TY - JOUR
T1 - Circulating pre-treatment T-cell receptor repertoire as a predictive biomarker in advanced or metastatic non-small-cell lung cancer patients treated with pembrolizumab alone or in combination with chemotherapy
AU - Abed, A.
AU - Beasley, A. B.
AU - Reid, A. L.
AU - Law, N.
AU - Calapre, L.
AU - Millward, M.
AU - Lo, J.
AU - Gray, E. S.
N1 - Funding Information:
This work was supported by an Oncomine Clinical Research Grant from Thermo Fisher Scientific (no grant number); a grant from the clinical trial unit at Fiona Stanley Hospital (no grant number); a research grant from the Lung Foundation Australia—Ellen Yates Memorial Grant in Aid for Lung Cancer Research (no grant number); a fellowship to AA from the International Lung Cancer Foundation; and a fellowship to ESG. from the Cancer Council of Western Australia.
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/12
Y1 - 2023/12
N2 - Background: The circulating T-cell receptor (TCR) repertoire is a dynamic representation of overall immune responses in an individual. Materials and methods: We prospectively collected baseline blood from patients treated with first-line pembrolizumab monotherapy or in combination with chemotherapy. TCR repertoire metrics were correlated with clinical benefit rate (CBR), progression-free survival (PFS), overall survival (OS) and immune-related adverse events (irAEs). We built a logistic regression classifier by fitting all four TCR-β repertoire metrics to the immune checkpoint inhibitor (ICI) CBR data. In the subsequent receiver operating characteristic (ROC) analysis of the resulting logistic regression model probabilities, the best cut-off value was selected to maximise sensitivity to predict CBR to ICI. Results: We observed an association between reduced number of unique clones and CBR among patients treated with pembrolizumab monotherapy (cohort 1) [risk ratio = 2.86, 95% confidence interval (CI) 1.04-8.73, P = 0.039]. For patients treated with pembrolizumab plus chemotherapy (cohort 2), increased number of unique clones [hazard ratio (HR) = 2.96, 95% CI 1.28-6.88, P = 0.012] and Shannon diversity (HR = 2.73, 95% CI 1.08-6.87, P = 0.033), and reduced evenness (HR = 0.43, 95% CI 0.21-0.90, P = 0.025) and convergence (HR = 0.41, 95% CI 0.19-0.90, P = 0.027) were associated with improved PFS, while only an increased number of unique clones (HR = 4.62, 95% CI 1.52-14.02, P = 0.007) were associated with improved OS. Logistic regression models combining the TCR repertoire metrics improved the prediction of CBR (cohorts 1 and 2) and were strongly associated with PFS (cohort 1, HR = 0.38, 95% CI 0.19-0.78, P = 0.009) and OS (cohort 2, HR = 0.20, 95% CI 0.05-0.76, P < 0.0001). Reduced TCR conversion was associated with increased frequency of irAEs needing systemic steroid treatment. Conclusion: Combined pre-treatment circulating TCR metrics might serve as a predictive biomarker for clinical outcomes among patients with advanced non-small-cell lung cancer treated with pembrolizumab alone or in combination with chemotherapy.
AB - Background: The circulating T-cell receptor (TCR) repertoire is a dynamic representation of overall immune responses in an individual. Materials and methods: We prospectively collected baseline blood from patients treated with first-line pembrolizumab monotherapy or in combination with chemotherapy. TCR repertoire metrics were correlated with clinical benefit rate (CBR), progression-free survival (PFS), overall survival (OS) and immune-related adverse events (irAEs). We built a logistic regression classifier by fitting all four TCR-β repertoire metrics to the immune checkpoint inhibitor (ICI) CBR data. In the subsequent receiver operating characteristic (ROC) analysis of the resulting logistic regression model probabilities, the best cut-off value was selected to maximise sensitivity to predict CBR to ICI. Results: We observed an association between reduced number of unique clones and CBR among patients treated with pembrolizumab monotherapy (cohort 1) [risk ratio = 2.86, 95% confidence interval (CI) 1.04-8.73, P = 0.039]. For patients treated with pembrolizumab plus chemotherapy (cohort 2), increased number of unique clones [hazard ratio (HR) = 2.96, 95% CI 1.28-6.88, P = 0.012] and Shannon diversity (HR = 2.73, 95% CI 1.08-6.87, P = 0.033), and reduced evenness (HR = 0.43, 95% CI 0.21-0.90, P = 0.025) and convergence (HR = 0.41, 95% CI 0.19-0.90, P = 0.027) were associated with improved PFS, while only an increased number of unique clones (HR = 4.62, 95% CI 1.52-14.02, P = 0.007) were associated with improved OS. Logistic regression models combining the TCR repertoire metrics improved the prediction of CBR (cohorts 1 and 2) and were strongly associated with PFS (cohort 1, HR = 0.38, 95% CI 0.19-0.78, P = 0.009) and OS (cohort 2, HR = 0.20, 95% CI 0.05-0.76, P < 0.0001). Reduced TCR conversion was associated with increased frequency of irAEs needing systemic steroid treatment. Conclusion: Combined pre-treatment circulating TCR metrics might serve as a predictive biomarker for clinical outcomes among patients with advanced non-small-cell lung cancer treated with pembrolizumab alone or in combination with chemotherapy.
KW - biomarkers
KW - chemotherapy
KW - immunotherapy
KW - non-small-cell lung cancer
KW - T-cell receptor repertoire
UR - http://www.scopus.com/inward/record.url?scp=85178236181&partnerID=8YFLogxK
U2 - 10.1016/j.esmoop.2023.102066
DO - 10.1016/j.esmoop.2023.102066
M3 - Article
C2 - 37995426
AN - SCOPUS:85178236181
SN - 2059-7029
VL - 8
JO - ESMO Open
JF - ESMO Open
IS - 6
M1 - 102066
ER -