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

Kathryn J. Brayer, Huining Kang, Adel K. El-Naggar, Simon Andreasen, Preben Homøe, Katalin Kiss, Lauge Mikkelsen, Steffen Heegaard, Daniel Pelaez, Acadia Moeyersoms, David T. Tse, Yan Guo, David Y. Lee, Scott A. Ness

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number1390
JournalCancers
Volume15
Issue number5
DOIs
StatePublished - Mar 2023

Keywords

  • bioinformatics
  • biomarker
  • MYB oncogene
  • oral cancer
  • survival analysis
  • transcriptome analysis

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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