Centriole signaling restricts hepatocyte ploidy to maintain liver integrity.

Hepatocyte polyploidization is a tightly controlled process that is initiated at weaning and increases with age. The proliferation of polyploid hepatocytes in vivo is restricted by the PIDDosome-P53 axis, but how this pathway is triggered remains unclear. Given that increased hepatocyte ploidy protects against malignant transformation, the evolutionary driver that sets the upper limit for hepatocyte ploidy remains unknown. Here we show that hepatocytes accumulate centrioles during cycles of polyploidization in vivo. The presence of excess mature centrioles containing ANKRD26 was required to activate the PIDDosome in polyploid cells. As a result, mice lacking centrioles in the liver or ANKRD26 exhibited increased hepatocyte ploidy. Under normal homeostatic conditions, this increase in liver ploidy did not impact organ function. However, in response to chronic liver injury, blocking centriole-mediated ploidy control leads to a massive increase in hepatocyte polyploidization, severe liver damage, and impaired liver function. These results show that hyperpolyploidization sensitizes the liver to injury, posing a trade-off for the cancer-protective effect of increased hepatocyte ploidy. Our results may have important implications for unscheduled polyploidization that frequently occurs in human patients with chronic liver disease.

Novel Predictive Models for High-Value Care Outcomes Following Glioblastoma Resection.

BACKGROUND: Treating patients with glioblastoma (GBM) requires extensive medical infrastructure. Individualized risk assessment for extended length of stay (LOS), nonroutine discharge disposition, and increased total hospital charges is critical to optimize delivery of care. Our study sought to develop predictive models identifying independent risk factors for these outcomes. METHODS: We retrospectively reviewed patients undergoing GBM resection at our institution between January 2017 and September 2020. Extended LOS and elevated hospital charges were defined as values in the upper quartile of the cohort. Nonroutine discharge was defined as any disposition other than to home. Multivariate models for each outcome included covariates demonstrating P ≤ 0.10 on bivariate analysis. RESULTS: We identified 265 patients undergoing GBM resection, with an average age of 58.2 years. 24.5% of patients experienced extended LOS, 22.6% underwent nonroutine discharge, and 24.9% incurred elevated total hospital charges. Decreasing Karnofsky Performance Status (KPS) (P = 0.004), increasing modified 5-factor frailty (mFI-5) index (P = 0.012), lower surgeon experience (P = 0.005), emergent surgery (P < 0.0001), and larger tumor volume (P < 0.0001) predicted extended LOS. Independent predictors of nonroutine discharge included older age (P = 0.02), decreasing KPS (P < 0.0001), and emergent surgery (P = 0.048). Nonprivate insurance (P = 0.011), decreasing KPS (P = 0.029), emergent surgery (P < 0.0001), and larger tumor volume (P = 0.004) predicted elevated hospital charges. These models were incorporated into an open-access online calculator (https://neurooncsurgery3.shinyapps.io/gbm_calculator/). CONCLUSIONS: Several factors were independent predictors for at least 1 high-value care outcome, with lower KPS and emergent admission associated with each outcome. These models and our calculator may help clinicians provide individualized postoperative risk assessment to glioblastoma patients.