The storage of energy as a cause of malignant transformation: a 7-phase model of carcinogenesis

Cancer biomarker discovery: the entropic hallmark

Background

It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods.

Methodology/Principal Findings

Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer.

Conclusions/Significance

We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-througput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases.

Beyond the oncogene paradigm: understanding complexity in cancerogenesis

In the past decades, an enormous amount of precious information has been collected about molecular and genetic characteristics of cancer. This knowledge is mainly based on a reductionistic approach, meanwhile cancer is widely recognized to be a 'system biology disease'. The behavior of complex physiological processes cannot be understood simply by knowing how the parts work in isolation. There is not solely a matter how to integrate all available knowledge in such a way that we can still deal with complexity, but we must be aware that a deeply transformation of the currently accepted oncologic paradigm is urgently needed. We have to think in terms of biological networks: understanding of complex functions may in fact be impossible without taking into consideration influences (rules and constraints) outside of the genome. Systems Biology involves connecting experimental unsupervised multivariate data to mathematical and computational approach than can simulate biologic systems for hypothesis testing or that can account for what it is not known from high-throughput data sets. Metabolomics could establish the requested link between genotype and phenotype, providing informations that ensure an integrated understanding of pathogenic mechanisms and metabolic phenotypes and provide a screening tool for new targeted drug.

Brain metastases of melanoma--mechanisms of attack on their defence system by engineered stem cells in the microenvironment

This report gives a better emphasis on the role of targeted effectors (e.g. a combination of 5-FC with CD-NSPCs as compared to the application of NSPCs alone) and how such delivery of pro-drug activating enzymes and other tumor-killing substances may overcome melanocytic defence system, interact with and promote the host defence and immune response modulations not only in melanoma but, potentially, in other highly-metastatic cancers.

Changes of the power coefficient in the 'metabolism-mass' relationship in the evolutionary process of animals

The power coefficient k decreases along evolution in an allometric relationship between the oxygen consumption rate and the body mass of animals. This theoretical study investigated the role of the power coefficient k and its behavior along evolution. The animals were organized in three groups according to the values of the power coefficient k as follows: (I) from unicellular Prokaryotes to Eukaryotes; (II) from Mytilus and Annelida to Pisces; (III) from Reptilia to Mammals and Aves. At the beginning of each animal group (stage), the value of k was close to 0.9-1.0 and at the end of the stage it was close to 0.67-0.70. Exponential sharp increase of the power coefficient k was observed during the biological transition from Protozoa to simply organized Metazoa and in the transition from Poikylothermic to Homothermic organisms (e.g. from Pisces to Reptilia). Also, when using the periodogram regression analysis, a cyclic (periodic) pattern in this increase was observed (i.e. period T approximately 8-11 units, P<0.05). It was postulated that the power coefficient k, as with the coefficient a, might represent the increase of complexity of animal organization within each group.

A thermodynamic interpretation of malignancy: do the genes come later?

Current theories on cancer development focus on 'unlucky' mutations affecting oncogenes or tumour suppressor genes. In this article a theory will be developed which interprets cancer as an adaptive phenomenon -- a response to cellular stress induced by an energetic overload which would ultimately lead to an increase in cellular entropy. One of these adaptive mechanisms is paneuploid polyploidization, a phenomenon frequently described in malignant tumours. This inherent property of the genome to multiply with limited sequence variability may be involved just to make new proteins which are more appropriate to manage the harmful situation of energetic overload. Another important mechanism to prevent increasing entropy is the change in chirality of proteins and carbon hydrates because the use of enantiomers with higher intrinsic energy ultimately reduces entropy of the cell. These chiral alterations in turn affect the molecular structures of proteins and DNA, resulting in abnormal function of the former and disturbances of replication, transcription and repair of the latter. Moreover, the altered proteins may -- as a secondary step -- induce structural changes of the DNA. Because changes in chirality affect the structure of a cell randomly, one can expect alterations of multiple genes or proteins, and this is exactly what has been described in the literature. Therefore, this hypothesis may help to clarify confusing findings of tumour genetics accumulated over the last two decades. Cancer could be seen as a reaction of a cell to entrap energy which reduces entropy, or, in other words, cancer may best be regarded as entropic devolution.