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Head and Neck Squamous Cell Carcinoma Transcriptome Analysis by Comprehensive Validated Differential Display

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Head and Neck Squamous Cell Carcinoma Transcriptome Analysis by Comprehensive Validated Differential Display Oncogene (2006) 25, 1821–1831 & 2006 Nature Publishing Group All rights reserved 0950-9232/06 $30.00 www.nature.com/onc ONCOGENOMICS Head and neck squamous cell carcinoma transcriptome analysis by comprehensive validated differential display A Carles1,4, R Millon2,4, A Cromer1,4,5, G Ganguli1, F Lemaire1,6, J Young1,7, C Wasylyk1, D Muller2, ISchultz 2, Y Rabouel1,2, D Dembe´ le´ 1, C Zhao1,8, P Marchal1, C Ducray3, L Bracco3, J Abecassis2, O Poch1 and B Wasylyk1 1Institut de Ge´ne´tique et de Biologie Mole´culaire et Cellulaire, CNRS/INSERM/ULP, IllkirchCedex, France; 2Laboratoire de Biologie Tumorale, UPRES EA 34-30, Centre Paul Strauss, Strasbourg, France and 3Exonhit Therapeutics, Paris, France Head and neck squamous cell carcinoma (HNSCC)is Introduction common worldwide and is associated with a poor rate of survival. Identification of new markers and therapeutic Head and neck squamous cell carcinoma (HNSCC) is targets, and understanding the complex transformation common worldwide and has a poor rate of survival. It is process, will require a comprehensive description of the fifth most frequent cancer in men, with an incidence genome expression, that can only be achieved by of about 780 000 new cases per year in the world. There combining different methodologies. We report here the is a need for a better understanding of HNSCC, for the HNSCC transcriptome that was determined by exhaustive development of rational targeted interventions and to differential display (DD)analysis coupled with validation define new prognostic or diagnostic markers (Hasina by different methods on the same patient samples. The and Lingen, 2004). The need to comprehensively resulting 820 nonredundant sequences were analysed by describe gene expression patterns has engendered the high throughput bioinformatics analysis. Human proteins emergence of large-scale technologies. Comprehensive were identified for 73% (596)of the DD sequences. A transcriptome analysis is widely applied in cancer large proportion (>50%)of the remaining unassigned research (Liotta and Petricoin, 2000; Liang and Pardee, sequences match ESTs (expressed sequence tags)from 2003). Various methodologies have been used and each human tumours. For the functionally annotated proteins, one has its advantages and limitations (Stein and Liang, there is significant enrichment for relevant biological 2002; Ding and Cantor, 2004). Combining different processes, including cell motility, protein biosynthesis, approaches is important for a complete description of stress and immune responses, cell death, cell cycle, cell cancer transcriptomes. We report here a large-scale proliferation and/or maintenance and transport. Three of analysis of HNSCC by differential display (DD) and the novel proteins (TMEM16A, PHLDB2 and ARH- compare it with macro- and micro-array (mA) studies on GAP21)were analysed further to show that they have the the same samples. potential to be developed as therapeutic targets. DD (Liang and Pardee, 1992) is a powerful, simple Oncogene (2006) 25, 1821–1831. doi:10.1038/sj.onc.1209203; and widely used technology. It combines three common published online 31 October 2005 techniques: reverse transcription (RT), polymerase chain reaction (PCR), polyacrylamide gel electrophor- Keywords: macroarray; microarray; integrative geno- esis, and detects differences in gene expression patterns mics; bioinformatics between two or more samples. The strength of DD is its ability to identify novel genes, whereas a limitation is the frequency of false positives requiring time-consuming validation methods. mAs generate a large amount data Correspondence: Dr B Wasylyk, Institut de Ge´ ne´ tique et de Biologie quickly, and they have become a standard tool. They ONCOGENOMICS Mole´ culaire et Cellulaire, CNRS/INSERM/ULP, 1 rue Laurent Fries, BP10142, 67404 Illkirch Cedex, France. give numerical estimates of gene expression levels for E-mail: [email protected] hundreds to thousands of sequences spotted on various 4These authors contributed equally to this work. supports. However, the data obtained depend on the 5Current address: Department of Cell Biology, Harvard Medical information that was used to generate the arrays, and School, 240 Longwood Avenue, Boston, MA 02115, USA. there are problems of sensitivity, reproducibility and 6Current address: CEA Grenoble-DRDC, Laboratoire BioPuces, 17 rue des Martyrs, 38054 Grenoble Cedex 9, France. specificity for homologous sequences (Stein and Liang, 7Current address: MIMR, Monash University, Clayton 3168, 2002; Liang and Pardee, 2003). As both DD and mAs Australia. have limitations, combining the two methodologies is 8Current address: The Hospital for Sick Children, Dept Genetics & expected to give a more comprehensive description of Genomic Biology, 555 University Avenue, Toronto, Ontario, Canada M5G 1X8. cancer transcriptomes. Received 1 August 2005; revised 13 September 2005; accepted 19 Here, we report the first extensive description of September 2005; published online 31 October 2005 hypopharyngeal carcinoma differential gene expression HNSCC transcriptome A Carles et al 1822 using large-scale DD combined with reverse Northern and macroarray blot (MAB) validation. We compared Tumours identified and characterised by histopathology and patient history the results with a parallel Affymetrix mA study that used the same samples (Cromer et al., 2004). In addition, innovative bioinformatics tools were used to analyse the RNA extracted and DNAsel treated results. We used our integrative genomics and bioinfor- matics platform Gscope and three-step protocol (Chal- Sample preparation mel F, submitted) in order to assign computationally Reverse transcription cross-validated human protein sequences to each DD 3´ primers (3 x HT11 A/G/C) nucleotide sequence. We evaluated the concordance between the gene expression profiles generated by the PCR display different technologies. The large sets of genes that were 3´ primers (3 x HT11 A/G/C) shown to be differentially expressed were functionally 5´ primers (58 x HAP primers) analysed, in order to describe biological relevant path- ways. Several novel genes were evaluated phenotypically to describe their observable characteristics (such as 1750 bands isolated localization and expression levels), and shown to be PCR differential candidates for further evaluation as targets to develop therapeutics for cancer. 14000 clones tested Reverse Northern Hybridisation (RNH) Selection Results PCR-DD and validation by reverse Northern Validation/ hybridization Pilot study This study A pilot study was previously reported, that described 70 RNH using mixed probes RNH using focussed probes sequences obtained from a PCR-DD comparison of the transcriptomes of three stages of HNSCC and corre- ~200 clones 2467 clones sequenced sponding normal tissue (N) (Figure 1) (Lemaire et al., - 30 non-relevant 2003). Sequences from differentially displayed bands (bacteria, cloning vectors) were selected and validated by reverse Northern hybridization (RNH) using ‘mixed’ probes, consisting - 304 poor quality, of the particular combination of HAP primers used for unusuable (repeats...) the DD (Figure 1). As this approach selected few clones, -133 too short we investigated different methods to prepare the probes, (< 25 bases) finally resorting to ‘focused’ probes prepared with each specific HAP primer, which improved the hybridization - 1180 redundant signals and thereby allowed us to select and validate a sequences more comprehensive set of sequences. We now report a large-scale study, in which a total of 2467 clones were 70 unique sequences 820 unique sequences selected by RNH (choosing where possible two clones from each band), and sequenced (Figure 1). The sequences were analysed by high throughput automatic Figure 1 Overviews outlining the DD protocol and the bioinfor- matics sequence analysis of the 2467 sequences. The pilot study has analysis (see Materials and methods). been reported (Lemaire et al., 2003). Of the 2467 sequences, 467 were immediately excluded for different reasons. A total of 30 sequences were non- human (bacteria, plasmids, etc.), 304 were not analy- sable because of their bad quality or the presence of MAB analysis with a larger number ofpatient samples repeats (i.e. ALUs, MIRs, L3, MER47A, etc.) and 133 In order to validate the analysis by a different approach, were too short (less than 25 bases). The remaining 2000 and to extend it to more patients, cDNAs were spotted sequences corresponded to 820 differentially expressed on MABs. The MABs were hybridized in triplicate with nonredundant (NR) genes. Most of the redundancy 50 different labelled cDNAs, prepared from 30 tumours resulted from sequencing two or more clones from the (T) and 20 matched N tissues. The hybridization signals same DD band. The DD conditions were sufficiently were low (near background) for 77% of the spots, selective that particular transcripts were rarely repre- medium for 20% and high for 3%. The high proportion sented by different bands. The final NR list contains 432 of low hybridization signals is expected, as low sequences that are overexpressed in tumours, 349 that abundance transcripts constitute a large proportion of are underexpressed, and 39 that have more complex the overall mRNA population. Differentially expressed profiles, including different profiles between tumour sequences were identified by statistical analysis of types. all of the signals (to minimize overlooking relevant Oncogene HNSCC transcriptome A Carles et al 1823 sequences). A total
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