Prognostic gene expression signatures can be measured in tissues collected in RNAlater preservative.

Gene expression signatures have the ability to serve in both prognostic and predictive capacities in patient management. The use of RNA as the starting material and the lability of this analyte, however, dictate that tissues must be snap-frozen or stored in a solution that can maintain the integrity of the RNA. We compared pairs of snap-frozen and RNAlater preservative-suspended tissue from 30 such paired lymph node-negative breast tumors and 21 such paired Dukes' B colon tumors. We assessed the correlation of gene expression profiles and prediction of recurrence based on two prognostic algorithms. Tissues stored in RNAlater preservative generated expression profiles with excellent correlation (average Pearson correlation coefficients of 0.97 and 0.94 for the breast and colon tumor pairs, respectively) compared to those produced by tissues that were snap-frozen. The correlation in the prediction of recurrence was 97% and 95% for the breast and colon tumor pairs, respectively, between these two types of tissue handling protocols. This novel finding demonstrates that prognostic signatures can be obtained from RNAlater preservative-suspended tissues, an important step in bringing gene expression signatures to the clinic.

[1]  J. Foekens,et al.  Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer , 2005, The Lancet.

[2]  H. Juhl,et al.  Tissue ischemia time affects gene and protein expression patterns within minutes following surgical tumor excision. , 2004, BioTechniques.

[3]  Wei Wang,et al.  A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. , 2004, Cancer cell.

[4]  David C. Atkins,et al.  Gene expression profiles and molecular markers to predict recurrence of Dukes' B colon cancer. , 2004, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[5]  Monika Milewski,et al.  Decoding randomly ordered DNA arrays. , 2004, Genome research.

[6]  Ash A. Alizadeh,et al.  Prediction of survival in diffuse large-B-cell lymphoma based on the expression of six genes. , 2004, The New England journal of medicine.

[7]  A. Ashworth,et al.  Molecular profiling of breast cancer: clinical implications , 2004, British Journal of Cancer.

[8]  Terence P. Speed,et al.  A benchmark for Affymetrix GeneChip expression measures , 2004, Bioinform..

[9]  H. Baelde,et al.  Improvement of extraction and processing of RNA from renal biopsies. , 2004, Kidney international.

[10]  Wolfgang Huber,et al.  Systematic analysis of T7 RNA polymerase based in vitro linear RNA amplification for use in microarray experiments , 2004, BMC Genomics.

[11]  Carlos Caldas,et al.  Expression microarray reproducibility is improved by optimising purification steps in RNA amplification and labelling , 2004, BMC Genomics.

[12]  Andrew J. Wilson,et al.  Gene expression profiling-based prediction of response of colon carcinoma cells to 5-fluorouracil and camptothecin. , 2003, Cancer research.

[13]  Mattias Lorentzon,et al.  cDNA‐arrays and real‐time quantitative PCR techniques in the investigation of chronic achilles tendinosis , 2003, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[14]  Adrian Wiestner,et al.  A gene expression-based method to diagnose clinically distinct subgroups of diffuse large B cell lymphoma , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[15]  D. Dorris,et al.  Oligodeoxyribonucleotide probe accessibility on a three-dimensional DNA microarray surface and the effect of hybridization time on the accuracy of expression ratios , 2003, BMC biotechnology.

[16]  J. Inman,et al.  A new strategy to amplify degraded RNA from small tissue samples for microarray studies. , 2003, Nucleic acids research.

[17]  E. Lander,et al.  A molecular signature of metastasis in primary solid tumors , 2003, Nature Genetics.

[18]  M. West,et al.  Gene expression phenotypic models that predict the activity of oncogenic pathways , 2003, Nature Genetics.

[19]  Atul Butte,et al.  The use and analysis of microarray data , 2002, Nature Reviews Drug Discovery.

[20]  John Quackenbush.  Microarray data normalization and transformation , 2002, Nature Genetics.

[21]  Franco Cerrina,et al.  Gene expression analysis using oligonucleotide arrays produced by maskless photolithography. , 2002, Genome research.

[22]  T. Hastie,et al.  Optimization and evaluation of T7 based RNA linear amplification protocols for cDNA microarray analysis , 2002, BMC Genomics.

[23]  David E. Misek,et al.  Gene-expression profiles predict survival of patients with lung adenocarcinoma , 2002, Nature Medicine.

[24]  M. Ellis,et al.  Development and validation of a method for using breast core needle biopsies for gene expression microarray analyses. , 2002, Clinical cancer research : an official journal of the American Association for Cancer Research.

[25]  R. Nadon,et al.  Statistical issues with microarrays: processing and analysis. , 2002, Trends in genetics : TIG.

[26]  T. Golub,et al.  DNA microarrays in clinical oncology. , 2002, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[27]  Anders Wallqvist,et al.  Establishing connections between microarray expression data and chemotherapeutic cancer pharmacology. , 2002, Molecular cancer therapeutics.

[28]  D. Geschwind,et al.  An evaluation of tyramide signal amplification and archived fixed and frozen tissue in microarray gene expression analysis. , 2002, Nucleic acids research.

[29]  Van,et al.  A gene-expression signature as a predictor of survival in breast cancer. , 2002, The New England journal of medicine.

[30]  J. Craft,et al.  Clonal origins of human breast cancer , 2001, The Journal of pathology.

[31]  J Quackenbush,et al.  Effects of ischemia on gene expression. , 2001, The Journal of surgical research.

[32]  P. Meltzer.  Spotting the target: microarrays for disease gene discovery. , 2001, Current opinion in genetics & development.

[33]  David A Jones,et al.  Preservation of RNA for Functional Genomic Studies: A Multidisciplinary Tumor Bank Protocol , 2001, Modern Pathology.

[34]  Christian A. Rees,et al.  Molecular portraits of human breast tumours , 2000, Nature.

[35]  N. Sampas,et al.  Molecular classification of cutaneous malignant melanoma by gene expression profiling , 2000, Nature.

[36]  B. Geoerger,et al.  Biological stability of RNA isolated from RNAlater-treated brain tumor and neuroblastoma xenografts. , 2000, Medical and pediatric oncology.

[37]  T. Godfrey,et al.  Quantitative mRNA expression analysis from formalin-fixed, paraffin-embedded tissues using 5' nuclease quantitative reverse transcription-polymerase chain reaction. , 2000, The Journal of molecular diagnostics : JMD.

[38]  W. Symmans,et al.  Breast cancer heterogeneity: evaluation of clonality in primary and metastatic lesions. , 1995, Human pathology.

[39]  M. Durm,et al.  Intratumor variability in prognostic indicators may be the cause of conflicting estimates of patient survival and response to therapy. , 1994, Cancer research.

[40]  J. Eberwine,et al.  Amplified RNA synthesized from limited quantities of heterogeneous cDNA. , 1990, Proceedings of the National Academy of Sciences of the United States of America.