Unbiased Detection of Driver Mutations in Extramammary Paget Disease

Abstract Purpose: Extramammary Paget disease (EMPD) is an uncommon skin malignancy whose genetic alterations are poorly characterized. Previous reports identified mutations in chromatin remodeling genes and PIK3CA. In order to unambiguously determine driver mutations in EMPD, we analyzed 87 EMPD samples using exome sequencing in combination with targeted sequencing. Experimental Design: First, we analyzed 37 EMPD samples that were surgically resected using whole-exome sequencing. Based on several in silico analysis, we built a custom capture panel of putative driver genes and analyzed 50 additional formalin-fixed, paraffin-embedded samples using target sequencing. ERBB2 expression was evaluated by HER2 immunohisotochemistry. Select samples were further analyzed by fluorescence in situ hybridization. Results: A median of 92 mutations/sample was identified in exome analysis. A union of driver detection algorithms identified ERBB2, ERBB3, KMT2C, TP53, PIK3CA, NUP93, AFDN, and CUX1 as likely driver mutations. Copy-number alteration analysis showed regions spanning CDKN2A as recurrently deleted, and ERBB2 as recurrently amplified. ERBB2, ERBB3, and FGFR1 amplification/mutation showed tendency toward mutual exclusivity. Copy-number alteration load was associated with likelihood to recur. Mutational signatures were dominated by aging and APOBEC activation and lacked evidence of ultraviolet radiation. HER2 IHC/fluorescence in situ analysis validated ERBB2 amplification but was underpowered to detect mutations. Tumor heterogeneity in terms of ERBB2 amplification status was observed in some cases. Conclusions: Our comprehensive, unbiased analysis shows EMPD is characterized by alterations involving the PI3K–AKT pathway. EMPD is distinct from other skin cancers in both molecular pathways altered and etiology behind mutagenesis.