Abstract 184P
Background
Immune-related subgroup classification in immune checkpoint blockade (ICB) therapy is largely inconclusive in lung adenocarcinoma (LUAD).
Methods
First, the single sample Gene set Enrichment Analysis (ssGSEA) algorithm and K-means algorithm were used to identify immune-based subtypes for LUAD cohort based on the immunogenomic profiling of 29 immune signatures from the Cancer Genome Atlas (TCGA) database (n = 535). Second, we conducted a bioinformatics analysis on data to examine the prognostic and predictive value of immune-based subtypes. The survival analysis and further cox proportional hazards regression analysis were conducted in LUAD. Then, immune score, tumor-infiltrating immune cells (TIICs) and immune checkpoint expression of the three subtypes were analyzed respectively. In the end, GO and KEGG of the differentially expressed genes (DEGs) between 3 immune-based subtypes were analyzed for functional enrichment pathways.
Results
A total of 3 immune-based subtypes with different immune signatures were identified for LUAD. We identified three LUAD subtypes named cluster 1 (C1), cluster 2 (C2) and cluster 3 (C3). Patients in cluster 3 had higher stromal, immune, and ESTIMATE scores, while cluster 1 was the opposite. Cases in cluster 1 showed an enrichment of macrophages M0 and activation of dendritic cells, while in cluster 3 tumors were enriched in CD8+ T cell, activation of CD memory T cells and macrophages M1. Cluster 3 was characterized by greater immune cell infiltration, as well as better survival prognosis compared to the other subtypes. In addition, patients in cluster 3 had higher expression levels of immune checkpoint such as PD-L1, PD1, CTLA4, LAG3, IDO1 and HAVCR2. TMB scores of clusters showed no significantly statistical differences. Furthermore, we identified that immune-related pathways were enriched in cluster 3.
Conclusions
Based on this study, combined-biomarkers were identified to predict outcomes following immune checkpoint inhibitor (ICI) treatment. Furthermore, our findings have enormous potential for assisting in the identification of immunological biomarkers and serving as a starting point for novel combination-based therapy strategies.
Legal entity responsible for the study
The authors.
Funding
Natural Science Foundation of Shandong Province.
Disclosure
All authors have declared no conflicts of interest.