Immune-infiltrating signature-based classification reveals CD103+CD39+ T cells associate with colorectal cancer prognosis and response to immunotherapy.

Background: Current stratification systems for tumor prognostic prediction and immunotherapeutic efficacy evaluation are less satisfying in colorectal cancer (CRC). As infiltrating immune cells in tumor microenvironment (TME) played a key role in tumor progression and responses to immune checkpoint blockade (ICB) therapy, we want to construct an immune-related scoring system with detailed immune profiles to stratify CRC patients. Methods: We developed a scoring system based on immune-related signatures and validated its ability to predict prognosis and immunotherapeutic outcomes in CRC. CD45+ cells from CRC patients were sorted to investigate detailed immune profiles of the stratification system using mass cytometry. A single-cell RNA sequencing dataset was used to analyze transcriptomic profiles. Results: We constructed an immune-related signature score (IRScore) based on 54 recurrence-free survival (RFS)-related immune signatures to stratify CRC patients. We revealed that IRScore was positively correlated with RFS and favorable outcomes in ICB treatment. Moreover, we depicted a detailed immune profile in TME using mass cytometry and identified that CD103+CD39+ T cells, characterized by an exhaustive, cytotoxic and proliferative phenotype, were enriched in CRC patients with high IRScore. As a beneficial immune signature, CD103+CD39+ T cells could predict prognosis and responses to ICB therapy in CRC. Conclusions: All the analyses above revealed that IRScore could be a valuable tool for predicting prognosis and facilitating the development of new therapeutic strategies in CRC, and CD103+CD39+ T cells were one of defined immune signatures in IRScore, which might be a key factor for antitumor immunity.

Distinct immunological signatures discriminate severe COVID-19 from non-SARS-CoV-2-driven critical pneumonia.

Immune profiling of COVID-19 patients has identified numerous alterations in both innate and adaptive immunity. However, whether those changes are specific to SARS-CoV-2 or driven by a general inflammatory response shared across severely ill pneumonia patients remains unknown. Here, we compared the immune profile of severe COVID-19 with non-SARS-CoV-2 pneumonia ICU patients using longitudinal, high-dimensional single-cell spectral cytometry and algorithm-guided analysis. COVID-19 and non-SARS-CoV-2 pneumonia both showed increased emergency myelopoiesis and displayed features of adaptive immune paralysis. However, pathological immune signatures suggestive of T cell exhaustion were exclusive to COVID-19. The integration of single-cell profiling with a predicted binding capacity of SARS-CoV-2 peptides to the patients' HLA profile further linked the COVID-19 immunopathology to impaired virus recognition. Toward clinical translation, circulating NKT cell frequency was identified as a predictive biomarker for patient outcome. Our comparative immune map serves to delineate treatment strategies to interfere with the immunopathologic cascade exclusive to severe COVID-19.

IL-7 receptor alpha defines heterogeneity and signature of human effector memory CD8+ T cells in high dimensional analysis.

The IL-7 receptor alpha chain (IL-7Rα or CD127) can be differentially expressed in memory CD8+ T cells. Here we investigated whether IL-7Rα could serve as a key molecule in defining a comprehensive landscape of heterogeneity in human effector memory (EM) CD8+ T cells using high-dimensional Cytometry by Time-Of-Flight (CyTOF) and single-cell RNA-seq (scRNA-seq). IL-7Rα had diverse, but organized, expressional relationship in EM CD8+ T cells with molecules related to cell function and gene regulation, which rendered an immune landscape defining heterogeneous cell subsets. The differential expression of these molecules likely has biological implications as we found in vivo signatures of transcription factors and homeostasis cytokine receptors, including T-bet and IL-7Rα. Our findings indicate the existence of heterogeneity in human EM CD8+ T cells as defined by distinct but organized expression patterns of multiple molecules in relationship to IL-7Rα and its possible biological significance in modulating downstream events.

Broad Immune Monitoring and Profiling of T Cell Subsets with Mass Cytometry.

Mass cytometry (cytometry by time-of-flight, CyTOF) is a high-dimensional single-cell analytical technology that allows for highly multiplexed measurements of protein or nucleic acid abundances by bringing together the detection capacity of atomic mass spectroscopy and the sample preparation workflow typical of regular flow cytometry. In 2014 the mass cytometer was adapted for the acquisition of samples from microscopy slides (termed imaging mass cytometry), greatly increasing the applicability of this technology with the inclusion of spatial information. By using antibodies (or other probes) labeled with purified metal isotopes, mass cytometers are currently able to detect more than 50 different parameters at a single-cell level, exceeding the dimensionality of any other flow cytometry methodology currently on the market. This capability licenses unprecedented possibilities in many areas dealing with complex cellular mixtures (immunology, cell biology, and beyond), improving biomarker discovery and moving us closer to affordable personalized medicine than before.

High-Dimensional Single-Cell Analysis with Mass Cytometry.

Mass cytometry is an analytical technology that combines the sample preparation workflow typical of flow cytometry and the detection capacity of atomic mass spectroscopy, allowing for highly multiplexed measurements of protein or nucleic acid targets on single cells. In 2014, the mass cytometer was adapted for the acquisition of samples from microscopy slides (termed imaging mass cytometry), greatly increasing the applicability of this technology. By using antibodies (or other probes) labeled with purified metal isotopes, the mass cytometer is able to detect up to 50 different parameters (current practical limit) at the single-cell level, enabling a deep and thorough profiling of individual cells in terms of their cell surface protein phenotype, physiological state, proliferation potential, and many other cell states or features. © 2017 by John Wiley & Sons, Inc.