Evolution of Translational Omics Lessons Learned and the Path Forward (2012) / Chapter Skim
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Appendix A: Case Studies
Appendix A: Case Studies
Pages 183-238
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The development of HER2 as an effect modifier biomarker has transformed breast cancer treatment by identifying the 20-30 percent of patients with overexpression of the HER2 oncogene who are likely to benefit from therapy targeting HER2 (De et 183
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. HER2 Testing in Clinical Practice In 2007, a panel established by the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP)
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. A prospective randomized trial (National Surgical Adjuvant Breast and Bowel Project [NSABP]
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, the test has not been submitted to FDA for clearance or approval; however, Genomic Health indicated that the company benefited from prior interaction with FDA and the extensive background material FDA provides on its website about assay validation.1 Two ongoing prospective studies (the TAILORx and RxPONDER trials, see section below on Clinical Utility) direct patient management on the basis of Oncotype DX Recurrence Score.
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and computational model for determining the Recurrence Score. Five steps were used to develop the final gene list and Recurrence Score computational model.
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measured and reported the reproducibility within and between blocks in the clinical validation study. Statistical and Bioinformatics Validation The computational procedures used to determine the Recurrence Score are published, and there is public information that provides an overview of how the computational model was generated (see Discovery Phase)
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. Genomic Health was blinded to the clinical outcome data until the RT-PCR data were locked and transferred to NSABP.5 Clinical/Biological Validation Archival tissue from breast cancer patients in three studies was used to clinically validate the prognostic value of Oncotype DX (Table A-2)
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Study design Prospective– Retrospective; Retrospective with retrospective matched case control case inclusion criteria Cases = patients who died from breast cancer Controls = breast cancer patients individually matched to cases alive at the date of death of their matched case Patient Lymph-node-negative; Lymph-node-negative; Lymph-node-negative; characteristics ER+ ER +/– ER +/– Treatment Tamoxifen; no +/–Tamoxifen; no No systemic therapy chemotherapy chemotherapy Sample # 668 220 cases, 570 149 controls Blinding Yes Yes Yes Independence Different specimens Different specimens Different specimens than used in discovery than used in discovery than used in discovery NSABP control of Kaiser Permanente MD Anderson control clinical outcome data control of clinical of clinical outcome outcome data data
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with low-risk death in ER+, distant recurrence-free RSs compared to tamoxifen-treated and survival in ER+/– high-risk RSs; RS tamoxifen-untreated patients with no provided significant patients (p = 0.003 adjuvant systemic predictive power and p = 0.03, therapy independent of age respectively) and tumor size; RS was predictive of overall survival NOTE: ER = estrogen receptor, NSABP = National Surgical Adjuvant Breast and Bowel Project, RS = Recurrence Score.
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Women with a low Recurrence Score received hormonal therapy alone while women with a high Recurrence Score received hormonal therapy and chemotherapy. Women with Recurrence Scores in the mid-range risk group were randomized to receive either chemotherapy plus hormonal therapy or hormonal therapy alone.
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trial found that the Recurrence Score was an independent predictor of distant recurrence in women with node-negative and node-positive, hormonereceptor-positive patients treated with anastrozole (Arimidex) , an aromatase inhibitor (Dowsett et al., 2010)
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The computational model for Oncotype DX was published, but several aspects of test development are not specified in detail in the published literature, including how the 250-gene list was selected during test discovery and how the archival tissue from three clinical studies was used in test training and development of the computational model. Gene expression and clinical data from the discovery phase are not publicly available.
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. Discovery Phase The 70-gene signature was developed using archival samples of primary invasive breast tissue from 78 breast cancer patients (34 patients developed distant metastases within 5 years, 44 patients were disease-free after 5 years)
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. Investigators reanalyzed RNA from 162 patient samples from the discovery and clinical validation (described in the next section)
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.13 Clinical/Biological Validation Table A-3 lists the clinical validation studies that have been performed to assess MammaPrint. The first validation, published as part of the discovery phase paper, assessed 19 patient samples.
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Study Does 70-gene Does 70-gene Does MammaPrint have question(s) expression signature signature confirm prognostic value in a show comparable results from group of independent performance to previous validation patients, beyond clinical development study in lymph- risk classifications?
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(2006) Blinding Not stated Rosetta Data centralized at the Inpharmatics TRANSBIG Secretariat; carried out 100% concordance microarray analysis; between risk classification all raw data were by Agendia and Swiss available to all Institute of Bioinformatics; investigators statistical analysis carried out by IDDI Independence Different specimens Included 61 samples Different specimens than than used in from discovery used in discovery discovery phase Involvement of the Swiss Not conducted by a Not conducted by a Institute of Bioinformatics, separate group separate group TRANSBIG Secretariat, IDDI, and independent auditors Results Disease outcome Estimated HR for Distant metastasis: was predicted by distant metastases Unadjusted HR = 2.32 gene signature in 17 in poor vs.
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. A third validation study (Buyse et al., 2006)
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will provide higher quality evidence to assess the benefit of chemotherapy because data will be collected prospectively within a large, randomized clinical trial population. Clinical Utility The European Organisation for Research and Treatment of Cancer, with partial support from Agendia, is conducting a large multicenter, prospective randomized trial to compare MammaPrint with common clinicopathological criteria (using Adjuvant!
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Number Summary 02/06/2007 K062694 Original clearance for MammaPrint test • ingle laboratory S • resh frozen tissue F • atients less than 61 years old P • ncludes laboratory procedures, software, and I computational procedures Modifications 06/22/2007 K070675 • hanged specimen type to fresh tissue stored in C specific RNA preservative • hange in software version C 07/21/2008 K080252 • ddition of a second scanner A • eplacement of low-density microarray with R high-density microarray 12/11/2009 K081092 • odified intended use by adding 5-year prognostic M information for breast cancer patients 61 years and older 01/28/2011 K101454 • dded 2 scanners, 2 bioanalyzers, and a new A laboratory for MammaPrint testing SOURCE: FDA, 2011a. survival and disease-free survival (Clinicaltrials.gov, 2011b)
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provided a clinical validation with patients who had not participated in the discovery and validation studies, and confirmed MammaPrint as a prognostic test. However, the hazard ratios between the poor and good prognosis groups reported in Buyse et al.
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Pathwork Diagnostics consulted with FDA on several occasions, including a pre-IDE meeting at which FDA determined that an IDE was not required because the proposed study design involved an analysis of archived samples.17 Discovery Phase Published information on gene discovery and computational model development for the Tissue of Origin test is limited. The Tissue of Origin test for frozen and FFPE specimens include the same 15 tumor types, but they use different computational procedures and processing methods (Pillai et al., 2011)
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. In comparison, the optimal procedures for frozen tissue specimens included 1,550 genes in the computational model (FDA, 2008b)
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.19 Clinical/Biological Validation Table A-5 lists the clinical validation studies for the Tissue of Origin test. The clinical validation for the Tissue of Origin test for frozen samples was a blinded, multicenter study that found overall sensitivity of 87.8 percent and specificity of 99.4 percent (Monzon et al., 2009)
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207 APPENDIX A TABLE A-5 Clinical/Biological Validation Studies for the Tissue of Origin Test Study Monzon et al., 2009 Pillai et al., 2011 Tissue 2 academic, 3 commercial 7 tissue banks source(s) biospecimen banks; electronic microarray files for 271 tumors obtained from the International Genomics Consortium Specimen Frozen Formalin-fixed paraffin-embedded preparation (FFPE)
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. The intended use statement in the FDA clearance decision summary specifies that the Tissue of Origin test "measure[s]
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Pathwork initially offered its Tissue of Origin test for FFPE as an LDT through its CLIA-certified laboratory, but in 2010 received FDA clearance for this version of the test. Clinical validation studies blinded Pathwork to reference diagnoses, specified that the test was locked down, and involved tissue specimens from a number of biospecimen banks.
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. According to Vermillion, this biomarker panel was further refined in a series of studies encompassing more than 2,000 subjects, but detailed information describing the discovery and development process that led to the panel of 5 biomarkers comprising the OVA1 computational model have not been made available in the peer-reviewed literature.22 Test Validation Phase Analytical Validation The investigators determined that reproducibility on the mass spectrometry platform was not adequate for routine clinical use (Fung, 2010)
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The computational procedures are proprietary.23 Clinical/Biological Validation The clinical validation study was a prospective, double-blind study involving 27 subject enrollment sites (Miller et al., 2011; Ueland et al., 2011)
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The American College of Obstetricians and Gynecologists and Society of Gynecologic Oncologists (SGO) issued a committee opinion in March 2011 that OVA1 "appears to improve the predictability of ovarian cancer in women with pelvic masses" but noted that the clinical utility of this test has not been established (ACOG and SGO, 2011)
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Emanuel Petricoin and Lance Liotta, investigators from FDA and NCI, collaborated with researchers at the bioinformatics company Correlogic to develop a proteomics-based approach for ovarian cancer screening using serum samples. Investigators used data from mass spectrometry analysis of serum proteins to develop a computational model for identifying spectral patterns that could discriminate between healthy patients and those with ovarian cancer, and published their findings in the Lancet (Petricoin et al., 2002)
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The cases and most of the controls were obtained as frozen samples from the National Ovarian Cancer Early Detection Program (NOCEDP) ; 17 additional controls were obtained at the Simone Protective Cancer Institute (SPCI)
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. Independent investigators began looking into mass spectrometry profiling of serum samples for ovarian cancer because of its clinical importance, interest of the scientific community, and potential progression into clinical use (Baggerly et al., 2004a,b, 2005a,b; Sorace and Zhan, 2003)
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also demonstrated that use of a simpler statistical analysis may have illuminated deficiencies in experimental design at an early stage of research. This case study demonstrates the benefits of making data publicly available to allow for independent assessment of the data and computational model.
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A subset of biopsies were graded by three independent pathologists blinded to the clinical information before selecting samples for test discovery, computational model development, and test validation. A custom microarray representing 7,370 genes was used for the discovery phase of test development.
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Samples used in the primary clinical validation study did not overlap with samples used in the discovery phase. The secondary clinical validation reused all 63 patient samples from the primary validation as well as some samples that had been used in the discovery phase (Figure A-1)
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In the primary clinical validation study, samples from 63 patients were blinded 30 Personal communication, Mitch Nelles, XDx, October 12, 2011.
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population? Study design Prospective Prospective Prospective Prospective Not marker Not marker Not marker Not marker directed directed directed directed ≥ 1 year Patient Time Time > 55 days characteristics posttransplant posttransplant posttransplant, posttransplant not stated not stated > 30 days post rejection treatment Sample 63 samples; 184 samples; 281 samples; 300 samples; number 63 patients 124 patients 166 patients 154 patients Blinding Yes Yes Yes Yes Independence Different All specimens Different Different specimens than used in specimens than specimens than used in primary clinical used in used in discovery discovery validation plus discovery some Development Development specimens used Development involved XDx involved XDx in discovery involved XDx and transplant and transplant and transplant cardiologists cardiologists Development cardiologists directing directing involved XDx directing CARGO CARGOa and transplant CARGO cardiologists directing CARGO
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The secondary clinical validation study was performed to confirm the results in a larger sample set of CARGO patients. This clinical validation study evaluated 184 samples from 124 patients, which included the 63 samples used in the primary clinical validation study as well as samples that were used in the discovery phase of development (see Figure A-1)
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developed from the full dataset was 0.67 (95% CI 0.56-0.78) Clinical Utility Monitoring Risk of Future ACR In a prospective evaluation of 104 CARGO patients who were at least 30 days past a heart transplantation and whose blood samples had not been used to develop the AlloMap computational model, results suggested that the gene expression score used to determine rejection at the time of testing may determine the likelihood of ACR in the subsequent 12 weeks (Mehra et al., 2007, 2008)
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. However, the Blue Cross Blue Shield Association Technology Evaluation Center decided in September 2011 that AlloMap did not meet its utility criteria as a method to monitor cardiac allograft rejection because the clinical validation studies were small and the cut points defining a positive test had not been independently validated (BCBSA, in press)
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was developed as a less invasive method than angiography to identify obstructive coronary artery disease (CAD) .35 Corus CAD is a blood test that measures the expression level of 23 genes to get a score on a scale of 1 to 40.
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A second microarray analysis to further define genes that could be a hallmark of CAD, and all subsequent work to develop Corus CAD, was performed in the prospective clinical trial PREDICT (Personalized Risk Evaluation and Diagnosis in the Coronary Tree)
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. PCR data used in the development and validation sets are not publicly available, although Cardio Dx has indicated they would be available upon request by qualified investigators.39 Analysis of the RT-PCR results from the validation study was performed at Scripps Translational Science Institute.40 Blood samples from 640 patients were used to develop the computational model (Elashoff et al., 2011)
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Approximately 13,000 tests were ordered between October 2010 and September 2011.41 Corus CAD is a very newly developed test, which may account for why it has not been incorporated into any guidelines. Multiple insurance plans currently pay for the test on a patient-by-patient basis.42 As noted on the CardioDx website, "CardioDx is actively pursuing third-party payer reimbursement for Corus CAD." Case Highlights This study highlights the importance of publishing detailed information regarding derivation of the computational model used for the diagnostic test.
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2010. Human epidermal growth factor receptor 2 assessment in a case-control study: Comparison of fluorescence in situ hybridization and quantitative reverse transcription polymerase chain reaction performed by central laboratories.
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Gene expression profiling as a noninvasive method to monitor for cardiac allograft rejection. Technology Evaluation Center.
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510(k) Substantial Equivalence Determination Decision Summary Assay and Instrument Combination Template (k073482)
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2004. Treatment of lymph-node-negative, oestrogen-receptor-positive breast cancer: Long-term findings from National Surgical Adjuvant Breast and Bowel Project randomised clinical trials.
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2010. P2-09-06: Meta-Analysis of the Decision Impact of the 21-Gene Breast Cancer Recurrence Score in Clinical Practice.
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2008. Clinical implications and longitudinal alteration of peripheral blood transcriptional signals indicative of future cardiac allograft rejection.
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2002. Real-world performance of HER2 testing -- National Surgical Adjuvant Breast and Bowel Project experience.
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2010. Multicenter validation of the diagnostic accuracy of a blood-based gene expression test for assessing obstructive coronary artery disease in nondiabetic patients.
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: A prospective multi-center, double blind study assessing a whole blood gene expression test for the detection of obstructive coronary artery disease In symptomatic patients referred for myocardial perfusion imag ing. Abstract presented at American Heart Association Meeting, November 15, 2011.
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2007b. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer.
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