Abstract
SUMMARY: Insertion and deletion (indels) have been recognized as an important source generating tumor-specific mutant peptides (neoantigens). The focus of indel-derived neoantigen identification has been on leveraging DNA sequencing such as whole exome sequencing, with the effort of using RNA-seq less well explored. Here we present ScanNeo, a fast-streamlined computational pipeline for analyzing RNA-seq to predict neoepitopes derived from small to large-sized indels. We applied ScanNeo in a prostate cancer cell line and validated our predictions with matched mass spectrometry data. Finally, we demonstrated that indel neoantigens predicted from RNA-seq were associated with checkpoint inhibitor response in a cohort of melanoma patients.
AVAILABILITY AND IMPLEMENTATION: ScanNeo is implemented in Python. It is freely accessible at the GitHub repository (https://github.com/ylab-hi/ScanNeo).
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 4159-4161 |
| Number of pages | 3 |
| Journal | Bioinformatics |
| Volume | 35 |
| Issue number | 20 |
| DOIs | |
| State | Published - Oct 15 2019 |
Bibliographical note
Funding Information:This work was supported by Young Investigator Award from the Prostate Cancer Foundation and Research Starter Grant from PhRMA foundation.
Publisher Copyright:
© 2019 The Author(s) 2019. Published by Oxford University Press. All rights reserved.
PubMed: MeSH publication types
- Journal Article
