Identification of Epigenetic Biomarkers with the use of Gene Expression and DNA Methylation for Breast Cancer Subtypes

Breast cancer is one of the most deadly cancers. It has four subtypes: Luminal A (LA), Luminal B (LB), HER2-enriched (HER2-E) and Basal-like (BL). For the cause of breast cancer subtypes, there are different genetic and epigenetic factors involved in its progression and susceptibility. Thus, the identification of genetic and/or epigenetic biomarkers can be helpful to understand the biological mechanisms better and to improve the diagnostic processes of this disease and its subtypes. Hence, this fact motivated us to investigate the epigenetic factor, such as DNA Methylation, with the integration of gene expression in order to find epigenetic biomarkers for breast cancer subtypes. In this regard, we have identified set of up and down regulated genes for each subtype using differential analysis. Thereafter, regression based feature ranking problem is formed in order to find the DNA Methylation site that is mostly responsible for the change in expression of a gene, which is considered as an epigenetic biomarker. A bagging integrated ensemble of decision trees is used for the same. The results of top ten up and down regulated genes and their corresponding most significant DNA Methylation sites are reported for breast cancer subtypes. Moreover, these genes are validated visually by means of survival and expression plots, showing TF-Gene-DNA Methylation interactions, Protein-Protein interaction network, KEGG pathway and GO enrichment analysis. The results show that top differentially expressed up and down regulated genes viz. MMP11, NUF2, EXO1, HJURP, HOXA4, SYNM, CAV1 and COL4A3BP in breast cancer subtypes may change their expression because of DNA Methylation sites viz. cg22418565, cg26029744, cg24741598, cg04550103, cg25952581, cg02109162, cg18498156 and cg04985097 respectively. The code, datasets and supplementary material are present online11http://www.nitttrkol.ac.in/indrajit/projects/epigenetic-mrna-breastcancer-subtypes/.

[1]  Heather C. Wick,et al.  Epigenetic regulation of gene expression in cancer: techniques, resources and analysis , 2017, bioRxiv.

[2]  E. Dahl,et al.  Intermediate filament dynamics and breast cancer: Aberrant promoter methylation of the Synemin gene is associated with early tumor relapse , 2010, Oncogene.

[3]  Lianghong Zheng,et al.  DNA methylation markers for diagnosis and prognosis of common cancers , 2017, Proceedings of the National Academy of Sciences.

[4]  Bing Yao,et al.  Epigenetic Regulations in Neuropsychiatric Disorders , 2019, Front. Genet..

[5]  Zhonghu Bai,et al.  Cancer Hallmarks, Biomarkers and Breast Cancer Molecular Subtypes , 2016, Journal of Cancer.

[6]  K. Robertson.  DNA methylation and human disease , 2005, Nature Reviews Genetics.

[7]  A. Jemal,et al.  Cancer statistics, 2018 , 2018, CA: a cancer journal for clinicians.

[8]  Kesheng Wang,et al.  Integrative Analysis of Genome-wide Expression and Methylation Data , 2013 .

[9]  Philip A. Doble,et al.  MMP-11 as a biomarker for metastatic breast cancer by immunohistochemical-assisted imaging mass spectrometry , 2018, Analytical and Bioanalytical Chemistry.

[10]  Chi-Meng Tzeng,et al.  Integrated Analysis of DNA Methylation and mRNA Expression Profiles to Identify Key Genes in Severe Oligozoospermia , 2017, Front. Physiol..

[11]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumours , 2013 .

[12]  Lucia Altucci,et al.  Cancer epigenetics: Moving forward , 2018, PLoS genetics.

[13]  Muhammad Mustafa,et al.  CTCF negatively regulates HOXA10 expression in breast cancer cells. , 2015, Biochemical and biophysical research communications.

[14]  Joshua M. Stuart,et al.  The Cancer Genome Atlas Pan-Cancer analysis project , 2013, Nature Genetics.

[15]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumors , 2012, Nature.

[16]  Adam G. Marsh,et al.  Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy , 2018, BMC Bioinformatics.

[17]  Kyung-Ah Sohn,et al.  Identification of epigenetic interactions between miRNA and DNA methylation associated with gene expression as potential prognostic markers in bladder cancer , 2017, BMC Medical Genomics.

[18]  Ioana Berindan-Neagoe,et al.  The Epigenetics of Triple-Negative and Basal-Like Breast Cancer: Current Knowledge , 2018, Journal of breast cancer.

[19]  M. Stratton,et al.  The cancer genome , 2009, Nature.