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A pan-cancer transcriptome analysis to identify the molecular mechanism of prexasertib resistance_RNASeq

ABSTRACT: A pan-cancer transcriptome analysis to identify the molecular mechanism of prexasertib resistance_RNASeq

PROVIDER: PRJNA599103 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR10832649_1.fastq.gz	Fastqsanger.gz
	SRR10832649_2.fastq.gz	Fastqsanger.gz
	SRR10832650_1.fastq.gz	Fastqsanger.gz
	SRR10832650_2.fastq.gz	Fastqsanger.gz
	SRR10832651_1.fastq.gz	Fastqsanger.gz

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A pan-cancer transcriptome analysis to identify the molecular mechanism of prexasertib resistance_RNASeq

Project description:The combined influence of oncogenic drivers, genomic instability, and/or DNA damage repair deficiencies increases replication stress in cancer. Cells with high replication stress rely on the upregulation of checkpoints like those governed by CHK1 for survival. Previous studies of the CHK1 inhibitor prexasertib demonstrated activity across multiple cancer types. Therefore, we sought to (1) identify markers of prexasertib sensitivity and (2) define the molecular mechanism(s) of intrinsic and acquired resistance using preclinical models representing multiple tumor types. Our findings indicate that while cyclin E dysregulation is a driving mechanism of prexasertib response, biomarkers associated with this aberration lack sufficient predictive power to render them clinically actionable for patient selection. Transcriptome analysis of a pan-cancer cell line panel and in vivo models revealed an association between expression of E2F target genes and prexasertib sensitivity and identified innate immunity genes associated with prexasertib resistance. Functional RNAi studies supported a causal role of replication fork components as modulators of prexasertib response. Mechanisms which protect cells from oncogene-induced replication stress may safeguard tumors from such stress induced by a CHK1 inhibitor, resulting in acquired drug resistance. Furthermore, resistance to prexasertib may be shaped by innate immunity. We included RNASseq data here as part of the study. Microarray data was uploaded separately.

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