A modular and self-adjuvanted multivalent vaccine platform based on porcine circovirus virus-like nanoparticles.

BACKGROUND: Virus-like particles (VLPs) are supramolecular structures composed of multiple protein subunits and resemble natural virus particles in structure and size, making them highly immunogenic materials for the development of next-generation subunit vaccines. The orderly and repetitive display of antigenic epitopes on particle surface allows efficient recognition and cross-link by B cell receptors (BCRs), thereby inducing higher levels of neutralizing antibodies and cellular immune responses than regular subunit vaccines. Here, we present a novel multiple antigen delivery system using SpyCatcher/Spytag strategy and self-assembled VLPs formed by porcine circovirus type 2 (PCV2) Cap, a widely used swine vaccine in solo. RESULTS: Cap-SC, recombinant Cap with a truncated SpyCatcher polypeptide at its C-terminal, self-assembled into 26-nm VLPs. Based on isopeptide bonds formed between SpyCatcher and SpyTag, classical swine fever virus (CSFV) E2, the antigen of interest, was linked to SpyTag and readily surface-displayed on SpyCatcher decorated Cap-SC via in vitro covalent conjugation. E2-conjugated Cap VLPs (Cap-E2 NPs) could be preferentially captured by antigen presenting cells (APCs) and effectively stimulate APC maturation and cytokine production. In vivo studies confirmed that Cap-E2 NPs elicited an enhanced E2 specific IgG response, which was significantly higher than soluble E2, or the admixture of Cap VLPs and E2. Moreover, E2 displayed on the surface did not mask the immunodominant epitopes of Cap-SC VLPs, and Cap-E2 NPs induced Cap-specific antibody levels and neutralizing antibody levels comparable to native Cap VLPs. CONCLUSION: These results demonstrate that this modularly assembled Cap-E2 NPs retains the immune potential of Cap VLP backbone, while the surface-displayed antigen significantly elevated E2-induced immune potency. This immune strategy provides distinctly improved efficacy than conventional vaccine combination. It can be further applied to the development of dual or multiple nanoparticle vaccines to prevent co-infection of PCV2 and other swine pathogens.

PNI-Based Nomograms to Predict Tumor Progression and Survival for Patients with Unresectable Hepatocellular Carcinoma Undergoing Transcatheter Arterial Chemoembolization.

BACKGROUND: The relationship between the prognostic nutritional index (PNI) and the prognosis of malignancy has been increasingly mentioned in recent research. This study aimed to construct nomograms based on the PNI to predict tumor progression and survival in patients with unresectable hepatocellular carcinoma (HCC) undergoing transcatheter arterial chemoembolization (TACE). MATERIALS AND METHODS: The development set included 785 patients who underwent their first TACE between 2012 and 2016, and the validation set included 336 patients who underwent their first TACE between 2017 and 2018. The clinical outcomes included the time to progression (TTP) and overall survival (OS). Cox regression was applied to screen for independent risk factors of TTP and OS in the development set, and PNI-based nomograms were constructed for TTP and OS. The predictive performance of nomograms was conducted through the C-index, calibration curves, and decision analysis curves in the development set and validation set. RESULTS: After multivariate analysis, the prognostic predictors of both TTP and OS included portal vessel invasion, extrahepatic metastasis, tumor number, alpha-fetoprotein (AFP) level, longest tumor diameter, and PNI. Furthermore, the Child-Pugh classification and platelets (PLTs) were independent risk factors for OS only. Nomograms for predicting TTP and OS were constructed using TTP and OS prognostic factors. In the development set and the validation set, the C-index of the TTP nomograms was 0.699 (95% confidence interval (CI): 0.680-0.718) and 0.670 (95%CI: 0.638-0.702), and the C-index of the OS nomograms was 0.730 (95%CI: 0.712-0.748) and 0.700 (95%CI: 0.665-0.723), respectively. CONCLUSION: Nomograms based on the PNI can effectively predict tumor progression and survival in patients with unresectable HCC undergoing TACE.