Identification of Immunotherapy Toxicity Biomarkers Using a Human Proteome Microarray

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Purified human proteins arrayed on PATH microarray slides are used for serum autoantibody profiling of melanoma patients treated with checkpoint inhibitors

Immunotherapy was developed to overcome immune response evasion by neoplastic cells. First applied to the treatment of melanoma, it is being increasingly adopted in the therapeutic protocol of different types of cancers. One of the strategies employed to recruit the immune system in the fight against cancer is to target immune checkpoints. These proteins exert a controlling action on the immune response preventing healthy cells from being damaged. The inhibition of checkpoint proteins enhances the anti-tumor immune response, thus cancer cells can be recognized and attacked. However, immunotherapy is not without side effects. A significant number of patients, in fact, experience severe adverse effects that lead to therapy termination. Although efforts have been made to gain a better understanding of the adverse response mechanism, no definitive conclusions have so far emerged. The aim of this study is to identify biomarkers predictive of immunotherapy toxicity for Anti-CTLA-4 and anti-PD-1, the most common checkpoint inhibitors used in melanoma treatment.

Introduction

The authors of this study hypothesized that there may be a link between an increased basal level of autoimmune serum antibodies and a severe adverse reaction to checkpoint inhibitors. To test this hypothesis a differential expression analysis was conducted.  A human proteome array (HuProt™ Human Proteome Microarray, CDI laboratories) featuring 19000 unique individually purified full-length human proteins printed on PATH® microarray slides, was interrogated with pre-treatment serum of stage IV metastatic melanoma patients.

Analysis of differential levels of serum antibodies

Patient samples were grouped based on immunotherapy toxicity outcome into severe, mild and no toxicity subgroups for each of the treatment protocols: Anti-CTLA-4 (39 samples), anti-PD-1 (28 samples), or the combination therapy (11 samples). IgG autoantibody profiles were compared between the patients’ subgroups. The analysis identified:

  • 914 differentially expressed (DE) antibodies associated with severe toxicity anti-CTLA-5-5,
  • 723 with anti-PD-1 toxicity,
  • 1161 associated with combination therapy adverse reaction.

Very little overlapping was observed for differentially expressed antibodies between different treatment protocols. The highest number of differentially expressed antibodies was observed for the combination therapy. To gain insight into the possible correlation between DE antibodies and a severe toxicity outcome statistically validated differentially expressed antibodies were subjected to pathway analysis. The results showed that proteins associated with immunity, autoimmunity, and apoptosis were being targeted by the immune systems of patients that showed a severe reaction to checkpoint inhibitors treatment.

Conclusions

The human Proteome microarray allows reproducible and sensitive profiling of serum autoantibodies, thus making it a suitable tool for the identification of a baseline antibody signature predictive of Immunotherapy toxicity. Although a larger sample size and a parallel assessment of genomic, proteomic and immunological profile are necessary to identify the mechanism of the adverse reactions the data presented corroborate the initial hypothesis that autoantibody profiling could be a useful indicator of patients susceptibility to checkpoint inhibitors.

For more information:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5880088/