Neutralization of Mitochondrial Superoxide by Superoxide Dismutase 2 Promotes Bacterial Clearance and Regulates Phagocyte Numbers in Zebrafish

Mitochondria are known primarily as the location of the electron transport chain and energy production in cells. More recently, mitochondria have been shown to be signaling centers for apoptosis and inflammation. Reactive oxygen species (ROS) generated as by-products of the electron transport chain within mitochondria significantly impact cellular signaling pathways. Because of the toxic nature of ROS, mitochondria possess an antioxidant enzyme, superoxide dismutase 2 (SOD2), to neutralize ROS. If mitochondrial antioxidant enzymes are overwhelmed during severe infections, mitochondrial dysfunction can occur and lead to multiorgan failure or death. Pseudomonas aeruginosa is an opportunistic pathogen that can infect immunocompromised patients. Infochemicals and exotoxins associated with P. aeruginosa are capable of causing mitochondrial dysfunction. In this work, we describe the roles of SOD2 and mitochondrial ROS regulation in the zebrafish innate immune response to P. aeruginosa infection. sod2 is upregulated in mammalian macrophages and neutrophils in response to lipopolysaccharide in vitro, and sod2 knockdown in zebrafish results in an increased bacterial burden. Further investigation revealed that phagocyte numbers are compromised in Sod2-deficient zebrafish. Addition of the mitochondrion-targeted ROS-scavenging chemical MitoTEMPO rescues neutrophil numbers and reduces the bacterial burden in Sod2-deficient zebrafish. Our work highlights the importance of mitochondrial ROS regulation by SOD2 in the context of innate immunity and supports the use of mitochondrion-targeted ROS scavengers as potential adjuvant therapies during severe infections.     

Checkpoint-blocker-induced autoimmunity is associated with favourable outcome in metastatic melanoma and distinct T-cell expression profiles

Background Immune checkpoint blockers (ICBs) activate CD8⁺ T cells, eliciting both anti-cancer activity and immune-related adverse events (irAEs). The relationship of irAEs with baseline parameters and clinical outcome is unclear.Methods Retrospective evaluation of irAEs on survival was performed across primary (N = 144) and secondary (N = 211) independent cohorts of patients with metastatic melanoma receiving single agent (pembrolizumab/nivolumab—sICB) or combination (nivolumab and ipilimumab—cICB) checkpoint blockade. RNA from pre-treatment and post-treatment CD8⁺ T cells was sequenced and differential gene expression according to irAE development assessed.Results 58.3% of patients developed early irAEs and this was associated with longer progression-free (PFS) and overall survival (OS) across both cohorts (log-rank test, OS: P < 0.0001). Median survival for patients without irAEs was 16.6 months (95% CI: 10.9–33.4) versus not-reached (P = 2.8 × 10⁻⁶). Pre-treatment monocyte and neutrophil counts, but not BMI, were additional predictors of clinical outcome. Differential expression of numerous gene pathway members was observed in CD8⁺ T cells according to irAE development, and patients not developing irAEs demonstrating upregulated CXCR1 pre- and post-treatment.Conclusions Early irAE development post-ICB is associated with favourable survival in MM. Development of irAEs is coupled to expression of numerous gene pathways, suggesting irAE development in-part reflects baseline immune activation.Subject terms: Immunotherapy, Melanoma     

Population Genetics Identifies Challenges in Analyzing Rare Variants

Geneticists have, for years, understood the nature of genome‐wide association studies using common genomic variants. Recently, however, focus has shifted to the analysis of rare variants. This presents potential problems for researchers, as rare variants do not always behave in the same way common variants do, sometimes rendering decades of solid intuition moot. In this paper, we present examples of the differences between common and rare variants. We show why one must be significantly more careful about the origin of rare variants, and how failing to do so can lead to highly inflated type I error. We then explain how to best avoid such concerns with careful understanding and study design. Additionally, we demonstrate that a seemingly low error rate in next‐generation sequencing can dramatically impact the false‐positive rate for rare variants. This is due to the fact that rare variants are, by definition, seen infrequently, making it hard to distinguish between errors and real variants. Compounding this problem is the fact that the proportion of errors is likely to get worse, not better, with increasing sample size. One cannot simply scale their way up in order to solve this problem. Understanding these potential pitfalls is a key step in successfully identifying true associations between rare variants and diseases.