KR20070031902A - Identification and characterization of a subset of glioblastomas sensitive to treatment with imatinib - Google Patents

Abstract

The present invention provides methods for diagnosing a cell proliferative disease in mammals in vitro using provided genetic labels, predicting behavior of a mammal suffering from cell proliferative disease in response to medical treatment with one or more PDGF receptor antagonists. And a method of selecting a mammal that is expected to respond to medical treatment with one or more PDGF receptor antagonists while suffering from a cell proliferative disease.

Description

IDENTIFICATION AND CHARACTERIZATION OF A SUBSET OF GLIOBLASTOMAS SENSITIVE TO TREATMENT WITH IMATINIB}

The present invention provides a method for diagnosing a cell proliferative disease in mammals using a provided gene label, a mammal suffering from a cell proliferative disease for medical treatment using one or more platelet-derived growth factor (PDGF) receptor antagonists. A method of predicting the behavior of an animal and a method of selecting a mammal that is predicted to respond to medical treatment with one or more PDGF receptor antagonists while suffering from cell proliferative disease.

Glial tumors are graded into four grades according to World Health Organization criteria. Grading is based on histological criteria such as nuclear atypical, mitotic activity, vascular thrombosis, microvascular proliferation and necrosis. Grade II tumors are genetically classified according to the origin of the cell type into astrocytoma, oligodendrocyte glioma and mixed oligodendrocyte. Grade III is classified into anaplastic astrocytoma and anaplastic oligodendrocyte. Grade IV, the highest form, is known as glioblastoma multiform glioblastoma (GBM).

Thus, glioblastoma (GBM) is the most common adult malignant brain tumor. Currently, therapies are based on surgery, radiation therapy and chemotherapy. However, when using the treatment regimens, the response is extremely poor. The two-year survival of GBM patients is less than 7.5% (Maher et al., 2001). Therefore, confirmation of new treatment strategies is highly guaranteed.

Based on the clinical course of the disease and the characterization of genetic modifications, GBM has been broadly classified as primary and secondary GBM (Maher et al., 2002). Primary GBMs are associated with the proliferation of mutantly modified EGF receptors, while secondary GBMs are characterized by p53 mutation and overexpression of PDGF and PDGF receptors. Secondary GBMs occur in younger patients as compared to primary GBMs. In addition, recent studies have identified a new subset of secondary GBMs characterized by overexpression of genes on chromosome 12q13-14 (Mischel et al., 2003).

Complex expression of PDGF and PDGF receptors in a subset of GBM is compatible with the functional role of signaling of PDGF receptors in autologous secretion in GBM growth. The concept can be demonstrated by an experimental approach. First, GBM-positive tumors can be induced in mice after PDGF overproduction in the brain of mice (Dai et al., 2001; Uhrbom et al., 1998). Second, experimental therapeutic studies with different types of PDGF receptor inhibitors demonstrated that growth of GBM derived cell lines could be blocked by inhibiting PDGF receptor signaling (Kilic et al., 2000; Shamah et al., 1993; Strawn et al., 1994).

The utility of clinically useful PDGF receptor antagonists such as Compound (I) has demonstrated the potential for therapeutic efficacy by inhibiting PDGF receptor signaling in tumors (see Pietras et al., 2003). Compound (I), in addition to the PDGF receptor, also blocks tyrosine kinase activity of c-Kit, c-Abl, Bcr-Abl and Arg, but is an orally available tyrosine kinase inhibitor (Capdeville et al., 2002). Reference). Studies of patients with CML and GIST associated with abnormalities of Bcr-Abl and c-Kit, respectively, have demonstrated clinical usefulness of compound (I) (Demetri et al., 2002; O'Brien et al., 2003).

As mentioned above, a novel therapeutic strategy for successfully treating a mammal, preferably a human, with GBM, but more generally a cell proliferative disease, has been disclosed since there has not been a satisfactory treatment of GBM to date. It is required to pay.

As used herein, a "mammal" is a warm blooded mammal, including humans.

A "biological sample" according to the invention is a sample of a mammal obtained from any biological material isolated from the mammal's body, including tissues, cells, plasma, serum, cells or tissue lysates, and preferably tumor tissues. . Such samples can be obtained by biopsy, for example.

The expression “platelet-derived growth factor (PDGF) receptor antagonist” herein refers to any agent that blocks PDGF receptor signaling, such as PDGF ligands or antibodies that target the receptor, which interfere with the binding of PDGF to the receptor. Soluble receptors or aptamers in recombinant form and LMW compounds that directly inhibit PDGF receptor kinase activity, such as Compound (I) (see below) and other reagents with similar mechanisms of action, and pharmaceutically acceptable salts thereof. Preferably the PDGF receptor antagonist useful for the action of the present invention is the following compound (I), or a pharmaceutically acceptable salt thereof.

The expression “pharmaceutically acceptable” is generally safe, non-toxic, biologically, alternatively, preferably, in the manufacture of pharmaceutical compositions comprising those acceptable for pharmaceutical use in mammals, preferably humans. Means useful.

A “pharmaceutically acceptable salt” is intended to mean a salt that retains the biological effectiveness of the free acids and bases of a particular compound (eg, Compound (I) or other PDGF receptor antagonist) and which is biologically or otherwise desirable. Examples of pharmaceutically acceptable salts include sulfate, pyrosulfate, bisulfate, sulfite, bisulfite, phosphate, monohydrogenphosphate, dihydrogenphosphate, metaphosphate, pyrophosphate, chloride, bromide, iodide, acetate , Propionate, decanoate, caprylate, acrylate, formate, isobutyrate, caproate, heptanoate, propionate, oxalate, malonate, succinate, suverate, sebecate, fumarate , Maleate, butyne-1,4-dioate, hexyn-1,6-dioate, benzoate, chlorobenzoate, methylbenzoate, dinitrobenzoate, hydroxybenzoate, methoxybenzoate, phthalate, Sulfonate, xylenesulfonate, phenylacetate, phenylpropionate, phenylbutyrate, sheet Sites, lactate, γ- hydroxybutyrate, glycollate, tartrate, methane-sulfonate include, propanesulfonate, naphthalene-1-sulfonate, naphthalene-2-sulfonate, mandelate and the rate.

Inorganic acids such as hydrochloric acid, hydrobromic acid, sulfuric acid, nitric acid, phosphoric acid and the like, or organic acids such as acetic acid, maleic acid, succinic acid, mandelic acid, fumaric acid, malonic acid, fibric acid, oxalic acid, glycolic acid, salicylic acid, pyra Nosidyl acid, such as glucuronic acid or galacturonic acid, alpha-hydroxy acid, such as citric acid or tartaric acid, amino acids, such as aspartic acid or glutamic acid, aromatic acid, such as benzoic acid or cinnamic acid, sulfonic acid Desired by any suitable method known in the art, including treatment with PDGF receptor antagonists, eg, the free base of compound (I), using, for example, p-toluenesulfonic acid or ethanesulfonic acid, and the like. Salts can be prepared.

If a compound, salt, or solvate is a solid, the person skilled in the art will understand that the compounds, salts, and solvates may exist in different crystalline forms, all of which are intended to be included within the scope of the invention and certain formulas. will be.

"Pharmaceutical composition" is also referred to herein as synonymous "pharmaceutical formulation" or "drug."

PDGF receptor antagonists comprising Compound (I), and pharmaceutically acceptable salts or solvates thereof, may be administered as pharmaceutical compositions of any pharmaceutical formulation that can be appreciated by those skilled in the art. Suitable pharmaceutical formulations include solid, semisolid, liquid or lyophilized formulations such as tablets, powders, capsules, suppositories, suspensions, liposomes, and aerosols. In addition, the pharmaceutical compositions may include suitable excipients, diluents, vehicles and carriers, and other pharmaceutical active agents, depending upon the use or mode of administration.

Acceptable methods of preparing the appropriate pharmaceutical formulation of the pharmaceutical composition can be routinely determined by one skilled in the art. For example, if a tablet form is required to obtain a desired product for oral, parenteral, topical, intravaginal, intranasal, bronchial, intraocular, intraocular and / or rectal administration, the ingredients are suitably mixed and granulated Pharmaceutical formulations can be prepared according to the conventional techniques of a pharmaceutical pharmacist, including the steps of crushing and compacting, mixing, filling and dissolving.

Solid or liquid pharmaceutically acceptable carriers, diluents, vehicles, or excipients may be used in the pharmaceutical composition. Examples of solid carriers include starch, lactose, calcium sulfate dihydrate, clay, sucrose, talc, gelatin, pectin, acacia, magnesium stearate, and stearic acid. Examples of liquid carriers include syrup, peanut oil, olive oil, saline, and water. Prolonged-release materials suitable as carriers or diluents, such as glyceryl monostearate or glyceryl distearate, may be included alone or in combination with waxes. When using a liquid carrier, the preparation may be in the form of syrups, elixirs, emulsions, soft gelatin capsules, sterile water for injection (eg liquids), or insoluble or water soluble liquid suspensions.

Administration of PDGF receptor antagonists, in particular compound (I), and pharmaceutically acceptable salts and solvates thereof may be effected according to any generally accepted mode of administration available to those skilled in the art. Examples of suitable modes of administration include oral, nasal, parenteral, topical, transdermal, and rectal administration.

A single dose of the pharmaceutical composition contains at least a therapeutically effective amount of the active compound (eg, compound (I) or a pharmaceutically acceptable salt or solvate thereof), preferably in one or more pharmaceutical formulation units. It is composed. Topically, for example as an ointment or cream; Orally, rectally, for example as suppositories; Parenterally by injection; Or a mammal, preferably a human patient, in need of treatment by any known or suitable dosage method of administration, including continuous administration by intravaginal, intranasal, bronchial, otic, or intraocular infusion. It may be administered in a dosage.

A "therapeutically effective amount" is intended to mean an amount of active agent that, when administered to a mammal in need thereof, is sufficient to be effective in treating a cell proliferative disease. The amount of therapeutically effective compound may vary depending on factors such as, for example, the particular compound, disease state and severity thereof, and the identity of the mammal in need thereof, and the amount can be routinely determined by one of skill in the art. .

The "treatment" or "treatment" of a disease state is:

(1) preventing a disease, ie, clinically treating a disease state in a mammal, preferably a human, that may be exposed to or susceptible to the disease state but has not yet experienced or exhibited symptoms of the disease state. Preventing redness from developing;

(2) inhibiting the disease state, ie, arresting the occurrence of the disease state or clinical symptoms thereof; or

(3) alleviating the disease state, that is, temporarily or continuously regressing the disease state or clinical symptoms thereof.

(4)

As used herein, "disease state" refers to a cell proliferative disease suggestive of accumulation of designated cell types and includes all tumors, cancers, carcinomas, sarcomas, lymphomas, blastomas, and the like. Preferably, the cell proliferative disease is glioblastoma.

The terms "genetic label", "biomarker", "label", and "feature" are synonymous and are used interchangeably herein.

Compound (I) is 4- (4-methylpiperazin-1-ylmethyl) -N- [4-methyl-3- (4-pyridin-3-yl) pyrimidin-2-ylamino) having the formula Phenyl] -benzamide:

Compound (I) free base, pharmaceutically acceptable salts thereof, and their preparation are described in registered European patent EP 0564409, which is incorporated herein by reference. Compound (I) free base matches the active site. Compound (I) is an inhibitor of platelet-derived growth factor receptor alpha and beta (PDGFRα and β), Bcr-Abl and c-kit tyrosine kinases.

Hereinafter, monomethanesulfonic acid addition salts of compound (I), referred to as salt (I), and preferred crystalline forms thereof, such as beta crystalline forms, are described in registered European patent EP 0998473, which is incorporated herein by reference. have.

Thus, the first aspect of the invention is at least

a) providing a biological sample from a mammal;

b) a method for diagnosing in vitro a cell proliferative disease of a mammal comprising measuring the expression and / or phosphorylation profile in a sample of at least 2 to 40 gene labels selected from Table 3.

Advantageously, the expression and / or phosphorylation profile of at least only three to five gene labels selected from Table 3 are measured in step b).

The expression level and / or phosphorylation status of the gene label may be based on RNA expression using, for example, RT-PCR techniques, or, for example, Western blotting, immunohistochemistry or ELISA (enzyme immunoassay), eg The biological sample can be analyzed by any conventional technique based on protein expression using any of the following techniques: immunological measurement, immunoprecipitation and electrophoretic analysis. Preferably, those skilled in the art will determine the expression level and / or phosphorylation level of a gene label in a sample.

For example, the expression and / or expression of the label using antibodies specific for the genetic label of its non-phosphorylated form, or its phosphorylated form, or both of its non-phosphorylated form and its phosphorylated form, may be used in standard immunological assays. Phosphorylation levels can be measured. In addition, for example, expression and / or phosphorylation of labels using ELISA-type assays, immunoprecipitation-type assays, conventional Western blotting assays, and immunohistochemical assays using monoclonal or polyclonal antibodies. The level can be measured.

According to a second aspect, the invention at least

a) providing a biological sample from a mammal;

b) measuring expression and / or phosphorylation profile in a sample of at least 2 to 40 gene labels selected from Table 3;

c) compare the expression and / or phosphorylation profile obtained in step b) with respect to the mean ± standard deviation calculated from Table 3 for reactive and non-reactive expression and / or phosphorylation profiles;

d)-if the expression and / or phosphorylation profile obtained in step b) is within the mean ± standard deviation range calculated for reactive expression and / or phosphorylation profile, then the mammal is expected to respond to the treatment;

If the expression and / or phosphorylation profile obtained in step b) is within the mean ± standard deviation range calculated for the non-responsive expression and / or phosphorylation profile, then the mammal is not expected to respond to the treatment;

If the expression and / or phosphorylation profile obtained in step b) is outside the range of mean ± standard deviation calculated for the reactive and non-reactive expression and / or phosphorylation profile, the mammal's behavior for the treatment is not determined. A method of predicting the behavior of a mammal suffering from a cell proliferative disorder for medical treatment using one or more PDGF receptor antagonists, comprising predicting the behavior of the animal.

In certain embodiments the expression and / or phosphorylation profile of at least only three to five gene labels, selected from Table 3, is measured in step b).

According to a third aspect, the invention at least

a) predicting mammalian behavior using the methods described above;

b) where the mammal is expected to respond, then select a mammal with a cell proliferative disease that is expected to respond to a medical treatment using one or more PDGF receptor antagonists, including selecting the mammal It is about how to.

The mammal may be selected for various purposes, for example, to initiate a clinical trial or to receive a medical therapy using one or more PDGF receptor antagonists or pharmaceutically acceptable salts thereof.

A fourth aspect of the invention provides for the expression and / or expression of a genetic marker in a mammal comprising cDNAs and / or antibodies for at least 2 to 40, preferably 3 to 5 genetic markers selected from Table 3 A kit for analyzing phosphorylation profiles in vitro.

In a fifth aspect the present invention provides for the expression and / or expression of genetic markers in mammals comprising cDNAs and / or antibodies against at least two to forty, preferably three to five, genetic markers selected from Table 3 A microarray or biochip for analyzing phosphorylation profiles in vitro.

The sixth aspect of the present invention

As a genetic marker for diagnosing cell proliferative diseases of mammals in vitro; And / or

As a genetic marker for predicting the behavior of a mammal suffering from a cell proliferative disorder for medical treatment with one or more PDGF receptor antagonists; And / or

Use of one or more genes and / or one or more gene products selected from Table 3 as genetic markers for selecting mammals with cell proliferative disorders predicted to respond to medical treatment using one or more PDGF receptor antagonists It is about.

In this regard, cDNAs corresponding to the gene, and / or antibody (s) specific for the gene product (either its phosphorylated form, or its unphosphorylated form, or both) are advantageously used.

According to the seventh aspect the present invention

For in vitro diagnosis of cell proliferative diseases of mammals; And / or

For predicting the behavior of mammals suffering from cell proliferative diseases for medical treatment with one or more PDGF receptor antagonists; And / or

The use of the aforementioned kits, microarrays or biochips for the selection of mammals suffering from cell proliferative diseases which are predicted to respond to medical treatment with one or more PDGF receptor antagonists.

According to an eighth aspect the present invention relates to the use of one or more PDGF receptor antagonists in the manufacture of a medicament for the treatment of a reactive mammal with a cell proliferative disorder selected using the above described method.

The invention also relates to a method of treating a cell proliferative disorder in a reactive animal in need of treatment comprising administering a therapeutically effective amount of PDGF receptor antagonist to a selected reactive mammal using the methods described above. .

In certain embodiments, the PDGF receptor antagonist is included in the pharmaceutical composition.

The invention is illustrated by the following drawings, without limitation:

Figure 1. GBM  Culture Growth rate  And compound (I) -sensitive

(A) 4000 cells per well were seeded in a 24-well plate, and cultured for 4 days, and then the number of cells was measured to determine the growth rate of 23 GBM cultures. Values are expressed as growth fold over the incubation period and as mean values from two independent experiments. (B) In order to determine the sensitivity to compound (I), 4000 cells of each of 16 GBM cultures except for the slowest growing 7 cultures were seeded in 96-well plate wells and 1 μM of compound (I) Incubation was for 4 days in the presence or absence. The number of cells at the end of the culture was measured by staining with crystal violet and photometric measurement. Compound (I) -sensitivity is expressed as percent growth inhibition induced by compound (I) treatment. The results presented with the standard deviation were derived from three independent experiments in which each culture was analyzed in quadruplicates. (C) The correlation between growth rate and compound (I) -sensitivity is explained by presenting the results of a scatter plot with a Pearson correlation coefficient of 0.39.

Fig 2. GBM  In culture PDGF  Receptor Expression and Activation

WGA-fractions from GBM cultures were subsequently immunoblotted using antibodies recognizing PDGFRα, PDGFRβ and phosphotyrosine to determine the expression level and activation state of PDGFα- and β-receptors in different cell cultures. Samples from cells expressing receptors were used for standardization between different filters as specificity controls. (A) Representative of immunoblotting analysis of GBM culture and control cells. Expression of PDGFα-Receptor (B) and PDGFβ-Receptor (C) in GBM Culture. Cell lines were arranged according to PDGFα-receptor expression levels. The expression level in GBM culture 21 was optionally set as 1. Insertion shows correlation between expression of PDGFα- and β-receptors measured by immunoblotting and mRNA expression analysis (Pearson's correlation coefficient, PDGFα-receptor r = 0.86, PDGFβ-receptor r = 0.52). (D) Tyrosine phosphorylation of PDGFR as measured by phospho-tyrosine immunoblotting. The area of the filter corresponding to the complex shift position of PDGFα-receptor and PDGFβ-receptor was analyzed. Cell lines were arranged as in B and C. Total PDGF receptor phosphorylation in GBM culture 21 was optionally set as 1.

Figure 3. Compound (I) -Sensibility PDGFR  Correlation between states.

Compound (I) sensitivity and PDGFα-receptor expression (left top panel), PDGFβ-receptor expression (right top panel), combined PDGFα- and β-receptor expression (left bottom panel) and total PDGF receptor tyrosine phosphorylation (right bottom panel) ) Is shown. The analysis was performed on the remaining 11 GBM cultures after excluding the 5 GBM cultures with the largest difference between the experiments in the compound (I) -sensitive experiment.

Figure 4. GBM In culture ERK  And Akt Phosphorylation levels of these compounds and their parameters (I) sensitivity or PDGF  Correlation Between Receptor Status

Specific phosphorylation of ERK and Akt was measured by immunoblotting using antibodies recognizing p44 / 42 MAPK, phospho-p44 / 42 MAPK Thr202 / Tyr204, Akt and phospho-Akt Ser473. ECL signals were measured and normalized to differences in transfer efficiency between filters using control digests. Relative phosphorylation of ERK (A) and Akt (C) in 10 GBM cultures and phosphorylation of ERK, Akt and compound (I) sensitivity (B, D, upper left panel), PDGF receptor expression (B, D, upper right Panel) and PDGF receptor phosphorylation (B, D, left panel).

Figure 5. Akt  And ERK Analysis of the efficacy of compound (I) on phosphorylation of and the above parameters and compound (I) sensitivity and PDGF  Correlation Between Receptor States.

Compound (I) -induced changes in ERK and Akt were observed by comparing ERK and Akt phosphorylation in untreated cells and cells preincubated with 1 μM of Compound (I) for 1 hour. Compound (I) -induced changes in ERK (A) and Akt (C) phosphorylation in 10 GBM cultures and the parameters and compound (I) sensitivity (B, D, upper left panel), PDGF receptor expression (B , D, upper right panel) and PDGF receptor phosphorylation (B, D, left panel).

Figure 23 23 using three different criteria for feature selection used in clustering assays. Glioblastoma  Hierarchical of cell cultures ( Hierarchical Clustering

(A) ANOVA test contains 88 elements with a p-value less than 0.05, while simultaneously exhibiting more than two-fold upregulation in at least three GBM cultures and two-fold downregulation in at least three other GBM cultures. Hierarchical clustering by Pearson's correlation coefficient containing gene lists. (B) Clustering of GBM cultures containing a list of 2795 characteristics obtained by setting the significance level to 0.05 in the ANOVA test. (C) Clustering after creation of a list of 311 properties, obtained as in (B) but with significance according to the ANOVA test p <0.000000001. Regardless of which criterion was used to select the list of characteristics, in all cases 17 out of 23 GBM cultures had the same distribution, i.e. 3 with GBM cultures 5, 7, 8 and 11 always clustered together. Color coding was used to explain that the main cluster was formed.

Figure 7. GBM  Three subgroups of culture ( subgroup Clustering of genes that define

The features used for the GBM cell clusters described in FIG. 6A were instrumentally clustered by Pearson's correlation coefficient, which presents a relationship tree for the properties. Through clustering, gene groups were analyzed according to similarity in expression patterns in 23 GBM cultures. Red and green indicate high and low expression of genes in individual GBM cultures, respectively.

Figure 23. GBM  Compilation of the results obtained after biochemical characterization of the culture, and expression profiling

The clustering presented is characterized after screening for features in which the p-value is less than 0.05 in the ANOVA test and at the same time indicates more than two-fold upregulation in at least three GBM cultures and two-fold downregulation in at least three other GBM cultures. It was obtained (Fig. 6A). The description of the growth rate is as in FIG. 1A, the number showing the fold increase in the number of cells over the 4 day incubation period. Sixteen GBM cultures analyzed in relation to compound (I) susceptibility included 6 responders (+, showing growth inhibition above 40%), 7 non-responders (−; showing growth inhibition below 20%) and 3 Dog responders (*; growth inhibition rate of 20-40%). The 21 GBM cultures analyzed for PDGF receptor expression and phosphorylation were divided into two groups with high (+; 10 GBM cultures) or low (-; 11 GBM cultures) with PDGF receptor expression or phosphorylation.

Figure 9. live -One-out leave - one - out ) Compound (I) responder in the test and No response Weighted-voting classification of children

Cell lines 6, 7, 9 and 31 were selected as responders and 5, 18, 21, 30, 35 and 38 were selected as non-responders for sorting. The x-axis describes the number (1-250) of the characteristics used for the sorting, and the y-axis described the fraction of cultures misclassified in the rib-one-out test.

10. Training set ( training set 5 excluded from) GBM  Classifier implementation on culture

The signals from grading from 10 glioblastoma cells were predicted for the response of five additional GBM cultures using a classifier consisting of 3-5 characteristics and consisting of the top characteristics in the signal for the graded gene list. The staple diagram shows compound (I) sensitivity of the culture as measured in FIG. 1B. Each bar at the bottom shows the classification of five GBM cultures obtained by a property list consisting of three, four, or five properties. Confidence in prediction with different classifiers for each cell culture is presented by confidence value.

The invention will be better understood with reference to the following detailed description of the experiment including the examples. Nevertheless, those skilled in the art will understand that the description of the experiment is not limited and may be variously modified, substituted, omitted, and modified without departing from the scope of the present invention.

I- materials and methods

I-1-tissue culture and GBM  Culture Growth rate  And compound (I) -sensitivity measurement

Establishment of primary GBM cultures was done according to standard methods (Ponten and Westermark, 1978). Primary cell cultures derived from glioblastomas were cultured in MEM supplemented with 10% FBS, 10 U / ml penicillin and 10 μg / ml streptomycin at 37 ° under an atmosphere of 5% CO ₂ . Cells were seeded at a density of 4000 cells / well in 24 well plates (Sarstedt) to measure growth rate. After incubation for 4 days, cells were harvested by trypsin digestion and counted on a Coulter cell counter. Growth rate was expressed as an increase in multiples of the number of cells during the incubation period. The data presented are derived from two independent experiments, in which each assay was run in duplicate.

I-2-Growth Inhibition Induced by Compound (I)

Compound (I) was obtained from Novartis Pharmaceuticals. For each experiment, 6 mg of Compound (I) was dissolved in 10 ml PBS, and then sterilized with a 45 μm filter to prepare a new 1 mM Compound (I) stock solution. Cell cultures whose growth rate did not exceed 1.2 fold over a four day period were not tested for growth inhibition induced by compound (I). Cells were seeded at a density of 4000 cells per well in 96 well plates (sarstedt) to determine the efficacy of Compound (I) on cell growth. The next day, the medium was replaced with medium with or without 1 μM compound (I). After 4 days of incubation, including media change after 2 days, cells were fixed for 30 minutes in cold 4% paraformaldehyde (PFA) in PBS and stained for 30 minutes with 0.01% crystal violet in 4% ethanol. The sample was washed three times with tap water and air dried for at least 30 minutes. Stained cells were lysed in 100 μl 1% SDS and absorbance was measured with a Biomek 1000 (Beckman) optics using a 600 nm filter.

Efficacy of compound (I) was expressed as% of increase in cell number over 4 days of treatment, so 100% growth drop corresponds to the same number of cells at the end and initiation of the incubation period. . Each experiment as a positive control previously included cells exhibiting compound (I) -sensitive growth (Sjoblom et al., 2001). Data presented on the efficacy of Compound (I) for each GBM culture are derived from two or three independent assays conducted in duplicate / 4.

I-3- PDGF  Receptor, ERK  And Akt Control cells for analysis of expression and phosphorylation status Decomposition  Produce

Aortic endothelial cells (PAE / Rα and PAE / Rβ cells (Claesson-Welsh et al., 1988; Claesson-Welsh et al., 1989) of pigs stably transfected with PDGF α- or β-receptors were cultured in standard culture conditions. High density seeding in a 10 cm dish (sarstedt) was used 16 hours later, cells were depleted of serum for 24 hours by exchange with medium containing 0.1% FBS, followed by 100 ng in medium containing 0.1% FBS. Cells were treated for 5 minutes at 37 ° with or without / ml PDGF-BB After washing with ice cold PBS, 0.5% Triton X-100, 0.5% deoxycholic acid, 150 mM NaCl, 20 mM Tris pH 7.5, Cells were digested on ice for 10 minutes in 1 ml of lysis buffer consisting of 10 mM EDTA, 30 mM tetra-sodium diphosphate decahydrate, 1% trasirol, 0.5% phenylmethyl sulfonyl fluoride (PMSF) and 0.5% NaV0 ₃ . After centrifugation at 15000 xg for 15 minutes, the cell lysate was removed. And protein concentration was measured using the BCA Protein Assay Reagent A kit (Pierce) After standardizing protein concentration, incubated with wheat germ aggregate (WGA) -Sepharose for 16 hours at 4 ° to glycoproteins. The cells were centrifuged at 15000 xg for 15 minutes to pellet the WGA-Sepharose beads The supernatant was removed and used as a control for ERK and Akt assays 0.5% Triton X-100, 0.5% di Three times with 1 ml of high salt digestion buffer consisting of oxycholic acid, 500 mM NaCl, 20 mM Tris pH 7.5, 10 mM EDTA, 30 mM tetra-sodium diphosphate decahydrate, 1% trasirol, 0.5% PMSF and 0.5% NaV0 ₃ WGA beads were washed over the WGA-Sepharose fraction of cell lysate-supernatant or glycoproteins, followed by Laemmli buffer (0.0625M Tris-HCl, 10% glycerol, 2% SDS, 5% beta-mercaptoethanol). , 0.0125% Bromophenol Blue ), Heated to 95 ° for 5 minutes and stored at -20 °.

I-4- PDGF  Analysis of Receptor Expression and Phosphorylation

Cell lysates from approximately 500,000 GBM cells, derived from subconfluent cultures stored in medium supplemented with 10% FCS, were prepared as described above. WGA-fractions were isolated as described above from cell lysates with normalized protein content.

Samples were SDS-PAGE using 7% polyacrylamide gels. Control samples from unstimulated or PDGF-BB-stimulated PAE / Rα and PAE / Rβ cells were loaded on each gel. The protein was then electrophoresed to a Hydrobond-C-Extra filter (Amersham Life Science). Block the filter for 1 h in TBS containing 5% BSA for detection of PDGFRβ, then 1 μg / ml 958 (Santa Cruz Bio) in TTBS (10 mM Tris-HCl, pH 7.4, 150 mM NaCl, 0.02% Tween-20) Incubation was overnight with a primary PDGFRβ antibody solution comprising Santa Cruz Biotechnologies. After washing three times for 10 minutes, the filter was incubated for 1 hour with a blush peroxidase coupled donkey anti-rabbit antibody (Amersham Life Science) diluted 1: 25000 and washed three times in TTBS. . Intelligent Darkbox II digital scanner (FUJIFILM) enhances with Lumi-Light plus Western blotting substrate (Roche) according to manufacturer's instructions Antigens were detected by chemiluminescence. After detection, the filter was stripped in stripping buffer (2% SDS, 62.5 mM Tris HCl pH 6.7 and 100 mM beta-mercaptoethanol) at 50 ° for 30 minutes, washed once in TTBS and containing 5% BSA. Block for 1 hour in TBS. For detection of PDGFRα the filter was re-probeed with 1 μg / ml PDGFRα Antibody 338 (Santa Cruz Biotechnology) in TTBS and incubated overnight. Development and detection were carried out as described above. For detection of phosphorylated PDGFR, the filter was reprobed third with 1 μg / ml phosphotyrosine specific antibody PY99 (Santa Cruz Biotechnology) in TTBS and incubated overnight. Development and detection were performed as described above, except using a blush peroxidase coupled both anti-mouse antibody (Amersham Life Science) diluted 1: 50000 in TTBS as a secondary antibody.

Receptor expression and phosphorylation was measured using AIDA software version 3.10.039 (Fujifilm). Values from GBM cultures were correlated with values from control samples to normalize the differences between filters in delivery efficiency. PDGFRα and PDGFR expression levels, and receptor phosphorylation in GBM culture 21 were optionally designated as value 1.

I-5-incubated in the absence or presence of compound (I) GBM In culture Akt  And ERK  Expression and Phosphorylation Analysis

Glioblastoma cell cultures were plated in 12-well plate wells (Falcon) until fusion. The next day, cells were left untreated or treated with 1 μM of compound (I) for 1 hour. Cell lysates were prepared as described above.

Samples with normalized protein content were SDS-PAGE using a 12% gel. Control samples from unstimulated or PDGF-BB-stimulated PAE / Rβ cells were loaded on each gel. Samples were transferred by electrophoresis to a Hydrobond-C-Extra filter (Amersham Life Science). To detect phosphorylated forms of ERK and Akt, filter was blocked in Tris buffered saline pH 7.6 (TBS), 0.137 M NaCl and 0.0035 M Tris-HCl containing 5% BSA for 1 hour and 0.001% Tween-20 1 μg / ml anti phospho-p44 / 42 MAPK Thr202 / Tyr204 (Cell Signaling Technology) or 1 μg / ml anti phospho-Akt Ser473 (cell signaling technology) in TBS (TTBS) Incubate together overnight. After three washes for 10 minutes in TTBS, incubate the filter for 1 hour with both anti-rabbit antibody (Amersham Life Science) coupled with Blush Peroxidase coupled to 1: 25000 and for 10 minutes in TTBS. Wash three times. Antigens were detected by enhanced chemiluminescence using a Lumi-Lite Plus Western Blotting Substrate (ROSOSE) according to the manufacturer's instructions with an Intelligent Darkbox II digital scanner (Fujifilm). After detection, the filter was peeled off in 0.4 M NaOH for 10 minutes, washed once in TTBS and blocked for 1 hour in TBS containing 5% BSA. Filters were reprobed with 1 μg / ml anti p44 / 42 MAPK (cell signaling technology) and 1 μg / ml anti Akt (cell signaling technology) overnight in TTBS for measurement of ERK and Akt expression. Development and detection were carried out as described above. The values were measured using AIDA software version 3.10.039 (FUJIFILM).

Reference samples from PAE / Rβ cells were used to measure relative expression and phosphorylation of ERK and Akt in different GBM cultures. The response to compound (I) treatment was expressed as a fold change in the specific phosphorylation of ERK and Akt.

I-6-for Gene Expression Assays RNA  extraction

RNA was extracted from subconfluent 75 cm culture dewater in one of each of 23 GBM cultures using the RNAeasy kit (Qiagen) according to the manufacturer's instructions. The amount of RNA was assessed spectrophotometrically to yield 10-100 μg of RNA from different cultures. The structural integrity of RNA was confirmed by agarose gel electrophoresis.

I- 7-Competitive Hybridization  for RNA Amplification and labeling

5 μg of RNA from each cell line was used for some modified linear amplifications (Van Gelder et al., 1990). Briefly, 5 μg of RNA, 1 μl of bacterial RNA cocktail, 1 μl of dT-T7 primer (1 μg / ml, SEQ ID NO: 1: AAA CGA CGG CCA GTG AAT TGT AAT ACG ACT CAC TAT AGG CGC) TTT TTT TTT TTT TTT, 4 μl of 5 × Superscript II reaction buffer (Invitrogen), 2 μl of DTT (Invitrogen), 1 μl of Ultratrapure dNTP mix (Clontech (Clontech)), 1 μl RNAsin (Ambion), 1 μl template switch oligo primer (1 μg / ml, SEQ ID NO: 2: AAA CAG TGG TAT CAA CGC AGA GTA CGC GGG) and 2 μl Superscript II (Invitro CDNA was reverse transcribed in a mixture of). 106 μl of water, 15 μl of Advantage 10X PCR buffer (Clontech), 3 μl of UltraPure dNTP mix, 1 μl of RNase H (Promega) and 3 μl for secondary strand synthesis cDNA polymerase (Clontech) was added. The samples were then incubated in a PCR instrument (Applied Bio9systems) at 37 ° for 2 minutes for RNase H digestion. Samples were subsequently incubated at 94 ° for 3 minutes to denature, incubated at 65 ° for 3 minutes for primer annealing and incubated at 75 ° for extension by cDNA polymerase. The reaction was terminated by the addition of 7.5 μl 1M NaOH and 2 mM EDTA and incubated at 65 ° for 10 minutes. The reaction mixture was washed by phenol extraction with 350 μl of water and 500 μl of phenol-chloroform-isoamyl alcohol 25: 24: 1 (Sigma) and 500 in a Microcon YM-100 centrifugal filter. Wash three times with [mu] l of water and finally concentrate to a 16 [mu] l dose. Anti-sense RNA was generated by in vitro transcription using an in vitro transcription kit (Ambion). As described above, cDNA was reverse transcribed from anti-sense RNA in the SuperScript II reaction followed by the production of double stranded DNA in the DNA polymerase reaction. Amplification In the second step, the UTP nucleotide mix was partially substituted with a 1: 3 UTP Cy-dye-UTP mix (Ambion). At the same time, a pool consisting of the same amount of RNA obtained from all cultures was amplified and used as reference in later hybridization experiments.

I-8-Sense cDNA  For chips Cy -dyes- Labeled Anti -sense RNA of Hybridization

Each cell culture was hybridized in triplicate by double dye-exchange, with reference samples of pooled cultures. For each hybridization, 4 μg of labeled sample and 4 μg of labeled pool in 66 μl of 4 μl of cotDNA (1 μg / ml, invitrogen), 4 μl of polyadenylic acid (2 μg / ml, sigma), 8 Mixed with 70 μl ethanol and 7 μl 3M sodium acetate pH 5.2. After settling, the samples were centrifuged at 15000 x g at 4 ° for 20 minutes by incubating at -70 ° for 30 minutes. The pellet was washed with 70% ethanol and air dried for 60 minutes and 8 μl of water and 40 μl of hybridization solution (5 × SSC, 6 × Denhardt's solution, 60 mM Tris-HCl pH 7.6, 0.12% sacosyl) (sarkosyl), 48% formamide, bacterial filtered), heated to 100 ° for 5 minutes and cooled to room temperature. Samples were pre-cooled microarray chips (The Welcome Trust Sanger Institute, Human Version 1.2.1, containing approximately 10,000 elements corresponding to approximately 6000 individual genes, http: // www. sanger.ac.uk/Projects/Microarrays/) and covered with cover glass and incubated at 47 ° in a Corning hybridization chamber containing 40 μl of 40% formamide and 2 × SSC for 16 hours at 47 °. . The chip was washed once in 2 × SSC for 5 minutes, 3 times in 0.1 × SSC and 0.1% SDS for 30 minutes and once in 0.1 × SSC for 10 minutes. Finally, the chips were dried by centrifugation at 1000 rpm for 2 minutes.

I-9-Scanning Arrays of Chips and Data  extraction

The chip was scanned with ScanArray 5000 (GSI Lumonics) using ScannArray software version 3.1 (PackardBioChip Technologies). Expression intensity values were measured using QuantArray software version 3.0.0.0 (Packard Biochip Technology). Unreliable spots were manually signaled and the signal was measured by histogram method.

I-10-Hierarchical Clustering

Data was loaded into GeneSpring and then normalized to LOWESS. A listing was made that included genes differentially expressed by analysis of variance, ANOVA, or arbitrarily set cut-off values. For variance analysis in Gene Spring, the global error model was turned off because the samples could not be assumed to have the same variance, and the Bonferroni model was used for multiple test corrections. The feature list was created in several different ways, but three versions were chosen for final presentation. In the first gene list, the traits present 88 traits, with p-values less than 0.05 in the ANOVA test, and also upregulated by more than two-fold in at least three samples and down-regulated by more than two-fold in at least three samples. The standards had to be fulfilled. The second and third gene lists were written to include 2795 and 311 characteristics and to have inclusion criteria of ANOVA p-values of less than 0.05 or 0.000000001, respectively. Three gene lists were used successively to cluster the cell culture according to the Pearson correlation coefficient.

I-11-to identify marker genes for compound (I) -reactivity Under supervision  analysis

The weighted voting method (Golub et al., 1999) was applied to 10 cell cultures with minimal differences between experiments in growth inhibition experiments. Expression data from 10 cell cultures were loaded into GeneCluster version 2.1.3 beta ( http://www-genome.wi.mit.edu/cancer/software/genecluster2/gc2.html ) (Golub et al., 1999; Tamayo et al., 1999). Tests were performed by rib one out cross validation by running a classification using a different length feature list. The selection for classifying the characteristics is based on using the allowed number of characteristics with the highest center signal for the noise value. Gene clusters are set up to adopt the characteristics with the highest absolute signal for noise values, but the list does not need to include the same number of characteristics from the positive and negative signal side for the gene list by noise class.

Classifiers containing 3-5 characteristics were constructed for evaluation of classifiers on independent sets of GBM cultures. Feature selection was based on the best signal for noise ratio of features among responders and non-responders in the training set. The classifier was then used for classification based on weighted voting methods for classification of five independent GBM cultures whose compound (I) susceptibility was measured experimentally.

II  - result

II - One - GBM  Characterization of Compound (I) -Sensibility of Cultures

Prior to characterizing 23 different cultures with respect to compound (I) susceptibility, growth characteristics of the individual cultures were analyzed by measuring the increase in the number of cells following 4 days of growth in medium supplemented with 10% FCS. As shown in Fig. 1A, a large difference in growth rate was observed. Only the slowest growing cultures showed a 1.2-fold increase in the number of cells after four days of growth, and the fastest growing cultures showed an 18-fold increase in the number of cells.

Growth inhibition induced by compound (I) treatment was analyzed by comparing the number of cells after 4 days of growth in the presence or absence of compound (I). Efficacy of compound (I) is expressed as percentage of decrease in cell number increase during 4 days of treatment. The seven slowest growing cultures were excluded from the assay. Results from three independent experiments on the remaining 16 cultures are shown in FIG. 1B. Significant differences were observed between cultures in response to compound (I) treatment. Cell cultures 5, 18, 21, 30, 34, 35 and 38 all exhibited growth inhibition of less than 15%. In contrast, the growth of cultures 6, 7, 9, 11, 31 and 45 fell by more than 40%. Cultures 8, 13 and 27 showed moderate response with growth inhibition of 20-40%.

Correlation coefficients between the two parameters were calculated to analyze the relationship between growth inhibition and growth rate. As shown in FIG. 1C, the assay provided no evidence of a strong correlation between growth rate and response to Compound (I) treatment.

II - 2 - GBM  In culture PDGF  Correlation of Receptor Expression and Activation and Compound (I) Susceptibility

PDGF receptors are the most promising targets that mediate the growth inhibitory action on compound (I) -induced growth inhibition of GBM culture. PDGF receptor expression and activation were analyzed and the parameters correlated with growth inhibition (FIGS. 2 and 3).

PDGF receptor activation and expression were analyzed by immunoblotting WGA-fractions from cultured GBM cells using antibodies against PDGFα- and β-receptors and phospho-tyrosine antibodies. As a positive control, ligand-stimulated or unstimulated porcine aortic endothelial cells transfected with PDGFα- or β-receptors were used (FIG. 2A). The value for receptor expression, and the value for total PDGF receptor phosphorylation, were optionally set to 1 in culture 21.

As shown in Figures 2B and C, more than 100-fold differences in PDGFα- and β-receptor expression between cultures were observed. Predictions for PDGF receptor protein expression were compared with data from gene expression analysis (see below) and r-values of 0.86 and 0.52 were obtained for PDGFα- and β-receptors, respectively (FIGS. 2B and C, insertions). In addition, PDGF receptor phosphorylation was measured by measuring phospho-tyrosine signals at the complex shift sites of PDGFα- and β-receptors (FIG. 2A, D). Overall the assay yielded a pattern very similar to that obtained by combining PDGFα- and β-receptor expression. Thus, the assay suggested that the culture showed similar phosphorylation per receptor.

Results from the correlation of these data using 11 compound (I) susceptibility of the 16 cultures analyzed are shown in FIG. 3. Cultures 11, 45, 8, 27 and 34 were excluded from the assay because of the large differences in growth inhibition experiments of these cultures. All four analyzed PDGF receptor-related parameters showed a high correlation with compound (I) sensitivity, which showed an r-value ranging from 0.85 (PDGFβ-receptor expression) to 0.73 (PDGFα-receptor expression).

Thus, this analysis revealed a wide range of differences related to PDGF receptor expression in a panel of GBM cultures, and also showed a strong correlation between PDGF receptor expression and Compound (I) sensitivity and overall PDGF receptor phosphorylation and Compound (I) sensitivity. Turned out.

II In the presence and absence of compound (I) ERK  And Akt Activation status

Protein kinases ERK and Akt are important mediators of PDGF receptor signaling and also participate in downstream signaling induced by other types of cell surface receptors, such as, for example, integrins. Both enzymes were activated through phosphorylation and immunoblotting using antibodies specific for the activated and phosphorylated form was used to determine the activation state of the enzyme. The activation status of these enzymes was measured in 11 cultures using robust results from growth inhibition studies. The activation states of both ERK and Akt showed a large difference between cell cultures (FIGS. 4A and C). Activation status is related to compound (I) response (Figures 4B and D, upper left panel), total PDGF receptor expression (Figures 4B and D, upper right panel) or PDGF receptor phosphorylation (Figures 4B and D, left panel) No correlation was observed when there was.

Changes in specific phosphorylation of ERK and Akt induced by treatment with Compound (I) for 1 hour were analyzed to determine whether drug-induced changes in these pathways correlated with Compound (I) response or receptor expression. . Overall, only moderate changes in ERK and Akt phosphorylation were observed after drug treatment (FIGS. 5A and C). No correlation was observed between compound (I) -induced changes and compound (I) reactivity or PDGF receptor status in Akt phosphorylation (FIG. 5D). However, a correlation between drop in ERK phosphorylation and compound (I) -induced growth inhibition was observed (r = -0.47).

The assay suggests a large difference in ERK and Akt activation generated between cell cultures and indicates that the basal level of activation of this pathway is not correlated with PDGF receptor status or compound (I) sensitivity. It also established that Compound (I) treatment did not correlate with strong changes in the total activation state of the signaling molecule. However, some correlations with changes in compound (I) -induced changes in growth response and ERK phosphorylation were also observed.

II -4-21 GBM Gene expression-based clustering of inducible primary cultures

Gene expression profiling was performed to describe similarities and differences based on gene expression between 23 GBM-derived primary cultures. RNA was isolated from low-passage cultures incubated at 10% FCS. RNA was amplified twice in order to obtain sufficient RNA for microarray analysis. The fluorescent dye was incorporated into the RNA at the second amplification. Each culture was analyzed in triplicate using a cDNA array (http://www.sanger.ac.uk/Projects/Microarrays/) containing approximately 10,000 human cDNAs. Reference RNAs consisted of RNA pools from all cultures.

The results from hierarchical clustering are shown in FIG. 6. As shown, different statistical criteria were used to determine which genes should be used for clustering. Regardless of which criterion was used, several matching patterns including 17 of 23 samples could be observed. Cultures 18, 21, 35, and 38 were clustered together in all analytes (cluster 1). In addition, cultures 5, 7, 8 and 11 were found together in all analytes (cluster 2). Finally, groups comprising cultures 9, 10, 15, 16, 31, 34, 37, 43 and 45 (cluster 3) were observed regardless of statistical criteria for gene selection.

FIG. 7 shows clustering diagrams derived after analysis using genes exhibiting at least 2 fold regulation in three samples, including the cluster-limited genes listed in Tables 1 and 2. FIG.

Differentially expressed genes in Table 1 were grouped according to their molecular action as described by the gene ontology program. The 88 hybridization signals used for clustering of cells represent 75 unique genes. 47 of these genes were thought to belong to actions in the gene ontology program; Most genes have been found in category signaling proteins, transcriptional regulators, and proteins involved in attachment or proliferation.

The genes in Table 2 were organized according to the emergence method of gene clusters defining three culture clusters. Its average expression in three culture clusters was concentrated to account for its expression pattern associated with the three culture clusters. Gene clusters III and VI generally consist of genes that are upregulated in culture clusters 2 and 3, respectively. The gene cluster I group is almost always high in the culture cluster 1 group except for a few. In contrast, gene clusters IV and V comprise genes that are down regulated in culture cluster 1 and gene cluster III consists of low expression genes in culture cluster 3.

II -5-growth characteristics and PDGF  Receptor status and GBM  Comparison of Gene Expression-based Clustering of Cultures

The growth rate of GBM cultures, and the results from the compound (I) susceptibility analysis thereof, were combined with the results from metrological clustering of cultures based on gene expression (FIG. 8). Some trends of interest have been observed. Six of the seven slowest growing cultures (shown in bold) were found in cluster 3. Six responders were concentrated in clusters 2 and 3. Everything in cluster 2 was found in subcluster 2b. Four of the seven non-responders (18, 21, 35, 38) constituted a complete set of subclusters 1b.

In addition, the results obtained from PDGF receptor status were compared with grouping of cultures based on gene expression (FIG. 8). Regarding PDGF receptor expression and phosphorylation, cultures were classified into two classes, resulting in 10 cultures with high expression or phosphorylation, and 11 cultures with low expression or phosphorylation. Cluster 1 was certainly supplemented with cultures with low receptor expression and phosphorylation, while Clusters 2 and 3 both consisted of a mixture of two categories. The compilation of this data also emphasized that all six firm compound (I) non-responders exhibited low receptor expression and phosphorylation, while all robust responders were characterized by high receptor expression and phosphorylation.

II For gene expression patterns associated with compound (I) reactivity; Under supervision  Confirm

In connection with the indication that there is a correlation between gene expression pattern and compound (I) reactivity, supervised analysis was conducted for the purpose of identifying gene expression patterns that best correlate with compound (I) reactivity. For this purpose the 10 cultures that give the most obvious results for compound (I) sensitivity are selected from the responders (cultures 6, 7, 9 and 31) and non-responders (cultures 5, 18, 21, 30, 35 and 38) (FIG. 1 B).

The supervised analysis was conducted using a weighted voting method that included a "leave-one-out" check. As shown in FIG. 9, 2-40 properties were used for sorting, and all 10 cultures were correctly sorted by rib-one-out identification. 8 and 16 genes were used for classification, which included a list of 4 and 10 traits, respectively. The genes used in the rib-one-out test are listed in Table 3.

Expression data from all 10 cultures were used to construct classifiers of 3-5 characteristics (Table 4). The classifier was used to accurately describe all 10 cultures used to construct the classifier as responders and non-responders. To extend the assay, classifiers were used for preliminary testing on five cultures (cultures 8, 11, 27, 34 and 45) that were not included in the training set (FIG. 10). The results from the application of this classifier to the preliminary test set are shown in FIG. 10. Interestingly, cultures 11 and 45 were with all three classifiers characterized as responders, identical to the results from growth inhibition experiments. In addition, as with the growth inhibition results, culture 34 was consistently classified as non-responder. Cultures 8 and 27 showing moderate response were with all three responders specified as no responders and responders, respectively. As indicated above, primary GBM cultures vary widely in terms of compound (I) -sensitivity. Characterization of PDGF receptor status showed a clear correlation between compound (I) -sensitivity and PDGF receptor expression and phosphorylation (FIGS. 1-3, 8). No obvious correlation was seen between compound (I) -sensitive or basal phosphorylation of ERK and Akt (FIG. 4). Compound (I) -sensitivity showed some correlation with compound (I) -induced decline in ERK phosphorylation (FIG. 5). Gene expression profiling suggested the presence of different distinct GBM subsets with respect to compound (I) -sensitivity, growth rate and PDGF receptor phosphorylation (FIGS. 6-8). Finally, a supervised analysis of gene expression data could be used to prepare a short list of genes predicting compound (I) -response (FIGS. 9, 10).

Although previous studies have reported on GBM cell lines, an analysis of the systemic effects of PDGF receptor inhibition on GBM growth was described for the first time herein.

The correlation between PDGF receptor status and compound (I) -response (FIG. 3) was significant. Analysis of PDGF receptor expression and phosphorylation suggested a strong co-variation between these parameters, suggesting that ligand-production is not significantly different between cultures.

There is no correlation between the basic activation states of the downstream signaling molecules Akt and ERK, and PDGF receptor states (FIG. 4) suggesting that activation of Akt and ERK in these GBM cultures is under the control of multiple signaling pathways. will be. In this regard it should be noted that both growth-inhibitory experiments and Akt- and ERK-activation assays were performed in cells preserved in the presence of 10% FCS. Thus, it can be seen that the potential impact of PDGF receptor signaling on these pathways can be detected more clearly under different culture conditions.

Analysis of compound (I) -induced changes in Akt and ERK phosphorylation focuses on 10 selected GBM cultures (cultures 6, 7, 9 and 31) and 6 non-responders that exhibit potent growth-inhibiting responses . If Akt-signaling is important in PDGF receptor signaling, it is rather surprising that the predicted growth inhibition efficacy that is likely to be achieved through PDGF receptor inhibition can be observed in the absence of a consistent drop in the activation of Akt (FIG. 5). This finding is explained by the presence of PDGF receptor dependent pAkt, which is affected by PDGF receptor inhibition, rather than detected in cells conserved under culture conditions in which serum components provide high activation of Akt via PDGF in the dependent pathway. Can be. It should be noted that the cell lysate analyzed for compound (I) -induced change in signaling was derived from cells that were only exposed to compound (I) for 1 hour. Thus, it should be confirmed that such a length of time in a well-characterized PDGF-dependent control system is sufficient to induce a detectable change in PDGF receptor-dependent phosphorylation of ERK and Akt.

Multiple analyzes of gene-expression profiles and biochemical characterization revealed a series of correlations of interest (FIGS. 6 and 8). Briefly, cluster 1 is supplemented with cultures with low PDGF receptor expression and low susceptibility to compound (I), cluster 2 is supplemented with compound (I) -responders with high PDGF receptor expression, cluster 3 is mainly growth rate It consists of cultures with low and inconsistent PDGF receptor expression. Preliminary analysis of genes included in gene clusters III, IV and V overexpressed in GBM Cluster 2 supplemented with Compound (I) -Responder (FIG. 7, Table 2) shows specific developmental origins of GBM subsets, or specific biological Failed to present features.

Classifiers describing responders and non-responders were constructed using supervised assays based on characterization of Compound (I) -sensitivity and gene-expression analysis of the GBM panel (FIG. 9, Table 3). In general, the classifier may be used for at least two purposes. First, it can be used as a starting point for the development of diagnostic or prognostic tools. If the classifier's performance is good, the classifier's function can be developed without paying attention to the biological significance of the genes that make up the classifier. Second, the classifier can point out the biological relationship that causes the two phenotypes identified by the classifier in compound (I) -sensitive or -resistant.

references

SEQUENCE LISTING <110> Ludwig Institute for Cancer Research et al Herstrand, Daniel Hesselager, Gan Kister, Monica Ostman, arnne <120> Identification and Characterization of a Subset of Glioblastomas Sensitive to Treatment with Imatinib <130> ON / 4-33771A <150> GB 0410883.3 <151> 2004-05-14 <150> GB 0425257.3 <151> 2004-11-16 <160> 2 <170> PatentIn version 3.2 <210> 1 <211> 57 <212> DNA <213> Artificial <220> <223> Primer <400> 1 aaacgacggc cagtgaattg taatacgact cactataggc gctttttttt ttttttt 57 <210> 2 <211> 30 <212> DNA <213> Artificial <220> <223> Primer <400> 2 aaacagtggt atcaacgcag agtacgcggg 30

Claims (18)

a) providing a biological sample from a mammal; b) measuring expression and / or phosphorylation profile in a sample of at least 2 to 40 gene labels selected from Table 3; c) comparing the gene expression profile of the patient with the average unresponsive expression profile shown in Table 3; d) determining the similarity between the two gene expression profiles formed as a result of the comparison of (b); e) a method for diagnosing a cell proliferative disease in mammals, the method comprising at least determining the likelihood of the patient having a GBM status reactive to the drug by the similarity measured in (c). The method of claim 1, wherein the expression and / or phosphorylation profile of at least three to five gene labels selected from Table 3 are measured in step b). a) providing a biological sample from a mammal; b) measuring expression and / or phosphorylation profile in a sample of at least 2 to 40 gene labels selected from Table 3; c) compare the expression and / or phosphorylation profile obtained in step b) with respect to the mean ± standard deviation calculated from Table 3 for reactive and non-reactive expression and / or phosphorylation profiles; d)-if the expression and / or phosphorylation profile obtained in step b) is within the mean ± standard deviation range calculated for reactive expression and / or phosphorylation profile, the mammal is expected to respond to the treatment; If the expression and / or phosphorylation profile obtained in step b) is within the mean ± standard deviation range calculated for the non-responsive expression and / or phosphorylation profile, predict that the mammal will not respond to the treatment; If the expression and / or phosphorylation profile obtained in step b) is outside the mean ± standard deviation calculated for the reactive and nonreactive expression and / or phosphorylation profile, then the behavior of the mammal as a response to the treatment is not determined. At least comprising predicting the behavior of the mammal, A method of predicting the behavior of a mammal suffering from a cell proliferative disorder for medical treatment using one or more PDGF receptor antagonists. The method of claim 3, wherein the expression and / or phosphorylation profile of at least three to five gene labels selected from Table 3 are measured in step b). a) predicting the behavior of a mammal using the method according to claim 3 or 4; b) when the mammal is expected to respond, then the mammal has a cell proliferative disease that is expected to respond to a medical treatment using at least one PDGF receptor antagonist, the method comprising at least selecting the mammal. How to screen. The method of any one of claims 1 to 5, wherein the mammal is a human. A kit for analyzing in vitro the expression and / or phosphorylation profile of a genetic label of a mammal comprising cDNAs and / or antibodies against at least 2 to 40 genetic labels selected from Table 3. 8. The kit of claim 7, comprising cDNAs and / or antibodies against at least three to five gene labels selected from Table 3. The kit of claim 7 or 8, wherein the mammal is a human. A microarray or biochip for analyzing in vitro the expression and / or phosphorylation profile of a genetic label of a mammal, comprising cDNAs and / or antibodies against at least 2 to 40 genetic labels selected from Table 3. The microarray or biochip of claim 10, comprising cDNAs and / or antibodies against at least three to five gene labels selected from Table 3. The microarray or biochip of claim 10, wherein the mammal is a human. Diagnosing the cell proliferative disease of the mammal in vitro; Predicting the behavior of a mammal suffering from a cell proliferative disorder for medical treatment with one or more PDGF receptor antagonists; Use of one or more genes and / or one or more gene products selected from Table 3 as genetic markers for selecting mammals with cell proliferative disorders predicted to respond to medical treatment using one or more PDGF receptor antagonists . The use according to claim 13, wherein the antibody (s) specific for the cDNA and / or gene product corresponding to the gene are used. Diagnosing the cell proliferative disease of the mammal in vitro; Predicting the behavior of a mammal suffering from a cell proliferative disorder for medical treatment with one or more PDGF receptor antagonists; Use of a kit according to any one of claims 7 to 9 for selecting a mammal having a cell proliferative disease which is predicted to respond to medical treatment using at least one PDGF receptor antagonist. Diagnosing the cell proliferative disease of the mammal in vitro; Predicting the behavior of a mammal suffering from a cell proliferative disorder for medical treatment with one or more PDGF receptor antagonists; Use of a microarray or biochip according to any one of claims 10 to 12 for screening mammals suffering from cell proliferative diseases which are predicted to respond to medical treatment using at least one PDGF receptor antagonist. . Use of at least one PDGF receptor antagonist for use in the manufacture of a medicament for the treatment of a reactive mammal with a cell proliferative disease selected using the method according to claim 5. 18. The use of any of claims 13 to 17, wherein the mammal is a human.