The mechanisms by which DNA alleles contribute to disease risk, drug response, and other human phenotypes are highly context-specific, varying across cell types and different conditions. Human induced pluripotent stem cells are uniquely suited to study these context-dependent effects but cell lines from hundreds or thousands of individuals are required. Village cultures, where multiple induced pluripotent stem lines are cultured and differentiated in a single dish, provide an elegant solution for scaling induced pluripotent stem experiments to the necessary sample sizes required for population-scale studies. Here, we show the utility of village models, demonstrating how cells can be assigned to an induced pluripotent stem line using single-cell sequencing and illustrating that the genetic, epigenetic or induced pluripotent stem line-specific effects explain a large percentage of gene expression variation for many genes. We demonstrate that village methods can effectively detect induced pluripotent stem line-specific effects, including sensitive dynamics of cell states. Village cultures, where multiple stem cell lines are cultured in a single dish, provide an elegant solution for population-scale studies. Here, authors show the utility of village models – showing that expression heterogeneity is largely a result of line-specific effects and not village cultures. They can differentiate into virtually any cell type in the human body5, providing a model system to study human cell types in vitro. Recent work has demonstrated that hiPSCs are a powerful system for investigating large-scale inter-individual variation and context-dependent effects that would be challenging to recreate in vivo. Here, we consider context-dependent effects genetic relationships with phenotypes only detectable under specific conditions. For example, some expression quantitative trait loci (eQTLs) are only detected in specific tissues6, cell types7, cell states8, or following drug9 or chemokine10 exposure. While hiPSCs are a powerful model system to interrogate these context-specific effects, large-scale hiPSC culture is expensive and time-consuming, creating challenges for studies that require hundreds to thousands of donor lines. Previous studies have relied on bulk RNA sequencing (RNA-seq) to assess gene expression, which has two major limitations. First, it effectively averages the heterogeneous expression of different cell types into a single measure. Secondly, the types of experimental design used in bulk RNA-seq require each hiPSC line to be cultured, extracted and processed independently—creating inherent correlations between line and batch effects.Using human induced pluripotent stem cells (hiPSCs) and their derivatives to study complex human traits such as diseases and drug responses is becoming a new research frontier through the intersection with population genetic approaches11. One of these studies paired flow sorting of survival motor neuron protein levels with whole genome sequencing. The proportion of each hiPSC line in each survival motor neuron flow-sorted group of cells were estimated with computational methods. The study design provided statistical power to detect survival motor neuron protein quantitative trait loci—genetic variants associated with protein expression levels of cell lines. While this approach is effective, it is not easily scalable for high-throughput assays of molecular phenotypes. Other studies have applied village culture methods with single-cell RNA-sequencing (scRNA-seq). Each cell is assigned to a line in the pool in tusing demultiplexing methods15. However, the impact on molecular phenotypes due to multiple cell lines in a single village culture has not been assessed.To mitigate these limitations, recent studies have applied a village approach to culture hiPSCs—where multiple unrelated lines are cultured and differentiated in a single dishThis is a challenge, as it needs to be clarified whether cell signaling in villages will influence the transcriptional profiles of each independent hiPSC line. If such effects were to exist, they would likely lead to biases in the identification of both eQTLs and context-dependent effects due to the creation of ‘artificial’ correlations in the phenotypes between donor lines. Here, we develop village culture systems and demonstrate their efficacy for population-scale stem cell studies. We investigate how growth rates impact the proportions of cells from each line in the village and whether cell signaling alters the transcriptional profiles of individual cells in village culture conditions. We evaluated these properties across multiple independent laboratories.We show that the inter-line gene expression is unaffected by culturing lines in a village or between sites. In other words, the genetic, epigenetic or line-dependent effects that underlie gene expression variation between different lines are consistent when the cells are cultured separately or in a village. Furthermore, we demonstrate that line-specific effects that change across a cell-state pseudotime (dynamic effects) can be reproducibly detected, further supporting the use of village culture systems for large-scale studies with hiPSCs. Our results demonstrate that the village model can be effectively used to detect eQTLs and other cell line-specific effects, and we provide important details that will allow these approaches to be easily implemented in different laboratories.We implemented a multi-phased experimental design that enabled the interrogation of village culture conditions while also comparing inter-laboratory and cryopreservation effects using scRNA-seq Fig. .Fig. 1ExTo compare the effects of village culture conditions in different laboratories, Phase I involved the generation of data from three independent sites—the University of Queensland , the University of Melbourne  and the Garvan Institute of Medical Research . The same lines from the same passage , the same protocols and the same reagents  were used at each site with one exception—lines were plated at a lower density at Site 3 (~1/10 the plating density used at Sites 1 and 2). Villages were generated using equal proportions of each uni-cultured line (cultured in separate dishes) and maintained for four days before single cell capture. For the scRNA-seq capture of uni- and village cultures in Phase I, cells were detached and dissociated simultaneously at each site and placed on ice. Samples from Sites 1 and 2 were transported to Site 3, where the samples were processed and captured together Fig. . FinallyIn the analysis of the scRNA-seq data, we estimated the variance explained by hiPSC line, replicate, site, cryopreservation and village status and the interaction of each of those covariates using a linear mixed model Fig. . FinallyTo investigate the potential impacts of village culture conditions on individual lines, we collected samples of the lines cultured separately and, after four days, cultured in a village at the three independent sites as previously described  to the proportions following culture in a village. After demultiplexing the samples (see Methods), we found that all lines were present in all samples, albeit at different proportions in the village than the uni-culture samples at Sites 1 and 2 but not 3. At Sites 1 and 2, the village samples had a larger proportion of FSA0006 and a smaller proportion of MBE1006 and TOB0421 Fig. . These rWe tested whether variation in hiPSC line growth rates could contribute to variation in the proportion of each line in the village and demonstrated that FSA0006 had almost double the growth rate of the other two lines  followed by Village (median rho = 0.98), line (median rho = 0.98) and Site , the village status explains 0.22%, and the interaction of line and Village covariates (Line:Village) only explains 0.32% of the variation in the fresh samples  that the village culture system could have on gene expression denoting a pluripotent state. We identified that, on average, only a small percentage of the total variance of pluripotency gene expression was explained by the village status for common stem cell markers such as F15 Fig. . FurtherF15 Fig. .These results suggest that culturing hiPSCs in a village and cryopreservation of villages do not significantly alter the proportions of each line or their unique transcriptional profiles and suggest that village systems are appropriate for population genomic studies.16 with our data. Indeed, the majority of eQTLs previously identified by DeBoever et al. that had at least two genotypes in this dataset demonstrated consistent effects in both the uni-culture  and village samples , the Garvan Institute of Medical Research (ETH01307) and the University of Queensland (2015001434). All patients gave written informed consent to collect and use their biological data for this research.19  complete with StemFlexTM Supplement  with Rock inhibitor Y-27632  on Costar non-treated six well polystyrene plates  coated with Vitronectin XF  diluted in CellAdhere Buffer . Cells were subcultured once a week with ReLeSR for two weeks  before equal numbers of the hiPSC lines were combined and plated together. The same lot number of all reagents were used between the three locations . hiPSC villages were cryopreserved in 1 mL with CryoStor® CS10  per manufacturer instructions.1 mL aliquots of each of the hiPSC lines FSA0006, MBE1006 and TOB04216 cells from each replicate at each site were centrifuged at 300 × g for three minutes and the supernatant was discarded. The cell pellets were resuspended in 100 µL cold Fluorescence-Activated Cell Sorting (FACS) buffer . Then, 2 µL of Totalseq-A hashing antibody was added and the cells were gently pipetted to mix before incubating for 20 min on ice. Cells were then washed twice with FACS buffer by centrifuging at 300 × g for 5 min, discarding the supernatant and resuspending the cell pellet in 100 µL cold FACS buffer. Cells were briefly stained with 4′,6-diamidino-2-phenylindole (DAPI) before using flow cytometry  to sort and capture live single cells. Cell pools contained one sample from each site  were used to hashtag hiPSC pools from each different location  before combining and super-loading onto the 10x Genomics Chromium Controller (10x Genomics) to capture single cells. Briefly, 1 × 10GEM generation, barcoding, cDNA amplification, and library construction were performed according to the 10x Genomics Chromium User Guide (CG000183). Libraries were prepared with the Single Cell 3’ V3.0 Library and Gel Bead Kit .TM media complete with StemFlexTM Supplement with Rock inhibitor Y-27632 on Costar non-treated six-well polystyrene plates coated with Vitronectin XF. Media was changed on day 2 and then cells from three wells were detached and counted on days 4, 5, 6, and 7 each. The resulting cell counts were used to estimate growth rates with ratrack20.hiPSC lines FSA0006, MBE1006 and TOB0421 were each plated in two six-well plates on day 0 in StemFlex19 were thawed and plated in mTeSRTM Plus media complete with mTeSRTM Plus Supplement  with Rock inhibitor Y-27632  on Costar TC-treated six-well plates  coated with Matrigel® hESC-Qualified Matrix  diluted in Dulbecco’s Modified Eagle Medium/F-12 . Each hiPSC was maintained for two passages before pooling into a village using equal numbers of each line. Aliquots of the village were cryopreserved using CryoStor® CS10  per manufacturer instructions. The village was plated for >90% confluency to start cardiomyocyte differentiations and differentiated over 15 days using the STEMdiffTM Cardiomyocyte Differentiation Kit  per manufacturer instructions. Cells were collected at Days 0 (hiPSCs at time of village construction), 1, 2, 3, 4, 5, 7, and 15. For hiPSC maintenance interrogations, the cryopreserved village was thawed and plated with mTeSRTM Plus media complete with mTeSRTM Plus Supplement  with Rock inhibitor Y-27632  on Costar TC-treated six-well plates  coated with Matrigel® hESC-Qualified Matrix  diluted in Dulbecco’s Modified Eagle Medium/F-12 . The villages were maintained for eight passages.1 mL aliquots of each of the hiPSC lines  using 0.1× lysis buffer and lysed for 2.5 min to obtain intact nuclei. Single cell ATAC and RNA-seq libraries were prepared using the Chromium single cell multiome ATAC + gene expression platform (10x Genomics). Nuclei were prepared and counted to ensure quality and concentration. Nuclei were then transposed according to the manufacturer’s protocol. Transposed nuclei suspension was loaded onto Next GEM Chip J targeting 20,000 nuclei and then ran on a Chromium Controller instrument to generate GEM emulsion (10x Genomics). Single-cell gene expression libraries, as well as single cell ATAC-seq libraries, were generated according to the manufacturer’s protocol using the Chromium Next GEM Single Cell multiome ATAC+ gene expression kit. Final libraries were quantified using high sensitivity D1000 TapeStation (Agilent). Each library was sequenced separately on a NovaSeq 6000 instrument using an SP 100 cycles reagent kit (Illumina), targeting 25,000 reads/nuclei for ATAC-seq and a minimum of 20,000 reads/nuclei for gene expressionThe cardiac differentiated village samples were prepared for the 10x Genomics Single Cell Multiome (ATAC + GEX) kit per manufacturer instructions. Briefly, cells were detached from the plate using TrypleE and washed twice using 0.04% BSA in PBS. Cells were treated with DNAse solution for 5 min on ice and washed using 0.04% BSA in PBS. Cells were counted and 1.5 × 10TM Plus media complete with mTeSRTM Plus Supplement  and centrifuging at 300 × g for four minutes to pellet cells. The supernatant was discarded before washing with phosphate-buffered saline (PBS) and incubated in GibcoTM TrypLETM Express Enzyme  for eight minutes. Cold Fluorescence-Activated Cell Sorting (FACS) buffer  was added to the cells before centrifuging at 300 × g for four minutes and aspirating the supernatant. The cell pellets were resuspended in 500 µL cold Fluorescence-Activated Cell Sorting (FACS) buffer . Trypan blue was then used to assess the pool viability (>70% viable). Approximately 32,000 cells of each sample were loaded onto a separate well of the Chromium Single Cell Chip B  to capture 20,000 single cells with the Gel Bead Kit V3.0 .Samples from the hiPSCs villages that were maintained for eight passages—passage one, four and eight—were superloaded onto the 10x Genomics Chromium Controller (10x Genomics) to capture single cells. Briefly, cryopreserved samples were thawed at 37 °C before adding to 4 mL mTeSRGEM generation, barcoding, cDNA amplification, and library construction were performed according to the 10x Genomics Chromium User Guide (CG000183). Libraries were prepared with the Single Cell 3’ V3.0 Library and Gel Bead Kit .TM Plus media complete with mTeSRTM Plus Supplement on Costar TC-treated six-well plates coated with Matrigel® hESC-Qualified Matrix diluted in Dulbecco’s Modified Eagle Medium/F-12. Cells were imaged every business day for up to eight days on a Celigo Imaging Cytometer. the media was changed per the manufacturer’s recommendations. The resulting cell confluencies were used to estimate growth rates with ratrack20.The 18 hiPSC lines were each plated in three wells of a 6-well plate on day 0 in mTeSRThe 10x Genomics Cell Ranger Single Cell Software Suite (version 3.1.0) was used to process the 3’ single-cell RNA-seq libraries (chemistry v3). Raw base calls were used to demultiplex the multiplexed pools, which were then mapped to the GRCh38-1.2.0 genome (Ensembl release 84) using STAR (version 2.5.1b) for each pool independently.Demuxafy21 to combine droplet calls between different methods. These methods demultiplex the different hiPSC lines in the pools and identify doublets between two lines. The village containing three hiPSC lines used SNP genotype demultiplexing Popscle Demuxlet v0.1-beta13, Popscle Freemuxlet v0.1-beta22, scSplit v1.0.114, Souporcell v1.015, and Vireo v0.4.212 with additional doublets classified by Scrublet23 and DoubletDetection v 3.024. Droplets classified as singlets by at least four of the SNP-based demultiplexing or transcription-based doublet detecting softwares, as well as the hashtag demultiplexing and were classified as the same hiPSC line by at least three of the SNP-based demultiplexing softwares, were retained for downstream analysis. All other droplets were excluded.The single cell village pools were demultiplexed with Souporcell v1.015 and additional doublets identified with scds v1.12.025 and DoubletDetection v 3.024. The village containing 18 hiPSC lines maintained over eight passages was demultiplexed using Popscle Demuxlet v0.1-beta13, Popscle Freemuxlet v0.1-beta22, Souporcell v1.015, and Vireo v0.4.212 with additional doublets classified by Scrublet v1.023. The recommended guidelines were followed for each of the softwares as briefly described.The cardiomyocyte differentiation of the 18 hiSPC line village was SNP genotype demultiplexed with Popscle pileup was used to identify the single nucleotide variants (SNVs) in the pool. Then, Demuxlet was run with reference genotypes for each hiPSC line in the pool using a genotype error coefficient of 1 and genotype error offset rate of 0.05 and default options for all other parameters.Popscle pileup was used to identify the single nucleotide variants (SNVs) in the pool followed by Freeuxlet executed with default parameters.scSplit using default options and the -n 3 option to provide the number of hiPSC lines in the pool.Low quality and duplicated reads were removed before using freebayes to classify high quality SNVs in the dataset. The resulting bam and vcf were used for Souporcell was run using the souporcell_pipeline.py script with known variant locations from the reference imputed SNP genotypes that overlapped gene exons using the–common_variants parameter and all other default parameter options.Model 1 of cellSNP v0.3.2 was used to identify allele frequencies at the locations of the common variants (MAF = 0.1) in the genotyped reference genotype file for the three hiPSC lines. The resulting pileup was filtered for SNP locations covered by at least 20 UMIs and had at least 10% minor allele frequency across all droplets. Vireo version 0.4.2 was then used to demultiplex the droplets in the pool using reference SNP genotypes and indicating the number of individuals in the pools.Scrublet was used to identify transcription-based doublets that included two cells from different cell types. Scrublet was implemented in python v3.6.3 per developer recommendations with at least three counts per droplet, three cells expressing a given gene, 30 PCs and a doublet rate based on the following equation:N is the number of droplets captured and R is the expected doublet rate. Scrublet was assessed at four different minimum numbers of variable gene percentiles: 80, 85, 90, and 95. Then, the best variable gene percentile was selected based on the distribution of the simulated doublet scores and the location of the doublet threshold selection. If the chosen threshold does not fall between a bimodal distribution, those pools were rerun with a manual threshold set.Scds25 is a transcription-based doublet detecting method. Scds was implemented with the cxds function and bcds functions with default options followed by the cxds_bcds_hybrid with estNdbl set to TRUE so that doublets were estimated based on the values from the cxds and bcds functions.DoubletDetection24 is a transcription-based method for identifying doublets. Droplets without any UMIs were removed before analysis with DoubletDetection. Then the doubletdetection.BoostClassifier function was run with 50 iterations with use_phenograph set to False and standard_scaling set to True. The predicted number of doublets per iteration was visualized across all iterations. Any pool that did not converge after 50 iterations were rerun with increasing numbers of iterations until they reached convergence.26 was used to identify cells from each location and doublets that included cells from two locations.Hashtag demultiplexing27 was used to detect the cell cycle state of each cell. The quality control metrics for these high-quality single cells for the fresh samples  from the mitochondrial percentage median or contained <1750 total genes. This resulted in 88,927 high-quality single cells being used for downstream analysis. Cyclone from the scran package v1.4.5les Fig.  are presles Fig.  are presSCTransform as previously described28. Expression data were also corrected by cell cycle status, mitochondrial percentage, and ribosomal percentage.Data were normalized with a regularized negative binomial regression, and variance stabilized with Pearson residuals using Demuxafy using the ‘AtLeastHalfSinglet’ integration method  and those with >25% mitochondrial content .57,451 droplets were captured, and 29,055 cells remained after removing the droplets that were classified as a doublet by The mean expression of each gene for each line was compared between samples with a two-sided Spearman Rank correlation, and the distributions of the correlations between samples of different covariates were plotted.scCODA29 v0.1.8. An FDR of 0.05 was used for all scCODA analyses. scCODA was sequentially run once using each cell line as the reference for each analysis and the majority vote was used to identify cell lines whose proportion was credibly changed more than half the time. The specific metrics are provided in Supplementary Data The proportional changes of lines between samples were estimated using 20 were correlated with proportions of hiPSC line estimated using Demuxafy at each time single cells were captured. Two-sided Spearman rank correlation was used to measure the strength of the correlation and statistical significance.The growth rates of the hiPSC lines in the 18-line village that were estimated with ratrackvar is the estimated variable, i:n is all the variables, including residual and σ2 represents the estimated variance.The proportion of the variance explained by the hiPSC line, the replicate and the village status for each gene was determined by fitting a linear mixed model for normalized and regularized expression of each gene. Briefly, normalized UMI counts were fit as the dependent variable of a linear mixed model with the independent variables as random effects. The intra-class correlation (ICC) was used to estimate the variance explained by each variable where The variables included for the fresh samples across the three sites were: line, village, site, and replicate. For the cryopreserved samples, the variables were line, village, cryopreservation and replicate. For the village containing 18 lines, the covariates modeled were line and passage number. The significance of a given variable was tested using an ANOVA between the model with and without that covariate. Significant covariates were then tested for significant interaction as well.n = 572). Differential expression was detected using logistic regression implemented in Seurat. Replicates were fit as a covariate in the model, and significance was corrected for all tests across all groups with the Bonferroni correction method.All genes expressed in at least 10% of cells in a given line at a given site were tested for differential expression with a logistic regression between the uni-culture and village samples. For comparison across the samples, all groups were down-sampled to the smallest number of cells at one condition . The effects (β) were tested for significant agreement with DeBoever et al. eQTLs with a χscvelo30 package (v0.2.3) to estimate the latent time of all single cells. First, sequence reads overlapping spliced and unspliced read count matrices were prepared using velocyto31 (v0.17.17). Cells that had <1000 unspliced counts and genes that were expressed in <20 cells and had <10 unspliced counts were filtered and removed. The batch effects were normalized using pycombat32 (Combat v0.3.0) using a proposed approach33. Briefly, the spliced 34. Thirty PCs, cell cycle, and mitochondrial percentage were fit as covariates.Cells from each cell line in each village status and at each site were integrated for visualization Fig.  using thhttps://github.com/powellgenomicslab/iPSC_Village_Publication) and Zenodo35. Data have been made available to support the reproduction of these results on Gene Expression Omnibus (GSE225282) and Zenodo35. Growth rate experiments were blinded to the experimenter. Experiments were not randomized.Three hiPSC lines that were previously established, well-characterized and used in previous studies were selected for use in the three-line hiPSC village experiments described. Three hiPSC lines, three sites and three replicates at each site were selected as the minimum required number to effectively identify variation between the different covariates. Four days of culture in the hiPSC villages were selected since this is typical for seeding stem cells in preparation for differentiation experiments. One week was used for the cryopreservation experiments since at least one week is required for stem cells to recover from thawing before beginning experiments. Single cell capture pools were generated with one sample from each site to prevent possible technical variation during capture, library preparation and sequencing that could confound site effects. Only droplets classified to contain cells from the cellranger pipeline were used in subsequent analyses. The resulting data were demultiplexed with genetic data (for each hiPSC line) and antibody hashtags (for each site). Droplets identified as doublets (containing two or more cells) or those could not be assigned to either a site or a hiPSC line were removed from the analysis. Data were then filtered for cells that were less than four median average deviations (MAD) from the mitochondrial percentage median or contained more than 1750 total genes (Supplementary Figs. No statistical method was used to predetermine the sample size. The hiPSC villages were captured on Days 0, 1, 2, 3, 4, 5, 7, and 15 to capture the transcriptional changes that occur early during differentiation. Droplets that contained cells based on cellranger estimation were maintained for analysis. Further, droplets that were annotated as doublets or could not be assigned to a hiPSC line with genetics by demultiplexing and/or doublet detecting methods were removed from downstream analyses. Growth rate experiments were blinded to the experimenter. Experiments were not randomized.No statistical method was used to predetermine sample size. The hiPSC villages were cryopreserved after one, four or eight passages and then thawed and captured at the same time to prevent possible capture, library preparation or sequencing confounding effects. Droplets that were not identified to contain cells by cellranger were removed from downstream analyses. Further, droplets that could not be assigned to a single hiPSC line with genetic demultiplexing were also removed. The growth rate experiments were blinded to the experimenter. The experiments were not randomized.> 3.6.8All analyses were executed in R version 4.2.1 or python versions Further information on research design is available in the Supplementary informationDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Supplementary Data 8Reporting Summary


We reviewed the data published from 2018 to 2022. A total of 41 articles based on 56 in vitro experiments met our eligibility criteria. Using a meta-analysis based on a random effect model, we evaluated the cytotoxicity of cisplatin (IC50) after 48- or 72-h cell exposure. We found large differences between studies using a particular cell line. According to the random effect model, the 95% confidence intervals for IC50 were extremely wide. The heterogeneity of cisplatin IC50, as measured by the I2 index for all cancer cell lines, was over 99.7% at culture times of 48 or 72 h. Therefore, the variability between studies is due to experimental heterogeneity rather than chance. Despite the higher IC50 values after 48 h than after 72 h, the heterogeneity between the two culture periods did not differ significantly. This indicates that the duration of cultivation is not the main cause of heterogeneity. Therefore, the available data is diverse and not useful as a reference. We discuss possible reasons for the IC50 heterogeneity and advise researchers to conduct preliminary testing before starting experiments and not to solely rely on the published data. We hope that this systematic meta-analysis will provide valuable information for researchers searching for new cancer drugs using cisplatin as a reference drug.Cisplatin is a classic anticancer drug widely used as a reference drug to test new metal complex drug candidates. We found an unexpected diversity in cisplatin-related cytotoxicity values, expressed as IC Cisplatin is widely used in everyday clinics as well as in clinical trials ,2, and a50 is a quantitative measure that specifies how much of a particular substance  is required to inhibit in vitro biological processes by 50%. In the context of cancer research, IC50 determines the concentration of a chemical compound that can inhibit cancer cell growth by half, relative to cells grown without the compound. IC50 is a very important measure that is also related to EC50, the plasma concentration required to obtain 50% of the maximum effect in vivo. Hence, the relationship between in vitro and in vivo cytotoxicity can help to reject chemical compounds during the initial stage of clinical study  assays) ,14. We uThe MTT test is a colorimetric assay that is most frequently used to determine cytotoxicity. It is based on the activity of succinate dehydrogenase, a mitochondrial enzyme of living cells that converts the soluble tetrazolium salt, 3--2,5-diphenyltetrazolium bromide, into its reduced form, insoluble formazan. The formazan crystal precipitates occur in small amounts or not in all damaged cells. To obtain reliable and reproducible results by using the MTT test, laboratory precision work is required at all stages of the test, particularly in the last stage of the assay, i.e., the dissolution of formazan crystals. Therefore, there many modifications to the MTT test have been introduced. One of these is CCK-8 assays, which use a tetrazolium salt as a substrate and which, under the influence of dehydrogenase, becomes converted into a colored, soluble compound instead of formazan crystals. In CCK-8 assays, a highly water-soluble tetrazolium salt is used; therefore, this test exhibits better detection sensitivity .SRB assays allow for the determination of the total amount of protein in the examined sample, which is directly proportional to the number of cells. The basis of this method is the electrostatic binding of sulforhodamine to proteins at an appropriate pH, depending on the qualitative composition of amino acids, after cell fixation with trichloroacetic acid .The assay of intracellular ATPs allows for the determination of the efficiency of mitochondrial energy processes, which reflect cell viability. The change in the ATP is proportional to the increase or decrease in the number of cells, as well as to the decrease in the efficiency of energy processes in cells. The determination of the number of ATPs can be based on bioluminescence occurring in the reaction with the luciferase catalyzing the oxidation of luciferin to oxyluciferin, with the participation of one ATP molecule .50 values of carboplatin, etoposide, paraquat in an in vitro model based on human glioblastoma cells .The confidence interval around the variable effect depends on the variance between the studies τ2, H2, and I2 for 48 h and 72 h, which assess the heterogeneity of the studies. Homogeneity analysis based on Q statistics rejects the hypothesis of homogeneity in both culture duration subgroups and for a joint set of papers (p < 0.0005)  than after 72 h (47.775). However, the variance value depends on the effect size (cytotoxicity measured by IC50 for HepG2), which is also higher after 48 h. Thus, the square roots of variances relative to means, i.e., variability coefficients are similar: 106.5320.5/18.07 = 0.57 at 48 h and 47.7750.5/10.93 = 0.63 at 72 h. Moreover, the results of the Q Cochran test of inter-group homogeneity were not significant  . The var2 statistic is larger for a subgroup of 48 h (1095.3) than for a 72 h (784.2), and the overall H2 is 1947.6. Inconsistency in the findings among the included studies based on experimental times was also compared by the I2 index. For example, according to 2 = (H2 − 1)/H2 = 1 − 1/1095.319 = 99.91%, indicates significant heterogeneity. Similarly, we observed significant heterogeneity for 72 h culturing (7 studies), according to index I2 = 1 − 1/784.171 = 99.87%, and significant overall heterogeneity according to I2 = 1 − 1/1947.583 = 99.94%. The prediction intervals are much wider than confidence intervals  but for 48 h (p = 0.032). The higher asymmetry after 48 h is due to the outlier study (numbered 11).According to the regression Egger test for funnel plot asymmetry , there i50 and averaged values for IC50 assessed from 11 publications for 48 h and from 7 publications for 72 h based on the HepG2 cell line. Almost all individual effects with 95% confidence intervals did not reach zero (p < 0.001) for all examined publications except for the 72 h study numbered 16 . τ2 equal to 52.84 is the variance of the observed effects of 48 h culturing, while the variance τ2 for 72 h is lesser: 43.14 .In these analyses, we have again observed considerable inconsistency in the raw data under different time points of MCF-7 cell culture . The hyp0.5/15.27 = 0.47 at 48 h and 43.140.5/10.70= 0.61 at 72 h.The square roots of variances relative to means, i.e., variability coefficients are 52.84p = 0.112). As shown in 2 = 99.7% at 48 h indicates significant heterogeneity. Likewise, there is significant heterogeneity at 72 h (I2 = 99.8%) as well as an overall heterogeneity of I2 = 99.8%. The prediction intervals are much wider than the confidence intervals due to the substantial τ2 variance , for 72 h (p = 0.015) and for a joint group (p < 0.001)  is distant (by −1.84791) from a red-dashed line which denotes overall differences. The differences are not observed for HeLa and HepG2 lines, where the grey and red lines almost overlap. In fact, for the MCF-7 cell line, a larger variety of experimental methods was used as compared to other lines  . Figure er lines . The dif culture .50 cytotoxicity in the same cell line in vitro has already been described in previous studies , whereas the overall cytotoxicity is 13.38  . Notwithstanding, the significance of the Cochran Q test comparing variances after 48 h and 72 h was not obtained, confirming that this heterogeneity is not related to the cell culture time. Similarly to I2 indices, other statistics measuring the heterogeneity such as τ2 and H2 confirm substantial heterogeneity within time-subgroups and within the overall effect. The prediction intervals are much wider than confidence intervals due to the substnatial heterogeneity τ2, both for all publications and for the overall effects in the time-subgroups.The forest plots illustrate a large discrepancy between cisplatin IC8–16.42) . Finally8–16.42) . Thus, t50 values and the averaged values within time-subgroup IC50 illustrate significant deviations from these averaged values in most cases.As confirmed by the asymmetry forest plots, most of the results of the Egger’s regression tests for funnel plot asymmetry are significant . Moreover, 0.95 confidence intervals for differences between individual IC50 results. In the work of Damian et al. [50 values of three different anticancer drugs: carboplatin, etoposide, and paraquat were tested against two glioblastoma lines—U87MG and U373MG—via the four analytical methods simultaneously . Different IC50 values were obtained for each reference drug depending on the method used. For the cytotoxicity values determined using trypan blue, significant differences were observed compared to other methods. The obtained results allowed to the researchers to distinguish the advantages and limitations of each of the tested methods [To the best of our knowledge, there are few publications that attempt to describe the quality of the ICn et al. , the IC5 methods .50 values of 5-fluorouracil tests available in the literature on 10 types of human cancer cell lines (AGS (gastric adenocarcinoma), DLD1 and SNU-C4 , HCT116 , HT-29 and MKN28 (gastric adenocarcinoma), MKN45 and SGC7901 (gastric carcinoma), SK-MES-1 (lung carcinoma), SW620 (colon adenocarcinoma)) were compared by using MTT, CCK-8, SRB, and a clonogenic assay in 12–72 h cultures with different cell densities. A wide scatter of the 5-fluorouracil IC50 results  was observed. According to the authors of the study, these differences may be related to the type and proliferative potential of the cell line used, the method used, the seeding density, the drug exposure time, and its concentration.In a more recent work by Arokia Femina et al. , the IC550 values obtained for the HeLa (48 h) and HepG2 (48 h and 72 h) lines indicates a significant influence of factors other than the type of cell line, the duration of culture, and the method used. In our research, we did not consider the effect of cell culture density, although the condition of the tested cell line and the preparation of the drug may have an impact. When new complex compounds are tested, there is often a problem with their solubility, so a certain amount of solvent, e.g., dimethyl sulfoxide (DMSO) is added to the culture. The methodology of the work rarely mentions whether the same amount of the same solvent was added to the control or the reference drug culture. According to our results, the large overall heterogeneity is not due to different cell culture times, but is due to other factors that are difficult to determine from published studies.Our research has focused on one of the most used anticancer drugs—cisplatin—which is the reference drug for many newly developed complexes with antiproliferative activities. Contrary to earlier authors, we conducted a broad review of the literature and ranked the results according to the three cell lines and the cultivation time. For the two tested HeLa and HepG2 lines, almost all results were obtained via the MTT method; only in the case of MCF-7 was the variety of methods used greater. The wide spread of ICAuthors typically do not provide enough information about experimental conditions that might help to explain inconsistency within the findings. Furthermore, the quality of experimental data description differs among publications. The observed diversity of results might also be related to the quality of tested cancer cell lines. In different research centers, cancer cell lines, despite having the same origin, may have their own “story”; in particular, such as the cell culture’s passage, the pre-assay preparation of the cell line and reagents, the concentration of cells, and the cell culture medium, among others. Interestingly, in 2003, the report from Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ) reported significant contamination of cell lines. About 18% of 252 “new” hematopoietic cell lines were cross-contaminated (by other cell lines). The scale of this problem emphasized the value of good laboratory practice . Additio50 values of cisplatin might be not the aim of a study; this value is often presented only for comparison with a chemical compound of interest in tumor treatment. Nevertheless, unexpected inconsistency in results makes it questionable that we have reliable models to test new anti-cancer drugs’ cytotoxicity in vitro.On the other hand, determining the ICFurther publications providing a better description of experimental conditions may help to determine the main factors affecting results and help to clarify the reasons for the inconsistency of published results.Meta-analysis was performed according to the PRISMA  statement guidelines .50, cytotoxicity, anticancer, antitumor, cisplatin, HeLa, HepG2, or MCF-7 cells was used. Databases searched: Science Direct, Scopus, and PubMed, for full-text research articles published between 2018 and 2022, and only journals in the field of chemistry, pharmacology, toxicology, or pharmaceutical science.A combination of the key words, ICWhen searching Science Direct, n = 2817; Scopus, n = 2431; and PubMed, n = 691.4.1.3. Eligibility:50 results in cell lines other than HeLa, HepG2, or MCF-7;Cisplatin IC50 data for cell culture times other than 48 and 72 h;Cisplatin ICResults obtained under unusual or special conditions  or under culture conditions described as ambiguous;50 results obtained using 3D spheroid cultures.Cisplatin ICRecords excluded as duplicates (n = 2925) and for other reasons (n = 2974). The reasons for excluding full text articles were as follows: 50 values for all three cancer cell lines was included.Forty studies were included in meta-analyses, based on the eligibility criteria. Of these studies, four reported results were based on MCF-7 and HepG2 cells, one was based on MCF-7 and HeLa cells, and three were based on HeLa and HepG2 cells. Only one publication reported results based on all three cell lines. To enhance results, a study published in 2016 describing cisplatin IC50 results for a specific cell line and for a specific culture period. In the same cell culture, cisplatin has a different IC50 value at 48 and 72 h; therefore, the effect of this drug may differ in studies with different experimental times. Cell culture time is a potential factor for cytotoxicity and was taken into account when performing the meta-analysis. For either HepG2 or MCF-7 cancer lines, each article published the results for one culture time point of interest i.e., 48 h or 72 h. In these cases, a meta-analysis was performed for two independent subgroups within the studies (48 h and 72 h). However, time subsets were not available for HeLa cell lines, as the vast majority of results were found for a culture time of 48 h. In order to examine whether the different IC50 values were due to real differences (heterogeneity), or whether the diversity of the IC50 results occurred by chance (homogeneity), the heterogeneity statistics of the cisplatin effects measured via IC50 were examined via meta-analysis. Measures of effect heterogeneity indicate the extent to which the differences between results of individual studies influenced the overall effect. The heterogeneity analysis was carried out separately for each time group.Of interest was the reliability of the IC2 was equal to zero. This was based on Cochran’s homogeneity test Q statistic with p-value based on a chi-square distribution with k-1 degrees of freedom (k is the number of studies). The Q test for homogeneity hypothesis was used to obtain information about the presence or absence of heterogeneity . However, to report on the extent of this heterogeneity, other statistics were used. For example, the heterogeneity was assessed using the inter-study variance τ2. Additionally, I2 and H2 indices were calculated to assess heterogeneity [2 = (H2 − 1)/H2 expresses the amount of variability in a meta-analysis that is explained by the inter-trial heterogeneity rather than sampling error. Unlike Q, it does not necessarily depend on the number of studies included in the meta-analysis. I2 index can be directly compared between meta-analyses with different numbers of studies and different types of outcome data [Cochran’s homogeneity Q statistics are the weighted sum of squared differences between individual study effects and the pooled effect across studies, with weights the same as for the pooling method. Homogeneity was analysed by testing whether the variability between studies τogeneity . I2 = (Home data .50), the random effects model was chosen, which assumes that there are meaningful differences between studies.Because the studies chosen in the meta-analysis were from different sites and likely included results of different specifications .The truncated Knapp–Hartung method   on the precision (1/SE):e is the estimated true effect, SE is the standard error of effect, and ε is a random noise. The size of α (intercept) indicates the extent of the asymmetry. Eggers’ test estimates the statistics based on the t-distribution. Test of intercept α = 0 is based on t-distribution with k-2 degrees of freedom. Additionally, to test for publication bias in the meta-analysis, a trim-and-fill analysis was applied (results not presented).In meta-analysis, it is important to assess the bias. Publication bias appears because studies with desirable results are more likely to be published. Consequently, published results may be biased in a certain direction. Analysis of the publication bias was performed using the Eggers’ regression-based test for meta-analysis with continuous outcomes ,77. The 50 values and averaged IC50 values for the respective time were calculated. It was assumed that for a specific cell line  and for a specific culture time (48 or 72 h), the correct IC50 value is approximated by the average of the relevant values.In addition, to assess the significance of the deviation from the mean value for a specific publication , for each tumor cell line, and culture time considered, the difference between individual published ICi-th individual published IC50 value and averaged IC50 valuek is the number of publications, as the particular time of cell culture (48 or 72 h); im is the individual published IC50, and m is the assumed theoretical IC50 assessed as the average of im. In addition, corresponding standard errors iSD and in  resulted in the same degrees of diversity, as measured via I2. This indicates that experimental duration is not the main cause of this inconsistency. A substantial degree of heterogeneity was confirmed by other statistics such as τ2, H2, and the significant Q Cochran test for homogeneity. For all cancer cell lines considered, the differences between individual publications and the deviation of the IC50 values from the means of the time-subgroup values were often significant.In 42 studies published between 2018 and 2022, we found an unexpected degree of diversity in cisplatin-related cytotoxicity values in MCF-7, HepG2, and HeLa tumour cell lines. After performing a meta-analysis using mixed-effect models, we observed a substantial degree of heterogeneity in the cisplatin cytotoxicity effects assessed via ITo determine the reasons for such diversity in the published results, the stratified analyses of a large series of reports with comprehensive descriptions of their experiment conditions would be helpful. Many factors can affect the quality of cytotoxicity test results, including cell line quality, study protocol validation, and the optimal selection of techniques.50 values. The data available in the literature are too diverse and unreliable to serve as a reference. It is therefore advisable to carry out a separate reference control for each new experiment, and to not rely solely on the available literature data of IC50.The observed inconsistency in reported cytotoxicity results reduces confidence when comparing new compounds with published cisplatin IC


The non-homologous end joining pathway is vital for repairing DNA double-strand breaks (DSB), with DNA-dependent protein kinase (DNA-PK) playing a critical role. Altered DNA damage response (DDR) in chronic (CML) and acute myeloid leukemia (AML) offers potential therapeutic opportunities. We studied the therapeutic potential of AZD-7648 (DNA-PK inhibitor) in CML and AML cell lines. This study used two CML (K-562 and LAMA-84) and five AML  cell lines. DDR gene mutations were obtained from the COSMIC database. The copy number and methylation profile were evaluated using MS-MLPA and DDR genes, and telomere length using qPCR. p53 protein expression was assessed using Western Blot, chromosomal damage through cytokinesis-block micronucleus assay, and γH2AX levels and DSB repair kinetics using flow cytometry. Cell density and viability were analyzed using trypan blue assay after treatment with AZD-7648 in concentrations ranging from 10 to 200 µM. Cell death, cell cycle distribution, and cell proliferation rate were assessed using flow cytometry. The cells displayed different DNA baseline damage, DDR gene expressions, mutations, genetic/epigenetic changes, and p53 expression. Only HEL cells displayed inefficient DSB repair. The LAMA-84, HEL, and KG-1 cells were the most sensitive to AZD-7648, whereas HL-60 and K-562 showed a lower effect on density and viability. Besides the reduction in cell proliferation, AZD-7648 induced apoptosis, cell cycle arrest, and DNA damage. In conclusion, these results suggest that AZD-7648 holds promise as a potential therapy for myeloid leukemias, however, with variations in drug sensitivity among tested cell lines, thus supporting further investigation to identify the specific factors influencing sensitivity to this DNA-PK inhibitor.  DNA douaneously . One of aneously ,5. The Dectively ,6.BCR-ABL1, which encodes an oncoprotein with abnormally high tyrosine kinase activity [Genomic stability is crucial for faithful genome replication, therefore, cells have developed a complex DNA damage response (DDR) network to protect genome integrity, and repair damaged DNA . Dysfuncactivity . AML is activity ,15. Someactivity ,16,17.50 value of 0.6 nM in biochemical assays and a >100-fold selectivity against many closely related kinases, such as PI3Ks [Genomic instability associated with cancer may provide targetable vulnerabilities for cancer therapy , and givas PI3Ks ,19,21. Cas PI3Ks . Considering the doubt regarding the therapeutic potential of AZD-7648 in the treatment of myeloid leukemias, studies in this area are necessary to elucidate the relevance of this approach. Therefore, our study aimed to assess the therapeutic potential of AZD-7648 in monotherapy for myeloid leukemia treatment using in vitro models of CML and AML. We hypothesized that AZD-7648 may have promise as a new therapeutic strategy for these myeloid leukemias in monotherapy. The results from our study may help shed some light on the efficacy of this DNA-PK inhibitor and may help clarify the relevance of this therapeutic line for these diseases.The mutational status of genes involved in the DDR of CML and AML cell lines included in this study was retrieved from the COSMIC platform . CML celConsidering the functions associated with the mutated genes, particularly those linked with DNA repair pathways, distinct patterns are evident among the cell lines. The NER pathway was the most affected repair mechanism in the K-562, HEL, and KG-1 cell lines and the MMR pathway in THP-1 cells. LAMA-84 presented more alterations in the Fanconi anemia pathway, NB-4 in the HRR pathway, and HL-60 with the same number of mutations in the BER and HRR pathways. Further information involving the mutations can be found in the MGMT), were assessed in CML and AML cell lines using methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA). As shown in MLH1, MSH2, and PMS2 genes appeared to be the most altered, as each presented genetic abnormalities in five different cell lines. The MSH6 gene was only altered on one CML cell line (LAMA-84). The HEL cell line presented only a genetic abnormality, specifically an amplification within the MSH2 gene. Similarly, both K-562 (CML) and THP-1 (AML) cell lines just carried amplifications, affecting three genes each. On the other hand, the KG-1 cell line carried only deletions in the MLH1 and MSH2 genes. The HL-60 and NB-4 cell lines carried the highest number of genetic alterations, each with five genes affected. The MGMT gene exhibited the highest degree of methylation  were evaluated via qPCR. As illustrated in RAD51, significantly surpassing HL-60, K-562, NB-4, and THP-1 (p < 0.01), and KG-1 (p < 0.001), which was the cell line with the lowest expression levels. Both the LAMA-84 and HL-60 cell lines presented the highest expression levels of CHEK2, significantly above those of HEL , K-562, KG-1, NB-4, and THP-1 (p < 0.001). Among these cell lines, NB-4 had the lowest expression levels. The PRKDC gene’s lowest expression levels were observed in HL-60 cells, significantly lower than in the KG-1 cell line (p < 0.05). KG-1, followed by LAMA-84 cells, exhibited the highest expression levels for this gene. Although without statistical significance, the NB-4 cell line displayed the highest TP53 expression levels, followed by HEL. Among the remaining cell lines, except HL-60 cells that do not express the gene TP53, noticeably lower expression levels were observed. Lastly, regarding the PARP1 and XRCC6 genes, the expression levels were mostly similar across the cell lines. However, for both genes, particularly for the PARP1 gene, LAMA-84 cells appeared to have the highest expression levels, while NB-4 had the lowest.The baseline expression levels of the genes involved in NHEJ and alternative repair pathways , K-562 (p < 0.01), and THP-1 (p < 0.05).We began by characterizing the frequency of DSB in the CML and AML cell lines, as well as in IMC . Baseline levels of phosphorylated-H2AX (γH2AX), a biomarker of DSB, were quantified through flow cytometry . The HELp < 0.001), as well as KG-1 (p < 0.01).The chromosomal damage was assessed using the cytokinesis-block micronucleus cytome assay (CBMN), wherein binucleated (BN) viable cells were categorized into cells lacking chromosomal damage biomarkers (CDBs), cells with micronuclei (MNi), cells with nuclear buds (NBUDs), and cells with nucleoplasmic bridges (NPBs). Firstly, total chromosomal damage was quantified as a percentage of cells with CDBs. As detailed in p < 0.01). Within this cell line, the MNi frequency was 1.6-fold and 8.4-fold higher than the NBUDs and NPBs, respectively. The KG-1 cell line also presented MNi as the dominant chromosomal damage. Here, MNi were 1.8-fold and 2.2-fold more frequent than the NBUDs and NPBs, respectively. NPBs were the prevalent damage type in the LAMA-84 cell line, with the percentage of this damage being 2.0-fold and 1.9-fold higher than in MNi and NBUDs, respectively. When compared to IMC cells, the levels of NPBs were significantly higher, not only in the LAMA-84 (p < 0.001) but also in the K-562 (p < 0.01), HEL, KG-1, and NB-4 (p < 0.05) cell lines. Lastly, NBUDs were the predominant type of damage in the remaining cell lines, specifically HEL, HL-60, K-562, NB-4, and THP-1. In these cases, the percentage of NBUDs was 2.1-fold, 1.7-fold, 2.6-fold, 1.6-fold, and 1.9-fold higher than that of MNi, respectively. When comparing NPBs and NBUDs, the latter percentage was 2.4-fold, 3.5-fold, 1.9-fold, 2.3-fold, and 4.7-fold higher in the HEL, HL-60, K-562, NB-4 and THP-1 cells, respectively. Among these cell lines, THP-1 showed the highest NBUDs percentage, significantly surpassing that of the IMC cells (p < 0.05).Additionally, the percentage of BN cells displaying each type of damage  was calculated . The CMLp < 0.01).The telomere length was assessed using qPCR and normalized to the telomere length of IMC cells . The cel2O2. As shown in 2O2 in the K-562 , KG-1 , and THP-1  cells, compared to the baseline (0 hour time point). Then, this increase was followed by a significant decrease in γH2AX levels at the 24 h time point in the K-562  and THP-1  cell lines, reaching the baseline levels of damage. Though this decrease was not statistically significant in KG-1 cells (1.9-fold), no statistically significant differences were found between the baseline DSB levels and the levels 24 h after H2O2 exposure in any of these three cell lines. In the HL-60, LAMA-84, and NB-4 cells, while not statistically significant, a peak 1 h after the genotoxic stimuli was observed. This peak resulted from respective 1.8-fold, 1.4-fold, and 1.2-fold increases in γH2AX levels compared to the baseline. A decrease in DSB levels between the 1 and 24 h time points was observed , showing a recovery of the original γH2AX levels. Consequently, no statistical differences were observed between these cell lines’ 0 and 24 h time points. The HEL cell line showed a significant 1.9-fold increase (p < 0.05) in γH2AX levels 1 h after exposure to H2O2, followed by a 1.2-fold decrease at 24 h. When comparing the damage quantified at 24 h with that at the baseline levels, a significant 1.2-fold (p < 0.05) difference remains evident.DSB repair kinetics were established by assessing γH2AX levels through flow cytometry at different time points following exposure to a genotoxic stimulus with H50) was not reached in the HL-60, K-562, NB-4, and THP-1 cells at any time point (IC50 > 200 µM). However, different behaviors were observed among these cell lines, and in HL-60 and K-562, time seemed to have limited influence on the effect of the tested doses on cell viability. In contrast, the NB-4 and THP-1 cells presented a more pronounced decrease in cell viability over time, particularly at 72 h. After 24 h of incubation, HEL cells required the lowest concentration of AZD-7648, showing an IC50 ranging between 150 µM and 200 µM  failed to achieve a 50% decrease in cell viability. However, following 48 and 72 h of incubation required the lowest concentrations for these time points, resulting in IC50 values of 92.6 µM and 81.6 µM, respectively. Like this cell line, in KG-1 cells, a 50% decrease in cell viability was not reached at the tested concentrations at 24 h. At 48 h, a decrease in viability of approximately 50% was obtained with the 200 µM dose, yet the mathematical IC50 was only reached at 72 h, with a value of 159.9 µM.The effects of AZD-7648 on cell density and viability are represented in d 200 µM b. After p < 0.001; KG-1: 7.9-fold, p < 0.001) and late apoptotic/necrotic cells  was observed in both cell lines. This increase was linked to a decrease in the percentage of viable cells (p < 0.001). In the LAMA-84 cell line, treatment with 100 µM of AZD-7648 led to an increase in the percentage of early apoptotic (2.8-fold) and late apoptotic/necrotic  cells, compared to untreated cells. The treatment with 200 µM of the inhibitor significantly increased the early and late apoptotic LAMA-84 cells . The effect of the highest tested dose was evaluated in the cell lines where the IC50 was not reached . Mainly, the K-562 and THP-1 cells treated with 200 µM of the inhibitor showed a decrease in viable cells, accompanied by a significant increase of 2.6-fold (p < 0.001) and 1.7-fold (p < 0.05) in the early apoptotic and 2.1-fold (p < 0.01) and 2.4-fold (p < 0.01) in the late apoptotic/necrotic cells, respectively, compared to the control. Despite the absence of statistical difference, a 2-fold increase in the late apoptotic/necrotic population was noticeable in the HL-60 and NB-4 cells following inhibitor treatment  . No statreatment a. In agreement with these results, cells treated with AZD 7648 showed morphological aspects typical of apoptosis, like blebbing, nuclear fragmentation, and cellular contraction b. After 50 was reached , further supporting apoptosis as the main cell death mechanism due to a significant increase in cleaved PARP and activated caspase-3-positive cells (p < 0.001) was observed after treatment with 50 µM and 150 µM of AZD-7648, respectively, compared to untreated cells. Similarly, in the LAMA-84 cell line, the inhibitor increased the percentage of cells with cleaved PARP . In the KG-1 cell line, after 48 h of treatment, similar results were observed, with a 2.6-fold, and 7.8-fold (p < 0.001) increase in the cleaved PARP levels after treatment with 100 µM and 200 µM, respectively. Likewise, an increase in activated caspase-3-positive cells was observed after 24 h of treatment  compared to the control. The KG-1 cell line presented a similar trend after 48 h of treatment with 100 µM and 200 µM of AZD-7648, increasing the percentage of activated caspase-3 cells by 4.9-fold and 13.3-fold (p < 0.001), correspondingly. Afterwards, we quantified the levels of cleaved PARP and activated caspase-3 in the cell lines where the ICve cells a. Followp < 0.01) for 24 h. The tested doses in LAMA-84, 100 µM, and 200 µM increased γH2AX-positive cells by 1.9-fold and 4.4-fold (p < 0.001), respectively. For the KG-1 cell line, treatment with 100 µM and 200 µM of AZD-7648 for 48 h led to similar increases in γH2AX-positive cells .As represented in 0/G1 phase, leading to an increased percentage of cells in this cell cycle phase compared to untreated cells. The treatment with the IC25 dose induced a significant increase in the proportion of cells in the G0/G1 phase in HEL , KG-1 , and LAMA-84  cells. A similar trend in cell cycle distribution was observed for these cell lines after exposure to higher doses . The HL-60, NB-4 and THP-1 cell lines exhibited a significant increase of 2.2-fold (p < 0.001), 1.9-fold (p < 0.001), and 1.3-fold (p < 0.001), correspondingly, in G0/G1 cells after the treatment with 200 µM of AZD-7648. On the contrary, in K-562 cells, the cell cycle distribution remained similar between the control and treated cells. Additionally, the presence of an apoptotic peak (Sub-G1), corresponding to the DNA fragmentation typical of apoptotic cells, was observed across all tested concentrations of AZD-7648, except in HL-60, particularly in the HEL cells treated with 150 µM (p < 0.01) and KG-1 cells treated with 200 µM (p < 0.01), thus reinforcing the induction of apoptosis as demonstrated in previous studies  hours of treatment with AZD-7648 . This DN studies .p < 0.001; LAMA-84: 6.7-fold, p < 0.01). In the KG-1 cell line, treatment with 100 µM and 200 µM of the inhibitor for 48 h resulted in significant decreases of 8-fold (p < 0.05) and 9-fold (p < 0.01) in cell proliferation, respectively.The incorporation of BrdU, a marker for cell proliferation, was assessed in the LAMA-84, HEL, and KG-1 cell lines after treatment with different concentrations of AZD-7648 for 24 h, or 48 h in the case of KG-1 . CompareSignificant progress has been made in the CML and AML treatment options. However, CML patients develop resistance or are intolerant to tyrosine kinase inhibitors  and AML Of the tested cell lines, the cellular density and viability decrease induced by AZD-7648 was more evident in the LAMA-84, HEL, and KG-1 cell lines. A decrease in cell viability after treatment with a DNA-PK inhibitor was also observed in previous studies . As prevBRCA1, RAD51D, PAXIP1, and RBBP8), three of which are only mutated in this cell line. Considering that the HR repair pathway is responsible for the accurate repair of DSBs [BCR-ABL1. This fusion gene has been linked to resistance to apoptosis and the down-regulation of DNA-PKcs, leading to deficient DNA repair [The NB-4 cell line also presented high γH2AX levels. This cell line has the highest number of mutated genes related to HR repair  repair pathways, was associated with high basal levels of MNi . Among tg DNA-PK ,7, as weg DNA-PK ,39. The MLH3 in the LAMA-84 cell line. Elevated methylation levels were mainly detected in the direct reversal damage repair gene (MGMT). The copy number amplification potentially triggers the increased expression of corresponding MMR proteins. This increase could result in a more effective MMR pathway, increasing the cell’s capacity to repair DNA mismatches and errors caused by DDR inhibitors. Furthermore, MMR and HR pathways are connected, and studies showed that MMR proteins, such as MSH2 and MSH3, are involved in HR repair choice [The HL-60 and K-562 cell lines, closely followed by the NB-4 and THP-1 cells, demonstrated resistance to AZD-7648. As is known, the same type of DNA damage can be repaired by different repair pathways, thus showing the redundancy in DNA repair ,41,42. Tr choice ,44. ThisA previous study proved that a population of p53-deficient cells was not sensitive to DNA-PK inhibition . This woTP53 gene were detected in all cell lines; however, the nature and severity of these mutations varied depending on the specific cell line. In the case of the HL-60 cell line, the extensive deletion of the TP53 gene was detected [TP53 expression. In the KG-1 cell line, the TP53 mutation originated from a substitution in a non-coding region that functions as a splice donor site. In the HEL and NB-4 cells, a missense mutation led to the replacement of one amino acid, and the SIFT (Sorting Intolerant From Tolerant) score predicted that the mutations are likely to have a harmful or damaging effect on the protein’s function. For the K-562 and THP-1 cell lines, the TP53 mutation resulted in a frameshift due to an insertion or deletion, respectively. Notably, these mutations in the above-mentioned five cell lines are located within the p53 DNA binding domain. Lastly, in LAMA-84 cells, a nonsense mutation is found in the p53 tetramerization domain, which could account for the observed lower molecular weight of p53 in this cell line. All these mutations are considered oncogenic  or likely oncogenic .Genetic alterations in the detected  and corrAs previously shown by Fok et al., the treatment with AZD-7648 induces apoptosis . We also0/G1 phase. Cell cycle arrest in this phase allows cells to repair damaged DNA or follow the apoptotic pathway [0/G1 and reduction in BrdU incorporation after treatment with a DNA-PK inhibitor were also previously observed by Hafsi et al. [Besides the cytotoxic effect observed after treatment with AZD-7648, this inhibitor also presented a cytostatic effect. This effect was observed as an increase in the percentage of cells in the Gi et al. . The cyti et al. ,50. In a50 values of less than 3 nM and 14 nM, respectively [50 values of 21 nM and 13 nM, respectively [50 of 0.6 nM), AZD-7648 also presents a high selectivity against closely related kinases  [While previous works explored the potential of DNA-PK inhibition as a therapeutic pathway in AML, limited effects were observed when treating the cell lines only with this inhibitor ,52,53. Iectively ,54. CC-1ectively . In the , PI3Kδ) ,21. ThisAlthough this study gives information about the therapeutic potential of AZD-7648 in myeloid leukemias, it is essential to identify some limitations that could provide direction for future research. Firstly, this study used in vitro cell culture models, which do not fully represent the complexity of leukemia in a living organism and the diversity of genetic and molecular alterations found in patients. Therefore, future research could use primary cell line cultures and in vivo studies to better assess the drug’s effectiveness and safety. Furthermore, in this study, a human lymphocyte cell line was used as the model for normal cells, instead of a myeloid cell line. This choice was due to the difficulties associated with establishing and maintaining normal myeloid cell lines, making the lymphocyte cell line a better alternative. Secondly, at the tested concentrations, AZD-7648, in addition to inhibiting DNA-PK, may also present off-target effects on other kinases involved in DSB repair, such as ATM and ATR. Hence, in future studies, it would be valuable to investigate the status and activity of these proteins to clarify the mechanism of action of this drug at the tested concentrations. Lastly, the differences in drug sensitivity observed among the tested cell lines highlight the heterogeneity of leukemia cells and the specific factors influencing these differences should be studied.6 cells/mL and maintained at 37 °C in a humidified atmosphere containing 5% CO2. The cell lines were negative for Mycoplasma and were authenticated using short tandem repeat analysis.We used two CML in blast crisis cell lines (K-562 and LAMA-84) and five AML cell lines: HEL (human erythroleukemia), HL-60 (acute myeloid leukemia), KG-1 (human erythroleukemia), NB-4 (acute promyelocytic leukemia), and THP-1 (acute monocytic leukemia). K-562, HEL, HL-60, and KG-1 were purchased from the ATCC, and LAMA-84, NB-4, and THP-1 were purchased from the German Collection of Microorganisms and Cell Cultures (DSMZ). Additionally, an immortalized normal human lymphocyte cell line (IMC) was used and obtained from the Cytogenetics and Genomics Laboratory, Faculty of Medicine, University of Coimbra. All the cells were cultured in Roswell Park Memorial Institute 1640 medium  supplemented with 10% or 20% (IMC) of heat-inactivated fetal bovine serum , 2 mM of L-glutamine, 100 U/mL of penicillin, and 100 μg/mL of streptomycin . Cells were grown at initial densities of 0.3 (HL-60), 0.4 (HEL and NB-4), or 0.5  × 10AZD-7648 (AZD—DNA-PK inhibitor) was purchased from MedChemExpress and was prepared in dimethyl sulfoxide (DMSO). Cell lines were incubated in the absence or presence of increasing doses of AZD-7648, ranging from 10 to 200 µM, for different periods depending on the assay. The stocks were prepared in the medium on the day of use to avoid DMSO cytotoxicity and ensure consistency between conditions.https://cancer.sanger.ac.uk/cell_lines accessed on 10 August 2023. The genes were grouped according to human DNA repair genes (mdanderson.org accessed on 10 August 2023). The oncogenic classification and the mutations coding impact were obtained from two databases, the Franklin by Genoox  and the Varsome (https://varsome.com/ accessed on 10 August 2023). Lastly, the SIFT and PolyPhen scores and predictions were gathered from the Variant Effect Predictor (https://useast.ensembl.org/Homo_sapiens/Tools/VEP accessed on 10 August 2023). The DDR pathways mutations data were retrieved from the COSMIC platform, available at MS-MLPA (ME011) probe panel was applied as described in the manufacturer’s protocol . This panel determines the methylation status of selected GCGC sites in the promoter regions of human repair genes. It also detects deletions or duplications in the human 3′ region of these genes. Succinctly, 100 ng of each DNA sample was used, and the amplification products were detected and measured using capillary electrophoresis on an ABI-3500 genetic analyzer . Subsequently, the results were evaluated using Coffalyser software version v.220513.1739 . Each MS-MLPA assay also included three control DNA samples obtained from healthy individuals and negative control (no template control). Methylation analysis involved the identification of distinct methylation ranges: demethylation (0–9%), hemi-methylation (10–50%), and methylation (51–100%). For copy number analysis, a value below 0.8 was categorized as deletion (copy number loss), while a value surpassing 1.2 was categorized as duplication (copy number gain).CHEK2, PARP1, PRKDC, RAD51, TP53, and XRCC6) was evaluated by qPCR  in a QuantStudio™ 3 System . Hypoxanthine phosphoribosyltransferase (HPRT) was used as the endogenous control gene. Relative gene expression was calculated using the 2−ΔΔCt formula, and the results represent the fold change mean ± SEM of three independent experiments. The total RNA of the seven cell lines was extracted using TripleXtractor  and converted to cDNA using Xpert cDNA Synthesis Kit (GRiSP), according to the manufacturer’s protocol. Expression of six DDR genes . Afterwards, cells were stained with 1 µL of anti-γH2AX antibody  for 20 min, in the dark, at room temperature. Lastly, cells were washed, resuspended in PBS, and analyzed in a FACS Calibur flow cytometer (Becton Dickinson). Through CellQuest software v.3.3 (Becton Dickinson), 50,000 cells were acquired, and data were analyzed using Paint-a-Gate software v.3.0 (Becton Dickinson). The results were expressed in mean fluorescence intensity  and represented mean ± SEM of three independent experiments.The γH2AX expression levels were evaluated through flow cytometry. Briefly, 0.5 × 10Chromosomal damage biomarkers were evaluated using the cytokinesis-block micronucleus cytome assay. Cell lines were cultured at their optimal density and incubated for 24 h with 4.5 µg/mL or 3 µg/mL (NB-4) of cytochalasin-B . Cells were then treated and analyzed as described by Costa et al. . Chromos−ΔΔCt formula. The results represent the fold change mean ± SEM of three independent experiments.The genomic DNA used was isolated using the salting out method. According to the manufacturer’s instructions, the telomere length of the tested cell lines was assessed using Relative Human Telomere Length Quantification qPCR Assay Kit . Briefly, two primer sets were used: the telomere primer that recognizes and amplifies telomere sequences and the single copy reference primer that serves as a reference for data normalization. Equal amounts of DNA (5 ng/µL) were used for each reaction. qPCR reactions were performed in a QuantStudio™ 3 System . The telomere length of the IMC cell line was used as a reference for calculating telomere length. Relative telomere length was calculated using the 22O2   in a humidified atmosphere containing 5% CO2. The repair capacity of double-strand breaks was evaluated by assessing its kinetics through the expression levels of γH2AX. Following the genotoxic exposure, the cell suspensions were harvested, centrifuged for 5 min at 42× g, and cultured in a new medium. Then, at 1 h and 24 h post-exposure to H2O2, 0.5 × 106 cells were collected and subjected to a 5 min PBS wash at 300× g. The levels of γH2AX were quantified using the intracellular staining protocol outlined in The cell lines were cultured at their optimal density and were exposed, for 30 min, to HThe trypan blue exclusion assay assessed cell density and viability for 72 h. Briefly, after every 24 h of incubation, an aliquot of cells was harvested and stained with an equal volume of trypan blue (Sigma-Aldrich), loaded in a hemocytometer, and counted resorting to the Countess™ II Automated Cell Counter (ThermoFisher Scientific). The instrument automatically calculates cell density and viability based on the number of viable cells per mL or the percentage of viable cells, respectively. The results were expressed as mean ± SEM of five independent experiments.6 cells were collected and washed with PBS by centrifugation at 1000× g for 5 min. Afterwards, cells were resuspended in 100 μL of AV binding buffer and incubated with 5 μL of AV-APC  and 1 μL of PI (Biolegend) for 15 min in the dark at room temperature. Cells were then diluted in 300 µL of AV binding buffer, and the analysis was run on a FACSCalibur (Becton Dickinson) flow cytometer. Through CellQuest software v.3.3 (Becton Dickinson), 50,000 events were acquired, and data were analyzed using Paint-a-Gate (Becton Dickinson). Results were expressed as a percentage of viable cells (AV−/PI−), early apoptotic (AV+/PI−), late apoptotic/necrotic (AV+/PI+), and necrotic cells (AV−/PI+) and represent the mean ± SEM of five independent experiments. Cell death was assessed using flow cytometry, through annexin V (AV) and propidium iodide (PI) double staining, and by morphological analysis using optic microscopy. Succinctly, after 24 h or 48 h (KG-1) of incubation in the absence or presence of 50 µM, 100 µM, 150 µM, or 200 µM of AZD-7648, 0.5 × 106 cells from the different conditions were collected and seeded in glass slides. The smears were subjected to staining and analysis following the procedures defined by Lapa et al. [For morphological analysis, 1 × 10a et al. .6 cells were collected and washed with PBS by centrifugation for 5 min at 1000× g. The cells were fixed by incubation at 4 °C for 30 min with 200 μL of 70% ethanol solution added during vortex agitation. Afterwards, cells were washed with PBS, resuspended in 300 µL of propidium iodide/RNase, and analyzed on a FACSCalibur flow cytometer (Becton Dickinson). Cell cycle distribution was analyzed using ModFitLT Software v. 2.0 . Results were expressed as the percentage of cells in the different cell cycle phases  according to propidium iodide fluorescence intensity and represent the mean ± SEM of five independent experiments. When present, apoptotic cells were identified as a sub-G1 population.Cell cycle analysis was performed using flow cytometry using a propidium iodide/RNase cell cycle analysis kit (Immunostep). Cells were grown in the absence or presence of 50 µM, 100 µM, 150 µM or 200 µM of AZD-7648 for 24 h or 48 h (KG-1). Then, 1 × 1050 was reached, particularly LAMA-84, HEL, and KG-1. After 24 h or 48 h (KG-1) of treatment with different concentrations of AZD-7648, 1 × 106 cells were washed, fixated, and permeabilized using BD Citofix Perm solution. Three hours before the end of this incubation, the cells were labeled with BrdU at 37 °C. Cells were stained with anti-cleaved PARP (PE), anti-activated caspase 3 (FITC), anti-H2AX (Alexa Fluor™ 647), and anti-BrdU (PerCP-Cy5.5). These markers were analyzed using flow cytometry in a FACSCalibur cytometer (Becton Dickinson). Results represent the mean ± SEM of five independent experiments and are expressed as the percentage of positive cells for each molecular marker.The Apoptosis, DNA damage, and Cell Proliferation Kit  and anti-activated caspase 3 (BD Pharmingen) were used to analyze molecular markers of apoptosis, DNA damage, and cell proliferation, according to the manufacturer’s instructions. This method was exclusively performed in cell lines where the IC50 was calculated to the data concerning the exposure of cells at 24, 48, and 72 h, and the determination was performed by a non-linear curve fit dose-response. The normality of the samples was assessed using the Shapiro–Wilk test. Statistical significance was determined using a range of methods. These included unpaired t-tests (with or without Welch’s correction), one sample t test, Wilcoxon signed-rank test, the Mann–Whitney test, and ordinary one-way ANOVA. Following the ANOVA, either Tukey’s or Dunnett’s multiple comparisons tests were used. Moreover, Welch and Brown–Forsythe ANOVA, followed by Dunnett’s T3 multiple comparisons test, and Kruskal–Wallis test, followed by Dunn’s multiple comparisons test were also used. One-way ANOVA for repeated measures followed by Tukey’s multiple comparisons test or the Friedman test followed by Dunn’s multiple comparisons test was used to evaluate the effects of H2O2 through time. In this study, a significance level of p < 0.05 was considered statistically significant. All values were expressed as the mean ± SEM of the number of independent experiments (indicated in the figure legends).Statistical analysis was performed in GraphPad Prism 9 software . The ICIn conclusion, these results using CML and AML models support the further investigation of the potential of AZD-7648 as a new therapy for myeloid leukemias. The tested cell lines presented different drug sensibilities, showing that the value of this therapy may depend, for example, on the patient’s genetic background, the expression of specific genes, and DDR efficiency and damage at the baseline level. Therefore, subsequent studies are necessary to determine with more precision what may confer sensitivity to this inhibitor. However, this work opens up the possibility of testing new combination schemes with other agents using lower doses that could synergistically induce a cytostatic and cytotoxic effect and overcome the resistance to AZD-7648. Lastly, studies that would assess the therapeutic potential of AZD-7648 in combination with conventional therapy may also help to elucidate this inhibitor’s promise further, considering that previous studies already showed the advantage of combining this drug with other DDR inhibitors, chemotherapy, or radiation ,53,59,60


At present, the influence of the internal metallic endoskeleton of Spacer on the biomechanical strength of Spacer remains unclear. The aim of this study was to analyze the mechanical stability of a novel Spacer applying a annular skeleton that mimics the structure of trabecular bone using finite element methods.The femur models of three healthy individuals and skeletonless Spacer, K-Spacer, and AD-Spacer were assembled to create 15 3D models. Finite element analysis was performed in an Ansys Bench2022R1. Biomechanical parameters such as stress and strain of the Spacer, internal skeleton and femur were evaluated under three loads, which were applied with the maximum force borne by the hip joint (2100 N), standing on one leg (700 N), and standing on two legs (350 N). The mechanical properties of the new hip Spacer were evaluated.The stresses on the medial and lateral surfaces of the AD-Spacer and K-Spacer were smaller than the stresses in the state without skeletal support. The maximum stresses on the medial and lateral surfaces of the AD-Spacer were smaller than those of the inserted K-Spacer, and the difference gradually increased with the increase of force intensity. When the skeleton diameter was increased from 3 to 4 mm, the stresses in the medial and lateral sides of the AD-Spacer and K-Spacer necks decreased. The stress of both skeletons was concentrated at the neck, but the stress of the annular skeleton was evenly distributed on the medial and lateral sides of the skeleton. The mean stress in the proximal femur was higher in femurs with K-Spacer than in femurs with AD-Spacer.AD-Spacer has lower stress and higher load-bearing capacity than K-Spacer, and the advantages of AD-Spacer are more obvious under the maximum load state of hip joint. Total hip arthroplasty (THA) is the ideal treatment for advanced hip disease, achieving remarkable results in relieving pain, correcting deformity, and improving joint mobility. Periprosthetic joint infection (PJI) is a catastrophic complication after prosthetic joint replacement, with an incidence of 0.4–1.44% . PJI meaThe use of Spacer containing antibiotics maintains hip stability, lower extremity length and patient mobility while the infection is eradicated –10 SpaceToday, studies on the mechanical strength of the Spacer are imperfect and controversial. Schollner et al.  performeFor this purpose, our team has developed a two-layer Spacer Antibiotic Delayed Release System (AD-Spacer) with an applied ring skeleton. Inside it can be placed antibiotic-loaded calcium sulfate. The long-term and massive release of antibiotics from calcium sulfate for the treatment of periarticular prosthetic infections has been demonstrated . And an Three healthy participants between the ages of 20 and 60 years without any history of hip trauma, hormone use, or chronic alcohol use were used in this study Table . 3D modeThe surface errors such as spikes, intersections etc. of the femur models were corrected using Geomagic Studio 10 software (Raindrop Inc. USA). After these corrections, the 3D smooth solid model was developed and imported into SolidWorks program  in STEP format.The smoothed femurs were imported into SolidWorks software  in STEP format. The head and neck of the femoral solid model were cut off 2 mm above the base of the femoral neck and perpendicular to the femoral neck.  , 24. . With the increase of force intensity, the difference gradually increased. Fig. A Under aAs the diameter of the skeleton increased, the stress on the medial and lateral sides of the Spacer neck also decreased.K-Spacer internal skeleton increased from 3 to 4 mm. The medial wall stress of Spacer decreases by 1.18%, 4.43% and 3.94%, respectively, under the load of 2100 N, 700 N and 350 N. The lateral wall stress decreases by 0.44%, 3.05% and 9.98% under the load of 2100 N, 700 N and 350 N, respectively.  Fig. B.From the cloud diagram, the stresses of the AD-Space, K-Spacer and skeletonless Spacer were all concentrated in the neck, but the stress distribution of the AD-Spacer was more uniform Fig. .The maximum stress of the internal metal skeleton is proportional to the magnitude of the force applied, and the maximum stress of the annular skeleton is smaller than that of the Kirschner wire monolayer skeleton. Figure  CThe strComparing the Von Mises stresses of the two endoskeletons, under the same load, the stress carried by the 3 mm endoskeletons was less than that carried by the 4 mm endoskeletons. (P < 0.05) the hip joint is subject to multiple muscles and ligaments pulling in the normal state, this experiment simplified force model was used for finite element analysis; (2) this experiment will femur assumed as Homogeneous, isotropic material. This is different from the actual bone material properties of non-homogeneous, anisotropic different (3) The hip joint is subjected to cyclic loading in daily life, and only a few of its several static loads mechanical strengths under static loads. Regarding the new Hip Spacer of mechanical strength of the related issues. and the incidence of complications remain to be further investigated through various experiments and clinical analysis of large samples.It was shown that the AD-Spacer with simulated bone trabecular structure had higher stress compared to the conventional K-Spacer, while the AD-Spacer with applied annular skeleton had better weight-bearing capacity. The AD-Spacer has less chance of fracture than the K-Spacer and the skeletonless Spacer. It is our future research direction to Further optimization of Spacer structure and apply the high strength material into the skeleton of AD-Spacer to achieve the normal function of patient Spacer implantation.


In vitro analysis revealed that inhibition of PVT1 impeded the proliferation, migration, and colony formation of ESCA cells, increased the expressions of p-RIP1 and p-MLKL and promoted necroptosis. By contrast, PVT1 overexpression resulted in a decrease in necroptotic cell death events, thus promoting tumor progression. Collectively, the established 6-NRLs panel was a promising biomarker for the prognostic prediction of ESCA. Moreover, our current findings provided potential targets for individualized therapy for ESCA patients.Necroptosis is a newly identified programmed cell death associated with the biological process of various cancers, including esophageal carcinoma (ESCA). Meanwhile, the dysregulation of long non-coding RNAs (lncRNAs) is greatly implicated in ESCA progression and necroptosis regulation. However, the lncRNAs involved in regulating necroptosis in ESCA are still unclear. In this study, we aim to explore the expression profile of necroptosis-related lncRNAs (NRLs), and evaluate their roles in ESCA prognosis and treatment. In the present study, 198 differentially expressed NRLs were identified between the ESCA and adjacent normal tissues through screening the data extracted from the Cancer Genome Atlas (TCGA) database. And, a prognostic panel consisting of 6 NRLs was constructed using the LASSO algorithm and multivariate Cox regression analysis. The ESCA patients with high risks had a markedly reduced survival time and higher mortality prevalence. Moreover, C-index of 6 NRLs-panel was superior to 48 published prognostic models based on lncRNAs or mRNAs for ESCA. There were significant differences between the high-risk and low-risk groups in tumor-related pathways, genetic mutations, and drug sensitivity responses.  As one of the most common gastrointestinal tumors worldwide, esophageal carcinoma (ESCA) is often associated with delayed diagnosis and inferior outcomes , 2. At pAs a newly identified programmed cell death, necroptosis is regulated by TNF-α and RIPK1/RIPK3-dependent phosphorylation of MLKL , 9, and Long non-coding RNAs (lncRNAs) are a group of special non-coding RNAs with transcript lengths over 200 nucleotides , which aLncRNA plasmacytoma variant translocation 1(PVT1) is located on chromosome 8 of the c-Myc gene and is abnormally expressed in multiple malignancies, including nasopharyngeal carcinoma , colorecIn the present work, we thoroughly explored the expression pattern of NRLs in ESCA and established a prognostic panel based on six NRLs by least absolute shrinkage and selection operator (LASSO) and multi-Cox regression. Moreover, we assessed its predictive value using principal component analysis (PCA), time-dependent receiver operating characteristic (ROC), concordance index (C-index), nomogram, tumor mutational burden (TMB) analysis, and chemotherapy response analysis of ESCA patients. Besides, we further performed the gene set enrichment analysis (GSEA) to explore its underlying mechanisms. Finally, the expression of one NRL, PVT1, in ESCA cells was detected, suggesting its role in necroptosis. Collectively, these data provided valuable insights into the progression and prognosis of ESCA.https://portal.gdc.cancer.gov/), and their corresponding transcriptomic FPKM data, somatic mutations, and clinical information were also collected. Patients with missing information on survival time or those with survival time < 1 month were excluded from the analysis. In addition, 159 necroptosis-related genes (NRGs) were acquired from the Kyoto Encyclopedia of Genes and Genomes   .https://metascape.org/gp/index.html#/) was adopted to conduct the functional enrichment analysis and protein-protein interaction (PPI) network of DE-NRGs. Besides, NRG mutations were also assessed in ESCA using the cBioPortal website .The DE-NRGs between ESCA and adjacent normal tissues were identified using the “limma” package. Subsequently, Metascape  were identified using Pearson correlation analysis  based on their expression. Subsequently, DE-NRLs were screened using the “limma” package.The optimal panel of prognostic NRLs was determined using the LASSO-Cox algorithm, and a corresponding prognostic panel was constructed. In the meantime, we equally divided all patients into training and testing groups, the risk score of each patient with ESCA was calculated using the formula as follows:Coef (i) represents the coefficient, and x(i) represents the standardized level of each NRL. According to the median risk score of each patient, all patients were categorized into low-risk and high-risk groups. Subsequently, the predictive capacity of the 6-NRLs prognostic panel was assessed for various clinicopathological characteristics by the log-rank method. Besides, a nomogram was generated, and the 1-, 3- and 5-year recurrence rates of ESCA patients were predicted based on such a nomogram.We retrieved the published prognostic signatures of ESCA constructed based on lncRNAs or mRNAs since 2017 using multiple databases. Then, “timeROC” and “survcomp” packages were applied for model comparison to evaluate the predictive ability of each model.The potential enrichment pathways among different risk groups were identified using the GSEA with the “clusterProfiler” package. Moreover, “maftools”, “survival,” and “survminer” were applied to reveal the difference and survival of the TMB between the above-mentioned two groups of patients.The “pRRophetic”, “ggpub”, and “ggplot2” packages were used to identify the potential chemotherapeutic drugs that might be applied for ESCA therapy. Moreover, the Wilcoxon signed-rank test was adopted to determine the half-maximal inhibitory concentration (IC50) of common compounds between high-risk and low-risk groups.2. TSZ   and necrostatin-1  were used as previously described [The human esophageal epithelial cells (HEECs) and human esophageal cell lines, including ECA109, KYSE150, and KYSE510, were maintained in RPMI-1640 medium  supplemented with 10% fetal bovine serum  and penicillin-streptomycin cocktail  at 37° C in a humidified atmosphere containing 5% COescribed .−ΔΔCt method. Total RNA was isolated from the cells using TRIzol Reagent . Subsequently, purified RNA was reversely transcribed to cDNA using HiScript III RT SuperMix . RT-qPCR was performed using ChamQ Universal SYBR qPCR Master Mix . The PVT1 plasmid was adopted as a positive control, while the negative control contained all components except for cDNA. Each experiment was carried out three times. GAPDH was employed as the housekeeping gene. The relative expression of PVT1 was determined using the 2^For PVT1 overexpression, the full-length sequence of PVT1 was synthesized and cloned into the pcDNA3.1(+) vector . The shRNAs targeting PVT1 were synthesized by Sangon Biotech Co., Ltd. , and To conduct migration assays, uncoated transwell inserts with 8 μm pores were inserted into 24-well plates. Next, we added 700 μl of RPMI-1640 medium with 20% FBS to each lower chamber, and a total of 5×104 infected ECA-109, KYSE-150, or KYSE-510 cells were resuspended in 200 μl serum-free medium in each upper chamber. The remaining cells in the upper chamber were wiped clean with a cotton swab after 24 hours of incubation (48 hours for KYSE-510 cells) at 37° C, 5%CO2. The bottom membrane with invaded cells was fixed with 4% paraformaldehyde and dyed with 0.1% crystal violet  for 30 min, respectively. The migrated cells were counted in five random fields at 200× magnification using ImageJ software. The results were expressed as the mean number of migrated cells per field.For colony formation assay, 1000 infected ECA-109, KYSE-150, or KYSE-510 cells were inoculated into the six-well plates and incubated for 12 days at 37° C, 5% CO2. When clones were visible to the naked eye, the cells were washed with phosphate-buffered saline (PBS) twice and fixed with 4% paraformaldehyde for 20 min. When clonal colonies were visible (≥ 50 cells/colony), the cells were washed twice with phosphate-buffered saline (PBS) and fixed with 4% paraformaldehyde for 20 minutes, followed by staining with 0.1% crystal violet solution for 30 min. After being air-dried, the colonies were photographed and counted.To evaluate the proliferative capacity of infected cells, a cell counting kit-8 (CCK-8) experiment was conducted. Specifically, infected ECA-109, KYSE-150, or KYSE-510 cells were inoculated into 96-well plates at a density of 3000 cells per well for proliferation for 0, 1, 2, 3, 4, and 5 days, then 10ul CCK-8 reagent  was added to each well and incubated for 2 h at 37° C. for 2 hours. The absorbance at 450 nm was measured using a microplate reader .Briefly, ESCA cells under different treatments were rinsed with cold PBS two times and then lysed using RIPA buffer  containing protease inhibitors  and phosphatase inhibitors . Moreover, the contents of soluble proteins were determined by the BCA protein detection kit . Subsequently, Western blotting analysis was carried out as previously described  using anhttps://portal.gdc.cancer.gov/) and KEGG website (https://www.kegg.jp/). Other details are available from the corresponding author upon a reasonable request.The data supporting the conclusions of this study could be acquired from TCGA database , Nutlin.3a (Rebemadlin), BIRB.0796 (Doramapimod), and PD.0332991 , in the low-risk group, were higher compared with the high-risk group , while tIn vitro experiments revealed that depletion of PVT1 significantly inhibited the proliferation and migration of ECA-109 and KYSE-150 cells compared with the controls  based on LASSO and multi-Cox regression. Simultaneously, a nomogram, internal testing cohort, PCA, and TMB analysis were adopted to assess the validity of the prognostic panel. Besides, we further investigated the predictive capability of this prognostic model in various clinicopathological features and multiple prognostic signatures. The results showed that regardless of age, sex, grade, and other clinicopathologic indicators, the prognosis model could effectively divide ESCA patients into low- and high-risk groups. On the other hand, this 6-NRLs panel has more predictive power than other prognostic models. Overall, our results showed that the 6-NRLs prognostic panel had a good performance in predicting the prognosis of ESCA patients.As one of the most common malignant tumors worldwide, ESCA originates from the esophageal mucosa epithelium. Some studies have confirmed that the dysregulation of lncRNAs is extensively involved in the biological processes of ESCA, including proliferation, apoptosis, metastasis, angiogenesis, and treatment resistance , 40, 41.To further investigate the underlying molecular mechanisms of the signature, the GSEA was carried out between different risk groups. The signaling pathways related to metabolisms, such as the TCA cycle, ribosome, glycosaminoglycan degradation, mTOR signaling pathway, and primary bile acid biosynthesis, were mainly enriched in the high-risk group. Conversely, TGF, notch, pentose phosphate, and Hedgehog pathways were enriched in the low-risk group. It has been found that the inhibition of mitochondrial oxidative phosphorylation mediated via clomipramine helps restrain ESCC progression . The mutIn vitro analysis revealed that overexpression of PVT1 facilitated the proliferation, migration, and colony formation in ESCA cells, and depletion of PVT1 effectively alleviated this phenotype. Interestingly, inhibiting PVT1 increased the expressions of p-RIP1 and p-MLKL and enhanced necroptosis, suggesting that PVT1 was a potential NRLs in ESCA.In addition, the functional phenotype of PVT1 in ESCA cell lines was explored through experimental studies. We first verified the expression level of PVT1 from the TCGA database and cell lines. in vitro and in vivo experiments.However, our research has some limitations. First, our results were mainly based on the TCGA dataset. Therefore, other large-scale case series data and clinical samples for external verification are required to further evaluate the applicability of the signature. Second, we only verified that PVT1 was a possible oncogenic lncRNA, while the specific mechanism of necroptosis regulating ESCA is still unclear, and the remaining NRGs and NRLs and more detailed molecular mechanisms need to be further proved via In this study, we constructed a promising prognostic panel consisting of six NRLs, which was not only an independent predictor but also a potential therapeutic target. Furthermore, we also found that PVT1 was a potential regulator of necroptosis, and it participated in the development of ESCA. Collectively, our current findings provided valuable insights into the tumor progression and clinical outcomes of ESCA patients.Supplementary FiguresSupplementary Table 1Supplementary Tables 2 and 3Supplementary Table 4Supplementary Table 5Supplementary Tables 6 and 7