Immunotherapy is currently transforming cancer treatment. Notably, immune checkpoint blockers (ICB) have shown unprecedented therapeutic successes in numerous tumor types, including cancers that were traditionally considered as non-immunogenic. However, a significant proportion of patients do not respond to these therapies. Thus, early selection of the most sensitive patients is key, and the development of predictive companion biomarkers constitutes one of the biggest challenges of ICB development. Recent publications have suggested that the tumor genomic landscape, mutational load, and tumor-specific neoantigens, are potential determinants of the response to ICB and can influence patients' outcome upon immunotherapy. Further, defects in the DNA repair machinery have consistently been associated with improved survival and durable clinical benefit from ICB. Thus, closely reflecting the DNA damage repair capacity of tumor cells and their intrinsic genomic instability, the mutational load and its associated tumor-specific neoantigens appear as key predictive paths to anticipate potential clinical benefits of ICB. In the era of next generation sequencing, while more and more patients are getting the full molecular portrait of their tumor, it is crucial to optimally exploit sequencing data for the benefit of patients. Therefore, sequencing technologies, analyses tools and relevant criteria for mutational load and neoantigens prediction should be homogenized and combined in more integrative pipelines, to fully optimize the measurement of such parameters, so that these biomarkers can ultimately reach the analytical validity and reproducibility required for a clinical implementation.
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