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

Revealing the biotechnological potential of Delftia sp. JD2 by a genomic approach

Delftia sp. JD2 is a chromium-resistant bacterium that reduces Cr(VI) to Cr(III), accumulates Pb(II), produces the phytohormone indole-3-acetic acid and siderophores, and increases the plant growth performance of rhizobia in co-inoculation experiments. We aimed to analyze the biotechnological potential of JD2 using a genomic approach. JD2 has a genome of 6.76Mb, with 6,051 predicted protein coding sequences and 93 RNA genes (tRNA and rRNA). The indole-acetamide pathway was identified as responsible for the synthesis of indole-3-acetic acid. The genetic information involved in chromium resistance (the gene cluster, chrBACF,) was found. At least 40 putative genes encoding for TonB-dependent receptors, probably involved in the utilization of siderophores and biopolymers, and genes for the synthesis, maturation, exportation and uptake of pyoverdine, and acquisition of Fe-pyochelin and Fe-enterobactin were also identified. The information also suggests that JD2 produce polyhydroxybutyrate, a carbon reserve polymer commonly used for manufacturing petrochemical free bioplastics. In addition, JD2 may degrade lignin-derived aromatic compounds to 2-pyrone-4,6-dicarboxylate, a molecule used in the bio-based polymer industry. Finally, a comparative genomic analysis of JD2, Delftia sp. Cs1-4 and Delftia acidovorans SPH-1 is also discussed. The present work provides insights into the physiology and genetics of a microorganism with many potential uses in biotechnology