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WO2006135904A2 - Procede permettant d'obtenir de meilleurs resultats pour des applications qui utilisent directement ou indirectement des resultats de dosage d'expression genetique - Google Patents

Procede permettant d'obtenir de meilleurs resultats pour des applications qui utilisent directement ou indirectement des resultats de dosage d'expression genetique Download PDF

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WO2006135904A2
WO2006135904A2 PCT/US2006/023046 US2006023046W WO2006135904A2 WO 2006135904 A2 WO2006135904 A2 WO 2006135904A2 US 2006023046 W US2006023046 W US 2006023046W WO 2006135904 A2 WO2006135904 A2 WO 2006135904A2
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cells
drug
cell
results
cell sample
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WO2006135904A3 (fr
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David E. Kohne
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • G01N33/5008—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics
    • G01N33/502—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing non-proliferative effects
    • G01N33/5023—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells for testing or evaluating the effect of chemical or biological compounds, e.g. drugs, cosmetics for testing non-proliferative effects on expression patterns
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis

Definitions

  • the present invention relates to methods for obtaining gene expression results which are improved through the use of enhanced normalization, and the use of those improved results in additional gene expression-based methods and analyses.
  • RN RNA transcript number
  • NAS RNA transcript expression assay result
  • prior art gene expression analysis comparison methods and the production of prior art gene comparison assay measured particular gene NAS ratio (NASR) and normalized differential gene expression ratio (N-DGER) and other equivalent results were extensively described and discussed in a prior filed provisional patent application (148) and co-pending U.S. application 11/421,961, and in references cited in those document and cited herein. That submitted provisional patent application and non-provisional applications and their cited references are incorporated by reference in their entireties into the present patent application.
  • a goal of gene expression analysis is to utilize the measured gene expression assay results to find one or more relationships or patterns in the analysis results, which have utility for one or more purposes.
  • a relationship can be simple, and involve the direct comparison of the gene expression analysis assay measured RN or abundance values or normalized assay signal (NAS) values or their equivalents, for particular genes associated with one or more biological samples, in order to produce a particular gene comparison N- DGER or NASR value.
  • NAS normalized assay signal
  • the N-DGER value may represent the comparison of the extent of expression of: the same particular gene in different cell samples, i.e. an SGDS comparison; different particular genes in different cell samples, i.e. a DGDS comparison; or different genes in the same cell sample, i.e. a DGSS comparison.
  • Such information is often used by the prior art to identify particular genes which may be drug candidates, particular genes which are associated with a particular disease situation, particular genes which are affected by particular toxic or nontoxic compounds of any kind, particular genes which are associated with a particular therapeutic process or compound, particular genes which are associated with a particular biological state such as a cell cycle or differentiated state or some other state, and many other purposes.
  • Such prior art usage of particular gene N-DGER values can involve just one particular gene N-DGER value, or two or more such values.
  • the use of multiple particular gene N-DGER values can require complex analysis.
  • Prior art has analysed a large number of biological situations by comparing the particular gene N-DGER values. These include but are not limited to, each invention related area described herein.
  • a prior art assay measured particular gene abundance or RN or RAS result for a cell sample is also believed to be biologically accurate by the prior art.
  • Prior art often produces and further analyses these results for multiple particular genes in one cell sample to produce a gene expression profile, herein termed a GEP, for the cell sample.
  • GEP gene expression profile
  • Prior art produced GEPs are also believed to be biologically accurate by the prior art.
  • Prior art often further analyses gene expression profiles for diseased, treated, different and normal cell samples in order to identify one or more particular genes whose expression is characteristic for or specific for the diseased treated, different, or biological state (57-63, 82- 97). Such gene expression profiles are also further compared and/or analysed in order to discover and identify gene expression regulation pathways.
  • Prior art measured gene expression abundance and/or RN and/or NAS and/or NASR and/or N-DGER results are often used directly or indirectly in a further application, herein termed a higher order application, to produce higher order application results.
  • prior art measured gene expression assay abundance and/or RNA and/or NAS and/or NASR and/or N-DGER results are often directly and indirectly used by the prior art in further applications which analyse these results to produce further application results. This is an example of the direct use of prior art measured gene expression assay results in a further application.
  • a zero order application result an application which directly utilizes measured gene expression assay measured abundance and/or RN and/or NAS and/or NASR and/or N-DGER results is termed a zero order application result, and a zero order application is a higher order application.
  • Prior art also often directly or indirectly uses zero order application results in a further application, herein termed a first order application, to produce first order application results.
  • a first order application is also a higher order application.
  • a first order application directly uses zero order application results, and indirectly uses gene expression assay measured abundance and/or RNA and/or NAS and/or NASR and/or N-DGER results. Examples of the higher order application use of prior art gene expression results are discussed below.
  • Prior art measured gene expression abundance and/or RN and/or NAS and/or NASR and/or N-DGER results from one or another of these invention related areas are often further analysed by more complex analysis methods.
  • Such a prior art gene expression analysis result can be supervised or unsupervised.
  • each gene expression result is associated with one or more biological or other characteristic, and then analysed.
  • a typical example of a supervised analysis is the classification of biological samples. Such analysis has been used widely in disease situations, especially for the cancer area.
  • Unsupervised analysis involves looking for structure and relationships in the gene expression data itself.
  • a typical example of such unsupervised analysis is gene clustering, i.e. discovering sets of genes with similar expression patterns.
  • sample clustering i.e.
  • References 1-12 contain a variety of discussions, examples, and references pertaining to unsupervised or supervised gene expression data analysis.
  • References 1-147 present a variety of different biological, medical, pharmaceutical, basic research, manufacturing, agricultural, and industrial, associated analyses of these types. The purpose of each of these analyses as well as others, involves one or more of the following. Classifying biological samples. Defining cell or organism regulatory pathways and networks. Defining disease pathways and networks. Defining disease susceptibilities. Defining the response to therapy. Predicting response to therapy, and other clinical outcomes. Determining compound and treatment toxicity. Determining response to genetic changes. Drug discovery, development, manufacturing and use. Determining metabolic interrelationships and regulatory pathways and networks. Determining a wide variety of systems biology interrelationships and insights. Such analyses represent only a fraction of the uses which are possible. Examples of many of these and other uses are described in one or another of references 1-147. SUMMARY OF THE INVENTION
  • the present invention contributes heavily to the effectiveness and reliability of such applications of gene expression determinations through the utilization of gene expression study and application results which are improved through the use of improved normalization practices.
  • the invention concerns a method for producing an improved gene expression profile(GEP) for one or more cell samples.
  • the method involves determining one or more particular gene(PG) improved results(IR) for at least one cell sample; and compiling the PG IR values to produce one or more forms of improved GEP for said cell sample.
  • the cells in the cell sample can be of essentially any type, for example, normal cells; abnormal cells; untreated cells; treated cells; physically treated cells; chemically treated cells; drug treated cells; bioactive compound treated cells; cells from a psychologically treated individual; drug candidate treated cells; toxic compound treated cells; differentiated cells; undifferentiated cells; biological agent infected cells; virus infected cells; cells from an individual infected by a pathogenic bacterium; cells from an individual infected by a eukaryotic microbe; neoplastic cells; cancer cells; diseased cells; pathological cells; in vitro cultured cells; in vitro cultured cells of an immortalized cell line; in vivo sampled cells; in vivo sampled cells of a particluar tissue; prokaryotic cells; eukaryotic cells; temporally treated cells; mammalian cells; mouse cells; rat cells; and human cells.
  • Cells can further be of a particular age, development
  • one or a plurality of cell samples can be analyzed, e.g., at least 2, 3, 5, 10, 20, 50, 100, 200, 300, 500, 1000, or even more or a number in a range of 1-5, 2-10, 11-50, 51-100, 101-500, 501-1000, 1000-10000, among others.
  • improved results(IR) for a plurality of different PGs are obtained and/or used, e.g., at least 2, 3, 5, 10, 20, 50, 100, 200, 300, 500, 1000, or even more or a number in a range of 1-5, 2-10, 11-50, 51-100, 101-500, 501-1000, 1000-10000, among others.
  • PGs of the cell sample GEP include at least one cellular RNA, e.g., mRNA, siKNA, miRNA, regulatory RNA; the GEP is improved in quantitative accuracy, qualitative accuracy, or both, interpretability, reproducibility, intercomparability, and/or utility as compared to a GEP compiled from results which are not IRs; determination of one or more particular geen improved results is performed using one or more microarray assays, RT-PCR, an affinity binding media, nuclease protection method, and/or a clone counting method.
  • mRNA e.g., mRNA, siKNA, miRNA, regulatory RNA
  • the GEP is improved in quantitative accuracy, qualitative accuracy, or both, interpretability, reproducibility, intercomparability, and/or utility as compared to a GEP compiled from results which are not IRs
  • determination of one or more particular geen improved results is performed using one or more microarray assays, RT-PCR, an affinity binding media, nuclea
  • Another aspect concerns a method for identifying a particular cell sample type of interest, and involves comparing gene expression profiles (GEPs) of at least one cell sample type of interest and at least one reference cell sample type of interest, and identifying the cell sample type of interest based on best match comparison of the respective GEPs, e.g., GEPs which incorporate expression results for a plurality of PGs.
  • GEPs gene expression profiles
  • the method can also include identifying, for a plurality of PGs, which PGs are differentially expressed in the cell sample of interest, and/or utilizing the method of the first aspect above (e.g., as embodiment as indicated or otherwise described herein) to determine a GEP(s) for one or more cell samples of the cell sample type of interest or for one or more cell samples of a specified reference cell sample type of interest, or both, and incorporating those results in at least one GEP.
  • one or more regulated genes are detectably expressed in both the cell sample of interest and the reference cell sample type; one or more up regulated genes is not detectable as being expressed in one of the cell samples; a cell type is as indicated for the aspect above; the cell sample(s) of interest include a plurality of separate different cell or cell sample types (e.g., at least 2, 3, 4, 5, 7, 10, 20, 30, 50, 2-5, 5-10, 10-20, 20-50, or even more);
  • Another aspect provides a method for identifying a set of genes which may be used to identify or characterize a particular cell sample type of interest, and includes determining improved gene expression results for a plurality of particular genes (PGs) in the particular cell sample or sample (or cell sample type(s)) of interest and in at least one reference cell sample type; and analyzeing and identifying PGs which are differentially expressed in the cell sample of interest compared to the reference cell sample type.
  • the method can also include selecting at least a subset of the differentially expressed genes as the set of genes which may be used to identify or characterize the cell sample or cell sample type of interest.
  • the improved gene expression results are compiled as a GEP (directly or following analysis) for one or more cell samples of the the cell samples or cell sample types of interest or for one or more cell samples of a specified reference cell sample type of interest, or both; and the process of identifying PGs which are differentially expressed involves comparing gene expression profiles (GEPs) of at least one cell sample or cell sample type of interest and at least one reference cell sample type of interest.
  • GEPs gene expression profiles
  • one or more regulated genes are detectably expressed in both the cell sample or cell sample type of interest and the reference cell sample type; one or more up regulated genes is not detectable as being expressed in one of the the cell samples or cell sample types; cells of a type as indicated above are used in a cell sample;
  • the selecting involves identifying from a set of differentially expressed PGs a discrimination set of one or more PGs which can be used to reliably, selectively, and specifically identify individual cell samples of the type of interest and to distinguish those cell sample types of interest from the specific reference cell sample type.
  • the discrimination set can also distinguish the cell sample type of interest from a plurality of other cell sample types (e.g., cell sample types from other organisms, other growth stages, other tissues, cells subjected to other chemical and/or physical treatments, and the like).
  • the bases for selection includes the magnitude of the differential expression for a particular gene; the consistency of occurrence and direction of the differential expression for a particular gene or genes.
  • the selection process or method or the application involves use of a linear discriminant method, a K- nearest neighbor method, a neural network method, a decision tree method, a partially supervised method, a class discovery method, a hierarchical agglomerative clustering method, a hierarchical divisive clustering method, a non-hierarchical K-means method, a self organizing maps and trees method, a principal component analysis method, a relationship between clustering and a principal component method, a gene shaving method, a clustering in discretised space method, a graph based clustering method, a Bayesian model method, a fuzzy clustering method, a clustering of genes and samples method, a data mining analysis method, a systems biology analysis method, an independent component analysis method; and/or a direct comparison method.
  • a related aspect concerns an improved set of cell sample type discrimination gene set identifier nucleic acid molecules, which includes a set of nucleic acid molecules which provide specific detection of individual particular genes identified by the methods of the preceding aspect, which reliably, selectively, and specifically identify individual cell samples of the type or types of interest, or distinguish the cell sample type or types of interest from at least one specific reference cell sample type, or both, based on improved gene expression results.
  • the set of identifier nucleic acid molecules includes a set of labeled or unlabeled or both hybridization probes, a set of capture oligonucleotides (e.g., incorporated in an oligonucleotide microarray), a set of amplification primers; the molecules provide identification of cells of a cell type as indicated above, e.g, a cancer cells, cells infected by an infectious agent, cells of a developmental state, cells exposed to or treated by a bioactive molecule, and/or cells exposed to a defined environmental condition.
  • a cell type e.g, a cancer cells, cells infected by an infectious agent, cells of a developmental state, cells exposed to or treated by a bioactive molecule, and/or cells exposed to a defined environmental condition.
  • An aspect similar to the aspect two above provides a method for identifying improved sets of particular genes for an application utilizing gene expression results, where the method involves obtaining improved gene expression results for at least one application pertinent gene, and selecting a discrimination gene set based on differential gene expression of the gene in at least one application pertinent cell sample type.
  • application pertinent cell type or types
  • the discrimination gene set is selected utilizing the method of an embodiment of the aspect two above
  • the improved gene expression results are obtained utilizing the method of any of the embodiments of the first aspect above.
  • the application includes one or more of a data mining analysis, a systems biology analysis, a regulatory pathway identification, or analysis, or monitoring, or any two, or all three, a drug or bioactive compound or biomarker discovery and identification, a drug or bioactive compound or biomarker validation, a drug or bioactive compound or biomarker development, a drug or bioactive compound efficacy analysis, a drug or bioactive compound safety evaluation, a drug or bioactive compound toxicity evaluation, a drug or bioactive compound QA/QC evaluation, a drug or bioactive compound manufacturing monitoring, a drug or bioactive compound or biomarker related diagnostic test development or use or both, a particular cell sample of interest related diagnostic test development or use or both, a disease or pathologic state or both detection or evaluation or both, a disease or pathologic state or both detection or evaluation or both, before and after administration of a therapeutic treatment, a disease or pathologic state or both detection or evaluation or
  • the method also includes providing a set of a set of particular gene identifier nucleic acid molecules (e.g., as described for the preceding aspect), where members of the set of nucleic acid molecules provide specific detection of corresponding members of said discrimination gene set; such set can, for example, include at least 2, 3, 4, 5, 7, 10, 15, 20, 50, or even more different identifier nucleic acid molecules.
  • the invention also concerns as aspect providing a method for producing improved results for an application which directly or indirectly utilizes at least one gene expression , profile for at least one particular gene, where the method involves utilizing at least one improved gene expression profile (GEP) directly or indirectly in the application, thereby producing improved application results.
  • GEP improved gene expression profile
  • the GEP is produced according to an embodiment of the first aspect above; the GEP is a particular cell sample or cell sample type GEP; the GEP includes a cell sample GEP which includes a set of one or more regulated PGs which may potentially be used (or can be used or are actually used) to selectively and specifically identify a particular cell sample type or a particular cell sample type physiological state (PS) of interest or both.
  • the GEP is a particular cell sample or cell sample type GEP
  • the GEP includes a cell sample GEP which includes a set of one or more regulated PGs which may potentially be used (or can be used or are actually used) to selectively and specifically identify a particular cell sample type or a particular cell sample type physiological state (PS) of interest or both.
  • PS cell sample type physiological state
  • Particular embodiments involve use of an analysis method as indicated above; the application includes a component or components as indicated above.
  • Another aspect concerns an improved method for identifying regulated particular genes (PGs) which are regulated in response to exposure to a particular treatment.
  • the method involves comparing at least one improved gene expression profile (GEP) (e.g., produced by the method of an embodiment of the first apect above) incorporating improved results for at least one cell sample exposed to the treatment with at least one improved gene expression profile for at least one reference cell sample, thereby identifying PGs with differential expression in the treated cell sample, and can also include subjecting cells in the treated cell sample to the treatment and cells of the reference cell sample are not subjected to the treatment, e.g., the sample and reference cells can be matched except for the treatment.
  • GEP improved gene expression profile
  • the method can also involve utilizing one or more selection processes to identify and rank the regulated PGs based on the magnitude and direction of the change in expression level for PGs in the treated cell sample.
  • the method can also include utilizing one or more further selection processes to evaluate the suitability of each of the regulated PGs for the purpose of the comparison, and interpreting and ranking and arranging the members of the set of regulated PGs and their characteristics in a manner which reflects their suitability of use for the purpose of the said comparison and identification; the selection process can include one or more analysis techniques as indicated above.
  • the method can also include exposing at least one of a plurality of matching cell samples to a treatment of interest thereby forming a treated cell sample, while at least one other of said cell sample portions is not exposed to said treatment of interest, and constitutes a reference sample, and using the method of an embodiment of the first aspect to produce a GEP for each of the cell samples.
  • the treatment can include one or more (e.g., any combination of the listed treatments taken 2, 3,4 at a time) of exposure to a compound in a compound screening library, exposure to a pharmaceutical drug screening hit, exposure to a pharmaceutical drug lead, exposure to a pharmaceutical drug, exposure to a potentially toxic compound, exposure to a toxic compound, exposure to an illegal drug, exposure to nucleic acid binding compound, exposure to an infectious agent, exposure to a virus, exposure to a bacterium, exposure to radiation, exposure to light, exposure to ultraviolet light, exposure to a temperature shift, exposure to a biological stress condition, exposure to a psychological stress condition, exposure to a physical condition, exposure to a bioactive compound, and exposure to an environmental condition;
  • the regulated genes are as indicated above;
  • the cell type(s), PGs, RNA, improvement type, and/or assay type is as indicated above;
  • the process of selecting genes and/or discrimination sets of PGs is as indicated above; a set
  • another aspect concerns a method for producing higher order application results which are improved in one or more of qualitative accuracy, quantitative accuracy, interpretability, reproducibility, intercomparability, and utility, relative to prior art produced higher order application results, by using a method for producing improved GEPs as described for aspects and embodiments above to produce improved results, and utilizing one or more of those improved results directly or indirectly in a higher order application to produce higher order application results which are improved in one or more of qualitative accuracy, quantitative accuracy, interpretability, reproducibility, intercomparability, and utility, relative to prior art produced higher order application results.
  • the higher order application is an application or includes an application component as indicated above
  • Yet another aspect concerns a method for producing improved information and results concerning the physiological state of cells in a cell sample (e.g., from an individual organism or tissue, or type of organism or tissue) of a particular cell type of interest.
  • the method involves utilizing one or more particular physiological state gene expression profiles (PS GEPs) to identify the physiological state of different samples of the particular cell type of interest, where particular PS GEPs for the particular cell type of interest selectively distinguish a particular physiological state(PS) for the particular cell type of interest, and where the PS GEPs are improved by the incorporation of improved gene expression results and where the information and results are improved in one or more of qualitative accuracy, quantitative accuracy, interpretability, reproducibility, intercomparability, and utility, relative to prior art produced information and results.
  • PS GEPs physiological state gene expression profiles
  • the method can also include monitoring the physiological state and analyzing the monitoring results to evaluate and determine the physiological state of the particular cell type sample of interest over time and/or under changing or changed conditions.
  • the method of an embodiment of the first aspect above is utilized to produce one or more physiological state gene expression profiles (PS GEPs) for the particular cell type of interest which selectively distinguish a particular physiological state(PS) for the particular cell type of interest.
  • PS GEPs physiological state gene expression profiles
  • eh cell type is as indicated above; the cell type is a eukaryotic cell type, a prokaryotic cell type, a plant cell type, a bacterial cell type, a pathogenic bacterial cell type, a yeast cell type, a fungal cell type, a mammalian cell type, a human cell type, an in vitro grown cell type, an immortalilzed cell line type, an in vivo grown cell type, an infectious organism or agent infected cell type, a virus infected cell type, a genetically modified cell type, and/or an in vivo or in vitro cell type used for producing or manufacturing a pharmaceutical agent or protein or small molecule or lipid.
  • the particular physiological state is or includes a cell cycle stage related PS, a cell growth state related PS, a cell size related PS, a differentiated state related PS, an undifferentiated state related PS, a toxic state related PS, a cell age related PS, an infectious state related PS, a nutritional state related PS, a drug or bioactive agent treatment of the cell type related PS, an environmental state related PS, a physical treatment of the cell type related PS, a psychological treatment of the cell type related PS, a chemical treatment of the cell type related PS, and/or a hormone treatment related PS.
  • the invention also concerns an aspect providing a method for producing improved clinical trial information and results (or therapeutic evaluation information and results) which are improved in qualitative accuracy, quantitative accuracy, interpretability, reproducibility, intercomparability, or utility, relative to prior art produced such information and results, for the evaluation of one or more or all of the safety, dose, or efficacy of a drug or bioactive agent(BA), where the method includes monitoring one or more improved gene expression profiles (GEPs) for drug or BA treated and untreated particular cell types of interest respectively for the appearance of one or more drug or BA treatment desired effects or undesired effects or both in the treated cell types of interest, where the improved GEPs incorporate improved gene expression results.
  • GEPs gene expression profiles
  • Certain embodiments also include analyzing the results of the monitoring to evaluate the safety, dose, and efficacy of the drug or BA treatment of the particular cell types of interest, and/or include using the method of an embodiment of the first aspect to produce one or more of the particular GEPs.
  • the cell type(s) is or includes a cell type as indicated above; the cell type is or includes eukaryotic, prokaryotic, plant, bacteria, yeast or fungus, mammalian, human, cell types infected with a biological or other infectious agent, normal cell types, abnormal, untreated, treated, psychological treated, toxic compound treated, differentiated, undifferentiated, neoplastic, in vitro grown, in vivo, diseased, and pathologic.
  • the GEP is or inlcudes a complete GEP for the treated and untreated cell type or types of interest; the GEP is or includes a partial GEP specific for a particular treated or untreated cell type or types of interest; the GEP is or includes a combination complete and partial GEPs for the treated or untreated cell type or types of interest; the desired or undesired effect is or includes the known desired effects of the drug or BA on the cell types of interest, the unknown potential desired effects of the drug or BA on the cell types of interest, the known undesired effects of the drug on the cell types of interest, or the unknown potential undesired effects on the cell types of interest.
  • a further aspect concerns a method for producing improved information and results concerning the efficacy and toxicity or both or the desired and undesired effects or both, of treatment for a patient being treated with a particular drug or bioactive agent (BA) 5 or with a combination of a plurality of drugs or BAs or both, which is improved in one or more of qualitative accuracy, quantitative accuracy, interpretability, reproducibility, intercomparability, and utility, relative to such prior art produced information and results.
  • the method involves monitoring one or more improved gene expression profiles (GEPs) of patient cell samples for drug or BA treated particular cell types of interest for the appearance and/or level of one or more drug treatment desired effects or undesired effects or both in said treated cell types of interest, where the improved GEPs incorporate improved gene expression results.
  • the method can be performed for a plurality of patients, e.g., at least 2, 3, 5, 7, 10, 20, 30, 50, 100, or more.
  • the method also includes analyzing the the monitoring results to determine the effectiveness of the treatment or undesired effects of the treatment or both, and/or using a method of an embodiment of the first aspect above to produce cell type specific GEPs for the combination of the patient cell types of interest and drug or BA of interest, and/or comparing at least one GEP for a treated cell sample from the patient with at least one untreated cell sample.
  • treated cell sample or the untreated cell sample or both is from the patient; a GEP is or includes a partial GEP specific for a particular treated or untreated cell type or types of interest; the GEP is or includes a combination complete and partial GEPs for the treated or untreated cell type or types of interest; the desired or undesired effect is or includes the known desired effects of the drug or BA on the cell types of interest, theunknown potential desired effects of the drug or BA on the cell types of interest, the known undesired effects of the drug on the cell types of interest, the unknown potential undesired effects on the cell types of interest.
  • related aspect concerns a method for producing improved patient bioactive agent treatment related health care, and involves utilizing the method of any the embodiments of the preceding aspect to determine the effectiveness of the particular drug or bioactive agent (BA) treatment in a patient, and selecting a drug or BA treatment utilizing the determination of effectiveness information.
  • BA bioactive agent
  • the selecting is or includes continuation of treatment with said drug or bioactive agent, an increase in dosage of said drug or bioactive agent, a decrease in dosage of said drug or bioactive agent, termination of treatment with said drug or bioactive agent, administration of an additional drug or bioactive agent.
  • the effectiveness information includes information on the efficacy of drug or bioactive agent in the patient, information on the safety of the drug or bioactive agent in the patient, and/or tolerance of dosage level information in said patient;
  • the bioactive agent is a food, nutritional supplement, or nutritional compound.
  • Yet another related aspect concerns a method for producing improved patient bioactive agent treatment related health care, and involves selecting treatment for a patient based on comparison of at least one improved GEP for the patient, and at least one reference GEP indicative of patient response to the drug or bioactive agent treatment.
  • the GEP for a patient can be produced by the method of an embodiment of the first aspect above.
  • the patient suffers from a disease or condition for which the presence of certain allelic variants is indicative of variation in the effectiveness of treatment with the drug or bioactive agent or indicative of differences in effectiveness of different drugs or bioactive agents; the method of an embodiment of the aspect two above is used to determine the effectiveness of the particular drug or bioactive agent (BA) treatment in a patient, and can further involve utilizing the determination of effectiveness information to select a drug or BA treatment.
  • BA drug or bioactive agent
  • the selecting is or includes continuation of treatment with the drug or bioactive agent, an increase in dosage of the drug or bioactive agent, a decrease in dosage of the drug or bioactive agent, termination of treatment with said drug or bioactive agent, or administration of an additional drug or bioactive agent.
  • the effectiveness information is or includes information on the efficacy of the drug or bioactive agent in the patient, information on the safety of the drug or bioactive agent in the patient, and/or tolerance of dosage level information in the patient.
  • the invention concerns an electronic representation of an improved gene expression profile, including electronic representations of a plurality of improved results and/or GEPs obtained by the method of an embodiment of the first aspect above and/utilizing embodiments of any of the additional embodiments above which can be used in producting an improved GEP.
  • the representation may be visible and/or may be recorded in computer memory and/or in a computer accessible data storage device.
  • a related aspect provides a method for determining improved application results for an application which directly or directly utilizes improved gene expression profile (GEP) information, where the method involves entering data describing or derived from said GEP in computer accessible form, operating on that data with a computer program comprising program steps to calculate the application results.
  • GEP gene expression profile
  • the application may be any of the applications described herein and/or may include analysis components as indicated for aspects above.
  • the present invention concerns obtaining and using improved results from gene expression assays, including, for example, the use of gene expression profiles. Such improved results are obtained due to applying correct normalization to the assay results.
  • bioactive agent refers to any treatment which produces a change or response at the cellular level for at least some cell types. Such treatments can include exposure to a chemical compound or compounds, exposure to radiation and/or light, elevated temperature, and the like.
  • cell type and “cell sample type” are used broadly to refer to cells which differ in at least one distinguishable parameter, and, unless indicated to the contrary, such types are not limited to distinctions between cells from different organisms and/or different differentiated cell classes.
  • a prior art higher order application can produce biological and/or other conclusions which are known to be valid and correct only when it is known that the gene expression results used or incorporated into the analysis are correct.
  • prior art believes and practices that the prior art produced gene expression results are correct.
  • prior art also generally believes and practices that the prior art produced gene expression result analyses which utilize the prior art gene expression results, are also correct.
  • Such prior art produced gene expression results may comprise gene expression analysis assay measured particular gene RN values or particular gene abundance values, or particular cell sample GEPs, or particular gene NAS values or equivalent values, and/or particular gene comparison NASR values or particular gene comparison N-DGER values, or equivalent values.
  • Such improved gene expression assay results comprise improved gene expression analysis assay measured particular gene RN values or particular gene abundance values or particular gene NAS values or equivalent values, and/or improved particular gene comparison N-DGER values or particular gene comparison NASR values or equivalent values.
  • the term higher order application will herein refer to any prior art known or any unknown method which directly or indirectly uses gene expression results to produce higher order application results.
  • gene expression results which are directly or indirectly used in a higher order application may comprise gene expression assay measured particular gene RN results and/or particular gene abundance results, and/or particular gene NAS results and/or equivalent results, and/or particular gene comparison NASR results or particular gene comparison N-DGER results or equivalent results.
  • Such higher order applications may refer to one or more of the above described simple particular gene comparison analysis methods, or one or more of the above described supervised or unsupervised analysis methods such as the various types of cluster analysis and principle component analysis, or one or more of the systems biology analysis methods, or one or more other known or unknown gene expression result analysis methods.
  • improved particular gene RN assay result and improved particular gene abundance assay result, and particular gene NAS assay result, and improved particular gene NASR, and improved particular gene comparison N-DGER assay result
  • particular gene RN, abundance, NAS and particular gene comparison N-DGER and NASR are defined in the glossary of said submitted provisional application.
  • improved RN, abundance, NAS, N-DGER, or NASR gene expression analysis assay result, or another equivalent assay result will be referred to as an improved result, or IR, unless otherwise noted.
  • the present invention relates to any present or future application or process which directly or indirectly utilizes or incorporates or relies on one or more IRs for the application process.
  • Such applications and processes include, but are not limited to, any prior art or future application or process which directly or indirectly utilizes or incorporates or relies on one or more gene expression assay measured particular gene RN values or particular gene abundance values or particular gene NAS values or other equivalent values, and/or gene expression comparison assay measured particular gene comparison NASR values or particular gene comparison N-DGER values or other particular gene comparison equivalent values, for the application or process.
  • Such applications or processes include, but are not limited to, gene expression data analysis methods and algorithms of all kinds and systems biology analysis algorithms and methods of all kinds which directly or indirectly utilize gene expression results, as well as any other use of analysis of gene expression results.
  • Such applications and processes can involve any known or unknown biological life form, including all known or unknown viruses, prokaryotes, and eukaryotes.
  • the invention relates broadly to basic, applied, commercial and industrial research and development of virtually all kinds which have a biological aspect.
  • the present invention relates to all areas of basic, applied, commercial, and industrial biological research including, but not limited to, the following. Biochemistry, bioinformatics, biotechnology, cell biology, chemical biology, cell therapy, cell and organ transplantation, developmental biology, ecology, endocrinology, epidemiology, evolution, genetics, gene therapy, genomics, gerontology, immunology, infectious diseases, microbiology, molecular biology, nephrology, neurology, opthamology, pediatrics, pharmacology, physiology, plant biology, psychiatry, public health, structural biology, surgery, urology, drug discovery, molecular therapeutics, epidemiology, carcinogenisis, inflammation, pain, nutrition, reproduction, virology, toxicology, pathology, dermatology, gastroenterology, musculoskeletal studies, pregnancy, pulmonary studies, breast cancer, cardiovascular studies, cerebrospinal research, allergy and asthma studies, hepatology, atherosclerosis, diabetes studies, hematology, oncology, osteoporosis studies,
  • Said invention relates to essentially all areas of marine and terrestrial basic, applied, commercial and industrial agricultural research and development. This includes most of the above mentioned areas as well as the following. Developing improved viruses, microbes, cells, plants and animals, by natural and genetic engineering means, for food production and other purposes. Terrestrial and marine virus, microbe, plant, and animal diseases of all kinds, and disease mechanisms and host-pathogen interactions. Discovery, development, validation, production and use of antiviral agents, anti microbial agents, antifungal agents, pesticides, vaccines of all kinds, plant and animal growth agents, and agricultural pharmaceutical agents of all kinds. Agricultural ecology and toxicology. Products and services which are associated with the above described areas.
  • Said invention relates to a large number of medical areas, both human and veterinary and these include, but are not limited to, essentially all areas of basic, commercial, industrial, and applied human and veterinary medical research and development. These include, but are not limited to, the following.
  • Said present invention is related to essentially all areas of human and veterinary medicine including those earlier described basic, commercial, or applied biological research areas. Further said present invention is related to essentially all areas of human and veterinary pharmaceutical and basic and applied and commercial and industrial and service research and development, drug discovery and validation and manufacturing, and the re- evaluation of existing drugs or drug rescue, including but not limited to the following areas.
  • Said present invention relates to essentially all of the steps in the process of human and veterinary drug discovery, characterization, optimization, validation, prescription and use.
  • drug includes antiviral, and microbial, and antifungal compounds, as well as vaccines and other drug and Bioactive molecule types of all kinds.
  • Such invention related steps include, but are not limited to, the following, (a) The identification and characterization and development of one or more biological and/or non-biological drug target discovery systems, (b) Establishing quality control (QC) and quality assurance (QA) methods for each drug target discovery system, (c) The identification and characterization and development of one or more drug target candidates, (d) The identification and characterization and development of one or more biological and/or non-biological systems for screening drug candidates for the target, (e) Establishing QC and QA methods for the drug screening systems, (f) The identification and characterization of one or more drug candidates for each drug target and the evaluation of the specificity, and potency or efficacy and toxicity, of the candidate drug in the drug screening system, (g) The optimization of the drug candidate specificity, potency, and toxicity of the drug candidate in the screening system, (h) The identification and development of diagnostic tests for evaluating the drug candidate and target characteristics, (i) Establishing QC and QA methods for the scale up of synthesis of the drug candidate, (j) The identification
  • the invention further relates broadly to basic, commercial, applied, and industrial, research and development and manufacturing and applied and service use of the following. Prokaryote cells and cell cultures, and eukaryotic cells and cultured primary and continuous cells.
  • Eukaryotic organisms, organs, and tissues, as well as organs and tissues cultured in vitro Such invention related uses include, but are not limited to, the following.
  • the use of prokaryotic and eukaryotic cultured cells for a wide variety of basic, commercial, applied and industrial, research and development and service applications.
  • Such eukaryotic cells include primary and continuous stem cell lines and the use of genetically modified microbial, plant, fungal or animal organisms or cells for various aspects of drug, biochemical, bioproduct or food production.
  • the use of organisms and genetically modified organisms includes interfering RNA treatment of such organisms.
  • the invention also relates broadly to basic, commercial, applied, and industrial research and development aspects of toxicology. Many if not most of the above described invention related areas also relate directly or indirectly to toxicology, as well as to the areas of quality control and monitoring of water, food quality, nutrition, public health, marine and terrestrial ecology, forensics, and many kinds of technology development, QC and QA, and various services associated with one or more of the above.
  • the invention relates to the direct or indirect use of one or more gene expression assay measured invention improved abundance and/or RN and/or NAS and/or NASR and/or N-DGER, herein termed Invention Improved Results or IRs, in a further application which directly or indirectly utilizes IRs, herein termed a higher order application, to produce improved higher order application results, herein termed Improved Application Results or IARs. Said IRs are discussed and defined in reference 148 and U.S. application 11/421,961. .
  • IRs in a higher order application of any kind, produces higher order application results which can be known to be significantly improved, relative to prior art produced higher order application results.
  • production of invention improved abundance and/or RN and/or NAS and/or NASR and/or N-DGER results or IR causes an invention "improvement ripple effect" which extends far downstream from the immediate production of the IR.
  • the direct use of one or more of these IRs in an application of any kind, herein termed a zero order application, to produce zero order application results which are, relative to prior art produced zero order application results, significantly improved, is a practice of the invention.
  • An example of a zero order application is the direct use of invention improved abundance and/or RNA and/or NAS values for one or more particular genes in a cell sample to produce improved data mining analysis zero order results.
  • a further downstream invention improvement ripple effect is the direct use of one or more zero order application IRs in an application of any kind, herein termed a first order application, to produce first order application results which are, relative to prior art produced first order application results, significantly improved, and a further practice of the invention.
  • An example of a first order application is the direct use of data mining analysis IRs in a systems biology analysis application of any kind to produce improved systems biology results.
  • An even further downstream invention improvement ripple effect is the direct use of one or more first order application IRs in an application of any kind, herein termed a second order application, to produce second order application results which are relative to prior art produced second order application results, significantly improved, and a practice of the invention.
  • An example of a second order application is the direct use of one or more systems biology analysis IRs in a second order application for the discovery of drug candidates.
  • Higher order invention improvement ripple effects also occur.
  • the direct use of one or more improved lower order application IRs in a higher order application produces higher order application results which, relative to prior art produced higher order application results, are significantly improved, and is a practice of the invention.
  • One of skill in the art will recognize that the use of lower order application IRs in a higher order application of any kind which utilizes lower order application results, will result in improved higher order application results.
  • the practice of the present invention involves the following, but not all of the items need be present in all practices of the invention, (a) Conduct one or more gene expression or gene expression comparison assays, (b) Determine for each gene expression or gene expression comparison assay the particular gene RN IR results and/or the particular gene abundance IR results and/or particular gene NAS IR results and/or the particular gene other equivalent IR results, and/or the particular gene comparison NASR IR results and/or the particular gene comparison N-DGER IR results and/or the particular gene comparison other equivalent IR results, by using the methods and means described in reference 148 and U.S. application 11/421,961. (c) Directly use one or more of the above described gene expression IRs in a higher order application.
  • Such higher order applications include all prior art known and unknown higher order applications.
  • Such methods include, but are not limited to, the above described simple and complex gene expression result analysis methods, as well as all higher order application methods described in references 1- 147. This includes all supervised and unsupervised gene expression result analysis methods, as well as those gene expression analysis methods used in conjunction with systems biology analyses.
  • Such methods include, but are not limited to, the following prior art classification methods and any valid modifications of such methods, (i) Linear discriminant methods, (ii) Support vector machine methods, (iii) K-nearest neighbour method, (iv) Neural network methods, (v) Decision tree methods, (vi) Partially supervised analysis methods, (vii) Class discovery method.
  • Such methods also include, but are not limited to, the various prior art forms of class discovery and time series analysis and their modifications.
  • analysis methods include the following prior art cluster analyses and any modifications of such methods, (i) Hierarchical agglomerative clustering methods, (ii) Hierarchical divisive clustering methods, (iii) Non-hierarchical K-means methods, (iv) Self-organizing maps and trees methods, (v) Relationship between clustering and principle component analysis methods, (vi) Gene shaving methods, (vii) Clustering in discretised space methods, (viii) Graph based clustering methods, (ix) Bayesian or model based clustering and fuzzy clustering methods, (x) Clustering of genes and samples methods. The above list was obtained from reference 10.
  • References 9 and 10 contain useful summaries of prior art gene expression results analysis methods of all kinds. References 1-13 are also useful and contain many prior art gene expression result analysis method descriptions, and references to their use. Prior art analysis methods and other higher order applications and their use are also referred to in many of the references 14-147. (d) Use of one or more of the above described improved gene expression result analysis results or other high order application results in an even higher order application. Such applications include all prior art known and unknown other higher order applications which directly or indirectly utilize gene expression analysis assay results and/or gene expression assay result analysis results. Such applications include, but are not limited to, the very broad applications described in the Field of the Invention section and those described in the cited references.
  • Frieberg et al Genomewide mRNA Profiling: Impact on Compound Evaluation and Target Identification In Anti-Bacterial Research. Targets. 1(1): 20-29 (2002) 45) Systems Biology Introduction. Kitano, Systems Biology: A Brief Overview - Csete et al, A Genomic Regulatory Network For Development-Noble, Modeling From The Heart: From Genes To Cells To The Whole Organ. Science 295: 1661-1682 (2002)
  • 20060057630 MLL translocations specify a distinct gene expression profile, distinguishing a unique leukemia
  • MLL translocations specify a distinct gene expression profile, distinguishing a unique leukemia
  • 20040214203 Genes related to sensitivity and resistance to chemotherapeutic drug treatment
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  • 20030134300 MLL translocations specify a distinct gene expression profile, distinguishing a unique leukemia 20030134280 Identifying drugs for and diagnosis of benign prostatic hyperplasia using gene expression profiles
  • 20040229245 Methods and algorithms for performing quality control during gene expression profiling on DNA microarray technology
  • 20060088876 Method for the early detection of breast cancer, lung cancer, pancreatic cancer and colon polyps, growths and cancers as well as other gastrointestinal disease conditions and the preoperative and postoperative monitoring of transplanted organs from the donor and in the recipient and their associated conditions related and unrelated to the organ transplantation
  • 20060084075 Program for analysis of the time-series data obtained by DNA array method, a method for analysis of the time-series data obtained by DNA array method, and a device for analysis of the time-series data obtained by DNA array method
  • 20050130212 Method, computer program having program code means and computer program product for analyzing a regulatory genetic network of a cell 20050130189 Compositions and methods for treating and diagnosing irritable bowel syndrome
  • 20040214203 Genes related to sensitivity and resistance to chemotherapeutic drug treatment
  • 20040086855 Method for screening genes expressing at desired part 20040081618 Method of screening physiologically active substance 20040067500 Compositions and methods relating to the peroxisomal proliferator activated receptor-alpha mediated pathway 20040058376 Expression monitoring for gene function identification
  • PCBP Presenilin/Crk binding polypeptides
  • compositions and methods for isolating genes comprising subcellular localization sequences
  • 20060088876 Method for the early detection of breast cancer, lung cancer, pancreatic cancer and colon polyps, growths and cancers as well as other gastrointestinal disease conditions and the preoperative and postoperative monitoring of transplanted organs from the donor and in the recipient and their associated conditions related and unrelated to the organ transplantation
  • 20040214203 Genes related to sensitivity and resistance to chemotherapeutic drug treatment
  • certain embodiments concern a method of predicting the likelihood of long-term survival of a cancer patient without the recurrence of cancer.
  • the method involves knowing (e.g., by determining) the expression level of one or more prognostic RNA transcripts or their expression products in a cancer cell obtained from the patient, normalized against a control transcript or transcripts (e.g., the expression level of all RNA transcripts or their products in the cancer cell, or of a reference set of RNA transcripts or their expression products).
  • the prognostic RNA transcript can be a transcript of one or more genes selected from the group consisting of B_Catenin; BAGl; BINl; BUBl; C20_orfl; CCNBl; CCNE2; CDC20; CDHl; CEGPl; CIAPl; cMYC; CTSL2; DKFZp586M07; DR5; EpCAM; EstRl; FOXMl; GRB7; GSTMl; GSTM3; HER2; HNRPAB; IDl; IGFlR; ITGA7; Ki_67; KNSL2; LMNBl; MCM2; MELK; MMP12; MMP9; MYBL2; NEK2; NMEl; NPD009; PCNA; PR; PREP; PTTGl; RPLPO; Src; STK15; STMY3; SURV; TFRC; TOP2A; and TS.
  • B_Catenin BAGl
  • Expression of one or more of BAGl; BCatenin; BINl; CEGPl; CIAPl; cMYC; DKFZp586M07; DR5; EstRl; GSTMl; GSTM3; IDl; IGFlR; ITGA7; NPD009; PR; and RPLPO indicates an increased likelihood of long-term survival without cancer recurrence.
  • the embodiments concern a method of preparing a personalized genomics profile for a patient diagnosed with an ER positive breast cancer, by (a) subjecting RNA extracted from breast cancer cells obtained from the patient to gene expression analysis; (b) determining the expression level in the tissue of the RNA transcripts of GRB7 and STMY3, where the expression level is normalized against a control gene or genes and optionally is compared to the amount found in a breast cancer reference tissue set; and (c) creating a report summarizing the data obtained by the gene expression analysis, where the report includes a prediction of the likelihood of long term survival of the patient in which expression of GRB 7 and STMY3 indicates a decreased likelihood of long-term survival without breast cancer recurrence.
  • the embodiments obtained by apply the present invention to the methods of the '674 patent also include a method of predicting the likelihood of long-term survival of an ER positive breast cancer patient (e.g., a patient diagnosed with an invasive ER positive breast cancer) without the recurrence of breast cancer, where the method includes determining the expression level of the RNA transcripts of GRB 7 and STMY3 or their expression products in an ER positive breast cancer cell obtained from the patient, normalized against the expression level of a control gene or genes (e.g., all RNA transcripts or their products in the ER positive breast cancer cell, or of a reference set of RNA transcripts or their expression products); where expression of GRB7 and STMY3 indicates a decreased likelihood of long-term survival without breast cancer recurrence.
  • the method can include subjecting the expression level data to statistical analysis, and determining whether the likelihood of such long-term survival has increased or decreased.
  • Study Design Molecular assays were performed on paraffin-embedded, formalin-fixed primary breast tumor tissues obtained from 252 individual patients diagnosed with invasive breast cancer. All patients were lymph node-negative, ER-positive, and treated with Tamoxifen. Mean age was 52 years, and mean clinical tumor size was 2 cm. Median follow-up was 10.9 years. As of Jan. 1, 2003, 41 patients had local or distant disease recurrence or breast cancer death. Patients were included in the study only if histopathologic assessment, performed as described in the Materials and Methods section, indicated adequate amounts of tumor tissue and homogeneous pathology.
  • Each representative tumor block was characterized by standard histopathology for diagnosis, semi-quantitative assessment of amount of tumor, and tumor grade. When tumor area was less than 70% of the section, the tumor area was grossly dissected and tissue was taken from 6 (10 micron) sections. Otherwise, a total of 3 sections (also 10 microns in thickness each) were prepared. Sections were placed in two Costar Brand Microcentrifuge Tubes (Polypropylene, 1.7 mL tubes, clear). If more than one tumor block was obtained as part of the surgical procedure, the block most representative of the pathology was used for analysis.
  • ABI PRISM 7900.TM. Sequence Detection System.TM. Perkin-Elmer-Applied Biosystems, Foster City, Calif., USA.
  • ABI PRISM 7900.TM. consists of a thermocycler, laser, charge-coupled device (CCD), camera and computer. The system amplifies samples in a 384-well format on a thermocycler. During amplification, laser-induced fluorescent signal is collected in real-time through fiber optics cables for all 384 wells, and detected at the CCD.
  • the system includes software for running the instrument and for analyzing the data.
  • Tumor tissue was analyzed for 187 cancer-related genes and 5 reference genes. Adequate RT-PCR profiles were obtained from 242 of the 252 patients. The threshold cycle (CT) values for each patient were normalized based on the median of the 7 reference genes for that particular patient. Clinical outcome data were available for all patients from a review of registry data and selected patient charts. Outcomes were classified as:
  • Event Alive with local, regional or distant breast cancer recurrence or death due to breast cancer.
  • No Event Alive without local, regional or distant breast cancer recurrence or alive with contralateral breast cancer recurrence or alive with non-breast second primary cancer or died prior to breast cancer recurrence.
  • Analysis was performed by: A. determination of the relationship between normalized gene expression and the binary outcomes of 0 or 1; B. Analysis of the relationship between normalized gene expression and the time to outcome (0 or 1 as defined above) where patients who were alive without breast cancer recurrence or who died due to a cause other than breast cancer were censored. This approach was used to evaluate the prognostic impact of individual genes and also sets of multiple genes.
  • the expression of any of the following genes in breast cancer indicates a reduced likelihood of survival without cancer recurrence: C20_orfl; CCNBl; CDC20; CDHl; CTSL2; EpCAM; GRB7; HER2; KNSL2; LMNBl; MCM2; MMP9; MYBL2; NEK2; PCNA; PREP; PTTGl; STMY3; SURV; TS; MELK, while the expression of any of the following genes in breast cancer indicates a better prognosis for survival without cancer recurrence: BAGl; BCatenin; CEGPl; CIAPl; cMYC; DKFZp586M07; EstRl; GSTMl; GSTM3; IDl; ITGA7; PR.
  • the genes that have a p-value ⁇ 0.05 in the Cox model were identified.
  • the Cox model provides the relative risk (RR) of recurrence or death for a unit change in the expression of the gene.
  • RR relative risk
  • any threshold value will define subgroups of patients with respectively increased or decreased risk.
  • the expression of any of the following genes in breast cancer indicates a reduced likelihood of survival without cancer recurrence: GRB7; SURV; LMNBl; MYBL2; HER2; MELK; C20_orfl; PTTGl; BUBl; CDC20; CCNBl; STMY3; KNSL2; CTSL2; MCM2; NEK2; Ki.sub.-67; CCNE2; TOP2A-4; PCNA; PREP; FOXMl; NMEl; STKl 5; HNRPAB; MMP9; TS; Src; MMP12; TFRC, and the expression of any of the following genes in breast cancer indicates a better prognosis for survival without cancer recurrence: PR; GSTMl; DR5; CEGPl; BAGl; EstRl; DKFZp586M07; BINl; NPD009; RPLPO; GSTM3; IGFlR.
  • stepwise entry of each individual gene into the model is performed, where the first gene entered is pre-selected from among those genes having significant univariate p-values, and the gene selected for entry into the model at each subsequent step is the gene that best improves the fit of the model to the data.
  • This analysis can be performed with any total number of genes. In the analysis the results of which are shown below, stepwise entry was performed for up to 10 genes.
  • coefficients for genes that are predictors of beneficial outcome are positive numbers and coefficients for genes that are predictors of unfavorable outcome are negative numbers.
  • the "Ct" values in the equation are .DELTA.Cts, i.e. reflect the difference between the average normalized Ct value for a population and the normalized Ct measured for the patient in question.
  • the convention used in the present analysis has been that .DELTA.Cts below and above the population average have positive signs and negative signs, respectively (reflecting greater or lesser mRNA abundance).
  • the relative risk (RR) calculated by solving this equation will indicate if the patient has an enhanced or reduced chance of long-term survival without cancer recurrence.
  • the following ten-gene set has been identified by this analysis as having particularly strong predictive value of patient survival: GRB7; LMNBl; ER; STMY3; KLKlO; PR; KRT5; FGFRl; MCM6; SNRPF.
  • GRB7, LMNBl, STMY3, KLKlO, FGFRl, and SNRPF contribute to poor prognosis.
  • the methods described in the '674 patent are illustrative of determination and/or use of the correlation between the molecular gene expression profiles of any infectious or non-infectious disease or pathologic state and disease-free survival for patients who have been treated or untreated.
  • corresponding gene markers for the disease or condition of interest are used for diagnosis, selection of treatment, evaluation of treatment course and/or outcome prognosis, and/or prognosis of disease or condition recurrence or non- recurrence, and/or of patent condition and/or morbidity and/or mortality.
  • Other disease or conditions include, but are not limited to other forms of cancer, such as other forms of breast cancer, lung cancers, leukemias, lymphomas, prostate cancers, cervical cancers, thyroid cancers, and skin cancers.
  • Example 3 Changes in gene expression in granulocytic cells
  • Embodiments of the present invention are also illustrated by application of the present improved gene expression results and profiles to the methods described in U.S. Patent 6,365,352, which is incorporated herein by reference in its entirety.
  • the methods described therein include a method to identify granulocytic cell genes (e.g., cytokine genes, genes encoding cell surface receptors and genes encoding intermediary signaling molecules) that are differentially expressed upon exposure to a pathogen by preparing a gene expression profile of a granulocytic cell population exposed to a pathogen and comparing that profile to a profile prepared from quiescent granulocytic cells, thereby identifying cDNA species, and therefore genes, which are expressed de novo upon neutrophil contact with a pathogen.
  • granulocytic cell genes e.g., cytokine genes, genes encoding cell surface receptors and genes encoding intermediary signaling molecules
  • a method to identify granulocytic cell genes that are differentially expressed in response to a sterile inflammatory disease by preparing a gene expression profile of a granulocytic cell population isolated from a subject exhibiting the symptoms of a sterile inflammatory disease and comparing that profile to a profile prepared from granulocytic cells isolated from a normal granulocytic cell population.
  • cDNA species, and therefore genes, which are differentially expressed in the granulocytic cells of a subject exhibiting the symptoms of a sterile inflammatory disease are thereby identified.
  • the present invention also includes a method to identify granulocytic cell genes that are differentially expressed upon exposure of a granulocytic cell population to an agonist (pro-inflammatory molecule) by preparing a gene expression profile of a granulocytic cell population contacted with an agonist and comparing that profile to a profile prepared from noncontacted granulocytic cells, thereby identifying cDNA species, and therefore genes, which are expressed de novo in the granulocytic cells contacted with the agonist are thereby identified.
  • an agonist pro-inflammatory molecule
  • the present invention further includes a method to identify a therapeutic or prophylactic agent that modulates the response of a granulocyte population to a pathogen, comprising the steps of preparing a first gene expression profile of a quiescent granulocyte population, preparing a second gene expression profile of a granulocyte population exposed to a pathogen, treating said exposed granulocyte population with the agent, preparing a third gene expression profile of the treated granulocyte population, comparing the first, second and third gene expression profiles and identifying agents that modulate the response of a granulocyte population to the pathogen.
  • Another aspect of the invention is a method to identify a therapeutic agent that modulates the expression of genes in a granulocyte population found in a subject having Another aspect of the invention includes a method to identify a therapeutic or prophylactic agent that modulates the response of a granulocyte cell population in a subject having a sterile inflammatory disease, comprising the steps of preparing a first gene expression profile of a granulocyte population in a subject having a sterile inflammatory disease, treating the granulocyte population with the agent, preparing a second gene expression profile of the treated granulocyte population, comparing the first and second gene expression profiles with the gene expression profile of a normal granulocyte population and identifying agents that modulate the expression of genes whose transcription levels are altered in the granulocyte population of the subject as compared with normal granulocyte population.
  • a further aspect of the present invention is a method to identify a therapeutic or prophylactic agent that modulates the response of a granulocytic population to an agonist (pro-inflammatory molecule), comprising the steps of preparing a first gene expression profile of a quiescent granulocyte population, preparing a second gene expression profile of a granulocyte population exposed to an agonist, treating the exposed granulocyte population with the agent, preparing a third gene expression profile of the treated granulocyte population, comparing the first, second and third gene expression profiles and identifying agents that modulate the response of a granulocytic population exposed to an agonist.
  • agonist pro-inflammatory molecule
  • the present invention also includes a method of diagnosing the exposure of a subject to a pathogen, comprising the steps of preparing a first gene expression profile of a granulocyte population from the subject, comparing the first gene expression profile to a second gene expression profile of a granulocyte population exposed to that pathogen and to a third gene expression profile of a normal granulocyte preparation and diagnosing whether the subject has been exposed to a pathogen.
  • Another aspect of the invention includes a method of diagnosing a sterile inflammatory disease in a subject, comprising the steps of preparing a first gene expression profile of a granulocyte population from the subject, comparing the first gene expression profile to at least one second gene expression profile from a granulocyte population from a subject having a sterile inflammatory disease and to a third gene expression profile of a normal granulocyte preparation and thereby determining if the subject has a sterile inflammatory disease.
  • the present invention also includes a method of identifying new bacterial virulence factor genes by preparing a first gene expression profile of a quiescent granulocyte population, preparing a second gene expression profile of a granulocyte population exposed to a virulent or avirulent bacterial strain, preparing a third gene expression profile from a granulocyte population exposed to a bacterial strain with a mutation in a putative bacterial virulence factor gene, comparing the first, second and third gene expression profiles and identifying a bacterial virulence factor gene.
  • compositions comprising a grouping of nucleic acids that correspond to at least a part of one or more of the genes whose expression levels are modulated in a granulocyte population that has been exposed to a pathogen, these nucleic acids being affixed to a solid support.
  • an aspect of the invention is a composition comprising a grouping of nucleic acids that correspond to at least part of one or more genes whose expression levels are modulated in a granulocyte population found in a subject having a sterile inflammatory disease, these nucleic acids being affixed to a solid support.
  • RNA expression profiles generated from cDNAs made with RNA isolated from neutrophils exposed to virulent and avirulent bacteria Expression profiles of RNA expression levels from neutrophils exposed to various bacteria offer a powerful means of identifying genes that are specifically regulated in response to bacterial infection. As an example, the production of expression profiles from neutrophils exposed to virulent and avirulent E. coli and Y. pestis allow the identification of neutrophil genes that are specifically regulated in response to bacterial infection.
  • Neutrophils were isolated from normal donor peripheral blood following the LPS-free method.
  • Peripheral blood was isolated using a butterfly needle and a syringe containing 5 cc ACD, 5 cc of 6% Dextran (in normal saline). After 30 minutes of settling, plasma was collected and HBSS Hank's balcinceal salt solution (without Ca.sup.++ or Mg.sup.++) was added to a total volume of 40 ml. The plasma was centrifuged (1500 rpm, for 15 m at 4.degree. C), the supernatant decanted and cold HBSS added to resuspend the cells.
  • the cell suspension was then layered onto a cold Ficoll Hypaq, centrifuged at 500.times.g for 30 m at 4.degree. C.
  • the pellet contains polymorphonuclear neutrophils.
  • Neutrophils can also be isolated by other commonly used methods such as those disclosed in Current Protocols of Immunology (John Wiley & Sons, Inc.), Babior et al. (1981) In:Leokocyte Function, Cline, M. J. Ed., p.1-38 (Church Livingstone, N. Y.), and Haslett et al. (1985) Am. J. Pathol. 119:101-110.
  • neutrophils were incubated with E. coli or Y. pestis. Before incubation, bacteria are harvested and washed in phosphate buffered saline and opsonized either autologous human serum or complement factor C7 deficient human serum (SIGMA). Incubation was at a ratio of approximately a PMN:bacteria ratio of 1:20 in RPMI 1640 (HEPES buffered) with heat inactivated Fetal Bovine Serum at 37.degree. C. with gentle mixing in a rotary shaker bath.
  • SIGMA complement factor C7 deficient human serum
  • LPS bacterial lipopolysaccharide
  • latex beads bacterial lipopolysaccharide
  • LPS was added to approximately 3.38 x l ⁇ .sup.8 cells in 100 ml of RPMI Roswell Park. Memorial Institute containing 6% autologous serum to a final concentration of 1 ng/ml to 1 .mu.g/1. Incubation proceeded for 30 or 120 minutes with gentle rotation in disposable polycarbonate Erlenmeyer flasks at 37.degree. C. After incubation, the cells were spun down and washed once with HBSS. fl
  • Total cellular RNA was prepared from untreated and treated neutrophils are described above using the procedure of Newburger et al.(1981) J. Biol. Chem. 266(24): 16171-7 and Newburger et al. (1988) Proc. Natl. Acad Sci USA 85:5215-5219. Ten micrograms of total RNA, the amount obtainable from about 3.times.lO.sup.6 neutrophils, is sufficient for a complete set of cDNA expression profiles.
  • cDNA was synthesized according to the protocol described in the GIBCO/BRL kit for cDNA synthesis.
  • the reaction mixture for first-strand synthesis included 6 ⁇ g of total RNA, and 200 ng of a mixture of 1-base anchored oligo(dT) primers with all three possible anchored bases with sequences as specified in the '352 patent along with other components for first-strand synthesis reaction except reverse transcriptase.
  • the reaction mixture was incubated at 65 degree C for 5 m, chilled on ice and the process repeated.
  • the reaction mixture may include 10 g of total RNA, and 2 pmol of 1 of the 2-base anchored oligo(dT) primers such as RP5.0, RP6.0, or RP9.2 (the sequences of which are provided in the '352 patent) along with other components for first-strand synthesis reaction except reverse transcriptase.
  • This mixture was then layered with mineral oil and incubated at 65 degree C for 7 min followed by 50 degree C for another 7 min.
  • the adapter oligonucleotide sequences were Al and A2 (the sequences of which are provided in the '352 patent).
  • One microgram of oligonucleotide A2 was first phosphorylated at the 5' end using T4 polynucleotide kinase (PNK). After phosphorylation, PNK was heated denatured, and 1 .mu.g of the oligonucleotide Al was added along with lO.times. annealing buffer (1 M NaCl/100 mM Tris-HCl, pH8.0/10 mM EDTA, pH8.0) in a final vol of 20 .mu.l.
  • This mixture was then heated at 65 degree C for 10 min followed by slow cooling to room temperature for 30 min, resulting in formation of the Y adapter at a final concentration of 100 ng/.mu.l.
  • About 20 ng of the cDNA was digested with 4 units of BgI II in a final vol of 10 .mu.l for 30 min at 37.degree. C.
  • Two microliters (.apprxeq.4 ng of digested cDNA) of this reaction mixture was then used for ligation to 100 ng (.apprxeq.5O- fold) of the Y-shaped adapter in a final vol of 5 ⁇ l for 16 hr at 15 degree C.
  • reaction mixture was diluted with water to a final vol of 80 ⁇ l (adapter ligated cDNA concentration, .apprxeq.50 pg/ ⁇ l) and heated at 65 degree C for 10 min to denature T4 DNA ligase, and 2 ⁇ l aliquots (with 100 pg of cDNA) were used for PCR.
  • the labeled oligonucleotide was diluted to a final concentration of 2 ⁇ M in 80 ⁇ l with unlabeled oligonucleotide ALL
  • the PCR mixture (20 ⁇ l) consisted of 2 ⁇ l (.apprxeq.100 pg) of the template, 2 ⁇ l of 10 times PCR buffer (100 mM Tris.HCl, pH 8.3/500 mM KCl), 2 ⁇ l of 15 mM MgCl.sub.2 to yield 1.5 mM final Mg.sup.2+ concentration optimum in the reaction mixture, 200 ⁇ M dNTPs, 200 nM each 5' and 3' PCR primers, and 1 unit of Amplitaq Gold.
  • PCR was done to avoid artifactual amplification arising out of arbitrary annealing of PCR primers at lower temperature during transition from room temperature to 94 degree C in the first PCR cycle.
  • PCR consisted of 5 cycles of 94 degree C for 30 sec, 55 degree C for 2 min, and 72 degree C. for 60 sec followed by 25 cycles of 94 degree C for 30 sec, 60 degree C for 2 min, and 72 degree C for 60 sec. A higher number of cycles resulted in smeary gel patterns.
  • PCR products (2.5 ⁇ l) were analyzed on 6% polyacrylamide sequencing gel.
  • FIG. 1 in the '352 patent presents an autoradiogram of the expression profile generated from cDNAs made from RNA isolated from control (untreated) neutrophils (lanes 1, 5, 10, 13, 14 and 16), neutrophils incubated with avirulent E. coli K12 (lanes 2 and 11), virulent Y. pestis D27 (lane 3), avirulent Y. pestis D28 (lane 4), Y. pestis yopB (lane 6), Y. pestis yopE (lane 7), Y. pestis yoph (lane 8), latex beads (lanes 9 and 19), virulent Entero Hemorrhagic E.
  • the anchoring oligo d(T)18 nl, n2 has A and C at the nl and n2 positions, respectively.
  • the cDNAs were digested with BgHI.
  • Neutrophils were isolated from normal donor peripheral blood following the LPS-free method as set forth in Example 1. Neutrophils were incubated with virulent and avirulent E. coli or Y. pestis, LPS at 1 ng/ml, GM-CSF at 100 units/ml, TNFa at 1000 units/ml, or .gamma.IFN at 100 units/ml.
  • the bacterial cells, LPS or cytokines were added to approximately 3.38.times.lO.sup.8 cells in 100 ml of RPMI containing 6% Hl autologous serum. Incubation proceeded for 2 to 4 hours, preferably 2 hours, with gentle rotation in disposable polycarbonate Erlenmeyer flasks at 37.degree. C. After incubation, the cells were spun down and washed once with HBSS.
  • FIG. 2 in the '352 patent is an autoradiogram of the expression profiles generated from cDNAs made with RNA isolated from control (untreated) neutrophils (lanes 1, 5, 10 and 14), neutrophils incubated with avirulent E. coli K12 (lanes 2 and 11), virulent Y. pestis (lanes 3 and 12), avirulent Y. pestis (lanes 4 and 13), 1 ng/ml LPS (lanes 6 and 15), 100 units/ml GM-CSF(lanes 7 and 16), 1000 units/ml TNF.alpha.
  • the anchoring oligo d(T)18nl, n2 has A and C at the nl and n2 positions for lanes 1-9 and G and G at the nl and n2 for lanes 10-18.
  • the cDNAs were digested with BgHI. As shown by FIG. 2 in the '352 patent, the differential expression of mRNA species (as exhibited by cDNA fragments) in neutrophils exposed to virulent and avirulent E. coli and Y. pestis is not equivalent to the differential expression of mRNA species in neutrophils exposed to the various cytokines.
  • FIG. 3 in the '352 patent shows an autoradiogram of the expression profiles generated from cDNAs made with RNA isolated from control (untreated) neutrophils (lane 1), neutrophils incubated with avirulent E. coli Kl 2 (lane 2), virulent Y.
  • FIG. 4 shows a summary of genes which are differentially expressed in neutrophils upon exposure to virulent and avirulent E. coli and Y. pestis. Expression patterns are determined by visual examination of the autoradiography gels comparing band intensity between neutrophils exposed to the various bacteria. The autoradiography gels can also be scanned using commonly available equipment, such s a UMAX D-IL scanner.
  • Tables 1 and 2 in the '352 patent provide a summary of cDNA bands which are differentially expressed in response to exposure to E. coli.
  • RNA is extracted and the gene expression profiles prepared as described in Example 1.
  • cDNAs genes which are differentially expressed in the neutrophils isolated from a subject exhibiting the symptoms of a sterile inflammatory disease
  • the cDNA profiles prepared from neutrophils from said subject are compared to profiles prepared from neutrophils isolated from the normal donor.
  • Bands which exhibit altered intensities when compared between the gene expression profiles prepared from neutrophils from said subject and profiles prepared from neutrophils isolated from the normal donor are then extracted from the display gel as previously described in Example 1.
  • the isolated fragments are then reamplified using 5' and 3' primers, subcloned into pCR-Script (Stratagene) and sequenced using an ABI automated sequencer. Once sequences are obtained which correspond to the bands of interest, the sequences can be compared to known nucleic acid sequences in the available data bases.
  • This description is illustrative of identifying differentiall expressed genes corresponding to a disease or condition, and thus can be generalized to encompass any sterile or non-sterile disease or pathologic state of any kind for any kind of organism or cell.
  • the respective diseased cells and control cells are used for generating the expression profiles.
  • Example 1 Method to identify a therapeutic or prophylactic agent that modulates the response of a granulocyte population to a pathogen:
  • the methods set forth in Example 1 offer a powerful approach for identifying therapeutic or prophylactic agents that modulate the expression of neutrophils or other granulocytic cells to a pathogen.
  • profiles of normal granulocytes and neutrophils or other granulocytes exposed to pathogens such as E. coli, Y. pestis or other pathogenic bacteria are prepared as set forth in Example 1.
  • a profile is also prepared from a granulocyte population that has been exposed to the pathogen in the presence of the agent to be tested. By examining for differences in the intensity of individual bands between the three profiles, agents which up or down regulate genes of interest in the pathogen exposed granulocytes can be identified.
  • screening for agents which up or down regulate the expression of human pre-B cell enhancing factor can be identified by examining the differences in band intensity between profiles produced from normal granulocytes, granulocytes exposed to the pathogen and granulocytes exposed to the pathogen in the presence of the agent to be tested.
  • PBEF human pre-B cell enhancing factor
  • FIG. 4 PBEF is expressed at high levels when exposed to avirulent bacteria, including E. coli Kl 2 and avirulent Y. pestis but is not expressed at high levels in granulocytes exposed to pathogenic Y. pestis.
  • Agents that up regulate PBEF expression as demonstrated by increased band density in the profile produced from granulocytic cells exposed to virulent Y. pestis in the presence of the agent may be useful in modulating the response of neutrophils to bacterial infection.
  • This description of this example is illustrative of the process of identifying any therapeutic or prophylactic agent for treating any cell or organism infected with any infectious agent or affected by other disease or condition, but using the corresponding cells and therapeutic marker genes.
  • Method to identify a therapeutic or prophylactic agent that modulates the expression of genes in a granulocyte cell population found in a subject having a sterile inflammatory disease The methods set forth in Example 4 offer a powerful approach for identifying therapeutic or prophylactic agents that modulate the expression of neutrophils or other granulocytic cells in subjects exhibiting the symptoms of a sterile (non-infectious) inflammatory disease. For instance, gene expression profiles of normal granulocytes and granulocytes from a subject exhibiting the symptoms of a sterile inflammatory disease are prepared as set forth in Examples 1 and 4.
  • a profile is also prepared from a granulocyte population from a subject exhibiting the symptoms of a sterile inflammatory disease that have been exposed to the agent to be tested.
  • Agents that up-regulate a gene or genes that are expressed at abnormally low levels in a granulocytic cell population from a subject exhibiting the symptoms of a sterile inflammatory disease compared to a normal granulocytic cell population as well as agents that down regulate a gene or genes that are expressed at abnormally high levels in a granulocytic cell population from a subject exhibiting the symptoms of a sterile inflammatory disease are contemplated.
  • Solid supports can be prepared that comprise immobilized representative groupings of nucleic acids corresponding to the genes or fragments of said genes from granulocytic cells whose expression levels are modulated in response to exposure to a pathogen or in a subject having a sterile inflammatory disease.
  • representative nucleic acids can be immobilized to any solid support to which nucleic acids can be immobilized, such as positively charged nitrocellulose or nylon membranes (see Sambrook et al. (1989) Molecular Cloning: a laboratory manual 2nd., Cold Spring Harbor Laboratory) as well as porous glass wafers such as those disclosed by Beattie (WO 95/11755).
  • Nucleic acids are immobilized to the solid support by well established techniques, including charge interactions as well as attachment of derivatized nucleic acids to silicon dioxide surfaces such as glass which bears a terminal epoxide moiety.
  • a solid support comprising a representative grouping of nucleic acids can then be used in standard hybridization assays to detect the presence or quantity of one or more specific nucleic acid species in a sample (such as a total cellular mRNA sample or cDNA prepared from said mRNA) which hybridize to the nucleic acids attached to the solid support.
  • Any hybridization methods, reactions, conditions and/or detection means can be used, such as those disclosed by Sambrook et al. (1989) Molecular Cloning: a laboratory manual 2nd., Cold Spring Harbor Laboratory, Ausbel et al.(1987) Current Protocols in Molecular Biology, Greene Publishing and Wiley-Interscience or Beattie (WO 95/11755).
  • One of ordinary skill in the art may determine the optimal number of genes that must be represented by nucleic acid fragments immobilized on the solid support to effectively differentiate between samples, e.g. neutrophils exposed to various pathogens or neutrophils isolated from a patient to be tested for a sterile inflammatory disease.
  • samples e.g. neutrophils exposed to various pathogens or neutrophils isolated from a patient to be tested for a sterile inflammatory disease.
  • at least about 5, 10, 20, 50, 100, 150, 200, 300, 500, 1000 or more preferably, substantially all of the detectable mRNA species in a cell sample or population will be present in the gene expression profile or array affixed to a solid support. More preferably, such profiles or arrays will contain a sufficient representative number of mRNA species whose expression levels are modulated under the relevant infection, disease, screening, treatment or other experimental conditions.
  • a sufficient representative number of such mRNA species will be about 1, 2, 5, 10, 15, 20, 25, 30, 40, 50, 50-75 or 100 in number and will be represented by the nucleic acid molecules or fragments of nucleic acid molecules immobilized on the solid support.
  • nucleic acids encoding all or a fragment of one or more of the known genes or previously reported ESTs that are identified in FIG .4 and Tables 1 and 2 of the '352 patent may be so immobilized.
  • the skilled artisan will be able to optimize the number and particular nucleic acids for a given purpose, i.e., screening for modulating agents, identifying activated granulocytes, etc.
  • the general process of this example generalizes to encompass a solid support containing any group of genes which are characteristic of a particular diseased, or pathologic, or normal, or differentiated, or treated cell type of any kind.
  • Method of diagnosing exposure of a subject to a pathogen Expression profiles of RNA expression levels from neutrophils exposed to various bacteria, such as those disclosed in Examples 1 and 3, offer a powerful means to diagnose exposure of a subject to a pathogen.
  • the display patterns generated from cDNAs made with RNA isolated from neutrophils exposed to pathogenic and nonpathogenic E. coli and Y. pestis exhibit unique patterns of cDNA species corresponding to neutrophil mRNA species (genes) whose expression levels are modulated in response to contact of the neutrophils with the bacteria.
  • the contacting of neutrophils with different species of pathogens may result in the production of expression profiles that are unique to each pathogen species or strain. These unique expression profiles are useful in diagnosing whether a subject has been exposed to or is infected with a given pathogen.
  • expression profiles are produced as set forth in Example 1 using neutrophil samples exposed to various pathogens, such as pathogenic strains of E. coli, Y. pestis, Staphylococci, Streptococci or any other bacterial species. Neutrophils are then isolated from the subject to be tested for exposure to a pathogen and an expression profile prepared from the subject's neutrophils by the methods set forth in Example 1. The expression profile prepared from the subject neutrophils can then be compared to the expression profiles prepared from neutrophils exposed to the various pathogen species or strains to determine which expression profile most closely matches the expression profile prepared from the subject, thereby, diagnosing exposure of the subject to a pathogen.
  • pathogens such as pathogenic strains of E. coli, Y. pestis, Staphylococci, Streptococci or any other bacterial species.
  • the description of this example can be generalized to encompass the diagnosis of any diseased or pathologic cell state caused by any infectious agent of any kind, as well as to exposure to chemical agents.
  • an expression pattern which is identified as characteristic of exposure to the infectious agent or chemical agent is used for matching with cells which have a putative exposure to determine the exposure or diagnose the infection or exposure.
  • Method of diagnosing a sterile inflammatory disease in a subject Expression profiles of RNA expression levels from neutrophils isolated from a subject having a sterile inflammatory disease, such as those disclosed in Example 4, offer a powerful means to diagnose inflammatory diseases such as psoriasis, rheumatoid arthritis, glomerulonephritis, asthma, cardiac and renal reperfusion injury, thrombosis, adult respiratory distress syndrome, inflammatory bowel diseases such as Crohn's disease and ulcerative colitis and periodontal disease.
  • inflammatory diseases such as psoriasis, rheumatoid arthritis, glomerulonephritis, asthma, cardiac and renal reperfusion injury, thrombosis, adult respiratory distress syndrome, inflammatory bowel diseases such as Crohn's disease and ulcerative colitis and periodontal disease.
  • the gene expression profiles generated from cDNAs made with RNA isolated from neutrophils from subjects having various sterile inflammatory diseases may exhibit unique patterns of cDNA species corresponding to neutrophil mRNA species (genes) whose expression levels are modulated during the inflammatory process. These unique expression profiles are useful in diagnosing whether a subject has a sterile inflammatory disease.
  • expression profiles are produced as set forth in Examples 1 and 4 using neutrophil samples isolated from patients with various sterile inflammatory diseases. Neutrophils are then isolated from the subject to be tested and an expression profile prepared from the subject's neutrophils by the methods set forth in Example 1. The expression profile prepared from the subject neutrophils can then be compared to the expression profiles prepared from neutrophils isolated from patients with various sterile inflammatory diseases to determine which expression profile most closely matches the expression profile prepared from the subject, thereby, diagnosing whether the subject as a sterile inflammatory disease.
  • Phenotypic diversity includes both normal variation associated with a change in physiological state and abnormal variation associated with a pharmacological or disease state.
  • One aspect of the current invention differentiates between abnormal variation associated with disease and/or pharmacological state and normal variation associated with physiological state.
  • a preferred embodiment of the current invention matches an experimental sample to one or more reference samples that match the experimental sample in at least one parameter that is a determinant of physiological status, pharmacological and/or disease status and compares the expression profiles of the experimental and reference samples.
  • the current invention is used to identify genes that are differentially expressed between matched samples.
  • the embodiments of the present invention are also applicable to diagnosing the disease state of a sample.
  • the embodiments of the present invention are also applicable to characterizing and monitoring disease states. This includes identifying and monitoring the level of a disease state as well as monitoring the effect of therapies on a disease state.
  • the embodiments of the present invention are also applicable to identifying and monitoring drug responses that are specific to a given physiological state.
  • the present invention is also useful for designing drug therapies that are tailored to the physiological state of a subject.
  • the present invention in one aspect can also be used to identify the physiological or pharmacological state of a sample.
  • the invention involves gathering information about the physiological, pharmacological and/or disease state of a sample. If 5 for example, the goal is to diagnose disease in an experimental sample from a human patient one aspect of the invention is to discover information about the physiological and pharmacological state of the sample. Another aspect of the invention is to match the experimental sample to reference samples of similar physiological and pharmacological state. This requires knowledge of the physiological and pharmacological state of the reference sample. In this example, another aspect of the invention that the reference samples are also of known disease status to allow diagnosis of the disease state of the experimental sample. Information about physiological state can be gathered in a variety of ways.
  • the sex can be obtained for example through an interview, a visual inspection or through karyotyping.
  • Information about genotypic state can be derived by sequence analysis. There are a variety of methods, such as array based analysis, standard sequencing techniques, and other commercially available methods.
  • Information about disease state can be also be obtained through a variety of mechanisms such as identification of symptoms or morphological examination of effected tissue. Determinants of disease state include phenotypic symptoms, level of disease, progress of therapy. It is possible to have more than one disease contributing to the disease state of the sample.
  • Information about pharmacological state can similarly be obtained through a variety of mechanisms. In some circumstances a subject can be interviewed. Under other circumstances it may be necessary to inspect the medical history of the subject or to assay for evidence of drug use through chemical analysis of blood, urine, skin, saliva or hair.
  • the best expression profile to use as a reference sample is an average from a plurality of expression profiles of common physiological state.
  • a phenotypic disease state may alter physiological state expression profile (women with a history of sexual abuse have dramatically altered levels of certain hormones-this would be a disease state that might go clinically undetected).
  • samples can be matched by disease state, by physiological state, or by pharmacological state, or any combination of these states.
  • the objective is to minimize differences between the experimental and reference samples.
  • variation between the experimental and reference sample is limited to a single aspect of a disease, physiological or pharmacological state that is being interrogated.
  • the invention removes variation due to one or more indicators of physiological status, pharmacological status or disease status.
  • the invention removes variation due to one or more indicators of physiological status and one or more indicators of pharmacological status. In another aspect the invention removes variation due to one or more indicators of physiological status and one or more indicators of disease status. In another aspect the invention removes variation due to one or more indicators of disease status and one or more indicators of pharmacological status.
  • the reference sample(s) is selected to match the experimental sample in at least one parameter that is a determinant of physiological state. In this aspect of the invention it is preferable that the reference sample(s) matches the experimental sample in many parameters that are determinants of physiological state.
  • the reference sample and the experimental sample could be from subjects that are similar in age, gender, reproductive status or ethnic origin, any combination of these aspects or other aspects that are determinants of physiological state.
  • the reference sample is selected to match the experimental sample in at least one aspect of a disease state. In this aspect of the invention it is preferable that the reference sample(s) matches the experimental sample in many parameters that are determinants of disease state.
  • the reference sample is selected to match the experimental sample in at least one aspect of a pharmacological state.
  • the reference sample(s) matches the experimental sample in many parameters that are determinants of pharmacological state.
  • matched experimental and reference samples are compared to identify differences. Comparisons that can be made include, but are not limited to: diseased to normal from matching physiological state, diseased to diseased from different physiological states, normal to normal from different physiological states, diseased to diseased from the same physiological state, and normal to normal from the same physiological state.
  • a sample of unknown physiological state can be compared to a plurality of samples of known physiological state to identify the physiological state of the sample.
  • expression profiles will be compared.
  • expression profiles are compared to identify genes that are differentially expressed between the samples.
  • This embodiment of the invention is useful, for example, for identifying genes that are differentially expressed in a diseased and normal sample or in different levels of disease.
  • Genes that are differentially expressed can be used as diagnostic or prognostic markers or drug/therapy targets or indicators of physiological or pharmacological status. They can be used individually or in sets of, for example, 2, 5, 10, 20, 30, 100, 150, 200, 250, 500, or 1,000 or more.
  • the identified genes can be used to design probes for microarrays.
  • Diagnosing Disease States In a particularly preferred embodiment the current invention can be used to diagnose disease. Reference samples are selected to match the experimental sample in physiological and/or pharmacological state and to represent a plurality of different known disease states. The expression profile from the experimental sample is then compared to a plurality of expression profiles from reference samples to identify one or more reference samples that match the expression profile of the experimental sample. The experimental sample is diagnosed with the disease of the matching reference sample(s).
  • the disease states represented are selected from a subset of diseases that match one or more symptoms in the experimental sample. For example, if the experimental sample is from a 30-year-old female patient with difficulty becoming pregnant, samples from 30-year-old females diagnosed with specific forms of infertility can be chosen as reference samples.
  • Monitoring Disease States Following the diagnosis of a particular disease in a patient or subject it is often useful to obtain information about the level of the disease state. If diagnosis is followed by therapy it is also often useful to obtain information about the level of the disease state during and after therapy.
  • the invention is used to identify or characterize the stage of a tumor.
  • Tumorogenic experimental samples are compared to reference samples that are matched to the experimental sample in one or more indicators of physiological or pharmacological status.
  • Reference samples with well characterized tumors are selected. Comparison can be of morphological features or of other biological readouts including expression profiles.
  • the present method stages tumors by comparison to reference samples of matching physiological and/or pharmacological state, thus eliminating gene expression differences that result from differences in physiological and/or pharmacological state that may not be relevant to the disease state.
  • the present invention can be used for monitoring the disease state of a subject undergoing one or more therapies. This requires the comparison of a sample before treatment with samples following treatment. There may be changes to the physiological state of the patient that occur over the course of the therapy that are unrelated to the therapy. When comparing a sample before treatment to a sample after treatment it will be preferable to identify changes between the samples that result from a change in physiological state. In one aspect the current invention identifies changes that are the result of physiological change rather than therapeutic intervention.
  • the current invention can be used to correlate differences in drug efficacy with differences in physiological state. Some drug therapies are highly effective in one patient but ineffective or deleterious in another patient. Differences in drug efficacy may correlate with differences in genotypic state, disease state or physiological state.
  • the current invention can be used to identify changes in gene expression following drug treatment that are specific to a physiological state. This could facilitate the discovery/design of therapies that are specific for the physiological state of the patient. Drug therapies will have different effects depending on the physiological status of subject. Some drug therapies have different side effects in different physiological states. Some drug therapies have different efficacies in men and women; in particular many are less effective in women than in men. In a preferred embodiment the current invention is used to identify drug effects that are specific to women. In another preferred embodiment the method is used to identify drug effects that are specific to men.
  • the invention can also be used to identify therapeutic regimens that are optimized for the physiological state of the patient.
  • Therapeutic treatments ideally impart maximal disease reduction with minimal adverse side effects, but many therapeutic treatments do have undesirable side effects. These side effects may be specific to the physiological state of the sample.
  • the current invention could be used as a tool to design therapeutic regimens that are specific for the physiological state of the subject.
  • a sample for which relatively little information is known about the subject from which the sample was supplied could be compared to a plurality of expression profiles of known physiological status in order to determine the physiological status of the subject.
  • a blood or semen sample isolated from a crime scene could be used to obtain information about the physiological status of the criminal, such as age and ethnic origin.
  • a relational database is preferred and can be used, but one of skill in the art will recognize that other databases could be used.
  • a relational database is a set of tables containing data fitted into predefined categories. Each table, or relation, contains one or more data categories in columns. Each row contains a unique instance of data for the categories defined by the columns.
  • a typical database for the invention would include a table that describes a sample with columns for age, gender, reproductive status, expression profile and so forth. Another table would describe a disease: symptoms, level, sample identification, expression profile and so forth. See U.S. Ser. No. 09/354,935, which is hereby incorporated by reference in its entirety for all purposes.
  • the invention matches the experimental sample to a database of reference samples.
  • the database is assembled with a plurality of different samples to be used as reference samples.
  • An individual reference sample in one embodiment will be obtained from a patient during a visit to a medical professional.
  • the sample could be for example a tissue, blood, urine, feces or saliva sample.
  • Information about the physiological, disease and/or pharmacological status of the sample will also be obtained through any method available. This may include, but is not limited to, expression profile analysis, clinical analysis, medical history and/or patient interview. For example, the patient could be interviewed to determine age, sex, ethnic origin, symptoms or past diagnosis of disease, and the identity of any therapies the patient is currently undergoing. A plurality of these reference samples will be taken.
  • a single individual may contribute a single reference sample or more than one sample over time.
  • confidence levels in predictions based on comparison to a database increase as the number of reference samples in the database increases.
  • some of the indicators of status will be determined by less precise means, for example information obtained from a patient interview is limited by the subjective interpretation of the patient. Additionally, a patient may lie about age or lack sufficient information to provide accurate information about ethnic or other information. Descriptions of the severity of disease symptoms is a particularly subjective and unreliable indicator of disease status.
  • the database is organized into groups of reference samples. Each reference sample contains information about physiological, pharmacological and/or disease status.
  • the database is a relational database with data organized in three data tables, one where the samples are grouped primarily by physiological status, one where the samples are grouped primarily by disease status and one where the samples are grouped primarily by pharmacological status. Within each table the samples can be further grouped according to the two remaining categories. For example the physiological status table could be further categorized according to disease and pharmacological status.
  • the present invention may be embodied as a method, data processing system or program products. Examples of computer programs and databases are shown in U.S. Ser. Nos.
  • the present invention may take the form of data analysis systems, methods, analysis software and etc.
  • Software written according to the present invention is to be stored in some form of computer readable medium, such as memory, hard-drive, DVD ROM or CD ROM, or transmitted over a network, and executed by a processor.
  • the present invention also provides a computer system for analyzing physiological states, levels of disease states and/or therapeutic efficacy.
  • the computer system comprises a processor, and memory coupled to said processor which encodes one or more programs.
  • U.S. Pat. No. 5,733,729 illustrates an example of a computer system that may be used to execute the software of an embodiment of the invention.
  • This patent shows a computer system that includes a display, screen, cabinet, keyboard, and mouse.
  • the mouse may have one or more buttons for interacting with a graphic user interface.
  • the cabinet preferably houses a CD-ROM or DVD-ROM drive, system memory and a hard drive which may be utilized to store and retrieve software programs incorporating computer code that implements the invention, data for use with the invention and the like.
  • a CD is shown as an exemplary computer readable medium
  • other computer readable storage media including floppy disk, tape, flash memory, system memory, and hard drive
  • a data signal embodied in a carrier wave may be the computer readable storage medium.
  • the patent also shows a system block diagram of a computer system used to execute the software of an embodiment of the invention.
  • the computer system includes monitor, and keyboard, and mouse.
  • the computer system further includes subsystems such as a central processor, system memory, fixed storage (e.g., hard drive), removable storage (e.g., CD-ROM), display adapter, sound card, speakers, and network interface.
  • Other computer systems suitable for use with the invention may include additional or fewer subsystems.
  • another computer system may include more than one processor or a cache memory.
  • Computer systems suitable for use with the invention may also be embedded in a measurement instrument. The embedded systems may control the operation of, for example, a GeneChip.RTM. Probe array scanner as well as executing computer codes of the invention.
  • Computer methods can be used to measure the variables and to match samples to eliminate gene expression differences that are a result of differences that are not of interest. For example, a plurality of values can be input into computer code for one or more of a: physiological, pharmacological or disease states. The computer code can thereafter measure the differences or similarities between the values to eliminate changes not attributable to a value of interest. Examples of computer programs and databases that can be used for this purpose are shown U.S. Ser. Nos. 09/354,935, 08/828,952, 09/341,302, 09/397,494, 60/220,587, and 60/220,645, which are hereby incorporated by reference in their entireties.
  • microarrays will be used to measure expression profiles. Microarrays are particularly well suited because of the reproducibility between different experiments. DNA microarrays provide one method for the simultaneous measurement of the expression levels of large numbers of genes. Each array consists of a reproducible pattern of thousands of different DNAs attached to a solid support. Labeled RNA or DNA is hybridized to complementary probes on the array and then deteced by laser scanning. Hybridization intensities for each probe on the array are determined and converted to a quantitative read-out of relative gene expression levels. The data can be further analyzed to identify expression patterns and variation that correlates with the biological state of the sample. (See U.S. Pat. Nos.
  • High-density oligonucleotide arrays are particularly useful for monitoring the gene expression pattern of a sample.
  • total mRNA isolated from the sample is converted to labeled cRNA and then hybridized to an array such as a GeneChip.RTM. oligonucleotide array.
  • Each sample is hybridized to a separate array. Relative transcript levels are calculated by reference to appropriate controls present on the array and in the sample. See Mahadevappa, M. & Warrington, J. A. Nat. Biotechnol. 17, 1134-1136 (1999) which is hereby incorporated by reference in its entirety for all purposes.
  • the current invention is particularly useful when applied to analysis of experimental samples from female subjects. Women differ from men in the physiological indicator of gender, which contributes to an as yet uncharacterized level of differential gene expression. In addition, there is a tremendous amount of normal variation between female subjects and between different samples from the same female subject. In particular, the female reproductive system and the menstrual cycle add an additional level of physiological variation to the analysis of samples derived from female subjects. As part of a monthly cycle the lining of the female uterus, the endometrium, undergoes a cycle of controlled tissue remodeling unparalleled in other organs. This cycle is presumably driven by changes in gene expression.
  • the current invention correlates information about variation in gene expression with variation in gender.
  • Male and female samples that are matched in other indicators of physiological state are compared to identify genes that are differentially expressed.
  • a healthy 30-year-old male of similar, i.e., European, descent could be compared to a healthy 30-year-old female of European descent to identify genes that are differentially expressed between the two physiological conditions.
  • the current invention could also be used to monitor changes in pharmacological status resulting from drug treatments, taking normal physiological variation into account.
  • the subjects in the first example could be compared again following therapeutic treatment.
  • the genes that were identified in the first example would be compared or subtracted from the genes identified in the second example to identify genes that are differentially expressed as a result of the therapy.
  • the current invention diagnoses diseases of the female reproductive system.
  • Many disorders of the female reproductive system have relatively poor methods of diagnosis and prognosis and many are typically diagnosed based simply on patient perception, which tends to be unreliable.
  • pre-menstrual syndrome effects large numbers of women, but is typically diagnosed only when other explanations for the observed symptoms are eliminated.
  • More reliable methods of diagnosis such as the use of gene expression profiles for diagnosis and prognosis have been complicated by the changes in gene expression that accompany the normal physiological variation of the system.
  • Menopause is a woman's final menstrual period, but currently the actual event can be determined only in retrospect, after she has not had a period for 12 continuous months. Menopause can occur naturally any time between the mid-30s through the late 50s, but can also be brought on prematurely by events such as gynecological surgery, cancer therapy and certain illnesses and diseases.
  • the current invention can be used to determine a molecular profile consistent with a diagnosis of menopause that would allow earlier diagnosis.
  • the current invention diagnosis diseases of the female reproductive organs.
  • An expression profile from an experimental sample is compared to expression profiles from reference samples that match the experimental sample in physiological state.
  • the reference samples represent a plurality of different disease states that effect the uterus and the experimental sample is identified as being of the disease state of the reference sample that is the closest match.
  • the samples can be derived from, for example, endometrial tissue, myometrial tissue, and/or uterine tissue.
  • a database of reference samples could be comprised of expression profiles from endometrial samples and data points identifying the physiological, pharmacological and/or disease state of the samples. These reference samples would be from many different individuals representing many different physiological, pharmacological and/or disease states.
  • the reference samples can be derived from for example: normal tissue at different stages of development and differentiation, tissues affected with a variety of pathological conditions, including but not limited to, premenstrual syndrome, PMDD, stress urinary incontinence, polycystic ovarian disease, endometriosis, endometrial cancer, infertility, hormone imbalance, and tissue subjected to a variety of perturbations including but not limited to hormone replacement therapy, or chemical contraception.
  • reference samples will be taken from individuals during routine doctor visits.
  • the reference samples would represent different physiological states of the menstrual cycle including but not limited to the secretory and proliferative stages of the endometrium.
  • nucleic acid samples may contain transcripts of interest.
  • suitable nucleic acid samples may contain nucleic acids derived from the transcripts of interest.
  • a nucleic acid derived from a transcript refers to a nucleic acid for whose synthesis the mRNA transcript or a subsequence thereof has ultimately served as a template.
  • a cDNA reverse transcribed from a transcript, an RNA transcribed from that cDNA, a DNA amplified from the cDNA, an RNA transcribed from the amplified DNA, etc. are all derived from the transcript and detection of such derived products is indicative of the presence and/or abundance of the original transcript in a sample.
  • suitable samples include, but are not limited to, transcripts of the gene or genes, cDNA reverse transcribed from the transcript, cRNA transcribed from the cDNA, DNA amplified from the genes, RNA transcribed from amplified DNA, and the like.
  • Transcripts may include, but not limited to pre-mRNA nascent transcript(s), transcript processing intermediates, mature mRNA(s) and degradation products. It is not necessary to monitor all types of transcripts to practice this invention. For example, one may choose to practice the invention to measure the mature mRNA levels only.
  • such sample is a homogenate of cells or tissues or other biological samples.
  • such sample is a total RNA preparation of a biological sample.
  • a nucleic acid sample is the total mRNA isolated from a biological sample.
  • the total MRNA prepared with most methods includes not only the mature MRNA, but also the RNA processing intermediates and nascent pre-mRNA transcripts.
  • total MRNA purified with poly (T) column contains RNA molecules with poly (A) tails. Those poly A+ RNA molecules could be mature mRNA, RNA processing intermediates, nascent transcripts or degradation intermediates.
  • Biological samples may be of any biological tissue or fluid or cells. Frequently the sample will be a "clinical sample” which is a sample derived from a patient. Clinical samples provide rich sources of information regarding the various states of genetic network or gene expression. Some embodiments of the invention are employed to detect mutations and to identify the function of mutations. Such embodiments have extensive applications in clinical diagnostics and clinical studies. Typical clinical samples include, but are not limited to, sputum, blood, blood cells (e.g., white cells), tissue or fine needle biopsy samples, urine, peritoneal fluid, and pleural fluid, or cells therefrom. Biological samples may also include sections of tissues such as frozen sections taken for histological purposes. Another typical source of biological samples are cell cultures where gene expression states can be manipulated to explore the relationship among genes. In one aspect of the invention, methods are provided to generate biological samples reflecting a wide variety of states of the genetic network.
  • RNase present in homogenates before homogenates can be used for hybridization.
  • Methods of inhibiting or destroying nucleases are well known in the art.
  • cells or tissues are homogenized in the presence of chaotropic agents to inhibit nuclease.
  • RNases are inhibited or destroyed by heat treatment followed by proteinase treatment.
  • Methods of isolating total mRNA are also well known to those of skill in the art. For example, methods of isolation and purification of nucleic acids are described in detail in Chapter 3 of Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization With Nucleic Acid Probes, Part I. Theory and Nucleic Acid Preparation, P. Tijssen, ed. Elsevier, N.Y. (1993) and Chapter 3 of Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization With Nucleic Acid Probes, Part I. Theory and Nucleic Acid Preparation, P. Tijssen, ed. Elsevier, N.Y. (1993)).
  • the total RNA is isolated from a given sample using, for example, an acid guanidinium-phenol-chloroform extraction method and polyA.sup.+ mRNA is isolated by oligo dT column chromatography or by using (dT)n magnetic beads (see, e.g., Sambrook et al., Molecular Cloning: A Laboratory Manual (2nd ed.), VoIs. 1-3, Cold Spring Harbor Laboratory, (1989), or Current Protocols in Molecular Biology, F. Ausubel et al., ed. Greene Publishing and Wiley-Interscience, New York (1987)). See also PCT/US99/25200 for complexity management and other sample preparation techniques, which is hereby incorporated by reference in its entirety.
  • PCR polymerase chain reaction
  • LCR ligase chain reaction
  • RT-PCR typically incorporates preliminary steps to isolate total RNA or mRNA for subsequent use as an amplification template.
  • One tube mRNA capture methods may be used to prepare poly(A)+ RNA samples suitable for immediate RT- PCR in the same tube (Boehringer Mannheim). The captured mRNA can be directly subjected to RT-PCR by adding a reverse transcription mix and, subsequently, a PCR mix.
  • the sample mRNA is reverse transcribed with a reverse transcriptase and a primer consisting of oligo dT and a sequence encoding the phage T7 promoter to provide single stranded DNA template.
  • the second DNA strand is polymerized using a DNA polymerase.
  • T7 RNA polymerase is added and RNA is transcribed from the cDNA template. Successive rounds of transcription from each single cDNA template result in amplified RNA.
  • Methods of in vitro polymerization are well known to those of skill in the art (see, e.g., Sambrook, supra).
  • the direct transcription method described above provides an antisense (aRNA) pool.
  • aRNA antisense
  • the oligonucleotide probes provided in the array are chosen to be complementary to subsequences of the antisense nucleic acids.
  • the target nucleic acid pool is a pool of sense nucleic acids
  • the oligonucleotide probes are selected to be complementary to subsequences of the sense nucleic acids.
  • the probes may be of either sense as the target nucleic acids include both sense and antisense strands.
  • the protocols cited above include methods of generating pools of either sense or antisense nucleic acids. Indeed, one approach can be used to generate either sense or antisense nucleic acids as desired.
  • the cDNA can be directionally cloned into a vector (e.g., Stratagene's p Bluscript II KS (+) phagemid) such that it is flanked by the T3 and T7 promoters. In vitro transcription with the T3 polymerase will produce RNA of one sense (the sense depending on the orientation of the insert), while in vitro transcription with the T7 polymerase will produce RNA having the opposite sense.
  • a vector e.g., Stratagene's p Bluscript II KS (+) phagemid
  • In vitro transcription with the T3 polymerase will produce RNA of one sense (the sense depending on the orientation of the insert), while in vitro transcription with the T7 polymerase will produce RNA having the opposite sense.
  • Other suitable cloning systems include phage lambda
  • a specific application of the above methods is a method for diagnosing endometrial cancer in an endometrial tissue sample, where the method involves obtaining a gene expression profile from the endometrial tissue sample where expression of the following genes is measured: KIAA0367, KIAAOl 19, platelet activating factor acetylhydrolase IB gamma-subunit, UDP-galactose transporter related ioszyme, HMG-I and Lamin B; and identifying the sample as being cancerous if KIAA0367 expression is downregulated as compared to normal (e.g., a normal control sample) and KIAAO 119, platelet activating factor acetylhydrolase IB gamma-subunit, UDP-galactose transporter related ioszyme, HMG-I and Lamin B expression is upregulated as compared to normal (e.g., a normal control sample).
  • arrays were washed (with 6 times SSPE and 0.5 times SSPE containing Triton X-100 (0.005%)), and stained with streptavidin-phycoerythrin (SAPE; Molecular Probes, Eugene, Oreg.). Quantification of bound labeled probe was conducted using the Agilent G2500A GeneArray scanner (Agilent Technologies, Palo Alto, Calif.).
  • the total fluorescence intensity for each array was scaled to the uniform value of 600.
  • Chip performance was quantitated by calculating a signal to noise ratio (raw average signal/noise). Chips were removed from further analysis if their signal-to-noise ratio was less than 5. Genes were only included in further analysis if they were called "present” in at least 10% of the chips. Approximately 12,000 Affymetrix probe sets remained following this cutoff. The quality of the gene expression data was further controlled by identifying outliers based on principal components analysis and by analyzing the normal distributions of the gene intensities.
  • Receiver operator curves were used to choose appropriate thresholds for each classifier, requiring a sensitivity of at least 90%.
  • the ROC diagnostic calculates the sensitivity and specificity for each parameter.
  • gene markers were first ranked for their ability to stratify good outcome from poor outcome using a training set of 29 randomly chosen samples. The predictive value of each gene was then tested on the remaining 29 samples. This allowed for the identification of genes with the most robust predictive values.
  • Example 4 of the publication description exemplified the identification of genes that are differentially expressed between responders and non-responders.
  • Bone marrow samples were obtained for gene expression analysis from 80 patients prior to drug treatment. Of the 80 base-line samples, 14 were removed from the analysis since they came from non- evaluable patients. Samples were enriched for myeloid cells, processed for messenger RNA (the molecules that encode for gene-specific proteins), and hybridized to the Affymetrix U133A gene chip. 58 of the 66 samples passed additional quality control measures following hybridization to the Ul 33 A chip.
  • the gene expression data was integrated with the clinical information and retrospective analyses were performed to identify genes that could stratify responders from non-responders with a high level of sensitivity.
  • a survival analysis showed that patients who were classified as responders based on oncoLBC expression significantly outperformed patient classification using the clinical data. This was due to the oncoLBC marker identifying a subset of non-responders with an increased overall survival. Based on the Cox hazard model, combining the oncoLBC and a second gene marker, the aryl hydrocarbon receptor (AHR), increased the specificity and positive predictive value to 75% and 56%, respectively. These results indicated that using either the oncoLBC alone, or in combination with the AHR gene presents an effective array for predicting response to ZamestraTM treatment.
  • AHR aryl hydrocarbon receptor
  • Example 5 of the publication concerned identification of genes that are differentially expressed between responders and non-responders (Repeat Analysis). As described, supervised analysis was performed using the gene expression data to identify additional genes that were differentially expressed between all responders and at least 40% of non-responders.
  • genes that could predict response to Tipifamib with the highest level of sensitivity possible.
  • a total of 19 genes were identified that could stratify responders and non-responders (shown in Tables 7 and 8 of the publication) and that gave significant p-values in the t-test (p ⁇ 0.05).
  • the genes include those involved in signal transduction, apoptosis, cell proliferation, oncogenesis, and potentially, FTI biology (ARHH, LBC and, IL3RA).
  • Example 6 of the publication concerned identification of a minimal set of 3 gene markers.
  • LOOCV was used to determine the optimal number of genes.
  • Classifiers were built with increasing number of genes based on t- test p-values, and the error rate of these classifiers was calculated using LOOCV while keeping the sensitivity of predicting response at 100%. It was found that a 3-gene classifier (including LBC, AHR, and MINA53) could predict response with the lowest error rate. This was also seen when a leave-five-out cross validation was performed. When more genes were added the error rate increased indicating that additional genes introduced noise to the classifier. For the 3-gene classifier the LOOCV demonstrated a sensitivity of 86% and specificity of 70% with an overall diagnostic accuracy of 74
  • range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, unless clearly indicated to the contrary description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as each of the individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.

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Abstract

L'invention concerne un procédé permettant d'obtenir de meilleurs résultats pour des applications de tout genre qui utilisent directement ou indirectement des résultats de dosage d'expression génétique.
PCT/US2006/023046 2005-06-13 2006-06-13 Procede permettant d'obtenir de meilleurs resultats pour des applications qui utilisent directement ou indirectement des resultats de dosage d'expression genetique Ceased WO2006135904A2 (fr)

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WO2011110751A1 (fr) 2010-03-12 2011-09-15 Medisapiens Oy Procédé, agencement et produit-programme d'ordinateur permettant d'analyser un échantillon biologique ou médical
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CN110322924A (zh) * 2010-04-29 2019-10-11 加利福尼亚大学董事会 利用关于基因组模型的数据集成的途径识别方法(paradigm)
US10254204B2 (en) 2011-03-07 2019-04-09 Accelerate Diagnostics, Inc. Membrane-assisted purification
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US9434937B2 (en) 2011-03-07 2016-09-06 Accelerate Diagnostics, Inc. Rapid cell purification systems
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US11603550B2 (en) 2013-03-15 2023-03-14 Accelerate Diagnostics, Inc. Rapid determination of microbial growth and antimicrobial susceptibility
US9677109B2 (en) 2013-03-15 2017-06-13 Accelerate Diagnostics, Inc. Rapid determination of microbial growth and antimicrobial susceptibility
US10669566B2 (en) 2015-03-30 2020-06-02 Accelerate Giagnostics, Inc. Instrument and system for rapid microorganism identification and antimicrobial agent susceptibility testing
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US10619180B2 (en) 2015-03-30 2020-04-14 Accelerate Diagnostics, Inc. Instrument and system for rapid microorganism identification and antimicrobial agent susceptibility testing
US10253355B2 (en) 2015-03-30 2019-04-09 Accelerate Diagnostics, Inc. Instrument and system for rapid microorganism identification and antimicrobial agent susceptibility testing
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CN110019155A (zh) * 2017-09-30 2019-07-16 山西医科大学 microRNA组学数据扰动平台
CN110019155B (zh) * 2017-09-30 2023-04-07 山西医科大学 microRNA组学数据扰动平台
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