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Table of Contents
ABSTRACT
Abstract
Introduction
Materials And Methods
Cell Culture
Drug Preparation
Cell Viability Assay
Tumor Xenografts
Cell Cycle Analysis
DSB Detection
Repair Assay
SiRNA Transfection
Western Blot
Nuclear‐Localized Top2 Detection
BLISS Method
Peak Annotation
Detection Of RNA Synthesis
Bulk RNA Sequencing And Data Analysis
Statistical Analysis
Results
Discussion
Author Contributions
Disclosure
Ethics Statement
Consent
Conflicts Of Interest
Supporting Information
ABSTRACT
The synergistic effects of drug combinations have emerged as a promising approach for achieving efficient cancer treatment. Through our exploration of drug combinations, we found that medroxyprogesterone acetate (MPA), a steroid, induced a synergistic antitumor effect in combination with the topoisomerase II inhibitor etoposide (ETP). In this study, we investigated the mechanisms underlying this synergistic effect for potential clinical applications. To elucidate the relevant mechanisms, we performed a cell viability assay, cell cycle analysis, DNA repair assays, detection of DNA double‐strand breaks (DSBs) and the nuclear localization of topoisomerase II (Top2), and genome‐wide detection of DSBs. MPA synergistically increased ETP‐induced DSBs, resulting in cell cycle arrest in the G2/M phase. Interestingly, this effect was not due to the inhibition of DSB repair but to a specific increase in the Top2‐DNA covalent complex formed by ETP. A genome‐wide search for DSB locations revealed that DSB formation was promoted near promoter regions, suggesting the involvement of MPA transcriptional modulation in this mechanism. We also found that various steroids promoted DSB formation when combined with ETP, strongly supporting our synergistic model. Therefore, this synergistic effect is based on an innovative mechanism that differs from conventional strategies targeting the DNA damage response and is expected to contribute toward novel therapeutic options.
Abstract
Through our exploration of the synergistic effects of drug combinations for potential clinical applications, we found that steroids potentiate the anticancer effects of etoposide, a topoisomerase II inhibitor. Steroids, when combined with etoposide, increase DNA double‐strand breaks not via DNA repair inhibition but transcriptional modulation.
Introduction
DNA damage can be implemented in cancer therapy. For example, alkylating agents, platinum‐based drugs, and topoisomerase inhibitors remain active and exert their antitumor effects by causing DNA damage [ 1 ]. Owing to their favorable results against various types of cancers, DNA‐damaging anticancer agents remain the cornerstone of cancer chemotherapy [ 2 ]. In contrast, complete remission is often difficult to achieve with a single agent, and combination therapy with multiple agents is attracting attention as an approach to overcome the limitations of single‐agent therapies [ 3 , 4 ]. In particular, if the combination can induce a synergistic effect that exceeds the sum of the impact of each drug, the dosage of the drug can be reduced, thereby reducing the severity of the side effects [ 5 , 6 ]. To achieve synergistic effects, many studies have proposed combined approaches using inhibitors that target DNA repair mechanisms in response to DNA damage [ 7 ]. In clinical research, HR repair, a repair pathway for DSB, is often used as a target for combination methods [ 8 , 9 ]. Combinations of the Phosphoinositide 3‐kinase (PI3K) inhibitor, alpelisib, which reduces homologous recombination activity, with PARP inhibitors ( NCT01623349 ) [ 10 ] and the first‐in‐class inhibitor targeting Rad51, CYT‐0851, with capecitabine ( NCT03997968 ) [ 11 ] are expected to be promising therapeutic approaches. However, tumors can adapt to such combinations and acquire resistance through diverse pathways [ 12 , 13 ]. Therefore, it is important to develop drug combinations that target diverse mechanisms to expand the treatment options [ 4 ]. To develop novel drug combination methods, we explored compound candidates that exhibited synergistic effects when combined with DDAs. Here, we combined a validated compound library including approximately 1600 compounds and several DNA damaging agents, such as TLZ (PARP inhibitor), ETP (Top2 inhibitor), CPT (Top1 inhibitor), and CDDP (DNA cross‐linking agent) and analyzed cell proliferation by neutral red assay, comparing a DDA alone to a combination of DDAs and a compound (data not shown). We then identified MPA, a steroid, as a compound that exhibits synergistic effects when used in combination with the Top2 inhibitor ETP. Both drugs are used in clinical oncology; however, the mechanism underlying their combined effects remains unknown [ 14 , 15 ]. This study presents the detailed mechanism and suggests the prospective clinical application.
Materials and Methods
Cell Culture
The human cervical cancer cell line HeLa and human lung adenocarcinoma cell line A549 were acquired from Riken BRC (Tsukuba, Japan). The colorectal adenocarcinoma cell line DLD‐1 was acquired from the ATCC (Manassas, VA). All three cell lines were log‐phase cells that grew exponentially. HeLa and A549 cells were grown in Dulbecco's Modified Eagle medium (DMEM) supplemented with 10% (v/v) fetal bovine serum (FBS). DLD‐1 cells were grown in RPMI‐1640 medium supplemented with 10% FBS. All cells were maintained at 37°C in a 5% CO 2 atmosphere.
Drug Preparation
Steroids, including MPA, ETP, TLZ, CPT, CDDP, DOX, merbarone, novobiocin, and RNA polymerase II inhibitor, DRB, were obtained from Selleck Chemicals (Houston, TX, USA). ICRF‐193 was purchased from Sigma‐Aldrich (St. Louis, MO, USA). Stock solutions were prepared in DMSO and stored at −20°C in the dark. Immediately before use, the samples were diluted in the culture medium.
Cell Viability Assay
Cell viability was evaluated using an NR assay as previously described [ 16 ]. HeLa (5000 cells/well), A549 (10,000 cells/well), and DLD‐1 (5000 cells/well) cells were seeded in 24‐well plates and treated with the selected drugs on the following day. After drug treatment, the medium was replaced with fresh medium containing neutral red at 40 μg/mL, and incubation continued for 3 h. Neutral red taken up in viable cells was extracted with destaining solution (1% acetic acid and 50% ethanol). The absorbance of the neutral red extract was measured at 540 nm using an EnSpire microplate reader (PerkinElmer, Waltham, MA, USA). Relative cell viability was calculated as the relative value of absorbance normalized to that of the DMSO‐treated control cell samples.
Tumor Xenografts
Detailed information can be found in Doc. S1.
Cell Cycle Analysis
Cells were trypsinized, washed with cold PBS, fixed in 70% ethanol, and stored at −20°C until staining. Staining involved the incubation of cells with 50 μg/mL propidium iodide solution in PBS mixed with RNase (1 mg/mL) for 30 min on ice. Cells were analyzed using a FACSLyric flow cytometer (BD Biosciences, Franklin Lakes, NJ, USA). Approximately 10,000 cells were counted for analysis.
DSB Detection
For the detection of DSB, γH2AX as a DSB marker was analyzed using flow cytometry, as previously described [ 16 ]. Cells were trypsinized, washed with cold PBS, and stained with 0.6 μg/mL fluorescein isothiocyanate (FITC)‐conjugated γH2AX antibody (16‐202A, Merck Millipore, Billerica, MA, USA) in the staining buffer overnight at 4°C. After resuspension, approximately 10,000 cells were counted using a FACSLyric flow cytometer. DSB levels were presented as a fold change of the median of γH2AX intensity normalized to that of the DMSO‐treated control samples.
Repair Assay
HR and NHEJ activities were evaluated using DR‐GFP and EJ5‐GFP reporters. HeLa cells stably expressing DR‐GFP and EJ5‐GFP were transfected with an I‐Sce1 endonuclease expression plasmid using the FuGENE HD transfection reagent (Promega, Madison, WI, USA). pDRGFP and pCBASceI were gifts from Maria Jasin (Addgene plasmids #26475 and #26477). pimEJ5GFP was a gift from Jeremy Stark (Addgene plasmid #44026). HR and NHEJ frequencies were analyzed by measuring the number of green fluorescent protein (GFP)‐positive cells using a FACSLyric flow cytometer 48 h after transfection. Drug treatment was performed 4 h after transfection, and the medium was replaced with the drug until FACS analysis. Relative HR and NHEJ efficiencies were calculated and normalized to those of DMSO‐treated control samples. Approximately 30,000 cells were counted for analysis.
siRNA Transfection
Following the manufacturer's protocol, the cells were transfected with 20 nM siRNA using Lipofectamine RNAiMAX Transfection Reagent (Invitrogen, Carlsbad, CA, USA) for 48 h. siRNA oligonucleotides for human Top2A (ON‐TARGETplus SMARTpool siRNA) were obtained from Horizon Discovery (Cambridge, United Kingdom). Their stock solutions were prepared in RNase‐free water to obtain a concentration of 20 μM and stored at −20°C.
Western Blot
Proteins in whole‐cell lysates were resolved by sodium dodecyl sulfate‐polyacrylamide gel electrophoresis (SDS‐PAGE) and transferred onto Immobilon‐P polyvinylidene fluoride (PVDF) membranes (Merck Millipore, Burlington, MA, USA). The membranes were then blocked with 0.2% I‐Block (Invitrogen) and incubated with the following primary and secondary antibodies: anti‐Top2α (1:1000, 12,286, CST, Beverly, MA) and anti‐GAPDH (1:1000, 5174, CST). Chemiluminescence was analyzed using the CDP‐Star chemiluminescence substrate for alkaline phosphatase (Invitrogen) and the appropriate secondary antibodies. Protein expression was quantified using an ImageQuant LAS‐500 system (Fuji Film, Tokyo, Japan).
Nuclear‐Localized Top2 Detection
The detection of nuclear‐localized Top2 was performed as described previously [ 17 ] with some modifications. Briefly, the drug‐treated cells were trypsinized and washed with cold PBS. Samples were extracted with PBS containing 0.5% Triton X‐100 by mixing with a rotator for 5 min at 4°C, washed with cold PBS, and fixed in 4% paraformaldehyde for 20 min at room temperature. Thereafter, the samples were washed with PBS, blocked in 3% BSA for 1 h, and incubated with PE‐conjugated Top2α antibody (1:100, 34,184, CST) for 1 h at room temperature. The samples were then rinsed with PBS, resuspended in PBS containing 0.5% BSA, and analyzed using a FACSLyric flow cytometer. Nuclear‐localized Top2 quantities were presented as a fold change of the median Top2 intensity normalized to that of the DMSO‐treated control samples. Approximately 10,000 cells were counted for analysis.
BLISS Method
BLISS analysis was performed as described previously [ 18 ], with some modifications. Briefly, drug‐treated cells in a 24‐well culture plate were washed with cold PBS and fixed in 4% paraformaldehyde for 4 h at 4°C. Thereafter, cells were incubated in lysis buffer LB1 (Tris–HCl 10 mM, NaCl 10 mM, EDTA 1 mM, Triton X‐100 0.2%, pH 8 at 4°C) for 1 h at 4°C and LB2 (Tris–HCl 10 mM, NaCl 150 mM, EDTA 1 mM, SDS 0.3%, pH 8 at 25°C) for 1 h at 37°C. After reaching equilibration in CutSmart buffer (NEB, Ipswich, MA, USA), in situ DSB blunting was performed with blunting mix, including the Quick Blunting Kit (NEB), for 1 h at room temperature. After reaching equilibration in T4 Ligase buffer (NEB), in situ DSB ligation was performed with ligation mix, including T4 DNA ligase (NEB) and 0.4 μM of the modified BLISS RA5 adapter, which removes the unique modifier identification (UMI) (Sense 5'‐GATCGTCGGACTGTAGAACTCTGAACCCCTATAGTGAGTCGTATTACCGGCCTCAATCGAA‐3′, Antisense 5'‐CGATTGAGGCCGGTAATACGACTCACTATAGGGGTTCAGAGTTCTACAGTCCGACGATC‐3′) for 16 h at 16°C. To remove the unligated adapters, the cells were incubated in high‐salt wash buffer (Tris–HCl 10 mM, NaCl 2 M, EDTA 2 mM, Triton X‐100 0.5%, pH 8 at 25°C) for 1 h at room temperature five times. After that, the genomic DNA was extracted in DNA extraction mix (SDS 1%, NaCl 100 mM, EDTA 50 mM, Tris–HCl 10 mM, pH 8) with 1 mg/mL Proteinase K for 16 h at 55°C while shaking at 800 rpm. DNA fragmentation was performed with BIORUPTOR‐One (Diagenode, Liège, Belgium) to achieve a mean fragment size of 300–500 bp. The in vitro transcription reaction was performed for 14 h at 37°C using the MEGAscript kit (Invitrogen). The following RA3 adapter ligation, reverse transcription, and library preparation were performed using NEBNext Multiplex Small RNA Library Prep Set for Illumina (Set 1) (E7300, NEB). The libraries were sequenced by Azenta Life Sciences on an Illumina NovaSeq (Illumina, San Diego, CA, USA) with 2 × 150 bp read lengths ( n = 2).
Peak Annotation
Peak annotation was performed using the R package ChIPseeker [ 19 ]. Briefly, quality control of fastq files acquired from BLISS analysis was performed using fastp (ver 0.23.2). Thereafter, reads were mapped to the GRCh38 reference genome using BWA‐MEM (ver 0.7.17) and sorted by genomic coordinates with SAMtools (ver 1.15.1) to generate BAM files. Duplicate reads were marked using the MarkDuplicatesSpark tool from GATK (ver 4.2.0.0). The filtered BAM files were subsequently used to perform peak calling with MACS2 (ver 2.2.7.1). Differential peak analysis was performed using the R package DiffBind (ver 3.8.4) to identify peaks with significant differences between groups. We annotated the genomic features where the peaks were located and compared peak profiles among samples using ChIPseeker (ver 1.34.1). The promoter region was defined as 3 kb from the transcription start site (TSS).
Detection of RNA Synthesis
RNA synthesis was detected using the Click‐iT RNA Alexa Fluor 488 Imaging Kit (Invitrogen). Briefly, EU was added to drug‐treated cells at 1 mM and incubated for 2 h in a CO 2 incubator at 37°C to label cells. Cells were trypsinized, fixed in 4% paraformaldehyde for 20 min, and permeabilized in 0.5% Triton X‐100 for 15 min at room temperature. Thereafter, the cells were suspended in the Click‐iT reaction cocktail and incubated for 30 min at room temperature. The samples were then rinsed with PBS, resuspended in PBS containing 0.5% BSA, and analyzed using a FACSLyric flow cytometer. RNA synthesis levels were presented as a fold change of the median EU incorporation intensity normalized to that of the DMSO‐treated control samples. Approximately 10,000 cells were counted for analysis.
Bulk RNA Sequencing and Data Analysis
Total RNA was isolated using a NucleoSpin RNA Plus (Takara Bio, Shiga, Japan). RNA‐seq library preparation, sequencing, mapping, and gene expression analysis were performed by the RIKEN Center for Integrative Medical Sciences (IMS) (Kanagawa, Japan). Only high‐quality RNA preparations, with an RNA integrity number (RIN) greater than 7.0, were used for RNA library construction. The RNA sequencing libraries were prepared using the Ultra II RNA Library Prep Kit for Illumina (NEB) with 100 ng of total RNA for each sample. The libraries were submitted to the Illumina NextSeq 2000 (Illumina), and paired‐end (2 × 50 bp) sequencing was performed. FASTQ files were generated from binary base call (BCL) files using bcl2fastq. FASTQ was used for quality control by removing adapter sequences and low‐quality sequences, and the reads after filtering were mapped to the reference genome using STAR (ver 2.7.10a). featureCounts (ver 2.0.1) was subsequently used to calculate read counts for each gene. For differential expression analysis, we performed the Quasi‐likelihood test to find DEGs between the control and test groups using the edgeR (ver 3.40.2) package. Gene ontology and pathway analyses were performed using clusterProfiler (ver 4.6.2).
Statistical Analysis
All data were analyzed using GraphPad Prism 9 (GraphPad, La Jolla, CA, USA). Means were compared using Student's t‐test. Statistical significance was set at p < 0.05.
Results
MPA Induces a Synergistic Antitumor Effect When Combined With ETP
To confirm the synergistic effect of the combined treatment with ETP and MPA, we evaluated cell viability using the NR assay in various tumor cell lines. The assay indicated that HeLa cells showed growth inhibition at MPA concentrations above 10 μM and DLD‐1 cells at 30 μM. Interestingly, A549 cells exhibited a two‐step growth inhibition to MPA. Once the cells exhibited growth inhibition at an MPA concentration of 0.3 μM, viability was maintained up to 3 μM; however, above 10 μM, the cells exhibited statistically significant growth inhibition compared to 0.3 μM (Figure S1A–C ). The relative cell viability of these tumor cells decreased to less than 0.5 at 30 μM of MPA treatment. Next, we analyzed the dose–response of MPA in combination with ETP treatment in HeLa cells. Treatment with ETP at 0.3 μM significantly induced a sensitizing effect of 3 and 10 μM MPA (Figure 1A ). We also analyzed the dose–response of ETP to MPA treatment in HeLa, A549, and DLD‐1 cells. Compared to the dose response curve of the DMSO control, MPA treatment at 3 μM facilitated sensitizing responses in all tumor cell lines treated with ETP (Figure 1B–D ). We performed cell cycle analysis in HeLa, A549, and DLD‐1 cells to confirm the mechanism by which the combination treatment induced growth inhibition. The cell cycle distribution indicated that MPA accumulated in G2/M cells combined with ETP (Figure 1E–G ). These synergistic effects were also tested in a tumor xenograft model. The administered MPA precipitated subcutaneously and was gradually absorbed into the mouse body. A trend toward weight gain was observed after MPA administration, but the dosage was limited (Figure S2A ). Under these limitations, the combination of ETP and MPA groups exhibited an average decrease in tumor size compared to the ETP monotherapy group, but the difference was not significant (Figure S2B,C ). These results suggest that MPA synergistically sensitizes various types of tumor cells in combination with ETP via cell cycle checkpoint signaling.
MPA Promotes ETP ‐Formed DSBs Through a Mechanism Distinct From DNA Repair Inhibition
ETP induces DSBs by blocking Top2 function, resulting in the arrest of the G2/M cell cycle. To investigate whether the population of G2/M cells accumulated through combined treatment was due to an increase in DSBs, we analyzed the formation of DSB in HeLa, A549, and DLD‐1 cells by detecting γH2AX using flow cytometry. The results revealed that only MPA treatment at 3 μM did not induce DSBs in these cells, while a combination of MPA and ETP significantly increased DSBs compared with ETP treatment alone (Figure S3 and Figure 2A–C ). Next, we performed HR and NHEJ assays to confirm whether MPA affected DSB repair pathways and increased the number of DSBs when combined with ETP. The results revealed that HR and NHEJ repair activities did not change after MPA treatment, indicating that MPA did not affect either repair pathway (Figure 2D,E ). We also analyzed the formation of DSB to confirm the combined effects of MPA and other DNA‐damaging agents, including the PARP inhibitor TLZ, Top1 inhibitor CPT, and DNA cross‐linker CDDP. Interestingly, only ETP exhibited a synergistic effect with MPA (Figure 2F ). These results suggest that MPA synergistically induces DSBs when combined with Top2 inhibitors.
MPA Potentiates the Top2 Poisons With Top2 Inhibitors
To confirm how the Top2 function affects the synergistic effect, we performed loss‐of‐function analysis for Top2α, one of the Top2 isoforms, by analyzing the formation of DSB. siRNA targeting Top2α was able to knock down most of the proteins (Figure 3A ). In Top2α knockdown cells, the amount of DSB formation by ETP was significantly reduced, but MPA synergistically promoted DSB formation with ETP under transfection with siTop2A as well as siCtrl (Figure 3B ). The degree of the synergistic effect was considered to be strongly related to the increase in the number of DSBs caused by the combined use of MPA. Therefore, we calculated the MPA‐induced γH2AX intensity with ETP and investigated the effect of Top2α knockdown (Figure 3C ). Top2α silencing significantly reduced the amount of synergistic DSB formation (Figure 3C ). Therefore, Top2α may play a critical role in the synergistic effect. ETP forms a Top2‐DNA covalent complex (Top2cc), termed the Top2‐poison, to induce DSBs [ 20 ]. Next, we analyzed the nuclear localization of Top2α using a flow cytometer. The distributions of Top2α intensity confirmed that ETP increased the nuclear localization of Top2α, indicating the formation of Top2cc (Figure 3D ). The results revealed that MPA synergistically increased the nuclear localization of Top2α when combined with ETP (Figure 3D ). To confirm these results, we examined the combined effects of MPA and other Top2 inhibitors, including DOX, merbarone, ICRF‐193, and novobiocin, by analyzing the formation of DSB. Regarding the action of each Top2 inhibitor, doxorubicin is classified as an inhibitor that causes Top2 poisons, as is etoposide [ 21 ]; merbarone and ICRF‐193 are catalytic inhibitors [ 22 , 23 ]; and novobiocin is a gyrase inhibitor [ 24 ]. We found that the Top2 inhibitors ETP and DOX, which also form Top2cc, synergistically increased DSBs when combined with MPA (Figure 3E ). These results suggest that MPA specifically potentiates Top2cc formation.
MPA ‐Modulated Localized Transcription Activity Promotes DSB Formation
To determine where the synergistically increased DSBs were formed, we used the BLISS method and ChIPseeker to analyze the location of DSB formation in the genome. In the annotation data, we observed that MPA specifically formed DSBs near the promoter region in combination with ETP (Figure 4A ) because transcriptional activation promotes DSB formation by ETP [ 25 ]. Next, we investigated whether transcriptional regulation affected these synergistic effects. We first confirmed that DRB, an RNA polymerase II inhibitor, significantly reduced the number of DSBs formed by ETP (Figure 4B ). Then, we analyzed the synergistic effect of DSB formation and the nuclear localization of Top2α under reduced transcription activity stimulated by DRB. The results suggested that both MPA‐induced DSBs and the nuclear localization of Top2α significantly decreased under DRB treatment (Figure 4C,D ). We investigated the overall transcriptional activity of MPA in untreated and DRB‐treated cells by analyzing the uptake of EU. However, MPA did not induce any significant changes in transcriptional activity (Figure 4E ). Thereafter, we performed RNA‐seq analysis to capture microscopic changes in transcription levels regulated by MPA. Interestingly, the differential expression analysis revealed that approximately 80% of the DEGs were upregulated genes, suggesting that MPA locally activates transcription (Figure 4F and Figure S4A ). Gene ontology and pathway analyses of the upregulated genes revealed high levels of steroid‐responsive processes and pathways (Figure S4B,C ). Therefore, we focused on GMPR , which had the highest fold change (FC) as a representative example among the upregulated genes, and reanalyzed DSB formation around its locus from BLISS analysis data. The peak profiling data showed that the number of peaks detected around the GMPR locus was higher in the “ETP + MPA combination” than in “ETP alone” (Figure 4G ). These results suggest that MPA‐regulated localized transcriptional activity promotes ETP‐induced Top2cc formation.
Transcriptional Regulation of Steroids in General Synergistically Potentiates the Top2 Poisons
Steroids have transcriptional regulatory functions, with MPA being a type of steroid. Therefore, we investigated whether other steroids induced a synergistic effect in combination with ETP. We combined 54 steroids with ETP to evaluate their synergistic effects on DSBs. Almost all of the steroids, when used alone, formed fewer DSBs than the DMSO control. In contrast, multiple combinations of steroids and ETP resulted in significantly more DSBs when compared with treatment with ETP alone (Figure 5A ). We then calculated the proportion of steroid‐induced DSBs to evaluate the synergistic effects of steroids. Interestingly, most steroids (53 out of 54) exhibited positive scores, indicating a synergistic effect in which combined treatment increased DSBs more than monotherapy with ETP (Figure 5B ). These results suggest that MPA and most steroids induce a synergistic effect when combined with ETP.
Discussion
The present study demonstrates a novel strategy for the sensitization of Top2 inhibitors using steroids. Previous sensitization methods for DNA‐damaging agents are characterized by a reduced DSB repair capacity, as represented by the synthetic lethality of PARP inhibitors in BRCA‐mutated tumors [ 26 , 27 ]. However, treatment is difficult due to the acquisition of resistance, including the restoration of restorative function [ 28 , 29 ]. Therefore, the development of novel sensitization methods using mechanisms that do not solely rely on the inhibition of DSB repair is expected to provide a variety of therapeutic options. Various Top2 inhibitors have been developed with Top2cc formation or enzyme inhibition as their mechanisms of action [ 21 ]. We found that steroids only specifically sensitize tumor cells when combined with inhibitors that form Top2cc, including ETP and DOX. The chromosomal translocation caused by ETP is strongly affected by its transcriptional activity [ 30 , 31 ]. As a detailed mechanism, it was suggested that ETP‐induced reversible Top2cc is converted to irreversible Top2cc by collision with transcription at the transcriptionally active site, resulting in DSBs and translocation [ 25 ]. This is consistent with our BLISS analysis, in which synergistic DSB formation occurred near the promoter regions that regulate transcription. In contrast, transcriptional regulation by steroids had negligible effects on total transcription. Thus, reversible Top2ccs collide with transcription at sites of local transcriptional regulation by steroids, resulting in the promotion of DSB formation (Figure 5C ). The promotion of transcriptional activity increases cell sensitivity by converting the reversible Top2cc trapped by ETP into DSB. Therefore, the search for factors that strongly activate transcription may lead to the development of more effective therapies when used in combination with ETP. Steroids may be a combination factor that effectively enhances the antitumor effects of ETP. The formation of Top2cc by ETP occurs at sites of topological DNA stress throughout the genome [ 32 ]. To increase the probability of interference between transcription and Top2cc, it would be more efficient to regulate a large number of targets in a broad region of the genome rather than the transcriptional activation of a single target gene. In this regard, steroids bind to multi‐species receptors and regulate the transcriptional activity of diverse target genes [ 33 , 34 ]. Consequently, the combination of steroids and ETP used in this study may be a reasonable strategy for cancer sensitization. In contrast, most steroids induce a synergistic effect when used in combination with ETP; however, there were large differences in their effects, as shown in Figure 5B . The complete transcriptional regulatory network of steroids, including target factors, remains unclear [ 35 , 36 ]; therefore, it is difficult to predict the synergistic effects of their combined use. The development of methods to predict the degree of synergy will be necessary in optimizing therapeutic applications. These findings present significant challenges and utility in clinical practice. Many steroids are clinically used as anti‐nausea agents in cancer treatment [ 37 ]. Moreover, their combination with Top2 inhibitors may enhance cytotoxicity, particularly in normal tissues, which may have unexpected and severe consequences. In the future, its effects on normal tissues should be clarified, and the timing of concomitant administration should be carefully considered. Our results also suggest that Top2 inhibitors could be useful in the treatment of hormone‐hypersecreting tumors such as ACC, which result in the oversecretion of steroid hormones [ 38 ]. Interestingly, the efficacy of ETP + DOX + CDDP therapy, including Top2 inhibitors, has already been recognized as chemotherapy for adrenocortical cancer, although there is no clear evidence [ 39 ]. Therefore, in this study, the need to reconsider steroid administration in Top2 inhibitor chemotherapy and the rationale for ACC treatment are clear. Based on these results, it is expected that a combination therapy of Top2 inhibitors and steroids could be developed to establish an efficient cancer therapy. However, as shown in Figure S2 , no enhancement of the antitumor effect by the combination of ETP and MPA was observed in the in vivo model. This could be due to pharmacokinetic issues with MPA: MPA is more likely to bind to plasma proteins, resulting in less systemic delivery [ 40 ]. Correspondingly, delivery of MPA to the tumor is also reduced and may not reach the dose that causes the combined synergistic effect. In contrast, such pharmacokinetics would be improved by the structure of the steroid [ 41 ]. Therefore, for future clinical applications, the search for steroids that maximize both “promotion of transcriptional activity” and “delivery of the compound to the tumor” will be challenging. In conclusion, our study demonstrated that local transcriptional regulation by steroids synergistically increased DSBs formed by Top2 inhibitors and enhanced their cell‐killing effect. This synergistic effect is based on a novel mechanism of action that differs from the conventional concept of targeting the DNA damage response. Therefore, these findings are expected to have the potential for development in clinical practice, including the development of efficient combination therapies.
Author Contributions
Ying Zhao: data curation, investigation, validation, visualization, writing – original draft. Tetsuro Hisayoshi: data curation, investigation, resources, software. Doudou Zhang: investigation. Saaya Suzuki: investigation. Takashi Watanabe: data curation, investigation. Atsuo Kobayashi: investigation. Qianqian Guo: investigation. Yukihide Momozawa: supervision. Takashi Shimokawa: data curation, investigation, resources. Shunsuke Kato: supervision, writing – review and editing. Yoshio Miki: conceptualization, funding acquisition, project administration, supervision, writing – review and editing. Shigeaki Sunada: conceptualization, data curation, formal analysis, funding acquisition, investigation, methodology, project administration, resources, supervision, validation, visualization, writing – review and editing.
Disclosure
Animal experiments were approved by the Institutional Animal Care and Use Committee of the National Institutes for Quantum Science and Technology (QST, approval number 20‐1005).
Ethics Statement
The authors have nothing to report.
Consent
The authors have nothing to report.
Conflicts of Interest
Prof. Yoshio Miki is a former member of the Cancer Science Editorial Board. Other authors do not have any COI to declare.
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