decays with the distance in the breast cancer subtypes b) the chromosome location of cis- clusters of gene couples, and c) whether or not the loss of long-distance co-expression is observed in the whole range of interactions. We found that in the correlation matrix for the control phenotype, positive and negative Pearson correlations deviate from a random null model independently of the distance between couples. Conversely, for all BrCa subtypes, in all chromosomes, positive correlations decay with distance, and negative correlations do not differ from the null model. We also found that BrCa clusters are distance-dependent, meanwhile for the control phenotype, chromosome location does not determine the clustering. To our knowledge, this is the first time that a dependence on distance is reported for gene clusters in breast cancer. Since this method uses the whole cis- interaction geneset, combination with other -omics approaches may provide further evidence to understand in a more integrative fashion, the mechanisms that disrupt gene regulation in cancer.Alfredo González-EspinozaAlfredo González-EspinozaJose Zamora-FuentesEnrique Hernández-LemusEnrique Hernández-LemusJesús Espinal-EnríquezJesús Espinal-EnríquezFrontiers Media S.A.articleeigenvalue decompositiongene co-expression clusteringloss of long-distance co-expressionco-expression matricesbreast cancer molecular subtypesNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENFrontiers in Oncology, Vol 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	eigenvalue decomposition gene co-expression clustering loss of long-distance co-expression co-expression matrices breast cancer molecular subtypes Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	eigenvalue decomposition gene co-expression clustering loss of long-distance co-expression co-expression matrices breast cancer molecular subtypes Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Alfredo González-Espinoza Alfredo González-Espinoza Jose Zamora-Fuentes Enrique Hernández-Lemus Enrique Hernández-Lemus Jesús Espinal-Enríquez Jesús Espinal-Enríquez Gene Co-Expression in Breast Cancer: A Matter of Distance
description	Gene regulatory and signaling phenomena are known to be relevant players underlying the establishment of cellular phenotypes. It is also known that such regulatory programs are disrupted in cancer, leading to the onset and development of malignant phenotypes. Gene co-expression matrices have allowed us to compare and analyze complex phenotypes such as breast cancer (BrCa) and their control counterparts. Global co-expression patterns have revealed, for instance, that the highest gene-gene co-expression interactions often occur between genes from the same chromosome (cis-), meanwhile inter-chromosome (trans-) interactions are scarce and have lower correlation values. Furthermore, strength of cis- correlations have been shown to decay with the chromosome distance of gene couples. Despite this loss of long-distance co-expression has been clearly identified, it has been observed only in a small fraction of the whole co-expression landscape, namely the most significant interactions. For that reason, an approach that takes into account the whole interaction set results appealing. In this work, we developed a hybrid method to analyze whole-chromosome Pearson correlation matrices for the four BrCa subtypes (Luminal A, Luminal B, HER2+ and Basal), as well as adjacent normal breast tissue derived matrices. We implemented a systematic method for clustering gene couples, by using eigenvalue spectral decomposition and the k–medoids algorithm, allowing us to determine a number of clusters without removing any interaction. With this method we compared, for each chromosome in the five phenotypes: a) Whether or not the gene-gene co-expression decays with the distance in the breast cancer subtypes b) the chromosome location of cis- clusters of gene couples, and c) whether or not the loss of long-distance co-expression is observed in the whole range of interactions. We found that in the correlation matrix for the control phenotype, positive and negative Pearson correlations deviate from a random null model independently of the distance between couples. Conversely, for all BrCa subtypes, in all chromosomes, positive correlations decay with distance, and negative correlations do not differ from the null model. We also found that BrCa clusters are distance-dependent, meanwhile for the control phenotype, chromosome location does not determine the clustering. To our knowledge, this is the first time that a dependence on distance is reported for gene clusters in breast cancer. Since this method uses the whole cis- interaction geneset, combination with other -omics approaches may provide further evidence to understand in a more integrative fashion, the mechanisms that disrupt gene regulation in cancer.
format	article
author	Alfredo González-Espinoza Alfredo González-Espinoza Jose Zamora-Fuentes Enrique Hernández-Lemus Enrique Hernández-Lemus Jesús Espinal-Enríquez Jesús Espinal-Enríquez
author_facet	Alfredo González-Espinoza Alfredo González-Espinoza Jose Zamora-Fuentes Enrique Hernández-Lemus Enrique Hernández-Lemus Jesús Espinal-Enríquez Jesús Espinal-Enríquez
author_sort	Alfredo González-Espinoza
title	Gene Co-Expression in Breast Cancer: A Matter of Distance
title_short	Gene Co-Expression in Breast Cancer: A Matter of Distance
title_full	Gene Co-Expression in Breast Cancer: A Matter of Distance
title_fullStr	Gene Co-Expression in Breast Cancer: A Matter of Distance
title_full_unstemmed	Gene Co-Expression in Breast Cancer: A Matter of Distance
title_sort	gene co-expression in breast cancer: a matter of distance
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/d497c37a8dc7469fac2ddec516d424a2
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Gene Co-Expression in Breast Cancer: A Matter of Distance

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