Related Experiment Video
Updated: Jan 1, 2026
Experimental Melanoma Immunotherapy Model Using Tumor Vaccination with a Hematopoietic Cytokine
Published on: February 24, 2023
Somatic Mutations and Neoepitope Homology in Melanomas Treated with CTLA-4 Blockade
Tavi Nathanson1, Arun Ahuja1, Alexander Rubinsteyn1
1Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York.
Abstract:
Immune checkpoint inhibitors are promising treatments for patients with a variety of malignancies. Toward understanding the determinants of response to immune checkpoint inhibitors, it was previously demonstrated that the presence of somatic mutations is associated with benefit from checkpoint inhibition. A hypothesis was posited that neoantigen homology to pathogens may in part explain the link between somatic mutations and response. To further examine this hypothesis, we reanalyzed cancer exome data obtained from our previously published study of 64 melanoma patients treated with CTLA-4 blockade and a new dataset of RNA-Seq data from 24 of these patients. We found that the ability to accurately predict patient benefit did not increase as the analysis narrowed from somatic mutation burden, to inclusion of only those mutations predicted to be MHC class I neoantigens, to only including those neoantigens that were expressed or that had homology to pathogens. The only association between somatic mutation burden and response was found when examining samples obtained prior to treatment. Neoantigen and expressed neoantigen burden were also associated with response, but neither was more predictive than somatic mutation burden. Neither the previously described tetrapeptide signature nor an updated method to evaluate neoepitope homology to pathogens was more predictive than mutation burden. Cancer Immunol Res; 5(1); 84-91. ©2016 AACR.
Insights
Somatic mutation burden, not neoantigen characteristics, best predicts response to immune checkpoint inhibitors in melanoma. Further analysis of neoantigen homology to pathogens did not improve prediction accuracy.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Immune checkpoint inhibitors (ICIs) offer significant promise for treating various cancers.
- Previous research indicated a correlation between somatic mutation burden and patient response to ICIs.
- A hypothesis suggested that neoantigen homology to pathogens might explain this association.
Purpose of the Study:
- To investigate whether neoantigen characteristics, including homology to pathogens, improve the prediction of patient response to CTLA-4 blockade.
- To re-evaluate the association between somatic mutation burden and treatment response using existing and new datasets.
Main Methods:
- Reanalysis of cancer exome data from 64 melanoma patients treated with CTLA-4 blockade.
- Inclusion of RNA-Seq data from 24 of these patients.
- Evaluation of prediction models based on somatic mutation burden, predicted MHC class I neoantigens, expressed neoantigens, and neoantigens with pathogen homology.
Main Results:
- Prediction of patient benefit did not improve by narrowing the analysis from somatic mutation burden to specific neoantigen types.
- Somatic mutation burden was associated with response only in pre-treatment samples.
- Neoantigen burden and expressed neoantigen burden were associated with response but not more predictive than overall somatic mutation burden.
- Neither a previously described tetrapeptide signature nor a novel method for evaluating neoepitope homology to pathogens enhanced predictive accuracy over mutation burden.
Conclusions:
- Somatic mutation burden remains a strong predictor of response to CTLA-4 blockade in melanoma.
- Neoantigen characteristics, including homology to pathogens, do not offer superior predictive value compared to overall somatic mutation burden.
- Further research may be needed to identify more refined biomarkers for ICI response.
Related Concept Videos
01:27Tumor Immunotherapy
02:57Targeted Cancer Therapies
There are several types of targeted therapies against...
02:50Combination Therapies and Personalized Medicine
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...