Augmenting Chemotherapy Response In Ovarian Cancer: Omega-3 Polyunsaturated Fatty Acids Target TOP2A

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This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4490207/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/Objectives: Ovarian cancer presents significant challenges in treatment efficacy, necessitating exploration of alternative therapeutic approaches. This study aimed to investigate the effects of omega-3 polyunsaturated fatty acids (n-3 PUFAs), particularly in conjunction with chemotherapy, on ovarian teratocarcinoma cells. Subject/Methods : The study conducted rigorous cell viability assays to assess the impact of n-3 PUFAs on doxorubicin (DOXO)-induced cytotoxicity. Clonogenic assays, hanging drop assays, and apoptosis assays were employed to validate the observed effects. Network pharmacological analyses and molecular docking simulations were conducted to elucidate potential molecular mechanisms underlying the observed synergistic effects. Results: Cell viability assays demonstrated a significant augmentation of DOXO-induced cytotoxicity by n-3 PUFAs, resulting in decreased cellular viability and migratory capacity. Clonogenic assays confirmed a reduction in colony formation in the combined treatment group, supported by additional experimental assays. Network pharmacological analyses identified topoisomerase II A (TOP2A) gene as a key target, while molecular docking simulations revealed structural analogies between n-3 PUFAs and DOXO, suggesting shared mechanisms of action. Conclusion: The integration of computational and experimental approaches uncovered the synergistic effects of n-3 PUFAs and DOXO in ovarian cancer treatment. This study bridges the gap between theoretical understanding and practical application, offering promising prospects for enhanced therapeutic outcomes in ovarian cancer management. Ovarian cancer omega-3 polyunsaturated fatty acids chemotherapy doxorubicin TOP2A molecular docking synergistic effects Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Ovarian cancer ranks as the seventh leading cause of female mortality globally and is the third most common gynecological cancer in India [ 1 ]. A staggering 314,000 new ovarian cancer cases and 207,000 related deaths were reported in 2020 [ 2 ]. Due to its insidious symptoms at early stages, ovarian cancer often remains undetected until later stages [ 3 ]. Despite recent strides in cancer therapy, conventional cytotoxic treatments such as chemotherapy and radiotherapy have several drawbacks, leading to treatment failure, cancer relapse, and unsatisfactory long-term clinical outcomes[ 4 ][ 5 ]. These drawbacks predominantly stem from two major issues: (1) Conventional treatments fail to eradicate tumor-initiating cells (TICs), a population of self-renewing and drug-resistant cancer cells, or cause the development of drug resistance in tumor cells [ 6 ][ 7 ]. (2) The use of traditional medicines can result in both local and systemic toxicity due to the widespread death of normal cells [ 8 ]. Most oncologists believe that targeting a single molecular component may not be adequate to halt this process since cancer cell survival is governed by intricate molecular interactions between growth and death signals [ 9 ]. Hence, there is an urgent need to combine traditional treatments with compounds that can enhance the effectiveness of chemotherapy without harming healthy cells. Doxorubicin (DOXO) is one of the most effective antineoplastic drugs and is used either alone or in combination with other therapies [ 10 ][ 11 ]. It inhibits topoisomerase II by DNA intercalation and the formation of free radicals, thereby causing cancer cell death [ 12 ][ 13 ]. Omega-3 polyunsaturated fatty acids (n-3 PUFAs) are essential fatty acids that are integral to the regular development and growth of various human tissues [ 14 ][ 15 ]. They incorporate into the cell membrane and, by altering the membrane composition and function, modulate intracellular signaling in different types of cancers. Their metabolites regulate the expression of genes involved in key cellular processes by binding to various transcription factors [ 16 ][ 17 ][ 18 ]. These properties position PUFAs as potential modulators in various cancer cellular processes. Numerous studies have demonstrated that n-3 PUFAs, specifically eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), reduce tumor growth by triggering cancer cell apoptosis, either alone [ 19 ][ 20 ] or in combination with established anticancer therapy [ 21 ][ 22 ]. Although various studies have reported the synergistic effects of n-3 PUFAs with chemotherapy drugs in chronic myeloid leukemia (CML), breast, prostate, lung, gastric, and ovarian cancers[ 23 ][ 24 ][ 25 ][ 26 ][ 27 ], there are limited in-depth reports on the synergistic effects of PUFAs and the chemotherapy drug DOXO[ 28 ][ 29 ][ 30 ]. Diets rich in n-3 PUFAs, found in Mediterranean and Japanese diets, may help reduce the risk of cancer[ 31 ]. Studies conducted on zebrafish models indicate that DHA reduces the proliferation and invasion of ovarian cancer by modulating the NF-κB, mTOR, and MAPK pathways[ 32 ][ 33 ]. N-3 PUFAs, like DHA and EPA, enhance chemotherapy effectiveness by aiding drug absorption into cancer cells' lipid bilayers and inhibiting survival pathways [ 34 ]. DHA enhances the efficacy of anticancer drugs like cisplatin and doxorubicin by increasing their cytotoxicity in various cancer cells, including those resistant to multiple drugs, while also shielding non-target organs like the gastrointestinal tract from damage and improving tumor response to irinotecan therapy in specific cases[ 35 ][ 36 ]. In the previous study, we have shown that n-3 polyunsaturated fatty acids (PUFAs) can enhance the effectiveness of doxorubicin in treating breast cancer[ 37 ]. However, the exact mechanism of synergistic action of n-3 PUFAs with Doxorubicin has not been explored yet. Computer-aided drug discovery (CADD) techniques are extensively employed in modern drug development, with TOP1 and TOP2A identified as biomarkers for poor survival in epithelial ovarian carcinoma [ 38 ][ 39 ]. DHA and EPA, structurally similar to DOXO, demonstrate similar mechanisms of action as DNA intercalators and TOP2A inhibitors, synergistically enhancing chemotherapy efficacy against ovarian cancer [ 40 ]. The objective of this study is to assess the influence of n-3 PUFAs, such as DHA and EPA, both separately and in conjunction with DOXO, on ovarian cancer cells. The aim is to examine the impact of this combination on anti-proliferation, apoptosis, and anti-metastasis. Furthermore, in silico experiments were conducted to elucidate the mode of action of PUFAs in tandem with DOXO. The outcomes of this investigation carry significant ramifications for furthering our comprehension of the possible therapeutic benefits of these substances in treating ovarian cancer. Materials and Methods Materials Docosahexaenoic acid was purchased from Sigma‒Aldrich (Sigma Aldrich, MO, USA). Eicosapentaenoic acid was purchased from TCI (Tokyo Chemical Industry India Pvt. Ltd; Tokyo Japan). Doxorubicin, DMEM, penicillin and streptomycin, trypsin, and cell culture grade DMSO were obtained from HiMedia® (India). Annexin-V and propidium iodide antibodies were obtained from the Dead Cell Apoptosis Kit (Invitrogen, USA). The required glassware and plasticware, including consumables, were obtained from Borosil ® and Tarson Ⓡ (India), respectively. Maestro (Schrödinger) was used for the molecular dynamics/simulation studies, while open-source software such as AutoDock Tools, AutoDock Vina, PyMOL, and LigPlot + was used for the molecular docking studies. ImageJ (NIH) was used to perform image processing, and MS Excel was used for data processing and analysis. Methods Cell Culture The ovarian teratocarcinoma cell line PA1 was purchased from the Cell Repository of the National Centre for Cell Science (NCCS), Pune, India, and was grown and maintained in Dulbecco’s modified Eagle’s medium (HiMedia) supplemented with 10% fetal bovine serum (HiMedia) and 5% penicillin and streptomycin (HiMedia). Cell Cytotoxicity Assay A standard cell cytotoxicity assay was performed by seeding 10000 cells into 96-well plates. After 24 hr, the cells were treated with the desired concentrations of 1% DMSO and kept in a 5% CO2 incubator at 37°C. After 24 h of incubation, the drug was removed, and 10 µl of MTT was added to 90 µl of 1X PBS (pH 7.4) and incubated for four hrs. After 4 h, formazan crystal formation was observed under an inverted microscope, and the crystals were dissolved in 180 µl of analytical grade DMSO. Once the crystals were dissolved, the OD was measured at 570 nm using an ELISA plate reader (MULTISKAN FC, Thermo Scientific, USA). The experiment was performed in triplicate. Wound Healing Assay 10000 cells were seeded in 96-well plates, and the cells were allowed to grow in a 5% CO 2 incubator until a monolayer was observed. With a 10 µl pipette tip, the monolayer was scratched, and then the media was removed without disturbing the monolayer. The cells were then washed with sterile 1X PBS and treated with the desired drug concentrations. After treatment, the cells were kept in a 5% CO 2 incubator for treatment. Images were taken at 0, 24, 48, and 72 hrs for further analysis. The scratch area was measured via ImageJ software. Long-Term Clonogenic Assay Cells (10,000/well) were plated in 6-well plates, allowed to grow for 24 h, and treated as per the experimental plan. After 24 h of treatment, the drug-containing medium was changed to a fresh medium, and the cells were allowed to grow for two weeks. After the completion of the experiment, the surviving cells were washed with PBS and fixed with 3.6% paraformaldehyde. The surviving cells were stained with 0.05% crystal violet, and images of the cells were captured with a camera (Olympus, Tokyo, Japan). Hanging Drop Assay A total of 10000 cells per 10 µl per drop were loaded onto the bottom side of the lid of a Petri dish. Three drops were used for each concentration. In the petri dish, 5–10 ml of sterile 1x PBS was added, and the lid was gently closed by inverting and not disturbing the drops. The Petri plates were kept in a 5% CO 2 incubator for 48 hrs for spheroid formation. Once compact, the spheroids were treated with the appropriate drug concentrations. The cells were kept in a 5% CO 2 incubator. Images were taken at 0 h, 24 h, 48 h, and 73 h of spheroid formation. The spheroid area was calculated via ImageJ software. DNA fragmentation 10 6 cells were treated with the desired drug concentrations for 24 hrs. Media and trypsin-treated cells were collected and centrifuged at 2000 rpm for 5 min at room temperature. DNA was isolated by lysing the cells in 0.5 ml of detergent buffer containing 10 mM Tris (pH 7.4), 5 mM EDTA, and 0.2% Triton. The cells were vortexed and incubated on ice for 30 min. Further centrifugation at 12000 rpm for 30 min was performed, and the supernatants were divided into two 250 µl aliquots. Then, 50 µl of ice-cold 5 M NaCl was added to each aliquot, and the mixture was vortexed. Precipitation of DNA was performed by adding 600 µl of ethanol and 150 µl of 3 M sodium acetate, pH 5.2, followed by mixing by pipetting up and down. The tubes were incubated at -80°C for 1 h. The samples were centrifuged at 10000 rpm for 20 min, and the DNA extracts were pooled together by redissolving the pellets in 400 µl of extraction buffer (10 mM Tris and 5 mM EDTA). DNA was extracted with phenol/chloroform/isoamyl alcohol (25:24:1) and precipitated with ethanol. The pellet was air-dried and resuspended in 20 µl of Tris-acetate-EDTA buffer. DNA was quantified via a UV spectrometer at 260 nm and then visualized via 1.2% agarose gel electrophoresis followed by gel docking. Apoptosis An Annexin V-PI staining assay was performed using an Attune NxT flow cytometer (Thermo Fisher Scientific). The procedure was followed according to the protocol provided with the V13245 dead cell apoptosis kit (Invitrogen). A total of 10 6 cells were treated for 24 hours and harvested from the media by trypsinization. The cells were centrifuged at 2000 rpm for 5 min, and the pellets were washed twice with 1X PBS. Then, 100 µl of 1X Annexin Binding Buffer with 1 µl of Annexin V and 1 µl of PI were added to the pellet. After the cells were incubated for 30–45 min, they were analyzed using a flow cytometer. Cell cycle assay 2 × 10 5 cells per well were plated in six-well plates and allowed to attach. After the desired combination treatment for 24 hr, the cells were collected, fixed in ice-cold 70% ethanol overnight, and stored at 20°C. The ethanol-suspended cells were then centrifuged at 2000 rpm for 5 min and washed twice in 1X PBS to remove residual ethanol. The pellets were suspended in 0.5 ml of PI/RNase A reagent and incubated at 37°C for 30 min. Cell cycle profiles were obtained using an Attune NxT flow cytometer (Thermo Fisher Scientific). The data were analyzed with Attune software. Network Analysis Genes encoding proteins targeted for DHA, EPA, and doxorubicin were mined from the DrugBank ( www.drugbank.com ), and a list of genes highly mutated in ovarian cancer was obtained from the TCGA Database on the GDC Data Portal, National Cancer Institute ( www.portal.gdc.cancer.gov ). Common interacting genes obtained from the Venn diagram were entered into the String Database ( www.string-db.org ). The obtained network was then visualized in Cytoscape. Using the CytoHubba extension in Cytoscape, the top 10 hub genes were then ranked by the MCC scoring matrix. Molecular Docking Autodock Vina (The Scripps Research Institute) software was used for molecular docking experiments. First, ligand and protein structures in SDF and PDB formats were downloaded. The ligands doxorubicin (CID: 31703), docosahexaenoic acid (CID: 445580), and eicosapentaenoic acid (CID: 446284) were obtained from the PubChem NCBI database, and the protein crystal structure topoisomerase II A (PDB ID: 1ZXM) was obtained from the Protein Database (PDB). AutoDockTools (version 1.5.7) was used to prepare the proteins and ligands. Docking investigations using AutoDock Vina were carried out on an existing ligand target site. PyMOL (version 2.4.1, Schrodinger LLC) and Maestro were used to study molecular visualization and interactions. Molecular Simulation The Desmond Molecular Dynamic System (D.E. Shaw Research, New York, NY, 2017) was used to perform 100 ns of molecular dynamics (MD) and simulation to investigate the stability of the docked complexes and the interaction of TOP2A with the ligands. The complex system was solvated using the SPC solvent system in a 10 Å orthorhombic box with a periodic boundary condition (PBC) box, and the complex system was neutralized by adding counterions using Desmond's System Setup panel. The structural alterations of TOP2A caused by ligand binding were measured in terms of the root mean square deviation (RMSD) and compared to the docked structure of the relevant complex. In addition, the amino acid fluctuations during the 100 ns MD simulation were computed and displayed as an RMSF (root mean square fluctuation) plot. Statistical analysis The statistical analysis was performed using MS Excel via one-way ANOVA. The experiments were repeated in triplicate. The standard deviation represents how spread out the values are in a dataset. This gives us an idea of how closely the observations are clustered around the mean. To calculate the mean of a dataset in Excel, we used the AVERAGE (3 independent readings) function. To calculate the standard deviation of a dataset, we used = STDEV. S (3 independent readings) function. The standard deviation of triplicate values was used for the calculations. p < 0.05 was considered to indicate statistical significance. Results Cell Cytotoxicity Assay This study examined the effects of n-3 PUFAs on the cytotoxicity of doxorubicin in the ovarian teratocarcinoma cell line PA-1. An MTT assay was performed to determine the nontoxic concentrations of DHA and EPA. Concentrations ranging from 1 µM to 200 µM were tested, and it was found that the nontoxic concentration of DHA was 20 µM, while that of EPA was 40 µM. After screening at concentrations ranging from 0.1 µM to 10 µM, doxorubicin was found to have an IC 50 of 0.5 µM. To evaluate the combined toxicity, the cells were treated with nontoxic concentrations of 20 µM DHA with 0.5 µM doxorubicin and 40 µM EPA with 0.5 µM doxorubicin. Figure 1A shows that the percentage of viable cells significantly decreased after treatment with the combination of PUFAs and doxorubicin. Compared with DOXO alone, the combination of DHA + DOXO decreased cell viability by 10–15% (p < 0.05), while the combination of EPA + DOXO decreased cell viability by 25–30% (p < 0.05). Thus, the study concluded that n-3 PUFAs significantly increase doxorubicin-induced cytotoxicity in the ovarian teratocarcinoma cell line PA1. Wound Healing Assay This study aimed to evaluate the effect of polyunsaturated fatty acids (PUFAs) and their combination with doxorubicin (DOX) on cell movement by conducting a wound healing assay (also known as the scratch assay). It is a widely used in vitro technique to observe cell migration and wound closure dynamics by creating a controlled scratch in a cell monolayer mimicking a wound. This approach provides insights into cellular responses and is vital for understanding cell behavior under different conditions. After a 24-hour treatment, there was a significant decrease in cell movement. The results showed that the combination of DOXO with PUFAs led to a considerable decrease in cell movement after 24 h. In particular, the relative wound healing decreased by 20% (p < 0.05) in the group treated with the combination of DOXO and DHA and by 25% (p < 0.05) in the group treated with the combination of DOXO and EPA, as shown in Fig. 1B. The cell death caused by the combination dose increased the width of the scratch/wound, as shown in Fig. 1C, contributing to the decrease in wound healing. Long-Term Clonogenic Assay The clonogenic assay is an important technique used in cancer research to evaluate the ability of a single cell to grow into a colony. In this study, the effects of different treatment regimens on colony growth were investigated. The results showed that cells treated with a combination of DHA + DOXO and EPA + DOXO had a significantly lower number of surviving colonies than those treated with DHA, EPA, or DOX alone (Fig. 1D). These findings suggest that DHA, EPA, and DOX may promote colony survival better than the combination treatments. These results have significant implications for the development of effective cancer therapies. Hanging Drop Assay The hanging drop assay is a laboratory technique used to study how cells interact with each other and their surrounding environment by forming 3D spheroids. In this study, the cells were allowed to form spheroids for 2 days before being treated with specific concentrations of drugs. The spheroids were then monitored for the next 72 hours to determine any changes in size or structure. Compared with the control treatment, the combination treatment did not affect the size of the spheroids at 24 h. However, after 48 h, when DHA was combined with DOXO and EPA combined with DOXO, a significant reduction in the size of the spheroids was observed compared to that of the spheroids treated with DHA, EPA, or DOXO alone. These observations were consistent with the 72-h spheroid size (Fig. 2A). A significant reduction in the size of the spheroids was statistically quantified via image processing with ImageJ software (Fig. 2B). Apoptosis assay The cytotoxicity results of the study showed that the combination treatment of DHA and EPA with DOXO had a greater effect on the number of apoptotic cells than treatment with only DHA, EPA, or DOXO. The combination treatment increased the number of apoptotic cells in a dose-dependent manner. The researchers observed that there was no significant difference in apoptotic rates between cells exposed to 20 µM DHA, 40 µM EPA, and the control. However, when DHA was combined with DOXO or EPA was combined with DOXO, the rate of late apoptosis increased significantly, indicating that the combination treatment was more effective at inducing apoptosis in cancer cells. The study further showed that the late apoptotic rate was significantly greater in cells treated with the combination of DHA and DOXO, reaching up to 53.80% than in cells treated with DOXO alone. Similarly, cells treated with the combination of EPA and DOXO showed a late apoptotic rate of 38.88%, which was significantly greater than that of cells treated with DOXO alone. However, no significant difference was observed in the percentage of early apoptotic cells. In addition to investigating the apoptotic rate, this study investigated the influence of DHA/EPA on the progression of the cell cycle by performing a cell cycle analysis. The results of the analysis showed that the combination treatment of DHA and EPA with DOXO had a greater effect on the progression of the cell cycle than treatment with DOXO alone. DNA fragmentation assay Doxorubicin is a chemotherapeutic agent that acts by disrupting DNA replication and repair mechanisms. It does so by intercalating between the DNA base pairs, thereby preventing the DNA from unwinding and replicating. Additionally, it inhibits topoisomerase 2A, which is a critical enzyme involved in DNA repair. As a result, the DNA of the cells treated with DOXO became fragmented. To visualize the extent of this DNA damage, we performed a DNA fragmentation assay. Our results showed that cells treated with a combination of DHA + DOXO and EPA + DOXO exhibited more DNA damage (smear) than cells treated with DOXO alone. These findings support the hypothesis that combining DOXO with other agents (such as DHA and EPA) can enhance its cytotoxic effects. Cell cycle analysis Cell cycle analysis is a laboratory technique that evaluates the distribution of cells at different phases of the cell cycle. The DNA content was measured by staining cells with fluorescent dyes, followed by flow cytometry. This enables the identification of cell cycle stages, providing insights into cellular proliferation, growth, and potential abnormalities. In an experiment, flow cytometry was used to assess the effect of n-3 polyunsaturated fatty acids (PUFAs), specifically 20 µM DHA and 40 µM EPA, in combination with the chemotherapy drug DOXO on cell cycle progression. The researchers observed that treatment with the combination of DHA or EPA along with DOXO resulted in a significant increase in the percentage of cells in the sub-G1 phase compared to that of control cells (as shown in Fig. 5). When the cells were exposed to the indicated concentrations of 20 µM DHA, 40 µM EPA, a combination of 20 µM DHA + 0.5 µM DOXO, or 40 µM EPA + 0.5 µM DOXO for 24 hours, the percentage of the sub-G1 population significantly increased by 15–16% (p < 0.05) compared with that in the DOXO group (8%). Additionally, the number of cells in the G0/G1 phase decreased along with the increase in the number of cells in the sub-G1 phase compared to that of control cells. Thus, the combination of n-3 PUFAs (DHA and EPA) with DOXO led to a significant increase in cell apoptosis, as evidenced by the increased percentage of cells in the sub-G1 phase. Network Analysis To determine the mechanism of action of the combination of n-3 PUFAs (DHA and EPA) with DOXO in ovarian cancer cells, we performed detailed in silico network analysis to identify common genes and their interactions with three different ligands, namely, DHA, EPA, and DOXO. By analyzing the data, we were able to identify 19 genes that were common to all three ligands and were found in ovarian cancer (Fig. 6). We then generated a STRING network using StringDB and Cytoscape to map the genes and their interactions. To determine the most critical genes in the network, we used the MCC algorithm in the CytoHubba extension of Cytoscape, which revealed the top 10 hub genes (Fig. 7). We noticed that the TOP2A gene interacted with 6 of the top 10 hub genes, making it a promising protein of interest for future studies. Hence further in silico studies were performed on TOP2A. Molecular Docking Molecular modeling studies were conducted to determine the binding conformations of ligands within the TOP2A binding cavity. The ligands studied were doxorubicin and the PUFAs: DHA and EPA. The receptor atoms of TOP2A were obtained from the PDB database and were treated as rigid, while all ligands were considered flexible during the docking simulation. The binding cavity of the preexisting ligand ANA in TOP2A (PDBID: 1ZXM) was used as the binding cavity for the ligands used in this study. The docking simulation was performed in AutoDock Vina. A pool of possible ligand conformations was generated, and a set of conformational poses was computed with their respective binding affinities. The conformation with the least binding affinity for TOP2A was regarded as the best conformation. The results showed that doxorubicin had the lowest binding energy of -10 kcal/mol when it was docked with TOP2A. It interacted with the target protein through H-bonds in the best conformation pose. The binding affinity and interacting residues are provided in Table 1. The MOE tool was used to visualize the interacting amino acids, and the 3D interaction of TOP2A with doxorubicin and the PUFA-DHA and EPA complex with H-bond interacting residues is shown in Fig. 8. Molecular Dynamics Simulation Molecular dynamic simulations are commonly utilized to study and analyze the dynamic perturbations occurring in protein-ligand complex conformations. During a 100 ns simulation period, it has been observed that the potential energy tends to decrease for both receptors, indicating that the system is stabilizing. We analyzed the conformation of the receptor-ligand complex throughout the simulation period and calculated the Root-Mean-Square Deviation (RMSD) for both protein and ligand. The RMSD value helps us determine the average displacement change for a particular frame relative to a reference frame. The best docking poses of DHA, EPA, and doxorubicin obtained by molecular docking with TOP2A (PDB ID: 1ZXM) were subjected to MD simulation using Maestro software to examine the binding stability within the binding cavity of TOP2A. TOP2A was simulated for 100 ns with the lead posture of the provided ligands, and the conformational changes for the receptor-ligand interactions were obtained. We examined the RMSD and protein-ligand interactions between the supplied ligands. The RMSD graphs were generated by calculating the RMSD values for the C-α atoms of TOP2A after binding with the ligands, and the RMSD values of the ligands were recorded to determine their binding efficiency within the binding cavity of TOP2A during the 100 ns MD simulation (Fig. 9). Upon interaction with doxorubicin, TOP2A started stabilizing after 40 ns at 4.8 Å and remained stable throughout the simulation. Similarly, doxorubicin also started stabilizing after 40 ns at 4 Å and remained stable throughout the simulation (Fig. 9A). However, upon interaction with DHA, TOP2A stabilized after 60 ns at 3.6 Å A and persisted for up to 100 ns. DHA stabilized early at approximately 30 ns at 4 Å up to 100 ns (Fig. 9B). In the TOP2A-EPA complex, TOP2A stabilizes after 40 ns at 2.6 Å and lasts up to 100 ns, while EPA stabilizes after 60 ns at 10.5 Å and lasts for the entire duration (Fig. 9C). Based on the protein stabilization graphs above, we can observe fluctuations in the protein backbone. These fluctuations may be a result of the interactions between the protein and the ligands within its structure. As the protein stabilizes, different ligands come into contact with different residues within the binding cavity. For example, as shown in Fig. 10, in the case of doxorubicin, the number of ligand contacts with Glu59, Asp66, Asn92, Tyr123, Asp124, and Asn135 increased, while the number of contacts with Arg70, Ile97, Pro98, Ser121, and Thr187 decreased. Throughout the simulation, the ligand contacts the Asn63, Asn67, Val109, Ile113, Thr119, Gly133, Gly136, and Lys140 residues (Fig. 10A). On the other hand, DHA (Fig. 10B) shows strong contact with Met33, Tyr34, Ile283, Phe285, Ala290, Ser292, and Glu351, while EPA (Fig. 10C) shows strong contact with Trp34, Tyr44, Glu277, and Gln281. There are some common residues with which both EPA and DHA make contact, such as Trp34, Tyr44, Tyr246, and Gln281. However, EPA makes more contact with these residues than does DHA. Discussion Ovarian cancer has a low five-year survival rate and is the leading cause of death among gynecologic cancers[ 1 ]. Doxorubicin (DOX) is a potent chemical drug that is used to treat various types of cancer, including ovarian cancer [ 12 ]. The effectiveness of DOXO in ovarian treatment is hindered by its inherent cytotoxicity and the development of drug resistance at higher doses [ 38 ]. Hence there is a pressing need to explore novel therapeutic agents or combination therapies targeting this disease, particularly for advanced or recurrent stages. A growing body of evidence suggests that sustained intake of omega-3 fatty acids correlates with a markedly reduced risk of certain cancers [ 39 ][ 40 ]. Previous investigations have substantiated the capacity of docosahexaenoic acid (DHA) or EPA and its analogs to impede cell proliferation and tumor progression in preclinical models [ 37 ], [ 40 ], [ 41 ]. According to a recent study using systematic mendelian randomization, the intake of DHA has been shown to reduce the risk of ovarian cancer in European populations [ 42 ]. Wang and colleagues (2022) demonstrated that a diet rich in fish and marine omega-3 PUFAs is associated with improved cancer survival [ 43 ]. The current study aimed to investigate whether DHA and EPA have the potential to improve the effectiveness of DOXO therapy. The results of the study showed that the combination of DOXO and n-3 PUFAs increased the death of PA-1 cells, as demonstrated by the MTT assay. The effectiveness of the combination was further confirmed by the induction of cell cycle arrest, apoptosis, and the reduction of cancer cell clonogenicity in ovarian cancer cells. These results support previous studies done by researchers[ 37 ][ 41 ]. The distribution of cells in the cell cycle was analyzed, which showed that the combination of DOXO and n-3 PUFAs increased the number of cells in the subG1 phase and decreased the G2/M transition. The Annexin V/PI staining assays proved that the combination resulted in apoptosis in PA-1 cells, which was further confirmed by the DNA fragmentation assay that showed a higher level of DNA degradation in cells treated with the combination. We also investigated the effect of DHA/EPA, omega-3 fatty acids, on ovarian cancer cell migration and found that it significantly inhibited migration. This suggests that DHA/EPA has the potential to enhance the anti-metastatic effects of DOXO. This is consistent with previous research by Zheng et al. (2014), which found that DHA inhibited the migration of endometrial cancer cells by suppressing mTOR1/2 signaling [ 44 ]. After confirming the beneficial effect of n-3 PUFAs in vitro, we conducted in silico studies to determine how they work. Through network analysis, we identified nineteen genes that are common to ovarian cancer, DHA, EPA, and doxorubicin. We used StringDB and Cytoscape to construct a STRING network and identified the top 10 hub genes, which included CCND1, MYC, CTNNB1, CASP3, CASP8, CDH1, NOTCH1, PI3CA, CDK4, and CDK6. Among these genes, TOP2A strongly interacts with six of the top 10 hub genes, including CCND1, MYC, CTNNB1, PI3CA, CDK4, and CDK6. These genes are important in various cellular processes and have been implicated in different types of cancers, including ovarian cancer. Dysregulation of these genes can contribute to tumor development and progression [ 41 ]. Our study on molecular docking has revealed that n-3 PUFAs act similarly to DNA intercalators and TOP2A inhibitors, just like the reference drug DOXO. A recent study based on molecular docking studies with TOP2A as the target protein supports this finding. The study suggests that DHA and EPA may have a similar mechanism of action with DOXO, as DNA intercalators and TOP2A inhibitors [ 45 ]. Our molecular dynamics study revealed that the bond between n-3 PUFAs and TOP2A is equally stable as that of DOXO and TOP2A. This was determined by analyzing the structure of the best-docked hits, fluctuations during interactions, and overall structural stability through the computation of the RMSD and protein-ligand contacts. These findings are consistent with recent studies that suggest TOP2A is a potential target in ovarian cancer. Additionally, TOP2A plays a role in regulating signaling via the AKT/mTOR pathway, which in turn promotes the proliferation of ovarian cancer cells[ 46 ][ 47 ]. According to a study conducted by Bai and colleagues, elevated levels of TOP2A mRNA were found in both advanced-stage diseases and high-grade ovarian malignancies. The study also discovered that TOP2A overexpression was significantly associated with lower overall survival rates in all patients with epithelial ovarian carcinoma (EOC) and serous patients[ 48 ]. Our study has revealed that the combination of n-3 PUFAs with doxorubicin can significantly enhance the drug's antitumor activity. This is primarily attributed to the interference of n-3 PUFAs with the PI3K/AKT/mTOR pathway and the inhibition of topoisomerase II, which can make doxorubicin work more effectively. Furthermore, our research has shown that n-3 PUFAs act as TOP2A receptor antagonists, which can potentially lower the therapeutic dose of doxorubicin required to achieve the desired results. As a result, this approach can reduce the toxic side effects associated with high doses of doxorubicin, resensitize cancer cells to the drug, and suppress drug resistance. In conclusion, our findings suggest that the combination of doxorubicin and n-3 PUFAs can be a promising strategy to combat cancer. These findings suggest that N-3 PUFAs combined with DOXO could be a novel and potentially effective combination for the treatment of ovarian cancer. We recommend conducting more in vivo research on this combination. Conclusion Our study has found that combining doxorubicin with omega-3 polyunsaturated fatty acids (specifically DHA and EPA) has significant anticancer effects through various mechanisms, including TOP2A inhibition and DNA intercalation. This combination therapy can reduce the necessary therapeutic dose of DOX, reducing toxic side effects and improving the quality of life of ovarian cancer patients. Further research is needed to confirm the safety and efficacy of this innovative treatment approach through in vivo studies. Declarations Acknowledgment The authors would like to thank the Director of the MIT School of Bioengineering Sciences & Research, MIT ADT University, for infrastructure support and funding. We also thank the Atal Incubation Centre, MIT ADT University, for providing access to the flow cytometer. Author contributions PG designed the study, conducted the investigation and data analysis, and wrote the original draft. SH contributed to the methodology of Figs. 7, 8, 9 and 10. KRN and VS contributed to the conceptualization, project administration, funding acquisition, and writing—review, and editing of the manuscript. Funding MIT School of Bioengineering Sciences & Research, MIT ADT University, Pune, India. Data availability The data are available upon request from the authors. Competing interests The authors declare no financial or nonfinancial competing interests. Ethics statement This is not applicable as no human or animal involved in the study Declaration of generative AI and AI-assisted technologies in the writing process During the preparation of this work the author(s) used Grammerly in order to rectify grammatical mistakes and improve the quality of manuscript. 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Additional Declarations No competing interests reported. Supplementary Files Table1.xlsx Table 1 : The best-docked versions of TOP2A with DOXO, DHA, and EPA are shown together with the residues that interact with them. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4490207","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":312685603,"identity":"e23d867d-4e78-42a8-b8f3-ae0c45ba8db4","order_by":0,"name":"Pradnya Gurav","email":"","orcid":"","institution":"MIT Arts, Design and Technology University","correspondingAuthor":false,"prefix":"","firstName":"Pradnya","middleName":"","lastName":"Gurav","suffix":""},{"id":312685604,"identity":"343cf72d-764c-4705-898d-566e215909e1","order_by":1,"name":"Shubham Hajare","email":"","orcid":"","institution":"MIT Arts, Design and Technology University","correspondingAuthor":false,"prefix":"","firstName":"Shubham","middleName":"","lastName":"Hajare","suffix":""},{"id":312685605,"identity":"5ee0a218-8345-4112-9b7a-e3dd9dfafb76","order_by":2,"name":"Venkateswara Swamy","email":"","orcid":"","institution":"MIT Arts, Design and Technology University","correspondingAuthor":false,"prefix":"","firstName":"Venkateswara","middleName":"","lastName":"Swamy","suffix":""},{"id":312685606,"identity":"12af4eb4-4994-4111-8296-a1089b4b70ce","order_by":3,"name":"Kedar R.N.","email":"data:image/png;base64,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","orcid":"","institution":"MIT Arts, Design and Technology University","correspondingAuthor":true,"prefix":"","firstName":"Kedar","middleName":"","lastName":"R.N.","suffix":""}],"badges":[],"createdAt":"2024-05-28 10:36:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4490207/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4490207/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58087437,"identity":"a3c95b88-89d5-44a9-a39f-43b81f8095b8","added_by":"auto","created_at":"2024-06-11 03:11:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":575871,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDHA and EPA enhance the effect of DOXO in ovarian cancer cells. \u003c/strong\u003e(A and B)PA-1 cells were treated with the indicated concentrations of 20 µMDHA, 4 µMEPA, and a combination of 20 µMDHA+ 0.5 µM doxorubicin and 40 µMEPA +0.5 µM DOXO for24 h,and cell viability was measured by the MTT assay. (C) Migration was assessed by a wound healing assay after treatment for 24 h.(D) PA-1 cells were treated with the indicated concentrations of DOXO together with DHA and EPA for 24 h, and the cells were subjected to a long-term clonogenic assay using crystal violet. All the bar graphs represent the mean ±SD of an experiment performed in triplicate (*P ≤ 0.05, **P ≤ 0.001, ***P ≤ 0.0001).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/bfd5122af94c32bec47abcd3.png"},{"id":58087438,"identity":"b947e669-7f15-468b-9b05-3b9d99bb8180","added_by":"auto","created_at":"2024-06-11 03:11:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":574754,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePA-1 hanging-drop culture- DHA and EPA with DOXO results in significantly smaller and more compact aggregates in ovarian cancer cells. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Images of PA-1 cells treated with the indicated concentrations of 20 µM DHA, 4 µM EPA, the combination of 20 µM DHA, 0.5 µM doxorubicin, and 40 µM EPA +0.5 µM DOXO in hanging drop culture for 24 h, 48 h and 71 h. Images were captured using a camera (Olympus, Tokyo, Japan). (\u003cstrong\u003eB\u003c/strong\u003e) Quantification was performed via ImageJ software. The asterisk represents a statistically significant difference in aggregate size (P\u0026lt;0.0001) when treated with the indicated concentrations of DOXO together with DHA and EPA for 24 h, 48 h, and 72 h.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/ed46ac1ab851bcdce3b72795.png"},{"id":58087648,"identity":"1fa00610-12e0-46cd-a837-d9fc9aa78a72","added_by":"auto","created_at":"2024-06-11 03:19:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":260079,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDHA and EPA combined with DOXO induced more apoptosis in ovarian cancer cells.\u003c/strong\u003e A representative dot plot showing that PA-1 cells were treated with the indicated concentrations of DOXO together with DHA and EPA for 24 h, and apoptotic cells were analyzed by Annexin V-FITC staining using flow cytometry. The data presented arerepresentative of three separate experiments.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/a4cbdd31f29abf9491be08b0.png"},{"id":58088149,"identity":"de45b1d2-8b33-4b4b-a085-527d0600eee6","added_by":"auto","created_at":"2024-06-11 03:27:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":210210,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eDetection of apoptotic DNA fragmentation in PA1 cells.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePA-1 cells were treated with the indicated concentrationsof DOXO together with DHA and EPA for 24 h. Apoptosis can be visualized as a ladder pattern due to DNA cleavage caused by the combination treatment by standard agarose gel electrophoresis.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/9edc20cf6f5bcdb72fe9fa1c.png"},{"id":58087647,"identity":"57dbf54e-8b9b-4b02-9306-66d53ac03b47","added_by":"auto","created_at":"2024-06-11 03:19:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":39612,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFlow cytometry analysis to determine the proportion of PA-1 cells in different phases of the cell cycle. After PA-1 cells\u003c/strong\u003e\u003c/em\u003e\u003cem\u003ewere treated\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003ewith the indicated concentrations of DOXO together with DHA and EPA for 24 h, propidium iodide (PI) staining was performed, and the results were analyzed by flow cytometry. Bar diagram showing the cell distribution in the subG1, G0/G1, S, and G2/M phases for PA-1 cells treated with vehicle control and combination treatment. The data presented are representative of three separate experiments.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/f28bb46acf83632a9bbb5db0.png"},{"id":58088569,"identity":"1a55b07d-866f-4fdc-8bfa-3d83527642ac","added_by":"auto","created_at":"2024-06-11 03:35:58","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":184928,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eVenn diagram of genes common to ovarian cancer, DOXO, DHA, and EPA.\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eA Venn diagram showing genes common to DHA, EPA, and doxorubicin that are found in ovarian cancer.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/b6bd74b340c577563179908b.png"},{"id":58087652,"identity":"80c741e2-8f30-4980-9b81-f8395739a3b4","added_by":"auto","created_at":"2024-06-11 03:19:58","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":248656,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eVisual representation of the protein–protein interaction (PPI) network of the overlapping DEGs and the hub genes. \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eThe top 19 genes thatare common to DHA, EPA, and doxorubicin and are found in ovarian cancerwere subjected to STRINGnetwork analysis using StringDB and Cytoscape. The top 10 hub genes were identified using the MCC algorithm in the CytoHubba extension in Cytoscape, where a higher score is represented in red and a lower score is represented in yellow.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/8117a3eb820c5c6a0e41ba99.png"},{"id":58087444,"identity":"f9583ea1-a6db-4b6f-9792-7154dbd81927","added_by":"auto","created_at":"2024-06-11 03:11:58","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":585488,"visible":true,"origin":"","legend":"\u003cp\u003eA schematic model of the interactions of TOP2A with (A) DOXO, (B) DHA, and (C) EPA showing stable binding within the active site of the TOP2A enzyme.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/2fcf8729875cf59442f7377b.png"},{"id":58087446,"identity":"fbfe234c-36fd-421a-a145-cf91ae888d31","added_by":"auto","created_at":"2024-06-11 03:11:58","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":255799,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eInteraction plot of the TOP2A protein with doxorubicin, DHA, and EPA. The interaction plot\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e (or contacts) shows the nature of the amino acid residues that are part of the catalytic site of TOP2A. The residual interactions of the active site with doxorubicin, DHA, and EPA are shown in different color trajectories.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/5839683f906dc4fd0bcfedff.png"},{"id":58087448,"identity":"9cff3eca-c23c-47f1-b753-52d3610f1c0c","added_by":"auto","created_at":"2024-06-11 03:11:58","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":664228,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eInteraction plots of the proteinsTOP2A and doxorubicin (A), DHA (B), and EPA (C)\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure10.png","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/8c8cbccfa03520eecaa2a5f8.png"},{"id":58600348,"identity":"bfd28454-3ebb-4dfc-a9af-e1f1b21aeae7","added_by":"auto","created_at":"2024-06-18 17:29:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5102026,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/689ff3e2-0931-4f00-b25d-2768de9f5ce1.pdf"},{"id":58088568,"identity":"b76138b1-ee4f-434d-9331-e3a666258dc1","added_by":"auto","created_at":"2024-06-11 03:35:58","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8962,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e: The best-docked versions of TOP2A with DOXO, DHA, and EPA are shown together with the residues that interact with them.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4490207/v1/a181fbafb26a429a6aed4539.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Augmenting Chemotherapy Response In Ovarian Cancer: Omega-3 Polyunsaturated Fatty Acids Target TOP2A","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOvarian cancer ranks as the seventh leading cause of female mortality globally and is the third most common gynecological cancer in India [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A staggering 314,000 new ovarian cancer cases and 207,000 related deaths were reported in 2020 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Due to its insidious symptoms at early stages, ovarian cancer often remains undetected until later stages [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Despite recent strides in cancer therapy, conventional cytotoxic treatments such as chemotherapy and radiotherapy have several drawbacks, leading to treatment failure, cancer relapse, and unsatisfactory long-term clinical outcomes[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese drawbacks predominantly stem from two major issues: (1) Conventional treatments fail to eradicate tumor-initiating cells (TICs), a population of self-renewing and drug-resistant cancer cells, or cause the development of drug resistance in tumor cells [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. (2) The use of traditional medicines can result in both local and systemic toxicity due to the widespread death of normal cells [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Most oncologists believe that targeting a single molecular component may not be adequate to halt this process since cancer cell survival is governed by intricate molecular interactions between growth and death signals [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Hence, there is an urgent need to combine traditional treatments with compounds that can enhance the effectiveness of chemotherapy without harming healthy cells.\u003c/p\u003e \u003cp\u003eDoxorubicin (DOXO) is one of the most effective antineoplastic drugs and is used either alone or in combination with other therapies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e][\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. It inhibits topoisomerase II by DNA intercalation and the formation of free radicals, thereby causing cancer cell death [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOmega-3 polyunsaturated fatty acids (n-3 PUFAs) are essential fatty acids that are integral to the regular development and growth of various human tissues [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e][\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. They incorporate into the cell membrane and, by altering the membrane composition and function, modulate intracellular signaling in different types of cancers. Their metabolites regulate the expression of genes involved in key cellular processes by binding to various transcription factors [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e][\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e][\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. These properties position PUFAs as potential modulators in various cancer cellular processes.\u003c/p\u003e \u003cp\u003eNumerous studies have demonstrated that n-3 PUFAs, specifically eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), reduce tumor growth by triggering cancer cell apoptosis, either alone [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e][\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] or in combination with established anticancer therapy [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e][\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Although various studies have reported the synergistic effects of n-3 PUFAs with chemotherapy drugs in chronic myeloid leukemia (CML), breast, prostate, lung, gastric, and ovarian cancers[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e][\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e][\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e][\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e][\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], there are limited in-depth reports on the synergistic effects of PUFAs and the chemotherapy drug DOXO[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e][\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e][\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Diets rich in n-3 PUFAs, found in Mediterranean and Japanese diets, may help reduce the risk of cancer[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Studies conducted on zebrafish models indicate that DHA reduces the proliferation and invasion of ovarian cancer by modulating the NF-κB, mTOR, and MAPK pathways[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e][\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eN-3 PUFAs, like DHA and EPA, enhance chemotherapy effectiveness by aiding drug absorption into cancer cells' lipid bilayers and inhibiting survival pathways [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. DHA enhances the efficacy of anticancer drugs like cisplatin and doxorubicin by increasing their cytotoxicity in various cancer cells, including those resistant to multiple drugs, while also shielding non-target organs like the gastrointestinal tract from damage and improving tumor response to irinotecan therapy in specific cases[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e][\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In the previous study, we have shown that n-3 polyunsaturated fatty acids (PUFAs) can enhance the effectiveness of doxorubicin in treating breast cancer[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, the exact mechanism of synergistic action of n-3 PUFAs with Doxorubicin has not been explored yet.\u003c/p\u003e \u003cp\u003eComputer-aided drug discovery (CADD) techniques are extensively employed in modern drug development, with TOP1 and TOP2A identified as biomarkers for poor survival in epithelial ovarian carcinoma [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e][\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. DHA and EPA, structurally similar to DOXO, demonstrate similar mechanisms of action as DNA intercalators and TOP2A inhibitors, synergistically enhancing chemotherapy efficacy against ovarian cancer [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe objective of this study is to assess the influence of n-3 PUFAs, such as DHA and EPA, both separately and in conjunction with DOXO, on ovarian cancer cells. The aim is to examine the impact of this combination on anti-proliferation, apoptosis, and anti-metastasis. Furthermore, in silico experiments were conducted to elucidate the mode of action of PUFAs in tandem with DOXO. The outcomes of this investigation carry significant ramifications for furthering our comprehension of the possible therapeutic benefits of these substances in treating ovarian cancer.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cp\u003eDocosahexaenoic acid was purchased from Sigma‒Aldrich (Sigma Aldrich, MO, USA). Eicosapentaenoic acid was purchased from TCI (Tokyo Chemical Industry India Pvt. Ltd; Tokyo Japan). Doxorubicin, DMEM, penicillin and streptomycin, trypsin, and cell culture grade DMSO were obtained from HiMedia\u0026reg; (India). Annexin-V and propidium iodide antibodies were obtained from the Dead Cell Apoptosis Kit (Invitrogen, USA). The required glassware and plasticware, including consumables, were obtained from Borosil\u003csup\u003e\u0026reg;\u003c/sup\u003e and Tarson\u003csup\u003eⓇ\u003c/sup\u003e (India), respectively. Maestro (Schr\u0026ouml;dinger) was used for the molecular dynamics/simulation studies, while open-source software such as AutoDock Tools, AutoDock Vina, PyMOL, and LigPlot\u0026thinsp;+\u0026thinsp;was used for the molecular docking studies. ImageJ (NIH) was used to perform image processing, and MS Excel was used for data processing and analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMethods\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eCell Culture\u003c/h2\u003e \u003cp\u003eThe ovarian teratocarcinoma cell line PA1 was purchased from the Cell Repository of the National Centre for Cell Science (NCCS), Pune, India, and was grown and maintained in Dulbecco\u0026rsquo;s modified Eagle\u0026rsquo;s medium (HiMedia) supplemented with 10% fetal bovine serum (HiMedia) and 5% penicillin and streptomycin (HiMedia).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eCell Cytotoxicity Assay\u003c/h2\u003e \u003cp\u003eA standard cell cytotoxicity assay was performed by seeding 10000 cells into 96-well plates. After 24 hr, the cells were treated with the desired concentrations of 1% DMSO and kept in a 5% CO2 incubator at 37\u0026deg;C. After 24 h of incubation, the drug was removed, and 10 \u0026micro;l of MTT was added to 90 \u0026micro;l of 1X PBS (pH 7.4) and incubated for four hrs. After 4 h, formazan crystal formation was observed under an inverted microscope, and the crystals were dissolved in 180 \u0026micro;l of analytical grade DMSO. Once the crystals were dissolved, the OD was measured at 570 nm using an ELISA plate reader (MULTISKAN FC, Thermo Scientific, USA). The experiment was performed in triplicate.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eWound Healing Assay\u003c/h2\u003e \u003cp\u003e10000 cells were seeded in 96-well plates, and the cells were allowed to grow in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator until a monolayer was observed. With a 10 \u0026micro;l pipette tip, the monolayer was scratched, and then the media was removed without disturbing the monolayer. The cells were then washed with sterile 1X PBS and treated with the desired drug concentrations. After treatment, the cells were kept in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator for treatment. Images were taken at 0, 24, 48, and 72 hrs for further analysis. The scratch area was measured via ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLong-Term Clonogenic Assay\u003c/h2\u003e \u003cp\u003eCells (10,000/well) were plated in 6-well plates, allowed to grow for 24 h, and treated as per the experimental plan. After 24 h of treatment, the drug-containing medium was changed to a fresh medium, and the cells were allowed to grow for two weeks. After the completion of the experiment, the surviving cells were washed with PBS and fixed with 3.6% paraformaldehyde. The surviving cells were stained with 0.05% crystal violet, and images of the cells were captured with a camera (Olympus, Tokyo, Japan).\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eHanging Drop Assay\u003c/h2\u003e \u003cp\u003e \u003cb\u003eA total of\u003c/b\u003e 10000 cells per 10 \u0026micro;l per drop were loaded onto the bottom side of the lid of a Petri dish. Three drops were used for each concentration. In the petri dish, 5\u0026ndash;10 ml of sterile 1x PBS was added, and the lid was gently closed by inverting and not disturbing the drops. The Petri plates were kept in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator for 48 hrs for spheroid formation. Once compact, the spheroids were treated with the appropriate drug concentrations. The cells were kept in a 5% CO\u003csub\u003e2\u003c/sub\u003e incubator. Images were taken at 0 h, 24 h, 48 h, and 73 h of spheroid formation. The spheroid area was calculated via ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eDNA fragmentation\u003c/h2\u003e \u003cp\u003e10\u003csup\u003e6\u003c/sup\u003e cells were treated with the desired drug concentrations for 24 hrs. Media and trypsin-treated cells were collected and centrifuged at 2000 rpm for 5 min at room temperature. DNA was isolated by lysing the cells in 0.5 ml of detergent buffer containing 10 mM Tris (pH 7.4), 5 mM EDTA, and 0.2% Triton. The cells were vortexed and incubated on ice for 30 min. Further centrifugation at 12000 rpm for 30 min was performed, and the supernatants were divided into two 250 \u0026micro;l aliquots. Then, 50 \u0026micro;l of ice-cold 5 M NaCl was added to each aliquot, and the mixture was vortexed. Precipitation of DNA was performed by adding 600 \u0026micro;l of ethanol and 150 \u0026micro;l of 3 M sodium acetate, pH 5.2, followed by mixing by pipetting up and down. The tubes were incubated at -80\u0026deg;C for 1 h. The samples were centrifuged at 10000 rpm for 20 min, and the DNA extracts were pooled together by redissolving the pellets in 400 \u0026micro;l of extraction buffer (10 mM Tris and 5 mM EDTA).\u003c/p\u003e \u003cp\u003eDNA was extracted with phenol/chloroform/isoamyl alcohol (25:24:1) and precipitated with ethanol. The pellet was air-dried and resuspended in 20 \u0026micro;l of Tris-acetate-EDTA buffer. DNA was quantified via a UV spectrometer at 260 nm and then visualized via 1.2% agarose gel electrophoresis followed by gel docking.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eApoptosis\u003c/h2\u003e \u003cp\u003eAn Annexin V-PI staining assay was performed using an Attune NxT flow cytometer (Thermo Fisher Scientific). The procedure was followed according to the protocol provided with the V13245 dead cell apoptosis kit (Invitrogen). A total of 10\u003csup\u003e6\u003c/sup\u003e cells were treated for 24 hours and harvested from the media by trypsinization. The cells were centrifuged at 2000 rpm for 5 min, and the pellets were washed twice with 1X PBS. Then, 100 \u0026micro;l of 1X Annexin Binding Buffer with 1 \u0026micro;l of Annexin V and 1 \u0026micro;l of PI were added to the pellet. After the cells were incubated for 30\u0026ndash;45 min, they were analyzed using a flow cytometer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCell cycle assay\u003c/h2\u003e \u003cp\u003e2 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells per well were plated in six-well plates and allowed to attach. After the desired combination treatment for 24 hr, the cells were collected, fixed in ice-cold 70% ethanol overnight, and stored at 20\u0026deg;C. The ethanol-suspended cells were then centrifuged at 2000 rpm for 5 min and washed twice in 1X PBS to remove residual ethanol. The pellets were suspended in 0.5 ml of PI/RNase A reagent and incubated at 37\u0026deg;C for 30 min. Cell cycle profiles were obtained using an Attune NxT flow cytometer (Thermo Fisher Scientific). The data were analyzed with Attune software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eNetwork Analysis\u003c/h2\u003e \u003cp\u003eGenes encoding proteins targeted for DHA, EPA, and doxorubicin were mined from \u003cb\u003ethe DrugBank\u003c/b\u003e (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.drugbank.com\" target=\"_blank\"\u003ewww.drugbank.com\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.drugbank.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and a list of genes highly mutated in ovarian cancer was obtained from the TCGA Database on the GDC Data Portal, National Cancer Institute (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.drugbank.com\" target=\"_blank\"\u003ewww.portal.gdc.cancer.gov\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.portal.gdc.cancer.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCommon interacting genes obtained from the Venn diagram were entered into the String Database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.drugbank.com\" target=\"_blank\"\u003ewww.string-db.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.string-db.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The obtained network was then visualized in Cytoscape. Using the CytoHubba extension in Cytoscape, the top 10 hub genes were then ranked by the MCC scoring matrix.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMolecular Docking\u003c/h2\u003e \u003cp\u003eAutodock Vina (The Scripps Research Institute) software was used for molecular docking experiments. First, ligand and protein structures in SDF and PDB formats were downloaded. The ligands doxorubicin (CID: 31703), docosahexaenoic acid (CID: 445580), and eicosapentaenoic acid (CID: 446284) were obtained from the PubChem NCBI database, and the protein crystal structure topoisomerase II A (PDB ID: 1ZXM) was obtained from the Protein Database (PDB). AutoDockTools (version 1.5.7) was used to prepare the proteins and ligands. Docking investigations using AutoDock Vina were carried out on an existing ligand target site. PyMOL (version 2.4.1, Schrodinger LLC) and Maestro were used to study molecular visualization and interactions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMolecular Simulation\u003c/h2\u003e \u003cp\u003eThe \u003cb\u003eDesmond Molecular Dynamic System (D.E. Shaw Research, New York, NY, 2017)\u003c/b\u003e was used to perform 100 ns of molecular dynamics (MD) and simulation to investigate the stability of the docked complexes and the interaction of TOP2A with the ligands. The complex system was solvated using the SPC solvent system in a 10 \u0026Aring; orthorhombic box with a periodic boundary condition (PBC) box, and the complex system was neutralized by adding counterions using Desmond's System Setup panel. The structural alterations of TOP2A caused by ligand binding were measured in terms of the root mean square deviation (RMSD) and compared to the docked structure of the relevant complex. In addition, the amino acid fluctuations during the 100 ns MD simulation were computed and displayed as an RMSF (root mean square fluctuation) plot.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe statistical analysis was performed using MS Excel via one-way ANOVA. The experiments were repeated in triplicate. The standard deviation represents how spread out the values are in a dataset. This gives us an idea of how closely the observations are clustered around the mean. To calculate the mean of a dataset in Excel, we used the AVERAGE (3 independent readings) function. To calculate the standard deviation of a dataset, we used\u0026thinsp;=\u0026thinsp;STDEV. S (3 independent readings) function. The standard deviation of triplicate values was used for the calculations. p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n\u003ch2\u003eCell Cytotoxicity Assay\u003c/h2\u003e\n\u003cp\u003eThis study examined the effects of n-3 PUFAs on the cytotoxicity of doxorubicin in the ovarian teratocarcinoma cell line PA-1. An MTT assay was performed to determine the nontoxic concentrations of DHA and EPA. Concentrations ranging from 1 \u0026micro;M to 200 \u0026micro;M were tested, and it was found that the nontoxic concentration of DHA was 20 \u0026micro;M, while that of EPA was 40 \u0026micro;M. After screening at concentrations ranging from 0.1 \u0026micro;M to 10 \u0026micro;M, doxorubicin was found to have an IC\u003csub\u003e50\u003c/sub\u003e of 0.5 \u0026micro;M.\u003c/p\u003e\n\u003cp\u003eTo evaluate the combined toxicity, the cells were treated with nontoxic concentrations of 20 \u0026micro;M DHA with 0.5 \u0026micro;M doxorubicin and 40 \u0026micro;M EPA with 0.5 \u0026micro;M doxorubicin. Figure\u0026nbsp;1A shows that the percentage of viable cells significantly decreased after treatment with the combination of PUFAs and doxorubicin. Compared with DOXO alone, the combination of DHA\u0026thinsp;+\u0026thinsp;DOXO decreased cell viability by 10\u0026ndash;15% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while the combination of EPA\u0026thinsp;+\u0026thinsp;DOXO decreased cell viability by 25\u0026ndash;30% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Thus, the study concluded that n-3 PUFAs significantly increase doxorubicin-induced cytotoxicity in the ovarian teratocarcinoma cell line PA1.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n\u003ch2\u003eWound Healing Assay\u003c/h2\u003e\n\u003cp\u003eThis study aimed to evaluate the effect of polyunsaturated fatty acids (PUFAs) and their combination with doxorubicin (DOX) on cell movement by conducting a wound healing assay (also known as the scratch assay). It is a widely used in vitro technique to observe cell migration and wound closure dynamics by creating a controlled scratch in a cell monolayer mimicking a wound. This approach provides insights into cellular responses and is vital for understanding cell behavior under different conditions.\u003c/p\u003e\n\u003cp\u003eAfter a 24-hour treatment, there was a significant decrease in cell movement. The results showed that the combination of DOXO with PUFAs led to a considerable decrease in cell movement after 24 h. In particular, the relative wound healing decreased by 20% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the group treated with the combination of DOXO and DHA and by 25% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the group treated with the combination of DOXO and EPA, as shown in Fig.\u0026nbsp;1B. The cell death caused by the combination dose increased the width of the scratch/wound, as shown in Fig.\u0026nbsp;1C, contributing to the decrease in wound healing.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n\u003ch2\u003eLong-Term Clonogenic Assay\u003c/h2\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003eThe clonogenic assay is an important technique used in cancer research to evaluate the ability of a single cell to grow into a colony. In this study, the effects of different treatment regimens on colony growth were investigated. The results showed that cells treated with a combination of DHA\u0026thinsp;+\u0026thinsp;DOXO and EPA\u0026thinsp;+\u0026thinsp;DOXO had a significantly lower number of surviving colonies than those treated with DHA, EPA, or DOX alone (Fig.\u0026nbsp;1D). These findings suggest that DHA, EPA, and DOX may promote colony survival better than the combination treatments. These results have significant implications for the development of effective cancer therapies.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n\u003ch2\u003eHanging Drop Assay\u003c/h2\u003e\n\u003cp\u003eThe hanging drop assay is a laboratory technique used to study how cells interact with each other and their surrounding environment by forming 3D spheroids. In this study, the cells were allowed to form spheroids for 2 days before being treated with specific concentrations of drugs. The spheroids were then monitored for the next 72 hours to determine any changes in size or structure.\u003c/p\u003e\n\u003cp\u003eCompared with the control treatment, the combination treatment did not affect the size of the spheroids at 24 h. However, after 48 h, when DHA was combined with DOXO and EPA combined with DOXO, a significant reduction in the size of the spheroids was observed compared to that of the spheroids treated with DHA, EPA, or DOXO alone. These observations were consistent with the 72-h spheroid size (Fig.\u0026nbsp;2A). A significant reduction in the size of the spheroids was statistically quantified via image processing with ImageJ software (Fig.\u0026nbsp;2B).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\n\u003ch2\u003eApoptosis assay\u003c/h2\u003e\n\u003cp\u003eThe cytotoxicity results of the study showed that the combination treatment of DHA and EPA with DOXO had a greater effect on the number of apoptotic cells than treatment with only DHA, EPA, or DOXO. The combination treatment increased the number of apoptotic cells in a dose-dependent manner. The researchers observed that there was no significant difference in apoptotic rates between cells exposed to 20 \u0026micro;M DHA, 40 \u0026micro;M EPA, and the control. However, when DHA was combined with DOXO or EPA was combined with DOXO, the rate of late apoptosis increased significantly, indicating that the combination treatment was more effective at inducing apoptosis in cancer cells.\u003c/p\u003e\n\u003cp\u003eThe study further showed that the late apoptotic rate was significantly greater in cells treated with the combination of DHA and DOXO, reaching up to 53.80% than in cells treated with DOXO alone. Similarly, cells treated with the combination of EPA and DOXO showed a late apoptotic rate of 38.88%, which was significantly greater than that of cells treated with DOXO alone. However, no significant difference was observed in the percentage of early apoptotic cells.\u003c/p\u003e\n\u003cp\u003eIn addition to investigating the apoptotic rate, this study investigated the influence of DHA/EPA on the progression of the cell cycle by performing a cell cycle analysis. The results of the analysis showed that the combination treatment of DHA and EPA with DOXO had a greater effect on the progression of the cell cycle than treatment with DOXO alone.\u003c/p\u003e\n\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\n\u003ch2\u003eDNA fragmentation assay\u003c/h2\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003eDoxorubicin is a chemotherapeutic agent that acts by disrupting DNA replication and repair mechanisms. It does so by intercalating between the DNA base pairs, thereby preventing the DNA from unwinding and replicating. Additionally, it inhibits topoisomerase 2A, which is a critical enzyme involved in DNA repair. As a result, the DNA of the cells treated with DOXO became fragmented.\u003c/p\u003e\n\u003cp\u003eTo visualize the extent of this DNA damage, we performed a DNA fragmentation assay. Our results showed that cells treated with a combination of DHA\u0026thinsp;+\u0026thinsp;DOXO and EPA\u0026thinsp;+\u0026thinsp;DOXO exhibited more DNA damage (smear) than cells treated with DOXO alone. These findings support the hypothesis that combining DOXO with other agents (such as DHA and EPA) can enhance its cytotoxic effects.\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\n\u003ch2\u003eCell cycle analysis\u003c/h2\u003e\n\u003cp\u003eCell cycle analysis is a laboratory technique that evaluates the distribution of cells at different phases of the cell cycle. The DNA content was measured by staining cells with fluorescent dyes, followed by flow cytometry. This enables the identification of cell cycle stages, providing insights into cellular proliferation, growth, and potential abnormalities.\u003c/p\u003e\n\u003cp\u003eIn an experiment, flow cytometry was used to assess the effect of n-3 polyunsaturated fatty acids (PUFAs), specifically 20 \u0026micro;M DHA and 40 \u0026micro;M EPA, in combination with the chemotherapy drug DOXO on cell cycle progression. The researchers observed that treatment with the combination of DHA or EPA along with DOXO resulted in a significant increase in the percentage of cells in the sub-G1 phase compared to that of control cells (as shown in Fig.\u0026nbsp;5).\u003c/p\u003e\n\u003cp\u003eWhen the cells were exposed to the indicated concentrations of 20 \u0026micro;M DHA, 40 \u0026micro;M EPA, a combination of 20 \u0026micro;M DHA\u0026thinsp;+\u0026thinsp;0.5 \u0026micro;M DOXO, or 40 \u0026micro;M EPA\u0026thinsp;+\u0026thinsp;0.5 \u0026micro;M DOXO for 24 hours, the percentage of the sub-G1 population significantly increased by 15\u0026ndash;16% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) compared with that in the DOXO group (8%). Additionally, the number of cells in the G0/G1 phase decreased along with the increase in the number of cells in the sub-G1 phase compared to that of control cells.\u003c/p\u003e\n\u003cp\u003eThus, the combination of n-3 PUFAs (DHA and EPA) with DOXO led to a significant increase in cell apoptosis, as evidenced by the increased percentage of cells in the sub-G1 phase.\u003c/p\u003e\n\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\n\u003ch2\u003eNetwork Analysis\u003c/h2\u003e\n\u003cp\u003eTo determine the mechanism of action of the combination of n-3 PUFAs (DHA and EPA) with DOXO in ovarian cancer cells, we performed detailed \u003cem\u003ein silico\u003c/em\u003e network analysis to identify common genes and their interactions with three different ligands, namely, DHA, EPA, and DOXO. By analyzing the data, we were able to identify 19 genes that were common to all three ligands and were found in ovarian cancer (Fig.\u0026nbsp;6). We then generated a STRING network using StringDB and Cytoscape to map the genes and their interactions. To determine the most critical genes in the network, we used the MCC algorithm in the CytoHubba extension of Cytoscape, which revealed the top 10 hub genes (Fig.\u0026nbsp;7). We noticed that the TOP2A gene interacted with 6 of the top 10 hub genes, making it a promising protein of interest for future studies. Hence further \u003cem\u003ein silico\u003c/em\u003e studies were performed on TOP2A.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\n\u003ch2\u003eMolecular Docking\u003c/h2\u003e\n\u003cp\u003eMolecular modeling studies were conducted to determine the binding conformations of ligands within the TOP2A binding cavity. The ligands studied were doxorubicin and the PUFAs: DHA and EPA. The receptor atoms of TOP2A were obtained from the PDB database and were treated as rigid, while all ligands were considered flexible during the docking simulation. The binding cavity of the preexisting ligand ANA in TOP2A (PDBID: 1ZXM) was used as the binding cavity for the ligands used in this study. The docking simulation was performed in AutoDock Vina. A pool of possible ligand conformations was generated, and a set of conformational poses was computed with their respective binding affinities. The conformation with the least binding affinity for TOP2A was regarded as the best conformation.\u003c/p\u003e\n\u003cp\u003eThe results showed that doxorubicin had the lowest binding energy of -10 kcal/mol when it was docked with TOP2A. It interacted with the target protein through H-bonds in the best conformation pose. The binding affinity and interacting residues are provided in Table\u0026nbsp;1. The MOE tool was used to visualize the interacting amino acids, and the 3D interaction of TOP2A with doxorubicin and the PUFA-DHA and EPA complex with H-bond interacting residues is shown in Fig.\u0026nbsp;8.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\n\u003ch2\u003eMolecular Dynamics Simulation\u003c/h2\u003e\n\u003cp\u003eMolecular dynamic simulations are commonly utilized to study and analyze the dynamic perturbations occurring in protein-ligand complex conformations. During a 100 ns simulation period, it has been observed that the potential energy tends to decrease for both receptors, indicating that the system is stabilizing. We analyzed the conformation of the receptor-ligand complex throughout the simulation period and calculated the Root-Mean-Square Deviation (RMSD) for both protein and ligand. The RMSD value helps us determine the average displacement change for a particular frame relative to a reference frame. The best docking poses of DHA, EPA, and doxorubicin obtained by molecular docking with TOP2A (PDB ID: 1ZXM) were subjected to MD simulation using Maestro software to examine the binding stability within the binding cavity of TOP2A. TOP2A was simulated for 100 ns with the lead posture of the provided ligands, and the conformational changes for the receptor-ligand interactions were obtained. We examined the RMSD and protein-ligand interactions between the supplied ligands.\u003c/p\u003e\n\u003cp\u003eThe RMSD graphs were generated by calculating the RMSD values for the C-\u0026alpha; atoms of TOP2A after binding with the ligands, and the RMSD values of the ligands were recorded to determine their binding efficiency within the binding cavity of TOP2A during the 100 ns MD simulation (Fig.\u0026nbsp;9). Upon interaction with doxorubicin, TOP2A started stabilizing after 40 ns at 4.8 \u0026Aring; and remained stable throughout the simulation. Similarly, doxorubicin also started stabilizing after 40 ns at 4 \u0026Aring; and remained stable throughout the simulation (Fig.\u0026nbsp;9A). However, upon interaction with DHA, TOP2A stabilized after 60 ns at 3.6 \u0026Aring; A and persisted for up to 100 ns. DHA stabilized early at approximately 30 ns at 4 \u0026Aring; up to 100 ns (Fig.\u0026nbsp;9B). In the TOP2A-EPA complex, TOP2A stabilizes after 40 ns at 2.6 \u0026Aring; and lasts up to 100 ns, while EPA stabilizes after 60 ns at 10.5 \u0026Aring; and lasts for the entire duration (Fig.\u0026nbsp;9C).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on the protein stabilization graphs above, we can observe fluctuations in the protein backbone. These fluctuations may be a result of the interactions between the protein and the ligands within its structure. As the protein stabilizes, different ligands come into contact with different residues within the binding cavity. For example, as shown in Fig.\u0026nbsp;10, in the case of doxorubicin, the number of ligand contacts with Glu59, Asp66, Asn92, Tyr123, Asp124, and Asn135 increased, while the number of contacts with Arg70, Ile97, Pro98, Ser121, and Thr187 decreased. Throughout the simulation, the ligand contacts the Asn63, Asn67, Val109, Ile113, Thr119, Gly133, Gly136, and Lys140 residues (Fig.\u0026nbsp;10A). On the other hand, DHA (Fig.\u0026nbsp;10B) shows strong contact with Met33, Tyr34, Ile283, Phe285, Ala290, Ser292, and Glu351, while EPA (Fig.\u0026nbsp;10C) shows strong contact with Trp34, Tyr44, Glu277, and Gln281. There are some common residues with which both EPA and DHA make contact, such as Trp34, Tyr44, Tyr246, and Gln281. However, EPA makes more contact with these residues than does DHA.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOvarian cancer has a low five-year survival rate and is the leading cause of death among gynecologic cancers[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Doxorubicin (DOX) is a potent chemical drug that is used to treat various types of cancer, including ovarian cancer [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The effectiveness of DOXO in ovarian treatment is hindered by its inherent cytotoxicity and the development of drug resistance at higher doses [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Hence there is a pressing need to explore novel therapeutic agents or combination therapies targeting this disease, particularly for advanced or recurrent stages. A growing body of evidence suggests that sustained intake of omega-3 fatty acids correlates with a markedly reduced risk of certain cancers [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e][\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Previous investigations have substantiated the capacity of docosahexaenoic acid (DHA) or EPA and its analogs to impede cell proliferation and tumor progression in preclinical models [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. According to a recent study using systematic mendelian randomization, the intake of DHA has been shown to reduce the risk of ovarian cancer in European populations [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Wang and colleagues (2022) demonstrated that a diet rich in fish and marine omega-3 PUFAs is associated with improved cancer survival [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe current study aimed to investigate whether DHA and EPA have the potential to improve the effectiveness of DOXO therapy. The results of the study showed that the combination of DOXO and n-3 PUFAs increased the death of PA-1 cells, as demonstrated by the MTT assay. The effectiveness of the combination was further confirmed by the induction of cell cycle arrest, apoptosis, and the reduction of cancer cell clonogenicity in ovarian cancer cells. These results support previous studies done by researchers[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e][\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The distribution of cells in the cell cycle was analyzed, which showed that the combination of DOXO and n-3 PUFAs increased the number of cells in the subG1 phase and decreased the G2/M transition. The Annexin V/PI staining assays proved that the combination resulted in apoptosis in PA-1 cells, which was further confirmed by the DNA fragmentation assay that showed a higher level of DNA degradation in cells treated with the combination. We also investigated the effect of DHA/EPA, omega-3 fatty acids, on ovarian cancer cell migration and found that it significantly inhibited migration. This suggests that DHA/EPA has the potential to enhance the anti-metastatic effects of DOXO. This is consistent with previous research by Zheng et al. (2014), which found that DHA inhibited the migration of endometrial cancer cells by suppressing mTOR1/2 signaling [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAfter confirming the beneficial effect of n-3 PUFAs in vitro, we conducted \u003cem\u003ein silico\u003c/em\u003e studies to determine how they work. Through network analysis, we identified nineteen genes that are common to ovarian cancer, DHA, EPA, and doxorubicin. We used StringDB and Cytoscape to construct a STRING network and identified the top 10 hub genes, which included CCND1, MYC, CTNNB1, CASP3, CASP8, CDH1, NOTCH1, PI3CA, CDK4, and CDK6. Among these genes, TOP2A strongly interacts with six of the top 10 hub genes, including CCND1, MYC, CTNNB1, PI3CA, CDK4, and CDK6. These genes are important in various cellular processes and have been implicated in different types of cancers, including ovarian cancer. Dysregulation of these genes can contribute to tumor development and progression [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study on molecular docking has revealed that n-3 PUFAs act similarly to DNA intercalators and TOP2A inhibitors, just like the reference drug DOXO. A recent study based on molecular docking studies with TOP2A as the target protein supports this finding. The study suggests that DHA and EPA may have a similar mechanism of action with DOXO, as DNA intercalators and TOP2A inhibitors [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Our molecular dynamics study revealed that the bond between n-3 PUFAs and TOP2A is equally stable as that of DOXO and TOP2A. This was determined by analyzing the structure of the best-docked hits, fluctuations during interactions, and overall structural stability through the computation of the RMSD and protein-ligand contacts. These findings are consistent with recent studies that suggest TOP2A is a potential target in ovarian cancer. Additionally, TOP2A plays a role in regulating signaling via the AKT/mTOR pathway, which in turn promotes the proliferation of ovarian cancer cells[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e][\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. According to a study conducted by Bai and colleagues, elevated levels of TOP2A mRNA were found in both advanced-stage diseases and high-grade ovarian malignancies. The study also discovered that TOP2A overexpression was significantly associated with lower overall survival rates in all patients with epithelial ovarian carcinoma (EOC) and serous patients[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Our study has revealed that the combination of n-3 PUFAs with doxorubicin can significantly enhance the drug's antitumor activity. This is primarily attributed to the interference of n-3 PUFAs with the PI3K/AKT/mTOR pathway and the inhibition of topoisomerase II, which can make doxorubicin work more effectively.\u003c/p\u003e \u003cp\u003eFurthermore, our research has shown that n-3 PUFAs act as TOP2A receptor antagonists, which can potentially lower the therapeutic dose of doxorubicin required to achieve the desired results. As a result, this approach can reduce the toxic side effects associated with high doses of doxorubicin, resensitize cancer cells to the drug, and suppress drug resistance.\u003c/p\u003e \u003cp\u003eIn conclusion, our findings suggest that the combination of doxorubicin and n-3 PUFAs can be a promising strategy to combat cancer.\u003c/p\u003e \u003cp\u003eThese findings suggest that N-3 PUFAs combined with DOXO could be a novel and potentially effective combination for the treatment of ovarian cancer. We recommend conducting more in vivo research on this combination.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study has found that combining doxorubicin with omega-3 polyunsaturated fatty acids (specifically DHA and EPA) has significant anticancer effects through various mechanisms, including TOP2A inhibition and DNA intercalation. This combination therapy can reduce the necessary therapeutic dose of DOX, reducing toxic side effects and improving the quality of life of ovarian cancer patients. Further research is needed to confirm the safety and efficacy of this innovative treatment approach through \u003cem\u003ein vivo\u003c/em\u003e studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgment\u003c/h2\u003e\n\u003cp\u003eThe authors would like to thank the Director of the MIT School of Bioengineering Sciences \u0026amp; Research, MIT ADT University, for infrastructure support and funding. We also thank the Atal Incubation Centre, MIT ADT University, for providing access to the flow cytometer.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003ePG designed the study, conducted the investigation\u0026nbsp;and\u0026nbsp;data analysis, and wrote the original draft. SH contributed\u0026nbsp;to\u0026nbsp;the methodology of Figs. 7, 8, 9 and 10. KRN and VS contributed\u0026nbsp;to\u0026nbsp;the\u0026nbsp;conceptualization, project administration, funding acquisition, and\u0026nbsp;writing\u0026mdash;review, and\u0026nbsp;editing of\u0026nbsp;the\u0026nbsp;manuscript.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eMIT School of Bioengineering Sciences \u0026amp; Research, MIT ADT University, Pune, India.\u003c/p\u003e\n\u003ch2\u003eData availability\u003c/h2\u003e\n\u003cp\u003eThe data\u0026nbsp;are available\u0026nbsp;upon\u0026nbsp;request from the authors.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors declare no financial or\u0026nbsp;nonfinancial\u0026nbsp;competing interests.\u003c/p\u003e\n\u003ch2\u003eEthics statement\u003c/h2\u003e\n\u003cp\u003eThis is not applicable as no human or animal involved in the study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of generative AI and AI-assisted technologies in the writing process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this work the author(s) used Grammerly in order to rectify grammatical mistakes and improve the quality of manuscript. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eShabir S, Gill PK (2020) Global scenario on ovarian cancer \u0026ndash; Its dynamics, relative survival, treatment, and epidemiology. Adesh Univ J Med Sci Res 2(1):17\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.25259/aujmsr_16_2019\u003c/span\u003e\u003cspan address=\"10.25259/aujmsr_16_2019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCabasag CJ et al (2022) Nov., Ovarian cancer today and tomorrow: A global assessment by world region and Human Development Index using\u0026thinsp;\u0026lt;\u0026thinsp;scp\u0026thinsp;\u0026gt;\u0026thinsp;GLOBOCAN\u0026thinsp;2020, \u003cem\u003eInt. J. 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J Ovarian Res 9(1):1\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13048-016-0244-9\u003c/span\u003e\u003cspan address=\"10.1186/s13048-016-0244-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\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, omega-3 polyunsaturated fatty acids, chemotherapy, doxorubicin, TOP2A, molecular docking, synergistic effects","lastPublishedDoi":"10.21203/rs.3.rs-4490207/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4490207/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground/Objectives:\u003c/strong\u003e Ovarian cancer presents significant challenges in treatment efficacy, necessitating exploration of alternative therapeutic approaches. This study aimed to investigate the effects of omega-3 polyunsaturated fatty acids (n-3 PUFAs), particularly in conjunction with chemotherapy, on ovarian teratocarcinoma cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubject/Methods\u003c/strong\u003e: The study conducted rigorous cell viability assays to assess the impact of n-3 PUFAs on doxorubicin (DOXO)-induced cytotoxicity. Clonogenic assays, hanging drop assays, and apoptosis assays were employed to validate the observed effects. Network pharmacological analyses and molecular docking simulations were conducted to elucidate potential molecular mechanisms underlying the observed synergistic effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Cell viability assays demonstrated a significant augmentation of DOXO-induced cytotoxicity by n-3 PUFAs, resulting in decreased cellular viability and migratory capacity. Clonogenic assays confirmed a reduction in colony formation in the combined treatment group, supported by additional experimental assays. Network pharmacological analyses identified topoisomerase II A (TOP2A) gene as a key target, while molecular docking simulations revealed structural analogies between n-3 PUFAs and DOXO, suggesting shared mechanisms of action.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The integration of computational and experimental approaches uncovered the synergistic effects of n-3 PUFAs and DOXO in ovarian cancer treatment. This study bridges the gap between theoretical understanding and practical application, offering promising prospects for enhanced therapeutic outcomes in ovarian cancer management.\u003c/p\u003e","manuscriptTitle":"Augmenting Chemotherapy Response In Ovarian Cancer: Omega-3 Polyunsaturated Fatty Acids Target TOP2A","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-11 03:11:53","doi":"10.21203/rs.3.rs-4490207/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":"7cec619e-dec9-43e5-8622-5d4d1f98a80d","owner":[],"postedDate":"June 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-24T10:33:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-11 03:11:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4490207","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4490207","identity":"rs-4490207","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}