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.
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.
Authors: Berit M Pfitzner; Bianca Lederer; Judith Lindner; Christine Solbach; Knut Engels; Mahdi Rezai; Karel Dohnal; Hans Tesch; Martin L Hansmann; Christoph Salat; Michaela Beer; Andreas Schneeweiss; Peter Sinn; Agnes Bankfalvi; Silvia Darb-Esfahani; Gunter von Minckwitz; Bruno V Sinn; Ralf Kronenwett; Karsten Weber; Carsten Denkert; Sibylle Loibl Journal: Mod Pathol Date: 2017-12-22 Impact factor: 7.842
Authors: José Luis García-Giménez; Marta Seco-Cervera; Trygve O Tollefsbol; Carlos Romá-Mateo; Lorena Peiró-Chova; Pablo Lapunzina; Federico V Pallardó Journal: Crit Rev Clin Lab Sci Date: 2017-12-11 Impact factor: 6.250
Authors: Jean-Philippe Jais; Thierry Jo Molina; Philippe Ruminy; David Gentien; Cecile Reyes; David W Scott; Lisa M Rimsza; George Wright; Randy D Gascoyne; Louis M Staudt; Corinne Haioun; Herve Tilly; Philippe Gaulard; Gilles A Salles; Fabrice Jardin; Karen Leroy Journal: Haematologica Date: 2017-07-04 Impact factor: 9.941
Authors: D Dionysopoulos; K Pavlakis; V Kotoula; E Fountzilas; K Markou; I Karasmanis; N Angouridakis; A Nikolaou; K T Kalogeras; G Fountzilas Journal: Strahlenther Onkol Date: 2013-02-13 Impact factor: 3.621
Authors: Pulak R Manna; Cloyce L Stetson; Carol Daugherty; Ikue Shimizu; Peter J Syapin; Ghislaine Garrel; Joelle Cohen-Tannoudji; Ilpo Huhtaniemi; Andrzej T Slominski; Kevin Pruitt; Douglas M Stocco Journal: Mech Ageing Dev Date: 2015-08-21 Impact factor: 5.432
Authors: Vassiliki Kotoula; Konstantine T Kalogeras; George Kouvatseas; Despoina Televantou; Ralf Kronenwett; Ralph M Wirtz; George Fountzilas Journal: Virchows Arch Date: 2012-12-20 Impact factor: 4.064