Overexpression of HPIP as a biomarker for metastasis and prognosis prediction in endometrial cancer patients

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Abstract

Background: Hematopoietic pre-B-cell leukemia transcription factor (PBX)-interacting protein (HPIP) has shown to be overexpressed in several human cancers. The purpose of this study was to explore the expression of HPIP in endometrial cancer (EC) and its associated effects on disease. Methods: A total of 113 EC patients at the Harbin Medical University Cancer Hospital between August 2011 and September 2012 were studied for immunohistochemistry analysis. HPIP expression was detected using real-time reverse transcription PCR, Western blotting, and immunohistochemistry. Prognostic value of HPIP expression was examined using multivariate Cox regression analysis and Kaplan-Meier method. Results: The result of Western blotting indicated that HPIP protein expression is significantly high in normal tissues compared to EC tissues (P < 0.001). The expression of HPIP was significantly associated with FIGO stage (P < 0.001), histological grade (P < 0.001), depth of myometrial invasion (P < 0.001), and lymph node metastasis (P = 0.033). Kaplan-Meier analysis demonstrated that there was a significant difference in overall survival and disease-free survival between the two groups of patients stratified by HPIP expression level (log-rank, both P = 0.002). Patients with HPIP high expression had significantly shorter median survival time than those with HPIP low expression. Moreover, results of the multivariate analysis revealed that HPIP expression was an independent prognostic factor for predicting overall survival (P = 0.015) and disease-free survival (P = 0.017) in patients with EC. Conclusion: The present study provides evidence that HPIP predicts EC progression and poor survival, highlighting its potential as a therapeutic target for EC.

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Cheng, L., Zhao, T., Li, S., Wang, Y., Fei, H., & Meng, F. (2019). Overexpression of HPIP as a biomarker for metastasis and prognosis prediction in endometrial cancer patients. Journal of Clinical Laboratory Analysis, 33(8). https://doi.org/10.1002/jcla.22959

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