Biomolecular Condensation: A New Phase in Cancer Research.

Multicellularity was a watershed development in evolution. However, it also meant that individual cells could escape regulatory mechanisms that restrict proliferation at a severe cost to the organism: cancer. From the standpoint of cellular organization, evolutionary complexity scales to organize different molecules within the intracellular milieu. The recent realization that many biomolecules can "phase-separate" into membraneless organelles, reorganizing cellular biochemistry in space and time, has led to an explosion of research activity in this area. In this review, we explore mechanistic connections between phase separation and cancer-associated processes and emerging examples of how these become deranged in malignancy. SIGNIFICANCE: One of the fundamental functions of phase separation is to rapidly and dynamically respond to environmental perturbations. Importantly, these changes often lead to alterations in cancer-relevant pathways and processes. This review covers recent advances in the field, including emerging principles and mechanisms of phase separation in cancer.

Improving HPC System Performance by Predicting Job Resources via Supervised Machine Learning.

High-Performance Computing (HPC) systems are resources utilized for data capture, sharing, and analysis. The majority of our HPC users come from other disciplines than Computer Science. HPC users including computer scientists have difficulties and do not feel proficient enough to decide the required amount of resources for their submitted jobs on the cluster. Consequently, users are encouraged to over-estimate resources for their submitted jobs, so their jobs will not be killing due insufficient resources. This process will waste and devour HPC resources; hence, this will lead to inefficient cluster utilization. We created a supervised machine learning model and integrated it into the Slurm resource manager simulator to predict the amount of required memory resources (Memory) and the required amount of time to run the computation. Our model involves using different machine learning algorithms. Our goal is to integrate and test the proposed supervised machine learning model on Slurm. We used over 10000 tasks selected from our HPC log files to evaluate the performance and the accuracy of our integrated model. The purpose of our work is to increase the performance of the Slurm by predicting the amount of require jobs memory resources and the time required for each particular job in order to improve the utilization of the HPC system using our integrated supervised machine learning model. Our results indicate that for larger jobs our model helps dramatically reduce computational turnaround time (from five days to ten hours for large jobs), substantially increased utilization of the HPC system, and decreased the average waiting time for the submitted jobs.

Mutations in the Drosophila tricellular junction protein M6 synergize with RasV12 to induce apical cell delamination and invasion.

Complications from metastasis are responsible for the majority of cancer-related deaths. Despite the outsized medical impact of metastasis, remarkably little is known about one of the key early steps of metastasis: departure of a tumor cell from its originating tissue. It is well documented that cellular delamination in the basal direction can induce invasive behaviors, but it remains unknown if apical cell delamination can induce migration and invasion in a cancer context. To explore this feature of cancer progression, we performed a genetic screen in Drosophila and discovered that mutations in the protein M6 synergize with oncogenic Ras to drive invasion following apical delamination without crossing a basement membrane. Mechanistically, we observed that M6-deficient RasV12 clones delaminate as a result of alterations in a Canoe-RhoA-myosin II axis that is necessary for both the delamination and invasion phenotypes. To uncover the cellular roles of M6, we show that it localizes to tricellular junctions in epithelial tissues where it is necessary for the structural integrity of multicellular contacts. This work provides evidence that apical delamination can precede invasion and highlights the important role that tricellular junction integrity can play in this process.

The dark side of hippo signaling: A cancer promoter role.

The Hippo signaling pathway regulates organ size and tissue homeostasis. Given this role it is unsurprising that dysregulation of this pathway has implications for cancer progression. A convincing body of literature shows that the Hippo pathway serves a tumor suppressive function with its inactivation leading to massive overgrowth. However, additional studies have also shown that activation of Hippo signaling can promote tumor progression. It remains unknown how a single pathway can produce such diametrically opposed effects. This lack of knowledge is in part due to our inability to make meaningful comparisons from studies which have taken place in a variety of cell types, tissues, and organisms. Recently however, we have published 2 studies using the Drosophila wing disk to study the Hippo pathway and have found that Hippo pathway activation can promote cell migration and invasion while Hippo pathway inactivation leads to overgrowth. Thus we propose here that Drosophila can provide a research platform with which to begin addressing how the Hippo pathway can both enhance and suppress tumor progression due to published pro- and anti-tumor functionalities of the Hippo pathway in the same tissue.