Expression of microtubule-associated protein tau in breast cancer and its clinical significance: a bioinformatics analysis
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R737.9

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    Abstract:

    Objective: To analyze the expression of microtubule-associated protein tau (MAPT) in breast cancer and its clinical significance though bioinformatics approach.    
    Methods: Data about MAPT expression in breast cancer were downloaded from the public databases that included TCGA, bc-GenExMiner, GEO and Kaplan Meier Plotter. The MAPT expression profiles and their relations with the types of breast cancer as well as the treatment and prognosis of breast cancer were analyzed. 
    Results: The result of overall analysis showed that MAPT expression was higher in breast cancer tissue than that in normal breast tissue (P<0.01), but the results of stratified analysis showed that MAPT expression was increased in breast cancer with low malignancy, early clinical stage or sensitivity to endocrine therapy and conversely, the opposite was true. Breast cancer with high MAPT expression was more sensitive to tamoxifen but more likely resistant to paclitaxel (P<0.01). The result of overall analysis showed that the overall survival and relapse-free survival in patients with high MAPT expression were longer than those in patients with low MAPT expression (HR=0.65, 95% CI=0.48–0.89, P<0.05; HR=2.91, 95% CI=1.54–5.51, P<0.05), but the results of stratified analysis showed that consistent result was only achieved in patients with Luminal A breast cancer, while the irrelevant or opposite results were seen in patients with other types of breast cancer.
    Conclusion: MAPT expressions are diversified in different types of breast cancer, which were closely associated with drug resistance and prognosis of breast cancer. So, it is of certain clinical significance for treatment selection and the prognostic assessment of breast cancer.

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ZHAO Dongyi, ZHOU Enxiang, LI Lun, YANG Yongping, XIE Pingfang. Expression of microtubule-associated protein tau in breast cancer and its clinical significance: a bioinformatics analysis[J]. Chin J Gen Surg,2019,28(5):597-605.
DOI:10.7659/j. issn.1005-6947.2019.05.012

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History
  • Received:February 22,2019
  • Revised:April 16,2019
  • Adopted:
  • Online: May 25,2019
  • Published: