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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Microarrays in breast cancer research and clinical practice--the future lies ahead
Sofia K Gruvberger-Saal1, Heather E Cunliffe, Kristen M Carr
1Institute for Cancer Genetics, Columbia University, New York, New York 10032, and New York Presbyterian Hospital, New York, NY 10021, USA.
Abstract:
Molecular profiling for classification and prognostic purposes has demonstrated that the genetic signatures of tumors contain information regarding biological properties as well as clinical behavior. This review highlights the progress that has been made in the field of gene expression profiling of human breast cancer. Breast cancer has become one of the most intensely studied human malignancies in the genomic era; several hundred papers over the last few years have investigated various clinical and biological aspects of human breast cancer using high-throughput molecular profiling techniques. Given the grossly heterogeneous nature of the disease and the lack of robust conventional markers for disease prediction, prognosis, and response to treatment, the notion that a transcriptional profile comprising multiple genes, rather than any single gene or other parameter, will be more predictive of tumor behavior is both appealing and reasonable. Promising results have emerged from these studies, correlating gene expression profiles with prognosis, recurrence, metastatic potential, therapeutic response, as well as biological and functional aspects of the disease. Clearly, the integration of genomic approaches into the clinic lies in the near future, but prospective studies based on larger patient cohorts representing the whole spectrum of breast cancer, oncogenic pathway-based studies, attendant care in bioinformatic analyses and validation studies are needed before the full promise of gene expression profiling can be realized in the clinical setting.
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