Multiparametric high-content imaging assays have become established to classify cell phenotypes from functional genomic and small-molecule library screening assays. Several groups have implemented machine learning classifiers to predict the mechanism of action of phenotypic hit compounds by comparing the similarity of their high-content phenotypic profiles with a reference library of well-annotated compounds. However, the majority of such examples are restricted to a single cell type often selected because of its suitability for simple image analysis and intuitive segmentation of morphological features. The aim of the current study was to evaluate and compare the performance of a classic ensemble-based tree classifier trained on extracted morphological features and a deep learning classifier using convolutional neural networks (CNNs) trained directly on images from the same dataset to predict compound mechanism of action across a morphologically and genetically distinct cell panel. Our results demonstrate that application of a CNN classifier delivers equivalent accuracy compared with an ensemble-based tree classifier at compound mechanism of action prediction within cell lines. However, our CNN analysis performs worse than an ensemble-based tree classifier when trained on multiple cell lines at predicting compound mechanism of action on an unseen cell line. This allows the use of more physiologically relevant cell-based assay conditions and also provides a phenotypic profile to help elucidate the MoA for hits discovered by target-agnostic phenotypic screening.6Cellular morphology is influenced by multiple intrinsic and extrinsic factors acting on cell physiology. Striking changes in morphology are observed when cells are exposed to biologically active small molecules. Compound-induced alteration in morphology is a manifestation of various perturbed cellular processes. We can hypothesize that compounds with a similar mechanism of action (MoA), which act upon the same signaling pathways, will produce comparable phenotypes, and that cell morphology can predict compound MoA. Multiparametric high-content imaging assays have become established across a number of screening groups to classify cell phenotypes from functional genomic and small-molecule library screening assays.2 The majority of early high-content phenotypic profiling studies, utilizing morphological profiling, applied unsupervised hierarchical clustering in order to group treatments into bins that produce similar cellular phenotypes.7 More recently, several groups have evolved phenotypic profiling through the application of machine learning classifiers to predict the MoA of phenotypic hits, by comparing the similarity of the high-content phenotypic profiles with a reference library of well-annotated compounds.8 This can be performed by arranging unannotated compounds in feature space and using proximity to nearby labeled data to infer MoA.10 A slightly different approach is to train a classifier with labeled data and then attach labels to unknown compounds.12 However, the majority of such examples of compound MoA prediction are restricted to a single cell type, often selected because of its suitability for simple image analysis and intuitive segmentation of morphological features. The restriction of multiparametric high-content image analysis to single “easy-to-image” cell line models limits the application of phenotypic profiling and MoA classification studies across more morphologically complex and disease-relevant cell-based assay systems. Furthermore, the expansion of multiparametric high-content studies across broader panels of morphologically and genetically distinct cell lines, which more accurately represents the heterogeneity of human disease, has several benefits. This allows correlation of phenotypic response data with basal genomic, transcriptomic, or proteomic data to support further understanding of compound MoA at the molecular level and identification of biomarkers of phenotypic response. Such application of multiparametric high-content phenotypic screens across larger cell line panels, equivalent to the Cancer Cell Line Encyclopedia (CCLE) or Genomics of Drug Sensitivity in Cancer (GDSC) and new emerging induced pluripotent stem cell (iPSC)-derived model resources, can further support drug repurposing and pharmacogenomic studies across more complex cell-based phenotypes.A landmark paper in the field of high-content phenotypic profiling was published in 2004, when Perlman et al. first demonstrated that multiparametric phenotypic fingerprints could be clustered according to compound MoA using a custom similarity metric and hierarchical clustering.14 (Suppl. Table S1) applied to eight genetically and morphologically distinct human breast cancer cell lines, representing four clinical subtypes Convolutional neural networks (CNNs) trained on five-channel imagesMore specifically, we evaluate and quantify the performance of an ensemble-based tree classifier and a CNN classifier, with regards to predicting compound MOA, when trained and predicted on each individual cell line and on “previously unseen” additional cell types.l-glutamine, incubated at 37 °C humidified and 5% CO2.The breast cancer cell line panel Table 1 Cells were plated in 96-well optical bottom plates  at a density of 2500 cells per well in 100 µL of media in the inner 60 wells and incubated for 24 h before compound treatment.Compounds Table 2 Suppl. Table S1). Thirty microliters of cell painting solution was added to plates and left to incubate for 30 min at room temperature in the dark. Plates were then washed with 100 µL of PBS three times; after the final aspiration and addition of PBS, plates were sealed with a transparent plate seal .To label cells in 96-well plates, the cells were fixed by adding an equal volume of 8% paraformaldehyde  to the existing media, resulting in a final paraformaldehyde concentration of 4%, which was left to incubate for 30 min at room temperature. The plates were then washed with 100 µL of phosphate-buffered saline (PBS) and permeabilized with 50 µL of 0.1% Triton X-100 solution for 20 min at room temperature. A solution of cell painting reagents was made up in 1% bovine serum albumin (BSA) solution (see Suppl. Table S1) at 20× magnification; exposure times were kept constant between plates and batches as to not influence intensity values. Images were captured across four different sites per well, with each site containing approximately 50–200 cells in negative control wells depending on the cell line, with the MDA-MB-157 cell line containing fewer cells per image compared with the other tested cell lines due to the large cell size characteristics of that particular cell line.Imaging was carried out on an ImageXpress micro XL , a multiwavelength wide-field fluorescent microscope equipped with a robotic plate loader . In the cell painting assay used for this study, images were acquired in five fluorescent channels . Using these masks marking the boundary of cellular objects, we measured morphological features for multiple image channels returning per object measurements. Out-of-focus and low-quality images were detected through saturation and focus measurements and removed from the dataset. Image averages of single-object (cell) measurements were aggregated by taking the median of each measured feature per image. Features were normalized on a plate-by-plate basis by dividing each feature by the median DMSO response for that feature; a z score was then calculated for each feature over the entire pooled dataset to standardize each feature to a mean of zero and unit variance. Feature selection was performed by calculating pairwise correlations of features and removing one of a pair of features that have a correlation greater than 0.9, and removing features with very low or zero variance of cellular objects.Images were analyzed using CellProfiler v2.1.1The ensemble tree-based classifier was implemented using scikit-learn’s (version 0.19) “GradientBoostingClassifier” with default parameters except for the number of estimators, which was increased from 100 to 600. Data used for the tree-based classifier were median profiles representing an image average of the morphological features, and test accuracy was measured using the Jaccard similarity score.16 to accept input in the form of five-channel arrays rather than the typical RGB three-channel images. The models were trained with batches of 32 images per graphics processing unit (GPU) with random 90° rotations for 20 epochs with an initial learning rate of 0.01 with an ADAM optimizer17 using categorical cross-entropy as the loss function; test accuracy was measured with the Jaccard similarity score.The CNN classifier was implemented in PyTorch (version 0.3.0) by modifying the ResNet18 architectureSuppl. Fig. S1).The number of epochs was chosen based as the point at which training and validation accuracies plateaued, as well as losses stopped decreasing, when training and predicting MoAs on a single cell line , for each individual breast cancer cell type, are presented in Suppl. Fig. S2). Training the CNN classifier on a dataset in which the training examples contained equal numbers of each class greatly improved accuracy when predicting an unseen cell line. Accuracies were slightly below those of the tree-based classifier , likely due to the reduced number of training examples available.The predictive performance of the classifiers applied to unseen cell lines was compared by training on seven out of the eight cell lines and testing on the withheld eighth cell line. The ensemble-based tree classifier saw a reasonable reduction in classification accuracy when tested on unseen cell lines Fig. 3a.Suppl. Fig. S4), with accuracies similar to those of ResNet18 models trained and tested on the same cell line  are becoming increasingly common in a wide range of machine learning classification tasks, and the convolution aspect of CNNs plays an important role when working with image data. CNNs have recently been applied to the classification of cell phenotypes from high-content imaging data, where they have been shown to perform well when using highly optimized publicly available high-content benchmarking datasets.11 Many groups have reported increased accuracy of CNN classifiers on high-content imaging data over approaches using extracted morphological features, which is in contrast to our own findings , a single dataset is split into training and test partitions. The method used in this study randomly sampled proportions, which may lead to overfitting and overoptimistic prediction accuracies due to the test data containing replicates from the same wells as found in the training set, as well as the same compound at different concentrations. Alternative approaches, which can be used in such instances, include a “hold one compound out” cross-validation strategy9 . As would be expected, using the LOCO and LOCACLO cross-validation strategies decreases prediction accuracies when compared with training and testing on random partitions of image data for both CNN and gradient-boosted tree classifiers. However, the cross-validation strategies mirror the results of the random partition of training and test method in that there was a significant loss of prediction accuracy when the CNN model was transferred to an unseen cell line .Predicting compound MoA from high-content image-based screening is a classification task, which can be approached in two ways. The first method is to develop an image analysis algorithm to extract morphological information from the images of cells and generate a multivariate dataset describing cellular phenotypes, which are subsequently used to train a classifier.findings Fig. 2.918 The ability to predict compound MoA with a high degree of accuracy, despite the machine learning model never having seen this cell line before, will be very useful, for example, in cases where an investigator has trained a model on a large annotated compound set and would like to predict MoAs from further compound screens in new cell lines, without having to rescreen and retrain.Specific experimental questions addressed by this current study include direct comparison of the predictive performance between classical machine learning (ensemble-based tree classifier) and deep learning (CNN) models, when applied to predicting compound MoA across a disease-relevant panel of morphologically distinct human breast cancer cell lines. We further address how well the performance of each machine learning model can generalize to new cell line data. We trained our machine learning models on seven breast cancer cell lines and tested prediction accuracy on a withheld eighth cell line. Both types of classifier suffered a reduction in classification accuracy when applied to unseen cell lines, although the CNN performed noticeably worse on certain cell lines. This difference between classifier performance is likely explained by the data preprocessing steps in which the data for the ensemble tree-based classifier are subjected to plate-by-plate normalization to the negative control values, which will remove many of the cell line-specific morphologies, while this normalization step is not replicated in the CNN data preprocessing. As this is essentially an overfitting problem, there may be additional measures, such as further image augmentation, that may improve the generalizability of CNN models to distinct cell lines.We also assessed if the addition of more data from morphologically distinct cell lines during model training increases prediction accuracy when applied to the classification of a single cell line. It was found that the CNN classifier did not benefit from the additional data, and that the possible benefit of more training examples did not overcome the increased heterogeneity and morphological differences between the cell lines. The ensemble-based tree classifier did generally benefit from additional training examples, although model performance was highly variable and sensitive to the combination of additional cell lines used during training. This leads us to the conclusion that more data are not necessarily better when training classifiers for MoA prediction, and those cell line-specific morphologies can dramatically impact model performance.There are a number of reasons why transferring an MoA classifier from one cell line to another may fail. One possible explanation is that the intrinsic morphological differences between different cell lines are greater than the morphological changes induced by a compound, and that classifiers with no knowledge of cell line labels may confuse compound-induced morphologies with cell line morphologies. For example, if a cell line inherently has a large cell area morphology, it may often cause classification errors for compounds, which cause more spindle-like cell lines to spread. Alternatively, there may be a biological explanation, such as differential expression, mutation, or alternative splicing of pharmacological targets between the cell lines or altered downstream pathways, which may alter the phenotypic response of a cell line to a particular small molecule.Our results indicate that while a CNN classifier may represent an efficient approach to study compound MoAs across larger cell line panels, the trained models are difficult to generalize between morphologically distinct cell lines. The more classical machine learning models trained on extracted morphological features offer opportunities to normalize the data in order to remove cell line-specific effects and improve model generalizability and transferability between cell lines. Broad cell panel screening studies that include cell line models presenting with more complex heterogeneous cell morphologies, including “clumpy” cell cultures, present significant challenges to efficient cell segmentation. The use of CNNs and the omission of custom image analysis algorithms for each cell line remove considerable resource burden and experimental or human bias when performing high-content imaging studies across morphologically distinct cell panels. Therefore, investigators need to weigh the pros and cons of each approach and its suitability to the dataset under investigation. Furthermore, the implementation of CNNs is likely to support the application of high-content phenotypic profiling and MoA classification across a broader variety of mechanistic classes and more complex assays, including iPSC differentiation, co-culture, and 3D models, which are often unsuitable for image-based segmentation. Alternatively, classical machine learning techniques, like ensemble-based tree classifiers, are much easier to interpret than CNNs, and inform which morphological features are important for distinguishing between mechanistic compound classes.www.github.com/CarragherLab/2018-08_transfer_ML_between_cell_lines). We anticipate that these data will support the high-content image analysis and machine learning communities, to further evolve new approaches to high-content phenotypic profiling and MoA prediction across morphologically distinct cell panels and more complex cell-based assay formats.We anticipate that the methods and results presented in this article will support an increased prediction accuracy of compound MoAs across a broader variety of cell-based assay systems, including genetically distinct cell panels. Such approaches are well placed to advance in vitro pharmacogenomic studies beyond simple univariate assay endpoints toward more complex assays and phenotypes. Finally, we provide all source code and MoA datasets used in this study through a dedicated open-access link (Click here for additional data file.Supplemental material, Supplemental_Material_for_Evaluation_of_machine_learning_classifiers_by_Warchal_et_al-final-version3 for Evaluation of Machine Learning Classifiers to Predict Compound Mechanism of Action When Transferred across Distinct Cell Lines by Scott J. Warchal, John C. Dawson and Neil O. Carragher in SLAS Discovery


Saurauja roxburghii. Derivatization of ursolic acid by oxidation with dioxoruthenium (VI) tetraphenylporphyrins was investigated. Oxidation selectivity on the terpene structure was modulated by the auxiliaries introduced on the tetraphenylporphyrin. The natural triterpenes and oxidized derivatives were tested for cytotoxicity against the C6 rat glioma and A431 human skin carcinoma cell lines. Although they have the same ursane-type pentacyclic triterpene cores, the position and numbers of hydroxyls on the terpene structures significantly affected the activity and the selectivity towards the tested cell lines.Structure-activity relationships of ursane-type pentacyclic triterpenes obtained from natural sources and by chemical derivatization are reviewed. Ursolic acid, corosolic acid, and a new ursane-type pentacyclic triterpene, 7,24-dihydroxyursolic acid, were isolated from the methanolic extract of the leaves of the Bangladeshi medicinal plant,  Exploration of novel drugs or drug leads from Nature has been the major subject in natural product chemistry . Some poPlants have been utilized as medicines for thousands of years. These medicines initially took the form of crude drugs such as tinctures, teas, poultices, powders, and other herbal formulations ,3. The sCatharanthus roseus (L.) G. Don (Apocynaceae) (formerly Vinca rosea L.) and have been used clinically for over 40 years [Podophyllum peltatum L. (Berberidaceae) but was found to be too toxic in mice so derivatives were made, with the first clinically approved drug being etoposide [Taxus brevifolia Nutt. (Taxaceae) and was clinically introduced to the U.S. market in the early 1990s. Camptothecin was isolated from Camptotheca acuminata Decne. (Nyssaceae) but originally showed unacceptable myelosuppression [Drug discovery from medicinal plants has played an especially important role in the treatment of cancer and, indeed, most new clinical applications of plant secondary metabolites and their derivatives over the last half century have been applied towards combating cancer. Of the all available anticancer drugs between 1940 and 2002, 40% were natural products or natural product-derived, with another 8% considered natural product mimics ,6,7. Antpression ,11,12. Ipression . Togethe et al. [1) is a highly promising anticancer drug after inducing apoptosis in melanoma cell lines in vitro and in vivo , which are putative precursors of colon cancer, and increased neutral sphingomyelinase activity [Ursane type pentacyclic triterpenes abundantly exist in the plant kingdom. Of the ursane type pentacyclic triterpenes, ursolic acid . Among the 23 derivatives they synthesized, 3β-amino derivative 3 was found to be 20 times more potent than the parent ursolic acid on the HL-60, Bel-7402 and HeLa cell lines. Usually, compounds with β-oriented hydrogen-bond forming groups at C-3 exhibit more potent cytotoxicity than their α-counterparts. Besides, dimeric compounds 4 and 5 show selective cytotoxicity against HL-60 cell lines. Similarly, Shao et al. [6–9. Their SAR studies also showed that a polar group at either the 3-OH and/or 17-COOH positions was essential for the cytotoxic activity. Alternatively, C-2 cyano or trifluoromethyl derivatives of 1-en-3-one-ursolic acid (compounds 10 and 11) showed higher activity than C-2 iodo- and non-substituted analogues (compounds 12 and 13) in antiproliferation assays using KU7, 253JB-V, Panc-1, and Panc-28 cancer cell lines (IC50: 0.17–1.13 mM) [14) was reported to significantly reduce the formation of skin tumors. Concurrently, 14 inhibited the tissue plasminogen activator (TPA), generation of NO, and expression of iNOS and COX-2, which are important factors in tumor promotion [14 induced apoptosis in PPC-1 and U-87MG cancer cells. Two new ursane-type triterpenes, microfokienoxane C (15) and 3β,28-dihydroxy-11α-methoxyurs-12-ene (16) have recently been isolated from the leaves of Microtropis fokienensis; compound 15 showed cytotoxic activity against HepG2 and Hep3B cancer cell lines while compound 16 exhibited the activity against the HepG2 cell line [Several attempts were undertaken for the derivatization of ursolic acid seeking to obtain analogs with improved anti-tumor activity . Chao-Me et al.  modifiedo et al.  also syn1.13 mM) . Among tell line . Boswell et al. [Saurauja roxburghii. This is an evergreen tree belonging to the family Dilleniaceae commonly found in Bangladesh, Butan, Northeast India, Nepal, Malaysia, Pakistan and Sri Lanka with various local names such as Sing krang, Sing khau, etc. Hereinafter Tanaka et al. [Thus, ursolic acid and its derivatives have been reported to show cytotoxicity against some cancer cell lines but have not been thoroughly explored in comparison to beutalinic acid derivatives and other lupanes. For examples, besides the derivatization of preexisting hydroxyl groups, their number and position in ursane triterpene structures, which may affect the cytotoxic activity, have not been investigated. Under such circumstances, recently Mazumder et al.  investiga et al.  develope et al. [Saurauja roxburghii, where powdered plant leaves were soaked in MeOH for seven days with occasional shaking and stirring (n-hexane-chloroform (1:1), chloroform-methanol , and then methanol), and then subjected to the repeated reverse phase (RP)-HPLC, otherwise normal phase HPLC was used. Eventually five ursane-type triterpenes were isolated , along with (3) the thirty carbon signals in 13C-NMR, which include two olefinic carbons for C-12 and C-13 and one down field carbonyl carbon for C-28 at around δ 180. Although Mazumder et al. [1H and/or 13C NMR signals, i.e., only the differences in the number of hydroxyls and/or the position of the hydroxyl and the methyl substitutions in the same skeleton  and 0.96 , the 12-H vinyl proton at 5.49 (t) and the doublet methine proton (for 18-H) at 2.64 . Stereochemistry of the 3-hydroxyl on the A-ring was elucidated by the observation of the doublet/doublet 3-H proton signal at 3.46 ; such coupling constants indicated the 3-H proton was oriented as one axial/axial and one equatorial/axial orientations in the A-ring, hence the α-proton. This substitution was further confirmed by the 13C-NMR signal of C-3 at 78.2 ppm [1H-1H COSY, HMQC, and HMBC experiments [24, corosolic acid, was obtained as a white amorphous solid. The ursane-12-en skeleton of this terpenoid was deduced as being similar to that of ursolic acid [13C-NMR analysis detected the two oxygenated methane signals at 69.1 (C-2) and 83.9 (C-3), which suggested a 2,3-dihydroxyl ursolic acid structure [i.e., the 2,3-dihydroxyls, was unambiguously concluded by 2D-NMR experiments such as 1H-1H COSY, HMQC and HMBC data. Compound 25, 24-hydroxyl corosolic acid, was obtained as a white amorphous solid. This natural terpene contains the ursane-12-en skeleton with the two hydroxy substitutions at the C-2 and C-3, showing very similar NMRs to those of the corosolic acid 24. The 1H-NMR showed the diastereotopic hydroxymethylene protons as two doublet protons at 3.37 and 4.01, which in turn exhibited the cross-peak correlation with a carbon signal at 66.2 in HSQC spectrum. The further analysis of NOE, HMBC and NOESY confirmed the structure as 2,3,24-trihydroxyl-urs-12-en-28-oic acid. Compound 26, maslinic acid, was obtained as a white amorphous solid. The NMR data were very similar to those of the corosolic acid 24 except for the environment around the dimethyl groups in the E-ring; while two methyl signals in the corosolic acid 24 split into the doublets, they were both singlets in 26. Additionally, no COSY correlations were observed among the 29-H, 19-H, 20-H, and 30-H as in 24. Based on DEPT analysis, the compound 26 should contain the gem-dimethyl substituent at the C-20 position of the E-ring, hence leading to the maslinic acid structure, a positional isomer of corosolic acid. Compound 27 was reported as new compound, which was obtained as an amorphous solid. IR detected the representative absorption bands for the ursane-12-en structure, such as the hydroxyl , carbonyl , and olefinic  groups. The 1H-NMR, 13C-NMR, and HMBC correlation suggested the structure of 27 being very similar to the 24-hydroxyl corosolic acid 24. Thus, 1H-NMR detected the characteristic proton signals for the ursane-12-en skeleton, i.e., one olefinic proton at 5.22, four singlet methyl proton at 0.81, 0.96, 1.08, and 1.13, and two doublet methyl protons at 0.88  and at 0.96 .13C-NMR analysis also detected the two olefinic carbons at 126.7 and 139.7, in addition to the six methyl signals at 17.4, 17.6, 17.7, 21.6, 23.1, and 24.1. As the case of the other ursane-12-en-type structures 2, 24, 25, the cis-fused D/E ring systems was also confirmed by the observation of the NOESY correlation between 12-H and 18-H. The observation of the carbon signals at 65.9 , 66.9 (methine carbon), and 74.6 (methine carbon), suggested the presence of three hydroxyls on the ursane-12-en skeleton; the oxymethine carbon at C-3 (74.6) was assigned through HMBC correlations with H- 23 (1.08) and H-24 (3.63). NOE between the 3-H and axial 1-H concluded the β-orientation of the hydroxyl at C-3. Alternatively, the oxymethylene at the β-substituted C-24 position (65.9) was assigned through the HMBC correlations with 23-H (1.08), 5-H (1.31), and 3-H (3.73), as well as the NOESY correlation with 1-H. The oxymethine at C-7 (66.9) was also assigned based on the HMBC correlations with 5-H (1.31) and 6-H (1.32); the NOESY correlation with axial 3-H and the bridgehead 27-H moreover determined the -axial orientation of 7-H (hence the β-hydroxyl at C-7). The1H-1H COSY and HMQC experiments were further carried out to assign all proton and carbon signals in 27, giving rise to a new corosolic acid derivative, 3, 7, 24-trihydroxyl-urs-12-en-28-oic acid. This compound further been confirmed by ESI-QTOF MS/MS fragmentation analysis [As these urs-12-en-28-oic acids are widely available in the plant kingdom, their basic skeletons , 5-H 1., and 3-Hi.e., the mimic of cytochrome P450, might diversify the core-structure of ursolic acid (2) [ i.e., the oxidation efficiency of the C–H, O–H, or olefins at the different positions of the target substrates. The following sections review the development of ‘Ru’-porphyrin catalysts, the oxidative derivatization of ursolic acid and modulation of the cytotoxicity towards different cancer cell lines.As described above, the hydroxylation patterns of ursane-type triterpenes significantly affects the cytotoxicity. These hydroxylated terpene metabolites are produced in many higher plants through the action of cytochrome P450 ,33. The acid (2) . The aut et al. [Selective oxygenation of saturated C-H bonds has been a major challenge in synthetic chemistry as exemplified by the pioneering work of Breslow and co-workers ,43,44,45 et al. . i.e., oxidation efficiency of the C-H, O-H, or olefins at the different positions of the target substrates. We employed the ruthenium porphyrin derivatives 3.8a–g as oxidation catalysts for the oxidation of ursolic acid 2 12 in hot decalin [3.8a–g in 20%–30% yields. Then, an in situ oxidation protocol was used employing porphyrins 3.8a–g  was oxidized to afford variously oxidized products, including lactone 28 [29 [30 [31 and 32 [33 [28–33 were known natural and/or chemically derivatized compounds. While the compound 33 was obtained by the oxidation of the C3-hydroxyl group of 2, the compounds 28–32 could be derived by the allylic oxidation at C-11. We also obtained the small amounts of other oxidized products, which might be derived from the oxidation of the inactivated C-H bonds on the terpene skeleton, but enough amounts could not be obtained to determine their structures. Thus, under the conditions given in ctone 28  C-11-hyde 28 [29 ,55 C-11- [29 [30  dienes 31 and 32  and C-3-d 32 [33 . All of 28–33 was clearly affected by the auxiliaries of the ‘Ru’-porphyrins 3.8a–g. Thus, the parent ‘Ru’-porphyrins 3.8a–g gave the lactone 28 (25%) and the α-hydroxylated compound 29 (35%) as two major products (29 was significantly decreased by the acid derivative 3.8b (4%), instead equally producing the other derivatives 30–32 (each about 10%); the introduction of the acid group on the metalloporphyrin might cause the interaction with the substrate 2, for example, with the carboxylic acid or the hydroxyl groups in 2, hence altering the oxidation selectivity. On the other hand, while the (R)-isomers 3.8d and 3.8e gave the α-hydroxylated 29 as the major product (entries 4 and 5), the reactivity of the corresponding (S)-oxidants 3.8f and 3.8g was significantly reduced (entries 6 and 7). For both cases, the oxidation efficiency was retarded by using the sterically more demanding 1-naphthyl derivatives 3.8e and 3.8g . Meanwhile, the ketone 33 was solely obtained when the indane derivatives 3.8c was used (entry 3) [3.8a–g gave profound effects on the oxidation reactivity and selectivity, and even small functional groups on the side chains of the tetraphenylporphyrins, i.e., acid, amides, or chirality, could recognize the triterpene structure 2, and exhibited matched and/or mismatched combinations for the dioxoruthenium-catalyzed oxidation.We observed that the distribution of the oxidized products products , but theentry 3) . This is2, 24–27 against two tumor cell lines, i.e., the human epidermoid carcinoma cell line, A431 and the rat glioma cell line, C6 [2, 24–27 were dissolved in 100% ethanol and then diluted with Dulbecco's Modified Eagle's Medium (DMEM) as the working solutions which were added to the cells with a final volume of 0.2 mL  and cultured over 0, 3 h, 6 h, 12 h, 24 h and 48 h, respectively [2) exhibited the cytotoxicity against C6 rat glioma at the concentrations of 10–100 μM, while this terpenoid did not show any activity towards the A431 carcinoma (24) showed cytotoxicity against the both cell lines (2) and corosolic acid (24) was the additional hydroxyl group at the C-2 in 24  or by shifting the C-19 methyl to the C-20 (maslinic acid 26), made the compounds inactive (26) is reported to show the cytotoxicity against HT29 human colon-cancer cells [25, is a strong cytotoxic natural product against some cancel cells, such as the human glioblastoma cell lines U-87, human breast cancer cell lines MCF-7 (ATCC HTB-22), MDA-MD-231 (ATCC HTB-26), and the human hepatoma cell Hep G2 [ i.e., functional group substitutions and/or stereochemistry, make these triterpene natural products promising candidates for drug development and/or for tools for investigating the mode of action. On the other hand, for chemically oxidized compounds 28–33, cytotoxicity was also examined as the same way as described for compounds 2, 24–27. It was observed that only the lactone 28 had cytotoxic activity against both the A431 and C6 tumor cell lines; therefore we can conclude that the oxidation at the C-11 and C-13 positions of ursolic acid (2), gave ursolic acid an additional cytotoxic activity against A431 tumor cell. Thus, the authors observed that the cytotoxic activity and the tumor selectivity of the natural and the chemically oxidized ursolic acids are sensitively modulated by simply modulating the oxidation states on the core terpene structure. Again, the simple modification of the cytotoxic inactive . These rer cells ; hence ml Hep G2 ,61. Thus i.e., with carboxyl or hydroxyl groups, of which structural variants exhibit a diverse range of activities. Alternatively, the core terpene structures could also be derivatized by the chemical oxidation in pursuit of enhancing the activity and/or modulating the target selectivity, i.e., against a specific tumor cell line. We investigated the isolation of the natural products from the extracts of the Bangladeshi medicinal plant, Saurauja roxburghii, a higher plant indigenous to south East Asia and some parts of North America. By using conventional extraction procedures, we isolated the five ursane-type pentacyclic triterpenes. The structures of these five compounds were unambiguously determined by extensive NMR and MS analyses, and also by comparisons with the literature data, if available. Then these natural triterpenes were tested for cytotoxicity against the C6 rat glioma and A431 human skin carcinoma cell lines. Very interestingly, despite the fact that these five compounds have the same ursane-type pentacyclic triterpene core structures, only ursolic acid (2) and corosolic acid (24) showed cytotoxicity at 10 μM concentrations. Furthermore, while the corosolic acid showed the cytotoxicity against both cell lines, ursolic acid exhibited selective cytotoxicity against the C6 glioma cell. These results clearly show that the position and numbers of hydroxyls on the terpene structure affect the activity and selectivity to the cancer cell lines. Inspired by these results, our group sought to diversify the hydrophobic ursane-type triterpene ursolic acid, for further SAR studies, by applying chemical oxidation using “Ru”-porphyrins. The newly developed auxiliary catalyzed ‘Ru’-tetraphenylporphyrins chemical oxidation system could produce oxidized ursolic acid derivatives could give a new direction in designing the porphyrin-based reagents as well as other oxidants. It is noted that the chemically oxidized products 28–33 were all naturally occurring compounds, but were difficult to isolate from the S. roxburghii in previous investigations, thus the chemical protocol can be complementary to the isolation of natural products.Natural products are the most consistently successful sources of biologically diverse compounds, and especially, plants provide a large bank of rich, complex, and highly varied structures. Many higher plants contain densely oxidized terpene metabolites,


The present 1H HR-MAS NMR-based metabolomic study was performed on ovarian cancer cell line A2780, on its cis-Pt resistant variant A2780cisR, and on the cell line HEK-293 treated with 0.03 µM and 0.015 µM of DiRu-1 corresponding to full and half IC50 doses, respectively, to investigate the mode of action of this ruthenium complex. The resulting changes in the metabolic profile of the cell lines were studied using HR-MAS NMR of cell lysates and a subsequent statistical analysis. We show that DiRu-1 in a 0.03 µM dose has significant impact on the levels of a number of metabolites, such as glutamine, glutamate, glutathione, cysteine, lipid, creatine, lactate, and acetate, especially pronounced in the A2780cisR cell line. The IC50/2 dose shows some significant changes, but full IC50 appears to be necessary to observe the full effect. Overall, the metabolic changes observed suggest that redox homeostasis, the Warburg effect, and the lipid metabolism are affected by DiRu-1.The trithiolato bridged diruthenium complex DiRu-1 [( RAPTA-C has been very active in vivo, where it inhibited lung metastases in mice. RAED compounds are highly cytotoxic against a number of cancer cell lines including those that developed resistance against cis-Pt  with the corresponding aromatic thiols. The most active compound obtained so far is [(η6-p-MeC6H4Pri)2Ru2(µ2-SC6H4-p-But)3]Cl (DiRu-1) , estrogen-responsive breast adenocarcinoma (MCF-7) and triple-negative breast adenocarcinoma (MDA-MB-231) cell lines with IC50 values in the nanomolar range (Our group has developed a large variety of diruthenium (DiRu-1) , with anar range . A recenIt is a matter of fact that the energy metabolism of cancer cells is altered compared to that of healthy cells. The change in metabolism manifesting as cancer cells ferment glucose to lactate even in the presence of oxygen instead of mitochondrial oxidative phosphorylation is known as the Warburg effect ,13. WhilIncreased conversion of glutamine (Gln) to glutamate (Glu) is another characteristic observed in cancer . It has Beside this, redox homeostasis pathways are upregulated. An example can be serine metabolism which leads to the production of dihydronicotinamide-adenine dinucleotide phosphate (NADPH) and GSH . Additio50 of DiRu-1 (0.03 µM) and to a half-dose (0.015 µM). Non-tumor HEK-293 cell line was used to provide a reference.In this context, the knowledge of the influence of DiRu-1 on the metabolism of ovarian cancer cells will help us to elucidate its modes of action. For this purpose, the effect of DiRu-1 treatment on the metabolic changes in the A2780 and A2780cisR cell lines was investigated. The cells were treated with DiRu-1 in a dose corresponding to the IC3, (–CH2)n, and α-CH2 groups. Since these resonances are typical for the long alkyl chains present in various types of lipids such as phospholipids, fatty acids, or triglycerides, they will be referred to as lipid resonances throughout the manuscript. The 1H high resolution magic angle spinning (HR-MAS) NMR 1-D NOESY and T2-filtered PROJECT [In this study, the cells were lysed prior to an NMR investigation in order to reach higher stability . Therefo PROJECT  spectra 1H-NMR spectra recorded with the PROJECT sequence [2-fitered suppression of broad components improves the visibility of small metabolite resonances as can be seen in In order to perform a statistical analysis, the spectra were manually divided into 52 buckets in the aliphatic and 44 buckets in the aromatic region . The bucsequence  were useThe effects of DiRu-1 were statistically tested based on the bucketed spectra providing data matrices of 10 × 52  and 10 × 44 (aromatic region) for each group  and each cell line. The models obtained from principal component analysis (PCA) showed some clustering of the three treatment groups but no separation between them ; Table 2Buckets that strongly contribute to the separation observable in the score plots of both PCA and PLS/PLS-DA  were ideIdentified metabolites and changes in their levels are summarized in 3, (–CH2)n, lipid β-CH2, and α-CH2, and were significant for ω-CH3, (–CH2)n, and α-CH2. Of note, the decreases were also significant for ω-CH3, (–CH2)n, and α-CH2 when half of the IC50 dose was applied.The levels of lipids based on the evaluation of individual detected groups were significantly altered only for the A2780cisR cell line. Decreases were observed after DiRu-1 treatment for the groups that were clearly identified, namely ω-CHThe phosphocholine level increased significantly in both treated A2780cisR and HEK-293 cell lines, and the choline level did not change significantly upon treatment with DiRu-1 in any of the tested cell lines.GSH was upregulated especially in A2780cisR and to a smaller extent also in the HEK-293 cell line. Using the lower dose of 0.015 µM, the significant upregulation occurred only in A2780cisR cells.The glutamine (Gln) level changed in all three cell lines but only upon treatment with 0.03 µM of DiRu-1. Interestingly, a significant increase of the Gln level was observed for A2780cisR while a decrease was observed for the other two cell lines. On the other hand, the glutamate (Glu) level decreased significantly in A2780cisR already with a 0.015 µM dose of DiRu-1.Amino acids cysteine (Cys), alanine (Ala), leucine (Leu), tyrosine (Tyr), and phenylalanine (Phe) showed a trend towards increased or decreased values, which, however, were not significant after correcting for multiple comparisons. All of the changes to be considered occurred in the A2780cisR cell line with the exception of Phe which decreased consistently only in A2780.The myo-inositol showed an increase in one of the two buckets in A2780cisR when the 0.015 µM dose of DiRu-1 was applied. Overall, most of the changes on myo-inositol were not significant across the cell lines.The changes in AMP were not very consistent in any of the cell lines. The AMP level decreased in one of the two buckets in the case of the A2780 cell line treated with DiRu-1. There were no consistent changes in the other two cell lines.The uracil level changed consistently only in A2780cisR where it showed an increase upon DiRu-1 treatment but was not significant. In the other two cell lines, the changes were neither consistent nor significant. In general, changes in uracil, uridine diphosphate (UDP), and uridine triphosphate (UTP) levels were not very consistent, as can be seen in The creatine level increased significantly in A2780cisR treated with DiRu-1. The change was significant for both doses and in both buckets assigned to creatine (Cre). No consistent Cre changes were observed in the A2780 or HEK-293 cell lines treated with the complex.The lactate level dropped significantly in the A2780cisR and HEK-293 cell lines upon treatment with DiRu-1. In both cases, the effect was significant when using the 0.015 –µM DiRu-1 dose.The acetate level decreased significantly only in A2780cisR cells when treated with any of the two doses of DiRu-1.Further, there were yet unidentified buckets 6, 10, 15, 21, 23, 27, 35, and 43 which showed significant changes in A2780cisR. Bucket 10 showed over 100% increase when treated with any of the two doses compared to the control. A somewhat smaller but still very high increase was observed also for bucket 35. Buckets 21, 23, 35, and 39 showed significant changes in the HEK-293 cell line as well.Correlation analysis was performed on normalized integral averages using the Pearson algorithm. The results are visualized as heatmaps. For every cell line, control and 0.03 µM DiRu-1 treated groups were tested. For each identified metabolite, a representative bucket was chosen .2 and (–CH2)n seem to be correlated positively with acetate level as well as with Glu and AMP and negatively with phosphocholine and Ura in the A2780cisR cell line. In the A2780 and HEK-293 cell lines, the correlations were not uniform across different lipid signals.The heatmaps give a complex overview over the correlations among a number of different metabolites identified in the cell spectra. From the heatmaps, it is observed that the correlation of Glu with Gln is, to some extent, positive in the A2780 and HEK-293 cell lines in contrast to the A2780cisR cell line where negative correlation can be observed. GSH is positively correlated with Ura/UDP/UTP in all three cell lines and in A2780cisR significantly. It is further negatively correlated with a bucket assigned to nicotinamide adenine dinucleotide (NADH) in all three cell lines and in HEK-293 significantly. Lipid levels based on β-CHp-cymene complexes. The most active compound DiRu-1 showed significant cytotoxicity against different cancer cell lines. Nevertheless, its mode of action is still not fully understood. It has been shown that it is able to catalyze GSH oxidation, but this mechanism can only partly account for the measured cytotoxicity. Interestingly, recent ICP-MS studies showed that up to 97% of Ru is localized in the mitochondria of treated cancer cells [Over the last years, our group developed a number of trithiolato bridged diruthenium er cells .1H-HR-MAS NMR spectroscopy. We show that the treatment of the cells with DiRu-1 at a dose of 0.03 µM (IC50) induces significant changes in the metabolic profile of the A2780cisR cell line and to a less extent of the metabolic profile of the HEK-293 cell line. Interestingly, the metabolic profile of the A2780 cell line seems to be less affected upon treatment with DiRu-1, suggesting a different mode of action in the two A2780 cell lines.In this study, three cell lines were treated with DiRu-1 and analyzed using In A2780cisR cells, we have observed that (i) the GSH level increased significantly even after treatment with the 0.015 µM dose of DiRu-1 and that (ii) the Gln level increased and (iii) the Glu level dropped using the 0.03 µM dose. The Cys level drop with lesser significance was additionally observed. The increase in GSH levels was observed to some extent in the other two cell lines as well but with less significance. Similarly, an increase in GSH in both cancer cell lines has been observed in cells treated with a Ru prism . ElevateGln level increased while Glu showed a significant drop in the A2780cisR cell line while no such consistent changes were observed in the other two cell lines. A negative correlation, yet not statistically significant, has been observed in the heatmap for A2780cisR cells. On the contrary, the correlation in the other two cell lines was positive for these two metabolites. Gln has multiple roles in cells. It serves as a source of carbon; reduces nitrogen; and is involved in the production of GSH, nucleotides, and lipids. Further, it seems to be involved in cell signaling. In cancer, it has multiple roles including neoplasm manifestation, tumor progression, and metastasis. Gln metabolism varies with organs, and different subtypes of cancer can show distinct metabolic patterns. Glu, the first product of Gln catabolism, is either consumed or released from the cell. The efflux is coupled to Cys influx ,30,31. B50 values against both A2780 cell lines. Also, Cramer et al. showed that the depletion of Cys following the introduction of a pharmacologically optimized cysteinase resulted in cell death of cancer cells due to the depletion of GSH and the accumulation of ROS [Cys availability is one of key factors in the first step of GSH synthesis . As repon of ROS . The decThe level of creatine increased significantly only in A2780cisR cells; this effect occurred even when the lower of the doses was applied. Creatine plays a number of roles in a cell. Among other functions, it is an antioxidant with possible protective activity on oxidatively damaged mitochondria ,37,38. I3, (–CH2)n, lipid β-CH2, and α-CH2 groups, are another group of metabolites that changed significantly only in A2780cisR cells. A similar effect, a decrease in the detected level of lipids, has been earlier described for A2780 cells treated with a Ru prism. The same study reported an increase in detected lipid levels in treated HEK-293 cells and inconsistent changes in A2780cisR cells [Lipids, at least as represented by the ω-CHsR cells . Herein,sR cells ,32. The sR cells ,41,42,43The lactate level decreased significantly in both the A2780cisR and HEK-293 cell lines. A similar effect has been earlier observed for a Ru prism . Higher When evaluating the results of this study, certain limitations needs to be taken into account. Analogously to the earlier study reported by our group , we chos50/2) shows yet a number of significant changes, it appears that IC50 represents the necessary dose to observe the most significant changes. Interestingly, there are significant differences in the metabolic responses of A2780 and A2780cisR cells treated with DiRu-1 despite responding to the same IC50 value of DiRu-1 as has been shown previously. It is possible that the mechanism of DiRu-1 action differs in the two cell lines. The exact reasons behind this observation remain yet to be explained.Most of the significant changes were observed in A2780cisR cells, and while the lower dose of DiRu-1 . The HEK-293 cell line was provided by Prof. Mühlemann, University of Bern.2. HEK-293 cells were grown in Dulbecco’s Modified Eagle Medium (DMEM) with the same supplements as in the previous case with additional 1% HEPES pH buffer.A2780 cells were grown in Roswell Park Memorial Institute (RPMI) 1640 medium containing 10% fetal calf serum (FCS), 2 mM Gln, and 1% antibiotics (penicillin/streptomycin) at 37 °C and 5% CO50 values when compared to ovarian cancer cells A2780, indicating no high selectivity [Cytotoxicity tests of DiRu-1 for A2780 and A2780cisR were determined previously using the 3--2,5-diphenyltetrazolium bromide (MTT) assay . In thisectivity ,48,49.2 flasks with a density of 8 × 104 cells/cm2 and left to grow for 24 h at 37 °C in a humidified incubator in the presence of 5% CO2. The incubation time of 24 h has been chosen as in our previous study on a similar Ru complex; we have shown that 24 h incubation was adequate to observe a sufficient effect [In each group, 10 independently prepared samples have been measured, leading to a total number of 90 measurements . The cells used for the metabolomics study were firstly seeded in 25 cmt effect .2O (controls).Afterwards, the medium in which the cells were grown was disposed. Subsequently, the cells were washed with 5 mL of phosphate-buffered saline (PBS). For drug treatment, 5 mL of fresh DMEM or RPMI-1640 medium were added to the flasks containing 3 µL aqueous solutions of DiRu-1 to reach a final concentration of 0.03 µM or 0.015 µM, respectively, or solely HAfter 24 h of incubation, the medium was disposed and cells were washed with 5 mL of PBS. Subsequently, trypsin/ethylenediaminetetraacetic acid (EDTA) was added, and after ~5 min, when the cells detached, 1 mL of DMEM was added and cells were transferred into new Falcon tubes. Cell viability was determined using 10 µL of 0.4% Trypan Blue Stain for 10 µL of cell suspension. An automatic cell counter was used for this purpose. The cells were further centrifuged and, after disposal of the supernatant, resuspended in freezing medium . The cell suspension was then transferred into cryovials and kept frozen at −80°C.2O, alternatingly sonicated for 30 s and dipped into liquid nitrogen for 15 s three times, and finally frozen in liquid N2 and stored at −80 °C.To prepare the cell lysate samples for NMR analysis, the cells were thawed at 37 °C, transferred into 1 mL of preheated medium, and washed three times with PBS. The pellet was resuspended in 20 µL of PBS-D1H13C HR-MAS probe-head of a 500 MHz spectrometer  and left to equilibrate with the temperature set to 272 K while being spun at 5 kHz at the magic angle. Two types of one-dimensional 1H NMR spectra both with presaturation of the water resonance have been recorded for each sample: a 1-D NOE spectrum, using the pulseprogram noesypr1d taken from the Bruker pulse sequence library, and a 1-D PROJECT [2-filter of 102.4 ms for suppression of broad components. The spectra were recorded with a spectral width of 6002 Hz (12 ppm), 32,768 data points, 4 s relaxation delay, and 512 scans for NOESY and 1024 scans for PROJECT, respectively. Additionally, 2-D 1H-1H TOCSY experiments (pulseprogram dipsi2phpr from the Bruker pulse sequence library) and 2-D 1H J-resolved experiments (pulseprogram jresgpprqf from the Bruker pulse sequence library) were recorded for two samples of each group to help with the assignment of individual metabolites.Each sample was thawed at 37 °C directly before measurements. The cell lysate was pipetted into a 4-mm MAS rotor, and the volume was regulated with a 12-µL insert. The closed rotor was inserted into a dual inverse  PROJECT  spectrumascii files that served as an input for statistics.All spectra have been identically processed using an exponential multiplication with a line broadening of 1 Hz. All spectra have been calibrated with respect to the phosphocholine resonance at 3.23 ppm. The baseline correction has been performed independently for two regions: the upfield (0.350–4.793 ppm) part and the downfield (5.575–9.001 ppm) part for avoiding the residual water resonance. The processed spectra have been exported as The ascii files have been divided into groups (cell line and dose). The aliphatic and aromatic regions were treated separately. The regions of spectra were divided into buckets, each bucket representing resonances of individual metabolites wherever possible. Fifty-two buckets were defined in the aliphatic region in NOESY spectra. Forty-four buckets were defined for the aromatic region of the PROJECT spectra.Probabilistic quotient normalization (PQN) was applied to all integrals in the analyzed set. The type of scaling used and further details on the analysis can be found in summary in Division of the data into groups according to cell line and DiRu-1 dose enabled evaluation of the effect of DiRu-1 and dose within one cell line, general differences in metabolism of three different cell lines, and comparison of the treatment effect in different cell lines. The preprocessed data were then used as an input for principal component analysis (PCA) of the groups. The highest contributing principal components (PC-1-PC-3) have been plotted in PCA score plots. Outliers including cases where the quality of the sample was insufficient and/or low S/N spectra have been excluded from the analysis .Next, partial least squares (PLS) and/or partial least squares discriminant analysis (PLS-DA) were performed using the PLS toolbox software . Similar as in the case of PCA, the latent variables for PLS or PLS-DA that contributed the most to the models have been plotted.Venetian blinds method was used for cross-validation. Further details on statistical analysis are summarized in A correlation matrix was calculated in each cell line for the control and 0.03 µM DiRu-1 groups using the Pearson algorithm. Subsequently, corresponding heatmaps were produced.1H NOESY, PROJECT, and 2-D TOCSY spectra ; Matlab R2012a  and PLS Toolbox  for Matlab; Python 3.7 . The data were stored using MetaboLights data repository .In this study, we treated three cell lines with DiRu-1 and analyzed their lysed suspensions using HR-MAS NMR spectroscopy. The treatment showed significant metabolic changes mainly in the A2780cisR cell line. The A2780 cell line exhibited changes, which, however, were not significant. It turned out that the full IC50 dose of 0.03 µM of DiRu-1 was required to observe the treatment effect at a sufficient significance level.The levels of GSH and creatine increased in the A2780cisR cell line upon treatment with DiRu-1. The increase in GSH and creatine levels can be related to their function as antioxidants. Changes affecting redox homeostasis can be related to the fact that DiRu-1 is able to catalyze GSH oxidation as it has been shown earlier. Furthermore, the Gln level was increased in A2780cisR cells treated with DiRu-1 while the Glu level decreased. The combination of increased Gln and decreased Glu could mean reduced glutaminolysis.Another group of metabolites affected were lipids. The overall decrease in detected lipid levels in A2780cisR cells undergoing treatment with DiRu-1 could be explained by downregulated biosynthesis, decreased uptake, or a lack of lipid storage and distribution.Last but not least, lactate levels have been observed dropping in A2780cisR cells treated with DiRu-1. As high lactate has been reported to be a sign of poor prognosis for a cancer patient, we consider a decrease in lactate a sign of positive drug response.It can be concluded that DiRu-1 caused most metabolic changes in the A2780cisR cell line and that the changes observed are partially related to the specific DiRu-1 structure and its related nature.


Here, we show using flame emission assay that a long-term increase in cell K+ content per g cell protein is a mandatory factor for transition of quiescent human peripheral blood lymphocytes (PBL) to proliferation induced by phytohemagglutinin, phorbol ester with ionomycin, and anti-CD3 antibodies with interleukin-2 (IL-2). The long-term increase in K+ content is associated with IL-2-dependent stage of PBL activation and accompanies the growth of small lymphocytes and their transformation into blasts. Inhibition of PBL proliferation with drugs specific for different steps of G0/G1/S transit prevented both blast-transformation and an increase in K+ content per cell protein. Determination of the water content in cells by measuring the density of cells in the Percoll gradient showed that, unlike the K+ content, the concentration of K+ in cell water remains unchanged, since water and K+ change in parallel. Correlation of proliferation with high cell K+ and water content has been confirmed by the data obtained in comparative study of PBL and permanently cycling Jurkat cells. Our data suggest that K+ is important for successful proliferation as the main intracellular ion that participates in regulation of cell water content during cell transition from quiescence to proliferation. We concluded that high K+ content in cells and the associated high water content is a characteristic feature of proliferating cells.Many evidence shows that K Inhibition of membrane-associated ion channels and pumps as well as ion co-transporters induces cell cycle arrest and stops proliferation11. An involvement of monovalent ions in regulation of cell proliferation is demonstrated by the proliferation-related changes in the profile of the transcribed mRNAs coding ion channels and transporters17. Monovalent ions may be involved in signaling network in cycling cell: changes in concentrations of cellular ions regulate pHi, membrane potential and the activity of some cell proteins with important function in the cell cycle progression21.Intracellular monovalent ions such as K+ in proliferation. The asymmetric distribution of Na+ and K+ is a characteristic feature of most animal cells and higher cell K+ conсentration is necessary for the higher cell proliferation24. It was shown on Ehrlich ascites cells that K+ concentration in cell water remains unchanged during cell cycle21. Meanwhile, we found significant changes in K+ content (Ki) in proliferating cultures of permanent cell lines: Ki calculated per g of cell protein content declined during culture growth from low to high density25. These changes in Ki were not accompanied by increasing cell Na+ content (Nai) and occurred simultaneously with a decrease in cell proliferation. We also found age-dependent decrease in Ki per g of cell protein in growing cultures of human mesenchymal stem cells26. Of interest, cell K+ content assayed by X-ray fluorescence spectrometry and mass spectrometry differs considerably between human pluripotent cells and non-pluripotent cells27.Our attention is focused on the role of intracellular Ki and proliferation was investigated in activated human peripheral blood lymphocytes (PBL)29. PBL represents an adequate model for investigating ion changes associated with cell transition from quiescence to proliferation. In PBL, stimulated by phytohemagglutinin, K+ content calculated per cell protein has been found to increase during the prereplicative stage28. In this study, we present new evidence that in human PBL, stimulated to exit from quiescence (G0) to cell cycle, K+ content per cell protein rises gradually in the course of IL-2-dependent transition of small resting T lymphocytes from G0 into large blasts and DNA synthesis. We also show that cell water content per cell protein calculated from cell buoyant density, is higher in activated than in resting PBL and cellular K+ concentration does not change during lymphocyte transition to proliferation. It is concluded that high cell K+ content per cell protein content as a sign of higher cellular hydration is a hallmark of cell proliferation and transformation.Relationship between changes in K+ content28. Figure i that is followed by its increase up to 48 hour. An initial decrease in Ki takes place simultaneously with an increase in Nai. It has previously been established, that rapid reciprocal changes in Nai and Ki as well as enhanced ion fluxes via Na pump and ion channels represent an early ion response as a part of initial T-cell receptor [TCR] activation by antigen30. As seen in Fig. i was observed, whereas Nai increased during the first 2–5 hours after stimulation and later it does not change or slightly increased to the end of second day. In our study, to evaluate changes in Ki and Nai, we normalized analytically measured cell ion content per cell protein content in the same culture. In cell biology studies, such evaluation is widely used for estimating intracellular contents of ions because of uncertainties in measuring cell volume and water content in proliferating cells. Indeed, in asynchronous growing cultures, cycling cells have different sizes and it is impossible to compare cells from different established lines as well as cells of different origin.First, we confirmed our previous report that in human PBL stimulated by mitogenic PHA transition from quiescence to proliferation is accompanied by long-term increase in cell Ki per cell protein content (Ki/g) accompanies PBL transition from quiescence to proliferation. In resting T cells, calcium ionophores and phorbol esters are capable of triggering two early signalling cascades, such as intracellular Ca2+/NF-AT and protein kinase C/NF-kB, that are sufficient to induce Go/G1/S transit32. In our experiments, phorbol 12,13-dibutyrate  and ionomycin (500 nM) were capable of inducing proliferation in isolated human PBL  was followed by gradually increasing Ki/g during the next day without significant changes in Nai/g. Altogether, above data indicate that as compared to resting cells, in late activated PBL Ki/g is higher depending on stimuli as well as on donor. In comparison with resting cells, in activated PBL, Ki per g cell protein ratio was 25–30% higher.To initiate prolνiferation in resting PBL we also used antibodies for CD3 (anti-CD3) together with interleukin-2 (IL-2). This combination is widely used to distinguish signalling pathways which are responsible for early T cell activation and cell cycle progression0/G1/S transition when Ki is increased, we used two-step activation of quiescent PBL34. There is a possibility to differentiate between the initial T cell activation induced by signalling from TCR and the cell cycle progression when formation of the high affinity IL-2 receptor (IL-2R) takes place36. In two-step activation experiments we used submitogenic concentrations of PHA  to make PBL responsive to exogenous IL-2, and determined CD25 expression as a marker for IL-2Rα-chain and IL-2-dependent progression of stimulated T cells.To identify a stage of G+ cells began to increase as early as in 5 hour, however, in 24 h the percentage of CD25+ cells rose to 18.6 ± 1.7% only . Addition of IL-2 to competent PBL induced the sustained elevation of Ki to 790 ± 31 μmole/g during the next 48 hour  phases at 24 hour and a maximum of cells (up to 45%) in (S + G2/M) phases was at 48 hour or later depending on donor  after 5 hour to (36.6 ± 3.5%) after 24 hour, and to the end of the second day, T cell population becomes represented mainly by large CD25+ cells  to prevent IL-2 production in mitogen-stimulated PBL. Immunosuppressive action of CsA is due to inactivation of calciuneurin, Ca2+-dependent phosphatase, that activates nuclear factor of activated T cells (NFAT) required for expression of IL-2 gene37. CsA has been shown to prevent induction of T cell proliferation.To highlight further the relationship between intracellular Ki in activated cells but does not affect the initial decrease of Ki in response to PHA  was added to PBL culture 1 hour prior to PHA. Cell cycle analysis revealed a decrease in S phase in CsA-treated PHA-stimulated PBL . After 48 hour of PHA stimulation in the presence of 80 μM WHI-P131, Ki was 516 ± 29 μmole/g instead of 820 ± 47 μmole/g in cells activated without WHI-P131  changes in activated PBL. Therefore, we investigated whether cell water content was changed in quiescent PBL stimulated to enter cell cycle. Cell water content was determined by measurements of the buoyant density of cells in discontinuous Percoll density gradients. This is the most sensitive and reliable of all currently existing methods for determination of water content in native cell40.In view of the significant increase in KIsolated human PBL stimulated by PHA or by anti-CD3 with IL-2 were used for experiments. Figure 42. In early studies of leukocytes separation in Ficoll-Hypaque density gradient it was reported that the mean density of monocytes was higher that of lymphocytes43. Monocytes can be depleted from the mononuclear cell suspension, since they adhere to plastic surfaces and lymphocytes do not. Usually, after depletion of monocytes by plastic adherence, 85–95% of the mononuclear cells are lymphocytes.The presence of populations with different buoyant densities in resting PBL is more likely due to the heterogeneity of lymphocytes that are isolated from the whole fresh blood. According to the Basic Separation Protocol for human peripheral blood, after gradient separation procedure up to 40% of the mononuclear cells are monocytesWe tried to distinguish between lymphocytes and monocytes in view of differences in their sizes. Monocytes may be defined by flow cytometry on the basis of light scatter properties. In our flow cytometry analysis, FSC/SSC plots demonstrated two populations in isolated PBL, the smaller of which (5–11%) might be represented by monocytes. From Fig. 44. It is known, NK cells do not express cell-surface CD3.The increased heterogeneity of PBL stimulated to exit from quiescence is most likely associated with asynchronous cell growth. Isolated PBL consists of T cells (75–90%), B cells (5–15%), NK cells (5–10%). All these cells have many subsets based on their maturation, activation, expansion stages and are characterized by their own growth response to activating stimuli. For instance, NK cells are large granular lymphocytes of low cell density+ cells and to the third day only T cell population becomes represented mainly by large cells  in light subpopulation and 4.61 ± 0,07 mL/g (n = 3) in heavy subpopulation. After 24 hour of cell stimulation by PHA the water content increased to 6.48 ± 0.56 mL/g (n = 3) in the lighter cells and to 5.51 ± 0.50 mL/g (n = 3) in the heavier cells, and after 48 hour of stimulation two subpopulations with water contents up to 8.55 ± 0.26 mL/g (n = 3) and 6.55 ± 0.30 mL/g (n = 3) were present. The higher water content was also found in PBL, activated by anti-CD3 with IL-2  these cells were mainly distributed in region of 1.057 and 1.051 g/mL Fig. . The cali in populations of PBL with different buoyant densities. As found by flame emission measurements, the lighter subpopulations of activated PBL differed by Ki from heavy resting PBL. In representative experiment shown in Fig. i was 542 µmole/g, whereas in activated PBL it was 791 µmole/g the (low-density population) and 699 µmole/g (the high-density population). In continuously proliferating leukemic T cells Jurkat Ki was found to be 818 and 691 µmole/g protein in the low- and high-density populations, correspondently  anions” sequestered in cell. It is the amount of these anions in combination with Na, K ATPase pump that determines the water balance of the cell and the accumulation of K+ in the cells55. We can suggest that in activated PBL, an increase in dry mass  during blasttransformation is accompanied by an increase in the amount of impermeant anions per g dry mass, inevitably leading to an increase water influx to restore osmotic balance of cell with medium. Here, K+ as the major cellular osmolyte enters the cell so that an increase in Ki per g cell protein correlates always with an increase in cell water content per g cell protein, and therefore, the higher ratio of Ki per g cell protein indicate the higher cell water content/g protein ratio. Thus, in growing animal cell, increased cell K+ content per g cell protein indicates increased cellular hydration. This means, that despite the lack of significant concentration differences, K+ may be important for initiating cell proliferation as the intracellular ion that participates in regulation of volume and water content. Indeed, iincreasing evidence indicate that K+ channels of plasma membrane are involved in regulation of cell proliferation: their expression and function can be regulated by the cell cycle, and inhibition of K+ channel activity results in cell cycle arrest57.It is known from the theory of monovalent ion distribution between animal cells and the medium that the amount of Ki and water content in cells induced to proliferation. It was shown that in Ehrlich ascites (ELA) cells synchronized in G0/G1 by serum starvation and then released in serum-containing medium, increase in Nai and Cli (not of Ki) as well as in water content was observed in late G1/S transition21. Because of the concomitant change in water content, cell Na+ and Cl− concentrations did not differ between G1 and S. It was concluded that Na+ regulates proliferation by controlling intracellular pH, while Cl− regulates membrane potential and participate in cell volume regulation during S-phase.To date, few studies are available on changes in Ki in quiescent PBL stimulated to proliferation with synchronized ELA cells we note some similarities in changes of cell water content. In both studies, water content/protein content ratio increases during cell activation, however, in released ELA cells, the increase in water content was observed in the late cell cycle transit, and it was smaller (about 11–12%) than in activated PBL (up to 45–49%). Differences in absolute values of water content changes between ELA cells and PBL are most likely explained by different functional status of cells. Namely, serum deprivation for 72 hours shifted ELA cells into nonproliferative state in which about 7% and 4% of cell population still remained in S and in G2/M phases, correspondently21. Upon reintroduction to standard culture conditions, ELA cells restored proliferation with maximal S phase (about 36%) as soon as in 16 hours.When compared our data on water and K60. In quiescent PBL, antigen recognition with appropriate co-stimulation triggers exit from G0 state and further transit through cell cycle (G0 → G1/S/G2/M). In contrast to ELA cells released after starvation, antigen-activated PBL have long growth phase (48–72 hours) that precedes DNA replication. This time is required to increase cell size and metabolism. In activated PBL, prior S phase entry, total protein content was increased 2–2.5 times during 2 days whereas in ELA cells protein content did not differ between different samples or increased about 1.2 times 16 hours after release21. Significant differences in growth intensity correlates with differences in absolute changes in water content in PBL stimulated to proliferation from quiescence and in ELA cells released after starvation.Human peripheral blood lymphocytes are quiescent (G0) cells. Cellular quiescence is actively maintained: certain transcription factors acts as regulators of gene expression patterns that enforce the quiescent phenotypei, our data on stimulated PBL contrasts with data on ELA cells21. As shown, in synchronized ELA cells, neither the concentration nor the content of K+ were changed during cell cycle progression. In contrast, in quiescent PBL stimulated to enter cell cycle, Ki/g was significantly (by 20–30%) increased concomitant with an increase in cell protein content. As far as in activated PBL the water content was also increased, the intracellular concentration of K+ was not changed during transit from quiescence to proliferation. The main finding with activated PBL is that during the exit from quiescent state, an increase in cell K+ content occurs simultaneously with an increase in cell water content, thus resulting to higher cellular hydration.As to K61.Intracellular water is responsible for the conformations and functions of all biomolecules through direct interaction with their hydration shells and hydration changes affect cell functions at multiple levels including cell metabolism and gene expression. There is also considerable evidence that water of cancer cells is similar to that of embryonic tissue and consistently higher than that of normal cells of similar origin+ content per cell protein content concomitant with cell water increase during human lymphocytes transition from quiescence to proliferation and conclude that intracellular K+ concentration remains unchanged during G0/G1/S progression. Our data suggest that the functional meaning of long-term increase in cell K+ content during the transition from cell quiescence to proliferation may be that K+ as a dominant intracellular osmolyte is involved in the regulation of cell water content during cell growth and transformation and high cell K+ content per cell protein content (as a sign of higher cellular hydration) is a hallmark of cell proliferation and transformation. This conclusion seems to be of importance for all cells which are quiescent under homeostasis  and respond to stimuli by exiting from quiescence and entering cell cycle.In summary. In this study we describe proliferation-associated increase in cell KThe research and all procedures involved human blood lymphocytes were performed in accordance with standards of the Declaration of Helsinki (1989) and approved by the Ethics Committee of the Institute of Cytology (No. 223/934 on the 27/10/2017). Lymphocytes were isolated from fresh venous blood of healthy adult donors. Written informed consent was obtained from all of the participants according to agreement between the Institute of Cytology RAS and the State Institution “Mariinsky Hospital” .28. After depletion of adherent cells on plastic bottles, isolated lymphocyte population was >85% CD3+ cells. Isolated PBL were incubated overnight in RPMI-1640 medium with heat-inactivated AB IV Rh (+) human serum (5%) in CO2-air (5–95%) atmosphere at 37 °C without antibiotics. The next day the cell suspension (1.5 × 106 cells/mL) was placed into vials, and stimulated by 10 μg/mL phytohemagglutinin M , or by 10 nM phorbol 12,13-dibutyrate  and 500 nM ionomycin , or by 3.5 µg/mL anti-CD3 antibodies with human recombined IL-2 , or left unstimulated. In the «two-pulse activation experiments», PBL were treated with submitogenic concentrations of PHA (0.8–1.0 μg/mL) for 20 hours to induce “competence” and then the competent cells were stimulated by IL-2 (100–200 U/mL) to induce progression to the S phase. Lymphocytes of one donor (up to 400 × 106 cells) were used in each experiment.For experiments, PBL were obtained by density gradient centrifugation over Histopaque , as described previously2-air (5–95%) atmosphere at 37 °C without antibiotics.To compare the ion homeostasis and water content of quiescent and activated T cells with those of transformed T cells we use human leukemia T cell Jurkat . Jurkat cells were maintained in RPMI-1650 with 10% fetal calf serum  containing 2 mM L-glutamine in CO+ and Na+ content was measured by emission photometry in an air–propane flame using a Perkin-Elmer AA 306 spectrophotometer, as described previously28. In summary, the cells were pelleted in RPMI medium, washed five times with MgCl2 solution (96 mM) and treated with 5% trichloroacetic acid (TCA). TCA extracts were analyzed for ion content. TCA precipitates were dissolved in 0.1 N NaOH and analyzed for protein by Lowry procedure. The cell ion content was expressed as amount of ions per amount of protein in each sample analyzed.Cellular KCell water was determined by measurements of the buoyant density of cells in discontinuous Percoll gradients. The density gradient centrifugation method is a widely accepted method of measuring the average density of a cell population. In our experience, this is the most sensitive and reliable of all currently existing methods for determination of cell water. An isotonic Percoll solution was made by mixing Percoll  and PBS at a 9:1 volume ratio. Densities of 1.040–1.077 g/mL were prepared by diluting the isotonic Percoll solution in PBS at concentrations of 25–53% and tested by the refractive index measured using a Atago PR-RI Palette digital refractometer (Japan).6 cells) were placed on the top of the gradient and centrifuged for 20 min at 400 g . After centrifugation, the fractions were collected, placed into 1.5 mL Eppendorf tubes, suspended in the RPMI medium and used for determination of ion content and cell protein.An eight-layered Percoll gradient was obtained by layering 0.25 mL of each Percoll solution in 95 mm-length tubes. The density step was about 0.005 g/mL. The concentrated cell suspensions /[0.72(ρ − 1)], where ρ is the measured buoyant density of the cells and ρdry is the density of the cell dry mass, the latter taken as 1.38 g/ml. The ratio of protein to dry mass was taken as 0.72. The buoyant density of cells is a more sensitive and reliable measure for cell water content than all known techniques including methods using intra- and extracellular water markers.The water content per g protein, 40. Resting or stimulated with mitogens PBL were centrifuged at 2000g and re-suspended in Hank’s balanced salt solution. Cells were diluted to concentrations of (0.5–1) × 106 cells/mL, which lie within the operating range of the instrument.Cell size was measured by Scepter cell counter equipped with a 40-μm sensor and software version 2.1, 2011 39. Briefly, at definite time after mitogenic stimulation, PBL (106 cells/mL) were suspended in PBS containing 200 µg/mL of saponin  for 30 min, then washed and treated with 250 μg/ml ribonuclease  and 50 μg/mL propidium iodide  in PBS for 30 min at 37 °C. Cell cycle analysis was performed with Coulter Epics XL Flow Cytometer  and WinList and ModFit LT software . At least 10,000 cells were measured per sample.FACS analysis was used to assess the proliferation of stimulated PBL and cultured T cell Jurkat39. PBL were pelleted by centrifugation, rinsed once and suspended in PBS (106 cells/mL) and stained with PE-labeled CD25 Abs . Mouse IgG-PE isotype control was used for assessing the background staining of cells. The percentage of CD25+ cells was determined after gating on lymphocytes. Cells were analyzed on a Coulter Epics XL Flow Cytometer . Statistical analysis of results was performed according to the standard protocol of the data treatment Epics XL.To assess the expression of IL-2R, phycoerythrin (PE)-coupled CD25 antibodies as cell surface markers of the α-chain, and FACS analysis were used as described previouslyt-test and one-way ANOVA with Tukey’s post hoc tests for multiple comparisons, P < 0.01 and P < 0.05. The specific details of each experiment are provided in the corresponding figure legends.All data are presented as the mean and standard error of the mean (SEM) from at least three independent experiments. Statistical significance was assessed using two-tailed Student’s


Small cell lung cancer (SCLC) is an aggressive type of lung cancer which disseminates vigorously and has a dismal prognosis. Metastasis of SCLC is linked to an extremely high number of circulating tumor cells (CTCs), which form chemoresistant spheroids, termed tumorospheres. Intravasation and extravasation during tumor spread requires the activity of a number of proteases to disintegrate the stroma and vascular tissue. Generation of several permanent SCLC CTC lines allowed us to screen for the expression of 35 proteases using Western blot arrays. Cell culture supernatants of two CTC lines, namely BHGc7 and 10, were analyzed for secreted proteases, including matrix metalloproteinases (MMPs), ADAM/TS, cathepsins, kallikreins, and others, and compared to proteases expressed by SCLC cell lines . In contrast to NCI-H526 and SCLC26A, MMP-9 was highly expressed in the two CTC lines and in GLC16 derived of a relapse. Furthermore, cathepsins  were highly expressed in the CTC lines, whereas ADAM/TS and kallikreins were not detectable. In conclusion, SCLC CTCs express MMP-9 and a range of cathepsins for proteolysis and, aside from tissue degradation, these enzymes are involved in cell signaling, survival, and the chemoresistance of tumor cells. Metastasis describes the dissemination of cancer cells from the primary tumor to adjacent normal tissue, and further to distal organs where the secondary lesions are a major cause of mortality ,2. MetasCirculating tumor cells (CTCs) are the primary effectors of metastatic relapse in patients with cancer, as shown by their correlation to prognosis and drug response ,8. AlthoLung cancer remains one of the most prevalent and malignant cancers worldwide, with SCLC representing its most aggressive variant ,15. The SCLC represents a suitable model for studying early tumor spread and the development of drug resistance. This tumor entity is distinguished by an extremely high count of CTCs, which was reported to be linked to prognosis and response to therapy . SCLC CTFor all of the following experiments, only the significantly expressed proteases out of the 35 enzymes assayed are shown. GLC14 and GLC16 represent lines established from metastases of the same patient before and after failure of chemoradiotherapy, respectively. Results demonstrate that during the progressive disease, GLC16 showed elevated expression of most proteases, with marked overexpression of MMP-9, cathepsins S, X/Z/P and D, as well as partial downregulation of cathepsin V .NCI-H526 and SCLC26A represent local metastases to bone and pleural fluid, respectively. NCI-H526 exhibited high expression of proprotein convertase-9 (PC-9) and cathepsins V and D, with weaker occurrence of cathepsin C and low levels of other cathepsins, urokinase-type plasminogen activator (uPA), and MMP-8/9  class II molecules, and in contrast to other lysosomal proteases, it retains stability outside the lysosome and cleaves ECM proteins including laminin, fibronectin, elastin, osteocalcin, and some collagens . Immune Despite the role of uPA and its receptor uPAR/CD87 as major regulators of ECM degradation, and their involvement in cell migration and invasion under physiological and pathological conditions, they were not found in the CTCs tested here . OtherwiThe functional activity of CTC-derived proteases has been studied with help of a microfluidics system . This syGLC14 and GLC16 were obtained from Department of Radiation Biology, the Finsen Centre, National University Hospital, Copenhagen, Denmark and NCI-H526 was obtained from the American Tissue Culture Collection . GLC14, GLC16, and GLC19 constitute a series of three cell lines which have been established from biopsies of a single SCLC patient . In detaFor assessment of the proteases expressed, cell culture supernatants were processed using a Human Proteome Profiler Protease Kit according to the manufacturer’s instructions . In brief, this Western blot array comprised reagents to detect 35 proteases, including ADAM/TS, kallikreins, MMPs, cathepsins, uPA, neprilysin (CD10), presenilin-1, DPPIV (CD26), and proprotein convertase 9 (PC-9). Assays were performed in duplicate. The different arrays contain several control spots to calibrate for protein content of the samples applied. Conditioned medium of the respective cell lines (500 µL) were used for performing the assay and the spots detected by chemoluminescence were analyzed using Origin 9.0 software .Tumorospheres of BHGc10 cell line were isolated by sedimentation and resuspended in Matrigel (Sigma-Aldrich). Matrigel was thawed overnight at 2–8 °C before use, mixed with medium containing the spheroids (1:1) and dispensed to 18-well plates  using pre-cooled pipettes. Outgrowth of tumor cells was observed by light microscopy and areas covered by the original cluster and the invaded cells quantitated using Image J.t tests, using Origin 9.0 software. p < 0.05 was regarded as statistically significant.Results were evaluated using unpaired Due to the high heterogeneity of the CTCs, detection of the expression of proteases has been limited to demonstration of increased levels of MMP-9 compared to normal blood cell types . Our scr


The ability of the new compounds to induce apoptosis and prevent necrosis was evaluated on three different types of cancer cell lines, which are; liver HepG-2, breast MCF-7, and colon HCT116. The obtained results show that Li-TUD-1 has the ability to control necrosis and thus reduce the side effects of treatments containing silica in the case of lithium added to them, especially in chronic cases. This opinion has demonstrated by the significant increase in the IC50 value and cell viability compared to control groups. Consequently, the idea is new, so it needs more develop and test with materials that have a more apoptotic impact than silica to induce apoptosis without induction of necrosis.There are many molecules used as a drug carrier. TUD-1 is a newly synthesized mesoporous silica (SM) molecule possess two important features; consists of mesoporous so it is very suitable to be drug carrier in addition to that it has the ability to induce apoptosis in cancer cells. However, the effect of TUD-1 appears to act as cell death inducer, regardless of whether it is necrosis or apoptosis. Unfortunately, recent studies indicate that a proportion of cells undergo necrosis rather than apoptosis, which limits the use of TUD-1 as a secure treatment. On the other hand, lithium considered as necrosis inhibitor element. Hence, the current study based on the idea of producing a new Li-TUD-1 by incorporated mesoporous silica (TUD-1 type) with lithium in order to produce a new compound that has the ability to activate apoptosis by mesoporous silica (TUD-1 type) and at the same time can inhibit the activity of necrosis by lithium. Herein, lithium incorporated in TUD-1 mesoporous silica by using sol–gel technique in one-step synthesis procedure. Moreover, lithium incorporated in TUD-1 with different loading in order to form different active sites such as isolated lithium ions, nanoparticles of Li The invention of a new anti-cancer treatment is related to understanding the mechanism of entering the molecules into the cell and then following the pathway(s) which the treatment will activate to induce cells to apoptosis. Hence, molecules with high permeability or loading high-impact molecules should be selected for vectors that have the ability to enter cells easily , 2. But Consequently, many vital applications that rely directly on these properties have emerged like immediate/sustained drug delivery systems, bio-therapeutic agent delivery, controlled/targeted drug delivery systems –9. MoreoOn the other hand, lithium has been tested for many years as a treatment for the mood disorders , 18; it In an attempt to produce a double-sided effect and triple feature drug, lithium was incorporated onto mesoporous silica TUD-1 in order to combine the three good features  this study was designed. The new Li-TUD-1 that combines the qualities of silica in terms of easy entry to the cell as a carrier and urged by the cell to apoptosis, and lithium, which protects the cell from going to necrosis. This new Li-TUD-1 will be known as Li-TUD-1.2 : xLi : 0.5TEAOH : 1TEA : 11H2O, where x = 0.01, 0.05, 0.1, and 0.2. The prepared materials were synthesized by mixing a solution consisting of triethanolamine  and LiNO3 (99% Sigma) with tetraethyl orthosilicate  under vigorous stirring. After 30 min, tetraethyl ammonium hydroxide  was added dropwise and the overall mixture stirred for at least 2 h at room temperature. The resulting homogeneous solution/gel was aged at room temperature for 24 h and then dried at 371 K for another 24 h. The obtained solid was ground and hydrothermally treated in a 50 mL Teflon-lined stainless steel autoclave at 451 K under autogenous pressure for 4 h. The obtained solid was ground again and then calcined in static air at 873 K for 10 h applying a heating ramp rate of 1 K/min. The obtained solids were stored in a clean glass bottles and kept in dissector. The four samples were coded as Li-x, where x is the loading wt% which are 1, 5, 10 and 20.Four Li-TUD-1 samples were prepared according to a molar ratio composition of SiOCuKα (λ = 1.5406 Å) radiation and secondary monochromator attached with Shimadzu software with pdf-2 library for the analysis of XRD data. The data collection was carried out under ambient conditions. Moreover, FT-IR spectra of Li-TUD-1 were recorded using THERMO SCIENTIFIC, DXR FT-IR spectrometer by KBr pellet method in the wavenumber range of 4000–400 cm−1. Finally, the morphological structure of prepared materials were characterized by field emission scanning electron microscope (FE-SEM)  equipped with energy dispersive spectroscopy (EDS) microanalysis system.The prepared materials were characterized by several techniques to understand the structure of each sample. X-ray diffraction (XRD) measurements were carried out with Shimadzu LabX-XRD-6000 diffractometer with 50 value ) were purchased from Sigma Chemical Co. . While media and related products were supplemented from Gibco/Life Technologies Co . Cells Human hepatic carcinoma (HEPG-2), breast (MCF-7) and colon HCT116) used in the current study were purchased from Vacsera . In preparation to treatment, cells maintained in cell culture media RPMI which is supplemented with 100 µg/mL streptomycin/penicillin and 10% heat-inactivated (FBS) fetal bovine serum. The cytotoxicity of the elements and were tested against HEPG-2, MCF-7, and colon HCT116 tumor cell lines. Confluent 80% cells were exposed to the Li alone, TUD-1 alone and Li-TUD-1 with  for 72 h. SRB evaluation test used to determine the IC16 used iθ range of 5–70ο are presented in Fig. ο which can be attributed to the amorphous phase of SiO2 [ο, 24.6ο, 26.0ο, 26.6ο, 28.5ο, 37.7ο 2that. These peaks can be attributed to the formation of crystalline phases of Li4SiO4 and Li8SiO6. The crystals formation of lithium silicate different phases was also observed by Janes and co-working during the synthesis of Li-SBA-15 [XRD spectra of Li-TUD-1 samples were measured within the 2 of SiO2 . Moreovei-SBA-15 . Therefoi-SBA-15 .Fig. 1Th−1, which can be attributed to the asymmetric stretching and symmetric modes of Si–O–Si lattice vibrations, respectively [−1 could be attributed to the surface silanol group (Si–OH). The intensity of this peak was stronger with Li content; this can be explained by the formation of more Si–OH groups due to the hydrophilicity of Li-silicate crystals, which adsorb more water molecules. These adsorbed water molecules interact with the Si–O–Si of TUD-1 to form the surface hydroxyls. Hence, the intensity of the peak became stronger [−1 band was gradually decreasing with Li content, and other bands at 779, 740, and 628 cm−1 were clearly seen. These bands can be attributed to the formation of lithium silicate crystals. Finally, the obtained FT-IR results are in a good agreement with the XRD results.FT-IR spectra of Li-TUD-1 samples collected at ambient conditions without further treatment Fig. . All theectively , 29. It stronger . MoreoveFigure 50 values >100 µg/mL, for TUD-1 and Li separately while the impact was < 1000 in all cell lines treated with Li-TUD-1 for each concentration . These results clearly prove the synergy between Li and silica in the increasing IC50 values to be more effective in different cell lines.The obtained results confirmed that the mesoporous silica (TUD-1), Li, and the Li-TUD-1 exhibit different cytotoxicity impact against HEPG-2, MCF-7 and colon HCT116 tumor cell lines with the IC50 values on the investigated samples are listed in Table 50 going to be increased parallel with the Li-TUD-1 concentration. While, concentration 20 exhibited different behavior where increased instead of decreased. This is—most likely—due to the presence of the extra-framework Li oxides. The calculated IC50 of the investigated samples are plotted in Fig. Moreover, the ICPrevious results showed that there is a significant improvement in the event of the use of Li-TUD-1 (Si–Li) comparing to use elements alone. However, the difficulty lies in identifying the mechanism that caused it. Therefore, in attempt to confirm the mechanism of action, cells were stained with Acridine Orange and Ethidium Bromide (1:1) to detect apoptotic bodies, which are considered as an essential indicator of the impact mechanism Fig. .Fig. 5Th50. On the other hand, the protective role that had been played by the Li-TUD-1 (Li-TUD-1) in preventing of necrosis and allow of apoptosis had been evaluated by count the apoptotic and the necrotic cell per 100 cell. Consequently, HepG-2, MCF-7 and HCT-116 cancer cell lines were treated with IC50 concentrations determined before  appear on different cancer cell lines after treated with ICore Fig. .Fig. 6De50 value went to be high, indicating that a part of the cells moved from necrosis to programmed cell death. Therefore, this new molecule has reduced necrosis and this is good but it did not stop the cells from dividing, which led to an increase in the proportion of cells that have not neither died, by necrosis nor programmed death.Two different pathways, apoptosis and necrosis  control 50) has increased rather than decreased, so this new molecule has actually been prevented the occurrence of necrosis but also reduced the activity of silica catalyst for apoptosis.In fact, the molecule was worked within the roadmap had been set for it significantly reducing the proportion of necrosis. But, in the opposite it appears to have reduced the cytotoxicity of TUD-1 as the cell death rate  was successfully prepared in one-step synthesis and it showed high potential in the reduction of necrosis. However, the impact of the new Li-TUD-1 on different cancer cells remain in the beginning and further studies must be conducted in vitro as well as in vivo.