• Dépistage, diagnostic, pronostic

  • Évaluation des technologies et des biomarqueurs

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Clinicopathological and prognostic significance of programmed death ligand-1 expression in breast cancer: a meta-analysis

A partir d'une revue systématique de la littérature publiée jusqu'en avril 2016 (6 études), cette méta-analyse évalue, chez les patientes atteintes d'un cancer du sein (7 877 cas), l'association entre le niveau d'expression intratumorale de PD-L1 et l'agressivité de la tumeur (grade tumoral, présence de métastases ganglionnaires) ainsi que la survie

Background : Programmed cell death-ligand 1 (PD-L1) may be a useful molecule for targeted immunotherapy. Therefore, this meta-analysis aimed to investigate PD-L1 expression in breast cancer and its associations with clinicopathological factors and outcomes, which may help determine whether PD-L1 expression is a useful prognostic marker.

Methods : The Medline Ovid, Cochrane, PubMed, Google Scholar, and Web of Knowledge databases were searched for studies that evaluated the prognostic or clinicopathological significance of PD-L1 expression in patients with breast cancer, and reported at least one survival-related outcome.

Results : Six studies that included 7877 cases were selected for the analysis. Higher PD-L1 expression in all cells was related to higher histological grade and lymph node metastasis. Higher PD-L1 expression in tumor cell was related to larger tumor size, estrogen receptor negativity, progesterone receptor negativity, human epidermal growth factor type-2 positivity, and triple-negative breast cancer. PD-L1 positivity in all cells was associated with poorer disease-free survival, although it was not significantly associated with overall survival.

Conclusion : The present meta-analysis revealed that cases of breast cancer with PD-L1 positivity in all cells exhibited higher histological grades, lymph node metastasis, and poorer disease-free survival. Therefore, positive expression of PD-L1 may be a useful prognostic marker in breast cancer.

BMC Cancer , article en libre accès, 2017

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