Abstract

Abstract Significant morphologic overlap can exist between distinct salivary gland neoplasms, making differential diagnosis challenging, even with the use of new immunohistochemistry stains and FISH probes (Griffith et al., Arch Pathol Lab Med 2017). RNA-sequencing (RNAseq) technology is increasingly being used as a tool for identify diagnostic molecular signatures in a wide variety of diseases (Byron et al., Nat Rev Genet 2016). Furthermore, transcriptomics data are being used to develop biomarkers that can be used in drug discovery assays. Using an unbiased RNAseq analysis pipeline (Brayer et al., Cancer Discov 2016; Brown et al., PLos One 2017), we developed molecular profiles for 126 salivary gland tumors with accompanying clinical data–68 adenoid cystic carcinoma (ACC), 23 acinic cell carcinoma (Acinic), 5 basal cell adenoma (BCA), 20 basal cell adenocarcinoma (BCAC), and 10 secretory carcinoma (SC)–and have identified distinct gene expression patterns for each neoplasm. Additionally, a detailed analysis within each cancer type has revealed heterogeneous gene expression patterns, with altered signaling pathways, suggesting molecular subtypes exist. In both ACC and Acinic samples we identified unique molecular signatures found in patients with poor overall survival. Transcripts within each molecular signature that are independent of gender, age, and cancer stage, but correlated with clinical outcome data, are being identified for use as diagnostic or prognostic biomarkers and for use in drug discovery assays. Preliminary results to identify biomarkers for these neoplasms will also be presented. Citation Format: Kathryn J. Brayer, Yoshitsugu Mitani, Adel El-Naggar, Scott A. Ness. Differential expression analysis and biomarker identification in five salivary gland carcinoma types [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1511.

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