Linear DNA Amplicons as a Novel Antiviral and Cancer Vaccine Strategy

Background DNA-based vaccines represent a simple, safe and promising strategy for harnessing the immune system to fight infectious diseases as well as various forms of cancer and thus are considered an important tool in the cancer immunotherapy toolbox. Nonetheless, the manufacture of plasmid DNA vaccines has several drawbacks, including long lead times and the need to remove impurities from bacterial cultures. Here we report the development of polymerase chain reaction (PCR)-produced amplicon expression vectors as DNA vaccines and their in vivo application to elicit antigen-specific immune responses in animal cancer models.1 Methods Plasmid DNA and amplicon expression was assessed both in vitro, by Hela cells transfection, and in vivo, by evaluating luciferase expression in mice through optical imaging. Immunogenicity induced by DNA amplicons was assessed by vaccinating mice, cats and ferrets against SARS-CoV-2 Spike protein. Similarly, amplicons encoding a tumor-associated antigen (Telomerase Reverse Transcriptase, TERT) and neoantigens were tested to evaluate the antitumoral effect of DNA amplicons in murine cancer models in combination with immunecheckpoint inhibitors (ICIs). Results Amplicons encoding Spike Receptor Binding Domain (RBD) were strongly immunogenic in all models and were able to confer antiviral effects. DNA vaccines encoding tumorassociated- antigens, such as telomerase reverse transcriptase or neoantigens expressed by murine tumor cell lines were able to elicit antigen-specific immune responses and proved to significantly impact tumor growth when administered in combination with ICIs. Conclusions These results strongly support the further exploration of the use of PCR-based amplicons as an innovative immunotherapeutic approach to viral diseases and cancer treatment.

Patient-reported health outcomes of SARS-CoV-2-tested patients presenting to emergency departments: a propensity score-matched prospective cohort study.

OBJECTIVE: This study aimed to compare the long-term physical and mental health outcomes of matched severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive and SARS-CoV-2-negative patients controlling for seasonal effects. STUDY DESIGN: This was a retrospective cohort study. METHODS: This study enrolled patients presenting to emergency departments participating in the Canadian COVID-19 Emergency Department Rapid Response Network. We enrolled consecutive eligible consenting patients who presented between March 1, 2020, and July 14, 2021, and were tested for SARS-CoV-2. Research assistants randomly selected four site and date-matched SARS-CoV-2-negative controls for every SARS-CoV-2-positive patient and interviewed them at least 30 days after discharge. We used propensity scores to match patients by baseline characteristics and used linear regression to compare Veterans RAND 12-item physical health component score (PCS) and mental health component scores (MCS), with higher scores indicating better self-reported health. RESULTS: We included 1170 SARS-CoV-2-positive patients and 3716 test-negative controls. The adjusted mean difference for PCS was 0.50 (95% confidence interval [CI]: -0.36, 1.36) and -1.01 (95% CI: -1.91, -0.11) for MCS. Severe disease was strongly associated with worse PCS (ß = -7.4; 95% CI: -9.8, -5.1), whereas prior mental health illness was strongly associated with worse MCS (ß = -5.4; 95% CI: -6.3, -4.5). CONCLUSION: Physical health, assessed by PCS, was similar between matched SARS-CoV-2-positive and SARS-CoV-2-negative patients, whereas mental health, assessed by MCS, was worse during a time when the public experienced barriers to care. These results may inform the development and prioritization of support programs for patients.

Predictors of longer-term depression trajectories during the COVID-19 pandemic: a longitudinal study in four UK cohorts.

BACKGROUND: The COVID-19 pandemic has caused an increase in mental ill health compared with prepandemic levels. Longer-term trajectories of depression in adults during the pandemic remain unclear. OBJECTIVE: We used latent growth curve modelling to examine individual trajectories of depression symptoms, and their predictors, beyond the early stage of the pandemic. METHODS: Data were collected in three waves in May 2020, September/October 2020 and February/March 2021 in four UK cohorts (Millennium Cohort Study, Next Steps cohort, British Cohort and National Child Development Study). We included n=16 978 participants (mean age at baseline: 20, 30, 50 and 62, respectively). Self-reported depressive symptoms were the study outcome. FINDINGS: Symptoms of depression were higher in younger compared with older age groups (d=0.7) across all waves. While depressive symptoms remained stable from May 2020 to Autumn 2020 overall (standardized mean difference (SMD)=0.03, 95% CI 0.02 to 0.04), they increased in all age groups from May 2020 to Spring 2021 (SMD=0.12, 95% CI 0.11 to 0.13). Feelings of loneliness were the strongest predictor and concurrent correlate of increasing depressive symptoms across all cohorts, prepandemic mental health problems and having a long-term illness were also significantly associated with an increase in depression symptoms across all ages. By contrast, compliance with social distancing measures did not predict an increase in depression symptoms. CONCLUSIONS: Feeling lonely and isolated had a large effect on depression trajectories across all generations, while social distancing measures did not. CLINICAL IMPLICATIONS: These findings highlight the importance of fostering the feeling of connectedness during COVID-19-related distancing measures.