Engelcarstens7101

Analysis of immunotherapy shows that these genes can discriminate between responder and non-responder.

This model can facilitate the identification of immune properties of genes, decoding tumor-immune interactions for precision immunotherapy in oncology.

This model can facilitate the identification of immune properties of genes, decoding tumor-immune interactions for precision immunotherapy in oncology.Three-dimensional (3D) culture systems have been developed that can re-capitulate organ level responses, simulate compound diffusion through complex structures, and assess cellular heterogeneity of tissues, making them attractive models for advanced in vitro research and discovery. Organoids are a unique subtype of 3D cell culture that are grown from stem cells, are self-organizing, and closely replicate in vivo pathophysiology. Organoids have been used to understand tissue development, model diseases, test drug sensitivity and toxicity, and advance regenerative medicine. However, traditional organoid culture methods are inadequate because they are low throughput and ill-suited for single organoid imaging, phenotypic assessment, and isolation from heterogenous organoid populations. To address these bottlenecks, we have adapted our tissue culture consumable and instrumentation to enable automated imaging, identification, and isolation of individual organoids. Organoids grown on the 3D CytoSortⓇ Array can be reliably tracked, imaged, and phenotypically analyzed using brightfield and fluorescent microscopy as they grow over time, then released and transferred fully intact for use in downstream applications. Using mouse hepatic and pancreatic organoids, we have demonstrated the use of this technology for single-organoid imaging, clonal organoid generation, parent organoid subcloning, and single-organoid RNA extraction for downstream gene expression or transcriptomic analysis. The results validate the ability of the CellRaft AIRⓇ System to facilitate efficient, user-friendly, and automated workflows broadly applicable to organoid research by overcoming several pain points 1) single organoid time-course imaging and phenotypic assessment, 2) establishment of single cell-derived organoids, and 3) isolation and retrieval of single organoids for downstream applications.Worldwide obesity, defined as abnormal or excessive fat accumulation that may result in different comorbidities, is considered a pandemic condition that has nearly tripled in the last 45 years. Most studies on obesity use animal models or adipocyte monolayer cell culture to investigate adipose tissue. However, besides monolayer cell culture approaches do not fully recapitulate the physiology of living organisms, there is a growing need to reduce or replace animals in research. In this context, the development of 3D self-organized structures has provided models that better reproduce the in vitro aspects of the in vivo physiology in comparison to traditional monolayer cell culture. Besides, recent advances in omics technologies have allowed us to characterize these cultures at the proteome, metabolome, transcription factor, DNA-binding and transcriptomic levels. These two combined approaches, 3D culture and omics, have provided more realistic data about determined conditions. Thereby, here we focused on the development of an obesity study pipeline including proteomic analysis to validate adipocyte-derived spheroids. Through the combination of collected mass spectrometry data from differentiated 3T3-L1 spheroids and from murine white adipose tissue (WAT), we identified 1732 proteins in both samples. By using a comprehensive proteomic analysis, we observed that the in vitro 3D culture of differentiated adipocytes shares important molecular pathways with the WAT, including expression of proteins involved in central metabolic process of the adipose tissue. Together, our results show a combination of an orthogonal method and an image-based analysis that constitutes a useful pipeline to be applied in 3D adipocyte culture.KRAS, the most frequently mutated oncogene in human cancers, was considered "undruggable" until the identification of small molecules that bind irreversibly to the mutant reactive cysteine at residue 12. Despite the encouraging anticancer activity of KRASG12C inhibitors in clinical trials, identification of more potent drugs is expected to achieve the maximal clinical benefit, which is hindered by the low sensitivity or throughput of current biochemical approaches. To overcome these limitations, a biotin-streptavidin-enhanced enzyme-linked immunosorbent assay (BA-ELISA) based on the competitive interaction of biotin-labeled probe and the test compound with KRASG12C was developed. Compared with reported assays, less protein was used in BA-ELISA, which significantly improves the resolution of inhibitor potency, thus contributing to the identification of highly potent inhibitors. Furthermore, BA-ELISA can also be expanded to determine the cellular potency of the inhibitors using KRASG12C mutant living cells. JAK Inhibitor I order Using three previously disclosed compounds, ARS-1620, AMG 510, and MRTX849, we demonstrated that BA-ELISA is a highly sensitive, specific, and robust method for high-throughput screening of KRASG12C inhibitors.Ion channels are drug targets for neurologic, cardiac, and immunologic diseases. Many disease-associated mutations and drugs modulate voltage-gated ion channel activation and inactivation, suggesting that characterizing state-dependent effects of test compounds at an early stage of drug development can be of great benefit. Historically, the effects of compounds on ion channel biophysical properties and voltage-dependent activation/inactivation could only be assessed by using low-throughput, manual patch clamp recording techniques. In recent years, automated patch clamp (APC) platforms have drastically increased in throughput. In contrast to their broad utilization in compound screening, APC platforms have rarely been used for mechanism of action studies, in large part due to the lack of sophisticated, scalable analysis methods for processing the large amount of data generated by APC platforms. In the current study, we developed a highly efficient and scalable software workflow to overcome this challenge. This method, to our knowledge the first of its kind, enables automated curve fitting and complex analysis of compound effects. Using voltage-gated sodium channels as an example, we were able to immediately assess the effects of test compounds on a spectrum of biophysical properties, including peak current, voltage-dependent steady state activation/inactivation, and time constants of activation and fast inactivation. Overall, this automated data analysis method provides a novel solution for in-depth analysis of large-scale APC data, and thus will significantly impact ion channel research and drug discovery.Mcm2-7 is the catalytic core of the eukaryotic replicative helicase, which together with CDC45 and the GINS complex unwind parental DNA to generate templates for DNA polymerase. Being a highly regulated and complex enzyme that operates via an incompletely understood multi-step mechanism, molecular probes of Mcm2-7 that interrogate specific mechanistic steps would be useful tools for research and potential future chemotherapy. Based upon a synthetic lethal approach, we previously developed a budding yeast multivariate cell-based high throughput screening (HTS) assay to identify putative Mcm inhibitors by their ability to specifically cause a growth defect in an mcm mutant relative to a wild-type strain[1]. Here, as proof of concept, we used this assay to screen a 1280-member compound library (LOPAC) for potential Mcm2-7 inhibitors. Primary screening and dose-dependent retesting identified twelve compounds from this library that specifically inhibited the growth of the Mcm mutant relative to the corresponding wild-type strain (0.9 % hit rate). Secondary assays were employed to rule out non-specific DNA damaging agents, establish direct protein-ligand interaction via biophysical methods, and verify in vivo DNA replication inhibition via fluorescence activated cell sorter analysis (FACS). We identified one agent (β-carboline-3-carboxylic acid N-methylamide, CMA) that physically bound to the purified Mcm2-7 complex (Kdapp119 µM), and at slightly higher concentrations specifically blocked S-phase cell cycle progression of the wild-type strain. In total, identification of Mcm2-7 as a CMA target validates our synthetic lethal HTS assay paradigm as a tool to identify chemical probes for the Mcm2-7 replicative helicase.The field of Immuno-Oncology (IO) is evolving to utilise novel antibody backbones that can co-target multiple cell-surface stimulatory and inhibitory co-receptors (SICR). This approach necessitates a better understanding of SICR co-expression at the single-cell level on IO-relevant tumor-infiltrating leukocyte (TIL) cell types such as T and natural killer (NK) cells. Using high-dimensional flow cytometry we established a comprehensive SICR profile for tumor-resident T and NK cells across a range of human solid tumors where there is a clear need for improved immunotherapeutic intervention. Leveraging the power of our large flow panel, we performed deep-phenotyping of the critical CD8+CD39+ Cytotoxic T Lymphocyte (CTL) population that is enriched for tumor-reactive cytotoxic cells, revealing subsets that are differentiated by their SICR profile, including three that are uniquely defined by NKG2A expression. This study establishes a comprehensive SICR phenotype for human TIL T and NK cells, providing insights to guide the design and application of the next generation of IO molecules.The severe acute respiratory syndrome coronavirus 2 responsible for COVID-19 remains a persistent threat to mankind, especially for the immunocompromised and elderly for which the vaccine may have limited effectiveness. Entry of SARS-CoV-2 requires a high affinity interaction of the viral spike protein with the cellular receptor angiotensin-converting enzyme 2. Novel mutations on the spike protein correlate with the high transmissibility of new variants of SARS-CoV-2, highlighting the need for small molecule inhibitors of virus entry into target cells. We report the identification of such inhibitors through a robust high-throughput screen testing 15,000 small molecules from unique libraries. Several leads were validated in a suite of mechanistic assays, including whole cell SARS-CoV-2 infectivity assays. The main lead compound, calpeptin, was further characterized using SARS-CoV-1 and the novel SARS-CoV-2 variant entry assays, SARS-CoV-2 protease assays and molecular docking. This study reveals calpeptin as a potent and specific inhibitor of SARS-CoV-2 and some variants.There is substantial evidence that in addition to nicotine, other compounds found in tobacco smoke significantly influence smoking behavior. Further, recent years have seen an explosion in the availability of non-combusted products that deliver nicotine, such as e-cigarettes and "home-brew" vaping devices that are essentially unregulated. There are many thousands of compounds in tobacco smoke alone, and new products are constantly introducing new compounds. Uncovering which of these compounds are active, across multiple smoking-relevant subtypes of the nicotinic acetylcholine receptor (nAChR) that influence tobacco/nicotine addiction, requires a high-throughput screening (HTS) approach. Accordingly, we developed a panel of HTS-friendly cell-based assays, all performed in the same cellular background and using the same membrane potential dye readout, to measure the function of the α3β4-, α4β2-, and α6β2-nAChR subtypes. These subtypes have each been prominently and consistently associated with human smoking behavior.