Ovarian cancer (OC) is a deadly disease and lacks a precise marker for diagnosis worldwide. Our previous work has shown the overexpression of flotillin-1 (FLOT1) in OC tissue. To improve diagnostic sensitivity and accuracy, we evaluated the serum level of FLOT1 in OC patients and found that the serum concentration of FLOT1 as well as CA125 was significantly increased in patients with OC compared with healthy control (p < 0.01) and those with benign tumors (p < 0.05). The detection rate (above the upper limit of a cut-off value) of FLOT1 and CA125 was 77.78% and 72.22%, respectively, in patients with OC, which was increased to 88.89% in combination. The elevation of FLOT1 was confirmed in the serum of nude mice after the implantation of human OC cells. A high level of FLOT1 protein in the serum was positively correlated with the overexpression of FLOT1 protein in OC tissues. Furthermore, the level of m6A modification of FLOT1 mRNA was significantly high in OC cells compared with normal ovarian epithelial cells, leading to an increase in FLOT1 mRNA expression. Application of a methylation inhibitor, 3-deazaadenosine, decreased FLOT1 mRNA expression in OC cells and suppressed tumor formation in a xenograft mouse model. In conclusion, the current study demonstrated that FLOT1 is a novel serum biomarker of OC and can be targeted by m6A modification inhibition. These data highlight the potential application of FLOT1 as a diagnostic marker and a therapeutic target for patients with OC.

Tumor-associated antigens (TAAs) have been shown to be associated with a variety of connective tissue diseases. However, the role of TAAs in primary Sjögren's syndrome (pSS) patients is still unclear. This study aims to explore the correlation between TAA levels and systemic clinical manifestations and disease activity in pSS patients.

Data were retrospectively collected from 108 patients with pSS (pSS group) and 100 healthy subjects (HCs group). Comparison of clinical characteristics and serological parameters between the TAA-positive group and the TAA-negative group. The independent risk factors of TAAs positivity were analyzed by univariate and multivariate regression, and the receiver operating characteristic curve was used to analyze the diagnostic performance of TAAs for pSS-associated interstitial lung disease (pSS-ILD).

Compared with the control group, the positivity rates of CEA, CA125, CA15-3, and CYFRA21-1 were higher, and the levels of serum CA125, CA15-3, and CYFRA21-1were higher in the pSS group. The incidence of ILD, pleural effusion, pericardial effusion, and ESSDAI ≥5 in the TAA-positive group was higher than in the TAA-positive group. Multivariate logistic regression analysis showed that the incidence of ILD was identified as an independent risk factor for TAA positivity. The AUC of CEA, CYFRA21-1, and NSE in the diagnosis of pSS-ILD were 0.690, 0.840, and 0.872, respectively, and the combined diagnosis could reach 0.952.

Certain TAA-positive rates and serum levels were increased in pSS patients. The TAA-positive group is correlated with the ESSDAI scores. ILD was an independent risk factor for TAA positivity, and CYFRA21-1 and NSE had the best diagnostic value in patients with pSS-ILD.

Demons-Meigs (DM) syndrome is characterized by the association of a benign ovarian tumor most often a fibroma or fibrothecoma with pleural and intraperitoneal effusions. It is a rare pathological entity. We report the case of a 40-year-old female patient with typical DM syndrome, characterized by the coexistence of pleural and intraperitoneal effusions, an ovarian mass, and a CA-125 level of 633 IU/ml. Laparotomy revealed abundant ascites and a large right ovarian mass, which was subsequently removed. Histopathological examination confirmed an ovarian fibroma. DM syndrome has a favorable prognosis, and treatment is primarily based on the removal of the ovarian tumor, without the need for chemotherapy or other therapeutic approaches.

To provide a comprehensive understanding and propose a strategy for the management of extragonadal malignant germ cell tumors (EMGCTs) arising from extracranial and nonvaginal sites.

We retrospectively reviewed the cases of 12 patients with EMGCTs arising from extracranial and nonvaginal sites treated in our center over the past 38 years. Data on clinicopathological characteristics, treatment modalities, and follow-up information were analyzed.

Among 209 patients diagnosed with EMGCTs, 12 women (5.7%) with EMGCTs of extracranial and nonvaginal sites were identified. These patients had tumors in the sacrococcygeal region (n = 4), abdominal cavity (n = 3), groin region (n = 2), uterus (n = 2), and mediastinum (n = 1). The median age at diagnosis was 23 years. Symptoms included abnormal uterine bleeding (n = 3), abdominal discomfort (n = 3), compression symptoms (n = 3), palpable mass (n = 2), and asymptomatic (n = 1). Yolk sac tumors (YSTs) were the most common histologic type. The median level of serum alpha-fetoprotein (AFP), a sensitive tumor marker, was 8216 ng/ml (2.7-74,157 ng/ml). One patient started bleomycin/etoposide/cisplatin without a pathologic diagnosis based on clinical diagnosis (high AFP levels and imaging findings), and 11 patients started chemotherapy following tumor biopsy or surgical resection. During the follow-up, one patient suffered a recurrence, two patients were alive with disease, and nine patients were disease-free.

Extracranial and nonvaginal EMGCTs are a heterogeneous group of tumors due to their varied onset ages, location, and clinical presentation. An all-around clinical evaluation is crucial for selecting appropriate treatment. Most patients achieve a good prognosis after surgical resection and chemotherapy. Patients with these rare diseases may benefit from individualized treatment and timely referral to experienced medical centers.

Liquid biopsy has emerged as a non-invasive cancer diagnosis and prognosis tool. Circular RNAs (circRNAs) have become promising biomarkers due to their stability and regulatory roles in cancer biology. This study aimed to evaluate the potential of hsa_circ_0008285 as a diagnostic biomarker for ovarian cancer (OC). 102 paired cancer and adjacent normal tissue samples, along with plasma from 98 OC patients, 42 polycystic ovary syndrome (PCO) patients, 35 endometriosis patients, and 93 healthy donors, were analyzed. Differentially expressed circRNAs were identified using Illumina HiSeq 2000 high-throughput sequencing in OC tissue samples (n = 4). Quantitative real-time polymerase chain reaction (qRT-PCR) was employed to validate the expression of hsa_circ_0008285. Diagnostic efficacy and sensitivity were assessed using receiver operating characteristic (ROC) analysis. High-throughput sequencing identified hsa_circ_0008285 as the most significantly upregulated circRNA (P = 0.000012). qRT-PCR results confirmed increased expression of hsa_circ_0008285 in OC tissues and plasma compared to healthy controls (P < 0.0001). ROC analysis demonstrated an area under the curve (AUC) of 0.74 (95 % CI: 0.6567-0.8306, P < 0.0001), indicating moderate diagnostic potential. Notably, the combined detection of hsa_circ_0008285 and CA_125 improved diagnostic specificity and sensitivity. Correlation analysis revealed that hsa_circ_0008285 upregulation was associated with tumor size, differentiation, and T stage. These findings suggest that hsa_circ_0008285 holds promise as a non-invasive biomarker for the diagnosis of OC, with potential applications in clinical practice.

Ovarian cancer has the highest mortality rate among gynecological cancers, making early detection crucial, as the five-year survival rate drops from 92% with early-stage diagnosis compared to 31% with late-stage diagnosis. Current diagnostic methods such as histopathological examination and detection of cancer antigen 125 and human epididymis protein 4 biomarkers are either invasive or lack specificity and sensitivity. However, the Papanicolaou (Pap) test, which is widely used for cervical cancer screening, shows the potential for detecting ovarian cancer by identifying tumor DNA in cervical scrapings. Since aberrant DNA methylation patterns are linked to cancer progression, DNA methylation offers a promising avenue for early diagnosis. Therefore, this study aimed to develop a methylation-based machine-learning model to stratify patients with ovarian cancer from the cervical scraping samples collected via Pap test.

Cervical scrapings were collected by gynecologists using conventional Pap smears. In total, 160 samples were collected: 95 normal, 37 benign, and 28 malignant. Methylation data were generated using the Illumina Infinium MethylationEPIC BeadChip array, which contains approximately 850,000 CpG loci. Methylation data were initially divided into training and testing sets in a 3:1 ratio comprising 120 and 40 samples, respectively. A two-step methylation-based model was trained using the training data for classification: a principal component analysis (PCA) model, consisting of 30 features, to classify samples as normal or tumor; then a gradient boosting model, containing 16 features, to further stratify tumor samples as benign or malignant. The two-step model achieved an accuracy of 0.88 and an F1-score of 0.86 on the testing data. Furthermore, an over-representation analysis was conducted to explore the functions associated with genes mapped from differentially methylated positions (DMPs) in comparisons between normal and tumor samples, as well as between benign and malignant samples. These results suggest that DMPs may be associated with olfactory transduction when comparing normal versus tumor samples, and immune regulation when comparing benign and malignant samples.

Our two-step model shows promise for predicting ovarian cancer and suggests that cervical scrapings may be a viable alternative for sample collection during screening.

Ovarian cancer (OC), a leading cause of gynecological cancer mortality, is frequently detected at advanced stages due to asymptomatic early progression. This study investigates plasma-based untargeted metabolomics for identifying biomarkers to screen and differentiate ovarian tumors (OT). Plasma samples from OC, benign ovarian tumors (BOT), and healthy controls (HC) were analyzed. Samples were randomized into train and test sets, with differential metabolites screened via two-tailed Student's t-test and partial least squares discriminant analysis. ROC models evaluated discriminatory capacity. Key metabolites demonstrated high predictive value: TMAO and hippuric acid distinguished OT from HC (AUC > 0.95), while linoleic acid, alpha-linolenic acid, and arachidonic acid (AUC > 0.9) further supported OT screening. Kynurenine differentiated OC from BOT (AUC = 0.808). Reduced levels of specific lysophosphatidylcholines (LPC (17:0/0:0), LPC (15:0/0:0)) also distinguished OT from HC (AUC = 0.771-0.89). These findings suggest plasma metabolomics holds promise for noninvasive biomarker discovery in OT screening and distinguishing between malignant and benign cases, though further validation of metabolite quantification is warranted prior to clinical application.

We aimed to investigate the prognostic role of CEACAM1 and to construct a radiomic model to predict CEACAM1 expression and prognosis in ovary cancer (OC). Sequencing data and CT scans in OC were sourced from TCGA and TCIA databases. CEACAM1 expression was assessed by Cox regression analyses, Kaplan-Meier curves and GSVA enrichment analysis. Furthermore, radiomic features were extracted from CT scans and selected by LASSO and ROC. The selected radiomic features were used to construct a radiomic model to predict CEACAM1 expression. In addition, the radiomic score (RS) and its relationship with OC survival were investigated by Kaplan-Meier and ROC curves. At last, RS and clinical features were included into LASSO, using nomogram to predict OC prognosis. Cox regression analyses showed that CEACAM1 expression was an independent prognostic factor and associated with immune cell infiltration in OC. By LASSO and ROC, six radiomic features were selected and used to construct a radiomic model. The PR, calibration, DCA and ROC curves revealed the good performance and clinical utility of the radiomic model to predict CEACAM1 expression. In addition, RS based on radiomic features was found to be associated with OC survival. At last, a nomogram based on RS, age, chemotherapy and tumor residual disease was constructed and was found to have high accuracy in predicting OC prognosis. For the first time, our study constructed a radiomic model to predict CEACAM1 expression and prognosis of OC patients. Those findings may guide novel diagnosis and treatment for OC patients.

Background: Serum biomarkers such as Carcinoma Antigen 125 (CA125) and Human Epididymis Protein 4 (HE4) are widely used in the diagnosis and prognosis of gynecological malignancies. Serum biomarkers such as CA125 and HE4 represent essential tools in improving early detection, risk stratification, and therapeutic decision-making for gynecological malignancies. However, their role in identifying uterine sarcomas remains debated. This systematic review and case series aims to examine the diagnostic and prognostic significance of CA125 and HE4 in uterine sarcomas. Methods: A systematic review was performed on studies investigating serum CA125 and HE4 levels in uterine sarcomas. A case series of all uterine sarcomas treated at the Campus Bio-Medico Gynecology Unit of Rome from 2010 to 2020 was analyzed. Results: The analysis of the 11 selected studies allowed us to investigate the role of CA125 in uterine sarcomas. No studies analyzing the role of HE4 in monitoring the disease were found. A total of 16 patients with confirmed uterine leiomyosarcoma were included in our case series. Conclusions: Neither CA125 nor HE4 can currently be considered definitive biomarkers for the diagnosis of uterine leiomyosarcomas. However, they may serve as useful adjuncts in the differential diagnosis between leiomyomas and leiomyosarcomas, particularly in reproductive-age patients.

The COVID-19 pandemic has significantly impacted cancer diagnosis, treatment, and prognosis; however, its effects on ovarian cancer remain unclear.

This multicenter retrospective study utilized the Surveillance, Epidemiology, and End Results database to compare changes in the diagnosis, treatment, prognosis, and risk factors among ovarian cancer patients pre- and post-COVID-19 pandemic. Patients diagnosed before the pandemic (pre-COVID-19 group) and those diagnosed during the pandemic (post-COVID-19 group) were matched through 1:1 propensity score matching. Kaplan-Meier analysis compared cancer-specific survival (CSS) and overall survival (OS). Factors associated with survival were identified by the Cox proportional hazards model, while a competing risks model was used to determine factors associated with cancer-specific death.

A total of 9,112 ovarian cancer patients were included in the study, with 4,536 diagnosed before COVID-19 and 4576 diagnosed during COVID-19. The results showed that the post-COVID-19 group presented at a more advanced stage had lower tissue differentiation, experienced more delayed treatments, and received fewer surgical interventions. Although there was no significant difference in survival between the pre-COVID-19 group and the post-COVID-19 group, patients with delayed treatment had a worse prognosis than those without delayed treatment. Additionally, we identified independent factors associated with survival outcomes, including age, tumor grade, clinical stage, pathological stage, specific histology, treatment delays, surgical intervention, and systemic therapy.

The survival outcomes of the pre-COVID-19 group and the post-COVID-19 group were relatively consistent, likely due to the short follow-up. Future research is necessary to continue monitoring the outcomes of patients in the post-COVID-19 group to determine its long-term impact.

Gamma-delta (γδ) T cells are a critical component of the tumor microenvironment and have been recognized as a promising biomarker and target for cancer therapy. Increasing evidence suggests that γδT cells play distinct roles in different cancers. However, the impact of γδT cells in breast cancer remains controversial.

In this study, we investigated the role of γδT cells in breast cancer using a comprehensive approach, including bulk and single-cell sequencing, radiomics based on magnetic resonance imaging (MRI), genomic data, and immunohistochemistry. Single-cell RNA profiling was used to infer the potential lineage evolution of γδT cells and their interactions with other immune cells. Bulk RNA sequencing was included to uncover the heterogeneity in signaling pathways, as well as radiotherapy and immunotherapy responses, among patients with varying levels of γδT cell abundance. Genomic analysis was used to recognize the critical gene mutations with the infiltration of γδT cells. Immunohistochemistry was performed to validate the prognostic value of γδT cells in breast cancer patients. Lastly, radiomics was used to establish a correlation between the abundance of γδT cells and the features of MRI images.

The γδT cell infiltration was closely associated with favorable prognosis in triple-negative breast cancer (TNBC) but not in other subtypes of breast cancer. γδT cells may exert antitumor effects through intrinsic lineage evolution or interact with antigen-presenting cells through ligand-receptor pairs. Patients with a high γδT cell abundance may benefit more from chemotherapy or radiotherapy alone than their combination. Additionally, patients with a high γδT cell abundance were more likely to benefit from immunotherapy. Finally, we established a radiomic model based on dynamic contrast-enhanced-MRI, which indicated the potential for estimating the γδT cell abundance for patients with TNBC.

Our study provides novel insight and a theoretical basis for individualized therapy of patients with TNBC based on γδT cells.

The clinical prognostic factors for ovarian clear cell carcinoma (OCCC) are limited, and we aim to construct a model to predict the survival of OCCC patients.

Data were extracted from the SEER database for patients diagnosed with OCCC. Cox regression analyses were used to identify independent risk factors for OCCC. Two nomograms were developed, and the results were evaluated comprehensively by C-index, ROC curve, calibration curve, and DCA curve. Patients diagnosed with OCCC were used as the validation set to verify the model.

A total of 1855 OCCC patients from the SEER database were used as the training set, and 101 patients from our hospital were used as the validation set. Cox regression analysis of the independent risk factors affecting the prognosis of OCCC was used to construct nomograms. The C-index of the training set OS was 0.76, and the validation set OS was 0.75. The AUC of the training set OS is 0.803, 0.794, and 0.802 for 1, 3, and 5 years, and 0.774, 0.800, and 0.923 for the validation set. The calibration curve and DCA curve also showed that OS and CSS have good predictive power.

A nomogram based on 8 prognostic factors analyzed by Cox regression can predict the prognosis of OCCC patients effectively.

Accurate early diagnosis of ovarian cancer is crucial. The objective of this research is to create a comprehensive model that merges clinical variables, O-RADS, and deep learning radiomics to support preoperative diagnosis and assess its efficacy for sonographers.

Data from two centers were used: Center 1 for training and internal validation, and Center 2 for external validation. DL and radiomics features were extracted from transvaginal ultrasound images to create a DL radiomics model using the LASSO method. A machine learning model ensemble was created by merging clinical variables, O-RADS scores, and DL radiomics model predictions. The model's effectiveness was evaluated by measuring the area under the receiver operating characteristic curve (AUC) and analyzing its impact on improving the diagnostic skills of sonographers. Moreover, the model's additional usefulness was assessed through integrated discrimination improvement (IDI), net reclassification improvement (NRI), and subgroup analysis.

The ensemble model demonstrated superior diagnostic performance for ovarian cancer compared to standalone clinical models and clinical O-RADS models. Notably, there were significant improvements in the NRI and IDI across all three datasets, with p-values < 0.05. The ensemble model exhibited exceptional diagnostic performance, achieving AUCs of 0.97 in both the internal and external validation sets. Moreover, the implementation of this ensemble model substantially improved the diagnostic precision and reliability of sonographers. The sonographers' average AUC improved by 11 % in the internal validation set and by 7.7 % in the external validation set.

The ensemble model significantly enhances preoperative ovarian cancer diagnosis accuracy and improves sonographers' diagnostic capabilities and consistency.

Tumors are among the most predominant health problems in the world, and the annual incidence of cancer is increasing globally; therefore, there is an urgent need to identify effective therapeutic targets. Chloride intracellular channel 4 (CLIC4) belongs to the family of chloride intracellular channels (CLICs), which are widely expressed in various tissues and organs, such as the brain, lung, pancreas, colorectum, and ovary, and play important roles in promoting apoptosis, promoting angiogenesis, maintaining normal proliferation of endothelial cells, and regulating the assembly and reconstruction of the cytoskeleton. The expression and function of CLIC4 in tumors varies. It has been reported that CLIC4 is low expressed in gastric cancer, skin cancer and prostate cancer, suggesting a tumor suppressor role. Interestingly, CLIC4 is overexpressed in pancreatic, ovarian and breast cancers, indicating a cancer-promoting role. CLIC4 expression is dysregulated in some solid tumors, which may be because CLIC4 is involved in the growth, migration or invasion of some cancer cells through various mechanisms. Regulation of CLIC4 expression may be a potential therapeutic strategy for some tumors. CLIC4 may be a promising therapeutic target and a biomarker for some cancers. In this study, we review the role of CLIC4 in several cancers and its value in the diagnosis and treatment of tumors.

This study aims to analyze the factors associated with the lack of carbohydrate antigen 125 (CA-125) elevation in cases of acute heart failure (HF) decompensation. This retrospective study was conducted on 3167 consecutive patients admitted for acute HF in the cardiology department of a referral hospital (June 2019 to June 2024). Admissions from outpatient clinics (n: 1018) and transfers from other hospitals (n: 752) were excluded. The variables of interest included clinical, echocardiographic, therapeutic, and analytical factors. Low CA-125 levels were defined as values ≤ 50 U/mL. A total of 1397 patients were included, of whom 515 had normal CA-125 levels and 882 had elevated levels. Clinically, independent predictors of low CA-125 were sinus rhythm on electrocardiogram (OR: 1.42, 95% CI: 1.12-1.64; p: 0.003) and sleep apnea-hyponpnea syndrome (OR: 1.76, 95% CI: 1.15-2.70; p: 0.009). Echocardiographically, inferior vena cava collapse greater than 50% with inspiration was associated with low CA-125 (OR: 1.78, 95% CI: 1.19-2.69; p = 0.005), as well as with non-severe right ventricular dysfunction. (OR: 2.42; IC95%: 1.39-4.20; p: 0.002). Analytically, elevated NT-proBNP levels were associated with elevated CA-125 levels (OR: 0.99; IC95%: 0.99-0.99; p: 0.006). Survival was higher in the group with CA-125 ≤ 50 U/mL (p: 0.019). Conversely, as CA-125 values increased, mortality also rose. In conclusion, the absence of CA-125 elevation in patients admitted for acute HF is associated with sinus rhythm, sleep apnea-hyponpnea syndrome, low NT-proBNP levels, and inferior vena cava collapse greater than 50% with inspiration.

To analyze long-term trends of the incidence and mortality of ovarian cancer in the United States.

Patients diagnosed with ovarian cancer were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2017. Joinpoint regression analysis was used to analyze the incidence and mortality trend, and the changes were reported as average annual percentage change (AAPC) with a 95% confidence interval (CI). Kaplan-Meier survival curve and Cox regression analyses were utilized for survival analysis.

A total of 74 682 patients were included, among whom 49 491 (66.27%) died and 44 487 (59.57%) died from ovarian cancer. The mean age was 61.95 ± 15.23 years. The incidence of ovarian cancer showed a decreased trend from 2000 to 2017 with an AAPC of -1.9 (95%CI: -2.0, -1.7). Both the overall mortality and cancer-specific mortality for ovarian cancer decreased from 2000 to 2017, with AAPCs of -5.0 (95%CI: -5.7, -4.2) and -4.6 (95%CI: -5.4, -3.8), respectively. There was a significant decrease in the incidence and mortality of patients with the distant SEER stage, histological subtypes of serous and malignant Brenner carcinoma, and grades II and III from 2000 to 2017. Older age, Black race, histological subtypes of carcinosarcoma, higher tumor grade, and radiotherapy were associated with poorer overall survival and cancer-specific survival, whereas higher income, histological subtype of endometrioid, and surgery were associated with better survival.

This study provided evidence of a statistically significant decrease in the incidence and mortality of ovarian cancer from 2000 to 2017. Key message What is already known on this topic?  Ovarian cancer is one of the most common tumors in women, with high morbidity and mortality. However, trends in long-term morbidity and mortality of patients with ovarian cancer have not been reported. What this study adds  Overall incidence and mortality for ovarian cancer showed a decreased trend from 2000 to 2017, and trends in incidence and mortality varied by stage, histological subtype, and tumor grade. Factors associated with overall survival and cancer-specific survival also differ. How this study might affect research, practice, or police  This study provides evidence of long-term trends in ovarian cancer incidence and mortality from 2000 to 2017.

Serum miRNAs are potential biomarkers for ovarian cancer; however, many factors may influence miRNA expression. To understand potential confounders in miRNA analysis, we examined how sociodemographic factors and comorbidities, including known ovarian cancer risk factors, influence serum miRNA levels in women without ovarian cancer.

Data from 1,576 women from the Mass General Brigham Biobank collected between 2012 and 2019, excluding subjects previously or subsequently diagnosed with ovarian cancer, were examined. Using a focused panel of 179 miRNA probes optimized for serum profiling, miRNA expression was measured by flow cytometry using the Abcam FirePlex assay and correlated with subjects' electronic medical records.

The study population broadly reflected the New England population. The median age of subjects was 49 years, 34% were current or prior smokers, 33% were obese (body mass index > 30 kg/m2), 49% were postmenopausal, and 11% had undergone prior bilateral oophorectomy. Significant differences in miRNA expression were observed among ovarian risk factors such as age, obesity, menopause, BRCA1 or BRCA2 germline mutations, or existence of breast cancer in family history. Additionally, miRNA expression was significantly altered by prior bilateral oophorectomy, hypertension, and hypercholesterolemia. Other variables, such as smoking; parity; age at menarche; hormonal replacement therapy; oral contraception; breast, endometrial, or colon cancer; and diabetes, were not associated with significant changes in the panel when corrected for multiple testing.

Serum miRNA expression patterns are significantly affected by patient demographics, exposure history, and medical comorbidities.

Understanding confounders in serum miRNA expression is important for refining clinical assays for cancer screening.

Ovarian cancer is frequently occurring and fatal for women. CA-125 is important in the screening, diagnosis, and treatment of ovarian cancer. This review study was conducted to explore the influence of CA-125 in addressing ovarian cancer.

To investigate the role of CA-125 in ovarian cancer, we conducted a comprehensive search for high-quality articles in the Medline, Web of Science Core Collection and Scopus databases using the keywords "ovarian cancer," "ovarian carcinoma," "ovarian neoplasms," and "CA-125" from the 2000 to 2024. We included full-text, peer-reviewed articles in English with relevant keywords published since 2000. We excluded case reports, commentaries, letters to the editor, books, case series, systematic reviews, animal studies, and articles that were not accessible in full text.

After screening the 7947 records, 88 studies were included in this review. In the literature review, it was found that researchers utilized CA-125 for diagnosing ovarian cancer, its predicting, evaluating treatment response, assessing ovarian cancer survival, and early detection of recurrence. In some cases, researchers employed additional tumor markers alongside CA-125 to enhance the test's sensitivity.

CA-125 has become a pivotal marker for ovarian cancer. Its role in the diagnosis, treatment, and ongoing assessment of ovarian cancer cannot be overstated. Continuous monitoring of CA-125 levels can provide comprehensive insights, and categorizing patients as low-risk or high-risk based on CA-125 levels could lead to better outcomes. Integrating CA-125 with other biomarkers may enhance the accuracy of the test and elevate its relevance in patient care.

Extracellular vesicles (EVs), as cell-derived small vesicles, facilitate intercellular communication within the tumor microenvironment (TME) by transporting biomolecules. EVs from different sources have varied contents, demonstrating differentiated functions that can either promote or inhibit cancer progression. Thus, regulating the formation, secretion, and intake of EVs becomes a new strategy for cancer intervention. Advancements in EV isolation techniques have spurred interest in EV-based therapies, particularly for tumor immunotherapy. This review explores the multifaceted functions of EVs from various sources in tumor immunotherapy, highlighting their potential in cancer vaccines and adoptive cell therapy. Furthermore, we explore the potential of EVs as nanoparticle delivery systems in tumor immunotherapy. Finally, we discuss the current state of EVs in clinical settings and future directions, aiming to provide crucial information to advance the development and clinical application of EVs for cancer treatment.

Background/Objectives: The prognosis of endometriosis-related ovarian clear cell carcinoma (OCCC) versus non-endometriosis-associated OCCC remains unclear. We examined the impact of endometriosis on OCCC diagnosis and progression and assessed whether prior surgical intervention for endometriotic ovarian cysts affects prognosis. Methods: In this retrospective study (2006-2024), OCCC patients were classified as non-endometriosis-associated or endometriosis-related. A subgroup analysis compared endometriosis-related OCCC patients with and without a history of endometriotic ovarian cyst surgery. Results: The average CA-125 level was 104.20 (29.90, 347.70) in the non-endometriosis-associated OCCC group and 80.70 (32.40, 247.90) in the endometriosis-related OCCC group (p = 0.32). Early-stage diagnosis occurred in 62.77% and 75.21% of these groups, respectively (p = 0.046). The average age at diagnosis was 53.95 ± 9.71 years for the non-endometriosis-associated group and 45.68 ± 7.98 years for the endometriosis-related group (p < 0.001). Mortality or poor prognosis was observed in 24.11% and 17.80% of these groups, respectively (p = 0.226). In endometriosis-related OCCC, comparisons were made between patients with and without a history of endometriotic ovarian cyst surgery. The average age at diagnosis was 45.84 ± 8.24 years for those without a surgical history and 44.71 ± 6.35 years for those with a surgical history (p = 0.59). Early-stage diagnosis was observed in 77.23% and 62.50%, respectively (p = 0.339). Mortality or poor prognosis occurred in 14.85% of those without a surgical history and 35.29% of those with a surgical history (p = 0.008). The hazard ratio for women with a surgical history was 3.48 (1.29-8.69) (p = 0.008). The incidence rate was 3.17 per 1000 person-years (PYRs) for individuals without surgery and 13.36 per 1000 PYRs for those with a history of surgical intervention (p = 0.008). Conclusions: Endometriosis did not impact the prognosis of women with OCCC. However, women with endometriosis-related OCCC were diagnosed at earlier stages and at younger ages. A history of endometriotic ovarian cyst surgery did not influence OCCC detection but was linked to poorer survival outcomes.

The existing drugs for ovarian cancer (OC) are unsatisfactory and thus new drug targets are urgently required. We conducted proteome-wide Mendelian randomization (MR) and colocalization analysis to pinpoint potential targets for OC.

Data on protein quantitative trait loci (pQTL) for 734 plasma proteins were obtained from large genome-proteome-wide association studies. Genetic associations with OC were derived from the Ovarian Cancer Association Consortium, which included 25,509 cases and 40,941 controls. MR analysis was performed to evaluate the association between the proteins and the OC risk. Colocalization analysis was conducted to check whether the identified proteins and OC shared causal variants. In addition, the phenome-wide MR analysis was performed to clarify protein associations across the phenotype, and drug target databases were examined for target validation.

Genetically predicted circulating levels of 44 proteins were associated with OC risk at Benjamini-Hochberg correction. Genetically predicted 17 proteins had evidence of the increased risk of OC (CLEC11A, MFAP2, TYMP, PDIA3, IL1R1, SPINK1, PLAU, DKK2, IL6ST, DLK1, LRRC15, CDON, ANGPTL1, SEMA4D, AKR1A1, TNFAIP6, and FCGR2B); 27 proteins decreased the risk of OC(SIGLEC9, RARRES1, SPINT3, TMEM132A, HAVCR2, CNTN2, TGFBI, GSTA1, HGFAC, TREML2, GRAMD1C, ASAH2, CPNE1, CCL25, MAPKAPK2, POFUT1, PREP, NTNG1, CA10, CACNA2D3, CA8, MAN1C1, MRC2, IL10RB, RBP4, GP5 and CALCOCO2). Bayesian colocalization demonstrated that GRAMD1C, RBP4, PLAU, PDIA3, MFAP2, POFUT1, MAN1C1 and DKK2 shared the same variant with OC. The phe-MR analyses assessed the side effects of these 44 identified proteins, and the drug target database offered information on both approved and investigational indications.

This study provides proof of a causal relationship between genetically predicted 44 proteins associated with OC risk, which could serve as promising drug targets for OC.

In this study, the influence of glycoproteomic changes, specifically MUC16, on NK cell-mediated immunotherapy response in ovarian cancer is explored. Analysis of glycoprotein data from the CPTAC database identified significant upregulation of MUC16 in ovarian cancer tissues, associated with tumor invasiveness and immune evasion. Experimental findings showed that MUC16 knockdown increased NK cell cytotoxicity, decreased invasiveness, and boosted NK cell activation, while MUC16 overexpression resulted in the opposite effects. In vivo experiments demonstrated that MUC16 knockdown suppressed tumor growth, enhanced NK cell infiltration, and bolstered NK cell activation, underscoring the potential of MUC16 as a target for novel immunotherapy approaches in ovarian cancer treatment.

Uterine adenomyosis, a common benign tumor disease in gynecology, mainly manifested as chronic pelvic pain, menstrual disorders, dysmenorrhea, etc., has a great impact on patients' daily life and work. Compared with traditional surgery and drug therapy, uterine artery embolization (UAE), as a new treatment with less trauma, faster recovery and uterine preservation, can relieve pain while preserving normal physiological and reproductive functions of the uterus, which is favored by the majority of patients. In this study, the patients were divided into two groups based on magnetic resonance imaging (MRI) test. Their serum CA125 level was detected, and the degree of symptom relief and health index were evaluated, aiming to explore the clinical efficacy and influencing factors of UAE in the treatment of adenomyosis. The results showed that before UAE, CA125 level in group B was significantly higher than that in group A, and 2 days after UAE, CA125 level in both groups was lower than before treatment, indicating that the serum CA125 level may be related to the type of adenomyosis, but UAE has a good therapeutic effect on both focal and diffuse adenomyosis. 3 months after interventional treatment, the patients had significantly reduced symptoms with dramatically improved health status and the VAS pain score was significantly reduced, indicating that UAE can significantly improve the clinical symptoms of patients with adenomyosis. Uterine artery embolization was performed in both groups. No serious complications occurred during the operation, and the technical success rate reached 100%. In summary, UAE, as a minimally invasive treatment, has obvious and significant clinical effects in the treatment of adenomyosis, and is an important alternative treatment for adenomyosis.

Background: Ovarian cancer (OC) is the third most common and second most lethal onco-gynecological disease in the world, with high-grade serous ovarian cancer (HGSOC) making up the majority of OC cases worldwide. The current serological biomarkers used for OC diagnosis are lacking sensitivity and specificity, thus new biomarkers are greatly needed. Recently, the chromatin remodeling complex gene ARID1A, Notch and Wnt pathway gene expression, as well as HOX-related gene promoter methylation have been linked with promoting OC. Methods: In this pilot study, 10 gene expression biomarkers and 4 promoter methylation biomarkers were examined as potential diagnostic and prognostic indicators of OC in 65 fresh-frozen gynecologic tumor tissues. Results: Out of 10 genes analyzed, the expression of eight biomarkers was significantly reduced in OC cases compared to benign, and HOX-related gene promoter methylation significantly increased in OC tumors. Out of 14 biomarkers, CTNNB1 showed the best single biomarker separation of HGSOC from benign cases (AUC = 0.97), while a combination of the seven Notch pathway-related gene expressions (NOTCH1, NOTCH2, NOTCH3, NOTCH4, DLL1, JAG2, and HES1) demonstrated the best separation of HGSOC from the benign cases (AUC = 1). Conclusions: The combination of multiple gene expression or gene promoter methylation biomarkers shows great promise for the development of an effective biomarker-based diagnostic approach for OC.

Ovarian cancer, particularly high-grade serous ovarian cancer (HGSOC), is the most lethal gynecological tumor, with most patients experiencing recurrence within 5 years. Long-term survival in HGSOC patients with advanced stages is exceedingly rare.

We report a case of advanced HGSOC with exceptional long-term recurrence-free survival following initial treatment. In June 2009, the patient underwent suboptimal cytoreductive surgery for stage IIIC ovarian cancer, including total hysterectomy, bilateral salpingo-oophorectomy, omentectomy, appendectomy, and resection of mesenteric and peritoneal lesions. Postoperatively, residual lesions were observed in the mesenteries and para-aortic lymph nodes. Despite unfavorable prognostic factors (advanced stage, aggressive pathology, and incomplete resection), the patient showed remarkable chemosensitivity, remaining recurrence-free for 15 years.

The factors influencing long-term survival in HGSOC patients are not yet fully understood. We present this rare case to contribute data for further studies on long-term survival in advanced HGSOC.

Women with low-risk endometrial cancer, as defined by the Korean Gynecologic Oncology Group (KGOG) criteria, have a low risk of lymph node metastasis and an excellent prognosis without lymphadenectomy. However, it is unclear whether lymphadenectomy should be performed in premenopausal women who meet the KGOG criteria other than elevated cancer antigen 125 (CA125) levels, because the CA125 level can be elevated by benign conditions. We investigated the patterns of metastasis and recurrence to assess the value of lymphadenectomy in this population.

Premenopausal women with endometrial cancer meeting the KGOG criteria, except for those with elevated CA125 levels, were eligible. The characteristics of the eligible women were collected from seven institutes in the Republic of Korea by reviewing their medical records. Recurrence-free survival (RFS) was estimated using the Kaplan-Meier method and compared using the log-rank test.

Seventy-three patients were included. Of 62 women who underwent lymphadenectomy, only two (3.2%) had lymph node metastasis. Eighteen women (24.7%) received adjuvant therapy. At a median follow-up of 59 months, the 5-year RFS was 88.8%. Five women (7%) experienced recurrence, two had lymph node recurrence, and three had non-nodal recurrence. RFS was similar between the women who did and did not undergo lymphadenectomy (P=0.737).

Premenopausal women who had elevated CA125 levels but met all other KGOG criteria showed a low risk of lymph node metastasis and recurrence as well as a good prognosis. Therefore, lymphadenectomy can be omitted in this population.

This study aimed to evaluate the efficacy and safety of pegylated liposomal doxorubicin (PLD) for patients with partially platinum-sensitive, platinum-resistant, or platinum-refractory ovarian cancer.

Patients with partially platinum-sensitive, platinum-resistant, or platinum-refractory ovarian cancer were recruited in this prospective, open-label, single-arm, multicenter study. Eligible patients were given 4-6 cycles of PLD (40 mg/m2 on day 1, every 4 weeks). The primary endpoint was progression-free survival (PFS). Secondary endpoints were overall survival (OS), objective response rate (ORR), disease control rate (DCR), quality of life, and safety. Exploratory endpoints included the change trend of CA125 and platinum-free interval.

Between June 2017 and November 2020, 167 eligible patients were included in the full analysis set. The median PFS and OS were 6.8 months (95% CI, 4.4-9.3 months) and 19.1 months (95% CI, 15.0-23.3 months), respectively. The ORR and DCR were 32.3% and 60.5%, respectively. The ORR (62.3 vs 22.5%) and DCR (84.9 vs 60.7%) of patients with a CA125 decrease after the first cycle were significantly higher than those without a CA125 decrease (all P < .05). Grade ≥ 3 and serious adverse events were reported in 9.9% and 3.9% of patients, respectively. No treatment-related death was observed.

PLD showed promising efficacy and manageable tolerability in patients with partially platinum-sensitive, platinum-resistant, or platinum-refractory ovarian cancer.ClinicalTrials.gov Identifier: Chinese Clinical Trial Registry, ChiCTR1900022962.

MUC16/CA125 is a common diagnostic marker for many types of cancer. However, due to the widespread expression of MUC16 in cancer, its specificity and sensitivity as a target are poor, which severely limits its clinical application. In recent years, various studies have shown that the clinical application potential of MUC16/CA125 has been greatly improved. The update of detection technology improves the accuracy and range of detection, and improves the early diagnosis rate of cancer. Targeting MUC16/CA125 is an important strategy for tumor therapy. Targeting residual amino acids, n-glycoylation structures or other targets on the surface of MUC16 cells can greatly improve the accuracy of detection and therapy. The new drug delivery method broke through the original technical shackles, targeted MUC16 positive cells more specifically and improved the drug efficacy. In this paper, the technological advances in detecting and identifying MUC16 targets and the great progress in cancer screening and treatment based on MUC16 as a target are described in detail, revealing the great potential of MUC16 as a target in cancer screening and treatment, and illustrating the potential clinical application value of MUC16.

The HOX gene family encodes for regulatory transcription factors that play a crucial role in embryogenesis and differentiation of adult cells. This highly conserved family of genes consists of thirty-nine genes in humans that are located in four clusters, A-D, on different chromosomes. While early studies on the HOX gene family have been focused on embryonic development and its related disorders, research has shifted to examine aberrant expression of HOX genes and the subsequent implication in cancer prediction and progression. Due to their role of encoding master regulatory transcription factors, the abnormal expression of HOX genes has been shown to affect all stages of tumorigenesis and metastasis. This review highlights the novel role of the HOX family's clinical relevance as both prognostic and diagnostic biomarkers in hematological and solid tumors.

Genomic analysis has played a significant role in the identification of driver mutations that are linked to disease progression and response to drug treatment in ovarian cancer. A prominent example is the stratification of epithelial ovarian cancer (EOC) patients with homologous recombination deficiency (HRD) characterized by mutations in DNA damage repair genes such as BRCA1/2 for treatment with PARP inhibitors. However, recent studies have shown that some epithelial ovarian tumors respond to PARP inhibitors irrespective of their HRD or BRCA mutation status. An exclusive focus on the genome overlooks the significant insight that can be gained from other biological analytes, including proteins, which carry out cellular functions. Proteogenomics is the integration of genomics, transcriptomics, epigenomics and proteomics data. This review paper provides novel insight into the role of proteogenomics as an analytical approach to identify predictive biomarkers of drug treatment response in epithelial ovarian cancer. Proteogenomic analysis can facilitate the identification of predictive biomarkers of drug treatment response, consequently greatly improving the stratification of patients with EOC for treatment towards a goal of personalized medicine.

Extracellular vesicles (EVs), crucial mediators in cell-to-cell communication, are implicated in both homeostatic and pathological processes. Their detectability in easily accessible peripheral fluids like saliva positions them as promising candidates for non-invasive biomarker discovery. However, the lack of standardized methods for salivary EVs isolation greatly limits our ability to study them. Therefore, we rigorously compared salivary EVs isolated using two scalable techniques-co-precipitation and immuno-affinity-against the long-established but labor-intensive ultracentrifugation method. Employing Cryo-Electron Microscopy (Cryo-EM), Nanoparticle Tracking Analysis, Western blots (WB), and proteomics, we identified significant method-dependent variances in the size, concentration, and protein content of EVs. Importantly, our study uniquely demonstrates the ability of EV isolation to detect specific biomarkers that remain undetected in whole saliva by WB. RT-qPCR analysis targeting six miRNAs confirmed a consistent enrichment of these miRNAs in EV-derived cargo across all three isolation methods. We also found that pre-filtering saliva samples with 0.22 or 0.45 µm pores adversely affects subsequent analyses. Our findings highlight the untapped potential of salivary EVs in diagnostics and advocate for the co-precipitation method as an efficient, cost-effective, and clinically relevant approach for small-volume saliva samples. This work not only sheds light on a neglected source of EVs but also paves the way for their application in routine clinical diagnostics.

This study explores the application of serum biomarkers in the diagnosis of adenomatous polyps and evaluates the effectiveness of different markers and their combined diagnosis in adenomatous polyp detection. Using receiver operating characteristic curve analysis, this study assessed the efficacy of serum biomarkers such as carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), alpha-fetoprotein (AFP), carbohydrate antigen 199 (CA199), and prothrombin time (PT) in diagnosing adenomatous polyps in 90 patients. The study also compared the diagnostic accuracy of individual tests versus combined diagnostic approaches and analyzed the impact of polyp size and number on the levels of these markers. Among the individual tests, CA125 showed relatively high diagnostic efficacy. However, combined diagnostic approaches, such as the combination of CEA and CA125, the trio of CEA, CA125, and AFP, and the quartet of CEA, CA125, AFP, and PT, significantly improved diagnostic sensitivity and specificity. Additionally, the study found that the size and number of adenomatous polyps significantly influenced the levels of CEA, CA125, CA199, and PT, with larger and more numerous polyps associated with higher marker levels. This study demonstrates that combined diagnostic strategies have significant advantages in diagnosing adenomatous polyps, providing more accurate and comprehensive diagnostic information. Furthermore, the impact of polyp size and number on serum biomarker levels suggests that these clinical factors should be considered in clinical assessments. These findings offer new perspectives and approaches for the diagnosis of adenomatous polyps.

This study aimed to identify unique characteristics in the peripheral blood mononuclear cells (PBMCs) of endometriosis patients and develop a non-invasive early diagnostic tool. Using single-cell RNA sequencing (scRNA-seq), we constructed the first single-cell atlas of PBMCs from endometriosis patients based on 107,964 cells and 25,847 genes. Within CD16+ monocytes, we discovered JUP as a dysregulated gene. To assess its diagnostic potential, we measured peritoneal fluid (PF) and serum JUP levels in a large cohort of 199 patients including 20 women with ovarian cancer (OC). JUP was barely detectable in PF but was significantly elevated in the serum of patients with endometriosis and OC, with levels 1.33 and 2.34 times higher than controls, respectively. Additionally, JUP was found in conditioned culture media of CD14+/CD16+ monocytes aligning with our scRNA-seq data. Serum JUP levels correlated with endometriosis severity and endometrioma presence but were unaffected by dysmenorrhea, menstrual cycle, or adenomyosis. When combined with CA125 (cancer antigen 125) JUP enhanced the specificity of endometriosis diagnosis from 89.13% (CA125 measured alone) to 100%. While sensitivity remains a challenge at 19%, our results suggest that JUP's potential to enhance diagnostic accuracy warrants additional investigation. Furthermore, employing serum JUP as a stratification marker unlocked the potential to identify additional endometriosis-related genes, offering novel insights into disease pathogenesis.

It remains unclear whether extracting peritumoral volume (PTV) radiomics features are useful tools for evaluating response to chemotherapy of epithelial ovarian cancer (EOC).

To evaluate MRI radiomics signatures (RS) capturing subtle changes of PTV and their added evaluation performance to whole tumor volume (WTV) for response to chemotherapy in patients with EOC.

Retrospective.

219 patients aged from 15 to 79 years were enrolled.

3.0 or 1.5T, axial fat-suppressed T2-weighted imaging (FS-T2WI), diffusion-weighted imaging (DWI), and contrast enhanced T1-weighted imaging (CE-T1WI).

MRI features were extracted from the four axial sequences and six different volumes of interest (VOIs) (WTV and WTV + PTV (WPTV)) with different peritumor sizes (PS) ranging from 1 to 5 mm. Those features underwent preprocessing, and the most informative features were selected using minimum redundancy maximum relevance and least absolute shrinkage and selection operator to construct the RS. The optimal RS, with the highest area under the curve (AUC) of receiver operating characteristic was then integrated with independent clinical characteristics through multivariable logistic regression to construct the radiomics-clinical model (RCM).

Mann-Whitney U test, chi-squared test, DeLong test, log-rank test. P < 0.05 indicated a significant difference.

All the RSs constructed on WPTV exhibited higher AUCs (0.720-0.756) than WTV (0.671). Of which, RS with PS = 2 mm displayed a significantly better performance (AUC = 0.756). International Federation of Gynecology and Obstetrics (FIGO) stage was identified as the exclusive independent clinical evaluation characteristic, and the RCM demonstrated higher AUC (0.790) than the RS, but without statistical significance (P = 0.261).

The radiomics features extracted from PTV could increase the efficiency of WTV radiomics for evaluating the chemotherapy response of EOC. The cut-off of 2 mm PTV was a reasonable value to obtain effective evaluation efficiency.

4 TECHNICAL EFFICACY: Stage 2.

Ovarian cancer is one of the predominant gynecologic malignancies worldwide, ranking as the fifth leading cause of cancer-induced mortality among women globally. Post-translational modifications (PTMs) refer to the enzyme-catalyzed attachment of functional groups to proteins, thereby inducing structural and functional alterations. Recent evidence suggests that PTMs play multifaceted roles in the pathogenesis of ovarian cancer, influencing processes such as cell cycle, metabolism reprogramming, chemoresistance, and immune responses against cancer. Accordingly, a comprehensive understanding of the diverse PTMs in ovarian cancer is imperative for decoding the complex molecular mechanisms that drive cancer progression. This review discusses the latest developments in the study of protein PTMs in ovarian cancer and introduces pharmacological approaches that target these modifications as therapeutic strategies.

Pyruvate dehydrogenase kinase 1 (PDK1) is a new therapeutic target that is dysregulated in multiple tumors. This study aims to explore the potential role and regulatory mechanism of PDK1 in epithelial ovarian cancer (EOC). We detect PDK1 expression in EOC tissues and cells using qRT-PCR and western blot analysis, and the effects of PDK1 on EOC cell malignant behaviors are explored. RNA sequencing analyses are performed to explore the differentially expressed genes in PDK1-silenced EOC cells. Furthermore, tumor-bearing mouse models are established to assess the impacts of PDK1 and BGN on EOC tumor growth and metastasis in vivo. The results show that PDK1 is upregulated in EOC tissues and cell lines. Biglycan (BGN) is downregulated in PDK1-silenced EOC cells, and its expression is positively correlated with PDK1 levels in EOC tissues. PDK1 depletion inhibits EOC cell proliferation, migration and invasion. Mechanistically, PDK1 and BGN are colocalized in the cytoplasm of EOC cells and interact with each other. PDK1 positively regulates BGN expression by enhancing BGN mRNA stability. BGN overexpression partially reverses the anti-tumor effects of PDK1 depletion on EOC cell malignant behaviors. PDK1 has also been revealed to upregulate BGN to activate the NF-κB oncogenic pathway in EOC cells. Additionally, PDK1 accelerates tumor growth and metastasis by modulating BGN expression. In conclusion, PDK1 functions as an oncogene, facilitating EOC progression by upregulating BGN and activating the NF-κB pathway. These findings may provide valuable biomarkers for the diagnosis and treatment of EOC.

Background: Cuproptosis is a copper-induced mitochondrial cell death, and regulating cuproptosis is becoming a rising cancer treatment modality. Here, we attempted to establish a cuproptosis-associated lncRNAs (CRLs) signature (CRlncSig) to predict the survival, immune landscape, and treatment response in ovarian cancer (OC) patients. Methods: A series of statistical analyses were used to identify the key CRLs that are closely related to the prognosis, and a prognostic CRlncSig was constructed. The predictive accuracy of the CRlncSig was further validated in an independent Gene Expression Omnibus (GEO) set. Then, we compared the immune cell infiltration, immune checkpoints, tumor microenvironment (TME), tumor mutational burden (TMB), drug sensitivity, and efficacy of immunotherapy between the two subgroups. We further built a nomogram integrating the CRlncSig and different clinical traits to enhance the clinical application of the CRlncSig. Results: Nine hub CRLs, namely RGMB-AS1, TYMSOS, DANCR, LINC00702, LINC00240, LINC00996, DNM1P35, LINC00892, and TMEM254-AS1, were correlated with the overall survival (OS) of OC and a prognostic CRlncSig was established. The CRlncSig classified OC patients into two risk groups with strikingly different survival probabilities. The time-dependent ROC (tdROC) curves demonstrated good predictive ability in both the training cohort and an independent validation cohort. Multivariate analysis confirmed the independent predictive performance of the CRlncSig. We constructed a nomogram based on the CRlncSig, which can predict the prognosis of OC patients. The high-risk score was characterized by decreased immune cell infiltration and activation of stroma, while activation of immunity was observed in the low-risk subgroup. Moreover, patients in low-risk subgroups had more Immunophenoscore (IPS) and fewer immune escapes compared to high-risk subgroups. Finally, an immunotherapeutic cohort confirmed the value of the CRlncSig in predicting immunotherapy outcomes. Conclusions: The developed CRlncSig may be promising for the clinical prediction of OC patient outcomes and immunotherapeutic responses.

As a prevalent malignancy in women, ovarian cancer (OC) presents a challenge in clinical practice because of its poor prognosis and poor therapeutic efficacy. The mechanism by which cuproptosis activity is accompanied by immune infiltration in OC remains unknown. Here, we investigated cuproptosis-related OC subtypes and relevant immune landscapes to develop a risk score (RS) model for survival prediction.

Cuproptosis-related genes (CRGs) were identified to construct molecular subtypes via an unsupervised clustering algorithm based on the expression profiles of survival-related CRGs in the GEO database. Single-cell datasets were used to estimate immune infiltration among subtypes. The RS oriented from molecular subtypes was developed via LASSO Cox regression in the TCGA OC dataset and independently validated in the GEO and TCGA datasets. Hub markers from RS were identified in tissues and cell lines. The function of the key gene from RS was identified in vitro.

We investigated cuproptosis activity and immune infiltration to establish three clinical subtypes of OC based the differentially expressed genes (DEGs) from CRGs to create an RS model validated for clinical efficacy and prognosis. Six hub genes from the RS served as ongenic markers in OC tissues and cell lines. The function of GAS1 in the RS model revealed that it exerts oncogenic effects.

Our study provides a novel RS model including 6 hub genes associated with cuproptosis and immune infiltration to predict OC prognosis as well as clinical efficacy.