已发表论文

MTFR2  的过表达可预测乳腺癌的预后不良

 

Authors Lu W, Zang R, Du Y, Li X, Li H, Liu C, Song Y, Li Y, Wang Y

Received 14 July 2020

Accepted for publication 1 October 2020

Published 2 November 2020 Volume 2020:12 Pages 11095—11102

DOI https://doi.org/10.2147/CMAR.S272088

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Sanjeev Srivastava

Background: Mitochondrial fission regulator 2  (MTFR2 ) has been reported to promote proliferation, migration and invasion in tumors; however, little is known about its function in breast cancer. Thus, we investigated the effect of MTFR2  expression on prognosis of breast cancer.
Methods: The expression of MTFR2  in breast cancer tissues was detected by immunohistochemistry, and overall survival (OS) and recurrence free survival (RFS) were evaluated by the Log rank test and Cox model.
Results: We found that MTFR2  expression was significantly associated with clinical stage (P< 0.001), T classification (P=0.005), N classification (P=0.001), M classification (P=0.041), HER2  expression (P= 0.001), and molecular subtypes (P=0.002), respectively. Compared with low MTFR2  expression, the patients with higher expression of MTFR2  exhibited significantly shorter OS and RFS (All P < 0.001). Both univariate and multivariate analyses showed that MTFR2  was an independent prognostic factor for OS (HR, 2.8, 95% CI 1.1– 6.8, P = 0.023) and RFS (HR, 2.8, 95% CI 1.2– 6.4, P = 0.015) in breast cancer patients. Moreover, in HER2  positive and TNBC subtype, the associations between high MTFR2  expression and poor OS and RFS were more pronounced.
Conclusion: Taken together, our results demonstrated that high MTFR2  expression was associated with poor prognosis of breast cancer patients, and such an association was more pronounced in the patients with aggressive tumors. Therefore, MTFR2  expression might be a potentially important prognostic biomarker and clinical target for patients with breast cancer.
Keywords: MTFR2 , breast neoplasms, prognosis, biomarker, survival analysis