Tumour heterogeneity and evolutionary dynamics in colorectal cancer

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.

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Integrated multi-omics analyses on patient-derived CRC organoids highlight altered molecular pathways in colorectal cancer progression involving PTEN

Journal of Experimental & Clinical Cancer Research ◽

10.1186/s13046-021-01986-8 ◽

2021 ◽

Vol 40 (1) ◽

Author(s):

Marta Codrich ◽

Emiliano Dalla ◽

Catia Mio ◽

Giulia Antoniali ◽

Matilde Clarissa Malfatti ◽

...

Keyword(s):

Colorectal Cancer ◽

Cancer Progression ◽

Cell Model ◽

Patient Specific ◽

Driver Genes ◽

Proteomic Data ◽

Whole Exome ◽

Molecular Stability ◽

Culturing Conditions ◽

Colorectal Cancer Progression

Abstract Background Colorectal cancer (CRC) represents the fourth leading cause of cancer-related deaths. The heterogeneity of CRC identity limits the usage of cell lines to study this type of tumor because of the limited representation of multiple features of the original malignancy. Patient-derived colon organoids (PDCOs) are a promising 3D-cell model to study tumor identity for personalized medicine, although this approach still lacks detailed characterization regarding molecular stability during culturing conditions. Correlation analysis that considers genomic, transcriptomic, and proteomic data, as well as thawing, timing, and culturing conditions, is missing. Methods Through integrated multi–omics strategies, we characterized PDCOs under different growing and timing conditions, to define their ability to recapitulate the original tumor. Results Whole Exome Sequencing allowed detecting temporal acquisition of somatic variants, in a patient-specific manner, having deleterious effects on driver genes CRC-associated. Moreover, the targeted NGS approach confirmed that organoids faithfully recapitulated patients’ tumor tissue. Using RNA-seq experiments, we identified 5125 differentially expressed transcripts in tumor versus normal organoids at different time points, in which the PTEN pathway resulted of particular interest, as also confirmed by further phospho-proteomics analysis. Interestingly, we identified the PTEN c.806_817dup (NM_000314) mutation, which has never been reported previously and is predicted to be deleterious according to the American College of Medical Genetics and Genomics (ACMG) classification. Conclusion The crosstalk of genomic, transcriptomic and phosphoproteomic data allowed to observe that PDCOs recapitulate, at the molecular level, the tumor of origin, accumulating mutations over time that potentially mimic the evolution of the patient’s tumor, underlining relevant potentialities of this 3D model.

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Stochastic fluctuations drive non-genetic evolution of proliferation in clonal cancer cell populations

10.1101/2021.06.08.447479 ◽

2021 ◽

Author(s):

Carmen Ortega-Sabater ◽

Gabriel Fernandez-Calvo ◽

Víctor M Pérez-García

Keyword(s):

Evolutionary Dynamics ◽

Growth Dynamics ◽

Driver Mutations ◽

Organizational Changes ◽

Tumour Heterogeneity ◽

Stochastic Fluctuations ◽

Oncological Patients ◽

Single Genotype ◽

History Of ◽

Broad Variety

Evolutionary dynamics allows to understand many changes happening in a broad variety of biological systems, ranging from individuals to complete ecosystems. It is also behind a number of remarkable organizational changes that happen during the natural history of cancers. These reflect tumour heterogeneity, which is present at all cellular levels, including the genome, proteome and phenome, shaping its development and interrelation with its environment. An intriguing observation in different cohorts of oncological patients is that tumours exhibit an increased proliferation as the disease progresses, while the timescales involved are apparently too short for the fixation of sufficient driver mutations to promote an explosive growth. In this paper we discuss how phenotypic plasticity, emerging from a single genotype, may play a key role and provide a ground for a continuous acceleration of the proliferation rate of clonal populations with time. Here we address this question by means of stochastic and deterministic mathematical models that capture proliferation trait heterogeneity in clonal populations and elucidate the contribution of phenotypic transitions on tumour growth dynamics.

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Mutational analysis of driver genes with tumor suppressive and oncogenic roles in gastric cancer

PeerJ ◽

10.7717/peerj.3585 ◽

2017 ◽

Vol 5 ◽

pp. e3585 ◽

Cited By ~ 2

Author(s):

Tianfang Wang ◽

Yining Liu ◽

Min Zhao

Keyword(s):

Gastric Cancer ◽

Cancer Progression ◽

Complex Disease ◽

Mutational Analysis ◽

Driver Mutations ◽

Driver Genes ◽

Protein Coding ◽

Mirna Genes ◽

Genetic Mechanisms ◽

New Treatment

Gastric cancer (GC) is a complex disease with heterogeneous genetic mechanisms. Genomic mutational profiling of gastric cancer not only expands our knowledge about cancer progression at a fundamental genetic level, but also could provide guidance on new treatment decisions, currently based on tumor histology. The fact that precise medicine-based treatment is successful in a subset of tumors indicates the need for better identification of clinically related molecular tumor phenotypes, especially with regard to those driver mutations on tumor suppressor genes (TSGs) and oncogenes (ONGs). We surveyed 313 TSGs and 160 ONGs associated with 48 protein coding and 19 miRNA genes with both TSG and ONG roles. Using public cancer mutational profiles, we confirmed the dual roles of CDKN1A and CDKN1B. In addition to the widely recognized alterations, we identified another 82 frequently mutated genes in public gastric cancer cohort. In summary, these driver mutation profiles of individual GC will form the basis of personalized treatment of gastric cancer, leading to substantial therapeutic improvements.

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

Blood ◽

10.1182/blood-2020-142086 ◽

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.

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MRN (MRE11-RAD50-NBS1) Complex in Human Cancer and Prognostic Implications in Colorectal Cancer

International Journal of Molecular Sciences ◽

10.3390/ijms20040816 ◽

2019 ◽

Vol 20 (4) ◽

pp. 816 ◽

Cited By ~ 15

Author(s):

Yiling Situ ◽

Liping Chung ◽

Cheok Lee ◽

Vincent Ho

Keyword(s):

Colorectal Cancer ◽

Cancer Progression ◽

Human Cancer ◽

Progression Free Survival ◽

Current Evidence ◽

Treatment Target ◽

Free Survival ◽

Mrn Complex ◽

Prognostic Implications ◽

Relationship Of

The MRE11-RAD50-NBS1 (MRN) complex has been studied in multiple cancers. The identification of MRN complex mutations in mismatch repair (MMR)-defective cancers has sparked interest in its role in colorectal cancer (CRC). To date, there is evidence indicating a relationship of MRN expression with reduced progression-free survival, although the significance of the MRN complex in the clinical setting remains controversial. In this review, we present an overview of the function of the MRN complex, its role in cancer progression, and current evidence in colorectal cancer. The evidence indicates that the MRN complex has potential utilisation as a biomarker and as a putative treatment target to improve outcomes of colorectal cancer.

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Scarcity of Recurrent Regulatory Driver Mutations in Colorectal Cancer Revealed by Targeted Deep Sequencing

JNCI Cancer Spectrum ◽

10.1093/jncics/pkz012 ◽

2019 ◽

Vol 3 (2) ◽

Author(s):

Rebecca C Poulos ◽

Dilmi Perera ◽

Deborah Packham ◽

Anushi Shah ◽

Caroline Janitz ◽

...

Keyword(s):

Colorectal Cancer ◽

Excision Repair ◽

Regulatory Elements ◽

Driver Mutations ◽

Gene Promoters ◽

Driver Genes ◽

Panel Testing ◽

Target Capture ◽

Target Capture Sequencing ◽

Capture Sequencing

Abstract Background Genetic testing of cancer samples primarily focuses on protein-coding regions, despite most mutations arising in noncoding DNA. Noncoding mutations can be pathogenic if they disrupt gene regulation, but the benefits of assessing promoter mutations in driver genes by panel testing has not yet been established. This is especially the case in colorectal cancer, for which few putative driver variants at regulatory elements have been reported. Methods We designed a unique target capture sequencing panel of 39 colorectal cancer driver genes and their promoters, together with more than 35 megabases of regulatory elements focusing on gene promoters. Using this panel, we sequenced 95 colorectal cancer and matched normal samples at high depth, averaging 170× and 82× coverage, respectively. Results Our target capture sequencing design enabled improved coverage and variant detection across captured regions. We found cases with hereditary defects in mismatch and base excision repair due to deleterious germline coding variants, and we identified mutational spectra consistent with these repair deficiencies. Focusing on gene promoters and other regulatory regions, we found little evidence for base or region-specific recurrence of functional somatic mutations. Promoter elements, including TERT, harbored few mutations, with none showing strong functional evidence. Recurrent regulatory mutations were rare in our sequenced regions in colorectal cancer, though we highlight some candidate mutations for future functional studies. Conclusions Our study supports recent findings that regulatory driver mutations are rare in many cancer types and suggests that the inclusion of promoter regions into cancer panel testing is currently likely to have limited clinical utility in colorectal cancer.

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Assessment of the evolutionary consequence of putative driver mutations in colorectal cancer with spatial multiomic data

10.1101/2021.07.14.451265 ◽

2021 ◽

Author(s):

Andrea Sottoriva ◽

Trevor A Graham ◽

Timon Heide ◽

Jacob Househam ◽

George D Cresswell ◽

...

Keyword(s):

Genomic Medicine ◽

Genetic Alterations ◽

Neutral Evolution ◽

Driver Mutations ◽

Sufficient Data ◽

Driver Genes ◽

Phenotypic Properties ◽

Evolutionary Consequence ◽

Selective Evolution

Cancer genomic medicine relies on targeting driver genes. However, current catalogues of cancer drivers are mostly based on indirect measurements of mutation frequencies, positions or types, rather than their effect on clonal expansions in vivo. Moreover, nongenetic drivers are largely unknown, as are the epigenetic and transcriptomic effects of genetic drivers. Here we perform spatial computational inference on multiomic data with matched whole-genome sequencing, ATAC-seq and RNA-seq. Using 436 samples, we directly quantify the contribution, or lack thereof, of putative driver genes to subclonal expansions in vivo in 30 colorectal carcinomas (4-33 samples per patient, median=15). Although subclonal neutral evolution was widespread (13/26 cases with sufficient data), there were cases with clear evidence of subclonal selection (6/26) in which we measured epigenetic and transcriptomic differences between subclones in vivo. In 7/26 cases we could not distinguish between neutral or selective evolution with the available data. We identified expanding subclones that were not driven by known genetic alterations, and propose candidate epigenetic drivers. We identified the distinguishing patterns of genomic heterogeneity produced in fast, exponentially growing tumours (7/26) versus neoplasms growing only at the periphery (19/26), as well as identifying clonally intermixed (16/28 cases with sufficient data) versus segregated malignancies (10/28). Our model-based approach measures genetic and non-genetic subclonal selection, or lack thereof, in space and time and allows in vivo comparisons of the emergent phenotypic properties of subclones within human tumours.

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Mathematical Model of Colorectal Cancer Initiation

10.1101/2020.02.08.939603 ◽

2020 ◽

Author(s):

Chay Paterson ◽

Hans Clevers ◽

Ivana Bozic

Keyword(s):

Colorectal Cancer ◽

Mathematical Model ◽

Evolutionary Dynamics ◽

Epidemiological Data ◽

Premalignant Lesions ◽

Measured Parameter ◽

Driver Genes ◽

Effective Strategies ◽

Cancer Initiation ◽

Parameter Values

ABSTRACTQuantifying evolutionary dynamics of cancer initiation and progression can provide insights into more effective strategies of early detection and treatment. Here we develop a mathematical model of colorectal cancer initiation through inactivation of two tumor suppressor genes and activation of one oncogene, accounting for the well-known path to colorectal cancer through loss of tumor suppressors APC and TP53, and gain of the KRAS oncogene. In the model, we allow mutations to occur in any order, leading to a complex network of incomplete mutational genotypes on the way to colorectal cancer. We parametrize the model using experimentally measured parameter values, many of them only recently available, and compare its predictions to epidemiological data on colorectal cancer incidence. We find that the reported incidence of colorectal cancer can be recovered using a mathematical model of colorectal cancer initiation together with experimentally measured mutation rates in colorectal tissues and proliferation rates of premalignant lesions. We demonstrate that the order of driver events in colorectal cancer is determined by the combined effect of the rates at which driver genes are mutated and the fitness effects they provide. Our results imply that there may not be significant immune suppression of untreated benign and malignant colorectal lesions.

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Genealogies in Growing Solid Tumors

10.1101/244160 ◽

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.

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Malignant transformation and genetic alterations are uncoupled in early colorectal cancer progression

BMC Biology ◽

10.1186/s12915-020-00844-x ◽

2020 ◽

Vol 18 (1) ◽

Author(s):

Soulafa Mamlouk ◽

Tincy Simon ◽

Laura Tomás ◽

David C. Wedge ◽

Alexander Arnold ◽

...

Keyword(s):

Colorectal Cancer ◽

Cancer Progression ◽

Genetic Alterations ◽

Driver Mutations ◽

Early Colorectal Cancer ◽

High Grade ◽

Neoplastic Progression ◽

Genetic Changes ◽

Chromosome 20 ◽

Genetic Profiles

Abstract Background Colorectal cancer (CRC) development is generally accepted as a sequential process, with genetic mutations determining phenotypic tumor progression. However, matching genetic profiles with histological transition requires the analyses of temporal samples from the same patient at key stages of progression. Results Here, we compared the genetic profiles of 34 early carcinomas with their respective adenomatous precursors to assess timing and heterogeneity of driver alterations accompanying the switch from benign adenoma to malignant carcinoma. In almost half of the cases, driver mutations specific to the carcinoma stage were not observed. In samples where carcinoma-specific alterations were present, TP53 mutations and chromosome 20 copy gains commonly accompanied the switch from adenomatous tissue to carcinoma. Remarkably, 40% and 50% of high-grade adenomas shared TP53 mutations and chromosome 20 gains, respectively, with their matched carcinomas. In addition, multi-regional analyses revealed greater heterogeneity of driver mutations in adenomas compared to their matched carcinomas. Conclusion Genetic alterations in TP53 and chromosome 20 occur at the earliest histological stage in colorectal carcinomas (pTis and pT1). However, high-grade adenomas can share these alterations despite their histological distinction. Based on the well-defined sequence of CRC development, we suggest that the timing of genetic changes during neoplastic progression is frequently uncoupled from histological progression.

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