Background & Aim Enumerating circulating white blood cells in peripheral blood using flow cytometry is a popular method for tracking changes in the immune system. We have developed a methodology using quantitative flow cytometry to study 100+ phenotypes in combination with bioinformatic approaches to identify characteristic immune profiles or combinations of similarly expressed leukocytes among patient groups. Currently, aside from survival and degree of disease progression or treatment benefit there is a lack of methods for identifying active changes to the immune system and good markers for identify cause of adverse events, all problems which could be solved with the use of immune monitoring. Currently, the Mayo clinic has utilized this method in over 30% of their MSC, DC, and CAR-T clinical trials with the intent of monitoring all trials using this methodology. Thus far we have applied this analysis to disease patient groups such as amyotrophic lateral sclerosis, thyroid cancer, liver cancer, glioblastoma multiforme, and chronic lymphocytic leukemia. Methods, Results & Conclusion These analyses uncovered previously unidentified subgroups of ALS patients that predicted survival, biomarkers in diseased patients, and changes in the immune systems of those in clinical trials. When clustered with healthy volunteers, we found two distinct profiles of ALS patients, one that more closely resembled a healthy immune system and one that did not. Patients that profiled separately from healthy volunteers had unique phenotypic characteristics such as increased absolute counts of CD3+CD56+ (p>0.001), CD3+CD8+CD28+ (p>0.001), CD3+CD4+PD-1+ T cells, increased survival (p=0.012), and were more likely to have familial ALS rather than sporadic (p=0.011). Additionally, we have tested our system on a cohort of 130 healthy volunteers to see which immune parameters contribute most to clustering of non-diseased individuals. Thus, we believe that profiling patients based on their immune systems can aid in predicting which immune modulating therapies will be most effective and in the future help in tailoring immune therapies specific to the patient. Based on our work we have confidence that immune monitoring it is key in unlocking complex mechanisms between the various components of the immune system that are critical to wound repair, healing and regenerative medicine as well as an essential tool for clinical trials.
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