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Wiener klinische Wochenschrift

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01.08.2017 | original article

Expression of caveolin-1 in breast cancer stroma as a potential prognostic biomarker of survival and progression: a meta-analysis

verfasst von: Xiuying Li, Jinfan Sun, Shuenqin Hu

Erschienen in: Wiener klinische Wochenschrift | Ausgabe 15-16/2017

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Summary

Background

It has been shown that caveolin-1 plays a potential role as a diagnostic and prognostic biomarker in various cancer types. The aim of the present study was to clarify whether caveolin-1 expressed in the breast cancer stroma could be a prognostic factor for breast cancer patients.

Methods

We searched the PubMed, ScienceDirect and Web of Science databases for published literature investigating associations between stromal caveolin-1 expression and survival outcome in breast cancer patients. With respect to survival outcomes, the pooled hazard ratios (HRs) of caveolin-1 and the 95% confidence intervals (CI) were calculated.

Results

Our meta-analysis identified a total of 10 studies involving 2072 cases. Further investigation demonstrated that a lack of caveolin-1 expression in the breast cancer stroma is a hazard for overall survival (OS) (HR = 2.33, 95% CI: 1.57–3.46) and disease-free/progression-free survival (DFS/PFS) (HR = 3.05, 95% CI: 2.26–4.12) in breast cancer patients. Moreover, lack of caveolin-1 expression in the cancer-associated fibroblasts was a significant predictor of DFS/PFS (HR = 2.79, 95% CI: 1.75–4.46).

Conclusion

Our results indicated that lack of expression of caveolin-1 in the breast cancer stroma is associated with a poor prognosis.

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Titel: Expression of caveolin-1 in breast cancer stroma as a potential prognostic biomarker of survival and progression: a meta-analysis
verfasst von: Xiuying Li
Jinfan Sun
Shuenqin Hu
Publikationsdatum: 01.08.2017
Verlag: Springer Vienna
Erschienen in: Wiener klinische Wochenschrift / Ausgabe 15-16/2017
Print ISSN: 0043-5325
Elektronische ISSN: 1613-7671
DOI: https://doi.org/10.1007/s00508-017-1173-3

Springer Medizin Österreich

Summary

Background

Methods

Results

Conclusion

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