Tumor mutational burden (TMB), the number of somatic mutations within the coding region of a tumor genome, is an emerging biomarker that correlates with response to immunotherapeutic agents such as checkpoint inhibitors.1-4. Recent studies indicate that a high tumor mutational burden, or load, increases the likelihood that immunogenic neoantigens expressed by tumor cells may induce a response to immunotherapy.1-4
Next-generation sequencing (NGS) can help researchers estimate TMB, identify neoantigens, study innovative therapies to boost the immune response, and understand how genetic variation can influence their efficacy. Characterization of expressed neoantigens has also contributed to development of vaccines and cell-based therapeutic methods.
While the clinical utility of tumor mutational burden is being defined, continuing efforts to standardize TMB analysis are ongoing.
Recent studies have demonstrated that tumor mutational burden can be effectively estimated using targeted sequencing panels.5-6 Specific features are recommended to enhance accuracy in TMB scoring, such as a minimum size of 1.5 Mb genomic content, and algorithms to filter variants that are unlikely to contribute to immunogenicity. 5-6
Mutations in protein coding genes of cancer cells are a source of potential neoantigens that the immune system can target. NGS has enabled the predictive selection of novel tumor antigens that can be applied to elicit a tumor-specific response.
DNA and/or RNA is efficiently characterized by exome sequencing and/or transcriptome sequencing. Improved bioinformatics tools aid neoantigen selection by predicting the presentation of mutant peptides for recognition by the immune system.
A study by Dr. Albrecht Stenzinger and his colleagues investigated the influence of gene panel size on the precision of tumor mutational burden measurement.Read Article
Learn why Professor Jo Vandesompele, PhD says RNA editing could be valuable in assessing tumor mutational burden and identifying neoantigens through gene expression.Read Interview
Illumina offers several library preparation and sequencing options with access to data analysis options for tumor mutational load and neoantigen identification. Streamlined workflows and flexible kit configurations accommodate multiple study designs.
Approximately 90% of the world’s sequencing data are generated using Illumina sequencing by synthesis (SBS) chemistry.*
Click on the below to view products for each workflow step.
Assay targeting multiple variant types, including tumor mutational burden and microsatellite instability, even from low-quality samples.TruSeq DNA Exome
A cost-effective library preparation and exome enrichment solution.
A low-cost solution for analyzing human RNA isolated from limited or low-quality samples, including FFPE.TruSeq Stranded Total RNA Library Prep Kit
A robust, highly scalable whole-transcriptome analysis solution for a variety of species and sample types, including FFPE.
Flexible configurations that support up to 12 exomes per run.
Flexibility and scalable throughput for virtually any genome, sequencing method, and scale of project.
Explore user-friendly data analysis apps for RNA-Seq and other common methods.
This app rapidly aligns samples using Isaac and performs indel, SNV, CNV, and SV analysis and annotation.
This NGS approach consolidates hundreds of cancer-related biomarkers, including tumor mutational burden as well as single nucleotide variants, gene fusions, copy number variants, and other variant types, into a single assay.
*Data calculations on file, Illumina, Inc, 2017.