A k-mer based transcriptomics approach for antisense drug discovery targeting the Ewing's family of tumors

基于 k-mer 的转录组学方法,用于发现针对 Ewing 家族肿瘤的反义药物

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作者:Andrew J Annalora, Shawn O'Neil, Jeremy D Bushman, James E Summerton, Craig B Marcus, Patrick L Iversen

Abstract

Ewing's sarcoma treatment failures are associated with high mortality indicating a need for new therapeutic approaches. We used a k-mer counting approach to identify cancer-specific mRNA transcripts in 3 Ewing's Family Tumor (EFT) cell lines not found in the normal human transcriptome. Phosphorodiamidate morpholino oligomers targeting six EFT-specific transcripts were evaluated for cytotoxicity in TC-32 and CHLA-10 EFT lines and in HEK293 renal epithelial control cells. Average morpholino efficacy (EC50) was 0.66 ± 0.13 in TC-32, 0.25 ± 0.14 in CHLA-10 and 3.07 ± 5.02 µM in HEK293 control cells (ANOVA p < 0.01). Synergy was observed for a cocktail of 12 morpholinos at low dose (0.3 µM) in TC-32 cells, but not in CHLA-10 cells. Paired synergy was also observed in both EFT cell lines when the PHGDH pre-mRNA transcript was targeted in combination with XAGE1B or CYP4F22 transcripts. Antagonism was observed when CCND1 was targeted with XAGE1B or CYP4F22, or when IGFBP-2 was targeted with CCND1 or RBM11. This transcriptome profiling approach is highly effective for cancer drug discovery, as it identified new EWS-specific target genes (e.g. CYP4F22, RBM11 and IGBP-2), and predicted effective antisense agents (EC50 < 1 µM) that demonstrate both synergy and antagonism in combination therapy.

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