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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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Deterministic trapping, encapsulation and retrieval of single-cells.

TL;DR: A novel method for conducting true single-cell encapsulation at very high efficiency for the manipulation of precious samples and the development of the complete device operation that permits highly efficient single- cell encapsulation and droplet retrieval is presented.
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Precision medicine in breast cancer: genes, genomes, and the future of genomically driven treatments.

TL;DR: The technological advances that have catalyzed these developments, the landscape of mutations in breast cancer, the clinical impact of genomic profiling, and the incorporation of genomic information into clinical care and clinical trials are focused on.
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The use of molecular imaging combined with genomic techniques to understand the heterogeneity in cancer metastasis.

TL;DR: How various imaging methods that allow for quantification of metastatic tumour heterogeneity, along with the potential of developing imaging, integrated with other in vitro diagnostic approaches such as genomics and exosome analyses, have the potential role as a non-invasive biomarker for guiding the treatment algorithm is reviewed.
Journal ArticleDOI

Computational approaches for inferring tumor evolution from single-cell genomic data

TL;DR: An overview of the state-of-the-art single-cell DNA sequencing methods, technical errors that are inherent in the resulting large-scale datasets, and computational methods to overcome these errors are presented.
Journal ArticleDOI

A new branch on the tree: next-generation sequencing in the study of cancer evolution.

TL;DR: A clearer understanding of those alterations that undergo positive and negative selection throughout carcinogenesis and leading to metastatic dissemination would provide a boon not only to the understanding of cancer evolution, but to the development of potential targets for therapeutic intervention as well.
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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