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. 2021 Mar 18;24(4):102325. doi: 10.1016/j.isci.2021.102325

DNA repair and cholesterol-mediated drug efflux induce dose-dependent chemoresistance in nutrient-deprived neuroblastoma cells

Soo Yeon Chae 1,2,5, Dowoon Nam 1,2,5, Do Young Hyeon 3,5, Areum Hong 1,5, Timothy Dain Lee 3, Sujin Kim 1,2, Dongjoon Im 1,2, Jiwon Hong 1,2, Chaewon Kang 1,2, Ji Won Lee 4, Daehee Hwang 3,∗, Sang-Won Lee 1,2,∗∗, Hugh I Kim 1,2,6,∗∗∗
PMCID: PMC8050388  PMID: 33889821

Summary

Neuroblastoma is a solid, heterogeneous pediatric tumor. Chemotherapy is widely used to treat neuroblastoma. However, dose-dependent responses and chemoresistance mechanisms of neuroblastoma cells to anticancer drugs remain challenging. Here, we investigated the dose-dependent effects of topotecan on human neuroblastoma cells (SK-N-SH, SH-SY5Y, and SK-N-BE) under various nutrient supply conditions. Serum-starved human neuroblastoma cells showed reduced toxicity. Their survival rate increased upon treatment with a high concentration (1 μM) of topotecan. Quantitative profiling of global and phosphoproteome identified 12,959 proteins and 48,812 phosphosites, respectively, from SK-N-SH cells. Network analysis revealed that topotecan upregulated DNA repair and cholesterol-mediated topotecan efflux, resulting in topotecan resistance. Results of DNA damage assay, cell cycle, and quantitative analyses of membrane cholesterol supported the validity of these resistance factors and their applicability to all neuroblastoma cells. Our results provide a model for high dose-dependent chemoresistance in neuroblastoma cells that could enable a patient-dependent chemotherapy screening strategy.

Subject areas: Molecular Biology, Cancer, Proteomics

Graphical abstract

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Highlights

  • The survival rate was increased on nutrient-deprived human neuroblastoma cells

  • Performed proteomics and network analysis-based pharmacodynamic study

  • DNA repair was accelerated resistance in nutrient-deprived human neuroblastoma cells

  • Cholesterol-mediated efflux was increased at resistance conditions

Molecular Biology ; Cancer ; Proteomics

Introduction

Neuroblastoma is the most common extracranial solid pediatric tumor, accounting for 6-10% of all childhood cancers. Neuroblastoma tumors originate from precursor cells in the sympathetic nervous system or the adrenal medulla (Maris et al., 2007; Stiller and Parkin, 1992; Maris and Matthay, 1999; Johnsen et al., 2018, 2019). The disease course of neuroblastoma is highly heterogeneous, and factors such as the age at diagnosis, stage, and tumor biology are known to affect treatment outcomes (Cheung and Dyer, 2013; Maris, 2010; Coldman et al., 1980). The current treatment strategy for neuroblastoma is tailored according to the risk stratification based on clinical and biological factors (Cohn et al., 2009; Leclair et al., 2004). Multicenter clinical trials offer tailored treatment approaches that have significantly improved the outcomes for neuroblastoma over the past decades, particularly for patients with low- and intermediate-risk neuroblastoma (Van Arendonk and Chung, 2019; Mossé et al., 2014). The treatment outcome for high-risk neuroblastoma has also been improved with intensive multimodal treatment. However, a substantial number of patients still experience relapse or progression (Herd et al., 2019; Morgenstern et al., 2013).

Anticancer drugs often fail to treat neuroblastoma due to the respective differences in the phenotypic profiles of tumors (Maeda and Khatami, 2018; Ngan, 2015; Hiyama and Hiyama, 2005). To optimize therapeutic outcomes given the individual differences, drug stability and efficacy tests using human cells in the form of 2-dimensional (2D) cell cultures or xenografts are commonly performed prior to the treatment (Niu and Wang, 2015; Macaire et al., 2019; Zanoni et al., 2016). However, drug responses in patients differ from those observed in cellular model systems. Under in vivo conditions, solid tumors are multicellular spheroid structures, the interiors of which are divided into three layers: the proliferating zone, the quiescent viable cell zone, and the necrotic core (Edmondson et al., 2014; Kim, 2005; Khaitan et al., 2006). Cells in the deeper regions of a tumor are deprived of oxygen, nutrients, and growth factors (Minchinton and Tannock, 2006; Höckel and Vaupel, 2001). Cells grown in 2D cultures under serum starvation show the morphology and behavior similar to those shown by cells in the interior of tumors due to an analogous environment characterized by poor vascularization and nutrient-deprived condition (Levin et al., 2010). Therefore, a 2D culture of tumor cells under serum starvation serves as a good model system that mimics the interior of tumors; their study can provide information about the behavior of tumor cells at the molecular level.

Despite the heterogeneity in the phenotypic profiles of patients with neuroblastoma, equivalent doses of anticancer drugs are typically used in the chemotherapy regimen of individual patients. Despite extensive investigations into the molecular mechanisms of drug resistance (Longley and Johnston, 2005; Gottesman, 2002; Holohan et al., 2013) and the action of anticancer drugs (Starobova and Vetter, 2017; Alcindor and Beauger, 2011; Gregg et al., 1992), the dose-dependent effects of these drugs on tumor suppression have not been fully elucidated. Therefore, to develop therapeutic strategies for neuroblastoma, it is necessary to consider the concentration-dependent effects of anticancer drugs on tumor suppression.

Topotecan is an effective chemotherapeutic drug for induction therapy of high-risk neuroblastoma (De Ioris et al., 2011; Park et al., 2006). In this study, we investigated the dose-dependent effects of topotecan on human neuroblastoma cells (SK-N-SH, SH-SY5Y, and SK-N-BE). Serum-starved neuroblastoma cells commonly exhibited higher survival rates. Specifically, serum-starved SK-N-SH cells showed unique resistance to topotecan, when a high concentration (1 μM) of topotecan was used. We performed quantitative proteomic analysis of serum-starved SK-N-SH cells treated with topotecan to identify resistance factors. Functional enrichment and network analyses of the upregulated proteins in the resistance condition revealed that increased DNA repair activity and topotecan efflux as resistance factors. Time-resolved topotecan measurements performed using multiple reaction monitoring mass spectrometry (MRM-MS) further confirmed the decrease in topotecan levels in serum-starved SK-N-SH cells via the increased topotecan efflux. DNA damage assay, cell cycle analysis, and cholesterol detection confirmed the increased DNA repair activity and topotecan efflux in all neuroblastoma cells investigated in this study. Our results suggest a potential cellular mechanism for dose-dependent topotecan resistance and provide a strategy to predict topotecan efficacy in patients with neuroblastoma.

Results

Nutrient-deprivation induces chemoresistance in human neuroblastoma cells

We first investigated the effects of topotecan on the survival of SK-N-SH, SH-SY5Y, and SK-N-BE cells under 10% fetal bovine serum (FBS) or serum starvation. The cells were treated with topotecan at concentrations ranging from 0.1 nM to 10 μM for up to 72 hr, and cell viability assays were performed every 24 hr after the initial drug treatment using cell counting kit-8 (CCK-8). Different cell viability trends were observed between 10% FBS and serum starvation conditions after 24 hr of the initial drug treatment (Figure 1). The viability of SK-N-SH, SH-SY5Y, and SK-N-BE human neuroblastoma cells was reduced significantly to 46.9, 42.6, and 50.5%, respectively, at 48 hr (Figure 1 and Table S1, Table depicting the viability of human neuroblastoma cells, related Figure 1) and 39.3, 36.7, and 52.0%, respectively, at 72 hr under 10% FBS after treatment with 1 μM topotecan (Table S1, Table depicting the viability of human neuroblastoma cells, related Figure 1 and Figure S1, dose-response viability curves at 72 hr, related Figure 1).

Figure 1.

Figure 1

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Cell viability assays of SK-N-SH, SH-SY5Y, and SK-N-BE human neuroblastoma cells treated with different concentrations of topotecan

Viability plots were constructed for cells incubated with 10% FBS (left) and for serum-starved cells (middle). Dose-response curves were also constructed at 48 hr under identical conditions. Data are presented as mean ± S.D. values derived from three independent experiments. ∗p < 0.05, ∗∗p < 0.01.

Serum-starved neuroblastoma cells exhibited higher overall survival rates than the cells grown in 10% FBS. For topotecan concentrations between 0.1 nM and 0.1 μM, topotecan-treated SK-N-SH, SH-SY5Y, and SK-N-BE cells showed a marginal increase in the viability under serum starvation compared to control cells not treated with topotecan (Figure 1). The findings suggest that topotecan treatment was not cytotoxic to the cells under serum starvation. However, when treated with 1 μM of topotecan, the viability of serum-starved SK-N-SH cells was significantly increased (p < 0.01) to approximately 1.6 folds (155%) with respect to control cells after 48 hr (Figure 1A and Table S1, Table depicting the viability of human neuroblastoma cells, related Figure 1) and 1.8 folds (179%) after 72 hr. A similar dose-dependent effect of topotecan was observed on the viability of SK-N-SH cells obtained from a different source (Korea Cell Line Bank) (Figure S2, Results of the cell viability assay performed with SK-N-SH cells obtained from a different source, related Figure 1). Although the effect was not as pronounced as that observed in SK-N-SH cells, the viability of serum-starved SH-SY5Y and SK-N-BE cells treated with 1 μM of topotecan was increased by 131% and 120%, respectively, after 72 hr (Table S1B and S1C, Table depicting the viability of human neuroblastoma cells, related Figures 1, Figure S1B, and S1C, dose-response viability curves at 72 hr, related Figure 1). These data indicate that neuroblastoma cells cultured in 10% FBS underwent apoptosis in response to topotecan treatment due to topotecan-induced DNA damage, whereas serum-starved cells might be resistant to apoptosis. Notably, even when 10 μM of topotecan was administered, SK-N-SH, SH-SY5Y, and SK-N-BE cells exhibited significantly higher viability (102.8, 84.5, and 79.7%, respectively) under serum starvation after 72 hr than under 10% FBS (4.83, 15.5, and 41.6%, respectively). Collectively, these data indicate that serum starvation induces chemoresistance toward topotecan in neuroblastoma cells even up to high concentrations.

Quantitative proteomic profiling of SK-N-SH cells

To understand the molecular basis of the chemoresistance, we performed quantitative proteomic profiling of SK-N-SH cells. Proteins were extracted from the samples obtained after 5 min and 48 hr of 0.1 or 1 μM topotecan treatment or without topotecan treatment (control) under serum starvation or 10% FBS (Figures 2A and S3A, Proteomics experiments, related Figure 2). After tryptic digestion, the two sets of six peptide samples (control, 5 min, and 48 hr treatment under serum starvation or at 10% FBS) were labeled with 6-plex tandem mass tag (TMT) reagents (Figure S3, Proteomics experiments, related Figure 2). All 6-plex TMT-labeled peptide samples were pooled and the peptide pool was first subjected to immobilized metal affinity chromatography (IMAC) phosphopeptide enrichment as described previously (Park et al., 2015). The whole phosphopeptide sample was fractionated into 12 online non-contiguously fractionating and concatenating (NCFC) fractions using the dual-online-NCFC-reverse-phase/reverse-phase liquid chromatography (DO-NCFC-RP/RP-MS/MS) system (Lee et al., 2016) to generate 12 phosphopeptide LC-MS/MS data set. We obtained a total of 24 LC-MS/MS phospho data sets—12 after treatment with 0.1 μM topotecan and 12 after treatment with 1 μM topotecan (Figure S3, Proteomics experiments, related Figure 2). The flow-through sample (i.e. non-phosphopeptides) from the IMAC experiments was subsequently fractionated into 24 online NCFC fractions using DO-NCFC-RP/RP-MS/MS system to generate 24 global LC-MS/MS data sets (Figure S3, Proteomics experiments, related Figure 2). For each of the 24 global LC-MS/MS data sets and the 12 phospho LC-MS/MS data sets, we identified the peptides through a search of the UniProt human reference database using the MS-GF + search engine using a target decoy setting and a peptide spectrum match-false discovery rate of 1%. From the SK-N-SH cells treated with 0.1 and 1 μM topotecan, we identified 285,027 and 281,156 non-redundant peptides, respectively, and 10,995 and 10,983 proteins with two or more sibling peptides, respectively (Figures 2B and 2C, and Data S1, The list of peptides and proteins from the proteomics analysis, related Figure 2). From the same peptide samples of 0.1 and 1 μM topotecan treatment, we identified 42,241 and 61,151 non-redundant phosphopeptides, respectively (Data S1, The list of peptides and proteins from the proteomics analysis, related Figure 2). There were high overlaps of the identified peptides and proteins between two TMT data sets (Figure S3B, Proteomics experiments, related Figure 2), supporting the validity of proteomic experiments. Compared to the previous proteome profile (3,333 proteins and 5,593 proteins from SK-N-SH cells) (Halakos et al., 2019; Li et al., 2018) and phosphoproteome profile (15,417 phosphopeptides from SK-N-BE2 cells) (Scaturro et al., 2018) obtained from neuroblastoma cells, our data represent a more comprehensive neuroblastoma proteome (Figures 2B and 2C) and phosphoproteome for the identification of protein signatures associated with topotecan resistance under serum starvation.

Figure 2.

Figure 2

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Global proteome and phosphoproteome profiling of SK-N-SH cells treated with 0.1 or 1 μM topotecan

(A) Schematic representation of the experimental procedure for quantitative proteomic analysis. Two sets (0.1 and 1 μM topotecan) of six cells (three cells of 10% FBS and three cells of serum starvation) were separately subjected to identical processes of protein extraction/digestion, 6-plex TMT-labeling, IMAC enrichment, and global/phosphoproteome analyses.

(B and C) The numbers of proteins characterized from SK-N-SH cells after treatment with 1 μM topotecan and 0.1 μM topotecan compared with the previously characterized proteome of the identical cell line.

Topotecan resistance-associated protein signatures

Proteins whose abundance or phosphorylation was increased or decreased in serum-starved cells but not changed in those that were cultured with 10% FBS may contribute to topotecan resistance. To identify these proteins, we performed the following four comparisons of peptide abundances (TMT intensities) determined at 48 hr with and without treatment of 0.1 or 1 μM topotecan under 10% FBS or serum starvation: 0.1 μM vs. no treatment (0.1 μM FBS) and 1 μM vs. no treatment under 10% FBS (1 μM FBS), and 0.1 μM vs. no treatment (0.1 μM starvation) and 1 μM vs. no treatment (1 μM starvation) under serum starvation. From the four comparisons, we identified differentially expressed peptides and phosphopeptides with absolute log2-fold-changes > 1 (2-fold) and differentially expressed proteins (DEPs) with two or more unique differentially expressed peptides in the same direction (Data S2, The differentially expressed peptides and phosphopeptides and DEPs, related Figure 3.).

Figure 3.

Figure 3

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Protein signatures associated with topotecan resistance

(A and B) Venn diagram showing relationships between upregulated proteins (A) or phosphopeptides (B) under 0.1 μM and 1 μM starvation and 0.1 μM and 1 μM 10% FBS.

(C) Cellular processes enriched by the upregulated proteins or phosphopeptides specifically in serum-starved cells. The enrichment significance of each process is indicated as -log10 (p value), where the p value was computed using the DAVID software. The p value = 0.05 cutoff is indicated by a dotted line.

(D) Network model describing the cellular pathways of the proteins with increased/decreased abundances or phosphorylation in serum-starved cells. Circled P on a node indicates upregulated phosphorylation of the corresponding protein. Topotecan and cholesterol are denoted by “T” and “Ch,” respectively. Conditions under which the abundance or phosphorylation of the corresponding protein is increased (up-pointing triangle) or decreased (down-pointing triangle) are indicated by the colors of nodes and circled P (see node legend). The names of proteins validated by the immunoblotting assay are shown in red. Solid arrows indicate direct activation, transport, and single-step conversion (e.g. conversion of metabolites in cholesterol biosynthesis pathway) of molecules, whereas dotted arrows indicate indirect activation and multi-step conversion of molecules. Solid inhibition symbols indicate direct inhibition of molecules.

(E) Quantification of the levels of BLM, DHCR24, and Phospho-IRS-1 (48 hr relative vs. control) by immunoblotting. The bar plots present mean ± S.D. values (n = 3).

We then focused on the DEPs and differentially expressed phosphopeptides that were upregulated specifically under serum starvation but not changed under 10% FBS (Figures 3A and 3B, highlighted in red), which are likely to account for the induced property of topotecan resistance under serum starvation. To examine cellular processes associated with these upregulated proteins or the proteins containing the upregulated phosphopeptides, we performed enrichment analysis of gene ontology biological processes using the DAVID software (Huang et al., 2008). Upregulated proteins were mainly associated with processes related to the cell cycle (cell cycle, apoptotic process, and DNA damage response/DNA repair) and lipid synthesis/transport (Figure 3C). Upregulation of cell cycle proteins was consistent with the increased cell viability observed under serum starvation (Figure 1). Proteins with upregulated phosphorylation were mainly associated with the same cell-cycle-related processes that were enriched by the upregulated proteins, except for lipid synthesis/transport (Figure 3C). Instead, the insulin/mTOR signaling pathway, one of the most potent upstream signaling pathways of lipid synthesis/transport that activates sterol regulatory-element binding protein (SREBP) transcription factors, was enriched by these phosphoproteins. Since metabolic enzymes are commonly controlled by the protein abundance and rarely by phosphorylation, the complementary enrichment of lipid synthesis and insulin/mTOR signaling supports the validity of our global proteome and phosphoproteome.

To understand the collective effects of the upregulated proteins or phosphoproteins involved in the cell cycle, lipid synthesis/transport, and insulin/mTOR signaling on topotecan resistance, we built a network model (Figure 3D) describing the interactions among the upregulated proteins and phosphoproteins involved in these processes based on previously reported mode-of-action and topotecan resistance (Pommier, 2006; Liscovitch and Lavie, 2000). Topotecan binds to topoisomerase I (TOP1) in the TOP1 cleavage complex (TOP1cc), forming an irreversible TOP1cc that induces double-strand DNA (dsDNA) breaks during DNA replication at the S phase, followed by cell-cycle arrest at the G2 phase and apoptosis (Pommier, 2006; Kollmannsberger et al., 1999) (Figure 3D, top left). Topotecan induces dsDNA breaks and then activates the ATR-CHK1 pathway for their repair (Lambert et al., 2010; Adamson et al., 2012). Our network model revealed the downregulation of TOP1, upregulation of DNA repair proteins (BLM, ERCC1, and RRM2), and increased phosphorylation of proteins (CHK1, CDC25B, BLM, PARP4, and RRM2) in DNA repair signaling pathways under serum starvation (Figure 3D, left), which enhanced cell viability upon induction of DNA damage by topotecan. In addition, the network model showed the upregulation of proteins involved in cholesterol synthesis (HMGCS1, HMGCR, FDFT1, SQLE, CYP51A1, MSMO1, and DHCR24) and efflux (APOE) under serum starvation and increased topotecan efflux via topotecan chelation by cholesterol in a CAV1-dependent pathway (Liscovitch and Lavie, 2000) (Figure 3D, middle). The network model further showed the increased phosphorylation of proteins involved in the insulin/mTOR signaling (IRS1, PTPN1, PIK3R2, AKT2, AKT1S1, LPIN2, and EIF4EBP1), which led to the upregulation of cholesterol biosynthetic proteins via SREBP transcription factors (Figure 3D, right). These data collectively suggest that the upregulated DNA repair and cholesterol-mediated topotecan efflux and the activated insulin/mTOR signaling may contribute to the resistance to a high dose (1 μM) of topotecan in serum-starved SK-N-SH cells.

To check the validity of these findings obtained using the network analysis, we first performed immunoblotting (IB) to confirm the upregulation of the three representative proteins BLM, DHCR24, and Phospho-IRS-1 for increased DNA repair, cholesterol-mediated topotecan efflux, and insulin/mTOR signaling, respectively, in the network model. Western blotting assays confirmed the upregulation of BLM, DHCR24, and Phospho-IRS-1 proteins in SK-N-SH cells at 48 hr after 1 μM topotecan treatment under serum starvation; however, virtually no changes were observed under 10% FBS (Figure 3E). Taken together, these data support the contribution of increased DNA repair and cholesterol-mediated topotecan efflux to high-dose topotecan resistance in serum-starved SK-N-SH cells.

Increased DNA repair and altered cell cycle distribution associated with topotecan resistance under serum starvation

Chemotherapy-induced DNA-damage correlates with the release of the activated caspases (Rodríguez-Hernández et al., 2006). To verify improvements in DNA damage via enhanced DNA repair under serum starvation, as previously described (Koivusalo and Hietanen, 2004), we performed the DNA damage assay by measuring the amounts of activated caspase-3/7 released into the culture media in the presence of 10% FBS and when exposed to serum starvation (48 hr after topotecan treatment). In the presence of 10% FBS, the amount of the activated caspase-3/7 released into the culture media by SK-N-SH cells slightly increased to 101% after treatment with 0.1 μM topotecan (Figure 4A). When treated with a higher concentration of topotecan, i.e., 1 μM, the amount further increased to approximately 112%. This increasing pattern was more evident at 72 hr after topotecan treatment (Figure S4, Bar-plot depicting the levels of activated caspase-3/7 at 72 h in SK-N-SH cells, related Figure 4). Such an increase in the levels of released activated caspase-3/7 confirmed the increase in DNA damage upon culturing the cells in presence of 10% FBS, consistent with the decreased viability in topotecan-treated SK-N-SH cells cultured with 10% FBS (Figure 1A). In contrast, serum-starved SK-N-SH cells exhibited significantly (p < 0.01) lower DNA damage than those cultured in the presence of 10% FBS, as indicated by the decreased amounts of activated caspase-3/7 48 hr after treatment with 0.1 μM (88.1%) and 1 μM (89.6%) topotecan (Figure 4A). These data confirm the increased DNA repair activity in serum-starved SK-N-SH cells, as indicated by the upregulation of BLM (Figure 3E).

Figure 4.

Figure 4

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Bar-plot for the amount of activated caspase-3/7 in SK-N-SH cells and cell cycle analysis

(A) Bar-plot depicting the amount of activated caspase-3/7 in SK-N-SH cells and (B and C) cell cycle analysis. Plots were generated for cells incubated with 10% FBS and for serum-starved cells. Data are presented as mean ± S.D. values derived from three independent experiments. ∗∗p < 0.01.

Topotecan delays S phase progression during DNA replication by inducing dsDNA breaks and arrests the cells at the G2 phase. Our network model suggested a decrease in dsDNA breaks and an increase in the repair of dsDNA breaks, as indicated by the downregulation of TOP1 and upregulation of BLM, respectively. To examine the effects of decreased DNA damage and increased DNA repair on the cell cycle of serum-starved SK-N-SH cells, we next performed the cell cycle analysis of SK-N-SH cells at 48 hr after 1 μM topotecan treatment under serum starvation and 10% FBS by staining the DNA with the propidium iodide (PI) fluorescent dye. Topotecan treatment significantly increased the numbers of SK-N-SH cells in the S and G2/M phases under 10% FBS (Figures 4B, S5A, and S5B, Histogram of cell cycle analysis, related Figure 4). However, the increase was significantly suppressed under serum starvation (Figures 4C, S5C, and S5D, Histogram of cell cycle analysis, related Figure 4). Moreover, the number of SK-N-SH cells in the G0/G1 phase was higher under serum starvation than that under 10% FBS. These data collectively suggest that both decreased DNA damage and increased DNA repair activity can facilitate the progression of SK-N-SH cells through the S and G2/M phases due to successful DNA repair and replication, which increases the cell population re-entering the G0/G1 phase, supporting the prediction from our network model.

Topotecan resistance-associated cholesterol-mediated drug efflux

The network model also suggested that the intracellular concentration of topotecan could be decreased in serum-starved SK-N-SH cells via increased topotecan efflux, contributing to topotecan resistance under conditions of serum starvation. To test this prediction, we measured the amount of topotecan inside SK-N-SH cells at 5 min, 24 hr, and 48 hr after treatment with 1 μM topotecan (Figure 5A) by quantitating topotecan in the protein-free supernatant of cell lysates using MRM analysis with RPLC-triple quadrupole mass spectrometry. The amount of topotecan in the cells peaked 5 min after topotecan treatment under both serum starvation and 10% FBS; thereafter, it gradually decreased. Importantly, the amount of topotecan was significantly (33%) lower under serum starvation than that under 10% FBS, 48 hr after topotecan treatment. This observation suggests that either the metabolism or efflux of topotecan was increased at 48 hr. Previously, the metabolism of topotecan was shown to reach a maximum level after 15 min in the isolated perfused rat liver (Platzer et al., 1998). Although the abundances of CYP enzymes responsible for topotecan metabolism can differ between serum-starved neuroblastoma cells and rat liver cells, topotecan seems to be rapidly metabolized following treatment. Considering the upregulation of the proteins involved in the cholesterol-mediated topotecan efflux at 48 hr, the decreased amount of topotecan is more likely due to the increased efflux of topotecan. Notably, the survival rate of serum-starved SK-N-SH cells started to significantly (p < 0.01) increase 48 hr after treatment (Figure 1A).

Figure 5.

Figure 5

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Quantitative analysis of cellular topotecan and membrane cholesterol Bar plots present the level of cellular topotecan ±S.D

values (n = 3) (A) Fluorescence bar plot and imaging of filipin III-stained membrane cholesterol for SK-N-SH cells (B). The bar plots present mean ± S.E. values (n = 3). ∗∗p < 0.01.

To correlate the cellular amount of topotecan with cholesterol-mediated topotecan efflux, we measured the amount of cholesterol located in the membrane of SK-N-SH cells at 48 hr after exposure to topotecan via cholesterol assay using filipin III, a histochemical stain for cholesterol that emits fluorescence at wavelengths ranging from 385 to 470 nm (Drabikowski et al., 1973). The representative fluorescence images of the fixed SK-N-SH cells revealed that the amount of cholesterol was significantly (p < 0.01) higher on the surface of the cells under serum starvation than that under 10% FBS (Figure 5B). Together with the upregulation of DHCR24 confirmed by western blotting (Figure 3E), these data suggest that more cholesterol was synthesized and effluxed under serum starvation conditions in topotecan-treated SK-N-SH cells, consistent with the prediction from the network model. The network model suggested that the whole cholesterol synthesis pathway was upregulated based on the upregulation of metabolic enzymes involved in the pathway. Metabolomic analysis of serum-starved SK-N-SH cells can be employed to further confirm whether the abundance of the intermediate metabolites was increased under conditions of serum starvation.

Topotecan resistance-associated alterations in cell cycle distribution and cholesterol efflux

We showed the dose-dependent topotecan resistance in human neuroblastoma cells (SK-N-SH, SH-SY5Y, and SK-N-BE) under conditions of serum starvation (Figure 1). The aforementioned experiments supported the validity of topotecan resistance factors (i.e., increased DNA repair and cholesterol-mediated topotecan efflux) predicted from the network model in serum-starved SK-N-SH cells. To examine the general validity of these resistance factors in nutrient-deprived neuroblastoma cells, we next performed the same analyses in SH-SY5Y and SK-N-BE cells (Figure 6). The western blots showed that 1 μM topotecan upregulated the expression of both BLM and DHCR24 proteins under conditions of serum starvation in SH-SY5Y cells but only upregulated DHCR24 in SK-N-BE cells (Figures 6A and 6B).

Figure 6.

Figure 6

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IB quantification, Cell cycle analysis, and membrane cholesterol quantification in SH-SY5Y and SK-N-BE

IB quantification of BLM and DHCR24 (48 hr vs. control) of SH-SY5Y (A) and SK-N-BE (B). The bar plots present mean ± S.D. values (n = 3). Cell cycle analysis of propidium iodide stained SH-SY5Y (C) and SK-N-BE (D) cells. Fluorescence bar plot and image of filipin III-stained membrane cholesterol for SH-SY5Y (E) and SK-N-BE (F) cells. Data are expressed as mean ± S.D. values (n = 3). Fluorescence data are expressed as mean ± S.E. derived from three independent experiments (n = 3).

Upon culturing SH-SY5Y and SK-N-BE cells in the presence of 10% FBS, the levels of activated caspase-3/7 released into the culture media increased to 112 and 111%, respectively, 48 hr after treatment with 1 μM topotecan (Figure S6, Bar-plots depicting the levels of activated caspase-3/7 at 48 hr and 72 hr in SH-SY5Y and SK-N-BE cells, related Figure 6). This increasing pattern was more evident 72 hr after treatment with 1 μM topotecan. These results are consistent with the findings in SK-N-SH cells. In contrast, serum-starved SH-SY5Y and SK-N-BE cells exhibited significantly (p < 0.01) lower DNA damage than those under 10% FBS, as indicated by the decreased levels of activated caspase-3/7, particularly 72 hr after 1 μM topotecan treatment (88.7 and 96.7% in SH-SY5Y and SK-N-BE cells, respectively). The finding that there was relatively more DNA damage in SK-N-BE cells than that in SK-N-SH and SH-SY5Y cells was in agreement with the observation that there was no apparent increase in DNA repair activity (i.e., BLM protein levels) in SK-N-BE cells (Figure 6A), unlike the increased DNA repair activity in the other two cell types. This also correlated with the relatively lower topotecan resistance (i.e., less increased viability) of SK-N-BE cells (Figure 1).

Cell cycle analysis further showed that the numbers of both SH-SY5Y and SK-N-BE cells in the S and G2/M phases after 1 μM topotecan treatment decreased under serum starvation compared to that under 10% FBS, similar to SK-N-SH cells (Figures 6C, 6D, and S7, Cell cycle analysis in SH-SY5Y and SK-N-BE, related Figure 6). These data suggest that the decreased DNA damage and/or the increased DNA repair facilitated cell cycle progression through the S and G2/M phases in serum-starved SH-SY5Y and SK-N-BE cells similar to that in serum-starved SK-N-SH cells, thereby increasing the cell population re-entering the G0/G1 phase. Interestingly, the cell cycle shift associated with topotecan resistance was less apparent in serum-starved SK-N-BE cells. This is consistent with no apparent upregulation of BLM and less reduction of DNA damage, resulting in less effective facilitation of the cell cycle progression compared to that in serum-starved SK-N-SH and SH-SY5Y cells. Moreover, the membrane cholesterol levels were increased in serum-starved SH-SY5Y and SK-N-BE cells after treatment with 1 μM topotecan than that in the cells cultured with 10% FBS (Figures 6D and 6E). This finding was consistent with the upregulation of DHCR24 observed in the two cell types, similar to that in the serum-starved SK-N-SH cells.

In summary, these results indicate that topotecan resistance was induced in serum-starved SK-N-SH and SH-SY5Y cells via increased DNA repair and cholesterol-mediated topotecan efflux. However, in serum-starved SK-N-BE cells, the resistance was predominantly induced by increased cholesterol-topotecan efflux. SH-SY5Y is a third subclone cell line derived from SK-N-SH that demonstrates neuronal function and differentiation (Biedler et al., 1973). Nevertheless, SH-SY5Y cells still share topotecan resistance factors with their parent SK-N-SH cells under nutrient-deprived conditions. Therefore, our study demonstrated the resistance factors, increased DNA repair and/or cholesterol-mediated topotecan efflux applicable to topotecan resistance in all three neuroblastoma cells used in this study and possibly to topotecan resistant tumor cells of the patients.

Discussion

We investigated the dose-dependent effects of the anticancer drug topotecan on SK-N-SH, SH-SY5Y, and SK-N-BE human neuroblastoma cells under serum starvation. Given the difficulty of controlling the tumor burden and substantial toxicity after chemotherapy, it is necessary to develop an effective strategy to improve treatment regimens with higher drug efficacy and fewer adverse effects. To address these issues for topotecan, we studied its pharmacodynamics to understand the mechanism underlying the resistance to a high concentration of topotecan (1 μM) observed in serum-starved SK-N-SH cells. Quantitative proteomic analysis and functional enrichment analysis indicated that DNA damage was decreased, and DNA repair mediated by the ATR-CHK1 pathway was increased in the serum-starved cells to promote survival. Network analysis further suggested that high topotecan concentrations triggered cholesterol-mediated efflux in the cells under serum starvation, contributing to topotecan resistance. DNA damage assay and analyses of the cell cycle and cholesterol in the neuroblastoma cells supported the validity of these resistance factors. Finally, we demonstrated that cholesterol-mediated resistance was generally applicable and DNA repair further accelerated this resistance.

Previously, several mechanisms underlying the development of topotecan resistance have been elucidated using topotecan resistant cells generated via continuous exposure to topotecan (Rasheed and Rubin, 2003). These mechanisms can be categorized into the following: (1) altered accumulation and transport of topotecan, involving reduced accumulation of topotecan due to impaired energy-dependent uptake (Ma et al., 1998) and increased efflux of topotecan via overexpression of ABCB1 (Klejewski et al., 2017) and ABCG2 (Ricci et al., 2016; Yang et al., 2000), (2) mutations of TOP1—such as R364H mutation near the catalytic tyrosine (Urasaki et al., 2001) and E418K mutation (Chang et al., 2002)—that affect the formation of topotecan-stabilized TOP1-DNA complex (irreversible TOP1cc), and (3) altered downstream responses to the formation of the irreversible TOP1cc, including increased DNA repair via overexpression of XRCC1 (Park et al., 2002). These mechanisms can differ from those induced by alterations in tumor microenvironment including nutrient deprivation investigated in this study. The increase in DNA repair could be a shared mechanism in the two resistance models generated by continuous exposure and serum starvation. However, the specific upregulated DNA repair pathways were different in the two resistance models (i.e., ATR-CHK1 DNA repair pathway under serum starvation, and XRCC1-mediated DNA excision repair pathway after continuous exposure to topotecan). Similarly, the efflux of topotecan could be increased in both the resistance models; however, cholesterol-mediated topotecan efflux was increased under serum starvation while ABCB1 or ABCG2-mediated topotecan efflux was upregulated after continuous exposure. Interestingly, serum starvation resulted in the coordinated activation of multiple resistance mechanisms, such as DNA repair and cholesterol-mediated topotecan efflux, thereby leading to reduced DNA damage. However, this coordinated activation of multiple mechanisms was not manifested in the continuous exposure model, probably because the selection of topotecan-resistant cells by continuous exposure ended whenever one of the resistance factors was activated. In contrast, serum starvation can alter multiple cellular pathways to effectively induce the development of resistance against topotecan. Therefore, our results indicate that topotecan resistance should be tested in diverse tumor microenvironments to define a more complete list of resistance factors.

To test the clinical relevance of these resistance factors, it should be evaluated whether alterations in these factors (e.g., upregulation of BLM and DHCR24 representing increased DNA repair and cholesterol-mediated topotecan efflux, respectively) correlate with topotecan resistance in a large cohort of patients with topotecan-sensitive and resistant neuroblastoma. In clinical settings, the alterations in validated resistance factors in a large cohort can be then evaluated in tumor cells from patients prior to topotecan treatment. For example, the abundance of BLM and DHCR24 could be evaluated using immunohistochemistry during histological examinations or by western blotting in primary tumor cells established from tumor tissues. Evaluating whether the abundance of the markers exceeds the threshold values identified in large cohorts can enable the prediction of the therapeutic outcomes of topotecan treatment for individual patients. For patients who are predicted to be resistant to topotecan, alternative therapeutics or options can be recommended, thereby improving the therapeutic strategy for high-risk neuroblastoma.

In this study, we identified upregulated cholesterol synthesis and trafficking that could increase the topotecan efflux using proteomic analysis of serum-starved neuroblastoma cells. However, it is possible that metabolic pathways other than cholesterol synthesis were dysregulated under conditions of serum starvation. For example, the levels of metabolites related to cholesterol, such as sphingolipids and phospholipids, or reactive oxygen species could be altered under serum starvation conditions. Therefore, metabolomic analysis of serum-starved SK-N-SH cells can be employed to identify other altered metabolic pathways that are associated with the development of topotecan resistance. Finally, our approach of integrating pharmacodynamics, proteomics, and network analysis—possibly together with metabolomic analysis—can be employed for diverse chemotherapeutic drugs toward which high-risk cancers show dose-dependent resistance for characterizing the resistance factors and thereby optimizing the therapeutic strategies.

Limitations of the study

Our research discovered the cellular factors (increased DNA repair and cholesterol-mediated topotecan efflux) for topotecan resistance and the mechanistic links of these factors to topotecan resistance in serum-starved neuroblastoma cells that reflect the characteristics of tumor cells located in the deeper region of solid tumors. However, to test the clinical relevance of these findings, it should examined be whether alterations (e.g., upregulation of BLM and DHCR24) correlate with topotecan resistance in a large cohort of patients with topotecan-sensitive and resistant neuroblastoma.

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Hugh I. Kim (hughkim@korea.ac.kr).

Materials availability

This study did not generate new unique reagents.

Data and code availability

The accession number for the the mass spectrometry proteomics data reported in this paper is ProteomeXchange Consortium: PXD014648 via the PRIDE (Perez-Riverol et al., 2019) partner repository.

Methods

All methods can be found in the accompanying Transparent methods supplemental file.

Acknowledgments

This work was supported by the Korea Basic Science Institute (KBSI) National Research Facilities & Equipment Center (NFEC) grant funded by the Korea government (Ministry of Education) (2019R1A6C1010028 and 2020R1A6C103A027) and the Collaborative Genome Program for Fostering New Post-Genome Industry (NRF-2017M3C9A5031597) of the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT, and Future Planning. This work was also supported by the NRF of Korea (2019R1A2C2086193), the National Research Council of Science and Technology of Korea (CRC-15-04-KIST), and the Korea University Future Research Grant. We acknowledge the KBSI for confocal measurements. H.I.K thanks Prof. Min-Sik Kim at Daegu Gyeongbuk Institute of Science & Technology (DGIST) for the critical discussion of the manuscript.

Author contributions

S.Y.C., D.N., A.H., D.I., J.H., C.K., and S.K. conducted the experiments. S.Y.C., A.H., H.I.K., S.-W.L., and D.H. designed the experiments. S.Y.C., D.Y. H., A.H., T.D.L., and D.N. analyzed the data. S.Y.C., D.Y. H., D.N., A.H., J.W.L., H.I.K., S.-W.L., and D.H. wrote the paper.

Declaration of interests

The authors declare no competing financial interests.

Published: April 23, 2021

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.isci.2021.102325.

Contributor Information

Daehee Hwang, Email: daehee@snu.ac.kr.

Sang-Won Lee, Email: sw_lee@korea.ac.kr.

Hugh I. Kim, Email: hughkim@korea.ac.kr.

Supplemental information

Document S1. Transparent methods, Figures S1–S7, and Table S1, related Figure 1,2,4,5, and 6
mmc1.pdf (1.1MB, pdf)
Data S1. The list of peptides and proteins from the proteomics analysis, related Figure 2
mmc2.xlsx (117.4MB, xlsx)
Data S2. The differentially expressed peptides and phosphopeptides and DEPs, related Figure 3
mmc3.xlsx (3.8MB, xlsx)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Transparent methods, Figures S1–S7, and Table S1, related Figure 1,2,4,5, and 6
mmc1.pdf (1.1MB, pdf)
Data S1. The list of peptides and proteins from the proteomics analysis, related Figure 2
mmc2.xlsx (117.4MB, xlsx)
Data S2. The differentially expressed peptides and phosphopeptides and DEPs, related Figure 3
mmc3.xlsx (3.8MB, xlsx)

Data Availability Statement

The accession number for the the mass spectrometry proteomics data reported in this paper is ProteomeXchange Consortium: PXD014648 via the PRIDE (Perez-Riverol et al., 2019) partner repository.

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