Immune cells in the body are constantly reacting to messages from cancer cells, other immune cells, and micro-organisms. These messages produce specific patterns of molecular expression that are relevant to illnesses such as cancer, autoimmune disease, infection, and inflammation, as well as to therapeutic interventions. The patterns have been challenging for scientists to discern because of the minute quantities of the pertinent molecules in the cells. Investigators have now made an important step in revealing these molecular patterns in immune cells from the blood and thereby discovering novel indicators of health and disease.
Researchers CellPrint Biotechnology LLC, Case Western Reserve University, and the Cleveland Clinic Foundation led by Professor David Kaplan carried out the study. Their work is published in the peer-reviewed Journal of Cellular and Molecular Medicine.
Professor Kaplan explained that their method relies on a more advanced version of flow cytometry, a technology that measures what is happening inside individual cells by passing them through a laser beam to detect the molecules within. Unlike traditional approaches, this new version has up to a hundred times better resolution, which means it can detect molecules that exist in very small amounts and analyze how they are connected. “Our amplification technology has demonstrated excellent sensitivity and, with our recent development of restricted-dimensional cytometry, we have achieved a high level of precision,” Professor Kaplan noted. Restricted-dimensional cytometry is a streamlined way of measuring fewer features at a time to gain clearer and more reliable results.
Professor Kaplan’s team first showed that the method works by examining a well-known pathway of the immune system called the stimulator of interferon genes pathway, which triggers the body’s first line of defense against infections. By using samples from healthy volunteers, they confirmed that their system could measure molecular changes in a steady and predictable way. This showed that their method could capture both the broader picture and the finer details of how signals move within cells.
Later, when the same method was tested on blood samples treated with a drug known to effect cell death, unexpected patterns appeared. Some signalling molecules kept their relationships, others split apart, and brand-new connections were formed. One example involved a group of molecules tied to programmed cell death, the natural process where old or damaged cells are safely removed. Some cellular molecules were closely linked before treatment but showed broken coordination after the drug was introduced. These findings suggest that medicines can rewire the inner workings of cells in ways that might be missed by less sensitive techniques.
Equally striking, when applied to blood samples from people with plasma cell disorders such as multiple myeloma, a cancer of plasma cells, and amyloidosis, a condition where proteins build up abnormally in tissues, the method uncovered unique signalling patterns for different types of cells. Monocytes, which are immune cells that fight infection, and helper T cells, which guide immune responses, displayed distinctive sets of molecular interactions, with certain molecules strongly linked in one cell type but not the other. These differences, the team believes, may be crucial to understanding how these diseases develop and progress.
Professor Kaplan stressed the wider meaning of their work: “We have described a simplified technology, based on a signal amplification technology and restricted-dimensional cytometry, that allows for the analysis of the signalling network in blood mononuclear cells from clinical samples. This analysis is likely to provide valuable novel insights into the participation of the signalling network in pathophysiology and pathogenesis”. Pathophysiology refers to the changes in body functions caused by disease, while pathogenesis means the origin and development of disease.
Professor Kaplan’s findings from this investigation not only show that cell signalling can be pictured with great clarity but also hint that these molecular maps could guide doctors and scientists toward better ways of understanding and even predicting disease behavior. By showing how molecules in blood immune cells interact differently in sickness and in health, this method could inspire new directions for diagnosis, prognosis, and treatment. Diagnosis is the process of identifying a disease, prognosis is the likely course or outcome of that disease, and treatment is the way doctors act to manage it.
As cell signalling lies at the center of many illnesses, the possible uses of this discovery are wide-ranging. The results could help clinicians monitor disease in real time, measure how patients respond to treatment, and reveal hidden pathways that matter in cancer and immune system disorders. Professor Kaplan and his team’s study demonstrates that by listening more carefully to the quiet conversations inside blood immune cells, science is moving closer to turning these subtle signals into meaningful clinical insights.
Journal Reference
Kaplan D., Lazarus H.M., Valent J., Anwer F., Mazzoni S., Samaras C., Williams L., Nakashima M., Hanna M., Raza S., Christian E., Khouri J. “Signalling Network Analysis of Blood Mononuclear Cells From Clinical Samples by Bivariate Correlation.” Journal of Cellular and Molecular Medicine, 2025; Volume 29. DOI: https://doi.org/10.1111/jcmm.70550
About the Author
Professor Kaplan received MD and PhD degrees from the University of Chicago. He served as a pathology resident at Barnes and Jewish Hospitals in Saint Louis and continued his research efforts as a post-doctoral fellow at Washington University. Dr. Kaplan joined the faculty in the Case Western Reserve University School of Medicine where he established a biomedical research laboratory. He also served as the director of Diagnostic Immunology and Virology laboratories at University Hospitals Cleveland. He has achieved many firsts in his research including the first cloning of human cytotoxic T cells specific for influenza virus, the first stable gene transfer into human T lymphocytes, the first use of antisense DNA to turn off expression of specific proteins in human T cells, and the first description of T cell surface molecules active in mediating immunoregulation.
