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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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Detection of Tumor PIK3CA Status in Metastatic Breast Cancer Using Peripheral Blood

TL;DR: Analysis of plasma-derived ctDNA for the detection of PIK3CA mutations in patients with metastatic breast cancer is feasible and the results suggest that Pik3CA mutational status can change upon disease recurrence, emphasizing the importance of reassessing PIK 3CA status on contemporary (not archival) biospecimens.
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Cancer genomics: one cell at a time.

TL;DR: The study of single cancer cells has transformed from qualitative microscopic images to quantitative genomic datasets, fueled by the development of single-cell sequencing technologies, which provide a powerful new approach to study complex biological processes in human cancers.
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MATH, a Novel Measure of Intratumor Genetic Heterogeneity, Is High in Poor-Outcome Classes of Head and Neck Squamous Cell Carcinoma

TL;DR: As NGS of tumor DNA becomes widespread in clinical research and practice, MATH should provide a simple, quantitative, and clinically practical biomarker to help evaluate relations of intratumor genetic heterogeneity to outcome in any type of cancer.
Journal ArticleDOI

Microenvironmental Regulation of Epithelial–Mesenchymal Transitions in Cancer

TL;DR: A unique paracrine cross-talk between the microenvironment and the cancer cells, which promotes tumor outgrowth in the metastatic organ, is outlined, and opportunities for novel antimetastatic approaches for cancer therapy are discussed.
Journal ArticleDOI

A new genome‐driven integrated classification of breast cancer and its implications

TL;DR: The characterisation of a new genome‐driven integrated classification of breast cancer is characterised, which substantially refines the existing classification systems currently used and provides a new framework for studying the underlying biology of each novel subtype.
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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