Energy management – a critical role in cancer induction?

How much energy is stored in SARS‐CoV‐2 and its structural elements?

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is the virus causing the COVID‐19 disease. Data regarding the morphological properties of this virus are collected from the literature and then the energy stored in each structural element is calculated with Domalski and Hearing's group contribution method. Viruses, including the Corona viruses, derive all of their energy from the host cell and carry out all of their activities with this energy. SARS‐CoV‐2 construct a vehicle needed for the delivery of its mRNA to other hosts to inflict them with the disease. Upon transfer of the viral RNA to the new host, the remaining parts of the viral structure are discarded. Structural and molecular assessments showed that the chemical formula of SARS‐CoV‐2 virus is C_7,336,852H_12,384,463N_1,247,424O_1,915,357P_100,231S_25,084 and its enthalpy of formation is −8.70 × 10⁻¹⁶ kJ. Comparison of SARS‐CoV‐2 with the other viruses shows that its elemental composition does not like any of the others. The results of this study are expected to improve our knowledge of the thermodynamic properties of this virus.

Chronoradiobiology of Breast Cancer: The Time Is Now to Link Circadian Rhythm and Radiation Biology

Circadian disruption has been linked to cancer development, progression, and radiation response. Clinical evidence to date shows that circadian genetic variation and time of treatment affect radiation response and toxicity for women with breast cancer. At the molecular level, there is interplay between circadian clock regulators such as PER1, which mediates ATM and p53-mediated cell cycle gating and apoptosis. These molecular alterations may govern aggressive cancer phenotypes, outcomes, and radiation response. Exploiting the various circadian clock mechanisms may enhance the therapeutic index of radiation by decreasing toxicity, increasing disease control, and improving outcomes. We will review the body’s natural circadian rhythms and clock gene-regulation while exploring preclinical and clinical evidence that implicates chronobiological disruptions in the etiology of breast cancer. We will discuss radiobiological principles and the circadian regulation of DNA damage responses. Lastly, we will present potential rational therapeutic approaches that target circadian pathways to improve outcomes in breast cancer. Understanding the implications of optimal timing in cancer treatment and exploring ways to entrain circadian biology with light, diet, and chronobiological agents like melatonin may provide an avenue for enhancing the therapeutic index of radiotherapy.

Why women may live longer than men do? A telomere-length regulated and diet-based entropic assessment

BACKGROUND & AIMS

Empirical analyses of the data available around the word concluded that women have longer life span now, when compared to the men. Available literature unfortunately could not offer full answers to this observation. The "entropic age" concept suggests that ageing related changes in the body, such as loss of molecular functions and overwhelming of the maintenance systems, may be explained in terms of entropy generation.

METHODS

Telomere-length regulated entropic assessment based on metabolic activity with four different diets carried out.

RESULTS

Estimates of the life expectancy of the women on all of these diets is longer than those of the men. Faster shortening of the telomere lengths in men was the major reason of the shorter life expectancy. The highest and the lowest life expectancy for women were estimated with Mediterranean and the vegetarian diets, respectively; men were estimated to have the longest life span with the vegetarian diet and the shortest life span with the ketogenic diet.

CONCLUSIONS

A higher rate of metabolism causes higher entropy generation and hints correlations that can be helpful in future ageing research. Faster shortening of the telomere lengths in men was the major reason of the estimation of the shorter life span for men.

Unravelling the complexity of signalling networks in cancer: A review of the increasing role for computational modelling

Cancer induction is a highly complex process involving hundreds of different inducers but whose eventual outcome is the same. Clearly, it is essential to understand how signalling pathways and networks generated by these inducers interact to regulate cell behaviour and create the cancer phenotype. While enormous strides have been made in identifying key networking profiles, the amount of data generated far exceeds our ability to understand how it all "fits together". The number of potential interactions is astronomically large and requires novel approaches and extreme computation methods to dissect them out. However, such methodologies have high intrinsic mathematical and conceptual content which is difficult to follow. This review explains how computation modelling is progressively finding solutions and also revealing unexpected and unpredictable nano-scale molecular behaviours extremely relevant to how signalling and networking are coherently integrated. It is divided into linked sections illustrated by numerous figures from the literature describing different approaches and offering visual portrayals of networking and major conceptual advances in the field. First, the problem of signalling complexity and data collection is illustrated for only a small selection of known oncogenes. Next, new concepts from biophysics, molecular behaviours, kinetics, organisation at the nano level and predictive models are presented. These areas include: visual representations of networking, Energy Landscapes and energy transfer/dissemination (entropy); diffusion, percolation; molecular crowding; protein allostery; quinary structure and fractal distributions; energy management, metabolism and re-examination of the Warburg effect. The importance of unravelling complex network interactions is then illustrated for some widely-used drugs in cancer therapy whose interactions are very extensive. Finally, use of computational modelling to develop micro- and nano- functional models ("bottom-up" research) is highlighted. The review concludes that computational modelling is an essential part of cancer research and is vital to understanding network formation and molecular behaviours that are associated with it. Its role is increasingly essential because it is unravelling the huge complexity of cancer induction otherwise unattainable by any other approach.

Repurposing Metformin as Therapy for Prostate Cancer within the STAMPEDE Trial Platform

Metformin is a safe, well-tolerated, inexpensive treatment that can be given in addition to current standard-of-care therapies for prostate cancer. Its use might mitigate the deleterious side effects of castration and exert an additional anticancer effect. It will be incorporated in the STAMPEDE trial platform in summer 2016. This will test its true utility as a repurposed treatment for men with high-risk locally advanced or metastatic prostate cancer at first presentation.

Lactate dehydrogenase A is a potential prognostic marker in clear cell renal cell carcinoma

Background

Over 90% of cancer-related deaths in clear cell renal cell carcinoma (RCC) are caused by tumor relapse and metastasis. Thus, there is an urgent need for new molecular markers that can potentiate the efficacy of the current clinical-based models of prognosis assessment. The objective of this study is to evaluate the potential significance of lactate dehydrogenase A (LDHA), assessed by immunohistochemical staining, as a prognostic marker in clear cell renal cell carcinoma in relation to clinicopathological features and clinical outcome.

Methods

We assessed the expression of LDHA at the protein level, by immunohistochemistry, and correlated its expression with multiple clinicopathological features including tumor size, clinical stage, histological grade, disease-free and overall survival in 385 patients with primary clear cell renal cell carcinoma. We also correlated the LDHA expression with overall survival, at mRNA level, in an independent data set of 170 clear cell renal cell carcinoma cases from The Cancer Genome Atlas databases. Cox proportional hazards models adjusted for the potential clinicopathological factors were used to test for associations between the LDHA expression and both disease-free survival and overall survival.

Results

There is statistically significant positive correlation between LDHA level of expression and tumor size, clinical stage and histological grade. Moreover, LDHA expression shows significantly inverse correlation with both disease-free survival and overall survival in patients with clear cell renal cell carcinoma. Our results are validated by examining LDHA expression, at the mRNA level, in the independent data set of clear cell renal cell carcinoma cases from The Cancer Genome Atlas databases which also shows that higher lactate dehydrogenase A expression is associated with significantly shorter overall survival.

Conclusion

Our results indicate that LDHA up-regulation can be a predictor of poor prognosis in clear cell renal cell carcinoma. Thus, it represents a potential prognostic biomarker that can boost the accuracy of other prognostic models in patients with clear cell renal cell carcinoma.

Fractal dimension of chromatin: potential molecular diagnostic applications for cancer prognosis

Fractal characteristics of chromatin, revealed by light or electron microscopy, have been reported during the last 20 years. Fractal features can easily be estimated in digitalized microscopic images and are helpful for diagnosis and prognosis of neoplasias. During carcinogenesis and tumor progression, an increase of the fractal dimension (FD) of stained nuclei has been shown in intraepithelial lesions of the uterine cervix and the anus, oral squamous cell carcinomas or adenocarcinomas of the pancreas. Furthermore, an increased FD of chromatin is an unfavorable prognostic factor in squamous cell carcinomas of the oral cavity and the larynx, melanomas and multiple myelomas. High goodness-of-fit of the regression line of the FD is a favorable prognostic factor in acute leukemias and multiple myelomas. The nucleus has fractal and power-law organization in several different levels, which might in part be interrelated. Some possible relations between modifications of the chromatin organization during carcinogenesis and tumor progression and an increase of the FD of stained chromatin are suggested. Furthermore, increased complexity of the chromatin structure, loss of heterochromatin and a less-perfect self-organization of the nucleus in aggressive neoplasias are discussed.