Patterns of somatic alterations between matched primary and metastatic colorectal tumors characterized by whole-genome sequencing

The role of individual inheritance in tumor progression and metastasis

Metastasis, the dissemination and growth of tumor cells at secondary sites, is the primary cause of patient mortality from solid tumors. Metastasis is an extremely complex, inefficient process requiring contributions of not only the tumor cell but also local and distant environmental factors, at both the cellular and molecular level. Variation in the function of any of the steps in the metastatic cascade may therefore have profound implications for the ultimate course of the disease. In addition to the somatic and cellular heterogeneity that can affect cancer outcome, an individual's specific ancestry or genetic background can also significantly influence metastatic progression. These inherited variants not only encoded for metastatic susceptibility but also provided a window to study critical factors that are not easily accessible with current technologies. Furthermore, investigations into inherited metastatic susceptibility enable identification of important molecular and cellular processes that are not subject to mutation and are consequently not detectable by standard cancer genome sequencing strategies. Incorporation of inherited variation into metastasis research therefore provides methods to more comprehensively investigate the etiology of the lethal consequences of tumor progression.

Inferring mutational timing and reconstructing tumour evolutionary histories

Cancer evolution can be considered within a Darwinian framework. Both micro and macro-evolutionary theories can be applied to understand tumour progression and treatment failure. Owing to cancers' complexity and heterogeneity the rules of tumour evolution, such as the role of selection, remain incompletely understood. The timing of mutational events during tumour evolution presents diagnostic, prognostic and therapeutic opportunities. Here we review the current sampling and computational approaches for inferring mutational timing and the evidence from next generation sequencing-informed data on mutational timing across all tumour types. We discuss how this knowledge can be used to illuminate the genes and pathways that drive cancer initiation and relapse; and to support drug development and clinical trial design.