Comment[ArrayExpressAccession] E-GEOD-12071 Investigation Title Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer Comment[Submitted Name] Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer Publication Title Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer. Publication Author List Karlsson E, Delle U, Danielsson A, Olsson B, Abel F, Karlsson P, Helou K Publication DOI PubMed ID 18778486 Experimental Design transcription profiling by array Experimental Design Term Source REF EFO Public Release Date 2008-08-29 Experiment Description Expression profiling of breast cancer tumours, comparing 10 year survivors to deceased patients Background It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. Methods 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used to evaluate the gene lists on the different data sets, a correlation-based classifier and a VFI (Voting Features Interval) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients which had developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. Results A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). Conclusion The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients should have had different adjuvant treatment than they did. Keywords: Expression Microarray, Lymph-node-negative Breast Cancer, Clinical Outcome, Classification 23 fresh frozen primary node negative breast cancer tumours from 10 year survivors were compared to 23 tumours from deceased patients in order to find genes where the expression differed between the two groups Microarrays were produced at the Swegene DNA Microarray Resource Center, Department of Oncology, Lund University, Sweden (http://swegene.onk.lu.se). Frozen tumours were homogenized together with TRIzol Reagent (Invitrogen, Carlsbad, CA, USA). From the cell-suspension total RNA was extracted using RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s protocol. The quality of the RNA was evaluated with the Agilent 2100 BioAnalyser (Agilent Technologies, Palo Alto, CA, USA). Specimens where the 28S/16S ratio was lower than 1.0 or the RIN-value was lower than 6.7 were excluded from the study. For each sample, Cy3-dCTP (Amersham Biosciences, Buckinghamshire, UK) labelled probes were synthesized from 5 µg of the total tumour RNA and Cy5-dCTP (Amersham Biosciences) labelled reference were synthesized from 5 µg of commercial reference RNA (Universal Human Reference RNA, Stratagene, La Jolla, CA, USA) by reverse transcription. The probes were purified using ChipShot™ labelling cleanup system (Promega, Madison, WI, USA). The hybridizations were carried out using Pronto! Micro Array reagent systems (Corning Inc., Corning, NY, USA). For each sample, labelled tumour cDNA and reference cDNA were co-precipitated and hybridised to the microarray slide. The microarray slides were scanned with Agilent microarray scanner G2565AA (Agilent Technologies) and image analysis was performed using the Genepix 6.0.0.45 software (Axon Instruments, Union City, CA, USA). Date of Experiment Term Source Name EFO Term Source Version Term Source File Person Last Name Karlsson Karlsson Delle Helou Person First Name Elin Elin Ulla Khalil Person Mid Initials Person Email elin.karlsson@gu.se Person Affiliation Göteborg University Person Phone Person Fax Person Address Oncology, Göteborg University, Blå stråket 2, Göteborg, Sweden Person Roles submitter Person Roles Term Source REF Person Roles Term Accession Number Normalization Type Normalization Term Accession Number Normalization Term Source REF Replicate Type Replicate Term Accession Number Replicate Term Source REF Quality Control Type Quality Control Term Accession Number Quality Control Term Source REF Protocol Name P-GSE12071-1 P-GSE12071-6 P-GSE12071-5 P-GSE12071-4 P-GSE12071-2 P-GSE12071-3 P-GSE12071-7 Protocol Description ID_REF =
VALUE = normalized log2 ratio (Cy3/Cy5) representing test/reference Images were quantified using Genepix 6.0.0.45 (Axon Instruments). Scanned on an Agilent G2565AA scanner. The probes were purified using ChipShot™ labelling cleanup system (Promega). The hybridizations were carried out using Pronto! Micro Array reagent systems (Corning Inc.). For each sample, labelled tumour cDNA and reference cDNA were co-precipitated and hybridised to the oligoarray slide. After hybridization, slides were washed sequential. Total RNA extracted using Trizol following manufacturer's instructions Probes labelled with Cy3 were synthesized from 5 µg of the total tumour RNA and reference labelled with Cy5 were synthesized from 5 µg of commercial reference RNA by reverse transcription. Intensities were calculated by median spot - median background. Flagged spots and spots for which background adjusted intensities were <0 or >65 000 were excluded as well as spots with intensities below 20 in both channels. Intensities below 20 in one channel were set to 20 to compensate for extreme quotients. pin-based Lowess normalization were performed with 12 blocks in each group Protocol Software Protocol Hardware Protocol Contact Protocol Type bioassay_data_transformation image_aquisition image_aquisition hybridization nucleic_acid_extraction labeling feature_extraction Protocol Term Source REF Protocol Term Accession Number Experimental Factor Name AGE AT DIAGNOSIS TUMOUR SIZE Experimental Factor Type age at diagnosis tumour size Experimental Factor Term Source REF Experimental Factor Term Accession Number Comment[SecondaryAccession] GSE12071 Comment[GEOLastUpdateDate] 2009-03-15 Comment[GEOReleaseDate] 2008-08-28 Comment[ArrayExpressSubmissionDate] 2008-07-09 SDRF File E-GEOD-12071.sdrf.txt