Radiomics and Radiogenomics Models to Predict Molecular Integrated Risk Classes and Prognostic Factors in Endometrial Cancer.

Fondazione Policlinico Universitario Agostino Gemelli IRCCS1,000 enrolled

Overview

The aim is to develop radiogenomics models to stratify patients into three main risk categories (Favorable, Intermediate, and Unfavorable) according to the ProMisE model (9) and use these models to predict the most prognostically relevant EC histopathological features (i.e. FIGO stage, degree of tumor differentiation, histotype, LVSI status, myometrial and cervical invasion, lymph node metastases). These models would support clinicians in personalizing surgical and adjuvant treatment choice among the options considered by the international guidelines.

Study Type

INTERVENTIONAL

Allocation

Purpose

DIAGNOSTIC

Masking

NONE

Enrollment

1,000

Conditions

Endometrial Cancer

Interventions

trascriptomic profiling

The mutational and copy number analyses will be complemented by transcriptomic profiling. RNA will be extracted from FFPE samples using miRNAeasy FFPE kit (Qiagen) and checked for quality and quantify by 2100 Bioanalyzer instrument (Agilent) and Qubit Fluorometer (ThermoFisher), respectively. Transcriptome analyses will be performed by RNA-seq. We will apply total RNAseq using the Illumina® TruSeq Stranded Total RNA workflow that provides a solution allowing the detection of whole transcriptome, splicing variants, and transcript fusions of human RNA isolated from FFPE samples. Libraries will be run using the Illumina's Novaseq6000 system, with a least 50 millions of reads/sample, the minimum read depth for the correct evaluation of low expressed transcripts.

Eligibility

Sex: FEMALEMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * Pathologically confirmed diagnosis of primary endometrial cancer (endometrioid, clear cell, serous, mixed, any grade) * FIGO stage IA-IB * Formalin-fixed, paraffin-embedded (FFPE) tissue at the diagnosis available - Availability of preoperative MRI scans in dicom (.dcm) format * Availability of preoperative US images in dicom (.dcm) format * Availability of preoperative CT-scan images in dicom (.dcm) format (optional) * Available clinical information (e.g. baseline information, surgery, adjuvant therapy, median follow up period 24 months) Exclusion Criteria: * Metastatic cancer to the uterus (not primary EC) * Uterine sarcoma * Conservative surgery * FIGO stage \> II * Formalin-fixed, paraffin-embedded (FFPE) tissue at the diagnosis not available * Patients without available MRI, US or CT-scan images on digital media * Clinical information not available or incomplete * Any other malignancy in the previous 5 years or synchronous * Patients aged under 18 years

Outcomes

Primary Outcomes

Predictive value of the model

Receiver operating characteristic (ROC) curve and 95% confidence interval (CI) will be performed to determine cut-off values for the studied quantitative variables.

Time frame: up to one year

Secondary Outcomes

Validity of the model

To test the validity of different clinical and ultrasound variables Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) will be determined