Illustration of white blood cells attacking a cancer cell
Illustration of white blood cells attacking a cancer cell.
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Checkpoint and Combination Therapy Overview

Checkpoint immunotherapy development continues to grow at an incredible rate—as of 2018 there were more than 2250 clinical immunotherapy trials incorporating checkpoint therapy, with two of the three largest selling oncology drugs being checkpoint-based immunotherapies.

As this field becomes even more cutting-edge, immuno-oncology trials have become much more complex, combining inhibitors with a variety of small molecules, agonists, vaccines, and multiple checkpoint therapies. The development of these immunotherapies is even more challenging due to the lead discovery, bioprocess optimization, and biomarker development processes, and the functional interactions stemming from the patient immune cells.

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Challenges in the Field

This presents both a competitive atmosphere for deciding which mono and combination therapies will be of highest utility in various indications, and also a complex environment for understanding how these therapies can be used in a precise manner, both mechanistically and biomarker-wise, for the right patient at the right time.

In some cases, patients chosen for this type of therapy only have one opportunity to be treated with an immunotherapy, due to their compromised or low-functioning immune system, so being able to predict response, identify which patients are likely to benefit most, as well as minimize the potential for adverse effects, is likely to change the way these cell products are developed and produced.

Figure 1. Adapted from the cancer immunity cycle.† 

†Chen DS and Mellman I. Oncology meets immunology: the cancer immunity cycle. Journal of Immunity 2013; 39:1-10.

Predicting Response

IsoPlexis has begun to help unravel these questions in complex checkpoint and combination immunotherapies over the last few years. Previous methods, such as histology or serum cytokine measurements, are only estimating function and have had limited correlations to clinical outcome. IsoPlexis’ polyfunctional strength uniquely correlated with response in several studies.1-2 IsoPlexis’ systems have the unique ability to detect these highly functional cells (Figure 1), which are missed on bulk ELISA, flow cytometry, and RNA sequencing-based platforms. PSI as a biomarker outperformed other measured metrics.


Researchers have now used the IsoCode technology for profiling T cell function from the tumor, bone marrow, and blood of a variety of patients in a number of published and public trials. The results have demonstrated how IsoPlexis’ new resolution into the cytokine signatures from single cells point to a novel ability to stratify complex patient responses in combination checkpoint therapy and offer a glimpse into the future of understanding mechanism and personalized medicine in these complex immunotherapies.

  1. Mackay S, et al. Single-cell PSI of CD8+ TILs in melanoma shows uniquely sensitive correlates with response to anti-PD-1/CTLA4 therapy, where histology and serum cytokines were unable to detect significant associations. Presented at SITC 2018.
  2. Lim Z-F, et al. Translational Single Cell Proteomics Profiling of Live T-Lymphocytes in Oncogene-Addictive NSCLC under Immune Checkpoint Inhibitor (CPI) Treatment. Presented at TRCCC 2019.
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