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- Chromosomal abnormalities and molecular landscape of metastasizing mucinous salivary adenocarcinoma.
- Paper ID
- Section of Otolaryngology, Department of Surgery, Yale School of Medicine, 789 Howard Avenue, New Haven, CT 06519, USA.
Oral oncology, 2017;66:38-45
PMID: 28249646 (view at PubMed or Europe PMC)
- Background: Mucinous adenocarcinoma of the salivary gland (MAC) is a lethal cancer with unknown molecular etiology and a high propensity to lymph node metastasis. Mostly due to its orphan status, MAC remains one of the least explored cancers that lacks cell lines and mouse models that could help translational and pre-clinical studies. Surgery with or without radiation remains the only treatment modality but poor overall survival (10-year, 44%) underscores the urgent need for mechanism-based therapies.Methods: We developed the first patient-derived xenograft (PDX) model for pre-clinical MAC studies and a cell line that produces aggressively growing tumors after subcutaneous injection into nude mice. We performed cytogenetic, exome, and proteomic profiling of MAC to identify driving mutations, therapeutic targets, and pathways involved in aggressive cancers based on TCGA database mining and GEO analysis.Results: We identified in MAC KRAS (G13D) and TP53 (R213X) mutations that have been previously reported as drivers in a variety of highly aggressive cancers. Somatic mutations were also found in KDM6A, KMT2D, and other genes frequently mutated in colorectal and other cancers: FAT1, NBEA, RELN, RLP1B, and ZFHX3. Proteomic analysis of MAC implied epigenetic up-regulation of a genetic program involved in proliferation and cancer stem cell maintenance.Conclusion: Genomic and proteomic analyses provided the first insight into potential molecular drivers of MAC metastases pointing at common mechanisms of CSC propagation in aggressive cancers. The in vitro/in vivo models that we created should aid in the development and validation of new treatment strategies against MAC.
- Paper Status
- Genes Analysed
- Mutated Samples
- Total No. of Samples