Back to Search
Start Over
Identification and Ranking of Recurrent Neo-Epitopes in Cancer
- Source :
- BMC Medical Genomics, BMC Medical Genomics, Vol 12, Iss 1, Pp 1-14 (2019)
- Publication Year :
- 2018
- Publisher :
- Cold Spring Harbor Laboratory, 2018.
-
Abstract
- Immune escape is one of the hallmarks of cancer and several new treatment approaches attempt to modulate and restore the immune system’s capability to target cancer cells. At the heart of the immune recognition process lies antigen presentation from somatic mutations. These neo-epitopes are emerging as attractive targets for cancer immunotherapy and new strategies for rapid identification of relevant candidates have become a priority. We carefully screen TCGA data sets for recurrent somatic amino acid exchanges and apply MHC class I binding predictions. We propose a method for in silico selection and prioritization of candidates which have a high potential for neo-antigen generation and are likely to appear in multiple patients. While the percentage of patients carrying a specific neo-epitope and HLA-type combination is relatively small, the sheer number of new patients leads to surprisingly high reoccurence numbers. We identify 769 epitopes which are expected to occur in 77629 patients per year. While our candidate list will definitely contain false positives, the results provide an objective order for wet-lab testing of reusable neo-epitopes. Thus recurrent neo-epitopes may be suitable to supplement existing personalized T cell treatment approaches with precision treatment options.
- Subjects :
- lcsh:Internal medicine
Cancer Research
Neo-epitope
lcsh:QH426-470
Databases, Factual
Computer science
Somatic cell
In silico
T cell
medicine.medical_treatment
Genes, MHC Class I
Genomics
Computational biology
Epitope
Epitopes
Mice
Cancer immunotherapy
Neo-antigen
Neoplasms
MHC class I
medicine
Cytotoxic T cell
Animals
Humans
lcsh:RC31-1245
Alleles
Precision treatment
Cancer
chemistry.chemical_classification
biology
Computational Biology
medicine.disease
Amino acid
lcsh:Genetics
medicine.anatomical_structure
chemistry
Cardiovascular and Metabolic Diseases
biology.protein
Immunotherapy
Technology Platforms
Research Article
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- BMC Medical Genomics, BMC Medical Genomics, Vol 12, Iss 1, Pp 1-14 (2019)
- Accession number :
- edsair.doi.dedup.....7e6f9d468f0c3c6af76a1987db580945
- Full Text :
- https://doi.org/10.1101/389437