Ovarian Cancer Genetics: Subtypes and Risk Factors

The genetics of ovarian cancer are a complex, ever evolving concept that presents hurdles in classification, diagnosis, and treatment in the clinic. Instead of common driver mutations, genomic instability is one of the hallmarks of ovarian cancer. While ovarian cancer is stratified into different clinical subtypes, there still exists extensive genetic and progressive diversity within each subtype. In high-grade serous ovarian cancer, the most common subtype, TP53 is mutated in over 90% of all patients while the next most common mutation is less than 20%. However, next-generation sequencing and biological statistics have shown that mutations within DNA repair pathways, including BRCA1 and BRCA2, are common in about 50% of all high-grade serous patients leading to the development of a breakthrough therapy of poly ADP ribose polymerase (PARP) inhibitors. This is just one example of how a better understanding of the complex genetic background of ovarian cancer can improve clinical treatment. A thorough review of ovarian cancer genetics and the effect it has on disease development, diagnosis, progression, and treatment will enhance the understanding of how to better research and treat ovarian cancer

A Synthetic Lethality Screen Using a Focused siRNA Library to Identify Sensitizers to Dasatinib Therapy for the Treatment of Epithelial Ovarian Cancer.

Molecular targeted therapies have been the focus of recent clinical trials for the treatment of patients with recurrent epithelial ovarian cancer (EOC). The majority have not fared well as monotherapies for improving survival of these patients. Poor bioavailability, lack of predictive biomarkers, and the presence of multiple survival pathways can all diminish the success of a targeted agent. Dasatinib is a tyrosine kinase inhibitor of the Src-family kinases (SFK) and in preclinical studies shown to have substantial activity in EOC. However, when evaluated in a phase 2 clinical trial for patients with recurrent or persistent EOC, it was found to have minimal activity. We hypothesized that synthetic lethality screens performed using a cogently designed siRNA library would identify second-site molecular targets that could synergize with SFK inhibition and improve dasatinib efficacy. Using a systematic approach, we performed primary siRNA screening using a library focused on 638 genes corresponding to a network centered on EGFR, HER2, and the SFK-scaffolding proteins BCAR1, NEDD9, and EFS to screen EOC cells in combination with dasatinib. We followed up with validation studies including deconvolution screening, quantitative PCR to confirm effective gene silencing, correlation of gene expression with dasatinib sensitivity, and assessment of the clinical relevance of hits using TCGA ovarian cancer data. A refined list of five candidates (CSNK2A1, DAG1, GRB2, PRKCE, and VAV1) was identified as showing the greatest potential for improving sensitivity to dasatinib in EOC. Of these, CSNK2A1, which codes for the catalytic alpha subunit of protein kinase CK2, was selected for additional evaluation. Synergistic activity of the clinically relevant inhibitor of CK2, CX-4945, with dasatinib in reducing cell proliferation and increasing apoptosis was observed across multiple EOC cell lines. This overall approach to improving drug efficacy can be applied to other targeted agents that have similarly shown poor clinical activity

Roadmap on Photovoltaic Absorber Materials for Sustainable Energy Conversion

Photovoltaics (PVs) are a critical technology for curbing growing levels of anthropogenic greenhouse gas emissions, and meeting increases in future demand for low-carbon electricity. In order to fulfil ambitions for net-zero carbon dioxide equivalent (CO2eq) emissions worldwide, the global cumulative capacity of solar PVs must increase by an order of magnitude from 0.9 TWp in 2021 to 8.5 TWp by 2050 according to the International Renewable Energy Agency, which is considered to be a highly conservative estimate. In 2020, the Henry Royce Institute brought together the UK PV community to discuss the critical technological and infrastructure challenges that need to be overcome to address the vast challenges in accelerating PV deployment. Herein, we examine the key developments in the global community, especially the progress made in the field since this earlier roadmap, bringing together experts primarily from the UK across the breadth of the photovoltaics community. The focus is both on the challenges in improving the efficiency, stability and levelized cost of electricity of current technologies for utility-scale PVs, as well as the fundamental questions in novel technologies that can have a significant impact on emerging markets, such as indoor PVs, space PVs, and agrivoltaics. We discuss challenges in advanced metrology and computational tools, as well as the growing synergies between PVs and solar fuels, and offer a perspective on the environmental sustainability of the PV industry. Through this roadmap, we emphasize promising pathways forward in both the short- and long-term, and for communities working on technologies across a range of maturity levels to learn from each other.Comment: 160 pages, 21 figure

Robots, art and complexity science

Creating robotic systems has proved extremely attractive to many artists, and a variety of examples will be shown. Robots are defined to be autonomous machines that can interact with their environment. Sensors enable information about the environment to enter the robot, and actuators allow the robot to act on the environment. Some robots are reactive, linking sensors directly to actuators, giving kinds of reflex actions. Some robots have cognitive abilities that enable them to process their sensory information and use their actuators in purposeful ways. This may, or may not, be viewed as intelligent behaviour. Some robots have embodied intelligence where apparently purposeful behaviour emerges from the construction and physical properties of their components e.g. a rubber arm can twist back to its original position without the need for further cogitation or power. Generally artists want audiences to engage with their creations, and artists are naturally attracted to robotics as a medium of exploration and expression. Robots can be engaging and fun, and they can behave in unexpected and provocative ways. Robotic objects can sense and respond to the viewer or audience, opening up new interactive possibilities for the artist. In many areas of life, art is a driver of innovation and discovery, and we argue that robotic art can be a driver of innovation in the science of complex systems. Robot communities form an intermediate class of complex system, more complex than many physical systems but less complex than human systems. Robot systems allow replicable experiments that are impossible in human systems. But robot art takes us beyond this. Artists observe and experiment in a different way to scientists. They do not necessarily form or test hypotheses, and the outcomes of their experiments may be completely unpredictable. The divergent experiments of artists take us to parts of complex systems space that might never be visited otherwise. The nature of robotics allows us to make extensive observations and measurements of such space. This combination gives the potential for new insights into the fundamental questions in the emerging science of complex systems

Questions about Hindmanâ s theorem

Non UBCUnreviewedAuthor affiliation: Appalachian State UniversityFacult

Epimorphin-Induced MET Sensitizes Ovarian Cancer Cells to Platinum

<div><p>Distinctive genotypic and phenotypic features of ovarian cancer via epithelial-mesenchymal transition (EMT) have been correlated with drug resistance and disease recurrence. We investigated whether therapeutic reversal of EMT could re-sensitize ovarian cancer cells (OCCs) to existing chemotherapy. We report that epimorphin, a morphogenic protein, has pivotal control over mesenchymal versus epithelial cell lineage decision of the putative OCCs. Exposure to epimorphin induced morphological changes reminiscent of mesenchymal-to-epithelial transition (MET), but in a dose dependent manner, i.e., at 10 µg/mL of epimorphin cells obtain a more mesenchymal-like morphology while at 20 µg/mL of epimorphin cells display an epithelial morphology. The latter changes were accompanied by suppression of mesenchymal markers, such as vimentin (∼8-fold↓, <i>p</i><0.02), Twist1 (∼7-fold↓, <i>p</i><0.03), dystroglycan (∼4-fold↓, <i>p</i><0.01) and palladin (∼3-fold↓, <i>p</i><0.01). Conversely, significant elevations of KLF4 (∼28-fold↑, <i>p</i><0.002), β-catenin (∼6-fold↑, <i>p</i><0.004), EpCAM (∼6-fold↑, <i>p</i><0.0002) and occludin (∼15-fold↑, <i>p</i><0.004) mRNAs as part of the commitment to the epithelial cell lineage were detected in response to 20 µg/mL of exogenous epimorphin. Changes in occludin mRNA levels were accompanied by a parallel, albeit weaker expression at the protein level (∼5-fold↑, <i>p</i><0.001). Likewise, acquisition of epithelial-like properties, including mucin1, CK19, and β-catenin gene expression, was also obtained following epimorphin treatment. Further, MMP3 production was found to be reduced whereas laminin secretion was strongly amplified upon epimorphin-induced MET. These results suggest there is a dosage window for actions of epimorphin on cellular differentiation, wherein it can either suppress or enhance epithelial differentiation of OCCs. Importantly, induction of epithelial-like phenotypes by epimorphin led to an enhanced sensitivity to carboplatin. Overall, we demonstrate that epimorphin can revert OCCs away from their mesenchymal phenotype and toward an epithelial phenotype, thereby enhancing their sensitivity to a front-line chemotherapeutic agent.</p></div