Dynamic Peripheral T-Cell Analysis Identifies On-Treatment Prognostic Biomarkers of Atezolizumab plus Bevacizumab in Hepatocellular Carcinoma.

Abstract

Introduction: Variability in response to atezolizumab plus bevacizumab (AB) treatment of hepatocellular carcinoma (HCC) underscores the critical need for the development of effective biomarkers. We sought to identify peripheral blood biomarkers reflecting response to AB treatment.

Methods: We analyzed dynamic changes in peripheral blood mononuclear cells from a prospective, multicenter cohort of 65 patients with HCC, using flow cytometry to evaluate the T-cell population before and 3 weeks after the first AB treatment.

Results: We found a unique response of the CD8⁺ T cells in terms of both frequency and phenotype, in contrast to CD4⁺ T cells and regulatory T cells. Notably, CD8⁺ T cells showed significant changes in expression of Ki-67 and T-cell immunoreceptors with Ig and ITIM domains (TIGIT). These distinct responses were observed particularly in the programmed cell death receptor-1 (PD-1)⁺ subpopulation of CD8⁺ T cells. Interestingly, the baseline differentiation status of PD-1⁺CD8⁺ T cells, particularly the central memory T-cell subset, correlated positively with greater proliferation (higher Ki-67 expression) of PD-1⁺CD8⁺ T cells after treatment. Moreover, effector memory cells expressing CD45RA correlated negatively with the increase in TIGIT⁺/PD-1⁺CD8⁺ T cells. The increase in TIGIT⁺/CD8⁺ T cells was associated with the development of immune-related adverse events, whereas increase in Ki-67⁺/PD-1⁺CD8⁺ T cells was associated with the better objective response rate. Importantly, dynamic shifts of Ki-67⁺/PD-1⁺CD8⁺ T cells and TIGIT⁺/CD8⁺ T cells significantly predicted progression-free survival and overall survival, as confirmed by multivariate analysis.

Conclusion: These findings highlight the potential of dynamic changes in CD8⁺ T cells as an on-treatment prognostic biomarker. Our study underscores the value of peripheral blood profiling as a noninvasive and practical method for predicting the clinical outcomes of AB treatment in patients with HCC.