Gene Expression Analysis in Human Breast Cancer

Abstract

Breast Cancer is the most commonly diagnosed cancer in women, with more than 1.2 million women diagnosed annually worldwide. It is also a frequently fatal disease and remains difficult to treat, despite advances in all facets of cancer management. While a number of genetic mutations have been identified in human breast cancers, he specific combinations of the mutations required in concert for formation of a breast carcinoma remains unknown, making precise detection or prognostic predictions impossible. Although estrogen receptor (ER) status is predictive of response to hormonal treatments, there are currently no clinically useful predictive markers of a patient’s response to chemotherapy. This results in all patients who are eligible for chemotherapy receiving the same treatment even though de novo drug resistance will result in the treatment failing in about 80% of cases. Developing improved diagnostic tools to cluster different breast cancers into groups based on genetic parameters has the potential to revolutionise individualised treatment options and subsequent efficacy. This in turn will improve quality of life for patients undergoing therapy who will no longer suffer the consequences of unnecessary treatments and more importantly, a subsequent improved survival rate.