Ovarian Cancer, the Revised FIGO Staging System, and the Role of Imaging

The tipping point: Key oncologic imaging findings resulting in critical changes in the management of malignant genitourinary and gynecological tumors

OBJECTIVE

The purpose of this article is to review the staging systems for common malignant genitourinary and gynecological tumors, including renal cell carcinoma, urinary bladder carcinoma, as well as cervical, endometrial, and ovarian carcinoma, and to highlight the key imaging findings ("tipping points") that may alter patient management algorithms based on radiological staging.

CONCLUSION

There are identifiable imaging features for the common genitourinary and gynecological malignancies, including the size of the primary tumor, tumor extension, invasion of adjacent structures, lymph node involvement, and distant metastasis, which provide important prognostic information and determine patient management. Radiologists must be aware of these imaging findings ("tipping points") when interpreting staging examinations.

Trials of interventions for ovarian and testicular germ cell tumors registered in ClinicalTrials.gov: A cross-sectional study

INTRODUCTION

There is unmet need in the treatment of ovarian and testicular germ cell tumors (GCTs). This study analyzed registered trials of interventions for GCTs.

MATERIALS AND METHODS

We included trials of interventions for GCTs registered on ClinicalTrials.gov by July 29, 2022. We analyzed their interventions, outcome measures and study design.

RESULTS

We included 142 trials registrations; 42 (30 %) for ovarian GCTs, 50 (35 %) for testicular GCTs, and 50 (35 %) trials for both. The majority of the trials were completed (56 %) and did not have results available (75 %). Most trials were in Phase 2. Information about the study design were not reported for many analyzed trials. Most trials had a single-group assignment (44 %) and were open-label (68 %). The median planned number of enrolled participants was 43. Most registrations used medicine(s) (87 %), either as a single type of intervention or in combination. The most commonly used type of medicine was chemotherapy (54 %). Primary outcome was not reported in 23 % of registrations, and secondary outcomes were not reported in 35 % of registrations. Overall survival was used in 6 % of registrations as a primary outcome and in 31 % of registrations as a secondary outcome.

CONCLUSIONS

Few trials on GCTs were registered on ClinicalTrials.gov, and their number was declining in recent times. Most registrations did not report relevant information about the study design, or results if completed. More effort is needed to foster trials on GCTs, as well as to optimize the management of the registrations and foster the publication of research results.

A modified diffusion-weighted magnetic resonance imaging-based model from the radiologist's perspective: improved performance in determining the surgical resectability of advanced high-grade serous ovarian cancer

BACKGROUND

Complete resection of all visible lesions during primary debulking surgery is associated with the most favorable prognosis in patients with advanced high-grade serous ovarian cancer. An accurate preoperative assessment of resectability is pivotal for tailored management.

OBJECTIVE

This study aimed to assess the potential value of a modified model that integrates the original 8 radiologic criteria of the Memorial Sloan Kettering Cancer Center model with imaging features of the subcapsular or diaphragm and mesenteric lesions depicted on diffusion-weighted magnetic resonance imaging and growth patterns of all lesions for predicting the resectability of advanced high-grade serous ovarian cancer.

STUDY DESIGN

This study included 184 patients with high-grade serous ovarian cancer who underwent preoperative diffusion-weighted magnetic resonance imaging between December 2018 and May 2023 at 2 medical centers. The patient cohort was divided into 3 subsets, namely a study cohort (n=100), an internal validation cohort (n=46), and an external validation cohort (n=38). Preoperative radiologic evaluations were independently conducted by 2 radiologists using both the Memorial Sloan Kettering Cancer Center model and the modified diffusion-weighted magnetic resonance imaging-based model. The morphologic characteristics of the ovarian tumors depicted on magnetic resonance imaging were assessed as either mass-like or infiltrative, and transcriptomic analysis of the primary tumor samples was performed. Univariate and multivariate statistical analyses were performed.

RESULTS

In the study cohort, both the scores derived using the Memorial Sloan Kettering Cancer Center (intraclass correlation coefficients of 0.980 and 0.959, respectively; both P<.001) and modified diffusion-weighted magnetic resonance imaging-based models (intraclass correlation coefficients of 0.962 and 0.940, respectively; both P<.001) demonstrated excellent intra- and interobserver agreement. The Memorial Sloan Kettering Cancer Center model (odds ratio, 1.825; 95% confidence interval, 1.390-2.395; P<.001) and the modified diffusion-weighted magnetic resonance imaging-based model (odds ratio, 1.776; 95% confidence interval, 1.410-2.238; P<.001) independently predicted surgical resectability. The modified diffusion-weighted magnetic resonance imaging-based model demonstrated improved predictive performance with an area under the curve of 0.867 in the study cohort and 0.806 and 0.913 in the internal and external validation cohorts, respectively. Using the modified diffusion-weighted magnetic resonance imaging-based model, patients with scores of 0 to 2, 3 to 4, 5 to 6, 7 to 10, and ≥11 achieved complete tumor debulking rates of 90.3%, 66.7%, 53.3%, 11.8%, and 0%, respectively. Most patients with incomplete tumor debulking had infiltrative tumors, and both the Memorial Sloan Kettering Cancer Center and the modified diffusion-weighted magnetic resonance imaging-based models yielded higher scores. The molecular differences between the 2 morphologic subtypes were identified.

CONCLUSION

When compared with the Memorial Sloan Kettering Cancer Center model, the modified diffusion-weighted magnetic resonance imaging-based model demonstrated enhanced accuracy in the preoperative prediction of resectability for advanced high-grade serous ovarian cancer. Patients with scores of 0 to 6 were eligible for primary debulking surgery.

Protocol for identifying metabolite biomarkers in patient uterine fluid for early ovarian cancer detection

High mortality of ovarian cancer (OC) is primarily attributed to the lack of effective early detection methods. Uterine fluid, pooling molecules from neighboring ovaries, presents an organ-specific advantage over conventional blood samples. Here, we present a protocol for identifying metabolite biomarkers in uterine fluid for early OC detection. We describe steps for uterine fluid collection from patients, metabolite extraction, metabolomics experiments, and candidate metabolite biomarker screening. This standardized workflow holds the potential to achieve early OC diagnosis in clinical practice. For complete details on the use and execution of this protocol, please refer to Wang et al.1.

Diagnostic accuracy and clinical value of [68Ga]Ga-FAPI-46 PET/CT for staging patients with ovarian cancer: study protocol for a prospective clinical trial

BACKGROUND

[18F]Fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) is recommended during diagnostic work-up for ovarian cancer; however, [18F]FDG PET has several inherent limitations. The novel oncologic PET-tracer fibroblast activation protein inhibitor (FAPI) has demonstrated promising results in multiple cancer types, including ovarian cancer, and could overcome the limitations of [18F]FDG PET; however, high-quality clinical studies are lacking. The primary objective of the present study is to compare the diagnostic accuracy of [68Ga]Ga-FAPI-46 PET/CT and [18F]FDG PET/CT in ovarian cancer patients and to investigate how this potential difference impacts staging and patient management.

METHODS AND DESIGN

Fifty consecutive ovarian cancer patients will be recruited from Aalborg University Hospital, Denmark. This study will be a single-center, prospective, exploratory clinical trial that adheres to the standards for reporting diagnostic accuracy studies (STARD). This study will be conducted under continuous Good Clinical Practice monitoring. The eligibility criteria for patients are as follows: (1) biopsy verified newly diagnosed ovarian cancer or a high risk of ovarian cancer and referred for primary staging with [18F]FDG PET/CT; and (2) resectable disease, i.e., candidate for primary debulking surgery or neoadjuvant chemotherapy followed by interval debulking surgery. All recruited study subjects will undergo [68Ga]Ga-FAPI-46 PET/CT at primary staging, before primary debulking surgery or neoadjuvant chemotherapy (Group A + B), in addition to conventional imaging (including [18F]FDG PET/CT). Study subjects in Group B will undergo an additional [68Ga]Ga-FAPI-46 PET/CT following neoadjuvant chemotherapy prior to interval debulking surgery. The results of the study-related [68Ga]Ga-FAPI-46 PET/CTs will be blinded, and treatment allocation will be based on common clinical practice in accordance with current guidelines. The histopathology of surgical specimens will serve as a reference standard. A recruitment period of 2 years is estimated; the trial is currently recruiting.

DISCUSSION

To our knowledge, this trial represents the largest, most extensive, and most meticulous prospective FAPI PET study conducted in patients with ovarian cancer thus far. This study aims to obtain a reliable estimation of the diagnostic accuracy of [68Ga]Ga-FAPI-46 PET/CT, shed light on the clinical importance of [68Ga]Ga-FAPI-46 PET/CT, and examine the potential applicability of [68Ga]Ga-FAPI-46 PET/CT for evaluating chemotherapy response.

TRIAL REGISTRATION

clinicaltrials.gov: NCT05903807, 2nd June 2023; and euclinicaltrials.eu EU CT Number: 2023-505938-98-00, authorized 11th September 2023.

Adenocarcinoma of Mullerian Origin Found Through an Elective Inguinal Hernia Resection: A Case Report

We report an asymptomatic 59-year-old female undergoing an elective umbilical hernia excision who was found to have an ovarian adenocarcinoma within the excised hernia. Patients are rarely diagnosed with cancer after an umbilical hernia excision. An excised hernia is rarely the means for an initial diagnosis of cancer. We describe a case of an ovarian carcinoma incidentally found through an umbilical hernia excision with consequential treatment with neoadjuvant platinum-based chemotherapy followed by debulking surgery with a total hysterectomy with bilateral salpingo-oophorectomy with a transoperative pathology report of a high-grade serous carcinoma located in the left fimbrial frond surrounded by a background of serous tubal intraepithelial carcinomas. This case demonstrates the need to perform histological examinations of all excised hernias, even in asymptomatic patients, as malignancy can be found inside a hernia, and it emphasizes the importance of considering adenocarcinomas of Mullerian origin in the differential diagnosis of a malignancy found in a hernia in an asymptomatic female patient.

A Perspective Review: Analyzing Collagen Alterations in Ovarian Cancer by High-Resolution Optical Microscopy

High-grade serous ovarian cancer (HGSOC) is the predominant subtype of ovarian cancer (OC), occurring in more than 80% of patients diagnosed with this malignancy. Histological and genetic analysis have confirmed the secretory epithelial of the fallopian tube (FT) as a major site of origin of HGSOC. Although there have been significant strides in our understanding of this disease, early stage detection and diagnosis are still rare. Current clinical imaging modalities lack the ability to detect early stage pathogenesis in the fallopian tubes and the ovaries. However, there are several microscopic imaging techniques used to analyze the structural modifications in the extracellular matrix (ECM) protein collagen in ex vivo FT and ovarian tissues that potentially can be modified to fit the clinical setting. In this perspective, we evaluate and compare the myriad of optical tools available to visualize these alterations and the invaluable insights these data provide on HGSOC initiation. We also discuss the clinical implications of these findings and how these data may help novel tools for early diagnosis of HGSOC.

Imaging of Peritoneal Metastases in Ovarian Cancer Using MDCT, MRI, and FDG PET/CT: A Systematic Review and Meta-Analysis

This review aims to compare the diagnostic performance of multidetector CT (MDCT), MRI, including diffusion-weighted imaging, and FDG PET/CT in the detection of peritoneal metastases (PMs) in ovarian cancer (OC). A comprehensive search was performed for articles published from 2000 to February 2023. The inclusion criteria were the following: diagnosis/suspicion of PMs in patients with ovarian/fallopian/primary peritoneal cancer; initial staging or suspicion of recurrence; MDCT, MRI and/or FDG PET/CT performed for the detection of PMs; population of at least 10 patients; surgical results, histopathologic analysis, and/or radiologic follow-up, used as reference standard; and per-patient and per-region data and data for calculating sensitivity and specificity reported. In total, 33 studies were assessed, including 487 women with OC and PMs. On a per-patient basis, MRI (p = 0.03) and FDG PET/CT (p < 0.01) had higher sensitivity compared to MDCT. MRI and PET/CT had comparable sensitivities (p = 0.84). On a per-lesion analysis, no differences in sensitivity estimates were noted between MDCT and MRI (p = 0.25), MDCT and FDG PET/CT (p = 0.68), and MRI and FDG PET/CT (p = 0.35). Based on our results, FDG PET/CT and MRI are the preferred imaging modalities for the detection of PMs in OC. However, the value of FDG PET/CT and MRI compared to MDCT needs to be determined. Future research to address the limitations of the existing studies and the need for standardization and to explore the cost-effectiveness of the three imaging modalities is required.

Endometriosis-Related Ovarian Cancer: Where Are We Now? A Narrative Review towards a Pragmatic Approach

BACKGROUND

Endometriosis affects more than 10% of reproductive-aged women, causing pelvic pain and infertility. Despite the benign nature of endometriosis, ovarian endometriomas carry a higher risk of developing endometrioid carcinomas (EnOCs) and clear cell ovarian carcinomas (CCCs). Atypical endometriosis, defined as cytological atypia resembling intraepithelial cancer, is considered the precursor of endometriosis-associated ovarian cancer (EAOC). This narrative review aims to provide an overview of EAOC, proposing a practical approach to clinical and therapeutic decision making.

METHODS

An electronic literature search was conducted from inception up to January 2023, using the MEDLINE database via PubMed to evaluate the existing literature on EAOC, including its pathogenesis, the diagnostic process, and the therapeutic possibilities, with articles not relevant to the topic or lacking scientific merit being excluded.

RESULTS

Eighty-one articles were included in the review to present the current state of the art regarding EAOC. A pragmatic clinical flowchart is proposed to guide therapeutic decisions and improve patient outcomes.

CONCLUSIONS

Endometriosis patients may have an increased risk of developing EAOC (either EnOC or CCC). Despite not being fully accepted, the concept of AE may reshape the endometriosis-ovarian cancer relationship. Further research is needed to understand the unaddressed issues.

Contrast-enhanced CT radiomics for preoperative prediction of stage in epithelial ovarian cancer: a multicenter study

BACKGROUND

Preoperative prediction of International Federation of Gynecology and Obstetrics (FIGO) stage in patients with epithelial ovarian cancer (EOC) is crucial for determining appropriate treatment strategy. This study aimed to explore the value of contrast-enhanced CT (CECT) radiomics in predicting preoperative FIGO staging of EOC, and to validate the stability of the model through an independent external dataset.

METHODS

A total of 201 EOC patients from three centers, divided into a training cohort (n = 106), internal (n = 46) and external (n = 49) validation cohorts. The least absolute shrinkage and selection operator (LASSO) regression algorithm was used for screening radiomics features. Five machine learning algorithms, namely logistic regression, support vector machine, random forest, light gradient boosting machine (LightGBM), and decision tree, were utilized in developing the radiomics model. The optimal performing algorithm was selected to establish the radiomics model, clinical model, and the combined model. The diagnostic performances of the models were evaluated through receiver operating characteristic analysis, and the comparison of the area under curves (AUCs) were conducted using the Delong test or F-test.

RESULTS

Seven optimal radiomics features were retained by the LASSO algorithm. The five radiomics models demonstrate that the LightGBM model exhibits notable prediction efficiency and robustness, as evidenced by AUCs of 0.83 in the training cohort, 0.80 in the internal validation cohort, and 0.68 in the external validation cohort. The multivariate logistic regression analysis indicated that carcinoma antigen 125 and tumor location were identified as independent predictors for the FIGO staging of EOC. The combined model exhibited best diagnostic efficiency, with AUCs of 0.95 in the training cohort, 0.83 in the internal validation cohort, and 0.79 in the external validation cohort. The F-test indicated that the combined model exhibited a significantly superior AUC value compared to the radiomics model in the training cohort (P < 0.001).

CONCLUSIONS

The combined model integrating clinical characteristics and radiomics features shows potential as a non-invasive adjunctive diagnostic modality for preoperative evaluation of the FIGO staging status of EOC, thereby facilitating clinical decision-making and enhancing patient outcomes.

The dual roles of circRNAs in Wnt/β-Catenin signaling and cancer progression

Cancer, a complex pathophysiological condition, arises from the abnormal proliferation and survival of cells due to genetic mutations. Dysregulation of cell cycle control, apoptosis, and genomic stability contribute to uncontrolled growth and metastasis. Tumor heterogeneity, microenvironmental influences, and immune evasion further complicate cancer dynamics. The intricate interplay between circular RNAs (circRNAs) and the Wnt/β-Catenin signalling pathway has emerged as a pivotal axis in the landscape of cancer biology. The Wnt/β-Catenin pathway, a critical regulator of cell fate and proliferation, is frequently dysregulated in various cancers. CircRNAs, a class of non-coding RNAs with closed-loop structures, have garnered increasing attention for their diverse regulatory functions. This review systematically explores the intricate crosstalk between circRNAs and the Wnt/β-Catenin pathway, shedding light on their collective impact on cancer initiation and progression. The review explores the diverse mechanisms through which circRNAs modulate the Wnt/β-Catenin pathway, including sponging microRNAs, interacting with RNA-binding proteins, and influencing the expression of key components in the pathway. Furthermore, the review highlights specific circRNAs implicated in various cancer types, elucidating their roles as either oncogenic or tumour-suppressive players in the context of Wnt/β-Catenin signaling. The intricate regulatory networks formed by circRNAs in conjunction with the Wnt/β-Catenin pathway are discussed, providing insights into potential therapeutic targets and diagnostic biomarkers. This comprehensive review delves into the multifaceted roles of circRNAs in orchestrating tumorigenesis through their regulatory influence on the Wnt/β-Catenin pathway.

Development and validation of an ultrasound‑based radiomics nomogram to predict lymph node status in patients with high-grade serous ovarian cancer: a retrospective analysis

BACKGROUND

Despite advances in medical imaging technology, the accurate preoperative prediction of lymph node status remains challenging in ovarian cancer. This retrospective study aimed to investigate the feasibility of using ultrasound-based radiomics combined with preoperative clinical characteristics to predict lymph node metastasis (LNM) in patients with high-grade serous ovarian cancer (HGSOC).

RESULTS

Patients with 401 HGSOC lesions from two institutions were enrolled: institution 1 for the training cohort (n = 322) and institution 2 for the external test cohort (n = 79). Radiomics features were extracted from the three preoperative ultrasound images of each lesion. During feature selection, primary screening was first performed using the sample variance F-value, followed by recursive feature elimination (RFE) to filter out the 12 most significant features for predicting LNM. The radscore derived from these 12 radiomic features and three clinical characteristics were used to construct a combined model and nomogram to predict LNM, and subsequent 10-fold cross-validation was performed. In the test phase, the three models were tested with external test cohort. The radiomics model had an area under the curve (AUC) of 0.899 (95% confidence interval [CI]: 0.864-0.933) in the training cohort and 0.855 (95%CI: 0.774-0.935) in the test cohort. The combined model showed good calibration and discrimination in the training cohort (AUC = 0.930) and test cohort (AUC = 0.881), which were superior to those of the radiomic and clinical models alone.

CONCLUSIONS

The nomogram consisting of the radscore and preoperative clinical characteristics showed good diagnostic performance in predicting LNM in patients with HGSOC. It may be used as a noninvasive method for assessing the lymph node status in these patients.

Paradigm Shift: A Comprehensive Review of Ovarian Cancer Management in an Era of Advancements

Ovarian cancer (OC) is the female genital malignancy with the highest lethality. Patients present a poor prognosis mainly due to the late clinical presentation allied with the common acquisition of chemoresistance and a high rate of tumour recurrence. Effective screening, accurate diagnosis, and personalised multidisciplinary treatments are crucial for improving patients' survival and quality of life. This comprehensive narrative review aims to describe the current knowledge on the aetiology, prevention, diagnosis, and treatment of OC, highlighting the latest significant advancements and future directions. Traditionally, OC treatment involves the combination of cytoreductive surgery and platinum-based chemotherapy. Although more therapeutical approaches have been developed, the lack of established predictive biomarkers to guide disease management has led to only marginal improvements in progression-free survival (PFS) while patients face an increasing level of toxicity. Fortunately, because of a better overall understanding of ovarian tumourigenesis and advancements in the disease's (epi)genetic and molecular profiling, a paradigm shift has emerged with the identification of new disease biomarkers and the proposal of targeted therapeutic approaches to postpone disease recurrence and decrease side effects, while increasing patients' survival. Despite this progress, several challenges in disease management, including disease heterogeneity and drug resistance, still need to be overcome.

An Unusual Presentation: High-Grade Serous Carcinoma of the Fallopian Tube Manifesting With Altered Mental Status Secondary to a Single Brain Metastasis-A Case Report and Review of the Literature

Epithelial ovarian and fallopian cancers are aggressive lesions that rarely metastasize to the central nervous system. Brain metastases usually occur in the setting of known primary disease or widespread metastatic disease. However, in extremely rare cases, an isolated intracranial neoplasm may be the first presentation of fallopian cancer. To the best of our knowledge, only one such case has been reported previously. We present an illustrative case with multimodality imaging and histopathologic correlation of a fallopian tube carcinoma first presenting with altered mental status secondary to an isolated brain metastasis. A 64-year-old female with no pertinent medical history presented with altered mentation. Initial workup identified a 1.6 cm avidly enhancing, solitary brain lesion at the gray-white junction with associated vasogenic edema concerning for either central nervous system lymphoma or metastatic disease. Additional imaging identified a 7.5 × 3 cm left adnexal lesion, initially thought to be a hydrosalpinx with hemorrhage, but magnetic resonance imaging suggested gynecologic malignancy. No lesions elsewhere in the body were identified. Given the lack of locoregional or systemic disease, the intracranial and pelvic lesions were assumed to represent synchronous but distinct processes. The intracranial lesion was biopsied. Preliminary results were suggestive of lymphoma, but further analysis was consistent with high-grade serous carcinoma of müllerian origin. Positron emission tomography/computed tomography was performed to evaluate for other neoplastic lesions, only highlighting the intracranial and pelvic lesions. At this point, a diagnosis of metastatic fallopian cancer was made. The patient was taken for robot-assisted laparoscopy with surgical debulking of the pelvic neoplasm, pathology demonstrating high-grade serous carcinoma of the fallopian tube, matching that of the intracranial lesion. Even though rare, metastatic fallopian cancer should be considered in patients with isolated brain lesions and adnexal lesions, even in the absence of locoregional or systemic disease.

Radiomics nomogram for preoperative differentiation of early-stage serous borderline ovarian tumors and serous malignant ovarian tumors

Objectives

This study aimed to construct a radiomics nomogram and validate its performance in the preoperative differentiation between early-stage (I and II) serous borderline ovarian tumors (SBOTs) and serous malignant ovarian tumors (SMOTs).

Methods

Data were collected from 80 patients with early-stage SBOTs and 102 with early-stage SMOTs (training set: n = 127; validation set: n = 55). Univariate and multivariate analyses were performed to identify the independent clinicoradiological factors. A radiomics signature model was constructed using radiomics features extracted from multidetector computed tomography images of the venous phase, in which the least absolute shrinkage and selection operator regression was employed to lessen the dimensionality of the data and choose the radiomics features. A nomogram model was established by combining independent clinicoradiological factors with the radiomics signature. The performance of nomogram calibration, discrimination, and clinical usefulness was evaluated using training and validation sets.

Results

In terms of clinicoradiological characteristics, age (p = 0.001), the diameter of the solid component (p = 0.009), and human epididymis protein 4 level (p < 0.001) were identified as the independent risk factors of SMOT, for which the area under the curves (AUCs) were calculated to be 0.850 and 0.836 in the training and validation sets, respectively. Nine features were finally selected to construct the radiomics signature model, which exhibited AUCs of 0.879 and 0.826 for the training and validation sets, respectively. The nomogram model demonstrated considerable calibration and discrimination with AUCs of 0.940 and 0.909 for the training and validation sets, respectively. The nomogram model displayed more prominent clinical usefulness than the clinicoradiological and radiomics signature models according to the decision curve analysis.

Conclusions

The nomogram model can be employed as an individualized preoperative non-invasive tool for differentiating early-stage SBOTs from SMOTs.

A Comprehensive Review of Current Trends in the Diagnosis and Treatment of Ovarian Germ Cell Tumors

Ovarian germ cell tumors constitute a rare and intricate spectrum of neoplasms characterized by diverse histological subtypes. This comprehensive review elucidates the classification, diagnosis, treatment, prognosis, and unique challenges associated with these tumors. The classification is rooted in histological attributes, with principal subtypes encompassing dysgerminoma, immature teratoma, yolk sac tumor (endodermal sinus tumor), choriocarcinoma, and mixed germ cell tumors. Each subtype bears distinct characteristics and clinical implications, necessitating precise diagnosis and tailored therapeutic strategies. Diagnosis hinges upon recognizing the broad clinical presentation, employing imaging techniques (such as ultrasound and MRI), evaluating tumor markers (alpha-fetoprotein and beta-human chorionic gonadotropin), and conducting histopathological examinations where necessary. Staging, primarily utilizing the International Federation of Gynecology and Obstetrics (FIGO) system, is pivotal in determining the extent of disease, guiding treatment choices, and facilitating prognostic assessment. Treatment modalities encompass surgery, chemotherapy (including standard regimens and emerging therapies), radiation therapy, targeted therapies, and immunotherapy. Prognosis is influenced by histological subtype, tumor stage, patient age, surgical success, response to chemotherapy, and tumor markers, while predictive biomarkers are continually emerging. Despite advances in treatment, ovarian germ cell tumors pose distinct challenges, including late diagnosis, treatment-related side effects, and the enigma of chemoresistance. An integral aspect of comprehensive care is supportive strategies to manage symptoms and offer psychological and emotional support. This review accentuates the vital role of early diagnosis and multidisciplinary care in optimizing outcomes. Future research directions and evolving clinical practices are explored in these intricate and distinctive malignancies, highlighting the dynamic landscape of ovarian germ cell tumors.

Machine learning-derived identification of prognostic signature for improving prognosis and drug response in patients with ovarian cancer

Clinical assessments relying on pathology classification demonstrate limited effectiveness in predicting clinical outcomes and providing optimal treatment for patients with ovarian cancer (OV). Consequently, there is an urgent requirement for an ideal biomarker to facilitate precision medicine. To address this issue, we selected 15 multicentre cohorts, comprising 12 OV cohorts and 3 immunotherapy cohorts. Initially, we identified a set of robust prognostic risk genes using data from the 12 OV cohorts. Subsequently, we employed a consensus cluster analysis to identify distinct clusters based on the expression profiles of the risk genes. Finally, a machine learning-derived prognostic signature (MLDPS) was developed based on differentially expressed genes and univariate Cox regression genes between the clusters by using 10 machine-learning algorithms (101 combinations). Patients with high MLDPS had unfavourable survival rates and have good prediction performance in all cohorts and in-house cohorts. The MLDPS exhibited robust and dramatically superior capability than 21 published signatures. Of note, low MLDIS have a positive prognostic impact on patients treated with anti-PD-1 immunotherapy by driving changes in the level of infiltration of immune cells. Additionally, patients suffering from OV with low MLDIS were more sensitive to immunotherapy. Meanwhile, patients with low MLDIS might benefit from chemotherapy, and 19 compounds that may be potential agents for patients with low MLDIS were identified. MLDIS presents an appealing instrument for the identification of patients at high/low risk. This could enhance the precision treatment, ultimately guiding the clinical management of OV.

Prediction model of adnexal masses with complex ultrasound morphology

Background

Based on the ovarian-adnexal reporting and data system (O-RADS), we constructed a nomogram model to predict the malignancy potential of adnexal masses with sophisticated ultrasound morphology.

Methods

In a multicenter retrospective study, a total of 430 subjects with masses were collected in the adnexal region through an electronic medical record system at the Fourth Hospital of Harbin Medical University during the period of January 2019-April 2023. A total of 157 subjects were included in the exception validation cohort from Harbin Medical University Tumor Hospital. The pathological tumor findings were invoked as the gold standard to classify the subjects into benign and malignant groups. All patients were randomly allocated to the validation set and training set in a ratio of 7:3. A stepwise regression analysis was utilized for filtering variables. Logistic regression was conducted to construct a nomogram prediction model, which was further validated in the training set. The forest plot, C-index, calibration curve, and clinical decision curve were utilized to verify the model and assess its accuracy and validity, which were further compared with existing adnexal lesion models (O-RADS US) and assessments of different types of neoplasia in the adnexa (ADNEX).

Results

Four predictors as independent risk factors for malignancy were followed in the preparation of the diagnostic model: O-RADS classification, HE4 level, acoustic shadow, and protrusion blood flow score (all p < 0.05). The model showed moderate predictive power in the training set with a C-index of 0.959 (95%CI: 0.940-0.977), 0.929 (95%CI: 0.884-0.974) in the validation set, and 0.892 (95%CI: 0.843-0.940) in the external validation set. It showed that the predicted consequences of the nomogram agreed well with the actual results of the calibration curve, and the novel nomogram was clinically beneficial in decision curve analysis.

Conclusion

The risk of the nomogram of adnexal masses with complex ultrasound morphology contained four characteristics that showed a suitable predictive ability and provided better risk stratification. Its diagnostic performance significantly exceeded that of the ADNEX model and O-RADS US, and its screening performance was essentially equivalent to that of the ADNEX model and O-RADS US classification.

High density of CXCL12-positive immune cell infiltration predicts chemosensitivity and recurrence-free survival in ovarian carcinoma

BACKGROUND

Ovarian carcinoma is the most lethal gynecologic malignancy because of its late diagnosis, extremely high recurrence rate, and limited curative treatment options. In clinical practice, high-grade serous carcinoma (HGSC) predominates due to its frequency, high aggressiveness, and rapid development of drug resistance. Recent evidence suggests that CXCL12 is an important immunological factor in ovarian cancer progression. Therefore, we investigated the predictive and prognostic significance of the expression of this chemokine in tumor and immune cells in patients with HGSC.

METHODS

We studied a cohort of 47 primary high-grade serous ovarian carcinomas and their associated recurrences. A tissue microarray was constructed to evaluate the CXCL12 immunostained tumor tissue. CXCL12 expression was evaluated and statistically analyzed to correlate clinicopathologic data, overall survival, and recurrence-free survival.

RESULTS

A high proportion of CXCL12 + positive immune cells in primary ovarian serous carcinoma correlated significantly with chemosensitivity (p = 0.005), overall survival (p = 0.021), and longer recurrence-free survival (p = 0.038). In recurrent disease, high expression of CXCL12 was also correlated with better overall survival (p = 0.040). Univariate and multivariate analysis revealed that high CXCL12 + tumor-infiltrating immune cells (TICs) (HR 0.99, p = 0.042, HR 0.99, p = 0.023, respectively) and combined CXCL12 + /CD66b + infiltration (HR 0.15, p = 0.001, HR 0.13, p = 0.001, respectively) are independent favorable predictive markers for recurrence-free survival.

CONCLUSION

A high density of CXCL12 + TICs predicts a good response to chemotherapy, leading to a better overall survival and a longer recurrence-free interval. Moreover, with concomitant high CXCL12/CD66b TIC density, it is an independent favorable predictor of recurrence-free survival in patients with ovarian carcinoma.

Prediction of the survival of patients with advanced-stage ovarian cancer patients undergoing interval cytoreduction with the use of computed tomography reevaluation after neoadjuvant chemotherapy

PURPOSE

To predict ovarian cancer patients' survival by computed tomography (CT) reevaluation after neoadjuvant chemotherapy.

PATIENTS AND METHODS

In this retrospective single-center cohort study, all patients with advanced epithelial ovarian cancer underwent platinum-based chemotherapy followed by interval cytoreductive surgery. Assessment of abdominal and pelvic lesions before and after chemotherapy using CT scoring criteria. Meanwhile, the progression-free survival and overall survival times were obtained. The Kaplan-Meier method was used to estimate survival curves. Univariate analysis of continuous and categorical variables was performed for prognostic significance using the Cox proportional hazards model. Variables with p < 0.10 on univariate analysis were then included in a multivariate forward stepwise Cox regression analysis.

RESULTS

A total of 162 patients were included, with a median age of 52 years (range, 20-72 years). One hundred seven patients (66.0%) underwent suboptimal cytoreduction, and there was no statistically significant difference in patient survival between surgical procedures (log-rank p = 0.092). Six radiographic features were hazard factors for suboptimal cytoreduction. Four features in the postchemotherapy CT images were assigned as predictive criteria by the stepwise regression model (area under the curve [AUC] = 0.689). As compared with a higher AUC (0.713) in the model involving two clinical variables (age and postsurgery CA-125) and two postchemotherapy CT features, the model considering the CT score changes before and after chemotherapy had the highest diagnostic accuracy (AUC = 0.843).

CONCLUSION

CT reevaluation after neoadjuvant chemotherapy is essential for ovarian cancer, the changes of CT feature and score are potential great tools to predict patient survival.

Diagnostic performance of noninvasive imaging using computed tomography, magnetic resonance imaging, and positron emission tomography for the detection of ovarian cancer: a meta-analysis

OBJECTIVE

The aim of this meta-analysis was to compare the diagnostic value of noninvasive imaging methods computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) in the detection of ovarian cancer (OC).

METHODS

PubMed, Embase, and Ovid were comprehensively searched from the date of inception to 31st, March, 2022. Pooled sensitivity, specificity, positive likelihood ratio (+ LR), negative likelihood ratio (- LR), diagnostic odds ratio (DOR), and area under the curve (AUC) of summary receiver operating characteristic (SROC) with their respective 95% confidence intervals (CIs) were calculated.

RESULTS

Sixty-one articles including 4284 patients met the inclusion criteria of this study. Pooled estimates of sensitivity, specificity, and AUC of SROC with respective 95% CIs of CT on patient level were 0.83 (0.73, 0.90), 0.69 (0.54, 0.81), and 0.84 (0.80, 0.87). The overall sensitivity, specificity, SROC value with respective 95% CIs of MRI were 0.95 (0.91, 0.97),0.81 (0.76, 0.85), and 0.90 (0.87, 0.92) on patient level. Pooled estimates of sensitivity, specificity, SROC value of PET/CT on patient level were 0.92 (0.88, 0.94), 0.88 (0.83, 0.92), and 0.96 (0.94, 0.97).

CONCLUSION

Noninvasive imaging modalities including CT, MRI, PET (PET/CT, PET/MRI) yielded favorable diagnostic performance in the detection of OC. Hybrid implement of different tools (PET/MRI) is more accurate for identifying metastatic OC.

Prognostic value of preoperative serological biomarkers in patients undergoing cytoreductive surgery for ovarian cancer peritoneal metastases

Objectives

Peritoneal metastases of ovarian cancer (PMOC) are common at initial presentation. Cytoreductive surgery (CRS) of curative intent has been proven to be efficient in increasing the overall survival (OS) and the disease-free survival (DFS) of these patients. Nevertheless, CRS is associated with high postoperative morbidity, which makes patient selection a major concern. Appropriate prognostic factors that can predict patient outcomes after surgery are still lacking. Preoperative biomarkers and their ratios have been shown to be predictive of patient prognosis for various solid tumors. We aimed to study their correlation with the prognosis of patients undergoing CRS for PMOC.

Methods

This retrospective study included patients with PMOC operated by CRS. Preoperative biomarkers and other clinicopathological characteristics were studied to determine their prognostic value in terms OS and DFS.

Results

216 patients were included. Patients with preoperative hemoglobin (Hb) <11.7 g/dL had a poorer prognosis in terms of OS (p=0.0062) and DFS (p=0.0077). Additionally, increased neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR) >0.32, and platelet-to-lymphocyte ratio (PLR) >214.5 were associated with worse OS (p=0.022, p=0.0028, and p=0.0018, respectively) and worse DFS (p=0.028, p=0.003, and p=0.019, respectively). Multivariate analysis showed that the variables mentioned above were independent predictive factors for OS and DFS.

Conclusions

Preoperative Hb level, NLR, MLR, and PLR are prognostic factors for OS and DFS in PMOC patients operated by curative CRS.

MR Imaging of Gynecologic Tumors: Pearls, Pitfalls, and Tumor Mimics

MR imaging is the modality of choice for the pre-treatment evaluation of patients with gynecologic malignancies, given its excellent soft tissue contrast and multi-planar capability. However, it is not without pitfalls. Challenges can be encountered in the assessment of the infiltration of myometrium, vagina, cervical stroma, and parametria, which are crucial prognostic factors for endometrial and cervical cancers. Other challenges can be encountered in the distinction between solid and non-solid tissue and in the identification of peritoneal carcinomatosis for the sonographically indeterminate adnexal mass.

The Validation of a Precursor Lesion of Epithelial Ovarian Cancer in Fancd2-KO Mice

Ovarian cancer (OC) has the highest mortality rate of all gynaecological malignancies. The asymptomatic nature and limited understanding of early disease hamper research into early-stage OC. Therefore, there is an urgent need for models of early-stage OC to be characterised to improve the understanding of early neoplastic transformations. This study sought to validate a unique mouse model for early OC development. The homozygous Fanconi anaemia complementation group D2 knock-out mice (Fancd2^-/-) develop multiple ovarian tumour phenotypes in a sequential manner as they age. Using immunohistochemistry, our group previously identified purported initiating precursor cells, termed 'sex cords', that are hypothesised to progress into epithelial OC in this model. To validate this hypothesis, the sex cords, tubulostromal adenomas and equivalent controls were isolated using laser capture microdissection for downstream multiplexed gene expression analyses using the Genome Lab GeXP Genetic Analysis System. Principal component analysis and unbiased hierarchical clustering of the resultant expression data from approximately 90 OC-related genes determined that cells from the sex cords and late-stage tumours clustered together, confirming the identity of the precursor lesion in this model. This study, therefore, provides a novel model for the investigation of initiating neoplastic events that can accelerate progress in understanding early OC.

Enhancement of sonodynamic treatment of ovarian cancer based on Pt-B-P ternary nanoparticles

Sonodynamic therapy (SDT) can noninvasively focus sound energy to deep tumor tissues and activate sonosensitizer (such as chlorin e6(Ce6)) to produce antitumor effects. However, due to the hypoxic microenvironment of the tumor, the effect of sonodynamic therapy is limited. In this work, we successfully synthesized Platinum-Boron-Phosphorus ternary nanoparticles (Pt-B-P NPs) for the first time to efficiently catalyze the decomposition of hydrogen peroxide (H₂O₂) in tumor tissues to produce sufficient oxygen (O₂) and improve the effect of sonodynamic treatment of ovarian cancer. In vitro studies, we found that compared with Platinum nanoparticles (Pt NPs), Pt-B-P NPs have the significantly increased ability to catalyze the decomposition of H₂O₂ to produce oxygen and thus the hypoxic environment of tumor cells could be improved efficiently. Meanwhile, the bio-distribution, therapeutic effect and bio-safety of Pt-B-P NPs in vivo were evaluated using BALB/c-nu mouse model of ovarian cancer and the desired result had been achieved.

How do serum lipid levels change and influence progression-free survival in epithelial ovarian cancer patients receiving bevacizumab treatment?

Background

This study aimed to investigate how serum lipid levels affect epithelial ovarian cancer (EOC) patients receiving bevacizumab treatment and to develop a model for predicting the patients’ prognosis.

Methods

A total of 139 EOC patients receiving bevacizumab treatment were involved in this study. Statistical analysis was used to compare the median and average values of serum lipid level variables between the baseline and final follow-up. Additionally, a method based on machine learning was proposed to identify independent risk factors for estimating progression-free survival (PFS) in EOC patients receiving bevacizumab treatment. A PFS nomogram dividing the patients into low- and high-risk categories was created based on these independent prognostic variables. Finally, Kaplan–Meier curves and log-rank tests were utilized to perform survival analysis.

Results

Among EOC patients involved in this study, statistical analysis of serum lipid level variables revealed a substantial increase in total cholesterol, triglycerides, apolipoprotein A1, and free fatty acids, and a significant decrease in apolipoprotein B from baseline to final follow-up. Our method identified FIGO stage, combined chemotherapy regimen, activated partial thromboplastin time, globulin, direct bilirubin, free fatty acids, blood urea nitrogen, high-density lipoprotein cholesterol, and triglycerides as risk factors. These risk factors were then included in our nomogram as independent predictors for EOC patients. PFS was substantially different between the low-risk group (total score &lt; 298) and the high-risk group (total score ≥ 298) according to Kaplan–Meier curves (P &lt; 0.05).

Conclusion

Serum lipid levels changed variously in EOC patients receiving bevacizumab treatment. A prediction model for PFS of EOC patients receiving bevacizumab treatment was constructed, and it can be beneficial in determining the prognosis, selecting a treatment plan, and monitoring these patients’ long-term care.

Deep learning for the ovarian lesion localization and discrimination between borderline and malignant ovarian tumors based on routine MR imaging

To establish a deep learning (DL) model in differentiating borderline ovarian tumor (BOT) from epithelial ovarian cancer (EOC) on conventional MR imaging. We retrospectively enrolled 201 patients of 102 pathologically proven BOTs and 99 EOCs at OB/GYN hospital Fudan University, between January 2015 and December 2017. All imaging data were reviewed on picture archiving and communication systems (PACS) server. Both T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) MR images were used for lesion area determination. We trained a U-net++ model with deep supervision to segment the lesion area on MR images. Then, the segmented regions were fed into a classification model based on DL network to categorize ovarian masses automatically. For ovarian lesion segmentation, the mean dice similarity coefficient (DSC) of the trained U-net++ model in the testing dataset achieved 0.73 [Formula: see text] 0.25, 0.76 [Formula: see text] 0.18, and 0.60 [Formula: see text] 0.24 in the sagittal T2WI, coronal T2WI, and axial T1WI images, respectively. The DL model by combined T2WI computerized network could differentiate BOT from EOC with a significantly higher AUC of 0.87, an accuracy of 83.7%, a sensitivity of 75.0% and a specificity of 87.5%. In comparison, the AUC yielded by radiologist was only 0.75, with an accuracy of 75.5%, a sensitivity of 96.0% and specificity of 54.2% (P < 0.001).The trained DL network model derived from routine MR imaging could help to distinguish BOT from EOC with a high accuracy, which was superior to radiologists' assessment.

Cardiovascular outcomes trial data from EMPA-REG OUTCOME, CAROLINA and CARMELINA: Assessment of a novel staging system for type 2 diabetes

AIMS

To apply the diabetes staging system (DSS), a novel disease staging system similar to what is used in oncology but designed to improve diabetes management, to three large type 2 diabetes (T2D) cardiovascular (CV) outcome trials to assess whether increasing DSS stage was associated with higher rates of all-cause mortality (ACM) and/or CV death.

MATERIALS AND METHODS

The DSS uses discrete CV events (none to ≥3: Stage 1 to 4), end-stage kidney disease (Stage 5) and microvascular complications (none to 3: A to D) to determine disease stage in individuals with T2D. The DSS stage for patients from the CAROLINA, EMPA-REG OUTCOME and CARMELINA trials was determined. Incidence rates for ACM/CV death were calculated across DSS stages and Cox regression analyses were performed.

RESULTS

The risk of ACM or CV death increased with increasing DSS (Stage 1 to 5; P for trend <0.0001) in all trials. In CAROLINA, the risk of ACM and CV death increased with increasing number of microvascular complications (A to D; both P for trend <0.0001), similar in CARMELINA (P for trend = 0.0020 and 0.0005, respectively). In EMPA-REG OUTCOME, having all three microvascular complications (Stage D), versus none, increased the risk of ACM and CV death (P = 0.0015 and 0.0010, respectively).

CONCLUSIONS

Applying the DSS across T2D clinical trial populations with different CV risk revealed a significantly increased risk of ACM and CV death with higher DSS stage. The DSS may merit assessment in other T2D populations and evaluation of the impact of additional outcomes, such as heart failure, could also be worthwhile.

Changes in Nucleolin Expression during Malignant Transformation Leading to Ovarian High-Grade Serous Carcinoma

OBJECTIVE

Ovarian high-grade serous carcinoma (HGSC) is a fatal malignancy of women. Alterations in the expression of nuclear proteins are early steps in malignant transformation; nucleolin is one such protein. Changes in nucleolin expression and circulatory levels during ovarian HGSC development are unknown. The study goal was to determine if tissue and circulatory levels of nucleolin change in response to malignant transformation leading to ovarian HGSC.

METHODS

Sera, ovaries, and BRCA+ fimbria from healthy subjects, and sera and tumor tissues from patients (n = 10 each), and healthy hens and hens with HGSC were examined in exploratory and prospective studies for nucleolin expression by immunohistochemistry, immunoblotting, gene expression, and immunoassay, and analyzed by analysis of variance (ANOVA).

RESULTS

Compared with normal, nucleolin expression was higher in patients and hens with ovarian HGSC and in women with a risk of HGSC (P < 0.05). Compared with normal (1400 + 105 pg/mL, n = 8), serum nucleolin levels were 1.5 and 1.7-fold higher in patients with early- (n = 5) and late-stage (n = 5) HGSC, respectively. Additionally, serum nucleolin levels increased significantly (P < 0.05) prior to the formation of detectable masses.

CONCLUSION

This pilot study concluded that tissue and serum levels of nucleolin increase in association with malignant changes in ovaries and fimbriae leading to ovarian HGSC.

Current Update on PET/MRI in Gynecological Malignancies-A Review of the Literature

Early detection of gynecological malignancies is vital for patient management and prolonging the patient's survival. Molecular imaging, such as positron emission tomography (PET)/computed tomography, has been increasingly utilized in gynecological malignancies. PET/magnetic resonance imaging (MRI) enables the assessment of gynecological malignancies by combining the metabolic information of PET with the anatomical and functional information from MRI. This article will review the updated applications of PET/MRI in gynecological malignancies.

Utility of Matrix Metalloproteinases in the Diagnosis, Monitoring and Prognosis of Ovarian Cancer Patients

Ovarian cancer is one of the most common gynecologic malignancies. It is characterized by a high mortality rate, which is mainly due to the asymptomatic course of the disease. In light of the high mortality rate and increasing morbidity, new diagnostic methods are being explored to enable earlier detection, better monitoring, and improved prognosis. Such diagnostic methods include the assessment of tumor markers in various biological samples. Among the markers currently being investigated, extracellular matrix metalloproteinases (MMPs) are of particular interest. The objective of this article was to compile the existing knowledge of MMPs in ovarian cancer patients and to describe their potential diagnostic utility. Additionally, this article provides an overview of the symptoms, complications, and risk factors associated with ovarian cancer and the role of MMPs in physiology and pathology. Preliminary results indicate that tissue expression and blood and body fluid levels of MMPs may be different in ovarian cancer patients than in healthy women. The expression and concentration of individual MMPs have been shown to be correlated with cancer stage and disease severity. In addition, the preliminary value of some of these enzymes in predicting prognosis is discussed. However, as the amount of data is limited, more studies are needed to fully evaluate the potential function of individual MMPs in ovarian cancer patients. Based on the knowledge gathered for this article, it seems that MMP-2, MMP-3, MMP-7, MMP-8, MMP-9, MMP-13, are tentatively the most useful. A thorough evaluation of their utility as modern biomarkers in ovarian cancer requires further investigation.

Pre-Treatment CRP-Albumin-Lymphocyte Index (CALLY Index) as a Prognostic Biomarker of Survival in Patients with Epithelial Ovarian Cancer

Background

The novel CRP–albumin–lymphocyte (CALLY) index is an improved immunonutritive scoring system, based on serum C-reactive protein (CRP), serum albumin, and the lymphocyte count. It has been determined as a prognostic index for patients with hepatocellular carcinoma. This study was conducted to explore the prognostic value of the CALLY index in patients with epithelial ovarian cancer (EOC) undergoing surgery.

Methods

Patients with EOC treated with surgery as an initial therapy were enrolled to form the training and validation cohorts. The effect of the CALLY index on overall survival (OS) and disease-free survival (DFS) was analyzed using Kaplan–Meier method and Cox proportional hazards model. The CALLY index was calculated as: (Albumin × Lymphocyte)/ (CRP × 10⁴).

Results

There were 190 patients in the training cohort and 120 in the validation cohort, respectively. With a cut-off value of 3, patients were classified into the CALLY <3 and CALLY ≥3 groups. The CALLY index ≥3 was associated with better survival outcomes both in the training and validation cohorts. The univariate and multivariate COX analysis revealed that FIGO stage, lymphatic metastasis, and CALLY index were the prognostic factors for both OS and DFS.

Conclusion

The CALLY index is a novel prognostic biomarker for patients with EOC after surgery. The novel CALLY index could select appropriate patients with poor prognosis for postoperative adjuvant therapy.

Multivariate logistic regression analysis of the correlation between five biomarkers and ovarian cancer in patients with intermediate-risk: A prospective cross-sectional study

Objective: To find potential diagnostic biomarkers for ovarian cancer (OC), a prospective analysis of the expression of five biomarkers in patients with intermediate-risk and their correlation with the occurrence of OC was conducted.

Method: A prospective observational study was carried out, patients who underwent surgical treatment with benign or malignant ovarian tumors in our hospital from January 2020 to February 2021 were included in this study, and a total of 263 patients were enrolled. Based on the postoperative pathological results, enrolled patients were divided into ovarian cancer group and benign tumor group (n = 135). The ovarian cancer group was further divided into a mid-stage group (n = 46) and an advanced-stage group (n = 82). The basic information of the three groups of patients was collected, the preoperative imaging data of the patients were collected to assess the lymph node metastasis, the preoperative blood samples were collected to examine cancer antigen 125 (CA125), carbohydrate antigen 19–9 (CA19–9), Neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and the postoperative pathological data were sorted and summarized.

Result: The average during of disease in the advanced ovarian cancer group was 0.55 ± 0.18 years higher than the benign tumor group (0.43 ± 0.14 years), p < 0.001. In the advanced ovarian cancer group, the ratio of patients with the tumor, node, metastasis (TNM) stage IV (64.63%), with tumor Grade stage II and III (93.90%), and without lymph node metastasis (64.63%) was respectively more than that in the mid-stage group (accordingly 0.00, 36.96, 23.91%) (p < 0.001); The ratio of patients with TNM grade III in the mid-stage group (73.91%) was more than that in the advanced group (35.37%) (p < 0.001). The levels of the five biomarkers: CA19-9, CA125, NLR, PLR, and BDNF were different among the three groups (p < 0.001).

Conclusion: CA19-9, CA125, NLR, PLR, BDNF are five biomarkers related to the occurrence of ovarian cancer and are risk factors for it. These five biomarkers and their Combined-Value may be suitable to apply in the diagnosis and the identification of ovarian cancer in patients with intermediate-risk.

Identification of an Amino Acid Metabolism Signature Participating in Immunosuppression in Ovarian Cancer

Ovarian cancer is one of the most fatal gynecologic cancer types, and its heterogeneity in the microenvironment limited the efficacy of the current treatment. In this study, we aimed at building a risk score to predict patient survival based on the amino acid metabolic genes and TCGA RNA-seq dataset (n = 376). We first used univariate analysis and PCA to select and test the survival-related genes, and the LASSO regression was applied to build the risk score signature with prediction accuracy estimation by survival analysis and ROC. We then conducted GSEA and GSVA to investigate the biological roles of the signature and run ESTIMATE and 4 different immunocyte infiltration algorithms to investigate the immunological diversity between the risk groups. Furthermore, the immune checkpoint expression was compared. We finally explored the cMap and PRISM database to screen out sensitive drugs for high-risk patients and analyzed the oncogenic role of TPH1 by clone formation and transwell migration assays. As a result, the risk score predicted patients' survival and stage with high accuracy. We found that the signature mainly affected the extracellular activities and cancer immunity by functional enrichment. We further discovered that the high-risk OV harbored a high level of stromal cell infiltration and was associated with highly infiltrated fibroblasts and decreased CD8+ T cells. The immune checkpoint analyses showed that TGFB1 and CD276 were upregulated. Finally, we screened out 4 PRISM drugs with lower IC₅₀ in the high-risk group and validated the oncogenic role of TPH1 in OV cancers. We believe this research offered a novel understanding of the interplay between amino acid metabolism and immunity in OV and will benefit patients with better prognostic management and therapeutic strategy development.

Magnetic Resonance Imaging and Diffusion Weighted Imaging-Based Histogram in Predicting Mesenchymal Transition High-Grade Serous Ovarian Cancer

RATIONALE AND OBJECTIVES

To investigate the value of magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI) findings in predicting mesenchymal transition (MT) high-grade serous ovarian cancer (HGSOC).

MATERIALS AND METHODS

Patients with HGSOC were enrolled from May 2017 to December 2020, who underwent pelvic MRI including DWI (b = 0,1000 s/mm²) before surgery, and were assigned to the MT HGSOC or non-MT HGSOC group according to histopathology results. Clinical characteristics and MRI features including DWI-based histogram metrics were assessed and compared between the two groups. Univariate and multivariate analyses were performed to identify the significant variables associated with MT HGSOC - these variables were then incorporated into a predictive nomogram, and ROC curve analysis was subsequently carried out to evaluate diagnostic performance.

RESULTS

A total of 81 consecutive patients were recruited for pelvic MRI before surgery, including 37 (45.7%) MT patients and 44 (54.3%) non-MT patients. At univariate analysis, the features significantly related to MT HGSOC were identified as absence of discrete primary ovarian mass, pouch of Douglas implants, ovarian mass size, tumor volume, mean, SD, median, and 95th percentile apparent diffusion coefficient (ADC) values (all p < 0.05). At multivariate analysis, the absence of discrete primary ovarian mass {odds ratio (OR): 46.477; p = 0.025}, mean ADC value ≤ 1.105 (OR: 1.023; p = 0.009), and median ADC value ≤ 1.038 (OR: 0.982; p = 0.034) were found to be independent risk factors associated with MT HGSOC. The combination of all independent criteria yielded the largest AUC of 0.82 with a sensitivity of 83.87% and specificity of 66.67%, superior to any of the single predictor alone (p ≤ 0.012). The predictive C-index nomogram performance of the combination was 0.82.

CONCLUSION

The combination of absence of discrete primary ovarian mass, lower mean ADC value, and median ADC value may be helpful for preoperatively predicting MT HGSOC.

The Effect of Bone Marrow Mesenchymal Stem Cells-Exosomes (BMSC-EXO) on Tumor Angiogenesis and Its Mechanism in Ovarian Cancer Microenvironment

In ovarian cancer microenvironment, BMSC cells can differentiate into a variety of stem cells, thereby reducing the damage to tissues, and this effect lies in the exosomal substances secreted by BMSC cells. Then, in ovarian cancer microenvironment, whether BMSC-exo exhibited an effect on angiogenesis at the tumor site, and its possible molecular mechanism remains unclear. BALA nude mice and ovarian cancer tumor tissues were collected to isolate vascular endothelial cells which were then assigned into Control group, 40 μg/ml BMSC-exo group, 80 μg/ml BMSC-exo group, 120 μg/ml BMSC-exo group in the presence of Wnt/β-catenin inhibitor (PNU-74654) followed by analysis of proliferation and migration of ovarian cancer vascular endothelial cells (OCVECs) and the angiogenesis. 40 μg/ml and 80 μg/mlBMSC-exo group showed significantly higher cell proliferation than control group with higher cell number in 80 μg/ml BMSC-exo group than 40 μg/ml BMSC-exo group (P < 0.05). The number of cell migration after BMSC-exo treatment was increased (P < 0.05) and the tumor tissue showed obvious angiogenesis with more CD31-positive cells (P < 0.05). PNU-74654 group showed significantly downregulated Wnt and β-catenin proteins (P < 0.05) and lower cell number and higher migration rate of vascular endothelial cells (P < 0.05). In conclusion, exosomes secreted by BMSC can repair damaged tissues possibly through activation of Wnt/β-catenin signaling pathway.

Incidence and Survival Rates for Female Malignant Germ Cell Tumors: An Institutional Review

Background

Germ cell tumor survival rates have improved over the past few decades. However, there is a lack of data on survival rates and the incidence of female germ cell tumors. This study aims to determine the incidence and survival rates of female germ cell tumors in our institution.

Methodology

This retrospective cross-sectional study was carried out at Shaukat Khanum Memorial Hospital and Research Centre, and the records over 10 years, from January 2010 to December 2020 were examined. The data of 290 females with malignant germ cell tumors were selected from 1387 females with ovarian masses, and their survival records were examined. For statistical analysis, SPSS software (version 24.0; IBM Corp. Armonk, NY) was utilized. The survival analysis was determined using the Kaplan-Meier method.

Results

The mean age of patients was 21.45 ± 9.28 years. The mean duration of diagnosis was 4.53 ± 2.59 years. In 245 (84.5%) patients, ovarian malignancy was involved while uterine malignancy was observed in 44 (15.2%) cases and there was one (0.3%) case of cervical carcinoma. The most common stage at diagnosis of malignancy was IA (96 (33.1%)), followed by IIIC (58 (20.0%)), IV (56 (19.3%)) and IC (26 (9.0%)). Chemotherapy was given in 244 (84.1%) cases. Out of 290 cases, 26 (9.0%) had a recurrence of the tumor while 264 (91.0%) did not have a recurrence of the tumor. Out of 290 cases, 46 (15.9%) died during follow-up, 129 (44.4%) had disease-free survival while 115 (39.7%) were healthy till the end of the study. The mean duration of survival was 3.56 ± 2.33 years. When patients' survival was compared between treatment groups, patients who did not receive chemotherapy fared better than those who did.

Conclusion

Female germ cell tumor patients have a good overall survival rate of more than 20% after 10 years of follow-up with effective adjuvant therapy and conservative surgery. However, more research is needed to determine the long-term effects of chemotherapy on ovarian function.

Surgery in Advanced Ovary Cancer: Primary versus Interval Cytoreduction

Primary debulking surgery (PDS) has remained the only treatment of ovarian cancer with survival advantage since its development in the 1970s. However, survival advantage is only observed in patients who are optimally resected. Neoadjuvant chemotherapy (NACT) has emerged as an alternative for patients in whom optimal resection is unlikely and/or patients with comorbidities at high risk for perioperative complications. The purpose of this review is to summarize the evidence to date for PDS and NACT in the treatment of stage III/IV ovarian carcinoma. We systematically searched the PubMed database for relevant articles. Prior to 2010, NACT was reserved for non-surgical candidates. After publication of EORTC 55971, the first randomized trial demonstrating non-inferiority of NACT followed by interval debulking surgery, NACT was considered in a wider breadth of patients. Since EORTC 55971, 3 randomized trials-CHORUS, JCOG0602, and SCORPION-have studied NACT versus PDS. While CHORUS supported EORTC 55971, JCOG0602 failed to demonstrate non-inferiority and SCORPION failed to demonstrate superiority of NACT. Despite conflicting data, a subset of patients would benefit from NACT while preserving survival including poor surgical candidates and inoperable disease. Further randomized trials are needed to assess the role of NACT.

The functional multipotency of transforming growth factor β signaling at the intersection of senescence and cancer

The transforming growth factor β (TGF-β) family of cytokines comprises a group of proteins, their receptors, and effector molecules that, in a coordinated manner, modulate a plethora of physiological and pathophysiological processes. TGF-β1 is the best known and plausibly most active representative of this group. It acts as an immunosuppressant, contributes to extracellular matrix remodeling, and stimulates tissue fibrosis, differentiation, angiogenesis, and epithelial-mesenchymal transition. In recent years, this cytokine has been established as a vital regulator of organismal aging and cellular senescence. Finally, the role of TGF-β1 in cancer progression is no longer in question. Because this protein is involved in so many, often overlapping phenomena, the question arises whether it can be considered a molecular bridge linking some of these phenomena together and governing their reciprocal interactions. In this study, we reviewed the literature from the perspective of the role of various TGF-β family members as regulators of a complex mutual interplay between senescence and cancer. These aspects are then considered in a broader context of remaining TGF-β-related functions and coexisting processes. The main narrative axis in this work is centered around the interaction between the senescence of normal peritoneal cells and ovarian cancer cells. The discussion also includes examples of TGF-β activity at the interface of other normal and cancer cell types.

Immature Teratoma With Metastatic Gliosis

Immature teratomas are rare malignant tumors of the ovary. They are made of immature components of germ cell origin. The incidence of immature teratomas is highest in young adults aged 18 to 39. The prognosis heavily depends on the International Federation of Gynecology and Obstetrics (FIGO) staging system and is influenced by factors such as cell type, tumor grade, capsular rupture, and metastatic risk factors. Initial treatment is complete surgical resection. When indicated, platinum-based adjuvant chemotherapy with bleomycin, etoposide, and cisplatin (BEP) is the treatment of choice. Next-generation sequencing of the tumor can influence treatment in the recurrent setting. Temozolomide is an alkylating agent used to target high-grade gliomas. Bevacizumab is a targeted therapy that interferes with the process of angiogenesis by inhibiting vascular endothelial growth factor (VEGF).

We report a 36-year-old female who presented with a 17.6cm x 10.5cm x 24.2cm intraabdominal mass and ascites. Upon tumor resection, she was found to have a stage IIIa, grade 2 immature teratoma of the left ovary, with glial tissue being the metastatic cell type. Disease progression continued despite treatment with BEP. She was then treated experimentally with six months of bevacizumab and temozolomide, given its rarity and targeted therapy for glial tissue. Despite monoclonal antibody therapy, the tumor progressed again and was treated with docetaxel and gemcitabine. A repeat CT of the chest, abdomen, and pelvis demonstrated scattered peritoneal implants that were increasing in size. Chromosome analysis was performed and revealed somatic mutations of MLH1, MSH2, MSH6, and PD-L1. The patient has requested a break from chemotherapy but will be treated with direct immunotherapy when she restarts.

This case’s importance lies in its rarity because fewer than 10 cases of immature teratomas with metastatic glial tissue are noted in the world’s literature. Furthermore, this is the first reported case of this cell type being treated with immunotherapy in the world literature.

Deregulated miRNA clusters in ovarian cancer: Imperative implications in personalized medicine

Ovarian cancer (OC) is one of the most common and fatal types of gynecological cancer. OC is usually detected at the advanced stages of the disease, making it highly lethal. miRNAs are single-stranded, small non-coding RNAs with an approximate size ranging around 22 nt. Interestingly, a considerable proportion of miRNAs are organized in clusters with miRNA genes placed adjacent to one another, getting transcribed together to result in miRNA clusters (MCs). MCs comprise two or more miRNAs that follow the same orientation during transcription. Abnormal expression of the miRNA cluster has been identified as one of the key drivers in OC. MC exists both as tumor-suppressive and oncogenic clusters and has a significant role in OC pathogenesis by facilitating cancer cells to acquire various hallmarks. The present review summarizes the regulation and biological function of MCs in OC. The review also highlights the utility of abnormally expressed MCs in the clinical management of OC.

A prognostic model of patients with ovarian mucinous adenocarcinoma: a population-based analysis

BACKGROUND

Ovarian mucinous carcinoma is a disease that requires unique treatment. But for a long time, guidelines for ovarian serous carcinoma have been used for the treatment of ovarian mucinous carcinoma. This study aimed to construct and validate nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with ovarian mucinous adenocarcinoma.

METHODS

In this study, patients initially diagnosed with ovarian mucinous adenocarcinoma from 2004 to 2015 were screened from the Surveillance, Epidemiology, and End Results (SEER) database, and divided into the training group and the validation group at a ratio of 7:3. Independent risk factors for OS and CSS were determined by multivariate Cox regression analysis, and nomograms were constructed and validated.

RESULTS

In this study, 1309 patients with ovarian mucinous adenocarcinoma were finally screened and randomly divided into 917 cases in the training group and 392 cases in the validation group according to a 7:3 ratio. Multivariate Cox regression analysis showed that the independent risk factors of OS were age, race, T_stage, N_stage, M_stage, grade, CA125, and chemotherapy. Independent risk factors of CSS were age, race, marital, T_stage, N_stage, M_stage, grade, CA125, and chemotherapy. According to the above results, the nomograms of OS and CSS in ovarian mucinous adenocarcinoma were constructed. In the training group, the C-index of the OS nomogram was 0.845 (95% CI: 0.821-0.869) and the C-index of the CSS nomogram was 0.862 (95%CI: 0.838-0.886). In the validation group, the C-index of the OS nomogram was 0.843 (95% CI: 0.810-0.876) and the C-index of the CSS nomogram was 0.841 (95%CI: 0.806-0.876). The calibration curve showed the consistency between the predicted results and the actual results, indicating the high accuracy of the nomogram.

CONCLUSION

The nomogram provides 3-year and 5-year OS and CSS predictions for patients with ovarian mucinous adenocarcinoma, which helps clinicians predict the prognosis of patients and formulate appropriate treatment plans.

Analgesia for Gynecologic Oncologic Surgeries: A Narrative Review

PURPOSE OF REVIEW

Gynecologic oncologic malignancies are amongst the most common cancers affecting women across the world. This narrative review focuses on the current state of evidence around optimal perioperative pain management of patients undergoing surgeries for gynecologic malignancies with a specific focus on cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC).

RECENT FINDINGS

Recent improvements in postoperative pain management following all types of gynecologic procedures, including minimally invasive, open-abdominal, or CRS + HIPEC, have been implemented through enhanced recovery after surgery (ERAS) protocols. These protocols encompass the use of preemptive analgesia, neuraxial and regional techniques, local anesthetic infiltration, and multimodal analgesia. The severity of postoperative pain varies for minimally invasive cancer surgery to open debulking procedures. Therefore, an individualized perioperative analgesic plan is critical depending on the surgical approach. For CRS + HIPEC, neuraxial techniques such as thoracic epidurals and opioid sparing multimodal analgesics have shown efficacy in the perioperative period. However, future research is needed as many of these patients develop chronic pain with very limited research done in this realm.

Two-dimensional and three-dimensional T2 weighted imaging-based radiomic signatures for the preoperative discrimination of ovarian borderline tumors and malignant tumors

BACKGROUND

Ovarian cancer is the most women malignancy in the whole world. It is difficult to differentiate ovarian cancers from ovarian borderline tumors because of some similar imaging findings.Radiomics study may help clinicians to make a proper diagnosis before invasive surgery.

PURPOSE

To evaluate the ability of T2-weighted imaging (T2WI)-based radiomics to discriminate ovarian borderline tumors (BOTs) from malignancies based on two-dimensional (2D) and three-dimensional (3D) lesion segmentation methods.

METHODS

A total of 95 patients with pathologically proven ovarian BOTs and 101 patients with malignancies were retrospectively included in this study. We evaluated the diagnostic performance of the signatures derived from T2WI-based radiomics in their ability to differentiate between BOTs and malignancies and compared the performance differences in the 2D and 3D segmentation models. The least absolute shrinkage and selection operator method (Lasso) was used for radiomics feature selection and machine learning processing.

RESULTS

The radiomics score between BOTs and malignancies in four types of selected T2WI-based radiomics models differed significantly at the statistical level (p < 0.0001). For the classification between BOTs and malignant masses, the 2D and 3D coronal T2WI-based radiomics models yielded accuracy values of 0.79 and 0.83 in the testing group, respectively; the 2D and 3D sagittal fat-suppressed (fs) T2WI-based radiomics models yielded an accuracy of 0.78 and 0.99, respectively.

CONCLUSIONS

Our results suggest that T2WI-based radiomic features were highly correlated with ovarian tumor subtype classification. 3D-sagittal MRI radiomics features may help clinicians differentiate ovarian BOTs from malignancies with high ACC.

Expression of TIMPs and MMPs in Ovarian Tumors, Ascites, Ascites-Derived Cells, and Cancer Cell Lines: Characteristic Modulatory Response Before and After Chemotherapy Treatment

Background

The tissue inhibitors of metalloproteinase (TIMPs) and their associated metalloproteinase (MMPs) are essential regulators of tissue homeostasis and are essential for cancer progression. This study analyzed the expression of TIMP-1,-2,-3 and the associated MMPs (MMP-2,-9,-11,-14) in different Stages, Grades and World Health Organization (WHO) classifications of serous ovarian tumors, ascites, ascites-derived cells from chemo-naïve (CN) and relapsed (CR) patients, and in ovarian cancer cell lines. The status of TIMPs and associated MMPs in response to chemotherapy treatment was assessed in cancer cell lines; TCGA data was interrogated to gauge TIMPs and associated MMPs as prognostic and platinum-response indicators.

Methods

The levels of TIMP-1, -2 and -3 were assessed by immunohistochemistry. The mRNA expression of TIMPs and MMPs was quantified by real time PCR (qRT-PCR). The chemosensitivity (IC₅₀ values) to Cisplatin or Paclitaxel in cell lines was evaluated by MTT assay. The levels of TIMPs in ascites and cell lysates were analyzed by an ELISA assay.

Results

The expression of TIMP-2 was significantly upregulated in Type 2 compared to Type 1 tumors and normal/benign ovarian tissues. TIMP-3 expression was significantly enhanced in Stage III, Grade 3 and Type 2 tumors compared to normal/benign ovarian tissues. The mRNA expression of MMP-9,-11 and -14 was significantly upregulated in Stage IV compared to normal/benign ovarian tissues. The expression of TIMP-1 was highest, followed by TIMP-2 and then TIMP-3 in CN ascites. At the cellular level, TIMP-2 mRNA expression was significantly higher in CN compared to CR epithelial cells in patients. The expression of TIMP-1 and -2, MMPs and cancer stem cells (CSCs) were upregulated in response to chemotherapy treatments in cancer cell lines. Interrogation of the TCGA dataset suggests shifts in platinum responses in patients consistent with genetic alterations in TIMP-2, -3 and MMP-2, -11 genes in tumors; and decreased overall survival (OS) and progression-free survival (PFS) in patients with altered MMP-14 genes.

Conclusions

TIMPs and related MMPs are differentially expressed in serous ovarian tumors, ascites, ascites-derived cells and ovarian cancer cell lines. Chemotherapy treatment modulates expression of TIMPs and MMPs in association with increased expression of genes related to cancer stem cells.

Plasma circN4BP2L2 is a promising novel diagnostic biomarker for epithelial ovarian cancer

BACKGROUND

Circular RNAs (circRNAs) are more stable than linear RNA molecules, which makes them promising diagnostic biomarkers for diseases. By circRNA-sequencing analysis, we previously found that circN4BP2L2 was significantly decreased in epithelial ovarian cancer (EOC) tissues, and was predictive of disease progression. The aim of this study was to evaluate the diagnostic value of plasma circN4BP2L2 in EOC.

METHODS

Three hundred seventy-eight plasma samples were acquired prior to surgery. Samples were obtained from 126 EOC patients, 126 benign ovarian cyst patients, and 126 healthy volunteers. CircN4BP2L2 was assessed using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) were assessed using enzyme-linked immunosorbent assay (ELISA). EOC cells were transfected with small interference RNAs (siRNAs) and cell proliferation, migration, invasion, cell cycle and cell apoptosis were performed to assess the effect of circN4BP2L2 in EOC. Receiver operating curve (ROC), the area under the curve (AUC), sensitivity and specificity were estimated.

RESULTS

Plasma circN4BP2L2 was significantly downregulated in EOC patients. Decreased circN4BP2L2 was significantly associated with advanced tumor stage, worse histological grade, lymph node metastasis and distant metastasis in EOC. CircN4BP2L2 inhibited tumor cell migration and invasion in vitro. CircN4BP2L2 could significantly separate EOC from benign (AUC = 0.82, P <  0.01) or normal (AUC = 0.90, P <  0.01) cohort. Early stage EOC vs benign (AUC = 0.81, P <  0.01) or normal (AUC = 0.90, P <  0.01) cohort could also be distinguished by circN4BP2L2. In discrimination between EOC cohort and benign or normal cohort, circN4BP2L2 performed equally well in both pre- and post-menopausal women. The combination of circN4BP2L2, CA125 and HE4 showed high sensitivity and specificity in detecting EOC cases.

CONCLUSIONS

Plasma circN4BP2L2 is significantly downregulated in EOC and might serve as a promising novel diagnostic biomarker for EOC patients, especially in early stage EOC cases. CircN4BP2L2 might act as an adjunct to CA125 and HE4 in detecting EOC. Further large-scale studies are warranted to verify our results.

Current Treatments and New Possible Complementary Therapies for Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is one of the deadliest gynaecological malignancies. The late diagnosis is frequent due to the absence of specific symptomatology and the molecular complexity of the disease, which includes a high angiogenesis potential. The first-line treatment is based on optimal debulking surgery following chemotherapy with platinum/gemcitabine and taxane compounds. During the last years, anti-angiogenic therapy and poly adenosine diphosphate-ribose polymerases (PARP)-inhibitors were introduced in therapeutic schemes. Several studies have shown that these drugs increase the progression-free survival and overall survival of patients with ovarian cancer, but the identification of patients who have the greatest benefits is still under investigation. In the present review, we discuss about the molecular characteristics of the disease, the recent evidence of approved treatments and the new possible complementary approaches, focusing on drug repurposing, non-coding RNAs, and nanomedicine as a new method for drug delivery.

Nomogram of Combining CT-Based Body Composition Analyses and Prognostic Inflammation Score: Prediction of Survival in Advanced Epithelial Ovarian Cancer Patients

PURPOSE

To investigate the value of body composition changes measured by quantitative computer tomography (QCT) in evaluating the prognosis of advanced epithelial ovarian cancer (AEOC) patients who underwent primary debulking surgery (PDS) and adjuvant platinum-based chemotherapy, and constructed a nomogram model for predicting survival in combination with prognostic inflammation score (PIS).

METHOD

Fifty-seven patients with AEOC between 2012 and 2016 were retrospectively enrolled. Pre- and post-treatment CT images were used to analyze the body composition biomarkers. The subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), cross-sectional area of paraspinal skeletal muscle area (PMA), skeletal muscle density (SMD), body mineral density (BMD) were measured from two sets of CT images.

RESULTS

In multivariate analyses, VFA gain, PMA loss, BMD loss, and PIS were independent risk factors of overall survival (OS) (HR = 3.7, 3.0, 2.8, 1.9, respectively, all p < 0.05). Receiver operating characteristic (ROC) curves showed that the prognostic model combining body composition changes (BCC) and PIS had the highest predictive performance (area under the curve = 0.890). The concordance index (C-index) of the prognostic nomogram was 0.779 (95% CI, 0.673-0.886). Decision curve analysis (DCA) demonstrated the prognostic nomogram had a great distinguishing performance.

CONCLUSION

CT-based body composition analyses and PIS were associated with poor OS for AEOC patients who underwent PDS and adjuvant platinum-based chemotherapy. The prognostic nomogram with a combination of BCC and PIS was dependable in predicting survival for AEOC patients during treatment.