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-throughput 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

Maghemite Nanoparticles Acts as Nanozymes, Improving Growth and Abiotic Stress Tolerance in Brassica napus

Yttrium doping-stabilized γ-Fe2O3 nanoparticles were studied for its potential to serve as a plant fertilizer and, through enzymatic activity, support drought stress management. Levels of both hydrogen peroxide and lipid peroxidation, after drought, were reduced when γ-Fe2O3 nanoparticles were delivered by irrigation in a nutrient solution to Brassica napus plants grown in soil. Hydrogen peroxide was reduced from 151 to 83 μM g−1 compared to control, and the malondialdehyde formation was reduced from 36 to 26 mM g−1. Growth rate of leaves was enhanced from 33 to 50% growth compared to fully fertilized plants and SPAD-measurements of chlorophyll increased from 47 to 52 suggesting improved agronomic properties by use of γ-Fe2O3 nanoparticles as fertilizer as compared to chelated iron