GB2584441A - Medical uses, methods and uses - Google Patents

Abstract

The present invention relates to an agent, and method of using said agent, for treating cancer in a patient, wherein the cancer is characterised in that it has wild type Receptor Tyrosine Kinase (RTK) activity and it comprises reduced and/or absent CDKN2A activity. The agent used is a compound which inhibits an RTK, preferably an inhibitor of one or more RTKs of the ERbB receptor family such as EGFR, ErbB-2, ErbB-3 and ErbB-4. Additionally, the agent may be administered with one or more additional anti-cancer therapies. Preferably, the additional anti-cancer therapy comprises an inhibitor of BCL-XL. Exemplified is the combination of either gefitinib or lapatinib with either A11554638 or A13318525 in treating lung cancer. Also claimed are methods of predicting patient response to treatment, methods of identifying a patient with cancer in need of treatment and kits comprising the means to detect the activity or mutational status of several genes in a cancer cell sample.

Description

Medical uses, Methods and Uses The present invention relates generally to methods of identifying and treating patients having cancer characterised in that it has a wild type Receptor Tyrosine Kinase (RTK).

The invention also relates to uses and kits.

Lung cancer is the most lethal of all malignancies -every year 2.1 million new cases are discovered and 1.8 million die of the disease. Approximately 80% of lung cancers are non-small cell lung cancer (NSCLC). Advanced NSCLC is generally treated with platinum-based doublet chemotherapies, but is only marginally effective in the majority of cases.

The median overall survival for patients is less than 12 months and the 5-year survival rate is below 10%.

Surgery is the most potentially curative therapeutic option for NSCLC, however it is not always possible and is dependent on the stage of the cancer. Epidermal growth factor receptor (EGFR) has been shown to be overexpressed in as much as 40-80% of NSCLCs (Sridhar, S. S. et at. Lancet Oncol 4, 397-406 (2003)), however currently, only 20% of NSCLC patients received targeted therapies that inhibit tumour growth by inactivating EGFR.

EGFR can be successfully inhibited in patients by the use of antibodies as well as tyrosine kinase inhibitors (TKIs). Early clinical studies comparing EGFR-TKIs to placebo as second-or third-line therapy showed benefit of EGFR-TKIs, and demonstrated differences in response between subgroups of the patients (Shepherd, F. A. et at N Engl J Med 353, 9N 123-132). In parallel, other studies indicated that response to EGFR-TKIs could be predicted based on the presence of activating mutations on EGFR (Lynch, T. J. et a/. N Engl J Med 350, 2129-2139, (2004)). It was later shown that first-line EGFR-TKIs was superior to chemotherapy in patients with EGFR mutant adenocarcinoma, while the opposite was shown in the group of EGFR wild-type (wt) adenocarcinoma (Mok, T. S. et al. N Engl J Med 361, 947-957 (2009)). These results were supported by a subsequent study showing that first-line therapy EGFR-TKIs, with an impressive 74% response rate, was superior to conventional chemotherapy in NSCLC patients with EGFR mutations (Maemondo, M. at at N Engl J Med 362, 2380-2388 (2010)). Further, a study comparing EGFR-TKIs and chemotherapy (docetaxel) as second-line therapy in NSCLC patients with wild-type EGFR showed overall benefit of docetaxel, but disease control was achieved in 26% of the patients treated with EGFR-TKIs (Garassino, M. C. of aL Lancet Oncol 14, 981988, (2013).

Based on these results and similar studies, current clinical practice includes RTK status evaluation and limits RTK-TKI based therapy to patients with confirmed RTK mutations.

An additional clinical problem is that tumours that initially respond to RTK-TKIs develop resistance towards the treatment resulting in regrowth of the tumour. For prolonged control of the disease and potential cure, alternative types of therapy are desirable.

Against this background, the inventors have surprisingly discovered that a subgroup of patients with cancers comprising wild type RTK and reduced and/or absent CDKN2A activity could actually benefit from RTK-TKI based therapy. Furthermore, they have discovered that targeting of the RTK and the anti-apoptotic protein Bcl-xL is useful in treating the subgroups of cancer patients described herein, and, for example, patients who initially respond to RTK-TKIs but who develop resistance towards the treatment resulting in regrowth of the tumour.

In a first aspect, the invention provides, an agent which inhibits a Receptor Tyrosine Kinase (RTK) for use in treating cancer in a patient, wherein (i) it has wild type RTK activity and (ii) it comprises reduced and/or absent CDKN2A activity.

In a second aspect, the invention provides, a use of an agent which inhibits a Receptor Tyrosine Kinase (RTK) in the manufacture of a medicament for treating cancer in a patient, wherein the cancer is characterised in that (i) it has wild type RTK activity and (ii) it comprises reduced and/or absent CDKN2A activity.

In a third aspect, the invention provides, a method of treating cancer in a patient, wherein the cancer is characterised in that (i) it has wild type RTK activity and (ii) it comprises reduced and/or absent CDKN2A activity, wherein the method comprises administering an agent which inhibits a Receptor Tyrosine Kinase (RTK) to the patient.

The inventors have therefore surprisingly discovered that a subgroup of patients with wild type RTKs could benefit from RTK-TKI based therapy. In the case of NSCLC, the inventors predict that approximately 4%, or over 90,000 patients with NSCLCs harbouring wild type EGFR will respond and benefit from EGFR inhibition. Using multi-level molecular response profiling after EGFR inhibition in NSCLC cells, the inventors identified EGFR wild type cells with a molecular response to treatment. This analysis revealed that CDKN2A deletion is associated with increased sensitivity to EGFR-TKIs. Accordingly, the inventors have identified a patient subgroup, who currently are not eligible for targeted therapy, but would benefit from and respond to EGFR inhibition as a first-line treatment.

The inventors' findings therefore provide selection criteria for determining which cancer patients, such as NSCLC patients, will benefit from treatment with RTK inhibitors, such as the EGFR inhibitor gefitinib. The inventors' findings allow identification of patients that would benefit from RTK inhibitors and patients who would not, and have also identified treatments which can improve the responsiveness of cancer cells which develop resistance to RTK inhibitors.

Receptor tyrosine kinases (RTKs) are high-affinity cell surface receptors for many polypeptide growth factors, cytokines, and hormones. RTK activation leads to activation of downstream signal transduction pathways, such as the MAP kinase signalling cascade. The RTK family comprises several subfamilies which include, among others, epidermal growth factor receptors (EGFRs), fibroblast growth factor receptors (FGFRs), insulin and insulin-like growth factor receptors (IR and IGFR), platelet-derived growth factor receptors (PDGFRs), vascular endothelial growth factor receptors (VEGFRs), hepatocyte growth factor receptors (HGFRs), and proto-oncogene c-KIT.

RTK monomers are organized into an extracellular (N-terminal), a transmembrane, and a cytoplasmic kinase domain. They are activated via ligand-induced dimerisation that results in receptor auto-phosphorylation and tyrosine activation of RTKs' substrates including phospholipase C-y, mitogen-activated protein kinases and phosphatidylinositol 3-kinase. Mutations that affect RTK signaling often lead to cell transformation, which is observed in a wide variety of malignancies. This results in increased cell proliferation, survival, invasion and metastasis. Therefore, targeting RTK signaling pathways remains a challenge for scientists and clinicians working in the cancer field. RTKs are targeted using monoclonal antibodies that prevent ligand binding and therefore the activation of downstream signaling pathways. Tyrosine kinase inhibitors (small molecules) act on the tyrosine kinase domain of RTK, preventing receptors' auto-phosphorylation and inhibiting signal transduction (Raged T. (2015) Targeting RTK Signaling Pathways in Cancer. Cancers, 7(3), 1758-84).

Preferably, the RTK is one or more RTK of the ErbB receptor family.

The ErbB RTK family comprises: EGFR (ErbB-1, HER1), ErbB-2 (HER2, neu in rodents), ErbB-3 (HER3) and ErbB-4 (HER4). These structurally related receptors comprise single chain transmembrane glycoproteins consisting of an extracellular ligand-binding ectodomain, a transmembrane domain, a short juxtamembrane section, a tyrosine kinase domain and a tyrosine-containing C-terminal tail.

Preferably, the RTK is one or more selected from the group comprising: EGFR, ErbB-2, ErbB-3 and ErbB-4.

In an embodiment, the RTK is EGFR. EGFR, also known as ErbB1-or HER1, comprises 31 exons coding for different protein variants with up to 1210 amino acids. Exons 1-16 encode the extracellular domain, exon 17 encodes the transmembrane region and remaining exons, exons 18-31 encodes the intracellular domain. EGFR is activated by binding of one of its specific ligands, such as EGF or transforming growth factor-a (TGFa, to its extracellular domain, resulting in receptor homo-or hetero-dimerisation, and receptor autophosphorylation and transphosphorylation through intrinsic tyrosine kinase activity. This triggers an intracellular pathways that can result in fate determination, cell survival, apoptosis, tissue specialization, cell migration, cell proliferation, and invasion and metastasis.

In normal cells without oncogenic mutations in the EGFR signalling pathway and with the cell cycle checkpoint control in place (i.e. normal CDKN2A/B status) both proliferation and apoptosis signalling are controlled by positive and negative regulation resulting in a balanced system (see Figure 10a). However, in CDKN2A and/or CDKN2B deleted NSCLC the cell cycle checkpoint is absent and p53 signalling is impaired through mdm2 dependent inhibition (degradation) of p53. As seen in the Examples, the net effect of this is uncontrolled signalling from the wild type EGFR and reduced pro-apoptotic signalling (see Figure 10c). The inventors have surprisingly found that in these cancer cells inhibition of EGFR signalling can be beneficial. Additionally, they have found that combining inhibition of EGFR signalling together with inhibition of anti-apoptotic Bcl-xL signalling can revert the imbalance and cause cancer cell death. Overall, these findings have identified an unexpected subgroup of cancer patients that are sensitive to inhibition of signalling through the ErbB-family of tyrosine kinase receptors.

By an "agent which inhibits" we include the meaning of any compound which inhibits (e.g., antagonizes, suppresses, reduces, decreases, blocks, and/or reverses) the expression and/or biological activity and/or effect of its target. More particularly, an inhibitor can act in a manner such that the biological activity of its target is decreased in a manner that is antagonistic (e.g., against, a reversal of, contrary to) to the natural, wild type, action of the target.

According to the present invention, an agent which inhibits an RTK (also referred to interchangeably as an RTK inhibitor, of which an RTK-TKI is an example) is any agent that inhibits (antagonises, supresses, reduces, prevents, decreases, blocks, and/or reverses) the expression and/or biological activity of an RTK.

The biological activity or biological action of an RTK, such as an EGFR, refers to any function(s) exhibited or performed by a naturally occurring (wild type) form of the protein as measured or observed in vivo (i.e. in the natural physiological environment of the protein) or in vitro (i.e. under laboratory conditions).

Biological activities of an RTK, such as EGFR are well known in the art and include, but are not limited to, binding to ligand (e.g. EGF), receptor homo-or heterodimerisation, tyrosine kinase activity, and downstream activities related to cellular homeostasis and development.

The biological activity of an RTK can be measured by methods known in the art, including but not limited to measuring receptor phosphorylation or phosphorylation of downstream signalling intermediates by Western blot or other assays where the abundance of a phosphorylated protein is analysed by the use of antibodies directed against the phosphorylated form of the protein, and/or measuring ligand:receptor interaction or receptor:receptor interaction or receptor:adaptor protein interaction through for example co-immunoprecipitation or other pull-down assays coupled to Western blot or Mass spectrometry analysis or by proximity ligation assay.

Particular examples of what the agent may be are described below.

In an embodiment, the agent may be one that inhibits the biological activity of an RTK by at least 2, or at least 5, or at least 10, or at least 50 fold compared to the biological activity of an RTK in the absence of an inhibitor. More preferably, the agent inhibits an RTK by at least 100, or at least 1,000, or at least 10,000 fold compared to the biological activity of an RTK in the absence of an inhibitor.

In an embodiment, the agent may be one that selectively inhibits an RTK. For example, the agent may inhibit members of the ErbB family to a greater extent than it inhibits a different RTKs, for example, members of the FGFR family. Preferably, the agent inhibits its target RTK(s), for example EGFR, at least 5, or at least 10, or at least 50 times more than it inhibits another RTK, for example FGFR. More preferably, the agent inhibits its target RTK(s) at least 100, or at least 1,000, or at least 10,000 times more than it another 5 RTK, for example FGFR.

In an embodiment, the agent may be a selective multi-target RTK inhibitor. In an embodiment, the agent may be a selective dual targeting inhibitor, such as lapatinib, which targets both EGFR and HER2. In an embodiment, the agent may be a selective pan-ErbB family inhibitor, such as afatinib (see Table 1 for further details).

In a preferred embodiment, the agent is one that binds to the RTK in order to inhibit the biological activity of the RTK. More preferably the agent is one that selectively binds to an RTK. By an agent that selectively binds to an RTK, we include the meaning that the agent binds to an RTK with a greater affinity than to an irrelevant polypeptide such as human serum albumin. Preferably, the agent binds to an RTK with at least 5, or at least 10 or at least 50 times greater affinity than to the irrelevant polypeptide. More preferably, the agent binds to an RTK with at least 100, or at least 1,000, or at least 10,000 times greater affinity than to the irrelevant polypeptide. Such binding may be determined by methods well known in the art, including but not limited to Biacore, Thermal protein profiling (TPP), Cellular thermal shift assay (CETSA) Nuclear magnetic resonance spectroscopy (NMR) In an embodiment, the agent is one that binds to the extracellular domain of the RTK. In an alternative embodiment, the agent is one that binds to the intracellular domain of the RTK, in particular to the adenosine triphosphate (ATP)-binding site of the RTK. In another alternative embodiment, the agent is one that binds to the intracellular domain of the RTK, in particular to the kinase domain of the RTK. The extracellular domain, the intracellular domain, and the kinase domain of a given RTK could be readily identified by a person skilled in the art. The nucleotide (gene) sequence and the corresponding amino acid sequence of the human EGFR, ErbB-2, -3, and -4 are known in the art and can be found under GenBank Accession Nos. NG_007726 (EGFR), NG_007503 (ERBB2), NG_011529 (ERBB3), NG_011805 (ERBB4), or under Entrez GenelD:1956 (EGFR), GenelD:2064 (ERBB2), GenelD:2065 (ERBB3), GenelD:2066 (ERBB4), respectively.

In an embodiment, the agent acts by one or more of: a) targeting the extracellular domain of the RTK resulting in inhibition of ligand binding and/or receptor homo-or heterodimerization resulting in inhibition of receptor activation; b) targeting of the intracellular domain of the RTK through binding to the adenosine triphosphate (ATP)-binding site of the RTK resulting in reversible or irreversible inhibition of receptor activation; c) targeting of the intracellular domain of the RTK preventing the receptors' autophosphorylation site resulting in reversible or irreversible inhibition of receptor activation; or d) targeting of the intracellular kinase domain resulting in a reversible or irreversible inhibition of receptor activation.

In an embodiment, the agent does not bind directly to the RTK, but instead extorts its effect of RTK inhibition through interaction with a different protein, or molecule.

In an embodiment, the agent is any one of a small molecule, an antibody or antigen binding fragment thereof (including nanobody), an antibody mimetic, other bioconjugates or immunoconjugates, a polypeptide, a peptide, a peptidomimetic, a nucleic acid (including ribozymes, antisense, RNAi and aptamers), a virus or virus-like particle carrying a therapeutic biomolecule, a hormone, and/or a natural product.

Preferably, the agent is one of (i) an anti-ErbB family tyrosine kinase inhibitor (TKI); and (ii) an anti-ErbB family monoclonal antibody.

There are two main classes of ErbB inhibitors: anti-ErbB family tyrosine kinase inhibitors (TKIs) (small molecules/drugs) and anti-ErbB monoclonal antibodies.

Non-limiting examples of small molecules include EGFR-specific and reversible inhibitors such as, for example, gefitinib (marketed as IRESSA®, ZD1839) and erlotinib (marketed as TARCEVA®, OSI-774, CP-358); EGFR/ERBB2 dual targeting reversible inhibitors, such as lapatinib (marketed as TYKERB® or TYVERB®); EGFR/ERBB2 dual targeting and irreversible inhibitors, such as afatinib (marketed as GILOTRIF® or GIOTRIF®).

Further non-limiting examples of small molecules (TKIs) that can be used in the context of the present invention are shown in Table 1: Molecule Type of Type Route of Standard Target inhibitor administration Dosing gefitinib reversible small molecule oral 250mg oral tablet, once daily EGFR erlotinib reversible small molecule oral 100-150mg EGFR

oral tablet,

once daily lapatinib reversible small molecule oral 250-1500mg oral tablet, once daily EGFR, HER2 afatinib irreversible small molecule oral 30-40mg oral table, once daily EGFR, HER2, ErbB-4 canertinib, Cl-1033 irreversible small molecule oral oral EGFR, HER2 neratinib irreversible small molecule oral 80-240mg oral table, daily HER2 vandetanib n/a small molecule oral 300mg oral tablets, daily EGFR, VEGFA, Protein tyrosine kinase 6, angIopoietin1 receptor, Ret dacomitinib irreversible small molecule oral 45mg oral, once daily EGFR, HER2, ErbB-4 pelitinib, EKB-569 small molecule oral oral, daily EGFR, HER2, ErbB-4 rr brigatinib reversible small molecule oral 90-180mg ALK, ROS1, IGF-1R, Flt3, EGFR, HGFR, HER2, ErbB4, IR, ABL1

oral table,

once daily cetuximab reversible monoclonal antibody IV 250-400mg/m2 intravenous infusion weekly EGFR panitumumab reversible monoclonal antibody IV 6mg/kg IV EGFR every 2 weeks necitumumab reversible monoclonal antibody IV 800mg IV on EGFR Days 1 and 8 of each 3-week cycle trastuzumab reversible monoclonal antibody IV 2-4mg/kg IV, HER2, EGFR, receptors, 1-3 wks apart various IgG complement C1q-r-s subunits pertuzumab reversible monoclonal antibody IV 420-840mg HER2 IV, 3wks apart Table 1: ErbB family tyrosine kinase inhibitors (TKIs) Non-limiting examples of monoclonal antibodies include EGFR specific chimeric (mouse/human) antibodies such as cetuximab (marketed as ERBITUX®); ERBB2 specific chimeric (mouse/human) antibodies such as trastuzumab (marketed as HERCEPTIN®).

Preferably the agent is selected from the group comprising: gefitinib, erlotinib, afatinib lapatinib, pelitinib, canertinib cetuximab, neratinib, panitumumab, vandetanib, necitumumab, dacomitinib, trastuzumab, brigatinib, pertuzumab, and functional analogs, or derivatives thereof.

Particularly preferred EGFR inhibitors are: gefitinib; erlotinib; the dual targeting EGFR/ERBB2 inhibitor afatinib.

It will be appreciated that the invention is not limited to these specific agents, and can include an agonist (described below) of such agents or agents having substantially similar biological activity as these agents, such as generics or biosimilars.

An agent having substantially similar biological activity as the specific agents listed above, for example gefitinib, refers to an agent having substantially any function(s) exhibited or performed by the agent, for example gefitinib, that is ascribed to the agent as measured or observed in vivo (i.e., under physiological conditions) or in vitro (i.e., under laboratory conditions).

It will be appreciated that the small molecule may be a product of drug/prodrug/compound/peptide selection or design, or a prodrug, generic, biosimilar, or functional variant thereof.

The term "prodrug" refers to a biologically inactive compound which can be metabolized in the body to produce a drug.

The term "generic" refers to small-molecules or drugs made from synthesized chemicals with a fixed number of atoms and a known chemical structure. A generic is chemically identical to its branded counterpart and contains the same active ingredients.

The term "biosimilar" refers to molecules or drugs in which the active ingredient is made by a living organism, and which are highly similar to the original biological drug and contain no clinically meaningful differences.

A "functional variant" of a small molecule or drug refers to a variant with substantially similar biological activity as the specific molecule. The functional variant will have substantially any function(s) exhibited or performed by the specific molecule, for example gefitinib, that is ascribed to the molecule as measured or observed in vivo (i.e. under physiological conditions) or in vitro (i.e. under laboratory conditions). It will be appreciated that the functional variant may not have an identical composition or structure to the molecule.

The term "small molecule" includes small organic molecules, drugs, prodrugs and/or compounds. Suitable small molecules may be identified by methods such as screening large libraries of compounds (Beck-Sickinger & Weber (2001) Combinational Strategies in Biology and Chemistry (John Wiley & Sons, Chichester, Sussex); by structure-activity relationship by nuclear magnetic resonance (Shuker et al (1996) "Discovering high-affinity ligands for proteins: SAR by NMR. Science 274: 1531-1534); encoded self-assembling chemical libraries Melkko et al (2004) "Encoded self-assembling chemical libraries." Nature Biotechnol. 22: 568-574); DNA-templated chemistry (Gartner et al (2004) "DNA-templated organic synthesis and selection of a library of macrocycles. Science 305: 16011605); dynamic combinatorial chemistry (Ramstrom & Lehn (2002) "Drug discovery by dynamic combinatorial libraries." Nature Rev. Drug Discov. 1: 26-36); tethering (Arkin & Wells (2004) "Small-molecule inhibitors of protein-protein interactions: progressing towards the dream. Nature Rev. Drug Discov. 3: 301-317); and speed screen (Muckenschnabel et al (2004) "SpeedScreen: label-free liquid chromatography-mass spectrometry-based high-throughput screening for the discovery of orphan protein ligands." Anal. Biochem. 324: 241-249). Typically, small organic molecules will have a dissociation constant for the polypeptide in the nanomolar range, particularly for antigens with cavities. The benefits of most small organic molecule binders include their ease of manufacture, lack of immunogenicity, tissue distribution properties, chemical modification strategies and oral bioavailability. Small molecules with molecular weights of less than 5000 daltons are preferred, for example less than 400, 3000, 2000, or 1000 daltons, or less than 500 daltons.

By small molecule, we also include the meaning of prodrugs thereof. For example, the agent may be administered as a prodrug which is metabolised or otherwise converted into its active form once inside the body of a subject. The term "prodrug" as used herein refers to a precursor or derivative form of a pharmaceutically active substance that is less active compared to the parent drug and is capable of being enzymatically activated or converted into the more active parent form (see, for example, D. E. V. Wilman "Prodrugs in Cancer Chemotherapy" Biochemical Society Transactions 14, 375-382 (615th Meeting, Belfast 1986) and V. J. Stella et al. "Prodrugs: A Chemical Approach to Targeted Drug Delivery" Directed Drug Delivery R. Borchardt et al (ed.) pages 247-267 (Humana Press 1985)).

Another type of agent (RTK inhibitor) can include an antibody, antigen binding fragment thereof, or an antigen binding peptide or 'binding partner". Antibodies are characterized in that they comprise immunoglobulin domains and as such, they are members of the immunoglobulin superfamily of proteins.

The term "antibody' or "antibody molecule" as used herein throughout the specification includes but is not limited to polyclonal, monoclonal, chimeric, single chain, Fab fragments and fragments produced by a Fab expression library. Such fragments include fragments of whole antibodies which retain their binding activity fora target substance, Fv, F(ab') and F(ab')2 fragments, as well as single chain antibodies (scFv), fusion proteins and other synthetic proteins which comprise the antigen-binding site of the antibody. The term also includes antibody-like molecules which may be produced using phage-display techniques or other random selection techniques for molecules which bind to the specified polypeptide or to particular regions of it. Thus, the term antibody includes all molecules which contain a structure, preferably a peptide structure, which is part of the recognition site (i.e. the part of the antibody that binds or combines with the epitope or antigen) of a natural antibody.

Furthermore. the antibodies and fragments thereof may be humanised antibodies. which are now well known in the art.

By "ScFv molecules" we mean molecules wherein the VH and VI_ partner domains are linked via a flexible oligopeptide. Engineered antibodies, such as ScFv antibodies, can be made using the techniques and approaches long known in the art. The advantages of using antibody fragments, rather than whole antibodies, are several-fold. The smaller size of the fragments may lead to improved pharmacological properties, such as better penetration to the target site. Effector functions of whole antibodies, such as complement binding, are removed. Fab, Fv, ScFv and dAb antibody fragments can all be expressed in and secreted from E. coli, thus allowing the facile production of large amounts of the fragments. Whole antibodies, and F(ab')2 fragments are "bivalent". By "bivalent" we mean that the antibodies and F(ab')2 fragments have two antigen combining sites. In contrast, Fab, Fv, ScFv and dAb fragments are usually monovalent, having only one antigen combining site.

It is possible however that the ScFv may be monovalent, divalent, trivalent or tetravalent. The 5 ScFv may be a diabody, tribody, or a tetrabody. The two or more VH and VL partner domains in a divalent, trivalent or tetravalent or diabody, tribody, or a tetrabody may be different. In such a situation, an ScFv agent may comprise more than 2 or more than 3, for example 4 different VH and VL domains.

Antibodies may be produced by standard techniques, for example by immunisation with the appropriate (glyco)polypeptide or portion(s) thereof, or by using a phage display library.

If polyclonal antibodies are desired, a selected mammal (e.g., mouse, rabbit, goat, horse, etc) is immunised with an immunogenic polypeptide bearing a desired epitope(s), optionally haptenised to another polypeptide. Depending on the host species, various adjuvants may be used to increase immunological response. Such adjuvants include, but are not limited to, Freund's, mineral gels such as aluminium hydroxide, and surface active substances such as lysolecithin, pluronic polyols, polyanions, peptides, oil emulsions, keyhole limpet hemocyanin, and dinitrophenol. Serum from the immunised animal is collected and treated according to known procedures. If serum containing polyclonal antibodies to the desired epitope contains antibodies to other antigens, the polyclonal antibodies can be purified by immunoaffinity chromatography. Techniques for producing and processing polyclonal antisera are well known in the art.

Monoclonal antibodies directed against entire polypeptides or particular epitopes thereof can also be readily produced by one skilled in the art. The general methodology for making monoclonal antibodies by hybridomas is well known. Immortal antibody-producing cell lines can be created by cell fusion, and also by other techniques such as direct transformation of B lymphocytes with oncogenic DNA, or transfection with Epstein-Barr virus. Panels of monoclonal antibodies produced against the polypeptides listed above can be screened for various properties; i.e., for isotype and epitope affinity. Monoclonal antibodies may be prepared using any of the well-known techniques which provides for the production of antibody molecules by continuous cell lines in culture.

It is preferred if the antibody is a monoclonal antibody. In some circumstances, particularly if the antibody is to be administered repeatedly to a human patient, it is preferred if the monoclonal antibody is a human monoclonal antibody or a humanised monoclonal antibody, which are suitable for administration to humans without engendering an immune response by the human against the administered immunoglobulin. Suitably prepared nonhuman antibodies can be "humanised" in known ways, for example by inserting the CDR regions of mouse antibodies into the framework of human antibodies. Humanised antibodies can be made using the techniques and approaches described in Verhoeyen et a/ (1988) Science, 239, 1534-1536, and in Kettleborough et a!, (1991) Protein Engineering, 14(7), 773-783. In some instances, Fv framework residues of the human immunoglobulin are replaced by corresponding non-human residues. In general, the humanised antibody will contain variable domains in which all or most of the CDR regions correspond to those of a non-human immunoglobulin, and framework regions which are substantially or completely those of a human immunoglobulin consensus sequence.

Completely human antibodies may be produced using recombinant technologies. Typically large libraries comprising billions of different antibodies are used. In contrast to the previous technologies employing chimerisation or humanisation of e.g. murine antibodies this technology does not rely on immunisation of animals to generate the specific antibody. Instead the recombinant libraries comprise a huge number of pre-made antibody variants wherein it is likely that the library will have at least one antibody specific for any antigen. Thus, using such libraries, an existing antibody having the desired binding characteristics can be identified.

It is appreciated that when the antibody is for administration to a non-human individual, the antibody may have been specifically designed/produced for the intended recipient species.

WO 98/32845 and Soderlind et al (2000) Nature BioTechnol. 18: 852-856 describe technology for the generation of variability in antibody libraries. Antibody fragments derived from this library all have the same framework regions and only differ in their CDRs. Since the framework regions are of germline sequence the immunogenicity of antibodies derived from the library, or similar libraries produced using the same technology, are expected to be particularly low (Soderlind et al, 2000), This property is of great value for therapeutic antibodies, reducing the risk that the patient forms antibodies to the administered antibody, thereby reducing risks for allergic reactions, the occurrence of blocking antibodies, and allowing a long plasma half-life of the antibody. Thus, when developing therapeutic antibodies to be used in humans, modern recombinant library technology (Soderlind et a!, 2001, Comb. Chem. & High Throughput Screen. 4: 409-416) is now used in preference to the earlier hybridoma technology.

By antibodies we also include heavy-chain antibodies structurally derived from camelidae antibodies, such as Nanobodies® (Ablynx). These are antibody-derived therapeutic proteins that contain the structural and functional properties of naturally-occurring heavy-chain antibodies. The Nanobody® technology was developed following the discovery that camelidae (camels and llamas) possess fully functional antibodies that lack light chains. These heavy-chain antibodies contain a single variable domain (VHH) and two constant domains (CH2 and CH3). The cloned and isolated VHH domain is a perfectly stable polypeptide harbouring the full antigen-binding capacity of the original heavy-chain antibody. These VHH domains with their unique structural and functional properties form the basis of Nanobodies®. They combine the advantages of conventional antibodies (high target specificity, high target affinity and low inherent toxicity) with important features of small molecule drugs (the ability to inhibit enzymes and access receptor clefts). Furthermore, they are stable, have the potential to be administered by means other than iniection. are easier to manufacture, and can be humanised. (See, for example US 5,840,526; US 5,874,541; US 6,005,079, US 6.765,087; EP 1 589 107; WO 97/34103; W097/49805; US 5,800,988; US 5,874, 541 and US 6,015,695).

By "antibody" we also include an antibody mimetic.

By "antibody mimetic" we include organic compounds that are not structurally related to antibodies but are capable of binding to a target in a manner analogous to that of the antigen-antibody interaction. They are usually artificial peptides or proteins with a molar mass of about 3 to 20 kDa. Affibodies are a type of antibody mimetic, and their protein scaffold is derived from the B-domain of staphylococcal protein A. By a "nucleic acid" also termed "oligonucleotide", "nucleic acid sequence," "nucleic acid molecule," and "polynucleotide" we include a DNA sequence or analog thereof, or an RNA sequence or analog thereof. Nucleic acids are formed from nucleotides.

Other types of agents (RTK inhibitors) can include, but are not limited to, aptamers, RNAi, and ribozymes.

An aptamer is a sequence of single strand nucleic acid (DNA or RNA) with a variable region of about 40 nucleotide bases selected from randomized combinatorial nucleic acid libraries by virtue of their ability to bind to a predetermined specific target molecule with high affinity and specificity. Suitable aptamers that bind to an RTK may be identified by methods such as in vitro selection and amplification (Ellington & Szostak (1992) "Selection in vitro of single stranded DNA molecules that fold into specific ligand binding structures." Nature 355: 850-852; and Daniels eta! (2003) "A tenascin-C aptamer identified by tumour cell SELEX: systematic evolution of ligands by exponential enrichment." Proc. Natl Acad. Sci. USA 100, 15416-15421). The aptamer may be a nuclease-stable Spiegelmer' (Helmling et al (2004) "Inhibition of ghrelin action in vitro and in vivo by an RNA-Spiegelmer." Proc. Nat! Acad. ScL USA 101: 13174-13179). Aptamers typically have dissociation constants in the micromolar to the subnanomolar range. Aptamers have a defined three-dimensional structure and are capable of discriminating between compounds with very small differences in structure.

RNA interference (RNAi) is a biological process in which double stranded RNA, and in mammalian systems, short interfering RNA (siRNA), is used to inhibit and/or silence expression of complementary genes. In the target cell, siRNA are unwound and associate with an RNA induced silencing complex (RISC), which is then guided to the mRNA sequences that are complementary to the siRNA, whereby the RISC cleaves the mRNA.

Ribozymes are RNA enzymes that catalyze site-specific phosphodiester bond cleavage of a target RNA sequence. More specifically, ribozymes are antisense RNA molecules that function by binding to the target RNA moiety and inactivate it by cleaving the phosphodiester backbone at a specific cutting site.

The term "peptidomimetic" refers to a compound that mimics the conformation and desirable features of a particular peptide as a therapeutic agent, but that avoids the undesirable features. They are used extensively in science and medicine as agonists and antagonists of protein and peptide ligands of cellular and other receptors, and as substrates and substrate analogues for enzymes. Some examples are morphine alkaloids (naturally-occurring endorphin analogues), penicillins (semi-synthetic), and HIV protease inhibitors (synthetic). For example, morphine is a compound which can be orally administered, and which is a peptidomimetic of the peptide endorphin. Such compounds have structural features that mimic a peptide or a protein and as such are recognised and bound by other proteins. Binding the peptidomimetic either induces the binding protein to carry out the normal function caused by such binding (agonist) or disrupts such function (antagonist, inhibitor).

Agents of the invention also include agonists thereof. By "agonist" we include a compound that is characterised by the ability to agonise (e.g. enhance, stimulate, induce, increase, and/or mimic) the biological activity of a naturally occurring or synthetic molecule, protein or compound (such as a small molecule) that can act as an agent as define herein. More particularly, an agonist can include, but is not limited to, a compound, polypeptide, peptide, or nucleic acid that mimics or enhances the activity of the natural or synthetic molecule, protein or compound, and includes any homologue, mimetic which is characterised by its ability to agonise (e.g. enhance, stimulate, induce and/or increase) the biological activity of a naturally occurring or synthetic molecule, protein or compound.

By "treating" or "treatment" we include administering therapy to reverse, reduce, alleviate, arrest or cure the symptoms, clinical signs, and/or underlying pathology of a specific disorder, disease, injury or condition in a manner to improve or stabilise an individual's disease. Thus, treatment refers to administration of the agent to a patient in need thereof, with the expectation that they will obtain a therapeutic benefit. "Treating" or "treatment" of a cancer in a mammal includes one or more of: inhibiting growth of the cancer (e.g. arresting its development), preventing spread of the cancer (e.g. preventing metastases), relieving the cancer (e.g. causing regression of the cancer), preventing recurrence of the cancer, and palliating symptoms of the cancer. As such, a therapeutic benefit can be achieved without curing a particular disease or condition, but rather, preferably encompasses a result which includes one or more of alleviation of the disease or condition, reduction of a symptom associated with the disease or condition, elimination of the disease or condition, prevention or alleviation of a secondary disease or condition resulting from the occurrence of a primary disease or condition (e.g. metastatic tumour growth resulting from a primary cancer), and/or prevention of the disease or condition. A therapeutic benefit can be assessed by one of ordinary skill in the art and/or by a trained clinician who is treating the patient.

The term "preventing" is art-recognised, and when used in relation to a condition, such as cancer or any other medical condition, it includes administration of an agent/composition which reduces the frequency of, or delays the onset of, symptoms, clinical signs, and/or underlying pathology of a specific disorder, disease, injury or medical condition in an individual relative to an individual who does not receive the molecule/composition. The term "prophylactic" treatment is art-recognised and is used interchangeably with "preventing" and "prevention". "Prophylactic treatment" includes administration of a molecule/compound prior to clinical manifestation of the unwanted condition (e.g. cancer) (i.e., it protects the individual against developing the unwanted condition), whereas if it is administered after manifestation of the unwanted condition, the treatment is therapeutic, (i.e., it is intended to diminish, ameliorate, or stabilize the existing unwanted condition or side effects thereof). In the context of cancer, prevention may include preventing spread of the cancer (e.g., preventing metastases). By prevention we also include preventing the development of resistance to treatment and/or therapy. For example, resistance may be prevented through the simultaneous administration of more than one therapy/drug (combination therapy) as described herein.

By "a patient" we include the meaning of a subject, or individual in need of treatment and/or prevention of a disease or condition as described herein. The patient may be a vertebrate, such as a vertebrate mammal.

to In an embodiment, the patient may is selected from the group comprising: a primate (for example, a human; a monkey; an ape); a rodent (for example, a mouse, a rat, a hamster, a guinea pig, a gerbil, a rabbit); a canine (for example, a dog); a feline (for example, a cat); an equine (for example, a horse); a bovine (for example, a cow); and/or a porcine (for example, a pig). ts

Most typically, a patient will be a human patient.

By the cancer is characterised in that it "has wild type RTK activity" we include that the cancer comprises an RTK which has a biological activity or biological action substantially the same as the biological activity or biological action exhibited or performed by a naturally occurring (wild type) form of the protein. Such activity and/or action is measured or observed in vivo (i.e., in the natural physiological environment of the protein) or in vitro (i.e., under laboratory conditions). Enzymatic activity of a wild type receptor can be tested by an in vitro enzyme activity assay, where the kinase activity of the RTK is estimated by measurement of phosphorylation of a specific substrate.

It will be appreciated that a cancer will have wild type RTK activity if the RTK does not comprise an activating (i.e. oncogenic) mutation. Accordingly, following sequencing of the gene or part of a gene or its RNA product, if there are no oncogenic mutations it will be assumed that the RTK has wild type activity. For example, in an embodiment in which the RTK is EGFR, for the cancer to have wild type EGFR activity, EGFR would not contain an activating/oncogenic mutation.

The presence of oncogenic mutations are routinely identified by methods known in the art such as Chromogenic and Fluorescence In-Situ Hybridization (CISH and FISH); SNP-arrays; Methylation Arrays; DNA-sequencing; RNA level assays; and protein level assays.

Activating mutations of ErbB family members are known in the art, and include but are not limited to those described below in Table 2.

In an embodiment, wherein the RTK is EGFR, determining the activity, level, and/or 5 mutational status of EGFR comprises determining whether the EGFR comprises an activating mutation selected from the group comprising: -Exon 18 substitutions including: G719C, G719S, G719A, V689M, N700D, E709K/Q and/or S720P; Exon 19 deletions including: AE746-A750, AE746-T751, AE746-A750 (ins RP), AE746-T751 (ins NI), AE746-T751 (ins VA), AE746-8752 (ins NV), AL747-E749 (A750P), AL747-A750 (ins P), AL747-T751, AL747-T751 (ins P/S), AL747-S752, AL747-752 (E746V), AL747-752 (P7538), AL747-S752 (ins Q), AL747-P753 and/or AL747-P753 (ins S); Exon 20 substitutions including: V765A, S7681, T783A and/or AS752-1759; and/or Exon 21 substitutions including: L858R, N826S, A839T, K846R, L861Q and/or G863D In an embodiment, wherein the RTK is ERBB2, determining the activity, level, and/or mutational status of ERBB2 comprises determining whether the ERBB2 comprises an activating mutation selected from the group comprising: S310F/Y, S429R, R678Q, L755S/NP, 755-759 deletion, D769H/Y, Y772_A775dup, V777L/M, G778_P780dupN777LN777M, V842I and/or L869R.

In an embodiment, wherein the RTK is ERBB3, determining the activity, level, and/or 25 mutational status of ERBB3 comprises determining whether the ERBB3 comprises an activating mutation selected from the group comprising: V104L and/or V104M.

In an embodiment, wherein the RTK is ERBB4, determining the activity, level, and/or mutational status of ERBB4 comprises determining whether the ERBB4 comprises an activating mutation selected from the group comprising: R106C and/or R106H.

EGFR mutations ERBB2 mutations ERBB3 mutations ERBB4 mutations Exon 18 S310F/Y Substitutions unknown relevance in lung Substitutions substitutions including: unknown relevance in lung G719C S429R V104L R106C G719S R678Q V104M R106H G719A L755S/A/P V689M 755-759 deletion N700D D769H/Y E709K/Q Y772 A775dup S720P V777L/M G778 P780dup/V777L/V777M Exon 19 deletions including: V8421 AE746-A750 L869R AE746-T751 AE746-A750 (ins RP) AE746-T751 (ins NI) AE746-T751 (ins VA) AE746-S752 (ins NV) AL747-E749 (A750P) AL747-A750 (ins P) AL747-T751 AL747-T751 (ins P/S) AL747-5752 AL747-752 (E746V) AL747-752 (P753S) AL747-S752 (ins Q) AL747-P753 AL747-P753 (ins S) AS752-1759 Exon 20 V765A S7681 T783A Exon 21 L858R N826S A839T K846R L861Q G863D Table 2: Table of oncogenic mutations in EGFR, ERBB2, ERBB3 and ERBB4 In an embodiment, the cancer is characterised in that it has wild type RTK activity, if the RTK is not mutated.

By the cancer is characterised in that it comprises "reduced and/or absent CDKN2A activity" we include that the biological activity or biological action of CDKN2A is substantially decreased and/or is absent compared to the biological activity or biological action exhibited or performed by a naturally occurring (wild type) form of the protein. Such activity and/or action is measured or observed in vivo (i.e. in the natural physiological environment of the protein) or in vitro (i.e. under laboratory conditions). The terms "reduced and/or absent CDKN2A activity" and "CDKN2A inactivation" will be used interchangeably herein.

CDKN2A, also known as cyclin-dependent kinase Inhibitor 2A, is a gene which encodes two proteins, including the INK4 family member p16 (or p16INK4a) and p14arf. The CDKN2A locus is at chromosome 9p21. Both p16 and p14 act as tumour suppressors by regulating the cell cycle and/or apoptosis signalling. p16 inhibits cyclin dependent kinases 4 and 6 (CDK4 and CDK6) and thereby activates the retinoblastoma (Rb) family of proteins, which block G1 to S-phase transition resulting in G1 arrest. pl 4ARF (known as p19ARF in the mouse) activates the p53 tumour suppressor. Somatic mutations of CDKN2A are common in the majority of human cancers, and it is estimated that CDKN2A is the second most commonly inactivated gene in cancer after p53 (Gil J. and Peters G. Nat Rev Mol Cell Bid. 2006 Sep;7(9):667-77; Kim WY and Sharpless NE Cell. 2006 Oct 20;127(2):265-75).

CDKN2B, also known as cyclin-dependent kinase Inhibitor 2B, is a gene which lies adjacent to the tumor suppressor gene CDKN2A. It encodes a cyclin-dependent kinase inhibitor, also known as p15Ink4b protein, which forms a complex with CDK4 or CDK6, and prevents the activation of the CDK kinases by cyclin D; thus the encoded protein functions as a cell growth regulator that inhibits cell cycle G1 progression.

CDKN2A and CDKN2B are tumour suppressor genes. Tumour suppressor genes are normal genes that regulate cell division, repair DNA mistakes, and/or regulate apoptosis or programmed cell death. Mutations which inactivate a tumour suppressor gene by effecting their expression or biological activity can lead to loss of control of cell growth which can lead to cancer.

In an embodiment, the cancer comprises reduced and/or absent CDKN2B activity.

Preferably, reduced and/or absent CDKN2A and/or CDKN2B activity is reduced and/or absent due to deletion, mutation and/or methylation of CDKN2A and/or CDKN2B.

Three mechanisms have been implicated in CDKN2A inactivation: homozygous deletion, hypermethylation, and point mutation. Specifically, methylation of CpG sites in the promoter region of the CDKN2A gene is known to be associated with its reduced expression, and therefore reduced and/or absent activity. Homozygous deletion of chromosome 9 will result in reduced and/or absent CDKN2A and/or CDKN2B activity. Evaluation of gene copy number can be used to detect a deletion of the genetic loot 5 where both CDKN2A and CDKN2B reside (Gil J. and Peters G. Nat Rev Mol Cell Biol. 2006 Sep;7(9):667-77; Kim WY and Sharpless NE Cell. 2006 Oct 20;127(2):265-75).

As can be seen in the accompanying Examples, CDKN2A mRNA levels were not significantly different between samples with heterozygous CDKN2A deletion and samples with normal CDKN2A copy number, indicating that loss of one CDKN2A copy can be compensated for. Homozygous deletion of CDKN2A however showed clear loss of CDKN2A mRNA expression as expected (Figure 9a).

Methods of determining if CDKN2A and/or CDKN2B activity is reduced and/or absent due to deletion, mutation and/or methylation of CDKN2A and/or CDKN2B are known in the art, see, for example, Sergey Kurdyukov and Marlyn Bullock "DNA Methylation Analysis: Choosing the Right Method" Biology (Basel). 2016 Mar; 5(1): 3, and include, but not limited to: Methylation Arrays; DNA-sequencing; DNA-level assays; RNA level assays; and protein level assays.

By "DNA-sequencing" we include techniques known in the art, including whole genome shotgun sequencing, next-generation sequencing, including long-read sequencing and short-read sequencing.

By "DNA-level assays" we include techniques known in the art, including DNA-arrays, SNP-arrays, whole genome sequencing (long-read sequencing and short-read sequencing), whole exome sequencing, targeted DNA panel sequencing, polymerase chain reaction (PCR), digital-PCR, Southern blot, Chromogenic in-situ hybridization (CISH) and fluorescence in-situ hybridization (FISH), methylation assays, methylation arrays, PCR-ELISA, nCounter® technology.

By "RNA-level assays" we include techniques known in the art, including Chromogenic in-situ hybridization (CISH) and fluorescence in-situ hybridization (FISH), RNA-sequencing, RNA microarrays, quantitative RT-PCR, digital RT-PCR, Northern blot, nCounter® technology, RT-PCR-ELISA.

By "protein-level assays" we include techniques known in the art, including HPLC, antibody-based assays (such as immunohistochemistry, protein gel electrophoresis, Western blot, ELISA, proximity ligation assay, proximity extension assay), Mass spectrometry-based methods (both labelled or unlabelled samples), and combinations of methods such as RNA/protein such as multiplex PCR/liquid chromatography assay, nCounter® technology.

Examples of commercially available products for testing any target DNA, RNA or protein level, not just CDKN2A but also others include: cobas product line of real-time PCR tests io (Roche Diagnostics); Vysis fluorescence in situ hybridization FISH probes for DNA (Abbott); Ventana immunohistochemistry assays ((Ventana Medical Systems Inc.); and therascreen real-time PCR tests (QIAGEN).

As explained above, in CDKN2A/B inactivated NSCLC the cell cycle checkpoint is absent and p53 signalling is impaired through mdm2 dependent inhibition (degradation) of p53.

The net effect of this is uncontrolled signalling from the wild type EGFR and reduced proapoptotic signalling. The inventors hypothesise that cancer cells develop an EGFR signalling dependence when CDKN2A and/or CDKN2B activity is reduced and/or absent.

Preferably, the cancer is further characterised in that (iii) it is dependent on the activity of the wild-type RTK for proliferation and/or survival.

It will be appreciated that for a cancer to be dependent on the activity of a wild-type RTK for proliferation and/or survival, the RTK signalling pathway must not comprise an oncogenic mutation. The skilled person will understand that an oncogene is a gene that encodes a protein that is capable of inducing cancer. An oncogenic mutation may also be termed an activating mutation. If an RTK signalling pathway comprises an oncogenic mutation, the cancer will generally be dependent on that oncogene for proliferation and/or survival. This is a concept known as "oncogene addiction". Oncogene addiction refers to the reliance on one single dominating oncogene for growth and survival, so that inhibition of this one specific oncogene can halt a neoplastic phenotype. In other words, in the embodiment wherein the RTK is EGFR, the cancer cell must not contain an activating mutation in the EGFR signalling pathway.

However, certain cancer cells can be dependent on RTK signalling even without oncogenic mutations in the RTK signalling pathway. For example, certain cancer cells might be highly dependent on a specific RTK because during their development, they lost the function of another gene that normally contributes to the regulation of the signalling activated by said RTK. It will be appreciated that the cancer is therefore dependent on the activity of the wild-type RTK, i.e. RTK-mediated cancer, and in an embodiment, is an EGFR-mediated cancer. By an RTK or EGFR "mediated-cancer" we include that the cancer results from the activity of the RTK (such as EGFR). The skilled person will appreciate that in, for example, an EGFR-mediated cancer, the activity of EGFR is responsible for cancer cell growth, survival and/or tumour growth.

An important difference between oncogenes and tumour suppressor genes (discussed above in relation to CDKN2A and CDKN2B) is that oncogenes result from the activation of proto-oncogenes, but tumour suppressor genes cause cancer when they are inactivated.

Preferably, the cancer comprises KRAS having a wild type activity, BRAF having a wild type activity, ROS1 having a wild type activity, and/or ALK having a wild type activity.

By "wild type activity" we include that the cancer comprises KRAS, BRAF, ROS1 and ALK which have a biological activity or biological action substantially the same as the biological activity or biological action exhibited or performed by a naturally occurring (wild type) form of the protein. Such activity and/or action is measured or observed in vivo (i.e. in the natural physiological environment of the protein) or in vitro (i.e. under laboratory conditions).

Preferably, the cancer does not comprise an activating RTK mutation, an activating KRAS mutation, an activating BRAF mutation, an activating ROS1 mutation, and/or an activating ALK mutation. Examples of such mutations are shown in Table 3.

The skilled person will appreciate that the cancer to be treated by the invention must not comprise an activation mutation in a proto-oncogene. The skilled person will understand that a proto-oncogene is a normal gene which, when altered by mutation, becomes an oncogene that can contribute to cancer. In the context of the present invention, such proto-oncogenes are KRAS, BRAF, ROS1 and ALK.

The skilled person will appreciate that if the cancer to be treated comprised, for example, BRAF containing an activating mutation (such as V600E), BRAF would be oncogenic and the cancer would be dependent on the activity of BRAF for growth and survival, and not dependent on an RTK. The skilled person will appreciate that this type of cancer could be treated with a BRAF inhibitor.

The skilled person is aware of oncogenic KRAS mutations, oncogenic BRAF mutations, and oncogenic ROS1 mutations, and oncogenic ALK mutations, and these include those described below in Table 3.

KRAS mutations BRAF mutations ALK mutations ROS1 mutations Exon 2 Exon 11 EML4-ALK fusion ROS1 fusions including: including: G12C G464E E13;A20 CD74-ROSI fusion C6;R32 G12V G464V E6;A20 CD74-ROS1 fusion C6;R34 G12D G466A E20;A20 EZR-ROS1 fusion El 0;R34 G12A G466E E18;A20 SLC34A2-ROS1 fusion S14;R32 G1 2S G466V E14;A20 SLC34A2-ROS1 fusion S14;R34 G12R G469A E15;A20 SDC4-ROS1 fusion S2;R32 G12F G469L E2;A20 SDC4-ROS1 fusion S2;R34 G12Y E17;A20 TPM3-ROS1 fusion T8;R35 G13C Exon 15 E3;A20 FIG-ROS1 fusion F7;R35 G13D N581S E6;A19 LIMA1-ROS1 fusion L; R36 G13A D594G E21;A20 MSN-ROS1 fusion M;R34 G1 3V G596V E6;A17 C CDC6-ROS1 fusion C; R34 G13R V600E LRIG3-ROS1 fusion L;R35 G13S V600K Other ALK fusions TMEM106B-ROS1 fusion T; R35 V600D TFG-ALK fusion T6;A20 TPD52L1-ROS1 fusion T; R33 Exon 3 V600R KIF5B-ALK fusion K24;A20 CLTC-ROS1 fusion C;R35 061H V600M KLC1-ALK fusion K9;A20 Q61R K601E PTPN3-ALK fusion P2;A10 061L HIP1-ALK fusion H21;A20 "61K TPR-ALK fusion T15;A20 BIRC6-ALK fusion 610; A20 DCTN1-ALK fusion D26;A20 SQSTM1-ALK fusion S5;A20 PRKAR1A-ALK fusion P5;A20 PPM1B-ALK fusion P1;A20 El F2AK3-ALK fusion E2;A20 BCL11A-ALK fusion B4;A20 CEBPZ-ALK fusion C3;A20 PICALM-ALK fusion P19;A20 GCC2-ALK fusion GI 2;A20 LMO7-ALK fusion L15;A20 PHACTR1-ALK fusion PH7;A20 CMTR1-ALK fusion C2;A20 Table 3: Table describing oncogenic mutations in KRAS, BRAF, ALK and ROS1 These mutations may be routinely identified by methods selected from the group comprising: Chromogenic and Fluorescence In-Situ Hybridization (CISH and FISH); SNP-arrays; Methylation Arrays; DNA-sequencing; RNA level assays; and protein level assays.

The inventors have also surprisingly discovered, that in the embodiment wherein the cancer is NSCLC, determining whether the cancer has an epithelial lineage further helps to identify a patient who has NSCLC and will benefit from treatment with the agent which inhibits an RTK (e.g. EGFR), for example, from gefitinib treatment.

In an embodiment in which the cancer is NSCLC, the cancer is further characterised in that it comprises expression of one or more epithelial marker, including but not limited to: Cdh1 (E-cadherin) and Epithelial Cell Adhesion Molecule (EpCAM).

In an embodiment in which the cancer is NSCLC, the cancer is further characterised in that it comprises an absence or low level expression of one or more mesenchymal marker, including but not limited to: CDH2 and/or Vimentin.

By "low level expression" of one or more mesenchymal marker, we include that the cancer expresses one or more mesenchymal marker at a lower level than a control sample comprising cells which are known to be mesenchymal.

It will be appreciated that, in principle, epithelial cells should not express, or express very low level of mesenchymal markers such as CDH2 and/or Vimentin.

By "expression" we include the level, amount, concentration, or abundance of a marker.

The term "expression" may also refer to the rate of change of the amount, concentration or activity of a marker. Expression can be represented, for example, by the amount or synthesis rate of messenger RNA (mRNA) encoded by a gene (e.g. CDH1) the amount or synthesis rate of polypeptide corresponding to a given amino acid sequence encoded by a gene (e.g. CDH1), or the amount or synthesis rate of a biochemical form of a marker accumulated in a cell, including, for example, the amount of particular post-translational modifications of a marker such as a polypeptide, nucleic acid or small molecule. The term can be used to refer to an absolute amount of a marker in a sample or to a relative amount of a marker, including amount or concentration determined under steady-state or non-steady-state conditions. Expression may also refer to an assay signal that correlates with the amount, concentration, activity or rate of change of a marker. The expression of a marker can be determined relative to the level of a marker in a control sample.

Evaluation of marker expression can be done by any routine method such as by immunohistochemistry (IHC) with specific antibodies. Positive expression in cancer cells is determined by a pathologist by evaluation of staining intensity in cancer cells in the tissue section. Normally this evaluation results in a "score for a marker, typically from 04, where 4 is highest expression and 0-1 corresponds to absence/low expression.

It will be appreciated that in a clinical setting, for a targeted analysis using IHC only a few (1-2) markers per lineage would be evaluated using specific antibodies. For research and discovery purposes when omics type of data is available, signatures could be used instead (see the accompanying Example).

Preferably, the cancer is selected from the group comprising: lung cancer, breast cancer, 30 oesophagus cancer, bladder cancer, stomach cancer and head and neck cancer.

As described in the accompanying Example, apart from NSCLC, both CCLE and another similar large public domain resource, the Genomics of Drug Sensitivity in Cancer (GDSC), predicted cell lines from breast, esophagus, bladder/urinary tract and stomach cancer as sensitive, and in addition GDSC predicted sensitive cells from head and neck cancer.

Importantly, similarly to NSCLC all of these cancer types include significant subsets that are driven by EGFR mutations or ERBB2 amplification. This suggests that the signalling dependence in these cancer types is similar to the NSCLC findings presented herein, and that CDKN2A deletion would have a predictive value for ErbB-family targeting therapy response also in these cancer types.

Preferably, the cancer is non-small cell lung cancer (NSCLC) including adenocarcinoma, squamous cell carcinoma, adenosquamous carcinoma, large cell carcinoma and large cell neuroendocrine cancer.

Routine pathological analyses are performed by the skilled physician to determine the histological subtype of lung cancer. Guidelines are followed regionally and defined by trusted organisations such as ASCO, ESMO and WHO (see for example Travis WD et al. "The 2015 World Health Organization Classification of Lung Tumors" J Thorac Oncol. 2015 Sep;10(9):1 243-1260).

Resistance to TKIs, such as gefitinib, is an ongoing challenge and tumours that are sensitive to TKIs eventually progress despite continued therapy. In the present case, the inventors have observed upregulation of the transcriptional repressor BCL6 in response to treatment with gefitinib (Figure 6b). Further, the inventors have observed that cancers expressing EGFRwt had overexpression BCL2L1, coding for the antiapoptotic protein Bel-xL, before treatment with EGFR-TKIs (Figure 6c). This suggests that these cancers may be resistant to EGFR inhibition from the outset (i.e. the cancer has intrinsic resistance to monotherapy with an EGFR inhibitor). Interestingly, the inventors observed that tumours with inactive (deleted) CDKN2A expressed higher mRNA levels of BCL2L1 (Figure 9c). The inventors hypothesise that such baseline expression of BCL2L1 could blunt the effects of EGFR-TKIs even if there was an initial molecular response, indicating that combination therapy including inhibitors of Bcl-xL could improve the efficacy of EGFR-TKIs. The inventors additionally observed synergistic effects between the Bcl-xL inhibitors and an EGFR-TKI (Figure 8a).

The inventors now show combined targeting of EGFR and the anti-apoptotic protein Bel-xL produced synergistic effects and efficient killing at very low drug concentrations. Taken together, these data demonstrate that the combination of an RTK inhibitor and a Bcl-xL inhibitor provides an effective treatment of cancer inpatients, particularly in lung cancer patients.

Therefore, it will be appreciated that although the agents of the invention described above may be clinically effective in the absence of any other therapeutic agent it may be advantageous to administer these agents in conjunction with a further therapeutic agent (e.g. anti-cancer therapy).

Preferably, the step of treating the cancer further comprises administering one or more additional anti-cancer therapy to the patient.

Therefore, the patient receives a combination therapy comprising the agent and one or more additional anti-cancer therapy.

By "anti-cancer therapy" we include radiation therapy, chemotherapy, therapy comprising inhibitors of Bcl-xL and RTK inhibitors.

Examples of chemotherapy include but are not limited to vinorelbine (VNR), vincristine (VCR), paclitaxel (TAX), mitomycin C (MMC), irinotecan (CPT-11), 5-fluorouracil (5-FU), etoposide (VP-16), or cisplatin (CDDP).

Examples of agents (RTK inhibitors) can be found in Table 1.

Preferably, the additional anti-cancer therapy comprises an inhibitor of Bcl-xL. Examples of Bcl-xL inhibitors are described below.

Accordingly, in one aspect, the invention provides a combination therapy for the treatment of a cancer. In certain embodiments, the method or treatment comprises administering to the patient a combination of at least one RTK inhibitor and at least one anti-cancer therapy, such as an inhibitor of Bcl-xL. In an embodiment, the invention provides a combination therapy for the first-line treatment of a cancer.

By "first-line" treatment of a cancer, we include the initial therapy used after a diagnosis, which may be combined with surgery, chemotherapy and/or radiation therapy.

In one embodiment, the invention provides a combination for the treatment of a patient with a cancer in which the tumour cells are substantially non-responsive, resistant, or refractory to first-line therapy with chemotherapy, immunotherapy or other non-EGFR targeted therapies (i.e. "second-line" therapy). It will be appreciated that treatment with an additional anti-cancer therapy, such as an inhibitor of Bcl-xL could also be administered after the patient has received monotherapy with an RTK inhibitor and has stopped responding and/or relapsed (i.e. the anti-cancer therapy can be administered sequentially, following treatment with the agent (RTK inhibitor)).

Accordingly, the medical uses of the present invention also include treating a patient with a cancer in which the tumour cells are substantially non-responsive, resistant, or refractory to therapy with an RTK inhibitor. The treatment comprises the step of administering to the patient a combination of an effective amount of an agent which inhibits an RTK and an effective amount of a therapeutic composition comprising at least one inhibitor of Bcl-xL.

to By "substantially non-responsive" we include a tumour or a cancer that shows stable growth or increased growth after administration of a therapeutic agent. We also include a patient that shows stable disease or progressive disease after administration of a therapeutic agent. By "substantially non-responsive to an RTK inhibitor" we include a tumour or a cancer that shows stable growth or increased growth after administration of an RTK inhibitor. In some embodiments, an RTK inhibitor is administered to a patient in need of treatment, and "substantially non-responsive" to the RTK inhibitor includes: no reduction in the number of, or continued growth of, cancer cells; no reduction in the tumour size; an increase in tumour size; no inhibition of, or a continuation of, cancer cell infiltration into peripheral organs including, for example, the spread of cancer into soft tissue and bone; no inhibition of, or a continuation of, tumour metastasis; no inhibition of, or a continuation of, tumour growth; no or little relief of one or more symptoms associated with the specific cancer; no or little reduction in tumorigenicity, tumourgenic frequency, or tumourgenic capacity of a tumour; no or little reduction in the number or frequency of cancer stem cells in a tumour; or some combination of effects.

By "refractory" to therapy we include a disease and/or condition that is initially unresponsive, becomes unresponsive over time (e.g., within three months (i.e. disease progression may be observed on or within three months of treatment)), or recurs shortly after discontinuation of treatment. In some embodiments, a cancer that is "refractory" to therapy is one which does not respond to treatment.

By "resistant" to therapy we include a disease and/or condition that is unresponsive to therapy. In one embodiment, the cancer may be resistant at the beginning of treatment or it may become resistant during, treatment. If a cancer has become resistant during treatment, it has acquired resistance, for example, mediated by secondary resistance or compensatory mutations. In certain embodiments, a "refractory" cancer is also termed a "resistant" cancer. In an embodiment, the cancer is resistant from the outset, in other words, the cancer has intrinsic resistance to treatment with an RTK inhibitor (such as an EGFR inhibitor).

An "inhibitor" is as defined above. According to the present invention, an inhibitor of Boi-s xL (also referred to as a Bcl-xL inhibitor) is any compound that inhibits (for example antagonises, suppresses, reduces, prevents, decreases, blocks, and/or reverses) the expression and/or biological activity of Bcl-xL.

The biological activity or biological action of Bcl-xL refers to any function(s) exhibited or performed by a naturally occurring (wild type) form of the protein. Such activity and/or action is measured or observed in vivo (i.e. in the natural physiological environment of the protein) or in vitro (i.e. under laboratory conditions).

Biological activities of Bcl-xL are well known in the art and include, but are not limited to, inhibition of apoptosis and regulation of autophagy (Peter E. Czabotar, Guillaume Lessene, Andreas Strasser & Jerry NI. Adams Nature Reviews Molecular Cell Biology volume 15, pages 49-63 (2014); Chiara Gabellini, Daniela Trisciuogliol and Donatella Del Bufalo Carcinogenesis, 2017, Vol. 38, No. 6, 579).

Particular examples of the inhibitor of BcI-xL are described below.

In an embodiment, the inhibitor of BcI-xL may be one that inhibits the biological activity of Bcl-xL by at least 2, or at least 5, or at least 10, or at least 50 fold compared to the biological activity of Bcl-xL in the absence of an inhibitor. More preferably, the inhibitor of Bcl-xL inhibits Bcl-xL by at least 100, or at least 1,000, or at least 10,000 fold compared to the biological activity of Bcl-xL in the absence of an inhibitor.

In an embodiment, the inhibitor of Bcl-xL may be one that selectively inhibits BcI-xL. For example, the inhibitor of Bcl-xL may inhibit Bcl-xL to a greater extent than it inhibits Bcl-2.

Preferably, the inhibitor of Bcl-xL inhibits Bcl-xL, at least 5, or at least 10, or at least 50 times more than it inhibits BcI-2. More preferably, the BcI-xL inhibits Bcl-xL at least 100, or at least 1,000, or at least 10,000 times more than Bcl-2.

In a preferred embodiment, the Bcl-xL inhibitor is one that binds to Bcl-xL in order to inhibit the biological activity of BcI-xL. More preferably the Bcl-xL inhibitor is one that selectively binds to Bcl-xL. By a BcI-xL inhibitor that selectively binds to Bcl-xL we include the meaning that the Bcl-xL inhibitor binds BcI-xL with a greater affinity than for an irrelevant polypeptide such as human serum albumin. Preferably, the Bcl-xL inhibitor binds Bcl-xL with at least 2, or at least 5, or at least 10 or at least 50 times greater affinity than for the irrelevant polypeptide. More preferably, the Bcl-xL inhibitor binds Bcl-xL with at least 100, or at least 1,000, or at least 10,000 times greater affinity than for the irrelevant polypeptide.

Such binding may be determined by methods well known in the art, including but not limited to Biacore, Thermal protein profiling (TPP), Cellular thermal shift assay (CETSA) Nuclear magnetic resonance spectroscopy (NMR).

In an embodiment, the agent is one that binds to one or more Bc12 homology (BH) domains and/or phosphorylation sites of Bcl-xL. The amino acid sequence of the human Bcl-xL is known in the art and can be found under GenBank Accession No. Genbank (gene): NG 029002, or under Entrez GenelD Entrez Gene ID: 598.

Preferably, the additional anti-cancer therapy is a Bcl-xL inhibitor selected from the group 15 comprising: Navitoclax, BM-1197, ABT-737, sabutoclax, A-1155463, A-1331852, Isosorbide, Gossypol, 4'-fluoro-1,1'-biphenyl-4-carboxylic acid, APG-1252, AT-101, WEHI539 hydrochloride, TW-37, FL518, CRTB6.

Examples of Bcl-xL inhibitors can be found in Table 4.

Molecule Type Route of administration Dosing Target navitoctax, AST-263 small molecule oral oral 150mg, daily Bcl2, Bcl-xL, Bcl-W A-1155463 small molecule n/a n/a Bcl-xL A-1331852 small n/a n/a BcI-xL -molecule-gossypol small molecule oral oral once daily for 21 days, repeat course every 28 days Bcl-xL ABT-737 small molecule n/a oral Bc12, Bcl-xL BM-1197 small molecule n/a n/a BcI2, BcI-xL, Mc1-1 4'-FLUORO1,1'-BIPHENYL-4-CARBOXYLIC ACID small molecule n/a n/a BcI-xL Isosorbide small molecule oral oral 450mg/1m1 (oral, slow release) Bc12, Bcl-xL, Mc1-1 WEHI-539 hydrochloride small molecule n/a n/a Bcl-xL sabutoclax, BI- small molecule n/a intravenous infusion BcI-xL, Bcl- 97C1 2, Mc1-1 and Bfl-1 (apogossypol derivative) APG-1252 small molecule n/a intravenous infusion Bc12, BcI-xL AT-101 (R-(-) small molecule n/a oral Bcl2, BcI-xL, Mcl-1 enantiomer of Gossypol acetic acid) TW-37 small molecule n/a n/a BcI2, Bcl-xL, MGM Table 4: Examples of BcI-xL inhibitors.

In an embodiment, the additional anti-cancer therapy is a Bcl-xL inhibitor. For example, the additional anti-cancer therapy is a selective Bcl-xL inhibitor.

in an embodiment, the agent is one which inhibitsEGFR and the additional anti-cancer therapy is a BcI-xL inhibitor. For example, the EGFR inhibitor is gefitinib and the additional anti-cancer therapy is Navitoclax. Alternatively, the EGFR inhibitor is gefitinib and the additional anti-cancer therapy is A-1155463. Alternatively, the EGFR inhibitor is gefitinib and the additional anti-cancer therapy is A-1331852. Alternatively, the EGFR inhibitor is erlotinib and the additional anti-cancer therapy is Navitoclax, A-1155463, or A-1331852. Alternatively, the EGFR inhibitor is afatinib and the additional anti-cancer therapy is Navitoclax, A-1155463, or A-1331852. Alternatively, the EGFR inhibitor is lapatinib and the additional anti-cancer therapy is Navitoclax, A-1155463, or A-1331852 Preferably, the agent and the additional anti-cancer therapy are administered sequentially or concurrently.

It will be appreciated that the combination of an agent which inhibits an RTK (e.g. an EGFR inhibitor) and an additional anti-cancer therapy (e.g. Bcl-xL inhibitor) may be administered in any order or concurrently. In selected embodiments, the agent will be administered to patients that have previously undergone treatment with the additional anti-cancer therapy. In certain other embodiments, the agent and the additional anti-cancer therapy will be administered substantially simultaneously or concurrently. For example, a subject may be given the additional anti-cancer therapy while undergoing a course of treatment with the agent. In certain embodiments, the additional anti-cancer therapy will be administered within 1 year of the treatment with the agent. In certain alternative embodiments, the additional anti-cancer therapy will be administered within 10, 8, 6, 4, or 2 months of any treatment with the agent. In certain other embodiments, the additional anti-cancer therapy will be administered within 4, 3, 2, or 1 week of any treatment with the agent. In some embodiments, the additional anti-cancer therapy will be administered within 6, 5, 4, 3, 2, or 1 days of any treatment with the agent. It will further be appreciated that the agent and additional anti-cancer therapy may be administered to the subject within a matter of hours or minutes (i.e. substantially simultaneously or concurrently).

Preferred amounts of the agent to administer may be chosen by one of skill in the art, and include amounts known in the art to be efficacious for treating cancers. For example, suitable dosing for an EGFR inhibitor will be the dosing already established for that EGFR inhibitor, as known in the art. Examples of suitable methods to treat cancer with EGFR inhibitors and suitable amounts of EGFR inhibitors to use are known in the art, such as, for example, those described in Table 1.

A preferred amount of the agent or of the additional cancer therapy to administer or treat with includes a minimum of about 5 mg and a maximum of about 20,000 mg, and can include ranges between: about 20 mg and about 15,000 mg, about 40 mg and about 10,000 mg, about 80 mg and about 5000 mg, about 120 mg and about 2000 mg, about 180 mg and about 1500 mg, about 200 mg and about 1000 mg, about 250 mg and about 800 mg, about 300 mg and about 700 mg, about 400 mg and about 600 mg. Other preferred amounts include about 10 mg, about 30mg, about 40mg, about 50 mg, about 100 mg, about 150 mg, about 200 mg, about 250 mg, about 300 mg, about 350 mg, about 400 mg, about 450 mg, about 500 mg, about 550 mg, about 600 mg, about 650 mg, about 700 mg, about 750 mg, about 800 mg, about 850 mg, about 900 mg, about 950 mg, about 1000 mg about 1200 mg, about 1400 mg about 1600 mg, about 1800 m_gi about 2000 mg, about 2200 mg, about 2400 mg, about 2600 mg, about 2800 mg, about 3000 mg, about 3500 mg, about 4000 mg, about 4500 mg, about 5000 mg, about 5500 mg, about 6000 mg, about 6500 mg, about 7000 mg, about 8000 mg, about 10,000 mg, about 12,000 mg, and about 15,000 mg. The dosing will be over any time period, preferably monthly, more preferably weekly, and even more preferably daily.

In one embodiment, one may administer the agents described herein orally, although one can also administer them parenterally, i.e. by any non-oral means, such as by intradermal (ID), intramuscular (IM), subcutaneous (SC) or intravenous (IV) injection. In one embodiment, an EGFR inhibitor is gefitinib and is administered orally in a bolus of about 2,000 mg once per week. In another embodiment, the EGFR inhibitor is gefitinib and is administered daily at about 250 mg per day. In another embodiment, the inhibitor is erlotinib and is administered orally at about 100-150 mg per day. In another embodiment, the inhibitor is afatanib and is administered orally at about 30-40 mg per day (see Table 1).

In one embodiment, one may administer additional cancer therapies described herein orally, although one can also administer them nasally, or parenterally, i.e. by any non-oral means, such as by intradermal (ID), intramuscular (IM), subcutaneous (SC) or intravenous (IV) injection. In one embodiment, the additional cancer therapy is Navitoclax and is administered orally at 150mg per day. Further information regarding the dosages for Bel-lo xL inhibitors can be found in Table 4.

It will be appreciated that if an RTK inhibitor is administered in combination with a BcIXI inhibitor, a lower dose of either of the drugs may be as efficacious due to the synergistic effects.

It will be appreciated that the agent could be delivered to a patient using a virus or virus-like particle carrying the agent. If the agent (RTK inhibitor) is based on RNA interference (e.g., an siRNA), the siRNAs may be chemically synthesized, produced using in vitro transcription, etc. Since siRNA can discriminate between nucleotide sequences that differ by only a single nucleotide, it is possible to design siRNAs that uniquely target a wild type form of the RTK gene (e.g. EGFR).

The delivery of siRNA to tumours can potentially be achieved via any of several gene delivery "vehicles" that are currently available. These include viral vectors, for example, adenovirus, adeno-associated virus, lentivirus, herpes simplex virus, vaccinia virus, and retrovirus, as well as chemical-mediated gene delivery systems (such as liposomes, nanoparticles), or mechanical DNA delivery systems (gene guns, electroporation). The oligonucleotides to be expressed for such siRNA-mediated inhibition of gene expression would be between 18 and 28 nucleotides in length.

Periods of time in which to administer any Bcl-xL inhibitors and/or RTK inhibitors are either known in the art and/or may be determined by one of skill in the art, and include for about a day, for about 2 days, for about 3 days, for about 4 days, for about 5 days, for about 6 days, for about a week, for about a week and a half, for about 2 weeks, for about 2 and a half weeks, for about 3 weeks, for about three and a half weeks, for about 4 weeks, for about 5 weeks, for about 6 weeks, for about 8 weeks, for about 10 weeks, for about 15 weeks, for about 20 weeks, for about 25 weeks, for about 30 weeks, for about 40 weeks, and for about 52 weeks. The Bcl-xL inhibitors and/or RTK inhibitors may be optionally administered over successive periods of time with one or more rest periods (i.e. no administration of Bcl-xL inhibitors and/or RTK inhibitors). Rest periods again are either known in the art and/or may be determined by one of skill in the art, and include for about a day, for about 2 days, for about 3 days, for about 4 days, for about 5 days, for about 6 days, for about a week, for about a week and a half, for about 2 weeks, for about 2 and a half weeks, for about 3 weeks, for about three and a half weeks, for about 4 weeks, for about 5 weeks, for about 6 weeks, for about 8 weeks, for about 10 weeks, for about 15 weeks, for about 20 weeks, for about 25 weeks, for about 30 weeks, for about 40 weeks, and for about 52 weeks.

In another aspect, the invention provides a method of predicting response to treatment comprising an agent which inhibits a Receptor Tyrosine Kinase (RTK) in a patient with cancer, wherein the method comprises the steps of determining if the cancer (i) has wild type RTK activity; and (ii) comprises reduced and/or absent CDKN2A activity, and predicting the response to treatment comprising the agent on the basis of those steps.

In an embodiment, if it has been predicted that the patient will respond to treatment, the method further comprises therapeutic administration of the agent to the patient.

By "predicting response to treatment", we include the determination of the likelihood that the patient will respond either positively or negatively to a given therapy. By the term "predicting response to treatment ", we also include an assessment of any parameter that can be useful in determining the response of a patient.

The response (positive or negative) can be assessed using any endpoint indicating a benefit to the patient, including, without limitation, inhibition, to some extent, of tumour growth, including slowing down and complete growth arrest; reduction in the number of tumour cells; reduction in tumour size or volume; inhibition (i.e. reduction, slowing down or ablation) of tumour cell infiltration into adjacent peripheral organs and/or tissues; inhibition of metastasis; enhancement of anti-tumour immune response, possibly resulting in regression or rejection of the tumour; relief, to some extent, of one or more symptoms associated with the tumour; increase in the length of survival following treatment; and/or decreased mortality at a given point of time following treatment.

The response in individual patients may be characterised using terms understood in the art, for example, complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD) according to the Response Evaluation Criteria for Solid Tumours (RECIST).

In another aspect, the invention provides a method of identifying a patient with cancer in need of treatment comprising an agent which inhibits a Receptor Tyrosine Kinase (RTK), wherein the method comprises the steps of determining if the cancer (i) has wild type RTK activity; and (ii) comprises reduced and/or absent CDKN2A activity, and identifying the patient as one in need of treatment comprising the agent, on the basis of those steps.

In an embodiment, if the method identifies a patient with cancer in need of treatment comprising therapeutic administration of the agent, the method further comprises therapeutic administration of the agent to the patient.

In an embodiment, if the method predicts that the patient will not respond to therapeutic administration of the agent, the method further comprises therapeutic administration of the agent, and an additional anti-cancer therapy.

Preferably, the additional anti-cancer therapy is as described above.

As can be seen in the accompanying Examples, the inventors have observed that cancers expressing EGFRwt had overexpression BCL2L1, coding for the antiapoptotic protein BelxL, before treatment with EGFR-TKIs (Figure 6c). This suggests that these cancers may be resistant to EGFR inhibition from the outset (i.e. the cancer has intrinsic resistance to monotherapy with an EGFR inhibitor). Interestingly, the inventors observed that tumours with inactive (deleted) CDKN2A expressed higher mRNA levels of BCL2L1 (Figure 9c). The inventors hypothesise that such baseline expression of BCL2L1 could blunt the effects of EGFR-TKIs even if there was an initial molecular response, indicating that combination therapy including inhibitors of Bcl-xL could improve the efficacy of EGFR-TKIs. The inventors additionally observed synergistic effects between the Bcl-xL inhibitors and an EGFR-TKI (Figure 8a).

Accordingly, BCL2L1 and/or BcI-xL expression and/or activity may be used to predict resistance to treatment with RTK inhibitors, such as EGFR inhibitors.

In an embodiment, once a patient has been identified who is in need of treatment comprising an agent which inhibits a Receptor Tyrosine Kinase (RTK), the method further comprises administering to the patient said agent. The agent is as described above.

Preferably, the methods further comprise the step of (iii) determining if the cancer is dependent on the activity of the wild type RTK for its proliferation and/or survival.

Preferably, the methods comprise the step, performed before step (i) of obtaining or receiving or providing a test sample from a patient.

It will be appreciated that the test sample and the control sample may be comprised within a single tissue sample. For example, if the sample is a biopsy, the test sample will comprise one or more cancer cell (i.e. the diseased tissue) and the control sample may be from surrounding healthy tissue.

Suitable methods of obtaining a test sample are known to a person skilled in the art.

Alternatively, a test sample may be provided in which case no medical intervention is necessary.

Preferably the sample is a cell, tissue or fluid sample (or derivative thereof) comprising or consisting of blood (fractionated or unfractionated), plasma, plasma cells, serum, tissue cells or equally preferred, protein or nucleic acid derived from a cell or tissue sample. A test sample can include any bodily fluid or tissue from a patient that may contain tumour cells or proteins of tumour cells. The term "test sample" or "patient sample" can be used generally to refer to a sample of any type which contains cells or products that have been secreted from cells to be evaluated by the present method, including but not limited to, a sample of isolated cells, a tissue sample and/or a bodily fluid sample. Preferably, the sample is a tissue sample.

According to the present invention, a sample of isolated cells comprises cells in suspension which have been collected from an organ, tissue or fluid by any suitable method which results in the collection of a suitable number of cells for evaluation by the methods of the present invention. The cells in the cell sample are not necessarily of the same type, although purification methods can be used to enrich for the type of cells that are preferably evaluated. Cells can be obtained, for example, by scraping of a tissue, processing of a tissue sample to release individual cells, or isolation from a bodily fluid.

A tissue sample, although similar to a sample of isolated cells, is defined herein as a section of an organ or tissue of the body which typically includes several cell types and/or extracellular matrix which holds the cells together. It will be appreciated that the term "tissue sample" may be used, in some instances, interchangeably with a "cell sample", although it is preferably used to designate a more complex structure than a cell sample.

to A tissue sample can be obtained by a biopsy, for example, including by cutting, slicing, or a punch.

A bodily fluid sample, like the tissue sample, contains the cells to be evaluated, and is a fluid obtained by any method suitable for the particular bodily fluid to be sampled.

Bodily fluids suitable for sampling include, but are not limited to, blood, mucous, seminal fluid, saliva, sputum, bronchial lavage, breast milk, bile and urine.

In general, the sample type (i.e. cell, tissue or bodily fluid) is selected based on the accessibility and structure of the organ or tissue to be evaluated for tumour cell growth and/or on what type of cancer is to be evaluated. For example, if the organ/tissue to be evaluated is the lung, the sample can be a sample of cells from a biopsy (i.e. a cell sample) or a lung tissue sample from a biopsy (a tissue sample). The present invention is particularly useful for evaluating patients with lung cancer and particularly, non-small cell lung carcinoma, and in this case, a typical sample is a section of a lung tumour from the patient.

The sample may contain nucleic acids such as DNA and/or RNA and peptides such as polypeptides.

Accordingly, the test sample comprises one or more cancer cell. Preferably, the one or more cancer cell is a lung cancer cell a breast cancer cell, an oesophagus cancer cell, a bladder cancer cell, a stomach cancer cell, and a head and neck cancer cell.

It will be appreciated that the one or more cancer cell may be termed one or more tumour cell.

Preferably, the one or more cancer cell is a non-small cell lung cancer (NSCLC) cell.

In an embodiment, the methods further comprise evaluating a control sample. In an embodiment, the control sample is obtained, received or provided. It will be appreciated that in a clinical setting a control is not necessarily available, but scoring is done by evaluating, for example, a tissue slice (in situ). Controls within a sample may be surrounding tissue, or in the case of a qRT-PCR (RNA), control genes, such as housekeeping genes may be used.

Examples of control samples include those described above and may be obtained from non-CDKN2A deleted cell lines, non-mutated cells of the same lineage or tissue as the test sample which may be from the same individual, or cells or tissue from a healthy individual of the same lineage or tissue as the test sample. It will be appreciated that the test sample and the control sample may be comprised within a single tissue sample. For example, if the sample is a biopsy, the test sample will comprise one or more cancer cell (i.e. the diseased tissue) and the control sample may be from surrounding healthy tissue.

Preferably test and control samples are derived from the same species as the patient. Preferably test and control samples are matched for age, gender and/or lifestyle relative to the patient.

In an embodiment, determining if the cancer has wild type RTK activity comprises the step of determining the activity, level, and/or mutational status of the RTK.

"Activity of the RTK" is as defined above. As discussed above, biological activities of an RTK, such as EGFR are well known in the art and include, but are not limited to, binding to ligand (e.g. EGF), receptor homo-or heterodimerisation, tyrosine kinase activity, and/or downstream activities related to cellular homeostasis and development.

By "level" of the RTK we include the amount, concentration, and/or abundance of RTK.

The term "level" of the RTK may also refer to the rate of change of the amount, concentration and/or activity of an RTK. A level can be represented, for example, by the amount and/or synthesis rate of messenger RNA (mRNA) encoded by a gene, the amount and/or synthesis rate of polypeptide corresponding to a given amino acid sequence encoded by a gene, and/or the amount and/or synthesis rate of a biochemical form of an RTK accumulated in a cell, including, for example, the amount of particular modifications of an RTK such as a polypeptide and/or nucleic acid after it has been synthesised. The term can be used to refer to an absolute amount of an RTK in a sample and/or to a relative amount of the RTK, including amount or concentration determined under steady-state or non-steady-state conditions. Level may also refer to an assay signal that correlates with the amount, concentration, activity and/or rate of change of an RTK (e.g. phosphorylation.

The level of phosphorylation of an RTK could also be measured as an indication of RTK activation. The level of an RTK can be determined relative to the level of RTK in a control sample.

Analysis of mutational status (e.g. through sequencing) can determine if the RTK is wild type and therefore has wild type activity.

In an embodiment, wherein the RTK is EGFR, determining the activity, level, and/or mutational status of EGFR comprises determining whether the EGFR comprises an activating mutation selected from the group comprising: Exon 18 substitutions including: G719C, G719S, G719A, V689M, N700D, E709K/Q and/or S720P; - Exon 19 deletions including: AE746-A750, AE746-7751, AE746-A750 (ins RP), AE746-T751 (ins A/I), AE746-7751 (ins VA), AE746-S752 (ins NV), AL747-E749 (A750P), AL747-A750 (ins P), AL747-T751, AL747-T751 (ins P/S), AL747-S752, AL747-752 (E746V), AL747-752 (P7535), AL747-5752 (ins Q), AL747-P753 and/or AL747-P753 (ins S); - Exon 20 substitutions including: V765A, S768I, T783A and/or AS752-1759; and/or Exon 21 substitutions including: L858R, N826S, A839T, K846R, L861Q and/or G863D In an embodiment, wherein the RTK is ERBB2, determining the activity, level, and/or mutational status of ERBB2 comprises determining whether the ERBB2 comprises an activating mutation selected from the group comprising: S310F/Y, S429R, R678Q, L755SINP, 755-759 deletion, D769H/Y, Y772 A775dup, V777L/M, G778_P780dupN777UV777M, V842I and/or L869R.

In an embodiment, wherein the RTK is ERBB3, determining the activity, level, and/or mutational status of ERBB3 comprises determining whether the ERBB3 comprises an activating mutation selected from the group comprising: V104L and/or V104M.

In an embodiment, wherein the RTK is ERBB4, determining the activity, level, and/or mutational status of ERBB4 comprises determining whether the ERBB4 comprises an activating mutation selected from the group comprising: R106C and/or R106H.

In an embodiment, the activity, level, and/or mutational status of the RTK is determined using a method selected from the group comprising: Chromogenic and Fluorescence In-Situ Hybridization (CISH and FISH); SNP-arrays; Methylation Arrays; DNA-sequencing; RNA level assays; and protein level assays.

In an embodiment, the methods further comprise the step of determining if the cancer comprises reduced and/or absent CDKN2B activity.

In an embodiment, the step of determining if the cancer comprises reduced and/or absent CDKN2A and/or CDKN2B activity comprises determining if CDKN2A and/or CDKN2B activity is reduced and/or absent due to deletion, mutation and/or methylation of CDKN2A and/or CDKN2B and can be carried out using any of the methods described herein.

In an embodiment, the step of determining if CDKN2A and/or CDKN2B activity is reduced and/or absent due to deletion of CDKN2A and/or CDKN2B comprises (a) providing or obtaining a sample comprising genomic DNA from said patient; and b) analysing said genomic DNA to determine copy number alterations of CDKN2A in chromosome 9 of the sample.

In an embodiment, determining if CDKN2A and/or CDKN2B activity is reduced and/or absent due to deletion, mutation and/or methylation of CDKN2A and/or CDKN2B is measured using a method selected from the group comprising: Methylation assays, methylation arrays, DNA-sequencing (including SNP-arrays, whole genome sequencing, whole exome sequencing, long-read sequencing and short-read sequencing, targeted panels, digital PCR), and RNA level assays such as chromogenic and fluorescence in-situ hybridization, RNA sequencing, RNA microarrays, quantitative RT-PCR, digital RT-PCR, Southern blot, protein level assays including HPLC, immunoasssays (immunohistochemistry, protein gel electrophoresis, ELISA, proximity ligation assay, proximity extension assay), labelled on unlabelled mass spectrometry, and combinations of methods such as RNA/protein such as multiplex PCR/liquid chromatography assay.

In an embodiment, the step of determining if the cancer is dependent on the activity of the wild type RTK for its proliferation and/or survival comprises determining if the cancer comprises KRAS, BRAF, ROS1 and ALK with wild type activity.

"Wild type activity" is as defined above and includes that the cancer comprises KRAS, BRAF, ROS1 and ALK which have a biological activity or biological action substantially the same as the biological activity or biological action exhibited or performed by a naturally occurring (wild type) form of the protein as measured or observed in vivo (i.e. in the natural physiological environment of the protein) or in vitro (i.e. under laboratory conditions).

As discussed above, the skilled person will appreciate that determining if the cancer comprises KRAS, BRAF, ROS1 and ALK with wild type activity, may comprise determining if the cancer comprises an activating KRAS mutation, BRAF mutation, ROS1 mutation and/or ALK mutation.

The skilled person will appreciate that determining if the cancer comprises an activating KRAS mutation, BRAF mutation, ROS1 mutation and/or ALK mutation can be done using any appropriate method known in that art, including but not limited to: Chromogenic and Fluorescence In-Situ Hybridization (CISH and FISH); SNP-arrays; Methylation Arrays; DNA-sequencing; RNA level assays; and protein level assays. Detail of these assays was provided above.

In an embodiment, the method of predicting response to treatment comprising an agent which inhibits an RTK in a patient with cancer, can include: a) measuring in a test sample containing one or more cancer cell, at least one of (i)- (iii), and at least one of (iv)-(vi): (i) the activity of an RTK; (ii) the level of an RTK; (Hi) the mutational status of the RTK; (iv) mutational status of CDKN2A and/or CDKN2B; (v) methylation of CDKN2A and/or CDKN2B; and (vi) deletion of CDKN2A and/or CDKN2B; b) measuring in a control sample at least one of (i)-(iii), and at least one of (iv)-(vi); wherein the measurement of at least one of (i)-(iii) in (a) and (b) allows the skilled person to determine whether the cancer comprises RTK with wild type activity; and wherein the measurement of at least one of (iv)-(vi) in (a) and (b) allows the skilled person to determine whether the cancer comprises reduced and/or absent CDKN2A and/or CDKN2B activity; and c) predicting that the patient will respond to therapeutic administration of the agent (e.g. EGFR inhibitor), if it is determined that the cancer comprises RTK with wild type activity and reduced and/or absent CDKN2A and/or CDKN2B activity.

In an embodiment of the method of predicting response to treatment comprising an agent which inhibits an RTK in a patient with cancer, determining if the cancer: (i) has wild type RTK activity; (H) comprises reduced and/or absent CDKN2A and/or CDKN2B activity; and (Hi) is dependent on the activity of the wild type RTK for its proliferation and/or survival, is predictive that the patient will respond to therapeutic administration of the agent.

In an embodiment, the method of identifying a patient with cancer in need of treatment comprising an agent which inhibits an RTK, can include: a) measuring in a test sample containing one or more cancer cell, at least one of (i)(iii), and at least one of (iv)-(vi): (i) the activity of an RTK; (H) the level of an RTK; (Hi) the mutational status of the RTK; (iv) mutational status of CDKN2A and/or CDKN2B; (v) methylation of CDKN2A and/or CDKN2B; and (vi) deletion of CDKN2A and/or CDKN2B; b) measuring in a control sample at least one of (i)-(iii), and at least one of (iv)-(vi); wherein.The measurement _of at least one of (1)4iii) in_(a)NW_(b) allows the skilled person to determine whether the cancer comprises RTK with wild type activity; and wherein the measurement of at least one of (iv)-(vi) in (a) and (b) allows the skilled person to determine whether the cancer comprises reduced and/or absent CDKN2A and/or CDKN2B activity; and c) identifying a patient with cancer as one in need of treatment comprising an agent (e.g. EGFR inhibitor), if it is determined that the cancer comprises RTK with wild type activity and reduced and/or absent CDKN2A and/or CDKN2B activity.

In an embodiment of the method of identifying a patient with cancer in need of treatment comprising an agent which inhibits an RTK, determining if the cancer: (i) has wild type RTK activity; (ii) comprises reduced and/or absent CDKN2A and/or CDKN2B activity; and (iii) is dependent on the activity of the wild type RTK for its proliferation and/or survival, allows the identification of a patient with cancer in need of treatment comprising an agent which inhibits an RTK.

Preferably, the "test sample" and "control sample" are as defined above.

In the accompanying Examples, using cell line model systems, the inventors discovered that NSCLC with an epithelial lineage further predicts response to EGFR-TKIs. This analysis indicated that epithelial lineage (assayed by mRNA expression of the epithelial to marker E-cadherin (CDH1)) was associated with sensitivity to EGFR-TKIs, while mesenchymal lineage (mRNA expression of the mesenchymal marker vimentin (VIM)) was associated with resistance) (Figure 3d).

In an embodiment in which the cancer is NSCLC. the cancer is further characterised in that it comprises expression of one or more epithelial marker, including but not limited to: Cdh1 (E-cadherin) and Epithelial Cell Adhesion Molecule (EpCAM).

In an embodiment in which the cancer is NSCLC, the cancer is further characterised in that it comprises an absence or low-level expression of one or more mesenchymal marker, including but not limited to: CDH2 and/or Vimentin.

In an embodiment in which the cancer is NSCLC, the method comprises the use of one or more reagent for detecting expression, of Cdh1 (E-cadherin), Epithelial Cell Adhesion Molecule (EpCAM), CDH2 and/or Vimentin.

In an embodiment in which the cancer is NSCLC, the one or more reagent is capable of binding to Cdh1 (E-cadherin), Epithelial Cell Adhesion Molecule (EpCAM), CDH2 and/or Vimentin.

In an embodiment, the one or more reagent is labelled with a detectable moiety.

In an embodiment, the detectable moiety is selected from the group comprising of a fluorescent moiety, a luminescent moiety, a chemiluminescent moiety, a radioactive moiety, an enzymatic moiety, a ligand moiety or a ligand binding moiety.

Routine methods for evaluating the expression of a marker are known in the art and include immunohistochemical staining of formalin-fixed, paraffin embedded tissue sections.

Images are then scored, for example from 1-4, for the abundance of the stain in the section. Other methods include in situ hybridization (RNA) for specific epithelial markers, or methods for evaluating RNA/protein levels from liquid or tissue biopsies.

In an embodiment, the patient is selected from the group comprising: a primate (for example, a human; a monkey; an ape); a rodent (for example, a mouse, a rat, a hamster, a guinea pig, a gerbil, a rabbit); a canine (for example, a dog); a feline (for example, a cat); an equine (for example, a horse); a bovine (for example, a cow); and/or a porcine (for example, a pig).

Preferably, the cancer is as described above.

In an embodiment, the cancer is selected from the group comprising: lung cancer, breast cancer, oesophagus cancer, bladder cancer, stomach cancer and head and neck cancer.

In an embodiment, the cancer is non-small cell lung cancer (NSCLC) including adenocarcinoma, squamous cell carcinoma, adenosquamous carcinoma, large cell carcinoma and large cell neuroendocrine cancer.

Preferably, the RTK is as described above. In an embodiment, the RTK is an RTK of the ErbB family.

Preferably, the RTK is selected from the group comprising: EGFR, ErbB-2, ErbB-3 and ErbB-4.

Preferably the agent is as described above.

In another aspect, the invention provides, use of CDKN2A and/or CDKN2B deletion, mutation and/or methylation status for predicting the responsiveness of a patient with cancer to treatment comprising an agent which inhibits a Receptor Tyrosine Kinase (RTK); wherein the cancer is characterised in that it comprises wild type RTK activity; and is dependent on the activity of the wild type RTK for its proliferation and/or survival.

In an embodiment, the use further comprises therapeutic administration of the agent to the patient.

The determination of CDKN2A and/or CDKN2B deletion, mutation and/or methylation status is as described above.

The characterisation of the cancer in that it comprises wild type RTK activity; and is dependent on the activity of the wild type RTK for its proliferation and/or survival is as described above.

In an embodiment, the use further comprises determining CDKN2A and/or CDKN2B deletion, mutation and/or methylation status in a test sample. This use may include comparison with a control sample. Preferably, the "test sample" and "control sample" are as defined above.

In another aspect, the invention provides, use of CDKN2A and/or CDKN2B deletion, mutation and/or methylation status for selecting a patient with cancer for treatment comprising an agent which inhibits a Receptor Tyrosine Kinase (RTK); wherein the cancer is characterised in that it comprises wild type RTK activity; and is dependent on the activity of the wild type RTK for its proliferation and/or survival.

In an embodiment, the use further comprises therapeutic administration of the agent to the patient.

The determination of CDKN2A and/or CDKN2B deletion, mutation and/or methylation status is as described above.

The characterisation of the cancer in that it comprises wild type RTK activity; and is dependent on the activity of the wild type RTK for its proliferation and/or survival is as described above.

In an embodiment, the use further comprises determining CDKN2A and/or CDKN2B deletion, mutation and/or methylation status in a test sample. This use may include comparison with a control sample. Preferably, the "test sample" and "control sample" are as defined above.

In another aspect, the invention provides, use of one or more reagents that determine if a patient has a cancer which: (i) comprises a wild type RTK activity; (ii) comprises reduced and/or absent CDKN2A and/or CDKN2B activity; and (iii) is dependent on the activity of the wild type RTK for its proliferation and/or survival, wherein following the determination of (i)-(iii) the patient having cancer is treated with an agent which inhibits a Receptor Tyrosine Kinase (RTK).

In an embodiment, the agent is as defined above.

In an embodiment, the cancer is as defined above.

In an embodiment, the RTK is as defined above.

In an embodiment, the determination of (i)-(iii) is as defined above.

Preferably, the use comprises reagents which determine whether a given RTK has wild type activity.

Preferably, the use comprises reagents which determine reduced and/or absent CDKN2A and/or CDKN2B activity.

In another aspect, the invention provides a kit comprising: means for detecting: (I) the activity, level, and/or mutational status of an RTK; (II) CDKN2A and/or CDKN2B deletion, mutation and/or methylation; (III) KRAS mutational status; BRAF mutational status; ROS1 mutational status; and ALK mutational status.

In an embodiment, the kit comprises appropriate controls. For example, control samples, 25 _Stith as _those_ described save, which would be used for comparison to test samples, control probes such as for housekeeping genes (which may be of use in techniques such as RT-PCR), and/or control antibodies such as an isotype control.

In an embodiment, determining the activity of an RTK comprises the step of determining the activity, level, and/or mutational status of the RTK. Methods for this determination are discussed above.

In one embodiment, a means for detecting the activity of an RTK, or CDKN2A and/or CDKN2B deletion, mutation and/or methylation, can generally be any type of reagent that can be used in any of the methods described herein such as Chromogenic and Fluorescence In-Situ Hybridization (CISH and FISH); SNP-arrays; Methylation Arrays; DNA-sequencing; RNA level assays; and protein level assays. Such means for detecting include, but are not limited to: antibodies reactive to RTK peptides, DNA probes and RNA probes.

In an embodiment, the kit comprises instructions for carrying out the method.

In another aspect, the invention provides, a combination of at least one Receptor Tyrosine Kinase (RTK) inhibitor and at least one inhibitor of Bcl-xL.

In another aspect, the invention provides, a combination of a Receptor Tyrosine Kinase (RTK) inhibitor and an inhibitor of Bcl-xL for treating cancer in a patient wherein the cancer is characterised in that (i) it has wild type RTK activity and (ii) it comprises reduced and/or absent CDKN2A activity.

In another aspect, the invention provides an agent, a use, a method, a kit, a combination substantially as described herein with reference to the accompanying claims, description, examples and figures.

All of the documents referred to herein are incorporated herein, in their entirety, by reference.

The listing or discussion of an apparently prior published document in this specification should not necessarily be taken as an acknowledgement that the document is part of the state of the art or is common general knowledge.

The invention will now be described by reference to the following Figures and Examples.

Preferred, non-limiting examples which embody certain aspects of the invention will now be described, with reference to the following figures: Figure 1. Selection of NSCLC cell lines for molecular profiling. a. Hierarchical clustering based on mRNA profiling of the 185 lung cancer cell lines available in COLE. b. Vulcano plot of the output from a differential expression analysis based on mRNA profiling between the two NSCLC clusters. c. Overview of the erlotinib sensitivity for 37 NSCLC cell lines from the epithelial cluster. Indicated are also the 15 cell lines included in the present study.

Figure 2. Overview of molecular profiling in NSCLC cell line panel. a. Number of identified transcripts and proteins (gene centric) are in line with the setup goals, allowing in-depth analysis across all cell lines. b. In total 11291 and 13511 genes were identified at the protein and mRNA level respectively, with an overlap of 10711 genes. c. Scatterplot showing the relationship between cellular abundance of proteins (estimated by number of identified PSMs) and mRNAs (estimated by FPKM values).

Figure 3. Molecular response profiling in NSCLC cell line panel and candidate EGFR-TKI predictive markers. a. Example of output from molecular response profiling at mRNA and protein level for the gefitinib sensitive cell line HCC-827 and the gefitinib resistant cell line NCI-I-11975. b. Core regulation in response to gefitinib at mRNA and protein level was used for clustering of the cell lines to identify EGFR wt cell lines with EGFR mutant-like molecular response. c. Loss of CDKN2A and CDKN2B was associated with gefitinib sensitivity in EGFRwt NSCLC cells. d. Epithelial lineage (high expression of CDH1 and low expression of VIM) was associated with sensitivity to EGFR-TKIs in EGFRwt NSCLC cells with CDKN2A deletion (CCLE public domain data). e. Gefitinib resistance was associated with higher expression of the tyrosine kinase receptors AXL and MET.

Figure 4. Evaluation of NSCLC subgroups in public domain cell line resources a. Distribution of epithelial (CDH1) and mesenchymal (VIM) marker mRNA expression in CCLE and cutoffs used for determination of epithelial cells. b. Distribution of epithelial (CDH1) and mesenchymal (VIM) marker mRNA expression in GDSC and cutoffs used for determination of epithelial cells. c. CDKN2A mRNA expression plotted against CDKN2A copy number information for CCLE cell lines, and cutoff used for determination of CDKN2A deleted cells. d. CDKN2A mRNA expression plotted against CDKN2B mRNA expression for GDSC cell lines annotated as either CDKN2A deleted (red), normal (green) and amplified (gray). e. Top barplot shows frequency of EGFR mutated, KRAS mutated, predicted resistant wild-type and predicted sensitive wild-type cell lines for different cancer types. Indicated is also the percentage of predicted sensitive cell lines when available. Bottom barplot shows number of cell lines predicted to be sensitive for different cancer types. f. Same as in e. but for GDSC cell lines.

Figure 5. Evaluation of predictive markers in CCLE and GDSC a. Boxplot showing erlotinib response in different subsets of NSCLC cell lines in COLE as measured by activity area. b. Boxplot showing gefitinib response in different subsets of NSCLC cell lines in GDSC as measured by IC50 value. c. Density plot showing of erlotinib response distribution in different subsets of NSCLC cell lines in COLE as measured by activity area. d. Density plot showing of gefitinib response distribution in different subsets of NSCLC cell lines in GDSC as measured by IC50 value. e. Vulcano plot showing differences in response to 24 compounds in the CCLE resource between EGFRwt/KRASwt NSCLC predicted as sensitive to EGFR-TKIs. f. Vulcano plot showing differences in response to 265 compounds in the GDSC resource between EGFRwt/KRASwt NSCLC predicted as sensitive to EGFR-TKIs.

Figure 6. Candidate EGFR-TKI combination therapy targets. a. Heatmap showing regulation of tyrosine kinase receptors in response to gefitinib (24h, 2.5 uM) in cell lines identified as molecular responders. b. General upregulation of genes previously associated with resistance to targeted therapy (BCL6, ERBB2, ERBB3, FGFR2), already 24h after gefitinib treatment. c. Two EGFRwt NSCLC cell lines identified as molecular responders show overexpression of BCL2L1 coding for the antiapoptotic protein Bcl-xL.

Figure 7. EGFR-TKI combination therapy screen in lung cancer cell lines. a. EGFR-TKI (gefitinib) dose-response curves for 12 lung cancer cell lines in the cell line panel.

Highlighted in green and red are the IC20 dose ranges for molecular responding and non- responding cell lines respectively. b. Overview of the experimental setup for the EGFRTKI combination therapy screen. c. Vulcano plot showing the output from a differential sensitivity analysis between molecular responders and non-responders for the different combination therapies. d. Drug sensitivity scores (DSS) scores for four different Bc1-xL/Bc1- 2 inhibitors in combination with 0.5 uM gefitinib for the 12 different cell lines.

Figure 8. Generalizability and Synergy. a. 2-dimensional drug screening for evaluation of synergistic effects between the EGFR inhibitor gefitinib and the Bcl-xL inhibitor A11554638, the Bcl-xL inhibitor A13318525, the Bc1-xUBc1-2 inhibitor navitoclax or the Bcl-2 inhibitor venetoclax in NCI-H2935 NSCLC cells. Numbers in heatmap indicate viability where red corresponds to high viability and blue corresponds to cell death. b. 2-dimensional drug screening for evaluation of synergistic effects between the EGFR/ERBB2 inhibitor lapatinib and the Bcl-xL inhibitor A11554638, the BcI-xL inhibitor A13318525, the Bcl-xL/Bcl-2 inhibitor navitoclax or the Bcl-2 inhibitor venetoclax in NCI-H2170 NSCLC cells. Numbers in heatmap indicate % viability where red corresponds to high viability and blue corresponds to cell death.

Figure 9. Evaluation of CDKN2A status in lung adenocarcinoma samples. a. Evaluation of CDKN2A copy number on the CDKN2A mRNA level. b. Frequency of mutations in 35 CDKN2A normal adenocarcinoma and CDKN2A deleted adenocarcinoma. c. BCL2L1 expression in CDKN2A deleted adenocarcinoma and CDKN2A normal adenocarcinoma.

d. Hierarchical clustering of CDKN2A normal and CDKN2A deleted adenocarcinoma samples based on the expression of 119 epithelial-mesenchymal signature genes.

Figure 10. Model for EGFR signaling dependence in CDKN2A deleted lung cancer. a. In normal cells without oncogenic mutations in the EGFR signaling pathway and with the cell cycle checkpoint control in place (normal CDKN2A/B status) both proliferation/survival signalling and apoptosis/death signalling are controlled by positive and negative regulation resulting in a balanced system. b. In EGFR mutated NSCLC proliferation/survival signalling is constitutively activated resulting in oncogenic signalling. Oncogenic signalling is also activating tumor suppressors such as p53, and if EGFR signalling is inhibited by EGFR-TKIs (e.g. gefitinib) apoptosis is induced resulting in cancer cell death. c. In CDKN2A/B deleted NSCLC the cell cycle checkpoint is absent and p53 signalling is impaired through mdm2 dependent inhibition (degradation) of p53. The net effect of this is uncontrolled signalling from the wt EGFR and reduced pro-apoptotic signalling. As suggested here inhibition EGFR signalling together with inhibition of anti-apoptotic Bcl-xL signalling can revert the imbalance and cause cancer cell death.

Example 1 -CDKN2A status predicts the response to EGFR targeting therapy in EGFRwt cancer Currently there are no biomarkers that can predict response to epidermal growth factor receptor (EGFR) targeting therapy in EGFR wild-type non-small cell lung cancer (NSCLC), even though previous studies indicate that a subset of these patients would respond to therapy. Here we have used multi-level molecular response profiling after EGFR inhibition in NSCLC cells to identify EGFR and KRAS wild type cells with a molecular response to treatment. This analysis revealed that CDKN2A deletion in NSCLC cells is associated with increased sensitivity to EGFR inhibitors. Further evaluation of drug sensitivity in EGFR/KRAS wild type CDKN2A deleted NSCLC cells using public domain data showed increased sensitivity to a wide range of ErbB family inhibitors. To identify combination therapy targets for EGFR inhibitor based therapy in CDKN2A deleted NSCLC cells, we performed a combination therapy screen. This analysis indicated that combined targeting of EGFR and the anti-apoptotic protein Bcl-xL produced potent synergistic effects and efficient killing at very low drug concentrations. Evaluation of our results against public domain clinical data indicate that a significant subpopulation of EGFR/KRASwt NSCLC could benefit from combination therapy consisting of EGFRIERBB2 inhibitors and Bcl-xL inhibitors.

Introduction

Intensive cancer research during the last decades has resulted in deep knowledge about the molecular drivers of cancer as well as a long list of suggested targets for cancer therapy. One such example is epidermal growth factor receptor (EGFR), that has been shown overexpressed in as much as 40-80% of non small cell lung cancer (NSCLC)1. EGFR can be successfully inhibited in patients by the use of antibodies as well as tyrosine kinase inhibitors (TKIs). Early clinical studies comparing EGFR-TKIs to placebo as second or third line therapy showed benefit of EGFR-TKIs, and demonstrated differences in response between subgroups of the patients2. In parallel, other studies indicated that response to EGFR-TKIs could be predicted based on the presence of activating mutations on EGFR3. It was later shown that first line EGFR-TKIs was superior to chemotherapy in patients with EGFR mutant adenocarcinoma, while the opposite was shown in the group of EGFR wild-type (wt) adenocarcinoma4. These results were supported by a subsequent study showing that first line therapy EGFR-TKIs, with an impressive 74% response rate, was superior to conventional chemotherapy in NSCLC patients with EGFR mutations5. Further, a study comparing EGFR-TKIs and docetaxel as second line therapy in NSCLC patients with wt EGFR receptor showed overall benefit of docetaxel, but disease control was achieved in 26% of the patients treated with EGFR-TK1s6. Based on these results and similar studies, current clinical practise includes EGFR status evaluation and limits EGFR-TKI based therapy to NSCLC patients confirmed EGFR mutations.

The question whether EGFR-TKIs have any clinical benefit in patients with wt EGFR NSCLC remains unsolved. When analysing the value of EGFR-TKIs vs placebo as first line therapy in patients with advanced NSCLC unsuitable for chemotherapy, it was demonstrated that EGFR-TKIs increased progression free survival in a subgroup of patients with wt EGFR, and the authors concluded that biomarkers are needed to identify potential responders'. A re-analysis of early studies of EGFR-TKIs vs placebo as second line therapy, focusing on the subgroup of patients where EGFR status was known, showed a small but significant benefit of EGFR-TKIs in both progression free survival and overall survival in the group of patients with confirmed wt EGFR5. These studies indicate that a subpopulation of patients with wt EGFR NSCLC could benefit from EGFR-TKI based therapy. However, since there are presently no biomarkers that can predict the response to EGFR targeting therapy in EGFR wt NSCLC this population remains undefined.

An additional clinical problem is that tumors that initially respond to EGFR-TKIs inevitably will develop resistance towards the treatment resulting in regrowth of the tumor. For prolonged control of the disease and potential cure, EGFR-TKIs needs to be used in combination with other, so far not defined, types of therapy. A deeper understanding of the molecular consequences of EGFR inhibition will improve the possibility of predicting treatment response as well as to understand the development of resistance. Here, we use a systems biology approach to generate such knowledge in order to find novel predictive biomarkers as well as novel targets for EGFR-TKI based combination therapy.

Results Selection of NSCLC cells for profiling based on "dominant cancer driver phenotype" analysis Careful selection of model cell lines is crucial in order to generate biologically meaningful information. As a starting point for selecting the lung cancer cell lines to include in this is study we used the Cancer Cell Line Encyclopedia (CCLE), a large collection of human cell lines (947) of known origin, characterised in terms of mutational status (>1300 genes), gene copy number, and gene expressions. A follow up publication based on the CCLE molecular profiling data showed that not all cancer cell lines were representative as models for their respective cancer types10. To select NSCLC cell lines for the current study we used a similar approach where we extracted gene expression data for the 185 lung cancer cell lines available in CCLE. Based on this data we then performed clustering of the cell lines, resulting in the division of lung cancer cell lines into three main groups (Figure la). One group represented cell lines generated from small cell lung cancer, and the remaining two groups contained NSCLC cell lines. In order to evaluate the differences between the two NSCLC groups we _performed differential expression analysis based on the CCLE transcriptomics data. The separation of the two NSCLC cell line clusters was heavily driven by large differences in lineage, with one cluster being more epithelial and the other more mesenchymal (Figure 1b). Differences in lineage have previously been shown important for response to different types of cancer therapy including EGFR-TKIs, where epithelial lineage is associated with sensitivity11. In addition, while the presence of KRAS mutations were similar in both NSCLC groups (25-27%), EGFR mutations were more prevalent in the epithelial NSCLC group (9% vs 2%).

As indicated by the analysis performed above, clustering of cell lines based on gene expression can give us higher order information about what is actually driving the cancer cells. Knowing the mutational status of individual genes will not be enough to predict if a cancer cell is dependent on a specific driver pathway as suggested by KRAS mutant NSCLC cells dividing into biologically very distinct clusters. We call this higher order information about cancer drivers the "dominant cancer driver phenotype" (DCDP). Further, we strongly believe that knowing the DCDP of individual cancers will help us predict response to targeted therapies more accurately.

The DCDP-analysis suggested that the likelihood of finding EGFR-TKI sensitive cell lines is higher in the epithelial cluster than in the mesenchymal cluster. As our aim was to identify novel markers of EGFR-TKI response in EGFR wt cells we therefore focused our attention to cell lines in the epithelial cluster.

Out of the 68 cell lines in the epithelial cluster, the CCLE resource provide pharmacological profiles for 24 different anti-cancer drugs including the EGFR-TKI erlotinib in 37 of the cell lines9. Plotting the activity area for erlotinib across the 37 cell lines showed as expected that the sensitivity was in general higher for cell lines with an EGFR mutation, lower for cell lines with a KRAS mutation and intermediate for cell lines that are wild type for both EGFR and KRAS (Figure 1c). Included in the CCLE cell lines is also one cell line (NCI-H1975) that in addition to an activating EGFR mutation (L858R) also carry the EGFR T790M mutation associated with resistance to EGFR-TKIs.

Out of these 37 cell lines, 15 were selected for molecular profiling. This panel included as reference one cell line with an activating EGFR mutation (HCC827, EGFR exon 19 del) and one cell line (NCI-H1975) carrying an activating EGFR mutation (L858R) and in addition the EGFR-TKI resistance mutation T790M. Next, 10 different cell lines with no mutations in either EGFR or KRAS and with varying response to an EGFR-TKI (erlotinib) were included. Lastly, 3 cell lines with KRAS mutations were included to complete the cell line panel used for molecular response profiling (Figure 1c).

EGFR-TKI molecular response profiling in NSCLC cells The large-scale in-depth analysis of gefitinib response in the NSCLC cell lines was successfully performed as planned, generating data in line with our goals (Figure 2). In total 60 samples (15 cell lines, +/-gefitinib, in duplicates) were analysed by HiRIEF-LCMS to generate proteome level information and 90 samples (same as proteomics but triplicates) were analysed using RNAsequencing for transcriptome level information. To our knowledge, the analytical depth at both mRNA and protein level achieved and the scale of this study constitute the most comprehensive molecular profiling of EGFR-TKI response performed up to date.

The NSCLC panel included two reference cell lines for evaluation of molecular response to EGFR-TKIs. First, a gefitinib sensitive cell line (HCC-827) harboring a typical EGFR exon 19 deletion and second, a gefitinib resistant cell line (NCI-H1975) harboring two different EGFR mutations, one activating mutation (L858R) and in addition the gatekeeper mutation T790M that inhibits gefitinib from binding to the receptor. As expected, molecular profiling showed dramatic impact of gefitinib treatment on both mRNA and protein level in the sensitive cell line, while very little effect was seen in the resistant cell line (Figure 3a).

To evaluate the molecular response to EGFR-TKIs in the cell line panel we first performed differential analysis between untreated and treated cells for each cell line separately to define commonly regulated mRNAs (n=1080) and proteins (n=627) in our data ("core regulation"). Regulation patterns for these mRNAs and proteins were then used to perform hierarchical clustering of cell lines. Through this analysis we were able to identify EGFRwt NSCLC cell lines with a molecular response to gefitinib that was similar to the response seen in the sensitive reference cell line HCC-827 (Figure 3b). Across all 15 NSCLC cell lines included in this study (including 2 EGFR mutated, 3 KRAS mutated and 10 EGFRwt/KRASwt), we identified five EGFRwt/KRASwt cell lines as mutant-like molecular responding (clustering together with HCC-827) and five EGFRwtIKRASwt cell lines as non-responding (clustering together with NCI-H1975 or KRAS mutant cell lines). These 10 EGFRwt/KFtASwt cell lines were then used as models for gefitinib responding/nonresponding EGFRwt cancer cells as described below.

Candidate EGFR-TKI predictive markers in NSCLC pane! To identify candidate gefitinib predictive biomarkers in EGFRwt/KRASwt NSCLC we performed differential analysis of baseline mRNA and protein expression between the five EGFR mutant like molecular responding and the five non-responding cell lines using the profiling data generated from untreated cells. One of the most striking findings from this analysis was that the molecular responding cell lines were lacking mRNA expression of the tumor suppressors CDKN2A (coding for p16 and p14) and CDKN2B (coding for p15) (Figure 3c). P16 and p15 are both central negative regulators of Gl/S transition and p14 negatively regulates mdm2 resulting in stabilisation of p5312*13. In addition to our own generated data, public domain data from cancer cell line encyclopedia (CCLE) was used to evaluate differences in mutation patterns and gene copy number aberrations. Evaluation of gene copy number showed that all five molecular responder cell lines had a deletion of the genetic locus where both CDKN2A and CDKN2B resides. Our data thus indicate that loss of CDKN2A/B is associated with an EGFRmutant like response to EGFR-TKIs. This is of particular importance as loss or inactivation of CDKN2A is one of the most frequent genetic aberration in both adenocarcinoma and squamous cell carcinoma of the lung. Using public domain data from CCLE we further investigated molecular determinants of EGFR-TKI response in CDKN2A deleted NSCLC cell lines. This analysis indicated that epithelial lineage (assayed by mRNA expression of the epithelial marker e-cadherin, CDH1) was associated with sensitivity to EGFR-TKIs, while mesenchymal lineage (mRNA expression of the mesenchymal marker vimentin, VIM) was associated with resistance (Figure 3d). This finding is in line with previous reports where it has also been shown that epithelial to mesenchymal transition is a potential resistance mechanism for targeting therapy as well as conventional chemotherapy. Our analyses also show that two alternative tyrosine kinase receptors that has previously been connected to development of resistance to EGFR-TKI5 (AXL and MET) were highly expressed in four of five resistant EGFRwt cell lines already before treatment with gefitinib suggesting that these cells were relying less on EGFR for proliferation and survival (Figure 3e).

Candidate EGFR-TKI predictive markers in NSCLC panel Overall, our data thus indicated that deletion of CDKN2A and epithelial lineage predicts response to EGFR-TKIs in EGFRwt/KRASwt NSCLC cell lines, and that normal CDKN2A and mesenchymal lineage predicts lack of response. To investigate the frequency of potential EGFR-TKI responding wild-type cells further, we used CCLE and another similar large public domain resource, the Genomics of Drug Sensitivity in Cancer14 (GDSC). First, to evaluate lineage, we investigated mRNA expression of e-cadherin and vimentin across all cell lines in CCLE and GDSC. This analysis indicated that epithelial cells could be easily determined by the analysis of these two markers (Figure 4a-b). Next, CDKN2A copy number status in CCLE and GDSC cell lines were evaluated using copy number data as well as mRNA expression data retrieved from the two resources (Figure 4c-d). Finally, mutational status of EGFR and KRAS for all cell lines were retrieved. Using this information four cell line subgroups were defined; 1.EGFRmut, 2.KRASmut and EGFRwt/KRASwt cells divided into 3.PredResistant (CDKN2A normal and/or mesenchymal) and 4.PredSensitive (CDKN2Adeleted and epithelial). This analysis showed consistency between the resources with 9.3% and 11.9% of NSCLC cell lines predicted as EGFRwt/KRASwt sensitive in CCLE and GDSC respectively (Figure 4e-f). Apart from NSCLC, both resources predicted cell lines from breast, esophagus, bladder/urinary tract and stomach cancer as sensitive, and in addition GDSC predicted sensitive cells from head and neck cancer. Importantly, similarly to NSCLC all of these cancer types include significant subsets that are driven by EGFR mutations or ERBB2 amplification15. This suggests that the signaling dependence in these cancer types is similar to the NSCLC findings here presented, and that CDKN2A deletion would have a predictive value for ErbB -family targeting therapy response also in these cancer types.

Both CCLE and GDSC contain sufficient numbers of NSCLC cell lines for further evaluation of the EGFR-TKI response prediction in EGFRwt/KRASwt cells. Using the EGFR-TKI sensitivity information available in CCLE for erlotinib and GDSC for gefitinib we investigated the accuracy of our response predictions. Importantly, this analysis showed that in NSCLC cell lines without EGFR or KRAS mutations, either CDKN2A deletion or epithelial lineage could be used for prediction of EGFR-TKI response (Figure 5a-b). Further, our analysis showed that combining the information of CDKN2A status and lineage increased the significance in the prediction, as well as the fold difference in EGFRTKI response between cells predicted as sensitive and those predicted as resistant. In addition, the EGFRwt/KRASwt NSCLC cells that were predicted as resistant were indistinguishable from KRAS mutated cells (Figure 5c-d).

Both COLE and GDSC hold drug response information for multiple compounds, and as a next step we evaluated differences between the two EGFRwt/KRASwt cell line groups in overall drug response. Out of the 24 different compounds available in the CCLE resource, erlotinib and lapatinib (dual targeting EGFR/ERBB2 inhibitor) were more effective in EGFRwt/KRASwt NSCLC predicted as sensitive to EGFR-TKIs, supporting the predictive value of the biomarkers (Figure 5e). Interestingly, the predicted resistant cells were more sensitive to the MET inhibitor PHA-665752, which would be in line with previous knowledge of mesenchymal cells expressing_ higher levels of MET'. A similar analysis based on GDSC drug response data covering 265 compounds again indicated that the prediction was valid, as multiple different EGFR targeting compounds were more effective in cells predicted as sensitive (Figure 5f). Importantly, this analysis indicate that the predictive capacity is not restricted to erlotinib and gefitinib, but extends to dual targeting inhibitors like lapatinib and afatinib, pan-ERBB family inhibitors like pelitinib, and even EGFR-targeting antibodies such as cetuximab.

Candidate EGFR-TKI resistance mediators and combination therapy targets in NSCLC panel To kill cancer cells effectively and reach long-term remission the general understanding is that mono-therapy in most cases is insufficient. Our previous studies of signalling in response to gefitinib have indicated that multiple mechanisms are employed by cancer cells to escape the effects of EGFR-TKI treatment. Targeting such adaptation signalling in combination with EGFR-TKIs could result in improvement of treatment efficacy, and increased understanding of this type of signalling and its consequences is therefore valuable. Using our generated molecular response data, analysis of receptor tyrosine kinase (RTK) levels in response to gefitinib revealed that multiple alternative RTKs were upregulated at both mRNA and protein level in cell lines defined as molecular responders (Figure 6a). A closer analysis of RTKs previously associated with EGFR-TKI resistance (ERBB212, ERBB318 and FGFR219) showed common upregulation already 24h after to gefitinib treatment (Figure 6b). This data suggest that cancer cells very rapidly switch to alternative RTKs when EGFR is inhibited, and that pan-ERBB family targeting or combination therapy including targeting of alternative RTKs may increase treatment efficacy. Another candidate escape mechanism suggested by our previous studies was upregulation of the transcriptional repressor BCL6. BCL6 expression has previously been associated with imatinib resistance in leukemia cells through inhibition of both p53 and p21, important tumor suppressor regulators of apoptosis and proliferation20. Analysis of BCL6 regulation in response to gefitinib in the NSCLC panel validated our previous results as several cell lines showed upregulation of BCL6 (Figure 6b), indicating that targeting of BCL6 in combination with EGFR-TKIs should be explored. Further, analysis of BCL2L1, coding for the antiapoptotic protein Bcl-xL (encoded by BCL2L1)21, showed that two of the EGFRwt cell lines defined as molecular responders had overexpression of this gene already before treatment with EGFR-TKIs (Figure 6c). Bcl-xL has been associated with development of resistance towards multiple types of targeted therapy22, and our data indicate that some cancer cells have high levels of this protein already before exposure to therapy. Such baseline expression could blunt the effects of EGFR-TKIs even if there was an initial molecular response, again indicating that combination therapy including inhibitors of Bcl-xL could improve the efficacy of EGFR-TKIs.

High throughput screening in NSCLC cells for identification of EGFR-TKI 30 combination therapy targets To perform an investigation of potential EGFR-TKI combination therapy targets in NSCLC a high-throughput screening (HTS) approach was used. First we profiled the dose response of gefitinib across the 10 EGFRwt/KRASwt cell lines and the two EGFRmut reference cell lines. In accordance with our molecular response profiling conclusions, the mutant-like responding EGFRwt cell lines also showed a lower IC20 value than the non-responding cell lines (Figure 7a). For the HTS combination screen a fixed gefitinib concentration was used (0.5uM, approx. median 1C20 in mutant-like responding cells) together with increasing doses of individual combination compounds (528 different) as detailed in Figure 7b. For each gefitinib combination in each cell line a drug sensitivity score (DSS) was calculated as described previously23. Finally differential combination therapy sensitivity between the mutant-like responders and non-responders was tested.

Importantly, three different combinations including three different Bcl-xUBcl-2 inhibitors were identified as effective in killing the mutant-like responding CDKN2A deleted cells (Figure 7c-d). While one of the inhibitors (Navitoclax) targets both Bcl-xL and BcI-2, the other two inhibitors (A-1155463 and A-1331852) targets Bcl-xL specifically. Also present in the combination therapy screen was a Bcl-2 specific inhibitor (Venetoclax), but this inhibitor did not cause any cell killing (Figure 7d) suggesting that the true EGFR-TKI combination therapy target was Bcl-xL.

To validate the results from the combination drug screen a focused investigation of the synergistic effects of EGFR-TKIs and Bcl-xL/Bcl-2 inhibitors was performed. This screen could confirm the synergistic effects between the Bcl-xL inhibitors (A11554638 and A13318525) and gefitinib as shown in NCI-H2935 cells (Figure 8a). Further, this screen showed again that the BcI-2 targeting drug venetoclax was without effect in these cells. To expand the evaluation, the synergistic effects between lapatinib, a dual targeting EGFR/ERBB2 inhibitor, and different Bcl-xL/Bcl-2 inhibitors was evaluated in NCI-H2170 cells (Figure 8b). These results very closely reproduced the results from the gefitinib experiments in NCI-H2935, strongly indicating that these results are generalizable to include overall targeting of the ErbB family in combination with Bcl-xL inhibition.

Clinical evaluation in lung adenocarcinoma For a first evaluation of our discovery in clinical samples we retrieved public domain data for lung adenocarcinoma generated in The Cancer Genome Atlas (TCGA) project. For a total of 509 lung adenocarcinoma samples both mRNA profiling data, copy number data and mutation data was available in the TCGA resource. First we evaluated the impact of CDKN2A copy number status on CDKN2A mRNA levels (Figure 9a). This analysis revealed that CDKN2A mRNA levels were not significantly different between samples with heterozygous CDKN2A deletion and samples with normal CDKN2A copy number, indicating that loss of one CDKN2A copy can be compensated for. Homozygous deletion of CDKN2A however showed clear loss of CDKN2A mRNA expression as expected. For the continued analysis we therefore kept only samples with normal CDKN2A copy number (n=169) and samples with homozygous CDKN2A deletion (n=93). Next we evaluated if loss of CDKN2A was associated with mutations in any specific genes (Figure 9b). Interestingly this analysis showed a clear enrichment for EGFR mutations in the group of CDKN2A deleted tumors (22%) compared to tumors with normal CDKN2A copy number (9%). This association strongly indicate that oncogenic EGFR signalling in combination with loss of CDKN2A is favourable for the cancer cells and selected for during tumor formation. In extension this finding also suggests that overactivity of EGFR through other mechanisms than mutation would be favourable for cancer cells, supporting our finding that loss of CDKN2A indicate response to EGFR targeting therapy. Further, a small but significant difference in BCL2L1 mRNA expression was noticed, where CDKN2A deleted tumors showed higher expression (Figure 9c).

Since our studies indicated that lineage, in addition to CDKN2A status, is an important determinant of EGFR-TKI response we evaluated the lineage of the adenocarcinoma tumor samples. To do this we clustered the CDKN2A deleted and normal samples based on the mRNA expression of 119 epithelial-mesenchymal signature genes (Figure 9d). This analysis divided the adenocarcinoma samples into two equally sized clusters, cluster 1 containing 125 epithelial like adenocarcinoma samples and cluster 2 containing 137 mesenchymal like adenocarcinoma samples. Interestingly, the epithelial like adenocarcinoma cluster was clearly enriched in CDKN2A deleted samples (44%) compared to the mesenchymal like adenocarcinoma cluster (28%).

The division of clinical samples into epithelial and mesenchymal subgroups was much less clear than what was evident in the cell line panel. A likely explanation to this result is that the clinical samples used for generating the TCGA data contains also normal cells (e.g. stromal and immunological cells), and in addition tumors are known to be heterogenous in cell content and therefore cancer cells of different lineage can be part of the same tumor in varying proportions. Drug response prediction based on gene expression signatures heavily dependent on lineage markers (epithelial or mesenchymal) is problematic to use in the clinic due to the cell type heterogeneity and infiltrating stromal cells in cancer tissue samples24. For this reason additional phenotypic markers apart from lineage based markers would further sharpen the predictive power of CDKN2A status in a clinical setting.

In conclusion, this clinical evaluation supports our hypothesis that cancer cell dependence on EGFR signalling is increased in CDKN2A deleted tumors. Further, the analyses indicate that CDKN2A deleted cells are expressing higher mRNA levels of BCL2L1, which further support the here suggested combination therapy targeting both EGFR signalling and Bc1-xL.

Model for EGFR signaling dependence in CDKN2A deleted NSCLC In summary, our data has revealed an unexpected subgroup of EGFRwt KRASwt NSCLC cells that are sensitive to inhibition of signalling through the EGFR-family of tyrosine kinase receptors. This subgroup is defined by CDKN2A/B deletion, but our data indicate that further refinement of the sensitive subgroup could be made by the addition of additional markers. In cell line model systems epithelial lineage further predicts response to EGFRTKIs. Even though our public domain analysis suggests that epithelial lineage and CDKN2A deletion could be a favourable combination for NSCLC cancer cells, and show that EGFR mutations are overrepresented in CDKN2A deleted tumors, further studies are needed to validate our findings in a clinical setting.

Importantly, our combination therapy screens suggest that targeting of the anti-apoptotic protein Bcl-xL together with EGFR/ERBB2 produce synergistic cell killing in the EGFRwt subgroup here defined.

Based on our generated data we suggest a model for EGFR dependence in CDKN2A deleted NSCLC (Figure 10). In normal cells without mutations without oncogenic mutations in the EGFR signaling pathway and with the cell cycle checkpoint control in place (normal CDKN2A/B status) both proliferation/survival signalling and apoptosis/death signalling are controlled by positive and negative regulation resulting in a balanced system (Figure 10a). In EGFR mutated NSCLC the proliferation/survival signalling is constitutively activated resulting in oncogenic signalling. Such signalling results in activation of cellular surveillance systems controlled by the tumor suppressor p53, aiming to shut down the oncogenic signalling or send cells into aptosis. This creates an "oncogene addiction", where the cancer cell is dependent on continued oncogenic signalling to escape the proapoptotic signaling. Blocking EGFR-signalling by EGFR-TKIs such as gefitinib therefore not only results in inhibition of proliferation/survival, but also swings the balance over to apoptosis and cell death (Figure 10b). In CDKN2A/B deleted NSCLC the cell cycle checkpoint is absent and p53 signalling is impaired through mdm2 dependent inhibition (degradation) of p53. The net effect of this is uncontrolled signalling from the wt EGFR and reduced pro-apoptotic signalling. As suggested here inhibition EGFR signalling together with inhibition of anti-apoptotic Bcl-xL signalling can revert the imbalance and cause cancer cell death. (Figure 10c).

Materials and Methods Cell lines and treatments Non-small cell lung cancer cell lines NCI-H441, NCI-H1568, NCI-H1573, NCI-H1666, NCI-H1869, NCI-H1975, NCI-H2009, NCI-H2085, NCI-H2087, NCI-H2170, HCC-827 and HCC-2935 were purchased from ATCC, CAL-12T and HCC78 were purchased from DSMZ and NCI-H322 was purchased from Sigma-Aldrich. All cell lines were expanded initially as detailed in the culture instructions, and then switched to RPMI-1640 AQ medium (Sigma-Aldrich R2405) supplemented with 10% FBS (Sigma-Aldrich F7524) and 1% penicillin/streptomycin (Sigma-Aldrich P4333). Cells were cultured at 37°C and 5% CO2.

to All cell lines were tested and found Mycoplasma-free using MycoAlert Mycoplasma detection kit (Lonza, Cat. No. LT07-218). Gefitinib was purchased from Selleckchem (Catalog No. S1025) and diluted in DMSO to a stock concentration of 5 mM. For mRNA and proteins profiling experiments cells were seeded, and 24h after seeding triplicate cultures were either treated with gefitinib (2.5uM) or with DMSO alone (ctrl). Harvesting of cells was performed 24h after treatment by washing adherent cells in PBS followed by trypsination (Trypsin-EDTA solution, Sigma, T3924). Each sample was subsequently aliquoted for profiling using RNAsequencing and MS-based proteomics.

Sample preparation for mass spectrometry For extraction of proteins, pellets (biological duplicates) containing 5-million-cells were lysed with SDC buffer (5% Sodium Deoxycholate (SDC), 1mM DTT (Sigma-Aldrich, 43819), 25 mM HEPES pH 7.6), vortexed and kept on ice for 10 min, then shaken in a thermo-mixer at 95°C for 10 min followed by sonication (2 cycles of 30 sec, 80% energy).

Vials were centrifuged at 14,000g for 15 min. Supernatants containing proteins were collected into new vials. Protein concentration was determined by DC protein assay kit (BioRad 5000112).

Protein extracts were digested with trypsin (Pierce, 90058) using a slightly modified filter aided sample preparation (FASP) protocols. 250}tg of supernatant was mixed with 1 mM DTT, 8M urea, 25 mM HEPES, pH 7.6 and transferred to a 10-kDa cut-off centrifugation filtering unit (Pall, Nanosep®), and centrifuged at 14,000g for 15 min. Proteins were alkylated by 50 mM iodoacetamide (IAA) in 8 M urea, 25 mM HEPES for 10 min. The proteins were then centrifuged at 14,000g for 15 min followed by 2 more additions and centrifugations with 4 M urea, 25 mM HEPES. Trypsin (Promega) in 250mM urea, 50 mM HEPES was added to the cell lysate at a ratio of 1:50 trypsin:protein and incubated overnight at 37°C in thermo-mixer with mixing speed 300 rpm. The filter units were centrifuged at 14,000g for 15 min followed by another centrifugation with MilliQ water and the flow through was collected. 50 pg peptides were taken from each sample and pooled together to prepare the internal reference sample mixture. The sample peptide and the internal reference peptides were subsequently individually labelled with TMT-10plex isobaric label reagents (Thermal Scientific, Cat. No. 90110) according to the manufacturer's protocol. Each TMT-10plex set was used for labelling peptides from two cell lines +/-gefitinib in duplicates, with remaining two labels used for the internal reference in duplicate. After pooling samples in each TMT-set, the labelled peptides were cleaned by reverse phase cleanup method using Polymetric Reverse Phase cartridge (Phenomenex Strata-X-C, 8B-S100-TAK). Pooled sample were dried using speedvac and re-dissolved in 600 JAI of 3% acetonitrile (ACN), 0.1% formic acid (FA) and pH was ensured to be below 3. Reverse phase column was conditioned by adding 600 pl methanol and re-equilibrated with 600 pl of 3% ACN, 0.1% FA. Pooled sample was added to the column, washed with 600 p1 of 3% ACN, 0.1% FA and eluted with 600 pi of 80% ACN, 0.1% FA.

Eluted samples was collected, dried using speedvac and dissolved in MilliQ water to determine peptide concentration. The sample was aliquoted to 500pg peptides mixture for isoelectric focusing (IEF).

Peptide-level isoelectric focusing (HiRIEF) TMT labelled peptides were separated by immobilized pH gradient -isoelectric focusing (IPG-IEF) on pH 3-10 strips (500 tag peptides per strip) as described previously (HiRIEF method26). Peptides were extracted from the strips by a prototype liquid handling robot, supplied by GE Healthcare Bio-Science AB. A plastic device with 72 wells was put onto each strip a_nd 50 pl of water was added to each well. After 30 min incubation, the liquid was transferred to a 96 well plate and the extraction was repeated 2 more times with 35% ACN and 35% ACN, 0.1% FA in MilliQ water, respectively. The extracted peptides were dried in Speed-Vac and dissolved in 3% ACN, 0.1% FA.

LC-MS/MS analysis For each LC-MS run of a HiRIEF fraction, the auto sampler (Ultimate 3000 RSLC system, Thermo Scientific Dionex) dispensed 15p1 of mobile phase A (95% water, 5% dimethylsulfoxide (DMSO), 0.1% formic acid) into the corresponding well of the microtiter plate, mixed by aspirating/dispensing 10p1 ten times, and finally injected 7p1 into a C18 guard desalting column (Acclaim pepmap 100, 75pm x 2cm, nanoViper, Thermo). After 5min of flow at 5p1/min with the loading pump, the 10-port valve switched to analysis mode in which the NC pump provided a flow of 250nL/min through the guard column. The curved gradient (curve 6 in the Chromeleon software) then proceeded from 3% mobile phase B (90% acetonitrile, 5% DMSO, 5% water, 0.1% formic acid) to 45% B in 50min followed by wash at 99% mobile phase B and re-equilibration. Total LC-MS run time for each fraction was 74min. We used a nano EASY-Spray column (pepmap RSLC, C18, 2pm bead size, 100A, 75pm internal diameter, 50cm long, Thermo) on the nano electrospray ionization (NSI) EASY-Spray source (Thermo) at 60°C. Online LC-MS was performed using a hybrid Q-Exactive mass spectrometer (Thermo Scientific). FTMS master scans with 70,000 resolution (and mass range 300-1700 m/z) were followed by data-dependent MS/MS (35,000 resolution) on the top 5 ions using higher energy collision dissociation (HCD) at 30% normalized collision energy. Precursors were isolated with a 2m/z window. Automatic gain control (AGC) targets were 1e6 for MS1 and 1e5 for MS2. Maximum injection times were 100ms for MS1 and 150ms for MS2. The entire duty cycle lasted -1.5s. Dynamic exclusion was used with 60s duration. Precursors with unassigned charge state or charge state 1 were excluded. An underfill ratio of 1% was used.

Proteomics database search pipeline Raw MS/MS files were converted to mzML format using msconvert from the ProteoWizard tool suite27. Spectra were then searched using MSGF+28 (v10072) and Percolator29 (v2.08), where 8 subsequent search results were grouped for Percolator target/decoy analysis. The reference database used was the human protein subset of ENSEMBL 79. MSGF+ settings included precursor mass tolerance of 10ppm, fully-tryptic peptides, maximum peptide length of 50 amino acids and a maximum charge of 6. Fixed modifications were TMT-10plex on lysines and N-termini, and carbamidomethylation on cysteine residues, a variable modification was used for oxidation on methionine residues. Quantification of TMT-10plex reporter ions was done using OpenMS projects IsobaricAnalyzers° (v2.0). PSMs found at 1% FDR (false discovery rate) were used to infer gene identities (gene symbol centric search), which were quantified using the medians of PSM quantification ratios. Protein false discovery rates were calculated using the picked-FDR methods' and limited to 1% FDR. For downstream analysis, quantitative MS-data generated in each TMT set was normalized to average internal reference signal. For plotting and clustering of protein expression in untreated cells, average relative values for each cell line are used. For evaluation of regulation in response to gefitinib, the ratio between treated and average untreated cells were used.

RNA sequencing and mapping Lung cancer cells were cultured in triplicate dishes as described above, and after harvesting of cells using trypsination, total RNA was extracted using RNeasy kit (Qiagen, Hilden, Germany) according to manufacture's instructions. RNA libraries were created using strand-specific TruSeq kit with poly-A selection for all RNA samples according to manufacture's instructions. Quality control were checked by Bioanalyzer/Caliper. Sequencing (Paired-end 2 x 125 bp) was performed by HiSeq2500 (Illumine, San Diego, CA, USA) as standard RNA-seq protocol. Library preparation as well as sequencing was performed at the sequencing facility (National Genomics Infrastructure) at SciLifeLab in Stockholm, Sweden. Mapping of the raw reads was performed using Tophat/2.0.4 to the Human genome assembly build GRCh37. Raw read counts were calculated with HTSeq v0.5.1 on bam files with duplicates removed. FPKM values for genes and transcripts were generated using cufflinks/2.1.1 on bamfiles with duplicates removed. Analysis was performed on all genes with a gene biotype annotated in ENSEMBL as protein coding.

Genes with missing reads in any of the samples were removed from the analysis. FPKM values were used for hierarchical clustering. Differential expression analysis was performed on total read normalized values using the DESeq2" package in R. CCLE and GDSC data analysis For analysis of CCLE cell lines, all data was downloaded from https://portals.broadinstitute.org/ccle. For analysis of CDKN2A copy number, preprocessed copy-number values per gene was used, mutation data was downloaded as pre-processed binary calls and drug response data was downloaded as pharmacologic profiles for 24 anticancer drugs across 504 CCLE lines including activity area and IC50 as drug response -m-aasures7Gerre expression data was downloaded as Gerter-centric RMAnormalized mRNA expression data. For initial hierarchical clustering of 185 NSCLC cell lines, all genes were ranked by inter-quartile range (IQR) in gene expression across the cell lines. The top 5000 genes with highest IQR were then selected for hierarchical clustering of genes and cell lines in R using the heatmap.2 function in the gplots package with spearman correlation as distance measure and WardD2 as linkage method. For differential gene expression analysis, two-sided t-test was performed and p-values were adjusted for multiple testing using the false-discovery rate (FDR) with the procedure outlined by Benjamini and Hochberg". All analyses were performed in R (version 3.2.2) using the t.test and p.adjust functions from the R stats package.

For analysis of GDSC cell lines, all data was downloaded from www.cancerrxgene.org. For analysis of CDKN2A copy number, pre-processed copy number data was downloaded and CDKN2A deletion was defined if CDKN2A was annotated with LOH and minimum copy number was 0. Mutation data was downloaded as sequencing binary event matrix (BEM), and drug response data was downloaded as pre-processed data. Gene expression data was downloaded as RMA normalised expression data, and ENSG identifiers were mapped to gene symbols using the biomart package in R. TCGA data analysis Data from The Cancer Genome Atlas (TCGA) for lung adenocarcinoma (LUAD) including gene expression data, copy number data, gene-level mutation data as well as clinical information was accessed via the UCSC Cancer Browser.

For differential gene expression analysis two-sided t-test was performed and p-values were adjusted for multiple testing using the false-discovery rate (FDR) with the procedure outlined by Benjamini and Hochberg(63). All analyses were performed in R (version 3.2.2) using the t.test and p.adjust functions from the R stats package.

Unsupervised cluster analysis of the LUAD gene expression profiles was performed using 119 genes defined as epithelial-mesenchymal signature genes All patients and genes were clustered using hierarchical clustering with ward.d2 linkage and Spearman's correlation. Heatmaps were produced using the heatmap.2 function from the gplots package in R. HTS screening Determination of cell density for screening Cells were plated on 384-well black clear bottom plate (Sigma) in five different concentrations using a 2-fold dilutions series (8000-500 cells/in 20 pL). Cellular ATP levels were assessed after a 72 hours incubation (37°C and 5% CO2) using CellTiterGlo (Promega) as a surrogate for viability. Detection was done on an EnSight plate reader (PerkinElmer) and density for all cell lines based on growth rate was determined to 1500 cells/well.

Determination of gefitinib concentration-response Gefitinib (Selleck) was serial diluted in a 1:3 ratio for 11 concentrations and with 50 pM being the highest final concentration in the well. Media with 5 pL of gefitinib working stocks and viability controls (DMSO, 100 pM benzethonium chloride) were pre-dispensed followed by 20 pL of each cell line with 1500 cells/well. After incubation for 72 h the plate was assessed in the same manner as before with CellTiterGlo. IC50 concentration for each cell line was estimated by plotting % viability against log10 gefitinib concentration (M).

Drug Sensitivity and Resistance Testing (OSP]) and follow-up studies Compounds and viability controls (DMSO, 100 pM benzethonium chloride) were pre-dispensed on 384-well black clear bottom plate (Sigma) with an Echo acoustic liquid handler (Labcyte). Each compound was plated in 5 concentrations spanning a 10,000-fold concentration range (10-fold dilution). For discovery combination screening with gefitinib (DSRT), individual compounds in a compound library (524 compounds) were plated in assay ready plates and gefitinib was added on the day of screening. For drug combination validation experiments, all compounds were pre-plated. Lapatinib and venetoclax were purchased from VWR and navitoclax, A11554638 and A13318525 were purchased from Selleck. Assay ready plates were stored in pressurized StoragePods (Roylan Developments) under inert atmosphere until used. Using a MultiDrop Combi (Thermo Scientific) 5 pL media with or without 500 nM gefitinib (Selleck) was first dispensed into assay ready plates and centrifuged briefly. 20 pL of a single-cell suspension was then seeded using a peristaltic pump to the plates at a density of 1500 cells/per well. Plates were then transferred to an incubator for 72 h followed by read-out with CeliTiterGlo.

DSRT Data Processing Using in house or cloud-based (https://breeze.fimmli/DSRT) software, data from the plate reader were normalized per plate to percent viability using values from control wells. Concentration-response curves were fitted to percent viability values using a four-parameter logistic model and processed further to a sensitivity metric (DSS) using a weighted area-under-the-curve calculation23. DSS for each drug was compared between conditions tested.

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Claims (47)

1. Claims 1. An agent which inhibits a Receptor Tyrosine Kinase (RTK) for use in treating cancer in a patient, wherein the cancer is characterised in that (i) it has wild type RTK activity and (ii) it comprises reduced and/or absent CDKN2A activity.
2. 2. Use of an agent which inhibits a Receptor Tyrosine Kinase (RTK) in the manufacture of a medicament for treating cancer in a patient, wherein the cancer is characterised in that (i) it has wild type RTK activity and (ii) it comprises reduced and/or absent CDKN2A activity.
3. 3. A method of treating cancer in a patient, wherein the cancer is characterised in that (i) it has wild type RTK activity and (ii) it comprises reduced and/or absent CDKN2A activity, wherein the method comprises administering an agent which inhibits a Receptor Tyrosine Kinase (RTK) to the patient.
4. 4. An agent for use, a use, or a method according to any of Claims 1-3, wherein the cancer is further characterised in that (iii) it is dependent on the activity of wild type RTK for proliferation and/or survival.
5. 5. An agent for use, a use, or a method according to any of Claims 1-4, wherein the cancer comprises KRAS having a wild type activity, BRAF having a wild type activity, ROS1 having a wild type activity, and/or ALK having a wild type activity.
6. 6. An agent for use, a use, or a method according to any of Claims 1-5, wherein the cancer does not comprise an activating RTK mutation, an activating KRAS mutation, an activating BRAF mutation, an activating ROS1 mutation and/or an activating ALK mutation.so
7. 7. An agent for use, a use, or a method according to any of Claims 1-6, wherein the cancer further comprises reduced and/or absent CDKN2B activity.
8. 8. An agent for use, a use, or a method according to any of Claims 1-7, wherein reduced and/or absent CDKN2A and/or CDKN2B activity is reduced and/or absent due to deletion, mutation and/or methylation of CDKN2A and/or CDKN2B.
9. 9. An agent for use, a use, or a method according to any of Claims 1-8, wherein the patient is selected from the group comprising: a primate (for example, a human; a monkey; an ape); a rodent (for example, a mouse, a rat, a hamster, a guinea pig, a gerbil, a rabbit); a canine (for example, a dog); a feline (for example, a cat); an equine (for example, a horse); a bovine (for example, a cow); and/or a porcine (forexample, a pig).
10. 10. An agent for use, a use, or a method according to any of Claims 1-9, wherein the cancer is selected from the group comprising: lung cancer, breast cancer, oesophagus cancer, bladder cancer, stomach cancer and head and neck cancer.
11. 11. An agent for use, a use, or a method according to any of Claims 1-10, wherein the cancer is non-small cell lung cancer (NSCLC) for example adenocarcinoma, squamous cell carcinoma, adenosquamous carcinoma, large cell carcinoma or large cell neuroendocrine cancer.
12. 12. An agent for use, a use, or a method according to any of Claims 1-11, wherein the RTK is one or more RTK of the ERbB receptor family.
13. 13. An agent for use, a use, or a method according to any of Claims 1-12, wherein the RTK is selected from the group comprising: EGFR, ErbB-2, ErbB-3 and ErbB-4.
14. 14. An agent for use, a use, or a method according to any of Claims 1-13, wherein the agent acts by one or more of: a) targeting the extracellular domain of the RTK resulting in inhibition of ligand binding and/or receptor dime homo-or heterodimerization resulting in inhibition of receptor activation; and/or b) targeting of the intracellular domain of the RTK through binding to the adenosine triphosphate (ATP)-binding site of the RTK resulting in reversible or irreversible inhibition of receptor activation; and/or c) targeting of the intracellular domain of the RTK preventing the receptors' autophosphorylation site resulting in reversible or irreversible inhibition of receptor activation; and/or d) targeting of the intracellular kinase domain resulting in a reversible or irreversible inhibition of receptor activation.
15. 15. An agent for use, a use, or a method according to any of Claims 1-14, wherein the agent is selected from the group comprising: small molecule, an antibody or antigen binding fragment thereof (including nanobody), an antibody mimetic, other bioconjugates or immunoconjugates, a polypeptide, a peptide, a peptidomimetic, a nucleic acid (including ribozymes, antisense, RNAi and aptamers), a virus or virus-like particle carrying a therapeutic biomolecule, a hormone, and/or a natural product.
16. 16. An agent for use, a use, or a method according to any of Claims 1-15, wherein the agent is one of (i) an anti-ErbB family tyrosine kinase inhibitor (TKI); and (H) an anti-ErbB family monoclonal antibody.
17. 17. An agent for use, a use, or a method according to any of Claims 1-16, wherein the agent is selected from the group comprising: gefitinib, erlotinib, afatinib, lapatinib, pelitinib, cetuximab, neratinib, panitumumab, vandetanib, necitumumab, dacomitinib, trastuzumab, brigatinib, pertuzumab, and functional analogs, or derivatives thereof.
18. 18. An agent for use, a use, or a method according to any of Claims 1-17, wherein the step of treating the cancer further comprises administering one or more additional anti-cancer therapy to the patient.
19. 19. An agent for use, a use, or a method according to Claim 18, wherein the additional anti-cancer therapy comprises an inhibitor of Bcl-xL. 25
20. 20. An agent for use, a use, or a method according to any of Claims 18-19, wherein the additional anti-cancer therapy is selected from the group comprising: Navitoclax, BM-1197, ABT-737, sabutoclax, A-1155463, A-1331852, Isosorbide, Gossypol, 4-fluoro-1,11-biphenyl-4-carboxylic acid, APG-1252, AT-101, WEHI-539 hydrochloride, TW-37, FL518, CRTB6.
21. 21. An agent for use, a use, or a method according to any of Claims 18-20, wherein the agent and the additional anti-cancer therapy are administered sequentially or concurrently.
22. 22. A method of predicting response to treatment comprising an agent which inhibits a Receptor Tyrosine Kinase (RTK) in a patient with cancer, wherein the method comprises the steps of determining if the cancer (i) has wild type RTK activity; and (ii) comprises reduced and/or absent CDKN2A activity, and predicting if the patient will respond to therapeutic administration of the agent on the basis of those steps.
23. 23. A method of identifying a patient with cancer in need of treatment comprising an to agent which inhibits a Receptor Tyrosine Kinase (RTK), wherein the method comprises the steps of determining if the cancer (i) has wild type RTK activity; and (ii) comprises reduced and/or absent CDKN2A activity, and identifying the patient as one in need of treatment comprising the agent on the basis of those steps.
24. 24. The method of any of Claims 22-23, wherein the method further comprises therapeutic administration of the agent to the patient.
25. 25. The method of any of Claims 22-24, wherein the method further comprises the step of determining (iii) if the cancer is dependent on the activity of the wild type RTK for its proliferation and/or survival.
26. 26. The method of any of Claims 22-25, wherein the method comprises the step, performed before step (i) of obtaining or receiving or providing a test sample from a patient.
27. 27. The method of Claim 26, wherein the test sample comprises one or more cancer cell.
28. 28. The method of Claim 27, wherein the one or more cancer cell is selected from the group comprising: a lung cancer cell a breast cancer cell, an oesophagus cancer cell, a bladder cancer cell, a stomach cancer cell, and a head and neck cancer cell.
29. 29. The method of any of Claims 27-28, wherein the one or more cancer cell is a non-small cell lung cancer (NSCLC) cell.
30. 30.
31. 31.
32. 32.
33. 33.
34. 34.
35. 35.The method of any of Claims 22-29, wherein the method further comprises obtaining, receiving or providing a control sample.The method of any of Claims 22-30, wherein determining if the cancer has wild type RTK activity comprises the step of determining the activity, level, and/or mutational status of the RTK.The method of any of Claims 22-31, wherein the method comprises the step of determining if the cancer comprises reduced and/or absent CDKN2B activity.The method of Claim 32, wherein the step of determining if the cancer comprises reduced and/or absent CDKN2A and/or CDKN2B activity comprises determining if CDKN2A and/or CDKN2B activity is reduced and/or absent due to deletion, mutation and/or methylation of CDKN2A and/or CDKN2B.The method of any of Claims 25-33, wherein the step of determining if the cancer is dependent on the activity of the wild type RTK for its proliferation and/or survival comprises determining if the cancer comprises KRAS, BRAF, ROS1 and ALK with wild type activity.The method of any of Claims 22-34, wherein the patient is selected from the group comprising: a primate (for example, a human; a monkey; an ape); a rodent (for example, a mouse, a rat, a hamster, a guinea pig, a gerbil, a rabbit); a canine (for example, a dog); a feline (for example, a cat); an equine (for example, a horse); a bovine (for example, a cow); and/or a porcine (for example, a pig).
36. 36. The method of any of Claims 22-35, wherein the cancer is as defined in any of Claims 10-11.
37. 37. The method of any of Claims 22-36, wherein the RTK is as defined in any of Claims 12-13.
38. 38. The method of any of Claims 22-37, wherein the agent is as defined in any of the preceding claims.
39. 39. Use of CDKN2A and/or CDKN2B deletion, mutation and/or methylation status for predicting the responsiveness of a patient with cancer to treatment comprising an agent which inhibits a Receptor Tyrosine Kinase (RTK); wherein the cancer is characterised in that it comprises wild type RTK activity; and is dependent on the activity of the wild type RTK for its proliferation and/or survival.
40. 40. Use of CDKN2A and/or CDKN2B deletion, mutation and/or methylation status for selecting a patient with cancer for treatment comprising an agent which inhibits a Receptor Tyrosine Kinase (RTK); wherein the cancer is characterised in that it comprises wild type RTK activity; and is dependent on the activity of the wild type RTK for its proliferation and/or survival.
41. 41. Use of one or more reagents that determine if a patient has a cancer which: (i) comprises a wild type RTK activity; (ii) comprises reduced and/or absent CDKN2A and/or CDKN2B activity; and (Hi) is dependent on the activity of the wild type RTK for its proliferation and/or survival, wherein following the determination of (i)-(iii) the patient having cancer is treated with an agent which inhibits a Receptor Tyrosine Kinase (RTK).
42. 42. The use of any of Claims 39-41, wherein the agent is as defined in any of the preceding claims.
43. 43. The use of any of Claims 39-41, wherein the cancer is as defined in any of the preceding claims.
44. 44. The use of any of Claims 39-43, wherein the RTK is as defined in any of the preceding claims.
45. 45. The use of any of Claims 39-44, wherein the determination of (i)-(iii) is as defined in any preceding claims.
46. 46. The use of any of Claims 39-45, wherein the use further comprises reagents which determine reduced and/or absent CDKN2A and/or CDKN2B activity.
47. 47. A kit comprising: means for detecting: (I) the activity, level, and/or mutational status of an RTK; (II) CDKN2A and/or CDKN2B deletion, mutation and/or methylation; 48. 49. 50. 51.(III) KRAS mutational status; BRAF mutational status; ROS1 mutational status; and ALK mutational status.A combination of at least one Receptor Tyrosine Kinase (RTK) inhibitor and at least one inhibitor of Bcl-xL.A combination of a Receptor Tyrosine Kinase (RTK) inhibitor and an inhibitor of Bcl-xL for treating cancer in a patient wherein the cancer is characterised in that (i) it has wild type RTK activity and (H) it comprises reduced and/or absent CDKN2A activity.A method for treating a patient with an epidermal growth factor receptor (EGFR) inhibitor-resistant cancer comprising administering to the patient a combination of at least one Bcl-xL inhibitor and at least one EGFR inhibitor.An agent, a use, a method, a kit, a combination substantially as claimed herein with reference to the accompanying claims, description, examples and figures.