Malignant Ovarian Cancer Research Articles

CORO1C Regulates the Malignant Biological Behavior of Ovarian Cancer Cells and Modulates the mRNA Expression Profile through the PI3K/AKT Signaling Pathway.

Ovarian cancer (OC) is a frequently occurring gynecological tumor, and its global incidence has recently increased. Coronin-like actin-binding protein 1C (CORO1C) is known to activate the phosphoinositide 3-kinase (PI3K)-protein kinase B (AKT) pathway and promote tumor progression. However, its role in OC remains unclear. This study investigated the role of CORO1C in OC malignancy. In this study, quantitative real-time polymerase chain reaction (qRT-PCR) was used to examine AKT and CORO1C mRNA expression in clinical OC tissues and cells. Immunohistochemical analysis and western blotting were used to examine protein expression in OC tissues and cells, respectively. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), scratch wound-healing, and Transwell assays were performed to examine cell proliferation and migration. RNA-Seq was used to validate the relationship between AKT and CORO1C expression. The results showed that CORO1C was highly expressed in clinical OC tissues and SKOV3 cells, correlating with the International Federation of Gynecology and Obstetrics (FIGO) stage. Furthermore, CORO1C knockout inhibited the proliferation, migration, and invasion of SKOV3 cells; altered the gene expression patterns in these cells; and was closely associated with the PI3K/AKT pathway. Western blotting confirmed that CORO1C knockout reduced the levels of phosphorylated PI3K and AKT. Additionally, CORO1C knockout increased phosphatase and tensin homologs deleted on chromosome 10 (PTEN) protein expression, whereas CORO1C overexpression decreased it. In conclusion, this study demonstrated that high CORO1C levels in OC are associated with greater metastasis and worse prognosis. CORO1C negatively regulates PTEN expression, activates the PI3K/AKT pathway, and promotes OC cell malignancy In patients with OC, CORO1C may function as an effective therapeutic and predictive biomarker.

Ascitic Shear Stress Activates GPCRs and Downregulates Mucin 15 to Promote Ovarian Cancer Malignancy.

The accumulation of ascites in patients with ovarian cancer increases their risk of transcoelomic metastasis. Although common routes of peritoneal dissemination are known to follow distinct paths of circulating ascites, the mechanisms that initiate these currents and subsequent fluid shear stresses are not well understood. Here we developed a patient-based, boundary driven computational fluid dynamics model to predict an upper range of fluid shear stress generated by the accumulation of ascites. We show that ovarian cancer cells exposed to ascitic shear stresses display heightened G protein-coupled receptor mechanosignaling and the induction of an epithelial to mesenchymal-like transition through p38α mitogen-activated protein kinase and mucin 15 modulation. An emergent immunomodulatory secretome and endoplasmic reticulum stress activation is also present in shear stimulated cancer cells, positioning elevated shear stress as a protumoural signal. Together, these findings suggest maintenance strategies for overcoming mechanotransduction mediated metastasis within the peritoneal cavity.

HDAC7 promotes ovarian cancer malignancy via AKT/mTOR signalling pathway.

Ovarian cancer is of the most lethal malignancy and causes serious threat to women health worldwide. A deep understanding of molecular mechanisms underlying ovarian cancer progression is critical for the development of promising therapeutic strategies. In this study, we aimed to employ immunohistochemistry to determine the protein level of HDAC7 in patient tissues, our data showed HDAC7 levels are upregulated in tumour tissues. In addition, we also performed Kaplan-Meier survival analysis to investigate the association between HDAC7 expression and clinical prognosis, and found that HDAC7 expression was associated with poor prognosis in ovarian cancer patients. Inhibition of HDAC7 cells resulted in lower cell proliferation, invasion and colony formation. Furthermore, we also found that HDAC7 inhibition suppressed PI3K/AKT/mTOR pathway. In contrast, exogenous HDAC7 expression activated the PI3K/AKT/mTOR pathway in HDAC7 knockout cells and rescued the cell proliferation, invasion and colony formation. However, inhibition of p-AKT induced lower cell proliferation, metastasis and colony formation abilities. In murine model, HDAC7 KO significantly decreased the tumour burden. These data indicate that HDAC7 is involved in regulation of PI3K/AKT/mTOR pathway and targeting of HDAC7 could be potential therapeutic strategy in the treatment of ovarian cancer.

Antibacterial and cytotoxic metabolites produced by Streptomyces tanashiensis BYF-112 isolated from Odontotermes formosanus

Chemical investigations of the termite-associated Streptomyces tanashiensis BYF-112 resulted in the discovery of four novel alkaloid derivatives: vegfrecines A and B (1 and 2), exfoliazone A (3), and venezueline H (7), in addition to nine known metabolites (4−6, 8−13). The structures of these compounds were elucidated through comprehensive spectroscopic analysis and comparison with existing literature data. Antibacterial assays revealed that viridomycin A (11) exhibited potent antibacterial activity against Staphylococcus aureus, with a zone of inhibition (ZOI) of 12.67 mm, in comparison to a ZOI of 17.67 mm for the positive control gentamicin sulfate. Viridomycin A (11) showed moderate activity against Micrococcus tetragenus and Pseudomonas syringae pv. actinidae, with ZOI values of 15.50 and 14.33 mm, respectively, which were inferior to those of gentamicin sulfate (34.67 and 24.00 mm). Viridomycin F (12) also exhibited moderate antibacterial effects against S. aureus, M. tetragenus, and P. syringae pv. actinidae, with ZOI values of 8.33, 16.50, and 10.83 mm, respectively. Cytotoxicity assays demonstrated that viridobruunine A (5), exfoliazone (6), viridomycin A (11), and X-14881E (13) exhibited significant cytotoxicity against human malignant melanoma (A375), ovarian cancer (SKOV-3), and gastric cancer (MGC-803) cell lines, with IC50 values ranging from 4.61 to 19.28 μmol·L−1. Furthermore, bioinformatic analysis of the complete genome of S. tanashiensis suggested a putative biosynthetic gene cluster (BGC) responsible for the production of compounds 1−12. These findings indicate that the secondary metabolites of insect-associated S. tanashiensis BYF-112 hold promise as potential sources of novel antibacterial and anticancer agents.

Machine-learning diagnostic models for ovarian tumors

PurposeTo create a diagnostic framework for clinical behavior and pathological tissue prognosis in ovarian cancer by using machine-learning (ML) methods based on multiple biomarkers. Experimental designOverall, 713 patients with ovarian tumors at Sun Yat Sen Memorial Hospital were randomized into training and test cohorts. Four supervised ML classifiers, namely Support Vector Machine, Random Forest, k-nearest neighbor, and logistic regression were used to derive diagnostic and prognostic information from 10 parameters commonly available from pretreatment peripheral blood tests and age. The best prediction model was selected and validated by comparing the accuracy and the area under the ROC curve of each prediction model and by applying the external data of Guangdong Maternal and Child Health Center. ResultsML techniques were superior to conventional regression-based analyses in predicting multiple clinical parameters pertaining to ovarian tumor. Ensemble methods combining weak decision trees and RF showed the best reference in diagnosis, especially for malignant ovarian cancer. The values for the highest accuracy and area under the ROC curve for malignant ovarian cancer from benign or borderline ovarian tumors with RF were 99.82 % and 0.86 (micro-average ROC curve), respectively. The greatest accuracy and AUC for the diagnosis of pathological tissue with logistic regression curve were 78.0 % and 0.95 (micro-average ROC curve), respectively. In external validation, the random forest prediction model had an accuracy of 0.789 for applying data from external centers to verify tumor benignity and malignancy, and the logistic regression model had an accuracy of 0.719 for predicting the nature of the tumor. ConclusionsAn ovarian tumor can be diagnosed and characterized before initial treatment via ML systems to provide critical diagnostic and prognostic information. The use of predictive algorithms can facilitate customized treatment options with patient preprocessing stratification.

Hsa_circ_0000129 targets miR-383-5p/tropomyosin 3 axis to facilitate ovarian cancer progression.

Ovarian cancer is one of the most prevalent malignancies among women. CircRNAs play key roles in the progression of ovarian cancer. This study aimed to investigate the mechanism of action of hsa_circ_0000129 and its effects on ovarian cancer. Expression of hsa_circ_0000129, tropomyosin 3 (TPM3), and miR-383-5p in ovarian cancer cell lines and tissue specimens was detected using qRT-PCR or western blotting. Cell counting kit-8 (CCK-8), colony formation, and transwell assays were performed to assess viability, proliferation, and migration of ovarian cancer cells. A xenograft model was used to study tumorigenicity of ovarian cancer cells in vivo. Luciferase and RNA immunoprecipitation assays were performed to determine binding between miR-383-5p and hsa_circ_0000129 or TPM3. Upregulation of hsa_circ_0000129 and TPM3 and downregulation of miR-383-5p were observed in ovarian cancer. Low hsa_circ_0000129 and TPM3 expression repressed viability, migration, and proliferation of ovarian cancer cells. Inhibition of miR-383-5p had a contrary effect. Furthermore, knockdown of hsa_circ_0000129 restricted the tumorigenicity of ovarian cancer cells. Mechanistically, hsa_circ_0000129 has a sponging effect on miR-383-5p, which targets TPM3. Hsa_circ_0000129 stimulated development of the malignant ovarian cancer phenotype by sponging miR-383-5p and releasing TPM3.

Enhancing Ovarian Cancer Detection Using Self-Organizing Maps and Improved Recurrent Neural Networks with Extended Harmony Search Optimization

Background: Ovarian cancer (OC) is a highly fatal malignancy of the female reproductive system, characterized by its high mortality rate and the challenges associated with clinical research due to the disease's complexity and late-stage diagnosis. Advances in technology, such as the Internet of Medical Things (IoMT), offer new opportunities for improving OC detection and diagnosis. Objective: This study aimed to develop and evaluate a novel method for OC detection using IoMT data, leveraging Self-Organizing Maps (SOM) and Improved Recurrent Neural Networks (IRNN) enhanced with the Extended Harmony Search Optimization (EHSO) algorithm to improve feature selection and classification accuracy. Methods: The study utilized OC data from the IoMT and applied SOM for feature selection, which helps in managing and classifying large datasets. SOM was employed to improve data representation and address challenges in labeling and classifying data. The IRNN model, optimized using the EHSO algorithm, was developed to enhance classification performance. The model was tested using a dataset from Kaggle comprising 179 benign and 172 malignant OC images with 50 attributes. Results: The IRNN model with EHSO demonstrated superior performance compared to other methods. In the training dataset, it achieved an accuracy of 95.72% and a Root Mean Square Error (RMSE) of 4.8%. For the testing dataset, the model maintained a high accuracy of 90.4% and an RMSE of 6.8%. The IRNN with EHSO outperformed alternative methods in terms of specificity and sensitivity, while the Genetic Algorithm (GA) showed the lowest performance across all metrics. Conclusion: The proposed method using SOM and IRNN with EHSO significantly improves the detection of ovarian cancer by optimizing feature selection and classification accuracy. This approach offers a promising advancement in utilizing IoMT data for early and accurate OC diagnosis, potentially enhancing patient outcomes through more effective detection and treatment strategies.

TRPM2-AS promotes ovarian cancer cell proliferation and inhibits cell apoptosis by upregulating the nearby gene TRPM2 via miR-6764-5p

Ovarian cancer (OC) becomes a fatal gynecologic malignant cancer in females worldwide. Target therapy is a promising therapeutical choice for patients with OC, and identifying biomarkers and exploring molecular mechanisms are necessary. In this study, the functions and mechanism of long noncoding RNA transient receptor potential cation channel subfamily M member 2 antisense RNA (TRPM2-AS) in OC were explored. TRPM2-AS expression in OC cells was analyzed utilizing reverse transcription quantitative polymerase chain reaction (RT-qPCR). Cell counting kit-8 (CCK-8) and colony forming assays were carried out to explore the influence of TRPM2-AS on OC cell viability and proliferation. Cell apoptosis was detected using TdT-mediated dUTP Nick-End labeling (TUNEL) and flow cytometry analysis. Protein expression of apoptotic markers was subjected to western blotting. RNA pulldown or luciferase reporter assays were applied to explore the interaction between TRPM2-AS and miR-6764-5p or the binding of miR-6764-5p and TRPM2. The results showed that TRPM2-AS is highly expressed in OC cells and was mainly localized in cytoplasm. TRPM2-AS depletion suppressed OC cell viability and proliferation while increasing cell apoptotic rate. TRPM2 displayed a high level in OC cells and was positively regulated by TRPM2-AS. TRPM2-AS interacted with miR-6764-5p and thereby upregulated TRPM2 expression. In addition, TRPM2 overexpression reversed the repressive impact of TRPM2-AS depletion on malignant OC cellular process. In conclusion, TRPM2-AS promotes OC cell viability and proliferation while enhancing cell apoptosis through interaction with miR-6764-5p to regulate TRPM2 level.

Early-stage diagnosis of ovarian cancer via digital immunoassay on a SlipChip

Ovarian cancer (OC) is one of the three major gynecologic malignancies and has the highest mortality rate because of the late diagnosis. Liquid biopsy based on serum protein biomarkers has demonstrated great potential for early diagnosis but remains limited by the analysis performance of conventional immunoassay technologies, such as chemiluminescence, and biomarkers, such as CA125. To address this challenge and achieve accurate early-stage diagnosis of OC, we developed a digital immunoassay on a SlipChip (DiSC) for quantitative analysis of a potential serum protein biomarker, Spondin-1 (SPON1). The DiSC system achieved a limit of detection (LoD) of 23 fg/μL for digital quantification of SPON1. The DiSC system was utilized to quantify the serum level of SPON1 in 357 clinical serum samples, including 63 from patients with benign ovarian tumors and 294 from patients with malignant ovarian cancer, ranging from stages I to IV. SPON1 concentrations were significantly different in samples from patients with malignant ovarian cancer. Notably, significantly different SPON1 levels were observed in early stages (I and II), in lymph node-negative cases (N0), and before metastasis (M0), suggesting that SPON1 could serve as a sensitive diagnostic biomarker for early-stage OC. The differential diagnostic model based on SPON1 levels quantified using DiSC demonstrated an area under the curve (AUC) of 0.8187 for early-stage OC, a significant improvement over CA-125 (AUC = 0.6967). For OC of all stages, the AUC was 0.8225, which could be further increased to 0.8750 when combined with CA-125. This showcases the potential of SPON1 as a novel biomarker for sensitive early-stage diagnosis of ovarian cancer and the capability of the DiSC system in discovering low-abundance biomarkers for disease diagnosis.

New insight into the CNC-bZIP member, NFE2L3, in human diseases.

Nuclear factor erythroid 2 (NF-E2)-related factor 3 (NFE2L3), a member of the CNC-bZIP subfamily and widely found in a variety of tissues, is an endoplasmic reticulum (ER) membrane-anchored transcription factor that can be released from the ER and moved into the nucleus to bind the promoter region to regulate a series of target genes involved in antioxidant, inflammatory responses, and cell cycle regulation in response to extracellular or intracellular stress. Recent research, particularly in the past 5years, has shed light on NFE2L3's participation in diverse biological processes, including cell differentiation, inflammatory responses, lipid homeostasis, immune responses, and tumor growth. Notably, NFE2L3 has been identified as a key player in the development and prognosis of multiple cancers including colorectal cancer, thyroid cancer, breast cancer, hepatocellular carcinoma, gastric cancer, renal cancer, bladder cancer, esophageal squamous cell carcinoma, T cell lymphoblastic lymphoma, pancreatic cancer, and squamous cell carcinoma. Furthermore, research has linked NFE2L3 to other cancers such as lung adenocarcinoma, malignant pleural mesothelioma, ovarian cancer, glioblastoma multiforme, and laryngeal carcinoma, indicating its potential as a target for innovative cancer treatment approaches. Therefore, to gain a better understanding of the role of NFE2L3 in disease, this review offers insights into the discovery, structure, function, and recent advancements in the study of NFE2L3 to lay the groundwork for the development of NFE2L3-targeted cancer therapies.

Tumorigenic role of Pak4 in ovarian cancer and its correlation with immune infiltration

BackgroundOvarian cancer is the most common cause of gynecological cancer death. Pak4 has been proved to be tumorigenic in many types of cancers, but its role in ovarian cancer is still not clarified.MethodsIn this study, we used immunohistochemistry to investigate into Pak4 expression in different histological types of ovarian cancer. TIMER, TISCH2, GEPIA, ualcan, KM plotter, GSCA and GeneMANIA were used to identify the prognostic roles and gene regulation networks of Pak4 in ovarian cancer. Immune infiltration levels were investigated using TIMER database.ResultsPak4 was highly expressed in ovarian cancers, regardless of different FIGO stages and histological grades. Single cell sequencing database proved that Pak4 was highly expressed in malignant ovarian cancer cells. Pak4 level was significantly correlated with different histological types of ovarian cancer. Pak4 expression was negatively connected with OS and PFS of ovarian cancer patients. Functions of Pak4 and its interacted genes were mainly involved in protein serine/threonine kinase activity, regulation of actin filament-based process and regulation of cytoskeleton organization. Pak4 level was negatively correlated with immune biomarkers of B cell infiltration (p = 2.39e-05), CD8 + T cell infiltration (p = 1.51e-04), neutrophil (p = 1.74e-06) and dendritic cell (p = 4.41e-08). Close correlation was found between Pak4 expression and T cell exhaustion (p < 0.05).ConclusionsOur results demonstrated the expression level, gene interaction networks and immune infiltration levels of Pak4 in ovarian cancer. And the results revealed role of Pak4 in tumorigenesis and the possibility to be a potential immunotherapeutic target.

M2 macrophage-derived exosomal circTMCO3 acts through miR-515-5p and ITGA8 to enhance malignancy in ovarian cancer

Tumor-associated macrophages of the M2 phenotype promote cancer initiation and progression. Importantly, M2 macrophage-derived exosomes play key roles in the malignancy of cancer cells. Here, we report that circTMCO3 is upregulated in ovarian cancer patients, and its high expression indicates poor survival. M2-derived exosomes promote proliferation, migration, and invasion in ovarian cancer, but these effects are abolished by knockdown of circTMCO3. Furthermore, circTMCO3 functions as a competing endogenous RNA for miR-515-5p to reduce its abundance, thus upregulating ITGA8 in ovarian cancer. miR-515-5p inhibits ovarian cancer malignancy via directly downregulating ITGA8. The decreased oncogenic activity of circTMCO3-silencing exosomes is reversed by miR-515-5p knockdown or ITGA8 overexpression. Exosomal circTMCO3 promotes ovarian cancer progression in nude mice. Thus, M2 macrophage-derived exosomes promote malignancy by delivering circTMCO3 and targeting the miR-515-5p/ITGA8 axis in ovarian cancer. Our findings not only provide mechanistic insights into ovarian cancer progression, but also suggest potential therapeutic targets.

Comparative Analysis of Primary Ovarian Cancer Cells and Established Cell Lines as a New Tool for Studies on Ovarian Cancer Cell Complexity.

Primary cancer cells reflect the genetic background and phenotype of a tumor. Immortalized cells with higher proliferation activity have an advantage over primary cells. The aim of the study was to immortalize the primary ovarian cancer (OvCa) cells using the plasmid-carrying human telomerase reverse transcriptase (hTERT) gene and compare their phenotype and biological activity with the primary cells. The primary OvCa3 A and OvCa7 A cells were isolated from the ascitic fluid of two high-grade serous ovarian cancer patients and were characterized using immunocytochemical methods, flow cytometry, real-time RT-PCR, Western blot, metabolic activity, and migratory potential. Both immortalized ovarian cancer cell lines mirrored the phenotype of primary cancer cells, albeit with modifications. The OvCa3 A hTERT cells kept the mesenchymal stem cell phenotype of CD73/CD90/CD105-positivity and were CD133-negative, whereas the cell population of OvCa7 A hTERT lost CD73 expression, but almost 90% of cells expressed the CD133 characteristic for the CSCs phenotype. Immortalized OvCa cells differed in gene expression level with respect to Sox2 and Oct4, which was associated with stemness properties. The OvCa7 A hTERT cells showed higher metabolic and migratory activity and ALDH1 expression than the corresponding primary OvCa cells. Both primary and immortalized cell lines were able to form spheroids. The newly established unique immortalized cell line OvCa7 A hTERT, with the characteristic of a serous ovarian cancer malignancy feature, and with the accumulation of the p53, Pax8, and overexpression of the CD133 and CD44 molecules, may be a useful tool for research on therapeutic approaches, especially those targeting CSCs in ovarian cancer and in preclinical 2D and 3D models.

Iron promotes ovarian cancer malignancy and advances platinum resistance by enhancing DNA repair via FTH1/FTL/POLQ/RAD51 axis

Iron is crucial for cell DNA synthesis and repair, but an excess of free iron can lead to oxidative stress and subsequent cell death. Although several studies suggest that cancer cells display characteristics of ‘Iron addiction’, an ongoing debate surrounds the question of whether iron can influence the malignant properties of ovarian cancer. In the current study, we initially found iron levels increase during spheroid formation. Furthermore, iron supplementation can promote cancer cell survival, cancer spheroid growth, and migration; vice versa, iron chelators inhibit this process. Notably, iron reduces the sensitivity of ovarian cancer cells to platinum as well. Mechanistically, iron downregulates DNA homologous recombination (HR) inhibitor polymerase theta (POLQ) and relieves its antagonism against the HR repair enzyme RAD51, thereby promoting DNA damage repair to resist chemotherapy-induced damage. Additionally, iron tightly regulated by ferritin (FTH1/FTL) which is indispensable for iron-triggered DNA repair. Finally, we discovered that iron chelators combined with platinum exhibit a synergistic inhibitory effect on ovarian cancer in vitro and in vivo. Our findings affirm the pro-cancer role of iron in ovarian cancer and reveal that iron advances platinum resistance by promoting DNA damage repair through FTH1/FTL/POLQ/RAD51 pathway. Our findings highlight the significance of iron depletion therapy, revealing a promising avenue for advancing ovarian cancer treatment.

Abstract B073: A spatially resolved single-cell tumor microenvironment of clinicomolecular subtypes of high-grade serous ovarian cancer

Abstract Background &amp; objective: High grade serous ovarian cancer (HGSC) is the most lethal type of ovarian cancer malignancies. Around 50% of HGSCs are DNA-repair homologous recombination deficient (HRD) and 15% have CCNE1 gene amplification. Previous results have shown that tumor microenvironment (TME) can impact clinical prognosis in HGSC. In this study our objective was to characterize the interplay of the TME with HRD and CCNE1 amplification in HGSC and its association with clinical outcomes. Materials and methods: We collected TME spatial protein expression, genomics, and clinical data from 250 HGSC patients. We determined BRCA1/2 germline and somatic mutation status using targeted sequencing and promoter hyper-methylation. For the tumors without BRCA1/2 mutations, we performed shallow whole genome sequencing, and estimated the CCNE1 amplification and HRD status using shallowHRD and BRCAness copy number profiles. Immune cell infiltration was assessed also using IHC for CD8, CD20, CD68, and CD103. The single-cell spatial landscapes were analyzed for 1000 tumor cores from the tumor center and tumor periphery using cyclic immunofluorescence (tCycIF) imaging for 34 different protein markers. We categorized and spatially analyzed the single cells from the TME to distinct cellular subpopulations using the TRIBUS and scimap software. Results: In our study of the TME using highly multiplexed tissue imaging we identified a total of 4.8 million single cells of them 1.6 million were immune cells belonging to eight biological subpopulations. The immune cell proportion detected in each sample showed high concordance with the IHC estimation by a pathologist. Interestingly, the CD8+, CD20+, CD11c+, and CD15+ high immune cell infiltrations were higher in BRCA1/2 mutated as compared to the CCNE1 amplified tumors. High immune infiltration was associated with prolonged overall survival only in samples debulked before chemotherapy but not in samples debulked after chemotherapy. Using consensus clustering for cell protein expression and cell morphology, we identified five distinct tumoral and stromal cell clusters which showed significant heterogeneity among the tumor genotypes and association with clinical outcomes. Then, after clustering of the spatial single-cell proximity data, we identified 13 distinct recurrent cellular neighborhoods (RCNs). The two RCNs related to the tumor-stroma and tumor-immune interfaces exhibited the highest differences between HRD and CCNE1 samples. Finally, by using random forest machine learning classifiers of the cells and its neighborhoods, and using an approach to minimize overfitting, we were able to detect the features more representative in HRD samples, for example, MHC-I expression in cancer cells and in stromal cells. Conclusion: The integration of multi-omics data revealed distinct TMEs associated with HRD and clinical outcomes; this has the potential to be used to discover biomarkers for precision oncology in HGSCs. Citation Format: Fernando Perez-Villatoro, Lilian van Wagensveld, Aleksandra Shabanova, Siamak Hajizadeh, Julia Casado, Ella Anttila, Maaike A. van der Aa, Roy F.P.M. Kruitwagen, Gabe S. Sonke, Koen K. Van de Vijver, Peter K. Sorger, Hugo M. Horlings, Anniina Färkkilä. A spatially resolved single-cell tumor microenvironment of clinicomolecular subtypes of high-grade serous ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr B073.

Integrin αvβ3 and LHRH Receptor Double Directed Nano-Analogue Effective Against Ovarian Cancer in Mice Model.

The high mortality rate of malignant ovarian cancer is attributed to the absence of effective early diagnosis methods. The LHRH receptor is specifically overexpressed in most ovarian cancers, and the integrin αvβ3 receptor is also overexpressed on the surface of ovarian cancer cells. In this study, we designed LHRH analogues (LHRHa)/RGD co-modified paclitaxel liposomes (LHRHa-RGD-LP-PTX) to target LHRH receptor-positive ovarian cancers more effectively and enhance the anti-ovarian cancer effects. LHRHa-RGD-LP-PTX liposomes were prepared using the thin film hydration method. The morphology, physicochemical properties, cellular uptake, and cell viability were assessed. Additionally, the cellular uptake mechanism of the modified liposomes was investigated using various endocytic inhibitors. The inhibitory effect of the formulations on tumor spheroids was observed under a microscope. The co-localization with lysosomes was visualized using confocal laser scanning microscopy (CLSM), and the in vivo tumor-targeting ability of the formulations was assessed using the IVIS fluorescent imaging system. Finally, the in vivo anti-tumor efficacy of the formulations was evaluated in the armpits of BALB/c nude mice. The results indicated that LHRHa-RGD-LP-PTX significantly enhanced cellular uptake in A2780 cells, increased cytotoxicity, and hand a more potent inhibitory effect on tumor spheroids of A2780 cells. It also showed enhanced co-localization with endosomes or lysosome in A2780 cells, improved tumor-targeting capability, and demonstrated an enhanced anti-tumor effect in LHRHR-positive ovarian cancers. The designed LHRHa-RGD-LP-PTX liposomes significantly enhanced the tumor-targeting ability and therapeutic efficacy for LHRH receptor-positive ovarian cancers.

Advances in artificial intelligence for the diagnosis and treatment of ovarian cancer (Review).

Artificial intelligence (AI) has emerged as a crucial technique for extracting high‑throughput information from various sources, including medical images, pathological images, and genomics, transcriptomics, proteomics and metabolomics data. AI has been widely used in the field of diagnosis, for the differentiation of benign and malignant ovarian cancer (OC), and for prognostic assessment, with favorable results. Notably, AI‑based radiomics has proven to be a non‑invasive, convenient and economical approach, making it an essential asset in a gynecological setting. The present study reviews the application of AI in the diagnosis, differentiation and prognostic assessment of OC. It is suggested that AI‑based multi‑omics studies have the potential to improve the diagnostic and prognostic predictive ability in patients with OC, thereby facilitating the realization of precision medicine.

Prehabilitation in gynecological oncology - are we ready to implement the program in polish oncological centers?

Prehabilitation is a concept of holistic approach to the patient and includes preoperative efforts focused on optimalization of patient's general condition. The idea of prehabilitation started at the beginning of the 21st century. However, prehabilitation programs in gynecological cancer patients are not standardized and are heterogeneous. The aim of the study it to present the concept of prehabilitation and propose prehabilitation protocol to be introduced in Polish oncological centers. A search in PubMed, Medline, EMBASE (Ovid) and PsycINFO databases was conducted using the following keywords: prehabilitation, gynecological, abdominal surgery, and cancer. The primary outcomes were complications, hospitalization stay, intensive care unit transfer rate, blood loss, wound healing, and reoperation rate. The search was performed in July 2022 and covered the period from 1st January 2000 till 30th June 2022. A total number of 1,118 articles have been identified. Out of all eligible papers only 42 fulfilled the research criteria and were included in the study. The analysis showed that there is no standardized prehabilitation protocol for gynecological cancer surgery, although most include three-modal approach - physical activity, nutrition, and psychological intervention. There is no standard model for physical capacity evaluation, however, 1,118 6 Minute Walk Test (6MWT) is the most common. Frailty evaluation is based on different measurements that prevent from direct comparison of obtained results between studies. We are not ready to implement the prehabilitation program in polish oncological centers. The main reason elvicz is: lack of accredited ovarian cancer centers, lack of well-established standardized prehabilitation programs for gynecological malignancies (ovarian cancer especially), and lack of proper information for patients about advantages of adequate preparation elvic expected surgery. Furter studies on different prehabilitation programs and information campaigns both for patients and gynecologist are required to make implementing prehabilitation possible in Poland.

Frailty in middle-aged and older adult postoperative patients with gynecological malignancies structural equation modeling.

Frailty and self-management are important determinants of quality of life in cancer patients. However, their synergistic effects and potential mechanisms on quality of life in middle-aged and older adult postoperative gynecologic malignancy patients have not been adequately studied. This cross-sectional study aimed to explore the relationship between frailty, self-management, and quality of life in middle-aged and older adult postoperative gynecologic malignancy patients. A cross-sectional study was conducted from January 2024 to April 2024 in three gynecological wards of a tertiary hospital in Wuxi. The study recruited 177 patients aged 45 years or older who underwent surgery for gynecologic malignancies (cervical, ovarian, and endometrial cancer). Data were collected using demographic and clinical characteristics, the Edmonton Frailty Scale, the Self-Management Competence Scale, and the EORTC Core Quality of Life Questionnaire. Structural equation modeling was used to explore the interactions between frailty, self-management, and quality of life. The prevalence of frailty in middle-aged and older adult postoperative gynecologic malignancy patients was 39.5%, with a mean total self-management score of 125.81 ± 13.21 and a mean total quality of life score of 69.26 ± 10.88. The fit indices of the model indicated a good fit, and that frailty had multiple effects on quality of life; specifically, frailty could affect the quality of life directly or through self-management, i.e., self-management partially mediated frailty and quality of life. Self-management is a mediating variable between frailty and quality of life, suggesting that clinical workers can intervene in self-management skills to improve patient's quality of life and physical and mental health.

Body Mass Index and Risk of Female Reproductive System Tumors Subtypes: A Meta-Analysis Using Mendelian Randomization.

Introduction: A strong association was previously established between body mass index (BMI) and female reproductive system tumors; however, the causal relationship is unclear. We conducted a Mendelian randomization (MR) study to further explore this association. Methods: Genetic information for BMI was retrieved from a published genome-wide association study involving 339,224 participants. Genetic associations with five common female reproductive system tumors were obtained from the FinnGen, UK Biobank studies, and other large consortia. Results: Genetic predisposition towards BMI exhibits a significant association with multiple tumors of the female reproductive system. Specifically, for every 1-unit increase in BMI log-transformed odds ratio (OR). The OR fluctuations overall for patients with breast cancer ranged from 0.661 to 0.996 (95% confidence interval [CI],0.544-1.000, P < 0.05). When stratified by estrogen receptor (ER) status, the OR for patients with ER (+) breast cancer ranged from 0.782 to 0.844 (95% CI, 0.616-0.994, P < 0.05) and that for those with ER (-) breast cancer ranged from 0.663 to 0.789 (95% CI, 0.498-0.991, P < 0.05). Additionally, ORs were as follows for cancer types: 1.577-1.908 (95% CI, 1.049-2.371, P < 0.05) for endometrial carcinoma; 1.216-1.303 (95% CI, 1.021-1.591, P < 0.05) for high-grade serous ovarian cancer; 1.217 (95% CI, 1.034-1.432, P < 0.05) for low-grade malignant serous ovarian cancer; and 1.502 (95% CI, 1.112-2.029, P < 0.05) for endometrioid ovarian carcinoma. Furthermore, our findings indicated that genetic predisposition towards BMI did not exhibit a causal association with uterine fibroids, cervical precancerous lesions, or cervical cancer itself. Conclusion: A genetic association was established between a high BMI and high risk of developing multiple tumors of the female reproductive system and their associated subtypes. This underscores the significance of taking measures to prevent reproductive system tumors in women who have a high BMI.