The great escape: tumour cell plasticity in resistance to targeted therapy

Boumahdi, Soufiane; Sauvage, Frédéric J. de

doi:10.1038/s41573-019-0044-1

Cited by 537 publications

(443 citation statements)

References 236 publications

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“…Considering genetic and phenotypic heterogeneity of resistant melanomas, innovative diagnostic and therapeutic approaches are still needed to forestall the emergence of resistance and improve durability of response. As suggested in recently published review by Boumahdi and de Sauvage [16], targeting cancer cell plasticity should provide an opportunity to increase the efficacy of anticancer treatment, however, a comprehensive landscape of cancer cell plasticity still remains to be established. Figure S2.…”

Section: Resultsmentioning

confidence: 99%

“…Mechanisms of resistance primarily directed to support proliferation and survival of cancer cells implicate a plethora of transcriptional regulators, adaptive responses, and feedback loops that extensively affect melanoma cell phenotype enabling the expansion of distinct cell subpopulations in the presence of drug(s) [27,[47][48][49][50][51][52]. Several evidence indicates that a multicellular heterogenous ecosystem of melanoma is changed in a stepwise manner during development of resistance, and many alterations accompanying this process are reversible in nature, which contributes to a high phenotypic plasticity of melanoma cells [16,36,[53][54][55][56][57]. Diverse subpopulations within the tumor are considered as key contributors to variable inter-patient responses to therapy [58], although relapsed melanomas at distinct sites of the same patient can also rely on different resistance programs [12].…”

Section: Discussionmentioning

confidence: 99%

“…The plasticity of melanoma as enabler of drug resistance was a subject of most recent reviews [16,37,53]. Arozarena and Wellbrock [53] proposed three phases of response to MAPK inhibitor therapy in MITF high melanomas, initial with induced reprogramming, adaptive with enhanced drug tolerance and acquired with drug resistance.…”

Section: Discussionmentioning

confidence: 99%

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Dissecting Mechanisms of Melanoma Resistance to BRAF and MEK Inhibitors Revealed Genetic and Non-Genetic Patient- and Drug-Specific Alterations and Remarkable Phenotypic Plasticity

Hartman

Sztiller-Sikorska

Gajos-Michniewicz

et al. 2020

Cells

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The clinical benefit of MAPK pathway inhibition in BRAF-mutant melanoma patients is limited by the development of acquired resistance. Using drug-naïve cell lines derived from tumor specimens, we established a preclinical model of melanoma resistance to vemurafenib or trametinib to provide insight into resistance mechanisms. Dissecting the mechanisms accompanying the development of resistance, we have shown that (i) most of genetic and non-genetic alterations are triggered in a cell line-and/or drug-specific manner; (ii) several changes previously assigned to the development of resistance are induced as the immediate response to the extent measurable at the bulk levels; (iii) reprogramming observed in cross-resistance experiments and growth factor-dependence restricted by the drug presence indicate that phenotypic plasticity of melanoma cells largely contributes to the sustained resistance. Whole-exome sequencing revealed novel genetic alterations, including a frameshift variant of RBMX found exclusively in phospho-AKT high resistant cell lines. There was no similar pattern of phenotypic alterations among eleven resistant cell lines, including expression/activity of crucial regulators, such as MITF, AXL, SOX, and NGFR, which suggests that patient-to-patient variability is richer and more nuanced than previously described. This diversity should be considered during the development of new strategies to circumvent the acquired resistance to targeted therapies.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Dissecting Mechanisms of Melanoma Resistance to BRAF and MEK Inhibitors Revealed Genetic and Non-Genetic Patient- and Drug-Specific Alterations and Remarkable Phenotypic Plasticity

Hartman

Sztiller-Sikorska

Gajos-Michniewicz

et al. 2020

Cells

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“…Instead, it may be that treatment alters non-CNA related aspects of the fitness landscape, or does not change the fitness landscape sufficiently to cause traversal to a new CNA-defined fitness peak. An alternative explanation is that chemotherapy response in CRC may be entirely plastic 27 , and so does not involves the clonal selection of individual lineages – a phenomenon that may be common across cancer types 28 . In CRC, previous work is suggestive that plasticity is established very early in CRC 20 and is consistent with reports of early metastatic spread 26 .…”

Section: Discussionmentioning

confidence: 99%

Negative selection may cause grossly altered but broadly stable karyotypes in metastatic colorectal cancer

Cross

Mossner

Nowinski

et al. 2020

Preprint

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Aneuploidy, defined as the loss and gain of whole and part chromosomes, is a near-ubiquitous feature of cancer genomes, is prognostic, and likely an important determinant of cancer cell biology. In colorectal cancer (CRC), aneuploidy is found in virtually all tumours, including precursor adenomas. However, the temporal evolutionary dynamics that select for aneuploidy remain broadly uncharacterised. Here we perform genomic analysis of 755 samples from a total of 167 patients with colorectal-derived neoplastic lesions that cross-sectionally represent the distinct stages of tumour evolution, and longitudinally track individual tumours through metastasis and treatment. Precancer lesions (adenomas) exhibited low levels of aneuploidy but high intra-tumour heterogeneity, whereas cancers had high aneuploidy but low heterogeneity, indicating that progression is through a genetic bottleneck that suppresses diversity. Individual CRC glands from the same tumour have similar karyotypes, despite prior evidence of ongoing instability at the cell level. Pseudo-stable aneuploid genomes were observed in metastatic lesions sampled from liver and other organs, after chemo- or targeted therapies, and late recurrences detected many years after the diagnosis of a primary tumour. Modelling indicates that these data are consistent with the action of stabilising selection that ‘traps’ cancer cell genomes on a fitness peak defined by the specific pattern of aneuploidy. These data show that the initial progression of CRC requires the traversal of a rugged fitness landscape and subsequent genomic evolution, including metastatic dissemination and therapeutic resistance, is constrained by stabilising selection.

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“…The emergence of mechanisms of resistance in targeted therapies has been attributed to either the selection of rare pre-existing genetic alterations upon drug treatment (77) or the transient acquisition of a drug-refractory phenotype by a small proportion of cancer cells through epigenetic modifications (78). In both cases, these alterations would be detectable in the expression of the corresponding genes.…”

Section: Discussionmentioning

confidence: 99%

Mechanistic models of signaling pathways deconvolute the functional landscape of glioblastoma at single cell resolution

Peña‐Chilet

Loucera

et al. 2019

Preprint

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The rapid development of single cell RNA-sequencing (scRNA-seq) technologies is revealing an unexpectedly large degree of heterogeneity in gene expression levels across the different cells that compose the same tissue sample. However, little is known on the functional consequences of this heterogeneity and the contribution of individual cell-fate decisions to the collective behavior of the tissues these cells are part of. Mechanistic models of signaling pathways have already proven to be useful tools for understanding relevant aspects of cell functionality. Here we propose to use this mechanistic modeling strategy to deconvolute the complexity of the functional behavior of a tissue by dissecting it into the individual functional landscapes of its component cells by using a single-cell RNA-seq experiment of glioblastoma cells. This mechanistic modeling analysis revealed a high degree of heterogeneity at the scale of signaling circuits, suggesting the existence of a complex functional landscape at single cell level. Different clusters of neoplastic glioblastoma cells have been characterized according to their differences in signaling circuit activity profiles, which only partly overlap with the conventional glioblastoma subtype classification. The activity of signaling circuits that trigger cell functionalities which can easily be assimilated to cancer hallmarks reveals different functional strategies with different degrees of aggressiveness followed by any of the clusters.In addition, mechanistic modeling allows simulating the effect of interventions on the components of the signaling circuits, such as drug inhibitions. Thus, effects of drug inhibitions at single cell level can be dissected, revealing for the first time the mechanisms that individual cells use to avoid the effect of a targeted therapy which explain why and how a small proportion of cells display, in fact, different degrees of resistance to the treatment. The results presented here strongly suggest that mechanistic modeling at single cell level not only allows uncovering the molecular mechanisms of the tumor progression but also can predict the success of a treatment and can contribute to a better definition of therapeutic targets in the future.

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The great escape: tumour cell plasticity in resistance to targeted therapy

Cited by 537 publications

References 236 publications

Dissecting Mechanisms of Melanoma Resistance to BRAF and MEK Inhibitors Revealed Genetic and Non-Genetic Patient- and Drug-Specific Alterations and Remarkable Phenotypic Plasticity

Dissecting Mechanisms of Melanoma Resistance to BRAF and MEK Inhibitors Revealed Genetic and Non-Genetic Patient- and Drug-Specific Alterations and Remarkable Phenotypic Plasticity

Negative selection may cause grossly altered but broadly stable karyotypes in metastatic colorectal cancer

Mechanistic models of signaling pathways deconvolute the functional landscape of glioblastoma at single cell resolution

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