Identification of potent pan-ephrin receptor kinase inhibitors using DNA-encoded chemistry technology.

EPH receptors (EPHs), the largest family of tyrosine kinases, phosphorylate downstream substrates upon binding of ephrin cell surface-associated ligands. In a large cohort of endometriotic lesions from individuals with endometriosis, we found that EPHA2 and EPHA4 expressions are increased in endometriotic lesions relative to normal eutopic endometrium. Because signaling through EPHs is associated with increased cell migration and invasion, we hypothesized that chemical inhibition of EPHA2/4 could have therapeutic value. We screened DNA-encoded chemical libraries (DECL) to rapidly identify EPHA2/4 kinase inhibitors. Hit compound, CDD-2693, exhibited picomolar/nanomolar kinase activity against EPHA2 (Ki: 4.0 nM) and EPHA4 (Ki: 0.81 nM). Kinome profiling revealed that CDD-2693 bound to most EPH family and SRC family kinases. Using NanoBRET target engagement assays, CDD-2693 had nanomolar activity versus EPHA2 (IC50: 461 nM) and EPHA4 (IC50: 40 nM) but was a micromolar inhibitor of SRC, YES, and FGR. Chemical optimization produced CDD-3167, having picomolar biochemical activity toward EPHA2 (Ki: 0.13 nM) and EPHA4 (Ki: 0.38 nM) with excellent cell-based potency EPHA2 (IC50: 8.0 nM) and EPHA4 (IC50: 2.3 nM). Moreover, CDD-3167 maintained superior off-target cellular selectivity. In 12Z endometriotic epithelial cells, CDD-2693 and CDD-3167 significantly decreased EFNA5 (ligand) induced phosphorylation of EPHA2/4, decreased 12Z cell viability, and decreased IL-1ß-mediated expression of prostaglandin synthase 2 (PTGS2). CDD-2693 and CDD-3167 decreased expansion of primary endometrial epithelial organoids from patients with endometriosis and decreased Ewing's sarcoma viability. Thus, using DECL, we identified potent pan-EPH inhibitors that show specificity and activity in cellular models of endometriosis and cancer.

Ultrahigh Resolution Lipid Mass Spectrometry Imaging of High-Grade Serous Ovarian Cancer Mouse Models.

No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights on how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and a triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide a direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.

Experimental investigation and multi-objective optimization of eco-friendly near-dry electrical discharge machining of shape memory alloy using Cu/SiC/Gr composite electrode.

The near-dry electrical discharge machining processes have been conducted using air-mist or gas mist as a dielectric fluid to minimize the environmental impacts. In this article, near-dry electrical discharge machining (NDEDM) experiments have been performed to improve machining performance using an oxygen-mist dielectric fluid, a copper composite electrode, and Cu-Al-Be polycrystalline shape memory alloy (SMA) work materials. The copper composite electrode is made up of 12 wt% silicon carbide and 9 wt% graphite particles. The oxygen-mist pressure (Op), pulse on time (Ton), spark current (Ip), gap voltage (Gv), and flow rate of mixed water (Fr) were used as process parameters, and the material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR) were used as performance characteristics. The global optimal alternative solution has been predicted by the PROMETHEE-II (Preference Ranking Organization METhod for Enrichment Evaluations-II) optimization technique. The best combinations of process parameters have been used to examine the microstructure of composite tools and SMA-machined surfaces by scanning electron microscopy (SEM) analysis. The best global optimum settings (oP: 9 bar, Ip: 60 µs, Ip: 12 A, Gv: 40 V, and Fr: 12 ml/min) are predicted to attain optimum machining performance (MRR: 39.049 g/min, TWR: 1.586 g/min, and SR: 1.78 µm). The tool wear rate of the NDEDM process has been significantly reduced by the copper composite electrode due to increasing microhardness, wear resistance, and melting point. When compared to the pure copper electrode tool, the MRR of NDEDM is improved to 21.91%, while the TWR and SR are reduced to 46.66% and 35.02%, respectively.

Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer.

Ovarian cancer (OC) is one of the deadliest cancers affecting the female reproductive system. It may present little or no symptoms at the early stages and typically unspecific symptoms at later stages. High-grade serous ovarian cancer (HGSC) is the subtype responsible for most ovarian cancer deaths. However, very little is known about the metabolic course of this disease, particularly in its early stages. In this longitudinal study, we examined the temporal course of serum lipidome changes using a robust HGSC mouse model and machine learning data analysis. Early progression of HGSC was marked by increased levels of phosphatidylcholines and phosphatidylethanolamines. In contrast, later stages featured more diverse lipid alterations, including fatty acids and their derivatives, triglycerides, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, and phosphatidylinositols. These alterations underscored unique perturbations in cell membrane stability, proliferation, and survival during cancer development and progression, offering potential targets for early detection and prognosis of human ovarian cancer.

Discovery of Highly Potent and BMPR2-Selective Kinase Inhibitors Using DNA-Encoded Chemical Library Screening.

The discovery of monokinase-selective inhibitors for patients is challenging because the 500+ kinases encoded by the human genome share highly conserved catalytic domains. Until now, no selective inhibitors unique for a single transforming growth factor ß (TGFß) family transmembrane receptor kinase, including bone morphogenetic protein receptor type 2 (BMPR2), have been reported. This dearth of receptor-specific kinase inhibitors hinders therapeutic options for skeletal defects and cancer as a result of an overactivated BMP signaling pathway. By screening 4.17 billion "unbiased" and "kinase-biased" DNA-encoded chemical library molecules, we identified hits CDD-1115 and CDD-1431, respectively, that were low-nanomolar selective kinase inhibitors of BMPR2. Structure-activity relationship studies addressed metabolic lability and high-molecular-weight issues, resulting in potent and BMPR2-selective inhibitor analogs CDD-1281 (IC50 = 1.2 nM) and CDD-1653 (IC50 = 2.8 nM), respectively. Our work demonstrates that DNA-encoded chemistry technology (DEC-Tec) is reliable for identifying novel first-in-class, highly potent, and selective kinase inhibitors.

Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer.

Ovarian cancer (OC) is one of the deadliest cancers affecting the female reproductive system. It may present little or no symptoms at the early stages, and typically unspecific symptoms at later stages. High-grade serous ovarian cancer (HGSC) is the subtype responsible for most ovarian cancer deaths. However, very little is known about the metabolic course of this disease, particularly in its early stages. In this longitudinal study, we examined the temporal course of serum lipidome changes using a robust HGSC mouse model and machine learning data analysis. Early progression of HGSC was marked by increased levels of phosphatidylcholines and phosphatidylethanolamines. In contrast, later stages featured more diverse lipids alterations, including fatty acids and their derivatives, triglycerides, ceramides, hexosylceramides, sphingomyelins, lysophosphatidylcholines, and phosphatidylinositols. These alterations underscored unique perturbations in cell membrane stability, proliferation, and survival during cancer development and progression, offering potential targets for early detection and prognosis of human ovarian cancer. Teaser: Time-resolved lipidome remodeling in an ovarian cancer model is studied through lipidomics and machine learning.

Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models.

No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering that little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights into how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSOC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes were compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.

Homogeneous and Functional Group Tolerant Ring-Closing Metathesis for DNA-Encoded Chemical Libraries.

Reaction heterogeneity, poor pH control, and catalyst decomposition in the ring-closing metathesis (RCM) of DNA-chemical conjugates lead to poor yields of the cyclized products. Herein we address these issues with a RCM reaction system that includes a novel aqueous solvent combination to enable reaction homogeneity, an acidic buffer system which masks traditionally problematic functional groups, and a decomposition-resistant catalyst which maximizes conversion to the cyclized product. Additionally, we provide a systematic study of the substrate scope of the on-DNA RCM reaction, a demonstration of its applicability to a single-substrate DNA-encoded chemical library that includes sequencing analysis, and the first successful stapling of an unprotected on-DNA [i, i+4] peptide.

The genomic landscape of estrogen receptor α binding sites in mouse mammary gland.

Estrogen receptor α (ERα) is the major driving transcription factor in the mammary gland development as well as breast cancer initiation and progression. However, the genomic landscape of ERα binding sites in the normal mouse mammary gland has not been completely elucidated. Here, we mapped genome-wide ERα binding events by chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) in the mouse mammary gland in response to estradiol. We identified 6237 high confidence ERα binding sites in two biological replicates and showed that many of these were located at distal enhancer regions. Furthermore, we discovered 3686 unique genes in the mouse genome that recruit ER in response to estradiol. Interrogation of ER-DNA binding sites in ER-positive luminal epithelial cells showed that the ERE, PAX2, SF1, and AP1 motifs were highly enriched at distal enhancer regions. In addition, comprehensive transcriptome analysis by RNA-seq revealed that 493 genes are differentially regulated by acute treatment with estradiol in the mouse mammary gland in vivo. Through integration of RNA-seq and ERα ChIP-seq data, we uncovered a novel ERα targetome in mouse mammary epithelial cells. Taken together, our study has identified the genomic landscape of ERα binding events in mouse mammary epithelial cells. Furthermore, our study also highlights the cis-regulatory elements and cofactors that are involved in estrogen signaling and may contribute to ductal elongation in the normal mouse mammary gland.

Reprogramming of the estrogen responsive transcriptome contributes to tamoxifen-dependent protection against tumorigenesis in the p53 null mammary epithelial cells.

The tumor suppressor gene p53 is frequently mutated in human breast cancer and is a marker for poor prognosis and resistance to chemotherapy. Transplantation of p53 null mouse mammary epithelium into syngeneic wild-type mice leads to normal mammary gland development followed by spontaneous mammary tumors that recapitulate many of the phenotypic, molecular and genetic features of human breast cancer. Transient exposure of p53 null mice to the anti-estrogen, tamoxifen leads to sustained and robust protection against tumor development. However the mechanism underlying this anti-tumor activity remains poorly understood. Here we demonstrate that transient exposure to tamoxifen leads to a reduction in mammary ductal side-branching and epithelial cell proliferation after tamoxifen withdrawal. Global gene expression analysis showed that transient tamoxifen exposure leads to persistent changes in the expression of a subset of estrogen regulated gene signatures in mammary epithelial cells (MECs). Among these was the protein tyrosine phosphatase, non-receptor type 5 (Ptpn5). We show that Ptpn5 is a novel tamoxifen regulated target gene which is upregulated in MECs after transient tamoxifen exposure and displays tumor suppressor activity in human breast cancer cells. Further, PTPN5 expression is strongly associated with good clinical outcome in tamoxifen treated human breast cancer patients suggesting that PTPN5 may represent a novel biomarker of tamoxifen response in human breast cancer.

Stimulatory effect of insulin on theca-interstitial cell proliferation and cell cycle regulatory proteins through MTORC1 dependent pathway.

The present study examined the effect of insulin-mediated activation of the mammalian target of rapamycin complex 1 (MTORC1) signaling network on the proliferation of primary culture of theca-interstitial (T-I) cells. Our results show that insulin treatment increased proliferation of the T-I cells through the MTORC1-dependent signaling pathway by increasing cell cycle regulatory proteins. Inhibition of ERK1/2 signaling caused partial reduction of insulin-induced phosphorylation of RPS6KB1 and RPS6 whereas inhibition of PI3-kinase signaling completely blocked the insulin response. Pharmacological inhibition of MTORC1 with rapamycin abrogated the insulin-induced phosphorylation of EIF4EBP1, RPS6KB1 and its downstream effector, RPS6. These results were further confirmed by demonstrating that knockdown of Mtor using siRNA reduced the insulin-stimulated MTORC1 signaling. Furthermore, insulin-stimulated T-I cell proliferation and the expression of cell cycle regulatory proteins CDK4, CCND3 and PCNA were also blocked by rapamycin. Taken together, the present studies show that insulin stimulates cell proliferation and cell cycle regulatory proteins in T-I cells via activation of the MTORC1 signaling pathway.

Metformin: direct inhibition of rat ovarian theca-interstitial cell proliferation.

OBJECTIVE: To determine whether metformin has direct effects on ovarian theca-interstitial (T-I) cell proliferation through activation of adenosine monophosphate-activated protein kinase (AMPK). DESIGN: In vitro experimental study. SETTING: Academic medical center laboratory. ANIMAL(S): Immature Sprague-Dawley female rats. INTERVENTION(S): Ovarian T-I cells were isolated, purified, and cultured in the absence (control) or presence of insulin (1 µg/mL) with or without metformin or other activators/inhibitors of AMPK (AICAR, compound C). MAIN OUTCOME MEASURE(S): Proliferation assessed by determination of expression levels of proteins involved in cell cycle progression, cyclin D3, and cyclin-dependent kinase 4 (CDK4) with Western blot analysis, and determination of DNA synthesis with bromodeoxyuridine (BrdU) incorporation assay; activation of AMPK, Erk1/2, and S6K1 determined by Western blot analysis with the use of antibodies specific for the phosphorylated (activated) forms. RESULT(S): Metformin inhibited insulin-induced ovarian T-I cell proliferation and the up-regulation of the cell cycle regulatory proteins, cyclin D3 and CDK4. Metformin independently activated AMPK in a dose-dependent manner. Treatment with metformin inhibited insulin-induced activation of Erk1/2 and S6K1. This effect was reversed with the addition of compound C, a known AMPK inhibitor. CONCLUSION(S): Metformin directly inhibits proliferation of ovarian T-I cells via an AMPK-dependent mechanism. These findings further validate the potential benefits of metformin in the treatment of conditions associated with hyperinsulinemia and excessive growth of ovarian T-I cells (such as polycystic ovary syndrome).

Human chorionic gonadotropin stimulates theca-interstitial cell proliferation and cell cycle regulatory proteins by a cAMP-dependent activation of AKT/mTORC1 signaling pathway.

In addition to playing a cardinal role in androgen production, LH also regulates growth and proliferation of theca-interstitial (T-I) cells. Here, we show for the first time that LH/human chorionic gonadotropin (hCG) regulates T-I cell proliferation via the mammalian target of rapamycin complex 1 (mTORC1) signaling network. LH/hCG treatment showed a time-dependent stimulation of T-I cell proliferation and phosphorylation of protein kinase B (AKT), ERK1/2, and ribosomal protein (rp)S6 kinase 1 (S6K1), and its downstream effector, rpS6. Pharmacological inhibition of ERK1/2 signaling did not block the hCG-induced phosphorylation of tuberin, the upstream regulator of mTORC1 or S6K1, the downstream target of mTORC1. However, inhibition of AKT signaling completely blocked the hCG response. Furthermore, the AKT-specific inhibitor abolished forskolin (FSK)-stimulated phosphorylation of AKT, tuberin, S6K1, and rpS6. Human CG and FSK-mediated phosphorylation of AKT and downstream targets of mTORC1 were attenuated by inhibition of adenylyl cyclase. Pharmacologic targeting of mTORC1 with rapamycin also abrogated hCG or FSK-induced phosphorylation of S6K1, rpS6, and eukaryotic initiation factor 4E binding protein 1. In addition, hCG or FSK-mediated up-regulation of the cell cycle regulatory proteins cyclin-dependent kinase 4, cyclin D3, and proliferating cell nuclear antigen was blocked by rapamycin. These results were further confirmed by demonstrating that knockdown of mTORC1 using small interfering RNA abolished hCG-mediated increases in cell proliferation and the expression of cyclin D3 and proliferating cell nuclear antigen. Taken together, the present studies show a novel intracellular signaling pathway for T-I cell proliferation involving LH/hCG-mediated activation of the AKT/mTORC1 signaling cascade.