Combination of breast cancer microarray data by using bioinformatic methods - Meta-analysis approaches
Dedeoğlu, Bala Gür
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Today breast cancer is one of the major cancer types among women in the world. After lung cancer, it is the second leading cause of cancer death in women. Breast cancer is a multi-factorial and complex genetic disease, which was studied in detail at the molecular level. With the use of microarray technology breast cancer was classified into molecular subtypes. Although some genes were found to be responsible for the development and the progression of the disease, many of the molecular mechanisms underlying breast cancer progression remain poorly understood. This deficit has led to significant interest in the quest for novel predictive markers for breast cancer. Microarray is a high throughput technique, which provides to detection of thousands of genes' expression. There are many publicly accessible databases, which have raw and processed data of microarray analysis and clinical and /or pathological information of samples. Meta-analysis approaches are provided more information from independent microarray datasets, which were uploaded on publicly accessible databases. Meta-analysis approaches are used for different cancer types and various diseases including breast cancer increasingly in recent years. These methods allow the finding of predictive biomarkers for the development and progression of the disease while they can also be used for new or alternative targets for the treatment of the disease. Meta-analysis might increase the knowledge by gathering and processing individual microarray datasets. Accordingly it is predicted that new or alternative targets might be identified by researching on numerous disease mechanisms including breast cancer.