Dataset Information

Biomarker discovery for colon cancer using a 761 gene RT-PCR assay.

ABSTRACT:

Background

Reverse transcription PCR (RT-PCR) is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE) clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco typeDX assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis) and the likelihood of tumor response to standard chemotherapy regimens (prediction). We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application.

Results

RNA was extracted from formalin fixed paraffin embedded (FPE) tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery.

Conclusion

We have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of genes analyzed while maintaining the high specificity, sensitivity and reproducibility that are characteristics of RT-PCR. Biomarkers discovered using this approach can be transferred to a clinical reference laboratory setting without having to re-validate the assay on a second technology platform.

SUBMITTER: Clark-Langone KM

PROVIDER: S-EPMC1994687 | biostudies-literature | 2007 Aug

REPOSITORIES: biostudies-literature

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Publications

Biomarker discovery for colon cancer using a 761 gene RT-PCR assay.

Clark-Langone Kim M KM Wu Jenny Y JY Sangli Chithra C Chen Angela A Snable James L JL Nguyen Anhthu A Hackett James R JR Baker Joffre J Yothers Greg G Kim Chungyeul C Cronin Maureen T MT

BMC genomics 20070815

<h4>Background</h4>Reverse transcription PCR (RT-PCR) is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE) clinical study tumor specimens. This technology has als ...[more]

PMID: 17697383

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Project description:The Oncotype Dx assay is frequently used to test if breast cancer patients can be spared from chemotherapy without negative effects for their future clinical course. However, due to conflicting data on the assay utility, in the recent past its reimbursement situation in Germany was revised; due to continued requests by clinicians for predictive values, our group decided to implement an Oncotype Dx like alternative assay with the objective of obtaining quality and cost optimization. Customized RT2-Profiler assays covering the 21 gene panel of the Oncotype Dx assay were applied to a pilot cohort of breast cancer patients with known Oncotype Dx Recurrence Score (RS). The Ct values obtained with RT2-Profiler-assays were used to calculate the unscaled Recurrence Score (RSu) values and the thereon based RS according to the Oncotype DX assay rules if available. Despite consistent assay performance it was impossible to establish correlations between RT2-Profiler recurrence scores with the respective Oncotype DX values not to mention exact matches. By following the Oncotype DX assay and its interpretation as close as possible we faced several obstructions such as lack of information on RNA amount used, missing units in the single gene expression report, missing references cited in the original study that should explain the determination of the recurrence score formula, and vague information on the normalization of the gene expression impeding the reproduction of Oncotype Dx results in other laboratories. Unfortunately, the Oncotype Dx assay cannot be confirmed by the customized RT2-profiler assay, not least because of the fact that the individual gene measurements are not provided in the medical report, although these are mandatory for the RS calculation. In fact, the "single gene report" only contains unscaled scores of the ER, PR, and Her2 genes without any internationally accepted unit used to describe a transcript quantity. Therefore a direct comparison with the in-house measurement to evaluate its performance is impossible. With regard to our findings and the fact that the Oncotype RS represents a likelihood of the risk of relapse it thus remains impossible to assess the clinical necessity of this assay.

Project description:BackgroundPseudorabies virus (PRV), a neurotropic herpesvirus of pigs, serves as an excellent model system with which to investigate the herpesvirus life cycle both in cultured cells and in vivo. Real-time RT-PCR is a very sensitive, accurate and reproducible technique that can be used to detect very small amounts of RNA molecules, and it can therefore be applied for analysis of the expression of herpesvirus genes from the very early period of infection.ResultsIn this study, we have developed and applied a quantitative reverse transcriptase-based real-time PCR technique in order to profile transcription from the whole genome of PRV after lytic infection in porcine kidney cells. We calculated the relative expression ratios in a novel way, which allowed us to compare different PRV genes with respect to their expression dynamics, and to divide the PRV genes into distinct kinetic classes. This is the first publication on the whole-genome analysis of the gene expression of an alpha-herpesvirus by qRT2-PCR. We additionally established the kinetic properties of uncharacterized PRV genes and revised or confirmed data on PRV genes earlier examined by traditional methods such as Northern blot analysis. Our investigations revealed that genes with the same expression properties form clusters on the PRV genome: nested overlapping genes belong in the same kinetic class, while most convergent genes belong in different kinetic classes. Further, we detected inverse relationships as concerns the expressions of EP0 and IE180 mRNAs and their antisense partners.ConclusionMost (if not all) PRV genes begin to be expressed from the onset of viral expression. No sharp boundary was found between the groups of early and late genes classified on the basis of their requirement for viral DNA synthesis. The expressions of the PRV genes were analyzed, categorized and compared by qRT2-PCR assay, with the average of the minimum cycle threshold used as a control for the calculation of a particular R value. In principle, this new calculation technique is applicable for the analysis of gene expression in all temporally changing genetic systems.

Project description:BackgroundThe Oncotype DX Prostate Cancer Assay is a multi-gene RT-PCR expression assay that was developed for use with fixed paraffin-embedded (FPE) diagnostic prostate needle biopsies containing as little as 1 mm of prostate tumor in the greatest dimension. The assay measures expression of 12 cancer-related genes representing four biological pathways and 5 reference genes which are algorithmically combined to calculate the Genomic Prostate Score (GPS). This biopsy-based assay has been analytically and subsequently clinically validated as a predictor of aggressive prostate cancer. The aim of this study was to validate the analytical performance of the Oncotype DX Prostate Cancer Assay using predefined acceptance criteria.ResultsThe lowest quartile of RNA yields from prostate needle biopsies (six 5 ?m sections) was between 19 and 34 ng. Analytical validation of the process requiring as little as 5 ng of RNA met all pre-defined acceptance criteria. Amplification efficiencies, analytical sensitivity, and accuracy of gene assays were measured by serially diluting an RNA sample and analyzing features of the linear regression between RNA expression measured by the crossing point (Cp) versus the log2 of the RNA input per PCR assay well. Gene assays were shown to accurately measure expression over a wide range of inputs (from as low as 0.005 ng to 320 ng). Analytical accuracy was excellent with average biases at qPCR inputs representative of patient samples <9.7% across all assays while amplification efficiencies were within ±6% of the median. Assessments of reproducibility and precision were performed by testing 10 prostate cancer RNA samples over multiple instruments, reagent lots, operators, days (precision), and RNA input levels (reproducibility) using appropriately parameterized linear mixed models. The standard deviations for analytical precision and reproducibility were 1.86 and 2.11 GPS units (100-unit scale) respectively.ConclusionsThe Oncotype DX Prostate Cancer Assay, a clinical RT-PCR assay specifically designed for use with prostate needle biopsies, has been analytically validated using very limited RNA inputs. The assay requirements and analytical performance will provide physicians with test results from a robust and reliable assay which will enable improved treatment decisions for men diagnosed with early-stage prostate cancer.

Dataset Information

Biomarker discovery for colon cancer using a 761 gene RT-PCR assay.

Background

Results

Conclusion

Publications

Biomarker discovery for colon cancer using a 761 gene RT-PCR assay.

Similar Datasets

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