MDSC Assays: Predicting Immunotherapy Responses to Enhance Patient Stratification

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 Myeloid-Derived Suppressor Cells (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.

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

Flow cytometry provides an unrivaled view of the cellular immune response to cancer, measuring key peripheral immune cells.

CellCarta’s MDSC assays can improve prediction of immune response to immune checkpoint inhibitors.

  • 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
  • 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. Check 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. Check full text
  • De Henau O et al. Overcoming resistance to checkpoint blockade therapy by targeting PI3Kγ in myeloid cells. Nature 2016;539:443-447. Check 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. Check full text
  • Wolchok JD et al. Nivolumab plus ipilimumab in advanced melanoma. NEJM 2013;369(2):122-33. Check full text