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Erschienen in:
05.08.2023 | Original Article
Post-transplant inflammatory cytokine signature adds value for predicting tumor recurrence after liver transplantation for hepatocellular carcinoma
Erschienen in: Hepatology International | Ausgabe 6/2023
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Background
Cytokines are key regulators of post-transplant inflammation responses which reconstitute post-transplant hepatic and systemic environments to influence the likelihood of tumor relapse. This study investigated the prognostic value of post-transplant cytokines on tumor recurrence after liver transplantation (LT) for hepatocellular carcinoma (HCC).
Methods
A retrospective analysis was conducted in prospectively collected 150 adult HCC patients who received liver transplantation from 1997 to 2015. The post-transplant 41 inflammatory cytokines were quantified by multiplexing analysis and determined their prognostic value for predicting post-LT tumor recurrence by receiver operative characteristic analysis. A prediction model for post-LT tumor recurrence was generated by the logistic regression and internally validated Bootstrapping and compared with external prediction models.
Results
Post-transplant circulating CCL11, IFNα2, and IL17A cytokines were identified to be significant predictors of post-LT tumor recurrence and survival. A prediction score composed of the post-transplant 3-cytokine (P3C) signature, UCSF criteria, and pre-LT AFP was established. The P3C-UCSF-AFP score significantly predicted post-LT tumor recurrence and poor survival both in deceased donor liver transplantation (DDLT) and living donor liver transplantation (LDLT). The P3C-UCSF-AFP score was validated to significantly predict post-LT 2-year and 5-year tumor recurrence, outperforming the RETREAT score, French AFP model, up-to-seven, UCSF criteria, and Milan criteria. Importantly, the P3C-UCSF-AFP score could cost-effectively stratify high-risk recipients subjected to a refinement of post-recurrence survival.
Conclusion
The integrated P3C-UCSF-AFP score not only compensated for the pre-LT unpredictability and predicted post-LT tumor recurrence accurately, but also guided the clinical refinements of post-LT surveillance and therapeutic strategies in transplant oncology.
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