Recent Advances in the Role of Arid5a in Immune Diseases and Cancer

Interleukin-6 Modulation in Ovarian Cancer Necessitates a Targeted Strategy: From the Approved to Emerging Therapies

Despite significant advances in treatments, ovarian cancer (OC) remains one of the most prevalent and lethal gynecological cancers in women. The frequent detection at the advanced stages has contributed to low survival rates, resistance to various treatments, and disease recurrence. Thus, a more effective approach is warranted to combat OC. The cytokine Interleukin-6 (IL6) has been implicated in various stages of OC development. High IL6 levels are also correlated with a lower survival rate in OC patients. In this current review, we summarized the pivotal roles of IL6 in OC, including the initiation, development, invasion, metastasis, and drug resistance mechanisms. This article systematically highlights how targeting IL6 improves OC outcomes by altering various cancer processes and reports the ongoing clinical trials that would further shape the IL6-based targeted therapies. This review also suggests how combining IL6-targeted therapies with other therapeutic strategies could further enhance their efficacy to combat OC.

Flotillins affect LPS-induced TLR4 signaling by modulating the trafficking and abundance of CD14

Lipopolysaccharide (LPS) induces a strong pro-inflammatory reaction of macrophages upon activation of Toll-like receptor 4 (TLR4) with the assistance of CD14 protein. Considering a key role of plasma membrane rafts in CD14 and TLR4 activity and the significant impact exerted on that activity by endocytosis and intracellular trafficking of the both LPS acceptors, it seemed likely that the pro-inflammatory reaction could be modulated by flotillins. Flotillin-1 and -2 are scaffolding proteins associated with the plasma membrane and also with endo-membranes, affecting both the plasma membrane dynamics and intracellular protein trafficking. To verify the above hypothesis, a set of shRNA was used to down-regulate flotillin-2 in Raw264 cells, which were found to also become deficient in flotillin-1. The flotillin deficiency inhibited strongly the TRIF-dependent endosomal signaling of LPS-activated TLR4, and to a lower extent also the MyD88-dependent one, without affecting the cellular level of TLR4. The flotillin depletion also inhibited the pro-inflammatory activity of TLR2/TLR1 and TLR2/TLR6 but not TLR3. In agreement with those effects, the depletion of flotillins down-regulated the CD14 mRNA level and the cellular content of CD14 protein, and also inhibited constitutive CD14 endocytosis thereby facilitating its shedding. Ultimately, the cell-surface level of CD14 was markedly diminished. Concomitantly, CD14 recycling was enhanced via EEA1-positive early endosomes and golgin-97-positive trans-Golgi network, likely to compensate for the depletion of the cell-surface CD14. We propose that the paucity of surface CD14 is the reason for the down-regulated signaling of TLR4 and the other TLRs depending on CD14 for ligand binding.

Gene regulatory network topology governs resistance and treatment escape in glioma stem-like cells

Poor prognosis and drug resistance in glioblastoma (GBM) can result from cellular heterogeneity and treatment-induced shifts in phenotypic states of tumor cells, including dedifferentiation into glioma stem-like cells (GSCs). This rare tumorigenic cell subpopulation resists temozolomide, undergoes proneural-to-mesenchymal transition (PMT) to evade therapy, and drives recurrence. Through inference of transcriptional regulatory networks (TRNs) of patient-derived GSCs (PD-GSCs) at single-cell resolution, we demonstrate how the topology of transcription factor interaction networks drives distinct trajectories of cell state transitions in PD-GSCs resistant or susceptible to cytotoxic drug treatment. By experimentally testing predictions based on TRN simulations, we show that drug treatment drives surviving PD-GSCs along a trajectory of intermediate states, exposing vulnerability to potentiated killing by siRNA or a second drug targeting treatment-induced transcriptional programs governing non-genetic cell plasticity. Our findings demonstrate an approach to uncover TRN topology and use it to rationally predict combinatorial treatments that disrupts acquired resistance in GBM.

Towards a comprehensive regulatory map of Mammalian Genomes

Genome mapping studies have generated a nearly complete collection of genes for the human genome, but we still lack an equivalently vetted inventory of human regulatory sequences. Cis-regulatory modules (CRMs) play important roles in controlling when, where, and how much a gene is expressed. We developed a training data-free CRM-prediction algorithm, the Mammalian Regulatory MOdule Detector (MrMOD) for accurate CRM prediction in mammalian genomes. MrMOD provides genome position-fixed CRM models similar to the fixed gene models for the mouse and human genomes using only genomic sequences as the inputs with one adjustable parameter - the significance p-value. Importantly, MrMOD predicts a comprehensive set of high-resolution CRMs in the mouse and human genomes including all types of regulatory modules not limited to any tissue, cell type, developmental stage, or condition. We computationally validated MrMOD predictions used a compendium of 21 orthogonal experimental data sets including thousands of experimentally defined CRMs and millions of putative regulatory elements derived from hundreds of different tissues, cell types, and stimulus conditions obtained from multiple databases. In ovo transgenic reporter assay demonstrates the power of our prediction in guiding experimental design. We analyzed CRMs located in the chromosome 17 using unsupervised machine learning and identified groups of CRMs with multiple lines of evidence supporting their functionality, linking CRMs with upstream binding transcription factors and downstream target genes. Our work provides a comprehensive base pair resolution annotation of the functional regulatory elements and non-functional regions in the mammalian genomes.

Role of epigenetics in the clinical evolution of COVID-19 disease. Epigenome-wide association study identifies markers of severe outcome

BACKGROUND

COVID-19 has a wide spectrum of clinical manifestations and given its impact on morbidity and mortality, there is an unmet medical need to discover endogenous cellular and molecular biomarkers that predict the expected clinical course of the disease. Recently, epigenetics and especially DNA methylation have been pointed out as a promising tool for outcome prediction in several diseases.

METHODS AND RESULTS

Using the Illumina Infinium Methylation EPIC BeadChip850K, we investigated genome-wide differences in DNA methylation in an Italian Cohort of patients with comorbidities and compared severe (n = 64) and mild (123) prognosis. Results showed that the epigenetic signature, already present at the time of Hospital admission, can significantly predict risk of severe outcomes. Further analyses provided evidence of an association between age acceleration and a severe prognosis after COVID-19 infection. The burden of Stochastic Epigenetic Mutation (SEMs) has been significantly increased in patients with poor prognosis. Results have been replicated in silico considering COVID-19 negative subjects and available previously published datasets.

CONCLUSIONS

Using original methylation data and taking advantage of already published datasets, we confirmed in the blood that epigenetics is actively involved in immune response after COVID-19 infection, allowing the identification of a specific signature able to discriminate the disease evolution. Furthermore, the study showed that epigenetic drift and age acceleration are associated with severe prognosis. All these findings prove that host epigenetics undergoes notable and specific rearrangements to respond to COVID-19 infection which can be used for a personalized, timely, and targeted management of COVID-19 patients during the first stages of hospitalization.

Integrated analyses reveal evolutionarily conserved and specific injury response genes in dorsal root ganglion

Rodent dorsal root ganglion (DRG) is widely used for studying axonal injury. Extensive studies have explored genome-wide profiles on rodent DRGs under peripheral nerve insults. However, systematic integration and exploration of these data still be limited. Herein, we re-analyzed 21 RNA-seq datasets and presented a web-based resource (DRGProfile). We identified 53 evolutionarily conserved injury response genes, including well-known injury genes (Atf3, Npy and Gal) and less-studied transcriptional factors (Arid5a, Csrnp1, Zfp367). Notably, we identified species-preference injury response candidates (e.g. Gpr151, Lipn, Anxa10 in mice; Crisp3, Csrp3, Vip, Hamp in rats). Temporal profile analysis reveals expression patterns of genes related to pre-regenerative and regenerating states. Finally, we found a large sex difference in response to sciatic nerve injury, and identified four male-specific markers (Uty, Eif2s3y, Kdm5d, Ddx3y) expressed in DRG. Our study provides a comprehensive integrated landscape for expression change in DRG upon injury which will greatly contribute to the neuroscience community.