CD5 Expression Dynamically Changes During the Differentiation of Human CD8 + T Cells Predicting Clinical Response to Immunotherapy

• Published in: Immune network 2023, Vol.23 (4), p.35.1-35.16
• Main Authors: Young Ju Kim, Kyung Na Rho, Saei Jeong, Gil-Woo Lee, Hee-Ok Kim, Hyun-Ju Cho, Woo Kyun Bae, In-Jae Oh, Sung-Woo Lee, Jae-Ho Cho
• Format: Article
• Language: Korean
• ISSN: 1598-2629; 2092-6685

Defining the molecular dynamics associated with T cell differentiation enhances our understanding of T cell biology and opens up new possibilities for clinical implications. In this study, we investigated the dynamics of CD5 expression in CD8+ T cell differentiation and explored its potential clinical uses. Using PBMCs from 29 healthy donors, we observed a stepwise decrease in CD5 expression as CD8+ T cells progressed through the differentiation stages. Interestingly, we found that CD5 expression was initially upregulated in response to T cell receptor stimulation, but diminished as the cells underwent proliferation, potentially explaining the differentiation-associated CD5 downregulation. Based on the proliferation-dependent downregulation of CD5, we hypothesized that relative CD5 expression could serve as a marker to distinguish the heterogeneous CD8+ T cell population based on their proliferation history. In support of this, we demonstrated that effector memory CD8+ T cells with higher CD5 expression exhibited phenotypic and functional characteristics resembling less differentiated cells compared to those with lower CD5 expression. Furthermore, in the retrospective analysis of PBMCs from 30 non-small cell lung cancer patients, we found that patients with higher CD5 expression in effector memory T cells displayed CD8+ T cells with a phenotype closer to the less differentiated cells, leading to favorable clinical outcomes in response to immune checkpoint inhibitor (ICI) therapy. These findings highlight the dynamics of CD5 expression as an indicator of CD8+ T cell differentiation status, and have implications for the development of predictive biomarker for ICI therapy.