Tumour evolution inferred by single-cell sequencing
Nicholas Navin,Jude Kendall,Jennifer Troge,Peter Andrews,Linda Rodgers,Jeanne McIndoo,Kerry Cook,Asya Stepansky,Dan Levy,Diane Esposito,Lakshmi Muthuswamy,Alexander Krasnitz,W. Richard McCombie,James W. Hicks,Michael Wigler +14 more
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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.read more
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Single-cell genomic analysis in plants
TL;DR: The technical challenges of analysing material from a single plant cell are outlined, the applications of single-cell genomics are examined, and the integration of this approach with genome editing is examined.
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JAK2 and genomic instability in the myeloproliferative neoplasms: A case of the chicken or the egg?†
TL;DR: Current understanding of the molecular defects present in patients with an MPN, and the effects of mutations targeting Janus kinase 2 (JAK2)‐mediated intracellular signaling on DNA damage and on the elimination of mutation‐bearing cells by programmed cell death are summarized.
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Clinical translation of [ 18 F]ICMT-11 for measuring chemotherapy-induced caspase 3/7 activation in breast and lung cancer
Suraiya Dubash,Shairoz Merchant,Kathrin Heinzmann,Francesco Mauri,Ioannis Lavdas,Marianna Inglese,Marianna Inglese,Kasia Kozlowski,N Rama,N Masrour,J F Steel,Andrew Thornton,Adrian Lim,Conrad R. Lewanski,Susan Cleator,R C Coombes,Laura M. Kenny,Laura M. Kenny,Eric O. Aboagye +18 more
TL;DR: It is summarized that tumour response could occur in the absence of predominant chemotherapy-induced caspase-3/7 activation measured non-invasively across entire tumour lesions in patients with breast and lung cancer.
Journal ArticleDOI
Integrative multi-omics analysis of a colon cancer cell line with heterogeneous Wnt activity revealed RUNX2 as an epigenetic regulator of EMT.
Hongyang Yi,Hongyang Yi,Guipeng Li,Yongkang Long,Weizheng Liang,Weizheng Liang,Huanhuan Cui,Bin Zhang,Ying Tan,Yunfei Li,Luochen Shen,Daqi Deng,Yisen Tang,Chenyu Mao,Shuye Tian,Yunting Cai,Qionghua Zhu,Yuhui Hu,Wei Chen,Liang Fang +19 more
TL;DR: RUNX2 is revealed as a new EMT-promoting epigenetic regulator in colon cancer, which may potentially serve as a prognostic marker for tumor metastasis and poor survival of colon cancer patients, as well as patients afflicted with other types of cancer.
Journal ArticleDOI
PhyloOncology: Understanding cancer through phylogenetic analysis.
Jason A. Somarelli,Kathryn E. Ware,Rumen Kostadinov,Jeffrey Robinson,Hakima Amri,Mones Abu-Asab,Nicolaas H. Fourie,Rui Diogo,David L. Swofford,Jeffrey P. Townsend +9 more
TL;DR: Well-developed phylogenetic applications provide fast, robust approaches to analyze high-dimensional, heterogeneous cancer data sets, and one suite of algorithms and concepts with potential to shed light on cancer biology is phylogenetics.
References
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