Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy.

BACKGROUND: Tumor-associated antigens and their derived peptides constitute an opportunity to design off-the-shelf mainline or adjuvant anti-cancer immunotherapies for a broad array of patients. A performant and rational antigen selection pipeline would lay the foundation for immunotherapy trials with the potential to enhance treatment, tremendously benefiting patients suffering from rare, understudied cancers. METHODS: We present an experimentally validated, data-driven computational pipeline that selects and ranks antigens in a multipronged approach. In addition to minimizing the risk of immune-related adverse events by selecting antigens based on their expression profile in tumor biopsies and healthy tissues, we incorporated a network analysis-derived antigen indispensability index based on computational modeling results, and candidate immunogenicity predictions from a machine learning ensemble model relying on peptide physicochemical characteristics. RESULTS: In a model study of uveal melanoma, Human Leukocyte Antigen (HLA) docking simulations and experimental quantification of the peptide-major histocompatibility complex binding affinities confirmed that our approach discriminates between high-binding and low-binding affinity peptides with a performance similar to that of established methodologies. Blinded validation experiments with autologous T-cells yielded peptide stimulation-induced interferon-γ secretion and cytotoxic activity despite high interdonor variability. Dissecting the score contribution of the tested antigens revealed that peptides with the potential to induce cytotoxicity but unsuitable due to potential tissue damage or instability of expression were properly discarded by the computational pipeline. CONCLUSIONS: In this study, we demonstrate the feasibility of the de novo computational selection of antigens with the capacity to induce an anti-tumor immune response and a predicted low risk of tissue damage. On translation to the clinic, our pipeline supports fast turn-around validation, for example, for adoptive T-cell transfer preparations, in both generalized and personalized antigen-directed immunotherapy settings.

Sunset Yellow protects against oxidative damage and exhibits chemoprevention in chemically induced skin cancer model.

Skin cancer and other skin-related inflammatory pathologies are rising due to heightened exposure to environmental pollutants and carcinogens. In this context, natural products and repurposed compounds hold promise as novel therapeutic and preventive agents. Strengthening the skin's antioxidant defense mechanisms is pivotal in neutralizing reactive oxygen species (ROS) and mitigating oxidative stress. Sunset Yellow (SY) exhibits immunomodulatory characteristics, evidenced by its capacity to partially inhibit the secretion of proinflammatory cytokines, regulate immune cell populations, and modulate the activation of lymphocytes. This study aimed to investigate the antioxidant and anti-genotoxic properties of SY using in-silico, in vitro, and physiochemical test systems, and to further explore its potential role in 7,12-dimethylbenz(a) anthracene (DMBA)/ 12-o-tetradecanoylphorbol-13-acetate (TPA)-induced two-stage skin carcinogenesis. In vitro experiments showed that pre-treatment of SY significantly enhanced the cell viability of HaCaT cells when exposed to tertiary-Butyl Hydrogen Peroxide (tBHP). This increase was accompanied by reduced ROS levels, restoration of mitochondrial membrane potential, and notable reduction in DNA damage in (SY + tBHP) treated cells. Mechanistic investigations using DPPH chemical antioxidant activity test and potentiometric titrations confirmed SY's antioxidant properties, with a standard reduction potential ( E o ) of 0.211 V. Remarkably, evaluating the effect of topical application of SY in DMBA/TPA-induced two-step skin carcinogenesis model revealed dose-dependent decreases in tumor latency, incidence, yield, and burden over 21-weeks. Furthermore, computational analysis and experimental validations identified GSK3ß, KEAP1 and EGFR as putative molecular targets of SY. Collectively, our findings reveal that SY enhances cellular antioxidant defenses, exhibits anti-genotoxic effects, and functions as a promising chemopreventive agent.

Exploring Thiazolopyridine AV25R: Unraveling of Biological Activities, Selective Anti-Cancer Properties and In Silico Target and Binding Prediction in Hematological Neoplasms.

Thiazolopyridines are a highly relevant class of small molecules, which have previously shown a wide range of biological activities. Besides their anti-tubercular, anti-microbial and anti-viral activities, they also show anti-cancerogenic properties, and play a role as inhibitors of cancer-related proteins. Herein, the biological effects of the thiazolopyridine AV25R, a novel small molecule with unknown biological effects, were characterized. Screening of a set of lymphoma (SUP-T1, SU-DHL-4) and B- acute leukemia cell lines (RS4;11, SEM) revealed highly selective effects of AV25R. The selective anti-proliferative and metabolism-modulating effects were observed in vitro for the B-ALL cell line RS4;11. Further, we were able to detect severe morphological changes and the induction of apoptosis. Gene expression analysis identified a large number of differentially expressed genes after AV25R exposure and significant differentially regulated cancer-related signaling pathways, such as VEGFA-VEGFR2 signaling and the EGF/EGFR pathway. Structure-based pharmacophore screening approaches using in silico modeling identified potential biological AV25R targets. Our results indicate that AV25R binds with several proteins known to regulate cell proliferation and tumor progression, such as FECH, MAP11, EGFR, TGFBR1 and MDM2. The molecular docking analyses indicates that AV25R has a higher binding affinity compared to many of the experimentally validated small molecule inhibitors of these targets. Thus, here we present in vitro and in silico analyses which characterize, for the first time, the molecular acting mechanism of AV25R, including cellular and molecular biologic effects. Additionally, this predicted the target binding of the molecule, revealing a high affinity to cancer-related proteins and, thus, classified AVR25 for targeted intervention approaches.

Estimation of natural radioactivity in the soil samples around the uranium site, royal village, Khandela, Sikar district, Rajasthan.

The measurements of activity concentration of radium ( 226Ra ), thorium ( 232Th) and potassium ( 40K ) natural radionuclides using high purity germanium ( HPGe ) detector to assess harmful effects on people residing around Royal Uranium Site, Sikar, Rajasthan, India. The activity concentrations range from 29.03 ± 3.72 to 69.95 ± 4.07 Bq/kg for 226Ra with a mean value of 47.01 Bq/kg, 57.99 ± 6.13 to 113.94 ± 6.54 Bq/kg with a mean value of 86.56 Bq/kg for 232Th,678.19 ± 76.36 to 1426.55 ± 81.32 Bq/kg for 40K with a mean value of 1195 Bq/kg. Average Radium Equivalent Activity was measured 261.59 ± 35.48 Bq/kg. The total outdoor absorbed gamma dose rate ranged from 78.42 to 157.91 nGy/h with a mean value of 122.12 nGy/h.The average annual effective dose equivalent outdoors and indoors was found 0.75 mSv.Mean external (Hex) and internal (Hin) hazard indices are measured 0.70 and 0.82, respectively, for the study area.

Logic-based modeling and drug repurposing for the prediction of novel therapeutic targets and combination regimens against E2F1-driven melanoma progression.

Melanoma presents increasing prevalence and poor outcomes. Progression to aggressive stages is characterized by overexpression of the transcription factor E2F1 and activation of downstream prometastatic gene regulatory networks (GRNs). Appropriate therapeutic manipulation of the E2F1-governed GRNs holds the potential to prevent metastasis however, these networks entail complex feedback and feedforward regulatory motifs among various regulatory layers, which make it difficult to identify druggable components. To this end, computational approaches such as mathematical modeling and virtual screening are important tools to unveil the dynamics of these signaling networks and identify critical components that could be further explored as therapeutic targets. Herein, we integrated a well-established E2F1-mediated epithelial-mesenchymal transition (EMT) map with transcriptomics data from E2F1-expressing melanoma cells to reconstruct a core regulatory network underlying aggressive melanoma. Using logic-based in silico perturbation experiments of a core regulatory network, we identified that simultaneous perturbation of Protein kinase B (AKT1) and oncoprotein murine double minute 2 (MDM2) drastically reduces EMT in melanoma. Using the structures of the two protein signatures, virtual screening strategies were performed with the FDA-approved drug library. Furthermore, by combining drug repurposing and computer-aided drug design techniques, followed by molecular dynamics simulation analysis, we identified two potent drugs (Tadalafil and Finasteride) that can efficiently inhibit AKT1 and MDM2 proteins. We propose that these two drugs could be considered for the development of therapeutic strategies for the management of aggressive melanoma.

NaviCenta - The disease map for placental research.

The placenta remains the key organ to pregnancy complications, such as preeclampsia, contrarily the pathophysiology underlying the placental dysfunctions remains elusive. Here, we present our Disease Map "NaviCenta", which is an online resource based on the interactions between tissues, cellular compartments, and molecules that mediate disease-related processes in the placenta. We built cellular and molecular interaction networks based upon manual curation and annotation of publicly available information in the scientific literature, pathways resources, and Omics data. NaviCenta (Navigate the plaCenta) serves as an open access, spatio-temporal, multi-scale knowledge base, and analytical tool for enhanced interpretation and hypothesis testing on various placental disease phenotypes.

Cell-Type-Specific Gene Regulatory Networks of Pro-Inflammatory and Pro-Resolving Lipid Mediator Biosynthesis in the Immune System.

Lipid mediators are important regulators in inflammatory responses, and their biosynthetic pathways are targeted by commonly used anti-inflammatory drugs. Switching from pro-inflammatory lipid mediators (PIMs) to specialized pro-resolving (SPMs) is a critical step toward acute inflammation resolution and preventing chronic inflammation. Although the biosynthetic pathways and enzymes for PIMs and SPMs have now been largely identified, the actual transcriptional profiles underlying the immune cell type-specific transcriptional profiles of these mediators are still unknown. Using the Atlas of Inflammation Resolution, we created a large network of gene regulatory interactions linked to the biosynthesis of SPMs and PIMs. By mapping single-cell sequencing data, we identified cell type-specific gene regulatory networks of the lipid mediator biosynthesis. Using machine learning approaches combined with network features, we identified cell clusters of similar transcriptional regulation and demonstrated how specific immune cell activation affects PIM and SPM profiles. We found substantial differences in regulatory networks in related cells, accounting for network-based preprocessing in functional single-cell analyses. Our results not only provide further insight into the gene regulation of lipid mediators in the immune response but also shed light on the contribution of selected cell types in their biosynthesis.

Network analyses reveal new insights into the effect of multicomponent Tr14 compared to single-component diclofenac in an acute inflammation model.

BACKGROUND: Modifying the acute inflammatory response has wide clinical benefits. Current options include non-steroidal anti-inflammatory drugs (NSAIDs) and therapies that may resolve inflammation. Acute inflammation involves multiple cell types and various processes. We, therefore, investigated whether an immunomodulatory drug that acts simultaneously at multiple sites shows greater potential to resolve acute inflammation more effectively and with fewer side effects than a common anti-inflammatory drug developed as a small molecule for a single target. In this work, we used time-series gene expression profiles from a wound healing mouse model to compare the effects of Traumeel (Tr14), a multicomponent natural product, to diclofenac, a single component NSAID on inflammation resolution. RESULTS: We advance previous studies by mapping the data onto the "Atlas of Inflammation Resolution", followed by in silico simulations and network analysis. We found that Tr14 acts primarily on the late phase of acute inflammation (during resolution) compared to diclofenac, which suppresses acute inflammation immediately after injury. CONCLUSIONS: Our results provide new insights how network pharmacology of multicomponent drugs may support inflammation resolution in inflammatory conditions.

A proteomic profile of the healthy human placenta.

BACKGROUND: The placenta remains one of the least studied organs within the human body. Yet, placental dysfunction has been associated with various pregnancy complications leading to both maternal and fetal death and long-term health consequences. The aim of this study was to characterise the protein networks of healthy term placental sub-anatomical regions using label free quantification mass spectrometry. METHODS: Three healthy placentae were sampled at five sample sites and each biopsy was dissected into maternal-, middle-, and fetal- sub-anatomical regions. Quadrupole-orbitrap mass spectrometer was used in data dependant analysis mode to identify 1859 unique proteins before detailed differential expression between regions. RESULTS: Protein profiling identified 1081, 1086, and 1101 proteins in maternal, middle, and fetal sub-anatomical regions respectively. Differentially expressed proteins were identified considering the effect between sample site location and sub-anatomical region on protein expression. Of these, 374 differentially expressed proteins (Two-way ANOVA adjusted p-value < 0.05, HSD Tukey adjusted p-value 0.05) were identified between sample site locations and sub-anatomical regions. The placenta specific disease map NaviCenta ( https://www.sbi.uni-rostock.de/minerva/index.xhtml?id=NaviCenta ) was used to focus functional analysis results to the placenta specific context. Subsequently, functional analysis with a focus on senescence, and mitochondrial function were performed. Significant differences were observed between sub-anatomical regions in protein intensity and composition. A decrease in anti-senescent proteins within the maternal sub-anatomical region, and an increase in proteins associated with a switch from ATP to fatty acid consumption as a source of energy between middle and fetal sub-anatomical regions were observed. CONCLUSION: These results suggest that normal proteomic variations exist within the anatomical structure of the placenta, thus recommending serial sectioning methodology for consistent placental research.

3D Modeling of Non-coding RNA Interactions.

Non-coding RNAs (ncRNAs) are a growing class of transcripts, with lengths ranging from tens to several thousand of bases, involved in the regulation of a large number of biological processes and diseases. Many of these ncRNAs have emerged as the molecules of interest for prognostic, diagnostic, and therapeutic purposes in many diseases including cancer. Although ncRNAs do not encode proteins, they fold into complex structures to interact with target proteins, DNA, or other RNAs. In contrast to microRNAs (miRNAs) where researchers mainly focused on the nucleotide sequence for target prediction in the past, folding and structural conservation seems to be important to encode functions and interactions of long non-coding RNA (lncRNA). In this chapter, we discuss methods and tools available for the structural modeling of ncRNAs together with various examples from the literature where structural modeling helped decipher the function of ncRNAs. We also provide a step-by-step procedure to design 3D structures of ncRNAs combining state-of-the-art tools available toward the design of novel RNA therapeutics.

Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence.

We live in an unprecedented time in oncology. We have accumulated samples and cases in cohorts larger and more complex than ever before. New technologies are available for quantifying solid or liquid samples at the molecular level. At the same time, we are now equipped with the computational power necessary to handle this enormous amount of quantitative data. Computational models are widely used helping us to substantiate and interpret data. Under the label of systems and precision medicine, we are putting all these developments together to improve and personalize the therapy of cancer. In this review, we use melanoma as a paradigm to present the successful application of these technologies but also to discuss possible future developments in patient care linked to them. Melanoma is a paradigmatic case for disruptive improvements in therapies, with a considerable number of metastatic melanoma patients benefiting from novel therapies. Nevertheless, a large proportion of patients does not respond to therapy or suffers from adverse events. Melanoma is an ideal case study to deploy advanced technologies not only due to the medical need but also to some intrinsic features of melanoma as a disease and the skin as an organ. From the perspective of data acquisition, the skin is the ideal organ due to its accessibility and suitability for many kinds of advanced imaging techniques. We put special emphasis on the necessity of computational strategies to integrate multiple sources of quantitative data describing the tumour at different scales and levels.

Pulley Reconstruction Following Surgical Release of DC1 Pulley in De Quervain's Tenosynovitis: Surgical Technique and Case Series.

De Quervain's disease (DQD) is tenosynovitis of the first dorsal compartment (DC1) of the wrist between the osteofibrous tunnel and the tendons involving the APL and EPB sheaths at the radial styloid. Surgical intervention is indicated when pain does not resolve despite 3 to 6 months of conservative management. Release of the first dorsal compartment is an effective treatment of DQD. In addition to surgical release, we performed pulley reconstruction using a new technique in the present series of 20 patients which has not been previously described with a followup of over 1 year. All patients showed a consistent improvement in VAS score at over one year followup with resolution of Finkelstein, Eichoff and WHAT test. Only one temporary neuropraxia was encountered due to stretching/scar entrapment of superficial branch of radial nerve. Our innovative technique of pulley reconstruction is not only easy to understand and perform but has shown consistent result in the 20 cases operated with this technique with a follow up of at least 1 year. The technique has the distinct advantage of having a quick learning curve and gives reliable, lasting results without complications or recurrence.

Do Carbon Nanotubes and Asbestos Fibers Exhibit Common Toxicity Mechanisms?

During the last two decades several nanoscale materials were engineered for industrial and medical applications. Among them carbon nanotubes (CNTs) are the most exploited nanomaterials with global production of around 1000 tons/year. Besides several commercial benefits of CNTs, the fiber-like structures and their bio-persistency in lung tissues raise serious concerns about the possible adverse human health effects resembling those of asbestos fibers. In this review, we present a comparative analysis between CNTs and asbestos fibers using the following four parameters: (1) fibrous needle-like shape, (2) bio-persistent nature, (3) high surface to volume ratio and (4) capacity to adsorb toxicants/pollutants on the surface. We also compare mechanisms underlying the toxicity caused by certain diameters and lengths of CNTs and asbestos fibers using downstream pathways associated with altered gene expression data from both asbestos and CNT exposure. Our results suggest that indeed certain types of CNTs are emulating asbestos fiber as far as associated toxicity is concerned.

Single extracellular vesicle analysis in human amniotic fluid shows evidence of phenotype alterations in preeclampsia.

Amniotic fluid surrounding the developing fetus is a complex biological fluid rich in metabolically active bio-factors. The presence of extracellular vesicles (EVs) in amniotic fluid has been mainly related to foetal urine. We here characterized EVs from term amniotic fluid in terms of surface marker expression using different orthogonal techniques. EVs appeared to be a heterogeneous population expressing markers of renal, placental, epithelial and stem cells. Moreover, we compared amniotic fluid EVs from normal pregnancies with those of preeclampsia, a hypertensive disorder affecting up to 8% of pregnancies worldwide. An increase of CD105 (endoglin) expressing EVs was observed in preeclamptic amniotic fluid by bead-based cytofluorimetric analysis, and further confirmed using a chip-based analysis. HLA-G, a typical placental marker, was not co-expressed by the majority of CD105+ EVs, in analogy with amniotic fluid stromal cell derived-EVs. At a functional level, preeclampsia-derived EVs, but not normal pregnancy EVs, showed an antiangiogenic effect, possibly due to the decoy effect of endoglin. Our results provide a characterization of term amniotic fluid-EVs, supporting their origin from foetal and placental cells. In preeclampsia, the observed antiangiogenic characteristics of amniotic fluid-EVs may reflect the hypoxic and antiangiogenic microenvironment and could possibly impact on the developing fetus or on the surrounding foetal membranes.

Network- and enrichment-based inference of phenotypes and targets from large-scale disease maps.

Complex diseases are inherently multifaceted, and the associated data are often heterogeneous, making linking interactions across genes, metabolites, RNA, proteins, cellular functions, and clinically relevant phenotypes a high-priority challenge. Disease maps have emerged as knowledge bases that capture molecular interactions, disease-related processes, and disease phenotypes with standardized representations in large-scale molecular interaction maps. Various tools are available for disease map analysis, but an intuitive solution to perform in silico experiments on the maps in a wide range of contexts and analyze high-dimensional data is currently missing. To this end, we introduce a two-dimensional enrichment analysis (2DEA) approach to infer downstream and upstream elements through the statistical association of network topology parameters and fold changes from molecular perturbations. We implemented our approach in a plugin suite for the MINERVA platform, providing an environment where experimental data can be mapped onto a disease map and predict potential regulatory interactions through an intuitive graphical user interface. We show several workflows using this approach and analyze two RNA-seq datasets in the Atlas of Inflammation Resolution (AIR) to identify enriched downstream processes and upstream transcription factors. Our work improves the usability of disease maps and increases their functionality by facilitating multi-omics data integration and exploration.

Computational Models on Pathological Redox Signalling Driven by Pregnancy: A Review.

Oxidative stress is associated with a myriad of diseases including pregnancy pathologies with long-term cardiovascular repercussions for both the mother and baby. Aberrant redox signalling coupled with deficient antioxidant defence leads to chronic molecular impairment. Abnormal placentation has been considered the primary source for reactive species; however, placental dysfunction has been deemed secondary to maternal cardiovascular maladaptation in pregnancy. While various therapeutic interventions, aimed at combating deregulated oxidative stress during pregnancy have shown promise in experimental models, they often result as inconclusive or detrimental in clinical trials, warranting the need for further research to identify candidates. The strengths and limitations of current experimental methods in redox research are discussed. Assessment of redox status and oxidative stress in experimental models and in clinical practice remains challenging; the state-of-the-art of computational models in this field is presented in this review, comparing static and dynamic models which provide functional information such as protein-protein interactions, as well as the impact of changes in molecular species on the redox-status of the system, respectively. Enhanced knowledge of redox biology in during pregnancy through computational modelling such as generation of Systems Biology Markup Language model which integrates existing models to a larger network in the context of placenta physiology.

Can urodynamic diagnosis of dysfunctional voiding/external sphincter nonrelaxation be made on two-channel pressure-flow study without video-urodynamics, electromyography, or urethral pressure profilometry? Plateau detrusor pattern in perspective.

AIMS: urodynamic diagnosis of dysfunctional voiding/external-sphincter nonrelaxation (DV/EUSD) needs assistance of specialized testing namely urethral pressure profilometry (UPP), electromyography (EMG), and/or videofluoroscopy (VUDS). We aimed to find a predictive model based on standard pressure-flow study without need for specialized testing. MATERIAL AND METHODS: In this retrospective study (2017-2021), clinical and urodynamic data of adult men and women presenting with voiding dysfunction was collected. Mandatory inclusion criteria were availability of all-(1) findings of clinical examination and neurological status, (2) a valid filling cystometry and pressure-flow study (with active detrusor contraction), (3) a final clinic-urodynamic diagnosis. Voiding cystourethrography (VCUG) was performed to confirm the location of obstruction. RESULTS: Data of 218 participants (178♂, 40♀) was eligible. Plateau detrusor contraction pattern was observed in 89.0% of men and 86% of women with DV/EUSD; whereas only 7.5% men and no women with other obstructions demonstrated this pattern. Forward likelihood Logistic regression analysis revealed presence of plateau pattern, lower bladder outlet obstruction index (BOOI), and smaller difference between Pdetmax and PdetQmax highly predictive of presence of DV/EUSD in men as per the following equation-Y = -9.900 + (0.085 × BOOI) + (0.123 × pdetmax - pdetQmax) + (4.061 × detrusor pattern). A kattan-type nomogram was constructed based on the above equation. In women, presence of plateau pattern alone was highly predictive of DV/EUSD. CONCLUSION: Diagnosis of DV/EUSD can be accurately predicted using parameters of three-channel urodynamics (plateau pattern, BOOI, Pdetmax-pdetQmax) minimizing need for specialized testing.

Expanding Indications of Primary Arthrodesis in Selected Individuals for Managing Complex Hindfoot Trauma During COVID-19 Pandemic.

Background: During the COVID-19 pandemic, public health measures to encourage social distancing have been implemented, including cancellation of outdoor activities, organized sports, and schools/colleges. Neglected hindfoot fractures have emerged as a consequence with increased frequency. Similarly, complex ankle and pilon fractures that require staged management, prolonged hospital stay, and soft-tissue care have emerged as a potential concern as prolonged exposure to healthcare setting adds to risk of acquiring as well as transmitting COVID-19 infection. The authors present their experience with expanding these indications for hindfoot arthrodesis as they encounter a greater number of neglected ankle and hindfoot trauma. Methods: This was a retrospective observational study of collected data from the trauma unit of our hospital. Inclusion criteria included all trauma classified by the AO/OTA as occurring at locations 43, and who underwent subtalar and ankle arthrodesis. This included distal tibia, malleolar, talus, and calcaneus fractures. These patients were followed up to at least 6 months till complete fracture union. Results: A total of 18 patients underwent arthrodesis of either the ankle or subtalar joint between March and October 2020. Mean age of patients undergoing arthrodesis of the hindfoot was 69.2 years (43-84 years). Indications for the procedure included Displaced and comminuted intra-articular distal tibia fractures in elderly (6 patients), Malunited ankle fractures (2 patients), Neglected Ankle fractures managed conservatively (3 patients), Calcaneus fractures (5 patients), and neglected Talus body fracture (2 patients). All patients were followed up to at least 6 months and everyone went onto successful painless union between 3 and 6 months of the arthrodesis procedure without any significant complications. Conclusion: In summary, COVID-19 pandemic has led to a change in paradigm of trauma management and foot and ankle management is no different than other musculoskeletal trauma systems. The authors propose an expansion of indications for hindfoot arthrodesis in managing complex hindfoot trauma in pandemic situation.

Drug Repurposing at the Interface of Melanoma Immunotherapy and Autoimmune Disease.

Cancer cells have a remarkable ability to evade recognition and destruction by the immune system. At the same time, cancer has been associated with chronic inflammation, while certain autoimmune diseases predispose to the development of neoplasia. Although cancer immunotherapy has revolutionized antitumor treatment, immune-related toxicities and adverse events detract from the clinical utility of even the most advanced drugs, especially in patients with both, metastatic cancer and pre-existing autoimmune diseases. Here, the combination of multi-omics, data-driven computational approaches with the application of network concepts enables in-depth analyses of the dynamic links between cancer, autoimmune diseases, and drugs. In this review, we focus on molecular and epigenetic metastasis-related processes within cancer cells and the immune microenvironment. With melanoma as a model, we uncover vulnerabilities for drug development to control cancer progression and immune responses. Thereby, drug repurposing allows taking advantage of existing safety profiles and established pharmacokinetic properties of approved agents. These procedures promise faster access and optimal management for cancer treatment. Together, these approaches provide new disease-based and data-driven opportunities for the prediction and application of targeted and clinically used drugs at the interface of immune-mediated diseases and cancer towards next-generation immunotherapies.

UV-A,B,C Emitting Persistent Luminescent Materials.

The nearly dormant field of persistent luminescence has gained fresh impetus after the discovery of strontium aluminate persistent luminescence phosphor in 1996. Several efforts have been put in to prepare efficient, long decay, persistent luminescent materials which can be used for different applications. The most explored among all are the materials which emit in the visible wavelength region, 400-650 nm, of the electromagnetic spectrum. However, since 2014, the wavelength range is extended further above 650 nm for biological applications due to easily distinguishable signal between luminescent probe and the auto-fluorescence. Recently, UV-emitting persistent materials have gained interest among researchers' due to their possible application in information storage, phototherapy and photocatalysis. In the present review, we summarize these recent developments on the UV-emitting persistent luminescent materials to motivate young minds working in the field of luminescent materials.