Human and animal cell lines serve as model systems in a wide range of life sciences such as cancer and infection research or drug screening. Reproducible data are highly dependent on authenticated, contaminant-free cell lines, no better delivered than by the official and certified biorepositories. Offering a web portal to high-throughput information on these model systems will facilitate working with and comparing to these references by data otherwise dispersed at different sources.celldive.dsmz.de. A wide variety of data sources are generated such as RNA-seq transcriptome data and STR (short tandem repeats) profiles. Several starting points ease entering the database via browsing, searching or visualising. This web tool is designed for further expansion on meta and high-throughput data to be generated in future. Explicated examples for the power of this novel tool include analysis of B-cell differentiation markers, homeo-oncogene expression, and measurement of genomic loss of heterozygosities by an enlarged STR panel of 17 loci. We here provide DSMZCellDive to access a comprehensive data source on human and animal cell lines, freely available at Sharing the data on cell lines by the biorepository itself will be of benefit to the scientific community  since it (1) supports the selection of appropriate model cell lines, (2) ensures reliability, (3) avoids misleading data, (4) saves on additional experimentals, and (5) serves as reference for genomic and gene expression data. For more than 70 years, cell lines have become indispensable for life sciences, especially for biomedical research. Human and animal cell lines represent cost-effective model systems of almost unlimited availability. Furthermore, they are relatively easy to manipulate. The vast majority of cell lines are derived from spontaneously immortalised tumour cells carrying specific characteristics. They have become essential models not only for cancer research such as investigating mechanisms of tumorigenesis, targets for therapy, or drug efficacies but also for other areas of biological sciences. Cell lines are made available to the scientific community by cell lines banks, who also control and guarantee for cell line authenticity. In general both, diagnosis and clinical parameters of the donor as well as molecular characteristics of the cell line itself, are required for the selection of an appropriate model cell line for a specific research question.. However, so far the mentioned sources contain only limited information about genetic or transcriptional aberrations characterising a cell line. Today, molecular characteristics obtained from high-throughput sequencing data from cell lines become more and more relevant for the selection of appropriate models. In this context, the cell lines project database ofCOSMIC  provides mutation profiles and copy number variations of over 1,000 cancer cell lines. Further publicly accessible datasets for download are multiple high-throughput sequencing data from the CCLE (Cancer Cell Lines Encyclopedia) panelvia theDepMap Portal which also offers interactive data visualisation. In order to support the search for appropriate cell line models Jeonget al. developed the online databaseGEMiCCL which enables the comparison of genomic, transcriptomic and copy number data generated in different projects, including CCLE, COSMIC and the NCI-60 cell lines panel. Importantly, the comparison of the data from different sources points out thate.g. mutation data can strongly vary for a cell line depending on the data source. This observation is not surprising, as selective culture conditions can foster evolution of cell lines, impacting the genetic and transcriptional diversity of the same cell line between two laboratories. Thus, the major drawbacks during the selection process for an appropriate model cell line are either that the molecular data cannot easily be traced back to the source of the cell line and culture conditions used for the generation of the data, and that bioinformatics skills are required to re-analyse publicly available omics data after downloading.Usually, the required information about cell lines has to be gathered from different sources, often including the study of literature. In addition to the information provided in the cell line data sheets of the biorepositories themselves, several online databases independent of the biorepositories can be consulted. The largest available online platform listing key information and references from continuous cell lines is CellosaurusDSMZCellDive, a novel web portal that offers access to evaluated RNA-seq data and STR profiles generated from material of human and animal cell lines that are provided to the scientific community via theDSMZ catalogue.So far, most molecular data including high-throughput sequencing data are available from different sources but not from the cell line repository itself. This fact ultimately confronts the selection of cell lines with the question from which resource the cell line with the appropriate molecular characteristics is actually available. To overcome this limitation we developedAll data were provided by internal sources at the DSMZ, extracted from various formats using tailored scripts, and finally transferred into an SQL database. The data were integrated by using cell culture identifiers, such as the name of the cell line and DSMZ ACC-No. The SQL database is based on MariaDB Version 10.3. PHP 7 is used to generate the web pages and to query an internal SQL database. The JavaScript libraries jQuery and Plotly.js are used to do asynchronous server requests and draw charts, respectively. Heat maps are created using the R library heatmaply. The PHP library Parsedown is used to display the COI barcoding report.schema.org) to do basic queries. The Bioschemas initiative (bioschemas.org) aims to extend these vocabularies for life sciences. We have integrated Bioschemas profiles and added a machine-readable markup for all cell lines. The Bioschemas representations enhance interoperability and standardisation of DSMZCellDive.The importance of machine-readability is increasing steadily. So far, web search engines use a standardised vocabulary  information, STR (short tandem repeat) profiles, and COI (cytochrome c oxidase I) DNA barcodes are bundled at start as listed in. In contrast to the cited paper, the non-malignant cell line NC-NC, a B lymphoblastoid cell line, is included and RNA-seq data were quantifiedvia Salmon and normalisedvia DESeq2 in order to keep pace with state-of-the-art data analysis.The vast majority of data entries in DSMZCellDive is composed of RNA-seq data. We started with our published data on 100 human leukemia and lymphoma cell lines (LL-100 panel). Although the HLA gene cluster on chromosome 6 is highly polymorphic, it is not suitable for cell line authentication due to a low exclusion rate and instability of gene expression. Furthermore, HLA typing is important for cancer research since determination of tissue compatibility by tumour neoantigen binding to HLA surface proteins and rejection of specific HLA alleles play a role. Here, HLA typing was determined on LL-100 RNA-seq datavia arcasHLA, an alignment-based tool.HLA genes encode proteins in the major histocompatibility complex (MHC) which play a central role in discriminating self and non-selfvia Amelogenin. STR typing is serving as a reference technique for identity control of human cell lines at biological resource centers and available as global standard (ANSI/ATCC ASN-0002-2021 (2021). Authentication Of Human Cell Lines: Standardization Of Short Tandem Repeat (STR) Profiling. ANSI eStandards Store). Data sources were kindly provided by ATCC, JCRB, and amended by DSMZ.The applied genotyping system (Promega Powerplex 18D) uses STR microsatellite repeats which are located at 17 specific genomic loci that are highly polymorphic in human populations including gender determinationDNA barcoding for animal samples is frequently based on the Cytochrome c oxidase subunit 1 (COI or COX1) DNA sequence known to exert specific differences between species - prerequisite for species identification. DSMZCellDive harbours COI barcodes for all animal cell lines available at the DSMZ.celllines tablevia one-to-many connections to its primary keycell_id. Since one cell line can have multiple STR profiles, a meta table is used to connect profiles to cell lines. This should not be confused with the fact that one cell line may carry multiple STR alleles per STR loci, a phenomenon called microsatellite instability (MSI). The whole COI barcoding DNA sequence as well as the report is saved as markdown in a single text field as currently no search or comparison operations are planned on these data, since species-specificity only not genetic individuality is resolved by this technique.All data were extracted from various data formats and integrated into a relational SQL database. The database structure contains seven tables in total and can be extended with more data types easily . All datThe DSMZCellDive website was designed to be easily extensible by more data types. For this reason, the web layout contains a sidebar instead of a classical navbar, as it allows more content. The header contains breadcrumbs to meet the requirements of the hierarchical structure of the page. The starting page gives an overview on all available data types and provides links to all tables and tools. Each data source has its own overview page, describing the data, available literature and providing further links.Each RNA-seq data set has its own entry page and supports visualisation as bar chart or heat map. An interactive web interface enables the user to enter genes (up to five for bar charts and up to 20 for heat maps), select tumour entities or cell lines directly, and choose whether normalised data, raw counts, or TPM (transcripts per kilobase million) values should be used. Currently, only RNA-seq data from the LL-100 panel are available; however, it is planned to add more data sets in the near future. For this reason, an integrated view on all RNA-seq data from the different projects was added early on. Since data are normalised within each project, normalised values between projects should not be compared, only TPM data and bar charts are available here.browser and asearch tool. While the browser allows access to unique comprehensive STR data sets of DSMZ and other major cell lines banks, the search tool allows users to compare own STR profiles for similarity matching with regard to authenticity. As a result of the search closest matches according to the following equation are displayed and the ratio to the reference is given in percent distance as described previously.The STR data sets come with aThe result page offers further information on the cell lines and is cross-linked to the respective cell line detail page, which also enables access to the cell line data sheet of the DSMZ catalogue.i.e. the species, cell type, morphology, and culture media. Depending on whether it is a human or animal cell line, STR profiles or COI DNA barcode reports are displayed, respectively. If the cell line belongs to any RNA-seq project, a histogram of all genes is shown, as well as HLA typing data.All data are integrated on cell line level. Each of the currently almost 900 cell lines has its own detail page, including meta data on the cell line,.CD1A, CD19, CD24, CD27, CD34, CD38, CD40, CD79A, CD79B, CD80, CR2, CXCR4, IL2RA, MME, MS4A1, SDC1, SLAMF7, andTNFRSF8) across the B-cell derived cell lines included in the LL-100 panel. Intriguingly, specific B-cell markers get lost in the tumour cells. For example, although CD19 is usually expressed in all B-cells from pre-B-cells until the terminal differentiation to plasma cells, its expression is typically absent in Hodgkin lymphoma (HL), plasma cell leukemia (PCL), primary effusion lymphoma (PEL) and in a fraction of Diffuse large B-cell lymphoma (DLBCL). Accordingly,CD19 loss is also seen in cell lines representing HL, PCL, and PEL  belongs to the ANTP class (according to theDrosophila antennapedia gene) and consists of 48 members in humans. Their physiological expression pattern in the hematopoietic compartment has been termed “NKL-code“ comprising eleven genes. This code is a useful tool to evaluate deregulated NKL homeobox genes in myeloid and lymphoid leukemia/lymphoma patients. To date, 24 aberrantly activated NKL homeobox genes are described in T-cell acute lymphoblastic leukemia (T-ALL), representing the strongest group of oncogenes in this malignancy. TLX1 (formerly HOX11) and TLX3 (HOX11L2) are the most frequently deregulated NKL homeobox genes in T-ALL while NKX2-5 is only rarely expressed.According to their conserved homeobox sequences, these genes are arranged in eleven classes and several subclasses.TLX3 andNKX2-5 as barplots. Both genes are expressed in particular T-ALL cell lines while silenced in cell lines derived from other leukemia/lymphoma entities. NKL homeobox gene VENTX is physiologically expressed in lymphoid T-cell progenitors and myeloid conventional dendritic cells (cDC). MUTZ-3 is an AML (acute myeloid leukemia) cell line derived from a cDC progenitor. This cell line expresses VENTX and represents a useful model to investigate differentiation of dendritic cells and their derived malignancies.VENTX, TLX3 andNKX2-5 in selected cell lines as heat map, demonstrating strikingly highVENTX expression in MUTZ-3. Thus, DSMZcellDive is a useful tool to identify and illustrate normal and aberrant (homeobox) gene expression in leukemia/lymphoma cell lines.Cell lines are useful models to investigate regulation and function of oncogenes including homeobox genes. To identify a leukemia/lymphoma cell line expressing a particular homeo-oncogene, our published LL-100 dataset and the here presented online tool DSMZCellDive may assist to find a suitable cell line modelin vitro evolution of tumour cell lines is well known, the underlying genomic alterations often remain obscure. Despite elaborate quality control via STR genotyping of lot charges, crucial genetic changes of a tumour model may remain hidden to the applying scientist.Althoughet al. describes a large genetic divergence between THP-1 cells from a European and a US biorepository. Although globally standardised STR genotyping in biorepositories is primarily used to prevent the spread of misidentified cell lines, STR typing can distinguish subclones from parental cell lines when minor changes in the STR profile have occurred due to MSI or LOH  can be demonstrated in one of the most commonly used models for AML research, the cytokine-dependent cell line THP-1. A recent publication by Noronha or LOH . Specifictively , indicatin vitro data towards trusted scientific conclusions.Thus, DSMZCellDive enables scientists to verify the authenticity of cell lines by providing an extended STR-17 panel, which measures the degree of correspondence between the original cell line and already slightly modified cell lines. Since all commonly measured STR loci for authentication are combined in the STR-17 panel, this is independent of the STR typing kits used. By presenting the diploid STR datasets in two columns, LOH and UPD events can be deduced, which in turn immediately shows users how often and at what point their own STR data has deviated from the STR reference profile. The described tools will increase reliability ofe.g. to support the selection of appropriate model cell lines, while cell lines are acquired. Furthermore, its concept allows implementation of future data readily and, more importantly, provides reliable data of cell lines available at DSMZ, which can serve as reference data for industry and science.With the interactive web portal DSMZCellDive at hand, access to cell lines omics and meta data is bundled at one site. DSMZCellDive presents its own RNA-seq data exclusively from cell lines of the DSMZ. The novel web portal allows researchers to browse and visualize authentic NGS data generated according to high quality standardsAll data underlying the results are available as part of DSMZCellDive and no additional source data are required.https://celldive.dsmz.deWebsite:Source code at github to download and process: https://github.com/JKoblitz/DSMZCellDiveWebsite:https://github.com/claupomm/RNA-seq_ll100 RNA-seq:https://github.com/claupomm/HLA-analysisHLA analysis:Zenodo for archived source code at time of publication:https://doi.org/10.5281/zenodo.6404422Website:https://doi.org/10.5281/zenodo.6401600RNA-seq pipeline:https://doi.org/10.5281/zenodo.6401594HLA analysis:MIT LicenseLicense: I confirmed that I had read this submission and found that the author had properly modified the manuscript.Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?YesIs the rationale for developing the new software tool clearly explained?YesIs the description of the software tool technically sound?YesAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?YesIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?YesReviewer Expertise:cell biology, genetic mutationI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. In this manuscript, the authors are concerned with the creation of a new web portal that creates a database of cell metadata and characteristic analysis information in cell banks and biorepositories, and will be able to provide useful information for researchers using cell lines. This manuscript can be highly evaluated as an initiative. We also hope that information such as RNA-seq will be expanded in the future, and that fusion gene search based on sequence information and data sharing with other banks will also be expected. However, I think it will be a better manuscript if you reconsider the following points, so please consider modifying it.MajorIn the RNA-seq heat map analysis, the clustering results performed based on the similarity of the expression profile of each gene are displayed, but the clustering result based on the similarity of the expression profile of each cell line should also be displayed.MinorThe legend in Fig. 4B is not appropriate. There are no cell lines highlighted in yellow, while there is no indication of the color of cells highlighted in red.Although the data in Fig. 4B shows only 9 loci data as an example of LOH, it is considered that 17 loci data is collected in this database, so please describe the verification using all the data.Also, why not explain the example of MSI-H using MOLT-4 etc.?Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?YesIs the rationale for developing the new software tool clearly explained?YesIs the description of the software tool technically sound?YesAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?YesIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?YesReviewer Expertise:cell biology, genetic mutationI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. We thank the reviewer for their valuable comments. Please find our responses here:Major "In the RNA-seq heat map analysis, the clustering results performed based on the similarity of the expression profile of each gene are displayed, but the clustering result based on the similarity of the expression profile of each cell line should also be displayed."Thank you for your note on the heat map display. Clustering by cell line has been offered as option in the past, albeit by cell line solely without gene clustering. We now enabled clustering by cell line line and gene simultaneously (option “both”).  Minor"The legend in Fig. 4B is not appropriate. There are no cell lines highlighted in yellow, while there is no indication of the color of cells highlighted in red."Many thanks to the reviewer for the hint. We have now displayed the colors correctly in Fig. 4B and described the cell lines highlighted in red as genetically unbiased.  "Although the data in Fig. 4B shows only 9 loci data as an example of LOH, it is considered that 17 loci data is collected in this database, so please describe the verification using all the data."Figure 4B has been redone so that all STR locations are now captured and the matches across STR 17 are completely shown.  "Also, why not explain the example of MSI-H using MOLT-4 etc.?"An explanation of the MSI phenomenon based on MOLT-4 would unfortunately go beyond the scope of this paper. For a satisfactory explanation, the failure of DNA MMR and the origin of DNA replication errors would have to be presented, so that the scope in this manuscript would be exceeded. In addition, it would need to be discussed much more deeply that the rule established by Amanda Capes-Davies for relatedness of cell lines when there is at least 80% similarity of the STR profile does not apply to MSI cell lines : 2510-2519). Finally, MSI lines need additional tests as described in the STR standard of 2021 (ANSI/ATCC ASN-0002-2021 (2021) Authentication Of human cell lines: standardization of Short Tandem Repeat (STR) profiling. ANSI eStandards Store).   In the submitted article of Koblitz et al., DSMZCellDive, a comprehensive data source for human and animal cells, will be presented, one aim is to provide high-throughput information through a web portal that aggregates data and references that are otherwise spread across multiple sources.  A variety of data sources are generated, such as RNA-seq transcriptome data and STR (Short Tandem Repeats) profiles, which are essential for working with cell lines.  The new tool is explained and described in detail, e.g. how to access the database via browsing, searching or visualization. The database can be extended with meta- and high-throughput data that will be generated in the future to finally allows a comprehensive summary and detailed characterizations of a cell line. To illustrate the power of the tool, analysis of B-cell differentiation markers, homeo-oncogenes, homeo-oncogene expression, and measurement of genomic loss of heterozygotes through an expanded STR panel of 17 loci were described.  DSMZCellDive offers enormous added value to the scientific community by supporting the selection of suitable model cell lines and thus ensuring the reliability and reproducibility of experiments.  Optimal in vitro conditions also save resources in the long term. The comprehensive data acquisition and provision of the tool leads to a massive upgrading of in vitro models, which enables the reduction of animal experiments and thus sustainably implements the 3R principles in research.Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?YesIs the rationale for developing the new software tool clearly explained?YesIs the description of the software tool technically sound?YesAre sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?YesIs sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?YesReviewer Expertise:Cell line establishment, Cell line characterization, cell line quality checkI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. We thank the reviewer for the evaluation of our work and appreciate the positive comments.


Daphne genkwa plant, is known to have pharmacological properties; however, its modulatory effect on multidrug resistance, which is (MDR) mediated by ATP-binding cassette (ABC) drug transporters, has not been investigated. In this study, we examine the interaction between hydroxygenkwanin, ABCB1, and ABCG2, which are two of the most well-characterized ABC transporters known to contribute to clinical MDR in cancer patients. Hydroxygenkwanin is not an efflux substrate of either ABCB1 or ABCG2. We discovered that, in a concentration-dependent manner, hydroxygenkwanin significantly reverses ABCG2-mediated resistance to multiple cytotoxic anticancer drugs in ABCG2-overexpressing multidrug-resistant cancer cells. Although it inhibited the drug transport function of ABCG2, it had no significant effect on the protein expression of this transporter in cancer cells. Experimental data showing that hydroxygenkwanin stimulates the ATPase activity of ABCG2, and in silico docking analysis of hydroxygenkwanin binding to the inward-open conformation of human ABCG2, further indicate that hydroxygenkwanin sensitizes ABCG2-overexpressing cancer cells by binding to the substrate-binding pocket of ABCG2 and attenuating the transport function of ABCG2. This study demonstrates the potential use of hydroxygenkwanin as an effective inhibitor of ABCG2 in drug combination therapy trials for patients with tumors expressing higher levels of ABCG2.Hydroxygenkwanin, a flavonoid isolated from the leaves of the  ATP-binding cassette (ABC) transporters are a superfamily of proteins that utilize the chemical energy derived from ATP hydrolysis to translocate compounds, including many of the most commonly prescribed anticancer drugs, across biological membranes ,2. Two oDaphne genkwa Sieb.et Zucc plant, which is commonly known as blue daphne or lilac daphne, and it is native to East Asia [The potential application of inherently well-tolerated, plant-derived, bioactive compounds for the sensitization of multidrug-resistant cancer cells has been explored as an alternative approach ,25. Numeast Asia . It has ast Asia ,35, antiast Asia , and it ast Asia . In addiast Asia ,43,44,45In this study, we investigated the potential reversal effect of hydroxygenkwanin on MDR, mediated by ABCB1 and ABCG2. We discovered that at low, sub-toxic concentrations, hydroxygenkwanin could selectively re-sensitize ABCG2-overexpressing multidrug-resistant cancer cells to cytotoxic anticancer drugs. Moreover, we demonstrated that hydroxygenkwanin reverses ABCG2-mediated MDR by modulating the drug efflux function of ABCG2, without altering its expression at the protein level in these cancer cells. These findings were further supported by data from ATPase assays and molecular docking analysis. Overall, our study demonstrates the potential of using hydroxygenkwanin as a chemotherapy adjuvant to improve the efficacy of anticancer drugs.50 values of hydroxygenkwanin  and a half-maximal effective concentration value (EC50) of approximately 19 nM. Our data indicate that hydroxygenkwanin interacts with, and has a high affinity with, ABCG2, which is in accordance with previous reports that have demonstrated other chemosensitizing agents binding to the drug-binding pocket of ABCG2 and stimulating ABCG2-mediated ATP hydrolysis [Next, the effect of hydroxygenkwanin on the Vdrolysis ,63,64,65drolysis ,54,66.We found that hydroxygenkwanin attenuates ABCG2-mediated drug efflux, as shown after an in silico molecular docking analysis of hydroxygenkwanin in the inward-open structure of human ABCG2 (PDB:6VXH)  was perfDaphne genkwa Sieb.et Zucc, a well-known traditional Chinese medicinal plant [The ability of ABCG2 to transport a wide range of conventional anticancer drugs and molecularly targeted agents contributes to poor clinical outcomes in cancer patients . Regrettal plant . Previoual plant , oral sqal plant , and glial plant . Moreoveal plant . Recentlal plant  and by ial plant . In thisFirst, the intrinsic cytotoxicity of hydroxygenkwanin was determined in drug-sensitive parental cell lines and multidrug-resistant sublines overexpressing ABCB1 or ABCG2. We found that hydroxygenkwanin is equally cytotoxic to both parental and multidrug-resistant cell lines, thus suggesting that it is not rapidly transported out of cancer cells by either ABCB1 or ABCG2 . More imIn summary, this study demonstrates that hydroxygenkwanin is a potent and selective modulator for ABCG2. Collectively, our findings indicate that further study is needed to evaluate its potential use as a chemotherapy adjuvant to improve the efficacy of anticancer drugs in patients with tumors expressing relatively high levels of ABCG2.Hydroxygenkwanin was purchased from Selleckchem . The TOOLS Cell Counting (CCK-8) kit was acquired from Biotools Co., Ltd. . Paclitaxel, vincristine, colchicine, mitoxantrone, SN-38, topotecan, and all other chemicals were obtained from Sigma , unless otherwise stated.2 humidified air, and grown in media supplemented with 10% fetal calf serum (FCS), 2 mM L-glutamine, and 100 units/mL of a penicillin–streptomycin solution mixture; then, the cell lines were screened periodically for mycoplasma contamination using a TOOLS Mycoplasma Detection Kit. The cell lines were kindly provided by Drs. Michael Gottesman and Susan Bates .The ABCB1-overexpressing KB-V1 cell line, derived from human epidermal cancer, was maintained in DMEM supplemented with 1 μg/mL of vinblastine . The ABC2 humidified air. Cytotoxic drugs were subsequently added at various concentrations, in the absence or presence of hydroxygenkwanin or a reference inhibitor (0.5% (v/v) final concentration of DMSO in all wells), for an additional 72 h before being processed, as previously noted [50) value of each drug regimen was calculated using a fitted concentration–response curve obtained from at least three independent experiments.The cytotoxicity of cytotoxic drugs was determined by standard MTT and CCK-8 assays, as previously noted ,88. Briely noted . The 50%Flow cytometry assays, with the ABCG2 substrate, pheophorbide A (PhA) (395 nm excitation and 670 nm emission), were performed, as previously noted ,89. BrieAn immunoblot assay for the detection of human ABCG2, with the positive loading control, tubulin, was performed using BXP-21 (1:1000 dilution) and anti-alpha tubulin   antibodies, respectively, as previously noted .i assay, using total membrane vesicles prepared from ABCG2 baculovirus-infected High-Five insect cells, as previously noted [The vanadate (Vi)-sensitive ATPase activity of ABCG2 was determined based on the endpoint Ply noted ,90.The ABCG2 protein (PDB:6VXH)  and ligaExperimental values are presented as an average ± standard deviation (SD) or as an average ± standard error of the mean (SEM); they were calculated from dose–response data, from at least three independent experiments, using GraphPad Prism software  and KaleidaGraph software . Unpaired two-tailed Student’s t-tests were performed to analyze the difference between experimental data and control, or improvement in fit data.


Breast cancer (BCa) has long been a health burden to women across the globe. However, the burden is not equally carried across races. Though the manifestation and behavior of BCa differs among racial groups, the racial representation of models used in preclinical trials and clinical trial participants lacks this heterogeneity. Women of African Ancestry (WAA) are disproportionately afflicted by having an increased risk of developing BCas that are more aggressive in nature, and consequently suffer from poorer outcomes relative to women of European ancestry (WEA). Notwithstanding this, one of the most commonly used tools in studying BCa, cell lines, exhibit a sizeable gap in cell line derivatives of WEA relative to WAA. In this review, we summarize the available BCa cell lines grouped by race by major suppliers, American Type Culture Collection (ATCC) and the European Collection of Authenticated Cell Cultures (ECACC). Next, examined the enrollment of WAA in clinical trials for BCa. Of the cell lines found provided by ATCC and ECACC, those derived from WEA constituted approximately 80% and 94%, respectively. The disparity is mirrored in clinical trial enrollment where, on average, WEA made up more than 70% of participants in trials found where ancestry information was provided. As both experimental models and clinical trial participants primarily consist of WEA, results may have poorer translatability toward other races. This highlights the need for greater racial diversity at the preclinical and clinical levels to more accurately represent the population and strengthen the translatability of results.The online version contains supplementary material available at 10.1186/s13058-022-01551-x. Women of African ancestry (WAA) are 40% more likely to die of BCa than women of European ancestry (WEA) and have the highest death rates due to BCa of all racial groups . Data frWomen of African ancestry are usually diagnosed with BCa at advanced stages and are disproportionally diagnosed with the most aggressive form of BCa , 4. SeveBreast cell lines from the American Type Culture Collection (ATCC) and European Collection of Authenticated Cell Cultures (ECACC) databases were found using the search terms: “breast cell lines,” “breast cells,” and “breast cancer cell lines.” Both cancerous and non-cancerous cell lines were included when compiling the list of available cell lines. The race of the individual from which the cell lines were derived was determined based on information provided by ATCC and ECACC. In cases where race was not specified by these suppliers, ancestry information was obtained from the Swiss Institute of Bioinformatics.Trials included in Additional file With the exception of the antiestrogen effect of IC146474 clinical trial, clinical trials that did not provide the racial background of its participants were excluded. Cases of male breast cancer were not considered.No limitation was placed on the date for studies included in the literature review.The systematic approach utilized over the years to understand and treat cancers includes preclinical models followed by clinical trials. Preclinical models comprise in vitro and in vivo research and, in both instances, the application of 2D models, cell lines that are also used as organoids and 3D cultures are all vital. Taking sociological factors into account, a closer look at the representational BCa models that have been used over the decades to understand, treat, and prevent BCa is crucial. As described above, there is a clear disparity in incidence and mortality rates for WAA with BCa. What is more is that women of WEA have higher incidence rates, yet women of WAA have higher mortality rates and are more prone to developing the more aggressive and least studied form of BCa—triple negative breast cancer (TNBC). This then begs the question, as to how much do socioeconomical factors contribute versus lifestyle and genetic predisposition. As scientists and clinicians, our preclinical models and clinical trials are primarily employed to address and find answers for the latter reasons and so this review aims to take a closer look at the representational models used to understand, treat, and prevent BCas.Cultured cells have proven to be cornerstone catalysts in propelling oncology by acting as disease models. Such models have allowed for the elucidation of pathways responsible for cancer initiation and progression, the study of the behavior of cancers, and the discovery of novel therapeutic agents. Although primary cells represent the most appropriate models for analysis owing to their close resemblance to the source tissue, their limited lifespans in culture present a roadblock to long-term investigation. Cell lines remedy this by circumventing the major barrier to immortality—senescence.Although BCa is of a heterogenous nature, the racial diversity of commercially available cell lines borders on the homogeneous. This is reflected in the catalogue of breast cell lines provided by two major suppliers of cell lines: the ATCC and the ECACC. Of ATCC’s breast cell lines where race could be determined  was examined. The trial, in which tamoxifen was used to treat hormone sensitive BCa, involved 46 patients (races not specified) for a period of more than 3 months . Later, Scientific American reports that although racial minorities constitute 40% of the US population, they are typically vastly outnumbered in clinical trials by participants of European descent, who can constitute up to 80–90% of recruits [The racial disparity in BCa clinical trial enrollment is evident across trials supported by several organizations  is expressed across all BCa subtypes; however, overexpression appears more common in aggressive disease subtypes. Trop-2 is expressed in the majority of TNBCs and may be considered an actionable biomarker. Sacituzumab govitecan-hziy is an antibody–drug conjugate that targets Trop-2 for the selective delivery of SN-38. In 2020, Sacituzumab govitecan  was approved by the FDA for the treatment of patients who have received at least two prior therapies for metastatic disease . The phaIn the IMpassion130 phase 3 clinical trial  of Atezolizumab and Nab-Paclitaxel in advanced TNBC, it was shown that the addition of the immunotherapy drug Atezolizumab to chemotherapy (nab-paclitaxel) prolonged progression-free survival among patients with metastatic TNBC. In this TNBC specific study, the study population was 67.5% WEA (609 patients), with WAA comprising 6.5% (59 patients) . The resP = 0.007. The association was also seen with early-stage post-menopausal BCa with a HR for death of 1.49, 95% CI = 1.28—1.73; P < 0.001 [Although the aforementioned clinical trials did not stratify treatment outcome data by race, a study examined 6676 BCa patients (662 were WAA) enrolled in phase 3 clinical trials carried out by the Southwest Oncology Group (SWOG) between 1974 and 2009. When factors such as stage, therapy, and follow-up were kept equal, WAA had poorer survival relative to WEA. The WAA diagnosed with early-stage premenopausal BCa, regardless of receptor status, had increased mortality with a hazard ratio (HR) for death of 1.41, 95% confidence interval (CI) = 1.10—1.82;  < 0.001 . HoweverThe field of medicine is evolving toward a more personalized approach to patient care, aimed at improving outcomes while reducing treatment-related toxicities. This personalized approach has to begin by systematically addressing commonalities and differences in biomarker expression, at the somatic and germline levels among races taking into account the geographical locale and socio-economic factors among women with BCa. Toward this end, an intentional course at increasing the representation of preclinical models and enrollment in clinical trials is necessary. As such, this needs to be factored in at the levels of funding agencies, IRB, suppliers of in vitro models, and sponsors/investigators of clinical trials. For example, the African Genome Registry (AGR) project a part of the African Caribbean Cancer Consortium (AC3) group, to be undertaken by researchers of the African-Caribbean scNetwork aims to address genetic differences between cancerous and neighboring normal cells of prostate, breast, and cervical cancers from MAA and WAA. This would be done via single cell sequencing of the aforementioned cancers from patients living in the USA, Caribbean, and Africa. Similarly, a current clinical trial project, IRONMAN that is amassing the largest registry of men with advanced PCa has been intentional about increasing the representation of MAA with PCa. Another project similar in nature to IRONMAN under the AGR aims to create a registry of patients of African descent with BCa and PCa of all types and stages from the USA, Caribbean, and Africa. These are being done by strategically partnering with various organizations like the African-Caribbean Cancer Consortium (AC3) and Prostate Cancer Transatlantic Consortium (CaPTC), research consortia that include research groups in the Caribbean and Africa that are high in representation from people of African ancestry. Notwithstanding, tackling BCa wholistically, has to also consider socioeconomic factors such as access to healthcare, dietary trends, and environmental factors, which will maximize the improvement of patient care for women with BCa.For the efficacy of therapeutic agents and the findings from all stages of research to have stronger external validity, consideration must be taken when choosing in vitro models and recruiting patients such that they reflect that population they intend to benefit. It was demonstrated that a clear racial disparity exists among the most commonly used in vitro models, cell lines, where on average those derived from WEA constituted more than 80% of those commercially available from major suppliers. Consequently, if a conscious effort is not made to include the fewer cell lines from racial minorities, those used as disease models skew toward European derivatives. The same can be said for the lack of diversity in clinical trials, especially those geared toward TNBC, which disproportionately affect WAA. At this stage, it becomes even more critical for racial equality among study participants as these results will determine if therapies advance to the final stages to eventually become available as treatment options to the public. Acknowledging and shedding light on the issue at hand is the first step in moving toward more inclusive research that, over time, ensures that clinical outcomes are more favorable toward racial minorities.Additional file 1. Racial diversity of breast cancer clinical trials funded by various organizations N = number of participants.Additional file 2. Cell lines supplied by the ATCC and ECACC disaggregated by race N = number of cell lines.


Somatic embryogenesis could potentially contribute to the maximization of solid polyploid production due to the single cell origin of regenerants. In the present study, a novel procedure for establishing homogeneous tetraploid embryogenic cell lines in Magnolia officinalis has been established. Embryogenic cell aggregate (ECA) about 100–200 μm across, and consisting of dozens of cells, regenerated into a single colony of new ECAs and somatic embryos following colchicine treatment. Histological analysis indicated that the few cells that survived some colchicine regimes still regenerated to form a colony. In some colonies, 100% tetraploid somatic embryos were obtained without mixoploid formation. New granular ECA from single colonies with 100% tetraploid somatic embryos were isolated and cultured individually to proliferate into cell lines. These cell lines were confirmed to be homogeneous tetraploid by flow cytometry. Many tetraploid somatic embryos and plantlets were differentiated from these cell lines and the stability of ploidy level through the somatic embryogenesis process was confirmed by flow cytometry and chromosome counting. The establishment of homogeneous polyploid cell lines, which were presumed to represent individual polyploidization events, might expand the phenotypic variations of the same duplicated genome and create novel breeding opportunities using newly generated polyploid plantlets.The production of synthetic polyploids for plant breeding is compromised by high levels of mixoploids and low numbers of solid polyploid regenerants during  Artificial polyploid induction can be used for the improvement of important plant traits, in support of crop breeding strategies . It has In vitro regeneration systems provide a powerful tool for mitotic ploidy manipulation  of 0, 0.05, 0.1, 0.15, and 0.2% . The culTo estimate the number of ECAs in the cell suspension, aliquots of 1 mL of cell suspension were precipitated by centrifugation, and resuspended in 0.1 mL of M3 medium and pipetted onto a glass slide. Images were taken under an OLYMPUS SZX16 microscope and the number of ECAs were counted with CellSens Dimension software.After plating the colchicine treated ECAs onto a piece of filter paper and cultured on semi-solid M4 medium for 4 weeks, each surviving ECA regenerated into a single colony consisting of somatic embryos and/or new ECAs . The numFor plantlet conversion, the cotyledonary somatic embryos were first transferred to 9 cm Petri dishes containing 20 mL of semi-solid M4 medium for germination. The cultures were maintained at 25°C under a 16 h photoperiod. The germinated somatic embryos were transferred to glass culture vessels containing 100 mL of semi-solid M4 medium and cultured at 25°C under a 16 h photoperiod.To trace the cellular origin of ECAs following colchicine treatment, fluorescein diacetate (FDA) and propidium iodide (PI) were used to label living cells and dead cells, respectively . ECAs weFlow cytometry was used to determine the ploidy level of cell lines, somatic embryos and plantlets . For DNAThe ploidy level of tetraploid plantlets and somatic embryos verified by flow cytometry were further confirmed by chromosome counting to precisely determine the number of chromosomes . Root ti2. For stomatal length and width measurements, three stomata in each image were randomly selected and measured (n = 24).To compare the difference of stomata characteristics between diploid and tetraploid plantlets, nail polish imprints were made from the abaxial surface of leaves. Briefly, the abaxial surface of the leaves were covered with a thin layer of nail polish and allowed to dry. The polish imprints were then carefully lifted off with forceps and placed on a glass slide. The stomata were observed and imaged under LEICA DM5500 B microscope with LAS software. For evaluating the stomatal density, the number of stomata per field of view under the 40× objective was recorded in eight different images. The size of the image was measured to calculate the number of stomata per mmFlow cytometry were used for screening of clones with a high percentage of tetraploid plantlets. To establish tetraploid cell line production, single granular ECAs from the colonies confirmed with a high percentage of tetraploid plantlets were isolated and cultured individually on semi-solid M2 medium for proliferation . These cin vitro plantlets of diploid and tetraploid status were collected, and the biomass was measured.To assess the effects of polyploidization, the size of the somatic embryos and biomass of the plantlets (3 months after somatic embryo germination) regenerated from diploid and tetraploid cell lines were measured and compared. Diploid and tetraploid cell lines were used to produce somatic embryos with the same method. ECAs with a diameter of 200–450 μm were obtained and plated on a piece of filter paper and cultured on semi-solid M4 medium for somatic embryo initiation. Thirty somatic embryos initiated from diploid and tetraploid cell lines were collected 5 weeks after somatic embryo initiation. Images were taken under an OLYMPUS SZX16 microscope. The length and diameter of somatic embryos were calculated with CellSens Dimension software. For plant conversion, germinated somatic embryos were transferred to glass culture vessels containing 100 mL of semi-solid M4 medium and cultured at 25°C under a 16 h photoperiod. Following 7 weeks culture, 12 p < 0.05. The measurement of somatic embryos, in vitro plantlets and stomata characteristics were analyzed with Student’s t-test at p < 0.05.The colchicine treatment experiment was designed with a randomized complete block design, and each treatment contained five replicates. Data were processed and analyzed with SPSS 19.0 software using Duncan’s multiple range tests at M. officinalis were initiated from mature zygotic embryos on semi-solid M1 medium. After initiation, PEMs were subcultured on semi-solid M2 medium for proliferation , yielded 24 reatment . The frereatment . Fifteenreatment . Relativreatment . One plaWhen colchicine treated ECAs were plated onto a piece of filter paper and cultured on semi- solid M4 medium, each surviving ECAs regenerated into a single-ECA-derived colony. Three types of regeneration response could be distinguished in single-ECA-derived colonies . Each sin = 24, 100%) recovered from the treatment of ECAs with 0.2% colchicine for 72 h were determined to be tetraploid , which represented the highest embryogenic potential among other size ranges of tetraploid ECAs. However, this response was still much lower than their diploid counterpart, which produced 217 somatic embryos in 50 ECAs with a diameter of 200–450 μm in the same period. Significant differences in the morphologies of diploid  was established by integrates in vivo bud regeneration via calluses with polyploid induction. At the mature leaf stage, not just octoploids but also tetraploid, diploid and mixoploid plants could be forecasted with a high degree of accuracy by observing the size and shape of shoots and leaves (Fortunella crassifolia) is much larger than the diploid, and the two types could be clearly discriminated by size in a mixed population of diploid and tetraploid cells (In the present study, somatic embryos regenerated from 0.2% colchicine treatment for 72 h could be clearly discriminated from those of control, as they are much bigger in size. This kind of “giant” somatic embryos was also observed in other colchicine regimes. When these somatic embryos were selected based on morphology characteristics and the ploidy levels were analyzed by flow cytometry, all were found to be tetraploid. After the tetraploid cell lines were established and verified, somatic embryos were produced and compared with the diploid lines. Generally, tetraploid somatic embryos were shorter and thicker in appearance than those of diploid lines. These findings suggest that the morphology of somatic embryos may be employed as a potential morphology indicator to predict ploidy level to expedite identification of putative tetraploid regenerates at an early stage before plantlet conversion. Other systems show a similar change in morphological phenotype with polyploidization. The d leaves . A widesid cells .Magnolia officinalis belongs to the Magnoliaceae, which consists of over 300 species in two genera–Magnolia L. and Liriodendron L (Liriodendron tulipifera was published nearly 40 years ago (Liriodendron tulipifera (M. officinalis in the present study, is based on the manipulation of the somatic embryogenesis process following antimitotic agent treatment. Our method has great potential for the creation of new polyploid germplasm for species with established somatic embryogenesis protocols, especially in the magnolia family.endron L . Many maears ago . Since tlipifera . The effM. officinalis demonstrate the potential of establishing polyploid embryogenic cell lines via induction along the somatic embryogenesis pathway. The use of very small ECAs composed of dozens of cells is highlighted. Only a few cells in the ECAs survived colchicine treatment and regenerated into single colonies. However, the dual potential of differentiation and proliferation of the ECAs was then manipulated to produce somatic embryos for ploidy analysis and new ECAs for cell line establishment, respectively. The present study shown that a high frequency of homogeneous polyploid cell lines can be established by proliferation of single new granular ECAs picked up from colonies with a high presence of polyploid somatic embryos. Somatic embryos and new ECAs in the same colonies derived from each colchicine treated ECA share a common origin from a very limited numbers of cells. The ploidy level of somatic embryos can reflect the ploidy level of cells that survived antimitotic agent treatment and regenerate. This increases the likelihood of being able to establish and purify polyploid cell lines. Our results provide insight into the potential of obtaining new polyploid embryogenic cell lines via polyploid induction with a somatic embryogenesis system.Our results with The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.in vitro tissue culture experiments and chromosome set doubling experiments and carried out the phenotypic analysis. YG, JM, and YJ performed the flow cytometry analyses. JC and YG performed the Chromosome counting experiment. LL, WL, and HC revised the manuscript. All authors contributed to the article and approved the submitted version.LL conceived and designed the experiments and wrote the manuscript. YG, JM, and QX performed the The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Breast cancer subtypes are characterized by the expression and activity of estrogen-, progesterone- and HER2-receptors and differ by the treatment as well as patient prognosis. Tumors of the HER2-subtype overexpress this receptor and are successfully targeted with anti-HER2 therapies. We wanted to know if the HER2-receptor and the downstream signaling network act similarly also in the other subtypes and if this network could potentially be a therapeutic target beyond the HER2-positive subtype. To this end, we quantitatively assessed the wiring of signaling events in the individual subtypes to unravel the characteristics of HER-signaling. Our data along with a model-based analysis suggest that major parts of the intracellular signal transduction network are unchanged between the different breast cancer subtypes and that the clinical differences mostly come from the different levels at which these receptors are present in tumor cells as well as from the particular mutations that are present in individual tumors.1 regularization, where the impact of these mutations on pathway activation was uncovered. Finally, we predicted and experimentally validated the proliferation response of cells to drug co-treatments. We developed a unified mathematical model that can describe the ERBB receptor and downstream signaling in response to therapeutic drugs targeting this clinically relevant signaling network in cell line that represent three major subtypes of breast cancer. Our data and model suggest that alterations in this network could render anti-HER therapies relevant beyond the HER2-positive subtype.Targeted therapies have shown striking success in the treatment of cancer over the last years. However, their specific effects on an individual tumor appear to be varying and difficult to predict. Using an integrative modeling approach that combines mechanistic and regression modeling, we gained insights into the response mechanisms of breast cancer cells due to different ligand–drug combinations. The multi-pathway model, capturing ERBB receptor signaling as well as downstream MAPK and PI3K pathways was calibrated on time-resolved data of the luminal breast cancer cell lines MCF7 and T47D across an array of four ligands and five drugs. The same model was then successfully applied to triple negative and HER2-positive breast cancer cell lines, requiring adjustments mostly for the respective receptor compositions within these cell lines. The additional relevance of cell-line-specific mutations in the MAPK and PI3K pathway components was identified via L The development of therapeutic antibodies and small-molecule kinase inhibitors has revolutionized cancer treatment. Many of these therapeutics target receptor tyrosine kinases, which connect extracellular growth factors with intracellular signaling networks and, when deregulated, drive oncogenic mechanisms . AdvanceThe ERBB signaling network is one of the main drivers of cell growth . The ERBERBB2 and ERBB3 are exceptional as the structure of the ERBB2 ligand-binding domain is constitutively in a dimerization-prone conformation rendering the binding of a ligand unnecessary to induce dimerization, while ERBB3 is kinase-impaired . Upon liAmong them, the MAP kinase (MAPK) cascade as well as the phosphoinositide 3-kinase (PI3K) pathway play essential roles in signal processing and propagation ,13,14,15Regulation of the ERBB signaling network is highly complex, varies between individual breast cancer subtypes and has been previously studied using mathematical modeling—a powerful tool to render complex systems intelligible and accessible ,25,26,27Furthermore, the drug-response mechanisms of different breast cancer subtypes have been evaluated before. For example, Schoeberl et al. explored the optimal way to therapeutically inhibit ligand-induced activation of the ERBB–PI3K axis , while IHere, we investigated combinations of several ligands as well as of different therapeutic drugs and their dynamic effects on cell line models of three breast cancer subtypes and their proliferative behavior. Beyond the previously published work, we expanded the analysis by weighting cell-type-specific differences in model parameters and thus the characteristics of the cell lines that propagate in differential activation of the individual signaling branches.To this end, we used data-based mechanistic modeling with ordinary differential equations (ODEs) to understand the response mechanisms to different ligands and drugs in three breast cancer subtypes. A signaling model, including receptors as well as downstream signal transduction was developed and calibrated on time-resolved proteomics data. To link the signaling output to the condition-specific growth response of the cells, we implemented a proliferation model applying a linear regression approach.1 regularization, only two biological specifics that needed to be adjusted to make our model applicable to cell lines of other breast cancer subtypes.A proliferation screen of single treatments provided calibration data for the regression parameters, while we could successfully predict proliferation measurements of various drug co-treatments thereby validating our model. Along these lines, we identified, by LOn the one hand, the receptor expression levels were different in the respective cell lines, and on the other hand, the mutation states in genes that are components of the investigated pathways strongly impacted the wiring of signaling. Still, the core signaling network was not affected by these adjustments thus underlining its general applicability. Our study therefore supports the concept of targeting the ERBB signaling network beyond the HER2-positive subtype of breast cancer.2. All cell lines were authenticated  and negatively tested for mycoplasma contamination before and after completion of the study.The human breast cancer cell lines MCF-7 (HTB-22™), T47D (HTB-133™), MDA-MB-231 (HTB-26™) and SKBR3 (HTB-30™) were obtained from the American Type Culture Collection  and maintained in Dulbecco’s Modified Eagle’s Medium: Nutrient Mixture F-12 , supplemented with 10% FCS , 50 units/mL penicillin and 50 µg/mL streptomycin sulfate  at 37 °C with 5% CODetails on all the antibodies, drugs and ligands used in this study are provided in For time course experiments, 3 × 10The RPPA experiments were performed as previously described ,39. Brie® luminescent assay . Luminiscence was determined using a GloMax® microplate reader .To determine the effects of the different ligands and drug treatments on the viability of cancer cells, 3000 cells of the respective cell lines were seeded in 96-well white plates in DMEM/F12 with 10% FCS . Prior to the addition of ligands, the cells were pre-treated with the corresponding drugs for 1 h. Cells were grown for 6 days, and the effects on cell viability, i.e., the amount of ATP reflecting the number of metabolically active and proliferative cells, was evaluated using CellTiter-Glox denoted the vector of dynamic states, such as c-RAF, MEK, etc., and u represented external perturbations, such as treatment with a ligand or a drug. Initial concentrations and kinetic rates were comprised in The developed model consisted of two parts, a mechanistic ODE model describing the ERBB signaling network and a linear regression model linking cell proliferation to signaling features. The mechanistic signaling model was described by nonlinear ODEs p, including the dynamic model parameters The mechanistic model along with corresponding observations was parameterized by the parameters ormation . The par1 penalty [The mechanistic signaling model was linked to cell proliferation by a regression model. Signaling features, including the area under the curve (AUC), the half-life and the peak height, were derived from the calibrated dynamic model for ppERK, pAKT, pP70S6K and active receptor dimers and used as predictor variables for the linear regression model with the cell proliferation as the response variable. Signaling features with the highest predictive power were selected applying an L penalty , and theeatments .As previous studies reported synergistic effects of drug co-treatments ,48,49,501 prior, and subsequently refitting the model without those fold change parameters was estimated to be compatible with 0. The The identification of cell-line-specific parameters for the cell lines MDA-MB-231 and SKBR3 were performed using a lasso-based regularization approach ,52,53. Tatistics .While kinetic rates constants ERBB downstream activation correlates with the receptor composition. To investigate the impact of various growth factors on the dynamic signaling response of cells derived from different breast cancer subtypes, we studied two cell lines of the luminal A subtype, T47D and MCF7, in addition to the triple-negative MDA-MB-231 and HER2-positive SKBR3 cell lines. The cells were stimulated with four ligands to induce receptor activation and downstream signaling in the absence or presence of four drugs targeting EGFR, ERBB2, or ERBB3. EGF, BTC and TGFa are ligands for EGFR. BTC and NRG1, a ligand for ERBB3, also bind and activate ERBB4, another receptor of the ERBB family a. We assTo experimentally validate this, we inhibited ERBB3 or knocked down ERBB4 and observed that ERBB3 was required for the activation of downstream signaling by NRG1, while ERBB4 was not . We concWe then quantified the dynamic changes in the phosphorylation states and the total protein levels of eight central proteins in the ERBB–MAPK–PI3K signaling network. In total, we experimentally tested 80 conditions, covering four cell lines, which were incubated in an array with four ligands, five drugs and an untreated control c. These In an initial analysis, we wanted to discern cell-line-specific effects focusing on the response to the ligands EGF and NRG1 by assessing their effect on the activation of AKT and ERK proteins as representatives of the PI3K and MAPK pathways, respectively. These two pathways are the two main downstream signaling branches activated upon EGF/NRG1 stimulation. As shown in This indicated cell-line-specific differences in the propagation of the original input signals. To explain the observed differential activation behavior, we first regarded the receptor composition of the four cell lines as described by Niepel et al.  Figure b. The reConsidering the ligand specificity of EGF to EGFR and of NRG1 to ERBB3 (and ERBB4), the differential downstream response might at least partially originate from the distinct ratios of the ERBB-receptors expressed by the cell lines. To test this hypothesis, an activation ratio of NRG1 over EGF was calculated for each protein and cell line, based on the area under the curve (AUC) of the phosphorylation dynamics displayed in Furthermore, there exists a strong dependence of pathway activation on the respective repertoire of receptors. This correlation followed our expectations, as cells with high ERBB3/EGFR ratios, such as MCF7, were more susceptible for NRG1, and conversely MDA-MB-231 was for EGF. Similarly, the horizontal location of pAKT and pERK in the correlation plot reflects the subsequent downstream activation, where AKT is shifted to the right, meaning to an activation via NRG1.The exception is represented by MDA-MB-231, which predominantly expresses EGFR and, in addition, carries an activating mutation in KRAS all favoring signaling via the MAPK pathway. Hence, our findings confirm the known dominant role of ERBB3 in AKT activation and, respectively, EGFR as a main factor in ERK phosphorylation ,56. TakeHaving validated our initial hypothesis, we next wanted to address three main questions: (i) Are there other variables that determine downstream signaling and cellular response on top of the receptor composition? If true, (ii) what other factors are needed to explain the response? Furthermore, (iii), can we establish a unified model of ERBB signaling for the luminal, TNBC and HER2-positive cell-line systems that is able to predict the effect of ligand stimulation and drug treatments for the three breast cancer subtypes?To explore the differential downstream activation of breast cancer subtypes, we established an ODE model describing the ERBB signaling network as displayed in Upon ligand binding, several ERBB homo- and heterodimers form, leading to the trans-activation of receptors and to the induction of downstream signaling . Our modOnce activated, the receptor dimers induce phosphorylation and thereby the activation of the MAPK and PI3K signaling pathways, which ultimately converges in the activation of P70S6 kinase in our experimental system . The matUsing the complete data set, the model was first implemented for the luminal cell lines MCF7 and T47D. The time-resolved total and phosphoproteomics data of EGFR, ERBB2, ERBB3, c-RAF, MEK, ERK, AKT and P70S6K proteins are complemented by the absolute protein abundances taken from Niepel et al.  and usedIn phase I, the inhibition phase, we assessed drug-induced changes independent of any ligand, while in phase II, we addressed the dynamics of the ligand-induced protein activation in unperturbed and in drug-perturbed conditions a. SampleLigands induce a conformational change, dimerization and activation of their respective receptors, whereas our drugs of interest either inhibit receptor dimerization (pertuzumab), impede receptor activation at the level of the extracellular domain  or block ATP-binding in the kinase domain (erlotinib). We implemented this inhibition in the mathematical model by multiplying the dimer formation and activation rate with an inhibition term As shown in Drug effects in combination with this ligand for MCF7 are displayed in Trastuzumab and erlotinib only showed a minor inhibitory effect in combination with this ligand, while cetuximab did not have any. However, this picture turned when cells were stimulated with one of the EGFR ligands. Erlotinib and cetuximab led to a strong reduction of protein phosphorylation, in particular, upon stimulation with EGF or TGFa, while the other drugs had only minor effects . In addi877 and Tyr1221/Tyr1222, of EGFR at Tyr1086 and to a lesser extent also of ERBB3 at Tyr1289  Trastuzumab as well as pertuzumab induced ligand-independent phosphorylation of ERBB2 at Tyr Tyr1289 . This ef416 of the protein kinase SRC. This suggests that these antibodies might trigger phosphorylation of ERBB receptors involving the Src kinase. This drug-induced phosphorylation was stronger in the T47D cell line compared to MCF7 and more pronounced when incubated with trastuzumab as compared to pertuzumab  Lumretuzumab and pertuzumab both led to a strong inhibition of ERBB3 phosphorylation , the slopes and the peak height of states of interest.The selection of states used for the generation of the feature set was made up of pAKT, pERK, pP70S6K and the active dimers, which were previously shown to have predictive power . These f1 regularization. Our analysis showed that the AUC of pAKT combined with the AUC of pP70S6K had the highest predictive power. Thus, these features served as predictor variables to describe the phenotypic readout, i.e., cell proliferation.Cells were treated with the same drug-ligand combinations that had been used to obtain the original data set. Then, a subset of signaling features was selected from the complete feature set, based on their prediction ability as determined by LThe predictive power of all signaling features tested is summarized in We then wanted to test if the resulting proliferation model would correctly predict treatment efficacy. To this end, we generated growth predictions for 24 combination treatments. The model suggested the co-treatment of pertuzumab with erlotinib as the overall most efficient treatment in the luminal A cells b. To valModel predictions and validation data were in good agreement, featuring only a minor increase in the mean estimated error of 0.005, representing 3% of total data spread, compared to the training data set of single treatments c. These We next wanted to assess whether the identified network kinetics are luminal cell-line-specific or if the model could be adapted also to other breast cancer subtypes. To this end, we examined the ligand-induced phosphorylation of MAPK and PI3K pathway proteins under drug influence in TNBC MDA-MB-231 as well as HER2-positive SKBR3 cells.1 regularization as previously described [Time-resolved phosphoproteomics data was generated for these two cell lines applying the same experimental conditions that we previously used with the luminal cell lines, except that we induced signaling in the SKBR3 cells with only EGF and NRG1 and that we used pertuzumab, trastuzumab and lumretuzumab as inhibitors. To identify key functions that are differentially regulated between these cell lines, differences in parameters of the established signal transduction model were analyzed based on Lescribed .1 prior  as well as an activating b-RAF mutation (G464V) . Given t289/Ser296/Ser301.In addition, this specific mutation in b-RAF has previously been reported to trigger feedback inhibition of RAS and c-RAF by ERK, which should result in a decrease in the basal activation ratio of c-RAF ,65. To tThese residues are phosphorylated by ERK and inhibit the interaction between RAS and c-RAF thereby leading to the inactivation of c-RAF as part of a negative feedback loop . MatchinIn this cell line, a strong preference towards PI3K signaling was observed, which was reflected by the low activation rates of c-RAF and MEK as well as an increase in the activation rate of P70S6K by AKT a, comparFinally, we analyzed the cell-line-specific activation of signaling branches. Along these lines, we analyzed the activation fluxes of the P70S6 kinase via either pERK or pAKT and then calculated their respective log10 ratios a. As thePIK3CA present in MCF7 and T47D. However, in these cell lines, the MAPK signaling gained relevance upon stimulation of EGFR, leading to a transient switch towards MAPK-regulated activation of P70S6K. Yet, this impact was short, and the predominant activation via AKT quickly reestablished.A positive score would indicate dominance of the MAPK pathway in the activation of P70S6K over PI3K signaling and vice versa. Signaling via AKT indeed dominated the steady state in the luminal cell lines, which can be explained with activating the hot-spot mutations in This overshoot behavior reflects the transient dynamics of ERK phosphorylation—particularly when the EGFR was activated by EGF. The dynamics of ERK-activation were longer-lasting with the other two EGFR-ligands tested, TGFa and BTC, both leading to a shortly extended activation of P70S6K by ERK. The transient nature of P70S6K activation via EGFR was in contrast to the longer lasting activation via ERBB3 particularly in MCF7, which was clear upon activation with NRG1 see also b.b-RAF.In sharp contrast to the two luminal cell lines, P70S6K was mostly activated by MAPK signaling in MDA-MB-231 cells a. This wAlong the same lines, stimulation with NRG1 did not lead to a sizeable activation of any downstream signaling proteins and thus did not affect the P70S6K activation flux ratio see also . The levThe dominance of PI3K signaling is so strong in SKBR3 that, even with activation of EGFR and downstream MAPK signaling, a balanced ratio of P70S6K activation was not reached for the MAPK and PI3K pathways. ERBB2 is the preferred binding partner of ERBB3, which has six p85 binding sites in its intracellular domain and thus preferentially induces AKT signaling ,67. EvenBased on the experimental data as well as the cell-line-specific parameters we identified in modeling, we propose specific major activation routes for the different cell lines Thus, we established a unified mathematical model for ERBB and downstream MAPK as well as PI3K signaling, which required only a few biologically relevant adaptations to correctly describe the molecular responses of luminal A T47D and MCF7, TNBC MDA-MB-231 and HER2-positive SKBR3 cell lines upon stimulation with several ligands as well as perturbations with drugs targeting EGFR, ERBB2 and ERBB3.The ERBB signaling network plays a crucial role in the regulation of cellular growth, migration and survival, which are all critical phenotypes in health and disease ,9. AlthoEGFR are frequent in relapsed lung adenocarcinoma, BRAF is often mutated in melanoma, and PIK3CA is often mutated in various entities, including luminal breast cancer. Beyond single nucleotide variants, the ERBB2 gene locus is amplified and a diagnostic marker in several entities, including HER2-positive breast cancer. Together, these factors affect tumor physiology. However, the complex interplay of signaling pathways and how these trigger cancer phenotypes in response to different inputs is not fully understood.For example, activating mutations in Here, we established a mathematical model that mechanistically describes the activation dynamics of ERBB proteins and of two prominent downstream pathways, RAF-MEK-ERK and PI3K-AKT. The amounts and phosphorylation states of central components within these pathways were quantified with high temporal resolution to capture dynamic changes in their respective abundance and activities.To perturb and thereby constrain the proliferation signaling of the cell lines in our study, five drugs targeting the ERBB receptor family were analyzed as single agents as well as in combination, always in the presence of different ligands. The drugs specifically targeted the EGFR, ERBB2 and ERBB3 receptor tyrosine kinases, while ligands were selected to either activate EGFR or ERBB3. The ODE model was then calibrated on the experimental data of single drug treatments, initially from the two luminal breast cancer cell lines, MCF7 and T47D.To establish a link between pathway activation and cell proliferation as our phenotypic readout, we combined this mechanism-based signaling model with a linear regression model. Signaling features, such as the area under the curve of single activated proteins, were simulated by our signaling model and served as input for the regression model. The regression model was then calibrated on experimental data, which we collected in a proliferation screen depicting the proliferative response of MCF7 and T47D cells under the respective ligand–drug treatments.The coupling of signaling and proliferation models, both calibrated on single drug treatments, made it possible to reliably predict phenotypic responses also to co-treatments imposed at the receptor level. Thereby, our combined model could be validated. This approach of linking an ODE signaling model with a proliferation regression model enabled us to find a balance between the mechanistic complexity and the comprehensibility of the model.The validity of this implementation is supported by the fact that the applied drugs directly target signaling components, i.e., the growth factor receptors in our study . Thus, wPIK3CA mutation status.Having analyzed two different luminal cell lines, we wanted to know if cell-line-specific differences in the activation of downstream signaling branches needed to be considered in the model. Regarding the initial model calibration on the luminal cell lines MCF7 and T47D, model parameters could indeed be implemented as identical between these two cell lines with the exception of the respective protein abundances as well as the These were estimated separately for each cell line . This isPIK3CA is the most frequently mutated gene in luminal breast cancer and the same hotspot mutations present in MCF7 and T47D have been found in 45% of patient tumors, underlining the clinical relevance of the model systems in our study [Therefore, our data and the model suggested that the H1047R mutation in the kinase domain has a stronger effect than the E545K mutation in the helical domain. This observation is in line with the increased basal activation of pAKT in the T47D cell line. These properties of the two luminal cell lines lead to a dominance of the PI3K-AKT signaling branch also in ERBB-downstream signaling. ur study .1 regularization was applied to analyze whether, and if so, which model parameters were necessary to be adjusted, for this cell line to compensate for cell-line-specific differences in the activation of downstream signaling branches. In this process, both inactive c-RAF as well as increased basal activation of MEK were identified as major distinguishing factors between MDA-MB-231 and the luminal cell lines.In order to assess whether our model was also applicable to TNBC, MDA-MB-231 cells were tested in the same experimental setup as used with the luminal cell lines. LIndeed, the phosphorylation of MEK and ERK was prolonged and elevated even under steady state conditions in MDA-MB-231, which could be due to an activating b-RAF mutation that is present in this cell line . This b-These molecular changes combined with a strong dominance of EGFR in this TNBC cell line, led to a shift between pathway branches from PI3K signaling towards MAPK signaling, standing in sharp contrast to the pathway regulation in the luminal cell lines. Taking these factors into account, our mathematical model then required few further adjustments regarding the receptor dimerization rates to reliably fit the experimental data. Hence, the same model could be applied to luminal and TNBC breast cancer cell lines, which have distinct receptor compositions, mutation states and growth properties and thus going beyond previous modeling approaches .1 regularization identified the basal activation ratio of c-RAF as the most important parameter necessary to be adjusted. However, while the basal MEK phosphorylation was enhanced in the MDA-MB-231 cell line, this parameter was reduced in SKBR3.We then wanted to know whether the model could correctly predict the signaling dynamics also for the HER2-positive subtype of breast cancer. To this end, we employed the SKBR3 cell line as a suitable experimental system. This cell line has a high ratio of ERBB2 over all other members of the ERBB family. LHence, the MAPK signaling pathway seems to be less relevant in SKBR3 as compared to the luminal cell lines MCF7 and T47D, whereas the PI3K pathway strongly dominates signaling downstream of the ERBB receptor level. However, even though the SKBR3 cells appear to be addicted to PI3K signaling, adjustment of our model for the highly biased expression of the signaling components as well as for the other identified cell-line-specific parameters, allowed to precisely describe the experimental data. Hence, our mathematical model is able to comprehensively reflect ERBB signaling towards RAF-MEK-ERK as well as PI3K-AKT signaling in three subtypes of breast cancer.EGFR and other RTKs are flexible in structure, and the binding of growth factors increases their probability of adopting a state, which is favorable for dimerization ,73, tranIn contrast, the presence of an extended tertiary structure is an intrinsic feature of ERBB2, which does not require structural changes during the formation of active heterodimers . However877 and, to a lesser extent, at Tyr1221/Tyr1222 upon incubation with either trastuzumab or pertuzumab, which was more prominent with trastuzumab compared to pertuzumab and in T47D compared to MCF7 cell lines. A similar effect was not observed with cetuximab suggesting that the phosphorylation related to the specific antibodies and/or ERBB2. In HER2-positive SKBR3, Tyr1221/Tyr1222 were found even more strongly phosphorylated while MDA-MB-231 cells appeared to not be affected by any of the therapeutic antibodies. The latter observation might be related to the predominance of EGFR expression in MDA-MB-231.We observed the phosphorylation of ERBB2 at position Tyr877 is phosphorylated by Src [1221 and Tyr1222 are autophosphorylated by ERBB2 [Tyrd by Src  while Ty1086, however, not at Tyr1148. Both these sites are autophosphorylated by EGFR [1086 is also a target of Src kinase [Similar to the phosphorylation of ERBB2, we observed phosphorylation also of EGFR Tyr by EGFR . Howeverc kinase . Hence, Along the lines of activation of ERBB2, phosphorylation of EGFR was not changed by cetuximab in any of the cell lines tested, while we also observed phosphorylation of ERBB3 with trastuzumab and pertuzumab, this was much less compared to ERBB2 or EGFR in all tested lines. This was unexpected as the ERBB3-receptor is even the most strongly expressed member of the ERBB-family in MCF7.The phosphorylation of all kinases was strongest in SKBR3, followed by T47D and MCF7 cells. This order reflects the absolute numbers and receptor-ratios in these cell lines regarding expression of ERBB2. Elevated phosphorylation of EGFR and ERBB2 in response to treatment with trastuzumab has been reported before in ERBB2-overexpressing cell lines . Here, wDokmanovic et al. investigated the impact of trastuzumab at the level of receptor phosphorylation and stability . TrastuzHence, the effects of trastuzumab on receptor stability seem to be cell line-dependent. A reduction in ERBB3 protein levels was observed after several  days of treatment with trastuzumab. Here, we found particularly lumretuzumab to reduce total ERBB3 levels within minutes and even without any ligand.In the time-scale of our measurements, the levels of ERBB3 were independent of drugs other than lumretuzumab, including erlotinib, and were then only and similarly reduced after stimulation with NRG1. Therefore, the dynamics of receptor downregulation seem to depend on the specific antibodies, the receptors and their abundance as well as on the specific growth factors.Different growth factors and downstream pathways are commonly associated with particular phenotypic responses, such as proliferation, migration and survival ,82,83. TPrevious modeling studies have followed a similar idea ,31. HoweThese originate from autocrine or paracrine signaling loops also involving the tumor microenvironment ,85. ThisFurthermore, our implementation contains simplifications in terms of regarded receptors. It has been shown, for example, that the insulin-like growth factor receptor (IGF-R) and the hepatocyte growth factor receptor (cMET) mediate a variety of cellular processes in breast cancer cells as well ,89. It rExploiting our experimental data as well as the mathematical model we were finally out to uncover interactions between ERBB signaling and cell proliferation. Our model implied that co-treatment of luminal cell lines with pertuzumab and erlotinib should have the strongest effect on proliferation. Furthermore, we confirm this in experiments. It should be noted, however, that the observed effects were mild in the tested cell lines.This is in line with the physiology of luminal breast cancer, which is driven by the estrogen receptor much more than by ERBB receptor-signaling. In addition, the uncoupling of PI3K signaling in these cell lines likely supports this phenotype due to the mutated PIK3CA . Still, Endocrine resistance comes also with an upregulation of ERBB-proteins and, according to our model, the receptor composition is likely one major determinant of ERBB and downstream pathway activities on tumor physiology then. Along the same lines, the PIK3CA-inhibitor alpelisib has been approved for treatment of hormone receptor positive, HER2-negative metastatic breast cancer further supporting the impact PI3K-signaling has in the luminal subtypes once endocrine resistance has kicked in  and suppHere, we developed a modeling strategy that combines the molecular ERBB signaling network with the proliferation phenotype. We determined the relevant variables that affect downstream MAPK and PI3K signaling and presented a unified model that enabled us to assess the effect of single and combination treatments and to predict the resulting proliferative behavior in cell lines representing three subtypes of breast cancer. At the same time, the model provided insights into the regulation of the downstream pathway activation and pointed at a shift in activated signaling branches between breast cancer cells of different subtypes.The weighting of cell-type-specific characteristics, which enabled us to analyze this activation of the individual signaling branches and construct one model for all cell lines, represents the major novelty of this work. The complexity of the biological systems was analyzed as well as the responses to drugs and ligands that we could infer, highlight the potential of mathematical modeling for the prediction of signaling readouts and hints at mechanisms in the underlying biology. Our study further supports the concept of anti-HER therapies in HER2-low breast cancer.