Elevated expression of podocalyxin is associated with lymphatic invasion, basal-like phenotype, and clinical outcome in axillary lymph node-negative breast cancer
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Lymphatic invasion (LVI) is associated with disease recurrence in axillary node-negative (ANN) breast cancer. Using gene expression profiling of 105 ANN tumors, we found that podocalyxin (PODXL) was more highly expressed in tumors with LVI (LVI+) than in those without LVI (LVI−). Differences in PODXL expression were validated using real-time polymerase chain reaction as well as by immunohistochemistry in an independent set of 652 tumors on tissue microarrays. Disease-free survival (DFS) analyses were conducted for association of high PODXL protein expression with risk of distant recurrence overall and within breast cancer subtypes using both Cox and cure-rate models. High PODXL expression was associated with poor prognosis features including large tumor size, high histological grade, estrogen and progesterone receptor negativity, and with clinical alterations characteristic of the basal-like breast cancer phenotype. Surprisingly, despite having other poor prognosis characteristics, women with high PODXL expressing tumors had better long-term DFS in multivariate analysis with traditional clinicopathologic factors including LVI and HER2 status (P = 0.001). PODXL has the potential to be a useful biomarker for identifying good prognosis patients in characteristically poor prognosis breast cancer groups and may impact treatment of women with this disease.
KeywordsPodocalyxin Lymphatic invasion Breast cancer Cure-rate model
Epidermal growth factor receptor
Gene expression array
Human epidermal growth factor receptor 2
Real-time polymerase chain reaction
This study has been supported by a grant from the Canadian Institutes of Health Research and with funds provided by the Terry Fox Run (ILA, SBB, FO’M), by a Senior Investigator award from the Canadian Institutes of Health Research (SBB), and by project funds from the MITACS Network of Centres of Excellence in Mathematical Sciences (SBB). YEY is supported by MITACS Industrial Fellowship and a CIHR Fellow in Genetic Epidemiology and Statistical Genetics with CIHR STAGE (Strategic Training for Advanced Genetic Epidemiology). The authors thank the study participants and gratefully acknowledge the technical assistance of Lucine Bosnoyan-Collins and Suzanne Tjan and the contributions of the Toronto Breast Cancer Group to this work. We also thank Candemir Cigsar for statistical insights.
Conflict of interest
The authors declare they have no conflicts of interest.
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