Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Advances in Colorectal Cancer Biomarker Discovery Stan Hamilton, MD Head, Pathology and Laboratory Medicine Major Uses of Biomarkers • • • • • • • • Risk assessment Exposure Assessment Screening Surveillance Diagnosis Prognosis Prediction Monitoring Five Types of Biomarker Studies • Exploratory (correlative) studies using clinically annotated biospecimens and research assays • “Retrospective-prospective” studies using clinically annotated biospecimens, known clinical outcomes, and analytically validated assays Modified from Dr. Richard Schilsky Five Types of Biomarker Studies • Prospective biomarker/drug co-development studies • Prospective biomarker development studies • Prospective biomarker validation studies Modified from Dr. Richard Schilsky Current studies and trials • • • • • • Prognostic and predictive markers Assays for markers and targets Subpopulation, niche, enrichment trials Rare tumors Discovery, test, validation studies Both level of evidence (Level I from prospective marker-directed trials) and weight of evidence Integral vs. Integrated Biomarker Studies • Integral studies: Tests must be performed in order for the trial to proceed, i.e. tests are essential to the trial (includes markerdirected trials with CLIA compliance). Modified from Dr. Richard Schilsky Integral marker trials • Diverse solid-tumor types • Logistics for tumor tissue and control specimens • Biomarker assay resources • Regulatory compliance with Clinical Laboratory Improvement Amendments of 1988 (CLIA-88) • Turnaround time for risk assessment and therapy assignment 7 Integral vs. Integrated Biomarker Studies • Integrated studies: Studies that are intended to identify and validate assays or marker tests that might be used in future trials, but the assay results are not used to make decisions in the current trial. Modified from Dr. Richard Schilsky Correlative Biomarker Studies • Correlative studies: Studies to develop biomarkers/assays or imaging tests that are performed retrospectively, are exploratory in nature, and do not meet the criteria of being an integral or integrated study Modified from Dr. Richard Schilsky Key Issues in Clinical Biomarker Development • Define intended clinical use • Prospectively study the population and specimens for the intended use • Use an analytically validated biomarker test • Hypothesis and sample size must be adequate to demonstrate improved clinical outcomes when the biomarker test is applied. From Dr. Richard Schilsky Clinical Trial Study Designs • If we are confident that the therapy will not work in marker-negative patients AND • We have a validated assay that can reliably assess the status of the marker THEN • We might design and conduct clinical trials only in marker-positive patients Modified from Dr. Richard Schilsky Prospective Marker Validation Studies The most informative design Marker+ Marker− Randomization Randomization Targeted Therapy Standard Therapy Targeted Therapy Standard Therapy E5202 trial schema High-Risk Patients 18q LOH are Stratify: RANDOMIZED Disease stage IIA or IIB Microsatellite instability (stable/low vs high) 18q LOH Low-Risk Patients MSS/MSI-L with retention of 18q alleles or MSI-H are OBSERVED MSI-L = low-level microsatellite instability MSI-H = high-level microsatellite instability *Bevacizumab continued for an additional 6 months Arm A: mFOLFOX6 q2w × 12 Arm B: mFOLFOX6 + bevacizumab* q2w × 12 Arm C: Observation only TAILORx NODE NEGATIVE BREAST CANCER STUDY ER/PR + tumors ONCOTYPE DX ASSAY Score < 11 29% of pts Score 11-25 44% of pts Score >25 27% of pts R Endocrine Therapy Endocrine + Chemotherapy Chemotherapy + Endocrine Therapy Accrual goal= 4800 randomized patients, 11000 screened Non inferiority = decrease in 5 year DFS from 90 to 87% or less (Slide courtesy of Dr. Richard Schilsky) Obstacles to Biomarker Research • Adequacy of biospecimen acquisition, processing and storage • Access to CLIA-certified labs • Funding for biomarker studies • Regulatory requirements • Contractual agreements with commercial partners Modified from Dr. Richard Schilsky Advantages of Centralized Core Labs • Standardization for trials – Sample collection, processing, and assays • Expertise of trained personnel • Availability of state-of-the-art technologies 19 Advantages of Centralized Core Labs • Assay development, validation, consultation, and interpretation • Quality and reliability • Cost-effectiveness • Uniform access to non-renewable specimens for investigators 20 Integral Biomarker Specimen Flow – E5202 Fax results – avg 4 working days 5 working days Surgery 6 0 d a y s m a x Site registers patient, ships 2 blocks (1 tumor, 1 normal) PCO-RL* Laboratory QC and Processing ECOG Rando MDACC* tests for 18qLOH, MSI Fax results – avg 4 working days Site registers patient to Treatment *CAP-certified lab for CLIA-88 compliance 21 Advantages of Decentralized Labs • “Real-world” • Access • Convenience 22 Biomarkers in CRC: Recent Advances • Complexity of microRNA alterations in the adenoma-adenocarcinoma sequence • Gene expression profiling for prognosis in Stage II colon cancer • Markers for EGFR antibody therapy • Heterogeneity 23 • miRNA – Cell differentiation – Cell cycle progression – Apoptosis – Regulation of gene expression • Over 100 miRNAs implicated in colorectal cancer He L. et al. (2004) Nat Rev Genet: 522–531 Mucosa-Adenoma-Adenocarcinoma Sequence NNM ALG AHG CA p < 0.001 Red: p< 0.01 Grey: p< 0.05 Black: p> 0.05 Significant Pairwise Comparisons for 230 miRS hsa-miR-224 hsa-miR-877* hsa-miR-1 hsa-miR-632 hsa-miR-130a NM: Non-neoplastic mucosa ALG: Adenoma with lowgrade dysplasia AHG: Adenoma with highgrade dysplasia CA: Adenocarcinoma Example of Group 1A: Early Persistent Example of Group 2B: Late Conclusions • Large number of miRNAs deregulated in progression from non-neoplastic mucosa to adenoma to adenocarcinoma • Complex patterns of dysregulation dependent on the phase in progression • Dysregulation often an early event • Use of miRNAs as biomarkers or as therapeutic targets or agents dependent upon the timing of altered expression. Biomarkers in CRC: Recent Advances • Complexity of microRNA alterations in the adenoma-adenocarcinoma sequence • Gene expression profiling for prognosis in Stage II colon cancer • Markers for EGFR antibody therapy • Heterogeneity 30 The 12-Gene Oncotype DX® Colon Cancer Recurrence Score® 7 CANCER RELATED GENES Cell Cycle Stromal Ki-67 C-MYC MYBL2 FAP BGN INHBA GADD45B 5 REFERENCE GENES ATP5E PGK1 GPX1 UBB VDAC2 QUASAR Results: Colon Cancer Recurrence Score® Predicts Recurrence Following Surgery Prospectively-Defined Primary Analysis in Stage II Colon Cancer (n=711) Risk of Recurrence at 3 years 35% 30% 25% 20% 15% 10% p=0.004 5% | | ||||| | | | ||||||||||||| ||||||||||||||| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ||||||||||||||||||||||||||||| |||||||||||| || | || ||||||| | | | |||||| | 0% 0 10 20 30 40 50 60 70 Recurrence Score Kerr et al., ASCO 2009, #4000 QUASAR Results: Recurrence Risk in Pre-specified Recurrence Risk Groups 1.0 Low Intermediate High Range of RS Proportion of patients <30 43.7% 30-40 30.7% ≥41 25.6% Comparison of High vs. Low Recurrence Risk Groups using Cox Model: HR = 1.47 (p=0.046) 0.8 Proportion Event Free Recurrence Risk Group 0.6 0.4 Recurrence Risk Group 0.2 Low 12% ( 9% -16%) Intermediate 18% 22% (13%-24%) High 0.0 0 n=711 1 Kaplan-Meier Estimates (95% CI) of Recurrence Risk at 3 years 2 (16%-29%) 3 4 5 Years Kerr et al., ASCO 2009, #4000 Biomarkers in CRC: Recent Advances • Complexity of microRNA alterations in the adenoma-adenocarcinoma sequence • Gene expression profiling for prognosis in Stage II colon cancer • Markers for EGFR antibody therapy • Heterogeneity 34 JNCI 101:1310, 2009 PLoS One 4: e7287, 2009 PLoS ONE 4: e7287, 2009 Biomarkers in CRC: Recent Advances • Complexity of microRNA alterations in the adenoma-adenocarcinoma sequence • Gene expression profiling for prognosis in Stage II colon cancer • Markers for EGFR antibody therapy • Heterogeneity 38 PROJECT T9 Delivering on the promise of personalized molecular medicine PROJECT T9 Two-stage analysis Sequenom screen Dynamic Orthologous confirmation Sanger Sequencing Any activating mutations in >5% in any major tumor lineage PI3K/AKT MEK Pathway Pathway Receptors Downstream Effectors EGFR CDK4 AKT1, 2, 3 BRAF FGFR1,2,3 CTNNB1 PIK3CA HRAS KIT FBXW7 PHLPP2 KRAS VEGF JAK2 FRAP (mTOR) MEK1,2 PDGFRA RET RICTOR NRAS GNAQ FLT3 PDPK1 RAF1 ERa IDH1,2 PIK3R1 PRKAG1/2 MET Dear1 MC1R ALK TNK2(ACK1) ABCB1 Heterogeneity of Biomarkers • Intra-tumoral • Primary cf. synchronous metastasis • Multiple metastases • Primary cf. metachronous recurrence • Recurrence cf. recurrence after chemotherapy 41 Heterogeneity of Biomarkers • Co-mutation heterogeneity: The rule, not the exception • Discordance varies with genes • Primary cf. synchronous liver metastasis – KRAS: 30%, most acquired – NRAS: 100%, 75% acquired and 25% lost 42 Opportunities for future progress • Ability to complete the various types of biomarker studies including validation trials to contribute to personalized cancer care • Large numbers of patients required Opportunities for future progress • Funding - Patient accrual (cf. industry trials) - Effort of faculty for salary support - Marker studies Sources Phasing with protocol development Opportunities for future progress • Complexity and duration of protocol review process • Regulatory issues • Informatics • Markers to be valued and addressed like drugs • “A bad marker is as harmful as a bad drug.”