CN1997755A - Identification and characterization of a glioblastoma subpopulation sensitive to imatinib treatment - Google Patents

Abstract

The present invention relates to methods for in vitro diagnosis of a cell proliferative disease in a mammal using specific genetic markers, predicting the behavior of a mammal having a cell proliferative disease in response to a drug treatment using at least one PDGF receptor antagonist, and selecting a mammal having a cell proliferative disease and predicted to be responsive to a drug treatment using at least one PDGF receptor antagonist.

Description

Identification and characterization of a glioblastoma subpopulation sensitive to imatinib treatment

technical field

The present invention relates to the use of specific genetic markers for the in vitro diagnosis of cell proliferative disorders in mammals and the prediction of the response behavior of mammals suffering from cell proliferative disorders to drug treatment with at least one platelet-derived growth factor (PDGF) receptor antagonist , and a method of selecting a mammal having a cell proliferative disorder predicted to respond to drug treatment with at least one PDGF receptor antagonist.

Background technique

Gliomas can be divided into four grades according to the World Health Organization's criteria. Grading is based on histologic criteria such as nuclear atypia, mitotic activity, intravascular thrombosis, microvascular proliferation, and necrosis. According to the cell type of origin, grade II tumors can generally be divided into astrocytoma, oligodendroglioma, and mixed oligoastrocytoma. Grade III can be divided into anaplastic astrocytoma and anaplastic oligodendroglioma. The highest form, grade IV, is commonly known as glioblastoma multiforme (GBM).

Thus, glioblastoma (GBM) is the most common malignant brain tumor in adults. Current treatment is based on surgery, radiation therapy and chemotherapy. However, the response to these treatments has been poor. The two-year survival rate for GBM patients is less than 7.5% (Maher et al., 2001). There is therefore a great need to identify new therapeutic strategies.

Based on the clinical course of the disease and the characterization of its genetic alterations, GBM can be roughly divided into primary and secondary GBM (as reviewed by Maher et al., 2002). Primary GBM is associated with amplification of a mutationally altered EGF receptor, whereas secondary GBM is characterized by p53 mutations and overexpression of PDGF and PDGF receptors. Secondary GBM is seen in younger patients compared with primary GBM. Recent studies have also identified a new subtype in secondary GBM characterized by the overexpression of genes on chromosome 12q13-14 (Mischel et al., 2003).

The co-expression of PDGF and PDGF receptors in GBM subtypes is consistent with a functional link in autocrine PDGF receptor signaling in GBM. This formulation has been supported experimentally. First, overproduction of PDGF in the mouse brain induced GBM-like tumors in mice (Dai et al., 2001; Uhrbom et al., 1998). Second, experimental therapeutic studies with different classes of PDGF receptor inhibitors have shown that growth of GBM-derived cell lines can be blocked by interfering with PDGF receptor signaling (Kilic et al., 2000; Shamah et al., 1993; Strawn et al. People, 1994).

The availability of clinically available PDGF receptor antagonists, such as compound I, demonstrates the possibility of obtaining therapeutic effects by interfering with PDGF receptor signaling in tumors (reviewed in Pietras et al., 2003). Compound I is an orally available tyrosine kinase inhibitor that also blocks the activity of c-Kit, c-Abl, Bcr-Abl and Arg in addition to the PDGF receptor (reviewed by Capdeville et al., 2002). The clinical efficacy of compound I has been well established in studies of patients with CML and GIST (associated with variants of Bcr-Abl and c-Kit, respectively) (Demetri et al., 2002; O'Brien et al., 2003).

As mentioned above, since there is as yet no satisfactory treatment for GBM, there is a need to find new therapeutic strategies that can successfully treat mammals, preferably humans, with GBM, and more generally with cell proliferative disorders.

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

"Biological sample" in the present invention refers to a mammalian sample obtained from any biological material isolated from a mammalian body, including tissue, cells, plasma, serum, cell or tissue lysate, and preferably tumor tissue. Such samples may be obtained, for example, by biopsy.

The expression "platelet-derived growth factor (PDGF) receptor antagonist" herein refers to any agent that can block PDGF receptor signal transduction, including such as antibodies against PDGF ligands or receptors, which can prevent PDGF from interacting with receptors. Conjugated recombinant soluble receptors or aptamers, and low-molecular-weight compounds that directly interfere with PDGF receptor kinase activity, such as compound I (see below) and other agents with similar mechanisms of action, and pharmaceutically acceptable salts thereof. A preferred PDGF receptor antagonist for use in the practice of the present invention is Compound I below, or a pharmaceutically acceptable salt thereof.

The expression "pharmaceutically acceptable" means that it can be used for the preparation of pharmaceutical compositions, which are generally safe, non-toxic, and have no biological or other undesired effects, and also includes those that can be used for mammalian (preferably human) pharmaceutical use.

"Pharmaceutically acceptable salt" refers to salts that retain the biological effectiveness of the free acids and bases of a particular compound (eg, Compound I or other PDGF receptor antagonists) and are not biologically or otherwise unacceptable. Examples of pharmaceutically acceptable salts include sulfates, pyrosulfates, bisulfates, sulfites, bisulfites, phosphates, hydrogenphosphates, dihydrogenphosphates, metaphosphates, pyrophosphates, chlorides, Bromide, Iodide, Acetate, Propionate, Caprate, Caprylate, Acrylate, Formate, Isobutyrate, Hexanoate, Heptanoate, Propiolate, Oxalate , malonate, succinate, suberate, sebacate, fumarate, maleate, butyne-1,4-diolate, hexyne-1,6-diolate, Benzoate, Chlorobenzoate, Methylbenzoate, Dinitrobenzoate, Hydroxybenzoate, Methoxybenzoate, Phthalate, Sulfonate, Xylene Sulfonate, Phenyl Acetate, Phenylpropionate, Phenylbutyrate, Citrate, Lactate, Gamma-Hydroxybutyrate, Glycolate, Tartrate, Methylsulfonate, Propyl Sulfonate, naphthalene-1-sulfonate, naphthalene-2-sulfonate and mandelate.

The desired salt can be prepared by any suitable method known in the art, including the use of inorganic acids (such as hydrochloric acid, hydrobromic acid, sulfuric acid, nitric acid, phosphoric acid, etc.) or organic acids (acetic acid, malic acid, succinic acid, mandelic acid, etc.) , fumaric acid, malonic acid, pyruvic acid, oxalic acid, glycolic acid, salicylic acid, pyranosidic acid (such as glucuronic acid or galacturonic acid), alpha-hydroxy acids (such as citric acid or tartaric acid), amino acids (such as Aspartic acid or glutamic acid), aromatic acid (such as benzoic acid or styrene acid), sulfonic acid (such as p-toluenesulfonic acid or ethanesulfonic acid), etc.) base.

For solid compounds, salts or solvates, those skilled in the art understand that these compounds, salts or solvates may exist in different crystalline forms, all of which are included within the scope of the invention and the specific formulae.

"Pharmaceutical composition" is also referred to herein by the synonymous term "pharmaceutical formulation" or "medicament".

PDGF receptor antagonists including Compound I and pharmaceutically acceptable salts or solvates thereof are suitable for administration in pharmaceutical compositions in any suitable pharmaceutical form recognized by the skilled person. Suitable pharmaceutical forms include solid, semi-solid, liquid or lyophilized preparations, such as tablets, powders, capsules, suppositories, suspensions, liposomes and aerosols. Depending on the specific use or mode of administration, the pharmaceutical composition may also contain suitable excipients, diluents, vehicles and carriers, as well as other pharmaceutically active agents.

Methods that can be used to prepare suitable pharmaceutical forms of pharmaceutical compositions will generally be determined by those skilled in the art. For example, pharmaceutical formulations may be prepared according to conventional medicinal chemistry techniques, including such steps as mixing, filling, and appropriate dissolution of the components to obtain oral, parenteral, topical, intravaginal, intraanal, intratracheal, intraocular, intraaural, and /or rectal administration of the product as desired.

Solid or liquid pharmaceutically acceptable carriers, diluents, vehicles or excipients may be used in the pharmaceutical composition. Exemplary solid carriers include starch, lactose, calcium hydrogen sulfate, terra alba, sucrose, talc, gelatin, pectin, acacia, magnesium stearate and stearic acid. Exemplary liquid carriers include syrup, peanut oil, olive oil, saline solution and water. The carrier or diluent may contain a suitable extended release material, such as glyceryl monostearate or glyceryl distearate alone or in combination with a wax. When a liquid carrier is used, the preparation can be in the form of syrup, elixir, emulsion, soft gel capsule, sterile injectable solution (eg, solution), or as a non-aqueous or aqueous suspension.

Administration of the PDGF receptor antagonists, particularly Compound I, and pharmaceutically acceptable salts and solvates thereof, may be administered according to any of the generally accepted modes available to those skilled in the art. Illustrative examples of methods of administration are oral, nasal, parenteral, topical, transdermal and rectal.

A dose of a pharmaceutical composition contains at least a therapeutically effective amount of an active compound (such as compound I or a pharmaceutically acceptable salt or solvate thereof), and preferably consists of one or more pharmaceutical dosage units. The selected dosage may be administered to a mammal, preferably a human patient, in need of such treatment by any known or suitable method for administering the dosage form, including topically (e.g., in the form of an ointment or cream); orally; rectally (e.g., in the form of an ointment or cream); suppository form); parenterally (by injection); or continuous vaginal, nasal, tracheal, or intraocular administration.

A "therapeutically effective amount" refers to an amount sufficient to produce an active agent that treats a cell proliferative disorder when administered to a mammal in need thereof. The therapeutically effective amount of a compound varies depending on the specific compound, the disease condition and its severity, the mammal in need of the treatment, etc., and the dosage routine is determined by the skilled artisan.

"Treating" a disease state includes:

(1) preventing disease, that is, avoiding clinical symptoms of a disease state in mammalian (preferably human) individuals who may be exposed to or susceptible to the disease state but have not experienced or exhibited the disease symptoms;

(2) inhibit the disease state, that is, block the development of the disease state or its clinical symptoms; or

(3) Alleviation of the disease state, even if the disease state or its clinical symptoms disappear temporarily or permanently.

"Disease state" as used above refers to a cell proliferative disorder, ie accumulation of a certain type of cells, including all tumors, cancers, carcinomas, sarcomas, lymphomas, blastomas, and the like. The cell proliferative disease is preferably glioblastoma.

The terms "genetic marker", "biomarker", "marker" and "characteristic" 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]benzene]-benzene Formamide has the following molecular formula:

The free base of compound I, its pharmaceutically acceptable salts and formulations thereof are disclosed in the granted European patent EP 0564409, incorporated herein by reference. Compound I free base is its active part. Compound I is an inhibitor of platelet-derived growth factor receptor alpha and beta (PDGFR alpha and beta), Bcr-Abl and c-kit tyrosine kinases.

The methanesulfonic acid addition salt of the compound (hereinafter referred to as "salt I") and its preferred crystalline form (eg, the beta crystalline form) are disclosed in granted European patent EP 0998473, incorporated herein by reference.

Accordingly, a first aspect of the present invention relates to a method of in vitro diagnosis of a cell proliferative disorder in a mammal comprising at least:

a) providing a biological sample of said mammal; and

b) Determining the expression and/or phosphorylation profile of at least 2 to 40 genetic markers selected from Table 3 in said sample.

Conveniently only the expression and/or phosphorylation profiles of at least 3 to 5 genetic markers selected from Table 3 are determined in step b).

The expression level and/or phosphorylation state of a genetic marker in a biological sample can be determined by any conventional technique based on, for example, measuring RNA expression using, for example, RT-RNA techniques, or based on, for example, using, for example, Western blot, immunohistochemistry Or ELISA (Enzyme-Linked Immunosorbent Assay), including any technique of immunoassay, immunoprecipitation, and electrophoretic assay to measure protein expression. Preferably the skilled person will determine the expression level of the genetic marker and/or its phosphorylation level in the sample.

For example, expression and/or phosphorylation of a genetic marker can be measured by standard immunoassays using antibodies specific for the non-phosphorylated form, or the phosphorylated form, or both the non-phosphorylated and phosphorylated forms of the genetic marker level. Expression levels and/or phosphorylation of markers can also be determined by ELISA-type assays using, for example, monoclonal or polyclonal antibodies, immunoprecipitation-type assays, conventional Western blot assays, and immunohistochemical assays.

A second aspect of the present invention relates to a method of predicting the response behavior of a mammal suffering from a cell proliferative disorder to drug treatment with at least one PDGF receptor antagonist comprising at least:

a) providing a biological sample of said mammal; and

b) Determining the expression and/or phosphorylation profile of at least 2 to 40 genetic markers selected from Table 3 in said sample.

c) comparing the expression and/or phosphorylation profile obtained in step b) with the mean ± standard deviation calculated according to Table 3 to obtain a reactive and non-responsive expression and/or phosphorylation profile; and

d) predicting the behavior of said mammal as follows:

- said mammal is predicted to respond to the treatment if the expression and/or phosphorylation profile obtained in step b) is within the mean ± standard deviation of the calculated reactive expression and/or phosphorylation status.

- said mammal is predicted to be non-responsive to the treatment if the expression and/or phosphorylation profile obtained in step b) is within the mean ± standard deviation of the calculated non-responsive expression and/or phosphorylation state ;and

- if the expression and/or phosphorylation profile obtained in step b) is outside the range of the mean ± standard deviation of the calculated reactive and non-responsive expression and/or phosphorylation status, the lactation cannot be determined Animal response behavior to the treatment.

In a specific embodiment, only the expression and/or phosphorylation profiles of at least 3 to 5 genetic markers selected from Table 3 can be determined in step b).

A third aspect of the invention relates to a method of selecting a mammal suffering from a cell proliferative disorder that is predicted to respond to drug treatment with at least one PDGF receptor antagonist, the method comprising at least:

a) using the method described above to predict the behavior of said mammal; and

b) selecting the mammal if the mammal is predicted to respond to the treatment.

The mammal may be selected for a number of purposes, such as entering a clinical trial, or administering to it a drug treatment with at least one PDGF receptor antagonist or a pharmaceutically acceptable salt thereof.

A fourth aspect of the present invention relates to a kit for in vitro analysis of expression and/or phosphorylation profiles of genetic markers in mammals, said kit containing at least 2 to 40, preferably 3 to 5 genetic markers selected from Table 3 Labeled cDNA and/or antibodies.

In a fifth aspect, the present invention relates to a microarray or biochip for in vitro analysis of expression and/or phosphorylation profiles of genetic markers in mammals, which contains at least 2 to 40, preferably 3 to 5 genetic markers selected from Table 3 Labeled cDNA and/or antibodies.

A sixth aspect of the invention relates to the use of at least one gene and/or at least one gene product selected from Table 3 as a genetic marker for:

- in vitro diagnosis of cell proliferative disorders in mammals; and/or

- predicting the response behavior of a mammal suffering from a cell proliferative disease to drug treatment with at least one PDGF receptor antagonist; and/or

- selecting a mammal suffering from a cell proliferative disorder, wherein said mammal is predicted to respond to drug treatment with at least one PDGF receptor antagonist.

In this regard, it may be convenient to use cDNA corresponding to the gene, and/or antibodies specific for the gene product (either its phosphorylated form, or its non-phosphorylated form, or both).

A seventh aspect of the present invention relates to the use of the aforementioned kit, microarray or biochip for:

- in vitro diagnosis of cell proliferative disorders in mammals; and/or

- predicting the response behavior of a mammal suffering from a cell proliferative disease to drug treatment with at least one PDGF receptor antagonist; and/or

- selecting a mammal suffering from a cell proliferative disorder, wherein said mammal is predicted to respond to drug treatment with at least one PDGF receptor antagonist.

An eighth aspect of the present invention relates to the use of at least one PDGF receptor antagonist in the manufacture of a medicament for the treatment of a reactive mammal suffering from a cell proliferative disorder, wherein said reactive mammal is selected according to the above method to proceed.

The invention also discloses a method of treating a cell proliferative disorder in a responsive mammal in need of such treatment, comprising administering thereto a therapeutically effective amount of a PDGF receptor antagonist, said responsive mammal being selected according to the methods described above.

In specific embodiments, the PDGF receptor antagonist is contained in a pharmaceutical composition.

The invention is illustrated but not limited by the following figures:

Figure 1. Growth Rate and Compound I Sensitivity of GBM Cultures

(A) The growth rate of 23 GBM cultures was determined by inoculating 4000 cells/well on a 24-well plate and determining the number of cells after 4 days of culture. The value is the fold growth during culture and is the mean of two independent experiments. (B) To determine the sensitivity to Compound I, the remaining 16 GBM cultures were removed from the 7 groups with the slowest growth, and 4000 cells were each inoculated in the wells of a 96-well plate in the presence or absence of 1 μM In the case of Compound I, grow for 4 days. Cell numbers at the end of the culture were determined by crystal violet staining and photometry. Sensitivity to Compound I was expressed as percent growth inhibition induced by Compound I treatment. Results (including standard deviation) are from 3 independent experiments in which each set of cultures was analyzed 4 times. (C) Results are presented in a scatter plot (Pearson's correlation coefficient of 0.39) illustrating the correlation between growth rate and Compound I sensitivity.

Figure 2. Expression and activation of PDGF receptors in GBM cultures

The expression levels and activation status of PDGFα- and β-receptors in different cell cultures were determined by serial immunoblotting of WGA fractions from GBM cultures using antibodies recognizing PDGFRα, PDGFRβ, and phosphorylated tyrosine. Samples from cells expressing either receptor were used as specificity controls and for normalization across filters. (A) Example of representative immunoblot analysis in GBM cultures and control cells. Expression of PDGFα-receptor (B) and PDGFβ-receptor (C) in GBM cultures. Cell lines were ranked according to the expression level of PDGFα-receptor. The GBM culture 21 value was arbitrarily set to 1. Inset shows the correlation between PDGF α- and β-receptor expression determined from immunoblot and mRNA expression analysis (Pearson correlation, PDGF α-receptor r=0.86, PDGF β-receptor r=0.52). (D) Tyrosine phosphorylation of PDGFR as determined by phosphorylated tyrosine immunoblotting. Filtered areas corresponding to the combined migration sites of PDGF α- and β-receptors were analyzed. The cell lines are arranged as in B and C. The total PDGF receptor phosphorylation level in GBM culture 21 was set arbitrarily at 1.

Figure 3. Correlation of Compound I Sensitivity with PDGFR Status

Shown is the correlation of Compound I sensitivity with PDGFα-receptor expression (upper left panel), with PDGFβ-receptor expression (upper right panel), and with combined expression of PDGFα- and PDGFβ-receptors ( Left panel below), and the relationship with total PDGF receptor tyrosine phosphorylation (right panel below). The 5 GBM cultures showing the greatest intra-assay variation in the Compound I sensitivity assay were removed and the remaining 11 GBM cultures were analyzed.

Figure 4. Phosphorylation levels of ERK and Akt in GBM cultures and correlation of these parameters with Compound I sensitivity or PDGF receptor status

Specific phosphorylation of ERK and Akt was determined by immunoblotting using antibodies recognizing p44/42MAPK, phospho-p44/42MAPK Thr202/Tyr204, Akt, and phospho-Akt Ser473. ECL signal was quantified and control lysates were used to normalize differences in transfer efficiency between filters. Relative phosphorylation of ERK (A) and Akt (C) and ERK, Akt phosphorylation and Compound I sensitivity (B, D, upper left panel), PDGF receptor expression (B, D, upper left panel) in 10 GBM cultures Right panels), and the correlation of PDGF receptor phosphorylation (B, D, lower panels).

Figure 5. Analysis of the Effect of Compound I on Akt and ERK Phosphorylation, and the Correlation of These Parameters with Compound I Sensitivity and PDGF Receptor Status

Compound I-induced changes in ERK and Akt were monitored by comparing the phosphorylation of ERK and Akt in untreated cells and cells pre-incubated with 1 μM Compound I for 1 hour. Phosphorylation changes of ERK (A) and Akt (C) in 10 GBM cultures induced by Compound I and the relationship between these parameters and Compound I sensitivity (B, D, upper left panel), PDGF receptor expression (B, D, Upper right panels), and the correlation of PDGF receptor phosphorylation (B, D, lower panels). Figure 6. Hierarchical clustering of 23 glioblastoma cell cultures according to 3 different criteria used to select features in the hierarchical clustering analysis

(A) Hierarchical clustering based on Pearson's correlation with a list of 88-element genes that had an ANOVA test p-value of less than 0.05 and were upregulated greater than 2-fold in at least 3 GBM cultures and in at least 3 additional down-regulated 2-fold in GBM cultures. (B) GBM cultures were clustered from a list comprising 2795 features obtained by setting a significance level of 0.05 in the ANOVA test. (C) As in B, clustered after obtaining a list of 311 features, but setting the significance of the ANOVA test at p<0.000000001. Using color coding to illustrate that no matter what criteria was used to select the feature list, three main clusters were formed showing the same distribution in either case for 17 of the 23 GBM cultures, e.g. GBM cultures 5, 7, 8 and 11 are always clustered together.

Figure 7. Clusters of genes defining the three subtypes of GBM cultures

The features shown in Figure 6A for GBM cell clustering were clustered hierarchically according to Pearson's correlation, resulting in a relational tree for these features. This cluster pair analyzed several sets of genes based on their similarity in expression patterns across 23 GBM cultures. Red and green indicate high and low expression of genes, respectively, in individual GBM cultures.

Figure 8. Compilation after obtaining biological characterization and expression profiling results for 23 GBM cultures

Clusters shown are the result of selecting features with a p-value less than 0.05 in the ANOVA test that were also upregulated >2-fold in at least 3 GBM cultures and down-regulated 2-fold in at least 3 additional GBM cultures ( Figure 6A). The growth rate is depicted in Figure 1A, where the numbers indicate the fold increase in cell number during the 4 days of culture. Regarding Compound I sensitivity, the 16 analyzed GBM cultures were divided into 6 responders (+, indicating greater than 40% growth inhibition), 7 non-responders (-, indicating less than 20% growth inhibition), and 3 moderate Responders (*; 20-40% growth inhibition). Regarding PDGF receptor expression and phosphorylation, the 21 analyzed GBM cultures were divided into two groups with high (+; 10 GBM cultures) or low (-; 11 GBM cultures) PDGF receptor expression or Phosphorylation.

Figure 9. Weighted-voting classification performance of compound I responders and non-responders in the leave-one-out test

Cell lines 6, 7, 9 and 31 were selected for classification as responders and 5, 18, 21, 30, 35 and 38 as non-responders. The x-axis depicts the number of features used for classification (1-250), and the y-axis depicts the fraction of cultures misclassified in the leave-one-out method.

Figure 10. Classifier performance on 5 GBM cultures excluded from the training set

The response of an additional 5 GBM cultures was predicted using a classifier consisting of 3-5 features topping the list of signal-to-noise ratio-ranked genes from 10 glioblastoma cells. The classification chart shows the Compound I sensitivity of the cultures as determined in Figure 1B. The classification of the five GBM cultures according to a list of characteristics consisting of 3, 4 or 5 characteristics is given under each column. The ability of the different classifiers to make predictions for each cell culture is shown with confidence values.

The present invention can be better understood from the following detailed description of experiments, including examples. However, the skilled person should know that the experimental description is not limiting, and various modifications, substitutions, omissions and changes can be made without departing from the scope of the present invention.

Example

I-Materials and methods

Determination of I-1 Tissue Culture and GBM Culture Growth Rate and Compound I Sensitivity

Primary GBM cultures were established according to standard methods (Ponten and Westermark, 1978). Primary cell cultures from glioblastoma were inoculated in MEM supplemented with 10% FBS, 10 U/ml penicillin and 10 μg/ml streptomycin at 37°C in an atmosphere containing 5% CO ₂ .

To determine the growth rate, cells were seeded in 24-well plates (Sarstedt) at a density of 4000 cells per well. After 4 days in culture, cells were harvested by trypsinization and counted with a Coulter cell counter. Growth rate is expressed as the number of doublings of cells during culture. The data presented are from two independent experiments, where each analysis was performed in duplicate.

I-2-Compound I-induced growth inhibition

Compound I was obtained from Novartis Pharmaceuticals. For each experiment, a fresh 1 mM Compound I stock solution was prepared by dissolving 6 mg of Compound I in 10 ml of PBS, then sterile filtered through a 45 μm filter. Compound I-induced growth inhibition was not detected in cell cultures in which the growth rate did not exceed 1.2-fold over the 4 day period. To determine the effect of Compound I on cell growth, cells were seeded in 96-well plates (Sarstedt) at a density of 4000 cells per well. The next day the medium was changed to medium with or without 1 μM Compound I. After 4 days of culture (including medium change after 2 days), cells were fixed in cold PBS containing 4% paraformaldehyde (PFA) for 30 minutes and stained with 0.01% crystal violet in 4% ethanol for 30 minutes. The samples were washed 3 times with tap water and air dried for at least 30 minutes. Stained cells were dissolved in 100 μl 1% SDS and their absorbance quantified with a Biomek 1000 (Beckman) photometric tool (600 nm filter).

The effect of Compound I is expressed as a percentage reduction in cell number growth during the 4 days of treatment, so a 100% reduction in growth corresponds to the same number of cells at the end of the culture period as it was at the beginning. Cells that had shown compound I sensitive growth were included as positive controls in each experiment (Sjöblom et al., 2001). Data shown are from two or three independent analyzes of the effect of Compound I in each GBM culture, all performed in duplicate/quadruplicate.

1-3-Preparation of control cell lysate for analysis of expression and phosphorylation status of PDGF receptors--ERK and Akt

Using standard culture conditions, porcine aortic endothelial cells stably transfected with PDGFα or β receptors (PAE/Rα and PAE/Rβ cells, respectively (Claesson-Welsh et al., 1988; Claesson-Welsh et al., 1989)) were cultured as High density seeding was done in 10 cm dishes (Sarstedt). After 16 hours, the serum in the cells was removed and replaced with a medium containing 0.1% FBS for 24 hours. Cells were then treated for 5 minutes at 37°C in medium with or without 100 ng/ml PDGF-BB in 0.1% FBS. After washing with ice-cold PBS, cells were lysed on ice for 10 minutes in 1 ml lysis buffer containing 0.5% Triton X-100, 0.5% deoxycholic acid, 150 mM NaCl, 20 mM Tris pH 7.5, 10 mM EDTA , 30 mM sodium pyrophosphate decahydrate, 1% aprotinin, 0.5% phenylmethylsulfonyl fluoride (PMSF) and 0.5% NaVO ₃ . After centrifugation at 15000 xg for 15 minutes, cell lysates were collected and protein concentrations were measured using the BCA protein assay reagent A kit (Pierce). After normalization to protein concentration, glycoproteins were isolated by incubation with wheat bacterial agglutinin (WGA)-agarose for 16 hours at 4°C. Centrifuge the samples at 15000 x g for 15 min to pellet the WGA-Sepharose beads. The supernatant was removed and kept as a control for analyzing ERK and Akt. Wash WGA beads 3 times with 1 ml high salt lysis buffer containing 0.5% Triton X-100, 0.5% deoxycholic acid, 500 mM NaCl, 20 mM Tris pH 7.5, 10 mM EDTA, 30 mM sodium pyrophosphate decahydrate , 1% aprotinin, 0.5% PMSF and 0.5% NaVO ₃ . The glycoproteins of the cell lysate supernatant or WGA-agarose fraction were mixed with Laemmli buffer (0.0625M Tris-HCl, 10% glycerol, 2% SDS, 5% β-mercaptoethanol, 0.0125% bromophenol blue), Heat to 95°C for 5 minutes and store at -20°C.

Analysis of I-4-PDGF receptor expression and phosphorylation

Cell lysates of approximately 500,000 GBM cells were prepared as above from confluent cultures maintained in medium containing 10% FCS. WGA fractions with normalized protein content in cell lysates were isolated as above.

Samples were subjected to SDS-PAGE using a 7% polyacrylamide gel. Control samples from unstimulated or PDGF-BB stimulated PAE/Rα and PAE/Rβ cells were placed on each gel. Proteins were then electrophoretically transferred to Hydrobond-C-Extra filters (Amersham Life Science). To detect PDGFRβ, filters were blocked in TBS containing 5% BSA for 1 hour, and then mixed with primary PDGFRβ antibody solution, TTBS containing 1 μg/ml 958 (Santa Cruz Biotechnologies) (10mM Tris-HCl pH 7.4, 150 mM NaCl, 0.02% Tween-20) overnight. After three 10 min washes, the filters were incubated for 1 h with horseradish peroxidase-conjugated donkey anti-rabbit antibody (Amersham Life Science) diluted 1:25000 and washed three times in TTBS. Antigens were detected by enhanced chemiluminescence with an Intelligent Darkbox II digital scanner (FUJIFILM) using Lumi-Light plus Western blotting substrate (Roche) according to the manufacturer's instructions. After detection, the filters were stripped in stripping buffer (2% SDS, 62.5mM TrisHCl pH 6.7, and 100mM β-mercaptoethanol) at 50°C for 30 minutes, washed once in TTBS and blocked in TBS containing 5% BSA for 1 Hour. For detection of PDGFRα, filters were re-bound with TTBS containing 1 μg/ml PDGFRα antibody 338 (Santa Cruz Biotechnologies) and incubated overnight. Perform operations and checks as described above. For detection of phosphorylated PDGFR, filters were re-bound with TTBS containing 1 μg/ml phosphotyrosine-specific antibody PY99 (Santa Cruz Biotechnologies) and incubated overnight. Manipulation and detection were performed as described above, but horseradish peroxidase-coupled goat anti-mouse antibody (Amersham LifeScience) diluted 1:50000 in TTBS was used as the secondary antibody.

Receptor expression and phosphorylation were quantified using AIDA software version 3.10.039 (FUJIFILM). The different transfer efficiencies between the filters were normalized by relating the values of the GBM cultures to the values of the control samples, either setting the values of GBM culture 21 to 1 for PDGFRα and PDGFRβ expression levels and receptor phosphorylation.

I-5 - Analysis of Akt and ERK expression and phosphorylation in GBM cultures grown with or without compound I

Glioblastoma cell cultures were plated confluently into the wells of a 12-well plate (Falcon). The next day cells were treated with or without 1 [mu]M Compound I for 1 hour. Cell lysates were prepared as above.

Samples normalized for protein content were subjected to SDS-PAGE using a 12% gel. Control lysates from unstimulated or PDGF-BB-stimulated PAE/Rα and PAE/Rβ cells were placed on each gel. Proteins were then electrophoretically transferred to Hydrobond-C-Extra filters (Amersham Life Science). To detect phosphorylated forms of ERK and Akt, filters were blocked in Tris-buffered saline pH 7.6 (TBS), 0.137 M NaCl, and 0.0035M Tris-HCl containing 5% BSA for 1 hour, and then mixed with 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 and 0.001% Tween-20 (TTBS) were incubated overnight. After three 10-min TTBS washes, the filters were incubated with horseradish peroxidase-coupled goat anti-rabbit antibody (Amersham Life Science) diluted 1:25,000 for 1 h and washed three times in TTBS for 10 min each. minute. Antigens were detected with an Intelligent Darkbox II digital scanner (FUJIFILM) using Lumi-Light plus Western blotting substrate (Roche) according to the manufacturer's instructions. After detection, the filters were stripped in 0.4M NaOH for 10 minutes, washed once in TTBS and blocked in TBS containing 5% BSA for 1 hour. To detect ERK and Akt expression, filters were probed again with TTBS containing 1 μg/ml anti-p44/42 MAPK (Cell Signaling Technology) and 1 μg/ml anti-Akt (Cell Sighaling Technology) and incubated overnight. Perform operations and checks as described above. Quantification was performed using AIDA software version 3.10.039 (FUJIFILM).

The relative expression and phosphorylation of ERK and Akt in different GBM cultures was determined by using reference samples from PAE/Rβ cells. Response to compound I treatment was expressed as ERK and Akt specific phosphorylation fold change.

I-6 - RNA Extraction for Gene Expression Analysis

RNA was extracted from 75 cm ² confluent plates of each of 23 GBM cultures using the RNAeasy kit (Qiagen) according to the manufacturer's instructions. The amount of RNA was assessed spectrophotometrically, showing that 10-100 μg of RNA could be produced in different cultures. The structural integrity of the RNA was confirmed by agarose gel electrophoresis.

I-7 - Amplification and Labeling of RNA for Competitive Hybridization

Linear amplification with some variation was performed using 5 μg of RNA from each cell line (Van Gelder et al., 1990). Briefly, at 42°C, containing 5 μg RNA, 1 μl bacterial RNA mix, 1 μl dT-T7 primer (1 μg/ml, SEQ ID No 1: AAA CGA CGG CCAGTG AAT TGT AAT ACG ACT CAC TAT AGG CGC TTT TTT TTTTTT TTT ), 4 μl 5X SuperscriptII reaction buffer (Invitrogen), 2 μl DTT (Invitrogen), 1 μl Ultrapure dNTP mix (Clontech), 1 μl RNase inhibitor (Ambion), 1 μl template switching oligo primer (1 μg/ml, SEQ ID No 2 : AAA CAGTGG TAT CAA CGC AGA GTA CGC GGG) and 2 μl Superscript II (Invitrogen) in a mixture of reverse transcribed cDNA for 1 hour. For second strand synthesis, 106 μl water, 15 μl Advantage 10X PCR buffer (Clontech), 3 μl Ultrapure dNTP mix, 1 μl RNase H (Promega) and 3 μl cDNA polymerase (Clontech) were added. Samples were then incubated in a PCR machine (Applied Bio9systems) at 37°C for 2 minutes to complete RNaseH degradation. Samples were then denatured by incubation at 94°C for 3 minutes, incubated at 65°C for 3 minutes to anneal the primers, and extended at 75°C by cDNA polymerase. The reaction was terminated by adding 7.5 μl of 1M NaOH and 2 mM EDTA and incubating at 65 °C for 10 min. The reaction mixture was cleaned by phenol extraction with 350 μl water and 500 μl 25:24:1 phenol:chloroform:isoamyl alcohol (Sigma), washed 3 times with 500 μl water in a Microcon YM-100 centrifugal filter, and finally concentrated to The volume is 16 μl. Antisense RNA was generated by in vitro transcription using an in vitro transcription kit (Ambion). cDNA was reverse transcribed again from this antisense RNA in a Superscript II reaction, followed by a DNA polymerase reaction to generate double-stranded DNA, as described above. In the second step of amplification, the UTP nucleotide mixture was partially replaced by a 1:3 mixture of UTP and Cy-dye-UTP (Ambion). In parallel, a pool consisting of equal amounts of RNA from all cultures was amplified to serve as a reference for the following hybridization experiments. Hybridization of I-8-Cy-dye-labeled antisense RNA and sense cDNA chip

Each cell culture was hybridized with a reference sample of pooled cultures, and double fluorescence exchange was performed to obtain quadruplicate samples. For each hybridization, a volume of 66 μl of 4 μg labeled sample and 4 μg labeled pool was mixed with 4 μl cotDNA (1 mg/ml, Invitrogen), 4 μl polyadenylate (2 μg/ml, Sigma), 8 μl 70% ethanol and 7 μl 3M sodium acetate pH 5.2 was mixed. After precipitation was incubated at -70°C for 30 minutes, the samples were centrifuged at 15000xg, 4°C for 20 minutes. The precipitate was washed with 70% ethanol and dried in air for 60 minutes, then dissolved in 8 μl of water and 40 μl of hybridization buffer solution (5×SCC, 6×Denhardt’s solution, 60 mM Tris-HCl pH 7.6, 0.12% N-dodecane Sodium sarcosinate, 48% formalin, after sterile filtration), heated at 100°C for 5 minutes and cooled to room temperature. Samples were placed on pre-cooled microarray chips (The WelcomeTrust 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/ ), covered with a glass cover, and incubated at 47°C for 16 hours in a Corning hybridization chamber containing 40 μl of 40% formalin and 2×SSC solution at 47°C. The chips were washed once with 2×SSC for 5 minutes, washed three times with 0.1×SSC and 0.1% SDS for 30 minutes, and then washed once with 0.1×SSC for 10 minutes. Finally, the chips were dried by centrifugation at 1000 rpm for 2 minutes.

I-9-Chip Array Scanning and Data Selection

Chips were scanned with a ScanArray 5000 (GSI Lumonics) using ScannArray version 3.1 software (Packard BioChip Technologies). Expression intensity values were quantified using QuantArray version 3.0.0.0 software (Packard BioChip Technologies). Unreliable points were marked manually and the signal was quantified in a histogram method.

I-10 Hierarchical Clusters

Import the data into GeneSpring software and perform LOWESS normalization. A list containing differentially expressed genes was generated by analysis of variance (ie, ANOVA) or with either set cutoffs. To use ANOVA in GeneSpring, the model for the overall error was discarded because it was assumed that the samples would not have the same variance, and the Bonferroni model was used for multiple testing correction. There are several different ways to generate the feature list, but in the end 3 versions were chosen for the final presentation. In the first gene list, the feature has a p-value of less than 0.05 in the ANOVA test and must meet the criteria: that is, it is up-regulated by more than 2 times in at least 3 samples and down-regulated by more than 2 times in at least 3 samples, resulting in a total of 88 a characteristic gene. The second and third gene lists contained 2795 and 311 characteristic genes, respectively, obtained using the inclusion criteria of ANOVA p-value less than 0.05 or 0.000000001. These three gene lists were then used for hierarchical clustering of cell cultures according to Pearson correlation.

I-11 - Supervised analysis to identify marker genes for compound I responsiveness

Weighted voting (Golub et al., 1999) was used for the 10 cell cultures containing minimal inter-experimental variation in growth inhibition assay values. Import expression data from 10 cell cultures into GeneCluster 2.1.3 beta release

(http://www-EMI21.1qenome.wi.mit.edu/cancer/sofiware/qeneduster2/qc2.html) (see Golub et al., 1999; Tamayo et al., 1999). Classification performance of feature lists of different lengths was tested using leave-one-out cross-validation. The selection of categorical features was based on using the allowable number of features with the highest median signal-to-noise ratio. The GeneCluster is set to select the feature with the highest absolute signal-to-noise ratio, and the list does not necessarily contain the same number of features as the front and back sides of the signal-to-noise ratio gene ranking table.

To evaluate classifiers for independent GBM cultures, a classifier with 3-5 features was built. Feature selection is based on the highest signal-to-noise ratio value between responders and non-responders in the training set. These classifiers were then used to classify 5 independent GBM cultures whose Compound I sensitivity had been empirically determined based on a weighted voting process.

II-Results

II-1-Compound I-sensitivity description of GBM cultures

Prior to describing the sensitivity of 23 different cultures to compound I, the growth characteristics of the individual cultures were analyzed by determining the increase in cell number during 4 days in media containing 10% FCS. As shown in Figure 1A, it can be seen that there is a large difference in growth rate. The slowest growing culture had only a 1.2-fold increase in cell number over the 4 day period, whereas the fastest growing culture had an 18-fold increase in cell number.

Growth inhibition induced by Compound I treatment was analyzed by comparing the number of cells after 4 days of growth without and with Compound I. The effect of Compound I was expressed as the percent reduction in cell number growth during the 4 days of treatment. The 7 slowest growing cultures were removed from this analysis. The results of 3 individual independent experiments on the remaining 16 cultures are shown in Figure 1B. The responses of the different cultures to Compound I treatment varied widely. Growth inhibition of cell cultures 5, 18, 21, 30, 34, 35 and 38 was less than 15%. In contrast the growth of cultures 6, 7, 9, 11, 31 and 45 were all reduced by more than 40%. Cultures 8, 13 and 27 responded intermediately with 20-40% growth inhibition.

To analyze whether growth inhibition is related to growth rate, the correlation between these two parameters was calculated. As shown in Figure 1C, this analysis did not provide a strong correlation between growth rate and response to Compound I treatment.

Expression and activation of PDGF receptors in II-2-GBM cultures and their correlation with compound I sensitivity

The PDGF receptor is the most likely target to mediate the growth inhibitory effect of Compound I in inducing growth inhibition in GBM cultures. Therefore, expression and activation of PDGF receptors were analyzed and these parameters correlated with growth inhibition (Figures 2 and 3).

PDGF receptor activation and expression were analyzed by immunoblotting of WGA fractions of cultured GBM cells using antibodies against PDGF alpha and beta receptors as well as antibodies against phosphorylated tyrosine. Ligand-stimulated or unstimulated porcine aortic endothelial cells transfected with PDGFα and β receptors were used as positive controls ( FIG. 2A ). Values for receptor expression and total PDGF receptor phosphorylation in culture 21 were arbitrarily set at 1.

As shown in Figures 2B and C, the difference in expression of PDGFα and β receptors in these cultures was greater than 100-fold. Comparison of estimates of PDGF receptor protein expression with data from gene expression analysis (see below) yielded r values of 0.86 and 0.52 for PDGFα and β receptors, respectively (Figure 2B and C, inset). In addition, phosphorylation of PDGF receptors was determined by quantifying the signal of phosphorylated tyrosines at the combined migration sites of PDGF alpha and beta receptors (Fig. 2A,D). Taken together, this analysis yielded a similar pattern to that obtained in combined PDGF[alpha] and [beta] receptor expression. Therefore, this analysis indicated that each receptor was similarly phosphorylated in the culture.

The results of the correlation of these data with the Compound I sensitivity of 11 of the 16 cultures analyzed are shown in FIG. 3 . Cultures 11, 45, 8, 27 and 34 were omitted from this analysis due to their large differences in growth inhibition experiments. All four analyzed PDGF receptor-related parameters had high correlations with Compound I sensitivity, with r values ranging from 0.85 (PDGFα receptor expression) to 0.73 (PDGFα receptor expression).

Thus, these analyzes revealed widespread differences in PDGF receptor expression in GBM cultures, and also indicated a relationship between PDGF receptor expression and Compound I sensitivity, and between total PDGF receptor phosphorylation and Compound I sensitivity have a strong correlation.

II-3-Activation status of ERK and Akt in the absence or presence of compound I

The protein kinases ERK and Akt are important mediators of PDGF receptor signaling but are also involved in downstream signaling triggered by other cell surface receptors such as integrins. Both enzymes are activated by phosphorylation, so immunoblotting with antibodies specific for the activated phosphorylated form can be used to determine the activation status of these enzymes. The activation status of these enzymes was determined in 11 cultures with strong results in the growth inhibition assay. The activation status of ERK and Akt both showed large differences between cell cultures (Figure 4A and C). No total PDGF receptor expression (Figure 4B and D, upper right panel) or PDGF receptor phosphorylation (Figure 4B and D, The correlation between the graph below).

Specific phosphorylation changes in ERK and Akt induced by Compound I treatment for 1 hour were analyzed to investigate whether drug-induced changes in these pathways were associated with Compound I responses or receptor expression. Overall, only mild changes in ERK and Akt phosphorylation were observed after drug treatment (Fig. 5A and C). No correlation was observed between Compound I-induced changes in Akt phosphorylation and Compound I responsiveness or PDGF receptor status (Fig. 5D). However, there was a correlation between compound I-induced growth inhibition and decreased ERK phosphorylation (r=-0.47).

Thus, these analyzes revealed large differences in ERK and Akt activation between cell cultures, indicating that the basal level of activation of these pathways is independent of PDGF receptor status or Compound I sensitivity. They also determined that Compound I treatment was not associated with strong changes in the net activation state of these signaling molecules. However, some link does exist between the growth response and compound I-triggered changes in ERK phosphorylation.

II-4 - Gene expression-based clustering of primary cultures from GBM

To describe differences and similarities based on gene expression between primary cultures from 23 GBMs, gene expression profiles were drawn. RNA was isolated from low-throughput cultures grown in 10% FCS. To obtain sufficient RNA for microarray analysis, two rounds of RNA amplification were performed. A fluorescent dye is incorporated into the RNA during the second round of amplification. Each culture was analyzed in quadruplicate using cDNA arrays (http://www.sanger.ac.uk/Projects/Microarrays/) containing approximately 10,000 human cDNAs. Reference RNA consisted of RNA pools from all cultures.

The results of hierarchical clustering are shown in Figure 6. As indicated, different statistical criteria were used to determine which genes were applied to the clusters. Regardless of the standard used, certain fixed patterns were observed involving 17 of the 23 samples. Cultures 18, 21, 35 and 38 were in one cluster (cluster 1) in all analyses. Also cultures 5, 7, 8 and 11 co-occurred in all analyses (cluster 2). Finally, a group comprising cultures 9, 10, 15, 16, 31, 34, 37, 43 and 45 (cluster 3) was seen regardless of the statistical criteria used to select genes.

Figure 7 shows the cluster diagram obtained for the analysis of genes regulated at least 2-fold in the 3 samples, including the cluster-defined genes also listed in Tables 1 and 2.

Differentially expressed genes are grouped in Table 1 according to their molecular function as described by the Gene Ontology program. The 88 hybridization signals for clustered cells represent 75 unique genes. Of these genes, 47 belonged to functions in the Gene Ontology project; while most of the genes belonged to the categories of signaling proteins, transcriptional regulators, and proteins related to adhesion and proliferation.

In Table 2 they are categorized according to their occurrence in the gene clusters defining the 3 culture clusters. Their average expression across the 3 culture clusters is highlighted to illustrate their expression patterns relative to the three culture clusters. In general, gene cluster groups III and VI consisted of genes upregulated in culture clusters 2 and 3, respectively.

With some exceptions, gene cluster group I was almost always highly expressed in culture cluster group 1. In contrast, gene clusters IV and V contained genes that were downregulated in culture cluster 1, while gene cluster II consisted of genes that were underexpressed in culture 3.

II-5 - Comparison of growth properties and PDGF receptor status in GBM culture populations based on gene expression

The results analyzing the growth rate of GBM cultures and their sensitivity to Compound I were combined with the results of hierarchical clustering of cultures based on gene expression (Figure 8). Some meaningful trends can be observed. Of the 7 slowest growing cultures, 6 (in bold) were found in cluster 3. The 6 responders were concentrated in clusters 2 and 3. Those belonging to cluster 2 all appeared in subcluster 2b. Of the 7 non-responders, 4 cultures (18, 21, 35, 38) comprised the repertoire of subcluster 1b.

Likewise, results from PDGF receptor status were also compared to grouping of cultures based on gene expression (Figure 8). Cultures were divided into two categories based on PDGF receptor expression and phosphorylation, with 10 cultures having high expression or phosphorylation and 11 cultures having low expression or phosphorylation. Cluster 1 was clearly enriched for cultures with low receptor expression and phosphorylation, whereas both clusters 2 and 3 consisted of a mixture of the two classes. This pooling of data also highlights that all 6 strong Compound I non-responders showed low receptor expression and phosphorylation, whereas all of the significant responders were characterized by high receptor expression and phosphorylation.

II-6 - Supervised Identification of Gene Expression Patterns Associated with Compound I Responsiveness

Given the indication that there is a correlation between gene expression patterns and Compound I responsiveness, a supervisory analysis was performed to identify the gene expression patterns most correlated with Compound I responsiveness. To this end, the 10 cultures with the most significant results in the Compound I sensitivity assay were divided into responders (cultures 6, 7, 9 and 31) and non-responders (cultures 5, 18, 21, 30, 35 and 38) (Fig. 1B).

Conduct surveillance analysis using weighted voting methods, including leave-one-out confirmation. As shown in Figure 9, all 10 cultures were correctly classified in the leave-one-out validation when classified using 2-40 features. Overall, 8 and 16 genes were used for classification in lists consisting of 4 and 10 features, respectively. The genes used in the leave-one-out assay are listed in Table 3.

Using expression data from 10 cultures, classifiers with 3-5 features were generated (Table 4). Using this classifier, all 10 cultures used to establish the classifier were correctly classified as responders and non-responders. To extend this analysis, the classifier was initially tested on 5 cultures not included in the training set (cultures 8, 11, 27, 34 and 45) (Figure 10). The results of using these classifiers for preliminary testing are shown in Figure 10. Interestingly, consistent with the results of the growth inhibition experiments, cultures 11, 45 were defined as responders in all 3 classifiers. Also consistent with the results of the growth inhibition experiments, culture 34 was consistently classified as a non-responder. Cultures 8 and 27, with moderate responses, were defined as non-responders and responders, respectively, in all 3 classifiers.

As shown above, primary GBM cultures varied widely in compound I sensitivity. By characterizing the status of the PDGF receptor, a significant correlation was shown between Compound I sensitivity and PDGF receptor expression and phosphorylation (Figures 1-3, 8). No significant correlation was seen between Compound I sensitivity or basal phosphorylation of ERK and Akt (Figure 4). There was a certain correlation between Compound I sensitivity and Compound I-induced reduction in ERK phosphorylation (Figure 5). Gene expression profiles indicated the presence of distinct GBM subtypes that differed in Compound I sensitivity, growth rate, and PDGF receptor phosphorylation (Figures 6-8). Finally, by supervised analysis of gene expression data, a short list of genes predictive of Compound I responsiveness could be generated (Figures 9, 10).

While previous studies have reported inhibition in GBM cell lines, here the first systematic analysis of the effect of PDGF receptor inhibition on GBM growth is described.

The correlation between PDGF receptor status and Compound I reactivity (Figure 3) is surprising. Analysis of PDGF receptor expression and phosphorylation indicated strong correlated variation between these parameters, indicating that ligand production was not significantly different in the cultures.

There was no correlation between the basal activation status of the downstream signaling molecules Akt and ERK and the PDGF receptor status (Figure 4), indicating that the activation of Akt and ERK in these GBM cultures is under the control of multiple signaling pathways. It should be noted here that growth inhibition experiments as well as analysis of Akt and ERK activation were performed in cells maintained in 10% FCS. Therefore, the potential effects of PDGF receptor signaling on these pathways may be more readily detectable under other culture conditions.

Analysis of compound I-induced changes in Akt and ERK phosphorylation focused on 10 selected GBM cultures, cultures 6, 7, 9 and 31 with pronounced growth inhibitory responses and 6 non-responsive cultures. Given the importance of Akt signaling in PDGF receptor signaling, it is somewhat surprising that a growth inhibitory effect (probably via PDGF receptor inhibition) could be observed in the absence of reduced persistence of Akt activation (Fig. 5). One possible explanation for these findings is the presence of PDGF receptor-dependent pAkt that is affected by PDGF receptor inhibition, but when serum components can provide high activation of Akt through a PDGF-independent pathway, intracellular The pAkt will not be detected. It should also be noted that cell lysates used to analyze Compound I-induced changes in signaling were from cells exposed to Compound I for 1 hour only. Therefore, this length of time sufficient to elicit detectable changes in PDGF receptor-dependent phosphorylation of ERK and Akt must be confirmed in a well-characterized PDGF-dependent control system.

Combined analysis of gene expression profiles and biochemical characterizations revealed a series of meaningful relationships (Figures 6 and 8). Briefly, cluster 1 was enriched for cultures with low PDGF receptor expression and low compound I sensitivity, cluster 2 was enriched for compound I reactants with high PDGF receptor expression, and cluster 3 was mainly composed of non- Composition of low growth rate cultures with consistent PDGF receptor expression. Preliminary analysis of genes contained in gene clusters III, IV, and V that were overexpressed in GBM culture cluster 2 (enriched for compound I reactants) (Figure 7, Table 2) did not suggest a role for this GBM subpopulation. Specific developmental origin or specific biological properties.

Using supervised analysis based on compound I sensitivity characterization and gene expression analysis of the GBM panel, a classifier describing responders and non-responders was generated (Figure 9, Table 3). In general, the classifier has at least two functions. First, they can be used as a starting point for developing diagnostic or prognostic tools. As long as the classifier performs well, this function of the classifier can be developed without paying attention to the biological significance of the genes that make up the classifier. Second, the classifier is able to specify the biological relationship leading to the two phenotypes identified by the classifier (here compound I sensitive or resistant).

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Table 1

Cluster grouping

Product This Review of Biological Function 1 2 3 Explanation Overall Genes

List of differentially expressed genes from the signature lists used to generate the GBM clusters shown in Figure 6A and Figure 7. Genes are classified according to their function as defined by Gene Ontology.

Table 2

                                            

Product Interpretation 1 2 3 This Review of Bioprocessing The Whole Gene

List of differentially expressed genes from the signature lists used to generate the GBM clusters shown in Figure 6A and Figure 7. Genes were classified according to the cluster analysis results of differentially expressed genes (Fig. 7).

Table 2

                                            

Product Explanation 1 2 3 This Review of Bioprocessing Whole Genes

List of differentially expressed genes from the signature lists used to generate the GBM clusters shown in Figure 6A and Figure 7. Genes were classified according to the cluster analysis results of differentially expressed genes (Fig. 7).

table 3

Genes for 4-character list in leave-one-out test

ordinary time used cell culture 31 9 7 6 5 38 18 35 twenty one 30 describe Classification R R R R NR NR NR NR NR NR CXCL12CXCL12CKTSF1B1COL1A1COL1A1ITGABSLC6ABCOXIBNDNCOL1A1  1010544211111 2.01.81.31.91.51.60.40.51.00.71.8 1.71.71.41.71.33.20.30.40.82.31.8 2.01.91.51.71.42.70.40.61.21.41.8 1.51.50.42.41.81.70.40.51.21.82.3 0.40.40.11.10.70.50.51.10.50.61.1 0.30.60.30.60.60.51.41.30.70.60.6 0.10.20.10.20.20.71.31.40.30.40.2 0.40.50.10.40.30.32.61.30.20.20.4 0.10.10.00.30.10.50.80.90.30.10.4 0.20.10.00.50.40.31.30.50.40.30.6 Stromal cell-derived factor 1 precursor (SDF-1)(CXCL12) Stromal cell-derived factor 1 precursor (SDF-1)(CXCL12) cysteine KNOT superfamily 1, BMP antagonist; GRBMLIN collagen α1(1 ) chain precursor collagen α1(1) chain precursor integrin α-8 sodium and chloride-dependent creatine transporter 1 (CT1) cytochrome C oxidase polypeptide VIIBBNSBSTC00002766964 aprotinin collagen α1(1) chain precursor total 40

Genes for 10-character list in leave-one-out test

ordinary time used cell culture 31 9 7 6 5 38 18 35 twenty one 30 describe Classification R R R R NR NR NR NR NR NR CXCL12COL1A1CXCL12COL1A1COL1A1AEBP1CKTSF1B1AEBP1PTGFRITGABFOXF2COXIBSLC6ABNONFAPVSNL1PHYH  1010101098876652111111111 2.01.91.81.51.81.61.31.61.31.01.61.60.50.41.11.70.71.51.40.50.5 1.71.71.71.31.81.81.41.71.40.83.21.70.40.30.82.32.31.01.70.40.5 2.01.71.91.41.81.71.51.61.31.22.72.60.60.41.31.71.41.41.30.60.7 1.52.31.51.82.31.20.41.20.91.21.70.70.50.41.81.21.81.80.70.40.8 0.41.10.40.71.11.00.10.90.70.50.50.21.10.50.51.70.61.70.40.61.1 0.30.60.60.60.60.60.30.70.80.70.50.71.31.40.70.50.60.60.71.41.1 0.10.20.20.20.20.80.10.80.60.30.70.21.41.30.40.20.40.30.42.21.4 0.40.40.50.30.40.50.10.60.50.20.30.21.32.60.40.10.20.20.62.41.5 0.10.30.10.10.40.40.00.40.50.30.50.40.90.80.30.40.10.40.32.41.4 0.20.50.10.40.60.40.00.50.60.40.30.20.51.30.40.60.30.70.70.30.8 Stromal cell-derived factor 1 precursor (SDF-1) (CXCL12) collagen α1(1) chain precursor stromal cell-derived factor 1 precursor (SDF-1) (CXCL12) collagen α1(1) chain precursor collagen α1 (1) chain precursor Adipocyte enhancer-binding protein 1 precursor: AB-binding protein 1 cysteine KNOT superfamily 1, BMP antagonist; GRBMLIN Adipocyte enhancer-binding protein 1 precursor: AB-binding protein 1 prostaglandin P2α receptor BNSBSTG00002766964 integrin α-8FORKHBAD box protein F2 (FORKHBAD-associated protein FKHL6) cytochrome C oxidase polypeptide VIIB sodium and chloride-dependent creatine transporter 1 (CT1) BNSBSTC00002766964BNSG00000170714 aprotinin SBPRASB (fibroblast activation protein alpha) Viscone-like protein 1 (VILIP-1) (neurocone-like protein 1) phytanyl-CoA dioxygenase, peroxisome precursor Total 100

List of features included in the 4-feature (top) and 10-feature (bottom) classifiers,

The classifier was used for weighted voting classification of 10 GBM cultures.

The relative expression of these features in the 10 GBM cultures included in the analysis is shown.

Table 4

Composition of classifiers with 3, 4 or 5 features at the top of the list of genes ranked by signal-to-noise ratio from 10 glioblastoma cell cultures. The relative expression of these features in the 10 GBM cultures of the training set and of the 5 GBM cultures of the test set are shown. The signal-to-noise ratio is based on the difference in mean expression in the two groups. The decision cutoff was the mean of the mean of expression among responders and non-responders.

Claims (18)

1. the method that is used for in-vitro diagnosis mammalian cell proliferation disease comprises at least:

A) provide described mammiferous biological sample;

B) measure at least 2 to 40 expression and/or phosphorylation spectrums that are selected from the genetic marker of table 3 in the described sample,

C) patient's gene expression profile and the average anergy express spectra in the table 3 are compared;

D) according to the similarity in relatively more definite two gene expression profiles in (b);

E) the similarity degree by determining in (c) is determined the possibility of patient's GBM situation to responding property of medicine.

2. method as claimed in claim 1 is wherein measured at least 3 to 5 expression and/or phosphorylation spectrums that are selected from the genetic marker of table 3 in step b).

3. the prediction Mammals that suffers from cell proliferation disorders comprises at least the method for the reflex action of the pharmacological agent that utilizes at least a pdgf receptor antagonist:

A) provide described mammiferous biological sample;

B) measure at least 2 to 40 expression and/or phosphorylation spectrums that are selected from the genetic marker of table 3 in the described sample;

C), express with reactivity of calculating according to table 3 and anergy and/or the mean+SD of phosphorylation spectrum compares with the expression that obtains in the step b) and/or phosphorylation spectrum; And

D) the described mammiferous behavior of following prediction:

Expression that obtains in-Ruo the step b) and/or phosphorylation spectrum are in the mean+SD scope that reactivity is expressed and/or phosphorylation is composed of calculating, predict that then described Mammals responds to this treatment;

Expression that obtains in-Ruo the step b) and/or phosphorylation spectrum are in the mean+SD scope that anergy is expressed and/or phosphorylation is composed of calculating, predict that then described Mammals is reactionless to this treatment; And

The expression that obtains in-Ruo the step b) and/or phosphorylation spectrum, be in the reactivity of calculating and anergy is expressed and/or the scope of the mean+SD of phosphorylation spectrum outside, then can not determine of the reflex action of described Mammals to this treatment.

4. method as claimed in claim 3 is wherein measured at least 3 to 5 expression and/or phosphorylation spectrums that are selected from the genetic marker of table 3 in the step b).

5. select to suffer from the mammiferous method of cell proliferation disorders, described Mammals responds to the pharmacological agent that utilizes at least a pdgf receptor antagonist through prediction, and described method comprises at least:

A) mammiferous behavior as described in utilization is predicted as the method for claim 3 or 4; And

B) if the described Mammals of prediction responds to treatment, then select this Mammals.

6. as each method in the claim 1 to 5, wherein said Mammals is behaved.

7. be used for the expression of analyzed in vitro Mammals genetic marker and/or the test kit of phosphorylation spectrum, described test kit contains cDNA and/or the antibody that is selected from least 2 to 40 genetic markers in the table 3.

8. test kit as claimed in claim 7 is comprising the cDNA and/or the antibody that are selected from least 3 to 5 genetic markers in the table 3.

9. as the test kit of claim 7 or 8, wherein said Mammals is behaved.

10. be used for the expression of analyzed in vitro Mammals genetic marker and/or the microarray or the biochip of phosphorylation spectrum, wherein contain the cDNA and/or the antibody that are selected from least 2 to 40 genetic markers in the table 3.

11., wherein contain the cDNA and/or the antibody that are selected from least 3 to 5 genetic markers in the table 3 as the microarray or the biochip of claim 10.

12. as the microarray or the biochip of claim 10 or 11, wherein said Mammals is behaved.

13. will be selected from least one gene and/or at least one gene product of table 3 is used for as genetic marker:

The mammiferous cell proliferation disorders of-in-vitro diagnosis; And/or

The Mammals that-prediction suffers from cell proliferation disorders is to the reflex action of the pharmacological agent that utilizes at least a pdgf receptor antagonist; And/or

-select to suffer from the Mammals of cell proliferation disorders, wherein said Mammals responds to the pharmacological agent that utilizes at least a pdgf receptor antagonist through prediction.

14. as the purposes of claim 13, use therein is to have specific antibody corresponding to the cDNA of described gene and/or to described gene product.

15. the purposes as each test kit in the claim 7 to 9 is used for:

The mammiferous cell proliferation disorders of-in-vitro diagnosis; And/or

The Mammals that-prediction suffers from cell proliferation disorders is to the reflex action of the pharmacological agent that utilizes at least a pdgf receptor antagonist; And/or

-select to suffer from the Mammals of cell proliferation disorders, wherein said Mammals responds to the pharmacological agent that utilizes at least a pdgf receptor antagonist through prediction.

16., be used for as each the microarray or the purposes of chip in the claim 10 to 12:

The mammiferous cell proliferation disorders of-in-vitro diagnosis; And/or

The Mammals that-prediction suffers from cell proliferation disorders is to the reflex action of the pharmacological agent that utilizes at least a pdgf receptor antagonist; And/or

-select to suffer from the Mammals of cell proliferation disorders, wherein said Mammals responds to the pharmacological agent that utilizes at least a pdgf receptor antagonist through prediction.

17. the purposes of at least a pdgf receptor antagonist in making medicine, this medicine is used for the treatment of the reactive Mammals that suffers from cell proliferation disorders, and the mammiferous selection of wherein said reactivity method as claimed in claim 5 is carried out.

18. as each purposes in the claim 13 to 17, wherein said Mammals is behaved.

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