Human epidermal growth factor 2 (HER2/ERBB2) is frequently amplified/mutated in cancer. The tyrosine kinase inhibitors (TKIs) lapatinib, neratinib, and tucatinib are FDA-approved for the treatment of HER2-positive breast cancer. Direct comparisons of the preclinical efficacy of the TKIs have been limited to small-scale studies. Novel biomarkers are required to define beneficial patient populations.In this study, the anti-proliferative effects of the three TKIs were directly compared using a 115 cancer cell line panel. Novel TKI response/resistance markers were identified through cross-analysis of drug response profiles with mutation, gene copy number and expression data.HER2-mutant and EGFR-mutant cells. High expression of HER2, VTCN1, CDK12, and RAC1 correlated with response to all three TKIs. DNA damage repair genes were associated with TKI resistance. BRCA2 mutations were correlated with neratinib and tucatinib response, and high expression of ATM, BRCA2, and BRCA1 were associated with neratinib resistance.All three TKIs were effective against HER2-amplified breast cancer models; neratinib showing the most potent activity, followed by tucatinib then lapatinib. Neratinib displayed the greatest activity in HER2-amplified, -mutant, and EGFR-mutant cell lines. This analysis revealed novel resistance mechanisms that may be exploited using combinatorial strategies.Neratinib was the most effective HER2-targeted TKI against  ERBB2/HER2) gene is frequently amplified or mutated in cancer.1HER2 gene amplification and/or protein overexpression has been well described in breast and other cancers, and numerous HER2-targeting therapies have been developed and approved. More recently, the advent of next-generation sequencing has facilitated the discovery of a spectrum of somatic HER2 gene mutations that serve as oncogenic drivers and can be therapeutically targeted.3 Several HER2-targeted therapies have been developed and approved for the treatment of HER2-positive (HER2+) breast cancer over the past three decades. HER2-targeted therapies can be broadly divided into three categories: the monoclonal antibodies trastuzumab (Herceptin) and pertuzumab (Perjeta), the antibody–drug conjugates trastuzumab emantasine  and trastuzumab deruxtecan , and small molecule tyrosine kinase inhibitors (TKIs).7 Trastuzumab plus pertuzumab and chemotherapy are the established first-line therapy for early and advanced HER2+ breast cancer.8 Three HER2-targeted TKIs, lapatinib (Tykerb/Tyverb), neratinib (Nerlynx), and tucatinib (Tukysa), have been approved for the treatment of HER2+ breast cancer after progression following HER2-targeted therapy.10 These drugs are all orally available and target the kinase domain of HER2. Lapatinib, the first Food and Drug Administration (FDA)-approved HER2-targeted TKI, is a reversible inhibitor of both epidermal growth factor receptor (EGFR) and HER2 and is approved for the treatment of advanced HER2+ breast cancer following progression on previous therapy, in combination with capecitabine.9 Neratinib is an irreversible inhibitor of EGFR, HER2, and HER4 and is FDA approved for the adjuvant treatment of early-stage HER2+ breast cancer after 1 year of trastuzumab treatment.10 Neratinib also received FDA approval for the treatment of metastatic HER2+ breast cancer in patients who received two prior lines of HER2-directed therapies.11 Tucatinib was recently approved by the FDA for the treatment of patients with metastatic HER2+ breast cancer in combination with trastuzumab and capecitabine.12 Tucatinib displays a higher selectivity for HER2 over the other HER family members, in comparison to lapatinib and neratinib.13 However, neratinib, an irreversible pan-HER inhibitor, is more potent in biochemical assays. Lapatinib is a reversible inhibitor like tucatinib but has the advantage of targeting both EGFR and HER2, unlike the HER2-specific tucatinib.13 As the number of therapies available to treat first-line treatment-refractory HER2+ breast cancer grows, it is important to understand the factors that differentiate these clinically approved TKIs.The human epidermal growth factor 2  was purchased from LC Laboratories. Tucatinib (200291) was acquired from MedKoo. Compounds were stored as dry powders at room temperature in the dark and dissolved in dimethyl sulfoxide (DMSO) before experiments. For dose–response testing, the compound stock was diluted in √10-fold steps in DMSO to obtain a 9-point dilution series, followed by further dilution in aqueous buffer and culture medium.A cancer cell line panel of 115 cancer cell lines was utilised in this study ,17 a total of 18 regions in EGFR, HER2, and HER3 were selected, and custom oligonucleotides were designed and synthesised at Illumina . Luminescence was quantified on an Envision multimode reader (PerkinElmer). Percentage growth was calculated relative to untreated controls. IC50 values were calculated by non-linear regression using IDBS XLfit 5. For all analyses, 10logIC50 values (in nmol/L) were used.Sensitivity to neratinib, lapatinib, and tucatinib was examined in cell proliferation assays as previously described.10logIC50 values of neratinib, lapatinib, and tucatinib on 102 cancer cell lines  >0.5 are considered similar and are connected with a line in the network tree. Compounds connected to neratinib, lapatinib, or tucatinib were retained. Hierarchical clustering was performed using the Ward method and 1 − ρ as measure of distance as described.18 Different colours in the network tree represent different clusters identified by the hierarchical clustering.The 19 and grouped according to the OncoTree classification. The colorectal cell lines were further divided according to a consensus classification based on gene expression.20 Drug sensitivity data were visualised in boxplots for disease types represented by at least two cell lines.Cell line tissue and disease types were annotated according to the Cellosaurus knowledge resourceEGFR, HER2, and HER3 were confirmed by targeted sequencing. The relationship between drug sensitivity and genetic alterations was examined by four different methods. First, a type II analysis of variance (ANOVA) was performed in R. The ANOVA analysis covered 40 genetic alterations, including the most commonly altered mutations in oncogenes and tumour-suppressor genes.18 Cell lines harbouring either EGFR mutations/amplifications or HER2 mutations/amplifications were analysed as four separate groups. Second, Mann–Whitney U test in R was performed to determine correlations between cell line sensitivity and all cancer gene mutations that occur in at least three cell lines. This resulted in 117 different cancer genes, plus EGFR and HER2 mutation/amplification. An adjusted p value of <0.2 was considered significant. Third, the effect on sensitivity of the presence of 20 clinically actionable genes with validated hotspot mutations or copy number variations was examined by type II ANOVA analysis. All p values were subjected to Benjamini–Hochberg multiple testing correction. The first three types of analysis are unbiased. The fourth method specifically analysed HER-mutated cell lines by Mann–Whitney U test to determine whether HER alterations alone are markers of response to each HER2-targeted TKIs.Mutation analysis was carried out in order to determine markers of inhibitor response. Cell lines were classified as genetically ‘altered’ if at least one allele was altered by point mutation, insertion, deletion, or copy number variation, that is, gene amplification or deletion of essential parts of a gene. The mutation status of cell lines was obtained from the Catalogue of Somatic Mutations in Cancer (COSMIC) and CCLE database. In order to ensure that alterations reported by the databases were relevant to cancer growth and drug response, all mutations must be reported as a hotspot mutation in Cancer Hotspots, described as oncogenic, gain of function, or being involved in drug response in OncoKB or Jax CKB, or be described as pathogenic in the literature. Mutation status of 10logIC50 values and gene expression, with associated p values determined. In order to understand whether a significant correlation is specific to the particular inhibitor, a Sigma (Σ) score was calculated based on the correlations for each gene with 168 reference compounds that were previously screened in the same cell line panel.18 Correlations were validated with the CCLE RNAseq,21 COSMIC CLP (v86), and the Genentech22 mRNA expression databases, which contain data for 104, 105, and 79 cell lines, respectively.Gene expression profiles of 99 of the 115 cell lines , HER3 (n = 10), or EGFR (n = 10) genes  than EGFR-amplified cell lines . This includes the lung cancer cell line NCI-H1975 that has an EGFRT790M mutation, which is associated with resistance to first- and second-generation EGFR inhibitors.Cell lines with alterations in the Is Table . NeratinHER3 varied considerably in sensitivity to neratinib. Of the ten HER3-mutant cell lines, five harboured an EGFR mutation or HER2 mutation or amplification as well (Table R475W cell lines (HEC-1 and HEC-1-B) showed good response to neratinib. However, both cell lines also had HER2 mutations. Likewise, both cancer cell lines (SKBR3 and AU565) that were HER3E952Q mutant were highly sensitive to neratinib were also HER2 amplified. HER3M91I UM-UC-3 and HER3D297H FaDu cell lines were moderately sensitive to neratinib, whereas the two cell lines (DLD-1 and HCT-15) that have three mutations in HER3 were relatively resistant to all three HER2-targeted TKIs. Therefore, the role of HER3 mutations in neratinib sensitivity remains unclear.Cell lines with mutations in ll Table . Two of EGFR and HER2, by a type II ANOVA.16HER2 amplification was identified as a drug response marker for all three TKIs, as expected for HER2-targeted therapies  and the affinity of neratinib (EGFR and HER4) and lapatinib (EGFR) for HER family members other than HER2.33 Brasó-Maristany et al. found that neratinib was more potent than lapatinib or tucatinib in the (HER2+ oestrogen receptor-negative (ER−)) SKBR3 and (HER2+ER+) BT474 breast cancer cell lines.34 The study also showed that the addition of trastuzumab enhanced the efficacy of all three TKIs. Similarly, Li et al. examined the three TKIs in combination with T-DM1.35 Co-treatment with neratinib and T-DM1 in HER2-amplified or HER2-mutated cell lines enhanced HER2 ubiquitination and internalisation, thereby increasing T-DM1 activity. This seems to be specific to the irreversible inhibitor, as the addition of lapatinib or tucatinib to T-DM1 did not increase HER2 ubiquitination in vitro.34Tucatinib is the most recently approved of the three TKIs and there are limited data comparing all three compounds in vitro. This study is the first comparison of the three HER2-targeted TKIs in 115 cancer cell lines. Three recent studies have carried out smaller-scale direct comparisons between neratinib, lapatinib, and tucatinib in cell line models. Nagpal et al. compared the anti-proliferative effects of neratinib, afatinib, lapatinib, and tucatinib and found that neratinib was most effective against the HER2+ human breast cancer cell line SKBR3 and the mouse-derived HER2+ cell line TBCP-1, followed by tucatinib.HER2 amplification resulting in the strongest correlation with response in all the analyses carried out  were present in C-33A, a cervical cancer cell line without amplification or mutations in EGFR, HER2, or HER3,38 that was potently inhibited by neratinib .41 The SUMMIT basket trial investigated neratinib in patients with solid tumours that had a HER2 or HER3 mutation.42 Of the 141 patients in this trial, encompassing 21 different cancer types, 125 had HER2 mutations and 16 had HER3 mutations. The SUMMIT trial provided clinical evidence  that neratinib has actionability against several oncogenic HER2 mutations.42 Neratinib and lapatinib response significantly correlated with EGFR mutation  occur in known HER2 hotspots associated with sensitivity to HER2-targeted agents.nib Fig. ; howeversis Fig. .PBRM1 and SMARCA4, respectively; Fig. SMARCA4 mutations prevalent in small cell ovarian cancer and PBRM1 altered in renal cell carcinoma.45SMARCA4-mutated cancers may depend on SMARCA2 and are therefore susceptible to synthetic lethality with SMARCA2 inhibition. This may be a potential combinatorial strategy to further enhance tucatinib response. Our analysis also suggested that APC mutations are a marker of tucatinib resistance. APC mutations are most commonly associated with the initiation of colorectal cancer, but APC is also sporadically mutated or lost in breast cancer, resulting in activation of the Wnt pathway, loss of cellular polarity, and cell migration.46SMC1A alterations were correlated with neratinib response. SMC1A mutations and overexpression have previously been associated with colorectal cancer aggression.47Beyond the HER family, this study highlights several potential novel mutation and gene expression markers of TKI response and resistance. Mutations in two chromatin re-modellers that epigenetically regulate gene expression correlated with sensitivity to lapatinib and tucatinib  breast cancer and our results support further preclinical examination of a CDK4/6 inhibitor in combination with lapatinib or tucatinib. High expression of several DNA damage repair genes, including ATM, BRCA1, and BRCA2, was associated with TKI insensitivity. In addition, inactivating BRCA2 mutations correlated with response to both neratinib and tucatinib  polymerase inhibitors may be a promising combinatorial strategy in this setting.None of the genes examined in the expression analysis were associated with resistance to all three TKIs Fig. . CDK6 exnib Fig. . The addHER2-mutant and EGFR-mutant models compared to the other HER2-targeted TKIs and was the most potent of the three TKIs in breast cancer models. Tucatinib showed excellent selectivity for HER2-amplified cell lines; however, it had minimal effect on HER2-mutant cell lines. A list of genetic markers of response and resistance were identified for each TKI that confirm the specificity of the drugs for their targets and provide new avenues of investigation regarding potential combination strategies.This study provides comprehensive profiling of three HER2-targeted TKIs in a large panel of cancer cell lines. Neratinib displayed the greatest anti-proliferative activity against Supplemental Material


To understand whether the effects of PTCy are unique and also to understand better the biology of GVHD prevention by PTCy, here we tested the relative impact of cyclophosphamide compared with five other optimally dosed chemotherapeutics  that vary in mechanisms of action and drug resistance. Only cyclophosphamide, methotrexate, and cytarabine were effective in preventing fatal GVHD, but cyclophosphamide was superior in ameliorating both clinical and histopathological GVHD. Flow cytometric analyses of blood and spleens revealed that these three chemotherapeutics were distinct in constraining conventional T-cell numerical recovery and facilitating preferential Treg recovery at day +21. However, cyclophosphamide was unique in consistently reducing proliferation and expression of the activation marker CD25 by alloreactive CD4+Foxp3- conventional T cells at day +7. Furthermore, cyclophosphamide restrained the differentiation of alloreactive CD4+Foxp3- conventional T cells at both days +7 and +21, whereas methotrexate and cytarabine only restrained differentiation at day +7. No chemotherapeutic selectively eliminated alloreactive T cells. These data suggest that constrained alloreactive CD4+Foxp3- conventional T-cell numerical recovery and associated preferential CD4+CD25+Foxp3+ Treg reconstitution at day +21 may be potential biomarkers of effective GVHD prevention. Additionally, these results reveal that PTCy uniquely restrains alloreactive CD4+Foxp3- conventional T-cell proliferation and differentiation, which may explain the superior effects of PTCy in preventing GVHD. Further study is needed to determine whether these findings also hold true in clinical HCT.Post-transplantation cyclophosphamide (PTCy) reduces the incidence and severity of graft-versus-host disease (GVHD), thereby improving the safety and accessibility of allogeneic hematopoietic cell transplantation (HCT). We have shown that PTCy works by inducing functional impairment and suppression of alloreactive T cells. We also have identified that reduced proliferation of alloreactive CD4 Allogeneic hematopoietic cell transplantation (HCT) is the only potentially curative therapy for many life-threatening hematologic diseases, but historically was not accessible to many patients for lack of a suitable human leukocyte antigen (HLA)-matched donor. HLA-haploidentical donors are available for nearly all patients, but early results of HLA-haploidentical HCT showed unacceptably high rates of graft failure, graft-versus-host disease (GVHD), and transplant-related mortality due to strong bi-directional alloreactivity . The adm+Foxp3+ regulatory T cells (Tregs)  . We also day +21 . We have day +21 .regs upregulate expression of ALDH, the main in vivo detoxifying pathway for cyclophosphamide  and ATP-binding cassette (ABC) transporters , 4, 7. Hsphamide , after asphamide , 4, 9. Tsphamide , 11, butsphamide –14. EachIt is unclear whether the effects of cyclophosphamide (CY) given in the early post-transplant period are unique. In 1971, survival after murine MHC-haploidentical HCT was compared after treatment with cyclophosphamide, methotrexate, mercaptopurine, chlormethine, or cortisol, each administered on days +5, +8, +11, and +14 . CyclophTo assess whether the biological effects of PTCy may be unique and provide further insights into our mechanistic understanding of the immunological mechanisms by which PTCy prevents GVHD, we investigated in our murine MHC-haploidentical HCT model  the relaad libitum.B6C3F1/Crl (donor) and B6D2F1/Crl (recipient) female mice, 10-12 weeks old at the time of transplant, were obtained from the Charles River Laboratories. Mice were housed in specific-pathogen-free conditions at the NCI and were provided food and water 6 B6C3F1 T-cell-depleted bone marrow +/- 40x106 red blood cell-depleted B6C3F1 splenocytes via tail vein injection. Recipient mice received levofloxacin-treated water from days 0 to +14. Survival was followed daily, and blinded assessments of weights and clinical scores using a standardized rubric , paclitaxel , vincristine , and cytarabine  were diluted with sterile PBS to appropriate concentrations, while bendamustine  was reconstituted using sterile water to 5 mg/ml per the manufacturer’s instructions and then further diluted to the appropriate concentrations with sterile PBS. Cyclophosphamide  was prepared as previously described , extracellular antibodies, fixation/permeabilization (eBioscience Foxp3/Transcription Factor Staining Kit), and intracellular antibodies. Single stains were used to generate compensations, and fluorescence-minus-one controls were prepared for CD25, Ki-67, and phospho-STAT5. Data were acquired on an LSRFortessa (BD Biosciences) and analyzed using FCS Express (De Novo Software). Cell subsets had to be at least 50 cells to allow for reliable further subsetting; subsets with denominators less than this threshold were excluded from further subsetting analyses.Blood and spleens were collected and processed as previously described . Viable k (clone 36-7-5), and BV711 anti-H2kk (clone AF3-12.1) from BD Biosciences; PE-Cy5 anti-CD8 (clone 53-6.7), PE-Cy7 anti-H2kd (clone SF1-1.1), and BV605 anti-Ki67 (clone 16A8) from BioLegend; and APC-eFluor780 anti-CD4 (clone GK1.5), PerCP-eFluor710 anti-Vβ6 (clone RR4-7), eFluor450 anti-Foxp3 (clone FJK-16s), and PE anti-phospho-STAT5 (Tyr694) (clone SRBCZX) from Invitrogen.Fluorochrome-conjugated monoclonal antibodies used for flow cytometry included BUV395 anti-CD3 (clone 145-2C11), BV786 anti-CD8a (clone 53-6.7), PE-CF594 anti-CD25 (clone PC61), AF700 anti-CD44 (clone IM7), BUV737 anti-CD62L (clone MEL-14), PE anti-H2kpost hoc correction for the multiple comparisons to the control group. Non-transformed data are displayed and are shown as box-and-whisker plots for ease of understanding, but transformed data were used for statistical testing. SAS/STAT software (SAS Institute Inc.), version 14.3, was used for analyses of survival, weight, and clinical score data. GraphPad Prism (GraphPad Software), version 8.4.3 was used for all other statistical analysis. P values <0.05 were considered statistically significant in an exploratory mode of analysis of repeated measurements of correlated immunologic outcomes.Survival distributions were compared using the exact log-rank test. Weight and clinical score area-under-the-curve (AUC) comparisons were performed using Wilcoxon’s rank sum test and were restricted to intervals in which ≥70% of vehicle-treated mice survived. Weight and clinical score data are shown as the mean +/- SEM. Due to strong serial correlations, weight and clinical score SEMs were not corrected for multiple measurements. Cell counts and median fluorescence intensities were natural logarithmically transformed and cell subset percentages were transformed using an arcsine transformation prior to one-way ANOVA. ANOVA results were followed with the Holm-Sidak Mice were treated under a protocol approved by the NCI Animal Care and Use Committee in accordance with the NIH Guide for the Care and Use of Laboratory Animals.We have previously shown that PTCy is maximally effective in our B6C3F1→B6D2F1 MHC-haploidentical HCT model when given between days +3 to +5 with dosing on days +3 and +4 being among the best dosing schedules and also is what is used clinically , 45–56. We next compared the optimal doses of these other chemotherapeutics with the previously established optimal dose of CY (25 mg/kg/day) in this MHC-haploidentical HCT model , with alCY was superior to all other chemotherapeutics in ameliorating clinical GVHD  in MTX-treated mice and, to a lesser extent, ARA-C-treated mice, whereas this percentage was reduced in CY-treated mice  Tregs at day +7  conventional T-cell subsets, in both blood and spleens  or proliferating at day +7 and only restrained alloreactive CD4+ conventional T-cell differentiation at day +7 (not day +21); indeed, MTX was associated with a more differentiated phenotype at day +21 compared with even vehicle-treated mice. These findings provide further support for reduced alloreactive CD4+ conventional T-cell proliferation at day +7 and preferential Treg recovery at day +21 as potential biomarkers for effective GVHD control by PTCy as identified in our previous publications on optimal dosing and timing of PTCy  alloreactive CD4+ conventional T cells at day +7. Overall though, the decline was modest and not associated with substantial clinical or histopathologic reduction in GVHD severity for most drugs.In retrospect, the lack of selective alloreactive T-cell elimination should not be surprising since cyclophosphamide, as an alkylator, is a non-cell-cycle-specific chemotherapeutic. Thus, it appears that PTCy may be killing a substantial percentage of T cells in a dose-dependent manner, but this effect is broad and not selective for alloreactive T cells , 61. IntMoreover, no chemotherapeutic induced pan T-cell depletion at day +7 compared with vehicle-treated mice, which may in part be attributable to intermediate rather than maximally tolerated doses being tested as intermediate doses were the most optimal for survival for each chemotherapeutic. Even so, we have previously shown that very high doses of PTCy, which did greatly reduce T-cell counts at day +7, resulted in preferential survival of alloreactive T cells at day +7 and actually led at day +21 to a tremendous rebound in alloreactive T-cell counts, consequent blunting of regulatory T-cell recovery, and worse GVHD in our model compared with intermediate dosing . Indeed,+ conventional T-cell proliferation at day +7 and later dosing on days +5/+6 was associated with a blunted relative recovery of Tregs by day +21, likely contributing in either case to the lower efficacy seen when compared with PTCy on days +3/+4  alloreactive CD4+ conventional T cells at that timepoint. The divergence in some immunologic effects of MTX and PTCy suggests that GVHD control by MTX may occur via a different mechanism than PTCy and may explain why MTX is only effective for acute GVHD clinically, while PTCy can prevent both acute and chronic GVHD.Our data showed no clear association between drug metabolism or resistance pathways and effective GVHD control. We had specifically chosen chemotherapeutics with varying involvement of ABC transporters and ALDH in resistance pathways Table 1 egs lack , likely egs lack , 31, 36.sphamide . Even soAn additional interesting finding of this study is that BEN was ineffective in ameliorating severe and fatal GVHD in our MHC-haploidentical HCT model. Recently, post-transplantation BEN has shown promise in pre-clinical murine HCT studies  and mixereg recovery at day +21, but also uncover that PTCy uniquely restrains alloreactive CD4+ conventional T-cell proliferation and differentiation. To what extent these findings hold true in patients, particularly those receiving adjunct immunosuppression beyond PTCy or to patients undergoing combined HCT/solid organ transplantation , and the Lasker Foundation. This work was made possible through the NIH Medical Research Scholars Program, a public-private partnership supported jointly by the NIH and contributions to the Foundation for the NIH from the Doris Duke Foundation, Genentech, the American Association for Dental Research, and the Colgate-Palmolive Company. None of these supporting institutions or companies were involved in the study design, data collection, data analysis, data interpretation, manuscript preparation, or the decision to submit the manuscript for publication.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.


The results of this study showed a correlation between longer DOX exposure time and lower IC50 values, which can be attributed to an increased cellular uptake and intracellular exposure of DOX, ultimately leading to cell death. We found that the total intracellular concentrations of DOX were a median value of 230 times higher than the exposure concentrations after exposure to free DOX. The intracellular uptake of DOX from solution was at least 10 times higher than from liposomal formulation. A physiologically based pharmacokinetic model was developed to translate these novel quantitative findings to a clinical context and to simulate clinically relevant drug concentration–time curves. This showed that a liver tumor resembling the liver cancer cell line SNU449, the most resistant cell line in this study, would not reach therapeutic exposure at a standard clinical parenteral dose of doxorubicin (50 mg/m2), which is serious limitation for this drug. This study emphasizes the importance of in-vitro to in-vivo translations in the assessment of clinical consequence of experimental findings.Cytostatic effects of doxorubicin in clinically applied doses are often inadequate and limited by systemic toxicity. The main objective of this in vitro study was to determine the anti-tumoral effect (IC The anthracycline doxorubicin (DOX) is a well-established chemotherapeutic drug, commonly used to treat solid tumors and hematologic malignancies. While DOX treatment has shown great potential in slowing down disease progression over the past decades, clinically used doses often show insufficient anti-tumor efficacy, whereas higher doses frequently result in systemic toxicity in patients. Therefore, there is a pressing need to develop drug delivery strategies with increased DOX-induced anti-tumor potency, while reducing off-target toxicity to noncancerous tissues .7.4 of 2.4 are key properties. Other carrier-mediated processes, such as solute carrier transporter SLCO1A2 and SLC22A16, and ATP-binding cassette transporter-mediated efflux, are also involved in the net influx into the cells -DOX trifluoroacetate (DOX IS) and -DOXol trifluoroacetate (DOXol IS) were purchased from Alsachim . Stock solutions (100 mM) for the cell viability experiments were prepared by dissolving DOX hydrochloride in DMSO . Lansoprazole stock solution (67.7 mM) was prepared by dissolving lansoprazole in DMSO.Resazurin sodium salt, penicillin-streptomycin amphotericin cocktail, lansoprazole, acetonitrile, ammonium formate, formic acid and phosphate buffered saline  tablets were purchased from Sigma-Aldrich . Methanol was purchased from Merck Millipore  and all solvents were HPLC grade or higher. All water used in the study was of ultra-pure grade  and the second was pegylated liposomal DOX . The micro-PK and pharmacodynamics (PD) were monitored during 24-, 48- and 72-h exposure at DOX concentrations of 0.001–1000 µM and 0.1–1000 µM for DOXS and DOXPL, respectively. The effect of lansoprazole (500 µM) on the two study formulations DOXS and DOXPL was also investigated.In this study, the intracellular uptake and antitumor effect of DOX was investigated following exposure of two different formulations in four human cancer lines (described in detail below). One study drug was DOX as a solution  and the human breast cancer cell line MCF7  were cultured at 37 °C with 5% CO2 and 95% humidity within a CO2 incubator. The HepG2, Huh7 and MCF7 cell lines were routinely cultured in DMEM supplemented with 1% antibiotic antimycotic solution and 10% FBS (cell culture media + FBS: CCMFed). The SNU449 cell line was cultured RPMI medium supplemented with 1% antibiotic antimycotic solution and 10% FBS (cell culture media + FBS: CCMFed). Standard culture medium without supplemented FBS was used during starvation (CCMSM). Misidentification of all cell lines was checked at the Register of Misidentified Cell Lines, and none of the chosen cell lines were on the list [50 values for DOX during normal and hypoxic conditions. SNU449 was selected as it is one of the most drug-resistant commercially available cell lines, which is not genetically engineered to be chemo-resistant [®, which is treatment of breast cancer in Europe and Canada.The three PLC cell lines , with the outermost wells filled with PBS to minimize the edge effect [Fed was removed, and the cells washed with 200 µL PBS. To allow synchronization of the cell cycle, 200 µL CCMSM was added to each well containing cells for 2 h prior treatment [Fed for two hours (when applicable), followed by treatment with DOXS or DOXPL. For DOXS, the DOX stock solution in DMSO was used to create a range of 0.001–1000 µM in CCMFed, and for DOXPL the product Doxil® was used to create a range of 0.1 to 1000 µM in CCMFed. Cells were treated with 200 µL/well of the respective DOXS and DOXPL preparations. Toxicity threshold values of DMSO were also evaluated in separate viability assays for each cell line. To determine the inert range of DMSO concentrations, the maximum dose of DMSO administered during DOX treatment (1% DMSO at 1000 µM DOX solution) times ten was set as the highest concentration. DMSO dilutions in CCMFed in a concentration range of 0.01–10% (v/v) was administered to cells 24, 48 and 72 h.Cells were plated at a seeding density of 1 × 10e effect . The celreatment . After cSM. Post treatment, culture medium was removed and the cells washed once with PBS. A volume of 150 µL resazurin solution was added and cells were incubated overnight. The relative fluorescence intensity was measured at excitation and emission wavelengths of 560/5 and 590/5 nm, respectively, on a Tecan Safire II plate reader. Six technical replicates were set up for each experimental group, with three biological replicates for all treatments, except for the pretreatment with lansoprazole where there was only one biological replicate.Cell viability was evaluated after drug treatment for 24, 48 or 72 h by a resazurin reduction assay, as previously described . A 1% soS or DOXPL corresponding to their calculated IC50 values, based on the pooled results of the cell viability assays in this study. The maximum concentration used for these experiments was chosen to be 200 µM. Cells were seeded at a seeding density of 4 × 106 cells per T75 flask , and allowed to attach overnight. Prior to treatment, CCMFed was removed, and the cells washed with PBS. To allow synchronization of the cell cycle, 15 mL CCMSM was added to each flask containing cells 2 h prior to treatment. Cells were treated for 24, 48 and 72 h, respectively. Following drug treatment, culture medium was removed and kept on ice. Cells were washed twice with 5 mL PBS, which was collected and kept on ice. A volume of 3 mL trypsin-EDTA was added to each flask, after which they were incubated for 4 min. The resulting cell suspension was collected and diluted with 3 mL CCMFed, and the cells counted using a TC20™ Automated cell counter and counting slides (Bio Rad). Using the histogram/gating option of the automated cell counter the average diameter of the cells was determined. The cell suspension was subsequently centrifuged at 140 g for 5 min, the supernatant removed, stored on ice, and the pellet was resuspended in 1000 µL ice-cold MilliQ water. Samples were lysed by two freeze–thaw cycles, consisting of snap freezing of samples in liquid nitrogen followed by thawing at 37 °C in a water bath for 10 min. After the final thaw cycle, samples were sonicated on ice for 30 s and stored at −20 °C until analysis.The cells were treated with concentrations of DOXm/z 544 (DOX), 546 (DOXol), 548 (DOX IS) and 550 (DOXol IS), each with a cone voltage of 8 V. The sampling frequency was 10 Hz.An ACQUITY UPLC I-Class system coupled to a single-quadrupole QDa mass detector  was used to quantify intracellular concentrations of both DOX and its main metabolite DOXol. The mobile phases consisted of (A) 5.0 mM ammonium formate in water:acetonitrile (95:5) with 0.1% formic acid at pH 3.01 ± 0.07 and (B) acetonitrile. The analytes DOX and DOXol were chromatographically separated under the following LC conditions. The gradient used was: initially 5% (B), then a linear increase over 0.00–3.00 min of 5–30% (B), followed by 3.00–3.25 min linear increase to 85% (B), and then held at 85% (B) 3.25–4.25 min. Then linear decrease 4.25–4.50 min of 85–5% (B), and finally 5% (B) maintained 4.50–6.00 min. The total run time was 6 min, the flow rate was 500 μL/min, the sample injection volume was 10 μL, and the sample manager temperature was 10 °C. The column was a C18 column  kept at 60 °C. In the single quadrupole QDa detector, the positive electrospray capillary voltage was set at 0.80 kV and probe and source temperatures were 600 °C and 120 °C, respectively. The quantification was performed in single-ion recording mode. The mass detection channels were set to PL-treated samples, the commercial formulation (2 mg/mL) was diluted to working standards in methanol (5–1000 µM) and stored as mentioned above. All samples were prepared in 96-well 1.00 mL round collection plates from Waters®. To construct calibration curves in sample relevant matrices, untreated control sample replicates were pooled and spiked (100 µL) with 25 µL of the appropriate working standard solution (0.25–1000 µM). Chilled (−20 °C) acetonitrile (375 µL) containing the isotopically labelled internal standards at matrix specific amounts (0.3–3 µM) were then added to precipitate cellular proteins. Samples were mixed (by pipetting up and down) before storage overnight at −20 °C. The following day, samples were brought to room temperature before mixing and subsequent centrifugation at 2200 rpm for 3 min at 4 °C. Portions of the supernatants (100 µL) were transferred to a new 96-well collection plate and dried under a gentle stream of nitrogen in a water bath (≈25 °C) using a 3D-printed manifold (U-PRINT) for at least 10 min. The residuals were dissolved in matrix appropriate volumes of mobile phase A (50 to 500 µL) and then injected into the instrument. Linear calibration curves (R2 > 0.995) for both DOX and DOXol were constructed between 0.05 and 50 µM for the intracellular and washing matrices and between 1 and 200 µM for the exposure media matrix. A volume of 25 µL of methanol was added to cell portion samples (100 µL) of unknown concentration and they were subsequently treated exactly as the calibration samples. Matrix effects and extraction recoveries were evaluated according to Matuszewski et al. in 2003 [Stock solutions of analytes and isotopically labelled internal standards were prepared in methanol (1 mg/mL). From these, working standards containing DOX and DOXol were diluted in methanol (0.25–1000 µM) and stored in amber vials at −20 °C. For quantification of DOX in 2003 . The datV), defined as the percentage of fluorescence value of treated cells compared to fluorescence value of untreated cells, according to Equation (1) [SM+R without any cells in the plate and SM+R.Cell viability (tion (1) :(1)V=Iex50 values, Equation (2), referred to as a four-parameter logistic model equation, was fitted to the experimental data:x is the concentration of DOXS or DOXPL, ΔV the viability at no DOXS or DOXPL exposure, i.e., corresponding to 100% viability, x50 the concentration of 50% viability, and γ a parameter connected to the slope of the sigmoidal characteristic of the logistic equation. In the fitting, S or DOXPL and was assumed to be equal to zero and consequently not fitted.To accurately calculate viability values and the ICx50. However, the estimation of x50 using only Equation (2) was found to be highly dependent on the other parameters, and at viability values far from x50.In principle, fitting of Equation (2) also gives x50 was estimated as the linear interpolation (Equation (3)) between the x values corresponding to the V value closest above (HV) and closest below (LV) the V50 = ΔV/2 value, i.e., half of the 100% viability value:The value of V50, determination of x50 could not be performed, and it was therefore excluded from the analysis. If more than one such experiment was detected for any replicate of a specific treatment condition, the entire treatment condition was excluded from further statistical study. The average and standard deviation of the x50 values of the different replicate experiments were calculated, and these values are here called IC50.In any experiment in which the cell viability did not reach less than 10 values for the cells treated with DMSO, Equation (3) was used and adjusted so HV and LV were the viability values closest above and closest below the V90 = ΔV × 0.9 value, i.e., 90% the ΔV value. From that equation, the standard error of IC10, here denoted V90, LV, HV.To calculate the ICURIC) and intracellular concentration (CIC). These were calculated with Equations (5) and (6), and are based on the UPLC-MS measured concentration in the cell lysates.For characterization of intracellular DOX and DOXol exposure there were two calculated parameters, cellular uptake ratio (CIC is an average intracellular concentration that includes the higher concentration that is expected for the cell nucleus and mitochondria [In Equation (5), there are two main assumptions. Firstly, chondria . SecondlURIC) was calculated according to Equation (6). This is an estimation of the fraction of DOX that was taken up from the surrounding media irrespective of the concentration or formulation applied. This parameter corresponds to the cellular availability of the study drug and is as such a dimensionless parameter. In this parameter, the CIC for both DOX and its main metabolite DOXol was included, as DOX is metabolized to DOXol intracellularly:ConcE is the exposure concentration, C_DOXIC is the intracellular concentration of DOX and C_DOXolIC is the intracellular concentration of DOXol, the main metabolite of DOX ). All calculations were performed in Excel 2016 and supporting visual basic macros.The cellular uptake ratio , logarithmic values were used in these comparisons and tests, which also had the advantage of higher homoscedasticy of data. The statistical software Minitab was used in these analyses.To judge the statistical significance of differences in responses for different cell lines, treatments and exposure times, mean values of ICClinical evaluation of the experimental results was performed applying a physiologically based modeling approach . The distribution was initially informed using reported information on initial (<24 h) liposomal distribution to plasma, liver, kidney, spleen and lung [PL elimination, i.e., release of DOX, and further optimization of the distribution  was subsequently estimated. The release of DOX was described under the assumption that this process predominately occurs by unspecific spontaneous disintegration of the liposomes. This is supported by comparable systemic disappearance of DOXPL and unloaded liposomes [PL) in plasma , was established as a combination of the interstitial (CInt) and intracellular concentration for liver cells. This parameter symbolizes the total concentration that the cells of interest will be exposed to. The established models were subsequently used, together with measured in vitro URIC ratios for DOX, to assess whether adequate DOX concentration levels in cancer cells are achieved, i.e., within target therapeutic zone, after a clinically relevant dose (50 mg/m2) DOXS or DOXPL. The therapeutic zone was defined on the basis of the cell viability investigations as the concentration range above the lowest concentration with detectable effect (~10%).A new parameter, cellular exposure concentration  IC50 values (µM) . In addition, Huh-7 showed a 3-fold difference to HepG2 and MCF7 when comparing Huh-7 with the other cell lines (p < 0.01). Furthermore, the relative difference between the mean IC50 values between HepG2 and MCF7 following both DOXS and DOXPL treatments showed no clear difference, despite their different tissue origins (p > 0.5 at any time point and treatment).Cell viability of HepG2, Huh7, SNU-449 and MCF-7 was measured after exposure to different concentrations of DOXues (µM) . The IC5S and DOXPL reduced the IC50 values . From 48 to 72 h, the changes in IC50 values were considerably lower for HepG2, MCF7 and SNU449 cell lines, while the increasing trend seems to continue for Huh-7 under DOXS treatment.As expected, there was a clear trend that longer exposure times for DOX0 values . From 24S versus DOXPL, it is notable that the IC50 values in all cancer cell models were higher for the DOXPL than DOXS within the same cell model. Specifically, in the HepG2 and MCF7, we observed approximately 10 times higher IC50 values for DOXPL compared to DOXS, as they ranged between 760 ± 120 µM (24 h in MCF7) to 110 ± 62 µM (72 h in HepG2), respectively (p < 0.00005). In the SNU449 cell line, and in some cases also for Huh7, the IC50 was not precisely determinable for DOXPL. However, where it was calculable, a similar relative difference between the treatments was observed as for the other cell lines.When comparing sensitivity to DOXectively  . This was not the case for MCF7, which had an IC10 of 0.23 ± 0.025% at 72 h exposure. While this is lower than the maximum dose of DMSO, the corresponding concentration of DOX (230 µM) was almost 10 times as much as was needed to kill all cells at 72 h exposure. These data suggest that DMSO was unlikely to contribute to toxicity of DOXs in any of the four different cell lines.The cell viability of the DOX-treated human tumor cells was investigated after a 2 h pretreatment with lansoprazole (500 µM), and the ICIn this study, a UPLC-MS method was developed to simultaneously quantify DOX and its primary metabolite DOXol in cell lysate (intracellular compartment) and in extracellular media. Matrix effects were most pronounced in the intracellular sample portions, suggesting ionization enhancement effects. Interestingly, extraction recoveries were higher for DOXol than DOX, but the isotopically labelled internal standards corrected for these differences . The selS or DOXPL corresponding to their calculated IC50 values  for DOXS and DOXPL into the human cell lines during the three different treatment periods are given in URIC for DOXS and DOXPL ranged from 4.5 to 1500 and 0.12 to 5.2, respectively. In general, the ratio URIC DOXS/URIC DOXPL had a median value of 87 across all cell lines and time points (p < 0.00005). The lowest URIC and CIC of DOX for both formulations was observed for SNU449, which is in accordance with this cell line having the highest IC50-value  for SNU449  .The model predicted extensive intracellular accumulation of DOX, mediated by the parametrization of DNA binding, where a maximum exposure to an interstitial DOX concentration ratio of ~10,000 was simulated for the liver a,b. Measr SNU449 c. In rel0 mg/m2) d. NotablS) or as the nano-sized pegylated liposome Doxil® (DOXPL). Three human liver cancer cell lines  and one human breast cancer cell line (MCF7), used as a reference, were selected based on previously published data and on their response to DOX [50 values for DOXS and DOXPL at wide extracellular concentration ranges using a novel and more accurate approach, prioritizing the crucial concentrations in the mid part of the slope in the viability curves (Equations (2)–(4)). The effects on cell viability between the different cell lines and exposure times were related to the cellular uptake and intracellular concentrations of DOX and DOXol. This comparison was also extended into a theoretical model where extra- and intracellular concentration–time profiles of DOX were simulated to assess the significance of experimental URIC values in terms of anti-tumor effect in a clinical situation. These findings drive the field forward in increasing the understanding how drug response between is affected by intracellular uptake of DOX, both in the context of preclinical research using cell lines, as well as the potential translation to the clinic through theoretical modelling.In this study, cytotoxic potency and its relation to intracellular exposure of DOX and its active metabolite doxorubicinol (DOXol) was investigated in four human cancer cell lines, following treatment of DOX as a solution  , the cellular exposure was predicted to reach the therapeutic zone (>0.1 µM) after a 50 mg/m2 dose  c,d. This/m2 dose c,d. This50 values at longer exposure times observed in this study could be attributed to an overall increased cellular uptake of DOX and a subsequent accumulation inside the cell nucleus, where it induces cell death through different mechanisms, including ferroptosis [®) [S or DOXPL at their IC50 values, were several fold higher than their exposure concentrations  . The DOXosis [®) ,49,50. Ttrations . With TAtrations .S or DOXPL in all investigated cell lines, with DOXS several-fold more potent than DOXPL. These ratios are in accordance with earlier reports, in which DOXS was shown to be 10 to 1000 times as potent as DOXPL during different exposure conditions [50 values than DOXS. For instance, Li et al. in 2020 reported DOX-loaded micelles in the range of 0.35–0.50 µM in three different cell lines  [50 for free DOX was reported to be 2.6–3.1 µM [50s were 1.4 µM and 0.50 µM, respectively [CIC for DOXPL was lower than for DOXS, showing a 1 to 3 log value difference for each cell line and time point. For MCF7, the ICUR value increased with exposure time, while no clear trends can be noted in the other cell lines. A plausible hypothesis for the lower in vitro potency for DOXPL is a low, variable and incomplete release of DOX extracellularly from the liposome  [PL and/or low intracellular DOX release. Some reports propose that the main mode of action for DOXPL is attributed to DOX that is released extracellularly and subsequently taken up by the cells [®) into cancer cell lines in vitro. Taking together our findings supporting a decreased potency of DOXPL compared to DOXS and the existing controversy in published literature, further research of the structure–activity relationships for cellular targeting and uptake for various types of TNP is encouraged, including pegylated liposomes.There was a clear difference in cell viability between DOXnditions ,48. Othe0 cells) . Their I6–3.1 µM . These fectively . In our  uptake) . Anotherhe cells ,54. Ther50 values for DOXs or DOXPL in the examined cell lines. One plausible explanation is that slightly acidic conditions (pH 6) are required in order to have a PPI-effect on DOX potency [DOX passes across cell membranes by passive lipoidal diffusion, as well as by carrier-mediated influx and efflux processes . Cellula potency .URIC of DOX and the lack of distinct correlation with the extracellular concentration in the four cell lines suggests that passive diffusion is a key mechanism for the overall intracellular delivery of DOX into these cell lines, which is supported by previous studies [S might contribute to reduced anti-tumor effect in avascular tumor regions in patients, as it reduces the intercellular diffusion of deeper tumor regions.The high  studies ,10. The  studies ,56. The S. However, the concentration of DOXol was still overall higher intracellularly, as the liquid volume measured extracellularly was consistently higher compared to the intracellular volume. The difference in concentration might be due to the fact that DOXol was formed inside the cells and is still mostly bound to different intracellular compartments, reducing the diffusion and/or carrier-mediated transport of DOXol out of the cells. The quantification of DOX and DOXol is assumed to reflect one single compartment, which is a simplification as DOX most likely accumulates in the cell nucleus, as previously reported. Instead, this experimental setup gives an average intracellular concentration that encompasses both the “free” DOX in the cytoplasm as well as the DOX intercalated in the nuclear and mitochondrial DNA.The metabolite DOXol can be quantified in vivo to measure how efficiently DOX is taken up and metabolized by cells; however, this strategy is seldom replicated for in vitro cell assays . This ca50 values were calculated based on the determined cell viability data at various exposure concentrations using a novel and more accurate approach, which prioritizes crucial concentrations in the mid part of the slope in viability curves. As the cellular uptake is several folds higher for the sensitive cell lines , the difference in the calculated in vitro IC50 could be attributed to cellular net uptake of DOX and intracellular disposition . These differences between cell lines, formulations and exposure time which affect the in vitro cellular uptake, intracellular retention and exposure, will affect cell viability after DOX-treatment and warrants further investigations in order to fully optimize the concept of localized tumor drug treatment.In all stages of drug discovery, there is a clear need to distinguish between the observed effects of the agent’s concentration-dependent potency and its potential active metabolites at the site of action. Improving the understanding of drug exposure at the site of action is especially relevant in pharmacological cellular or tissue models, as the fraction of the drug that reaches the site of action in the cell or some sub-cellular space is usually unknown. In this study, the ICS to be a more potent chemotherapeutic formulation compared to the nano-sized liposomal DOXPL (Doxil®) during the applied in vitro conditions. This is most likely due to a slower and incomplete uptake of DOX from the liposomal formulation, which might be a result of lower extracellular availability of DOX when dosed as DOXPL. While preclinical studies have reported on the potential of TACE and TNPs combination therapy in HCC treatment, the data in this study demonstrate the need to design TNPs with a high drug load and a tumor triggered release of DOX [S and DOXPL maintained over time (lower IC50), suggests that extending high local DOX concentration in the liver tumor during TACE treatment could be an efficient therapeutic strategy for HCC. The PBPK model used in this study provided a more accurate description of the DOX concentration–effect relationship. The performed simulations exemplify the relevance of in vitro to in vivo translations in the assessment of clinical consequence of experimental findings, and highlight the importance of tumor characterization before selecting a strategy for therapeutic intervention.Overall, the results of this study show DOXe of DOX . We foun


Cancer cells are addicted to ribosome biogenesis and high levels of translation. Thus, differential inhibition of cancer cells can be achieved by targeting aspects of ribosome biogenesis or ribosome function. Using RiboMeth-seq for profiling of the ∼112 2′-O-Me sites in human ribosomal RNA, we demonstrated pronounced hypomethylation at several sites in patient-derived diffuse large B-cell lymphoma (DLBCL) cell lines with a more severe perturbation in ABC-DLBCL compared to GBC-DLBCL. We extended our analysis to tumor samples from patients and demonstrated significant changes to the ribosomal modification pattern that appeared to consist of cell growth-related as well as tumor-specific changes. Sites of hypomethylation in patient samples are discussed as potential drug targets, using as an example a site in the small subunit (SSU-C1440) located in a ribosomal substructure that can be linked to DLBCL pathogenesis. Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin’s lymphoma in adulthood accounting for 30–40% of all non-Hodgkin’s lymphomas . TreatmeAn alternative approach to cancer treatment relies on the addiction of cancers to ribosome biogenesis . RibosomHere, we present RiboMeth-seq profiling of four cell line models of DLBCL as well as of samples from 17 primary patient DLBCLs. The cell lines comprised models of GBC-DLBCL (RL and HT) and ABC-DLCBL (OCI-Ly3 and U-2932). The patient DLBCL samples represented a wide range of clinical manifestations and were compared to reactive lymph nodes from three donors. We observed specific changes in ribose methylation pattern in DLBCL samples that seems to correlate with proliferation, and we suggest that such changes are a molecular feature of DLBCL. To our knowledge, this is the first demonstration of rRNA methylation changes in cancer specimens from patients and the observations are discussed in the context of targeting the changes in cancer treatment.Human lymphoma cell lines were maintained in RPMI-1640 medium (Gibco) supplemented with final concentrations of 25 mM HEPES (Gibco), 1 mM sodium pyruvate (Gibco), 100 U/ml penicillin–streptomycin (Gibco) and heat-inactivated fetal bovine serum (Gibco) at 10% for RL, HT and U-2932 or 20% for OCI-Ly3.Nineteen fresh-frozen DLBCL biopsies from patients diagnosed with primary DLBCL were obtained from the Department of Pathology at our institution . The specimens were collected during 2002–2013. The diagnoses were based on standard histology and immunophenotyping according to the WHO classification. All tissue samples were fresh frozen, stored at −80°C and embedded in Tissue-Tek O.C.T. Compound prior to RNA extraction. All biopsies had a tumor percentage of >80%. The majority of samples have previously been classified according to Hans’ classification into GCB or non-GCB subtypes . ReactivSections of formalin-fixed, paraffin-embedded samples of DLBCL (3 μm thick) were used for immunohistochemical evaluation of Ki-67 antigen, using the Ki-67 antibody MIB-1 clone (DAKO/Agilent GA626) following the manufacturer’s instructions. The staining was performed on Dako Omnis (Agilent), utilizing the EnVision Flex+ detection kit (GV800). The primary antibody was diluted using Antibody Diluent (Dako DM830) and subsequently incubated for 20 min. The sections were counterstained with hematoxylin and the percentage of stained Ki-67 nuclei was evaluated [Ki-67 labeling index (Ki-67LI)].Whole-cell RNA was isolated from cell cultures using Trizol Reagent (Thermo Scientific) according to the manufacturer. RNA from tumor biopsies and benign RLNs was isolated using Trizol Reagent and Qiagen miRNeasy kit according to the manufacturer. Whole-cell RNA from solid tissues pooled from five adult donors was purchased from BioChain .Five micrograms of whole-cell RNA was degraded by alkaline hydrolysis, size fractionated and ligated to adaptors as previously described ,22. In bApproximately 50 ng whole-cell RNA was treated with 2 U of TURBO™ DNase (Thermo Scientific) at 37°C for 20 min, extracted once with phenol:chloroform:isoamyl alcohol (25:24:1) and once with chloroform, and subsequently precipitated with 3× volume of 96% ethanol in the presence of 300 mM NaAc and 15 μg of glycogen. The DNase-treated RNA was reverse transcribed using iScript-cDNA kit (Bio-Rad) according to the manufacturer’s instructions except that the RNA was denatured in the reaction buffer at 90°C for 30 s prior to adding the reverse transcriptase. One-twentieth of the cDNA was used for qPCR analysis on a LightCycler Nano System (Roche) using FastStart Essential DNA Green Master (Roche) according to the manufacturer’s instructions. Relative fold expression was calculated using the ΔΔCq method, normalized to snRNA U6, and expression in RLN set to 1. RLNs and tumor biopsies, and DNA primers used for RT-qPCR analyses are listed in t-test and statistically significant differences between groups were indicated as *P < 0.05, **P < 0.01 and ***P < 0.001.Statistical analyses were performed using Microsoft Excel and GraphPad Prism 7. RiboMeth-seq results  were expressed as mean ± standard deviation, and SNORD expression data from RiboMeth-seq (RPKM) and RT-qPCR (ΔΔCq method) as mean ± standard error of the mean. Misincorporation at base modifications was expressed as 95% confidence interval of the median. Correlations between ribose methylation sites or summed ΔRMS scores compared to Ki-67LI were analyzed using Spearman’s rank correlation. Comparison of two groups was analyzed by two-tailed Student’s unpaired In order to define a baseline for perturbations of rRNA modifications in DLBCL, we first profiled ribose methylation levels by RiboMeth-seq in two cell lines representing GCB-DLBCL (RL and HT) and two cell lines representing ABC-DLCBL (OCI-Ly3 and U-2932). As a reference, we profiled three reactive lymph nodes Figure . In the The GBC- and ABC-DLBCL cell lines showed some common characteristics; e.g. SSU-C1440 was hypomethylated in all cell lines compared to RLN, and conversely, LSU-G4593 was hypermethylated compared to RLN Figure . To compPatient-derived cancer cell lines adapt to propagation in the laboratory and may accumulate additional mutations. Thus, we profiled patient DLBCL samples to validate that rRNA hypomethylation was of clinical relevance to DLBCL. Our sample comprised 17 DLBCLs, of which 7 were typed as GCB, 4 as non-GCB and 6 were not typed . The RMSWe next asked whether the methylation changes occurred in a coordinated fashion when individual tumors were compared. This would require extensive coordination because the box C/D guide RNAs are expressed from many different host genes. Indeed, when all RiboMeth-seq profiles were superimposed, a somewhat erratic picture emerged, suggesting absence of a regulatory pathway driving the methylation changes. However, in pairwise comparisons using Spearman’s rank correlation, it appeared that there was a coordinate decrease in methylation levels at three of the most affected sites . Increas1acp3Ψ1248, SSU-m7G1639 and SSU-m62A1851 to be hypomodified in both cell lines and primary DLBCL, in contrast to LSU-m1A1309 and LSU-m3U4500 that were unaltered  mutated genes in two whole-exome sequencing studies ,31. The The majority of methylation changes in DLBCL mirrored the changes observed during mouse development. This adds to the idea of relatedness between development and tumorigenesis, e.g. as observed in comparisons between developmental and pathological epithelial–mesenchymal transition (EMT) ,39. We ec-jun mRNA (Ribose methylations are found at conserved and functionally important parts of the ribosome . One of jun mRNA . RACK1, jun mRNA , is flanjun mRNA . RACK1 ajun mRNA . Thus, wjun mRNA . In thisIn conclusion, our study supports the idea that certain box C/D guide RNAs are relevant as biomarkers in cancer, and that these guide RNAs as well as the modification they install should be considered as a novel type of cancer targets.RiboMeth-seq data are deposited at NCBI Gene Expression Omnibus: GSE153502.zcaa035_Supplemental_FilesClick here for additional data file.


Protein phosphatase 2A (PP2A) is a ubiquitously expressed intracellular serine/threonine phosphatase. Deregulation of PP2A is a common event associated with adenocarcinomas of the colon and rectum. We have previously shown that breast cancer cell lines are sensitive to the PP2A activator FTY720, and that sensitivity is predicted by high Aurora kinase A (AURKA) mRNA expression. In this study, we hypothesized that high relative AURKA expression could predict sensitivity to FTY720-induced apoptosis in colorectal cancer (CRC). The CRC cell lines NCI H716, COLO320DM, DLD-1, SW480, and HT-29 show a high relative AURKA expression as compared to LS411N, T84, HCT116, SW48, and LOVO. Following viability assays, LS411N, T84, HCT116, and SW480 were shown to be sensitive to FTY720, whereas DLD-1 and HT-29 were non-sensitive. Hence, AURKA mRNA expression does not predict sensitivity to FTY720 in CRC cell lines. Differentially expressed genes (DEGs) were obtained by comparing the sensitive CRC cell lines (LS411N and HCT116) against the non-sensitive (HT-29 and DLD-1). We found that 253 genes were significantly altered in expression, and upregulation of CERS4, PPP2R2C, GNAZ, PRKCG, BCL2, MAPK12, and MAPK11 suggests the involvement of the sphingolipid signaling pathway, known to be activated by phosphorylated-FTY720. In conclusion, although AURKA expression did not predict sensitivity to FTY720, it is evident that specific CRC cell lines are sensitive to 5 µM FTY720, potentially because of the differential expression of genes involved in the sphingolipid pathway. With more than 1.9 million newly diagnosed cases in 2020 and nearly 935,000 deaths worldwide, colorectal cancer (CRC) is the third most prevalent cancer in men, and the second most commonly occurring malignancy in women , and molCRC is a heterogeneous disease with significant inter-patient differences in therapy response in terms of efficacy and toxicity, partly owing to molecular diversity ,8. SysteTo avoid unnecessary side effects and healthcare costs, oncological treatments should be reserved only for those patients who would benefit . HoweverProtein phosphatase 2A (PP2A) is a ubiquitously expressed intracellular serine/threonine phosphatase that maintains physiological cell function by counteracting kinase-mediated phosphorylation. PP2A plays an important role in tumor suppression , and dec®), a structural analogue of sphingosine developed from the fungal metabolite myriocin [FTY720  of 5 mmol/L. It was also shown that FTY720 restored PP2A activity by suppressing SE translocation (SET) and the cancerous inhibitor of PP2A (CIP2A), two endogenous PP2A inhibitors, independently of its antagonistic activity towards S1PRs [The mechanisms responsible for FTY720-induced cancer cell death are poorly understood, and appear to vary according to the type of cancer. FTY720 was found to moderately inhibit the survival of CRC cell lines with a half-maximal inhibitory concentration  signaling pathway, dephosphorylation of extracellular signal-regulated kinase (ERK), and inhibition of SphK . The larFTY720 is known to have minimal cytotoxic effects on normal colonic cells , and couAurora kinase A (AURKA) mRNA expression was identified as a biomarker of PP2A-dependent growth factor activation, and was used to classify breast cancer cases into a novel therapeutic class of tumors with predicted susceptibility to the restoration of PP2A activity using FTY720 (unpublished data). It would be of interest to evaluate whether AURKA expression might offer a similar opportunity to predict novel therapeutic subtypes in CRC.The main aim of this study was to assess AURKA expression in CRC cell lines as a predictive biomarker of sensitivity to FTY720, and to group CRC cell lines into sensitive and non-sensitive groups following exposure to FTY720. 2 atmosphere. The media were supplemented with penicillin G (100 U/mL) and streptomycin (0.1 mg/mL). The human CRC cell lines LS411N (CRL-2159), T84 (CCL-248), HCT116 (CCL-247), SW48 (CCL-231), LOVO (CCL-229), NCI H716 (CCL-251), COLO 320DM (CCL-220), DLD-1 (CCL-221), SW480 (CCL-228), and HT-29 (HTB-38), acquired from the American Type Culture Collection , were cultured in Dulbecco’s Modified Eagle Medium (DMEM)-high glucose  with 10% foetal bovine serum (FBS) (Sigma-Aldrich). They were grown at 37 °C in a 5% CO® Mini Kit , and quantified by 260/280 nm using UV-spectrophotometry . The quality of the RNA was determined by the RNA integrity number (RIN) using the RNA6000 Nano protocol on the Agilent 2100 Bioanalyzer system . RNA extraction was carried out using the RNeasy® Plex gene expression assay (Thermo Fisher Scientific) [® Plex gene expression assay. The limit of detection (LOD), defined as the sample that yields a signal higher than three times the standard deviation of the mean of the blank , was calculated. The gene expression data of AURKA were divided by the geomean of the gene expression data of the reference genes. The mRNA was isolated from the mentioned CRC cell lines and analyzed using the QuantiGeneentific) . Gene ex® Plex gene expression assay results, three cell lines predicted to be sensitive to FTY720  and three cell lines predicted to be non-sensitive to FTY720  were cultured with various concentrations of FTY720.Based on the QuantigeneThe FTY720 was purchased from Sigma-Aldrich, and dissolved in 1% dimethyl sulfoxide  to a primary concentration of 58 mM. Working solutions of FTY720 and DMSO (vehicle control) were prepared fresh in the culture medium.g for 10 min. The supernatant was decanted, and 100 μL of DMSO was added to each plate. The plate was then placed on a thermomixer  for 2 min at 300 rpm to ensure that all crystals dissolved, and then transferred to a spectrophotometer , and the absorbance at 570 nm was measured. The same procedure was repeated after 48 h. This procedure was repeated twice. Cell viability assays were carried out on six CRC cell lines, of which three were predicted to be sensitive to FTY720, and three were predicted to be non-sensitive to the PP2A activator. The CRC cell lines were seeded in a 96-well plate, and treated with 0.05 µM, 0.1 µM, 0.5 µM, 1 µM, 2.5 µM, 5 µM, 10 µM, and 25 µM FTY720, and cell survival rate was evaluated using a standard 3--2,5-diphenyltetrazolium bromide (MTT) assay (Sigma-Aldrich). After 24 h, the medium was aspirated, and fresh medium containing MTT (5 mg/mL) was added to each well. The cells were incubated at 37 °C for 4 h, after which, the plates were centrifuged at 14,000× ® platform .RNA samples were submitted for library generation and sequencing to Beijing Genomics Institute (BGI). In brief, enrichment of poly(A) mRNA was performed using poly(T) oligo attached to magnetic beads, followed by fragmentation. First strand cDNA synthesis was carried out using random hexamer N6 primers and reverse transcriptase, followed by adaptor ligation to cDNA fragments. Following PCR amplification and purification, single-stranded DNA circles were generated in a final library. DNA nanoballs (DNBs) were subsequently generated by rolling circle replication, which underwent paired end sequencing (100 bp) on the DNBseqThe raw image data produced by the sequencer was converted by BGI into sequences using base calling software. Data filtering was then carried out to obtain ‘clean reads’ facilitating correct alignments in downstream analysis. This included the identification and removal of adaptor sequences, as well as the removal of low quality reads, and reads with lengths smaller than the set threshold. The average quality of reads of 20 bases was calculated from the 3′-end until the average quality was larger than nine. The bases that negatively impacted the quality in the 3′-end were removed. Assessment sequencing was conducted where the distributions of the read lengths were plotted and sequenced. The gene expression level was calculated using reads per kilobase per million mapped reads (RPKM), which is a normalisation technique used to eliminate any variation caused by differences in sample quality and coverage. The sequencing depth was normalised by dividing the total read counts in a sample by a scaling factor of one million, resulting in reads per million mapped reads (RPM). The gene length was also normalised by dividing the RPM values by the length of the gene in kilobases.The resultant RPKM values were used to compare the difference in gene expression among samples. When multiple transcripts for a gene were present, the longest transcript was used to calculate its expression level and coverage. The analysis of differentially expressed genes (DEGs) was conducted based on the analysis method of the Poisson distribution. This included the screening of genes that were differentially expressed among the samples analyzed. The Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was then conducted.® Plex gene expression assay was non-parametric, the Mann–Whitney U test was used to test the hypothesis that AURKA mRNA is significantly overexpressed in CRC cell lines that are sensitive to the PP2A activator FTY720, compared to CRC cell lines that are non-sensitive.All statistical analysis was carried out using Microsoft Excel or the SPSS statistical package v23 . Given that the gene expression data extracted from the QuantiGeneAURKA expression was normalized against the geometric mean of the three reference genes TBP, HPRT1, and PPIB, and was used to predict PP2A activity. As shown in 50 at a dose lower than 5 µM.Cell viability assays were carried out to test whether AURKA expression predicted FTY720 sensitivity. The dose-dependent effect of FTY720 on CRC cell lines provided information on their sensitivity to PP2A activation. Sensitivity to FTY720 was defined as reaching ICThe results of the cell viability assays after 24 and 48 h of exposure to FTY720 are illustrated as line graphs in Z = −1.389, p = 0.165), leading us to accept the null hypothesis that AURKA mRNA expression does not predict sensitivity to FTY720. Based on the results of the cell viability assays, two sensitive and two non-sensitive steady state CRC cell lines were sent for RNA sequencing. The Mann–Whitney U test was used to test the hypothesis that AURKA mRNA is significantly overexpressed in CRC cell lines that are sensitive to FTY720, compared to CRC cell lines that are non-sensitive. The difference in AURKA expression between the sensitive and non-sensitive groups was found to be non-significant using the Mann–Whitney U test  < 0.05). For an overview of the DEGs, volcano plots were drawn where the fold-change of gene expression was plotted on the x-axis versus the significance of difference in gene expression between pools on the y-axis (The gene expression of two sensitive and two non-sensitive CRC cell lines for FTY720 were investigated by RNA sequencing. We decided to select LS411N (CMS1) and HCT116 (CMS4) as representative of the sensitive group, since both were derived from primary adenocarcinomas of the colon. T84 was not selected because it was derived from lung metastatic tissue. The DEGs were obtained by comparing the sensitive CRC cell lines against the two non-sensitive ones, which were DLD-1 (CMS1) and HT-29 (CMS3). We found 253 genes that were significantly altered in expression, including 195 upregulated and 58 downregulated genes  activity. The KEGG database was used to further identify critical signal regulation pathways. The top significant KEGG pathways were identified, and are shown in The results of this study suggest that CRC cell lines have a differential response to the PP2A activator FTY720, and that a subset of CRC cellular models have deregulated pathways that promote sensitivity to PP2A activation. Although previous studies in breast cancer cellular models showed that sensitivity to low-dose FTY720 could be predicted by a high mRNA expression of AURKA (unpublished data), this study shows that sensitivity to FTY720 in CRC cell lines cannot be predicted using this model. In addition, breast cancer cell lines are responsive to lower doses of FTY720 , suggest50 at doses of FTY720 less than 5 µM, were HCT116, T84, LS411N, and SW480. Since DLD-1 and HT-29 reached IC50 at doses greater than 5 µM, we classified them as non-sensitive to FTY720. Although in other studies, SW480, HT-29, and DLD-1 cell lines were reported to be sensitive to 10 µM of FTY720 [The sensitive cell lines, which reached ICf FTY720 . The DEGs obtained by comparing the sensitive and non-sensitive groups (as classified in this study) suggest that the main driver of sensitivity to FTY720 in CRC cells is associated with the sphingolipid pathway, represented by the CERS4, PPP2R2C, and BCL2 genes. Ceramide is known to be a tumor suppressor, promoting PP2A phosphatase activity , and leaSphingolipids are a family of molecules enriched in lipid rafts whose metabolites are emerging as bioactive signaling molecules involved in the development of cancer. S1P plays a pivotal role in the early stages of colorectal carcinogenesis: it increases cell proliferation, inhibits apoptosis, and promotes oncogenic transformation. The two isoforms of SphK, SphK1, and SphK2, catalyse the conversion of the membrane phospholipid sphingosine to the bioactive lipid S1P, an oncogenic mediator which drives a number of vital processes in tumor cells, including cell growth, survival, migration, invasion, and angiogenesis . SphK1 rExpression levels of SphK1 are significantly higher in CRC cells and tissues compared to normal colonic mucosa, and are associated with more advanced tumor stages and a poorer prognosis in CRC patients ,42,43,44Expression of SphK2 and the S1P transporter sphingolipid transporter 2 (SPNS2) are also upregulated in CRC specimens ,50. SphKDownregulation of SphK1 expression sensitized RKO cells to cisplatin (DDP) in a concentration and time-dependent manner . SimilarThe pathogenesis of CRC may, therefore, be mediated by ceramide and members of the SphK/S1P pathway, which could represent selective targets for chemoprophylaxis. The results of this study show that the expression levels of members of the sphingolipid pathway are associated with sensitivity to FTY720 in CRC cell lines, and show potential for use as predictive biomarkers. Further studies on larger panels of CRC cells are required to validate these results. There appears to be a significant difference in the mechanisms associated with low PP2A activity in breast cancer as compared to CRC cell lines. We previously showed that breast cancer cell lines are sensitive to doses of FTY720 between 0.05 µM and 0.1 µM , and tha


Ovarian cancer (OC) is a life-threatening tumor and the deadliest among gynecological cancers in developed countries. First line treatment with a carboplatin/paclitaxel regime is initially effective in the majority of patients, but most advanced OC will recur and develop drug resistance. Therefore, the identification of alternative therapies is needed. In this study, we employed a panel of high-grade serous ovarian cancer (HGSOC) cell lines, in monolayer and three-dimensional cell cultures. We evaluated the effects of a novel tubulin-binding agent, plocabulin, on proliferation, cell cycle, migration and invasion. We have also tested combinations of plocabulin with several drugs currently used in OC in clinical practice. Our results show a potent antitumor activity of plocabulin, inhibiting proliferation, disrupting microtubule network, and decreasing their migration and invasion capabilities. We did not observe any synergistic combination of plocabulin with cisplatin, doxorubicin, gemcitabine or trabectedin. In conclusion, plocabulin has a potent antitumoral effect in HGSOC cell lines that warrants further clinical investigation. Ovarian cancer (OC) is the leading cause of death for patients with gynecological malignancies. It is an indolent disease, frequently diagnosed at advanced stages due to the lack of specific symptoms. For decades, treatment of OC has consisted of surgery and systemic adjuvant or neoadjuvant chemotherapy with a carboplatin/paclitaxel regimen. However, despite achieving initial complete remission, about 80% of patients with advanced disease will relapse and finally progress to a platinum-resistant OC .Platinum response is one of the major prognostic factors in OC. The classical classification of recurrence in platinum-sensitive or platinum-resistant/refractory disease has been based on the cut-off of 6 months after completing chemotherapy, and no validated biomarkers, other than histological subtype, are known to predict likelihood of primary platinum-resistant or platinum-refractory disease . Few sinIn recent years some relevant progress has occurred in the treatment of high grade serous ovarian carcinoma (HGSOC), the most prevalent subtype of OC, with the introduction of poly-adenosine diphosphate ribose polymerase inhibitors (PARPi). These targeted therapies are now being administered as maintenance therapy after chemotherapy, achieving a relevant improvement in PFS, not only after first line chemotherapy –6, but aLithoplocamia lithistoides. Plocabulin belongs to a family of tubulin-binding agents that inhibits tubulin polymerization by binding to the dimer’s end, with one of the highest known affinities among tubulin-binding agents. This mechanism alters the dynamic instability of microtubules and affects cells both in interphase and mitosis, inhibiting cell growth and migration  is a compound of marine origin derived from the Madagascan sponge igration –12. Rece in vivo .Phase I studies have demonstrated promising antitumor effects of plocabulin in patients with advanced tumors and, currently, it is being further assessed in clinical trials in advanced colorectal cancer, breast cancer and other solid tumors , 14.in vitro efficacy of plocabulin in a panel of 12 HGSOC cell lines with distinct sensitivities to cisplatin (CDDP), alone and in combination with other drugs currently applied in clinical practice. Studies have been done both in monolayer culture (2D) and three dimensional (3D) spheroids, a promising preclinical model for testing antitumor drugs.In the current study, we explore for the first time the PEA1, PEA2, PEO1, PEO4, PEO6, PEO14, PEO23, PEO16, OVCAR-3 and 59M cell lines were obtained from the European Collection of Authenticated Cell Cultures (ECACC), and cultured following the guidelines of the repository. OV866(2) and TOV3041G were obtained from Centre Hospitalier de L´Université de Montréal (CHUM), and kindly provided by Dr. Mes-Masson.BRCA2 ; PEO1, PEO4, PEO6 and 59M: Dulbecco’s Modified Eagle Medium (DMEM), both supplemented with 10% Fetal Bovine Serum (FBS) and 100 U/ml penicillin–streptomycin. OV866(2) and TOV3041G were grown in a combination of 199 and MCDB105 (1:1) media with 5% FBS and 50 μg/ml gentamicin . All cells were incubated at 37°C in a 5% COAll cell lines were tested periodically for mycoplasma infection and authenticated by genetic profiling using polymorphic short tandem repeat loci with the Geneprint 10 kit .For monolayer culture experiments, cells were seeded in flat bottom 96-well plates  24 hours before drug exposure . Then, cells were exposed to different drug concentrations for 72 hours. After this time, cellular confluence was measured with sulforhodamine B (SRB) colorimetric assay.In the case of 3D culture, spheroids were cultured using ultra-low attachment (ULA) plates (Corning) as previously described , 18. Cel50) values were calculated using linear regression with GraphPad Prism 7 software .Colorimetry (SRB) and luminescence (CTG) were measured using a Synergy 4 microplate reader , and in both cases half maximal inhibitory concentration  and TOV3041G, which covered all CDDP possible scenarios.The experimental design was based on the evaluation of two drugs on a 6x6 matrix (https://synergyfinder.org) to explore the synergistic effects of plocabulin with the other drugs .Invasion and migration capacity was evaluated in 2D and 3D conditions.® were used for invasion experiments (Corning). Twenty-four hours later, cells were removed from the top chamber using a cotton swab and the inserts were fixed by the Diff-Quick method . Pictures of the inserts were taken and cells were counted manually with ImageJ  using a representative area of each well.For monolayer culture experiments, cells were treated with plocabulin for 72 hours and then transferred into transwell inserts in low serum conditions . 8 μm pore transwell inserts were employed for migration assays, and pre-coated inserts with Matrigel50 dose for 72 hours. After this time, for invasion assays, drugs were removed and Matrigel® (1:3 with culture media) was added to the spheroids. Pictures were taken every day. For migration assays, spheroids were transferred onto a Matrigel® layer, and pictures were taken as done for invasion assays.In 3D conditions cells were plated in ULA plates and spheroids let to grow for four days. At day 4, plocabulin was added at the correspondent ICFor the study of microtubules, immunofluorescence staining was performed on OV866(2) cell line for α- and γ-tubulin. Briefly, cells were seeded on glass coverslips and 24 hours later were exposed to different concentrations of plocabulin  for 48 hours. After this time, two different IF approaches were done:- Detection of alterations in microtubules and mitotic spindle: Cells were fixed with methanol for 10 minutes at -20°C and incubated with a blocking solution  for 30 minutes and incubated with the corresponding primary and secondary antibodies, as previously described .Pictures were taken with a Leica DM IRM fluorescence microscope equipped with a 100X oil immersion objective and a DFC 340 FX digital camera . Micronuclei were scored in a minimum of 5 fields for each treatment condition.Antibody and Hoechst details are listed on For cell cycle studies, OV866(2) cells were exposed to 0.1 or 1 nM concentrations of plocabulin for 24h. After this time, cells were fixed with 70% ice-cold ethanol for 15 minutes at 4°C and then stained with a propidium iodide solution (Merck) for 30 minutes, in the dark, at room temperature. After washing with phosphate buffered saline, cells were analyzed for cell cycle on a Celigo S plate cytometer .Statistical analysis of all experiments was carried out by means of the Student’s T-test using Microsoft Excel . Statistical significance is reported when p-value ≤ 0.05.All experiments were performed at least in duplicate.50 values determined for each cell line and drug in 2D and 3D conditions.50 values obtained. Only PEO14 was resistant to a concentration of 10 nM. Besides PEO14, 59M showed the highest IC50 value for plocabulin; they are both chemo naïve cell lines but sensitive (PEO14) or resistant (59M) to CDDP, according to our sensitivity stratification. We could not correlate plocabulin response with previous treatments or BRCA status, but it showed antitumoral activity in all CDDP sensitivity groups.When cultured in monolayer, plocabulin was effective in 11/12 cell lines, at doses in low nanomolar/picomolar range (< 1.2 nM), as we can see in the IC50 values over 10 nM, which is 100–1000 times more resistance than in monolayer culture .However, in 3D spheroids only PEO4, PEO6 and PEO16 showed a response to plocabulin in a low nanomolar range. Of these cells, as we can see in the ratio PM 3D/2D column, PEO4 was almost 3 times more resistant to plocabulin in 3D conditions, whilst PEO6 and PEO16 were sensitized to plocabulin in these culture conditions. All the other cell lines had ICCell mobility assays were performed in 7 cell lines, chosen by their different sensitivity to CDDP: PEA1, PEA2, PEO1, PEO4, PEO14, PEO16 and OV866(2).® layer, again, we saw the highest inhibition in PEO14 , followed by OV866(2) , PEA2  and PEA1 . The latter, although not significant, show a similar trend towards inhibition of migration and invasion (We observed a reduction of both transwell migration (3 cell lines) and invasion (4 cell lines) when treating cells with plocabulin Figure 2® without disintegration. Of all these selected cell lines, only OV866(2) migrated   or tight spheroids (OV866(2) and PEO16) were assayed, since loose aggregates (PEA1 and PEA2) cannot be transferred to MatrigelThe effect of plocabulin treatment on the microtubule network of OV866(2) cells was analyzed by immunofluorescence staining of α- and γ-tubulin.50 value doses (0.1 nM), microtubule distribution was slightly disorganized, and this effect was accentuated at 1 nM  and TOV3041G). Although some combinations showed punctual synergy at individual dose combinations, overall, none of the experiments showed a positive synergy score for all four algorithms analyzed in SynergyFinder Plus  have mutations in BRCA2  and migration of PEA2, PEO14 and OV866(2) HGSOC cell lines in monoculture, and in 3D spheroids of OV866(2) cells, reducing spheroid volume and cell sprouting area, even though the latter become more resistant to plocabulin in 3D. We and others have previously reported that 3D tumor spheroid-based migration assays reflect better the solid tumor microenvironment and represent both cell-cell and cell-ECM interactions. Our technique is highly reproducible and therefore appropriate for the evaluation of therapeutic drugs with anti-migratory properties , 31.We and others have previously published the importance of the angiogenic process in OC and its relation to poor prognosis . MoreoveAs previously reported by Martínez-Díez et al. in a lung cancer cell line, we have observed in OV866(2) HGSOC cell line that plocabulin has a potent depolymerizing effect on microtubules, which affects cells in interphase and mitosis. In this cell line, plocabulin treatment causes the appearance of multipolar mitoses, chromosome missegregation and multinucleated cells that do not undergo anaphase/cytokinesis, forcing cells to enter senescence or apoptotic death, as seen in cell cycle experiments. Martínez-Díez et al. also reported that plocabulin-induced disorganization and fragmentation of the microtubule network could be related to the inhibition of cell migration in cells where the antiproliferative effects of this drug were not evident .In this work we have also explored combinations of plocabulin with various drugs currently administered to patients with HGSOC in routine clinical practice, but none of them showed a synergistic or additive effect. Part of the reasons for the lack of interaction between the drugs is that plocabulin as a single drug is already effective at low concentrations. Combination with paclitaxel was not tested because paclitaxel and plocabulin share a similar mechanism of action (microtubule inhibitors) and dose-limiting toxicity (neurotoxicity) . The com50 values obtained in monolayer culture, but still very low, and may not be enough when scaled to in vivo models.As mentioned throughout the discussion, this work presents a series of strengths, such as the use of a large panel of HGSOC cell lines, the use of 3D models that better represent tumor architecture, and the analyses of drug effects in less studied processes such as migration and invasion in 2D culture and in spheroids. Moreover, we have employed a robust and restrictive tool for the exploration of drug combinations. This method did not reveal any synergies in our hands, but they cannot be discarded by complementary approaches, like animal model experiments. Nevertheless, we recognize a series of limitations. First of all, we have only been able to demonstrate migration and invasion inhibition in four cell lines in 2D and only one in 3D. Confirmation in other cell lines that migrate and invade would be desirable. Also, 3D spheroids were exposed to a maximum concentration of plocabulin of 10 nM, 100-1000 times stronger than ICin vitro effects of plocabulin, a novel tubulin-binding agent, in OC. Our results show that plocabulin has potent cytotoxic activity in a panel of HGSOC cell lines, including CDDP resistance scenario, and that it inhibits migration and invasion of tumor cells and spheroids. Further clinical evaluation of this drug in OC would be warranted.To our knowledge, this is the first work to describe the The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Concept, VH-S, AR, and MMe. Methodology, all authors. Formal analysis, VH-S, SZ, AR, and MMe. Supervision, JT, AR, and MMe. Project administration, MMe and AR. Writing and original draft preparation, VH-S, AR, and MMe. Writing, review and editing, all authors. All authors contributed to the article and approved the submitted version.AG reports honoraria  and travel/accommodation/expenses , outside the submitted work. MM-D is employee and shareholder of PharmaMar S.A. . AR reports honoraria and advisory/consultancy , research grant/funding to his institution , travel/accommodation/expenses , and speakers bureau , outside the submitted work. MMe reports honoraria , research grant/funding to her institution (Eisai and PharmaMar), travel/accommodation/expenses , outside the submitted work.The authors declare that this study received funding from PharmaMar S.A. (MM-D). The funder had the following involvement with the study: performed immunofluorescence experiments and reviewed draft preparation.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.