Combine technology, unleash breakthroughs

The more we discover about our immune system and its response to disease, the more we realize how much there is to learn. Immune complexity is vast and interconnected. If we identify causative factors, we must then ask: Which ones are relevant to the disease or therapeutic response of interest? Which of the many pathways involved play a critical role in the problem we are trying to solve?

Given the dynamic and multicellular nature of immune responses, most research is focused on characterizing changes in cell populations that occur during disease progression, but is limited in distinguishing biomarkers that strongly correlate to pathogenesis, prognosis or outcome. In turn, biomarkers that provide weak biological correlates become adopted, and the opportunity to understand truly effective medicine is lost. Instead, an integrated approach that can overcome the challenges in selecting accurately predictive biomarkers is key to identifying and translating important immunologic and pathologic characteristics.

To start, highly multiplexed single-cell proteomics is a powerful tool for identifying and characterizing complex immune responses. Integrating this with large-scale plasma proteomic datasets can further enable interrogation of interconnected systems, adding a novel level of detail and insights to recognize new patterns. By combining multiple modalities, we can uncover the critical biomarkers and signatures that together hold higher predictive power in clinical research settings.

Here, we highlight this partnership with examples using CyTOF™ and SomaScan™ technologies. CyTOF systems use mass cytometry to simultaneously detect more than 50 markers in a single cell, providing a detailed view of cellular diversity and functional states within complex biological systems. The SomaScan Platform enables 11,000 protein measurements (half the genetically encoded human proteome!) from a 55 µL sample, uncovering downstream effects of genes and protein-protein interactions that reveal disease origin as well as potential risk of disease progression. 

Immune signature of postoperative cognitive decline includes one plasma protein and 10 immune cell features

An article by Verdonk et al. set out to better understand the biological processes underlying postoperative cognitive decline (POCD) in elderly patients. POCD, which can lead to impairments in verbal and visual memory, language comprehension, visuospatial abstraction, attention and concentration, is one of the most common complications after major surgery and affects 25–55% of elderly patients for up to a year. Researchers from Stanford University aimed to estimate POCD risk by identifying biomarkers with which they could develop a prognostic test. They looked to highly multiplexed single-cell mass cytometry and plasma-based proteomic modalities to assess connected biological systems and reveal pathophysiological crosstalk. They used CyTOF technology to analyze circulating immune cell subsets and the SomaScan Assay to quantify the pre- and post-operative plasma concentrations of proteins. The combination of technologies provided a comprehensive analysis of innate and adaptive immune cell activities that could differentiate patients with and without POCD. The resulting POCD immune signature offered a list of potential biomarkers for the development of point-of-care tests to help personalize perioperative management of at-risk patients.

Shared common characteristics across multi-omic assays distinguish distinct tumor microenvironments

Multiple myeloma (MM) is a cancer of plasma cells that arises from premalignant monoclonal gammopathy of undetermined significance (MGUS) and often progresses through an asymptomatic smoldering (SMM) phase. Identifying high-risk SMM individuals who are likely to progress to MM in the span of 2–3 years is a priority for clinicians. However, there is no consensus on how to accurately predict this continuum. Fernandez et al. looked to examine interactions between abnormal clonal plasma cells and the tumor microenvironment (TME) in the early disease states of MM to inform risk assessment and direct therapy.  The researchers used CyTOF technology to perform high-dimensional immunological analysis of bone marrow specimens and the SomaScan Assay to perform proteomic analysis of bone marrow plasma from 73 subjects with SMM. Mass cytometry, TCR-seq and plasma proteomics together identified three taxa of subjects that shared common characteristics across all three assays, revealing important immunologic and pathologic features of individuals with SMM and suggesting that the progression from MGUS to MM does not consist of a single pathway in the TME.

Multimodal proteomics finds age- and disease-specific changes associated with COVID-19

A publication from Arthur et al. examined the cellular and soluble determinants of COVID-19 relative to aging by profiling approximately 4,700 proteins from 71 individuals with pulmonary disease and 148 healthy donors (25–80 years old). Based on the knowledge that immune cell composition and environment can change significantly with age, combining technologies opens opportunities to learn about why responses to infection can differ with age. The team used blood testing in tandem with mass cytometry and proteomic profiling with the SomaScan Assay to examine the phenotypic characteristics of plasma and PBMC. CyTOF technology helped the researchers better understand changes in immune cell populations in COVID-19 patients, identifying both disease- and age-related changes in CD4+ T, CD8+ T and B cell subsets. Subsequent proteomic analysis revealed strong age-dependent effects within the disease signatures in addition to several disease-associated markers that had not been previously reported. Multi-omic analysis showed distinct age- and disease-specific alterations and provided new insights into potential mediators of the physiological impacts of COVID-19.

Learn more about a multi-omic approach

Learn more about how CyTOF technology increases cytometric utility by enabling the simultaneous assessment of a high number of parameters in every cell to maximize the information obtained from each sample.

Learn more about how the SomaScan Platform can detect the most proteins over a broad dynamic range without sacrificing reproducibility, sensitivity or specificity.