COMP-22. LARGE SCALE TRANSCRIPTOMIC ANALYSIS OF MELANOMA BRAIN METASTASES

Neuro-oncology(2018)

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Abstract
Brain metastases are the most common cause of adult brain tumors and highly challenging to treat. Additionally, melanoma brain metastases carry a particularly poor prognosis, with a median overall survival of 4–5 months. Standard-of-care treatment of brain metastases includes surgery, radiation, and chemotherapy. However, melanoma is a radio-resistant cancer, thus significantly limiting options for treatment of its metastasis to the brain. There is clearly a significant demand for new treatment approaches. We are conducting a large scale, whole transcriptomic analysis of melanoma brain metastases to provide insight into molecular changes that may contribute to metastasis as well as to identify potential therapeutic targets of the metastasized cancer. Total RNA was extracted from >50 melanoma brain metastases formalin-fixed paraffin-embedded (FFPE) samples and libraries constructed and enriched for coding region transcript fragments. Libraries were subjected to Transcriptome Capture (TCap) targeting 21,415 genes, which represents greater than 98% of the RefSeq exome, and sequenced using the Illumina HiSeq platform. Preliminary transcriptomic analysis of melanoma brain metastasis samples reveals that ion channel expression manifests as a prominent feature in metastatic melanoma and that in some cases correlates with poor clinical outcome. Greater than 20% of FDA approved drugs target ion channels. We report that repurposing of one such class of drugs targeting the ligand-gated neurotransmitter GABAA receptors can impair melanoma cell viability. We will report on differential expression analysis between recent melanoma transcriptomic studies1,2 and melanoma brain metastases samples and correlation of expression with primary melanoma DNA variants as well as potential therapeutic targets based on anomalous expression of protein coding genes, including of ion channels. References: 1Akbani, et al. (The Cancer Genome Atlas Network, TCGA). Genome classification of cutaneous melanoma. Cell 2015; 161(7): 1681–1696. 2Tirosh, et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 2016; 352 (6282): 189–196.
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Key words
large scale transcriptomic analysis,transcriptomic analysis,melanoma
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