Analysis of Prognostic and Predictive Genomic Signatures Using Archival Paraffin-embedded Tumor Specimens in Breast Cancer
Recruitment status was Active, not recruiting
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 Design:||Observational Model: Cohort
Time Perspective: Retrospective
|Study Start Date:||September 2010|
|Estimated Primary Completion Date:||August 2012 (Final data collection date for primary outcome measure)|
|Breast cancer patients|
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.
|National University Hospital|
|Principal Investigator:||Soo Chin Lee, MBBS, MRCP||National University Hospital, Singapore|