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Catch my drift? Making sense of genomic intra-tumour heterogeneity.

ABSTRACT: The cancer genome is shaped by three components of the evolutionary process: mutation, selection and drift. While many studies have focused on the first two components, the role of drift in cancer evolution has received little attention. Drift occurs when all individuals in the population have the same likelihood of producing surviving offspring, and so by definition a drifting population is one that is evolving neutrally. Here we focus on how neutral evolution is manifested in the cancer genome. We discuss how neutral passenger mutations provide a magnifying glass that reveals the evolutionary dynamics underpinning cancer development, and outline how statistical inference can be used to quantify these dynamics from sequencing data. We argue that only after we understand the impact of neutral drift on the genome can we begin to make full sense of clonal selection. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer? Edited by Dr. Robert A. Gatenby.

SUBMITTER: Sottoriva A

PROVIDER: S-EPMC5446319 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Catch my drift? Making sense of genomic intra-tumour heterogeneity.

Sottoriva Andrea A Barnes Chris P CP Graham Trevor A TA

Biochimica et biophysica acta. Reviews on cancer 20170107 2

The cancer genome is shaped by three components of the evolutionary process: mutation, selection and drift. While many studies have focused on the first two components, the role of drift in cancer evolution has received little attention. Drift occurs when all individuals in the population have the same likelihood of producing surviving offspring, and so by definition a drifting population is one that is evolving neutrally. Here we focus on how neutral evolution is manifested in the cancer genome ...[more]

PMID: 28069394

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Project description:BackgroundIntra-tumour heterogeneity in lymphoid malignancies encompasses selection of genetic events and epigenetic regulation of transcriptional programs. Clonal-related neoplastic cell populations are unsteadily subjected to immune editing and metabolic adaptations within different tissue microenvironments. How tissue-specific mesenchymal cells impact on the diversification of aggressive lymphoma clones is still unknown.MethodsCombining in situ quantitative immunophenotypical analyses and RNA sequencing we investigated the intra-tumour heterogeneity and the specific mesenchymal modifications that are associated with A20 diffuse large B-cell lymphoma (DLBCL) cells seeding of different tissue microenvironments. Furthermore, we characterized features of lymphoma-associated stromatogenesis in human DLBCL samples using Digital Spatial Profiling, and established their relationship with prognostically relevant variables, such as MYC.FindingsWe found that the tissue microenvironment casts a relevant influence over A20 transcriptional landscape also impacting on Myc and DNA damage response programs. Extending the investigation to mice deficient for the matricellular protein SPARC, a stromal prognostic factor in human DLBCL, we demonstrated a different immune imprint on A20 cells according to stromal Sparc proficiency. Through Digital Spatial Profiling of 87 immune and stromal genes on human nodal DLBCL regions characterized by different mesenchymal composition, we demonstrate intra-lesional heterogeneity arising from diversified mesenchymal contextures and impacting on the stromal and immune milieu.InterpretationOur study provides experimental evidence that stromal microenvironment generates topological determinants of intra-tumour heterogeneity in DLBCL involving key transcriptional pathways such as Myc expression, damage response programs and immune checkpoints.FundingThis study has been supported by the Italian Foundation for Cancer Research (AIRC) (grants 15999 and 22145 to C. Tripodo) and by the University of Palermo.

Project description:Intra-individual tumoral heterogeneity (ITH) is a hallmark of solid tumors and impedes accurate genomic diagnosis and selection of proper therapy. The purpose of this study was to identify ITH of ovarian serous adenocarcinomas (OSAs) and to determine the utility of ascitic cancer cells as a resource for mutation profiling in spite of ITH. We performed whole-exome sequencing, copy number profiling, and DNA methylation profiling of four OSA genomes using multiregional biopsies from 13 intraovarian lesions, 12 extraovarian tumor lesions (omentum/peritoneum), and ascitic cells. We observed substantial levels of heterogeneity in mutations and copy number alterations (CNAs) of the OSAs. We categorized the mutations into 'common', 'shared' and 'private' according to the regional distribution. Six common, 8 shared, and 24 private mutations were observed in known cancer-related genes,. but common mutations had a higher mutant allele frequency and included TP53 mutations in all four OSAs. Region-specific chromosomal amplifications and deletions involving BRCA1, PIK3CA, and RB1 were also identified. Of note, the mutations detected in ascitic cancer cells represented 92.3-100% of overall somatic mutations in the given case. Phylogenetic analyses of ascitic genomes predicted a polyseeding origin of somatic mutations in ascitic cells. Our results demonstrate that despite ITH, somatic mutations, CNAs, and DNA methylations in both âcommonâ category and cancer-related genes were highly conserved in ascitic cells of OSAs, highlighting the clinical relevance of genome analysis of ascitic cells. Ascitic tumor cells may serve as a potential resource to discover somatic mutations of primary OSA with diagnostic and therapeutic relevance. The purpose of this study was to identify intra-individual tumor heterogenety of ovarian serous adenocarcinomas Four to nine different ovarian cancer areas from intraovarian and extra-ovarian lesions that were at least 1cm apart as well as 50 ml ascites were collected from the four OSA patients. Genomic DNA from tumor and matched normal samples were simultaneously hybridized onto the array. Total 29 array experiments were conducted.

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Catch my drift? Making sense of genomic intra-tumour heterogeneity.

Publications

Catch my drift? Making sense of genomic intra-tumour heterogeneity.

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