Determination of target genes for classified molecular subtypes of triple-negative breast cancer form microarray gene expression profiling: An integrative in silico approach.

BACKGROUND: Highly heterogeneous triple-negative breast cancer (TNBC) has tough clinical features, which were gradually solving and improving in diagnosis by the molecular subtyping of TNBC. AIM: Presently, this study was focused on analyzing the genetic makeup of TNBC subtypes. SETTINGS AND DESIGN: This study explored the MicroArray expression profiling of differentially expressed genes in molecular subtypes BL1, BL2, IM, luminal androgen receptor, M, and mesenchymal stem-like of TNBC by analyzing the Gene Expression Omnibus dataset GSE167213. Various gene ontologies-based protein-protein interaction (PPI) networks were subtyped TNBC genes. The effect of genetic alteration on TNBC cases was also interpreted. MATERIALS AND METHODS: The MicroArray gene expression profiling was done through R programming and subjected to functional annotation through the database for annotation, visualization, and integrated discovery. The PPI networking of functionally associated genes was interpreted by STRING. The survival analysis was done through cBioPortal. STATISTICAL ANALYSIS USED: The t-test was used through R programming to generate the P values for a test of the significance of expressed genes. RESULTS: A total of 54,613 significant probes were analyzed in the TNBC MicroArray dataset. The functional PPI networks of BL1, BL2, and IM upregulated genes showed significant associations. The survival analysis of differentially expressed genes showed the significant prognostic effect of 32 upregulated genes of different subtypes on TNBC cases with genetic alterations, whereas the remaining genes showed no significant effects. CONCLUSION: The output of the present study provided significant target gene panels for different TNBC subtypes, which would add an informative genetic value to TNBC diagnosis.

PDXNet portal: patient-derived Xenograft model, data, workflow and tool discovery.

We created the PDX Network (PDXNet) portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources, to facilitate collaboration among researchers and to make these data easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols and training materials for processing PDX data. Currently, the portal contains PDXNet model information and data resources from 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCI's Patient-Derived Model Repository (PDMR) for public access. These models have 2134 associated sequencing files from 873 samples across 308 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal includes results from freely available, robust, validated and standardized analysis workflows on PDXNet sequencing files and PDMR data (3857 samples from 629 patients across 85 disease types). The PDXNet portal is continuously updated with new data and is of significant utility to the cancer research community as it provides a centralized location for PDXNet resources, which support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials.

Ponesimod inhibits astrocyte-mediated neuroinflammation and protects against cingulum demyelination via S1P1 -selective modulation.

Ponesimod is a sphingosine 1-phosphate (S1P) receptor (S1PR) modulator that was recently approved for treating relapsing forms of multiple sclerosis (MS). Three other FDA-approved S1PR modulators for MS-fingolimod, siponimod, and ozanimod-share peripheral immunological effects via common S1P1 interactions, yet ponesimod may access distinct central nervous system (CNS) mechanisms through its selectivity for the S1P1 receptor. Here, ponesimod was examined for S1PR internalization and binding, human astrocyte signaling and single-cell RNA-seq (scRNA-seq) gene expression, and in vivo using murine cuprizone-mediated demyelination. Studies confirmed ponesimod's selectivity for S1P1 without comparable engagement to the other S1PR subtypes (S1P2,3,4,5 ). Ponesimod showed pharmacological properties of acute agonism followed by chronic functional antagonism of S1P1 . A major locus of S1P1 expression in the CNS is on astrocytes, and scRNA-seq of primary human astrocytes exposed to ponesimod identified a gene ontology relationship of reduced neuroinflammation and reduction in known astrocyte disease-related genes including those of immediate early astrocytes that have been strongly associated with disease progression in MS animal models. Remarkably, ponesimod prevented cuprizone-induced demyelination selectively in the cingulum, but not in the corpus callosum. These data support the CNS activities of ponesimod through S1P1 , including protective, and likely selective, effects against demyelination in a major connection pathway of the brain, the limbic fibers of the cingulum, lesions of which have been associated with several neurologic impairments including MS fatigue.

Bioinformatics tools developed to support BioCompute Objects.

Developments in high-throughput sequencing (HTS) result in an exponential increase in the amount of data generated by sequencing experiments, an increase in the complexity of bioinformatics analysis reporting and an increase in the types of data generated. These increases in volume, diversity and complexity of the data generated and their analysis expose the necessity of a structured and standardized reporting template. BioCompute Objects (BCOs) provide the requisite support for communication of HTS data analysis that includes support for workflow, as well as data, curation, accessibility and reproducibility of communication. BCOs standardize how researchers report provenance and the established verification and validation protocols used in workflows while also being robust enough to convey content integration or curation in knowledge bases. BCOs that encapsulate tools, platforms, datasets and workflows are FAIR (findable, accessible, interoperable and reusable) compliant. Providing operational workflow and data information facilitates interoperability between platforms and incorporation of future dataset within an HTS analysis for use within industrial, academic and regulatory settings. Cloud-based platforms, including High-performance Integrated Virtual Environment (HIVE), Cancer Genomics Cloud (CGC) and Galaxy, support BCO generation for users. Given the 100K+ userbase between these platforms, BioCompute can be leveraged for workflow documentation. In this paper, we report the availability of platform-dependent and platform-independent BCO tools: HIVE BCO App, CGC BCO App, Galaxy BCO API Extension and BCO Portal. Community engagement was utilized to evaluate tool efficacy. We demonstrate that these tools further advance BCO creation from text editing approaches used in earlier releases of the standard. Moreover, we demonstrate that integrating BCO generation within existing analysis platforms greatly streamlines BCO creation while capturing granular workflow details. We also demonstrate that the BCO tools described in the paper provide an approach to solve the long-standing challenge of standardizing workflow descriptions that are both human and machine readable while accommodating manual and automated curation with evidence tagging. Database URL:  https://www.biocomputeobject.org/resources.

BCO App: tools for generating BioCompute Objects from next-generation sequencing workflows and computations.

The BioCompute Object (BCO) standard is an IEEE standard (IEEE 2791-2020) designed to facilitate the communication of next-generation sequencing data analysis with applications across academia, government agencies, and industry. For example, the Food and Drug Administration (FDA) supports the standard for regulatory submissions and includes the standard in their Data Standards Catalog for the submission of HTS data. We created the BCO App to facilitate BCO generation in a range of computational environments and, in part, to participate in the Advanced Track of the precisionFDA BioCompute Object App-a-thon. The application facilitates the generation of BCOs from both workflow metadata provided as plaintext and from workflow contents written in the Common Workflow Language. The application can also access and ingest task execution results from the Cancer Genomics Cloud (CGC), an NCI funded computational platform. Creating a BCO from a CGC task significantly reduces the time required to generate a BCO on the CGC by auto-populating workflow information fields from CGC workflow and task execution results. The BCO App supports exporting BCOs as JSON or PDF files and publishing BCOs to both the CGC platform and to GitHub repositories.

Lauric Acid Modulates Cancer-Associated microRNA Expression and Inhibits the Growth of the Cancer Cell.

BACKGROUND: microRNAs are known to regulate various protein-coding gene expression posttranscriptionally. Fatty acids are cell membrane constituents and are also known to influence the biological activities of the cells like signal transduction, growth and differentiation of the cells, apoptosis induction, and other physiological functions. In our experiments, we used lauric acid to analyse its effects on human cancerous cell lines. OBJECTIVE: Our objective was to speculate the miRNA expression profile in lauric acid treated and untreated cancerous cell lines and further study the metabolic pathways of the targeted tumour suppressor and oncogenes. METHODS: The KB cells and HepG2 cells were treated with lauric acid and miRNA was isolated and the expression of tumour suppressor and oncogenic miRNA was measured by quantitative PCR. The untreated cells were used as control. The metabolic pathways of the target tumour suppressor and oncogenes were examined by GeneMANIA software. RESULTS: Interestingly, the lauric acid treatment suppresses the expression of oncogenic miRNA and significantly upregulated the expression of some tumour suppressor miRNAs. GeneMANIA metabolic pathway revealed that the upregulated tumour suppressor miRNAs regulate several cancer-associated pathways such as DNA damage, signal transduction p53 class mediator, stem cell differentiation, cell growth, cell cycle phase transition, apoptotic signalling pathway, cellular response to stress and radiation, etc. whereas oncogenic miRNAs regulate the cancer-associated pathway like cell cycle phase transition, apoptotic signalling pathway, cell growth, response to oxidative stress, immune response activating cell surface protein signalling pathway, cyclin-dependent protein kinase activity, epidermal growth factor receptor signalling pathways, etc. Conclusion: In our study, we found that lauric acid works as an anticancer agent by altering the expression of miRNAs.

Dementia and hearing loss: A narrative review.

Dementia and hearing loss are both common among older people. The co-occurrence of the two conditions increases complexities in all aspects of an individual's care and management plan. There has been increasing research interest in the relationship between dementia and hearing loss in recent years. In this review we discuss the relationship between hearing loss and dementia, including hearing loss as a risk factor for dementia; the effects of dementia with hearing loss on affected persons' quality of life and the care they receive; screening and available interventions; and opportunities for prevention. We also discuss dementia and hearing loss in the care home setting, as the majority of residents have either, or indeed both, dementia and/or hearing loss. Several mechanisms have been suggested for how hearing loss and dementia may be related but the evidence for how these may operate together is still unclear. Similarly, although it is to be hoped that the active identification and management of hearing problems may help to reduce the future development of cognitive impairment, evidence for this is still lacking.

Insight into ethylene interactions with molybdenum suboxide cluster anions from photoelectron spectra of chemifragments.

Recent studies on reactions between MoxOy- cluster anions and H2O/C2H4 mixtures revealed a complex web of addition, hydrogen evolution, and chemifragmentation reactions, with chemifragments unambiguously connected to cluster reactions with C2H4. To gain insight into the molecular-scale interactions along the chemifragmentation pathways, the anion photoelectron (PE) spectra of MoC2H2-, MoC4H4-, MoOC2H2-, and MoO2C2H2- formed directly in MoxOy- + C2H4 (x > 1; y ≥ x) reactions, along with supporting CCSD(T) and density functional theory calculations, are presented and analyzed. The complexes have spectra that are all consistent with η2-acetylene complexes, though for all but MoC4H4-, the possibility that vinylidene complexes are also present cannot be definitively ruled out. Structures that are consistent with the PE spectrum of MoC2H2- differ from the lowest energy structure, suggesting that the fragment formation is under kinetic control. The PE spectrum of MoO2C2H2- additionally exhibits evidence that photodissociation to MoO2- + C2H2 may be occurring. The results suggest that oxidative dehydrogenation of ethylene is initiated by Lewis acid/base interactions between the Mo centers in larger clusters and the π orbitals in ethylene.

Hydrogen evolution from water using Mo-oxide clusters in the gas phase: DFT modeling of a complete catalytic cycle using a Mo2O4-/Mo2O5- cluster couple.

Density functional theory (DFT) calculations using a small metal cluster couple, Mo2O4-/Mo2O5-, are used to model a complete catalytic cycle for H2 production from water. While Mo2O4- is known to readily react with water to form Mo2O5- and release H2, the principal challenge is in reducing Mo2O5- to Mo2O4- to complete the cycle. We investigate the role of several potential sacrificial reagents (ethylene, propylene, CO and acetylene) that can reduce Mo2O5- after the initial oxidation. DFT calculations of the free energy reaction pathways demonstrate the presence of overall kinetically accessible barriers that are below the entrance channel (separated reactants) in the Mo2O4- + H2O reaction (step I) followed by the Mo2O5- + sacrificial reagent reactions (step II). Though the overall reaction is thermodynamically favorable, the first step is highly exothermic while the second step is endothermic. The deepest part of the potential energy surface is a complex of Mo2O5- with the sacrificial reagent. If the energy gained in the first reaction and the succeeding complex formation is not lost due to collisions, the subsequent barriers can be overcome, leading to possible catalytic applications of the Mo2O4-/Mo2O5- cluster couple in H2 production reactions.

Simple relationship between oxidation state and electron affinity in gas-phase metal-oxo complexes.

The photoelectron spectra of WO3H(-) and WO2F(-) are presented and analyzed in the context of a series of previous similar measurements on MO(y)(-) (M = Mo, W; y = 0-3), MO4H(-) and AlMOy(-) (y ≤ 4) complexes. The electronic structures of the WO3H and WO2F anion and neutral complexes were investigated using the B3LYP hybrid density functional method. The spectra of WO3H(-), WO2F(-), and previously measured AlWO3(-) photoelectron spectra show that the corresponding neutrals, in which the transition metal centers are all in a +5 oxidation state, have comparable electron affinities. In addition, the electron affinities fit the general trend of monotonically increasing electron affinity with oxidation state, in spite of the WO3H(-), WO2F(-), and AlWO3(-) having closed shell ground states, suggesting that the oxidation state of the metal atom has more influence than shell closing on the electron affinity of these transition metal-oxo complexes. Results of DFT calculations suggest that the neutrals are pyramidal and the anions are planar. However, the barriers for inversion on the neutral surface are low, and attempts to generate simple Franck-Condon simulations based on simple normal coordinate displacement, ignoring the effects of inversion, are inadequate.

Inhibition of Granzyme B by PI-9 protects prostate cancer cells from apoptosis.

BACKGROUND: In order for tumors to grow and proliferate, they must avoid recognition by immune cells and subsequent death by apoptosis. Granzyme B (GrB), a protease located in natural killer cells, initiates apoptosis in target cells. Inhibition of GrB by PI-9, its natural inhibitor, can prevent apoptosis. Here we investigate whether PI-9 protects prostate cancer cells from apoptosis. METHODS: The expression of PI-9 was quantified by qPCR in several prostate cancer cell lines, and GrB activity was tested in each cell line. PI-9 was overexpressed in LNCaP cells, which lack endogenous PI-9. Apoptosis was induced by natural killer cells in LNCaP cells that either contained or lacked PI-9, and the percent cell death was quantified. Lastly, PI-9 levels were examined by qPCR and immunohistochemistry in prostate tumor tissue. RESULTS: Prostate cancer cell lines that expressed PI-9 could inhibit GrB. Overexpression of PI-9 protected LNCaP cells from natural killer cell-mediated apoptosis. Examination of the levels of PI-9 in tissue from prostate tumors showed that PI-9 could be upregulated in low grade tumors and stochastically dysregulated in high grade tumors. Additionally, PI-9 was found consistently in high grade prostatic intraepithelial neoplasia and atrophic lesions. CONCLUSIONS: These results indicate that overexpression of PI-9 can protect prostate cancer cells from apoptosis, and this effect may occur in human prostate tumors. These findings imply that early prostatic inflammation may trigger this increase in PI-9. This suggests that PI-9 upregulation is needed early in tumor progression, before additional protective mechanisms are in place.

Peptide length and leaving-group sterics influence potency of peptide phosphonate protease inhibitors.

The ability to follow enzyme activity in a cellular context represents a challenging technological frontier that impacts fields ranging from disease pathogenesis to epigenetics. Activity-based probes (ABPs) label the active form of an enzyme via covalent modification of catalytic residues. Here we present an analysis of parameters influencing potency of peptide phosphonate ABPs for trypsin-fold S1A proteases, an abundant and important class of enzymes with similar substrate specificities. We find that peptide length and stability influence potency more than sequence composition and present structural evidence that steric interactions at the prime-side of the substrate-binding cleft affect potency in a protease-dependent manner. We introduce guidelines for the design of peptide phosphonate ABPs and demonstrate their utility in a live-cell labeling application that specifically targets active S1A proteases at the cell surface of cancer cells.