Peripheral blood T-cell receptor repertoire profiling of advanced non-small cell lung cancer patients receiving PD-1/PD-L1 treatment.

e21004 Background: Whether peripheral blood T cell receptor (TCR) repertoire profiling can serve as a biomarker to predict clinical benefit from anti-PD-1/PD-L1 checkpoint immunotherapy is not well understood. Moreover, it is not known which methods for TCR repertoire analysis are most clinically meaningful. To address this, we have performed TCR repertoire analysis of patients with advanced/metastatic non-small cell lung cancer (NSCLC) receiving PD-1/PD-L1 treatment. Methods: We analyzed 29 patients receiving PD-1/PD-L1 monotherapy or combination therapy in any line of treatment, excluding patients with EGFR mutations or Alk alterations. Genomic DNA was extracted from peripheral blood examples, and CDR3 regions of the rearranged TCR beta genes were amplified and sequenced using the immunoSEQ platform (Adaptive Biotechnologies, Seattle, WA). Libraries were sequenced using Illumina HiSeq 2500. TCR clonality, diversity, evenness, and the percentage of high-frequency clones (> 0.1% of the repertoire) were calculated at pre-treatment and post-treatment (1 – 3 months) timepoints. Morisita’s overlap index was calculated for 25 paired pre- and post-treatment samples. Metrics were compared in patients with and without durable clinical response at 6 months using the Mann-Whitney test. Results: There were no statistically significant differences in TCR repertoire clonality, diversity, evenness, or high-frequency clones between patients with and without durable clinical benefit, either at pre-treatment or post-treatment time points (p > 0.05). Conclusions: TCR repertoire metrics including clonality, diversity, evenness, percentage of high-frequency clones, and Morisita’s overlap index do not predict immunotherapy responses in this cohort of advanced/metastatic NSCLC patients receiving PD-1/PD-L1 monotherapy or combination therapy. Limitations of this study include sample size and heterogeneity of the patient cohort. This highlights the need for advanced TCR repertoire metrics, for example, considering shared TCR specificities and clonal identity. In ongoing work, we are defining TCR specificity groups and TCR clones in NSCLC as biomarkers of immunotherapy responsiveness.