Genome chaos: Creating new genomic information essential for cancer macroevolution
Introduction
Following a half century of extensive molecular research intended to identify and characterize common cancer gene mutations, the facts are at odds with initial expectations. The somatic gene mutation theory, which has dominated cancer research ever since the identification of the first oncogene, predicted that “less than a handful” of cancer genes exist; however, hundreds of “cancer-causing genetic factors” were reported [[1], [2], [3]]. The current Cancer Genome Project was intended to winnow down the candidates using large numbers of clinical data; instead, it unearthed more [4]. Such unexpected diverse cancer gene mutation profiles challenge the key rationale of focusing on the identification of a few commonly shared mutations—obviously, the concept that five to six key common cancer genes are responsible for stepwise “cancer development” does not hold up [1,2,5,6]. Furthermore, a slew of incorrect predictions and limited clinical implications forcefully question the gene mutation theory itself.
Most researchers have unfortunately ignored such conceptual limitations of the cancer gene mutation theory. The gene theory’s incorrect predictions do not shake their belief but rather propels a strategy of producing more gene and molecular pathway data, which, under the gene theory, should eventually deliver the gene-based mechanisms for a cure.
In contrast, increased researchers have proposed an array of alternative hypotheses/approaches to challenge the gene-centric status quo. Some well-known examples include the Aneuploidy Theory of Cancer [7,8]; the Tissue Organization Field Theory [9]; the idea that cancers represent various new cellular species [2,7,[10], [11], [12], [13]]; the cancer attractor theory [14] and endogenous network theory [15]; the concept of cancer as atavism [16,17], re-activated retrotransposon-mediated genomic changes [18], or as a result of a mismatch between the human genome and rapidly changing lifestyles [19]; theories influenced by developmental biology and epigenetics [[20], [21], [22]]; theories related to genetic and impact from inflammation or micro-organismal-system environmental factors (infection, metabolism, mutator phenotypes) [[23], [24], [25]]; the cancer stem cell hypothesis [26,27]; the polyploidy and giant cells concept [[28], [29], [30]]; and the theory of heterogeneity and tumor society [[31], [32], [33]] (for more details, see [2,5]).
Even though these alternative approaches cover diverse biological disciplines and distinguish themselves from the core of the cancer gene mutation theory, many still lie within its reductionist framework, even if aiming to shine light on different, less popular molecular mechanisms. Usually, they shift the research focus from DNA/RNA/proteins to other small bio-molecules (lipids, sugars, fatty acids), from cancer cells to different cell types (stem cells, cells with different degrees of differentiation, stromal cells), from nuclear organization to other subcellular organization (mitochondria, exosomes, condensates, circulating free DNA), or from genomic elements to micro-environments (immune system, microbiota). For example, increased studies focus on different levels of genetic/epigenetic and genomic organization (profiling the epigenome rather than genes, characterizing copy number variations, analyzing noncoding rather than coding sequences), various novel aspects of somatic evolution (the source of non-genetic variants, the function of higher system constraints like tissues or immune systems), and key non-genomic factors related to evolution (energy, stress response including inflammation, network dynamics, system maintenance/repair, adaptation). Importantly, most of these “new theories” have adopted similar platforms by studying molecular pathways, essentially treating favored subjects with a gene-based understanding. As a result, most alternative research often represents an effort to modify the gene theory by extending its coverage, without challenging its underlying gene-centric and neo-Darwinian evolutionary frameworks [2,5]. One fundamental realization continues to be missing: different levels of biosystems require different types of inheritance and evolutionary selection. The genome is not just a bag of genes, and gene- and genome-mediated evolution involve different laws. For example, most current systems biologists ignore karyotype dynamics when discussing network interactions, assuming that system inheritance is gene content-based and that network dynamics occur within identical karyotypes. Such assumptions are popular in developmental fields as well, which has slowed down the effort to integrate developmental programs with two-phased cancer evolution.
What we need is a new conceptual framework which will not only explain what cancer is, using current molecular data in the context of creating new bio-systems, but also illustrate how cancer emerges from normal tissue over time and what types of genomic information and cancer evolutionary mechanisms are involved at each stage. Without such a new framework, no matter how much data we collect (genetic, epigenetic, cellular, or tissual), how many models we develop (concerning genomics, development, or systems biology), or how many molecular mechanisms we discover, confusion will only increase. As Bob Weinberg candidly pointed out: “The data that we now generate overwhelm our abilities of interpretation, and the attempts of the new discipline of ‘systems biology’ to address this shortfall have to date produced few insights into cancer biology beyond those revealed by simple, home-grown intuition. The coupling between observational data and biological insight is frayed if not broken…We lack the conceptual paradigms and computational strategies for dealing with this complexity” [34]. Clearly, the paradigm utilized is of ultimate importance, as any powerful computational strategies or impressive amounts of data depend on paradigms to correctly guide and interpret them.
Fortunately, the Genome Theory has been introduced to serve as this necessary novel paradigm [1,2,5,35]. Directly applied to cancer research, the Genome Theory: 1) defines cancer as a new system emergent from normal tissue, which often results from evolutionary trade-offs; 2) incorporates the discovery of two-phased cancer evolution containing cellular (punctuated) macroevolution and cellular (stepwise) microevolution, which correspond to karyotype alterations and gene mutations/epigenetic alterations, respectively; 3) describes a new two-phased cancer model where phase transitions (including transformation, metastasis, and drug resistance) are characterized by the formation of new genomes through genome reorganization followed by stochastic gene-mediated population growth; 4) highlights genomic heterogeneity in cellular adaptation and new system emergence, where the mechanism of heterogeneity is fuzzy inheritance; 5) establishes an Evolutionary Mechanism of Cancer that unifies diverse individual molecular mechanisms, including developmental and tissue factors; 6) proposes that altering the topology of sequence order along chromosomes creates new bioinformation essential for cancer evolution; 7) redefines genomic/non-genetic information and their interactive relationship in somatic evolution; 8) exposes how karyotype coding defines system inheritance and serves as an organizer for the genomic network; 9) illustrates the function of meiotic pairing through sexual reproduction as the mechanism of karyotype coding maintenance; and 10) reveals the importance of separating the germline (for system constraint) and somatic genome (for system dynamics by plasticity), which explains the high level of chromosomal instability observed in somatic cells [5,36].
In this Perspective, the general mechanism of cancer is discussed using the Genome Theory, in the context of genomic information, cellular stress, and cellular macroevolution. In particular, the following topics will be examined: how new genomic information leads to cancer system emergence; the relationship between genome chaos and various types of chromosomal abnormalities; and the differing roles of karyotype alteration and gene mutation, diverse cellular phenotypes, orderly and abnormal development, and stochastic cancer emergence, given the discovery of two-phased cancer evolution and array of genomic/developmental information involved.
Section snippets
Why do cancers represent new emergent systems from tissue, often as trade-offs of cellular adaptation under stress?
How to define or even phrase a question strongly influences the direction of its research and consequences, including ideological boundaries, types of hypotheses, and experimental systems and methodologies. For example, when cancer is phrased as a problem of “out of control growth,” efforts to understand normal and abnormal growth become a priority. In contrast, if cancer is phased as a “developmental issue,” the timing and spatial regulation of differentiation and de-differentiation become a
Why is karyotype coding (chromosomal sets coding), compared to multiple other levels of genomic and non-genomic information, ultimately important for cancer evolution?
So far, the publication of two-phased cancer evolution and the Genome Theory has failed to drastically change the research landscape [1,2,5,35,51]. The main obstacle to these new ideas has been the gene theory and its traditional paradigm of gene-centric inheritance and neo-Darwinian stepwise evolution. In this section, we propose the concept of multiple levels of bio-information, identify dominant types of information dynamics for each given level or scale, and justify how karyotype-encoded
What is the underlying relationship between different types of genome variations, under normal and crisis conditions?
Plenty of molecular mechanistic studies exist for given chromosomal aberrations such as aneuploidy and translocations, and most focus on gene mutations and molecular pathways. In contrast, fewer efforts have been made to study the relationship among different types of chromosomal variations [55,65]. Recently, the linkage between cellular stress, immune response, and different types of chromosomal variations has been established [85,99]. After establishing genome-level heterogeneity as the
Implications and future research
The two-phased cancer evolutionary model calls for establishing new platforms to study how new systems emerge from tissue. Even though there is an array of new perspectives, the following subjects deserve more attention as they represent some major confusions and debates in the field:
Funding source
No specific funding for this manuscript.
Declaration of Competing Interest
The authors declare that there are no conflicts of interest.
Acknowledgments
This manuscript is part of our series of publications on the subject of “the mechanisms of cancer and organismal evolution.” We would like to thank Robert Gatenby, James Shapiro and Denis Noble, and Eagle Zhang for their insights on non-genomic information, evolution, and genomic terms, respectively. Some cancer evolutionary ideas in this manuscript have been discussed in the recent Cancer and Evolution Symposium (https://cancerevolution.org).
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