Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster session 01

115P - Combination of two distinct subsets of peripheral blood CD8+ T cells from patients with NSCLC predicts response outcome to immune checkpoint inhibitor therapy

Date

10 Sep 2022

Session

Poster session 01

Topics

Tumour Immunology;  Immunotherapy

Tumour Site

Non-Small Cell Lung Cancer

Presenters

Jae-Ho Cho

Citation

Annals of Oncology (2022) 33 (suppl_7): S27-S54. 10.1016/annonc/annonc1037

Authors

J. Cho1, S. Lee1, J.S. Yun2, H. Kim3, H. Cho4, S.Y. Song2, I. Oh4

Author affiliations

  • 1 Microbiology And Immunology, Chonnam National University Medical School & Chonnam National University Hwasun Hospital, 519-809 - Hwasun/KR
  • 2 Thoracic And Cardiovascular Surgery, Chonnam National University Medical School & Chonnam National University Hwasun Hospital, 519-809 - Hwasun/KR
  • 3 Biomarker Development Team, Selecxine, 05855 - Seoul/KR
  • 4 Internal Medicine, Chonnam National University Medical School & Chonnam National University Hwasun Hospital, 519-809 - Hwasun/KR
More

Abstract 115P

Background

Immune checkpoint inhibitor (ICI) has achieved a great success as a promising regime for the treatment of patients with many types of solid malignancies, associated with predictive biomarker of PD-L1 expression. However, generally a low rate of ICI therapy response remains a critical hurdle to overcome for expanding its versatile therapeutic efficacy and necessitates importance of developing a biomarker better predicting response outcome after ICI.

Methods

Peripheral blood CD8+ T cell compartment from patients with stage IV of non-small cell lung cancer (n=121) before ICI treatment targeting programmed cell death 1 (PD-1) or its ligand 1 (PD-L1) was analyzed and correlated with patients’ ICI treatment outcome.

Results

Strong correlation between the patients' response outcome after ICI and the proportion of two distinct subsets of blood CD8+ T cells, namely CD27+ CD28+ CD45RA- CCR7- and CD27+ CD28+ CD45RA+ CCR7- cells was observed. Using these two cellular parameters combined with machine learning based probability graph, we found that both initial discovery (n=72) and later validation cohorts of patients (n=49) showed a power of predicting approximately 55.6% of ICI responders (95% CI, 23.1-88%; PR based on the RECISTv1.1 criteria) compared to that of ∼15.3% (95% CI, 7-23.6%; no biomarker included) and of ∼22.2% (95% CI, 0-49.3%; biomarker based on tumor PD-L1 expression). Mechanistically, the observed strong correlation was due to the basal functional fitness and reactive capacity of responding CD8+ T cells, which was characterized by lower initial levels of perforin, granzyme B and interferon-γ expression in these cells before ICI treatment. As such, the patients with enhanced proportion of this subset in their bloods showed greater capacity to enhance ICI-driven upregulation of cytotoxic molecules and accordingly better ICI response outcomes.

Conclusions

These observations are in line with current notion that a relatively less differentiated subset of CD8+ T cells would be a major target for ICI and provide a potential of developing this non-invasive blood-based approach as an ICI response predictor for patients with cancer.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Chonnam National University Medical School and Chonnam National University Hwasun Hospital.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.