Repeated games for eikonal equations, integral curvature flows and non-linear parabolic integro-differential equations

The main purpose of this paper is to approximate several non-local evolution equations by zero-sum repeated games in the spirit of the previous works of Kohn and the second author (2006 and 2009): general fully non-linear parabolic integro-differential equations on the one hand, and the integral curvature flow of an interface (Imbert, 2008) on the other hand. In order to do so, we start by constructing such a game for eikonal equations whose speed has a non-constant sign. This provides a (discrete) deterministic control interpretation of these evolution equations. In all our games, two players choose positions successively, and their final payoff is determined by their positions and additional parameters of choice. Because of the non-locality of the problems approximated, by contrast with local problems, their choices have to "collect" information far from their current position. For integral curvature flows, players choose hypersurfaces in the whole space and positions on these hypersurfaces. For parabolic integro-differential equations, players choose smooth functions on the whole space

Bezielle Selectively Targets Mitochondria of Cancer Cells to Inhibit Glycolysis and OXPHOS

Bezielle (BZL101) is a candidate oral drug that has shown promising efficacy and excellent safety in the early phase clinical trials for advanced breast cancer. Bezielle is an aqueous extract from the herb Scutellaria barbata. We have reported previously that Bezielle was selectively cytotoxic to cancer cells while sparing non-transformed cells. In tumor, but not in non-transformed cells, Bezielle induced generation of ROS and severe DNA damage followed by hyperactivation of PARP, depletion of the cellular ATP and NAD, and inhibition of glycolysis. We show here that tumor cells' mitochondria are the primary source of reactive oxygen species induced by Bezielle. Treatment with Bezielle induces progressively higher levels of mitochondrial superoxide as well as peroxide-type ROS. Inhibition of mitochondrial respiration prevents generation of both types of ROS and protects cells from Bezielle-induced death. In addition to glycolysis, Bezielle inhibits oxidative phosphorylation in tumor cells and depletes mitochondrial reserve capacity depriving cells of the ability to produce ATP. Tumor cells lacking functional mitochondria maintain glycolytic activity in presence of Bezielle thus supporting the hypothesis that mitochondria are the primary target of Bezielle. The metabolic effects of Bezielle towards normal cells are not significant, in agreement with the low levels of oxidative damage that Bezielle inflicts on them. Bezielle is therefore a drug that selectively targets cancer cell mitochondria, and is distinguished from other such drugs by its ability to induce not only inhibition of OXPHOS but also of glycolysis. This study provides a better understanding of the mechanism of Bezielle's cytotoxicity, and the basis of its selectivity towards cancer cells

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Functional analysis of Ectodysplasin-A mutations causing selective tooth agenesis.

Mutations of the Ectodysplasin-A (EDA) gene are generally associated with the syndrome hypohidrotic ectodermal dysplasia (MIM 305100), but they can also manifest as selective, non-syndromic tooth agenesis (MIM300606). We have performed an in vitro functional analysis of six selective tooth agenesis-causing EDA mutations (one novel and five known) that are located in the C-terminal tumor necrosis factor homology domain of the protein. Our study reveals that expression, receptor binding or signaling capability of the mutant EDA1 proteins is only impaired in contrast to syndrome-causing mutations, which we have previously shown to abolish EDA1 expression, receptor binding or signaling. Our results support a model in which the development of the human dentition, especially of anterior teeth, requires the highest level of EDA-receptor signaling, whereas other ectodermal appendages, including posterior teeth, have less stringent requirements and form normally in response to EDA mutations with reduced activity

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment