Int J Mol Sci. 2024 Dec 14;25(24):13424. doi: 10.3390/ijms252413424.

ABSTRACT

The predominant neurodegenerative diseases, Alzheimer's disease, Parkinson's disease, dementia with Lewy Bodies, Huntington's disease, amyotrophic lateral sclerosis, and frontotemporal dementia, are rarely pure diseases but, instead, show a diversity of mixed pathologies. At some level, all of them share a combination of one or more different toxic biomarker proteins: amyloid beta (Aβ), phosphorylated Tau (pTau), alpha-synuclein (αSyn), mutant huntingtin (mHtt), fused in sarcoma, superoxide dismutase 1, and TAR DNA-binding protein 43. These toxic proteins share some common attributes, making them potentially universal and simultaneous targets for therapeutic intervention. First, they all form toxic aggregates prior to taking on their final forms as contributors to plaques, neurofibrillary tangles, Lewy bodies, and other protein deposits. Second, the primary enzyme that directs their aggregation is transglutaminase 2 (TGM2), a brain-localized enzyme involved in neurodegeneration. Third, TGM2 binds to calmodulin, a regulatory event that can increase the activity of this enzyme threefold. Fourth, the most common mixed pathology toxic biomarkers (Aβ, pTau, αSyn, nHtt) also bind calmodulin, which can affect their ability to aggregate. This review examines the potential therapeutic routes opened up by this knowledge. The end goal reveals multiple opportunities that are immediately available for universal therapeutic treatment of the most devastating neurodegenerative diseases facing humankind.

PMID:39769187 | DOI:10.3390/ijms252413424

Int J Mol Sci. 2024 Dec 14;25(24):13418. doi: 10.3390/ijms252413418.

ABSTRACT

The complex and heterogeneous genomic landscape of multiple myeloma (MM) and many of its clinical and prognostic implications remains to be understood. In other cancers, such as breast cancer, using whole-exome sequencing (WES) and molecular signatures in clinical practice has revolutionized classification, prognostic prediction, and patient management. However, such integration is still in its early stages in MM. In this study, we analyzed WES data from 35 MM patients to identify potential mutational signatures and driver mutations correlated with clinical and cytogenetic characteristics. Our findings confirm the complex mutational spectrum and its impact on previously described ontogenetic and epigenetic pathways. They show TYW1 as a possible new potential driver gene and find no significant associations of mutational signatures with clinical findings. Further studies are needed to strengthen the role of mutational signatures in the clinical context of patients with MM to improve patient management.

PMID:39769182 | DOI:10.3390/ijms252413418

Diagnostics (Basel). 2024 Dec 18;14(24):2848. doi: 10.3390/diagnostics14242848.

ABSTRACT

BACKGROUND: This study investigated whether point-of-care platelet function measurements could predict favorable outcomes in patients with acute ischemic stroke (AIS). Antiplatelet agents, such as aspirin, are known to reduce the risk of recurrent stroke by 20-30%. However, identifying nonresponders to therapy remains a clinical challenge. The study aimed to assess the prognostic value of serial Platelet Function Analyzer (PFA)-100 measurements and hematological ratios in AIS patients.

METHODS: A prospective cohort study was conducted on 212 AIS patients in Taiwan. Platelet function was assessed at baseline, week 2, and week 4 using PFA-100. The primary outcome was functional recovery, defined by a modified Rankin Scale (mRS) score of 0-3, at 1-month and 1-year. Subgroup analyses compared outcomes between pre- and post-aspirin administrations. Statistical analyses examined the association between changes in platelet function and clinical outcomes.

RESULTS: Difference in collagen and epinephrine (CEPI) measurements between baseline and week 2 was associated with favorable mRS scores (p < 0.001). A difference in CEPI closure time greater than 99 seconds was most predictive of a favorable outcome with an adjusted odds ratio of 11.859 (95% CI 2.318-60.669) at 1-month follow-up. Subgroup analyses revealed predictive value in pre-aspirin measurements at 1-month follow-up (p = 0.007).

CONCLUSIONS: Serial PFA-100 measurements and hematological biomarkers, specifically changes in on-treatment CEPI closure times, may help predict favorable clinical outcome in AIS patients. These findings suggest that dynamic platelet function assessment could play a role in optimizing antiplatelet therapy in AIS management.

PMID:39767209 | DOI:10.3390/diagnostics14242848

Genes (Basel). 2024 Dec 15;15(12):1602. doi: 10.3390/genes15121602.

ABSTRACT

BACKGROUND/OBJECTIVES: Neural differentiation requires a multifaceted program to alter gene expression along the proliferation to the differentiation axis. While critical changes occur at the level of transcription, post-transcriptional mechanisms allow fine-tuning of protein output. We investigated the role of tRNAs in regulating gene expression during neural differentiation in Drosophila larval brains.

METHODS: We quantified tRNA abundance in neural progenitor-biased and neuron-biased brains using the hydrotRNA-seq method. These tRNA data were combined with cell type-specific mRNA decay measurements and transcriptome profiles in order to model how tRNA abundance affects mRNA stability and translation efficiency.

RESULTS: We found that (1) tRNA abundance is largely constant between neural progenitors and neurons but significant variation exists for 10 nuclear tRNA genes and 8 corresponding anticodon groups, (2) tRNA abundance correlates with codon-mediated mRNA decay in neuroblasts and neurons, but does not completely explain the different stabilizing or destabilizing effects of certain codons, and (3) changes in tRNA levels support a shift in translation optimization from a program supporting proliferation to a program supporting differentiation.

CONCLUSIONS: These findings reveal coordination between tRNA expression and codon usage in transcripts that regulate neural development.

PMID:39766869 | DOI:10.3390/genes15121602

Genes (Basel). 2024 Nov 27;15(12):1530. doi: 10.3390/genes15121530.

ABSTRACT

BACKGROUND: In the realm of system biology, it is a challenging endeavor to infer a gene regulatory network from time-series gene expression data. Numerous Boolean network inference techniques have emerged for reconstructing a gene regulatory network from a time-series gene expression dataset. However, most of these techniques pose scalability concerns given their capability to consider only two to three regulatory genes over a specific target gene.

METHODS: To overcome this limitation, a novel inference method, LBF-MI, has been proposed in this research. This two-phase method utilizes limited Boolean functions and multivariate mutual information to reconstruct a Boolean gene regulatory network from time-series gene expression data. Initially, Boolean functions are applied to determine the optimum solutions. In case of failure, multivariate mutual information is applied to obtain the optimum solutions.

RESULTS: This research conducted a performance-comparison experiment between LBF-MI and three other methods: mutual information-based Boolean network inference, context likelihood relatedness, and relevance network. When examined on artificial as well as real-time-series gene expression data, the outcomes exhibited that the proposed LBF-MI method outperformed mutual information-based Boolean network inference, context likelihood relatedness, and relevance network on artificial datasets, and two real Escherichia coli datasets (E. coli gene regulatory network, and SOS response of E. coli regulatory network).

CONCLUSIONS: LBF-MI's superior performance in gene regulatory network inference enables researchers to uncover the regulatory mechanisms and cellular behaviors of various organisms.

PMID:39766797 | DOI:10.3390/genes15121530

Antibiotics (Basel). 2024 Dec 2;13(12):1154. doi: 10.3390/antibiotics13121154.

ABSTRACT

Background: Klebsiella pneumoniae is an opportunistic pathogen that causes a wide range of infections worldwide. The emergence and spread of multidrug-resistant clones requires the implementation of novel therapeutics, and phages are a promising approach. Results: In this study, two Klebsiella phages, KpTDp1 and KpTDp2, were isolated from wastewater samples in Tunisia. These phages had a narrow host range and specifically targeted the hypervirulent K2 and K28 capsular types of K. pneumoniae. Both phages have double-stranded linear DNA genomes of 49,311 and 49,084 bp, respectively. Comparative genomic and phylogenetic analyses placed phage KpTDp2 in the genus Webervirus, while phage KpTDp1 showed some homology with members of the genus Jedunavirus, although its placement in a new undescribed genus may be reconsidered. The replication efficiency and lytic ability of these phages, combined with their high stability at temperatures up to 70 °C and pH values ranging from 3.5 to 8.2, highlight the potential of these phages as good candidates for the control of hypervirulent multidrug-resistant K. pneumoniae. Methods: Phage isolation, titration and multiplicity of infection were performed. The stability of KpTDp1 and KpTDp2 was tested at different pH and temperatures. Genomic characterization was done by genome sequencing, annotation and phylogenetic analysis. Conclusions: The ability of KpTDp1 and KpTDp2 to lyse one of the most virulent serotypes of K. pneumoniae, as well as the stability of their lytic activities to pH and temperature variations, make these phages promising candidates for antibacterial control.

PMID:39766544 | DOI:10.3390/antibiotics13121154

Brain Sci. 2024 Nov 25;14(12):1180. doi: 10.3390/brainsci14121180.

ABSTRACT

Accurate identification and functional annotation of splicing isoforms and non-coding RNAs (lncRNAs), alongside full-length protein-encoding transcripts, are critical for understanding gene (mis)regulation and metabolic reprogramming in Alzheimer's disease (AD). This study aims to provide a comprehensive and accurate transcriptome resource to improve existing AD transcript databases. Background/Objectives: Gene mis-regulation and metabolic reprogramming play a key role in AD, yet existing transcript databases lack accurate and comprehensive identification of splicing isoforms and lncRNAs. This study aims to generate a refined transcriptome dataset, expanding the understanding of AD onset and progression. Methods: Publicly available RNA-seq data from pre-AD and AD tissues were utilized. Advanced bioinformatics tools were applied to assemble and annotate full-length transcripts, including splicing isoforms and lncRNAs, with an emphasis on correcting errors and enhancing annotation accuracy. Results: A significantly improved transcriptome dataset was generated, which includes detailed annotations of splicing isoforms and lncRNAs. This dataset expands the scope of existing AD transcript databases and provides new insights into the molecular mechanisms underlying AD. The findings demonstrate that the refined dataset captures more relevant details about AD progression compared to publicly available data. Conclusions: The newly developed transcriptome resource and the associated analysis tools offer a valuable contribution to AD research, providing deeper insights into the disease's molecular mechanisms. This work supports future research into gene regulation and metabolic reprogramming in AD and serves as a foundation for exploring novel therapeutic targets.

PMID:39766379 | DOI:10.3390/brainsci14121180

Biomolecules. 2024 Dec 14;14(12):1599. doi: 10.3390/biom14121599.

ABSTRACT

Extracellular vesicles (EVs) are lipid bilayer nanoparticles released from all known cells and are involved in cell-to-cell communication via their molecular content. EVs have been found in all tissues and body fluids, carrying a variety of biomolecules, including DNA, RNA, proteins, metabolites, and lipids, offering insights into cellular and pathophysiological conditions. Despite the emergence of EVs and their molecular contents as important biological indicators, it remains difficult to explore EV-mediated biological processes due to their small size and heterogeneity and the technical challenges in characterizing their molecular content. EV-associated small RNAs, especially microRNAs, have been extensively studied. However, other less characterized RNAs, including protein-coding mRNAs, long noncoding RNAs, circular RNAs, and tRNAs, have also been found in EVs. Furthermore, the EV-associated proteins can be used to distinguish different types of EVs. The spectrum of EV-associated RNAs, as well as proteins, may be associated with different pathophysiological conditions. Therefore, the ability to comprehensively characterize EVs' molecular content is critical for understanding their biological function and potential applications in disease diagnosis. Here, we set out to provide an overview of EV-associated RNAs and proteins as well as approaches currently being used to characterize them.

PMID:39766306 | DOI:10.3390/biom14121599

Biomolecules. 2024 Nov 27;14(12):1513. doi: 10.3390/biom14121513.

ABSTRACT

Immune checkpoint inhibitors, such as anti-PD-1 antibodies, represent a significant advancement in cancer immunotherapy, but their efficacy varies notably between individuals, influenced by complex biological systems. Recent evidence suggests that sex-related biological differences play a pivotal role in modulating these responses. This study uses a systems biology approach to examine how sex-specific differences in the immune system contribute to variability in the response to treatment. Our model extends previous frameworks by incorporating sex-specific parameters that reflect observed immunological distinctions. The results from the simulation studies align with our clinical observations, showing that on average, males exhibit a more robust response to anti-PD-1 treatment compared to females. Additionally, this study explores the potential of combination therapy with recombinant IL-12, revealing sex-specific differences in treatment efficacy. These findings underscore the need for personalized immunotherapy strategies that consider individual immunological profiles, including sex, to optimize treatment outcomes.

PMID:39766221 | DOI:10.3390/biom14121513

Antioxidants (Basel). 2024 Dec 5;13(12):1485. doi: 10.3390/antiox13121485.

ABSTRACT

Elaeagnus latifolia (EL) is a wild fruit known for containing several health-promoting compounds. This study aimed to evaluate the effects of EL fruit extract on high-fat diet (HFD)-induced obesity and lipopolysaccharide (LPS)-activated macrophages. Mice fed an HFD and given EL fruit extract for 10 weeks exhibited significantly lower body weight, reduced lipid accumulation, diminished oxidative stress in adipocytes, and decreased macrophage infiltration compared to those not receiving the EL extract. Moreover, the EL fruit extract activated the transcription factors Pparg and Cebpa, initiating adipogenesis and modulating the expression of NF-κB/Nrf-2-induced target genes. This resulted in smaller adipocyte size, reduced inflammation, and less oxidative stress in HFD-fed mice. In vitro, the EL extract induced a shift in macrophage phenotype from M1 to M2, reduced IκBα/NF-κB phosphorylation, and effectively decreased energy production in macrophages by downregulating the expression of several proteins involved in glycolysis and the tricarboxylic acid cycle. This mechanistic study suggests that administering EL fruit extract could be an effective strategy for managing obesity and its associated pathologies.

PMID:39765814 | DOI:10.3390/antiox13121485

Biology (Basel). 2024 Dec 7;13(12):1025. doi: 10.3390/biology13121025.

ABSTRACT

The journal Biology was launched in 2012 [...].

PMID:39765692 | DOI:10.3390/biology13121025

Syst Appl Microbiol. 2025 Jan 3;48(1):126579. doi: 10.1016/j.syapm.2025.126579. Online ahead of print.

ABSTRACT

Six novel Bifidobacterium strains H1HS16NT, Bin2N, Hma3N, H6bp22N, H1HS10N, and H6bp9N, were isolated from the honey stomach of Apis mellifera. Cells are Gram-positive, non-motile, non-sporulating, facultatively anaerobic, and fructose 6-phosphate phosphoketolase-positive. Optimal growth conditions occur at 37 °C in anaerobiosis in MRS medium added with 2 % fructose and 0.1 % L-cysteine. The 16S rRNA gene sequences analysis revealed clustering with Bifidobacterium species found in honeybees. Strains Hma3N, H6bp22N, and H1HS16NT showed significant similarity to Bifidobacterium polysaccharolyticum JCM 34588T, with an average similarity of 99.63 %. In contrast, strains Bin2N, H1HS10N, and H6bp9N were closely related to Bifidobacterium apousia JCM 34587T, with an average similarity of 99.22 %. Moreover, strains Hma3N and H6bp22N exhibited ANI values of 96.65 % and 96.53 % when compared to Bifidobacterium polysaccharolyticum JCM 34588T, while strains H1HS16NT, Bin2N, H6bp9N, and H1HS10N revealed ANI values of 94.18 %, 94.33 %, 94.22 %, and 95.50 % respectively when compared to B. apousia JCM 34587T. dDDH analysis confirmed that strains Hma3N and H6bp22N belong to B. polysaccharolyticum, whereas strains H1HS16NT, Bin2N, H6bp9N, and H1HS10N represent a novel species. The peptidoglycan of the novel species is of the A4α type (L-Lys-D-Asp). The main cellular fatty acids of the type strain H1HS16NT are C16:0, C14:0, C19:0 cyclo ω9c, and C18:1 ω9c. The DNA G + C content of the type strain is 60.8 mol%. Genome analyses of the strains were also conducted to determine their biosynthesis-related gene clusters, probiotic features, and ecological distribution patterns. Phenotypic and genotypic characterization show that strain H1HS16NT is distinct from the type strains of other recognized Bifidobacterium species. Thus, Bifidobacterium kimbladii sp. nov. (H1HS16NT = DSM 115187T = CCUG 76695T) is proposed as a novel Bifidobacterium species.

PMID:39764984 | DOI:10.1016/j.syapm.2025.126579

Brief Bioinform. 2024 Nov 22;26(1):bbae685. doi: 10.1093/bib/bbae685.

ABSTRACT

Spatial transcriptomics (ST) technologies enable dissecting the tissue architecture in spatial context. To perceive the global contextual information of gene expression patterns in tissue, the spatial dependence of cells must be fully considered by integrating both local and non-local features by means of spatial-context-aware. However, the current ST integration algorithm ignores for ST dropouts, which impedes the spatial-aware of ST features, resulting in challenges in the accuracy and robustness of microenvironmental heterogeneity detecting, spatial domain clustering, and batch-effects correction. Here, we developed an STMGraph, a universal dual-view dynamic deep learning framework that combines dual-remask (MASK-REMASK) with dynamic graph attention model (DGAT) to exploit ST data outperforming pre-existing tools. The dual-remask mechanism masks the embeddings before encoding and decoding, establishing dual-decoding-view to share features mutually. DGAT leverages self-supervision to update graph linkage relationships from two distinct perspectives, thereby generating a comprehensive representation for each node. Systematic benchmarking against 10 state-of-the-art tools revealed that the STMGraph has the optimal performance with high accuracy and robustness on spatial domain clustering for the datasets of diverse ST platforms from multi- to sub-cellular resolutions. Furthermore, STMGraph aggregates ST information cross regions by dual-remask to realize the batch-effects correction implicitly, allowing for spatial domain clustering of ST multi-slices. STMGraph is platform independent and superior in spatial-context-aware to achieve microenvironmental heterogeneity detection, spatial domain clustering, batch-effects correction, and new biological discovery, and is therefore a desirable novel tool for diverse ST studies.

PMID:39764614 | DOI:10.1093/bib/bbae685

Front Microbiol. 2024 Dec 23;15:1504418. doi: 10.3389/fmicb.2024.1504418. eCollection 2024.

ABSTRACT

INTRODUCTION: WhiA is a conserved protein found in numerous bacteria. It consists of an HTH DNA-binding domain linked with a homing endonuclease (HEN) domain. WhiA is one of the most conserved transcription factors in reduced bacteria of the class Mollicutes. Its function in Mollicutes is unknown, while it is well-characterized in Streptomyces. Here, we focused on WhiA protein from Mycoplasma gallisepticum.

METHODS: We used a combination molecular dynamics, EMSA, MST and AFM to study the DNA-binding and ATP-binding properties of WhiA from M. gallisepticum. The transcriptional repressor function of WhiA was demonstrated using gene knockdown, reporter constructs and proteome analysis.

RESULTS: We demonstrate that WhiA homolog from M. gallisepticum binds a conserved sequence of the GAYACRCY core (Y = C or T, R = A or G), which is located in the promoter of an operon coding for ribosomal proteins and adenylate kinase (rpsJ operon). We show that WhiA in M. gallisepticum is a repressor of rpsJ operon and a sensor of ATP. HTH domain binds to the core motif and HEN domain binds to the auxiliary motif GTTGT that is located downstream to the core motif. We show that binding by both domains to DNA is required to fulfill the transcription repressor function. Knockdown of whiA does not affect actively growing M. gallisepticum, but leads to the growth retardation after freezing.

DISCUSSION: We propose the following model for M. gallisepticum WhiA function. WhiA remains bound to the core motif at any conditions. At low ATP concentrations (starvation) HEN domain binds auxiliary motif and represses rpsJ operon transcription. At high ATP concentrations (nutrient-rich conditions) HEN domain binds ATP and releases auxiliary motif. It leads to the de-repression of rpsJ operon and increased production of ribosomal proteins.

PMID:39764455 | PMC:PMC11701221 | DOI:10.3389/fmicb.2024.1504418

Front Plant Sci. 2024 Dec 23;15:1542150. doi: 10.3389/fpls.2024.1542150. eCollection 2024.

NO ABSTRACT

PMID:39764239 | PMC:PMC11701225 | DOI:10.3389/fpls.2024.1542150

bioRxiv [Preprint]. 2024 Dec 26:2024.12.23.630107. doi: 10.1101/2024.12.23.630107.

ABSTRACT

Obesity is a global health crisis, with its prevalence particularly severe in the United States, where over 42% of adults are classified as obese. Obesity is driven by complex molecular and tissue-level mechanisms that remain poorly understood. Among these, angiogenesis-primarily mediated by vascular endothelial growth factor (VEGF-A)-is critical for adipose tissue expansion but presents unique challenges for therapeutic targeting due to its intricate regulation. Systems biology approaches have advanced our understanding of VEGF-A signaling in vascular diseases, but their application to obesity is limited by scattered and sometimes contradictory data. To address this gap, we performed a comprehensive analysis of the existing literature to synthesize key findings, standardize data, and provide a holistic perspective on the adipose vascular microenvironment. The data mining revealed five key findings: (1) obesity increases adipocyte size by 78%; (2) vessel density in adipose tissue decreases by 51% in obese mice, with vessels being 47-58% smaller and 4-9 times denser in comparison with tumor vessels; (3) capillary basement membrane thickness remains similar regardless of obesity; (4) VEGF-A shows the strongest binding affinity for VEGFR1, with four times stronger affinity for VEGFR2 than for NRP1; and (5) binding affinities measured by radioligand binding assay and surface plasmon resonance (SPR) are significantly different. These consolidated findings provide essential parameters for systems biology modeling, new insights into obesity-induced changes in adipose tissue, and a foundation for developing angiogenesis-targeting therapies for obesity.

PMID:39763822 | PMC:PMC11703262 | DOI:10.1101/2024.12.23.630107

New Phytol. 2025 Jan 6. doi: 10.1111/nph.20386. Online ahead of print.

NO ABSTRACT

PMID:39763115 | DOI:10.1111/nph.20386

J Texture Stud. 2025 Feb;56(1):e70001. doi: 10.1111/jtxs.70001.

ABSTRACT

The increasing demand for protein-rich, plant-based foods has driven the development of meat analogs that closely mimic the texture and mouthfeel of animal meat. While plant-based fibrils and electrospun silk fibroin fibers have been explored for texture enhancement and scaffolding in both meat analogs and cell-based meats, the use of wet-spun fibroin protein fibers as a food ingredient remains underexplored. This study investigates the potential of wet-spun recombinant fibroin fibers to enhance the textural properties of meat analogs. Short fibers, with varying tensile strengths and diameters, were incorporated into a commercial ground pork analog to create improved patty samples. The results showed that adding hydrophilic, 30 μm-diameter, 3-mm short protein fibers at 1% (w/w) significantly increased the springiness of the pork analog by 45%. Additionally, fiber sheets designed to mimic the endomysium structure of intramuscular connective tissue were integrated into the minced pork analog using a three-dimensional needle punching technique. This approach successfully recreated the interlacing endomysium structure found in whole-muscle pork, yielding a texture that closely matched the slice shear force, springiness, and cohesiveness of traditional pork. In conclusion, the incorporation of wet-spun protein fibers offers a promising strategy to enhance the textural qualities of meat analogs, making them more comparable to animal meat and potentially more appealing to consumers seeking high-quality plant-based alternatives.

PMID:39762716 | DOI:10.1111/jtxs.70001

Funct Integr Genomics. 2025 Jan 6;25(1):8. doi: 10.1007/s10142-024-01514-9.

ABSTRACT

Gene‒gene interactions play pivotal roles in disease pathogenesis and are fundamental in the development of targeted therapeutics, particularly through the elucidation of oncogenic gene drivers in cancer. The systematic analysis of pathways and gene interactions is critical in the drug discovery process for various cancer subtypes. SPAG5, known for its role in spindle formation during cell division, has been identified as an oncogene in several cancers, although its specific impact on AML remains underexplored. This study leverages a high-throughput swarm-based deep neural network (SDNN) and transcriptomic data-an approach that enhances predictive accuracy and robustness through collective intelligence-to augment, model, and enhance the understanding of the TP53 pathway in AML cohorts. Our integrative systems biology approach identified SPAG5 as a uniquely downregulated driver in adult AML, underscoring its potential as a novel therapeutic target. The interaction of SPAG5 with key hub genes such as MDM2 and CDK1 not only reinforces its role in tumour suppression through negative regulation but also highlights its potential in moderating the phenotypic and genomic alterations associated with AML progression. This study of the role and interaction dynamics of SPAG5 sets the stage for future research aimed at developing targeted and personalized treatment approaches for AML, utilizing the capabilities of genetic interventions.

PMID:39762615 | DOI:10.1007/s10142-024-01514-9

Cell Death Differ. 2025 Jan 6. doi: 10.1038/s41418-024-01431-1. Online ahead of print.

ABSTRACT

Cellular senescence contributes to a variety of pathologies associated with aging and is implicated as a cellular state in which cancer cells can survive treatment. Reported senolytic drug treatments act through varying molecular mechanisms, but heterogeneous efficacy across the diverse contexts of cellular senescence indicates a need for predictive biomarkers of senolytic activity. Using multi-parametric analyses of commonly reported molecular features of the senescent phenotype, we assayed a variety of models, including malignant and nonmalignant cells, using several triggers of senescence induction and found little univariate predictive power of these traditional senescence markers to identify senolytic drug sensitivity. We sought to identify novel drug targets in senescent cells that were insensitive to frequently implemented senolytic therapies, such as Navitoclax (ABT-263), using quantitative mass spectrometry to measure changes in the senescent proteome, compared to cells which acquire an acute sensitivity to ABT-263 with senescence induction. Inhibition of the antioxidant GPX4 or the Bcl-2 family member MCL-1 using small molecule compounds in combination with ABT-263 significantly increased the induction of apoptosis in some, but not all, previously insensitive senescent cells. We then asked if we could use BH3 profiling to measure differences in mitochondrial apoptotic priming in these models of cellular senescence and predict sensitivity to the senolytics ABT-263 or the combination of dasatinib and quercetin (D + Q). We found, despite being significantly less primed for apoptosis overall, the dependence of senescent mitochondria on BCL-XL was significantly correlated to senescent cell killing by both ABT-263 and D + Q, despite no significant changes in the gene or protein expression of BCL-XL. However, our data caution against broad classification of drugs as globally senolytic and instead provide impetus for context-specific senolytic targets and propose BH3 profiling as an effective predictive biomarker.

PMID:39762561 | DOI:10.1038/s41418-024-01431-1