scholarly journals Normal tissue architecture determines the evolutionary course of cancer

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jeffrey West ◽  
Ryan O. Schenck ◽  
Chandler Gatenbee ◽  
Mark Robertson-Tessi ◽  
Alexander R. A. Anderson
Keyword(s):  
Evolutionary Dynamics ◽  
Neutral Evolution ◽  
Driver Mutations ◽  
Tumor Evolution ◽  
Tissue Architecture ◽  
Spatial Constraints ◽  
Fitness Effects ◽  
Two Factors ◽  
Mixing Rates ◽  
Precancerous Stage

AbstractCancer growth can be described as a caricature of the renewal process of the tissue of origin, where the tissue architecture has a strong influence on the evolutionary dynamics within the tumor. Using a classic, well-studied model of tumor evolution (a passenger-driver mutation model) we systematically alter spatial constraints and cell mixing rates to show how tissue structure influences functional (driver) mutations and genetic heterogeneity over time. This approach explores a key mechanism behind both inter-patient and intratumoral tumor heterogeneity: competition for space. Time-varying competition leads to an emergent transition from Darwinian premalignant growth to subsequent invasive neutral tumor growth. Initial spatial constraints determine the emergent mode of evolution (Darwinian to neutral) without a change in cell-specific mutation rate or fitness effects. Driver acquisition during the Darwinian precancerous stage may be modulated en route to neutral evolution by the combination of two factors: spatial constraints and limited cellular mixing. These two factors occur naturally in ductal carcinomas, where the branching topology of the ductal network dictates spatial constraints and mixing rates.

scholarly journals Tissue structure accelerates evolution: premalignant sweeps precede neutral expansion

2019 ◽  
Author(s):  
Jeffrey West ◽  
Ryan O. Schenck ◽  
Chandler Gatenbee ◽  
Mark Robertson-Tessi ◽  
Alexander R. A. Anderson
Keyword(s):  
Tissue Structure ◽  
Neutral Evolution ◽  
Driver Mutations ◽  
Tumor Evolution ◽  
Spatial And Temporal Patterns ◽  
Spatial Constraints ◽  
Continuous Growth ◽  
Two Factors ◽  
Early Expression ◽  
Dispersal Events

Cancer has been hypothesized to be a caricature of the renewal process of the tissue of origin: arising from (and maintained by) small subpopulations capable of continuous growth1. The strong influence of the tissue structure has been convincingly demonstrated in intestinal cancers where adenomas grow by the fission of stem-cell-maintained glands influenced by early expression of abnormal cell mobility in cancer progenitors2, 3. So-called “born to be bad” tumors arise from progenitors which may already possess the necessary driver mutations for malignancy4, 5 and metastasis6. These tumors subsequently evolve neutrally, thereby maximizing intratumoral heterogeneity and increasing the probability of therapeutic resistance. These findings have been nuanced by the advent of multi-region sequencing, which uses spatial and temporal patterns of genetic variation among competing tumor cell populations to shed light on the mode of tumor evolution (neutral or Darwinian) and also the tempo4, 7–11. Using a classic, well-studied model of tumor evolution (a passenger-driver mutation model12–16) we systematically alter spatial constraints and cell mixing rates to show how tissue structure influences functional (driver) mutations and genetic heterogeneity over time. This model approach explores a key mechanism behind both inter-patient and intratumoral tumor heterogeneity: competition for space. Initial spatial constraints determine the emergent mode of evolution (neutral to Darwinian) without a change in cell-specific mutation rate or fitness effects. Transition from early Darwinian to late neutral evolution is accelerated by the combination of two factors: spatial constraints and well-timed dispersal events.

Opposing Evolutionary Pressures Drive Clonal Evolution and Health Outcomes in the Aging Blood System

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 37-37
Author(s):  
Kimberly Skead ◽  
Armande Ang Houle ◽  
Sagi Abelson ◽  
Marie-Julie Fave ◽  
Boxi Lin ◽  
...  
Keyword(s):  
Gene Disruption ◽  
Large Scale ◽  
Evolutionary Dynamics ◽  
Clonal Evolution ◽  
Neutral Evolution ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Sequencing Data ◽  
High Coverage ◽  
Passenger Mutations

The age-associated accumulation of somatic mutations and large-scale structural variants (SVs) in the early hematopoietic hierarchy have been linked to premalignant stages for cancer and cardiovascular disease (CVD). However, only a small proportion of individuals harboring these mutations progress to disease, and mechanisms driving the transformation to malignancy remains unclear. Hematopoietic evolution, and cancer evolution more broadly, has largely been studied through a lens of adaptive evolution and the contribution of functionally neutral or mildly damaging mutations to early disease-associated clonal expansions has not been well characterised despite comprising the majority of the mutational burden in healthy or tumoural tissues. Through combining deep learning with population genetics, we interrogate the hematopoietic system to capture signatures of selection acting in healthy and pre-cancerous blood populations. Here, we leverage high-coverage sequencing data from healthy and pre-cancerous individuals from the European Prospective Investigation into Cancer and Nutrition Study (n=477) and dense genotyping from the Canadian Partnership for Tomorrow's Health (n=5,000) to show that blood rejects the paradigm of strictly adaptive or neutral evolution and is subject to pervasive negative selection. We observe clear age associations across hematopoietic populations and the dominant class of selection driving evolutionary dynamics acting at an individual level. We find that both the location and ratio of passenger to driver mutations are critical in determining if positive selection acting on driver mutations is able to overwhelm regulated hematopoiesis and allow clones harbouring disease-predisposing mutations to rise to dominance. Certain genes are enriched for passenger mutations in healthy individuals fitting purifying models of evolution, suggesting that the presence of passenger mutations in a subset of genes might confer a protective role against disease-predisposing clonal expansions. Finally, we find that the density of gene disruption events with known pathogenic associations in somatic SVs impacts the frequency at which the SV segregates in the population with variants displaying higher gene disruption density segregating at lower frequencies. Understanding how blood evolves towards malignancy will allow us to capture cancer in its earliest stages and identify events initiating departures from healthy blood evolution. Further, as the majority of mutations are passengers, studying their contribution to tumorigenesis, will unveil novel therapeutic targets thus enabling us to better understand patterns of clonal evolution in order to diagnose and treat disease in its infancy. Disclosures Dick: Bristol-Myers Squibb/Celgene: Research Funding.

scholarly journals Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios

2019 ◽  
Author(s):  
Marc J Williams ◽  
Luiz Zapata ◽  
Benjamin Werner ◽  
Chris Barnes ◽  
Andrea Sottoriva ◽  
...  
Keyword(s):  
Evolutionary Dynamics ◽  
Quantitative Model ◽  
Driver Mutations ◽  
Cancer Evolution ◽  
Sequencing Data ◽  
Synonymous Mutations ◽  
Fitness Effects ◽  
Somatic Evolution ◽  
Normal Oesophagus

AbstractThe distribution of fitness effects (DFE) defines how new mutations spread through an evolving population. The ratio of non-synonymous to synonymous mutations (dN/dS) has become a popular method to detect selection in somatic cells, however the link, in somatic evolution, between dN/dS values and fitness coefficients is missing. Here we present a quantitative model of somatic evolutionary dynamics that yields the selective coefficients from individual driver mutations from dN/dS estimates, and then measure the DFE for somatic mutant clones in ostensibly normal oesophagus and skin. We reveal a broad distribution of fitness effects, with the largest fitness increases found for TP53 and NOTCH1 mutants (proliferative bias 1-5%). Accurate measurement of the per-gene DFE in cancer evolution is precluded by the quality of currently available sequencing data. This study provides the theoretical link between dN/dS values and selective coefficients in somatic evolution, and reveals the DFE for mutations in human tissues.

scholarly journals Extensive subclonal mutational diversity in human colorectal cancer and its significance

2019 ◽  
Vol 116 (52) ◽  
pp. 26863-26872 ◽  
Author(s):  
Lawrence A. Loeb ◽  
Brendan F. Kohrn ◽  
Kaitlyn J. Loubet-Senear ◽  
Yasmin J. Dunn ◽  
Eun Hyun Ahn ◽  
...  
Keyword(s):  
Mutation Rate ◽  
Malignant Cell ◽  
Neutral Evolution ◽  
Driver Mutations ◽  
Accurate Estimation ◽  
Tumor Evolution ◽  
Wild Type ◽  
Mutation Burden ◽  
Genes Encoding ◽  
Subclonal Mutation

Human colorectal cancers (CRCs) contain both clonal and subclonal mutations. Clonal driver mutations are positively selected, present in most cells, and drive malignant progression. Subclonal mutations are randomly dispersed throughout the genome, providing a vast reservoir of mutant cells that can expand, repopulate the tumor, and result in the rapid emergence of resistance, as well as being a major contributor to tumor heterogeneity. Here, we apply duplex sequencing (DS) methodology to quantify subclonal mutations in CRC tumor with unprecedented depth (104) and accuracy (<10−7). We measured mutation frequencies in genes encoding replicative DNA polymerases and in genes frequently mutated in CRC, and found an unexpectedly high effective mutation rate, 7.1 × 10−7. The curve of subclonal mutation accumulation as a function of sequencing depth, using DNA obtained from 5 different tumors, is in accord with a neutral model of tumor evolution. We present a theoretical approach to model neutral evolution independent of the infinite-sites assumption (which states that a particular mutation arises only in one tumor cell at any given time). Our analysis indicates that the infinite-sites assumption is not applicable once the number of tumor cells exceeds the reciprocal of the mutation rate, a circumstance relevant to even the smallest clinically diagnosable tumor. Our methods allow accurate estimation of the total mutation burden in clinical cancers. Our results indicate that no DNA locus is wild type in every malignant cell within a tumor at the time of diagnosis (probability of all cells being wild type, 10−308).

scholarly journals Genealogies in Growing Solid Tumors

2018 ◽  
Author(s):  
Duke U. Rick Durrett
Keyword(s):  
Evolutionary Dynamics ◽  
Big Bang ◽  
Two Dimensions ◽  
Three Dimensions ◽  
Driver Mutations ◽  
Tumor Evolution ◽  
Alternative Theory ◽  
The Past ◽  
Fitness Advantage ◽  
Expanding Population

AbstractOver the past two decades, the theory of tumor evolution has largely focused on the selective sweeps model. According to this theory, tumors evolve by a succession of clonal expansions that are initiated by driver mutations that have a fitness advantage over the resident types. A 2015 study of colon cancer [44] has suggested an alternative theory of tumor evolution, the so-called Big Bang model, in which all of the necessary driver mutations are acquired before expansion began, and the evolutionary dynamics within the expanding population are predominantly neutral. In this paper, we will describe a simple mathematical model inspired by work of Hallatschek and Nelson [25] that makes quantitative predictions about spatial patterns of genetic variability. While this model has some success in matching observed patterns in two dimensions, it fails miserably in three dimensions. Despite this failure, we think the model analyzed here will be a useful first step in building an accurate model.

scholarly journals Genotype patterns in growing solid tumors

2018 ◽  
Author(s):  
Mridu Nanda ◽  
Rick Durrett ◽  
U Harvard ◽  
U Duke
Keyword(s):  
Evolutionary Dynamics ◽  
Big Bang ◽  
Driver Mutations ◽  
Tumor Evolution ◽  
Alternative Theory ◽  
Cancer Data ◽  
The Past ◽  
Big Bang Model ◽  
Expanding Population ◽  
Colon Cancer Data

AbstractOver the past decade, the theory of tumor evolution has largely focused on the selective sweeps model. According to this theory, tumors evolve by a succession of clonal expansions that are initiated by driver mutations. In a 2015 analysis of colon cancer data, Sottoriva et al [34] proposed an alternative theory of tumor evolution, the so-called Big Bang model, in which one or more driver mutations are acquired by the founder gland, and the evolutionary dynamics within the expanding population are predominantly neutral. In this paper we will describe a simple mathematical model that reproduces qualitative features of the observed paatterns of genetic variability and makes quantitative predictions.

scholarly journals Revisiting the tumorigenesis timeline with a data-driven generative model

2019 ◽  
Vol 117 (2) ◽  
pp. 857-864 ◽  
Author(s):  
Kamel Lahouel ◽  
Laurent Younes ◽  
Ludmila Danilova ◽  
Francis M. Giardiello ◽  
Ralph H. Hruban ◽  
...  
Keyword(s):  
Evolutionary Dynamics ◽  
Mechanistic Explanation ◽  
Driver Mutations ◽  
Tumor Evolution ◽  
Early Event ◽  
Driver Gene ◽  
Driver Genes ◽  
Fitness Advantage ◽  
Sequencing Studies ◽  
Cancer Types

Cancer is driven by the sequential accumulation of genetic and epigenetic changes in oncogenes and tumor suppressor genes. The timing of these events is not well understood. Moreover, it is currently unknown why the same driver gene change appears as an early event in some cancer types and as a later event, or not at all, in others. These questions have become even more topical with the recent progress brought by genome-wide sequencing studies of cancer. Focusing on mutational events, we provide a mathematical model of the full process of tumor evolution that includes different types of fitness advantages for driver genes and carrying-capacity considerations. The model is able to recapitulate a substantial proportion of the observed cancer incidence in several cancer types (colorectal, pancreatic, and leukemia) and inherited conditions (Lynch and familial adenomatous polyposis), by changing only 2 tissue-specific parameters: the number of stem cells in a tissue and its cell division frequency. The model sheds light on the evolutionary dynamics of cancer by suggesting a generalized early onset of tumorigenesis followed by slow mutational waves, in contrast to previous conclusions. Formulas and estimates are provided for the fitness increases induced by driver mutations, often much larger than previously described, and highly tissue dependent. Our results suggest a mechanistic explanation for why the selective fitness advantage introduced by specific driver genes is tissue dependent.

scholarly journals Measuring the distribution of fitness effects in somatic evolution by combining clonal dynamics with dN/dS ratios

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Marc J Williams ◽  
Luis Zapata ◽  
Benjamin Werner ◽  
Chris P Barnes ◽  
Andrea Sottoriva ◽  
...  
Keyword(s):  
Evolutionary Dynamics ◽  
Quantitative Model ◽  
Driver Mutations ◽  
Broad Distribution ◽  
Synonymous Mutations ◽  
Fitness Effects ◽  
Somatic Evolution ◽  
Normal Oesophagus ◽  
Somatic Mutant ◽  
New Mutations

The distribution of fitness effects (DFE) defines how new mutations spread through an evolving population. The ratio of non-synonymous to synonymous mutations (dN/dS) has become a popular method to detect selection in somatic cells. However the link, in somatic evolution, between dN/dS values and fitness coefficients is missing. Here we present a quantitative model of somatic evolutionary dynamics that determines the selective coefficients of individual driver mutations from dN/dS estimates. We then measure the DFE for somatic mutant clones in ostensibly normal oesophagus and skin. We reveal a broad distribution of fitness effects, with the largest fitness increases found for TP53 and NOTCH1 mutants (proliferative bias 1–5%). This study provides the theoretical link between dN/dS values and selective coefficients in somatic evolution, and measures the DFE of mutations in human tissues.

scholarly journals Tumour heterogeneity and evolutionary dynamics in colorectal cancer

Oncogenesis ◽  
2021 ◽  
Vol 10 (7) ◽  
Author(s):  
Dedrick Kok Hong Chan ◽  
Simon James Alexander Buczacki
Keyword(s):  
Colorectal Cancer ◽  
Cancer Progression ◽  
Evolutionary Dynamics ◽  
Big Bang ◽  
Complex Model ◽  
Neutral Evolution ◽  
Driver Mutations ◽  
Current Evidence ◽  
Tumour Heterogeneity ◽  
Driver Genes

AbstractColorectal cancer (CRC) has a global burden of disease. Our current understanding of CRC has progressed from initial discoveries which focused on the stepwise accumulation of key driver mutations, as encapsulated in the Vogelstein model, to one in which marked heterogeneity leads to a complex interplay between clonal populations. Current evidence suggests that an initial explosion, or “Big Bang”, of genetic diversity is followed by a period of neutral dynamics. A thorough understanding of this interplay between clonal populations during neutral evolution gives insights into the roles in which driver genes may participate in the progress from normal colonic epithelium to adenoma and carcinoma. Recent advances have focused not only on genetics, transcriptomics, and proteomics but have also investigated the ecological and evolutionary processes which transform normal cells into cancer. This review first describes the role which driver mutations play in the Vogelstein model and subsequently demonstrates the evidence which supports a more complex model. This article also aims to underscore the significance of tumour heterogeneity and diverse clonal populations in cancer progression.

scholarly journals Clonal approaches to understanding the impact of mutations on hematologic disease development

Blood ◽  
2019 ◽  
Vol 133 (13) ◽  
pp. 1436-1445 ◽  
Author(s):  
Jyoti Nangalia ◽  
Emily Mitchell ◽  
Anthony R. Green
Keyword(s):  
Somatic Mutations ◽  
Clonal Selection ◽  
Single Cells ◽  
Driver Mutations ◽  
Great Promise ◽  
Tumor Evolution ◽  
Disease Development ◽  
Hematopoietic Tissue ◽  
The Impact

Abstract Interrogation of hematopoietic tissue at the clonal level has a rich history spanning over 50 years, and has provided critical insights into both normal and malignant hematopoiesis. Characterization of chromosomes identified some of the first genetic links to cancer with the discovery of chromosomal translocations in association with many hematological neoplasms. The unique accessibility of hematopoietic tissue and the ability to clonally expand hematopoietic progenitors in vitro has provided fundamental insights into the cellular hierarchy of normal hematopoiesis, as well as the functional impact of driver mutations in disease. Transplantation assays in murine models have enabled cellular assessment of the functional consequences of somatic mutations in vivo. Most recently, next-generation sequencing–based assays have shown great promise in allowing multi-“omic” characterization of single cells. Here, we review how clonal approaches have advanced our understanding of disease development, focusing on the acquisition of somatic mutations, clonal selection, driver mutation cooperation, and tumor evolution.

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