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The year 2021 marks the 50th anniversary of the National Cancer Act, signed by President Nixon, which declared a national “war on cancer.” Powered by enormous financial support, this past half-century has witnessed remarkable progress in understanding the individual molecular mechanisms of cancer, primarily through the characterization of cancer genes and the phenotypes associated with their pathways. Despite millions of publications and the overwhelming volume data generated from the Cancer Genome Project, clinical benefits are still lacking. In fact, the massive, diverse data also unexpectedly challenge the current somatic gene mutation theory of cancer, as well as the initial rationales behind sequencing so many cancer samples. Therefore, what should we do next? Should we continue to sequence more samples and push for further molecular characterizations, or should we take a moment to pause and think about the biological meaning of the data we have, integrating new ideas in cancer biology? On this special anniversary, we implore that it is time for the latter. We review the Genome Architecture Theory, an alternative conceptual framework that departs from gene-based theories. Specifically, we discuss the relationship between genes, genomes, and information-based platforms for future cancer research. This discussion will reinforce some newly proposed concepts that are essential for advancing cancer research, including two-phased cancer evolution (which reconciles evolutionary contributions from karyotypes and genes), stress-induced genome chaos (which creates new system information essential for macroevolution), the evolutionary mechanism of cancer (which unifies diverse molecular mechanisms to create new karyotype coding during evolution), and cellular adaptation and cancer emergence (which explains why cancer exists in the first place). We hope that these ideas will usher in new genomic and evolutionary conceptual frameworks and strategies for the next 50 years of cancer research.

We appear to be faced with ‘two truths’ in cancer—one of major advances and successes and another one of remaining short-comings and significant challenges. Despite decades of research and substantial progress in treating cancer, most patients with metastatic cancer still experience great suffering and poor outcomes. Metastatic cancer, for the vast majority of patients, remains incurable. In the context of advanced disease, many clinical trials report only incremental advances in progression-free and overall survival. At the same time, the breadth and depth of new scientific discoveries in cancer research are staggering. These discoveries are providing increasing mechanistic detail into the inner workings of normal and cancer cells, as well as into cancer–host interactions; however, progress remains frustratingly slow in translating these discoveries into improved diagnostic, prognostic, and therapeutic interventions. Despite enormous advances in cancer research and progress in progression-free survival, or even cures, for certain cancer types—with earlier detection followed by surgical, adjuvant, targeted, or immuno- therapies, we must challenge ourselves to do even better where patients do not respond or experience evolving therapy resistance. We propose that defining cancer evolution as a separate domain of study and integrating the concept of evolvability as a core hallmark of cancer can help position scientific discoveries into a framework that can be more effectively harnessed to improve cancer detection and therapy outcomes and to eventually decrease cancer lethality. In this perspective, we present key questions and suggested areas of study that must be considered—not only by the field of cancer evolution, but by all investigators researching, diagnosing, and treating cancer.

The powerful utilities of current DNA sequencing technology question the value of developing clinical cytogenetics any further. By briefly reviewing the historical and current challenges of cytogenetics, the new conceptual and technological platform of the 21st century clinical cytogenetics is presented. Particularly, the genome architecture theory (GAT) has been used as a new framework to emphasize the importance of clinical cytogenetics in the genomic era, as karyotype dynamics play a central role in information-based genomics and genome-based macroevolution. Furthermore, many diseases can be linked to elevated levels of genomic variations within a given environment. With karyotype coding in mind, new opportunities for clinical cytogenetics are discussed to integrate genomics back into cytogenetics, as karyotypic context represents a new type of genomic information that organizes gene interactions. The proposed research frontiers include: 1. focusing on karyotypic heterogeneity (e.g., classifying non-clonal chromosome aberrations (NCCAs), studying mosaicism, heteromorphism, and nuclear architecture alteration-mediated diseases), 2. monitoring the process of somatic evolution by characterizing genome instability and illustrating the relationship between stress, karyotype dynamics, and diseases, and 3. developing methods to integrate genomic data and cytogenomics. We hope that these perspectives can trigger further discussion beyond traditional chromosomal analyses. Future clinical cytogenetics should profile chromosome instability-mediated somatic evolution, as well as the degree of non-clonal chromosomal aberrations that monitor the genomic system’s stress response. Using this platform, many common and complex disease conditions, including the aging process, can be effectively and tangibly monitored for health benefits.

Simple Summary Fusion of exons or introns from two different genes can lead to the formation of chimeric RNAs. Several recent studies have reported that chimeric RNAs promote tumorigenesis and cancer drug resistance. Therefore, chimeric RNAs are crucial for generating phenotypic diversity between cancer cells that drives the adaptive evolution of cancer. Here, we will discuss the significance of chimeric RNAs in generating functional diversity in cancer cells and their potential impact on developing cancer from an evolutionary viewpoint. Abstract Gene fusions can give rise to somatic alterations in cancers. Fusion genes have the potential to create chimeric RNAs, which can generate the phenotypic diversity of cancer cells, and could be associated with novel molecular functions related to cancer cell survival and proliferation. The expression of chimeric RNAs in cancer cells might impact diverse cancer-related functions, including loss of apoptosis and cancer cell plasticity, and promote oncogenesis. Due to their recurrence in cancers and functional association with oncogenic processes, chimeric RNAs are considered biomarkers for cancer diagnosis. Several recent studies demonstrated that chimeric RNAs could lead to the generation of new functionality for the resistance of cancer cells against drug therapy. Therefore, targeting chimeric RNAs in drug resistance cancer could be useful for developing precision medicine. So, understanding the functional impact of chimeric RNAs in cancer cells from an evolutionary perspective will be helpful to elucidate cancer evolution, which could provide a new insight to design more effective therapies for cancer patients in a personalized manner.

The importance of human microbiota and their genomes, human microbiome, in health and disease has been increasingly recognized. Human microbiome has tremendous impact in our pathophysiology by modulating metabolic functions, protecting against pathogens, and educating the immune system. In particular, human microbiome is a major player at the interface between humans and their environment and therefore is crucial to the development of environmental disease. In this article, we briefly summarize and interpret the recent advances in the understanding of the roles of human microbiome in environment-related health and disease, and call for a more systematic integration of human microbiome and environmental disease research within the framework of evolutionary medicine.

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.

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.

The main goals of illustrating the cancer genomic landscape are to identify common gene mutations and profile genetic signatures for specific types or stages of cancer. However, the biggest finding is the overwhelming genetic/nongenetic heterogeneity in cancer, reflected in landscapes of gene mutations, epigenomic changes, genome/karyotype alterations, and somatic copy number variations. To promote the integration of these different landscapes, the genome theory of somatic cell evolution is briefly discussed, which redefines the concept of the genome, and links genome-mediated genomic coding to system inheritance or blueprint. The multiple-level landscape model is introduced following the description of punctuated cancer evolution, the relationship of evolutionary phase transition and genome instability, the importance of fuzzy inheritance in heterogeneity, and the mechanism of cancer as an emergent system with different genomes. Micro- and macroevolution are related to gene/epigene and genome evolutions, respectively, and it is thus important to compare the patterns and principles of cancer and organismal evolution.

Signal transducer and activator of transcription (Stat)-3 signals mediate many of the metabolic effects of the fat cell-derived hormone, leptin. In mice, brain-specific depletion of either the long form of the leptin receptor (Lepr) or Stat3 results in comparable obese phenotypes as does replacement of Lepr with an altered leptin receptor locus that codes for a Lepr unable to interact with Stat3. Among the multiple brain regions containing leptin-sensitive Stat3 sites, cells expressing feeding-related neuropeptides in the arcuate nucleus of the hypothalamus have received much of the focus. To determine the contribution to energy homeostasis of Stat3 expressed in agouti-related protein (Agrp)/neuropeptide Y (Npy) arcuate neurons, Stat3 was deleted specifically from these cells, and several metabolic indices were measured. It was found that deletion of Stat3 from Agrp/Npy neurons resulted in modest weight gain that was accounted for by increased adiposity. Agrp/Stat3-deficient mice also showed hyperleptinemia, and high-fat diet-induced hyperinsulinemia. Stat3 deletion in Agrp/Npy neurons also resulted in altered hypothalamic gene expression indicated by increased Npy mRNA and decreased induction of suppressor of cytokine signaling-3 in response to leptin. Agrp mRNA levels in the fed or fasted state were unaffected. Behaviorally, mice without Stat3 in Agrp/Npy neurons were mildly hyperphagic and hyporesponsive to leptin. We conclude that Stat3 in Agrp/Npy neurons is required for normal energy homeostasis, but Stat3 signaling in other brain areas also contributes to the regulation of energy homeostasis. Fil: Gong, Lijie. Wayne State University School of Medicine; Estados Unidos Fil: Yao, Fayi. Wayne State University School of Medicine; Estados Unidos Fil: Hockman, Kristin. Wayne State University School of Medicine; Estados Unidos Fil: Heng, Henry H.. Wayne State University School of Medicine; Estados Unidos Fil: Morton, Gregory J.. University of Washington; Estados Unidos Fil: Takeda, Kiyoshi. Kyushu University; Japón Fil: Akira, Shizuo. Osaka University; Japón Fil: Low, Malcolm J.. Oregon Health and Science University; Estados Unidos Fil: Rubinstein, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina Fil: MacKenzie, Robert G.. Wayne State University School of Medicine; Estados Unidos

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.

Endoplasmic Reticulum (ER) stress refers to a condition of accumulation of unfolded or misfolded proteins in the ER lumen. A variety of biochemical stimuli or pathophysiologic conditions can directly or indirectly induce ER stress, leading to activation of an ER-originated adaptive signaling response called Unfolded Protein Response (UPR). Recent studies demonstrated that ER stress and UPR signaling are critically involved in the initiation and progression of many diseases, such as metabolic disease, cardiovascular disease, neurodegenerative disease, and cancer. In this study, we show that ER stress induced by pharmacologic reagents, including tunicamycin (TM) and thapsigargin (Tg), promotes hepatic lipogenesis and lipid droplet formation. Using quantitative gene expression analysis, we identified 3 groups of key lipogenic regulators or enzymes that are inducible by pharmacological ER stress in a human hepatoma cell line Huh-7. These ER stress-inducible lipogenic factors include: 1) lipogenic trans-activators including CCAAT/ enhancer binding protein alpha (C/EBPα), peroxisome proliferator-activated receptor gamma (PPARγ), PPARγ coacti-vator 1-alpha (PGC1α), and Liver X receptor alpha (LXRα); 2) components of lipid droplets including fat-specific protein 27 (FSP27), adipose differentiation related protein (ADRP), fat-inducing transcript 2 (FIT2), and adipocyte lipid-binding protein (AP2); 3) key enzymes involved in de novo lipogenesis including acetyl-CoA carboxylase 1 (ACC1) and stearoyl-CoA desaturase-1 (SCD1). Supporting the role of pharmacologic ER stress in up-regulating de novo lipogenesis, TM or Tg treatment significantly increased accumulation of cytosolic lipid droplet formation in the hepatocytes. Moreover, we showed that forced expression of an activated form of X-box binding protein 1 (XBP1), a potent UPR trans-activator, can dramatically increase expression of PPARγ and C/EBPα in Huh-7 cells. The identification of ER stress-inducible lipogenic regulators provides important insights into the molecular basis by which acute ER stress promotes de novo lipogenesis. In summary, the findings from this study have important implication in understanding the link between ER stress and metabolic disease.

Hemogen is a nuclear protein encoded by HEMGN (also known as hemogen in mouse, EDAG in human and RP59 in rat). It is considered to be a hematopoiesis-specific gene that is expressed during the ontogeny of hematopoiesis. Herein, we characterize two distinct splicing variants of HEMGN mRNA with restricted expression to hematopoietic cells and to round spermatids in the testis, respectively. Expression of the testis-specific HEMGN mRNA (HEMGN-t) is developmentally regulated and is concurrent with the first wave of meiosis in prepuberal mice. Sequence analysis reveals that HEMGN-t and the hematopoietic HEMGN mRNA (HEMGN-h) share a common coding sequence with distinct 5' and 3' untranslated regions and that these two isoforms are transcribed from the same gene locus, HEMGN, through the use of alternative promoters and polyadenylation sites. Thus, HEMGN expression exemplifies a developmental regulatory mechanism by which the diversification of gene expression is achieved through using distinct regulatory sequences in different cell types. Moreover, the existence of a testis-specific isoform of HEMGN suggests a role in spermatogenesis. Finally, fluorescence in situ hybridization demonstrates that HEMGN is localized to chromosome 4 A5-B2 in mouse and to chromosome 9q22 in human, which is a region known to harbor a cluster of leukemia breakpoints.