Immunotherapy Response and Survival Outcome by Immunophenotypic Signature in Non-Small Cell Lung Cancer

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• Current biomarkers like PD-L1 and tumor mutation burden for immune checkpoint inhibitor (ICI) therapy in lung cancer are suboptimal.
• Identifying novel predictive biomarkers is crucial for optimizing treatment strategies in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC).

Purpose of the Study:

• To investigate immunophenotypic factors within the tumor microenvironment (TME) as potential predictive biomarkers for ICI therapy in LUAD and LUSC patients.
• To evaluate the association of immune TME subtypes and tertiary lymphoid structures (TLS) with treatment response and patient survival.

Main Methods:

• Analysis of clinical, genomic, and transcriptomic data from five patient cohorts (3 public, 2 retrospective).
• Evaluation of immune TME subtype and TLS signature using RNA expression data.
• Deconvolutional cellular decomposition via the Kassandra algorithm and survival analysis using log-rank test and Cox regression.

Main Results:

• An immune-hot phenotype in LUAD correlated with improved overall survival (OS) and progression-free survival (PFS).
• A high TLS signature predicted superior ICI response rates and improved PFS, independent of multivariate adjustments.
• Increased T-cell and macrophage infiltration were predictive of ICI response, while PD-L1 status and specific mutations (KEAP1, STK11) were linked to poorer survival outcomes.

Conclusions:

• Dynamic immune cell recruitment, characterized by an immune-hot TME and high TLS score, is a strong predictor of ICI benefit in LUAD.
• These immunophenotypic factors show promise as biomarkers for ICI therapy, potentially outperforming current markers.
• Further prospective research is needed to validate these findings and explore combinations with PD-(L)1 inhibitors.