Quantifying local malignant adaptation in tissue-specific evolutionary trajectories by harnessing cancer’s repeatability at the genetic level

Abstract

Cancer is a potentially lethal disease, in which patients with nearly identical genetic backgrounds can develop a similar pathology through distinct combinations of genetic alterations. We aimed to reconstruct the evolutionary process underlying tumour initiation, using the combination of convergence and discrepancies observed across 2,742 cancer genomes from 9 tumour types. We developed a framework using the repeatability of cancer development to score the fitness of genetic clones, as their potential to malignantly progress and invade their environment of origin. Using this framework, we found that pre-malignant skin and colorectal lesions appeared specifically adapted to their local environment, yet insufficiently for full cancerous transformation. We found that metastatic clones were more adapted to the site of origin than to the invaded tissue, suggesting that genetics may be more important for local progression than for the invasion of distant organs. In addition, we used network analyses to investigate evolutionary properties at the system-level, highlighting that different dynamics of fitness progression can be modelled by such a framework in tumourtype-specific fashion. We find that occurrence-based methods can be used to specifically recapitulate the process of cancer initiation and progression, as well as to evaluate the adaptation of genetic clones to given environments. The repeatability observed in the evolution of most tumour types could therefore be harnessed to better predict the trajectories likely to be taken by tumours and pre-neoplastic lesions in the future.

Assessing Cell Activities rather than Identities to Interpret Intra-Tumor Phenotypic Diversity and Its Dynamics

“…Better understanding the dynamics of intra-tumor heterogeneity will help tailor better therapeutics to control and funnel cancer evolution. During malignant somatic evolution, cells drift away from their well-characterized normal ancestors by following trajectories unique to each patient (Tokutomi et al, 2019), whereas there is convergence across patients to (de)activate the necessary cellular activities Weinberg, 2000, 2011). Consequently, we investigated the relevance of focusing on what cancer cells do, rather than what they are, to measure phenotypic diversity in the cancer context.…”

Separating the Local and Malignant Dimensions of Cancer Adaptation

“…We recently developed a framework to measure the local malignant adaptation (LMA) of genetic clones in 9 tissues, based on the repeatability of genomic alterations in these cancers. 1 Such a framework can help assess the malignant potential of genetic clones and predict their future evolution. This methodology used a single scale to reflect how likely a combination of alterations was to give rise to a cancer in a specific environment (Figure 1).…”

“…This evolutionary process of cancer development repeats itself on a tissue-specific basis. 1 We harnessed this repeatability to quantify the LMA of a ‘clone’ (a genotype based on the presence of driver alterations) to its tissue-specific environment. To factor in the contribution of each driver alteration and their interplay, our framework was centred on a single assumption: despite different evolutionary trajectories, all clones that gave rise to cancer were similarly adapted to their local tissue.…”