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At least 19 records

Gestational exposure to HIV drugs alters intestinal mucosa-associated microbial diversity in adult rat offspring

The antiretroviral (ARV) drug combination of abacavir sulfate, dolutegravir, and lamivudine [ABC/DTG/3TC; Tri combination Anti-retroviral therapy (TC-ART)] has revolutionized HIV treatment by effectively targeting different stages of viral replication. Despite its therapeutic efficiency for maintaining low viremia in the mother during pregnancy, there are concerns for long-term liabilities in offspring that are indirectly exposed during vulnerable periods of development. The commensal microbiota plays a crucial role in maintaining overall gut health, and disruption of the microbiome is often linked to various extraintestinal effects such as immune dysregulation and inflammation. We recently reported the effects of this drug combination in altering fecal microbiome composition of aged rats perinatally exposed to ABC/DTG/3TC-ART. The fecal microbiome can provide only a snapshot of the composition of microbial community at the end of the digestive tract, which may not reflect the microbial population interacting with ileal mucosa. Thus, the current work reports the effects of this drug combination in the gut mucosa-associated microbiome of the same animals, which showed significant microbial diversity and species richness in high dose exposed female adult offspring, along with dose-dependent changes in Firmicutes/Bacteroidetes ratio. The high dose exposure also showed an increase in opportunistic bacterial species in male animals. Overall, we found that, similar to the fecal microbiome, perinatal exposure to TC-ART led to sex- and dose-dependent alterations in the gut mucosa-associated microbial population in aged rats, suggesting that early life exposure to these drugs may influence gut mucosa-associated immune responses and intestinal permeability.

Research & Experimental Medicine↗

C10-Benzoate Esters of Anhydrotetracycline Inhibit Tetracycline Destructases and Recover Tetracycline Antibacterial Activity

Tetracyclines (TCs) are an important class of antibiotics threatened by enzymatic inactivation. These tetracycline-inactivating enzymes, also known as tetracycline destructases (TDases), are a subfamily of class A flavin monooxygenases (FMOs) that catalyze hydroxyl group transfer and oxygen insertion (Baeyer–Villiger type) reactions on TC substrate scaffolds. Semisynthetic modification of TCs (e.g., tigecycline, omadacycline, eravacycline, and sarecycline) has proven effective in evading certain resistance mechanisms, such as ribosomal protection and efflux, but does not protect against TDase-mediated resistance. Here, we report the design, synthesis, and evaluation of a new series of 22 semisynthetic TDase inhibitors that explore D-ring substitution of anhydrotetracycline (aTC) including 14 C10-benzoate ester and eight C9-benzamides. Overall, the C10-benzoate esters displayed enhanced bioactivity and water solubility compared to the corresponding C9-benzamides featuring the same heterocyclic aryl side chains. The C10-benzoate ester derivatives of aTC were prepared in a high-yield one-step synthesis without the need for protecting groups. The C10-esters are water-soluble, stable toward hydrolysis, and display dose-dependent rescue of tetracycline antibiotic activity in E. coli expressing two types of tetracycline destructases, represented by TetX7 (Type 1) and Tet50 (Type 2). The best inhibitors recovered tetracycline antibiotic activity at concentrations as low as 2 μM, producing synergistic scores <0.5 in the fractional inhibitory concentration index (FICI) against TDase-expressing strains of E. coli and clinical P. aeruginosa. The C10-benzoate ester derivatives of aTC reported here are promising new leads for the development of tetracycline drug combination therapies to overcome TDase-mediated antibiotic resistance.

60 APPLIED LIFE SCIENCES↗

Impact of structural biology and the protein data bank on us fda new drug approvals of low molecular weight antineoplastic agents 2019–2023

Abstract Open access to three-dimensional atomic-level biostructure information from the Protein Data Bank (PDB) facilitated discovery/development of 100% of the 34 new low molecular weight, protein-targeted, antineoplastic agents approved by the US FDA 2019–2023. Analyses of PDB holdings, the scientific literature, and related documents for each drug-target combination revealed that the impact of structural biologists and public-domain 3D biostructure data was broad and substantial, ranging from understanding target biology (100% of all drug targets), to identifying a given target as likely druggable (100% of all targets), to structure-guided drug discovery (>80% of all new small-molecule drugs, made up of 50% confirmed and >30% probable cases). In addition to aggregate impact assessments, illustrative case studies are presented for six first-in-class small-molecule anti-cancer drugs, including a selective inhibitor of nuclear export targeting Exportin 1 (selinexor, Xpovio), an ATP-competitive CSF-1R receptor tyrosine kinase inhibitor (pexidartinib,Turalia), a non-ATP-competitive inhibitor of the BCR-Abl fusion protein targeting the myristoyl binding pocket within the kinase catalytic domain of Abl (asciminib, Scemblix), a covalently-acting G12C KRAS inhibitor (sotorasib, Lumakras or Lumykras), an EZH2 methyltransferase inhibitor (tazemostat, Tazverik), and an agent targeting the basic-Helix-Loop-Helix transcription factor HIF-2α (belzutifan, Welireg).

60 APPLIED LIFE SCIENCES↗

Effect of in utero and lactational exposure to antiretroviral therapy on the gut microbial composition and metabolic function in aged rat offspring

Despite the highly effective impact of antiretroviral therapy (ART) in reducing mother-to-child transmission of human immunodeficiency virus (HIV), there are concerns of long-term impacts of ART on the health of the offspring. The implications of perinatal exposure to antiviral drugs on the gut bacterial population and metabolic function in the offspring is unclear but may influence health outcomes given the various reported effects of the microbiome in human health. This study aims to gain insight into the potential effect ofin uteroand lactational exposure to ART on gut microbiota populations and short‐chain fatty acids (SCFAs) production in aged rat offspring. Pregnant rats were administered a combination of antiretroviral drugs (abacavir/dolutegravir/lamivudine) at two different dose levels during gestation and throughout lactation, and the fecal bacterial abundance and SCFA levels of the offspring were analyzed when they reached 12 months of age. Our results showed dose-dependent and sex-based differences in fecal microbial abundance at various taxonomic levels. Specifically, we found a decline inFirmicutesin males, and an increase inActinobacteriaamong males and females. Furthermore, a sex-specific distribution reorganization ofLactobacillus,Bifidobacterium, andAkkermansiawas identified. No significant difference in the concentration of prominent SCFAs and IgA levels were identified. These findings provide preliminary information indicating the need to evaluate perinatal effects of ART more comprehensively on the gut bacterial and metabolic function in future studies, and their potential role in offspring health outcomes.

Research & Experimental Medicine↗

Activation dynamics of a water-soluble human mu-opioid receptor

The mu-opioid receptor (MOR), a class A G protein-coupled receptor mediates opioid analgesia and remains a central target for pain therapeutics. While crystal structures of MOR exist, they provide limited insight into the receptor’s dynamic conformational landscape underlying function. Here, we engineered a thermostable water-soluble MOR variant (wsMOR) that retains native-like ligand-binding and activation dynamics. This variant enables high-yield production and detailed solution-phase structural studies that are challenging with membrane-embedded MOR, providing a valuable tool for studying receptor activation and aqueous-phase drug screening. Using a combined computational and experimental approach, we performed long-timescale all-atom molecular dynamics simulations together with neutron scattering and single-molecule FRET, revealing a structurally stable receptor with a diverse ensemble of conformations at different temporal resolutions. In the ligand-free state, wsMOR displayed high conformational flexibility, which decreased upon agonist binding, particularly in transmembrane helix 6, a hallmark of G protein-coupled receptor activation. Positive allosteric modulation and G protein binding further stabilized active-like states. These findings highlight wsMOR’s conformational plasticity across picosecond to millisecond timescales and provide a foundation for structure-guided development of next-generation opioid ligands with improved efficacy and safety.

E, Agyemang [University of Tennessee Knoxville]↗

Coupling Kinesin Spindle Protein and Aurora B Inhibition with Apoptosis Induction Enhances Oral Cancer Cell Killing

Many proteins regulating mitosis have emerged as targets for cancer therapy, including the kinesin spindle protein (KSP) and Aurora kinase B (AurB). KSP is crucial for proper spindle pole separation during mitosis, while AurB plays roles in chromosome segregation and cytokinesis. Agents targeting KSP and AurB selectively affect dividing cells and have shown significant activity in vitro. However, these drugs, despite advancing to clinical trials, often yield unsatisfactory outcomes as monotherapy, likely due to variable responses driven by cyclin B degradation and apoptosis signal accumulation networks. Accumulated data suggest that combining emerging antimitotics with various cytostatic drugs can enhance tumor-killing effects compared to monotherapy. Here, we investigated the impact of inhibiting anti-apoptotic signals with the BH3-mimetic Navitoclax in oral cancer cells treated with the selective KSP inhibitor, Ispinesib, or AurB inhibitor, Barasertib, aiming to potentiate cell death. The combination of BH3-mimetics with both KSP and AurB inhibitors synergistically induced substantial cell death, primarily through apoptosis. A mechanistic analysis underlying this synergistic activity, undertaken by live-cell imaging, is presented. Our data underscore the importance of combining BH3-mimetics with antimitotics in clinical trials to maximize their effectiveness.

Silva, João P. N. (ORCID:0000000344554286)↗

Combatting melioidosis with chemical synthetic lethality

Burkholderia thailandensishas emerged as a nonpathogenic surrogate forBurkholderia pseudomallei, the causative agent of melioidosis, and an important Gram-negative model bacterium for studying the biosynthesis and regulation of secondary metabolism. We recently reported that subinhibitory concentrations of trimethoprim induce vast changes in both the primary and secondary metabolome ofB. thailandensis. In the current work, we show that the folate biosynthetic enzyme FolE2 is permissive under standard growth conditions but essential forB. thailandensisin the presence of subinhibitory doses of trimethoprim. Reasoning that FolE2 may serve as an attractive drug target, we screened for and identified ten inhibitors, including dehydrocostus lactone (DHL), parthenolide, and β-lapachone, all of which are innocuous individually but form a chemical-synthetic lethal combination with subinhibitory doses of trimethoprim. We show that DHL is a mechanism-based inhibitor of FolE2 and capture the structure of the covalently inhibited enzyme using X-ray crystallography. In vitro, the combination of subinhibitory trimethoprim and DHL is more potent than Bactrim, the current standard of care against melioidosis. Moreover, unlike Bactrim, this combination does not affect the growth of most commensal and beneficial gut bacteria tested, thereby providing a degree of specificity againstB. pseudomallei. Our work provides a path for identifying antimicrobial drug targets and for utilizing binary combinations of molecules that form a toxic cocktail based on metabolic idiosyncrasies of specific pathogens.

Science & Technology - Other Topics↗

A magnetic‐directed micro‐particle with near‐ IR light triggered guest‐release property

Abstract In this study, guest carriers, composed of magnetic‐directed hydrogel particles with near‐infrared (NIR)‐light‐triggered guest‐release properties, are prepared via the one‐pot method. The gel particles contain photostable NIR‐responsive polypyrrole nanoparticles with temperature‐sensitive poly(N‐isopropyl acrylamide), the combination of which can induce the accelerated release of encapsulated drugs by 337% upon 5 minutes of NIR light irradiation based on the release profile of NRMG‐1 at 10–15 min. Additionally, with magnetic iron oxide particles crosslinking the polyvinyl alcohol frames, these gel particles can form a physical barrier that decreases the release rate by 20% under an external magnetic field over 24 h. The magnetic iron oxide particles also enable the gel particles to reach their target destination without extra drug losses.

60 APPLIED LIFE SCIENCES↗

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy

Tuberculosis (TB) is the world’s deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism Mycobacterium tuberculosis (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen’s antibiotic susceptibility. Both rapid identification and rapid antibiotic susceptibility testing of Mtb are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the Mtb complex strain Bacillus Calmette-Guérin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin, and amikacin, as well as a pan-susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and on patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all five BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5,000. We show how this instrument and our machine learning model enable combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

60 APPLIED LIFE SCIENCES↗

NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study

Abstract Neurodegenerative diseases involve progressive neuronal death. Traditional treatments often struggle due to solubility, bioavailability, and crossing the Blood-Brain Barrier (BBB). Nanoparticles (NPs) in biomedical field are garnering growing attention as neurodegenerative disease drugs (NDDs) carrier to the central nervous system. Here, we introduced computational and experimental analysis. In the computational study, a specific IFPTML technique was used, which combined Information Fusion (IF) + Perturbation Theory (PT) + Machine Learning (ML) to select the most promising Nanoparticle Neuronal Disease Drug Delivery (N2D3) systems. For the application of IFPTML model in the nanoscience, NANO.PTML is used. IF-process was carried out between 4403 NDDs assays and 260 cytotoxicity NP assays conducting a dataset of 500,000 cases. The optimal IFPTML was the Decision Tree (DT) algorithm which shown satisfactory performance with specificity values of 96.4% and 96.2%, and sensitivity values of 79.3% and 75.7% in the training (375k/75%) and validation (125k/25%) set. Moreover, the DT model obtained Area Under Receiver Operating Characteristic (AUROC) scores of 0.97 and 0.96 in the training and validation series, highlighting its effectiveness in classification tasks. In the experimental part, two samples of NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) were synthesized by thermal decomposition of an iron(III) oleate (FeOl) precursor and structurally characterized by different methods. Additionally, in order to make the as-synthesized hydrophobic NPs (Fe 3 O 4 _A and Fe 3 O 4 _B) soluble in water the amphiphilic CTAB (Cetyl Trimethyl Ammonium Bromide) molecule was employed. Therefore, to conduct a study with a wider range of NP system variants, an experimental illustrative simulation experiment was performed using the IFPTML-DT model. For this, a set of 500,000 prediction dataset was created. The outcome of this experiment highlighted certain NANO.PTML systems as promising candidates for further investigation. The NANO.PTML approach holds potential to accelerate experimental investigations and offer initial insights into various NP and NDDs compounds, serving as an efficient alternative to time-consuming trial-and-error procedures.

60 APPLIED LIFE SCIENCES↗

Mechanistic Insights into the Successful Development of Combination Therapy of Enfortumab Vedotin and Pembrolizumab for the Treatment of Locally Advanced or Metastatic Urothelial Cancer

Antibody–drug conjugates (ADCs) consist of an antibody backbone that recognizes and binds to a target antigen expressed on tumor cells and a small molecule chemotherapy payload that is conjugated to the antibody via a linker. ADCs are one of the most promising therapeutic modalities for the treatment of various cancers. However, many patients have developed resistance to this form of therapy. Extensive efforts have been dedicated to identifying an effective combination of ADCs with other types of anticancer therapies to potentially overcome this resistance. A recent clinical study demonstrated that a combination of the ADC enfortumab vedotin (EV) with the immune checkpoint inhibitor (ICI) pembrolizumab can achieve remarkable clinical efficacy as the first-line therapy for the treatment of locally advanced or metastatic urothelial carcinoma (la/mUC)—leading to the first approval of a combination therapy of an ADC with an ICI for the treatment of cancer patients. In this review, we highlight knowledge and understanding gained from the successful development of EV and the combination therapy of EV with ICI for the treatment of la/mUC. Using urothelial carcinoma as an example, we will focus on dissecting the underlying mechanisms necessary for the development of this type of combination therapy for a variety of cancers.

Oncology↗

Different chemical scaffolds bind to L-phe site in Mycobacterium tuberculosis Phe-tRNA synthetase

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mt), is one of the deadliest infectious diseases. The rise of multidrug-resistant strains represents a major public health threat, requiring new therapeutic options. Bacterial aminoacyl-tRNA synthetases (aaRS) have been shown to be highly promising drug targets, including for TB treatment. These enzymes play an essential role in translating the DNA gene code into protein sequence by attaching specific amino acid to their cognate tRNAs. They have multiple binding sites that can be targeted for inhibitor discovery: amino acid binding pocket, ATP binding pocket, tRNA binding site and an editing domain. Recently we reported several high-resolution structures of M. tuberculosis phenylalanyl-tRNA synthetase (MtPheRS) complexed with tRNA Phe and either L-Phe or a nonhydrolyzable phenylalanine adenylate analog. Here, in this study, using Nucleic Magnetic Resonance (NMR) and Surface Plasmon Resonance (SPR) we identified fragments that bind to MtPheRS and we determined crystal structures of their complexes with MtPheRS/tRNA Phe . All the binders interact with the L-Phe amino acid binding site. The analysis of interactions of the new compounds combined with adenylate analog structure provides insights for the rational design of antituberculosis drugs. The 3 ' arm of the tRNA Phe in all the structures was disordered with exception of one complex with D-735 compound. In this structure the 3' CCA end of the acceptor stem is observed in the editing domain of MtPheRS providing insights regarding the post-transfer editing activity of class II aaRS.

Gade, Priyanka [Univ. of Chicago, IL (United State↗

Structural basis for varying drug resistance of SARS-CoV-2 M pro E166 variants

ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (M pro ) has an essential role in the virus lifecycle and, accordingly, it is a target for antiviral drugs. Multiple studies have identified an M pro mutation (E166V) that confers strong resistance to clinically relevant inhibitors, including nirmatrelvir, but the underlying mechanism is not fully understood. Here, we report on crystal structures of SARS-CoV-2 M pro E166V in complex with nirmatrelvir, ensitrelvir, and bofutrelvir. The structures suggest that resistance is caused in part by the loss of a direct hydrogen bond and also, especially for nirmatrelvir, by a steric clash with the substituted valine residue. In comparison, the binding of bofutrelvir shows greater flexibility, which may help alleviate this steric effect and allow bofutrelvir to fit the mutant active site despite the loss of a direct polar contact. Thermal stability analyses also corroborate E166V most severely affecting the binding of nirmatrelvir and, to lesser and different extents, ensitrelvir and bofutrelvir. We further show that E166I causes even more severe nirmatrelvir resistance, whereas E166A and E166L have much milder effects. These studies shed light on the molecular mechanisms of a key M pro drug resistance mutation and may help inform the design of next-generation inhibitors. IMPORTANCE Using a combination of high-resolution X-ray crystallographic and biochemical analyses, we reveal the molecular mechanisms by which a mutation in the severe acute respiratory syndrome coronavirus 2 main protease (M pro ) confers strong resistance against clinically relevant antiviral drugs that inhibit M pro activity. The results presented here may help inform the design of next-generation inhibitors to combat the problem of therapy resistance.

Microbiology↗

Modeling aerosol bolus inhalations in the human lung with the multiple path particle deposition model: Comparison with experimental data

Existing one-dimensional (1D) models of aerosol dosimetry often ignore mixing mechanisms of inhaled aerosols during their transport in the lung. This mixing or aerosol dispersion results from different physical mechanisms in different regions of the lung. It is a higher order effect, which cannot be directly captured in 1D modeling approaches, and thus is sometimes modeled as a diffusive process. Here, in this study, we improved our recently developed alveolar mixing module incorporated in the multiple path particle dosimetry model (MPPD) to account for flow irreversibility and particle trapping in the alveolar spaces, as well as mixing occurring in the tracheobronchial region. This new version of MPPD was coupled with CFPD-based predictions of aerosol bolus dispersion in the oral airway. The model was used to predict the deposition, dispersion, and mode shift of aerosol bolus inhaled at different penetration depths within the lung for breathing patterns and particle size matching those used in a previous experimental study (Darquenne et al., 2016). Even though a quite simplified approach was used, the computations appear to describe subject-specific and test-specific experimental data reasonably well. The proposed combined dispersion-deposition model can be a useful tool for targeted drug delivery and also for exposure health risk assessment.

MPPD↗

Novel CHI3L1 ‐Associated Angiogenic Phenotypes Define Glioma Microenvironments: Insights From Multi‐Omics Integration

ABSTRACT The CHI3L1 signaling pathway significantly influences glioma angiogenesis, but its role in the tumor microenvironment (TME) remains elusive. We propose a novelCHI3L1‐associated vascular phenotype classification for glioma through integrative analyses of multiple datasets with bulk and single‐cell transcriptome, genomics, digital pathology, and clinical data. We investigated the biological characteristics, genomic alterations, therapeutic vulnerabilities, and immune profiles within these phenotypes through a comprehensive multi‐omics approach. We constructed the vascular‐related risk (VR) score based onCHI3L1‐associated vascular signatures (CAVS) identified by machine learning algorithms. Utilizing unsupervised consensus clustering, gliomas were stratified into three distinct vascular phenotypes: Cluster A, marked by high vascularization and stromal activation with a relatively low levels of tumor‐infiltrating lymphocytes (TILs); Cluster B, characterized by moderate vascularization and stromal activity, coupled with a high density of TILs; and Cluster C, defined by low vascularization and sparse immune cell infiltration. We observed that the CAVS effectively indicated glioma‐associated angiogenesis and immune suppression by single‐cell RNA‐seq analysis. Moreover, the high‐VR‐score group exhibited enhanced angiogenic activity, reduced immune response, resistance to immunotherapy, and poorer clinical outcomes. The VR score independently predicted glioma prognosis and, combined with a nomogram, provided a robust clinical decision‐making tool. Potential drug prediction based on transcription factors for high‐risk patients was also performed. Our study reveals thatCHI3L1‐associated vascular phenotypes shape distinct immune landscapes in gliomas, offering insights for optimizing therapeutic strategies to improve patient outcomes.

Oncology↗

A goldilocks computational protocol for inhibitor discovery targeting DNA damage responses including replication-repair functions

While many researchers can design knockdown and knockout methodologies to remove a gene product, this is mainly untrue for new chemical inhibitor designs that empower multifunctional DNA Damage Response (DDR) networks. Here, we present a robust Goldilocks (GL) computational discovery protocol to efficiently innovate inhibitor tools and preclinical drug candidates for cellular and structural biologists without requiring extensive virtual screen (VS) and chemical synthesis expertise. By computationally targeting DDR replication and repair proteins, we exemplify the identification of DDR target sites and compounds to probe cancer biology. Our GL pipeline integrates experimental and predicted structures to efficiently discover leads, allowing early-structure and early-testing (ESET) experiments by many laboratories. By employing an efficient VS protocol to examine protein-protein interfaces (PPIs) and allosteric interactions, we identify ligand binding sites beyond active sites, leveraging in silico advances for molecular docking and modeling to screen PPIs and multiple targets. A diverse 3,174 compound ESET library combines Diamond Light Source DSI-poised, Protein Data Bank fragments, and FDA-approved drugs to span relevant chemotypes and facilitate downstream hit evaluation efficiency for academic laboratories. Two VS per library and multiple ranked ligand binding poses enable target testing for several DDR targets. This GL library and protocol can thus strategically probe multiple DDR network targets and identify readily available compounds for early structural and activity testing to overcome bottlenecks that can limit timely breakthrough drug discoveries. By testing accessible compounds to dissect multi-functional DDRs and suggesting inhibitor mechanisms from initial docking, the GL approach may enable more groups to help accelerate discovery, suggest new sites and compounds for challenging targets including emerging biothreats and advance cancer biology for future precision medicine clinical trials.

59 BASIC BIOLOGICAL SCIENCES↗

Transient histone deacetylase inhibition reveals cell type invariant and specific effects of chromatin decondensation on irradiation response

Radiation therapy plays a prominent role in breast cancer treatment, but the high doses of radiation damage both healthy and cancerous cells. Therefore, additional research is needed into combination therapies that could preferentially radiosensitize cancer cells compared to surrounding healthy tissue without causing deleterious side effects. Histone deacetylase inhibitor drugs (HDACis) have been tested as radiosensitizers in both basic research and clinical trials, but the long exposure time typically used in these treatments and the lack of matched healthy cell controls often leave aspects of their mechanism of action unclear. Here, we show that transient (2 h) trichostatin A (TSA) treatment of cancerous and non-tumorigenic breast epithelial cell lines increases immediate DNA damage and decreases long term cell viability in both cell types at high radiation doses. Transient TSA treatment also causes an increase in DNA damage signals after 5 Gy X-rays in other cancer and healthy cell types: A375 melanoma cells and BJ5-ta fibroblasts. This suggests that chromatin decompaction acts to increase cellular vulnerability to initial DNA damage from high doses of radiation in a cell type independent manner that does not rely on changes to DNA repair pathways caused by longer TSA treatment. However, responses to lower doses of radiation and long term survival are more cell type specific: only MCF7 cells experience an effect of TSA on DNA damage after 1 Gy X-ray radiation while MCF10a cells experience somewhat more evident cell viability effects of combined TSA and radiation treatment long term.

Li, Heng [Biochemistry & Cellular and Molecular Bi↗