Leena Karhinen

ORP2 is a ubiquitously expressed OSBP-related protein previously implicated in endoplasmic reticulum (ER)—lipid droplet (LD) contacts, triacylglycerol (TG) metabolism, cholesterol transport, adrenocortical steroidogenesis, and actin-dependent cell dynamics. Here, we characterize the role of ORP2 in carbohydrate and lipid metabolism by employing ORP2-knockout (KO) hepatoma cells (HuH7) generated by CRISPR-Cas9 gene editing. The ORP2-KO and control HuH7 cells were subjected to RNA sequencing, analyses of Akt signaling, carbohydrate and TG metabolism, the extracellular acidification rate, and the lipidome, as well as to transmission electron microscopy. The loss of ORP2 resulted in a marked reduction of active phosphorylated Akt(Ser473) and its target Glycogen synthase kinase 3β(Ser9), consistent with defective Akt signaling. ORP2 was found to form a physical complex with the key controllers of Akt activity, Cdc37, and Hsp90, and to co-localize with Cdc37 and active Akt(Ser473) at lamellipodial plasma membrane regions, in addition to the previously reported ER–LD localization. ORP2-KO reduced glucose uptake, glycogen synthesis, glycolysis, mRNA-encoding glycolytic enzymes, and SREBP-1 target gene expression, and led to defective TG synthesis and storage. ORP2-KO did not reduce but rather increased ER–LD contacts under basal culture conditions and interfered with their expansion upon fatty acid loading. Together with our recently published work (Kentala et al. in FASEB J 32:1281–1295, 2018 ), this study identifies ORP2 as a new regulatory nexus of Akt signaling, cellular energy metabolism, actin cytoskeletal function, cell migration, and proliferation.

Lipid droplets (LDs) are cellular organelles specialized in triacylglycerol (TG) storage undergoing homotypic clustering and fusion. In non-adipocytic cells with numerous LDs this is balanced by poorly understood droplet dissociation mechanisms. We identify non-muscle myosin IIa (NMIIa/MYH-9) and formin-like 1 (FMNL1) in the LD proteome. NMIIa and actin filaments concentrate around LDs, and form transient foci between dissociating LDs. NMIIa depletion results in decreased LD dissociations, enlarged LDs, decreased hydrolysis and increased storage of TGs. FMNL1 is required for actin assembly on LDs in vitro and for NMIIa recruitment to LDs in cells. We propose a novel acto-myosin structure regulating lipid storage: FMNL1-dependent assembly of myosin II-functionalized actin filaments on LDs facilitates their dissociation, thereby affecting LD surface-to-volume ratio and enzyme accessibility to TGs. In neutrophilic leucocytes from MYH9-related disease patients NMIIa inclusions are accompanied by increased lipid storage in droplets, suggesting that NMIIa dysfunction may contribute to lipid imbalance in man.

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Triple negative breast cancer (TNBC) is a highly heterogeneous and aggressive type of cancer that lacks effective targeted therapy. Despite detailed molecular profiling, no targeted therapy has been established. Hence, with the aim of gaining deeper understanding of the functional differences of TNBC subtypes and how that may relate to potential novel therapeutic strategies, we studied comprehensive anticancer-agent responses among a panel of TNBC cell lines. The responses of 301 approved and investigational oncology compounds were measured in 16 TNBC cell lines applying a functional profiling approach. To go beyond the standard drug viability effect profiling, which has been used in most chemosensitivity studies, we utilized a multiplexed readout for both cell viability and cytotoxicity, allowing us to differentiate between cytostatic and cytotoxic responses. Our approach revealed that most single-agent anti-cancer compounds that showed activity for the viability readout had no or little cytotoxic effects. Major compound classes that exhibited this type of response included anti-mitotics, mTOR, CDK, and metabolic inhibitors, as well as many agents selectively inhibiting oncogene-activated pathways. However, within the broad viability-acting classes of compounds, there were often subsets of cell lines that responded by cell death, suggesting that these cells are particularly vulnerable to the tested substance. In those cases we could identify differential levels of protein markers associated with cytotoxic responses. For example, PAI-1, MAPK phosphatase and Notch-3 levels associated with cytotoxic responses to mitotic and proteasome inhibitors, suggesting that these might serve as markers of response also in clinical settings. Furthermore, the cytotoxicity readout highlighted selective synergistic and synthetic lethal drug combinations that were missed by the cell viability readouts. For instance, the MEK inhibitor trametinib synergized with PARP inhibitors. Similarly, combination of two non-cytotoxic compounds, the rapamycin analog everolimus and an ATP-competitive mTOR inhibitor dactolisib, showed synthetic lethality in several mTOR-addicted cell lines. Taken together, by studying the combination of cytotoxic and cytostatic drug responses, we identified a deeper spectrum of cellular responses both to single agents and combinations that may be highly relevant for identifying precision medicine approaches in TNBC as well as in other types of cancers.

A recent trend in drug development is to identify drug combinations or multi-target agents that effectively modify multiple nodes of disease-associated networks. Such polypharmacological effects may reduce the risk of emerging drug resistance by means of attacking the disease networks through synergistic and synthetic lethal interactions. However, due to the exponentially increasing number of potential drug and target combinations, systematic approaches are needed for prioritizing the most potent multi-target alternatives on a global network level. We took a functional systems pharmacology approach toward the identification of selective target combinations for specific cancer cells by combining large-scale screening data on drug treatment efficacies and drug-target binding affinities. Our model-based prediction approach, named TIMMA, takes advantage of the polypharmacological effects of drugs and infers combinatorial drug efficacies through system-level target inhibition networks. Case studies in MCF-7 and MDA-MB-231 breast cancer and BxPC-3 pancreatic cancer cells demonstrated how the target inhibition modeling allows systematic exploration of functional interactions between drugs and their targets to maximally inhibit multiple survival pathways in a given cancer type. The TIMMA prediction results were experimentally validated by means of systematic siRNA-mediated silencing of the selected targets and their pairwise combinations, showing increased ability to identify not only such druggable kinase targets that are essential for cancer survival either individually or in combination, but also synergistic interactions indicative of non-additive drug efficacies. These system-level analyses were enabled by a novel model construction method utilizing maximization and minimization rules, as well as a model selection algorithm based on sequential forward floating search. Compared with an existing computational solution, TIMMA showed both enhanced prediction accuracies in cross validation as well as significant reduction in computation times. Such cost-effective computational-experimental design strategies have the potential to greatly speed-up the drug testing efforts by prioritizing those interventions and interactions warranting further study in individual cancer cases. Selective inhibition of specific panels of multiple protein targets provides an unprecedented potential for improving therapeutic efficacy of anticancer agents. We introduce a computational systems pharmacology strategy, which uses the concept of target inhibition networks to predict effective multi-target combinations for treating specific cancer types. The strategy is based on integration of two complementary information sources, drug treatment efficacies and drug-target binding affinities, which are readily available in drug screening labs. Compared to the cancer sequencing efforts, which often result in a huge number of non-targetable genetic alterations, the target combinations from our strategy are druggable, by definition, hence enabling more straightforward translation toward clinically actionable treatment strategies. The model predictions were experimentally validated using siRNA-mediated target silencing screens in three case studies involving MDA-MB-231 and MCF-7 breast cancer and BxPC-3 pancreatic cancer cells. In more general terms, the cancer cell-specific target inhibition networks provided additional insights into the drugs' mechanisms of action, for instance, how the cancer cell survival pathways can be targeted by synergistic and synthetic lethal interactions through multi–target perturbations. These results demonstrate that the principles introduced here offer the possibilities to move toward more systematic prediction and evaluation of the most effective drug target combinations.

During the epithelium remodelling such as the flattening of the Drosophila follicular epithelium, the α-integrin subunits are unconventionally secreted through a dGRASP-dependent route that is built de novo. The biogenetic process starts with the upregulation of a small subset of targeted mRNAs, including dgrasp. Here, we show that dgrasp mRNA upregulation is triggered by the tension of the underlying oocyte and by applied external forces at the basal side of the follicular epithelium. We show that integrins are also involved in dgrasp mRNA upregulation and the epithelium remodelling. Tension leads to the recruitment of RhoA to the plasma membrane, where it participates in its remodelling. The LIM protein PINCH can cycle to the nucleus and is involved in dgrasp mRNA upregulation. We propose that integrins are involved in triggering the biogenesis of their own unconventional secretion route that they use to strengthen adhesion and ensure epithelial integrity at the next stages of development, perhaps by acting as mechanosensors of the underlying tension through RhoA and PINCH.

Glycoproteins exit the endoplasmic reticulum (ER) of the yeast Saccharomyces cerevisiae in coàt protein complex II (COPII) coated vesicles. The coat consists of the essential proteins Sec23p, Sec24p, Sec13p, Sec31p, Sar1p and Sec16p. Sec24p and its two nonessential homologues Sfb2p and Sfb3p have been suggested to serve in cargo selection. Using temperature-sensitive sec24-1 mutants, we showed previously that a secretory glycoprotein, Hsp150, does not require functional Sec24p for ER exit. Deletion of SFB2, SFB3 or both from wild type or the deletion of SFB2 from sec24-1 cells did not affect Hsp150 transport. SFB3 deletion has been reported to be lethal in sec24-1. However, here we constructed a sec24-1 Δsfb3 and a sec24-1 Δsfb2 Δsfb3 strain and show that Hsp150 was secreted slowly in both. Turning off the SEC24 gene did not inhibit Hsp150 secretion either, and the lack of SEC24 expression in a Δsfb2 Δsfb3 deletant still allowed some secretion. The sec24-1 Δsfb2 Δsfb3 mutant grew slower than sec24-1. The cells were irregularly shaped, budded from random sites and contained proliferated ER at permissive temperature. At restrictive temperature, the ER formed carmellae-like proliferations. Our data indicate that ER exit may occur in vesicles lacking a full complement of Sec23p/24p and Sec13p/31p, demonstrating diversity in the composition of the COPII coat.

Exit of proteins from the yeast endoplasmic reticulum (ER) is thought to occur in vesicles coated by four proteins, Sec13p, Sec31p, Sec23p and Sec24p, which assemble at ER exit sites to form the COPII coat. Sec13p may serve a structural function, whereas Sec24p has been suggested to operate in selection of cargo proteins into COPII vesicles. We showed recently that the soluble glycoprotein Hsp150 exited the ER in the absence of Sec13p function. Here we show that its ER exit did not require functional Sec24p. Hsp150 was secreted to the medium in a sec24-1 mutant at restrictive temperature 37°C, while cell wall invertase and vacuolar carboxypeptidase Y remained in the ER. The determinant guiding Hsp150 to this transport route was mapped to the C-terminal domain of 114 amino acids by deletion analysis, and by an HRP fusion protein-based EM technology adapted here for yeast. This domain actively mediated ER exit of Sec24p-dependent invertase in the absence of Sec24p function. However, the domain was entirely dispensable for ER exit when Sec24p was functional. The Sec24p homolog Sfb2p was shown not to compensate for nonfunctional Sec24p in ER exit of Hsp150. Our data show that a soluble cargo protein, Hsp150, is selected actively and specifically to budding sites lacking normal Sec24p by a signature residing in its C-terminal domain.