"In the light of evolution:" keratins as exceptional tumor biomarkers.

Keratins (KRTs) are the intermediate filament-forming proteins of epithelial cells, classified, according to their physicochemical properties, into "soft" and "hard" keratins. They have a key role in several aspects of cancer pathophysiology, including cancer cell invasion and metastasis, and several members of the KRT family serve as diagnostic or prognostic markers. The human genome contains both, functional KRT genes and non-functional KRT pseudogenes, arranged in two uninterrupted clusters on chromosomes 12 and 17. This characteristic renders KRTs ideal for evolutionary studies. Herein, comprehensive phylogenetic analyses of KRT homologous proteins in the genomes of major taxonomic divisions were performed, so as to fill a gap in knowledge regarding the functional implications of keratins in cancer biology among tumor-bearing species. The differential expression profiles of KRTs in diverse types of cancers were investigated by analyzing high-throughput data, as well. Several KRT genes, including the phylogenetically conserved ones, were found to be deregulated across several cancer types and to participate in a common protein-protein interaction network. This indicates that, at least in cancer-bearing species, these genes might have been under similar evolutionary pressure, perhaps to support the same important function(s). In addition, semantic relations between KRTs and cancer were detected through extensive text mining. Therefore, by applying an integrative in silico pipeline, the evolutionary history of KRTs was reconstructed in the context of cancer, and the potential of using non-mammalian species as model organisms in functional studies on human cancer-associated KRT genes was uncovered.

Radiation Type- and Dose-Specific Transcriptional Responses across Healthy and Diseased Mammalian Tissues.

Ionizing radiation (IR) is a genuine genotoxic agent and a major modality in cancer treatment. IR disrupts DNA sequences and exerts mutagenic and/or cytotoxic properties that not only alter critical cellular functions but also impact tissues proximal and distal to the irradiated site. Unveiling the molecular events governing the diverse effects of IR at the cellular and organismal levels is relevant for both radiotherapy and radiation protection. Herein, we address changes in the expression of mammalian genes induced after the exposure of a wide range of tissues to various radiation types with distinct biophysical characteristics. First, we constructed a publicly available database, termed RadBioBase, which will be updated at regular intervals. RadBioBase includes comprehensive transcriptomes of mammalian cells across healthy and diseased tissues that respond to a range of radiation types and doses. Pertinent information was derived from a hybrid analysis based on stringent literature mining and transcriptomic studies. An integrative bioinformatics methodology, including functional enrichment analysis and machine learning techniques, was employed to unveil the characteristic biological pathways related to specific radiation types and their association with various diseases. We found that the effects of high linear energy transfer (LET) radiation on cell transcriptomes significantly differ from those caused by low LET and are consistent with immunomodulation, inflammation, oxidative stress responses and cell death. The transcriptome changes also depend on the dose since low doses up to 0.5 Gy are related with cytokine cascades, while higher doses with ROS metabolism. We additionally identified distinct gene signatures for different types of radiation. Overall, our data suggest that different radiation types and doses can trigger distinct trajectories of cell-intrinsic and cell-extrinsic pathways that hold promise to be manipulated toward improving radiotherapy efficiency and reducing systemic radiotoxicities.

p73 isoforms meet evolution of metastasis.

Cancer largely adheres to Darwinian selection. Evolutionary forces are prominent during metastasis, the final and incurable disease stage, where cells acquire combinations of advantageous phenotypic features and interact with a dynamically changing microenvironment, in order to overcome the metastatic bottlenecks, while therapy exerts additional selective pressures. As a strategy to increase their fitness, tumors often co-opt developmental and tissue-homeostasis programs. Herein, 25 years after its discovery, we review TP73, a sibling of the cardinal tumor-suppressor TP53, through the lens of cancer evolution. The TP73 gene regulates a wide range of processes in embryonic development, tissue homeostasis and cancer via an overwhelming number of functionally divergent isoforms. We suggest that TP73 neither merely mimics TP53 via its p53-like tumor-suppressive functions, nor has black-or-white-type effects, as inferred by the antagonism between several of its isoforms in processes like apoptosis and DNA damage response. Rather, under dynamic conditions of selective pressure, the various p73 isoforms which are often co-expressed within the same cancer cells may work towards a common goal by simultaneously activating isoform-specific transcriptional and non-transcriptional programs. Combinatorial co-option of these programs offers selective advantages that overall increase the likelihood for successfully surpassing the barriers of the metastatic cascade. The p73 functional pleiotropy-based capabilities might be present in subclonal populations and expressed dynamically under changing microenvironmental conditions, thereby supporting clonal expansion and propelling evolution of metastasis. Deciphering the critical p73 isoform patterns along the spatiotemporal axes of tumor evolution could identify strategies to target TP73 for prevention and therapy of cancer metastasis.

Ginger for Healthy Ageing: A Systematic Review on Current Evidence of Its Antioxidant, Anti-Inflammatory, and Anticancer Properties.

The world's population is ageing at an accelerated pace. Ageing is a natural, physiological but highly complex and multifactorial process that all species in the Tree of Life experience over time. Physical and mental disabilities, and age-related diseases, would increase along with the increasing life expectancy. Ginger (Zingiber officinale) is a plant that belongs to the Zingiberaceae family, native to Southeast Asia. For hundreds of years, ginger has been consumed in various ways by the natives of Asian countries, both as culinary and medicinal herb for the treatment of many diseases. Mounting evidence suggests that ginger can promote healthy ageing, reduce morbidity, and prolong healthy lifespan. Ginger, a well-known natural product, has been demonstrated to possess antioxidant, anti-inflammatory, anticancer, and antimicrobial properties, as well as an outstanding antiviral activity due to a high concentration of antiviral compounds. In this review, the current evidence on the potential role of ginger and its active compounds in the prevention of ageing is discussed.

Novel integrated workflow allows production and in-depth quality assessment of multifactorial reprogrammed skeletal muscle cells from human stem cells.

Skeletal muscle tissue engineering aims at generating biological substitutes that restore, maintain or improve normal muscle function; however, the quality of cells produced by current protocols remains insufficient. Here, we developed a multifactor-based protocol that combines adenovector (AdV)-mediated MYOD expression, small molecule inhibitor and growth factor treatment, and electrical pulse stimulation (EPS) to efficiently reprogram different types of human-derived multipotent stem cells into physiologically functional skeletal muscle cells (SMCs). The protocol was complemented through a novel in silico workflow that allows for in-depth estimation and potentially optimization of the quality of generated muscle tissue, based on the transcriptomes of transdifferentiated cells. We additionally patch-clamped phenotypic SMCs to associate their bioelectrical characteristics with their transcriptome reprogramming. Overall, we set up a comprehensive and dynamic approach at the nexus of viral vector-based technology, bioinformatics, and electrophysiology that facilitates production of high-quality skeletal muscle cells and can guide iterative cycles to improve myo-differentiation protocols.

Thrombocytopenia in COVID­19 and vaccine­induced thrombotic thrombocytopenia.

The highly heterogeneous symptomatology and unpredictable progress of COVID­19 triggered unprecedented intensive biomedical research and a number of clinical research projects. Although the pathophysiology of the disease is being progressively clarified, its complexity remains vast. Moreover, some extremely infrequent cases of thrombotic thrombocytopenia following vaccination against SARS­CoV­2 infection have been observed. The present study aimed to map the signaling pathways of thrombocytopenia implicated in COVID­19, as well as in vaccine­induced thrombotic thrombocytopenia (VITT). The biomedical literature database, MEDLINE/PubMed, was thoroughly searched using artificial intelligence techniques for the semantic relations among the top 50 similar words (>0.9) implicated in COVID­19­mediated human infection or VITT. Additionally, STRING, a database of primary and predicted associations among genes and proteins (collected from diverse resources, such as documented pathway knowledge, high­throughput experimental studies, cross­species extrapolated information, automated text mining results, computationally predicted interactions, etc.), was employed, with the confidence threshold set at 0.7. In addition, two interactomes were constructed: i) A network including 119 and 56 nodes relevant to COVID­19 and thrombocytopenia, respectively; and ii) a second network containing 60 nodes relevant to VITT. Although thrombocytopenia is a dominant morbidity in both entities, three nodes were observed that corresponded to genes (AURKA, CD46 and CD19) expressed only in VITT, whilst ADAM10, CDC20, SHC1 and STXBP2 are silenced in VITT, but are commonly expressed in both COVID­19 and thrombocytopenia. The calculated average node degree was immense (11.9 in COVID­19 and 6.43 in VITT), illustrating the complexity of COVID­19 and VITT pathologies and confirming the importance of cytokines, as well as of pathways activated following hypoxic events. In addition, PYCARD, NLP3 and P2RX7 are key potential therapeutic targets for all three morbid entities, meriting further research. This interactome was based on wild­type genes, revealing the predisposition of the body to hypoxia­induced thrombosis, leading to the acute COVID­19 phenotype, the 'long­COVID syndrome', and/or VITT. Thus, common nodes appear to be key players in illness prevention, progression and treatment.

A Counterintuitive Neutrophil-Mediated Pattern in COVID-19 Patients Revealed through Transcriptomics Analysis.

The COVID-19 pandemic has persisted for almost three years. However, the mechanisms linked to the SARS-CoV-2 effect on tissues and disease severity have not been fully elucidated. Since the onset of the pandemic, a plethora of high-throughput data related to the host transcriptional response to SARS-CoV-2 infections has been generated. To this end, the aim of this study was to assess the effect of SARS-CoV-2 infections on circulating and organ tissue immune responses. We profited from the publicly accessible gene expression data of the blood and soft tissues by employing an integrated computational methodology, including bioinformatics, machine learning, and natural language processing in the relevant transcriptomics data. COVID-19 pathophysiology and severity have mainly been associated with macrophage-elicited responses and a characteristic "cytokine storm". Our counterintuitive findings suggested that the COVID-19 pathogenesis could also be mediated through neutrophil abundance and an exacerbated suppression of the immune system, leading eventually to uncontrolled viral dissemination and host cytotoxicity. The findings of this study elucidated new physiological functions of neutrophils, as well as tentative pathways to be explored in asymptomatic-, ethnicity- and locality-, or staging-associated studies.

In Silico Investigation of the Biological Implications of Complex DNA Damage with Emphasis in Cancer Radiotherapy through a Systems Biology Approach.

Different types of DNA lesions forming in close vicinity, create clusters of damaged sites termed as "clustered/complex DNA damage" and they are considered to be a major challenge for DNA repair mechanisms resulting in significant repair delays and induction of genomic instability. Upon detection of DNA damage, the corresponding DNA damage response and repair (DDR/R) mechanisms are activated. The inability of cells to process clustered DNA lesions efficiently has a great impact on the normal function and survival of cells. If complex lesions are left unrepaired or misrepaired, they can lead to mutations and if persistent, they may lead to apoptotic cell death. In this in silico study, and through rigorous data mining, we have identified human genes that are activated upon complex DNA damage induction like in the case of ionizing radiation (IR) and beyond the standard DNA repair pathways, and are also involved in cancer pathways, by employing stringent bioinformatics and systems biology methodologies. Given that IR can cause repair resistant lesions within a short DNA segment (a few nm), thereby augmenting the hazardous and toxic effects of radiation, we also investigated the possible implication of the most biologically important of those genes in comorbid non-neoplastic diseases through network integration, as well as their potential for predicting survival in cancer patients.

Bioinformatic approaches to the investigation of the atavistic genes implicated in cancer.

Introduction: Cancer is a widespread phenomenon occurring across multicellular organisms and represents a condition of atavism, wherein cells follow a path of reverse evolution that unlocks a toolkit of ancient pre-existing adaptations by disturbing hub genes of the human gene network. This results to a primitive cellular phenotype which resembles a unicellular life form. Methods: In the present study, we have employed bioinformatic approaches for the in-depth investigation of twelve atavistic hub genes (ACTG1, CTNNA1, CTNND1, CTTN, DSP, ILK, PKN2, PKP3, PLEC, RCC2, TLN1 and VASP), which exhibit highly disrupted interactions in diverse types of cancer and are associated with the formation of metastasis. To this end, phylogenetic analyses were conducted towards unravelling the evolutionary history of those hubs and tracing the origin of cancer in the Tree of Life. Results: Based on our results, most of those genes are of unicellular origin, and some of them can be traced back to the emergence of cellular life itself (atavistic theory). Our findings indicate how deep the evolutionary roots of cancer actually are, and may be exploited in the clinical setting for the design of novel therapeutic approaches and, particularly, in overcoming resistance to antineoplastic treatment.

Mining Natural Products with Anticancer Biological Activity through a Systems Biology Approach.

Natural products, like turmeric, are considered powerful antioxidants which exhibit tumor-inhibiting activity and chemoradioprotective properties. Nowadays, there is a great demand for developing novel, affordable, efficacious, and effective anticancer drugs from natural resources. In the present study, we have employed a stringent in silico methodology to mine and finally propose a number of natural products, retrieved from the biomedical literature. Our main target was the systematic search of anticancer products as anticancer agents compatible to the human organism for future use. In this case and due to the great plethora of such products, we have followed stringent bioinformatics methodologies. Our results taken together suggest that natural products of a great diverse may exert cytotoxic effects in a maximum of the studied cancer cell lines. These natural compounds and active ingredients could possibly be combined to exert potential chemopreventive effects. Furthermore, in order to substantiate our findings and their application potency at a systems biology level, we have developed a representative, user-friendly, publicly accessible biodatabase, NaturaProDB, containing the retrieved natural resources, their active ingredients/fractional mixtures, the types of cancers that they affect, and the corresponding experimentally verified target genes.

A Systems-Based Key Innovation-Driven Approach Infers Co-option of Jaw Developmental Programs During Cancer Progression.

Cancer acquires metastatic potential and evolves via co-opting gene regulatory networks (GRN) of embryonic development and tissue homeostasis. Such GRNs are encoded in the genome and frequently conserved among species. Considering that all metazoa have evolved from a common ancestor via major macroevolutionary events which shaped those GRNs and increased morphogenetic complexity, we sought to examine whether there are any key innovations that may be consistently and deterministically linked with metastatic potential across the metazoa clades. To address tumor evolution relative to organismal evolution, we revisited and retrospectively juxtaposed seminal laboratory and field cancer studies across taxa that lie on the evolutionary lineage from cnidaria to humans. We subsequently applied bioinformatics to integrate species-specific cancer phenotypes, multiomics data from up to 42 human cancer types, developmental phenotypes of knockout mice, and molecular phylogenetics. We found that the phenotypic manifestations of metastasis appear to coincide with agnatha-to-gnathostome transition. Genes indispensable for jaw development, a key innovation of gnathostomes, undergo mutations or methylation alterations, are aberrantly transcribed during tumor progression and are causatively associated with invasion and metastasis. There is a preference for deregulation of gnathostome-specific versus pre-gnathostome genes occupying hubs of the jaw development network. According to these data, we propose our systems-based model as an in silico tool the prediction of likely tumor evolutionary trajectories and therapeutic targets for metastasis prevention, on the rationale that the same genes which are essential for key innovations that catalyzed vertebrate evolution, such as jaws, are also important for tumor evolution.

Neural Networks Recapitulation by Cancer Cells Promotes Disease Progression: A Novel Role of p73 Isoforms in Cancer-Neuronal Crosstalk.

Mechanisms governing tumor progression differ from those of initiation. One enigmatic prometastatic process is the recapitulation of pathways of neural plasticity in aggressive stages. Cancer and neuronal cells develop reciprocal interactions via mutual production and secretion of neuronal growth factors, neurothrophins and/or axon guidance molecules in the tumor microenvironment. Understanding cancer types where this process is active, as well as the drivers, markers and underlying mechanisms, has great significance for blocking tumor progression and improving patient survival. By applying computational and systemic approaches, in combination with experimental validations, we provide compelling evidence that genes involved in neuronal development, differentiation and function are reactivated in tumors and predict poor patient outcomes across various cancers. Across cancers, they co-opt genes essential for the development of distinct anatomical parts of the nervous system, with a frequent preference for cerebral cortex and neural crest-derived enteric nerves. Additionally, we show that p73, a transcription factor with a dual role in neuronal development and cancer, simultaneously induces neurodifferentiation and stemness markers during melanoma progression. Our data yield the basis for elucidating driving forces of the nerve-tumor cell crosstalk and highlight p73 as a promising regulator of cancer neurobiology.