Biomarkers for Diagnosis and Prognosis of Endometrial Carcinoma

Study Overview
=================
Brief Summary
-----------------
Endometrial cancer (EC) is the most frequent gynecological malignancy but there is currently lack of both non-invasive diagnostic tools and novel markers to stratify patients based on their risk of future recurrence. Patient care could be improved by advances in these two aspects. In the present study, the investigators aim to identify diagnostic serum metabolite and protein biomarker signatures for early detection of cancer in asymptomatic high-risk population and prognostic biomarkers for selection of patients with poor prognosis.

Detailed Description
-----------------
Rationale: Endometrial cancer (EC) is the most frequent gynaecological malignancy in the developed world. Optimal treatment of EC depends on early diagnostics and pre-operative stratification to appropriately select the extent of surgery and to plan further therapeutic approach. Currently, invasive endometrial histology is the gold standard for diagnosis, as there are no valid non-invasive methods available, and patient stratification is based on histopathology and surgical findings. There is a great need for efficient and reliable screening test for asymptomatic women with high risk of EC including Lynch syndrome patients and tamoxifen treated patients. In addition, a prognostic test is needed to stratify pre-operatively EC patients with high risk of progression in need of radical surgery together with adjuvant chemo/ratio therapy from EC patients with good prognosis. In this project the investigators are addressing this lack of non-invasive diagnostic and prognostic biomarkers of EC. Objective: the investigators aim to identify diagnostic serum metabolite and protein biomarker signatures for early detection of cancer in asymptomatic high-risk population and (secondary objective) prognostic biomarkers for selection of patients with poor prognosis.

Official Title
-----------------
Minimally and Non-invasive Methods for Early Detection and Progression of Endometrial Cancer

Conditions
-----------------
Endometrial Cancer

Intervention / Treatment
-----------------
* Other: Blood sampling


Participation Criteria
=================
Eligibility Criteria
-----------------
Inclusion Criteria Cases: endometrioid, serous, clear cell or mucinous endometrial cancer dedifferentiated endometrial cancer high grade or low grade endometrial cancer Inclusion Criteria Controls: benign uterine diseases, e.g. myoma uteri, prolapsed uterus prophylactic hysterectomy for Lynch syndrome Exclusion Criteria Cases: atypical hyperplasia other types of cancer sarcoma uteri previous diagnosis of endometrial cancer Exclusion Criteria Controls: any cancer benign ovarian diseases previous EC pregnancy at the time of enrollment

Ages Eligible for Study
-----------------
Minimum Age: 18 Years

Sexes Eligible for Study
-----------------
Female

Accepts Healthy Volunteers
-----------------
No

Study Plan
=================
How is the study designed?
-----------------

Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Cases<br>Women older than 18 years and diagnosed with endometrial cancer will be included. Blood sampling will be performed on all subjects and will be used for proteomics and metabolomics analyses. | Other: Blood sampling<br>* Blood sampling (10 mL) prior to standard care (e.g. surgery, medical treatment)<br>|
| controls<br>Women older than 18 years and with a benign endometrial disturbance will be included. Blood sampling will be performed on all subjects and will be used for proteomics and metabolomics analyses. | Other: Blood sampling<br>* Blood sampling (10 mL) prior to standard care (e.g. surgery, medical treatment)<br>|

What is the study measuring?
-----------------
Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Creation of a diagnostic algorithm | Blood metabolome and proteome will be analysed and bioinformatics/biostatistical analysis will be used to derive diagnostic algorithms based on blood metabolites, proteins and clinical data. Algorithms in the biomarker discovery study will be developed by comparing EC and patients with benign uterine pathologies. | 2020-2021 | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Creation of a prognostic algorithm | Blood metabolome and proteome will be analysed and bioinformatics/biostatistical analysis will be used to derive prognostic algorithms based on blood metabolites, proteins, clinical data at baseline and follow up information. Algorithms in the biomarker discovery study will be developed by comparing EC patients with low risk and high risk for cancer progression and recurrence. | 2021 | 

 Terms related to the study
=================
Keywords Provided by Centre Hospitalier Valida
-----------------
metabolomics, proteomics, early diagnosis, prognosis