A System-wide Approach to Monitor Responses to Synergistic BRAF and EGFR Inhibition in Colorectal Cancer Cells.

Intrinsic and/or acquired resistance represents one of the great challenges in targeted cancer therapy. A deeper understanding of the molecular biology of cancer has resulted in more efficient strategies, where one or multiple drugs are adopted in novel therapies to tackle resistance. This beneficial effect of using combination treatments has also been observed in colorectal cancer patients harboring the BRAF(V600E) mutation, whereby dual inhibition of BRAF(V600E) and EGFR increases antitumor activity. Notwithstanding this success, it is not clear whether this combination treatment is the only or most effective treatment to block intrinsic resistance to BRAF inhibitors. Here, we investigate molecular responses upon single and multi-target treatments, over time, using BRAF(V600E) mutant colorectal cancer cells as a model system. Through integration of transcriptomic, proteomic and phosphoproteomics data we obtain a comprehensive overview, revealing both known and novel responses. We primarily observe widespread up-regulation of receptor tyrosine kinases and metabolic pathways upon BRAF inhibition. These findings point to mechanisms by which the drug-treated cells switch energy sources and enter a quiescent-like state as a defensive response, while additionally compensating for the MAPK pathway inhibition.

PaDuA: A Python Library for High-Throughput (Phospho)proteomics Data Analysis.

The increased speed and sensitivity in mass spectrometry-based proteomics has encouraged its use in biomedical research in recent years. Large-scale detection of proteins in cells, tissues, and whole organisms yields highly complex quantitative data, the analysis of which poses significant challenges. Standardized proteomic workflows are necessary to ensure automated, sharable, and reproducible proteomics analysis. Likewise, standardized data processing workflows are also essential for the overall reproducibility of results. To this purpose, we developed PaDuA, a Python package optimized for the processing and analysis of (phospho)proteomics data. PaDuA provides a collection of tools that can be used to build scripted workflows within Jupyter Notebooks to facilitate bioinformatics analysis by both end-users and developers.

Rearrangement of the Protein Phosphatase 1 Interactome During Heart Failure Progression.

BACKGROUND: Heart failure (HF) is a complex disease with a rising prevalence despite advances in treatment. Protein phosphatase 1 (PP1) has long been implicated in HF pathogenesis, but its exact role is both unclear and controversial. Most previous studies measured only the PP1 catalytic subunit (PP1c) without investigating its diverse set of interactors, which confer localization and substrate specificity to the holoenzyme. In this study, we define the PP1 interactome in cardiac tissue and test the hypothesis that this interactome becomes rearranged during HF progression at the level of specific PP1c interactors. METHODS: Mice were subjected to transverse aortic constriction and grouped on the basis of ejection fraction into sham, hypertrophy, moderate HF (ejection fraction, 30%-40%), and severe HF (ejection fraction <30%). Cardiac lysates were subjected to affinity purification with anti-PP1c antibodies followed by high-resolution mass spectrometry. PP1 regulatory subunit 7 (Ppp1r7) was knocked down in mouse cardiomyocytes and HeLa cells with adeno-associated virus serotype 9 and siRNA, respectively. Calcium imaging was performed on isolated ventricular myocytes. RESULTS: Seventy-one and 98 PP1c interactors were quantified from mouse cardiac and HeLa lysates, respectively, including many novel interactors and protein complexes. This represents the largest reproducible PP1 interactome data set ever captured from any tissue, including both primary and secondary/tertiary interactors. Nine PP1c interactors with changes in their binding to PP1c were strongly associated with HF progression, including 2 known (Ppp1r7 and Ppp1r18) and 7 novel interactors. Within the entire cardiac PP1 interactome, Ppp1r7 had the highest binding to PP1c. Cardiac-specific knockdown in mice led to cardiac dysfunction and disruption of calcium release from the sarcoplasmic reticulum. CONCLUSIONS: PP1 is best studied at the level of its interactome, which undergoes significant rearrangement during HF progression. The 9 key interactors that are associated with HF progression may represent potential targets in HF therapy. In particular, Ppp1r7 may play a central role in regulating the PP1 interactome by acting as a competitive molecular "sponge" of PP1c.

Early T Cell Recognition of B Cells following Epstein-Barr Virus Infection: Identifying Potential Targets for Prophylactic Vaccination.

Epstein-Barr virus, a B-lymphotropic herpesvirus, is the cause of infectious mononucleosis, has strong aetiologic links with several malignancies and has been implicated in certain autoimmune diseases. Efforts to develop a prophylactic vaccine to prevent or reduce EBV-associated disease have, to date, focused on the induction of neutralising antibody responses. However, such vaccines might be further improved by inducing T cell responses capable of recognising and killing recently-infected B cells. In that context, EBNA2, EBNA-LP and BHRF1 are the first viral antigens expressed during the initial stage of B cell growth transformation, yet have been poorly characterised as CD8+ T cell targets. Here we describe CD8+ T cell responses against each of these three "first wave" proteins, identifying target epitopes and HLA restricting alleles. While EBNA-LP and BHRF1 each contained one strong CD8 epitope, epitopes within EBNA2 induced immunodominant responses through several less common HLA class I alleles (e.g. B*3801 and B*5501), as well as subdominant responses through common class I alleles (e.g. B7 and C*0304). Importantly, such EBNA2-specific CD8+ T cells recognised B cells within the first day post-infection, prior to CD8+ T cells against well-characterised latent target antigens such as EBNA3B or LMP2, and effectively inhibited outgrowth of EBV-transformed B cell lines. We infer that "first wave" antigens of the growth-transforming infection, especially EBNA2, constitute potential CD8+ T cell immunogens for inclusion in prophylactic EBV vaccine design.

Robust, Sensitive, and Automated Phosphopeptide Enrichment Optimized for Low Sample Amounts Applied to Primary Hippocampal Neurons.

Because of the low stoichiometry of protein phosphorylation, targeted enrichment prior to LC-MS/MS analysis is still essential. The trend in phosphoproteome analysis is shifting toward an increasing number of biological replicates per experiment, ideally starting from very low sample amounts, placing new demands on enrichment protocols to make them less labor-intensive, more sensitive, and less prone to variability. Here we assessed an automated enrichment protocol using Fe(III)-IMAC cartridges on an AssayMAP Bravo platform to meet these demands. The automated Fe(III)-IMAC-based enrichment workflow proved to be more effective when compared to a TiO2-based enrichment using the same platform and a manual Ti(IV)-IMAC-based enrichment workflow. As initial samples, a dilution series of both human HeLa cell and primary rat hippocampal neuron lysates was used, going down to 0.1 µg of peptide starting material. The optimized workflow proved to be efficient, sensitive, and reproducible, identifying, localizing, and quantifying thousands of phosphosites from just micrograms of starting material. To further test the automated workflow in genuine biological applications, we monitored EGF-induced signaling in hippocampal neurons, starting with only 200 000 primary cells, resulting in ∼50 µg of protein material. This revealed a comprehensive phosphoproteome, showing regulation of multiple members of the MAPK pathway and reduced phosphorylation status of two glutamate receptors involved in synaptic plasticity.

Profound Understanding of Effect of Transition Metal Dopant, Sintering Temperature, and pO2 on the Electrical and Optical Properties of Proton Conducting BaCe0.9Sm0.1O3-δ.

This study reports the effect of transition metal (TM) substitution on the electrical and optical properties of BaCe0.9Sm0.1O3-δ (BCS). Concentrations of 5-10 mol % of each of Fe and Co have been doped for the B-site of BCS by citric acid autocombustion method. Powder X-ray diffraction has revealed the formation of an orthorhombic perovskite-type structure. FTIR confirmed a distortion in the lattice upon TM-doping in BCS. Scanning electron microscopy (SEM) images of 1400 °C sintered samples have manifested a higher densification in BaCe0.8Sm0.1Co0.1O3-δ (BCSC10) with a grain size ∼11 µm compared to the parent compound BCS (∼2 µm). Thermogravimetric (TG) analysis showed a water uptake in case of BaCe0.85Sm0.1Co0.05O3-δ (BCSC5), while BaCe0.85Sm0.1Fe0.05O3-δ (BCSF5) did not show a noteworthy uptake of water. TG has also proved that the incorporation of Fe and Co in BCS did not improve the chemical stability in CO2 at elevated temperature. The band gap estimated using Kubelka-Munk model based on the diffuse reflectance data was found to be the lowest for BCSC5 (2.47 eV). However, it increases upon lowering oxygen partial pressure (pO2), which was interpreted by a band structure modifications. Among the samples investigated, BCSC10 sintered at 1400 °C showed the highest electrical conductivity of 0.02 S cm(-1) in air at 600 °C, while its proton mobility appears to be negligible under the investigated humidity atmosphere.

Pathomx: an interactive workflow-based tool for the analysis of metabolomic data.

BACKGROUND: Metabolomics is a systems approach to the analysis of cellular processes through small-molecule metabolite profiling. Standardisation of sample handling and acquisition approaches has contributed to reproducibility. However, the development of robust methods for the analysis of metabolomic data is a work-in-progress. The tools that do exist are often not well integrated, requiring manual data handling and custom scripting on a case-by-case basis. Furthermore, existing tools often require experience with programming environments such as MATLAB® or R to use, limiting accessibility. Here we present Pathomx, a workflow-based tool for the processing, analysis and visualisation of metabolomic and associated data in an intuitive and extensible environment. RESULTS: The core application provides a workflow editor, IPython kernel and a HumanCyc™-derived database of metabolites, proteins and genes. Toolkits provide reusable tools that may be linked together to create complex workflows. Pathomx is released with a base set of plugins for the import, processing and visualisation of data. The IPython backend provides integration with existing platforms including MATLAB® and R, allowing data to be seamlessly transferred. Pathomx is supplied with a series of demonstration workflows and datasets. To demonstrate the use of the software we here present an analysis of 1D and 2D (1)H NMR metabolomic data from a model system of mammalian cell growth under hypoxic conditions. CONCLUSIONS: Pathomx is a useful addition to the analysis toolbox. The intuitive interface lowers the barrier to entry for non-experts, while scriptable tools and integration with existing tools supports complex analysis. We welcome contributions from the community.

Metabolic profiling predicts response to anti-tumor necrosis factor α therapy in patients with rheumatoid arthritis.

OBJECTIVE: Anti-tumor necrosis factor (anti-TNF) therapies are highly effective in rheumatoid arthritis (RA) and psoriatic arthritis (PsA), but a significant number of patients exhibit only a partial or no therapeutic response. Inflammation alters local and systemic metabolism, and TNF plays a role in this. We undertook this study to determine if the patient's metabolic fingerprint prior to therapy could predict responses to anti-TNF agents. METHODS: Urine was collected from 16 RA patients and 20 PsA patients before and during therapy with infliximab or etanercept. Urine metabolic profiles were assessed using nuclear magnetic resonance spectroscopy. Discriminating metabolites were identified, and the relationship between metabolic profiles and clinical outcomes was assessed. RESULTS: Baseline urine metabolic profiles discriminated between RA patients who did or did not have a good response to anti-TNF therapy according to European League Against Rheumatism criteria, with a sensitivity of 88.9% and a specificity of 85.7%, with several metabolites contributing (in particular histamine, glutamine, xanthurenic acid, and ethanolamine). There was a correlation between baseline metabolic profiles and the magnitude of change in the Disease Activity Score in 28 joints from baseline to 12 months in RA patients (P = 0.04). In both RA and PsA, urinary metabolic profiles changed between baseline and 12 weeks of anti-TNF therapy. Within the responders, urinary metabolite changes distinguished between etanercept and infliximab treatment. CONCLUSION: The clear relationship between urine metabolic profiles of RA patients at baseline and their response to anti-TNF therapy may allow development of novel approaches to the optimization of therapy. Differences in metabolic profiles during treatment with infliximab and etanercept in RA and PsA may reflect distinct mechanisms of action.

A Scoping Review of Behavioural Studies on Heated Tobacco Products.

Heated tobacco products (HTPs) are electronic devices that heat tobacco sticks to temperatures much lower than those which cause pyrolysis and combustion in cigarettes. While this electrical heating causes the formation of an inhalable aerosol which contains nicotine, the aerosol from HTPs contains significantly fewer and lower levels of the harmful and potentially harmful chemicals found in cigarette smoke. As a result, HTP use potentially conveys reduced risks to health compared to cigarette smoking. While this relative reduction in individual health risk is becoming clearer, what is less certain is the impact of HTPs on overall population­level health, taking into account both the potential positive impact on adult smokers who completely switch to using HTPs and any unintended impacts such as use by tobacco non­users and particularly by youth. The aim of this scoping review was to collate and evaluate the published scientific evidence to date, with a cut­off of 1 January 2024, investigating the impact of HTPs on population­level health. This evaluation suggests that HTP use is almost exclusively observed among those with a history of cigarette smoking, and there is a growing body of evidence for the ability of HTPs to provide support for adult smokers to transition away from cigarette smoking, in the absence of any significant "gateway" into tobacco use initiation. Many studies have reported a significant degree of dual use of cigarettes and HTPs, and efforts to assess the reasons for such patterns of use, whether these provide overall exposure reductions, and whether dual use acts as a bridge towards a complete transition away from cigarette smoking, requires further investigation. In addition, correction of the widespread and increasing misperceptions of HTPs among adult smokers is recommended to promote HTP uptake as a potentially less harmful alternative to smoking in this population.