Functional genetic screens to uncover tumor-intrinsic nodes of immune resistance have uncovered numerous mechanisms by which tumors evade our immune system. However, due to technical limitations, tumor heterogeneity is imperfectly captured with many of these analyses. Here, we provide an overview of the nature and sources of heterogeneity that are relevant for tumor-immune interactions. We argue that this heterogeneity may actually contribute to the discovery of novel mechanisms of immune evasion, given a sufficiently large and heterogeneous set of input data. Taking advantage of tumor cell heterogeneity, we provide proof-of-concept analyses of mechanisms of TNF resistance. Thus, consideration of tumor heterogeneity is imperative to increase our understanding of immune resistance mechanisms. The reason that screens have largely been limited to single cell lines in publications is a technical one: to ensure maintenance of library complexity , and thus fidelity and confidence of the hits identified, a(n extremely) large number of cells need to be used in such screens, making the inclusion of multiple cell lines labor-intensive. Despite this limitation, their success and fidelity were demonstrated by virtue of their identification of common pathways by several groups. By and large they comprise the TNF, IFNγ, antigen presentation and autophagy pathways .APOBEC3 activity in late-stage cancers which promotes the stochastic mutation of the tumor genome  hypoxic tissues, such as melanoma, have heightened expression of cIAP1. These tumors therefore display enhanced resistance against TNF . Extendisitivity , 36.+ T cell responses antigen burden and immune resistance mechanisms genomic, transcriptomic and proteomic omics data. At the same time, the screening data should be derived from both in vitro and in vivo screens from as many genetic backgrounds as possible [reviewed in -specific dependencies. Aside from these functional genetic screens, the cell lines used in these studies have also been extensively characterized, including the collection of RNA, DNA, epigenetic, metabolic and drug-sensitivity metrics –72. The Hi cell lines specifically  and RNF31 . By performing this analysis, we could find factors whose ablation reduces viability of TNFnd RNF31 .TRAF2 and BIRC2 to establish resistance to TNF in different tumor cell lines. While it had been difficult to fully comprehend this differential sensitivity before, given that TRAF2 and cIAP1 are thought to signal in a linear fashion, we could now make transcriptomic comparisons between TNFHi cell lines in which both TRAF2 and BIRC2 sensitize, those in which solely BIRC2 knockout sensitizes, those in which solely TRAF2 knockout sensitizes, or those cell lines in which neither the loss of TRAF2 nor the loss of BIRC2 reduces the viability of the affected cell line ? Therefore, and as mentioned above, the true complexity of tumor-immune interactions, and forms and mechanisms of heterogeneity at play require more data to be integrated in these models. Firstly, and perhaps most easy to accomplish, the field should invest in performing more tumor : T cell screens, to complement those that have already been reported in key publications in the recent past , 75, 80.s (as in , 13, in DV performed the analyses. DV and DP wrote the manuscript. All authors contributed to the article and approved the submitted version.


Our dataset has a great potential for re-use given the recent surge in interest surrounding the role of CIN in breast cancer. The large size of the dataset, coupled with the diversity of the cell types represented, provides numerous possibilities for future comparisons.These data show the relative amount of chromosomal instability (CIN) in a diverse array of human breast cell types, including non-transformed mammary epithelial cells as well as cancer cell lines. Additional data is also provided from human embryonic and mesenchymal stem cells. To produce this dataset, we compared a published chromosomal instability gene signature against publicly available datasets containing gene expression information for each cell. We then analyzed these data with the Python GSEAPY software package to provide a CIN enrichment score. These data are useful for comparing the relative amounts of CIN in different breast cell types. This includes cells representing the major clinical (ER/PR Specifications Table1•While CIN is a defining hallmark of cancer, little is known about its relationship with stemness. High levels of CIN are associated with breast cancer evolution and metastasis •These data add value to our original research article by allowing us to assess potential associations between CIN levels and stem-like breast cancer cells and draw important conclusions regarding the impact of CIN on tumor initiation.•The CIN enrichment scores provided in this dataset are useful for comparing the relative amounts of CIN present in different non-transformed and cancer cell lines from the breast.•This dataset may be useful to anyone associated with breast cancer research. CIN is a hallmark of cancer and is well described to play a role in tumor evolution, especially in regards to therapeutic resistance •These data can be used/reused for further insights into associations between CIN levels and numerous additional variables, including cell-of-origin, mutational status, subtype, gene expression, etc.2The deposited dataset consists of two distinct Excel spreadsheets Breast cancer cell lines https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50470HCC38 sorted cells https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA750073We compared these datasets to the CIN signature by first converting FASTQ files to gene-expression matrices and processing so that only the data were retained. Scores were obtained for each cell type by performing single sample gene set enrichment analysis (GSEA) with Python GSEAPY Library software, and the resulting data were processed into Excel format.The resulting spreadsheets are labelled and described as follows:Breast cell lines – Excel spreadsheet listing the CIN enrichment scores for an assortment of breast cancer cell lines as well as non-transformed human cells. Cell names are listed across the top of each column with the corresponding ES and NES scores underneath.HCC38 sorted breast cancer cells – Excel spreadsheet containing the CIN enrichment scores for HCC38 breast cancer cells sorted according to their cell surface EpCAM (Ep) and integrin αvβ3 (b3) status from three independent experiments. Sorted cells from each experiment were divided into four categories: EpCAM low (lo) versus high (hi) and αvβ3 positive (pos) versus negative (neg). Each cell type belonging to a particular experiment was given a unique Run number (SRR) listed across the top of each column. For quick reference, the sorted cell type is included underneath, followed by the ES and NES scores.3Publicly available RNA sequencing data from breast cancer and normal mammary cell lines was obtained from NCBI GEO (GSE50470), while data from sorted HCC38 cell populations was downloaded from the NCBI Sequence Read Archive (PRJNA750073). FASTQs were converted to gene-expression matrices and the files were processed to remove all the header information and only retain the data. The CIN gene signature was acquired from Bakhoum et al. https://gseapy.readthedocs.io/en/latest/). First, input files were read using Python's Pandas library and joined with each other using the ID & amp columns before deleting any unnecessary columns. Ensemble Gene IDs were mapped to their HGNC Symbols using Python's BioMart API (https://pypi.org/project/biomart). Any Ensemble ID which did not have a corresponding HGNC Symbol was dropped. Once we obtained the data frame having HGNC Symbols as rows, samples as columns, and their feature counts as values in all rows, this data frame, along with the CIN gene set was passed to the Single Sample GSEA Python library. The final data comprised 36,866 rows and 106 columns before feeding it into GSEAPY. To determine the enrichment scores (ES), we applied Single Sample GSEA to the final data frame. The experiment was repeated with a normalized version of the data frame, but the normalized enrichment scores (NES) were identical to the ES. GSEAPY output was then processed into Excel format and saved as final results files.To generate the CIN scores for each cell type, we analyzed data with the Python GSEAPY Library (None.We confirm that the authors have read and follow the ethical requirements for publication in Data in Brief and that the current work does not involve human subjects, animal experiments, or any data collected from social media platforms.Shahnawaz A. Baba: Conceptualization, Methodology, Writing – original draft. Shreyas Labhsetwar: Methodology, Formal analysis, Software. Richard Klemke: Methodology, Formal analysis, Software. Jay S. Desgrosellier: Conceptualization, Methodology, Formal analysis, Visualization, Investigation, Supervision, Funding acquisition.


Haloferax mediterranei bacterioruberin-rich carotenoid extracts (BRCE) (0–100 µg/ml) in six BC cell lines, representative of the intrinsic phenotypes and a healthy mammary epithelium cell line. Cell index values were obtained using xCELLigence RTCA System. Furthermore, cell diameter, viability, and concentration were measured at 12 h, 24 h, and 30 h. We found that BC cells were selectively affected by BRCE . After 30 h, the population of BC cells exposed to 100 µg/ml was 11.7–64.6% of the control (p = 0.0001–0.0009). Triple-negative cells were significantly affected [MDA-MB-231  and MDA-MB-468 ]. Cell size was also reduced after 30 h treatment in 3.8 (± 0.1) µm and 3.3 (± 0.02) µm for SK-BR-3 (p < 0.0001) and MDA-MB-468 (p < 0.0001), respectively. In conclusion, Hfx. mediterranei BRCE exerts a cytotoxic effect on BC cell lines representative of all studied intrinsic subtypes. Furthermore, results obtained for MDA-MB-231 and MDA-MB-468 are very promising, considering the aggressive behaviour of the triple-negative BC subtype.Oxidative stress has been linked to the onset and progression of different neoplasia. Antioxidants might help prevent it by modulating biochemical processes involved in cell proliferation. Here, the aim was to evaluate the in vitro cytotoxic effect of  These microorganisms synthesize a rare C50 carotenoid called bacterioruberin (BR) and its derivatives monoanhydrobacterioruberin (MABR) and bisanhydrobacterioruberin (BABR)3. In addition, although to a lesser extent, they also synthesize astaxanthin, zeaxanthin, lycopene, and β-carotene5. Haloferax mediterranei is particularly relevant among haloarchaea since it has been used as a model organism for studying numerous pathways9. Furthermore, its carotenoid production can be easily enhanced by altering cell culture conditions15.Halophilic archaea or haloarchaea are extremophilic microorganisms that require a hypersaline environment to thrive16. Nevertheless, C50 carotenoid properties have not been addressed lately21. Haloarchaeal carotenoids have excellent antioxidant activity28, but there is still scarce information concerning their potential effects on human health. Recent research has revealed that haloarchaeal carotenoids exerted in vitro anticancer activity in a few colorectal, breast, liver, and cervical cancer cell lines20. However, much research needs to be done to support these preliminary results and draw a firm conclusion.Carotenoids are well-known for their health-beneficial properties, including antioxidant, antiproliferative, antitumoral, and immunomodulatory activities29. Breast tumours can be classified into four subtypes according to the presence or absence of hormone receptors (estrogen (ER) and progesterone receptors (PR)) and the overexpression of human epidermal growth factor receptor 2 (HER2) in combination with a set of clinical features. The four subtypes were named luminal A (ER+ PR+ HER2−), luminal B (ER+ PR HER2±), HER2-enriched (ER− PR− HER2+), and triple-negative (ER− PR− HER2−) BC31. Despite the advanced BC treatments in recent years, there is still a need for bioactive compounds that can help in the prevention and/or treatment of this pathology. Hence, this in vitro work aimed to determine if a Hfx. mediterranei BRCE was cytotoxic to BC cell lines representative of each subtype plus a mammary epithelium cell line as a control to evaluate the cytotoxicity in healthy tissue. In addition, we investigated the effect of the BRCE treatment on total viable cell number, cell adhesion, and cell diameter. Thus, this study contributes to the knowledge of the potential therapeutic applications of haloarchaeal carotenoids in BC.Breast cancer (BC) is still the leading cause of death (7%) in women worldwideHfx. mediterranei R-4 (ATCC33500) was grown in a complex medium containing 12.5% (w/v) of inorganic salts32, 0.5% (w/v) yeast extract  and 1.5% (w/v) d(+)-Glucose anhydrous BioChemica . The pH was buffered using 30 mM Tris  and adjusted to a pH of 7.3. Growth conditions included 36.5 °C and shaking at 170 rpm in a shaking incubator  based on the data reported by Montero-Lobato and Giani et al.11. First, cells were incubated as described elsewhere12. Then, cells were centrifuged at 7800 rpm for 30 min to remove the supernatant and were washed twice with a 10% (w/v) inorganic salts solution, plus the last wash with distilled water to remove all remnants of salt and induced cell lysis. Cell pellets were kept at − 20 °C until further use.Panreac AppliChem, Panreac Quimica, Barcelona, Spain) was added to the cell pellets in a ratio of 1 ml of acetone per 10 ml cell culture10. After that, a 4 °C overnight incubation and later centrifugation  were necessary to obtain the BRCE. As a result, BR concentration was calculated as follows10:Pure acetone of HPLC grade . Then, a mammalian cell culture media (DMEM (Dulbecco's modified Eagle's medium) F-12 (1:1) with l-glutamine and 15 mM HEPES  supplemented with 10% fetal bovine serum (FBS) , and 1% penicillin (50 U/ml) and streptomycin (50 mg/ml)  was added to the BRCE up to a final concentration of 150 µg/ml. Sonication with an ultrasonic probe (Branson SFX 550)  was required to ensure total solubilization. Previous assays were carried out to optimize sonication time. Therefore, both the solubilization and stability of the pigments were guaranteed. The samples were kept on ice, and the sonication conditions with microtip were pulsed on-time of 20 s, off-time of 40 s, amplitude of 20%, and a total duration of 4 min. The sonication cycle was repeated with off-times of 5 min between cycles to ensure the cooling of the sample. Filtration using 0.2 µm filters was carried out to guarantee sterilization of the solution before cell treatment.Considering that carotenoids were solubilized in acetone, we aimed to replace this organic solvent with a solution compatible with human cells so that in evaluating the anticancer activity, we could ensure that the pigments caused the effects observed. Therefore, after BR quantification, acetone was removed by evaporation with a centrifugal vacuum concentrator system  medium supplemented with 10% FBS  and 1% penicillin–streptomycin . DMEM F-12 was selected as culture media for all cell lines to reduce variability and to ensure the nutrition requirements of all cell lines, considering that it is one of the most enriched available culture media33. All cell lines were incubated at 37 °C in a humified atmosphere with 5% CO2.One healthy epithelial mammary cell line (184A1) and six human BC cell lines representative of each intrinsic subtype were used in this study : Luminal A (MCF-7 and T-47D), Luminal B (BT-474), HER2-enriched (SK-BR-3), and triple-negative (MDA-MB-468 and MDA-MB-231). Since no analytical studies were carried out to confirm the absence of trace quantities of acetone, 184A1 was used as a control to evaluate the effect of the treatment on non-tumour cells and to normalize the results when compared with tumour cells. They were all grown in a monolayer and maintained as adherent cell cultures in DMEM F-12 with stable Agilent Technologies, San Diego, CA) was used to evaluate cell adhesion over time34. The equipment took measurements every 15 min for 100 h to ensure the achievement of the complete curve.xCELLigence real-time RTCA DP Instrument   using the external computer system RTCA software Pro 2.3.4 . First, background reading was done with DMEM F-12  culture media. Next, cells were seeded to the 16 well microplates . All steps were performed under sterile conditions. Firstly, 25,000, 50,000, and 75,000 cells were seeded to determine the seeding density for the rest of the experiments. The objective was to determine an initial cell density allowing later measurements at different stages of cell growth  in 96-well plates  and DMEM F-12 was used as the positive and negative control, respectively.For this experiment, xCELLigence RTCA was set up according to the manufacturer's instructions. The instrument was placed inside a humidified COCapricorn Scientific; Ebsdorfergrund, Germany). Total cell number, viability, and diameter were analyzed using a CASY OLS cell counter and analyzer (CASY TTT) . Cell adherence was assessed using xCELLigence Real-Time Cell Analysis System. Half maximal inhibitory concentration (IC50) for the total viable cells was calculated using GraphPad 7 Software . In addition, the selectivity index (SI), defined as the ratio of IC50 for normal cells to that for BC cell lines, was calculated to evaluate the toxicity of the BRCE studied against normal cells and to predict their therapeutic potential.Normal mammary epithelium and BC cells were seeded in 96-well cell culture plates with a density of 50,000 cells/well. After 12 h (to ensure complete cell attachment), culture media was removed, and serial concentrations ranging from 10 to 100 µg/ml BRCE were added. DMSO and DMEM F-12 were used as the positive and negative control, respectively. After 12 h, 24 h, and 30 h of treatment, cells grown in each plate well were harvested using trypsin–EDTA (0.05%)  using a 10 ×/0.25 objective.Cell images were acquired with an optical microscope . The differences were considered statistically significant at p-values < 0.05*, < 0.005**, < 0.0005***, < 0.0001****. All experiments were repeated at least three times unless otherwise indicated.Data are expressed as the mean ± standard deviation (SD). Statistical significance was calculated by ANOVA (followed by Dunnet's test for multiple comparisons) analysis using GraphPad 7 software (Hfx. mediterranei BRCE (10–100 µg/ml) on the adhesion of human epithelial mammary and BC cell lines was studied using the xCELLigence RTCA system.In this experiment, the effect of 34. For this reason, this equipment was also used to establish the optimal cell quantity to seed for the subsequent experiments.The curves generated by the cell index representation can give us information about the proliferation dynamics of each cell lineFigure An initial cell density of 50,000 cells was chosen to keep homogeneity because, in most cell lines, this density ensured that three measurements could be made at three stages of growth . However, this number of cells in the BT-474 cell line was excessive for proper measurements, as shown in Fig. In Fig. 50 values at 30 h (Table p < 0.0001).When considering the different intrinsic subtypes, the IC h Table  indicate50 of 184A1 cells could not be calculated since 75% inhibition was obtained with the highest concentration tested (100 µg/ml). Consequently, this concentration was used as IC50 without a better option. Thus, the SI is an underestimation of the real potential value. An SI > 1.0 is considered a favourable value since it indicates a drug with higher efficacy against tumour cells than against normal cells35. Hfx. mediterranei carotenoids present an SI > 2 in MCF-7 and BT-474 cell lines (Table p < 0.0001) was obtained for MDA-MB-231 and MDA-MB-468 cell lines representing triple-negative subtype. Furthermore, the highest concentration tested led to an approximately 60–70% reduction of cell index in these cell lines.A SI was estimated to determine the cytotoxicity of the compound to the normal cells Table . The IC5Of note, perturbance in all curves is observed at 12 h due to plate removal from the equipment to add treatment.p < 0.0001), 1.3 (± 0.2) µm (T-47D) (p = 0.006), 1.5 (± 0.1) µm (BT-474 25K) (p = 0.0006), 1.8 (± 0.2) µm (SK-BR-3) (p < 0.0001), 1.2 (± 0.3) µm (MDA-MB-468) (p = 0.02) and 1.5 (± 0.2) µm (MDA-MB-231) (p = 0.0005) at the highest concentration (100 µg/ml) , 3.8 (± 0.1) µm (SK-BR-3) (p < 0.0001), 3.3 (± 0.02) µm (MDA-MB-468) (p < 0.0001), 1.8 (± 0.1) µm (MDA-MB-231) (p < 0.0001), and except for 1.3 (± 0.1) µm (T-47D) (p = 0.0005), and 1.4 (± 0.3) µm (BT-474 25K) (p = 0.0001), whose diameters remained constant.Regarding human mammary epithelial cells (184A1), after 30 h treatment, their diameter did not seem to be affected by the treatment, with an average diameter of 18.9 (± 0.2) µm  and MCF-7 (55.4 (± 4.3)%) (p < 0.0001), followed by SK-BR-3 (62.3 (± 1.1)%) (p < 0.0001) and MDA-MB-231 (69.9 (± 0.7)%) (p < 0.0001). After 30 h, T-47D viability dropped to 54.9 (± 2.0)% (p < 0.0001), joining the previously mentioned cell lines. In contrast, BT-474 (25K) viability was only reduced by 22.7 (± 3.0)% (p < 0.0001). Interestingly, although affected, cell viability was not reduced below 50% in most cases. In consequence, IC50 values were not calculated for this section.After 12 h treatment, BC cell viability was already diminished at 100 µg/ml. The most affected cell lines were MDA-MB-468 (40.4 (± 0.4)%)  except BT-474 (p = 0.0103), whose cell population was smaller as the concentration of BRCE increased.Considering the significant results obtained in the xCELLigence curves of the effect of the haloarchaeal BRCE treatment but the relatively low decrease in viability, cell counting was used to monitor the proliferation of BC cell lines. Figure p = 0.002), 29.4 (± 0.7)% (T-47D) (p < 0.0001), 11.7 (± 0.4)% (BT-474) (p < 0.0001), 64.6 (± 7.2)% (SK-BR-3) (p = 0.0009), 19.6 (± 0.9)% (MDA-MB-231) (p < 0.0001), 45.5 (± 1.6)% (MDA-MB-468) (p = 0.0002), of the control without treatment. Table However, with prolonged exposure to the treatment 24–30 h), the population of viable cells was significantly reduced. After 30 h, the cell population exposed to 100 µg/ml was 57.9 (± 0.9)% (MCF-7)  was not significantly affected by the treatment regarding cell size, viability, adhesion, and concentration.34. Apart from that, the innovative technology of xCELLigence was crucial for obtaining continuous measurements of cell adhesion rather than a single-time quantification.One of the best advantages of xCELLigence RTCA system technology is that it allows observing growth responses to treatments on cell lines in real-time without chemicals and dyes as in other conventional cytotoxicity analyses34. Cell index depends on cell number, morphology, size, and attachment strength.This system measures the electrons that flow between the gold microelectrodes placed at the bottom of the microtiter plate using an electrically conductive solution, such as a cell culture medium. Once cells have adhered to the plate, the electron flow between electrodes and the conductive solution is blocked. The equipment translates this impedance into a unit called cell index that allows monitoring and quantifying cell proliferation and attachment20. However, the effect on cell adhesion had not been addressed before this work. Luminal A and luminal B were more sensitive to the treatment than the rest of the subtypes. Luminal A is the most frequently diagnosed subtype, representing between 50 and 60% of cases36. Despite this, Luminal A tumours generally imply a good patient prognosis since strategies that block estrogen receptor function can be used37. Although these treatments are usually effective, over time, tumours evolve and might become resistant to these hormone-based drugs38. The fact that these carotenoids can act selectively on cancer cells is very promising. Luminal B usually behaves more aggressively than Luminal A tumours since they are associated with a higher probability of relapse and metastasis40.The most affected cell lines in terms of cell index were BT-474 , MCF-7, and T-47D. The sensitivity of the MCF-7 cell line to haloarchaeal carotenoids has been recently reported41. The particularity of triple-negative tumours is that, given their phenotype, they do not respond to endocrine or molecular targeted therapy42. Consequently, they can only be treated with chemotherapy, resulting in poor outcomes. Therefore, developing or discovering new drugs or coadjuvants is necessary.The results obtained for triple-negative cell lines are also relevant, considering the aggressiveness that these tumours usually present, with a mortality rate of 40%35. This study demonstrates that BRCE from Haloferax mediterranei exerts a selective effect in all tested breast cancer cell lines representative of the four different intrinsic subtypes. These results agree with the selective effect of haloarchaeal carotenoids. Previous research reported that Natrialba pigments present an SI > 2, higher than the SI for the chemotherapeutic drug 5-fluorouracil (SI < 1.7)20.A selective effect is crucial for effective cancer treatment to exert high antitumor activity and minimal toxicity to normal tissues. An SI > 1.0 indicates that a compound has higher efficacy against tumour cells than against normal cellsThe observed decrease in cell index indicates a reduction in the detected adhesion of the cells to the plates. However, from these data is difficult to conclude if it is due to reduced cell proliferation, cell death, or a change in the morphology of the cells. For this reason, the diameter, viability, and total number of viable cells per ml were studied in parallel.47 and none on carotenoids than those using more standardized methods, such as MTT52. On that account, this makes comparing results with previous research more difficult.Although the advantages of using the xCELLigence technology are numerous, one limitation shall be considered in this field. Since it is a relatively new technique, there are fewer studies on natural compoundsHfx. mediterranei BRCE on BC cells. Cell diameters were significantly reduced, and morphology alterations were detected in all tested BC cell lines exposed to the BRCE treatment. This effect was also reported for HepG2 cells testing extract from another haloarchaeon and morphological modifications22. In addition, the loss of the standard shape has been previously reported in the MCF-7 cell line in response to haloarchaeal carotenoids20.The analysis of viable cell diameter, cell viability, and the total number of viable cells was essential to determine the effect of Hfx. mediterranei BRCE could affect BC cell viability, following the few studies previously published. Our results showed that BRCE treatment hindered cell viability, but it did not reduce it below 50% in most cases. MDA-MB-468 and MCF-7 were the most affected cell lines. The sensitivity of the MCF-7 cell line to haloarchaeal carotenoids has been recently reported with an IC50 value of 21 µg/ml20.One of our main objectives in this study was to determine if Halogeometricum limi (0.72 µg/ml) and Haloplanus vescus (0.045–0.72 µg/ml) exerted anticancer activity on HepG2 cells, leading to a decrease of 23% and 27% viability, respectively21. Recent research indicated that Natrialba sp. M6 pigments could reduce the viability of different cancer cell lines with concentrations ranging between 21.18 and 38.24 µg/ml20. The differences observed between studies might be related to the composition of the extract since it has been recently reported how the culture conditions and the species influence it12.Many studies have explored the antiproliferative activities of carotenoids, but few are focused on haloarchaeal ones. Results reported by Hou and Cui coincide with the results here displayed since they described that carotenoid extracts from 0/G1 cell cycle arrest apoptosis induction53, which was in agreement with a similar effect on MDA-MB-23154. This research on lycopene also demonstrated that it could inhibit protein kinase B (Akt) and mammalian target of rapamycin (mTOR) activation, although the mechanism remains unclear. Recent research has described the potentiating effect of fucoxanthin combined with doxorubicin, a chemotherapeutic drug55. Further research will be necessary to elucidate the mechanism of action behind the impact of haloarchaeal carotenoids on BC cell lines.The sensitivity of the triple-negative cell line MDA-MB-468 should be highlighted. An earlier study has reported this responsiveness to lycopene due to GNatrialba sp. M6 carotenoids20. In addition, lutein has been described to selectively target cancer cells by exerting a pro-oxidant effect since it increases ROS generation in triple-negative cells. In contrast, normal cells remain unaffected56.The normal mammary cell line 184A1 was not significantly affected by the treatment in terms of cell size, viability, adhesion, and concentration, which is in line with previous researchers reporting similar selective effects on cancer cell lines using .Regarding Luminal A cell lines (MCF-7 and T-47D), cell adhesion, viability, and viable cell concentration were altered significantly in both cell lines, whereas cell diameter was differentially influenced. The Luminal subtype seems to be sensitive to haloarchaeal carotenoid treatment+ PR− HER2+). Therefore, more studies would be needed to explore the effects of this treatment also on cell lines representing Luminal B without HER2 overexpression (ER+ PR− HER2−).Similarly, the Luminal B cell line (BT-474) was one of the most affected cell lines since the cell index values differed clearly from the control, probably due to a delay in growth since viability was not strongly influenced, whereas the cell concentration was. However, BT-474 belongs to those Luminal B tumours with overexpression of HER2  are encouraging. Cell adhesion was significantly impaired due to the several variables studied in this article. The diameter, viability, and cell concentration were significantly diminished in both cell lines at the highest concentrations. MDA-MB-468 was more sensitive to treatment than MDA-MB-231, which makes sense considering that MDA-MB-231 is a Basal B cell line with features of claudin-low triple-negative tumours, which usually behave more aggressively than Basal A triple-negative tumours, from which MDA-MB-468 cell line is representative−/low/CD44+, cell surface markers, have been described for this cell line, implying stem cell properties59. However, despite this, both cell lines responded favourably, opening the door for further studies in this area.CD2420. In addition, lycopene suppresses cell proliferation, possibly through p53 and Bax mRNA upregulation60, and can modulate the gap junction intercellular communication in BC61.The molecular mechanisms involved in the effect of haloarchaeal carotenoids in BC cell lines are not precise yet. However, some researchers have described that carotenoids from halophilic archaea might exert an apoptotic influence via caspase activation. They can also inhibit MMP-9 protease, which is involved in invasion, angiogenesis, and metastasis in cancerHfx. mediterranei cell culture conditions might influence carotenoid extracts composition, thus, altering their antioxidant, antiglycemic, and antilipidemic properties12. This study explores the antiproliferative activity of a Hfx. mediterranei carotenoid extract obtained from a cell culture under certain conditions (12.5% SW (w/v), 1.5% glucose, 36.5 °C). For that reason, further studies are required to determine if variations in the composition of BRCE due to culture conditions also affect the antiproliferative effect. Currently, very little information is available about the pharmacological applications that haloarchaeal carotenoids might have. This study provides for the first time the effect of BRCE on different BC cell lines, representative of the four main types of BC tumours. This work presents new insights into the biological activity and potential biomedical applications of complex haloarchaeal carotenoids. The experiments presented here confirmed that Haloferax mediterranei BRCE was cytotoxic to all tested BC cell lines representative of each BC subtype.It is also worth mentioning that recent research has discussed how In contrast, normal mammary tissue cells were not sensitive to the treatment. One of the main limitations of this work is that the contribution of the individual carotenoids conforming the extract to its antiproliferative activity is yet unknown. Consequently, more experimental evidence is required to answer the questions about these natural compounds' potential health benefits and mechanism of action.In conclusion, we have demonstrated that BRCE exerts selective antiproliferative and cytotoxic effects on BC cell lines representative of each intrinsic subtype. Notably, its effect on triple-negative cell line viability is promising. Therefore, considering the aggressiveness and the lack of targeted treatments for this intrinsic subtype, BRCE may be postulated as a potential therapeutic strategy. Finally, our study provides insights into potential applications of haloarchaeal carotenoids and enables advances in understanding its effects in vitro.


Dehalobacterium and Dehalogenimonas, and nZVI as a treatment train to detoxify chlorinated methanes , and 1,2-DCA. First, we showed that CF (500 μM) was fully degraded by 1 g/L nZVI to DCM as a major by-product, which was susceptible to fermentation by Dehalobacterium to innocuous products. Our results indicate that soluble compounds released by nZVI might cause an inhibitory impact on Dehalobacterium activity, avoiding DCM depletion. The DCM dechlorination activity was recovered when transferred to a fresh medium without nZVI. The increase in H2 production and pH was discarded as potential inhibitors. Similarly, a Dehalogenimonas-containing culture was unable to dichloroeliminate 1,2-DCA when exposed to 1 g/L nZVI, but dechlorinating activity was also recovered when transferred to nZVI-free media. The recovery of the dechlorinating activity of Dehalobacterium and Dehalogenimonas suggests that combination of nZVI and bioremediation techniques can be feasible under field conditions where dilution processes can alleviate the impact of the potential inhibitory soluble compounds.Nanoscale zero-valent iron (nZVI) has the potential to degrade a diversity of chlorinated compounds, and it is widely used for remediation of contaminated groundwaters. However, some frequently detected contaminants such as dichloromethane (DCM) and 1,2-dichloroethane  have shown nearly no reactivity with nZVI. Here, we tested the feasibility of combining anaerobic dechlorinating bacteria, The online version contains supplementary material available at 10.1007/s11356-023-25376-z. At the heart of this process are membrane-bound reductive dehalogenases, which use chlorinated compounds as electron acceptors to generate cellular energy while using H2 as electron donor for organohalide respiration  aqueous solution and a 0.9 M ferrous chloride (III)  aqueous solution. Both solutions were prepared using ultrapure water (Milli-Q). Water used to prepare the FeCl3 solution was previously deoxygenated by bubbling with N2. Then, the NaBH4 solution was added dropwise to the FeCl3 solution while stirring at 200 rpm and bubbling with N2. Then, nZVI was washed three times using anaerobic ultrapure water, and it was finally stored in a serum bottle and sealed with Teflon-coated butyl rubber aluminum crimp caps until use to keep anaerobic conditions.Particles of nZVI were synthesized as described elsewhere  estuary sediments and slurry samples collected from a membrane bioreactor operating in a centralized industrial wastewater treatment plant, respectively. Both cultures were cultivated for more than 5 years in an anaerobic defined medium described elsewhere  and Na2S·9H2O and L-cysteine (0.2 mM each) as reducing agents. Dehalobacterium cultures also contained tungsten (22.8 μM) and selenium (24.2 μM). Yeast extract (200 mg/L) and acetate (5 mM) were added to the Dehalobacterium and Dehalogenimonas cultures, respectively. Microcosms containing Dehalobacterium were gassed with N2 (0.4 bar overpressure), and Dehalogenimonas cultures were gassed with N2/CO2  and H2 (added to an overpressure of 0.4 bar) unless otherwise stated. Both media were buffered with bicarbonate solution (0.01 M). When indicated, either Tris-HCl  or HEPES (60 mM) was added as buffer solutions.The cultures containing Dehalobacterium and Dehalogenimonas were inoculated by transferring 3 mL and 5 mL from cultures during the exponential degradation phase of DCM and 1,2-DCA, respectively. The microcosms containing nZVI were not gassed with H2 but with N2/CO2 . Biotic controls were cultivated under static conditions; biotic-abiotic treatments and abiotic controls were incubated under shaking conditions (150 rpm) with the aim of maintaining the nanoparticles in suspension. All treatments were maintained at 25 °C in the dark.Sixty-five mL of the anaerobic medium described above was added into 100-mL serum bottles and sealed with Teflon-coated butyl rubber septa aluminum crimp caps. When indicated, some of the medium components were omitted. At least three treatments were included for each experiment: (i) abiotic controls containing the anaerobic defined medium and nZVI, (ii) biotic controls containing the anaerobic defined medium and the corresponding bacterium, and (iii) biotic-abiotic treatments containing the anaerobic defined medium, nZVI, and the corresponding bacterium. Each microcosm was amended with either 1,2-DCA, CF or DCM . In the biotic treatments, hexamethyldisilazane.The morphological features of nZVI and the interaction between cells and nZVI particles were analyzed with a Zeiss Merlin Field-Emission Scanning Electron Microscope (SEM). Samples were prepared as follows: a drop from the sample was placed in silicon chips, where it was then fixed with 2.5% glutaraldehyde in phosphate buffer 0.1 M for 2 h at 4 °C, post-fixed with 1% osmium tetroxide with 0.8% potassium ferrocyanide for 2 h, and dehydrated in increasing concentrations of ethanol . Finally, it was chemically dried with L32 ratio, which corresponds to a defined oxidation state of iron according to Tan et al.  to measure the oxidation state of nZVI. A FEI Tecnai G2 F20 HR(S) was used. This TEM was equipped with a Gatan Image Filter (GIF) Quantum SE963 operated at 200 kV to obtain energy electron loss spectroscopy (EELS) analysis. This analysis defines an n et al. . Accordicis-1,2-dichloroethene, vinyl chloride, chloroethane, methane, ethene, and 1,2-DCA, the initial oven temperature was 35 °C; it was held for 3 min and then ramped at 10 °C/min to 240 °C, which was held for 4 min  fitted with an Agilent DB-624 column (30 m × 0.32 mm with 0.25 μm film thickness) and a flame ionization detector. Helium was used as the carrier gas (0.9 mL/min), and the injector and detector temperatures were set at 250 and 300 °C, respectively. To analyze CF, propene, We first studied the abiotic dechlorination of CF, DCM, and 1,2-DCA by nZVI and the effect of omitting vitamins (V−) and sulfur-cysteine (S−) from the complete medium (CM) described in the “nZVI synthesis and bacterial cultures” section.Based on previous reports, CF reacted with nZVI producing mainly DCM (Song and Carraway − or bicarbonate (present in our culture medium) can deactivate reaction sites in the nZVI surface , and DCM was detected as a byproduct at very low concentrations (≤ 10 μM) after 115 days Fig. , B. In mcis-1,2-dichloroethene, and 1,2-DCA  and 1,2-DCA (500 μM) was assessed using 1 g nZVI/L. Consistent with previous reports  by a Dehalobacterium was not observed with either 0.5 or 1 g nZVI/L, while biotic microcosms fully fermented DCM in 4 days , which could favor the decomposition of functional groups in proteins and lipopolysaccharides from cell membranes  compared with cultures without nZVI (4.9 ± 0.1) , 8.5, and 9 without nZVI. Degradation of DCM in cultures at pH 7 and 8.5 occurred at similar degradation rates after a lag phase of 6 days, but cultures at pH 9 exhibited an extended lag phase of 18 days before DCM was fully consumed  Fig. . To deteDehalobacterium activity, we buffered the Dehalobacterium-containing cultures with 25 mM Tris-HCl (pH = 7.5) and amended 1 g nZVI/L, but degradation of DCM was not observed for 12 days although pH was 8.2 ± 0.3 . It provides evidence that H2 accumulated because of water hydrolysis by nZVI even though hydrogenotrophs were present in the bacterial consortium  found inhibitory for DCM fermentation in Dehalobacterium , ii) particles of nZVI were removed from microcosms with no addition of H2 , and iii) particles of nZVI were not removed (control). All treatments were amended with 2000 μM DCM after CF depletion.We prepared nine abiotic-biotic microcosms containing y 7 Fig. , three d2 concentration was 4 ± 1 mM  , and complete degradation of DCM was observed after a lag phase of 14 ± 3 days in microcosms derived from treatment “–nZVI, –H2” Fig. , indicatDehalobacterium. Some strategies to attenuate such inhibitory effect include the surface modification of nanoparticles with surface stabilizers such as surfactants or polyelectrolytes, which slow down nZVI reaction rates, the production of H2, the release of ROS and iron ions, and avoid contact between nZVI particles and cells   Fig.  and D annm) Fig.  and E. Anm) Fig. . At the nm) Fig.  and F.FiL32 ratio values  biotic microcosms (control + H2), ii) biotic microcosms without H2 (control -H2), iii) abiotic-biotic microcosms containing 0.5 g nZVI/L, and iv) abiotic-biotic microcosms containing 1 g nZVI/L. Both control treatments removed 1,2-DCA at the same rate with the concomitant production of ethene, while those microcosms containing nZVI did not show 1,2-DCA depletion despite the circumneutral pH and the high production of H2 that could be used as electron donor for Dehalogenimonas .As shown in Fig. nas Fig. . Therefonas Fig. . This isnas Fig. , indicatDehalogenimonas activity by nZVI, our results are not necessarily transferable to field studies. The high complexity of the soil and groundwater composition could avoid the direct contact between nanoparticles and cells while providing optimum conditions for ORB growth .Despite the inhibition of Dehalobacterium and Dehalogenimonas was inhibited at 1 g nZVI/L, which was the optimal concentration of nZVI found to fully remove CF (500 μM). Further experiments discarded that changes in both pH and partial pressure of H2 provoked by nZVI exerted inhibition on Dehalobacterium. The fact that both Dehalogenimonas and Dehalobacterium recovered the dechlorinating capability after being transferred to nZVI-free medium pointed to soluble compounds released by particles as potential inhibitors. These findings have implication for remediation strategies aiming to combine both abiotic and biotic treatments to decontaminate aquifers with mixtures of chlorinated compounds. In particular, our study suggests that factors such as the buffering capacity of groundwaters and dilution processes can play crucial roles in the viability of this combined strategy in bioremediation treatments.Our laboratory tests demonstrated that dechlorinating activity of ESM 1(DOCX 236 kb)


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