Cancer neoantigens are a class of HLA-bound peptides that originate from tumor-specific mutations. Although vaccination against such antigens has long been thought to be a potentially effective and safe form of cancer treatment, precise identification of patient-specific cancer neoantigens has only become possible with the availability of advanced NGS technologies and other tools. Recently, exciting progresses have been made in the clinical development of highly personalized cancer vaccines (Ott et al., Nature, 2017; Sahin et al., Nature, 2017).
NovoNeoantigen™ is a robust bioinformatics pipeline developed by Novogene for the precise identification of cancer neoantigens with whole exome sequencing (WES) and whole transcriptome sequencing data from paired tumor-normal samples.
Sequencing Strategy, Data Quality Guarantee, and FFPE Sample Requirements
- Within 27 working days from sample receipt in our laboratory to data delivery
- Standard analysis:
- Data Filtering
- Alignment to reference genome (Software used: BWA for WES and HISAT2 for FFPE RNA-Seq
- Somatic variant calling (Software used: Samtools, VarScan, SomaticSniper)
- VEP peptide annotation
- Gene expression profiling
- Somatic missense mutation variants filter (Tumor MAF ≥ 30%, FPKM ≥ 1)
- HLA class I typing prediction (Software used: HLAminer)
- Neoantigen prediction
- Customized analysis:
- Please contact Novogene technical support for further information on customized bioinformatics analysis
NovoNeoantigen Sequencing Data
NovoNeoantigen has been validated with a public dataset of four tumor cell lines and an autologous lymphoblastoid cell line as the germline control (Schrörs et al., Oncotarget, 2017).
There were 4 neoantigens identified in the paper as the following:
With the same set of raw data, NovoNeoantigen generated the following results: