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Early Detection of Clinically Significant Cancer – Are We There Yet? Christos Patriotis, PhD Cancer Biomarkers Research Group Division of Cancer Prevention, NCI Early Detection Can Help Reduce Mortality from Cancer Mortality rates from cancers where screening tools are available are considerably lower than from cancers for which no viable screening tools exist (e.g., colon, breast, lung) Better risk assessment and early detection of cancer when treatment is effective can help reduce mortality Addressing the issue of over-diagnosis can further improve overall survival by reducing unnecessary morbidity from overtreatment Early Detection Research Network EDRN EDRN is a national infrastructure supported by NCI to help move promising biomarkers for early cancer detection and risk assessment from the laboratory bench to clinical validation Mission and Goals • Discover, develop and validate biomarkers for cancer risk assessment and the early detection of clinically significant cancer (molecular diagnosis and prognosis) • Conduct correlative studies and trials to validate biomarkers as indicators of early, pre-invasive cancer or cancer risk • Develop quality assurance programs for biomarker testing and evaluation • Forge public-private partnerships EDRN and Biomarker Research EDRN established in 2000 Focused solely on early detection biomarker research Provides guidelines on reference samples, study designs and validation Unparalleled, fully operational, open-access network Strong scientific collaborations, e.g., Associate Membership Program for translational research Biomarker Development Pipeline EDRN Investigator-Driven Consortium Assay Development (Phase II & III) Discovery (Phase I & II) U24 (RFA-CA-09-019) U01 (RFA-CA-09-017) U01 (RFA-CA09-018) Validation (Phase II & III) U24 (RFA-CA-09-020) Building Teams via Collaborative Groups EDRN Defines Phases of Biomarker Development EDRN Source: Pepe et. al., J. Natl. Cancer Inst. 93, 1054-1061, 2001 Vertical Integration of Biomarker Discovery, Development and Validation Discovery (BDLs and others) Candidate Biomarker Identified (BDLs, CVCs, BRLs) NO Development (BDLs, CVCs, BRLs) YES NO Re-evaluate biomarker for utility as a predictive, prognostic or target marker NO Pre-validation (BDLs, CVCs, BRLs, DMCC) Validation (BDLs, CVCs, BRLs, DMCC) YES Re-evaluate biomarker use in clinical setting NO Cost Effective? YES Milestones Study design and sample selection to ensure that candidate biomarker clinically useful Robust and reproducible assay Protocol for sample collection is fully established and valid for cross-laboratory validation Biomarker distinguishes cases from controls with statistical validity Cost-effectiveness Biomarker is reproducible across a wide spectrum of cases and controls collected prospectively from retrospective cohorts of samples – e.g. such samples may come from recently concluded trials that have appropriate case and control groups Phase IV: Biomarker is further tested and refined in asymptomatic population and found to be effective (i.e., reducing incidence or mortality of disease) – beyond the scope of EDRN Utilization of biomarker in clinical care setting Foundational Studies on Phases and Study Design for Biomarker Development Phases of Biomarker Discovery and Validation Preclinical Exploratory PHASE 1 Promising directions identified Clinical Assay and Validation PHASE 2 Clinical assay detects established disease Retrospective Longitudinal PHASE 3 Biomarker detects preclinical disease and a “screen positive” rule defined Prospective Screening PHASE 4 Extent and characteristics of disease detected by the test and the false referral rate are identified Cancer Control PHASE 5 Impact of screening on reducing burden of disease on population is quantified PRoBE Study Design: Prospective-specimen collection, Retrospective Blinded Evaluation RESOURCES: Sample Reference Samples Clinical validation studies are expensive Only few biomarkers may succeed There is a need for a triage system that allows “Go or No-Go” decision EDRN has developed a mechanism through which biomarkers are first tested in Standard Reference Samples constructed for a specific intended clinical use If initial evaluation is successful, then a large, multi-center validation study is planned Reference Samples are sets of cases and controls collected based on PRoBE principles and statistically powered to allow rapid assessment of technologies and biomarkers discovered through a wide variety of technology platforms. First-ever concept originated and implemented within EDRN for rapid evaluation of technologies and biomarkers Breast Standard Reference Set Clinical Application: • An assembled set of well-characterized and annotated specimens for testing biomarkers which, in conjunction with mammography, can detect and discriminate breast cancer from benign conditions. Prospective (pre-diagnostic; PRoBE) collection of samples for early detection of BC: • • Samples and specified Common Data Elements (CDEs) are collected from eligible individuals referred to diagnostic radiology after mammography (and/or another imaging modality, e.g., US), but prior to surgery and diagnosis Samples collected at mammography screening clinic and confirmed as cases or controls following referral, biopsy, and pathology report Reference Set: serum and plasma in 200 ul aliquots: • • • • • 207 Incident ICA 55 DCIS/LCIS 63 Benign pathology with atypia (ADH) 231 Benign pathology without atypia 276 Healthy controls (no evidence of breast disease by screening mammography (BI-RADS 1 or 2) EDRN Reference Sets • Lung Cancer (3) • Prostate Cancer • Liver Cancer (2) • Colon Cancer • Pancreatic Cancer • Bladder Cancer Request EDRN Standard Reference Set 1. Obtain application form from EDRN public portal (http://edrn.nci.nih.gov/resources/sample-reference-sets) and prepare proposal as per provided requirements. 2. Submit application to NCI Program Officer for evaluation and for review of preliminary biomarker performance data by DMCC. 3. Approval Decision: • • • Not approved - denied; Additional information required; and/or Approved 4. Notify approved investigator • • • NCI prepares MTA to be executed with receiving institution DMCC creates pull-list, shipment list and ensures set is blinded NCI-Frederick ships out reference set 5. Investigator conducts assays (4 months) and deposits data with DMCC. 6. DMCC provides sample ID to investigator. After 3 months data is posted on secure EDRN website. After 12 months data is posted on EDRN public portal (unless peer-reviewed publication is imminent). Common Data Elements Common Data Elements provide a set of standard terms and values for a given domain • • • • They are classified into organ, epidemiological, and specimen CDEs Critical to coordinating and managing a multi-center biomarker validation study EDRN CDE Ontology necessary for integrating all data warehouses, study management systems, and informatics tools into one harmonized knowledge environment Based on ISO/IEC 11179 (standard for data elements) Captured by EDRN and maintained by the EDRN DMCC and IC (FHCRC/JPL) EDRN Knowledge Environment Access to science data sets Access to biomarker data and results Access to specimen information Access to study data http://cancer.gov/edrn (operational) http://edrn.jpl.nasa.gov (beta; emerging capabilities) Validation Study Management VSIMS: Online study management system supporting all EDRN validation studies. Built upon the EDRN CDE repository and using reusable modules to speed development for new studies. eSIS: System in development to track the progress of all EDRN-funded projects, including timelines, GANTT charts, phases of development, current study status. How Do We Choose Winners Or Losers Among Markers? Clinical Performance Characteristics Improved Benefits – Unmet Clinical Needs Cost-Effectiveness Is the Biomarker’s Performance Reproducible on an Independent Sample Set? Examples • TSP1, Kallikreins 2,3,5,11, and EPCA-2 were “no go” for further validation after they failed on blinded testing using the EDRN prostate cancer reference set (AUC for TSP1 and EPCA-2 dropped from >0.95, in preliminary studies, to <0.55 on the reference set). • In contrast, Percent[-2]proPSA held its performance (AUC=0.69) on the same reference set. It’s performance was also validated by a subsequent Phase II study on a separate cohort of samples from an appropriately recruited population. An IVD is currently under review by FDA. Does the Biomarker have Clinical Value? Example DCP in preliminary data indicated better sensitivity and specificity than that of AFP, the conventional clinical biomarker for HCC. A large, blinded validation study indicated that although overall, DCP does not perform better than AFP, it has a better sensitivity and specificity in detecting HCC with viral etiology Impact: Biology of non-viral and virus-induced cirrhosis is different; DCP is a better marker than AFP for early detection of virus-induced liver cancer Importance of Failures “As in real life, we often learn more from negative results than we do from positive ones. It is time that we, as a community, start to regard failures as being as informative as successes. After all, we do know the difficulty of learning from positive only experience.” EDRN •Accelerator – to drive good markers through to the clinic •Brake – to use good clinical design to eliminate markers without added value EDRN in the News… Scientific Organization of Phase II/Phase III OC Biomarker Validation Study OC Biomarker Validation Study Lessons Learned While many of the biomarkers can distinguish between cases and controls in specimens obtained at diagnosis (Phase II), the vast majority of them failed in distinguishing cancer from healthy control-associated specimens when the samples were obtained more than 6 months prior to clinical diagnosis (Phase III) OC Biomarker Validation Study Lessons Learned (continued) This outcome emphasizes the importance of using appropriate specimens for biomarker research - from early discovery stages to clinical validation. Bias introduced by systematic differences in the case and control specimens must be maximally avoided by adapting the principles of PRoBE study design Better understanding of the natural history of the disease and the discovery of biomarkers in lesions, which most likely represent the precursors of aggressively growing disease can help identify more reliable biomarkers EDRN in the News… Therefore, reports from studies funded by the Early Detection Research Network (EDRN) using prospectively diagnosed ovarian cancer data from the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) screening trial have been eagerly awaited. The authors of the 2 reports in this issue of the journal are to be commended for having designed and conducted scientifically solid phase 3 studies, which were nested in a large, randomized screening trial and will serve as the standard against which future analyses of this kind should be judged (14, 15). Major EDRN Accomplishments Detection/ Biomarker Assay Discovery Blood Refine/ Clinical Adapt for Clin Use Validation Clinical Translation FDA IVD pending review FDA IVD pending review proPSA Urine PCA3 Urine/TMA assay for T2S:Erg fusion for Prostate Cancer CLIA in process FISH for T2S:Erg fusion for Prostate Cancer In CLIA Lab Aptamer-based markers for Lung Cancer In CLIA Lab Proteomic Panel for Lung Cancer In CLIA Lab OVA1TM for Ovarian Cancer FDA Approved SOPs for Blood (Serum, Plasma), Urine, Stool, N/A Vimentin Methylation Marker for Colon Cancer In CLIA Lab ROMA Algorithm for CA125 and HE4 Tests for Pelvic Mass Malignancies FDA Approved Blood/DCP and AFP-L3 for Hepatocellular Carcinoma FDA Approved Together with AFP-L3 used for monitoring cirrhotic patients for HCC in China Blood GP73 Frequently used by biomarker research community Over-Diagnosis: Consequence of Screening and Early Detection Screened and “cured” Death unrelated to cancer Cancer Never screened Sources of Cancer Over-diagnosis 1. The pathologist: diagnostic uncertainty 2. Underlying tumor biology B. Kramer, 9/15/2011 Cancer Progression – A Heterogeneous Process Size Size at which cancer causes death Size at which cancer causes symptoms Fast Slow This is over-Dx. Very Slow Non-progressive Abnormal cell Time Death from other causes B. Kramer, 9/15/2011 Patterns of Rapid Increase in Cancer Incidence: True Increase vs. Overdiagnosis Indicators of Increased True Occurrence of Cancer vs. Overdiagnosis New Diagnoses Number of new cancer diagnoses and deaths Deaths Time Suggests a true increase in the amount of cancer New Diagnoses Number of new cancer diagnoses and deaths Deaths Time Suggests overdiagnosis of cancer B. Kramer, 9/15/2011 Incidence and Mortality of Five Cancers: (Surveillance, Epidemiology, and End Results: SEER) 6 New Diagnoses 4 Prostate Cancer Rate 8 Thyroid Cancer 2 (per 100,000 people) Rate (per 100,000 people) 10 Deaths 0 1975 1980 1985 1990 1995 2000 2005 Year Melanoma New Diagnoses Rate 15 10 5 Deaths 0 1975 1980 1985 1990 1995 2000 2005 Year (per 100,000 people) Rate (per 100,000 people) 20 225 200 175 New Diagnoses 150 125 100 75 Deaths 50 25 0 1975 1980 1985 1990 1995 2000 2005 Year 175 Breast Cancer 150 125 New Diagnoses 100 75 50 Deaths 25 0 1975 1980 1985 1990 1995 2000 2005 Year Rate (per 100,000 people) Kidney Cancer 12 10 8 6 4 New Diagnoses Deaths 2 0 1975 1980 1985 1990 1995 2000 2005 Year Source: HG Welch, JNCI 2010 Female Breast Cancer Incidence Trends in Connecticut by Stage and 5-Year Time Periods of Diagnosis 200 Total Rate per 100,000 Women-Years 100 Localized Regional In-situ Distant 10 1 0.1 1940 1960 Year 1980 2000 WF Anderson, Breast Cancer Res Treat 2006 Strategies to Investigate Overdiagnosis & Underdiagnosis Annotate collected specimens with method of diagnosis • Molecular patterns of screen-detected cases are enriched with overdiagnosed cases • Molecular patterns of true interval cases are enriched with aggressive cases that we need to prevent (and target pathways for prevention) Collect normal organ as well as the tumor • Study cancer at tissue-level, not simply as a cell-based disease • Examples: prostate, breast, esophageal, melanoma B. Kramer, 9/15/2011 Address Overdiagnosis & Underdiagnosis • Identify and develop prognostic biomarkers for early detection to complement screening modalities – Indeterminate pulmonary lesions on CT screening – PSA/biopsy-detected Prostate Cancer • Identify and develop biomarkers of risk of progression of precursor lesions to aggressive cancer – – – – Progression of Breast BBD with/without Atypia to IBC Progression of DCIS/LCIS to IBC IPMN cyst progression to Pancreatic Cancer Colon adenoma progression to CRC Address Overdiagnosis & Underdiagnosis (continued) • Develop and validate biomarkers for early detection of Interval cancers to complement screening modalities – Develop blood biomarkers for the early detection of TNBC, especially for women under the age of 50 and of African American descent. On positive test refer to more frequent screening imaging (mammography, MRI, or other newly developed molecular imaging) THANK YOU