Revealing the inherent heterogeneity of human malignancies by variant consensus strategies coupled with cancer clonal analysis

Tumors are heterogeneous in composition. They are composed of cancer cells proper, along with stromal elements that collectively form a microenvironment, all of which are necessary to nurture the malignant process. In addition, many of the stromal cells are modified to support the unique needs of the malignant state. Tumors are composed of a variety of clones or subpopulations of cancer cells, which may differ in karyotype, growth rate, expression of cell surface markers, sensitivity to therapeutics, etc. New tools and methods to provide an improved understanding of tumor clonal architecture are needed to guide therapy.The subclonal structure and transcription status of underlying somatic mutations reveal the trajectory of tumor progression in patients with cancer. Approaching the analysis of tumors to reveal clonal complexity in a quantitative manner should facilitate better characterization and therapeutic assignments. The challenge is the interpretation of massive amounts of data from next generation sequencing (NGS) experiments to find what is truly meaningful for improving the understanding of basic cancer biology, as well as therapeutic assignments and outcomes. To meet this need, a methodology named CloneViz was developed and utilized for the identification of serial clonal mutations.Whole exome sequencing (WES) on an Illumina HiSeq 2500 was performed on paired tumor and normal samples from a Multiple Myeloma (MM) patient at presentation, then first and second relapse. Following alignment, a consensus strategy for variant selection was employed along with computational linkage to a formal tumor clonality analysis based on visualization and quantitative methods.

[1]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[2]  R. Kyle,et al.  Drug therapy: Multiple myeloma , 2004 .

[3]  A. Fernández-Medarde,et al.  Ras in cancer and developmental diseases. , 2011, Genes & cancer.

[4]  P. Nowell.  The clonal evolution of tumor cell populations. , 1976, Science.

[5]  A. Magurran,et al.  Measuring Biological Diversity , 2004 .

[6]  B. Barlogie,et al.  Antitumor activity of thalidomide in refractory multiple myeloma. , 1999, The New England journal of medicine.

[7]  M. Stratton.  Exploring the Genomes of Cancer Cells: Progress and Promise , 2011, Science.

[8]  Joshua F. McMichael,et al.  DGIdb - Mining the druggable genome , 2013, Nature Methods.

[9]  A. McKenna,et al.  Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy. , 2014, Cancer cell.

[10]  John Crowley,et al.  Global gene expression profiling of multiple myeloma, monoclonal gammopathy of undetermined significance, and normal bone marrow plasma cells. , 2002, Blood.

[11]  Björn Usadel,et al.  Trimmomatic: a flexible trimmer for Illumina sequence data , 2014, Bioinform..

[12]  Joshua F. McMichael,et al.  The Origin and Evolution of Mutations in Acute Myeloid Leukemia , 2012, Cell.

[13]  Trevor J Pugh,et al.  Initial genome sequencing and analysis of multiple myeloma , 2011, Nature.

[14]  J. Salk.  Clonal evolution in cancer , 2010 .

[15]  Wendy S. W. Wong,et al.  Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs , 2012, Bioinform..

[16]  Carissa A. Sanchez,et al.  Genetic clonal diversity predicts progression to esophageal adenocarcinoma , 2006, Nature Genetics.

[17]  O. Cope,et al.  Multiple myeloma. , 1948, The New England journal of medicine.

[18]  Ara Darzi,et al.  Preparing for precision medicine. , 2012, The New England journal of medicine.

[19]  Lisa J. Murray,et al.  Intraclonal heterogeneity is a critical early event in the development of myeloma and precedes the development of clinical symptoms , 2013, Leukemia.

[20]  Mel Greaves,et al.  Darwinian medicine: a case for cancer , 2007, Nature Reviews Cancer.

[21]  P. Campbell,et al.  Single-cell mutational profiling and clonal phylogeny in cancer , 2013, Genome research.

[22]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[23]  M. DePristo,et al.  A framework for variation discovery and genotyping using next-generation DNA sequencing data , 2011, Nature Genetics.

[24]  Benjamin J. Raphael,et al.  Mutational landscape and significance across 12 major cancer types , 2013, Nature.

[25]  P. Elliott,et al.  The proteasome inhibitor PS-341 inhibits growth, induces apoptosis, and overcomes drug resistance in human multiple myeloma cells. , 2001, Cancer research.

[26]  Donald J. Johann,et al.  Cancer and the tumor microenvironment: a review of an essential relationship , 2009, Cancer Chemotherapy and Pharmacology.

[27]  K. Kinzler,et al.  Cancer Genome Landscapes , 2013, Science.

[28]  D Puthier,et al.  High incidence of N and K‐Ras activating mutations in multiple myeloma and primary plasma cell leukemia at diagnosis , 2001, Human mutation.

[29]  A I Pick,et al.  THE TREATMENT OF MULTIPLE MYELOMA , 1948, Harefuah.

[30]  D. Hanahan,et al.  Hallmarks of Cancer: The Next Generation , 2011, Cell.

[31]  D. Dingli,et al.  Improved survival in multiple myeloma and the impact of novel therapies. , 2008, Blood.

[32]  Martin Goodson,et al.  Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads. , 2011, Genome research.

[33]  James R. Downing,et al.  Genomic Analysis of the Clonal Origins of Relapsed Acute Lymphoblastic Leukemia , 2008, Science.

[34]  BMC Bioinformatics , 2005 .

[35]  M. Gerlinger,et al.  How Darwinian models inform therapeutic failure initiated by clonal heterogeneity in cancer medicine , 2010, British Journal of Cancer.

[36]  Helga Thorvaldsdóttir,et al.  Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration , 2012, Briefings Bioinform..

[37]  Pablo Cingolani,et al.  © 2012 Landes Bioscience. Do not distribute. , 2022 .

[38]  Bin Li,et al.  Mutation of NRAS but not KRAS significantly reduces myeloma sensitivity to single-agent bortezomib therapy. , 2014, Blood.

[39]  John Quackenbush,et al.  Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV , 2011, Bioinform..

[40]  B. Barlogie,et al.  Total therapy with tandem transplants for newly diagnosed multiple myeloma. , 1999, Blood.

[41]  A. Ashworth,et al.  Intraclonal heterogeneity and distinct molecular mechanisms characterize the development of t(4;14) and t(11;14) myeloma. , 2012, Blood.

[42]  J. Carpten,et al.  Clonal competition with alternating dominance in multiple myeloma. , 2012, Blood.

[43]  T. Chevassut,et al.  The Genetic Architecture of Multiple Myeloma , 2014, Advances in hematology.

[44]  A. Sivachenko,et al.  Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples , 2013, Nature Biotechnology.

[45]  Darren J. Burgess,et al.  Cancer genetics: Initially complex, always heterogeneous , 2011, Nature Reviews Cancer.

[46]  D. Hanahan,et al.  The Hallmarks of Cancer , 2000, Cell.

[47]  Thomas G. Dietterich.  Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.

[48]  Alexander van Oudenaarden,et al.  Genetic and phenotypic diversity in breast tumor metastases. , 2014, Cancer research.

[49]  Li Ding,et al.  Genomic Landscape of Non-Small Cell Lung Cancer in Smokers and Never-Smokers , 2012, Cell.

[50]  Christopher A. Miller,et al.  VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. , 2012, Genome research.