SynAI: an AI-driven cancer drugs synergism prediction platform.

Summary: The SynAI solution is a flexible AI-driven drug synergism prediction solution aiming to discover potential therapeutic value of compounds in early stage. Rather than providing a finite choice of drug combination or cell lines, SynAI is capable of predicting potential drug synergism/antagonism using in silico compound SMILE (Simplified Molecular Input Line Entry System) sequences. The AI core of SynAI platform has been trained against cell lines and compound pairs listed by NCI (National Cancer Institute)-Almanac and DurgCombDB datasets. In total, the training data consists of over 1 200 000 in vitro synergism tests on 150 cancer cell lines of different organ origins. Each cell line is tested against over 6000 pairs of FDA (Food and Drug Administration) approved compound combinations. Given one or both candidate compound in SMILE sequence, SynAI is able to predict the potential Bliss score of the combined compound test with the designated cell line without the needs of compound synthetization or structural analysis; thus can significantly reduce the candidate screening costs during the compound development. SynAI platform demonstrates a comparable performance to existing methods but offers more flexibilities for data input. Availability and implementation: The evaluation version of SynAI is freely accessible online at https://synai.crownbio.com.

Integrative application of silicon and/or proline improves Sweet corn (Zea mays L. saccharata) production and antioxidant defense system under salt stress condition.

Silicon (Si) and/or proline (Pro) are natural supplements that are considered to induce plants' stress tolerance against various abiotic stresses. Sweet corn (Zea mays L. saccharata) production is severely afflicted by salinity stress. Therefore, two field tests were conducted to evaluate the potential effects of Si and/or Pro (6mM) used as seed soaking (SS) and/or foliar spray (FS) on Sweet corn plant growth and yield, physio-biochemical attributes, and antioxidant defense systems grown in a saline (EC = 7.14dS m-1) soil. The Si and/or Pro significantly increased growth and yield, photosynthetic pigments, free proline, total soluble sugars (TSS), K+/Na+ratios, relative water content (RWC), membrane stability index (MSI), α-Tocopherol (α-TOC), Ascorbate (AsA), glutathione (GSH), enzymatic antioxidants activities and other anatomical features as compared to controls. In contrast, electrolytes, such as SS and/or FS under salt stress compared to controls (SS and FS using tap water) were significantly decreased. The best results were obtained when SS was combined with FS via Si or Pro. These alterations are brought about by the exogenous application of Si and/or Pro rendering these elements potentially useful in aiding sweet corn plants to acclimate successfully to saline soil.

Interplay of silymarin and clove fruit extract effectively enhances cadmium stress tolerance in wheat (Triticum aestivum).

Introduction: Osmoprotectant supplementation can be used as a useful approach to enhance plant stress tolerance. However, the effect of silymarin and clove fruit extract (CFE) on wheat plants grown under cadmium (Cd) stress has not been studied. Methods: Wheat seeds were planted in plastic pots filled with ions-free sand. A ½-strength Hoagland's nutrient solution was used for irrigation. Pots were treated with eight treatments thirteen days after sowing: 1) Control, 2) 0.5 mM silymarin foliar application [silymarin], 3) 2% CFE foliar application [CFE], 4) CFE enriched with silymarin (0.24 g silymarin L-1 of CFE) [CFE-silymarin], 5) Watering wheat seedlings with a nutritious solution of 2 mM Cd [Cd]. 6) Cadmium + silymarin, 7) Cadmium + CFE, and 8) Cadmium + CFE-silymarin. The experimental design was a completely randomized design with nine replicates. Results and discussion: The Cd stress decreased grain yield, shoot dry weight, leaf area, carotenoids, chlorophylls, stomatal conductance, net photosynthetic rate, transpiration rate, membrane stability index, nitrogen, phosphorus, and potassium content by 66.9, 60.6, 56.7, 23.8, 33.5, 48.1, 41.2, 48.7, 42.5, 24.1, 39.9, and 24.1%, respectively. On the other hand, Cd has an Application of CFE, silymarin, or CEF-silymarin for wheat plants grown under Cd stress, significantly improved all investigated biochemical, morphological, and physiological variables and enhanced the antioxidant enzyme activities. Applying CFE and/or silymarin enhanced plant tolerance to Cd stress more efficiently. Our findings suggest using CFE-silymarin as a meaningful biostimulator for wheat plants to increase wheat plants' tolerance to Cd stress via enhancing various metabolic and physiological processes.

Functional patient-derived organoid screenings identify MCLA-158 as a therapeutic EGFR × LGR5 bispecific antibody with efficacy in epithelial tumors.

Patient-derived organoids (PDOs) recapitulate tumor architecture, contain cancer stem cells and have predictive value supporting personalized medicine. Here we describe a large-scale functional screen of dual-targeting bispecific antibodies (bAbs) on a heterogeneous colorectal cancer PDO biobank and paired healthy colonic mucosa samples. More than 500 therapeutic bAbs generated against Wingless-related integration site (WNT) and receptor tyrosine kinase (RTK) targets were functionally evaluated by high-content imaging to capture the complexity of PDO responses. Our drug discovery strategy resulted in the generation of MCLA-158, a bAb that specifically triggers epidermal growth factor receptor degradation in leucine-rich repeat-containing G-protein-coupled receptor 5-positive (LGR5+) cancer stem cells but shows minimal toxicity toward healthy LGR5+ colon stem cells. MCLA-158 exhibits therapeutic properties such as growth inhibition of KRAS-mutant colorectal cancers, blockade of metastasis initiation and suppression of tumor outgrowth in preclinical models for several epithelial cancer types.

Doping control analysis of small peptides in human urine using LC-HRMS with parallel reaction monitoring mode: screening and confirmation.

This study described a reliable analytical method, which combines solid-phase extraction (SPE) with liquid chromatography-high resolution mass spectrometry (LC-HRMS) employing the parallel reaction monitoring (PRM) mode, for screening 41 small peptides and 3 non-peptide growth hormone secretagogues in human urine. Additionally 36 small peptides and 3 non-peptide growth hormone secretagogues were also confirmed in the same way. For the whole screening procedure, the PRM mode was applied to the HRMS detection of small peptides, which reduces the background noise from matrix compounds to a large extent and thus improves the selectivity and reliability of the peptide analytes. Meanwhile, competent chromatographic separation was achieved within a total runtime of 14 minutes, indicating an improvement in the detection efficiency. Moreover, the PRM mode could also be applied to the confirmation procedure due to its strong identification power with a low risk of generating false positives or negatives and good selectivity. Validation was performed according to the relevant World Anti-Doping Agency (WADA) criteria, including selectivity and reliability, limit of detection (LOD), limit of identification (LOI), recovery, extraction stability and carryover. The LODs of the peptide analytes ranged between 0.20 ng mL-1 and 0.92 ng mL-1 in urine, while their LOIs ranged between 0.20 ng mL-1 and 2.00 ng mL-1, which met the corresponding Minimum Required Performance Levels (MRPLs) as defined by WADA. The developed method furnished the rapid and sensitive detection of small peptides in urine for more than 5000 samples with no false-positive or false-negative, indicating that it is an eligible method for doping control analysis.

Differential reprogramming of breast cancer subtypes in 3D cultures and implications for sensitivity to targeted therapy.

Screening for effective candidate drugs for breast cancer has shifted from two-dimensional (2D) to three-dimensional (3D) cultures. Here we systematically compared the transcriptomes of these different culture conditions by RNAseq of 14 BC cell lines cultured in both 2D and 3D conditions. All 3D BC cell cultures demonstrated increased mitochondrial metabolism and downregulated cell cycle programs. Luminal BC cells in 3D demonstrated overall limited reprogramming. 3D basal B BC cells showed increased expression of extracellular matrix (ECM) interaction genes, which coincides with an invasive phenotype not observed in other BC cells. Genes downregulated in 3D were associated with metastatic disease progression in BC patients, including cyclin dependent kinases and aurora kinases. Furthermore, the overall correlation of the cell line transcriptome to the BC patient transcriptome was increased in 3D cultures for all TNBC cell lines. To define the most optimal culture conditions to study the oncogenic pathway of interest, an open source bioinformatics strategy was established.

3D imaging of colorectal cancer organoids identifies responses to Tankyrase inhibitors.

Aberrant activation of the Wnt signalling pathway is required for tumour initiation and survival in the majority of colorectal cancers. The development of inhibitors of Wnt signalling has been the focus of multiple drug discovery programs targeting colorectal cancer and other malignancies associated with aberrant pathway activation. However, progression of new clinical entities targeting the Wnt pathway has been slow. One challenge lies with the limited predictive power of 2D cancer cell lines because they fail to fully recapitulate intratumoural phenotypic heterogeneity. In particular, the relationship between 2D cancer cell biology and cancer stem cell function is poorly understood. By contrast, 3D tumour organoids provide a platform in which complex cell-cell interactions can be studied. However, complex 3D models provide a challenging platform for the quantitative analysis of drug responses of therapies that have differential effects on tumour cell subpopulations. Here, we generated tumour organoids from colorectal cancer patients and tested their responses to inhibitors of Tankyrase (TNKSi) which are known to modulate Wnt signalling. Using compounds with 3 orders of magnitude difference in cellular mechanistic potency together with image-based assays, we demonstrate that morphometric analyses can capture subtle alterations in organoid responses to Wnt inhibitors that are consistent with activity against a cancer stem cell subpopulation. Overall our study highlights the value of phenotypic readouts as a quantitative method to asses drug-induced effects in a relevant preclinical model.

In vitro 3D phenotypic drug screen identifies celastrol as an effective in vivo inhibitor of polycystic kidney disease.

Polycystic kidney disease (PKD) is a prevalent genetic disorder, characterized by the formation of kidney cysts that progressively lead to kidney failure. The currently available drug tolvaptan is not well tolerated by all patients and there remains a strong need for alternative treatments. The signaling rewiring in PKD that drives cyst formation is highly complex and not fully understood. As a consequence, the effects of drugs are sometimes difficult to predict. We previously established a high throughput microscopy phenotypic screening method for quantitative assessment of renal cyst growth. Here, we applied this 3D cyst growth phenotypic assay and screened 2320 small drug-like molecules, including approved drugs. We identified 81 active molecules that inhibit cyst growth. Multi-parametric phenotypic profiling of the effects on 3D cultured cysts discriminated molecules that showed preferred pharmacological effects above genuine toxicological properties. Celastrol, a triterpenoid from Tripterygium Wilfordii, was identified as a potent inhibitor of cyst growth in vitro. In an in vivo iKspCre-Pkd1lox,lox mouse model for PKD, celastrol inhibited the growth of renal cysts and maintained kidney function.

Transcriptome analysis of Cinnamomum longepaniculatum by high-throughput sequencing

Background: Cinnamomum longepaniculatum is an important commercial crop and the main source of volatile terpenoids. The biosynthesis of key bioactive metabolites of C. longepaniculatum is not well understood because of the lack of available genomic and transcriptomic information. To address this issue, we performed transcriptome sequencing of C. longepaniculatum leaves to identify factors involved in terpenoid metabolite biosynthesis. Results: Transcriptome sequencing of C. longepaniculatum leaves generated over 56 million raw reads. The transcriptome was assembled using the Trinity software and yielded 82,061 unigenes with an average length of 879.43 bp and N50 value of 1387 bp. Furthermore, Benchmarking Universal Single-Copy Orthologs analysis indicated that our assembly is 91% complete. The unigenes were used to query the nonredundant database depending on sequence similarity; 42,809 unigenes were homologous to known genes in different species, with an annotation rate of 42.87%. The transcript abundance and Gene Ontology analyses revealed that numerous unigenes were associated with metabolism, while others were annotated in functional categories including transcription, signal transduction, and secondary metabolism. The Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that 19,260 unigenes were involved in 385 metabolic pathways, with 233 unigenes found to be involved in terpenoid metabolism. Moreover, 23,463 simple sequence repeats were identified using the microsatellite identification tool. Conclusion: This is the first detailed transcriptome analysis of C. longepaniculatum. The findings provide insights into the molecular basis of terpenoid biosynthesis and a reference for future studies on the genetics and breeding of C. longepaniculatum.

High-Throughput Phenotypic Screening of Kinase Inhibitors to Identify Drug Targets for Polycystic Kidney Disease.

Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most interventions still focus on alleviating PKD-associated symptoms. The mechanistic complexity of the disease, as well as the lack of functional in vitro assays for compound testing, has made drug discovery for PKD challenging. To identify modulators of PKD, Pkd1-/- kidney tubule epithelial cells were applied to a scalable and automated 3D cyst culture model for compound screening, followed by phenotypic profiling to determine compound efficacy. We used this screening platform to screen a library of 273 kinase inhibitors to probe various signaling pathways involved in cyst growth. We show that inhibition of several targets, including aurora kinase, CDK, Chk, IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced cyst swelling. Additionally, we show that multiparametric phenotypic classification discriminated potentially undesirable (i.e., cytotoxic) compounds from molecules inducing the desired phenotypic change, greatly facilitating hit selection and validation. Our findings show that a pathophysiologically relevant 3D cyst culture model of PKD coupled to phenotypic profiling can be used to identify potentially therapeutic compounds and predict and validate molecular targets for PKD.

Cellular adhesome screen identifies critical modulators of focal adhesion dynamics, cellular traction forces and cell migration behaviour.

Cancer cells migrate from the primary tumour into surrounding tissue in order to form metastasis. Cell migration is a highly complex process, which requires continuous remodelling and re-organization of the cytoskeleton and cell-matrix adhesions. Here, we aimed to identify genes controlling aspects of tumour cell migration, including the dynamic organization of cell-matrix adhesions and cellular traction forces. In a siRNA screen targeting most cell adhesion-related genes we identified 200+ genes that regulate size and/or dynamics of cell-matrix adhesions in MCF7 breast cancer cells. In a subsequent secondary screen, the 64 most effective genes were evaluated for growth factor-induced cell migration and validated by tertiary RNAi pool deconvolution experiments. Four validated hits showed significantly enlarged adhesions accompanied by reduced cell migration upon siRNA-mediated knockdown. Furthermore, loss of PPP1R12B, HIPK3 or RAC2 caused cells to exert higher traction forces, as determined by traction force microscopy with elastomeric micropillar post arrays, and led to considerably reduced force turnover. Altogether, we identified genes that co-regulate cell-matrix adhesion dynamics and traction force turnover, thereby modulating overall motility behaviour.

Development of a 3D Tissue Culture-Based High-Content Screening Platform That Uses Phenotypic Profiling to Discriminate Selective Inhibitors of Receptor Tyrosine Kinases.

3D tissue cultures provide a more physiologically relevant context for the screening of compounds, compared with 2D cell cultures. Cells cultured in 3D hydrogels also show complex phenotypes, increasing the scope for phenotypic profiling. Here we describe a high-content screening platform that uses invasive human prostate cancer cells cultured in 3D in standard 384-well assay plates to study the activity of potential therapeutic small molecules and antibody biologics. Image analysis tools were developed to process 3D image data to measure over 800 phenotypic parameters. Multiparametric analysis was used to evaluate the effect of compounds on tissue morphology. We applied this screening platform to measure the activity and selectivity of inhibitors of the c-Met and epidermal growth factor (EGF) receptor (EGFR) tyrosine kinases in 3D cultured prostate carcinoma cells. c-Met and EGFR activity was quantified based on the phenotypic profiles induced by their respective ligands, hepatocyte growth factor and EGF. The screening method was applied to a novel collection of 80 putative inhibitors of c-Met and EGFR. Compounds were identified that induced phenotypic profiles indicative of selective inhibition of c-Met, EGFR, or bispecific inhibition of both targets. In conclusion, we describe a fully scalable high-content screening platform that uses phenotypic profiling to discriminate selective and nonselective (off-target) inhibitors in a physiologically relevant 3D cell culture setting.

Hierarchical classification strategy for Phenotype extraction from epidermal growth factor receptor endocytosis screening.

BACKGROUND: Endocytosis is regarded as a mechanism of attenuating the epidermal growth factor receptor (EGFR) signaling and of receptor degradation. There is increasing evidence becoming available showing that breast cancer progression is associated with a defect in EGFR endocytosis. In order to find related Ribonucleic acid (RNA) regulators in this process, high-throughput imaging with fluorescent markers is used to visualize the complex EGFR endocytosis process. Subsequently a dedicated automatic image and data analysis system is developed and applied to extract the phenotype measurement and distinguish different developmental episodes from a huge amount of images acquired through high-throughput imaging. For the image analysis, a phenotype measurement quantifies the important image information into distinct features or measurements. Therefore, the manner in which prominent measurements are chosen to represent the dynamics of the EGFR process becomes a crucial step for the identification of the phenotype. In the subsequent data analysis, classification is used to categorize each observation by making use of all prominent measurements obtained from image analysis. Therefore, a better construction for a classification strategy will support to raise the performance level in our image and data analysis system. RESULTS: In this paper, we illustrate an integrated analysis method for EGFR signalling through image analysis of microscopy images. Sophisticated wavelet-based texture measurements are used to obtain a good description of the characteristic stages in the EGFR signalling. A hierarchical classification strategy is designed to improve the recognition of phenotypic episodes of EGFR during endocytosis. Different strategies for normalization, feature selection and classification are evaluated. CONCLUSIONS: The results of performance assessment clearly demonstrate that our hierarchical classification scheme combined with a selected set of features provides a notable improvement in the temporal analysis of EGFR endocytosis. Moreover, it is shown that the addition of the wavelet-based texture features contributes to this improvement. Our workflow can be applied to drug discovery to analyze defected EGFR endocytosis processes.

Identification of anti-tumour biologics using primary tumour models, 3-D phenotypic screening and image-based multi-parametric profiling.

BACKGROUND: Monolayer cultures of immortalised cell lines are a popular screening tool for novel anti-cancer therapeutics, but these methods can be a poor surrogate for disease states, and there is a need for drug screening platforms which are more predictive of clinical outcome. In this study, we describe a phenotypic antibody screen using three-dimensional cultures of primary cells, and image-based multi-parametric profiling in PC-3 cells, to identify anti-cancer biologics against new therapeutic targets. METHODS: ScFv Antibodies and designed ankyrin repeat proteins (DARPins) were isolated using phage display selections against primary non-small cell lung carcinoma cells. The selected molecules were screened for anti-proliferative and pro-apoptotic activity against primary cells grown in three-dimensional culture, and in an ultra-high content screen on a 3-D cultured cell line using multi-parametric profiling to detect treatment-induced phenotypic changes. The targets of molecules of interest were identified using a cell-surface membrane protein array. An anti-CUB domain containing protein 1 (CDCP1) antibody was tested for tumour growth inhibition in a patient-derived xenograft model, generated from a stage-IV non-small cell lung carcinoma, with and without cisplatin. RESULTS: Two primary non-small cell lung carcinoma cell models were established for antibody isolation and primary screening in anti-proliferative and apoptosis assays. These assays identified multiple antibodies demonstrating activity in specific culture formats. A subset of the DARPins was profiled in an ultra-high content multi-parametric screen, where 300 morphological features were measured per sample. Machine learning was used to select features to classify treatment responses, then antibodies were characterised based on the phenotypes that they induced. This method co-classified several DARPins that targeted CDCP1 into two sets with different phenotypes. Finally, an anti-CDCP1 antibody significantly enhanced the efficacy of cisplatin in a patient-derived NSCLC xenograft model. CONCLUSIONS: Phenotypic profiling using complex 3-D cell cultures steers hit selection towards more relevant in vivo phenotypes, and may shed light on subtle mechanistic variations in drug candidates, enabling data-driven decisions for oncology target validation. CDCP1 was identified as a potential target for cisplatin combination therapy.

The nuclear factor κB family member RelB facilitates apoptosis of renal epithelial cells caused by cisplatin/tumor necrosis factor α synergy by suppressing an epithelial to mesenchymal transition-like phenotypic switch.

Cis-diamminedichloroplatinum(II) (cisplatin)-induced renal proximal tubular apoptosis is known to be preceded by actin cytoskeleton reorganization, in conjunction with disruption of cell-matrix and cell-cell adhesion. In the present study, we show that the proinflammatory cytokine tumor necrosis factor α (TNF-α) aggravated these cisplatin-induced F-actin and cell adhesion changes, which was associated with enhanced cisplatin-induced apoptosis of immortalized proximal tubular epithelial cells. TNF-α-induced RelB expression and lentiviral small hairpin RNA (shRNA)-mediated knockdown of RelB, but not other nuclear factor κB members, abrogated the synergistic apoptosis observed with cisplatin/TNF-α treatment to the level of cisplatin-induced apoptosis. This protective effect was associated with increased stress fiber formation, cell-matrix, and cell-cell adhesion in the shRNARelB (shRelB) cells during cisplatin/TNF-α treatment, mimicking an epithelial-to-mesenchymal phenotypic switch. Indeed, gene array analysis revealed that knockdown of RelB was associated with upregulation of several actin regulatory genes, including Snai2 and the Rho GTPase proteins Rhophilin and Rho guanine nucleotide exchange factor 3 (ARHGEF3). Pharmacological inhibition of Rho kinase signaling re-established the synergistic apoptosis induced by combined cisplatin/TNF-α treatment of shRelB cells. In conclusion, our study shows for the first time that RelB is required for the cisplatin/TNF-α-induced cytoskeletal reorganization and apoptosis in renal cells by controlling a Rho kinase-dependent signaling network.

The residence time of focal adhesion kinase (FAK) and paxillin at focal adhesions in renal epithelial cells is determined by adhesion size, strength and life cycle status.

Focal adhesions (FAs) are specialized membrane-associated multi-protein complexes that link the cell to the extracellular matrix and enable cell proliferation, survival and motility. Despite the extensive description of the molecular composition of FAs, the complex regulation of FA dynamics is unclear. We have used photobleaching assays of whole cells to determine the protein dynamics in every single focal adhesion. We identified that the focal adhesion proteins FAK and paxillin exist in two different states: a diffuse cytoplasmic pool and a transiently immobile FA-bound fraction with variable residence times. Interestingly, the average residence time of both proteins increased with focal adhesion size. Moreover, increasing integrin clustering by modulating surface collagen density increased residence time of FAK but not paxillin. Finally, this approach was applied to measure FAK and paxillin dynamics using nocodazole treatment followed by washout. This revealed an opposite residence time of FAK and paxillin in maturing and disassembling FAs, which depends on the ventral and peripheral cellular position of the FAs.

Automated analysis of NF-κB nuclear translocation kinetics in high-throughput screening.

Nuclear entry and exit of the NF-κB family of dimeric transcription factors plays an essential role in regulating cellular responses to inflammatory stress. The dynamics of this nuclear translocation can vary significantly within a cell population and may dramatically change e.g. upon drug exposure. Furthermore, there is significant heterogeneity in individual cell response upon stress signaling. In order to systematically determine factors that define NF-κB translocation dynamics, high-throughput screens that enable the analysis of dynamic NF-κB responses in individual cells in real time are essential. Thus far, only NF-κB downstream signaling responses of whole cell populations at the transcriptional level are in high-throughput mode. In this study, we developed a fully automated image analysis method to determine the time-course of NF-κB translocation in individual cells, suitable for high-throughput screenings in the context of compound screening and functional genomics. Two novel segmentation methods were used for defining the individual nuclear and cytoplasmic regions: watershed masked clustering (WMC) and best-fit ellipse of Voronoi cell (BEVC). The dynamic NFκB oscillatory response at the single cell and population level was coupled to automated extraction of 26 analogue translocation parameters including number of peaks, time to reach each peak, and amplitude of each peak. Our automated image analysis method was validated through a series of statistical tests demonstrating computational efficient and accurate NF-κB translocation dynamics quantification of our algorithm. Both pharmacological inhibition of NF-κB and short interfering RNAs targeting the inhibitor of NFκB, IκBα, demonstrated the ability of our method to identify compounds and genetic players that interfere with the nuclear transition of NF-κB.

cAMP signalling protects proximal tubular epithelial cells from cisplatin-induced apoptosis via activation of Epac.

BACKGROUND AND PURPOSE: Nephrotoxicity is the principal dose-limiting factor for cisplatin chemotherapy and is primarily associated with proximal tubular epithelial cells, including disruption of cell adhesions and induction of apoptosis. Cell adhesion and survival is regulated by, amongst other factors, the small GTPase Rap and its activator, the exchange protein directly activated by cAMP (Epac). Epac is particularly enriched in renal tubule epithelium. This study investigates the cytoprotective effects of cAMP-Epac-Rap signalling in a model of cisplatin-induced renal cell injury. EXPERIMENTAL APPROACH: The Epac-selective cAMP analogue 8-pCPT-2'-O-Me-cAMP was used to activate the Epac-Rap signalling pathway in proximal tubular epithelial cells. Cells were exposed to cisplatin, in the presence or absence of 8-pCPT-2'-O-Me-cAMP, and nephrotoxicity was determined by monitoring cell-cell junctions and cell apoptosis. KEY RESULTS: Activation of Epac-Rap signalling preserves cell-cell junctions and protects against cell apoptosis of mouse proximal tubular cells during cisplatin treatment. Activation with the Epac-selective cAMP analogue 8-pCPT-2'-O-Me-cAMP or receptor-mediated induction of cAMP both induced cytoprotection against cisplatin, whereas a PKA-selective cAMP analogue was not cytoprotective. 8-pCPT-2'-O-Me-cAMP mediated cytoprotection was blocked by RNAi-mediated silencing of Epac-Rap signalling in these cells. In contrast, 8-pCPT-2'-O-Me-cAMP did not protect against cisplatin-induced cell death of cancer cells that lacked Epac1 expression. CONCLUSIONS AND IMPLICATIONS: Our study identifies activation of Epac-Rap signalling as a potential strategy for reducing the nephrotoxicity associated with cisplatin treatments and, as a result, broadens the therapeutic window of this chemotherapeutic agent.

Systems microscopy approaches to understand cancer cell migration and metastasis.

Cell migration is essential in a number of processes, including wound healing, angiogenesis and cancer metastasis. Especially, invasion of cancer cells in the surrounding tissue is a crucial step that requires increased cell motility. Cell migration is a well-orchestrated process that involves the continuous formation and disassembly of matrix adhesions. Those structural anchor points interact with the extra-cellular matrix and also participate in adhesion-dependent signalling. Although these processes are essential for cancer metastasis, little is known about the molecular mechanisms that regulate adhesion dynamics during tumour cell migration. In this review, we provide an overview of recent advanced imaging strategies together with quantitative image analysis that can be implemented to understand the dynamics of matrix adhesions and its molecular components in relation to tumour cell migration. This dynamic cell imaging together with multiparametric image analysis will help in understanding the molecular mechanisms that define cancer cell migration.