Early-stage Ovarian Cancer Research Articles

Sentinel lymph node detection in early stage ovarian cancer: the primary experience in N. N. Blokhin national medical Research Center of Oncology

Background. Surgical staging including pelvic and para-aortic lymphadenectomy is recommended in patients with clinical early-stage epithelial ovarian cancer. The therapeutic role of pelvic and para-aortic lymphadenectomy is still under debate, this procedure can increase risk of intra- and post-operative complications. using the sentinel lymph node (SLN) detection in early stage ovarian cancer in very promising and decreases the level of surgical damage. But nowadays the data on effectiveness, safety sensitivity and specificity of SLN are limited and the technique has to be standardized.Aim. To determine the feasibility of the SLN detection procedure using indocyanine green in early stage ovarian cancer.Materials and methods. four patients with clinical stage I epithelial ovarian cancer underwent SLN detection using indocyanine green. The tracer was injected into hilum of the ovary or ovarian ligament stumps in the case of previous adnexectomy. SLN were detected in infrared spectrum. Systemic retroperitoneal lymph node dissection of the pelvic and paraaortic areas was performed after SLN being removed. frozen section of was not performed in this study.Results. SLN were detected in paraaortic area in three of four patients. no one of patients had metastatic disease.Conclusion. The primary experience demonstrates SLN mapping of the ovary being feasible. Prospective study is required to evaluate sensitivity and specificity of SLn detection in early stage ovarian cancer.

595P Multi-marker liquid biopsy for detection of early-stage ovarian cancer

Ovarian cancer is often not detected (∼70% of the cases) until it has spread to regional or distant sites, thus limiting curative options. In contrast, when detected in a localized state, the 5-year survival rate increases dramatically to ∼90% in comparison to the ∼30% survival rate for distant cases. Currently, only 15% of cases are detected at early stages highlighting the need for the development of non-invasive detection strategies such as liquid biopsies.

Clinical calculator redefines prognosis for high-risk early-stage ovarian cancers and potential to guide treatment in the adjuvant setting

ObjectiveTo determine the utility of a clinical calculator to redefine prognosis and need for chemotherapy among patients with early-stage high-risk epithelial ovarian cancer. MethodsData were abstracted for stage I-II, high-risk ovarian cancer from the National Cancer Database from years 2005 to 2015. Based on demographic, pathologic, surgical, and laboratory characteristics, a clinical score was developed using Cox regression. Propensity score weighting was used to adjust for differences between patients who did and did not receive chemotherapy. ResultsOf 8188 patients with early-stage high-risk ovarian cancer, 6915 (84%) did and 1273 (16%) did not receive chemotherapy. A clinical calculator was created utilizing age, stage, histology, grade, tumor size, number of pelvic and paraaortic lymph nodes examined, the presence of malignant ascites, and CA125. The calculator divided patients into low, moderate, and high-risk groups with 5-year OS (overall survival) of 92%, 82%, and 66%, and 10-year OS of 85%, 67%, and 44%, respectively. Chemotherapy improved 5-year OS and 10-year OS in the high-risk group (56% to 73%; p < 0.001, 34% to 48%; p < 0.001). The moderate risk group had improved 5-year OS (80% to 85%; p = 0.01) but not 10-year OS (66% to 66%; p = 0.13). Chemotherapy did not improve 5-year or 10-year OS in low-risk patients (93% to 92%, p = 1.0, 86% to 84%, p = 0.99). ConclusionsThe prognosis among high-risk early-stage ovarian cancer patients is heterogeneous. This calculator may aid in patient-centered counseling regarding potential treatment benefits.

A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses.

To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts. Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM. The performance of the metabolite panel was evaluated in an independent set of sera from 118 ovarian cancer cases and 56 subjects with BPM. The contributions of the panel for improving upon the performance of ROMA were further assessed. A 7-marker metabolite panel (7MetP) developed in the training set yielded an AUC of 0.86 [95% confidence interval (CI): 0.76-0.95] for early-stage ovarian cancer in the independent test set. The 7MetP+ROMA model had an AUC of 0.93 (95% CI: 0.84-0.98) for early-stage ovarian cancer in the test set, which was improved compared with ROMA alone [0.91 (95% CI: 0.84-0.98); likelihood ratio test P: 0.03]. In the entire specimen set, the combined 7MetP+ROMA model yielded a higher positive predictive value (0.68 vs. 0.52; one-sided P < 0.001) with improved specificity (0.89 vs. 0.78; one-sided P < 0.001) for early-stage ovarian cancer compared with ROMA alone. A blood-based metabolite panel was developed that demonstrates independent predictive ability and complements ROMA for distinguishing early-stage ovarian cancer from benign disease to better inform clinical decision making.

Is There a Survival Benefit of Adjuvant Chemotherapy in Stage IC1 Epithelial Ovarian Cancer Patients? A Meta-Analysis

The purpose of the present systematic review is to clarify whether adjuvant chemotherapy improves survival rates in women with stage IC1 ovarian cancer. We searched Medline, Scopus, Clinicaltrials.gov, EMBASE, Cochrane Central Register of Controlled Trials CENTRAL and Google Scholar. We considered comparative observational studies and randomized trials that investigated survival outcomes (progression-free (PFS) and overall survival (OS)) among women with intraoperative rupture of early-stage epithelial ovarian cancer who received adjuvant chemotherapy and those that did not. Eleven studies, which recruited 7556 patients, were included. The risk of bias was defined as moderate after assessment with the Risk of Bias in non-Randomized Trials tool. Meta-analysis was performed with RStudio. Seven studies investigated the impact of adjuvant chemotherapy on recurrence-free survival of patients experiencing intraoperative cyst rupture for otherwise stage I ovarian cancer. The outcome was not affected by the use of adjuvant chemotherapy as the effect estimate was not significant (HR 1.24, 95% CI 0.74, 2.04). The analysis of data from 5 studies similarly revealed that overall survival rates were comparable among the two groups (HR 0.75, 95% CI 0.54, 1.05). This meta-analysis did not detect any benefit from adjuvant chemotherapy for stage IC ovarian cancer patients with cyst rupture. However, conclusions from this investigation are limited by a study population which included multiple histologic subtypes, high and low grade tumors and incompletely staged patients.

Clinical Performance of a Multivariate Index Assay in Detecting Early-Stage Ovarian Cancer in Filipino Women.

This study evaluated the clinical performance and overall utility of a multivariate index assay in detecting early-stage ovarian cancer in a Filipino population. This is a prospective cohort study among Filipino women undergoing assessment for an ovarian mass in a tertiary center. Patients diagnosed with early-stage ovarian cancer and who underwent a physical examination before level III specialist ultrasonographic and Doppler evaluation, multivariate index assay (MIA2G), and surgery for an adnexal mass were included in this study. Ovarian tumors were classified as high-risk for malignancy based on the IOTA-LR2 score. The ovarian imaging and biomarker results were correlated with the reference standard: surgico-pathologic findings. The MIA2G exhibited the best overall performance among individual classifiers with a sensitivity of 91.7% and NPV of 84.7%, with a concomitant higher sensitivity in early-stage disease, whether as an individual classifier (93.5%) or in serial combination with ultrasound (85.5%). The performance of biomarkers (specificity, positive predictive values, and AUROC) such as MIA2G and CA-125 significantly improved when combined with an ultrasound risk scoring approach (p < 0.01). MIA2G showed a higher sensitivity for detecting lesions among EOC and late-stage ovarian cancers than otherwise. The application of biomarkers for evaluating ovarian masses in our local setting is secondary to ultrasound but adopting multivariate index assays rather than CA-125 would increase the detection of early-stage ovarian cancers regardless of menopausal status. This is most relevant in areas where level III sonographers or gynecologic oncologists are limited and preoperative referrals to these specialists can improve the survival of our patients.

Circulating tumor-derived small extracellular vesicles micro RNAs plus CA-125 objectively tests residual tumor prior to debulking surgery in advanced ovarian cancer (525)

<b>Objectives:</b> No residual disease after debulking surgery (R0 resection) is the most critical independent prognostic factor for advanced ovarian cancer (AOC). There is an unmet clinical need for selecting primary or interval debulking surgery in AOC patients using existing prediction models, such as CA-125, CT, PET-CT, or laparoscopy. Therefore, it is of paramount importance to preoperatively estimate the likelihood of R0 resection for choosing the best therapeutic strategy. In this study, we sought to develop a novel, non-invasive, and objective detection method. <b>Methods:</b> Differentially expressed microRNAs (miRNA) in circulating small extracellular vesicles (sEVs) between any residual disease (R0) and no residual disease (non-R0) AOC patients were revealed using small RNA sequencing. miRNA expression of plasma samples was measured by TaqMan qRT-PCR. The prediction model of residual disease risk was established via LASSO and logistic regression analysis based on the discovery-validation set. Tissue sEVs were extracted from primary tumor tissue, metastatic tumor tissue, adjacent tissue, or non-tumor tissue by differential ultracentrifugation and size exclusion chromatography (SEC). Cell-type-specific markers (EpCAM, FAP, CD45, CD31) in tumor sEVs pool were evaluated by western blot analysis. Plasma sEVs were captured by the magnetic bead sorting system (MACS) using specific surface proteins as markers (EpCAM, CD45, CD235a). <b>Results:</b> A total of 270 subjects were recruited in this study from four clinical centers. According to the comprehensive plasma sEVs miRNAs profile in AOC patients, we identified and optimized a risk model consisting of plasma sEVs 5-miRNA and CA-125 for predicting residual disease (AUC:0.912; sensitivity:0.964; specificity:0.884; PPV:0.911; NPV:0.905;). Moreover, there were significant differences in model index scores between AOC patients and patients with benign ovarian tumors, early-stage ovarian cancer with FIGO I or II, and advanced colorectal cancer. Our data showed that EpCAM-positive sEVs accounted for the highest in tumor sEVs pool. Besides, these 5-miRNAs were a high concentration horizontal packaging in plasma EpCAM-sEVs. By further comparing the sEVs 5-miRNA expression in paired tumor and non-tumor tissue as well as plasma, we found that they were mainly originated from epithelial ovarian cancer cells and their tumor microenvironment. These results indicated that plasma sEVs 5-miRNA in AOC patients was associated with residual disease. <b>Conclusions:</b> Collectively, our study demonstrated a distinct profile of circulating sEVs miRNAs between R0 and non-R0 patients and obtained a robust model of circulating tumor-derived sEVs 5-miRNA combined with CA-125 to preoperatively anticipate a high risk of residual disease for optimizing clinical treatment and guiding differential diagnosis. This prediction panel, as a tool of non-invasive liquid biopsy, can be part of a standard monitoring strategy for screening high-risk patients who are allowed for neoadjuvant chemotherapy.

Long-term survival of early stage I epithelial ovarian cancer: A multicenter retrospective observational study (321)

<b>Objectives:</b> Therapy for early-stage epithelial ovarian cancer (EOC) involves complete surgical staging with or without adjuvant chemotherapy. The current international multi-center study aimed to investigate the long-term survival of different histological subtypes for stage I EOC. <b>Methods:</b> A multi-center cohort study was performed among all patients with FIGO stage I (IA-IC3) EOC treated at four European referral centers between 1985 and 2021. Overall survival (OS) and progression-free (PFS) survival were compared between the different stage I groups using Kaplan-Meier survival curves. <b>Results:</b> A total of 1115 patients met the inclusion criteria. Of them, 48.4% (<i>n</i>=540) were in stage IA, 6.6% (<i>n</i>=73) stage IB, and 45% (<i>n</i>=502) stage IC: stage IC1 54% (<i>n</i>=271), stage IC2 31.5% (<i>n</i>=158), and stage IC3 14.5% (<i>n</i>=73). The predominant histologic subtypes included highgrade serous (25.4%), low-grade endometrioid (24.8%), and clear cell (19%). Complete surgical staging, including lymphadenectomy, was performed in 62.1%, and 60% received adjuvant platinum-based chemotherapy. The median follow-up was 48 months. The median five-year (5y) OS and PFS rates were 94% and 86%, respectively, with no difference between stage IA and IB. However, a significantly better OS and PFS were observed for stage IA as compared to stage IC (p=0.007 and p<0.001, respectively). Considering histologic subtypes, a significant better PFS was documented for low-grade mucinous and low-grade endometrioid subgroup (HR: 0.22; 95% CI: 0.09-0.45, p=0.001; HR: 0.49; 95% CI: 0.29-0.83, p=0.007, respectively), as well a better OS for the latter (HR: 0.43; 95% CI: 0.22-0.86, p=0.017). In stage IA-B, the different histology subtypes showed a comparable prognosis (5y: OS: 96% and PFS: 92%), with the exception of a worsened OS for high-grade mucinous cases (HR: 5.90; 95% CI: 1.55-22.4, p=0.009). Among stage IC, the histologic subgroups showed comparable OS (5y 92%), but significantly better PFS for low-grade mucinous and low-grade endometrioid subtypes (HR: 0.21; 95% CI: 0.05-0.86, p=0.031; HR: 0.44; 95% CI: 0.23-0.84, p=0.013, respectively). In the subgroup of high-grade serous ovarian cancer patients in stage IC disease, the chemotherapy with carboplatin/paclitaxel seems to be superior compared to single-agent platinum (5y OS: 100% vs 83%; p=0.009). In multivariate analysis, partial staging procedure (compared to complete) was found as risk factor for worsen PFS (HR: 1.73; 95% CI: 1.13-2.66, p=0.012), while low-grade endometrioid histology (compared to high-grade serous) showed better outcome regarding OS (HR: 0.46; 95% CI: 0.22-0.95, p=0.036) and PFS (HR: 0.42; 95% CI: 0.25-0.73, p=0.002). <b>Conclusions:</b> Overall, stage I ovarian cancer patients treated in referral centers exhibited an excellent prognosis regardless of the histologic type. Histologic subtype and quality of surgical treatment affect the prognosis. Our data suggest platinum-based combination chemotherapy for the subgroup of FIGO stage IC high-grade serous ovarian cancer.

Incidence of lymph node metastasis in early-stage low-grade serous ovarian cancer: a systematic review

ObjectiveThe objective of this systematic review was to assess the incidence of lymph node metastasis in patients with clinically presumed early-stage low-grade serous ovarian cancer that underwent primary surgical treatment.MethodsThis...

Development of a Multiprotein Classifier for the Detection of Early Stage Ovarian Cancer.

Simple SummaryWhen ovarian cancer is detected early, the survival rate is high. Unfortunately, existing blood tests are neither sensitive nor specific enough to screen women for ovarian cancer. The purpose of this study was to determine the levels of 92 cancer-related proteins in the blood of women with ovarian cancer compared to healthy women in order to develop a test for ovarian cancer detection. We tested the blood of more than 400 women and identified four proteins that, when combined, successfully detected over 90% of the women with ovarian cancer. We then tested more than 700 additional blood samples and found that the combination of the four proteins successfully distinguished the majority of the blood samples from women with both early and late stages of ovarian cancer compared to healthy women. These four proteins show promise in the development of a test to detect the early stages of ovarian cancer.Background: Individual serum biomarkers are neither adequately sensitive nor specific for use in screening the general population for ovarian cancer. The purpose of this study was to develop a multiprotein classifier to detect the early stages of ovarian cancer, when it is most treatable. Methods: The Olink Proseek Multiplex Oncology II panel was used to simultaneously quantify the expression levels of 92 cancer-related proteins in sera. Results: In the discovery phase, we generated a multiprotein classifier that included CA125, HE4, ITGAV, and SEZ6L, based on an analysis of sera from 116 women with early stage ovarian cancer and 336 age-matched healthy women. CA125 alone achieved a sensitivity of 87.9% at a specificity of 95%, while the multiprotein classifier resulted in an increased sensitivity of 91.4%, while holding the specificity fixed at 95%. The performance of the multiprotein classifier was validated in a second cohort comprised of 192 women with early stage ovarian cancer and 467 age-matched healthy women. The sensitivity at 95% specificity increased from 74.5% (CA125 alone) to 79.2% with the multiprotein classifier. In addition, the multiprotein classifier had a sensitivity of 95.1% at 98% specificity for late stage ovarian cancer samples and correctly classified 80.5% of the benign samples using the 98% specificity cutpoint. Conclusions: The inclusion of the proteins HE4, ITGAV, and SEZ6L improved the sensitivity and specificity of CA125 alone for the detection of early stages of ovarian cancer in serum samples. Furthermore, we identified several proteins that may be novel biomarkers of early stage ovarian cancer.

Systematic Pelvic and Para-Aortic Lymphadenectomy During Fertility-Sparing Surgery in Patients With Early-Stage Epithelial Ovarian Cancer: A Retrospective Study.

ObjectiveThe implication of pelvic and para-aortic lymphadenectomy in surgical staging of early-stage epithelial ovarian cancer (eEOC) is still debated. Limited data are available about systematic lymphadenectomy during fertility-sparing surgery (FSS) in patients with eEOC.MethodsThe medical records of 38 patients with FIGO stage I EOC and below 40 years who underwent FSS at our hospital between January 2003 and December 2018 were retrospectively reviewed.ResultsAmong them, 18 patients (47.4%) underwent comprehensive lymphadenectomy, 11 patients (28.9%) underwent lymph node sampling, and 9 patients (23.7%) did not undergo lymphadenectomy. There was no statically significant difference in age, histology, grade, surgical approach, chemotherapy, and gestation among the three groups. With a median follow-up of 52.5 months (range: 24–153), three patients (7.9%) with FIGO stage IC EOC developed tumor recurrence. In these patients, progress-free survival (PFS) was 92.1%, and overall survival (OS) was 94.7%. No significant difference in the OS. Three patients had among all the patients, 15 patients (39.5%) had gestation after treatment, and 23 patients (60.5%) did not have gestation after treatment.ConclusionThe number of lymph nodes removed did not significantly affect survival eEOC with FSS. Systematic pelvic and para-aortic lymphadenectomy could not be performed for mucious eEOC patients with FSS if intraoperative freezing in confirmed and no suspicious lymph nodes are found. A better understanding of sentinel lymph node biopsy may help to identify whether the patient requires FSS.

Abstract 3390: Preliminary results for a novel single extracellular vesicle assay for early stage ovarian cancer: The power of co-localized detection of surface biomarkers

Abstract Introduction: Ovarian cancer (OC) is one of the deadliest cancers, with 314,000 new cases and 207,000 deaths globally in 2020. Serum CA125 has been explored as an OC biomarker for the past 40 years, but lacks sensitivity for early stage OC and is not recommended for screening average-risk, asymptomatic women. We hypothesize that co-localization of biomarkers on the surface of individual extracellular vesicles (EVs), which are shed into the circulation by cancer cells, may lead to development of a blood test for early stage OC. We evaluated the potential of our approach in detecting early stage OC in clinical samples. Methods: We isolated EVs using size-exclusion chromatography and immunoaffinity capture, and detected biomarkers co-localized on the surface of individual EVs with proximity ligation qPCR. Using this approach, we evaluated 49 antibody combinations recognizing 2 or more biomarkers. Each combination consisted of 1 capture antibody and 2 oligonucleotide-tagged detection antibodies. We tested plasma samples from women with early stage I/II high-grade serous ovarian carcinoma (HGSOC)(n=18; 48-80 yr, med 57) and late stage HGSOC (n=24; 37-80 yr, med 54). HGSOC samples were sourced from 2 commercial vendors. Controls comprised samples from women with benign ovarian masses (n=26; 23-76 yr, med 39.5) sourced from a single vendor, and samples prospectively collected by Mercy from healthy women with no cancer history (n=24; 22-72 yr, med 52.5). PCR cycle threshold (Ct) values were measured for each of 49 combinations and data was evaluated using univariate analysis. Performance was compared to plasma CA125 measured at Mercy by commercial ELISA. Results: 8 of 49 combinations distinguished all stages of HGSOC relative to benign and healthy controls with AUCs ranging from 0.86 (95% CI 0.78-0.94) to 0.95 (95% CI 0.90-1.00), comparable to CA125 with an AUC of 0.87 (95% CI 0.79-0.95). One of the most effective combinations (STn, BST2, MUC1) had a sensitivity of 0.78 (95% CI 0.52-0.94) at a specificity of 0.96 (95% CI 0.87-0.99) in detecting early stage HGSOC. This combination also detected HGSOC in 6 of 11 women (3 early stage, 3 late stage) with normal CA125 (&amp;lt; 25 U/mL) and correctly classified 7 of 8 women with benign masses and high CA125 (&amp;gt; 25 U/mL). Conclusions: These preliminary data suggest that co-localization of surface biomarkers in single EVs may provide an effective means to identify women with early stage HGSOC, including those with normal CA125, while avoiding false positives in women with benign masses and high CA125. Despite the inherent challenges associated with commercial samples, our finding that several combinations detected early stage HGSOC is promising. Statistically powered studies with curated repository specimens are underway to refine combinations and independently validate our assay for early stage OC detection. Citation Format: Laura T. Bortolin, Daniel P. Salem, Sanchari Banerjee, Kelly M. Biette, Delaney M. Byrne, Anthony D. Couvillon, Peter A. Duff, Jonian Grosha, MacKenzie Sadie King, Christopher R. Sedlak, Ibukunoluwapo O. Zabroski, Claire Alexander, Karen Copeland, Daniel Gusenleitner, Emily S. Winn-Deen, Eric K. Huang, Bo R. Rueda, Joseph Charles Sedlak. Preliminary results for a novel single extracellular vesicle assay for early stage ovarian cancer: The power of co-localized detection of surface biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3390.

Abstract LB168: Platelet RNA signature enables early and accurate detection of ovarian cancer: An intercontinental, biomarker identification study

Abstract Background: Morpho-physiological alternations of platelets provided a rationale to harness RNA sequencing of tumor-educated platelets (TEPs) for preoperative diagnosis of cancer. Timely, accurate, and non-invasive detection of ovarian cancer in women with adnexal masses presents a significant clinical challenge. Patients and Methods: This intercontinental, hospital-based, diagnostic study included 761 treatment-naïve inpatients with histologically confirmed adnexal masses and 167 healthy controls from nine medical centers (China, n=3; Netherlands, n=5; Poland, n=1) between September 2016 and May 2019. The main outcomes were the performance of TEPs and their combination with CA125 in two Chinese (VC1 and VC2) and the European (VC3) validation cohorts collectively and independently. Exploratory outcome was the value of TEPs in public pan-cancer platelet transcriptome datasets. Results: The AUCs for TEPs in the combined validation cohort, VC1, VC2, and VC3 were 0.918 (95% CI 0.889-0.948), 0.923 (0.855-0.990), 0.918 (0.872-0.963), and 0.887 (0.813-0.960), respectively. Combination of TEPs and CA125 demonstrated an AUC of 0.922 (0.889-0.955) in the combined validation cohort; 0.955 (0.912-0.997) in VC1; 0.939 (0.901-0.977) in VC2; 0.917 (0.824-1.000) in VC3. For subgroup analysis, TEPs exhibited an AUC of 0.858, 0.859, and 0.920 to detect early-stage, borderline, non-epithelial diseases and 0.899 to discriminate ovarian cancer from endometriosis. Analysis of public datasets suggested that TEPs had potential to detect multiple malignancies (Table 1). Conclusions: TEPs had robustness, compatibility, and universality for preoperative diagnosis of ovarian cancer since it withstood validations in populations of different ethnicities, heterogeneous histological subtypes, early-stage ovarian cancer as well as other malignancies. However, these observations warrant prospective validations in a larger population before clinical utilities. Table 1. Performance for TEPs in public pan-cancer datasets. Disease n Healthy Control AUC, area under the curve (95% CI) Women NSCLC (non-small-cell lung cancer) 126 77 0.758 (0.691-0.825) Breast cancer 38 77 0.817 (0.726-0.909) Colorectal cancer 18 77 0.973 (0.945-1.000) Pancreatic cancer 16 77 0.993 (0.981-1.000) Glioblastoma 10 77 0.923 (0.831-1.000) Men NSCLC 119 82 0.746 (0.677-0.815) Colorectal cancer 25 82 0.933 (0.884-0.982) Pancreatic cancer 22 82 0.993 (0.984-1.000) Glioblastoma 19 82 0.981 (0.959-1.000) All NSCLC 245 159 0.774 (0.728-0.820) Colorectal cancer 40 159 0.978 (0.961-0.996) Breast cancer 38 159 0.821 (0.736-0.906) Pancreatic cancer 35 159 0.987 (0.974-0.999) Glioblastoma 35 159 0.931 (0.890-0.972) Hepatobiliary carcinomas 14 159 0.991 (0.978-1.000) Citation Format: Yue Gao, Chun-Jie Liu, Hua-Yi Li, Xiao-Ming Xiong, Sjors G.j.g. In ‘t Veld, Gui-Ling Li, Jia-Hao Liu, Guang-Yao Cai, Gui-Yan Xie, Shao-Qing Zeng, Yuan Wu, Jian-Hua Chi, Qiong Zhang, Xiao-Fei Jiao, Lin-Li Shi, Wan-Rong Lu, Wei-Guo Lv, Xing-Sheng Yang, Jurgen M.j. Piek, Cornelis D de Kroon, C.a.r. Lok, Anna Supernat, Sylwia Łapińska-Szumczyk, Anna Łojkowska, Anna J. Żaczek, Jacek Jassem, Bakhos A. Tannous, Nik Sol, Edward Post, Myron G. Best, Bei-Hua Kong, Xing Xie, Ding Ma, Thomas Wurdinger, An-Yuan Guo, Qing-Lei Gao. Platelet RNA signature enables early and accurate detection of ovarian cancer: An intercontinental, biomarker identification study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB168.

Abstract 2253: Plasma metabolomic profiles associated with early and late-stage high-grade serous ovarian cancer

Abstract Background: Ovarian cancer has poor survival due to more than 60% of patients being diagnosed at advanced stage. Therefore, discovery of novel, non-invasive early detection biomarkers has high potential to improve survival. Here, we identified plasma metabolomic profiles associated with early-stage and late-stage high-grade serous ovarian cancer (HGSOC), the most common histotype. Method: We examined 197 lipid and lipid-related metabolites measured using a validated, liquid chromatography tandem mass spectrometry method (Broad Institute, Cambridge, MA) in plasma collected prior to surgery from 40 early-stage and 40 late-stage HGSOC patients and 40 population-based controls matched on age, year, and menopausal status at blood draw. We used multivariable logistic regression, adjusted for matching factors, tubal ligation, oral contraceptive use, and parity, to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) of ovarian cancer risk per 1 standard deviation increase in probit-transformed metabolite levels. We used Metabolite Set Enrichment Analysis (MSEA) to identify metabolite groups. We accounted for testing multiple correlated hypotheses using the number of effective tests (NEF) or false discovery rate (FDR). Results: Compared to controls, there were 34 metabolites associated with early-stage HGSOC and 88 metabolites associate with late-stage HGSOC (unadjusted p-value&amp;lt;0.05). All metabolites associated with risk of early-stage HGSOC and majority (n=80, 90%) of the metabolites associated with risk of late-stage HGSOC were inversely associated with ORs ranging from 0.28 to 0.48 for early-stage and 0.08 to 0.59 for late-stage HGSOC. Interestingly, the direction of association across all these metabolites were similar in both early-stage and late-stage HGSOC, with stronger effect estimates for late-stage HGSOC. After multiple testing correction, there were 9 statistically significant metabolites associated with risk of late-stage HGSOC (NEF p-value&amp;lt;0.05) whereas no individual metabolites remained associated with risk of early-stage HGSOC. MSEA revealed similar patterns of association compared to controls across the 11 lipid groups assessed in early and late-stage HGSOC cases. Metabolite groups of phosphatidylethanolamine plasmalogens and triglycerides were inversely associated with early-stage HGSOC compared to controls (FDR p-value&amp;lt;0.05). Metabolite groups of phosphatidylethanolamine plasmalogens and phosphatidylcholines were inversely, and diglycerides were positively associated with late-stage HGSOC compared to controls (FDR p-value&amp;lt;0.05). Conclusion: Our results revealed early-stage and late-stage HGSOC having similar plasma metabolomic profiles overall although there were more metabolites that were significantly associated with late-stage HGSOC than early-stage HGSOC compared to population-based controls. Citation Format: Naoko Sasamoto, Oana A. Zeleznik, Allison F. Vitonis, Daniel W. Cramer, Julian Avila-Pacheco, Clary B. Clish, Shelley S. Tworoger, Kathryn L. Terry. Plasma metabolomic profiles associated with early and late-stage high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2253.

Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review.

Simple SummaryOvarian high-grade serous carcinoma (HGSC) has a 5-year survival rate of less than 50%, making it one of the most lethal gynecological cancers for women in the developed world today. Delayed presentation of clinical symptoms and late-stage diagnosis drive the high mortality rate of this disease. Early detection is associated with significant improvements in survival, however, screening in the general population is currently not recommended at this time due to a notable lack of sensitive and specific biomarkers for early-stage disease. In this review, we provide an overview of the current landscape of ovarian cancer diagnostics, emphasizing emerging methodologies for the non-invasive detection of HGSC.With a 5-year survival rate of less than 50%, ovarian high-grade serous carcinoma (HGSC) is one of the most highly aggressive gynecological malignancies affecting women today. The high mortality rate of HGSC is largely attributable to delays in diagnosis, as most patients remain undiagnosed until the late stages of -disease. There are currently no recommended screening tests for ovarian cancer and there thus remains an urgent need for new diagnostic methods, particularly those that can detect the disease at early stages when clinical intervention remains effective. While diagnostics for ovarian cancer share many of the same technical hurdles as for other cancer types, the low prevalence of the disease in the general population, coupled with a notable lack of sensitive and specific biomarkers, have made the development of a clinically useful screening strategy particularly challenging. Here, we present a detailed review of the overall landscape of ovarian cancer diagnostics, with emphasis on emerging methods that employ novel protein, genetic, epigenetic and imaging-based biomarkers and/or advanced diagnostic technologies for the noninvasive detection of HGSC, particularly in women at high risk due to germline mutations such as BRCA1/2. Lastly, we discuss the translational potential of these approaches for achieving a clinically implementable solution for screening and diagnostics of early-stage ovarian cancer as a means of ultimately improving patient outcomes in both the general and high-risk populations.

Fertility Preserving Surgery Outcomes for Ovarian Malignancy: Data from a Tertiary Cancer Centre in Central London.

Fertility Sparing Surgery (FSS) appears to be a safe means of treating early-stage ovarian cancer based on relatively limited evidence. However, there is currently insufficient evidence to aid women in counselling about their potential fertility outcomes. The aim of this study was to assess the reproductive outcomes and prognosis of women who have undergone FSS for ovarian malignancy. Between 1 June 2008 and 1 June 2018, a retrospective review of a clinical database was conducted to identify all consecutive patients who underwent FSS in a central London gynaecological oncology centre. All patients with a histological diagnosis of ovarian malignancy (excluding borderline ovarian tumours) were eligible. All identified patients were then prospectively called into a follow up and asked to complete a questionnaire about their fertility outcomes. A total of 47 women underwent FSS; 36 were included in this study. The mean age was 30.3 years (95% Confidence Interval [CI]: 27.6 to 33.0 years). During the study period, 17/36 (47.2%) of the women had attempted to conceive following surgery, with a successful live birth rate of 52.9% (9/17). The mean time of recurrence was 125.3 months (95% CI: 106.5–144.1 months). The mean time to death was 139.5 months (95% CI: 124.3–154.8). The cancer grade, tumour stage and use of Assisted Reproductive Technology (ART) were the main factors significantly associated with the risk of recurrence and death. In conclusion, this study suggests that a large proportion of women will not attempt to conceive following FSS. For those who do attempt to conceive, the likelihood of achieving a live birth is high. However, careful counselling about the higher risk of recurrence and worse survival for women with high grade cancer, disease Stage > IA and potentially those who undergo ART is essential before contemplating FFS.

Detection of early-stage ovarian cancer using a liquid biopsy test based on extracellular vesicle proteins.

e17558 Background: We have recently conducted a study to evaluate the predictive value of proteins associated with extracellular vesicles (EVs) isolated using an alternating current electrokinetic (ACE) system, for the detection of early stage (I &amp; II) ovarian cancer cases. Ovarian cancer patients, typically, have few symptoms in stages I &amp; II; the disease is often undetected until it is advanced. Currently, only 15% of cases are detected at early stages when clinical treatment outcomes are improved. Methods: We tested the feasibility of detecting the presence of early stage (I-II) ovarian cancer using protein biomarkers carried by EVs in patient blood. Using an ACE microelectrode array, EVs were purified from ovarian cancer patient plasma (N = 70; Stage I = 51, Stage II = 19) and female non-cancer donors (N = 290) and tested for the presence of cancer biomarker proteins with multiple bead-based multiplex immunoassay kits. An adaptive boosted trees machine learning algorithm with 100x cross-validation was developed to identify the most important features for differentiation between cases and controls. Results: The machine learning algorithm identified relevant biomarkers for the detection of ovarian cancer with a receiver-operator characteristic area under the curve (AUC) of 0.952 (95% CI: 0.918 – 0.985). Overall sensitivity was 72.9% at 99% specificity, rising to 84.3% at 95% specificity. When further stratified, Stage I sensitivity was 70.6% and stage II sensitivity was 78.9% at the 99% specificity level, as expected. We also separated the cases into endometroid carcinoma (N = 24) and serous carcinoma (N = 36). At the 99% specificity level, the sensitivity was 87.5% and 63.9%, respectively. Conclusions: These results suggest that it is possible to detect early-stage ovarian cancer by analyzing the EV-bound proteins isolated with the ACE technology. EVs may carry the earliest signals of cancer development and a blood-based EV-protein biomarker test can yield high sensitivity and specificity. Stable biomarker detection with small input volumes may be possible. These results require further investigation in larger datasets to validate the current observations with the potential application for general, routine screening, as well as for populations at elevated disease risk.

Exploring the value of intraoperative frozen section in the diagnosis and treatment of patients with early-stage ovarian cancer: A retrospective analysis of 421 patients.

e17568 Background: Rapid and accurate judgment of the source and nature of tumors is conducive for surgeons to select the appropriate scope and method of surgery, and avoid unnecessary over-treatment or under-treatment. This study aimed to explore the diagnostic and treatment value of intraoperative frozen section pathology in patients with early-stage ovarian cancer (EOC) in the real world. Methods: We retrospectively collected the clinical and pathological data of EOC at West China Second University Hospital between January,2013 and December,2017, which diagnosed as stage ⅠA- IIA EOC according to the International Federation of Gynecology and Obstetrics (FIGO) 2014 standard of Ovarian cancer, fallopian tube cancer and peritoneal cancer. Results: There were totally 421 cases of EOC in the Second West China Hospital of Sichuan University from 2013 to 2017. The average age was 42.9 ± 13.5 years old. There were 395 patients who had finished the comprehensive staging surgeries. Group A consisted of 239 patients (60.5%) who had completed staging operation through only one surgery, while Group B consisted of 156 cases (39.5%) who had completed that through a second-time surgery. The frozen section submission rate of staging operation in the two groups were 99.2% (237/239) and 35.3% (55/156), respectively. Meanwhile, the coincidence rates of frozen and paraffin sections in the two groups were 98.3% (233/237) and 70.9% (39/55). The submission rate and coincidence rate of intraoperative frozen sections in Group A were higher than those in Group B (the submission rate: X2= 199.983, P&lt; 0.05; the coincidence rate: X2= 52.541, P &lt; 0.05). Conclusions: Our results confirm that increasing the submission rate of intraoperative frozen section and improving the accuracy of frozen section attach great importance to the diagnosis and treatment of EOC. Once identified, timely and comprehensive staging surgery can help improve patient outcomes for those who do not take fertility preservation into consideration.[Table: see text]

Embryological Aspects and Anatomical Variations of the Inferior Vena Cava – Its Importance in Gynecologic Oncology Surgery

Summary Surgical procedures of the retroperitoneum are often performed in gynecologic oncology surgery clinics. The most complex among them is paraaortic lymphadenectomy. It is generally performed in cases of bulky lymph nodes in ovarian carcinomas and sarcomas to achieve optimal cytoreduction. In the early stages of ovarian cancer, type II non-endometrioid endometrial cancer, and in advanced stages of cervical cancer, paraaortic lymphadenectomy is an integral part of staging. Moreover, the retroperitoneum is approached in cases of retroperitoneal gynecologic sarcomas. The largest vessels of the human body – the inferior vena cava and the abdominal aorta are localized in the retroperitoneum. Therefore, iatrogenic vessel injury during oncogynecological surgery is more likely to affect the inferior vena cava. Anatomical variations of the vein additionally increase the risk of vascular lesions. Therefore, surgeons should be aware of possible anatomical variations. The present article aimed to highlight the heterogeneity of anatomical variations of the inferior vena cava related to gynecologic oncology surgery. Embryogenesis of the vein and its variations are also discussed. Additionally, some anomalies of the ureter, associated with the embryogenesis of the inferior vena cava, are mentioned.

Extracellular vesicle-based biomarker assay for the detection of early-stage ovarian cancer.

5542 Background: Detection of cancer with improved discrimination compared to current blood tests could be achieved using an approach that assesses extracellular vesicles (EVs). This approach should have high sensitivity (se) because of EVs abundance in blood and high specificity (sp) by assaying EVs with multiple cancer-related protein and glycosylation epitopes (PGEs) co-localized on their surfaces. We are developing a platform technology that detects multiple cancer-related PGEs co-localized on the same EV using immunoaffinity-capture and proximity-ligation qPCR. In this study, we compare the performance of this technology vs plasma CA125 for correctly categorizing early-stage high-grade serous ovarian cancer (HGSOC) vs healthy/benign ovarian tumors (OT). Methods: We evaluated our EV-based platform technology using 7 PGE combinations to discriminate HGSOC from benign adnexal masses. We first derived a prediction model on a retrospectively collected cohort of 42 HGSOC and 26 benign OT samples from 2 commercial vendors and 24 healthy controls (HC) using a machine-learning algorithm. We validated this model on an independent cohort [89 HGSOC: Stage I (17), II (35), III (37); 192 benign OT] from university-associated biobanks and 124 HC. We also assessed the assay’s performance in plasma from 87 women with off-target cancers and 42 women with inflammatory conditions from commercial vendors. For each sample, we also measured CA125 levels using a commercial ELISA. Results: The prediction model distinguishes HGSOC from benign and HC with an AUC of 0.965 (95% CI 0.93-0.99), with 89.9% (0.82-0.95) se at 98% sp. For stage I/II HGSOC, the model achieves an AUC of 0.942 (0.9-0.99), with 84.6% (0.72-0.93) se at 98% sp. By comparison, CA125 achieves an AUC of 0.875 (0.81-0.94) and 44.2% (0.3-0.59) se at 98% sp. Direct comparison of CA125 and our model shows a significant difference at 98% sp for both all and stage I/II HGSOC (McNemar p-val &lt; 0.001). When comparing HGSOC to HC, there is no significant difference between our model and CA125 (p-val = 1.0). There is a significant difference when comparing patients with all stage and stage I/II HGSOC to patients with benign OT (p-val &lt; 0.001). Our assay had 1 false positive and CA125 had 3 false positives out of 42 inflammatory cases. Conclusions: These preliminary data suggest our platform technology for detecting PGEs co-localized on individual EVs may detect all stages of HGSOC from plasma with high se at a very high sp. Our assay may improve on CA125 by distinguishing stage I/II HGSOC from benign OT and could have clinical utility for both early detection and surgical referral recommendation for benign and malignant OT. While the diverse cohorts in this study may present challenges in interpretation, the reproducibility in an independent cohort is encouraging and supports further investigation using cases and controls from well-defined cohort studies.