Circular RNA cancer vaccines drive immunity in hard-to-treat malignancies.

Rationale: Messenger RNA (mRNA) vaccine outperforms other kinds of cancer immunotherapy due to its high response rates, easy preparation, and wide applicability, which is considered as one of the most promising forms of next-generation cancer therapies. However, the inherent instability and insufficient protein expression duration of mRNA limit the efficacy and widespread application of the vaccine. Methods: Here, we first tested the possibility of a novel circular RNA (circRNA) platform for protein expression and compare its duration with linear RNA. Then, we developed a lipid nanoparticle (LNP) system for circRNA delivery in vitro and in vivo. Next, the innate and adaptive immune response of circRNA-LNP complex was evaluated in vivo. The anti-tumor efficacy of circRNA-LNP was further confirmed in three tumor models. Finally, the possibility of combination therapy with circRNA-LNP and adoptive cell transfer therapy was further investigated in a late-stage tumor model. Results: We successfully increased the stability of the RNA vaccine by circularizing the linear RNA molecules to form highly stable circRNA molecules which exhibited durable protein expression ability. By encapsulating the antigen-coding circRNA in LNP enabling in vivo expression, we established a novel circRNA vaccine platform, which was capable of triggering robust innate and adaptive immune activation and showed superior anti-tumor efficacy in multiple mouse tumor models. Conclusions: Overall, our circRNA vaccine platform provides a novel prospect for the development of cancer RNA vaccines in a wide range of hard-to-treat malignancies.

The utility of MEWS for predicting the mortality in the elderly adults with COVID-19: a retrospective cohort study with comparison to other predictive clinical scores.

BACKGROUND: Older adults have been reported to be a population with high-risk of death in the COVID-19 outbreak. Rapid detection of high-risk patients is crucial to reduce mortality in this population. The aim of this study was to evaluate the prognositc accuracy of the Modified Early Warning Score (MEWS) for in-hospital mortality in older adults with COVID-19. METHODS: A retrospective cohort study was conducted in Wuhan Hankou Hospital in China from 1 January 2020 to 29 February 2020. Receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of MEWS, Acute Physiology and Chronic Health Evaluation II (APACHE II), Sequential Organ Function Assessment (SOFA), quick Sequential Organ Function Assessment (qSOFA), Pneumonia Severity Index (PSI), Combination of Confusion, Urea, Respiratory Rate, Blood Pressure, and Age ≥65 (CURB-65), and the Systemic Inflammatory Response Syndrome Criteria (SIRS) for in-hospital mortality. Logistic regression models were performed to detect the high-risk older adults with COVID-19. RESULTS: Among the 235 patients included in this study, 37 (15.74%) died and 131 (55.74%) were male, with an average age of 70.61 years (SD 8.02). ROC analysis suggested that the capacity of MEWS in predicting in-hospital mortality was as good as the APACHE II, SOFA, PSI and qSOFA (Difference in AUROC: MEWS vs. APACHE II, -0.025 (95% CI [-0.075 to 0.026]); MEWS vs. SOFA, -0.013 (95% CI [-0.049 to 0.024]); MEWS vs. PSI, -0.015 (95% CI [-0.065 to 0.035]); MEWS vs. qSOFA, 0.024 (95% CI [-0.029 to 0.076]), all P > 0.05), but was significantly higher than SIRS and CURB-65 (Difference in AUROC: MEWS vs. SIRS, 0.218 (95% CI [0.156-0.279]); MEWS vs. CURB-65, 0.064 (95% CI [0.002-0.125]), all P < 0.05). Logistic regression models implied that the male patients (≥75 years) had higher risk of death than the other older adults (estimated coefficients: 1.16, P = 0.044). Our analysis further suggests that the cut-off points of the MEWS score for the male patients (≥75 years) subpopulation and the other elderly patients should be 2.5 and 3.5, respectively. CONCLUSIONS: MEWS is an efficient tool for rapid assessment of elderly COVID-19 patients. MEWS has promising performance in predicting in-hospital mortality and identifying the high-risk group in elderly patients with COVID-19.