Methylation-related genes involved in renal carcinoma progression

Zamora-Fuentes, Jose María; Hernández-Lemus, Enrique; Espinal-Enríquez, Jesús

doi:10.3389/fgene.2023.1225158

Cited by 3 publications

(2 citation statements)

References 76 publications

(82 reference statements)

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“…Finally, we also investigated whether the methylation profile of DNA may be involved in this loss of long-range co-expression in cancer. We showed that, despite the fact that methylation profile does exert influence on particular genes that may affect the cell states depending on the progression stage [28], we cannot establish a clear association between methylation profiles and co-expression between neighboring genes.…”

Section: Loss Of Long-range Co-expression In Cancermentioning

confidence: 64%

The Role of Transcription Factors in the Loss of Inter-Chromosomal Co-Expression for Breast Cancer Subtypes

Trujillo-Ortíz,

Espinal-Enríquez,

Hernández-Lemus

2023

IJMS

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Breast cancer encompasses a diverse array of subtypes, each exhibiting distinct clinical characteristics and treatment responses. Unraveling the underlying regulatory mechanisms that govern gene expression patterns in these subtypes is essential for advancing our understanding of breast cancer biology. Gene co-expression networks (GCNs) help us identify groups of genes that work in coordination. Previous research has revealed a marked reduction in the interaction of genes located on different chromosomes within GCNs for breast cancer, as well as for lung, kidney, and hematopoietic cancers. However, the reasons behind why genes on the same chromosome often co-express remain unclear. In this study, we investigate the role of transcription factors in shaping gene co-expression networks within the four main breast cancer subtypes: Luminal A, Luminal B, HER2+, and Basal, along with normal breast tissue. We identify communities within each GCN and calculate the transcription factors that may regulate these communities, comparing the results across different phenotypes. Our findings indicate that, in general, regulatory behavior is to a large extent similar among breast cancer molecular subtypes and even in healthy networks. This suggests that transcription factor motif usage does not fully determine long-range co-expression patterns. Specific transcription factor motifs, such as CCGGAAG, appear frequently across all phenotypes, even involving multiple highly connected transcription factors. Additionally, certain transcription factors exhibit unique actions in specific subtypes but with limited influence. Our research demonstrates that the loss of inter-chromosomal co-expression is not solely attributable to transcription factor regulation. Although the exact mechanism responsible for this phenomenon remains elusive, this work contributes to a better understanding of gene expression regulatory programs in breast cancer.

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Section: Loss Of Long-range Co-expression In Cancermentioning

confidence: 64%

The Role of Transcription Factors in the Loss of Inter-Chromosomal Co-Expression for Breast Cancer Subtypes

Trujillo-Ortíz,

Espinal-Enríquez,

Hernández-Lemus

2023

IJMS

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“…The genes in cancerous samples tend to co-express mainly with their nearest neighbors and lose co-expression relations with medium and long distance genes. This phenomenon has been observed in lung cancer (Andonegui-Elguera et al, 2021), clear cell renal carcinoma (Zamora-Fuentes et al, 2020;Zamora-Fuentes et al, 2022), as well as other thirteen types of cancer (Garcia-Cortes et al, 2022).…”

Section: Introductionmentioning

confidence: 68%

CNVs in 8q24.3 do not influence gene co-expression in breast cancer subtypes

2023

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Gene co-expression networks are a useful tool in the study of interactions that have allowed the visualization and quantification of diverse phenomena, including the loss of co-expression over long distances in cancerous samples. This characteristic, which could be considered fundamental to cancer, has been widely reported in various types of tumors. Since copy number variations (CNVs) have previously been identified as causing multiple genetic diseases, and gene expression is linked to them, they have often been mentioned as a probable cause of loss of co-expression in cancerous networks. In order to carry out a comparative study of the validity of this statement, we took 477 protein-coding genes from chromosome 8, and the CNVs of 101 genes, also protein-coding, belonging to the 8q24.3 region, a cytoband that is particularly active in the appearance of breast cancer. We created CNVS-conditioned co-expression networks of each of the 101 genes in the 8q24.3 region using conditional mutual information. The study was carried out using the four molecular subtypes of breast cancer (Luminal A, Luminal B, Her2, and Basal), as well as a case corresponding to healthy samples. We observed that in all cancer cases, the measurement of the Kolmogorov-Smirnov statistic shows that there are no significant differences between one and other values of the CNVs for any case. Furthermore, the co-expression interactions are stronger in all cancer subtypes than in the control networks. However, the control network presents a homogeneously distributed set of co-expression interactions, while for cancer networks, the highest interactions are more confined to specific cytobands, in particular 8q24.3 and 8p21.3. With this approach, we demonstrate that despite copy number alterations in the 8q24 region being a common trait in breast cancer, the loss of long-distance co-expression in breast cancer is not determined by CNVs.

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