WO2007101122A2 - Methods and compositions involving slc17a1 - Google Patents

Abstract

The present invention concerns methods and compositions for evaluating whether an EGFR-targeted agent is a promising treatment option in a patient based on the level of expression of a gene called SLC17Al . It was determined that cells sensitive to SLC17Al had a significantly greater amount of gene expression of SLC17A1 than cells considered resistant to SLC17A1. Other aspects of the invention include methods for identifying other such candidate markers for drug toxicity and/or drug efficacy.

Description

DESCRIPTION

METHODS AND COMPOSITIONS INVOLVING SLC17A1

BACKGROUND OF THE INVENTION

This invention was made with government support under GM061393 awarded by the National Institute of Health. The government has certain rights in the invention.

This application claims the benfit of U.S. Provisional Patent Application No. 60/776,393, filed on February 24, 2006.

1. Field of the Invention The present invention relates generally to the fields of molecular biology, oncology, and pharmacology. More particularly, it concerns diagnostic, prognostic, and therapeutic methods and compositions involving cancers that may be treated with a class of epidermal growth factor receptor (EGFR)-targeted agents, which includes tyrosine kinase inhibitors (TKI), and potential efficacy of those agents to treat such cancers. The invention involves evaluating SLCl 7Al expression to assess and/or predict efficacy or possible resistance to such agents.

2. Description of Related Art

The epidermal growth factor receptor (EGFR) is part of a subfamily of four closely related receptors EGFR/HER1 (ErbB-1), HER2/neu (ErbB-2), HER3 (ErbB-3) and HER4 (ErbB-4). EGFR has been implicated in the development and progression of a number of human solid tumors, including those of the lung, breast, prostate, colon, ovary, head and neck (Salomon et al., 1995; Arteaga, 2003; Eccles et al., 1994; Nicholson, 2001). Overexpression of EGFR was also found to be a negative prognostic factor for adult soft tissue sarcomas (STS) (Thomas, 2003). EGFR is a membrane protein which has a specific external ligand binding domain, a transmembrane domain and an internal domain which has tyrosine kinase enzyme activity. When a specific ligand, for example EGF or TGF-α, binds to the EGFR, it causes receptor dimerization and autophosphorylation of the internal receptor domain. This initiates a cascade of cellular reactions that result in increased cell division and influences other aspects of malignant progression of the tumor: angiogenesis, metastasis and inhibition of apoptosis. Therefore, inhibition of the EGFR provides a rational target for anticancer therapy (Wakeling, 2002; Ciardiello et al, 2002; Mendelsohn, 2001;Arteaga, 2001 ; Perez-Soler, 2004; Patel et al, 2004; Golsteyn, 2004). The EGFR TKIs include a variety of small molecules that compete with ATP for binding to the receptor's intracellular tyrosine kinase (TK) pocket. These agents can inhibit the autophosphorylation of the EGFR thus blocking the EGFR signaling cascade. Two TKIs, gefϊtinib and erlotinib, are currently approved for the treatment of non-small cell lung cancer (NSCLC) (Bishop et al, 2002).

Individual variability in response to EGFR inhibitors has been observed in various clinical studies. Identifying patients most likely to respond to EGFR/ HERl- targeted agents will improve the chances of achieving a positive outcome. Therefore, investigators are interested in defining factors that could be used to identify patients more sensitive to EGFR inhibitors. Receptor expression itself is the most obvious candidate and several studies indicate a correlation between EGFR/HER1 overexpression and poor prognosis (Chou et al, 2005). However, these findings are confounded by problems with assessing EGFR/HERl expression accurately and lack of a standardized scoring system (Taron et al., 2005). Studies in patients with NSCLC have found that patients with somatic mutations in the TK domain of the EGFR/HERl receptor are extremely susceptible to gefitinib (Amador et al., 2004; Takano et al, 2005; Cappuzzo et al, 2005; Han et al, 2005). Although different types of mutations were identified, they all clustered around the ATP -binding pocket of the receptor's TK domain and have been shown to enhance sensitivity to gefitinib in preclinical models. Recently, studies have found that EGFR mutations and increased copy numbers were significantly associated with better clinical outcome in gefitinib-treated NSCLC patients (Jain et al, 2005; Boyd, 1995; Monks et al, 1997; Stinson et al, 1992). Furthermore, a group has identified that epithelial membrane protein-1 (EMP-I) correlates with gefitinib resistance (Blower et al, 2002). The number of CA single sequence repeats (CA-SSR) in intron 1 of the EGFR gene, which affects transcription efficiency of the gene, has also been suggested to be associated with the response to EGFR inhibitors (Mitsudomi et al, 2005).

Although there are a growing number of studies addressing predictive biomarkers for response to the EGFR inhibitors, most of them are focusing on the two FDA-approved agents, erlotinib and gefitinib. Moreover, current information indicates that some patients who have a significant response to gefitinib do not have a reported mutation. Therefore, the situation may be more complicated, and a biomarker that would be able to predict the variability in response to a class of EGFR TKIs in a broader sample of tumors would be very useful in predicting in which patients EGFR- targeted agents would be efficacious.

SUMMARY OF THE INVENTION

The present invention is based on the determination that the expression level of SLCl 7Al in cancer cells inversely correlates with the toxicity and sensitivity of those cells to a class of EGFR-targeted agents, such as EGFR TKIs. Cancer cells that express the SLC 17Al gene at higher levels than resistant cells are more likely to be sensitive to these agents, and therefore, the present invention concerns methods and compositions for predicting therapeutic efficacy of an EGFR-targeted agent in a patient.

It is contemplated that the methods disclosed herein apply to any EGFR- targeted agent that inhibits EGFR activity, including but not limited to the tyrosine kinase activity of EGFR. EGFR-targeted agents include proteins that specifically bind EGFR (for instance, antibodies such as cetuximab or panitumumab), a tyrosine kinase inhibitor (such as gefitinib, lapatinib, or AG1478, or derivatives thereof), or a ganglioside GM3 lactone or analog thereof (such as HKl-ceramide 2). Moreover, it is contemplated that the EGFR-targeted agent may be or include compounds such as erlotinib, gefitinib, lapatinib, canertinib, Tyrphostin AG 825, cetuximab, ABX-EGF (panitumumab), hR3, tyrphostin AG1318, tyrphostin RG13022, tyrphostin, erbstatin, RF14921, tyrphostin T23, tyrphostin T47, tyrphostin RG-13022, RG14620, tyrphostin AG879 or AG1478 (NSC693255)— or derivatives thereof, which include PD153035 (NSC669364), PD153717 (NSC669365), erlotinib (NSC718781), as well as PD158780 (NSC691853), PD165557 (NSC691854), PD168393 (NSC691856), PD168735 (NSC691857), PD169541 (NSC691858), PD169540 (NSC691859), PD166075 (NSC691860), and PDl 83805 (NSC709239). In particular embodiments the EGFR-targeted agent is specifically a tyrosine kinase inhibitor of EGFR. In additional embodiments, the EGFR-targeted agent is a small molecule tyrosine kinase inhibitor, while in others the EGFR-targeted agent is a monoclonal antibody against EGFR. Methods of the invention include a method for predicting efficacy of an EGFR-targeted agent in a cancer patient comprising: a) obtaining a sample containing cancer cells from the patient; b) assaying the level of SLC 17Al expression in the cells, and, c) treating or not treating the patient with an EGFR-targeted agent depending on whether the level of SLC 17Al expression is higher than a standardized level of expression from EGFR-targeted agent resistant cancer cells, wherein the patient who is not treated with an EGFR-targeted agent is treated with another anticancer therapy. Furthermore, it is contemplated that a method of the invention may comprise: a) obtaining a sample containing cells from the patient; b) assaying the level of SLC17A1 expression in the cells, and, c) treating or not treating the patient with an EGFR-targeted agent depending on whether the level of SLC17A1 expression is higher than a standardized level of expression from EGFR-targeted agent resistant cancer cells, wherein the patient who is not treated with an EGFR-targeted agent is treated with another anti-cancer therapy. Thus, it is contemplated that in certain cases the expression level of SLCl 7Al in non cancer cells may be used a therapeutic guide.

The present invention also includes a method for determining whether to treat a cancer patient with an EGFR-targeted agent comprising: a) identifying a patient with a type of cancer that may be treated with an EGFR-targeted agent; b) obtaining cells (e.g., cancer cells) from the patient; c) measuring the level of SLCl 7Al expression in the cancer cells; and, d) treating the patient with an EGFR-targeted agent if SLC 17Al is expressed at a level that is higher than the level in cancer cells resistant to the EGFR-targeted agent or treating the patient with an anti-cancer therapy that is not an EGFR-targeted agent if SLCl 7Al is expressed at a level lower than cancer cells that are sensitive to the EGFR-targeted agent. In some embodiments of the invention, there are methods for predicting efficacy of an EGFR-targeted agent in a cancer patient comprising: a) having a sample containing cells (e.g., cancer cells) from the patient obtained from the patient; b) obtaining information regarding the level of SLCl 7Al expression in the cells, and, c) treating or not treating the patient with an EGFR-targeted agent depending on whether the level of SLC17A1 expression is higher than a standardized level of expression from EGFR-targeted agent resistant cancer cells, wherein the patient who is not treated with an EGFR-targeted agent is treated with another anti-cancer therapy. It is generally contemplated that a medical practitioner or medical personnel may be involved in performing the various steps of this embodiment. The medical practitioner or personnel may request that a sample be obtained from the patient or that person may obtain the sample themselves from the patient.

Alternatively, in other embodiments of the invention, there are methods for assisting in predicting efficacy of an EGFR-targeted agent in a cancer patient comprising a) obtaining a sample containing cells (e.g., cancer cells) from the patient; b) assaying the level of SLC 17Al expression in the cells; and c) reporting information regarding the level of SLCl 7Al expression in the cells. It is generally contemplated that a laboratory or laboratory personnel who are processing medical information from patients may be involved in performing the various steps of this embodiment. Laboratory personnel may obtain the sample directly from the patient or they may obtain the sample by receiving it after it has been obtained directly from the patient, such as from a medical practitioner who directly obtained the sample from the patient. The sample may then be assayed to determine the level of SLC 17Al expression in the cells. The level of expression may be further correlated with sensitivity or resistance to an EGFR-targeted agent. Information regarding the level of SLC 17Al expression may then be reported. Such information may include any results relating correlating the expression, as discussed below, or to the actual level of SLC 17Al expression. The information may constitute the likelihood that the patient's cancer cells will be resistant or sensitive to an EGFR-targeted agent.

Samples containing cells from the patient include, but are not limited to, a tissue biopsy, blood or serum, a swab, a lavage, smear, or scrape from the patient. In certain aspects of the invention samples comprising cells from the patient comprise cancer cells. Methods may further involve correlating the level of SLC17A1 expression in the sample with sensitivity and/or resistance to an EGFR-targeted agent. The word "correlating" is used according to its ordinary meaning to "establish a relationship to." It is contemplated that in some embodiments of invention, a medical practitioner, medical personnel, or laboratory personnel correlate the level of expression to sensitivity or resistance to an EGFR-targeted agent. In cases where the correlating is not done by a medical practitioner, such as by a laboratory, the information obtained from correlating the level of expression may be conveyed to another person or party, such as the medical practitioner. Moreover, in certain embodiments, the level of expression is correlated with varying degrees of sensitivity or resistance, such has high, moderate, or low sensitivity or resistance. In addition, the correlation may be done using a computer program or algorithm, which may or may not correlate the levels to a likelihood of sensitivity or resistance. A likelihood of sensitivity or resistance may be expressed by a percentage or generally classified.

In further embodiments of the invention, correlating involves comparing the level of SLC17A1 expression in the sample with a standardized level of SLC17A1 expression from EGFR-targeted agent resistant cancer cells, from EGFR-sensitive cancer cells, or from normal cells, or a combination thereof. It is contemplated that a control sample for comparison purposes need not be run for every sample from a patient or from every assay involving at least one sample from a patient. It is contemplated that a standardized level of expression from a control sample may be used for comparison purposes. A standardized level may be expressed in terms of a numerical range or a window of expression levels of it may be expressed in as a specific numerical value with an associated standard deviation for the value. It is contemplated that a standardized level of SLC 17Al expression from cancer cells deemed resistant to EGFR-targeted agents may be employed. In other embodiments, a standardized level of SLC 17Al expression from cancer cells deemed sensitive to EGFR-targeted agents may be employed. Additionally or alternatively, a standardized level of SLC 17Al expression from non-cancerous cells or normal cells may be employed.

In other embodiments, correlating does not involve a comparison step but instead involves consulting a chart or database that provides information about the levels of SLCl 7Al expression in other types of cells. The chart or database may provide information regarding the likelihood of sensitivity and/or resistance to an

EGFR-targeted agent.

The present methods concern providing information that will assist a medical practitioner in treating a cancer patient, particularly regarding treating a cancer patient with an EGFR-targeted agent. In some embodiments of the invention, a medical practitioner will decide not to treat the patient with an EGFR-targeted agent because the level of SLC 17Al expression in the sample is not higher than the level in cancer cells resistant to an EGFR-targeted agent or the level of expression in the sample is similar to the level in a such a resistant cancer cell.

In other embodiments, the level of SLC 17Al expression in the sample is higher than the level in cancer cells resistant to an EGFR-targeted agent and the patient is treated with an EGFR-targeted agent. In further embodiments of the invention, the patient is further monitored for sensitivity or resistance to the EGFR- targeted agent that he/she is treated with.

The methods of the invention concern assays for the level of SLC 17Al in a sample or in cancer cells used for comparison purposes. It is contemplated that expression may be assayed directly by measuring SLC17A1 protein and/or SLC17A1 RNA in the cells in certain embodiments of the invention. It is also contemplated that assays that indirectly measure S LC 17Al protein or RNA may be employed such as by measuring SLC17A1 activity in the cell or a surrogate marker for SLC17A1 protein or RNA levels in the cells. In embodiments in which SLC 17Al RNA is measured, in some cases, one or more probes and/or primers for SLC 17Al RNA (or cDNA) are used. The skilled artisan is well aware how to design and create probes and primers for a particular known sequence such as SLC 17Al. Moreover, such nucleic acid molecules may be used in nucleic acid amplification reactions to measure the RNA. The nucleic acid molecules may be labeled directly or indirectly in order to qualify or quantify SLCl 7Al expression levels. Such techniques are well known in the art and they include, but are not limited to labels that are fluorescent, colorimetric, enzymatic, or radioactive.

In some embodiments, the level of SLC 17Al expression is assayed by measuring SLC17A1 protein in the cells. In certain embodiments, SLC17A1 protein is measured using a molecule that specifically binds SLC 17Al protein, which can be a substrate or a protein. In specific cases, the protein is an antibody, such as one that specifically binds to SLC 17Al.

The patients who are expected to benefit from methods of the invention are patients who may be treated with an EGFR-targeted agent. The present invention may further involve identifying a patient who may be treated therapeutically or preventatively with an EGFR-targeted agent or who was treated with an EGFR- targeted agent. In some embodiments, the patient has been diagnosed with cancer, has been previously treated for cancer successfully or unsuccessfully (failed therapy), is at risk for cancer (based on, for instance, risk factors which may or may not include familial history), or is at risk for a recurring cancer. In particular embodiments, the patient has cancer, such as a solid tumor. Moreover, the patient may have been diagnosed with or determined to be at risk for cancer of the lung, breast, prostate, colon, kidney, ovary, or head and neck in some embodiments of the invention, though the invention is not limited to such cancers. Moreover, the cancer may be any solid tumor. The present invention also concerns the methodology for identifying genetic markers indicative of toxicity or efficacy of a drug or class of drugs. Therefore, in some embodiments of the invention there are methods for identifying a candidate marker of toxicity or efficacy of a drug or class of drugs comprising: a) comparing the level of gene expression in cell lines of a panel with the level of cellular toxicity from the target drug or class of target drugs in the cell line panel; and, b) identifying any gene exhibiting a correlation between expression and toxicity, wherein the correlating gene is a candidate marker for toxicity or efficacy. Such a method can be employed to evaluate a specific drug or a class of drugs that can be categorized together because of one or more similarities in terms of mechanism of action, structure, bioavailability, metabolism in a patient, and/or mode of administration.

A cell line panel refers to a set of at least 10 cell lines, though it is contemplated that the panel may have at least or at most 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, 1800, 1900, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10,000 or more cell lines in the panel. The cell lines may be restricted or unrestricted in terms of type of cell line, which can pertain to cell type origin, disease state, organism, phenotype or developmental stage, for example. In certain embodiments, the cell lines are restricted by disease state, such as being cancer cell lines. In particular cases, the cell line panel is the NCI60 cancer cell line panel. The method involves correlating gene expression in the cell lines with the toxicity or efficacy of the drug or class of drugs in those same cell lines. The correlation can be performed as explained in the Examples using algorithms for undertaking such evaluations. In some embodiments, there are steps for containing cell lines with the relevant drug or one or more members of a class of drugs and/or for classifying cell lines based on their toxicity and/or efficacy in the context of a particular drug or class of drugs.

In certain embodiments, methods also involve eliminating any gene that exhibits a correlation between expression and toxicity from a negative control drug, wherein any gene that exhibits a correlation between expression and toxicity from the target drug or class of target drugs in the cell line panel and not from a control drug in the cell line panel is a candidate marker.

Additionally, methods can involve estimating the false discovery rate for any gene. The false discovery rate is an estimate that provides some indication of confidence level. In certain embodiments, this can be done using a bootstrap simulation on the Pearson correlation coefficients between the expression of the gene and the cellular toxicity or efficacy across the cell lines, as is discussed in further details in the Examples and the cited references. In certain embodiments, methods also involve evaluating whether cellular toxicity is an indicator of efficacy of the drug or class of drugs comprising categorizing the efficacy of the drug or class of drugs in cell lines in the cell line panel and correlating the efficacy of the drug or class of drugs with the level of gene expression in the cell lines. Other methods also include testing biological samples from patients for expression of the candidate marker and determining whether expression correlates with efficacy or toxicity. This may be implemented, for instance, with patients who are given an EGFR-targeted agent. A tissue sample may be taken from these patients to determine the level of expression of the candidate marker. This could be done by a variety of ways known to those of skill in the art, including by immunohistochemistry. Then the efficacy and/or toxicity can be assessed in patients. For example, efficacy can be evaluated by assessing a particular therapeutic or physiological outcome, such as reduction in tumor size. Toxicity can be evaluated, for instance, through patient reporting of physiological effects that may be attributed to toxicity, such as the incidence or severity of side effects observed with, for example, an EGFR-targeted agent (e.g., interstitial lung disease, skin reaction). Subsequently, a correlation between expression and toxicity and/or efficacy can be evaluated or confirmed.

In additional embodiments, methods also concern assaying the level of expression of the candidate marker in a sample from a patient who may be treated with a target drug or a drug from the class of target drugs and treating or not treating the patient with the drug depending on the level of expression. Again, SLC 17Al may be the candidate marker.

Embodiments discussed in the context of SLCl 7Al expression and resistance/sensitivity may also be implemented with respect to the invention's general methodology as well, and vice versa. Any embodiment discussed with respect to one aspect of the invention applies to other aspects of the invention as well.

The embodiments in the Example section are understood to be embodiments of the invention that are applicable to all aspects of the invention.

The use of the term "or" in the claims is used to mean "and/or" unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive, although the disclosure supports a definition that refers to only alternatives and "and/or."

Throughout this application, the term "about" is used to indicate that a value includes the standard deviation of error for the device or method being employed to determine the value.

Following long-standing patent law, the words "a" and "an," when used in conjunction with the word "comprising" in the claims or specification, denotes one or more, unless specifically noted.

Other objects, features and advantages of the present invention will become apparent from the following detailed description. It should be understood, however, that the detailed description and the specific examples, while indicating specific embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present invention. The invention may be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein.

FIG. 1. The distribution of Pearson correlation coefficients for the 12 EGFR inhibitors and the 24 control drugs using the NCI dataset. Each point here represents an agent. P-value: the associated p value in the linear regression model; Controls: non-EGFR agents. AG1478 has the highest correlation coefficient. FIG. 2. The distribution of Pearson correlation coefficients for the 12 EGFR inhibitors and the 24 control drugs using the Stanford dataset. Each point here represents an agent. P-value: the associated p value in the linear regression model; Controls: non-EGFR agents. AG1478 has the highest correlation coefficient.

FIG. 3. The distributions of simulated correlation coefficients for the expression of SLC 17Al and the cellular toxicity across the NCI60 cancer cell lines.

For each agent, 10,000 simulations were done to calculate the Pearson correlation coefficients. Percentage: the proportion of each correlation coefficient in the pooled data (EGFR TKIs: 10,000x12 values; non-EGFR agents: 10,000x24 values).

FIG. 4. Fold changes of SLCl 7Al expression in either resistant or sensitive cell lines for each of the 12 EGFR TKIs. Bootstrap score: the percentage of the 100,000 simulations that SLC17A1 are overexpressed (fold change > 1.33-fold) in either cytotoxic group.

DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS I. Epidermal Growth Factor Receptor (EGFR) and EGFR-Targeted Agents Human epidermal growth factor receptor (EGFR) is a transmembrane protein.

Binding of ligands, such as epidermal growth factor and TGF-α, with its N-terminus on the extracellular surface induces receptor dimerization and activates the tyrosine kinase activity of the intracellular domain. Activation of EGFR leads to a cascade of cellular events that ultimately result in DNA synthesis, and cell proliferation, maturation, survival, and apoptosis. The expression of EGFR is mainly regulated at the transcription level (Xu et al, 1984). It has been demonstrated that EGFR mRNA production can be stimulated directly or indirectly by treating cells with EGF, dexamethasone, thyroid hormone, retinoic acids, interferon α, or wild-type p53 (Deb et al, 1994; Grandis et al, 1996; Hudson et al , 1989; Subler et al , 1994; Xu et al. , 1993.

The EGFR 5' regulatory region spans about 4 kb covering 2kb upstream and 2 kb downstream of exon 1. The regulatory elements include a promoter region and two separate enhancer regions. The function of the EGFR promoter and enhancers are well studied and documented (Ishii et al, 1985; Haley et al, 1987; Johnson et al, 1988; Kageyama et al, 1988; Maekawa et al, 1989; each of which in incorporated by reference). Briefly, there is no TATA or CAAT box found in the promoter. Instead, there are multiple transcription initiation sites (Ishii et al, 1985; Haley et al, 1987; Johnson et al, 1988; Kageyama et al, 1988). A number of cis- and trans- regulators have been discovered. These regulators include EGF responsive DNA-binding protein (ERDBP-I), p53, p63, SpI, Vitamin D-responsive element (VDRE) and estrogen responsive element, which reflects the perplexing regulation of EGFR.

Deoxyribonuclease I footprinting showed that SpI can bind to four CCGCCC sequences (-457 to -440, -365 to -286, -214 to -200, and -110 to -84) in the EGFR gene promoter and may, therefore, play a vital role in the gene regulation (Johnson et al, 1988). Studies by Gebhardt and colleagues (1999) demonstrated that a dinucleotide (CA)n repeat polymorphism in the intron 1 of EGFR (near the downstream enhancer) ranging from 14 to 21 repeats, appears to regulate EGFR expression. The longer allele with 21 repeats showed an 80% reduction of gene expression compared to the shorter allele with 16 repeats (Gebhardt et al, 1999; Buerger et al, 2000). Data from studies on the polymorphic CA repeat suggest that this polymorphic site may play a role in cancer susceptibility (Brandt et al, 2004).

Overexpression of EGFR is found in about 30% of human primary tumors. Its activation in these tumors appears to promote tumor growth by increasing cell proliferation, motility, adhesion, invasive capacity, and by blocking apoptosis (Tysnes et al, 1997). EGFR overexpression and dysregulation has been associated with poorer prognosis in patients, and with metastasis, late-stage disease, and resistance to chemotherapy, hormonal therapy, and radiotherapy (Salomon et al, 1995); Akimoto et al, 1999); Wosikowski et al, 2000).

Several EGFR-targeted cancer therapies are currently under development. EGFR-targeting agents are typically directed to inhibiting EGFR phosphorylation or blocking EGF binding. Such therapies include antibodies that specifically bind EGFR and small molecules that inhibit its tyrosine kinase activity. Two EGFR-targeting drugs have been approved, Iressa® (gefitinib) and Erbitux® (cetuximab), and Tarceva® (erlotinib) is in phase III trials. This particular invention has application in the context of those therapies that inhibit the tyrosine kinase activity of EGFR. II. SLC17A1

The present application concerns SLC 17Al expression levels and their correlation with sensitivity to EGFR-targeted cancer agents, such as TKIs. SLC 17Al expression levels may be evaluated on a nucleic acid level or on a protein level.

SLC 17Al refers to the solute carrier family 17 (sodium phosphate), member 1. The SLC 17 family of transporters were initially described as phosphate carriers, but current understanding is that this group of proteins mediate the transmembrane transport of organic anions (for review see Reimer et al, 2004, which is hereby incorporated by reference). There are three subfamilies. SLCl 7Al (the protein is also referred to as NPTl), which goes by the alias NaPi-I, constitutes one family and its predominant substrate is thought to be organic acids, phosphate, and chloride.

SLC17A2-4 constitute another family, while SLC17A6-8 are proteins that mediate the vesicular uptake of glutamate. The terms SLC17A1 and NPTl are used interchangeably in this disclosure. The Genbank Accession number for the cDNA

(SEQ ID NO:1) and protein (SEQ ID NO:2) sequences of SLC17A1 is NM_005074, which is hereby incorporated by reference.

A. SLC17A1 Nucleic Acids

The present invention concerns SLCl 7Al polynucleotides and oligonucleotides that are indicative of expression levels of the SLC 17Al gene or that can be used to determine that expression level. The polynucleotides or oligonucleotides may be identical or complementary to all or part of a nucleic acid sequence encoding a SLC 17Al amino acid sequence. These nucleic acids may be used directly or indirectly to assess, evaluate, quantify, or determine SLCl 7Al expression.

1. Polynucleotides and Oligonucleotides

As used in this application, the term "SLCl 7Al polynucleotide" refers to a SLC17Al-encoding nucleic acid molecule, which may or may not have been isolated essentially or substantially free of total genomic nucleic acid to permit hybridization and amplification. The polynucleotide may be an RNA molecule or a corresponding cDNA molecule that encodes SLCl 7Al or that is complementary to a nucleic acid sequence that encodes SLC 17Al. The term "polynucleotide" encompasses the term "oligonucleotide" though it is contemplated that in some embodiments of the invention a polynucleotide that is not an oligonucleotide is contemplated. For instance, determining the amount of an SLCl 7Al polynucleotide in a cell need not refer to something that is an oligonucleotide.

A SLC17A1 oligonucleotide refers to a nucleic acid molecule that is 100 residues in length or fewer and complementary or identical to at least 5 contiguous nucleotides of a SLC 17Al -encoding sequence, such as SEQ ID NO:1, which is the cDNA sequence encoding human SLCl 7Al (NM 005074).

It is contemplated that those of skill in the art are well aware of how to design and use nucleic acid sequences to detect and/or measure the amount of a nucleic acid such as SLC17A1 RNA in a cell or other biological sample. This may be based on hybridization properties (for example, with probes and/or primers).

A nucleic acid encoding all or part of an SLCl 7Al protein may contain a contiguous nucleic acid sequence encoding all or a portion of such a polypeptide of the following lengths, or a sequence of at least or at most the following lengths: 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360, 370, 380, 390, 400, 410, 420, 430, 440, 441, 450, 460, 470, 480, 490, 500, 510, 520, 530, 540, 550, 560, 570, 580, 590, 600, 610, 620, 630, 640, 650, 660, 670, 680, 690, 700, 710, 720, 730, 740, 750, 760, 770, 780, 790, 800, 810, 820, 830, 840, 850, 860, 870, 880, 890, 900, 910, 920, 930, 940, 950, 960, 970, 980, 990, 1000, 1010, 1020, 1030, 1040, 1050, 1060, 1070, 1080, 1090, 1095, 1100, 1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000, 5500, 6000, 6500, 7000, 7500, 8000, 9000, 10000, or more nucleotides, nucleosides, or base pairs, including such sequences from SEQ ID NO:1, other SLCl 7Al encoding sequences, or ErbB2-encoding sequences. It further contemplated that oligonucleotides or polynucleotides used in methods of the invention may be, be at least or be at most 60, 65, 70, 75, 80, 85, 90, 95, 96, 97, 98, 99, or 100% (or any range derivable therein) complementary or identical to an SLC17A1 polynucleotide, such as an SLC17A1 polynucleotide from a human (an example of a human sequence is SEQ ID NO:1). Therefore, it is contemplated that the lengths and percentage of complementarity or identity may be implemented with respect to human SLCl 7Al polynucleotides. Alternatively, polynucleotides may be characterized in terms of the polypeptides they encode. For example, the present invention concerns evaluating the level of SLCl 7Al expression. In the context of nucleic acids, this may mean that the nucleic acid being evaluated is one that encodes SLC 17Al polypeptide or one that is at least or at most 60, 65, 70, 75, 80, 85, 90, 95, 96, 97, 98, 99, or 100% (or any range derivable therein) identical to the sequence of a human SLC 17Al, such as SEQ ID NO:2.

In particular embodiments, the invention concerns isolated DNA segments and recombinant vectors incorporating all or part of an SLC17A1 polynucleotide sequence. The term "recombinant" may be used in conjunction with a polypeptide or the name of a specific polypeptide, and this generally refers to a polypeptide produced from a nucleic acid molecule that has been manipulated in vitro or that is the replicated product of such a molecule. In certain other embodiments, the invention concerns isolated DNA segments and recombinant vectors that include within their sequence a contiguous nucleic acid sequence from that shown in SEQ ID NO:1. This definition is used in the same sense as described above and means that the nucleic acid sequence substantially corresponds to a contiguous portion of that shown in SEQ ID NO:1 and has relatively few codons that are not identical, or functionally equivalent, to the codons of SEQ ID NO:1. The term "functionally equivalent codon" is used herein to refer to codons that encode the same amino acid, such as the six codons for arginine or serine, and also refers to codons that encode biologically equivalent amino acids. It also will be understood that this invention is not limited to the particular nucleic acid and amino acid sequences of SEQ ID NO:1 and SEQ ID NO:2 respectively. Recombinant vectors and isolated DNA segments may therefore variously include the SLC 17Al -coding regions themselves, coding regions bearing selected alterations or modifications in the basic coding region (such as mutations or polymorphisms), or they may encode larger polypeptides that nevertheless include SLC17Al-coding regions or may encode biologically functional equivalent proteins or peptides that have variant amino acids sequences.

Moreover, the nucleic acids are not limited to coding sequences. In some embodiments of the invention, genomic SLC 17Al sequences can be used to determine directly or indirectly SLCl 7Al expression. For instance, the number of TA repeats in the promoter of the UGTlAl gene has been shown to correlate with expression levels of the gene. See U.S. Patent 6,472,157, which is hereby incorporated by reference. A nucleic acid sequence can be "exogenous," which means that it is foreign to the cell into which the vector is being introduced or that the sequence is homologous to a sequence in the cell but in a position within the host cell nucleic acid in which the sequence is ordinarily not found.

Vectors include plasmids, cosmids, viruses (bacteriophage, animal viruses, and plant viruses), and artificial chromosomes {e.g., YACs). One of skill in the art would be well equipped to construct a vector through standard recombinant techniques, which are described in Sambrook et al. (2001) and Ausubel et al. (1996), both incorporated herein by reference.

2. Probes and Primers The nucleic acid sequences disclosed herein have a variety of uses as probes or primers for embodiments involving nucleic acid hybridization in methods of the invention. SLCl 7Al polynucleotides and oligonucleotides can be readily employed for such uses.

The term "primer," as used herein, is meant to encompass any nucleic acid that is capable of priming the synthesis of a nascent nucleic acid in a template- dependent process. Typically, primers are oligonucleotides from ten to twenty and/or thirty base pairs in length, but longer sequences can be employed. Primers may be provided in double-stranded and/or single-stranded form, although the single-stranded form is preferred. The term "probe" refers to any nucleic acid of which at least a single strand of the probe is capable of specifically hybridizing to a target nucleic acid under appropriate hybridization conditions. A probe may be single- or double- stranded.

The use of a probe or primer of between 13 and 100 nucleotides, between 17 and 100 nucleotides in length, or in some aspects of the invention up to 1-2 kilobases or more in length, allows the formation of a duplex molecule that is both stable and selective. Such probes or primers can be of lengths described above from SEQ ID NO:1. Molecules having complementary sequences over contiguous stretches greater than 20 bases in length are generally preferred, to increase stability and/or selectivity of the hybrid molecules obtained. One will generally prefer to design nucleic acid molecules for hybridization having one or more complementary sequences of 20 to 30 nucleotides, or even longer where desired. Such fragments may be readily prepared, for example, by directly synthesizing the fragment by chemical means or by introducing selected sequences into recombinant vectors for recombinant production.

The various probes and primers designed around the nucleotide sequences of the present invention may be of any length. By assigning numeric values to a sequence, for example, the first residue is 1, the second residue is 2, etc., an algorithm defining all primers can be proposed: n to n + y where n is an integer from 1 to the last number of the sequence and y is the length of the primer minus one, where n + y does not exceed the last number of the sequence. Thus, for a 10-mer, the probes correspond to bases 1 to 10, 2 to 11, 3 to 12 ... and so on. For a 15-mer, the probes correspond to bases 1 to 15, 2 to 16, 3 to 17 ... and so on. For a 20- mer, the probes correspond to bases 1 to 20, 2 to 21, 3 to 22 ... and so on.

Accordingly, the nucleotide sequences of the invention may be used for their ability to selectively form duplex molecules with complementary stretches of DNAs and/or RNAs or to provide primers for amplification of DNA or RNA from samples. Depending on the application envisioned, one would desire to employ varying conditions of hybridization to achieve varying degrees of selectivity of the probe or primers for the target sequence. For applications requiring high selectivity, one will typically desire to employ relatively high stringency conditions to form the hybrids. For example, relatively low salt and/or high temperature conditions, such as provided by about 0.02 M to about 0.10 M NaCl at temperatures of about 50⁰C to about 7O⁰C. Such high stringency conditions tolerate little, if any, mismatch between the probe or primers and the template or target strand and would be particularly suitable for isolating specific genes or for detecting specific mRNA transcripts. It is generally appreciated that conditions can be rendered more stringent by the addition of increasing amounts of formamide.

For certain applications, for example, site-directed mutagenesis, it is appreciated that lower stringency conditions are preferred. Under these conditions, hybridization may occur even though the sequences of the hybridizing strands are not perfectly complementary, but are mismatched at one or more positions. Conditions may be rendered less stringent by increasing salt concentration and/or decreasing temperature. For example, a medium stringency condition could be provided by about 0.1 to 0.25 M NaCl at temperatures of about 37°C to about 55°C, while a low stringency condition could be provided by about 0.15 M to about 0.9 M salt, at temperatures ranging from about 20⁰C to about 55°C. Hybridization conditions can be readily manipulated depending on the desired results.

In other embodiments, hybridization may be achieved under conditions of, for example, 5O mM Tris-HCl (pH 8.3), 75 mM KCl, 3 mM MgCl₂, 1.0 mM dithiothreitol, at temperatures between approximately 2O⁰C to about 37°C. Other hybridization conditions utilized could include approximately 10 mM Tris-HCl (pH 8.3), 50 mM KCl, 1.5 mM MgCl₂, at temperatures ranging from approximately 40⁰C to about 72°C. In certain embodiments, it will be advantageous to employ nucleic acids of defined sequences of the present invention in combination with an appropriate means, such as a label, for determining hybridization. A wide variety of appropriate indicator means are known in the art, including fluorescent, radioactive, enzymatic or other ligands, such as avidin/biotin, which are capable of being detected. In preferred embodiments, one may desire to employ a fluorescent label or an enzyme tag such as urease, alkaline phosphatase or peroxidase, instead of radioactive or other environmentally undesirable reagents. In the case of enzyme tags, colorimetric indicator substrates are known that can be employed to provide a detection means that is visibly or spectrophotometrically detectable, to identify specific hybridization with complementary nucleic acid containing samples.

In general, it is envisioned that the probes or primers described herein will be useful as reagents in solution hybridization, as in PCR™, for detection of expression of corresponding genes, as well as in embodiments employing a solid phase. In embodiments involving a solid phase, the test DNA (or RNA) is adsorbed or otherwise affixed to a selected matrix or surface. This fixed, single-stranded nucleic acid is then subjected to hybridization with selected probes under desired conditions. The conditions selected will depend on the particular circumstances (depending, for example, on the G+C content, type of target nucleic acid, source of nucleic acid, size of hybridization probe, etc.). Optimization of hybridization conditions for the particular application of interest is well known to those of skill in the art. After washing of the hybridized molecules to remove non-specifically bound probe molecules, hybridization is detected, and/or quantified, by determining the amount of bound label. Representative solid phase hybridization methods are disclosed in U.S. Patents 5,843,663, 5,900,481 and 5,919,626. Other methods of hybridization that may be used in the practice of the present invention are disclosed in U.S. Patents 5,849,481, 5,849,486 and 5,851,772. The relevant portions of these and other references identified in this section of the Specification are incorporated herein by reference.

Nucleic acids used as a template for amplification may be isolated from cells, tissues or other samples according to standard methodologies (Sambrook et al, 2001). In certain embodiments, analysis is performed on whole cell or tissue homogenates or biological fluid samples without substantial purification of the template nucleic acid. The nucleic acid may be genomic DNA or fractionated or whole cell RNA. Where RNA is used, it may be desired to first convert the RNA to a complementary DNA.

Pairs of primers designed to selectively hybridize to a nucleic acid corresponding to SEQ ID NO:1 or other SLC 17Al nucleic acid sequence are contacted with the template nucleic acid under conditions that permit selective hybridization. Depending upon the desired application, high stringency hybridization conditions may be selected that will only allow hybridization to sequences that are completely complementary to the primers. In other embodiments, hybridization may occur under reduced stringency to allow for amplification of nucleic acids contain one or more mismatches with the primer sequences. Once hybridized, the template- primer complex is contacted with one or more enzymes that facilitate template- dependent nucleic acid synthesis. Multiple rounds of amplification, also referred to as "cycles," are conducted until a sufficient amount of amplification product is produced.

The amplification product may be detected or quantified. In certain applications, the detection may be performed by visual means. Alternatively, the detection may involve indirect identification of the product via chemiluminescence, radioactive scintigraphy of incorporated radiolabel or fluorescent label or even via a system using electrical and/or thermal impulse signals (Bellus, 1994).

A number of template dependent processes are available to amplify the oligonucleotide sequences present in a given template sample. One of the best known amplification methods is the polymerase chain reaction (referred to as PCR™) which is described in detail in U.S. Patents 4,683,195, 4,683,202 and 4,800,159, and in Innis et al., \ 988, each of which is incorporated herein by reference in their entirety.

A reverse transcriptase PCR™ amplification procedure may be performed to quantify the amount of mRNA amplified. Methods of reverse transcribing RNA into cDNA are well known (see Sambrook et ah, 2001). Alternative methods for reverse transcription utilize thermostable DNA polymerases. These methods are described in WO 90/07641. Polymerase chain reaction methodologies are well known in the art. Representative methods of RT-PCR are described in U.S. Patent 5,882,864.

Another method for amplification is ligase chain reaction ("LCR"), disclosed in European Application No. 320 308, incorporated herein by reference in its entirety.

U.S. Patent 4,883,750 describes a method similar to LCR for binding probe pairs to a target sequence. A method based on PCR™ and oligonucleotide ligase assay (OLA), disclosed in U.S. Patent 5,912,148, may also be used.

Alternative methods for amplification of target nucleic acid sequences that may be used in the practice of the present invention are disclosed in U.S. Patents 5,843,650, 5,846,709, 5,846,783, 5,849,546, 5,849,497, 5,849,547, 5,858,652, 5,866,366, 5,916,776, 5,922,574, 5,928,905, 5,928,906, 5,932,451, 5,935,825, 5,939,291 and 5,942,391, GB Application No. 2 202 328, and in PCT Application No. PCT/US89/01025, each of which is incorporated herein by reference in its entirety. Qbeta Replicase, described in PCT Application No. PCT/US87/00880, may also be used as an amplification method in the present invention. In this method, a replicative sequence of RNA that has a region complementary to that of a target is added to a sample in the presence of an RNA polymerase. The polymerase will copy the replicative sequence which may then be detected.

An isothermal amplification method, in which restriction endonucleases and ligases are used to achieve the amplification of target molecules that contain nucleotide 5 '-[alpha-thio] -triphosphates in one strand of a restriction site may also be useful in the amplification of nucleic acids in the present invention (Walker et al. , 1992). Strand Displacement Amplification (SDA), disclosed in U.S. Patent 5,916,779, is another method of carrying out isothermal amplification of nucleic acids which involves multiple rounds of strand displacement and synthesis, i.e., nick translation.

Other nucleic acid amplification procedures include transcription-based amplification systems (TAS), including nucleic acid sequence based amplification

(NASBA) and 3SR (Kwoh et al., 1989; PCT Application WO 88/10315, incorporated herein by reference in their entirety). European Application No. 329 822 disclose a nucleic acid amplification process involving cyclically synthesizing single-stranded

RNA ("ssRNA"), ssDNA, and double-stranded DNA (dsDNA), which may be used in accordance with the present invention.

PCT Application WO 89/06700 (incorporated herein by reference in its entirety) disclose a nucleic acid sequence amplification scheme based on the hybridization of a promoter region/primer sequence to a target single-stranded DNA ("ssDNA") followed by transcription of many RNA copies of the sequence. This scheme is not cyclic, i.e., new templates are not produced from the resultant RNA transcripts. Other amplification methods include "RACE" and "one-sided PCR" (Frohman, 1990; Ohara et al, 1989).

Following any amplification or step such as primer extension, it may be desirable to separate the amplification or primer extension product from the template and/or the excess primer. In one embodiment, amplification products are separated by agarose, agarose-acrylamide or polyacrylamide gel electrophoresis using standard methods (Sambrook et al, 2001). Separated amplification products may be cut out and eluted from the gel for further manipulation. Using low melting point agarose gels, the separated band may be removed by heating the gel, followed by extraction of the nucleic acid.

Separation of nucleic acids may also be effected by chromatographic techniques known in art. There are many kinds of chromatography which may be used in the practice of the present invention, including adsorption, partition, ion- exchange, hydroxylapatite, molecular sieve, reverse-phase, column, paper, thin-layer, and gas chromatography as well as HPLC.

In certain embodiments, the amplification products are visualized. A typical visualization method involves staining of a gel with ethidium bromide and visualization of bands under UV light. Alternatively, if the amplification products are integrally labeled with radio- or fluorometrically-labeled nucleotides, the separated amplification products can be exposed to x-ray film or visualized under the appropriate excitatory spectra. In one embodiment, following separation of amplification products, a labeled nucleic acid probe is brought into contact with the amplified marker sequence. The probe preferably is conjugated to a chromophore but may be radiolabeled. In another embodiment, the probe is conjugated to a binding partner, such as an antibody or biotin, or another binding partner carrying a detectable moiety. In particular embodiments, detection is by Southern blotting and hybridization with a labeled probe. The techniques involved in Southern blotting are well known to those of skill in the art (see Sambrook et al, 2001). One example of the foregoing is described in U.S. Patent 5,279,721, incorporated by reference herein, which discloses an apparatus and method for the automated electrophoresis and transfer of nucleic acids. The apparatus permits electrophoresis and blotting without external manipulation of the gel and is ideally suited to carrying out methods according to the present invention.

Other methods of nucleic acid detection that may be used in the practice of the instant invention are disclosed in U.S. Patents 5,840,873, 5,843,640, 5,843,651, 5,846,708, 5,846,717, 5,846,726, 5,846,729, 5,849,487, 5,853,990, 5,853,992,

5,853,993, 5,856,092, 5,861,244, 5,863,732, 5,863,753, 5,866,331, 5,905,024,

5,910,407, 5,912,124, 5,912,145, 5,919,630, 5,925,517, 5,928,862, 5,928,869, 5,929,227, 5,932,413 and 5,935,791, each of which is incorporated herein by reference.

Other methods involve fluorescent in situ hybridization (FISH), which refers to process that vividly paints chromosomes or portions of chromosomes with fluorescent molecules. Such techniques are well known to those of skill in the art

(Weier et al, 2002; Moter et al, 2000; Nath et al, 1998). Another method that may also be employed involves RNA in situ hybridization (RISH). This technique may utilize nonradioactive probes such as digoxigenin-labeled copy RNA (cRNA) probes for the examination of mRNA expression, and is well known to one of ordinary skill in the art.

Reverse transcription (RT) of RNA to cDNA followed by relative quantitative

PCR™ (RT-PCR) can be used to determine the relative concentrations of specific mRNA species isolated from a cell, such as a SLC 17Al -encoding transcript. By determining that the concentration of a specific mRNA species varies, it is shown that the gene encoding the specific mRNA species is differentially expressed.

Specifically contemplated are chip-based DNA technologies such as those described by Hacia et al (1996) and Shoemaker et al (1996). Briefly, these techniques involve quantitative methods for analyzing large numbers of genes rapidly and accurately. By tagging genes with oligonucleotides or using fixed probe arrays, one can employ chip technology to segregate target molecules as high density arrays and screen these molecules on the basis of hybridization (see also, Pease et al, 1994; and Fodor et al, 1991). It is contemplated that this technology may be used in conjunction with evaluating the expression level of SLC 17Al with respect to diagnostic methods of the invention. It is contemplated that any embodiments discussed above with respect to

SLCl 7Al may be implemented with respect to ErbB2 using an ErbB2 polynucleotide, such as a human ErbB2 polynucleotide. The detection of ErbB2 may be implemented to determine whether a cancer in a patient is an ErbB2-overexpressing cancer.

III. Proteinaceous Compositions The present invention concerns evaluating the expression and/or activity of the polypeptide SLC 17Al, as well as determining whether a cancer is a ErbB2- overexpressing cancer. As used herein, a "proteinaceous molecule," "proteinaceous composition," "proteinaceous compound," "proteinaceous chain" or "proteinaceous material" generally refers, but is not limited to, a protein of greater than about 200 amino acids or the full length endogenous sequence translated from a gene; a polypeptide of greater than about 100 amino acids; and/or a peptide of from about 3 to about 100 amino acids. All the "proteinaceous" terms described above may be used interchangeably herein.

In certain embodiments the size of the at least one proteinaceous molecule may be at least, at most or may comprise, but is not limited to, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220, 230, 240, 250, 275, 300, 325, 350, 375, 400, 425, 450, 475, 500, 525, 550, 575, 582, 600, 625, 650, 675, 700, 725, 750, 775, 800, 825, 850, 875, 900, 925, 950, 975, 1000, 1100, 1200, 1300, 1400, 1500, 1750, 2000, 2250, 2500 or greater amino molecule residues, and any range derivable therein. It is specifically contemplated that such lengths of contiguous amino acids from SEQ ID NO:2 (amino acid sequence of human SLC17A1) are part of the invention.

Certain aspects of the present invention concern the purification, and in particular embodiments, the substantial purification, of an encoded protein or peptide. The term "purified protein or peptide" as used herein, is intended to refer to a composition, isolatable from other components, wherein the protein or peptide is purified to any degree relative to its naturally-obtainable state. A purified protein or peptide therefore also refers to a protein or peptide, free from the environment in which it may naturally occur.

Generally, "purified" will refer to a protein or peptide composition that has been subjected to fractionation to remove various other components, and which composition substantially retains its expressed biological activity. Where the term

"substantially purified" is used, this designation will refer to a composition in which the protein or peptide forms the major component of the composition, such as constituting about 50%, about 60%, about 70%, about 80%, about 90%, about 95% or more of the proteins in the composition.

Various methods for quantifying the degree of purification of the protein or peptide will be known to those of skill in the art in light of the present disclosure. These include, for example, determining the specific activity of an active fraction, or assessing the amount of polypeptides within a fraction by SDS/PAGE analysis. A preferred method for assessing the purity of a fraction is to calculate the specific activity of the fraction, to compare it to the specific activity of the initial extract, and to thus calculate the degree of purity, herein assessed by a "-fold purification number." The actual units used to represent the amount of activity will, of course, be dependent upon the particular assay technique chosen to follow the purification and whether or not the expressed protein or peptide exhibits a detectable activity.

Various techniques suitable for use in protein purification will be well known to those of skill in the art. These include, for example, precipitation with ammonium sulfate, PEG, antibodies and the like or by heat denaturation, followed by centrifugation; chromatography steps such as ion exchange, gel filtration, reverse phase, hydroxylapatite and affinity chromatography; isoelectric focusing; gel electrophoresis; and combinations of such and other techniques. As is generally known in the art, it is believed that the order of conducting the various purification steps may be changed, or that certain steps may be omitted, and still result in a suitable method for the preparation of a substantially purified protein or peptide.

Another embodiment of the present invention are antibodies. In some cases, the antibody is an ErbB2 targeting agent, while in others, it is used to evaluate, assess, or determine SLC17A1 or ErbB2 expression. It is understood that antibodies can be used to quantify polypeptides. Such antibodies, polyclonal or monoclonal, can be generated. Means for preparing and characterizing antibodies are also well known in the art {See, e.g., Harlow and Lane, 1988; incorporated herein by reference). Alternatively, they can be obtained commercially. For example, SLC 17Al antibodies can be readily obtained from Santa Cruz Biotechnology (A2B1, Santa Cruz, California) and Lab Vision Corp. (Ab-2, Fremont, California). As discussed, in some embodiments, the present invention concerns immunodetection methods for assessing, evaluating, determining, quantifying and/or otherwise detecting biological components such as SLC 17Al polypeptides.

Immunodetection methods include enzyme linked immunosorbent assay (ELISA), radioimmunoassay (RIA), immunoradiometric assay, fluoroimmunoassay, chemiluminescent assay, bioluminescent assay, western blot, and screening an antibody array, though several others are well known to those of ordinary skill. The steps of various useful immunodetection methods have been described in the scientific literature, such as, e.g., Doolittle et al, 1999; Gulbis and Galand, 1993; De Jager et al. , 1993 ; and Nakamura et al. , 1987, each incorporated herein by reference.

In general, the immunobinding methods include obtaining a sample suspected of containing a protein, polypeptide and/or peptide, and contacting the sample with a first antibody, monoclonal or polyclonal, in accordance with the present invention, as the case may be, under conditions effective to allow the formation of immunocomplexes.

The immunobinding methods include methods for detecting and quantifying the amount of an antigen component in a sample and the detection and quantification of any immune complexes formed during the binding process. Here, one would obtain a sample suspected of containing an antigen or antigenic domain, and contact the sample with an antibody against the antigen or antigenic domain, and then detect and quantify the amount of immune complexes formed under the specific conditions.

In terms of antigen detection, the biological sample analyzed may be any sample that is suspected of containing an antigen or antigenic domain, such as, for example, a cancer cell or tissue, or any biological fluid that comes into contact with the cell or tissue, including blood and/or serum.

Contacting the chosen biological sample with the antibody under effective conditions and for a period of time sufficient to allow the formation of immune complexes (primary immune complexes) is generally a matter of simply adding the antibody composition to the sample and incubating the mixture for a period of time long enough for the antibodies to form immune complexes with, i.e., to bind to, any antigens present. After this time, the sample-antibody composition, such as a tissue section, ELISA plate, dot blot or Western blot, will generally be washed to remove any non-specifically bound antibody species, allowing only those antibodies specifically bound within the primary immune complexes to be detected.

In general, the detection of immunocomplex formation is well known in the art and may be achieved through the application of numerous approaches. These methods are generally based upon the detection of a label or marker, such as any of those radioactive, fluorescent, biological and enzymatic tags. U.S. Patents concerning the use of such labels include 3,817,837; 3,850,752; 3,939,350; 3,996,345; 4,277,437;

4,275,149 and 4,366,241, each incorporated herein by reference. Of course, one may find additional advantages through the use of a secondary binding ligand such as a second antibody and/or a biotin/avidin ligand binding arrangement, as is known in the art.

One method of immunodetection designed by Charles Cantor uses two different antibodies (see, Sano et al, 1992). A first step biotinylated, monoclonal or polyclonal antibody is used to detect the target antigen(s), and a second step antibody is then used to detect the biotin attached to the complexed biotin. In that method the sample to be tested is first incubated in a solution containing the first step antibody. If the target antigen is present, some of the antibody binds to the antigen to form a biotinylated antibody/antigen complex. The antibody/antigen complex is then amplified by incubation in successive solutions of streptavidin (or avidin), biotinylated DNA, and/or complementary biotinylated DNA, with each step adding additional biotin sites to the antibody/antigen complex. The amplification steps are repeated until a suitable level of amplification is achieved, at which point the sample is incubated in a solution containing the second step antibody against biotin. This second step antibody is labeled, for example, with an enzyme that can be used to detect the presence of the antibody/antigen complex by histoenzymology using a chromogen substrate. With suitable amplification, a conjugate can be produced which is macroscopically visible.

Another known method of immunodetection takes advantage of the immuno- PCR (Polymerase Chain Reaction) methodology. The PCR™ method is similar to the Cantor method up to the incubation with biotinylated DNA, however, instead of using multiple rounds of streptavidin and biotinylated DNA incubation, the DNA/biotin/streptavidin/antibody complex is washed out with a low pH or high salt buffer that releases the antibody. The resulting wash solution is then used to carry out a PCR™ reaction with suitable primers with appropriate controls. At least in theory, the enormous amplification capability and specificity of PCR™ can be utilized to detect a single antigen molecule.

As detailed above, immunoassays, in their most simple and/or direct sense, are binding assays. Certain preferred immunoassays are the various types of enzyme linked immunosorbent assays (ELISAs) and/or radioimmunoassays (RIA) known in the art. Immunohistochemical detection using tissue sections is also particularly useful. However, it will be readily appreciated that detection is not limited to such techniques, and/or western blotting, dot blotting, FACS analyses, and/or the like may also be used.

Irrespective of the format employed, ELISAs have certain features in common, such as coating, incubating and binding, washing to remove non- specifically bound species, and detecting the bound immune complexes. These are described below. In coating a plate with either antigen or antibody, one will generally incubate the wells of the plate with a solution of the antigen or antibody, either overnight or for a specified period of hours. The wells of the plate will then be washed to remove incompletely adsorbed material. Any remaining available surfaces of the wells are then "coated" with a nonspecific protein that is antigenically neutral with regard to the test antisera. These include bovine serum albumin (BSA), casein or solutions of milk powder. The coating allows for blocking of nonspecific adsorption sites on the immobilizing surface and thus reduces the background caused by nonspecific binding of antisera onto the surface.

In ELISAs, it is probably more customary to use a secondary or tertiary detection means rather than a direct procedure. Thus, after binding of a protein or antibody to the well, coating with a non-reactive material to reduce background, and washing to remove unbound material, the immobilizing surface is contacted with the biological sample to be tested under conditions effective to allow immune complex

(antigen/antibody) formation. Detection of the immune complex then requires a labeled secondary binding ligand or antibody, and a secondary binding ligand or antibody in conjunction with a labeled tertiary antibody or a third binding ligand. "Under conditions effective to allow immune complex (antigen/antibody) formation" means that the conditions preferably include diluting the antigens and/or antibodies with solutions such as BSA, bovine gamma globulin (BGG) or phosphate buffered saline (PBS)/Tween. These added agents also tend to assist in the reduction of nonspecific background.

The "suitable" conditions also mean that the incubation is at a temperature or for a period of time sufficient to allow effective binding. Incubation steps are typically from about 1 to 2 to 4 hours or so, at temperatures preferably on the order of 25°C to 27°C, or may be overnight at about 4°C or so. Following all incubation steps in an ELISA, the contacted surface is washed so as to remove non-complexed material. An example of a washing procedure includes washing with a solution such as PBS/Tween, or borate buffer. Following the formation of specific immune complexes between the test sample and the originally bound material, and subsequent washing, the occurrence of even minute amounts of immune complexes may be determined.

To provide a detecting means, the second or third antibody will have an associated label to allow detection. This may be an enzyme that will generate color development upon incubating with an appropriate chromogenic substrate. Thus, for example, one will desire to contact or incubate the first and second immune complex with a urease, glucose oxidase, alkaline phosphatase or hydrogen peroxidase- conjugated antibody for a period of time and under conditions that favor the development of further immune complex formation (e.g., incubation for 2 h at room temperature in a PBS-containing solution such as PBS-Tween).

After incubation with the labeled antibody, and subsequent to washing to remove unbound material, the amount of label is quantified, e.g., by incubation with a chromogenic substrate such as urea, or bromocresol purple, or 2,2'-azino-di-(3-ethyl- benzthiazoline-6-sulfonic acid (ABTS), or H₂O₂, in the case of peroxidase as the enzyme label. Quantification is then achieved by measuring the degree of color generated, e.g., using a visible spectra spectrophotometer. The antibodies of the present invention may also be used in conjunction with both fresh-frozen and/or formalin-fixed, paraffin-embedded tissue blocks prepared for study by immunohistochemistry (IHC). For example, immunohistochemistry may be utilized to characterize SLC 17Al or to evaluate the amount SLCl 7Al in a cell. The method of preparing tissue blocks from these particulate specimens has been successfully used in previous IHC studies of various prognostic factors, and/or is well known to those of skill in the art (Brown ed al, 1990; Abbondanzo et al, 1990; Allred et al, 1990). Other details are provided in the Examples section.

IV. Correlating Expression Levels

The present invention concerns using the expression level of SLC 17Al in cancer cells of a patient to evaluate or predict how that patient will respond to an EGFR-targeted agent. In other embodiments of the invention, there are methods for identifying genes whose expression correlates with a drug phenotype, such as efficacy or toxicity related to the drug. The basis for these methods involves correlating expression of a particular gene with a particular phenotype. In the case of SLC 17Al and sensitivity to an EGFR-targeted agent, the expression levels of SLC 17Al correlate with sensitivity in that higher levels of expression are more strongly indicative of sensitivity than resistance. Alternatively, it is also contemplated that methods involve comparing the level of SLCl 7Al expression from a biological sample with the level of expression observed for cancer cells that are resistant to an EGFR-targeted agent and/or cancer cells that are sensitive to an EGFR-targeted agent and predicting the sensitivity or resistance of the cancer cells in the biological sample based on whether it is closer to a standardized level of expression in the resistant cells and/or in the sensitive cells.

Examples of EGFR-targeted agents are those agents that inhibit specifically EGFR and reduce or inhibit its activity. In particular embodiments, the agent inhibits specifically the tyrosine kinase activity of EGFR. These EGFR tyrosine kinase inhibitor agents include, but are not limited to, AG1478, PD153035, PD153717, erlotinib (brand name TARCEVA®), gefitinib (IRESSA®), lapatinib (TYKERB®), PD158780, PD165557, PD168393, PD168735, PD169541, PD169540, PD166075, PD 183805. It is specifically contemplated that any agent listed above and in the table may also be disclaimed as part of the invention. The PD series is a class of EGFR TKI agents prototyped by AGl 478. In certain embodiments, the EGFR-targeted agent in the invention is AG 1478 or a derivative thereof, which would or could include an of the PD compounds discussed above. TABLE 1

A. Expression Levels

The comparison point for characterizing the SLCl 7Al levels as "higher" can be the expression of SLC17A1 in resistant cells, though it is also contemplated that the levels may be "higher" than the expression in normal (noncancerous cells). It is contemplated that "higher" may represent an increase of about or at least about 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, 200 percent or more, or any range derivable therein, than a standardized or normalized level of expression in cancer cells considered to be resistant to an EGFR-targeted agent. Alternatively, the increase may be expressed in terms of about or at least about an increase of 2-, 3-, 4-, 5-, 6-, 7-, 8-. 9-. 10-fold or more, or any range derivable therein. The expression of SLC 17Al in cells that are considered to be resistant to

EGFR-targeted agents can be evaluated as disclosed in the Examples. In order to define a standardized level of SLCl 7Al expression in resistant and/or sensitive cancer cells from a patient, tumor samples will be obtained from patients treated with an EGFR-targeted therapy. These samples will be evaluated for SLC17A1 expression using a quantitative assay such as RT-PCR. These data then will be analyzed to investigate for a potential relationship between expression and clinical outcomes. The corresponding clinical database will be queried to identify individuals with clinical benefit/sensitivity to EGFR-targeted therapies by looking for subjects who were determined to have protocol defined complete response, partial response or disease stabilization. Clinical resistance will be defined as those subjects that were noted to have progressive disease.

Expression can be evaluated by a number of quantitative assays such as RT- PCR. Moreover, for association of the expression levels with either clinical resistance or sensitivity to the agents, the data will be fitted in a linear model with the expression level as an independent variable and the resistance/sensitivity as a dependable variable. The significance level of the association can be estimated by the associated p values (eg. p<0.05) in the linear regression which shows the probability that the observed level of association is caused by random effects. As with the in vitro data in the Examples, an inverse correlation between the level of SLCl 7Al in the sample and the likelihood that a sample will be resistant to the anti-EGFR agent will be established. This will allow for the determination of a range of expression levels associated with either clinical resistance or sensitivity to the agents.

A resistant cell line is one in which the cell line's GI50 value is greater than (mean + 0.8*SD). Similarly, if a cell line's GI50 is smaller than (mean - 0.8*SD), it is defined as a sensitive cell line

It is also contemplated that a comparison point for characterizing the SLC 17Al level may be that they are similar to a standardized expression level of SLCl 7Al in cells considered sensitive to an EGFR-targeted agent, though it is also contemplated that the levels may also be similar to the expression in normal (noncancerous cells). The term "similar" means that the level of expression is within about or within at least about 1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 185, 190, 195, 200 percent or more, or any range derivable therein, of a standardized level of SLCl 7Al in cancer cells considered to be sensitive to an EGFR- targeted agent. Alternatively, a similar level of expression may be expressed in terms of a level of expression that is within about or within at least about of 2-, 3-, A-, 5-, 6-, 7-, 8-. 9-. 10-fold or more, or any range derivable therein. The cancer cells used for comparison purposes may be one or more different cancer cell lines and/or biological cancer samples (from patients).

B. Arrays

The present invention may involve the use of arrays or data generated from an array. Data may be readily available as is discussed in the Examples, Moreover, an array may be prepared in order to generate data that may then be used in correlation studies.

An array generally refers to ordered macroarrays or microarrays of nucleic acid molecules (probes) that are fully or nearly complementary or identical to a plurality of mRNA molecules or cDNA molecules and that are positioned on a support material in a spatially separated organization. Macroarrays are typically sheets of nitrocellulose or nylon upon which probes have been spotted. Microarrays position the nucleic acid probes more densely such that up to 10,000 nucleic acid molecules can be fit into a region typically 1 to 4 square centimeters. Microarrays can be fabricated by spotting nucleic acid molecules, e.g., genes, oligonucleotides, etc., onto substrates or fabricating oligonucleotide sequences in situ on a substrate. Spotted or fabricated nucleic acid molecules can be applied in a high density matrix pattern of up to about 30 non-identical nucleic acid molecules per square centimeter or higher, e.g. up to about 100 or even 1000 per square centimeter. Microarrays typically use coated glass as the solid support, in contrast to the nitrocellulose-based material of filter arrays. By having an ordered array of complementing nucleic acid samples, the position of each sample can be tracked and linked to the original sample. A variety of different array devices in which a plurality of distinct nucleic acid probes are stably associated with the surface of a solid support are known to those of skill in the art. Useful substrates for arrays include nylon, glass and silicon Such arrays may vary in a number of different ways, including average probe length, sequence or types of probes, nature of bond between the probe and the array surface, e.g. covalent or non- covalent, and the like. The labeling and screening methods of the present invention and the arrays are not limited in its utility with respect to any parameter except that the probes detect expression levels; consequently, methods and compositions may be used with a variety of different types of genes. Representative methods and apparatus for preparing a microarray have been described, for example, in U.S. Patent Nos. 5,143,854; 5,202,231 ; 5,242,974;

5,288,644; 5,324,633; 5,384,261; 5,405,783; 5,412,087; 5,424,186; 5,429,807;

5,432,049; 5,436,327; 5,445,934; 5,468,613; 5,470,710; 5,472,672; 5,492,806; 5,525,464; 5,503,980; 5,510,270; 5,525,464; 5,527,681; 5,529,756; 5,532,128;

5,545,531; 5,547,839; 5,554,501; 5,556,752; 5,561,071; 5,571,639; 5,580,726;

5,580,732; 5,593,839; 5,599,695; 5,599,672; 5,610;287; 5,624,711; 5,631,134;

5,639,603; 5,654,413; 5,658,734; 5,661,028; 5,665,547; 5,667,972; 5,695,940;

5,700,637; 5,744,305; 5,800,992; 5,807,522; 5,830,645; 5,837,196; 5,871,928; 5,847,219; 5,876,932; 5,919,626; 6,004,755; 6,087,102; 6,368,799; 6,383,749;

6,617,112; 6,638,717; 6,720,138, as well as WO 93/17126; WO 95/11995; WO

95/21265; WO 95/21944; WO 95/35505; WO 96/31622; WO 97/10365; WO

97/27317; WO 99/35505; WO 09923256; WO 09936760; WO0138580; WO

0168255; WO 03020898; WO 03040410; WO 03053586; WO 03087297; WO 03091426; WO03100012; WO 04020085; WO 04027093; EP 373 203; EP 785 280;

EP 799 897 and UK 8 803 000; the disclosures of which are all herein incorporated by reference.

It is contemplated that the arrays can be high density arrays, such that they contain 100 or more different probes. It is contemplated that they may contain 1000, 16,000, 65,000, 250,000 or 1,000,000 or more different probes. The probes can be directed to targets in one or more different organisms. The oligonucleotide probes range from 5 to 50, 5 to 45, 10 to 40, or 15 to 40 nucleotides in length in some embodiments. In certain embodiments, the oligonucleotide probes are 20 to 25 nucleotides in length. The location and sequence of each different probe sequence in the array are generally known. Moreover, the large number of different probes can occupy a relatively small area providing a high density array having a probe density of generally greater than about 60, 100, 600, 1000, 5,000, 10,000, 40,000, 100,000, or 400,000 different oligonucleotide probes per cm . The surface area of the array can be about or less than about 1, 1.6, 2, 3, 4, 5, 6, 7, 8, 9, or 10 cm².

Moreover, a person of ordinary skill in the art could readily analyze data generated using an array. Such protocols are disclosed above, and include information found in WO 9743450; WO 03023058; WO 03022421; WO 03029485; WO 03067217; WO 03066906; WO 03076928; WO 03093810; WO 03100448 Al, all of which are specifically incorporated by reference.

C. Kits

Any of the compositions described herein may be comprised in a kit. In a non-limiting example, reagents for evaluating the level of SLCl 7Al expression are included in a kit. In some embodiments, the kit includes reagents for determining the level of SLC 17Al mRNA or protein. It is contemplated that kits may include nucleic acids for amplifying, priming, hybridizing to, or otherwise detecting SLCl 7Al coding sequences. Alternatively, the kit may include reagents that bind to SLC 17Al protein, such as antibodies (monoclonal or polyclonal) that specifically recognize SLC 17Al.

Kits for implementing methods of the invention described herein are specifically contemplated. The kits will thus comprise in some embodiments, in suitable container means, one or more of the following: an enzyme for amplifying or detecting an SLCl 7Al transcript with or capable of detecting an SLC 17Al transcript, one or more buffers, such as reaction buffer, or a hybridization buffer, compounds for preparing amplified nucleic acid sequences or detecting nucleic acid sequences, and components for isolating sequences. Other kits of the invention may include components for making a nucleic acid array comprising polymorphic sequences or sequences that will allow the detection of polymorphisms and/or the absence of such polymorphisms, and thus, may include, for example, a solid support.

All or part of any nucleic acid discussed above may be implemented as part of a kit.

The components of the kits may be packaged either in aqueous media or in lyophilized form. The container means of the kits will generally include at least one vial, test tube, flask, bottle, syringe or other container means, into which a component may be placed, and preferably, suitably aliquoted. Where there is more than one component in the kit, the kit also will generally contain a second, third or other additional container into which the additional components may be separately placed. However, various combinations of components may be comprised in a vial. The kits of the present invention also will typically include a means for containing the nucleic acids, and any other reagent containers in close confinement for commercial sale. Such containers may include injection or blow-molded plastic containers into which the desired vials are retained.

When the components of the kit are provided in one and/or more liquid solutions, the liquid solution is an aqueous solution, with a sterile aqueous solution being particularly preferred.

However, the components of the kit may be provided as dried powder(s). When reagents and/or components are provided as a dry powder, the powder can be reconstituted by the addition of a suitable solvent. It is envisioned that the solvent may also be provided in another container means. In some embodiments, labeling dyes are provided as a dried power. It is contemplated that 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 120, 130, 140, 150, 160, 170, 180, 190, 200, 300, 400, 500, 600, 700, 800, 900, 1000 μg or at least or at most those amounts of dried dye are provided in kits of the invention. The dye may then be resuspended in any suitable solvent, such as DMSO. The container means will generally include at least one vial, test tube, flask, bottle, syringe and/or other container means, into which the nucleic acid formulations are placed, preferably, suitably allocated. The kits may also comprise a second container means for containing a sterile, pharmaceutically acceptable buffer and/or other diluent. The kits of the present invention will also typically include a means for containing the vials in close confinement for commercial sale, such as, e.g., injection and/or blow-molded plastic containers into which the desired vials are retained.

Such kits may also include components that facilitate isolation of nucleic acids. It may also include components that preserve or maintain the nucleic acids or that protect against their degradation. Such components may be nuclease-free or protect against nucleases, such as DNAses or RNAses. Such kits generally will comprise, in suitable means, distinct containers for each individual reagent or solution.

A kit will also include instructions for employing the kit components as well the use of any other reagent not included in the kit. Instructions may include variations that can be implemented. Kits of the invention may also include one or more of the following: Control nucleic acids; nuclease-free water; PEG or dextran; ethanol; acetic acid; sodium acetate; ammonium acetate; guanidinium; detergent; nucleic acid size marker; tube tips; and RNase or DNase inhibitors. It is contemplated that such reagents are embodiments of kits of the invention.

Such kits, however, are not limited to the particular items identified above and may include any reagent used for the manipulation or characterization of nucleic acids that determine or detect polymorphisms discussed herein. The following examples are included to demonstrate preferred embodiments of the invention. It should be appreciated by those of skill in the art that the techniques disclosed in the examples which follow represent techniques discovered by the inventor to function well in the practice of the invention, and thus can be considered to constitute preferred modes for its practice. However, those of skill in the art should, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments which are disclosed and still obtain a like or similar result without departing from the spirit and scope of the invention.

EXAMPLE 1

Materials and Methods for Examples 2-4 Cellular Toxicity Data Cellular toxicity data on 11 EGFR inhibitors known to be potent inhibitors of

HERl and HER2 kinase activity (Chambers, 1992; Wilkinson and Rogers,. 1973) and the FDA-approved EGFR inhibitor erlotinib (Felsenstein, 1985), provided as GI50s (concentrations required to inhibit growth by 50%) were included in this analysis. Amongst them, data on 4 agents (AG1478, PD153035, PD153717, erlotinib) are publicly available at DTP/NCI (World Wide Web at dtp.nci.nih.gov/). The data on the remaining 8 agents (PD158780, PD165557, PD168393, PD168735, PD169541, PD169540, PD166075, PDl 83805) were generated as part of a prior study conducted at NCI (18), and were provided by NCI with the permission of Pfizer, Inc. AG1478, [4-(3-Chloroanilino)-6,7-dimethoxyquinazoline], is the prototype for this class of compounds and is commonly used as a potent and selective inhibitor of HERl in laboratory models. Also included as a control were publicly available data at DTP/NCI on 24 well characterized cytotoxic agents, representing multiple different mechanisms of action. These included 9 alkylating/platinating agents (carmustine, busulfan, carboplatin, lomustine, chlorambucil, cisplatin, melphalan, mitomycin C, oxaliplatin); 4 antimitotics (paclitaxel, docetaxel, vinblastine, vincristine); 5 RNA/DNA antimetabolites (hydroxyurea; 6-thiopurine, 5-azacytidine, 5-fluorouracil, methotrexate); 2 topoisomerase I inhibitors (camptothecin, irinotecan); and 4 topoisomerase II inhibitors (daunorubicin, doxorubicin, mitoxantrone, etoposide). For all of these drugs, if there were replicates with different maximum concentrations, the test with the highest concentration was always used. If there were replicates with the same conditions, the arithmetical mean of the replicates was used. cDNA Microarray Data of the NCI60 Cancer Cell Lines

The baseline expression levels of approximately 8,000 unique genes (a total of 9,706 probes, of which approximately 3,700 represent previously characterized human proteins, approximately 1,900 have homologues in other organisms and the remaining approximately 2,400 were identified only by ESTs) determined by genome- wide cDNA microarrays among the 60 NCI60 cancer cell lines are publicly available at the Genomics and Bioinformatics Group website of NCI (on the Internet at discover.nci.gov/) (the NCI dataset) (Cohen, 2005). An independent dataset available from the Stanford NCI60 Cancer Microarray Project (on the Internet at genome-www.stanford.edu/nci60/) (the Stanford dataset) (R Development Core Team, 2005) was used to compare the results from the NCI dataset and for the verification analyses. Gene expression levels are expressed as either Iog₂(ratio) for the NCI dataset or the raw ratio for the Stanford dataset, where ratio is equal to the red/green fluorescence ration (Cy5:Cy3) after computational balancing of the two channels (Cohen, 2005; R Development Core Team, 2005). The original expression values were downloaded without any further pre-processing.

Identification of Genes Associated with Anticancer Agents. To estimate correlation between gene expression and cellular toxicity of anticancer agents, Pearson correlation coefficients and the associated p values were calculated using a linear model. Given a pair of data points: the expression level of a gene i in cell line j, Xi_j and the cellular toxicity (as measured by logioGI50) of a cell line j for agent k, y^ a linear relationship is modeled as: jfø = βo + β\ Xij+ ε (1) The signs of the Pearson correlation coefficients represent the directionality of the correlation, which can be either inverse or positive. The Pearson correlation coefficients and the associated p values were computed using a built-in function stats: :1m in the R Statistics Package (Tsai et ah, 2003; Meuwissen and Goddard, 2004; Falzon et ah, 1986). Genes that showed significant correlation {e.g., p < 0.05) for all of the 12 EGFR inhibitors were selected. To identify genes that are specifically associated with the EGFR inhibitors, a drug-by-drug "cleaning" procedure was used to remove from this candidate list those genes that are commonly associated with other non-EGFR-targeted cytotoxic agents. Verification Analyses

If not specified, the Stanford dataset was used for verification analyses. i. A bootstrap simulation (Tenenhouse, 2005) was done on the Pearson correlation coefficients for the identified candidate genes. The pseudocode works as follows:

Given N pairs of original cellular toxicity data y^_k and expression data X_/j for gene i, cell line j and agent k,

For each gene i and agent k

{ (a) Randomly select N pairs of y^ and Xy from the original data pool with replacement;

(b) Calculate the Pearson correlation coefficient and the associated p-value by fitting the same linear model as (1);

Repeat steps (a) and (b) for B = 10,000 times;

Calculate the average correlation coefficient; Count the number of significant {e.g., p < 0.05) simulations.

} ii. A fold change analysis on expression levels was done to compare the gene expression in different cytotoxic groups. A cell line was classified into either sensitive or resistant cytotoxic group based on the deviation to mean by its GI50 value. For each drug, if a cell line's GI50 value is greater than (mean + 0.8*SD), it is defined as a resistant cell line. Similarly, if a cell line's GI50 is smaller than (mean - 0.8*SD), it is defined as a sensitive cell line. SD stands for the standard deviation of the GI50 values of the NCI60 cell lines for each drug. The fold change of gene expression was calculated by comparing the average expression values, which were represented by the ratio of Cy5:Cy3, between the resistant and the sensitive groups. A bootstrap simulation (Tenenhouse, 2005) on the fold changes was used to estimate the proportion that a gene is overexpressed (defined as fold change > 1.33) in either cytotoxic group. The bootstrap simulation works as follows:

Suppose there are Ni cell lines within Ti cytotoxic group and N₂ cell lines within T₂ cytotoxic group, for each gene i and agent k {

(a) Randomly select one expression value Xφ- , n from Ni expression values in Ti cytotoxic group, with replacement;

(b) Randomly select one expression value X;_tk, T2 from N₂ expression values in T₂ cytotoxic group, with replacement;

(c) Calculate /J)_n = ^¹¹ (2) and £)_T2 = ^^¹ (3), where D is the fold

change of expression for either cytotoxic group;

Repeat (a), (b) and (c) for B=I 00,000 times;

Count instances with significant fold changes. }

EXAMPLE 2 Identification of Genes Correlated with Cellular Toxicity of EGFR Inhibitors

To identify genes whose expression is correlated with cellular toxicity of EGFR inhibitors, the Pearson correlation coefficients of GI50 and gene expression values were estimated using both the NCI dataset and the Stanford dataset of cDNA microarray chips (Scherf et al, 2000; Ross et ai, 2000) by fitting a linear regression model. The genes with expression levels associated with all EGFR inhibitors at a specified significance level were identified as candidates for further analyses. The complete list of Pearson correlation coefficients and the associated p values for all cDNA probes are provided in Appendix Table Sl. Using the NCI dataset, at a significance level of p < 0.01, none of the genes showed significant correlations with all EGFR inhibitors. At a significance level of p < 0.05, four genes showed significant correlation coefficients for all EGFR inhibitors (Table 1). In other words, for each of these four genes, there was a significant correlation between the gene expression level and the cellular toxicity to each of the EGFR inhibitors. Two of the genes, LOC440138 and an unannotated EST, showed consistent positive correlations (i.e., increased expression results in resistance) and the remaining two genes, SLCl 7Al and RBKS (ribokinase), showed consistent inverse correlations (i.e., increased expression results in sensitivity). Table 1 below shows candidate genes associated with the EGFR TKIs using the NCI dataset. The 4 genes showing significant (p < 0.05) positive or inverse correlation coefficients for all of the 12 agents are listed.

TABLE 1

Correlated with Controls

5ACC' 3ACC' Symbol Chromosome Name Average r^B

R54591 R54592 LOC440138 13ql4.2 Similar to hypothetical protein 0.40 Yes

B230397C21

W88694 W88695 0.33 Yes

AA037228 RBKS 2p23.3 Ribokinase -0.50 Yes

AA004989 AA004990 SLC17A1 6p23-p21.3 Solute carrier family 17 (sodium -0.44 No phosphate), member 1

A: and 3' accession number

B: r, the average Pearson correlation coefficient across the agents.

Controls: non-EGFR agents

Using the Stanford dataset, at a significance level of p < 0.01, none of the genes showed significant correlations with all of the EGFR inhibitors. At a significance level of p < 0.05, 12 genes showed significant correlations. However, among these genes, only RBKS was also in the list of candidate genes using the NCI dataset. Therefore, the inventors tried to get additional overlapping genes between the two datasets by increasing significance levels. When the inventors used a significance level of p < 0.15 (marginally significant), 75 genes showed significant correlations with all EGFR inhibitors. Candidate genes associated with the EGFR inhibitors using the Stanford dataset: the 75 genes showing significant (p < 0.15) positive or inverse correlation coefficients for all of the 12 agents are listed (Table 2). This included the three genes (SLCl 7Al, RBKS, LOC440138) that were significant using the NCI dataset at p < 0.05. These candidate genes were then subjected to a drug-by-drug "cleaning" procedure to remove the genes that were also correlated with other cytotoxic agents.

TABLE 2

Correlated with Controls

5ACC^ 3ACC" Symbol Chromosome Name Average r

R54591 R54592 LOC440138 13ql4.2 Similar to hypothetical protein 0.40 Yes

B230397C21

R53658 R53547 SELB 3q21.3 Elongation factor for selenoprotein 0.36 Yes translation

T54423 T54471 NA NA Transcribed locus, moderately similar to 0.35 Yes

XP_519812.1 similar to hypothetical protein FLJ20533 [Pan troglodytes]

W95741 W95719 NUP62 19ql3.33 Nucleoporin 62kDa 0.33 Yes AA054677 AA056433 SFRS4 Ip35.3 Splicing factor, arginine/serine-rich 4 0.30 Yes H09426 H09077 NA NA Transcribed locus 0.29 Yes N94810 N63512 C9orf5 9q31 Chromosome 9 open reading frame 5 -0.27 Yes AA040901 AA037773 RBMSl 2q24.2 RNA binding motif, single stranded -0.27 Yes interacting protein 1

AA045045 AA045046 RBMSl 2q24.2 RNA binding motif, single stranded -0.29 Yes interacting protein 1

T99915 R00266 PLG 6q26 Plasminogen -0.29 Yes R79490 R79223 MMP2 16ql3-q21 Matrix metalloproteinase 2 (gelatinase A, -0.29 Yes

72kDa gelatinase, 72kDa type IV collagenase)

N46894 N49585 ELYS Iq44 ELYS transcription factor-like protein -0.30 Yes

TMBS62

T95281 T95282 SPTLC2 14q24.3-q31 Serine palmitoyltransferase, long chain base -0.30 Yes subunit 2

AA039439 DHX34 19ql3.3 DEAH (Asp-Glu-Ala-His) box polypeptide -0.30 Yes

34

AA034276 AA032067 ARHGAPl I lpl2-ql2 Rho GTPase activating protein 1 -0.30 Yes AA053685 AA053240 NAGK 2pl3.3 N-acetylglucosamine kinase -0.30 Yes W77795 W72109 AATF 17ql l.2-ql2 Apoptosis antagonizing transcription factor -0.30 Yes AA044117 AA044290 SLC39A1 Iq21 Solute carrier family 39 (zinc transporter), -0.31 Yes member 1

Correlated with Controls

5ACCT 3AC(T Symbol Chromosome Name Average r^B

AA044628 AA043507 KIF23 15q23 Kinesin family member 23 -0.31 Yes T83194 T90664 CYP4A11 Ip33 Cytochrome P450, family 4, subfamily A, -0.32 Yes polypeptide 11

W47361 W47362 FOLR3 I lql3 Folate receptor 3 (gamma) -0.32 Yes R12204 R39927 NA NA Clone TESTIS-814 mRNA sequence -0.32 Yes H51156 H51118 PTPRS 19pl3.3 Protein tyrosine phosphatase, receptor type, -0.33 Yes

S

AA004989 AA004990 SLC17A1 6p23-p21.3 Solute carrier family 17 (sodium -0.33 No phosphate), member 1

W76572 W72569 NUDTl 7p22 Nudix (nucleoside diphosphate linked -0.33 Yes moiety X)-type motif 1

AA037538 AA037454 DKFZP564J0 I lql3.1 DKFZP564J0863 protein -0.33 Yes 863 AA056070 AA056022 CSPG2 5ql4.3 Chondroitin sulfate proteoglycan 2 -0.33 Yes (versican)

W37230 W37813 GPI7 4pl6.3 GPI7 protein -0.33 Yes H79887 H79794 TLEl 9q21.32 Transducin- like enhancer of split 1 (E(spl) -0.33 Yes homolog, Drosophila)

W81411 PEGlO 7q21 Paternally expressed 10 -0.33 Yes

N77387 N64793 COQ6 14q24.3 Coenzyme Q6 homolog (yeast) -0.33 Yes AA036956 KCNJ8 12pl l.23 Potassium inwardly-rectifying channel, -0.33 Yes subfamily J, member 8

W30724 N99063 TRUBl 10q25.3 TruB pseudouridine (psi) synthase homolog -0.34 Yes 1 (E. coli)

AA040667 AA040550 AMBP 9q32-q33 Alpha- 1 -microglobulin/bikunin precursor -0.34 Yes AA035021 AA035488 LAMCl Iq31 Laminin, gamma 1 (formerly LAMB2) -0.34 Yes AA056466 HDGF Iq21-q23 Hepatoma-derived growth factor (high- -0.34 Yes mobility group protein 1 -like)

N63138 PRICKLEl 12ql2 Prickle-like 1 (Drosophila) -0.35 Yes N20008 PLCB4 2Op 12 Phospholipase C, beta 4 -0.35 Yes N34799 NA 2p23.2 LOC440853 -0.35 Yes

W76024 W72468 FAM13A1 4q22.1 Family with sequence similarity 13, -0.35 Yes

Correlated with Controls

5ACC^ 3ACC' Symbol Chromosome Name Average r member Al

N34396 PCSK5 9q21.3 Proprotein convertase subtilisin/kexin type -0.35 Yes

AA055476 NA Ip36.33 Similar to C219-reactive peptide -0.35 Yes

W90290 W90633 AKRlBl 7q35 Aldo-keto reductase family 1 , member B 1 -0.35 Yes

(aldose reductase)

AA031396 AA031265 PSMD4 Iq21.2 Proteasome (prosome, macropain) 26S -0.35 Yes subunit, non-ATPase, 4

AA032024 AA031913 KIAA0251 16pl3.11 KIAA0251 protein - -00..3355 Yes

AA037443 MT2A 16ql3 Metallothionein 2A - -00..3355 Yes

AA040627 AA040165 LEPR Ip31 Leptin receptor - -00..3366 Yes

W79558 W79526 CLDN7 17pl3 Claudin 7 - -00..3366 Yes

AA007510 AA007511 DDX47 12pl3.2 DEAD (Asp-Glu-Ala-Asp) box polypeptide - -00..3366 Yes

47

W49562 W49563 PLCB4 2Op 12 Phospholipase C, beta 4 - -00..3366 Yes

AA057288 AA058733 TBLlX Xp22.3 Transducin (beta)-like lX-linked - -00..3377 Yes

AA028007 FBXL2 3p23 F-box and leucine-rich repeat protein 2 - -00..3377 Yes

N50356 N51577 TBC1D12 10q23.33 TBCl domain family, member 12 - -00..3377 Yes

AA043579 AA043580 PTPN13 4q21.3 Protein tyrosine phosphatase, non-receptor - -00..3377 Yes type 13 (APO- 1/CD95 (Fas)-associated phosphatase)

AA058429 AA056750 CKLFSF3 16q22.1 Chemokine-like factor super family 3 - -00..3377 Yes

N29100 N20199 TXNDC5 6p24.3 Thioredoxin domain containing 5 - -00..3377 Yes

AA035526 MPZLl Iq24.2 Myelin protein zero-like 1 - -00..3377 Yes

N31358 N21401 LEPR Ip31 Leptin receptor - -00..3377 Yes

R64233 R64132 SDPR 2q32-q33 Serum deprivation response - -00..3388 Yes

(phosphatidylserine binding protein)

H02935 H04238 FAS 10q24.1 Fas (TNF receptor superfamily, member 6) - -00..3388 Yes

AA033947 LAPTM4B 8q22.1 Lysosomal associated protein - -00..3399 Yes transmembrane 4 beta

W24901 N95790 ALDH3B1 I lql3 Aldehyde dehydrogenase 3 family, member -0.40 Yes

Bl

Correlated with Controls

5ACC^ 3ACC^ Symbol Chromosome Name Average r

T65630 T65562 CD24 6q21 CD24 antigen (small cell lung carcinoma -0.40 Yes cluster 4 antigen)

AA031663 AA031664 CENTA2 17ql l.2 Centaurin, alpha 2 -0.43 Yes

R99201 R99202 RBMS2 12ql3.3 RNA binding motif, single stranded -0.43 Yes interacting protein 2

N90843 N64505 C6orfl55 6ql3 Chromosome 6 open reading frame 155 -0.43 Yes

N77803 N62892 C10orf65 10q24.2 Chromosome 10 open reading frame 65 -0.43 Yes

W72090 GLS 2q32-q34 Glutaminase -0.45 Yes

R28233 R27977 FCHO2 5ql3.2 FCH domain only 2 -0.45 Yes

R38231 R38232 HUMPPA 17q25.1 Paraneoplastic antigen -0.45 Yes

AA056228 -0.46 Yes

AA054642 -0.47 Yes

W00613 N63302 IQWDl Iq24.2 Glycine cleavage system protein H -0.48 Yes

(aminomethyl carrier)

W03155 N74443 -0.51 Yes

AA037228 RBKS 2p23.3 Ribokinase -0.51 Yes

A: 5ACC and 3ACC: 5' accession number and 3' accession number B: r, the average Pearson correlation coefficient across the agents. Controls: non-EGFR agents

EXAMPLE 3 Identification of EGFR-specific Candidate Genes

Because there was an interest in identifying those genes with expression levels specifically associated with the cellular toxicity to a class of EGFR-targeted anticancer agents, a representative subset of 24 cytotoxic agents was also examined. These control drugs represent a variety of mechanisms, which are functionally distinct from the EGFR TKIs. The complete data including the Pearson correlation coefficients and the associated p values for the 24 non-EGFR agents are shown in Supplemental Table S2, which is provided on a CD filed herewith, which is hereby incorporated by reference in its entirety. To identify EGFR-specific candidate genes, a drug-by-drug "cleaning" procedure was applied to remove from our candidate gene lists those genes that were also significant for one of the 24 drugs at each step. Using the NCI dataset, among the four original candidates: SLC17A1, RBKS, LOC440138 and an unannotated EST, only SLCl 7Al was not significantly associated with any one of the 24 control drugs at significance level of p < 0.05 (Table 1). FIG. 1 shows the distribution of the Pearson correlation coefficients and the associated p values of SLC 17Al for all of the 36 drugs including 12 EGFR inhibitors and 24 control agents. Obviously, the EGFR inhibitors as a group are different from the 24 control drugs in terms of correlations with the expression of SLC17A1. The expression of SLC17A1 and GI50 were significantly correlated for all of the 12 EGFR inhibitors, while its expression was not significantly correlated with the GI50 of any of the 24 control agents. Using the Stanford dataset, SLCl 7Al was again the only gene that showed no significant correlation with any of the 24 control agents at significance level of p < 0.15 (Table 2, FIG. 2). Even after the inventors performed the "drug-by-drug" cleaning using all of the 171 drugs in the NCI Standard Anticancer Agents Database that is available at the DTP website, SLC17A1 was only found to be significantly associated with 4-ipomeanol, a drug previously developed for NSCLC (Gottesman and Ambudkar, 2001). Thus, SLC17A1 was identified as a potential candidate gene with expression inversely correlated specifically with the GI50 of EGFR-targeted anticancer agents. EXAMPLE 4 Verification Analyses of SLC17A1 as an EGFR-specific Gene

A bootstrap simulation on the Pearson correlation coefficients between the expression of SLC17A1 and the cellular toxicity across the NCI60 cell lines was performed to provide an empirical estimation of the false discovery rate (Tenenhouse and Sabbagh, 2002; Soumounou et al, 2001). The inventors randomly selected paired data points of gene expression and cellular toxicity as represented by GI50 from the original data pool. The Pearson correlation coefficient and the associated p value were calculated for each of the simulated datasets. The procedure was repeated for B = 10,000 times.

As shown in FIG. 3, the distribution of the pooled 120,000 (10,000 x 12 agents) Pearson correlation coefficients for the 12 EGFR inhibitors is clearly different from the 240,000 (10,000x24 agents) Pearson correlation coefficients of the 24 control agents (t -test p-value < 2.2 x 10^~16). Noticeably, the correlation coefficients for the control agents are distributed around 0, which implies no correlation between the gene expression and cellular toxicity. In contrast, the correlation coefficients for the EGFR inhibitors are distributed around approximately -0.35, which implies a pretty strong inverse correlation. The overlapping area of the distributions, which represents the numbers of correlation coefficients that fall into either group, is approximately 40%. In other words, our empirical false discovery rate was estimated as 40%, which represents the chance that the "real" correlation between the expression of SLC17A1 and the cellular toxicity of the EGFR inhibitors is indeed not different from that estimated using the control agents.

Experiments were conducted to confirm that SLC 17Al was overexpressed in cell lines that were sensitive to the EGFR inhibitors. The NCI60 cancer cell lines were classified into different cytotoxic groups: resistant group or sensitive group based on the cellular toxicity data as measured by GI50 for each EGFR inhibitor (Supplemental

Table S3, which is provided in the CD that is incorporated by reference in its entirety). Because there was an interest in knowing the expression patterns of SLCl 7Al in either resistant or sensitive cell lines, the fold change of expression levels was calculated by comparing the two cytotoxic groups. A bootstrap simulation method was designed to estimate the distribution of the occurrences of gene overexpression in either resistant or sensitive group of cell lines. As shown in FIG. 4, SLC 17Al never showed significant overexpression (fold change > 1.33) in the resistant cell lines. Its overexpression was only observed in the sensitive cell lines. This observation clearly supports the association analysis in which the expression of SLC 17Al showed significant inverse correlation with the GI50 for the EGFR inhibitors.

EXAMPLE 5 Confirmation of EGFR Expression in Cancer Cells

An independent analysis of SLCl 7Al expression in different cells lines was undertaken to confirm the expression data previously reported. This was done using

RT-PCR. Total RNA was extracted from cell pellets of NCI60 panel by using the

RNeasy min kit (Qiagen, Germany). Complementary DNA (cDNA) of each sample was then obtained through reverse-transcription of 1 μg total RNA using Superscript II reverse transcriptase with random hexamer primers according to manufacturer's protocol (Invitrogen). PCR reaction was then performed to amplify the NPTl

(SLC 17Al) gene. The β-actin gene was used as a control. Each reaction was carried out with 1 unit of Hotstar Taq polymerase (Qiagen), 2.4 mM Mg²⁺ and 2 μl cDNA in a 40 μl final volume. In order to detect both high and low level of expression, the reactions were cycled either 35 or 38 times with 95°C for 10 s, 56°C for 10 s and 72°C for 20 s after an initial denaturation of 95°C for 12 min. Primers for NPTl and

Actin were as follows:

NPT1-E5F 5'-GGCTGGCCCATGGTCTTCTAT-S' (SEQ ID NO:3) NPT1-E6R 5'-CTGGACCAGGGAGGATGTGATG-S' (SEQ ID NO:4) Actin 308F 5'-ACGTGGACATCCGCAAAGAC-S' (SEQ ID NO:5) Actin 308R 5'-CAAGAAAGGGTGTAACGCAACTA-S ' (SEQ ID NO:6).

Results: With PCR of 35 cycles, NPTl was amplified from 6 cell lines:

ACHN, TK-10, CAKI-I, A549, A498 and 786-0. To detect the cells with lower expression level, PCR was performed again with 38 cycles. As a result, another 19 cell lines showed a detectable level of NPTl gene expression. These included IGR- OVl, NCI-H23, SK-MEL-2, UO-31, SN12C, DU-145, SK-OV-3, OVCAR-8, OVCAR-5, OVCAR-4, NCI-H522, NCI-H460, UACC-62, UACC-257, SK-MEL-5, SK-MEL-28, CCRF-CEM, SW-620 and HCC-2998 (Table 3).

When this data was compared to the Microarray data using the same linear modeling methods (Table 4), overall, the expression of SLC17A1 is still inversely correlated with the cytotoxicty (GI₅₀) as determined using the same modeling methods described above. Generally, this experiment biologically confirmed the in silico results above that were based on the public microarray data.

Table 3

RT-PCR semi-quantitative results for SLC17A1 (NPTl) expression in the NCI₆₀ cell lines

Table 4

Results of linear regressions on cytotoxicity (GI50) and RTPCR expression of

SLC 17Al

REFERENCES

The following references, to the extent that they provide exemplary procedural or other details supplementary to those set forth herein, are specifically incorporated herein by reference.

U.S. Patent 5,610;287

U.S. Patent 3,817,837

U.S. Patent 3,850,752 U.S. Patent 3,939,350

U.S. Patent 3,996,345

U.S. Patent 4,275,149

U.S. Patent 4,277,437

U.S. Patent 4,366,241 U.S. Patent 4,683,195

U.S. Patent 4,683,202

U.S. Patent 4,800,159

U.S. Patent 4,883,750

U.S. Patent 5,143,854 U.S. Patent 5,202,231

U.S. Patent 5,242,974

U.S. Patent 5,279,721

U.S. Patent 5,288,644

U.S. Patent 5,324,633 U.S. Patent 5,384,261

U.S. Patent 5,405,783

U.S. Patent 5,412,087

U.S. Patent 5,424,186

U.S. Patent 5,429,807 U.S. Patent 5,432,049

U.S. Patent 5,436,327

U.S. Patent 5,445,934 U.S. Patent 5,468,613

U.S. Patent 5,470,710

U.S. Patent 5,472,672

U.S. Patent 5,492,806 U.S. Patent 5,503,980

U.S. Patent 5,510,270

U.S. Patent 5,525,464

U.S. Patent 5,525,464

U.S. Patent 5,527,681 U.S. Patent 5,529,756

U.S. Patent 5,532,128

U.S. Patent 5,545,531

U.S. Patent 5,547,839

U.S. Patent 5,554,501 U.S. Patent 5,556,752

U.S. Patent 5,561,071

U.S. Patent 5,571,639

U.S. Patent 5,580,726

U.S. Patent 5,580,732 U.S. Patent 5,593,839

U.S. Patent 5,599,672

U.S. Patent 5,599,695

U.S. Patent 5,624,711

U.S. Patent 5,631,134 U.S. Patent 5,639,603

U.S. Patent 5,654,413

U.S. Patent 5,658,734

U.S. Patent 5,661,028

U.S. Patent 5,665,547 U.S. Patent 5,667,972

U.S. Patent 5,695,940

U.S. Patent 5,700,637

U.S. Patent 5,744,305

U.S. Patent 5,800,992 U.S. Patent 5,807,522

U.S. Patent 5,830,645

U.S. Patent 5,837,196

U.S. Patent 5,840,873 U.S. Patent 5,843,640

U.S. Patent 5,843,650

U.S. Patent 5,843,651

U.S. Patent 5,843,663

U.S. Patent 5,846,708 U.S. Patent 5,846,709

U.S. Patent 5,846,717

U.S. Patent 5,846,726

U.S. Patent 5,846,729

U.S. Patent 5,846,783 U.S. Patent 5,847,219

U.S. Patent 5,849,481

U.S. Patent 5,849,486

U.S. Patent 5,849,487

U.S. Patent 5,849,497 U.S. Patent 5,849,546

U.S. Patent 5,849,547

U.S. Patent 5,851,772

U.S. Patent 5,853,990

U.S. Patent 5,853,992 U.S. Patent 5,853,993

U.S. Patent 5,856,092

U.S. Patent 5,858,652

U.S. Patent 5,861,244

U.S. Patent 5,863,732 U.S. Patent 5,863,753

U.S. Patent 5,866,331

U.S. Patent 5,866,366

U.S. Patent 5,871,928

U.S. Patent 5,876,932 U.S. Patent 5,882,864

U.S. Patent 5,900,481

U.S. Patent 5,905,024

U.S. Patent 5,910,407 U.S. Patent 5,912,124

U.S. Patent 5,912,145

U.S. Patent 5,912,148

U.S. Patent 5,916,776

U.S. Patent 5,916,779 U.S. Patent 5,919,626

U.S. Patent 5,919,626

U.S. Patent 5,919,630

U.S. Patent 5,922,574

U.S. Patent 5,925,517 U.S. Patent 5,928,862

U.S. Patent 5,928,869

U.S. Patent 5,928,905

U.S. Patent 5,928,906

U.S. Patent 5,929,227 U.S. Patent 5,932,413

U.S. Patent 5,932,451

U.S. Patent 5,935,825

U.S. Patent 5,939,291

U.S. Patent 5,942,391 U.S. Patent 6,004,755

U.S. Patent 6,087,102

U.S. Patent 6,368,799

U.S. Patent 6,383,749

U.S. Patent 6,472,157 U.S. Patent 6,617,112

U.S. Patent 6,638,717

U.S. Patent 6,720,138 European Appln. 320 308

European Appln. 329 822

European Appln. 373 203

European Appln. 785 280 European Appln. 799 897

GB Appln. 2 202 328

PCT Appln. PCT/US87/00880

PCT Appln. PCT/US89/01025

PCT Appln. WO 95/35505 PCT Appln. WO 99/35505

PCT Appln. WO 96/31622

PCT Appln. WO 97/27317

PCT Appln. WO 95/21944

PCT Appln. WO 95/21265 PCT Appln. WO 93/17126

PCT Appln. WO 95/11995

PCT Appln. WO 88/10315

PCT Appln. WO 97/10365

PCT Appln. WO 90/07641 PCT Appln. WO 89/06700

PCT Appln. WO 0138580

PCT Appln. WO 0168255

PCT Appln. WO 03020898

PCT Appln. WO 03022421 PCT Appln. WO 03023058

PCT Appln. WO 03029485

PCT Appln. WO 03040410

PCT Appln. WO 03053586

PCT Appln. WO 03066906 PCT Appln. WO 03067217

PCT Appln. WO 03076928

PCT Appln. WO 03087297

PCT Appln. WO 03091426

PCT Appln. WO 03093810 PCT Appln. WO 03100012 PCT Appln. WO 03100448A1 PCT Appln. WO 04020085 PCT Appln. WO 04027093 PCT Appln. WO 9743450 PCT Appln. WO 09923256 PCT Appln. WO 09936760 UK Appln. 8 803 000

Abbondanzo et al , Breast Cancer Res. Treat. , 16:182(151), 1990.

Akimoto et al, Clin. Cancer Res. 5:2884-2890, 1999.

Allred et al, Arch. Surg., 125(l):107-113, 1990.

Amador et al., Cancer Res., 64(24):9139-9143, 2004.

Amador et al, Cancer Res., 64(24):9139-9143, 2004. Arteaga, J. Clin. Oncol, 19: 32S-40S, 2001.

Arteaga, Semin. Oncol, 5(14):3-9, 2003.

Ausubel et al, In: Current Protocols in Molecular Biology, John, Wiley & Sons, Inc, New York, 1996.

Bellus, J. Macromol ScL Pure Appl Chem., A31(1): 1355-1376, 1994. Bishop et al, Oncogene, 21(1): 119-127, 2002.

Blower et al, Pharmaco genomics J., 2:259-271, 2002.

Boyd, In: Anticancer drug development guide: preclinical screening, clinical trials and approval, Teicher (Ed.), Totowa, NJ: Humana Press 23-41, 1995.

Brandt et al, Cancer Res., 64:7-12, 2004. Brown et al Immunol Ser., 53:69-82, 1990.

Buerger et al, Cancer Res., 60(4):854-857, 2000.

Cappuzzo et al, J. Natl. Cancer Inst, 97(9):643-655, 2005.

Chambers, In: Linear models. Chapter 4 of Statistical Models, Chambers and Hastie

(Eds.), Wadsworth & Brooks/Cole, 1992. Chou et al, Clin. Cancer Res., 11(10):3750-3757, 2005.

Ciardiello and Tortora, Expert Opin. Investig. Drugs, 11(6):755-768, 2002.

Cohen et al, Oncologist, 10(7):461-466, 2005.

De Jager et al, Semin. Nucl Med, 23(2):165-179, 1993.

Deb et al, Oncogene, 9:1341-1349, 1994. Doolittle and Ben-Zeev, Methods MoI Biol, 109:215-237, 1999.

Eccles et al, Invasion Metastasis, 14:337-348, 1994.

Falzon et α/., Cancer Res., 46(7):3484-3489, 1986.

Felsenstein, Evolution, 39:783-791, 1985. Fodor et al, Biochemistry, 30(33):8102-8108, 1991.

Frohman, In: PCR Protocols: A Guide To Methods And Applications, Academic Press, N. Y., 1990.

Gebhardt e? α/., J. Biol Chem., 274(19):13176-13180, 1999.

Golsteyn, Drug Discov. Today, 9(14):587, 2004. Gottesman and Ambudkar, J Bioenerg. Biomembr., 33(6):453-458, 2001.

Grandis et al, Nature Med., 2:237-240, 1996.

Gulbis and Galand, Hum. Pathol, 24(12):1271-1285, 1993.

Hacia et al, Nature Genet., 14:441-449, 1996.

Haley et al, Oncogene Res., l(4):375-396, 1987. Han et al, J. Clin. Oncol, 23(11):2493-2501, 2005.

Harlow and Lane, In: Antibodies, a Laboratory Manual, Cold Spring Harbor Laboratory, 139-281, 1988.

Hudson et al, MoI Endocrinol, 3:400-408, 1989.

Innis et al, Pr oc Natl Acad Sci USA, 85(24):9436-9440, 1988. Ishii et al, Proc. Natl Acad. Sci. USA, 82(15):4920-4924, 1985.

Ishii et al, Proc. Natl Acad. Sci. USA, 82(15):4920-4924, 1985.

Jain et al, Proc. Natl. Acad. Sci. USA, 102(33): 11858-11863, 2005.

Johnson et al, J. Biol Chem., 263(12):5693-5699, 1988.

Kageyama et al, J. Biol. Chem., 263(13):6329-6336, 1988. Kwoh et al, Proc. Natl Acad. Sci. USA, 86:1173, 1989.

Maekawa et al, J. Biol Chem., 264(10):5488-5494, 1989.

Mendelsohn, Endocr. Relat. Cancer, 8:3-9, 2001.

Meuwissen and Goddard, Genet. SeI. Evol., 36(2): 191-205, 2004.

Mitsudomi et al, J. Clin. Oncol, 23(11):2513-2520, 2005. Monks et al, Anticancer Drug D es., 12:533-541, 1997.

Moter and Gobel, J. Microbiol. Methods, 41(2):85-112, 2000.

Nakamura et al, In: Handbook of Experimental Immunology (4^th Ed.), Weir et al (Eds.), 1 :27, Blackwell Scientific Publ, Oxford, 1987.

Nath and Johnson, Biotech. Histochem., 73(l):6-22, 1998. Nicholson et al, Eur. J. Cancer, 37:S9-15, 2001.

Ohara et al, Proc. Natl. Acad. Sci. USA, 86:5673-5677, 1989.

Patel et al, Crit. Rev. Oncol. Hematol., 50(3):175-186, 2004.

Pease et al, Proc. Natl Acad. Sci. USA, 91 :5022-5026, 1994. Perez-Soler, Clin. Cancer Res., 10(12 Pt 2):4238s-4240s, 2004.

R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, ISBN 3-900051-07- 0, URL http://www.R-project.org, 2005.

Reimer et al, Pflugers Arch., 447(5):629-633, 2004. Reimer et al, Pflugers Arch., 447(5):629-633, 2004.

Salomon et al, Crit. Rev. Oncol. Hematol 19:183-232, 1995.

Sambrook et al, In: Molecular cloning, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY, 2001.

Sano et al, Science, 258(5079):120-122, 1992. Shoemaker et al. , Nature Genetics, 14:450-456, 1996.

Soumounou et al, Am. J. Physiol Renal. Physiol, 281(6):F1082-91, 2001.

Stinson e^ α/., Anticancer Res., 12:1035-1053, 1992.

Subler e^ α/., Oncogene, 9:1351-1359, 1994.

Takano et al, J. Clin. Oncol, 23(28):6829-6837, 2005. Takano et al, J. Clin. Oncol, 23(28):6829-6837, 2005.

Taron e^ α/., Clin. Cancer Res., l l(16):5878-5885, 2005.

Tenenhouse and Sabbagh, Pflugers. Arch., 444(3):317-326, 2002.

Tenenhouse, Annu. Rev. Nutr., 25:197-214, 2005.

Thomas, Cancer Nurs., 26(6 Suppl):21S-25S, 2003. Tsai CA et al, Biometrics, 59(4): 1071-1081, 2003.

Tysnes et al, Invasion Metastasis, 17:270-280, 1997.

Wakeling, Curr. Opin. Pharmacol, 2(4):382-387, 2002.

Walker et al, Nucleic Acids Res. 20(7):1691-1696, 1992.

Weier et al, Expert Rev. MoI Diagn., 2(2):109-l 19, 2002. Wilkinson and Rogers, Applied Statistics, 22:392-399, 1973.

Wosikowski et al, Biochim. Biophys. Acta, 1497:215-226, 2000.

Xu et al Proc. Natl. Acad. Sci. USA, 81 :7308-7312, 1984.

Xu et al, J. Biol Chem., 268:16065-16073, 1993.

Claims

1. A method for predicting the efficacy of an epidermal growth factor receptor (EGFR)-targeted agent in a patient comprising: a) obtaining a sample containing cancer cells from the patient; b) assaying the level of SLC17A1 expression in the cells; and, c) treating the patient with an EGFR-targeted agent or another anticancer agent depending on the level of SLC17A1 expression in the cells.

2. The method of claim 1, wherein the level of SLC17A1 expression in the cells is compared with a level of SLCl 7Al expression from EGFR-targeted agent sensitive cells.

3. The method of claim 2, wherein EGFR-targeted agent sensitive cells are cancer cells.

4. The method of claim 2, wherein EGFR-targeted agent sensitive cells are normal cells.

5. The method of claim 1, wherein the level of SLCl 7Al in the cells is compared with a level of SLCl 7Al expression from EGFR-targeted agent resistant cancer cells.

6. The method of claim 5, wherein the level of SLC 17Al expression in the sample is not higher than the level of SLC17A1 expression from EGFR-targeted agent resistant cancer cells and the patient is not treated with an EGFR-targeted agent but is treated with another anticancer agent.

7. The method of claim 5, wherein the level of SLC17A1 expression in the sample is higher than the level of SLC 17Al expression from EGFR-targeted agent resistant cancer cells and the patient is treated with an EGFR-targeted agent.

8. The method of claim 1, wherein the level of SLC 17Al expression is assayed by measuring SLC17A1 protein or RNA in the cells.

9. The method of claim 8, wherein the level of SLC 17Al expression is assayed by measuring SLCl 7Al RNA in the cells.

10. The method of claim 9, wherein SLC 17Al RNA is measured using a probe and/or primers.

11. The method of claim 10, wherein SLC 17Al RNA is measured using nucleic acid amplification.

12. The method of claim 10, wherein the probe and/or primers are labeled directly or indirectly.

13. The method of claim 12, wherein the label is fluorescent, colorimetric, enzymatic, or radioactive.

14. The method of claim 8, wherein the level of SLC17A1 expression is assayed by measuring SLC 17Al protein in the cells.

15. The method of claim 14, wherein SLC17A1 protein is measured using a protein that specifically binds SLC 17Al protein.

16. The method of claim 15, wherein the protein that specifically binds SLC17A1 protein is an antibody.

17. The method of claim 1 , wherein the sample is a tumor biopsy.

18. The method of claim 1 , further comprising identifying a patient who may be treated with an EGFR-targeted agent or who was treated with an EGFR-targeted agent.

19. The method of claim 18, wherein the patient has been diagnosed with a malignant solid tumor or cancer of the lung, breast, prostate, colon, kidney, ovary, or head and neck.

20. The method of claim 18, wherein the patient has a recurrent cancer or has failed a previous anticancer therapy.

21. The method of claim 1 , wherein the EGFR-targeted agent is a tyrosine kinase inhibitor (TKI).

22. The method of claim 1 , wherein the EGFR-targeted agent is a monoclonal antibody.

23. A method for predicting efficacy of an EGFR-targeted agent in a cancer patient comprising: a) having a sample containing cancer cells from the patient obtained from the patient; b) obtaining information regarding the level of SLC 17 A 1 expression in the cells, and, c) treating the patient with an EGFR-targeted agent or another anticancer agent depending on the level of SLCl 7Al expression in the cells.

24. The method of claim 23, wherein the level of SLC 17Al expression in the cells is compared with a level of SLCl 7Al expression from EGFR-targeted agent sensitive cells.

25. The method of claim 24, wherein EGFR-targeted agent sensitive cells are cancer cells.

26. The method of claim 24, wherein EGFR-targeted agent sensitive cells are normal cells.

27. The method of claim 23, wherein the level of SLC 17Al in the cells is compared with a level of SLC 17Al expression from EGFR-targeted agent resistant cancer cells.

28. The method of claim 27, wherein the level of SLC17A1 expression in the sample is not higher than the level of SLC 17Al expression from EGFR-targeted agent resistant cancer cells and the patient is not treated with an EGFR-targeted agent but is treated with another anticancer agent.

29. The method of claim 27, wherein the level of SLC17A1 expression in the sample is higher than the level of SLCl 7Al expression from EGFR-targeted agent resistant cancer cells and the patient is treated with an EGFR-targeted agent.

30. The method of claim 23, wherein the sample is obtained by a third party.

31. The method of claim 23, wherein the sample is a tumor biopsy.

32. The method of claim 24, further comprising identifying a patient who may be treated with an EGFR-targeted agent or who was treated with an EGFR-targeted agent.

33. The method of claim 32, wherein the patient has been diagnosed with a malignant solid tumor or cancer of the lung, breast, prostate, colon, kidney, ovary, or head and neck.

34. The method of claim 32, wherein the patient has a recurrent cancer or has failed a previous anticancer therapy.

35. The method of claim 23, wherein the EGFR-targeted agent is a tyrosine kinase inhibitor (TKI).

36. The method of claim 23, wherein the EGFR-targeted agent is a monoclonal antibody.

37. A method for assisting in predicting efficacy of an EGFR-targeted agent in a cancer patient comprising a) obtaining a sample containing cancer cells from the patient; b) assaying the level of SLC 17Al expression in the cells; and, c) reporting information regarding the level of SLC 17Al expression in the cells.

38. The method of claim 37, further comprising correlating the level of SLC17A1 expression in the sample with sensitivity and/or resistance to an EGFR-targeted agent.

39. The method of claim 38, wherein the level of SLC17A1 expression in the cells is compared with a level of SLCl 7Al expression from EGFR-targeted agent sensitive cells.

40. The method of claim 39, wherein EGFR-targeted agent sensitive cells are cancer cells.

41. The method of claim 39, wherein EGFR-targeted agent sensitive cells are normal cells.

42. The method of claim 38, wherein the level of SLC 17Al in the cells is compared with a level of SLCl 7Al expression from EGFR-targeted agent resistant cancer cells.

43. The method of claim 42, wherein the level of SLC 17Al expression in the sample is not higher than the level of SLCl 7Al expression from EGFR-targeted agent resistant cancer cells and the patient is not treated with an EGFR-targeted agent but is treated with another anticancer agent.

44. The method of claim 42, wherein the level of SLC 17Al expression in the sample is higher than the level of SLCl 7Al expression from EGFR-targeted agent resistant cancer cells and the patient is treated with an EGFR-targeted agent.

45. The method of claim 37, wherein the level of SLC17A1 expression is assayed by measuring SLC 17Al protein or RNA in the cells.

46. The method of claim 45, wherein the level of SLC17A1 expression is assayed by measuring SLC 17Al RNA in the cells.

47. The method of claim 46, wherein SLC17A1 RNA is measured using a probe and/or primers.

48. The method of claim 47, wherein SLCl 7Al RNA is measured using nucleic acid amplification.

49. The method of claim 47, wherein the probe and/or primers are labeled directly or indirectly.

50. The method of claim 49, wherein the label is fluorescent, colorimetric, enzymatic, or radioactive.

51. The method of claim 45, wherein the level of SLC 17Al expression is assayed by measuring SLC17A1 protein in the cells.

52. The method of claim 51 , wherein SLC 17Al protein is measured using a protein that specifically binds SLCl 7Al protein.

53. The method of claim 52, wherein the protein that specifically binds SLC 17Al protein is an antibody.

54. The method of claim 37, wherein the sample is a tumor biopsy.

55. The method of claim 37, wherein the patient has been diagnosed with a malignant solid tumor or cancer of the lung, breast, prostate, colon, kidney, ovary, or head and neck.

56. The method of claim 37, wherein the patient has a recurrent cancer or has failed a previous anticancer therapy.

57. The method of claim 37, wherein the EGFR-targeted agent is a tyrosine kinase inhibitor (TKI).

58. The method of claim 37, wherein the EGFR-targeted agent is a monoclonal antibody.

59. A method for determining whether to treat a patient with an EGFR-targeted agent comprising: a) identifying a patient with a type of cancer that may be treated with an EGFR-targeted agent; b) obtaining cancer cells from the patient; c) measuring the level of SLC17A1 expression in the cancer cells; and, d) treating the patient with an EGFR-targeted agent if SLC17A1 is expressed at a level that is higher than the level in cancer cells resistant to the EGFR-targeted agent or treating the patient with an anti-cancer therapy that is not an EGFR-targeted agent if SLC 17Al is expressed at a level lower than cancer cells that are sensitive to the EGFR-targeted agent.

60. A method for identifying a candidate marker of toxicity or efficacy of a drug or class of drugs comprising: a) comparing the level of expression of a gene in a cell line panel with the level of cellular toxicity from the target drug or class of target drugs in the cell line panel; and, b) identifying any genes exhibiting a correlation between expression and toxicity, wherein the gene is a candidate marker.

61. The method of claim 60, further comprising eliminating any gene that exhibits a correlation between expression and toxicity from a control drug, wherein any gene that exhibits a correlation between expression and toxicity from the target drug or class of target drugs in the cell line panel and not from a control drug in the cell line panel is a candidate marker.

62. The method of claim 61 , further comprising estimating the false discovery rate for any gene.

63. The method of claim 61 , further comprising evaluating whether cellular toxicity is an indicator of efficacy of the drug or class of drugs comprising categorizing the efficacy of the drug or class of drugs in cell lines in the cell line panel and correlating the efficacy of the drug or class of drugs with the level of cellular expression of the gene in the cell lines.

64. The method of claim 61 , further comprising testing biological samples from patients for expression of the candidate marker and determining whether expression correlates with efficacy or toxicity.

65. The method of claim 61 , further comprising assaying the level of expression of the candidate marker in a sample from a patient who may be treated with a target drug or a drug from the class of target drugs and treating or not treating the patient with the drug depending on the level of expression.