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Integrated methylomic and transcriptomic characterisation of postoperative systemic inflammatory dysregulation (RNA EXPRESSION)

ABSTRACT: Integrated methylomic and transcriptomic characterisation of postoperative systemic inflammatory dysregulation (RNA EXPRESSION)

PROVIDER: PRJNA762882 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR15872000_1.fastq.gz	Fastqsanger.gz
	SRR15872000_2.fastq.gz	Fastqsanger.gz
	SRR15872001_1.fastq.gz	Fastqsanger.gz
	SRR15872001_2.fastq.gz	Fastqsanger.gz
	SRR15872002_1.fastq.gz	Fastqsanger.gz

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Project description:Treatment options and reliable predictive marker to determine patients at risk to develop postoperative LD and to define the optimal time point of liver resection are limited. Accordingly, there is an urgent need for an easily assessable preoperative test to predict postoperative liver function recovery, specifically as current markers are often expensive, time consuming and sometimes invasive. Emerging evidence suggests that microRNA (miRNA) signatures represent potent diagnostic, prognostic and treatment response biomarkers for several diseases. Using next-generation sequencing as an unbiased systematic approach 554 miRNAs were detected in preoperative plasma of 21 patients suffering from postoperative LD after liver resection and 27 matched controls. Subsequently, we identified a miRNA signature - consisting of miRNAs 151a-5p, 192-5p and 122-5p - that highly correlated with patients developing postoperative LD after liver resection. The predictive potential for postoperative LD was subsequently confirmed using real-time PCR in an independent validation cohort of 98 patients. Ultimately, a regression model of the two miRNA ratios 151a-5p to 192-5p and 122-5p to 151a-5p was found to reliably predict postoperative LD, severe morbidity, prolonged intensive care unit and hospital stay and even mortality prior to surgery with a remarkable accuracy, thereby outperforming established markers of postoperative LD. Ultimately, we documented that miRNA ratios closely followed liver function recovery after partial hepatectomy. Conclusion: Given the clinical relevance of predicting potentially fatal postoperative clinical outcome after liver resection, our data demonstrate the clinical utility of a novel miRNA-based biomarker to support the selection of patients undergoing partial hepatectomy. The dynamical changes during liver function recovery indicate a possible role in tailoring the optimal time point of surgery to each individual patient. Thereby, our data might help to tailor surgical strategies to the specific risk profile of individual patients.

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Integrated methylomic and transcriptomic characterisation of postoperative systemic inflammatory dysregulation (RNA EXPRESSION)

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