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Open Access 01-02-2019 | Preclinical study

Connexin 43 is an independent predictor of patient outcome in breast cancer patients

Authors: Maria Chasampalioti, Andrew R. Green, Ian O. Ellis, Emad A. Rakha, Andrew M. Jackson, Ian Spendlove, Judith M. Ramage

Published in: Breast Cancer Research and Treatment | Issue 1/2019

Abstract

Purpose

Gap junctions are specialized membrane structures that form channels between adjacent cells allowing cell communication. Gap junctions and specifically Connexin 43 (Cx43) are down-regulated in cancer; however, there are contrasting reports on how this effects breast cancer patient survival. This paper is the first large-scale tissue microarray analysis of Cx43 expression in breast cancer patients with an associated clinical long-term follow-up.

Methods

Using a validated TMA of 1118 primary breast cancers, coupled to a comprehensive database of clinicopathological variables, the expression levels and subcellular localisation of Cx43 was assessed by immunohistochemistry. Its impact in terms of survival, distant metastasis-free survival, and clinicopathological variables was determined.

Results

Patients whose tumors expressed high levels of Cx43 had significantly better survival (p < 0.001) than patients with low levels. High Cx43 expression within tumors was associated with an 18-month survival advantage. Loss of Cx43 expression was associated with markers of poor prognosis, namely large tumor size, high grade, high proliferation status, high pleomorphism, high mitosis, poor Nottingham Prognostic Index (NPI), and triple negative tumors. Cx43 expression was independent of tumor size, grade, stage and ER-status in predicting poor survival on multivariate analysis (p = 0.004).

Conclusion

Connexin 43 (Cx43) is an independent predictor of breast cancer survival and distant metastasis-free survival. High expression of Cx43 was seen in only 13% of tumors, suggesting that drugs to increase Cx43 expression may result in prolonged patients survival.

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Title: Connexin 43 is an independent predictor of patient outcome in breast cancer patients
Authors: Maria Chasampalioti
Andrew R. Green
Ian O. Ellis
Emad A. Rakha
Andrew M. Jackson
Ian Spendlove
Judith M. Ramage
Publication date: 01-02-2019
Publisher: Springer US
Published in: Breast Cancer Research and Treatment / Issue 1/2019
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI: https://doi.org/10.1007/s10549-018-5063-9

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