The ability of human pluripotent stem cells for unlimited proliferation and self-renewal promotes their application in the fields of regenerative medicine. The morphological assessment of growing colonies and cells, as a non-invasive method, allows the best clones for further clinical applications to be safely selected. For this purpose, we analyzed seven morphological parameters of both colonies and cells extracted from the phase-contrast images of human embryonic stem cell line H9, control human induced pluripotent stem cell (hiPSC) line AD3, and hiPSC line HPCASRi002-A (CaSR) in various passages during their growth for 120 h. The morphological phenotype of each colony was classified using a visual analysis and associated with its potential for pluripotency and clonality maintenance, thus defining the colony phenotype as the control parameter. Using the analysis of variance for the morphological parameters of each line, we showed that selected parameters carried information about different cell lines and different phenotypes within each line. We demonstrated that a model of classification of colonies and cells by phenotype, built on the selected parameters as predictors, recognized the phenotype with an accuracy of 70–75%. In addition, we performed a qRT-PCR analysis of eleven pluripotency markers genes. By analyzing the variance of their expression in samples from different lines and with different phenotypes, we identified group-specific sets of genes that could be used as the most informative ones for the separation of the best clones. Our results indicated the fundamental possibility of constructing a morphological portrait of a colony informative for the automatic identification of the phenotype and for linking this portrait to the expression of pluripotency markers. Pluripotent stem cells are capable of unlimited proliferation and self-renewal. The application of human pluripotent stem cells (hPSCs), including human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs), is intended to make a revolutionary breakthrough in the field of regenerative medicine, the creation of new drugs, the in vitro modeling of human diseases, and cell bank development ,2,3,4. IUnder in vitro conditions, hPSCs grow in the form of monolayer multicellular colonies with characteristic morphological features. The use of hPSCs in clinic requires a high level of quality control; a homogeneous, clonal composition of the cell population is one of the necessary conditions for their safe application. Various molecular methods are used to assess the state of undifferentiated, healthy colonies. However, the use of invasive assessment methods does not allow these cells to be further used in clinical practice. The noninvasive assessment of cell culture quality is currently not quantitative and can often be biased. It may depend on the experience of the investigator or subtle morphological differences between cell lines and clones. The various existing commercial high-content/high-throughput image acquisition systems not always can be applicable for the morphological analysis of hPSC colonies, since multicellular colonies are formed by close-packed small cells (10–16 μm in diameter), many parameters of which may be overlooked during automatic image analyses ,8,9,10. Clonality is another important characteristic of hPSC colonies. The clonal origin of hiPSC colonies guarantees their further safe use in the clinic, since the heterogeneous composition of the colony is directly related to adaptation in culture leading to the occurrence of chromosomal aberrations . The losMany studies focused on studying the genetic, epigenetic, molecular, and signaling pathways that control the induction and maintenance of pluripotency, as well as the mechanisms of hPSC self-renewal. At the same time, how a stem cell colony is formed, how its growth and cell behavior are regulated, and how this is related to the morphological and functional parameters remain poorly understood. It is important to emphasize that the parametric analysis of the morphological characteristics of various hiPSC clones is in good agreement with the gene expression data; thus, it is a reliable indicator of their quality ,17. ThesIn this study, we extracted and quantitatively analyzed seven morphological parameters of cells and colonies from three hPSC lines and linked these data to their clonality, pluripotency status, and differentiation ability towards three germ layers. We identified specific morphological parameters as the most informative ones in terms of variance between lines and different morphological features and used these parameters to train classification models of colony phenotypes. Finally, we linked the data of the morphological phenotype to the pluripotency status, reflecting the expression of pluripotency marker genes and differentiation markers, and further linked it to create the morphological “portrait” of the colony with a good phenotype. Our results indicated the fundamental possibility of constructing a morphological “portrait” of a colony informative for the automatic identification of the phenotype and link this portrait to the expression of pluripotency genes.The routine culture of hPSCs presents some unique challenges when compared with culturing other human cell types. It is well accepted that healthy and high-quality hPSCs should exhibit the following characteristics: relatively round shapes; tightly packed cells with a high nucleus: cytoplasm ratio, where the nucleus practically inhabits the entire cell; prominent nucleoli; colony centers becoming very dense; and a well-defined edge .We extracted and analyzed seven parameters  characteParameters Area and Perimeter describe the size of the cell’s/colony’s interior and boundary, respectively, while the Minor axis and Feret’s diameters represent the level of elongation. Shape factor quantifies the circularity of cells/colonies, thus representing a measure of their compactness. This parameter, also known as isoperimetric quotient, varies between 0 and 1, where 1 corresponds to the circularity of a circle and smaller values are associated with less circular and compact shapes. One of the indicators of the good quality of hPSCs is the ability for compactness as the colony reaches 72 h of culture. We quantified the compact packing of cells within colonies via the area of the free intercellular space (AIS), with larger values of this parameter being associated with less compact packing. Therefore, AIS represents an additional measure of compactness for colonies.At first, we investigated how the morphological parameters of cells and colonies varied across lines, passages, and growing times. The colony growth process led to a gradual increase over time in most parameters, except Shape factor . The H9 p > 0.05) in any parameter. These data probably point to the possibility to access the quality of the culture at the early time points (24–48 h) and to terminate it in the case of the sign of spontaneous differentiation.The analysis also showed that the variance in the morphological parameters of colonies from the same cell line came mostly from the time point changes rather than from the difference between various passages. For example, the comparison of control hiPSC colonies taken from the middle passage range (passages 21–28) and the late one (passages 39 and 56), fixed at the same time range (24–48 h) for each passage, did not show a significant difference  as a control parameter .p < 0.05). A closer comparison of the groups demonstrated that different lines were characterized by different morphological parameters sensitive to phenotypic separation (p < 0.05) in mean values between colonies with “bad” and “good” phenotypes. The same was true for hiPSC line CaSR, except for the fact that Perimeter only showed a trend towards statistical significance (p = 0.07). Therefore, these two lines exhibited similar sets of colony morphological parameters that could be considered as informative for assessing colony phenotypes. On the other hand, no colony parameter for hiPSC line AD3 showed a significant difference in mean values for different phenotypes  difference between the groups of good and bad phenotypes for hiPSC line AD3. Cells in hiPSC line AD3 colonies with the good phenotype on average had smaller mean values of Area, Perimeter, Minor axis, and both Feret’s diameters then cells with the bad phenotype, which could have been related to the more compact cells in good colonies. They were also more regular in form in the good colonies, which manifested as higher mean Shape factor for the good phenotype as compared with the bad one. Cells from the H9 line also demonstrated a statistically significant difference between phenotypes in the mean values of Shape factor, but in contrast to hiPSC line AD3, this change was associated with a lower average value of this parameter in the good colonies. This could probably indicate differences in colony growth patterns between these cell lines. We did not observe a statistically significant difference in the mean values of cell morphological parameters for hiPSC line CaSR . The resulting cross-validation accuracy of this model was 70 ± 6%, indicating that the phenotype could be predicted with good precision when the parameters were considered in combination.To find out which parameters were more informative in the context of such classification, we trained a set of classification models on the same data using all possible subsets of colony parameters as predictors, with the subset length ranging from two to seven parameters. As expected, the accuracy of these models grew almost monotonically as more parameters were added . We thenWe combined a given number of the best parameters from Applying the minimal classification model to the whole data sample led to a phenotype prediction accuracy of 77% . Bad andNext, we performed a similar analysis of the phenotype classification models based on cellular morphological parameters as predictors. Preliminary calculations showed that Feret’s D and Minimal Feret’s D contributed to the model accuracy in a measure comparable to the contribution of Minor axis, so we excluded these two parameters from consideration to simplify model training. A trained classification model including all other cell parameters (“full model”) produced a cross-validation accuracy of phenotype prediction equal to 69 ± 3%, which was less accurate than when colonial parameters were used as predictors.Classification models based on all possible subsets of the four cellular parameters showed that on average, three parameters were sufficient to reach the highest possible accuracy . The anaApplying the minimal model based on the cellular parameters to the whole data sample led to a phenotype prediction accuracy of 69% . Bad andDNMTB3, SALL4, IGFR1, CD9, DPPA4, OCT4, REX1, NANOG, SOX2, and KLF4 genes) in colonies from the three cell lines with different clonality statuses and phenotypes. By comparing the quantitative gene expression levels between all cell lines, we found that hiPSC line AD3 was mostly characterized by an elevated expression as compared with H9, while some markers that differentiated hiPSC line CaSR from H9 tended to be underexpressed in hiPSC line CaSR , SALL4 (hiPSC line AD3), SOX2 (both hiPSC lines), DNMTB3 (in H9 and hiPSC line AD3), IGFR1 (H9), KLF4 (hiPSC line AD3), DPPA4 (H9), and OCT4 (hiPSC line CaSR). The following genes were overexpressed in nonclonal colonies compared with clonal ones: SOX2 (H9), OCT4 (hiPSC line AD3), SALL4 (H9 and hiPSC line CaSR), KLF4 (H9), DNMTB3 (hiPSC line CaSR), NANOG (H9), IGFR1 (hiPSC line CaSR), CD9 (hiPSC line CaSR), and DPPA4 (hiPSC line CaSR). The fact that the sign of change in expression (over- or underexpression) of many genes varied across the lines pointed to the existence of line-dependent mechanisms that control pluripotency, in agreement with previous publications , where “data” is a list of data values in the form: list of parameter values for a colony/cell → phenotype. With this form of ValidationSet option, the validation set was selected automatically from “data” during the model training. As a control, we performed computational experiments on classification on the cellular data with the manual separation of the training, validation, and testing data sets and obtained the same model performance , and Minor axis and Perimeter (from the cell data). The classification models demonstrated lower performance on hiPSC line CaSR data. To find out the link between pluripotency and clonality in different lines, we examined pluripotency marker expression in hPSC colonies with good and bad morphological phenotypes of clonal and nonclonal (bulk) expansion. We observed significant changes in the expression levels of the pluripotency marker genes in a line- and clonality-dependent manner. Among them,


Coessentiality networks derived from CRISPR screens in cell lines provide a powerful framework for identifying functional modules in the cell and for inferring the roles of uncharacterized genes. However, these networks integrate signal across all underlying data and can mask strong interactions that occur in only a subset of the cell lines analyzed.IGF1R-PIK3CA, and illustrate the implications for drug targeting. We further demonstrate how context-dependent functional interactions can elucidate lineage-specific gene function, as illustrated by the maturation of proreceptors IGF1R and MET by proteases FURIN and CPD.Here, we decipher dynamic functional interactions by identifying significant cellular contexts, primarily by oncogenic mutation, lineage, and tumor type, and discovering coessentiality relationships that depend on these contexts. We recapitulate well-known gene-context interactions such as oncogene-mutation, paralog buffering, and tissue-specific essential genes, show how mutation rewires known signal transduction pathways, including RAS/RAF and This approach advances our understanding of context-dependent interactions and how they can be gleaned from these data. We provide an online resource to explore these context-dependent interactions at diffnet.hart-lab.org.The online version contains supplementary material available at 10.1186/s13059-022-02712-z. ESR1-FOXA1 pathway in ER+ breast cancer cell lines and the BRAFV600E module in melanoma cells  matrix of quantile normalized BFs, and n is the number of cell lines associated with the “context.” Positive dPCC represents a gain of interaction (GOI) because the higher PCCall depends on the presence of cells with the feature of interest, and negative dPCC represents loss of interaction (LOI) because excluding cells associated with the feature of interest increases the PCC.where PCCobs) for each gene pair/feature combination empirically. Briefly, we determined n, the number of cell lines associated with the feature. Then we randomly removed n cell lines from the set of all 808 cell lines and calculated the all-by-all PCC matrix for all pairs of genes, PCCrand. For each gene pair, we measured dPCCrand = PCCall − PCCrand. We repeated this process 1000× and compared the observed dPCCobs to the bootstrapped distribution of dPCCrand to calculate a two-sided empirical P-value that dPCCobs is higher or lower than random expectation. In general, our sampled null distributions of dPCCrand are not well estimated by classical distributions, and our estimate of P-value is therefore limited to a discrete distribution in steps of 0.001. We repeated this bootstrap resampling to generate null distributions of dPCCrand for every gene pair for each of the 393 contexts identified by the logistic regression model . See “calc_diff_coess_pval.py” for code and details.We evaluated the statistical significance of the observed dPCC , LN-18 (CRL-2610), and U-118 MG (HTB-15) were sourced from the American Type Culture Collection (ATCC). Cell line identities were confirmed by STR fingerprinting by M.D. Anderson Cancer Center’s Cytogenetic and Cell Authentication Core (Promega Powerplex 16 High Sensitivity Assay). All cell lines were routinely tested for mycoplasma contamination using cells cultured in non-antibiotic medium .2. Cell lines were cultured in HEPES modified Dulbecco’s modified Eagle’s medium (Sigma D6171) supplemented with 10% FBS (Sigma), 1 mM sodium pyruvate (Gibco), 2 mM L-alanyl-L-glutamine dipeptide (Gibco), 1× penicillin-streptomycin (Gibco), and 100 μg/mL Normocin (InvivoGen).All cell lines were grown at 37 °C in humidified incubators at 5.0% COLentivirus was produced by the University of Michigan Vector Core. Virus stocks were not titered in advance. All transductions were performed in a 6-well plate format across multiple plates with a range of virus volumes and 8 μg/mL polybrene (EMD Millipore). The pool with the most optimal transduction efficiency was expanded and collected for western blotting.5 LN-18 per well, 6 × 105 U-118 MG per well, 6 × 105 M059K per well.Non-transduced cells were eliminated via selection with 2 μg/mL puromycin dihydrochloride (Gibco). Selection was maintained until all non-transduced control cells reached 0% viability. Once selection with puromycin was complete, three replicates were seeded in a 6-well plate format using the following amounts of viable cells: 4 × 10Cells were washed with PBS and harvested in RIPA lysis buffer  supplemented with Halt Protease Inhibitor Cocktail . Twenty micrograms of cell lysate was denatured in Laemmli SDS-Sample Buffer  and loaded on a precast 4–15% Mini-Protean TGX Stain-Free gel (Bio-Rad). After electrophoresis and transfer, the PVDF membrane (Bio-Rad) was blocked in 5% nonfat milk with TBST (Bio-Rad) at room temperature for 1 h and incubated with primary antibody overnight. MET  antibody was purchased from cell signaling technology. CPD  and GAPDH  antibodies were purchased from Thermo Fisher Scientific. The membranes were then washed in TBST three times, followed by incubation with goat anti-rabbit/Mouse secondary antibodies  for 1 h at room temperature. After washing with TBST, the membranes were developed by films. All western blots were repeated twice. Image quantification was performed in ImageJ.Additional file 1: Figure S1. Regression model. Figure S2. Screenshot of Diffnet web service at https://diffnet.hart-lab.org. Figure S3. Selected regression model features. Figure S4. Raw Western blots from Fig. Additional file 2. Tab-delimited table of regression coefficients, with 2918 genomic and lineage features used to predict background-specific essentiality of 2987 genes.Additional file 3. Tab-delimited table of top 2644 hits from differential PCC analysis.Additional file 4. Quantitative data from Western blot experiments.Additional file 5. Review history.


They provide a key tool with which to study cell toxicity and responses to environmental stressors on a cellular level in wild bird species of interest.The validation of the use of primary cell lines from non-lethal matrixes of feathers and blood of nestlings of a wild bird species, the tawny owl  is described. Tawny Owl Feather Fibroblast (TOFF) cells and peripheral blood mononuclear cells (PBMCs) were isolated and cultured from the pulp of the secondary wing feathers and whole blood respectively from free-living tawny owl nestlings. Cell growth was registered up until 48 h for both the PBMC cells and the TOFFs. The validation of these primary cell lines in free-living birds has the potential to advance the assessment of immunotoxicological effects in wildlife  Utilising in vitro tools such as primary and secondary cell lines can make it possible to study the cellular responses to stressors in wildlife via a non-destructive manner. For example, in vitro studies on blood primary cell lines of peripheral blood mononuclear cells (PBMCs) have shown to be good substitutes for exposure experiments in live animals since they represent an attractive tissue source in molecular and immunologic studies  cell lines that have lost the true characteristics of the original tissue from which they are isolated. Serial passaging is known to cause genotypic and phenotypic variation in cell lines. Variation can often be so far from that of the original tissue to where they do not adequately mimic the in vitro for many validated downstream applications from personalised medicine to veterinary medicine, and wildlife research. However, taking blood samples from live animals can be logistically challenging and requires specialised expertise in the handling and extracting of blood. The amount of blood that can be taken from an individual to minimise adverse outcomes is also limited, especially in smaller species. Other non-destructive matrixes could then be explored for example skin biopsies from free-swimming humpback whales  and one non-adherent cell line (PBMCs). They were chosen because they are both: 1) easily accessed without using lethal methods; 2) represent cells with immunological importance (which will be the focus of our downstream applications). Overall, a standardised tool to assess immunotoxicology in free-living birds is lacking, yet very timely given the increase in epidemics such as avian influenzas  in central Norway. A nest box with three tawny owl nestlings was visited on the 26th of May 2021, 3 weeks after hatching. Blood samples (approx. 1–1.5 ml) were taken from the wing vein from each of the three nestlings using a pre-heparinized sterile 2 ml BD PlastiPak syringe with a 0.6 × 25 mm BD Microlance 3 23G no.16 and transferred to a heparinized tube. One secondary wing feather was taken from each of the nestlings and stored in zip bags. Samples were transported to the laboratory facilities within 1 h of collection. Samples were collected as part of a larger ongoing project .2 incubator at 38°C and 5% CO2 gas for 30 days.All the following steps were completed within 24 h of feather sampling. Feather samples from each individual was stored in separate plastic bags in the cooler or fridge (4°C) from sampling until the culturing was performed. The calamus was separated from the rest of the wing feather  using a g for 10 min for samples that were treated within 12 h, or 20 min for samples that were treated within 12–24 h, with the break on. The supernatant with the PBMCs containing the white blood cells (WBCs) was poured off into a new 15 ml tube. The WBC suspension was then washed with the same amount of DPBS with 2% FBS and centrifuged at 300 g for 10 min. The supernatant was discarded, and the pellet was resuspended. The cells resuspension was added into 10 ml Dulbecco’s modified Eagle’s medium  added 5% foetal calf serum  and 1% of Pen-Strep, 100 U/ml Penicillin and 100 μg/ml Streptomycin (cell culture media) in T-25 flasks. A subset of cells was then plated out into 96 well plates to allow for viewing under the microscope. Cells were incubated in a CO2 incubator at 38°C and 5% CO2 gas for 30 days.All the following steps were performed with blood samples stored within 24 h after blood sampling. The blood samples were stored in a dark area at room temperature. Approximately 2 ml of whole blood was transferred into a 15 ml sterile tube. The same amount of Dulbecco’s phosphate-buffered-saline with 2% foetal bovine serum  was also transferred to the tube. The blood/DPBS mixture was then added to a separation tube (SepMate™ -15 (IVD), Stemcell Technologies) that contained 4.5 ml density gradient media  and 80 µl Lymphocyte Enrichment Cocktail  to enrich lymphocytes from the whole blood samples. The separation tube was then centrifuged at 1200 Cells in the 96 well plates were checked daily and photographed weekly. Cell culture media was added to the cell cultures approximately once a week. Photos were taken either with an apple iPhone through the lens of a Leica DM1000/DM3000 microscope or on the EVOS XL Core image software.Growth of PBMCs and TOFFs were registered in the 96 well plates after 5 days  and blood (PBMCs) from a free-living raptor species, the tawny owl for this purpose. Fibroblasts and PBMCs have key immunological properties , therefoin vitro studies can be further expanded into wildlife, instead of model species. This non-lethal method of a primary cultures creates possibilities of expanding the number of species and individuals to look for pollutant effects and investigate biological processes rather than the sacrificing of one individual to immortalize a secondary cell line; which are not as biological relevant as primary cell lines. Which in turn, create possibilities of making an environment of cell exposure for specific species that are suffering from pollution exposure in the wild. By using cell lines from wildlife species of interest, the results have the potential to have less inter-species bias (both between different wild bird species and between domesticated vs wild bird species).Historically, cell lines have been based on domestic species like the domestic chicken  or quail (Coturnix coturnix) . By valiin vitro experiments. TOFF cells can be used for infection/exposure studies with pollutants and pathogens of choice  on a cellular level of any wild bird species of interest. For further studies, it is also possible to increase the levels of pollutants in the in-vitro studies compared to the current environmental concentrations to simulate how future contamination levels will affect the immune response.The next step in this procedure will be to utilise Tawny Owl PBMCs and TOFFs for immunotoxicology studies by exposing the cells to environmentally relevant levels of pollutants . PBMCs can be used for classic lymphocyte proliferation assays, which makes it feasible to measure toxicity of the cells. The assay discovers the compound’s ability to block or cause biological activity without having toxic effects on cells , which mf choice ). Previof choice . These svia pollution levels. However, care must be taken when interpreting the results on cell lines because they cannot completely replace or reflect the whole complexity of the physiological processes that takes place in an entire organism (Current anthropogenic threats makes raptors more vulnerable to toxicants as they are susceptible to bioaccumulate high levels of metals and other pollutants . Furtherorganism . However


ABQ-1-17) as anti-CML agents. In the current work, ABQ-3 was taken to the National Cancer Institute (NCI) for screening to determine its in vitro antiproliferative effects against a large panel of human tumor cell lines at five doses. ABQ-3 revealed significant growth inhibition against HCT-116 CRC and MCF-7 breast cancer cells with 2.00 µM and 2.35 µM GI50 values, respectively. The MTT test also showed that ABQ-3 possessed anticancer effects towards HCT-116 and MCF-7 cells with IC50 values of 5.22 ± 2.41 μM and 7.46 ± 2.76 μM, respectively. Further experiments indicated that ABQ-3 induced apoptosis in both cell lines, and molecular docking studies explicitly suggested that ABQ-3 exhibited DNA binding in a similar fashion to previously reported compounds. Based on in silico pharmacokinetic prediction, ABQ-3 might display drug-like features enabling this compound to become a lead molecule for future studies.Colorectal cancer (CRC), breast cancer, and chronic myeloid leukemia (CML) are life-threatening malignancies worldwide. Although potent therapeutic and screening strategies have been developed so far, these cancer types are still major public health problems. Therefore, the exploration of more potent and selective new agents is urgently required for the treatment of these cancers. Quinones represent one of the most important structures in anticancer drug discovery. We have previously identified a series of quinone-based compounds ( Colorectal cancer (CRC) is a very malignant and prevalent tumor worldwide. Age, local inflammatory changes, genetic components, and a substantial number of environmental and lifestyle factors account for important risks of CRC development. The great majority of patients with CRC are generally diagnosed at late stages with metastases requiring the administration of radiation therapy and chemotherapy as the leading therapeutic strategies for controlling the disease. Although these therapeutic options have evolved to targeted therapy and immunotherapy, the prognosis of CRC has never reached to the desired rate beyond a delay of disease progression so far. The complexity of the underlying mechanisms of the disease and the development of resistance are the major challenges for the treatment failure ,4,5,6,7.On the other hand, breast cancer is the most prevalent and second most deadly cancer among women across the world. It is heterogenous in nature, containing various subtypes with specific properties. Age, heredity, and steroid hormones are major risk factors in breast cancer development. In spite of traditional treatment strategies, including surgery, chemotherapy, and radiotherapy along with hormonotherapy and targeted therapy options to improve overall survival in breast cancer patients, drug resistance is the major impediment to achieving effective anticancer treatment ,10,11,12Chronic myeloid leukemia (CML) is a myeloproliferative disease characterized by the presence of chromosomal abnormality leading to the aberrant Abelson oncogene (Abl)-breakpoint cluster region (Bcr) gene fusion, which encodes for the Bcr-Abl tyrosine kinase. Tyrosine kinase inhibitors such as imatinib, dasatinib, nilotinib, bosutinib, and ponatinib are the mainstay of CML treatment. However, due to the resistance and toxicity problems emerging during treatment with these agents, new treatment approaches to be efficient in CML treatment are required ,14,15.Apoptosis, known as programmed cell death, maintains the elimination of large numbers of cells that are no longer needed without causing any harm to the developing organism ,17. NecrIt has also gained great importance in developing new, more effective, and selective drugs that precisely target/block the changes that cause cancer growth and proliferation. Natural products are associated with the development of novel therapeutic products for cancer treatment; new natural product analogs revealing great chemical diversity and high potential biological activities have become the apple of the eye of scientists ,24,25,26para position revealed the highest inhibitory capacity. The biological potency decreased in these structures with the extension of the bulky alkyl tail in the alkoxy group , illustrated in The 1,4-quinone moiety is a prominent source of biologically active substances, as shown in In order to enhance biological activity, we additionally studied the lead molecules to determine further activity against HCT-116 CRC and MCF7 breast cancer cells. Moreover, the most effective anticancer compound was subjected to further mechanistic experiments, such as the in vitro determination of levels of apoptosis in both cell lines and the in silico analysis of the DNA binding mode. Several pharmacokinetic determinants of this compound were also anticipated in silico.ABQ-3, NCI: D-827196/1, ABQ-11, NCI: D-827197/1, and ABQ-12, NCI: D-827198/1) towards 60 cancer cell lines [ABQ-3 (2-chloro-3-((4-methoxyphenyl)amino)-5,6-dimethyl-1,4-benzoquinone) was appointed as a lead PQ analog because of its significant selective anticancer potential compared to ABQ-11 and ABQ-12 for five-dose in vitro anticancer activity assessment in the range of 0.01–100 µM.In our previous study, PQ analogs  were docll lines  at a sinll lines ,43. Afte50 (growth inhibitory activity), TGI (cytostatic activity), and LC50 (cytotoxic activity)) [ABQ-3. The GI50 is an indicative concentration with a 50% growth inhibition, whereas TGI refers to the total growth inhibitory activity, and LC50 is an indicative concentration in which 50% of cancer cells died. These parameters were calculated for each cell line from the log concentration versus % growth inhibition curves on 60 human cancer cell lines to create dose–response curves [In the current work, GItivity))  were usee curves ,45.ABQ-3 showed high anticancer effects against all leukemia cell lines with GI50 values of around 2.50 µM. ABQ-3 revealed sensitivity towards all leukemia cell lines in concordance with our previous encouraging results that the IC50 values of ABQ-3 against K562, Jurkat, and MT-2 cells were found as 0.82 ± 0.07 µM, 1.51 ± 0.29 µM and 5.41 ± 0.95 µM, respectively. ABQ-3 also exerted low cytotoxicity against the healthy cell line  with the values of 1.79, and 1.40 µM GI50, respectively. HCT-116 (CRC) had a value of 2.00 µM GI50, LOX IMVI, and UACC-257 (melanoma) had values of 1.79 and 1.86 µM GI50, IGROV1, OVCAR-3, OVCAR-4, OVCAR-8, and NCI/ADR-RES (ovarian cancer) had GI50 values in the range of 1.71–2.12 µM, and MCF-7, MDA-MB-231/ATCC, T-47D, and MDA-MB-468 (breast cancer) had GI50 values in the range of 1.29–2.35 µM. TGI values lower than 20.00 µM were determined with most of the mentioned cell types. Finally, ABQ-3 demonstrated a potent lethal function towards the majority of cancer cell lines in the range of 5.60–26.60 µM LC50 values. All the dose–response curves of ABQ-3 against the 60 human cancer cell lines are outlined in On the other hand, EKVX, HOP-92 (NSCLC), HCT-116, SW-620 (CRC), LOX IMVI, MDA-MB-435, and UACC-257 (melanoma), IGROV1, OVCAR-3, OVCAR-4, OVCAR-8, and NCI/ADR-RES (ovarian cancer), MCF-7, MDA-MB-231/ATCC, T-47D, and MDA-MB-468 (breast cancer) were also found susceptible to ABQ-3 . This anABQ-3 displayed significant sensitivity towards HCT-116 and MCF-7 cell lines based on NCI GI50, TGI, and LC50 parameters. In addition, CRC and breast cancer are important research platforms that we have been working on for a long time. Therefore, we further examined the anticancer effects of ABQ-3 on these two cell lines via an MTT -2,5-diphenyltetrazolium bromide) assay at five dose concentrations  in comparison with cisplatin. Cisplatin was selected as a control because cisplatin has been used for the treatment of various cancers such as CRC and breast cancer [t cancer ,48,49,50ABQ-3 inhibited the cell viability of HCT-116 and MCF-7 with notable IC50 values of 5.22 ± 2.41 μM and 7.46 ± 2.76 μM compared to cisplatin   . The perreatment .ABQ-3 displayed notable anticancer effects on CRC and breast cancer cells, we further searched for its apoptotic effects in HCT-116 and MCF-7 cells using the annexin V/ethidium homodimer III staining assay, which was detected by a fluorescence microscope representing apoptosis, necrosis, or late apoptosis/necrosis with green, yellow and red staining, respectively (ABQ-3 was found to possess similar apoptotic behavior in HCT-116 cells (61.80%) with cisplatin (62.30%). In addition, ABQ-3 showed 22.70% late apoptotic/necrotic and 15.50% necrotic activity in HCT-116 cells when compared with cisplatin   B. The di-7 cells B.ABQ-3 in comparison with ABQ-11 and ABQ-12 in the minor groove of DNA  and −6.610 kcal/mol (PDB ID: 2GB9) indicated that ABQ-3 was able to bind to DNA with a higher binding potential compared to ABQ-11 and ABQ-12   using MDs: 2GWA . The docd ABQ-12 . ABQ-3 pctively) A,B.ABQ-3 were estimated by projecting compounds on the QikProp algorithm [ABQ-3 on cytochrome P450 (CYP) enzymes, the bioavailability, passive gastrointestinal absorption, and brain penetration of ABQ-3 were in silico anticipated with the help of the SwissADME web service [ABQ-3 served a drug-like character that crucial pharmacokinetic determinants, including the octanol/water partition coefficient (QPlogPo/w), aqueous solubility (QPlogS), human serum albumin binding (QPlogKhsa), and brain/blood partition coefficient (QPlogBB) were coherent within specified ranges (ABQ-3 exhibited an excellent % of absorption (100%) and followed Lipinski’s rule of five and Jorgensen’s rule of three without any violation.The pharmacokinetic features of lgorithm . Moreove service ,59. ABQ-d ranges . ABQ-3 eABQ-3 based on the SwissADME tool , implying its high penetration through the BBB. ABQ-3 was also detected with a red dot, explaining that it was not a substrate for P-glycoprotein [The demonstration of physicochemical determinants of DME tool  indicategg model  refers toprotein ,60,61.There are many gaps to fill in the treatment of CRC and breast cancer, albeit to the advancements in the screening programs and in the therapeutic options related to prognostic biomarkers. The discovery of new potential anticancer agents to be effective in both cancers may hold the key to the enhancement of treatment responses for patients with CRC and breast cancer. Several lines of evidence have documented that quinone-based compounds, in particular PQ analogs, stand out as promising candidates for anticancer drug discovery ,63.1  parameters of  enzymes ,73,74.ABQ-3, ABQ-11, and ABQ-12 were carried out previously. Their structures were characterized by spectral analysis previously [The synthetic experiments of eviously .The PQs were investigated for their growth inhibitory activity by the NCI  protocol at a 10 µM concentration in DMSO for 60 cancer cell lines. Compounds were added to the microtiter culture plates and incubated for 48 h at 37 °C. Sulforhodamine B (SRB) was applied for end-point detection. The percentage of the growth of the exposed cells was measured in comparison to the nonexposed control cells, and the findings of each tested compound were calculated ,44,74.ABQ-3) for a higher testing level to determine GI50, TGI, and LC50 for each cell line after generating a dose–response curve, including concentrations of 0.01, 0.1, 1, 10, and 100 µM for ABQ-3 [Serial 5 × 10-fold dilution was carried out from an initial DMSO stock solution before incubation at each individual concentration. The Developmental Therapeutics Program (DTP)-NCI screened the most effective compound  at a 4 × 104 cells/mL concentration for 48 h (the optimum cell number was quantified and linked with an earlier study) [ABQ-3 was prepared in DMSO  and cisplatin in DMF  at concentrations in the range of 0.1–10 mM and further was diluted with fresh culture medium. The concentration of DMSO and DMF in the final culture medium was 1% without affecting the cell viability [HCT-116 cells ) and MCF-7 cells  were incubated in Dulbecco’s modified Eagle’s medium (DMEM)  and RPMI 1640 , respectively. All media  was supplemented with 10% fetal bovine serum (FBS)  and 89 μg/mL streptomycin  at 37 °C, 5% COiability ,40.ABQ-3 and cisplatin on cell viability. HCT-116 and MCF-7 cell lines were subjected to ABQ-3 and cisplatin at 1, 3, 10, 30, and 100 μM concentrations at 37 °C for 48 h before being stained with an MTT solution and further incubated for 4 h. After the removal of supernatants, 100 μL DMSO and DMF (for cisplatin) were added to each well. For the analysis of the absorbance of the solution, a plate reader Infinite M1000  was used. All experiments were applied with three repeats, and IC50 values were identified as the drug concentrations, which decreased the absorbance to 50% of the control values.MTT  assay was used as previously explained ,40 for tABQ-3 and cisplatin at an IC50 concentration for 12 h before the cell death detection kit  was carried out with some modifications to the manufacturer’s protocol [HCT-116 and MCF-7 cells were incubated with protocol . Both ceprotocol .p < 0.05, ** p < 0.01, and *** p < 0.001. GraphPad Prism7  was used for the determination of the IC50 values.All findings were exhibited as means ± SD. Data were screened using a one-way analysis of variance, and diversity was accepted at * ABQ-3, ABQ-11, and ABQ-12 were also prepared using the LigPrep module of Maestro. Ultimately, Glide/XP docking protocols were administered for all these ligands [Initially, DNA was downloaded from RSCB (PDB IDs: 2GWA  and 2GB9 ligands ,53,54,55ABQ-3.The QikProp  and SwisABQ-3 was selected for NCI-60 during in vitro screening at five doses towards a huge panel of cancer cells, including HCT-116 and MCF-7 cell lines. ABQ-3 displayed 2.00 µM GI50, 4.37 µM TGI, and 9.55 µM LC50 values against HCT-116 cells, whereas these values were detected as 2.35 µM, 6.05 µM and 30.60 µM, respectively, against MCF-7 cells, demonstrating the growth inhibitory, cytostatic, and cytotoxic effects of ABQ-3 on these cell lines. Based on MTT screening, this compound also showed significant cytotoxicity against HCT-116 and MCF-7 cells. Furthermore, the cell death assay demonstrated that ABQ-3 enhanced apoptotic activity in HCT-116 and MCF-7 cell lines when compared with cisplatin. Molecular docking studies suggested the strong DNA binding of ABQ-3. In silico ADME prediction indicated that ABQ-3 afforded positive drug-likeness values, thus, making this titled compound a potentially good and orally active anticancer agent for future studies.The quinone-based compound


This study aimed to establish a mathematical survival model database containing cell-specific coefficients from human digestive system cells exposed to electroporation pulses (EPs).A total of 20 types of human digestive system cell lines were selected to investigate the effect of EPs on cell viability. Cell viability was measured after exposure to various pulse settings, and a cell survival model was established using the Peleg–Fermi model. Next, the cell-specific coefficients of each cell line were determined.Cell viability tended to decrease when exposed to stronger electric field strength (EFS), longer pulse duration, and more pulse number, but the decreasing tendency varied among different cell lines. When exposed to a lower EFS , only a slight decrease in cell viability occurred. All cell lines showed a similar tendency: the extent of electrical injury (EI) increased with the increase in pulse number and duration. However, there existed differences in heat sensitivity among organs.This database can be used for the application of electroporation-based treatment (EBT) in the digestive system to predict cell survival and tissue injury distribution during the treatment. In termury (TI) , 4. As Eury (TI) .Although the mechanism of cell electroporation is still controversial, it is well-established that the electric field distribution plays a major role in the biological outcome of EPs, which is primarily determined by the pulse parameter, electrode configuration, environmental conditions, and tissue properties , 6. Therin vitro experiment data and mathematical modeling, Dermol and Miklavčič compared the goodness of fit and applicable situation among different mathematical models of electroporation, confirming Peleg-Fermi model is suitable for treatment planning of electrochemotherapy and IRE  exposed to EPs was established by in vitro. Detailed information on the cell lines is provided in 2 humidified incubator  at 37°C.A total of 20 types of human digestive system cell lines, including 17 cancer cell lines and three normal cell lines, were selected to investigate the effect of EPs on cell viability 4 cells/ml. The cell suspension (500 μl) was added to a 2 mm gap cuvette . A square wave pulse generator  was used to generate a burst of EPs. The detailed protocol of the pulse setting for each procedure is summarized in Before exposure to EPs, the cells were washed with phosphate-buffered saline solution, harvested by trypsin, and resuspended in DMEM culture medium to a concentration of 8 × 10After exposure to EPs, the cell suspension was re-collected immediately, dispensed into 96-well plates, and incubated for 24 h. Cell viability was assessed using the cell counting kit (CCK)-8 commercial kit  following the manufacturer's instructions. The optical density (OD) value at a wavelength of 450 nm was measured using an automatic microplate reader . Cell viability was calculated using the following equation:Aexp, Ablan, and Acon are the mean OD values of the experimental, blank medium, and control groups, respectively. For each parameter setting of each cell line, the experiment was repeated 10 times. All data were analyzed using GraphPad .where The equation for the Peleg–Fermi model was as following:S is the cell viability after EP; E is the EFS; Ec(N) and Ac(N) are two functions that depend on the pulse number (N) and cell-specific coefficients, where Ec(N) represents the EFS required for the half lethality of cells, and Ac(N) is the constant of the cell survival curve slope under specific pulse parameters; and E0, A0, k1, and k2 are the coefficients related to the pulse duration, frequency, and cell type. R2 was calculated as statistical measure for the goodness of fit, which indicates the correlation between the calculated and practically determined value. The value of Ec(N) and Ac(N) was calculated based on Equation (2) as first step. Then the value of the coefficients was calculated subsequently based on the results of the first step and Equations (3) and (4), respectively. Thus, two R2 values was acquired in step 2 because E0 and k1 were fitted separately from A0 and k2 based on different equation.where in vitro study were not suitable for curve fitting. To solve this problem, the modified Peleg–Fermi model and power function model was used instead  and t0 = 1 ms.where Ec(N) (N = 100) were estimated using Equation (3) for each cell line.The survival model curve fitting and calculation of the coefficients were referenced from Goldberg et al. , and werEc(N), the field at which 50% of a population of cells, as the threshold for subsequent numerical analysis.In Pelge-Fermi equation, with the increase of the pulse number, even very weak electric filed will induce electric injury, which is inconsistent with the reality. Therefore, a threshold is needed to limit the calculation for IRE. Here, we defined To evaluate the efficacy of the mathematical model for IRE, a numerical analysis was performed using COMSOL Multiphysics  using the finite element method in accordance with our previous study . To simpA time-dependent study was performed to investigate the accumulative electrical and thermal effects of EP on the tissue. Specifically, the pulse parameter was set to 2,000 V in pulse voltage, 100 μs in pulse duration, and 1 Hz in frequency. A total of 100 pulses were used for EI analysis. To fully evaluate the thermal effect of IRE and heat sensitivity of each organ, 200 pulses  were set for the analysis of TI.Ec(N) for each cell line.Because the results from the Peleg–Fermi model and Arrhenius model depicted survival rate, the threshold of irreversible injury for the probability of EI and TI was set as 0.5, implying that if the probability of EI or TI was >0.5, it could be treated as an irreversible injury. The effective electric field was defined as the threshold of EFS for electroporation that was set as the corresponding value of To quantitatively evaluate the model from a certain cell line, the relative area ratio of the probability of EI and the probability of TI were calculated using Equations (7) and (8):SEI is the area of EI, STI is the area of TI, and Stotal is the total area of the tissue domain. All data were analyzed and compared using GraphPad . As the calculation of EI is based on the specific coefficients obtained from the Peleg–Fermi model at the cellular level, the corresponding SEI can be acquired for each of the 20 cell lines. Since the calculation of TI is based on the Arrhenius equation at the organ level, STI can only be obtained for each organ.where Statistical analysis was performed using GraphPad. The results are expressed as mean ± SD.The viability of each cell line exposed to EPs under various pulse durations, pulse numbers, and EFS was determined. Ec, Ac, and Ec(100) of the 20 cell lines under different pulse durations. Ec and Ac for each cell line with the increase in pulse number under a pulse duration of 100 μs. The data of Ec and Ac under pulse durations of 25, 50, and 75 μs are available in the online database. Moreover, the results of power function model of all cell lines are available in the online database as well  values were in the range of 800–1,000 V/cm, and for a pulse duration of 100 μs, most of the Ec(100) values were between 400 and 600 V/cm. For most of the cell lines, the value of Ec(100) decreased with increasing pulse duration. When treated with EPs with a 100 μs pulse duration, the Ec(100) value varied from 459 to 684 V/cm for esophageal cells, 85 to 536 V/cm for gastric cells, 316 to 632 V/cm for colon cells, 401 to 665 V/cm for hepatic cells, 174 to 485 V/cm for biliary cells, and 532 to 713 V/cm for pancreatic cells.For the 25 μs pulse duration, most of the SEI and STI of each cell line from the digestive system are shown in SEI and STI for specific pulse numbers can be found in the online database  and cholangiocarcinoma cell lines (HCCC-9810 and QBC-939) showed higher slopes and maximum values of the SEI curve than the other cell lines. In contrast, the viability of cell lines from the esophagus and pancreas showed a relatively lower inhibition rate when exposed to EPs  of all cell lines was calculated and compared in this study. For most cell lines, the value of Ec(100) was approximately 500–700 V/cm, which is generally considered as the threshold for electroporation  and 60 days . They also found that harmless, self-limiting adverse effect and lasting tissue regeneration occurred during the 60 days follow-up . Recentlin vitro cell experiments that cannot completely reflect the effect of EPs at the tissue level. However, there is still no qualified method for directly evaluating cell activity under EP in vivo. This study can assess the biological effect of EPs on the survival of the digestive system to a large extent, laying a theoretical foundation for future studies. Second, the Peleg–Fermi model contains the EFS, pulse number, and pulse duration without frequency; however, pulse frequency may have a considerable effect on both EIs and TIs. This model may not be suitable for high-frequency EPs. Third, the EI and TI were calculated via the Peleg–Fermi equation and Arrhenius equation; however, there may exist an electrical-thermal coupling effect during electroporation, which needs to be further investigated for a more accurate model. Additionally, normal tissue properties were used to establish the numerical analysis model due to the lack of data from the tumor; therefore, the efficacy of this model needs to be further verified by in vivo studies in the future.This study has some limitations. First, the cell survival model was established based on in vitro cell experiments and in silico analysis. The efficacy of the database was evaluated by numerical analysis of both EIs and TIs of the digestive system. This database can be used for basic research, computational simulation, medical device design, and treatment planning that can predict cell survival and tissue injury distribution after exposure to EPs during EBT.In this study, a mathematical model database for cell survival containing cell-specific coefficients of 20 human digestive cell lines was established based on The original contributions presented in the study are included in the article/XH and NZ designed the study, performed the related experiment, and wrote and edited the manuscript. YZ, ZL, JZ, XC, and ZQ researched and analyzed the data, helped in writing, and reviewed the manuscript. QL, YW, LM, TH, and YLi helped to perform the related experiments. FR and YLv designed the study and revised the manuscript. All authors have approved the final manuscript.This study was supported by National Natural Science Foundation of China (grant no. 81727802), the Fundamental Research Funds for Central Universities (grant no. XJH012020022), the Scientific Development Funding of the First Affiliated Hospital of Xi'an Jiaotong University (2020QN-08), and the Basic Natural Science Research Project of Shaanxi Province (2021JQ-401). The funders had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Osteosarcoma (OS) is a malignant tumour affecting mainly children and elderly people. Despite significant advances in cancer medicine, osteosarcoma patients’ survival is not improving. The primary treatment methods are established using in vitro models that rely upon the application of well-established cell lines, including U-2 OS, Saos-2 and MG-63. The molecular phenotype of these cell lines is still not fully outlined. Therefore, our study aimed to establish the expression profile of molecular markers related to osteosarcoma survival, progression and metastasis. Non-bone-related cells were used as a reference, i.e. HeLa cell line and human adipose-derived stromal cells (hASCs). Evaluated osteosarcoma cell lines showed characteristic phenotypes with unique patterns related to upregulation of MMP-7, MMP-14, BMP-7, miR-21-5p, miR-124-3p and downregulation of lncRNA MEG3. Our findings may facilitate the selection of the most reliable cellular model for pre-clinical investigations focused on developing new and satisfying methods of osteosarcoma therapy.Osteosarcoma (OS) is a bone tumour affecting adolescents and elderly people. Unfortunately, basic treatment methods are still underdeveloped, which has a high impact on the poor survivability of the patients. Studies designed to understand the underlying mechanisms of osteosarcoma development, as well as preclinical investigations aimed at establishing novel therapeutic strategies, rely significantly upon in vitro models, which apply well-established cell lines such as U-2 OS, Saos-2 and MG-63. In this study, the expression of chosen markers associated with tumour progression, metastasis and survival were identified using RT-qPCR. Levels of several onco-miRs  and long non-coding RNA MEG3 were established. The mRNA expression of bone morphogenetic proteins (BMPs), including BMP-2, BMP-3, BMP-4, BMP-6, BMP-7, as well as their receptors: BMPR-IA, BMPR-IB and BMPR-II was also determined. Other tested markers included metalloproteinases, i.e., MMP-7 and MMP-14 and survivin (BIRC5), C-MYC, as well as CYCLIN D (CCND1). The analysis included comparing obtained profiles with transcript levels established for the osteogenic HeLa cell line and human adipose-derived stromal cells (hASCs). The tested OS cell lines were characterised by a cancer-related phenotype, such as increased expression of mRNA for BMP-7, as well as MMP-7 and MMP-14. Osteosarcoma cells differ considerably in miR-21-5p and miR-124-3p levels, which can be related to uncontrolled tumour growth. The comprehensive examination of osteosarcoma transcriptome profiles may facilitate the selection of appropriate cell models for preclinical investigations aimed at the development of new strategies for OS treatment. Osteosarcoma (OS) is a primary malignant bone tumour formed by cells producing osteoid and immature bone tissue. It mainly affects children and young people (aged 15–19 years) . To understand molecular mechanisms underlying osteosarcoma development and to determine the potential usefulness of newly developed therapeutic strategies, scientists design preclinical assays that rely significantly on in vitro models, applying well-established cell lines, including U-2 OS, Saos-2 and MG-63. Thus, this study analysed the molecular characterisation of those acknowledged human osteosarcoma cell lines. The cells are considered good models for functional osteosarcoma studies. However, in the literature, discrepancies in the characteristics of the molecular phenotype of those cells are noted. Pautke et al. profoundly characterized the osteogenic properties of the osteosarcoma cell lines Saos-2, MG-63 and U-2 OS [Furthermore, Fromigue et al. indicated that the highest migratory capacity characterizes Saos-2, while MG-63 cells have the lowest . In turnGiven the differences in the molecular phenotype of OS cell lines, the main objective of this paper was to investigate the expression profiles of several non-coding RNAs and mRNAs of genes involved in bone biology and tumour progression. The expression profiles of selected biomarkers determined in OS cell lines were compared with the HeLa cell line, known for its osteoinductive properties mediated by bone morphogenetic proteins (BMPs) ,7, as weWe have tested levels of so-called onco-microRNAs (onco-miRs), including miR-21-5p, miR-124-3p, miR-223-3p and miR-320a-3p, and long non-coding RNA—MEG3. The onco-miRs regulate multiple cellular processes of cancer cells, including their division, differentiation and viability. For example, functional in vitro studies showed that miR-21-directly targets the tumour suppressor phosphatase and tensin homologue (PTEN), regulating the proliferation of osteosarcoma cells (MG 63 and U-2 OS) and head and neck cancers (HNC) cell lines ,11. AddiPlethora of onco-miRs also regulate the expression of bone morphogenic proteins . Thus, iMoreover, given that miRNAs regulate genes controlling apoptosis and cell cycle arrest, we decided to determine mRNA levels of several pro-survival markers highly expressed in various malignant tumour tissues and tumour cell lines, including osteosarcomas. The prominent anti-apoptotic molecule, i.e., survivin (BIRC5), was identified as a gene highly expressed in osteosarcoma tissues and involved in osteosarcoma development . C-MYC, A functional characteristic of osteosarcoma based on ncRNA and mRNA profiles is crucial for the proper selection of representative models and in seeking suitable candidates for future therapeutic targets ,18. The The analysis of non-coding RNAs  revealedAnalysis of mRNA levels for particular BMPs showed common gene expression profiles of BMP-2 and BMP-6 molecules a,d. IncrBMP-7 transcripts compared to the HeLa cell line and hASC population  activity. Moreover, miR-124 targets the expression of osterix (SP7/OSX), inhibiting the differentiation of progenitor cells into osteoblasts . It was The tested reference cell lines, i.e., HeLa and hASC, showed a different pattern of miR-124 expression. We noted significantly decreased levels of miR-124 in the HeLa cell line, which is consistent with the study by Zhang et al., who indicated that miR-124 levels are reduced in HeLa and other human cervical cancer (CC), namely SiHa. The study by Zhang and his group also demonstrated that the overexpression of miR-124 might suppress proliferation and decrease the migratory and invasive properties of the tested CC cell lines. Increased expression of miR-124 induced in HeLa also inhibited the epithelial-mesenchymal transition process in vitro .Further, we demonstrated that miR-223 levels are comparable between U-2 OS, Saos-2 and MG-63 cells. MiR-223 is proposed as a good prognostic and diagnostic marker in osteosarcoma. Significantly lowered expression of miR-223 was noted in osteosarcoma patients compared to the healthy controls . The stuThis observation also corresponds with the expression pattern of miR-320, which is an essential modulator of cancer metastasis and proliferation. Increased cell viability with simultaneous downregulation of miR-320a was noted in various cancers, e.g., breast cancer , cervicaThe ASC may promote osteosarcoma growth, invasion and migratory properties by releasing exosomes that carry proteins, mRNA and various non-coding RNAs . ASCs maThe analysis of mRNA expression for BMP-2 showed that its levels are similar in U-2 OS, Saos-2 and HeLa cells. A recent study by Tian et al. revealed that BMP-2 activates the Wnt/β-catenin signalling pathway and promotes the EMT of osteosarcoma . AdditioBMPs are highly expressed in the HeLa cell line, which confirmed the study performed by Kochanowska et al. ,66. HoweWe have also determined the mRNA expression profile of BMP receptors (BMPRs), including BMPR-IA, BMPR-IB and BMPR-II, which initiate intracellular pathways through SMAD proteins . However, it may also act via the JNK and p38 MAP kinase pathway ,68. The Because non-coding RNAs regulate BMPs’ signalling cascade, their correlation has started to be intensively studied. The correlation between miRNA and BMPs can disclose the molecular aetiology of different diseases. For example, it was shown that miR-22 and BMP-7/6 form a regulatory feedback circuit in the course of renal fibrosis . In thisIn our study, we have also determined the expression of genes strictly related to cancer development and progression. The obtained results indicated that the expression of C-MYC in all OS cell lines is lowered compared to HeLa cells. C-MYC is a transcription factor significant for cancer cell proliferation and invasion. The depletion of C-MYC in HeLa cells and MDA-MB-231 cells (human breast adenocarcinoma) strongly impaired their proliferative and migratory activity, which was also accompanied by decreased accumulation of β-catenin . Moreove0/G1 phase and resulted in a shift toward rapid proliferation [Moreover, we showed that hASCs were characterised by lowered expression of both C-MYC and CYCLIN D. The study by Melnik et al. demonstrated that the expression of c-MYC protein correlates with increased proliferative activity of ASCs and may significantly decrease during its cultivation . Paula eferation .Another molecule regulating the division of cells is the survivin belonging to the inhibitor of apoptosis (IAPs) family. Gene coding of the survivin (BIRC5) is upregulated in various malignancies, including osteosarcoma . These rFinally, our study showed that all tested OS cell lines expressed significantly increased mRNA levels for metalloproteinase 7 and 14 . The results confirmed the invasive phenotype of osteosarcoma cells. Moreover, it was revealed that mRNA levels for MMP-14 differ significantly among the tested OS cell lines, suggesting that it may be an important marker of osteosarcoma development. The highest expression of MMP-14 was noted for MG-63, confirming the high invasiveness of this cell line. A potential mechanism explaining the activation of MMP-14 in MG-63 and its role during migration and invasion was presented by Wang et al. . MMP-14 The presented gene expression profile may be a valuable complement to studies related to osteosarcomas’ cancer- and bone-related phenotypes. The classification of OS cell lines based on their transcriptome profile determined using RT-qPCR should provide support to various groups commonly applying this technique in their studies. This knowledge may be beneficial in terms of preclinical studies and the identification of a relevant model. Furthermore, an analysis of the molecular mechanism underlying osteosarcoma progression is necessary. Identifying promising therapeutic candidates may facilitate osteosarcoma diagnosis, restore drug sensitivity and improve therapeutic effects by developing more effective targeted therapies to overcome the poor prognosis of this cancer.2 incubator. The cells were cultured in a complete growth media consisting of basal media, i.e., McCoy’s 5A for U-2 OS and Saos-2, Eagles’ Minimum Essential Medium for MG-63 and HeLa and Dulbecco’s Modified Eagle Medium with low glucose for hASC. All media were supplemented with 10% of foetal bovine serum (FBS) and 1% of the antibiotic solution containing 10,000 units of penicillin and 10 mg of streptomycin/mL . Cultures were maintained in T-75 flasks and harvested at logarithmic phase at confluence established at 90%. Cultures were washed in Hank’s Balanced Salt Solution without calcium and magnesium  and trypsinized for approximately 10 min at 37 °C (StableCell™ Trypsin Solution). Cells were centrifuged , washed again, counted and homogenized with Extrazol . The cell lines, including three osteosarcoma models  and human cervix epithelioid carcinoma (HeLa) were derived from the European Collection of Authenticated Cell Cultures , while and human mesenchymal stromal cells (hASC) were purchased from Millipore . The cells were propagated at constant conditions  in sterile conditions using a CO6 were homogenised using 1 mL of Extrazol . The chloroform, isopropanol, ethanol and DEPC-treated water used during total RNA isolation were derived from Sigma-Aldrich . Detailed protocols used to determine transcript levels were published previously [®&Fluorescein Kit  in a total volume equal to 10 μL. The final concentration of primers used in the reaction was 400 nM. The primers were synthesised by Sigma-Aldrich, Poznan, Poland and purified using HPLC technology. The RT-qPCR thermal cyclers from Bio-Rad  were used, i.e., T100 during RNA purification and cDNA synthesis and CFX Connect Real-Time PCR Detection System for transcript levels measurements.All reagents used for the RT-qPCR were molecular biology grade. RNase-free plastic pipette tips, PCR tubes, microcentrifuge tubes, and conical tubes were used during the experiment to avoid degradation of the matrices. Total RNA was isolated from cell homogenates using the phenol-chloroform method published by Chomczynski and Sacchi . Monolayeviously ,45,92. IThe primers used for the reaction are presented in p < 0.05, ** for p < 0.01, *** p for < 0.001 and **** p < 0.0001. The results are presented as mean values obtained in at least three independent reactions, while whiskers represent standard deviation (±SD).The obtained results were verified using analysis of variance (ANOVA) with the Bonferroni correction (Bonferroni post hoc test). The analysis was performed using GraphPad Prism 8 . Statistically significant differences were marked with * for In summary, we used the RT-qPCR technique to determine expression patterns of several non-coding RNAs and genes associated with OS development. We compared them with profiles obtained for the HeLa cell line and human adipose-derived stromal cells (hASCs).We showed that miR-21-5p and BMP-7 could be relevant markers of osteosarcoma cell lines. mRNA levels for BMP receptors showed a cell-specific expression pattern. The results confirmed the molecular phenotype of the osteosarcoma cells, associated with their invasiveness and manifested by low expression of MEG3 and high mRNA levels for metalloproteinases, especially for MMP-14. Moreover, we established that the levels of miR-223 and miR-320 noted in OS cell lines and hASC are comparable. These onco-miRs could be significant players in OS development associated with the activity of ASCs in the tumour microenvironment.The presented gene expression profile may prove to be a valuable complement to studies aimed at the characterization of osteosarcoma and its cancer- and bone-related phenotypes. Comprehensive molecular identification of OS cell lines provides helpful information that may benefit the proper selection of a model for functional analysis aimed at developing new methods of osteosarcoma treatment.


Human papillomavirus positive tonsillar and base of tongue cancers are rising in incidence but chemoradiotherapy has not improved survival, so novel treatments are needed. Therefore, targeted therapy with phosphoinositide 3-kinase, poly-ADP-ribose-polymerase, and WEE1 inhibitors was pursued alone or combined with/without radiotherapy or using APR-246 and their effects were analyzed by WST-1 viability, proliferation, and cytotoxicity assays on tonsillar and base of tongue cancer cell lines. All three inhibitors induced dose dependent inhibition of viability and proliferation and their effects were enhanced by adding irradiation or by combining the inhibitors. However, adding irradiation to already synergistic inhibitor combinations did generally not induce additional inhibitory effects. Only very high APR-246 doses decreased viability, so its use was limited in this context. To conclude, the effects of the inhibitors were frequently enhanced by adding radiotherapy or by combining them, but adding radiotherapy to the latter did not generally induce further inhibition. +) tonsillar and base of tongue cancer (TSCC/BOTSCC) is rising in incidence, but chemoradiotherapy is not curative for all. Therefore, targeted therapy with PI3K (BYL719), PARP (BMN-673), and WEE1 (MK-1775) inhibitors alone or combined was pursued with or without 10 Gy and their effects were analyzed by viability, proliferation, and cytotoxicity assays on the TSCC/BOTSCC cell lines HPV+ UPCI-SCC-154 and HPV− UT-SCC-60A. Effective single drug/10 Gy combinations were validated on additional TSCC lines. Finally, APR-246 was assessed on several TSCC/BOTSCC cell lines. BYL719, BMN-673, and MK-1775 treatments induced dose dependent responses in HPV+ UPCI-SCC-154 and HPV− UT-SCC-60A and when combined with 10 Gy, synergistic effects were disclosed, as was also the case upon validation. Using BYL719/BMN-673, BYL719/MK-1775, or BMN-673/MK-1775 combinations on HPV+ UPCI-SCC-154 and HPV− UT-SCC-60A also induced synergy compared to single drug administrations, but adding 10 Gy to these synergistic drug combinations had no further major effects. Low APR-246 concentrations had limited usefulness. To conclude, synergistic effects were disclosed when complementing single BYL719 BMN-673 and MK-1775 administrations with 10 Gy or when combining the inhibitors, while adding 10 Gy to the latter did not further enhance their already additive/synergistic effects. APR-246 was suboptimal in the present context. Human papillomavirus positive (HPV Morecurrence ,39,40,41ical use ,43. + UM-SCC-47, UPCI-SCC-154, and HPV-UT-SCC-60A [PIK3CA/FGFR3 mutations, but still showed dose dependent responses and synergy [+ CU-OP-2, -3, -20, and HPV− CU-OP-17 with/without (w/wo) PIK3CA/FGFR3 mutations and could confirm dose dependent responses and synergy [+/HPV− CU-OP lines and revealed positive synergistic effects similar to that for certain breast cancer types [Due to early inhibitor studies in vitro on breast and urothelial cancer, we also initially explored the effects of some of the then available non-FDA approved PI3K and FGFR inhibitors  on TSCC/BOTSCC cell lines HPV-SCC-60A . These l synergy . We thener types . More recently, we also tested single and combined poly-ADP-ribose-polymerase (PARP) and WEE1 inhibitors on the CU-OP lines ,47. Howe+ TSCC/BOTSCC, similar to that for other cancers, especially upon failure or resistance to anti PD-1/PDL-1 therapy, often given today, but before doing so, more knowledge would be of value [Clearly, some, but not all above combinations, could be useful clinically for relapsed HPVof value ,47,48,49of value ,47,48,49+ UPCI-SCC-154 and HPV− UT-SCC-60A. More importantly, in parallel, on the same two cell lines, we investigated whether adding irradiation (IR) to the aforementioned inhibitors alone or their combinations could improve their efficacy, since IR has been shown to enhance the effect of PARP inhibitors in other systems [+/HPV− TSCC/BOTSCC cell lines. In this study, we explored the effects of PI3K, PARP, and WEE1 inhibitors  alone and the recent BMN-673 and MK-1775 combination  as well  systems . We then systems , we also systems . We therTP53 and HPV− UT-SCC-60A, a TSCC with mutant TP53, respectively, were obtained from Susan Gollin, University of Pittsburgh USA and Reidar Grénman, University of Turku, Finland, respectively, and both were kept in Dulbecco’s modified Eagle’s medium (Gibco) [+ CU-OP-2 (with a PIK3CA and FGFR3 mutation), CU-OP-3, CU-OP-20 (with a PIK3CA mutation), and HPV− CU-OP-17, all with wt TP53, were obtained from N. Powell, Cardiff University UK [2.UPCI-SCC-154, a tongue squamous cell carcinoma with wt  (Gibco) ,53. HPV+rsity UK ,54. Theyrsity UK ,54. All For analysis, UPCI-SCC-154 and UT-SCC-60A were seeded with 5000 cells/well, while the CU-OP lines (without feeders) were seeded at 7500 cells/well with all in 96-well plates in 90–200 μL media. All experiments were repeated at least three times.FDA approved phosphoinositide 3-kinase (PI3K) inhibitor BYL719, poly-ADP-ribose-polymerase (PARP) inhibitor BMN-673 as well as non-FDA approved WEE1 inhibitor MK-1775 were all purchased at Selleckhem Chemicals Munich, Germany. Stock solutions at 10 mM for all inhibitors were diluted in the presence of 1% DMSO. Further dilutions were, however, all made with PBS and stored at −20 °C. The inhibitors were diluted once again before use  and utilized in the following doses: BYL719 0.5–20 μM; PD-0332991 5–40 μM; and for BMN-673 0.1–50 μM and MK-1775 0.1–50 μM. APR-246 was kindly obtained from Prof. Klas Wiman, Karolinska Institutet, Stockholm, Sweden and stocked in DMSO and then further diluted 10–100 μM in PBS before use. IR with 10 Gray (Gy), was given with an X-Rad 225XL machine  3 hours (h) before inhibitor treatment to UPCI-SCC-154 and UT-SCC-60A, while to CU-OP cells, 10 Gy was given at the same time or 3 h after inhibitor treatment, if not stated otherwise.Viability pursued for 72 h after treatment was assessed by a WST-1 assay  in accordance with the instructions of the manufacturer and repeated three times, as previously reported in more detail .The 96-well plates with the various cell lines were placed into the IncuCyte S3 Live® Cell Analysis System utilizing the Incucyte™ Cytotox Red Reagent  and followed for proliferation (cell confluence) and cytotoxicity by taking images every 2 h, as described earlier . Of the To verify the efficacy of the single inhibitors or their combinations in comparison to the negative PBS control, a multiple t-test followed by correction for multiple comparison of the means conferring to the Holm Sidak method was performed ,46,55,56+ CU-OP-2, -3, and -20 and HPV− CU-OP-17 presented dose dependent responses to BYL719, BMN-673, and MK-1775 [Previously, we have shown that HPV MK-1775 . Here, w MK-1775 , and thep < 0.05) (p < 0.05) but not after 72 h (p < 0.05)  A. For UTter 72 h C. Upon a < 0.05) B,D. p < 0.05) (p < 0.05) (p < 0.05) when IR was not applied  E. Upon c < 0.05) F. UT-SCC applied G. Upon c applied H. p < 0.05) (p < 0.05)  I,J. For  < 0.05) K,L.Combinational indices (CIs) 48 and 72 h after treatment of BYL719, BMN-673, and MK-1775, w/wo IR, were calculated for UPCI-SCC-154 and UT-SCC-60A to determine the effect of combinations .In line with For UT-SCC-60A, again in line with the viability data, clear positive combinational effects were observed at 48 h for the BYL719 and 10 Gy and MK-1775 and 10 Gy combinations, while the 10 Gy and BMN-673 combinations mainly resulted in neutral or adverse effects D–F. To conclude, for UPCI-SCC-154, adding 10 Gy to BYL719 and BMN-673 enhanced the efficacy of single drugs, while for the 10 Gy and MK-1775 inhibitor combination, neutral effects were obtained. For UT-SCC-60A, enhanced efficacy was shown with the 10 Gy BYL719 and 10 Gy MK-1775 combinations, but not by combining 10 Gy with BMN-673. Due to the positive effects above of single drugs and IR, we decided to conduct some complementary experiments on two additional cell lines. A pilot study on CU-OP-2, with 10 Gy given at the same time or 3 h after treatment with 0.5 µM BYL719 showed mainly positive effects, irrespective of the timing of IR (data not shown). p < 0.05) (p < 0.05), while for CU-OP-20, this increase was not so pronounced  . Moreoveonounced . When caonounced .To summarize, UPCI-SCC-154 was generally more sensitive to single doses of the inhibitors than UT-SCC-60A, however, both cell lines were most sensitive to MK-1775 and more resistant to BMN-673 with the drug doses used here. Adding IR with 10 Gy frequently decreased the viability in comparison to using single drugs alone in both cell lines, especially 48–72 h after treatment. This was illustrated in detail by calculating the combinational effects ,56, show+ CU-OP-2, -3, and -20 and HPV− CU-OP-17 were shown to present synergistic responses to BMN-673 combined with MK-1775, but not as often and also to a lesser extent when compared to the BYL719 and CDK4/6 combination [+ UPCI-SCC-154 and HPV− UT-SCC-60A) and more combinations, in other words, 0.5–1 µM each of either BYL719 and MK-1775, BYL719, and BMN-673 and the recently examined combination BMN-673 and MK-1775, and now w/wo IR with 10 Gy  (p < 0.05) (All combinations of BYL719 with MK-1775 wo IR decreased the viability significantly compared to PBS in both cell lines (at least  < 0.05) A,C. Upon < 0.05) B,D. p < 0.05) (p < 0.05) and this was enhanced further upon applying 10 Gy, since significance was reached at all timepoints except for combinations with 0.5 µM BYL719 at 24 h (at least p < 0.05)  E,F. In U < 0.05) G,H. p < 0.05) (p < 0.05) (p < 0.05)  I. In UT- < 0.05) K. Combin < 0.05) J,L.Combinational indices (CIs) of BYL719, BMN-673, and MK-1775, w/wo IR, were calculated for each cell line 48 and 72 h after treatment to determine the effect of the various combinations, and these showed mainly positive or neutral effects . UPCI-SCC-154 is often more sensitive to single drug treatments than UT-SCC-60A, so we hypothesized that CIs would thereby indicate more positive effects for the latter compared to the former cell line  due to pBYL719/MK-1775 combinations resulted exclusively in positive effects in UT-SCC-60A, while for UPCI-SCC-154, the effects were more neutral. Adding 10 Gy did not change the effects at 48 h but at 72 h, giving IR was likely less positive than wo IR for both cell lines. BYL719/BMN-673 combinations showed positive effects in both cell lines w/wo IR.BMN-673/MK-1775 combinations showed positive effects in both cell lines with lower doses of MK-1775, while higher MK-1775 doses provided either a more neutral or even negative combinational effect and with positive effects being greater in UT-SCC-60A compared to UPCI-SCC-154. Adding 10 Gy had marginal effects in both cell lines.To summarize, BYL719/MK-1775, BYL719/BMN-673, or BMN-673/MK-1775 combinations were generally quite efficient and superior to using one inhibitor alone, with UPCI-SCC-154 generally being more sensitive to most combined treatments compared to UT-SCC-60A. However, adding 10 Gy to already efficient combinations did not usually improve the inhibition of viability further, and although IR tended to possibly boost the effect of all inhibitor combinations after 48 h , this wa+ UPCI-SCC-154, CU-OP-2, -3, -20, and HPV− UT-SCC-60A and CU-OP-17 , while this was still not the case for HPV+ CU-OP-3 and HPV− UT-SCC-60A (All cell lines were relatively resistant to APR-246. Only the highest dose (70 µM) was able to decrease the viability significantly after 72 h for HPV-SCC-60A . These f+ UPCI-SCC-154 and HPV− UT-SCC-60A. To validate the data, with some very efficient combinations in the viability tests, the same doses of BYL719 and MK-1775 w/wo 10 Gy were used to follow their effects on the proliferation of the HPV+ CU-OP-2 and -20 cell lines. Due to the positive effects with a decrease in viability using single administrations of 0.5 µM or 1.0 µM of either BYL719, BMN-673 and MK-1775 together with 10 Gy, we here examined the effects of these treatments and corresponding doses on cell confluence and cytotoxicity on HPV− UT-SCC-60A lines. Compared to PBS, low doses of BYL719 and BMN-673 had marginal effects on the cell confluence on both cell lines, while the effects of MK-1775 were slightly more pronounced, but when adding 10 Gy to the single inhibitors, a prominent decease was observed in cell confluence, especially for the UT-SCC-60A cell line with BYL719 and MK-1775, but not BMN-673, in line with the viability data  with the same doses used as in the viability tests for HPVd BYL719 . Cytotox− UT-SCC-60A. Compared to PBS, low doses of the inhibitors had virtually no or marginal effects on cytotoxicity in either cell line, however, adding 10 Gy enhanced the effect of MK-1775, but not for BYL719 and BMN-673 on both cell lines  alone or in different combinations w/wo IR (10 Gy) on two well-established TSCC/BOTSCC cell lines HPVell line ,45,54. F+ UPCI-SCC-154 and HPV− UT-SCC-60A, with the former being generally more sensitive than the latter and by adding 10 Gy, mainly positive or synergistic effects were obtained. Similar data were seen with BYL719, BMN-673, and MK-1775 w/wo 10 Gy on CU-OP-2, while these effects were not at all pronounced for the more sensitive cell line CU-OP-20. Dose dependent responses to single BYL719, BMN-673, and MK-1775 treatments were found in HPV+ UPCI-SCC-154 and HPV− UT-SCC-60A generally decreased the viability much more than using one drug alone in both cell lines, however, adding 10 Gy did not markedly improve this already efficient decrease in the viability in any of the cell lines. Combining BYL719/BMN-673, BYL719/MK-1775, or BMN-673/MK-1775 in HPVFinally, only relatively high concentrations of APR-246 exhibited a prominent decrease on all of the tested cell lines. The dose dependent responses found in UPCI-SCC-154 and UT-SCC-60A with single BYL719, BMN-673, and MK-1775 administrations was expected, since this has been demonstrated before with corresponding inhibitors on other tumor cell lines by others and us ,45,46,48+ UPCI-SCC-154 and CU-OP-2 as well as HPV− UT-SCC-60A, but not so much on CU-OP-20, irrespective of whether they had PIK3CA mutations or not. We presently have no direct explanation for this positive finding, but PI3K inhibitors have been shown to interact with IR in other systems [Adding 10 Gy to BYL719 posed additive effects on HPV systems . For exa systems . Likewis systems . Consequ+ UPCI-SCC-154 showed positive responses to that combination, this was not the case for UT-SCC-60A, despite the two cell lines being relatively equally sensitive to 10 Gy. Similarly, HPV+ CU-OP-2 and CU-OP-20 showed differing responses, with the former being sensitive and the latter insensitive to the BMN-673 10 Gy combination.Combining 10 Gy with BMN-673 showed different patterns. While HPVThe fact that both UPCI-SCC-154 and UT-SCC-60A were relatively insensitive to treatment with BMN alone is, however, not surprising. We have previously shown that the TSCC/BOTSCC cell lines, independent of HPV status, can be either sensitive or resistant to the PARP inhibitor olaparib . FurtherBRCA-1 and 2 mutations, which would be sensitive to PARP inhibitors by using different biomarkers, was pointed out as an important issue and discussed in some detail [In contrast, in other systems, it has been shown that PARP inhibitors, together with IR, have very good effects such as in BRCA1(+/−) lymphoblastoid cells, hepatocellular cancer and lung and breast cancer xenografts ,61,62. Me detail . Clearly+ UPCI-SCC-154 and HPV− UT-SCC-60A were responsive to low doses of MK-1775, similar to what we have shown before (and here) for the CU-OP-cell lines and in line with data by others on the HPV+/HPV− head and neck cancer cell lines [TP53 mutation, it is more sensitive to MK-1775 than to BYL719 and BMN-673, while instead, UPCI-SCC-154 with no TP53 mutation and being HPV+ also exhibited positive effects to PARP inhibitors, as previously shown for other HPV+ cell lines [Notably, both HPVll lines ,65. Furtll lines  (for revll lines ). + head and neck cancer cell lines, but there was no investigation with regard to RT/IR [+ cell lines [− cell lines, whereas Chk1 inhibitors were more efficient in HPV+ tumor models [Combining WEE1 inhibitors with IR has positive effects, as has been shown before for other cancer types such as leukemic T-cells, osteosarcoma, or cells with TP53 mutations such as lung and breast cancer cell lines ,67,68. Tto RT/IR . In anotll lines . In a moll lines . In thatr models . TP53 mutations or various BRCA-1 or 2 mutations or others, may affect the different responses to the various combinations, irrespective of the HPV status of the tumors. It is likely that identifying HPV status alone will be insufficient and one will have to characterize the tumors in more detail before applying specific individualized therapies [Clearly, there are some data using various inhibitors in combination with IR, however, these are not always concordant, suggesting that these issues need to be further clarified. It is most likely more complicated, since the mutational profiles of the individual tumors vary, and harboring, for example, herapies ,69,70. Combining BYL719/BMN-673, BYL719/MK-1775, and BMN-673/MK-1775 mainly elicited positive effects on both cell lines and decreased the viability with low doses. This was of note, but not entirely unexpected, although the latter combination (BMN-673/MK-1775) in our hands had not previously shown the most optimal synergy on the CU-OP cell lines . ObviousThe BYL719 and BMN-673 combination seemed useful in both cell lines in this study. This would then be in line with other studies, where PARP inhibitors have been combined with PI3K inhibitors for high grade serous ovarian and breast cancer with some antitumor effects . The autThe final inhibitor combination in this report was using PI3K together with a WEE1 inhibitor. Here, an additive/synergistic effect was also mainly observed on UT-SCC-60A, most likely due to it being the most resistant cell line, while for UPCI-SCC-154, already sensitive to MK-1775, the additive/synergistic effect was not as pronounced. We attempted to compare our data to similar reports, but were not able to find larger studies using this approach in head and neck cancer, instead, both were often combined separately (e.g. with PARP inhibitors) ,72,73,74Adding IR to the three BYL719/BMN-673, BYL719/MK-1775, and BMN-673/MK-1775 beneficial combinations did not really improve their effects further in a pronounced way. However, in some cases, an earlier response and more marked decrease in viability was observed already after 48 h with regard to the UT-SCC-60A cell line, but this was not markedly reflected when calculating the CIs. Nevertheless, it was of interest to follow the effects of single inhibitors alone w/wo IR as well as to follow the effects of combined inhibitors w/wo IR. The data suggest that depending on the tumor and the situation, one could design a treatment that would include a specific inhibitor together with IR or use two inhibitors in combination. For these, further studies would be of interest, however, the decisive choice would then be either upon recurrence, if the patient tumor does not respond to the possibilities used today, or in the future for primary treatment. However, for the latter, further studies are of importance.TP53 mutations in tumors sensitive to WEE1 are not similar to the ones where APR-246 has its best effects, since the UT-SCC-60A line has a p.Arg342Ter (c.1024C > T), which initiates a premature stop codon in exon 9 of TP53 and results in a truncated TP53 protein [Finally, in this report, we also explored the effect of APR-246 on quite a few cell lines with the anticipation that it would possibly show some effects because high risk HPV E6 downregulates TP53 or because UT-SCC-60A has a documented TP53 mutation ,76. Howe protein ,78,79. I protein ,81. FurtThere were limitations in this study, in that we had a small number of inhibitors and cell lines. However, we did validate some of the most important combinations, and it is obvious that the variability between the different cell lines, irrespective of HPV status, poses additional issues. Obviously, it is not possible to generalize on the sensitivity of the tumors to specific inhibitors or their combinations w/wo IR, solely by HPV status. In the future, a profound molecular analysis of the various cancers should be conducted before the selection of treatment, and experiments carried out to follow if the selection was optimal.In summary, combining 10 Gy with single BYL719 BMN-673 and MK1775 inhibitors can potentially be of use for TSCC/BOTSCC, but is likely not needed when already combining inhibitors exhibiting synergy, while APR-246 was not optimal in this context. Nevertheless, without more detailed analysis of the individual tumors, it may not be possible to predict which combination is the best. +/HPV− TSCC/ BOTSCC cell lines, and when the inhibitors were combined with 10 Gy, or used in combination, mainly positive/synergistic effects were obtained. However, adding 10 Gy to the already efficient postive/synergistic inhibitor combinations had no major further effects. Furthermore, low APR-246 concentrations had limited effects. In this study, single PI3K, PARP, and WEE1 inhibitors BYL719, BMN-673, and MK-1775 induced dose dependent inhibition of viability and proliferation in the HPVTo conclude, adding 10 Gy to single BYL719, BMN-673, and MK-1775 low dose administrations or combining these inhibitors notably enhanced their efficacy, while adding 10 Gy to the latter did not induce any major further improvement of their already enhanced effects. APR-246 was suboptimal in this context.


In order to investigate novel AS-associated LGR4, we discarded LGR4 isoforms from GSO databases. We used siRNA to knock down the specific isoform to check the cell proliferation, migration, and invasion when treated with metformin.  First, the expression of LGR4 in HCC tumor tissues and cell lines was detected by western blotting and immunofluorescence. The ability of cell proliferation, migration, and invasion was detected with CCK8, wound-healing, and transwell assays when overexpressing LGR4 or treating with metformin. The  The level of LGR4 expression was higher in HCC cell lines and tumor tissues. The HCC cell proliferation, migration, and invasion were increased when overexpressing LGR4, which could be reduced by metformin treatment. The GEO database (GSE190076) showed that LGR4 had switching properties in HCC cell lines treated with metformin. We used siRNA to knock down the specific isoform, and the result showed that the specific isoform siRNA could promote the inhibition of cell invasion caused by metformin treatment.  LGR4 could promote the ability of cell proliferation, migration, and invasion in HCC, which could be reduced by metformin through alternative splicing. Hepatocellular carcinoma is the most common type of liver cancer all over the world, especially in China , 2, althLGR4 belongs to the GPCRs superfamily and is recognized as a trans-membrane receptor of the LGR family. Recently, a study indicated that LGR4 could interact with PrPc to promote tumorigenesis and liver metastasis by stemness of colorectal cancer stem cells . In acutIn our research, we investigated the function of LGR4 in the HCC, and we also found that metformin could reduce the expression of LGR4. We also indicated the mechanism of the regulatory effect of metformin. The study could provide evidence of LGR4 function, which could be recognized as a target for HCC treatment.2 at 37°C. The HCC cell lines were treated with metformin (20 μM) [Normal cell lines (L02) and Huh-7 and HepG3B cell lines were obtained from the American Type Culture Collection (ATCC). All cells were cultured in DMEM  with FBS (10%), in an atmosphere containing 5% CO (20 μM) . The HCCAccording to the previous procedure , the tre5 cells per well. And DMEM (10% FBS) was cultured in the bottom chambers. After 6 hours, 4% paraformaldehyde was used to fix the inserts and stain them with 0.1% crystal violet solution. Also, the images were obtained under a microscope.The treated cells were digested and added into the top chambers of transwell inserts with FBS-free DMEM. The cell density is 2 × 10μL pipette tip was used to scratch, cells were washed, and the cell was incubated with DMEM for another 12 hours. Three random areas were photographed to assess the distance of migration.The treated cells were digested and cultured in 6-well plates. After treatment, a 200 According to the previous procedure , proteinβ-catenin staining, the treated cells were washed with PBS three times and fixed, then treated with 0.1% Triton X . Subsequently, a blocking buffer was added and the primary antibody was incubated overnight at 4°C. The next day, the treated cells were incubated with a secondary antibody, then treated with DAPI. Finally, the images were captured by a microscope.For The GEO database (GSE190076) was used to indicate the different gene expressions. Then, the transcript was analyzed with an isoform switch analyser. A total of 480 genes underwent isoform switching. KEGG pathway analysis was also used to analyze the genes' function.p value < 0.05. Differences were determined using a two-way analysis of variance (ANOVA) or unpaired Student's t-test by Prism software.All measurements were presented as the mean ± standard deviations (SD) from three independent experiments. Statistical significance was defined as a First, the level of LGR4 expression was detected in HCC tissues. It showed that LGR4 expression was increased in the tumor tissues . We alsoβ-catenin pathway in many cancers. So, the immunofluorescence indicated that the β-catenin expression was higher in the LGR4 overexpressed cells  to indicate the different gene expressions. It showed the mRNA level of LGR4 had no difference between the two groups, which meant it may be regulated by alternative splicing. Then, we analyzed transcript usage with an isoform switch analyser. A total of 480 genes underwent isoform switching . KEGG paβ-catenin expression. It indicated that the specific isoform siRNA could also reduce the expression of catenin in response to metformin treatment , the use of metformin may improve disease-free survival and overall survival in CRC patients with T2DM . In bladβ-catenin axis to promote the progression of hepatocellular carcinoma [β-catenin signaling in many diseases [β-catenin.LGR4 belongs to the GPCRs superfamily and is recognized as a trans-membrane receptor of the LGR family. In this study, we found that the level of LGR4 in Huh-7 and HepG3B cell lines was much higher than that in L02 cell lines. It indicated that the LGR4 expression was increased in HCC tissues and at cell levels. LGR4 overexpression could promote the processes of proliferation, migration, and invasion. Although the study indicated that Hsa_circ_0003945 could regulate the miR-34c-5p/LGR4/arcinoma , the exadiseases –18. So, β-catenin expression. Apart from alternative splicing, the genes also focus on sulfur metabolism pathways, and the study also indicated that sulfane sulfur metabolism could be used to treat cancers. We will also analyze sulfur metabolism in the future.Alternative splicing could produce multiple transcripts of mRNA to regulate the gene expression . Then, wIn conclusion, we demonstrated that LGR4 could promote the proliferation, migration, and invasion of HCC, which could be reduced by metformin through alternative splicing.