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Tumour evolution inferred by single-cell sequencing

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TLDR
It is shown that with flow-sorted nuclei, whole genome amplification and next generation sequencing the authors can accurately quantify genomic copy number within an individual nucleus and indicate that tumours grow by punctuated clonal expansions with few persistent intermediates.
Abstract
Genomic analysis provides insights into the role of copy number variation in disease, but most methods are not designed to resolve mixed populations of cells. In tumours, where genetic heterogeneity is common, very important information may be lost that would be useful for reconstructing evolutionary history. Here we show that with flow-sorted nuclei, whole genome amplification and next generation sequencing we can accurately quantify genomic copy number within an individual nucleus. We apply single-nucleus sequencing to investigate tumour population structure and evolution in two human breast cancer cases. Analysis of 100 single cells from a polygenomic tumour revealed three distinct clonal subpopulations that probably represent sequential clonal expansions. Additional analysis of 100 single cells from a monogenomic primary tumour and its liver metastasis indicated that a single clonal expansion formed the primary tumour and seeded the metastasis. In both primary tumours, we also identified an unexpectedly abundant subpopulation of genetically diverse 'pseudodiploid' cells that do not travel to the metastatic site. In contrast to gradual models of tumour progression, our data indicate that tumours grow by punctuated clonal expansions with few persistent intermediates.

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Stress-Induced Mutagenesis: Implications in Cancer and Drug Resistance

TL;DR: Molecular mechanisms of stress-response-dependent (stress-induced) mutagenesis that occur from bacteria to cancer, and are activated by starvation, drugs, hypoxia, and other stressors are reviewed.
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Advances in computational approaches for prioritizing driver mutations and significantly mutated genes in cancer genomes

TL;DR: A review of methods and computational tools developed during the past several years for detecting potential driver or actionable mutations in rapidly emerging precision cancer medicine may help investigators find an appropriate tool.
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Targeting the Adaptability of Heterogeneous Aneuploids

TL;DR: It is shown here, using a combination of experimental data and a general stochastic model, that the degree of phenotypic variation, thus evolvability, escalates with the level of overall growth suppression and likely explains the challenge of treating aneuploidy diseases with a single stress-inducing agent.
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Genetic insights into the morass of metastatic heterogeneity.

TL;DR: How genetic heterogeneity impacts metastatic disease and the implications of current knowledge for future research endeavours and therapeutic interventions are examined.
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Molecular functions of the iron-regulated metastasis suppressor, NDRG1, and its potential as a molecular target for cancer therapy.

TL;DR: The role of this important metastasis suppressor is described, the relationship between the molecular structure of this protein and its functions remains unclear and interesting unresolved issues regarding this protein are discussed.
References
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Journal ArticleDOI

The neighbor-joining method: a new method for reconstructing phylogenetic trees.

TL;DR: The neighbor-joining method and Sattath and Tversky's method are shown to be generally better than the other methods for reconstructing phylogenetic trees from evolutionary distance data.
Journal ArticleDOI

Ultrafast and memory-efficient alignment of short DNA sequences to the human genome

TL;DR: Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches and can be used simultaneously to achieve even greater alignment speeds.
Journal ArticleDOI

The clonal evolution of tumor cell populations

TL;DR: Each patient's cancer may require individual specific therapy, and even this may be thwarted by emergence of a genetically variant subline resistant to the treatment, which should be directed toward understanding and controlling the evolutionary process in tumors before it reaches the late stage usually seen in clinical cancer.
Journal ArticleDOI

Distant metastasis occurs late during the genetic evolution of pancreatic cancer

TL;DR: In this article, the authors rely on data generated by sequencing the genomes of seven pancreatic cancer metastases to evaluate the clonal relationships among primary and metastatic cancers and find that clonal populations that give rise to distant metastases are represented within the primary carcinoma, but these clones are genetically evolved from the original parental, non-metastatic clone.

SF-010-4 Distant metastasis occurs late during the genetic evolution of pancreatic cancer

TL;DR: A quantitative analysis of the timing of the genetic evolution of pancreatic cancer was performed, indicating at least a decade between the occurrence of the initiating mutation and the birth of the parental, non-metastatic founder cell.
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