Functional versus non-functional intratumor heterogeneity in cancer

Williams, Marc; Werner, Benjamin; Graham, Trevor A.; Sottoriva, Andrea

doi:10.1080/23723556.2016.1162897

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…To better understand the potential functional versus non-functional nature of intratumor heterogeneity (Jamal-Hanjani et al, 2017), we asked whether frequent driver mutations found in canine gliomas (Figure 1A) are part of major (dominant) versus minor clone, and how these driver events compare with measured heterogeneity across molecular subtypes in human pediatric and adult gliomas (Williams et al, 2016). We observed that among less heterogeneous tumor samples (Shannon entropy near 0), shared driver events across canine and adult gliomas are part of major clones, including PIK3CA mutations in canine gliomas, IDH1/2 mutations in IDH-mutant adult gliomas, and EGFR somatic mutations in adult IDH wild-type GBM (Figure 2D).…”

Section: Aneuploidy Is a Major Driver Of Canine And Pediatric High-grade Gliomamentioning

confidence: 99%

Comparative Molecular Life History of Spontaneous Canine and Human Gliomas

et al. 2020

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Section: Aneuploidy Is a Major Driver Of Canine And Pediatric High-grade Gliomamentioning

confidence: 99%

Comparative Molecular Life History of Spontaneous Canine and Human Gliomas

et al. 2020

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“…Interpreting intratumour heterogeneity is challenging due to the complexity of tumour evolutionary dynamics (Burrell, McGranahan, Bartek, & Swanton, 2013;Cross, Graham, & Wright, 2016;Gerlinger et al, 2012;Lipinski et al, 2016;Venkatesan & Swanton, 2016;Williams, Werner, Graham, & Sottoriva, 2016). Greater heterogeneity at the scale of tumour clonal composition may reflect higher genomic instability (Hanahan & Weinberg, 2011) and may correspond to a greater likelihood of malignant cell phenotypes being present (Greaves & Maley, 2012;Maley et al, 2006Maley et al, , 2017.…”

Section: Introductionmentioning

confidence: 99%

When, why and how tumour clonal diversity predicts survival

Noble

Burley

Sueur

et al. 2020

Evolutionary Applications

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The utility of intratumour heterogeneity as a prognostic biomarker is the subject of ongoing clinical investigation. However, the relationship between this marker and its clinical impact is mediated by an evolutionary process that is not well understood. Here, we employ a spatial computational model of tumour evolution to assess when, why and how intratumour heterogeneity can be used to forecast tumour growth rate and progression‐free survival. We identify three conditions that can lead to a positive correlation between clonal diversity and subsequent growth rate: diversity is measured early in tumour development; selective sweeps are rare; and/or tumours vary in the rate at which they acquire driver mutations. Opposite conditions typically lead to negative correlation. In cohorts of tumours with diverse evolutionary parameters, we find that clonal diversity is a reliable predictor of both growth rate and progression‐free survival. We thus offer explanations—grounded in evolutionary theory—for empirical findings in various cancers, including survival analyses reported in the recent TRACERx Renal study of clear‐cell renal cell carcinoma. Our work informs the search for new prognostic biomarkers and contributes to the development of predictive oncology.

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“…Interpreting intratumour heterogeneity is challenging due to the complexity of tumour evolutionary dynamics (Gerlinger et al, 2012;Burrell et al, 2013;Lipinski et al, 2016;Cross et al, 2016;Venkatesan & Swanton, 2016;Williams et al, 2016). Greater heterogeneity at the scale of tumour clonal composition may reflect higher genomic instability (Hanahan & Weinberg, 2011) and may correspond to a greater likelihood of malignant cell phenotypes being present (Maley et al, 2006;Greaves & Maley, 2012;Maley et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

When, why and how clonal diversity predicts future tumour growth

Noble

Burley

Sueur³

et al. 2019

Preprint

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Intratumour heterogeneity holds promise as a prognostic biomarker in multiple cancer types. However, the relationship between this marker and its clinical impact is mediated by an evolutionary process that is not well understood. Here we employ a spatial computational model of tumour evolution to assess when, why and how intratumour heterogeneity can be used to forecast tumour growth rate, an important predictor of clinical progression. We identify three conditions that can lead to a positive correlation between clonal diversity and subsequent growth rate: diversity is measured early in tumour development; selective sweeps are rare; and/or tumours vary in the rate at which they acquire driver mutations. Opposite conditions typically lead to negative correlation. Our results further suggest that prognosis can be better predicted on the basis of both clonal diversity and genomic instability than either factor alone. Nevertheless, we find that, for predicting tumour growth, clonal diversity is likely to perform worse than conventional measures of tumour stage and grade. We thus offer explanations -grounded in evolutionary theory -for empirical findings in various cancers. Our work informs the search for new prognostic biomarkers and contributes to the development of predictive oncology.

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Functional versus non-functional intratumor heterogeneity in cancer

Cited by 5 publications

References 9 publications

Comparative Molecular Life History of Spontaneous Canine and Human Gliomas

Comparative Molecular Life History of Spontaneous Canine and Human Gliomas

When, why and how tumour clonal diversity predicts survival

When, why and how clonal diversity predicts future tumour growth

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