A wide-ranging record of the genomic elements that might result in various common Breast Cancer subtypes

It is evaluated recently that 450,000 people suffering from breast cancer die every year all over the world in more than 1, 300,000 cases. This disease is classified on clinical basis into three treatment groups. Among them, estrogen receptor (ER) +ve group is a larger one. Another group is HER2 amplified group when targeted effectively resulted in the opening of many more ways for the researchers to investigate on other DNA copy number aberrations. Basal-like breast cancers are otherwise known as triple negative breast cancers, each of them lacking the expression of ER, HER2 and progesterone receptor. The basal-like breast cancers have the therapeutic option of only chemotherapy. Triple negative breast cancers also might influence the disease incidence in breast cancer patients with BRCA1 mutations or if the patients are African origin.

The researchers in this study analyzed primary breast cancers through DNA copy number arrays, Exome sequencing, micro RNA sequencing, DNA methylation, mRNA arrays and reverse-phase protein arrays. By collecting information from five different technical platforms, the researchers could explain more about the already existing gene expression based Breast cancer subtypes. Depending on the significant molecular genetic differences identified from the five different technical platforms, the scientists have validated the presence of four main classes of Breast cancer.

It was estimated that more than ten percent of all Breast cancer cases were caused due to mutations in the GATA3, PIK3CA and TP53 genes. But then, several subtype associated breast cancers were also noticed previously. In the case of luminal A subtype cancer, new mutations causing breast cancer were also observed in MAP3K1, PIK3CA and GATA3 genes. The researchers of this study also could identify two new protein expression subgroups possibly created by specific signaling pathways dominant in two molecular subtypes and by stromal elements. Through integrated analysis, they could identify the two molecular subtypes called HER2 or phosphorylated HER2 and EGFR or phosphorylated EGFR signs in the HER2 protein expression subtype.

The researchers in this study also compared the basal-like breast tumors with the serous ovarian tumors. They could observe certain common molecular origins showing up the association of aetiology and therapeutic prospects between the two types of tumors. Though there are six different technical platforms used in this study to reveal several aspects of breast cancer, two of those molecular studies that could provide valuable content are mRNA expression profiling or DNA copy number analysis and parallel sequencing. Analyzing the mRNA expression data that was clustered revealed that breast cancer was caused by several other intrinsic subtypes indicated by many different disease entities. Recently, large information regarding the breast cancer, concentrated on deformities observed in microRNA expression, DNA methylation and protein expression. This additional information seems to offer some more chances for the scientific community to probe further into the molecular aspects of breast cancer.

In this study, the breast tumor assay was performed by six technical platforms. Each of the technical procedures and certain integrated pathway analysis methods were used for identification of several mutations specific to the subtype, genomic abnormalities that are traceable through treatments and many more activities enhancing the tumor. Some of the genes that were found to be involved in causing breast cancer are PTEN, TP53, CDH1, PIK3CA, MLL3, GATA3, RB1, CDKN1B, MAP3K1 and AKT1. This study has further identified new genes that play their role in breast cancer. The mutations seen in the RUNX1, AFF2, TBX3, CBFB, PTPN22, PIK3R1, PTPRD, SF3B1, NF1, TBX4, TBX5 and CCND3 responsible in several other functions were observed to be playing their part in causing breast cancer.

The basal-like tumor analysis was performed and the common features of this analysis were compared with that of serous ovarian tumor. Both of them were compared with the Luminal sample analysis. The similar features identified were RB1 loss, BRCA1 inactivation, AKT3 expression, Cyclin E1 amplification, expression and amplification of MYC and more number of TP53 mutations. A correlation analysis of the breast cancer expression profile with each tumor of the external multitumor type transcriptomic data set was performed. The mRNA expressions were highly correlating with those of serous ovarian cancers.

Conclusion: The molecular analysis of breast tumors builds up the existing knowledge base with the collection of possible genomic elements responsible for causing common breast cancer subtypes. The various epigenetic and genetic variations led to four main classes of breast cancer. Some of the common genetic factors are observed between certain breast cancer subtypes and serous ovarian cancer. The results here allow us to understand the reason behind the convergent evolution of genes across various organisms as well as the clonal expansion of breast cancer models.

References:

Daniel C. Koboldt, Robert S. Fulton, Michael D. McLellan, Heather Schmidt, Joelle Kalicki-Veizer, Joshua F. McMichael, Lucinda L. Fulton, David J. Dooling, Li Ding, Elaine R. Mardis, & Richard K. Wilson (The Cancer Genome Atlas network). Comprehensive Molecular Portraits of Human Breast Tumors. Nature, 2012; DOI: 10.1038/nature11412

http://www.nature.com/nature/journal/vaop/ncurrent/full/nature11412.html

Washington University School of Medicine (2012, September 23). Some deadly breast cancers share genetic features with ovarian tumors. ScienceDaily. Retrieved September 25, 2012, from http://www.sciencedaily.com/releases/2012/09/120923145106.htm