AU2014202575B2

AU2014202575B2 - A method for profiling kinase inhibitors

Info

Publication number: AU2014202575B2
Application number: AU2014202575A
Authority: AU
Inventors: Rene Houtman; Timothy Pietro Suren Perera; Robby Ruijtenbeek; Willem Jan-Paul Edmond Talloen; Matthias Luc Aime Versele
Original assignee: Janssen Pharmaceutica NV
Current assignee: Janssen Pharmaceutica NV
Priority date: 2006-10-27
Filing date: 2014-05-13
Publication date: 2016-05-26
Anticipated expiration: 2027-10-29
Also published as: AU2014202575A1; AU2014202643B2; AU2014202642A1; AU2014202643A1; AU2014202642B2

Abstract

5 The present invention is concerned with method for pharmacologically profiling compounds using an array of substrates, in particular kinase substrates, immobilized on a porous matrix. This method was found particular useful in the prediction of drug response, i.e. to enable the distinction between responders and non-responders in the treatment of cells, tissues, organs or warm-blooded animals with the compound to be 10 tested, and in compound differentiation.

Description

1 A METHOD FOR PROFILING KINASE INHIBITORS The present application is a divisional application of Australian Application No. 2007310787, which is incorporated in its entirety herein by reference. 5 FIELD OF THE INVENTION The present invention is concerned with a method for pharmacologically profiling compounds using an array of substrates, in particular kinase substrates, immobilized on a porous matrix. More particularly, a method useful in the prediction of drug response, i.e. to enable the distinction between responders and non-responders in the treatment 10 of cells, tissues, organs or warm-blooded animals with the compound to be tested, and in compound differentiation, is disclosed. BACKGROUND OF THE INVENTION Any discussion of the prior art throughout the specification should in no way be considered as an admission that such prior art is widely known or forms part of common 15 general knowledge in the field. The cost of drug discovery and development is increasing, while the rate of new drug approvals is declining. In contrast to major technological advances with in silico and in vitro primary screening tools, there are only limited advances in the tools available for establishing the actions of agents in the complex biochemical networks characteristic of 20 fully assembled living systems. Recent advances in genomics and proteomic technologies have begun to address this challenge by providing the tools that allow analyzing variations in gene transcription and protein expression at the protein level, in samples of high biological complexity. For instance, genomic and proteomic signatures have provided insights into the molecular mechanisms of a range of physiological and 25 pathological processes, such as for example the pathology of cancer (Vogelstein, B., Kinzler, K.W., Nat. Med. 10(8), 789-99 (2004)), including tumor invasion (Gupta, G.P., et al. Cold Spring Harb Symp Quant Biol. 70:149-58 (2005)). However, the general application of these methods to establish the actions of agents in complex biological systems, is hampered by the given that these methods rely on - 1a changes in protein abundance to deduce their role in cellular processes and, therefore, provide only an indirect estimate of dynamics in protein function. Indeed, several important forms of post-transcriptional regulation, including protein-protein and protein small-molecule interactions, determine protein function and may or may not be directly 5 reflected in gene expression signatures. To address this issue, a chemical proteomic strategy referred to as activity-based protein profiling (ABPP) has emerged that utilizes active site-directed probes to profile the functional state of enzyme families directly in complex proteomes (Jessani, N., Cravatt, B.F., Curr Opin Chem Biol. Feb;8(1):54-9 (2004); Evans, M.J., Cravatt, B.F. Chem. Rev. Aug;106(8):3279-301 (2006)). By 10 development of chemical probes that capture fractions of the proteome based on shared functional properties, rather than mere abundance, ABPP interrogates -2 portions of the biomolecular space that are inaccessible to other large-scale profiling methods. More than a dozen enzyme classes are now addressable by ABPP, including all major classes of proteases, kinases, phosphatases, glycosidases, and oxidoreductases. The application of ABPP to a number of cell and animal models has 5 succeeded in identifying enzyme activities associated with a range of diseases, including cancer, malaria, and metabolic disorders. The ABPP method also facilitates the generation of selective inhibitors for disease-linked enzymes, including enzymes of uncharacterized function. In summary, ABPP constitutes a powerful hypothesis generating technology engine, illuminating which members of enzyme superfamilies 10 are associated with specific physiological or pathological processes and, at the same time, facilitating the creation of selective chemical reagents to test the functions of these proteins. The human genome encompasses some 2,000 proteins that utilize adenosine 5 15 triphosphate (ATP) in one way or another and some 500 of these encode for protein kinases, i.e the protein-tyrosine and protein:-serine/threonine kinases, that share a catalytic domain conserved in sequence and structure but which are notably different in how their catalysis is regulated, Substrate phosphorylation by these enzymes is nature's predominant molecular way of organizing cellular signal transduction and regulating 20 biochemical processes in general. It is not surprising, therefore, that abnormal phosphorylation of cellular proteins is a hallmark of disease and that there is a growing interest in the use of kinase inhibitors as drugs for therapeutic intervention in many disease states such as cancer, diabetes, inflammation and arthritis. It is accordingly understandable that a number of ABPP approaches to interrogate the kinase proteome 25 have been developed, in one method the kinase substrates are fluorescently labeled and a phosphorylation-induced fluorescence change allows real-time visualization of protein kinase activity in both cell lysates and living cells (Chen, CA, et at Biochim. Biophys. Acta. 1697(1-2):39-51 (2004)). In another method the phosphorylation of the peptide substrates is determined using fluorescently labeled anti-phosphotyrosine 30 antibodies (van Beuningen, R,, et at Clinical Chemistry 47:1931-1933 (2001); Schuller A. er al, I Ith Annual World Congres of Drug Discovery Technology (8-10 Aug 2006), Boston, MA, USA). Protein tyrosine kinases (PTKs) are enzymes that catalyze the transfer of phosphate from ATP to tyrosine residues in polypeptides. The human genome contains about 90 35 functional PTKs that regulate cellular proliferation, survival, differentiation and motility. Many members of the PTK family have been identified as oncogenes over the last 25 years. More recently, inhibition of tyrosine kinase activity has become an important new route to treat cancer. Imatinib (Gleevec) is a very effective drug to treat -3 patients with Philadelphia-chromosome (Ph) positive chronic mycloid leukemia (CML); imatinib inhibits the constitutive tyrosine kinase activity of BCR-ABL, the gene product encoded by the ber-abi fusion gene, a result of the Ph translocation. Imatinib is also effective as a treatment for gastro-intestinal tumors (GIST). The 5 underlying mechanism is that GISTs are often the result of overactivation of the receptor tyrosine kinases cKIT or PDGFRalpha, both of which are also inhibited by imatinib. However, a significant problem associated with imatinib treatment is the occurrence of resistance upon prolonged treatment, both in CML and in GIST. Two other approved molecules, erlotinib (Tarceva) and gefitinib (Iressa), are tyrosine kinase 10 inhibitors primarily targeted at the EGFR receptor. The clinical efficacy of erlotinib and gefitinib is by far not as impressive as imatinib: the response rate of edlotinib and gefitinib in an unselected non-small-cell lung cancer (NSCLC) patient population is between 10 and 20%. In addition, acquired resistance occurs frequently and rapidly during treatment with EGFR inhibitors. Hence, the early detection of emerging 15 resistance during treatment, and the stratification of drug-naive patients that are likely to respond to a kinase inhibitor from those that are not, will save patients the trouble and the precious time undergoing useless therapy (and provide the opportunity to timely undergo alternative treatments), will save money for patients and reimbursement agencies, and will increase the chances of approval of a drug in a more limited but 20 well-defined patient population. Additionally, during the clinical development of a drug, these stratification tools can be employed to probe for indications with a particularly high fraction of likely responders. Several examples of such prediction tools have been developed and some are in clinical use. Trastuzumab (Herceptin), a monoclonal antibody directed against the extracellular 25 domain of Her2, is only administered to metastatic breast cancer patients that overexpress Her2. Activating mutations in EGFR have been correlated with exquisite sensitivity to EGFR inhibitors, both in vitro and in the clinic. Conversely, secondary mutations in EGFR have been associated with acquired resistance to erlotinib and/or gefitinib; likewise, mutations in the kinase domains of BCR-ABL, cKlT and 30 PDGRalpha have been associated with resistance to imatinib. Also mutations in key downstream molecules in the receptor tyrosine kinase signaling cascades that allow for RTK-independent signaling, such as constitutive overactive RAS, and inactivated or deleted PTEN (the P13 phosphatase), sometimes inversely correlate with response to RTK inhibitors. With the advent of genome-wide profiling technology, and instigated 35 by the realization that many kinase inhibitors have multiple targets and that the relevant targets critical for effectiveness of a treatment are not always clear, unbiased methods to stratify responders and non-responders have been suggested. The most advertised of these methods is the use of gene expression signatures. In -such cases, a whole-genome -4 expression profile (before treatment) of several responders is compared to that of several non-responders, and genes that are differentially expressed between the two groups can be used to predict the likelihood of unknown cases. A critical disadvantage of this method is that it is not directly related to the mechanism of action of kinase 5 inhibitors and hence relies on indirect parameters to assess responsiveness of a sample. Moreover, this method (and most other response-prediction methods) are based on parameters (in this case gene expression) in the untreated sample only. As a consequence, these methods are very sensitive to tumor heterogeneity and sample quality. 10 It has now been found that the ABPP approach is particularly useful in pharmacologically profiling a compound with the objective to determine patient response to a given drug or regimen. In particular in oncology, the use of ABPP has proven useful to provide "fingerprints" that can predict response to therapeutics in cell lysates prepared from cancer cell lines, xenograft tumors or cancer patient biopsies. 15 AIMS OF THE INVENTION The present invention relates to a method for providing a pharmacological profile of kinase inhibitors. Further the invention relates to use of said method for reliably predicting a patient's response to a specific kinase inhibitor. 20 In other preferred embodiments of the present invention relates to a tool for providing a pharmacological profile of kinase inhibitors. It is an object of the present invention to overcome or ameliorate at least one of the disadvantages of the prior art, or to provide a useful alternative. SUMMARY OF THE INVENTION 25 According to a first aspect of the present invention, there is provided a method for obtaining a pharmacological profile of a kinase inhibitor using a first and a second array of substrates immobilized on a porous matrix, said method comprising the subsequent steps of: - 4a (i) preparing a cell lysate from a cell line, including cancer cell lines; primary and immortalized tissue cell lines; non-human animal model biopsies and patient biopsies; (ii) filtering said cell lysate over a filter in the 10 to 0.1 micrometer range to 5 obtain a filtered cell lysate; (iii) contacting said first array of substrates in the presence of the kinase inhibitor with a first fraction of said filtered cell lysate and determining the response of said first array (iv) contacting said second array of substrates in the absence of the kinase 10 inhibitor with a second fraction of said filtered cell lysate and determining the response of said second array; and obtaining the pharmacological profile as the ratio of the array substrate response in step (iii) over the array substrate response in step (iv), wherein: 15 said substrates are at least two peptide kinase substrates selected from the group consisting of the peptide kinase substrates with sequence numbers 1-28, 30, 32 87, 89-107 and 109-337; said substrates consist of the peptide kinase substrates with sequence numbers 15,16,22,34,62,83,86,87,100,105,108,110,113,125,129 and 133; 20 said substrates consist of the peptide kinase substrates with sequence numbers 15, 16, 21, 23, 38, 42, 53, 62, 69, 77, 83, 86, 91, 94, 103, 112, 114, 129, 133, 136 and 138; said substrates consist of the peptide kinase substrates with sequence numbers 142, 2, 163, 173, 177, 190, 161, 197, 207, 208, 213, 241, 73, 252, 255, 258, 262, 79, 25 87, 266, 86, 269, 95, 296, 303, 305, 308 and 138; or said substrates consist of the peptide kinase substrates with sequence numbers 5, 10, 38, 30, 54, 57, 68, 72, 73, 74, 82, 91, 98, 99, 102, 104, 110, 135, 118, 119, 71 and 138. According to a second aspect of the present invention, there is provided a method for 30 predicting kinase inhibitor response in a cancer patient comprising the step of obtaining a pharmacological profile according to the method of the invention using a biopsy from said cancer patient for the preparation of the cell lysate, wherein said pharmacological profile predict the response of said patient to said kinase inhibitor.

- 4b Unless the context clearly requires otherwise, throughout the description and the claims, the words "comprise", "comprising", and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to say, in the sense of "including, but not limited to". 5 The present invention concerns a method for obtaining a pharmacological profile of a kinase inhibitor using a first and a second array of substrates immobilized on a porous matrix, said method comprising the subsequent steps of; (i) preparing a cell lysate from a cell line, including cancer cell lines; primary and immortalized tissue cell lines; non-human animal model biopsies and 10 patient biopsies; (ii) filtering said cell lysate over a filter in the 10 to 0.1 micrometer range to obtain a filtered cell lysate; (iii) contacting said first array of substrates in the presence of the kinase inhibitor with a first fraction of said filtered cell lysate and determining the 15 response of said first array -5 (v) contacting said second array of substrates in the absence of the kinase inhibitor with a second fraction of said filtered cell lysate and determining the response of said second array; aid obtaining the pharmacological profile as the ratio of the array substrate response in 5 step (iii) aver the array substrate response in step (iv). Preferably, said substrates are selected from the group consisting of hormone receptors, peptides, enzymes, oligonucleotides, monoclonal antibodies, haptens and aptamers., More preferably, said substrates are kinase substrates. Advantageously, said substrates are peptide kinase substrates. 10 In a preferred embodiment, said substrates are at least two peptide kinase substrates selected from the group consisting of the peptide kinase substrates with sequence numbers I to 337. Advantageously, said substrates consist either of the peptide kinase substrates with sequence numbers 15, 16, 22. 34, 62, 83, 86, 87, 100, 105, 108, 110, 15 113, 125, 129, and 133; of the peptide kinase substrates with sequence numbers 15, 16, 21, 23, 38, 42. 53, 62, 69, 77, 83, 86, 91, 94, 103, 112, 114, 129, 133, 136 and 138; of the peptide kinase substrates with sequence numbers 142, 2, 163, 173, 177, 190, 161, 197, 207, 208, 213, 241, 73, 252, 255, 258, 262, 79, 87, 266, 86, 269, 95, 296, 303, 305, 308, and 138; or of the peptide kinase sustrates with sequence numbers 5, 10, 38, 20 30 54, 57, 68,72, 73,74, 82, 91, 98, 99, 102, 104, 110, 135, 118, 119, 71, 138. In the method of the present invention, the cell lysate is preferably prepared from a cancer cell line; xenograft tumor or cancer patient biopsy, including tumor and normal tissue. 25 It is preferred that the response of the array of substrates is determined using a detectable signal, said signal resulting from the interaction of the sample with the array of substrates, advantageously using detectably labeled antibodies, more advantageously using fluorescently labeled anti-phosphotyrosine antibodies. 30 Another aspect of the present invention includes the use of the pharmacological profile determined according to the method of the present invention, to enable the distinction between responders and non-responders in the treatment of cells, tissues, organs or warm-blooded animals for a kinase inhibitor. Preferably, the kinase inhibitor to be tested is selected from the group consisting of 35 MTKI 1, 605 and erlotinib. Use according to any one of claims 14 or 15 wherein pharmacological profile is determined using an array of substrates comprising at least 2 peptides selected from the -6 peptide kinase substrates with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108,110,113,125,129, and 133. Use according to any one of claims 14 or 15 wherein pharmacological profile is 5 determined using an array of substrates comprising at least 2 peptides selected either from the peptide kinase substrates with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133; from the peptide kinase substrates with sequence numbers 15, 16, 21, 23, 38, 42, 53, 62, 69, 77, 83, 86, 91, 94, 103, 112, 114, 129, 133, 136 and 138; from the peptide kinase substrates with sequence numbers 142, 10 2, 163, 173, 177, 190, 161, 197, 207, 208, 213, 241, 73, 252, 255, 258, 262, 79, 87, 266, 86, 269, 95, 296, 303, 305, 308, and 138; or from the peptide kinase substrates with sequence numbers 5, 10, 38, 30, 54, 57, 68, 72, 73, 74, 82, 91, 98, 99, 102, 104, 110, 135, 118, 119, 71, 138. 15 The present invention also concerns a method to enable the distinction of responders from non-responders cell lines and tumors to the treatment with 4,6 ethanediylidenepyrimido[4,5-b][6,1,12] benzoxadiazacvclopetadecine, 17-bromo 8,9,10,11,12,13,14,19-octahydro-20-methoxy-13-methyl- (MTK 1); or the pharmaceutically acceptable acid or base addition salts thereof; or erlotinib, or 20 compound 605, said method comprising; providing a sample from said cell lines and/or tumors; contacting an array of substrates with said sample in the presence of MTKII, erlotinib or 605; contacting an array of substrates with said sample in the absence of MTKII, erlotinib or 25 605; determine the response of said array to the sample in step (ii); determine the response of said array to the sample in step (iii); and obtain the pharmacological profile as the ratio in response of the array in steps (iv) over step (v); characterized in that the array of substrates comprises at least 2 peptides 30 selected from the group consisting of the peptide kinase substrates with sequence numbers 15, 16, 22, 34, 62, 83, 86., 87, 100, 105, 108, 110, 113, 125, 129, and 133; and wherein a responder is identified as an inhibition (ratio < 1.0) in response for at least two of the peptides selected from the peptide kinase substrates with sequence numbers 15, 16, 22, 34, 62,83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133. 35 A responder is preferably identified as an inhibition in response (ratio at least < 080) for at least two of the peptides selected from the group consisting of the peptide kinase substrates with sequence numbers 15, 16, 22, 34., 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133.

-7 Preferably, the array of substrates comprising at least 3 peptides selected from the group consisting of the peptide kinase substrates with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133; in particular the array of substrates comprises the peptide kinase substrates with sequence numbers 15, 16, 22, 5 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133; more in particular the array of substrates consists of the peptide kinase substrates with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133, In the method above, the group consisting of the peptide kinase substrates with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 10 133, can be replaced with the group consisting of the peptide kinase substrates with sequence numbers 15, 16, 21, 23, 38, 42, 53, 62, 69, 77, 83, 86, 91, 94, 103, 112, 114, 129, 133, 136 and 138; the group consisting of the peptide kinase substrates with sequence numbers 142, 2, 163, 173, 177, 190, 161, 197, 207, 208, 213, 241, 73, 252, 255, 258, 262, 79, 87, 266, 86, :269, 95, 296, 303, 305, 308, and 138; or the group 15 consisting of the peptide kinase substrates with sequence numbers 5, 10, 38, 30, 54, 57, 68, 72, 73, 74, 82, 91, 98, 99, 102, 104, 110, 135, 118, 119, 71, 138. In any method according to the present invention, the response of the array of substrates is preferably determined using antibodies in a solution free of antifungals, in 20 particular using an azide free solution. In the methods of the present invention, an overall accuracy of 60%, 70%, preferably 80 % or advantageously 90 % or higher can be obtained, 25 Another embodiment of the present invention concerns an array of substrates comprising peptides selected from the group consisting of the peptide kinase substrates with sequence numbers I to 337, with the proviso that said array does not consist of peptide kinase substrates with sequence numbers 1-140. Said array of substrates can consist of the peptide kinase substrates with sequence 30 numbers I to 337, or the peptide kinase substrates with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133, or the peptide kinase substrates with sequence numbers 15, [6, 21, 23, 38, 42, 53, 62,69, 77, 83, 86, 91, 94, 103, 112, 114, 129, 133, 136 and 138, or the peptide kinase substrates with sequence numbersl42, 2, 163, 173, 177, 190, 161, 197, 207, 208, 213, 241, 73, 252, 255, 258, 35 262, 79, 87, 266, 86, 269, 95, 296, 303, 305, 308, and 138, or the peptide kinase substrates with sequence numbers 5, 10, 38, 30, 54, 57, 68, 72, 73, 74, 82, 91, 98, 99, 102, 104, 110, 135, 118, 119, 71, 138.

-8 Another aspect of the present invention concers a method for predicting possible kinase inhibitor response in a patient in the treatment of cancer, comprising the steps of: (i) Preparing a cell lysate from a cancer patient biopsy, including normal and tumor tissue, 5 (ii) Contacting a first array of substrates according to the present invention with a fraction of the cell lysate of step (i) in the presence of a kinase inhibitor; (iii) Contacting a second array of substrates identical to said first array of substrates with a fraction of the cell lysate of step (i) in the absence of the kinase inhibitor; and 10 Obtaining a pharmacological profile for said patient as the ratio of the first array of substrates response over the second array of substrates response, wherein said pharmacological profile predicts said possible kinase inhibitor response. The invention will be further clarified in the following drawings and examples, which 15 are to be considered non-limiting to the scope of protection conferred by the claims. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1: Ratio of initial velocities of the phosphorylation of detectable peptides in treated over untreated lysates from cell line NCI-H3255. From left to right: DMSO, 20 lapatinib/Tykerb, MTKII/MTIKL geflkinib/ressa, erlotinib/Tarceva, ZD6474/zactima. Scale: white =1 (no inhibition); black=0. (10-fold inhibition). Figure 2: Ratio of initial velocities of the phosphorylation in treated over untreated DU145 samples: left three profiles are derived from cellular treatment with DMSO (outer left lane), MTKI1 (2" lane) or a histone deacetylase inhibitor (3d lane); right 25 most three lanes are derived from lysate treatment of untreated DU145 cells with DMSO (I" lane), MTKII ( 2 " lane), and the histone deacetylase inhibitor ( 3 "' lane), Scale: white =1 (no inhibition); black=0. I (10-fold inhibition). Figure 3: Ratio of initial velocity of peptide phosphorylation in the presence of solvent (DMSO) over the initial velocity of peptide phosphorylation in the presence of MTKI 30 or Tarceva; Scale: white =1 (no inhibition); black=0.25 (4-fold inhibition) DETAILED DESCRIPTION OF THE INVENTION The present invention describes a method to measure the inhibition of tyrosine kinase activity by small molecule compounds in lysates, prepared from cell lines or tumor 35 samples. Importandy, this method directly measures the relevant mechanism of action of a kinase inhibitor and the parameter that correlates with response status is a relative measure (i.e. the ratio of kinase activity in the absence and in the presence of -9 compound). It is demonstrated for a multi-targeted kinase inhibitor, MTKI-1, that responder cell lines can be discriminated from non-responder cell lines based on these phosphopeptide profiles with an overall accuracy of 82 % in 27 cell lines. The kinases that phosphorylate these peptides are closely linked to the mechanism of action of the 5 inhibitor, In addition, it is shown that also in xenograft tumor lysates or for similar kinase inhibitors, many of the same peptides can discriminate responders from non responders, indicating that this technology should be applicable to patient stratification. In one embodiment the present invention provides a method for pharmacologically 10 profiling of compounds using an array of substrates immobilized on a porous matrix, said method comprising; () contacting the array of substrates with either an untreated sample or a sample pretreated with the compound to be tested; (ii) determine the response of said array to the untreated sample; 15 (iii) determine the response of said array to the pretreated sample and (iv) obtain the pharmacological profile as the difference in response of the array in steps (ii) and step (iii). The substrates as used herein, are meant to include hormone receptors, peptides, 20 enzymes, oligonucleotides, monoclonal antibodies, haptens and aptamers. In particular the substrates used or kinase substrates, more in particular peptide kinase substrates, even more particular the peptide kinase substrates in Table 1, most particular using at least 2, 6, 12, 40, 50, 60, 70, 80, 90, 100, 110, 120 or 130 peptides of the peptide kinase substrates of Table 1. In an even further embodiment the array of substrates comprising 25 at least 2 peptides selected from the group consisting of the peptides with sequence numbers 4, 19, 24, 69, 113, 114, 136 and 138; more in particular the array of substrates consist of the peptides with sequence numbers 4, 19, 24, 69, 113, 114, 136 and 138. In an alternative further embodiment, the array of substrates comprising at least 2 peptides selected from the group consisting of the peptides with sequence numbers 15, 30 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129 and 133, more in particular the array of substrates consist of the peptides with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100,105, 108, 110, 113, 125, 129 and 133. In another alternative further embodiment, the array of substrates comprising at least 2 peptides selected from the group consisting of the peptides with sequence numbers 5, 35 10, 38, 30, 54, 57, 68, 72, 73, 74, 82, 91, 98, 99, 102, 104, 110, 135, 118, 119, 71, 138, more in particular the array of substrates consist of the peptides with sequence numbers 5, 10, 38, 30, 54, 57, 68, 72, 73, 74, 82, 91, 98, 99, 102, 104, 110, 135, 118, 119, 71, 138.

-10 Table l. list of 140 peptides used in the PAMCHIP96 profiling analysis, their sequence and SeqdNo. Seq. Name Sequence 1 41f653665_Y627 RLDGENYIRHSN 2 ACHB 383_395_Y390 WGRGTDEYFIRKP 3 ACHD_383_395_Y390 YISKAEEYFLLKS 4 AMPE_5_17_Y12 EREGSKRYCIQTK 5 ANXAI_13_25_Y20/T23 IENEEQEYVQTVK 6 ANXA2_16_28_Y23/S25 HSTPPSAYGSVKA 7 B3AT_39_51_Y46/S50 TEATATDYHTTSH 8 CIR_199_211_5206 TEASGYISSLEYP 9 CALM-93_10-Y99/S101 FDXDGNGYISAAE 10 CALM_95_107 Y99/S101 KDGNGYISAAELR 11 CBL_693_705_Y700 EGEEDTEYMTPSS 12 CD3Z_146_158_Y153 STATKDTYDALHM 13 CD79A_181 193_Y182/Y 88 EYEDENLYEGLNL 14 CDK2 8 20 T14/Y15 EKIGEGTYCVVYK 15 CDK7 157 169$S164 GLAKSFOSPNRAY 16 CREB1_122_134_Y134/8133 QKRRELSRRPSY 17 CRK_214 226_Y221 GPPEPGPYAQPSV 18 CTNB1_79_91_Y86 VADIDGQYAMTRA 19 DCX_109_121_Y112/S116 GIVYAVSSDRFRS 20 DDRI.506_518-Y513 LLLSNPAYRLLLA 21 DDRI_785_797_Y792/Y796Y797 FGMSRINLYAGDYY 22 DDR2_733_745_Y740 RNLYSGDYYRIQG 23 DYRIA_212J224Y219 KIDTEMKYYIVHL 24 DYRIA_312324Y319/Y321 CQLGQRIYQYIQS 25 BFS_246_258_Y253 GGTDEGIYDVPLL 26 EFS_246_258_Y253F GGTDEGIFDVPLL 27 EGFR_1062-1074_Y1069 EDSFLQRYSSDPT 28 EGFR_1103_1115_YI 110 GSVQNPVYHNQPL -11 29 EGFR_ 181130Y 1125 APSRDPHYQDPHS 30 EGFR 1165_1177Y1172 ISLDNPDYQQDFF 31 EGFR_1190_1202_Y41197 STAENAEYLRVAP 32 EGFR_862_874_Y869 LGAEEKEYHAEGG 33 EGFR_908_920_Y915 MTFGSKPYDGIPA 34 ENOG_37_49_Y43 SGASTGIYEALEL 35 EPIIA1_774_786_Y781 LDDFDGTYETQGG 36 EPHA2_581_593_Y588 QLKPLKTYVDPHT 37 EPHA2_765_777_Y772 EDDPEATYTTSGG 38 EPHA4589_601_Y596 LNQGVRTYVDPFT 39 EPHA4_921_933_Y928 QAIKMDRYKDNFT 40 EPHA7_607_619_Y608/Y614 TYIDPETYEDPNR 41 EPHB1_771_783_Y778 DDTSDPTYTSSLG 42 EPUB 19219333Y928 SAIKMVQYRDSFL 43 EPB4_583_595_Y590 IGHGTKVYIDPFT 44 EPOR_361_373_Y368 SEHAQDTYLVLDK 45 EPOR_419_431-Y426 ASAASFEYTILDP 46 ERBB2_1241_1253_Y1248 PTAENPEYLGLDV 47 ERBB2_870_882_Y877 LDIDETEYHADGG 48 ERBB2_945_957_Y952 PISTIDVYMIMVK 49 ERBB4_11811193_Y1188 QALDNPEYHNASN 50 ERBB4_1277_1289_Y1284 IVAENPEYLSEFS 51 P261_26 38 S33 RLQRRRGSSIPQF 52 FABH_13_25 Y19 DSKNFDDYMKSLG 53 FAK1_569_581_Y576/Y577 RYMEDSTYYKASK 54 FAK2_572_584_Y579/Y580 RYIEDEDYYKASV 55 FER_707_719_Y714 RQEDGGVYSSSGL 56 PES_706_718_Y713 RJEEADGVYAASGG 57 FGFR_759771_Y766 ALTSNQEYLDLSM 58 FGP2_762_774_Y769 TLTTNEEYLDLSQ 59 FGFR3_641 653Y648 DVHNLDYYKKTTN 60 FGFR3_753 765_Y760 TVTSTDEYLDLSA -12 6.1 RK.30.392.Y387 KVDNEDIYESRHE 62 GSK3B_209_221 Y216 RGEPNVSYICSRY 63 H2BR 26 38 S321S36 ON KRSRKESY 64 INSR_1348_1360_S1354/Y1355 SLGFKRSYEEHIP 65 INSR_993_1005_Y993/Y999 YASSNPEYLSASD 66 IRS 11222_1234_Y1230 SSEDLSAYASISF 67 IRS2_535_545_Y540 GGGGGEFYGYMTM 68 JAKL_10151027Y022/Y1023 AIETDKEYYTVKD 69 K2C6B_53_65 S59 GAGFGSRSLYGLG 70 K2CS_425_437_S431 SAYGGLTSPGLSY 71 KSYK_518_530_Y525/Y526 ALRADENYYKAQT 72 LAT_194_206_Y200 MESIDDYVNVPES 73 LAT_249_261_Y255 EEGAPDYENLQEL 74 LCK_387_399_Y394 RLIEDNEYTAREG 75 LTh_669_681_Y772/Y776/Y777 RDIYRASYYRRGD 76 MBP198_210_Y203 ARTAHYGSLPQKS 77 MB?_259_271_Y261/Y268/S266 FGYGGRASDYKSA 78 MB?263275Y268/S266/S270 GRASDYKSAHKGF 79 MET_1227 1239_Y1230/Y1234/Y1235 RDMYDKEYYSVHN 80 MK01180_192_Y187 HTGFLTEYVATRW 81 MKOI1J98O210Y205 IMLNSKGYTKSID 82 MK07_211_223_T218/Y220 AEHQYFMTEYVAT 83 MK10 216 228 T221/Y223 TSFMMTPYVVTRY 84 MK12_178_190_T183/Y185 ADSEMTGYVVTRW 85 M1K14_173 185.T.180/Yl82 RHTDDEMTGYVAT 86 NCF1_313_325_S315/S320 QRSRKRLSQDAYR 87 NPT2_501 513_T508 AKALGKRTAKYRW 88 NTRKI-489_501_Y496 HIIENPQYPSDAC 89 NTRK2_509_521_Y516 PVENPQYFGITN 90 NTRK2_695_707_Y702/Y706/Y707 FGMSRDVYSTDYY 91 NTRK2 6997. 7_Y702/Y706/Y707 RDVYSTDYYRVGO 92 ODBA_340_352 S345 DDSSA.YRSVDEVN -13 93 ODPAT299303_829118293 SNSOPOVSYRTRE 94 P2AB_297_309_T304/Y307 EPHVTRRTPDYFL 95 P85A_600_612_Y607/S608 NENTEDQYSLVED 96 PAM) 1)1233J18 VGEEEHVYSFPNK 97 PAXI_24_36_Y31 FLSEETPYSYPTG 98 PDPKl2914fY9 ARTTSQIYTJAVPI 99 PDPKI369_381 Y373Y376 DEDCYONYDNLIS 100 PECAI_706_718_Y713 KKDTETVYSEVRK 101 PERI459471 Y471 QRSELDKSSAHSY 102 PGFRB_1002 1014_Y1009 LDTSSVLYTAVQP 103 POFRE_572-584_Y579/Y581 VSSDGBYIYVWDP 104 PGFRB_709_721_Y716 RPPSAELYSNALP 105 PGFRB_768_780_Y771/Y775/Y778 SSNYMAPYDNYVP 106 PGFRB_771_783_Y771/Y775/Y778 YMAPYDNYVPSAP 07 PLCGI1246_1258_S1248/Y1253 EGSFESRYQQPFE 108 PLCG1_764_776_Y771 IGTAEPDYGALYE 109 PLCG1776-788 Y783 EGRNPGFYVEANP 110 PRRX2_202_214_Y214 WTASSPYSTVPPY 111 PTNI 1535_547_Y542 SKRKGHEYTNIKY 112 RAFM331343_S337/S338/Y339/Y340 RPROQRDSSYWE 113 RASA _453_465_Y460 TVDGKEIYNTIRR 114 RB_804_816_8807/S811 IYISPLKSPYKIS 115 RBL2_99_111 Y111/8103 VPTVSKGTVEGNY 116 RET_1022_1034_Y1029 TPSDSLIYDDGLS 117 RET_680_692_Y687 AQAFPVSYSSSA 118 RON_1346_1358_YI353 SALLGDHYVQLPA 119 RON_1353_1365_Y1356/Yl360 YVQLPAIYMNLGP 120 SRC8_CHICK 470_482 Y477 VSQREAEYEPETV 121 SRC8_CHICK_476_488_Y477/Y483 EYEPETVYEVAGA 122 SRC8_CHICK_492_504_Y499 YQAEENT\DEYEN 123 STASA_687_699_Y694 LAKAVDGYVKPQI 124 1STATI_694_706_Y701 DOPKOTGYIK~lhL- 125 STATE? 683 695 Y690 NLQERRKYLKHRL 126 STAT3 698 710 Y705 DPGSAAPYLKTKF 127 STAT4 686 698_Y693 TRGDKGYVPSVF 128 STAT4_714_726_Y725 PSDLLPMSPSVYA 129 SYNI_2_14_S9 NYLRRRLSDSNFM 130 TAU 512 524_Y514/T522 SGYSSPGSPGTPG 131 TEC_512_524_Y519 RYFLDDQYTSSSG 132 TNNT1_2_14_Y9 SDTEEQEYEEEQP 133 TYRO3_679_691 Y686 KIYSGDYYRQGCA 134 VEGFR_ 1049_1061 _Y1053 KNPDYVRKGDTRL 135 VEGFR2_1052_1064_Y1059 DIYKDPDYVRKGD 136 VEGFR2_944_956_Y951 RFRQGKDYVGAIP 137 VGFR3_1061_1073_Y1063/Y1068/S1073 DIYKDPDYVRKGS 138 VINC_815_827_Y821 KSFLDSGYRILGA 139 ZAP7O485_497_Y492/Y493 ALGADDSYYTARS 140 ZBT16_621_633_8628 LRTHNGASPYQCT in an alternative embodiment, the substrates used are kinase substrates, more in particular peptide kinase substrates, even more particular the peptide kinase substrates in Table 2, most particular using at least 2, 6,12, 16,20, 24, 28, 32, 36, 40, 50, 60, 70, 5 80, 90, 100, 110, 120, 130, 150, 180, 200, 220 or 240 peptides of the peptide kinase substrates of Table 2. In an even further embodiment the array of substrates comprising at least 2 peptides selected from the group consisting of peptides with sequence numbers 142, 2, 163, 173, 177, 190, 161, 197, 207, 208, 213, 241, 73, 252, 255, 258, 262, 79, 87, 266, 86, 269, 95, 296, 303, 305, 308, and 138; more in particular the array 10 of substrates consist of the peptides with sequence numbers 142, 2, 163, 173, 177, 190, 161, 197, 207, 208, 213, 241, 73, 252, 255, 258, 262, 79, 87, 266, 86, 269, 95, 296, 303, 305, 308, and 138.

-15 Table 2: list of 256 peptides used in an alternative profiling analysis, their sequence en Seq.Id.No. Seq. Name Sequence 1 41 653 665 Y627 RLDGENIYTRHSN 141 ABL Y272 HKLOGGQYGEVYTGV 142 ABLIMI_350 364 Y357 RTSSESIYSRPGSSI 143 ABLIMI_454 468 Y461 GSINSPVYSRHSYTP 2 ACB_383_395_Y390 WGRGTDEYFIRKP 3 ACHD_383 395 Y390 YISKAEYFILKS 144 ACLY_675_689 Y682 SRTTDGVYEGVAIGG 145 ACTB 159 173Y166 VTHTVPIYEGYALPH 146 ADAM9_805819_Y15 PARPAPAPPLYSSLT 147 ADD2 482496_Y489 PNQFVPLYTDPQEVL 148 AGBL2 10 24_Y17 KQTIPDPYEDFMYRH 149 ANKRD26_289_303_Y296 RKNLEATYGTVRTGN 150 ANXA2_192_206_Y199 DQDARDLYDAGVKRK 151 ANXA2 231_245_Y238 RYKSYSPYDMLESIR 152 APCDDI_103_117_Y110 FKAYQFYYCSNRCTN 153 APP_750_764_Y757 :SKMQQNGYENTYK 154 ARHGEFIOL124_138_Y13 ALEEDVIYDDVPCES 155 BAG3-240_254_Y247 YQTHQPVYHKIQGDD 156 BCAR1 242 256_Y249 APGPQDIYDVPPVRG 157 BCAR1 320 334Y327 PLLREFTYDVPPAFA 158 BCAR]_355 369 Y362 SPPAEDVYDVPPPAP 159 BCAR!_365_379_Y372 PPPAPDLYDVPPGLR 160 BCARI_657_671_Y664 EGGWMEDYDYVHLQG 361 BCAR1_380_394 Y387 RPGPGTLYDVPRERV 162 BCR_239_253_Y246 SCGVDGDYEDAELNP 163 OlIorf35_217_231_Y224 WNSVARRYPNLFTNM 164 l9orf2l_88_102_Y95 EDEGWQVYRLGARDA 165 Clorf73_928_942 Y935 VKSLEDPYSQQIRLQ 16 166 C20orf 18_281-295_Y288 CPFIDNTYSCSGKLL 167 C2orf4 203 217_Y210 DESQGEIYRSIEHLD 168 C3orf61381523 145 RAYADSYYYEDGGMK 169 C3orf6 272 286 Y279 TDGEDADYTHFTNQQ 170 C9orf86_672_686_Y683 APGGRHPGGGDYEBEL 171 CALR368_82Y75 1TQNGRFYAJSARFK 172 CAVI_7_21_Y14 VDSEGHLYTVPIREQ 173 BL667_681_Y674 SSSANAIYSLAARPL I1 CL693_705_Y700 EGEEDTEYMTPSS 174 CBLB_882_896_Y889 TNRTSQDYDQLPSCS 13 CD79A_181_193_Y182/Y188 EYEDENLYEGLNL 14 CDK2_8_20_T14/YI5 EKIGEGTYGVVYK 175 CDK3_12_26_Y19 EGTYGVVYKAKNRET 15 CDK7_157_169_S164 GLAKSFGSPNRAY 176 CENTB2 735 749_Y742 MRESEGLYGQPGDET 177 CFL1_61_75_Y68 GQTVDDPYATFVKML 178 CLDNI 197i 211Y210 RPYPKPAPSSGKDYV 179 CLDN2_187.201_Y194 SQRNRSNYYDAYQAQ 16 CREB_1122_134YI34/S133 QKRREILSRRPSY 180 TNND1 214_228_Y221 SRHYEDGYPGGSDNY 181 CTTN 414_428Y421 RLPSSPVYEDAASFK 182 CYDC2 12 26 Y19 EGTYGVVYKGRHKTT 183 DCBLD2_558_572_Y565 KKKTEGTYDLPYWDR 184 DCBLD2_743_757_Y750 PAPDELVYQVPQSTQ 19 DCX_109_121_Y1 12/116 GIVYAVSSDRFRS 20 DDR. 506 518_Y513 LLLSNPAYRLLLA 22 DDR2_733_745_Y740 RNLYSGDYYRIQG 185 DDX3X259_273Y266 RYGRRKQYPISLVLA 186 DDX5_195_209_Y202 RLKSTCIYGGAPKGP 187 DKFZp434CO328_451_465_Y458 RVSTDLKYRKQPWGL -17 188 DKFZp761P0423_404_418_Y411 ATQPEPIYAESTKRK 189 lOKI308_3221Y315 CPSQDSLYSDPLDST 190 DOKI402_416_Y409 YNPATDDYAVPPPRS 24 DYRIA_312_324_Y319/Y321 CQLGQRIYQYIQS 191 EFNBI_310_324_Y317 ENNYCPHYEKVSGDY 30 EGFR_1165_1177_YI172 ISLDNPDYQQDFF 192 EW389442_456_Y449 TLDTLSIYETPSMGL 193 EL102_41_55_Y48 WSLPNPEYYTLRYAD 194 ELMO2_706_720_Y717 IPKEPSSYI)FVYHYG 195 35 EPHAI774_786_Y781 LDDFDGTYETQGG 37 EPHA2_765_777_Y772 FDDPEATYTTSGG 38 EPHA4_589_601_Y596 LNQGVRTYVDPFT 42 EPHB1-921-933 Y928 SAIKMVQYRDSFL 196 EPHB2 774 788_Y781 DDTSDPTYTSNLGGK 197 EPHB3_607_621_Y614 'VYIDPFTYEDPNEAV 198 EPHB4 767 781_Y774 ENSSDPTYTSSLGGK 44 EPOR_3619373_Y368 SEHAQDTYLVLDK 199 ERBB2_1241_1255_Y1248 PTAENPEYLGLDVPV 47 ERBB2870_882_Y877 LDIDETEYHADGG 200 ERBB3_1152_1166_Y1159 EEEDVNGYVMPDTHL 201 ERRFI_388_402_Y395 KVSSTHYYLLPERPP 202 F1R_273 287-Y280 TSSKKVIYSQPSARS 203 FAKY407 IDEEDTYTMPSTRD 204 FAKY861 PIONQHIYQPVGKPD 205 FAKY925 DRSNDKVYENVTGLV 53 FAKI-569_581_Y576/Y577 RYMEDSTYYKASK 55 FER_707_719 Y714 RQEDGOVYSSSGL 206 FGD6_747_761_Y754 EYENIRHYEBWEYE 207 FGFRLOP_330_344_Y337 GTGEDDDYVDDFNST 208 FKS EFGTYGTLSK 209 FLJ1273 43 57 Y50 GDVSQFPYVEFTGRD 210 FLJ 12747-469_483_Y476 RHGEQSLYSPQTPAY 211 P1220625_33_47_Y40 LNGAEPNYHSLPSAR 212 FLT1 Y1333 PPDYNSVVLYSTPPI 213 FYN_206_220_Y213 RKLDNGGYYITTRAQ 214 GAB 1_252_266_Y259 ASVDSSLYNLPRSYS 215 GOLGA5_47_61-Y54 QQNTDLIYQTGPKST 216 GPRC5C_392_406_Y399 KVPSEGAYD1LPRA 217 GRLFI1081_1095_Y1088 DGFDPSDYAEPMDAV 62 GSK3B 209_221 Y216 RGEPNVSYICSRY 63 H2BR_26_38_832/S36 DGKKRKRSRKESY 218 H41_183_197_Y190 PQGPPEIYSDT'QFPS 219 HCFC2_553_567_Y560 KSEVDETYALPATKI 220 HCK404.418Y411 RVIEDNEYTAREGAK 221 HKS1 AABEIYAARRG 222 HNRPA2B1_312_326_Y319 SRNMGGPYGGGNYGP 223 HNRPF.2995313_Y306 KATENDIYNFFSPLN 224 HNRPH3_289_303_Y296 GMDNQGGYGSVGRMG 225 HRIHFB2122_166_180_Y173 GQRQALDYVELSPLT 226 HRMTIL2_292_306_Y299 STSPESPYTHWKQTV 227 HSPCB_294_308_Y301 DDITQEEYGEEYKSL 228 HSPCB_477_491_Y484 KETQKSIYYITGESK 229 ILF3_757_771 Y764 QSYNQSPYSNYGPPQ 230 1NSR11831197Y1190 )IYEFDYYRKGGKGL 231 IRS 1_655_669_Y662 QRVDPNGYMMMSPSG 232 IRS2_816_830_Y823 CGGDSDQYVLMSSPV 233 ITGB4_1200 12 47Y1207 GAQGEGPYSSLVSCR 234 ITSN2960_974 Y967 REEPEALYAAVNKKP 235 JAK2_563_577_Y570 VRREVGDYGQLHETE -19 69 K2C6E_53_65 859 AOFGSRSLYGLG 236 KDRY1059 DIYKDPDYVRKGDAR 237 KDR Y996 EEAPEDLYKDFLTLE 238 KIAA2002_1100_1114YI 107 PNPCSATYSNLCQSR 239 KIAA2002_634_648_Y641 AYDNLAIYKSFLGTS 240 KIRREL_401 415_Y408 TRVMKAIYSSFKDDV 241 KIRREL_550_564_Y557 SGLERTPYEAYDPIG 242 KITY703 DHAEAALYKNLLILSK 243 KITY721 CSDSTNEYMDMKPGV 244 KIT_Y936 SESTNHIYSNLANCS 245 KRTJ9_58_72_Y65 SGGYGGQYGGVLTAS 73 LAT_249_261 Y255 MESIDDYVNVPES 246 LAT2_186_200_Y193 EDEESEDYQNSASI 247 LDHB_233_247_Y240 KMVVESAYEVIKLKG 248 LISCH7_302_316_Y309 SIYAPSTYAHLSPAK 249 LLGL1 502 516_Y509 KVGCFDPYSDDPRLG 250 LMO7 341355 Y348 RSWASPVYTBADGTP 251 LMO7801_815Y08 IDATSGIYNSEKSSN 252 LPHN2_1343_1357_Y1350 RSENEDIYYKSMPNL 253 LPP_268_282 Y275 RGGMDYAY1PPPGLQ 254 LPP_294_308_Y301 GRYYEGYYAAGPGYG 255 LYN 186-200 Y193 RSLDNGGYYISPRT 256 LYN_498_512_Y508 DDFYTATEGQYQQQP 257 MAPIB 1882_1896_Y1889 PDEEDYDYESYEKTT 258 MAPK8_178192 Y185 TSFMMTPYVVTRYYR 259 MARCH7_308_322_Y315 SLNSENSYVSPRILT 260 MARVELD2_7_21_Y14 SRNRDRRYDEVPSDL 261 MATR3_212_226_Y219 GYYDRMDYEDDRLRD 76 MBP_198_210_Y203 ARTAHYGSLPQKS 77 MBP 259-27 1Y26/Y268/8266 GYGGRASDYKSA -20 262 MCP_362_376Y369 KADGGAEYATYQTKS 79 MET_1227_1239_YI 230/Y1 234/Y 1235RDMYDKEYYSVH-tN 263 METY1230 FGLARDMYDKEYYSV 87 NPT2 501 513T508 AKALGKRTAKYRW 264 METAPIO03O17YI 1.0 PTRPVPSYIQRPDYA 265 METAPI92_106_Y99 TOKLRPHYPLMPTRP 80 MKOI180_192_Y187 HTGFLTEYVATRW 83 MKI0_216_228_T221/Y223 TSFMMTPYVVTRY 266 APG_298_312_Y307 TAADEEEDEYSGGLC 86 NCF1313_325_S315S320 QRSRKRLSQDAYR 129 SYNI_2_14_S9 NYLRRRLSDSNFM 267 NEK2_12_26_Y 19 YTIGTGSYGRCQKIR 268 NTE_11 88_1202_Y 1195 FGKFDQIYDVGYQYG 91 NTRK2_699_711_Y702/Y706/Y707 RDVYSTDYYRVGG 94 P2AB_297.309 T304/Y307 BPHVTRRTPDYFL 269 P2RY2_223_237_Y230 RRLLKPAYGTSGGLP 95 P85A 600_612_Y607/S608 NENTEDQYSLVED 270 PABPC1_357_371_Y364 ATKPLYVALAQRK 271 PAG1l334_348Y341 LTVPESTYTSIQGDP 272 PAG1l352_366_Y359 PSSCNDLYATVKDFE 273 PAGIl410_424_Y417 LVPKENDYESISDLQ 274 PARD3 482_496-Y489 IGCSAPIYVKNTLPR 96 PAXi_111_123_Yl18 VGEEEHVYSFPNK 97 PAXI_24_36_Y31 -LSEETPYSYPTG 275 PCMI_1169_1183_YI176 NSSGKTEYMAFPKPF 276 PCTK2_196_210_Y203 EKLGEGTYATVYKGR 277 PDFGA_Y574 PDGHEYIYVDPMQLP 278 FDFGAY768 LYDRPASYKKKSMLD 279 PDFGB_Y3021 PNEGDNDYUPLPDP 98 PDPKJ_2_14_Y9 ARTTSQLYDAVPI -21 99 PDPK1_369_381_Y373/Y376 DEDCYGNYDNLLS 123 STA5A 687_699_Y694 LAKAVIDGYVKPQI 280 281 PGMi 346360Y353 SATKIALYETPTGWK 282 PIK3R1 303 317_Y310 LRKTRDQYLMWLTQK 283 PIK3R2_598_612_Y605 KNETEDQYALMXEDED 284 PKP4_471_485_Y478 ALNTATYAEPYRPI 285 PLAGLI 17_31_Y24 EKFTIHNYSHSRERP 108 PLCG 764776Y771 IGTAEPDYGALYE 286 PLECI_3245_3259_Y3252 RARQEELYSELQARE 287 PLEKHA6 485_499_Y492 PPRSEDIYADPAAYV 288 PLEKHA7_463_477_Y470 SLSFPENYQTLPKST 289 PRKCD_306_320_Y313 SSEPVGIYQGFEKKT 290 PRKCD_327 341_Y334 MQDNSGTYGKhVEGS 110 PRRX2.202.214 Y214 WTASSPYSTVPPY 291 PSMA2_69_83_Y76 KHIGLVYSGMGPDY 292 PTK2 585_599_Y592 GDFGLSRYMEDSTYY 293 PTK9_336350-Y343 BLTADFLYEEVHPKQ 111 PTN11_535_547_Y542 SKRKGHEYTNIKY 294 PTPNI 1_573_587_Y580 REDSARVYENVGLMQ 295 PTTGI_104_118_YJI1 VPASDDAYPEIEKFF 112 RAFI 331_343_S337/S338/Y339/Y34 RPRGQRDSSYYWE 113 RASA1_453_465_Y460 TVDGKEIYNTIRR 114 RB_804_816_S807/S811 IYISPLKSPYKIS 296 RBM3_120_134_Y127 SRPGGYGYGYGRSRD 297 RBMX_234_248 Y241 YAPPPRDYTYRDYGH 116 RET_1022_1034_Y1029 TSDSLIYDDGLS 298 ET_Y1096 RYPNDSVYANWMLSP 299 RICS_1673_1687_Y1680 QYDNLEDYHSLPQHQ 300 RIPK2_374_388_Y381 SRKAQDCYFMKLHHC .22 118 RON)1346j1358 Y1353 SALLGDHYVQLPA 126 STAT3698710Y705 DPGSAAPYLKTKF 301 SACS_3345_3359_Y3352 AKLEHLIYLKNRLSS 302 SCAMP3_79 93 Y86 EPKJNYGSYSTQASAA 303 SF3A3_472_486_Y479 QPDThEYEDSSGNV 304 SHANK2 387 401 Y394 GQMPENPYSEVGKIA 305 SEB 3*26 340_Y333 KVTIADDYSDPFDAK 306 SHC1 233.247_Y240 EPPDHQYYNDFPGKE 307 SIPAIL3_1162_1176 Y 1169 STPGS.ATYVRYKPSP 308 SLC20A2_370_384_Y377 KPAQE3SNYR LRRNN 309 SNIP_257_271_Y264 IYRKEPLYAAFPGSH 310 SNRP70-139_153_Y146 RSGKPRGYAFIEYEH 311 SNX3_15_29_Y22 PQNLNDAYGPPSNFL 312 SORBS._319 333 Y326 RAEPKSIYEYQPGKS 313 SPAST_205_219_Y212 SKSQTDVYNDSTNLA 314 SPRED2 261_275_Y268 KHDYNYPYVDSSDFG 315 SPRY4_68_82_Y75 TSHVENDYIDNPSLA 316 SRCY215 KLDSOGFYITSRTQF 121 SRC8_CHICK_476_488_Y477/Y483 EYEPETVYEVAGA 317 STAM_377_391_Y384 EDPMYSMYAKLQNQP 318 STAM2_185_199_Y192 HTETKSLYPSSEIQL 319 STAM2_364-378Y371 LVNEAPVYSVYSKLH 320 STAT3_697_711_Y704 ADPGAAPYLKTKFIC 131 TEC_512_524 Y519 RYFLDDQYTSSSC 321 TENCI_486_500_Y493 GPLDGSPYAQVQRPP 322 TIODI232_246_Y239 KLKPMLIYHSENPRA 323 TJP2_ 1l1125Y1118 AQKHPDIYAVPIKTH 324 TJP2t499513_Y506 SPEDEAIYGPNTKMV 325 TJP3 390_404_Y397 RESSYDIYRVPSSQS 326 TMEPAI 225 239_Y232 MEGPPPTYSEVIGHY -23 327 TNS3_347_361_Y354 GPVDGSLYAKVRKKS 328 TXNRDI124_138_YI131 KVVYENAYGQFGPH 329 TXNRDI_145_159_Y152 NKGKEKIYSAERFLI 133 TYRQ3_679_691_Y686 KIYSGDYYRQGCA 330 UBE2J1 1 15_Y5 METRYNLKSPAVKRL 100 PECAl_706_718_Y713 KKDTETVYSEVRK 331 VASP_32_46_Y39 AFSRVQIYHNPTANS 332 VAV2_135_149_Y142 TENDDDVYRSLEELA 134 VEGFRI_1(9_1061_Y1053 KNPDYVRKGDTRL 136 VEGFR2 944956Y95i RFRQGKDYVGAIP 333 EGFR3_Y1333 ARGGQVFYNSEYGEL 334 VEGFR3 YI1337 QVFYNSEYGELSEPS 138 VINC_815_827_Y821 KSFLDSOYRIHGA 335 139 1 ZAP70 485_497_Y492/Y493 ALGADDSYYTARS 140 ZBT1 6 621_6338628 LRTHNGASPYQCT 336 ZNF326 129) 43Y136 GSSWEAPYSRSKLRP 337 ZNF598_299_313_Y306 GVVGGEDYEEVDRYS As used herein the peptide substrates are named as follows; SwissProt Entry Name for the Human protein _ Start position of the peptide within the full length protein _ Stop position within the full length protein _ Position of the 5 tyrosine or seine that can be phosphorylated. The porous matrix as used herein, could be any material having oriented through-going channels as are generally known in the art;such as for example described in PCT patent publication WO 01/19517 and is typically made from a metal oxide, glass, silicon oxide 10 or cellulose. In a particular embodiment the porous material is made of a metal oxide selected from the group consisting of zine oxide, zirconium oxide, tin oxide, aluminum oxide, titanium oxide and thallium; in a more particular embodiment the metal oxide consists of aluminum oxide, -24 The samples used in the methods of the invention could in principle be any biological sample, such as for example blood, urine, saliva, tissue biopsy or autopsy material and then in particular cell lysates thereof, but would typically consist of cell lysates prepared from cell lines, including cancer cell lines; primary and immortalized tissue 5 cell lines; non-human animal model biopsies and patient biopsies. In one embodiment of the invention, the cell lysates are prepared from cancer cell lines; xenograft tumors or cancer patient biopsies, including tumor and normal tissue. it will be appreciated that the preferred method for the pretreatment of the samples will 10 depend on the particular compound to be tested, and the type of sample used. The optimum method can be readily determined by those skilled in the art using conventional methods and in view of the information set out herein. For example, in the treatment of cell lysates, the compound to be tested may be added to the cell lysate directly; in non-human animal models the compound to be tested will typically be 15 administered at a therapeutically effective amount of the particular compound, optionally in addition salt form, and/or combined in intimate admixture with a pharmaceutically acceptable carrier, which may take a wide variety of forms depending on the form of preparation desired for administration. These pharmaceutical compositions are desirably in unitary dosage form suitable, preferably, for systemic 20 administration such as oral, percutaneous, or parenteral administration; or topical administration such as via inhalation, a nose spray, eye drops or via a cream, gel, shampoo or the like. The optimum method and order of administration and the dosage amounts and regime can be readily determined by those skilled in the art and as provided in more detail in the examples hereinafter. 25 In those embodiments of the present invention where the methods according to the invention are used to pharmacologically profile kinase inhibitors, the array of substrates is contacted with the pretreated sample in the presence of the compound to be tested. It is accordingly an object of the present invention to provide a method for obtaining a pharmacological profile of a kinase inhibitor using an array of substrates immobilized 30 on a porous matrix, said method comprising; (i) contacting the array of substrates with a sample in the presence of the kinase inhibitor; (i) contacting the array of substrates with a sample in the absence of the kinase inhibitor; 35 (iii) determine the response of said array to the sample in step (1); (iv) determine the response of said array to the sample in step (ii); and obtain the pharmacological profile as the difference in response of the array in steps (iii) and step (iv).

-25 The response of the array of substrates is determined using a detectable signal, said signal resulting from the interaction of the sample with the array of substrates, As mentioned hereinbefore, in determining the interaction of the sample with the array of substrates the signal is either the result of a change in a physical or chemical property 5 of the detectably labeled substrates, or indirectly the result of the interaction of the substrates with a detectably labeled molecule capable of binding to the substrates. For the latter, the molecule that specifically binds to the substrates of interest (e.g., antibody or polynucleotide probe) can be detectably labeled by virtue of containing an atom (e.g., radionuclide), molecule (eg., fluorescein), or complex that, due to a physical or 10 chemical property, indicates the presence of the molecule. A molecule may also be detectably labeled when it is covalently bound to or otherwise associated with a "reporter" molecule (e.g. , a biomolecule such as an enzyme) that acts on a substrate to produce a detectable atom, molecule or other complex, 15 Detectable labels suitable for use in the present invention include any composition detectable by spectroscopic, photochemical, biochemical, imrmunochemical, electrical, optical or chemical means. Labels useful in the present invention include biotin for staining with labeled avidin or streptavidin conjugate, magnetic beads (eg., Dynabeads'), fluorescent dyes (e.g., fluorescein, fluorescein-isothiocyanate (FTFC), 20 Texas red, rhodamine, green fluorescent protein, enhanced green fluorescent protein, lissamine, phycoerythrin, Cy2, Cy3, Cy3.5, Cy5, Cy5.5, Cy7, FluorX [AmershamL, SyBR Green I & H [Molecular Probesj, and the like), radiolabels (e.g., 3H125i, 35s, 1c or 3 2 p), enzymes (e.g., hydrolases, particularly phosphatases such as alkaline phosphatase, esterases and glycosidases, or oxidoreductases, particularly peroxidases 25 such as horse radish peroxidase, and the like), substrates, cofactors, inhibitors, chemilluminescent groups, chromogenic agents, andcolorimetric labels such as colloidal gold or colored glass or plastic (e. g., polystyrene, polypropylene, latex, etc.) beads. Patents teaching the use of such labels include U. S, Pat. Nos. 3,817, 837; 3,850, 752; 3,939, 350; 3,996, 345; 4,277, 437; 4,275, 149; and 4,366, 241. 30 Means of detecting such labels are well known to those of skill in the art. Thus, for example, chemiluminescent and radioactive labels may be detected using photographic film or scintillation counters, and fluorescent markers may be detected using a photodetector to detect emitted light (eg., as in fluorescence-activated cell sorting). 35 Enzymatic labels are typically detected by providing the enzyme with a substrate and detecting a colored reaction product produced by the action of the enzyme on the substrate. Colorimetric labels are detected by simply visualizing the colored label. Thus, for example, where the label is a radioactive label, means for detection include a 26 scintillation counter, photographic film as in autoradiography, or storage phosphor imaging. Where the label is a fluorescent label, it may be detected by exciting the fluorochrome with the appropriate wavelength of light and detecting the resulting fluorescence. The fluorescence may be detected visually, by means of photographic 5 film, by the use of electronic detectors such as charge coupled devices (CCDs) or photomultipliers and the like. Similarly, enzymatic labels may be detected by providing the appropriate substrates for the enzyme and detecting the resulting reaction product. Also, simple colorimetric labels may be detected by observing the color associated with the label. Fluorescence resonance energy transfer has been adapted to detect binding of 10 unlabeled ligands, which may be useful on arrays. In a particular embodiment of the present invention the response of the array of substrates to the sample is determined using detectably labeled antibodies; more in particular fluorescently labeled antibodies. In those embodiments of the invention 15 where the substrates consist of kinase substrates, the response of the array of substrates is determined using fluorescently labeled anti-phosphotyrosine antibodies, As outlined in more detail in the examples hereinafter, the use of fluorescently labeled anti phosphotyrosine antibodies allows real-time determination of the substrate activity and accordingly provides the possibility to express the array activity as the initial kinase 20 velocity, In this embodiment the pharmacological profile is determined as the ratio of the array substrate response to the (pre)treated samples over the array substrate response to the untreated samples. Hence, in a particular embodiment the present invention provides a method for 25 obtaining a pharmacological profile of a kinase inhibitor using an array of substrates immobilized on a porous matrix, said method comprising; (i) contacting the array of substrates with a sample in the presence of the kinase inhibitor; (ii) contacting the array of substrates with a sample in the absence of the kinase 30 inhibitor; (iii) determine the response of said array to the sample in step (i); (iv) determine the response of said array to the sample in step (ii); and obtain the pharmacological profile as the ratio of the array substrate response in step (iii) over the array substrate response in step (iv). 35 ~27 In a further aspect of this embodiment, and any of the embodiments of the invention; - the samples consist of cell lysates obtainable from any biological sample (supra), in particular cell lysates prepared from cancer cell lines; xenograft tumors or cancer patient biopsies, including tumor and normal tissue, 5 - the array of substrates consist of kinase substrates, in particular peptide kinase substrates, more in particular comprising at least 2, 6, 12, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130 or 140 peptides of the peptide kinase substrates of Table 1. In an even further embodiment the array of substrates comprising at least 2 peptides selected from the group consisting of peptides 10 with sequence numbers 4, 19, 24, 69, 113, 114, 136 and 138, or from the group consisting of peptides with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133 or from the group consisting of peptides with sequence numbers 15, 16, 21, 23, 38, 42, 53, 62, 69, 77, 83, 86, 91, 94, 103, 112, 114, 129, 133, 136 and 138, or from the 15 group consisting of peptides with sequence numbers 5, 10, 38, 30, 54, 57, 68, 72, 73, 74, 82, 91, 98, 99, 102, 104, 110, 135, 118, 119, 71, 138. Alternatively, the array of substrates consist of kinase substrates, more in particular peptide kinase substrates, even more particular the peptide kinase substrates in Table 2, most particular using at least 2, 6, 12, 16, 20, 24, 28, 20 32, 36, 40, 50, 60, 70, 80, 90, 100, [10, 120, 130, 150, 180, 200, 220 or 240 peptides of the peptide kinase substrates of Table 2. In an even further embodiment the array of substrates the array of substrates consist of the peptides with sequence numbers 142, 2, 163, 173, 177, 190, 161, 197, 207, 208, 213, 241, 73, 252, 255, 258, 262, 79, 87, 266, 86, 269, 95, 296, 303, 25 305, 308, and 138. - the response of the array of substrates is determined using antibodies, in particular fluorescently labeled antibodies, more in particular fluorescently labeled anti-phosphotyrosine antibodies; most particular using the commercially available PY20-FITC antibodies. It has been observed that the 30 presence of antifungal compound, such as azoles or azide, in the sample could influence the array response, thus in a particular embodiment the response of the array of substrates is done using antibodies, in any of the above embodiments, in a solution free of antifungals, in particular using an azide free solution. 35 the samples are filtered prior to the incubation on the porous matrix, i.e. prior to the contacting of the substrate array with the samples in both steps (i) and (ii), Filtering of the samples is done using art known procedures, such as for example but not limited to -filter membranes made from ~28 regenerated cellulose, cellulose esters, nylon, polypropylene, glass, anopore or teflon, typically the filter range should match the oriented through-going channels of the porous matrix, and is for example in the 10 to 01 micrometer range. In particular using an inorganic 0.2 micrometer filter, 5 more in particular using an anopore 0.2 m-icrometer filter, as provided in the examples hereinafter. - the celi lysates used in step (i) are pre-incubated with the kinase inhibitor. It will be appreciated that the preferred method for the pre-incubation of the cell lysates will depend on the particular compound to be tested, and the 10 type of cell lysates used. The optimum method can be readily determined by those skilled in the art using conventional methods, but would typically consist of incubating the cell lysates in the appropriate buffer, for example M-PER buffer (PIERCE) containing phosphatase and protease inhibitors, with the compound to be tested for a period in the range of 30 min - 60 min, 15 Again, the incubation is typically done on ice. Hence, in a further embodiment the present invention provides a method for obtaining a pharmacological profile of a kinase inhibitor using an array of substrates immobilized on a porous matrix, said method comprising; 20 (i) obtain cell lysates prepared from cancer cell lines; xenograft tumors or cancer patient biopsies, including tumor and normal tissue; (ii) filter the cell lysates over a filter in the 10 to 0.1 micrometer range; (iii) incubate a fraction of said cell lysates with the kinase inhibitor to be tested; (iv) contact the array of substrates in the presence of the kinase inhibitor to be 25 tested, with the incubated fraction of step (iii); (v) contact the array of substrates in the absence of the kinase inhibitor to be tested, with the fraction of cell lysates which was not incubated with the kinase inhibitor; (vi) determine the response of said array in step (iv); 30 (vii) determine the response of said array in step (v); and obtain the pharmacological profile as the ratio of the array substrate response in step (iv) over the array substrate response in step (v). In this embodiment, and any of the embodiments of the invention, one or more of the 35 following further restrictions may apply; - the array of substrates consist of kinase substrates, in particular peptide kinase substraes, more in particular comprising at least 2, 6, 12, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130 or 140 peptides of the peptide kinase -29 substrates of Table 1. In an even further embodiment the array of substrates comprising at least 2 peptides selected from the group consisting of peptides with sequence numbers 4, 19, 24, 69, 113, 114, 136 and 138; from the group consisting of 15, 16, 21, 23, 38, 42, 53, 62, 69, 77, 83, 86, 91, 94, 103, 112, 5 114, 129, 133, 136 and 138, from the group consisting of 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133 or from the group consisting of 5, 10, 38, 30, 54, 57, 68, 72, 73, 74, 82, 91, 98, 99, 102, 104, 110, 135, 118, 119, 71, 138. Alternatively, the array of substrates consist of kinase substrates, more in particular peptide kinase substrates, even more 10 particular the peptide kinase substrates in Table 2, most particular using at least 2, 6, 12, 16, :20, 24, 28, 32, 36, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 150, 180, 200, 220 or 240 peptides of the peptide kinase substrates of Table 2. In an even further embodiment the array of substrates consist of the peptides with sequence numbers 142, 2, 163, 173, 177, 190, 161, 197, 207, 15 208, 213, 241, 73, 252, 255, 258, 262, 79, 87, 266, 86, 269, 95, 296, 303, 305, 308, and 138. - the response of the array of substrates is determined using antibodies, in particular fluorescently labeled antibodies, more in particular fluorescently labeled anti-phosphotyrosine antibodies; most particular using the 20 commercially available PY20-FITC antibodies. It has been observed that the presence of antifungal compound, such as azoles or azide, in the sample could influence the array response, thus in a particular embodiment the response of the array of substrates is done using antibodies, in any of the above embodiments, in a solution free of antifungals, in particular using an 25 azide free solution. - Filtering of the satnples is done using art known procedures, such as for example but not limited to filter membranes made from regenerated cellulose, cellulose esters, nylon, polypropylene, glass, anopore or teflon, typically the filter range should match the oriented through-going channels 30 of the porous matrix, and is for example in the 10 to 0,1 micrometer range. In particular using an inorganic 0.2 micrometer filter, more in particular using an anopore 0,2 micrometer filter, as provided in the examples hereinafter. 35 In another embodiment, the present invention provides the use of the pharmacological profile determined using the methods of the invention, to enable the distinction between responders and non-responders in the treatment of cells, tissues, organs or warm blooded animals with the compound to be tested. In particular to enable the distinction -30 of responders from non-responders cell lines and tumors to the treatment with the compound to be tested As outlined in the examples hereinafter, it has also been an object of the present 5 invention to provide the identification of specific sets of substrates, herein also referred .to as "molecular signature" or "fingerprint', on the substrate array of Table 1, that enables the distinction of responders from non-responders cell lines and tumors to the treatment with a class of macrocyclic quinazoline derivatives (1) below, described as multi targeted kinase inhibitors (MTKI) in PCT patent publication WO 2004/10765. 10 X2 T Y (1 Z 6W R? x 6 6> 7 N 8 N 1 In particular to the treatment with a compound of formula (I) wherein; Z represents NH; Y represents -C.alkyl~, -C.

5 alkyl-NRG'-C .salkyl -, -Csalkyt-NR1A-CO-C 1 5 alkyl-, 15 Calkyl-NH-CO-Het 0 -, or -Het 2 t CH-CO-NH-Calky-; X1 represents 0, or -0-C 2 alkyl-; represents a direct bond, -Cb 2 alkyl-, 0, -O-C[ 2 alkyl-, NR or NR t -Qalkyl~; R1 represents hydrogen, cyano, halo or hydroxy, preferably halo; R2 represents hydrogen, cyano, halo, or hydroxy; 20 R 3 represents hydrogen;

R

4 represents C 1 ualkyloxy-; R1 represents hydrogen, or CI-alkyI-; R represents hydrogen or CI 4 alkyl; R1 4 represents hydrogen or C 14 alkyl; 25 Het 0 represents pyrrolidinyl, piperazinyl or piperidinyl; and Het 22 represents pyrrolidinyl, piperazinyl or piperidinyL In particular to enable the distinction of responders from non-responders cell lines and tumors to the treatment with -31 4,6-ethanediylidenepyrimido[4,-b][6,1,1 2benzoxadiazacyclopentadecine, 17 bromo-8,9,10,11,12,13,14,19-octahydro-20-methoxy- 1 3-methyl- (MTKU); or the pharmaceutically acceptable acid or base addition salts thereof. N 5 (II) As used in the foregoing definitions and hereinafter, - halo is generic to fluoro, chloro, bromo and iodo; - C 1 alkyl defines methyl or ethyl; 10 - C 11 alkyl defines straight and branched chain saturated hydrocarbon radicals having from 1. to 3 carbon atoms such as, for example, methyl, ethyl, propyl and the like; - C 1

,

4 alkyl defines straight and branched chain saturated hydrocarbon radicals having from 1 to 4 carbon atoms such as, for example, methyl, ethyl, propyl, butyl, 1-methylethyl, 2-methylpropyl, 2;2-dimethylethyl and the like; 15 - C 1 -alkyl defines straight and branched chain saturated hydrocarbon radicals having from 1 to 5 carbon atoms such as, for example, methyl, ethyl, propyl, butyl, pentyl, imethylbutyl, 2,2-dimethylpropyl, 2,2-dimethylethyl and the like; - C3)alkyl defines straight and branched chain saturated hydrocarbon radicals having from 3 to 9 carbon atoms such as propyl, butyl, pentyl, hexyl, heptyl, octyl, nonyl 20 and the like; - C 4 alkyloxy defines straight or branched saturated hydrocarbon radicals such as methoxy, ethoxy, propyloxy, butyloxy, 1 -methylethyloxy, 2-methylpropyloxy and the like; - the term "CO" refers to a carbonyl group. 25 The pharmaceutically acceptable acid or base addition salts as mentioned hereinabove are meant to comprise the therapeutically active non-toxic acid and non-toxic base addition salt forms which MTKI 1 is able to form. The basic properties can be converted in their pharmaceutically acceptable acid addition salts by treating said base 30 form with an appropriate acid. Appropriate acids comprise, for example, inorganic acids such as hydrohalic acids, etg. hydrochloric or hydrobromic acid; sulfuric; nitric; phosphoric and the like acids; or organic acids such as, for example, acetic, propanoic, hydroxyacetic, lactic, pyruvic, oxalic, malonic, succinic (i.e. butanedioic acid), maleic, -32 fumaric, malic, tartaric, citric, methanesulfonic, ethanesulfonic, benzenesulfonic, p-toluenesulfonic, cyciJamic, salicylic, p-aminosalicylic, pamoic and the like acids. The acidic properties may be converted in their pharmaceutically acceptable base 5 addition salts by treating said acid form with a suitable organic or inorganic base. Appropriate base salt forms comprise, for example, the ammonium salts, the alkali and earth alkaline metal salts, e.g. the lithium, sodium, potassium, magnesium, calcium salts and the like, salts with organic bases, esg. the benzathine, N-methyl-D-glucamine, hydrabamine salts, and salts with amino acids such as, for example, arginine, lysine and 10 the like. The terms acid or base addition salt also comprise the hydrates and the solvent addition forms which MTKI I is able to form. Examples of such forms are e.g. hydrates, alcoholates and the like. 15 Using the pharmacological profiling methods of the present invention (supra) with the substrates of Table 1, the "molecular signature" for MTKIH was found to comprise at least 2 peptides selected from the group consisting of peptides with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129., and 133 20 Using the pharmacological profiling methods of the present invention (supra) with the substrates of Table 2, the "molecular signature" for MTKI1 was found to comprise at least 2 peptides selected from the group consisting of peptides with sequence numbers 142, 2, 163, 173, 177, 190, 161, 197, 207, 208, 213, 241, 73, 252, 255, 258, 262, 79, 25 87, 266, 86, 269, 95, 296, 303, 305, 308, and 138. It is accordingly an object of the present invention to provide a method to enable the distinction of responders from non-responders cell lines and tumors to the treatment with 4,6-ethanediylidenepyrimido[4,5-bj6,1,12] benzoxadiazacyclopentadecine, 30 17-bromo-8,9,10,11,12,13,14,19-octahydro-20-methoxy-13-methyl- (MTKI 1); or the pharmaceutically acceptable acid or base addition salts thereof; said method comprising; (i) obtaining a sample from said cell lines and/or tumors; (ii) contacting an array of substrates with said sample in the presence of 35 VMKII; (iii) contacting an array of substrates with said sample in the absence of MTKI 1; (iv) determine the response of said array to the sample in step (ii); (v) determine the response of said array to the sample in step (iii); and -33 obtain the pharmacological profile as the ratio in response of the array in steps (iv) over step (v); characterized in that the array of substrates comprises at least 2 peptides selected from the group consisting of peptides with sequence numbers 4, 19, 24, 69, 113, 114, 136 and 138; and wherein a responder is identified as an inhibition (ratio < 5 1 f0) in response for at least two of the peptides selected from peptides with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133. in this embodi ment, one or more of the following further restrictions may apply; the array of substrates is immobilized on a matrix, more in particular on a porous matrix, such as for example, but not limited to any material having 10 oriented througb-going channels as are generally known in the art, such as for example described in PCT patent publication WO 01/19517 and is typically made from a metal oxide, glass, silicon oxide or cellulose. In a particular embodiment the porous material is made of a metal oxide selected from the group consisting of zinc oxide, zirconium oxide, tin oxide, 15 aluminum oxide, titanium oxide and thallium; in a more particular embodiment the metal oxide consists of aluminum oxide; - the sample could in principle be any biological sample, such as for example blood, urine, saliva, tissue biopsy or autopsy material and then in particular cell lysates thereof, but would typically consist of cell lysates prepared from 20 cell lines, including cancer cell lines; primary and immortalized tissue cell lines; non-human animal model biopsies and patient biopsies. In one embodiment of the invention, the cell lysates are prepared from cancer cell lines; xenograft tumors or cancer patient biopsies, including tumor and normal tissue; 25 - the array of substrates comprising at least 3, 4, 5, 6 or 7 peptides selected from the group consisting of peptides with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133.; in particular the array of substrates comprises the peptides with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133; more in 30 particular the array of substrates consists of the peptides with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133; - the response of the array of substrates is determined using a detectable signal, said signal resulting from the interaction of the sample with the array 35 of substrates. As mentioned hereinbefore, in determining the interaction of the sample with the array of substrates the signal is either the result of a change in the physical or chemical property of the detectably labeled substrates, or indirectly the result of the interaction of the substrates with a -34 detectably labeled molecule capable of binding to the substrates. In an even farther embodiment, the response of the array of substrates is determined using antibodies, in particular fluorescently labeled antibodies, more in particular fluorescently labeled anti-phosphotyrosine antibodies; most 5 particular using the commercially available PY20-FITC antibodies. It has been observed that the presence of antifungal compound, such as azoles or azide, in the sample could influence the array response, thus in a particular embodiment the response of the array of substrates is determined using antibodies, in any of the above embodiments, in a solution free of 10 antifungals, in particular using an azide free solution. - a responder is identified as an inhibition in response (ratio at least < 0.80) for at least three of the peptides selected from peptides with sequence numbers 15, 16, 22, 34, 62, 83, 86, 87, 100, 105, 108, 110, 113, 125, 129, and 133, 15 The aforementioned method could optionally comprise one or more of the following additional steps; - an additional step in which a fraction of the sample is preincubated with MTKII prior to its application on the array of subtrates. 20 - an additional step in which the samples are filtrated prior to their application on the array of substrates. Filtering of the samples is done using art known procedures, such as for example but not limited to filter membranes made from regenerated cellulose, cellulose esters, nylon, polypropylene, glass, anopore or teflon, typically the filter range should match the oriented through-going 25 channels of the porous matrix, and is for example in the 10 to 0.1 micrometer range. in particular using an inorganic 0.2 micrometer filter, more in particular using an anopore 0.2 micrometer filter, as provided in the examples hereinafter. EXPERIMENTAL DATA AND EXAMPLES 30 Materials and Methods: The use of PAMCHIPs in prediction of drug response and in compound differentiation. PAMGENE technology using the tyrosine peptide PAMCHIP96 allows the kinetic detection of the phosphorylation of 1.44 tyrosine peptides spotted onto a 3-dimensional 35 porous well of a 96-well plate (www.parngene.com). This technology can be used to measure the activity of purified kinases and the effects of -kinase inhibitors thereon. Phosphotyrosine peptides are detected using a mix of fluorescently labeled anti- -35 phosphotyrosine antibodies. Phosphorylation of peptides can be followed in real tine due to the possibility of removing the reaction mix for a few seconds during the assay by a pumping mechanism to allow CCD camera detection of phosphopeptides bound to the fluorescent antibody. These consecutive datapoints (quantified spot images) 5 generate a kinetic curve for each individual peptide, and allow for the calculation of initial velocities and endpoints associated with each individual peptide. This technology has been modified to enable profiling of tyrosine kinase activities in untreated and compound-treated lysates (lysates prepared from cancer cell lines, xenograft tumors and patient biopsies, tumor and normal tissue, can all be used), as 10 well as treated and untreated cell lines. The use of these profiles was demonstrated in stratifying compound responder from non responders cell lines and tumors, as well as in the differentiation of tyrosine kinase inhibitors based on their target selectivity and ATP competitiveness, as well as in characterizing the indirect effect of non-kinase inhibitors (such as histone deacetylase inhibitors) on kinase activity. 15 Cultured cell lysates Cells cultured in appropriate medium in T175 flasks, treated with compound if necessary, are harvested at 70-90% confluency. Media is removed, cells are washed withlOml ice cold PBS containing 0.1mM NaVO4 20 and lysed in Iml of NI-PER buffer (PIERCE) containing phosphatase and protease inhibitors (HALT, PIERCE). Cells are collected by scraping, and centrifuged for 10 minutes at 12 000xg. Supernatant lysates are filtered through a 0.2 micrometer filter (Anotop 0.2 gim anopore filter; Whatmann). Lysates are flash frozen in liquid nitrogen and stored at-80C. 25 Tumor and tissue lysates 100 mg of frozen tumor or tissue blocks, or sections, are lysed in iml of M-PER buffer (PIERCE) containing phosphatase and protease inhibitors (HALT, PIERCE). The suspension is mixed using a ULTRA-TURRAX blender (IKA werke), and centrifuged 30 twice for 10 minutes at 12 000xg. Supernatant lysates are filtered through a 0.2 Micrometer filter (Anotop 0.2 gm anopore filter; Whatmann). Lysates are flash frozen in liquid nitrogen and stored at-80C. PAMCRIP procedure 35 Just prior to the PAMCHIP experiment, total protein content is quantitated in the lysates and lysates are diluted to 1 mg/mi in a total volume of 200 gi, with M-PER phosphatase and protease inhibitors (HALT, PIERCE). 10 gg of total lysate (corresponding to 10 g) will be used per well on the PAMCHIP96.

-36 To all 200 pl lysates 10 units of benzonase (Novagen) is added and lysates are further incubated for 30 min on ice and next centrifuged for. 10 minutes at 12 000xg. The supernatant is then 1:1 diluted with compound or DMS0 diluted to the appropriate concentration in water, and lysates are further incubated exactly 60 nn on ice. 5 Meanwhile, a PAMCHIP96 tyrosine peptide chip (PAMOENE) is blocked with 2% BSA (filtered through a 0.2 pm anopore filter; Whatmann) using the standard setting of a PAMSTATION96 (PAMOENE). The composition of the kinase buffer is as follows: 1x ABL buffer (NEB), 0,5mg/mil BSA (from 10 mg/ml NEB stock), 100 pM ATP (dissolved and diluted in Ix ABL 10 buffer), 5 gg/ml PY20-FITC (ExAlpha Biologicals, azide-free preparation). A twofold concentrated kinase buffer is prepared chilled on ice, DMSO or compound is added as appropriate, and the solution is added 1:1 to the (compound treated) ice cold lysates, and immediately applied to a tyrosine peptide PAMCHIP96. The assay is run on a PAMSTATION96 according to standard procedures: after loading of the plate, solution 15 is pumped once onto the wells, a first exposure is read (150 mSec) and then a kinetic reading program (reading every 5 min for 150 nSec) is run for 60 min. Lysates are run in 6 technical replicates for each condition; replicates are always applied horizontally next to each other to avoid vertical strip effects of the chip. 20 Data analysis Preprocessing, The data (spot images) are further quantified and linked to the peptide identities using EVOLVE PAMGRID software (PAMGENE). The quantified data are then fit to a curve using CurveFitHT software (PAMGENE) using the Vinip2 curve fitting 25 algorithm, applied on the first 30 min of the assay; the initial velocity is derived at the first kinetic time point read. All subsequent data analyses were done on initial velocities (Vini) using the software packages Onniviz and R (Thaka, R. and Gentlemen, R, (1996) R: a language for data analysis and graphics. J, Comput, Graph, Stat, 5, 299-314). 30 Testingfbr diferen tially inhibited peptides. After replacing the Vini's lower than 0.1 by 0.1, all Vini's were log2-transformed to approach normality, Subsequently, it was tested whether the compound-induced reduction in Vini's differed significantly between responding and non-responding 35 tumors. This test was done for each peptide separately using a mixed model (Littell, R,C., Milliken, G.A., Stroup, W;W., Wolfinger, R.D 1996. SAS system for mixed models. Cary, North Carolina: SAS Institute Inc.) allowing the incorporation of both technical variation (i.e., the variation across replicates) and biological variation (i.e., the -37 variation among the various responding and non-responding cell lines or tumors). Variation between cell lines or tumors in Vini and in treatment effect on Vini was modeled respectively by random intercepts and random compound effects per cell line or tumor, nested in response status. The difference in compound-induced reduction in 5 Vini between responding and non-responding cell lines or tumors was tested through the interaction between compound treatment and response status, both modeled as fixed effects. The p-values for the test for this interaction were corrected for multiple testing using False Discovery Rate procedure (Benjamini,Y. and IHochberg,Y. 1995. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple 10 Testing. I Roy, Stat. Soc. R, 57(1): 289-300), resulting in so-called q-values. Example 1: Generation of signature peptides in a 27-cell lines panel for MTKL. It was tested whether the Pamichip peptide arrays are a useful tool to predict the response of a cell line to the multi-targeted kinase inhibitor, MTKL MTKJ inhibits the 15 proliferation of a range of cell lines in vitro with widely varying ICso's. The lysates prepared from these 27 cell lines, representing diverse cancer cell types, were profiled on the peptide arrays in the absence or presence of 5pM MTKI, in 6 replicates for each condition. In this panel, 13 cell Lines were defined as responder cell lines (IC 0 < 3pM; cell lines are ordered according to increasing IC50 in Example 1, whereas 14 cell lines 20 are classified as 'non-responder' cell lines (ICo > 10 pM). Intermediary cell lines and cell lines with highly variable IC 50 measurements were omitted from the analysis. The experiment included the highly responsive H3255 lung cancer cell line, which overexpresses mutant EGFR L858R. This mutant variant is highly responsive to MTI, which is an ATP-competitive compound that binds to the active conformation of EGFR 25 (similar to erlotinib and gefitinib). Accordingly, the most profound changes induced by MTKI in lysate kinase activity can be observed for this highly responsive cell line. To identify those peptides for which the inhibition of phosphorylation by MTK correlates well with the response status of the cell line from which the lysate was prepared, a statistical mixed-model was set up to identify those peptides that are most 30 likely to change after MTKI treatment in responder cell lysates compared to non responder lysates, taken into account the inter-replicate variability (see the material and methods section for a more detailed description of the statistical test). The 16 peptides that are most likely to change by MTKI treatment in responders versus non-responders are listed in Example 1, using a cut-off p-value of 0.01 (correction for the large number 35 of repeated measurements in this statistical analysis indicates that this p-value translates to a q value of 0.1). To illustrate that the inhibition of the phosphorylation of these peptides in a given lysate does indeed correlate with the response of the corresponding cell line to MTKI, the following cut-off was chosen to classify responders and non- -38 responders: minimally 4 peptides out of the 16 peptide list should be inhibited with a ratio of less than 048 (more than 20% inhibition) to classify as a responder. Applying this rule to all 27 cell lines indicates an overall classification accuracy of 82% (with 78% sensitivity, and 86% specificity). Interestingly, two out of three responders that are 5 falsely predicted as non-responders (Colo699 and H2009) have the highest IC50 of all 13 responders (ic these are 'borderline' responders). Note that the use of these 20 peptides as a classification tool can be optimized according to the required sensitivity and specificity, 10 Results represented by the ratio of initial velocity of peptide phosphorylation in the presence of solvent (DMSO) over the initial velocity of peptide phosphorylation in the presence of MTKI are shown in Tables 3 A to D .; 'NaN indicates that there is no detectable phosphorylation in the presence of DMSO 15 In order to adapt the sensitivity or specificity to specific needs (e.g. to eliminate false positives or alternatively false negatives as much as possible), the skilled person can adapt the prediction statistics easily, e.g. by changing the Responder prediction ratio. Table 3A H3255 NCI-N87 H1322 SNL1484 H2122 SKBR3 A431 peptides MTKI MTKI MTLKI MTKI MTKI MTKI MTKI CDK7_157_1693164 0.55 0.82 0.88 0.67 0.90 0,97 0.53 CREB1_122 134_Y134/3133 0.73 0.82 0.94 0.70 0.85 0.99 0.63 DDR2_733_745_Y740 0.44 0.95 0.85 0.75 0.81 0.93 0,56 ENOG_37_49_Y43 0.76 0.91 0.76 0.68 0.71 0.77 0.83 GSK3B_209_221_Y216 0.60 0.83 0.94 0.78 0.84 089 0.56 K110216_228_T221/Y223 0.47 0,73 0.76 0.72 0.79 0.68 0.46 NCFI_313_325_S315/S320 0.59 0.89 0.88 0.80 0.94 0.94 0.57 NPT2_501_513-T508 0.68 0.88 08 05 0,90 0.77 0.53 PECA l_706_718 13 0.68 0.82 0.73 0.64 0.67 0.68 0.72 PGFRB_768_780 Y771/Y77 5/Y778 012 0.32 0,92 NaN NaN NaN 0,97 PLCG 1_764_776_Y771 0.97 0.78 0.79 0.70 0.76 0.75 0.82 PRRX2_202_214_Y214 0.67 0 82 0,85 0.67 0.84 0.75 0.75 -39 RASAI_453_465_Y460 0.65 0.59 0,83 0.58 0.78 0.88 0.62 STAT2_683 695_Y690 02 0.83 0.89 0.73 0.90 0,81 0.57 SYNl_2_14_89 0.70 0.75 0.91 0.67 0.91 1.03 0.58 TYRO3_679_691_Y686 0.47 0.85 0.96 0.85 0.95 0,90 0.52 status R R R R R R R prediction R R R R R R R Table 3B BT4740 DUI4 SUM] SUM159 D 5 49 H2009 Colo699 HT1373 peptides MTKI MTKI. MTKI MTKI MTKI MTKI MTKI CDK7_157_169"S164 0.83 074 0.63 0.72 0.89 093 1.10 CREBI_122_134_Y134/S1 33 1.03 90 0.93 0.88 0.97 0.86 0.95 DDR2733745Y740 0.83 0.83 0.71 0.83 0.95 1.20 0.92 ENOG_37_49_Y43 0.82 0.55 0.65 0.91 0.81 0.86 0.87 0SK3B-209221_Y216 1.13 0.87 0.94 0.41 LOO 1.03 0,97 MKI0_216_228T221/Y22 3 0.89 0.76 0.66 0.79 0.89 0.86 0.87 NCF 31,3325_S315/S320 0.99 .88 0.87 1.06 0.89 0.93 1 02 NPT2_501_513_T508 0.98 0.77 0.90 0.78 0.76 0.95 1.00 PECAI_706_718_Y713 .87 0.51 0.73 0.87 0.79 0.83 0.86 PGFRB_768_780_Y771/Y7 75/Y778 NaN NaN 0.39 0.58 0.43 0.23 NaN PLCGI_764_776.Y771 0.79 0.68 0.76 0.95 0.81 0.78 0.76 PRRX2 202 214 Y214 0.84 0.56 0.68 0.71 0.90 0.76 0.91 RASAI 453_465 Y460 .82 0.61 0.69 0.93 83 0.81 0.78 STAT2 683 695 Y690 1.09 0.91 0,93 0.89 0.84 0.93 0.97 SYNI_2 14 S9 1.03 0.94 0.92 1.02 0.93 0.95 .92 TYRO36'79_691_Y686 0.87 0.88 9.68 076 0.89 1.18 0.87 status R R R R R R NR -40 prediction NR R R R NR NR NR Table 3C MDA MB43 HEK23 SHSYS MDA23 5s RSJSAI 9 H23 Y H1650 IPAR peptides MTKI MTKI MTKI MTKI MTKI MTKI MTKI CDK7_157_169_S164 [08 0.81 1.20 0.92 0.97 0.82 1.13 CREB1_122_134_Y1341S133 [09 0.99 [08 L02 1.17 0.88 1.04 DDR2 733_745_Y740 1.07 [02 100 0.81 1.01 085 1.11 ENOG_37_49_Y43 0,84 0.95 0.96 0.80 0.99 0.73 0.93 GSK3B_209_221 Y216 1.14 111 1.18 109 0.87 0.79 0-98 MKIO_216_228_T221/Y223 1.29 0.96 0.75 0.98 1.10 0.69 0.83 NCFI313_325_S315/S320 1.09 1.00 0.96 0.86 1.26 0.92 1 03 NPT2_501_513_T508 1.05 0.96 0.89 0.91 L17 0.91 1.09 PECAI_706_718_Y713 0.76 0.85 1.00 0.62 0,96 0.70 0,86 PGFRB_768_780_Y771/Y775 /Y778 NaN NaN NaN NaN NaN 0.32 NaN PLCGI_764_776_Y771 0.98 0.90 1.02 0.84 0.96 0.84 0.93 PRRX2 202_214_Y214 1.03 [03 1.30 0.67 0.92 0.91 0.97 RASA1_453_465Y460 0.88 1.17 0.89 0.71 0.87 0.98 0.80 ST2683_695_Y690 1.09 1.03 1.03 0.93 [17 0.85 1.00 SYNI 2 14 89 1.12 1.05 0.92 1,01 111 0.83 0.92 TYRO3_679 691 Y686 0.93 1,22 0.93 1.10 0.95 0.90 0.99 stats NR NR NR NR NR NR NR prediction NR NI NR NR NR R NR Table 3D MOLT4 r MCF7 MKN45 SNUS GTL16 Ul 18MG peptides MTKI MTKI MTKI MTKI MTKI MTKI CDK7_157169_S164 0.91 0.89 0.90 0.98 0.98 0.85 -41 CREBI 122_134_Y134/S133 1.02 085 094 11 0.91 0,99 DDR2_733_745_Y740 0.78 ,15 0.94 0.95 1.00 1.00 ENOG_37_49_Y43 0.77 0.83 0.91 0.81 0.80 0.85 GSK3B 209 221_Y216 L19 0.89 099 0,98 111 1.06 MKIO 216 228 T221/Y223 085 1.03 0.95 0.99 0.96 0.97 NCF1 313_325_S315/S320 118 0.90 0.95 0.99 0.96 105 NPT2_501_513T508 0.96 0.90 0.97 0.98 0.89 0.94 PECA1 706718.Y713 0.77 0.74 0.83 0.81 0,95 0.92 PGFRB768_780_Y771/Y775 /Y778 0.17 NaN 1.04 0.89 0.75 NaN PLCGI764_776_Y771 0.80 0.78 0.92 0.84 0.90 0.91 PRRX2_202_214_Y214 0.72 0.90 1.04 089 0,97 103 RASAl_453_465-Y460 0.79 0.81 0.92 0,92 0.81 0.94 STAT2_683_695_Y690 0.95 09 0.97 0.91 1 06 0.97 SYN_2 14 89 122 0.92 0.94 1.01 0.91 1.02 TYRO3_679691_Y686 0,97 0.98 1.00 0.89 0.92 0.91 status NR NR NR NR NR NR prediction R NR NR NR NR NR R=Rsponder to MTKI NR=Non-Responder to MTKI A responder is predicted when minimally 4 peptides have a ratio <0.8 (indicated in 5 hold) Overall prediction accuracy: : 82% (22/27) Sensitivity (number of predicted Responders over number of actual Responders): 78% (10/13) Specificity (number of predicted Non-Responders over number of actual Non 10 Responders); 86% (12/14) Example 2: Generation of signature peptides in xenograft tumors for MTKI. To explore whether a similar approach allows for the classification of responder and non-responder tumors, the same strategy as above was applied to 12 different xenognft 15 tumors, which were subcutaneously grown in nude immuno-compromised mice from -42 human cancer cell lines. These tumors can be divided in 6 responsive tumors and 6 non-responsive tumors. The responsive tumors are arranged according to their responsiveness to MTKI in vivo, ranging from abrupt tumor regression of H3255, A431 and H322 tumors, to potent inhibition of tumor growth for DU145, SUM149 and 5 BT474. The non-responsive, tumors (H460 and H441, HT29, PC3, SKOV3, H1 703) are all non-responsive to MTKI in vivo. Lysates were made from homogenized frozen tumor blocks and analyzed in the absence or presence of 5 pM MTK, as before, Overall, the phosphorylation rate of most peptides was significantly faster in tumor lysates compared to the corresponding cell lines. Nevertheless, inhibition of peptide 10 phosphorylation profiles indicated that there is a subset of peptides for which the inhibition of phosphorylation correlated with responsiveness of the tumors to MTKL A statistical test was applied to this data set -similar as before for the 27 cell lines- and the 21 peptides that best discriminate between responders and non-responders is shown in Tables 4A and B. The cut-off p-value used for this set is 0.1. Note that the p-values 15 for these peptides to discriminate between responders and non-responder tumors are significantly lower than those derived for the cell lines because the number of tumors (12) is far lower then the number of cell lines in Example 1 (27). Note that 7 of the peptides in this tumor signature set were also found in the 16-peptide cell line signature set (Example 1) indicating that inhibition of some of the same activities are critical to 20 reduce tumor growth in vivo as compared to inhibition of growth in vitro, but also pointing to the importance of other kinases in the in vivo setting. Importantly, for many signature peptides the extent of inhibition correlated with the responsiveness of the tumor to MTKI. Results represented by the ratio of initial velocity of peptide phosphorylation in the 25 presence of solvent (DMSO) over the initial velocity of peptide phosphorylation in the presence of MTKI are shown in Tables 4A-B.; 'NaN indicates that there is no detectable phosphorylation in the presence of DMSO In order to adapt the sensitivity or specificity to specific needs (e.g. to eliminate false 30 positives or alternatively false negatives as much as possible), the skilled person can adapt the prediction statistics easily, e.g. by changing the Responder prediction ratio. Table 4A SUM14 H3255 A431 H-322 DU145 9 BT474 Peptide MTKI MTKI MTKI MITKI MTKI MTKI CDK7_157_169_S164 0.45 0.60 0.77 0.96 0.93 0.88 43 .REBI 122 134_Y134/8133 0.61 0.67 00 0.93 1 02 1,02 DDR1_785797Y792/Y796/Y797 0.48 038 0.71 0.64 0.88 0,94 DYRIA_212_224_Y219 0.62 0.03 0.59 0.90 0.10 0.07 EPHA4589 601_Y596 0.44 0.51 0.63 0.77 103 079 EPHBI921-933Y928 0.44 0.39 0.75 0.81 0.85 0.70 FAK1_569_581 Y576/Y577 0.48 0.58 0.82 0272 094 0.89 GSK3B_209_221_Y216 0.57 0.67 0.77 1.7 0.91 0.89 K2C6B_53_65_$59 0.56 0.54 0.80 0.77 0.86 0.80 MBP_259_271 Y261/Y268/S266 0.47 0.60 0.65 0.81 1.04 0.85 MKI 0216228T22 1/Y223 0.31 0.60 0.68 0.77 0.75 0.83 NCF I313325S315/S320 073 0.66 0.78 0,97 0,94 102 NTRK2_699 711 Y702/Y706/Y707 0.48 046 0.76 0.77 0.85 0.77 P2AB 297309T304/Y307 0.66 0.65 0.77 0,81 0.87 0.62 PGFRB_572 584_Y579/Y581 0.66 0.64 0.67 0.72 0.69 0.75 RAFI_331_343_S337/S338/Y339/Y3 40 0.53 0.58 0.79 0.83 0.99 0.94 RB_804_816_8807/8811 0.52 0.53 0.75 0.76 0.83 0.80 SYNI_2_14_$9 0.50 0.76 0.78 0.88 1.01 0.96 TYRO3_679_691_Y686 0.51 0.55 0.80 0.83 1.03 0.84 VEGFR2944956Y951 0.52 0.58 0.75 0.95 0.86 0.84 VINC_815_827_Y821 0.40 0.52 0.76 0.84 0.75 085 response status R R R R R R response prediction R R R R NR NR Table 4B SKOV PC3 H460 H441 HT29 H17003 Peptide 3MTKI MTKI MTKI MTKI MTKI MTKI CDK7_157_169 8164 0.89 0.82 0.98 0.93 0.96 0.77 CREB1_122_134Y134/S133 1.03 0.86 1.02 0,95 1.00 0.93 DDRI_785_797_Y792/Y796/Y797 0.87 0,83 LO1 0.77 0.85 0.96 DYRIA 212 224_Y219 0.67 0.44 NaN 0.83 0.50 NaN -44 EPHA4_589_601_Y596 1.20 0.83 2.10 0.86 1.08 087 EPHB1_921_933-Y928 0.77 0,81 1.01 0.85 1.03 0.64 FAK1_569 581 Y5761Y577 0.88 0.83 1.12 082 0.77 0.73 GSK3B 209 221 Y216 1.06 0.77 0.95 0.97 0.98 0.98 K2C6E 53_65_S59 0.85 0.71 0.97 0.79 0.82 0.94 MBP_25927i1Y2611Y268/S266 1.16 0.84 1.02 0.79 0.89 0.89 MK1O_216_228_T221/Y223 0.4 0.67 0.96 0.85 0.3 0.84 NCF12133325 S315/S320 0.91 0.83 1.01 0,93 0.92 0,95 NTRK2_699_711_Y702/Y706/Y707 0.7 0.73 0.99 0.80 0.87 0.88 R2AB_297_309_T304/Y307 1.37 0.84 1.06 0.92 1.00 0.88 PGFRB_572_584_Y579/Y581 0.61 0.62 1.12 0.74 0.68 077 RAFI_331_343_S337/S338/Y339/Y3 40 1.01 085 L03 0.88 0.97 0,94 RB_804_816_S807/S811 094 0.61 0.96 0.82 0.75 0,86 SYNI 2_14_S9 LO0 0.75 L07 0.98 1.01 0.91 TYRO3_679_691_Y686 0.98 0.81 103 0.83 0.92 0.95 VEGFR2 944 56 Y951 0.90 0.77 0.91 0.91 1.01 0.82 VINC_815_827_Y821 0,79 0.66 0.85 0.88 0.89 0.80 response status NR NR NR NR NR NR response prediction NR R NR R=Responder to MTKI NR=Non-Responder to MTKI A Responder is predicted when minimally 7 peptides have a ratio < 0.8 (indicated in 5 bold font). Overall prediction accuracy: 9/12 (75%) Sensitivity (number of predicted Responders over number of actual Responders): 4/6 (67%). Specificity (number of predicted Non-Responders over number of actual Non 10 Responders): 5/6 (83%).

-45 Examnple 3: Human frozen tissue and tumor samples. The same approach as for the xenograft tumor lysates was applied to human tissue (frozen tissue purchased from Proteogenex), Snap-frozen lung tumors and normal -matched tissue were tested. It was found that all samples gave robust signals, and that 5 different tumors resulted in different responses to MTKII treatment, suggesting that this technology is applicable to frozen human tissue in general and may predict response of tumors (and other tissue) to MTKIl or other tyrosine kinase inhibitors. Example 4: Compound differentiation 10 PAMCHIPS can also be used to profile and differentiate compounds. Five tyrosine kinase inhibitors (from left to right: DMSO, lapatinib/Tykerb, MTKII/MTKL gefitinibfhessa, erlotinib/Tarceva, ZD6474/zactima) result in a distinct inhibition profile in lysates prepared from the responsive cell line NCI-H3255. Likewise, profiles have been generated from less responsive cell lines to differentiate compounds. Results 15 are represented infig. 1 It was found that also non-kinase inhibitors can have profound effects on the PAMCHIP profile, when lysates are prepared from compound treated cells. An example is given where either a histone deacetylase inhibitor or MTKIl is applied on 20- DU-145 prostate cancer cells at 5pM for 20 hours, A robust effect of the histone deacetylase inhibitor is observed on the PAMCRIP profile after cellular treatment, whereas little effect can be seen when lysates are treated with a histone deacetylase inhibitor, consistent with the idea that this compound indirectly inhibits kinases in a cellular context. This illustrates that any compound, when applied to cells, can 25 potentially be profiled using PAMCHIPS. Results are represented in fig. 2. Example 5: Design of a novel 256-peptide array- Generation of signature peptides in xenograft tumors for MTKL To improve the specificity of the standard 140 peptide array and therefore the ability of 30 peptide sets to discriminate between responders and non-responders, a novel set of 256 peptides was selected, The following strategy was used: first, phosphotyrosine peptides were identified in lysates of two cancer cell lines, DUl45 and NCI-N87, by mass spectrometry (in collaboration with Cell Signalling Technologies). This yielded 937 phosphopeptides, many of which were never described earlier, 63 peptides of particular 35 interest were added. known autophosphorylation sites or other substrates of tyrosine kinases that were underrepresented in the 937 peptides. All of these 1000 peptides were then synthesized using the SPOT methodology (a fast, cost-effective peptide synthesis procedure by JPT, Berlin, Germany), and spotted on 7 different 144 peptide arrays.

-46 These arrays were incubated with 32 different cell line and tumor lysates, in the absence and presence of MTKI. From these peptides 194 peptides were selected based on (a) detectability in at least one of the lysates, (b) differential phosphorylation rates across the lysates, and (c) differential inhibition by MTKI in various lysates. In addition 5 62 peptides were added from the standard 140-peptide array that were found useful in previous experiments (such as those in Examples I to 4). The selected 256 peptides were then synthesized using standard high quality procedures by JPT (custom synthesis) and spotted as a single array by Pamgene. This new array (256-peptides) was used to profile 12 xenograft tumor lysates as before in the absence or presence of 10 MTKI. The same mixed-model statistical analysis as before was used to select peptides that discriminate responder versus non-responder tumors, Results of that analysis are shown in Example 5 (28 peptides with P value < 0.1), The fold inhibition of many of these peptides by MTKI is higher compared to the peptides selected from the 140 peptide array (see Example 2), indicating that these peptides are indeed more selective 15 for certain MTKI target kinases. Most importantly, prediction accuracy is greatly improved compared to the peptide set derived from the 140-peptide set, illustrating the usefulness of the peptide selection strategy described above. Results are shown in Tables SA and B Ratio of initial velocity of peptide phosphorylation in the presence of solvent (DMSO) 20 over the initial velocity of peptide phosphorylation in the presence of MTKI; 'NaN indicates that there is no detectable phosphorylation in the presence of DMSO Table 5A H3255 A431 H322 DU145 SUM149 BT474 Peptides MTKI MTKI MTKI MTKI MTKI MTKI BLIM_350_364_Y357 0.82 037 0.72 0.81 0.49 0.71 ACHB_383_395_Y390 0.05 0.35 0.29 0.01 0.68 0.67 Cl lorf35_217_231_Y224 014 0.36 0.05 NaN 0.75 0.80 CBL_667_681_Y674 0.80 0.48 0.65 0.72 0.02 0118 CFLl-6i_75_Y68 0.55 0.36 0.63 0.60 0.04 0.07 DOKI_402_416_Y409 032 0.32 0.80 0.74 0.52 0.83 BCAR_380_394_Y387 0.11 0.13 034 0.51 0.05 0.82 EPHB3_607_621_Y6i4 0.60 0.88 0.65 0.73 0.19 033 FGFRIOP-330_344_Y33 7 0-65 0.96 1 04 0.97 0.51 0,94 -47 FKS 0.1 0,55 0.68 0.69 0.11 0,12 FYN_206_220_Y213 0.28 0.51 0.29 0.05 124 0.66 KIRREL_550_564_Y557 0.22 0.78 0.69 0.63 NaN 017 LAT-249 261-Y255 0.50 0,83 0,82 0.88 0.09 1.12 LPHN2 1343-135-7Y13 50 0.83 0.87 0.70 0.75 010 0.47 LYN_186_200_Y-193 0.28 0.08 0.38 0.13 0.06 0.69 MAPK8_178_192_Y 185 0.29 0.41 0.27 0.02 034 0.62 MCP_362_376_Y369 L04 0.11 0.61 036 0.04 0.25 MET-12271239Y230/ Y12341Y1235 0.72 0.99 0.66 0.43 0.08 0.53 NPT2_501_513_T508 0.55 0.66 0.22 0.05 0.92 0.87 NAPG_298_312Y307 0.59 0.75 0.79 0.74 0.26 0.69 NCF1_313_325-S315/13 20 0.47 0.57 0.22 0.10 0.80 0.93 P2RY2_223_237_Y230 0.39 0.68 041 0.50 0.93 0.96 P85A600_612_Y607/S6 08 0.34 0.68 0.74 0.73 0.21 033 RBM3_120_134_Y127 0.39 0.71 0.58 0.36 L01 0.99 SF3A3472_486 Y479 NaN NaN 0.85 0.33 NaN 0.53 SHB_36_340333 0.17 0.28 0.93 032 NaN 0.49 SLC2OA2_370_384_Y377 0.14 0.53 0.20 0.05 0.84 0.81 VEGFR2_944_956_Y951 0.12 0.49 0.22 0.11 L55 0,81 response status R R R R R R response prediction R R R R Table 5B SKOV3 U87MG PC3 H460 H441 BT29 Peptides MTKI MTKI MTKI MTKI MTKI MTKI ABLIM I350_364_Y357 039 0.73 0,71 0.87 0.70 0,79 ACHB_383_395_Y390 053 0.32 0.42 NaN 0.60 0.55 -48 C 1orf35 217_231 Y224 0,83 0.67 0.56 NaN 0.36 0,73 CBL-667-681 Y674 0.48 0.50 0.82 0.68 0.55 031 CFLI_61_75_Y68 052 0.52 071 0.67 0.46 0.63 DOKI_402_416_Y409 0.68 0.81 0.85 077 032 0.97 BCARI 380_394_Y387 0.57 0.45 048 0,85 0.68 0.73 EPHfB3_607_621_Y614 0.67 0.72 0.83 0.66 0.63 0.63 FGFRIOP_330_344_Y33 7 0.98 114 0.90 0,91 0.90 0.91 FKS 0.59 0.66 035 071 0.54 0.69 FYN_206_220_Y213 0.83 0.41 0,40 NaN 0.73 032 KIRREL_550_564_Y557 0.91 0.54 0.78 0.72 0.56 0.69 LAT_249261_Y255 038 1.09 0.96 0,71 0.93 0.87 LPHN2_1343_1357_Y13 50 037 0.69 0.80 032 0.64 033 LYNJ186200_Y193 0.49 0.48 0.76 NaN 0.57 038 MAPK8_178_192..Y 185 0.54 054 4.47 NaN 037 0.61 MCP_362_376_Y369 0.65 031 0.83 0.67 0.55 0.64 MET 1227 1239 Y1230/ Y1234/Y1235 0.78 0.64 0.81 0.67 44 0.0 NPT2_501_513_T508 0.91 0.82 0.59 0.92 0.82 0.75 NAPG_298_312_Y307 0.73 0.88 0.80 0.70 079 0.73 NCFI_313_325_S315/S3 20 0.85 0.77 0.44 0.73 0.83 0.60 P2RY2_223_237_Y230 0.92 0.87 0.79 0.85 0.80 0,64 P85A_600_612_Y607/S6 08 0.63 105 0,85 0.73 0.76 0.72 RBM3_120_134_Y127 0.86 036 0.60 0.89 032 0.71 SF3A3_472_486_Y479 0.48 1.08 1,20 0.47 0.93 0.96 SHB_326_340_Y333 0.96 0.83 0.92 0.68 0.87 116 SLC2OA2_370 384 Y377 0.88 0.95 0.49 0.63 0.76 0.59 VEGFR2944_956_Y95 1 0.63 076 0.69 NaN 037 0.36 -49 response status NR NR INR NR NR NR response prediction NR NR NR NR NR NR R4Responder to MTKI NR=Non-Responder to MTKI 5 A Responder is predicted when minimally 14 peptides have a ratio < 0.7 (indicated in bold font). Overall accuracy: 100% Example 6: MTKI-derived signature peptides can also be used to predict response 10 to other EGFR inhibitors, such as Tarceva (erlotinib). To test whether other EGFR inhibitors, related to MTKI, such as Tarceva (erlotinib; - OSI pharmaceuticals), are also amenable to this response prediction methodology, 9 cell lines were profiled in the presence of MTKI, or Tarceva (5 pM in both cases). Although minor differences are detectable in the MTKI and Tarceva profiles (eg MTKI 15 is slightly more potent on 1355, consistent with a lower IC50 on EGFR 1858R compared to Tarceva; MTKI is also more potent on N87, a cell line largely driven by Her2, for which MTKI is a better inhibitor than Tarceva; on the other hand Tarceva has additional activity in GTL16 lysates compared to MTKI for unknown reasons), overall there is a striking resemblance in the inhibition pattern between MTKI and Tarceva 20 (see figure 3). The value of the previously derived MTKI prediction peptides is illustrated in Tables 6A to C. Based on these peptides also response to Tarceva can be predicted with identical accuracy as for MTKI (and with the same false predictions, in casu H2009 and MOLT4). These results illustrate that the 16 peptides that correlate with response to MTKI likely also predict reponse to other EGFR inhibitors, such as 25 Tarceva (erlotinib), or Tressa (gefitinib; AstraZeneca). Ratio of initial velocity of peptide phosphorylation in the presence of solvent (DMSO) over the initial velocity of peptide phosphorylation in the presence of MTKI or Tarceva; 'NaN indicates that there is no detectable phosphorylation in the presence of 30 DMSO.

-50 Table 6A H3255 A431 DU145 Peptides MTKI TARC MTKI TARC MTKI TARC CDK7_157_169_S164 0.04 0.12 0.70 0.80 0.36 0.26 CREBI_122_134_Y134/S133 0.35 0.46 0.71 0.81 0.80 0.78 0DR2_733-745_Y740 9.13 018 0.73 0.83 0.44 0.50 ENTOG_37_49_Y43 0.74 0.80 0.91 0,84 0.72 0.67 OSK3B 209_221_Y216 0.10 0.16 0.67 0.72 0.33 0.55 MK10_216&228_T221/Y223 0.16 0.19 070 0.78 0.65 0.63 NCF I313_325_S315/S320 0.39 0.50 0.70 0.78 0,80 0.79 NPT2_501_513_T508 0.35 0.50 0.58 0.70 0.76 0.57 PECAI_706-718tY713 0.78 0.80 0.96 0,82 0.74 0.68 PGFRB_768_780_Y771/Y775/Y 778 NaN NaN L15S 1.00 0.64 0.49 PLCGI_764 776_Y771 0,95 0.90 0.94 0.84 0.76 0.69 PRRX2_202_214_Y214 0.62 0.66 0.90 0.80 0.64 0.75 RASAI_453_465)Y460 0.42 0.47 0.84 0.72 0.62 0.56 STAT2_683_695Y690 0.28 0.39 0.72 0,82 0.79 0.71 SYN 1_14_S9 0.25 0.30 0.71 0.81 0.72 0.65 TYRO3_679_691_Y686 0.12 0.17 0.68 0.78 0.42 0.48 response status R R R R R R response prediction R R R R R R Table 6B N87 SKBR3 SUM149 Peptides MTKI TARC MTKI TARC MTKI TARC CDK7_157_169_S164 0.05 0.04 NaN NaN NaN NaN CREB 122 134 Y134/S133 0.1 0.82 0.82 0.70 0.94 0.94 DDR2_733_745_Y740 0.36 0.34 0.03 0.02 NaN NaN ENOG_37 49-Y43 0.89 0.95 0.80 0.82 0.85 086 GSK3B_209_221_Y216 0.26 0.46 0.30 0.21 NaN NaN M1*0_216_228_T221Y223 0.58 0.78 0.21 0.47 0.03 0.07 -51 NCFI_313_3258315/8320 0.79 0,91 0.79 0.78 1.0 118 NPT2_501_513_T508 .2 0.96 0.75 0.74 ,11 1.34 PECA1706 718.Y713 0.73 0.76 0.96 0.74 0.60 0.68 PGFRB768_780_Y77 I/Y775/Y 778 NaN NaN 0.09 1.63 0.40 0.52 PLCGI_764_776_Y771 0.89 0,86 0.74 0.81 0.84 0.80 PRRX2_202_214_Y214 0.65 0.72 0.57 0.41 0.62 0.80 RASA 1_453 465_Y460 0.76 083 0.42 0.23 0.37 0.39 STAT2_683_695_Y690 0,85 0.95 0.69 0.70 0.85 0.95 SYN_2_14_89 0.79 0.93 0.69 0.67 03 08 TYRO3_679_691_Y686 0.44 0.40 0.05 0.04 NaN NaN response status R R R R R R response prediction R R R R R R Table 6C H2009 GTL16 MQLT4 eptides MTKI TARC MTKI TARC MTKI TARC CDK7_157_169S 164 1.22 1.28 1.04 106 0.85 0.68 CREB1_122_134_Y134/S133 116 113 1.09 0,99 0.90 O58 DDR2_733_745_Y740 1.15 L08 1.08 1.01 0.91 0.81 ENOG_37_49_Y43 0.90 0.96 0.99 0.98 0.73 0.72 GSK3B-209_221 _Y216 1.09 1.15 1.00 0.99 0.88 0.79 MK10_216_228_T221/Y223 1.14 1.16 1.03 0.96 0.82 0.78 NCF1313_325_S315/S320 1.10 L07 1.03 0.96 0.91 0.82 NPT2 501 513 T508 LO8 103 0.98 0.91 0.89 0.69 PECA1_706_718_Y713 0.88 0.84 0.92 0.86 0.64 0.72 PGFRB_768_780_Y77'/Y775/Y 78 0.71 0.75 0.80 0.89 0.60 0.63 PLCG1_764_776_Y771 0.87 0.86 0.95 0.92 0.85 0.74 PRRX2_202_214_Y214 0.92 0.86 0.96 0.75 0.64 0.71 RASA1_453_465_Y460 101 1.00 1.04 0.98 0.67 0.75 STAT2_683_695_Y690 L17 1.12 1.02 0.97 111 1.06 -52 SYNI.2_14_89 L17 1.17 1.07 1.02 0,97 0.86 TYRO3_679_691_Y686 1.10 L03 0.99 0.91 0.88 0.76 response status R R NR NR NR NR response prediction NR NR NR NR R R A responder is predicted when minimally 4 peptides <0.8 MTKI: Accuracy: 78% (7/9); Sensitivity: 86% (6/7); Specificity: 50% (1/2) Tarceva: Accuracy: 78% (7/9); Sensitivity: 86% (6/7); Specificity: 50% (1/2) 5 Example 7: Inhibition of cMet in cell lysates can be correlated to a specific peptide set. To examine whether the currently available 140-tyrosine peptide arrays from Paingene will also detect other kinase activities then those described above, another compound 10 was profiled using the same methodology: ; this is an exquisitely selective inhibitor of the cMET receptor tyrosine kinase (see US2007 0203136 A1) and with formula: F N N NN Similarly, a range of cell lines with varying responsiveness to the cMET inhibitor 605 in HOF-induced colony formation, were profiled (in this case 1pM compound was 15 sufficient for significant inhibition of peptide phosphorylation in the responder cell lysates). As shown in Example 7, clear-cut differences in peptide phosphorylation inhibition by 605 could be identified in the responder lysates versus non-responder lysates. Note that the cMet signature peptide set features two peptides derived from Ron, the closest hornologue to cMet, 605 does not inhibit purified Ron kinase at I pM 20 at all. However, these Ron sites have been demonstrated to be targets for phosphorylation by cMet (Follenzi et a., 2000, Oncogene 19, 4041-3049). The 605 signature peptides show no overlap at all with the MTKI signature peptides set, consistent with the absence of any overlap in kinase specificity between MTKI and 605. These data illustrate that for two types of tyrosine kinase inhibitors, the multi 25 targeted EGFR inhibitor, MTKI (and Tarceva), and the selective cMET inhibitor 605, specific peptides can be identified of which the compound mediated inhibition of phosphorylation rates in sample lysates predict actual biological response of these samples to the compounds using the herein described methodology. Results are shown in Tables 7A to C, -53 Table 7A MKN45 SNU5 Kato2 H441 H1792 Peptides 605 605 605 605 605 ANNAI_13_25Y20/T23 0.03 0.06 0.27 0.22 1,16 CALML95_107Y99/S101 0.14 0.03 0.11 0.14 053 EPHA4_589_601_Y596 0.27 0.26 0.29 0.32 0.77 EGFR_1165_1177_Y1172 0.22 0.02 0.10 0.43 0.33 FAK2_572_584_Y579/Y580 0.57 0.38 0.45 0.56 0.86 FGFR1_759_771_Y766 0.10 0.04 0.01 0.01 NaN JAKI1015 1027 Y1022/Y102 3 0.07 0.03 0.18 0.02 0.96 LAT_194_206_Y200 0.11 0.04 0.07 0.16 0.04 LAT_249 261_Y255 0.59 0.26 0.64 0.71 1.04 LCK_387_399_Y394 0.01 0.01 0.01 NaN NaN MK07_211 223T218/Y220 041 0,29 0.31 0.37 0.85 NTRK2_699_711 Y702/Y706/Y 707 0.64 0.43 0.42 0.54 0.86 PDPK1_2_14_Y9 0.56 0.35 0.37 0.39 PDPKI-369 381 Y373/Y376 0.36 0.10 0.27 0.23 0.84 POFRB1002_1014_Y1009 0.19 0.13 0.05 0.02 LOS PGFRB_709_721_Y716 0.46 0.25 0.21 0.36 1.01 PRRX2_202_214_Y214 0.44 0.28 0.27 0.33 0.81 VEGFR2_1052_1064_Y1059 0.02 0.04 0.03 0.05 0,84 RON_1346_1358_Y]353 0.12 0.06 0.08 0.05 0.71 RON_1353_1365_Y 1356/Y 360 0.04 0.16 0.17 0.07 NaN KSYK_518_530_Y525/Y526 026 0.20 0.14 0.22 0.79 VtNC_815_827_Y821 0.55 0.36 0.34 0.49 0.79 response status R R R R R response prediction R R R R R -54 Table 7B WIDR A549 YKG N87 Caco2 Peptides 605 605 605 605 605 ANXAI_13_25_Y20/T23 0.49 0.92 NaN 0.77 NaN CALM_95_107_Y99/S101 0.31 NaN NaN 0.12 NaN BPHA4589 601 Y596 0.59 L08 1.36 0.88 0.75 EGFR.. 1651177_Y 1172 0,85 1.34 NaN 0.86 NaN FAK2_572_584_Y579/Y580 0.91 0,90 0,92 0,97 1.05 FGFRI759_771_Y766 NaN NaN NaN NaN NaN JAKI_1015_1027 Y1022/Y1021 3 0.39 191 NaN NaN NaN LAT_194_206_Y200 0,86 NaN NaN 0.63 NaN LAT_249_261_Y255 102 1.24 0.69 0.91 NaN LCK_387_399_Y394 NaN NaN NaN NaN NaN MKO7_21 1223T218/Y220 0.87 0.97 0.79 1.06 0.80 NTRK2_699_71 _Y702/Y706/Y 707 0.88 0.95 1.09 0.96 0.92 PDPKI_2_14 Y9 0.85 1.02 LO 0.70 0.77 PDPKI 369_381_Y373/Y376 0.65 1.12 NaN 0.59 NaN PGFRB 1002_1014 Y1009 NaN NaN NaN NaN NaN PGFRB_709_721_Y716 0.71 1 10 NaN 0.78 NaN PRRX2_202_214_Y214 0.74 0.84 1 23 0.78 0,83 VEGFR2 1052_1064_Y1059 0.54 081 NaN 0.68 NaN RON_1346_1358_Y1353 0.12 0.37 NaN NaN NaN RON9 353 365Y1356/Y1360 0.04 NaN NaN NaN NaN KSYK_518_530_Y525/Y526 0.81 1.16 0.46 1.02 0,95 VINC815_827_Y821 0.71 0,81 L13 0.96 0,89 response status R NR NR NR NR response prediction R NR NR R NR ~.55 Table 7C 1322 SNU484 H2122 H2106 Peptides 605 605 605 605 ANXA1L13_25_Y20/T23 108 NaN L04 0.69 CALM_95_107_Y99/S101 NaN NaN 0.49 0.14 EPH A4_589_601-Y596 0.82 0.87 1.10 2.26 EGFR_11 65_1177 Y1172 1.43 0.86 1.06 1.01 FAK2_572_584_Y579/Y580 106 0.91 107 1.10 FGFRi_759-771_Y766 NaN NaN 1.05 NaN JAK1_1015_1027Y1022/Y1023 1.25 NaN 0.96 0.72 LAT 194206,_Y200 0.65 NaN 0.71 NaN LAT_249_261_Y255 L23 127 0.98 0.97 LCK387_399 Y394 NaN NaN NaN NaN MK07_211_223_T218/Y220 0.90 1.02 0.98 0.90 NTRK2-699_711_Y702/Y706/Y707 1.01 0.97 1.03 1.12 PDPK1_2_14_Y9 L02 0.96 0.94 0.99 PDPK1_369_381_Y373/Y376 111 0.66 .10 0,98 PGFRB_1002_1014_Y1009 NaN NaN 0.85 0.41 PGFRB_709_721_Y716 0.92 0.69 1.2 0.67 PRRX2 202 214 Y214 0.93 0.90 133 1 08 VEGFR2_1052_1064_Y1059 NaN 059 1.02 0.96 RON_1346_1358_Y1353 NaN NaN 0.17 NaN RON_1353_1365_Y1356/Y1360 NaN NaN 0.08 NaN KSYK 518_530_Y525/Y526 1.08 1.03 1 46 0.85 VINC_815_827_Y821 0.89 0.76 144 1.00 response status NR NR NR NR response prediction NR NR NR NR R=Responder to OMET NR=Non-Responder to cNT ~56 A Responder is predicted when minimally 7 peptides have a ratio <08 (indicated in bold font). overall prediction accuracy: 12/13 (92%) sensitivity (number of predicted Responders over number of actual Responders):616 5 (100%) specificity (number of predicted Non-Responders over number of actual Non Responders): 7/8 (88%) While the foregoing specification teaches the principles of the present invention, with 10 examples provided for the purpose of illustration, it will be understood that the practice of the invention encompasses all of the usual variations, adaptations and/or modifications as come within the scope of the following claims and their equivalents.

Claims

1. A method for obtaining a pharmacological profile of a kinase inhibitor using a first and a second array of substrates immobilized on a porous matrix, said method 5 comprising the subsequent steps of: (i) preparing a cell lysate from a cell line, including cancer cell lines; primary and immortalized tissue cell lines; non-human animal model biopsies and patient biopsies; (ii) filtering said cell lysate over a filter in the 10 to 0.1 micrometer range to 10 obtain a filtered cell lysate; (iii) contacting said first array of substrates in the presence of the kinase inhibitor with a first fraction of said filtered cell lysate and determining the response of said first array (iv) contacting said second array of substrates in the absence of the kinase 15 inhibitor with a second fraction of said filtered cell lysate and determining the response of said second array; and obtaining the pharmacological profile as the ratio of the array substrate response in step (iii) over the array substrate response in step (iv), wherein: 20 said substrates are at least two peptide kinase substrates selected from the group consisting of the peptide kinase substrates with sequence numbers 1-28, 30, 32 87, 89-107 and 109-337; said substrates consist of the peptide kinase substrates with sequence numbers 15,16,22,34,62,83,86,87,100,105,108,110,113,125,129 and 133; 25 said substrates consist of the peptide kinase substrates with sequence numbers 15,16, 21,23, 38, 42, 53, 62, 69, 77, 83, 86, 91,94, 103, 112,114,129,133, 136 and 138; said substrates consist of the peptide kinase substrates with sequence numbers 142,2,163,173,177,190,161,197,207,208,213,241,73,252,255,258,262,79, 30 87, 266, 86, 269, 95, 296, 303, 305, 308 and 138; or said substrates consist of the peptide kinase substrates with sequence numbers 5,10,38,30,54,57,68,72,73,74,82,91,98,99,102,104,110,135,118, 119,71 and 138. - 58

2. The method as in any one of the preceding claims, wherein the cell lysate is prepared from a cancer cell line; xenograft tumor or cancer patient biopsy, including tumor and normal tissue. 5

3. A method as in any one of the preceding claims, wherein the response of the array of substrates is determined using a detectable signal, said signal resulting from the interaction of the sample with the array of substrates.

4. A method as claimed in any one of the preceding claims, wherein the 10 response of the array of substrates to the sample is determined using detectably labeled antibodies.

5. A method as claimed in claim 4 wherein the response of the array of substrates is determined using fluorescently labeled anti-phosphotyrosine antibodies. 15

6. A method for predicting kinase inhibitor response in a cancer patient comprising the step of obtaining a pharmacological profile according to the method of any one of claims 1 to 5 using a biopsy from said cancer patient for the preparation of the cell lysate, wherein said pharmacological profile predict the response of said patient 20 to said kinase inhibitor.