To investigate trends in surgical experience performing pelvic and paraaortic lymphadenectomies by gynecologic oncology (GO) fellows in the U.S. Summary statistics for ACGME GO training programs were obtained from the ACGME public reporting system. The ACGME data only contains this short time frame. For each academic year spanning 2019-2020 through 2024-2025, the national mean procedure count was extracted for pelvic and paraaortic lymphadenectomies. Over the past 5 years there has been a significant decline in the number of pelvic (p = 0.0004) and paraaortic (p = 0.002) lymphadenectomies being performed by GO fellows in the U.S. During this same time there was a progressive significant upward trend in the number of SNL performed (p = 0.003). The mean procedure count declined from 61 to 38 on pelvic and 36 to 18 on para-aortic and SLN increased from 63 to 96. Gynecologic oncology training experience in performing both pelvic and paraaortic lymphadenectomy has declined. The decline may have implications that extend to training in radical pelvic surgery.
The treatment of gynecologic malignancies has moved towards a precision medicine model with an approach to prognostication and management based on biomarker testing. The objective of this review is to describe the current landscape of biomarker testing in gynecologic cancer including clinical implications and the approach to testing. A review of the literature was performed that included published clinical trials which utilized biomarker testing as part of inclusion/exclusion criteria, prospective trials that addressed the application and scoring of biomarkers utilized in gynecologic cancers, prospective clinical trials that utilized biomarker findings to determine management, and national or society guidelines for the scoring of biomarkers and treatment of gynecologic cancers. The use of biomarker testing as part of the management of gynecologic cancers is the standard of care for both treatment and prognostication. In endometrial cancer, biomarker testing has been incorporated into the staging system and impacts treatment in both the upfront and recurrent setting. Specific biomarkers of interest for endometrial cancer include estrogen receptor (ER), progesterone receptor (PR), DNA Polymerase Epsilon (POLE), mismatch repair proteins (MMR), and Human Epidermal growth factor Receptor-2 (HER2). In ovarian cancer, biomarker testing is primarily utilized in the recurrent setting to guide management of platinum-resistant ovarian cancer with a specific focus on targeted therapy utilizing antibody drug conjugates (ADCs) and immunotherapy. Immunotherapy has become an important component of therapy for cervical cancer and Programmed death-ligand 1 (PD-L1) testing is a key biomarker in determining treatment. The utilization of appropriate assays and processes to accurately assess the status of biomarkers in the pathology laboratory is crucial to the treatment of gynecologic malignancies in the precision medicine era.
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Background/Objectives: Since non-invasive implants and invasive implants (metastases) are a key point of differentiation between serous borderline tumors (SBTs) and low-grade serous carcinoma (LGSC), the correct diagnosis of these two types of extraovarian lesions is crucial for patient treatment and prognosis. However, accurate diagnosis can be challenging even for experienced pathologists. The aim of this study was to evaluate interobserver agreement in the classification of these extraovarian lesions. Methods: Twenty-four cases of ovarian SBT and LGSC with 33 samples of non-invasive implants of SBT and metastasis of LGSC were independently reviewed by three gynecologic pathologists and three general pathologists. Diagnostic criteria included destructive invasion, micropapillary architecture, and retraction clefts. To measure interobserver agreement, Fleiss' kappa and Cohen's kappa were calculated, with consensus diagnoses determined by the majority of gynecologic pathologists. Results: According to the consensus, diagnosis 42.4% biopsies were classified as metastases of LGSC and 57.6% as non-invasive implants of SBT. Overall reproducibility was substantial (κ = 0.61). The agreement among gynecologic pathologists, as well as between gynecologic pathologists and the consensus (using leave-one-out reference), was substantial to near-perfect (κ = 0.745-0.821). General pathologists' agreement with the consensus was moderate (κ = 0.467-0.698). Agreement between general pathologists was also moderate, with κ values ranging from 0.413 to 0.518. The difference in pairwise agreement between the two groups was statistically significant, confirming that gynecologic pathologists outperformed general pathologists in classifying extraovarian lesions. Conclusions: The results showed that current diagnostic reproducibility remains suboptimal, particularly among general pathologists, underscoring the need for improved training and standardized criteria. Ultimately, a multidisciplinary approach combining morphological expertise, immunohistochemical validation and molecular stratification will be essential for optimizing diagnosis and treatment.
Financial toxicity is increasingly recognized as a consequential dimension of cancer care, yet multicenter evidence in China remains limited for patients with gynecologic cancers undergoing radiotherapy, a treatment pathway that often entails repeated visits and substantial non-medical costs. This study estimated the prevalence and severity of financial toxicity and examined its association with quality of life and psychological distress. A multicenter cross-sectional survey was conducted in three tertiary hospitals in China, led by West China Second University Hospital, Sichuan University. Adult patients with gynecologic cancers receiving external beam radiotherapy and or brachytherapy with definitive, adjuvant, or curative-intent salvage or consolidation intent were consecutively recruited. Financial toxicity was assessed using the COmprehensive Score for financial Toxicity (COST, 0 to 44; lower scores indicate worse toxicity). Quality of life was measured using the EORTC QLQ-C30, and psychological distress using the Distress Thermometer (DT, 0 to 10; clinically significant distress defined as DT ≥ 4). Multivariable regression models included hospital fixed effects to account for measured differences across centers and adjusted for sociodemographic, access-burden, and clinical covariates. Among 1,533 returned questionnaires, 1,303 were valid and analyzed (85.0%). Mean COST score was 21.6 (SD 7.4); 17.5% had severe financial toxicity (COST ≤ 14), 48.0% moderate (15 to 24), and 34.5% mild (≥25). Mean QLQ-C30 global health status was 61.3 (SD 14.2). Mean DT score was 4.3 (SD 2.1), and 65.2% met criteria for clinically significant distress. In adjusted analyses, each 5-point decrease in COST was associated with lower global health status (β -4.17, 95% CI -4.62 to -3.72), lower emotional functioning (β -4.68, 95% CI -5.20 to -4.16), higher fatigue (β 4.47, 95% CI 3.93 to 5.01), and higher DT score (β 0.32, 95% CI 0.23 to 0.40), all p < 0.001. Each 5-point decrease in COST was associated with higher odds of clinically significant distress (OR 1.34, 95% CI 1.22 to 1.47; p < 0.001). Financial toxicity was common among gynecologic radiotherapy patients in China and was independently associated with poorer quality of life and higher psychological distress. Integrating financial toxicity screening with supportive care pathways during radiotherapy may help identify high-risk patients and guide targeted assistance.
Accurate identification of pelvic vascular structures is critical for safe and effective gynecologic cancer surgery, yet intraoperative recognition of the internal iliac artery, its branches, and corresponding venous pathways remains challenging due to complex anatomy and inter-individual variability. This study investigates the feasibility of fully automated, multi-class segmentation of both major pelvic vessels and smaller branches of the internal iliac artery and internal iliac vein using the nnU-Net v2 deep learning framework. Contrast-enhanced computed tomography angiography datasets from 47 patients were used for model training and evaluation. The nnU-Net v2 deep learning framework was employed to perform fully automated segmentation across nine vascular categories. These targets included major vessels, the internal iliac artery and vein, and an "other vessels" category consolidating surgically critical smaller branches, such as the obturator, uterine, and gluteal vessels. Model performance was quantitatively evaluated against ground truth annotations using the Dice Similarity Coefficient and Mean Surface Distance. The model achieved high segmentation accuracy for large-diameter vessels such as the aorta and iliac arteries, with average Dice similarity coefficients exceeding 0.83 for arterial structures and 0.75 for venous structures. Smaller branches exhibited lower overlap scores but maintained anatomically coherent and clinically recognizable patterns, particularly for the obturator and gluteal arteries. These findings demonstrate the potential of automated 3D vascular segmentation to enhance preoperative planning, anatomical education, and intraoperative safety in complex pelvic procedures. Furthermore, this represents the first systematic evaluation of the segmentation of major branches of the internal iliac artery in gynecologic oncology patients.
Disparities in clinical trial enrollment raise concerns about the generalizability of antibody-drug conjugate (ADC) efficacy in gynecologic cancers. We evaluated real-world survival outcomes across demographic subgroups and assessed concordance with pivotal trials, while contextualizing findings within ongoing challenges of underrepresentation. We conducted a cohort study of patients with advanced gynecologic cancers treated with ADCs at a tertiary academic center (June 2019-September 2025). Primary outcomes were overall survival (OS) and progression-free survival (PFS) by age, race, and ethnicity. Secondary objectives examined ECOG performance status, line of therapy, and Area Deprivation Index. Exploratory analyses assessed treatment discontinuation secondary to toxicity. Survival was estimated using Kaplan-Meier methods with univariable and multivariable models. Among 142 patients,105 received mirvetuximab soravtansine (MIRV), 34 trastuzumab deruxtecan (T-DXd), and 16 tisotumab vedotin (TV). Median age was 64.8 years; 66.9% identified as White, 12.7% Asian, 6.3% Black/African American, and 14.1% Other. Most patients were non-Hispanic/Latina (88.7%), while 11.3% identified as Hispanic/Latina. In unadjusted analyses, PFS varied by treatment line in the MIRV cohort (p = 0.04), while OS differed by ethnicity and performance status (p < 0.01). Performance status was also associated with OS in the T-DXd cohort (p = 0.01). These associations were not significant in multivariable models. Treatment discontinuation due to toxicity occurred in 17.6% and did not differ by subgroup. Real-world ADC outcomes were consistent with pivotal trials, with no independent survival differences by subgroup after adjustment. These findings support continued investigation of clinical and structural factors influencing outcomes.
Pelvic radiotherapy (RT) is essential for gynecological cancer; however, it often causes chronic, under-recognized sexual toxicity in survivorship care. We applied a two-part hurdle model to separately evaluate predictors of sexual activity and function in women receiving RT for gynecological cancers. We conducted a retrospective cohort study involving 120 women treated with definitive or adjuvant pelvic RT (external beam radiotherapy [EBRT]-inclusive or vaginal brachytherapy [VBT]-only) for gynecological cancer at a single medical center. The primary outcome was post-treatment sexual function quantified via the 19-item Female Sexual Function Index, while the secondary outcomes included the predictors of sexual activity (binary status defined as any non-zero score on physiological domains) and functional quality (total score) among active women, analyzed using a two-part hurdle model consisting of logistic and beta regressions with a Smithson-Verkuilen transformation. The cohort exhibited a severe floor effect, with 64.2% (77/120) of patients classified as sexually inactive. In the activity hurdle, lubricant use (OR 12.2; 95% CI: 1.66-88.9; P = .01) and multiparity (OR 12.6; 95% CI, 1.74-91.8; P = .01) were associated with continued sexual engagement, whereas age demonstrated an independent negative association (OR 0.89 per year; 95% CI, 0.81-0.99; P = .04). In the functional hurdle, sexually active patients treated with EBRT-inclusive regimens demonstrated significantly lower functional scores compared to the VBT-only cohort (the exponentiated coefficient of β = 0.17; P = .001). Historical comparisons revealed significant deficits across all domains, especially orgasm (P < .001), within the EBRT-inclusive cohort relative to published healthy controls. The management of RT-induced sexual dysfunction requires a tiered approach that prioritizes mechanical lubricants to overcome initial activity barriers, while necessitating rehabilitation strategies to mitigate profound functional deficits and to improve the quality of life for patients requiring EBRT. The main strength is the methodological separation of uncoupling of behavioral engagement hurdles from inherent tissue radiation toxicity; limitations comprise the retrospective design, baseline clinical imbalances between cohorts, and the small number of sexually active patients receiving brachytherapy. Sexual dysfunction following pelvic RT presents as a complex bifurcated phenomenon, wherein sexual engagement is strongly associated with parity-related anatomical factors and mechanical lubricative support, whereas overall functional quality is constrained by exposure to EBRT.
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Early diagnosis of ovarian cancer remains one of the most important unmet needs in gynecologic oncology because survival is strongly stage-dependent and most patients still present with disseminated disease. Conventional non-invasive tools, particularly CA-125, transvaginal ultrasound, and composite triage algorithms, remain clinically useful but are limited by suboptimal sensitivity for stage I disease and by reduced specificity in premenopausal women and in benign inflammatory or endometriosis-associated conditions. Circulating tumor DNA (ctDNA) has therefore emerged as a candidate biomarker capable of extending liquid biopsy beyond conventional serology. In ovarian cancer, however, ctDNA implementation is constrained by low tumor shedding in early-stage disease, marked biologic heterogeneity across histotypes, clonal hematopoiesis-related background noise, and major pre-analytical and analytical sources of variability. This narrative review, informed by structured searches of PubMed, Scopus, and Web of Science, examines the evolving evidence for ctDNA mutations, methylation-based assays, multi-omic platforms, and machine-learning models across three distinct clinical contexts: population screening, preoperative triage of adnexal masses, and post-treatment assessment of molecular residual disease. We also discuss positive predictive value, false-positive harms, health-economic implications, standardization initiatives, and ongoing prospective studies. Overall, current evidence suggests that the most plausible near-term role for liquid biopsy in ovarian cancer is not as a universal stand-alone screening test, but as an integrated component of risk stratification and disease-monitoring frameworks that combine molecular signals with clinicopathologic and imaging data.
Ovarian Cancer (OC), the deadliest gynecological malignancy, poses a major therapeutic challenge in advanced stages owing to its high recurrence rate and metastatic potential. In this regard, it is noteworthy that immunotherapy has recently gained significant attention in OC treatment, a phenomenon attributable to notable advances in over-the-counter Chimeric Antigen Receptor (CAR)-based cell therapy. At the heart of CAR-T Cell (CAR-T) immunotherapy is genetically modified CAR molecules that enable immune cells to target and recognize tumor antigens. Based on such strategies, CAR-T therapies have developed rapidly in hematological oncology and are gradually being extended to solid tumors. Despite their potential in OC treatment, several factors, including off-target effects attributable to the lack of Tumor-Specific Antigens (TSAs), as well as severe side effects such as tumor immune barriers, Cytokine Release Syndrome (CRS), and neurotoxicity, have been established to limit the clinical use of CAR-T therapies. Moreover, compared to CAR-T, CAR-Natural Killer (NK) and CAR-Macrophage (M) therapies have distinct advantages. The killing mechanism of NK cells integrates both CAR-dependent and non-dependent pathways, avoiding severe CRS and neurotoxicity. Furthermore, besides directly phagocytosing tumors due to its strong ability to infiltrate tumors, CAR-M therapy could also effectively improve the Immunosuppressive Microenvironment (IME) via immunomodulatory factor secretion to remodel M2-type Tumor-Associated Macrophages (TAMs) into the M1 phenotype with anti-tumor function. In this review, we systematically describe the research progress in CAR-T therapy for OC and compare the similarities and differences of three types of cellular therapies (CAR-T, CAR-NK, and CAR-M) regarding their mechanisms of action, clinical advantages, and technological bottlenecks. We hope that our findings will provide a theoretical basis for optimizing immunotherapeutic strategies for OC. Trial Registration: ClinicalTrials.gov identifier: NCT03585764.
Extrachromosomal DNA (ecDNA) constitutes a principal factor in the amplification of oncogenes and the progression of tumors in solid malignancies. This review synthesizes emerging mechanistic, genomic, and immunologic evidence across multiple tumor types, including glioblastoma, lung, breast, gastrointestinal, hepatobiliary, urothelial, prostate, gynecologic, pediatric, and head-and-neck cancers, with the goal of clarifying the role of ecDNA in immune escape and therapy resistance and outlining its translational implications for precision oncology. ecDNA comprises substantial acentromeric circular elements that serve as transcriptional hubs, modulate enhancer-promoter interactions, and undergo dynamic copy-number cycling, thereby fostering intratumoral heterogeneity and resistance to therapy. Recurrent oncogenic cargos, including epidermal growth factor receptor (EGFR), v-myc avian myelocytomatosis viral oncogene homolog (MYC), erb-b2 receptor tyrosine kinase 2, also known as human epidermal growth factor receptor 2 (ERBB2/HER2), and cyclin D1 (CCND1), are frequently located in ecDNA. They can interconvert with intrachromosomal homogeneously staining regions (HSRs) under treatment pressure. Emerging evidence links ecDNA to an immune-cold phenotype, characterized by downregulation of antigen presentation and decreased responsiveness to immune checkpoint inhibitors. We further emphasize diagnostic and translational methodologies that incorporate ecDNA detection through liquid biopsy and the spatial mapping of tumor topology. Finally, we propose a comprehensive clinical implementation framework that integrates ecDNA profiling, longitudinal monitoring, and immune microenvironment assessment to guide precision therapy. Gaining a deeper understanding of ecDNA biology has the potential to ultimately transform it from merely a prognostic biomarker into a targetable element within cancer therapy.
Diabetes mellitus is widely regarded as a risk factor for cancers. There is considerable controversy over whether maternal diabetes can cause cancer. This study aims to comprehensively assess and quantify the association between maternal diabetes and the risk of cancers in mother-offspring. The PubMed, Embase, and Web of Science databases were searched up to September 30, 2025, to explore the impact of maternal diabetes on cancer in mothers and their offspring. The primary outcome was the risk of cancers in the mother or offspring, presented as risk ratios (RRs) with 95% confidence intervals (CI). The I2 statistic is used to assess heterogeneity among studies, thereby guiding the selection of random-effects or common-effects models. The 81 studies involving 44 917 447 mother-offspring. Maternal diabetes was associated with increased risks of any cancers in mothers and offspring. In studies adjusted for multiple confounders, the risk of offspring suffering from haematological malignancies (RR, 1.37; 95% CI, 1.23-1.52; I2 = 1.0%) has significantly increased, especially leukaemia (1.34; 1.22-1.47; 0.0%). However, the risk of solid tumours (1.17; 1.09-1.24; 70.1%) in mothers increases significantly, especially, head and neck (1.34; 1.23-1.47; 35.1%), respiratory system (1.33; 1.05-1.67; 0.0%), gastrointestinal (1.30; 1.16-1.45; 45.5%), and gynecologic (1.16; 1.04-1.29; 64.1%). Maternal pre-gestational diabetes was more strongly associated with the risk of most cancers in offspring than gestational diabetes (1.60 [1.14-2.14] vs. 1.10 [1.02-1.18]; subgroup difference p = 0.0046). Maternal diabetes is associated with an increased risk of cancers in mothers and offspring. Further high-quality large-sample studies are needed to clarify and consolidate potential causal relationships.
Ovarian cancer (OC) remains one of the leading causes of gynecologic cancer mortality, largely due to late diagnosis, frequent relapse, and the emergence of chemoresistance. An important but often-overlooked contributor to treatment failure is the heterogeneous penetration of anticancer drugs within tumors. Structural and biochemical barriers-including abnormal vasculature, elevated interstitial pressure, dense extracellular matrix, drug efflux transporters, and malignant ascites-generate steep intratumoral concentration gradients that conventional preclinical models fail to capture. As a result, systemic pharmacokinetic measurements frequently provide limited insight into tumor-level drug exposure. Patient-derived organoids (PDOs) have emerged as physiologically relevant 3D models that preserve the genetic, architectural, and functional characteristics of the original tumor. These systems enable controlled investigation of pharmacokinetic and pharmacodynamic processes, including drug penetration, metabolism, retention, and exposure-response relationships. Adding cell-free malignant ascites supernatant enhances PDOs' ability to mimic the metastatic peritoneal microenvironment of OC. This review discusses recent advances in PDO technologies and examines how PDO-derived data can inform intratumoral pharmacokinetics and dosing strategies using physiologically based pharmacokinetic modeling and in vitro-in vivo extrapolation. Emerging hybrid platforms, including organoid-on-chip systems, vascularized co-cultures, and multi-omics integration, are crucial to improve translational prediction and support precision oncology.
Ovarian cancer is one of the most lethal gynecologic malignancies, mainly due to late diagnoses and chemoresistance. The immune checkpoint inhibitors and other immunotherapies achieve very low response rates in ovarian cancer. Nanotechnology-assisted co-delivery can helpful by simultaneously delivering multiple therapeutic agents together with their collective advantages. This review documents recent advances in nanocarrier-based co-delivery of immunotherapeutics for ovarian cancer, including organic (liposomes, Polymeric nanoparticles, dendrimers), inorganic (gold nanoparticles, mesoporous silica nanoparticles, and metal-organic frameworks), and hybrid (polymer-drug conjugates combined with gene vectors, polymer-lipid nanoparticles) nanocarrier systems. Early clinical trial data show that such systems can reprogram the myeloid cells in ovarian cancer. Key co-delivery strategies covered include combinations of chemotherapy with checkpoint inhibitors, cytokines with adjuvants, and gene therapies with conventional drugs. Nanocarrier-based co-delivery enables synergistic therapy by simultaneously targeting tumor cells and the immune microenvironment. The co-delivery of chemotherapeutics with immune checkpoint inhibitors promotes antigen expression by relieving immune suppression within the tumor microenvironment, hence improving the subsequent immune activation while increasing the infiltration of T-cells. Similarly, nanoparticle delivery of immunostimulatory cytokines produces local immune activation with reduced systemic toxicity, and gene-editing nanotherapies have also emerged. Nanotechnology-assisted co-delivery strategies overcome the immunotherapy limitations in ovarian cancer. Preclinical and early clinical outcomes are encouraging, with some challenges in safety, synthesis, and regulatory concerns. Continued innovation in biodegradable nanocarriers and rigorous clinical evaluation are crucial to fully realize the clinical impact in ovarian cancer.
Tubo-ovarian cancer represents the most lethal gynecologic malignancy, and its burden is compounded by the absence of effective screening and the substantial lifetime risk carried by women with germline BRCA1 or BRCA2 pathogenic variants. While risk-reducing salpingo-oophorectomy remains the standard for prevention, conferring reduction in tubo-ovarian cancer risk and improved overall survival, it also induces premature menopause with significant effects on quality of life and bone, cardiovascular, and sexual health. These consequences have driven the exploration of alternative preventive strategies, and a paradigm shift toward individualized risk assessment. Emerging data highlight that tubo-ovarian cancer risk among BRCA pathogenic variant carriers is not uniform but influenced by gene type, variant position, family history, and modifiable factors such as parity, breastfeeding, and oral contraceptive use. Modern risk models integrate genetic, familial, and lifestyle data to refine personalized estimates and guide the timing of intervention. Concurrently, the understanding that many high-grade serous carcinomas originate in the fallopian tube has prompted evaluation of risk-reducing salpingectomy with delayed oophorectomy as a staged surgical strategy that may balance oncologic safety with preservation of hormonal function. Ultimately, management of BRCA pathogenic variant carriers must combine genomic precision, reproductive planning, and patient-centered counseling to align cancer prevention with quality of life, supporting truly individualized care in hereditary tubo-ovarian cancer risk reduction. Despite several reviews on hereditary tubo-ovarian cancer prevention, a clinically relevant gap remains in translating contemporary evidence into a practical counseling framework for women with BRCA1/2 pathogenic variants. This narrative review aims to synthesize current evidence on tubo-ovarian cancer risk assessment and risk-reducing strategies in this population, with a focus on individualized counseling and shared decision-making.
Endometrial cancer continues to be the most common gynecologic malignancy in the United States. Endometrial tumors frequently express hormonal receptors, making this pathway targeting an attractive anti-cancer treatment. Recent advances have broadened our understanding of the androgen receptor's role in solid tumors beyond prostate cancer. Understanding the significance of androgen receptor signaling and its effects on tumor behavior and therapeutic outcomes in endometrial cancer is important for further clinical development. This review presents inter-connected pathways involving sex hormone-binding globulin, androgens, and androgen receptor signaling in cellular processes related to tumor pathogenesis. Sex hormone-binding globulin regulates androgen levels, influencing aromatase activity and estrogen production, which in turn activates estrogen receptors involved in gene expression promoting cell growth. Concurrently, notch pathway transcription factor forkhead box A1 modulates androgen receptor activity, impacting androgen receptor target gene expression and cell proliferation. Lysin-specific histone demethylases lysine demethylase 4A and lysine demethylase 4B modify chromatin at c-Myc and p27 promoter regions, respectively, affecting gene expression critical for cell-cycle regulation and tumor progression, demonstrating complex regulation of cellular mechanisms by hormone signaling pathways. lysine demethylase 4A interacts with androgen receptor signaling through chromatin remodeling, influencing transcriptional regulation of key cell-cycle genes. The complexity of androgen receptor signaling in endometrial cancer, marked by its varied expression and influence, necessitates a deeper investigation to harness its full therapeutic potential. The exploration of androgen receptor-targeted therapies offers promising avenues for refining treatments and improving outcomes of patients with endometrial cancer. This narrative review synthesizes current evidence on androgen receptor signaling and its therapeutic implications in endometrial cancer. Several potential androgen receptor-targeted approaches are also discussed in the context of future therapeutic development. These possible candidates to call for further development include (1) triple hormonal targeting with androgen receptor inhibitor, aromatase inhibitor, gonadotropin-releasing hormone and agonism, (2) targeting androgen receptor and lysine-specific demethylase 1-dependent forkhead box A1 demethylation, (3) targeting lysine demethylase 4B, (4) gamma secretase inhibitor combination therapy, and (5) combined androgen receptor and immune checkpoint inhibition.
Endometriosis and endometrial cancer are distinct gynecological conditions that share overlapping biological mechanisms with implications for clinical management. Endometriosis is a chronic, benign disorder characterized by the ectopic implantation of functional tissue lining the uterus, primarily affecting women of reproductive age. It commonly causes chronic pelvic pain, dysmenorrhea, dyspareunia, and infertility. The disease is marked by persistent inflammation, hormonal dysregulation, and alterations in cellular signaling, which mirror some neoplastic processes despite lacking malignant potential. Endometrial cancer is a malignant tumor of the uterine lining, most frequently diagnosed in postmenopausal women. Its incidence is rising due to aging, obesity, and prolonged estrogen exposure. Epidemiological studies suggest a modest increase in endometrial cancer risk among women with endometriosis. However, detection bias and metabolic confounders may influence this association. Both conditions share estrogen dependence, chronic inflammatory microenvironments, and dysregulated pathways such as PI3K/AKT/mTOR. Somatic mutations in genes, including PTEN and ARID1A, further underline molecular intersections. Clinical management is tailored to disease type and severity. Endometriosis therapy emphasizes stepwise hormonal treatment, multidisciplinary pain management, and surgery when indicated. Endometrial cancer management relies on staging, with particular emphasis on molecular classification and histopathology to guide surgery, radiotherapy, chemotherapy, hormone therapy, and immunotherapy in advanced cases. Emerging noninvasive biomarkers and precision medicine strategies may enhance diagnosis, monitoring, and targeted treatment in both conditions. Understanding their shared and divergent mechanisms aids risk stratification, individualized therapy, and improved quality of life. Further prospective studies are needed to optimize patient-specific management and translate mechanistic insights into clinical practice.
Ovarian cancer (OC) is a leading cause of cancer-related mortality in women, largely due to the lack of effective strategies for early detection. Here, we aimed to develop a liquid biopsy assay integrating cell-free DNA (cfDNA) fragmentomic features with serum biomarkers for sensitive OC detection. Plasma cfDNA from training (n = 91) and independent validation (n = 46) cohorts comprising patients with OC, benign ovarian diseases, and healthy controls, underwent low-coverage whole-genome sequencing to extract copy number variation, fragment size distribution, and Neomer features. Fragmentomic features were first integrated using a stacked machine-learning model and subsequently combined with serum biomarkers CA125 and HE4 to construct the final diagnostic model. Model performance was evaluated in the overall cohort and stratified by disease stage, histological subtype, and tumor grade. An external validation cohort (n = 58) was further used to assess model generalizability. The combined model integrating cfDNA fragmentomic features and serum biomarkers demonstrated superior diagnostic accuracy compared with all alternative approaches. In the independent validation cohort, the model achieved an AUC of 0.968 (95% CI: 0.896-0.996), with 85.7% sensitivity and 96.0% specificity. For early-stage OC (FIGO stage I and II), the model yielded an AUC of 0.938 (95% CI: 0.864-0.988), achieving 72.2% sensitivity at a specificity of 96%. Robust performance was observed across histological subtypes (AUC: 0.925-0.991) and tumor grades (AUC: 0.976-0.977). Stratified analyses further confirmed strong discrimination between OC and healthy controls (AUC: 0.995, 95% CI: 0.980-1.000) as well as benign ovarian diseases (AUC: 0.963, 95% CI: 0.921-0.993). In the external validation cohort, the combined model maintained robust diagnostic performance, achieving an AUC of 0.962 (95% CI: 0.898-0.991), with 86.2% sensitivity at 96% specificity. Integrating cfDNA fragmentomics with CA125 and HE4 via machine learning demonstrates strong potential for ovarian cancer detection and clinicopathological subtyping, supporting future evaluation for clinical translation in population screening and preoperative risk assessment.