PD-1 Limits IL-2 Production and Thymic Regulatory T Cell Development.

Inhibitory proteins, such as programmed cell death protein 1 (PD-1), have been studied extensively in peripheral T cell responses to foreign Ags, self-Ags, and neoantigens. Notably, these proteins are first expressed during T cell development in the thymus. Reports suggest that PD-1 limits regulatory T cell (Treg) development, but the mechanism by which PD-1 exerts this function remains unknown. The present study expands the evaluation of murine PD-1 and its ligands in the thymus, demonstrating that some of the highest expressers of PD-1 and programmed death-ligand 1 are agonist selected cells. Surprisingly, we reveal a selective role for PD-1 in regulating the developmental niche only for Tregs because other agonist selected cell populations, such as NK T cells, remain unchanged. We also ruled out PD-1 as a regulator of proliferation or cell death of agonist selected Tregs and further demonstrated that PD-1-deficient Tregs have reduced TCR signaling. Unexpectedly, the data suggest that PD-1-deficient thymocytes produce elevated levels of IL-2, a Treg niche-limiting cytokine. Collectively, these data suggest a novel role for PD-1 in regulating IL-2 production and the concurrent agonist selection of murine thymic Tregs. This observation has implications for the use of checkpoint blockade in the context of cancer and infection.

Predictors of thrombosis during VV ECMO: an analysis of 9809 patients from the ELSO registry.

Venovenous extracorporeal membrane oxygenation (VV-ECMO) is a life-saving therapy for critically ill patients, but it carries an increased risk of thrombosis due to blood interacting with non-physiological surfaces. While the relationship between clinical variables and thrombosis remains unclear, our study aimed to identify which factors are most predictive of thrombosis. The Extracorporeal Life Support Organization Registry was queried to obtain a cohort of VV-ECMO patients aged 18 years and older from 2015 to 2019. Patients who were over 80-years-old, at the extremes of weight, who received less than 24 h of ECMO, multiple rounds of ECMO, or had missing data were excluded. Multivariate logistic regression modeling was used to assess predictors of thrombosis and mortality. A total of 9809 patients were included in the analysis, with a mean age of 47.1 ± 15.1 years and an average ECMO run time of 305 ± 353 h. Thrombosis occurred in 19.9% of the cohort, with circuit thrombosis (8.6%) and membrane lung failure (6.1%) being the most common. Multivariate analysis showed that ECMO runs over 14 days (OR: 2.62, P < 0.001) and pregnancy-related complications (OR: 1.79, P = 0.004) were associated with an increased risk of thrombosis. Risk factors for circuit thrombosis included incremental unit increases in the pump flow rate at 24 h (OR: 1.07 [1.00-1.14], P = 0.044) and specific cannulation sites. Increased body weight (OR: 1.02 [1.00-1.04], P = 0.026) and increased duration on ECMO (OR: 3.82 [3.12-4.71], P < 0.001) were predictive of membrane lung failure. Additionally, patients with thrombosis were at increased likelihood of in-hospital mortality (OR: 1.52, P < 0.001). This study identified multiple thrombotic risk factors in VV-ECMO, suggesting that future studies investigating the impact of pregnancy associated complications and ECMO flow rate on hemostasis would be illuminating.

An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer.

Mechanisms of therapeutic resistance and vulnerability evolve in metastatic cancers as tumor cells and extrinsic microenvironmental influences change during treatment. To support the development of methods for identifying these mechanisms in individual people, here we present an omic and multidimensional spatial (OMS) atlas generated from four serial biopsies of an individual with metastatic breast cancer during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata that includes treatment times and doses, anatomic imaging, and blood-based response measurements to clinical and exploratory analyses, which includes comprehensive DNA, RNA, and protein profiles; images of multiplexed immunostaining; and 2- and 3-dimensional scanning electron micrographs. These data report aspects of heterogeneity and evolution of the cancer genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples of how integrative analyses of these data reveal potential mechanisms of response and resistance and suggest novel therapeutic vulnerabilities.

pepsickle rapidly and accurately predicts proteasomal cleavage sites for improved neoantigen identification.

MOTIVATION: Proteasomal cleavage is a key component in protein turnover, as well as antigen processing and presentation. Although tools for proteasomal cleavage prediction are available, they vary widely in their performance, options and availability. RESULTS: Herein, we present pepsickle, an open-source tool for proteasomal cleavage prediction with better in vivo prediction performance (area under the curve) and computational speed than current models available in the field and with the ability to predict sites based on both constitutive and immunoproteasome profiles. Post hoc filtering of predicted patient neoepitopes using pepsickle significantly enriches for immune-responsive epitopes and may improve current epitope prediction and vaccine development pipelines. AVAILABILITY AND IMPLEMENTATION: pepsickle is open source and available at https://github.com/pdxgx/pepsickle. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Human Leukocyte Antigen Susceptibility Map for Severe Acute Respiratory Syndrome Coronavirus 2.

Genetic variability across the three major histocompatibility complex (MHC) class I genes (human leukocyte antigen A [HLA-A], -B, and -C genes) may affect susceptibility to and severity of the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19). We performed a comprehensive in silico analysis of viral peptide-MHC class I binding affinity across 145 HLA-A, -B, and -C genotypes for all SARS-CoV-2 peptides. We further explored the potential for cross-protective immunity conferred by prior exposure to four common human coronaviruses. The SARS-CoV-2 proteome was successfully sampled and was represented by a diversity of HLA alleles. However, we found that HLA-B*46:01 had the fewest predicted binding peptides for SARS-CoV-2, suggesting that individuals with this allele may be particularly vulnerable to COVID-19, as they were previously shown to be for SARS (M. Lin, H.-T. Tseng, J. A. Trejaut, H.-L. Lee, et al., BMC Med Genet 4:9, 2003, https://bmcmedgenet.biomedcentral.com/articles/10.1186/1471-2350-4-9). Conversely, we found that HLA-B*15:03 showed the greatest capacity to present highly conserved SARS-CoV-2 peptides that are shared among common human coronaviruses, suggesting that it could enable cross-protective T-cell-based immunity. Finally, we reported global distributions of HLA types with potential epidemiological ramifications in the setting of the current pandemic.IMPORTANCE Individual genetic variation may help to explain different immune responses to a virus across a population. In particular, understanding how variation in HLA may affect the course of COVID-19 could help identify individuals at higher risk from the disease. HLA typing can be fast and inexpensive. Pairing HLA typing with COVID-19 testing where feasible could improve assessment of severity of viral disease in the population. Following the development of a vaccine against SARS-CoV-2, the virus that causes COVID-19, individuals with high-risk HLA types could be prioritized for vaccination.

Burden of tumor mutations, neoepitopes, and other variants are weak predictors of cancer immunotherapy response and overall survival.

BACKGROUND: Tumor mutational burden (TMB; the quantity of aberrant nucleotide sequences a given tumor may harbor) has been associated with response to immune checkpoint inhibitor therapy and is gaining broad acceptance as a result. However, TMB harbors intrinsic variability across cancer types, and its assessment and interpretation are poorly standardized. METHODS: Using a standardized approach, we quantify the robustness of TMB as a metric and its potential as a predictor of immunotherapy response and survival among a diverse cohort of cancer patients. We also explore the additive predictive potential of RNA-derived variants and neoepitope burden, incorporating several novel metrics of immunogenic potential. RESULTS: We find that TMB is a partial predictor of immunotherapy response in melanoma and non-small cell lung cancer, but not renal cell carcinoma. We find that TMB is predictive of overall survival in melanoma patients receiving immunotherapy, but not in an immunotherapy-naive population. We also find that it is an unstable metric with potentially problematic repercussions for clinical cohort classification. We finally note minimal additional predictive benefit to assessing neoepitope burden or its bulk derivatives, including RNA-derived sources of neoepitopes. CONCLUSIONS: We find sufficient cause to suggest that the predictive clinical value of TMB should not be overstated or oversimplified. While it is readily quantified, TMB is at best a limited surrogate biomarker of immunotherapy response. The data do not support isolated use of TMB in renal cell carcinoma.

Putatively cancer-specific exon-exon junctions are shared across patients and present in developmental and other non-cancer cells.

This study probes the distribution of putatively cancer-specific junctions across a broad set of publicly available non-cancer human RNA sequencing (RNA-seq) datasets. We compared cancer and non-cancer RNA-seq data from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) Project and the Sequence Read Archive. We found that (i) averaging across cancer types, 80.6% of exon-exon junctions thought to be cancer-specific based on comparison with tissue-matched samples (σ = 13.0%) are in fact present in other adult non-cancer tissues throughout the body; (ii) 30.8% of junctions not present in any GTEx or TCGA normal tissues are shared by multiple samples within at least one cancer type cohort, and 87.4% of these distinguish between different cancer types; and (iii) many of these junctions not found in GTEx or TCGA normal tissues (15.4% on average, σ = 2.4%) are also found in embryological and other developmentally associated cells. These findings refine the meaning of RNA splicing event novelty, particularly with respect to the human neoepitope repertoire. Ultimately, cancer-specific exon-exon junctions may have a substantial causal relationship with the biology of disease.

Myeloid lineage enhancers drive oncogene synergy in CEBPA/CSF3R mutant acute myeloid leukemia.

Acute Myeloid Leukemia (AML) develops due to the acquisition of mutations from multiple functional classes. Here, we demonstrate that activating mutations in the granulocyte colony stimulating factor receptor (CSF3R), cooperate with loss of function mutations in the transcription factor CEBPA to promote acute leukemia development. The interaction between these distinct classes of mutations occurs at the level of myeloid lineage enhancers where mutant CEBPA prevents activation of a subset of differentiation associated enhancers. To confirm this enhancer-dependent mechanism, we demonstrate that CEBPA mutations must occur as the initial event in AML initiation. This improved mechanistic understanding will facilitate therapeutic development targeting the intersection of oncogene cooperativity.