Targeted nanomedicine-based approaches that aim at the simultaneous delivery of synergistic drug combinations to multiple cellular populations are of high relevance for tackling heterogeneity on solid tumors. Considering that cancer stem cells (CSC) may originate from non-stem cancer cells, single-drug regimens targeting only one of these cell populations could enable tumors to evade treatments. As such, the identification of a common marker, such as nucleolin, might result in a therapeutic advantage. The results herein generated suggested a transversal role of nucleolin in the internalization of F3 peptide-targeted pegylated pH-sensitive liposomes into bulk ovarian cancer cells, including putative CSC-enriched ovarian cells. The intracellular delivery of a drug combination such as the one tested herein was relevant in the context of cell lines with higher intrinsic resistances to doxorubicin. The enhanced efficacy of the F3 peptide-targeted liposomal combination of doxorubicin/C6-ceramide was supported by the downregulation of the Akt pathway, within a specific range of basal level of expression.high/CD44high). Co-encapsulation of DXR:C6-ceramide into F3 peptide-targeted liposomes improved cytotoxic activity relative to liposomes containing DXR alone, in an extent that depended on the intrinsic resistance to DXR and on the incubation time. The enhanced cytotoxicity of the targeted combination was mechanistically supported by the downregulation of PI3K/Akt pathway by C6-ceramide, only among the nucleolin-overexpressing cancer cells presenting a basal p-Akt/total Akt ratio lower than 1.Targeting multiple cellular populations is of high therapeutic relevance for the tackling of solid tumors heterogeneity. Herein, the ability of pegylated and pH-sensitive liposomes, functionalized with the nucleolin-binding F3 peptide and containing doxorubicin (DXR)/C6-ceramide synergistic combination, to target, in vitro, ovarian cancer, including ovarian cancer stem cells (CSC), was assessed. The underlying molecular mechanism of action of the nucleolin-mediated intracellular delivery of C6-ceramide to cancer cells was also explored. The assessment of overexpression of surface nucleolin expression by flow cytometry was critical to dissipate differences identified by Western blot in membrane/cytoplasm of SKOV-3, OVCAR-3 and TOV-112D ovarian cancer cell lines. The former was in line with the significant extent of uptake into (bulk) ovarian cancer cells, relative to non-targeted and non-specific counterparts. This pattern of uptake was recapitulated with putative CSC-enriched ovarian SKOV-3 and OVCAR-3 sub-population (EpCAM Cancer is one of the leading causes of death worldwide and responsible for an estimated 10 million deaths in 2020. Among them, female breast and ovary represented 6.9% and 2.1%, respectively, of the total of cancer deaths in 2020  (DSPE-PEG2k), 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[maleimide(polyethylene glycol)-2000] , L-α-phosphatidylethanolamine-N-(lissamine rhodamine B sulfonyl) (RhoD-PE), N-hexanoyl-D-erythrosphingosine (C6-ceramide) were acquired from Avanti Polar Lipids  or Lipoid . F3 (KDEPQRRSARLSAKPAPPKPEPKPKKAPAKK) and the nonspecific (NS) peptide were custom synthesized by Genecust . All other chemicals were of analytical grade purity.Doxorubicin hydrochloride (DXR) was obtained from MicroBiopharm . Calcein, 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid (HEPES), 2-(® HTB-77™) cancer cell line was cultured in DMEM high glucose . The ovarian cancer cell line TOV-112D (ATCC® CRL-11731™), the triple-negative breast cancer cell line MDA-MB-231 (ATCC® HTB-26™), the A549 (ATCC® CCL-185™) and H1975 (ATCC® CRL-5908™) human lung cancer cell lines and the nucleolin-overexpressing cell line MDA-MB-435S (ATCC® HTB-129™) were cultured in RPMI 1640 , both supplemented with 10% (v/v) of heat-inactivated Fetal Bovine Serum (FBS) , 100 U/mL penicillin, 100 µg/mL streptomycin . The OVCAR-3 (ATCC® HTB-161™) ovarian cancer cell line was cultured in RPMI 1640 , supplemented with 20% (v/v) of heat-inactivated Fetal Bovine Serum (FBS) , 100 U/mL penicillin, 100 mg/mL streptomycin . MCF12A (ATCC® CRL-10782™) cell line was cultured in RPMI 1640  supplemented with 5% (v/v) of heat inactivated FBS , 100 U/mL penicillin, 100 μg/mL streptomycin , 20 ng/mL human Epidermal Growth Factor  and 0.5 µg/mL hydrocortisone . All cell lines were maintained at 37 °C in a 5% CO2 atmosphere up to 1 month  to prevent unwanted mutations. Cells were routinely tested for mycoplasma contamination, following the Center for Neuroscience and Cell Biology (CNC) internal rules, and morphology was assessed by microscopy. Cell lines authentication was performed by short Tandem Repeat Profiling.The ovarian SKOV-3 (ATCC2k:DSPE-PEG2k-F3: C6-ceramide at 2.66:1.34:2:2:0.62:0.18:2 (18 mol% of ceramide) or 4:2:2:2:0.62:0.18:0 molar ratio, respectively, as previously described  , or with the corresponding isotypes IgG2b  and IgG1 K , for 30 min at 4 °C, in PBS-BSA. The cell-associated calcein signal was immediately analyzed by flow cytometry in a BD FACSCalibur system  and a total of 20,000 events were collected. Appropriate controls were used to assure the correct compensation of fluorescence signals in each channel.2. Afterwards, cell culture medium was exchanged for a fresh one and the experiment extended up to 96 (TOV-112D and A549), 120 (SKOV-3 and H1975) or 144 h (OVCAR-3), depending on the cell line used. Cell viability was assessed by the resazurin reduction assay, by monitoring absorbance at 570 nm and 600 nm (background) in a Spectramax Gemini EM . Cell death was calculated from the formula 100 − ((Test570–600 − CtrNeg570–600)/(Ctr570–600 − CtrNeg570–600)) × 100, where Test570–600, Ctr570–600 and CtrNeg570–600 were the corrected absorbance for treated cells, untreated controls and negative control, respectively.The cytotoxic potential of F3 peptide-targeted liposomal combinations of DXR:C6-ceramide against ovarian cancer  and non-small cell lung cancer (A549 and H1975) cell lines was assessed. Additionally, the cytotoxicity of free DXR or C6-ceramide against ovarian cancer  cell lines was also evaluated. Briefly, cancer cells, adherent to 96-well plates, were incubated with serial dilutions of different liposomal formulations containing DXR or free DXR or free C6-ceramide for 1, 4 or 8 h at 37 °C in an atmosphere of 5% CO50 of F3 peptide-targeted liposomal DXR:C6-ceramide combination at a molar ratio of 1:1 ([F3]L-DC611). SKOV-3 cells were incubated with 0.63 or 0.49 µM for 4 and 8 h, respectively, MDA-MB-231 cells were incubated with 25.9 or 6.35 µM for 1 and 4 h, respectively, at 37 °C of F3 peptide-targeted liposomal DXR ([F3]L-D), DXR:C6-ceramide combination at a molar ratio of 1:1 ([F3]L-DC611) and the non-targeted counterpart (L-DC611). DXR and C6-ceramide were quantified after extraction from the cultured cells using 500 µL of 80% of methanol and sonicated in a cup-horn for 2 min with 60% amplitude using cycles of 3 s on and 2 s off. Samples were frozen at −80 °C for 1.5 h and sonication was repeated with the same parameters as the previous step. Each sample (100 µL) was spiked with 10 µL of the internal standard solution (daunorubicin and C8-ceramide) and 10 µL of 50% acetonitrile + 0.1% formic acid followed by centrifugation for 20 min at 14,000× g, and the supernatant was collected for LC-MS/MS analysis. Calibration curves were prepared in cell-matrix by spiking 100 µL of blank cells with 10 µL of standard solution and 10 µL of the internal standards (IS) solution. Eight calibration points with concentration ranges of 0.009–0.597 µM for DXR and 0.001–0.075 µM for C6-ceramide were analyzed to generate the calibration curves. The samples were analyzed on an LC Nexera system  coupled to a hybrid triple quadrupole/linear ion-trap 4000 QTrap mass spectrometer operated by Analyst 1.6.3 . The injector was a CTC-xt . The chromatographic separation was performed using a Gemini C18 column  with a 4 × 2.0 mm C18 guard-column . The flow rate was set at 250 µL/min and mobile phases A and B were 0.1% formic acid in water and 0.1% formic acid in acetonitrile, respectively. The gradient elution was programmed to: 2–30% of B (0.0–0.3 min), 30–60% of B (0.3–3.5 min), 60–99% of B (3.5–4.0 min), 99% of B (4.0–7.9 min), 99–2% of B (7.9–8.0 min) and 2% of B (8.0–8.2 min). The ionization source  was operated in the positive mode set to an ion spray voltage of 5500 V, 40 psi for nebulizer gas 1 (GS1), 30 psi for the nebulizer gas 2 (GS2), 30 psi for the curtain gas (CUR), and the temperature was 600 °C. All molecules were analyzed by Multiple Reaction Monitoring (MRM) setting Q1 and Q3 at unit resolution, the entrance potential (EP) at 10 eV, the collision gas (CAD) at 8 psi, and the dwell time was 75 ms . Afterwards, RNA concentration and quality were determined using a NanoDrop 2000 . Samples presenting a 260/280 ratio under 1.9 were discarded. Samples of total RNA were stored at −80 °C until use. cDNA was obtained using the NZY First-Strand cDNA Synthesis kit  according to the protocol established by the manufacturer, using a Unocycler Thermal Cycler . Using species-specific pairs of primers, AKT1 and S6K1 gene expression was quantified by qRT-PCR using β-ACTIN or HPRT as housekeeping genes for data normalization. The primers were obtained from a primer bank database  and acquired from Integrated DNA Technologies   . NZYSpeeFollowing previous results obtained in breast cancer ,33, and p < 0.05 and ** p < 0.01, respectively), and in contrast with the result obtained with OVCAR-3 cells (p > 0.05). In addition, nucleolin was identified in the cytoplasmic/membrane fraction (lamin B1 negative) of all ovarian cancer cells tested (p < 0.05) and MDA-MB-231 (*** p < 0.001) cells, respectively (p < 0.01), MDA-MB-435S  and the non-stem cancer cell (EpCAMlow/−/CD44low/−) populations, but also putative intermediate cell populations (EpCAMhigh/CD44low/− and EpCAMlow/−/CD44high populations) (p < 0.05) or 7.1-fold (p < 0.001) higher cellular association to EpCAMhigh/CD44high SKOV-3 (low/−/CD44low/− non-stem cancer cell populations (non-SCC). These results supported the capacity of lipid-based nanoparticles functionalized with the nucleolin-binding F3 peptide to target, simultaneously, multiple cancer cell populations, including ovarian CSCs.CD44 and EpCAM markers, suitable for staining in flow cytometry, enabled the establishment of a gating strategy aiming at identifying not only the putative CSC (EpCAMlations) A. Accordlations) B,C. Thish SKOV-3 D or OVCAh SKOV-3 E sub-popTo further reinforce the therapeutic potential of the targeted drug combination, the cytotoxicity was then assessed.50 and IC90 values  was assessed. Herein, a new presentation strategy was adopted , in orde0 values  and faci90 values (90 higher than 50 µM), encapsulating either single (DXR) or drug combinations, targeted or non-targeted, for both 4 or 8 h incubation time. This higher resistance is particularly evident at the IC90. In fact, only the targeted drug combinations, either at a 1:1 ([F3]L-DC611) or 1:2 molar ratio ([F3]L-DC612) enabled a measurable 90% of SKOV-3 cancer cells death , following an 8 h incubation.The analysis of the IC0 values  clearly 90 values, but now moving to the TOV-112D cell line, the samples enabling the greener and smaller circles were still the targeted drug combinations, either at a 1:1 ([F3]L-DC611) or 1:2 molar ratio ([F3]L-DC612), closely followed by the targeted liposomes containing only DXR, for both 1  and 4 h  of incubation. With this cell line, a dependence on the incubation time was evidenced, for all of the tested samples, towards an increase of activity. As we move to the more sensitive cell line (OVCAR-3), differences among the IC90 values tend to dissipate. Nevertheless, the lowest values are still associated with [F3]L-DC611 and [F3]L-DC612, for both incubation times: 2.18 and 2.39 µM for 1 h and 1.11 and 1.77 µM for 4 h of incubation, respectively. Similar trends were observed within the set of IC50 values  in order to provide in the end, a cell density enabling drug quantification.To unravel some of the mechanisms supporting the improved cytotoxicity of the targeted drug combination, the capability of the developed F3 peptide-targeted lipid-based nanoparticle to enable intracellular drug delivery was assessed upon quantifying intracellular DXR and C6-ceramide by mass spectrometry. This experiment was performed with the triple-negative breast cancer MDA-MB-231 or ovarian cancer SKOV-3 cells, as in both, incubation with targeted drug combinations of DXR and C6-ceramide in a molar ratio of 1:1 enabled a 90% cell death, following 4 or 8 h, respectively, a level of cell death not reached by the counterpart containing DXR alone  enabled an intracellular accumulation of DXR that was always significantly higher than the one from the non-targeted counterpart (L-DC611), which instead was similar in the case of C6-ceramide (611) enabled intracellular levels of DXR similar to the ones from F3 peptide-targeted liposomes containing only DXR ([F3]L-D) in SKOV-3 and MDA-MB-231 cells.With this set of cells, an interesting observation arose. Regardless of the cell line or incubation time tested, the targeted formulation  or 24 h (p < 0.01) of incubation, relative to untreated cells. At 64 µM, a 5.4- or 25.8-fold decrease on p-Akt levels were observed following 4 (p < 0.001) or 24 h (p < 0.001), respectively, relative to untreated control  only at 32 or 64 µM of F3 peptide-targeted liposomal C6-ceramide  and their counterpart containing only DXR ([F3]L-D])  .Overall, these results pointed out that C6-Ceramide-mediated improved cytotoxicity of the F3 peptide-targeted drug combination is supported by the downregulation of phosphorylated/active Akt, an effect dependent on the basal levels of p-Akt .6) for 24 h, but without statistical significance , thus mediating their biological activities, such as cell differentiation, adhesion and leukocyte trafficking, inflammation, angiogenesis and tumor development ,41. Nuclp < 0.05) to the nucleolin positive control MDA-MB-435S cells. Interestingly, assessment of cell surface density alone, by flow cytometry, dissipated any previous differences relative to MDA-MB-435S, while evidencing a decrease on OVCAR-3 , with cell surface levels significantly higher than the non-neoplastic cell line tested, in line with previously demonstrated nucleolin overexpression in ovarian cancer SKOV-3 and OVCAR-3 cell lines . Th. Thp > 044low/−) . This is44low/−) ,7,45, be90 level of SKOV-3 cells, where the intrinsic resistance to DXR, relative to OVCAR-3 and TOV-112D , presenhievable .3H-DPPC, by C-26 cells was significantly lower than that of radiolabeled 14C-C6-ceramide at all times tested, suggesting the latter being translocated into the cells in its free form. Importantly, the extent of the transbilayer diffusion associated with short-chain sphingolipids was reduced in the presence of DSPE-PEG2k in the same formulation [Interestingly, similar intracellular levels of C6-ceramide in ovarian cancer SKOV-3 and triple-negative breast cancer MDA-MB-231 cell lines, upon delivery by non-targeted and targeted liposomes, suggested a passive delivery process, in contrast to DXR. This was actually in line with the previously described cellular uptake of short-chain sphingolipids . In factmulation . Moreovemulation , relativMechanistically, the cytotoxic activity may be underlined by two sets of mechanisms. While DXR is a topoisomerase II inhibitor inducing cell necrosis even when actively delivered ,37, the Additionally, basal protein levels of glucosylceramide synthase (GCS), an enzyme involved in ceramide metabolism  has beenThese observations were accompanied by a minimal impact on the mRNA levels of AKT1 and S6K1 , a downsImportantly, data suggested that pathway inhibition is not due to Akt degradation but rather to its deactivation. This is consistent with the proposed interaction of ceramide with PI3KC2β, an upstream effector of Akt pathway, suppressing its activation, and consequently decreasing p-Akt levels in ovarian cancer cells . Moreovehigh/CD44high). Interestingly, while the active intracellular delivery of DXR has been reinforced, C6-ceramide uptake seemed to be associated with a passive process, independent from the presence of the F3 peptide. Intracellular delivery of a drug combination as the one herein tested revealed to be relevant in the context of cell lines with higher intrinsic resistance to DXR, as in the case of ovarian SKOV-3 cells. In fact, the enhanced efficacy of the F3 peptide-targeted liposomal combination of DXR/C6-ceramide was supported by the downregulation of the Akt pathway, within a specific range of basal level of expression.Overall, upon a certain level of surface nucleolin expression as determined by flow cytometry, the results herein generated pointed towards a transversal role of nucleolin in the internalization of F3 peptide-targeted pegylated pH-sensitive liposomes into bulk ovarian cancer cells, including putative CSC-enriched ovarian SKOV-3 and OVCAR-3 cells (EpCAM


To complete mitosis, the bridge that links the two daughter cells needs to be cleaved. This step is carried out by the endosomal sorting complex required for transport (ESCRT) machinery. AKTIP, a protein discovered to be associated with telomeres and the nuclear membrane in interphase cells, shares sequence similarities with the ESCRT I component TSG101. Here we present evidence that during mitosis AKTIP is part of the ESCRT machinery at the midbody. AKTIP interacts with the ESCRT I subunit VPS28 and forms a circular supra-structure at the midbody, in close proximity with TSG101 and VPS28 and adjacent to the members of the ESCRT III module CHMP2A, CHMP4B and IST1. Mechanistically, the recruitment of AKTIP is dependent on MKLP1 and independent of CEP55. AKTIP and TSG101 are needed together for the recruitment of the ESCRT III subunit CHMP4B and in parallel for the recruitment of IST1. Alone, the reduction of AKTIP impinges on IST1 and causes multinucleation. Our data altogether reveal that AKTIP is a component of the ESCRT I module and functions in the recruitment of ESCRT III components required for abscission. To complete cell division, the bridge that links the two daughter cells needs to be cleaved. This step is carried out by a machinery named “endosomal sorting complex required for transport” (ESCRT). The dissection of this machinery is important in basic biology and for investigating diseases in which cell division is altered. AKTIP, a factor discovered to be needed for chromosome integrity, shares similarities with a component of the ESCRT machinery named TSG101. Here we present evidence that AKTIP is part of the ESCRT machinery, as TSG101. More specifically, we show that AKTIP physically interacts with members of the ESCRT machinery and forms a characteristic circular structure at the center of the bridge linking the daughter cells. We also show that the reduction of AKTIP levels causes defects in the assembly of the ESCRT machinery and in cell division. In future work, it will be interesting to investigate the association of AKTIP with cancer, because in tumorigenesis cell division is altered and since an implication in cancer has been described for TSG101 and other ESCRT factors. To complete cytokinesis, cells need to cleave the intercellular bridge, a membrane structure enriched in microtubules linking the two daughter cells. This cleavage step, named abscission, is operated by the endosomal sorting complex required for transport (ESCRT) machinery ,2. BeyonDuring cytokinesis, the members of the ESCRT machinery are positioned at the midbody of the intercellular bridge. The ESCRT machinery comprises the ESCRT I, II and III modules. The ESCRT I module includes TSG101, VPS37, MVB12 and VPS28 . The ESCDrosophila which has no CEP55, ALIX and TSG101 recruitment to the midbody is promoted by the centralspindlin component Pavarotti  [The assembly of the ESCRT machinery at the midbody is initiated by CEP55, which recruits the ESCRT I component TSG101 and ALIX ,5,12,13.n MKLP1) .Super-resolution microscopy has permitted the interpretation at 100–200 nanometer scale of the organization of ESCRT and ESCRT associated factors supra-molecular complexes formed at the midbody –19. SuchDrosophila) is organized in foci enriched at the nuclear rim in interphase cells and that a reduction in AKTIP (or Peo) results in telomeric defects, aging and cancer aggressiveness [In our previous work, we have shown that a protein named AKTIP , α-tubulin and endogenous AKTIP and imaged by confocal microscopy. In interphase, AKTIP is detectable as discrete and abundant foci at the nuclear rim and within the nucleus. During the initial phases of mitosis, AKTIP moves along the microtubules and on the spindle midzone during anaphase. In late telophase, AKTIP accumulates on the intercellular bridge at the center of the midbody. At this stage, the AKTIP punctate signal is also visible at the reforming nuclear rim and in the nucleoplasm .To validate the specificity of the localization of AKTIP to the midbody, we compared the immunostaining obtained using the monoclonal anti-AKTIP antibody , which delivers ~120nm resolution . Cells wThese data taken together demonstrate a physical organization of AKTIP at the midbody similar to that of components of the ESCRT machinery.To investigate the biochemical association of AKTIP with the ESCRT machinery we carried out a yeast two hybrid screen on ESCRT I, II, III subunits and on the ESCRT associated factors. Yeast cells were co-transformed with a plasmid encoding AKTIP fused to the Gal4 DNA-binding domain, in combination with plasmids encoding ESCRT or ESCRT associated factors fused to the VP16 activation domain and the LacZ activity in co-transformants was measured. We observe that AKTIP significantly interacts with the ESCRT I subunit VPS28 .To validate the interaction between AKTIP and VPS28 in mammalian cells, VPS28 was cloned as a GST-fusion and AKTIP as a MYC- or HA-tagged fusion. 293T cells were co-transfected with control GST or GST-VPS28 and either MYC-AKTIP or HA-AKTIP. Pull down assays followed by Western blotting show that AKTIP co-precipitates with VPS28 Figs  and S2. We next analyzed in vivo the co-localization of AKTIP and VPS28. Spinning disk analyses and image reconstruction of HeLa cells stained with anti-AKTIP and anti-VPS28 antibodies show that the two signals are in proximity at the midbody . The sigSince TSG101 is known to bind VPS28 ,31–34, wTaken together, these data show that VPS28 can be in complex with both TSG101 and AKTIP. In vivo, AKTIP and TSG101 and AKTIP and VPS28 are concomitantly present in proximity at the center of the midbody.α positions equal to 1.9 Å (AKTIP and TSG101 sequences contain a ubiquitin E2 variant (UEV) domain, which in AKTIP is in its central region (aa 78–220) . To compto 1.9 Å . Betweento 1.9 Å .To define the AKTIP region implicated in the interaction with VPS28, we produced three GFP-tagged AKTIP truncations, including the N-terminus (aa 1–76), the C-terminus (aa 221–292) or the UEV (aa 78–220) portions of AKTIP. 293T cells were co-transfected with the different AKTIP constructs together with full length GST-VPS28. Pulldown experiments demonstrate that the central region of AKTIP interacts with VPS28 . To furtTo extend the characterization of AKTIP in relation with the ESCRT subunits, we tested AKTIP on the ESCRT I subunits VPS37A to D and on the ESCRT II subunits VPS25, VPS36 and VPS22. To this end GST- or GFP-tagged ESCRT subunits were tested on MYC-tagged AKTIP. Pull down assay shows no significant interaction between AKTIP and ESCRT I VPS37A to D or ESCRT II VPS25, VPS36 and VPS22 Figs  and S3B.Given the similarity between AKTIP and TSG101, we explored the possibility of an interaction between AKTIP and SEPT9. This idea comes from the fact that an interaction between SEPT9 and TSG101 was previously described and assigned to two N-terminal PTAP motifs in SEPT9 . We usedTogether these data show that AKTIP interacts with the ESCRT I module and shares with the ESCRT I subunit TSG101 the ability to bind the N-terminus of VPS28. However, at the condition tested and differently from TSG101, AKTIP binds VPS28 through its UEV domain and does not bind SEPT9 .The ESCRT I subunits require for the execution of abscission the ESCRT III module. To evaluate the relationship between AKTIP and the ESCRT III module, we carried out 3D-SIM co-analyzation studies of AKTIP and of the ESCRT III components CHMP4B, CHMP2A and IST1, for which the localization has been previously defined using super-resolution microscopy ,19,36.Co-staining of AKTIP and CHMP4B  or CHMP2We next analyzed the proximity of AKTIP to IST1. This analysis shows that in early forming midbodies neither AKTIP nor IST1 are yet organized in a supra-molecular structure. In the mid-stage, AKTIP and IST1 are detected as ring shaped structures. Two IST1 rings flank the central, single, larger, and thicker AKTIP ring at the midbody . In lateTriple staining of AKTIP, TSG101 and IST1 in HeLa cells shows that while AKTIP and TSG101 localize in close proximity, the IST1 rings flank the AKTIP-TSG101 signal . In agreThese results taken together show that the AKTIP circular supra-molecular structure is associated with the ESCRT I module that includes TSG101 and VPS28, and localizes in proximity, albeit not coincidently, with ESCRT III subunits IST1, CHMP2A and CHMP4B when these organize into double rings in the central area of the midbody.Since in mammalian cells at the earliest stages of abscission, CEP55 controls the recruitment of TSG101 and of the TSG101 associated factor ALIX ,5,12,13,To validate this last point, i.e. the independence of AKTIP from TSG101 and ALIX extrapolated from the data obtained in siCEP55 cells, we analyzed by immunofluorescence TSG101 in shAKTIP cells. This analysis shows that the level of TSG101 positive midbodies is not dependent on AKTIP . We nextWe next monitored by immunofluorescence the midbodies for the presence of ALIX in shAKTIP cells and reverse. We observe that AKTIP loss does not impact on ALIX recruitment to the midbody and viceversa .To complete the picture of the elements playing a role in the assembly of the early members of the ESCRT complex and given the biochemical interaction of AKTIP with VPS28, we checked whether VPS28 was affected in shAKTIP cells. Immunofluorescence analysis shows no significant differences of VPS28 in shAKTIP cells as compared to controls . The revAltogether, these results show that the recruitment of AKTIP to the midbody can happen independently of CEP55, TSG101, ALIX and VPS28.Drosophila the recruitment to the midbody of TSG101 and ALIX can be independent of CEP55, while it is promoted by the centralspindlin component Pav  [We next investigated whether AKTIP recruitment to the midbody was dependent on MKLP1. The idea for this came from data showing that in mammals) . We alsomammals) .To analyze the association of AKTIP and MKLP1, firstly we performed co-immunofluorescence and analyzed by confocal imaging the relative spatiotemporal distribution of the two factors. We observe that AKTIP and MKLP1 have similar distributions . To obtaAs a second step, to evaluate if the recruitment of AKTIP was MKLP1 dependent, we analyzed AKTIP localization at the midbody in siMKLP1 cells . The quaIn summary, these data provide evidence that MKLP1 not only localizes in close proximity to AKTIP but also, importantly, is needed for the recruitment of AKTIP to the midbody.The ESCRT I module contributes to the assembly of ESCRT III modules ,32. TherWe firstly analyzed the ESCRT III subunit CHMP4B in shAKTIP cells by immunofluorescence. The data show that the number of CHMP4B positive midbodies in shAKTIP cells are comparable to control cells, revealing that AKTIP depletion alone is not sufficient to affect CHMP4B recruitment to the midbody . Along wWe next asked whether AKTIP would influence CHMP4B by cooperating with TSG101. We produced siTSG101 and shAKTIP/siTSG101 cells by transient transfection of siTSG101 in control and shAKTIP cells, respectively. siTSG101 causes a reduction of TSG101 positive midbodies in both conditions . In lineWe next analyzed by immunofluorescence the presence of CHMP4B in either shAKTIP cells or in co-depleted shAKTIP, siALIX cells. We observe that the siALIX alone does not significantly affect CHMP4B recruitment, neither it does in combination with AKTIP reduction Figs .As a further step we looked at IST1 in shAKTIP, siTSG101 and shAKTIP/siTSG101 cells. We observe that both AKTIP and TSG101 are required for IST1 recruitment. Furthermore, we observe that the levels of the reduction of IST1 are comparable in shAKTIP, siTSG101 and shAKTIP/siTSG101 cells, suggesting that AKTIP and TSG101 act in a common path for the recruitment of IST1 to the midbody Figs .To further explore whether both AKTIP and TSG101 were needed for IST1 recruitment to the midbody, we tested the ability of AKTIP to rescue TSG101 deficiency. To this end we created a stable AKTIP-FLAG overexpressing cell line. We verified the presence of AKTIP-FLAG at midbody by immunofluorescence with an anti-FLAG antibody and monitored the expression level of AKTIP in AKTIP-FLAG cells . We nextTaken together, these results indicate that AKTIP and TSG101 cooperate in the recruitment of CHMP4B to the midbody, but act in two independent pathways. On the other hand, the absence of additivity and of rescue indicates, respectively, that AKTIP and TSG101 act in the same pathway on IST1 but are both needed for its recruitment to the midbody.Given that AKTIP loss causes a reduction of IST1 and that IST1 functions in cytokinesis , we askeFinally, since in our previous work we documented a role for AKTIP in telomere dysfunction , we nextAKTIP is a protein with similarities with the ESCRT I subunit TSG101 ,27. HereThe first experimental evidence linking AKTIP to the ESCRT complex is in the characteristics of its supra-molecular organization. We show that AKTIP forms a large multimeric circular structure around microtubules at the midbody where the ESCRT complex is recruited ,16. The A second set of experimental evidence links AKTIP to the ESCRT I module. AKTIP biochemically interacts with VPS28. VPS28 is an ESCRT I member required for the assembly of ESCRT complex ,32. VPS2Drosophila [Interestingly, the positioning of AKTIP at the midbody is not controlled by CEP55. Coherently with this experimental evidence, the sequence of AKTIP does not include the CEP55 binding residues 158–162 identified in TSG101 . AKTIP rosophila .The third piece of evidence functionally associating AKTIP with the ESCRT machinery is the impact of AKTIP on ESCRT III recruitment to the midbody. Notably, the combined depletion of AKTIP and TSG101 reduces the recruitment of the ESCRT III member CHMP4B. On the other hand, the single depletion is not sufficient to impair CHMP4B recruitment. These results show that AKTIP and TSG101 act in parallel arms on the recruitment of CHMP4B . PreviouA direct relationship between members of the ESCRT I module and IST1 has been previously described and indicated as a path modulating a subset of the ATPase VPS4 activity at the midbody . We repoGiven the function exerted by IST1 in the final stages of cell division , the AKTCollectively, the results presented demonstrate for the first time that AKTIP, a protein similar to the ESCRT I component TSG101, functionally associates with the ESCRT I module at the midbody and is required for the assembly of the ESCRT III module implicated in the final stages of cytokinesis. In future work, it will be interesting to explore if the AKTIP association with the ESCRT machinery has an impact on cancer, which has been indicated for TSG101  and more2 in DMEM (Life Technologies) supplemented with 10% FBS (Life Technologies) and 50U/ml penicillin and streptomycin (Life Technologies). For transient RNA interference, cells were cultured in 6-well plates and were transfected with 20μM siRNA oligonucleotides using Lipofectamine 2000 (Life Technologies) following manufacturer’s instructions. Cells were collected or fixed 48hrs post-transfection. To obtain cell lines stably interfered for AKTIP or TRF2 we used lentivirus (LV) mediated interference and the LV-shAKTIP (shAKTIP), LV-shTRF2 (shTRF2) and LV-scramble (shctr) vectors were described previously [HeLa cells (ATCC CCL-2) and 293T cells (ATCC CRL-11268) were grown at 37°C; 5% COeviously . The muleviously  at a moieviously . SeventyOne-week post-transduction, cells were lysed by addition of TRIzol reagent (Invitrogen) and RNA extracted according to the manufacturer’s instructions. After DNase treatment (Invitrogen), RNA was reverse transcribed into cDNA as already described . Q-PCR rAKTIP Forward 5’- TCCACGCTTGGTGTTCGAT-3’;AKTIP Reverse 5’-TCACCTGAGGTGGGATCAACT-3’;TRF2 Forward 5’- TCCTCACGATGGCCAAAAAG-3’;TRF2 Reverse 5’- GCTGTTTATCTTCCTTCCCTGTACT-3’;GAPDH Forward 5’-TGGGCTACACTGAGCACCAG-3’;GAPDH Reverse 5’-GGGTGTCGCTGTTGAAGTCA-3’–ΔΔCq method as previously described [and analyzed with the 2escribed . For Wesescribed  and quanHeLa cells were seeded onto glass coverslips in 6-well plates and fixed with 3.7% formaldehyde in PBS for 10min. Cells were then permeabilized with 0.25% Triton X-100 in PBS for 5min, treated with PBS 1% BSA for 30min and then stained with primary antibodies in PBS 1% BSA for 1hr at RT. For AKTIP-TSG101 co-immunofluorescence, HeLa cells were seeded onto glass coverslips, fixed as previously described [For Structured illumination microscopy (3D-SIM) and Multispot-SIM (MSIM) imaging, HeLa cells were seeded onto glass coverslips  in 6-well plates and fixed with 3.7% formaldehyde in PBS for 10min at RT and then incubated in 50mM NH4Cl/PBS (15min). Cells were incubated with primary and secondary antibodies diluted in PBS-BSA 1% for 1hr at RT and washed in PBS. Acquisition of 3D-SIM images was performed using a DeltaVision OMX v4 Blaze microscope  equipped with the BGR-FR filter drawer for acquisition of 3D-SIM images, an Olympus Plan Apochromat 100×/1.4 PSF oil immersion objective lens and liquid-cooled Photometrics Evolve EM-CCD cameras for each channel. 15 images per section per channel were acquired with a z-spacing of 0.125μm ,48. Stru3D volume reconstructions and movies generation were done in Imaris . Image analysis and quantification was performed using Image J/FIJI , Excel (Yeast two hybrid assays were performed as previously described . BrieflyGST pull down were performed as previously described . Full leFor GFP-TRAP 293T cells were transfected with plasmids encoding GFP-tagged versions of ESCRT-subunits or SEPT9 isoforms and pCMV6-Entry-AKTIP-Myc-Flag (ORIGENE). pEGFPC2 plasmids encoding SEPT9 isoforms were kind gifts from Ulrike Eggert . Cells were then lysed in pull down lysis buffer , cleared by centrifugation and incubated magnetic agarose GFP-trap beads (Chromotek) for 10 minutes. Captured fraction separated by magnetisation and washed with pull down wash buffer . Eluted proteins were recovered with 2x LDS sample buffer and resolved by SDS- PAGE. Resolved proteins were transferred onto nitrocellulose by Western blotting and were probed with the indicated antibodies in 5% milk. HRP-conjugated secondary antibodies were incubated with ECL Prime enhanced chemiluminescent substrate  and visualized by exposure to autoradiography film. The following primary antibodies were used: anti-HA , anti-MYC , anti-GST , anti-GFP . The secondary antibodies used were goat anti-rabbit HRP-conjugated .AKTIP and TSG101 sequence alignment was performed with Jalview . The PDB AKTIP homology model  and the Statistical analyses were performed using Excel and Graphpad Prism software. Results are shown as mean ± SEM of at least three independent experiments. Data were analyzed using unpaired two-tailed Student’s t-test. p-values below 0.05 were considered significant and reported in figures as *p<0.05; **p<0.01; *** p<0.001. p values above 0.05 were considered not significant and were not reported in figures.S1 Fig(A) AKTIP localization at the midbody in HeLa cells using anti-AKTIP antibodies WH0064400M2 clone 2A11 and HPA041794. (B) Detection of exogenous AKTIP-FLAG in transfected cells using anti-FLAG antibody. (C) Immunofluorescence of HeLa cells transduced with a control lentivector containing a scramble interfering sequence (shctr) or with AKTIP interfering sequence (shAKTIP) stained for α-tubulin (green) and AKTIP (red). Scale bars, 5μm. (D) Western blotting of AKTIP expression in shAKTIP and shctr cells. Actin was used as loading control. (E) Representative Q-PCR of AKTIP mRNA expression in shAKTIP and shctr cells.(TIF)Click here for additional data file.S2 FigWestern blotting showing that AKTIP interacts with GST-VPS28 but not with GST alone. Cells were transfected with plasmids encoding the indicated fusion proteins. Purified VPS28-GST or GST alone were used to pull down interacting proteins; cell lysates and glutathione-bound fractions were then analyzed with HA antisera. GST-pull downs were repeated two times. In the HA-AKTIP blot we observe a major band at the correct molecular weight, in the pulldown fractions we observe also degradation products that retain the GST moiety.(TIF)Click here for additional data file.S3 Fig(A) Grey squares: identical residues in AKTIP and TSG101 sequences. Blue boxes: H1, H2, H3, and H4 TSG101 helices. Red boxes: H2, H3, H4, H5 and H6 helices predicted in AKTIP model. White arrows: β-strands. (B) Western blotting showing that AKTIP does not interact with VPS25, VPS22 and VPS36 and confirming its interaction with VPS28. Cells were transfected with the indicated fusion proteins. Purified VPS25-GFP, VPS22-GFP, VPS36-GFP, VPS28-GFP or GFP alone were used to trap interacting proteins; then cell lysates and GFP-trapped fractions were analyzed with MYC antisera. GFP-TRAP were repeated twice.(TIF)Click here for additional data file.S4 Fig(A-B) Representative images and quantification of sictr and siCEP55 transiently transfected HeLa cells stained for CEP55 (red) and α-tubulin (green). Scale bar, 2.5μm. For results in (B) at least 100 midbodies per condition were counted. (C-D) Representative images and quantification of multinucleated cells in sictr and siCEP55 HeLa cells. For results in (D) at least 200 nuclei per condition were counted. Scale bar, 5μm.(TIF)Click here for additional data file.S5 Fig(A-B) Representative images and quantification of sictr and siTSG101 transiently transfected HeLa cells stained for TSG101 (red) and α-tubulin (green). (C-D) Representative images and relative quantification of shctr and shAKTIP HeLa cells stained for ALIX (red) and α-tubulin (green) showing that ALIX is present at the midbody in shAKTIP cells. (E-F) Representative images and relative quantification of sictr and siALIX HeLa cells stained for AKTIP (red) and α-tubulin (green) showing that AKTIP is present at the midbody in siALIX cells. (G-H) Representative images and quantification of sictr and siALIX transiently transfected HeLa cells stained for ALIX (red) and α-tubulin (green). (I-J) Representative images and quantification of sictr and siVPS28 transiently transfected HeLa cells stained for VPS28 (red) and α-tubulin (green). Scale bars, 5μm. For results in  at least 80 midbodies per condition were counted.(TIF)Click here for additional data file.S6 Fig(A-B) Representative images and quantification of sictr and siMKLP1 transiently transfected HeLa cells stained for α-tubulin (green) and MKLP1 (red). For results in (B) at least 25 midbodies per condition were counted. Scale bar, 2.5μm.(TIF)Click here for additional data file.S7 Fig(A) Quantification of the percentage of midbodies with abnormally localized CHMP4B (black) or with two rings (red) and with cones or spirals (white) of CHMP4B referred to CHMP4B positive midbodies in shctr and shAKTIP HeLa cells stained for CHMP4B and α-tubulin ((B-C) Representative images and relative quantification of shctr, shAKTIP, siTSG101, and shAKTIP/siTSG101 HeLa cells, stained for α-tubulin (green) and TSG101 (red). (D-E) Representative images and relative quantification of shctr, shAKTIP, siALIX, and shAKTIP/ siALIX HeLa cells, stained for α-tubulin (green) and ALIX (red). For results in (C and E) at least 100 midbodies per condition were counted. Scale bars, 2.5μm.-tubulin . (B-C) R(TIF)Click here for additional data file.S8 Fig(A-B) Representative images and relative quantification of ctr, and AKTIP-FLAG HeLa cells, stained for α-tubulin (green) and FLAG (red). (C) Representative Q-PCR of AKTIP mRNA expression in ctr and AKTIP-FLAG HeLa cells. (D-E) Representative images and relative quantification of sictr, siTSG101, AKTIP-FLAG/siTSG101 HeLa cells, stained for α-tubulin (green) and TSG101 (red). (F) Representative Q-PCR of AKTIP mRNA expression in shctr, 3’UTR shAKTIP and AKTIP-FLAG/3’UTR shAKTIP HeLa cells. For results in (B and E) at least 80 midbodies per condition were counted Scale bars, 2.5μm.(TIF)Click here for additional data file.S9 Fig(A) Western blotting of AKTIP expression in siAKTIP and sictr cells. Actin was used as loading control. (B) Representative Q-PCR of TRF2 mRNA expression in shTRF2 and shctr HeLa cells. (C-D) Representative images and relative quantification of shctr, shAKTIP, and shTRF2 HeLa cells, stained for α-tubulin (green) and IST1 (red). For results in (D) at least 100 midbodies per condition were counted. Scale bar, 2.5μm.(TIF)Click here for additional data file.S1 Movie3D volume rendering of mid stage midbody imaged with 3D-SIM. HeLa cells were stained with antibodies against α-tubulin (green) and AKTIP (red). The volume rendering and the movie generation were performed with IMARIS software .(MP4)Click here for additional data file.S2 Movie3D volume rendering of late stage midbody imaged with 3D-SIM. HeLa cells were stained with antibodies against α-tubulin (green) and AKTIP (red). The volume rendering and the movie generation were performed with IMARIS software .(MP4)Click here for additional data file.S3 Movie3D volume rendering of midbody imaged with MSIM. HeLa cells were stained with antibodies against AKTIP (green), and TSG101 (red). The volume rendering and the movie generation were performed with IMARIS software .(MP4)Click here for additional data file.S4 Movie3D volume rendering of mid stage midbody imaged with 3D-SIM. HeLa cells were stained with antibodies against α-tubulin (green), IST1 (blue) and AKTIP (red). The volume rendering and the movie generation were performed with IMARIS software .(MP4)Click here for additional data file.S5 Movie3D volume rendering of late stage midbody imaged with 3D-SIM. HeLa cells were stained with antibodies against α-tubulin (green), IST1 (blue) and AKTIP (red). The volume rendering and the movie generation were performed with IMARIS software .(MP4)Click here for additional data file.S6 MovieTime-lapse microscopy of HeLa cells stably expressing mCherry-tubulin treated with siAKTIP. The movie generation was performed with Fiji software.(AVI)Click here for additional data file.S7 MovieTime-lapse microscopy of HeLa cells stably expressing mCherry-tubulin treated with siAKTIP. The movie generation was performed with Fiji software.(AVI)Click here for additional data file.S8 MovieTime-lapse microscopy of HeLa cells stably expressing mCherry-tubulin treated with ctr. The movie generation was performed with Fiji software.(AVI)Click here for additional data file.


Numerous natural products exhibit antiproliferative activity against cancer cells by modulating various biological pathways. In this study, we investigated the potential use of eight natural compounds  and two repurposed agents (fulvestrant and metformin) as chemotherapy enhancers and mesenchymal-to-epithelial (MET) inducers of cancer cells. Screening of these compounds in various colon, breast, and pancreatic cancer cell lines revealed anti-cancer activity for all compounds, with curcumin being the most effective among these in all cell lines. Although some of the natural products were able to induce MET in some cancer cell lines, the MET induction was not related to increased synergy with either 5-FU, irinotecan, gemcitabine, or gefitinib. When synergy was observed, for example with curcumin and irinotecan, this was unrelated to MET induction, as assessed by changes in E-cadherin and vimentin expression. Our results show that MET induction is compound and cell line specific, and that MET is not necessarily related to enhanced chemosensitivity. Cancer is the second leading cause of death worldwide and about one in six deaths are due to cancer . ChemothNutrition and diet are effective in reducing cancer risk. Numerous dietary natural products have shown potential in prevention and/or treatment of cancers ,8,9. AccCleus forskohlii, was shown to induce tumor-initiating cells to undergo mesenchymal-to-epithelial transition, and to cause them to lose their tumor-initiating ability [In line with these observations, modulators of EMT, combined with chemotherapeutics and/or targeted drugs, may possibly improve clinical outcomes in cancer. Most studies aiming to address this issue, however, were conducted either in single cell lines, or only in one cancer type . Hence,  ability . Procyan ability . Additio ability ,32. It w ability . Fulvest ability ,35,36,37 ability ,51,52,53We first sought to characterize the inhibitory effect of natural products and repurposed agents on various breast, colon, and pancreatic cancer cell lines. We selected eight naturally occurring molecules, an estrogen antagonist, and an anti-diabetic drug that were previously shown to inhibit and/or reverse EMT. The cells were designated resistant if an IC50 value was not observed within the concentration ranges tested. For the breast cancer cell lines, curcumin exhibited a remarkable inhibition of cell viability, with IC50 values ranging from 12 to 40 μM among the cell lines tested . AdditioSince diet is an important factor in colon cancer risk, studying the effects of natural products on colon cancer may provide new insights into cancer prevention and treatment . In a siPancreatic ductal adenocarcinoma (PDAC) is among the most lethal cancer types, and a number of naturally occurring molecules in preclinical studies exhibit promising pharmacological features ,57. We eIn total, 12, 13, and 15 cancer cell lines (out of 16) were resistant (IC50 could not be determined within the concentration ranges tested) to forskolin, procyanidin B2, and fulvestrant, respectively, suggesting that these compounds were not effective inhibitors of cancer cell viability. Apigenin, curcumin, and resveratrol were the only three compounds for which IC50 values could be generated for all of the cell line types tested. Among these compounds, the lowest mean IC50 was obtained for curcumin for all three cancer types, with values of 23.8 μM, 10 μM, and 15 μM for breast, colon, and pancreatic cancer cells, respectively.We treated six cell lines from three cancer types with natural compounds and evaluated changes in the epithelial/mesenchymal phenotypes . We usedOverall, we noted transcriptional changes suggesting a shift towards a more epithelial phenotype in four out of the six cell lines tested upon treatment with at least one compound. The MET induction effects summarized in We next asked whether the treatment with natural compounds would result in chemosensitization. For this purpose, the KM12 and WiDr colon cancer cell lines were treated with various doses of natural products, alone or in combination with two doses (1 μM and 10 μM) of 5-FU, a commonly used chemotherapeutic in colon cancer, after twenty-four hours of cell seeding. Cell viability assays were then performed 72 h after the treatments. In KM12, we observed MET induction with 20 uM of fisetin and two doses (10 μM and 30 μM) of forskolin. However, only the 10 uM 5-FU and forskolin combination treatments resulted in synergy, with the combination index (CI) score ranging from 0.91 to 0.37 . AdditioWe next investigated the combinatory effects of irinotecan, used in pancreatic cancer, and some widely studied natural compounds, curcumin and resveratrol, in pancreatic cancer cell lines, AsPC-1, BxPC-3, MIA PaCa-2, and SU8686 . Most ofGemcitabine is a standard agent for the treatment of pancreatic cancer, either alone or in combination ,63. We tInnate or acquired resistance of cancer cells to chemotherapeutics is responsible for tumor growth and metastasis ,66. SeveA wide range of natural products have been reported as being cytotoxic for cancer cells and therefore useful in cancer therapy. Natural products can act as therapeutic, preventive, or chemosensitizer agents. Enhancement of chemotherapy sensitivity in tumor cells using naturally occurring biomolecules is a new and promising strategy aiming to promote the efficacy of conventional chemotherapeutics and targeted drugs . SeveralIn the present study, we used eight natural compounds and two repurposed agents, that were previously shown to modulate EMT in different types of cancer cell lines, to test their capability to sensitize cancer cells to chemotherapy in a comprehensive manner. Although there are studies supporting the modulatory effects of all these compounds on EMT, only a few of them were able to induce MET in specific cancer cell lines in our experiments, suggesting a highly selective cell-line specific action. Interestingly, none of the compounds were able to induce MET in the Caco-2 cell line, which can easily be induced to undergo EMT and MET under various other conditions . In factDifferent transcriptomic signatures have been evaluated for determining the EMT status of cancer cells ,72,73. EAmong the compounds we examined in this study, almost none were found to both trigger MET and induce chemosensitization. In KM12, although fisetin and forskolin induced MET, the fisetin and 5-FU combination did not show a synergistic effect. On the other hand, urolithin A synergized with 5-FU in KM12 in the absence of MET induction. Furthermore, slight MET induction in MIA PaCa-2 with natural compounds did not lead to improved sensitivity to irinotecan, gemcitabine, and gefitinib in almost all combinations.These findings show that synergy between natural compounds and chemotherapeutics/targeted agents can be observed only for some cell lines and that the underlying mechanism is likely not to be the simple induction of MET, but possibly a combination of several other mechanisms. The fact that synergistic effects were also quite variable across cancer types as well as in cell lines within a given cancer type suggests that the mechanisms underlying these observations are highly cell line specific.2.Breast cancer cell lines, CAL51, MDA-MB-157, MDA-MB-231, MDA-MB-436, MDA-MB-453, and MDA-MB-468 were cultured in DMEM medium . Colon cancer cell lines, Caco-2, HCT-8, KM-12, LS513, LoVo, SW837, and WiDr were cultured in RPMI-1640 medium . Pancreatic cancer cell lines, AsPC-1, BxPC-3, and SU8686 were cultured in RPMI-1640 medium, while MIA PaCa-2 cells were cultured in DMEM medium. The respective media were supplemented with 10% fetal bovine serum (FBS) , 1% penicillin-streptomycin , and 1% 200 mM L-Glutamine  at 37 °C with 5% COChemotherapeutics, 5-FU (S1224), gemcitabine (S1149) and irinotecan (S2217), were purchased from Selleckchem . Targeted cancer therapy drugs, gefitinib (S1025) and selumetinib (S1008) were purchased from Selleckchem, while lapatinib (11493) was purchased from Cayman Chemical . Fulvestrant  and metformin  were used as repurposed agents. Natural products, apigenin (S2262), curcumin (S1848), fisetin (S2298), and forskolin (S2449) were purchased from Selleckchem, while (-)- epigallocatechin gallate (70935), procyanidin B2 (19865), resveratrol (70675) and urolithin A (22607) were purchased from Cayman Chemical. All chemicals had more than 98% purity. Stock solutions were prepared according to the manufacturers’ instructions.Cancer cell lines were seeded at 2000 cells per well in 96-well plates . After incubation for 24 h, cells were treated with chemotherapeutics, targeted drugs, and natural compounds using 6 different concentrations: apigenin, curcumin, EGCG, fisetin, forskolin, procyanidin B2, resveratrol, urolithin A, fulvestrant: 0.1–100 μM; metformin: 0.4–60 mM (in colon and pancreatic cancers); metformin: 0.1–100 μM (in breast cancer). Cell viability was analyzed in quadruplicates using the CellTiter-Glo Luminescent Cell Viability Assay , according to the manufacturer’s protocol, after 72 h of treatment. IC50 values were obtained by a method previously described . DiffereTo quantitate synergy combination treatments of natural compounds, chemotherapeutics and targeted drugs were analyzed with the Chou-Talalay methods using CompuSyn Software  which generates a combination index (CI) which was calculated with the cell viability values from combination treatments. CI < 1 indicates synergy, CI = 1 indicates additive effect, while CI > 1 indicates antagonism.Total RNA was isolated using Purezol  according to the manufacturer’s instructions. Two micrograms of total RNA were reverse-transcribed into cDNA using the Revert-aid first strand cDNA synthesis kit  according to the supplier’s protocol using a random hexamer. Quantitative profiling of EMT marker genes CDH1 and VIM by qRT-PCR was performed in triplicates using a LightCycler 480 II real-time PCR system  and iTaq Universal SYBR Green Supermix . Real-time PCR reactions were run under cycling conditions according to the manufacturer’s instructions. GAPDH was used as an endogenous control in qPCR reactions in triplicates and gene expression signals were normalized to GAPDH. Relative expression values of CDH1 and VIM were calculated by the ddCt method according to samples with least expression as previously described . qPCR prp-values less than 0.05 were considered as statistically significant.Statistical analysis was performed using R Statistical Software  and different treatment groups were compared using the Mann–Whitney U test.


Testicular cancer (TC) is the most frequent type of cancer among young men aged between 15 and 34 years. TC is treated using cisplatin, but 3%–5% of TC patients fail to respond to cisplatin, with a very bad to fatal prognosis. Accordingly, it is most important to quickly and readily identify those TC patients who are resistant to cisplatin treatment.This study seeks to investigate changes in the glycosylation associated with cisplatin resistance to TC cell lines.A specific glycoprofiling of human chorionic gonadotropin (hCG) was analysed in three TC cell lines and one cell line of female origin. A typical calibration curve for hCG glycoprofiling showed a dynamic range up to 50 ng/ml, with a limit of detection of 0.3 ng/ml and assay reproducibility represented by relative standard deviation of 3.0%. Changes in the glycan signatures on hCG were analysed in cisplatin‐sensitive cell lines and in their cisplatin‐resistant sub‐lines using an enzyme‐linked lectin assay (ELLA) protocol. An immobilised antibody was applied to a selective capture of hCG from a cytoplasmic fraction of cell lysates with final incubation using a lectin from a panel of 17 lectins.Dolichos biflorus agglutinin (DBA) can selectively discriminate sensitive TC cell lines from resistant TC cell lines. Moreover, there are additional lectins which can provide useful information about the strength of cisplatin resistance.The results suggest that one particular lectin  50 values for the sensitive cell lines and for the resistant cell lines.This is the first study focused on the use of a specific glycoprofiling of hCG using a panel of lectins for the investigation of glycosylation changes associated with TC or associated with cisplatin resistance. We identified DBA lectin as the most perspective one to evaluate resistivity of TC lines. Moreover, we found some lectins, which can be applied for positive correlation between lectin binding to hCG and cisplatin IC This drug is also effective in curing TC patients having metastases with cure rates of up to 90% and with a general survival rate of up to 95%.Cisplatin  which cannot be repaired by the DNA repair mechanisms, resulting in a disruption of synthesis of DNA, mRNA and proteins, promoting the accumulation of reactive oxygen species; activating signalling pathways and finally resulting in cell death.N‐acetylglucosaminyltransferase V (GnT‐V), which synthesises β6GlcNAc branched N‐glycans,N‐glycans, were determined in a radioresistant nasopharyngeal carcinoma cell line.N‐glycans synthesised by upregulated FUT4 fucosyltransferase are also behind multidrug resistance of breast cancer cells.Glycomics is an emerging scientific discipline studying the involvement of glycans (complex carbohydrates) in the physiological and pathological processes including cancer development and progression.O‐glycan on Ser132 of the β‐subunit of hCG), which is known as the hyperglycosylated form of hCG (hCG‐H), in relation to various physiological and pathological conditions.We have not yet identified any study focusing on an investigation of glycan changes associated with cisplatin resistance of TC cells lines. Hence, the main aim of this study was to investigate changes in the glycan expression of four different cell lines together with their cisplatin‐resistant sub‐lines. We wanted to investigate glycosylation changes in hCG associated with cisplatin resistance and to identify lectins able to provide information about the presence of cisplatin resistance. The main reason for choosing hCG for glycoprofiling is the fact that the level of hCG is routinely used as a TC biomarker to monitor therapy efficiency.22.12.1.1The following antibodies were purchased from Abcam and were used in the study: anti‐hCG beta core fragment antibody [INN‐hCG‐106] (ab11382); anti‐hCG beta 1 epitope antibody [INN‐hCG‐2] (ab11388) and anti‐hCG beta 2 epitope antibody [INN‐hCG‐106] (ab11389).2.1.2Three different hCG proteins purchased from Abcam were used in the study to identify proper hCG standards to be recognised by the antibody, while being glycosylated: native human hCG beta protein (ab126653), native human hCG protein (ab77874) and recombinant human hCG beta 7 protein (ab164958).2.1.3Aleuria aurantia lectin , Concanavalin A , Dolichos biflorus agglutinin , Narcissus pseudonarcissus (Daffodil) lectin , Datura stramonium lectin , Galanthus nivalis lectin , Hippeastrum hybrid (Amaryllis) lectin , Lens culinaris agglutinin , Maackia amurensis agglutinin II , Phaseolus vulgaris erythroagglutinin , Phaseolus vulgaris leucoagglutinin , Peanut agglutinin , Pisum sativum agglutinin , Ricinus communis agglutinin I , Sambucus nigra agglutinin , Wisteria floribunda agglutinin  and Wheat germ agglutinin .The following biotinylated forms of lectins for the enzyme‐linked lectin assays (ELLA) were provided from Vector laboratories: 2.1.4All the following chemicals were obtained from Sigma: bovine serum albumin , albumin from human serum , hydrogen peroxide solution , phosphate‐buffered saline , phosphate‐buffered saline with Tween  and o‐phenylenediamine .Streptavidin‐conjugated HRP (ready‐to‐use) was obtained from Abcam (ab64269).2.22.2.1Aleuria aurantia lectin ; Maackia amurensis agglutinin II ; Phaseolus vulgaris erythroagglutinin ; Phaseolus vulgaris leucoagglutinin  and Sambucus nigra agglutinin .The following lectins were used to determine whether hCG standard is glycosylated and can be used in a standardisation process within an enzyme‐linked lectin assay (ELLA) format. All the following non‐conjugated lectins were obtained from Vector Laboratories: 2.2.2All the reagents used in SPR experiments were purchased from GE Healthcare, including HBS‐P+ , amine coupling kit (BR100050), EDC (0.4 M), NHS (0.1 M) and ethanolamine hydrochloride . For regeneration, the following regeneration buffers were tested : NaOH  and glycine/HCl ; acetate 5.0 (BR‐1003‐51) was used for coupling. In order to regenerate the SPR chip following binding with lectins, the following elution solutions were used (Vector Laboratories): that is, solutions for eluting mannose/glucose‐binding lectins (ES‐1100‐100); galactose/GalNAc‐binding lectins (ES‐2100‐100); fucose/arabinose‐binding lectins (ES‐3100‐100); GlcNAc/chitin‐binding lectins (ES‐5100‐100) and sialic acid‐binding lectins (ES‐7100‐100).SPR assays were run on Biacore X100  using a sensor chip CM5 (29‐1496‐04) under a constant flow rate of 30 μl/min at 25°C. Original SW Biacore X100 Control Software was used to operate the instrument.2.2.3In this examination, hCG was used as a ligand to be immobilised on the SPR chip. The SPR chip was activated using EDC/NHS (ratio 1+1) amine coupling with the chip activated for 420 s. Then, hCG  was diluted to 16.3 μg/ml (428 nM) in an acetate immobilisation buffer of pH 5.0 and was immobilised on the CM5 sensor chip for 1000 s. Finally, the SPR chip was blocked with ethanolamine (contact time of 420 s). A typical level of bound hCG was 1735 RU. The chip preparation was completed by washing the cell with a running buffer (HBS‐P+) for 10 min with application of five pulses of 20 mM NaOH for 30 s; finally, the chip was re‐equilibrated with a HBS‐P+ running buffer.A recombinant hCG  or a native hCG  was immobilised on the sensor chip CM5 for 600 s into cell 1 and cell 2, respectively, using a protein concentration of 16.3 μg/ml (428 nM).Interactions between the ligand immobilised on the chip (hCG) and lectins were measured by a multi‐cycle kinetics mechanism (MCK). Association and dissociation phases were set to 120 and 500 s, respectively. Lectins were diluted in a HBS‐P+ buffer to concentrations of 300, 150, 75, 37.5, 18.8 and 0 nM (lectins at a concentration of 18.8 nM were measured twice). Chip regeneration after each cycle was performed using 60 s pulse with the suitable glycoprotein eluting solution (Vector Laboratories) described above followed by 30 s pulse with 20 mM NaOH; finally, the chip was re‐equilibrated with an HBS‐P+ running buffer.Interactions between the ligand immobilised on the chip (hCG) and antibodies were also measured by MCK. Sample contact time and dissociation time were set to 120 and 750 s, respectively, for interaction with antibodies diluted in a HBS‐P+ buffer to concentrations of 73.3, 36.7, 18.33, 9.16, 4.58 and 0 nM (antibodies at a concentration of 4.58 nM were measured twice). Chip regeneration after each cycle was performed by surface washing using a 30 s pulse with a glycine/HCl regeneration buffer pH 2.5 and using 30 s pulse with 20 mM NaOH; finally, the chip was re‐equilibrated with an HBS‐P+ running buffer.via EDC/NHS chemistry and then blocked with ethanolamine . Chip preparation was completed by washing its surface for 10 min with a running buffer (HBS‐P+) and by five pulses of 20 mM NaOH for 30 s each. Interactions between antibodies immobilised on the chip and hCG were measured by MCK. Sample contact time and dissociation time were set to 120 s and 750 s, respectively. An analyte was diluted in an HBS‐P+ buffer to concentrations of 239, 119.5, 59.8, 29.9, 14.9 and 0 nM (hCG at a concentration of 14.9 nM was measured twice). Chip regeneration after each cycle was performed by washing the surface with a glycine/HCl regeneration buffer pH 2.5 for 30 s and for 30 s with 20 mM NaOH solution; finally, the chip was re‐equilibrated with an HBS‐P+ running buffer.In order to double check the bioaffinity interaction between hCG and an antibody, an anti‐hCG antibody was also immobilised onto the SPR chip. An anti‐hCG beta 2 epitope antibody , diluted to 2.86 μg/ml (19.0 nM) in an acetate immobilisation buffer (pH 5.0) was immobilised to a target level of 400 RU onto the sensor chip CM5 Interaction in a sandwich configuration was studied in two different forms by an MCK mechanism. In the first, we used a feature of the Biacore X100 Control Software to start each cycle with a capture. hCG (ab77874) diluted in a running buffer to 81.6 nM was repeatedly captured for 120 s over the immobilised antibody on the CM5 chip. In the next step, the lectin binding was investigated using a common MCK mechanism. In this case, sample (lectin) contact time and dissociation time were set to 120 and 500 s, respectively, and chip regeneration was performed with glycine pH 2.5 for 30 s and 20 mM NaOH for 30 s (i.e. both lectins and hCG were released from the surface). In the second approach, the hCG was injected over the antibody‐immobilised surface just once. Then the lectin binding to hCG captured over the anti‐hCG layer was monitored using MCK. Chip regeneration was performed using a suitable glycoprotein‐eluting solution for 30 s (i.e. only the lectin was released from the surface). In both versions, the lectin concentrations investigated were 300, 150, 75, 37.5, 18.8 and 0 nM.The data thus obtained were evaluated using the original SW Biacore X100 Evaluation Software with pre‐set preferences.2.3o‐phenylenedimamine) as a substrate. OPD and hydrogen peroxide were dissolved in a citrate‐phosphate buffer (pH = 4.6) to concentrations of 7.4 mM and 0.52 M, respectively. To each well, 100 μl of this OPD‐peroxide solution was applied. The absorbance at 450 nm was measured after 15 min incubation in dark and the reaction was stopped with 3.6 M H2SO4.The ELLA assay was based on a common protocol of a conventional sandwich ELISA. Briefly, 100 μl of an anti‐hCG antibody diluted to 1 μg/ml with PBS was added into the wells of the plate . After overnight incubation in a refrigerator, the plate was washed three times with 215 μl of PBST buffer. Unoccupied places in wells were blocked with 200 μl of HSA (1 mg/ml) for 45 min using a plate shaker . The ELISA plate was then incubated with 100 μl of sample and, after washing, 100 μl of lectins diluted by 1 mg/ml of HSA solution to concentration of 1.5 μg/ml were added and incubated for 1 h under shaking. After washing, 100 μl of 75× diluted streptavidin HRP in HSA (1 mg/ml) was added to the wells and incubated for 60 min. Then the plate was rinsed 3× with 215 μl of PBST buffer and once again with PBS. The detection was accomplished using OPD .2.4Since lectins are able to bind to the glycans present in the Fc fragment of the antibody , it is advisable to de‐activate such a glycan recognition site by glycan oxidation.2O2 solution, the signal was read at 490 nm after a blank subtraction.Glycans of anti‐hCG antibodies were modified to prevent binding of lectins, which would interfere with the glycoprofiling of hCG. Prior to oxidation, the following two reaction solutions were prepared: solution A (150 mM sodium acetate of pH 5.5) and solution B (25 mM sodium metaperiodate in solution A). An antibody ab11389 was diluted to 0.1 mg/ml with solution B and incubated at 4°C in dark for 30 min. The solution was then desalted using previously equilibrated columns (Zeba Spin 7000 MWCO). Freshly prepared 2 mM propionic acid hydrazide in solution A was added to an antibody solution at a 1:1 (v/v) ratio. The reaction mixture was incubated at ambient temperature in dark for 2 h. The final desalting was performed using a new desalting column and the oxidised and blocked antibody was stored at −80°C in aliquots. ELLA was used to control efficiency of oxidation of anti‐hCG antibody glycans. The wells of the ELISA plate were incubated with intact and chemically oxidised antibodies. The surface was subsequently blocked and left to interact with a panel of 17 biotinylated lectins. After 60 min incubation with streptavidin peroxidase (HRP) conjugate and OPD/H2.5Four cisplatin‐sensitive TC cell lines  and their cisplatin‐resistant variants (JEG‐3 CisR (D) VOL II, NCCIT CisR (D) VOL II, NTERA‐2 CisR and TCam‐2 CisR) together with a control non‐cancerous testis cell line (Hs 1.Tes) were used in the study.® CRL‐2073™) were maintained in RPMI 1640 medium (GIBCO® Invitrogen) containing 10% FBS, 10.000 IU/ml penicillin, 5 μg/ml streptomycin, 2.5 μg/ml amphotericin and 2 mM glutamine. The human embryonal carcinoma cell line NTERA‐2 (ATCC® CRL‐1973™) and the JEG‐3 choriocarcinoma cell line (ATCC® HTB‐36™) were cultivated in high‐glucose (4.5 g/L) DMEM (PAA Laboratories GmbH) supplemented with 10% FBS (GIBCO® Invitrogen), 10.000 IU/ml penicillin (Biotica), 5 μg/ml streptomycin, 2.5 μg/ml amphotericin and 2 mM glutamine (PAA Laboratories GmbH). Finally, the human normal testis cell line Hs 1.Tes (ATCC® CRL‐7002™) was grown in high‐glucose (4.5 g/L) DMEM (PAA Laboratories GmbH) with the addition of 10% FBS (GIBCO® Invitrogen).The TCam‐2 human seminoma cell line  as well as the human embryonal carcinoma cell line NCCIT (ATCCCisplatin‐resistant sub‐lines (JEG‐3 CisR (D) VOL II, NCCIT CisR (D) VOL II, NTERA‐2 CisR and TCam‐2 CisR) were generated in our laboratory over a period of 6 months. Cisplatin‐resistant sub‐lines used in this study were derived by a long‐term propagation of matched parental cells in sub‐lethal concentrations of cisplatin  in the culture medium described previously.2. The characteristics of the cell lines investigated are summarised in Table All the used parental as well as cisplatin‐resistant cell lines were incubated at 37°C in a humidified atmosphere with 5% CO2.63 cells/100 µl  and of 4 × 103 cells/100 µl for NCCIT cell line, respectively, per well, were placed in 96‐well white‐walled plates (Corning Costar Life Sciences) and treated with cisplatin (0.01–5 µg/ml) overnight. The relative viability of the cells was measured using the CellTiter‐Glo™ Luminescent Cell Viability Assay (Promega Corporation) according to the manufacturer's protocol and evaluated by the LUMIstar GALAXY reader (BMG Lab Technologies) after 6–7 days  VOL II cells) or after 3 days of treatment (NCCIT and NCCIT CisR (D) VOL II cells). Each concentration was measured in quadruplicates. IC50 values were calculated by CalcuSyn 1.1 software (Biosoft).For the determination of chemosensitivity, cisplatin‐sensitive and cisplatin‐resistant TC cells of 2 × 102.76 cells  or 8 × 106 cells  were centrifuged at 700 × g for 5 min. Pellets of cells were washed with 5–10 ml of ice‐cold PBS and centrifuged again at 700 x g for 5 min. Supernatants were removed and the pellets thus obtained were re‐suspended in 400 µl of Cytosol Extraction Buffer Mix (CEB Mix containing DTT and Protease Inhibitor Cocktail). After 20 min incubation of the samples on ice, the analysed samples were centrifuged again at 700 × g for 5 min. The isolated supernatants, representing the cytosolic protein fraction, were stored at −80°C.A cytosolic protein fraction from TC cell lines was prepared using Fraction PREP TM Cell Fractionation kit (Bio Vision) according to the manufacturer's protocol. Briefly, 4 x 1033.1Investigation of the lectin binding to hCG was performed using surface plasmon resonance (SPR) involving a panel of five lectins, three hCG standards and using injections of lectins at seven different concentration levels . In total, at least 107 SPR sensorgrams were recorded and evaluated. Recombinant hCG (ab164958) was not glycosylated since SPR did not show any binding to a panel of five lectins (data not shown) and this form of hCG was excluded from further assays. Hence, the glycosylation of only two hCG forms was investigated.D and RUmax) regarding the strength and intensity of the lectin binding to the hCGs immobilised on the SPR chip, are summarised in Table The results indicate that hCG (ab77874) generally shows a higher level of binding to a panel of lectins Figure  top leftIn the next experiment, the binding of antibodies to the two glycosylated forms of hCG was investigated. In this particular case, we investigated the binding of three different antibodies at seven different concentration levels  to the two different hCGs immobilised on the SPR chip, that is, investigating at least 42 SPR sensorgrams. Some experiments were performed in a configuration with an antibody immobilised on the SPR chip with hCG present in a running buffer to cross‐check antibody–hCG bioaffinity interactions (i.e. 63 SPR sensorgrams). A summary from these investigations is provided in Table The results suggest that the best bioaffinity interaction was achieved between the native human hCG protein (ab77874) captured over the immobilised anti‐hCG beta 2 epitope antibody (ab11389) Table .In the final SPR experiment, we investigated the possibility of binding lectins to hCG (ab77874) bioaffinity captured on the SPR chip modified by the immobilised anti‐hCG beta 2 epitope antibody (ab11389). In other words, it was important to determine whether a biorecognition between hCG and an antibody occurs at the epitope, which is distant from the glycan‐containing epitope on hCG making it possible to form an Ab/hCG/lectin sandwich configuration, which is required for a specific glycoprofiling of hCG.The results showed that MAA, SNA and PHAE lectins  and an oxidised anti‐hCG was performed in an ELISA‐like analysis format. The experiment indicates four lectins, in particular, significantly binding to the non‐oxidised anti‐hCG antibody. Of those four lectins, two bind to fucose (AAL and LCA) and the other two lectins bind to mannose glycan units (ConA) or terminal 2,6‐SA (SNA) on the non‐oxidised antibody. Oxidation of the glycan on the anti‐hCG resulted in a significant decrease in binding of all the lectins investigated Figure . On the In the next sequence, we used the oxidised form of the antibody taking into account that the binding of ConA and AAL to the antibody was not fully suppressed. So the results obtained by the glycoprofiling of hCG using ConA and AAL should be treated with caution.3.350 values for sensitive and resistant variants of the cell lines is provided in Table In this study, we used four different cell lines  with cisplatin‐sensitive and cisplatin‐resistant variants and one control cell line (CTRL i.e. Hs 1.Tes cell line) Table . We inveThe binding of selected lectins to hCG immunocaptured by the anti‐hCG antibody in the ELLA experiment is shown in Figure 3.3.1The NTERA‐2 cell line is a primary male testicular cell line, representing a malignant pluripotent embryonal carcinoma isolated from lung metastases with non‐seminoma‐related cells.In general, it may be stated that no significant changes in hCG's glycans are observed between the sensitive NTERA‐2 and the CTRL cell lines, when considering mannose‐recognising lectins such as ConA, HHL, DFL, GNL and PSA. Insignificant glycan changes when compared with the CTRL cell line were also observed for other lectins such as DBA, RCA, PNA, WGA, DSL, PHAL and PHAE Figure .A significant difference between the sensitive NTERA‐2 and the CTRL cell lines was observed using the LCA lectin  and the AAL lectin (recognising core and antennary fucose (aFuc)) with such glycans being present in lower amounts in the sensitive NTERA‐2 cell line compared to the CTRL one. Significantly lower binding to hCG from the sensitive NTERA‐2 cell line than for the CTRL was also observed for the WFL, SNA and MAA lectins Figure .Accordingly, we may conclude that the sensitive NTERA‐2 cell line does not synthesise a higher level of glycans than the CTRL cell line, which accords with the published data.3.3.2TCam‐2 cell line represents a testicular seminoma‐like cell line of male origin.While there is no difference in ConA binding, a significant increase in HHL and DFL binding to hCG for the cancerous‐sensitive cell line over the CTRL cell line was observed Figure . This inA significant increase in the binding of lectins to hCG from the cancerous‐sensitive cell line over the CTRL cell line was further observed for WFL, AAL, RCA, DSL, WGA, PHAL and SNA.N‐glycans (PHAL) or 2,6‐SA (SNA)‐containing glycans in the sensitive TCam‐2 cell line than in the CTRL cell line. An increased binding of SNA to hCG from the cancerous cell line TCam‐2 over the control cell line is in agreement with findings in the literature, where increased levels of sTn and sT antigens were shown in the tissues of the patient with seminoma type of TC.Hence, we may conclude that there is an increased expression of glycans containing pMan (HHL and DFL), aFuc (AAL), GalNAc (WFL), Gal/GalNAc (RCA), Gal‐GlcNAc (DSL), GlcNAc (WGA), branched N‐glycans in TC serum samples performed by another group of researchers revealed that, in particular, levels of tri‐/tetra‐antennary glycans (PHAL) with terminal sialylation (SNA and/or MAA), galactosylation (RCA and/or DSL) or terminal GlcNAc (WGA), were increased in GCT patients.Analysis of 3.3.3JEG‐3 cell line represents choriocarcinoma of placenta cell line of female origin.The JEG‐3 cell line exhibits lower ConA (Man), DFL (pMan), GNL (Man), LCA (cFuc), AAL (aFuc), WFL  and SNA 2,6‐SA) binding than in the CTRL cell line  of male origin.Hence, a lower expression of various types of glycans on hCG from the NCCIT cell line than for the CTRL cell line is similar to the JEG‐3 and NTERA‐2 cell lines.3.4The binding of selected lectins to hCG immunocaptured by the anti‐hCG antibody in the ELLA experiment is shown in Figure 3.4.1a antigen, GalNAc‐Gal) and SNA  binding to hCG expressed by the resistant cell line over the sensitive one  binding to hCG from the resistant NTERA‐2 cell line when compared with the sensitive NTERA‐2 cell line with a significant increase in DBA  and the resistant  cell lines versus cisplatin IC3.5.150 values is shown in Figure 50 values for the following lectins: AAL, DFL, DSL, HHL, PHAE, PNA, SNA and WFL with a quasi‐exponential and strong pattern of correlation for HHL .If we hypothesise that the changed glycosylation on hCG results from an exposure of cells to cisplatin, then any type of correlation between lectin binding and cisplatin IC50 value  activity (formation of Sda antigen) in colon, gastric cancer and embryonal carcinoma.a antigen to the enzymatic action of fucosyltransferases expressing sLea or sLex antigens on glycans, which are very important glycan determinants of induction of a metastatic process.a level is directly proportional to a decrease in the level of sLea or sLex antigens (aFuc) and vice versa.a antigen) to hCG was observed  to hCG of the sensitive cell line was observed , HHL , DFL , AAL (TCam‐2 and NCCIT), WFL (TCam‐2), WGA (TCam‐2), SNA (TCam‐2 and NCCIT) and MAA (NCCIT). This is in agreement with the study showing an increased binding of DBA lectin to hepatocellular carcinoma cells treated with the multikinase inhibitor sorafenib, while the binding of lectins such as MAA, PHAL, RCA and SNA was significantly reduced for the cells treated with sorafenib on a lectin microarray using a cytosolic cell fraction.w = 90–150 kDa for a resistant sub‐line than for a sensitive one.On the other hand, the binding of several lectins to HCG's glycans was lower for the cisplatin‐resistant cell lines than for the sensitive cell lines including SNA lectin. This is in agreement with the study, where it was observed that a resistant serous ovarian cancer cell line exhibited a lower binding of SNA, WFL and seven other lectins.N‐glycans.The level of fucosylated glycans was lower in the resistant ovarian cancer cell line than in the sensitive one, applying mass spectrometry to a cytosolic fraction of cells with released N‐ or O‐glycome using a lectin microarray or a MS‐based approach. Accordingly, it is important to note that in these studies the authors did not identify proteins with particularly changed glycans. Only one study indicates that a particular glycan signature can be associated with one protein or subset of proteins and the other particular glycan change can be associated with another protein or another subset of proteins.Lycopersicon esculentum lectin, increase in binding) and SNA (decrease), when using a lectin microarray. A lectin dot blot revealed that LCA bound to glycoproteins with Mw of 70–180 kDa; ConA bound glycoproteins with Mw of 50–180 kDa; LEL bound to glycoproteins with Mw of 50–110 kDa, Mw of 40–50 kDa, and with Mw above 180 kDa; while SNA bound to glycoproteins with Mw of 50–180 kDa.It should be observed that all the published studies discussed so far analysed the whole N‐glycans or O‐glycans significantly affects the binding of lectins recognising the terminal parts of the glycans   or CAD antigenThe results thus obtained lead us to hypothesise that the addition of GalNAc to ) Figure . Based o) Figure , cells a) Figure  or TC ce) Figure  with an Furthermore, lectins such as AAL, DFL, DSL, HHL, PHAE, PNA, WFL and PSA could potentially be used for the identification of a pre‐target resistant mechanism, while lectin SNA could be used for the identification of a post‐target resistant mechanism (i.e. to identify TC patients resistant to cisplatin treatment after a first round of chemotherapy). This hypothesis, however, needs to be verified using serum/plasma samples of TC patients.550 values for the sensitive cell lines and for the resistant cell lines. The results observed in the current study require validation using serum/plasma samples of TC patients in order to corroborate the clinical potential of specific glycoprofiling of hCG to identify cisplatin‐resistant TC patients, who have a poor prognosis.This is the first study focused on use of a specific glycoprofiling of hCG using a panel of lectins for investigation of glycosylation changes associated with TC or associated with cisplatin resistance. We identified the DBA lectin as the best prospect for evaluating the resistance of TC lines. Moreover, we identified some lectins to be used for positive correlation between lectin binding to hCG and cisplatin ICThe authors declare no conflict of interest.MH & EJ: investigation, data curation and writing ; KK: investigation, resources and writing original draft; MC & MM: conceptualisation, resources and writing ‐ review and editing; PK: funding acquisition, project administration and writing ‐ review and editing; TB: formal analysis, visualisation and writing  and JT: conceptualisation, formal analysis, funding acquisition, methodology, supervision and writing .The work with TC cell lines did not require ethics approval.Supplementary MaterialClick here for additional data file.