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

Wireless Power Transfer and Telemetry for Implantable Bioelectronics

© 2021 Wiley-VCH GmbHImplantable bioelectronic devices are becoming useful and prospective solutions for various diseases owing to their ability to monitor or manipulate body functions. However, conventional implantable devices (e.g., pacemaker and neurostimulator) are still bulky and rigid, which is mostly due to the energy storage component. In addition to mechanical mismatch between the bulky and rigid implantable device and the soft human tissue, another significant drawback is that the entire device should be surgically replaced once the initially stored energy is exhausted. Besides, retrieving physiological information across a closed epidermis is a tricky procedure. However, wireless interfaces for power and data transfer utilizing radio frequency (RF) microwave offer a promising solution for resolving such issues. While the RF interfacing devices for power and data transfer are extensively investigated and developed using conventional electronics, their application to implantable bioelectronics is still a challenge owing to the constraints and requirements of in vivo environments, such as mechanical softness, small module size, tissue attenuation, and biocompatibility. This work elucidates the recent advances in RF-based power transfer and telemetry for implantable bioelectronics to tackle such challenges.11Nsciescopu