In:
Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 28, No. 24 ( 2022-12-15), p. 5368-5382
Abstract:
The low mutational load of some cancers is considered one reason for the difficulty to develop effective tumor vaccines. To overcome this problem, we developed a strategy to design neopeptides through single amino acid mutations to enhance their immunogenicity. Experimental Design: Exome and RNA sequencing as well as in silico HLA-binding predictions to autologous HLA molecules were used to identify candidate neopeptides. Subsequently, in silico HLA-anchor placements were used to deduce putative T-cell receptor (TCR) contacts of peptides. Single amino acids of TCR contacting residues were then mutated by amino acid replacements. Overall, 175 peptides were synthesized and sets of 25 each containing both peptides designed to bind to HLA class I and II molecules applied in the vaccination. Upon development of a tumor recurrence, the tumor-infiltrating lymphocytes (TIL) were characterized in detail both at the bulk and clonal level. Results: The immune response of peripheral blood T cells to vaccine peptides, including natural peptides and designed neopeptides, gradually increased with repetitive vaccination, but remained low. In contrast, at the time of tumor recurrence, CD8+ TILs and CD4+ TILs responded to 45% and 100%, respectively, of the vaccine peptides. Furthermore, TIL-derived CD4+ T-cell clones showed strong responses and tumor cell lysis not only against the designed neopeptide but also against the unmutated natural peptides of the tumor. Conclusions: Turning tumor self-peptides into foreign antigens by introduction of designed mutations is a promising strategy to induce strong intratumoral CD4+ T-cell responses in a cold tumor like glioblastoma.
Type of Medium:
Online Resource
ISSN:
1078-0432
,
1557-3265
DOI:
10.1158/1078-0432.CCR-22-1741
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2022
detail.hit.zdb_id:
1225457-5
detail.hit.zdb_id:
2036787-9
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