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A Novel Epitope Quality-Based Immune Escape Mechanism Reveals Patient's Suitability for Immune Checkpoint Inhibition
Michael Wessolly1,2, Susann Stephan-Falkenau3, Anna Streubel3
1Institute of Pathology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Background:
Immune checkpoint inhibition, especially the blockade of PD-1 and PD-L1, has become one of the most thriving therapeutic approaches in modern oncology. Immune evasion caused by altered tumor epitope processing (so-called processing escapes) may be one way to explain immune checkpoint inhibition therapy failure. In the present study, we aim to demonstrate the effects of processing escapes on immunotherapy outcome in NSCLC patients.
Patients And Methods:
Whole exome sequencing data of 400 NSCLC patients (AdC and SCC) were extracted from the TCGA database. The ICB cohort was composed of primary tumor probes from 48 NSCLC patients treated with nivolumab. Mutations were identified by targeted amplicon-based sequencing including hotspots and whole exomes of 22 genes. The effect of mutations on proteasomal processing was evaluated by deep learning methods previously trained on 1260 known MHC-I ligands. Cox regression modelling was used to determine the influence on overall survival.
Results:
In the TCGA cohort, processing escapes were associated with decreased overall survival (p= 0.0140). In the ICB cohort, patients showing processing escapes in combination with high levels of PD-L1 (n=8/48) also showed significantly decreased overall survival, independently of mutational load or PD-L1 status.
Conclusion:
The concept of altered epitope processing may help to understand immunotherapy failure. Especially when combined with PD-L1 status, this method can be used as a biomarker to identify patients not suitable for immunotherapy.
Insights
Altered tumor epitope processing, or processing escapes, can predict immunotherapy failure in non-small cell lung cancer (NSCLC). This finding, especially when combined with PD-L1 status, may identify patients unsuitable for immune checkpoint inhibition therapy.
Area of Science:
- Oncology
- Immunotherapy
- Genomics
Background:
- Immune checkpoint inhibitors targeting PD-1/PD-L1 are key cancer therapies.
- Therapy failure can stem from immune evasion via altered tumor epitope processing (processing escapes).
- This study investigates the impact of processing escapes on immunotherapy outcomes in non-small cell lung cancer (NSCLC).
Purpose of the Study:
- To evaluate the effect of processing escapes on immunotherapy outcomes in NSCLC patients.
- To determine if processing escapes can serve as a biomarker for predicting immunotherapy response.
Main Methods:
- Analysis of whole exome sequencing data from 400 NSCLC patients (TCGA database).
- Targeted sequencing of 22 genes in 48 NSCLC patients treated with nivolumab (ICB cohort).
- Deep learning models assessed mutation effects on proteasomal processing; Cox regression analyzed overall survival.
Main Results:
- Processing escapes correlated with decreased overall survival in the TCGA cohort (p=0.0140).
- In the ICB cohort, processing escapes combined with high PD-L1 levels significantly reduced overall survival.
- This effect was independent of mutational load or PD-L1 status alone.
Conclusions:
- Altered epitope processing is a potential mechanism explaining immunotherapy failure.
- Combining processing escape analysis with PD-L1 status can identify patients unlikely to benefit from immunotherapy.
- This approach may refine patient selection for immune checkpoint blockade therapy.
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