Biological basis of extensive pleiotropy between blood traits and cancer risk.

BACKGROUND: The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations. METHODS: Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were sequenced to assess association with cancer diagnosis. RESULTS: The study identified 4093 common genetic variants, involving 1248 gene loci, that contributed to blood-cancer pleiotropism. Genomic hotspots of pleiotropism include chromosomal regions 5p15-TERT and 6p21-HLA. Genes whose products are involved in regulating telomere length are found to be enriched in pleiotropic variants. Pleiotropic gene candidates are frequently linked to transcriptional programs that regulate hematopoiesis and define progenitor cell states of immune system development. Perturbation of the myeloid lineage is indicated by pleiotropic associations with defined master regulators and cell alterations. Eosinophil count is inversely associated with cancer risk. A high frequency of pleiotropic associations is also centered on the regulation of small noncoding Y-RNAs. Predicted pleiotropic Y-RNAs show specific regulatory marks and are overabundant in the normal tissue and blood of cancer patients. Analysis of plasma small RNAs in women who developed breast cancer indicates there is an overabundance of Y-RNA preceding neoplasm diagnosis. CONCLUSIONS: This study reveals extensive pleiotropism between blood traits and cancer risk. Pleiotropism is linked to factors and processes involved in hematopoietic development and immune system function, including components of the major histocompatibility complexes, and regulators of telomere length and myeloid lineage. Deregulation of Y-RNAs is also associated with pleiotropism. Overexpression of these elements might indicate increased cancer risk.

Proteomic study of neuron and astrocyte cultures from senescence-accelerated mouse SAMP8 reveals degenerative changes.

Senescence-accelerated prone (SAMP) strain 8 mice suffer an earlier development of cognitive age-related pathologies and a shorter life span than conventional mice. Protein alterations in astrocytes, in addition to those in neurons, may contribute to neurodegenerative damage. We applied proteomics techniques to study cell-specific early markers of brain aging-related degeneration in SAMP8. The two-dimensional protein expression patterns of the SAMP8 neuron and astrocyte cultures were compared with those obtained from senescence-accelerated resistant mouse strain 1 cultures. Differentially expressed spots were identified by matrix-assisted laser desorption/ionization-time of flight peptide map fingerprinting and database search. Proteins belonged to cell pathways of energy metabolism, biosynthesis, cell transduction and signaling, stress response, and the maintenance of cytoskeletal functions. Most of the changes were cell type specific. However, there was a general increase in cell transduction, signaling, and stress-related proteins and a decrease in cytoskeletal proteins. In addition, neurons showed an increased expression of proteins involved in biosynthetic pathways. A number of the protein alterations have been previously reported in the brain tissue proteome of SAMP8, aged brain or Alzheimer's disease brain. Alterations in neuron and astrocyte proteoma indicated that both cell types are involved in the brain degenerative changes of SAMP8 mice. However, network analysis suggests that neuronal changes are more complex and have a greater influence.

Proinsulin protects against age-related cognitive loss through anti-inflammatory convergent pathways.

Brain inflammaging is increasingly considered as contributing to age-related cognitive loss and neurodegeneration. Despite intensive research in multiple models, no clinically effective pharmacological treatment has been found yet. Here, in the mouse model of brain senescence SAMP8, we tested the effects of proinsulin, a promising neuroprotective agent that was previously proven to be effective in mouse models of retinal neurodegeneration. Proinsulin is the precursor of the hormone insulin but also upholds developmental physiological effects, particularly as a survival factor for neural cells. Adeno-associated viral vectors of serotype 1 bearing the human proinsulin gene were administered intramuscularly to obtain a sustained release of proinsulin into the blood stream, which was able to reach the target area of the hippocampus. SAMP8 mice and the control strain SAMR1 were treated at 1 month of age. At 6 months, behavioral testing exhibited cognitive loss in SAMP8 mice treated with the null vector. Remarkably, the cognitive performance achieved in spatial and recognition tasks by SAMP8 mice treated with proinsulin was similar to that of SAMR1 mice. In the hippocampus, proinsulin induced the activation of neuroprotective pathways and the downstream signaling cascade, leading to the decrease of neuroinflammatory markers. Furthermore, the decrease of astrocyte reactivity was a central effect, as demonstrated in the connectome network of changes induced by proinsulin. Therefore, the neuroprotective effects of human proinsulin unveil a new pharmacological potential therapy in the fight against cognitive loss in the elderly.

Oxidative Stress Is a Central Target for Physical Exercise Neuroprotection Against Pathological Brain Aging.

Physical exercise is suggested for preventing or delaying senescence and Alzheimer's disease (AD). We have examined its therapeutic value in the advanced stage of AD-like pathology in 3xTg-AD female mice through voluntary wheel running from 12 to 15 months of age. Mice submitted to exercise showed improved body fitness, immunorejuvenation, improvement of behavior and cognition, and reduced amyloid and tau pathology. Brain tissue analysis of aged 3xTg-AD mice showed high levels of oxidative damage. However, this damage was decreased by physical exercise through regulation of redox homeostasis. Network analyses showed that oxidative stress was a central event, which correlated with AD-like pathology and the AD-related behaviors of anxiety, apathy, and cognitive loss. This study corroborates the importance of redox mechanisms in the neuroprotective effect of physical exercise, and supports the theory of the crucial role of oxidative stress in the switch from normal brain aging to pathological aging and AD.

Synchronous and asynchronous recursive random scale-free nets.

We investigate the differences between scale-free recursive nets constructed by a synchronous, deterministic updating rule (e.g., Apollonian nets), versus an asynchronous, random sequential updating rule (e.g., random Apollonian nets). We show that the dramatic discrepancies observed recently for the degree exponent in these two cases result from a biased choice of the units to be updated sequentially in the asynchronous version.

Recursive graphs with small-world scale-free properties.

We discuss a category of graphs, recursive clique trees, which have small-world and scale-free properties and allow a fine tuning of the clustering and the power-law exponent of their discrete degree distribution. We determine relevant characteristics of those graphs: the diameter, degree distribution, and clustering parameter. The graphs have also an interesting recursive property, and generalize recent constructions with fixed degree distributions.

Quantum Google in a complex network.

We investigate the behaviour of the recently proposed Quantum PageRank algorithm, in large complex networks. We find that the algorithm is able to univocally reveal the underlying topology of the network and to identify and order the most relevant nodes. Furthermore, it is capable to clearly highlight the structure of secondary hubs and to resolve the degeneracy in importance of the low lying part of the list of rankings. The quantum algorithm displays an increased stability with respect to a variation of the damping parameter, present in the Google algorithm, and a more clearly pronounced power-law behaviour in the distribution of importance, as compared to the classical algorithm. We test the performance and confirm the listed features by applying it to real world examples from the WWW. Finally, we raise and partially address whether the increased sensitivity of the quantum algorithm persists under coordinated attacks in scale-free and random networks.

Cancer develops, progresses and responds to therapies through restricted perturbation of the protein-protein interaction network.

The products of genes mutated or differentially expressed in cancer tend to occupy central positions within the network of protein-protein interactions, or the interactome network. Integration of different types of gene and protein relationships has considerably increased the understanding of the mechanisms of carcinogenesis, while also enhancing the applicability of expression signatures. In this scenario, however, it remains unknown how cancer develops, progresses and responds to therapies in a potentially controlled manner at the systems level. Here, by applying the concepts of load transfer and cascading failures in power grids, we examine the impact and transmission of cancer-related gene expression changes in the interactome network. Relative to random perturbations, this study reveals topological robustness associated with all cancer conditions. In addition, experimental perturbation of a central cancer node, which consists of over-expression of the α-synuclein (SNCA) protein in MCF7 breast cancer cells, also reveals robustness. Conversely, a search for proteins with an opposite topological impact identifies the autophagy pathway. Mechanistically, the existence of smaller shortest paths among cancer-related proteins appears to be a topological feature that partially contributes to the restricted perturbation of the network. Together, the results of this study suggest that cancer develops, progresses and responds to therapies following controlled, restricted perturbation of the interactome network.

Mean first-passage time for random walks on generalized deterministic recursive trees.

We describe a technique that allows the exact analytical computation of the mean first passage time (MFPT) for infinite families of trees using their recursive properties. The method is based in the relationship between the MFPT and the eigenvalues of the Laplacian matrix of the trees but avoids their explicit computation. We apply this technique to find the MFPT for a family of generalized deterministic recursive trees. The method, however, can be adapted to other self-similar tree families.

Biological convergence of cancer signatures.

Gene expression profiling has identified cancer prognostic and predictive signatures with superior performance to conventional histopathological or clinical parameters. Consequently, signatures are being incorporated into clinical practice and will soon influence everyday decisions in oncology. However, the slight overlap in the gene identity between signatures for the same cancer type or condition raises questions about their biological and clinical implications. To clarify these issues, better understanding of the molecular properties and possible interactions underlying apparently dissimilar signatures is needed. Here, we evaluated whether the signatures of 24 independent studies are related at the genome, transcriptome or proteome levels. Significant associations were consistently observed across these molecular layers, which suggest the existence of a common cancer cell phenotype. Convergence on cell proliferation and death supports the pivotal involvement of these processes in prognosis, metastasis and treatment response. In addition, functional and molecular associations were identified with the immune response in different cancer types and conditions that complement the contribution of cell proliferation and death. Examination of additional, independent, cancer datasets corroborated our observations. This study proposes a comprehensive strategy for interpreting cancer signatures that reveals common design principles and systems-level properties.