Challenges of new discoveries of clinical applications into the management of cancer patients Tomáš Zima, Veronika Mikulová Institute of Clinical Biochemistry and Laboratory Diagnostics, General University Hospital and First Faculty of Medicine in Prague Czech Republic TUMOR MARKERS Tumor markers are defined as qualitative or quantitative alteration or deviation from normal of a molecule, substances, or process that can be detected by some type of assay above and beyond routine clinical and pathological evaluation. Tumor markers may be detected within malignant cells or surrounding stroma of a primary cancer, or in metastases in local (such as lymph nodes) or distant tissues, or either cellular-based or as soluble products in blood, secretions or excretions. Tumor markers have a very long research history ….. Discoveries of the best known tumor markers 1928 - Ascheim- Zondek hCG 1936 - Gutman PAP 1957 - Bjorklund TPA 1963 - Abelev AFP 1965 - Gold CEA 1979 - Koprowski CA 19-9 1979 - Wang PSA 1981 - Best CA 125 1983 - Kufe CA 15-3 ….. with many thousands of publications in the last four decades ….. DEMONSTRATION OF TUMOR-SPECIFIC ANTIGENS IN HUMAN COLONIC CARCINOMATA BY IMMUNOLOGICAL TOLERANCE AND ABSORPTION TECHNIQUES* BY PHIL GOLD,$ M.D., AND SAMUEL O. FREEDMAN, M.D. (From the McGill University Medical Clinic, Montreal General Hospital, and the Department of Physiology, McGill University, Montreal, Canada) PLATES 35 TO 39 (Received for publication, November 16, 1964) ONLY A HANDFUL HAVE MOVED INTO CLINICAL PRACTICE TO DATE HER-2 CA 15-3 and CA 27.29 multiparameter gene expression analysis CTC proteomic analysis Oncotype DX CEA ECD of HER-2 p53 IHC based markers of proliferation uPA and PAI-1 bone marraow ER and PgR micrometastases Cyclin E fragments Cathepsin D DNA flow cytometry-based parameters REQUIREMENTS ESSENTIAL FOR ACCEPTANCE OF A TUMOR MARKER ▫ determine utility of marker ▫ evaluate magnitude of effect ▫ analyze reliability of marker ▫ technical issues (assay) ▫ analytical issues ( cutoff points, test/validation sets, multivariate analysis) ▫ trial design issues (appropriate patient population) WHEN IS A TUMOR MARKER USEFUL (USE)? MAGNITUDE OF THE TUMOR MARKER PURE PROGNOSTIC PURE PREDICTIVE FACTOR FACTOR MIXED FACTOR PRECISION AND ACCURACY OF THE TUMOR MARKER • identifying a difference in outcomes for patients in two different states defined by marker results is insuffiecient to introduce in into the clinic • many investigators conclude that their marker of interest has clinical utility if in their study the difference in outcomes between marker „positive“ and marker „negative“ patients is less then p<0,05 THIS CONCLUSION MAY BE MISTAKEN TECHNICAL FACTORS AFFECTING MEASUREMENT OF TUMOR MARKERS • difficulties arise because of x poor sensitivity and/or specificity of the assay for the analyte x poorly reproducible assays x differences between assays that use different reagents for measurements of the same marker • primary technical considerations are critical: 1.which type of assay should be used 2.reproducibility of the chosen assay Pauletti, G. et al. J Clin Oncol; 18:3651-3664, 2000 Comparison between FISH and IHC in predicting OS Pauletti, G. et al. J Clin Oncol; 18:3651-3664, 2000 ANALYTICAL ISSUE CONSIDERATIONS • assay interpretation ▫ visual assays x intra- and interobserver variability x automated and semiautomated systems appear to be highly accurate and are likely to be more reproducible • cut-off point determination • cut-off point validation x initial evaluation should be performed using „test set“ of patients x the utility of the cut-off point should then be confirmed using a „validation set“ CIRCULATING TUMOR MARKERS proteins autoantibodies free somatic DNA miRNA CTC GermLine DNA susceptibility pharmacogenetics WHAT APPROACHES ARE AVAILABLE • single gene assays x somtatic mutations and other alterations (gene amplificatition) x germline alterations • multigene arrays and signitures x classification x prognostication x prediction of treatment benefit • next generation sequencing Single gene assay • germline BRCA1 mutations ▫ single gene with many different mutations ▫ dramatically increases risk of breast and ovarian cancer x predisposition to triple negative breast cancer x may impact response to treatment BRCA1 • BRCA1 mutation ▫ 80% risk of developing breast cancer ▫ increased risk of ovarian cancer © Copyright 2005, Department of Biology, Davidson College, Davidson, NC 28036 BRCA2 • BRCA2 mutation ▫ the later manifestation of breast cancer ▫ increased risk for digestive tract, prostate and melanoma cancer © RCSB Protein Data Bank Multigene arrays • combination of expressed and repressed genes within a tumor • information about: ▫ global state of the tumor, revealing information pertaining to cellular x metabolic rates, x proliferative status x molecular interactions between malignant epithelial cells and surrounding cells Molecular heterogeneity of breast cancer has prognostic implication Sorlie T., Proc. Natl. Acad Sci, 2001 Gene signatures Oncotype DX 21 Gene Recurrence Score assay Proliferation Estrogen Ki67 ER Category RS (0-100) STK15 PR Survivin Bcl2 LOW RISK RS < 18 Cyclin B1 SCUBE2 MYBL3 MODERATE RS 19 – 30 CD68 RISK Invasion Stromolysin 3 Reference HIGH RISK RS ≥31 Cathepsin L2 Beta-actin GAPDH GSTM1 HER2 RPLPO GRB7 GUS BAG2 HER2 TFRC RFS and OS among the 295 patients using four distinct gene signatures • each of the signatures used different gene sets with minimal overlap • the signatures showed significant agreement in the outcome predictions for individual patients and are probably tracking a common set of biologic phenotypes • implications: ▫ many genes track together ▫ a high proportion of the genes may have limited biologic significance and are probably not targetable Next generation sequencing (massively parallel sequencing) • technology ▫ has revolutionised our ability to characterize cancers at the genomic, transcriptomic and epigenetic levels ▫ is cataloguing all mutations, copy number aberrations and somatic rearrangements at base pair resolution ▫ can be used as a means for unbiased transcriptomic analysis of mRNAs, small RNAs and noncoding RNAs, genome-wide methylation assays and high-throughput chromatin immunoprecipitation assays Next generation sequencing - methods Next generation sequencing - methods Next generation sequencing - applications Crucial role of CTCs • in the metastatic cascade ▫ tumor cells must invade the basement membrane and surrounding tissue and enter the bloodstream or lymphatics • tumor dissemination ▫ changes in cell-to-cell adhesion and extracellular matrix (ECM) adhesion x switch in cadherin expression (E-cadherin, N-cadherin) ▫ degradation of the ECM x MMPs, uPA system (poor prognosis) • tumor progression ▫ epithelial-mesenchymal transition (EMT) ▫ process of „self-seeding“ Klaus Pantel & Ruud H. Brakenhoff Nature Reviews Cancer 4, 448-456 (June 2004) Factors affecting CTCs count Mego M:Nature Reviews Clinical Oncology 7, 693-701 (December 2010). EMT process • characterization of EMT ▫ epithelial cells: x lose cell-to-cell contacts x lose cell polarity x downregulate epithelial- associated genes x acquire mesenchymal- gene expression x undergo changes in their cytoskeleton acquire mesenchymal appearance with increased motility and invasiveness Iwatsuki, M: Cancer Science, 101: 293–299 (2010) EMT and CTCs • EMT must have a role in the generation of at least a fraction of CTCs • EMT associated markers on CTCs TWIST1, AKT2, PI3Kα • EMT has also been associated with the stem-cell phenotype and resistance to apoptotic signals • CTCs markers linked to cancer stem cells NOTCHI1 (gene associated with self-renewing) – more than 60% of CTCs ALDH1 – almost 70% of CTCs Mego M:Nature Reviews Clinical Oncology 7, 693-701 (December 2010). Why are we interested in CTC detection ? Gene expression profiling in cancer circulating cells (CTCs) in breast carcinoma patients - a tool for early metastasis detection and therapy individualisation. • Targets 1. Introducing gene expression testing of CTCc by the AdnaGen diagnostic system and implementing standard operating procedure (SOP) for the tests 2. Reducing the costs of the overall testing process by increasing the efficiency of gene expression testing by the new real-time PCR expression profiling system BIOMARK from Fluidigm Inc. (www.fluidigm.com) (one of only two instruments in Europe are available to us for this project) 3. Establishing disease classification methods including predictive scores based on the measurements of CTC oncomarkers using GenEx software in collaboration with MultiD. 4. Individualizing therapy based on the obtained information, thereby increasing the quality and efficiency of the treatment. Trial population – number of enrolled patients *419 tests have been done in total Study flowchart Circulating tumor cells testing Study results • Patients characteristic´s Total CTC-positive Total 197 Tumor size stadium 1 45 20 (22%) stadium 2 80 40 (44%) stadium 3 34 29 (39%) stadium 4 11 2 (12%) Nodal status node-negative 76 24 (31%) node-positive 111 39 (35%) Histology ductal 141 36 (25%) lobular 10 2 (20%) others 46 5 (10%) Study results • Patients characteristic´s Total CTC-positive Grading G1 15 9 (60%) G2 54 16 (30%) G3 84 27 (32%) unknown 45 --- ER status ER-negative 118 34 (29%) ER-positive 64 21 (33%) PR status PR-negative 96 24 (26%) PR-positive 83 27 (33%) HER-2 status HER2-positive 42 12 (29%) HER2-negative 134 37 (28%) Triple negative 44 14 (32%) Study results CTC positivity rate