Nuevas tecnologías basadas en biomarcadores para oncología
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1 Nuevas tecnologías basadas en biomarcadores para oncología Simposio ASEBIO 14 de marzo 2013, PCB Jose Jimeno, MD, PhD Co-Founder / Vice Chairman Pangaea Biotech SL Barcelona, Spain
2 PANGAEA BIOTECH BUSINESS MODEL Discovery of predictive and prognostic signatures for customization of cancer therapy Technology & Products Breakthrough Cancer Research Unit In-house discovery & R+D of biomarkers Novel diagnostic product development (e.g. serum-based EGFR) New platform technology development (e.g. RNA extraction for FFPE tissue) Development of biomarker insights through pharma partnerships & service agreements Instituto Oncológico Dr Rosell (IOR) Patient care unit Medical Oncology Service for QuironDexeus University Hospital, Barcelona Thoracic surgery Molecular Pathology Instituto Diagnóstico Molecular (IDM) Directly support physicians in clinical decision-making Provision of diagnostic and molecular testing services Pharmaceutical clinical trial support Drug Discovery (& early preclinical development) Innovative targets based on in-house biomarker discoveries Strategic alliance with IQS to seek small molecules- TKIs Barcelona, Spain 2
3 OPERATIONAL DATA Pathological evaluations Genetic tests Patient visits Solid increase in laboratory activities year to year. Growth driven by increasing credibility in EU as innovators in the diagnostic space, and by large scale collaborations with global pharmas. Pangaea has conducted & completed a concordance study for Tarceva companion diagnostic. Pangaea underwent an official FDA audit with positive results (no findings, no issue of FDA Form Ourbiomarkerdiscoveryeffortsare partiallyfundedby: 750/LE1556 The Oncology Laboratory of Pangaea Biotech has been accredited by ENAC (Spanish Entity of Accreditation) for experimental procedures developed according to the International Standard ISO 15189:2007. Medical Laboratories. Particular requirements for quality and competence. GENOMA ESPAÑA For information on validity and scope, please visit: 3
4 INSIGHTS BEHIND PERSONALIZED MEDICINE Conceptually, response to therapy in advanced cancer patients leads to improved quality of life and survival. Resistance/failure to therapy in advanced cancer patients represents one of the most significant negative factors of health economics in oncology. Antiproliferative effects of any active anticancer compound is the result of an interaction with a given pathway. 4/18/2013 4
5 FOUNDATION OF PGX ANALYSES BASED ON NON-INVASIVE APPROACHES Substantial number of patients lack tumor tissue for immediate gene/molecular analysis. Time-dependent variations of tumor genotypic signatures are an important factor in interpretation of results. Real time gene information is key. Possibility to characterize gene molecular signatures at baseline and across therapies. Tools :e circulating DNA (serum/plasma) Cell free circulating tumor DNA (serum/plasma) Pleural Effusion Circulating Tumor Cells Sputum Other biological fluids 5
6 METHOD FOR THE DETECTION OF EGFR MUTATIONS IN BLOOD SAMPLES 6
7 METHODS: EGFR MUTATION TESTING IN CELL-FREE CIRCULATING DNA Blood Serum / plasma isolation and DNA purification PCR amplification with selective tumor cfdna enrichment Exon 19: deletion Exon 21: L858R F F E L R E A R WT L858R R MUT GeneScan TaqMan Mutated allele Mutated Wild type allele Wild type 7
8 SENSITIVITY & SPECIFICITY More than 500 paired tissue & serum samples analyzed for EGFR mutations Total del 19 L858R Sensitivity 60% 65% 55% Specificity >99% >99% >99% 8
9 LOD & SPIKING EXPERIMENTS Detection threshold for EGFR mutations in cfdna blood samples using PB technology: Exon 19: 1:1000(DNA input per PCR reaction: 10pg/microL) Exon 21(L858R): 1:2000(DNA input per PCR reaction: 2,5pg/microL) Exon 20(T790M): 1:5000(DNA input per PCR reaction: 5pg/microL) Spiking decreasing amounts of mutated DNA in the blood of healthy patients PB technology consistently detects: 2pgofmutatedDNA/microLofserumforexon19del;100%ofsensitivity 10 pg of mutated DNA/microL of serum for T790M; 100% of sensitivity 10 pg of mutated DNA/microL of serum for L858R; 100% of sensitivity 9
10 EGFR BLOOD ANALYSIS. PHASE III STUDY ERLOTINIB VS CT Tissue samples n=109 Exon19 + Exon21 + Serum samples n= Exon 19 Exon 21 Detected 33 (50%) 0 Not detected 33 (50%) 0 Detected 0 25 (60%) Not detected 0 18 (40%) No false positive detected (20 controls included) Rosell et al. ASCO
11 PHASE III TRIAL ERLOTINIB VS CT: PFS 11
12 PHASE III TRIAL ERLOTINIB VS CT: SURVIVAL DATA 12
13 IMPACT OF EGFR MUTATIONS IN BLOOD: SURVIVAL DATA 13
14 IMPACT OF EGFR MUTATIONS IN BLOOD: SURVIVAL DATA 14
15 EGFR IN CFDNA: FOLLOW UP 20 NSCLC EGFR mutated in tissue with metastatic disease and treated with TK inhibitors 9 pts positive in serum/plasma at baseline: In 6 pts there is an increase of detection, anticipating the onset of PD. (2 with T790 as well) In 3 pts that are ongoing (non-progressive) the mutation is still not detectable. 11 pts negative in serum/plasma at baseline: In 8 pts (treatment ongoing) the mutation is still not detectable In 3 pts the mutation was detected, anticipating the onset of PD (2 with T790 as well) 15
16 EGFR BLOOD MUTATION ANALYSIS AS FOLLOW-UP Relative mutant DNA blood 38 year old male, never smoker, large-cell carcinoma harboring EGFR exon 19 deletion ( ELREA) with multiple metastasis including lung. Exitus 18/07/
17 EGFR BLOOD MUTATION ANALYSIS AS FOLLOW-UP 17
18 CONSIDERATIONS Customized anti-cancer intervention based upon gene/molecular signatures will be dominant in the near future. Our model and approach to discover predictive & prognostic biomarkers are proven valid. Lack of tumor tissue and/or evolutionary cancer cell adaption must be considered. Consideration of minimally invasive techniques are a must in the context of pharmacogenomic testing. Pangaea has implemented a solid platform for EGFR &mutation analysis in blood, both at baseline and follow-up. Our EGFR blood mutation analysis model represents a paradigm of non-invasive PGX analysis applicable to a well-defined population. This approach permits the follow-up of patient outcomes to anticipate the onset of clinical events. A positive impact in health economics and in the context of anticancer therapeutic intervention may result from the use of this PGX model. 18
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