Uncovering Biomarkers for Resistance to Anti-PD-1 Treatment in Melanoma

July 13, 2022

Anti-PD-1 Treatment: The Good News

The blockbuster success of cancer immunotherapies targeting PD-1, a protein expressed by cancers to dampen the immune response, can be seen in the more than a dozen cancer types approved for this line of treatment. Recently, in a study of locally advanced rectal cancer, a new anti-PD-1 antibody produced the most convincing result to-date of tumor elimination in all 12 patients in the study.

Assessing PD-1-Based Treatment Resistance

Unfortunately, the majority of clinical trial results are not so remarkable. For every success story, there is a story of primary or secondary acquired resistance to anti-PD-1 therapies.

Primary resistance occurs when a tumor never fully responds to the treatment, and is extremely common in tumors that do not test positive for the most common PD-1 treatment biomarker, PD-L1. Perhaps more concerning, and more puzzling to researchers, is secondary resistance, where a tumor exhibits a strong initial response to the treatment and then stops responding.

Single Cell Analysis Uncovers Potential Biomarkers of Resistance

The mechanism(s) behind this treatment resistance are unknown, so researchers from Merck set out an observational study to identify potential biomarkers and pathways implicated in anti-PD-1 treatment resistance, specifically in melanoma.

One hundred and twenty four patients had pre-treatment samples collected, and patients with treatment-resistant tumors had post-treatment samples collected. After analysis using immunohistochemistry, whole exome sequencing and RNA sequencing, the researchers found that an 18-gene T cell inflammation-related biomarker they developed, called Tcell inf GEP, was increased in the resistant tumors during treatment.

At baseline, pre-treatment, tumors that were more responsive to treatment had higher levels of PD-L1 than tumors that ended up being resistant, perhaps as expected. Interestingly, however, PD-L1 expression went up during treatment in the resistant tumors as well. Although this study doesn’t produce a definitive answer as to the mechanism or exact pathway involved in resistance, it identifies potential biomarkers for further study, hopefully leading to a successful approach to better predict patient outcomes and inform treatment selection.

Outsourcing Bioinformatic Analyses

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Jane Cook, Journalist & Content Writer, Bridge Informatics

Jane is a Content Writer at Bridge Informatics, a professional services firm that helps biotech customers implement advanced techniques in management and analysis of genomic data. Bridge Informatics focuses on data mining, machine learning, and various bioinformatic techniques to discover biomarkers and companion diagnostics. If you’re interested in reaching out, please email daniel.dacey@old.bridgeinformatics.com or dan.ryder@old.bridgeinformatics.com.



illustration of cancer-fighting T cells

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