An Impermeant Ganetespib Analog Inhibits Extracellular Hsp90-Mediated Cancer Cell Migration that Involves Lysyl Oxidase 2-like Protein

Extracellular Hsp90 (eHsp90) activates a number of client proteins outside of cancer cells required for migration and invasion. Therefore, eHsp90 may serve as a novel target for anti-metastatic drugs as its inhibition using impermeant Hsp90 inhibitors would not affect the numerous vital intracellular Hsp90 functions in normal cells. While some eHsp90 clients are known, it is important to establish other proteins that act outside the cell to validate eHsp90 as a drug target to limit cancer spread. Using mass spectrometry we identified two precursor proteins Galectin 3 binding protein (G3BP) and Lysyl oxidase 2-like protein (LOXL2) that associate with eHsp90 in MDA-MB231 breast cancer cell conditioned media and confirmed that LOXL2 binds to eHsp90 in immunoprecipitates. We introduce a novel impermeant Hsp90 inhibitor STA-12-7191 derived from ganetespib and show that it is markedly less toxic to cells and can inhibit cancer cell migration in a dose dependent manner. We used STA-12-7191 to test if LOXL2 and G3BP are potential eHsp90 clients. We showed that while LOXL2 can increase wound healing and compensate for STA-12-7191-mediated inhibition of wound closure, addition of G3BP had no affect on this assay. These findings support of role for LOXL2 in eHsp90 stimulated cancer cell migration and provide preliminary evidence for the use of STA-12-7191 to inhibit eHsp90 to limit cancer invasion

Iterative Qubits Management for Quantum Index Searching in a Hybrid System

Recent advances in quantum computing systems attract tremendous attention. Commercial companies, such as IBM, Amazon, and IonQ, have started to provide access to noisy intermediate-scale quantum computers. Researchers and entrepreneurs attempt to deploy their applications that aim to achieve a quantum speedup. Grover's algorithm and quantum phase estimation are the foundations of many applications with the potential for such a speedup. While these algorithms, in theory, obtain marvelous performance, deploying them on existing quantum devices is a challenging task. For example, quantum phase estimation requires extra qubits and a large number of controlled operations, which are impractical due to low-qubit and noisy hardware. To fully utilize the limited onboard qubits, we propose IQuCS, which aims at index searching and counting in a quantum-classical hybrid system. IQuCS is based on Grover's algorithm. From the problem size perspective, it analyzes results and tries to filter out unlikely data points iteratively. A reduced data set is fed to the quantum computer in the next iteration. With a reduction in the problem size, IQuCS requires fewer qubits iteratively, which provides the potential for a shared computing environment. We implement IQuCS with Qiskit and conduct intensive experiments. The results demonstrate that it reduces qubits consumption by up to 66.2%

VENUS: A Geometrical Representation for Quantum State Visualization

Visualizations have played a crucial role in helping quantum computing users explore quantum states in various quantum computing applications. Among them, Bloch Sphere is the widely-used visualization for showing quantum states, which leverages angles to represent quantum amplitudes. However, it cannot support the visualization of quantum entanglement and superposition, the two essential properties of quantum computing. To address this issue, we propose VENUS, a novel visualization for quantum state representation. By explicitly correlating 2D geometric shapes based on the math foundation of quantum computing characteristics, VENUS effectively represents quantum amplitudes of both the single qubit and two qubits for quantum entanglement. Also, we use multiple coordinated semicircles to naturally encode probability distribution, making the quantum superposition intuitive to analyze. We conducted two well-designed case studies and an in-depth expert interview to evaluate the usefulness and effectiveness of VENUS. The result shows that VENUS can effectively facilitate the exploration of quantum states for the single qubit and two qubits

The effect of adjuvant chemotherapy on survival in node negative colorectal cancer with or without perineural invasion: a systematic review and meta-analysis

PurposeIt was aimed at assessing the benefits of adjuvant chemotherapy (ACT) for patients with node-negative colorectal cancer (CRC) either with or without perineural invasion (PNI).MethodsWe systematically searched PubMed, Cochrane Library, Embase, and Web of Science from database inception through October 1, 2023. Survival outcomes were analyzed using hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). The methodological quality of included studies was assessed using the Newcastle-Ottawa Scale (NOS). Heterogeneity for the descriptive meta-analyses was quantified using the I2 statistic.ResultsTen studies included in this review. ACT improved overall survival (OS) (HR 0.52, 95% CI 0.40–0.69) and disease-free survival (DFS) (HR 0.53, 95% CI 0.35–0.82) in PNI + patients but did not affect DFS (HR 1.13, 95% CI 0.72–1.77) in PNI- patients. A disease-specific survival (DSS) benefit with chemotherapy was observed in PNI + (HR 0.76, 95% CI 0.58–0.99) and PNI- patients (HR 0.76, 95% CI 0.57–1.00). And PNI decreased DFS (HR 1.94, 95% CI 1.52–2.47) and OS (HR 1.75, 95% CI 0.96–3.17) in node-negative CRC.ConclusionsIn conclusion, chemotherapy appears most beneficial for survival outcomes in node-negative patients with PNI, but may also confer some advantage in those without PNI.Systematic Review RegistrationIdentifier INPLASY2021120103

Potential molecular and cellular mechanisms of the effects of cuproptosis-related genes in the cardiomyocytes of patients with diabetic heart failure: a bioinformatics analysis

BackgroundDiabetes mellitus is an independent risk factor for heart failure, and diabetes-induced heart failure severely affects patients’ health and quality of life. Cuproptosis is a newly defined type of programmed cell death that is thought to be involved in the pathogenesis and progression of cardiovascular disease, but the molecular mechanisms involved are not well understood. Therefore, we aimed to identify biomarkers associated with cuproptosis in diabetes mellitus-associated heart failure and the potential pathological mechanisms in cardiomyocytes.MaterialsCuproptosis-associated genes were identified from the previous publication. The GSE26887 dataset was downloaded from the GEO database.MethodsThe consistency clustering was performed according to the cuproptosis gene expression. Differentially expressed genes were identified using the limma package, key genes were identified using the weighted gene co-expression network analysis(WGCNA) method, and these were subjected to immune infiltration analysis, enrichment analysis, and prediction of the key associated transcription factors. Consistency clustering identified three cuproptosis clusters. The differentially expressed genes for each were identified using limma and the most critical MEantiquewhite4 module was obtained using WGCNA. We then evaluated the intersection of the MEantiquewhite4 output with the three clusters, and obtained the key genes.ResultsThere were four key genes: HSDL2, BCO2, CORIN, and SNORA80E. HSDL2, BCO2, and CORIN were negatively associated with multiple immune factors, while SNORA80E was positively associated, and T-cells accounted for a major proportion of this relationship with the immune system. Four enriched pathways were found to be associated: arachidonic acid metabolism, peroxisomes, fatty acid metabolism, and dorsoventral axis formation, which may be regulated by the transcription factor MECOM, through a change in protein structure.ConclusionHSDL2, BCO2, CORIN, and SNORA80E may regulate cardiomyocyte cuproptosis in patients with diabetes mellitus-associated heart failure through effects on the immune system. The product of the cuproptosis-associated gene LOXL2 is probably involved in myocardial fibrosis in patients with diabetes, which leads to the development of cardiac insufficiency

Integrated Proteomic and Metabolomic Analysis of an Artificial Microbial Community for Two-Step Production of Vitamin C

An artificial microbial community consisted of Ketogulonicigenium vulgare and Bacillus megaterium has been used in industry to produce 2-keto-gulonic acid (2-KGA), the precursor of vitamin C. During the mix culture fermentation process, sporulation and cell lysis of B. megaterium can be observed. In order to investigate how these phenomena correlate with 2-KGA production, and to explore how two species interact with each other during the fermentation process, an integrated time-series proteomic and metabolomic analysis was applied to the system. The study quantitatively identified approximate 100 metabolites and 258 proteins. Principal Component Analysis of all the metabolites identified showed that glutamic acid, 5-oxo-proline, L-sorbose, 2-KGA, 2, 6-dipicolinic acid and tyrosine were potential biomarkers to distinguish the different time-series samples. Interestingly, most of these metabolites were closely correlated with the sporulation process of B. megaterium. Together with several sporulation-relevant proteins identified, the results pointed to the possibility that Bacillus sporulation process might be important part of the microbial interaction. After sporulation, cell lysis of B. megaterium was observed in the co-culture system. The proteomic results showed that proteins combating against intracellular reactive oxygen stress (ROS), and proteins involved in pentose phosphate pathway, L-sorbose pathway, tricarboxylic acid cycle and amino acids metabolism were up-regulated when the cell lysis of B. megaterium occurred. The cell lysis might supply purine substrates needed for K. vulgare growth. These discoveries showed B. megaterium provided key elements necessary for K. vulgare to grow better and produce more 2-KGA. The study represents the first attempt to decipher 2-KGA-producing microbial communities using quantitative systems biology analysis

Phase I Evaluation of STA-1474, a Prodrug of the Novel HSP90 Inhibitor Ganetespib, in Dogs with Spontaneous Cancer

The novel water soluble compound STA-1474 is metabolized to ganetespib (formerly STA-9090), a potent HSP90 inhibitor previously shown to kill canine tumor cell lines in vitro and inhibit tumor growth in the setting of murine xenografts. The purpose of the following study was to extend these observations and investigate the safety and efficacy of STA-1474 in dogs with spontaneous tumors.This was a Phase 1 trial in which dogs with spontaneous tumors received STA-1474 under one of three different dosing schemes. Pharmacokinetics, toxicities, biomarker changes, and tumor responses were assessed. Twenty-five dogs with a variety of cancers were enrolled. Toxicities were primarily gastrointestinal in nature consisting of diarrhea, vomiting, inappetence and lethargy. Upregulation of HSP70 protein expression was noted in both tumor specimens and PBMCs within 7 hours following drug administration. Measurable objective responses were observed in dogs with malignant mast cell disease (n = 3), osteosarcoma (n = 1), melanoma (n = 1) and thyroid carcinoma (n = 1), for a response rate of 24% (6/25). Stable disease (>10 weeks) was seen in 3 dogs, for a resultant overall biological activity of 36% (9/25).This study provides evidence that STA-1474 exhibits biologic activity in a relevant large animal model of cancer. Given the similarities of canine and human cancers with respect to tumor biology and HSP90 activation, it is likely that STA-1474 and ganetespib will demonstrate comparable anti-cancer activity in human patients

Contrasting Sex-and Caste-Dependent piRNA Profiles in the Transposon Depleted Haplodiploid Honeybee Apis mellifera

Protecting genome integrity against transposable elements is achieved by intricate molecular mechanisms involving PIWI proteins, their associated small RNAs (piRNAs), and epigenetic modifiers such as DNA methylation. Eusocial bees, in particular the Western honeybee, Apis mellifera, have one of the lowest contents of transposable elements in the animal kingdom, and, unlike other animals with a functional DNA methylation system, appear not to methylate their transposons. This raises the question of whether the PIWI machinery has been retained in this species. Using comparative genomics, mass spectrometry, and expressional profiling, we present seminal evidence that the piRNAsystem is conserved in honeybees. We show that honey bee piRNAs contain a 2'-O-methylmodificationat the 3' end, andhave abias towards a 5' terminalU, which are signature features of their biogenesis. Both piRNA repertoire and expression levels are greater in reproductive individuals than in sterile workers. Haploid males, where the detrimental effects of transposons are dominant, have the greatest piRNA levels, but surprisingly, the highest expression of transposons. These results show that even in a transposon-depleted species, the piRNAsystem is required to guard the vulnerable haploid genome and reproductive castes against transposon-associated genomic instability. This also suggests that dosage plays an important role in the regulation of transposons and piRNAs expression in haplo-diploid systems

Statistical Risk and Performance Analyses on Naturalistic Driving Trajectory Datasets for Traffic Modeling

The development of autonomous driving technology has made simulation testing one of the most important tools for evaluating system performance. However, there is a lack of systematic methods for analyzing and assessing naturalistic driving trajectory datasets. Specifically, there is a lack of comprehensive analyses on data diversity and balance in machine learning-oriented research. This study presents a comprehensive assessment of existing highway scenario datasets in the context of traffic modeling in autonomous driving simulation tests. In order to clarify the level of traffic risk, we design a systematic risk index and propose an index describing the degree of data scatter based on the principle of Euclidean distance quantization. By comparing several datasets, including NGSIM, highD, INTERACTION, CitySim, and our self-collected Highway dataset, we find that the proposed metrics can effectively quantify the risk level of the dataset while helping to gain insight into the diversity and balance differences of the dataset