New paradigms in clonal evolution: punctuated equilibrium in cancer

The evolutionary theory of cancer: challenges and potential solutions

The clonal evolution model of cancer was developed in the 1950s-1970s and became central to cancer biology in the twenty-first century, largely through studies of cancer genetics. Although it has proven its worth, its structure has been challenged by observations of phenotypic plasticity, non-genetic forms of inheritance, non-genetic determinants of clone fitness and non-tree-like transmission of genes. There is even confusion about the definition of a clone, which we aim to resolve. The performance and value of the clonal evolution model depends on the empirical extent to which evolutionary processes are involved in cancer, and on its theoretical ability to account for those evolutionary processes. Here, we identify limits in the theoretical performance of the clonal evolution model and provide solutions to overcome those limits. Although we do not claim that clonal evolution can explain everything about cancer, we show how many of the complexities that have been identified in the dynamics of cancer can be integrated into the model to improve our current understanding of cancer.

Heterogeneity generating capacity in tumorigenesis and cancer therapeutics

Cells of multicellular organisms generate heterogeneity in a controlled and transient fashion during embryogenesis, which can be reactivated in pathologies such as cancer. Although genomic heterogeneity is an important part of tumorigenesis, continuous generation of phenotypic heterogeneity is central for the adaptation of cancer cells to the challenges of tumorigenesis and response to therapy. Here I discuss the capacity of generating heterogeneity, hereafter called cell hetness, in cancer cells both as the activation of hetness oncogenes and inactivation of hetness tumor suppressor genes, which increase the generation of heterogeneity, ultimately producing an increase in adaptability and cell fitness. Transcriptomic high hetness states in therapy-tolerant cell states denote its importance in cancer resistance to therapy. The definition of the concept of hetness will allow the understanding of its origins, its control during embryogenesis, its loss of control in tumorigenesis and cancer therapeutics and its active targeting.

Luminal breast epithelial cells from wildtype and BRCA mutation carriers harbor copy number alterations commonly associated with breast cancer

Cancer-associated mutations have been documented in normal tissues, but the prevalence and nature of somatic copy number alterations and their role in tumor initiation and evolution is not well understood. Here, using single cell DNA sequencing, we describe the landscape of CNAs in >42,000 breast epithelial cells from women with normal or high risk of developing breast cancer. Accumulation of individual cells with one or two of a specific subset of CNAs (e.g. 1q gain and 16q, 22q, 7q, and 10q loss) is detectable in almost all breast tissues and, in those from BRCA1 or BRCA2 mutations carriers, occurs prior to loss of heterozygosity (LOH) of the wildtype alleles. These CNAs, which are among the most common associated with ductal carcinoma in situ (DCIS) and malignant breast tumors, are enriched almost exclusively in luminal cells not basal myoepithelial cells. Allele-specific analysis of the enriched CNAs reveals that each allele was independently altered, demonstrating convergent evolution of these CNAs in an individual breast. Tissues from BRCA1 or BRCA2 mutation carriers contain a small percentage of cells with extreme aneuploidy, featuring loss of TP53 , LOH of BRCA1 or BRCA2 , and multiple breast cancer-associated CNAs in addition to one or more of the common CNAs in 1q, 10q or 16q. Notably, cells with intermediate levels of CNAs are not detected, arguing against a stepwise gradual accumulation of CNAs. Overall, our findings demonstrate that chromosomal alterations in normal breast epithelium partially mirror those of established cancer genomes and are chromosome- and cell lineage-specific.

Single-mitosis dissection of acute and chronic DNA mutagenesis and repair

How chronic mutational processes and punctuated bursts of DNA damage drive evolution of the cancer genome is poorly understood. Here, we demonstrate a strategy to disentangle and quantify distinct mechanisms underlying genome evolution in single cells, during single mitoses and at single-strand resolution. To distinguish between chronic (reactive oxygen species (ROS)) and acute (ultraviolet light (UV)) mutagenesis, we microfluidically separate pairs of sister cells from the first mitosis following burst UV damage. Strikingly, UV mutations manifest as sister-specific events, revealing mirror-image mutation phasing genome-wide. In contrast, ROS mutagenesis in transcribed regions is reduced strand agnostically. Successive rounds of genome replication over persisting UV damage drives multiallelic variation at CC dinucleotides. Finally, we show that mutation phasing can be resolved to single strands across the entire genome of liver tumors from F1 mice. This strategy can be broadly used to distinguish the contributions of overlapping cancer relevant mutational processes.

Decoding Cancer Evolution: Integrating Genetic and Non-Genetic Insights

The development of cancer begins with cells transitioning from their multicellular nature to a state akin to unicellular organisms. This shift leads to a breakdown in the crucial regulators inherent to multicellularity, resulting in the emergence of diverse cancer cell subpopulations that have enhanced adaptability. The presence of different cell subpopulations within a tumour, known as intratumoural heterogeneity (ITH), poses challenges for cancer treatment. In this review, we delve into the dynamics of the shift from multicellularity to unicellularity during cancer onset and progression. We highlight the role of genetic and non-genetic factors, as well as tumour microenvironment, in promoting ITH and cancer evolution. Additionally, we shed light on the latest advancements in omics technologies that allow for in-depth analysis of tumours at the single-cell level and their spatial organization within the tissue. Obtaining such detailed information is crucial for deepening our understanding of the diverse evolutionary paths of cancer, allowing for the development of effective therapies targeting the key drivers of cancer evolution.

Transcriptomic Maps of Colorectal Liver Metastasis: Machine Learning of Gene Activation Patterns and Epigenetic Trajectories in Support of Precision Medicine

The molecular mechanisms of the liver metastasis of colorectal cancer (CRLM) remain poorly understood. Here, we applied machine learning and bioinformatics trajectory inference to analyze a gene expression dataset of CRLM. We studied the co-regulation patterns at the gene level, the potential paths of tumor development, their functional context, and their prognostic relevance. Our analysis confirmed the subtyping of five liver metastasis subtypes (LMS). We provide gene-marker signatures for each LMS, and a comprehensive functional characterization that considers both the hallmarks of cancer and the tumor microenvironment. The ordering of CRLMs along a pseudotime-tree revealed a continuous shift in expression programs, suggesting a developmental relationship between the subtypes. Notably, trajectory inference and personalized analysis discovered a range of epigenetic states that shape and guide metastasis progression. By constructing prognostic maps that divided the expression landscape into regions associated with favorable and unfavorable prognoses, we derived a prognostic expression score. This was associated with critical processes such as epithelial-mesenchymal transition, treatment resistance, and immune evasion. These factors were associated with responses to neoadjuvant treatment and the formation of an immuno-suppressive, mesenchymal state. Our machine learning-based molecular profiling provides an in-depth characterization of CRLM heterogeneity with possible implications for treatment and personalized diagnostics.

Cancer Risk in Barrett's Esophagus: A Clinical Review

Esophageal adenocarcinoma (EAC) is rapidly increasing in incidence and is associated with a poor prognosis. Barrett's esophagus (BE) is a known precursor of esophageal adenocarcinoma. This review aims to explore Barrett's esophagus, esophageal adenocarcinoma, and the progression from the former to the latter. An overview of the definition, diagnosis, epidemiology, and risk factors for both entities are presented, with special attention being given to the areas of debate in the literature. The progression from Barrett's esophagus to esophageal adenocarcinoma is reviewed and the relevant molecular pathways are discussed. The definition of Barrett's esophagus remains debated and without international consensus. This, alongside other factors, has made establishing the true prevalence of Barrett's esophagus challenging. The degree of dysplasia can be a histological challenge, but is necessary to guide clinical management. The progression of BE to EAC is likely driven by inflammatory pathways, pepsin exposure, upregulation of growth factor pathways, and mitochondrial changes. Surveillance is maintained through serial endoscopic evaluation, with shorter intervals recommended for high-risk features.

Rapid acquisition of microorganisms and microbial genes can help explain punctuated evolution

The punctuated mode of evolution posits that evolution occurs in rare bursts of rapid evolutionary change followed by long periods of genetic stability (stasis). The accepted cause for the rapid changes in punctuated evolution is special ecological circumstances – selection forces brought about by changes in the environment. This article presents a complementary explanation for punctuated evolution by the rapid formation of genetic variants in animals and plants by the acquisition of microorganisms from the environment into microbiomes and microbial genes into host genomes by horizontal gene transfer. Several examples of major evolutionary events driven by microorganisms are discussed, including the formation of the first eukaryotic cell, the ability of some animals to digest cellulose and other plant cell-wall complex polysaccharides, dynamics of root system architecture, and the formation of placental mammals. These changes by cooperation were quantum leaps in the evolutionary development of complex bilolgical systems and can contribute to an understanding of the mechanisms underlying punctuated evolution.

The Genetic Evolution of Metastasis

Cancer is an evolutionary process that is characterized by the emergence of multiple genetically distinct populations or clones within the primary tumor. Intratumor heterogeneity provides a substrate for the selection of adaptive clones, such as those that lead to metastasis. Comparative molecular studies of primary tumors and metastases have identified distinct genomic features associated with the development of metastases. In this review, we discuss how these insights could inform clinical decision-making and uncover rational antimetastasis treatment strategies.

Somatic Genomic Testing in Patients With Metastatic or Advanced Cancer: ASCO Provisional Clinical Opinion

PURPOSE

An ASCO provisional clinical opinion offers timely clinical direction to ASCO's membership following publication or presentation of potentially practice-changing data from major studies. This provisional clinical opinion addresses the appropriate use of tumor genomic testing in patients with metastatic or advanced solid tumors.

CLINICAL CONTEXT

An increasing number of therapies are approved to treat cancers harboring specific genomic biomarkers. However, there is a lack of clarity as to when tumor genomic sequencing should be ordered, what type of assays should be performed, and how to interpret the results for treatment selection.

PROVISIONAL CLINICAL OPINION

Patients with metastatic or advanced cancer should undergo genomic sequencing in a certified laboratory if the presence of one or more specific genomic alterations has regulatory approval as biomarkers to guide the use of or exclusion from certain treatments for their disease. Multigene panel-based assays should be used if more than one biomarker-linked therapy is approved for the patient's disease. Site-agnostic approvals for any cancer with a high tumor mutation burden, mismatch repair deficiency, or neurotrophic tyrosine receptor kinase (NTRK) fusions provide a rationale for genomic testing for all solid tumors. Multigene testing may also assist in treatment selection by identifying additional targets when there are few or no genotype-based therapy approvals for the patient's disease. For treatment planning, the clinician should consider the functional impact of the targeted alteration and expected efficacy of genomic biomarker-linked options relative to other approved or investigational treatments.Additional information is available at www.asco.org/assays-and-predictive-markers-guidelines.

Cancer evolution: Darwin and beyond

Clinical and laboratory studies over recent decades have established branched evolution as a feature of cancer. However, while grounded in somatic selection, several lines of evidence suggest a Darwinian model alone is insufficient to fully explain cancer evolution. First, the role of macroevolutionary events in tumour initiation and progression contradicts Darwin's central thesis of gradualism. Whole-genome doubling, chromosomal chromoplexy and chromothripsis represent examples of single catastrophic events which can drive tumour evolution. Second, neutral evolution can play a role in some tumours, indicating that selection is not always driving evolution. Third, increasing appreciation of the role of the ageing soma has led to recent generalised theories of age-dependent carcinogenesis. Here, we review these concepts and others, which collectively argue for a model of cancer evolution which extends beyond Darwin. We also highlight clinical opportunities which can be grasped through targeting cancer vulnerabilities arising from non-Darwinian patterns of evolution.

The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer

Evolutionary game theory mathematically conceptualizes and analyzes biological interactions where one's fitness not only depends on one's own traits, but also on the traits of others. Typically, the individuals are not overtly rational and do not select, but rather inherit their traits. Cancer can be framed as such an evolutionary game, as it is composed of cells of heterogeneous types undergoing frequency-dependent selection. In this article, we first summarize existing works where evolutionary game theory has been employed in modeling cancer and improving its treatment. Some of these game-theoretic models suggest how one could anticipate and steer cancer's eco-evolutionary dynamics into states more desirable for the patient via evolutionary therapies. Such therapies offer great promise for increasing patient survival and decreasing drug toxicity, as demonstrated by some recent studies and clinical trials. We discuss clinical relevance of the existing game-theoretic models of cancer and its treatment, and opportunities for future applications. Moreover, we discuss the developments in cancer biology that are needed to better utilize the full potential of game-theoretic models. Ultimately, we demonstrate that viewing tumors with evolutionary game theory has medically useful implications that can inform and create a lockstep between empirical findings and mathematical modeling. We suggest that cancer progression is an evolutionary competition between different cell types and therefore needs to be viewed as an evolutionary game.

Tumour heterogeneity and evolutionary dynamics in colorectal cancer

Colorectal 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.

Multi-ancestral origin of intestinal tumors: Impact on growth, progression, and drug efficacy

Background

Data are steadily accruing that demonstrate that intestinal tumors are frequently derived from multiple founding cells, resulting in tumors comprised of distinct ancestral clones that might cooperate or alternatively compete, thereby potentially impacting different phases of the disease process.

Aim

We sought to determine whether tumors with a multi‐ancestral architecture involving at least two distinct clones show increased tumor number, growth, progression, or resistance to drug intervention.

Methods

Mice carrying the Min allele of Apc were generated that were mosaic with only a subset of cells in the intestinal epithelium expressing an activated form of PI3K, a key regulatory kinase affecting several important cellular processes. These cells were identifiable as they fluoresced green, whereas all other cells fluoresced red.

Results

Cell lineage tracing revealed that many intestinal tumors from our mouse model were derived from at least two founding cells, those expressing the activated PI3K (green) and those which did not (red). Heterotypic tumors with a multi‐ancestral architecture as evidenced by a mixture of green and red cells exhibited increased tumor growth and invasiveness. Clonal architecture also had an impact on tumor response to low‐dose aspirin. Aspirin treatment resulted in a greater reduction of heterotypic tumors derived from multiple founding cells as compared to tumors derived from a single founding cell.

Conclusion

These data indicate that genetically distinct tumor‐founding cells can contribute to early intratumoral heterogeneity. The coevolution of the founding cells and their progeny enhances colon tumor progression and impacts the response to aspirin. These findings are important to a more complete understanding of tumorigenesis with consequences for several distinct models of tumor evolution. They also have practical implications to the clinic. Mouse models with heterogenous tumors are likely better for predicting drug efficacy as compared to models in which the tumors are highly homogeneous. Moreover, understanding how interactions among different populations in a single heterotypic tumor with a multi‐ancestral architecture impact response to a single agent and combination therapies are necessary to fully develop personalized medicine.

Predicting Colorectal Cancer Occurrence in IBD

Patients with colonic inflammatory bowel disease (IBD) are at an increased risk of developing colorectal cancer (CRC), and are therefore enrolled into a surveillance programme aimed at detecting dysplasia or early cancer. Current surveillance programmes are guided by clinical, endoscopic or histological predictors of colitis-associated CRC (CA-CRC). We have seen great progress in our understanding of these predictors of disease progression, and advances in endoscopic technique and management, along with improved medical care, has been mirrored by the falling incidence of CA-CRC over the last 50 years. However, more could be done to improve our molecular understanding of CA-CRC progression and enable better risk stratification for patients with IBD. This review summarises the known risk factors associated with CA-CRC and explores the molecular landscape that has the potential to complement and optimise the existing IBD surveillance programme.

Cancer Community Ecology

Here we advocate Cancer Community Ecology as a valuable focus of study in Cancer Biology. We hypothesize that the heterogeneity and characteristics of cancer cells within tumors should vary systematically in space and time and that cancer cells form local ecological communities within tumors. These communities possess limited numbers of species determined by local conditions, with each species in a community possessing predictable traits that enable them to cope with their particular environment and coexist with each other. We start with a discussion of concepts and assumptions that ecologists use to study closely related species. We then discuss the competitive exclusion principle as a means for knowing when two species should not coexist, and as an opening towards understanding how they can. We present the five major categories of mechanisms of coexistence that operate in nature and suggest that the same mechanisms apply towards understanding the diversification and coexistence of cancer cell species. They are: Food-Safety Tradeoffs, Diet Choice, Habitat Selection, Variance Partitioning, and Competition-Colonization Tradeoffs. For each mechanism, we discuss how it works in nature, how it might work in cancers, and its implications for therapy.

High Concordance of Genomic Profiles between Primary and Metastatic Colorectal Cancer

The comparison of the genetic profiles between primary and metastatic colorectal cancer (CRC) is needed to enable the discovery of useful therapeutic targets against metastatic CRCs. We performed the targeted next generation sequencing assay of 170 cancer-associated genes for 142 metastatic CRCs, including 95 pairs of primary and metastatic CRCs, to reveal their genomic characteristics and to assess the genetic heterogeneity. The most frequently mutated gene in primary and metastatic CRCs was APC (71% vs. 65%), TP53 (54% vs. 57%), KRAS (45% vs. 44%), PIK3CA (16% vs. 19%), SMAD4 (15% vs. 14%) and FBXW7 (11% vs. 11%). The concordance in the top six frequently mutated genes was 85%, on average. The overall mutation frequencies were consistent with two sets of public data (TCGA and MSKCC). To the author’s knowledge, this is the first study to compare the genetic profiles of our cohort with that of the metastatic CRCs from MSKCC. Comparative sequencing analysis between primary and metastatic CRCs revealed a high degree of genetic concordance in the current clinically actionable genes. Therefore, the genetic investigation of archived primary tumor samples with the challenges of obtaining an adequate sample from metastatic sites appears to be sufficient for the application of cancer precision medicine in the metastatic setting.

To portray clonal evolution in blood cancer, count your stem cells

Clonal evolution, the process of expansion and diversification of mutated cells, plays an important role in cancer development, resistance, and relapse. Although clonal evolution is most often conceived of as driven by natural selection, recent studies uncovered that neutral evolution shapes clonal evolution in a significant proportion of solid cancers. In hematological malignancies, the interplay between neutral evolution and natural selection is also disputed. Because natural selection selects cells with a greater fitness, providing a growth advantage to some cells relative to others, the architecture of clonal evolution serves as indirect evidence to distinguish natural selection from neutral evolution and has been associated with different prognoses for the patient. Linear architecture, when the new mutant clone grows within the previous one, is characteristic of hematological malignancies and is typically interpreted as being driven by natural selection. Here, we discuss the role of natural selection and neutral evolution in the production of linear clonal architectures in hematological malignancies. Although it is tempting to attribute linear evolution to natural selection, we argue that a lower number of contributing stem cells accompanied by genetic drift can also result in a linear pattern of evolution, as illustrated by simulations of clonal evolution in hematopoietic stem cells. The number of stem cells contributing to long-term clonal evolution is not known in the pathological context, and we advocate that estimating these numbers in the context of cancer and aging is crucial to parsing out neutral evolution from natural selection, 2 processes that require different therapeutic strategies.

Breast tumours maintain a reservoir of subclonal diversity during expansion

Our knowledge of copy number evolution during the expansion of primary breast tumours is limited^1,2. Here, to investigate this process, we developed a single-cell, single-molecule DNA-sequencing method and performed copy number analysis of 16,178 single cells from 8 human triple-negative breast cancers and 4 cell lines. The results show that breast tumours and cell lines comprise a large milieu of subclones (7-22) that are organized into a few (3-5) major superclones. Evolutionary analysis suggests that after clonal TP53 mutations, multiple loss-of-heterozygosity events and genome doubling, there was a period of transient genomic instability followed by ongoing copy number evolution during the primary tumour expansion. By subcloning single daughter cells in culture, we show that tumour cells rediversify their genomes and do not retain isogenic properties. These data show that triple-negative breast cancers continue to evolve chromosome aberrations and maintain a reservoir of subclonal diversity during primary tumour growth.

Analysis of mutations in tumor and normal adjacent tissue via fluorescence detection

Inflammation is a major risk factor for many types of cancer, including colorectal. There are two fundamentally different mechanisms by which inflammation can contribute to carcinogenesis. First, reactive oxygen and nitrogen species (RONS) can damage DNA to cause mutations that initiate cancer. Second, inflammatory cytokines and chemokines promote proliferation, migration, and invasion. Although it is known that inflammation-associated RONS can be mutagenic, the extent to which they induce mutations in intestinal stem cells has been little explored. Furthermore, it is now widely accepted that cancer is caused by successive rounds of clonal expansion with associated de novo mutations that further promote tumor development. As such, we aimed to understand the extent to which inflammation promotes clonal expansion in normal and tumor tissue. Using an engineered mouse model that is prone to cancer and within which mutant cells fluoresce, here we have explored the impact of inflammation on de novo mutagenesis and clonal expansion in normal and tumor tissue. While inflammation is strongly associated with susceptibility to cancer and a concomitant increase in the overall proportion of mutant cells in the tissue, we did not observe an increase in mutations in normal adjacent tissue. These results are consistent with opportunities for de novo mutations and clonal expansion during tumor growth, and they suggest protective mechanisms that suppress the risk of inflammation-induced accumulation of mutant cells in normal tissue.

Systemic and rapid restructuring of the genome: a new perspective on punctuated equilibrium

The rates and patterns by which cells acquire mutations profoundly shape their evolutionary trajectories and phenotypic potential. Conventional models maintain that mutations are acquired independently of one another over many successive generations. Yet, recent evidence suggests that cells can also experience mutagenic processes that drive rapid genome evolution. One such process manifests as punctuated bursts of genomic instability, in which multiple new mutations are acquired simultaneously during transient episodes of genomic instability. This mutational mode is reminiscent of the theory of punctuated equilibrium, proposed by Stephen Jay Gould and Niles Eldredge in 1972 to explain the burst-like appearance of new species in the fossil record. In this review, we survey the dominant and emerging theories of eukaryotic genome evolution with a particular focus on the growing body of work that substantiates the existence and importance of punctuated bursts of genomic instability. In addition, we summarize and discuss two recent studies from our own group, the results of which indicate that punctuated bursts systemic genomic instability (SGI) can rapidly reconfigure the structure of the diploid genome of Saccharomyces cerevisiae.

Optimal control to reach eco-evolutionary stability in metastatic castrate-resistant prostate cancer

In the absence of curative therapies, treatment of metastatic castrate-resistant prostate cancer (mCRPC) using currently available drugs can be improved by integrating evolutionary principles that govern proliferation of resistant subpopulations into current treatment protocols. Here we develop what is coined as an 'evolutionary stable therapy', within the context of the mathematical model that has been used to inform the first adaptive therapy clinical trial of mCRPC. The objective of this therapy is to maintain a stable polymorphic tumor heterogeneity of sensitive and resistant cells to therapy in order to prolong treatment efficacy and progression free survival. Optimal control analysis shows that an increasing dose titration protocol, a very common clinical dosing process, can achieve tumor stabilization for a wide range of potential initial tumor compositions and volumes. Furthermore, larger tumor volumes may counter intuitively be more likely to be stabilized if sensitive cells dominate the tumor composition at time of initial treatment, suggesting a delay of initial treatment could prove beneficial. While it remains uncertain if metastatic disease in humans has the properties that allow it to be truly stabilized, the benefits of a dose titration protocol warrant additional pre-clinical and clinical investigations.

Genome chaos: Creating new genomic information essential for cancer macroevolution

Cancer research has traditionally focused on the characterization of individual molecular mechanisms that can contribute to cancer. Due to the multiple levels of genomic and non-genomic heterogeneity, however, overwhelming molecular mechanisms have been identified, most with low clinical predictability. It is thus necessary to search for new concepts to unify these diverse mechanisms and develop better strategies to understand and treat cancer. In recent years, two-phased cancer evolution (comprised of the genome reorganization-mediated punctuated phase and gene mutation-mediated stepwise phase), initially described by tracing karyotype evolution, was confirmed by the Cancer Genome Project. In particular, genome chaos, the process of rapid and massive genome reorganization, has been commonly detected in various cancers-especially during key phase transitions, including cellular transformation, metastasis, and drug resistance-suggesting the importance of genome-level changes in cancer evolution. In this Perspective, genome chaos is used as a discussion point to illustrate new genome-mediated somatic evolutionary frameworks. By rephrasing cancer as a new system emergent from normal tissue, we present the multiple levels (or scales) of genomic and non-genomic information. Of these levels, evolutionary studies at the chromosomal level are determined to be of ultimate importance, since altered genomes change the karyotype coding and karyotype change is the key event for punctuated cellular macroevolution. Using this lens, we differentiate and analyze developmental processes and cancer evolution, as well as compare the informational relationship between genome chaos and its various subtypes in the context of macroevolution under crisis. Furthermore, the process of deterministic genome chaos is discussed to interpret apparently random events (including stressors, chromosomal variation subtypes, surviving cells with new karyotypes, and emergent stable cellular populations) as nonrandom patterns, which supports the new cancer evolutionary model that unifies genome and gene contributions during different phases of cancer evolution. Finally, the new perspective of using cancer as a model for organismal evolution is briefly addressed, emphasizing the Genome Theory as a new and necessary conceptual framework for future research and its practical implications, not only in cancer but evolutionary biology as a whole.

Characterization of systemic genomic instability in budding yeast

Conventional models of genome evolution are centered around the principle that mutations form independently of each other and build up slowly over time. We characterized the occurrence of bursts of genome-wide loss-of-heterozygosity (LOH) in Saccharomyces cerevisiae, providing support for an additional nonindependent and faster mode of mutation accumulation. We initially characterized a yeast clone isolated for carrying an LOH event at a specific chromosome site, and surprisingly found that it also carried multiple unselected rearrangements elsewhere in its genome. Whole-genome analysis of over 100 additional clones selected for carrying primary LOH tracts revealed that they too contained unselected structural alterations more often than control clones obtained without any selection. We also measured the rates of coincident LOH at two different chromosomes and found that double LOH formed at rates 14- to 150-fold higher than expected if the two underlying single LOH events occurred independently of each other. These results were consistent across different strain backgrounds and in mutants incapable of entering meiosis. Our results indicate that a subset of mitotic cells within a population can experience discrete episodes of systemic genomic instability, when the entire genome becomes vulnerable and multiple chromosomal alterations can form over a narrow time window. They are reminiscent of early reports from the classic yeast genetics literature, as well as recent studies in humans, both in cancer and genomic disorder contexts. The experimental model we describe provides a system to further dissect the fundamental biological processes responsible for punctuated bursts of structural genomic variation.

The cellular origins of cancer with particular reference to the gastrointestinal tract

Stem cells or their closely related committed progenitor cells are the likely founder cells of most neoplasms. In the continually renewing and hierarchically organized epithelia of the oesophagus, stomach and intestine, homeostatic stem cells are located at the beginning of the cell flux, in the basal layer of the oesophagus, the isthmic region of gastric oxyntic glands and at the bottom of gastric pyloric-antral glands and colonic crypts. The introduction of mutant oncogenes such as KrasG12D or loss of Tp53 or Apc to specific cell types expressing the likes of Lgr5 and Mist1 can be readily accomplished in genetically engineered mouse models to initiate tumorigenesis. Other origins of cancer are discussed including 'reserve' stem cells that may be activated by damage or through disruption of morphogen gradients along the crypt axis. In the liver and pancreas, with little cell turnover and no obvious stem cell markers, the importance of regenerative hyperplasia associated with chronic inflammation to tumour initiation is vividly apparent, though inflammatory conditions in the renewing populations are also permissive for tumour induction. In the liver, hepatocytes, biliary epithelial cells and hepatic progenitor cells are embryologically related, and all can give rise to hepatocellular carcinoma and cholangiocarcinoma. In the exocrine pancreas, both acinar and ductal cells can give rise to pancreatic ductal adenocarcinoma (PDAC), although the preceding preneoplastic states are quite different: acinar-ductal metaplasia gives rise to pancreatic intraepithelial neoplasia culminating in PDAC, while ducts give rise to PDAC via. mucinous cell metaplasia that may have a polyclonal origin.

When, why and how tumour clonal diversity predicts survival

The utility of intratumour heterogeneity as a prognostic biomarker is the subject of ongoing clinical investigation. However, the relationship between this marker and its clinical impact is mediated by an evolutionary process that is not well understood. Here, we employ a spatial computational model of tumour evolution to assess when, why and how intratumour heterogeneity can be used to forecast tumour growth rate and progression-free survival. We identify three conditions that can lead to a positive correlation between clonal diversity and subsequent growth rate: diversity is measured early in tumour development; selective sweeps are rare; and/or tumours vary in the rate at which they acquire driver mutations. Opposite conditions typically lead to negative correlation. In cohorts of tumours with diverse evolutionary parameters, we find that clonal diversity is a reliable predictor of both growth rate and progression-free survival. We thus offer explanations-grounded in evolutionary theory-for empirical findings in various cancers, including survival analyses reported in the recent TRACERx Renal study of clear-cell renal cell carcinoma. Our work informs the search for new prognostic biomarkers and contributes to the development of predictive oncology.

Molecular Dynamics in Esophageal Adenocarcinoma: Who's in Control?

Esophageal adenocarcinoma (EAC) is one of the fastest-growing cancers in the world. It occurs primarily due to the chronic gastroesophageal reflux disease (GERD), during which the esophageal epithelium is frequently exposed to the acidic fluid coming up from the stomach. This triggers gene mutations in the esophageal cells, which may lead to EAC development. While p53 is activated to get rid of the mutated cells, NFκB orchestrates the remaining cells to heal the wound. However, if the mutations happen to TP53 (a common occasion), the mutant product turns to support tumorigenesis. In this case, NFκB goes along with the mutant p53 to facilitate cancer progression. TRAIL is one of the cytokines produced in response to GERD episodes and it can kill cancer cells selectively, but its clinical use has not been as successful as expected, because some highly sophisticated defense mechanisms against TRAIL have developed during the malignancy. To clear the obstacles for TRAIL action, using a second agent to disarm the cancer cells is required. CCN1 appears to be such a molecule. While supporting normal esophageal cell growth, CCN1 suppresses malignant transformation by inhibiting NFκB and kills the EAC cell through TRAIL-mediated apoptosis.

Convergent Evolution, Evolving Evolvability, and the Origins of Lethal Cancer

Advances in curative treatment to remove the primary tumor have increased survival of localized cancers for most solid tumor types, yet cancers that have spread are typically incurable and account for >90% of cancer-related deaths. Metastatic disease remains incurable because, somehow, tumors evolve resistance to all known compounds, including therapies. In all of these incurable patients, de novo lethal cancer evolves capacities for both metastasis and resistance. Therefore, cancers in different patients appear to follow the same eco-evolutionary path that independently manifests in affected patients. This convergent outcome, that always includes the ability to metastasize and exhibit resistance, demands an explanation beyond the slow and steady accrual of stochastic mutations. The common denominator may be that cancer starts as a speciation event when a unicellular protist breaks away from its multicellular host and initiates a cancer clade within the patient. As the cancer cells speciate and diversify further, some evolve the capacity to evolve: evolvability. Evolvability becomes a heritable trait that influences the available variation of other phenotypes that can then be acted upon by natural selection. Evolving evolvability may be an adaptation for cancer cells. By generating and maintaining considerable heritable variation, the cancer clade can, with high certainty, serendipitously produce cells resistant to therapy and cells capable of metastasizing. Understanding that cancer cells can swiftly evolve responses to novel and varied stressors create opportunities for adaptive therapy, double-bind therapies, and extinction therapies; all involving strategic decision making that steers and anticipates the convergent coevolutionary responses of the cancers.

Genomic profiling of sporadic liver metastatic colorectal cancer

Sporadic colorectal cancer (sCRC) is the third leading cause of cancer death in the Western world. Approximately, a quarter of sCRC patients present metastatic dissemination at the moment of diagnosis, the liver being the most frequently affected organ. Additionally, this group of CRC patients is characterized by a worse prognosis. In the last decades, significant technological developments for genome analysis have fostered the identification and characterization of genetic alterations involved in the pathogenesis of sCRC. However, genetic alterations involved in the metastatic process through which tumor cells are able to colonize other tissues with a different microenvironment, still remain to be fully identified. Here, we review current knowledge about the most relevant genomic alterations involved in the liver metastatic process of sCRC, including detailed information about the genetic profile of primary colorectal tumors vs. their paired liver metastases.

Clinical Implication of Concordant or Discordant Genomic Profiling between Primary and Matched Metastatic Tissues in Patients with Colorectal Cancer

Purpose

The purpose of this study was to identify the concordant or discordant genomic profiling between primary and matched metastatic tumors in patients with colorectal cancer (CRC) and to explore the clinical implication.

Materials and Methods

Surgical samples of primary and matched metastatic tissues from 158 patients (335 samples) with CRC at Korea University Anam Hospital were evaluated using the Ion AmpliSeq Cancer Hotspot Panel. We compared genetic variants and classified them as concordant, primary-specific, and metastasis-specific variants. We used a combination of principal components analysis and clustering to find genomic groups. Kaplan-Meier curves were used to appraise survival between genomic groups. We used machine learning to confirm the correlation between genetic variants and metastatic sites.

Results

A total of 282 types of deleterious non-synonymous variants were selected for analysis. Of a total of 897 variants, an average of 40% was discordant. Three genomic groups were yielded based on the genomic discrepancy patterns. Overall survival differed significantly between the genomic groups. The poorest group had the highest proportion of concordant KRAS G12V and additional metastasis-specific SMAD4. Correlation analysis between genetic variants and metastatic sites suggested that concordant KRAS mutations would have more disseminated metastases.

Conclusion

Driver gene mutations were mostly concordant; however, discordant or metastasis-specific mutations were present. Clinically, the concordant driver genetic changes with additional metastasis-specific variants can predict poor prognosis for patients with CRC.

Model genotype-phenotype mappings and the algorithmic structure of evolution

Cancers are complex dynamic systems that undergo evolution and selection. Personalized medicine approaches in the clinic increasingly rely on predictions of tumour response to one or more therapies; these predictions are complicated by the inevitable evolution of the tumour. Despite enormous amounts of data on the mutational status of cancers and numerous therapies developed in recent decades to target these mutations, many of these treatments fail after a time due to the development of resistance in the tumour. The emergence of these resistant phenotypes is not easily predicted from genomic data, since the relationship between genotypes and phenotypes, termed the genotype-phenotype (GP) mapping, is neither injective nor functional. We present a review of models of this mapping within a generalized evolutionary framework that takes into account the relation between genotype, phenotype, environment and fitness. Different modelling approaches are described and compared, and many evolutionary results are shown to be conserved across studies despite using different underlying model systems. In addition, several areas for future work that remain understudied are identified, including plasticity and bet-hedging. The GP-mapping provides a pathway for understanding the potential routes of evolution taken by cancers, which will be necessary knowledge for improving personalized therapies.

Assessing reliability of intra-tumor heterogeneity estimates from single sample whole exome sequencing data

Tumors are made of evolving and heterogeneous populations of cells which arise from successive appearance and expansion of subclonal populations, following acquisition of mutations conferring them a selective advantage. Those subclonal populations can be sensitive or resistant to different treatments, and provide information about tumor aetiology and future evolution. Hence, it is important to be able to assess the level of heterogeneity of tumors with high reliability for clinical applications. In the past few years, a large number of methods have been proposed to estimate intra-tumor heterogeneity from whole exome sequencing (WES) data, but the accuracy and robustness of these methods on real data remains elusive. Here we systematically apply and compare 6 computational methods to estimate tumor heterogeneity on 1,697 WES samples from the cancer genome atlas (TCGA) covering 3 cancer types (breast invasive carcinoma, bladder urothelial carcinoma, and head and neck squamous cell carcinoma), and two distinct input mutation sets. We observe significant differences between the estimates produced by different methods, and identify several likely confounding factors in heterogeneity assessment for the different methods. We further show that the prognostic value of tumor heterogeneity for survival prediction is limited in those datasets, and find no evidence that it improves over prognosis based on other clinical variables. In conclusion, heterogeneity inference from WES data on a single sample, and its use in cancer prognosis, should be considered with caution. Other approaches to assess intra-tumoral heterogeneity such as those based on multiple samples may be preferable for clinical applications.

Meta-Analysis of Cancer Triploidy: Rearrangements of Genome Complements in Male Human Tumors Are Characterized by XXY Karyotypes

Triploidy in cancer is associated with poor prognosis, but its origins remain unclear. Here, we attempted to differentiate between random chromosomal and whole-genome origins of cancer triploidy. In silico meta-analysis was performed on 15 male malignant and five benign tumor cohorts (2928 karyotypes) extracted from the Mitelman Database, comparing their ploidy and combinations of sex chromosomes. A distinct near-triploid fraction was observed in all malignant tumor types, and was especially high in seminoma. For all tumor types, X-chromosome doubling, predominantly observed as XXY, correlated strongly with the near-triploid state (r ≈ 0.9, p < 0.001), negatively correlated with near-diploidy, and did not correlate with near-tetraploidy. A smaller near-triploid component with a doubled X-chromosome was also present in three of the five benign tumor types, especially notable in colon adenoma. Principal component analysis revealed a non-random correlation structure shaping the X-chromosome disomy distribution across all tumor types. We suggest that doubling of the maternal genome followed by pedogamic fusion with a paternal genome (a possible mimic of the fertilization aberration, 69, XXY digyny) associated with meiotic reprogramming may be responsible for the observed rearrangements of genome complements leading to cancer triploidy. The relatively frequent loss of the Y-chromosome results as a secondary factor from chromosome instability.

A Review of Mathematical Models for Tumor Dynamics and Treatment Resistance Evolution of Solid Tumors

Increasing knowledge of intertumor heterogeneity, intratumor heterogeneity, and cancer evolution has improved the understanding of anticancer treatment resistance. A better characterization of cancer evolution and subsequent use of this knowledge for personalized treatment would increase the chance to overcome cancer treatment resistance. Model‐based approaches may help achieve this goal. In this review, we comprehensively summarized mathematical models of tumor dynamics for solid tumors and of drug resistance evolution. Models displayed by ordinary differential equations, algebraic equations, and partial differential equations for characterizing tumor burden dynamics are introduced and discussed. As for tumor resistance evolution, stochastic and deterministic models are introduced and discussed. The results may facilitate a novel model‐based analysis on anticancer treatment response and the occurrence of resistance, which incorporates both tumor dynamics and resistance evolution. The opportunities of a model‐based approach as discussed in this review can be of great benefit for future optimizing and personalizing anticancer treatment.

Mutational signatures and mutable motifs in cancer genomes

Cancer is a genetic disorder, meaning that a plethora of different mutations, whether somatic or germ line, underlie the etiology of the 'Emperor of Maladies'. Point mutations, chromosomal rearrangements and copy number changes, whether they have occurred spontaneously in predisposed individuals or have been induced by intrinsic or extrinsic (environmental) mutagens, lead to the activation of oncogenes and inactivation of tumor suppressor genes, thereby promoting malignancy. This scenario has now been recognized and experimentally confirmed in a wide range of different contexts. Over the past decade, a surge in available sequencing technologies has allowed the sequencing of whole genomes from liquid malignancies and solid tumors belonging to different types and stages of cancer, giving birth to the new field of cancer genomics. One of the most striking discoveries has been that cancer genomes are highly enriched with mutations of specific kinds. It has been suggested that these mutations can be classified into 'families' based on their mutational signatures. A mutational signature may be regarded as a type of base substitution (e.g. C:G to T:A) within a particular context of neighboring nucleotide sequence (the bases upstream and/or downstream of the mutation). These mutational signatures, supplemented by mutable motifs (a wider mutational context), promise to help us to understand the nature of the mutational processes that operate during tumor evolution because they represent the footprints of interactions between DNA, mutagens and the enzymes of the repair/replication/modification pathways.

Multiregion human bladder cancer sequencing reveals tumour evolution, bladder cancer phenotypes and implications for targeted therapy

We present an evolutionary analysis of the relative time of genetic events underlying tumorigenesis in human bladder cancers from 10 whole cystectomy specimens using multiregional whole-exome sequencing. We timed bladder cancer drivers, mutational signatures, ploidy and copy number alterations, provided evidence for kataegis and correlated alterations with tumour areas and histological phenotypes. We found that: (1) heterogeneous tumour areas/phenotypes had distinct driver mutations, (2) papillary-invasive tumours divided early into two parallel evolving branches and (3) parallel evolution of subclonal driver mutations occurred. APOBEC mutational signatures were found to be very early events, active in carcinoma in situ, and often remained a dominant source of mutations throughout tumour evolution. Genetic progression from carcinoma in situ followed driver mutations in NA13/FAT1, ZBTB7B or EP300/USP28/KMT2D. Our results point towards a more diverse mutational trajectory of bladder tumorigenesis and underpin the importance of timing of mutational processes and clonal architecture in bladder cancer as important aspects for successful prognostication and therapy. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Measuring Clonal Evolution in Cancer with Genomics

Cancers originate from somatic cells in the human body that have accumulated genetic alterations. These mutations modify the phenotype of the cells, allowing them to escape the homeostatic regulation that maintains normal cell number. Viewed through the lens of evolutionary biology, the transformation of normal cells into malignant cells is evolution in action. Evolution continues throughout cancer growth, progression, treatment resistance, and disease relapse, driven by adaptation to changes in the cancer's environment, and intratumor heterogeneity is an inevitable consequence of this evolutionary process. Genomics provides a powerful means to characterize tumor evolution, enabling quantitative measurement of evolving clones across space and time. In this review, we discuss concepts and approaches to quantify and measure this evolutionary process in cancer using genomics.

Clonal Reconstruction of Thyroid Cancer: An Essential Strategy for Preventing Resistance to Ultra-Precision Therapy

The introduction of ultra-precision targeted therapy has become a significant advancement in cancer therapeutics by creating treatments with less off target effects. Specifically with papillary thyroid carcinoma (PTC), the cancer's hallmark genetic mutation BRAF^V600E can be targeted with selective inhibitors, such as vemurafenib. Despite initial positive tumor responses of regression and decreased viability, both single agent or combination agent drug treatments provide a selective pressure for drug resistant evolving clones within the overall heterogeneous tumor. Also, there are evidences suggesting that sequential monotherapy is ineffective and selects for resistant and ultimately lethal tumor clones. Reconstructing both clonal and subclonal thyroid tumor heterogeneous cell clusters for somatic mutations and epigenetic profile, copy number variation, cytogenetic alterations, and non-coding RNA expression becomes increasingly critical as different clonal enrichments implicate how the tumor may respond to drug treatment and dictate its invasive, metastatic, and progressive abilities, and predict prognosis. Therefore, development of novel preclinical and clinical empirical models supported by mathematical assessment will be the tools required for estimating the parameters of clonal and subclonal evolution, and unraveling the dormant vs. non-dormant state of thyroid cancer. In sum, novel experimental models performing the reconstruction both pre- and post-drug treatment of the thyroid tumor will enhance our understanding of clonal and sub-clonal reconstruction and tumor evolution exposed to treatments during ultra-precision targeted therapies. This approach will improve drug development strategies in thyroid oncology and identification of disease-specific biomarkers.

Single-cell genetic analysis of clonal dynamics in colorectal adenomas indicates CDX2 gain as a predictor of recurrence

Colorectal adenomas are common precancerous lesions with the potential for malignant transformation to colorectal adenocarcinoma. Endoscopic polypectomy provides an opportunity for cancer prevention; however, recurrence rates are high. We collected formalin-fixed paraffin-embedded tissue of 15 primary adenomas with recurrence, 15 adenomas without recurrence, and 14 matched pair samples (primary adenoma and the corresponding recurrent adenoma). The samples were analysed by array-comparative genomic hybridisation (aCGH) and single-cell multiplex interphase fluorescence in situ hybridisation (miFISH) to understand clonal evolution, to examine the dynamics of copy number alterations (CNAs) and to identify molecular markers for recurrence prediction. The miFISH probe panel consisted of 14 colorectal carcinogenesis-relevant genes (COX2, PIK3CA, APC, CLIC1, EGFR, MYC, CCND1, CDX2, CDH1, TP53, HER2, SMAD7, SMAD4 and ZNF217), and a centromere probe (CEP10). The aCGH analysis confirmed the genetic landscape typical for colorectal tumorigenesis, that is, CNAs of chromosomes 7, 13q, 18 and 20q. Focal aberrations (≤10 Mbp) were mapped to chromosome bands 6p22.1-p21.33 (33.3%), 7q22.1 (31.4%) and 16q21 (29.4%). MiFISH detected gains of EGFR (23.6%), CDX2 (21.8%) and ZNF217 (18.2%). Most adenomas exhibited a major clone population which was accompanied by multiple smaller clone populations. Gains of CDX2 were exclusively seen in primary adenomas with recurrence (25%) compared to primary adenomas without recurrence (0%). Generation of phylogenetic trees for matched pair samples revealed four distinct patterns of clonal dynamics. In conclusion, adenoma development and recurrence are complex genetic processes driven by multiple CNAs whose evaluations by miFISH, with emphasis on CDX2, might serve as a predictor of recurrence.

Surface microstructures are associated with mutational intratumoral heterogeneity in colorectal tumors

BACKGROUND

Recent studies revealed that colorectal tumors are composed of genetically diverse subclones. We aimed to clarify whether the surface microstructures of colorectal tumors are associated with genetic intratumoral heterogeneity (ITH).

METHODS

The surface microstructures (pit patterns) of colorectal tumors were observed using magnifying endoscopy, and biopsy specimens were obtained from respective areas when tumors exhibited multiple pit patterns. A total of 711 specimens from 477 colorectal tumors were analyzed for BRAF, KRAS and TP53 mutations using pyrosequencing and direct sequencing. A panel of cancer-related genes was analyzed through targeted sequencing in 7 tumors.

RESULTS

Colorectal tumors with multiple pit patterns exhibited more advanced pit patterns and higher frequencies of KRAS and/or TP53 mutations than tumors with a single pit pattern. In tumors with multiple pit patterns, mutations were observed as public (common to all areas) or private (specific to certain areas), and private KRAS and/or TP53 mutations were often variable and unrelated to the pit pattern grade. Notably, invasive CRCs frequently exhibited public TP53 mutations, even in adenomatous areas, which is indicative of their early malignant potential. Targeted sequencing revealed additional public and private mutations in tumors with multiple pit patterns, indicating their single clonal origin.

CONCLUSIONS

Our results suggest intratumoral pit pattern variation does not simply reflect the process of colorectal tumor evolution, but instead represents genetically diverse subclones, and this diversity may be associated with malignant potential.

Expression-based analyses indicate a central role for hypoxia in driving tumor plasticity through microenvironment remodeling and chromosomal instability

Can transcriptomic alterations drive the evolution of tumors? We asked if changes in gene expression found in all patients arise earlier in tumor development and can be relevant to tumor progression. Our analyses of non-mutated genes from the non-amplified regions of the genome of 158 triple-negative breast cancer (TNBC) cases identified 219 exclusively expression-altered (EEA) genes that may play important role in TNBC. Phylogenetic analyses of these genes predict a "punctuated burst" of multiple gene upregulation events occurring at early stages of tumor development, followed by minimal subsequent changes later in tumor progression. Remarkably, this punctuated burst of expressional changes is instigated by hypoxia-related molecular events, predominantly in two groups of genes that control chromosomal instability (CIN) and those that remodel tumor microenvironment (TME). We conclude that alterations in the transcriptome are not stochastic and that early-stage hypoxia induces CIN and TME remodeling to permit further tumor evolution.

The Natural History of Colorectal Polyps: Overview of Predictive Static and Dynamic Features

For decades, colorectal screening strategies have been largely driven by static features, particularly polyp size. Although cross-sectional features of polyp size, morphology, and location are important determinants of clinical relevance before histology, they lack any dynamic information on polyp growth rates. Computed tomography colonography allows for in vivo surveillance of colorectal polyps, providing volumetric growth rates that are providing new insights into tumorigenesis. In this article, existing cross-sectional and longitudinal data on colorectal polyps are reviewed, with an emphasis on how these features may affect clinical relevance and patient management.

Molecular Evolution of Metaplasia to Adenocarcinoma in the Esophagus

Esophageal adenocarcinoma (EAC) develops from Barrett's esophagus (BE), a condition where the normal squamous epithelia is replaced by specialized intestinal metaplasia in response to chronic gastroesophageal acid reflux. In a minority of individuals, BE can progress to low- and high-grade dysplasia and eventually to intra-mucosal and then invasive carcinoma. BE provides researchers with a unique model to characterize the process by which a carcinoma arises from its precursor lesion. Molecular studies of BE have demonstrated that it is not simply a metaplastic tissue, but rather it harbors frequent alterations that are also present in dysplastic BE and in EAC. Both BE and EAC are characterized by loss of heterozygosity, aneuploidy, specific genetic mutations, and clonal diversity. Epigenetic abnormalities, primary alterations in DNA methylation, are also frequently seen in BE and EAC. Candidate gene and array-based approaches have demonstrated that numerous tumor suppressor genes exhibit aberrant promoter methylation, and some of these altered genes are associated with the neoplastic progression of BE. It has also been shown that the BE and EAC epigenomes are characterized by hypomethylation of intragenic and non-coding regions Recent studies have also provided new insight into the evolutionary forces underlying the molecular alterations seen in BE and EAC and into the molecular pathogenesis of EAC.

Reliance upon ancestral mutations is maintained in colorectal cancers that heterogeneously evolve during targeted therapies

Attempts at eradicating metastatic cancers with targeted therapies are limited by the emergence of resistant subclones bearing heterogeneous (epi)genetic changes. We used colorectal cancer (CRC) to test the hypothesis that interfering with an ancestral oncogenic event shared by all the malignant cells (such as WNT pathway alterations) could override heterogeneous mechanisms of acquired drug resistance. Here, we report that in CRC-resistant cell populations, phylogenetic analysis uncovers a complex subclonal architecture, indicating parallel evolution of multiple independent cellular lineages. Functional and pharmacological modulation of WNT signalling induces cell death in CRC preclinical models from patients that relapsed during the treatment, regardless of the drug type or resistance mechanisms. Concomitant blockade of WNT and MAPK signalling restrains the emergence of drug-resistant clones. Reliance upon the WNT-APC pathway is preserved throughout the branched genomic drift associated with emergence of treatment relapse, thus offering the possibility of a common therapeutic strategy to overcome secondary drug resistance.

Multiclonal tumor origin: Evidence and implications

An accurate understanding of the clonal origins of tumors is critical for designing effective strategies to treat or prevent cancer and for guiding the field of cancer risk assessment. The intent of this review is to summarize evidence of multiclonal tumor origin and, thereby, contest the commonly held assumption of monoclonal tumor origin. This review describes relevant studies of X chromosome inactivation, analyses of tumor heterogeneity using other markers, single cell sequencing, and lineage tracing studies in aggregation chimeras and engineered rodent models. Methods for investigating tumor clonality have an inherent bias against detecting multiclonality. Despite this, multiclonality has been observed within all tumor stages and within 53 different types of tumors. For myeloid tumors, monoclonal tumor origin may be the predominant path to cancer and a monoclonal tumor origin cannot be ruled out for a fraction of other cancer types. Nevertheless, a large body of evidence supports the conclusion that most cancers are multiclonal in origin. Cooperation between different cell types and between clones of cells carrying different genetic and/or epigenetic lesions is discussed, along with how polyclonal tumor origin can be integrated with current perspectives on the genesis of tumors. In order to develop biologically sound and useful approaches to cancer risk assessment and precision medicine, mathematical models of carcinogenesis are needed, which incorporate multiclonal tumor origin and the contributions of spontaneous mutations in conjunction with the selective advantages conferred by particular mutations and combinations of mutations. Adherence to the idea that a growth must develop from a single progenitor cell to be considered neoplastic has outlived its usefulness. Moving forward, explicit examination of tumor clonality, using advanced tools, like lineage tracing models, will provide a strong foundation for future advances in clinical oncology and better training for the next generation of oncologists and pathologists.

Big Bang Tumor Growth and Clonal Evolution

The advent and application of next-generation sequencing (NGS) technologies to tumor genomes has reinvigorated efforts to understand clonal evolution. Although tumor progression has traditionally been viewed as a gradual stepwise process, recent studies suggest that evolutionary rates in tumors can be variable with periods of punctuated mutational bursts and relative stasis. For example, Big Bang dynamics have been reported, wherein after transformation, growth occurs in the absence of stringent selection, consistent with effectively neutral evolution. Although first noted in colorectal tumors, effective neutrality may be relatively common. Additionally, punctuated evolution resulting from mutational bursts and cataclysmic genomic alterations have been described. In this review, we contrast these findings with the conventional gradualist view of clonal evolution and describe potential clinical and therapeutic implications of different evolutionary modes and tempos.