Inter-patient heterogeneity in the hepatic ischemia-reperfusion injury transcriptome: Implications for research and diagnostics

Silvia Groiss, Christian Viertler, Marcel Kap, Gerwin Bernhardt, Hans Jörg Mischinger, Anieta Sieuwerts, Cees Verhoef, Peter Riegman, Mogens Kruhøffer, David Svec, Sjoback Robert Sjöback, Karl Friedrich Becker, Kurt Zatloukal

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Cellular responses induced by surgical procedure or ischemia-reperfusion injury (IRI) may severely alter transcriptome profiles and complicate molecular diagnostics. To investigate this effect, we characterized such pre-analytical effects in 143 non-malignant liver samples obtained from 30 patients at different time points of ischemia during surgery from two individual cohorts treated either with the Pringle manoeuvre or total vascular exclusion. Transcriptomics profiles were analyzed by Affymetrix microarrays and expression of selected mRNAs was validated by RT-PCR. We found 179 mutually deregulated genes which point to elevated cytokine signaling with NFκB as a dominant pathway in ischemia responses. In contrast to ischemia, reperfusion induced pro-apoptotic and pro-inflammatory cascades involving TNF, NFκB and MAPK pathways. FOS and JUN were down-regulated in steatosis compared to their up-regulation in normal livers. Surprisingly, molecular signatures of underlying primary and secondary cancers were present in non-tumor tissue. The reported inter-patient variability might reflect differences in individual stress responses and impact of underlying disease conditions. Furthermore, we provide a set of 230 pre-analytically highly robust genes identified from histologically normal livers (<2% covariation across both cohorts) that might serve as reference genes and could be particularly suited for future diagnostic applications.

Original languageEnglish
Pages (from-to)20-29
Number of pages10
JournalNew Biotechnology
Volume79
DOIs
StatePublished - 25 Mar 2024

Keywords

  • Biomarker
  • Gene expression
  • Microarray
  • Pre-analytical workflows
  • Transplantation medicine

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