How to cite item

Programmed cell death ligand-1 (PD-L1) as a biomarker for nonsmall cell lung cancer (NSCLC) treatment—are we barking up the wrong tree?

   
@article{TLCR21112,
	author = {Wolfram C. M. Dempke and Klaus Fenchel and Stephen P. Dale},
	title = {Programmed cell death ligand-1 (PD-L1) as a biomarker for nonsmall cell lung cancer (NSCLC) treatment—are we barking up the wrong tree?},
	journal = {Translational Lung Cancer Research},
	volume = {7},
	number = {Suppl 3},
	year = {2018},
	keywords = {},
	abstract = {Immunotherapy with monoclonal antibodies targeting programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1) has become a standard of care treatment for patients with advanced or metastatic non-small cell lung cancer (NSCLC) in first and later treatment lines with durable responses seen in approximately 10–20% of patients treated. However, the optimal selection of eligible patients who will benefit most, is far from being clear and the best biomarker has not yet been established. PD-L1 expression as a predictive biomarker for immunotherapy in NSCLC patients has shown some value for predicting response to immune checkpoint inhibitors in some studies, but not in others, and its use has been complicated by a number of factors which has prompted many researchers to establish better predictive biomarkers for immunotherapy of NSCLC. Most recently, two phase III first-line NSCLC studies have provided evidence that tumour mutational burden (TMB) correlates with the clinical response to the combination of nivolumab and ipilimumab (CheckMate-227; NCT02477826), whereas atezolizumab response was correlated with T effector gene signature expression (IMPower 150; NCT02366143). Both studies demonstrated a significant primary endpoint [progression-free survival (PFS)] benefit in the TMB group and in the group of patients expressing a T effector cell signature, respectively. However, PFS benefit in both studies was seen regardless of the PD-L1 status of all patients suggesting that TMB and T effector cell signatures may be more robust to predict clinical response following treatment with checkpoint inhibitors. The role of putative novel predictive biomarkers evaluated in the CheckMate-227 and the IMPower 150 trials may, if confirmed in future prospective studies, offer a new perspective for predicting immunotherapy treatment outcomes of NSCLC patients in the near future.},
	issn = {2226-4477},	url = {https://tlcr.amegroups.org/article/view/21112}
}