Predict Responses to Immune Checkpoint Inhibitors and
Improve Patient Stratification through MDSC Monitoring

Insight into the
cellular response to your immune checkpoint inhibitor

The treatment of cancer has been revolutionized by the development of immunotherapies including PD-1/PD-L1 inhibitors and other checkpoint blockades. However, response rates have been variable and better response rates were seen in patients with lower levels of MDSC (Liu Y et al. Cancer Immunol Immunother 2018;67:1181-95). Patients with elevated MDSC may benefit from supplemental drugs and many combination therapies are currently in clinical development. Some of these combinations are thought to work by inhibiting MDSC and thereby creating a permissive environment for activated T cells.

MDSC measurement: exploratory biomarker, potential pharmacodynamic biomarker and patient stratification CLIA-certified assay

Accelerate your drug development with the right assay and data analysis approach

Flow cytometry provides an unrivalled view of the cellular immune response to cancer, measuring key peripheral immune cells. Caprion’s MDSC assays can improve prediction of immune response to immune checkpoint inhibitors and are available as exploratory and CLIA-certified assays.

  • Cyto-Chex® BCT for whole blood collection to improve sample integrity and ensure optimal MDSC measurement
  • Flow panels designed specifically to measure the frequency of blood monocytic and/or granulocytic MDSC
  • Absolute cell counts can be reported through the use of
    BioLegend® Precision Count BeadsTM
  • Option to use the CLIA-certified panel or the exploratory panel with up to 18 markers
  • icScoreTM – A proprietary algorithm licensed from Memorial Sloan Kettering Cancer Center, to support non-biased reliable gating for HLA-DR

Our MDSC assays were featured in peer-reviewed scientific publications

  • Wan D et al. Sequential depletion of myeloid-derived suppressor cells and tumor cells with a dual-pH-sensitive conjugated micelle system for cancer chemoimmunotherapy. J Control Release 2020;317:43-56. Full text
  • Callahan MK et al. Nivolumab plus ipilimumab in patients with advanced melanoma: updated survival, response, and safety data in a phase I dose-escalation study. J Clin Oncol 2018;36(4):391-398. Full text
  • De Henau O et al. Overcoming resistance to checkpoint blockade therapy by targeting PI3Kγ in myeloid cells. Nature 2016;539:443-447. Full text
  • Kitano S et al. Computational algorithm-driven evaluation of monocytic myeloid-derived suppressor cell frequency for prediction of clinical outcomes. Cancer Immunol Res 2014;2(8):812–21. Full text
  • Wolchok JD et al. Nivolumab plus ipilimumab in advanced melanoma. NEJM 2013;369(2):122-33. Full text