Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer

Nature Genetics, Journal Year: 2017, Volume and Issue: 49(3), P. 358 - 366

Published: Jan. 16, 2017

Language: Английский

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Tumor evolution: Linear, branching, neutral or punctuated?

Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, Journal Year: 2017, Volume and Issue: 1867(2), P. 151 - 161

Published: Jan. 19, 2017

Language: Английский

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Tree inference for single-cell data

Genome biology, Journal Year: 2016, Volume and Issue: 17(1)

Published: May 5, 2016

Understanding the mutational heterogeneity within tumors is a keystone for development of efficient cancer therapies. Here, we present SCITE, stochastic search algorithm to identify evolutionary history tumor from noisy and incomplete mutation profiles single cells. SCITE comprises flexible Markov chain Monte Carlo sampling scheme that allows user compute maximum-likelihood history, sample posterior probability distribution, estimate error rates underlying sequencing experiments. Evaluation on real data simulation studies shows scalability present-day single-cell improved reconstruction accuracy compared existing approaches.

Language: Английский

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The evolution of tumour phylogenetics: principles and practice

Nature Reviews Genetics, Journal Year: 2017, Volume and Issue: 18(4), P. 213 - 229

Published: Feb. 13, 2017

Language: Английский

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Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts

Science, Journal Year: 2021, Volume and Issue: 371(6532)

Published: Jan. 21, 2021

Following cancer through the body The heterogeneity of mammalian tumors has been well documented, but it remains unknown how differences between individual cells lead to metastasis and spread throughout body. Quinn et al. created a Cas9-based lineage tracer used single-cell sequencing generate phylogenies follow movement metastatic human implanted in lung mouse xenograph model. Using this model, they found that within same cell line, exhibited diverse phenotypes. These subclones differential gene expression profiles, some which were previously associated with metastasis. Science , issue p. eabc1944

Language: Английский

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The evolution of lung cancer and impact of subclonal selection in TRACERx

Nature, Journal Year: 2023, Volume and Issue: 616(7957), P. 525 - 533

Published: April 12, 2023

Lung cancer is the leading cause of cancer-associated mortality worldwide

Language: Английский

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Single-cell sequencing data reveal widespread recurrence and loss of mutational hits in the life histories of tumors

Genome Research, Journal Year: 2017, Volume and Issue: 27(11), P. 1885 - 1894

Published: Oct. 13, 2017

Intra-tumor heterogeneity poses substantial challenges for cancer treatment. A tumor's composition can be deduced by reconstructing its mutational history. Central to current approaches is the infinite sites assumption that every genomic position only mutate once over lifetime of a tumor. The validity this has never been quantitatively assessed. We developed rigorous statistical framework test with single-cell sequencing data. Our accounts high noise and contamination present in such found strong evidence same being mutationally affected multiple times individual tumors 11 12 data sets from variety human cancers. Seven cases involved loss earlier mutations, five which occurred at unaffected large-scale deletions. Four exhibited parallel mutation, potentially indicating convergent evolution base pair level. results refute general indicate more complex models are needed adequately quantify intra-tumor effective

Language: Английский

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SiFit: inferring tumor trees from single-cell sequencing data under finite-sites models

Genome biology, Journal Year: 2017, Volume and Issue: 18(1)

Published: Sept. 19, 2017

Single-cell sequencing enables the inference of tumor phylogenies that provide insights on intra-tumor heterogeneity and evolutionary trajectories. Recently introduced methods perform this task under infinite-sites assumption, violations which, due to chromosomal deletions loss heterozygosity, necessitate development utilize finite-sites models. We propose a statistical method for from noisy single-cell data model. The performance our synthetic experimental sets two colorectal cancer patients trace lineages in primary metastatic tumors suggests employing model leads improved phylogenies.

Language: Английский

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Inferring the Mutational History of a Tumor Using Multi-state Perfect Phylogeny Mixtures

Cell Systems, Journal Year: 2016, Volume and Issue: 3(1), P. 43 - 53

Published: July 1, 2016

Language: Английский

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Reconstructing metastatic seeding patterns of human cancers

Nature Communications, Journal Year: 2017, Volume and Issue: 8(1)

Published: Jan. 31, 2017

Reconstructing the evolutionary history of metastases is critical for understanding their basic biological principles and has profound clinical implications. Genome-wide sequencing data enabled modern phylogenomic methods to accurately dissect subclones phylogenies from noisy impure bulk tumour samples at unprecedented depth. However, existing are not designed infer metastatic seeding patterns. Here we develop a tool, called Treeomics, reconstruct phylogeny map anatomic locations. Treeomics infers comprehensive patterns pancreatic, ovarian, prostate cancers. Moreover, correctly disambiguates true artifacts; 7% variants were misclassified by conventional statistical methods. These artifacts can skew creating illusory heterogeneity among distinct samples. In silico benchmarking on simulated across wide range sample purities (15-95%) depths (25-800 × ) demonstrates accuracy compared with

Language: Английский

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