961P Genomic and transcriptomic profiling in head and neck tumours to identify treatment options: The WINTHER trial experience

Abstract

Most personalized medicine studies in head and neck (HN) tumors focus on DNA alterations. There is limited data on the role of transcriptomics to guide treatment selection and its correlation with genomic data. As part of the WINTHER trial, we performed targeted NGS (FoundationOne) on FFPE and gene expression profiling (customized Agilent assay on both tumor and analogous normal tissue) for DNA and RNA-matched drug ranks. Here we perform in-depth analysis of genomic and transcriptomic findings in a cohort of 29 pts with HN cancers. The HN cohort included 13 HNSCC, 9 adenoid cystic carcinoma (ACC) and 7 others (including 3 nasophagyngeal carcinoma (NPC)]. In total, 12 genomic- and 13 transcriptomic-matched therapies were identified. Based on genomic analysis, the proportion of targetable cases ranged from 77% in HNSCC, 55% in ACC and 28% in others, mostly PI3K pathway, receptor tyrosine kinase and DNA damage repair alterations. ACC had lower copy number alterations than others. TMB was low across all histologies, with the exception of one NPC (12 mut/Mb). There were few cases of oncogene amplifications, namely 2 cases with increased PIK3CA copy number in HNSCC (both with coexisting high PIK3CA expression in tumor and tumor/normal) and 1 HNSCC with FGFR2 amplification (without FGFR2 overexpression). On transcriptomic analysis, we found 7 cases with high expression of oncogenes in tumor samples, (>1.5 times the interquartile range above the third quartile). We identified high tumor expression of FGFR1 and/or FGFR2 in ACC (4/7 cases each) and HNSCC (1/11 each), all cases without coexisting genomic alterations in FGFR1 or FGFR2. In ACC, we found two-fold increase in mean number of potentially targetable alterations per sample with genomics + transcriptomics as compared to genomics (1.67 vs. 0.78). In other histologies, no significant changes in targetability rate were seen with transcriptomics added to genomics. The pattern of genomic alteration differs by histology in HN cancer. The addition of transcriptomics to genomic analysis increases the targetability rate, especially in ACC, given high expression of FGFR1 and FGFR2, potential drivers that are often missed with genomic level analysis alone.