The overwhelming need to improve preclinical models in oncology has stimulated research efforts to refine and validate robust orthotopic models that closely mimic the disease population and therefore have the potential to better predict clinical outcome with novel therapies. Sophisticated technologies including bioluminescence, contrast enhanced ultrasound imaging, positron emission tomography, computed tomography and magnetic resonance imaging have been added to existing serum- and histology-based biomarkers to assist with patient selection and the design of clinical trials. The rationale for the use of human hepatocellular carcinoma (HCC) cell lines, implementation of xenograft and orthotopic animal models and utilization of available biomarkers have been discussed, providing guidelines to facilitate preclinical research for the development of treatments for HCC patients. Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and its incidence in the United States and other countries has been steadily increasing over the past 25 years ,2. Given®, Adria Laboratories), showed rather low efficacy; however, with a response rate of 10-15%, doxorubicin remains the most effective single agent currently available [®, Bayer), significantly prolonged the time to tumor progression, increased overall survival in a placebo-controlled phase III study in HCC patients [®, Pfizer Inc.) was also tested in phase II clinical trials in HCC patients showing that HCC could be susceptible to treatment with anti-angiogenic compounds [Advanced HCC is highly refractive to currently available chemotherapies, and patients suffering from HCC often develop drug resistance during treatment. Several chemotherapeutic agents have been tested in patients with advanced HCC; however, the results were disappointing and life-threatening side effects frequently limit prolonged treatment . One of patients ,7 and sipatients . Becauseompounds ,10.Preclinical experimentation allows for simultaneous longitudinal implementation of various technologies and biomarkers to monitor the tumor take rate, growth and response to treatment as well as to confirm and correlate histological and histochemical results at various time points with serum or imaging biomarkers, which cannot be determined in HCC patients. Different animal models and biomarkers, such as serum alpha-fetoprotein (AFP), bioluminescence imaging (BLI), contrast enhanced ultrasound imaging (CEUS), positron emission tomography (PET), computed tomography (CT) and immunohistochemistry (IHC), can be utilized to build confidence in the efficacy and safety of tested compounds during preclinical research and help to develop biomarker strategies and design clinical trials.in vitro testing of human HCC cell lines is usually an early step in the process of anticancer drug discovery that involves evaluating viability, cell proliferation, clonogenicity and apoptosis. In vitro results from our studies in four commonly used human HCC cell lines: Huh7.5, HepG2, Hep3B and SK-Hep1, showed that sunitinib alone moderately inhibits proliferation in all four HCC cell lines with IC50s in the low micromolar or high nanomolar range. Doxorubicin used as a monotherapy was also effective; the IC50 was in the low nanomolar range in all four HCC cell lines deployed. Combining doxorubicin and sunitinib resulted in additive inhibitory effects on cell proliferation in all cell lines used in the study; however, none of the cell lines were very sensitive or resistant to imposed treatments [in vitro therapeutic efficacy with the drug combination was mainly due to the induction of apoptosis and inhibition of proliferation.Similar to other cancers, eatments . Mechaniin vitro systems lack the power to recapitulate the complex relationship between the tumor and its microenvironment, including local blood supply and angiogenesis, interactions between tumor cells and the organ where the tumor resides, and the influence of hormones, growth factors and cytokines on tumor growth and survival. Scientists usually start in vivo oncology work with subcutaneous (SC) xenograft models because these are relatively easy to perform; tumors are externally placed and simple caliper measurement of tumor size provides insight regarding compound efficacy measured as inhibition of tumor growth (TGI) [While results obtained using cell cultures provide important information regarding drug efficacy and mechanisms of action, th (TGI) A and 1Aath (TGI) ,13,14,15in vivo study, testing combination therapy using two or three drugs adds to the complexity of the study design and study execution. For example, if the study design calls for the use of only one imaging method and one biomarker, then each methodology must be deployed in the same model/study in all study groups treated with sole therapy as well as in study group(s) treated with two or three drugs used in combination. The practicality of study conduct end execution becomes even more complex if the study design requires testing a combination of two drugs in several HCC cell lines. Such a study will require 16 different study groups and with a minimum of eight animals per group to achieve statistical significance, anticipated study conduct will become very challenging for any lab even if a simple subcutaneous xenograft model is deployed. Because the number of available tumor cell lines is constantly increasing, testing novel compounds in all available cell lines becomes increasingly difficult, in particular since the research community in general lacks firm criteria to guide the decision on which HCC cell line has relevance for a particular patient population. In addition, tumor cells grown in culture are susceptible to undergoing genetic alterations not found in the original tumor, such that xenografts created by these cells may differ from those of naturally occurring tumors [Selecting the cell line(s) for an animal study is often challenging because the scientist must decide which cell line, from all cell lines available for a particular tumor type, best represents a particular human cancer, and selecting only one cell line that responds to exact treatment could be very misleading when it comes to clinical outcome . Even ifg tumors . in vivo data, we propose the use of cell cocktails composed of several HCC cell lines to create xenograft or orthotopic models as the next step in screening cascades aimed at building confidence in compound efficacy in in vivo studies in single-cell xenografts have confirmed therapeutic effect. Also, the deployment of cell cocktails allows for the assessment of eventual resistance to treatment of individual cell line(s) used to make the cocktail, pending same exposure to drug(s) and treatment duration. Finally, the use of tumor cell cocktails if and when possible will reduce the amount of drug needed for testing, lessen the time and resources needed for preclinical studies without compromising data quality and integrity as well as support the 3Rs animal welfare paradigm  [in vivo study to assess which cell line(s) used in the cell cocktail did not respond to treatment. To improve the robustness and predictive value of  Reduce) . When usAlternatively, human biopsies instead of tumor cell lines can be used to create xenograft or orthotopic models, but caveats to this approach are the high cost of procedures and transfer of biopsies along with safety issues due to a high rate of hepatitis C (HCV) and hepatitis B (HBV) infections in HCC patients ,20,21,22The local vasculature of the liver is extremely complex and is composed of nutritional and functional blood supplies that in addition to neo-vasculature created by tumor itself, collectively support tumor growth within the liver. In brief, total liver blood flow represents approximately 25% of the cardiac output, with roughly 100-130 mL of blood circulating through 100 g of liver tissue per minute, and this number is fairly constant across all mammalian species. The hepatic artery accounts for about 65% of the oxygen supply to the liver ,24,25. TOne of the most clinically effective ways to deliver drugs to the liver is through the hepatic artery because it allows continuous infusion directly into the arterial bed from which the tumor derives nearly all of its blood supply ,33. InjeClinical diagnosis and monitoring of HCC in patients consists of a blood test for elevated AFP concentrations followed by structural imaging utilizing one of several imaging modalities that are currently available. The most frequently used imaging methods are CEUS, contrast CT and MRI. Also, PET imaging with FDG and/or FLT is increasingly being used both preclinically and in clinical practice ,40,41,42AFP is the primary serum biomarker for HCC and is elevated in up to 40% of patients with early-stage HCC, with expression increasing in advanced disease ,46. AlthUS technology using microbubbles as a contrast agent is known to be an extremely useful tool for non-invasive assessment of liver vascular structure . CEUS isBLI is based on the detection of light emitted by living cells expressing a luciferase gene ,44. StabThe use of PET and MRI imaging is increasing as these technologies are becoming more affordable. However, due to the high cost, associated radiation, high level of skills required for data acquisition and interpretation as well as need for other labor-intensive procedures, PET and MRI imaging should be reserved only for advanced projects with a specific question in mind that cannot be answered using other imaging modalities. in vivo research and ensure translation of results to the clinical situation. A thorough preclinical approach to HCC research should build confidence in compound efficacy as well as safety and lead to the discovery of novel compounds or more efficacious drug combinations for treating HCC.There are multiple and independent biomarkers, including serum AFP, CEUS, PET and MRI imaging and tissue IHC, available for use in preclinical animal studies investigating novel compounds and therapeutic combination paradigms for HCC. The use of the cell cocktail approach, orthotopic models and careful study design as well as selection of biomarkers can maximize the value of


Tumors are heterogeneous at the cellular level where the ability to maintain tumor growth resides in discrete cell populations. Floating sphere-forming assays are broadly used to test stem cell activity in tissues, tumors and cell lines. Spheroids are originated from a small population of cells with stem cell features able to grow in suspension culture and behaving as tumorigenic in mice. We tested the ability of eleven common breast cancer cell lines representing the major breast cancer subtypes to grow as mammospheres, measuring the ability to maintain cell viability upon serial non-adherent passage. Only MCF7, T47D, BT474, MDA-MB-436 and JIMT1 were successfully propagated as long-term mammosphere cultures, measured as the increase in the number of viable cells upon serial non-adherent passages. Other cell lines tested  formed cell clumps that can be disaggregated mechanically, but cell viability drops dramatically on their second passage. HCC1937 and HCC1569 cells formed typical mammospheres, although they could not be propagated as long-term mammosphere cultures. All the sphere forming lines but MDA-MB-436 express E-cadherin on their surface. Knock down of E-cadherin expression in MCF-7 cells abrogated its ability to grow as mammospheres, while re-expression of E-cadherin in SKBR3 cells allow them to form mammospheres. Therefore, the mammosphere assay is suitable to reveal stem like features in breast cancer cell lines that express E-cadherin. This program is mediated by the activity of transcription factors such as SNAIL 1/2, ZEB 1/2 or TWIST 1/2, which results in loss of E-cadherin (E-Cad) expression, loss of cell polarity, acquisition of loose mesenchymal cell morphology and invasion capabilities, critical for the metastatic spread of epithelial tumors. In recent years it has been shown that EMT is also involved in cellular plasticity, a process by which non stem cells acquire stem cell traits. Mani et al.  found thIn an effort to apply the mammosphere assay to measure self-renewal to a wide variety of breast cancer cell lines, we tested the ability of eleven human breast cancer cell lines representing the major breast tumor subtypes, to grow as mammospheres. We found that several cell lines  had the ability to grow as mammospheres through serial non-adherent passage, while other cell lines did not. Based on this feature we can distinguish three groups of cell lines: the long term sphere forming cell lines , the short term sphere forming cell lines (-STSF- HCC1937 and HCC1569) and the non sphere forming cell lines . We performed a meta-analysis of gene expression data to identify putative regulators of this phenotype. We found that genes related to cell motion and migration are overrepresented among the genes differentially expressed in the sphere forming cell lines. Further analysis at the protein level showed a strong correlation between E-cadherin expression and sphere formation ability. Silencing of E-cadherin expression in MCF7 cells, a LTSF cell line, prevented the formation of mammospheres, while overexpression of E-cadherin in non-spherogenic cells (SKBR3) resulted in sphere formation. Consequently, the ability to grow as spheroids depends on E-cadherin expression. Therefore, the mammosphere assay may be a useful assay to study stem cell like behavior in some breast cancer cell lines.2 incubator. Characterization of cell lines according to their surface expression phenotype can be found in MCF-7, T47D, MDA-MB-231, MDA-MB-435, MDA-MB-468 breast carcinoma cell lines was obtained directly from the ATCC , JIMT-1 cells were obtained from the German Collection of Microorganisms, MDA-MB-436 and HCC-1937 were obtained from T. Stein  and SKBR3, BT474 and HCC-1569 were obtained form A. Pandiella  and grown in DMEM  supplemented with 10% fetal bovine serum  at 37°C in a 5% COMammospheres were collected by centrifugation in a Cytospin  onto glass slides prior to fixation. For monolayer cultures, cells were grown on LAB-TEK II chamber slides . Cells were fixed in 4% paraformaldehyde for 15-30 min at room temperature, washed with PBS and permeabilized/blocked for 1h at room temperature with PBS, 0.3% Triton X-100, 2.5% horse serum. Slides were then incubated with anti-E-cadherin primary antibody (diluted 1:100) see  overnighDifferential gene expression was carried out using the limma  package Gene set analysis was carried out for the Gene Ontology terms using FatiScan  in BabelSignificant GO terms were represented by directed acyclic graphs from Blast2GO .GO annotation for the genes in the microarray where taken from Ensembl 56 release (http://www.ensembl.org).Pre-packaged lentiviral particles that either encoded a non-targeting shRNA  or sequences specifically targeting the human E-cadherin gene  were purchased from a commercial provider (Santa Cruz Biotechnology). For viral infection of MCF-7 cells, the regular medium was replaced with culture medium containing 5 µg/mL polybrene . MCF-7 cells were then exposed to lentiviruses for 48 h. Because the lentiviral shRNA particles also encode a puromycin resistance gene for transduction selection, the cells were then washed and grown in culture medium containing 10 µg/mL puromycin dihydrochloride  for an additional 72 h. The transduced MCF-7 cells were allowed to recover and proliferate for at least 1 week before any experimental procedures and were then analyzed. To monitor the lentiviral transduction efficiency and transgene expression for the duration of the experiment, we incubated additional subsets of MCF-7 cells with lentiviral particles encoding a green fluorescence protein (GFP) reporter (sc-108084). Transduction efficiency (> 90%) was obtained as the ratio of the number of GFP-positive cells to the total number of cells from five random visual fields from three independent culture experiments.Stable cell lines expressing E-cadherin were generated by infection with the lentiviral vector pWZL Blast mouse E-cadherin (Addgene plasmid 18804) , infecte6 cells/100 µl for 10 min at 4°C. Cell suspensions were spun down and the different combinations of fluorochrome-conjugated monoclonal antibodies , counted and resuspended in staining buffer plus 10% FBS at a cell density of 103 cells/ml, at this cellular density the sphere assay gave rise to clonal spheres as described in other systems  and and14] a3 cells/ml) ensures that spheroids have a clonal origin . Th. Th42]. l origin . The amoWhile the exhaustion of the self-renewal potential of normal mammary epithelial stem cells takes place after 4-5 passages in suspension culture, there is much more variability when working with cancer stem cells, either derived from tumor samples or continuous cell lines. In general, fresh tumor cells cannot be grown in these culture conditions for longer than 4-5 passages, although Ponti et al.  reportedbona fide sphere structures (using the viability and disaggregation criteria proposed above), but do not express E-cadherin  motile phenotype, and spheroid formation. Our meta-analysis of gene expression data comparing LTSF and STSF versus NSF cell lines revealed a significant difference in the expression of genes associated with cell motility and migration, particularly at the level of the cell surface. We have uncovered a functional relation between E-cadherin expression, associated with typical epithelial morphology, and spheroid formation. E-cadherin is one of the earliest cell surface molecules that is down-regulated during EMT, allowing the cells to escape physical constraints imposed at the epithelium, acquire a mesenchymal-like phenotype and invade other tissues, the first step towards tumor dissemination. NSF cell lines  do not express E-cadherin on the cell surface, while LTSF and STSF do express E-cadherin, readily detectable at the cell-cell contact interface . Interescadherin  and 3. AIn summary, we find that the ability to form spheroids correlates with the acquisition of epithelial phenotype and expression of E-cadherin. In accordance with our results, Celia-Terrasa et al.  have recThis is a clear dissociation between spheroid formation and the absolute reflection of the stem cell phenotype, suggesting that the spheroid assay may only be used as a positive assay to measure stem cell behavior in cell lines that express appropriate adhesion determinants in its surface, such as E-cadherin in breast epithelial carcinoma cells. In conclusion, our results support the use of the spheroid assay as suitable for the study of stem cell traits in breast cancer cell lines showing an epithelial phenotype and expressing proper cell surface molecules (such as E-cadherin), though this assay is non-informative on cell lines that lack the expression of E-cadherin, either due to physiological reasons  or mutational driven (such as deletion of E-cadherin gene region in SKBR3 cells).Figure S1Expression of surface markers in LTSF (A) and STSF and NSF (B) breast cancer cell lines.Expression of 7 surface markers used to isolate mammary stem cells or breast cancer stem cells in the literature was checked by FACS. Isotypic control is represented by the grey curve and the specific staining by the white curve.(TIF)Click here for additional data file.Figure S2Sphere formation in clonogenic conditions.A) Quantitative limiting dilution assay for estimation of sphere forming cells in the population. Limiting dilution assay was performed as described in [ribed in , essenti(TIF)Click here for additional data file.Figure S3CD44+/CD24-/low phenotype in breast cancer cell lines.The expression of CD44 and CD24 markers was tested by FACS for each cell line and plotted and the percentage of each population is shown.(TIF)Click here for additional data file.Figure S4ALDH1 activity in breast cancer cell lines.ALDH1 activity was measured using the AldeFluor assay by FACS for each cell line and plotted, the percentage of ALDH1 positive cells is shown.(TIF)Click here for additional data file.File S1List of antibodies used.(DOC)Click here for additional data file.File S2Gene list of the differentially expressed transcripts between LTSF, STSF and NSF cell lines.(XLSX)Click here for additional data file.


In the present study, we screened a compound library containing 1,600 clinically used compounds with the aim to identify compounds, which potentially could be repositioned for colon cancer therapy. Two established colon cancer cell lines were tested using the fluorometric microculture cytotoxicity assay (FMCA). For compound comparison connectivity map (CMAP) analysis, NCI 60 data mining and protein kinase binding measurements were performed.Sixty-eight compounds were defined as hits with activity in both of these cell lines  at 10 μM drug concentration. Analysis of chemical similarity of the hit compounds revealed several distinct clusters, among them the antiparasitic benzimidazole group. Two of these compounds, mebendazole (MBZ) and albendazole (ABZ) are registered for human use. Data from the NCI 60 cell line panel revealed only modest correlation between MBZ and ABZ, indicating differences in mechanism of action. This was further supported when gene expression signatures were compared in the CMAP database; ABZ ranked very low when MBZ was used as the query signature. Furthermore, MBZ, but not ABZ, was found to significantly interact with several protein kinases including BCR–ABL and BRAF. Analysis of the diagnosis-specific activity of MBZ showed activity in 80 % of the colon cancer cell lines in the NCI 60 panel. Three additional colon cancer cell lines and three cell models with non-malignant phenotypes were subsequently tested, confirming selective colon cancer activity of MBZ.MBZ seemingly has repositioning potential for colorectal cancer therapy. In the past decades, target-based approaches with the aim to modulate specific diagnosis-related molecules and pathways have dominated the cancer drug discovery process and resulted in several successful novel therapies, best exemplified by the bcr–abl inhibitor imatinib for the treatment for chronic myelocytic leukemia (CML) .For primary screening, the colon cancer cell lines HCT 116 and RKO, obtained from American Type Culture Collection , were cultured in McCoy’s 5a medium supplemented with 10 % heat-inactivated fetal bovine serum, 2 mM 2.The colon cancer cell lines HT29, HT-8 and SW626 and the normal phenotype non-malignant epithelial MCF 10A, renal RPTEC/TERT1 and hepatocyte NeHepLxHT cell lines were used for validation experiments. These cell lines were all obtained from ATCC and cultured according to the protocols provided by the supplier. All the cell lines were cultured at 37 °C in a humidified atmosphere containing 5 % COThe Pharmakon 1600 library  consists of 1,600 annotated compounds previously used in the clinical setting. The library was delivered in 36 racks each containing 80 compounds at a concentration of 10 mM dissolved in DMSO. For the primary screening, aliquots of the DMSO solutions were transferred to 384-well Labcyte source plates  using a Biomek 2000 and stored at room temperature in containers under nitrogen atmosphere. These source plates were subsequently used to deliver 10 μM  of each drug to 384-well screening plates using a acoustic dispensing Echo 550 instrument equipped with Labcytes Access robotics (Labcyte).For dose–response studies, Labcyte source plates and the Echo dispenser were used in a similar manner to deliver different concentrations of each drug to destination plates using on board software protocols (Labcyte).The fluorometric microculture cytotoxicity assay (FMCA), described in detail previously  that contains genome-wide expression data for 1,309 compounds  build 02 (http://www.discoverx.com/tools-resources/publications-references). Results are presented as percent of control (POC). Selectivity score (S-score) is a quantitative measure of compound selectivity. S(35) is calculated as number of non-mutant kinases with POC <35/number of non-mutant kinases tested. Binding constants were determined with the same method using 11-point threefold serial dilutions of the compound. Curves were fitted using a nonlinear least square fit with the Levenberg–Marquardt algorithm  against a panel of 97 kinases tagged with DNA  software for analysis. A SI of <40 % in both colon cancer cell lines was set as the criteria for qualifying as a hit compound. Structural similarity to other compounds in the library was calculated based on a structural fingerprint consisting of chemical fragments located within the compound as computed by Vortex. Clustering of compounds based on these fingerprints was then performed within the Vortex program.50-values (the drug concentration resulting in a SI of 50 %).Concentration–response data of screening hits and standard agents were analyzed using the software GraphPad Prism4 . Data were processed using nonlinear regression to a standard sigmoidal dose–response model to obtain IChttp://discover.nci.nih.gov/cellminer/). Z scores are determined for each experiment/cell line pair by the subtraction from its intensity by the experiment mean (across the 60 cell lines) and division by the standard deviation of the experiment (across the 60 cell lines). The z score average was then calculated as the mean across all experiments that passed quality control criteria. The z score will have a mean of zero and a standard deviation of one.Analysis of data from the National Cancer Institute growth inhibitory screen in 60 cell lines (NCI 60 GI 50 data) was performed with the help by the NCI Cellminer database (The cytotoxic/antiproliferative activities in response to the 1,600 annotated compounds with documented clinical history at a concentration of 10 μM in the colon cancer cell lines RKO and HCT116 are shown in Fig. http://bioinformatics.charite.de/promiscuous/, von Eichborn et al. ABZ has previously demonstrated activity in several cancer types including colon cancer (Králová et al. Also from the standpoint of efficacy, MBZ may have advantages as demonstrated in a study of preclinical glioma models (Bai et al. We subsequently tested the binding affinities of MBZ and ABZ at 10 µM against a panel of 97 kinases. Whereas no kinase binding was observed for ABZ, MBZ appeared to be a potent inhibitor of several kinases with high affinity (POC <22, Fig. z score data revealed 80 % of the colon cancer cell lines to be sensitive, second only to the leukemia panel (Fig. Analysis of the diagnosis-specific activity of MBZ using NCI 60 nel Fig. a. The lunel Fig. b. The av50 of <5 µM whereas the drug was largely inactive in the non-malignant cell line models, thus indicating a potentially good therapeutic index in colon cancer (Fig. Five colon cancer cell lines, including those used in the primary screen, and three cell lines with non-malignant phenotypes were subsequently tested for response to MBZ Fig. c. All 5 cer Fig. c. IndeedIn conclusion, the overall results indicate that MBZ have repositioning potential for treatment of advanced colon cancer and clinical trials seem warranted.


The development of a drug-resistant cell line can take from 3 to 18 months. However, little is published on the methodology of this development process. This article will discuss key decisions to be made prior to starting resistant cell line development; the choice of parent cell line, dose of selecting agent, treatment interval, and optimizing the dose of drug for the parent cell line. Clinically relevant drug-resistant cell lines are developed by mimicking the conditions cancer patients experience during chemotherapy and cell lines display between two- and eight-fold resistance compared to their parental cell line. Doses of drug administered are low, and a pulsed treatment strategy is often used where the cells recover in drug-free media. High-level laboratory models are developed with the aim of understanding potential mechanisms of resistance to chemotherapy agents. Doses of drug are higher and escalated over time. It is common to have difficulty developing stable clinically relevant drug-resistant cell lines. A comparative selection strategy of multiple cell lines or multiple chemotherapeutic agents mitigates this risk and gives insight into which agents or type of cell line develops resistance easily. Successful selection strategies from our research are presented. Pulsed-selection produced platinum or taxane-resistant large cell lung cancer (H1299 and H460) and temozolomide-resistant melanoma  cell lines. Continuous selection produced a lapatinib-resistant breast cancer cell line (HCC1954). Techniques for maintaining drug-resistant cell lines are outlined including; maintaining cells with chemotherapy, pulse treating with chemotherapy, or returning to master drug-resistant stocks. The heterogeneity of drug-resistant models produced from the same parent cell line with the same chemotherapy agent is explored with reference to P-glycoprotein. Heterogeneity in drug-resistant cell lines reflects the heterogeneity that can occur in clinical drug resistance. The surviving daughter resistant cells are then compared to the parental sensitive cells using combination cell viability/proliferation assays such as the MTT , acid ph50 values. Three cell lines had higher levels of resistance but these were still relatively low-level at ~8–12-fold higher than the parental cells .To determine the level of drug resistance that occurs in the clinical treatment of cancer we can compare cell lines that have been established from cancer patients before and after chemotherapy Table  8–14). –14. 8–14For the purposes of this review we will divide drug-resistant cell models into two categories: clinically relevant models or high-level laboratory models. Both types of models have their advantages and disadvantages for research.50 value of the parent cell line. Examples of clinically relevant models are shown in Table Clinically relevant models are developed with the aim of trying to mimic the conditions cancer patients experience during chemotherapy. Doses of drug are lower, and a pulsed treatment strategy is often used where the cells recover in drug-free media. This mimics the cycles of chemotherapy a patient receives in the clinic. Disadvantages to clinically relevant models can include unstable resistance, very low-level resistance, and small molecular changes to detect and analyze. Based on the cell lines derived from the patients before and after chemotherapy shown in Table High-level laboratory models are developed with the aim of understanding potential mechanisms of toxicity and resistance to chemotherapy agents. Doses of drug are often high and treatment doses are escalated over time. Cells are frequently grown continually in the presence of drug or highly drug-resistant clones are selected from a mixed population. In some earlier drug-resistant models, mutagenesis was also induced prior to drug treatment , 23. HigChoosing a parental cell line is very important as it is the basis of all the subsequent experiments. The parental cell line should be very easy to maintain in cell culture as resistant variants usually become more challenging to grow. Ideally, the researchers performing the drug-resistant selection in the laboratory should be very familiar with growing the parental cells. Researchers experienced in growing a particular cell line will have more of an idea of when the cells need to be subcultured and when it is best to leave them. This experience is important when deciding when to subculture cells recovering from the drug treatment.50 value for the drug of interest as a two- to five-fold increase in resistance will result in an IC50 of the daughter resistant cell line remaining within the clinically relevant range. Table It is also important to consider the patient from whom the cell line is derived. If possible, it is good to choose a chemotherapy and radiation naïve cell line. Previous treatment with chemotherapeutic agents and radiation may have already caused changes in resistance pathways, and increased expression of drug resistance markers that may not be relevant to the agent being studied. However, chemotherapy and radiation naïve cell lines are relatively rare. As an alternative to a chemotherapy naïve cell line, choose a cell line with a relatively low baseline ICThe researcher needs to decide what kind of model they are trying to develop, a clinically relevant model or a high-level laboratory model. A clinically relevant model is informed by data gathered from the clinical administration of drug and usually has minimal escalation of the treatment dose. The sky is the limit for a high-level laboratory model where dose escalation is used extensively to achieve a large fold resistance. However, the solubility of the selecting agent will be final limiting factor in how much drug can be applied to cancer cells. Doses that approach the limit of solubility will not be in the clinically relevant range.The reality is that most selection strategies start out with a clinically relevant strategy and then are escalated within the clinical range and escalated further again beyond the clinical dose range to make a high-level model. The main reasons for this approach are the stability of the resistance phenotype produced and that the resistance established in the daughter cell line is statistically significant when compared to the parent cell line.Cell lines are frequently cultured in the presence of antibiotics in many laboratories. When establishing a new drug-resistant model, we recommend not using antibiotics as this does not mimic the clinical situation, cancer patients are not continually treated with antibiotics. Resistance mechanisms produced in the presence of antibiotics may not reflect clinical drug resistance.In order to produce a clinically relevant model of drug resistance, it is important to research how the chemotherapy agent is administered in the clinical treatment of cancer. The amount of chemotherapy administered intravenously (IV) is often expressed in the units milligrams per square meter. These can be converted to micrograms per milliliter or micromolar by consulting pharmacokinetic studies on the drug where the concentration achieved in the bloodstream is measured.2 cisplatin a peak-plasma level of ~6 μg/mL is reached but this quickly drops to <2 μg/mL after 2 h  polymerase (PARP) inhibitor class of drugs and is administered orally. The maximum tolerated dose of olaparib is 400 mg twice daily. Absorption is rapid and its peak-plasma concentration is reached within 1–3 h. Plasma levels then decline biphasically and it has a terminal elimination half-life of ~5–7 h . A phaseThe chemical stability of drugs used in establishing drug-resistant cell line models is also an important consideration when designing a selection strategy. For example, temozolomide an alkylating agent used in the treatment of glioblastoma and metastatic melanoma when in its active state, has a half-life of 25 and 60 min for the first and second phases  whilst d50; as the rate of recovery can be different between agents even if an equivalently cytotoxic dose is administered to cells. Figure The dose of drug used must be optimized for the parental cell line selected for use in developing the resistant model. A cytotoxicity assay in the parental cell line can be used to determine a suitable dose range. This dose range can then be compared to the pharmacokinetic information for the drug of interest. The rate of recovery from drug treatment is just as important as the IC2 as a single agent  cells, treatment doses were chosen in the range of IC setting . Two expIn most selection strategies the whole population of cells remains as one group throughout the selection, no cloning or other separation methods are used. If a pulse of drug is given, a small percentage of cells remain, which repopulates the flask. This new population of cells is then retreated with the next pulse , 19. AltIt is well known that tumors are heterogeneous –59. ConsThere are other physical methods of separation available to select different populations from a cell line such as limited dilution or cell sorting by flow cytometry. This can isolate cells which may be more resistant to chemotherapy than other populations within the same cell line . The advClonal populations can be established by limited dilution. This relies on the ability of the cells to grow independently of each other, and as such may not be suitable for all cell lines. It involves seeding cells at a very low density to result in one cell per well of a 96-well plate. Once the cells grow to confluency, they can be tested as a clonal population. Another method to obtain clonal populations is cloning rings . StandarA combination of drug treatment and cloning of cells has also been used to produce resistant models. KB-8-5-11 colchicine-resistant cells were developed from parental KB-3-1 cells by selecting clones after three stepwise increases in colchicine drug treatment . Clones Cloning can also be used to investigate heterogeneity within a developed drug-resistant model. A human colon cancer cell line (LoVo) was treated with cisplatin using a continuous exposure ranging from 0.005 to 20.0 μg/mL over 20 months in culture . At the It is reasonably common to have difficulties developing resistance or to produce drug-treated daughter cell lines which have not increased in resistance relative to the parental cell line. Selection strategies which do not produce drug resistance are interesting from a clinical perspective as this is what we want to achieve for cancer patients. Unfortunately, failures to develop drug resistance are generally not reported in the literature.As a risk-reduction strategy, a comparative selection strategy should be performed, where selection of multiple cell lines or multiple chemotherapeutic agents are performed in parallel in the laboratory. Figure An example of a comparative selection strategy used H69 SCLC cells treated with cisplatin or oxaliplatin for two time periods, 2 h or 4 days. The 4-day pulse selection produced more stable resistance than the 2-h pulse  Table 2.A large study by Tegze et al. aimed to develop 40 drug-resistant models from MCF-7 and MDA-MB-231 breast cancer cells using doxorubicin and paclitaxel as selecting agents. They succeeded in making 29 drug-resistant models, 10 doxorubicin and 4 paclitaxel-resistant MCF-7 cell lines, and 6 doxorubicin and 9 paclitaxel-resistant MDA-MB-231 cell lines. From this study it appears that paclitaxel resistance was easier to develop in MDA-MB-231 (ER-negative) cells and doxorubicin resistance was easier to develop in MCF-7 (ER-positive) cells.2 flasks were exposed to 50 μg/mL carboplatin and 150 ng/mL (H1299) or 50 ng/mL (H460) paclitaxel for 4 h. After this period, the drug was removed and the flasks were rinsed and fed with fresh complete media. The cells were then grown in drug-free media for 6 days, replenishing the media every 2–3 days. This was repeated once a week for 10 weeks. Table 50s of the platinum and taxane-resistant cell lines to a variety of chemotherapy agents. Resistance in the carboplatin-selected cells (1.5–2.3-fold) was considerably less than the resistance obtained in the paclitaxel-selected cells (2.4–4.4-fold). Selected cell lines show no obvious cross resistance pattern except within families of drugs, e.g., paclitaxel and docetaxel; carboplatin and cisplatin. The TAX-selected cells were also found to be resistant to vincristine, which is unsurprising since both agents affect microtubules. Both carboplatin-selected cell lines had a modest but statistically significant increased resistance to paclitaxel. The different patterns of resistance in cell lines selected under similar conditions show the complicated nature of multiple-drug resistance. For example, H1299-cpt became sensitive to vincristine, while after identical drug treatment, H460-cpt developed significant resistance to vincristine (2.9-fold). Overall, the low-level resistance (two- to five-fold) observed in these selected cell lines may be more clinically relevant to study than higher levels of resistance and this study highlights the importance to studying mechanisms in multiple models to identify relevant pathways.A study by our group  develope0 ng/mL H60 paclitIf a selection strategy fails to develop resistance, the treatment conditions can be altered in an attempt to produce higher levels of resistance. If the cells are growing very well after drug treatment, consider dose escalation. In some cases this may push the dose used above clinically relevant levels but it will increase the chance of resistance developing. Alternatively, the length of time the cells are exposed to drug can be increased or a pulsed-selection strategy could be converted to a continuous selection strategy. This may make the model less clinically relevant but may produce resistance that can be studied in the laboratory.The following section presents two case studies of drug-resistant cell lines developed in our laboratory, the reasons that selection conditions were chosen and the drug resistance outcomes of the developed cell lines. A case study using continuous selection is presented for lapatinib in breast cancer. A case study using pulsed selection is presented for temozolomide-resistant melanoma.50 method while a number of studies did not quantify the level of resistance. In contrast to the previously published models of acquired lapatinib resistance, the resistant models developed by us use a relatively low dose of lapatinib relative to the IC50 of the resulting cell line. To our knowledge our model of acquired lapatinib resistance, HCC1954-L are the first to show that extended exposure to low dose lapatinib results in significant lapatinib resistance, with resulting lapatinib IC50 values significantly higher than the concentration used for conditioning.Of the published models of acquired lapatinib resistance there is very little commonality in the procedures used to condition the cells, in either the concentrations of lapatinib used or in the determination of resistance status Table  65–72).–72.65–7250 of 0.43 ± 0.03 μM    Figure E. This rsitivity . The ressitivity F.50 was 0.44 ± 0.02 μM in the parental cells while the lapatinib IC50 in HCC1954-L cells was 2.73 ± 0.05 μM. This indicates that the HCC1954-L cells retain their resistant phenotype following a freeze/thaw cycle.In order to assess the stability of acquired resistance in the HCC1954-L cell line, sensitivity to lapatinib was assessed after freezing and thawing and following drug withdrawal. To establish a reliable cell line model of lapatinib resistance the phenotype must be stable when the cell line is frozen and re-thawed. To assess this, frozen stocks of the HCC1954-par and HCC1954-L cells were prepared in fetal calf serum containing 5% DMSO. After a minimum of 48 h in liquid nitrogen the frozen stocks were thawed and the viability of the stocks assessed by microscopy. The cells were then passaged a minimum of 3 times before lapatinib sensitivity assays were repeated  induced by long-term continuous treatment with sub-peak-plasma concentrations of lapatinib. The mechanisms of acquired resistance to lapatinib are being investigated in this model using proteomics and genomic techniques.50 concentrations of temozolomide were in the high micromolar range in melanoma cell lines. Previous studies in two melanoma cell lines demonstrated temozolomide IC50 concentrations of ~800 μM (50 ranged from 250 to 800 μM). However, in the clinical setting plasma levels of temozolomide only reach concentrations approaching 80 μM  and Malme-TMZ(B) display significantly increased IC50s for temozolomide of 440 ± 21 μM [1.44-fold increase (p = 0.004)] and 515 ± 45 μM [1.68-fold increase (p = 0.04)] , the pulse-selected variant of HT144, the IC50 increased to 490 ± 15 μM, which represents a 1.45-fold increase in resistance to TMZ (p = 0.002) . Malme-3M and the pulse-selected cell line Malme-TMZ have similar IC50s for EPI and mitoxantrone. Malme-TMZ is significantly more resistant to cisplatin (p = 0.001) and both HT144-TMZ and Malme-TMZ are significantly more resistant to docetaxel than the parent cell lines Malme-3M and HT144 , although the IC50 values are still in the very low nanomolar range.During drug selection of cell lines, cells can acquire altered sensitivity to other chemotherapeutic drugs. The two temozolomide-selected cell lines from each parent cell line with the highest levels of resistance [Malme-TMZ(B) and HT144(A)] were tested with four drugs to examine the chemosensitivity between the parent and the resistant cell lines Table . The melTwo temozolomide-resistant cell lines [Malme-TMZ(B) and HT144(A)] were established using two different selection methods. Duplicate selection proved useful in this selection strategy as one of the variants HT144-TMZ(B) did not develop resistance. Although the level of resistance induced was relatively low, these two cell lines provide unique clinically relevant models to study acquired temozolomide resistance in melanoma . The temOnce resistance has been established with the selection strategy the stability of the resistance needs to be determined. One important test of the stability of the model is the recovery of the drug-resistant phenotype from the frozen stocks. If the phenotype is lost or resistance is significantly lower on freeze thaw then the model will not be practical to use in the laboratory. If the resistance is not stable on freeze thaw then the drug-resistant cells need to be treated for longer, possibly with a higher dose of chemotherapeutic.The long-term stability of resistance also needs to be examined. Resistant cell models that have been selected by continuous exposure to drug should be grown for several months to determine if the resistance phenotype remains present. Some cell lines may be completely stably resistant Figure A and areAlternatively, the cells can be grown continuously in chemotherapeutic, either at the dose used in selection or a lower maintenance dose. This may be if the cells are not stably resistant on removal of the chemotherapeutic or if the researchers wish to ensure consistency of experiments. KB-CP20 cisplatin-resistant cells which were selected with increasing concentrations of cisplatin up to 20 μg/mL over a period of 6 months. The resistance was then maintained in media containing 5 μg/mL cisplatin . KB-5-8-Resistant models that are selected by pulse selection are often less stable than their continuously selected counterparts. However, IGROVCDDP is a stably resistant cell line established by pulse selection using dose escalation . Pulse-sMany mechanisms of resistance exist for each chemotherapy drug. The chemotherapeutic drug cisplatin has been studied in drug-resistant cell models for many years and mechanisms of resistance include decreased accumulation of drug, inactivation by glutathione and increased DNA repair . These mA comparative selection strategy could involve parallel selections of the same parental cell line with the same chemotherapy agent, under the same treatment conditions. Similar or different mechanisms could develop in these independent treatments. This is the randomness of natural selection. A study by Tegze et al. developed multiple drug-resistant cell lines from MCF-7 and MDA-MB-231 breast cancer cells . The parTwo models of cisplatin resistance were developed from H69 SCLC cells in the same research group in successive years , 89. TheThe cell line IGROV-1 has been used to develop cisplatin drug-resistant models by many research groups. IGROVCDDP cisplatin-resistant cells have an unusual resistant phenotype; they are cross resistant to paclitaxel as they overexpress P-gp . It is uThese examples demonstrate that the same cell line, treated with the same chemotherapy agent leads to the development of a heterogeneous range of drug-resistant models. Therefore, the development of drug-resistant models should be regarded as a process rather than an experiment that can be repeated in biological triplicate. If parallel models of the same treatment are produced the heterogeneity between drug-resistant cell lines should be examined with interest rather than dismissed as a non-reproducible experiment.We have provided a detailed guide to the decision-making process for the development and ongoing maintenance of drug-resistant cancer cell lines. There is no one right way to make drug-resistant cell lines. The case studies from our laboratories highlight how we have successfully developed models in a variety of ways for use in research projects.mycoplasma-free.H1299, H460, HCC1954, Malme-3M, OVCAR8, UPN251, and cells and their drug-resistant variants were grown in antibiotic and chemotherapy-free RPMI (Sigma #R8758). HT144 cells and their resistant variants were grown in antibiotic and chemotherapy-free McCoys 5A medium (Sigma). HT144, HCC1954, Malme-3M, OVCAR8, and UPN251 and their resistant variants were supplemented with 10% FCS . H1299, H460, and their resistant variants were supplemented with 5% FCS. All cell lines were maintained in a humidified atmosphere with 5% CO2 at 37°C. All cultures were tested routinely and were 4 cells/mL in 1 mL media. A control plate was set up separately with duplicate wells. On day 2 1 mL of media with drug was added to all plates excluding the control, which received drug-free media to the same volume. On day 5 media was changed on all plates and replaced with drug-free media. The control plate and one drugged plate were taken down and cell counted. Cell counts for the control were compared to the drug treatment. A percentage cell survival was calculated in order to see the effects of drug treatment on cell growth/survival.OVCAR8 or UPN251 cells were plated in duplicate into 6-well plates at a cell density of 1 × 103 cells were seeded in flat-bottomed 96-well plates and incubated overnight prior to addition of drug. Chemotherapeutics were obtained from St Vincent’s University Hospital, Dublin, Ireland. Lapatinib was purchased from Sequoia. Temozolomide was obtained from the National Cancer Institute. Other inhibitors and modulators were obtained from Sigma. Drug-free controls were included in each assay. Plates were incubated for a further 5  or 7 days (H1299 and H460) at 37°C in a humidified atmosphere with 5% CO2 and cell viability was determined using an acid phosphatase assay (To determine the cytotoxicity of chemotherapy drugs, cell growth/viability was measured using an acid phosphatase assay; 1.5–3 × 10se assay . Growth t-tests were used to determine significant differences using p < 0.05 as a cut off.All experiments were performed at minimum in triplicate. Two-sample, two-tailed Student’s Britta Stordal conceived the need for a review of methods of development of drug-resistant cell lines and wrote the manuscript. Martina McDermott, Alex J. Eustace, Steven Busschots, Laura Breen contributed their expertise in drug-resistant cell line development, contributed data for case studies and assisted with locating references, and drafting the manuscript. Norma O’Donovan, John Crown and Martin Clynes mentored the development of the drug-resistant cell lines used in the case studies, as well as contributing their expertise in drug-resistant cell line development. All authors approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Metastasis poses a great challenge in clinical management of many cancers. Metabolic demands of cancer cell proliferation – i.e. elevated aerobic glycolysis for biomass generation – have been well characterized, but the contribution of altered metabolism to metastasis remains to be elucidated. While elevated aerobic glycolysis, a phenomenon termed Warburg effect, is a hallmark of proliferative tumor cells, emerging evidence suggests that metastatic cancer cells have an opposite phenotype.We investigated the metabolism in cell lines of different metastatic capacity. In addition, to quantitatively study cell migration and metabolism, we used MCF10A breast epithelial cells with fluorescent histone tags along with live cell imaging and tracking by a custom MATLAB program to measure speed and behavior of migration.Our preliminary data suggest that the more metastatic cancer cells depend on mitochondrial metabolism. Furthermore, changing mitochondrial metabolism in MCF10A breast epithelial cell line affected not only the speed but also the pattern of cell migration. Consistent with the altered migratory behaviors, stimulation of mitochondrial metabolism changed cell adhesion markers.In sum, we show evidence that mitochondrial metabolism plays an important role in promoting cell migration and altering cell adhesion with implications for cancer metastasis.


Expression of E-cadherin was investigated as a hallmark of EMT by immunohistochemical examination. Cell motility and invasion were examined by wound-healing and invasion assays, respectively. The expression of Notch pathway molecules was analyzed by qPCR. Hypoxia increased the mRNA expression of Notch receptors, ligands and target genes, and Snail. Hypoxia decreased the expression of E-cadherin, and increased the motility and invasiveness of OSCC cell lines. γ-secretase inhibitor, a Notch-specific inhibitor, prevented these effects caused by h-ypoxia. These findings suggest that hypoxia induces EMT in OSCC cell lines via activation of Notch signaling, and inhibition of the Notch signaling pathway to suppress EMT may be a useful approach for the treatment of OSCC.Epithelial-mesenchymal transition (EMT) is an early step in the acquisition of invasiveness by malignant tumors. It has been clarified that the tumor microenvironment affects malignancy in a number of different carcinomas, in particular, that a hypoxic environment induces EMT. Activation of Notch signaling induces EMT, but it remains unclear how the Notch pathway is involved in oral squamous cell carcinoma (OSCC) under hypoxia. Three OSCC cell lines were cultured for examination under hypoxic (1% O Squamous cell carcinoma is the most common type of malignant neoplasm of the oral cavity. Due to the extent of recent investigation of its pathogenesis and management, the five-year survival rate for patients with oral squamous cell carcinoma (OSCC) has marginally improved within the last 15 years, yet it remains as low as 60% .Epithelial-mesenchymal transition (EMT) is a key step toward cancer metastasis. EMT is marked the by loss of epithelial characteristics (such as cell polarity and cell-cell junctions) and the gain of mesenchymal characteristics (including fibroblastic spindle-shaped morphology and increased motility). It has been proposed that EMT may provide a link between cancer metastasis and stem cell properties .The tumor microenvironment appears to play a prominent role in affecting EMT changes. For example, the E-cadherin transcriptional repressor, TWIST, is positively regulated by hypoxia-induced factor 1α (HIF-1α) . In a prNotch signaling influences a variety of cellular processes, including cell fate specification, proliferation, differentiation, apoptosis and the maintenance of stem cells . To dateCertain studies have revealed links between hypoxia and activation of Notch in solid tumors ,10. Low However, the molecular mechanisms by which hypoxia affects EMT and the Notch signaling pathway, in order to increase the invasiveness and metastatic potential of OSCC, are unclear. In this study, hypoxia potentiated EMT, which was induced by Notch signal activation, thus enhancing motility and invasiveness in human OSCC cell lines.2) or normoxia (21% O2) for 24 h. Notch activity was blocked by 5 μM DAPT, a γ-secretase inhibitor  in immunohistochemical, wound-healing and invasion assays.Human OSCC cell lines, HSC-2, HSC-4 and Ca99-2, were purchased from Health Science Research Resources Bank . Cell lines were cultured in Minimum Essential Medium Eagle , supplemented with 10% fetal bovine serum , penicillin (100 U/ml), streptomycin (100 μg/ml) and amphotericin B (0.25 μg/ml) . The cells were placed under hypoxia , and cDNAs were synthesized with a High-Capacity cDNA Reverse Transcription kit  from 1 μg of total RNA. qPCR was performed with the cDNA samples and 2X SYBR-Green PCR master mix (PE Applied Biosystems), using a Step One™ Real-Time PCR system (Applied Biosystems). The formation of the PCR product was monitored using SYBR-Green (Applied Biosystems). All samples were amplified in duplicate. The relative changes in the levels of the transcripts in each sample were determined by normalization with the β-actin mRNA levels. The sequences of the primers used in the real-time PCR are listed in Cells were fixed with 4% paraformaldehyde (Sigma-Aldrich) in phosphate buffered saline (PBS) and subjected to immunofluorescence staining. Cells were blocked with PBS containing 10% fetal calf serum and 0.1% Triton X-100 (Sigma-Aldrich). The primary rabbit polyclonal antibody used was anti-E-Cadherin . A fluorescent rhodamine-conjugated donkey anti-rabbit IgG antibody  was used as the secondary antibody.Cell migration was analyzed by a scratch wound-healing assay. Cells were grown to confluence and a scratch wound was made in the monolayer by dragging a pipette tip across it. Detached cells were washed away with PBS, and fresh medium was used for culture under hypoxia or normoxia. Photomicrographs of three areas were simultaneously captured under a phase contrast microscope , and migrated cells were counted in three scratched areas at magnification, ×400.5 cells/ml for a 24-well chamber, in serum-free medium. Medium containing 10% fetal bovine serum as a chemoattractant was added to the well. The cells were placed under hypoxia (1% O2) or normoxia (21% O2) for 24 and 48 h. Invaded cells were stained by Diff-Quik kit  according to the manufacturer’s instructions. Invaded cells were counted in three suitable areas by stereoscopic microscope  at magnification, ×400.’Cell invasion was analyzed using the BD BioCoat™ Matrigel™ Invasion Chamber , according to the manufacturer’s instructions. Individual cells were plated in the upper insert, at a density of 1.5×10Data are presented as mean ± standard deviation. Differences were analyzed to determine their statistical significance using Student’s t-test. P<0.05 was considered to indicate a statistically significant difference.To analyze whether Notch receptor activity was promoted by hypoxia in OSCC cell lines, Notch1-4 mRNA expression was investigated using qPCR . Notch1 We examined three Notch ligands, Jagged1/2 and Dll4 . ExpressThe expression of Notch target genes, HEY1 and HES1, was increased in all three OSCC cell lines (1.19- to 3.38-fold) . In partSnail, an E-cadherin repressor, was increased in all three OSCC cell lines by hypoxia (2.01- to 5.03-fold) . This inThe expression of E-cadherin was examined in a 24-h culture under hypoxia or normoxia. In all three OSCC cell lines, E-cadherin expression decreased upon culture under hypoxia compared with that under normoxia , indicatTo study cell motility, we used a scratch wound healing assay , in whicTumor metastasis entails a series of distinct, sequential steps, involving local tumor growth, invasion by transmigration through basement membranes and non-tumor host tissue, intravasation into blood vessels, dissemination and survival in the bloodstream, extravasation and re-establishment at distant sites . EMT als2, compared with the levels in 21% O2. These results suggest that a hypoxic environment induces EMT and an aggressive phenotype in OSCC cell lines.In the present study, hypoxia downregulated the expression of E-cadherin in three OSCC cell lines, as shown by immunohistochemical examination. Additionally, OSCC cell migration and invasion were also facilitated by culture in 1% OThe Notch signaling pathway exhibits different downstream effects depending on which sub-site or microenvironment it is influencing . Recentl2 or 21% O2 for 24 h was examined using qPCR. All three OSCC cell lines showed upregulation of the mRNA levels of Notch receptors, ligands and target genes under hypoxia, compared with the levels under normoxia, indicating that the Notch signaling was enhanced by the hypoxic stimulus in the OSCC cell lines. In addition, culture of lung (The expression of mRNA associated with Notch signaling in OSCCs cultured in 1% O of lung  and ovar of lung  cancer c of lung . HIF-1α  of lung . Stabili of lung –35.Upregulation of Snail correlates with metastasis and poor prognosis, whereas silencing of Snail is critical for reducing tumor growth and invasiveness ,37. HypoThe current study identified that hypoxia promoted cell motility and invasion, decreased the expression of E-cadherin and upregulated the Notch signaling pathway, indicating that hypoxia induced EMT in the OSCC cell lines. GSI inhibited this upregulation of cell motility and invasion, and the decrease in expression of E-cadherin under hypoxia. These results suggest that hypoxia induced EMT through the upregulation of Notch signaling activation. Elucidation of the mechanism of EMT through activation of the Notch signaling pathway may provide novel molecular targets and contribute to improving the prognosis of patients with OSCC.


Ascorbic acid demonstrates a cytotoxic effect by generating hydrogen peroxide, a reactive oxygen species (ROS) involved in oxidative cell stress. A panel of eleven human cancer cell lines, glioblastoma and carcinoma, were exposed to serial dilutions of ascorbic acid (5-100 mmol/L). The purpose of this study was to analyse the impact of catalase, an important hydrogen peroxide-detoxifying enzyme, on the resistance of cancer cells to ascorbic acid mediated oxidative stress.50) values, which indicate the concentration of ascorbic acid that reduced the number of viable cells by 50%, were detected with the crystal violet assay. The level of intracellular catalase protein and enzyme activity was determined. Expression of catalase was silenced by catalase-specific short hairpin RNA (sh-RNA) in BT-20 breast carcinoma cells. Oxidative cell stress induced apoptosis was measured by a caspase luminescent assay.Effective concentration , was silenced with specific sh-RNA. The effect was that catalase-silenced BT-20 cells (BT-20 KD-CAT) became more susceptible to high concentrations of ascorbic acid (50 and 100 mmol/L).The tested human cancer cell lines demonstrated obvious differences in their resistance to ascorbic acid mediated oxidative cell stress. Forty-five percent of the cell lines had an ECFifty-five percent of the human cancer cell lines tested were unable to protect themselves against oxidative stress mediated by ascorbic acid induced hydrogen peroxide production. The antioxidative enzyme catalase is important to protect cancer cells against cytotoxic hydrogen peroxide. Silenced catalase expression increased the susceptibility of the formerly resistant cancer cell line BT-20 to oxidative stress. Ascorbic acid (vitamin C), an essential nutrient for mammalian cells, acts as a cofactor of different enzymatic reactions, e.g. collagen synthesis. In addition, ascorbic acid has an important impact on oxidative stress caused by reactive oxygen species (ROS). Some of the most common ROS are superoxide anion, hydroxide radical and hydrogen peroxide . The proDifferent studies showed a toxic effect of extracellular ascorbic acid on a variety of cancer cell lines ‐9]. The. The9]. 50 ≤ 20 mmol/L) and 45% were more resistant (EC50 >20 mmol/L) to the incubation with ascorbic acid. In addition, the two benign cell types  belong to the more resistant cell group. The reason for the resistance of some tumour cell lines and the benign cells to ascorbic acid mediated hydrogen peroxide production may be due to efficient antioxidant defences. Immunohistochemistry has shown that cancer cells can have elevated levels of antioxidant enzymes . Ne. Ne31]. On the basis of our data, we were able to show a correlation between catalase activity and resistance of cancer cell lines to the ascorbic acid induced cytotoxic effect. Moreover, catalase is significant for cell protection against hydrogen peroxide. The ascorbic acid resistant cell line BT-20 became more susceptible to ascorbic acid after sh-RNA mediated catalase knock-down and the rate of apoptosis increased in these cells.The present study demonstrates great differences in the ability of cancer cell lines to prevent cell damage induced by increased levels of hydrogen peroxide induced by ascorbic acid. Forty-five percent of the cancer cell lines tested are not affected by ascorbic acid and hydrogen peroxide, respectively. Higher levels of catalase activity are found in cell lines that are more resistant to oxidative stress than in more susceptible cancer cell lines. This observation underlines the heterogeneity of cancer cells concerning their ability to prevent cell death induced by oxidative stress. Therefore, anticancer therapies based on increased generation of ROS are influenced in their efficacy by the antioxidative defence potential of cancer cells. In this context the results of the present study underline the important function of catalase as an antioxidative enzyme.The authors declare no conflict of interest.CK and CO drafted the manuscript, designed the study, set up the experiments, participated in data collection, analysed and interpreted the results and provided images and figures. MK, UK, BM, MS, and MiK carried out experiments and participated in data interpretation. UK, ACK and CTG revised the article for intellectual content and participated in editorial support. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-6882/12/61/prepubFigure S1. Glutathione peroxidase activity in BT-20 KD-CAT cells, BT-20 control cells and BT-20 wild type cells. The knock-down of catalase does not influence glutathione peroxidase activity, suggesting that glutathione peroxide may not play a major role in resistance to oxidative stress. Glutathione peroxidase was measured with BioVision’s Glutathione Peroxidase Activity Assay (#K762-100) according the manufacture’s instructions (www.biovision.com). For this, one million cells were homogenized in 200 μl cold assay buffer on ice, centrifuged at 10,000 xg for 15 min at 4°C and 50 μl of the supernatant were used for the assay. Glutathione peroxidase reduces hydrogen peroxide while oxidizing reduced glutathione (GSH) to oxidized glutathione (GSSG). The generated GSSG is reduced to GSH with consumption of NADPH by glutathione reductase. The decrease of NADPH, measured at 340 nm, is proportional to glutathione peroxidase activity. Glutathione peroxidase activity was normalized for protein concentration (determined by Bradford Assay) and expressed as mU per 100 μg of protein. The results shown are representative for 3 independent analyses. Click here for file


The development of monoclonal antibody (mAb) processes conventionally involves the generation of multiple cell lines in multiwell plates, cell line screening in shake flasks followed by final cell line selection and process optimisation in bioreactors. This process can typically take up to 18 months to generate a robust process suitable for early phase manufacturing and therefore any opportunity to streamline this process impacts directly on drug development timelines.This work describes the potential integration of the Micro-24 Bioreactor system  and the Duetz Microflask system (Applikon Biotechnology) into cell line development and early process development and demonstrates how these systems can be used for cell line evaluation and process optimisation. The Micro-24 Bioreactor system comprises 24 bioreactors (7ml working volume) each capable of independent temperature, dissolved oxygen and pH control. Cell cultures are carried out in a presterilised polycarbonate mammalian cell culture cassette with a central vent and are inoculated manually in a laminar flow cabinet before sealing with Type A single use closures and incubation under experimental conditions.2, 140 rpm; for Duetz Microflasks: 35°C, 5% CO2, 200 rpm, 80% humidity and for Micro-24 Bioreactors: 35°C, 650rpm, 6.95 pH, 30% DO. Viable cell numbers and viability were determined using a ViCell Cell Viability Analyser (Beckman Coulter) and antibody titres were determined using an Immunochemistry System (Beckman Coulter).The performance of a number of cell lines in the Micro-24 Bioreactor and the Duetz Microflask system was compared to that in shake flasks and bioreactors using cell numbers, viability and product titre. This data was then used to rank cell lines according to specific parameters. Unless otherwise stated a standard hydrolysate containing complex medium and standard experimental conditions were used throughout this work. For shake flasks these were: 35°C, 5% COA hydrolysate containing complex media fed batch process was run in each of the 24 bioreactors using the same model CHO cell line. Viable cell numbers (VCC), viability and titre were measured in each bioreactor and the coefficients of variation (CV) were calculated for each time point. This data was also used to calculate the specific productivity (SPR) for each bioreactor. At each time point CVs were generally less than 10% for each parameter measured and there was no significant difference between different rows of the cassette.To demonstrate the potential of this system to identify candidate mAb producing cell lines a series of experiments was carried out using the Micro-24 Bioreactor system and the results compared to those obtained in our standard cell line selection process. After initial screening in static multiwell plates during scale up a further screen in the Duetz Microflask system indicated significant differences in the performance of the remaining cell lines. In the standard hydrolysate containing batch process peak titres varied by up to 60% and there was a 2 fold difference in the overall SPR across the different cell lines.2=0.66 (Micro-24 v Duetz) and R2=0.72 (Micro-24 v shake flasks).The rank order of peak VCC was also similar in the Micro-24 and shake flasks (R2 = 0.7) although there was less similarity in overall SPR (R2 = 0.4).Based on titre and SPR data from the Duetz Microflask screen 12 of these cell lines were selected for further evaluation. Using the standard batch process conditions these cell lines were grown in parallel in the Micro-24 Bioreactors, Duetz Microflasks and conventional shake flasks. Although there were some differences in absolute titres the rank order of cell lines was similar in each of the systems tested here Figure  with R2=This data from the batch process was used to select 6 cell lines for evaluation in the standard fed batch process which was run in parallel in the Micro-24 Bioreactor and shake flasks.For each cell line the effect of feeding was similar in Micro-24 Bioreactors to shake flasks Figure  and the Clones ranked 1, 2, 5 and 12 in the Micro-24 Bioreactors were tested in conventional 2 litre bioreactors. In bioreactors the titre produced by the top ranked clone was approximately 20% higher than the clone ranked 12. The remaining 2 clones (ranked 2 and 5 in the Micro-24) produced intermediate titres.SEC, CE-IEF and NGHC data for the mAb produced in the Micro-24 showed no significant differences to that produced in control shake flasks.The Micro-24 Bioreactor also enables early stage process optimisation to be carried out at a small scale. The potential for media development is shown by the data in Table This data demonstrates that the Micro-24 Bioreactor can be used successfully to select high producing cell lines and to carry out initial process optimisation experiments. Although there were some differences in absolute data the rank orders and process trends identified in the Micro-24 Bioreactors were similar to those in conventional systems. Therefore this work has shown that the Micro-24 Bioreactor system could be used to replace shake flasks and bioreactors in cell line evaluation and early process improvement work.


Recent molecular profiles of hundreds of cell lines from The Cancer Cell Line Encyclopedia and thousands of tumour samples from the Cancer Genome Atlas now allow a systematic genomic comparison of cell lines and tumours. Here we analyse a panel of 47 ovarian cancer cell lines and identify those that have the highest genetic similarity to ovarian tumours. Our comparison of copy-number changes, mutations and mRNA expression profiles reveals pronounced differences in molecular profiles between commonly used ovarian cancer cell lines and high-grade serous ovarian cancer tumour samples. We identify several rarely used cell lines that more closely resemble cognate tumour profiles than commonly used cell lines, and we propose these lines as the most suitable models of ovarian cancer. Our results indicate that the gap between cell lines and tumours can be bridged by genomically informed choices of cell line models for all tumour types.Cancer cell lines are frequently used as  Cell lines are widely used in cancer research to study tumour biology. Here Domcke et al. compare genomic data from ovarian cancer cell lines with those from clinical ovarian tumour samples and identify cell lines that most closely resemble the genomic features of high-grade serous ovarian cancer. Genomic differences between cancer cell lines and tissue samples have been pointed out in several studies123Every year, >100,000 women around the globe die of ovarian cancerEpithelial ovarian cancer is traditionally divided into four major histological subtypes: serous, endometrioid, clear cell and mucinous carcinoma. Serous ovarian carcinoma is responsible for ~70% of epithelial ovarian cancersUntil recently, all histological subtypes were believed to arise from the ovarian surface epithelium and were often not differentiated in preclinical research or clinical trials. However, the discovery that the majority of invasive tumours may stem from different non-ovarian tissues accompanied by molecular analysis of the respective subtypes has led to the recognition that ovarian cancer is extremely heterogeneous and in fact comprises several distinct diseases12The most commonly used cell line models for ovarian cancer—and implicitly for the most prevalent subtype HGSOC—are SK-OV-3, A2780, OVCAR-3, CAOV3 and IGROV1 . However, their histopathological origin is partly unclear, and the need for well-characterized cell lines as models for the respective subtypes of ovarian cancer has been repeatedly voiced12in vitro studies of HGSOC. Although conclusions based on in vitro cell line experiments are not necessarily valid in a clinical setting, choosing cell lines most representative of certain subtypes should increase the value of cell line studies in preclinical research.Our comparison of data from TCGA and the CCLE reveals striking differences between some of the most commonly used cell line models and the majority of HGSOC samples. On the basis of our findings, we recommend an alternative set of ovarian cancer cell lines more suitable for TP53 mutations are near universal (95% of samples), and the few tumours with wild-type TP53 predominantly have flat copy-number profiles  are remarkably common in HGSOC, with the median fraction of the genome altered as large as 46% . Second,profiles . Third,  samples 5.TP53 , CCNE1, MYC, PIK3CA and KRAS .In addition to these average properties, alterations in cancer genes known to have a specific functional role in diverse cancer subtypes can help distinguish more or less suitable cell line models , right. TP53 mutation; and (4) in the absence of mutations in the seven ‘non-HGSOC’ genes (see above) commonly altered in other ovarian cancer subtypes . The suitability score is higher (1) the better the correlation between the copy-number profile of the cell line and the mean copy-number profile of HGSOC tumour samples; (2) the lower the frequency of non-synonymous mutations in protein-coding genes; (3) in the presence of a subtypes . Applyinsubtypes  to the lsubtypes . This orin vitro models for HGSOC. These cell lines have a TP53 mutation but no mutation in the seven non-HGSOC genes. Their copy-number profiles correlate well with the mean CNA of all tumours. They also have a high correlation with the copy-number profile of a single tumour sample  and one has wild-type TP53 and uncharacteristic mutations (OVMANA). However, the top-ranking HGSOC-like cell line, KURAMOCHI, as well as two further cell lines  also carry BRCA mutations, and therefore constitute possible models for in vitro investigation of ‘BRCAness’ in HGSOC  (ref. PTEN (Y155C)  ref.  and an i5C) ref. , IGROV1 f. PTEN Y5C Segmented copy-number data obtained from the CCLE website (platform: Affymetrix SNP6) , L(i) is the length of segment i and T is the threshold value of the CNi above which the segments are considered altered. In other words, FGA is the ratio of the sum of the lengths of all segments with signal above the threshold to the sum of all segment lengths. A threshold T of 0.2 was used for TCGA tumour samples and 0.3 for the CCLE cell lines. Different thresholds were chosen for the tumours and cell lines as the copy-number signal for tumours is often weakened due to contamination with non-tumour material or by tumour heterogeneity, whereas cell lines are purer. Similar reasoning was used when choosing a CN value >1.0 to define high-level amplifications in CCLE cell lines.For each segment To enable a gene-by-gene comparison of copy-number profiles from TCGA tumour samples and CCLE cell lines, the Bioconductor package CNTools was used to map the segmented copy-number data of all CCLE and TCGA samples to genesIn detail, the similarities and differences between cell lines and tumours on the copy-number level were quantified in three different ways see . For eacMutation frequencies were calculated as the ratio of mutation counts to number of bases covered. To focus on the mutations most likely to be functional, mutations in introns, untranslated regions, flanking and intergenic regions, as well as silent and RNA mutations, were excluded. The CCLE provided the number of reads per base in the sequenced regions (in ‘wig’ format), so the number of bases covered was given by the number of positions with one or more reads. TCGA, on the other hand, provided exon-wise coverage information, namely the length of each exon and an associated coverage per exon between 0 and 1. So the effective number of bases covered for each exon was given by the product of the length and coverage of the exon. The sum of these values is the total number of bases covered for each TCGA HGSOC sample.S, in which selected features of HGSOC are positively weighted and characteristics of other ovarian cancer subtypes are negatively weighted is given byThe extent to which the ovarian cancer cell lines match genetic characteristics shared by the majority of TCGA high-grade serous ovarian tumours was assessed using an empirical numerical score. This suitability score A is the correlation with the mean CNA of HGSOC tumours, B is 1 for cell lines harbouring a TP53 mutation and 0 otherwise, C is 1 for hypermutated cell lines and 0 otherwise, and D is the number of genes mutated among the seven ‘non-HGSOC’ genes recurrently altered only in the other ovarian cancer subtypes . This score serves to distinguish better and poorer cell line models of HGSOC, but is not considered a finely graduated ranking  were used for expression-based clustering of all CCLE cell lines. The top 5,000 genes by interquartile range (difference between the 25th and 75th percentile) across all cell lines were chosen, and 1−c (where c is Pearson’s correlation coefficient) was used as the distance for hierarchical clustering using Ward’s agglomeration methodRobust z-scores were derived separately for the two data sets before a combined analysis was performed using the 10,383 genes available on both platforms. We used data from the Affymetrix U133A platform for TCGA, although this meant missing data for one of the 316 tumour samples, as the CCLE expression data was obtained using Affymetrix U133 Plus 2.0 Arrays. The top 5,000 genes by interquartile range across the combined data set were chosen for principal component analysis as well as hierarchical clustering using 1−c as the distance, and complete linkage for agglomeration.For expression-based comparison of CCLE ovarian cancer cell lines and TCGA HGSOC tumour samples, http://www.cbioportal.org)55Data processing, analysis and visualization was done in the Perl and R programming environments, and statistical calculations were done using the R languagehttp://www.pubmed.org) on 4 June 2012 using several punctuation alternatives for the cell line names. This search method can lead to false-negative results, for example, it did not yield any hits for some cell lines such as COV318, although a few publications exist that do not refer to the cell line in the abstract.The number of Pubmed abstracts mentioning one of the 47 CCLE ovarian cancer cell lines was determined using the Pubmed search builder .Supplementary Figures S1-S4Genomic and histologic features of 47 ovarian cancer cell lines from the Cancer Cell Line Encyclopedia. Key features determined from literature research and our analysis of molecular profiles are summarized and cell lines are sorted according to approximate suitability as models of high-grade serous ovarian cancer.Ranking of 47 ovarian cancer cell lines from the Cancer Cell Line Encyclopedia based on average correlation of their expression profiles with those of high-grade serous ovarian cancer tumour samples from the Cancer Genome Atlas.


Depletion of Tregs has been shown to increase anti-tumor immunity. Tregs also play a critical role in the suppression of autoimmune responses. The study of Tregs has been hampered by a lack of adequate surface markers. Leucine Rich Repeat Containing 32 (LRRC32), also known as Glycoprotein A Repetitions Predominant (GARP), has been postulated as a novel surface marker of activated Tregs. However, there is limited information regarding the processing of LRRC32 or the regulatory phenotype and functional activity of Tregs expressing LRRC32.Elevated numbers of regulatory T cells (Tregs, we demonstrate that low levels of LRRC32 are present intracellularly prior to activation and that freshly isolated LRRC32+ Tregs are distinct from LRRC32- Tregs with respect to the expression of surface CD62L. Using LRRC32 transfectants of HEK cells, we demonstrate that the N-terminus of LRRC32 is cleaved prior to expression of the protein at the cell surface. Furthermore, we demonstrate using a construct containing a deleted putative signal peptide region that the presence of a signal peptide region is critical to cell surface expression of LRRC32. Finally, mixed lymphocyte assays demonstrate that LRRC32+ Tregs are more potent suppressors than LRRC32- Tregs.Using naturally-occurring freshly isolated Treg populations. In summary, understanding the processing and expression of LRRC32 may provide insight into the mechanism of action of Tregs and the refinement of immunotherapeutic strategies aimed at targeting these cells.A cleaved signal peptide site in LRRC32 is necessary for surface localization of native LRRC32 following activation of naturally-occurring freshly-isolated regulatory T cells. LRRC32 expression appears to alter the surface expression of activation markers of T cells such as CD62L. LRRC32 surface expression may be useful as a marker that selects for more potent T Proliferation was measured using a TopCount scintillation counter (Perkin-Elmer). Maximum proliferation was calculated by measuring the proliferation of cells in wells lacking Tregs and containing only Teffs and APCs. Background proliferation was ascertained via measurement of proliferation of Teffs only in the absence of APCs.Negatively selected CD4escribed . Each wep = 0.05 was considered significant, unless otherwise indicated.Statistical analysis was performed using Student's t test  or a three way ANOVA (mixed lymphocyte response assays) as indicated in the figure legends. A value of p value reported is reflective of the difference between the average proliferation of Tregs using LRRC32 as an independent variable while controlling for the individual assays as well as the titration. The R2 value represents the amount of variability in the ANOVA analysis that is accounted for by the presence or absence of LRRC32 on the surface of a Treg, the individual assays, as well as the titration.For the ANOVA, the overall Lrrc32 gene expression in Tregs [+ cell population with the highest expression of CD25 (CD25hi++), 2-3% of the CD4+ cell population with high expression of CD25 (CD25hi+), 17-20% of the CD4+ cell population with reduced expression of CD25 (CD25mid), or no expression of CD25 (CD25-). These analyses revealed that Lrrc32 expression increased with surface CD25 expression in a manner similar to Foxp3 expression -transfected e Figure , top rowHEK293 cells transfected with a C-terminus GFP-tagged LRRC32 construct lacking the signal peptide (C-GFP/LRRC32ΔSP) did not express surface LRRC32 by confocal microscopy , LRRC32 could not be detected in cell lysates of HEK293 cells transfected with the C-GFP/LRRC32ΔSP, suggesting that LRRC32 is either produced at levels that were undetectable or is rapidly broken down following translation -transfected HEK293 cell lysates had undetectable levels of Lrrc32 mRNA. Furthermore, as expected, GFP expression was observed in all of the HEK293 transfected cells examined  vs. 2.30% ± 1.05% (n = 6), data not shown), respectively. We subsequently confirmed that surface LAP expression is also observed in this cell population following activation with plate-bound anti-CD3 and soluble anti-CD28, in agreement with a recently published report .To address whether or not functional differences in LRRC32hi Tregs . As descs Figure , exhibitregs will be a prerequisite for successful adoptive immunotherapy techniques in humans. Murine adoptive immunotherapy models have demonstrated proof of concept that isolated Tregs can be used as therapy for several autoimmune disorders [regs in humans, however, is problematic, in part due to a paucity of specific surface markers. In this report, we demonstrate direct evidence of the surface expression of LRRC32 on freshly-isolated, naturally-occurring, and non-expanded CD4+ CD25hi human Tregs following TCR activation. We furthermore have characterized LRRC32 processing and demonstrate that sorted subsets of freshly isolated Tregs bearing this marker appear more suppressive than subsets lacking this marker.The isolation of naturally-occurring functional Tisorders -31. The Lrrc32 in CD25- Teffs can lead to Foxp3 upregulation and that these cells subsequently acquire a suppressive phenotype [Foxp3 has been shown to result in increased mRNA levels of Lrrc32, suggesting positive feedback between FoxP3 and LRRC32 [regs compared to CD25- Teffs, we demonstrate here that low levels of intracellular LRRC32 are detectable in naturally-occurring freshly-isolated unstimulated Tregs  binding B7.1 and B7.2, thereby depriving CD28 on Teffs of the ability to bind these co-stimulatory ligands, 2) inhibiting IL-2 transcription and progression of cells through the cell cycle via inhibition of cyclin D3, cdk4, and cdk6 production, and 3) decreasing the amount of time the TCR is engaged [+ and LRRC32- Treg subsets, we do not have data to suggest that differences in CTLA4 expression might have contributed to the observed differences in suppressive function in the LRRC32+ and LRRC32- Treg subsets. Clearly, the results in this set of experiments raise many more interesting questions and suggest that the role of LRRC32 in the context of these other cell activation markers is complex.Most natural FoxP3tivation ,45. As Ltivation -48. It aate GITR . Hence, t manner . Normaller [regs -52. Sincs Figure , it is p engaged -57. As weffs transfected with constructs containing either wildtype Lrrc32 or Lrrc32 lacking leucine rich repeat regions, the signal peptide, the cytoplasmic domain, or Lrrc32 with a mutated cytoplasmic residue postulated to be part of a PDZ domain and thus thought to bind an intracellular protein [reg cells. PDZ domain mutation studies have suggested that the intracellular portion of LRRC32 is critical for surface expression, and other studies examined the LRRC32 deletion mutants in the context of downstream effector molecules such as FoxP3 [Previous studies examining LRRC32 and T cell regulation have utilized T protein ,25. Thesas FoxP3 ,25. Thesas FoxP3 ,25. Howeas FoxP3 . Here, wIt is likely that the LRRC32 signal peptide is cleaved from the newly translocated preprotein by type I eukaryotic endoplasmic reticulum signal peptidase, based upon the amino acid sequence of LRRC32 . The ini+ CD4+CD25hiFoxP3+ Tregs express lower levels of surface CD62L compared to LRRC32- CD4+CD25hiFoxP3+ Tregs, suggesting that LRRC32 expression may alter surface expression of other activation markers of T cells such as CD62L. Finally, functional data demonstrate that LRRC32+ Tregs appear more suppressive compared to LRRC32- Tregs, suggesting that LRRC32 surface expression may be useful as a marker that selects for more potent Treg populations, although our data suggest that the functional difference in suppression between these two populations is not markedly robust. Hence, LRRC32 selection may be most useful when used in combination with other Treg markers [In summary, we have demonstrated a cleaved signal peptide site in LRRC32 is necessary for surface localization of native LRRC32 following activation of naturally-occurring freshly-isolated regulatory T cells. We show that LRRC32 markers .DVC, AKS, ABY, JVM, JO, HS, and EG performed experiments represented in this manuscript. DB provided statistical support. KDC, HS, and TSM provided valuable designed the study. DVC, TSM, and KDC drafted the manuscript. All authors read and approved the final manuscript.