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. 2017 Jan;5(1):84-91.
doi: 10.1158/2326-6066.CIR-16-0019. Epub 2016 Dec 12.

Somatic Mutations and Neoepitope Homology in Melanomas Treated With CTLA-4 Blockade

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Free PMC article

Somatic Mutations and Neoepitope Homology in Melanomas Treated With CTLA-4 Blockade

Tavi Nathanson et al. Cancer Immunol Res. .
Free PMC article

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.

Conflict of interest statement

AS: Consulting, Neon

Figures

Figure 1
Figure 1. Mutation Burden and Ultraviolet Signature
A. Median and range of mutation burden and allele-specific expression of mutations in samples collected prior to treatment (for benefit versus no benefit, all (n = 34, Mann-Whitney, P = 0.0006), expressed (n = 9, P = 0.024)). In A and B, the first pair of bars represent mutation burden for all sequenced tumors; the second pair represent mutation burden in the subset of tumors for which RNA was available; the third represent the expressed mutations. In A-C, blue bars represent benefiting tumors; red bars represent nonbenefiting tumors. B. Median and range of mutation burden and expressed mutations in samples collected after treatment (for benefit versus no benefit, all (n = 30, Mann-Whitney, P = 0.19), expressed (n = 15, P = 0.46)). C. Correlation between signature of DNA damage from ultraviolet (UV) exposure and clinical response (*Mann-Whitney, P = 0.003). D. Correlation between UV signature and mutation count (Spearman rho=0.77, P = 4e-14).
Figure 2
Figure 2. Neoantigen Burden
A. Median and range of neoantigen burden and allele-specific expression of neoantigens in samples collected prior to treatment (for benefit versus no benefit, all (n = 34, Mann-Whitney, P = 0.002), expressed (n = 9, P = 0.003)). B. Median and range of neoantigen burden and expressed neoantigens in samples collected after the initiation of treatment (for benefit versus no benefit, all (n = 30, Mann-Whitney, P = 0.49), expressed (n = 15, P = 0.46)). In A and B, blue bars represent benefiting tumors; red bars represent nonbenefiting tumors. The first pair of bars represent predicted neoantigens for all sequenced tumors; the second pair represent predicted neoantigens in the subset of tumors for which RNA was available; the third represent the expressed neoantigens.
Figure 3
Figure 3. Comparison of Neoepitopes
A. Flow chart illustrating the process for tumor-to-pathogen neoepitope comparison by Topeology. B. An example comparison of the CPDKSTSTL neoepitope (tumor ID 0095) and its wild-type peptide to the LPFEKSTVM Influenza A epitope from IEDB. In this case, the neoepitope results in a higher score (0.58) than the wild-type peptide (0.42). Only bold amino acids are considered for alignment. Amino acids labeled black do not impact the final Smith-Waterman alignment score for this comparison. Amino acids labeled green are equivalent in both sequences while amino acids labeled orange are not. C. Averaged tumor-to-pathogen similarity scores were highly correlated with the log of mutation burden (Pearson r = 0.97, P = 6.3 x 10−21).

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