The molecular characterization of immune subsets is important for designing effective strategies to understand and treat diseases. We characterized 29 immune cell types within the peripheral blood mononuclear cell (PBMC) fraction of healthy donors using RNA-seq (RNA sequencing) and flow cytometry. Our dataset was used, first, to identify sets of genes that are specific, are co-expressed, and have housekeeping roles across the 29 cell types. Then, we examined differences in mRNA heterogeneity and mRNA abundance revealing cell type specificity. Last, we performed absolute deconvolution on a suitable set of immune cell types using transcriptomics signatures normalized by mRNA abundance. Absolute deconvolution is ready to use for PBMC transcriptomic data using our Shiny app (https://github.com/giannimonaco/ABIS). We benchmarked different deconvolution and normalization methods and validated the resources in independent cohorts. Our work has research, clinical, and diagnostic value by making it possible to effectively associate observations in bulk transcriptomics data to specific immune subsets.

Motivation: Flow cytometry (FCM) is widely used in both clinical and basic research to characterize cell phenotypes and functions. The latest FCM instruments analyze up to 20 markers of individual cells, producing high-dimensional data. This requires the use of the latest clustering and dimensionality reduction techniques to automatically segregate cell sub-populations in an unbiased manner. However, automated analyses may lead to false discoveries due to inter-sample differences in quality and properties.

Immune checkpoint blockade (ICB) has substantially improved the prognosis of patients with cancer, but the majority experiences limited benefit, supporting the need for new therapeutic approaches. Up-regulation of sialic acid–containing glycans, termed hypersialylation, is a common feature of cancer-associated glycosylation, driving disease progression and immune escape through the engagement of Siglec receptors on tumor-infiltrating immune cells. Here, we show that tumor sialylation correlates with distinct immune states and reduced survival in human cancers. The targeted removal of Siglec ligands in the tumor microenvironment, using an antibody-sialidase conjugate, enhanced antitumor immunity and halted tumor progression in several murine models. Using single-cell RNA sequencing, we revealed that desialylation repolarized tumor-associated macrophages (TAMs). We also identified Siglec-E as the main receptor for hypersialylation on TAMs. Last, we found that genetic and therapeutic desialylation, as well as loss of Siglec-E, enhanced the efficacy of ICB. Thus, therapeutic desialylation represents an immunotherapeutic approach to reshape macrophage phenotypes and augment the adaptive antitumor immune response.

Background: A deeper understanding of differences and similarities in transcriptional regulation between species can uncover important information about gene functions and the role of genes in disease. Deciphering such patterns between mice and humans is especially important since mice play an essential role in biomedical research. Results: Here, in order to characterize evolutionary changes between humans and mice, we compared gene co-expression maps to evaluate the conservation of co-expression. We show that the conservation of co-expression connectivity of homologous genes is negatively correlated with molecular evolution rates, as expected. Then we investigated evolutionary aspects of gene sets related to functions, tissues, pathways and diseases. Genes expressed in the testis, eye and skin, and those associated with regulation of transcription, olfaction, PI3K signalling, response to virus and bacteria were more divergent between mice and humans in terms of co-expression connectivity. Surprisingly, a deeper investigation of the PI3K signalling cascade revealed that its divergence is caused by the most crucial genes of this pathway, such as mTOR and AKT2. On the other hand, our analysis revealed that genes expressed in the brain and in the bone, and those associated with cell adhesion, cell cycle, DNA replication and DNA repair are most strongly conserved in terms of co-expression network connectivity as well as having a lower rate of duplication events. Genes involved in lipid metabolism and genes specific to blood showed a signature of increased co-expression connectivity in the mouse. In terms of diseases, co-expression connectivity of genes related to metabolic disorders is the most strongly conserved between mice and humans and tumor-related genes the most divergent. Conclusions: This work contributes to discerning evolutionary patterns between mice and humans in terms of gene interactions. Conservation of co-expression is a powerful approach to identify gene targets and processes with potential similarity and divergence between mice and humans, which has implications for drug testing and other studies employing the mouse as a model organism.

Immune adaptation with aging is a major of health outcomes. Studies in humans have mainly focus on αβ T cells while γδ T cells have been neglected despite their role in immunosurveillance. We investigated the impact of aging on γδ T cell subsets phenotypes, functions, senescence and their molecular response to stress. Peripheral blood of young and old donors in Singapore have been used to assess the phenotype, functional capacity, proliferation capacity and gene expression of the various γδ T cell subsets. Peripheral blood mononuclear cells from apheresis cones and young donors have been used to characterize the telomere length, epigenetics profile and DNA damage response of the various γδ T cell subsets phenotype. Our data shows that peripheral Vδ2+ phenotype, functional capacity (cytokines, cytotoxicity, proliferation) and gene expression profile are specific when compared against all other αβ and γδ T cells in aging. Hallmarks of senescence including telomere length, epigenetic profile and DNA damage response of Vδ2+ also differs against all other αβ and γδ T cells. Our results highlight the differential impact of lifelong stress on γδ T cells subsets, and highlight possible mechanisms that enable Vδ2+ to be resistant to cellular aging. The new findings reinforce the concept that Vδ2+ have an "innate-like" behavior and are more resilient to the environment as compared to "adaptive-like" Vδ1+ T cells.

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.