A gene expression signature associated with B cells predicts benefit from immune checkpoint blockade in lung...

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• Immune checkpoint blockade (ICB) is a standard treatment for metastatic lung cancer, but predicting patient response remains a challenge.
• Only a subset of patients benefits from ICB, highlighting the urgent need for predictive biomarkers to guide treatment decisions and avoid adverse effects.
• Current predictive markers, including PD-L1 expression, have limitations in identifying patients likely to respond to ICB therapy.

Purpose of the Study:

• To investigate the potential of gene expression profiling from pre-treatment lung biopsies to identify predictive markers for ICB efficacy in metastatic lung adenocarcinoma.
• To evaluate the association of immune cell abundance, estimated via gene expression signatures, with progression-free survival (PFS) in patients receiving ICB.
• To compare the predictive performance of immune cell markers with PD-L1 mRNA and protein expression for ICB benefit.

Main Methods:

• Targeted mRNA expression profiling of 770 genes was performed on lung biopsies from 43 ICB-treated metastatic lung adenocarcinoma patients.
• Levels and proportions of 14 immune cell types were quantified using characteristic gene expression signatures.
• Receiver operating characteristic (ROC) analysis was used to assess the predictive accuracy of identified markers for ICB benefit.

Main Results:

• Increased abundance of B cells (HR=0.66, p=0.00074), CD45+ cells (HR=0.61, p=0.01), and total tumor-infiltrating lymphocytes (TILs) (HR=0.62, p=0.025) were significantly associated with prolonged PFS.
• B cells (AUC=0.77, p=0.0055) and CD45+ cells (AUC=0.73, p=0.019) demonstrated predictive value for ICB benefit.
• PD-L1 mRNA (AUC=0.54, p=0.72) and protein expression (AUC=0.68, p=0.082) showed limited predictive capacity.

Conclusions:

• Targeted gene expression profiling is a feasible method for routine diagnostic biopsies in lung cancer.
• B cells and total TILs show promise as complementary biomarkers for predicting ICB response in non-small cell lung cancer (NSCLC).
• Gene expression profiling could be integrated into routine diagnostics to enhance patient selection for ICB therapy, complementing existing next-generation sequencing (NGS) protocols.