Universal Patterns of Selection in Cancer and Somatic Tissues

Martincorena, Iñigo; Raine, Keiran; Gerstung, Moritz; Dawson, Kevin J.; Haase, Kerstin; Loo, Peter Van; Davies, Helen; Stratton, Michael R.; Campbell, Peter J.

doi:10.1016/j.cell.2018.06.001

Cited by 340 publications

(543 citation statements)

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“…We identified three types of genetics‐based factors that could quantify the adaptation of cells to a determined environment: selective advantage, driver self‐sufficiency and malignant epistatic interactions (Figure a). Selective advantage has been the focus of numerous previous studies (Gonzalez‐Perez & Lopez‐Bigas, ; Lawrence et al, ; Martincorena et al, ; Zapata et al, ) and was defined in our case as the ratio of observed occurrence of each clonal alteration (driver or not) compared to its expected occurrence given its number of clonal observations, weighted by gene size (in base pairs). We compared our selection score to the corrected dN/dS measure obtained by Zapata et al () in a recent publication.…”

Section: Resultsmentioning

confidence: 99%

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

Tokutomi

Moyret‐Lalle

Puisieux

et al. 2019

Evolutionary Applications

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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 nine tumour types. We developed a framework using the repeatability of cancer development to score the local malignant adaptation (LMA) of genetic clones, as their potential to malignantly progress and invade their environment of origin. Using this framework, we found that premalignant 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 malignant progression can be modelled by such a framework in tumour‐type‐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 preneoplastic lesions in the future.

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Section: Resultsmentioning

confidence: 99%

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

Tokutomi

Moyret‐Lalle

Puisieux

et al. 2019

Evolutionary Applications

View full text Add to dashboard Cite

show abstract

“…We then extended our screen for H3 mutations to 18 704 tumours, encompassing >60 cancer types other than T‐ALL (Tables SIV and SV). This dataset comprised 8764 internally sequenced specimens and 9940 TCGA samples re‐analysed using an in‐house variant calling pipeline as previously described (Martincorena et al , ). We identified only one neomorphic H3 mutation in an acute leukaemia specimen: a previously reported HIST1H3D p.K27M mutation in an adult AML case (TCGA‐AB2927‐03) (Lehnertz et al , ).…”

Section: Type 3 Histone Mutations In T Cell Leukaemiamentioning

confidence: 99%

Recurrent histone mutations in T‐cell acute lymphoblastic leukaemia

et al. 2018

Self Cite

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“…26 In the causal framework we adopt, this means that mutations can provide different cues for the temporal reconstruction of cancer development. Some mutations are just a byproduct of the increased genetic instability which characterizes the process of tumourigenesis.…”

Section: Comments On Temporal Sequence Of Hallmarksmentioning

confidence: 99%

“…Studies have shown that a typical tumour contains 2-8 "driver gene" mutations, 26,27 but which specific genes will be mutated in different tumours might vary. In addition, cells from different sections of the same tumour tend to have a diverse mutational landscape, suggesting that different mutations may converge towards the same phenotypic result.…”

Section: Comments On Temporal Sequence Of Hallmarksmentioning

confidence: 99%