The study involves the use of reagents or materials for diagnostic assessments that are not commercially available, specifically a metabolomic signature for screening endometrial carcinoma and/or other types of cancers, and follows a case-control design.

This study aims to achieve several objectives that contribute to evaluating the diagnostic potential of a specific "metabolomic signature" to be used for screening endometrial carcinoma. Specifically, the study seeks to assess the signature's discriminative ability in differentiating between benign endometrial neoplasms and neoplasms of different histological origins.

The study is structured into several phases, described below:

• Recruitment and data collection of patients selected for model training at IRCCS Pascale The study will be conducted on patients attending the IRCCS G. Pascale according to normal clinical practice. The patient's participation in the study will begin with the collection of their data and biological samples and will end with the follow-up visit.
• Recruitment and data collection of patients selected for the validation of the trained models at Diagnostica Medica.

This phase of the study will be conducted on patients who will attend the laboratories of the company "Dott.ri Armando and Pierpaolo Cavallo - Diagnostica Medica" according to standard diagnostic and healthcare practices. Specifically, patients who undergo the required checks within the normal diagnostic and healthcare pathway through laboratory medicine, and who meet the enrollment criteria, will be invited to participate in the study.

• Collection of biological samples from enrolled patients In the event of the patient's actual enrollment in the study, blood samples necessary for the study will be collected.
• Analysis of Biological Samples The analysis will consist of both a bioanalytical and a bioinformatic phase. The bioanalytical phase will involve the extraction of the metabolome from DBS (Dried Blood Spots) using a mixture of solvents optimized to extract both polar and apolar metabolites, as well as those with acidic, basic, and neutral properties. This will be followed by a purification phase of the extracted metabolites using liquid-phase partitioning and a post-lyophilization derivatization phase to enhance chromatographic separation. The definition of the metabolomic profile will be carried out using mass spectrometry techniques with a single quadrupole coupled with gas chromatography (GCMS) and high-resolution mass spectrometry techniques (UPLC-Q-Orbitrap).
• Measurement Methods for Results The results of the experiment will be evaluated in terms of sensitivity (defined as the ability to correctly identify affected subjects), specificity (defined as the ability to correctly identify subjects not affected by endometrial carcinoma), positive and negative predictive value (defined respectively as the probability of a subject being correctly classified as affected or not affected), and overall accuracy (defined as the total number of diagnostic errors made by the test). Preliminary evaluations of the diagnostic effectiveness of the metabolomic signature, measured by cross-validation estimates of classification models, showed sensitivity ranging from 93-100%, specificity ranging from 92-98%, and overall accuracy between 95-100%.

The study is expected to last a total of 2 years. All collected data will be integrated and analyzed using mathematical and statistical tools, both descriptive and multivariate.

Inclusion Criteria:

1. Female sex
2. Age between 50 and 80 years
3. Willingness to participate in the study and signing of the informed consent
4. Clinical condition of post-menopause

Exclusion Criteria:

1. Previous hysterectomy
2. Hormone replacement therapy
3. Immunosuppressive therapy

The project involves the recruitment of separate cohorts of subjects for the development phase of the metabolomic signature:

1. Women with endometrial carcinoma (n=50);
2. A corresponding cohort of healthy subjects to be used as controls (n=50);
3. Women with other non-oncological uterine conditions and oncological conditions affecting other organs (n=200);
4. An additional cohort will be recruited to validate the trained models (n=2800). This cohort will consist of postmenopausal women, aged between 50 and 80 years.