Allen Tannenbaum | bioRxiv Science

bioRxiv2016

Curvature Analysis of Estrogen Receptor Positive Breast Cancer Under PI3K Inhibition

In this note, we re-examine the work of Bosch et al. from a network point of view. In particular, we employ an extended defintion of Ollivier-Ricci curvature that allows us to study graphs with both positive and negative weights. This is done by utilizing a dual formulation of the Wasserstein 1-metric, allowing us to extend the Earth Movers Distance to signed measures. The resulting curvature may be applied study the robustness properties of general networks modelled as weighted graphs. In this note, we apply the theory to elucidate the robustness and therefore possible mechanisms of resistance of estrogen receptor positive breast cancer under PI3K inhibition.

Cancer Biology↗

bioRxiv2016

A Quantitative Analysis of Localized Robustness of MYCN in Neuroblastoma

The amplification of the gene MYCN (V-myc mye-locytomatosis viral-valeted oncogene, neuroblastoma derived) has been a well-documented indicator for poor prognosis in neuroblastoma, a childhood cancer. Unfortunately, there has been limited success in understanding MYCN functionality in the landscape of neuroblastoma and more importantly given that MYCN has been deemed \"undruggable,\" the need to potentially illuminate key opportunities that indirectly target MYCN is of great interest. To this end, this work employs an emerging quantitative technique from network science, namely network curvature, to quantify the biological robustness of MYCN and its surrounding neighborhood. In particular, when amplified in Stage IV cancer, MYCN exhibits higher curvature (more robust) than those samples with under expressed MYCN levels. When examining the surrounding neighborhood, the above argument still holds for network curvature, but is lost when only analyzing differential expression - a common technique amongst oncologists and computational/molecular biologists. This finding points to the problem (and possible solution) of drug targeting in the context ofcomplexity and indirect cell signaling affects that have often been obfuscated through traditional techniques.

Cancer Biology↗