scholarly journals Oncogenic Viruses as Entropic Drivers of Cancer Evolution

2021 ◽  
Vol 1 ◽  
Author(s):  
Italo Tempera ◽  
Paul M. Lieberman
Keyword(s):  
Systems Biology ◽  
Viral Infection ◽  
Cancer Cell ◽  
Driving Forces ◽  
Tumor Biology ◽  
Oncogenic Viruses ◽  
Cancer Evolution ◽  
Evolutionary Forces ◽  
Cell Evolution ◽  
Novel Therapeutic Strategies

Viral infection is an indisputable causal factor for nearly 17% of all human cancers. However, the diversity and complexity of oncogenic mechanisms raises new questions as to the mechanistic role of viruses in cancer. Classical viral oncogenes have been identified for all tumor-associated viruses. These oncogenes can have multiple oncogenic activities that may or may not be utilized in a particular tumor cell. In addition, stochastic events, like viral mutation and integration, as well as heritable host susceptibilities and immune deficiencies are also implicated in tumorigenesis. A more contemporary view of tumor biology highlights the importance of evolutionary forces that select for phenotypes better adapted to a complex and changing environment. Given the challenges of prioritizing singular mechanistic causes, it may be necessary to integrate concepts from evolutionary theory and systems biology to better understand viral cancer-driving forces. Here, we propose that viral infection provides a biological “entropy” that increases genetic variation and phenotypic plasticity, accelerating the main driving forces of cancer cell evolution. Viruses can also influence the evolutionary selection criteria by altering the tumor microenvironment and immune signaling. Utilizing concepts from cancer cell evolution, population genetics, thermodynamics, and systems biology may provide new perspectives on viral oncogenesis and identify novel therapeutic strategies for treating viruses and cancer.

Measuring evolutionary cancer dynamics from genome sequencing, one patient at a time

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Giulio Caravagna
Keyword(s):  
Genome Sequencing ◽  
Cancer Evolution ◽  
Sequencing Data ◽  
Evolutionary Forces ◽  
Sequencing Technologies ◽  
Cancer Genome Sequencing ◽  
Multiple Resolutions ◽  
Multiple Patients ◽  
Single Tumour ◽  
Generation Sequencing

AbstractCancers progress through the accumulation of somatic mutations which accrue during tumour evolution, allowing some cells to proliferate in an uncontrolled fashion. This growth process is intimately related to latent evolutionary forces moulding the genetic and epigenetic composition of tumour subpopulations. Understanding cancer requires therefore the understanding of these selective pressures. The adoption of widespread next-generation sequencing technologies opens up for the possibility of measuring molecular profiles of cancers at multiple resolutions, across one or multiple patients. In this review we discuss how cancer genome sequencing data from a single tumour can be used to understand these evolutionary forces, overviewing mathematical models and inferential methods adopted in field of Cancer Evolution.

scholarly journals Tumour viruses and innate immunity

2017 ◽  
Vol 372 (1732) ◽  
pp. 20160267 ◽  
Author(s):  
Sharon E. Hopcraft ◽  
Blossom Damania
Keyword(s):  
Immune Response ◽  
Inflammatory Response ◽  
Viral Infection ◽  
Innate Immune Response ◽  
Innate Immune ◽  
Host Cells ◽  
Oncogenic Viruses ◽  
Barr Virus ◽  
Human T Cell ◽  
Epstein Barr

Host cells sense viral infection through pattern recognition receptors (PRRs), which detect pathogen-associated molecular patterns (PAMPs) and stimulate an innate immune response. PRRs are localized to several different cellular compartments and are stimulated by viral proteins and nucleic acids. PRR activation initiates signal transduction events that ultimately result in an inflammatory response. Human tumour viruses, which include Kaposi's sarcoma-associated herpesvirus, Epstein–Barr virus, human papillomavirus, hepatitis C virus, hepatitis B virus, human T-cell lymphotropic virus type 1 and Merkel cell polyomavirus, are detected by several different PRRs. These viruses engage in a variety of mechanisms to evade the innate immune response, including downregulating PRRs, inhibiting PRR signalling, and disrupting the activation of transcription factors critical for mediating the inflammatory response, among others. This review will describe tumour virus PAMPs and the PRRs responsible for detecting viral infection, PRR signalling pathways, and the mechanisms by which tumour viruses evade the host innate immune system. This article is part of the themed issue ‘Human oncogenic viruses’.

scholarly journals Loss of USP28 and SPINT2 expression promotes cancer cell survival after whole genome doubling

2021 ◽  
Author(s):  
Sara Vanessa Bernhard ◽  
Katarzyna Seget-Trzensiok ◽  
Christian Kuffer ◽  
Dragomir B. Krastev ◽  
Lisa-Marie Stautmeister ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Dna Damage ◽  
Cancer Cell ◽  
Cancer Cell Line ◽  
Colorectal Cancer Cell Line ◽  
Whole Genome ◽  
Cancer Evolution ◽  
Genome Doubling ◽  
Whole Genome Doubling ◽  
Frequent Event

Abstract Background Whole genome doubling is a frequent event during cancer evolution and shapes the cancer genome due to the occurrence of chromosomal instability. Yet, erroneously arising human tetraploid cells usually do not proliferate due to p53 activation that leads to CDKN1A expression, cell cycle arrest, senescence and/or apoptosis. Methods To uncover the barriers that block the proliferation of tetraploids, we performed a RNAi mediated genome-wide screen in a human colorectal cancer cell line (HCT116). Results We identified 140 genes whose depletion improved the survival of tetraploid cells and characterized in depth two of them: SPINT2 and USP28. We found that SPINT2 is a general regulator of CDKN1A transcription via histone acetylation. Using mass spectrometry and immunoprecipitation, we found that USP28 interacts with NuMA1 and affects centrosome clustering. Tetraploid cells accumulate DNA damage and loss of USP28 reduces checkpoint activation, thus facilitating their proliferation. Conclusions Our results indicate three aspects that contribute to the survival of tetraploid cells: (i) increased mitogenic signaling and reduced expression of cell cycle inhibitors, (ii) the ability to establish functional bipolar spindles and (iii) reduced DNA damage signaling.

scholarly journals Establishment and Characterization of Immortalized Miniature Pig Pancreatic Cell Lines Expressing Oncogenic K-RasG12D

2020 ◽  
Vol 21 (22) ◽  
pp. 8820
Author(s):  
Hae-Jun Yang ◽  
Bong-Seok Song ◽  
Bo-Woong Sim ◽  
Yena Jung ◽  
Unbin Chae ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cell Line ◽  
Cell Lines ◽  
Cancer Cell ◽  
Tumor Biology ◽  
Human Pancreatic Cancer ◽  
Miniature Pig ◽  
Pancreatic Cell ◽  
Treatment And Prevention ◽  
Acinar To Ductal Metaplasia

In recent decades, many studies on the treatment and prevention of pancreatic cancer have been conducted. However, pancreatic cancer remains incurable, with a high mortality rate. Although mouse models have been widely used for preclinical pancreatic cancer research, these models have many differences from humans. Therefore, large animals may be more useful for the investigation of pancreatic cancer. Pigs have recently emerged as a new model of pancreatic cancer due to their similarities to humans, but no pig pancreatic cancer cell lines have been established for use in drug screening or analysis of tumor biology. Here, we established and characterized an immortalized miniature pig pancreatic cell line derived from primary pancreatic cells and pancreatic cancer-like cells expressing K-rasG12D regulated by the human PTF1A promoter. Using this immortalized cell line, we analyzed the gene expression and phenotypes associated with cancer cell characteristics. Notably, we found that acinar-to-ductal transition was caused by K-rasG12D in the cell line constructed from acinar cells. This may constitute a good research model for the analysis of acinar-to-ductal metaplasia in human pancreatic cancer.

scholarly journals Mutant Allele Imbalance in Cancer

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Craig M. Bielski ◽  
Barry S. Taylor
Keyword(s):  
Cancer Biology ◽  
Mutant Allele ◽  
Tumor Biology ◽  
Cellular Level ◽  
Driver Mutations ◽  
Annual Review ◽  
Publication Date ◽  
Cancer Evolution ◽  
Allele Imbalance ◽  
And Function

The search for somatic mutations that drive the initiation and progression of human tumors has dominated recent cancer research. While much emphasis has been placed on characterizing the prevalence and function of driver mutations, comparatively less is known about their serial genetic evolution. Indeed, study of this phenomenon has largely focused on tumor-suppressor genes recessive at the cellular level or mechanisms of resistance in tumors with mutant oncogenes targeted by therapy. There is, however, a growing appreciation that despite a decades-old presumption of heterozygosity, changes in mutant oncogene zygosity are common and drive dosage and stoichiometry changes that lead to selective growth advantages. Here, we review the recent progress in understanding mutant allele imbalance and its implications for tumor biology, cancer evolution, and response to anticancer therapy. Expected final online publication date for the Annual Review of Cancer Biology, Volume 5 is March 4, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals tugHall: a simulator of cancer-cell evolution based on the hallmarks of cancer and tumor-related genes

2020 ◽  
Vol 36 (11) ◽  
pp. 3597-3599 ◽  
Author(s):  
Iurii S Nagornov ◽  
Mamoru Kato
Keyword(s):  
Cancer Cell ◽  
Tumor Heterogeneity ◽  
Clonal Evolution ◽  
Source Code ◽  
Genomic Data ◽  
Supplementary Information ◽  
Cell Behavior ◽  
Supplementary Data ◽  
Hallmarks Of Cancer ◽  
Cell Evolution

Abstract Summary The flood of recent cancer genomic data requires a coherent model that can sort out the findings to systematically explain clonal evolution and the resultant intra-tumor heterogeneity (ITH). Here, we present a new mathematical model designed to computationally simulate the evolution of cancer cells. The model connects the well-known hallmarks of cancer with the specific mutational states of tumor-related genes. The cell behavior phenotypes are stochastically determined, and the hallmarks probabilistically interfere with the phenotypic probabilities. In turn, the hallmark variables depend on the mutational states of tumor-related genes. Thus, our software can deepen our understanding of cancer-cell evolution and generation of ITH. Availability and implementation The open-source code is available in the repository https://github.com/nagornovys/Cancer_cell_evolution. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Systems biology and the host response to viral infection

2007 ◽  
Vol 25 (12) ◽  
pp. 1383-1389 ◽  
Author(s):  
Seng-Lai Tan ◽  
Gopinath Ganji ◽  
Bryan Paeper ◽  
Sean Proll ◽  
Michael G Katze
Keyword(s):  
Systems Biology ◽  
Viral Infection ◽  
Host Response

scholarly journals Comprehensive genomic profiling in diabetic nephropathy reveals the predominance of proinflammatory pathways

2013 ◽  
Vol 45 (16) ◽  
pp. 710-719 ◽  
Author(s):  
K. J. Kelly ◽  
Yunlong Liu ◽  
Jizhong Zhang ◽  
Chirayu Goswami ◽  
Hai Lin ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Systems Biology ◽  
Gene Networks ◽  
Inflammatory Cells ◽  
Rna Seq ◽  
Cycle Arrest ◽  
Comprehensive Genomic Profiling ◽  
Novel Therapeutic Strategies ◽  
Stage Renal Disease ◽  
End Stage

Despite advances in the treatment of diabetic nephropathy (DN), currently available therapies have not prevented the epidemic of progressive chronic kidney disease (CKD). The morbidity of CKD, and the inexorable increase in the prevalence of end-stage renal disease, demands more effective approaches to prevent and treat progressive CKD. We undertook next-generation sequencing in a rat model of diabetic nephropathy to study in depth the pathogenic alterations involved in DN with progressive CKD. We employed the obese, diabetic ZS rat, a model that develops diabetic nephropathy, characterized by progressive CKD, inflammation, and fibrosis, the hallmarks of human disease. We then used RNA-seq to examine the combined effects of renal cells and infiltrating inflammatory cells acting as a pathophysiological unit. The comprehensive systems biology analysis of progressive CKD revealed multiple interactions of altered genes that were integrated into morbid networks. These pathological gene assemblies lead to renal inflammation and promote apoptosis and cell cycle arrest in progressive CKD. Moreover, in what is clearly a major therapeutic challenge, multiple and redundant pathways were found to be linked to renal fibrosis, a major cause of kidney loss. We conclude that systems biology applied to progressive CKD in DN can be used to develop novel therapeutic strategies directed to restore critical anomalies in affected gene networks.

scholarly journals Cancer cell lines show high heritability for motility but not generation time

2020 ◽  
Vol 7 (4) ◽  
pp. 191645
Author(s):  
Anastasia V. Wass ◽  
George Butler ◽  
Tiffany B. Taylor ◽  
Philip R. Dash ◽  
Louise J. Johnson
Keyword(s):  
Cancer Cells ◽  
Cell Lines ◽  
Cancer Cell ◽  
Generation Time ◽  
Natural Populations ◽  
Cancer Cell Lines ◽  
Raw Material ◽  
Cancer Evolution ◽  
Heritable Variation

Tumour evolution depends on heritable differences between cells in traits affecting cell survival or replication. It is well established that cancer cells are genetically and phenotypically heterogeneous; however, the extent to which this phenotypic variation is heritable is far less well explored. Here, we estimate the broad-sense heritability ( H 2 ) of two cell traits related to cancer hallmarks––cell motility and generation time––within populations of four cancer cell lines in vitro and find that motility is strongly heritable. This heritability is stable across multiple cell generations, with heritability values at the high end of those measured for a range of traits in natural populations of animals or plants. These findings confirm a central assumption of cancer evolution, provide a first quantification of the evolvability of key traits in cancer cells and indicate that there is ample raw material for experimental evolution in cancer cell lines. Generation time, a trait directly affecting cell fitness, shows substantially lower values of heritability than cell speed, consistent with its having been under directional selection removing heritable variation.

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