Tumor mutation burden (TMB) is the number of somatic mutations in the coding region of the tumor genome. It is an emerging biomarker that is related to the response to immunotherapeutics. Recent studies have shown that a high tumor mutation burden or burden increases the likelihood that immunogenic neoantigens expressed by tumor cells may induce a response to immunotherapy.
Next-generation sequencing (NGS) can help researchers estimate TMB, identify new antigens, study innovative therapies to enhance the immune response, and understand how genetic variation affects its efficacy. The characterization of expressed neoantigens will also facilitate the development of vaccines and cell-based therapies.
Method display
Estimated tumor mutation burden
Despite defining the clinical use of the tumor mutation burden, efforts are continuing to standardize TMB analysis.
New antigen identification
Mutations in the protein-coding genes of cancer cells are a source of potential new antigens that the immune system can target. NGS can predictively select novel tumor antigens that can be used to elicit tumor-specific responses. DNA and / or RNA can be effectively characterized by exome sequencing and / or transcriptome sequencing.
Creative Proteomics leads a rich team that uses the most rigorous experimental solutions and internationally recognized experimental techniques for Tumor mutations and neoantigens Solutions to obtain your customized information. Use the most accurate experimental results to help you better carry out tumor-related scientific research.
Our advantage
Mature and reliable Tumor mutations and neoantigens Solutions platform: rich project experience, participate in major projects, and publish high-level cooperation results.
The analysis contents and methods based on high-quality data analysis, pre-research and verification are indeed mature and feasible.
References
1. Rizvi NA, Hellmann MD, Snyder A, et al. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015.
2. Snyder A, Makarov V, Merghoub T, et al. Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma. N Engl J Med. 2014.
3. Garofalo A, Sholl L, Reardon B, et al. The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine. Genome Med. 2016.
4. Buchhalter I, Rempel E, Endris V, et al. Size Matters: Dissecting Key Parameters for Panel-Based Tumor Mutational Burden (TMB) Analysis. Int J Cancer. 2018.
* For Research Use Only. Not for use in the treatment or diagnosis of disease.
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