The data were analyzed using a latent variable approach. The results of the study show that academic buoyancy is a significant predictor of math achievement and that this relation is explained through academic self-efficacy, even when controlling for gender. Implications for practice and further research are also discussed.Academic buoyancy describes the ability to successfully overcome and recover from setbacks in an academic context . This day-to-day form of academic resilience has recently been defined in the context of positive psychology. The present study aimed to gain insights into the mechanisms of academic buoyancy by predicting math achievement. Since there is already evidence that this relationship is rather indirect than direct, we were particularly interested in investigating a potential actor of an indirect effect, namely academic self-efficacy. For this purpose,  According to the PISA  survey, in 2018 around 21% of 15-year-old students in Germany achieved the two lowest levels of competence in mathematics and reading skills . Yun et al. .The few studies devoted to the direct relationship between academic buoyancy and achievement suggest that academic buoyancy is a significant predictor of achievement, although the strength of the relationships varied. Martin  found a n et al.  reportedMoreover, Colmar et al.  examinedThus, we consider constructs that have conceptual overlap with academic buoyancy  to be relevant to the relationship between academic buoyancy and achievement and will therefore take a closer look at empirical predictors of academic buoyancy in the following section.confidence, which is mostly assessed via self-efficacy; coordination, which is represented by planning; commitment, which is assessed via persistence; composure, which is determined by low anxiety; and lastly control, which is represented by one’s response to uncertainty. The predictive power of the 5C’s has been repeatedly demonstrated in numerous studies  and that the expression of the construct at the earlier time predicted the expression at the later time (β = .21) ; coordination ; commitment ; composure ; control  . Furthermore, more than 93% of studies report positive correlations between self-efficacy and performance at the interindividual level  of N = 11 schools (Level 2) in southwestern Germany . Of the participating students, 50.2% were female. The students were in Grades 5 to 10 and were between 10 and 19 years old . According to Fritz and MacKinnon . As this indicated our missing data to be MCAR, we decided to apply the recommended full information maximum likelihood (FIML) estimations . We had 3.59% missing values in our variables but no systematic patterns of missing data. To analyze if the missing values were missing completely at random (MCAR), we conducted Little’s  MCAR tesvery good”) and 0 points representing the worst grade (“insufficient”). The reported grades in mathematics, which were used as a performance measure, had an average of M = 8.86 points (SD = 2.94). Finally, students completed the items on self-efficacy and academic buoyancy.Data were collected from October to December 2019 in schools whose principals had agreed to participate in the study. Prior to data acquisition, declarations of consent were distributed in class. Participation was voluntary and only those students who could provide a signed consent form from a parent or guardian were allowed to participate in the study. Teachers received the questionnaires in advance, with detailed instructions to ensure objectivity of implementation. Questionnaires were then completed in class. First, students provided information about their gender, age, grade level, and their most recent report card grade in mathematics. School grades were given according to a 15-point system, with 15 points representing the best possible grade  and the data protection committee of the Ministry of Education in Saarland. All data were handled anonymously.(“strongly agree) to 6 (“strongly disagree”). For better understanding, items were recoded so that high scores indicated high expressions of the relevant factor. Scale means were calculated for the questionnaires. To determine internal consistency, Cronbach’s alpha was calculated for all scales.The following section presents the instruments used to collect the data on the relevant constructs. To answer the questionnaire items, students were presented a six-point Likert scale to indicate how strongly they agreed with the given statements. The possible answers ranged from 1 χ2/df-ratio = 3.76.To assess students’ academic self-efficacy, we slightly adapted an instrument by Schwarzer and Jerusalem  comprisiχ2/df-ratio = 3.05.For academic buoyancy, we used a translated version of a common questionnaire by Martin and Marsh , b. The “insufficient”) to 15 points (“very good”).In addition to questionnaire items regarding academic self-efficacy and academic buoyancy, students’ most recent report card grades in mathematics were collected, ranging from 0 points . RMSEA and SRMR usually vary between 0 and 1 and excellent model fit is indicated with values of .05 or less. The χ2/df-ratio should be below 3 for perfect model fit. CFI, taking values from 0 to 1, should be .95 or greater for excellent fit of the data to the hypothesized model.Model fit was determined according to common recommendations , as recommended in the common literature , indicating that academic buoyancy significantly predicts academic self-efficacy in students. The higher the students’ academic buoyancy, the higher their self-efficacy.To test Hypothesis 1 (path a), we used a simple latent regression model with academic buoyancy predicting academic self-efficacy. The model showed acceptable fit with CFI = .96, RMSEA = .06, SRMR = .04, and β = .57, p < .001). The model for this hypothesis showed good fit to the data . The greater the students’ self-efficacy, the higher their math grade.For Hypothesis 2 (path b), we tested the path from academic self-efficacy to math achievement, which was significant (χ2/df-ratio = 5.20) and resulted in a significant regression . The more buoyant the students, the better their math grade.For Hypothesis 3 (path c), we tested the effect of academic buoyancy on math achievement. This model had acceptable fit . Academic self-efficacy was a significant predictor in the multiple regression with academic buoyancy  which justified testing the mediation model in the next step.In order to estimate the model for Hypothesis 4 (path c’), we conducted a multiple latent regression with the predictors—academic buoyancy and academic self-efficacy—regressed on the dependent variable, math achievement. This model showed good model fit  via self-efficacy was significant ; the 99% CI with bias-corrected bootstrapping did not include zero [0.57–1.33]. In the multiple regression with academic self-efficacy and academic buoyancy predicting achievement (path c’), academic buoyancy was not a significant predictor, which suggests that academic self-efficacy completely mediates the relationship between academic buoyancy and achievement .For the final mediation model, we estimated a model with academic buoyancy predicting math achievement χ2/df-ratio = 4.22. The indirect effect of academic buoyancy on math achievement via self-efficacy was again significant  and the 99% confidence interval with bias-corrected bootstrapping did not include zero [0.52–1.37]. In this case, academic buoyancy was also not a significant predictor in the multiple regression, which further indicates that academic self-efficacy completely mediates the relationship . Moreover, correlations with the covariate gender indicated that male students  were, on average, significantly more buoyant  but did not experience more self-efficacy  nor were they higher achieving in math  . This is in line with prior research .The significant predictive power of academic buoyancy on achievement, which we investigated in our second hypothesis is also in line with previous findings and shows that academic buoyancy is a performance-relevant construct. These findings are consistent with those of Martin  and Yun To answer our third hypothesis, we further examined whether academic self-efficacy is a significant predictor of math achievement in a multiple regression model with academic buoyancy—if academic self-efficacy predicts variance in math achievement beyond academic buoyancy—and found a significant effect. This justified testing a mediation model. However, we only had one time point at which we measured the predictors as well as the criterium.r = .48) and that is why we have to assume a multicollinearity between both variables. This also could cause the decreased relationship of academic buoyancy and achievement in the mediation model. As academic buoyancy and self-efficacy are theoretically linked and interwoven (Smith, The concluding mediation analyses showed that the relationship between academic buoyancy and achievement is fully associated through academic self-efficacy. Thus, when self-efficacy is included in the model, the direct relationship between academic buoyancy and math achievement is not significant. This complete indirect association of the relationship reveals that the performance-relevant effects of academic buoyancy do not directly impact performance. However, this by no means limits the relevance of academic buoyancy to performance. Rather, the results show, especially considering the current research background, that little is known about the mechanisms of academic buoyancy. Previous work, such as that by Colmar et al.  and Colln Smith, , it has Moreover, as recommended by Colmar et al. , we accoTaking these findings together, we have significantly contributed to the research on academic buoyancy and its relationship with achievement. We have provided another study suggesting that academic buoyancy is crucial to academic achievement, but especially influences other variables that, in turn, impact achievement. Moreover, we replicated previous findings with a large sample allowing structural equation modeling in a German-speaking country where academic buoyancy has rarely been considered thus far.However, the results of the study should, of course, not be interpreted without considering its limitations.The fundamental difficulties that can arise from data collection by questionnaire should be pointed out. The questionnaires used to assess academic self-efficacy and academic buoyancy were self-report methods. This means that it cannot be guaranteed that the questionnaire scores given by the students correspond to their actual characteristics in the corresponding constructs. This may be due to the effect of social pressure. It is also conceivable that students did not provide honest information for fear of the information being passed on to the teachers. Nevertheless, there is no appropriate alternative to self-report questionnaires for academic buoyancy or academic self-efficacy, and other studies have implemented them as well.The cross-sectional design of the study is limiting the implications as well. The project in which the present study took place was initially planned as a long-term study, with two data collection points separated by six months. However, due to the global COVID-19 pandemic, the second measurement point in spring 2020 had to be canceled. Datu and Yang  criticizAnother limitation is the use of the most recent grade in mathematics as a measure of academic performance. First of all, looking at a single grade on a school report is not sufficiently informative regarding students’ overall academic performance (Südkamp et al., Further, it could be problematic that the achievement measure was domain-specific and self-efficacy and academic buoyancy were measured domain-general. It is generally assumed that self-efficacy and performance measures correlate especially high when there is the greatest possible correspondence in terms of content (Feng et al., The results of the present study show that academic buoyancy is a relevant construct that should be further explored in future educational research.The predictors of academic buoyancy which are referred to as the 5C’s (Martin & Marsh, Moreover, research on academic buoyancy has so far been conducted almost exclusively in industrialized countries, mainly Australia and the UK, and individualistic societies (for a review, see Datu & Yang, Most studies on academic buoyancy have focused on students in higher grades. This focus is justified by the assumption that academic buoyancy plays a more significant role among older students. However, future studies should also look at younger students. As with many educational-psychological constructs with a performance-relevant effect, it can be assumed that academic buoyancy is acquired and trainable in childhood (e.g., self-regulated learning; Dignath et al., which students become buoyant and what exactly makes them buoyant—for example, by applying person-centered approaches. This could contribute to the development of interventions to make students more resilient to future academic adversity. If an intervention claims to make students more resilient and thus supports them in their everyday school life, academic buoyancy must play an essential role as students do not only suffer from “major negative outcomes,” but also the sum of “low-level negative outcomes” that burden them in the long run (Martin, More research should be dedicated to the questions of  Martin, , p. 496. Martin,  showed tThe significant association between academic buoyancy and achievement has been discussed in detail in this paper. However, performance is not the only variable that is positively influenced by academic buoyancy. Miller et al.  addresseBy examining the relationships between academic buoyancy, academic self-efficacy, and achievement, the present study provided insights into the mechanisms of academic buoyancy. The results are consistent with the previous state of research and extend it in a significant way. However, as academic buoyancy has been little researched so far, further studies dedicated to the construct are urgently needed. With better knowledge, interventions or classroom strategies to support students can be derived. Interventions can be targeted at all students, as the ability to cope with small setbacks is important for all learners. If students are able to recover from the adversities of everyday academic life, this can also be important for later confrontations with greater difficulties. The construct of academic buoyancy should therefore be the subject of greater research interest in the future.


V600E mutation; however, acquired resistance is unavoidable. The present study aimed to identify a potential target to reverse resistance.Vemurafenib (VEM) is a commonly used inhibitor of papillary thyroid cancer (PTC) and melanoma with the BRAFV600E melanoma cell line (A375/VR) was also established. RNA sequencing and bioinformatics analyses were conducted to identify dysregulated genes and construct a transcription factor (TF) network. The role of a potential TF, forkhead box P2 (FOXP2), verified by qRT-PCR, was selected for further confirmation.A VEM-resistant PTC cell line (B-CPAP/VR) was established by gradually increasing the drug concentration, and a VEM-resistant BRAFp < 0.05). RNA sequencing identified 9177 dysregulated genes in the resistant cell lines, and a TF network consisting of 13 TFs and 44 target genes was constructed. Alterations in FOXP2 expression were determined to be consistent between the two VEM-resistant cell lines. Finally, silencing FOXP2 resulted in an increase in drug sensitivity and significant suppression of the migration and colony formation abilities of the two resistant cell lines (p < 0.05).The two resistant cell lines were tolerant of VEM and displayed higher migration and colony formation abilities (The present study successfully established two VEM-resistant cell lines and identified a potential target for VEM-resistant PTC or melanoma. V600E mutant functions as the major driver of the MAPK pathway and is involved in the secondary genetic alteration of members of the PI3K-AKT pathway, thus leading to the aggressive development of PTC -2,5-diphenyltetrazolium bromide  for another 3 h. Next, the supernatant was removed and dimethyl sulfoxide  was added to each well and incubated for 15 min. The optical density (OD) of each well was measured at 490 nm using a microplate reader . The survival rate (%) was calculated according to the following formula [B-CPAP, A375, B-CPAP/VR, and A375/VR cell lines were collected and seeded at 5 × 10 formula :Survival rate (%) = mean OD of experimental group/mean OD of control group × 10050 was calculated according to the survival rate using SPSS version 17.0. The drug resistance index was calculated according to the formula [The IC formula :50 of drug-resistant cell line/ IC50 of corresponding parental cell lineResistance index (RI) = IC3 cells/well in 96-well plates. The OD of each well was measured at 490 nm using the MTT assay every day for 5 days. Four replicate wells were used for each time point. The proliferation rate was calculated using the following formula [The B-CPAP, A375, B-CPAP/VR, and A375/VR cell lines were collected and seeded at 3 × 10 formula :n = 1–5)Proliferation rate = mean OD of day measured (n)/mean OD of first day  inserted into a 24-well plate was used to measure cell motility. The B-CPAP, A375, B-CPAP/VR, and A375/VR cell lines were collected and resuspended in FBS-free culture medium, seeded in a chamber at 2 × 10B-CPAP, A375, B-CPAP/VR, and A375/VR single cells resuspended in the required medium were counted, and 800 cells/well were seeded in 6 well plates. Three days later, VEM (2 μM) was added to the medium and cells were cultured for an additional 11 days. After cloning, the cells were fixed with 4% paraformaldehyde for 30 min and stained with crystal violet for 10 min. Finally, cells were washed twice with PBS for two times and photographed using a digital camera.2 fold change (absolute) |Log2 FC | > 1 , and the resulting genes were used for further bioinformatics analyses.Total RNA of B-CPAP, A375, B-CPAP/VR, and A375/VR was extracted using TRIzol reagent  according to the manufacturer’s instructions. RNA quality and concentration were determined from OD260/280 readings using a NanoDrop ND-1000 spectrophotometer  and assessed on a 1% gel electrophoresis. RNA samples were subjected to BHBIO  for RNA sequencing. Differentially expressed genes (DEGs) were screened under a threshold of logKyoto Encyclopedia of Genes and Genomes (KEGG) analysis was conducted to analyze the enriched signaling pathways of the DEGs. A gene number > 2 was used as a threshold when screening for relevant KEGG pathways. TF-binding networks were constructed using the top 2000 dysfunctional genes utilizing weighted correlation network analysis (WGCNA).5 cells/well) were seeded into six-well plates. After the cells grew to 80% confluence, si-FOXP2 and control siRNA (si-NC) were transfected into VEM-resistant cell lines using Lipofectamine® 3000 (Invitrogen), according to the standard protocol. Forty-eight hours after transfection, transfection efficiency was determined by quantitative real-time PCR (qRT-PCR). The siRNA sequences for si-FOXP2 were as follows: sense (5′-3′): GGCUAGACCUCACUACUAATT, anti-sense (5′-3′): UUAGUAGUGAGGUCUAGCCTT.B-CPAP/VR and A375/VR cells  and then reverse-transcribed using a PrimeScript RT Reagent Kit with gDNA Eraser (TaKaRa) according to the manufacturer’s instructions. The complementary DNA template was amplified by qRT-PCR using SYBR Premix Ex Taq (TaKaRa Bio). qRT-PCR was conducted using the StepOne Plus Real-Time PCR System (Thermo Fisher Scientific). Briefly, the reaction system for quantification included 0.5 µL cDNA, 1 µL primers, 5 µL SYBR Green, and 3.5 µL deionized water. Amplification was performed as follows:−∆∆Ct method and were normalized to GAPDH expression. The primer sequences synthesized by Sangon Biotech  are listed in Table 94 °C for 5 min and 40 cycles of 94 °C for 5 s and 60 °C for 1 min. Gene expression data were analyzed using the 2p < 0.05.SPSS statistical software was used for statistical analysis. The data were tested using the Students’ t-test to analyze the differences between the different groups. Statistical significance was set at 50 value of B-CPAP/VR increased to 304.3 μM, around 44 times of the value of parental B-CPAP (6.92 μM). IC50 values of A375/VR and A375 were 76.76 μM and 1.23 μM respectively, and the resistance index was 62.3 . A transwell assay was performed to evaluate cell motility. A higher number of B-CPAP/VR and A375/VR cells traversed the membrane than B-CPAP and A375 cells, respectively, indicating that the migration ability of resistant cells was significantly enhanced . The colony formation assay results indicated that the colony number of both B-CPAP/VR and A375/VR was more than twice that of their parental cell lines after treatment with VEM for 11 d . All phenotypic changes suggested that the VEM-resistant cell lines were successfully established.The MTT assay results indicated that the proliferation ability of B-CPAP/VR and A375/VR was reduced when compared to the original cell lines . MTT analyses showed that after knockdown FOXP2, the IC50 values of B-CPAP/VR and A375/VR were reduced to 90.77 and 13.05 µM, respectively, much lower than the si-NC group cells  , and the FOXP2 knockdown group showed weaker clone formation and migration abilities . All the phenotype assays indicated that after downregulating FOXP2 expression, the VEM-resistant cell lines B-CPAP/VR and A375/VR were more sensitive to VEM.The expression level of FOXP2 in B-CPAP/VR and A375/VR were knocked down using siRNA. qRT-PCR results indicated a significant decrease in FOXP2 expression in the si-FOXP2 group compared to that in the si-NC group  Fig. . In addiTo reveal the possible mechanism and role played by FOXP2 in VEM resistance, we searched for FOXP2 in Table S1, but no relevant pathway was found. Next, we focused on the target gene, lysophosphatidic acid receptor 3 (LPAR3), of FOXP2, which might establish some connections with the pathways. LPAR3 was involved in five pathways Table ; interesV600E is the most common mutation in some types of cancer. It is highly related to high mortality in patients with PTC or melanoma, which also stimulates research on BRAF inhibitors. To date, the development of new targets is still an important strategy to reverse resistance to VEM and prolong the effective treatment of drug-resistant patients.Acquired drug resistance often occurs when it comes to clinical treatment for patients with cancer, especially for those carrying a mutation in a specific gene. BRAFIn clinical and pre-clinical studies on BRAF inhibitor resistance, the time for VEM resistance development ranged from 3 weeks to 1 year, and very few patients survived without developing resistance . It was V600E; however, to prevent drug resistance, more targets belonging to related pathways need to be identified.According to RNA sequencing data, many of the DEGs involved in the pathways were related to human diseases, but most of them were classified in signal transduction pathways. Many reports have also revealed that signaling pathways are indeed related to drug resistance in TC and melanoma based on in vitro and clinical studies . ClinicaTFs are proteins that control DNA transcripts to mRNA, which can not only upregulate downstream gene expression but also silence specific genes. Therefore, dysregulated TFs induce specific diseases, including cancer, which makes TFs interesting targets for future medications . Many dyKEGG analysis showed that FOXP2 does not directly participate in some signaling pathways, as FOXP2 functions as a TF. Nevertheless, it is possible for FOXP2 to manipulate some downstream genes to turn on/off signal transduction, and the TF network suggests that there is a connection between LPAR3 and FOXP2. LPAR3 encodes a member of the G protein-coupled receptor family and the EDG family of proteins . It is nV600E mutant PTC and melanoma cell lines, which can be used as in vitro models for other VEM-resistance studies. FOXP2 is a potential target and should be further explored as an innovative medication to reverse VEM resistance. The present study also identified a large number of DEGs, thereby providing a databank for target development.In this study, we established robust VEM-resistant BRAFTable S1


Glioblastomas (GBs) are characterised as one of the most aggressive primary central nervous system tumours (CNSTs). Single-cell sequencing analysis identified the presence of a highly heterogeneous population of cancer stem cells (CSCs). The proteins anterior gradient homologue 2 (AGR2) and glucose-regulated protein 78 (GRP78) are known to play critical roles in regulating unfolded protein response (UPR) machinery. The UPR machinery influences cell survival, migration, invasion and drug resistance. Hence, we investigated the role of AGR2 in drug-resistant recurrent glioblastoma cells.Immunofluorescence, biological assessments and whole exome sequencing analyses were completed under in situ and in vitro conditions. Cells were treated with CNSTs clinical/preclinical drugs taxol, cisplatin, irinotecan, MCK8866, etoposide, and temozolomide, then resistant cells were analysed for the expression of AGR2. AGR2 was repressed using single and double siRNA transfections and combined with either temozolomide or irinotecan.characterisations of the AGR2-expressed Jed66_GB and Jed41_GB recurrent glioblastoma tissues and cell lines showed features consistent with glioblastoma. Immunofluorescence data indicated that AGR2 co-localised with the UPR marker GRP78 in both the tissue and their corresponding primary cell lines. AGR2 and GRP78 were highly expressed in glioblastoma CSCs. Following treatment with the aforementioned drugs, all drug-surviving cells showed high expression of AGR2. Prolonged siRNA repression of a particular region in AGR2 exon 2 reduced AGR2 protein expression and led to lower cell densities in both cell lines. Co-treatments using AGR2 exon 2B siRNA in conjunction with temozolomide or irinotecan had partially synergistic effects. The slight reduction of AGR2 expression increased nuclear Caspase-3 activation in both cell lines and caused multinucleation in the Jed66_GB cell line.Genomic and biological AGR2 is highly expressed in UPR-active CSCs and drug-resistant GB cells, and its repression leads to apoptosis, via multiple pathways.The online version contains supplementary material available at 10.1186/s12935-022-02814-5. Glioblastomas are characterised as grade 4, and are highly aggressive primary central nervous system tumours (CNSTs) . Tumours(IDH1/2), phosphatase and tensin homolog (PTEN), cyclin dependent kinase inhibitor 2A (CDKN2A), tumour protein p53 (TP53), parkin RBR E3 ubiquitin protein ligase (Park2), protein tyrosine phosphatase receptor type D (PTPred) and neurofibromin 1(NF1) genes. Several amplifications of genes have also been identified including the amplifications of the epidermal growth factor receptor (EGFR), fibroblast growth factor receptor 2 (FGFR2), insulin receptor substrate 2 (IRS2), and AKT serine/threonine kinase 3 (AKT3) ; and TP53 in intron 8-exon9 . The specificity of the PCR products was ascertained by gel electrophoresis. Subsequently, the PCR products were purified and underwent cycle sequence reactions using a BigDye Terminator V3.1 Cycle Sequencing Kit . The purified sequencing products were finally resolved with capillary electrophoresis .DNA was extracted from the tissues and corresponding cell lines (Jed66_GB cell line passage 22 and Jed41_GB cell line passage 25) , and whole exomes were sequenced using Agiomix, UAE services. VCF files were annotated using the BaseSpace Variant Interpreter  (accessed on the 05/12/2021). Only those COSMIC variants that had damaging coding consequences were further assessed, as called by BaseSpace Variant Interpreter, or checked manually using PolyPhen-2 Wiki. They had a population frequency of less than 0.01 for all population sources. COSMIC variants detected in the tissues and corresponding cell lines were selected to enrich the tumorigenic and progressive genes. One critical exon variant in protocol . The priTo process in situ immunofluorescence, tissue sections were fixed and stained as previously described . For theSeveral drugs were used in this study. Taxol, a microtubule stabiliser ; cisplatin, a DNA cross-linker ; irinotecan, a DNA topoisomerase I inhibitor ; MCK8866, IRE1α inhibitor ; etoposide, DNA topoisomerase II inhibitor ; and temozolomide, DNA guanine and adenine methylation agent .2. On the next day, cells were treated for two hours with either cisplatin or etoposide, or for three days with either taxol, or irinotecan or MCK8866. 14 to 21 days following seeding, the clones were fixed with 4% PFA, stained with crystal violet and counted.For the clonogenic cytotoxic assay, cells were plated in 6-well plates at 1,000 and 2,000 cells per well for Jed66_GB and Jed41_GB, respectively. Cells were supplemented with DMEM-F12 and 10% FBS and left to adhere overnight at 37 °C with 5% CO50 values for temozolomide and irinotecan in order to use for growth inhibition assays, cells were plated in 96-well plates at 5 × 103 or 1 × 104 cells/well for Jed66_GB and Jed41_GB, respectively. For temozolomide, the concentrations used were 50, 100, 200, 400, 800, 1600, and 3200 µM for both cell lines. For irinotecan the concentrations 0.5, 1, 2, 4, 8, and 16 µM were used to treat Jed66_GB, while for Jed41_GB higher concentrations were required . After three days of drugs incubation, the cells were fixed with 4% PFA, stained with 1% crystal violet, and the absorbance was measured at 595 nm. All assays were performed in triplicate.To determine the IC4 cells/well and 4 × 104 cells/well for Jed66_GB, and Jed41_GB, respectively and were left overnight to attach in 400μL Transfection Media (TM) (DMEM-F12 media with 10% FBS and no antibiotics). The following day, cells were transfected with 0.6% or 1.0% of lipofectamine , or with 0.2% or 0.3% of Cy3-DsiRNA , or with 0.2% or 0.3% of the negative control . Cell death was at 80% using 1% lipofectamine concentration in initial experiments; therefore, the concentration of 0.6% lipofectamine was used for further AGR2 siRNA experiments.For basic transfection optimisation, cells were seeded in 8-well chamber slides at 2 × 10To optimise AGR2 repression using a single transfection, three siRNAs targeting different exon sequences were tested at a final concentration of 0.2% . The siRNA sequences were as follows: AGR2 exon 2A siRNA (5′-AGAUACCACAGUCAAACCUGGAGCCAAA-3′) , AGR2 exon 2B siRNA (5′-AAAGGACUCUCGACCCAAACUGCCCC-3′)  and AGR2 exon 5/6 siRNA (5′- CUGGUUUAUGAAACAACUGACAAACAC- 3′) . The cells were seeded as previously mentioned; then they were transfected, fixed with 4% PFA after 24/48 h of incubation and processed for immunofluorescence staining. For double transfections, cells were seeded as previously mentioned, transfected with control siRNA or AGR2 exon 2B siRNA, fixed with 4% PFA after two weeks and processed for immunofluorescence staining.To determine the siRNA-treatment-period that is appropriate to detect a possible early repression of AGR2, before any signs of cell death or reduction in cell densities were observed, cells were seeded and transfected with control siRNA or AGR2 exon 2B siRNA, as previously mentioned. The most appropriate post-transfection incubation periods were then determined to be eight hours for Jed66_GB cells, and 36 h for Jed41_GB. The fixation process and immunofluorescence staining were then carried out in the manner described previously.3 or 1 × 104 cells/well for Jed66_GB and Jed41_GB, respectively. Cells were either exposed to TM, or transfected with AGR2 exon 2B siRNA as mentioned above. After 24/48 h, the TM was removed, and either DMASO (1%), temozolomide (IC50 at 700 µM for Jed66_GB and 1000 µM for Jed41_GB) or irinotecan (IC50 at 2.05 µM for Jed66_GB and 100 µM for Jed41_GB) were added. After three days, the cells were fixed and stained using 1% crystal violet with 10% acetic acid, then the absorbance was measured at 595 nm. The combined transfection and drug treatments were also carried out in chamber slides in parallel to assess AGR2 expression via immunofluorescence staining.For combined transfections and drug treatments, cells were incubated in 96-well plates in 200μL of TM/well at 5 × 102 was counted using ImageJ. The average number of untreated cells per 3.9 mm2 was considered as a cell density of 100% and served to calculate the cell density percentage for the average number of treated cells per 3.9 mm2.To assess cell density, the number of nuclei per 3.9 mmTo assess AGR2 repression in individual cells that were immunofluorescence-co-stained for anti-AGR2 and anti-GRP78, images were analysed using ImageJ. Individual cells were selected using the polygon selection tool, and data for mean area intensities were recorded using the analyse, histogram and RGB tools. At least 100 cells were counted. P53 nuclear expression was assessed in at least 100 cells. All assays were performed in triplicates.2 test were used to assess for significant differences in the mean percentage of cell density, survival fractions, areas' intensities and the presence of multinucleated cells.The results were analysed using SPSS version 21.0. T-test, Z-test or ChiχIDH-damaging variants were detected. Two critically damaging variants, the missense variant p.Glu293Lys in the stanniocalcin-2 (STC2) gene detected in Jed66_GB and the homozygous missense variant p.Arg273Cys in TP53 detected in Jed41_GB, were conventionally sequenced, and the results concurred with those detected via whole exome sequencing . The sensitivity to cisplatin and MKC8866 for Jed66_GB and Jed41_GB were similar . The least effective applied drug was etoposide (IC50 14 µM for Jed66_GB and 29 μM for Jed41_GB). The overall responses to taxol, cisplatin or irinotecan were significantly higher in Jed66_GB than in Jed41_GB . Critically, the level of expression for AGR2 in both cell lines remained high in resistant surviving cells following the treatments with all drugs at IC50 concentrations   [TRAP1) [POLD1) [OTOP1) [TYK2) [ARID1B) [CD48) [USP18) [NCOR1) [NFE2L2) [KIF1A) [TP53 [LRP1B) [ADGRE5) [ATN1) [ATG2B) [MAZ) [WNK1) [UGT1A1) [UGT1A6) [Some studies have previously analysed the role of AGR2 or GRP78 in standard glioblastoma cell lines , 41. In BCR) , 44, TNF [TRAP1) –47, DNA  [POLD1) , otopetr [OTOP1) , tyrosin) [TYK2) , AT-rich[ARID1B) , CD48 mo) [CD48) , ubiquit [USP18) , nuclear [NCOR1) , NFE2 Li[NFE2L2) , and Kin [KIF1A) . For JedA) [TP53 , 44, 57, [LRP1B) , adhesio[ADGRE5) , atrophi) [ATN1) , autopha [ATG2B) , 62, MYCB) [MAZ) , 63, WNK) [WNK1) , 65, UDP[UGT1A1) , and UDP[UGT1A6) . Not sur[UGT1A6) , 15.Immunofluorescence results showed, for the first time, a clear subcellular co-localisation for AGR2 with GRP78 in glioblastoma in situ and in the corresponding cell lines. This is consistent with the notion that AGR2 is an interacting partner of GRP78 , 24. In CSCs are well identified in glioblastoma , 9, and The expression of AGR2 remained high in drug-resistant cells following treatments with a range of clinically applied drugs that utilize different modes of action –80. ThisShort and prolonged RNAi-mediated AGR2 exon 2B repression led to lower cell densities in both cell lines. Exon 2 covers nucleotides 66–211 and its transcript is thought to be present in the AGR2 full lengths, AGR2vC and AGR2vH isoforms . In thisKnocking down AGR2 using siRNA against AGR2 exon 2B in the primary cell lines had partially synergistic effects with the glioblastoma-associated drugs temozolomide and irinotecan. AGR2 knockout, in combination with other drugs, was previously shown to be effective in inhibiting the growth of different cell line models –88. To tP53 in Jed66_GB compared with mutated P53 in Jed41_GB. This is also consistent with the observations that Jed41_GB is more resistant to taxol, cisplatin and irinotecan compared with Jed66_GB. However, the higher capacity of Jed66_GB to proliferate could contribute to better overall recovery following treatment.How the repression of AGR2 could lead to the reduction of cell densities or cell death was partially clarified when observations for the earliest time points of repression were made for Jed66_GB and Jed41_GB . Both cell lines increased nuclear Caspase-3 activation following a slight reduction in AGR2, a feature seen previously in primary breast cancer cells . HoweverPLOD1 that are associated with nuclear integrity exist [p53, where the threshold of nuclear integrity is dependent on a functional P53, repression of AGR2 may interfere with P53, as previously shown, and cause multinucleation [P53, leukaemia NUP98 fusion partner 1 (LNP1) and Sad1 and UNC84 domain containing 2 (SUN2) [Second, early repression of AGR2 led to multinucleation only in Jed66_GB. This indicates that the pathway to induce apoptosis following AGR2 repression is cell line-dependent. How can the repression of AGR2 lead to apoptosis via multiple pathways? It was previously known that AGR2 can affect the presence of multiple molecules , 89, 90.ty exist , the repty exist , which ity exist . Alternacleation , 95. In 2 (SUN2) , 97, theIn conclusion, the data demonstrate that AGR2 and GRP78 are highly expressed in glioblastoma CSCs and drug-resistant cells in situ and in vitro. The repression of AGR2 exon 2B using siRNA resulted in the reduction of cell densities and was synergistically effective in decreasing cell densities of temozolomide- and irinotecan-treated Jed66_GB cells. The suppression of AGR2 influenced the presence of GRP78, possibly through navigating the UPR machinery. Early cell fate seemed to depend on the presence of wild-type P53 and can either lead to multinucleation followed by cell death or to delayed growth followed by attenuated cell death. Further work is critical to investigate the relationship between AGR2 and P53 and their impact on cell death following drug treatment in a larger cohort.Additional file 1: Figure S1. Histopathological classifications. Jed66_GB has malignant glial cells palisade around a central focus of necrosis and microvascular proliferations on the left and right sides . The tumour is positive for GFAP immunostaining (Power 100 X). Jed41_GB has numerous large bizarre multinucleated tumour cells on the right side and tumour necrosis on the left side . The tissue was GFAP positive (Power 100 X).Additional file 2: Figure S2. Biological characteristics of the glioblastoma primary cell lines Jed66_GB and Jed41_GB. A) Immunofluorescence images showing i) the expression of AGR2, ii) Nuclear localisation of AGR2. AGR2 is shown in red and DAPI in blue. Images were taken at 20x. B) A barograph displaying the doubling time for each cell line. Error bars represent errors between counts for three independent experiments. C) A line graph showing the clonogenic capacity for Jed66_GB cells (Passages 17-23) and Jed41_GB cells (Passages 8–14). Error bars represent errors between counts for three independent experiments. D) Immunofluorescence images showing the expression of Ki67 (red) or BMI (green) in both primary cell lines. Images were taken at 20x. E) A barograph showing the average percentage of cells positive for Ki67 or BMI. The error bars represent errors between counts for three independent experiments. F) Images of cells that underwent a scratch assay taken on day 0 before and after scratch and at days 3 and 4 after the gap was filled. Images were taken at 5x magnification.Additional file 3: Figure S3. Sequencing variants in the primary cell lines and corresponding tissues. A) Conventional sequencing for two critically damaging variants present in either cell line with its corresponding tissue, STC2 in Jed66_GB and TP53 in Jed41_GB. B) Only non-damaging and common variants for AGR2 or GRP78 were detected in either cell line. C) Prominent functions likely to be affected for both cell lines, as per related TC rare damaging COSMIC variants. Prominent functions are coloured in grey, genes affected in Jed66_GB are coloured in blue and those identified in Jed41_GB are coloured in green.Additional file 4: Figure S4. Further UPR markers co-stained with CSC markers in the primary cell lines. A) Immunofluorescence images for AGR2 (red) co-stained with CD133 (green), and GRP78 (green) co-stained with GFAP (red), or with OLIG2 (Red). DAPI is shown in blue. Images were taken at 20x magnification. B) Magnified images to show detail intracellular localization of the respective proteins. C) A barograph showing the percentages of double-positive cells for the aforementioned markers in the primary cell lines. Error bars represent errors between counts for three independent experiments.Additional file 5: Figure S5. siRNA optimisation for the primary cell lines. A) Barographs showing the survival fractions for the Cy3 transfection control and siRNA negative control at optimum concentrations of lipofectamine. Error bars represent errors between counts for three independent experiments. B) Immunofluorescence images showing the Cy3-positive cells are shown in red, and DAPI is shown in blue. Images were taken at 20x magnification. C) A barograph showing the percentages of Cy3-positive cells. Error bars represent errors between counts for three independent experiments. D) Immunofluorescence images showing cell densities following transfections, and the images were taken at 5x magnification. Cy3-positive cells are shown in red, and DAPI is shown in blue.Additional file 6: Table S1. Rare damaging COSMIC variants detected in the tissue and cell lines for Jed66_GB.Additional file 7: Table S2. Rare damaging COSMIC variants detected in the tissue and cell lines for Jed41_GB.Additional file 8: Table S3. It is likely affect prominent functions in the studied cell lines. Genes with rare damaging COSMIC variants were detected in the tissue and corresponding cell line for each patient and organized by prominent functions  for both Jed66_GB and Jed41_GB. Only variants with a possible/probable damaging PolyPhen effect were included, as per data annotated by BaseSpace or as detected manually using PolyPhen-2 Wiki.


Lenvatinib is a multi-kinase inhibitor approved as a first-line treatment for patients with unresectable advanced hepatocellular carcinoma (HCC). However, its response rate is unsatisfactory, primarily due to the acquisition of resistance, which limits its clinical significance for treating patients with HCC. Recent evidence suggests that epidermal growth factor receptor (EGFR) activation can trigger Lenvatinib-resistance; and is considered an important therapeutic target in HCC. Curcumin, one of the most studied naturally occurring botanicals with robust anti-cancer activity, is also reported to be a potent tyrosine kinase inhibitor. In this study, we hypothesized that the anti-EGFR potential of Curcumin might help overcome Lenvatinib resistance in HCC. We established two Lenvatinib-resistant cells and discovered that a combination of Curcumin and Lenvatinib exhibited a synergistic anti-tumor efficacy in the resistant HCC cell lines. In line with previous reports, Lenvatinib-resistant cell lines revealed significant activation of the EGFR, and genomewide transcriptomic profiling analysis identified that the PI3K-AKT pathway was associated with Lenvatinib resistance. The combination treatment with Curcumin and Lenvatinib dramatically suppressed gene and protein expression of the EGFR-PI3K-AKT pathway, suggesting Curcumin overcomes Lenvatinib resistance via inhibition of EGFR. We further validated these findings in tumor spheroids derived from resistant cell lines. In conclusion, we, for the first time, report that Curcumin reverses Lenvatinib resistance in HCC, and that their combination has clinical application potential for adjunctive treatment in HCC. Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and the third leading cause of cancer-related deaths . PatientHowever, the overall response rate of Lenvatinib is only ~24% , and eveSeveral naturally occurring botanical compounds have recently gained more attention from researchers and clinicians because of their inherent multi-targeted and safer therapeutic efficacy compared to conventional chemotherapy and targeted drugs ,26,27,282 atmosphere. Curcumin was generously provided by EuroPharma USA, Green Bay, WI, USA, and Lenvatinib was purchased from Sigma-Aldrich, St. Louis, MO, USA.Five human HCC cell lines  were examined in this study. SNU449 was obtained from the American Type Culture Collection . Huh-7 and PLC-PRF-5 (PLC) were obtained from the RIKEN BioResource Center Cell Bank . Dr. Ke, Department of Diabetes Complications and Metabolism, Beckman Research Institute of City of Hope, kindly provided us with SNU398 and Sk-Hep-1 cell lines. All cell lines were cultured in Dulbecco’s modified Eagle’s medium  supplemented with 10% fetal bovine serum  and 1% penicillin-streptomycin. All cells were maintained in a 37 °C incubator with a 5% humidified COFor these assays, five thousand cells were seeded into 96-well plates. After overnight incubation for cell adherence to the plates, all cell lines were treated with Lenvatinib, Curcumin, or their combination using different concentrations for 48 h. Following completion of the treatments, MTT assays were performed using the Cell Counting Kit-8  according to the manufacturer’s instructions. The absorbance of the final colored product was analyzed at 450 nm using a plate analyzer . To evaluate the effects of the drug combination, isobolograms were generated using ComboSyn software , and the combination index (CI) < 1.0 was considered a synergistic effect.Lenvatinib-resistant cells were developed from Huh-7 and PLC cell lines. Parental cells were continuously exposed to a Lenvatinib-supplemented medium. Surviving cell clones were transferred to a medium with a higher concentration of Lenvatinib, and the concentration of the drug was increased by 0.5 μM weekly for 10 months. Finally, resistant cells could stably grow in a 20 μM Lenvatinib-supplemented medium and were selected for final experimentation.4 cells were seeded into the Matrigel invasion chambers  with 8.0 µm pore-sized PET membranes. After another two days of the invasion, invaded cells were fixed and stained by Diff-Quick and counted.All HCC cell lines were seeded in 6-well plates and treated with drugs for 48 h. After treatment, 2.5 × 10One thousand cells were seeded in 6-well plates. After 3–5 days of incubation, cells were treated with individual drugs or their combination for 48 h. Following the completion of the treatment period, cells were cultured in a standard culture medium for another week and harvested. The cells were fixed in the culture plates with 100% methanol and stained with 1% crystal violet. Colony formation rates were quantified as the percentages of the stained area by ImageJ 1.53 software , as previously reported .Apoptosis and oxidative stress assays were performed following the treatment of cancer cell lines with each compound for 16 h. Cell apoptosis and oxidase stress levels were examined by the Muse Cell Analyzer  using the Annexin V and Dead Cell Kit and the Oxidative Stress Kit, per the manufacturer’s instructions.The method for these assays was previously described ,39. Briep < 0.05 and a Log2FC > 1.0. Subsequently, enrichment analysis of the KEGG pathways was carried out using the DAVID bioinformatic database. The top 50 enrichment pathways were ranked by the number of included genes. In addition, we also examined the prognostic impact of the EGFR pathway in HCC using the GSE10141 dataset.To discover significantly and differentially expressed genes in Lenvatinib-resistant vs. parental cell lines, we analyzed GSE211850, a publicly available dataset comparing gene expression profiling between the parental and Lenvatinib-resistant Huh-7 cell lines. Significantly upregulated genes were defined if they had a Total RNA was extracted from cancer cells and spheroids treated with Lenvatinib, Curcumin, or their combination for 16 h. cDNA synthesis was performed using a Reverse Transcription Kit . The qRT-PCR assays were performed using a SensiFAST SYBR Lo-ROX Kit  and the QuantStudio 6/7 Flex RT-PCR System . GAPDH was used as the housekeeping gene, and gene expression changes were calculated by the delta Ct method. The primer sequences used in this study are described in Western blotting was performed as previously reported ,39. Cellp < 0.05 was considered to be statistically significant. The overall survival analysis curves were created using the Kaplan-Meier method, and the differences in patient survival were analyzed by the log-rank test. All analyses were conducted using JMP 8.0.1 .All assays were performed in triplicate, and data were described as the mean ± standard deviation. Statistical comparisons were made using the Wilcoxon test (for 2 groups) or the Tukey-Kramer method (for 3 or more groups), and At first, we examined the sensitivity of each HCC cell to Lenvatinib. Cell viability assays following treatment with Lenvatinib (0–100 μM) revealed that Huh-7 cells ; <10 μM) were sensitive to Lenvatinib, and SNU398 cells , Sk-Hep-1 , SNU449 , and PLC  were relatively insensitive to Lenvatinib A. To detWe next evaluated whether Curcumin could exert anti-proliferative effects in these three cell lines B. CurcumThe primary aim of our study was to determine whether Curcumin could help overcome Lenvatinib resistance in HCC. To achieve this goal, we established two Lenvatinib-resistant cell lines, one from Huh-7, an endogenously Lenvatinib-sensitive cell line, and the other from PLC, the most Lenvatinib-insensitive cell line. Following the selection of resistant clones over several months, we noticed that resistant Huh-7 cells (rHuh-7) were more than 20 times more resistant than parental Huh-7 . Similarly, resistant PLC cell lines (rPLC) were more than two times more resistant than the parental PLC cells  and rPLC  compared to control and Lenvatinib treatment  and rPLC cells   B. In lin < 0.12) .Next, we examined the effect of Curcumin and Lenvatinib on the intracellular accumulation of reactive oxygen species (ROS) and apoptosis in HCC cells. The baseline percentages for the ROS-positive cell population were 3.9% (rHuh-7) and 9.9% rPLC; A. In botp < 0.01; Lenvatinib vs. combination, p < 0.01; Curcumin vs. combination, p < 0.01) and rPLC cells  and PLC (p < 0.01) cells, suggesting that EGFR expression might not be associated with the endogenous sensitivity to Lenvatinib  and 1.23 times higher in rPLC (p < 0.01) compared to the parental cell lines  in rHuh-7 compared to parental cells. The KEGG pathway analysis for these upregulated genes is depicted in To identify specific EGFR downstream pathways associated with Lenvatinib resistance, we performed genomewide expression profiling analysis between parental and resistant Huh-7 cells (GSE211850). There were 2522 significantly upregulated genes  and rPLC cells  and rPLC cell lines , compared to Curcumin treatment alone  and 2.3  in rHuh-7 cells, and from 15.0 (control) to 5.7  and 2.3  in rPLC cell line  and rPLC cells , we developed cancer spheroids from two Lenvatinib-resistant cells. Following the completion of treatments, the number and size of spheroids were evaluated. The Curcumin treatment and Lenvatinib significantly reduced spheroids’ number and size A. The nuWe also evaluated the expression of CD44 and CD133, which are the cancer stemness markers in many cancers, including HCC . InteresHepatocellular carcinoma (HCC) is the most common primary liver malignancy and is known to be a highly malignant tumor type due to its poor prognosis . UnresecCurcumin is a naturally-occurring botanical derived from turmeric and is one of the most widely studied, safe and inexpensive adjunctive treatment approaches used in various human cancers ,29,30,31According to our hypothesis, Curcumin enhanced the anti-tumor effects of Lenvatinib in both endogenously sensitive and relatively insensitive HCC cell lines by inhibiting cell proliferation, invasion, and colony formation ability. Moreover, we noted that Curcumin could reverse acquired resistance to Lenvatinib by suppressing the EGFR-PI3K-AKT signaling cascade D. In thiOur findings can potentially provide a new adjunctive therapeutic strategy in HCC. However, there were a few potential limitations to our study that we would like to acknowledge. First, we revealed that EGFR inhibition by Curcumin could overcome the acquired resistance of Lenvatinib using genomewide analysis and following experiments. However, we have not investigated how Curcumin could enhance the anti-tumor effect of Lenvatinib on endogenously insensitive cells. Secondly, we examined the effects of combination treatment in cancer cells and cancer spheroids but not in pre-clinical animal models of HCC. While this might provide additional insight, unfortunately, no robust animal models capture human HCC. In addition, although Curcumin is a safe compound, we did not directly evaluate any potential toxicity when combined with Lenvatinib. In the future, validation studies for the effect and toxicity of this combination in such animal experimental models or clinical studies might shed additional insight, given the safety profile of Curcumin with other chemotherapies and targeted drugs reported to date, the likelihood of any adverse combinatorial effects are highly unlikely.In conclusion, we provide the first evidence that Curcumin could reverse Lenvatinib resistance in HCC cells via suppression of EGFR and its downstream targets, which can offer a novel adjunctive, safe and efficacious therapeutic strategy in HCC.


BrPQ5) was selected for a full panel five-dose in vitro assay by the NCI’s Development Therapeutic Program (DTP) division to determine GI50, TGI, and LC50 parameters. The brominated PQ analog (BrPQ5) displayed remarkable activity against most tested cell lines, with GI50 values ranging from 1.55 to 4.41 µM. The designed molecules  obeyed drug-likeness rules, displayed a favorable predictive Absorption, Distribution, Metabolism, and Excretion (ADME) profile, and an in silico simulation predicted a possible BrPQ5 interaction with proteasome catalytic subunits. Furthermore, the in vitro cytotoxic activity of BrPQ5 was assessed, and IC50 values for U-251 glioma, MCF-7 and MDA-MB-231 breast cancers, DU145 prostate cancer, HCT-116 colon cancer, and VHF93 fibroblast cell lines were evaluated using an MTT assay. MCF-7 was the most affected cell line, and the effects of BrPQ5 on cell proliferation, cell cycle, oxidative stress, apoptosis/necrosis induction, and proteasome activity were further investigated in MCF-7 cells. The in vitro assay results showed that BrPQ5 caused cytotoxicity in MCF-7 breast cancer cells via cell cycle arrest and oxidative stress induction. However, BrPQ5 did not inhibit the catalytic activity of the proteasome. These results provide valuable insights for further discovery of novel antiproliferative agents.Plastoquinone analogs are privileged structures among the known antiproliferative natural product-based compound families. Exploiting one of these analogs as a lead structure, we report the investigation of the brominated PQ analogs (BrPQ) in collaboration with the National Cancer Institute of Bethesda within the Developmental Therapeutics Program (DTP). These analogs exhibited growth inhibition in the micromolar range across leukemia, non-small cell lung cancer , colon cancer , melanoma (LOX IMVI), and ovarian cancer (OVCAR-4) cell lines. One brominated PQ analog ( Breast cancer is a malignant tumor affecting areas in or around the breast tissue . There aBrPQ5. The cytotoxic activity of BrPQ5 was evaluated against U-251 glioma, MCF-7 and MDA-MB-231 breast cancers, DU145 prostate cancer, and HCT-116 colon cancer cell lines. Furthermore, the IC50 values were calculated. These results were compared with VHF93 fibroblast cells to determine cancer selectivity. To better elucidate the mechanisms underlying the cytotoxic activity of BrPQ5 against the most sensitive cell line, MCF-7, the cell proliferation was evaluated through its colony-forming ability. Moreover, we investigated the effect of BrPQ5 on apoptosis induction and cell cycle profile in MCF7 cells. The role of apoptotic/necrotic cell death and cell cycle changes on the decrease in cell proliferation was investigated. An excessive accumulation of reactive oxygen species (ROS) in cells can lead to oxidative stress-induced cellular damage [BrPQ5 as the ligand to study its binding mode, and proteasome activity was measured in MCF7 cells to confirm its inhibitory activity.Aminoquinones continue to attract significant attention as drug candidates because of their broad biological activity profiles and easy accessibility ,10,11. Mr damage . Thus, tDrugs such as mitomycin C, mitoxantrone, and doxorubicin and some of the biologically active synthetic molecules contain 1,4-quinone moiety. Our strategy was inspired by a natural 2,3-dimethyl-1,4-benzoquinone structure with a side chain of nine isoprenyl groups named PQ-A or PQ-9 , as wellBrPQ1 (NCI: D-825199/1), BrPQ2 (NCI: D-827603/1), BrPQ3 (NCI: D-827604/1), BrPQ4 (NCI: D-827602/1), BrPQ5 (NCI: D-825197/1), BrPQ6 (NCI: D-825198/1), BrPQ7 (NCI: D-827608/1), BrPQ8 (NCI: D-827605/1), BrPQ9 (NCI: D-827606/1), and BrPQ10 (NCI: D-827607/1) were tested by the NCI for an in vitro disease-oriented human cell screening panel assay. The structures of the BrPQ analogs are shown in BrPQ2, BrPQ5, BrPQ6, BrPQ9, and BrPQ10) exhibited broad-spectrum potent inhibitory effects on some leukemia cell lines. Furthermore, three BrPQ analogs  showed strong antiproliferative activity against breast cancer cell lines. Additionally, BrPQ5 was selected for a five-dose level screening for further in vitro evaluation. Details of the antiproliferative activity results at one-dose and five-dose analyses are provided separately under two subtitles.A preliminary antiproliferative in vitro assay  was performed under the Developmental Therapeutics Program (DTP) at the National Cancer Institute (NCI), Bethesda, to explore the cytotoxic activity of the BrPQ analogs against a panel of 60 human cancer cell lines, which included nine tumor subpanels, namely leukemia, lung, colon, CNS, melanoma, ovarian, renal, prostate, and breast cancer cell lines . Before BrPQ3, BrPQ4, BrPQ5, and BrPQ7) displayed remarkable antiproliferative activity against the colon HCT-116 cell line, with a growth inhibition of 64.64, 79.99, 85.93, and 65.27%, respectively. BrPQ3, BrPQ4, and BrPQ10 showed the best GI% values of 70.14, 93.36, and 79.67%, respectively, in the subpanel cell line of the melanoma cancer panel (LOX IMVI). Surprisingly, among the brominated PQ analogs, only one analog (BrPQ8) displayed maximum sensitivity against the ovarian OVCAR-4 cell line with a growth inhibition percentage of 85.94%. Moreover, two analogs (BrPQ4 and BrPQ7) exhibited excellent to moderate antiproliferative activity in some subpanel cell lines of the non-small cell lung cancer panel . BrPQ7 was the most potent analog with above 90% GI% values for the colon cancer line HOP-92. The bromi-nated PQ analogs showed a significant antiproliferative effect profile against leukemia and breast cancer models. BrPQ2 displayed maximum sensitivity toward K-562 and CCRF-CEM cancer cell lines of leukemia with 83.46 and 97.97% of GI%, respectively. It also showed promising activity against the T-47D (95.53%) breast cancer cell line. Three BrPQ analogs  showed a significant growth inhibition against K-562 with 99.57, 96.57, and 95.54%, respectively. The most potent BrPQ analog was the BrPQ5 against the SR cell line of leukemia with 97.94% of GI%. BrPQ6 exhibited the highest activity against CCRF-CEM  and MOLT-4  cell lines of the leukemia panel. On the other hand, the most endowed BrPQ analog (BrPQ7) displayed potency against the MDA-MB-468  breast cancer cell line.The observed one-dose results of each tested BrPQ analog were reported as a function of the growth percentage (GP) of treated cells. Their one-dose mean graphs and table are presented in the BrPQ5, NCI: D-825197/1) satisfied the pre-determined threshold inhibition criteria in a minimum number of cell lines and was advanced to the five-dose antiproliferative screening against the 60 cell panel at five-dose concentrations and 10-fold dilutions of five different concentrations (ranging from 0.01 µM to 100 µM). The five-dose mean graphs are presented in the 50 , TGI , and LC50 , presented in 50 values ranging from 1.55 to 4.41 µM. An excellent potency was seen for the selected BrPQ analog (BrPQ5) against the breast cancer cell lines MCF7, MDA-MB-231/ATCC, T-47D, and MDA-MB-468. Additionally, the analog BrPQ5 showed high activity with GI50 values ranging from 2.21 to 3.21 µM. It also displayed a pronounced activity against other cancer cell lines from different tumor subpanels. Moreover, this analog possessed promising TGI values ranging from 3.16 to 4.81 µM against some breast cancer cell lines. Additionally, significant TGI values ranging from 5.00 to 10.00 µM were noticed with some cancer cell lines. Concerning the lethality , a few panel cancer cell lines showed values exceeding 100 µM. Finally, it displayed potent lethal action against some cancer cell lines . All the five-dose–response curves of the BrPQ analog (BrPQ5) against the panel of 60 human cancer cell lines are presented in The brominated PQ analog (BrPQ5) were predicted using the free web tool SwissADME  developed by the Swiss Institute of Bioinformatics [BrPQ5) displayed a good lipophilic character with a consensus Log Po/w value of 2.75 and moderate solubility in water. The pink area in the bioavailability radar chart (in the Rot ≤ 10 (number of rotatable bonds), and TPSA < 140 Å2 . The BrPQ analog (BrPQ5) carries all the required properties without violating Lipinski’s rule of five. As a biologically active molecule containing less than or equal to five hydrogen bond donors and less than 10 hydrogen bond acceptors, BrPQ5 is likely to have rich absorption and cellular permeation.High oral bioavailability is a key factor that is essential for introducing biologically active molecules into the therapeutic market. Oral bioavailability can be predicted by examining molecular features, i.e., low polar surface area or total hydrogen bonding, reduced molecular flexibility, and good intestinal absorption ,37. All ormatics , and aret in the  represenBrPQ5) showed high gastrointestinal (GI) absorption according to the white of the BOILED-Egg, illustrated in the BrPQ5), as indicated by the BOILED-Egg graph, was predicted to passively permeate through the blood–brain barrier (BBB) according to the yolk portion of the BOILED-Egg chart. Additionally, the BrPQ analog (BrPQ5) was unsuitable as a substrate for P-glycoprotein (P-gp) according to the BOILED-Egg graph. The observed results from an in silico ADME study indicate the potential pharmacological use of the BrPQ analog (BrPQ5) that would be a suitable template for further studies to determine the clinical applications in specific leukemia types.The calculation method for SwissADME is an accurate predictive model  developed for lead optimization by calculating the lipophilicity and polarity of small molecules . The BrPBrPQ5 suggested that it blocks the cell cycle at the G0/G1 phase with the induction of the S phase and an increase in oxidative stress. Proteasome inhibitors show a few characteristic features. Additionally, BrPQ5 shares structural similarity with known proteasome inhibitors of natural origin, shikonin and celastrol, as they also have a quinone pharmacophore (BrPQ5 with human 20S proteasome beta-1 (caspase-like), beta-2 (trypsin-like), and beta-5 (chymotrypsin-like) subunits. The X-ray crystal structure for human 20S proteasome in complex with the proteasome inhibitor carfilzomib (PDB: 4R67) was used for the simulation. BrPQ5 was found to interact well with all the three subunits, and the interactions are discussed below.The analysis of cell cycle and oxidative stress in MCF-7 breast cancer cell lines after administering acophore . This prBrPQ5 with the beta5 subunit (chymotrypsin-like) of the human 20S proteasomeInteraction of : BrPQ5 appeared to occupy the S1 subpocket that accommodates small hydrophobic residues such as the Ala, Val, or Tyr of the substrate. BrPQ5 showed three H-bonding interactions. The amino hydrogen of BrPQ5 interacted with the side-chain hydroxy oxygen of Thr21. The quinone oxygen with a side-chain hydroxy hydrogen interacted with the amino hydrogen of Thr1. The quinone ring of BrPQ5 interacted with Thr1, which is further stabilized by the π–π interaction of the quinone ring with Tyr169. The phenyl group of BrPQ5 showed hydrophobic interactions with Gly47, Gly48, Ala49, and Ala50. BrPQ5.BrPQ5 with the beta-2 subunit (trypsin-like) of the human 20S proteasomeInteraction of : The acidic S1 subpocket, meant for accommodating basic P1 amino acids in the substrate, was found to interact well with BrPQ5. The quinone oxygen of BrPQ5 showed an H-bonding interaction with the backbone NH of Glu2, while methoxy oxygen displayed an H-bonding interaction with the backbone NH of Ala22. A π–π interaction was observed. A hydrophobic interaction was observed with Met1, Val20, Ala21, Val47, Gly48, Glu49, and Asn101. A 2D interaction plot illustrating the complex of the beta-2 subunit with BrPQ5 is shown in BrPQ5 with the beta-1 subunit (caspase-like) of the human 20S proteasomeInteraction of : BrPQ5 occupied the basic S1 subpocket meant for accommodating acidic amino acids. The quinone oxygen of BrPQ5 formed an H-bonding interaction with the side-chain amide NH of Asn8, while amino NH formed an H-bonding interaction with the side-chain carbonyl oxygen of Glu31. Both the quinone ring and phenyl ring of BrPQ5 exhibited a π–π interaction with Phe2 and His58, respectively. The interaction of the beta-1 subunit with BrPQ5 is shown as a 2D interaction plot in BrPQ5, U-251 human glioblastoma, MCF-7 and MDA-MB-231 human breast cancers, DU-145 human prostate cancer, and HCT-116 human colon cancer cell lines were used. These cell lines were chosen for in vitro studies according to NCI’s five dose–response analysis protocols. The VHF93 human fibroblast cell line was used as a noncancerous cell line to determine the specific anticancer activity of BrPQ5. As a positive control, doxorubicin HCl (DOXO) was used, containing the 1,4-quinone moiety. It is widely used to treat several cancer types [BrPQ5 showed cytotoxic activity in all cancer cell lines (50) values were generated using the inhibitor-normalized response variable slope function in GraphPad Prism 7 software. The lowest activity was against the U-251 human glioblastoma cell line, and the IC50 value could not be determined. DOXO had a similar cytotoxic profile with BrPQ5 against the U-251 human glioblastoma cell line  for further studies.termined F. These BrPQ5 on MCF-7 cell proliferation was assessed using a colony formation assay  production and scavenging. Excessive ROS production triggers se- veral structural and molecular modifications and causes a cytotoxic effect . Disruptytometry . As showBrPQ5 was investigated for its necrotic and apoptotic effects using flow cytometry. Unexpectedly, BrPQ5 did not induce apoptosis, while a significant induction in the necrotic cell percentage was observed only with the highest concentration (25 μM) tested  tested . In contBrPQ5 was the highest tested concentration, which was lower than the IC50 value in MCF7 cells. Supportively, as can be seen in cytotoxicity data, 5 and 10 µM BrPQ5 caused similar cytotoxic activity, while cytotoxicity increased with 25 µM BrPQ5. Also, these results were similar to the cell cycle and apoptosis/necrosis assay results. However, BrPQ5 modulated ROS production in a dose-independent manner and caused significant ROS production at 5 µM, suggesting its ability to induce oxidative stress in low concentrations. It is known that cancer cells can adapt themselves to low levels of ROS to continue tumor development, and only a powerful ROS induction can cause cell effective cell damage [BrPQ5 treatment may be responsible for the antiproliferative effect in MCF7 cells. The changes in the cell cycle and cell necrosis with increased concentrations of BrPQ5 contri-buted to the dose-dependent antiproliferative effects in MCF7 cells.In summary, 25 µM l damage . Thus, iBrPQ5’s interaction with proteasome catalytic subunits, we focused on further investigating the BrPQ5 effects on the catalytic activity of the proteasome. Especially, the β5 catalytic subunit of the proteasome is the main target for cancer treatment, and there are several clinically used proteasome inhibitors on the market, such as bortezomib, carfilzomib, and ixazomib [BrPQ5 and DOXO did not inhibit the proteasome activity, while 100 nM carfilzomib treatment caused significant proteasome inhibition  functionalized in amino phenyl moiety were resynthesized and evaluated for their antiproliferative effects in terms of their inhibition efficiency. The preliminary in vitro antiproliferative activities of all BrPQ analogs against the full NCI 60 cell line panel was determined by NCI at a 10 μM concentration. The in vitro preliminary antiproliferative evaluation revealed that the BrPQ analogs with alkoxy substituent(s) in the amino phenyl moiety have maximum sensitivity toward many cancer cell lines, particularly CCRF-CEM, HL-60(TB), K-562, MOLT-4, and SR leukemia cell lines, as well as breast cancer cell lines. BrPQ5 was the most potent against leukemia and breast cancer cell lines and was selected for five-dose NCI screening. Based on this preliminary one-dose and five-dose antiproliferative screening, further studies are required to provide more insights into the biological mechanism of action. Thus, in vitro studies were performed with different cancer cell models. The findings from these analyses hinted at the promising anticancer activity of BrPQ5 against the MCF-7 breast cancer cell line with the absence of any significant cytotoxicity against noncancerous VHF93 human fibroblast cells. Further studies were performed with BrPQ5 on MCF-7 cells to compare it with DOXO, a well-known chemotherapeutic drug. BrPQ5 treatment caused a strong oxidative stress induction with all tested concentrations and caused dose-dependent cytotoxic activity and the inhibition of cell proliferation in MCF7 cells. Oxidative stress induction is accompanied by cell cycle arrest and cellular necrosis in the highest concentration. Accordingly, these were the key pathways eliciting the anticancer activity of BrPQ5 in the MCF-7 cells. Assertively, these effects were similar to DOXO, which highlights the therapeutic potential of BrPQ5 in the treatment of breast cancer. BrPQ5 did not significantly inhibit the catalytic activity of the proteasome, and the proteasomal pathway did not play a role in the anticancer activity of BrPQ5 in the MCF-7 cells as suggested by in silico studies. The peptidomimetic inhibitors such as carfilzomib and ONX-0914 tend to occupy all four subpockets (S1–S4) meant for accommodating P1–P4 residues. In contrast, bortezomib and IPSI-001 occupied three (S1–S3) and two (S1 and S2) subpockets, respectively [BrPQ5, when compared to reported inhibitors, is quite small and could interact only with residues lining the S1 subpocket in all three cases . Irrespective of the nature of the pocket, BrPQ5 has shown favorable interactions in all three subunits. However, it appears that these interactions are insufficient to retain this relatively small molecule in the active site in the absence of no interacting pharmacophoric features with other subpockets. This may be why these compounds fail to show any significant inhibition in the proteasome inhibition assay. Extending the molecular architecture with minimal pharmacophoric features to interact with the S2 subpocket may provide us with a suitable candidate. However, favorable in silico ADME predictions in terms of drug-likeness, oral bioavailability, and pharmacokinetic parameters suggested that the brominated BrPQ analogs could serve as promising hit and/or lead analogs for the discovery of new compounds with more effective proteasome inhibiting activities for future studies. In our future studies, we plan to further design and synthesize similar structures. More efforts are currently underway in our laboratory to generate new targeted libraries.Herein, the brominated PQ analogs  Graphics, 7.7 GB Memory, and 1 TB disk capacity. Programs and software were installed on Ubuntu 20.04.3 LTS, 64-bit, 3.36.8 version, and X11 windowing system. The software and webserver used for the simulation and analysis included ChemDraw 19.1, UCSF Chimera, MGLTools-1.5.7, Autodock-4.2, LigPlot+, and pdb2pqr server.The molecules investigated within this research have been synthesized by our group ,28. MoleThree different series of the brominated PQ analogs were submitted to the National Cancer Institute (NCI), Bethesda, USA. As per the standard protocol of NCI, all compounds were evaluated for their antiproliferative activity at a single-dose assay (10 µM concentration in DMSO) on a panel of 60 cancer cell lines derived from leukemia, non-small cell lung, colon, CNS, melanoma, ovarian, renal, prostate, and breast cancer as per protocol. Tested compounds were added to the microtiter culture plates, followed by incubation for 48 h at 37 °C. Sulforhodamine B (SRB), a protein-binding dye, was used for endpoint determination. The percentage growth of the treated cells was determined and compared to the untreated control cells, and the results of each tested compound were reported. Data from the one-dose experiments pertain to the percentage growth at 10 μM ,35,53.BrPQ5) was then elevated by DTP-NCI for a higher testing level to determine three dose–response parameters  for each cell line after establishing a dose–response curve from five different concentrations of 0.01, 0.1, 1, 10, and 100 µM for BrPQ5. The detailed procedure for the latter assay had been elaborated earlier [Serial 5 × 10-fold dilutions from an initial DMSO stock solution were performed before incubation at each concentration. The most promising BrPQ analog  were dissolved in DMSO. DOXO was used as a reference compound to compare the effects of BrPQ5. For all assays, 0.5% DMSO concentration was not exceeded for cell treatments, and the control group was treated with 0.5% DMSO.U-251 human glioblastoma, MCF-7, MDA-MB-231 human breast cancers, DU-145 human prostate cancer, HCT-116 human colon cancer, and VHF93 human fibroblast cell lines were obtained from the American Type Culture Collection. U-251, MDA-MB-231, DU-145, HCT-116, and VHF93 cells were grown in DMEM (Gibco), and MCF-7 cells were cultured in DMEM:F12 (Gibco). The culture medium was supplemented with 10% heat-inactivated fetal bovine serum (Gibco), 10 U/mL penicillin, and 100 μg/mL streptomycin (Gibco) at 37 °C in a 5% CO4 cells per well were seeded in 96 well plates and incubated overnight. The cells were then treated with increasing concentrations of compounds  for 24 h. After the treatment, the medium was replaced with fresh media containing 1 mg/mL MTT dye. The cells were incubated for an additional 3 h for the formation of formazan by mitochondrial succinic dehydrogenase. Subsequently, the medium was removed, and the formazan crystals were dissolved in DMSO. The absorbance value of the dye was measured at 570 nm with a microplate reader . The IC50 values (compound concentrations that cause the 50% reduction in the cell viability) were calculated using GraphPad Prism 7 Software.Cell viability was assessed using the MTT assay (BioMatik). For this purpose, 1 × 10BrPQ5 on cell proliferation was assessed using a colony formation assay. Briefly, 1500 MCF-7 cells per well were seeded in 6-well plates and incubated overnight. The MCF-7 cells were treated with 5, 10, 25 μM BrPQ5, and 25 μM DOXO along with the control for 24 h. Then, the wells were washed with PBS, and the cells were grown in the fresh medium for 10 days. After the incubation period, the medium was removed, and the cells were fixed with cold methanol for 5 min. The cells were dyed with 0.5% crystal violet (10% methanol) for 20 min. Then, the dye was discarded, and the wells were washed with distilled water until the water became colorless. The plates were air-dried, and the wells were photographed under natural light. The colonies were manually counted from the photographs.The effect of BrPQ5 on oxidative stress was analyzed with (5-(and-6)-chloromethyl-2′,7′-dichlorodihydrofluorescein diacetate (H2DCFDA)  staining. Briefly, 3 × 105 MCF-7 cells per well were seeded in 6-well plates and incubated overnight. The MCF-7 cells were treated with 5, 10, and 25 μM BrPQ5 along with the control for 24 h. 25 μM DOXO and 100 μM H2O2 were used as positive controls. Subsequently, the cells were collected by trypsinization, and 20 μM of H2DCFDA dye was added to the cell suspension. The cells were incubated for 30 min and centrifuged at 500× g for 5 min. The supernatant was discarded, and the cells were suspended in PBS. The changes in oxidative stress with the treatments were analyzed by flow cytometry .The effect of BrPQ5 on cell cycle arrest was evaluated by the Muse Cell Cycle Kit (Millipore) according to the manufacturer’s protocol. The MCF-7 cells were treated with 5, 10, and 25 μM BrPQ5 and 25 μM DOXO along with the control for 24 h. The cells were collected by trypsinization and fixed in ice-cold 70% ethanol for 3 h. Subsequently, the cells were collected by 300× g centrifugation for 5 min. The cell pellet was suspended in 200 μL assay buffer and incubated for 30 min in the dark. The differences in the cell cycle stages  were analyzed by flow cytometry (BD Biosciences).The effect of BrPQ5 and 25 μM DOXO along with the control for 24 h. The cells were collected by 300× g centrifugation after trypsinization. The cells were resuspended in binding buffer and incubated with Annexin V-FITC and propidium iodide (PI) for 15 min at room temperature in the dark. The cells were centrifuged at 300× g for 5 min and resuspended in the binding buffer. The flow cytometric analysis was carried out immediately by BD Bioscience flow cytometry, and the percentages of apoptotic and necrotic cells were calculated using BD Bioscience software.The apoptotic and necrotic cell rate was analyzed with the Annexin V-FITC Apoptosis Detection Kit (Millipore) according to the manufacturer’s protocol. For the assay, the MCF-7 cells were treated with 5, 10, and 25 μM BrPQ5 and 25 μM DOXO along with control for 24 h. Then, the cells were scraped on ice, and cell lysates were prepared in lysis buffer  with three freeze–thaw cycles. The lysates were centrifuged . The total protein concentration was determined using the Protein Assay Kit . Free AMC concentration was used to create a standard curve for quantitative analysis. The proteasome activity was measured from the supernatants after 30 min incubation with the fluorogenic substrate in buffer containing 225 mM Tris, 45 mM potassium chloride, 7.5 mM magnesium acetate, 7.5 mM magnesium chloride, and 1 mM DTT, pH 7.8 using EnSpire multimode reader (PerkinElmer) at 360 nm excitation/460 nm emission.Proteasome β5 subunit activity was directly measured with the hydrolysis of the fluorogenic substrate Suc-Leu-Leu-Val-Tyr-AMC (Sigma-Aldrich). The MCF-7 cells were treated with 5, 10, and 25 μM post hoc test was used for multiple comparisons. The level of significance was set at p < 0.05.Statistical analysis was applied using GraphPad Prism 7 software . The data are expressed as the mean ± standard deviation (SD) of at least three independent experiments. Analysis of ANOVA variance with the Tukey’s http://swissadme.ch/index, accessed on 15 May 2022) was used to determine the ADME and pharmacokinetic properties of the brominated BrPQ analog (BrPQ5). The chemical structure was drawn using MarvinSketch to generate SMILE and inserted directly on the webpage to initiate the prediction process. The different physical properties, pharmacokinetic parameters, and ADME parameters, along with the BOILED-Egg chart, were downloaded from the server and analyzed.In this study, the free online server SwissADME (A molecular docking simulation was carried out using AutoDock-4.2 and MGLTools-1.5.7 . The ste(i)Protein preparation: Coordinates of human 20S proteasome subunits beta-1 (chain M), beta-2 (chain K), and beta-5 (chain L) were manually extracted from the X-ray crystal structure of the human 20S proteasome in a complex with carfilzomib (PDB:4R67) [DB:4R67) . The cooDB:4R67) . This al(ii)Ligand preparation: The structure of BrPQ5 was sketched in Chemdraw-19, 3D geometry optimized, energy minimized, and saved as ligand.pdb. Torsion and charge were assigned to the ligand and then saved as ligand.pdbqt using MGLTools-1.5.7.(iii)Docking preparation, run, analysis: (a) Generation of grid map files: the grid over the binding site on respective_protein (*.pdbqt) was generated using the coordinates of carfilzomib (3BV) bound to subunit beta-5 (chain L). The center of the grid was specified as the center of the protein-bound ligand with a box dimension of 40:42:40 and grid spacing of 0.375 Å. Map types were set considering the atom types in the BrPQ5. The grid parameter file was then saved as respective_protein.gpf and used to generate map files using the autogrid4 execution file; (b) Docking: the docking parameter file for each subunit was then written for BrPQ5 (respective_protein_BrPQ5.dpf) with 100 hybrid GA-LS runs, 150 population size, 2,500,000 energy evaluations, and 27,000 generations. The generated map files and the *.dpf files docking simulation were performed using the autodock4 execution file. (c) Analysis: the top scoring conformer in the largest cluster of the respective docking log file (*.dlg) was then picked for interaction analysis, and the 3D interaction plot was then saved as *.png (in BrPQ5, respective_protein.gpf, and respective_protein_BrPQ5.dpf files used in the study are provided in the *.png in . All the


We have corrected this loss-of-function OAT mutation in patient-derived induced pluripotent stem cells (iPSCs) using CRISPR/Cas9. The correction restored OAT expression in stem cells and normalized the elevated ornithine levels in cell lysates and cell media. These results show an efficient recovery of OAT function in iPSC, encouraging the possibility of autologous cell therapy for the HOGA disease.Hyperornithinemia with gyrate atrophy of the choroid and retina (HOGA) is a severe recessive inherited disease, causing muscular degeneration and retinochoroidal atrophy that progresses to blindness. HOGA arises from mutations in the ornithine aminotransferase  When unGene-editing tools offer novel therapeutic opportunities for many genetic diseases . For ophFin patients, and subsequently corrected the pathogenic mutation using Cas9-induced HDR. These corrected isogenic iPSC lines served to establish and characterize the first patient-derived iPSC model of HOGAFin. We observed a restoration of OAT enzyme production and function upon genetic correction of the mutation. The recovered aminotransferase activity lowered the elevated ornithine levels in cell cultures. This further normalized the concentrations of other metabolites in related pathways [Here, we have generated iPSC lines from two HOGApathways . Additio2Additional materials and methods can be found in Supplementary data.2.1We collected skin biopsies from two non-related voluntary female patients (aged 18 and 30). The patients were diagnosed in their childhood and have been on arginine-restricted diet ever since. Creatine and lysine supplementation started later in life. Both are homozygous for the most common Finnish OAT mutation c.1205 T > C p.(Leu402Pro).2.2The Coordinating Ethics Committee of the Helsinki and Uusimaa Hospital District approved the generation of the induced pluripotent stem cell lines upon informed consent of the donors (Nro #HUS/2754/2019).2.3We transfected 1 × 10^6 human fibroblasts with CRISPR/Cas9 activators, as previously described . BrieflyiPSC colonies were picked manually (d15) and plated on Matrigel-coated wells in E8 medium. Media were changed every other day and cells were expanded up to passage 10. Thereafter, we used PCR targeting EBNA1  and OriP  to confirmed that the reprogramming plasmids had not integrated into the genome .2.4For genome editing of the disease mutation, we designed a suitable guide RNA using online tools . We gen2.5For each electroporation experiment, we dissociated 2 × 10^6 patient-derived iPSC to single cells with StemPro Accutase (ThermoFisher Scientific). We electroporated the sgAlt-R® S.p. HiFi Cas9 Nuclease V3, Alt-R® Cas9 electroporation enhancer , sgRNA, and dsDNA donor template into the cells with Neon transfection systems . Cells were plated onto Matrigel-coated plates containing E8 with 5 μM ROCK inhibitor  and 15 μM Alt-R® HDR Enhancer (iDT), and incubated overnight at 37 °C, 5% CO2.24–48 h after electroporation, we sorted ATTO550 positive cells for monoclonal expansion in E8 with 5 μM ROCK inhibitor, 1% penicillin-streptomycin and 10% CloneR (StemCell Technologies). The medium was refreshed every 72 h until splitting. We individually screened a total of 55 monoclonal colonies by enzymatic digestion (Bsh1236i). All the clones were validated by Sanger sequencing (Eurofins Genomics).2.6https://benchling.com and CRISPOR. Sequences were confirmed by Sanger sequencing of the PCR products  using Ornithine Assay Kit . Results are expressed in μM. We based the statistical analysis on Tukey test for multiple comparison of group means.2.8We cultured the original (c.1205C/C) and edited (c.1205 T/T) iPSC lines (passage 15–20) to 60–95% confluency and collected 4 replicates of each line in 400 μl of extraction solvent . For targeted analysis of ornithine-related metabolites, FIMM metabolomics unit sonicated and analyzed the soluble fraction with Thermo Vanquish UHPLC+ system, coupled to a Q Exactive Orbitrap quadrupole mass spectrometer (ThermoFisher Scientific). Gradient on a SeQuant ZIC-pHILIC  column (Merck) was used with Mobile phase A , and B (acetonitrile). Instrument control operated with the Xcalibur 4.1.31.9 software (ThermoFisher Scientific).versus p.value (cut at 0.05).Metabolite peaks were integrated with TraceFinder™ 5.1 software using retention times confirmed with standards . Data quality was monitored with pooled human serum as Quality Control (QC). We ran post-measurement analysis with data normalized to total protein  within each prepared sample. Volcano plots generated in Rstudio with the ‘EnhancedVolcano’ package. Results shown as a matrix of fold change (cut at 0.5) 33.1Fin iPSC lines and subsequently corrected the HOGAFin mutation with our selected CRISPR/Cas9 design  in the targeted region.Nonetheless, the analysis of the top six predicted off-target regions did not reveal off-target modifications in any of the edited iPSC lines .3.2To ensure the quality and function of all our iPSCs, we tested their genetic integrity and pluripotency ability (see Supplementary data). A PCR for EBNA1 and OriP in 8 original patient cell lines confirmed that our iPSC lines did not retain the vectors employed for reprogramming (data not shown). All iPSC lines, before and after correction, presented distinctive hiPSC morphology and positive immunostainings of pluripotency markers . Furthermore, quantitative measurement by qPCR of pluripotency markers OCT4, Nanog and Sox2 in corrected cell lines revealed expected expression patterns, indicating that the editing process did not affect these characteristic pluripotency genes (data not shown). During embryoid body differentiation, all cell lines successfully differentiated into the three germ layers . Importantly, neither the reprogramming nor the editing process affected the karyotypes of edited or non-edited cell lines, as shown by G-banding of iPSCs from both patients . Along with the genetic results, these analyses suggest that the editing process did not impair neither the function nor characteristics of our iPSCs.3.3Fin patients. After the genetic correction, the iPSC lines edited in hetero- and homozygosity showed a strong production of OAT in the Western Blot analysis (The predominant Finnish HOGA-causing mutation c.1205 T > C p.(Leu402Pro) likely destabilizes the protein structure, ultimately leading to its degradation, as seen in patient fibroblasts . Accordianalysis A.Fig. 2M3.4OAT mutation leads to the recovery of the enzymatic activity.Given that patients present with elevated ornithine in circulation and body fluids, we measured ornithine concentration in cell media to assess OAT function in our cell model. Media from all corrected cell lines presented ornithine levels comparable to those in media from control iPSC lines (Hel24.3), significantly lower than those of the homozygous-mutant HOGA iPSCs B. Our reversus non-edited patient lines, using liquid chromatograph-mass spectrometry (LC-MS targeted metabolomics). We discovered that the levels of intracellular ornithine significantly decrease in edited cell lines when compared to the mutants  plays a key role in the pathology . AGAT prreatment . Additiof lysine , and oraf lysine  by the cOAT expression levels and OAT production. Our results show that mutant iPSC express OAT at the mRNA level but fail to produce the protein. This suggests that the Finnish-founder mutation under study, OAT c.1205 T > C p.(Leu402Pro), might destabilize the structure of the protein, ultimately leading to its degradation.As part of the molecular characterization, we analyzed the quantitative The current treatment strategies usually improve the muscular prognosis but only decelerate the progression of the retinal symptoms. Although long-term therapeutic alternatives have been proposed ,30, neitOAT expression under its physiological genetic control. Our iPSC feature lowered intracellular ornithine levels compared to their non-edited counterparts. The cell culture media of all our edited cell lines showed decreased ornithine concentration, albeit less pronounced in heterozygotes. This accords with previous observations of reduced OAT activity in carriers, although they show no clinical symptoms [Here, we sought to explore the genetic correction of the mutation directly in patient-derived iPSC. This approach allows the production of functional, autologous cells with the symptoms ,32.in vivo therapeutic alternative. Nevertheless, we believe that our results offer new opportunities for the modelling of this disease, mechanistic studies, and the evaluation of novel therapies for gyrate atrophy. We predict that the constant advancement of CRISPR/Cas9 editing, and delivery systems will bring promising optimization strategies to make new therapeutic alternatives a reality.Importantly, the edition did not produce any detectable off-target modifications, neither did it affect the pluripotent quality of the iPSCs nor their chromosomal integrity. However, the occurrence of undesired, on-target alterations makes it currently necessary to obtain monoclonal lines, as the effects of these changes on the phenotype remain uncertain. These events challenge the immediate utilization of the presented genome editing approach as an 10.13039/501100002341Academy of Finland (Grant 308481), Foundation for Paediatric Research, Sigrid Juselius Foundation, 10.13039/501100007417Paulo Foundation, Mary & Georg C. Ehrnrooth Foundation and 10.13039/501100003125Finnish Cultural Foundation. FIMM metabolomics unit was supported by HiLIFE and 10.13039/501100013840Biocenter Finland.The work was funded by The authors declare no conflict of interest.