MEDICAMENTS ET METABOLITES
Deux groupes : ML(métaboliseurs lents) et MR(métabolisateurs rapides -activité normale) voire même MUR (métaboliseurs ultra-rapides) pour certains enzymes.

  

SUSCEPTIBILITE AUX MEDICAMENTS
tests simples permettant d'identifier les individus susceptibles de présenter des anomalies de réponse (insuffisance, toxicité)


PREDICTION DE LA REPONSE : Génotypage ou phénotypage
phénotypage avec mesure de la réponse sanguine ou urinaire. Il y a un problèmes pour les médicaments agissant sur les neurotransmetteurs : il est impossible de faire des mesures directes (barrière encéphalique) sauf .. à l'autopsie.
génotypage basé sur l'étude du polymorphisme génétique. Le génotypage est d'application plus large que le phénotypage.


EXEMPLES DE POLYMORPHISMES GENETIQUES affectant la réponse aux médicaments

Géne	Médicament substrat	Conséquences cliniques
Enzymes du métabolisme
CYP2D6	AD tricycliques, neuroleptiques	Inéffcacité MUR, toxicité ML
Transporteurs
MDR1	antiépileptiques	Résistance au traitement
Récepteurs/cibles thérapeutiques autres
DRD2,3 et 4	neuroleptiques(clozapine,Haldol)	Efficacité variable, agranulocytose
HTR2A	clozapine	Efficacité variable

Il existe une variation ethnique importante dans la prévalence des phénotypes. La prévalence des métaboliseurs lents dans la population blanche est de 5 à 10% pour le CYP2D6, de 0,2 à 1% pour le CYP2C9, et de 2 à 4% pour le CYP2C19.
  Le 16 juin 2006 inauguration à l'HEGP, de la première plate-forme avec l'AmpliChipP450, (CYP2D6 et CYP2C19).  
  Une discussion d'avril 2007 dans le Bristish Medical Journal (cf Références), discute de l'opportunité d'utiliser les puces à ADN testant le cytochrome CYP2D6  pour permettre un choix raisonné d'un antidépresseur efficace.


LES ESPOIRS A CONFIRMER DES PUCES A ADN.

  Trois fabriquants de puces a ADN et des réactifs associés, sont présents sur le marché ; Amershaw, Agilent, Affymetrics. Le nombre de publications (d'articles de recherche) basés sur les résultats obtenus avec les puces à ADN a explosé sur les quatre dernières années atteignant 3000 en 2003.
   Malheureusement les résultats obtenus ne sont pas les mêmes suivants les puces utilisées. (Margaret Cam, 2003)
   Une standardisation des méthodes et des méthodes de présentation est nécessaire pour assurer la stabilité et la reproductibilité des résultats.
   Le passage des recherches à la clinique pour guider le choix du traitement adapté, par exemple dans certains types de cancer n'est pas pour tout se suite.
    Une étude récente de Tsuang (fev 2005) citée en référence montre que des combinaisons linéaires et non-linéaires de 8 biomarqueurs génétiques  (APOBEC3B, ADSS, ATM, CLC, CTBP1, DATF1, CXCL1, and S100A9) sont capables de distinguer entre schizophrenie, Bipolarité et sujet de contrôles avec une précision totale de  95%-97% comme indiqué par l'analyse ROC., ce qui montre la puissance de cette méthode, quand sa reproductibilité sera assurée.
     Ces divergences ont imposé la constitution d'une méthodologie standard MAQC - MICRO ARRAY QUALITY CONTROL-. qui semble donner des résultats homogènes sur un benchmark de plus de 12000 gènes en employant du RNA messager (mRNA) issu de cellules tumorales humaines ou du cerveau humain (Nature Biotechnology - Septembre 2006) ref 7. Mais cette technologie a encore du chemin à faire avant de pouvoir être utilisée en routine clinique pour prédire des cancers ou pronostiquer des maladies (Science 15/09/2006 p 1559) 
    Un projet français dans le cadre de RESOGEN vise à construire et à alayser les résultats de  deux puces sur lames de verre destinées à l'étude en parallèle de la totalité de l'expression des gènes des deux espèces, l'homme(27 000 sondes) et la souris (25 000 sondes) !.
   A noter, dans le registre des marteaux-pilons, la construction à Saclay de Neurospin, une unité surpuissante d'imagerie fonctionelle avec 11 000M2 de batiments prévus pour 150 chercheurs inauguré le 24 novembre 2006.

GENOMIQUE ET TOXICITE DES PRODUITS CHIMIQUES EXISTANTS
   Les médicaments récents et nous nouveaux produits chimiques sont testés pour leurs propriétés toxiques éventuelles. Mais les 30 000 produits chimiques préxistants n'ont pas été testés. En Europe l'EBI a créé la base de données TOX-MIAMExpress pour créer les données de toxicité et de toxicogénomique dans une forme standardisée. Tous les fabricants de produits chimiques doivent avoir testé retro-activement leurs produits pour 2010.
   Cela pose le problème de la délocalisation des fabrications incorporant  des produits  "toxiques" dans les pays n'ayant pas la même législation.

PREMIERS RESULTATS CLINIQUES ET OBSTACLES A SURMONTER
  Les premiers résultats ont été obtenus dans les traitements contre le cancer. Quels sont les facteurs génétiques qui font qu' un type de traitement sera efficace ?. Ces résultats sont le fruit d'une recherche numériquement importante et plus richement dotée, de deux ordres de grandeur, que la recherche en psychiatrie. Comme le note un article de synthèse de mars 2007,  la taille des métadonnées à analyser, avant de déterminer des sous-cohortes homogènes ( à la fois au test et au traitement), exige la combinaison de compétences spécialisées et une organisation spécifique.

LES STRATEGIES DE TRAITEMENT
  Les traitements stratifiés sont basès sur la présence de marqueurs biologiques permettant de déclencher un traitement un fois un seuil passé. C'est le cas actuellement du traitement de l'hypertension ou de l'ostéoporose. L'absence, actuelle et on l'espère provisoire, de marqueurs biologiques pour les troubles psychiatriques  ne permet de pratiquer qu'une médecine empirique basée sur des essais clinique. Les puces à ADN, en développement, permettront probablement dans un proche avenir d'avoir une médecine, si ce n'est individualisée, du moins stratifiée.

Ref1 - La pharmacogénétique : le lien entre génes et réponse aux médicaments
MA Loriot, Philippe Beaune Medecines-Sciences , juin-juillet 2004

Ref2 - Getting the noise Out of Gene Arrays in Genes in action, Science, 22 octobre 2004, Eliot Marshall, http://www.sciencemag.org

Ref3 -Genomics and Drug Toxicity Editorial Science 22/10/2004 PG Lord, T Papoian.
Microarray Projects :  Toxicogenomics and Nutrigenomics   Site EMBL-EBI

Quelques présentations générales :


Ref7 Nature Biotechnology - Septembre 2006   avec en particulier pour la norme MAQC
Canales RD, Luo Y, Willey JC, Austermiller B, Barbacioru CC, Boysen C, Hunkapiller K, Jensen RV, Knight CR, Lee KY, Ma Y, Maqsodi B, Papallo A, Peters EH, Poulter K, Ruppel PL, Samaha RR, Shi L, Yang W, Zhang L, Goodsaid FM.
Evaluation of DNA microarray results with quantitative gene expression platforms.
Nat Biotechnol. 2006 Sep;24(9):1115-22.

Ref8. Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers
Mark R. Trusheim(1), Ernst R. Berndt(1) & Frank L. Douglas(1)
Nature Reviews Drug Discovery 6, 287-293 (April 2007) | doi:10.1038/nrd2251
http://www.nature.com/nrd/journal/v6/n4/full/nrd2251.html

1: Nat Biotechnol. 2006 Sep;24(9):1115-22.

Evaluation of DNA microarray results with quantitative gene expression platforms. Canales RDLuo Y Willey JC Austermiller BBarbacioru CCBoysen C Hunkapiller KJensen RV, etc.. Goodsaid FM
We have evaluated the performance characteristics of three quantitative gene expression technologies and correlated their expression measurements to those of five commercial microarray platforms, based on the MicroArray Quality Control (MAQC) data set. The limit of detection, assay range, precision, accuracy and fold-change correlations were assessed for 997 TaqMan Gene Expression Assays, 205 Standardized RT (Sta)RT-PCR assays and 244 QuantiGene assays. TaqMan is a registered trademark of Roche Molecular Systems, Inc. We observed high correlation between quantitative gene expression values and microarray platform results and found few discordant measurements among all platforms. The main cause of variability was differences in probe sequence and thus target location. A second source of variability was the limited and variable sensitivity of the different microarray platforms for detecting weakly expressed genes, which affected interplatform and intersite reproducibility of differentially expressed genes. From this analysis, we conclude that the MAQC microarray data set has been validated by alternative quantitative gene expression platforms thus supporting the use of microarray platforms for the quantitative characterization of gene expression.

Tsuang MT, Nossova N, Yager T, Tsuang MM, Guo SC, Shyu KG, Glatt SJ, Liew CC
Assessing the validity of blood-based gene expression profiles for the classification of schizophrenia and bipolar disorder: a preliminary report.
Am J Med Genet B Neuropsychiatr Genet. 2005 Feb 5;133(1):1-5.
Recent advances have facilitated the use of blood-derived RNA to conduct genomic analyses of human diseases. This emerging technology represents a rigorous and convenient alternative to traditional tissue biopsy-derived RNA, as it allows for larger sample sizes, better standardization of technical procedures, and the ability to non-invasively profile human subjects. In the present pilot study, we have collected RNA from blood of patients diagnosed with schizophrenia or bipolar disorder (BPD), as well as normal control subjects. Using microarray analysis, we found that each disease state exhibited a unique expressed genome signature, allowing us to discriminate between the schizophrenia, BPD, and control groups. In addition, we validated changes in several potential biomarker genes for schizophrenia and BPD by RT-PCR, and some of these were found to code to chromosomal loci previously linked to schizophrenia. Linear and non-linear combinations of eight putative biomarker genes (APOBEC3B, ADSS, ATM, CLC, CTBP1, DATF1, CXCL1, and S100A9) were able to discriminate between schizophrenia, BPD, and control samples, with an overall accuracy of 95%-97% as indicated by receiver operating characteristic (ROC) curve analysis. We therefore propose that blood cell-derived RNA may have significant value for performing diagnostic functions and identifying disease biomarkers in schizophrenia and BPD

 La plate-forme de production de puces à ADN d'Evry : une des trois plates-formes pivot du nouveau programme ResoGen.  (communiqué CEA/SGF 7/10/2004 )

La plate-forme de production de puces à ADN d'Evry (CEA) a été sélectionnée avec les plates-formes de Sophia-Antipolis (CNRS) et de Strasbourg (CNRS-Inserm), pour assurer, dés à présent, la fabrication et l'analyse de deux puces sur lames de verre destinées à l'étude en parallèle de la totalité de l'expression des gènes de ces deux espèces.

La réalisation et l'analyse de ces lames s'inscrit dans le cadre du nouveau programme « ResoGen », programme de ressources génomiques partagées, mis en place par le Réseau National Genopole ® le 7 octobre 2004.

Né de la volonté de développer une expertise complète dans un champ d'investigation stratégique pour la recherche en génomique et d'en partager ressources et résultats, ce programme vise trois objectifs :

• Créer des ressources dans le domaine de la recherche en génomique afin de répondre aux besoins récurrents et convergents des laboratoires académiques
• Partager ces ressources sous respect d'une charte d'utilisation définie par le consortium ResoGen ;
• Transmettre, à terme, dans le domaine public les résultats des recherches ainsi facilitées.

La maîtrise de la conception des puces, de leur production, de leur analyse, du stockage et de l'interprétation des résultats, nécessitent des compétences particulières en bio-informatique, biologie moléculaire, sciences de l'ingénieur, informatique, statistiques,… présentent au sein de plates-formes spécialisées. Assurer la production et l'analyse des puces au sein de plates-formes clairement identifiées garanti une uniformisation des méthodes expérimentales dans la fabrication et l'utilisation des puces, favorise la mise en œuvre d'une démarche qualité sur les sites producteurs et enfin, offre la possibilité d'une réduction des coûts d'achat globaux en réactifs.

La mise à disposition des laboratoires académiques des différents organismes (CEA, CNRS, Inserm, Inra et université) de lames pangénomiques humaine et murine constitue donc l'une des premières ressource de ce nouveau programme  mis en place par le Réseau National Genopole ® (agence de moyens et structure de coordination des huit genopoles régionales). Etablies à partir de deux collections d'oligonucléotides, ces deux lames couvrent l'essentiel des ARN décrits à ce jour chez l'homme (27000 sondes distinctes) et la souris (25 000 sondes distinctes). Elles permettent l'étude, en parallèle, de la totalité de l'expression des gènes de ces deux espèces.

C'est dans ce cadre, que la plate-forme de production de puces à ADN d'Evry (CEA), reconnue comme l'une des plus performantes du dispositif national, assure, avec les plates-formes de Sophia antipolis (CNRS) et de Strasbourg(CNRS-Inserm), la fabrication et l'analyse de ces deux lames.

Ce programme prévoit par ailleurs la mise en place en accès libre et gratuit d'une procédure de validation des sondes, aboutissant à une meilleure définition des sets les mieux adaptés ainsi qu'un aide à la publication des données obtenues à travers un portail Internet dédié.

Inauguration à l'HEGP le 16 juin 2006 de la première plate-forme pour les puces à ADN, Roche AmpliChipP450

Ces puces à ADN permettent d'analyser le profil génétique des génes CYP2D6 (AD tricycliques, neurolesptiques, benzodiazépines en particulier)  et CYP2C19, impliqués dans le métabolisme de 25% des médicaments. La posologie adaptée à chaque patient peut ainsi être calculée..

Cytochrome P450 genotyping: the UK perspective

Claire L McLeod, Rumona Dickson, Katherine Payne, Munir Pirmohamed, and Thomas Walley   (18 April 2007)

---

 Dear Editor, In last weeks BMJ, Roy Perlis[1] provided a cogent overview of cytochrome P450 (CYP450) testing for prescribing antidepressants. He emphasised the lack of evidence supporting the use of CYP450 testing to improve outcomes in patients treated with antidepressants, and the need for well designed trials before CYP450 testing is used in practice. This argument was supported by evidence from the recent US Agency for Healthcare and Research Quality (AHRQ) review,[2] which attempted to assess the clinical and economic value of CYP450 testing for prescribing antidepressants, in particular the selective serotonin reuptake inhibitors. The work done by the AHRQ, however, is just the beginning. Antidepressants are only one potential area of application for CYP450 testing (in particular the isoform CYP2D6); antipsychotics represent another major area.

In UK clinical practice, mental health is recognised as a major challenge and as such it is one of the nine national service frameworks.[3] Depression and schizophrenia are two of the most exigent conditions, being both complex to diagnose and treat. The large amount of inter-individual variability in patient response to therapy is associated with adverse drug reactions or therapeutic failure, which have important implications for both the patient and the NHS. The inter-individual variability to therapy may in part be explained by differences in the target drug receptors, the transport proteins responsible for transporting the drug to its target and the enzymes responsible for metabolising the drug to its excretable form, as well as diet and lifestyle factors.

The National Institute for Health Research Health Technology Assessment program in the UK has commissioned our group (LRiG) to undertake a review of the clinical and cost effectiveness of CYP450 testing for prescribing antipsychotics and antidepressants. This review will particularly focus on the Roche AmpliChip®, which was approved by the Food and Drug Administration in December 2004. The test is intended to identify CYP2D6 and CYP2C19 genotypes, and can categorise patients as poor, intermediate, extensive, or ultra-rapid metabolisers.

The Institute for Prospective Technological Studies of the Joint Research Centre of the European Commission is also reviewing the evidence available to support CYP2D6 testing in clinical practice for patients with psychiatric conditions. In addition, this study aims to identify the information required to develop a model to evaluate the cost-effectiveness of CYP2D6 testing.

The results of these studies will not only be of relevance to the UK in assessing whether CYP450 testing represents a cost-effective strategy when prescribing antipsychotics and antidepressants, but may also assist in supplying data which will inform the development of robust clinical trials. These clinical trials will need to not only determine the clinical utility of the test, but also provide estimations of resource utilisation in order to furnish economic models with robust parameter estimates. This latter issue is of particular concern for publicly funded healthcare systems such as the NHS, which have to ensure that scarce resources are efficiently allocated.

References

1 Perlis R. Cytochrome P450 genotyping and antidepressants. BMJ. 2007 14 April;334(759).

2 Matchar D, Thakur M, Grossman I, McCroy D, Orlando L, Steffens D, et al. Testing for cytochrome P450 polymorphisms in adults with non-psychotic depression treated with SSRIs: Agency for Healthcare and Research Quality; 2006.

3 NHS. Mental Health NSF. 1999 [cited; Available from: http://www.dh.gov.uk/assetRoot/04/07/72/09/04077209.pdf

Competing interests: None declared

 

Pharmacogenetics and drug therapy in psychiatry--the role of the CYP2D6 polymorphism.

Vandel P,  Talon JM     Haffen E,    Sechter D.

Curr Pharm Des. 2007;13(2):241-50.

Service de Psychiatrie et Psychologie Medicale, CHU 25030 Besancon, France. pvandel@chu-besancon.fr

The importance of pharmacogenetics in medicine is growing with the identification of genetic variability by faster screening methods using automatic sequencers. A particularly interesting finding is that apart from environmental and psychological factors, drug response may be influenced by several biological factors as a result of genetic determinants leading to interindividual variability. Several mutations in genes coding for enzymes of the drug metabolizing system, as well as for neurotransmitter receptors or degrading enzymes and monoamine transport proteins, have been identified and investigated in psychiatry. But, despite the fact that some genetic polymorphisms of enzymes (mainly cytochrome P450 2D6) are well known, the application of pharmacogenetics as a therapeutic tool for improving patient care is rare. This review has three parts. In the first an overview is given of CYP450 characteristics and the genetic polymorphisms of interest to psychiatry. In the second the clinical implications of the CYP2D6 polymorphism are reviewed and in the third part other aspects on pharmacogenetic research in psychiatry are discussed. The aim of our review is to promote the application of pharmacogenetics in everyday clinical practice.

  Selegiline transdermal system: an examination of the potential for CYP450-dependent pharmacokinetic interactions with 3 psychotropic medications.

• Azzaro AJ, Ziemniak J,  Kemper E,  Campbell BJ,   VanDenBerg C.     J Clin Pharmacol. 2007 Feb;47(2):146-58.

Chief Scientific Officer, Somerset Pharmaceuticals, Inc, Rocky Point Center, 3030 North Rocky Point Drive, Suite 250, Tampa, FL 33607, USA.

Selegiline transdermal system (STS) is a recently approved monoamine oxidase inhibitor antidepressant. This article reports results from 3 studies examining the potential for cytochrome P450-dependent pharmacokinetic interactions between STS and 3 psychotropic medications that might be coadministered. Three open-label, randomized, Latin square, 3-sequence crossover design studies were conducted with healthy volunteers to determine the pharmacokinetic parameters of STS 6 mg/24 h and test drug (alprazolam, olanzapine, or risperidone) when administered alone and concomitantly. All pharmacokinetic parameters of interest were unaltered following selegiline or test drug monotherapy when compared to concomitant therapy. This was confirmed by least squares mean ratios and their 90% confidence intervals of log(e)-transformed C(max) and AUC(tau) values, using either standard bioequivalence criteria of 80% to 125% or study-defined 70% to 143% boundary criteria. These results demonstrate that STS 6 mg/24 h may provide an antidepressant option that is unlikely to result in CYP450-mediated pharmacokinetic drug-drug interactions.

PMID: 17244765 [PubMed - indexed for MEDLINE]

   Expression genomics in breast cancer research: microarrays at the crossroads of biology and medicine
Lance D Miller and Edison T Liu
Genome Institute of Singapore, 60 Biopolis Street, #02-01, Singapore 138672

Breast Cancer Research 2007, 9:206     doi:10.1186/bcr1662, published 26 mars 2007

The electronic version of this article is the complete one and can be found online at: http://breast-cancer-research.com/content/9/2/206

ABSTRACT 

Genome-wide expression microarray studies have revealed that the biological and clinical heterogeneity of breast cancer can be partly explained by information embedded within a complex but ordered transcriptional architecture. Comprising this architecture are gene expression networks, or signatures, reflecting biochemical and behavioral properties of tumors that might be harnessed to improve disease subtyping, patient prognosis and prediction of therapeutic response. Emerging 'hypothesis-driven' strategies that incorporate knowledge of pathways and other biological phenomena in the signature discovery process are linking prognosis and therapy prediction with transcriptional readouts of tumorigenic mechanisms that better inform therapeutic options

INTRODUCTION

DNA microarrays are tools for assessing the functional dynamics of genes and genomes in a highly parallel fashion. Historically defined as ordered collections of DNA probes for the specific detection of complementary DNA targets, microarrays enable genome-wide surveys of the relative abundance of mRNA transcripts, the high-resolution mapping of genomic copy number alterations, the identification of binding sites of nucleic acid-binding proteins, and the comprehensive analysis of single-nucleotide polymorphisms (SNPs). Although microarray technology and its applications have evolved considerably over the years to meet a growing range of genomic challenges [1], the classical format for microarrays in interrogating the transcriptome (that is, expression microarrays) has been a key technology for discovery in functional and medical genomics.

Since the mid-1990s, expression microarrays have been extensively applied to the study of cancer, and no cancer type has seen as much genomic attention as breast cancer. The most prolific area of breast cancer genomics has been the elucidation and interpretation of gene expression patterns that underlie biological and clinical properties of tumors. In a seminal study that analyzed expression profiles of primary breast tumors, Perou and colleagues [2] showed that the vast and complex transcriptional data generated by microarrays contained discernible patterns of gene expression that related to tumor biology and behavior. Through hierarchical cluster analysis, numerous 'gene clusters' could be recognized as biologically distinct networks reflecting the phenotypic wiring of individual tumors. These 'molecular portraits' revealed information on multiple biological tiers – from broad tumorigenic properties to discrete biochemical pathways to intra-tumor tissue heterogeneity – and led to the discovery of an 'intrinsic' gene subset that could distinguish between multiple new cancer subtypes on the basis of fundamental tumor properties associated with cell-type origin. These subtypes, termed Luminal A/ER+, Luminal B/ER+, Normal Breast-like, ERBB2+, and Basal-like (that is, the Perou–Sorlie subtypes), were subsequently shown to be stable and reproducible classes observable in different patient populations, and correlated significantly with tumor recurrence and patient survival [3,4].

Together, these studies provided early evidence that the transcriptional circuitry of breast cancer, as revealed by microarrays, could not only provide novel insights into the biology of cancer but could also accurately identify certain previously discernible clinical phenotypes (for example estrogen receptor (ER) status, HER2/neu expression, and proliferation rate) and robustly define new molecularly informed classifications that delineate novel disease entities associated with patient outcomes.

More recently, new investigative techniques have begun to refine our understanding of the breast cancer onco-transcriptome and how it relates to tumor biology and behavior. From this vantage point, the intersections between pathological mechanisms and clinical endpoints are being explored with new vigor. Traditional microarray methods for uncovering prognostic expression signatures, based primarily on empirical associations not requiring plausible biological relevance of the markers used, are now sharing the stage with mechanistically motivated strategies driven by knowledge of oncogenic pathways and processes. More commonly, experimental approaches show that patho-biological simulations performed in vitro reveal transcriptional configurations predictive of tumor biology in vivo. Together, these functional genomics strategies are changing the scientific process of breast cancer biomarker discovery, towards one that incorporates mechanistic knowledge.

- - - - -  - - - - -  - - - -  - - - - - 

FUTURE CHALLENGES

Expression arrays initially began simply as a method of multiplexing single gene discovery, akin to running several thousand quantitative RNA dot-blots. From this one-dimensional approach evolved the current state of the art: expression profiling to uncover pathway regulation of gene expression and to define molecular classes on the basis of integration of the total signals experienced by the cancer cell. Fundamental to this transition has been the ability to analyze and model complex systems made possible by mathematical algorithms coupled with computational capacity. It is in this realm of complexity analysis that the future of array-based expression genomics will lie. One can clearly see some of the more immediate areas of expansion.

First, data content can increase. Other characteristics of the transcriptome such as exon usage and noncoding RNAs (including microRNAs) are not well covered by the existing array technologies and their inclusion would inevitably result in greater precision and comprehensiveness. Exon junctions could conceivably be included in the battery of tests yet to be applied. Of course, this will require greater array capacity in terms of encompassing more probes in smaller spaces. Given the advances in microelectronics, those possibilities are currently available but are perhaps not cost-effective for broad biological experimentation.

Second, the analytical systems can be more informed. Although the output of individual probes can be viewed as events that are independent from that of any other probe, biologically, the degrees of freedom of transcriptional systems are already constrained by biochemical and even evolutionary reality. Thus, gene X is always coordinately expressed with gene Y, or gene A is always upstream of gene B, or proteins C, E, and F are always in a complex and function only as a unit, never alone. These genetic, biochemical, or physiologic relationships validated by other means can be incorporated as 'priors' as we seek higher orders of interaction.

Last, metadata sets will emerge that will markedly expand the ability to validate and to model transcriptional networks of biological and clinical significance. This is already taking place with Oncomine [36], and follows the success of other genomic databases. As a result of standardization, the availability of large numbers of data sets describing the transcriptional behavior of breast cancers has permitted the validation of local observations in silico. In the context of prognosis, the performance of expression signatures can now be validated in and compared across numerous independent cohorts [4,26,28,50], and analyzed in combination for synergistic interactions [30]. At some point, the content of the expression metadata sets for breast cancer will be large enough to sustain continuous activity in data mining, hypothesis generation, and validation. This requires the inclusion of detailed clinical information. In some medical research communities, this metadata set approach is more advanced. Comparative and evolutional geneticists use the growing number of complete genomes in publicly available databases as their primary substrate for investigation. In molecular epidemiology, whole-genome SNP databases with linked clinical data are being made available to qualified researchers for analysis and data mining.

These trends will have a great impact on breast cancer research. The advantage will be the ability to be comprehensive and yet precise at the same time, and the speed of discovery will be breathtaking. The challenge, however, will shift to organizational issues. How fast can we validate new marker sets? What kind of incentives can we use to encourage groups to share primary data? How can we sustain teams of computer scientists, basic molecular biologists, molecular pathologists, and oncologists to meet these challenges?

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