Downregulation of PIF1 induce DNA damage and inhibit ovarian cancer cell proliferation via RAD51

Downregulation of PIF1 induce DNA damage and inhibit ovarian cancer cell proliferation via RAD51 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Downregulation of PIF1 induce DNA damage and inhibit ovarian cancer cell proliferation via RAD51 Qi-Yin Zhou, Yu-Xin Hua, Qing-Qing Sun, Shang-Pu Zou, Jia-Lin Guo, and 13 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4495865/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background PIF1 helicase (5ʹ→3ʹ DNA helicase) is a member of helicase superfamily 1. It has unwinding activity and plays a crucial role in maintaining genome stability and coordinating DNA damage repair processes. Overexpression of PIF1 is common in several cancers; however, its role in ovarian cancer remains unclear. This study aimed to elucidate the regulatory role of PIF1 in ovarian cancer and explore its mechanism. Results Analysis of patient samples and public database datasets revealed a negative correlation between PIF1 overexpression and the overall survival rate of the patients. We found through molecular biology experiments and xenograft tumor models in nude mice that CRISPR/Cas9-mediated PIF1 partial knockdown in ovarian cancer cell lines significantly inhibited proliferation and clonogenicity, promoted senescence, and induced G2 cell cycle arrest. Moreover, PIF1 partial deficiency enhanced DNA damage in ovarian cancer cells, particularly sensitive to cisplatin. RAD51 serves as a central scaffold protein for homologous recombination repair and is crucial for timely and accurate DNA repair. We observed that PIF1 partial knockdown resulted in significant reduction of RAD51 in ovarian cancer cells. Notably, RAD51 overexpression in PIF1 partially deficient ovarian cancer cells rescued cell proliferation and DNA damage by increasing PIF1 expression. Immunofluorescence revealed the co-localization of EGFP-PIF1 and RAD51 in the cell nucleus, suggesting that the interaction between PIF1 and RAD51 may regulate the DNA damage response and cell survival in ovarian cancer cells. Conclusions Our study revealed that PIF1 is a druggable target for inducing DNA damage in ovarian cancer cells and provides insights into the potential synergistic mechanisms of action between PIF1 and RAD51 in ovarian cancer therapy. ovarian cancer DNA helicase PIF1 RAD51 proliferation DNA damage and repair chemoresistance poor prognosis homologous recombination Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Ovarian cancer is a common gynecologic malignancy. Early-stage disease lacks specific symptoms, thus effective screening-diagnostic methods are lacking [ 1 , 2 ]. Consequently, the global incidence and mortality rates of ovarian cancer remain high. According to the World Health Organization, approximately 324,603 new cases of ovarian cancer and 206,956 related deaths occurred in 2022 [ 3 ], suggesting a need for novel approaches to improving survival and quality of life among patients. The traditional treatment for ovarian cancer involves surgical intervention combined with adjuvant chemotherapy comprising platinum-based drugs (typically carboplatin) and taxanes (generally paclitaxel). However, drug resistance often develops during the treatment of ovarian cancer, resulting in poor outcomes and limiting treatment options. Drug resistance occurs due to several reasons, including reduced intracellular drug accumulation mediated by drug efflux proteins, altered apoptotic pathways, enhanced DNA repair, and drug resistance caused by tumor stem cells [ 4 ]. Ovarian cancer resistance is primarily caused by enhanced DNA damage repair [ 5 , 6 ]. Therefore, many studies have focused on ovarian cancer DNA repair defects as key targets for treatment [ 7 ]. PIF1 helicase (5ʹ→3ʹ DNA helicase), a member of the helicase superfamily 1, translocates along single-stranded DNA and unwinds double-stranded DNA in the 5ʹ→3ʹ direction [ 8 ]. PIF1 helicases localize to and facilitate the advancement of replication forks [ 9 ]. Additionally, PIF1 facilitates Okazaki fragment synthesis [ 10 ]. It also plays a crucial role in maintaining mitochondrial genome stability [ 11 – 13 ] and DNA damage repair. PIF1 participates in break-induced replication (BIR) [ 9 ]. During homologous recombination repair of DNA double-strand breaks (DSBs), human PIF1 interacts with BRCA1 to enhance the removal of G4 sequences [ 14 ]. PIF1 regulates telomerase activity in various organisms [ 15 – 19 ]. In humans, the interaction between PIF1 and telomerase reverse transcriptase promotes cervical cancer cell proliferation [ 20 ]. PIF1 expression in cancers has been extensively explored. PIF1 is overexpressed in clear cell renal cell carcinoma [ 21 ] and pancreatic cancer [ 22 ]. Low PIF1 expression is associated with a favorable prognosis in patients with neuroblastoma [ 23 ]. PIF1 knockdown promotes ferroptosis in lung adenocarcinoma [ 24 ]. Importantly, loss of PIF1 significantly increases tumor cell sensitivity to many chemotherapeutic drugs [ 22 , 25 , 26 ]. Thus, PIF1 plays a crucial role in cancer and serves as a potential chemotherapy target. Nevertheless, the precise function of PIF1 in regulating ovarian cancer is still unclear. This study therefore aimed to elucidate the regulatory role of PIF1 in ovarian cancer. Specifically, we investigated whether knocking out PIF1 affects the proliferation and chemoresistance of ovarian cancer cells and explored its potential as a prognostic marker and therapeutic target. Furthermore, this study examined the interaction between PIF1 and RAD51 recombinase (RAD51), aiming to reveal how they cooperatively regulate the proliferation and DNA damage repair mechanisms of ovarian cancer cells, providing a scientific basis for developing new ovarian cancer treatment strategies targeting these molecules. Methods Cell culture and CRISPR/Cas9 gene editing The human ovarian cancer cell lines A2780, HO-8910, ES-2, SKOV3, and OVCAR-3, as well as the human embryonic kidney cell line 293T, were acquired from the American Type Culture Collection (ATCC, Manassas, VA, USA). The benign human ovarian epithelial cell line IOSE was generously supplied by Hengyu Fan from Zhejiang University [ 27 ]. Cells were grown in Dulbecco's modified Eagle's medium (Gibco | Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum (Gibco | Thermo Fisher Scientific) and 1% penicillin-streptomycin (Gibco | Thermo Fisher Scientific). Cells were kept at a temperature of 37°C in a humidified environment with 95% air and 5% CO2, which are the standard culture conditions. PIF1-deficient cells were generated through the application of CRISPR/Cas9 technology. Lentivirus-mediated transfection was used to introduce plasmids into ES-2 and OVCAR-3 cells. Following 24 h of transfection, cells were treated with a concentration of 2 µg/mL puromycin for 3 days. Western blot analysis was employed to validate the partial knockout of the PIF1 gene and to assess PIF1 protein expression levels. Supplementary Table S1 provides the sequences of PIF1 sgRNAs. CRISPR/Cas9 plasmid was kindly provided by Kun-Liang Guan, West Lake University [ 28 ]. Cell proliferation and colony formation For the examination of the cell growth curve, cells were placed in 6-well plates (Corning, New York, NY, USA) at a density of 1 × 10 5 cells per well. Cell counts were performed in triplicate for each well at 24, 48, and 72 h after seeding. In the colony formation experiments, 1.5 mL of bottom agarose, consisting of 0.5% agarose (Sigma-Aldrich, St. Louis, MO, USA) in standard culture medium, was used to coat each well of a 6-well plate. Around 2,500 cells were mixed with 1.5 mL of top agarose, which included 0.35% agarose in a regular growth medium. This mixture was then applied as a layer onto each well. For cellular nourishment, a volume of 2 mL of cell culture media was applied to the topmost layer twice a week. The cells were incubated for 21 days under conventional culture conditions. After this period, they were stained with 0.5% crystal violet (Sigma-Aldrich) to quantify the colonies. There were six replicates in each experimental group. Western blotting Whole-cell lysates were generated with western blot and IP lysis buffer (Beyotime Biotechnology, Shanghai, China), and the protein content was determined using the bicinchoninic acid assay kit (Beyotime Biotechnology). Proteins were subjected to denaturation at a temperature of 95°C for 5 min. Subsequently, protein samples of 20-µg were isolated using SDS-PAGE. The gel was then transferred onto PVDF membranes (Merck | Millipore, Burlington, MA, USA). Membranes were obstructed with 5% milk at room temperature for 1 h, treated with primary antibodies (Table S2 ) against the target protein overnight at 4°C, and then exposed to horseradish peroxidase-conjugated secondary antibodies (Table S2 ) at room temperature for 1 h. Gels were visualized using an enhanced chemiluminescence detection kit (Merck | Millipore). Band intensity was quantified using an Imager 680 (Amersham | GE Healthcare, Chicago, IL, USA) and analyzed with ImageJ software (National Institutes of Health, Bethesda, MD, USA). Immunohistochemistry The tumor tissues removed from the nude mice were preserved overnight in a solution of 4% paraformaldehyde. After fixing, the tissues were dehydrated with ethanol at increasing concentrations. Then, xylene was used to replace the ethanol, and finally, the tissues were embedded in paraffin. The tissue blocks fixed in paraffin were cut into sections with a thickness of 5 µm. The deparaffinized sections were treated in 0.3% hydrogen peroxide (H 2 O 2 ) for 10 min to suppress endogenous peroxidase activity. The process of antigen retrieval was performed using a 10 mM sodium citrate buffer with a pH of 6.0 for 15 min. The sections were subsequently kept at a temperature of 4°C overnight and exposed to primary antibodies targeting PIF1, p-H2AX, BrdU, and RAD51 (Table S2 ). Subsequently, the sections were treated with biotinylated and peroxidase-conjugated secondary antibodies (1:400; Cell Signaling Technology, Danvers, MA, USA) for 30 min. Ultimately, the sections were stained again using a Vectastain ABC kit and a 3,3'-diaminobenzidine peroxidase substrate kit (Vector Laboratories, Burlingame, CA, USA). Ovarian tissue microarray analysis and tumor tissue biopsy The tissue microarrays containing paraffin-embedded human ovarian cancer tissue samples were acquired from Fanpu Biotech (Guilin, China). The data on tumor type, staging, and grading are presented in Table 1 . Immunohistochemical analysis was conducted on the ovarian tissue chips to assess PIF1 expression. The protein expression levels were determined by multiplying the proportion of cells that tested positive by the intensity of immunostaining. The allocation scores for percentage were as follows: 0 for non-positive cells, 1 for 1–25%, 2 for 26–50%, 3 for 51–75%, and 4 for 76–100%. Staining intensity was scored as: 0 for negative (-), 1 for weak (+), 2 for moderate (++), and 3 for strong (+++) (Fig. 1 A). The final expression score was categorized as no expression (0), weak expression (1–3), moderate expression (4–6), and high expression (8–12) (Table 1 ). In addition, fresh ovarian tumor tissues (n = 6) and adjacent non-tumor tissues (n = 2) were obtained by biopsy from patients at the First Affiliated Hospital of Jiaxing University (Jiaxing, Zhejiang, China). All participants or their legal guardians provided informed consent, and the study protocol was approved by the institutional review board of the First Hospital of Jiaxing City (LS2020-148). The study adhered to the principles of the Declaration of Helsinki. Table 1 Demographic and clinical characteristics of the patients with ovarian cancer (n = 99). Parameter Mean (standard deviation) (range) Age, years 49.70 (13.00) (18–82) Patients, n (%) Pathological type Normal Benign tumor Serous cystadenocarcinoma Endometrial Mucinous Clear cell 2 (2.0%) 3 (3.0%) 48 (48.5%) 30 (30.3%) 15 (15.2%) 1 (1.0%) Pathological grading Ⅰ Ⅰ-Ⅱ Ⅱ Ⅱ-Ⅲ Ⅲ 19 (20.4%) 9 (9.7%) 19 (20.4%) 7 (7.5%) 39 (41.9%) T stage T1 T2 T3 46 (48.9%) 23 (24.5%) 25 (26.6%) N stage N0 N1 88 (93.6%) 6 (6.4%) M stage M0 M1 72 (76.6%) 22 (23.4%) Ovarian cancer PIF1 IHC score Negative (0) + (1–3) ++ (4–6) +++ (8–12) 1 (1.0%) 15 (16.0%) 44 (46.8%) 34 (36.2%) Quantitative real-time polymerase chain reaction (qRT-PCR) The TRIzol reagent (Invitrogen | Thermo Fisher Scientific) was used to extract total RNA from grown cells. The RNA that was obtained was converted into complementary DNA (cDNA) using the PrimeScript RT Reagent Kit (Takara Bio, Shiga, Japan). The TB Green Master Mix reagent kit (Takara Bio) was used for real-time PCR analysis using the Realplex2 PCR equipment (Eppendorf, Hamburg, Germany). The mRNA levels of each gene were standardized by comparing them to the levels of the housekeeping gene GAPDH. The experiment was conducted three times. The primer sequences can be found in Table S3 . RNA interference GenePharma Co. (Suzhou, China) designed and synthesized siRNA oligonucleotides targeting the RAD51 gene (Table S4 ). A negative control siRNA was also provided by GenePharma Co. Ovarian cancer cells were placed into 6-well plates with a concentration of 5 × 10 5 cells per well. Following the manufacturer's instructions, siRNA sequences were transfected into the cells using Lipofectamine RNAiMAX reagent (Invitrogen). After 48 h of transfection (final siRNA concentration 100 nM), the cells were harvested, and the interference efficiency was analyzed by qRT-PCR or western blot. Mice and xenograft models Female BALB/c nude mice, free from specific pathogens, were acquired from Jiangsu Jicui Yaokang Biotechnology Co. (Nanjing, China). The mice were 6–8-weeks-old and were kept in facilities that met the standards for specific pathogen-free conditions for the whole duration of the study. The animals were cared for and used in accordance with institutional protocols and the National Institutes of Health Guide for the Care and Use of Laboratory Animals (8th edition) [ 29 ]. The study received ethical approval from the Medical College Animal Ethics Committee of Jiaxing University (Registration No. JUMC2020-069). Mice were anesthetized with diethyl ether and wild-type and PIF1-deleted cells (5 × 10 6 cells in phosphate buffered saline (PBS)) were subcutaneously injected into both flanks of the mice, with each group comprising 3–4 mice. Tumor volume was measured every 2 days using calipers, calculated with the formula: volume (mm³) = (width)² × height × 0.523. Mice were terminated by cervical dislocation when the diameter of the tumor exceeded 15 mm, which is the human endpoint. Tumor tissues were subsequently gathered for western blotting and immunohistochemistry investigations. Flow cytometry In order to perform cell cycle analysis, a total of 1 × 10 6 cells were gathered and treated with 70% ethanol for 24 h. Subsequently, the cells were separated by centrifugation and underwent two rounds of washing with PBS. Afterward, the cells were placed in 500 µL of PI/Rnase Staining Buffer (BD Biosciences, Franklin Lakes, NJ, USA) and incubated at 37°C in the absence of light for 30 min. They were then analyzed using flow cytometry (model flow cytometer; BD Biosciences) to quantify the cells in each phase. Data analysis was performed using ModFit software (Verity Software House, Topsham, ME, USA) with each experiment conducted in triplicate. Detection of senescence-associated β-galactosidase activity To analyze cell senescence, a total of 1 × 10 5 control cells and PIF1 partial knockout cells were collected and grown overnight in 12-wells plates. Following the washing of cells with 1 × PBS, they were then treated with 1 × fixation solution at room temperature for 15 min. This was subsequently followed by another round of washing with 1 × PBS. The process of senescence staining was performed using the senescence reagent (β-Galactosidase Staining Kit; Beyotime Biotechnology) in accordance with the instructions provided by the manufacturer. Following the staining process, the cells were left overnight to incubate at a temperature of 37°C. Subsequently, they were rinsed with a solution of 1 × PBS. The images were acquired using an inverted microscope (model CKX53, Olympus), with a minimum of three randomly selected fields. The quantity of senescent cells stained with blue dye in these regions was determined as a proportion of the overall cell count. Immunofluorescence and co-localization For the immunofluorescence analysis, a total of 5 × 10 4 grown cells were placed in 24-well plates. The cells were then rinsed with PBS and subsequently treated with 4% paraformaldehyde for 30 min to ensure fixation. Subsequently, the cells were obstructed with a 5% solution of bovine serum albumin for 1 h. Primary antibodies against p-H2AX, Ki-67, and RAD51 (Table S2 ) were incubated with the cells overnight at 4°C. After washing, the cells were incubated with Alexa488- or Alexa594-conjugated secondary antibodies (Abcam, Cambridge, UK) (Table S2 ) and stained with DAPI (Beijing Solarbio Science & Technology Co., Beijing, China) to visualize the cell nuclei. The laser scanning confocal microscope (model FV3000; Olympus) was used to obtain digital images. A minimum of three images were acquired for each group. For immunofluorescence co-localization analysis, plasmids carrying enhanced green fluorescent protein (EGFP)-tagged PIF1 (Fenghui Biotechnology, Hunan, China) and EGFP empty vector (Fenghui Biotechnology) were separately transfected into cells. Following 36 h of incubation, the cells were fixed and stained with DAPI as described above. Digital images were collected using a laser scanning confocal microscope (model FV3000; Olympus). Plasmids and overexpression of RAD51 in PIF1 partial knockout cells The human PIF1 cDNA expression construct (EGFP-PIF1) was purchased from Fenghui Biotechnology (Hunan, China). The Flag empty vector was provided by Dr. Heng-Yu Fan [ 30 ]. The Flag-PIF1 construct was created by inserting the human PIF1 cDNA (cloned by Fenghui Biotechnology) into the Flag empty vector, with sequencing validation performed by Sangon Biotech (Shanghai, China). The HA empty vector was acquired from Miaoling Biotechnology (Wuhan, China). Human RAD51 cDNA, cloned from the ovarian cancer cell line ES-2 using specific primers (Table S5), was then inserted into the HA empty vector. This construct was also validated by sequencing at Sangon Biotech (Shanghai, China). To construct the RAD51 overexpression vector, the pQCXIH retroviral vector containing the RAD51 cDNA sequence was utilized. pQCXIH plasmid was kindly provided by Kun-Liang Guan, West Lake University [ 31 ]. 293T cells were transfected with either the pQCXIH empty vector or pQCXIH-RAD51, together with Retro VSVG and Retro GPE constructs, using the PolyJet™ DNA In Vitro Transfection Reagent (Signagen Laboratories, Frederick, MD, USA), following the manufacturer's instructions. The transfection was carried out in a medium devoid of serum. After 48 h, the retroviral supernatant was collected, mixed with 5 µg/mL Polybrene (GeneChem Co., Shanghai, China), passed through a sterile 0.45-µm filter (Merck | Millipore), and employed to infect PIF1 partially deficient ES-2 cells. Following 48 h of infection, the specific cells were chosen using a concentration of 200 µg/mL puromycin in a completely supplied medium for 3 days. Stable RAD51 expression in the cells was confirmed via western blot analysis. Co-immunoprecipitation (Co-IP) After transfecting the plasmids into 293T cells for 36 h, the cells were lysed and centrifuged using a western blot and IP lysis buffer (Beyotime Biotechnology). The respective antibodies and protein A/G magnetic beads (MCE Magnetic, Mianyang, China) were incubated together at 4°C for 4 h, followed by washing four times with 400 µL of binding/washing buffer (1× PBS + 0.5% Tween-20 + 150 mM NaCl). Subsequently, the antibody-bead complexes and protein supernatants were incubated together overnight at 4°C. The immune complexes were washed six times with PBST buffer (1× PBS + 0.5% Tween-20 + 150 mM NaCl), resuspended in 1× loading buffer, and heated at 95°C for 5 min. Finally, the samples were analyzed by western blot. Cell counting kit-8 (CCK8) assay Three thousand cells were resuspended in 200 µL of medium and seeded into a 96-well plate. After cell adhesion, they were treated with increasing concentrations of cisplatin for 24 h. After the treatment period, cells were incubated with 10 µL of CCK-8 reagent (MCE Magnetic, Mianyang, China) in 100 µL of medium for 1–4 h. The Spark multimode microplate reader (Tecan, Männedorf, Switzerland) was used to measure absorbance at 450 nm, with data collected using TECAN software. Each condition was replicated four times. Kaplan-Meier plotter database An online database called Kaplan Meier plotter ( http://kmplot.com/analysis ) can be used to assess the relationship between gene mRNA expression and survival in a variety of cancer cohorts, such as patients with acute myeloid leukemia, multiple myeloma, lung, gastric, pancreatic, and breast cancers [ 32 ]. Histology, stage, grade and the use of chemotherapy were among the clinical data available for ovarian cancer patients (Table 2 and Table 3 ). An online analysis was conducted to examine the correlation between PIF1 mRNA expression and survival in ovarian cancer patients. The results were expressed as the hazard ratio and logarithmic rank P-value. Patients with PIF1 gene expression were grouped using the best available cut-off value [ 33 ]. Table 2 Demographic and clinical characteristics of patients with ovarian cancer (n = 655). Parameter Patients, n (%) Pathological type Serous cystadenocarcinoma 523 (79.8%) Endometrial 30 (4.6%) Other 102 (15.6%) Stage 1 51 (8.9%) 2 32 (5.6%) 3 426 (74.7%) 4 61 (10.7%) Grade 1 41 (6.7%) 2 162 (26.4%) 3 392 (63.9%) 4 18 (2.9%) Treatment Platin 478 (73.0%) Taxol 357 (54.5%) Platin + Taxol 356 (54.4%) Other 176 (26.9%) Table 3 Demographic and clinical characteristics of patients with ovarian cancer (n = 382). Parameter Patients, n (%) Pathological type Serous cystadenocarcinoma 346 (90.6%) Endometrial 10 (2.6%) Other 26 (6.8%) Stage 1 7 (1.8%) 2 13 (3.4%) 3 312 (81.9%) 4 49 (12.9%) Grade 1 9 (2.4%) 2 109 (29.0%) 3 240 (63.8%) 4 18 (4.8%) Treatment Platin 373 (97.6%) Taxol 274 (71.7%) Platin + Taxol 273 (71.4%) Other 8 (2.1%) GEPIA database The GEPIA database is an online database developed by Zhang's Lab at Peking University in Beijing, China [ 34 ]. It may be accessed at http://gepia.cancer-pku.cn/ . The association between PIF1 and ovarian cancer was analyzed with the “Boxplots” module of GEPIA. GEPIA employs the log2 (TPM + 1) method to represent data on a logarithmic scale when comparing TCGA normal and GTEx data. UALCAN database The UALCAN database provides a thorough and interactive analysis of bioinformatics utilizing RNA-seq and clinical data from 31 tumors in the TCGA dataset ( http://ualcan.path.uab.edu/ ) [ 35 ]. The association between PIF1 and ovarian cancer grades was analyzed with the “tumor grade” module of UALCAN. Statistical analysis Data are presented as mean ± standard deviation. Non-normally distributed variables were analyzed using the Mann-Whitney U test. Unpaired parametric tests were employed for normally distributed variables. Three or more groups were compared using one-way ANOVA. Statistical analyses were conducted using GraphPad Prism software (GraphPad Software, San Diego, CA, USA). Statistical significance was set at P < 0.05. Data obtained from mice that died were excluded from the analysis. Results PIF1 overexpression positively correlates with cancer grade and negatively correlates with the overall survival rate in ovarian cancer To determine the function of PIF1 in ovarian cancer, immunohistochemical techniques were employed to identify its expression in normal ovarian tissues (n = 2), benign tumor tissues (n = 3), and ovarian cancer tissues (n = 94) (Table 1 ). Based on the PIF1 protein expression scoring, the immunohistochemical results were categorized into four groups, ranging from the least powerful (−) to the most powerful (+++) in increasing order (Fig. 1 A). As shown in Table 1 , the distribution of PIF1 signal strength among the 94 ovarian cancer cases was as follows: (−) 1 case (1.0%), (+) 15 cases (16.0%), (++) 44 cases (46.8%), and (+++) 34 cases (36.2%). Owing to significant tissue section loss, three specimens were excluded. Figure 1 B demonstrates a notable disparity in PIF1 expression between normal ovaries and both serous cystadenomas and endometrioid carcinomas ( P < 0.05). Western blot analysis was conducted on six fresh ovarian cancer tissue samples and two adjacent non-tumor tissue samples derived from patients. Compared to non-malignant tissues, PIF1 was overexpressed in four of six ovarian cancer tissue samples (Fig. 1 G), and densitometric analysis of non-malignant and malignant tissues revealed statistically significant differences ( P < 0.05). These results validate the high expression of PIF1 in ovarian cancer tissues. Using the GEPIA database, we further investigated the expression of PIF1 in ovarian cancer to evaluate its correlation with disease progression. In ovarian cancer tissues, we observed a significant upregulation of PIF1 expression when compared to normal tissues (Fig. 1 E). The Kaplan-Meier curve analysis revealed a relationship between the PIF1 expression level and survival rate of patients with ovarian cancer (Table 2 and Table 3 ). The group with high PIF1 expression exhibited significantly lower overall survival and prognostic survival curves compared to the group with low PIF1 expression (Fig. 1 C-D). Additionally, using the UALCAN database, we found differences in PIF1 expression during the clinical grading of ovarian cancer. The expression of PIF1 in grade 3 ovarian cancer was notably elevated compared to grade 2 ovarian cancer (Fig. 1 F). These results further confirmed PIF1 upregulation in patients with ovarian cancer and suggested a positive correlation between PIF1 expression and ovarian cancer grade. Western blot analysis showed that, compared to benign human ovarian epithelial cell line (IOSE), PIF1 was highly expressed in most ovarian cancer cell lines (SKOV3, A2780, OVCAR-3, and ES-2) (Fig. 1 H). Furthermore, immunofluorescence analysis showed that EGFP-PIF1 was localized in the nucleus of cultured ovarian cancer cells (Fig. 1 I). These results collectively indicate that PIF1 is highly expressed in ovarian cancer tissues and cells and that its expression level is closely linked to ovarian cancer grading and patient survival rates. PIF1 partial knockdown inhibits the proliferation and colony formation of ovarian cancer cells To investigate whether PIF1 affects ovarian cancer cell proliferation, we used CRISPR/Cas9 to knock out PIF1 in ovarian cancer cell lines (ES-2 and OVCAR-3). Owing to the challenge of obtaining complete PIF1 gene knockout clones, we were only able to obtain two PIF1 partial knockdown clones that exhibited significantly lower levels of PIF1 protein expression (Fig. 2 A). This study utilized two distinct clones that were created using two separate CRISPR guide sequences. PIF1 partial knockdown decelerated ovarian cancer cell proliferation in both clones (Fig. 2 B) and markedly inhibited (OVCAR-3) or delayed (ES-2) colony formation (Fig. 2 C). Correspondingly, expression of the cell proliferation marker PCNA was lower in PIF1 partially deficient cells (Fig. 2 D), and cells exhibited decreased Ki-67 expression (Fig. 2 E). In summary, these findings indicate that PIF1 plays an important role in ovarian cancer cell proliferation. PIF1 partial knockdown inhibits cell cycle progression and promotes cell senescence The unrestricted proliferation of cancer cells depends on the disruption of normal regulatory cell cycle mechanisms [ 36 ]. To further elucidate the mechanism in which PIF1 loss inhibits cell proliferation, we conducted a flow cytometry analysis of the cell cycle in ES-2 and OVCAR-3 cells. In comparison to wild-type ovarian cancer cells, there was a notable increase in the percentage of PIF1 partially deficient cells in the G2 phase, while the percentage of cells in the G1 and S phases showed a significant decrease (Fig. 3 A). In PIF1 partially deficient cells, p21 and p27 expression was significantly higher (Fig. 3 B), indicating that PIF1 regulates the cell cycle via p21 and p27 upregulation. qRT-PCR analysis revealed upregulation of P53 transcription and downregulation of MDM2 transcription in PIF1 partially deficient ovarian cancer cells (Fig. 3 C). These findings imply that PIF1 partial deficiency blocks the cell cycle in human ovarian cancer cells. A stable cell cycle arrest characterizes cellular senescence, which limits cell proliferation [ 37 ]. We found that, compared with wild-type ovarian cancer cells, PIF1 partially deficient cells exhibit elevated SA-β-galactosidase staining intensity (Fig. 3 D). Plasminogen activator inhibitor-1 (PAI-1) is a marker for aging as its expression level is positively correlated with human age [ 38 , 39 ]. Lamin B1 is indispensable for maintaining the integrity of nuclear structure; however, aging cells tend to lose this structural integrity [ 40 , 41 ]. We observed an increase in PAI-1 and a decrease in lamin B1 protein expression in PIF1 partially deficient ovarian cancer cells (Fig. 3 E), confirming that PIF1 partial deficiency promotes senescence in ovarian cancer cells. These results suggest that PIF1 partial deficiency increases G2 phase cells and promotes cell senescence in ovarian cancer cells. PIF1 partial knockdown promotes DNA damage in ovarian cancer cells PIF1 has significant functions in DNA replication and repair. To elucidate the effects of the PIF1 protein on DNA damage in ovarian cancer cells, we conducted immunoblotting analysis and discovered that, compared to wild-type ovarian cancer cells, the expression of p-H2AX, p-CHK1, and p-CHK2 was significantly higher in PIF1 partially deficient ovarian cancer cells, while the total levels of H2AX, CHK1, and CHK2 remained relatively consistent (Fig. 4 A). Ataxia telangiectasia mutated (ATM) is a serine/threonine protein kinase that is activated during DNA DSBs and enhances the homologous recombination repair pathway [ 42 ]. The expression levels of phosphorylated ATM were significantly lower in ovarian cancer cells partially deficient in PIF1 (Fig. 4 A). A downstream target of ATM, the nonreceptor tyrosine kinase encoded by the c-Abl proto-oncogene, engages in interaction with ATM after DNA damage [ 43 ]. qRT-PCR revealed a decrease in c-Abl expression in PIF1 partially deficient ovarian cancer cells (Fig. S1 B). Through the CCK8 assay, it was observed that increasing concentrations of cisplatin effectively suppressed the proliferation of ovarian cancer cells. At a cisplatin concentration of 0.125 µg/mL (or 0.25 µg/mL), there was no significant difference between wild-type ovarian cancer cells before and after treatment, whereas the growth of PIF1 partial knockdown ovarian cancer cells was significantly different before and after treatment, indicating that PIF1 partial depletion may enhance cancer cell sensitivity to cisplatin (Fig. 4 B). Furthermore, the fluorescence intensity of p-H2AX in PIF1 partially deficient ovarian cancer cells was significantly higher than that in wild-type cells, and upon treatment with the same concentration of cisplatin, the fluorescence intensity of p-H2AX in PIF1 partially deficient ovarian cancer cells increased further (Fig. 4 C). Similar results were obtained when UV treatment was applied to wild-type ES-2 cells and ES-2 cells lacking PIF1 (Fig. S1 A). In summary, PIF1 is involved in DNA damage repair and its partial deficiency promotes DNA damage in ovarian cancer cells, thereby increasing their sensitivity to cisplatin. PIF1 partial deficiency suppresses tumor growth in vivo To further validate the impact of PIF1 partial knockout on ovarian cancer cell proliferation in vivo , we implanted wild-type/PIF1 partial knockdown ovarian cancer (ES-2 and OVCAR-3) cells subcutaneously into both flanks of BALB/c mice. Compared to wild-type mice, animals transplanted with PIF1 partial knockdown cells exhibited smaller tumor volumes and weights at animal sacrifice (Fig. 5 A-B). Growth curves provided compelling evidence that tumor cell growth was attenuated in the PIF1 partial knockdown group (Fig. 5 A-B). These findings demonstrate the importance of PIF1 for the survival of cancer cells in vivo . In subsequent experiments, immunoblotting revealed significantly elevated levels of the DNA damage-related protein p-H2AX, apoptosis-related protein PARP, and cell cycle kinase inhibitor p21 in tumor tissues lacking PIF1, while those of the proliferative protein PCNA and cell cycle protein cyclin B1 were significantly reduced (Fig. 5 C). Furthermore, immunohistochemical results confirmed decreased expression of the proliferative protein BrdU and increased expression of p-H2AX in tumor tissues lacking PIF1 (Fig. 5 D). These findings suggest that PIF1 partial knockdown suppresses tumor cell proliferation in vivo . PIF1 indirectly interacts with RAD51 protein to regulate ovarian cancer cell proliferation and DNA damage We noted a considerable decline in the expression of RAD51 protein in PIF1 partially deficient ovarian cancer cells (Fig. 6 A and Fig. 5 C). Previous studies have indicated that c-Abl interacts with RAD51 and phosphorylates it to regulate recombination repair of DNA DSBs [ 44 ]. qRT-PCR analysis indicated that the mRNA levels of c-Abl were lower in PIF1 partial knockdown ovarian cancer cells (Fig. S1 B), further confirming that PIF1 partial deficiency inhibits RAD51 expression in ovarian cancer cells. Therefore, we speculated that PIF1 and RAD51 co-regulate DNA damage in ovarian cancer. To gain deeper insights into the function of PIF1 in DNA damage in ovarian cancer cells, we silenced the expression of RAD51 in wild-type ovarian cancer cells. As a result, we observed an increase in the expression of the DNA damage marker protein p-CHK1 and a decrease in the expression of PIF1 (Fig. 6 B-C). The human breast cancer suppressor protein BRCA2 interacts directly with RAD51 to regulate homologous recombination [ 45 ]. After silencing RAD51 in ovarian cancer cells, a considerable decrease in the expression of the RAD51 protein complex BRCA2 was observed (Fig. S1 E). In addition, the growth of wild-type ovarian cancer cells was inhibited (Fig. 6 D and Fig. S1 C-D). Ovarian cancer cells with RAD51 knocked down exhibited phenotypes similar to those of PIF1 partially deficient ovarian cancer cells, and downregulation of RAD51 resulted in decreased PIF1 expression. In order to conduct a more in-depth examination of the functions of PIF1 and RAD51 in relation to the growth of ovarian cancer cells and the occurrence of DNA damage, we overexpressed RAD51 in PIF1 partially deficient ovarian cancer cells. Immunoblotting analysis revealed that overexpression of the RAD51 protein caused an increase in the expression of PIF1 protein, while the expression of the DNA damage marker proteins p-H2AX and p-CHK2 decreased (Fig. 6 E). Furthermore, immunofluorescence analysis confirmed that overexpression of RAD51 in PIF1 partially deficient ovarian cancer cells rescued the DNA damage caused by PIF1 partial deficiency (Fig. 6 F). Proliferation levels were assessed by cell counting for 3 days, revealing that RAD51 overexpression rescued the proliferation of PIF1 partially deficient ovarian cancer cells (Fig. 6 G). Following RAD51 overexpression, both the protein and mRNA levels of BRCA2 increased significantly (Fig. 6 H and Fig. S1 F). Immunofluorescence colocalization analysis revealed the colocalization of the RAD51 protein with the EGFP-PIF1 protein in ovarian cancer cells (Fig. 6 I). However, immunoprecipitation experiments showed that RAD51 and PIF1 did not physically interact with each other (Fig. 6 J). In summary, we speculate that PIF1 and RAD51 cooperate to regulate ovarian cancer cell proliferation and DNA damage. Functionally, PIF1 interacts with RAD51, but physically RAD51 acts independently of PIF1. This suggests that other proteins act as bridges between PIF1 and RAD51, or that PIF1 and RAD51 may be co-regulated through more complex protein networks. Discussion In this study, we found that ovarian cancer patients who had low levels of PIF1 expression had a superior overall survival rate and prognosis, according to the clinical data. This finding was further corroborated by the reduction in cell viability observed upon the partial knockdown of PIF1 in ovarian cancer cells. Additionally, PIF1 partial knockdown increased basal levels of DNA damage and DNA damage response signaling, which was further exacerbated by cisplatin treatment, supporting the hypothesis that PIF1 partial deficiency sensitizes ovarian cancer cells to cisplatin treatment. These findings strongly indicate that PIF1 could serve as a crucial target for pharmacological intervention and as a prognostic biomarker for ovarian cancer. The PIF1 helicase is essential for preserving the integrity of the genome and repairing DNA damage. Gagou et al. detected a slight increase in p-H2AX level but no significant activation of pSer1981 ATM or pSer345 CHK1 in PIF1-knocked down HCT116 cells [ 26 ]. Our results suggest that PIF1 partial knockdown resulted in p-H2AX, pSer317 CHK1, and pT68 CHK2 expression upregulation, and a decrease in pSer1981 ATM expression. CHK1 is a key component of the ATR cascade, which is rapidly activated by disrupting single-stranded DNA formed during DNA replication to suppress inappropriate initiation, promote replication restart, and prevent cell apoptosis [ 46 ]. Phosphorylation of CHK1 at different sites by ATM/ATR results in CHK1 exerting distinct functions [ 47 , 48 ]. Phosphorylation of CHK1 at the Ser317 site allows cells to re-enter the cell cycle after DNA replication stalling [ 49 ]. PIF1 helicases promote the progression of replication forks and resolve various obstacles in the replication fork structures. Therefore, we speculate that the activation of CHK1 at the Ser317 phosphorylation site, following PIF1 partial knockdown, may result from DNA replication stalling caused by PIF1 partial depletion rather than the inactivated Ser345 phosphorylation of CHK1 observed in previous reports. DNA DSBs activate ATM, which assists in DNA repair [ 50 ]. However, in our study, we found that ATM phosphorylation at Ser1981 was inhibited after PIF1 partial knockout, suggesting that PIF1 partial depletion may suppress ATM-related DNA damage repair pathways. In the autofeedback loop formed by P53 and MDM2 , a decrease in MDM2 and an increase in P53 occur simultaneously, activation of P53 initiates cell cycle arrest and apoptosis [ 51 ]. We observed similar results in PIF1 partially deficient ovarian cancer cells. It has been reported that PIF1 downregulation can enhance pancreatic cancer cells' sensitivity to gemcitabine [ 22 ] as well as sensitize other tumor cells to chemotherapy drugs such as hydroxyurea and aphidicolin [ 25 , 26 ]. We discovered in this study that reducing the expression of PIF1 increased the susceptibility of ovarian cancer cells to cisplatin. When exposed to small amounts of cisplatin, the survival rate of PIF1 partial knockdown ovarian cancer cells reduced considerably, but the survival rate of wild-type ovarian cancer cells remained unaltered. Immunofluorescence analysis revealed that DNA damage in PIF1 partial knockout ovarian cancer cells increased prominently following treatment with the same cisplatin concentration. In conjunction with earlier studies, this evidence suggests that PIF1 knockdown can increase the sensitivity of tumor cells to chemotherapeutic drugs. The standard chemotherapy for ovarian cancer involves the administration of platinum-based medications in conjunction with paclitaxel. The primary mechanism of cytotoxicity induced by paclitaxel is attributed to the inhibition of microtubule dynamics and compromised centrosome function, leading to mitotic arrest [ 52 ]. Our work revealed that the partial knockdown of PIF1 leads to the arrest of ovarian cancer cells at the G2 phase. This suggests a potential synergistic interaction between PIF1 depletion and paclitaxel in ovarian cancer cells, potentially amplifying the pathways leading to cell death. Homologous recombination is a mechanism for repairing DSBs in DNA and fork replication [ 53 , 54 ]. RAD51 serves as a central scaffold protein for homologous recombination repair [ 53 ] and is crucial for timely and accurate DNA repair [ 55 ]. RAD51 is a hallmark protein of homologous recombination [ 56 , 57 ]. BIR is a form of homologous recombination that involves the repair of single-ended DNA DSBs on folded replication forks [ 9 ]. PIF1 readily localizes to replication-associated fragile sites, inducing BIR [ 25 ]. A specific sequence mutation in Saccharomyces cerevisiae PIF1 (ScPIF1) leads to BIR defects [ 9 ]. Moreover, the typical BIR pathway relies on RAD51 in eukaryotes [ 58 ]. We observed significant downregulation of RAD51 protein expression upon PIF1 partial knockdown in ovarian cancer cells. Thus, we infer that PIF1 partial knockdown may interfere with the homologous recombination repair pathway. Subsequently, when we silenced RAD51 in ovarian cancer cells, we found that the expression of the PIF1 protein also decreased, leading to DNA damage and slower proliferation. Additionally, RAD51 overexpression in ovarian cancer cells partially rescued the DNA damage and proliferation defects caused by PIF1 partial knockout. Immunoprecipitation assays revealed no interactions between PIF1 and RAD51. ChIP assays in budding yeast revealed no notable variations in the abundance of RAD51 protein bound near DSBs in cells with mutated PIF1 [ 10 ]. This evidence suggests that PIF1 and RAD51 do not interact directly via binding. However, in immunofluorescence co-localization studies, we found that endogenous RAD51 protein in ovarian cancer cells co-localized with exogenous EGFP-PIF1 protein in the cell nucleus (Fig. 6 I). These results indicate that the PIF1 and RAD51 proteins are spatially close, suggesting functional interactions despite the lack of direct physical binding. Therefore, we speculated that the functional interaction between PIF1 and RAD51 in ovarian cancer may depend on the biological pathway of homologous recombination, particularly BIR. We intend to conduct further investigations into this potential in future studies. Conclusions In summary, our findings demonstrate that PIF1 is highly expressed in ovarian cancer compared to normal tissues and that overexpression of PIF1 is negatively associated with survival in ovarian cancer patients. PIF1 partial knockout may reduce the proliferation of ovarian cancer cells through multiple mechanisms, including senescence, cell cycle arrest, and DNA damage. This can have an inhibitory influence on the malignant ability of ovarian cancer cells. Additionally, we found that PIF1 indirectly collaborates with RAD51 to regulate the growth and DNA damage of ovarian cancer cells. These findings offer novel insights into the molecular mechanisms behind ovarian cancer and provide a theoretical foundation for the development of pharmacological therapy options. Simultaneously, the importance of PIF1 as a prognostic biomarker for ovarian cancer is underscored. Abbreviations Break-induced replication BIR DNA double-strand breaks DSBs RAD51 recombinase RAD51 Complementary DNA cDNA Enhanced green fluorescent protein EGFP Co-immunoprecipitation Co-IP Cell counting kit-8 CCK8 Ataxia telangiectasia mutated ATM Declarations Ethics approval and consent to participate All participants or their legal guardians provided informed consent, with the study protocol approved by the institutional review board of the First Hospital of Jiaxing City (LS2020-148). Animal experimental protocols in this manuscript received ethical approval from the Medical College Animal Ethics Committee of Jiaxing University (Registration No. JUMC2020-069). Consent for publication Not applicable. Competing interests The authors declare no competing interests. Availability of data and materials All data are contained in the figures, figure legends, or additional files, further inquiries can be directed to the corresponding authors. Acknowledgements We extend our gratitude to Jing-Ya Zhong, Jing-Jian Dong, and Li-Li Shi for their invaluable technical support. We also acknowledge Dr. Kun-Liang Guan for providing the CRISPR/Cas9 and pQCXIH plasmids, Dr. Heng-Yu Fan for the IOSE cells and FLAG empty vector plasmid and Dr. Yi-Ting Zhou for discussion. Author contributions W-WP and S-QC were responsible for the overall conception and design of this experiment. W-WP, X-MW, and Q-YZ collated and summarized the experimental results and wrote the manuscript. Q-YZ and H-YH participated in most of the experimental procedures in this study, and Q-QS participated in Co-IP experiments and some immunohistochemistry experiments. M-ZN and SZ were involved in the management and sampling of experimental animals. S-BL were involved in the immunohistochemical experiments. S-QC, XC, Z-JW and XZ participated in the collection of clinicopathological specimens. X-CZ, X-MW, LA, Y-JG, and MH revised the final manuscript. All authors read and approved the final manuscript. Funding and additional information This work was supported by grants from National Natural Science Foundation of China (31871402) and The Natural Science Foundation of Zhejiang Province (LY21H160047, LGD21H160003, LQ23C070001, Z20H160031, LGF20H160031, LGD22H030004). This work was supported by grants from National College Student Innovation and Entrepreneurship Training Program (222024R7034, 2024R417010) and Zhejiang Provincial Foreign Expert Grant (12.2018). This work was supported by Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics (12.2019). This work was supported by the Dutch Cancer Foundation (KWF, project 10666) and The Top-level Talent Project of Zhejiang Province. This work was supported by the Jiaxing talent pioneer innovation team (6.2021) and the Natural Science Foundation of Jiaxing(2020AD30073). This work was supported by Jiaxing Science Foundation for Young Talents (2023AY40005). 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xuan","middleName":"","lastName":"Che","suffix":""},{"id":312000499,"identity":"460da745-7a50-4d69-906a-9831bf73b193","order_by":11,"name":"Xian-Chao Zhang","email":"","orcid":"","institution":"Institute of Information Network and Artificial Intelligence, Jiaxing University","correspondingAuthor":false,"prefix":"","firstName":"Xian-Chao","middleName":"","lastName":"Zhang","suffix":""},{"id":312000500,"identity":"b7a404e5-2640-4899-996f-76c6327f4915","order_by":12,"name":"Michal Heger","email":"","orcid":"","institution":"Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics","correspondingAuthor":false,"prefix":"","firstName":"Michal","middleName":"","lastName":"Heger","suffix":""},{"id":312000501,"identity":"2efdf012-5aa8-4e54-844d-45bb7b01b264","order_by":13,"name":"Xin Zheng","email":"","orcid":"","institution":"Department of Gynecology and Obstetrics, Affiliated Hospital of Jiaxing University","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Zheng","suffix":""},{"id":312000502,"identity":"f1a01601-eb88-4fbc-b7d0-c6e398798467","order_by":14,"name":"Zhong-Jie Wu","email":"","orcid":"","institution":"First Hospital of Jiaxing","correspondingAuthor":false,"prefix":"","firstName":"Zhong-Jie","middleName":"","lastName":"Wu","suffix":""},{"id":312000503,"identity":"76cd43eb-94a6-4f5e-87da-57979896e854","order_by":15,"name":"Xiao-Min Wang","email":"","orcid":"","institution":"Jiaxing University","correspondingAuthor":false,"prefix":"","firstName":"Xiao-Min","middleName":"","lastName":"Wang","suffix":""},{"id":312000504,"identity":"5fa10b15-0830-4513-971f-3765e7b7a4b5","order_by":16,"name":"Shu-Qun Cheng","email":"","orcid":"","institution":"Jiaxing University","correspondingAuthor":false,"prefix":"","firstName":"Shu-Qun","middleName":"","lastName":"Cheng","suffix":""},{"id":312000505,"identity":"d30b2b92-7a62-414a-ad1e-58196a036e0a","order_by":17,"name":"Wei-Wei Pan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYNCCCgZmMM1DvJYzJGthbIMyiNJicCP34OfCeXXsBjcSGB+8bWOQNyesJS9ZeuY2NmbJGQnMhnPbGAx3NhDQYnY7x0CadxsPM79EAps0bxtDgsEBwlqMf/POkWBmk0hg/02sFjNp3gYDsC3MRGmxv/8uzZrnWAKzZM/DZsk55yQMNxDSItlz9vBtnpq6ZIPjyQc/vCmzkSdoCywukoGx0wCkJQiqh2uxI0bpKBgFo2AUjFAAAMzMN4URksFOAAAAAElFTkSuQmCC","orcid":"","institution":"Jiaxing University","correspondingAuthor":true,"prefix":"","firstName":"Wei-Wei","middleName":"","lastName":"Pan","suffix":""}],"badges":[],"createdAt":"2024-05-29 09:22:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4495865/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4495865/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58309795,"identity":"0959c2d2-99c7-4043-925b-67e3d56625a3","added_by":"auto","created_at":"2024-06-13 18:58:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":5672035,"visible":true,"origin":"","legend":"\u003cp\u003ePIF1 overexpression positively correlates with cancer grade and negatively correlates with the overall survival rate in ovarian cancer patients. (A) Detection of PIF1 expression in ovarian cancer tissue microarrays using immunohistochemistry. Representative images show varied PIF1 expression intensity (−, +, ++, +++). Scale bar, 80 μm (4×), 20 μm (40×). (B) Statistical analysis of\u003cem\u003e \u003c/em\u003e(A), * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05. Data are presented as mean ± SD. One-way ANOVA test. (C) Kaplan-Meier analysis reveals poorer overall survival in high \u003cem\u003ePIF1\u003c/em\u003e (n=267) versus low \u003cem\u003ePIF1\u003c/em\u003e (n=388) gene expression group in ovarian cancer patients (logrank test; \u003cem\u003eP\u003c/em\u003e= 0.00019). (D) Similar results were found for prognosis survival rate (logrank test; \u003cem\u003eP\u003c/em\u003e = 0.02) in the high (n=113) and low (n=269) \u003cem\u003ePIF1\u003c/em\u003e gene expression groups. (E) GEPIA database analysis shows higher expression of \u003cem\u003ePIF1\u003c/em\u003e gene in ovarian tumor tissues (T) (n=426) compared to normal tissues (N) (n=88), * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05. (F) UALCAN database analysis shows that \u003cem\u003ePIF1\u003c/em\u003e gene expression is higher in grade 3 ovarian cancer tissues (n=262) compared to grade 2 (n=32), **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001. (G) Immunoblotting and quantification of PIF1 protein expression in ovarian cancer tissues (CT) (n=6) compared to adjacent non-tumor tissues (NT) (n=2), * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, with GAPDH serving as the loading control. Data are presented as mean ± SD. Mann-Whitney U test. (H) Western blot and quantification show PIF1 expression levels in ovarian cancer cells and benign human ovarian epithelial cell line, ns \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05, ** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001, with β-actin as the loading control. Data are presented as mean ± SD. One-way ANOVA test. (I) Subcellular localization of EGFP-PIF1 (green) in various wild-type ovarian cancer cell lines, counterstained for cell nuclei with DAPI (blue). Scale bar, 20 μm (60×).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/1d78507c5e9a445ea31bd8d3.png"},{"id":58309803,"identity":"b77850fe-b23e-4f61-95dd-463d0f618f90","added_by":"auto","created_at":"2024-06-13 18:58:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1761692,"visible":true,"origin":"","legend":"\u003cp\u003ePIF1 partial knockdown inhibits the proliferation and colony formation of ovarian cancer cells. (A) Immunoblotting confirms the efficiency of PIF1 partial knockout in ovarian cancer cell lines, with β-actin serving as the loading control. Two independent clones (95# and 108# in OVCAR-3; 1# and 2# in ES-2) are shown. (B) A technique utilizing cell counting was employed to quantify the growth of ovarian cells with normal PIF1 expression and cells lacking PIF1. Each sample having 3 technical replicates, ** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, *** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001. Data are presented as mean ± SD. One-way ANOVA test. (C) Soft agar colony formation experiment was used to assess the proliferation capacity of wild type ovarian cancer cells in comparison to PIF1 partial knockdown cells, with n=6 per group, **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001. Data are presented as mean ± SD. One-way ANOVA test. (D) Immunoblotting revealed significantly reduced PCNA protein expression in PIF1 partial knockout cells compared to WT ovarian cancer cells, using β-actin as the loading control. (E) Immunofluorescence analysis shows decreased levels of Ki-67 (green) in PIF1 partial knockout ovarian cancer cells, with nuclei counterstained with DAPI (blue). Scale bar, 20 μm, ** \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01. Data are presented as mean ± SD. Unpaired parametric test.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/4fd7cc353abb40c4b92013c2.png"},{"id":58309797,"identity":"db021d30-3b58-4d9e-8d6a-1dc4cbaea90b","added_by":"auto","created_at":"2024-06-13 18:58:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":4144265,"visible":true,"origin":"","legend":"\u003cp\u003ePIF1 partial knockdown inhibits cell cycle progression and promotes cell senescence of ovarian cancer cells. (A) Flow cytometry detected changes in the cell cycle of PIF1 partial knockout ovarian cancer cells, with n=3 per group, ns \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05, * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003e P\u003c/em\u003e \u0026lt; 0.01, *** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, ****\u003cem\u003e P\u003c/em\u003e \u0026lt; 0.0001. Data are presented as mean ± SD. Unpaired parametric test. (B) Immunoblotting analysis of the expression changes of p21 and p27 proteins in PIF1 partial knockout ovarian cancer cells, using β-actin as the loading control. (C) qRT-PCR analysis of the expression changes of \u003cem\u003eP53\u003c/em\u003e and \u003cem\u003eMDM2\u003c/em\u003e genes in PIF1 partial knockout ovarian cancer cells, with \u003cem\u003eGAPDH\u003c/em\u003e gene serving as the normalization control, * \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003e P\u003c/em\u003e \u0026lt; 0.01, **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001. Data are presented as mean ± SD. Unpaired parametric test. (D) Senescence analysis using β-galactosidase staining was conducted for PIF1 partial knockout ovarian cancer cells, presented both qualitatively (top) and quantitatively (bottom), with senescent cells stained blue. Scale bar, 50 μm (10×, 20×, 40×), **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001. Data are presented as mean ± SD. Unpaired parametric test. (E) Immunoblotting analysis detected changes in the expression of lamin B1 and PAI-1 proteins in PIF1 partial knockout ovarian cancer cells, with β-actin as the loading control.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/7971f2e6c97609d1554c6742.png"},{"id":58310004,"identity":"9a140f93-d9ab-43a7-b496-1382ebf88403","added_by":"auto","created_at":"2024-06-13 19:06:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2170140,"visible":true,"origin":"","legend":"\u003cp\u003ePIF1 partial knockdown promotes DNA damage in ovarian cancer cells. (A) Immunoblotting analysis of the expression changes of pSer317 CHK1, pT68 CHK2, p-H2AX, and pSer1981 ATM proteins in PIF1 partial knockout ovarian cancer cells, with GAPDH/β-actin used as the loading control. (B) CCK8 analysis of cell viability changes after cisplatin treatment in wild-type ovarian cancer cells and PIF1 partial knockout ovarian cancer cells, ns \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05, * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, *** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. Data are presented as mean ± SD. One-way ANOVA test. (C) Immunofluorescence analysis demonstrated stronger immunofluorescence intensity of p-H2AX (red) in PIF1 partial knockout ovarian cancer cells compared to wild-type ovarian cancer cells, with a more significant increase in p-H2AX (red) immunofluorescence intensity after cisplatin (2 μg/mL) treatment in PIF1 partial knockout ovarian cancer cells. Cell nuclei were counterstained with DAPI (blue). ns \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05, *** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001. Scale bar, 20 μm (60×). Data are presented as mean ± SD. Two-way ANOVA test.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/369b81608c627747a00554ce.png"},{"id":58309801,"identity":"692d3c64-ea88-41d7-98b1-0ec274e4a737","added_by":"auto","created_at":"2024-06-13 18:58:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":14597237,"visible":true,"origin":"","legend":"\u003cp\u003ePIF1 partial deficiency suppresses tumor growth \u003cem\u003ein vivo\u003c/em\u003e. (A) Wild-type and PIF1 partial knockout ES-2 cells were injected subcutaneously into nude mice (5 × 10\u003csup\u003e6\u003c/sup\u003e cells per mouse/side, n=4 per group). Mice were euthanized when tumor volume exceeded 15 mm. Representative images of excised tumors are shown on the top. Tumor weights were measured at the end of the experiment (middle). The tumor weight of PIF1 partial knockout ovarian cancer cells was significantly lower than that of wild-type ovarian cancer cells in nude mice, * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05. Tumor growth curve of nude mice (bottom), ** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01. Tumor volumes were measured every 2 days per group. Data are presented as mean ± SD. Unpaired parametric test. (B) Wild-type and PIF1 partial knockout OVCAR-3 cells were injected subcutaneously into nude mice (5 × 10\u003csup\u003e6\u003c/sup\u003e cells per mouse/side, n=3 per group). Representative images of excised tumors are shown on the top. Tumor weights were measured at the end of the experiment (middle). The tumor weight of PIF1 partial knockout ovarian cancer cells was lower than that of wild-type ovarian cancer cells in nude mice, ** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01. Tumor growth curve of nude mice (bottom), * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05. Data are presented as mean ± SD. Unpaired parametric test. (C) Immunoblotting analysis in tumors from nude mice identified changes in the expression of PIF1, cyclin B1, p21, H2AX, p-H2AX, PARP, RAD51, and PCNA protein, with β-actin serving as the loading control. (D) Immunohistochemical staining highlighted expression changes of PIF1, BrdU, p-H2AX, and RAD51 in nude mouse tumors. Scale bar, 50 μm (10×, 20×, 40×).\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/5fc0dee6e8787596c247e7d4.png"},{"id":58309800,"identity":"4df41ecc-7980-4616-bafd-96434db93379","added_by":"auto","created_at":"2024-06-13 18:58:09","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3015712,"visible":true,"origin":"","legend":"\u003cp\u003ePIF1 indirectly interacts with RAD51 protein to regulate ovarian cancer cell proliferation and DNA damage. (A) Immunoblotting analysis of RAD51 expression changes in PIF1 partial knockout ovarian cancer cells, using β-actin as the loading control. (B) Analysis of mRNA and protein expression levels following transfection of control siRNA (NC) and \u003cem\u003eRAD51\u003c/em\u003e siRNA into WT ovarian cancer cells, using \u003cem\u003eGAPDH\u003c/em\u003e and β-actin as controls, respectively. **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001. Data: mean ± SD. One-way ANOVA test. (C) Immunoblotting analysis of pSer317 CHK1 and PIF1 expression changes following RAD51 silencing in ovarian cancer cells at 48 and 72 h, with β-actin as control. (D) Cell counting assessed proliferation changes following \u003cem\u003eRAD51\u003c/em\u003e interference in ES-2 cells over 4 days. ** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, *** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001. Data: mean ± SD. One-way ANOVA test. (E) Immunoblotting analysis of pSer317 CHK1, p-H2AX, RAD51, and PIF1 protein expression changes after RAD51 overexpressing in PIF1 partial deficient cells, with β-actin as loading control. (F) Immunofluorescence analysis of changes in p-H2AX (red) fluorescence intensity following RAD51 overexpression in PIF1 knockout cells, with nuclei stained with DAPI (blue). ** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001. Data: mean ± SD. One-way ANOVA test. (G) Overexpression of RAD51 partially rescued growth defects in PIF1 knockout ES-2 cells. ** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, **** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001. Data: mean ± SD. One-way ANOVA test. (H) Immunoblotting analysis of changes in BRCA2 expression following RAD51 overexpression in PIF1 partial knockout ES-2 cells, with β-actin as loading control. (I) Immunofluorescence detected co-localization of EGFP-PIF1 (green) and RAD51 (red) in ovarian cancer cells. (J) Immunoprecipitation assay indicated that PIF1 and RAD51 protein do not directly bind to each other.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/6842ab06f48ee2aba08ed2b2.png"},{"id":60041257,"identity":"b1948974-44fe-40e3-aec9-107d1bab7c20","added_by":"auto","created_at":"2024-07-11 03:02:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":38054469,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/101cea0a-8e38-4b8d-bf0d-39f6a91bd1b3.pdf"},{"id":58309794,"identity":"80693859-6735-41e6-8e29-96ca032a3368","added_by":"auto","created_at":"2024-06-13 18:58:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":36939,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/f6eae2fa3eca2640b1061dc0.docx"},{"id":58309798,"identity":"d798e833-462b-40e7-998a-39255adbe3ee","added_by":"auto","created_at":"2024-06-13 18:58:08","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":4346708,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigureS1.tif","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/80c26ce1624562f10e2b2ec4.tif"},{"id":58309804,"identity":"246cd4ee-fd51-493d-b379-ba30b8099ee2","added_by":"auto","created_at":"2024-06-13 18:58:10","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":6057944,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigureS2.tif","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/8b204fdd7b08e78366df6759.tif"},{"id":58309799,"identity":"aa735f58-1024-4096-8812-8b967f353beb","added_by":"auto","created_at":"2024-06-13 18:58:09","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":4343184,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigureS3.tif","url":"https://assets-eu.researchsquare.com/files/rs-4495865/v1/5e8c2c136e685b2353a5081a.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"Downregulation of PIF1 induce DNA damage and inhibit ovarian cancer cell proliferation via RAD51","fulltext":[{"header":"Background","content":"\u003cp\u003eOvarian cancer is a common gynecologic malignancy. Early-stage disease lacks specific symptoms, thus effective screening-diagnostic methods are lacking [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Consequently, the global incidence and mortality rates of ovarian cancer remain high. According to the World Health Organization, approximately 324,603 new cases of ovarian cancer and 206,956 related deaths occurred in 2022 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], suggesting a need for novel approaches to improving survival and quality of life among patients. The traditional treatment for ovarian cancer involves surgical intervention combined with adjuvant chemotherapy comprising platinum-based drugs (typically carboplatin) and taxanes (generally paclitaxel). However, drug resistance often develops during the treatment of ovarian cancer, resulting in poor outcomes and limiting treatment options. Drug resistance occurs due to several reasons, including reduced intracellular drug accumulation mediated by drug efflux proteins, altered apoptotic pathways, enhanced DNA repair, and drug resistance caused by tumor stem cells [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Ovarian cancer resistance is primarily caused by enhanced DNA damage repair [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, many studies have focused on ovarian cancer DNA repair defects as key targets for treatment [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePIF1 helicase (5ʹ\u0026rarr;3ʹ DNA helicase), a member of the helicase superfamily 1, translocates along single-stranded DNA and unwinds double-stranded DNA in the 5ʹ\u0026rarr;3ʹ direction [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. PIF1 helicases localize to and facilitate the advancement of replication forks [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Additionally, PIF1 facilitates Okazaki fragment synthesis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. It also plays a crucial role in maintaining mitochondrial genome stability [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and DNA damage repair. PIF1 participates in break-induced replication (BIR) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. During homologous recombination repair of DNA double-strand breaks (DSBs), human PIF1 interacts with BRCA1 to enhance the removal of G4 sequences [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. PIF1 regulates telomerase activity in various organisms [\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In humans, the interaction between PIF1 and telomerase reverse transcriptase promotes cervical cancer cell proliferation [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. PIF1 expression in cancers has been extensively explored. PIF1 is overexpressed in clear cell renal cell carcinoma [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and pancreatic cancer [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Low PIF1 expression is associated with a favorable prognosis in patients with neuroblastoma [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. PIF1 knockdown promotes ferroptosis in lung adenocarcinoma [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Importantly, loss of PIF1 significantly increases tumor cell sensitivity to many chemotherapeutic drugs [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Thus, PIF1 plays a crucial role in cancer and serves as a potential chemotherapy target.\u003c/p\u003e \u003cp\u003eNevertheless, the precise function of PIF1 in regulating ovarian cancer is still unclear. This study therefore aimed to elucidate the regulatory role of PIF1 in ovarian cancer. Specifically, we investigated whether knocking out PIF1 affects the proliferation and chemoresistance of ovarian cancer cells and explored its potential as a prognostic marker and therapeutic target. Furthermore, this study examined the interaction between PIF1 and RAD51 recombinase (RAD51), aiming to reveal how they cooperatively regulate the proliferation and DNA damage repair mechanisms of ovarian cancer cells, providing a scientific basis for developing new ovarian cancer treatment strategies targeting these molecules.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCell culture and CRISPR/Cas9 gene editing\u003c/h2\u003e \u003cp\u003eThe human ovarian cancer cell lines A2780, HO-8910, ES-2, SKOV3, and OVCAR-3, as well as the human embryonic kidney cell line 293T, were acquired from the American Type Culture Collection (ATCC, Manassas, VA, USA). The benign human ovarian epithelial cell line IOSE was generously supplied by Hengyu Fan from Zhejiang University [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Cells were grown in Dulbecco's modified Eagle's medium (Gibco | Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum (Gibco | Thermo Fisher Scientific) and 1% penicillin-streptomycin (Gibco | Thermo Fisher Scientific). Cells were kept at a temperature of 37\u0026deg;C in a humidified environment with 95% air and 5% CO2, which are the standard culture conditions. PIF1-deficient cells were generated through the application of CRISPR/Cas9 technology. Lentivirus-mediated transfection was used to introduce plasmids into ES-2 and OVCAR-3 cells. Following 24 h of transfection, cells were treated with a concentration of 2 \u0026micro;g/mL puromycin for 3 days. Western blot analysis was employed to validate the partial knockout of the \u003cem\u003ePIF1\u003c/em\u003e gene and to assess PIF1 protein expression levels. Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e provides the sequences of \u003cem\u003ePIF1\u003c/em\u003e sgRNAs. CRISPR/Cas9 plasmid was kindly provided by Kun-Liang Guan, West Lake University [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eCell proliferation and colony formation\u003c/h2\u003e \u003cp\u003eFor the examination of the cell growth curve, cells were placed in 6-well plates (Corning, New York, NY, USA) at a density of 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells per well. Cell counts were performed in triplicate for each well at 24, 48, and 72 h after seeding.\u003c/p\u003e \u003cp\u003eIn the colony formation experiments, 1.5 mL of bottom agarose, consisting of 0.5% agarose (Sigma-Aldrich, St. Louis, MO, USA) in standard culture medium, was used to coat each well of a 6-well plate. Around 2,500 cells were mixed with 1.5 mL of top agarose, which included 0.35% agarose in a regular growth medium. This mixture was then applied as a layer onto each well. For cellular nourishment, a volume of 2 mL of cell culture media was applied to the topmost layer twice a week. The cells were incubated for 21 days under conventional culture conditions. After this period, they were stained with 0.5% crystal violet (Sigma-Aldrich) to quantify the colonies. There were six replicates in each experimental group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eWestern blotting\u003c/h2\u003e \u003cp\u003eWhole-cell lysates were generated with western blot and IP lysis buffer (Beyotime Biotechnology, Shanghai, China), and the protein content was determined using the bicinchoninic acid assay kit (Beyotime Biotechnology). Proteins were subjected to denaturation at a temperature of 95\u0026deg;C for 5 min. Subsequently, protein samples of 20-\u0026micro;g were isolated using SDS-PAGE. The gel was then transferred onto PVDF membranes (Merck | Millipore, Burlington, MA, USA). Membranes were obstructed with 5% milk at room temperature for 1 h, treated with primary antibodies (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e) against the target protein overnight at 4\u0026deg;C, and then exposed to horseradish peroxidase-conjugated secondary antibodies (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e) at room temperature for 1 h. Gels were visualized using an enhanced chemiluminescence detection kit (Merck | Millipore). Band intensity was quantified using an Imager 680 (Amersham | GE Healthcare, Chicago, IL, USA) and analyzed with ImageJ software (National Institutes of Health, Bethesda, MD, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry\u003c/h2\u003e \u003cp\u003eThe tumor tissues removed from the nude mice were preserved overnight in a solution of 4% paraformaldehyde. After fixing, the tissues were dehydrated with ethanol at increasing concentrations. Then, xylene was used to replace the ethanol, and finally, the tissues were embedded in paraffin. The tissue blocks fixed in paraffin were cut into sections with a thickness of 5 \u0026micro;m. The deparaffinized sections were treated in 0.3% hydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) for 10 min to suppress endogenous peroxidase activity. The process of antigen retrieval was performed using a 10 mM sodium citrate buffer with a pH of 6.0 for 15 min. The sections were subsequently kept at a temperature of 4\u0026deg;C overnight and exposed to primary antibodies targeting PIF1, p-H2AX, BrdU, and RAD51 (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Subsequently, the sections were treated with biotinylated and peroxidase-conjugated secondary antibodies (1:400; Cell Signaling Technology, Danvers, MA, USA) for 30 min. Ultimately, the sections were stained again using a Vectastain ABC kit and a 3,3'-diaminobenzidine peroxidase substrate kit (Vector Laboratories, Burlingame, CA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOvarian tissue microarray analysis and tumor tissue biopsy\u003c/h2\u003e \u003cp\u003eThe tissue microarrays containing paraffin-embedded human ovarian cancer tissue samples were acquired from Fanpu Biotech (Guilin, China). The data on tumor type, staging, and grading are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Immunohistochemical analysis was conducted on the ovarian tissue chips to assess PIF1 expression. The protein expression levels were determined by multiplying the proportion of cells that tested positive by the intensity of immunostaining. The allocation scores for percentage were as follows: 0 for non-positive cells, 1 for 1\u0026ndash;25%, 2 for 26\u0026ndash;50%, 3 for 51\u0026ndash;75%, and 4 for 76\u0026ndash;100%. Staining intensity was scored as: 0 for negative (-), 1 for weak (+), 2 for moderate (++), and 3 for strong (+++) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The final expression score was categorized as no expression (0), weak expression (1\u0026ndash;3), moderate expression (4\u0026ndash;6), and high expression (8\u0026ndash;12) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In addition, fresh ovarian tumor tissues (n\u0026thinsp;=\u0026thinsp;6) and adjacent non-tumor tissues (n\u0026thinsp;=\u0026thinsp;2) were obtained by biopsy from patients at the First Affiliated Hospital of Jiaxing University (Jiaxing, Zhejiang, China). All participants or their legal guardians provided informed consent, and the study protocol was approved by the institutional review board of the First Hospital of Jiaxing City (LS2020-148). The study adhered to the principles of the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and clinical characteristics of the patients with ovarian cancer (n\u0026thinsp;=\u0026thinsp;99).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (standard deviation) (range)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.70 (13.00) (18\u0026ndash;82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathological type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003cp\u003eBenign tumor\u003c/p\u003e \u003cp\u003eSerous cystadenocarcinoma\u003c/p\u003e \u003cp\u003eEndometrial\u003c/p\u003e \u003cp\u003eMucinous\u003c/p\u003e \u003cp\u003eClear cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2.0%)\u003c/p\u003e \u003cp\u003e3 (3.0%)\u003c/p\u003e \u003cp\u003e48 (48.5%)\u003c/p\u003e \u003cp\u003e30 (30.3%)\u003c/p\u003e \u003cp\u003e15 (15.2%)\u003c/p\u003e \u003cp\u003e1 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathological grading\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eⅠ\u003c/p\u003e \u003cp\u003eⅠ-Ⅱ\u003c/p\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003cp\u003eⅡ-Ⅲ\u003c/p\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (20.4%)\u003c/p\u003e \u003cp\u003e9 (9.7%)\u003c/p\u003e \u003cp\u003e19 (20.4%)\u003c/p\u003e \u003cp\u003e7 (7.5%)\u003c/p\u003e \u003cp\u003e39 (41.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003cp\u003eT2\u003c/p\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (48.9%)\u003c/p\u003e \u003cp\u003e23 (24.5%)\u003c/p\u003e \u003cp\u003e25 (26.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (93.6%)\u003c/p\u003e \u003cp\u003e6 (6.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM0\u003c/p\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 (76.6%)\u003c/p\u003e \u003cp\u003e22 (23.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOvarian cancer PIF1 IHC score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative (0)\u003c/p\u003e \u003cp\u003e+ (1\u0026ndash;3)\u003c/p\u003e \u003cp\u003e++ (4\u0026ndash;6)\u003c/p\u003e \u003cp\u003e+++ (8\u0026ndash;12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.0%)\u003c/p\u003e \u003cp\u003e15 (16.0%)\u003c/p\u003e \u003cp\u003e44 (46.8%)\u003c/p\u003e \u003cp\u003e34 (36.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative real-time polymerase chain reaction (qRT-PCR)\u003c/h2\u003e \u003cp\u003eThe TRIzol reagent (Invitrogen | Thermo Fisher Scientific) was used to extract total RNA from grown cells. The RNA that was obtained was converted into complementary DNA (cDNA) using the PrimeScript RT Reagent Kit (Takara Bio, Shiga, Japan). The TB Green Master Mix reagent kit (Takara Bio) was used for real-time PCR analysis using the Realplex2 PCR equipment (Eppendorf, Hamburg, Germany). The mRNA levels of each gene were standardized by comparing them to the levels of the housekeeping gene GAPDH. The experiment was conducted three times. The primer sequences can be found in Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eRNA interference\u003c/h2\u003e \u003cp\u003eGenePharma Co. (Suzhou, China) designed and synthesized siRNA oligonucleotides targeting the RAD51 gene (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). A negative control siRNA was also provided by GenePharma Co. Ovarian cancer cells were placed into 6-well plates with a concentration of 5 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells per well. Following the manufacturer's instructions, siRNA sequences were transfected into the cells using Lipofectamine RNAiMAX reagent (Invitrogen). After 48 h of transfection (final siRNA concentration 100 nM), the cells were harvested, and the interference efficiency was analyzed by qRT-PCR or western blot.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMice and xenograft models\u003c/h2\u003e \u003cp\u003eFemale BALB/c nude mice, free from specific pathogens, were acquired from Jiangsu Jicui Yaokang Biotechnology Co. (Nanjing, China). The mice were 6\u0026ndash;8-weeks-old and were kept in facilities that met the standards for specific pathogen-free conditions for the whole duration of the study. The animals were cared for and used in accordance with institutional protocols and the National Institutes of Health Guide for the Care and Use of Laboratory Animals (8th edition) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The study received ethical approval from the Medical College Animal Ethics Committee of Jiaxing University (Registration No. JUMC2020-069). Mice were anesthetized with diethyl ether and wild-type and PIF1-deleted cells (5 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells in phosphate buffered saline (PBS)) were subcutaneously injected into both flanks of the mice, with each group comprising 3\u0026ndash;4 mice. Tumor volume was measured every 2 days using calipers, calculated with the formula: volume (mm\u0026sup3;) = (width)\u0026sup2; \u0026times; height \u0026times; 0.523. Mice were terminated by cervical dislocation when the diameter of the tumor exceeded 15 mm, which is the human endpoint. Tumor tissues were subsequently gathered for western blotting and immunohistochemistry investigations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFlow cytometry\u003c/h2\u003e \u003cp\u003eIn order to perform cell cycle analysis, a total of 1 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells were gathered and treated with 70% ethanol for 24 h. Subsequently, the cells were separated by centrifugation and underwent two rounds of washing with PBS. Afterward, the cells were placed in 500 \u0026micro;L of PI/Rnase Staining Buffer (BD Biosciences, Franklin Lakes, NJ, USA) and incubated at 37\u0026deg;C in the absence of light for 30 min. They were then analyzed using flow cytometry (model flow cytometer; BD Biosciences) to quantify the cells in each phase. Data analysis was performed using ModFit software (Verity Software House, Topsham, ME, USA) with each experiment conducted in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDetection of senescence-associated β-galactosidase activity\u003c/h2\u003e \u003cp\u003eTo analyze cell senescence, a total of 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e control cells and PIF1 partial knockout cells were collected and grown overnight in 12-wells plates. Following the washing of cells with 1 \u0026times; PBS, they were then treated with 1 \u0026times; fixation solution at room temperature for 15 min. This was subsequently followed by another round of washing with 1 \u0026times; PBS. The process of senescence staining was performed using the senescence reagent (β-Galactosidase Staining Kit; Beyotime Biotechnology) in accordance with the instructions provided by the manufacturer. Following the staining process, the cells were left overnight to incubate at a temperature of 37\u0026deg;C. Subsequently, they were rinsed with a solution of 1 \u0026times; PBS. The images were acquired using an inverted microscope (model CKX53, Olympus), with a minimum of three randomly selected fields. The quantity of senescent cells stained with blue dye in these regions was determined as a proportion of the overall cell count.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence and co-localization\u003c/h2\u003e \u003cp\u003eFor the immunofluorescence analysis, a total of 5 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e grown cells were placed in 24-well plates. The cells were then rinsed with PBS and subsequently treated with 4% paraformaldehyde for 30 min to ensure fixation. Subsequently, the cells were obstructed with a 5% solution of bovine serum albumin for 1 h. Primary antibodies against p-H2AX, Ki-67, and RAD51 (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e) were incubated with the cells overnight at 4\u0026deg;C. After washing, the cells were incubated with Alexa488- or Alexa594-conjugated secondary antibodies (Abcam, Cambridge, UK) (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e) and stained with DAPI (Beijing Solarbio Science \u0026amp; Technology Co., Beijing, China) to visualize the cell nuclei. The laser scanning confocal microscope (model FV3000; Olympus) was used to obtain digital images. A minimum of three images were acquired for each group.\u003c/p\u003e \u003cp\u003eFor immunofluorescence co-localization analysis, plasmids carrying enhanced green fluorescent protein (EGFP)-tagged PIF1 (Fenghui Biotechnology, Hunan, China) and EGFP empty vector (Fenghui Biotechnology) were separately transfected into cells. Following 36 h of incubation, the cells were fixed and stained with DAPI as described above. Digital images were collected using a laser scanning confocal microscope (model FV3000; Olympus).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePlasmids and overexpression of RAD51 in PIF1 partial knockout cells\u003c/h2\u003e \u003cp\u003eThe human PIF1 cDNA expression construct (EGFP-PIF1) was purchased from Fenghui Biotechnology (Hunan, China). The Flag empty vector was provided by Dr. Heng-Yu Fan [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The Flag-PIF1 construct was created by inserting the human PIF1 cDNA (cloned by Fenghui Biotechnology) into the Flag empty vector, with sequencing validation performed by Sangon Biotech (Shanghai, China). The HA empty vector was acquired from Miaoling Biotechnology (Wuhan, China). Human RAD51 cDNA, cloned from the ovarian cancer cell line ES-2 using specific primers (Table S5), was then inserted into the HA empty vector. This construct was also validated by sequencing at Sangon Biotech (Shanghai, China).\u003c/p\u003e \u003cp\u003eTo construct the RAD51 overexpression vector, the pQCXIH retroviral vector containing the RAD51 cDNA sequence was utilized. pQCXIH plasmid was kindly provided by Kun-Liang Guan, West Lake University [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. 293T cells were transfected with either the pQCXIH empty vector or pQCXIH-RAD51, together with Retro VSVG and Retro GPE constructs, using the PolyJet\u0026trade; DNA In Vitro Transfection Reagent (Signagen Laboratories, Frederick, MD, USA), following the manufacturer's instructions. The transfection was carried out in a medium devoid of serum. After 48 h, the retroviral supernatant was collected, mixed with 5 \u0026micro;g/mL Polybrene (GeneChem Co., Shanghai, China), passed through a sterile 0.45-\u0026micro;m filter (Merck | Millipore), and employed to infect PIF1 partially deficient ES-2 cells. Following 48 h of infection, the specific cells were chosen using a concentration of 200 \u0026micro;g/mL puromycin in a completely supplied medium for 3 days. Stable RAD51 expression in the cells was confirmed via western blot analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCo-immunoprecipitation (Co-IP)\u003c/h2\u003e \u003cp\u003eAfter transfecting the plasmids into 293T cells for 36 h, the cells were lysed and centrifuged using a western blot and IP lysis buffer (Beyotime Biotechnology). The respective antibodies and protein A/G magnetic beads (MCE Magnetic, Mianyang, China) were incubated together at 4\u0026deg;C for 4 h, followed by washing four times with 400 \u0026micro;L of binding/washing buffer (1\u0026times; PBS\u0026thinsp;+\u0026thinsp;0.5% Tween-20\u0026thinsp;+\u0026thinsp;150 mM NaCl). Subsequently, the antibody-bead complexes and protein supernatants were incubated together overnight at 4\u0026deg;C. The immune complexes were washed six times with PBST buffer (1\u0026times; PBS\u0026thinsp;+\u0026thinsp;0.5% Tween-20\u0026thinsp;+\u0026thinsp;150 mM NaCl), resuspended in 1\u0026times; loading buffer, and heated at 95\u0026deg;C for 5 min. Finally, the samples were analyzed by western blot.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eCell counting kit-8 (CCK8) assay\u003c/h2\u003e \u003cp\u003eThree thousand cells were resuspended in 200 \u0026micro;L of medium and seeded into a 96-well plate. After cell adhesion, they were treated with increasing concentrations of cisplatin for 24 h. After the treatment period, cells were incubated with 10 \u0026micro;L of CCK-8 reagent (MCE Magnetic, Mianyang, China) in 100 \u0026micro;L of medium for 1\u0026ndash;4 h. The Spark multimode microplate reader (Tecan, M\u0026auml;nnedorf, Switzerland) was used to measure absorbance at 450 nm, with data collected using TECAN software. Each condition was replicated four times.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eKaplan-Meier plotter database\u003c/h2\u003e \u003cp\u003eAn online database called Kaplan Meier plotter (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://kmplot.com/analysis\u003c/span\u003e\u003cspan address=\"http://kmplot.com/analysis\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) can be used to assess the relationship between gene mRNA expression and survival in a variety of cancer cohorts, such as patients with acute myeloid leukemia, multiple myeloma, lung, gastric, pancreatic, and breast cancers [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Histology, stage, grade and the use of chemotherapy were among the clinical data available for ovarian cancer patients (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). An online analysis was conducted to examine the correlation between \u003cem\u003ePIF1\u003c/em\u003e mRNA expression and survival in ovarian cancer patients. The results were expressed as the hazard ratio and logarithmic rank P-value. Patients with \u003cem\u003ePIF1\u003c/em\u003e gene expression were grouped using the best available cut-off value [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and clinical characteristics of patients with ovarian cancer (n\u0026thinsp;=\u0026thinsp;655).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients, n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePathological type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSerous cystadenocarcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e523 (79.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndometrial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e102 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eStage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e426 (74.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e162 (26.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e392 (63.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e478 (73.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTaxol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e357 (54.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlatin\u0026thinsp;+\u0026thinsp;Taxol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e356 (54.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e176 (26.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and clinical characteristics of patients with ovarian cancer (n\u0026thinsp;=\u0026thinsp;382).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients, n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePathological type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSerous cystadenocarcinoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e346 (90.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndometrial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eStage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e312 (81.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109 (29.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e240 (63.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e373 (97.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTaxol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e274 (71.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlatin\u0026thinsp;+\u0026thinsp;Taxol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e273 (71.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eGEPIA database\u003c/h2\u003e \u003cp\u003eThe GEPIA database is an online database developed by Zhang's Lab at Peking University in Beijing, China [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. It may be accessed at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gepia.cancer-pku.cn/\u003c/span\u003e\u003cspan address=\"http://gepia.cancer-pku.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The association between \u003cem\u003ePIF1\u003c/em\u003e and ovarian cancer was analyzed with the \u0026ldquo;Boxplots\u0026rdquo; module of GEPIA. GEPIA employs the log2 (TPM\u0026thinsp;+\u0026thinsp;1) method to represent data on a logarithmic scale when comparing TCGA normal and GTEx data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eUALCAN database\u003c/h2\u003e \u003cp\u003eThe UALCAN database provides a thorough and interactive analysis of bioinformatics utilizing RNA-seq and clinical data from 31 tumors in the TCGA dataset (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ualcan.path.uab.edu/\u003c/span\u003e\u003cspan address=\"http://ualcan.path.uab.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The association between \u003cem\u003ePIF1\u003c/em\u003e and ovarian cancer grades was analyzed with the \u0026ldquo;tumor grade\u0026rdquo; module of UALCAN.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Non-normally distributed variables were analyzed using the Mann-Whitney U test. Unpaired parametric tests were employed for normally distributed variables. Three or more groups were compared using one-way ANOVA. Statistical analyses were conducted using GraphPad Prism software (GraphPad Software, San Diego, CA, USA). Statistical significance was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Data obtained from mice that died were excluded from the analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003ePIF1 overexpression positively correlates with cancer grade and negatively correlates with the overall survival rate in ovarian cancer\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo determine the function of PIF1 in ovarian cancer, immunohistochemical techniques were employed to identify its expression in normal ovarian tissues (n\u0026thinsp;=\u0026thinsp;2), benign tumor tissues (n\u0026thinsp;=\u0026thinsp;3), and ovarian cancer tissues (n\u0026thinsp;=\u0026thinsp;94) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Based on the PIF1 protein expression scoring, the immunohistochemical results were categorized into four groups, ranging from the least powerful (\u0026minus;) to the most powerful (+++) in increasing order (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). As shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the distribution of PIF1 signal strength among the 94 ovarian cancer cases was as follows: (\u0026minus;) 1 case (1.0%), (+) 15 cases (16.0%), (++) 44 cases (46.8%), and (+++) 34 cases (36.2%). Owing to significant tissue section loss, three specimens were excluded. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB demonstrates a notable disparity in PIF1 expression between normal ovaries and both serous cystadenomas and endometrioid carcinomas (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Western blot analysis was conducted on six fresh ovarian cancer tissue samples and two adjacent non-tumor tissue samples derived from patients. Compared to non-malignant tissues, PIF1 was overexpressed in four of six ovarian cancer tissue samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG), and densitometric analysis of non-malignant and malignant tissues revealed statistically significant differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These results validate the high expression of PIF1 in ovarian cancer tissues.\u003c/p\u003e \u003cp\u003eUsing the GEPIA database, we further investigated the expression of PIF1 in ovarian cancer to evaluate its correlation with disease progression. In ovarian cancer tissues, we observed a significant upregulation of \u003cem\u003ePIF1\u003c/em\u003e expression when compared to normal tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). The Kaplan-Meier curve analysis revealed a relationship between the \u003cem\u003ePIF1\u003c/em\u003e expression level and survival rate of patients with ovarian cancer (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The group with high \u003cem\u003ePIF1\u003c/em\u003e expression exhibited significantly lower overall survival and prognostic survival curves compared to the group with low \u003cem\u003ePIF1\u003c/em\u003e expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D). Additionally, using the UALCAN database, we found differences in \u003cem\u003ePIF1\u003c/em\u003e expression during the clinical grading of ovarian cancer. The expression of \u003cem\u003ePIF1\u003c/em\u003e in grade 3 ovarian cancer was notably elevated compared to grade 2 ovarian cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). These results further confirmed \u003cem\u003ePIF1\u003c/em\u003e upregulation in patients with ovarian cancer and suggested a positive correlation between \u003cem\u003ePIF1\u003c/em\u003e expression and ovarian cancer grade.\u003c/p\u003e \u003cp\u003eWestern blot analysis showed that, compared to benign human ovarian epithelial cell line (IOSE), PIF1 was highly expressed in most ovarian cancer cell lines (SKOV3, A2780, OVCAR-3, and ES-2) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH). Furthermore, immunofluorescence analysis showed that EGFP-PIF1 was localized in the nucleus of cultured ovarian cancer cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI). These results collectively indicate that PIF1 is highly expressed in ovarian cancer tissues and cells and that its expression level is closely linked to ovarian cancer grading and patient survival rates.\u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003ePIF1 partial knockdown inhibits the proliferation and colony formation of ovarian cancer cells\u003c/h2\u003e \u003cp\u003eTo investigate whether PIF1 affects ovarian cancer cell proliferation, we used CRISPR/Cas9 to knock out PIF1 in ovarian cancer cell lines (ES-2 and OVCAR-3). Owing to the challenge of obtaining complete \u003cem\u003ePIF1\u003c/em\u003e gene knockout clones, we were only able to obtain two PIF1 partial knockdown clones that exhibited significantly lower levels of PIF1 protein expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). This study utilized two distinct clones that were created using two separate CRISPR guide sequences. PIF1 partial knockdown decelerated ovarian cancer cell proliferation in both clones (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) and markedly inhibited (OVCAR-3) or delayed (ES-2) colony formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Correspondingly, expression of the cell proliferation marker PCNA was lower in PIF1 partially deficient cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD), and cells exhibited decreased Ki-67 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). In summary, these findings indicate that PIF1 plays an important role in ovarian cancer cell proliferation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e\u003cb\u003ePIF1 partial knockdown inhibits cell cycle progression and promotes cell senescence\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe unrestricted proliferation of cancer cells depends on the disruption of normal regulatory cell cycle mechanisms [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. To further elucidate the mechanism in which PIF1 loss inhibits cell proliferation, we conducted a flow cytometry analysis of the cell cycle in ES-2 and OVCAR-3 cells. In comparison to wild-type ovarian cancer cells, there was a notable increase in the percentage of PIF1 partially deficient cells in the G2 phase, while the percentage of cells in the G1 and S phases showed a significant decrease (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In PIF1 partially deficient cells, p21 and p27 expression was significantly higher (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), indicating that PIF1 regulates the cell cycle via p21 and p27 upregulation. qRT-PCR analysis revealed upregulation of \u003cem\u003eP53\u003c/em\u003e transcription and downregulation of \u003cem\u003eMDM2\u003c/em\u003e transcription in PIF1 partially deficient ovarian cancer cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). These findings imply that PIF1 partial deficiency blocks the cell cycle in human ovarian cancer cells. A stable cell cycle arrest characterizes cellular senescence, which limits cell proliferation [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. We found that, compared with wild-type ovarian cancer cells, PIF1 partially deficient cells exhibit elevated SA-β-galactosidase staining intensity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Plasminogen activator inhibitor-1 (PAI-1) is a marker for aging as its expression level is positively correlated with human age [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Lamin B1 is indispensable for maintaining the integrity of nuclear structure; however, aging cells tend to lose this structural integrity [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. We observed an increase in PAI-1 and a decrease in lamin B1 protein expression in PIF1 partially deficient ovarian cancer cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE), confirming that PIF1 partial deficiency promotes senescence in ovarian cancer cells. These results suggest that PIF1 partial deficiency increases G2 phase cells and promotes cell senescence in ovarian cancer cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003ePIF1 partial knockdown promotes DNA damage in ovarian cancer cells\u003c/h2\u003e \u003cp\u003ePIF1 has significant functions in DNA replication and repair. To elucidate the effects of the PIF1 protein on DNA damage in ovarian cancer cells, we conducted immunoblotting analysis and discovered that, compared to wild-type ovarian cancer cells, the expression of p-H2AX, p-CHK1, and p-CHK2 was significantly higher in PIF1 partially deficient ovarian cancer cells, while the total levels of H2AX, CHK1, and CHK2 remained relatively consistent (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Ataxia telangiectasia mutated (ATM) is a serine/threonine protein kinase that is activated during DNA DSBs and enhances the homologous recombination repair pathway [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The expression levels of phosphorylated ATM were significantly lower in ovarian cancer cells partially deficient in PIF1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). A downstream target of ATM, the nonreceptor tyrosine kinase encoded by the c-Abl proto-oncogene, engages in interaction with ATM after DNA damage [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. qRT-PCR revealed a decrease in \u003cem\u003ec-Abl\u003c/em\u003e expression in PIF1 partially deficient ovarian cancer cells (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB). Through the CCK8 assay, it was observed that increasing concentrations of cisplatin effectively suppressed the proliferation of ovarian cancer cells. At a cisplatin concentration of 0.125 \u0026micro;g/mL (or 0.25 \u0026micro;g/mL), there was no significant difference between wild-type ovarian cancer cells before and after treatment, whereas the growth of PIF1 partial knockdown ovarian cancer cells was significantly different before and after treatment, indicating that PIF1 partial depletion may enhance cancer cell sensitivity to cisplatin (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Furthermore, the fluorescence intensity of p-H2AX in PIF1 partially deficient ovarian cancer cells was significantly higher than that in wild-type cells, and upon treatment with the same concentration of cisplatin, the fluorescence intensity of p-H2AX in PIF1 partially deficient ovarian cancer cells increased further (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Similar results were obtained when UV treatment was applied to wild-type ES-2 cells and ES-2 cells lacking PIF1 (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA). In summary, PIF1 is involved in DNA damage repair and its partial deficiency promotes DNA damage in ovarian cancer cells, thereby increasing their sensitivity to cisplatin.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePIF1 partial deficiency suppresses tumor growth\u003c/b\u003e \u003cb\u003ein vivo\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo further validate the impact of PIF1 partial knockout on ovarian cancer cell proliferation \u003cem\u003ein vivo\u003c/em\u003e, we implanted wild-type/PIF1 partial knockdown ovarian cancer (ES-2 and OVCAR-3) cells subcutaneously into both flanks of BALB/c mice. Compared to wild-type mice, animals transplanted with PIF1 partial knockdown cells exhibited smaller tumor volumes and weights at animal sacrifice (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B). Growth curves provided compelling evidence that tumor cell growth was attenuated in the PIF1 partial knockdown group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B). These findings demonstrate the importance of PIF1 for the survival of cancer cells \u003cem\u003ein vivo\u003c/em\u003e. In subsequent experiments, immunoblotting revealed significantly elevated levels of the DNA damage-related protein p-H2AX, apoptosis-related protein PARP, and cell cycle kinase inhibitor p21 in tumor tissues lacking PIF1, while those of the proliferative protein PCNA and cell cycle protein cyclin B1 were significantly reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Furthermore, immunohistochemical results confirmed decreased expression of the proliferative protein BrdU and increased expression of p-H2AX in tumor tissues lacking PIF1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). These findings suggest that PIF1 partial knockdown suppresses tumor cell proliferation \u003cem\u003ein vivo\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003ePIF1 indirectly interacts with RAD51 protein to regulate ovarian cancer cell proliferation and DNA damage\u003c/h2\u003e \u003cp\u003eWe noted a considerable decline in the expression of RAD51 protein in PIF1 partially deficient ovarian cancer cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Previous studies have indicated that c-Abl interacts with RAD51 and phosphorylates it to regulate recombination repair of DNA DSBs [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. qRT-PCR analysis indicated that the mRNA levels of \u003cem\u003ec-Abl\u003c/em\u003e were lower in PIF1 partial knockdown ovarian cancer cells (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB), further confirming that PIF1 partial deficiency inhibits RAD51 expression in ovarian cancer cells. Therefore, we speculated that PIF1 and RAD51 co-regulate DNA damage in ovarian cancer.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo gain deeper insights into the function of PIF1 in DNA damage in ovarian cancer cells, we silenced the expression of RAD51 in wild-type ovarian cancer cells. As a result, we observed an increase in the expression of the DNA damage marker protein p-CHK1 and a decrease in the expression of PIF1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-C). The human breast cancer suppressor protein BRCA2 interacts directly with RAD51 to regulate homologous recombination [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. After silencing RAD51 in ovarian cancer cells, a considerable decrease in the expression of the RAD51 protein complex \u003cem\u003eBRCA2\u003c/em\u003e was observed (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eE). In addition, the growth of wild-type ovarian cancer cells was inhibited (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD and Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC-D). Ovarian cancer cells with RAD51 knocked down exhibited phenotypes similar to those of PIF1 partially deficient ovarian cancer cells, and downregulation of RAD51 resulted in decreased PIF1 expression.\u003c/p\u003e \u003cp\u003eIn order to conduct a more in-depth examination of the functions of PIF1 and RAD51 in relation to the growth of ovarian cancer cells and the occurrence of DNA damage, we overexpressed RAD51 in PIF1 partially deficient ovarian cancer cells. Immunoblotting analysis revealed that overexpression of the RAD51 protein caused an increase in the expression of PIF1 protein, while the expression of the DNA damage marker proteins p-H2AX and p-CHK2 decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). Furthermore, immunofluorescence analysis confirmed that overexpression of RAD51 in PIF1 partially deficient ovarian cancer cells rescued the DNA damage caused by PIF1 partial deficiency (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). Proliferation levels were assessed by cell counting for 3 days, revealing that RAD51 overexpression rescued the proliferation of PIF1 partially deficient ovarian cancer cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG). Following RAD51 overexpression, both the protein and mRNA levels of BRCA2 increased significantly (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH and Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003eImmunofluorescence colocalization analysis revealed the colocalization of the RAD51 protein with the EGFP-PIF1 protein in ovarian cancer cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI). However, immunoprecipitation experiments showed that RAD51 and PIF1 did not physically interact with each other (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eJ). In summary, we speculate that PIF1 and RAD51 cooperate to regulate ovarian cancer cell proliferation and DNA damage. Functionally, PIF1 interacts with RAD51, but physically RAD51 acts independently of PIF1. This suggests that other proteins act as bridges between PIF1 and RAD51, or that PIF1 and RAD51 may be co-regulated through more complex protein networks.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we found that ovarian cancer patients who had low levels of \u003cem\u003ePIF1\u003c/em\u003e expression had a superior overall survival rate and prognosis, according to the clinical data. This finding was further corroborated by the reduction in cell viability observed upon the partial knockdown of PIF1 in ovarian cancer cells. Additionally, PIF1 partial knockdown increased basal levels of DNA damage and DNA damage response signaling, which was further exacerbated by cisplatin treatment, supporting the hypothesis that PIF1 partial deficiency sensitizes ovarian cancer cells to cisplatin treatment. These findings strongly indicate that PIF1 could serve as a crucial target for pharmacological intervention and as a prognostic biomarker for ovarian cancer.\u003c/p\u003e \u003cp\u003eThe PIF1 helicase is essential for preserving the integrity of the genome and repairing DNA damage. Gagou et al. detected a slight increase in p-H2AX level but no significant activation of pSer1981 ATM or pSer345 CHK1 in PIF1-knocked down HCT116 cells [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our results suggest that PIF1 partial knockdown resulted in p-H2AX, pSer317 CHK1, and pT68 CHK2 expression upregulation, and a decrease in pSer1981 ATM expression. CHK1 is a key component of the ATR cascade, which is rapidly activated by disrupting single-stranded DNA formed during DNA replication to suppress inappropriate initiation, promote replication restart, and prevent cell apoptosis [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Phosphorylation of CHK1 at different sites by ATM/ATR results in CHK1 exerting distinct functions [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Phosphorylation of CHK1 at the Ser317 site allows cells to re-enter the cell cycle after DNA replication stalling [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. PIF1 helicases promote the progression of replication forks and resolve various obstacles in the replication fork structures. Therefore, we speculate that the activation of CHK1 at the Ser317 phosphorylation site, following PIF1 partial knockdown, may result from DNA replication stalling caused by PIF1 partial depletion rather than the inactivated Ser345 phosphorylation of CHK1 observed in previous reports. DNA DSBs activate ATM, which assists in DNA repair [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. However, in our study, we found that ATM phosphorylation at Ser1981 was inhibited after PIF1 partial knockout, suggesting that PIF1 partial depletion may suppress ATM-related DNA damage repair pathways. In the autofeedback loop formed by \u003cem\u003eP53\u003c/em\u003e and \u003cem\u003eMDM2\u003c/em\u003e, a decrease in \u003cem\u003eMDM2\u003c/em\u003e and an increase in \u003cem\u003eP53\u003c/em\u003e occur simultaneously, activation of \u003cem\u003eP53\u003c/em\u003e initiates cell cycle arrest and apoptosis [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. We observed similar results in PIF1 partially deficient ovarian cancer cells.\u003c/p\u003e \u003cp\u003eIt has been reported that PIF1 downregulation can enhance pancreatic cancer cells' sensitivity to gemcitabine [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] as well as sensitize other tumor cells to chemotherapy drugs such as hydroxyurea and aphidicolin [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. We discovered in this study that reducing the expression of PIF1 increased the susceptibility of ovarian cancer cells to cisplatin. When exposed to small amounts of cisplatin, the survival rate of PIF1 partial knockdown ovarian cancer cells reduced considerably, but the survival rate of wild-type ovarian cancer cells remained unaltered. Immunofluorescence analysis revealed that DNA damage in PIF1 partial knockout ovarian cancer cells increased prominently following treatment with the same cisplatin concentration. In conjunction with earlier studies, this evidence suggests that PIF1 knockdown can increase the sensitivity of tumor cells to chemotherapeutic drugs. The standard chemotherapy for ovarian cancer involves the administration of platinum-based medications in conjunction with paclitaxel. The primary mechanism of cytotoxicity induced by paclitaxel is attributed to the inhibition of microtubule dynamics and compromised centrosome function, leading to mitotic arrest [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Our work revealed that the partial knockdown of PIF1 leads to the arrest of ovarian cancer cells at the G2 phase. This suggests a potential synergistic interaction between PIF1 depletion and paclitaxel in ovarian cancer cells, potentially amplifying the pathways leading to cell death.\u003c/p\u003e \u003cp\u003eHomologous recombination is a mechanism for repairing DSBs in DNA and fork replication [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. RAD51 serves as a central scaffold protein for homologous recombination repair [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and is crucial for timely and accurate DNA repair [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. RAD51 is a hallmark protein of homologous recombination [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. BIR is a form of homologous recombination that involves the repair of single-ended DNA DSBs on folded replication forks [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. PIF1 readily localizes to replication-associated fragile sites, inducing BIR [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. A specific sequence mutation in Saccharomyces cerevisiae PIF1 (ScPIF1) leads to BIR defects [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Moreover, the typical BIR pathway relies on RAD51 in eukaryotes [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. We observed significant downregulation of RAD51 protein expression upon PIF1 partial knockdown in ovarian cancer cells. Thus, we infer that PIF1 partial knockdown may interfere with the homologous recombination repair pathway. Subsequently, when we silenced RAD51 in ovarian cancer cells, we found that the expression of the PIF1 protein also decreased, leading to DNA damage and slower proliferation. Additionally, RAD51 overexpression in ovarian cancer cells partially rescued the DNA damage and proliferation defects caused by PIF1 partial knockout. Immunoprecipitation assays revealed no interactions between PIF1 and RAD51. ChIP assays in budding yeast revealed no notable variations in the abundance of RAD51 protein bound near DSBs in cells with mutated PIF1 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis evidence suggests that PIF1 and RAD51 do not interact directly via binding. However, in immunofluorescence co-localization studies, we found that endogenous RAD51 protein in ovarian cancer cells co-localized with exogenous EGFP-PIF1 protein in the cell nucleus (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI). These results indicate that the PIF1 and RAD51 proteins are spatially close, suggesting functional interactions despite the lack of direct physical binding. Therefore, we speculated that the functional interaction between PIF1 and RAD51 in ovarian cancer may depend on the biological pathway of homologous recombination, particularly BIR. We intend to conduct further investigations into this potential in future studies.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, our findings demonstrate that PIF1 is highly expressed in ovarian cancer compared to normal tissues and that overexpression of PIF1 is negatively associated with survival in ovarian cancer patients. PIF1 partial knockout may reduce the proliferation of ovarian cancer cells through multiple mechanisms, including senescence, cell cycle arrest, and DNA damage. This can have an inhibitory influence on the malignant ability of ovarian cancer cells. Additionally, we found that PIF1 indirectly collaborates with RAD51 to regulate the growth and DNA damage of ovarian cancer cells. These findings offer novel insights into the molecular mechanisms behind ovarian cancer and provide a theoretical foundation for the development of pharmacological therapy options. Simultaneously, the importance of PIF1 as a prognostic biomarker for ovarian cancer is underscored.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.11030741410488%\"\u003e\n \u003cp\u003eBreak-induced replication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.88969258589512%\"\u003e\n \u003cp\u003eBIR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.11030741410488%\"\u003e\n \u003cp\u003eDNA double-strand breaks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.88969258589512%\"\u003e\n \u003cp\u003eDSBs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.11030741410488%\"\u003e\n \u003cp\u003eRAD51 recombinase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.88969258589512%\"\u003e\n \u003cp\u003eRAD51\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.11030741410488%\"\u003e\n \u003cp\u003eComplementary DNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.88969258589512%\"\u003e\n \u003cp\u003ecDNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.11030741410488%\"\u003e\n \u003cp\u003eEnhanced green fluorescent protein\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.88969258589512%\"\u003e\n \u003cp\u003eEGFP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.11030741410488%\"\u003e\n \u003cp\u003eCo-immunoprecipitation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.88969258589512%\"\u003e\n \u003cp\u003eCo-IP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.11030741410488%\"\u003e\n \u003cp\u003eCell counting kit-8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.88969258589512%\"\u003e\n \u003cp\u003eCCK8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"63.11030741410488%\"\u003e\n \u003cp\u003eAtaxia telangiectasia mutated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"36.88969258589512%\"\u003e\n \u003cp\u003eATM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants or their legal guardians provided informed consent, with the study protocol approved by the institutional review board of the First Hospital of Jiaxing City (LS2020-148). Animal experimental protocols in this manuscript received ethical approval from the Medical College Animal Ethics Committee of Jiaxing University (Registration No. JUMC2020-069).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data are contained in the figures, figure legends, or additional files, further inquiries can be directed to the corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our gratitude to Jing-Ya Zhong, Jing-Jian Dong, and Li-Li Shi for their invaluable technical support. We also acknowledge Dr. Kun-Liang Guan for providing the CRISPR/Cas9 and pQCXIH plasmids, Dr. Heng-Yu Fan for the IOSE cells and FLAG empty vector plasmid and Dr. Yi-Ting Zhou for discussion.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eW-WP and S-QC were responsible for the overall conception and design of this experiment. W-WP, X-MW, and Q-YZ collated and summarized the experimental results and wrote the manuscript. Q-YZ and H-YH participated in most of the experimental procedures in this study, and Q-QS participated in Co-IP experiments and some immunohistochemistry experiments. M-ZN and SZ were involved in the management and sampling of experimental animals. S-BL were involved in the immunohistochemical experiments. S-QC, XC, Z-JW and XZ participated in the collection of clinicopathological specimens. X-CZ, X-MW, LA, Y-JG, and MH revised the final manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding and additional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from National Natural Science Foundation of China (31871402) and The Natural Science Foundation of Zhejiang Province (LY21H160047, LGD21H160003, LQ23C070001, Z20H160031, LGF20H160031, LGD22H030004). This work was supported by grants from National College Student Innovation and Entrepreneurship Training Program (222024R7034, 2024R417010) and Zhejiang Provincial Foreign Expert Grant (12.2018). This work was supported by Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics (12.2019). This work was supported by the Dutch Cancer Foundation (KWF, project 10666) and The Top-level Talent Project of Zhejiang Province. This work was supported by the Jiaxing talent pioneer innovation team (6.2021) and the Natural Science Foundation of Jiaxing(2020AD30073). This work was supported by Jiaxing Science Foundation for Young Talents (2023AY40005). This work was supported by Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKuroki L, Guntupalli SR. Treatment of epithelial ovarian cancer. BMJ. 2020;371:m3773. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmj.m3773\u003c/span\u003e\u003cspan address=\"10.1136/bmj.m3773\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorre LA, Trabert B, Desantis CE, Miller KD, Samimi G, Runowicz CD, et al. Ovarian cancer statistics, 2018. 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Trends Genet. 2022;38:752\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tig.2022.03.011\u003c/span\u003e\u003cspan address=\"10.1016/j.tig.2022.03.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"ovarian cancer, DNA helicase PIF1, RAD51, proliferation, DNA damage and repair, chemoresistance, poor prognosis, homologous recombination","lastPublishedDoi":"10.21203/rs.3.rs-4495865/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4495865/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePIF1 helicase (5ʹ\u0026rarr;3ʹ DNA helicase) is a member of helicase superfamily 1. It has unwinding activity and plays a crucial role in maintaining genome stability and coordinating DNA damage repair processes. Overexpression of PIF1 is common in several cancers; however, its role in ovarian cancer remains unclear. This study aimed to elucidate the regulatory role of PIF1 in ovarian cancer and explore its mechanism.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAnalysis of patient samples and public database datasets revealed a negative correlation between PIF1 overexpression and the overall survival rate of the patients. We found through molecular biology experiments and xenograft tumor models in nude mice that CRISPR/Cas9-mediated PIF1 partial knockdown in ovarian cancer cell lines significantly inhibited proliferation and clonogenicity, promoted senescence, and induced G2 cell cycle arrest. Moreover, PIF1 partial deficiency enhanced DNA damage in ovarian cancer cells, particularly sensitive to cisplatin. RAD51 serves as a central scaffold protein for homologous recombination repair and is crucial for timely and accurate DNA repair. We observed that PIF1 partial knockdown resulted in significant reduction of RAD51 in ovarian cancer cells. Notably, RAD51 overexpression in PIF1 partially deficient ovarian cancer cells rescued cell proliferation and DNA damage by increasing PIF1 expression. Immunofluorescence revealed the co-localization of EGFP-PIF1 and RAD51 in the cell nucleus, suggesting that the interaction between PIF1 and RAD51 may regulate the DNA damage response and cell survival in ovarian cancer cells.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur study revealed that PIF1 is a druggable target for inducing DNA damage in ovarian cancer cells and provides insights into the potential synergistic mechanisms of action between PIF1 and RAD51 in ovarian cancer therapy.\u003c/p\u003e","manuscriptTitle":"Downregulation of PIF1 induce DNA damage and inhibit ovarian cancer cell proliferation via RAD51","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-13 18:58:03","doi":"10.21203/rs.3.rs-4495865/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"45ebb31d-c0b4-4a26-91f7-8ecef6297d9e","owner":[],"postedDate":"June 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-11T02:53:29+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-13 18:58:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4495865","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4495865","identity":"rs-4495865","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}