Integrated T cell cytometry metrics for immune-monitoring applications in immunotherapy clinical trials

Systems immunology spanning tumors, lymph nodes, and periphery

“…Still, these categorical cell labels can mask the continuously variable nature of immunobiology, such as the differentiation state along the hematopoietic lineage. 69 Computational methods for immunomics are emerging alongside single-cell technologies to better capture this complex nature of immune cell function ( Table 2 ). These techniques are critical to capture the dynamic nature of cellular phenotypes both from single-cell proteomics and transcriptomics assays.…”

“…As an example, unsupervised learning methods for matrix factorization and trajectory inference can further provide a dynamic rather than a static method of studying multiple co-expressing features using continuous weights. 69 This can be applied to study immune cell trafficking by quantifying state transitions using weighted matrix factors or trajectory inference metrics, such as pseudotime, to compare between tumors and the periphery. However, without tracing the same cell, all of these single-cell assessments of trafficking directionality are limited to correlations between samples.…”

Immune profiling of age and adjuvant-specific activation of human blood mononuclear cells in vitro

“…Overall, the success of CyTOF during the last decade highlights the importance of advanced technologies in characterizing the immune response to the pathogens, and in developing new treatments or therapies to combat the disease [34][35][36] . High-dimensional data is complex and requires sophisticated computational analysis to extract meaningful biological insights.…”