Microsatellite polymorphism in the EGFR, NOTCH4 and E2F4 genes and their association with breast cancer risk

González-Hernández, Ana Isabel; Henríquez-Hernández, Luis Alberto; León, Antonio Cabrera de; Rodríguez-Pérez, María del Cristo; Murias-Rosales, Adolfo; Domínguez-Coello, Santiago; Brito-Díaz, Buenaventura; Almeida-González, Delia; Aguirre‐Jaime, Armando; Díaz-Chico, B.N.

doi:10.5301/jbm.2012.9583

Cited by 3 publications

(3 citation statements)

References 26 publications

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“…However, a notable feature of these genes is their critical roles in the pathways of gender specific cancers. For example, E2f4 have been reported to regulate liver cancer cell survival and risk for breast cancer 18 - 20 ; Hnrnpk has been linked to the neuroendocrine differentiation signaling in prostate cancer cells 21 as well as to the development of breast cancer 22 . In brain cancer the expression of Hnrnpk has been linked to the Egfr 23 .…”

Section: Discussionmentioning

confidence: 99%

Sex Difference of Egfr Expression and Molecular Pathway in the Liver: Impact on Drug Design and Cancer Treatments?

Wang¹,

Xiao²,

Gu³

et al. 2016

J. Cancer

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Epidermal growth factor receptor (EGFR) has been used as the target in drug design for cancer treatment including the liver cancer. Men and women have different levels of EGFR expression during the life. The whole genome expression profiles of livers of recombinant inbred (RI) strains derived from C57BL/6J (B6) X DBA/2J (D2) were used to compare three major molecular aspects of Egfr gene: the relative expression levels, gene network and eQTLs that regulate the expression of Egfr between female and male mice. Our data suggest that there is a significant difference in the expression levels in the liver between female and male mice. Several important genes in the gene network of Egfr are differentially expressed between female and male mice. The regulatory elements for the expression levels of Egfr between female and male mice are also different. In summary, our data reveals an important sex difference in the Egfr pathways in the liver of the mice. These data may have substantial impact on drug development and dosage determinant for women and men in the clinical trials.

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Section: Discussionmentioning

confidence: 99%

Sex Difference of Egfr Expression and Molecular Pathway in the Liver: Impact on Drug Design and Cancer Treatments?

Wang¹,

Xiao²,

Gu³

et al. 2016

J. Cancer

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“…Short alleles (\13 repeats) of (AGC)n in E2F4 were less frequent in women with cancer than in the control sample. Microsatellite instability of this repeat was also reported in BC [61]. Thus, besides AR gene, other genes with CAG repeats may also contribute to breast carcinogenesis, including POLG, ATN, FXN and E2F4.…”

Section: Genome-wide Cag Repeat Expansions and Breast Cancermentioning

confidence: 90%

Trinucleotide repeat expansions in human breast cancer-susceptibility genes: relevant targets for aspirin chemoprevention?

Altinöz

Tunalı

2015

Clin Transl Oncol

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“…3c, NMB q = 0.03), which encodes a transcription factor that plays a critical role in cell cycle regulation and binds to three known tumour suppressors, pRB, p107 and p13. When affected by microsatellite polymorphisms, E2F4 is linked to an enhanced risk for developing breast cancer 24 . Interestingly, it has also been shown that loss of E2F4 can suppress tumourigenesis 25 while its expression is needed for the proliferation of e.g.…”

Section: (Supplementarymentioning

confidence: 99%

A comparative analysis of network mutation burdens across 21 tumor types augments discovery from cancer genomes

Horn

et al. 2015

Preprint

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Heterogeneity across cancer makes it difficult to find driver genes with intermediate (2-20%) and low frequency (<2%) mutations 1 , and we are potentially missing entire classes of networks (or pathways) of biological and therapeutic value. Here, we quantify the extent to which cancer genes across 21 tumor types have an increased burden of mutations in their immediate gene network derived from functional genomics data. We formalize a classifier that accurately calculates the significance level of a gene's network mutation burden (NMB) and show it can accurately predict known cancer genes and recently proposed driver genes in the majority of tested tumours. Our approach predicts 62 putative cancer genes, including 35 with clear connection to cancer and 27 genes, which point to new cancer biology. NMB identifies proportionally more (4x) low-frequency mutated genes as putative cancer genes than gene-based tests, and provides molecular clues in patients without established driver mutations. Our quantitative and comparative analysis of pan-cancer networks across 21 tumour types gives new insights into the biological and genetic architecture of cancers and enables additional discovery from existing cancer genomes. The framework we present here should become increasingly useful with more sequencing data in the future.

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Microsatellite polymorphism in the EGFR, NOTCH4 and E2F4 genes and their association with breast cancer risk

Cited by 3 publications

References 26 publications

Sex Difference of Egfr Expression and Molecular Pathway in the Liver: Impact on Drug Design and Cancer Treatments?

Sex Difference of Egfr Expression and Molecular Pathway in the Liver: Impact on Drug Design and Cancer Treatments?

Trinucleotide repeat expansions in human breast cancer-susceptibility genes: relevant targets for aspirin chemoprevention?

A comparative analysis of network mutation burdens across 21 tumor types augments discovery from cancer genomes

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