- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT01247480
Analysis of Prognostic and Predictive Genomic Signatures Using Archival Paraffin-embedded Tumor Specimens in Breast Cancer
Major Aims of study:
- To create a gene expression-based prognostic device that complements or exceeds the prognostic utility of conventional biomarkers of breast cancer outcome.
- To identify one or more clinical subgroups of patients for which the prognostic device outperforms, or substantially adds to, the prognostic performance of conventional markers that currently determine therapeutic strategies.
Sub-Aims of study:
- Assess the prognostic value of the multiple gene expression signatures, alone and in combination, using a large cohort of breast cancer patients for which pathology, treatment and outcome is available. A "training" and "testing" design is proposed.
- Evaluate the utility of a prognostic device that measures gene expression levels from formalin-fixed paraffin-embedded specimens (FFPEs) of primary resected tumors. The investigators will utilize the Affymetrix Quantigene 2.0 Assay and/or the Illumina BeadXpress VeraCode DASL Gene Expression Assay (FDA-approved IVDMIA.)
- For specific clinical subgroups of patients/tumors, the investigators will mathematically identify additive or synergistic prognostic relationships between genes and gene signatures that, in combination, will yield maximal risk prediction (distant metastases-free survival) for patients.
- Compare the prognostic utility of the investigators device to that of the conventional prognostic variables that are currently used to determine therapeutic strategy.
- Incorporate the prognostic signatures into a practical prognosis algorithm that seeks to include conventional measures of outcome such as tumor size, histologic grade, nodal status, patient age, or Nottingham index, etc.
The investigators hypothesize that adequate quality and quantity of tumor RNA may be extracted from archival paraffin-embedded tumor specimens for gene expression profiling, and that archival tumor-derived genomic signatures may be used as prognosticators or predictors in breast cancer.
Study Overview
Status
Conditions
Detailed Description
800 breast cancer patients who fulfill the eligibiltiy criteria will be selected from the NUH breast cancer registry (400 for training, 400 for validation). Eligible patients should have at least 5 years' follow-up at NUH and have an available archival paraffin-embedded tumor block stored at the Department of Pathology, NUH. 8-10 ten-micron sections from each tumor block will be cut and RNA extracted from the sections. RNA will then be profiled using high-throughput gene expression platforms (Illumina Veracode assay, Affymetrix Quantigene assay). Raw gene expression data will be applied in the following signatures previously generated by the Genome Institute of Singapore:
- 32-gene p53 Pathway Signature
- 5-gene Genetic Grade Signature
- 33-gene TuM1 Signature
- 10-gene ER Signature (Miller & Tan, et. al., unpublished)
- 6-gene 3-Ratio Predictor (Miller & Karuturi, et. al., unpublished)
- 5-gene HER2 Amplicon Predictor (Miller & Karuturi, et. al., unpublished)
- 7-gene Basal-Luminal Discriminator (Miller, unpublished)
The prognostic and/or predictive abilities of these signatures will be compared with conventional clinical prognosticators and predictors with the goal of developing archival tumor-derived genomic tests for breast cancer management in the future.
The archival paraffin-embedded tumor blocks are left-over samples after clinical use. They are not samples that have been consented for research purpose. We are requesting for waiver of consent as this is a minimal risk study. We will ensure that sufficient tissue be left behind for future routine diagnostic purposes. Sections taken from each tumor will be coded with no patient identifiers to protect the privacy and confidentiality of the participants.
The results generated from the tumor samples in this study will not impact on the clinical management of the patients.
Study Type
Contacts and Locations
Study Locations
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Singapore, Singapore
- National University Hospital
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- Eligible patients should have at least 5 years' follow-up at NUH and have an available archival paraffin-embedded tumor block stored at the Department of Pathology, NUH
Exclusion Criteria:
- Non breast cancer patients
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
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Breast cancer patients
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Collaborators and Investigators
Investigators
- Principal Investigator: Soo Chin Lee, MBBS, MRCP, National University Hospital, Singapore
Publications and helpful links
General Publications
- Slodkowska EA, Ross JS. MammaPrint 70-gene signature: another milestone in personalized medical care for breast cancer patients. Expert Rev Mol Diagn. 2009 Jul;9(5):417-22. doi: 10.1586/erm.09.32.
- Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F, Talantov D, Timmermans M, Meijer-van Gelder ME, Yu J, Jatkoe T, Berns EM, Atkins D, Foekens JA. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet. 2005 Feb 19-25;365(9460):671-9. doi: 10.1016/S0140-6736(05)17947-1.
Study record dates
Study Major Dates
Study Start
Primary Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Estimate)
Study Record Updates
Last Update Posted (Estimate)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- BR05/22/10
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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