Impact of high tumor mutational burden in solid tumors and challenges for biomarker application. (September 2020) - McNamara, Mairéad G.; Jacobs, Timothy; Lamarca, Angela; Hubner, Richard A; Valle, Juan W; Amir, Eitan
Highlights: Detection of patients with cancer likely to respond to immunotherapy is crucial. Tumor mutational burden (TMB) is an emerging prognostic and predictive biomarker. Next generation sequencing provides TMB estimates in a more effective manner. There are challenges to TMB adoption into standard clinical practice. Validation of TMB alone or in combination models in prospective trials is warranted. Abstract: Accurate identification of patients with solid tumors likely to respond to immunotherapy is crucial. Tumor mutational burden (TMB) measures the number of somatic mutations in a tumor and is an emerging prognostic and predictive biomarker for anti-programmed cell death (PD) 1/anti-PD-ligand 1 therapy and other immunotherapeutic agents. Tumor mutational burden is assessed optimally by whole exome sequencing, but next generation sequencing provides TMB estimates in a more timely and cost-effective manner. Blood-based measurement of TMB in plasma offers an alternative to the need for adequate tumor tissue for molecular testing, and has demonstrated the ability to identify patients who derive benefit from immunotherapy. Tumor mutational burden has diverse prognostic impact in different solid tumor types and also has a demonstrated role in predicting improved survival in patients receiving immunotherapy. There are challenges to TMB adoption into standard clinical practice, including variations in its definition, with the mutational number defining TMB-high appearing to vary across cancer types. The magnitude of TMB also varies across different tumor types, with the highest levels reported in melanoma and other skin cancers (where ultraviolet light is the dominant mutational process), followed by non-small cell lung cancer and other squamous carcinomas. Concerns regarding inter-laboratory and inter-platform variations in analysis methods have been raised, highlighting the need for standardization. Integration of other genomic or pathological biomarkers with TMB may increase its prognostic and predictive capabilities and validation of individual or combination models in prospective trials is warranted.