Artificial Intelligence-based Platform, Integrating Pathologic, Imaging and Molecular Profiles of Prostate Cancer
NCT Number: NCT06468332
Acronym: PRISM-AI
Status: NOT_YET_RECRUITING
Study Type: OBSERVATIONAL
Conditions: Prostate Cancer
Sponsor: Azienda Ospedaliero Universitaria Maggiore della Carita
Sex: MALE
Age: ADULT, OLDER_ADULT
Enrollment: 400
Study Design: Observational Model: |Time Perspective: p
Start Date: 2024-07
Completion Date: 2030-12

Summary:
The goal of this observational study is to use an artificial intelligence-based platform, integrating clinical, pathologic, imaging, genomic and transcriptomic profiles of prostate cancer in order to outperform currently available risk-stratification tools. Thus could lead to a better risk assessment of prostate cancer progression and recurrence.

A key challenge in managing non-metastatic Prostate Cancer is identifying and distinguishing between men that are likely to progress to clinically significant disease and those whose disease is likely to remain indolent for the remainder of their lifetime, aiming to offer invasive treatment only to patients harboring a disease which would affect cancer specific survival.

In the context of a multidisciplinary team of urologists and digital health experts, a two-phases study has been designed. A retrospective cohort of 200 radical prostatectomy patients will be identified within three participating clinical centres. Clinical, pathology, MRI data will be collected and stored in an appropriate anonymised online platform. Whole exome sequences (DNAseq) will be analyzed for each patients (total samples=200) and transcriptome analyses (RNAseq) for both cancer and non-cancer tissues (total samples=400). In parallel, the recruitment of a prospective cohort of 200 biopsy-proven newly PCa patients will start. For these patients, blood and urine samples will be also collected. Data will be collected and genetic analyses (total samples=1,000) will be performed as in the retrospective phase. Patients will be treated and followed according to best clinical practice.

Expected Results The retrospective phase would allow to identify genes, pathological features and MRI imaging features that can correlate with PCa biology, in order to create and train the AI-based algorithm. The prospective phase will allow the validation of the prognostic tool, the definition of a novel risk grouping and the evaluation of the prognostic role of biofluid analysis.

Primary Outcome Measures: integration of pathologic, imaging, genomic and transcriptomic profiles of prostate cancer, Main outcome of preliminary phase is represented by the capability of the multiplex network to integrate several information in order to set up and build an artificial intelligence-based platform which is able to better define risk-stratification in prostate cancer. In this phase Formalin-fixed, paraffin-embedded tissue will be analyzed at molecular levels: genomic and trascriptomic information will be integrated with imaging and pathological information, 12 months|Validation of the artificial intelligence-based platform generated in the previous phase, in the prospective phase will be the validation of the prognostic tool, the definition of a novel risk grouping and the evaluation of the prognostic role of biofluid analysis., 3 years