Introduction: Patient-reported smoking history is frequently used as a stratification factor in NSCLC-directed clinical research. Nevertheless, this classification does not fully reflect the... Show moreIntroduction: Patient-reported smoking history is frequently used as a stratification factor in NSCLC-directed clinical research. Nevertheless, this classification does not fully reflect the mutational processes in a tumor. Next-generation sequencing can identify mutational signatures associated with tobacco smoking, such as single-base signature 4 and indel-based signature 3. This provides an opportunity to redefine the classification of smoking-and nonsmoking-associated NSCLC on the basis of individual genomic tumor characteristics and could contribute to reducing the lung cancer stigma.Methods: Whole genome sequencing data and clinical re-cords were obtained from three prospective cohorts of metastatic NSCLC (N = 316). Relative contributions and absolute counts of single-base signature 4 and indel-based signature 3 were combined with relative contributions of age-related signatures to divide the cohort into smoking -associated ("smoking high") and nonsmoking-associated ("smoking low") clusters.Results: The smoking high (n = 169) and smoking low (n = 147) clusters differed considerably in tumor mutational burden, signature contribution, and mutational landscape. This signature-based classification overlapped considerably with smoking history. Yet, 26% of patients with an active smoking history were included in the smoking low cluster, of which 52% harbored an EGFR/ALK/RET/ROS1 alteration, and 4% of patients without smoking history were included in the smoking high cluster. These discordant samples had similar genomic contexts to the rest of their respective cluster. Show less
Hurkmans, D.P.; Kuipers, M.E.; Smit, J.; Marion, R. van; Mathijssen, R.H.J.; Postmus, P.E.; ... ; Burg, S.H. van der 2020
Objectives A minority of NSCLC patients benefit from anti-PD1 immune checkpoint inhibitors. A rational combination of biomarkers is needed. The objective was to determine the predictive value of... Show moreObjectives A minority of NSCLC patients benefit from anti-PD1 immune checkpoint inhibitors. A rational combination of biomarkers is needed. The objective was to determine the predictive value of tumor mutational load (TML), CD8(+) T cell infiltration, HLA class-I and PD-L1 expression in the tumor. Materials and methods Metastatic NSCLC patients were prospectively included in an immune-monitoring trial (NTR7015) between April 2016-August 2017, retrospectively analyzed in FFPE tissue for TML (NGS: 409 cancer-related-genes) and by IHC staining to score PD-L1, CD8(+) T cell infiltration, HLA class-I. PFS (RECISTv1.1) and OS were analyzed by Kaplan-Meier methodology. Results 30 patients with adenocarcinoma (67%) or squamous cell carcinoma (33%) were included. High TML was associated with better PFS (p = 0.004) and OS (p = 0.025). Interaction analyses revealed that patients with both high TML and high total CD8(+) T cell infiltrate (p = 0.023) or no loss of HLA class-I (p = 0.026), patients with high total CD8(+) T cell infiltrate and no loss of HLA class-I (p = 0.041) or patients with both high PD-L1 and high TML (p = 0.003) or no loss of HLA class-I (p = 0.032) were significantly associated with better PFS. Unsupervised cluster analysis based on these markers revealed three sub-clusters, of which cluster-1A was overrepresented by patients with progressive disease (15 out of 16), with significant effect on PFS (p = 0.007). Conclusion This proof-of-concept study suggests that a combination of PD-L1 expression, TML, CD8(+) T cell infiltration and HLA class-I functions as a better predictive biomarker for response to anti-PD-1 immunotherapy. Consequently, refinement of this set of biomarkers and validation in a larger set of patients is warranted. Show less
