Tumour neoantigen identification software tools | Whole-genome sequencing data analysis
Cancer immunotherapy has gained significant momentum from recent clinical successes of checkpoint blockade inhibition. Massively parallel sequence analysis suggests a connection between mutational load and response to this class of therapy. Methods to identify which tumor-specific mutant peptides (neoantigens) can elicit anti-tumor T cell immunity are needed to improve predictions of checkpoint therapy response and to identify targets for vaccines and adoptive T cell therapies.
Assesses genome editing of a target locus by CRISPR-Cas9. TIDE quantifies the editing efficacy and simultaneously identifies the predominant types of insertions and deletions (indels) in the targeted pool of cells. The software requires only two standard polymerase chain reactions (PCRs) and two capillary sequencing runs. TIDE can assist in the testing and rational design of genome editing strategies. It is suitable for non-templated Cas9 editing.
A flexible, streamlined computational workflow for identification of personalized Variant Antigens by Cancer Sequencing (pVAC-Seq) that integrates tumor mutation and expression data (DNA- and RNA-Seq). This approach should help to evaluate tumor-specific neoepitopes in a much-reduced time, thereby increasing its applicability for clinical use.
Identifies tumor-specifc peptides and assess their potential to be neo-epitopes. MuPeXI is based on priority score intended to rank peptides according to likelihood of eliciting a T cell response. It returns tumor-specific peptides derived from nucleotide substitutions, insertions, and deletions, enriched with comprehensive annotation, including HLA binding and similarity to normal peptides. The tool allows the user to select the most likely immunogenic peptides.
Provides a cloud based analysis pipeline for tumor neoantigen detection. CloudNeo uses Docker containers to execute the tasks in workflow. It allows users to realize advantages of cloud analysis, including massive computing scalability and access to large datasets on the Cancer Genomics Cloud such as The Cancer Genome Atlas (TCGA), as these can be reached without downloading to a local server.
A neoantigen discovery pipeline to identify gene fusions in prostate cancers that may produce neoantigens. INTEGRATE-Neo, is comprised of the following steps: (i) gene fusion peptide prediction, (ii) HLA allele prediction, and (iii) gene fusion neoantigen discovery. To ensure user=friendliness, all of the modules within INTEGRATE-Neo are designed as standalone tools with their own optional parameters. Authors apply INTEGRATE-Neo to the TCGA prostate cohort data to demonstrate its utility for identifying gene fusion neoantigens that may serve as personalized cancer immunotherapy targets.
Supports the identification of therapeutically actionable genomic alterations in tumors. CGI (i) identifies validated oncogenic alterations in a tumor, (ii) predicts the effect of the remaining alterations of uncertain significance, (iii) reports the known influence of these variants on drug response according to the level of clinical evidence supporting it and (iv) lists the interactions of existing chemical compounds with genes bearing driver alterations.
Identifies cancer somatic mutations following the best practices of the genome analysis toolkit (GATK) from the genome/exome sequencing data of tumor-normal pairs. TSNAD is an integrated software that provides potential neoantigens which can be either extracellular mutations of membrane proteins or mutant peptides presented by class I major histocompatibility complex (MHC) molecules. It also offers a pipeline for mutation calling from sequencing data.