Transcriptomic Profiling Identifies a Prognostic and Predictive Immune Signature in Patients (Pts) With Lung Squamous Cell Carcinoma (LUSC)

Document Type

Conference Proceeding

Publication Date

10-1-2025

Publication Title

J Thorac Oncol

Keywords

biological marker, immune checkpoint inhibitor, mammalian target of rapamycin, transcriptome, aged, algorithm, cohort analysis, conference abstract, controlled study, cytotoxic T lymphocyte, differential gene expression, drug therapy, female, gender, human, human tissue, immune-related gene, inflammation, k means clustering, M1 macrophage, M2 macrophage, major clinical study, male, mast cell, natural killer cell, non small cell lung cancer, overall survival, predictive value, progression free survival, protein expression, special situation for pharmacovigilance, squamous cell lung carcinoma, tumor microenvironment

Abstract

Introduction: Intra-tumoral immune infiltration and inflammation have been strongly proposed as promising prognostic and predictive biomarkers in non-small cell lung cancer (NSCLC). However, a transcriptomic approach is not well validated in this setting. Herein, we developed a transcriptome-based score and validated its prognostic and predictive value in LUSC. Methods: The transcriptomic counts and clinical data were obtained from The Cancer Genome Atlas Lung Squamous Cell Carcinoma (TCGA-LUSC, n = 487). Immune genes were obtained from the molecular signature database and validated genes from the literature. The pts were clustered based on their expression of immune genes into high vs low immune profiles using unsupervised K-means clustering. The Differentially Expressed Genes (DEGs) between the two groups were identified, and then we intersected the DEGs with the immune genes to obtain the immune DEGs. The im mune DEGs were fitted into uni- and multi-variate cox regression models to find the independent predictors of survival. An immune score (IS) was calculated using the expression of these genes multiplied by the cox regression coefficients. Pts were split using the median IS into high- and low-IS groups in all datasets. Log-rank tests and Kaplan Meier analysis were used to correlate the score with Overall Survival (OS) and Progression-Free Survival (PFS). Tumor microenvironment using 'CIBERSORT' algorithm, and the proteomic landscape were also analyzed between the two groups. To further validate our findings, we examined the IS on the following GEO cohorts: GSE157009 with 249 LUSC pts and GSE135222 with 27 NSCLC pts treated with immune checkpoint inhibitors (ICI). Results: We identified 3,616 DEGs, of which 344 immune DEGs were obtained and fitted into the univariate and multivariate Cox regression models. CCL21, CD48, and IL2RB were identified as independent predictors of survival. The high- and low-IS groups included 378 and 375 pts, respectively. The high IS group demonstrated worse outcomes compared to the low IS group in all datasets. In TCGA-LUSC, pts with high IS had worse OS and PFS (P<0.05). Similar results were seen in the external validation dataset, with high IS group showing worse OS in GSE157009-LUSC (P=0.0082). Moreover, high IS predicted for worse PFS in pts treated with ICI in GSE135222-ICI cohort (P=0.018). Notably, these associations remained significant after adjusting for stage, gender, and age, confirming the IS as an independent predictor of survival in all of the cohorts (HR>2, P<0.001). High IS correlated with higher infiltration of M2 macrophages, activated dendritic and mast cells, while low IS correlated with higher M1 macrophages, resting mast cells, cytotoxic T-cells, and activated NK cells infiltration (P<0.05). Low IS correlated with higher protein expression of BCL2, BCL2L11, MSH2, MSH6, PARP1, and LCK, while high IS correlated with higher expression of AKT pathway and mTOR pathway activation proteins (P<0.05). Conclusions: We developed a transcriptome-based immune score in LUSC that is prognostic and predictive of responses to ICI. The score was based on 3 immune-related genes. Pts with high immune score had worse outcomes, worse PFS after ICI and higher levels of immune inhibitory cells.

Volume

20

Issue

10

First Page

S312

Last Page

S313

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