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Ophthalmic Segmentation and Analysis Software (OASIS): A Comprehensive Tool for Quantitative Evaluation of Meibography Images
No full textMeibomian gland dysfunction (MGD) is a prevalent cause of evaporative dry eye disease, resulting from the atrophy and reduced lipid secretion of the meibomian glands (MG). Current methods for evaluating MGs utilizing meibography rely on subjective assessment of gland loss. This study proposes an interactive image editor, Ophthalmic Segmentation and Analysis Software (OASIS), which includes features for manual and semi-automatic (assisted) analysis of meibography images. A natural history study collected 2,439 meibography images from 325 patients, which clinicians subsequently analyzed with OASIS. As part of OASIS’s manual analysis process, clinicians annotate three masks per image: the eyelid, glands, and gland loss. In the assisted process, OASIS can infer the gland mask using integrated deep-learning models, reducing the need for timely gland-by-gland annotation from the user. The Graphical User Interface (GUI) of OASIS also provides enhancement features and analysis tools, allowing users to apply filters, annotate ROIs, and calculate relevant clinical metrics. Metrics computed include gland count, eyelid area, gland loss area, gland area, gland loss percentage, gland area percentage, and, critically, a gland loss score based on the established Pult meiboscale. OASIS overcomes the limitations of previous methods by allowing clinicians to perform quantitative analyses of MGD in under 3 minutes, an 87% reduction in time compared to manual analysis. The software accurately calculates Pult meiboscale grades for meibography images with a fair agreement between the clinician and the software (kappa = 0.79). OASIS leads the efforts to develop in-depth quantitative biomarkers for MGD in clinical practices and therapeutic research.
Keywords: Meibomian gland dysfunction, software, deep learning, gland segmentatio
Taking Backgrounded Membrane Imaging (BMI) for particle analysis in biopharmaceutics to the next level - Statistical variability, detection limits and novel metrics.
No full textThe aggregation of proteins is a major threat to the integrity of biopharmaceutical products. Typically the state of aggregation at a specific timepoint is evaluated via particle analysis and counting or turbidity. Backgrounded Membrane Imaging (BMI) is a recently introduced methodology that provides a low-volume, high-throughput alternative to be used in biopharmaceutical development. Recent work has successfully evaluated BMI as an orthogonal method regarding its counting and sizing accuracy for subvisible particle analysis. The work at hand shows that apart from background noise, stochastic variations need to be considered to define the lower limit of detection. A systematic evaluation of particle identification robustness shows that particles at the lower and upper size limit of the technique are not reliably detected. To overcome potential biases due to particle crowding and overlapping, novel evaluation parameters are introduced: the Total Area, the Total Intensity and the BMI-Z-Average to be reported alongside the particle count. Overall, we were able to refine root causes for loss in data quality in BMI and to showcase the use of additional reporting parameters to shift focus to more robustly-identified and quantified larger particles
Catalyzing Biopharma Leaders: Sparking innovative medicines through inclusive engagement
No full textThe biopharma industry addresses the global unmet medical needs of patients through the discovery, development and access to medicines. To appropriately serve all populations, the consideration of variability to research model design, clinical study participants that represent the patient populations and their perspectives in medical research, varied perspectives and experiences , and engagement with educational ecosystems are pivotal. Literature reviews have addressed individual stages of the drug product lifecycle through these principles separately. This review aims at providing a holistic view of the specific application of inclusion and engagement principles in all stages of the lifecycle, catalyzing biopharma leaders into action, and educational activities in the context of guidelines, regulations, and case studies. Genetic heterogeneity, representative pre-clinical animal models, and data and algorithms to mitigate pre-clinical research bias are reviewed. Participation of all populations that reflect the clinical indication and the engagement of patient perspectives in clinical development is described. Principles for broad access, affordability, and healthcare system strengthening for inclusive access to medicines are explored post-regulatory approval. Finally, inclusive perspectives in product decision making and educational collaborations are described for upskilling the globally distributed biopharma workforce. A comprehensive understanding of these principles enables leaders to spark the development of safe and effective medicines that serve all patient groups by improving patient outcomes and health-related quality of life
Unlocking single cell RNA profiling at multicentre clinical trials: Strategies that Ensure Sample Integrity for gene expression analysis
No full textSingle cell omics is transforming the landscape of exploratory biomarker research, offering unprecedented insight into cellular complexity, heterogeneity, and interaction. While this approach provides a level of biological resolution far beyond traditional biomarker assays, the scaling of these technologies across multicenter clinical trials can present real challenges and costly delays.
Join us for a practical and forward-looking webinar where we’ll introduce two novel blood preservation methods that are simple to implement immediately after patient blood draw—no matter the site. Learn how these approaches can reduce variability, enhance data integrity, and support the reliable deployment of single cell profiling across complex clinical studies.
Two new, easy-to-implement blood preservation methods suitable for clinical sites
How these methods can reduce operational burden in multicenter trials
Ways to improve data quality through better sample preservation
The advantages and limitations of each preservation approac
An inflammation-associated control mechanism of allergy by proteolysis of IgE
No full textBackground: Acute IgE-mediated reactions are faster than adaptive immune responses which depend on IgM, IgA and IgG. Normal serum IgE concentrations are highly variable among individuals and extremely low in comparison with those of IgM and IgG. Omalizumab is a clinically approved monoclonal antibody that selectively binds free IgE, preventing allergy-specific IgE from binding to FcRI expressed on mast cells and basophils, thereby inhibiting degranulation and mediator release.
Methods: Proteolysis of IgE in vitro and in patient samples and biological effects of resulting IgE proteoforms were evaluated.
Results: Whereas IgG and IgM are neutrophil protease-resistant, the IgE heavy chain was cleaved in a bait region by these inflammation-associated proteases. The cleavages occurred on both free and CD-23-bound IgE, however, not with FcεRI-bound IgE. Proteolysis generated two proteoforms: a large IgE fragment (IgEcl) and a smaller IgE carboxyterminal fragment Cεtr. Proteolysed IgE did not bind to its receptors. The Cεtr fragment shared with chemokines high affinity to glycosaminoglycans (GAGs) and synergistically attracted neutrophils. The discovered bait site in IgE corresponded with a shared epitope recognized by Omalizumab and Omalizumab prevented IgE proteolysis. Both IgEcl and Cεtr were present in plasma from patients suffering from IgE-mediated allergies, chronic spontaneous urticaria, and more abundantly in atopic dermatitis (AD) patients.
Conclusions: This work reveals new mechanistic insights into the action of Omalizumab and into IgE immunology with clinical impacts. Indeed, IgE-specific cleavage by granulocyte proteinases may be an important feedback mechanism to control allergic responses
The Swiss Industrial Biocatalysis Consortium (SIBC) turns 20!
No full textIn 2024, the Swiss Industrial Biocatalysis Consortium (SIBC), celebrated its 20 years of bringing together experts from the pharma, flavor and fragrance, fine chemicals, and agrochemicals industries to discuss enzyme technology developments. In this perspective, we share recent examples of how our member organizations utilize biocatalysis in their respective industries. While the motivations for employing enzymatic synthesis and the end goals of various production processes may vary, we aim to emphasize the shared aspects that we are coming across. Over the past 20 years, those synergies have provided us with a fruitful basis for pre-competitive knowledge sharing around biocatalysis as a technology. We look forward to many more years of the SIBC and the surprises that await us through the potential of our enzymes
The transcription factor ZNF469 regulates collagen production in liver fibrosis.
No full textMetabolic dysfunction-associated steatotic liver disease (MASLD) - characterized by excess accumulation of fat in the liver - now affects one-third of the world's population. As MASLD progresses, extracellular matrix components including collagen accumulate in the liver, causing tissue fibrosis, a major determinant of disease severity and mortality. To identify transcriptional regulators of fibrosis, we computationally inferred the activity of transcription factors (TFs) relevant to fibrosis by profiling the matched transcriptomes and epigenomes of 108 human liver biopsies from a deeply characterized cohort of patients spanning the full histopathologic spectrum of MASLD. CRISPR-based genetic KO of the top 100 TFs identified ZNF469 as a regulator of collagen expression in primary human hepatic stellate cells (HSCs). Gain- and loss-of-function studies established that ZNF469 regulates collagen genes and genes involved in matrix homeostasis through direct binding to gene bodies and regulatory elements. By integrating multiomic large-scale profiling of human biopsies with extensive experimental validation, we demonstrate that ZNF469 is a transcriptional regulator of collagen in HSCs. Overall, these data nominate ZNF469 as a previously unrecognized determinant of MASLD-associated liver fibrosis
Combined inhibition of SHP2 overcomes adaptive resistance to type 1 BRAF inhibitors in BRAF V600E-driven high-grade glioma.
No full textBRAF-mutant gliomas can be targeted therapeutically using BRAF-selective inhibitors, yet responses are often transient due to adaptive resistance through reactivation of RAS-ERK signaling. Here, we evaluate the role of SHP2, a central regulator of RAS activity, and SHP2 inhibitors in overcoming resistance to BRAF inhibitors in glioma.RNAseq and protein expression in human tissue samples and glioma cell lines were used to identify resistance mechanisms. BRAF p.V600E glioma cell lines were tested to evaluate the impact of combined SHP2 and BRAF inhibition on ERK pathway activity, cell growth/death, and tumor forming ability. In vivo studies utilized heterotopic and orthotopic cell lines and patient-derived xenografts (PDX).We observed frequent ERK pathway reactivation in human glioma specimens following BRAF inhibitors, most commonly through EGFR and PDGFRβ activation. In glioma models, we observed that knockdown of SHP2 prevented adaptive upregulation of ERK activity in response to BRAF or MEK inhibitors. Combined small molecule inhibition with SHP2 and BRAF/MEK inhibitors increased the depth and durability of ERK suppression, inhibited growth, and killed tumor cells. RNA sequencing analysis revealed profound suppression of ERK transcriptional output with combined therapy and decreased EGFR reactivation. In cell lines with treatment-emergent resistance, combined SHP2 and BRAF inhibition overcame resistance to monotherapy. In vivo experiments confirmed enhanced tumor growth inhibition with combined therapy.Our findings demonstrate the critical role of RAS-ERK signaling reactivation in driving resistance to BRAF inhibition in glioma and demonstrate the potential utility of adding SHP2 inhibitors to overcome resistance
Skeletal Muscle Biomarkers of Amyotrophic Lateral Sclerosis: A Large-Scale, Multi-Cohort Proteomic Study
No full textImportance. Biomarkers are increasingly recognized as essential tools to advance Amyotrophic Lateral Sclerosis (ALS) therapy development, but their utility is critically dependent on having well-defined contexts-of-use.
Objective. Proteomic-based discovery and replication of plasma and cerebrospinal fluid biomarkers.
Design. Clinical phenotypic data and biofluid samples, collected from patients with ALS and healthy controls through several longitudinal observational studies, were used for the discovery and replication of biomarkers identified using SomaScan Version 4.1
Setting. Academic medical centers.
Participants. The discovery cohort included 161 people with ALS and 165 healthy controls. Longitudinal biological samples (median 4) were available from 132 people with ALS and 108 controls. The replication cohort included 83 people with ALS and 28 healthy controls. Longitudinal biological samples (3 visits) were available from 40 people with ALS.
Exposures. Disease state (ALS vs. healthy control).
Main Outcome(s) and Measure(s). SOMAmer (Slow Off-rate Modified Aptamer)-based semiquantitative measurement of ~7,000 proteins in plasma and CSF. Immunoassay validation of TNNT2 (Troponin T2) as a candidate biomarker of disease progression.
Results. We identified 329 plasma markers significantly differentially regulated between ALS and healthy controls (adjusted p.value 40% higher/lower relative abundance. PDLIM3, TNNT2, and MYL11 had the greatest log fold elevation. ANTXR2 and ART3 had the greatest log fold reduction. An overlapping set of plasma markers was found to increase (e.g. PDLIM3, TNNT2, and MYL11) or decrease (e.g. ANTXR2, ART3, and MSTN) with disease progression. CSF proteins with the greatest log fold elevation include NEFL, NEFH, CHIT1, CA3, MYL11 and GPNMB. Tissue specific signature enrichment based on GTEX and HPA suggest a significant contribution of muscle as a source of these biomarkers. Immunoassay validation of TNNT2, one of our lead biomarker candidates, shows strong correlation between SOMAmer intensity and TNNT2 concentration (R=0.81, p<2.2e-16), with TNNT2 increasing by 0.44ng/L per month.
Conclusions and Relevance. In addition to confirming previously reported biomarkers in plasma and CSF, we identified an array of biomarkers that not only differentiate ALS from controls but also change as the disease progresses. Several of these candidates are likely contributed by degenerating muscles. These candidate biomarkers have the potential to be implemented in the clinic to aid therapy development and to shed light on the underlying biology of the disease
A deep dive into spin-labeled polysorbate's interaction with therapeutic antibody using 2D NMR, EPR and MD simulations.
No full textPolysorbates (PS) are widely used surfactants in biopharmaceutical formulations playing a crucial role in protecting proteins against mechanical stress and interface-induced damage. However, their susceptibility to degradation can compromise their function and lead to particle formation. Recent studies suggest that monoclonal antibodies (mAbs) may mitigate PS degradation catalyzed by histidine chloride buffer, indicating the presence of protein-PS interactions. In this study, we investigated these interactions using NMR, starting with 1H T2 CPMG filter experiments and methyl fingerprinting, which failed to detect interactions. To enhance sensitivity, we synthesized spin-labeled PS (SLPS), enabling paramagnetic relaxation enhancement (PRE) NMR experiments, specifically amide fingerprinting, which successfully revealed interactions. Complementary electron paramagnetic resonance (EPR) measurements of SLPS and mAb also detected interactions, but only in the presence of sucrose, underscoring their weak and transient nature. Additionally, molecular dynamics simulations identified potential interaction hotspots on the antibody structure, providing mechanistic insights into these interactions