Antiproliferative Activity of Piceamycin by Regulating Alpha-Actinin-4 in Gemcitabine-Resistant Pancreatic Cancer Cells.

Although gemcitabine-based regimens are widely used as an effective treatment for pancreatic cancer, acquired resistance to gemcitabine has become an increasingly common problem. Therefore, a novel therapeutic strategy to treat gemcitabine-resistant pancreatic cancer is urgently required. Piceamycin has been reported to exhibit antiproliferative activity against various cancer cells; however, its underlying molecular mechanism for anticancer activity in pancreatic cancer cells remains unexplored. Therefore, the present study evaluated the antiproliferation activity of piceamycin in a gemcitabine-resistant pancreatic cancer cell line and patient-derived pancreatic cancer organoids. Piceamycin effectively inhibited the proliferation and suppressed the expression of alpha-actinin-4, a gene that plays a pivotal role in tumorigenesis and metastasis of various cancers, in gemcitabine-resistant cells. Long-term exposure to piceamycin induced cell cycle arrest at the G0/G1 phase and caused apoptosis. Piceamycin also inhibited the invasion and migration of gemcitabine-resistant cells by modulating focal adhesion and epithelial-mesenchymal transition biomarkers. Moreover, the combination of piceamycin and gemcitabine exhibited a synergistic antiproliferative activity in gemcitabine-resistant cells. Piceamycin also effectively inhibited patient-derived pancreatic cancer organoid growth and induced apoptosis in the organoids. Taken together, these findings demonstrate that piceamycin may be an effective agent for overcoming gemcitabine resistance in pancreatic cancer.

Antiproliferative Activity of Krukovine by Regulating Transmembrane Protein 139 (TMEM139) in Oxaliplatin-Resistant Pancreatic Cancer Cells.

Krukovine (KV) is an alkaloid isolated from the bark of Abuta grandifolia (Mart.) Sandw. (Menispermaceae) with anticancer potential in some cancers with KRAS mutations. In this study, we explored the anticancer efficacy and mechanism of KV in oxaliplatin-resistant pancreatic cancer cells and patient-derived pancreatic cancer organoids (PDPCOs) with KRAS mutation. After treatment with KV, mRNA and protein levels were determined by RNA-seq and Western blotting, respectively. Cell proliferation, migration, and invasion were measured by MTT, scratch wound healing assay, and transwell analysis, respectively. Patient-derived pancreatic cancer organoids (PDPCOs) with KRAS mutations were treated with KV, oxaliplatin (OXA), and a combination of KV and OXA. KV suppresses tumor progression via the downregulation of the Erk-RPS6K-TMEM139 and PI3K-Akt-mTOR pathways in oxaliplatin-resistant AsPC-1 cells. Furthermore, KV showed an antiproliferative effect in PDPCOs, and the combination of OXA and KV inhibited PDPCO growth more effectively than either drug alone.

RNA secondary structure packages evaluated and improved by high-throughput experiments.

Despite the popularity of computer-aided study and design of RNA molecules, little is known about the accuracy of commonly used structure modeling packages in tasks sensitive to ensemble properties of RNA. Here, we demonstrate that the EternaBench dataset, a set of more than 20,000 synthetic RNA constructs designed on the RNA design platform Eterna, provides incisive discriminative power in evaluating current packages in ensemble-oriented structure prediction tasks. We find that CONTRAfold and RNAsoft, packages with parameters derived through statistical learning, achieve consistently higher accuracy than more widely used packages in their standard settings, which derive parameters primarily from thermodynamic experiments. We hypothesized that training a multitask model with the varied data types in EternaBench might improve inference on ensemble-based prediction tasks. Indeed, the resulting model, named EternaFold, demonstrated improved performance that generalizes to diverse external datasets including complete messenger RNAs, viral genomes probed in human cells and synthetic designs modeling mRNA vaccines.

Principles for Predicting RNA Secondary Structure Design Difficulty.

Designing RNAs that form specific secondary structures is enabling better understanding and control of living systems through RNA-guided silencing, genome editing and protein organization. Little is known, however, about which RNA secondary structures might be tractable for downstream sequence design, increasing the time and expense of design efforts due to inefficient secondary structure choices. Here, we present insights into specific structural features that increase the difficulty of finding sequences that fold into a target RNA secondary structure, summarizing the design efforts of tens of thousands of human participants and three automated algorithms (RNAInverse, INFO-RNA and RNA-SSD) in the Eterna massive open laboratory. Subsequent tests through three independent RNA design algorithms (NUPACK, DSS-Opt and MODENA) confirmed the hypothesized importance of several features in determining design difficulty, including sequence length, mean stem length, symmetry and specific difficult-to-design motifs such as zigzags. Based on these results, we have compiled an Eterna100 benchmark of 100 secondary structure design challenges that span a large range in design difficulty to help test future efforts. Our in silico results suggest new routes for improving computational RNA design methods and for extending these insights to assess "designability" of single RNA structures, as well as of switches for in vitro and in vivo applications.

RNA design rules from a massive open laboratory.

Self-assembling RNA molecules present compelling substrates for the rational interrogation and control of living systems. However, imperfect in silico models--even at the secondary structure level--hinder the design of new RNAs that function properly when synthesized. Here, we present a unique and potentially general approach to such empirical problems: the Massive Open Laboratory. The EteRNA project connects 37,000 enthusiasts to RNA design puzzles through an online interface. Uniquely, EteRNA participants not only manipulate simulated molecules but also control a remote experimental pipeline for high-throughput RNA synthesis and structure mapping. We show herein that the EteRNA community leveraged dozens of cycles of continuous wet laboratory feedback to learn strategies for solving in vitro RNA design problems on which automated methods fail. The top strategies--including several previously unrecognized negative design rules--were distilled by machine learning into an algorithm, EteRNABot. Over a rigorous 1-y testing phase, both the EteRNA community and EteRNABot significantly outperformed prior algorithms in a dozen RNA secondary structure design tests, including the creation of dendrimer-like structures and scaffolds for small molecule sensors. These results show that an online community can carry out large-scale experiments, hypothesis generation, and algorithm design to create practical advances in empirical science.

Heat shock protein 90 (HSP90) inhibitors activate the heat shock factor 1 (HSF1) stress response pathway and improve glucose regulation in diabetic mice.

The cytoprotective stress response factor HSF1 regulates the transcription of the chaperone HSP70, which exhibits anti-inflammatory effects and improves insulin sensitivity. We tested the therapeutic potential of this pathway in rodent models of diabetes using pharmacological tools. Activation of the HSF1 pathway was achieved using potent inhibitors of the upstream regulatory protein, HSP90. Treatment with AUY922, a selective HSP90 inhibitor led to robust inhibition of JNK1 phosphorylation, cytoprotection and improved insulin signaling in cells, consistent with effects observed with HSP70 treatment. Chronic dosing with HSP90 inhibitors reversed hyperglycemia in the diabetic db/db mouse model, and improved insulin sensitivity in the diet-induced obese mouse model of insulin resistance, further supporting the concept that the HSF1 pathway is a potentially viable anti-diabetes target.

Predicting protein structures with a multiplayer online game.

People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.

Retinoic acid enhances prostaglandin E2 production through increased expression of cyclooxygenase-2 and microsomal prostaglandin E synthase-1 in rat brain microglia.

Retinoic acid (RA) is a well-known antiinflammatory agent. In this study, we show that RA has a dual effect on cyclooxygenase-2 (COX-2) expression in inflammatory activated microglia, the resident brain macrophages. After treatment of microglia with LPS or thrombin, COX-2 expression was induced in two phases, specifically, an initial increase at about 12 hr after stimulation followed by a decrease, and another increase at about 48-72 hr. However, PGE(2) and 15d-PGJ(2) were detected at about 12 hr, and the levels continuously increased thereafter. Interestingly, all-trans retinoic acid (ATRA) suppressed the expression of early-phase COX-2 but augmented late-phase COX-2 and inhibited iNOS in the whole time sequence. ATRA enhanced PGE(2) production but had little effect on 15d-PGJ(2). Moreover, ATRA selectively up-regulated the expression of a PGE(2) synthase, mPGES-1, but had little effect on the PGD(2) synthase, H-PGDS. The results collectively suggest that ATRA modulates microglial responses to inflammatory stimulators, particularly at the late phase, via enhancement of COX-2 expression and PGE(2) production.

Dynamic resolution of functionally related gene sets in response to acute heat stress.

BACKGROUND: Using a gene clustering strategy we determined intracellular pathway relationships within skeletal myotubes in response to an acute heat stress stimuli. Following heat shock, the transcriptome was analyzed by microarray in a temporal fashion to characterize the dynamic relationship of signaling pathways. RESULTS: Bioinformatics analyses exposed coordination of functionally-related gene sets, depicting mechanism-based responses to heat shock. Protein turnover-related pathways were significantly affected including protein folding, pre-mRNA processing, mRNA splicing, proteolysis and proteasome-related pathways. Many responses were transient, tending to normalize within 24 hours. CONCLUSION: In summary, we show that the transcriptional response to acute cell stress is largely transient and proteosome-centric.

Human adipose-derived stem cells display myogenic potential and perturbed function in hypoxic conditions.

Here, we enriched a human cell population from adipose tissue that exhibited both mesenchymal plasticity, self-renewal capacity, and a cell-surface marker profile indistinguishable from that of bone marrow-derived mesenchymal stem cells. In addition to adipogenic and osteogenic differentiation, these adipose-derived stem cells displayed skeletal myogenic potential when co-cultured with mouse skeletal myocytes in reduced serum conditions. Physical incorporation of stem cells into multinucleated skeletal myotubes was determined by genetic lineage tracing, whereas human-specific antibody staining was employed to demonstrate functional contribution of the stem cells to a myogenic lineage. To investigate the effects of hypoxia, cells were maintained and differentiated at 2% O(2). In contrast with reports on bone marrow-derived stem cells, both osteogenic and adipogenic differentiation were significantly attenuated. In summary, the relative accessibility of adipose-derived mesenchymal stem cells from human donors provides opportunity for molecular investigation of mechanistic dysfunction in disease settings and may introduce new prospects for cell-based therapy.

Identification of novel pathway regulation during myogenic differentiation.

Stem cell differentiation is governed by extracellular signals that activate intracellular networks (or pathways) to drive phenotypic specification. Using a novel gene clustering strategy we determined pathway relationships from a genome-wide transcriptional dataset of skeletal myoblast differentiation. Established myogenic pathways, including cell contractility and cell-cycle arrest, were predicted with extreme statistical significance (p approximately 0). In addition, gene sets associated with angiogenesis, neuronal activity, and mRNA splicing were regulated, exposing developmental and therapeutic implications. Acquisition of transcriptional data spanning the entire differentiation time course provided context for a dynamic landscape of functional pathway regulation. This novel perspective on myogenic cell differentiation revealed previously unrecognized patterns of regulation. We predict that similar analyses will facilitate ongoing efforts to define molecular mechanisms in other stem cell and developmental paradigms. Finally, by combining an iterative process of analysis with supplementation of novel pathways, this application may evolve into a powerful discovery tool.

Contribution of human bone marrow stem cells to individual skeletal myotubes followed by myogenic gene activation.

Much attention is focused on characterizing the contribution of bone marrow (BM)-derived cells to regenerating skeletal muscle, fuelled by hopes for stem cell-mediated therapy of muscle degenerative diseases. Though physical integration of BM stem cells has been well documented, little evidence of functional commitment to myotube phenotype has been reported. This is due to the innate difficulty in distinguishing gene products derived from donor versus host nuclei. Here, we demonstrate that BM-derived stem cells contribute via gene expression following incorporation to skeletal myotubes. By co-culturing human BM-derived mesenchymal stem cells (MSC) with mouse skeletal myoblasts, physical incorporation was observed by genetic lineage tracing and species-specific immunofluorescence. We used a human-specific antibody against the intermediate filament protein nestin, a marker of regenerating skeletal muscle, to identify functional contribution of MSC to myotube formation. Although nestin expression was never detected in MSC, human-specific expression was detected in myotubes that also contained MSC-derived nuclei. This induction of gene expression following myotube integration suggests that bone marrow-derived stem cells can reprogram and functionally contribute to the muscle cell phenotype. We propose that this model of myogenic commitment may provide the means to further characterize functional reprogramming of MSC to skeletal muscle.

Thrombin induces suppressor of cytokine signaling 3 expression in brain microglia via protein kinase Cdelta activation.

Microglia (brain macrophages) are activated upon brain damage. In this study, we demonstrated that thrombin, a pro-inflammatory stimulator of microglia, induced expression of suppressors of cytokine signaling (SOCS) in microglia. RT-PCR analysis and Northern blot analysis showed that thrombin induced SOCS3 mRNA expression. Further experiments indicated SOCS3 expression was not affected by cycloheximide, indicating thrombin directly stimulated SOCS3 transcript expression without de novo protein synthesis. We investigated whether PKCdelta played a role in thrombin-stimulated SOCS3 expression. We found that thrombin activated PKCdelta, and the specific inhibitor of PKCdelta, rottlerin, significantly suppressed thrombin-stimulated SOCS3 expression. In thrombin-pretreated cells, microglial activation-induced by another inflammatory stimulator, lipopolysaccharide, was attenuated compared to that in non-pretreated cells. These results suggest thrombin induce not only proinflammatory mediators but also negative feedback regulators of inflammation, SOCS, which prevent prolonged inflammatory reactions in microglia.