Epithelial STAT6 O-GlcNAcylation drives a concerted anti-helminth alarmin response dependent on tuft cell hyperplasia and Gasdermin C.

The epithelium is an integral component of mucosal barrier and host immunity. Following helminth infection, the intestinal epithelial cells secrete "alarmin" cytokines, such as interleukin-25 (IL-25) and IL-33, to initiate the type 2 immune responses for helminth expulsion and tolerance. However, it is unknown how helminth infection and the resulting cytokine milieu drive epithelial remodeling and orchestrate alarmin secretion. Here, we report that epithelial O-linked N-Acetylglucosamine (O-GlcNAc) protein modification was induced upon helminth infections. By modifying and activating the transcription factor STAT6, O-GlcNAc transferase promoted the transcription of lineage-defining Pou2f3 in tuft cell differentiation and IL-25 production. Meanwhile, STAT6 O-GlcNAcylation activated the expression of Gsdmc family genes. The membrane pore formed by GSDMC facilitated the unconventional secretion of IL-33. GSDMC-mediated IL-33 secretion was indispensable for effective anti-helminth immunity and contributed to induced intestinal inflammation. Protein O-GlcNAcylation can be harnessed for future treatment of type 2 inflammation-associated human diseases.

Can molecular dynamics simulations improve predictions of protein-ligand binding affinity with machine learning?

Binding affinity prediction largely determines the discovery efficiency of lead compounds in drug discovery. Recently, machine learning (ML)-based approaches have attracted much attention in hopes of enhancing the predictive performance of traditional physics-based approaches. In this study, we evaluated the impact of structural dynamic information on the binding affinity prediction by comparing the models trained on different dimensional descriptors, using three targets (i.e. JAK1, TAF1-BD2 and DDR1) and their corresponding ligands as the examples. Here, 2D descriptors are traditional ECFP4 fingerprints, 3D descriptors are the energy terms of the Smina and NNscore scoring functions and 4D descriptors contain the structural dynamic information derived from the trajectories based on molecular dynamics (MD) simulations. We systematically investigate the MD-refined binding affinity prediction performance of three classical ML algorithms (i.e. RF, SVR and XGB) as well as two common virtual screening methods, namely Glide docking and MM/PBSA. The outcomes of the ML models built using various dimensional descriptors and their combinations reveal that the MD refinement with the optimized protocol can improve the predictive performance on the TAF1-BD2 target with considerable structural flexibility, but not for the less flexible JAK1 and DDR1 targets, when taking docking poses as the initial structure instead of the crystal structures. The results highlight the importance of the initial structures to the final performance of the model through conformational analysis on the three targets with different flexibility.

Supramolecular prodrug of SN38 based on endogenous albumin and SN38 prodrug modified with semaglutide side chain to improve the tumor distribution.

To improve the biodistribution of the drug in the tumor, a supramolecular prodrug of SN38 was fabricated in situ between endogenous albumin and SN38 prodrug modified with semaglutide side chain. Firstly, SN38 was conjugated with semaglutide side chain and octadecanedioic acid via glycine linkers to obtain SI-Gly-SN38 and OA-Gly-SN38 prodrugs, respectively. Both SI-Gly-SN38 and OA-Gly-SN38 exhibited excellent stability in PBS for over 24 h. Due to the strong binding affinity of the semaglutide side chain with albumin, the plasma half-life of SI-Gly-SN38 was 2.7 times higher than that of OA-Gly-SN38. Furthermore, with addition of HSA, the fluorescence intensity of SI-Gly-SN38 was 4 times higher than that of OA-Gly-SN38, confirming its strong binding capability with HSA. MTT assay showed that the cytotoxicity of SI-Gly-SN38 and OA-Gly-SN38 was higher than that of Irinotecan. Even incubated with HSA, the SI-Gly-SN38 and OA-Gly-SN38 still maintained high cytotoxicity, indicating minimal influence of HSA on their cytotoxicity. In vivo pharmacokinetic studies demonstrated that the circulation half-life of SI-Gly-SN38 was twice that of OA-Gly-SN38. SI-Gly-SN38 exhibited significantly reduced accumulation in the lungs, being only 0.23 times that of OA-Gly-SN38. The release of free SN38 in the lungs from SI-Gly-SN38 was only 0.4 times that from OA-Gly-SN38 and Irinotecan. The SI-Gly-SN38 showed the highest accumulation in tumors. The tumor inhibition rate of SI-Gly-SN38 was 6.42% higher than that of OA-Gly-SN38, and 8.67% higher than that of Irinotecan, respectively. These results indicate that the supramolecular prodrug delivery system can be constructed between SI-Gly-SN38 and endogenous albumin, which improves drug biodistribution in vivo, enhances tumor accumulation, and plays a crucial role in tumor growth inhibition.

Design, synthesis, and biological evaluation of cathepsin B cleavage albumin-binding SN38 prodrug in breast cancer.

Here, we introduce a novel and effective approach utilizing a cathepsin B cleavage albumin-binding SN38 prodrug specifically designed for the treatment of metastatic breast cancer. Termed Mal-va-mac-SN38, our prodrug exhibits a unique ability to rapidly and covalently bind with endogenous albumin, resulting in the formation of HSA-va-mac-SN38. This prodrug demonstrates exceptional stability in human plasma. Importantly, HSA-va-mac-SN38 showcases an impressive enhancement in cellular uptake by 4T1 breast cancer cells, primarily facilitated through caveolin-mediated endocytosis. Intriguingly, the release of the active SN38, is triggered by the enzymatic activity of cathepsin B within the lysosomal environment. In vivo studies employing a lung metastasis 4T1 breast cancer model underscore the potency of HSA-va-mac-SN38. Histological immunohistochemical analyses further illuminate the multifaceted impact of our prodrug, showcasing elevated levels of apoptosis, downregulated expression of matrix metalloproteinases, and inhibition of angiogenesis, all critical factors contributing to the anti-metastatic effect observed. Biodistribution studies elucidate the capacity of Mal-va-mac-SN38 to augment tumor accumulation through covalent binding to serum albumin, presenting a potential avenue for targeted therapeutic interventions. Collectively, our findings propose a promising therapeutic avenue for metastatic breast cancer, through the utilization of a cathepsin B-cleavable albumin-binding prodrug.

The ZSWIM8 ubiquitin ligase regulates neurodevelopment by guarding the protein quality of intrinsically disordered Dab1.

Protein quality control (PQC) is essential for maintaining protein homeostasis and guarding the accuracy of neurodevelopment. Previously, we found that a conserved EBAX-type CRL regulates the protein quality of SAX-3/ROBO guidance receptors in Caenorhabditis elegans. Here, we report that ZSWIM8, the mammalian homolog of EBAX-1, is essential for developmental stability of mammalian brains. Conditional deletion of Zswim8 in the embryonic nervous system causes global cellular stress, partial perinatal lethality and defective migration of neural progenitor cells. CRISPR-mediated knockout of ZSWIM8 impairs spine formation and synaptogenesis in hippocampal neurons. Mechanistic studies reveal that ZSWIM8 controls protein quality of Disabled 1 (Dab1), a key signal molecule for brain development, thus protecting the signaling strength of Dab1. As a ubiquitin ligase enriched with intrinsically disordered regions (IDRs), ZSWIM8 specifically recognizes IDRs of Dab1 through a "disorder targets misorder" mechanism and eliminates misfolded Dab1 that cannot be properly phosphorylated. Adult survivors of ZSWIM8 CKO show permanent hippocampal abnormality and display severely impaired learning and memory behaviors. Altogether, our results demonstrate that ZSWIM8-mediated PQC is critical for the stability of mammalian brain development.

Plant-Derived Caffeic Acid and Its Derivatives: An Overview of Their NMR Data and Biosynthetic Pathways.

In recent years, caffeic acid and its derivatives have received increasing attention due to their obvious physiological activities and wide distribution in nature. In this paper, to clarify the status of research on plant-derived caffeic acid and its derivatives, nuclear magnetic resonance spectroscopy data and possible biosynthetic pathways of these compounds were collected from scientific databases (SciFinder, PubMed and China Knowledge). According to different types of substituents, 17 caffeic acid and its derivatives can be divided into the following classes: caffeoyl ester derivatives, caffeyltartaric acid, caffeic acid amide derivatives, caffeoyl shikimic acid, caffeoyl quinic acid, caffeoyl danshens and caffeoyl glycoside. Generalization of their 13C-NMR and 1H-NMR data revealed that acylation with caffeic acid to form esters involves acylation shifts, which increase the chemical shift values of the corresponding carbons and decrease the chemical shift values of the corresponding carbons of caffeoyl. Once the hydroxyl group is ester, the hydrogen signal connected to the same carbon shifts to the low field (1.1~1.6). The biosynthetic pathways were summarized, and it was found that caffeic acid and its derivatives are first synthesized in plants through the shikimic acid pathway, in which phenylalanine is deaminated to cinnamic acid and then transformed into caffeic acid and its derivatives. The purpose of this review is to provide a reference for further research on the rapid structural identification and biofabrication of caffeic acid and its derivatives.

PDI-Based Organic Small Molecule Regulated by Inter/Intramolecular Interactions for Efficient Solar Vapor Generation.

Organic small molecules with processing feasibility, structural diversity, and fine-tuned properties have the potential applications in solar vapor generation. However, the common defects of narrow solar absorption, low photothermal conversion efficiency, and photobleaching result in limited materials available and unsatisfactory evaporation performance. Herein, the perylene diimide (PDI) derivatives are exploited as stable sunlight absorbers for solar vapor generation. Particularly, the N,N'-bis(3,4,5-trimethoxyphenyl)-3,4,9,10-perylenetetracarboxylic diimide (PDI-DTMA) is well-designed with donor-acceptor-donor configuration based on plane rigid PDI core. The efficient photothermal conversion is enabled through strong intermolecular π-π stacking and intramolecular charge transfer, as revealed by experimental demonstration and theoretical calculation. The PDI-DTMA with a narrow band gap of 1.17 eV exhibits expanded absorption spectrum and enhanced nonradiative transition capability. The 3D hybrid hydrogels (PPHs) combining PDI-DTMA and polyvinyl alcohol are constructed. With the synergistic effect of solar-to-heat conversion, thermal localization management, water activation, and unobstructed water transmission of PPHs, the high water evaporation rates can reach 3.61-10.07 kg m-2 h-1 under one sun. The hydrogels also possess great potential in seawater desalination and sewage treatment. Overall, this work provides valuable insights into the design of photothermal organic small molecules and demonstrates their potentials in solar water evaporation.

A deep learning based method for automatic analysis of high-throughput droplet digital PCR images.

Droplet digital PCR (ddPCR) is a technique for absolute quantification of nucleic acid molecules and is widely used in biomedical research and clinical diagnosis. ddPCR partitions the reaction solution containing target molecules into a large number of independent microdroplets for amplification and performs quantitative analysis of target molecules by calculating the proportion of positive droplets by the principle of Poisson distribution. Accurate recognition of positive droplets in ddPCR images is of great importance to guarantee the accuracy of target nucleic acid quantitative analysis. However, hand-designed operators are sensitive to interference and have disadvantages such as low contrast, uneven illumination, low sample copy number, and noise, and their accuracy and robustness still need to be improved. Herein, we developed a deep learning-based high-throughput ddPCR droplet detection framework for robust and accurate ddPCR image analysis, and the experimental results show that our method achieves excellent performance in the recognition of positive droplets (99.71%) within a limited time. By combining the Hough transform and a convolutional neural network (CNN), our novel method can automatically filter out invalid droplets that are difficult to be identified by local or global encoding methods and realize high-precision localization and classification of droplets in ddPCR images under variable exposure, contrast, and uneven illumination conditions without the need for image pre-processing and normalization processes.

Atomistic origin of kinetics in hydrated aluminosilicate gels upon precipitation.

Calcium-alumino-silicate-hydrate (CaO-Al2O3-SiO2-H2O, or C-A-S-H) gel, which is the binding phase of cement-based materials, greatly influences concrete mechanical properties and durability. However, the atomic-scale kinetics of the aluminosilicate network condensation remains puzzling. Here, based on reactive molecular dynamics simulations of C-A-S-H systems formation with varying Al/Ca molar ratios, we study the kinetic mechanism of the hydrated aluminosilicate gels upon precipitation. We show that the condensation activation energy decreases with the Al/Ca molar ratio, which suggests that the concentration of the Al polytopes has a great effect on controlling the kinetics of the gelation reaction. Significantly, we demonstrate that 5-fold Al atoms are mainly forming at high Al/Ca molar ratios since there are insufficient hydrogen cations or extra calcium cations to compensate the negatively charged Al polytopes at high Al/Ca molar ratios during accelerated aging.

A Novel Motor Structure with Extended Particle Swarm Optimization for Space Robot Control.

This paper studies motor structures and optimization methods for space robots, proposing an optimized stepped rotor bearingless switched reluctance motor (BLSRM) to solve the poor self-starting ability and significant torque fluctuation issues in traditional BLSRMs. Firstly, the advantages and disadvantages of the 12/14 hybrid stator pole type BLSRM were analyzed, and a stepped rotor BLSRM structure was designed. Secondly, the particle swarm optimization (PSO) algorithm was improved and combined with finite element analysis for motor structure parameter optimization. Subsequently, a performance analysis of the original and new motors was conducted using finite element analysis software, and the results showed that the stepped rotor BLSRM had an improved self-starting ability and significantly reduced torque fluctuation, verifying the effectiveness of the proposed motor structure and optimization method.

Suppression of Macrophage Activation by Sodium Danshensu via HIF-1α/STAT3/NLRP3 Pathway Ameliorated Collagen-Induced Arthritis in Mice.

It is still a clinical challenge to sustain the remission of rheumatoid arthritis (RA); thus, identifying more effective and safer agents for RA treatment remains an urgent demand. We investigated the anti-arthritic activity and potential mechanism of action of sodium Danshensu (SDSS), a structurally representative water-soluble derivative of Danshen, on collagen-induced arthritis (CIA) mice. Our results showed that paw edema, synovium hyperplasia, bone destruction, and the serum levels of both IL-1ß and IL-6 were ameliorated by SDSS (40 mg/kg·d) in CIA mice. In addition, there was no difference between SDSS and methotrexate (MTX, 2 mg/kg·3d) treatment in the above indicators. Further mechanism studies illustrated that SDSS inhibited IL-1ß secretion by downregulating the HIF-1α/STAT3/NLRP3 pathway in macrophages. On the other hand, HIF-1α accumulation and HIF-1α/STAT3/NLRP3 pathway activation by IOX4 stimulation reduced the therapeutic effect of SDSS. These findings demonstrate that SDSS displays anti-arthritic activity in CIA mice and prevents proinflammatory cytokines secretion in macrophages by suppressing the HIF-1α/STAT3/NLRP3 pathway.

Two Stable Cd-MOFs as Dual-Functional Materials with Luminescent Sensing of Antibiotics and Proton Conduction.

Construction and investigation of dual-functional metal-organic frameworks (MOFs) with luminescent sensing and proton conduction provide widespread applications in clean energy and environmental monitoring fields. By selecting a phosphonic acid ligand 4-pyridyl-CH2N(CH2PO3H2)2 (H4L) and coligand 2,2'-biimidazole (H2biim), two cadmium-based MOFs [Cd1.5(HL)(H2biim)0.5] (1) and (H4biim)0.5·[Cd2(L)(H2biim)Cl] (2) with different structures and properties have been hydrothermally synthesized by controlling reaction temperature. Based on the excellent thermal and chemical stabilities, and good luminescent stabilities in water solution, 1 and 2 can serve as luminescent sensors of chloramphenicol (CAP) with different quenching constant (KSV) values and detection limits (LODs) in water, simulated environmental system, and real fish water system. Meanwhile, different sensing effects and possible sensing mechanisms are analyzed in detail. Moreover, 1 and 2 can also serve as good proton-conducting materials. The proton conductivities can reach up to 1.41 × 10-4 S cm-1 for 1 and 1.02 × 10-3 S cm-1 for 2 at 368 K and 95% relative humidity (RH). Among them, 2 shows better luminescent sensing and proton conduction performance than 1, which indicates that different crystal structures have a great impact on the properties of MOFs. Through the discussion of the relationship between structures and properties in detail, the possible reasons for the differences in properties are obtained, which can provide theoretical guidance for the rational design of this kind of dual-functional MOFs in the future.

Organic Compound Synthetic Accessibility Prediction Based on the Graph Attention Mechanism.

Accurate estimation of the synthetic accessibility of small molecules is needed in many phases of drug discovery. Several expert-crafted scoring methods and descriptor-based quantitative structure-activity relationship (QSAR) models have been developed for synthetic accessibility assessment, but their practical applications in drug discovery are still quite limited because of relatively low prediction accuracy and poor model interpretability. In this study, we proposed a data-driven interpretable prediction framework called GASA (Graph Attention-based assessment of Synthetic Accessibility) to evaluate the synthetic accessibility of small molecules by distinguishing compounds to be easy- (ES) or hard-to-synthesize (HS). GASA is a graph neural network (GNN) architecture that makes self-feature deduction by applying an attention mechanism to automatically capture the most important structural features related to synthetic accessibility. The sampling around the hypothetical classification boundary was used to improve the ability of GASA to distinguish structurally similar molecules. GASA was extensively evaluated and compared with two descriptor-based machine learning methods (random forest, RF; eXtreme gradient boosting, XGBoost) and four existing scores (SYBA: SYnthetic Bayesian Accessibility; SCScore: Synthetic Complexity score; RAscore: Retrosynthetic Accessibility score; SAscore: Synthetic Accessibility score). Our analysis demonstrates that GASA achieved remarkable performance in distinguishing similar molecules compared with other methods and had a broader applicability domain. In addition, we show how GASA learns the important features that affect molecular synthetic accessibility by assigning attention weights to different atoms. An online prediction service for GASA was offered at http://cadd.zju.edu.cn/gasa/.

Novel difluoromethyl-containing 1-((4-methoxy-3-(piperazin-1-yl)phenyl)sulfonyl)-1H-indole scaffold as potent 5-HT6R antagonists: Design, synthesis, biological evaluation, and early in vivo cognition-enhancing studies.

Herein, a series of novel 1-((4-methoxy-3-(piperazin-1-yl)phenyl)sulfonyl)- 1H-indole derivatives were designed and synthesized via hybridization strategy of idalopirdine and SB-271046. The optimal compound C14 (Ki = 0.085 nM), with difluoromethyl on C3 position on indole scaffold, increased the affinity for the 5-HT6R up to 10-folds than idalopirdine (Ki = 0.83 nM). Additionally, C14 had good pharmacokinetic properties and in vitro metabolic properties. Finally, C14 could efficiently reverse the scopolamine induced emotional memory deficits in novel object recognition assay in rats. Thus, we propose C14 might be considered as a new cognition-enhancing agent and the further studies are now underway in our laboratory.

Novel difluoromethylated 1-(phenylsulfonyl)-4-(piperazin-1-yl)-1H-indole derivatives as potent 5-HT6 receptor antagonist with AMDE-improving properties: Design, synthesis, and biological evaluation.

Serotonin type 6 receptor (5-HT6R) has been considered as a particularly promising target for treating cognitive deficits due to the positive effects of its antagonists in a wide range of memory impairment paradigms. In this study, we designed, synthesized, and evaluated a series of 3-(difluoromethyl)-1-(phenylsulfonyl)-4-(piperazin-1-yl)-1H-indole derivatives as potent 5-HT6R antagonists. Structure-activity relationship study led to the discovery of five compounds (6a, 6m, 6n, 6p and 6q) with potent binding affinity at 5-HT6R. In in vivo pharmacokinetic studies in rats, 6p showed 30-folds higher AUC (267 ng·h/mL) and better bioavailability (34.39 %) than those of 6a (9.37 ng·h/mL and 5.95 %, respectively) by using difluoromethyl group replacing a methyl group. Besides, 6p showed good brain penetration with Cb/Cp ratio ∼6. Based on the pharmacological characteristics and favorable pharmacokinetic properties, 6p was further chosen to evaluate cognition-enhancing property in the preliminary in vivo models. It is identified that 6p not only prevented scopolamine-induced learning deficits in the novel object recognition test but also rescued the recognition barrier caused by scopolamine. Finally, the combination of 6p and donepezil produces synergistic effects on increasing the acetylcholine levels in the intracerebral hippocampus. In light of these findings, we propose 6p as a potential 5-HT6R antagonist for treatment of AD.

Structural view on the role of the TRD loop in regulating DNMT3A activity: a molecular dynamics study.

DNA methyltransferase 3A (DNMT3A) has been regarded as a potential epigenetic target for the development of cancer therapeutics. A number of DNMT3A inhibitors have been reported, but most of them do not have good potency, high selectivity and/or low cytotoxicity. It has been suggested that a non-conserved region around the target recognition domain (TRD) loop is implicated in the DNMT3A activity under the allosteric regulation of the ATRX-DNMT3-DNMT3L (ADD) domain, but the molecular mechanism of the regulation of the TRD loop on the DNMT3A activity needs to be elucidated. In this study, based on the reported crystal structures, the dynamics of the TRD loop in different multimerization with/without the bound guest molecule, namely the ADD domain or the DNA molecule, was investigated using conventional molecular dynamics (MD) and umbrella sampling simulations. The simulation results illustrate that the TRD loop exhibits relatively higher flexibility than the other components in the whole catalytic domain (CD), which could be well stabilized into different local minima through the binding with either the ADD domain or the DNA molecule by forming tight hydrogen-bond and salt-bridge networks involving distinct residues. Moreover, the movement of the TRD loop away from the catalytic loop upon activation could be triggered simply by the detachment of the ADD domain, but not necessarily induced by the ADD domain relocation on the CD. All these dynamic structural details could be a supplement to the previously reported crystal structure, which underlines the importance of the structural flexibility for the critical residues in the TRD loop, arousing more interest in the rational design of novel DNMT3A inhibitors targeting this region.

Long non-coding RNA ncRuPAR regulates gastric cancer cell proliferation and apoptosis via phosphoinositide 3-kinase/protein kinase B signaling.

Objective: To determine the effect and mechanism of the long non-coding RNA (lncRNA) ncRuPAR (non-protein coding RNA, upstream of coagulation factor II thrombin receptor [F2R]/protease-activated receptor-1 [PAR-1]) in human gastric cancer. Methods: HGC-27-ncRuPAR overexpression and MGC-803-ncRuPAR-RNAi knockdown gastric cancer cell lines were established. We assessed the effect of ncRuPAR on cell proliferation, apoptosis, migration, and invasion using Cell Counting Kit 8, flow cytometry, scratch and transwell assays, respectively. Differentially expressed genes in HGC-27-ncRuPAR overexpression and HGC-27-empty vector cell lines were identified using Affymetrix GeneChip microarray analysis. Ingenuity Pathway Analysis (IPA) of the microarray results was subsequently conducted to identify ncRuPAR-enriched pathways, followed by validation using real time-quantitative PCR (RT-qPCR). As one of the top enriched pathways, phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway was further examined by western blotting to determine its role in ncRuPAR-mediated regulation of gastric cancer pathogenesis. Results: ncRuPAR inhibited human gastric cancer cell proliferation and induced G1/S phase arrest and apoptosis, but did not affect migration or invasion in vitro. Overexpression of ncRuPAR in vitro was found to inhibit its known target PAR-1, as well as PI3K/Akt signaling. The downstream targets of PI3K/Akt, cyclin D1 was downregulated, but there was no change in expression level of B-cell lymphoma 2 (Bcl-2). Conclusions: We showed that lncRNA-ncRuPAR could inhibit tumor cell proliferation and promote apoptosis of human gastric cancer cells, potentially by inhibiting PAR-1, PI3K/Akt signaling, and cyclin D1. The results suggest a potential role for lncRNAs as key regulatory hubs in GC progression.

Comprehensive analysis of the expression, prognostic significance, and function of FAM83 family members in breast cancer.

BACKGROUND: The FAM83 family plays a key role in tumorigenesis and cancer progression. However, the role of the FAM83 family in the development of breast tumors is unclear to date. This report explores the expression, prognostic significance, and function of the FAM83 family members in breast cancer using public databases. METHODS: UALCAN database was used to explore the expression of FAM83 family members in breast cancer. Furthermore, we validated the expression of FAM83 family members in twenty pairs of breast cancer and normal tissues by RT-PCR. Kaplan-Meier plotter database was used to explore the prognostic significance of FAM83 family members in breast cancer. GeneMANIA and DAVID databases were used for functional and pathway enrichment analysis of genes co-expressed with FAM83A, FAM83D, FAM83F, and FAM83G. MEXPRESS and UALCAN databases were used to analyze the level of DNA promoter methylation of FAM83A, FAM83D, FAM83F, and FAM83G in breast cancer. TIMER database was utilized to explore the relationships between immune cell infiltration and FAM83A, FAM83D, FAM83F, and FAM83G expression. RESULTS: Among FAM83 family members, FAM83A, FAM83D, FAM83F, and FAM83G were higher expressed in breast cancer than in normal tissues. We also validated the significant high expression of FAM83A, FAM83D, FAM83F, and FAM83G mRNA in breast cancer than in normal samples. Their increased expression has an adverse prognostic effect on breast cancer patients. These genes co-expressed with FAM83A, FAM83D, FAM83F, and FAM83G might take part in cell proliferation, G2/M transition of the mitotic cell cycle, regulation of apoptosis process and other cancer-related biological processes. In addition, they were mainly enriched in the Hippo signaling pathway, Hedgehog signaling pathway, PI3K/AKT signaling pathway, and other cancer-related pathways. We also found that promoter DNA methylation might regulate the expression of FAM83A, FAM83D, FAM83F, and FAM83G mRNA in most CpG islands. At last, we found the expression of FAM83A, FAM83D, FAM83F, and FAM83G mRNA was significantly related to immune cell infiltration. CONCLUSIONS: FAM83A, FAM83D, FAM83F, and FAM83G were highly expressed in breast cancer tissues and had an adverse effect on the survival outcomes of breast cancer patients. Also, they were involved in breast cancer-related signal pathways. Therefore, they might serve as potential therapeutic targets for breast cancer clinical treatment.

Comprehensive analysis of the expression, prognostic significance, and regulation pathway of G2E3 in breast cancer.

BACKGROUND: Loss of G2-specific E3-like (G2E3) protein sensitizes tumor cells to chemotherapy. However, the role of G2E3 in breast cancer development and patient's prognosis is unclear. Here, we explored the expression, prognostic significance, and regulatory pathway of G2E3 in breast cancer. METHODS: TCGA and UALCAN database were utilized to explore G2E3 expression in breast cancer and normal tissues and its expression in breast cancer based on clinicopathological characteristics, respectively. The Kaplan-Meier plotter database was utilized to determine the effect of G2E3 on the prognosis of breast cancer patients. RT-PCR was utilized to validate the G2E3 expression in cancerous and normal breast tissues. Immunohistochemistry analysis was utilized to validate the prognostic effect of G2E3 expression in breast cancer patients and the relationship between G2E3 expression and lymphocyte infiltration levels. Receiver operating characteristic (ROC) curves were also generated to validate the diagnostic value of G2E3 expression in recurrence/distant organ metastasis and death. The STRING database, DAVID database, and Sanger-box tools were utilized to perform GO functional, KEGG pathway enrichment, and GSEA analysis. The TISIDB database was utilized to determine the relationship between G2E3 expression and tumor immunity. Finally, CTD database was utilized to screen for potential therapeutic compounds that could reduce the G2E3 mRNA expression. RESULTS: TCGA data presented that G2E3 expression was higher in breast cancer tissues than in normal breast tissues. This result was further validated by RT-PCR (P = 0.003). The Kaplan-Meier plotter database suggested that patients with high G2E3 mRNA expression had significantly shorter RFS and OS than patients with low G2E3 mRNA expression. Immunohistochemistry analysis of 156 breast cancer clinical specimens also validated patients with G2E3-positive expression had a significantly shorter DFS and OS than patients with G2E3-negative expression. Thus, G2E3 expression was an independent prognostic predictor of DFS and OS. The G2E3-positive expression also has a high diagnostic value for recurrence/distant organ metastasis and death. GSEA analysis revealed that G2E3 might be enriched in the E2F, PI3K/AKT/mTOR signaling, DNA repair pathways, and other cancer-related signaling pathways. The TISIDB database showed that G2E3 expression was significantly negatively associated with lymphocyte infiltration. This result was further validated in clinical breast cancer samples (P = 0.048; R = -0.158). Using the CTD database, we found that (+)-JQ1 compound, 1,2-dimethylhydrazine, and other compounds may decrease the G2E3 mRNA expression. These compounds could serve as potential therapeutic compounds for the clinical treatment of breast cancer. CONCLUSIONS: G2E3 expression was higher in breast cancer tissues than in normal tissues. G2E3-positive expression was related to a worse survival outcome in patients with breast cancer. Genes co-expressed with G2E3 may be enriched in the breast cancer-related signaling pathways. The G2E3 expression was significantly negatively associated with lymphocyte infiltration. G2E3 may serve as a novel prognostic biomarker and therapeutic target for breast cancer.