Dynamics of Tumor and Immune Responses during Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

Abstract

Despite the initial successes of immunotherapy, there is an urgent clinical need for molecular assays that identify patients more likely to respond. Here, we report that ultrasensitive measures of circulating tumor DNA (ctDNA) and T-cell expansion can be used to assess responses to immune checkpoint blockade in metastatic lung cancer patients (N = 24). Patients with clinical response to therapy had a complete reduction in ctDNA levels after initiation of therapy, whereas nonresponders had no significant changes or an increase in ctDNA levels. Patients with initial response followed by acquired resistance to therapy had an initial drop followed by recrudescence in ctDNA levels. Patients without a molecular response had shorter progression-free and overall survival compared with molecular responders [5.2 vs. 14.5 and 8.4 vs. 18.7 months; HR 5.36; 95% confidence interval (CI), 1.57-18.35; P = 0.007 and HR 6.91; 95% CI, 1.37-34.97; P = 0.02, respectively], which was detected on average 8.7 weeks earlier and was more predictive of clinical benefit than CT imaging. Expansion of T cells, measured through increases of T-cell receptor productive frequencies, mirrored ctDNA reduction in response to therapy. We validated this approach in an independent cohort of patients with early-stage non-small cell lung cancer (N = 14), where the therapeutic effect was measured by pathologic assessment of residual tumor after anti-PD1 therapy. Consistent with our initial findings, early ctDNA dynamics predicted pathologic response to immune checkpoint blockade. These analyses provide an approach for rapid determination of therapeutic outcomes for patients treated with immune checkpoint inhibitors and have important implications for the development of personalized immune targeted strategies.Significance: Rapid and sensitive detection of circulating tumor DNA dynamic changes and T-cell expansion can be used to guide immune targeted therapy for patients with lung cancer.See related commentary by Zou and Meyerson, p. 1038.

©2018 American Association for Cancer Research.

Figures

Figure 1.. Overview of next-generation sequencing and T cell analyses.

We used serial blood samples collected at baseline, early after treatment initiation and at additional timepoints during immune checkpoint blockade to determine ctDNA and TCR repertoire dynamics. ctDNA trends were evaluated by TEC-Seq and the evolving TCR repertoire was assessed by TCR next generation sequencing. Dynamic changes in ctDNA and TCR clonotypic expansions were used to identify molecular response patterns and compared to RECIST 1.1 tumor burden evaluations. T0–T4 denote serial timepoints from the time of treatment initiation (T0), to the time of molecular response (T1), radiologic response (T2), molecular resistance (T3) and radiologic progression (T4).

Figure 2.. ctDNA and TCR clonal dynamics for a patient with sustained response to anti-PD1.

ctDNA (TP53 993+1G>T mutation shown in blue) decreased to undetectable levels signifying a complete molecular response at week 4 (A), in contrast CT imaging did not accurately capture the rate (B) or timing (C) of tumor regression (RECIST tumor burden dynamics are shown in green). A complete response by RECIST 1.1 was achieved 26 weeks later than the molecular response (C). In parallel, TCR repertoire dynamics revealed clonotypic amplifications of intratumoral TCR clones in peripheral blood at the time of radiographic response. TCR clones with statistically significant differential abundance were evaluated as individual clones (D) and as a composite of productive frequencies (E). Patient was off anti-PD1 therapy and on immunosuppressive therapy at week 30 (arrow), due to emergence of immune-related toxicity.

Figure 3.. ctDNA and TCR clonal dynamics for a patient with primary resistance to anti-PD1.

ctDNA levels (EGFR 745KELREA>T and TP53173V>L mutations shown in blue and red respectively) continued to rise from the time of initiation of anti-PD1 therapy (A). For this patient the change in the RECIST tumor burden was similar to the increase in ctDNA levels (RECIST tumor burden dynamics shown in green, B), however molecular resistance was detected earlier than conventional CT imaging (C). There were no clones with statistically significant expansion at week 4 compared to baseline, top 10 intratumoral clones found in peripheral blood are shown as individual clones (D) and by their average productive frequency (E).

Figure 4.. Early ctDNA clearance predicts progression-free and overall survival.

Patients with reduction of ctDNA to undetectable levels demonstrated a significantly longer PFS and OS compared to patients with no evidence of ctDNA elimination (log rank p=0.001 and P=0.008 respectively, A and B). Patients with undetectable ctDNA (molecular responders) clustered together independent of their tumor mutation burden (C) and the same pattern was observed for patients with detectable ctDNA (molecular nonresponders, D). Patients with ctDNA molecular response and either high or low tumor mutation burden had a significantly longer progression-free and overall survival (log rank P=0.015 and P=0.027 respectively).

Figure 5.. Early ctDNA clearance is associated with pathologic response to anti-PD1 therapy.

Molecular responses were consistent with pathologic responses to anti-PD1 therapy in early stage NSCLC. For a patient with a major pathologic response, ctDNA elimination (TP53 K132N mutation shown in blue) accurately captured the therapeutic effect compared to RECIST tumor burden dynamics (shown in green) that showed stable disease (A). In contrast, ctDNA levels (KRAS G12C and ALK G875R mutations shown in blue and purple) increased from baseline for a patient that did not achieve a pathologic response to anti-PD1 therapy (B). Changes in RECIST tumor burden, shown on the secondary axis of each plot, did not accurately predict outcome as both patients were classified as stable disease. The timeline of anti-PD1 therapy dosing, radiographic assessments and tumor resection is shown below each graph.