VCaP and hiPLNCaP cell lines were treated with 5 μmol/L AA for more than 20 passages, respectively, generating the AA-tolerant-subtypes VCaPAA and hiPLNCaPAA. Cell lines were treated with testosterone, dihydrotestosterone (DHT), R1881, and the androgen-metabolites 3β-androstanediol and 3α-androstanediol. 3β-androstanediol or 3α-androstanediol significantly reduced proliferation in all cell lines except the BPH-1 and androgen receptor-negative PC-3 and markedly downregulated AR and estrogen receptor alpha (ERα). Whereas ERβ expression was increased in all cell lines except BPH-1 or PC-3. In summary, 3β-adiol or 3α-adiol, as well as DHT and R1881, significantly reduced tumour cell growth in CRPC cells. Thus, these compounds represent novel potential therapeutic approaches to overcome drug-resistance in CRPC, especially with regard to AR-V7 function in therapy resistance. Furthermore, these data confirm the tumour suppressor properties of ERβ in CRPC.Novel treatments for castration-resistant prostate cancer (CRPC) such as abiraterone acetate (AA) or enzalutamide effectively target the androgen pathway to arrest aberrant signalling and cell proliferation. Testosterone is able to inhibit tumour cell growth in CRPC. Estrogen receptor-beta (ERβ) binds the testosterone-metabolites 3β-androstanediol and 3α-androstanediol in parallel to the canonical estradiol. In the prostate it is widely accepted that ERβ regulates estrogen signalling, mediating anti-proliferative effects. We used the prostate cancer cell lines LNCaP, PC-3, VCaP, and the non-neoplastic BPH-1. VCaP cells were treated with 1 nmol/L testosterone over 20 passages, yielding the cell line VCaPrev, sensitive to hormone therapies. In contrast, LNCaP cells were grown for more than 100 passages yielding a high passage therapy resistant cell line ( Prostate cancer (PCa) is the most prevalent cancer among men in Europe. Its incidence has increased continuously over the past decades , 2. In sAKR1C1, AKR1C2, or AKR1C3 are upregulated in CRPC. AKR1C1 and AKR1C2 convert 5a-DHT to 3α-androstanediol (3α-adiol) and 3β-androstanediol (3β-adiol), whereas AKRC1C3 converts Δ4-androstenedione to testosterone (In addition to such compounds that prevent androgen synthesis (i.e. abiraterone) or androgen receptor antagonists  , derivatosterone  9, 11]., 11.AKR1Both testosterone-derivatives (3α-adiol and 3β-adiol) have significant affinity for estrogen receptor alpha (ERa) and beta (ERβ) , 13. ERaTMPSSR-ERG, IGF1, and PSA, [et al. (2014) demonstrated an association between ARV7 and resistance to both enzalutamide and abiraterone in CRPC [Another driver of CRPC is the overexpression of the androgen receptor (AR). Overexpression of AR compensates for reduced androgen levels, augmenting continuous tumour growth. This leads to a significant increase in AR-mediated gene transcription, including upregulation of and PSA, , 10. Furand PSA, –19. Anto [et al. 14 demonsThe abilities to overcome such therapy resistance by androgen metabolites such as 3α-adiol and 3β-adiol, in CRPC, have not been considered so far. Recently, we demonstrated the ability of the ER-subtype selective compound 8βVE-2 to reset resistance to hormone therapies . In thisp < 0.0005, Figure p < 0.05) and 10 nmol/L to 1 μmol/L (p < 0.005) 3α-adiol; however, the effect was less prominent as compared with VCaP cells representing established CRPC and VCaP AA cells , . AKR1C1 is slightly downregulated in the presence of its product 3β-adiol but no such effects became obvious for AKR1C2 and 3α-adiol .Since therapy resistance of CRPC is predominantly affected by AR characteristics , we investigated AR expression in these different cell models and compared adiol treatments to androgen stimulation with non-metabolizable androgen R1881. Furthermore, we evaluated estrogen receptors (ERα and ERβ) as potential target for these compounds. PCa cell lines were treated with adiol concentrations of 1 μmol/L, an effective dosis in previous experiments, or 10 nmol/L R1881, which is comparable to physiological androgen concentrations. After treatment, western blotting was performed to investigate the expression of AR, ERα, and ERβ.AA cells showed the highest expression of AR. With increasing androgen deprivation, AR expression increased to levels significantly above those of VCaPrev and VCaP cells. However, treatment with 3α-adiol or 3β-adiol markedly reduced AR expression, whereas R1881 resulted in only a slight increase in AR expression. In addition, 3α-adiol or 3β-adiol also resulted in a considerable reduction in ERα expression. Interestingly, treatment with R1881 resulted in a dramatic increase in ERα. Finally, treatment with 3α-adiol, 3β-adiol, or R1881 markedly increased ERβ expression  testosterone. But also from this low expression level, 3α-adiol or 3β-adiol treatments led to a considerable reduction in AR expression, whereas the androgen R1881 increased AR expression. No such divergent effects from adiols and R1881 were observed on ERα and ERβ expression Figure . VCaP cen Figure .per se represent the T878A gain-of-function mutation and less susceptibility to ADT. To obtain cell models with increased potential for therapy resistance before this background, we established a high-passage LNCaP (hiPLNCaP) and AA-tolerant derivatives (hiPLNCaPAA).LNCaP cells There was also considerable expression of the steroid receptors AR, ERα, and ERβ in LNCaP CRPC cells. In the VCaP model, increasing resistance to androgen deprivation was evident by accumulating AR overexpression Figure ; howeverAA-cells was also reversible by adiol treatments with a slightly better efficacy from 3β-adiol  agonists and antagonists (LHRHa) reduces testosterone production (primarily in the testes) and the number of AR ligands . The effNew AR targeting therapies have been developed for the treatment of patients with VCaP based on evidence emphasizing the importance of AR signalling. Therefore, it is generally accepted that AR signalling is a key driver of CRPC , 24.Novel treatments such as AA, which suppresses ligand synthesis, or enzalutamide, which completely blocks the AR, effectively target the androgen pathway to arrest aberrant signalling, and are therefore most suitable for CRPC treatment –7, 25. HAA, hiPLNCaP, and hiPLNCaPAA cells, whereas the original pre-treatment cell model VCaPrev only showed marginal androgen-stimulated proliferation. Furthermore, it is evident that intratumoural steroidogenesis is crucial in CRPC. In addition, it is known that the androgen biosynthesis enzymes AKR1C1, AKR1C2, and AKR1C3 are upregulated in prostate cancer [These findings are similar to the results in our study. We confirmed that low (nmol/L) concentrations of R1881, testosterone, and 5a-DHT effectively reduce proliferation in LNCaP, VCaP, VCaPe cancer . AKR1C1 e cancer . HoweverAA, hiPLNCaP, and hiPLNCaPAA cells, whereas 3α-adiol or 3β-adiol did not affect BPH-1 and PC-3 cell proliferation. Guerini et al. (2005) demonstrated that 3α-adiol and 3β-adiol reduces tumour cell migration in AR-negative DU145 PCa cells. Inhibition of DU145 cell motility has been associated with the formation of the testosterone/dihydrotestosterone metabolite 3β-adiol, which acts through the activation of ERβ, which is present in these PCa cells [Notably, we did show that 3α-adiol or 3β-adiol leads to a significantly reduced proliferation in LNCaP, VCaPrev, VCaP, VCaPCa cells . In the In addition, it has been shown that 3α-adiol and 3β-adiol, two metabolites that do not bind the AR, have a higher affinity for estrogen receptors , 28, 29.et al. (2002), in which inhibition of growth in the developing ventral prostate was achieved with 3β-adiol [We further demonstrated that the decrease in proliferation after treatment with 3β-adiol or 3α-adiol could be explained by a significant increase in tumour cell cycle arrest. This decrease is in agreement with results from Weihua 3β-adiol .hiPLNCaPAA cells  supplemented only with 2% sodium pyruvate and 10% fetal bovine serum, steroid-free according to the manufacturer´s data sheet . To establish an androgen dependent variant VCaP cells were treated with 1 nmol/L testosterone  over 20 passages yielding the androgen-sensitive cell line (VCAPrev) and for the generation of a therapy resistant cell line (VCaPAA) VCaP cells were treated with 5 μmol/L AA  over 20 passages [hiPLNCaP) [hiPLNCaPAA). Cells were incubated at 37°C and 5% CO2 in a humidified incubator. Cells and supernatants were harvested for protein extraction or used for ELISA or FACS assays.We used the human prostate cancer cell lines VCaP , and LNCaP, BPH-1 and PC-3 from local certified stocks as previously described , 34. Bripassages . To demoiPLNCaP) , and wasTumour cell proliferation was evaluated by BrdU-ELISA. Cells were treated with 0.1, 1, or 10 nmol/L testosterone ; 0.1, 1, 5, or 10 nmol/L DHT  and R1881 ; and 0.01, 0.1, 1, 5, 10, 100, 250, or 1000 nmol/L 3α-adiol and 3β-adiol  for 48 h.Tumour cells were treated with 1 μmol/L 3α-adiol, 1 μmol/L 3β-adiol, 10 nmol/L R1881T, 10 nmol/L testosterone, or 10 nmol/L DHT. Total protein lysates were prepared using RIPA buffer with protease inhibitors . Concentrations were quantified by Bio-Rad DC Protein Assays . Primary antibodies are listed in Table g for 5 min and washed with PBS; 200 μL of ice-cold 70% ethanol was then added. Subsequently, cells were incubated for 3 h at −20°C and 200 μL of Muse™ Cell Cycle Reagent were added. Finally, tumour cells were incubated for 30 min at room temperature in the dark. Muse Cell Cycle Software Module was used for automatic calculations.Cell cycle was evaluated after treatment with 1 μmol/L 3α-adiol, 1 μmol/L 3β-adiol, or 10 nmol/L R1881 for 48 h, using the Muse™ Cell Cycle assay as described by the manufacturer. Treated tumour cells (200 μL) were centrifuged at 300 × P values were evaluated with GraphPad Prism software version 5.0 using an unpaired non-parametric t test and a 95% confidence interval .The mean ± SD and


Microfluidic channels enable the control of cell positioning and the capturing of cells for high-throughput screening and other cellular applications. In this paper, a simple microfluidic platform is proposed for capturing small volumes of cells using sidewall microgrooves. The cell docking patterns in the channels containing sidewall microgroove are also studied. Both numerical and experimental investigations are performed within channels containing sidewall microgrooves of three different widths . It is observed that channels containing sidewall microgrooves play an important role in regulating cell positioning and patterning. The obtained results revealed that 10 to 14 cells were positioned inside the sidewall channels of 200 μm width, two to five cells were positioned within the channels of 100 μm width, and one to two individual cells were docked within the sidewall channel of 50 μm width. Particle modelling shows the prediction of cell positioning within sidewall microgrooves. The positions of cells docked within microgroove-containing channels were also quantified. Furthermore, the shear stress variation and cell positioning in the sidewall microgrooves were correlated. Therefore, these sidewall microgroove-containing channels could be potentially useful for regulating cell positioning and patterning on two-dimensional surfaces, three-dimensional microenvironments and high-throughput screening. Cell patterning and positioning are of great importance in many biological applications, such as drug screening and cell-based biosensing. Mcrofluidic platforms hold great promise for biochemical synthesis, high-throughput drug screening, and cell-based biological assay –5. Micro6103813In this paper, a microfluidic device containing sidewall microgrooves that enables the trapping and positioning of cells in a controlled manner is developed. Furthermore, cell positioning in sidewall microgrooves is analysed. The effect of the cell docking and positioning on the sidewall microgroove-containing channels is also investigated. Computational simulations provided estimates of particle tracing patterns, which were accurate proxies for cell positioning. Computational modelling is compared to the experimental results of cell docking within the sidewall microgrooved channels. The particle trajectory was also predicted in sidewall microgrooves containing square microgeometry. Both numerical and experimental results are presented to demonstrate that the proposed microfluidic device containing sidewall grooves in the microchannel could be a potentially useful tool for studying the docking and positioning of small numbers of cells, down to one to two individual cells.Microfluidic devices with sidewall microgrooves were fabricated using the photolithography technique that has been previously developed –24 Figu. The sil6 cells/mL. After 20 min cell seeding, the medium was infused using a syringe pump at a flow rate of 5 μL/min. The medium was pumped to the inlet port of the microfluidic device  containing 10 % fetal bovine serum  and 1 % penicillin/streptomycin . To seed the cells into the microfluidic sidewall channel, the cells were trypsinized and dissociated with culture medium. A counting chamber, also known as a hemocytometer, was used to obtain the cell density. The cells were seeded in a microfluidic device through a cell inlet port at the cell density of 6×10Cell images were obtained using an inverted microscope . To analyse cell docking within sidewall microgrooves in the microchannel, we obtained cell numbers and their location through image analysis. The average cell size in the microgrooves was quantified by ImageJ software. The size of the loaded 3T3 fibroblast cells was on average 10 μm. The experiments were performed with different microgroove sizes three times in a microfluidic device. Statistical analysis was performed using the student t-test.Computational fluid dynamics (CFD) was used to simulate the fluid flow behaviour in the sidewall microgroove-containing channels using the finite element method . There exists ample literature on CFD, finite volume, finite element methods –27 and f28To estimate the cell penetration into the sidewall microgrooves, we performed a numerical simulation of our experimental setup. In our modelling, the unstructured mesh generation method was used for constructing the 3D mesh domain. Our fluid modelling is based on incompressible Navier-Stokes equations , 37 withContinuity equation:Momentum equation:3), μ dynamic viscosity of fluid (Pa Sec), and t time (sec). The properties of fluid (medium) in our modelling are considered to be the same as those of water; which implies the density of 1000 (kg/m3) and dynamic viscosity of 0.001 (Pa Sec).where −6.For our numerical modelling, the boundary conditions at the walls and at the bottom of the microgrooves is set as no-slip boundary conditions. The specified velocity condition is applied for the inflow boundary condition (Dirichlet boundary condition). Moreover, the specified pressure is used for the outflow boundary condition (Dirichlet boundary condition). The outlet static pressure of 0 (Pa) is applied for our case. Furthermore, the criteria for convergence  are considered to be equal to 10A PDMS-based microfluidic device with sidewall microgrooves was developed to regulate and control cell positioning and docking . This mip: 125, 250, 375 μm), channel width , microgroove length , and microgroove depth . The geometrical parameters involved are shown in g which is equal to the microgroove length Lg in our studies. Moreover, two dimensionless ratios were defined Wc*=Wc/Wg, and Rp*=Rp/ Wg. As a result, the number of geometrical factors involved was reduced to two dimensionless ratios. The obtained values of Rp* corresponding to the microfabricated microfluidic devices are 0.625, 1.25 and 1.875, respectively. We experimentally and theoretically evaluated the effect of these different parameters for cell docking and positioning within sidewall microgroove-containing channels.Sidewall microgrooves were fabricated in the channels to analyse cell docking behaviour without any of the gravity effect which is usually generated within bottom-micro-grooved channels –16. It ig.Cell docking and positioning were analysed within a microfluidic channel containing sidewall microgrooves  . The disCell docking results demonstrated that the number of cells docking within larger sidewall microgrooves (200 μm in width) is much higher than that of cells docking within smaller sidewall microgrooves (50 μm in width). Significant differences between the number of cells docked in the microfluidic device with 500 μm and 1500 μm channel widths were not observed. This could be related to the small size of the sidewall groove relative to the width of the channel itself. Not much difference in cell docking among the sidewall microgrooves of upstream, centre and downstream was observed. This can be explained by the fact that the post is located far away from the sidewall microgrooves. If the distance between a post and sidewall microgroove was short, the number of cells docking at the centre of the sidewall grooves might be higher compared to the upstream and downstream of the sidewall microgrooves. To confirm this hypothesis, fluidic flow and shear stress profiles were simulated. The obtained results for simulation are discussed in the theoretical modelling section. Generally, it was observed that cells were positioned and located at the centre of the sidewall microgrooves. Therefore, the obtained result for the sidewall microgrooves should prove useful for co-culturing different cell types.To support our experimental data, cell docking and positioning were analysed using histograms. One of the distinct features of our microfluidic device relates to the incorporation of the microposts. These posts are aligned in the middle of the microchannels as shown in maxmax=0.375. This range of the Reynolds number is within the limit of laminar flow, or more precisely creeping flow, Re<1. Hence, the obtained experimental flow regime is in agreement with the presented numerical modelling and consistent with the assumptions made for analytical solution.A variety of numerical experiments for sidewall microgrooves were investigated. As mentioned earlier, to consider all the fabricated microfluidic devices, different geometry and channel sizes were simulated. Hence, three different microgroove sizes were considered. The series started from 200×200, continued to the size of 100×100, and concluded with the size of 50×50. The three-dimensional modelling of the sidewall microgrooves is considered since in our case studies the depth (perpendicular to the screen) to height ratio of the microgrooves was not above one. Therefore, it will not be justified to use two-dimensional modelling for the prediction of flow pattern and streamlines in our solution domains. In the modelling, the maximum Reynolds number was ReThe shear stress variation inside the groove is shown in p* , which correspond to the microfabricated microfluidic devices. For each case study, the microchannel width Wc* was chosen as between 1.25 to 5 to cover all the corresponding microfabricated geometries. The results obtained for the upper region of the microgroove (a-a section) are shown in To study the effect of varying the channel width on the shear stress variation inside the microgroove, the micropost radius was kept constant and the width of the channel was changed. Simulations were run for the representative values of RThe shear stress magnitude decreases by increasing the channel width, and this is applicable for all three microfabricated channel widths. As expected, as the microchannel becomes wider, the velocity and shear stress values decrease when all the parameters are constant. Furthermore, the obtained numerical results correlate with the effect of micropost size in the shear stress distribution and cell positioning. Therefore, microposts can play a role as a geometrical control over the cell positioning in the sidewall microgrooves.To further understand the effect of variation of the width of microgroove on cell penetration, a set of numerical simulations was performed for three different geometry setups with a microchannel width of Wc . Cell penetration defined by Z is shown in In this study, we developed a unique and simple microfluidic platform for capturing a small volume of cells using sidewall microgroove-containing channels and microposts. It was demonstrated that the micropost size has an effect on the shear stress distribution inside the microgrooves. It was also observed that microgroove size plays a key role in cell capturing and cell positioning. In addition, the numerical modelling for predicting cell positioning inside the microgroove is presented. The effect of channel width variation on cell penetration is also investigated. Furthermore, the histograms of cell locations in the microgrooves were provided, and the most probable destination of the cells was shown. Sidewall microgroove-containing channels provide a platform for cell positioning and a shear-protected area for cell study, and are easily observable by a microscope. Hence, this simple yet adaptable microfluidic device should be useful for high-throughput screening, cell-based biological assay and cell-based biosensing, and also allow for high-density microscopic analysis with simplified image processing.p*  and microchannel width Wc*  which were different to those of the experimental microfluidic devices were chosen. The shear stress distributions for these test cases are shown in supplemental p*=0.625, 1.25 and 1.875 within the sidewall microgroove is presented in supplemental c* were varied from 1.25 to 4.3. It was observed that by keeping the micropost radius constant and increasing the microgroove width, the cell penetration is deepened. The obtained graphs reveal similar behaviour, as presented in To expand our numerical simulations, a variety of numerical experiments for sidewall microgrooves with dimensions other than those shown in


Phosphatase and tensin homolog (PTEN) is one of the most frequently inactivated tumor suppressors in breast cancer. While PTEN itself is not considered a druggable target, PTEN synthetic-sick or synthetic-lethal (PTEN-SSL) genes are potential drug targets in PTEN-deficient breast cancers. Therefore, with the aim of identifying potential targets for precision breast cancer therapy, we sought to discover PTEN-SSL genes present in a broad spectrum of breast cancers.To discover broad-spectrum PTEN-SSL genes in breast cancer, we used a multi-step approach that started with (1) a genome-wide short interfering RNA (siRNA) screen of ~ 21,000 genes in a pair of isogenic human mammary epithelial cell lines, followed by (2) a short hairpin RNA (shRNA) screen of ~ 1200 genes focused on hits from the first screen in a panel of 11 breast cancer cell lines; we then determined reproducibility of hits by (3) identification of overlaps between our results and reanalyzed data from 3 independent gene-essentiality screens, and finally, for selected candidate PTEN-SSL genes we (4) confirmed PTEN-SSL activity using either drug sensitivity experiments in a panel of 19 cell lines or mutual exclusivity analysis of publicly available pan-cancer somatic mutation data.PIK3CB, ADAMTS20, AP1M2, HMMR, STK11, and NUAK1). PIK3CB was previously identified as PTEN-SSL, while the other five genes represent novel PTEN-SSL candidates. Confirmation studies (step 4) provided additional evidence that NUAK1 and STK11 have PTEN-SSL patterns of activity. Consistent with PTEN-SSL status, inhibition of the NUAK1 protein kinase by the small molecule drug HTH-01-015 selectively impaired viability in multiple PTEN-deficient breast cancer cell lines, while mutations affecting STK11 and PTEN were largely mutually exclusive across large pan-cancer data sets.The screens (steps 1 and 2) and the reproducibility analysis (step 3) identified six candidate broad-spectrum PTEN-SSL genes  contains supplementary material, which is available to authorized users. PTEN mutations that result in loss of PTEN function confer an increased risk of developing benign and malignant tumors of the breast, thyroid, and endometrium here A = number of cases altered in both genes; B = number of cases altered in G1 but not G2; C = number of cases altered in G2 but not G1; and D = number of cases altered in neither genes (sic)”  provisional breast invasive carcinoma cohort , 32) andtim from ). We uset test and this was computed using GraphPad Prism version 7. For the secondary screen and the reanalysis in step 3, we used the one-sided Wilcoxon rank-sum test (R function wilcox.test) for comparing ATARiS scores between two groups of cell lines (PTEN+ and PTEN-). We used this non-parametric test because the ATARiS scores in our secondary screen and the sensitivity measures in step 3 had non-normal distributions  and were compared in the same way. The alternative hypothesis was that the median of the PTEN- cell line ATARiS scores is lower than that of PTEN+ cell line scores.Data with assumed equal variance were analyzed by the To identify PTEN-SSL genes in breast cancer, we first carried out a primary small interfering RNA (siRNA) screen in a pair of isogenic cell lines  controls   Fig. . Importaens Fig. . Therefones Fig. . A totalz score cutoff for primary hit selection to capture “true positive” PTEN-SSL genes, which would otherwise be excluded by a more stringent cutoff. This is because PTEN synthetic sick genes, by definition, will result in subtle but meaningful reductions in cell viability when silenced by RNAi reagents. However, since off-target gene silencing is well-known to be a considerable source of error in RNAi screens, we expected the 1537 primary hits to include a large number of “false positives” attributable to off-target siRNA effects. Furthermore, because most synthetic sickness and synthetic lethal relationships exist only in certain genetic backgrounds or under specific cellular conditions [We used a non-stringent nditions , anotherp value <0.05 (uncorrected for multiple testing) in the Wilcoxon rank-sum test was used as a non-stringent hit-selection criterion and we identified 24 secondary hits showing evidence of broad-spectrum PTEN-SSL activity across cell lines , a known PTEN-SSL gene [PIK3CB would not have scored as a hit if a more stringent statistical cutoff taking into account multiple testing were used. Thus, other novel, true positive PTEN-SSL genes could potentially be missed if a stringent criterion had been used at this step. As presented next, we subsequently assessed reproducibility of the 24 hits in independent screening datasets and followed this by drug sensitivity experiments using small molecule inhibitors of gene function and by analyses of mutual exclusivity of mutations in tumors.As in the primary screen, we used a non-stringent hit criterion with the aim of identifying a reasonably small set of possible broad-spectrum PTEN-SSL genes that would contain a subset of true PTEN-SSL genes. These few true broad-spectrum PTEN-SSL genes would have to be confirmed by subsequent experiments and analyses. Non-stringent statistical criteria have been similarly used for hit selection in synthetic lethal screens in part because of the relatively low validation rate of such screens –39. We uSSL gene , as one To date, several high-throughput RNAi screens have been carried out to systematically identify genetic dependencies in large collections of cancer cell lines , 41–45. z scores), increasingly negative scores indicate greater inhibition of cell growth in all cases. We determined the PTEN status of 75 breast cancer cell lines based on previously published reverse-phase protein array data [p < 0.0001; / Additional file p < 0.05 (without correcting for multiple testing) as a non-stringent criterion for selecting hits. This identified 1151, 658, and 50 possible broad-spectrum PTEN-SSL genes from the three studies, respectively , (adaptor related protein complex 1 mu 2 subunit (AP1M2), hyaluronan mediated motility receptor (HMMR), NUAK family kinase 1 (NUAK1), and serine/threonine kinase 11 (STK11). These overlaps in possible broad-spectrum PTEN-SSL genes were statistically significant (p < 0.05 as determined using the hypergeometric distribution)  Fig. . The ideNUAK1, also known as AMPK-related protein kinase 5 (ARK5), and STK11, also known as liver kinase B1 (LKB1), are functionally related, suggesting that their PTEN-SSL activity may stem from a common mechanism. NUAK1 can be inhibited by commercially available small molecules, and we assessed if two of them, HTH-01-015 and WZ4003 [50 values . By contrast, the PTEN- cell lines were not significantly more sensitive to WZ4003. This difference may be due to differing specificity of the two inhibitors: WZ4003 inhibits both NUAK1 and NUAK2 while the activity of HTH-01-015 is more specific to NUAK1 [Two of the broad-spectrum PTEN-SSL genes identified in our screen and shown to be reproducible in reanalysis of data from other studies, d WZ4003 , could rto NUAK1 .Fig. 5NUAs a second test of whether PTEN expression determines sensitivity to NUAK1 inhibition by HTH-01-015, we assessed its effects in the MCF-10A and MDA-MB-231 PTEN+/PTEN- isogenic cell lines. In both cases, the PTEN- cell lines were more sensitive to HTH-01-015 than their PTEN+ counterparts Fig. . TherefoPTEN and each of the six broad-spectrum PTEN-SSL genes . We first examined mutation data in the TCGA breast cancer cohort [PTEN and candidate PTEN-SSL genes was statistically significant  were assayed in this targeted study. We detected significant PTEN SSL effects for STK11 as indicated by mutual exclusivity of PTEN and STK11 , which regulates epithelial cell proliferation through its role in protein sorting [NUAK1 and STK11 encode protein kinases, which are functionally related in the AMP-activated protein kinase (AMPK) pathway. STK11  is a well-characterized tumor suppressor that phosphorylates and activates NUAK1 and 12 other members of the AMPK family [STK11 and NUAK1. We confirmed by small-molecule inhibition by HTH-01-015 that NUAK1 constitutes a novel PTEN-SSL vulnerability across a broad-spectrum of breast cancer cell lines. We also showed that, consistent with PTEN-SSL activity, PTEN and STK11 had mutually exclusive patterns of mutations in the MSK-IMPACT pan-cancer study. This study focused on the mutual exclusivity of somatic loss-of-function mutations. However, the functions of candidate PTEN-SSL genes could also potentially be dysregulated in cancer through epigenetic, transcriptional, translational, or post-translational mechanisms. Thus, mutual exclusivity analyses could be performed on such mechanisms if the relevant data became available.We then reanalyzed data from three published RNAi screens carried out in multiple breast cancer cell lines. Through this reanalysis, we identified six genes with reproducible and broad-spectrum PTEN-SSL activities. Among these, SL genes . ADAMTS2arcinoma . HMMR, acarriers , 54, enccarriers , 56. AP1 sorting . FinallyK family . We furtSTK11 or PTEN loss, respectively, induces G1/S arrest [PTEN-deleted cells have defective DNA double-strand break repair mechanisms [PTEN, STK11, and NUAK1 have interconnected functions in regulating cell cycle progression and DNA damage repair. Inactivation of either STK11 or PTEN individually accelerates progression through the G1/S checkpoint , 60. ConS arrest –63. InteS arrest –66. NUAKS arrest , 67, 68.S arrest . NUAK1 oS arrest . In addiS arrest , 71. In S arrest , and PTEchanisms .Therefore, we hypothesize that STK11 and NUAK1 are selectively essential for cell cycle progression and DNA damage repair in PTEN-deficient cancers Fig. . PTEN-deNUAK1 and STK11 individually in both PTEN+ and PTEN- cell lines using technologies such as CRISPR-Cas9. This would facilitate the study, in detail, of how these PTEN-SSL genes interact with PTEN in regulating cell cycle progression and DNA damage repair. Further chemical screens could also be carried out to identify drugs that would synergize with HTH-01-015 to selectively kill PTEN-deficient cancer cells.The hypothesized mechanism for PTEN-NUAK1 synthetic sickness/lethality is more direct. Since NUAK1 activation by AKT is involved in driving cell cycle progression caused by loss of PTEN, loss of NUAK1 function would directly reduce cell cycle progression. Consistent with this hypothesis, HTH-01-015 inhibition of NUAK1 in a PTEN-deficient osteosarcoma cell line has been shown to block the G1/S transition . In addiPIK3CB, ADAMTS20, AP1M2, HMMR, STK11, and NUAK1. Two of these, STK11 and NUAK1, function in the AMPK pathway, and we hypothesize that their SSL relationship with PTEN stems partly from shared elements of this pathway. In addition, inhibition of NUAK1 with the small-molecule HTH-01-015 was PTEN-SSL in a wide range of cell lines, confirming the broad-spectrum PTEN-SSL activity of NUAK1. Our findings support the introduction of therapies targeting NUAK1, including inhibitors such as HTH-01-015, for treatment of PTEN-deficient breast cancers.An RNAi-based functional genomics strategy followed by validation through reanalysis of independent RNAi screens identified six genes with PTEN-SSL activity in a wide range of cell lines: Additional file 1:Table S1. Growth media for breast cancer cell lines used in study. Table S2. PTEN protein abundance in cell lines quantified by western blot. Table S3. Classification of breast cancer cell lines as PTEN+ or PTEN- based on PTEN protein abundance. Table S4. Primary screen results and hits. Table S5. Details of shRNA library used in secondary screen. Table S6. shRNA barcode counts from secondary screen in 11 cell lines. Table S7. Fold-change in shRNA barcode count for 11 cell lines. Table S8. shRNAs used in ATARiS gene solutions, with ATARiS consistency scores per shRNA. Table S9. ATARiS gene level scores for 11 cell lines. Table S10. Secondary screen results and hits. Table S11. Screen results (zGARP scores) from Breast Functional Genomics Dataset. Table S12. Screen results (DEMETER scores) from Cancer Dependency Map Dataset. Table S13. Screen results (z scores) from Kinase Dependency Profiles Dataset. (XLSX 22688 kb)Additional file 2:Figure S1. PTEN protein abundance of breast cancer cell lines. (A) Western blots showing PTEN and actin (loading control) abundance in 19 breast cancer cell lines. (B) Scatter plot of RPPA-measured PTEN abundance reported by Marcotte et al. [versus PTEN abundance that we quantified through densitometric analysis of western blot bands in (A). Cell lines were categorized as PTEN-expressing (in black) or PTEN-deficient (in red) based on PTEN protein abundance. (PNG 201 kb)e et al.  versus PAdditional file 3:Figure S2. Mutual exclusivity analysis in TCGA breast invasive carcinoma cohort. OncoPrints showing deep (homozygous) deletions, fusions, small insertions and deletions, and non-silent single-base-substitution mutations detected by TCGA. Mutual exclusivity of mutations was determined using odds ratios and the Fisher exact test. Only tumors with mutations are shown. (PNG 125 kb)


Regulated intramembrane proteolysis of the amyloid precursor protein (APP) and its homologs, the APP like proteins APLP1 and APLP2, is typically a two-step process, which is initiated by ectodomain-shedding of the substrates by α- or β-secretases. Growing evidence, however, indicates that the cleavage process for APLP1 is different than for APP. Here, we describe that full-length APLP1, but not APP or APLP2, is uniquely cleaved by γ-secretase without previous ectodomain shedding. The new fragment, termed sAPLP1γ, was exclusively associated with APLP1, not APP, APLP2. We provide an exact molecular analysis showing that sAPLP1γ was uniquely generated by γ-secretase from full-length APLP1. Mass spectrometry analysis showed that the sAPLP1γ fragment and the longest Aβ-like peptide share the C-terminus. This novel mechanism of γ-secretase action is consistent with an ϵ-cut based upon the nature of the reaction in APP. We further demonstrate that the APLP1 transmembrane sequence is the critical determinant for γ-shedding and release of full-length APLP1. Moreover, the APLP1 TMS is sufficient to convert larger type-I membrane proteins like APP into direct γ-secretase substrates. Taken together, the direct cleavage of APLP1 is a novel feature of the γ-secretase prompting a re-thinking of γ-secretase activity modulation as a therapeutic strategy for Alzheimer disease. APP and APLPs have roles in neuronal differentiation, synaptogenesis, neurite outgrowth, and synaptic plasticity12. These proteins are expressed in different tissues and cell types. They bind to components of the extracellular matrix14, help mediate cell–cell interactions, and form homo- and heterotypic protein interactions in a modular mode17.APLP1 (amyloid precursor-like protein 1) is part of an evolutionarily conserved family of type-I transmembrane proteins including the amyloid precursor protein (APP) and APLP2 (amyloid precursor-like protein 2) which are homologous in function19, and its subcellular localization and oligomerization properties are different from those of APP and APLP215. APP and APLPs are substrates for neuronal adhesion with a purely zinc-dependent adhesive function for APLP120. As a neuronal adhesion receptor, APLP1 supports maintenance of dendritic spines and basal synaptic transmission while APP and APLP2 exhibit a basal adhesive activity. Zinc induces formation of neuronal contacts, primarily mediated by APLP1 high-order oligomers21. Silencing of APLP2 revealed a function in neurogenesis in an APP/APLP1 double knockout mouse background implying that APLP2 has a distinct role in priming cortical progenitors for neuronal differentiation22.APLP1 is an atypical member of the APP family. APLP1 expression is neuron-specific23. APP processing by BACE1 appears to be tightly regulated by BACE1 expression. In contrast, APLP1 and 2 are less tightly regulated and depend less on BACE1 expression24. The production of intracellular domains (ICDs) for all three family members is not reduced with decreased BACE1 activity24, a finding that has yet to be explained. Subsequent γ-cleavage of membrane-bound stubs of APLP1 (i.e. products of α- or β-cuts) generate Aβ-like peptides with 25, 27 and 28 residues . APL1β28 has been suggested to be a surrogate marker for Aβ1–42 production in the brain25. Peptides APL1β25, 27 and 28 were detected in human CSF and found to be decreased in Down syndrome (DS) patients compared to controls without any correlation to age or sex26. Since APL1β28 was found to be increased in CSF of AD patients25, this may indicate altered γ-secretase cleavage activity in AD pathogenesis.Shedding of APP and APLPs by α- or β-secretases (BACE1) results in the generation of membrane-bound C-terminal fragments (CTF) and soluble ectodomains that were recently detected as APP heteromers in human CSF27. Shedding of APP and APLPs by the α- and β-secretases results in the generation of membrane-bound CTFs. CTFs are further processed into ICDs which are postulated to be involved in transcriptional regulation30. Clustering of APP and APLPs impair their normal processing by secretases leading to reduced levels of soluble APPs and APLPs16. Zinc enriches APP family members at sites of cell-cell contacts and revealed a zinc-dependent role of APP/APLPs as neuronal cell adhesion proteins21.The enzymes involved in APLP1 ectodomain processing are less well defined24, APLP1-derived ICD (AL1ICD) production, and cellular localization of APLP1 indicated a slightly different cleavage process and a specific cytosolic role of AL1ICD in the regulation of transcription in comparison to its APP and APLP2 counterparts31. However, the sequence of AL1ICD is not well defined since the ICD γ-secretase cleavage site is rather based on alignments and on indirect analysis by Western blot than on an exact molecular analysis32.Furthermore, the release of full-length APLP1Here, we describe that APLP1, but not APP or APLP2, is cleaved by γ-secretase without previous ectodomain shedding. The new fragment, termed sAPLP1γ, was exclusively associated with APLP1 in the absence and presence of α-/β-secretase inhibitors, but not with APP or APLP2 or when γ-secretase activity was inhibited. The sAPLP1γ fragment was uniquely generated by γ-secretase from full-length APLP1, mainly in a competing reaction with BACE1 and detected as a released form of APLP1-overexpressing cells (HEK293T and SH-SY5Y) but also wild-type SH-SY5Y cells. Our sequence analysis showed that sAPLP1γ and the APL1β28 peptide share the same C-terminus. Mutational analyses revealed that the critical and decisive factor for γ-shedding and release of full-length APLP1 from the membrane is the APLP1 transmembrane sequence (TMS). The APLP1 TMS is sufficient to convert the large type-I membrane protein APP into a direct γ-secretase substrate.33, the loss of BACE1 processing of APLP1 has no detrimental effect on the de novo production of AL1ICD31. In the present study, we wanted to elucidate whether there is a γ-secretase-mediated cleavage of APLP1 without previous α- or β-processing. If true, this would ensure a certain cellular level of AL1ICD generated from APLP1 in a single-stage process.While BACE1 has a key role in the regulation of APLP1 maturation, trafficking, and secretion34, we analyzed soluble fragments in the conditioned media of HEK293T cells transiently overexpressing either APP, APLP1 or APLP2 with and without the respective secretase inhibitor  secretion while the γ-secretase inhibitor L-685,458 had no effect on either sAPP form , but fails to distinguish between sAPLP2α and sAPLP2β  recognizes both forms, sAPLP1α and sAPLP1β  cells. To detect APLP1 in the conditioned medium of wild-type (i.e. non-transfected) SH-SY5Y cells, sAPLP1 was immunoprecipitated with the APLP1 ectodomain-specific polyclonal antibody αAPLP1ecto and subsequently detected using 42464 (for sAPLP1α/β), αA1β1-28 (for sAPLP1γ), or 907892 (for flAPLP1) Fig. . WesternTo differentiate between soluble sAPLPγ and full-length APLP1 in the lysate and medium of APLP1 transfected HEK293T cells we performed Western blot analyses with the antibodies 42464 and αA1β1-28 that recognize both forms. The band corresponding to sAPLPγ migrates between the strongly glycosylated mature and the core-glycosylated immature full-length APLP1 and slightly higher than the shorter fragments sAPLP1α/β that do not bear the epitope sequence of αA1β1-28 , and the peptidic inhibitors GSI I and III. All four γ-secretase inhibitors prevented sAPLP1γ release in a similar manner, whereas sAPLP1α/β levels were found enhanced in the medium compared to the control and α- and β-secretase inhibitor treatments , DAPT -L-alanyl]-S-phenylglycine t-butyl ester; dipeptidic type;nts Fig. . Additionts Fig. , which i_ i.e., analyzing increased activities of ADAM10, the main α-secretase39, or BACE1 in APLP1-overexpressing cells. The results reveal that overexpression of BACE1 converts flAPLP1(m) into sAPLP1β with no residual amounts of sAPLP1γ detectable, while ADAM10 overexpression leads to significantly attenuated levels of flAPLP1(m) and detection of residual amounts of sAPLP1γ  and from wild-type SH-SY5Y cells after enrichment of sAPLP1γ by immunoprecipitation. Thus, sAPLP1γ is uniquely generated by γ-secretase from full-length APLP1, mainly in a competing reaction between the classical sheddases  and γ-secretase, whereas corresponding fragments of APP or APLP2 were not detected.25. Sequences extending beyond the known α- or β-secretase cleavage site were only identified in sAPLP1γ samples but not in sAPLP1α/β samples ending with amino acid 567 , the E2 domain (ΔE2) or the cytosolic domain (ΔCT)  Fig. .Figure 4Vice versa, the suitability of APP with the APLP1 TMS, termed APP (APLP1 TMS), as a direct substrate of γ-secretase was tested under the assumption that the APLP1 TMS interaction with the enzyme is not influenced by ectodomain or cytosolic residues of APP.All mutant derivatives of APLP1 were secreted into the supernatant and no obvious qualitative alterations were detected in the generation of respective sAPLP1γ forms between the mutants Fig. . As suchWe found that the chimera APP (APLP1 TMS) is directly cleaved by the γ-secretase and the respective mature soluble product sAPP*γ is detected in the supernatant by the polyclonal APLP1 antibody αA1β28 in the absence but not in the presence of the γ-secretase inhibitor Fig. . This deUsing antibodies directed against the APLP1 ectodomain to analyze processing and release of the chimera APLP1 (APP TMS) processing and its release, we found that the APP TMS prohibits a direct cleavage by the γ-secretase Fig. . However33, we show here that the release of full-length forms is solely dependent on the TMS of APLP1, enhanced by surrounding APP sequences  are mostly found inside the cell15.APP and the APP-like proteins  are multidomain transmembrane proteins that exhibit adhesive and signaling activities within the nervous system. The Aβ sequence is unique to APP but, co-expression of APP in individual combinations with APLPs modulates Aβ production40. While we confirm here that BACE1 is a major sheddase for APLP1, the loss of BACE1 processing of APP, APLP1 and APLP2 had no detrimental effect on the de novo production of ICDs24. However, BACE1-initiated APLP1 processing generated sAPLP1β, APL1β, and AL1ICD32. Together, these findings suggest the existence of another, yet unrecognized, major pathway for APLP1 processing and AL1ICD generation. We show here that, in the novel pathway, sAPLP1γ is directly generated by γ-secretase from full-length APLP1 and released into the cell culture supernatant. Thus, our new findings challenge our current understanding of APP and APLP1 processing and the role of APLP1-derived fragments in AD41.All three proteins exist as membrane-bound and secreted forms and possess homo- and heterotypic contact sites in their ectodomainsin vitro model for endogenous APLP1 expression and neuronal function) and in APLP1-overexpressing HEK293T and SH-SY5Y cells. Without finding a similar or equivalent fragment for APP or APLPL2, we are the first to describe this unique feature of APLP1 to our knowledge. Surprisingly, this novel mechanism of endoproteolytic cleavage exerted by γ-secretase is consistent with an ϵ-cleavage event based on the endoproteolytic nature of the reaction, which was originally designated for the liberation of the ICD from CTFs of APP by the γ-secretase42. The ϵ-cleavage occurs between amino acids 48-49 or 49–50 resulting in two AICDs . An alternative additional cleavage site is created when Gly33 is mutated to Gln which produces a shift and generates AICD5244. Historically, the ϵ-cleavage had been assumed to occur in the middle of the APP TMD to generate Aβ42. However, for APP – and likewise for APLP1 and APLP2 – the shedding of the ectodomain by β- or α-secretase is mandatory before the respective CTF becomes a substrate for γ-secretase45. While APLP1 can undergo processing by β- and γ-secretase to form short Aβ-like peptides47 such as APL1β25, APL1β27, and APL1β28, we also now demonstrate direct γ-secretase processing of APLP1.We found sAPLP1γ in wild-type SH-SY5Y cells  construct, the resulting protein was directly cleaved by γ-secretase. While these arguments indicate that the cleavage is γ-secretase specific, gene silencing experiments and/or a transfection of γ-secretase could provide information what proteolytic fragments of APLP1 are important for what biological function and how sAPLP1γ generation is controlled by varying levels of γ-secretase activity.31. The longer sequence of AL1ICD, compared to AICD forms43, might also explain why AL1ICD does not translocate to the nucleus despite binding to Fe6531, and does not have a direct nuclear signaling function like the ICDs of APP and APLP231. Also, our newly proposed mechanism answers the long-standing question as to why AL1ICD levels were found to be slightly higher in extracts of BACE1 KO brains24 - i.e. due to the direct and efficient γ-secretase cleavage of APLP1. AL1ICD levels might be slightly lower in AD brains, since BACE1 protein levels are significantly elevated in AD, the levels and enzymatic activity of BACE1 are increased in prodromal AD/AD brain tissue49 and CSF52. Given these results, varying APLP1/APP:BACE1 ratios could influence the AL1ICD levels as well as interaction partners of the γ-secretase complex53. Moreover, studies have provided strong evidence that the zinc metalloprotease meprin β can be considered an alternative β-secretase54. Meprin β could also influence AL1ICD levels since mutations near the start of the Aβ sequence were also found to alter the efficiency of meprin β cleavage of APP. The protective alanine to threonine mutation at the p2 position of the Aβ sequence identified as the first protective mutation against AD55 inhibits both BACE1 cleavage as well as meprin β cleavage56. Other factors that could determine the pathway of AL1ICD production are clustering mechanisms of APP and APLPs that impair APLP1 processing by secretases leading to reduced levels of soluble APPs and APLPs16. Overall, the endoproteolytic cleavage by γ-secretase, and the subsequent release of sAPLP1γ, represents a new pathway in which BACE1 and γ-secretase compete for the processing of APLP1.As demonstrated in the present study, this finding represents an alternative mechanism for AL1ICD generation in which the α/β-cleavage steps are by-passed. This process excludes the generation of APLP1-derived Aβ-like peptides from membrane-bound stubs and predicts the existence of an AL1ICD that starts with amino acid Ile 596 Fig. , five re57. Thus, based upon the known homo- and hetero-interaction sites in the ectodomain of APLP121, we tested the possibility that specific domains, or in general, a size-reduced ectodomain could qualitatively cause changes in sAPLP1γ generation. Though the exact cleavage site in mBCMA was not mapped57, the small size of the protein provided the only explanation for how mBCMA can be an immediate γ-secretase substrate. As previously postulated by Hemming and co-workers58, their definition of γ-secretase substrates  did not apply in the case of APLP1. In our present study, we found that neither the shortening of the large ectodomain nor the deletion of the small cytoplasmic domain of APLP1 affected the direct cleavage of APLP1. This result left the TMS of APLP1 as the only remaining candidate region possessing the necessary sequence. Consequently, we tested the TMS of APLP1 and used chimeric constructs, APLP1 with the TMS of APP and APP with the APLP1 TMS. We chose APP since it was not found to serve as a direct substrate of γ-secretase and has a TMS of similar length (24 residues vs. 23 in APLP1). Both TMSs are rich in glycine residues and both contain GxxxG motifs, termed as glycine zippers59, which are not found in APLP2. The GxxxG motif is known to mediate helix–helix interactions in the APP TMS in a consecutive arrangement62. In APLP1, a variation of the GxxxG motif is present (G/AxxxG/S) but a possible involvement in helical interactions has not been reported. Our data now show that the APLP1 TMS successfully converts APP into a γ-secretase substrate, while vice versa the TMS of APP in APLP1 prohibits direct cleavage by γ-secretase while α/β-secretase activities are not grossly altered. The 3D molecular views of the APP and APLPs TMSs . Regardless, recognition of the substrate TMS per se and its processing by γ-secretase is dictated by the TMS sequence upstream from the ε-cleavage site66 which in the case of APLP1 is the GAGGGS sequence  targeting the γ-secretase active site modulate the cleavage of full-length APLP1 and what would be the consequences for AD development and such treatment approaches?Finally, the importance of the APLP1 TMS sequence helps explain the previously observed but unaccounted for release of full-length APLP1 from cells that occurs independently from γ-secretase activity.61. The insertion of the N-terminal His6-tag in the APLP1 sequence after the signal peptide (aa1–38) was carried out by PCR based site-directed mutagenesis using partially overlapping primers . APLP1-APP chimeras were created by an inverse PCR technique . The transmembrane sequence of APP695 (aa635–658) was inserted into APLP1 instead of the APLP1 TMS (aa581–603) and vice versa. Primers were designed to cover one half of the inserted TMS and the corresponding adjoining sequence in the vector. The sequences of all PCR or mutagenesis fragments were verified by DNA sequencing (GATC).APP, APLP2 as well as APLP1 WT, APLP1 ΔE1-AcD, ΔE2 and ΔCT cDNA was ligated into custom made vectors pcDNA3-FLAG, pcDNA3-CFP and pcDNA3-YFP as previously described2. The HEK293T growth medium was DMEM (PAA) supplemented with 10% FCS (PAA), 2 mM glutamine and 1 mM sodium pyruvate. SH-SY5Y cells were grown in DMEM/Ham’s F12 (Biochrom) supplemented with 10% FCS (PAA), 2 mM glutamine, 1 mM sodium pyruvate and 1× non-essential amino acids (PAA). Cells were transfected with the indicated plasmids using polyethylenimine or Transfectin transfection reagent (BioRad). The cell culture medium was exchanged 18 hours after transfection. The newly added medium contained the indicated inhibitors and was conditioned for 6 hours. Activity of following secretases was inhibited by specific inhibitors from Calbiochem: α-secretase , β-secretase  and γ-secretase .HEK293T cells and SH-SY5Y cells were grown in an incubator at 37 °C and 5% COAntibodies used in the study together with their source and the epitope recognized. Antibody name, Antibody target, Source, Epitope recognized, Obtained from:αsAPPβ, Human sAPPβ, Rabbit polyclonal, C-terminus of human sAPPβ, IBL, Japan. 4B4, Human sAPPα, Rat polyclonal, C-terminus of human sAPPα, Kuhn et al. 2010; gift from Dr. Lichtenthaler. W0–2, Human Aβ, Mouse monoclonal, Human Aβ residues 4–10, Multhaup lab, EMD Milipore. 4G8, Human Aβ, Mouse monoclonal, Human Aβ residues 17–24, Covance, USA. 27576, Human APP, Rabbit polyclonal, C-terminus of human APP (residues 648–695), Multhaup lab. 42464, Human APLP1, Rabbit polyclonal, Ectodomain of human APLP1 (residues 499–557), Multhaup lab. αAPLP1ecto, Human APLP1, Goat polyclonal, Ectodomain of APLP1 (residues 34–580), R&D Systems, USA, AF3129. αAPL1β1–28, Human APL1β1–28, Rabbit polyclonal, Human APL1β1–28 (residues 568–595), Bachem, USA. 907892, Human APLP1, Rabbit polyclonal, C-terminus of human APLP1, Multhaup lab. 8–1, Human APLP2, Rabbit polyclonal, Ectodomain of human APLP2, Multhaup lab. 907899, Human APL2β, Rabbit polyclonal, Human APL2β, Multhaup lab. 907779, Human APLP2, Rabbit polyclonal, C-terminus of human APLP2, Multhaup lab.C-terminally FLAG tagged proteins in the conditioned medium were immunoprecipitated by adding 2 µl M2-FLAG antibody (Sigma) and 30 µl protein G sepharose  and incubated overnight in a rotating shaker at 4 °C. Soluble APLP1 species in the conditioned medium of untransfected SH-SY5Y cells were specifically enriched by overnight incubation with 5 µl of the polyclonal antibody αAPLP1ecto (R&D Systems) and 30 µl protein G sepharose at 4 °C. After centrifugation sepharose pellets were washed thrice with buffers with decreasing salt concentration and finally resuspended in gel loading buffer. Samples were subjected to SDS-PAGE and transferred to nitrocellulose membranes (Machery & Nagel). Immunodetection was performed using antibodies specific for the respective protein, followed by probing with horseradish peroxidase-coupled anti-mouse , anti-rabbit , anti-rat , or anti-goat IgG antibodies , respectively. Chemiluminescence was detected using ECL reagent. Band intensities were quantified by densitometry with ImageJ.HEK293T cells were transfected with pcDNA3-N-His-APLP1 and treated with either γ-secretase inhibitor L-685,458 or α-secretase inhibitor GM6001 and β-secretase inhibitor IV. The over 6 hours conditioned medium was applied to Ni-NTA columns (Machery & Nagel). Columns were washed with binding buffer containing 50 mM imidazole and bound proteins were eluted with 250 mM imidazole. The APLP1-containing elution fractions identified by dot blot were combined and concentrated with Amicon filter units. The proteins in the concentrated eluates were separated by SDS-PAGE and stained with Coomassie Brilliant Blue. Bands representing sAPLP1γ or sAPLP1α/β were isolated for LC-MS analysis.67). The resulting peptide mixtures were separated by reverse-phase chromatography using a Dionex Ultimate 3000 nanoLC system  on in-house manufactured 25 cm fritless silica microcolumns with an inner diameter of 100 μm packed with ReproSil-Pur C18-AQ 3 μm resin  on a 5–60% acetonitrile gradient (90 min) with 0.1% formic acid at a flow rate of 350 nl/min. Eluting peptides were ionized on-line by electrospray ionization and transferred into an LTQ Orbitrap Velos mass spectrometer  operated in the positive mode to measure full-scan MS spectra (from m/z 300–1700) in the Orbitrap analyzer at resolution R = 60,000 followed by isolation and fragmentation of the twenty most intense ions in the LTQ part by collision-induced dissociation.Proteins were separated by SDS-PAGE under reducing conditions, individual protein bands were excised and peptides were obtained by trypsin in-gel digestion as described previously  for peptide and protein identification was set to 1% for peptides and proteins and the minimum peptide length was set to 7 amino acids. No enzyme specificity was specified, so that all possible peptide fragments were included in the search.MaxQuant software (version 1.3.0.5) was used to process the raw MS files and the search engine Andromeda3D representations of α-helical transmembrane sequences were generated using builder in PyMOL 1.7.4.Data are expressed as means ± Standard Error. All statistical analyses were performed by one-sample t-test vs. untreated control (100%) with Bonferroni correction. Western blots shown are representative of at least two independent experiments.The data that support the findings of this study are available from the corresponding authors on reasonable request.Supplementary Information


We studied the effect of ionizing radiation (IR) on continuous growth of seven hESC lines. Cells were exposed to 0, 0.2, or 1 Gy of X-rays, and the growth rates of cell populations were assessed by measuring areas of the same individual colonies versus time. The population doubling times (DT) of sham-irradiated cells varied from 18.9 to 28.7 hours for different cell lines. All cell lines showed similar reaction to IR, i.e. cell populations dropped within 24–48 hours post IR; after that they recovered and grew with the same rate as the sham-irradiated cells. The relative cell survival (RCS), i.e. the ratio of normalized cell population in the irradiated samples to that of the sham-irradiated ones varied from 0.6 to 0.8 after 0.2 Gy, and from 0.1 to 0.2 after 1 Gy IR for different cell lines. We found that the RCS values of hESC lines correlated directly with their DT, i.e. the faster cells grow the more radiosensitive they are. We also found that DT and RCS values of individual colonies varied significantly within all hESC lines. We believe that the method developed herein can be useful for assessing other cytotoxic insults on cultures of hESC. Human embryonic stem cells (hESC) are unique models for studying genotoxic stresses including those produced by ionizing radiation (IR) because of their virtually unlimited proliferation potential1During the past decade considerable knowledge was gained regarding the effects of IR on hESC6710111314A distinct feature of hESC is that in culture they propagate in tightly associated colonies171920The hallmark of IR exposure of cells in culture is the loss of their ability to proliferate, which happens within several cell divisions upon the exposure. Therefore, the classical assay to measure the effect of IR on cells in culture is the clonogenic survival assay that measures proportion of the cells that retain the ability to proliferate (to form new colonies) after the exposureAnother technique to assess the cytotoxicity is to measure the growth rate of cells in cultureHerein, we propose to measure growth curves of hESC to assess the effects of IR on their proliferation by continuously measuring the areas of their colonies. Previously we applied this method to assess the effect of radioiodine treatment on hESCIt was documented that IR exposure results in fast apoptosis of hESC67112 incubator. The area of the colonies was measured immediately before irradiation (0 hours time point) and again upon 24 hour intervals up to 96 hours. We defined relative growth (RG) as the ratio of the area of the colonies at various time points to that at 0 hours. The resulting growth curves are shown in 26Seven lines of hESC were seeded in 6-well plates, and after 24 hours were irradiated with 0 Gy (sham irradiation), 0.2 Gy, or 1.0 Gy of X-rays as described in the methods section. Exposure to doses of IR higher than 1 Gy resulted in significant cell death, while doses lower than 0.2 Gy resulted in a negligible effect on cell growth. Immediately after exposure to IR the cells were placed in the COThe cell colonies exposed to 0.2 Gy of IR show only a slight delay in their growth . The colFor characterization of the reduction in cell populations and the delay in proliferation of hESC after IR exposure we use a relative cell survival (RCS) index defined as the ratio of the relative growth of the colonies of the IR exposed cells to that of the sham-irradiated cells at different times post-irradiation.These RCS values at different time points for different cell lines after exposure to 0.2 Gy and 1.0 Gy IR are shown in 2 = 0.87 and R2 = 0.76 respectively. In other words we found that the slower the growth rate of a hESC line the more cells survive IR exposures.To test if there is an association between RCS and growth rate of hESC lines we plotted RCS values averaged over all time points (except 0 hours) versus doubling times . The resThe above results describe average values for at least 20 colonies. We also noticed a significant variability in the growth rate between individual colonies of hESC lines, and decided to further investigate this phenomenon. All studied hESC lines show significant variation in growth rate between individual colonies. Whiskers plots shown in Using an increase in the colony area as a surrogate measurement for cell proliferation, we assessed the effect of IR on seven lines of hESC. We confirmed the dose-dependent increase in apoptosis immediately after exposure of hESC to IR. However, we cannot exclude that other pathways of cellular death are involved as this has been observed in the pastAfter an initial drop in the cell population all cell lines show recovery of their growth after 24 to 48 hours. We use RCS, i.e. the ratio of RG of irradiated cells to RG of sham-irradiated cells as a measure of their radiosensitivity. We found that RCS varied between different hESC lines. The RCS of the most sensitive H7 cell line was ca. 1.5 times lower than that of the least sensitive WA24 cells. Interestingly, we found strong direct correlation between RCS and cell population DT meaning that faster growing hESC are more prone to cell death than slower growing cell lines after exposure to IR. One possible explanation of this phenomenon could be that the faster growing cell lines have a higher percentage of cells in S phase. It was shownRemarkably, we found a significant difference in DT and RCS between individual colonies of the same cell line that is comparable or even larger than the difference in these parameters between different hESC lines. We could not establish a clear correlation between RCS and the size of the colony. We believe that DT and RCS could be characteristic features of individual colonies that are set during initial colony establishment from single cells. In hESC colonies cells are tightly packed and interconnected30Cultures of hESC have become popular models in toxicology studies. They are also widely used in studies regarding the roles and functions of important genes in embryonic development. The method presented herein is simple, sensitive, and can be easily automated. It also assesses cultures of hESC in the most physiologically relative format, i.e. growing in colonies. We believe that our approach will be useful in studies on the effects of various treatments and changes in gene expression on the proliferation of hESC.TM qualified surfaces plated in serum-free defined mTeSR1 media  at 37 °C and 5% CO2. The characteristics of the hESC cell lines used in this study are summarized in 2 at the conditions described above.Human Embryonic Stem cell lines: WA01 (H1), WA07 (H7), WA09 (H9), WA13 (H13), WA19, WA22, and WA24  were maintained in feeder-independent cell culture environments for human embryonic stem cells on BD Matrigel hESC-qualified Matrix  coated BD Falcon2 incubator after imaging. The area of the colonies was measured with AxioVision Software (Carl Zeiss) by manually outlining the borders of a colony.Areas of colonies were measured at the indicated time points starting from the 0 time point taken right before the IR as described in ref. We previously validated the use of colony area as a surrogate marker by direct measurement of cell density within coloniesy = y0 • eαx where α is the growth rate, and then DT was calculated using formula DT = 1/(α • log2(e)).At least 20 individual colonies were measured for each time point. Average, mean, standard deviation, and Student’s t-Test p values were calculated using Microsoft Excel. We defined relative growth values (RG) as ratios of the area of the colonies at various time points to their areas before exposure IR. Thus measured RG values were fitted by equation For detection of Caspase-3/7 activity hESC were grown for 2 days on tissue culture treated glass slides , and were exposed to 0, 0.2, or 1 Gy using Precision X-Ray X-Rad 320 irradiator. After irradiation cells were incubated for 3 hours in a cell culture incubator and then labelled with CellEvent™ caspase-3/7 green detection reagent  at a final concentration of 5 μM in the culture medium. Cell were incubated for 30 min at 37 °C in the dark. Stained cells were observed with the Zeiss Axiovert 200 fluorescence microscopeHow to cite this article: Panyutin, I. V. et al. Effect of ionizing radiation on the proliferation of human embryonic stem cells. Sci. Rep.7, 43995; doi: 10.1038/srep43995 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


BRD4, EZH2 and TOP2A were determined in paired formalin-fixed paraffin-embedded (FFPE) neurofibroma/MPNST samples derived from the same NF1 patient and in a set of plexiform neurofibromas, atypical neurofibromas and MPNST. We further examined the effect on cell viability of genetic or pharmacological inhibition of BRD4, EZH2 and TOP2A in an MPNST cell line panel. Our results indicated that in MPNST samples BRD4 mRNA levels were not upregulated and that MPNST cell lines were relatively insensitive to the bromodomain inhibitor JQ1. We corroborated that EZH2 mRNA expression is increased in MPNST but failed to confirm its reported pivotal role in MPNST pathogenesis as EZH2 knockdown by siRNA did not interfere with cellular proliferation and viability. Finally, the relation between TOP2A levels and sensitivity for doxorubicin was examined, confirming reports that TOP2A mRNA levels were overexpressed in MPNST and showing that MPNST cell lines exhibited relatively high TOP2A protein levels and sensitivity to doxorubicin. We tentatively conclude that the potential for effective therapeutic intervention in MPNST by targeting BRD4, EZH2 and TOP2A individually, may be limited. Clinical studies are necessary to ultimately prove the relevance of BRD4 and EZH2 inhibition as novel therapeutic strategies for MPNST.Malignant peripheral nerve sheath tumors (MPNST) are rare, highly aggressive sarcomas that can occur spontaneously or from pre-existing plexiform neurofibromas in neurofibromatosis type1 (NF1) patients. MPNSTs have high local recurrence rates, metastasize easily, are generally resistant to therapeutic intervention and frequently fatal for the patient. Novel targeted therapeutic strategies are urgently needed. Standard treatment for patients presenting with advanced disease is doxorubicin based chemotherapy which inhibits the actions of the enzyme topoisomerase IIα (TOP2A). Recent molecular studies using murine models and cell lines identified the bromodomain containing protein 4 (BRD4) and enhancer of zeste homolog 2 (EZH2) as novel targets for MPNST treatment. We investigated the expression and potential use of BRD4, EZH2 and TOP2A as therapeutic targets in human NF1-derived MPNSTs. The transcript levels of  The NF1 gene encodes a tumor suppressor called neurofibromin 1, which through its GTPase-activating protein (GAP) domain negatively regulates Ras signaling keeping cell proliferation in check. Inherited or sporadic mutations of NF1 and the partial inactivation of neurofibromin, lead to an increased risk of developing various tumors. Almost all NF1 patients develop cutaneous neurofibromas and in many patients plexiform neurofibromas cause additional morbidity. All tumors exhibit biallelic inactivation of the NF1 gene and consequently activated signaling through the Ras pathway driving cancer formation [TOP2A was among the most upregulated genes in MPNSTs when compared to benign neurofibromas [Neurofibromatosis type 1 (NF1) is an autosomal dominant disorder which has a ormation . Plexifoormation . MPNSTs ormation , 7. Of tormation . Transcrfibromas , 10. Howet al. reported the upregulation of Brd4 mRNA and protein levels in a newly developed murine MPNST model [Nf1-/-,P53-/- skin-derived precursor cells into nerves of athymic nude mice [in vitro growth and in vivo tumorigenesis [EZH2 knockdown using si/shRNA or EZH2 inhibition by 3-deazaneplanocin A causing cell cycle arrest and apoptosis in MPNST cells [A better understanding of the pathobiology of MPNST may lead to the identification of novel treatment targets. Recently, Patel ST model , 12 baseude mice . Furtherigenesis . It was igenesis . In addiigenesis . EZH2 isigenesis  and is figenesis . EZH2 inST cells , 18. EviST cells , 18. BotST cells , 20 thatTo further investigate the potential role as treatment targets of the above-mentioned proteins, we investigated the expression level of the target genes in FFPE and fresh frozen sample sets of plexiform neurofibromas and MPNSTs as well as neurofibroma and MPNST cell lines in order to validate the obtained results from the previous studies.From the Erasmus MC patient files, nine neurofibroma type 1 patients were selected of which resected plexiform neurofibroma material was present and who developed MPNST. Archival formalin-fixed paraffin-embedded (FFPE) tumor samples of both plexiform neurofibroma and MPNST from the same patient (paired samples) were recovered from the Erasmus MC tissue bank. Fresh frozen samples from plexiform neurofibroma (n = 11), atypical neurofibroma (n = 4) and MPNST (n = 7) were also obtained from the Erasmus MC tissue bank. The FFPE and fresh frozen sample sets do not overlap and were derived from distinct patients. All patients and tumor characteristics are listed in In short, for the diagnosis of MPNST we used morphological criteria . Immunostaining for S100 was used for identification of a Schwann cell component in the tumors. Atypical neurofibroma was defined by the presence of mitotic figures, and/or cytological atypia, and/or increased cellularity. The combination of all three features, however, defined low grade MPNST. Plexiform neurofibroma involved multiple nerve fascicles and lacked the above mentioned atypical features. Prior to our research the Daily Board of the Medical Ethics Committee Erasmus MC of Rotterdam, The Netherlands, reviewed the research proposal. As a result of this review, the Committee decided that the rules laid down in the Medical Research Involving Human Subjects Act do not apply to this research (MEC-2016-213).2 atmosphere. All cell lines were regulary monitored for mycoplasma infection and were subjected to authentication by performing a short tandem repeat (STR) DNA analyses and matched, when available, with STR databases. The absence of SUZ12 protein expression in ST88-14 and 90-8TL as reported by de Raedt et al. [Human MPNST cell lines ST88-14, 90-8TL, T265 (NF1-associated MPNST) and STS26T (sporadic MPNST) were kindly provided by Dr. Eduard Serra . sNF96.2 and HS53.T were obtained from the ATCC and derived from an NF1-associated MPNST and a cutaneous, NF1-derived, neurofibroma, respectively. Human embryonic kidney (HEK) 293T cells were a kind gift from the department of Genetics, Erasmus MC, Rotterdam, the Netherlands). All cell lines were cultured in DMEM (Gibco Life Technologies) supplemented with 10% fetal bovine serum, 100 IU/ml penicillin and 100 μg/ml streptomycin at 37°C in a humidified 5% COt et al.  was confTM total nucleic acid isolation kit (Ambion/Life Technologies). RNA quality and quantity were checked using a Nanodrop-1000 (Nanodrop Technologies).Total RNA was isolated from cell line pellets and fresh frozen tissues using RNAbee  according to the manufacturer’s instructions. RNA from FFPE tumor samples (5–6 20 μm sections) was isolated using the RecoverAll® Reverse Transcription Reagents (ThermoFisher Scientific). The mRNA expression levels of target genes and housekeepers were determined by real time PCR using TaqMan® Universal PCR Master Mix and specific Assay-On-Demand products (ThermoFisher Scientific/Applied Biosystems) using an ABI 7500 Real-Time PCR machine. The following assays were used EZH2 (Hs01016789_m1), TOP2A(Hs01032137_m1), BRD4(Hs04188087_m1). Expression of EZH2, TOP2A and BRD4 were normalized using PPIA  (Hs99999904_m1) using the comparative CT method [cDNA was synthesized from 250 ng of total RNA using TaqMan3VO4, 20 mM NaF, 1 mM Pefabloc) supplemented with a cocktail of protease inhibitors. Protein concentration was quantified using a Bradford assay . Equal amounts of total protein (15–20 μg/lane) were subjected to SDS-PAGE and subsequently transferred to a PVDF membrane by electroblotting. Remaining protein binding sites of the membrane were blocked in PBS, 0.05% Tween 20 (PBS/Tween) containing 5% non-fat dried milk. Primary antibody incubations were carried out in the same buffer with the following primary antibodies: mouse monoclonal anti-EZH2 , rabbit monoclonal anti-SUZ12 , rabbit polyclonal anti-BRD4 , rabbit monoclonal anti-TOP2A , rabbit monoclonal anti-NF1 , rat monoclonal anti-tubulin  and mouse monoclonal anti-β-actin . HRP conjugated goat-anti-rabbit, goat-anti-mouse and goat-anti-rat were used as secondary antibodies. Enhanced chemiluminiscence  was used to visualise the signal in a ChemiDoc MP Imager . Protein expression was quantitated using ImageJ, a public domain Java-based image processing program [Total protein was extracted from cells using lysis buffer , and the anthracycline doxorubicin  were determined by a sulforhodamine B (SRB) assay essentially as described by Keepers et al. [50 values were calculated by the use of Deltasoft 3 software.s et al. . In brieEZH2-specific siRNA  or a negative control scrambled siRNA  at a concentration of 50 nM using the DharmaFECT1 transfection reagent (Dharmacon/Thermo Scientific) as recommended by the manufacturer. Twentyfour hours post-transfection the medium was replaced with standard culture medium and cell density as a measure for proliferation was assessed by SRB staining at 24, 48 and 72 hours after transfection.Twentyfour hours prior to transfection the 90-8TL and T265 cell lines were plated in a 24-well plate in duplicate at such a concentration that the next day the wells reach 70–80% confluency. Cells were transfected with either a et al. reported a potential pathogenic role of a BET bromodomain family member (Brd4) in an MPNST mouse model. Inhibition of Brd4, which was found highly upregulated in MPNST, induced increased expression of the pro-apoptotic molecule Bim inducing apoptosis in MPNST cells and tumor shrinkage [BRD4 mRNA expression by qRT-PCR in a series of nine paired human MPNST and plexiform neurofibroma FFPE samples, each pair derived from the same patient (BRD4 mRNA levels in a set of fresh frozen plexiform neurofibromas (n = 7), atypical neurofibromas (n = 4) and MPNST (n = 11)  plexiform neurofibromas and MPNSTs. It must be noted, however, that mRNA levels may not be indicative for protein levels as in most MPNST cell lines BRD4 mRNA levels were similar but BRD4 protein levels varied considerable  . Both in samples . The paiable cf. . To furtable cf. . In an iy to JQ1 . ST88-140 values .EZH2 mRNA levels were significantly increased in the MPNST samples from 6 out of 9 plexiform neurofibroma/MPNST pairs  plexiform neurofibromas  assay. All four NF1-associated MPNST cell line  and one sporadic MPNST cell line (STS26T) were more sensitive to doxorubicin than the neurofibroma Hs53.T cells, many of them displaying IC50 values of less than 50 ng/ml  and MPNST cells derived thereof which display IC50 values of < 400 nM [et al. did use the human S462 MPNST cell line they did not present a dose-response curve from which an IC50 value could be deduced making a direct comparison with our results difficult. Likewise Patel et al. did not validate their findings regarding Brd4 overexpression in clinical tumor samples. Interestingly, de Raedt and colleagues provided evidence that BRD4 inhibition by JQ1 exerted only a modest, cytostatic effect on human MPNST cell lines and that only the combination of JQ1 with PD-901, a MEK-inhibitor, caused a tumor growth inhibition and regression [With respect to BRD4, it has been shown that inhibition of this protein profoundly suppresses MPNST tumorigenesis and tumor cell growth in a murine MPNST model . To confse model , we did igenesis , 29. Mor< 400 nM . Althouggression .et al. demonstrated that EZH2 is overexpressed in MPNST and fulfils a key role in tumorigenesis [EZH2 by si/shRNA or pharmacological inhibition of EZH2 in the S462 (NF1-derived MPNST) and MPNST724 (spontaneous MPNST) cell lines severely affected cellular proliferation rates, induced apoptosis and interfered with tumor formation in an MPNST724 xenograft model. We do confirm that EZH2, at least at the mRNA level, is more abundantly expressed in MPNST than in plexiform neurofibromas. However, when we examined the consequences of EZH2 downregulation on cellular proliferation in 90-8TL and T265 we did not observe any inhibitory effect, despite a significant EZH2 knockdown. It might be that the cell lines used by Zhang et al. respond differently to EZH2 knockdown or inhibition than the NF1-derived MPNST cell lines 90-8TL and T265 that we examined. It may be that knockdown of EZH2 is compensated for by other members of the PRC2 complex and/or the related EZH1. Our findings, however, do suggest that EZH2 functions may be dependent on cellular context. Importantly, it was recently reported that a substantial number of MPNST, irrespective of their origin  exhibit an inactivated PRC2 complex due to somatic loss-of-function mutations in SUZ12 and EED [et al. [3) in the tumor tissue. Only MPNST patients that display an active PRC2 complex may benefit from EZH2 inhibition.Zhang igenesis , 18. Bot and EED , 31. Bot [et al.  can be eTOP2A levels in MPNST were reported to be upregulated due to amplification of the TOP2A gene [TOP2A in MPNST and may explain why doxorubicin is widely used in the treatment of advanced MPNST patients. Though in general outcomes are poor, some patients may derive durable benefit from doxorubicin based treatment [The enzyme TOP2A functions in maintaining DNA topology after replication. The cellular abundance of TOP2A is reported to determine the efficacy of anthracycline based chemotherapy in various cancers –37. The P2A gene , 10. OurFrom this study, we tentatively conclude that the potential for effective therapeutic intervention in MPNST by targeting BRD4, EZH2 and TOP2A individually, is limited. However, this does not preclude the use of inhibitors in certain subpopulations of patients and/or in combination therapies. We strongly encourage other research groups to validate our findings and are in favor of clinical studies involving patients as only these will ultimately prove the true value of BRD4, EZH2 and TOP2A inhibitors in the MPNST setting. Last but not least further investigations are needed into the biology of MPNST to identify additional druggable disease drivers for novel therapeutic strategies.S1 FigA) Overview of neurofibroma and MPNST cell lines. (B) Western blot displaying SUZ12 protein expression in neurofibroma and MPNST cell line panel and HEK293T. ẞ-actin levels are shown as a loading control.((TIF)Click here for additional data file.S2 FigWestern blot displaying NF1 protein expression in neurofibroma and MPNST cell line panel and the non-small cell lung cancer cell lines NCI-H460 and NCI-H1299. Tubulin levels are shown as a loading control.(TIF)Click here for additional data file.S3 FigUncropped blot related to (TIF)Click here for additional data file.S4 FigUncropped blot related to (TIF)Click here for additional data file.S5 FigUncropped blot related to (TIF)Click here for additional data file.S6 FigUncropped blot related to (TIF)Click here for additional data file.S1 TableExcel file containing RT-PCR data related to (XLSX)Click here for additional data file.


Bruton’s tyrosine kinase (BTK) is a key regulator of the B-cell receptor signaling pathway, and aberrant B-cell receptor (BCR) signaling has been implicated in the survival of malignant B-cells. However, responses of the diffuse large B-cell lymphoma (DLBCL) to inhibitors of BTK (BTKi) are infrequent, highlighting the need to identify mechanisms of resistance to BTKi as well as predictive biomarkers. We investigated the response to the selective BTKi, tirabrutinib, in a panel of 64 hematopoietic cell lines. Notably, only six cell lines were found to be sensitive. Although activated B-cell type DLBCL cells were most sensitive amongst all cell types studied, sensitivity to BTKi did not correlate with the presence of activating mutations in the BCR pathway. To improve efficacy of tirabrutinib, we investigated combination strategies with 43 drugs inhibiting 34 targets in six DLBCL cell lines. Based on the results, an activated B-cell-like (ABC)-DLBCL cell line, TMD8, was the most sensitive cell line to those combinations, as well as tirabrutinib monotherapy. Furthermore, tirabrutinib in combination with idelalisib, palbociclib, or trametinib was more effective in TMD8 with acquired resistance to tirabrutinib than in the parental cells. These targeted agents might be usefully combined with tirabrutinib in the treatment of ABC-DLBCL. CD79A/B, and it serves as a receptor to antigens to promote growth, proliferation, and survival of both normal and malignant B-cells. In normal B-cells, following antigen binding, the tyrosine kinases LYN and SYK initiate a signal transduction cascade involving adaptors, kinases, and second messengers, including the Bruton’s tyrosine kinase (BTK). This signaling pathway is subverted in diffuse large B-cell lymphoma (DLBCL) and other B-cell malignancies by mutations of key signaling molecules, including CD79A/B and CARD11.B-cell receptor (BCR) signaling has been implicated in the pathogenesis of some B-cell malignancies. The BCR is associated with BTK, a cytoplasmic tyrosine kinase of the tec protein tyrosine kinase (TEC) family, is an essential component of the BCR signaling pathway and plays an essential role in various biologic functions of different cell types. BTK mutations in humans leads to X-linked agammaglobulinemia (XLA) which is one of the most frequently inherited immunodeficiency diseases and is characterized by an almost complete arrest of B-cell differentiation at the pre-B cell stage. The introduction of the irreversible first-generation BTK inhibitor, ibrutinib, to clinical practice has changed outcomes for patients with chronic lymphocytic leukemia (CLL), mantle cell lymphoma (MCL), and Waldenström macroglobulinemia (WM) ,2,3. It A subset of DLBCL display chronic active BCR signaling, which is not observed in resting B-cells that depend on tonic BCR signaling. This results in the constitutive activation of the NF-κB pathway. They are referred to as activated B-cell like lymphomas (ABC-like lymphomas). Individual knock-down of the different BCR components results in the death of the malignant B-cells. However, the clinical responses to BTKi are less satisfactory . In a phTo improve outcomes with targeted therapies, in particular for R/R DLBCL which has a dismal prognosis, rational mechanism-based approaches to synergistic treatment combinations are key. A deeper understanding of the mechanisms conferring both primary and acquired resistance is required. We identified DLBCL lines sensitive to tirabrutinib and established a model of acquired resistance to tirabrutinib. The effectiveness of tirabrutinib combined with small molecules in six DLBCL cell lines and in acquired resistance to tirabrutinib was evaluated, and this evaluation indicated that the combination of tirabrutinib with idelalisib, palbociclib, or trametinib may be an effective treatment for ABC-DLBCL. CD79B mutant cell line TMD8. However, other DLBCL cell lines containing the CD79B mutation  [CARD11 mutations [CARD11 mutations can block BTKi induced signaling [To assess the susceptibility of B-cell malignancies to tirabrutinib, a panel of 64 hematopoietic cell lines, including 10 GCB-DLBCL and 11 ABC-DLBCL lines, was screened . Six sho® .EC50 was investigated after 72 h of exposure to tirabrutinib at 1 nM to 10,000 nM and an assessment of viability using CellTiterGloAlthough viability was inhibited in all six sensitive cell lines a, TMD8 aThe phosphorylation of BTK was inhibited by tirabrutinib in sensitive and resistant cell lines, irrespective of whether they underwent cell death or not . HoweverA Cys481S mutation of BTK prevents ibrutinib from covalently binding to the BTK mutants. It was found in patients with both CLL and MCL. As such, tirabrutinib is predicted to exhibit reduced binding and potency toward the Cys481S mutation compared to the wild type (WT), although it has not been reported to date in patients with tirabrutinib therapy. This secondary point mutation is a well-known mechanism of acquired drug resistance against kinase inhibitors. Specifically, point mutations of the gatekeeper often diminish the inhibitory activity of kinase inhibitors. However, a gatekeeper BTK mutant, BTK T474A, is sensitive to tirabrutinib  but resiTo confirm that tirabrutinib maintained activity in vivo, murine xenograft experiments were performed . A 0.012δ inhibitor idelalisib, the CDK4/6 inhibitor palbociclib, and the MEK inhibitor trametinib. This that these might be the mechanism of resistance in TMD8 cells .® viability assay or AnnexinV-FITC staining. The calculation of EC50 was done using GraphPadPrism. Tirabrutinib resistant TMD8 (TMD8R) was generated by continuous exposure over nine months at concentrations of tirabrutinib ranging from 3 nM to 1000 nM until stable resistance to tirabrutinib was established. Specifically, the concentration of tirabrutinib was gradually increased from 3, 6, 12, 25, 40, 60, 80, 100, 200, 400, 800, and 1000 nM. Cell passage was performed twice a week. When the growth was fine, cells were re-suspended with fresh media containing the same concentration of tirabrutinib . Sensitivity of cells to tirabrutinib was tested by CellTiterGlo® at every step of passage. The mutational status of TMD8R was determined by Sanger sequencing. The combination index was calculated using CalcuSyn based on the multiple drug-effect equation of Chou-Talalay.The cell lines used in this study have been previously described and were obtained either from the originators or from Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (DSMZ). The identity of cell lines were confirmed by both metaphase cytogenetics and short tandem repeat assessment. Cell lines were grown in RPMI 1640 supplemented with 10% fetal calf serum. Sensitivity to tirabrutinib in cell lines as well as combination treatments was performed using a CellTiterGloTreated or untreated cells were lysed in Radio-Immunoprecipitation assay (RIPA) buffer containing a protease inhibitor cocktail. Western blotting was performed using antibodies from Cell Signaling for BTK, ERK, and STAT3 and Novus Biologicals for phospho-BTK.7 cells in Matrigel, subcutaneously. Randomization and treatment were initiated when the mean tumor volumes reached 400 mm3 for TMD8 and 200 mm3 for tirabrutinib resistant cells. Groups of mice were then dosed via diet containing tirabrutinib at concentrations of 0.0037%, 0.012% and 0.037%. The daily dosage was found to be comparable to the doses, 6, 20, and 60 mg/kg/day, respectively. Tumor growth was assessed using a caliper.To assess in vivo efficacy of tirabrutinib, severe combined immunodeficiency (SCID) mice were injected with 1 × 10We investigated the response to tirabrutinib in a panel of 64 hematopoietic cell lines. Although ABC-DLBCL cells were most sensitive amongst all cell types studied, the sensitivity did not correlate with BCR pathway mutations. We investigated combination strategies with 43 drugs in DLBCL. Tirabrutinib combined with idelalisib, palbociclib, or trametinib was more effective in ABC-DLBCL with acquired resistance to tirabrutinib than in the parental cells. Taken together, our data indicates that these targeted agents might be usefully combined with tirabrutinib in the treatment of ABC-DLBCL.