Genomic landscape of study cohort
tumor, tumors
TUMOR, HOT SPOT, REGRESSION, GLIOBLASTOMA, TUMORS
Genomic data were available for 20 patients, including all patients in the efficacy analysis group (Figure Genomic profiles of study cohort. An oncoplot depicting the genomic profiles of the study cohort. We focused on several key drivers of GBMs to analyze the mutation and copy number variation. Patients were ordered by radiographic response of existing lesion. Copy numbers derived from “GISTIC” are presented. EGFR “hot spot” variation (A289) is marked with an *. GBM, glioblastoma; EGFR, epidermal growth factor receptor; mMGMT, MGMT methylation status; NA, not available.Gain‐of‐function To comprehend the molecular characteristics underlying clinical response, we investigated transcriptomic profiles. As only a single patient met the primary endpoint, we focused on whether existing tumors experienced regression during therapy. We found four patients with tumor regression during therapy (SMC‐0002, SMC‐0014, SNUH‐003, and SNUH‐007) and compared them to the remaining patients to identify the genomic signatures associated with response to GC1118.GC1118 shows preferential inhibitory effect against high‐affinity EGFR ligands, thereby exerting a more profound therapeutic effect in a subset of tumors.We conducted pre‐ranked gene set enrichment analysis using differentially expressed genes between patients with tumor regression and without regression. Immune‐related pathways were enriched in the tumor‐regression group, while pathways involved in intercellular communication (e.g., synapses) were downregulated (Figure To understand the functional implications of enriched immune pathways in the tumor‐regression group, we deconvoluted the bulk RNA‐seq data into various cellular compositions with LM22 reference using CIBERSORTx. γδ‐T cells were significantly more abundant in the tumor‐regression group (