Identification of nomogram associated with durable clinical benefit gene for advanced non-small cell lung cancer with sensitivity to responsive to immunotherapy

Area of Science:

• Oncology
• Genomics
• Immunotherapy

Background:

• Immunotherapy with immune checkpoint inhibitors (ICIs) is standard for advanced non-small cell lung cancer (NSCLC).
• A significant portion of advanced NSCLC patients do not respond adequately to ICIs.
• Improved clinical predictability for NSCLC patients receiving ICIs is needed.

Purpose of the Study:

• To identify genomic and clinical factors associated with durable clinical benefit (DCB) from ICIs in NSCLC.
• To develop predictive nomograms for NSCLC patients undergoing ICI treatment.
• To stratify NSCLC patients based on treatment regimens for personalized prognosis prediction.

Main Methods:

• Retrieved clinical and genomic data for NSCLC patients receiving ICIs from cBioPortal.
• Compared gene alterations between patients with DCB and those with no durable benefit (NDB).
• Utilized Kaplan-Meier analysis for survival, and developed nomograms integrating clinical and genomic variables.

Main Results:

• Identified three patient subgroups based on immunotherapy regimens: anti-PD-1 monotherapy, anti-PD-1/anti-CTLA-4 combination, and first-line treatment.
• Found associations between mutations in TP53, PGR, PTPRT, RELN, MUC19, LRP1B, and FAT3 with progression-free survival (PFS).
• Developed three novel nomograms to predict ICI treatment prognosis across different NSCLC subgroups.

Conclusions:

• Mutations in PGR, PTPRD, RELN, MUC19, LRP1B, and FAT3 can serve as predictive biomarkers for ICI response.
• The developed nomograms show significant potential for predicting prognosis in NSCLC patients undergoing various ICI strategies.