Biology subjects

Bringas, R.

Publications and source records attributed to Bringas, R..

3 recordsLinked to original sources

bioRxiv2026

Integrated Analysis of HeberFERON-Driven Comparative Proteomic regulation in Glioblastoma Cells U-87MG

Glioblastoma is a very aggressive brain tumor with few therapeutics options. Type I and II Interferons (IFNs) co-formulation HeberFERON has been used in cancer treatment, with promising results in high grade brain tumors. High throughput techniques in easy-to-handle models have been important to interrogate biomolecules changes, describe mechanisms and find pharmacodynamic biomarkers. This study aims to elucidate the effect of HeberFERON over the cell proteome in comparison to its individual IFNs components. Proteomic changes with HeberFERON in the glioblastoma-derived cell line U-87MG, in comparison with individual IFN-2b and IFN-{gamma}, were studied using a nanoLC instrument EasyLC coupled to Velos Pro mass spectrometer; Maxquant and Perseus were also used. Several enrichment tools, networking analysis and canSAR for drug targets were employed. Translation, RNA processing, mitotic cell cycle, cytoskeleton and chromosome organization, apoptosis, autophagy, DNA repair are enriched to limit cellular growing together with changes in immune response components, supporting HeberFERON as a multitarget treatment. This co-formulation is distinguished at modulating RNA splicing with SMN complex, cytoskeleton organization and microtubule-based movement, nuclear envelope breakdown, DNA conformational changes, and oxidative phosphorylation, with a better drawing of effects over a variety of systems inside the tumoral cell. Together with previous microarray experiment, informative genes and proteins as pharmacodynamic biomarkers for antiproliferative effects showed up (ex. STAT1/2, CENPE, ATRIP, MAP1B, LIMA1, VCP, several ribosomal, spliceosome and proteasomal complexes proteins). This study complements transcriptomic and phosphoproteomic previous experiments in this model and underscore HeberFERON as a glioblastoma therapeutic.

cancer biology↗

bioRxiv2022

HeberFERON distinctively targets Cell Cycle in the glioblastoma-derived cell line U-87MG.

BackgroundHeberFERON is a co-formulation of 2b and {gamma} interferons, based on their synergism, that have shown its clinical superiority over individual interferons in basal cell carcinomas. In Glioblastoma (GBM), HeberFERON has shown promising preclinical and clinical results. This motivated us to design a microarray experiment aimed to identify the molecular mechanisms involved into the distinctive effect of HeberFERON compared with individual interferons. MethodsTranscriptional expression profiling including a control (untreated) and three groups receiving 2b-interferon, {gamma}-interferon and HeberFERON was performed using an Illumina HT-12 microarray platform. Unsupervised methods for gene and sample grouping, identification of differentially expressed genes, functional enrichment and network analysis computational biology methods were applied to identify distinctive patterns of HeberFERON action. Validation of most distinctive genes was performed by qPCR. Cell Cycle analysis of cell treated by HeberFERON for 24h, 48h and 72h was carried out by flow cytometry. ResultsThe three treatments show different behavior based on the gene expression profiles. Enrichment analysis identified several Mitotic Cell Cycle related events, in particular from Prometaphase to Anaphase, that are exclusively targeted by HeberFERON. FOXM1 transcription factor network which is involved in several Cell Cycle phases and is highly expressed in GBMs is significantly down regulated by HeberFERON. Flow cytometry experiments corroborated the action of HeberFERON over Cell Cycle in a dose and time dependent manner with a clear cellular arrest since 24h post-treatment. Despite the fact that p53 was not down-regulated by HeberFERON several genes involved in its regulatory activity were functionally enriched. Network analysis also revealed a strong relation of p53 with genes targeted by HeberFERON. We propose a mechanistic model to explain HeberFERON distinctive action, based on the simultaneous activation of PKR and ATF3, p53 phosphorylation changes as well as its reduced MDM2 mediated ubiquitination and export from nucleus to cytoplasm. PLK1, AURKB, BIRC5 and CCNB1 genes, all regulated by FOXM1, also play central roles in this model. These and other interactions could explain a G2/M arrest and the effect of HeberFERON over the proliferation of U-87MG. ConclusionsWe proposed molecular mechanisms underlying the distinctive behavior of HeberFERON compared to individual interferon treatments, where Cell Cycle related events showed the highest relevance.

cancer biology↗

bioRxiv2021

CIGB-300 synthetic peptide, an antagonist of CK2 kinase activity, as a treatment for Covid-19. A computational biology approach

Drug repositioning became the first choice for treating Covid-19 patients due to the urgent need to deal with the pandemic. Similarities in the hijacking mechanisms used by SARS-CoV-2 and several type of cancer, suggest the repurposing of cancer drugs to treat Covid-19. CK2 kinase antagonists have been proposed for the treatment of cancer. A recent study in cells infected with SARS-CoV-2 virus found a significant CK2 kinase activity, and the use of a CK2 inhibitor showed antiviral responses. CIGB-300, originally designed as an anticancer peptide, is an antagonist of CK2 kinase activity that binds to CK2 phospho-acceptor sites. Recent preliminary results show an antiviral activity of CIGB-300 versus a surrogate model of coronavirus. Here we present a computational biology study that provides evidences at the molecular level of how CIGB-300 might interfere with SARS-CoV-2 life cycle inside infected human cells. First, from SARS-CoV studies, we infer the potential incidence of CIGB-300 in SARS-CoV-2 interference on immune response. Next, from the analysis of multiple Omics data, we propose the action of CIGB-300 since early stage of viral infections perturbing the virus hijacking of RNA splicing machinery. It was also predicted the interference of CIGB-300 in virus-host interactions responsible for the high infectivity and the particular immune response to SARS-CoV-2 infection. Further, we provide evidences of CIGB-300 attenuation of phenotypes related to muscle, bleeding, coagulation and respiratory disorders.

bioinformatics↗