Detection of a novel, primate-specific 'kill switch' tumor suppression mechanism that may fundamentally control cancer risk in humans: an unexpected twist in the basic biology of TP53

A mathematically rigorous algorithm to define, compute and assess relevance of the probable dissociation constants in characterizing a biochemical network

Metabolism results from enzymatic- and non-enzymatic interactions of several molecules, is easily parameterized with the dissociation constant and occurs via biochemical networks. The dissociation constant is an empirically determined parameter and cannot be used directly to investigate in silico models of biochemical networks. Here, we develop and present an algorithm to define, compute and assess the relevance of the probable dissociation constant for every reaction of a biochemical network. The reactants and reactions of this network are modelled by a stoichiometry number matrix. The algorithm computes the null space and then serially generates subspaces by combinatorially summing the spanning vectors that are non-trivial and unique. This is done until the terms of each row either monotonically diverge or form an alternating sequence whose terms can be partitioned into subsets with almost the same number of oppositely signed terms. For a selected null space-generated subspace the algorithm utilizes several statistical and mathematical descriptors to select and bin terms from each row into distinct outcome-specific subsets. The terms of each subset are summed, mapped to the real-valued open interval [Formula: see text] and used to populate a reaction-specific outcome vector. The p1-norm for this vector is then the probable dissociation constant for this reaction. These steps are continued until every reaction of a modelled network is unambiguously annotated. The assertions presented are complemented by computational studies of a biochemical network for aerobic glycolysis. The fundamental premise of this work is that every row of a null space-generated subspace is a valid reaction and can therefore, be modelled as a reaction-specific sequence vector with a dimension that corresponds to the cardinality of the subspace after excluding all trivial- and redundant-vectors. A major finding of this study is that the row-wise sum or the sum of the terms contained in each reaction-specific sequence vector is mapped unambiguously to a positive real number. This means that the probable dissociation constants, for all reactions, can be directly computed from the stoichiometry number matrix and are suitable indicators of outcome for every reaction of the modelled biochemical network. Additionally, we find that the unambiguous annotation for a biochemical network will require a minimum number of iterations and will determine computational complexity.

A lex naturalis delineates components of a human-specific, adrenal androgen-dependent, p53-mediated 'kill switch' tumor suppression mechanism

We have recently described in this journal our detection of an anthropoid primate-specific, adrenal androgen-dependent, p53-mediated, 'kill switch' tumor suppression mechanism that reached its fullest expression only in humans, as a result of human-specific exposure to polycyclic aromatic hydrocarbons caused by the harnessing of fire - but which has components reaching all the way back to the origin of the primate lineage. We proposed that species-specific mechanisms of tumor suppression are a generalized requirement for vertebrate species to increase in body size or lifespan beyond those of species basal to their lineage or to exploit environmental niches which increase exposure to carcinogenic substances. Using empirical dynamic modeling, we have also reported our detection of a relationship between body size, lifespan, and species-specific mechanism of tumor suppression (and here add carcinogen exposure), such that a change in any one of these variables requires an equilibrating change in one or more of the others in order to maintain lifetime cancer risk at a value of about 4%, as observed in virtually all larger, longer-lived species under natural conditions. Here we show how this relationship, which we refer to as the lex naturalis of vertebrate speciation, elucidates the evolutionary steps underlying an adrenal androgen-dependent, human-specific 'kill switch' tumor suppression mechanism; and further, how it prescribes a solution to 'normalize' lifetime cancer risk in our species from its current aberrant 40% to the 4% that characterized primitive humans. We further argue that this prescription writ by the lex naturalis represents the only tenable strategy for meaningful suppression of the accelerating impact of cancer upon our species.

Can postfertile life stages evolve as an anticancer mechanism?

Why a postfertile stage has evolved in females of some species has puzzled evolutionary biologists for over 50 years. We propose that existing adaptive explanations have underestimated in their formulation an important parameter operating both at the specific and the individual levels: the balance between cancer risks and cancer defenses. During their life, most multicellular organisms naturally accumulate oncogenic processes in their body. In parallel, reproduction, notably the pregnancy process in mammals, exacerbates the progression of existing tumors in females. When, for various ecological or evolutionary reasons, anticancer defenses are too weak, given cancer risk, older females could not pursue their reproduction without triggering fatal metastatic cancers, nor even maintain a normal reproductive physiology if the latter also promotes the growth of existing oncogenic processes, e.g., hormone-dependent malignancies. At least until stronger anticancer defenses are selected for in these species, females could achieve higher inclusive fitness by ceasing their reproduction and/or going through menopause (assuming that these traits are easier to select than anticancer defenses), thereby limiting the risk of premature death due to metastatic cancers. Because relatively few species experience such an evolutionary mismatch between anticancer defenses and cancer risks, the evolution of prolonged life after reproduction could also be a rare, potentially transient, anticancer adaptation in the animal kingdom.

Bioinformatics and functional analyses of key genes in smoking-associated lung adenocarcinoma

Smoking is one of the most important factors associated with the development of lung cancer. However, the signaling pathways and driver genes in smoking-associated lung adenocarcinoma remain unknown. The present study analyzed 433 samples of smoking-associated lung adenocarcinoma and 75 samples of non-smoking lung adenocarcinoma from the Cancer Genome Atlas database. Gene Ontology (GO) analysis was performed using the Database for Annotation, Visualization and Integrated Discovery and the ggplot2 R/Bioconductor package. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using the R packages RSQLite and org.Hs.eg.db. Multivariate Cox regression analysis was performed to screen factors associated with patient survival. Kaplan-Meier and receiver operating characteristic curves were used to analyze the potential clinical significance of the identified biomarkers as molecular prognostic markers for the five-year overall survival time. A total of 373 differentially expressed genes (DEGs; |log2-fold change|≥2.0 and P<0.01) were identified, of which 71 were downregulated and 302 were upregulated. These DEGs were associated with 28 significant GO functions and 11 significant KEGG pathways (false discovery rate <0.05). Two hundred thirty-eight proteins were associated with the 373 differentially expressed genes, and a protein-protein interaction network was constructed. Multivariate regression analysis revealed that 7 mRNAs, cytochrome P450 family 17 subfamily A member 1, PKHD1 like 1, retinoid isomerohydrolase RPE65, neurotensin receptor 1, fetuin B, insulin-like growth factor binding protein 1 and glucose-6-phosphatase catalytic subunit, significantly distinguished between non-smoking and smoking-associated adenocarcinomas. Kaplan-Meier analysis demonstrated that patients in the 7 mRNAs-high-risk group had a significantly worse prognosis than those of the low-risk group. The data obtained in the current study suggested that these genes may serve as potential novel prognostic biomarkers of smoking-associated lung adenocarcinoma.

Species-specific mechanisms of tumor suppression are fundamental drivers of vertebrate speciation: critical implications for the 'war on cancer'

We recently reported our detection of an anthropoid primate-specific, 'kill switch' tumor suppression system that reached its greatest expression in humans, but that is fully functional only during the first twenty-five years of life, corresponding to the primitive human lifespan that has characterized the majority of our species' existence. This tumor suppression system is based upon the kill switch being triggered in cells in which p53 has been inactivated; such kill switch consisting of a rapid, catastrophic increase in ROS caused by the induction of irreversible uncompetitive inhibition of glucose-6- phosphate dehydrogenase (G6PD), which requires high concentrations of both inhibitor (DHEA) and G6P substrate. While high concentrations of intracellular DHEA are readily available in primates from the importation and subsequent de-sulfation of circulating DHEAS into p53-affected cells, both an anthropoid primate-specific sequence motif (GAAT) in the glucose-6-phosphatase (G6PC) promoter, and primate-specific inactivation of de novo synthesis of vitamin C by deletion of gulonolactone oxidase (GLO) were required to enable accumulation of G6P to levels sufficient to enable irreversible uncompetitive inhibition of G6PD. Malignant transformation acts as a counterforce opposing vertebrate speciation, particularly increases in body size and lifespan that enable optimized exploitation of particular niches. Unique mechanisms of tumor suppression that evolved to enable niche exploitation distinguish vertebrate species, and prevent one vertebrate species from serving as a valid model system for another. This here-to-fore unrecognized element of speciation undermines decades of cancer research data, using murine species, which presumed universal mechanisms of tumor suppression, independent of species. Despite this setback, the potential for pharmacological reconstitution of the kill switch tumor suppression system that distinguishes our species suggests that 'normalization' of human cancer risk, from its current 40% to the 4% of virtually all other large, long-lived species, represents a realistic near-term goal.