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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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Identification of PLX4032-resistance mechanisms and implications for novel RAF inhibitors

TL;DR: It is demonstrated that the PLX4032‐resistant melanoma cells are sensitive to novel, next‐generation BRAF inhibitors, especially the ‘paradox‐blocker’ PLX8394, supporting its use in clinical trials for treatment of melanoma patients with BRAF‐mutations.
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Progress in the clinical detection of heterogeneity in breast cancer.

TL;DR: This study reviews how the understanding of tumor heterogeneity in breast cancer evolved, and further summarizes recent advances in the detection and monitoring of this heterogeneity in patients with breast cancer.
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Computing tumor trees from single cells

TL;DR: Computational methods have been developed to reconstruct evolutionary lineages from tumors using single-cell genomic data, and the resulting tumor trees have important applications in cancer research and clinical oncology.
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Emerging roles of the tumor-associated stroma in promoting tumor metastasis

TL;DR: The stroma in human carcinomas consists of extracellular matrix and various types of non-carcinoma cells, mainly leukocytes, endothelial cells, fibroblasts, myofibroblast and bone marrow-derived progenitors, which actively supports tumor growth by stimulating neo-angiogenesis, as well as proliferation and invasion of apposed carcinoma cells.
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Methods, challenges and potentials of single cell RNA-seq

TL;DR: The current single cell RNA-seq efforts are reviewed and experimental protocols, challenges, challenges and potentials 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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