Genetic diagnosis of Down syndrome in an underserved community.

It is a matter of course that in high-income countries, infants born with features suggestive of Down syndrome (DS) are offered genetic testing for confirmation of a clinical diagnosis. Benefits of a definitive diagnosis include an end to the diagnostic odyssey, informed prognosis, opportunities for caregiver support, inclusion to social support networks, and more meaningful genetic counseling. The healthcare experience for families of children born with DS in low- and middle-income nations is in stark contrast with such a level of care. Barriers to obtaining genetic diagnosis might include economic disparities, geographical isolation, and lack of access to health care professionals trained in genetic medicine. As part of a combined research and community outreach effort, we provided genetic testing for several patients with DS. These individuals and their families live on several resource-limited Caribbean islands and have either limited or virtually no access to medical genetics services. Within this group were three families with recurrent DS. Karyotype established that translocation events were not involved in the DS in any of these families. This information enabled genetic counseling to help family members understand their recurrent DS. A definitive diagnosis of DS is beneficial to families in resource-limited communities and may help to provide such families with genetic counseling, reassurance, and peace of mind.

Unstable genomes elevate transcriptome dynamics.

The challenge of identifying common expression signatures in cancer is well known, however the reason behind this is largely unclear. Traditionally variation in expression signatures has been attributed to technological problems, however recent evidence suggests that chromosome instability (CIN) and resultant karyotypic heterogeneity may be a large contributing factor. Using a well-defined model of immortalization, we systematically compared the pattern of genome alteration and expression dynamics during somatic evolution. Co-measurement of global gene expression and karyotypic alteration throughout the immortalization process reveals that karyotype changes influence gene expression as major structural and numerical karyotypic alterations result in large gene expression deviation. Replicate samples from stages with stable genomes are more similar to each other than are replicate samples with karyotypic heterogeneity. Karyotypic and gene expression change during immortalization is dynamic as each stage of progression has a unique expression pattern. This was further verified by comparing global expression in two replicates grown in one flask with known karyotypes. Replicates with higher karyotypic instability were found to be less similar than replicates with stable karyotypes. This data illustrates the karyotype, transcriptome, and transcriptome determined pathways are in constant flux during somatic cellular evolution (particularly during the macroevolutionary phase) and this flux is an inextricable feature of CIN and essential for cancer formation. The findings presented here underscore the importance of understanding the evolutionary process of cancer in order to design improved treatment modalities.

Chromosomal instability and transcriptome dynamics in cancer.

Whole transcriptome profiling has long been proposed as a method of identifying cancer-specific gene expression profiles. Indeed, a multitude of these studies have generated vast amounts of expression data for many types of cancer, and most have identified specific gene signatures associated with a given cancer. These studies however, often contradict with each other, and gene lists only rarely overlap, challenging clinical application of cancer gene signatures. To understand this issue, the biological basis of transcriptome dynamics needs to be addressed. Chromosome instability (CIN) is the main contributor to genome heterogeneity and system dynamics, therefore the relationship between CIN, genome heterogeneity, and transcriptome dynamics has important implications for cancer research. In this review, we discuss CIN and its effects on the transcriptome during cancer progression, specifically how stochastic chromosome change results in transcriptome dynamics. This discussion is further applied to metastasis and drug resistance both of which have been linked to multiple diverse molecular mechanisms but are in fact driven by CIN. The diverse molecular mechanisms that drive each process are linked to karyotypic heterogeneity through the evolutionary mechanism of cancer. Karyotypic change and the resultant transcriptome change alter network function within cells increasing the evolutionary potential of the tumor. Future studies must embrace this instability-induced heterogeneity in order to devise new research and treatment modalities that focus on the evolutionary process of cancer rather than the individual genes that are uniquely changed in each tumor. Care is also needed in evaluating results from experimental systems which measure average values of a population.

Chromosomal instability (CIN): what it is and why it is crucial to cancer evolution.

Results of various cancer genome sequencing projects have "unexpectedly" challenged the framework of the current somatic gene mutation theory of cancer. The prevalence of diverse genetic heterogeneity observed in cancer questions the strategy of focusing on contributions of individual gene mutations. Much of the genetic heterogeneity in tumors is due to chromosomal instability (CIN), a predominant hallmark of cancer. Multiple molecular mechanisms have been attributed to CIN but unifying these often conflicting mechanisms into one general mechanism has been challenging. In this review, we discuss multiple aspects of CIN including its definitions, methods of measuring, and some common misconceptions. We then apply the genome-based evolutionary theory to propose a general mechanism for CIN to unify the diverse molecular causes. In this new evolutionary framework, CIN represents a system behavior of a stress response with adaptive advantages but also serves as a new potential cause of further destabilization of the genome. Following a brief review about the newly realized functions of chromosomes that defines system inheritance and creates new genomes, we discuss the ultimate importance of CIN in cancer evolution. Finally, a number of confusing issues regarding CIN are explained in light of the evolutionary function of CIN.

Why imatinib remains an exception of cancer research.

The archetype driving the drug targeting approach to cancer therapy is the success of imatinib against chronic phase chronic myeloid leukemia (CML-CP). Molecular targeting success of this magnitude has yet to be repeated for most solid tumors. To answer why imatinib remains an exception of cancer research, we summarize key features and patterns of evolution that contrast CML-CP from prostate cancer, an example of a solid tumor that also shares a signature fusion gene. Distinctive properties of CML-CP include: a large cell population size that is not geographically constrained, a highly penetrant dominant oncogene that sweeps the entire cell population, subsequent progressive and ordered clonal genetic changes, and the effectiveness of molecular targeting within the chronic phase, which is comparable to the benign phase of solid tumors. CML-CP progression resembles a clonal, stepwise model of evolution, whereas the pattern of solid tumor evolution is highly dynamic and stochastic. The distinguishing features and evolutionary pattern of CML-CP support why the success of imatinib does not carry over to most solid tumors. Changing the focus of cancer research from a gene-based view to a genome-based theory will provide insight into solid tumor evolutionary dynamics.

Decoding the genome beyond sequencing: the new phase of genomic research.

While our understanding of gene-based biology has greatly improved, it is clear that the function of the genome and most diseases cannot be fully explained by genes and other regulatory elements. Genes and the genome represent distinct levels of genetic organization with their own coding systems; Genes code parts like protein and RNA, but the genome codes the structure of genetic networks, which are defined by the whole set of genes, chromosomes and their topological interactions within a cell. Accordingly, the genetic code of DNA offers limited understanding of genome functions. In this perspective, we introduce the genome theory which calls for the departure of gene-centric genomic research. To make this transition for the next phase of genomic research, it is essential to acknowledge the importance of new genome-based biological concepts and to establish new technology platforms to decode the genome beyond sequencing.

The evolutionary mechanism of cancer.

Identification of the general molecular mechanism of cancer is the Holy Grail of cancer research. Since cancer is believed to be caused by a sequential accumulation of cancer gene mutations, the identification, characterization, and targeting of common genetic alterations and their defined pathways have dominated the field for decades. Despite the impressive data accumulated from studies of gene mutations, epigenetic dysregulation, and pathway alterations, an overwhelming amount of diverse molecular information has offered limited understanding of the general mechanisms of cancer. To solve this paradox, the newly established genome theory is introduced here describing how somatic cells evolve within individual patients. The evolutionary mechanism of cancer is characterized using only three key components of somatic cell evolution that include increased system dynamics induced by stress, elevated genetic and epigenetic heterogeneity, and genome alteration mediated natural selection. Cancer progression represents a macro-evolutionary process where karyotype change or genome replacement plays the key dominant role. Furthermore, the recently identified relationship between the evolutionary mechanism and a large number of diverse individual molecular mechanisms is discussed. The total sum of all the individual molecular mechanisms is equal to the evolutionary mechanism of cancer. Individual molecular mechanisms including all the molecular mechanisms described to date are stochastically selected and unpredictable and are therefore clinically impractical. Recognizing the fundamental importance of the underlying basis of the evolutionary mechanism of cancer mandates the development of new strategies in cancer research.

Genetic and epigenetic heterogeneity in cancer: a genome-centric perspective.

Genetic and epigenetic heterogeneity (the main form of non-genetic heterogeneity) are key elements in cancer progression and drug resistance, as they provide needed population diversity, complexity, and robustness. Despite drastically increased evidence of multiple levels of heterogeneity in cancer, the general approach has been to eliminate the "noise" of heterogeneity to establish genetic and epigenetic patterns. In particular, the appreciation of new types of epigenetic regulation like non-coding RNA, have led to the hope of solving the mystery of cancer that the current genetic theories seem to be unable to achieve. In this mini-review, we have briefly analyzed a number of mis-conceptions regarding cancer heterogeneity, followed by the re-evaluation of cancer heterogeneity within a framework of the genome-centric concept of evolution. The analysis of the relationship between gene, epigenetic and genome level heterogeneity, and the challenges of measuring heterogeneity among multiple levels have been discussed. Further, we propose that measuring genome level heterogeneity represents an effective strategy in the study of cancer and other types of complex diseases, as emphasis on the pattern of system evolution rather than specific pathways provides a global and synthetic approach. Compared to the degree of heterogeneity, individual molecular pathways will have limited predictability during stochastic cancer evolution where genome dynamics (reflected by karyotypic heterogeneity) will dominate.

Genome based cell population heterogeneity promotes tumorigenicity: the evolutionary mechanism of cancer.

Cancer progression represents an evolutionary process where overall genome level changes reflect system instability and serve as a driving force for evolving new systems. To illustrate this principle it must be demonstrated that karyotypic heterogeneity (population diversity) directly contributes to tumorigenicity. Five well characterized in vitro tumor progression models representing various types of cancers were selected for such an analysis. The tumorigenicity of each model has been linked to different molecular pathways, and there is no common molecular mechanism shared among them. According to our hypothesis that genome level heterogeneity is a key to cancer evolution, we expect to reveal that the common link of tumorigenicity between these diverse models is elevated genome diversity. Spectral karyotyping (SKY) was used to compare the degree of karyotypic heterogeneity displayed in various sublines of these five models. The cell population diversity was determined by scoring type and frequencies of clonal and non-clonal chromosome aberrations (CCAs and NCCAs). The tumorigenicity of these models has been separately analyzed. As expected, the highest level of NCCAs was detected coupled with the strongest tumorigenicity among all models analyzed. The karyotypic heterogeneity of both benign hyperplastic lesions and premalignant dysplastic tissues were further analyzed to support this conclusion. This common link between elevated NCCAs and increased tumorigenicity suggests an evolutionary causative relationship between system instability, population diversity, and cancer evolution. This study reconciles the difference between evolutionary and molecular mechanisms of cancer and suggests that NCCAs can serve as a biomarker to monitor the probability of cancer progression.

Mitotic cell death by chromosome fragmentation.

Cell death plays a key role for both cancer progression and treatment. In this report, we characterize chromosome fragmentation, a new type of cell death that takes place during metaphase where condensed chromosomes are progressively degraded. It occurs spontaneously without any treatment in instances such as inherited status of genomic instability, or it can be induced by treatment with chemotherapeutics. It is observed within cell lines, tumors, and lymphocytes of cancer patients. The process of chromosome fragmentation results in loss of viability, but is apparently nonapoptotic and further differs from cellular death defined by mitotic catastrophe. Chromosome fragmentation represents an efficient means of induced cell death and is a clinically relevant biomarker of mitotic cell death. Chromosome fragmentation serves as a method to eliminate genomically unstable cells. Paradoxically, this process could result in genome aberrations common in cancer. The characterization of chromosome fragmentation may also shine light on the mechanism of chromosomal pulverization.

Ovarian cancer evolution through stochastic genome alterations: defining the genomic role in ovarian cancer.

Ovarian cancer is the fifth leading cause of death among women worldwide. Characterized by complex etiology and multi-level heterogeneity, its origins are not well understood. Intense research efforts over the last decade have furthered our knowledge by identifying multiple risk factors that are associated with the disease. However, it is still unclear how genetic heterogeneity contributes to tumor formation, and more specifically, how genome-level heterogeneity acts as the key driving force of cancer evolution. Most current genomic approaches are based on 'average molecular profiling.' While effective for data generation, they often fail to effectively address the issue of high level heterogeneity because they mask variation that exists in a cell population. In this synthesis, we hypothesize that genome-mediated cancer evolution can effectively explain diverse factors that contribute to ovarian cancer. In particular, the key contribution of genome replacement can be observed during major transitions of ovarian cancer evolution including cellular immortalization, transformation, and malignancy. First, we briefly review major updates in the literature, and illustrate how current gene-mediated research will offer limited insight into cellular heterogeneity and ovarian cancer evolution. We next explain a holistic framework for genome-based ovarian cancer evolution and apply it to understand the genomic dynamics of a syngeneic ovarian cancer mouse model. Finally, we employ single cell assays to further test our hypothesis, discuss some predictions, and report some recent findings.

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.

Genome constraint through sexual reproduction: application of 4D-Genomics in reproductive biology.

Assisted reproductive technologies have been used to achieve pregnancies since the first successful test tube baby was born in 1978. Infertile couples are at an increased risk for multiple miscarriages and the application of current protocols are associated with high first-trimester miscarriage rates. Among the contributing factors of these higher rates is a high incidence of fetal aneuploidy. Numerous studies support that protocols including ovulation-induction, sperm cryostorage, density-gradient centrifugation, and embryo culture can induce genome instability, but the general mechanism is less clear. Application of the genome theory and 4D-Genomics recently led to the establishment of a new paradigm for sexual reproduction; sex primarily constrains genome integrity that defines the biological system rather than just providing genetic diversity at the gene level. We therefore propose that application of assisted reproductive technologies can bypass this sexual reproduction filter as well as potentially induce additional system instability. We have previously demonstrated that a single-cell resolution genomic approach, such as spectral karyotyping to trace stochastic genome level alterations, is effective for pre- and post-natal analysis. We propose that monitoring overall genome alteration at the karyotype level alongside the application of assisted reproductive technologies will improve the efficacy of the techniques while limiting stress-induced genome instability. The development of more single-cell based cytogenomic technologies are needed in order to better understand the system dynamics associated with infertility and the potential impact that assisted reproductive technologies have on genome instability. Importantly, this approach will be useful in studying the potential for diseases to arise as a result of bypassing the filter of sexual reproduction.

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.

Evolutionary mechanisms and diversity in cancer.

The recently introduced genome theory of cancer evolution provides a new framework for evolutionary studies on cancer. In particular, the established relationship between the large number of individual molecular mechanisms and the general evolutionary mechanism of cancer calls upon a change in our strategies that have been based on the characterization of common cancer gene mutations and their defined pathways. To further explain the significance of the genome theory of cancer evolution, a brief review will be presented describing the various attempts to illustrate the evolutionary mechanism of cancer, followed by further analysis of some key components of somatic cell evolution, including the diversity of biological systems, the multiple levels of information systems and control systems, the two phases (the punctuated or discontinuous phase and gradual Darwinian stepwise phase) and dynamic patterns of somatic cell evolution where genome replacement is the driving force. By linking various individual molecular mechanisms to the level of genome population diversity and tumorigenicity, the general mechanism of cancer has been identified as the evolutionary mechanism of cancer, which can be summarized by the following three steps including stress-induced genome instability, population diversity or heterogeneity, and genome-mediated macroevolution. Interestingly, the evolutionary mechanism is equal to the collective aggregate of all individual molecular mechanisms. This relationship explains why most of the known molecular mechanisms can contribute to cancer yet there is no single dominant mechanism for the majority of clinical cases. Despite the fact that each molecular mechanism can serve as a system stress and initiate the evolutionary process, to achieve cancer, multiple cycles of genome-mediated macroevolution are required and are a stochastically determined event. Finally, the potential clinical implications of the evolutionary mechanism of cancer are briefly reviewed.

Comparison of mitotic cell death by chromosome fragmentation to premature chromosome condensation.

Mitotic cell death is an important form of cell death, particularly in cancer. Chromosome fragmentation is a major form of mitotic cell death which is identifiable during common cytogenetic analysis by its unique phenotype of progressively degraded chromosomes. This morphology however, can appear similar to the morphology of premature chromosome condensation (PCC) and thus, PCC has been at times confused with chromosome fragmentation. In this analysis the phenomena of chromosome fragmentation and PCC are reviewed and their similarities and differences are discussed in order to facilitate differentiation of the similar morphologies. Furthermore, chromosome pulverization, which has been used almost synonymously with PCC, is re-examined. Interestingly, many past reports of chromosome pulverization are identified here as chromosome fragmentation and not PCC. These reports describe broad ranging mechanisms of pulverization induction and agree with recent evidence showing chromosome fragmentation is a cellular response to stress. Finally, biological aspects of chromosome fragmentation are discussed, including its application as one form of non-clonal chromosome aberration (NCCA), the driving force of cancer evolution.

Stochastic cancer progression driven by non-clonal chromosome aberrations.

Cancer research has previously focused on the identification of specific genes and pathways responsible for cancer initiation and progression based on the prevailing viewpoint that cancer is caused by a stepwise accumulation of genetic aberrations. This viewpoint, however, is not consistent with the clinical finding that tumors display high levels of genetic heterogeneity and distinctive karyotypes. We show that chromosomal instability primarily generates stochastic karyotypic changes leading to the random progression of cancer. This was accomplished by tracing karyotypic patterns of individual cells that contained either defective genes responsible for genome integrity or were challenged by onco-proteins or carcinogens that destabilized the genome. Analysis included the tracing of patterns of karyotypic evolution during different stages of cellular immortalization. This study revealed that non-clonal chromosomal aberrations (NCCAs) (both aneuploidy and structural aberrations) and not recurrent clonal chromosomal aberrations (CCAs) are directly linked to genomic instability and karyotypic evolution. Discovery of "transitional CCAs" during in vitro immortalization clearly demonstrates that karyotypic evolution in solid tumors is not a continuous process. NCCAs and their dynamic interplay with CCAs create infinite genomic combinations leading to clonal diversity necessary for cancer cell evolution. The karyotypic chaos observed within the cell crisis stage prior to establishment of the immortalization further supports the ultimate importance of genetic aberrations at the karyotypic or genome level. Therefore, genomic instability generated NCCAs are a key driving force in cancer progression. The dynamic relationship between NCCAs and CCAs provides a mechanism underlying chromosomal based cancer evolution and could have broad clinical applications.

Imaging genome abnormalities in cancer research.

Increasing attention is focusing on chromosomal and genome structure in cancer research due to the fact that genomic instability plays a principal role in cancer initiation, progression and response to chemotherapeutic agents. The integrity of the genome (including structural, behavioral and functional aspects) of normal and cancer cells can be monitored with direct visualization by using a variety of cutting edge molecular cytogenetic technologies that are now available in the field of cancer research. Examples are presented in this review by grouping these methodologies into four categories visualizing different yet closely related major levels of genome structures. An integrated discussion is also presented on several ongoing projects involving the illustration of mitotic and meiotic chromatin loops; the identification of defective mitotic figures (DMF), a new type of chromosomal aberration capable of monitoring condensation defects in cancer; the establishment of a method that uses Non-Clonal Chromosomal Aberrations (NCCAs) as an index to monitor genomic instability; and the characterization of apoptosis related chromosomal fragmentations caused by drug treatments.

Chromatin loops are selectively anchored using scaffold/matrix-attachment regions.

The biological significance of nuclear scaffold/matrix-attachment regions (S/MARs) remains a topic of long-standing interest. The key to understanding S/MAR behavior relies on determining the physical attributes of in vivo S/MARs and whether they serve as rigid or flexible chromatin loop anchors. To analyze S/MAR behavior, single and multiple copies of the S/MAR-containing constructs were introduced into various host genomes of transgenic mice and transfected cell lines. These in vivo integration events provided a system to study the association and integration patterns of each introduced S/MAR. By utilizing FISH to visualize directly the localization of S/MARs on the nuclear matrix or chromatin loop, we were able to assign specific attributes to the S/MAR. Surprisingly, when multiple-copy S/MARs were introduced they were selected and used as nuclear matrix anchors in a discriminatory manner, even though they all contained identical primary sequences. This selection process was probably mediated by S/MAR availability including binding strength and copy number, as reflected by the expression profiles and association of multi-copy tandem inserted constructs. Whereas S/MARs functioned as the mediators of loop attachment, they were used in a selective and dynamic fashion. Consequently, S/MAR anchors were necessary but not sufficient for chromatin loops to form. These observations reconcile many seemingly contradictory attributes previously associated with S/MARs.