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Immune checkpoint inhibitors are increasingly used in combination with chemotherapy for the treatment of non-small cell lung cancer, yet the success of combination therapies is relatively limited. Thus, more detailed insight regarding the tumor molecular markers that may affect the responsiveness of patients to therapy is required. Here, we set out to explore the proteome of two lung adenocarcinoma cell lines (HCC-44 and A549) treated with cisplatin, pemetrexed, durvalumab, and the corresponding mixtures to establish the differences in post-treatment protein expression that can serve as markers of chemosensitivity or resistance. The mass spectrometry study showed that the addition of durvalumab to the treatment mixture resulted in cell line- and chemotherapeutic agent-dependent responses and confirmed the previously reported involvement of DNA repair machinery in the potentiation of the chemotherapy effect. Further validation using immunofluorescence also indicated that the potentiating effect of durvalumab in the case of cisplatin treatment was dependent on the tumor suppressor RB-1 in the PD-L1 weakly positive cells. In addition, we identified aldehyde dehydrogenase ALDH1A3 as the general putative resistance marker. Further studies in patient biopsy samples will be required to confirm the clinical significance of these findings.

Dopamine receptors are G-protein-coupled receptors that are connected to severe neurological disorders. The development of new ligands targeting these receptors enables gaining a deeper insight into the receptor functioning, including binding mechanisms, kinetics and oligomerization. Novel fluorescent probes allow the development of more efficient, cheaper, reliable and scalable high-throughput screening systems, which speeds up the drug development process. In this study, we used a novel Cy3B labelled commercially available fluorescent ligand CELT-419 for developing dopamine D3 receptor-ligand binding assays with fluorescence polarization and quantitative live cell epifluorescence microscopy. The fluorescence anisotropy assay using 384-well plates achieved Z' value of 0.71, which is suitable for high-throughput screening of ligand binding. The assay can also be used to determine the kinetics of both the fluorescent ligand as well as some reference unlabeled ligands. Furthermore, CELT-419 was also used with live HEK293-D3R cells in epifluorescence microscopy imaging for deep-learning-based ligand binding quantification. This makes CELT-419 quite a universal fluorescence probe which has the potential to be also used in more advanced microscopy techniques resulting in more comparable studies., Competing Interests: MM is the Chief Scientific Officer of Celtarys Research S.L. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Tahk, Laasfeld, Meriste, Brea, Loza, Majellaro, Contino, Sotelo and Rinken.)

Brightfield cell microscopy is a foundational tool in life sciences. The acquired images are prone to contain visual artifacts that hinder downstream analysis, and automatically removing them is therefore of great practical interest. Deep convolutional neural networks are state-of-the-art for image segmentation, but require pixel-level annotations, which are time-consuming to produce. Here, we propose ScoreCAM-U-Net, a pipeline to segment artifactual regions in brightfield images with limited user input. The model is trained using only image-level labels, so the process is faster by orders of magnitude compared to pixel-level annotation, but without substantially sacrificing the segmentation performance. We confirm that artifacts indeed exist with different shapes and sizes in three different brightfield microscopy image datasets, and distort downstream analyses such as nuclei segmentation, morphometry and fluorescence intensity quantification. We then demonstrate that our automated artifact removal ameliorates this problem. Such rapid cleaning of acquired images using the power of deep learning models is likely to become a standard step for all large scale microscopy experiments., (© 2022. The Author(s).)

M 4 muscarinic acetylcholine receptor is a G protein-coupled receptor (GPCR) that has been associated with alcohol and cocaine abuse, Alzheimer's disease, and schizophrenia which makes it an interesting drug target. For many GPCRs, the high-affinity fluorescence ligands have expanded the options for high-throughput screening of drug candidates and serve as useful tools in fundamental receptor research. Here, we explored two TAMRA-labelled fluorescence ligands, UR-MK342 and UR-CG072, for development of assays for studying ligand-binding properties to M 4 receptor. Using budded baculovirus particles as M 4 receptor preparation and fluorescence anisotropy method, we measured the affinities and binding kinetics of both fluorescence ligands. Using the fluorescence ligands as reporter probes, the binding affinities of unlabelled ligands could be determined. Based on these results, we took a step towards a more natural system and developed a method using live CHO-K1-hM 4 R cells and automated fluorescence microscopy suitable for the routine determination of unlabelled ligand affinities. For quantitative image analysis, we developed random forest and deep learning-based pipelines for cell segmentation. The pipelines were integrated into the user-friendly open-source Aparecium software. Both image analysis methods were suitable for measuring fluorescence ligand saturation binding and kinetics as well as for screening binding affinities of unlabelled ligands.

Since 1991, the NAD(P)H-aided conversion of resazurin to fluorescent resorufin has been widely used to measure viability based on the metabolic activity in mammalian cell culture and primary cells. However, different research groups have used divergent assay protocols, scarcely reporting the systematic optimization of the assay. Here, we perform extensive studies to fine-tune the experimental protocols utilizing resazurin-based viability sensing. Specifically, we focus on (A) optimization of the assay dynamic range in individual cell lines for the correct measurement of cytostatic and cytotoxic properties of the compounds; (B) dependence of the dynamic range on the physical quantity detected (fluorescence intensity versus change of absorbance spectrum); (C) calibration of the assay for the correct interpretation of data measured in hypoxic conditions; and (D) possibilities for combining the resazurin assay with other methods including measurement of necrosis and apoptosis. We also demonstrate the enhanced precision and flexibility of the resazurin-based assay regarding the readout format and kinetic measurement mode as compared to the widely used analogous assay which utilizes tetrazolium dye MTT. The discussed assay optimization guidelines provide useful instructions for the beginners in the field and for the experienced scientists exploring new ways for measurement of cellular viability using resazurin.

Despite the use of multimodal treatment combinations, the prognosis of glioblastoma (GB) is still poor. To prevent rapid tumor recurrence, targeted strategies for the treatment of GB are widely sought. Here, we compared the efficacy of focused modulation of a set of signaling pathways in two GB cell lines, U-251 MG and T98-G, using a panel of thirteen compounds targeting cell cycle progression, proliferation, epigenetic modifications, and DNA repair mechanism. In parallel, we tested combinations of these compounds with temozolomide and lomustine, the standard chemotherapy agents used in GB treatment. Two major trends were found: within individual compounds, the lowest IC 50 values were exhibited by the Aurora kinase inhibitors, whereas in the case of mixtures, the addition of DNA methyltransferase 1 inhibitor azacytidine to lomustine proved the most beneficial. The efficacy of cell cycle-targeting compounds was further augmented by combination with radiation therapy using two different treatment regimes. The potency of azacytidine and lomustine mixtures was validated using a unique assay pipeline that utilizes automated imaging and machine learning-based data analysis algorithm for assessment of cell number and DNA damage extent. Based on our results, the combination of azacytidine and lomustine should be tested in GB clinical trials., (© 2021. The Author(s).)

BRET and fluorescence anisotropy (FA) are two fluorescence-based techniques used for the characterization of ligand binding to G protein-coupled receptors (GPCRs) and both allow monitoring of ligand binding in real time. In this study, we present the first direct comparison of BRET-based and FA-based binding assays using the human M 2 muscarinic acetylcholine receptor (M 2 R) and two TAMRA (5-carboxytetramethylrhodamine)-labeled fluorescent ligands as a model system. The determined fluorescent ligand affinities from both assays were in good agreement with results obtained from radioligand competition binding experiments. The assays yielded real-time kinetic binding data revealing differences in the mechanism of binding for the investigated fluorescent probes. Furthermore, the investigation of various unlabeled M 2 R ligands yielded pharmacological profiles in accordance with earlier reported data. Taken together, this study showed that BRET- and FA-based binding assays represent valuable alternatives to radioactivity-based methods for screening purposes and for a precise characterization of binding kinetics supporting the exploration of binding mechanisms., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Dopamine receptors are G protein-coupled receptors that have several essential functions in the central nervous system. A better understanding of the regulatory mechanisms of ligand binding to the receptor may open new possibilities to affect the downstream signal transduction pathways. The majority of the available ligand binding assays use either membrane preparations, cell suspensions, or genetically modified receptors, which may give at least partially incorrect understanding of ligand binding. In this study, we implemented an assay combining fluorescence and bright-field microscopy to measure ligand binding to dopamine D 3 receptors in live mammalian cells. For membrane fluorescence intensity quantification from microscopy images, we developed a machine learning-based user-friendly software membrane tools and incorporated it into a data management software aparecium that has been previously developed in our workgroup. For the experiments, a fluorescent ligand NAPS-Cy3B was synthesized by conjugating a dopaminergic antagonist N-(p-aminophenethyl)spiperone with a fluorophore Cy3B. The subnanomolar affinity of NAPS-Cy3B makes it a suitable ligand for the characterization of D 3 receptors in live HEK293 cells. Using a microplate compatible automated widefield fluorescence microscope, together with the membrane tools software, enables the detection and quantification of ligand binding with a high-throughput. The live cell assay is suitable for the characterization of fluorescent ligand binding and also in the competition experiments for the screening of novel unlabeled dopaminergic ligands. We propose that this simple yet more native-like approach is feasible in GPCR research, as it enables the detection of ligand binding in an environment containing more components involved in the signal transduction cascade., (© 2020 Federation of European Biochemical Societies.)

Measurement of virus concentration is essential for effective virus-based transfection technologies. Here, we describe a user-friendly, image-based cell-size estimation (ICSE) assay for baculovirus quantification that relies on automated determination of cell diameters from bright-field microscopy images. In the ICSE assay, microplate-based imaging systems and our custom ICSE-Tools software enable measurement of cell morphological parameters over time. Results from the ICSE assay were in agreement with virus concentration measurements obtained using the traditional plaque assay as well as the Coulter principle-based cell-size measurement assay. ICSE-Tools is designed for data organization and image analysis from microplate-based imaging systems, and is freely available at www.gpcr.ut.ee/software.html.