It is becoming more and more apparent that they are highly active, diverse, and involved in a large variety of processes. The essential role of lysosomes is exemplified by the detrimental consequences of their malfunction, which can result in lysosomal storage disorders, neurodegenerative diseases, and cancer. Using lysosome enrichment and mass spectrometry, we investigated the lysosomal proteomes of HEK293, HeLa, HuH-7, SH-SY5Y, MEF, and NIH3T3 cells. We provide evidence on a large scale for cell type–specific differences of lysosomes, showing that levels of distinct lysosomal proteins are highly variable within one cell type, while expression of others is highly conserved across several cell lines. Using differentially stable isotope-labeled cells and bimodal distribution analysis, we furthermore identify a high confidence population of lysosomal proteins for each cell line. Multi–cell line correlation of these data reveals potential novel lysosomal proteins, and we confirm lysosomal localization for six candidates. All data are available   •Analysis of lysosome-enriched fractions/whole cell lysates from six cell lines.•High dynamic range of lysosomal proteome.•SILAC labeled background cells enable identification of enriched proteins.•Definition of high confidence potential novel lysosomal proteins.•Validation of six lysosomal candidate proteins by immunostaining. We present a comprehensive analysis of lysosome-enriched fractions from six commonly used mammalian cell lines. We show that lysosomal proteins are highly dynamic with respect to their expression and/or localization at lysosomes and provide a novel strategy for the identification of specifically enriched proteins. Based on the correlation of data from all cell lines, we identify high confidence novel lysosomal proteins and confirm six selected candidates. Lysosomes, the central lytic organelles of the cell, are responsible for the degradation of a large variety of cellular compounds and the recycling of their building blocks, fulfilling a pivotal function for cellular homeostasis. Organelles and macromolecules, which are delivered to lysosomes through endosomes, phagosomes, and different forms of autophagy, are hydrolyzed by ∼60 enzymes residing in the lysosomal lumen . Defectse.g., for the exchange of metabolites (mTORC1), whose members and functions have been investigated in a variety of studies , theiewed in . The mosiewed in , 12.e.g., in their pH value or their mobility . Given In order to be able to assess such differences on a global scale, and to identify novel lysosomal proteins, unbiased large-scale approaches play a pivotal role. The method that is currently used most frequently is mass spectrometry–based proteomics, as it allows to simultaneously identify and quantify large numbers of proteins in a given sample. A variety of studies have been performed, which investigated lysosomes and lysosomal proteins in HEK293 , 19, 20,in vitro cultivated cells  have been identified  , which ied cells , making entified , which mWhile it is common practice to assess the likelihood of localization to a specific organelle in differential centrifugation approaches by comparison with other fractions , 31, to In the current study, we investigated the lysosomal proteome of six widely used cell lines using lysosome enrichment by SPIONs and mass spectrometry–based proteomics . For thr13C615N2 lysine , and 87.8 mg/ml light or 13C615N4 arginine  at 37 °C, 100% humidity, and 5% CO2. Each cell line was passaged at least six times to ensure complete SILAC labeling.HEK293 , HeLa , HuH-7 , SH-SY5Y , MEF , and NIH3T3  cells were cultured in SILAC Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% dialyzed fetal calf serum (FCS), 100 IU/ml penicillin, 100 μg/ml streptomycin, 181.2 mg/ml light or 6 cells were seeded per 10-cm plate and cultured in DMEM with 2.5% FCS for 72 h. Subsequently, the medium was changed to DMEM with 10% FCS including 10% of SPIONs solution  for either light or heavy SILAC labeled cells (two replicates each), followed by incubation for 24 h. For HEK293 cells, plates were coated with 100 μg/ml poly-L-lysine . For HEK293 and SH-SY5Y cells, 6 × 106 cells were seeded directly in DMEM with 10% FCS and 10% SPIONs followed by incubation for 24 h. Subsequently, for all cell lines, cells were washed twice with 1× PBS, fresh medium was added, and the cells were incubated for 36 h. Cells were washed three times with ice-cold 1× PBS, scraped in 2 ml isolation buffer  was transferred to a new tube. The pellet was resuspended in 2 ml isolation buffer, the procedure was repeated, and the PNS fractions were combined. The pooled PNS fractions of the individual cell lines were passed by gravity flow through LS columns  placed in a MidiMACS Separator , and washed with 5 ml isolation buffer. Lysosomes were eluted from the columns twice with 1 ml isolation buffer each using a plunger. Lysosomal integrity and isolation efficiency were assessed using the β-hexosaminidase assay with/without the addition of 0.8% Triton X-100   . To calcFor each sample, 100 μg of protein was precipitated by ice-cold chloroform/methanol  as described . Protein18 particles  for data-dependent acquisition (DDA) or data-independent acquisition (DIA) analyses, respectively. Peptides were resuspended in 5% ACN/5% FA and loaded on the analytical column at a flow rate of 600 nl/min, 100% solvent A (0.1% FA in water). Peptide separation was performed at a flow rate of 300 nl/min with a 240-min linear gradient (DDA) or a 120-min gradient (DIA) from 5 to 35% solvent B (95% ACN/0.1% FA). Survey spectra were acquired in the Orbitrap mass analyzer with a mass range of m/z 375 to 1575 at a resolution of 60,000. For DDA analyses, tandem mass spectrometry (MS/MS) fragmentation was performed for charge states between 2 and 4 by higher-energy collisional dissociation (HCD) with 30% collision energy and data were acquired in the Orbitrap at a resolution of 30,000. The cycle time was set to 5 s and the precursor isolation width to 1.6 m/z using the quadrupole. For mass spectrometry (MS) and MS/MS scans, the automatic gain control was set to 4 × 105 and 5 × 105, respectively. For DIA analyses, survey spectra were acquired in the Orbitrap mass analyzer with a mass range of m/z 350 to 1200 at a resolution of 120,000 and a maximum injection time of 50 ms. MS/MS was performed by isolation of m/z 24.1 windows using the quadrupole and higher-energy collisional dissociation fragmentation with 30% collision energy. Data were acquired in the Orbitrap at a resolution of 30,000, with a maximum injection time of 54 ms, and a fixed mass range of m/z 200 to 2000. The cycle time was set to 3 s, and the automatic gain control was set to 5 × 105 and 1 × 106 for MS and MS/MS spectra, respectively.Mass spectrometry analyses were performed using a Dionex Ultimate 3000 system coupled to an Orbitrap Fusion Lumos mass spectrometer (both Thermo Scientific). Columns were manufactured in-house as follows: 50-cm spray tips were generated from 360 μm outer diameter/100 μm inner diameter fused silica capillaries using a P-2000 laser puller (Sutter Instruments) and packed with 1.9 μm or 3 μm Reprosil AQ Cwww.matrixscience.com). For database searching, UniProt (Swiss-Prot + TrEMBL) Homo sapiens  and UniProt Mus musculus  in combination with the cRAP database (ftp://ftp.thegpm.org/fasta/cRAP/crap.fasta) including common contaminants were used. The following parameters were defined: variable modifications: oxidation of methionine, acetylation of protein N termini; fixed modification: propionamide at cysteine; mass tolerance: 10 ppm for precursor ions, 50 mmu for fragment ions; enzyme: trypsin except proline was the next amino acid; missed cleavage sites: two. Data were filtered with a false discovery rate (FDR) of 1% at the peptide level using Percolator  and M. musculus . The same search parameters as for Proteome Discoverer were applied with the exception of definition of heavy labeled arginine (Arg10) and lysine (Lys8) as fixed modification for cells receiving SPIONs in the heavy SILAC channel. DIA data were analyzed by Spectronaut (version 16.2.220903.53000). DDA and DIA raw files were used to generate hybrid spectral libraries using UniProt (Swiss-Prot) H. sapiens  or UniProt (Swiss-Prot) M. musculus  including common contaminants. For each peptide, the three to six most abundant b/y ions were selected for library generation, depending on their signal intensity. The same fixed/variable modifications were used as in Proteome Discoverer and MaxQuant analyses. Data were filtered with the following q value cutoffs: precursor = 0.01, protein (experiment) = 0.01, protein (run) = 0.05. Dynamic retention time alignment was performed based on the high-precision indexed retention time concept  in combination with Mascot 2.6.1  , Microsohttps://cran.r-project.org/web/packages/BH) with a default significance level . Principal component analysis was performed using the prcomp function of the R package stats, version 3.6.2, setting center = TRUE and scale = TRUE (https://CRAN.R-project.org/package=Hmisc). Heatmaps of abundance ratios and Pearson correlation were created with the heatmap.2 function from the R package gplots, version 3.0.3, and using hierarchical clustering (order = hclust) (http://cran.r-project.org/package=gplots). For UpSet plots, Proteome Discoverer data were joined using the full join function of the R package dplyr, version 0.7.4 . If a protein had been found in a cell line, the value was set to 1. Otherwise, if there was a missing value, the respective cell was set to 0. UpSet plots were generated with the upset function from the R package UpSetR, version 1.4.0, setting order.by = degree  and g:Profiler (https://biit.cs.ut.ee/gprofiler/) . For functional analysis of high confidence potential novel lysosomal proteins, the Gene Group Functional Profiling (g:GOSt) tool available in the g:Profiler web server (version from 2020-03–09) was used. Statistical enrichment analysis with g:GOSt was performed with GO molecular function, GO cellular component, GO biological process, and Reactome .The derived probability describes the likelihood of the observation based on the calculated model. Extreme abundance ratio values (100 and 0.01) were handled separately, as they indicate missing values in one of the distributions and are arbitrarily set by Proteome Discoverer. Therefore, they were replaced with the maximal or minimal abundance ratios observed during data analysis and the posterior probabilities of these values were set to 1 or 0, respectively. For each dataset, the FDR was calculated applying the Benjamini–Hochberg  multiplee = TRUE . Pearson= degree . For proofiler/) , 45. OveSamples for mass spectrometric analysis were generated for each cell line in four independent biological replicates. In order to address potential bias in the analysis of SILAC ratios, label switching was performed for the individual cell lines with two replicates receiving SPIONs in the light and heavy channels, respectively. In subsequent analyses, only proteins were considered with valid values in at least three biological replicates.Rab5-GFP expression vector was a kind gift from Sergio Grinstein.RNA was isolated from MEFs or NIH3T3 cells using the Nucleospin RNA plus kit . Subsequently, cDNA was generated using the RevertAid First Strand Synthesis kit  according to the manufacturer’s instructions utilizing random hexamer primers. Downstream RT-PCR amplification of lysosomal/endosomal genes was carried out with the respective set of primers . PCR proNIH3T3 cells were seeded 24 h prior to transfection, and 4.5 μg of the respective plasmid DNA was transfected using TurboFect transfection reagent . Cells were cultured for 24 h in DMEM with 10% FCS and 100 IU, ml penicillin/100 μg/ml streptomycin . Subsequently, the culture medium was replaced, fresh medium containing 500 μg/ml hygromycin B  was added to the cells, and this step was repeated after 24 h. Before analysis, all transfected cells were cultured for a minimum of 4 weeks in DMEM containing 500 μg/ml hygromycin B.LAMP2  overnight at 4 °C. The next day, all samples were repeatedly washed in 1× PBS with 0.2% saponin and incubated with the secondary antibodies donkey anti-rat Alexa Fluor 488 , donkey anti-rabbit Alexa Fluor 488 , and donkey anti-mouse Alexa Fluor 594  for 1 h at RT. After washing with 1× PBS, 0.2% saponin, coverslips were rinsed twice with H2O, and embedded in Mowiol-DABCO with DAPI  . Transiently transfected cells were analyzed with an inverted confocal laser scanning microscope  in combination with a UPLSAPO 60× oil immersion objective (NA:1.35) at 2× zoom, and stable cells were analyzed with the LSM 980 with Airy scan 2  microscope. All images of transient cells were acquired and processed with the Olympus FluoView Software, whereas images of stable cells were acquired and analyzed with the Zeiss Zen 3.2 Blue edition software.HeLa cells were cultured using cell culture medium as described above. Cells were seeded on glass coverslips 1 day prior to transfection. The transfection was carried out with 750 ng plasmid DNA using TurboFect and cells were cultured for 48 h before they were processed for immunostaining. Both transient (HeLa) and stable (NIH3T3) cells were washed three times with 1× PBS and fixated with either methanol or 4% paraformaldehyde in 1× PBS for 10 or 20 min, respectively. Subsequently, samples were rewashed three times with 1× PBS and incubated for 5 min in 1× PBS with 0.2% saponin, and for 15 min in 1× PBS with 0.02% glycine and 0.2% saponin. All samples were blocked for 1 h in 1× PBS with 0.2% saponin and 10% FCS. After blocking, cells were stained with primary antibodies against HA tag , Myc tag , and g for 10 min at 4 °C, and the supernatant was removed. Cell pellets were resuspended in RIPA lysis buffer , sonicated three times for 15 s with a Sonoplus sonicator  with 0.8 amplitude, and centrifuged at 20,000 g for 10 min at 4 °C. The supernatant was collected and the protein concentration determined using the BCA protein assay . Protein concentrations were adjusted to 2 μg/μl, samples combined with Laemmli buffer , SDHA , Calnexin , GM130 , CTSD , NPC2 , LIMP2 , ATP6V1B2 , ATP6V1D , HGSNAT , GBA , RAPTOR , MAN2B2 , NEDD4 , CSTB , KIF5B , FLOT1 , PPT1 , and β-actin . The next day, blots were washed three times with TBS-T and incubated for 1 h at RT with the respective secondary antibodies .The enrichment of lysosomes from mammalian cells typically results in high numbers of contaminating nonlysosomal proteins . In ordeFig. 1B and Figs. 1C and Fig. 1C), indicates that the percentage of lysosomes receiving SPIONs through unspecific fluid phase endocytosis in these cells is lower in comparison with the other lines.Following this strategy, we performed four biological replicates for each cell line. In order to account for systematic errors related to SILAC labeling and data analysis, we performed label switching, including SPIONs in two replicates of light and heavy labeled cells, respectively. After pooling and disruption of cells, we assessed lysosomal integrity using activity assays for the lysosomal luminal enzyme β-hexosaminidase . As we were especially interested in proteins located at the lysosome, we subsequently extracted a subset of proteins that are assigned to the lysosomal compartment in PANTHER and/or UniProt for mouse or human, irrespective of the fact if they fulfil a crucial function for this organelle .Using an optimized protocol , we analFig. 1rganelle . For theE). When considering only the putative lysosomal proteins, correlation coefficients were in general higher. The exceptions were comparisons of HeLa and NIH3T3/HEK293 cells, yielding the lowest values, indicating stronger quantitative differences between the lysosomal proteomes of these cell lines (C). Based on unsupervised hierarchical clustering, we observed a general clustering for samples that received SPIONs in the light or heavy SILAC channel, respectively (F). Since especially unspecific binding proteins are affected by the SILAC label switch, this observation underlines the strong contribution of background proteins to the individual datasets. Also for putative lysosomal proteins, we observed an effect of the SILAC labeling state of the cell line, but no general clustering occurred depending on which SILAC labeled cell line received SPIONs (D).To investigate the correlation among individual cell lines, we determined the Pearson correlation coefficients for the log2 abundance ratios of the identified proteins. On the whole protein level, NIH3T3 cells showed the lowest correlation with all other cell lines, while SH-SY5Y cells were most similar E. When cll lines C. Based ectively F. Since d SPIONs D.e.g., Western blot, quantitative PCR, or immunostaining approaches have shown highly variable expression levels across tissues, to our knowledge so far no attempts have been made to compare expression levels of lysosomal proteins between cell lines on a global scale. It remains therefore largely elusive in how far lysosomes differ between cell types.Based on the heterogeneity of tissue-specific phenotypes for individual lysosomal storage disorders , it is hA). HEK293 and NIH3T3 cells contributed with 512 and 257 proteins, respectively, the highest and lowest numbers of unique identifications. In all four human cell lines, 326 proteins were identified that were not detected in the two mouse lines, while 235 were unique for the mouse cells.To further assess differences in the lysosomal proteomes of the individual cell lines analyzed, we performed direct comparisons of the identified proteins . Of the Fig. 3versus 25% of total proteins were identified in all six cell lines, Fig. 3B). Furthermore, we detected 130 lysosomal proteins that were unique to human cells , while 42 proteins were unique to mouse cells (17 detected in both cell lines). Overall, while the majority of proteins were reproducibly detected across cell lines, each comparison of the individual proteomes resulted in unique subpopulations. This indicates distinct features of the lysosomes of the respective cells, which are possibly related to their individual functions/characteristics.For the putative lysosomal proteins identified across all datasets , we observed a similar behavior, however, with a markedly increased reproducibility compared with the whole dataset  heterogeneity. Furthermore, every cell requires a certain lysosomal “core proteome” to be able to deal with the turnover of ubiquitous cellular components. We argued that it is therefore highly unlikely that proteins belonging to this class are not expressed at all. It should be more reasonable that the expression levels of individual proteins belonging to this group are adapted to the specific characteristics of an individual cell type, reflecting its unique composition and function .A and S5A), presenting a “core feature” of lysosomes. This is probably also related to the fact that the presence and correct stoichiometry of the V-ATPase are essential for lysosomal function. Subsequently, we filtered for proteins with iBAQ values in at least two cell lines and three biological replicates each, calculated the median of the V-ATPase-normalized value for individual proteins, and grouped them into 32 classes based on their function and/or localization . Lysosomes enriched from HuH-7 and HeLa cells contained the highest amounts , while values in the other cell types were roughly similar. The observed differences were mainly due to the strong overrepresentation of hydrolases in HuH-7 cells, transporters in HeLa cells, and membrane proteins in both of them. Only lysosome-associated ubiquitin ligases and proteins related to mTORC1, which were most abundant in SH-SY5Y and HEK293 cells, respectively, were the highest in abundance in cell lines other than HeLa and HuH-7 (B).Initially, we calculated the sum of V-ATPase-normalized iBAQ values in the individual cell lines to estimate how many lysosomal proteins are present relative to the V-ATPase B. Lysosond HuH-7 B.TCIRG1 and ATP6AP1/ATP6AP2 (A). For proteins involved in the translocation of small molecules across the lysosomal membrane (A), we observed a dynamic range of three orders of magnitude with the cholesterol transporter SCARB2 and the Cl-/H+ exchanger CLCN6 showing the highest and lowest median expression levels, respectively (difference of ∼1400 fold).Subsequently, we investigated the expression levels of individual lysosomal proteins in the different cell lines. For the V-ATPase complex itself, we detected a conserved stoichiometry for proteins belonging to both the V0 and the V1 part with the exception of the associated proteins /ATP6AP2 A. For prmembrane A, we obs2+ channels MCOLN1, TPCN1, and TPCN2, for example, were expressed at very similar levels in all cell lines, while the amino acid- and oligopeptide-transporting members of the solute carrier (SLC) family showed both similar and highly variable expression patterns. SLC3A2 and SLC7A5, which are known to heterodimerize . Overall, amino acid/oligopeptide transporters were expressed especially by HeLa cells at high levels , implying a high importance of amino acids derived from lysosomal protein degradation for their metabolism. This is in line with studies reporting the dependence of cancer cell metabolism on amino acids originating from lysosomal degradation of proteins . The Ragulator members LAMTOR1, LAMTOR2, LAMTOR3, and LAMTOR4 were similarly expressed in all cell lines, while LAMTOR5 was ∼100-fold more abundant in HEK293 compared with SH-SY5Y cells. For all proteins of this group, we observed, in general, high expression levels in HEK293, HeLa, and HuH-7 cells, with the exception of RHEB, which showed for HEK293 cells an inverse behavior compared with SLC38A9. In accordance with the role of FLCN in the mTORC1-dependent phosphorylation and cytosolic retention of the lysosomal transcription factors TFEB and TFE3  or TFEB/TFE3 (only MEFs) in the lysosome-enriched fractions.For other proteins related to patterns B. The Raand TFE3 , 55, we B) and the highest abundances for LAMP1 and LAMP2. Proteins involved in lysosomal positioning (mainly components of the BORC complex (ARL8B and DTNBP1 (C). For lysosome-associated ubiquitin ligases, on the other hand, no trend with respect to certain cell lines was detectable (D). For hydrolases, the dynamic range of expression was in general smaller than for proteins located at/in the lysosomal membrane, while proteins related to lipid metabolism (E) were less variable compared to proteases (F) and those involved in the hydrolysis of glycosidic bonds (C and S5G). For the latter, we observed, for example, a highly conserved abundance across cell lines for GBA, while other proteins, such as NEU1 or MAN2B2, presented with variabilities of up to ∼140-fold. For the majority of hydrolases, HuH-7 cells showed the highest expression levels, indicating a higher throughput of substrates in their lysosomes, which is probably related to the liver’s function as the main recycling organ of the body.For membrane and membrane-associated proteins, we observed a similar dynamic range as for transporters B and the complex ) were prd DTNBP1 C. For lytectable D. For hytabolism E were leroteases F and thoic bonds C and S5GThe observed differences in  protein abundance could originate from differential protein expression, differential association/localization with lysosomes, and/or variabilities in lysosome enrichment efficiency. We, therefore, further investigated lysosomal protein abundance in whole cell lysates from all six cell lines to investigate which of these possibilities are most likely . We utilIn general, we observed a similar range of dynamic protein expression within individual cell lines, spanning >3 orders of magnitude between the lowest and highest expressed lysosomal proteins. When considering variability of expression levels for individual proteins across the six cell lines, we observed less pronounced differences  and S6. A and B). This could be related to signal suppression effects for peptides originating from low abundant lysosomal proteins in highly complex samples  for transporters and exchangers, also proteins that were of higher relative abundance in whole cell lysates . We calculated the log2-transformed ratios of SPIONs/control, median-normalized the values for individual replicates to compensate for differences in lysosome enrichment efficiency, and performed a bimodal distribution analysis. For each cell line, we estimated the mixture of two univariate normal distributions and assigned a posterior probability of lysosomal localization to each protein using an expectation-maximization algorithm , we hypothesized that the frequency of identification of an individual protein in multiple cell lines could be used as an indicator for the likelihood of lysosomal localization. We tested this hypothesis by correlation of the percentage of proteins belonging to a certain GO category with their frequency of identification across the individual datasets of the six cell lines . At the same time, we were able to deplete proteins from the cytoskeleton, nucleus, and mitochondria, while the percentage of cytoplasmic and Golgi apparatus proteins remained stable. For proteins assigned to endosomes, we observed the highest increase (∼3-fold) after such of lysosomal origin, indicating a specific enrichment, probably due to SPIONs, which did not completely transfer to the lysosomal compartment during the chase period. The increase in percentage of lysosomal proteins relative to the whole dataset confirmed that true positive lysosomal proteins are more likely to be reproducibly detected across several cell lines.Despite the increase in abundance for putative lysosomal proteins, their percentage in relation to the whole dataset peaked at only 11% (SH-SY5Y cells). As we detected putative lysosomal proteins more reproducibly across the individual cell lines B, we hypNext, we compared our dataset with results from previously published studies that identified potentially novel lysosomal proteins with other approaches. We considered datasets based on proximity biotinylation with BirA∗ , densityC). Finally, we removed previously reported putative lysosomal proteins from the high confidence lysosomal identifications in our dataset, resulting in a list of potentially novel lysosomal proteins. With respect to the complete list of proteins identified in at least one of the cell lines, only 2% were reproducibly identified in ≥5 cell lines, presenting high confidence potential novel lysosomal proteins , which was shown to maintain protein homeostasis through attenuation of ER stress (SLC12A9 (Solute carrier family 12 member 9), which belongs to the SLC12 family of electroneutral transporters facilitating the symport of Na+/K+ with Cl- (SLC31A1 (High affinity copper uptake protein 1), which belongs to the SLC31 family of copper transporters (TMEM63B (CSC1-like protein 2), an osmosensitive Ca2+ permeable channel (TSPAN3 (Tetraspanin-3), a member of the tetraspanin superfamily, which has been involved in trafficking of membrane proteins (NDFIP2 (NEDD4 family-interacting protein 2), which was reported to be involved in controlling the activity of WW-HECT domain E3 ubiquitin ligases, in particular NEDD4  colocalized with LAMP2, thereby confirming their lysosomal localization. For NDFIP2, however, we only observed a partial colocalization with LAMP2 while colocalization with the early endosomal marker Rab5 was much more pronounced. Subsequently, we further generated stable NIH3T3 cell lines for TM7SF3, NDFIP2, SLC31A1, and SLC12A9 and investigated these by coimmunostaining and Western blotting (LAMP2 (A) with median Manders' coefficients between 0.7 and 0.8 and Pearson's coefficients between 0.6 and 0.8 (B), indicating their predominantly lysosomal localization. Based on these experiments, we were able to show lysosomal localization for all six candidates in cells either transiently or stably overexpressing the respective protein, presenting for four of them a first proof with a method orthogonal to large-scale proteomics studies.For each candidate, we transiently transfected HeLa cells with an expression vector containing an HA- or MYC-tagged version of the respective cDNA and investigated lysosomal localization by coimmunostaining with an antibody directed against the respective tag and the lysosomal marker protein LAMP2 . In thesblotting . For allg . Surprisingly, the V-ATPase-normalized iBAQ levels of both β-hexosaminidase subunits HEXA and HEXB (C) did not match the pattern of enzymatic activity for all cell types, as both proteins were significantly less abundant in MEF than in HeLa and HuH-7, which all showed similar enzymatic activity for whole cell lysates (B). This implies that MEF cells contain a higher number of lysosomes with lower individual HEXA/HEXB levels. This could be the reason that they performed best in terms of lysosome enrichment efficiency, as more lysosomes can receive SPIONs in these cells (C).This study presents a systematic comparison of lysosome-enriched fractions from different cell lines. Already during cell lysis and lysosome enrichment, differences between the individual cell types became apparent, as we observed varying yields of β-hexosaminidase activity and lysosomal intact ratios in the input fraction preceding lysosome enrichment, as well as different recovery rates in the eluate fraction , B and Cand HEXB C did not lysates B. This ise cells C.via Fenton reactions, which would result in increased levels of protein oxidation. Investigation of data published previously by our group , implying that no striking fundamental differences exist in the lysosomal composition between the cell lines. When we investigated protein identification across all cell lines, we detected a highly reproducible core proteome of 2173 proteins, of which 308 have been previously reported to be lysosomal  proteins . Interestingly, this observation was only partially replicated on a whole cell lysate level (A). While both subunits also presented with a high variability in this dataset, they were more abundant than others. This implies that, in comparison with other subunits of the complex, a lower percentage of the total pool of these proteins is located at lysosomes.In order to compensate for variability between samples, we performed a replicate-wise normalization on a set of V-ATPase subunits that were detected in all analyses of lysosome-enriched fractions with ≥10 peptides. Even though it was shown that the cytosolic V1 part of the V-ATPase is able to dissociate from the V0 part integrated in the lysosomal membrane , we did undances A. Interete level A. While BLOC-one-related complex (BORC), which is involved in microtubule-mediated lysosomal transport  and mTORC1 members (B) in the different cell lines. For individual members of Ragulator, it was quite surprising to us to find lysosome-localized LAMTOR5 at highly variable levels (∼100-fold dynamic range), clearly exceeding the dynamic range observed for the other subunits. It was shown that loss of LAMTOR2 induces degradation of the other LAMTOR proteins .For  surface , were prith BORC , 78. Alosubunits C and mTO members B in the proteins . While tCLCN7 and its β-subunit OSTM1, which facilitate Cl- import into lysosomes , indicating probable other roles for GLMP in certain cell types. Intriguingly, also on a whole cell proteome level we observed highly conserved levels of MFSD1 in all cell lines and high variability of GLMP (A and S6B). Finally, for the complex of the lysosomal cobalamin transporter ABCD4 and the lysosomal membrane protein LMBRD1, which was shown to facilitate the transport of ABCD4 from the ER to lysosomes (ABCD4 (5- to 26-fold) throughout all cell lines. This indicates that LMBRD1 may be important for the transport of ABCD4, but not for its stability or function, as a roughly similar abundance would have to be maintained in this case.For complexes consisting of lysosomal transmembrane transporters and their accessory subunits, we found roughly equal stoichiometries in lysosome-enriched fractions, confirming their direct relationship. This was, for example, the case for ysosomes . For theysosomes . For MFSnit GLMP , however of GLMP A and S6Bysosomes , we obseA possible reason for the observed heterogeneity among cell lines could be transcriptional control of lysosomal protein expression. This could be either due to the activity of TFEB and its regulation by different upstream kinases  or the aOverall, the iBAQ data from both lysosome-enriched samples and whole cell lysates should provide a valuable resource to the community. They present an estimate of abundance for lysosomal proteins in different cell types and allow to estimate the lysosome-localized population for individual proteins. This could allow, for example, to investigate lysosomal heterogeneity in response to certain stimuli or upon alteration of transcription factor activity. Also, for the conceptualization of experiments, this should allow to choose appropriate model systems, as overexpression of the same protein may result in one cell line in a 2-fold higher abundance, while it will result in a 200-fold increase in another. This applies especially to certain metabolic pathways in the individual cell lines, as, for example, we observed extremely high relative levels of most lysosomal enzymes in HuH-7 cells, while concentrations of channels, transporters, and exchangers were rather average.e.g., due to proteolytic processing, it does not strongly influence the iBAQ value if high intensity peptides from another region are present or if peptides from this region are not utilized at all. If, however, the epitope that is recognized by a specific antibody is affected, the ability of the antibody to detect the respective protein will be heavily impaired. The same is true for posttranslational modifications, such as glycosylation, which are known to be present at many lysosomal luminal protein domains  and 85% (lysosome-enriched samples) of individual trends matched. The remaining cases, in which we failed to observe a correlation, could be due to several reasons. For the iBAQ analyses, all peptides across the protein sequence are considered. If a certain region of a given protein cannot be covered for a distinct cell line,  domains , 89, or  domains , 91. It A). When combining the data of all six cell lines, almost 4500 proteins were categorized as potentially novel lysosomal, representing >20% of known human/mouse proteins.To facilitate the identification of previously unknown lysosomal proteins from our datasets, we applied a novel strategy based on the inclusion of differentially SILAC-labeled background cells (which did not receive SPIONs) and bimodal distribution analysis of the resulting samples. While we were able to significantly deplete unspecifically binding proteins from our datasets and to define a population that was specific for the presence of SPIONs , we wereFig. 7p-value cutoff, can be identified in the individual bimodal distribution analyses of the cell lines , and also for such that were previously identified to be present in lysosome-enriched fractions  with the dataset identifier PXD020600. MS/MS spectrum identifications from MaxQuant searches were deposited at MS-Viewer (https://msviewer.ucsf.edu/) with the search keys c0vxdeqfnr  and qwtwxcxfbm (combined mouse datasets from MEF and NIH3T3 cells).The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium he PRIDE  partner S-Viewer  and are This article contains The authors declare no competing interests.


SF3B1 mutation can help unravel their contribution in patients’ worse prognosis. The cytotoxic effects and delayed leukemic infiltration induced by H3B-8800 support the potential use of SF3B1 inhibitors as a novel therapy in CLL.Understanding the pathogenic mechanisms of  SF3B1 are observed in 15% of patients with chronic lymphocytic leukemia (CLL) and are associated with poor prognosis, but their pathogenic mechanisms remain poorly understood. Using deep RNA-sequencing data from 298 CLL tumor samples and isogenic SF3B1 WT and K700E-mutated CLL cell lines, we characterize targets and pre-mRNA sequence features associated with the selection of cryptic 3′ splice sites upon SF3B1 mutation, including an event in the MAP3K7 gene relevant for activation of NF-κB signaling. Using the H3B-8800 splicing modulator, we show, for the first time in CLL, cytotoxic effects in vitro in primary CLL samples and in SF3B1-mutated isogenic CLL cell lines, accompanied by major splicing changes and delayed leukemic infiltration in a CLL xenotransplant mouse model. H3B-8800 displayed preferential lethality towards SF3B1-mutated cells and synergism with the BCL2 inhibitor venetoclax, supporting the potential use of SF3B1 inhibitors as a novel therapeutic strategy in CLL.Splicing factor 3B subunit 1 (SF3B1) is involved in pre-mRNA branch site recognition and is the target of antitumor-splicing inhibitors. Mutations in  SF3B1 mutations identified in cancer cells promote the usage of cryptic 3’ss located 10–30 nucleotides upstream of the canonical 3’ss. Each 3’ss has been reported to use its own BP adenosine (SF3B1 mutations have been detected in various cancer types including myelodysplastic syndromes (in 28–65% of the cases)  is a core component of the spliceosome, the cellular machinery in charge of removing introns from precursor mRNAs (pre-mRNA splicing). The spliceosome recognizes specific sequences at the intron boundaries, namely, the 5′ splice site (5’ss) and the 3′ splice site (3’ss), the latter comprising a branch point (BP) adenosine located 18–35 nucleotides (nt) upstream of the conserved AG dinucleotide at 3′ end of the intron and a polypyrimidine tract (Py tract) located between the BP and AG. Alternative usage of splice sites, namely, alternative splicing (AS), importantly contributes to protein diversity . SF3B1 rdenosine . SF3B1 me cases) , chronice cases) , uveal me cases) , and othe cases)  and havee cases) . In CLL,reatment , and a hreatment . SF3B1 mrognosis . Patientrognosis . Even parognosis , emphasiInterestingly, several antitumor drugs targeting SF3B1 have been identified and developed in the last decade . Among tSF3B1 mutations in CLL patients and in an isogenic CLL MEC1 cell line bearing the most frequent SF3B1 cancer mutation (K700E). We also characterize the cytotoxic effect of H3B-8800 both in vitro and in vivo and we explore a novel therapeutic approach combining H3B-8800 with venetoclax, a commonly used drug in CLL treatment.Here, we characterize the changes in alternative splicing induced by SF3B1 mutations in CLL, we developed the first isogenic MEC1 cell lines harboring (or not) the most prevalent SF3B1 mutation in CLL, K700E. MEC1 cells were edited using CRISPR/Cas9 and single-stranded oligodeoxynucleotides (ssODN) harboring two stabilizing phosphorothioate linkages at their 5′ and 3′ ends SF3B1 mut 3′ ends , validat 3′ ends  and digi 3′ ends , confirmmutation . Of releT clones .SF3B1 mutation on splicing in CLL, we first used RNA-seq data from tumor B cells from 298 patients diagnosed with CLL from the International Cancer Genome Consortium (ICGC) (vast-tools (SF3B1 mutation cancer cell fraction (CCF)  formed a different cluster, with the exception of two samples harboring SF3B1 mutations outside of the domain involved in branch point recognition  with high CCF (≥50%), excluding samples with mutations E862K and M757T in SF3B1, in other splicing factors or in other genes related to RNA metabolism . PCA and hierarchical clustering in SF3B1-mutated samples did not reveal global transcriptomic changes associated with specific mutations, although the comparison between 8 SF3B1 K700E samples and 3 SF3B1 H662D mutations did identify 136 differential alternative splicing events , and 162 differentially expressed genes, suggesting specific molecular effects of individual mutations (To investigate the impact of m (ICGC)  and B cest-tools  and the st-tools  Fig 2A)SF3B1 muton (CCF) . Althoug samples . In addi samples . PCA of l status . For furBiological and clinical information of the patients from the International Cancer Genome Consortium with RNA-seq data.Table S1. SF3B1K700E and SF3B1H662D samples from the patients’ cohort (vast-tools).Differentially spliced events between Table S2. SF3B1K700E and SF3B1H662D samples from the patients’ cohort.Differentially expressed genes between Table S3. SF3B1 mutations, additional RNA-seq analyses included RNAs from MEC1 SF3B1K700E heterozygous and WT isogenic cell lines described above. The fraction of differentially spliced events  between SF3B1 WT and SF3B1-mutant samples was enriched in Alt3’ss events both in CLL samples or MEC1 isogenic cell lines compared with the distribution of detected AS events (P < 0.0001)  . Both inormation .SF3B1WT and SF3B1-mutant samples from the patients’ cohort (vast-tools).Differentially spliced events between Table S4. SF3B1WT and SF3B1K700E MEC1 cell lines (vast-tools).Differentially spliced events between Table S5. SF3B1-mutated cases) splicing events, we developed JuncExplorer, a software designed to detect and quantify the usage of annotated and non-annotated splice junctions . Using this tool, events with a single pair of 3’ss choices (compared with events involving 3 or more 3’ss choices) were the most frequently mis-regulated type of Alt3’ss between SF3B1WT and mutated samples, both in patients and in cell lines,  in SF3B1WT samples was >5  or ≤5 (cryptic Alt3’ss), respectively. A change in 3’ss usage |ΔPSI| ≥15 upon SF3B1 mutation was required for classification as either alternative or cryptic Alt3’ss. We defined a total of 595 alternative Alt3’ss events and 268 cryptic Alt3’ss events in cell lines and 38 alternative Alt3’ss and 15 cryptic Alt3’ss in patients’ samples. Although most non-canonical AGs were located upstream and near of the canonical 3’ss   and cryptic  . Activateam Far)  represen0E cells  to analy0E cells . Alterna0E cells  and S4A.achinery . In summSF3B1WT and SF3B1-mutant samples from the patients’ cohort (Juncexplorer).Differentially spliced events between Table S6. SF3B1WT and SF3B1K700E MEC1 cell lines (JuncExplorer).Differentially spliced events between Table S7. SF3B1WT and SF3B1-mutated chronic lymphocytic leukemia samples with a single pair 3’ss plotted in Fig 4A (JuncExplorer).Differentially spliced events between Table S8. SF3B1WT and SF3B1K700E MEC1 cell lines with a single pair 3’ss plotted in Fig 4A (JuncExplorer).Differentially spliced events between Table S9. SF3B1WT and SF3B1K700E cells ordered depending on the Alt3’ss location.Alt3’ss events validated by RT–PCR in RNA samples from MEC1 Table S10. SF3B1 mutation requires the use of alternative branch point sequences. To investigate this question, we carried out mutagenesis analyses using expression plasmids (minigenes) in which the 3’ss region of an Adenovirus Major Late intron was replaced by 3’ss regions of ZNF561 , MAP3K7  or TARBP1 (displaying a NAGNAG event)  led to activation of the non-canonical 3’ss in SF3B1WT cells, whereas mutation of the 3’-most BP (BP1 mutant) prevented activation of the non-canonical 3’ss in SF3B1K700E cells  reduced the use of the non-canonical 3’ss in both cell types, whereas mutation of the 5’-most BP (BP2 mutant) did not significantly alter the choice of 3’ss in either of the two cell lines. Additional mutation of other putative branch sites were included leading to a further decrease in the usage of the alternative AG in both cell types, without affecting canonical AG usage  prevented its increased relative use in SF3B1K700E cells, whereas the 5’-most BP does not seem to have an impact on NAGNAG use ) with a ΔPSI = 50.93 showed also the lowest average PSI (2.87) in SF3B1WT patient samples . This Alt3’ss event was validated by RT-qPCR , the cryptic ZDHHC16 isoform was only detected in mutated samples with CCF >12 (except for cases when SF3B1 was mutated in E862K or M757T) and three samples with CCF < 12  involved in the activation of MAPKK were differentially spliced in SF3B1-mutated patients’ samples (Table S12). Recently, MAP3K7 AS has been postulated to promote NF-κB–driven tumorigenesis (MAP3K7 gene itself displaying strong mis-regulation upon SF3F1 mutation (ΔPSI = 60 in SF3B1WT versus SF3B1K700E CLL patients’ samples and ΔPSI = 70 in SF3B1WT versus SF3B1K700E MEC1 CLL cell lines). This 3’ss is located upstream of the canonical 3’ss of exon 5, which encodes part of the kinase domain, and its usage results in the disruption of the coding sequence and degradation of the corresponding transcript by NMD   . Measureificance .SF3B1-mutated chronic lymphocytic leukemia patient samples and SF3B1K700E MEC1 cell lines.Selected enriched Gene Ontology terms (enrichGO R package) for biological processes in genes displaying differentially spliced events in Table S12. SF3B1K700E and SF3B1WT MEC1 CLL cell lines. Cytotoxicity was measured after incubation of these cell lines with 1–100 nM H3B-8800 for 48 h. H3B-8800 induced cytotoxicity in a dose-dependent manner in both SF3B1WT and SF3B1K700E cell lines, this effect being significantly enhanced in SF3B1K700E cells at doses higher than 25 nM (mean viability at 75 nM was 52.1% ± 12.3% for SF3B1K700E cells and of 71.8% ± 10.8% for SF3B1WT cells) (We first assessed the cytotoxic effect of the splicing modulator H3B-8800 in the isogenic T cells) .SF3B1 mutations in samples with low SF3B1-mutant CCF  and in SF3B1wt CLL cells (81% ± 11.9%)  or human follicular dendritic cell-like (HK) cell lines. We observed that in the presence of HS-5 or HK cells, H3B-8800 induced lethality in both ry cells  and MEC1ry cells  with a pll lines . These dSF3B1K700E and SF3B1WT cell lines. Cells were intravenously inoculated via the tail in NOD–SCID interleukin-2 receptor gamma (IL2Rγ)null (NSG) mice, forming xenografts of isogenic MEC1 cells with SF3B1WT or SF3B1K700E . After 10 d, upon detection of bioluminescence, mice began to be treated orally with vehicle or H3B-8800 (6 mg/Kg) daily for 10 d and luciferase activity was captured at days 3, 6, and 10 by bioluminescence in vivo imaging. We observed lower bioluminescence signal or leukemic infiltration in SF3B1K700E MEC1 cell line compared with SF3B1WT MEC1 cell line and a decrease of this signal after H3B-8800 treatment in both of them (+ B lymphocytes by flow cytometry) were 54% ± 13.9% and 41% ± 17.4% for the SF3B1WT and SF3B1K700E groups treated with vehicle, respectively  for 6 h. RNA was isolated and deep sequenced using Illumina pair-ended sequencing technology and the datasets analyzed using vast-tools software. We observed that H3B-8800 induced extensive intron retention and exon skipping changes in both cell lines, with nearly 8,000 introns detected as more retained and more than 10,000 exons as more skipped upon treatment  with introns that were spliced more efficiently (n = 62) and with introns that did not change (n = 675) upon drug treatment. We observed that (i) retained introns and their flanking exons are shorter than the ones from non-changing introns, (ii) their 5’ss and 3’ss are weaker , and ii. A repreSF3B1-mutated cells to H3B-8800 might be explained by synergistic or antagonistic effects of drug treatment and SF3B1 mutation on particular splicing alterations. Out of 252 events associated with SF3B1 mutation, 56 were reversed by H3B-8800 treatment, whereas 68 were exacerbated (|ΔPSI| > 10)  . For exaSF3B1K700E and H3B-8800–treated SF3B1K700E cells  (SF3B1WT (ΔPSI = −37.6) and SF3B1K700E (ΔPSI = −34) cell lines (SF3B1WT or SF3B1K700E MEC1 cell lines with venetoclax (0–250 nM), a selective inhibitor of the anti-apoptotic protein BCL2, and H3B-8800 (0–75 nM) for 48 h. The results showed synergistic effects between the two drugs in the two cell lines . Altogether, these results demonstrate that the combination of H3B-8800 with venetoclax results in enhanced cytotoxic effect.RNA-seq analysis of H3B-8800–treated MEC1 cell lines identified 26 AS events in genes involved in apoptosis that were differentially spliced (|ΔPSI| ≥ 15) between 0E cells . 23/26 oclature)  which swclature)  and has clature) . H3B-880ll lines . Similarll lines . As BCL2ll lines , we incull lines . These dsoftware  Fig 9F)SF3B1K700SF3B1 is one of the most recurrently mutated genes, present in about 15% of CLL patients. These mutations—typically subclonal and subject to clonal evolution—have been linked to specific biological features of the disease such as unmutated imumoglobulin (Ig) heavy-chain variable region (IGHV) CLL subgroup, the intermediate CLL epigenetic subgroup, stereotyped BCR subset 2, R110-mutated IGLV3-21 subgroup, or 11q deletion  SF3B1 mutation using CRISPR/Cas9-genome editing. Although several SF3B1-mutant isogenic cell lines were previously generated from B-cell precursor leukemia cells, myeloid leukemia cells, murine embryonic stem cells, or induced pluripotent stem cells  and the distance (≥/<50 nt) to the canonical 3’ss. Interestingly, we observed, both in CLL primary cells and CLL cell lines that cryptic 3’ss can be located not only upstream but also downstream of the canonical 3’ss and that the distance between the two 3’ss, both in upstream and downstream cases, can be longer than 50 nucleotides and therefore is not as constrained as previously thought.Because the first reports of n cancer , importan cancer  and—lessn cancer  or closen cancer . Our anaK700E. The effects of mutating predicted branch points in minigene constructs were consistent with the use of different branch points by the alternative 3’ss and the canonical 3’ss, as previously described , aberrant expression of an alternatively spliced isoform of TMEM14C identified patients with good responses  and isogenic SF3B1K700E MEC1 cell lines as compared with WT cells. The cytotoxic effect of H3B-8800 was observed even in the presence of protective stroma. Other splicing inhibitors such as sudemycin D6 or E7107 also display stronger cytotoxic effects on splicing factor–mutant cancer cells, including mutations in SF3B1 and other splicing factors such as U2AF1  are dependent on their WT allele for splicing function and cell survival  splicing modulation . Also, cDifferent SF3B-binding molecules display common and differential effects on splicing regulation . In geneSF3B1 mutation compared with previous reports, (3) provides evidence that the SF3B1 inhibitor H3B-8800 displays therapeutic effects in mouse models of CLL, particularly when used on CLL cells harboring SF3B1 mutations, and (4) provides evidence of synergism between a SF3B1-targeting drug and venetoclax.In summary, the work presented here reports (1) the first generation of isogenic genome–edited CLL cell lines differing only by the presence or absence of a single amino acid substitution in SF3B1, (2) the identification of a wider variety of 3′ splice site activation events upon SF3B1 mutations in PBMCs were analyzed in previous sequencing studies (5 cells/ml in IMDM with GlutaMAX (GIBCO) supplemented with 10% (vol/vol) heat-inactivated FBS and 1% (vol/vol) penicillin–streptomycin 10,000 U/ml (GIBCO) in a humidified atmosphere at 37°C containing 5% carbon dioxide. The follicular dendritic cell line HK, kindly provided by Dr. Yong Sung Choi  (PBMCs from CLL patients (with ≥90% tumor B cells) and healthy donors were isolated, cryopreserved, and stored within the hematopathology collection registered at the Biobank . Clinical and biological data of each patient are detailed in Table S1. Written informed consent was obtained from all patients. The study was approved by the Hospital Clínic of Barcelona Ethics Committee.  studies . MEC1 (Andation) , was culSF3B1K700E MEC1 cell line are shown in Table S14. Annealing of crRNA and Alt-R CRISPR–Cas9 tracrRNA, ATTO 550 (IDT) was carried out at 95°C for 5 min, then the assembly of the crRNA:tracRNA duplex (10 μM) and the Cas9 protein (10 μM) was performed and mixed with ssODN (10 μM) and Alt-R Cas9 Electroporation Enhancer (IDT). MEC1 cell lines were electroporated using the Neon Transfection System (Thermo Fisher Scientific) with a 20 ms pulse at 1,600 V and seeded. Serial dilution in single-cell cultures was performed for 3 wk and then clones were screened using Taqα1 restriction enzyme, recognizing the c.2106G>A from the PAM sequence (6) or QIAamp DNA Mini Kit (>1 × 106) (QIAGEN); 50 ng DNA was used to quantify SF3B1 K700E mutation by digital PCR (Bio-Rad).ssODN complementary to the non-target strand  with twosequence . 30,000 SF3B1K700E MEC1 cell line.Oligonucleotide sequences used for the generation and characterization of Table S14. Cell viability was measured by flow cytometry using Annexin V (FITC) and propidium iodide (Invitrogen). For the MTT assay, 10,000 cells/well were seeded and incubated for 48 h. Then, thiazolyl blue tetrazolium bromide 98% at a concentration of 0.5 mg/ml in PBS was added to the cells and were incubated for 2 h until the presence of violet crystal was observed at the optical microscope (Leica DMI1). The stop solution (isopropanol and HCl 24:1) was added and the cells were carefully resuspended before reading the plates at the TECAN spectrophotometer at wavelengths of 570 and 670 nm.SF3B1WT or SF3B1K700E MEC1 cell lines were treated with 75 nM H3B-8800 or DMSO for 6 h, and RNA extraction was performed using the RNeasy Mini kit (QIAGEN). Stranded mRNA–seq libraries were prepared and two samples/lane were sequenced, following 2 × 125 nt paired-ended protocol at the CRG Genomics Core Facility on a HiSeq 2500 v4 (Illumina Inc). Triplicates were sequenced for each condition in separate lines. All the samples included in the comparison passed the FastQC quality control from MultiQC  (https://github.com/vastgroup/vast-tools). For each event, minimum 10 reads coverage was required.Splicing analyses were carried out using the toolset Vertebrate Alternative Splicing and Transcription Tools   with high CCF (≥50%) were analyzed, excluding samples with mutations E862K and M757T in SF3B1, in other splicing factors or in other RNA metabolism–related genes . We made two comparisons considering the distribution of the patients in PC1 for all the AS events detected (SF3B1-mutated samples versus 136 samples SF3B1WT samples) and the samples with PC1 < 0 (7 SF3B1-mutated samples versus 89 samples SF3B1WT samples). AS events needed to have at least 10 reads in 5 of SF3B1-mutated samples and 20 of the SF3B1WT samples to take them into consideration for the comparison and a |ΔPSI| higher than 15% and range of 5 between SF3B1 mutated and SF3B1WT samples. To detect differentially spliced events between two conditions (SF3B1 mutation or H3B-8800 treatment), we required a |ΔPSI| of at least 15% between the merged replicates under each condition and a minimum range of 5 between the PSI values under the two conditions in MEC1 cell lines.225 detected  because detected . We compJuncExplorer (https://gitlab.com/aghr/juncexplorer). JuncExplorer allows the identification and quantification of annotated and non-annotated (de-novo) splice junctions from RNA-seq reads mapped with a splice-aware mapper, for example, STAR . PSI values are calculated by converting the read numbers into relative frequencies per case for each of its splice sites for each of the 5’ and 3’ss. Alt 3’ss cases were considered when a unique GT donor site (5’) had several AG acceptor sites (3’) within a single intron. To detect differentially spliced events between two conditions (SF3B1 mutation or H3B-8800 treatment), we required a |ΔPSI| of at least 15% and range of 5 between the merged replicates under each condition. Cryptic 3’ss correspond to alternative 3’ss not detected in SF3B1 WT samples and detected in SF3B1-mutated samples. Downstream analysis of AS events was performed using Matt (https://gitlab.com/aghr/matt)   with spehr/matt) , and BP hr/matt) .SF3B1WT cells, Matt software (SF3B1WT control group) upon drug treatment.For the sequence features analysis associated with AS changes induced by the drug in software  was usedsoftware . The rethttps://vastdb.crg.eu/wiki/Downloads) (Prediction of impact on protein sequence was obtained from VastDB version 3 (wnloads) . First, ggplot and ggpubr packages in R (v3.6.3).Pearson coefficient correlation plots were obtained with Cutadapt version 2.4 discarding all reads with length shorter than 15. The adapter-trimmed reads were mapped with STAR 2.7.1.a (STAR (--quantMode GeneCounts) using uniquely mapping reads only. DESeq2 version 1.14.1 . Statistical significance was defined with adjusted P-value < 0.05 and the positive false discovery rate with Q-value < 0.05.Differentially expressed genes or genes bearing differentially spliced (|ΔPSI| ≥ 15 and range of 5) AS events  between SF3B1WT and SF3B1K700E MEC1 cell lines were performed using Maxwell simplyRNA kit (Promega), Illustra RNAspin Mini RNA Isolation Kit , or RNeasy Mini kit (QIAGEN), following the manufacturers’ instructions. 50 ng of total RNA were reverse transcribed with SuperScript III (Invitrogen), and PCR reactions were carried out using GoTaq enzyme (Promega). PCR products were separated by electrophoresis on 6% acrylamide gels, analyzed with GelDocTM XR+ (Bio-Rad) and quantified with ImageJ v1.53a. Primers used are listed in Table S15. TARBP1 PCR products were analyzed by fragment analysis in an ABI 3130 Genetic Analyzer (Thermo Fisher Scientific) using GeneMapper software v6.0 (Thermo Fisher Scientific).RNA extraction and DNAse treatment in Primers used for the validation of the different Alt3’ss patterns.Table S15. RPLPO as an endogenous housekeeping gene. mRNA expression levels were provided as arbitrary quantitative PCR units, taking as a calibrator the median of the WT samples. In the case of ZDHHC16 cryptic isoform, which was not detected in the WT samples, the median of the SF3B1-mutated samples was taken as reference.Total RNA from CLL primary samples was extracted using the TRIzol reagent (Invitrogen), and 1 μg of total RNA was then reverse transcribed to cDNA. Aberrant and canonical isoforms of MAP3K7 and ZDHHC16 were quantified in StepOnePlus Real-Time PCR System (Applied Biosystems) using specific primers (Table S16). The relative expression of each gene was analyzed by the comparative cycle threshold (Ct) method (ΔΔCt) using Primers used for the qPCR validations.Table S16. pCMV 57 Δi AdML plasmid harboring two exons and an intron from the adenovirus major late promoter transcript, flanked by PT1 and PT2 sequences that allow detection of transcripts from the expression vector  by RT–PCSF3B1WT and SF3B1K700E cell lines were transfected with 50 ng of minigene DNA plasmids and Alt-R Cas9 Electroporation Enhancer (IDT) using Neon Transfection System (Thermo Fisher Scientific) with a 20 ms pulse at 1,600 V. 24 h later, cells were collected for RNA extraction and validated by RT–PCR. The PCR products from the TARBP1 gene were analyzed by fragment analysis as described above. PCR products of other minigenes were separated by electrophoresis on standard native polyacrylamide gels as described above.MEC1 6) were lysed for 30 min in Tris–Triton-X Lysis buffer  supplemented with protease and phosphatase inhibitors (Sigma-Aldrich). Lysates were centrifuged at 15,000g for 15 min at 4°C, and protein concentration assessed by Bradford assay (Bio-Rad). Total extracts were separated by 10% SDS–PAGE and transferred to an Immobilon-P PVDF membrane (Merck Millipore). Primary and secondary antibodies used for Western blot analyses are shown in Table S17. Chemiluminescence was detected by using ECL substrate (Thermo Fisher Scientific) or Amersham ECL Select Western Blotting Detection Reagent (Cytiva) on a mini-LAS4000 Fujifilm device  and quantified by Multi Gauge software (FUJIFILM).Cells  in nuclear extracts obtained using nuclear extract kit as recommended by the manufacturers.+ (BD) positivity. Synergism between H3B-8800 and venetoclax was calculated using SynergyFinder 2.0  and incubated at different concentrations for 48 h with H3B-8800 (kindly provided by H3B Biomedicine) and/or venetoclax . Cytotoxicity was measured by Annexin V (Pacific blue/FITC) and PI-mediated (Invitrogen) and flow cytometry (Attune Acoustic Focusing Cytometer from Applied Biosystems for primary cells and BD LSRFortessa Flow Cytometer for the cell lines). For co-culture experiments, HS-5 and HK cells were seeded on day 1 at a density of 20,000 cell/well and 10,000 cells/well, respectively. On day 2, 20,000 MEC1 cells/well or 200,000 primary cell/well were added and incubated with 50–75 nM H3B-8800 for 48 h. Cytotoxicity was assessed by flow cytometry as described above, after selection of MEC1 cells by CD19nder 2.0 .HEK 293T cells were transfected using jetPEI with pLV430G-oFL-T2A-eGFP, a lentivirus expressing the luciferase gene cloned in an EGFP-expressing vector , and viral stocks were collected from the culture supernatant 48 h post-transfection. MEC1 cell lines were infected, and GFP-positive cells were sorted by flow cytometry 7 d afterwards.SF3B1K700E (in 17 mice) or GFP–SF3B1K700K (in 16 mice) MEC1 CLL cell lines were injected intravenously on 6–8 wk old NOD-SCID interleukin-2 receptor gamma (IL2Rγ)null (NSG) mice. Leukemic infiltration was followed by bioluminescence using a fluorescence/luminescence imaging system AEQUORIA (Hamamatsu Photonics K.K.). 10 d after the injection, once leukemic infiltration was detected by bioluminiscence, H3B-8800 (6 mg/Kg) or vehicle control  was administrated orally and daily for 10 d until the mice were euthanized 24 h after receiving the last dose. The experimental design was approved by the Animal Testing Ethic Committee of the University of Barcelona and Generalitat de Catalunya . Peripheral blood was extracted from the submaxillary vein. Bone marrow was obtained from femurs by cutting the neck and next to the condyles, and then injecting IMDM with a syringe and a 25G needle to facilitate bone marrow extraction. Peripheral blood, bone marrow, spleen, and liver samples were first processed with ACK lysing buffer (Lonza), and then, leukemic infiltration was measured using CD19+ (Invitrogen) to detect the tumoral B lymphocytes in a BD LSRFortessa Flow Cytometer. Mouse spleens were fixed in 10% formaldehyde, dehydrated by ethanol after 24 h, and embedded in dissolved paraffin. The specimens were finally stained by hematoxylin–eosin (HE) and CD79a (Roche) immunohistochemical staining and then analyzed in an Olympus BX53 optical microscope.10 millions of GFP–Statistical tests were performed as indicated in figure legends with R (v3.6.3) or GraphPad Prism (v8.4.0).SF3B1WT and SF3B1K700E MEC1 cell lines treated with H3B-8800 are available in the following database: Gene Expression Omnibus GSE190087. RNA-seq data from patient samples were accessed from the previously available (http://www.ebi.ac.uk/ega/), which is hosted at the European Bioinformatics Institute (EBI), under accession number EGAS00000000092.RNA-seq data from vailable  database


First, we determined the static concentration-response of DOX and DEX in breast cancer cell lines, JIMT-1 and MDA-MB-468. With a three-dimensional (3D) response surface analysis using a competitive interaction model, we characterized their interaction to be modestly synergistic in MDA-MB-468 or modestly antagonistic in JIMT-1 cells. Second, a cellular-level, pharmacodynamic (PD) model was developed to capture the time-course effects of the two drugs which determined additive and antagonistic interactions for DOX and DEX in MDA-MB-468 and JIMT-1, respectively. Finally, we performed in vitro to in vivo translation by utilizing DOX and DEX clinical dosing regimen that was previously identified to be maximally cardioprotective, to drive tumor cell PD models. The resulting simulations showed that a 10:1 DEX:DOX dose ratio over three cycles of Q3W regimen of DOX results in comparable efficacy based on MDA-MB-468 (additive effect) estimates and lower efficacy based on JIMT-1 (antagonistic effect) estimates for DOX + DEX combination as compared to DOX alone. Thus, our developed cell-based PD models can be used to simulate different scenarios and better design preclinical in vivo studies to further optimize DOX and DEX combinations.Dexrazoxane (DEX) is the only drug clinically approved to treat Doxorubicin-induced cardiotoxicity (DIC), however its impact on the anticancer efficacy of DOX is not extensively studied. In this manuscript, a proof-of-concept  Doxorubicin (DOX) is widely used to treat a variety of solid tumors and hematological malignancies in the clinic . HoweverThe cardioprotective activity of DEX has long been attributed to the iron-chelating activity of its metabolite, ADR-925 . This mein vitro-in vivo predictions indicated that DEX and DOX dose ratio of 10:1 and the Q3W (once every 3 weeks) DOX regimen offer maximal cardio-protection.While the cardioprotective effects of DEX have been well characterized in clinical and preclinical studies , the impin vitro IC50s were determined and DOX and DEX concentrations were selected for subsequent drug combination and time-course studies. A three-dimensional (3D) response surface analysis using a competitive interaction model was conducted to determine the nature of their interactions. Subsequently, a mathematical, cellular response, pharmacodynamic (PD) model was developed to capture the time-course effects of the two drugs as single agents as well as their dynamic drug-drug interaction in cancer cells, and relevant parameters were estimated. Finally, in vitro to in vivo translation was performed by utilizing clinically relevant doses and regimens of DOX and DEX, previously identified to be maximally cardioprotective  was purchased from Selleck Chemicals  while Dexrazoxane (DEX) was from Millipore Sigma-Aldrich Co. . DOX was dissolved in molecular biology grade water while DEX in DMSO as per manufacturer’s instructions. Stock solutions were stored at −80°C for long-term storage while fresh serial dilutions were prepared in cell culture media each time prior to experiments. JIMT-1 cells were procured from AddexBio  and cultured in cell culture media comprising of Dulbecco’s Modified Eagle’s Medium (DMEM) with 10% sterile filtered fetal bovine serum (FBS), 1% sodium bicarbonate, 1% MEM Non-essential amino acids, and 1% penicillin/streptomycin antibiotics. MDA-MB-468 cells were purchased from American Type Culture Collection (ATCC)  and cultured in DMEM with 10% FBS, and 1% penicillin/streptomycin. Both the cell lines were maintained at 37°C in a humidified atmosphere with 5% COlsewhere .3 or 5 × 103 cells per well (100 µL) of a 96-well plate. After overnight incubation, the cell lines were exposed to varying concentrations of DOX (0.005–1 µM), DEX (0.1–400 µM), or their combinations for 72–96 h for various sets of experiments. The CCK8 cell viability assay was subsequently carried out as per the manufacturer’s instructions and as described previously  and concentrations required to achieve 50% of maximal effects (IC50).R is the response to drug treatments (% cell viability), R0 is the baseline response (% cell viability in absence of drug treatments or control), Imax is the maximal effect of drug treatments, IC50 is the drug concentration required to achieve 50% of Imax, C is the drug concentration. The IC50 values were used to select concentrations for single agents and combinations during time-course and subsequent studies.An inhibitory Hill function was used to characterize the concentration-response curves for DOX and DEX in the two breast cancer cell lines, JIMT-1 and MDA-MB-468 at 72 h and to estimate their corresponding maximal effects , Imax,A and Imax,B are the maximal effects of the two drugs , CA and CB are concentrations of the drugs, IC50A and IC50B are the half-maximal inhibitory concentrations of the drugs, γA and γB are the respective Hill coefficients and ψ is the interaction term. All individual drug-related parameters were fixed from the DOX and DEX concentration-response curve fittings and the interaction term, ψ, was estimated using Monolix software version 2016R1 . The apparent interaction between the drugs was antagonistic when ψ > 1, synergistic when ψ <1 and additive when ψ = 1.Where, R is % cell viability, RAdditionally, three-dimensional (3D) response surface plots of cell viability versus DOX and DEX concentrations were constructed to visually evaluate the interaction between the drugs for both cell lines. Briefly, an additive interaction was assumed between both drugs  and 3D response surface plots were generated for both cell lines using Eq. in vitro cellular level pharmacodynamic model (PD) was developed for the single agents, DOX, DEX, as well as their combination effects on the cell viability of human breast cancer cell lines, JIMT-1 and MDA-MB-468 as described below.The First, the degradation kinetics of DOX and DEX in cell culture media described previously  were levR is the % cellular viability (cellular response) at time t, kg is the first-order growth rate constant for cancer cell lines, while R0 is the % cellular viability at time zero.Next, the cell growth of breast cancer cell lines, JIMT-1 and MDA-MB-468, without any treatment (control group) was best described by an exponential growth function as follows:Smax,x is the maximal killing rate constant while SC50,x is the concentration of DOX or DEX required to induce half-maximal effect in JIMT-1 and MDA-MB-468. Kx is the cytotoxicity Hill function, K1x to K3x are transit compartments with Ʈx the mean transit time between compartments and Cx represents the drug concentration.The cellular response or the PD effect of DOX or DEX on the cell viability of JIMT-1 and MDA-MB-468 was described by a stimulatory effect (Hill function) on the cell death of cancer cells. A stimulatory effect on cell death in the JIMT-1 and MDA-MB-468 cancer cells lines was needed to capture the significant reduction in cell viability as compared to the control arm, as suggested by the observed data. The delay between the exposure of DOX or DEX and the non-linear cytotoxic (stimulation of death) effect on JIMT-1 and MDA-MB-468 was captured with the inclusion of three transit compartments for both drugs. This is consistent with previously published reports describing their mechanisms including temporal delay due to intracellular signaling cascade involved in their cytotoxic effects. It is to be noted that several empirical functions for cell-killing such as linear, power or sigmoidal (Hill) functions were initially evaluated to describe the trends in the observed data. Furthermore, the number of transit compartments were also varied for model optimization. The cell-killing function and number of transit compartments in the final models were selected based on visual inspection, goodness-of-fit and precision on parameter estimates. The differential equations for the effect of DOX or DEX as single agents on JIMT-1 and MDA-MB-468 cells in the final model are as follows:As both the drugs induce cytotoxic effects (stimulation of death function) in JIMT-1 and MDA-MB-468, an interaction parameter, ψ, was applied to Eq. In vitro to in vivo translation of PD responses for the joint effect of DOX + DEX in JIMT-1 and MDA-MB-468 cells was performed by utilizing clinically relevant pharmacokinetic (PK) profiles of the two agents to drive the PD models developed in the in vitro setting. In the previous study assessing cardioprotective activity of the DOX + DEX combination (2 administered every 3 weeks (Q3W) alone or in combination with DEX 500 mg/m2 over three cycles was chosen for performing model simulations for cell viability of JIMT-1 and MDA-MB-468 cells using the PD models established in vitro.bination , it was tumor/AUCplasma with the linear trapezoidal method using Phoenix WinNonlin (Version 8.2). Subsequently, this ratio was used as a multiplicative factor (Fac1) to determine DOX tumor concentrations as a fraction of the simulated plasma concentrations of DOX for the 50 mg/m2 Q3W regimen. Similarly, DEX tumor concentrations were determined using a multiplicative factor, Fac2, as a fraction of the simulated plasma concentrations of DEX at a dose level of 500 mg/m2. Due to unavailability of tumor distribution data for DEX, arbitrary values of Fac2  were used to simulate various scenarios for DEX distribution to tumor tissue in humans.First, DOX and DEX plasma PK data was obtained from previously published reports  and charin vitro PD models established for JIMT-1 and MDA-MB-468 cells. Population simulations were conducted for 500 subjects with an arbitrary inter-individual variability (IIV) of 10% introduced on the PD parameters and the Fac1 and Fac2 parameters for each cell model. Evaluation of efficacy was performed by calculating the area under the effect (% cell viability) curve (AUEC) as an integrated measure of PD response for the following scenarios: DOX alone, DOX + DEX (Fac2 = 0.1), DOX + DEX (Fac2 = 1) and DOX + DEX (Fac2 = 10).The determined tumor concentrations were then used to drive the All PK-PD model fittings and simulations were performed using Monolix suites version 2016R1 or higher, while AUEC calculations were performed using RStudio version 1.2.5033.max of 0.988 and 0.959 (both close to 1) for the former compared with that of 0.74 and 0.825 for the latter in JIMT-1 and MDA-MB-468. Overall, MDA-MB-468 was more sensitive as compared to JIMT-1 for both DOX and DEX treatments as evidenced by a lower determined IC50 and a higher maximal killing for both DOX and DEX. The inhibitory Hill model captured the concentration-response data as demonstrated with observations versus individual prediction plots shown in The two breast cancer cell lines, JIMT-1 and MDA-MB-468, were exposed to a wide range of single agent (either DOX or DEX) concentrations for 72 h. The inhibitory Hill model was fitted to the concentration-response curves, each for DOX and DEX as single agents in both the cell lines as shown in To examine the cancer cell killing effects of the drug combinations and to determine the nature of their interactions in the static setting, cells were exposed to a range of DOX and DEX concentrations as single agents as well as their combinations for 72 h as indicated in deg, DOX) and DEX  previously estimated at 0.022 (±0.0004) h−1 and 0.054 (±0.0016) h−1, respectively, were used to describe their loss in cell culture media over time (As shown in ver time . Based over time  to accouThe model fittings for the time-course effects of DOX or DEX as single agents in JIMT-1 and MDA-MB-468 are shown in −1 and 0.0167 (±1.45%) h−1, for JIMT-1 and MDA-MB-468, respectively. The dynamic changes of JIMT-1 and MDA-MB-468 cell viability over 96 h in presence of DOX or DEX were adequately captured with stimulatory effects on cell death characterized with a capacity-limited, Hill function  for DOX was 0.0705 (±15.6%) h−1 and 1.16 (±3.55%) h−1 while the DOX concentration inducing 50% of maximal cell killing rate  was estimated to be 0.315 (±18.5%) µM and 0.761 (±7.48%) µM for JIMT-1 and MDA-MB-468. On the other hand, the estimated, maximal killing rate constant  for DEX was 0.0482 (±20.2%) h−1 and 0.29 (±48.5%) h−1 while the DEX concentration inducing 50% of maximal cell killing rate  was estimated to be 21.2 (±18.8%) µM and 17.5 (±23.7%) µM for JIMT-1 and MDA-MB-468. Thus, time-course data analysis confirmed DOX to be far more potent as compared to DEX which is consistent with the concentration-response analysis. Higher maximal killing rate (Smax) as well as lower concentration to induce 50% of Smax (SC50) was consistently estimated for DOX versus DEX in both the cell lines. The delayed effects of DOX and DEX were captured well with the help of three transit compartments on the stimulation of death function, with ƮDOX and ƮDEX representing the mean transit time. ƮDOX was estimated at ∼14 h and ∼ 36 h while ƮDEX was estimated at ∼30 h and ∼ 55 h for JIMT-1 and MDA-MB-468.In the absence of DOX or DEX, the cell viability was characterized with an exponential growth function Eq.  using a tion Eq. -3e. The To characterize the time-course combinatorial effects of DOX + DEX on the cell viability or stimulation of death of breast cancer cell lines, the model structure incorporated an interaction parameter ψ where ψ = 1, ψ < 1, and ψ > 1 indicates additive, synergistic, and antagonistic interactions, respectively -4i. The Methods section, the AUCtumor/AUCplasma ratio (Fac1) was calculated for DOX based on data extracted from literature (2) values of 0.1, 1 and 10 were utilized to describe DEX concentrations at the tumor site. For JIMT-1 cells, the predicted AUEC for % cell viability over three cycles of 3 weeks each was higher with the DOX + DEX combinations (∼1560-fold) as compared to DOX, indicating higher cell killing with DOX alone and antagonistic effects between DOX + DEX on tumor cells, consistent with the in vitro PD model (in vitro (2) did not have a significant impact on AUEC predictions of the DOX + DEX combination, likely due to the dominant effect of DOX on tumor cell killing due to its high potency as compared to DEX in tumor cells.Following establishment of cellular-level PD models for DOX and DEX in JIMT-1 and MDA-MB-468 cells, model-based simulations were performed to investigate the long-term effects of clinically relevant DOX and DEX dosing regimens in tumor cells . Figure terature  and was PD model . For MDAin vitro . Of notein vitro study to examine the nature of drug-drug interaction between DOX and DEX and translated our in vitro findings to the clinical setting. Our stepwise approach consisted of first, quantitatively capturing the static concentration-response and time-course anticancer effects of DOX and DEX as single agents. Then, by means of mathematical modeling, we characterized the nature of DOX + DEX interaction by estimating the interaction parameter ψ. We used breast cancer (BC) as a prototype disease and the cell lines JIMT-1 and MDA-MB-468 as prototypes for two difficult-to-treat breast cancer subtypes, BC refractory to HER2 therapy (JIMT-1) and triple negative BC (MDA-MB-468). Second, we performed the in vitro to in vivo translation of our findings for which we simulated the clinical tumor site concentration-time profiles for DOX and DEX dosing regimens (in vivo changes in cancer cell viability (PD responses) were found to be consistent with our in vitro findings that a 10:1 DEX:DOX dose ratio over three cycles of Q3W regimen of DOX results in comparable efficacy based on MDA-MB-468 (additive effect) estimates and lower efficacy based on JIMT-1 (antagonistic effect) estimates for DOX + DEX combination as compared to DOX alone. While the developed in vitro PD model and in vivo translation remains to be validated with future experiments, our previously developed cell-based TD (toxicodynamic) model  where large preclinical studies are not feasible.In this manuscript, we presented a proof-of-concept regimens  that werc) model  along wiJIMT-1 (HER2 expressing cell line resistant to trastuzumab) and MDA-MB-468 (triple negative breast cancer) were selected as “difficult to treat” breast tumor prototypes and considered representative cell lines for advanced/metastatic breast cancer patients . In suchin vitro IC50 for DOX and DEX in the two cell lines showed ∼500 to 2000 fold higher potency for DOX than DEX  and lower SC50 (∼23 to 68 folds) in the two cancer cell lines  of DOX was mediated by both topoisomerase II alpha (TOP2A) and topoisomerase II beta (TOP2B) isoforms in HTETOP fibrosarcoma cell line  did not interfere negatively with the in vivo activity of DOX in A2780 and MX-1 human tumor xenograft mouse models  . A cliniin vitro to in vivo translational modeling approach accounted for clinically relevant DOX and DEX doses and their pharmacokinetic aspects, an important caveat that remains to be addressed is extrapolation of effects at the pharmacodynamic level, given the differences between a static two-dimensional monolayer cell-culture system versus the three-dimensional tumor microenvironment in an in vivo system. To this end, next steps and ongoing efforts include extending the in vitro assessment of this combination to a three-dimensional and dynamic (3DD) cell culture system, which is more representative of in vivo conditions as compared to a standard two-dimensional (2D) monolayer cell culture system (in vivo using our present in vitro PD model as a starting point, provides some insights into the nature of the in vivo PD interaction between DOX and DEX in breast cancer cells to guide future studies of this combination.While our e system . Neverthin vivo conditions. Such developed PK/PD/TD models can serve as in silico tools to assess DOX and DEX combinations for safety and efficacy and enable better design of preclinical in vivo studies.To summarize, we have developed a proof-of-concept cell-based PD model which can serve as a platform to optimize DOX and DEX combinations for efficacy indices. As with the TD model, efforts are ongoing to extend the PK model to include different tissue compartments including the tumor and the heart and link appropriate tissue concentrations to PD/TD models so that efficacy and safety predictions can be simultaneously estimated. Similarly, evaluation of the dynamic changes in the intracellular signaling pathway for DOX and DEX PD models is underway to enable better quantitative understanding of the underlying mechanisms, as well as evaluation of this combination in a 3DD system to better reflect


Glioblastoma is one of the most common malignant brain tumors. Vitamin D, primarily its hormonally active form calcitriol, has been reported to have anti‐cancer activity. In the present study, we used patient‐derived glioma cell lines to examine the effect of vitamin D3 and calcitriol on glioblastoma. Surprisingly, vitamin D3 showed a more significant inhibitory effect than calcitriol on cell viability and proliferation. Vitamin D receptor (VDR) mediates most of the cellular effects of vitamin D, and thus we examined the expression level and function of VDR via gene silencing and gene knockout experiments. We observed that VDR does not affect the sensitivity of patient‐derived glioma cell lines to vitamin D3, and the gene encoding VDR is not essential for growth of patient‐derived glioma cell lines. RNA sequencing data analysis and sterolomics analysis revealed that vitamin D3 inhibits cholesterol synthesis and cholesterol homeostasis by inhibiting the expression level of 7‐dehydrocholesterol reductase, which leads to the accumulation of 7‐dehydrocholesterol and other sterol intermediates. In conclusion, our results suggest that vitamin D3, rather than calcitriol, inhibits growth of patient‐derived glioma cell lines via inhibition of the cholesterol homeostasis pathway. Vitamin D3 exerts a significantly stronger inhibitory effect on cell viability and cell proliferation of patient‐derived glioma cell lines than calcitriol, and this effect is mediated through inhibition of cholesterol homeostasis and cholesterol synthesis. We used GBM cell lines for research as well, which were isolated from GBM patient tumor samples and cultured with the serum‐free stem cell culture method. These cell lines were called patient‐derived glioma cell lines. Patient‐derived glioma cell lines have similar characteristics to GSC and retain a certain proportion of genomic and transcriptome characteristics from patients.Glioma, a type of central nervous system (CNS) tumor, is considered to derive from neuroglial stem or progenitor cells . More thCYP2R1), cytochrome P450 family 27 subfamily A member 1 (CYP27A1) and cytochrome P450 family 27 subfamily B member 1 (CYP27B1), to form active vitamin D , which then binds to vitamin D receptors (VDR) and regulates downstream genes . Hi. HiP = 0g. PCSK9 , 46, 47.HMGCR mRNA expression or the degradation of HMGCR protein, thereby regulating the cholesterol synthesis pathway [To further explore the changes in the contents of sterols after the treatment of vitamin D3, sterolomics analysis was performed by LC/MS. The results showed that the total sterols in patient‐derived glioma cell lines increased significantly after vitamin D3 treatment, whereas total cholesterol decreased Fig., which w pathway , 49, 50.DHCR7 and DHCR24, which led to excessive accumulation of downstream sterol intermediates. The accumulation of sterol intermediates further strengthened the inhibition of the cholesterol synthesis and cholesterol homeostasis pathways. This was the main mechanism by which vitamin D3 inhibited cell viability and proliferation in patient‐derived glioma cell lines.In summary, vitamin D3 stagnated cholesterol synthesis by inhibiting the expression levels of de novo by astrocytes [Changes in genetic and epigenetic signaling pathways in tumors often promote metabolic reprogramming . Alteredtrocytes . Meanwhitrocytes . TherefoDHCR7 and DHCR24, thereby inhibiting cholesterol synthesis and cholesterol homeostasis pathways. In our view, the effects of vitamin D3 on cholesterol homeostasis have been rarely reported, and its mechanisms have scarcely been studied [Although the research on vitamin D in GBM has focused on the active form of vitamin D, in the present study, we demonstrated that patient‐derived glioma cell lines were more sensitive to vitamin D3 than calcitriol and calcifediol. Interestingly, vitamin D3 obtained more significant inhibitory effects on cell viability and cell proliferation of patient‐derived glioma cell lines by inhibiting the expression levels of  studied , 58. MeaDHCR7 are associated with a disease called Smith–Lemly–Opitz‐syndrome (SLOS), which defects in hedgehog signaling [SMO) and inhibiting the expression level of GLI family zinc finger 1 (GLI1) in some types of cell lines [PTCH1), SMO and GLI1 were measured by a quantitative PCR (Fig. It is worth noting that mutations in gene ignaling , 61. Furll lines , 62. SucPCR Fig. . The resin vivo is more complex. In addition, whether this regulation occurred only on patient‐derived glioma cell lines or is a general feedback mechanism is also an important question. Limited by the lack of instruments, we were not able to examine whether the enzymatic activity of DHCR7 was inhibited after vitamin D3 treatment as previously reported, and only confirmed that the mRNA expression level of DHCR7 was decreased. How vitamin D3 regulated the mRNA expression or/and enzyme activity of DHCR7 at the microscopic level is still a very interesting question. These questions are worthy of further study.A major limitation of the present is that the experimental model used was only cell line, but the environment Although our works focused on vitamin D3, calcifediol and calcitriol also had interesting phenomena. Sterolomics in vitamin D3‐, calcifediol‐ or calcitriol‐treated groups was significantly different from each other Fig. . In the The authors declare that they have no conflicts of interest.https://www.webofscience.com/api/gateway/wos/peer‐review/10.1002/2211‐5463.13679.The peer review history for this article is available at RY and JC conceptualized and designed the study. RY wrote the manuscript. WZ, Y‐PY, GC, ZG and XW provided the human glioma cell lines. All authors read and approved the final version of the manuscript submitted for publication.