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.

Origins and Consequences of Chromosomal Instability: From Cellular Adaptation to Genome Chaos-Mediated System Survival.

When discussing chromosomal instability, most of the literature focuses on the characterization of individual molecular mechanisms. These studies search for genomic and environmental causes and consequences of chromosomal instability in cancer, aiming to identify key triggering factors useful to control chromosomal instability and apply this knowledge in the clinic. Since cancer is a phenomenon of new system emergence from normal tissue driven by somatic evolution, such studies should be done in the context of new genome system emergence during evolution. In this perspective, both the origin and key outcome of chromosomal instability are examined using the genome theory of cancer evolution. Specifically, chromosomal instability was linked to a spectrum of genomic and non-genomic variants, from epigenetic alterations to drastic genome chaos. These highly diverse factors were then unified by the evolutionary mechanism of cancer. Following identification of the hidden link between cellular adaptation (positive and essential) and its trade-off (unavoidable and negative) of chromosomal instability, why chromosomal instability is the main player in the macro-cellular evolution of cancer is briefly discussed. Finally, new research directions are suggested, including searching for a common mechanism of evolutionary phase transition, establishing chromosomal instability as an evolutionary biomarker, validating the new two-phase evolutionary model of cancer, and applying such a model to improve clinical outcomes and to understand the genome-defined mechanism of organismal evolution.

What Is Karyotype Coding and Why Is Genomic Topology Important for Cancer and Evolution?

While the importance of chromosomal/nuclear variations vs. gene mutations in diseases is becoming more appreciated, less is known about its genomic basis. Traditionally, chromosomes are considered the carriers of genes, and genes define bio-inheritance. In recent years, the gene-centric concept has been challenged by the surprising data of various sequencing projects. The genome system theory has been introduced to offer an alternative framework. One of the key concepts of the genome system theory is karyotype or chromosomal coding: chromosome sets function as gene organizers, and the genomic topologies provide a context for regulating gene expression and function. In other words, the interaction of individual genes, defined by genomic topology, is part of the full informational system. The genes define the "parts inheritance," while the karyotype and genomic topology (the physical relationship of genes within a three-dimensional nucleus) plus the gene content defines "system inheritance." In this mini-review, the concept of karyotype or chromosomal coding will be briefly discussed, including: 1) the rationale for searching for new genomic inheritance, 2) chromosomal or karyotype coding (hypothesis, model, and its predictions), and 3) the significance and evidence of chromosomal coding (maintaining and changing the system inheritance-defined bio-systems). This mini-review aims to provide a new conceptual framework for appreciating the genome organization-based information package and its ultimate importance for future genomic and evolutionary studies.

Understanding aneuploidy in cancer through the lens of system inheritance, fuzzy inheritance and emergence of new genome systems.

BACKGROUND: In the past 15 years, impressive progress has been made to understand the molecular mechanism behind aneuploidy, largely due to the effort of using various -omics approaches to study model systems (e.g. yeast and mouse models) and patient samples, as well as the new realization that chromosome alteration-mediated genome instability plays the key role in cancer. As the molecular characterization of the causes and effects of aneuploidy progresses, the search for the general mechanism of how aneuploidy contributes to cancer becomes increasingly challenging: since aneuploidy can be linked to diverse molecular pathways (in regards to both cause and effect), the chances of it being cancerous is highly context-dependent, making it more difficult to study than individual molecular mechanisms. When so many genomic and environmental factors can be linked to aneuploidy, and most of them not commonly shared among patients, the practical value of characterizing additional genetic/epigenetic factors contributing to aneuploidy decreases. RESULTS: Based on the fact that cancer typically represents a complex adaptive system, where there is no linear relationship between lower-level agents (such as each individual gene mutation) and emergent properties (such as cancer phenotypes), we call for a new strategy based on the evolutionary mechanism of aneuploidy in cancer, rather than continuous analysis of various individual molecular mechanisms. To illustrate our viewpoint, we have briefly reviewed both the progress and challenges in this field, suggesting the incorporation of an evolutionary-based mechanism to unify diverse molecular mechanisms. To further clarify this rationale, we will discuss some key concepts of the genome theory of cancer evolution, including system inheritance, fuzzy inheritance, and cancer as a newly emergent cellular system. CONCLUSION: Illustrating how aneuploidy impacts system inheritance, fuzzy inheritance and the emergence of new systems is of great importance. Such synthesis encourages efforts to apply the principles/approaches of complex adaptive systems to ultimately understand aneuploidy in cancer.

A Postgenomic Perspective on Molecular Cytogenetics.

BACKGROUND: The postgenomic era is featured by massive data collection and analyses from various large scale-omics studies. Despite the promising capability of systems biology and bioinformatics to handle large data sets, data interpretation, especially the translation of -omics data into clinical implications, has been challenging. DISCUSSION: In this perspective, some important conceptual and technological limitations of current systems biology are discussed in the context of the ultimate importance of the genome beyond the collection of all genes. Following a brief summary of the contributions of molecular cytogenetics/cytogenomics in the pre- and post-genomic eras, new challenges for postgenomic research are discussed. Such discussion leads to a call to search for a new conceptual framework and holistic methodologies. CONCLUSION: Throughout this synthesis, the genome theory of somatic cell evolution is highlighted in contrast to gene theory, which ignores the karyotype-mediated higher level of genetic information. Since "system inheritance" is defined by the genome context (gene content and genomic topology) while "parts inheritance" is defined by genes/epigenes, molecular cytogenetics and cytogenomics (which directly study genome structure, function, alteration and evolution) will play important roles in this postgenomic era.

Experimental Induction of Genome Chaos.

Genome chaos, or karyotype chaos, represents a powerful survival strategy for somatic cells under high levels of stress/selection. Since the genome context, not the gene content, encodes the genomic blueprint of the cell, stress-induced rapid and massive reorganization of genome topology functions as a very important mechanism for genome (karyotype) evolution. In recent years, the phenomenon of genome chaos has been confirmed by various sequencing efforts, and many different terms have been coined to describe different subtypes of the chaotic genome including "chromothripsis," "chromoplexy," and "structural mutations." To advance this exciting field, we need an effective experimental system to induce and characterize the karyotype reorganization process. In this chapter, an experimental protocol to induce chaotic genomes is described, following a brief discussion of the mechanism and implication of genome chaos in cancer evolution.

Heterogeneity-mediated cellular adaptation and its trade-off: searching for the general principles of diseases.

Big-data-omics have promised the success of precision medicine. However, most common diseases belong to adaptive systems where the precision is all but difficult to achieve. In this commentary, I propose a heterogeneity-mediated cellular adaptive model to search for the general model of diseases, which also illustrates why in most non-infectious non-Mendelian diseases the involvement of cellular evolution is less predictable when gene profiles are used. This synthesis is based on the following new observations/concepts: 1) the gene only codes "parts inheritance" while the genome codes "system inheritance" or the entire blueprint; 2) the nature of somatic genetic coding is fuzzy rather than precise, and genetic alterations are not just the results of genetic error but are in fact generated from internal adaptive mechanisms in response to environmental dynamics; 3) stress-response is less specific within cellular evolutionary context when compared to known biochemical specificities; and 4) most medical interventions have their unavoidable uncertainties and often can function as negative harmful stresses as trade-offs. The acknowledgment of diseases as adaptive systems calls for the action to integrate genome- (not simply individual gene-) mediated cellular evolution into molecular medicine.

Why it is crucial to analyze non clonal chromosome aberrations or NCCAs?

Current cytogenetics has largely focused its efforts on the identification of recurrent karyotypic alterations, also known as clonal chromosomal aberrations (CCAs). The rationale of doing so seems simple: recurrent genetic changes are relevant for diseases or specific physiological conditions, while non clonal chromosome aberrations (NCCAs) are insignificant genetic background or noise. However, in reality, the vast majority of chromosomal alterations are NCCAs, and it is challenging to identify commonly shared CCAs in most solid tumors. Furthermore, the karyotype, rather than genes, represents the system inheritance, or blueprint, and each NCCA represents an altered genome system. These realizations underscore the importance of the re-evaluation of NCCAs in cytogenetic analyses. In this concept article, we briefly review the definition of NCCAs, some historical misconceptions about them, and why NCCAs are not insignificant "noise," but rather a highly significant feature of the cellular population for providing genome heterogeneity and complexity, representing one important form of fuzzy inheritance. The frequencies of NCCAs also represent an index to measure both internally- and environmentally-induced genome instability. Additionally, the NCCA/CCA cycle is associated with macro- and micro-cellular evolution. Lastly, elevated NCCAs are observed in many disease/illness conditions. Considering all of these factors, we call for the immediate action of studying and reporting NCCAs. Specifically, effort is needed to characterize and compare different types of NCCAs, to define their baseline in various tissues, to develop methods to access mitotic cells, to re-examine/interpret the NCCAs data, and to develop an NCCA database.

HEK293 in cell biology and cancer research: phenotype, karyotype, tumorigenicity, and stress-induced genome-phenotype evolution.

293 cell line (widely known as the Human Embryonic Kidney 293 cells) and its derivatives were the most used cells after HeLa in cell biology studies and after CHO in biotechnology as a vehicle for the production of adenoviral vaccines and recombinant proteins, for analysis of the neuronal synapse formation, in electrophysiology and neuropharmacology. Despite the historically long-term productive exploitation, the origin, phenotype, karyotype, and tumorigenicity of 293 cells are still debated. 293 cells were considered the kidney epithelial cells or even fibroblasts. However, 293 cells demonstrate no evident tissue-specific gene expression signature and express the markers of renal progenitor cells, neuronal cells and adrenal gland. This complicates efforts to reveal the authentic cell type/tissue of origin. On the other hand, the potential to propagate the highly neurotropic viruses, inducible synaptogenesis, functionality of the endogenous neuron-specific voltage-gated channels, and response to the diverse agonists implicated in neuronal signaling give credibility to consider 293 cells of neuronal lineage phenotype. The compound phenotype of 293 cells can be due to heterogeneous, unstable karyotype. The mean chromosome number and chromosome aberrations differ between 293 cells and derivatives as well as between 293 cells from the different cell banks/labs. 293 cells are tumorigenic, whereas acute changes of expression of the cancer-associated genes aggravate tumorigenicity by promoting chromosome instability. Importantly, the procedure of a stable empty vector transfection can also impact karyotype and phenotype. The discussed issues caution against misinterpretations and pitfalls during the different experimental manipulations with 293 cells.

Evolutionary mechanism unifies the hallmarks of cancer.

The basis for the gene mutation theory of cancer that dominates current molecular cancer research consists of: the belief that gene-level aberrations such as mutations are the main cause of cancers, the concept that stepwise gene mutation accumulation drives cancer progression, and the hallmarks of cancer. The research community swiftly embraced the hallmarks of cancer, as such synthesis has supported the notions that common cancer genes are responsible for the majority of cancers and the complexity of cancer can be dissected into simplified molecular principles. The gene/pathway classification based on individual hallmarks provides explanation for the large number of diverse gene mutations, which is in contrast to the original estimation that only a handful of gene mutations would be discovered. Further, these hallmarks have been highly influential as they also provide the rationale and research direction for continued gene-based cancer research. While the molecular knowledge of these hallmarks is drastically increasing, the clinical implication remains limited, as cancer dynamics cannot be summarized by a few isolated/fixed molecular principles. Furthermore, the highly heterogeneous genetic signature of cancers, including massive stochastic genome alterations, challenges the utility of continuously studying each individual gene mutation under the framework of these hallmarks. It is therefore necessary to re-evaluate the concept of cancer hallmarks through the lens of cancer evolution. In this analysis, the evolutionary basis for the hallmarks of cancer will be discussed and the evolutionary mechanism of cancer suggested by the genome theory will be employed to unify the diverse molecular mechanisms of cancer.

Stress, genomic adaptation, and the evolutionary trade-off.

Cells are constantly exposed to various internal and external stresses. The importance of cellular stress and its implication to disease conditions have become popular research topics. Many ongoing investigations focus on the sources of stress, their specific molecular mechanisms and interactions, especially regarding their contributions to many common and complex diseases through defined molecular pathways. Numerous molecular mechanisms have been linked to endoplasmic reticulum stress along with many unexpected findings, drastically increasing the complexity of our molecular understanding and challenging how to apply individual mechanism-based knowledge in the clinic. A newly emergent genome theory searches for the synthesis of a general evolutionary mechanism that unifies different types of stress and functional relationships from a genome-defined system point of view. Herein, we discuss the evolutionary relationship between stress and somatic cell adaptation under physiological, pathological, and somatic cell survival conditions, the multiple meanings to achieve adaptation and its potential trade-off. In particular, we purposely defocus from specific stresses and mechanisms by redirecting attention toward studying underlying general mechanisms.

Genome chaos: survival strategy during crisis.

Genome chaos, a process of complex, rapid genome re-organization, results in the formation of chaotic genomes, which is followed by the potential to establish stable genomes. It was initially detected through cytogenetic analyses, and recently confirmed by whole-genome sequencing efforts which identified multiple subtypes including "chromothripsis", "chromoplexy", "chromoanasynthesis", and "chromoanagenesis". Although genome chaos occurs commonly in tumors, both the mechanism and detailed aspects of the process are unknown due to the inability of observing its evolution over time in clinical samples. Here, an experimental system to monitor the evolutionary process of genome chaos was developed to elucidate its mechanisms. Genome chaos occurs following exposure to chemotherapeutics with different mechanisms, which act collectively as stressors. Characterization of the karyotype and its dynamic changes prior to, during, and after induction of genome chaos demonstrates that chromosome fragmentation (C-Frag) occurs just prior to chaotic genome formation. Chaotic genomes seem to form by random rejoining of chromosomal fragments, in part through non-homologous end joining (NHEJ). Stress induced genome chaos results in increased karyotypic heterogeneity. Such increased evolutionary potential is demonstrated by the identification of increased transcriptome dynamics associated with high levels of karyotypic variance. In contrast to impacting on a limited number of cancer genes, re-organized genomes lead to new system dynamics essential for cancer evolution. Genome chaos acts as a mechanism of rapid, adaptive, genome-based evolution that plays an essential role in promoting rapid macroevolution of new genome-defined systems during crisis, which may explain some unwanted consequences of cancer treatment.

Single cell heterogeneity: why unstable genomes are incompatible with average profiles.

Multi-level heterogeneity is a fundamental but underappreciated feature of cancer. Most technical and analytical methods either completely ignore heterogeneity or do not fully account for it, as heterogeneity has been considered noise that needs to be eliminated. We have used single-cell and population-based assays to describe an instability-mediated mechanism where genome heterogeneity drastically affects cell growth and cannot be accurately measured using conventional averages. First, we show that most unstable cancer cell populations exhibit high levels of karyotype heterogeneity, where it is difficult, if not impossible, to karyotypically clone cells. Second, by comparing stable and unstable cell populations, we show that instability-mediated karyotype heterogeneity leads to growth heterogeneity, where outliers dominantly contribute to population growth and exhibit shorter cell cycles. Predictability of population growth is more difficult for heterogeneous cell populations than for homogenous cell populations. Since "outliers" play an important role in cancer evolution, where genome instability is the key feature, averaging methods used to characterize cell populations are misleading. Variances quantify heterogeneity; means (averages) smooth heterogeneity, invariably hiding it. Cell populations of pathological conditions with high genome instability, like cancer, behave differently than karyotypically homogeneous cell populations. Single-cell analysis is thus needed when cells are not genomically identical. Despite increased attention given to single-cell variation mediated heterogeneity of cancer cells, continued use of average-based methods is not only inaccurate but deceptive, as the "average" cancer cell clearly does not exist. Genome-level heterogeneity also may explain population heterogeneity, drug resistance, and cancer evolution.