Introduction:Programmed cell death protein-1 (PD-1) and programmed death-ligand 1 (PD-L1) blockade is currently widely used in the treatment of metastatic NSCLC. Despite available biomarker stratification, clinical responses vary. Thus, the search for novel biomarkers with improved response prediction is ongoing. Previously, using mass cytometry or cytometry by time-of-flight (CyTOF), our group demonstrated that CD39+CD8+ immune cells represent tumor antigen-specific, cytotoxic T cells in treatment-naive NSCLC. We hypothesized that accurate quantitation of this T cell subset would predict immunotherapy outcome.
Methods:To translate this to a clinical setting, the present study compared CyTOF data with a range of clinically relevant methods, including conventional immunohistochemistry (IHC), multiplex IHC or immunofluorescence (mIHC), and gene expression assay by NanoString.
Results:Quantification using mIHC but not conventional IHC or NanoString correlated with the CyTOF results. The specificity and sensitivity of mIHC were then evaluated in a separate retrospective NSCLC cohort. CD39+CD8+ T cell proportion, as determined by mIHC, successfully stratified responders and nonresponders to PD-1 or PD-L1 inhibitors (objective response rate of 63.6%, compared with 0% for the negative group). This predictive capability was independent from other confounding factors, such as total CD8+ T cell proportion, CD39+ lymphocyte proportion, PD-L1 positivity, EGFR mutation status, and other clinicopathologic parameters.
Conclusions:Our results suggest that the mIHC platform is a clinically relevant method to evaluate CD39+CD8+ T cell proportion and that this marker can serve as a potential biomarker that predicts response to PD-1 or PD-L1 blockade in patients with NSCLC. Further validation in additional NSCLC cohorts is warranted.
Keywords:CD39; Immunofluorescence; Immunotherapy; Lung cancer.
Intratumoral CD39+CD8+ T Cells Predict Response to Programmed Cell Death Protein-1 or Programmed Death Ligand-1 Blockade in Patients With NSCLC
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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