Dominant Gene Expression Profiles Define Adenoid Cystic Carcinoma (ACC) from Different Tissues: Validation of a Gene Signature Classifier for Poor Survival in Salivary Gland ACC

Simple Summary Adenoid cystic carcinoma (ACC) is a pathologically distinctive tumor that most often occurs in major or minor salivary glands, but can also occur in other tissues. We compared the gene expression profiles of ACC tumor samples from salivary gland, lacrimal gland, breast or skin. Despite their different tissues of origin, the ACC tumors displayed highly related patterns of gene expression. Indeed, gene expression patterns could not distinguish ACC tumors from different tissues, suggesting that genetic and epigenetic regulatory events induce a dominant ACC 'phenotype'. We also used the new cohort of salivary gland ACC tumors to validate a gene expression biomarker developed with a previously analyzed cohort. The 49-gene classifier correctly identified 98% of the poor survival patients, validating the biomarker and suggesting that a clinical test should be developed so patients at highest risk of poor survival can be identified and provided additional treatment. Adenoid cystic carcinoma (ACC) is an aggressive malignancy that most often arises in salivary or lacrimal glands but can also occur in other tissues. We used optimized RNA-sequencing to analyze the transcriptomes of 113 ACC tumor samples from salivary gland, lacrimal gland, breast or skin. ACC tumors from different organs displayed remarkedly similar transcription profiles, and most harbored translocations in the MYB or MYBL1 genes, which encode oncogenic transcription factors that may induce dramatic genetic and epigenetic changes leading to a dominant 'ACC phenotype'. Further analysis of the 56 salivary gland ACC tumors led to the identification of three distinct groups of patients, based on gene expression profiles, including one group with worse survival. We tested whether this new cohort could be used to validate a biomarker developed previously with a different set of 68 ACC tumor samples. Indeed, a 49-gene classifier developed with the earlier cohort correctly identified 98% of the poor survival patients from the new set, and a 14-gene classifier was almost as accurate. These validated biomarkers form a platform to identify and stratify high-risk ACC patients into clinical trials of targeted therapies for sustained clinical response.