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Updated: Dec 14, 2025

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
Published on: June 24, 2021
ASNEO: Identification of personalized alternative splicing based neoantigens with RNA-seq
Zhanbing Zhang1, Chi Zhou1, Lihua Tang2
1Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital; Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai 200009, China.
Abstract:
Cancer neoantigens have shown great potential in immunotherapy, while current software focuses on identifying neoantigens which are derived from SNVs, indels or gene fusions. Alternative splicing widely occurs in tumor samples and it has been proven to contribute to the generation of candidate neoantigens. Here we present ASNEO, which is an integrated computational pipeline for the identification of personalized Alternative Splicing based NEOantigens with RNA-seq. Our analyses showed that ASNEO could identify neopeptides which are presented by MHC I complex through mass spectrometry data validation. When ASNEO was applied to two immunotherapy-treated cohorts, we found that alternative splicing based neopeptides generally have a higher immune score than that of somatic neopeptides and alternative splicing based neopeptides could be a marker to predict patient survival pattern. Our identification of alternative splicing derived neopeptides would contribute to a more complete understanding of the tumor immune landscape. Prediction of patient-specific alternative splicing neopeptides has the potential to contribute to the development of personalized cancer vaccines.
Insights
This study introduces ASNEO, a tool identifying cancer neoantigens from alternative splicing events using RNA-seq. These novel neoantigens show higher immune scores and can predict patient survival, advancing personalized cancer vaccines.
Area of Science:
- Oncology
- Immunology
- Bioinformatics
Background:
- Cancer neoantigens are crucial for immunotherapy.
- Current methods primarily identify neoantigens from SNVs, indels, or gene fusions.
- Alternative splicing is prevalent in tumors and generates neoantigens.
Purpose of the Study:
- To present ASNEO, a computational pipeline for identifying personalized alternative splicing-based neoantigens (ASNEOs) from RNA-seq data.
- To validate ASNEO's capability in identifying MHC I-presented neopeptides.
- To explore the clinical relevance of ASNEOs in cancer immunotherapy.
Main Methods:
- Development of the ASNEO pipeline for alternative splicing neoantigen identification.
- Validation using mass spectrometry data for MHC I presentation.
- Application of ASNEO to immunotherapy-treated patient cohorts.
Main Results:
- ASNEO successfully identified neopeptides presented by MHC I.
- Alternative splicing-based neopeptides exhibited higher immune scores compared to somatic neoantigens.
- ASNEOs demonstrated potential as biomarkers for predicting patient survival.
Conclusions:
- ASNEO enhances the understanding of the tumor immune landscape by including alternative splicing-derived neoantigens.
- ASNEOs represent a promising avenue for developing personalized cancer vaccines.
- The identification of ASNEOs contributes to more comprehensive neoantigen discovery for cancer immunotherapy.
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