Predictive value of laboratory indicators for in-hospital death in children with community-onset sepsis: a prospective observational study of 266 patients.

BACKGROUND AND OBJECTIVES: This study aimed to identify predictors of sepsis-associated in-hospital mortality from readily available laboratory biomarkers at onset of illness that include haematological, coagulation, liver and kidney function, blood lipid, cardiac enzymes and arterial blood gas. METHODS: Children with sepsis were enrolled consecutively in a prospective observational study involving paediatric intensive care units (PICUs) of two hospitals in Beijing, between November 2016 and January 2020. The data on demographics, laboratory examinations during the first 24 hours after PICU admission, complications and outcomes were collected. We screened baseline laboratory indicators using the Least Absolute Shrinkage and Selection Operator (LASSO) analysis, then we constructed a mortality risk model using Cox proportional hazards regression analysis. The ability of risk factors to predict in-hospital mortality was evaluated by receiver operating characteristic (ROC) curves. RESULTS: A total of 266 subjects were enrolled including 44 (16.5%) deaths and 222 (83.5%) survivors. Those who died showed a shorter length of hospitalisation, and a higher proportion of mechanical ventilation, complications and organ failure (p<0.05). LASSO analysis identified 13 clinical parameters related to prognosis, which were included in the final Cox model. An elevated triglyceride (TG) remained the most significant risk factor of death (HR=1.469, 95% CI: 1.010 to 2.136, p=0.044), followed by base excess (BE) (HR=1.131, 95% CI: 1.046 to 1.223, p=0.002) and pH (HR=0.95, 95% CI: 0.93 to 0.97, p<0.001). The results of the ROC curve showed that combined diagnosis of the three indicators-TG+BE+pH-has the best area under the curve (AUC) (AUC=0.77, 95% CI: 0.69 to 0.85, p<0.001), with a 68% sensitivity and 80% specificity. CONCLUSION: Laboratory factors of TG, BE and pH during the first 24 hours after intensive care unit admission are associated with in-hospital mortality in PICU patients with sepsis. The combination of the three indices has high diagnostic value.

A structure-based designed small molecule depletes hRpn13Pru and a select group of KEN box proteins.

Proteasome subunit hRpn13 is partially proteolyzed in certain cancer cell types to generate hRpn13Pru by degradation of its UCHL5/Uch37-binding DEUBAD domain and retention of an intact proteasome- and ubiquitin-binding Pru domain. By using structure-guided virtual screening, we identify an hRpn13 binder (XL44) and solve its structure ligated to hRpn13 Pru by integrated X-ray crystallography and NMR to reveal its targeting mechanism. Surprisingly, hRpn13Pru is depleted in myeloma cells following treatment with XL44. TMT-MS experiments reveal a select group of off-targets, including PCNA clamp-associated factor PCLAF and ribonucleoside-diphosphate reductase subunit M2 (RRM2), that are similarly depleted by XL44 treatment. XL44 induces hRpn13-dependent apoptosis and also restricts cell viability by a PCLAF-dependent mechanism. A KEN box, but not ubiquitination, is required for XL44-induced depletion of PCLAF. Here, we show that XL44 induces ubiquitin-dependent loss of hRpn13Pru and ubiquitin-independent loss of select KEN box containing proteins.

hRpn13 shapes the proteome and transcriptome through epigenetic factors HDAC8, PADI4, and transcription factor NF-κB p50.

The anti-cancer target hRpn13 is a proteasome substrate receptor. However, hRpn13-targeting molecules do not impair its interaction with proteasomes or ubiquitin, suggesting other critical cellular activities. We find that hRpn13 depletion causes correlated proteomic and transcriptomic changes, with pronounced effects in myeloma cells for cytoskeletal and immune response proteins and bone-marrow-specific arginine deiminase PADI4. Moreover, a PROTAC against hRpn13 co-depletes PADI4, histone deacetylase HDAC8, and DNA methyltransferase MGMT. PADI4 binds and citrullinates hRpn13 and proteasomes, and proteasomes from PADI4-inhibited myeloma cells exhibit reduced peptidase activity. When off proteasomes, hRpn13 can bind HDAC8, and this interaction inhibits HDAC8 activity. Further linking hRpn13 to transcription, its loss reduces nuclear factor κB (NF-κB) transcription factor p50, which proteasomes generate by cleaving its precursor protein. NF-κB inhibition depletes hRpn13 interactors PADI4 and HDAC8. Altogether, we find that hRpn13 acts dually in protein degradation and expression and that proteasome constituency and, in turn, regulation varies by cell type.