Plamena N. Gabrovska

Single nucleotide polymorphism in hsa-mir-196a-2 and breast cancer risk: a case control study.

microRNAs are small, non-coding RNAs that influence gene expression on a post-transcriptional level. They participate in diverse biological pathways and may act as either tumor suppressor genes or oncogenes. As they may have an effect on thousands of target mRNAs, single-nucleotide polymorphisms in microRNA genes might have major functional consequences, because the microRNAs properties and/or maturation may change. miR-196a has been reported to be aberrantly expressed in breast cancer tissue. Additionally, the SNP rs11614913 in hsa-mir-196a-2 has been found to be associated with breast cancer risk in some studies although not in others. This study evaluated the association between rs11614913 and breast cancer risk in a Caucasian case-control cohort in Queensland, Australia. Results do not support an association of the tested hsa-mir-196a-2 polymorphism with breast cancer susceptibility in this cohort. As there is a discrepancy between our results and previous findings, it is important to assess the role of rs11614913 in breast cancer by further larger studies investigating different ethnic groups.

Investigation of the 1758G>C and 2880A>G variants within the NCOA3 gene in a breast cancer affected Australian population.

NCOA3 is a known low to moderate-risk breast cancer susceptibility gene, amplified in 5-10% and over expressed in about 60% of breast tumours. Additionally, this over expression is associated with Tamoxifen resistance and poor prognosis. Previously, two variants of NCOA3, 1758G>C and 2880A>G have been associated with breast cancer in two independent populations. Here we assessed the influence of the two NCOA3 variants on breast cancer risk by genotyping an Australian case-control study population. 172 cases and 178 controls were successfully genotyped for the 1758G>C variant and 186 cases and 182 controls were successfully genotyped for the 2880A>G variant using high-resolution melt analysis (HRM). The genotypes of the 1758G>C variant were validated by sequencing. χ(2) tests were performed to determine if significant differences exist in the genotype and allele frequencies between the cases and controls. χ(2) analysis returned no statistically significant difference (p>0.05) for genotype frequencies between cases and controls for 1758G>C (χ(2)=0.97, p=0.6158) or 2880A>G (χ(2)=2.09, p=0.3516). Similarly, no statistical difference was observed for allele frequencies for 1758G>C (χ(2)=0.07, p=0.7867) or 2880A>G (χ(2)=0.04, p=0.8365). Haplotype analysis of the two SNPs also showed no difference between the cases and the controls (p=0.9585). Our findings in an Australian Caucasian population composed of breast cancer sufferers and an age matched control population did not support the findings of previous studies demonstrating that these markers play a significant role in breast cancer susceptibility. Here, no significant difference was detected between breast cancer patients and healthy matched controls by either the genotype or allele frequencies for the investigated variants (all p ≥ 0.05). While an association of the two variants and breast cancer was not detected in our case-control study population, exploring these variants in a larger population of the same kind may obtain results in concordance with previous studies. Given the importance of NCOA3 and its involvement in biological processes involved in breast cancer and the possible implications variants of the gene could have on the response to Tamoxifen therapy, NCOA3 remains a candidate for further investigations.

Gene Expression Profiling in Human Breast Cancer – Toward Personalised Therapeutics?

The most integrated approach toward understanding the multiple molecular events and mechanisms by which cancer may develop is the application of gene expression profiling using microarray technologies. As molecular alterations in breast cancer are complex and involve cross-talk between multiple cellular signalling pathways, microarray technology provides a means of capturing and comparing the expression patterns of the entire genome across multiple samples in a high throughput manner. Since the development of microarray technologies, together with the advances in RNA extraction methodologies, gene expression studies have revolutionised the means by which genes suitable as targets for drug development and individualised cancer treatment can be identified. As of the mid-1990s, expression microarrays have been extensively applied to the study of cancer and no cancer type has seen as much genomic attention as breast cancer. The most abundant area of breast cancer genomics has been the clarification and interpretation of gene expression patterns that unite both biological and clinical aspects of tumours. It is hoped that one day molecular profiling will transform diagnosis and therapeutic selection in human breast cancer toward more individualised regimes. Here, we review a number of prominent microarray profiling studies focussed on human breast cancer and examine their strengths, their limitations, clinical implications including prognostic relevance and gene signature significance along with potential improvements for the next generation of microarray studies.