Non-small cell lung cancer (NSCLC) accounts for 80-85% of lung cancer cases and is a leading cause of cancer-related deaths. Despite advancements in immunotherapy, current treatments fall short due to tumor cell heterogeneity. There is a pressing need for new targets, especially for CAR T cell therapy. Neoantigens, novel peptide sequences from tumor-specific mutations presented by MHC on tumor cells, offer a promising target due to their specificity, which is crucial to prevent autoimmune reactions.

This study aims to identify highly specific neoantigens in NSCLC patients using patient-specific multiomic approaches, including immunopeptidomics and RNA sequencing. Immunopeptidomics, a mass spectrometry-based technique, identifies immunopeptides presented by MHC on the cell surface, providing direct insight into the immunoepitope landscape.

Samples were collected from 12 NSCLC patients, including both tumor and benign tissues. RNA was extracted and sequenced to identify patient-specific mutations using DeepVariant, detecting single nucleotide variants (SNVs) and insertions/deletions (INDELs). These mutations were used to create patient-specific FASTA databases, essential for matching mass spectrometry data to specific mutations using PEAKs and MSFragger software.

Immunopeptidomics analysis included benign tissues to ensure identified neoantigens were tumor-specific, preventing potential autoimmunity in therapeutic applications. Additionally, RNA-Seq data allowed us to predict MHC subtypes for each patient, facilitating further bioinformatic analysis. This included predicting the binding affinity of neoantigens to the patient"s MHC subtypes, validating them as true neoantigens.

As a proof of concept, we initially searched each patient"s raw data against a database extended with immunopeptide sequences from previously described actionable neoantigens (dbPepNeo), helping to benchmark and refine our method.

Proteomic analysis was integrated into the study, including data from both tumor and benign tissues to investigate the pathway of mutated proteins towards their presentation within the immunoepitope. Comparative analysis at proteomic and immunopeptidomics levels provided deeper insights into molecular mechanisms and the tumor microenvironment.

In conclusion, we established and applied an advanced immunopeptidomics platform to NSCLC patients, analyzing both tumor and benign tissue samples. Creating patient-specific databases allows us to pinpoint neoantigens unique to tumor tissue, potentially paving the way for personalized immunotherapy. Comparative analysis of proteomic and immunopeptidomics data between tumor and benign tissues enhances our understanding of molecular dynamics within the tumor microenvironment. Our study underscores the potential of combining multiomic approaches to discover actionable neoantigens, significantly impacting the development of targeted therapies for NSCLC.