Exploiting epigenetic dependencies in ovarian cancer therapy

Current data and future perspectives on DNA methylation in ovarian cancer (Review)

Ovarian cancer (OC) represents the most prevalent malignancy of the female reproductive system. Its distinguishing features include a high aggressiveness, substantial morbidity and mortality, and a lack of apparent symptoms, which collectively pose significant challenges for early detection. Given that aberrant DNA methylation events leading to altered gene expression are characteristic of numerous tumor types, there has been extensive research into epigenetic mechanisms, particularly DNA methylation, in human cancers. In the context of OC, DNA methylation is often associated with the regulation of critical genes, such as BRCA1/2 and Ras‑association domain family 1A. Methylation modifications within the promoter regions of these genes not only contribute to the pathogenesis of OC, but also induce medication resistance and influence the prognosis of patients with OC. As such, a more in‑depth understanding of DNA methylation underpinning carcinogenesis could potentially facilitate the development of more effective therapeutic approaches for this intricate disease. The present review focuses on classical tumor suppressor genes, oncogenes, signaling pathways and associated microRNAs in an aim to elucidate the influence of DNA methylation on the development and progression of OC. The advantages and limitations of employing DNA methylation in the diagnosis, treatment and prevention of OC are also discussed. On the whole, the present literature review indicates that the DNA methylation of specific genes could potentially serve as a prognostic biomarker for OC and a therapeutic target for personalized treatment strategies. Further investigations in this field may yield more efficacious diagnostic and therapeutic alternatives for patients with OC.

Spotlight on New Hallmarks of Drug-Resistance towards Personalized Care for Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is the deadliest gynecological malignancy worldwide. Despite the latest advances, a major clinical issue in EOC is the disappointing prognosis related to chemoresistance in almost one-third of cases. Drug resistance relies on heterogeneous cancer stem cells (CSCs), endowed with tumor-initiating potential, leading to relapse. No biomarkers of chemoresistance have been validated yet. Recently, major signaling pathways, micro ribonucleic acids (miRNAs), and circulating tumor cells (CTCs) have been advocated as putative biomarkers and potential therapeutic targets for drug resistance. However, further investigation is mandatory before their routine implementation. In accordance with the increasing rate of therapeutic efforts in EOC, the need for biomarker-driven personalized therapies is growing. This review aims to discuss the emerging hallmarks of drug resistance with an in-depth insight into the underlying molecular mechanisms lacking so far. Finally, a glimpse of novel therapeutic avenues and future challenges will be provided.

Diagnostic value of plasma-derived exosomal miR-223 for epithelial ovarian cancer

OBJECTIVES

To evaluate the diagnostic value of plasma exosomal miR-223 and its combination with CA125 for the diagnosis of early-stage epithelial ovarian cancer (EOC).

PATIENTS AND METHODS

Exosomes derived from the plasma of 78 EOC patients, 40 patients with epithelial benign ovarian tumors, and 52 healthy participants were isolated using the ultracentrifugation method and identified by transmission electron microscopy (TEM) and western blot.

RESULTS

The expression of exosomal miR-223 was significantly upregulated in the plasma of EOC patients compared to that in healthy subjects and patients with benign diseases. The combination of exosomal miR-223 and CA125 from plasma had an equivalent area under the ROC curve (AUC) to CA125 alone for discriminating between EOC and non-EOC cases, including healthy subjects and benign ovarian tumors. However, the AUC value of the combination was 0.944 (95% CI: 0.899-0.990) for differentially diagnosing early-stage EOC from healthy subjects, slightly higher than that of CA125 alone (0.928, 95% CI: 0.875-0.981), with a sensitivity and specificity of 0.9784 and 0.885, respectively.

CONCLUSION

Our data suggest that plasma exosomal miR-223 can be used as a complement to CA125 to increase the diagnostic power for differentiating early-stage EOC from healthy subjects.

The Prognosis and Immunotherapy Prediction Model of Ovarian Serous Cystadenocarcinoma Patient was Constructed Based on Cuproptosis-Related LncRNA

Cuproptosis can serve as potential prognostic predictors in patients with cancer. However, the role of this relationship in ovarian serous cystadenocarcinoma (OV) remains unclear. 376 OV tumor samples were obtained from the Cancer Genome Atlas (TCGA) database, and long non-coding RNAs (lncRNAs) related to cuproptosis were obtained through correlation analysis. The risk assessment model was further constructed by univariate Cox regression analysis and LASSO Cox regression. Bioinformatics was used to analyze the regulatory effect of relevant risk assessment models on tumor mutational burden (TMB) and immune microenvironment. We obtained 5 lncRNAs (AC025287.2, AC092718.4, AC112721.2, LINC00996, and LINC01639) and incorporated them into the Cox proportional hazards model. Kaplan-Meier (KM) curve analysis of the prognosis found that the high-risk group was associated with a poorer prognosis. The receiver operating characteristic (ROC) curve showed stronger predictive power compared to other clinicopathological features. Immune infiltration analysis showed that high-risk scores were inversely correlated with CD8+ T cells, CD4+ T cells, macrophages, NK cells, and B cells. Functional enrichment analysis found that they may act via the extracellular matrix (ECM)-interacting proteins and other pathways. We successfully constructed a reliable cuproptosis-related lncRNA model for the prognosis of OV.

Identification and Validation of a Novel Anoikis-Related Gene Signature for Predicting Survival in Patients With Serous Ovarian Cancer

Background

Ovarian cancer is an extremely deadly gynecological malignancy, with a 5-year survival rate below 30%. Among the different histological subtypes, serous ovarian cancer (SOC) is the most common. Anoikis significantly contributes to the progression of ovarian cancer. Therefore, identifying an anoikis-related signature that can serve as potential prognostic predictors for SOC is of great significance.

Methods

We intersected 308 anoikis-related genes (ARGs) and identified those significantly associated with SOC prognosis using univariate Cox regression. A LASSO Cox regression model was constructed and evaluated using Kaplan-Meier and receiver operating characteristic (ROC) analyses in TCGA (The Cancer Genome Atlas) and GSE26193 cohorts. We conducted quantitative real-time polymerase chain reaction (qPCR) to assess mRNA levels and applied bioinformatics to investigate the correlation between risk groups and gene expression, mutations, pathways, tumor immune microenvironment (TIME), and drug sensitivity in SOC.

Results

Among 308 ARGs, 28 were significantly associated with SOC prognosis. A 13-gene prognostic model was established through LASSO Cox regression in TCGA cohort. High-risk group had poorer prognosis than low-risk group (median overall survival (mOS): 34.2 vs. 57.1 months, hazard ratio (HR): 2.590, 95% confidence interval (CI): 0.159 - 6.00, P < 0.001). The area under the curve (AUC) values of 0.63, 0.65, and 0.74 reflected the predictive performance for 3-, 5-, and 8-year overall survival (OS) in GSE26193 validation cohort. Functional enrichment, pathway analysis, and TIME analysis identified distinct characteristics between risk groups. Drug sensitivity analysis revealed potential drug advantages for each group. Furthermore, qPCR validation once again confirmed the effectiveness of the risk model in SOC patients.

Conclusions

We developed and validated a robust ARG model, which could be used to predict OS in SOC patients. By systematically analyzing the correlation between the risk score of the ARGs signature model and various patterns, including the TIME and drug sensitivity, our findings suggest that this prognostic model contributes to the advancement of personalized and precise therapeutic strategies. Nevertheless, further validation studies and investigations into the underlying mechanisms are warranted.

Ginsenoside 20(S)-Rg3 reduces KIF20A expression and promotes CDC25A proteasomal degradation in epithelial ovarian cancer

Background

Ginsenoside 20(S)-Rg3 shows promising tumor-suppressive effects in ovarian cancer via inhibiting NF-κB signaling. This study aimed to explore the downstream tumor suppressive mechanisms of ginsenoside Rg3 via this signaling pathway.

Materials and methods

A systematical screening was applied to examine the expression profile of 41 kinesin family member genes in ovarian cancer. The regulatory effect of ginsenoside Rg3 on KIF20A expression was studied. In addition, we explored interacting proteins of KIF20A and their molecular regulations in ovarian cancer. RNA-seq data from The Cancer Genome Atlas (TCGA) was used for bioinformatic analysis. Epithelial ovarian cancer cell lines SKOV3 and A2780 were used as in vitro and in vivo cell models. Commercial human ovarian cancer tissue arrays were used for immunohistochemistry staining.

Results

KIF20A is a biomarker of poor prognosis among the kinesin genes. It promotes ovarian cancer cell growth in vitro and in vivo. Ginsenoside Rg3 can suppress the transcription of KIF20A. GST pull-down and co-immunoprecipitation (IP) assays confirmed that KIF20A physically interacts with BTRC (β-TrCP1), a substrate recognition subunit for SCFβ-TrCP E3 ubiquitin ligase. In vitro ubiquitination and cycloheximide (CHX) chase assays showed that via interacting with BTRC, KIF20A reduces BTRC-mediated CDC25A poly-ubiquitination and enhances its stability. Ginsenoside Rg3 treatment partly abrogates KIF20A overexpression-induced CDC25A upregulation.

Conclusion

This study revealed a novel anti-tumor mechanism of ginsenoside Rg3. It can inhibit KIF20A transcription and promote CDC25A proteasomal degradation in epithelial ovarian cancer.

Polyploidy, EZH2 upregulation, and transformation in cytomegalovirus-infected human ovarian epithelial cells

Human cytomegalovirus (HCMV) infection has been implicated in epithelial ovarian cancer (OC). Polyploidy giant cancer cells (PGCCs) have been observed in high-grade serous ovarian carcinoma (HGSOC); they possess cancer stem cell-like characteristics and give rise to progeny cells expressing epithelial-mesenchymal transition (EMT) markers. EZH2 plays a potential oncogenic role, correlating with high proliferative index and tumor grade in OC. Herein, we present the experimental evidence for HCMV as a reprogramming vector that elicited human ovarian epithelial cells (OECs) transformation leading to the generation of "CMV-transformed Ovarian cells" (CTO). The infection with the two high-risk clinical strains, namely HCMV-DB and BL provoked a distinct cellular and molecular mechanisms in infected OECs. EZH2 upregulation and cellular proliferation were curtailed by using EZH2 inhibitors. The HGSOC biopsies were characterized by an elevated EZH2 expression, possessing a strong positive correlation between the aforementioned marker and HCMV. From HGSOC biopsies, we isolated three HCMV clinical strains that transformed OECs generating CTO cells which displayed proliferative potentials in addition to EZH2 upregulation and PGCCs generation; these features were reduced upon EZH2 inhibition. High-risk HCMV strains transformed OECs confirming an HCMV-induced epithelial ovarian cancer model and highlighting EZH2 tumorigenic properties. Our findings might be highly relevant in the pathophysiology of ovarian tumors thereby nominating new targeted therapeutics.

Survival prognosis model for elderly women with epithelial ovarian cancer based on the SEER database

Objectives

We aimed to analyze the risk factors of elderly women with epithelial ovarian cancer (EOC) using data on the SEER database, and to generate a nomogram model their 1-, 3-, and 5-year prognoses. The resulting nomogram model should be useful for clinical diagnoses and treatment.

Methods

We collected clinical data of women older than 70 years with epithelial ovarian cancer (diagnosed on the basis of surgical pathology) from the SEER database including datasets between 2010 and 2019. We randomly grouped the data into two groups (7:3 ratio) using the R language software. We divided the independent prognostic factors obtained by univariate and multi-factor Cox regression analyses into training and validation sets, and we plotted the same independent prognostic factors in a nomogram model of overall survival (OS) at 1, 3, and 5 years. We used the C-index, calibration curve, and area under the curve to validate the nomograms. We further evaluated the model and its clinical applicability using decision curve analyses.

Results

We identified age, race, marital status, histological type, AJCC staging, differentiation degree, unilateral and bilateral tumor involvement, number of positive lymph nodes, chemotherapy, surgery, sequence of systemic treatment versus surgery, and time from diagnosis to treatment as independent prognostic factors for elderly women with EOC (P < 0.5). The C-indexes were 0.749 and 0.735 in the training and validation sets, respectively; the ROC curves showed that the AUC of each prognostic factor was greater than 0.7; and, the AUC values predicted by the line plot were similar in the training and validation sets. The decision curves suggest that this line plot model has a high clinical value for predicting overall survivals at 1, 3, and 5 years in elderly women with EOC.

Conclusion

The nomogram model in this study can provide an accurate assessment of the overall survival of women older than 70 years with EOC at the time of the first treatment, and it provides a basis for individualized clinical treatment.

Association of pre-diagnosis specific color groups of fruit and vegetable intake with ovarian cancer survival: results from the ovarian cancer follow-up study (OOPS)

Background: The colors of fruits and vegetables (FV) reflect the presence of pigmented bioactive compounds. The evidence of pre-diagnosis specific FV color group intake contributing to ovarian cancer (OC) survival is limited and inconsistent. Methods: A prospective cohort study was conducted between 2015 and 2020 with 700 newly diagnosed OC patients. Pre-diagnosis dietary information was assessed by a validated food frequency questionnaire. We classified FV into five groups based on the color of their edible parts (e.g., green, red/purple, orange/yellow, white, and uncategorized groups). Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of specific color groups of FV before diagnosis with OC survival. Potential multiplicative and additive interactions were assessed. Results: 130 patients died during a median follow-up of 37.57 (interquartile: 24.77-50.20) months. We observed the improved survival with a higher pre-diagnosis intake of total FV (HRtertile 3 vs. tertile 1 = 0.63, 95%CI = 0.40-0.99), total vegetables (HRtertile 3 vs. tertile 1 = 0.57, 95%CI = 0.36-0.90), and red/purple FV (HRtertile 3 vs. tertile 1 = 0.52, 95%CI = 0.33-0.82). In addition, we observed significant dose-response relationships for per standard deviation increment between total vegetable intake (HR = 0.79, 95%CI = 0.65-0.96) and red/purple group intake (HR = 0.77, 95%CI = 0.60-0.99) before diagnosis with OC survival. Additionally, pre-diagnosis green FV intake was borderline associated with better OC survival (HRper standard deviation increment = 0.83; 95%CI = 0.69-1.00). In contrast, we did not observe significant associations between pre-diagnosis intake of total fruits, orange/yellow, white, and uncategorized groups and OC survival. Conclusion: Pre-diagnosis FV intake from various color groups, especially the green and red/purple ones, may improve OC survival. Further studies are needed to validate our findings.

Prognosis comparison between small cell carcinoma of ovary and high-grade serous ovarian cancer: A retrospective observational cohort study

BACKGROUND

Small cell carcinoma of ovary (SCCO) is a rare and aggressive cancer primarily reported in the form of case reports. Due to limited epidemiological and prognostic analyses based on large populations, SCCO has varied considerably without prognostic models and a recognized first-line treatment strategy. The study aimed to compare the clinical characteristics, treatment methods, and prognosis of SCCO and high-grade serous ovarian cancer (HGSOC), the most prevalent subtype of ovarian cancer, in a large sample and develop a predictive model for these two subtypes.

METHODS

Data from the Surveillance, Epidemiology, and End Results program were analyzed for patients with SCCO or HGSOC from 2000 to 2017. Clinical, demographic, and treatment characteristics were compared between the two groups. Propensity-score matching, Cox risk regression analysis, and Kaplan-Meier survival curves were used to assess the data. Finally, a nomogram was developed to predict the patient survival time.

RESULTS

A total of 32,185 women, including 31,979 (99.4%) diagnosed with HGSOC and 206 (0.6%) diagnosed with SCCO, were identified. Age ≤ 51 years, single, median house income less than $70,000, early stage, and unilateral disease were more common characteristics of patients with SCCO than those with HGSOC. Patients with SCCO were more likely to receive radiotherapy (6.8% vs. 0.8%, p <0.001) and have tumors ≥ 141 mm (38.3% vs. 9.7%, p <0.001) than patients with HGSOC. The independent risk factors for SCCO patients included older age at diagnosis, advanced stage, surgery, radiotherapy, chemotherapy, larger tumor size, and bilateral tumor. Overall and cancer-specific survival rates were significantly lower for SCCO than more malignant HGSOC. Prognostic models and nomograms had been constructed to predict the individual survival rates of patients with SCCO and HGSOC.

CONCLUSION

Patients with SCCO presented with the early-stage disease more frequently than patients with HGSOC and had decreased overall and cancer-specific survival rates.

The Role of Iron and Cobalt in Gynecological Diseases

Iron and cobalt are micronutrients that play an important role in the regulation of cellular processes, being part of the centre of catalases, peroxidases, cytochromes and metalloproteins such as hemoglobin and myoglobin (Fe). Cobalt primarily functions as a component of hydroxycobalamin, which is essential for regulating red blood cell production. Maintaining normal levels of cobalt and iron in the human body is important, as a deficiency can lead to anaemia. These elements are also involved in reactions during which oxidative stress occurs and are therefore considered to be a cause of tumor formation. This paper will discuss aspects of the influence of cobalt and iron on mechanisms that may contribute to the growth of gynecological tumors, as well as other obstetric-gynecological disease entities, by altering the conditions of the microenvironment. In addition, the following review also highlights the role of cobalt and iron in the treatment of gynecological tumors.

Comparative glycoproteomics study on the surface of SKOV3 versus IOSE80 cell lines

Objective: Site- and structure-specific quantitative N-glycoproteomics study of differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells with the non-cancerous ovarian epithelial IOSE80 cells as the control.

Methods: C18-RPLC-MS/MS (HCD with stepped normalized collision energies) was used to analyze the 1: 1 mixture of labeled intact N-glycopeptides from SKOV3 and IOSE80 cells, and the site- and structure-specific intact N-glycopeptide search engine GPSeeker was used to conduct qualitative and quantitative search on the obtained raw datasets.

Results: With the control of the spectrum-level false discovery rate ≤1%, 13,822 glycopeptide spectral matches coming from 2,918 N-glycoproteins with comprehensive N-glycosite and N-glycan structure information were identified; 3,733 N-glycosites and 3,754 N-glycan sequence structures were confirmed by site-determining and structure-diagnostic fragment ions, respectively. With the control of no less than two observations among the three technical replicates, fold change ≥1.5, and p-value ≤ 0.05, 746 DEPGs in SKOV3 cells relative to IOSE80 cells were quantified, where 421 were upregulated and 325 downregulated.

Conclusion: Differential cell-surface N-glycosylation of ovarian cancer SKOV3 cells were quantitatively analyzed by isotopic labeling and site- and structure-specific N-glycoproteomics. This discovery study provides putative N-glycoprotein biomarker candidates for future validation study using multiple reaction monitoring and biochemical methods.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

The Emerging Role of Chromatin Remodeling Complexes in Ovarian Cancer

Ovarian cancer (OC) is the fifth leading cause of women's death from cancers. The high mortality rate is attributed to the late presence of the disease and the lack of modern diagnostic tools, including molecular biomarkers. Moreover, OC is a highly heterogeneous disease, which contributes to early treatment failure. Thus, exploring OC molecular mechanisms could significantly enhance our understanding of the disease and provide new treatment options. Chromatin remodeling complexes (CRCs) are ATP-dependent molecular machines responsible for chromatin reorganization and involved in many DNA-related processes, including transcriptional regulation, replication, and reparation. Dysregulation of chromatin remodeling machinery may be related to cancer development and chemoresistance in OC. Some forms of OC and other gynecologic diseases have been associated with mutations in specific CRC genes. Most notably, ARID1A in endometriosis-related OC, SMARCA4, and SMARCB1 in hypercalcemic type small cell ovarian carcinoma (SCCOHT), ACTL6A, CHRAC1, RSF1 amplification in high-grade serous OC. Here we review the available literature on CRCs' involvement in OC to improve our understanding of its development and investigate CRCs as possible biomarkers and treatment targets for OC.

The Potential of MicroRNAs as Clinical Biomarkers to Aid Ovarian Cancer Diagnosis and Treatment

Ovarian cancer is a commonly diagnosed malignancy in women. When diagnosed at an early stage, survival outcomes are favourable for the vast majority, with up to 90% of ovarian cancer patients being free of disease at 5 years follow-up. Unfortunately, ovarian cancer is typically diagnosed at an advanced stage due to the majority of patients remaining asymptomatic until the cancer has metastasised, resulting in poor outcomes for the majority. While the molecular era has facilitated the subclassification of the disease into distinct clinical subtypes, ovarian cancer remains managed and treated as a single disease entity. MicroRNAs (miRNAs) are small (19-25 nucleotides), endogenous molecules which are integral to regulating gene expression. Aberrant miRNA expression profiles have been described in several cancers, and have been implicated to be useful biomarkers which may aid cancer diagnostics and treatment. Several preliminary studies have identified candidate tumour suppressor and oncogenic miRNAs which may be involved in the development and progression of ovarian cancer, highlighting their candidacy as oncological biomarkers; understanding the mechanisms by which these miRNAs regulate the key processes involved in oncogenesis can improve our overall understanding of cancer development and identify novel biomarkers and therapeutic targets. This review highlights the potential role of miRNAs which may be utilised to aid diagnosis, estimate prognosis and enhance therapeutic strategies in the management of primary ovarian cancer.

Novel SMARCA Degraders for Treating Cancer

Provided herein are novel compounds as SMARCA degraders, pharmaceutical compositions, use of such compounds in treating cancer, and processes for preparing such compounds.

Dendritic Cell Vaccines: A Promising Approach in the Fight against Ovarian Cancer

Simple Summary

With an overall 5-year survival of only 20% for advanced-stage ovarian cancer patients, enduring and effective therapies are a highly unmet clinical need. Current standard-of-care therapies are able to improve progression-free survival; however, patients still relapse. Moreover, immunotherapy has not resulted in clear patient benefits so far. In this situation, dendritic cell vaccines can serve as a potential therapeutic addition against ovarian cancer. In the current review, we provide an overview of the different dendritic cell subsets and the roles they play in ovarian cancer. We focus on the advancements in dendritic cell vaccination against ovarian cancer and highlight the key outcomes and pitfalls associated with currently used strategies. Finally, we address future directions that could be taken to improve the dendritic cell vaccination outcomes in ovarian cancer.

Abstract

Ovarian cancer (OC) is the deadliest gynecological malignancy in developed countries and is the seventh-highest cause of death in women diagnosed with cancer worldwide. Currently, several therapies are in use against OC, including debulking surgery, chemotherapy, as well as targeted therapies. Even though the current standard-of-care therapies improve survival, a vast majority of OC patients relapse. Additionally, immunotherapies have only resulted in meager patient outcomes, potentially owing to the intricate immunosuppressive nexus within the tumor microenvironment. In this scenario, dendritic cell (DC) vaccination could serve as a potential addition to the therapeutic options available against OC. In this review, we provide an overview of current therapies in OC, focusing on immunotherapies. Next, we highlight the potential of using DC vaccines in OC by underscoring the different DC subsets and their functions in OC. Finally, we provide an overview of the advances and pitfalls of current DC vaccine strategies in OC while providing future perspectives that could improve patient outcomes.

Overexpression of SHARPIN promotes tumor progression in ovarian cancer

SHARPIN (Shank-associated RH domain interacting protein) plays an important role in tumorigenesis. However, its role in ovarian cancer remains largely unknown. To investigate this issue, we systematically analyzed the amplification and expression of the SHARPIN in the TCGA database. From the database, we found that SHARPIN was amplified in ovarian cancer compared to normal ovarian tissue, and the mRNA level of SHARPIN was significantly elevated in ovarian cancer compared to non-tumorigenic ovarian tissue. In addition, we observed similar results from ovarian cancer cell lines and clinical samples from ovarian cancer patients, which indicated that increased SHARPIN expression is associated with tumorigenesis in ovarian cancer. SHARPIN knockdown inhibited the migration and invasion of ovarian cancer cells, also inhibited cell cycle and promoted apoptosis, thereby suppressing cell proliferation. RNA-seq results showed that SHARPIN significantly increased the expression of P53 and P21 and decreased the expression of Cyclin D1 and c-Myc, all of which are involved in the regulation of cell proliferation. Subsequent mechanistic exploration revealed that SHARPIN knockdown increased the expression of caspases 3 and 9, leading to apoptosis of ovarian cancer cells. We also found that high expression of SHARPIN was associated with poor prognosis of ovarian cancer patients. Collectively, we demonstrated a positive correlation between SHARPIN and ovarian cancer progression and provide a basis for combined targeted therapy strategies for future ovarian cancer treatment.