Liquid Biopsies for Improving the Pre-operative Diagnosis of Ovarian Cancer
NCT ID: NCT04971421
Last Updated: 2021-07-21
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
450 participants
OBSERVATIONAL
2021-04-14
2024-10-01
Brief Summary
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Therefore, a diagnostic algorithm will be developed using ct-DNA and TEPs as liquid biomarkers in combination with the existing ultrasound models (RMI and IOTA-models) and tumor markers (CA125 and HE4) to differentiate between early ovarian cancer and benign ovarian tumors pre-operatively.
Nature and extent of the burden and risks associated with participation, benefit and group relatedness. There is no extra burden/risk for the patients in this study. Five extra vials of blood will be collected from each participant and two questionnaires will be filled out.
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Detailed Description
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The current preoperative possibilities to distinguish benign and malignant ovarian tumors are based on classification systems containing clinical, biochemical and ultrasound characteristics. For example, predictive ultrasound models developed by the IOTA (International Ovarian Tumor Analysis) consortium have been widely used. However, these models require training and expertise and are therefore not always easy to implement. The predictive value of current serum-biomarkers such as CA-125 is limited because this biomarker is not increased in 50% of early stage ovarian carcinoma and CA-125 may also have increased in benign gynecological conditions such as endometriosis.
Current Dutch guidelines make use of the Risk of Malignancy Index (RMI) to determine whether the risk of ovarian carcinoma is increased. This score is based on the concentration of CA125, specific ultrasound characteristics and menopausal status.
According to Dutch guidelines, patients with ovarian tumor are referred to oncology centers if the RMI is increased (\>200). The published sensitivity and specificity of RMI in a non-selected population of patients with ovarian tumors is 72% and 92%, respectively. However, the population treated in the oncology centers is enriched with patients with RMI \>200. In this selected population, our own prelimenary data show that the sensitivity is 84% for RMI and the specificity is only 51%. This means that the incidence of malignancy within this population is 40%. This is unacceptably low because this implies that half of the patients with benign tumors referred to oncology centers undergo unnecessarily extensive surgery and these patients become unnecessarily emotionally burdened with the possibility of getting cancer.
Tissue biopsies are an important tool in the treatment of ovarian carcinoma because theses procedures can confirm or rule out the presence of a malignancy preoperative. At an early stage, however, tissue biopsy is considered as an unwanted invasive procedure, as this procedure can cause tumor spreading and has an invasive character for patients.
In short, despite the development of numerous prediction models, accurate preoperative diagnosis of early stage ovarian carcinoma is a challenge. There is an urgent need to develop prediction models with a high degree of accuracy that are easy to implement in the clinic to maximize the number of malignant tumors treated in oncology centers.
Blood-based biopsies, 'liquid' biopsies, as an alternative to traditional tissue biopsies, are emerging as these biopsies can provide accurate and comprehensive information on tumors. Examples of such include circulating tumor DNA (ctDNA) circulating tumor cells (CTC) and tumor-educated platelets (TEPs). These platelets are normally responsible for hemostasis, but appear to be able to include tumor signals found in the presence of mirco-tumor RNA. By using whole genome sequencing and detecting structural DNA and RNA changes in the ctDNA and TEPs, malignancies can be detected or excluded. These DNA changes were firstly demonstrated by coincidence when using the NIPT (non-invasive pregnancy test), which, in addition to assessing possible errors in fetal DNA, is also able to detect abnormalities in maternal DNA; in asymptomatic pregnant women, DNA changes were found in maternal DNA accounting for the presence of a malignancy.
Research shows that within patients with early stage ovarian carcinoma (st I and II), ctDNA analysis showed a sensitivity of 69% and a specificity of \>99%. The amount of ctDNA correlates with the tumor burden. Other studies conducted within small patient populations show that when ctDNA is combined with existing tumor markers, CA-125 for example, sensitivity and specificity both increase. From prelimanery data on TEP-analysis performed in the NKI-AvL a sensitivity of 76% and specificity of 98% for high-grade ovarian carcinoma was found and a sensitivity of 81% and specificity of 80% for low-grade carcinoma was found.
Therefore, this study investigates the clinical value of longitudinal assessment of liquid biopsy-derived information for preoperative diagnosis in patients suspected of early ovarian cancer
Conditions
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Study Design
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CASE_CONTROL
PROSPECTIVE
Study Groups
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Benign ovarian tumors
All histological proven benign ovarian tumors
ctDNA - circulating tumor DNA
lcWGS and WGS of circulating tumor DNA
TEP - Tumor Educated Platelets
sequencing miRNA from TEPs
Malignant ovarian tumors
All histological proven malignant ovarian tumors
ctDNA - circulating tumor DNA
lcWGS and WGS of circulating tumor DNA
TEP - Tumor Educated Platelets
sequencing miRNA from TEPs
Borderline ovarian tumors
All histological proven borderline ovarian tumors
ctDNA - circulating tumor DNA
lcWGS and WGS of circulating tumor DNA
TEP - Tumor Educated Platelets
sequencing miRNA from TEPs
Interventions
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ctDNA - circulating tumor DNA
lcWGS and WGS of circulating tumor DNA
TEP - Tumor Educated Platelets
sequencing miRNA from TEPs
Eligibility Criteria
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Inclusion Criteria
2. Presence of a ovarian tumor and referred to specialized center for surgery based on:
1. Any ultrasound model e.g. RMI-scoring model ; IOTA-rules
2. Subjective assessment of the referring gynecologist
3. Normal Glomerular Filtration Rate (GFR): \>60ml/min/1,73m2
3. General criteria: a. Understanding of Dutch language b. Fit for surgery (WHO 1-2) c. Written informed consent
Exclusion Criteria
2. History of cancer (excl. BCC) within 5 years prior to inclusion
3. Multiple malignancies at the same time
18 Years
FEMALE
Yes
Sponsors
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Leiden University Medical Center
OTHER
Catharina Ziekenhuis Eindhoven
OTHER
Amsterdam UMC, location VUmc
OTHER
Delft Technical University
UNKNOWN
Johns Hopkins University
OTHER
Amphia Hospital
OTHER
Reinier de Graaf Groep
OTHER
Haga Hospital
OTHER
Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
OTHER
The Netherlands Cancer Institute
OTHER
Responsible Party
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Principal Investigators
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C.A.R. Lok MD, PhD
Role: PRINCIPAL_INVESTIGATOR
Dutch Cancer Institute
C.D. de Kroon
Role: PRINCIPAL_INVESTIGATOR
Leiden University Medical Center / Gynecology
J.M.J. Piek
Role: PRINCIPAL_INVESTIGATOR
Catharina Ziekenhuis Eindhoven / Gy-necology
Locations
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Dutch Cancer Institute NKI-AVL
Amsterdam, , Netherlands
Amsterdam UMC loc VUmc
Amsterdam-Zuidoost, , Netherlands
Catharina hospital Eindhoven
Eindhoven, , Netherlands
Leiden University Medical Center
Leiden, , Netherlands
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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NL75690.031.20
Identifier Type: -
Identifier Source: org_study_id
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