
==== Front
Discov Oncol
Discov Oncol
Discover Oncology
2730-6011
Springer US New York

39235706
1258
10.1007/s12672-024-01258-9
Research
Knocking down RAD51AP1 enhances chemosensitivity by inhibiting the self-renewal of CD133 positive ovarian cancer stem-like cells
Zeng Si-heng 12
Yan Zhi-qiang 2
Ren Qing 3
Lin Li-hui 2
Chen Zhen 763659186@qq.com

2
1 https://ror.org/037p24858 grid.412615.5 0000 0004 1803 6239 Department of Gynecology, Qingpu Branch of Zhongshan Hospital Affiliated to Fudan University, Shanghai, 200170 China
2 Department of Gynecology, Hainan West Central Hospital, Danzhou, 571700 China
3 grid.412523.3 0000 0004 0386 9086 Department of Gynecology, The Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200120 China
5 9 2024
5 9 2024
12 2024
15 41016 11 2023
21 8 2024
© The Author(s) 2024
2024
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Purpose

This study was designed to investigate the function of RAD51AP1 in the self-renewal and chemosensitivity of CD133 positive (CD133+) ovarian cancer (OC) stem-like cells.

Methods

CD133+ (CD133 positive) OVCAR4 and CD133 negative (CD133−) OVCAR4 cells were separated from OVCAR4 by flow cytometry. Then, the separated CD133+OVCAR4 cells were divided into the following groups: Vector group; RAD51AP1 group; siNC group; si-RAD51AP1 group. Next, sphere-formation assay and colony forming assay were used to evaluate the self-renewal and proliferation ability of cells; western blot to detect the expression of RAD51AP1, transforming growth factor beta 1 (TGF-β1) and SMAD4 proteins in tissues and cells; qRT-PCR to assess the mRNA levels of sex-determining region Y-box 2 (SOX2), octamer-binding transcription factor 4 (OCT4), NANOG and Kruppel-like factor 4 (KLF4).

Results

The performance of CD133+OVCAR4 cells was much better than that of CD133−OVCAR4 cells in sphere-formation assay and colony forming assay. Besides, compared with adjacent group and CD133−OVCAR4 cells, the expression level of RAD51AP1 increased significantly in OC group and CD133+OVCAR4 cells. Moreover, the over-expression of RAD51AP1 promoted the self-renewal and proliferation of CD133+OVCAR4 cells. On the contrary, knocking down the expression level of RAD51AP1 could inhibit the self-renewal and proliferation of CD133+OVCAR4 cells and improve the sensitivity of cells to chemotherapy drugs.

Conclusion

The findings of this study showed that RAD51AP1 was highly expressed in OC tissue and CD133+OVCAR4 cells, and regulated the self-renewal and chemosensitivity of tumor cells through the TGF-β1/SMAD4 signaling pathway.

Keywords

Ovarian cancer
RAD51AP1
Tumor proliferation
Cancer drug resistance
issue-copyright-statement© Springer Science+Business Media, LLC 2024
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pmcIntroduction

Ovarian cancer (OC) is the most deadly malignant tumor in women diagnosed with gynecological cancers [1]. In the United States and Europe, the incidence of OC is 11.7–12.1 cases per 100,000 people, while it is slightly lower in the Middle East and Asia [2]. More than 90% of malignant ovarian tumors originate from the epithelial tissue of ovary and/or fallopian tube. OC is divided into six types by the World Health Organization, including endometrial, mucinous, serous, clear cell, squamous cell and transitional cell carcinomas [3]. Due to its early spread, late detection and high recurrence rate in abdominal cavity, OC has a poor prognosis as well as a five-year survival rate less than 40% [4]. The treatment options of OC include platinum compound combined chemotherapy and cytoreductive surgery. Generally, OC is very sensitive to chemotherapy, but most of patients suffer from recurrent OC (ROC) after cytoreductive surgery and first-line chemotherapy [5].

ROC and its drug resistance to current chemotherapy schemes are global challenges. Notably, drug resistance is a complex phenomenon involving multiple genes and signaling pathways [6]. Therefore, it is of great importance to clarify the potential molecular mechanism of drug resistance, which is helpful for the management of decision-making for treatment and the identification of new effective drug targets. OC stem cells (OCSCs) have high self-renewal ability, play a very important role in tumor initiation, spread, metastasis and drug resistance, and are considered to be highly resistant to chemotherapy and the cause of high recurrence rate of OC [7, 8]. There are many surface molecular markers of OCSCs, such as CD24, CD44, CD117 and CD133 [8]. Among them, CD133, also known as prominin-1, is a glycoprotein with five transmembrane characteristics, which was first discovered in mouse neuroepithelial cells [9]. Also, a previous research has reported that CD133 exists in different adult stem cells and can inhibit cell differentiation [10]. Related studies show that the expression of CD133 is related to the chemosensitivity of OCSCs and can be used to monitor and predict the clinical outcome after chemotherapy. There are many factors leading to the tolerance of OC chemotherapy drugs [11]. The family members of ATP-binding cassette transporters (ATP-binding cassette transporters), including multidrug resistance protein 1 (MDR1), breast cancer resistance protein (BCRP) and MDR-associated protein 1 (MRP1), provide tumors with multiple anticancer drug resistance, such as paclitaxel, topoisomerase inhibitors and tyrosine kinase inhibitors [12]. Although traditional treatment can significantly reduce the tumor size and temporarily improve the symptoms of patients, it does not specifically and highly effectively target tumor subgroups, resulting in poor therapeutic effect of OC [13]. Therefore, it is of great significance to further study the drug resistance mechanism of OCSCs and explore new therapeutic targets.

RAD51-associated protein 1 (RAD51AP1) plays an important role in homologous recombination (HR) by activating RAD51 recombinase [14]. On the one hand, RAD51AP1 interacts with RAD51 or DMC1 recombinase to enhance their recombinase activity and stimulate the formation of D-loop [15]; and such process is the key step of HR-mediated DNA repair in mitosis and meiosis of cells. On the other hand, RAD51AP1 is also involved in promoting growth-related signal transduction. Moreover, some studies have shown that RAD51AP1 highly expresses in OC, cholangiocarcinoma and hepatocellular carcinoma, indicating its potential role in tumor proliferation [16–18]. Additionally, Bridges et al. proposed the important function of RAD51AP1 in tumor stem cells. Briefly, down-regulating RAD51AP1 inhibited the self-renewal and related potential of breast cancer stem cell (BCSC), and improved the efficacy of chemotherapy and radiotherapy [19]. Furthermore, Bridges also discovered that deletion of RAD51AP1 could weaken the renewal of colorectal cancer stem cell (CCSC) and enhance the sensitivity to chemotherapy [20]. However, the expression level and potential mechanism of RAD51AP1 in OCSCs are not clear. Therefore, the objective of this study was to expound the function of RAD51AP1 in OCSCs, further understand the occurrence and development mechanism of OC, and provide theoretical guidance for the development of new targeted drugs for OC.

Materials and methods

OC tumor and adjacent tissues were selected from patients receiving surgical resection in Hainan West Central Hospital from January 2023 to March 2023. The inclusion criteria were shown as follows: patients (1) were diagnosed as OC by histopathology; (2) had complete clinical and pathological data and follow-up information. The exclusion criteria were listed as follows: patients (1) were complicated with serious heart, brain, blood vessels and other important organ diseases; (2) had a history of tumors derived from other tissues; (3) had infection or pregnancy. This study was approved by the Ethics Committee of Hainan West Central Hospital (No. SH9H-2019-A681-1), and all patients signed written informed consent. All methods were carried out in accordance with relevant guidelines and regulations.

Cell culture

OVCAR4 (WARNER, WN-C10067) cells were cultured in RPMI1640 medium (Sigma, #51536 C) containing 10% fetal bovine serum (FBS, Gibco, #10099) and placed in a cell incubator containing 5% CO2 at 37 ℃.

CD133 positive (CD133+) cell sorting

OVCAR4 cells were prepared into single cell suspension, and the suspension density was adjusted to 1 × 107/mL by phosphate buffered saline (PBS). Next, CD133-APC antibody (Biolegend, #397906) was added according to the dilution ratio of 1:100. The mixture was incubated on ice in the dark for 30 min. Subsequently, the cells were washed twice with PBS, resuspended with 500 µL PBS and filtered with a 300-mesh filter. According to the expression level of CD133, the cells were sorted by flow cytometry (BD, LSRII). Finally, CD133 positive (CD133+) OVCAR4 and CD133 negative (CD133−) OVCAR4 cells were collected.

Plasmid construction and cell transfection

The RAD51AP1 gene fragments were amplified by KOD plus PCR (TOYOBO, # KOD-201) polymerase. Through one-step cloning kit (Vazyme, #C112-01), the obtained RAD51AP1 gene fragments were constructed into pcDNA3.1 to form plasmid pcDNA3.1-RAD51AP1. Next, the pcDNA3.1-RAD51AP1 plasmid formed was sent to BGI Genomics for sequencing and sequence comparison to ensure correctness. Subsequently, Lipofectamin 3000 (ThermoFisher, #L3000001) was used to transfect the constructed clone into CD133+OVCAR4 cells, and after transfection for 24 h, the subsequent experimental operation was carried out. GenePharma company was entrusted to synthesize the siRNA targeting RAD51AP1, with the sequence of 5′-AACCTCATATCTCTAATTGCA-3′. Later, siRNA was transfected into CD133+OVCAR4 cells by Lipofectamin 3000, and after transfection for 24 h, the subsequent tests were performed.

Sphere-formation assay

OVCAR4 cells in different groups were seeded into 6-well ultra-low adsorption plates (Corning, #3471) at a density of 2 × 104 cells/well using serum-free DMEM/F-12 (Gibco, #21331020) medium. The culture medium was supplemented with B-27 supplement (Gibco, #17504044, concentration: 1×), human epidermal growth factor (Sigma-Aldrich, # GF144, concentration: 10 ng/mL) and human beta fibroblast growth factor (Gibco, #13256-029, concentration: 20 ng/mL) [21]. The cells were cultured in an incubator for 7 days, then the images were collected under an optical microscope, and the number of spheres was statistically analyzed.

Cell colony forming assay

OVCAR4 cells in different groups were seeded into 6-well plates at a density of 2 × 104 cells/well. The cells were cultured at 37 ℃ and 5% CO2 to form colonies, and the culture medium was changed every five days. After 10 days, the medium was removed, and the cells were fixed with 10% (v/v) methanol for 15 min and then stained with 0.1% crystal violet (Sigma-Aldrich, #548-62-9) solution for 30 min. Subsequently, the cells were washed with PBS for three times, the images were collected under the optical microscope, and the number of cell colonies was recorded.

MTT assay

MTT assay kit (Beyotime, #C0009S) was used to detect the cell viability. Briefly, OVCAR4 cells in different groups were seeded into 96-well cell culture plates with 5,000 cells per well, and the culture volume was 100 µL. The cells were treated with different concentrations of paclitaxel (0, 1, 3, 7, 15 µg/mL), cisplatin (0, 0.5, 2, 5, 10 µg/mL) and doxorubicin (0, 1, 2.5, 5, 10 µg/mL) [22–24]. After 24 h, the culture medium was changed, and the cells were incubated with 10 µL MTT solution for 4 h. Subsequently, the liquid in each well was removed, and 100 µL Formazan solution was added and shaken for 10 min. Lastly, the optical density (OD) at the wavelength of 570 nm was measured by a microplate reader, and the cell viability and IC50 (half maximal inhibitory concentration) of each group were calculated.

RT-qPCR

Total RNA of cells in each group was extracted with Trizol (Invitrogen, #15596026) reagent. Then, the extracted RNA (1 µg) was reversely transcribed into cDNA with reverse transcription kit (Takara, #639549). Next, the qPCR system was configured using SYBR Green qPCR kit (Bio-Rad, #172–5270), and the reaction was carried out under 7500 Fast real-time fluorescence quantitative PCR system (ThermoFisher, #4351107). Through 2−ΔΔCt method, the relative expression of target genes was calculated taking GAPDH as an internal control. The primer sequences were displayed as follows: SOX2-F: 5′-AGCTCGCAGACCTACATGAA-3′, SOX2-R: 5′-CCGGGGAGATACATGCTGAT-3′; OCT4-F: 5′-CCCGAAAGAGAAAGCGAACC-3′, OCT4-R: 5′-GCAGCCTCAAAATCCTCTCG-3′; NANOG-F: 5′-ACCCAGCTGTGTGTACTCAA-3′, NANOG-R: 5′-CTGCGTCACACCATTGCTAT-3′; KLF4-F: 5′-AGAGACCGAGGAGTTCAACG-3′, KLF4-R: 5′-CGGATCGGATAGGTGAAGCT-3′: GAPDH-F: 5′-GTCTCCTCTGACTTCAACAGCG-3′, GAPDH-R: 5′-ACCACCCTGTTGCTGTAGCCAA-3′.

Western blot

The total protein of cells in each group was extracted by RIPA lysate (ThermoFisher, #89900), and the protein concentration was determined by BCA method (Vazyme, #E112-01/02). Next, the protein (20 µg) was subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) for 120 min, and then transferred to the polyvinylidene fluoride (PVDF) membrane (ThermoFisher, #LC2005) by wet transfer. Subsequently, the PVDF membrane was sealed with 5% skimmed milk for 1 h and incubated with RAD51AP1 (NOVUS, #NBP2-20060), transforming growth factor beta 1 (TGF-β1, Abcam, #ab215715), SMAD4 (Abcam, #ab40759), and GAPDH (ThermoFisher, #MA1-16757) antibodies at 4 ℃ overnight. On the next day, the membrane was washed with TBST for three times and then incubated with anti-rabbit secondary antibody (CST, #14708) at ambient temperature for 1 h. Again, the membrane was washed with TBST for three times. Subsequently, the membrane was exposed and photographed with developers (Merck, #WBKLS0050) under a western blot imaging analyzer (BioRad, #12003153), and the exposure results were quantitatively analyzed with ImageJ software.

Statistical treatment

The experimental data were statistically analyzed by SPSS 23.0 and plotted by Graph Pad Prism 9.0. Two-sample t-test was used for comparison between two groups, and one-way ANOVA for comparison among multiple groups. All experimental results were expressed as the mean ± standard deviation. P < 0.05 indicated a significant difference.

Results

OVCAR4 cells contain CD133 positive (CD133+) cancer stem-like cells

Tumor stem cells, as a small number of cells with self-renewal ability and multi-directional differentiation potential, are considered to play an important role in the origin, development, metastasis and drug resistance of tumors [25]. CD133 is regarded as a tumor stem cell marker [26]. In this study, the level of CD133 in OVCAR4 was analyzed by flow cytometry, and the analysis results revealed that about 10.1% cells showed CD133+ characteristics (Fig. 1A). To study the biological characteristics of CD133+ cell population, OVCAR4 cells with CD133− and CD133+ were sorted by flow cytometry, and the self-renewal and proliferation of the sorted cells were further analyzed. The sphere-formation assay results showed that CD133+OVCAR4 cells had significantly higher sphere-formation capacity than CD133−OVCAR4 cells (Fig. 1B, P < 0.01). The cell colony forming assay showed that the colonies formed by CD133+OVCAR4 cells were much more than those formed by CD133−OVCAR4 cells (Fig. 1C, P < 0.01). The above results indicated that the OVCAR4 cell populations contained CD133+ cell populations, and CD133+OVCAR4 cells had a stronger self-renewal ability and proliferation activity. Therefore, CD133+OVCAR4 cells may play an important role in the development, metastasis and drug resistance of OC.

Fig. 1 Evaluation of biological characteristics of CD133 positive (CD133 +) OVCAR4 cells. A Flow cytometry to analysis the expression level of CD133 in OVCAR4 cells; B evaluation of the sphere-formation capacity of CD133 positive (CD133+) OVCAR4 and CD133 negative (CD133−) OVCAR4 cells (left) and statistical analysis of the number of spheres (right); C assessment of the colony forming ability of CD 133+OVCAR4 and CD133−OVCAR4 cells (left) and statistical analysis of the number of cell colonies (right). **P < 0.01

High expression of RAD51-associated protein 1 (RAD51AP1) in ovarian cancer (OC) tissues and CD133 positive (CD133+) OVCAR4 cells

To determine the association of RAD51AP1 with OC, the expression level of RAD51AP1 in OC tissues was detected using western blot. The detection results showed that the expression level of RAD51AP1 was significantly elevated in OC tissues compared with that in adjacent normal tissues (Fig. 2A, P < 0.01). In addition, the expression level of RAD51AP1 in CD133+OVCAR4 cells was significantly higher than that in CD133−OVCAR4 cells (Fig. 2B, P < 0.01). The above results indicated that RAD51AP1 may exert important regulatory functions in OCSCs, which in turn affected the progression of OC.

Fig. 2 High expression of RAD51-associated protein 1 (RAD51AP1) in ovarian cancer (OC) tissues and CD133 positive (CD133 +) OVCAR4 cells. Western blot was applied to analyze the expression level of RAD51AP1. A, B Expression levels (top) and statistical analysis (bottom) of RAD51AP1 in OC tissues and adjacent tissues (A) as well as CD133+OVCAR4 and CD133−OVCAR4 cells (B). **P < 0.01. RAD51AP1: RAD51-associated protein 1; OC: ovarian cancer; CD133+: CD133 positive; CD133−: CD133 negative

RAD51-associated protein 1 (RAD51AP1) promotes the self-renewal and proliferation of CD133 positive (CD133+) OVCAR4

To investigate the biological function of RAD51AP1 in OCSCs, RAD51AP1 in CD133+OVCAR4 cells was over-expressed by transfection with pcDNA3.1-RAD51AP1; also, the expression level of RAD51AP1 was knocked down by transfection with RAD51AP1 siRNA. The protein expression level of RAD51AP1 in CD133+OVCAR4 cells was verified using western blot, and the results showed that the protein expression level of RAD51AP1 in the RAD51AP1 group was significantly increased compared with that in the Vector group (Fig. 3A, P < 0.01); compared with the siNC group, the protein expression level of RAD51AP1 in the si-RAD51AP1 group was notably decreased (Fig. 3A, P < 0.01). The above outcomes indicated that the protein level of RAD51AP1 was successfully over-expression and knocked down in CD133+OVCAR4 cells. Additionally, the results of the cell colony forming assay showed that the number of colonies in the RAD51AP1 group was significantly increased compared with that in the Vector group; while the number of colonies in the si-RAD51AP1 group was notably decreased compared with that in the siNC group (Fig. 3B, P < 0.01). Furthermore, the results of sphere-formation assay showed that, compared with the Vector group, the sphere-formation ability and the number of spheroids of cells in the RAD51AP1 group were significantly increased; while in contrast to the siNC group, the sphere-formation ability and the number of spheroids of cells in the si-RAD51AP1 group were remarkably decreased (Fig. 3C, P < 0.01). Moreover, the expression levels of transcription factors that could reflect the characteristics and malignancy of tumour stem cells, including sex-determining region Y-box 2 (SOX2), octamer-binding transcription factor 4 (OCT4), NANOG and Kruppel-like factor 4 (KLF4), were detected by qRT-PCR [27]. The results revealed that, compared with the Vector group, the expression levels of SOX2, OCT4, NANOG and KLF4 were significantly increased in the cells of the RAD51AP1 group; while relative to the siNC group, the expression levels of SOX2, OCT4, NANOG and KLF4 were markedly decreased in the cells of the si-RAD51AP1 group (Fig. 3D–G, P < 0.01). The above findings suggested that the elevated expression level of RAD51AP1 could promote the self-renewal and proliferation ability of OCSCs and increase the malignancy of OC.

Fig. 3 RAD51-associated protein 1 (RAD51AP1) promotes the self-renewal and proliferation of CD133 positive (CD133 +) OVCAR4. After over-expression and knock-down of RAD51AP1 in CD133+OVCAR4 cells, the subsequently experiments were carried out. A Western blot analysis (left) and statistical analysis (right) for the protein expression level of RAD51AP1 in cells of each group; B cell colony forming experiment analysis (top) and statistical analysis (bottom) for cell colony forming ability of each group; C sphere-formation assay analysis (left) and statistical analysis (right) for sphere-formation ability in each group; D–G the mRNA levels of SOX2 (D), OCT4 (E), NANOG (F) and KLF4 (G) were analyzed by qRT-PCR. **P < 0.01 vs. Vector GROUP, ##P < 0.01 vs. SiNC group. CD133+, CD133 positive; RAD51AP1: RAD51-associated protein 1; SOX2: sex-determining region Y-box 2; OCT4: octamer-binding transcription factor 4; KLF4: Kruppel-like factor 4

RAD51-associated protein 1 (RAD51AP1) promotes drug resistance in CD133 positive (CD133+) OVCAR4

There is evidence that tumour stem cells have more significant resistance to chemotherapeutic agents [28]. To verify whether the same effect was present in OC, MTT was applied to assess the viability of CD133+OVCAR4 and CD133−OVCAR4 cells under different chemotherapeutic drug treatments, including paclitaxel, cisplatin and doxorubicin. The results showed that the viability of cells under the treatment of paclitaxel, cisplatin and doxorubicin in the CD133+OVCAR4 group was significantly higher than that of cells in the CD133−OVCAR4 group; besides, the IC50 of cells treated by paclitaxel, cisplatin and doxorubicin in the CD133+OVCAR4 group were significantly higher than those in cells of the CD133−OVCAR4 group (Fig. 4A–C, P < 0.01). To further investigate the role of RAD51AP1 in drug resistance in OCSCs, MTT was employed to assess the cell viability of each group after over-expression and knock-down of RAD51AP1 expression levels in CD133+ OVCAR4 cells. The results showed that, under paclitaxel, cisplatin and doxorubicin treatments, the viability of cells was significantly higher in the RAD51AP1 group than in the Vector group, while significantly lower in the si-RAD51AP1 group than in the siNC group (Fig. 4D–F, P < 0.01). Besides, compared with the Vector group, the IC50 of cells treated by paclitaxel, cisplatin, and doxorubicin in the RAD51AP1 group was significantly raised; in contrast to the siNC group, the IC50 of cells treated by paclitaxel, cisplatin, and doxorubicin in the si-RAD51AP1 group was significantly lower (Fig. 4D–F, P < 0.01). The above outcomes indicated that the elevated expression level of RAD51AP1 promoted drug resistance in OCSCs, while the knock-down of RAD51AP1 expression level could significantly enhance the sensitivity of OCSCs to chemotherapeutic drugs.

Fig. 4 MTT analysis for the viability of cells in each group treated with different chemotherapeutic agents. A–C MTT analysis for the viability curves (top) and corresponding IC50 values (bottom) of CD133+OVCAR4 and CD133−OVCAR4 cells after treatment with different concentrations of paclitaxel (A), cisplatin (B), and doxorubicin (C). **P < 0.01. D–F After over-expression and knockdown of RAD51AP1 in CD133+ OVCAR4 cells, MTT assay was performed to analyze the viability curves (top) and corresponding IC50 values (bottom) of cells in each group after treatment with different concentrations of paclitaxel (D), cisplatin (E) and doxorubicin (F). **P < 0.01 vs. Vector group; ##P < 0.01 vs. siNC group. IC50: half maximal inhibitory concentration; CD133+: CD133 positive; CD133−: CD133 negative; RAD51AP1: RAD51-associated protein 1

RAD51-associated protein 1 (RAD51AP1) regulates CD133 positive (CD133+) OVCAR4 activity through the TGF-β1/SMAD4 signaling pathway

The TGF-β1/SMAD4 signaling pathway plays an important regulatory role in tumors [29]. To examine whether RAD51AP1 regulated the biological activity of OCSCs through the TGF-β1/SMAD4 signaling pathway, the protein expression levels of TGF-β1 and SMAD4 in each group were analyzed using western blot after over-expression and knock-down of RAD51AP1 in CD133+OVCAR4 cells. The analysis results showed that, compared with the Vector group, the protein level of TGF-β1 was significantly higher while the expression level of SMAD4 was much lower in the cells of the RAD51AP1 group. However, in comparison with the siNC group, the protein level of TGF-β1 was markedly lower while the expression level of SMAD4 was significantly higher in the cells of the si-RAD51AP1 group (Fig. 5A, B, P < 0.01). Consequently, RAD51AP1 may regulate the biological activity of OCSCs through the TGF-β1/SMAD4 signaling pathway.

Fig. 5 RAD51-associated protein 1 (RAD51AP1) regulates CD133 positive (CD133+) OVCAR4 activity through the TGF-β1/SMAD4 signaling pathway. A, B Protein expression levels of TGF-β1 and SMAD4 were detected using western blot (A) and statistically analyzed (B) after over-expression and knock-down of RAD51AP1 in CD133+OVCAR4 cells (A). **P < 0.01 vs. Vector group; ##P < 0.01 vs. siNC group

Discussion

OC has the highest mortality rate among gynecological malignancies, and chemotherapy is one of the most common treatment options for OC [30]. However, recurrence and drug resistance remain a challenge for clinical treatment of patients with advanced tumors. Therefore, it is necessary to elucidate the molecular biology and mechanisms associated with chemosensitivity to improve the survival of OC patients. OCSCs play an important regulatory role in OC recurrence, metastasis and drug resistance [13]. Although a number of studies have reported the mechanisms of drug resistance in OCSCs [31–33], further research and refinement are still needed to provide new directions and theoretical guidance for the treatment of OC.

OCSCs are identified and characterized by specific markers on cell membrane surface and intracellular markers [34, 35]. Ferrandina et al. first identified CD133 in OC [36]. Besides, it is reported that OC cells with CD133+ phenotype have more strong proliferation and colony ability than CD133− cells [37]. In this study, CD133 was adopted to analyze the CD133 expression level in OVCAR4 cell line. The results revealed that about 10% of cells expressed CD133+. Moreover, our experimental results demonstrated that CD133+OVCAR4 cells had greater self-renewal capacity and proliferation activity, consistent with the findings of Ricci et al. [37]. In addition, our drug resistance analysis showed that CD133+OVCAR4 cells had more prominent drug resistance, consistent with the findings of Liu et al. The above results not only demonstrated the role of CD133 in the characterization and recognition of OCSCs in OVCAR4 cell lines, but also verified the important function of OCSCs in OC proliferation and chemotherapeutic drug resistance.

RAD51AP1 not only exerts a central function in HR and gene integrity, but also plays a vital role in promoting signal transduction in the early growth phase of tumors [38, 39]. Through bioinformatics analysis, Filipe et al. found that RAD51AP1 showed a trend of high expression in OC tissues [16]. The experimental data in this study also demonstrated the high expression level of RAD51AP1 in OC. In addition, RAD51AP1 has been reported to play an important regulatory role in tumour stem cells. For example, Bridges et al. claimed that defects in RAD51AP1 played a key role in chemoresistance by inhibiting the self-renewal of colorectal cancer stem cells (CRCSC) and making cancer cells re-sensitive to chemotherapy [20]. Moreover, Bridges et al. also demonstrated that RAD51AP1 played a critical regulatory role in the self-renewal of BCSCs through in vivo limiting dilution assays [37]. RAD51AP1 deletion plays a protective role in spontaneous breast tumor and related lung metastasis in mice and can improve the efficacy of chemotherapy and radiotherapy. However, there are no studies that RAD51AP1 is associated with the self-renewal and chemoresistance of OCSCs. In this study, RAD51AP1 protein expression levels were significantly elevated in OCSCs, suggesting the possibility that RAD51AP1 also played an important regulatory role in OCSCs. The RAD51AP1 expression was over-expressed and knocked down in vitro using the CD133+OVCAR4 cell model. Our experimental results directly demonstrated that over-expression of RAD51AP1 significantly not only promoted the self-renewal and proliferation of CD133+OVCAR4, but also enhanced its tolerance to chemotherapeutic agents; whereas knock-down of RAD51AP1 significantly inhibited the self-renewal and proliferation of CD133+OVCAR4, and made cells re-sensitive to chemotherapeutic agents. Our findings are consistent with those of Bridges et al. in CRCSCs and BCSCs. All these studies have confirmed the important regulatory role of RAD51AP1 in the self-renewal and chemoresistance of tumour stem cells and further expanded our understanding of RAD51AP1 in different tumour models.

Notably, a study by Bridges et al. found that knock-down of RAD51AP1 gene significantly inhibited the tumor growth in a mouse model of colorectal cancer, but did not influence the normal homeostasis of the colonic epithelium, suggesting that RAD51AP1 did not affect the growth of normal cells [20]. This finding provides support for the exploration of RAD51AP1 serving as a potential therapeutic target for colorectal cancer. Considering the over-expression of RAD51AP1 in colorectal cancer patients, therapeutic strategies targeting RAD51AP1 only have a positive impact on cancer treatment without adversely affecting the growth of normal cells. Therefore, functional inactivation of RAD51AP1 has important potential in cancer prevention and treatment. Although we did not use the RAD51AP1 knock-down mouse model to analyse the growth status of ovarian epithelial cells in this study, given the conserved nature of the gene function and the results of this study, we hypothesized great potential of RAD51AP1 as a therapeutic target of OC. However, further experimental studies are required to confirm this inference.

There are four key genes involved in stem cell pluripotency, including SOX2, OCT4, KLF4 and NANOG, of which NANOG is the major regulator [40]. NANOG is a transcription factor involved in maintaining the self-renewal of stem cells. Many studies have proved the role of NANOG in normal and cancer stem cell function. High NANOG expression level is associated with a variety of cancers, including melanoma, glioma, colorectal cancer, and hepatocellular carcinoma. Also, high NANOG expression level is correlated with processes such as over-proliferation, drug resistance, and apoptosis inhibition [41]. After over-expression of RAD51AP1, we found that the expression level of NANOG was significantly increased in CD133+ OVCAR4 cells; whereas after knockdown of RAD51AP1, the expression level of NANOG was significantly decreased. Such result suggested that RAD51AP1 regulated the self-renewal ability of OCSCs by affecting NANOG. Liu et al. stated that NANOG regulated the proliferation of prostate cancer stem cells (PCSCs) through the TGF-β1/SMAD signaling pathway [42]. Besides, Xu et al. discovered that NANOG acted as a direct target of TGF-β/Activin-mediated SMAD signaling in human embryonic stem (ES) cells, and played a key role in maintaining self-renewal of human ES cells [43]. Therefore, we hypothesized that RAD51AP1 may regulate the expression level of NANOG in OCSCs by affecting the TGF-β1/SMAD signaling pathway. To prove this hypothesis, we examined the protein levels of TGF-β1 and SMAD. The results showed that the SMAD4 protein expression level increased significantly after knocking down RAD51AP1. It has been reported that SMAD4 is an oncogene capable of suppressing the expression of genes related to tumour growth [44]. In this study, the elevated expression level of SMAD4 not only suppressed the expression of NANOG, but also down-regulated the expression levels of SOX2, OCT4, and KLF4; the down-regulation of the expression levels of these pluripotent genes ultimately suppressed the self-renewal ability of OCSCs and enhanced the sensitivity of tumor cells to chemotherapeutic drugs. Similarly, Zhao et al. also stated that RAD51AP1 regulated the OC progression through the TGF-β1/SMAD signaling pathway [45]. However, compared with the study of Zhao et al., our experimental data further demonstrated that RAD51AP1 regulated OC progression by affecting the TGF-β1/SMAD signaling pathway in OCSCs. Such finding provides a more precise theoretical basis for our in-depth understanding to the function of OCSCs and the molecular mechanism of OC. Notably, the results of Zhao et al. revealed that the expression level of SMAD4 presented a down-regulation trend after knock-down of RAD51AP1 in serous ovarian carcinoma cell line (SKOV3). Such result may be caused by the variability among cell lines, and the mechanism behind it deserves more in-depth study in the future.

Although our study elucidates the possible mechanism by which RAD51AP1 promotes OC resistance. However, our study only explored single cell lines, and future research will need to investigate the characteristics of RAD51AP1 on other types of tumor stem cells, such as CD133+/CD117+, CD44+/CD177, CD44+/CD24 −. In addition, we have not demonstrated our conclusion in animal bodies, and in the next study, we can conduct experimental studies in nude mice.

Conclusion

In this study, our results demonstrated that RAD51AP1 plays an important regulatory role in OCSCs. Briefly, knock-down of RAD51AP1 can inhibit the expression levels of genes associated with pluripotency, including NANOG, SOX2, OCT4, and KLF4, through the TGF-β1/SMAD signaling pathway. Down-regulation of the levels of these genes ultimately inhibits OCSCs’ self renewal, proliferation and resistance to chemotherapeutic drugs. The findings of this study not only help us better understand the mechanism of drug resistance in OCSCs, but also provide new targets for the development of anticancer drugs against OCs. These new targets are expected to overcome the problem of resistance to conventional chemotherapeutic drugs, thereby providing a more effective strategy for the treatment of OC.

Acknowledgements

Not applicable.

Author contributions

Si-heng Zeng designed the study. Zhi-qiang Yan, Qing Ren and Li-hui Lin collated the data, carried out data analyses and produced the initial draft of the manuscript. Zhen Chen contributed to drafting the manuscript. All authors have read and approved the final submitted manuscript.

Funding

This study is supported by Hainan Provincial Health Industry Research Project (21A200308).

Data availability

All data can be obtained from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

This study was approved by the Ethics Committee of Hainan West Central Hospital (No. SH9H-2019-A681-1), and all patients signed written informed consent.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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References

1. Sung H Ferlay J Siegel RL Laversanne M Soerjomataram I Jemal A Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries CA Cancer J Clin 2021 71 3 209 49 10.3322/caac.21660 33538338
Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49.33538338 10.3322/caac.21660
2. Nash Z Menon U Ovarian cancer screening: current status and future directions Best Pract Res Clin Obstet Gynaecol 2020 65 32 45 10.1016/j.bpobgyn.2020.02.010 32273169
Nash Z, Menon U. Ovarian cancer screening: current status and future directions. Best Pract Res Clin Obstet Gynaecol. 2020;65:32–45.32273169 10.1016/j.bpobgyn.2020.02.010
3. Stewart C Ralyea C Lockwood S Ovarian cancer: an integrated review Semin Oncol Nurs 2019 35 2 151 6 10.1016/j.soncn.2019.02.001 30867104
Stewart C, Ralyea C, Lockwood S. Ovarian cancer: an integrated review. Semin Oncol Nurs. 2019;35(2):151–6.30867104 10.1016/j.soncn.2019.02.001
4. Penny SM Ovarian cancer: an overview Radiol Technol 2020 91 6 561 75 32606233
Penny SM. Ovarian cancer: an overview. Radiol Technol. 2020;91(6):561–75.32606233
5. Pujade-Lauraine E Combe P Recurrent ovarian cancer Ann Oncol 2016 27 Suppl 1 i63 5 10.1093/annonc/mdw079 27141075
Pujade-Lauraine E, Combe P. Recurrent ovarian cancer. Ann Oncol. 2016;27(Suppl 1):i63–5.27141075 10.1093/annonc/mdw079
6. Yang L Xie HJ Li YY Wang X Liu XX Mai J Molecular mechanisms of platinum–based chemotherapy resistance in ovarian cancer (review) Oncol Rep. 2022 47 4 82 10.3892/or.2022.8293 35211759
Yang L, Xie HJ, Li YY, Wang X, Liu XX, Mai J. Molecular mechanisms of platinum–based chemotherapy resistance in ovarian cancer (review). Oncol Rep. 2022;47(4):82.35211759 10.3892/or.2022.8293
7. Zhang T Xu J Deng S Zhou F Li J Zhang L Core signaling pathways in ovarian cancer stem cell revealed by integrative analysis of multi-marker genomics data PLoS ONE 2018 13 5 e0196351 10.1371/journal.pone.0196351 29723215
Zhang T, Xu J, Deng S, Zhou F, Li J, Zhang L, et al. Core signaling pathways in ovarian cancer stem cell revealed by integrative analysis of multi-marker genomics data. PLoS ONE. 2018;13(5):e0196351.29723215 10.1371/journal.pone.0196351
8. Pieterse Z Amaya-Padilla MA Singomat T Binju M Madjid BD Yu Y Ovarian cancer stem cells and their role in drug resistance Int J Biochem Cell Biol 2019 106 117 26 10.1016/j.biocel.2018.11.012 30508594
Pieterse Z, Amaya-Padilla MA, Singomat T, Binju M, Madjid BD, Yu Y, et al. Ovarian cancer stem cells and their role in drug resistance. Int J Biochem Cell Biol. 2019;106:117–26.30508594 10.1016/j.biocel.2018.11.012
9. Skubitz AP Taras EP Boylan KL Waldron NN Oh S Panoskaltsis-Mortari A Targeting CD133 in an in vivo ovarian cancer model reduces ovarian cancer progression Gynecol Oncol 2013 130 3 579 87 10.1016/j.ygyno.2013.05.027 23721800
Skubitz AP, Taras EP, Boylan KL, Waldron NN, Oh S, Panoskaltsis-Mortari A, et al. Targeting CD133 in an in vivo ovarian cancer model reduces ovarian cancer progression. Gynecol Oncol. 2013;130(3):579–87.23721800 10.1016/j.ygyno.2013.05.027
10. Klemba A Purzycka-Olewiecka JK Wcislo G Czarnecka AM Lewicki S Lesyng B Surface markers of cancer stem-like cells of ovarian cancer and their clinical relevance Contemp Oncol 2018 22 1A 48 55
Klemba A, Purzycka-Olewiecka JK, Wcislo G, Czarnecka AM, Lewicki S, Lesyng B, et al. Surface markers of cancer stem-like cells of ovarian cancer and their clinical relevance. Contemp Oncol. 2018;22(1A):48–55.
11. Guo C Song C Zhang J Gao Y Qi Y Zhao Z Revisiting chemoresistance in ovarian cancer: mechanism, biomarkers, and precision medicine Genes Dis 2022 9 3 668 81 10.1016/j.gendis.2020.11.017 35782973
Guo C, Song C, Zhang J, Gao Y, Qi Y, Zhao Z, et al. Revisiting chemoresistance in ovarian cancer: mechanism, biomarkers, and precision medicine. Genes Dis. 2022;9(3):668–81.35782973 10.1016/j.gendis.2020.11.017
12. Fletcher JI Williams RT Henderson MJ Norris MD Haber M ABC transporters as mediators of drug resistance and contributors to cancer cell biology Drug Resist Updat 2016 26 1 9 10.1016/j.drup.2016.03.001 27180306
Fletcher JI, Williams RT, Henderson MJ, Norris MD, Haber M. ABC transporters as mediators of drug resistance and contributors to cancer cell biology. Drug Resist Updat. 2016;26:1–9.27180306 10.1016/j.drup.2016.03.001
13. Ottevanger PB Ovarian cancer stem cells more questions than answers Semin Cancer Biol 2017 44 67 71 10.1016/j.semcancer.2017.04.009 28450177
Ottevanger PB. Ovarian cancer stem cells more questions than answers. Semin Cancer Biol. 2017;44:67–71.28450177 10.1016/j.semcancer.2017.04.009
14. Pires E Sung P Wiese C Role of RAD51AP1 in homologous recombination DNA repair and carcinogenesis DNA Repair 2017 59 76 81 10.1016/j.dnarep.2017.09.008 28963981
Pires E, Sung P, Wiese C. Role of RAD51AP1 in homologous recombination DNA repair and carcinogenesis. DNA Repair. 2017;59:76–81.28963981 10.1016/j.dnarep.2017.09.008
15. Wiese C Dray E Groesser T San Filippo J Shi I Collins DW Promotion of homologous recombination and genomic stability by RAD51AP1 via RAD51 recombinase enhancement Mol Cell 2007 28 3 482 90 10.1016/j.molcel.2007.08.027 17996711
Wiese C, Dray E, Groesser T, San Filippo J, Shi I, Collins DW, et al. Promotion of homologous recombination and genomic stability by RAD51AP1 via RAD51 recombinase enhancement. Mol Cell. 2007;28(3):482–90.17996711 10.1016/j.molcel.2007.08.027
16. Filipe A Katopodis P Chudasama D Kerslake R Jeyaneethi J Anikin V Differential expression of RAD51AP1 in ovarian cancer: effects of siRNA in vitro J Pers Med. 2022 12 2 201 10.3390/jpm12020201 35207688
Filipe A, Katopodis P, Chudasama D, Kerslake R, Jeyaneethi J, Anikin V, et al. Differential expression of RAD51AP1 in ovarian cancer: effects of siRNA in vitro. J Pers Med. 2022;12(2):201.35207688 10.3390/jpm12020201
17. Obama K Satoh S Hamamoto R Sakai Y Nakamura Y Furukawa Y Enhanced expression of RAD51 associating protein-1 is involved in the growth of intrahepatic cholangiocarcinoma cells Clin Cancer Res 2008 14 5 1333 9 10.1158/1078-0432.CCR-07-1381 18316552
Obama K, Satoh S, Hamamoto R, Sakai Y, Nakamura Y, Furukawa Y. Enhanced expression of RAD51 associating protein-1 is involved in the growth of intrahepatic cholangiocarcinoma cells. Clin Cancer Res. 2008;14(5):1333–9.18316552 10.1158/1078-0432.CCR-07-1381
18. Zhuang L Zhang Y Meng Z Yang Z Oncogenic roles of RAD51AP1 in tumor tissues related to overall survival and disease-free survival in hepatocellular carcinoma Cancer Control 2020 27 1 1073274820977149 10.1177/1073274820977149 33269607
Zhuang L, Zhang Y, Meng Z, Yang Z. Oncogenic roles of RAD51AP1 in tumor tissues related to overall survival and disease-free survival in hepatocellular carcinoma. Cancer Control. 2020;27(1):1073274820977149.33269607 10.1177/1073274820977149
19. Bridges AE Ramachandran S Pathania R Parwal U Lester A Rajpurohit P RAD51AP1 deficiency reduces tumor growth by targeting stem cell self-renewal Cancer Res 2020 80 18 3855 66 10.1158/0008-5472.CAN-19-3713 32665355
Bridges AE, Ramachandran S, Pathania R, Parwal U, Lester A, Rajpurohit P, et al. RAD51AP1 deficiency reduces tumor growth by targeting stem cell self-renewal. Cancer Res. 2020;80(18):3855–66.32665355 10.1158/0008-5472.CAN-19-3713
20. Bridges AE Ramachandran S Tamizhmani K Parwal U Lester A Rajpurohit P RAD51AP1 loss attenuates colorectal cancer stem cell renewal and sensitizes to chemotherapy Mol Cancer Res 2021 19 9 1486 97 10.1158/1541-7786.MCR-20-0780 34099522
Bridges AE, Ramachandran S, Tamizhmani K, Parwal U, Lester A, Rajpurohit P, et al. RAD51AP1 loss attenuates colorectal cancer stem cell renewal and sensitizes to chemotherapy. Mol Cancer Res. 2021;19(9):1486–97.34099522 10.1158/1541-7786.MCR-20-0780
21. Starbuck K Al-Alem L Eavarone DA Hernandez SF Bellio C Prendergast JM Treatment of ovarian cancer by targeting the tumor stem cell-associated carbohydrate antigen, Sialyl-Thomsen-Nouveau Oncotarget 2018 9 33 23289 305 10.18632/oncotarget.25289 29796189
Starbuck K, Al-Alem L, Eavarone DA, Hernandez SF, Bellio C, Prendergast JM, et al. Treatment of ovarian cancer by targeting the tumor stem cell-associated carbohydrate antigen, Sialyl-Thomsen-Nouveau. Oncotarget. 2018;9(33):23289–305.29796189 10.18632/oncotarget.25289
22. Poursheikhani A Yousefi H Tavakoli-Bazzaz J Seyed HG EGFR blockade reverses cisplatin resistance in human epithelial ovarian cancer cells Iran Biomed J 2020 24 6 370 8 32660222
Poursheikhani A, Yousefi H, Tavakoli-Bazzaz J, Seyed HG. EGFR blockade reverses cisplatin resistance in human epithelial ovarian cancer cells. Iran Biomed J. 2020;24(6):370–8.32660222
23. Zhang H Hu L Cheng M Wang Q Hu X Chen Q The hedgehog signaling pathway promotes chemotherapy resistance via multidrug resistance protein 1 in ovarian cancer Oncol Rep 2020 44 6 2610 20 10.3892/or.2020.7798 33125122
Zhang H, Hu L, Cheng M, Wang Q, Hu X, Chen Q. The hedgehog signaling pathway promotes chemotherapy resistance via multidrug resistance protein 1 in ovarian cancer. Oncol Rep. 2020;44(6):2610–20.33125122 10.3892/or.2020.7798
24. Guo N Gao C Liu J Li J Liu N Hao Y Reversal of ovarian cancer multidrug resistance by a combination of LAH4-L1-siMDR1 nanocomplexes with chemotherapeutics Mol Pharm 2018 15 5 1853 61 10.1021/acs.molpharmaceut.8b00031 29621396
Guo N, Gao C, Liu J, Li J, Liu N, Hao Y, et al. Reversal of ovarian cancer multidrug resistance by a combination of LAH4-L1-siMDR1 nanocomplexes with chemotherapeutics. Mol Pharm. 2018;15(5):1853–61.29621396 10.1021/acs.molpharmaceut.8b00031
25. Fan M Shi Y Zhao J Li L Cancer stem cell fate determination: mito-nuclear communication Cell Commun Signal 2023 21 1 159 10.1186/s12964-023-01160-x 37370081
Fan M, Shi Y, Zhao J, Li L. Cancer stem cell fate determination: mito-nuclear communication. Cell Commun Signal. 2023;21(1):159.37370081 10.1186/s12964-023-01160-x
26. Barzegar Behrooz A Syahir A Ahmad S CD133: beyond a cancer stem cell biomarker J Drug Target 2019 27 3 257 69 10.1080/1061186X.2018.1479756 29911902
Barzegar Behrooz A, Syahir A, Ahmad S. CD133: beyond a cancer stem cell biomarker. J Drug Target. 2019;27(3):257–69.29911902 10.1080/1061186X.2018.1479756
27. van Schaijik B Davis PF Wickremesekera AC Tan ST Itinteang T Subcellular localisation of the stem cell markers OCT4, SOX2, NANOG, KLF4 and c-MYC in cancer: a review J Clin Pathol 2018 71 1 88 91 10.1136/jclinpath-2017-204815 29180509
van Schaijik B, Davis PF, Wickremesekera AC, Tan ST, Itinteang T. Subcellular localisation of the stem cell markers OCT4, SOX2, NANOG, KLF4 and c-MYC in cancer: a review. J Clin Pathol. 2018;71(1):88–91.29180509 10.1136/jclinpath-2017-204815
28. Huang T Song X Xu D Tiek D Goenka A Wu B Stem cell programs in cancer initiation, progression, and therapy resistance Theranostics 2020 10 19 8721 43 10.7150/thno.41648 32754274
Huang T, Song X, Xu D, Tiek D, Goenka A, Wu B, et al. Stem cell programs in cancer initiation, progression, and therapy resistance. Theranostics. 2020;10(19):8721–43.32754274 10.7150/thno.41648
29. Zhao M Mishra L Deng CX The role of TGF-beta/SMAD4 signaling in cancer Int J Biol Sci 2018 14 2 111 23 10.7150/ijbs.23230 29483830
Zhao M, Mishra L, Deng CX. The role of TGF-beta/SMAD4 signaling in cancer. Int J Biol Sci. 2018;14(2):111–23.29483830 10.7150/ijbs.23230
30. Eisenhauer EA Real-world evidence in the treatment of ovarian cancer Ann Oncol 2017 28 suppl8 viii61 5 10.1093/annonc/mdx443 29232466
Eisenhauer EA. Real-world evidence in the treatment of ovarian cancer. Ann Oncol. 2017;28(suppl8):viii61–5.29232466 10.1093/annonc/mdx443
31. Koltai H Shalev N Anti-cancer activity of Cannabis sativa phytocannabinoids: molecular mechanisms and potential in the fight against ovarian cancer and stem cells Cancers (Basel). 2022 14 17 4299 10.3390/cancers14174299 36077833
Koltai H, Shalev N. Anti-cancer activity of Cannabis sativa phytocannabinoids: molecular mechanisms and potential in the fight against ovarian cancer and stem cells. Cancers (Basel). 2022;14(17):4299.36077833 10.3390/cancers14174299
32. He M Wu H Jiang Q Liu Y Han L Yan Y Hypoxia-inducible factor-2alpha directly promotes BCRP expression and mediates the resistance of ovarian cancer stem cells to adriamycin Mol Oncol 2019 13 2 403 21 10.1002/1878-0261.12419 30536571
He M, Wu H, Jiang Q, Liu Y, Han L, Yan Y, et al. Hypoxia-inducible factor-2alpha directly promotes BCRP expression and mediates the resistance of ovarian cancer stem cells to adriamycin. Mol Oncol. 2019;13(2):403–21.30536571 10.1002/1878-0261.12419
33. Wang K Wang Y Wang Y Liu S Wang C Zhang S EIF5A2 enhances stemness of epithelial ovarian cancer cells via a E2F1/KLF4 axis Stem Cell Res Ther 2021 12 1 186 10.1186/s13287-021-02256-2 33726845
Wang K, Wang Y, Wang Y, Liu S, Wang C, Zhang S, et al. EIF5A2 enhances stemness of epithelial ovarian cancer cells via a E2F1/KLF4 axis. Stem Cell Res Ther. 2021;12(1):186.33726845 10.1186/s13287-021-02256-2
34. Cojoc M Mabert K Muders MH Dubrovska A A role for cancer stem cells in therapy resistance: cellular and molecular mechanisms Semin Cancer Biol 2015 31 16 27 10.1016/j.semcancer.2014.06.004 24956577
Cojoc M, Mabert K, Muders MH, Dubrovska A. A role for cancer stem cells in therapy resistance: cellular and molecular mechanisms. Semin Cancer Biol. 2015;31:16–27.24956577 10.1016/j.semcancer.2014.06.004
35. Burgos-Ojeda D Rueda BR Buckanovich RJ Ovarian cancer stem cell markers: prognostic and therapeutic implications Cancer Lett 2012 322 1 1 7 10.1016/j.canlet.2012.02.002 22334034
Burgos-Ojeda D, Rueda BR, Buckanovich RJ. Ovarian cancer stem cell markers: prognostic and therapeutic implications. Cancer Lett. 2012;322(1):1–7.22334034 10.1016/j.canlet.2012.02.002
36. Ferrandina G Martinelli E Petrillo M Prisco MG Zannoni G Sioletic S CD133 antigen expression in ovarian cancer BMC Cancer 2009 9 221 10.1186/1471-2407-9-221 19583859
Ferrandina G, Martinelli E, Petrillo M, Prisco MG, Zannoni G, Sioletic S, et al. CD133 antigen expression in ovarian cancer. BMC Cancer. 2009;9:221.19583859 10.1186/1471-2407-9-221
37. Ricci F Bernasconi S Porcu L Erba E Panini N Fruscio R ALDH enzymatic activity and CD133 positivity and response to chemotherapy in ovarian cancer patients Am J Cancer Res 2013 3 2 221 9 23593543
Ricci F, Bernasconi S, Porcu L, Erba E, Panini N, Fruscio R, et al. ALDH enzymatic activity and CD133 positivity and response to chemotherapy in ovarian cancer patients. Am J Cancer Res. 2013;3(2):221–9.23593543
38. Kaminski N Wondisford AR Kwon Y Lynskey ML Bhargava R Barroso-Gonzalez J RAD51AP1 regulates ALT-HDR through chromatin-directed homeostasis of TERRA Mol Cell 2022 82 21 4001 e177 10.1016/j.molcel.2022.09.025 36265488
Kaminski N, Wondisford AR, Kwon Y, Lynskey ML, Bhargava R, Barroso-Gonzalez J, et al. RAD51AP1 regulates ALT-HDR through chromatin-directed homeostasis of TERRA. Mol Cell. 2022;82(21):4001–e177.36265488 10.1016/j.molcel.2022.09.025
39. Ni M Li J Zhao H Xu F Cheng J Yu M BRD4 inhibition sensitizes cervical cancer to radiotherapy by attenuating DNA repair Oncogene 2021 40 15 2711 24 10.1038/s41388-021-01735-3 33712705
Ni M, Li J, Zhao H, Xu F, Cheng J, Yu M, et al. BRD4 inhibition sensitizes cervical cancer to radiotherapy by attenuating DNA repair. Oncogene. 2021;40(15):2711–24.33712705 10.1038/s41388-021-01735-3
40. Yang L Shi P Zhao G Xu J Peng W Zhang J Targeting cancer stem cell pathways for cancer therapy Signal Transduct Target Ther 2020 5 1 8 10.1038/s41392-020-0110-5 32296030
Yang L, Shi P, Zhao G, Xu J, Peng W, Zhang J, et al. Targeting cancer stem cell pathways for cancer therapy. Signal Transduct Target Ther. 2020;5(1):8.32296030 10.1038/s41392-020-0110-5
41. Jeter CR Badeaux M Choy G Chandra D Patrawala L Liu C Functional evidence that the self-renewal gene NANOG regulates human tumor development Stem Cells 2009 27 5 993 1005 10.1002/stem.29 19415763
Jeter CR, Badeaux M, Choy G, Chandra D, Patrawala L, Liu C, et al. Functional evidence that the self-renewal gene NANOG regulates human tumor development. Stem Cells. 2009;27(5):993–1005.19415763 10.1002/stem.29
42. Liu C Sheng M Lin L Li H Guo S Zhang J NANOG regulates the proliferation of PCSCs via the TGF-beta1/SMAD pathway Open Med 2020 15 1 841 9 10.1515/med-2020-0221
Liu C, Sheng M, Lin L, Li H, Guo S, Zhang J, et al. NANOG regulates the proliferation of PCSCs via the TGF-beta1/SMAD pathway. Open Med. 2020;15(1):841–9.10.1515/med-2020-0221
43. Xu RH Sampsell-Barron TL Gu F Root S Peck RM Pan G NANOG is a direct target of TGFbeta/activin-mediated SMAD signaling in human ESCs Cell Stem Cell 2008 3 2 196 206 10.1016/j.stem.2008.07.001 18682241
Xu RH, Sampsell-Barron TL, Gu F, Root S, Peck RM, Pan G, et al. NANOG is a direct target of TGFbeta/activin-mediated SMAD signaling in human ESCs. Cell Stem Cell. 2008;3(2):196–206.18682241 10.1016/j.stem.2008.07.001
44. Chou JL Su HY Chen LY Liao YP Hartman-Frey C Lai YH Promoter hypermethylation of FBXO32, a novel TGF-beta/SMAD4 target gene and tumor suppressor, is associated with poor prognosis in human ovarian cancer Lab Invest 2010 90 3 414 25 10.1038/labinvest.2009.138 20065949
Chou JL, Su HY, Chen LY, Liao YP, Hartman-Frey C, Lai YH, et al. Promoter hypermethylation of FBXO32, a novel TGF-beta/SMAD4 target gene and tumor suppressor, is associated with poor prognosis in human ovarian cancer. Lab Invest. 2010;90(3):414–25.20065949 10.1038/labinvest.2009.138
45. Zhao H Gao Y Chen Q Li J Ren M Zhao X RAD51AP1 promotes progression of ovarian cancer via TGF-beta/Smad signalling pathway J Cell Mol Med 2021 25 4 1927 38 10.1111/jcmm.15877 33314567
Zhao H, Gao Y, Chen Q, Li J, Ren M, Zhao X, et al. RAD51AP1 promotes progression of ovarian cancer via TGF-beta/Smad signalling pathway. J Cell Mol Med. 2021;25(4):1927–38.33314567 10.1111/jcmm.15877
