Clinical validation of a blood-based multimodal immune-response score in a real-world cohort of advanced non–small cell lung cancer.
Abstract
e20581 Background: Immune checkpoint inhibitors (ICIs) have transformed care for advanced non-small cell lung cancer (aNSCLC), but predictive biomarkers remain imperfect. We previously developed a multimodal immunotherapy response score (MIRS), which integrated ctDNA epigenomic signatures with microsatellite instability (MSI) and tumor mutational burden (TMB) from a single blood draw, and validated its use as a predictive biomarker for ICI response. In this study, we assess the ability of MIRS to predict clinical outcomes in real-world patients treated with ICIs. Methods: MIRS was trained and validated using de-identified patient data from InfinityAI Data Library and expressed as percentile based on MIRS distribution with >20,000 aNSCLC samples. In this study, we validated the signature in an independent cohort of 32 aNSCLC patients by analyzing baseline plasma on Guardant360 Liquid (Guardant Health, Palo Alto, CA); 27/32 received PD-1/PD-L1 monotherapy and 7/32 had tumor PD-L1 TPS <1%. Patients with MIRS ≥50% were defined as MIRS-High. The primary endpoint was real-world progression-free survival (rwPFS). We fitted Cox proportional hazards models (adjusted for covariates such as sex, age, tissue PD-L1 expression, histologic subtype, ECOG, TNM stage and baseline methylation tumor fraction) and reported adjusted hazard ratios (aHR) with 95% CIs. Median rwPFS was estimated by Kaplan–Meier method. Model discrimination was summarized using concordance index (c-index). Results: MIRS-High patients (18/32) had significantly longer rwPFS (median 15.1 vs 7.2 months; aHR 0.24, 95% CI 0.07–0.82, p=0.02; c-index = 0.80). As a continuous variable, MIRS percentile was associated with improved rwPFS (p=0.04). Stratification by PD-L1 ≥50% (n=14) showed a consistent, but not statistically significant trend toward longer rwPFS (aHR 0.60, 95% CI 0.19–1.87, p=0.38; c-index = 0.75). When both biomarkers were combined, patients with PD-L1 ≥50% or MIRS-High (n=25) had significantly longer rwPFS (aHR 0.24, 95% CI 0.07–0.90, p=0.034). All complete responses (n=4) were MIRS-High (median MIRS score of 80th percentile in aNSCLC); patients with progressive disease (n=6) had a median MIRS of 27th percentile in aNSCLC (partial responders (n=15) had a median of 51th percentile in aNSCLC, and stable disease cases (n=7) had median of 55th percentile in aNSCLC). Conclusions: Patients with MIRS-High scores had a 76% lower adjusted hazard of progression or death even after accounting for key covariates. Additionally, all complete responses were MIRS-High and MIRS was associated with significantly improved PFS compared to known biomarkers such as tissue-based PDL1. These data indicate that the multimodal score taken via a single baseline blood sample strongly predicts ICI benefit and may be useful in ICI vs chemo combination decisions pending further ongoing validation.
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (14)
Jose García Sánchez
Medical Oncology Department, University Hospital Arnau de Vilanova-Liria, FISABIO, Valencia, Spain
Leonor Fernandez-Murga
Servicio de Oncología, Hospital Arnau de Vilanova-Liria, FISABIO, Valencia, Spain
Javier Garde Garde
Fundación Instituto Valenciano de Oncología, Valencia, Spain
Nuria Piera
University Hospital Arnau De Vilanova, Valencia, Spain
Paula Llor Rodríguez
Medical Oncology Department, Arnau de Vilanova-Liria Hospital, FISABIO, Valencia, Spain
Lucia Serrano Garcia
Molecular Oncology and Biomodels Laboratory, Arnau de Vilanova-Liria Hospital, FISABIO, Valencia, Spain
Francois Riva
Guardant Health Inc, Redwood City, CA
Sean Gordon
Guardant Health, Inc., Redwood City, CA
Jing Wang
Hunan Cancer Hospital Changsha China
Jim Hayes
Guardant Health, Palo Alto, CA
Justin Odegaard
Guardant Health, Palo Alto, CA
Darya I. Chudova
Guardant Health, Redwood City, CA
Reagan Barnett
Guardant Health, Inc., Redwood City, CA
Antonio Llombart-Cussac
Hospital Arnau de Vilanova, Valencia, Spain