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Updated: Mar 16, 2026
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Tumor immune profiling predicts response to anti-PD-1 therapy in human melanoma
Background:
Immune checkpoint blockade is revolutionizing therapy for advanced cancer, but many patients do not respond to treatment. The identification of robust biomarkers that predict clinical response to specific checkpoint inhibitors is critical in order to stratify patients and to rationally select combinations in the context of an expanding array of therapeutic options.
Methods:
We performed multiparameter flow cytometry on freshly isolated metastatic melanoma samples from 2 cohorts of 20 patients each prior to treatment and correlated the subsequent clinical response with the tumor immune phenotype.
Results:
Increasing fractions of programmed cell death 1 high/cytotoxic T lymphocyte-associated protein 4 high (PD-1hiCTLA-4hi) cells within the tumor-infiltrating CD8+ T cell subset strongly correlated with response to therapy (RR) and progression-free survival (PFS). Functional analysis of these cells revealed a partially exhausted T cell phenotype. Assessment of metastatic lesions during anti-PD-1 therapy demonstrated a release of T cell exhaustion, as measured by an accumulation of highly activated CD8+ T cells within tumors, with no effect on Tregs.
Conclusions:
Our data suggest that the relative abundance of partially exhausted tumor-infiltrating CD8+ T cells predicts response to anti-PD-1 therapy. This information can be used to appropriately select patients with a high likelihood of achieving a clinical response to PD-1 pathway inhibition.
Funding:
This work was funded by a generous gift provided by Inga-Lill and David Amoroso as well as a generous gift provided by Stephen Juelsgaard and Lori Cook.
Insights
Partially exhausted CD8+ T cells in tumors predict response to PD-1 blockade therapy. Identifying these cells helps select cancer patients likely to benefit from this immunotherapy.
Area of Science:
- Oncology
- Immunology
- Biomarker Discovery
Background:
- Immune checkpoint inhibitors (ICIs) offer new cancer treatment avenues.
- Many patients lack response to current ICI therapies.
- Biomarker identification is crucial for patient stratification and combination therapy selection.
Purpose of the Study:
- To identify predictive biomarkers for response to immune checkpoint blockade therapy.
- To correlate tumor immune phenotype with clinical outcomes in metastatic melanoma patients.
Main Methods:
- Multiparameter flow cytometry was used on 40 metastatic melanoma patient samples.
- Tumor immune phenotypes were analyzed before treatment.
- Clinical response and progression-free survival were correlated with immune cell fractions.
Main Results:
- A higher fraction of PD-1hiCTLA-4hi CD8+ T cells correlated with therapy response and PFS.
- These T cells exhibited a partially exhausted phenotype.
- Anti-PD-1 therapy increased activated CD8+ T cells, indicating reduced T cell exhaustion, without affecting Tregs.
Conclusions:
- The abundance of partially exhausted tumor-infiltrating CD8+ T cells predicts response to anti-PD-1 therapy.
- This finding aids in selecting patients likely to respond to PD-1 pathway inhibition.
