Programmed Death Ligand 1 (PD-L1) as a Predictive Biomarker for Pembrolizumab Therapy in Patients with Advanced Non-Small-Cell Lung Cancer (NSCLC)
Recently, immunotherapy has been shown to be an effective and helpful therapeutic option for the treatment of advanced non-small-cell lung cancer (NSCLC). The activity of antitumor T cells may be restored through the checkpoint blockade using anti-programmed death 1 or anti-programmed death ligand 1...
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Veröffentlicht in: | Advances in therapy 2019-10, Vol.36 (10), p.2600-2617 |
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Sprache: | eng |
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Zusammenfassung: | Recently, immunotherapy has been shown to be an effective and helpful therapeutic option for the treatment of advanced non-small-cell lung cancer (NSCLC). The activity of antitumor T cells may be restored through the checkpoint blockade using anti-programmed death 1 or anti-programmed death ligand 1 (PD-L1) antibodies, showing, in several cancer patients, an increased progression-free survival and overall survival compared with classical chemotherapy. As recently shown by several studies, the PD-L1 expression levels in tumors may offer a selection criterion for patients to predict their immunotherapy response. In particular, NSCLC patients with high tumor PD-L1 levels (proportional score ≥ 50% for first-line therapy and ≥ 1% for second-line treatment, respectively) showed better response rates to immunotherapy and longer survival in first-line therapy compared with conventional chemotherapy. PD-L1, whose expression is evaluated by using immunohistochemistry analysis, is currently the only biomarker approved for clinical use in the first- and second-line monotherapy setting and therefore plays a central role in treatment decision-making for patients with advanced NSCLC. In this review we will discuss the key role of PD-L1 as a predictive biomarker of response to pembrolizumab therapy in NSCLC patients by describing the appropriate techniques and methodologies for immunohistochemical evaluation of PD-L1 expression and providing an overview of the clinical studies supporting its predictive significance. |
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ISSN: | 0741-238X 1865-8652 |
DOI: | 10.1007/s12325-019-01057-7 |