Liter-scale manufacturing of shelf-stable plasmid DNA/PEI transfection particles for viral vector production.

The transfection efficiency and stability of the delivery vehicles of plasmid DNA (pDNA) are critical metrics to ensure high-quality and high-yield production of viral vectors. We previously identified that the optimal size of pDNA/poly(ethylenimine) (PEI) transfection particles is 400-500 nm and developed a bottom-up assembly method to construct stable 400-nm pDNA/PEI particles and benchmarked their transfection efficiency in producing lentiviral vectors (LVVs). Here, we report scale-up production protocols for such transfection particles. Using a two-inlet confined impinging jet (CIJ) mixer with a dual syringe pump set-up, we produced a 1-L batch at a flow rate of 100 mL/min, and further scaled up this process with a larger CIJ mixer and a dual peristaltic pump array, allowing for continuous production at a flow rate of 1 L/min without a lot size limit. We demonstrated the scalability of this process with a 5-L lot and validated the quality of these 400-nm transfection particles against the target product profile, including physical properties, shelf and on-bench stability, transfection efficiency, and LVV production yield in both 15-mL bench culture and 2-L bioreactor runs. These results confirm the potential of this particle assembly process as a scalable manufacturing platform for viral vector production.

Screening for lipid nanoparticles that modulate the immune activity of helper T cells towards enhanced antitumour activity.

Lipid nanoparticles (LNPs) can be designed to potentiate cancer immunotherapy by promoting their uptake by antigen-presenting cells, stimulating the maturation of these cells and modulating the activity of adjuvants. Here we report an LNP-screening method for the optimization of the type of helper lipid and of lipid-component ratios to enhance the delivery of tumour-antigen-encoding mRNA to dendritic cells and their immune-activation profile towards enhanced antitumour activity. The method involves screening for LNPs that enhance the maturation of bone-marrow-derived dendritic cells and antigen presentation in vitro, followed by assessing immune activation and tumour-growth suppression in a mouse model of melanoma after subcutaneous or intramuscular delivery of the LNPs. We found that the most potent antitumour activity, especially when combined with immune checkpoint inhibitors, resulted from a coordinated attack by T cells and NK cells, triggered by LNPs that elicited strong immune activity in both type-1 and type-2 T helper cells. Our findings highlight the importance of optimizing the LNP composition of mRNA-based cancer vaccines to tailor antigen-specific immune-activation profiles.

Development and validation of a machine learning model of radiation-induced hypothyroidism with clinical and dose-volume features.

BACKGROUND AND PURPOSE: Radiation-induced hypothyroidism (RIHT) is a common but underestimated late effect in head and neck cancers. However, no consensus exists regarding risk prediction or dose constraints in RIHT. We aimed to develop a machine learning model for the accurate risk prediction of RIHT based on clinical and dose-volume features and to evaluate its performance internally and externally. MATERIALS AND METHODS: We retrospectively searched two institutions for patients aged >20 years treated with definitive radiotherapy for nasopharyngeal or oropharyngeal cancer, and extracted their clinical information and dose-volume features. One was designated the developmental cohort, the other as the external validation cohort. We compared the performances of machine learning models with those of published normal tissue complication probability (NTCP) models. RESULTS: The developmental and external validation cohorts consisted of 378 and 49 patients, respectively. The estimated cumulative incidence rates of grade ≥1 hypothyroidism were 53.5% and 61.3% in the developmental and external validation cohorts, respectively. Machine learning models outperformed traditional NTCP models by having lower Brier scores at every time point and a lower integrated Brier score, while demonstrating a comparable calibration index and mean area under the curve. Even simplified machine learning models using only thyroid features performed better than did traditional NTCP algorithms. The machine learning models showed consistent performance between folds. The performance in a previously unseen external validation cohort was comparable to that of the cross-validation. CONCLUSIONS: Our model outperformed traditional NTCP models, with additional capabilities of predicting the RIHT risk at individual time points. A simplified model using only thyroid dose-volume features still outperforms traditional NTCP models and can be incorporated into future treatment planning systems for biological optimization.

Streptozotocin inhibits synaptic transmission and edaravone attenuates streptozotocin-induced electrophysiological changes in CA1 pyramidal neurons of rat hippocampal slices.

The purpose of this study was to investigate the acute and chronic effects of streptozotocin (STZ) upon synaptic transmission and the effects of edaravone (EDA, a free radical scavenger) on STZ-induced electrophysiological changes in CA1 pyramidal neurons of rat hippocampal slices. To accomplish this goal, spontaneous excitatory postsynaptic current (sEPSC), miniature excitatory postsynaptic current (mEPSC), spontaneous inhibitory postsynaptic current (sIPSC) and miniature inhibitory postsynaptic current (mIPSC) were recorded within hippocampal slices using whole-cell patch clamp techniques. The results showed that the amplitudes and frequencies of sEPSC, mEPSC, sIPSC and mIPSC were inhibited by 1000µM STZ, while treatment of EDA (1000µM) attenuated these STZ-induced changes. The degree of these neurotoxic effects of STZ and effects of EDA increased as a function of drug duration as assessed at 2, 4 or 8h of exposure. Taken together, our results demonstrate that STZ induces neurotoxicity within these hippocampal slices through its capacity to alter synaptic transmission and these STZ-induced alterations in electrophysiological responses are attenuated by EDA.