1. Proteomic based fingerprint come biomarker predittivi e farmacodinamici: dall’idea al progetto AIDOC Maria Paola Costi UNIMORE MITO-Pisa 4-5 Novembre 2014

2. Premesse e principi I campioni di sangue possono contenere informazioni sullo condizione del tumore e su biomarker farmacodinamici. Un singolo biomarker non è sufficientemente affidabile/predittivo per descrivere una condizione del tumore. Un biomarker profile ingegnierizzato e validato può fornire un tool affidabile per valutare l’efficacia di un farmaco in campioni clinici minimamente invasivi.

3. Uno studio di proteomic fingerprint basato sulla spettrometria di massa (MS) permette l’identificazione di un biomarker farmacodinamico di efficacia del farmaco sulla base della modulazione dei livelli proteici indotti. Biomolecules level change in ovarian cancer cell lines induced by peptdies targeting thymidylate synthase networks. Protein based fingerprint per caratterizzare l’efficacia di un farmaco in fase pre-clinica su linee cellulari di tumore ovarico. F.Genovese, MPCosti et al J Proteome Research, 2014

4. Studio traslazionale del proteomic fingerprint su campioni di EOC da CT con pemetrexed in seconda linea (fase II). Biopsies received end 2013 Biopsies were evaluated by pathologist and selected Tissue biopsies with 70% cancer cell were selected for proteomics approach Traslational study In collaboration with the Mayo Clinic of Berlin Charitè (Prof.Jalid Sheouli, TOC-Eutroc) On 52 biopsies of clinical from phase II clinical study

5. Panel di 25 proteine selezionate secondo i tre criteri. Targeted Mass Spectrometry. Heatmap of western blot data in attesa dei dati di proteomica su 25 proteine

6. Dal lab scale al MISTO fingerprint con AIDOC

7. Proteine & Lipidi Fingerprint mista di biomolecole MISTO fingerprint. Trattazione statistica complessa multilivello che supera il problema dell’uso di piattaforme MS diverse (Molecular discovery company). Veristrat-like technology*, implementata con lipidi, biomolecule di natura diversa. Impelmenta il TCGA (The Cancer Genome Atlas) in cui biomolecole diverse vengono considerate in un unique profile. *VeriStrat, (commercially available by Biodesix, Boulder, CO, USA)

8. From clinic to omic readout through novel mass spectrometry technologies: development of biomolecules fingerprint (s) to predict early response to antiangiogenetic drugs in ovarian cancer patients. AID-OC

9. The AID-OC project is based on the development of a new diagnostic tool based on the MISTO fingerprint MISTO fingerprint includes proteins, (and autoantibodies) and lipids to be used as pharmacodynamic (PD) markers in OC patients at the earlier phase of the therapeutic protocol (a few weeks) with the antiangiogenic drug becavcizumab associated with chemotherapy. To reach the objective AID-OC project will apply proteomics and lipidomics studies on low invasive samples (serum) based on the MITO16 clinical trial in retrospective and then prospective studies. The innovative tool includes Mass spectrometry (MS), combined with an automatic integration of the multiple omic data translated in an easy read- out for friendly use by non-specialised personnel, achieved using technologies from different scientific fields.

10. Main objectives To overcome the limitations of approaches used so far to predict the pharmacological effectiveness of bevacizumab using an innovative technology Main goal is to help physicians in the early decision on the continuation/change of ovarian cancer (OC) patient’s therapy

11. Partnership

12. AID-OC technology to predict early the response to bevacizumab with chemotherapy in ovarian cancer patients MISTO technology design for mass spectrometr y detection Technology handling for non-specialised personnel in hospital daily practice. Interface software, data analyisis with Easy read out visualization Proteins&lipids & autoantibodies Identification/valid ation in retro/prospective CT using MS MISTO can select patients for continuation of the therapy. PERT

13. Workflow del progetto

14. Grazie per l’attenzione