Udo Stropp

Automated Extraction of DNA and RNA from a Single Formalin-Fixed Paraffin-Embedded Tissue Section for Analysis of Both Single-Nucleotide Polymorphisms and mRNA Expression

BACKGROUND There is an increasing need for the identification of both DNA and RNA biomarkers from pathodiagnostic formalin-fixed paraffin-embedded (FFPE) tissue samples for the exploration of individualized therapy strategies in cancer. We investigated a fully automated, xylene-free nucleic acid extraction method for the simultaneous analysis of RNA and DNA biomarkers related to breast cancer. METHODS We copurified both RNA and DNA from a single 10-μm section of 210 paired samples of FFPE tumor and adjacent normal tissues (1-25 years of archival time) using a fully automated extraction method. Half of the eluate was DNase I digested for mRNA expression analysis performed by using reverse-transcription quantitative PCR for the genes estrogen receptor 1 (ESR1), progesterone receptor (PGR), v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived oncogene homolog (avian) (ERBB2), epoxide hydrolase 1 (EPHX1), baculoviral IAP repeat-containing 5 (BIRC5), matrix metallopeptidase 7 (MMP7), vascular endothelial growth factor A (VEGFA), and topoisomerase (DNA) II alpha 170kDa (TOP2A). The remaining undigested aliquot was used for the analysis of 7 single-nucleotide polymorphisms (SNPs) by MALDI-TOF mass spectrometry. RESULTS In 208 of 210 samples (99.0%) the protocol yielded robust quantification-cycle values for both RNA and DNA normalization. Expression of the 8 breast cancer genes was detected in 81%-100% of tumor tissues and 21%-100% of normal tissues. The 7 SNPs were successfully genotyped in 91%-97% of tumor and 94%-97% of normal tissues. Allele concordance between tumor and normal tissue was 98.9%-99.5%. CONCLUSIONS This fully automated process allowed an efficient simultaneous extraction of both RNA and DNA from a single FFPE section and subsequent dual analysis of selected genes. High gene expression and genotyping detection rates demonstrate the feasibility of molecular profiling from limited archival patient samples.

Prognostic algorithm identified in node-negative early breast cancer patients predicts outcome also in node-positive patients treated with adjuvant chemotherapy.

Abstract #6044 Background: Recently, we identified and validated a prognostic multigene score, which predicted outcome in early node-negative breast cancer patients that did not receive systemic therapy. The aim of this study was to examine the performance of our prognostic multigene algorithm in node-positive patients treated with adjuvant chemotherapy.
 Patients and Methods: Patients were treated with adjuvant anthracycline-based chemotherapy in the context of a randomized Phase III study. This was a two-arm trial (E-CMF vs. E-T-CMF) investigating postoperative dose-dense sequential chemotherapy with epirubicin (E) followed by CMF with or without paclitaxel (T). RNA was isolated from 222 formalin-fixed, paraffin-embedded tumor tissue samples, using a Siemens proprietary automated method based on silica-coated magnetic beads, followed by kinetic one-step RT-PCR for mRNA expression analysis of 9 informative genes and 2 normalization genes. For each patient a risk score was calculated using a linear combination of expression values. Patients were separated into high, intermediate and low risk by applying two thresholds of the score. As used in node-negative patients, distant metastasis-free survival (MFS) and overall survival (OS) were estimated by the Kaplan-Meier method and compared using the log-rank test. Cox analysis for MFS and OS was also performed.
 Results: The prognostic score could be calculated for 213 patients (102 E-T-CMF; 111 E-CMF). Looking at all patients independently of type of chemotherapy, the score could classify the patients into three distinct risk groups, which were significantly different in terms of MFS (log-rank test, p=0.004) and OS (p=0.01). The separation of the risk groups was even better when focusing on patients with more than three involved lymph nodes (MFS: p=0.0001; OS: p=0.0015; n=166). The respective analysis of the two treatment arms showed that the separation of the risk groups was only significant in E-CMF-treated patients (E-CMF: p=0.002; E-T-CMF: p=0.37). Interestingly, the subgroup of patients with more than three involved lymph nodes and classified as intermediate or high risk (n=77) had a nearly significant better MFS when treated with E-T-CMF in comparison with E-CMF (p=0.07; HR: 0.53; 95% CI: 0.2685 to 1.060).
 Conclusions: Our prognostic algorithm, identified and validated in node-negative patients that had not been systemically treated, predicts outcome also in node-positive chemotherapy-treated patients. Our findings suggest that the prognostic score may also be predictive of benefit from the addition of taxanes to adjuvant chemotherapy. This hypothesis needs to be confirmed in a larger cohort of samples from an independent clinical study. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 6044.