Quantitative Gene Expression Profiling in Formalin-Fixed, Paraffin-Embedded Tissues Using Universal Bead Arrays
2004; Elsevier BV; Volume: 165; Issue: 5 Linguagem: Inglês
10.1016/s0002-9440(10)63435-9
ISSN1525-2191
AutoresMarina Bibikova, Dimitri Talantov, Eugene Chudin, Joanne M. Yeakley, Jing Chen, Dennis Doucet, Eliza Wickham, David Atkins, David Barker, Mark S. Chee, Yixin Wang, Jian‐Bing Fan,
Tópico(s)RNA Research and Splicing
ResumoWe recently developed a sensitive and flexible gene expression profiling system that is not dependent on an intact poly-A tail and showed that it could be used to analyze degraded RNA samples. We hypothesized that the DASL (cDNA-mediated annealing, selection, extension and ligation) assay might be suitable for the analysis of formalin-fixed, paraffin-embedded tissues, an important source of archival tissue material. We now show that, using the DASL assay system, highly reproducible tissue- and cancer-specific gene expression profiles can be obtained with as little as 50 ng of total RNA isolated from formalin-fixed tissues that had been stored from 1 to over 10 years. Further, tissue- and cancer-specific markers derived from previous genome-wide expression profiling studies of fresh-frozen samples were validated in the formalin-fixed samples. The DASL assay system should prove useful for high-throughput expression profiling of archived clinical samples. We recently developed a sensitive and flexible gene expression profiling system that is not dependent on an intact poly-A tail and showed that it could be used to analyze degraded RNA samples. We hypothesized that the DASL (cDNA-mediated annealing, selection, extension and ligation) assay might be suitable for the analysis of formalin-fixed, paraffin-embedded tissues, an important source of archival tissue material. We now show that, using the DASL assay system, highly reproducible tissue- and cancer-specific gene expression profiles can be obtained with as little as 50 ng of total RNA isolated from formalin-fixed tissues that had been stored from 1 to over 10 years. Further, tissue- and cancer-specific markers derived from previous genome-wide expression profiling studies of fresh-frozen samples were validated in the formalin-fixed samples. The DASL assay system should prove useful for high-throughput expression profiling of archived clinical samples. The recent development of high-throughput microarray technologies provides a powerful tool for genome-wide gene expression analysis.1Lockhart DJ Dong H Byrne MC Follettie MT Gallo MV Chee MS Mittmann M Wang C Kobayashi M Horton H Brown EL Expression monitoring by hybridization to high-density oligonucleotide arrays.Nature Biotechnol. 1996; 14: 1675-1680Crossref PubMed Scopus (2828) Google Scholar For example, microarray-based tumor classification,2Golub TR Slonim DK Tamayo P Huard C Gaasenbeek M Mesirov JP Coller H Loh ML Downing JR Caligiuri MA Bloomfield CD Lander ES Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.Science. 1999; 286: 531-537Crossref PubMed Scopus (9333) Google Scholar, 3Perou CM Sorlie T Eisen MB van de Rijn M Jeffrey SS Rees CA Pollack JR Ross DT Johnsen H Akslen LA Fluge O Pergamenschikov A Williams C Zhu SX Lonning PE Borresen-Dale AL Brown PO Botstein D Molecular portraits of human breast tumours.Nature. 2000; 406: 747-752Crossref PubMed Scopus (12093) Google Scholar, 4Welsh JB Sapinoso LM Su AI Kern SG Wang-Rodriguez J Moskaluk CA Frierson Jr, HF Hampton GM Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer.Cancer Res. 2001; 61: 5974-5978PubMed Google Scholar as well as treatment response and clinical outcome prediction,4Welsh JB Sapinoso LM Su AI Kern SG Wang-Rodriguez J Moskaluk CA Frierson Jr, HF Hampton GM Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer.Cancer Res. 2001; 61: 5974-5978PubMed Google Scholar, 5Dhanasekaran SM Barrette TR Ghosh D Shah R Varambally S Kurachi K Pienta KJ Rubin MA Chinnaiyan AM Delineation of prognostic biomarkers in prostate cancer.Nature. 2001; 412: 822-826Crossref PubMed Scopus (1437) Google Scholar, 6van 't Veer LJ Dai H van de Vijver MJ He YD Hart AA Mao M Peterse HL van der Kooy K Marton MJ Witteveen AT Schreiber GJ Kerkhoven RM Roberts C Linsley PS Bernards R Friend SH Gene expression profiling predicts clinical outcome of breast cancer.Nature. 2002; 415: 530-536Crossref PubMed Scopus (7910) Google Scholar, 7West M Blanchette C Dressman H Huang E Ishida S Spang R Zuzan H Olson Jr, JA Marks JR Nevins JR Predicting the clinical status of human breast cancer by using gene expression profiles.Proc Natl Acad Sci USA. 2001; 98: 11462-11467Crossref PubMed Scopus (1110) Google Scholar have been demonstrated in many cancer types. However, these technologies typically require substantial quantities of fresh or frozen tissue. Although many institutions are now maintaining frozen tissue banks, which should facilitate gene expression analysis in the future, few of these now have sufficient clinical follow-up data. On the other hand, there is a vast supply of formalin-fixed, paraffin-embedded (FFPE) tissues for which the clinical outcome is already known.8Lewis F Maughan NJ Smith V Hillan K Quirke P Unlocking the archive—gene expression in paraffin-embedded tissue.J Pathol. 2001; 195: 66-71Crossref PubMed Scopus (265) Google Scholar The ability to analyze gene expression patterns in these archived tissues would greatly facilitate retrospective studies to correlate gene expression patterns with given disease states, or histological and clinical phenotypes. This approach could be used to discover biomarkers for therapeutic decision making and also to develop clinical tests, as FFPE sample collection and storage is a routine practice in pathology laboratories. A barrier to the analysis of FFPE samples is that RNA extracted from FFPE tissues is often significantly degraded. Previous studies show that only about 3% or less of the RNA isolated from paraffin samples is accessible to cDNA synthesis, compared to fresh-frozen samples.9Godfrey TE Kim SH Chavira M Ruff DW Warren RS Gray JW Jensen RH Quantitative mRNA expression analysis from formalin-fixed, paraffin-embedded tissues using 5′ nuclease quantitative reverse transcription-polymerase chain reaction.J Mol Diagn. 2000; 2: 84-91Abstract Full Text Full Text PDF PubMed Scopus (269) Google Scholar In particular, this has impeded progress in microarray-based gene expression quantitation from FFPE specimens.10Karsten SL Van Deerlin VM Sabatti C Gill LH Geschwind DH An evaluation of tyramide signal amplification and archived fixed and frozen tissue in microarray gene expression analysis.Nucleic Acids Res. 2002; 30: E4Crossref PubMed Scopus (120) Google Scholar As a result, most gene expression analysis of FFPE tissues has so far been done using immunohistochemical staining (IHC) and quantitative RT-PCR (qPCR), which allow only a few genes to be analyzed at a time.9Godfrey TE Kim SH Chavira M Ruff DW Warren RS Gray JW Jensen RH Quantitative mRNA expression analysis from formalin-fixed, paraffin-embedded tissues using 5′ nuclease quantitative reverse transcription-polymerase chain reaction.J Mol Diagn. 2000; 2: 84-91Abstract Full Text Full Text PDF PubMed Scopus (269) Google Scholar, 11Abrahamsen HN Steiniche T Nexo E Hamilton-Dutoit SJ Sorensen BS Towards quantitative mRNA analysis in paraffin-embedded tissues using real-time reverse transcriptase-polymerase chain reaction: a methodological study on lymph nodes from melanoma patients.J Mol Diagn. 2003; 5: 34-41Abstract Full Text Full Text PDF PubMed Scopus (149) Google Scholar, 12Lehmann U Bock O Glockner S Kreipe H Quantitative molecular analysis of laser-microdissected paraffin-embedded human tissues.Pathobiology. 2000; 68: 202-208Crossref PubMed Scopus (39) Google Scholar, 13Daigo Y Chin SF Gorringe KL Bobrow LG Ponder BA Pharoah PD Caldas C Degenerate oligonucleotide primed-polymerase chain reaction-based array comparative genomic hybridization for extensive amplicon profiling of breast cancers: a new approach for the molecular analysis of paraffin-embedded cancer tissue.Am J Pathol. 2001; 158: 1623-1631Abstract Full Text Full Text PDF PubMed Scopus (84) Google Scholar, 14Palmieri G Ascierto PA Cossu A Mozzillo N Motti ML Satriano SM Botti G Caraco C Celentano E Satriano RA Lissia A Tanda F Pirastu M Castello G Detection of occult melanoma cells in paraffin-embedded histologically negative sentinel lymph nodes using a reverse transcriptase polymerase chain reaction assay.J Clin Oncol. 2001; 19: 1437-1443PubMed Google Scholar, 15Specht K Richter T Muller U Walch A Werner M Hofler H Quantitative gene expression analysis in microdissected archival formalin-fixed and paraffin-embedded tumor tissue.Am J Pathol. 2001; 158: 419-429Abstract Full Text Full Text PDF PubMed Scopus (417) Google Scholar, 16Lehmann U Glockner S Kleeberger W von Wasielewski HF Kreipe H Detection of gene amplification in archival breast cancer specimens by laser-assisted microdissection and quantitative real-time polymerase chain reaction.Am J Pathol. 2000; 156: 1855-1864Abstract Full Text Full Text PDF PubMed Scopus (129) Google Scholar Although sufficient RNA can be isolated from a few 10-μm slide-mounted paraffin sections to quantitate up to 30 genes by qPCR,17Cronin M Pho M Dutta D Stephans JC Shak S Kiefer MC Esteban JM Baker JB Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay.Am J Pathol. 2004; 164: 35-42Abstract Full Text Full Text PDF PubMed Scopus (483) Google Scholar there is clearly a bottleneck in scaling up the number of genes that can be measured by this approach. Also, qPCR does not reliably measure RNA fragments shorter than 100 bp.17Cronin M Pho M Dutta D Stephans JC Shak S Kiefer MC Esteban JM Baker JB Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay.Am J Pathol. 2004; 164: 35-42Abstract Full Text Full Text PDF PubMed Scopus (483) Google Scholar We have recently developed a flexible, sensitive, and reproducible gene expression profiling assay, DASL (cDNA-mediated annealing, selection, extension and ligation), for parallel analysis of hundreds of genes with as little as 25 ng of total RNA.18Fan JB Yeakley JM Bibikova M Chudin E Wickham E Chen J Doucet D Rigault P Zhang B Shen R McBride C Li HR Fu XD Oliphant A Barker DL Chee MS A versatile assay for high-throughput gene expression profiling on universal array matrices.Genome Res. 2004; 14: 878-885Crossref PubMed Scopus (158) Google Scholar We hypothesized that the DASL assay might be able to overcome the technical limitations to microarray-based analysis of FFPE samples. While most array technologies use an in vitro transcription (IVT)-mediated sample labeling procedure,19Phillips J Eberwine JH Antisense RNA amplification: a linear amplification method for analyzing the mRNA population from single living cells.Methods. 1996; 10: 283-288Crossref PubMed Scopus (206) Google Scholar DASL uses random priming in the cDNA synthesis, and therefore does not depend on an intact poly-A tail for oligo-d(T) priming. In addition, the assay requires a relatively short target sequence of about 50 nucleotides for query oligonucleotide annealing. In this study, we characterized the sensitivity and quantitative performance of the assay system on FFPE tissues and demonstrated its utility for marker validation as well as new marker identification. The results show that the DASL assay is effective for an important and extensive source of archival clinical material that was hitherto largely inaccessible to microarray technology. This opens up new avenues to the large-scale discovery, validation, and clinical application of mRNA biomarkers of disease. Sample set consisted of 11 matched pairs of FFPE colon cancer and adjacent normal tissues, and 11 matched pairs of FFPE breast cancer and adjacent normal tissues. Colon cancer tissue specimens included 2 Dukes B1 (both well differentiated adenocarcinomas), 5 Dukes B2 (4 moderately and 1 well differentiated adenocarcinoma) and 4 Dukes C2 (2 well, 1 moderately differentiated, and 1 mucinous adenocarcinoma). Breast cancer tissue specimens included one Stage 0, two Stage I, six Stage IIA, one Stage IIB, and one Stage IIIC. There were nine infiltrative ductal carcinomas, one mucinous carcinoma and one ductal carcinoma in situ. Colon cancer was staged according to Modified Aston-Coller classification and breast cancer was staged according to AJCC Cancer Staging Manual (Sixth Edition, Springer, 2003). All samples were obtained from Asterand, Inc. (Detroit, MI) according to an Institutional Review Board approved protocol. Patient demographic and pathology information was also collected. Among the eleven sample pairs of each tissue type, four pairs were collected in a period within 1 year, four pairs in a period of 2 years, and three pairs in a period of 9 to 11 years before the current study (Table 1). Along with the FFPE samples, two matched pairs of fresh-frozen colon cancer and adjacent normal tissue and two matched pairs of fresh-frozen breast cancer and adjacent normal tissue were collected from the patients included in the FFPE sample set. The histopathological features of each sample were reviewed to confirm diagnosis and tumor content.Table 1Tissue SamplesSample ID*CC, colon cancer; CN, colon normal; BC, breast cancer; BN, breast normal.Surgery yearSample typeDiagnosisClinical stageTNM†Tumor classification scale.FS1_CC22002FrozenMucinous adenocarcinomaDukes C2T4N1M0FS1_CN2NormalFS1_CC42002FrozenModerately differentiated adenocarcinomaDukes C2T3N1M0FS1_CN4NormalFS1_BC22002FrozenInfiltrating ductal carcinomaStage IT1N0M0FS1_BN2NormalFS1_BC32002FrozenInfiltrating ductal carcinomaStage IIAT2N0M0FS1_BN3NormalFS1_CC12002FFPEWell differentiated adenocarcinomaDukes B2T3N0MxFS1_CN1NormalFS1_CC22002FFPEMucinous adenocarcinomaDukes C2T4N1M0FS1_CN2NormalFS1_CC32002FFPEWell differentiated adenocarcinomaDukes B1T2N0M0FS1_CN3NormalFS1_CC42002FFPEModerately differentiated adenocarcinomaDukes C2T3N1M0FS1_CN4NormalFS2_CC12001FFPEWell differentiated adenocarcinomaDukes B1T2N0M0FS2_CN1NormalFS2_CC22001FFPEWell differentiated adenocarcinomaDukes C2T3N1M0FS2_CN2NormalFS2_CC32001FFPEModerately differentiated adenocarcinomaDukes B2T4N0M0FS2_CN3NormalFS2_CC42001FFPEWell differentiated adenocarcinomaDukes C2T3N1M0FS2_CN4NormalFS3_CC11994FFPEModerately differentiated adenocarcinomaDukes B2T3N0M0FS3_CN1NormalFS3_CC21992FFPEModerately differentiated adenocarcinomaDukes B2T3N0M0FS3_CN2NormalFS3_CC31994FFPEModerately differentiated adenocarcinomaDukes B2T3N0MxFS3_CN3NormalFS1_BC12002FFPEMucinous adenocarcinomaStage IIAT2N0M0FS1_BN1NormalFS1_BC22002FFPEInfiltrating ductal carcinomaStage IT1N0M0FS1_BN2NormalFS1_BC32002FFPEInfiltrating ductal carcinomaStage IIAT2N0M0FS1_BN3NormalFS1_BC42002FFPEInfiltrating ductal carcinomaStage IIBT2N1M0FS1_BN4NormalFS2_BC12001FFPEInfiltrating ductal carcinomaStage IIAT2N0M0FS2_BN1NormalFS2_BC22001FFPEInfiltrating ductal carcinomaStage IT1N0M0FS2_BN2NormalFS2_BC32001FFPEInfiltrating ductal carcinomaStage IIICT2N3M0FS2_BN3NormalFS2_BC42001FFPEInfiltrating ductal carcinomaStage IIIAT2N2M0FS2_BN4NormalFS3_BC11993FFPEInfiltrating ductal carcinomaStage IIAT2N0M0FS3_BN1NormalFS3_BC21993FFPEInfiltrating ductal carcinomaStage IIAT2N0M0FS3_BN2NormalFS3_BC31993FFPEDuctal carcinoma in situStage 0TisN0M0FS3_BN3Normal* CC, colon cancer; CN, colon normal; BC, breast cancer; BN, breast normal.† Tumor classification scale. Open table in a new tab For total RNA isolation from FFPE tissues, three 20-μm-thick sections were cut from each tissue block. The High Pure RNA Paraffin Kit (Roche) was used. Proteinase K digestion time was 12 hours for each sample. All purification, DNase treatment, and other steps were performed according to the manufacturer's protocol. After total RNA isolation, samples were stored at −80°C until use. Total RNA from fresh-frozen tissue samples was isolated by a standard Trizol/chloroform method. Tissue was homogenized in Trizol reagent (Invitrogen). Total RNA was isolated from Trizol and precipitated at −20°C with isopropyl alcohol. RNA pellets were washed with 75% ethanol, dissolved in water, and stored at −80°C until use. RNA integrity was examined with the Agilent 2100 Bioanalyzer RNA 6000 Nano Assay (Agilent Technologies). qPCR analyses were performed on the ABI Prism 7900HT sequence detection system (Applied Biosystems) as described previously.18Fan JB Yeakley JM Bibikova M Chudin E Wickham E Chen J Doucet D Rigault P Zhang B Shen R McBride C Li HR Fu XD Oliphant A Barker DL Chee MS A versatile assay for high-throughput gene expression profiling on universal array matrices.Genome Res. 2004; 14: 878-885Crossref PubMed Scopus (158) Google Scholar Most PCR primers were designed to amplify approximately 90-bp fragments. Primers for the RPL13A transcript were designed to amplify 90-bp and 155-bp fragments. Microarrays were assembled by loading pools of glass beads (3 μm in diameter) derivatized with oligonucleotides onto the etched ends of fiber-optic bundles.20Barker DL Theriault G Che D Dickinson T Shen R Kain R Self-assembled random arrays: high-performance imaging and genomics applications on a high-density microarray platform.Proc SPIE. 2003; 4966: 1-11Crossref Scopus (23) Google Scholar About 50,000 optical fibers are hexagonally packed to form a ∼1.4 mm diameter bundle. The fiber optic bundles are assembled into an array matrix (Sentrix array), comprising 96 bundles arranged in an 8 × 12 matrix that matches the dimensions of standard microtiter plates.21Fan JB Oliphant A Shen R Kermani B Garcia F Gunderson K Hansen M Steemers F Butler SL Deloukas P Galver L Hunt S McBride C Bibikova M Chen J Wickham E Doucet D Chang W Campbell D Zhang B Kruglyak S Bentley D Haas J Rigault P Zhou L Stuelpnagel J Chee MS Highly parallel SNP genotyping.Cold Spring Harbor Symposia on Quantitative Biology. 2003; 68: 69-78Crossref PubMed Scopus (526) Google Scholar This arrangement allows simultaneous processing of 96 samples using standard robotics. Because the beads are positioned randomly, a decoding process is carried out to determine the location and identity of each bead in every array location.22Gunderson KL Kruglyak S Graige MS Garcia F Kermani B Zhao C Che D Dickinson T Wickham E Bierle J Doucet D Milewski M Yang R Siegmund C Haas J Zhou L Oliphant A Fan JB Barnard S Chee MS Decoding Randomly Ordered DNA Arrays.Genome Res. 2004; 14: 870-877Crossref PubMed Scopus (262) Google Scholar Decoding is an automated part of array manufacture. For array analysis, two probe oligonucleotides were designed to interrogate each target site on the cDNA as described previously,18Fan JB Yeakley JM Bibikova M Chudin E Wickham E Chen J Doucet D Rigault P Zhang B Shen R McBride C Li HR Fu XD Oliphant A Barker DL Chee MS A versatile assay for high-throughput gene expression profiling on universal array matrices.Genome Res. 2004; 14: 878-885Crossref PubMed Scopus (158) Google Scholar with 2 to 10 target sites per gene (average 6 sites). The first oligo consists of two parts: the gene-specific sequence and a universal PCR primer sequence (P1, 5′-ACTTCGTCAGTAACGGAC-3′) at the 5′-end. The second oligo consists of three parts: the gene-specific sequence, a unique address sequence which is complementary to one of 1520 capture sequences on the array, and a universal PCR primer sequence (P2, 5′-GTCTGCCTATAGTGAGTC-3′) at the 3′-end. A single address sequence is uniquely associated with a single target site. This address sequence allows the PCR-amplified products (see below) to hybridize to a universal microarray bearing the complementary probe sequences.21Fan JB Oliphant A Shen R Kermani B Garcia F Gunderson K Hansen M Steemers F Butler SL Deloukas P Galver L Hunt S McBride C Bibikova M Chen J Wickham E Doucet D Chang W Campbell D Zhang B Kruglyak S Bentley D Haas J Rigault P Zhou L Stuelpnagel J Chee MS Highly parallel SNP genotyping.Cold Spring Harbor Symposia on Quantitative Biology. 2003; 68: 69-78Crossref PubMed Scopus (526) Google Scholar The gene-specific sequence is designed with Tm ranging from 57°C to 62°C. cDNA synthesis, DASL process, array image processing, and signal extraction were as described previously.18Fan JB Yeakley JM Bibikova M Chudin E Wickham E Chen J Doucet D Rigault P Zhang B Shen R McBride C Li HR Fu XD Oliphant A Barker DL Chee MS A versatile assay for high-throughput gene expression profiling on universal array matrices.Genome Res. 2004; 14: 878-885Crossref PubMed Scopus (158) Google Scholar First, a 20-μl reverse transcription reaction containing a reaction mix (MMC; Illumina, San Diego, CA), biotinylated random hexamers and oligo-d(T)18, and total RNA (up to 1 μg), was incubated at room temperature for 10 minutes and then at 42°C for 1 hour. The oligo-d(T) priming helps improve assay sensitivity for fresh-frozen samples with intact RNA. Pooled assay oligos were annealed to their sequence-specific targets on the cDNA under a controlled hybridization program.21Fan JB Oliphant A Shen R Kermani B Garcia F Gunderson K Hansen M Steemers F Butler SL Deloukas P Galver L Hunt S McBride C Bibikova M Chen J Wickham E Doucet D Chang W Campbell D Zhang B Kruglyak S Bentley D Haas J Rigault P Zhou L Stuelpnagel J Chee MS Highly parallel SNP genotyping.Cold Spring Harbor Symposia on Quantitative Biology. 2003; 68: 69-78Crossref PubMed Scopus (526) Google Scholar The cDNA was immobilized on paramagnetic beads and washed to remove any excess or mis-hybridized oligos. Hybridized oligos were then extended and ligated to generate amplifiable templates, using Illumina-supplied reagents and conditions (BeadStation User's Manual, Illumina). A PCR reaction was performed with Cy3 labeled universal PCR primers. Single-stranded PCR products were prepared by denaturation, and were then hybridized to Sentrix arrays under a temperature gradient program.21Fan JB Oliphant A Shen R Kermani B Garcia F Gunderson K Hansen M Steemers F Butler SL Deloukas P Galver L Hunt S McBride C Bibikova M Chen J Wickham E Doucet D Chang W Campbell D Zhang B Kruglyak S Bentley D Haas J Rigault P Zhou L Stuelpnagel J Chee MS Highly parallel SNP genotyping.Cold Spring Harbor Symposia on Quantitative Biology. 2003; 68: 69-78Crossref PubMed Scopus (526) Google Scholar The arrays were imaged using a BeadArray Reader scanner (Illumina).20Barker DL Theriault G Che D Dickinson T Shen R Kain R Self-assembled random arrays: high-performance imaging and genomics applications on a high-density microarray platform.Proc SPIE. 2003; 4966: 1-11Crossref Scopus (23) Google Scholar Image processing and intensity data extraction software were as describe previously.23Galinsky VL Automatic registration of microarray images. II. Hexagonal grid.Bioinformatics. 2003; 19: 1832-1836Crossref PubMed Scopus (39) Google Scholar The DASL assay was performed three times independently, and samples were hybridized to three different array matrices. The sample and array coordinate information is shown in Table 2. All of the array data are represented in Supplementary Tables 1–3 at http://ajp.amjpathol.org.Table 2Sample and Array CoordinatesArray matrix 1Array matrix 2Array matrix 3Sample ID*CC, colon cancer; CN, colon normal; BC, breast cancer; BN, breast normal; FF, fresh-frozen.Samples†+, Successfully assayed samples. −, Samples with which assay was attempted but failed.R2 correlation‡R2, correlation between expression profiles of technical replicates at the gene level.SamplesR2 correlationSamplesR2 correlationFS1_CC2_FF+0.989+0.991FS1_CN2_FF+0.989+0.982FS1_CC4_FF+0.997+0.985FS1_CN4_FF+0.994+0.976FS1_BC2_FF+0.991+0.996FS1_BN2_FF+0.979+0.978FS1_BC3_FF+0.994+0.990FS1_BN3_FF+0.992+0.962FS1_CC1+0.990+0.978FS1_CN1+0.984+0.987FS1_CC2+0.991+0.993+0.993FS1_CN2+0.972+0.985+0.985FS1_CC3+0.984+0.898FS1_CN3+0.994+0.983FS1_CC4+0.970+0.965FS1_CN4+0.991+0.985FS2_CC1+0.975+0.944FS2_CN1+0.9130.923+0.851FS2_CC2+0.989+0.974FS2_CN2+0.988+0.974FS2_CC3+0.984+0.975FS2_CN3+0.980+0.970FS2_CC4+0.977+0.979FS2_CN4+0.994+0.987FS3_CC1+0.965+0.951+0.931FS3_CN1+0.974+0.963+0.929FS3_CC2+0.983+0.971FS3_CN2−−FS3_CC3+0.974+0.972FS3_CN3+0.983+0.971FS1_BC1+0.989+0.984FS1_BN1+0.978+0.945FS1_BC2+0.992+0.982FS1_BN2+0.817+0.732FS1_BC3+0.994+0.994FS1_BN3+0.978+0.974FS1_BC4+0.994+0.994FS1_BN4+0.930+0.900FS2_BC1+0.993+0.981FS2_BN1+0.971+0.832FS2_BC2+0.987+0.968FS2_BN2+0.983+0.957FS2_BC3+0.994+0.991FS2_BN3+0.990+0.982FS2_BC4+0.993FS2_BN4+0.966FS3_BC1+0.979+0.957FS3_BN1+0.985+0.952FS3_BC2+0.987+0.981FS3_BN2+0.983+0.931FS3_BC3+0.977+0.968FS3_BN3+0.969+0.912* CC, colon cancer; CN, colon normal; BC, breast cancer; BN, breast normal; FF, fresh-frozen.† +, Successfully assayed samples. −, Samples with which assay was attempted but failed.‡ R2, correlation between expression profiles of technical replicates at the gene level. Open table in a new tab Our method normalizes given array data with respect to reference data such as an average of multiple replicate arrays. We used cubic spline normalization that makes distributions of gene intensities on a given array and reference array similar. The normalization uses quantiles of sequence type signals to fit smoothing B-splines similar to what was proposed by Workman et al.24Workman C Jensen LJ Jarmer H Berka R Gautier L Nielser HB Saxild HH Nielsen C Brunak S Knudsen S A new non-linear normalization method for reducing variability in DNA microarray experiments.Genome Biol. 2002; 3: 48Crossref Google Scholar To identify disease- and tissue-specific markers, we performed two separate analyses. 1) FFPE samples on Array Matrix 2 were distributed into the following group pairs: colon normal versus colon cancer, breast normal versus breast cancer, and normal breast versus normal colon. We applied Mann-Whitney test with a P value cutoff of 0.01 and a twofold change requirement to identify marker genes using FFPE samples. 2) We divided fresh-frozen samples from Array Matrix 3 into colon cancer versus colon normal and breast cancer versus breast normal (two samples per group) and ran the algorithm using negative controls in combination with rank invariant set of probes for construction of an error model, as described by Fan et al.18Fan JB Yeakley JM Bibikova M Chudin E Wickham E Chen J Doucet D Rigault P Zhang B Shen R McBride C Li HR Fu XD Oliphant A Barker DL Chee MS A versatile assay for high-throughput gene expression profiling on universal array matrices.Genome Res. 2004; 14: 878-885Crossref PubMed Scopus (158) Google Scholar Based on the array signals of selected genes, we computed the correlation coefficient matrix for the FFPE samples and clustered them using Agnes function in the R package with Ward's method. The markers identified from Array Matrix 2 were used to cluster FFPE samples on Array Matrix 1 while markers identified on Array Matrix 3 were applied to clustering FFPE samples from the same matrix. We used 8 fresh-frozen and 44 FFPE tissues (Table 1) with time of storage ranging from 1 year to over 10 years for this study. Total RNA was extracted from fresh-frozen and FFPE tissues and converted to cDNA (see Materials and Methods). Aliquots of the cDNA reactions were taken for real-time PCR analysis. To assess the integrity of RNA isolated from these FFPE tissues, we measured the amplification efficiency of two fragments (90 bp and 155 bp) from a highly expressed gene (RPL13A). As shown in Figure 1, the absolute Ct values increased with the storage time, correlating well with previous observations that RNA fragmentation increases with storage time.17Cronin M Pho M Dutta D Stephans JC Shak S Kiefer MC Esteban JM Baker JB Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay.Am J Pathol. 2004; 164: 35-42Abstract Full Text Full Text PDF PubMed Scopus (483) Google Scholar In addition, a difference in threshold cycle (Ct) values was calculated by taking the average Ct value of duplicate samples for the amplification of the 90-bp fragment and subtracting the average Ct value for the amplification of the 155-bp fragment. The difference reflects the level of RNA degradation in the sample (ie, a bigger difference means more degraded). No difference in amplification efficiency was found in fresh-frozen samples, but the difference increased with the age of the archival samples from which the RNA was extracted, and was up to 6 cycle numbers in FFPE samples older than 10 years (Figure 1), indicating a high level of RNA degradation in these samples. To obtain reproducible gene expression results, we used an RT-PCR test to pre-qualify the RNA samples before array analysis. RT-PCR primers were designed to target ∼90-bp fragments in each of three housekeeping genes: UBC, HPRT, and PBDG. Of the 44 samples tested, only one sample (FS3-CN2) showed no amplification in RT-PCR even for the highly expressed ubiquitin C (UBC) gene. This sample also failed to produce any gene expression data on the array. We examined the impact of input RNA quantity on assay performance. Various amounts of total RNA (1000, 500, 250, and 100 ng) isolated from FFPE tissues were converted into cDNA. Each cDNA sample was split to perform two independent DASL assays. Highly reproducible results were obtained with as little as 50 ng of total RNA (R2Golub TR Slonim DK Tamayo P Huard C Gaasenbeek M Mesirov JP Coller H Loh ML Downing JR Caligiuri MA Bloomfield CD Lander ES Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.Science. 1999; 286: 531-537Crossref PubMed Scopus (9333) Google Scholar = 0.97). More importantly, as shown in Figure 2, gene expression profiles generated with 50 ng (as well as 125 ng and 250 ng, data not shown) input RNA were quite comparable with those generated with 500 ng of RNA (R2Golub TR Slonim DK Tamayo P Huard C Gaasenbeek M Mesirov JP Coller H Loh ML Downing JR
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