Genet Sel Evol. 2024 Nov 15;56(1):72. doi: 10.1186/s12711-024-00942-2.

ABSTRACT

BACKGROUND: Genotype imputation is a cost-effective method for obtaining sequence genotypes for downstream analyses such as genome-wide association studies (GWAS). However, low imputation accuracy can increase the risk of false positives, so it is important to pre-filter data or at least assess the potential limitations due to imputation accuracy. In this study, we benchmarked three different imputation programs (Beagle 5.2, Minimac4 and IMPUTE5) and compared the empirical accuracy of imputation with the software estimated accuracy of imputation (Rsqsoft). We also tested the accuracy of imputation in cattle for autosomal and X chromosomes, SNP and INDEL, when imputing from either low-density or high-density genotypes.

RESULTS: The accuracy of imputing sequence variants from real high-density genotypes was higher than from low-density genotypes. In our software benchmark, all programs performed well with only minor differences in accuracy. While there was a close relationship between empirical imputation accuracy and the imputation Rsqsoft, this differed considerably for Minimac4 compared to Beagle 5.2 and IMPUTE5. We found that the Rsqsoft threshold for removing poorly imputed variants must be customised according to the software and this should be accounted for when merging data from multiple studies, such as in meta-GWAS studies. We also found that imposing an Rsqsoft filter has a positive impact on genomic regions with poor imputation accuracy due to large segmental duplications that are susceptible to error-prone alignment. Overall, our results showed that on average the imputation accuracy for INDEL was approximately 6% lower than SNP for all software programs. Importantly, the imputation accuracy for the non-PAR (non-Pseudo-Autosomal Region) of the X chromosome was comparable to autosomal imputation accuracy, while for the PAR it was substantially lower, particularly when starting from low-density genotypes.

CONCLUSIONS: This study provides an empirically derived approach to apply customised software-specific Rsqsoft thresholds for downstream analyses of imputed variants, such as needed for a meta-GWAS. The very poor empirical imputation accuracy for variants on the PAR when starting from low density genotypes demonstrates that this region should be imputed starting from a higher density of real genotypes.

PMID:39548370 | DOI:10.1186/s12711-024-00942-2

NPJ Syst Biol Appl. 2024 Nov 16;10(1):134. doi: 10.1038/s41540-024-00468-9.

ABSTRACT

Phosphosignaling networks control cellular processes. We built kinase-mediated regulatory networks elicited by thrombin stimulation of brain endothelial cells using two computational strategies: Temporal Pathway Synthesizer (TPS), which uses phosphoproteomics data as input, and Temporally REsolved KInase Network Generation (TREKING), which uses kinase inhibitor screens. TPS and TREKING predicted overlapping barrier-regulatory kinases connected with unique network topology. Each strategy effectively describes regulatory signaling networks and is broadly applicable across biological systems.

PMID:39548089 | DOI:10.1038/s41540-024-00468-9

Nat Microbiol. 2024 Nov 15. doi: 10.1038/s41564-024-01843-2. Online ahead of print.

ABSTRACT

Chemical cues mediate interactions between marine phytoplankton and bacteria, underpinning ecosystem-scale processes including nutrient cycling and carbon fixation. Phage infection alters host metabolism, stimulating the release of chemical cues from intact plankton, but how these dynamics impact ecology and biogeochemistry is poorly understood. Here we determine the impact of phage infection on dissolved metabolite pools from marine cyanobacteria and the subsequent chemotactic response of heterotrophic bacteria using time-resolved metabolomics and microfluidics. Metabolites released from intact, phage-infected Synechococcus elicited strong chemoattraction from Vibrio alginolyticus and Pseudoalteromonas haloplanktis, especially during early infection stages. Sustained bacterial chemotaxis occurred towards live-infected Synechococcus, contrasted by no discernible chemotaxis towards uninfected cyanobacteria. High-throughput microfluidics identified 5'-deoxyadenosine and 5'-methylthioadenosine as key attractants. Our findings establish that, before lysis, phage-infected picophytoplankton release compounds that attract motile heterotrophic bacteria, suggesting a mechanism for resource transfer that might impact carbon and nutrient fluxes across trophic levels.

PMID:39548345 | DOI:10.1038/s41564-024-01843-2

Nat Cell Biol. 2024 Nov 15. doi: 10.1038/s41556-024-01550-4. Online ahead of print.

ABSTRACT

Cell state dynamics underlying successful tissue regeneration are undercharacterized. In the intestine, damage prompts epithelial reprogramming into revival stem cells (revSCs) that reconstitute Lgr5+ intestinal stem cells (ISCs). Here single-nuclear multi-omics of mouse crypts regenerating from irradiation shows revSC chromatin accessibility overlaps with ISCs and differentiated lineages. While revSC genes themselves are accessible throughout homeostatic epithelia, damage-induced remodelling of chromatin in the crypt converges on Hippo and the transforming growth factor-beta (TGFβ) signalling pathway, which we show is transiently activated and directly induces functional revSCs. Combinatorial gene expression analysis further suggests multiple sources of revSCs, and we demonstrate TGFβ can reprogramme enterocytes, goblet and paneth cells into revSCs and show individual revSCs form organoids. Despite this, loss of TGFβ signalling yields mild regenerative defects, whereas interference in both Hippo and TGFβ leads to profound defects and death. Intestinal regeneration is thus poised for activation by a compensatory system of crypt-localized, transient morphogen cues that support epithelial reprogramming and robust intestinal repair.

PMID:39548329 | DOI:10.1038/s41556-024-01550-4

Mol Syst Biol. 2024 Nov 15. doi: 10.1038/s44320-024-00073-2. Online ahead of print.

ABSTRACT

Eukaryotic mRNAs are transcribed, processed, translated, and degraded in different subcellular compartments. Here, we measured mRNA flow rates between subcellular compartments in mouse embryonic stem cells. By combining metabolic RNA labeling, biochemical fractionation, mRNA sequencing, and mathematical modeling, we determined the half-lives of nuclear pre-, nuclear mature, cytosolic, and membrane-associated mRNAs from over 9000 genes. In addition, we estimated transcript elongation rates. Many matured mRNAs have long nuclear half-lives, indicating nuclear retention as the rate-limiting step in the flow of mRNAs. In contrast, mRNA transcripts coding for transcription factors show fast kinetic rates, and in particular short nuclear half-lives. Differentially localized mRNAs have distinct rate constant combinations, implying modular regulation. Membrane stability is high for membrane-localized mRNA and cytosolic stability is high for cytosol-localized mRNA. mRNAs encoding target signals for membranes have low cytosolic and high membrane half-lives with minor differences between signals. Transcripts of nuclear-encoded mitochondrial proteins have long nuclear retention and cytoplasmic kinetics that do not reflect co-translational targeting. Our data and analyses provide a useful resource to study spatiotemporal gene expression regulation.

PMID:39548324 | DOI:10.1038/s44320-024-00073-2

Sci Rep. 2024 Nov 16;14(1):28254. doi: 10.1038/s41598-024-79352-9.

ABSTRACT

Due to their position on glomerular capillaries, podocytes are continuously counteracting biomechanical filtration forces. Most therapeutic interventions known to generally slow or prevent the progression of chronic kidney disease appear to lower these biomechanical forces on podocytes, highlighting the critical need to better understand podocyte mechano-signalling pathways. Here we investigated whether the mechanotransducer Piezo is involved in a mechanosensation pathway in Drosophila nephrocytes, the podocyte homologue in the fly. Loss of function analysis in Piezo depleted nephrocytes reveal a severe morphological and functional phenotype. Further, pharmacological activation of endogenous Piezo with Yoda1 causes a significant increase of intracellular Ca++ upon exposure to a mechanical stimulus in nephrocytes, as well as filtration disturbances. Elevated Piezo expression levels also result in a severe nephrocyte phenotype. Interestingly, expression of Piezo which lacks mechanosensitive channel activity, does not result in a severe nephrocyte phenotype, suggesting the observed changes in Piezo wildtype overexpressing cells are caused by the mechanosensitive channel activity. Moreover, blocking Piezo activity using the tarantula toxin GsMTx4 reverses the phenotypes observed in nephrocytes overexpressing Piezo. Taken together, here we provide evidence that Piezo activity levels need to be tightly regulated to maintain normal pericardial nephrocyte morphology and function.

PMID:39548228 | DOI:10.1038/s41598-024-79352-9

Adv Mar Biol. 2024;98:99-192. doi: 10.1016/bs.amb.2024.07.005. Epub 2024 Oct 7.

ABSTRACT

The substantial development of microscopic techniques and histological examination methods during the past five decades allowed for many new insights into the histology and microanatomy of Rhizostomeae. The present review focuses on new findings about histologically important structures: nerves, senses, muscles, gonads, zooxanthellae and nematocysts. Different ontogenetic stages of rhizostome species were included in the literature research, supplemented with the authors' unpublished data and figures. The overview of the research results reveals that the application of chemo- and immunohistochemical techniques have provided deeper insights into neuronal and sensory structures and their interconnections. Modern microscopic methods led to new findings on the histological gonadal organization and details of the processes of gametogenesis, fertilization, cleavage, gastrulation, and brooding. Advanced optical methods also allowed for a better understanding of Rhizostomeae-zooxanthellae associations and the morphology and function of nematocysts. Improvements in molecular biology allowed for more precise identification of zooxanthellae associated with rhizostome species. Although there has been significant progress in all of the research subjects covered here, we identify several knowledge gaps and conclude with some recommendations for future research.

PMID:39547756 | DOI:10.1016/bs.amb.2024.07.005

Adv Mar Biol. 2024;98:1-60. doi: 10.1016/bs.amb.2024.07.004. Epub 2024 Nov 8.

ABSTRACT

Max Egon Thiel worked as curator of the aquatic invertebrates collection at the Zoological Museum in Hamburg until 1963. Specialising in marine planktonic megafauna, he compiled a broad review of the research history on the Scyphozoa (Coronatae, Cubomedusae, Semaeostomeae) including the Staurozoa (as Stauromedusae), written in German. After publishing major parts in 1936 and 1938, World War II delayed further chapters until 1959 and 1962. A complete bibliography covering references up to 1970 was not printed until 1977. The final section on the taxon Rhizostomeae was completed as a typescript before his death, but was never published. In the present paper, the authors provide a synopsis of the published volumes in English. Following Thiel's original outline, the research history, as well as reviews of the current knowledge at the time about morphology, histology, ontogeny (life cycle), physiology, ecology, and phylogeny of the taxa are presented. The paper is complemented by two electronic supplements: A translated and revised version of the left-behind typescript of Max Egon Thiel about the taxon Rhizostomeae, and the revised digital list of references published in Thiel (1977).

PMID:39547749 | DOI:10.1016/bs.amb.2024.07.004

Cell. 2024 Nov 14;187(23):6424-6450. doi: 10.1016/j.cell.2024.10.026.

ABSTRACT

Every cell must solve the problem of how to fold its genome. We describe how the folded state of chromosomes is the result of the combined activity of multiple conserved mechanisms. Homotypic affinity-driven interactions lead to spatial partitioning of active and inactive loci. Molecular motors fold chromosomes through loop extrusion. Topological features such as supercoiling and entanglements contribute to chromosome folding and its dynamics, and tethering loci to sub-nuclear structures adds additional constraints. Dramatically diverse chromosome conformations observed throughout the cell cycle and across the tree of life can be explained through differential regulation and implementation of these basic mechanisms. We propose that the first functions of chromosome folding are to mediate genome replication, compaction, and segregation and that mechanisms of folding have subsequently been co-opted for other roles, including long-range gene regulation, in different conditions, cell types, and species.

PMID:39547207 | DOI:10.1016/j.cell.2024.10.026

Nucleic Acids Res. 2024 Nov 15:gkae1117. doi: 10.1093/nar/gkae1117. Online ahead of print.

ABSTRACT

RNA molecules function in numerous biological processes by folding into intricate structures. Here we present RASP v2.0, an updated database for RNA structure probing data featuring a substantially expanded collection of datasets along with enhanced online structural analysis functionalities. Compared to the previous version, RASP v2.0 includes the following improvements: (i) the number of RNA structure datasets has increased from 156 to 438, comprising 216 transcriptome-wide RNA structure datasets, 141 target-specific RNA structure datasets, and 81 RNA-RNA interaction datasets, thereby broadening species coverage from 18 to 24, (ii) a deep learning-based model has been implemented to impute missing structural signals for 59 transcriptome-wide RNA structure datasets with low structure score coverage, significantly enhancing data quality, particularly for low-abundance RNAs, (iii) three new online analysis modules have been deployed to assist RNA structure studies, including missing structure score imputation, RNA secondary and tertiary structure prediction, and RNA binding protein (RBP) binding prediction. By providing a resource of much more comprehensive RNA structure data, RASP v2.0 is poised to facilitate the exploration of RNA structure-function relationships across diverse biological processes. RASP v2.0 is freely accessible at http://rasp2.zhanglab.net/.

PMID:39546630 | DOI:10.1093/nar/gkae1117

J Chem Phys. 2024 Nov 21;161(19):194102. doi: 10.1063/5.0232831.

ABSTRACT

This study presents an enhanced protein design algorithm that aims to emulate natural heterogeneity of protein sequences. Initial analysis revealed that natural proteins exhibit a permutation composition lower than the theoretical maximum, suggesting a selective utilization of the 20-letter amino acid alphabet. By not constraining the amino acid composition of the protein sequence but instead allowing random reshuffling of the composition, the resulting design algorithm generates sequences that maintain lower permutation compositions in equilibrium, aligning closely with natural proteins. Folding free energy computations demonstrated that the designed sequences refold to their native structures with high precision, except for proteins with large disordered regions. In addition, direct coupling analysis showed a strong correlation between predicted and actual protein contacts, with accuracy exceeding 82% for a large number of top pairs (>4L). The algorithm also resolved biases in previous designs, ensuring a more accurate representation of protein interactions. Overall, it not only mimics the natural heterogeneity of proteins but also ensures correct folding, marking a significant advancement in protein design and engineering.

PMID:39546369 | DOI:10.1063/5.0232831

Methods Mol Biol. 2025;2878:273-291. doi: 10.1007/978-1-0716-4264-1_15.

ABSTRACT

To be able to understand how spaceflight can affect human biology, there is a need for maximizing the amount of information that can be obtained from experiments flown to space. Recently there has been an influx of data obtained from astronauts through multi-omics approaches based on both governmental and commercial spaceflight missions. In addition to data from humans, mitochondrial specific data is gathered for other experiments from rodents and other organisms that are flown in space. This data has started to universally demonstrate that mitochondrial dysfunction is the key regulator associated with increasing health risks associated with spaceflight. This mitochondrial dysfunction can have influence downstream on immune suppression, inflammation, circadian rhythm issues, and more. Due to the space environment, standard methodologies have to be altered for performing mitochondrial specific analysis and in general sample collection for omics. To perform mitochondrial specific analysis and data collection from samples flown to space we will outline the current sample collection methods, processing of the samples, and specific analysis. Specifically we will highlight the different mitochondrial methodologies and challenges involved with research associated with spaceflight.

PMID:39546268 | DOI:10.1007/978-1-0716-4264-1_15

Methods Mol Biol. 2025;2868:265-284. doi: 10.1007/978-1-0716-4200-9_14.

ABSTRACT

We propose that one of the main hurdles in delivering comprehensively informed care results from the challenges surrounding the extraction, representation, and retention of prior clinical experience and basic medical knowledge, as well as its translation into time- and context-informed actionable interventions. While emerging applications in artificial intelligence-based techniques, for example, large language models, offer impressive pattern association capabilities, they often fall short in producing human-readable explanations crucial to their integration into clinical care. Moreover, they require large well-defined and well-integrated data sets that typically conflict with the availability of such data in all but a few areas of medicine, for example, medical imaging and neuroimaging, noninvasive monitoring of bio-electrical activity, etc. In this chapter, we argue that approximate reasoning rooted in the knowledge that is explainable to the human clinician may offer attractive avenues for the introduction of such knowledge in a systematic way that supports formal retention, sharing, and reuse of new clinical and basic medical experience. We outline a conceptual protocol that targets the use of sparse and disparate data of different types and from different sources, seamlessly drawing on our collective experience and that of others. We illustrate the utility of such an integrative approach by applying the latter to the assessment and reconciliation of data from different experimental models, human and animal, in the example use case of a complex health condition.

PMID:39546235 | DOI:10.1007/978-1-0716-4200-9_14

Methods Mol Biol. 2025;2868:247-264. doi: 10.1007/978-1-0716-4200-9_13.

ABSTRACT

Gene regulatory networks are foundational in the control of virtually all biological processes. These networks orchestrate a myriad of cell functions ranging from metabolic rate to the response to a drug or other intervention. The data required to accurately identify these control networks remains very cost and labor intensive typically leading to relatively sparse time course data that is largely incompatible with conventional data-driven model identification techniques. In this work, we combine empirical identification of gene-gene interactions with constraints describing the expected dynamic behavior of the network to infer regulatory dynamics from under-sampled data. We apply this to the identification of gene regulatory subnetworks recruited in groups of subjects participating in several different exercise interventions. Intervention-specific response networks are compared to one another and control actions driving differences are identified. We propose that this approach can extract statistically robust and biologically meaningful insights into gene regulatory dynamics from a dataset consisting of a small number of participants with very limited longitudinal sampling, for example pre- and post- intervention only.

PMID:39546234 | DOI:10.1007/978-1-0716-4200-9_13

Methods Mol Biol. 2025;2868:37-48. doi: 10.1007/978-1-0716-4200-9_3.

ABSTRACT

Psychoneuroimmunology (PNI) advancements may revolutionize personalized medicine by identifying systemic biomarkers that enhance diagnosis and treatment. Inflammatory pathways connect personality traits with cognitive performance, aging-related disorders, and mortality risks. Studies have demonstrated the critical interactions between personality and various biological systems like the hypothalamic-pituitary-adrenal (HPA) axis. The gut-brain axis also affects behaviors and psychological states in older adults, with specific gut microbiota influencing cognition, mood, and personality. These findings underscore the practical implications of understanding personality-biology interactions. They can support preventive and personalized medicine for aging-associated disorders. Specifically, personality changes are prevalent in Alzheimer's disease (AD) patients, impacting clinical management and caregiver stress. Non-cognitive factors, such as personality traits and psychiatric symptoms, may serve as early markers of AD. Traits like high Neuroticism and low Openness can predict initial AD stages, often before a formal diagnosis. Personality alterations in AD are also linked to cerebrospinal fluid (CSF) and vascular imaging biomarkers, which can track AD pathology and serve as predictors. Dynamic personality assessment can aid in timely diagnosis, monitoring progression, and evaluating treatments of AD. Understanding personality traits is crucial for predicting burnout, lifespan, and intervention success. Integrating personality and PNI biomarkers into patient profiles will support the development of personalized and systems medicine.

PMID:39546224 | DOI:10.1007/978-1-0716-4200-9_3

Methods Mol Biol. 2025;2868:15-36. doi: 10.1007/978-1-0716-4200-9_2.

ABSTRACT

Research in psychoneuroimmunology (PNI) underscores the intricate connections within the "whole mind-body system." Personality plays a pivotal role, with specific traits linked to stress influencing neural behavior and psychophysiological disorders. Gene expression networks associated with personality affect neuronal plasticity, epigenetic processes, and adaptive behaviors, highlighting the importance of systems biology mechanisms. Systemic inflammation correlates with key personality traits. Understanding the roles of inflammatory and oxidative biomarkers in personality traits and disorders can help identify diagnostic and therapeutic targets for various diseases. Neurobiological features contribute to our understanding of personality disorders and related conditions. Personality traits are linked to distributed neuroendocrine networks, particularly the hypothalamic-pituitary-adrenal (HPA) axis, rather than localized brain areas. Correlations have also been identified between personality traits and thyroid hormones. Disrupted hypothalamic-pituitary-thyroid (HPT) axis functions may be associated with disease severity, depression, and distress, highlighting the need for comprehensive endocrinological and psychopathological evaluations. The gut-brain axis influences personality traits, emotions, stress, and social behaviors. Altered gut microbiota is common in psychiatric conditions, suggesting potential treatments targeting the microbiota. Chronic stress impacts cognitive functions and correlates with personality and mental health, emphasizing the need for comprehensive, multi-dimensional patient profiles for effective prevention and therapy. A biopsychosocial model integrating personality traits will advance personalized and systems medicine.

PMID:39546223 | DOI:10.1007/978-1-0716-4200-9_2

Microbiol Resour Announc. 2024 Nov 15:e0074024. doi: 10.1128/mra.00740-24. Online ahead of print.

ABSTRACT

Spirochetal bacteria isolated from arthropods of the genera Culex and Aedes are termed BR149, BR151 (Entomospira culicis), BR193 (Entomospira entomophila), and BR208 (Entomospira nematocerorum). Genome sizes assembled from Illumina MiSeq and Oxford Nanopore reads varied between 1.67 and 1.78 Mb containing three to six plasmids. GC content ranged from 38.5% to 45.76%.

PMID:39545808 | DOI:10.1128/mra.00740-24

FASEB J. 2024 Nov 30;38(22):e70153. doi: 10.1096/fj.202401420RR.

ABSTRACT

Resistance exercise upregulates and downregulates the expression of a wide range of genes in skeletal muscle. However, detailed analysis of mRNA dynamics such as response rates and temporal patterns of the transcriptome after resistance exercise has not been performed. We aimed to clarify the dynamics of time-series transcriptomics after resistance exercise. We used electrical stimulation-induced muscle contraction as a resistance exercise model (5 sets × 10 times of 3 s of 100-Hz electrical stimulation) on the tibialis anterior muscle of rats and measured the transcriptome in the muscle before and at 0, 1, 3, 6, and 12 h after muscle contractions by RNA sequencing. We also examined the relationship between the parameters of mRNA dynamics and the increase in protein expression at 12 h after muscle contractions. We found that the function of the upregulated genes differed after muscle contractions depending on their response rate. Genes related to muscle differentiation and response to mechanical stimulus were enriched in the sustainedly upregulated genes. Furthermore, there was a positive correlation between the magnitude of upregulated mRNA expression and the corresponding protein expression level at 12 h after muscle contractions. Although it has been theoretically suggested, this study experimentally demonstrated that the magnitude of the mRNA response after electrical stimulation-induced resistance exercise contributes to skeletal muscle adaptation via increases in protein expression. These findings suggest that mRNA expression dynamics such as response rate, a sustained upregulated expression pattern, and the magnitude of the response contribute to mechanisms underlying adaptation to resistance exercise.

PMID:39545720 | DOI:10.1096/fj.202401420RR

Elife. 2024 Nov 15;13:e95720. doi: 10.7554/eLife.95720. Online ahead of print.

ABSTRACT

Effects from aging in single cells are heterogenous, whereas at the organ- and tissue-levels aging phenotypes tend to appear as stereotypical changes. The mammary epithelium is a bilayer of two major phenotypically and functionally distinct cell lineages: luminal epithelial and myoepithelial cells. Mammary luminal epithelia exhibit substantial stereotypical changes with age that merit attention because these cells are the putative cells-of-origin for breast cancers. We hypothesize that effects from aging that impinge upon maintenance of lineage fidelity increase susceptibility to cancer initiation. We generated and analyzed transcriptomes from primary luminal epithelial and myoepithelial cells from younger <30 (y)ears old and older >55y women. In addition to age-dependent directional changes in gene expression, we observed increased transcriptional variance with age that contributed to genome-wide loss of lineage fidelity. Age-dependent variant responses were common to both lineages, whereas directional changes were almost exclusively detected in luminal epithelia and involved altered regulation of chromatin and genome organizers such as SATB1. Epithelial expression of gap junction protein GJB6 increased with age, and modulation of GJB6 expression in heterochronous co-cultures revealed that it provided a communication conduit from myoepithelial cells that drove directional change in luminal cells. Age-dependent luminal transcriptomes comprised a prominent signal that could be detected in bulk tissue during aging and transition into cancers. A machine learning classifier based on luminal-specific aging distinguished normal from cancer tissue and was highly predictive of breast cancer subtype. We speculate that luminal epithelia are the ultimate site of integration of the variant responses to aging in their surrounding tissue, and that their emergent phenotype both endows cells with the ability to become cancer-cells-of-origin and represents a biosensor that presages cancer susceptibility.

PMID:39545637 | DOI:10.7554/eLife.95720

Front Immunol. 2024 Oct 31;15:1470368. doi: 10.3389/fimmu.2024.1470368. eCollection 2024.

ABSTRACT

Melanoma is a metastatic, drug-refractory cancer with the ability to evade immunosurveillance. Cancer immune evasion involves interaction between tumor intrinsic properties and the microenvironment. The transcription factor E2F1 is a key driver of tumor evolution and metastasis. To explore E2F1's role in immune regulation in presence of aggressive melanoma cells, we established a coculture system and utilized transcriptome and cytokine arrays combined with bioinformatics and structural modeling. We identified an E2F1-dependent gene regulatory network with IL6 as a central hub. E2F1-induced IL-6 secretion unleashes an autocrine inflammatory feedback loop driving invasiveness and epithelial-to-mesenchymal transition. IL-6-activated STAT3 physically interacts with E2F1 and cooperatively enhances IL-6 expression by binding to an E2F1-STAT3-responsive promoter element. The E2F1-STAT3/IL-6 axis strongly modulates the immune niche and generates a crosstalk with CD4+ cells resulting in transcriptional changes of immunoregulatory genes in melanoma and immune cells that is indicative of an inflammatory and immunosuppressive environment. Clinical data from TCGA demonstrated that elevated E2F1, STAT3, and IL-6 correlate with infiltration of Th2, while simultaneously blocking Th1 in primary and metastatic melanomas. Strikingly, E2F1 depletion reduces the secretion of typical type-2 cytokines thereby launching a Th2-to-Th1 phenotype shift towards an antitumor immune response. The impact of activated E2F1-STAT3/IL-6 axis on melanoma-immune cell communication and its prognostic/therapeutic value was validated by mathematical modeling. This study addresses important molecular aspects of the tumor-associated microenvironment in modulating immune responses, and will contribute significantly to the improvement of future cancer therapies.

PMID:39544930 | PMC:PMC11560763 | DOI:10.3389/fimmu.2024.1470368