Inferring Tumor Phylogenies from Multi-region Sequencing

Slides:



Advertisements
Similar presentations
PhyloSub Jiao et. al. BMC Bioinformatics 2014, 15:35.
Advertisements

Shaping Genetic Alterations in Human Cancer: The p53 Mutation Paradigm Thierry Soussi, Klas G. Wiman Cancer Cell Volume 12, Issue 4, Pages (October.
Somatic Mutation of the 5′ Noncoding Region of the BCL-6 Gene Is Associated with Intraclonal Diversity and Clonal Selection in Histological Transformation.
Volume 127, Issue 3, Pages (September 2004)
Analysis of Mitochondrial DNA Diversity in the Aleuts of the Commander Islands and Its Implications for the Genetic History of Beringia  Olga A. Derbeneva,
Novel PMS2 Pseudogenes Can Conceal Recessive Mutations Causing a Distinctive Childhood Cancer Syndrome  Michel De Vos, Bruce E. Hayward, Susan Picton,
Nicholas McGranahan, Charles Swanton  Cell 
Visualizing Clonal Evolution in Cancer
Ranking Tumor Phylogeny Trees by Likelihood
Characterization and quantification of clonal heterogeneity among hematopoietic stem cells: a model-based approach by Ingo Roeder, Katrin Horn, Hans-Bernd.
Breast Tumor Heterogeneity: Source of Fitness, Hurdle for Therapy
Spatiotemporal Evolution of the Primary Glioblastoma Genome
Volume 67, Issue 4, Pages (April 2015)
Wei Jiao, Shankar Vembu, Amit G Deshwar,
Volume 127, Issue 3, Pages (September 2004)
Genome Evolution: Horizontal Movements in the Fungi
The Evolution of the Algorithms for Collective Behavior
On the Origin of Syn- and Metachronous Urothelial Carcinomas
Revealing the genomic heterogeneity of melanoma
Volume 74, Issue 5, Pages (November 2018)
Mohammed El-Kebir, Gryte Satas, Layla Oesper, Benjamin J. Raphael 
Volume 138, Issue 4, Pages (August 2009)
Epigenetic heterogeneity is associated with genetic heterogeneity in CLL samples. Epigenetic heterogeneity is associated with genetic heterogeneity in.
Genome Evolution: Horizontal Movements in the Fungi
The AML Salad Bowl Cancer Cell
Diagnostic approaches to measure the impact of cancer therapies on clonal evolution. Diagnostic approaches to measure the impact of cancer therapies on.
Volume 4, Issue 1, Pages 4-6 (July 2003)
Embracing Uncertainty in Reconstructing Early Animal Evolution
Optimizing Cancer Genome Sequencing and Analysis
The Amazing and Deadly Glioma Race
Evolutionary Inference across Eukaryotes Identifies Specific Pressures Favoring Mitochondrial Gene Retention  Iain G. Johnston, Ben P. Williams  Cell.
Multiregional Tumor Trees Are Not Phylogenies
Volume 69, Issue 5, Pages (May 2016)
Luisa De Sordi, Varun Khanna, Laurent Debarbieux  Cell Host & Microbe 
Progress in Molecular Genetics of Heritable Skin Diseases: The Paradigms of Epidermolysis Bullosa and Pseudoxanthoma Elasticum  Jouni Uitto, Leena Pulkkinen,
Stem Cell Heterogeneity and Plasticity in Epithelia
Imaging the Neural Basis of Locomotion
Intrinsic and Task-Evoked Network Architectures of the Human Brain
Volume 58, Issue 4, Pages (May 2015)
Volume 18, Issue 5, Pages (November 2015)
Global Edgetic Rewiring in Cancer Networks
Lung Cancer: A Wily Genetic Opponent
Volume 24, Issue 4, Pages (July 2018)
SNP Arrays in Heterogeneous Tissue: Highly Accurate Collection of Both Germline and Somatic Genetic Information from Unpaired Single Tumor Samples  Guillaume.
Breast Tumor Heterogeneity: Source of Fitness, Hurdle for Therapy
Volume 152, Issue 1, Pages (January 2019)
Volume 24, Issue 8, Pages (August 2018)
Analysis of High-Resolution HapMap of DTNBP1 (Dysbindin) Suggests No Consistency between Reported Common Variant Associations and Schizophrenia  Mousumi.
Volume 155, Issue 4, Pages (November 2013)
Intratumoral Heterogeneity of the Epigenome
Characteristics of Neutral and Deleterious Protein-Coding Variation among Individuals and Populations  Wenqing Fu, Rachel M. Gittelman, Michael J. Bamshad,
Evolution of the Cancer Stem Cell Model
Zhenhai Zhang, B. Franklin Pugh  Cell 
Patricia Munoz-Garrido, Jesper B. Andersen  Gastroenterology 
Volume 24, Issue 7, Pages (August 2018)
Jeffrey A. Fawcett, Hideki Innan  Trends in Genetics 
Olga A. Derbeneva, Elena B. Starikovskaya, Douglas C. Wallace, Rem I
Comprehensive Genetic Landscape of Uveal Melanoma by Whole-Genome Sequencing  Beryl Royer-Bertrand, Matteo Torsello, Donata Rimoldi, Ikram El Zaoui, Katarina.
Katy Hanlon, Lorna W. Harries, Sian Ellard, Claudius E. Rudin 
Spatiotemporal Evolution of the Primary Glioblastoma Genome
Cancer Stem Cells: Current Status and Evolving Complexities
Novel PMS2 Pseudogenes Can Conceal Recessive Mutations Causing a Distinctive Childhood Cancer Syndrome  Michel De Vos, Bruce E. Hayward, Susan Picton,
Volume 88, Issue 5, Pages (December 2015)
High-Definition Reconstruction of Clonal Composition in Cancer
Kinetics of clone appearance, size, persistence, and lineage content.
Squamous Cell Cancers: A Unified Perspective on Biology and Genetics
Comparison of Genetic Profiles Between Primary Melanomas and their Metastases Reveals Genetic Alterations and Clonal Evolution During Progression  Reiji.
Nicholas McGranahan, Charles Swanton  Cancer Cell 
Messages through Bottlenecks: On the Combined Use of Slow and Fast Evolving Polymorphic Markers on the Human Y Chromosome  Peter de Knijff  The American.
The AML Salad Bowl Cancer Cell
Presentation transcript:

Inferring Tumor Phylogenies from Multi-region Sequencing Zheng Hu, Christina Curtis  Cell Systems  Volume 3, Issue 1, Pages 12-14 (July 2016) DOI: 10.1016/j.cels.2016.07.007 Copyright © 2016 Elsevier Inc. Terms and Conditions

Figure 1 Tumor Phylogeny Reconstruction from Multi-region Bulk Sequencing Data (A) Schematic representation of tumor evolution where cells are related by a genealogical tree and growth occurs in the presence of spatial constraints. Each clone is defined by a distinct constellation of single-nucleotide variants (SNVs) and/or copy number alteratiosn (CNAs) and localizes to a particular region(s) of the tumor. For illustration, three bulk samples obtained at the time of primary tumor diagnosis are shown, each consisting of one or more clone, as indicated by the colored segments. Each SNV/CNA creates a new clone according to the infinite-allele model assumed in El-Kebir et al. (2016). Sample 1 is composed of clone d, sample 2 by clones b and c, and sample 3 by b and e. Although the mutation defining clone a can be detected in both sample 1 and sample 2, clone a is not detected in these two samples due to replacement by successive clones, d and c. (B) While an equivalent phylogeny can be reconstructed as in (A), information on the topography of samples within the tumor, coupled with inference of the mutational timeline, can reveal patterns of clone mixing and can aid delineation of the underlying growth dynamics (Sottoriva et al., 2015). For example, clonal mixing in an early tumor (turquoise SNV clone) could give rise to patterns of genetic heterogeneity where the same somatic alteration(s) is detected in distant regions (samples 1 and 2) of the tumor. (C) Schematic illustration of a tumor phylogenetic tree whose leaves correspond to mixtures of cells (clones) harboring somatic alterations in varied proportions and the edges describe their ancestral relationship. Phylogeny deconvolution aims to reconstruct the tree (including the relative timing of SNVs/CNAs) and mixing proportions from the somatic alterations that underlie the evolutionary process given m mixtures of the leaves of the tree. Light gray triangles and squares denote undetectable SNVs and CNAs, respectively. Cell Systems 2016 3, 12-14DOI: (10.1016/j.cels.2016.07.007) Copyright © 2016 Elsevier Inc. Terms and Conditions