In this study we profiled vaccine-induced polyclonal antibodies as well as plasmablast derived mAbs from individuals who received SARS-CoV-2 spike mRNA vaccine. Polyclonal antibody responses in vaccinees were robust and comparable to or exceeded those seen after natural infection. However, the ratio of binding to neutralizing antibodies after vaccination was greater than that after natural infection and, at the monoclonal level, we found that the majority of vaccine-induced antibodies did not have neutralizing activity. We also found a co-dominance of mAbs targeting the NTD and RBD of SARS-CoV-2 spike and an original antigenic-sin like backboost to seasonal human coronaviruses OC43 and HKU1. Neutralizing activity of NTD mAbs but not RBD mAbs against a clinical viral isolate carrying E484K as well as extensive changes in the NTD was abolished, suggesting that a proportion of vaccine induced RBD binding antibodies may provide substantial protection against viral variants carrying single E484K RBD mutations.

Obesity is associated with an increased risk of developing breast cancer and is also associated with worse clinical prognosis. The mechanistic link between obesity and breast cancer progression remains unclear, and there has been no development of specific treatments to improve the outcome of obese cancer patients. Here we show that obesity-associated NLRC4 inflammasome activation/ interleukin (IL)-1 signalling promotes breast cancer progression. The tumour microenvironment in the context of obesity induces an increase in tumour-infiltrating myeloid cells with an activated NLRC4 inflammasome that in turn activates IL-1β, which drives disease progression through adipocyte-mediated vascular endothelial growth factor A (VEGFA) expression and angiogenesis. Further studies show that treatment of mice with metformin inhibits obesity-associated tumour progression associated with a marked decrease in angiogenesis. This report provides a causal mechanism by which obesity promotes breast cancer progression and lays out a foundation to block NLRC4 inflammasome activation or IL-1β signalling transduction that may be useful for the treatment of obese cancer patients.

Clear cell renal cell carcinoma (ccRCC) is one of the most immunologically distinct tumor types due to high response rate to immunotherapies, despite low tumor mutational burden. To characterize the tumor immune microenvironment of ccRCC, we applied single-cell-RNA sequencing (SCRS) along with T-cell-receptor (TCR) sequencing to map the transcriptomic heterogeneity of 25,688 individual CD45+ lymphoid and myeloid cells in matched tumor and blood from three patients with ccRCC. We also included 11,367 immune cells from four other individuals derived from the kidney and peripheral blood to facilitate the identification and assessment of ccRCC-specific differences. There is an overall increase in CD8+ T-cell and macrophage populations in tumor-infiltrated immune cells compared to normal renal tissue. We further demonstrate the divergent cell transcriptional states for tumor-infiltrating CD8+ T cells and identify a MKI67 + proliferative subpopulation being a potential culprit for the progression of ccRCC. Using the SCRS gene expression, we found preferential prediction of clinical outcomes and pathological diseases by subcluster assignment. With further characterization and functional validation, our findings may reveal certain subpopulations of immune cells amenable to therapeutic intervention.

Single-cell sequencing is an emerging technology in the field of immunology and oncology that allows researchers to couple RNA quantification and other modalities, like immune cell receptor profiling at the level of an individual cell. A number of workflows and software packages have been created to process and analyze single-cell transcriptomic data. These packages allow users to take the vast dimensionality of the data generated in single-cell-based experiments and distill the data into novel insights. Unlike the transcriptomic field, there is a lack of options for software that allow for single-cell immune receptor profiling. Enabling users to easily combine mRNA and immune profiling, scRepertoire was built to process data derived from 10x Genomics Chromium Immune Profiling for both T-cell receptor (TCR) and immunoglobulin (Ig) enrichment workflows and subsequently interacts with a number of popular R packages for single-cell expression, such as Seurat. The scRepertoire R package and processed data are open source and available on GitHub and provides in-depth tutorials on the capability of the package.