Preanalytical variables and performance of diagnostic RNA-based gene expression analysis in breast cancer.

Prognostic multigene expression assays have become widely available to provide additional information to standard clinical parameters and to support clinicians in treatment decisions. In this study, we analyzed the impact of variations in tissue handling on the diagnostic EndoPredict test results. EndoPredict is a quantitative reverse transcription PCR assay conducted on RNA from formalin-fixed, paraffin-embedded (FFPE) tissue that predicts the likelihood of distant recurrence in patients with ER-positive/HER2-negative breast cancer. In this study, we performed a total of 138 EndoPredict assays to study the effects of preanalytical variables such as time to fixation, fixation time, tumor cell content, and section storage time on the EndoPredict test results. A time to fixation of up to 12 h and fixation of up to 5 days did not affect the results of the gene expression test. Paired samples of FFPE sections with tumor cell content ranging from 15 to 95 % and tumor-enriched samples showed a correlation coefficient of 0.97. Test results of tissue sections that have been stored for 12 months at +4 or +20 °C showed a correlation of 0.99 when compared to results of nonstored sections. In conclusion, preanalytical tissue handling is not a critical factor for diagnostic gene expression analysis with the EndoPredict assay. The test can therefore be easily integrated into the standard workflow of molecular pathology.

Gene-expression signature of tumor recurrence in patients with stage II and III colon cancer treated with 5'fluoruracil-based adjuvant chemotherapy.

Although receiving adjuvant chemotherapy after radical surgery, a disappointing proportion of patients with colorectal cancer will develop tumor recurrence. Probability of relapse is currently predicted from pathological staging, there being a need for additional markers to further select high-risk patients. This study was aimed to identify a gene-expression signature to predict tumor recurrence in patients with Stages II and III colon cancer treated with 5'fluoruracil (5FU)-based adjuvant chemotherapy. Two-hundred and twenty-eight patients diagnosed with Stages II-III colon cancer and treated with surgical resection and 5FU-based adjuvant chemotherapy were included. RNA was extracted from formalin-fixed, paraffin-embedded tissue samples and expression of 27 selected candidate genes was analyzed by RT-qPCR. A tumor recurrence predicting model, including clinico-pathological variables and gene-expression profiling, was developed by Cox regression analysis and validated by bootstrapping. The regression analysis identified tumor stage and S100A2 and S100A10 gene expression as independently associated with tumor recurrence. The risk score derived from this model was able to discriminate two groups with a highly significant different probability of tumor recurrence (HR, 2.75; 95%CI, 1.71-4.39; p = 0.0001), which it was maintained when patients were stratified according to tumor stage. The algorithm was also able to distinguish two groups with different overall survival (HR, 2.68; 95%CI, 1.12-6.42; p = 0.03). Identification of a new gene-expression signature associated with a high probability of tumor recurrence in patients with Stages II and III colon cancer receiving adjuvant 5FU-based chemotherapy, and its combination in a robust, easy-to-use and reliable algorithm may contribute to tailor treatment and surveillance strategies.

Decentral gene expression analysis: analytical validation of the Endopredict genomic multianalyte breast cancer prognosis test.

BACKGROUND: EndoPredict (EP) is a clinically validated multianalyte gene expression test to predict distant metastasis in ER-positive, HER2-negative breast cancer treated with endocrine therapy alone. The test is based on the combined analysis of 12 genes in formalin-fixed, paraffin-embedded (FFPE) tissue by reverse transcription-quantitative real-time PCR (RT-qPCR). Recently, it was shown that EP is feasible for reliable decentralized assessment of gene expression. The aim of this study was the analytical validation of the performance characteristics of the assay and its verification in a molecular-pathological routine laboratory. METHODS: Gene expression values to calculate the EP score were assayed by one-step RT-qPCR using RNA from FFPE tumor tissue. Limit of blank, limit of detection, linear range, and PCR efficiency were assessed for each of the 12 PCR assays using serial samples dilutions. Different breast cancer samples were used to evaluate RNA input range, precision and inter-laboratory variability. RESULTS: PCR assays were linear up to Cq values between 35.1 and 37.2. Amplification efficiencies ranged from 75% to 101%. The RNA input range without considerable change of the EP score was between 0.16 and 18.5 ng/µl. Analysis of precision (variation of day, day time, instrument, operator, reagent lots) resulted in a total noise (standard deviation) of 0.16 EP score units on a scale from 0 to 15. The major part of the total noise (SD 0.14) was caused by the replicate-to-replicate noise of the PCR assays (repeatability) and was not associated with different operating conditions (reproducibility). Performance characteristics established in the manufacturer's laboratory were verified in a routine molecular pathology laboratory. Comparison of 10 tumor samples analyzed in two different laboratories showed a Pearson coefficient of 0.995 and a mean deviation of 0.15 score units. CONCLUSIONS: The EP test showed reproducible performance characteristics with good precision and negligible laboratory-to-laboratory variation. This study provides further evidence that the EP test is suitable for decentralized testing in specialized molecular pathological laboratories instead of a reference laboratory. This is a unique feature and a technical advance in comparison with existing RNA-based prognostic multigene expression tests.

Decentral gene expression analysis for ER+/Her2- breast cancer: results of a proficiency testing program for the EndoPredict assay.

Gene expression profiles provide important information about the biology of breast tumors and can be used to develop prognostic tests. However, the implementation of quantitative RNA-based testing in routine molecular pathology has not been accomplished, so far. The EndoPredict assay has recently been described as a quantitative RT-PCR-based multigene expression test to identify a subgroup of hormone-receptor-positive tumors that have an excellent prognosis with endocrine therapy only. To transfer this test from bench to bedside, it is essential to evaluate the test-performance in a multicenter setting in different molecular pathology laboratories. In this study, we have evaluated the EndoPredict (EP) assay in seven different molecular pathology laboratories in Germany, Austria, and Switzerland. A set of ten formalin-fixed paraffin-embedded tumors was tested in the different labs, and the variance and accuracy of the EndoPredict assays were determined using predefined reference values. Extraction of a sufficient amount of RNA and generation of a valid EP score was possible for all 70 study samples (100%). The EP scores measured by the individual participants showed an excellent correlation with the reference values, respectively, as reflected by Pearson correlation coefficients ranging from 0.987 to 0.999. The Pearson correlation coefficient of all values compared to the reference value was 0.994. All laboratories determined EP scores for all samples differing not more than 1.0 score units from the pre-defined references. All samples were assigned to the correct EP risk group, resulting in a sensitivity and specificity of 100%, a concordance of 100%, and a kappa of 1.0. Taken together, the EndoPredict test could be successfully implemented in all seven participating laboratories and is feasible for reliable decentralized assessment of gene expression in luminal breast cancer.

Quantitative determination of estrogen receptor, progesterone receptor, and HER2 mRNA in formalin-fixed paraffin-embedded tissue--a new option for predictive biomarker assessment in breast cancer.

The development of optimized therapy strategies against malignant tumors is critically dependent on the assessment of tissue-based biomarkers in routine diagnostic tissue samples. We investigated a novel, fully automated, and xylene-free method for RNA isolation and biomarker determination using formalin-fixed paraffin-embedded (FFPE) tissue. The aim was to show that this approach is feasible and gives results that are comparable to the current gold standards. Expression of the breast cancer biomarkers ESR1, PGR, and HER2 was measured in a total of 501 FFPE tissue samples from 167 breast carcinomas, which had been stored for up to 21 years. Total RNA was extracted from tissue sections and biomarker expression was measured by kinetic RT-PCR (RT-kPCR). The results of the new method were compared with immunohistochemistry as the current gold standard.RNA was successfully isolated from all samples, with a mean yield of 1.4 µg/sample and fragment lengths of at least 150 bp in 99% of samples. RT-kPCR analysis of ESR1, PGR, and HER2 was possible in all samples. Comparing RT-kPCR results with standard IHC, we found a good concordance for ESR1 (agreement: 98.4%), PGR (84.4%), and HER2 (89.8%). We observed a low section-to-section variability of kPCR results for all 3 biomarkers (root of mean squared errors: 0.2 to 0.5 Ct values). The new approach is a reliable high-throughput instrument for standardized testing of biomarkers in clinical routine and for research studies on archived FFPE material up to 21 years old. For the assessment of ESR1, PGR, and HER2 the results are comparable to the current gold-standard.

A high-sensitivity, medium-density, and target amplification-free planar waveguide microarray system for gene expression analysis of formalin-fixed and paraffin-embedded tissue.

BACKGROUND: Many microarray platforms and their associated assay chemistries do not work properly with RNA extracted from formalin-fixed, paraffin-embedded (FFPE) tissue samples, a feature that severely hampers the use of microarrays in oncology applications, for which FFPE tissue is the routine specimen. Furthermore, the limited sensitivity of most microarray platforms requires time-consuming and costly amplification reactions of the target RNA, which negatively affects clinical laboratory work flow. METHODS: We developed an approach for sensitively and reliably measuring mRNA abundances in FFPE tissue samples. This approach involves automated RNA extractions, direct hybridization of extracted RNA to immobilized capture probes, antibody-mediated labeling, and readout with an instrument applying the principle of planar waveguides (PWG). A 14-gene multiplex assay conducted with RNA isolated from 20 FFPE blocks was correlated to an analysis of the same with reverse-transcription quantitative real-time PCR (RT-qPCR). RESULTS: The assay sensitivity for gene expression analysis obtained for the PWG microarray platform was <10 fmol/L, eliminating the need for target preamplification. We observed a correlation coefficient of 0.87 to state-of-the-art RT-qPCR technology with RNA isolated from FFPE tissue, despite a compressed dynamic range for the PWG system (a 2.9-log dynamic range for PWG in our test system vs 5.0 logs for RT-qPCR). The precision of the PWG platform was comparable to RT-qPCR (Pearson correlation coefficient of 0.9851 for PWG vs 0.9896 for RT-qPCR) for technical replicates. CONCLUSIONS: The presented PWG platform demonstrated excellent sensitivity and precision and is especially well suited for any application for which fast, simple, and robust multiplex assays of RNA in FFPE tissue are required.

RNA extraction from archival formalin-fixed paraffin-embedded tissue: a comparison of manual, semiautomated, and fully automated purification methods.

BACKGROUND: Formalin-fixed paraffin-embedded (FFPE) tumor material represents a valuable resource for the analysis of RNA-based biomarkers, both in research laboratories and in routine clinical testing. A robust and automated RNA-extraction method with a high sample throughput is required. METHODS: We evaluated extraction performance for 4 silica-based RNA-extraction protocols: (a) a fully automated, bead-based RNA-isolation procedure; (b) its manual counterpart; (c) a semiautomated bead-based extraction system; and (d) a manual column-based extraction kit. RNA from 360 sections (90 sections per extraction method) of 30 FFPE tumor blocks up to 20 years of age was purified and analyzed by quantitative reverse-transcription PCR for ESR1 (estrogen receptor 1), PGR (progesterone receptor), ERBB2 [v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian)], and RPL37A (ribosomal protein L37a). RESULTS: The semiautomated protocol gave the best yield. The 3 bead-based methods showed good across-method correlations in both yield and relative mRNA amounts (r = 0.86-0.95 and 0.98, respectively). In contrast, correlations between any of the bead-based methods and the manual column-based method were worse (r = 0.77-0.95 and 0.96, respectively). The fully automated method showed the lowest variation from section to section (root mean square error, 0.32-0.35 Cq, where Cq is the quantification cycle) and required the least hands-on time (1 h). CONCLUSIONS: The fully automated RNA-purification method showed the best reproducibility in gene expression analyses of neighboring sections of tissue blocks between 3 and 20 years of age and required the least overall and hands-on times. This method appears well suited for high-throughput RNA analyses in both routine clinical testing and translational research studies with archived FFPE material.