Resistance to antibody–drug conjugates (ADCs) has been observed in both preclinical models and clinical studies. However, mechanisms of resistance to pyrrolobenzodiazepine (PBD)-conjugated ADCs have not been well characterized and thus, this study was designed to investigate development of resistance to PBD dimer warheads and PBD-conjugated ADCs. We established a PBD-resistant cell line, 361-PBDr, by treating human breast cancer MDA-MB-361 cells with gradually increasing concentrations of SG3199, the PBD dimer released from the PBD drug-linker tesirine. 361-PBDr cells were over 20-fold less sensitive to SG3199 compared with parental cells and were cross-resistant to other PBD warhead and ADCs conjugated with PBDs. Proteomic profiling revealed that downregulation of Schlafen family member 11 (SLFN11), a putative DNA/RNA helicase, sensitizing cancer cells to DNA-damaging agents, was associated with PBD resistance. Confirmatory studies demonstrated that siRNA knockdown of SLFN11 in multiple tumor cell lines conferred reduced sensitivity to SG3199 and PBD-conjugated ADCs. Treatment with EPZ011989, an EZH2 inhibitor, derepressed SLFN11 expression in 361-PBDr and other SLFN11-deficient tumor cells, and increased sensitivity to PBD and PBD-conjugated ADCs, indicating that the suppression of SLFN11 expression is associated with histone methylation as reported. Moreover, we demonstrated that combining an ataxia telangiectasia and Rad3-related protein (ATR) inhibitor, AZD6738, with SG3199 or PBD-based ADCs led to synergistic cytotoxicity in either resistant 361-PBDr cells or cells that SLFN11 was knocked down via siRNA. Collectively, these data provide insights into potential development of resistance to PBDs and PBD-conjugated ADCs, and more importantly, inform strategy development to overcome such resistance.

Resistance to chemotherapy and targeted therapies is one of the major obstacles for current cancer treatment. Antibody–drug conjugates (ADCs) are a class of effective molecular-targeted therapeutics composed of a target-specific antibody and small-molecule cytotoxic warheads conjugated to the antibody via a chemical linker (1). Clinically approved ADCs, trastuzumab emtansine, brentuximab vedotin, gemtuzumab ozogamicin, inotuzumab ozogamicin, polatuzumab vedotin, enfortumab vedotin, trastuzumab deruxtecan, sacituzumab govitecan, and belantamab mafodotin are effective, but intrinsic and acquired resistance has been observed in the clinic for many of them (2–6). Multiple mechanisms can contribute to resistance to ADCs and development of resistance can depend upon either the specific antigen targeted by the antibody or the warhead conjugated to the antibody. Such mechanisms may include, but are not limited to, altered expression or mutation of the target, modified internalization or trafficking of the internalized ADCs, increased drug efflux via overexpression of drug transporters such as P-glycoprotein, and decreased sensitivity to the warhead (1–6).

Many ADCs conjugated with tesirine (SG3249, ref. 7), a drug linker that releases a synthetic pyrrolobenzodiazepine (PBD) dimer via a cleavable linker, are currently under preclinical and clinical evaluation (8–14). These tesirine-conjugated ADCs release the PBD warhead, SG3199 (7), which induces DNA interstrand crosslinks and causes stalled replication forks to trigger apoptosis, eliciting potent cytotoxicity in vitro and in vivo (7–14). Recent studies reported that specific ATP-binding cassette (ABC) drug transporters and loss of SLC46A3 expression play roles in the development of resistance to PBDs and PBD-based ADCs (15, 16). However, the possibility of developing resistance to PBDs and PBD-conjugated ADCs via alternate, yet unknown mechanisms cannot be ruled out, such as resistance mechanisms related to aberrant DNA damage response (DDR) induced by the SG3199 warhead. A thorough understanding of the development of resistance to PBDs and PBD-conjugated ADCs is imperative for predicting treatment response and for the development of novel treatment strategies that may prevent or overcome the emergence of therapy-resistant tumors.

In this study, we explored the mechanisms leading to resistance to the PBD dimer SG3199. We generated and characterized a PBD-resistant variant of the MDA-MB-361 breast cancer cell line, 361-PBDr. Proteomic analyses and subsequent studies revealed that downregulation of Schlafen family member 11 (SLFN11) protein is associated with resistance to SG3199. SLFN11 is a putative DNA/RNA helicase that is widely reported as a dominant genomic determinant of response to DNA-damaging agents (DDA; ref. 17). In response to DNA damage and replication stress, SLFN11 acts as a unique S-phase checkpoint independent of the ataxia telangiectasia and Rad3-related (ATR) protein kinase/CHK1 pathway. It binds to replication forks, opens chromatin, and irreversibly blocks replication to kill cells. Therefore, downregulation of SLFN11 results in decreased sensitivity to a variety of DDAs (18, 19), and expression levels of SLFN11 might provide a novel biomarker for clinical response to ADCs conjugated with PBD drug linkers. Our data also suggest possible therapeutic strategies to overcome PBD resistance mediated by SLFN11 deficiency including epigenetic derepression of SLFN11 (20) or combining with AZD6738 (21), an inhibitor of ATR that is involved in DDR.

Cell lines and reagents

All cell lines were obtained from the ATCC. Two resistant lines, 361-PBDr and 361-ADCr were generated by continuous exposure of human breast cancer MDA-MB-361 cells to gradually increasing concentrations of SG3199 and MEDI0641, respectively. MDA-MB-361 and two resistant line cells were grown in DMEM (Life Technologies) supplemented with 20% heat-inactivated FBS (Life Technologies). Other cell lines were grown in RPMI1640 (Life Technologies) with 10% FBS. All cells were cultured at 37°C in a humidified, 5% CO2 atmosphere incubator and were authenticated by short tandem repeat (STR) DNA profiling using real-time PCR analyses (IDEXX Bioresearch Laboratories). Moreover, STR profiling confirmed that the 361-PBDr and 361-ADCr cells were consistent with parental MDA-MB-361 cells. All cell lines were negative for Mycoplasma using PCR and the MycoSEQ Mycoplasma Detection Assay Kit (Thermo Fisher Scientific).

MEDI0641 is an ADC that consists of an anti-5T4 human IgG1 mAb, 5T4_0108, with an engineered cysteines for site-specific conjugation of the tesirine drug linker that releases the PBD warhead, SG3199 (22). 5T4-SG3400 is composed of 5T4_0108 site specifically conjugated with the SG3400 drug linker releasing the PBD dimer SG2000 (SJG-136; ref. 23) through a cleavable linker. 5T4-MMETA and 5T4-MMAE are site-specific ADCs conjugated with Lys-MMETA (tubulysin) and vc-MMAE drug-linkers. The 5T4-ADCs were conjugated as described previously and achieved drug to antibody ratio (DAR) of approximately 2 (24). Trastuzumab-ADCs were stochastically conjugated with tesirine, Lys-MMETA and vc-MMAE drug-linkers to achieve DAR of approximately 4. Docetaxel was purchased from Sanofi Aventis. Trastuzumab-DM1 were purchased from Hoffmann-La-Roche. EPZ011989 and camptothecin were purchased from Selleckchem. DM1 and MMAE were purchased from Concortis (Sorrento Therapeutics).

In vitro cytotoxicity assays

Cells in exponential growth phase were seeded in 96-well culture plates at 2,000 to 6,000 cells per well for adherent cells and 1 × 104 cells per well for suspension cells in 80-μL cell culture media (allowed to adhere overnight for adherent cells), and treated with 20 μL of serial dilutions of either ADCs or free drug in duplicate. Treated cells were cultured for another 3 to 6 days and the cell viability was determined by CellTiter-Glo Luminescent Viability Assay (Promega) according to the manufacturer’s protocol. For 3-week assays, fresh media containing various concentrations of MEDI0641 or SG3199 were changed each week. Viability was calculated as a percentage of the viable cells cultured in media or treated with DMSO solvent control. IC50 values for ADCs or free drugs were determined by using logistic nonlinear regression analysis with Prism software (GraphPad).

Flow cytometry

Cells (1 × 105) were incubated with 10 μg/mL 5T4_0108 or 1.25 μg/mL trastuzumab for 1 hour and then anti-human-APC conjugate (Life Technologies) for 30 minutes. Cells were washed twice with PBS, then flow cytometry was performed using a BD LSRII cytometer (Becton Dickinson) and analyzed with FlowJo software (Becton Dickinson).

Quantitative RT-PCR and PCR arrays

Total RNA was extracted using the RNeasy Plus Miniprep Kit (Qiagen) following the manufacturer’ protocols. Residual DNA was digested using the DNA-free DNA Removal Kit following the manufacturer’ instructions (Ambion). The synthesis of cDNA was performed by using the RT2 First Strand Kit (Qiagen). The Human Cancer Drug Resistance and Drug Metabolism RT2 Profiler PCR Arrays (Qiagen) were performed to identify gene expression changes of drug transporters by using RT2 SYBR Green ROX qPCR Mastermix (Qiagen) according to the manufacturer’s instructions. Quantitative RT-PCR was performed by using RT-PCR TaqMan probes (Applied Biosystems). Each sample in duplicate was run in 96-well plates using 7900HT Fast Real-Time PCR System (Applied Biosystems). Data analysis utilized the delta-delta cycle threshold (Ct) method using GAPDH or 18S values to normalize.

SLFN11 siRNA transfection

MDA-MB-361 and DU 145 cells were seeded into 6-well plates at 2 × 105 cells per well and transfected with 50 nmol/L of human SLFN11 or TPBG (5T4) SMARTpools, nontargeting control siRNAs (Dharmacon) with Dharmafect 1 (Dharmacon) on the following day according to manufacturer’s protocols. After 48-hour incubation, the cells were dissociated and seeded into 96-well plates and incubated overnight. CCRF-CEM and THP-1 cells were transfected with 1 μmol/L of Accell human SLFN11 SMARTpool siRNA and Accell control SMARTpool siRNA (Dharmacon) for 72 hours according to manufacturer’s protocols, and seeded into 96-well plates. After plating, cells were treated with SG3199, ADCs ± AZD6738 for cytotoxicity assays.

Western blot analysis

Cells were lysed in cell lysis buffer (Cell Signaling Technology). Lysates containing 50 to 80 μg of protein were separated on 4%–20% SDS-PAGE Precast Gels (Novex). Proteins were transferred onto polyvinylidene difluoride membranes using the iBlot 2 dry blotting system (Life Technologies). Membranes were probed with SLFN11(D2) and CHK1 antibody (Santa Cruz Biotechnology) at 1:100 dilution, or with S100A4, galectin-1, pCHK1(S345), and β-actin antibodies (Cell Signaling Technology) at 1:1,000 dilutions, or with AKR1C3 antibody (R & D Systems) at 1:500 dilution. Goat anti-mouse or anti-rabbit IgG HRP conjugate secondary antibodies (Abcam) were used with dilutions of 1:3,000 and 1:2,000. Signal was detected using SuperSignal West Pico Chemiluminescent substrate (Thermo Fisher Scientific) and membranes were visualized using an Amersham 600 Imaging System (GE Life Sciences).

Proteomic profiling and analyses

Proteomic profiling of 361-PBDr cells compared with parental MDA-MB-361 cells was performed and analyzed. Duplicate samples of 20 million sub-confluent 361-PBDr or MDA-MB-361 cells were lysed using 8 mol/L urea lysis buffer, pH 8.0, containing 20 mmol/L HEPES with protease and phosphatase inhibitors. Cell lysates were reduced and filtered before digesting with Trypsin/Lys-C Mix (Promega). The resulting four peptide samples from two lines were acidified with 0.1% trifluoroacetic acid and desalted using Oasis HLB 96-Well Plates (Waters). These peptides were then labeled with Sixplex Tandem Mass Tag (TMT) reagents (Thermo Fisher Scientific) according to manufacturer’s instructions (25). After labeling, peptides were combined and fractionated using an XBridge BEH C18 column (Waters) to concentrate samples into 16 fractions. The peptide fractions were analyzed using an Orbitrap Fusion Tribrid mass spectrometer interfaced with Dionex Ultimate 3000 RSLCnano LC-MS system operating at 120,000 resolutions over a mass range of 400–1,600 Da. Mass spectrometry data in the raw format were processed using Proteome Discoverer V2.1 software (PD, Thermo Fisher Scientific) integrated with the Mascot V 2.5 (Matrix Science) search engine utilizing the Reference Sequence (RefSeq) human protein database downloaded from NCBI. Unfragmented precursor and TMT reporter ions were removed using the nonfragment filter in the PD workflow. Search parameters included two missed arginine or lysine sites, oxidation of methionine and deamidation of asparagine and glutamine as variable modifications. Carbamidomethyl group on cysteine residue, TMT Sixplex at N-terminus and lysine residue were set as fixed modifications. The mass tolerances on precursor and fragment masses were set at 20 ppm and 0.05 Da, respectively. Percolator algorithm node (26) in PD was used for FDR calculations with cut-off value of 0.05 and peptide spectrum matches with delta Cn value better than 0.05 were automatically selected. Unique peptide spectrum matches with protein information and normalized reporter ion intensity was exported and used for statistical analysis (27). Relative protein abundance was evaluated by comparing replicate samples from 361-PBDr with parental cells and represented as log2 fold change. The cellular component analysis of identified proteins was performed by PD. Proteins with differential expression in 361-PBDr cells were further analyzed by the Perseus computational platform (28) and Ingenuity Pathway Analysis (IPA) software (Qiagen).

Statistical analyses

Synergy was determined using the Bliss independence model described in detail elsewhere (29). The significance of sensitivity differences between control and treated cells in cytotoxicity studies was determined by two-way ANOVA analysis with Prism software (GraphPad).

Generation and characterization of the PBD-resistant 361-PBDr cell line

Sensitivity to SG3199 and MEDI0641 was tested in the MDA-MB-361 breast cancer cell line with high 5T4 expression. Previous cytotoxicity assays of the cell line treated with these test articles typically resulted in a small surviving fraction after the 6-day treatment period (22). To determine whether this surviving population represented intrinsic resistance to either SG3199 or MEDI0641, the treatment phase was extended up to 21 days for the cytotoxicity assays. This resulted in complete eradication of tumor cells by either SG3199 at concentrations ≥0.13 nmol/L or MEDI0641 at concentrations ≥3.13 ng/mL (Fig. 1A). The lack of any surviving fraction suggested that these cells bore no intrinsic resistance to the PBD warhead or to the PBD-conjugated ADC in culture.

Figure 1.

Development and characterization of the PBD-resistant 361-PBDr cell line. A, Response of parental MDA-MB-361 cells to SG3199 or MEDI0641 treated for 21 days. Parental cells were seeded at 5,000 cells per well in 96-well plates, allowed to adhere overnight, and then treated with MEDI0641, isotype control ADC or SG3199. The cells from each treatment group were divided into three groups and cultured for 1 to 3 weeks. During that time, the media was changed on a weekly basis by using fresh culture media with the ADC or PBD warhead. Cell viability was determined each week. Representative experiments are shown, and the values indicate the mean percent cell viability of treated cells ± SD from duplicate wells compared to control cells treated with DMSO or media only. The values of maximal cell killing (max kill) represented the mean percent cell death of cells treated at highest concentrations of SG3199 (2 nmol/L) or MEDI0641 (12 ng/mL) from duplicate wells compared with control cells treated with DMSO or media only. B, Schematic representation of 361-PBDr cell line generation. Acquired resistance to the PBD warhead SG3199 was induced by treating parental MDA-MB-361 breast cancer cells with gradually increasing concentrations of SG3199. C, Enhanced cell proliferation of 361-PBDr cells compared with parental MDA-MB-361 cells. Parental and resistant cells were seeded into 96-well plates at 5,000 cells per well and cell viability was determined on day 6. Representative experiments are shown, and the values indicate the mean percent viability ± SD from duplicate wells with parental cells as control 100%. D, Morphologic changes of 361-PBDr line compared with parental line. Phase contrast images were taken at 400× magnification. Scale bar = 100 μm. E, Sensitivity of two cell lines to SG3199 and MEDI0641, a 5T4-targeting ADC conjugated with PBD payloads. Parental cells and 361-PBDr cells were seeded at 5,000 cells per well in 96-well plates, allowed to adhere overnight, and then treated with SG3199 or MEDI0641. Cell viability was determined on day 6. Representative experiments are shown, and the values indicate the mean percent cell viability of treated cells ± SD from duplicate wells compared to control cells treated with DMSO or media only. F, Relative 5T4 surface expression of 361-PBDr cells compared with parental line cells was determined by flow cytometry. The numbers in bold on each histogram represent the fold change in mean fluorescence intensity for cells stained with an anti-5T4 antibody compared with cells stained with isotype control.

Figure 1.

Development and characterization of the PBD-resistant 361-PBDr cell line. A, Response of parental MDA-MB-361 cells to SG3199 or MEDI0641 treated for 21 days. Parental cells were seeded at 5,000 cells per well in 96-well plates, allowed to adhere overnight, and then treated with MEDI0641, isotype control ADC or SG3199. The cells from each treatment group were divided into three groups and cultured for 1 to 3 weeks. During that time, the media was changed on a weekly basis by using fresh culture media with the ADC or PBD warhead. Cell viability was determined each week. Representative experiments are shown, and the values indicate the mean percent cell viability of treated cells ± SD from duplicate wells compared to control cells treated with DMSO or media only. The values of maximal cell killing (max kill) represented the mean percent cell death of cells treated at highest concentrations of SG3199 (2 nmol/L) or MEDI0641 (12 ng/mL) from duplicate wells compared with control cells treated with DMSO or media only. B, Schematic representation of 361-PBDr cell line generation. Acquired resistance to the PBD warhead SG3199 was induced by treating parental MDA-MB-361 breast cancer cells with gradually increasing concentrations of SG3199. C, Enhanced cell proliferation of 361-PBDr cells compared with parental MDA-MB-361 cells. Parental and resistant cells were seeded into 96-well plates at 5,000 cells per well and cell viability was determined on day 6. Representative experiments are shown, and the values indicate the mean percent viability ± SD from duplicate wells with parental cells as control 100%. D, Morphologic changes of 361-PBDr line compared with parental line. Phase contrast images were taken at 400× magnification. Scale bar = 100 μm. E, Sensitivity of two cell lines to SG3199 and MEDI0641, a 5T4-targeting ADC conjugated with PBD payloads. Parental cells and 361-PBDr cells were seeded at 5,000 cells per well in 96-well plates, allowed to adhere overnight, and then treated with SG3199 or MEDI0641. Cell viability was determined on day 6. Representative experiments are shown, and the values indicate the mean percent cell viability of treated cells ± SD from duplicate wells compared to control cells treated with DMSO or media only. F, Relative 5T4 surface expression of 361-PBDr cells compared with parental line cells was determined by flow cytometry. The numbers in bold on each histogram represent the fold change in mean fluorescence intensity for cells stained with an anti-5T4 antibody compared with cells stained with isotype control.

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We further investigated whether the cells could develop acquired resistance to SG3199. MDA-MB-361 cells were treated with gradually increasing drug concentrations ranging from 0.002 to 0.2 nmol/L of SG3199 and were cultured for about 15 months at which point no additional enhanced resistance was observed (Fig. 1B). A single-cell clone, 361-PBDr, resistant to SG3199, was selected by serial dilution culture. The prolonged treatment of SG3199 induced enhanced cell growth and significant morphologic changes (Fig. 1C and D). 361-PBDr cells form large adherent patches, compact multilayered colonies with a thick center and a thin smooth margin in culture.

Sensitivity of 361-PBDr cells to SG3199 decreased approximately 20-fold compared with parental MDA-MB-361 cells (Fig. 1E; Table 1). Significant cross-resistance between SG3199 and ADCs delivering SG3199, MEDI0641 and trasuzumab-SG3249 were observed. The reduced sensitivity to SG3199 and MEDI0641 remained essentially unchanged over the course of culture in growth medium devoid of SG3199 for 24 weeks, confirming that the 361-PBDr cell line has a stable resistant phenotype (Supplementary Fig. S1A and S1B).

Table 1.

Resistance profile of the 361-PBDr cell line to free drugs and ADCs.

MDA-MB-361361-PBDr
Free drugIC50 (nmol/L)Relative resistance (fold change in IC50)a
SG3199 0.01 0.21 21.0 
SG2000 0.19 1.80 9.5 
MMETA (tubulysin) 0.16 0.25 1.6 
MMAE 0.24 0.65 2.7 
Camptothecin 14.51 34.56 2.4 
DM1 1.57 2.02 1.1 
Docetaxel 3.17 3.59 1.1 
MDA-MB-361361-PBDr
Free drugIC50 (nmol/L)Relative resistance (fold change in IC50)a
SG3199 0.01 0.21 21.0 
SG2000 0.19 1.80 9.5 
MMETA (tubulysin) 0.16 0.25 1.6 
MMAE 0.24 0.65 2.7 
Camptothecin 14.51 34.56 2.4 
DM1 1.57 2.02 1.1 
Docetaxel 3.17 3.59 1.1 
ADCIC50 (ng/mL)
MEDI0641 0.18 ∼4,000 22,222 
5T4-SG3400 3.38 >4,000 1,183.4 
5T4-MMETA 0.44 3.94 9.0 
5T4-MMAE 4.35 40.15 9.2 
Trastuzumab-SG3249 2.03 >4,000 1,970.4 
Trastuzumab-MMETA 0.69 ∼43.19 62.6 
Trastuzumab-MMAE 6.06 ∼1,000 165.0 
Trastuzumab-DM1 0.47 ∼142.10 302.3 
ADCIC50 (ng/mL)
MEDI0641 0.18 ∼4,000 22,222 
5T4-SG3400 3.38 >4,000 1,183.4 
5T4-MMETA 0.44 3.94 9.0 
5T4-MMAE 4.35 40.15 9.2 
Trastuzumab-SG3249 2.03 >4,000 1,970.4 
Trastuzumab-MMETA 0.69 ∼43.19 62.6 
Trastuzumab-MMAE 6.06 ∼1,000 165.0 
Trastuzumab-DM1 0.47 ∼142.10 302.3 

Note: Parental and resistant 361-PBDr line cells were treated with indicated ADCs or free drugs. The cytotoxicity was assessed as indicated in Materials and Methods. Data are mean IC50 from multiple experiments (n ≥ 2) for each ADC or free drug.

aThe relative resistance values were calculated on the basis of the fold change in IC50 values for each free drug/ADC in 361-PBDr cells versus parental MDA-MB-361 cells.

The development of SG3199 resistance in the 361-PBDr cells also conferred resistance to other PBD warhead (Table 1). 361-PBDr cells were 9.5-fold less sensitive to the free PBD warhead, SG2000, and was 1,183-fold less sensitive to 5T4-SG3400, an ADC that releases the SG2000 warhead. The resistant line demonstrated moderate cross-resistance to other 5T4-targeting ADCs, regardless of payload such as 5T4-MMETA and 5T4-MMAE conjugated with either tubulysin or auristatin warheads, respectively. There was also moderate resistance of 361-PBDr cells to HER2-targeting ADCs, such as trastuzumab-MMETA, trastuzumab-MMAE, and trasuzumab-DM1. However, the cells were significantly more refractory to PBD-based ADCs than to ADCs conjugated with MMETA, MMAE, or DM1 payloads. Importantly, the cells did not display decreased sensitivity to free maytansine warheads or docetaxel, and showed only slight resistance to camptothecin, tubulysin, and auristatin (Table 1). These results with free warheads imply that the mechanisms rendering resistance to PBDs do not translate to decreased sensitivity to other warhead classes and suggest the development of PBD-specific resistance. Given that there was a slight or moderate decrease in sensitivity to the ADCs targeting 5T4 or HER2 with non-PBD warheads, we investigated whether downregulation of target expression could be responsible. Interestingly, the level of 5T4 expression in 361-PBDr cells was roughly half of the surface expression of 5T4 on parental MDA-MB-361 cells as determined by flow cytometry (Fig. 1F). Downregulation of HER2 on the surface of 361-PBDr cells compared with parental cells was also observed (Supplementary Fig. S1C).

Proteomic profiling of 361-PBDr indicates multifactorial resistance mechanisms

Quantitative proteomics is driving the discovery of new biomarkers. Differentially expressed proteins (DEP) between parental MDA-MB-361 and resistant 361-PBDr cells might directly or indirectly contribute to drug sensitivity. To investigate this possibility, we applied nanoflow liquid chromatography and TMT quantitative mass spectrometry to obtain a global view of the proteomic profile associated with SG3199-induced drug resistance (Fig. 2A). In total, over 8,160 proteins were identified and quantified in samples of parental MDA-MB-361 and resistant 361-PBDr cells, and these cover a variety of cellular compartments (Fig. 2B). Pairwise comparison identified 2,098 proteins that were differentially expressed (1,081 upregulated and 1,017 downregulated) in 361-PBDr cells compared with MDA-MB-361 cells with a threshold log2 fold change in expression of ≥0.45 or ≤−0.45 (Supplementary Table S1). Many DEPs are associated with drug resistance in cancers including, but not limited to, SLFN11 (decreased log2 −0.82-fold), S100A4 (increased log2 3.38-fold), galectin-1 (LGALS1, increased log2 2.71-fold), and AKR1C3 (increased log2 3.02-fold; Fig. 2C; ref. 18, 30–32). RT-PCR and Western blot analyses confirmed the significant downregulation of SLFN11 and upregulation of S100A4, AKR1C3, and galectin-1 observed in the proteomic analyses (Fig. 2D and E). Pathway analysis of DEPs revealed significant changes in protein expression in key cellular and molecular functions, such as cell growth and proliferation, cell death and survival, cell cycle, and DNA replication, recombination, and repair (Fig. 3A). Indeed, 361-PBDr cells exhibited increased cell growth and proliferation compared with parental cells (Fig. 1C).

Figure 2.

Proteomic profiling of 361-PBDr cells identified differentially expressed proteins. A, Experimental workflow of the quantitative proteomic profiling. Equal numbers of cells were lysed from duplicate samples of two cell lines. Extracted proteins was digested into tryptic peptides, which were labeled by TMT and analyzed by HPLC-MS/MS. Proteins were subsequently identified and quantified. B, Cellular localization analysis of the identified proteins. C, Volcano plot summarizing protein quantification results of 361-PBDr cells compared with parental cells. Shaded regions indicate DEPs with log2 fold change ≥0.45 or ≤−0.45 and significance P < 0.05. D, Quantitative RT-PCR assessed the differential RNA expression in 361-PBDr cells compared with parental cells. Relative mRNA abundance are represented as fold change in 361-PBDr cells compared with parental cells ± SD from two experiments. E, Western blot analysis demonstrated the differential protein expression of SLFN11, S100A4, AKR1C3, and galectin-1 in resistant 361-PBDr cells compared with parental MDA-MB-361 cells.

Figure 2.

Proteomic profiling of 361-PBDr cells identified differentially expressed proteins. A, Experimental workflow of the quantitative proteomic profiling. Equal numbers of cells were lysed from duplicate samples of two cell lines. Extracted proteins was digested into tryptic peptides, which were labeled by TMT and analyzed by HPLC-MS/MS. Proteins were subsequently identified and quantified. B, Cellular localization analysis of the identified proteins. C, Volcano plot summarizing protein quantification results of 361-PBDr cells compared with parental cells. Shaded regions indicate DEPs with log2 fold change ≥0.45 or ≤−0.45 and significance P < 0.05. D, Quantitative RT-PCR assessed the differential RNA expression in 361-PBDr cells compared with parental cells. Relative mRNA abundance are represented as fold change in 361-PBDr cells compared with parental cells ± SD from two experiments. E, Western blot analysis demonstrated the differential protein expression of SLFN11, S100A4, AKR1C3, and galectin-1 in resistant 361-PBDr cells compared with parental MDA-MB-361 cells.

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Figure 3.

Resistance of 361-PBDr may be due to enriched DEPs involved in cell growth and DDR, while drug efflux pumps do not appear to play a role. A, Molecular function analysis of DEPs by IPA (Qiagen). B, DEPs in 361-PBDr cells related to increased DDR. The data represent the results from two duplicated samples for each cell line. C, No significant upregulation of drug efflux transporters in 361-PBDr cells. RNA expression (left) and protein expression (right) of various drug transporters in 361-PBDr cells compared with parental line cells were determined with an RT-PCR Array from Qiagen and proteomic profiling, respectively. Relative mRNA and protein abundance are represented as log2 fold change in 361-PBDr cells compared with parental cells ± SD from two experiments. No protein levels ABCB1 or ABCG2 were detectable in either cell line.

Figure 3.

Resistance of 361-PBDr may be due to enriched DEPs involved in cell growth and DDR, while drug efflux pumps do not appear to play a role. A, Molecular function analysis of DEPs by IPA (Qiagen). B, DEPs in 361-PBDr cells related to increased DDR. The data represent the results from two duplicated samples for each cell line. C, No significant upregulation of drug efflux transporters in 361-PBDr cells. RNA expression (left) and protein expression (right) of various drug transporters in 361-PBDr cells compared with parental line cells were determined with an RT-PCR Array from Qiagen and proteomic profiling, respectively. Relative mRNA and protein abundance are represented as log2 fold change in 361-PBDr cells compared with parental cells ± SD from two experiments. No protein levels ABCB1 or ABCG2 were detectable in either cell line.

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Many proteins involved in DDR were differentially expressed in 361-PBDr cells. SLFN11 that sensitizes cancer cells to DDA was downregulated. ATR and ataxia-telangiectasia mutated (ATM) that coordinate cell cycle with DDR, and other proteins involved in homologous recombination (FANCD2, FANCI, HAT1, MDC1, BRCA1), nucleotide excision repair (DDB2, XPC), base excision repair (LIG3), nonhomologous end joining (XRCC4, PARP2) etc. were upregulated (Fig. 3B). The data indicated coordinated response of various DDR pathways to SG3199-induced DNA damage and increased DNA repair in 361-PBDr cells.

No significant role of drug transporters for acquired resistance of 361-PBDr

Overexpression of ABC drug transporters that actively efflux a variety of amphipathic compounds can cause multidrug resistance (MDR) in cancer cells. It is known that SG3199 is moderately susceptibility to ABCB1 (8), and moreover, it was recently reported that ABCC2 and ABCG2 are involved in acquired resistance to PBD-conjugated ADCs in Karpas-299 and NCI-N87 cells (15). We assessed expression of these transporters in 361-PBDr cells via proteomic profiling and a quantitative PCR array. There was no upregulation of ABCB1, ABCC2, ABCG2, or other transporters, and in fact, protein expression was either nonexistent or downregulated in the 361-PBDr cells (Fig. 3C). This is consistent with the observation that 361-PBDr cells exhibit no significant cross-resistance to other free warheads or docetaxel that are known to be substrates for efflux drug pumps (Table 1). Taken together, the data suggest that increased expression of drug efflux pumps is not significantly involved in resistance to PBD warheads in this setting.

Derepression of SLFN11 increases sensitivity to PBD warhead and ADC

Many DEPs were identified in 361-PBDr cells that potentially contributed to PBD resistance through multifactorial resistance mechanisms. Of particular interest was downregulated SLFN11. SLFN11 irreversibly blocks DNA replication to kill cells in response to DNA damage and replication stress, and decreased SLFN11 expression is correlated with decreased sensitivity to a variety of DDAs (18–19, 33). SLFN11 deficiency is observed in approximately half of the NCI-60 tumor cell panel (17) and epigenetic mechanisms regulate SLFN11 expression in various tumor cells and tissues (20, 34, 35). Enhancer of zeste homolog 2 (EZH2) mediates histone methylation and marked deposition of H3K27me3 within the SLFN11 gene body, and derepression of SLFN11 can be achieved by treatment with an EZH2 inhibitor (20). Given the role that SLFN11 plays in response to DDAs, we hypothesized that downregulation of SLFN11 in 361-PBDr cells is contributing to the resistance of 361-PBDr cells to DNA cross-linking PBDs and PBD conjugates.

To rescue SLFN11 expression in 361-PBDr cells, we cultured the cells in the presence of 10 μmol/L of the EZH2 inhibitor, EPZ011989 (EPZ) for 10 days. Significantly increased SLFN11 expression was observed (Fig. 4A) and EPZ-treated cells showed increased sensitivity to SG3199 and MEDI0641 (Fig. 4B). We further examined the correlation between SLFN11 protein levels (Western blot analysis) and sensitivity to the SG3199 PBD dimer (IC50 from cytotoxicity curves) in a broad panel of cancer cell lines. Generally, there was an inverse correlation between SLFN11 expression and derived IC50 values (Fig. 4C). Cell lines with high SLFN11 expression were more sensitive to SG3199, that is, displayed lower IC50 values, whereas the highest IC50 values were observed in cell lines with low/no levels of SLFN11. However, this correlation was not evident in certain cell lines. For example, SLFN11-deficient HCT116 colorectal carcinoma line cells were quite sensitive to SG3199 with an IC50 approximately 0.13 nmol/L. While HCT116 cells with very low level of Mre11 expression are defective in Mre11/Rad50/Nbs1 (MRN) complex and S-phase arrest as reported (36). The defects elicit sensitivity to DDAs through synthetic lethality and thus SLFN11-independent mechanisms may be responsible for this high SG3199 sensitivity.

Figure 4.

SLFN11 expression is associated with sensitivity to SG3199 and ADCs conjugated with PBD warheads A, The EZH2 inhibitor, EPZ, rescues SLFN11 expression. Western blot analysis and RT-PCR illustrated the derepressed SLFN11 in 361-PBDr cells treated with 10 μmol/L of EPZ for 10 days. B, EPZ increases sensitivity of 361-PBDr cells. 361-PBDr cells after EPZ treatment were dissociated and seeded in 96-well plates, incubated overnight and treated with SG3199 or MEDI0641. Cell viability was determined on day 6. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) from duplicate wells compared with control cells treated with DMSO or media. Two-way ANOVA analysis P < 0.001. C, SLFN11 expression is inversely correlated with the IC50 value for SG3199 in a panel of human hematologic and solid tumor cell lines. SLFN11 expression was illustrated by Western blot analysis (positive = 1, negative = 0). Pearson correlation coefficient (r) is −0.612 and P value is 0.007. D, EPZ rescued SLFN11 expression and increased the sensitivity to SG3199 in SLFN11-deficient K562 and NCI-H82 cells. Cells were cultured in the presence of 5 μmol/L of EPZ or DMSO control for 5 and 10 days, respectively. Cells were washed to remove EPZ, then seeded into 96-well plates at 1 × 104 per well. They were treated with SG3199 and viability was determined on day 3. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) from duplicate wells compared with control cells treated with DMSO. Two-way ANOVA analysis P < 0.001. Western blot analyses illustrated SLFN11 expression of K562 and NCI-H82 cells after treatment with EPZ or DMSO control. E, Loss of SLFN11 confers resistance to SG3199 and ADCs conjugated with PBD warheads. Cell lines were transfected with nontargeting control or SLFN11 siRNA in 6-well plates. After 48 hours, the MDA-MB-361 and DU 145 cells were dissociated and seeded into 96-well plates at 6,000 or 3,000 cells per well, respectively, allowed to adhere overnight, then treated with SG3199, MEDI0641, or trastuzumab-SG3249. The viability was determined on day 3. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) from duplicate wells compared with control cells treated with DMSO or media.Two-way ANOVA analysis P < 0.001. Loss of SLFN11 via siRNA did not impact proliferation of MDA-MB-361 or DU 145 cells. MDA-MB-361 and DU 145 cells after 48 hour transfection were dissociated and seeded into 96-well plates at 6,000 or 3,000 cells per well, respectively. The cell viability was determined on day 4. Representative experiments are shown, and the values indicate the mean percent viability ± SD from duplicate wells with the viability of the cells treated with control siRNA as 100%. Decreased expression of SLFN11 expression after 72 hours of siRNA transfection was confirmed via Western blot analyses and RT-PCR. The relative RNA expression of the cells treated with control siRNA was calculated as 100%. F, Knocked-down expression of SLFN11 also conferred PBD resistance in hematologic malignancy cell lines, CCRF-CEM and THP-1. Two cell lines were transfected with Accell nontargeting control or SLFN11 siRNA for 72 hours, then seeded in 96-well plates at 1 × 104 per well, treated with SG3199. The cell viability was determined on day 3. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) from duplicate wells compared with control cells treated with DMSO. Two-way ANOVA analysis P < 0.001. Decreased SLFN11 expression was confirmed via Western blots and RT-PCR after 72 hours of siRNA transfection. The relative RNA expression of the cells treated with control siRNA was calculated as 100%.

Figure 4.

SLFN11 expression is associated with sensitivity to SG3199 and ADCs conjugated with PBD warheads A, The EZH2 inhibitor, EPZ, rescues SLFN11 expression. Western blot analysis and RT-PCR illustrated the derepressed SLFN11 in 361-PBDr cells treated with 10 μmol/L of EPZ for 10 days. B, EPZ increases sensitivity of 361-PBDr cells. 361-PBDr cells after EPZ treatment were dissociated and seeded in 96-well plates, incubated overnight and treated with SG3199 or MEDI0641. Cell viability was determined on day 6. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) from duplicate wells compared with control cells treated with DMSO or media. Two-way ANOVA analysis P < 0.001. C, SLFN11 expression is inversely correlated with the IC50 value for SG3199 in a panel of human hematologic and solid tumor cell lines. SLFN11 expression was illustrated by Western blot analysis (positive = 1, negative = 0). Pearson correlation coefficient (r) is −0.612 and P value is 0.007. D, EPZ rescued SLFN11 expression and increased the sensitivity to SG3199 in SLFN11-deficient K562 and NCI-H82 cells. Cells were cultured in the presence of 5 μmol/L of EPZ or DMSO control for 5 and 10 days, respectively. Cells were washed to remove EPZ, then seeded into 96-well plates at 1 × 104 per well. They were treated with SG3199 and viability was determined on day 3. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) from duplicate wells compared with control cells treated with DMSO. Two-way ANOVA analysis P < 0.001. Western blot analyses illustrated SLFN11 expression of K562 and NCI-H82 cells after treatment with EPZ or DMSO control. E, Loss of SLFN11 confers resistance to SG3199 and ADCs conjugated with PBD warheads. Cell lines were transfected with nontargeting control or SLFN11 siRNA in 6-well plates. After 48 hours, the MDA-MB-361 and DU 145 cells were dissociated and seeded into 96-well plates at 6,000 or 3,000 cells per well, respectively, allowed to adhere overnight, then treated with SG3199, MEDI0641, or trastuzumab-SG3249. The viability was determined on day 3. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) from duplicate wells compared with control cells treated with DMSO or media.Two-way ANOVA analysis P < 0.001. Loss of SLFN11 via siRNA did not impact proliferation of MDA-MB-361 or DU 145 cells. MDA-MB-361 and DU 145 cells after 48 hour transfection were dissociated and seeded into 96-well plates at 6,000 or 3,000 cells per well, respectively. The cell viability was determined on day 4. Representative experiments are shown, and the values indicate the mean percent viability ± SD from duplicate wells with the viability of the cells treated with control siRNA as 100%. Decreased expression of SLFN11 expression after 72 hours of siRNA transfection was confirmed via Western blot analyses and RT-PCR. The relative RNA expression of the cells treated with control siRNA was calculated as 100%. F, Knocked-down expression of SLFN11 also conferred PBD resistance in hematologic malignancy cell lines, CCRF-CEM and THP-1. Two cell lines were transfected with Accell nontargeting control or SLFN11 siRNA for 72 hours, then seeded in 96-well plates at 1 × 104 per well, treated with SG3199. The cell viability was determined on day 3. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) from duplicate wells compared with control cells treated with DMSO. Two-way ANOVA analysis P < 0.001. Decreased SLFN11 expression was confirmed via Western blots and RT-PCR after 72 hours of siRNA transfection. The relative RNA expression of the cells treated with control siRNA was calculated as 100%.

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To strengthen the findings in the 361-PBDr cells, we investigated the effect of SLFN11 derepression with EPZ on cell lines shown to have SLFN11 deficiency. Treatment with 5 μmol/L EPZ for 5 or 10 days rescued SLFN11 expression in K562 chronic myeloid leukemia cells and NCI-H82 lung cancer cells, respectively, and enhancement of SG3199 sensitivity was observed (Fig. 4D). Taken together, these data suggest that SLFN11 expression can be regulated via histone methylation in those cells, and downregulated SLFN11 is at least partially contributing to the development of PBD resistance in 361-PBDr cells.

SLFN11 associated with the sensitivity to PBD and PBD-conjugated ADCs

To confirm the role of SLFN11 deficiency in resistance to PBD and PBD-based ADCs, we evaluated whether knockdown of SLFN11 gene expression via siRNA was able to induce resistance of parental MDA-MB-361 cells to SG3199 and PBD-conjugated ADCs. SLFN11 knockdown in parental cells conferred resistance to SG3199, and to MEDI0641 and trastuzumab-SG3249 that release the SG3199 warhead (Fig. 4E). In addition, silencing SLFN11 in DU 145 prostate cancer cells, known to have high levels of SLFN11, also induced significant resistance to SG3199 and MEDI0641. Trastuzumab-SG3249 was not tested in DU 145 cells because of their low HER2 expression. SLFN11 knockdown had no impact on proliferation of either cell line (Fig. 4E). Moreover, siRNA knockdown of SLFN11 in the hematologic cancer cell lines, CCRF-CEM (ALL) and THP-1 (AML), reduced SLFN11 expression that coincided with decreased sensitivity to SG3199 (Fig. 4F). The data demonstrate that silencing SLFN11 expression in various tumor cells correlates with decreased sensitivity to PBDs.

Combination of AZD6738, an ATR inhibitor, to overcome the resistance to PBDs and ADCs bearing PBD

PBDs form interstrand DNA crosslinks leading to replicative damage that activates the ATR pathway for DNA repair (9). Moderate ATR upregulation was observed in 361-PBDr cells (log2 0.55-fold, Fig. 3B; Supplementary Table S1). Given that inhibition of ATR can restore sensitivity to DDA in SLFN11-deficient settings (19, 37, 38), we hypothesized that ATR inhibition may reverse the PBD resistance caused by SLFN11 deficiency. Treatment with sublethal concentrations (0.5 or 1 μmol/L) of the ATR inhibitor AZD6738 (Supplementary Fig. S2A) significantly enhanced the sensitivity of 361-PBDr cells to SG3199, MEDI0641, or trastuzumab-SG3249 (Fig. 5A). Using the Bliss independence dose–response surface model to analyze multipoint dose curve combinations of SG3199 and AZD6738, data confirmed synergistic activity of the combination in 361-PBDr cells (Fig. 5B), whereas no obvious synergy was observed for combinations of AZD6738 with either SG3199 or PBD-conjugated ADCs in parental MDA-MB-361 cells (Supplementary Fig. S2C and S2D), although the parental cells were more sensitive to AZD6738 (Supplementary Fig. S2B). Western blot analysis showed that CHK1 phosphorylation induced by SG3199 and MEDI0641 was inhibited by combining with AZD6738, confirming that AZD6738 was targeting the ATR/CHK1 pathway (Fig. 5C). Furthermore, we investigated whether AZD6738 can enhance sensitivity to PBD warheads and PBD-based ADCs when SLFN11 is knocked down via siRNA in parental cells. Treatment with 0.5 μmol/L AZD6738 completely restored sensitivity to either the PBD warhead or to PBD-based ADCs (Fig. 5D). The synergistic effect of AZD6738 with SG3199 was also observed in CCRF-CEM ALL cells whose SLFN11 expression was knocked down via siRNA1(Fig. 5E). Taken together, the data suggest that treatment with AZD6738 could overcome the resistance to PBDs mediated by SLFN11 deficiency.

Figure 5.

The addition of the ATR inhibitor, AZD6738, reversed the resistance of tumor cells to SG3199 and ADCs conjugated with SG3199. A, Sensitivity shift of resistant 361-PBDr cells to SG3199, MEDI0641, and trastuzumab-SG3249 upon addition of sublethal concentrations of AZD6738. The cells were seeded into 96-well plates at 5,000 cells per well, incubated overnight, then treated with SG3199 or ADC in the presence or absence of sublethal concentrations (0.5 or 1 μmol/L) of AZD6738. The cell viability was measured on day 6. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) from duplicate wells compared with control cells. B, The 361-PBDr cells were seeded in 384-well plates at 3,000 cells per well, incubated overnight, then treated with AZD6738 and SG3199 in a 5 × 9 concentration grid. Cell viability was determined on day 5. Curves indicate the mean percentage of viable cells (± SD) with treatment relative to the mean of DMSO controls from quadruplicate wells (left). Cell viability data were analyzed by the Bliss independence model to assess potential synergy. Color-coded matrix displays the effect of synergy or antagonism, with darker blue colors corresponding to higher inhibition values indicative of greater synergy (middle). C, Western blot analysis of pCHK1 (S345), CHK1, and actin in 361-PBDr cells treated with 1 nmol/L SG3199, 1 μg/mL MEDI0641, and 1 μmol/L AZD6738 alone or combination for 16 hours. D, Sensitivity shift of SLFN11-deficient MDA-MB-361 cells to SG3199, MEDI0641, and trastuzumab-SG3249 upon the addition of a sublethal concentration of AZD6738. Parental MDA-MB-361 cells were transfected with nontargeting control or SLFN11 siRNA in 6-well plates. After 48 hours, the cells were dissociated and seeded into 96-well plates at 6,000 cells per well, cultured overnight, then treated with various concentrations of SG3199, MEDI0641, or trastuzumab-SG3249 in the presence or absence of 0.5 μmol/L AZD6738. The cell viability was measured on day 3. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) relative to the mean of 0 nmol/L SG3199 control or 0 ng/mL ADC controls in the presence or absence of AZD6738 treatment from duplicate wells. Two-way ANOVA analysis P < 0.001. E, AZD6738 treatment restores SG3199 sensitivity in SLFN11-deficient CCRF-CEM cells. The cells were transfected with Accell nontargeting control or SLFN11 siRNA. After 72 hours, the cells were seeded into 96-well plates at 1 × 104 cells per well and treated with SG3199 in the presence or absence of 0.5 μmol/L AZD6738. The cell viability was measured on day 3. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) relative to the mean of 0 nmol/L SG3199 control in the presence or absence of AZD6738 treatment from duplicate wells. Two-way ANOVA analysis P < 0.001.

Figure 5.

The addition of the ATR inhibitor, AZD6738, reversed the resistance of tumor cells to SG3199 and ADCs conjugated with SG3199. A, Sensitivity shift of resistant 361-PBDr cells to SG3199, MEDI0641, and trastuzumab-SG3249 upon addition of sublethal concentrations of AZD6738. The cells were seeded into 96-well plates at 5,000 cells per well, incubated overnight, then treated with SG3199 or ADC in the presence or absence of sublethal concentrations (0.5 or 1 μmol/L) of AZD6738. The cell viability was measured on day 6. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) from duplicate wells compared with control cells. B, The 361-PBDr cells were seeded in 384-well plates at 3,000 cells per well, incubated overnight, then treated with AZD6738 and SG3199 in a 5 × 9 concentration grid. Cell viability was determined on day 5. Curves indicate the mean percentage of viable cells (± SD) with treatment relative to the mean of DMSO controls from quadruplicate wells (left). Cell viability data were analyzed by the Bliss independence model to assess potential synergy. Color-coded matrix displays the effect of synergy or antagonism, with darker blue colors corresponding to higher inhibition values indicative of greater synergy (middle). C, Western blot analysis of pCHK1 (S345), CHK1, and actin in 361-PBDr cells treated with 1 nmol/L SG3199, 1 μg/mL MEDI0641, and 1 μmol/L AZD6738 alone or combination for 16 hours. D, Sensitivity shift of SLFN11-deficient MDA-MB-361 cells to SG3199, MEDI0641, and trastuzumab-SG3249 upon the addition of a sublethal concentration of AZD6738. Parental MDA-MB-361 cells were transfected with nontargeting control or SLFN11 siRNA in 6-well plates. After 48 hours, the cells were dissociated and seeded into 96-well plates at 6,000 cells per well, cultured overnight, then treated with various concentrations of SG3199, MEDI0641, or trastuzumab-SG3249 in the presence or absence of 0.5 μmol/L AZD6738. The cell viability was measured on day 3. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) relative to the mean of 0 nmol/L SG3199 control or 0 ng/mL ADC controls in the presence or absence of AZD6738 treatment from duplicate wells. Two-way ANOVA analysis P < 0.001. E, AZD6738 treatment restores SG3199 sensitivity in SLFN11-deficient CCRF-CEM cells. The cells were transfected with Accell nontargeting control or SLFN11 siRNA. After 72 hours, the cells were seeded into 96-well plates at 1 × 104 cells per well and treated with SG3199 in the presence or absence of 0.5 μmol/L AZD6738. The cell viability was measured on day 3. Representative experiments are shown, and curves indicate the mean percentage of viable cells (± SD) relative to the mean of 0 nmol/L SG3199 control in the presence or absence of AZD6738 treatment from duplicate wells. Two-way ANOVA analysis P < 0.001.

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Resistance to ADCs can occur though modulation of the target (mutations, downregulation, altered internalization/trafficking/recycling, etc.) or through reduced sensitivity to the warhead delivered by the ADC (increased efflux, pathway alterations, reduced lysosomal escape, etc.). Significant downregulation of 5T4 was observed in separate studies using cell models that acquired resistance to MEDI0641 (Supplementary Fig. S3) and thus we focused our efforts on identifying mechanisms that drive resistance to the warhead. We established a cell line, 361-PBDr, that developed acquired resistance to the PBD warhead SG3199 as an unconjugated molecule or delivered via ADC.

361-PBDr cells exhibited 20-fold decreased sensitivity to SG3199 compared with parental cells. It is important to note that the 361-PBDr cells were also resistant to the PBD analog SG2000 suggesting that the resistance mechanisms may be applicable to ADCs bearing various PBD warheads, though further studies are warranted to determine whether this is a pan-PBD effect or whether there are certain structural motifs that lead to the development of resistance to certain classes of PBDs. Development of PBD resistance did not carry over into other warhead classes as the 361-PBDr cells maintained their sensitivity to free tubulysin, auristatin, and maytansinoid warheads indicating that PBD-specific mechanisms are driving resistance to PBDs and PBD conjugates in 361-PBDr cells.

Given that drug efflux transporters can be a contributing factor to the development of resistance to various ADC warheads, and a recent report that ABCG2 and ABCC2 have implicated in acquired resistance to SG3199 (15), we evaluated levels of these efflux pumps in our 361-PBDr cells. Unlike the Corbett and colleagues’ article, we did not observe any increased expression of various ABC transporters in our PBD-resistant cells. This could be due to many factors. We used a different cell line (MDA-MB-361 vs. Karpas-299 and NCI-N87), and extended treatment with SG3199 to induce resistance while they used pulsatile dosing with either the warhead or SG3199-conjugated ADCs. It should be noted that the decrease in SG3199 IC50 values of their resistant cell lines were much less than what we observed: approximately 3- to 4-fold decrease in IC50 values compared to the 20-fold decreased sensitivity we observed with our 361-PBDr cells.

One interesting observation was the moderate downregulation of both 5T4 and HER2 in 361-PBDr cells after prolonged in vitro culture and treatment with SG3199. Currently, we do not know the mechanisms leading to downregulation of these proteins. Corbett and colleagues also reported a similar decrease in HER2 expression in their PBD-resistant NCI-N87 cells (15). Previous studies with MEDI0641 demonstrated that knockdown of 5T4 does not impact PBD sensitivity and parental MDA-MB-361 cells with knocked-down 5T4 by siRNA had proliferation and viability rates similar to parental cells treated with control siRNA (Supplementary Fig. S4), so these observations may be correlative but not causal. The sharp decrease in sensitivity to PBD-conjugated ADCs targeting 5T4 or HER2 was significantly greater than the decreased sensitivity to 5T4- or HER2-targeting ADCs conjugated with tubulysin, auristatin or maytansinoid payloads.

Aberrant DDR has been reported as a mechanism of acquired resistance to DNA cross-linking agents and other DDAs (39, 40). It was found previously that defects or deficiencies in certain DDR proteins such as ERCC1, XRCC2, BRCA1, and BRCA2 conferred increased sensitivity to PBDs (8, 41–43). In this study, we observed many DEPs in 361-PBDr cells that are involved in cell-cycle regulation, DNA replication, damage response, and a variety of repair pathways, including downregulation of SLFN11. SLFN11 deficiency correlates with poor response to a broad range of DDAs in preclinical models and clinic studies (18, 33–35, 44, 45). SLFN11 expression can be repressed through EZH2-mediated histone methylation with marked deposition of H3K27me3 (20) and inhibition of EZH2 via treatment with EPZ rescued SLFN11 expression and enhanced efficacy of topotecan or irinotecan in small cell lung cancer models (20). Our data demonstrated that EPZ restored SLFN11 expression and significantly reversed resistance to SG3199 and MEDI0641 in 361-PBDr cells. EPZ also derepressed SLFN11 and sensitized SLFN11-deficient NCI-H82 and K562 cells to SG3199. Given the data supporting the role of SLFN11 in sensitivity to PBDs or PBD-conjugated ADCs, epigenetic derepression of SLFN11 via EZH2 inhibitors or other epigenetic regulators could be a potential combinatorial therapy strategy for PBD-based ADCs to maximize clinical benefit.

We found that siRNA knockdown of SLFN11 in parental MDA-MB-361 breast cancer cells, DU 145 prostate cancer cells, THP-1 AML cells, and CCRF-CEM ALL cells, led to significantly reduced sensitivity to both SG3199 and PBD-based ADCs. In addition, SLFN11 expression correlated with sensitivity to SG3199 in a panel of solid tumor and hematological cancer cells. Taken together, the results demonstrate a role for SLFN11 expression in response to PBD-conjugated ADCs, and suggest that SLFN11 expression levels should be further evaluated as a predictive biomarker and incorporated into a patient stratification strategy to be employed in the clinical development of PBD-conjugated ADCs.

Furthermore, we found that combining sublethal concentrations of the ATR inhibitor AZD6738 with either SG3199 or ADCs conjugated with SG3199 synergistically inhibited 361-PBDr cell growth. The synergistic effect of AZD6738 and SG3199 was also observed in parental MDA-MB-361 and CCRF-CEM cells with knocked-down SLFN11 by siRNA. The synergy observed with the combination suggests that combining PBD-based ADCs with inhibitors that target ATR pathways might be a promising strategy to improve ADC efficacy, circumvent resistance and increase therapeutic index. It may be possible to treat with a combination of the two therapies, where the doses of each are below the established MTD, to reduce the toxicities associated with each therapy at the MTD. However, the potential for overlapping or increased toxicity with the combination (bone marrow toxicity, for example), even at reduced doses of each monotherapy, will need to be evaluated.

SLFN11 acts as an S-phase checkpoint independent of the ATR/CHK1 pathway and irreversibly blocks replication under replication stress caused by DDA to induce cell death (19). In SLFN11-deficient cells treated with PARP inhibitors and topoisomerase 1 inhibitors, ATR inhibition can reverse resistance to replicative damage (37, 38). Those studies provided a possible mechanism for our observation. In response to replicative stress caused by PBD-induced DNA interstrand crosslinking, parental cells could use dual mechanisms of cell-cycle regulation: one is SLFN11-dependent prolonged replication arrest leading to cell death, and the other is the ATR-dependent checkpoint that delays cell-cycle progression and promotes cell survival (46, 47). In contrast, SLFN11-deficient 361-PBDr cells could rely primarily on ATR activation for their cell-cycle regulation under replicative stress. Thus, the addition of the ATR inhibitor AZD6738 to SG3199 further abolishes cell-cycle regulation leading to enhanced cytotoxicity comparing to SLFN11-proficient parental MDA-MB-361 cells (Supplementary Fig. S5).

Additional evidence of a link between SLFN11 and ATR comes from data showing that SLFN11 mediates cleavage of specific type II RNAs required for ATR translation (48). In an SLFN11-deficient setting, ATR is thus fully expressed leading to repair of damage from DDA. Therefore, the sensitivity of SLFN11-deficient cells to DDAs such as PBDs could be restored upon treatment with an ATR inhibitor such as AZD6738. Studies are ongoing to further elucidate the mechanisms by which SLFN11 sensitizes tumor cells to PBDs and PBD-conjugated ADCs, and how ATR inhibition can overcome resistance to PBDs mediated by SLFN11 deficiency.

In summary, we have developed a cell model as a valuable tool to investigate molecular mechanisms of resistance to PBDs and ADCs conjugated with these PBDs. In addition, our findings provide the insight to further investigate SLFN11 as a resistance biomarker of PBD-conjugated ADCs for clinical patient selection, and to develop potential strategies to overcome SLFN11 deficiency–mediated resistance to PBDs through epigenetic activation of SLFN11 expression or combination with ATR inhibitors.

S. Hess reports receiving salary and stock from AstraZeneca. H. Wu reports other from AstraZeneca outside the submitted work. R. Herbst reports other from AstraZeneca during the conduct of the study. P.W. Howard reports other from AstraZeneca outside the submitted work. M. Cobbold reports other from AstraZeneca during the conduct of the study. No disclosures were reported by the other authors.

S. Mao: Conceptualization, resources, data curation, formal analysis, supervision, validation, investigation, visualization, methodology, writing–original draft, project administration, writing–review and editing. R. Chaerkady: Conceptualization, data curation, software, formal analysis, validation, investigation, visualization, methodology, writing–original draft, writing–review and editing. W. Yu: Software, formal analysis, visualization, methodology, writing–original draft, writing–review and editing. G. DAngelo: Data curation, formal analysis, writing–review and editing. A. Garcia: Investigation, methodology, writing–original draft, writing–review and editing. H. Chen: Investigation, methodology, writing–review and editing. A.M. Barrett: Investigation, writing–review and editing. S. Phipps: Investigation, methodology, writing–review and editing. R. Fleming: Resources, investigation, writing–review and editing. S. Hess: Conceptualization, resources, supervision, writing–review and editing. J.-O. Koopmann: Formal analysis, writing–review and editing. N. Dimasi: Resources, supervision, writing–review and editing. S. Wilson: Resources, writing–review and editing. K. Pugh: Investigation, writing–review and editing. K. Cook: Investigation, writing–review and editing. L.A. Masterson: Resources, supervision, writing–review and editing. C. Gao: Resources, supervision, writing–review and editing. H. Wu: Resources, supervision, writing–review and editing. R. Herbst: Supervision, writing–review and editing. P.W. Howard: Resources, supervision, writing–review and editing. D.A. Tice: Conceptualization, resources, supervision, project administration, writing–review and editing. M. Cobbold: Supervision, writing–review and editing. J. Harper: Conceptualization, resources, supervision, writing–original draft, project administration, writing–review and editing.

This study was supported by AstraZeneca. The authors would like to thank Jean-Noel Levy and Balakumar Vijayakrishnan for synthesizing the PBD payloads and PBD conjugates for our studies; Antibody Discovery & Protein Engineering and the Biological Expression team at AstraZeneca (Cambridge, United Kingdom) for synthesizing the antibodies for these studies; Jonathan Boyd of the Microscopy Core Facility in Antibody Discovery & Protein Engineering with cell imaging assistance. Finally, we thank Alan Lau and the AZD6738 team for providing the compound for these studies.

Nazzareno Dimasi is currently an employee of Viela Bio. Changshou Gao is currently an employee of Innovent Biologics. Ronald Herbst is currently an employee of Pyxis Oncology. David A. Tice is currently an employee of Arcellx. All other authors are employees of AstraZeneca.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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