Multiple myeloma patients with a long remission after autologous hematopoietic stem cell transplantation.

Autologous stem cell transplantation (autoHCT) is considered standard of care for newly diagnosed multiple myeloma (MM). Although most patients eventually progress after autoHCT, a small proportion achieve a durable response. In this retrospective study we included 1576 patients, 244 (15%) of whom were long-term responders (LTR), defined as having a progression-free survival (PFS) of ≥8 years after transplant. Patients in the LTR group were younger than the non-LTR group (median age 58.4 vs. 59.5 years; p = 0.012), less likely to have high-risk cytogenetics (4% vs. 14%; p < 0.001), more often had <50% bone marrow plasma cells (67% vs. 58%; p = 0.018) and R-ISS stage I disease (43% vs. 34%). More patients in the LTR group received post-transplant maintenance (63% vs. 52%; p = 0.002). Patients in the LTR group had higher rates of complete response (CR) at day100 (41% vs. 27%; p < 0.001) and at best post-transplant response (70% vs. 37%; p < 0.001), compared to the non-LTR group. Patients in the LTR groups had a median PFS of 169.3 months and the median overall survival (OS) had not been reached. The leading cause of death in the LTR was disease progression. In conclusion, 15% of patients in the cohort were LTR after upfront autoHCT, with distinct characteristics and a median PFS of more than 14 years.

Cytogenetic Profile in Monoclonal Gammopathy of Undetermined Significance, Smoldering and Symptomatic Multiple Myeloma: A Study of 1087 Patients with Highly Purified Plasma Cells.

The aim of this study was to examine the cytogenetic profiles of plasma cell neoplasms (PCNs) at various disease stages, encompassing 1087 patients with monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), newly diagnosed multiple myeloma (NDMM), and refractory/relapsed multiple myeloma (RRMM). Fluorescence in situ hybridization (FISH) analyses were conducted on highly purified plasma cell samples, revealing that 96% of patients exhibited at least one cytogenetic abnormality. The genomic complexity escalated from MGUS to SMM and further to NDMM and RRMM, largely driven by 1q gain, del(17p), MYC-rearrangement (MYC-R), del(1p), and tetraploidy. Elevated frequencies of high-risk cytogenetics (59%), 1q gain (44%), and del(17p) (23%), as well as the presence of subclones (48%), were particularly notable in RRMM cases. IGH::CCND1 was observed in 26% of the cases, with no apparent variations across races, ages, or disease groups. Concurrent chromosomal analysis with FISH revealed that the incidence of abnormal karyotypes was strongly correlated with the extent of neoplastic plasma cell infiltration, genomic complexity, and the presence of specific abnormalities like del(17p) and MYC-R. Approximately 98% of the cases with abnormal karyotypes were complex, with most featuring five or more abnormalities. Chromosome 1 structural abnormalities were the most prevalent, found in 65% of cases. The frequent presence of subclones and composite karyotypes underscored the genomic heterogeneity and instability in this cohort.

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.

Micronuclei and Genome Chaos: Changing the System Inheritance.

Micronuclei research has regained its popularity due to the realization that genome chaos, a rapid and massive genome re-organization under stress, represents a major common mechanism for punctuated cancer evolution. The molecular link between micronuclei and chromothripsis (one subtype of genome chaos which has a selection advantage due to the limited local scales of chromosome re-organization), has recently become a hot topic, especially since the link between micronuclei and immune activation has been identified. Many diverse molecular mechanisms have been illustrated to explain the causative relationship between micronuclei and genome chaos. However, the newly revealed complexity also causes confusion regarding the common mechanisms of micronuclei and their impact on genomic systems. To make sense of these diverse and even conflicting observations, the genome theory is applied in order to explain a stress mediated common mechanism of the generation of micronuclei and their contribution to somatic evolution by altering the original set of information and system inheritance in which cellular selection functions. To achieve this goal, a history and a current new trend of micronuclei research is briefly reviewed, followed by a review of arising key issues essential in advancing the field, including the re-classification of micronuclei and how to unify diverse molecular characterizations. The mechanistic understanding of micronuclei and their biological function is re-examined based on the genome theory. Specifically, such analyses propose that micronuclei represent an effective way in changing the system inheritance by altering the coding of chromosomes, which belongs to the common evolutionary mechanism of cellular adaptation and its trade-off. Further studies of the role of micronuclei in disease need to be focused on the behavior of the adaptive system rather than specific molecular mechanisms that generate micronuclei. This new model can clarify issues important to stress induced micronuclei and genome instability, the formation and maintenance of genomic information, and cellular evolution essential in many common and complex diseases such as cancer.

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.

Detecting Chromosome Condensation Defects in Gulf War Illness Patients.

BACKGROUND: Gulf War Illness (GWI) impacts 25-30% of gulf war veterans. Due to its heterogeneity in both etiology and symptoms, it has been challenging to establish the commonly accepted case definition for GWI. Equally challenging are the understanding of the general mechanism of GWI and the development of biomarkers useful for its clinical diagnosis and treatment. OBJECTIVE: We have observed that chromosome condensation defects can be detected in GWI patients. To document this phenomenon in GWI, we aim to describe and compare different types of chromosomal condensation defects in GWI patients, if possible. Since chromosomal condensation represents an important step of ensuring genome integrity, condensation defects could be used as a potential biomarker of GWI. METHODS: Lymphocytes from GWI patients have been used for short term cell culture followed by chromosome slide preparation. Both Giemsa staining and multiple color spectral karyotyping (SKY) were applied to study chromosome aberrations, focusing on different types of condensation defects. RESULTS: At least three subtypes of Defective Mitotic Figures (DMFs) were observed. Some individuals displayed elevated frequencies of DMFs. Another type of condensation defect identified as sticky chromosomes were also observed. CONCLUSION: Various types of condensation defects have been observed in GWI patients. It is rather surprising that some GWI patients exhibited a high level of chromosomal condensation defects. Previously, the elevated frequency of DMFs was only observed in cancer patients. Since chromosome condensation can be linked to other types of chromosome aberrations, as well as cellular stress conditions, the detailed mechanism and clinical impact should be further studied, especially with increased sample size.

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.

High Resolution Fiber-Fluorescence In Situ Hybridization.

High resolution fiber-Fluorescence in situ hybridization (FISH) is an advanced FISH technology that can effectively bridge the resolution gap between probe hybridizing on DNA molecules and chromosomal regions. Since various types of DNA and chromatin fibers can be generated reflecting different degrees of DNA/chromatin packaging status, fiber-FISH technology has been successfully used in diverse molecular cytogenetic/cytogenomic studies. Following a brief review of this technology, including its major development and increasing applications, typical protocols to generate DNA/chromatin fiber will be described, coupled with rationales, as well as technical tips. These released DNA/chromatin fibers are suitable for an array of cytogenetic/cytogenomic analyses.

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.

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.

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.

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.

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.

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.

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.

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.

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.