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RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL) prognostic model to evaluate the significance of intra- and peritumoral radiomics in predicting outcomes for high-grade serous ovarian cancer (HGSOC) patients receiving platinum-based chemotherapy. MATERIALS AND METHODS: A DL model was trained and validated on retrospectively collected unenhanced computed tomography (CT) scans from 474 patients at two institutions, which were divided into a training set (N = 362), an internal test set (N = 86), and an external test set (N = 26). The model incorporated tumor segmentation and peritumoral region analysis, using various input configurations: original tumor regions of interest (ROIs), ROI subregions, and ROIs expanded by 1 and 3 pixels. Model performance was assessed via hazard ratios (HRs) and receiver operating characteristic (ROC) curves. Patients were stratified into high- and low-risk groups on the basis of the training set's optimal cutoff value. RESULTS: Among the input configurations, the model using an ROI with a 1-pixel peritumoral expansion achieved the highest predictive accuracy. The DL model exhibited robust performance for predicting progression-free survival, with HRs of 3.41 (95% CI: 2.85, 4.08; P < 0.001) in training set, 1.14 (95% CI: 1.03, 1.26; P = 0.012) in internal test set, and 1.32 (95% CI: 1.07, 1.63; P = 0.011) in external test set. KM survival analysis revealed significant differences between the high-risk and low-risk groups (P < 0.05). CONCLUSION: The DL model effectively predicts survival outcomes in HGSOC patients receiving platinum-based chemotherapy, offering valuable insights for prognostic assessment and personalized treatment planning.
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High-grade serous ovarian cancer has a high degree of malignancy, and at detection, it is prone to infiltration of surrounding soft tissues, as well as metastasis to the peritoneum and lymph nodes, peritoneal seeding, and distant metastasis. Whether recurrence occurs becomes an important reference for surgical planning and treatment methods for this disease. Current recurrence prediction models do not consider the potential pathological relationships between internal tissues of the entire ovary. They use convolutional neural networks to extract local region features for judgment, but the accuracy is low, and the cost is high. To address this issue, this paper proposes a new lightweight deep learning algorithm model for predicting recurrence of high-grade serous ovarian cancer. The model first uses ghost convolution (Ghost Conv) and coordinate attention (CA) to establish ghost counter residual (SCblock) modules to extract local feature information from images. Then, it captures global information and integrates multi-level information through proposed layered fusion Transformer (STblock) modules to enhance interaction between different layers. The Transformer module unfolds the feature map to compute corresponding region blocks, then folds it back to reduce computational cost. Finally, each STblock module fuses deep and shallow layer depth information and incorporates patient's clinical metadata for recurrence prediction. Experimental results show that compared to the mainstream lightweight mobile visual Transformer (MobileViT) network, the proposed slicer visual Transformer (SlicerViT) network improves accuracy, precision, sensitivity, and F1 score, with only 1/6 of the computational cost and half the parameter count. This research confirms that the proposed algorithm model is more accurate and efficient in predicting recurrence of high-grade serous ovarian cancer. In the future, it can serve as an auxiliary diagnostic technique to improve patient survival rates and facilitate the application of the model in embedded devices.
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Algoritmos , Aprendizaje Profundo , Recurrencia Local de Neoplasia , Redes Neurales de la Computación , Neoplasias Ováricas , Humanos , Femenino , Neoplasias Ováricas/patología , Metadatos , Cistadenocarcinoma Seroso/patologíaRESUMEN
BACKGROUND: Epithelial ovarian cancer, especially high grade serous ovarian cancer (HGSOC) is by far, the most lethal gynecological malignancy with poor prognosis and high relapse rate. Despite of availability of several therapeutic interventions including poly-ADP ribose polymerase (PARP) inhibitors, HGSOC remains unmanageable and identification of early detection biomarkers and therapeutic targets for this lethal malady is highly warranted. Aberrant expression of protein kinase C iota (PKCί) is implicated in many cellular and physiological functions involved in tumorigenesis including cell proliferation and cell cycle deregulation. METHODS AND RESULTS: Two high grade serous ovarian cancer cells SKOV3 and COV362 were employed in this study. PKCί was genetically knocked down or pharmacologically inhibited and several functional and biochemical assays were performed. We report that PKCί is overexpressed in HGSOC cells and patient tissue samples with a significant prognostic value. Pharmacological inhibition of PKCί by Na-aurothiomalate or its shRNA-mediated genetic knockdown suppressed HGSOC cell proliferation, EMT and induced apoptosis. Moreover, PKCί positively regulated GLUT1 and several other glycolytic genes including HK1, HK2, PGK1, ENO1 and LDHA to promote elevated glucose uptake and glycolysis in HGSOC cells. Mechanistically, PKCί drove glycolysis via PI3K/AKT/mTOR signalling. Na-aurothiomalate and highly selective, dual PI3K/mTOR inhibitor dactolisib could serve as novel anti-glycolytic drugs in HGSOC. CONCLUSION: Taken together, our results indicate PKCί/PI3K/AKT/mTOR signalling cascade could be a novel therapeutic target in a lethal pathology like HGSOC.
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Proliferación Celular , Glucólisis , Isoenzimas , Neoplasias Ováricas , Fosfatidilinositol 3-Quinasas , Proteína Quinasa C , Proteínas Proto-Oncogénicas c-akt , Transducción de Señal , Serina-Treonina Quinasas TOR , Humanos , Femenino , Serina-Treonina Quinasas TOR/metabolismo , Proteínas Proto-Oncogénicas c-akt/metabolismo , Neoplasias Ováricas/metabolismo , Neoplasias Ováricas/genética , Neoplasias Ováricas/patología , Línea Celular Tumoral , Proteína Quinasa C/metabolismo , Proteína Quinasa C/genética , Fosfatidilinositol 3-Quinasas/metabolismo , Proliferación Celular/genética , Isoenzimas/metabolismo , Isoenzimas/genética , Cistadenocarcinoma Seroso/metabolismo , Cistadenocarcinoma Seroso/genética , Cistadenocarcinoma Seroso/patología , Apoptosis/genética , Regulación Neoplásica de la Expresión Génica , Carcinoma Epitelial de Ovario/metabolismo , Carcinoma Epitelial de Ovario/genética , Carcinoma Epitelial de Ovario/patología , PronósticoRESUMEN
Cholesterol homeostasis is essential for healthy mammalian cells and dysregulation of cholesterol metabolism contributes to the pathogenesis of various diseases including cancer. Cancer cells are dependent on cholesterol. Malignant progression is associated with high cellular demand for cholesterol, and extracellular cholesterol uptake is often elevated in cancer cell to meet its metabolic needs. Tumors take up cholesterol from the blood stream through their vasculature. Breast cancer grows in, and ovarian cancer metastasizes into fatty tissue that provides them with an additional source of cholesterol. High levels of extracellular cholesterol are beneficial for tumors whose cancer cells master the uptake of extracellular cholesterol. In this review we concentrate on cholesterol uptake mechanisms, receptor-mediated endocytosis and macropinocytosis, and how these are utilized and manipulated by cancer cells to overcome their possible intrinsic or pharmacological limitations in cholesterol synthesis. We focus especially on the involvement of lysosomes in cholesterol uptake. Identifying the vulnerabilities of cholesterol metabolism and manipulating them could provide novel efficient therapeutic strategies for treatment of cancers that manifest dependency for extracellular cholesterol.
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Neoplasias de la Mama , Colesterol , Neoplasias Ováricas , Humanos , Colesterol/metabolismo , Neoplasias Ováricas/metabolismo , Neoplasias Ováricas/patología , Femenino , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/patología , AnimalesRESUMEN
Objective: To determine the best possible value of pathological PCI (pPCI) as a prognostic marker for survival in high-grade serous epithelial ovarian cancer patients in patients treated with neoadjuvant chemotherapy and interval cytoreductive surgery. Methods: All patients with FIGO stage IIIC high-grade serous ovarian carcinoma were included. Receiver operating curves (ROC) were used to determine the best possible score for pPCI in predicting survival. Survival curves were calculated using the Kaplan-Meier test, and factors affecting survival were compared using the log-rank test. Results: From January 2018 to January 2024, 171 patients who underwent interval cytoreductive surgery were included. Complete cytoreduction was achieved in 88% of the patients. ROC curves determined a (pPCI) cut-off value of 8 as the best possible score for predicting survival with a sensitivity of 82% and specificity of 67% (Youden's Index = 0.60). pPCI with a cut-off value of 8 showed improved OS (p = 0.002) and DFS, (p = 0.001) in both univariate and multivariate analyses. Conclusion: Following interval cytoreductive surgery, despite optimal complete cytoreductive surgery, a pathological PCI of 8 is a poor prognostic indicator of survival and may serve as a surrogate clinical marker for guiding clinicians in adjuvant treatment, especially in resource-driven settings in the real world.
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Background: Treatment of recurrent platinum-resistant high grade serous ovarian cancer (HGSOC) remains a challenge. Novel treatment options for recurrent disease are an unmet need. Case: A 69-year-old with recurrent, metastatic, platinum-resistant HGSOC overexpressing TROP2 experienced a significant response to the antibody-drug conjugate (ADC) sacituzumab govitecan after multiple failed lines of chemotherapy and targeted treatment. Following sacituzumab govitecan treatment she experienced a confirmed partial response as well as a return of CA-125 to baseline. Having now completed 8 cycles (ie, over 6 months of treatment), her disease continues to demonstrate a response to sacituzumab govitecan treatment. The ADC has been well tolerated at a dose of 10 mg/kg with no dose-limiting toxicity or need for dose reductions. Conclusion: Sacituzumab govitecan may represent a treatment option for platinum-resistant/recurrent HGSOC that have previously failed prior lines of chemotherapy. Clinical trials with sacituzumab govitecan in platinum-resistant ovarian cancer patients are currently ongoing (https://classic.clinicaltrials.gov/ct2/show/NCT06028932).
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Recent work has shown evidence for the prognostic significance of tumor infiltrating B cells (B-TIL) in high grade serous ovarian carcinoma (HGSOC), the predominant histological subtype of ovarian cancer. However, it remains unknown how the favorable prognosis associated with B-TIL relates to the current standard treatments of primary debulking surgery (PDS) followed by chemotherapy or (neo-)adjuvant chemotherapy (NACT) combined with interval debulking surgery. To address this, we analyzed the prognostic impact of B-TIL in relationship to primary treatment and tumor infiltrating T cell status in a highly homogenous cohort of HGSOC patients. This analysis involved a combined approach utilizing histological data and high-dimensional flow cytometry analysis. Our findings indicate that while HGSOC tumors pre-treated with NACT are infiltrated with tumor-reactive CD8+ and CD4+ TIL subsets, only B-TIL and IgA plasma blasts confer prognostic benefit in terms of overall survival. Importantly, the prognostic value of B-TIL and IgA plasma blasts was not restricted to patients treated with NACT, but was also evident in patients treated with PDS. Together, our data point to a critical prognostic role for B-TIL in HGSOC patients independent of T cell status, suggesting that alternative treatment approaches focused on the activation of B cells should be explored for HGSOC.
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BACKGROUND: The clinicopathological parameters such as residual tumor, grade, the International Federation of Gynecology and Obstetrics (FIGO) score are often used to predict the survival of ovarian cancer patients, but the 5-year survival of high grade serous ovarian cancer (HGSOC) still remains around 30%. Hence, the relentless pursuit of enhanced prognostic tools for HGSOC, this study introduces an unprecedented gene expression-based molecular prognostic score (mPS). Derived from a novel 20-gene signature through Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression, the mPS stands out for its predictive prowess. RESULTS: Validation across diverse datasets, including training and test sets (n = 491 each) and a large HGSOC patient cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium (n = 7542), consistently shows an area-under-curve (AUC) around 0.7 for predicting 5-year overall survival. The mPS's impact on prognosis resonates profoundly, yielding an adjusted hazard-ratio (HR) of 6.1 (95% CI: 3.65-10.3; p < 0.001), overshadowing conventional parameters-FIGO score, residual disease, and age. Molecular insights gleaned from mPS stratification uncover intriguing pathways, with focal-adhesion, Wnt, and Notch signaling upregulated, and antigen processing and presentation downregulated (p < 0.001) in high-risk HGSOC cohorts. CONCLUSION: Positioned as a robust prognostic marker, the 20-gene signature-derived mPS emerges as a potential game-changer in clinical settings. Beyond its role in predicting overall survival, its implications extend to guiding alternative therapies, especially targeting Wnt/Notch signaling pathways and immune evasion-a promising avenue for improving outcomes in high-risk HGSOC patients.
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Neoplasias Ováricas , Humanos , Femenino , Pronóstico , Neoplasias Ováricas/genética , Neoplasias Ováricas/patología , Neoplasias Ováricas/mortalidad , Neoplasias Ováricas/metabolismo , Clasificación del Tumor , Cistadenocarcinoma Seroso/genética , Cistadenocarcinoma Seroso/patología , Cistadenocarcinoma Seroso/mortalidad , Cistadenocarcinoma Seroso/metabolismo , Biomarcadores de Tumor/genética , Medición de Riesgo/métodos , Perfilación de la Expresión Génica , Persona de Mediana EdadRESUMEN
BACKGROUND: High-grade serous ovarian cancer (HGSOC), which is known for its heterogeneity, high recurrence rate, and metastasis, is often diagnosed after being dispersed in several sites, with about 80% of patients experiencing recurrence. Despite a better understanding of its metastatic nature, the survival rates of patients with HGSOC remain poor. METHODS: Our study utilized spatial transcriptomics (ST) to interpret the tumor microenvironment and computed tomography (CT) to examine spatial characteristics in eight patients with HGSOC divided into recurrent (R) and challenging-to-collect non-recurrent (NR) groups. RESULTS: By integrating ST data with public single-cell RNA sequencing data, bulk RNA sequencing data, and CT data, we identified specific cell population enrichments and differentially expressed genes that correlate with CT phenotypes. Importantly, we elucidated that tumor necrosis factor-α signaling via NF-κB, oxidative phosphorylation, G2/M checkpoint, E2F targets, and MYC targets served as an indicator of recurrence (poor prognostic markers), and these pathways were significantly enriched in both the R group and certain CT phenotypes. In addition, we identified numerous prognostic markers indicative of nonrecurrence (good prognostic markers). Downregulated expression of PTGDS was linked to a higher number of seeding sites (≥ 3) in both internal HGSOC samples and public HGSOC TCIA and TCGA samples. Additionally, lower PTGDS expression in the tumor and stromal regions was observed in the R group than in the NR group based on our ST data. Chemotaxis-related markers (CXCL14 and NTN4) and markers associated with immune modulation (DAPL1 and RNASE1) were also found to be good prognostic markers in our ST and radiogenomics analyses. CONCLUSIONS: This study demonstrates the potential of radiogenomics, combining CT and ST, for identifying diagnostic and therapeutic targets for HGSOC, marking a step towards personalized medicine.
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High-grade serous ovarian cancer (HGSC) is an aggressive disease with poor prognosis. The oncoprotein ZNF703 is implicated in driving HGSC pathogenesis, but factors regulating its abundance remain unclear. In this study, we aim to investigate the potential connection between ZNF703 dysregulation and ubiquitin-mediated protein degradation in HGSC. Bioinformatics prediction was performed using BioGRID database. HGSC representative cell lines were utilized for in vitro and in vivo studies. Results showed that ZNF703 protein was stabilized upon proteasome inhibition, suggesting a regulation via ubiquitination. The ubiquitin E3 ligase PARK2 was found to interact with ZNF703 in a dose-dependent manner, promoting its polyubiquitination and subsequent proteasomal degradation. Re-expression of PARK2 in HGSC cells led to reduced ZNF703 levels together with decreased Cyclin D1/E1 abundance and G1 cell cycle arrest. ZNF703 overexpression alone increased S phase cells, Cyclin D1/E1 levels, and xenograft tumor growth, while co-expression with PARK2 mitigated these oncogenic effects. Collectively, our findings identify ZNF703 as a bona fide substrate of PARK2, reveal a tumor suppressive function for PARK2 in attenuating ZNF703-mediated G1/S transition and HGSC growth through instigating its degradation. This study elucidates a pivotal PARK2-ZNF703 axis with therapeutic implications for targeted intervention in HGSC.
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Proliferación Celular , Cistadenocarcinoma Seroso , Neoplasias Ováricas , Complejo de la Endopetidasa Proteasomal , Ubiquitina-Proteína Ligasas , Humanos , Femenino , Neoplasias Ováricas/patología , Neoplasias Ováricas/metabolismo , Neoplasias Ováricas/genética , Ubiquitina-Proteína Ligasas/metabolismo , Ubiquitina-Proteína Ligasas/genética , Complejo de la Endopetidasa Proteasomal/metabolismo , Cistadenocarcinoma Seroso/patología , Cistadenocarcinoma Seroso/metabolismo , Cistadenocarcinoma Seroso/genética , Línea Celular Tumoral , Animales , Ratones , Ubiquitinación , Ciclina D1/metabolismo , Ciclina D1/genética , Proteínas Oncogénicas/metabolismo , Proteínas Oncogénicas/genética , Ratones Desnudos , Proteolisis , Ciclina E/metabolismo , Ciclina E/genética , Ratones Endogámicos BALB C , Ensayos Antitumor por Modelo de Xenoinjerto , Regulación Neoplásica de la Expresión Génica , Proteínas PortadorasRESUMEN
High-grade serous ovarian cancer (HGSOC) is an aggressive disease known to develop resistance to chemotherapy. We investigated the prognostic significance of tumor cell states and potential mechanisms underlying chemotherapy resistance in HGSOC. Transcriptome deconvolution was performed to address cellular heterogeneity. Kaplan-Meier survival curves were plotted to illustrate the outcomes of patients with varying cellular abundances. The association between gene expression and chemotherapy response was tested. After adjusting for surgery status and grading, several cell states exhibited a significant correlation with patient survival. Cell states can organize into carcinoma ecotypes (CE). CE9 and CE10 were proinflammatory, characterized by higher immunoreactivity, and were associated with favorable survival outcomes. Ratios of cell states and ecotypes had better prognostic abilities than a single cell state or ecotype. A total of 1265 differentially expressed genes were identified between samples with high and low levels of C9 or CE10. These genes were partitioned into three co-expressed modules, which were associated with tumor cells and immune cells. Pogz was identified to be linked with immune cell genes and the chemotherapy response of paclitaxel. Collectively, the survival of HGSOC patients is correlated with specific cell states and ecotypes.
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Cistadenocarcinoma Seroso , Neoplasias Ováricas , Femenino , Humanos , Neoplasias Ováricas/mortalidad , Neoplasias Ováricas/genética , Neoplasias Ováricas/patología , Neoplasias Ováricas/inmunología , Neoplasias Ováricas/tratamiento farmacológico , Cistadenocarcinoma Seroso/genética , Cistadenocarcinoma Seroso/mortalidad , Cistadenocarcinoma Seroso/patología , Cistadenocarcinoma Seroso/inmunología , Pronóstico , Regulación Neoplásica de la Expresión Génica , Persona de Mediana Edad , Clasificación del Tumor , Transcriptoma , Estimación de Kaplan-Meier , Anciano , Resistencia a Antineoplásicos/genéticaRESUMEN
Dormancy in cancer is a clinical state in which residual disease remains undetectable for a prolonged duration. At a cellular level, rare cancer cells cease proliferation and survive chemotherapy and disseminate disease. We created a suspension culture model of high-grade serous ovarian cancer (HGSOC) dormancy and devised a novel CRISPR screening approach to identify survival genes in this context. In combination with RNA-seq, we discovered the Netrin signaling pathway as critical to dormant HGSOC cell survival. We demonstrate that Netrin-1, -3, and its receptors are essential for low level ERK activation to promote survival, and that Netrin activation of ERK is unable to induce proliferation. Deletion of all UNC5 family receptors blocks Netrin signaling in HGSOC cells and compromises viability during the dormancy step of dissemination in xenograft assays. Furthermore, we demonstrate that Netrin-1 and -3 overexpression in HGSOC correlates with poor outcome. Specifically, our experiments reveal that Netrin overexpression elevates cell survival in dormant culture conditions and contributes to greater spread of disease in a xenograft model of abdominal dissemination. This study highlights Netrin signaling as a key mediator HGSOC cancer cell dormancy and metastasis.
High-grade serous ovarian cancer (or HGSOC for short) is the fifth leading cause of cancer-related deaths in women. It is generally diagnosed at an advanced stage of disease when the cancer has already spread to other parts of the body. Surgical removal of tumors and subsequent treatment with chemotherapy often reduces the signs and symptoms of the disease for a time but some cancer cells tend to survive so that patients eventually relapse. The HGSOC cells typically spread from the ovaries by moving through the liquid surrounding organs in the abdomen. The cells clump together and enter an inactive state known as dormancy that allows them to survive chemotherapy and low-nutrient conditions. Understanding how to develop new drug therapies that target dormant cancer cells is thought to be an important step in prolonging the life of HGSOC patients. Cancer cells are hardwired to multiply and grow, so Perampalam et al. reasoned that becoming dormant poses challenges for HGSOC cells, which may create unique vulnerabilities not shared by proliferating cancer cells. To find out more, the researchers used HGSOC cells that had been isolated from patients and grown in the laboratory. The team used a gene editing technique to screen HGSOC cells for genes required by the cells to survive when they are dormant. The experiments found that genes involved in a cell signaling pathway, known as Netrin signaling, were critical for the cells to survive. Previous studies have shown that Netrin signaling helps the nervous system form in embryos and inhibits a program of controlled cell death in some cancers. Perampalam et al. discovered that Netrins were present in the environment immediately surrounding dormant HGSOC cells. Human HGSOC patients with higher levels of Netrin gene expression had poorer prognoses than patients with lower levels of Netrin gene expression. Further experiments demonstrated that Netrins help dormant HGSOC cells to spread around the body. These findings suggest that Netrin signalling may provide useful targets for future drug therapies against dormant cells in some ovarian cancers. This could include repurposing drugs already in development or creating new inhibitors of this pathway.
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Carcinoma Epitelial de Ovario , Supervivencia Celular , Netrinas , Neoplasias Ováricas , Transducción de Señal , Humanos , Femenino , Animales , Línea Celular Tumoral , Carcinoma Epitelial de Ovario/genética , Carcinoma Epitelial de Ovario/metabolismo , Carcinoma Epitelial de Ovario/patología , Neoplasias Ováricas/genética , Neoplasias Ováricas/patología , Neoplasias Ováricas/metabolismo , Netrinas/metabolismo , Netrinas/genética , Ratones , Netrina-1/metabolismo , Netrina-1/genética , Proliferación Celular , Receptores de Netrina/metabolismo , Receptores de Netrina/genéticaRESUMEN
PURPOSE: To investigate the value of microstructural characteristics derived from time-dependent diffusion MRI in distinguishing high-grade serous ovarian cancer (HGSOC) from serous borderline ovarian tumor (SBOT) and the associations of immunohistochemical markers with microstructural features. METHODS: Totally 34 HGSOC and 12 SBOT cases who received preoperative pelvic MRI were retrospectively included in this study. Two radiologists delineated the tumors to obtain the regions of interest (ROIs). Time-dependent diffusion MRI signals were fitted by the IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) model, to extract microstructural parameters, including fraction of the intracellular component (fin), cell diameter (d), cellularity and extracellular diffusivity (Dex). Apparent diffusion coefficient (ADC) values were obtained from standard diffusion-weighted imaging (DWI). The parameters of HGSOCs and SBOTs were compared, and the diagnostic performance was evaluated. The associations of microstructural indexes with immunopathological parameters were assessed, including Ki-67, P53, Pax-8, ER and PR. RESULTS: In this study, fin, cellularity, Dex and ADC had good diagnostic performance levels in differentiating HGSOC from SBOT, with AUCs of 0.936, 0.909, 0.902 and 0.914, respectively. There were no significant differences in diagnostic performance among these parameters. Spearman analysis revealed in the HGSOC group, cellularity had a significant positive correlation with P53 expression (P = 0.028, r = 0.389) and Dex had a significant positive correlation with Pax-8 expression (P = 0.018, r = 0.415). ICC showed excellent agreement for all parameters. CONCLUSION: Time-dependent diffusion MRI had value in evaluating the microstructures of HGSOC and SBOT and could discriminate between these tumors.
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Imagen de Difusión por Resonancia Magnética , Neoplasias Ováricas , Humanos , Femenino , Neoplasias Ováricas/diagnóstico por imagen , Neoplasias Ováricas/patología , Imagen de Difusión por Resonancia Magnética/métodos , Persona de Mediana Edad , Diagnóstico Diferencial , Estudios Retrospectivos , Adulto , Anciano , Cistadenocarcinoma Seroso/diagnóstico por imagen , Cistadenocarcinoma Seroso/patología , Clasificación del Tumor , Sensibilidad y Especificidad , Reproducibilidad de los ResultadosRESUMEN
OBJECTIVE: To determine the safety and efficacy of the oral progesterone antagonist onapristone extended release (onapristone-XR) in patients with recurrent progesterone receptor (PR)-positive adult-type granulosa cell tumor (aGCT), low-grade serous ovarian cancer (LGSOC), or endometrioid endometrial cancer (EEC). METHODS: This single-institution phase II study included patients with PR-positive aGCT, LGSOC, or EEC who received ≥1 prior line of chemotherapy. Patients were enrolled from 5/2019-5/2020. PR status was evaluated via immunohistochemistry. Eligible patients had PR expression ≥1% on tissue collected within 3 years of enrollment. Patients received 50 mg of onapristone-XR twice daily until disease progression or treatment discontinuation. Adverse events were graded by Common Terminology Criteria for Adverse Events version 5.0. The primary endpoint was overall response rate (ORR) by Response Evaluation Criteria in Solid Tumors 1.1. Secondary endpoints were response duration, clinical benefit rate (CBR), and safety. RESULTS: Five patients with LGSOC and 1 with EEC enrolled, but both cohorts closed early due to slow accrual. Fourteen patients with aGCT enrolled and completed stage 1 accrual. No responses were observed. Four patients with LGSOC were evaluable, with median PFS of 4.4 months (range, 1.8-NE) and CBR of 50% (range, 6.8%-93.2%). All 14 patients with aGCT were evaluable, with median PFS of 2.8 months (range, 1.6-4.9), 6-month PFS rate of 21.4% (range, 5.2%-44.8%), 12-month PFS rate of 14.3% (range, 2.3%-36.6%), and a CBR of 35.7% (range, 12.8%-64.9%). CONCLUSIONS: The study did not meet its primary endpoint. While onapristone-XR was well tolerated in all 3 arms, no objective responses were observed.
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Carcinoma Endometrioide , Neoplasias Endometriales , Tumor de Células de la Granulosa , Recurrencia Local de Neoplasia , Neoplasias Ováricas , Receptores de Progesterona , Humanos , Femenino , Persona de Mediana Edad , Anciano , Receptores de Progesterona/metabolismo , Neoplasias Endometriales/tratamiento farmacológico , Neoplasias Endometriales/patología , Recurrencia Local de Neoplasia/tratamiento farmacológico , Carcinoma Endometrioide/tratamiento farmacológico , Carcinoma Endometrioide/patología , Carcinoma Endometrioide/metabolismo , Neoplasias Ováricas/tratamiento farmacológico , Neoplasias Ováricas/patología , Neoplasias Ováricas/metabolismo , Tumor de Células de la Granulosa/tratamiento farmacológico , Tumor de Células de la Granulosa/metabolismo , Tumor de Células de la Granulosa/patología , Adulto , Gonanos/administración & dosificación , Gonanos/efectos adversos , Preparaciones de Acción Retardada/administración & dosificación , Anciano de 80 o más Años , Administración Oral , Cistadenocarcinoma Seroso/tratamiento farmacológico , Cistadenocarcinoma Seroso/patología , Cistadenocarcinoma Seroso/metabolismoRESUMEN
The high mortality rate due to chemoresistance in patients with high-grade ovarian cancer (HGSOC) emphasizes the urgent need to determine optimal treatment strategies for advanced and recurrent cases. Our study investigates the interplay between estrogens and chemoresistance in HGSOC and shows clear differences between platinum-sensitive and -resistant tumors. Through comprehensive transcriptome analyzes, we uncover differences in the expression of genes of estrogen biosynthesis, metabolism, transport and action underlying platinum resistance in different tissues of HGSOC subtypes and in six HGSOC cell lines. Furthermore, we identify genes involved in estrogen biosynthesis and metabolism as prognostic biomarkers for HGSOC. Additionally, our study elucidates different patterns of estrogen formation/metabolism and their effects on cell proliferation between six HGSOC cell lines with different platinum sensitivity. These results emphasize the dynamic interplay between estrogens and HGSOC chemoresistance. In particular, targeting the activity of steroid sulfatase (STS) proves to be a promising therapeutic approach with potential efficacy in limiting estrogen-driven cell proliferation. Our study reveals potential prognostic markers as well as identifies novel therapeutic targets that show promise for overcoming resistance and improving treatment outcomes in HGSOC.
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Proliferación Celular , Resistencia a Antineoplásicos , Estrógenos , Neoplasias Ováricas , Femenino , Humanos , Neoplasias Ováricas/tratamiento farmacológico , Neoplasias Ováricas/patología , Neoplasias Ováricas/metabolismo , Neoplasias Ováricas/genética , Estrógenos/metabolismo , Línea Celular Tumoral , Proliferación Celular/efectos de los fármacos , Clasificación del Tumor , Regulación Neoplásica de la Expresión Génica , Cistadenocarcinoma Seroso/tratamiento farmacológico , Cistadenocarcinoma Seroso/patología , Cistadenocarcinoma Seroso/metabolismo , Cistadenocarcinoma Seroso/genética , Antineoplásicos/farmacología , Antineoplásicos/uso terapéutico , Platino (Metal)/farmacología , Platino (Metal)/uso terapéuticoRESUMEN
BACKGROUND: This study aimed to develop and evaluate radiomics models to predict CD27 expression and clinical prognosis before surgery in patients with serous ovarian cancer (SOC). METHODS: We used transcriptome sequencing data and contrast-enhanced computed tomography images of patients with SOC from The Cancer Genome Atlas (n = 339) and The Cancer Imaging Archive (n = 57) and evaluated the clinical significance and prognostic value of CD27 expression. Radiomics features were selected to create a recursive feature elimination-logistic regression (RFE-LR) model and a least absolute shrinkage and selection operator logistic regression (LASSO-LR) model for CD27 expression prediction. RESULTS: CD27 expression was upregulated in tumor samples, and a high expression level was determined to be an independent protective factor for survival. A set of three and six radiomics features were extracted to develop RFE-LR and LASSO-LR radiomics models, respectively. Both models demonstrated good calibration and clinical benefits, as determined by the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis. The LASSO-LR model performed better than the RFE-LR model, owing to the area under the curve (AUC) values of the ROC curves (0.829 vs. 0.736). Furthermore, the AUC value of the radiomics score that predicted the overall survival of patients with SOC diagnosed after 60 months was 0.788 using the LASSO-LR model. CONCLUSION: The radiomics models we developed are promising noninvasive tools for predicting CD27 expression status and SOC prognosis. The LASSO-LR model is highly recommended for evaluating the preoperative risk stratification for SOCs in clinical applications.
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Neoplasias Ováricas , Tomografía Computarizada por Rayos X , Humanos , Femenino , Neoplasias Ováricas/diagnóstico por imagen , Neoplasias Ováricas/genética , Neoplasias Ováricas/metabolismo , Neoplasias Ováricas/patología , Pronóstico , Tomografía Computarizada por Rayos X/métodos , Persona de Mediana Edad , Miembro 7 de la Superfamilia de Receptores de Factores de Necrosis Tumoral/metabolismo , Miembro 7 de la Superfamilia de Receptores de Factores de Necrosis Tumoral/genética , Cistadenocarcinoma Seroso/diagnóstico por imagen , Cistadenocarcinoma Seroso/genética , Cistadenocarcinoma Seroso/patología , Cistadenocarcinoma Seroso/metabolismo , Anciano , Adulto , Curva ROC , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , RadiómicaRESUMEN
High-grade serous ovarian cancer (HGSOC) and ovarian clear cell carcinoma (CC), are biologically aggressive tumors endowed with the ability to rapidly metastasize to the abdominal cavity and distant organs. About 10% of HGSOC and 30% of CC demonstrate HER2 IHC 3 + receptor over-expression. We evaluated the efficacy of trastuzumab deruxtecan (T-DXd; DS-8201a), a novel HER2-targeting antibody-drug conjugate (ADC) to an ADC isotype control (CTL ADC) against multiple HGSOC and CC tumor models. Eleven ovarian cancer cell lines including a matched primary and metastatic cell line established from the same patient, were evaluated for HER2 expression by immunohistochemistry and flow cytometry, and gene amplification by fluorescence in situ hybridization assays. In vitro experiments demonstrated T-DXd to be significantly more effective against HER2 3 + HGSOC and CC cell lines when compared to CTL ADC (p < 0.0001). T-DXd induced efficient bystander killing of HER2 non-expressing tumor cells when admixed with HER2 3 + cells. In vivo activity of T-DXd was studied in HER2 IHC 3 + HGSOC and CC mouse xenograft models. We found T-DXd to be significantly more effective than CTL ADC against HER2 3 + HGSOC (KR(CH)31) and CC (OVA10) xenografts with a significant difference in tumor growth starting at day 8 (p = 0.0003 for KR(CH)31, p < 0.0001 for OVA10). T-DXd also conferred a survival advantage in both xenograft models. T-DXd may represent an effective ADC against primary and metastatic HER2-overexpressing HGSOC and CC.
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Patients with High-Grade Serous Ovarian Cancer (HGSOC) exhibit varied responses to treatment, with 20-30% showing de novo resistance to platinum-based chemotherapy. While hematoxylin-eosin (H&E) pathological slides are used for routine diagnosis of cancer type, they may also contain diagnostically useful information about treatment response. Our study demonstrates that combining H&E-stained Whole Slide Images (WSIs) with proteomic signatures using a multimodal deep learning framework significantly improves the prediction of platinum response in both discovery and validation cohorts. This method outperforms the Homologous Recombination Deficiency (HRD) score in predicting platinum response and overall patient survival. The study sets new performance benchmarks and explores the intersection of histology and proteomics, highlighting phenotypes related to treatment response pathways, including homologous recombination, DNA damage response, nucleotide synthesis, apoptosis, and ER stress. This integrative approach has the potential to improve personalized treatment and provide insights into the therapeutic vulnerabilities of HGSOC.
RESUMEN
Low-grade serous ovarian cancer (LGSOC) is a very rare histological subtype of serous ovarian cancer, representing ~2% of all epithelial ovarian cancer cases. LGSOC has a better prognosis but a lower response rate to chemotherapy in comparison to high-grade serous ovarian carcinoma (HGSOC). The present study is a retrospective review of the medical records of all patients with histologically proven LGSOC diagnosed and treated in a single institute between January 2003 and December 2019. A total of 23 patients diagnosed with LGSOC and treated at King Faisal Specialist Hospital and Research Center (Riyadh, Saudi Arabia) were identified. The median age at diagnosis was 45.5 years (range, 26-66 years) and the median body mass index was 26.1 (range, 18-43). A total of 21 patients (91.3%) had de novo LGSOC, whereas only 2 patients (8.7%) had LGSOC that had transformed from serous borderline ovarian tumors and recurred. A total of 8 patients (34.8%) were diagnosed with International Federation of Gynecology and Obstetrics stage IV, whereas 3 (13.0%), 3 (13.0%) and 9 (39.1%) were diagnosed with stages I, II and III, respectively. In addition, 10 (43.5%), 5 (21.7%), and 3 (13.0%) patients had complete response, stable disease and partial response statuses after first-line therapy, respectively. At a median follow-up time of 34 months [95% confidence interval (CI), 25.32-42.69], the median progression-free survival (PFS) time was 75.2 months (95% CI, 17.35-133.05) and the median overall survival (OS) time was not reached. In conclusion, LGSOC exhibited better PFS and OS times than HGSOC as compared with data from the literature, and there is the option for systemic treatment (chemotherapy or hormonal therapy). Optimal cytoreduction showed numerically higher, but non-significant, PFS and OS times compared with suboptimal debulking; however, the optimal systemic chemotherapy or hormonal treatment remains controversial.
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High grade serous ovarian cancer (HGSOC) is a lethal gynecologic malignancy in which chemoresistant recurrence rates remain high. Furthermore, HGSOC patients have demonstrated overall low response rates to clinically available immunotherapies. Amphiregulin (AREG), a low affinity epidermal growth factor receptor ligand is known to be significantly upregulated in HGSOC patient tumors following neoadjuvant chemotherapy exposure. While much is known about AREG's role in oncogenesis and classical immunity, it is function in tumor immunology has been comparatively understudied. Therefore, the objective of this present study was to elucidate how increased AREG exposure impacts the ovarian tumor immune microenvironment (OTIME). Using NanoString IO 360 and protein analysis, it was revealed that treatment with recombinant AREG led to prominent upregulation of genes associated with ovarian pathogenesis and immune evasion (CXCL8, CXCL1, CXCL2) along with increased STAT3 activation in HGSOC cells. In vitro co-culture assays consisting of HGSOC cells and peripheral blood mononuclear cells (PBMCs) stimulated with recombinant AREG (rAREG) led to significantly enhanced tumor cell viability. Moreover, PBMCs stimulated with rAREG exhibited significantly lower levels of IFNy and IL-2. In vivo rAREG treatment promoted significant reductions in circulating levels of IL-2 and IL-5. Intratumoral analysis of rAREG treated mice revealed a significant reduction in CD8+ T cells coupled with an upregulation of PD-L1. Finally, combinatorial treatment with an AREG neutralizing antibody and carboplatin led to a synergistic reduction of cell viability in HGSOC cell lines OVCAR8 and PEA2. Overall, this study demonstrates AREG's ability to modulate cytotoxic responses within the OTIME and highlights its role as a novel HGSOC immune target.