Short term effects of extremely low irradiance photobiomodulation on retinal function, in age related macular degeneration.

BACKGROUND: recently much studies evidenced the potential role of photo-biomodulation (PBM) in patients affected by Age-related Macular Degeneration (AMD). We designed a new wearable device for self-medication that employs the same broadband red light described in literature, but with extremely low irradiance. AIM: to demonstrate the safety and effectiveness of low-fluence light stimulations emitted by a LED source with appropriate wavelengths through our new device in improving short-term visual function in patients affected by severe non neovascular AMD. MATERIALS AND METHODS: we prospectively enrolled patients affected by severe non-neovascular AMD with a relative sparing of the foveal region. All the patients were randomly assigned in placebo or in treatment group. The treatment consisted of 10 sessions of 10-min each, using the new device comprised of micro-LEDs that emitted light onto an amorphous support assembled within Metallic eyeglasses. The placebo group blindly underwent the same number of PBM sessions with the micro-LED turned off. Before and after each placebo/treatment sessions all the patients received: optical coherence tomography (OCT), Best-Corrected Visual Acuity (BCVA) and Microperimetry (MP). RESULTS: no significant differences in the anatomical parameters were observed in the two groups. The MP mean sensitivity and the central visual function both far and near significantly improved in the treated group (respectively p < 0.001, p < 0.001). CONCLUSIONS: our pivotal demonstrated that the LED PBM delivered through our new device is a safe and effective tool for improving short-term visual function in patients affected by severe non-neovascular AMD.

Variant-specific pathophysiological mechanisms of AFF3 differently influence transcriptome profiles.

Background: We previously described the KINSSHIP syndrome, an autosomal dominant disorder associated with intellectual disability (ID), mesomelic dysplasia and horseshoe kidney,caused by de novo variants in the degron of AFF3. Mouse knock-ins and overexpression in zebrafish provided evidence for a dominant-negative (DN) mode-of-action, wherein an increased level of AFF3 resulted in pathological effects. Methods: Evolutionary constraints suggest that other mode-of-inheritance could be at play. We challenged this hypothesis by screening ID cohorts for individuals with predicted-to-be deleterious variants in AFF3. We used both animal and cellular models to assess the deleteriousness of the identified variants. Results: We identified an individual with a KINSSHIP-like phenotype carrying a de novo partial duplication of AFF3 further strengthening the hypothesis that an increased level of AFF3 is pathological. We also detected seventeen individuals displaying a milder syndrome with either heterozygous LoF or biallelic missense variants in AFF3. Consistent with semi-dominance, we discovered three patients with homozygous LoF and one compound heterozygote for a LoF and a missense variant, who presented more severe phenotypes than their heterozygous parents. Matching zebrafish knockdowns exhibit neurological defects that could be rescued by expressing human AFF3 mRNA, confirming their association with the ablation of aff3. Conversely, some of the human AFF3 mRNAs carrying missense variants identified in affected individuals did not complement. Overexpression of mutated AFF3 mRNAs in zebrafish embryos produced a significant increase of abnormal larvae compared to wild-type overexpression further demonstrating deleteriousness. To further assess the effect of AFF3 variation, we profiled the transcriptome of fibroblasts from affected individuals and engineered isogenic cells harboring +/+, DN/DN, LoF/+, LoF/LoF or DN/LoF AFF3 genotypes. The expression of more than a third of the AFF3 bound loci is modified in either the DN/DN or the LoF/LoF lines. While the same pathways are affected, only about one-third of the differentially expressed genes are common to these homozygote datasets, indicating that AFF3 LoF and DN variants largely modulate transcriptomes differently, e.g. the DNA repair pathway displayed opposite modulation. Conclusions: Our results and the high pleiotropy shown by variation at this locus suggest that minute changes in AFF3 function are deleterious.

Integrating distribution kinetics and toxicodynamics to assess repeat dose neurotoxicity in vitro using human BrainSpheres: a case study on amiodarone.

For ethical, economical, and scientific reasons, animal experimentation, used to evaluate the potential neurotoxicity of chemicals before their release in the market, needs to be replaced by new approach methodologies. To illustrate the use of new approach methodologies, the human induced pluripotent stem cell-derived 3D model BrainSpheres was acutely (48 h) or repeatedly (7 days) exposed to amiodarone (0.625-15 µM), a lipophilic antiarrhythmic drug reported to have deleterious effects on the nervous system. Neurotoxicity was assessed using transcriptomics, the immunohistochemistry of cell type-specific markers, and real-time reverse transcription-polymerase chain reaction for various genes involved in the lipid metabolism. By integrating distribution kinetics modeling with neurotoxicity readouts, we show that the observed time- and concentration-dependent increase in the neurotoxic effects of amiodarone is driven by the cellular accumulation of amiodarone after repeated dosing. The development of a compartmental in vitro distribution kinetics model allowed us to predict the change in cell-associated concentrations in BrainSpheres with time and for different exposure scenarios. The results suggest that human cells are intrinsically more sensitive to amiodarone than rodent cells. Amiodarone-induced regulation of lipid metabolism genes was observed in brain cells for the first time. Astrocytes appeared to be the most sensitive human brain cell type in vitro. In conclusion, assessing readouts at different molecular levels after the repeat dosing of human induced pluripotent stem cell-derived BrainSpheres in combination with the compartmental modeling of in vitro kinetics provides a mechanistic means to assess neurotoxicity pathways and refine chemical safety assessment for humans.

MarrowQuant 2.0: A Digital Pathology Workflow Assisting Bone Marrow Evaluation in Experimental and Clinical Hematology.

Bone marrow (BM) cellularity assessment is a crucial step in the evaluation of BM trephine biopsies for hematologic and nonhematologic disorders. Clinical assessment is based on a semiquantitative visual estimation of the hematopoietic and adipocytic components by hematopathologists, which does not provide quantitative information on other stromal compartments. In this study, we developed and validated MarrowQuant 2.0, an efficient, user-friendly digital hematopathology workflow integrated within QuPath software, which serves as BM quantifier for 5 mutually exclusive compartments (bone, hematopoietic, adipocytic, and interstitial/microvasculature areas and other) and derives the cellularity of human BM trephine biopsies. Instance segmentation of individual adipocytes is realized through the adaptation of the machine-learning-based algorithm StarDist. We calculated BM compartments and adipocyte size distributions of hematoxylin and eosin images obtained from 250 bone specimens, from control subjects and patients with acute myeloid leukemia or myelodysplastic syndrome, at diagnosis and follow-up, and measured the agreement of cellularity estimates by MarrowQuant 2.0 against visual scores from 4 hematopathologists. The algorithm was capable of robust BM compartment segmentation with an average mask accuracy of 86%, maximal for bone (99%), hematopoietic (92%), and adipocyte (98%) areas. MarrowQuant 2.0 cellularity score and hematopathologist estimations were highly correlated (R2 = 0.92-0.98, intraclass correlation coefficient [ICC] = 0.98; interobserver ICC = 0.96). BM compartment segmentation quantitatively confirmed the reciprocity of the hematopoietic and adipocytic compartments. MarrowQuant 2.0 performance was additionally tested for cellularity assessment of specimens prospectively collected from clinical routine diagnosis. After special consideration for the choice of the cellularity equation in specimens with expanded stroma, performance was similar in this setting (R2 = 0.86, n = 42). Thus, we conclude that these validation experiments establish MarrowQuant 2.0 as a reliable tool for BM cellularity assessment. We expect this workflow will serve as a clinical research tool to explore novel biomarkers related to BM stromal components and may contribute to further validation of future digitalized diagnostic hematopathology workstreams.

Inhibition of anti-tumor immunity by melanoma cell-derived Activin-A depends on STING.

The transforming growth factor-ß (TGF-ß) family member activin A (hereafter Activin-A) is overexpressed in many cancer types, often correlating with cancer-associated cachexia and poor prognosis. Activin-A secretion by melanoma cells indirectly impedes CD8+ T cell-mediated anti-tumor immunity and promotes resistance to immunotherapies, even though Activin-A can be proinflammatory in other contexts. To identify underlying mechanisms, we here analyzed the effect of Activin-A on syngeneic grafts of Braf mutant YUMM3.3 mouse melanoma cells and on their microenvironment using single-cell RNA sequencing. We found that the Activin-A-induced immune evasion was accompanied by a proinflammatory interferon signature across multiple cell types, and that the associated increase in tumor growth depended at least in part on pernicious STING activity within the melanoma cells. Besides corroborating a role for proinflammatory signals in facilitating immune evasion, our results suggest that STING holds considerable potential as a therapeutic target to mitigate tumor-promoting Activin-A signaling at least in melanoma.

Epithelial-mesenchymal plasticity determines estrogen receptor positive breast cancer dormancy and epithelial reconversion drives recurrence.

More than 70% of human breast cancers (BCs) are estrogen receptor α-positive (ER+). A clinical challenge of ER+ BC is that they can recur decades after initial treatments. Mechanisms governing latent disease remain elusive due to lack of adequate in vivo models. We compare intraductal xenografts of ER+ and triple-negative (TN) BC cells and demonstrate that disseminated TNBC cells proliferate similarly as TNBC cells at the primary site whereas disseminated ER+ BC cells proliferate slower, they decrease CDH1 and increase ZEB1,2 expressions, and exhibit characteristics of epithelial-mesenchymal plasticity (EMP) and dormancy. Forced E-cadherin expression overcomes ER+ BC dormancy. Cytokine signalings are enriched in more active versus inactive disseminated tumour cells, suggesting microenvironmental triggers for awakening. We conclude that intraductal xenografts model ER + BC dormancy and reveal that EMP is essential for the generation of a dormant cell state and that targeting exit from EMP has therapeutic potential.

Estrogen receptor positive breast cancers have patient specific hormone sensitivities and rely on progesterone receptor.

Estrogen and progesterone receptor (ER, PR) signaling control breast development and impinge on breast carcinogenesis. ER is an established driver of ER + disease but the role of the PR, itself an ER target gene, is debated. We assess the issue in clinically relevant settings by a genetic approach and inject ER + breast cancer cell lines and patient-derived tumor cells to the milk ducts of immunocompromised mice. Such ER + xenografts were exposed to physiologically relevant levels of 17-ß-estradiol (E2) and progesterone (P4). We find that independently both premenopausal E2 and P4 levels increase tumor growth and combined treatment enhances metastatic spread. The proliferative responses are patient-specific with MYC and androgen receptor (AR) signatures determining P4 response. PR is required for tumor growth in patient samples and sufficient to drive tumor growth and metastasis in ER signaling ablated tumor cells. Our findings suggest that endocrine therapy may need to be personalized, and that abrogating PR expression can be a therapeutic option.

Interleukin-17A (IL-17A): A silent amplifier of COVID-19.

One of the hallmarks of COVID-19 is the cytokine storm that provokes primarily pneumonia followed by systemic inflammation. Emerging evidence has identified a potential link between elevated interleukin-17A (IL-17A) levels and disease severity and progression. Considering that per se, IL-17A can activate several inflammatory pathways, it is plausible to hypothesize an involvement of this cytokine in COVID-19 clinical outcomes. Thus, IL-17A could represent a marker of disease progression and/or a target to develop therapeutic strategies. This hypothesis paper aims to propose this "unique" cytokine as a silent amplifier of the COVID-19 immune response and (potentially) related therapy.

Contraceptive progestins with androgenic properties stimulate breast epithelial cell proliferation.

Hormonal contraception exposes women to synthetic progesterone receptor (PR) agonists, progestins, and transiently increases breast cancer risk. How progesterone and progestins affect the breast epithelium is poorly understood because we lack adequate models to study this. We hypothesized that individual progestins differentially affect breast epithelial cell proliferation and hence breast cancer risk. Using mouse mammary tissue ex vivo, we show that testosterone-related progestins induce the PR target and mediator of PR signaling-induced cell proliferation receptor activator of NF-κB ligand (Rankl), whereas progestins with anti-androgenic properties in reporter assays do not. We develop intraductal xenografts of human breast epithelial cells from 36 women, show they remain hormone-responsive and that progesterone and the androgenic progestins, desogestrel, gestodene, and levonorgestrel, promote proliferation but the anti-androgenic, chlormadinone, and cyproterone acetate, do not. Prolonged exposure to androgenic progestins elicits hyperproliferation with cytologic changes. Androgen receptor inhibition interferes with PR agonist- and levonorgestrel-induced RANKL expression and reduces levonorgestrel-driven cell proliferation. Thus, different progestins have distinct biological activities in the breast epithelium to be considered for more informed choices in hormonal contraception.

Intraductal xenografts show lobular carcinoma cells rely on their own extracellular matrix and LOXL1.

Invasive lobular carcinoma (ILC) is the most frequent special histological subtype of breast cancer, typically characterized by loss of E-cadherin. It has clinical features distinct from other estrogen receptor-positive (ER+ ) breast cancers but the molecular mechanisms underlying its characteristic biology are poorly understood because we lack experimental models to study them. Here, we recapitulate the human disease, including its metastatic pattern, by grafting ILC-derived breast cancer cell lines, SUM-44 PE and MDA-MB-134-VI cells, into the mouse milk ducts. Using patient-derived intraductal xenografts from lobular and non-lobular ER+ HER2- tumors to compare global gene expression, we identify extracellular matrix modulation as a lobular carcinoma cell-intrinsic trait. Analysis of TCGA patient datasets shows matrisome signature is enriched in lobular carcinomas with overexpression of elastin, collagens, and the collagen modifying enzyme LOXL1. Treatment with the pan LOX inhibitor BAPN and silencing of LOXL1 expression decrease tumor growth, invasion, and metastasis by disrupting ECM structure resulting in decreased ER signaling. We conclude that LOXL1 inhibition is a promising therapeutic strategy for ILC.

Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study.

BACKGROUND: Positional weight matrix (PWM) is a de facto standard model to describe transcription factor (TF) DNA binding specificities. PWMs inferred from in vivo or in vitro data are stored in many databases and used in a plethora of biological applications. This calls for comprehensive benchmarking of public PWM models with large experimental reference sets. RESULTS: Here we report results from all-against-all benchmarking of PWM models for DNA binding sites of human TFs on a large compilation of in vitro (HT-SELEX, PBM) and in vivo (ChIP-seq) binding data. We observe that the best performing PWM for a given TF often belongs to another TF, usually from the same family. Occasionally, binding specificity is correlated with the structural class of the DNA binding domain, indicated by good cross-family performance measures. Benchmarking-based selection of family-representative motifs is more effective than motif clustering-based approaches. Overall, there is good agreement between in vitro and in vivo performance measures. However, for some in vivo experiments, the best performing PWM is assigned to an unrelated TF, indicating a binding mode involving protein-protein cooperativity. CONCLUSIONS: In an all-against-all setting, we compute more than 18 million performance measure values for different PWM-experiment combinations and offer these results as a public resource to the research community. The benchmarking protocols are provided via a web interface and as docker images. The methods and results from this study may help others make better use of public TF specificity models, as well as public TF binding data sets.

The secreted protease Adamts18 links hormone action to activation of the mammary stem cell niche.

Estrogens and progesterone control breast development and carcinogenesis via their cognate receptors expressed in a subset of luminal cells in the mammary epithelium. How they control the extracellular matrix, important to breast physiology and tumorigenesis, remains unclear. Here we report that both hormones induce the secreted protease Adamts18 in myoepithelial cells by controlling Wnt4 expression with consequent paracrine canonical Wnt signaling activation. Adamts18 is required for stem cell activation, has multiple binding partners in the basement membrane and interacts genetically with the basal membrane-specific proteoglycan, Col18a1, pointing to the basement membrane as part of the stem cell niche. In vitro, ADAMTS18 cleaves fibronectin; in vivo, Adamts18 deletion causes increased collagen deposition during puberty, which results in impaired Hippo signaling and reduced Fgfr2 expression both of which control stem cell function. Thus, Adamts18 links luminal hormone receptor signaling to basement membrane remodeling and stem cell activation.

EPD in 2020: enhanced data visualization and extension to ncRNA promoters.

The Eukaryotic Promoter Database (EPD), available online at https://epd.epfl.ch, provides accurate transcription start site (TSS) information for promoters of 15 model organisms plus corresponding functional genomics data that can be viewed in a genome browser, queried or analyzed via web interfaces, or exported in standard formats (FASTA, BED, CSV) for subsequent analysis with other tools. Recent work has focused on the improvement of the EPD promoter viewers, which use the UCSC Genome Browser as visualization platform. Thousands of high-resolution tracks for CAGE, ChIP-seq and similar data have been generated and organized into public track hubs. Customized, reproducible promoter views, combining EPD-supplied tracks with native UCSC Genome Browser tracks, can be accessed from the organism summary pages or from individual promoter entries. Moreover, thanks to recent improvements and stabilization of ncRNA gene catalogs, we were able to release promoter collections for certain classes of ncRNAs from human and mouse. Furthermore, we developed automatic computational protocols to assign orphan TSS peaks to downstream genes based on paired-end (RAMPAGE) TSS mapping data, which enabled us to add nearly 9000 new entries to the human promoter collection. Since our last article in this journal, EPD was extended to five more model organisms: rhesus monkey, rat, dog, chicken and Plasmodium falciparum.

Common genetic variants associated with Parkinson's disease display widespread signature of epigenetic plasticity.

Parkinson disease (PD) is characterized by a pivotal progressive loss of substantia nigra dopaminergic neurons and aggregation of α-synuclein protein encoded by the SNCA gene. Genome-wide association studies identified almost 100 sequence variants linked to PD in SNCA. However, the consequences of this genetic variability are rather unclear. Herein, our analysis on selective single nucleotide polymorphisms (SNPs) which are highly associated with the PD susceptibility revealed that several SNP sites attribute to the nucleosomes and overlay with bivalent regions poised to adopt either active or repressed chromatin states. We also identified large number of transcription factor (TF) binding sites associated with these variants. In addition, we located two docking sites in the intron-1 methylation prone region of SNCA which are required for the putative interactions with DNMT1. Taken together, our analysis reflects an additional layer of epigenomic contribution for the regulation of the SNCA gene in PD.

Short-lived AUF1 p42-binding mRNAs of RANKL and BCL6 have two distinct instability elements each.

Regulation of mRNA stability by RNA-protein interactions contributes significantly to quantitative aspects of gene expression. We have identified potential mRNA targets of the AU-rich element binding protein AUF1. Myc-tagged AUF1 p42 was induced in mouse NIH/3T3 cells and RNA-protein complexes isolated using anti-myc tag antibody beads. Bound mRNAs were analyzed with Affymetrix microarrays. We have identified 508 potential target mRNAs that were at least 3-fold enriched compared to control cells without myc-AUF1. 22.3% of the enriched mRNAs had an AU-rich cluster in the ARED Organism database, against 16.3% of non-enriched control mRNAs. The enrichment towards AU-rich elements was also visible by AREScore with an average value of 5.2 in the enriched mRNAs versus 4.2 in the control group. Yet, numerous mRNAs were enriched without a high ARE score. The enrichment of tetrameric and pentameric sequences suggests a broad AUF1 p42-binding spectrum at short U-rich sequences flanked by A or G. Still, some enriched mRNAs were highly unstable, as those of TNFSF11 (known as RANKL), KLF10, HES1, CCNT2, SMAD6, and BCL6. We have mapped some of the instability determinants. HES1 mRNA appeared to have a coding region determinant. Detailed analysis of the RANKL and BCL6 3'UTR revealed for both that full instability required two elements, which are conserved in evolution. In RANKL mRNA both elements are AU-rich and separated by 30 bases, while in BCL6 mRNA one is AU-rich and 60 bases from a non AU-rich element that potentially forms a stem-loop structure.

PWMScan: a fast tool for scanning entire genomes with a position-specific weight matrix.

Summary: Transcription factors regulate gene expression by binding to specific short DNA sequences of 5-20 bp to regulate the rate of transcription of genetic information from DNA to messenger RNA. We present PWMScan, a fast web-based tool to scan server-resident genomes for matches to a user-supplied PWM or transcription factor binding site model from a public database. Availability and implementation: The web server and source code are available at http://ccg.vital-it.ch/pwmscan and https://sourceforge.net/projects/pwmscan, respectively. Supplementary information: Supplementary data are available at Bioinformatics online.

MGA repository: a curated data resource for ChIP-seq and other genome annotated data.

The Mass Genome Annotation (MGA) repository is a resource designed to store published next generation sequencing data and other genome annotation data (such as gene start sites, SNPs, etc.) in a completely standardised format. Each sample has undergone local processing in order the meet the strict MGA format requirements. The original data source, the reformatting procedure and the biological characteristics of the samples are described in an accompanying documentation file manually edited by data curators. 10 model organisms are currently represented: Homo sapiens, Mus musculus, Danio rerio, Drosophila melanogaster, Apis mellifera, Caenorhabditis elegans, Arabidopsis thaliana, Zea mays, Saccharomyces cerevisiae and Schizosaccharomyces pombe. As of today, the resource contains over 24 000 samples. In conjunction with other tools developed by our group (the ChIP-Seq and SSA servers), it allows users to carry out a great variety of analysis task with MGA samples, such as making aggregation plots and heat maps for selected genomic regions, finding peak regions, generating custom tracks for visualizing genomic features in a UCSC genome browser window, or downloading chromatin data in a table format suitable for local processing with more advanced statistical analysis software such as R. Home page: http://ccg.vital-it.ch/mga/.

SMiLE-seq identifies binding motifs of single and dimeric transcription factors.

Resolving the DNA-binding specificities of transcription factors (TFs) is of critical value for understanding gene regulation. Here, we present a novel, semiautomated protein-DNA interaction characterization technology, selective microfluidics-based ligand enrichment followed by sequencing (SMiLE-seq). SMiLE-seq is neither limited by DNA bait length nor biased toward strong affinity binders; it probes the DNA-binding properties of TFs over a wide affinity range in a fast and cost-effective fashion. We validated SMiLE-seq by analyzing 58 full-length human, mouse, and Drosophila TFs from distinct structural classes. All tested TFs yielded DNA-binding models with predictive power comparable to or greater than that of other in vitro assays. De novo motif discovery on all JUN-FOS heterodimers and several nuclear receptor-TF complexes provided novel insights into partner-specific heterodimer DNA-binding preferences. We also successfully analyzed the DNA-binding properties of uncharacterized human C2H2 zinc-finger proteins and validated several using ChIP-exo.

SNP2TFBS - a database of regulatory SNPs affecting predicted transcription factor binding site affinity.

SNP2TFBS is a computational resource intended to support researchers investigating the molecular mechanisms underlying regulatory variation in the human genome. The database essentially consists of a collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. A SNP's effect on TF binding is estimated based on a position weight matrix (PWM) model for the binding specificity of the corresponding factor. These data files are regenerated at regular intervals by an automatic procedure that takes as input a reference genome, a comprehensive SNP catalogue and a collection of PWMs. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs. Homepage: http://ccg.vital-it.ch/snp2tfbs/.

The eukaryotic promoter database in its 30th year: focus on non-vertebrate organisms.

We present an update of the Eukaryotic Promoter Database EPD (http://epd.vital-it.ch), more specifically on the EPDnew division, which contains comprehensive organisms-specific transcription start site (TSS) collections automatically derived from next generation sequencing (NGS) data. Thanks to the abundant release of new high-throughput transcript mapping data (CAGE, TSS-seq, GRO-cap) the database could be extended to plant and fungal species. We further report on the expansion of the mass genome annotation (MGA) repository containing promoter-relevant chromatin profiling data and on improvements for the EPD entry viewers. Finally, we present a new data access tool, ChIP-Extract, which enables computational biologists to extract diverse types of promoter-associated data in numerical table formats that are readily imported into statistical analysis platforms such as R.