  We introduce a novel data-driven framework for the design of targeted gene
panels for estimating exome-wide biomarkers in cancer immunotherapy. Our first
goal is to develop a generative model for the profile of mutation across the
exome, which allows for gene- and variant type-dependent mutation rates. Based
on this model, we then propose a new procedure for estimating biomarkers such
as tumour mutation burden and tumour indel nurden. Our approach allows the
practitioner to select a targeted gene panel of a prespecified size, and then
construct an estimator that only depends on the selected genes. Alternatively,
the practitioner may apply our method to make predictions based on an existing
gene panel, or to augment a gene panel to a given size. We demonstrate the
excellent performance of our proposal using data from three non-small cell lung
cancer studies, as well as data from six other cancer types.
