REVERT - taRgeted thErapy for adVanced colorEctal canceR paTients

This is a clinical prospective, no-Profit, Interventional, Premarket Medical Device "early phase", multicentre, single-arm study, based on collecting data on predictive biomarkers of mCRC patients, integrate them with the results of the retrospective evaluation of outcomes and profiles of historical mCRC patients previously treated in the Oncology Units, in order to evaluate the efficacy of the best administered treatment. Results from the retrospective evaluation, will serve to build an AI-based profile capable to identify "good" or "poor" responders to therapy and to support the clinician towards the best treatment option. AI is a software based on algorithm defined as Medical Device Class IIa.

This is a clinical prospective, no-Profit, Interventional, Premarket Medical Device "early phase", multicentre, single-arm study, based on collecting data on predictive biomarkers of mCRC patients, integrate them with the results of the retrospective evaluation of outcomes and profiles of historical mCRC patients previously treated in the Oncology Units, in order to evaluate the efficacy of the best administered treatment. Results from the retrospective evaluation, will serve to build an AI-based profile capable to identify "good" or "poor" responders to therapy and to support the clinician towards the best treatment option. Following the first disease progression (PD), 2nd line therapy will be at Investigator's choice. The drugs under investigation are those commonly employed in mCRC patients as per usual standard of care. Artificial Intelligence (AI) is a software based on algorithm defined as Medical Device Class IIa.

The REVERT clinical trial is study, inserted within a wider European Project. The clinical study will take advantage of the results of the retrospective evaluation of mCRC patients' outcomes and profiles, aimed at evaluate the efficacy of treatment strategies, that will performed during the early activities of the European Project. In such retrospective analysis AI and Machine Learning (ML) will be instructed and used to derive predictive clinical data, after having analysed all possible variables including known mutational, biochemical and clinical features of samples from mCRC patients historically treated in the Oncology Units participating to the project and stored in partner Biobanks. AI and ML methodologies are based on Support Vector Machines and combine Multiple Kernel Learning and Random Optimization, incorporating already available large databases with new, potential prognostic/predictive biomarkers (e.g., gene mutations, epigenetic changes, gene expression profiling signatures). The emerging results will be used to help the choice of the best combinatorial therapy, for every prospectively enrolled mCRC patient. Sex and gender differences, also according to sidedness, will be analysed to evaluate their impact on survival and quality of life (QoL) in patients with mCRC.

Study length is planned to be about 24 months (12 months recruitment + 12 months of follow-up). The end of study is defined as the time when all enrolled patients will have experienced evidence of disease progression or will be out of treatment as per protocol, toxicity, medical decision or patient's withdrawal.

Eligibility Criteria:
Inclusion Criteria:

1. Signed and dated Informed Consent.
2. Age ≥ 18 years at time of Informed Consent.
3. Histologically- or cytologically-confirmed mCRC.
4. Assessed tumour EGFR pathway mutational status (K-RAS, N-RAS), BRAF, HER-2 neu, MSI.
5. Sufficient amount of representative tumour specimen (primary or metastatic, archival or newly obtained for confirmatory central laboratory testing of BRAF and KRAS mutational status.
6. Dihydropyrimidine dehydrogenase (DPD) before 5-FU infusion.
7. Eligibility to receive bevacizumab, cetuximab or panitumumab per locally approved label with regard to tumour RAS status.
8. Recurrence of disease after primary radical surgery and adjuvant therapy carried out \> 6 months prior the present trial.
9. Evidence of measurable or evaluable non-measurable disease as per RECIST, v1.1
10. ECOG PS of 0 or 1.
11. Adequate bone marrow function characterized by the following at screening:

    1. Absolute neutrophil count (ANC) ≥ 1.5 × 10\^9/L;
    2. Platelets ≥ 100 × 10\^9/L;
    3. Haemoglobin ≥ 9.0 g/dL.
12. Adequate renal function characterized by serum creatinine ≤ 1.5 × upper limit of normal (ULN), or creatinine clearance ≥ 50 mL/min.
13. Adequate hepatic function characterized by the following:

    1. Serum total bilirubin ≤ 1.5 × ULN and \< 2 mg/dL;
    2. Alanine aminotransferase (ALT) and/or aspartate aminotransferase (AST) ≤ 2.5 × ULN, or ≤ 5 ×ULN in presence of liver metastases.
14. Female patients are either postmenopausal for at least 1 year, surgically sterile for at least 6 weeks, or must agree to take appropriate precautions to avoid pregnancy.
15. Males must agree to take appropriate precautions to avoid fathering a child from screening through follow-up.

Exclusion Criteria:

1. Prior hypersensitivity or toxicity to chemotherapy drugs suggesting an inability to tolerate the proposed treatment.
2. Patients should not be candidate for upfront resection of metastatic disease.
3. Symptomatic brain metastasis.
4. Leptomeningeal disease.
5. Known history of acute or chronic pancreatitis.
6. History of chronic inflammatory bowel disease or Crohn's disease requiring medical intervention (immunomodulatory or immunosuppressive medications or surgery).
7. Impaired cardiovascular function or clinically significant cardiovascular diseases.
8. Uncontrolled hypertension defined as persistent elevation of systolic blood pressure ≥ 150 mmHg or diastolic blood pressure ≥ 100 mmHg despite current therapy.
9. Impaired hepatic function, defined as Child-Pugh class B or C.
10. Concurrent or previous other malignancy.
11. History of thromboembolic or cerebrovascular events ≤ 6 months prior to starting study treatment.
12. Concurrent neuromuscular disorder associated with elevated CK (e.g., inflammatory myopathies, muscular dystrophy, amyotrophic lateral sclerosis, spinal muscular atrophy).
13. Known contraindication to receive antineoplastic treatment at the planned doses.
14. Other severe, acute or chronic medical or psychiatric condition or laboratory abnormality that may increase the risk associated with study participation or study drug administration or that may interfere with the interpretation of study results and, in the judgment of the Investigator, would make the patient an inappropriate candidate for the study.
15. Pregnancy, confirmed by a positive human chorionic gonadotropin (hCG) laboratory test result, or lactating.
16. Participation to other clinical trial studies.