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Prediction and prioritization of neoantigens: integration of RNA sequencing data with whole-exome sequencing.
- Source :
-
Cancer science [Cancer Sci] 2017 Feb; Vol. 108 (2), pp. 170-177. Date of Electronic Publication: 2017 Feb 09. - Publication Year :
- 2017
-
Abstract
- The importance of neoantigens for cancer immunity is now well-acknowledged. However, there are diverse strategies for predicting and prioritizing candidate neoantigens, and thus reported neoantigen loads vary a great deal. To clarify this issue, we compared the numbers of neoantigen candidates predicted by four currently utilized strategies. Whole-exome sequencing and RNA sequencing (RNA-Seq) of four non-small-cell lung cancer patients was carried out. We identified 361 somatic missense mutations from which 224 candidate neoantigens were predicted using MHC class I binding affinity prediction software (strategy I). Of these, 207 exceeded the set threshold of gene expression (fragments per kilobase of transcript per million fragments mapped ≥1), resulting in 124 candidate neoantigens (strategy II). To verify mutant mRNA expression, sequencing of amplicons from tumor cDNA including each mutation was undertaken; 204 of the 207 mutations were successfully sequenced, yielding 121 mutant mRNA sequences, resulting in 75 candidate neoantigens (strategy III). Sequence information was extracted from RNA-Seq to confirm the presence of mutated mRNA. Variant allele frequencies ≥0.04 in RNA-Seq were found for 117 of the 207 mutations and regarded as expressed in the tumor, and finally, 72 candidate neoantigens were predicted (strategy IV). Without additional amplicon sequencing of cDNA, strategy IV was comparable to strategy III. We therefore propose strategy IV as a practical and appropriate strategy to predict candidate neoantigens fully utilizing currently available information. It is of note that different neoantigen loads were deduced from the same tumors depending on the strategies applied.<br /> (© 2016 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.)
- Subjects :
- Adenocarcinoma
Adult
Aged
Algorithms
Antigens, Neoplasm analysis
Carcinoma, Non-Small-Cell Lung immunology
DNA, Complementary
Gene Expression
High-Throughput Nucleotide Sequencing methods
Humans
Lung Neoplasms immunology
Male
Microarray Analysis methods
RNA, Messenger genetics
T-Lymphocytes, Cytotoxic immunology
Antigens, Neoplasm genetics
Carcinoma, Non-Small-Cell Lung genetics
Exome
Histocompatibility Antigens Class I genetics
Lung Neoplasms genetics
Mutation, Missense
Sequence Analysis, RNA methods
Subjects
Details
- Language :
- English
- ISSN :
- 1349-7006
- Volume :
- 108
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Cancer science
- Publication Type :
- Academic Journal
- Accession number :
- 27960040
- Full Text :
- https://doi.org/10.1111/cas.13131