US20170219586A1

US20170219586A1 - Salivary Transcriptomics and Proteomic Biomarkers for Breast Cancer Detection

Info

Publication number: US20170219586A1
Application number: US15/488,832
Authority: US
Inventors: David T. Wong; Lei Zhang; Hua Xiao; Hui Zhou
Original assignee: University of California
Current assignee: University of California
Priority date: 2010-02-10
Filing date: 2017-04-17
Publication date: 2017-08-03
Also published as: US20110212851A1; WO2011100472A1; US9624547B2

Abstract

Presented herein are biomarkers related to breast cancer. The presently identified salivary biomarkers create the basis for a breast cancer detection bioassay with sensitivity and specificity. Means and methods for evaluating the data generated using multiple biomarkers in order to validate findings and further use of the multiplexed breast cancer assay in clinical, diagnostic and therapeutic uses is also included.

Description

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application claims priority to provisional application U.S. Ser. No. 61/303,200, filed Feb. 10, 2010, herein incorporated by reference in its entirety.

STATEMENT AS TO RIGHTS TO INVENTIONS MADE UNDER FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government support under Grant No. DE016275, awarded by the National Institutes of Health. The Government has certain rights in this invention.

BACKGROUND

Breast cancer is the most frequent neoplasm and the leading cause of cancer mortality in women worldwide. According to estimates, approximately 41,000 women in the United States and 130,000 women in the European Union die from breast cancer yearly.
Detection of breast cancer at the earliest stages results in a much greater favorable outcome, with 10-year disease-free survival rate as high as 98% in patients in which the tumor stage is pT1a,bN0M0 (measuring 1 cm or less, with disease-free axillary lymph nodes and no distant metastasis). Needless to say, early detection is of paramount importance in reducing mortality from this major public health burden.
Current breast cancer detection methods are based on physical examination and imaging (for example, mammography, ultrasound, and MRI). These methods can produce a substantial percentage of false positive and false negative results especially in women with dense parenchymal breast tissue. Consequently, screening results in a number of negative biopsy results yielding a high percentage of false positives. There is also a demonstrated lack of sensitivity in detecting cancerous lesions in younger women yielding a significant percentage of false negatives. Accordingly, a clear need exists for added modalities of screening for breast cancer.
In the last decade, biomarker discoveries for breast cancer detection have focused on blood/or tissue, using proteomic, transcriptomic, and genomic approaches. In comparison to prognostic biomarkers, the development of detection biomarkers has been limited, mainly due to a lack of sensitivity and specificity for this clinical context. Most importantly, the use of tissue biomarkers for early detection will be limited to patients at very high risk because they rely on invasive procedures.
As such, a need exists for methods useful for detecting breast cancer, and in particular biomarkers that can detect early stages of the disease and are largely non-invasive.

BRIEF SUMMARY OF THE INVENTION

In accordance with some embodiments of the invention, a method of determining the likelihood of the presence or occurrence of breast cancer in a test subject is provided. The disclosed method includes analyzing a saliva sample from the subject with an assay that specifically detects at least two biomarkers in the saliva sample. The biomarkers are selected from the group of: S100A8 (S100 calcium binding protein A8) (SEQ ID NO: 1), CSTA (cystatin A) (SEQ ID NO:2), GRM1 (glutamate receptor, metabotropic 1) (SEQ ID NO: 3), TPT1 (tumor protein, translationally-controlled 1) (SEQ ID NO:4), GRIK1 (glutamate receptor, ionotropic, kainate 1) (SEQ ID NO: 5), H6PD (hexose-6-phosphate dehydrogenase) (SEQ ID NO: 6), IGF2BP1 (insulin-like growth factor 2 mRNA binding protein 1) (SEQ ID NO: 7), MDM4 (3T3 cell double minute 4) (SEQ ID NO: 8), and CA6 (carbonic anhydrase VI) (SEQ ID NO:8). The relative occurrence of at least two of these biomarkers is determined and compared to a control, thereby allowing the breast cancer status of the test subject to be determined.
In some embodiments, one of the biomarkers of the at least two biomarkers is cystatin A (CSTA). In other embodiments, two of the at least two biomarkers is CSTA and transformed 3T3 cell double minute 4 (MDM4). The relative occurrence of these biomarkers or these biomarkers and others in these instances is determined and compared to a control, for example, thereby allowing the breast cancer status of the test subject to be determined.
In some embodiments, the method of determining the likelihood of the presence or occurrence of breast cancer entails measuring at least three biomarkers. In some embodiments, two of the at least three biomarkers are CSTA and MDM4. The relative occurrence of these biomarkers or these biomarkers and others in these instances is determined and compared to a control, for example, thereby allowing the breast cancer status of the test subject to be determined.
In some embodiments, one of the biomarkers of the at least two biomarkers is anhydrase VI (CA6) polypeptide.
In other embodiments, the method of determining the likelihood of the presence or occurrence of breast cancer in a test subject includes an assay in which a nucleic acid encoding at least one biomarker is detected. The nucleic acid can be detected by, for example, mass spectroscopy, polymerase chain reaction (PCR), microarray hybridization, thermal sequencing, capillary array sequencing, or solid phase sequencing.
In other embodiments, the method of determining the likelihood of the presence or occurrence of breast cancer in a test subject includes an assay in which a polypeptide encoding at least one biomarker is detected. The polypeptide can be detected by, for example, enzyme-linked immunosorbent assay (ELISA), Western blot, flow cytometry, immunofluorescence, immunohistochemistry, or mass spectroscopy.
In accordance with other embodiments of the invention, a method for assessing the efficacy of a therapy is disclosed. This method includes analyzing a first saliva sample from the subject with an assay that specifically detects at least two biomarkers selected from the group consisting of S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4, and CA6. This first analysis provides a first expression profile. A therapy is applied to a subject. An analysis of a second saliva sample from the subject is undertaken with an assay that specifically detects at least two biomarkers selected from the group consisting of S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4, and CA6 thereby providing a second expression profile. The first and second expression profiles are compared in order to assess the efficacy of a therapy.
In another embodiment, a solid support is provided, wherein the solid support includes a capture binding probe selective for at least two biomarkers selected from the group of S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4. In some embodiments, a first and a second solid support are provided, wherein the first solid support includes a capture binding probe selective for at least two biomarkers selected from the group consisting of S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4, and wherein the second solid support includes a capture binding ligand for CA6.
In some embodiments, the capture binding ligand of the kit is an antibody. In another embodiment the kit provides one or more primers for the selective amplification of at least two biomarkers, wherein at least two of the biomarkers are selected from the group of: S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4. In some embodiments one or more of the primers possess a detectable label.
In accordance with some embodiments of the invention, a method of determining the likelihood of the presence or occurrence of breast cancer in a test subject is provided. The disclosed method includes analyzing a saliva sample from the subject with an assay that specifically detects at least nine biomarkers in the saliva sample. The biomarkers are selected from the group of: S100A8 (S100 calcium binding protein A8) (SEQ ID NO: 1), CSTA (cystatin A) (SEQ ID NO:2), GRM1 (glutamate receptor, metabotropic 1) (SEQ ID NO: 3), TPT1 (tumor protein, translationally-controlled 1) (SEQ ID NO:4), GRIK1 (glutamate receptor, ionotropic, kainate 1) (SEQ ID NO: 5), H6PD (hexose-6-phosphate dehydrogenase) (SEQ ID NO: 6), IGF2BP1 (insulin-like growth factor 2 mRNA binding protein 1) (SEQ ID NO: 7), MDM4 (3T3 cell double minute 4) (SEQ ID NO: 8), and CA6 (carbonic anhydrase VI) (SEQ ID NO:8). The relative occurrence of at least nine biomarkers is determined and compared to a control, thereby allowing the breast cancer status of the test subject to be determined.
In any of the embodiments above, wherein a method for determining the likelihood of the presence or occurrence of breast cancer in a test subject, the number of biomarkers used can be 2, 3, 4, 5, 6, 7, 8, 9, or more.
These and other embodiments, features and potential advantages will become apparent with reference to the following description and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic of the study designed to identify and validate biomarkers associated with breast cancer.

FIG. 2 is a schematic representation of the protocol for saliva collection.

FIG. 3 represents the demographic information of all the subjects used.

FIG. 4 represents biomarkers for breast cancer detection and effect of confounding factors (sample set n=93). The Mann-Whitney rank sum test was used to determine marker validation. Possible confounding factors, including age, ethnicity, smoking status, menopausal status, and HRT treatment, were evaluated for the biomarkers by logistic regression model. Linear regression model was constructed for each marker and used the factors cancer/normal and one of the confounders. cv.err:cross validation error rate.

FIG. 5 demonstrates the sensitivity achieved using a combination of the identified biomarkers. (A) The shading of the contigency table boxes reflects the fraction of each samples type in each quandrant. “Cancer” and “Non’ headings indicate subjects with and withour cancer, respectively. SB+ and SB−, salivary biomarker test positive or negative; NPV, negative predictive value; PPV, positive predictive value; Sen, sensitivity; Spec, specificity. (B) Score plot of principle component analysis (PCA). Combining the nine biomarkers, the control subjects (light shaded) separate from breast cancer patients (dark shading) with cumulative proportions of 66.9% for PC1 and 21.6% for PC2.

FIG. 6 represents cross-disease comparisons of the salivary mRNA biomarkers. The identified mRNA biomarkers for breast cancer detection were checked against other microarray datasets. t-test p-values were calculated for the identified breast cancer genes to other microarray datasets to check for significant variation (*after Boneferonni correction, P<0.0006) between patients and controls in those diseases. Sample sizes were 10 versus 10 for oral cancer, 10 versus 10 for lung cancer, 12 versus 12 for pancreatic cancer, 11 versus 11 for ovarian cancer, 13 versus 13 for diabetes, 8 versus 10 for primary Sjögren's Syndrome, and 10 versus 10 for breast cancer.

DETAILED DESCRIPTION OF THE INVENTION

Introduction

Early detection of breast cancer offers the promise of easier treatment (smaller surgeries, less radiation or chemotherapy) and improved survival. Conventional screening (physical examination and mammography) has a less-than desirable sensitivity and specificity. A sensitive assay to identify biomarkers using non-invasively collected specimens is therefore ideal for breast cancer detection.
While saliva is a source of easily accessible bodily fluids, there has been little effort to study its value in cancer diagnosis. Protein, as well as RNA, can be detected in saliva.
The present invention discloses the diagnostic/prognostic significance of nine salivary biomarkers S100A8 (SEQ ID NO: 1) (S100 calcium binding protein A8, also referred to as myloid-related protein 8 (MRP8) or S100A9 (MRP14)), CSTA (SEQ ID NO: 2)(cystatin A), GRM1 (SEQ ID NO: 3)(glutamate receptor, metabotropic 1), TPT1 (SEQ ID NO: 4)(tumor protein, translationally-controlled 1), GRIK1 (SEQ ID NO: 5) (glutamate receptor, ionotropic, kainate 1), H6PD (SEQ ID NO: 6)(hexose-6-phosphate dehydrogenase or glucose 1-dehydrogenase), IGF2BP1 (SEQ ID NO: 7)(insulin-like growth factor 2 mRNA binding protein 1), MDM4 (SEQ ID NO: 8)(Mdm4, transformed 3T3 cell double minute 4; HDMX; MDMX; MRP1; MGC132766; DKFZp781B1423), and CA6 (carbonic anhydrase VI) and combinations thereof, in breast cancer detection. Detection of these and other biomarkers in saliva are useful for diagnosis and prognosis of breast cancer.
Methods for detecting salivary biomarkers (proteins and nucleic acids) include techniques such as ELISA, PCR, for example, RT-PCR or mass spectroscopy, alone or in combination with other markers. Any specific probe can be used for detection, such as an antibody, a receptor, a ligand, RT-PCR etc. Mass spectroscopy can also be used for protein detection. Thus, the present invention can be used alone or as a complement to traditional antigen analysis to enhance the diagnosis of breast and other cancers.

Definitions

“S100A8,” “CSTA,” “GRM1,” “TPT1,” “GRIK1,” “H6PD,” “IGF2BP1,” “MDM4,” and “CA6” refer to nucleic acids, e.g., gene, pre-mRNA, mRNA, and polypeptides, polymorphic variants, alleles, mutants, and interspecies homologs that have an amino acid sequence that has greater than about 60% amino acid sequence identity, 65%, 70%, 75%, 80%, 85%, 90%, preferably 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98% or 99% or greater amino acid sequence identity, preferably over a region of over a region of at least about 25, 50, 100, 200, 500, 1000, or more amino acids, to a polypeptide encoded by a referenced nucleic acid or an amino acid sequence described herein. The nucleic acids and proteins of the invention include both naturally occurring or recombinant molecules. The nucleic acid or protein sequence is provided, for example, in SEQ ID NOs: 1-9.
“Cancer” refers to human cancers and carcinomas, sarcomas, adenocarcinomas, lymphomas, leukemias, etc., including solid and lymphoid cancers, kidney, breast, lung, kidney, bladder, colon, ovarian, prostate, pancreas, stomach, brain, head and neck, skin, uterine, testicular, esophagus, and liver cancer, including hepatocarcinoma, lymphoma, including non-Hodgkin's lymphomas (e.g., Burkitt's, Small Cell, and Large Cell lymphomas) and Hodgkin's lymphoma, leukemia, and multiple myeloma.
“Therapeutic treatment” and “cancer therapies” refers to chemotherapy, hormonal therapy, radiotherapy, and immunotherapy.
The terms “overexpress,” “overexpression” or “overexpressed” interchangeably refer to a protein that is transcribed or translated at a detectably greater level, usually in a cancer cell, in comparison to a normal cell. The term includes overexpression due to transcription, post transcriptional processing, translation, post-translational processing, cellular localization (e.g, organelle, cytoplasm, nucleus, cell surface), and RNA and protein stability, as compared to a normal cell. Overexpression can be detected using conventional techniques for detecting mRNA (i.e., RT-PCR, PCR, hybridization) or proteins (i.e., ELISA, immunohistochemical techniques, mass spectroscopy). Overexpression can be 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or more in comparison to a normal cell. In certain instances, overexpression is 1-fold, 2-fold, 3-fold, 4-fold or more higher levels of transcription or translation in comparison to a normal cell.
The terms “cancer-associated antigen” or “tumor-specific marker” or “tumor marker” interchangeably refers to a molecule (typically protein or nucleic acid such as RNA) that is expressed in the cell, expressed on the surface of a cancer cell or secreted by a cancer cell in comparison to a normal cell, and which is useful for the diagnosis of cancer, for providing a prognosis, and for preferential targeting of a pharmacological agent to the cancer cell. Oftentimes, a cancer-associated antigen is overexpressed in a cancer cell in comparison to a normal cell, for instance, about 1.2-fold over expression, about 2-fold overexpression, about 3-fold overexpression or more in comparison to a normal cell. Oftentimes, a cancer-associated antigen is a cell surface molecule that is inappropriately synthesized in the cancer cell, for instance, a molecule that contains deletions, additions or mutations in comparison to the molecule expressed on a normal cell. Oftentimes, a cancer-associated antigen will be expressed exclusively on the cell surface of a cancer cell and not synthesized or expressed on the surface of a normal cell. Exemplified cell surface tumor markers include the proteins c-erbB-2 and human epidermal growth factor receptor (HER) for breast cancer, PSMA for prostate cancer, and carbohydrate mucins in numerous cancers, including breast, ovarian and colorectal.
It will be understood by the skilled artisan that markers may be used singly or in combination with other markers for any of the uses, e.g., diagnosis or prognosis of breast cancer, disclosed herein.
The terms “identical” or percent “identity,” in the context of two or more nucleic acids or polypeptide sequences, refer to two or more sequences or subsequences that are the same or have a specified percentage of amino acid residues or nucleotides that are the same (i.e., about 60% identity, preferably 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or higher identity over a specified region, when compared and aligned for maximum correspondence over a comparison window or designated region) as measured using a BLAST or BLAST 2.0 sequence comparison algorithms with default parameters described below, or by manual alignment and visual inspection (see, e.g., NCBI web site hypertext transfer protocol://www.ncbi.nlm.nih.gov/BLAST/ or the like). Such sequences are then said to be “substantially identical.” This definition also refers to, or may be applied to, the compliment of a test sequence. The definition also includes sequences that have deletions and/or additions, as well as those that have substitutions. As described below, the preferred algorithms can account for gaps and the like. Preferably, identity exists over a region that is at least about 25 amino acids or nucleotides in length, or more preferably over a region that is 50-100 amino acids or nucleotides in length.
For sequence comparison, typically one sequence acts as a reference sequence, to which test sequences are compared. When using a sequence comparison algorithm, test and reference sequences are entered into a computer, subsequence coordinates are designated, if necessary, and sequence algorithm program parameters are designated. Preferably, default program parameters can be used, or alternative parameters can be designated. The sequence comparison algorithm then calculates the percent sequence identities for the test sequences relative to the reference sequence, based on the program parameters.
A “comparison window”, as used herein, includes reference to a segment of any one of the number of contiguous positions selected from the group consisting of from 20 to 600, usually about 50 to about 200, more usually about 100 to about 150 in which a sequence may be compared to a reference sequence of the same number of contiguous positions after the two sequences are optimally aligned. Methods of alignment of sequences for comparison are well-known in the art. Optimal alignment of sequences for comparison can be conducted, e.g., by the local homology algorithm of Smith & Waterman, Adv. Appl. Math. 2:482 (1981), by the homology alignment algorithm of Needleman & Wunsch, J. Mol. Biol. 48:443 (1970), by the search for similarity method of Pearson & Lipman, Proc. Nat'l. Acad. Sci. USA 85:2444 (1988), by computerized implementations of these algorithms (GAP, BESTFIT, FASTA, and TFASTA in the Wisconsin Genetics Software Package, Genetics Computer Group, 575 Science Dr., Madison, Wis.), or by manual alignment and visual inspection (see, e.g., Current Protocols in Molecular Biology (Ausubel et al., eds. 1987-2005, Wiley Interscience)).
An example of algorithm that is suitable for determining percent sequence identity and sequence similarity are the BLAST and BLAST 2.0 algorithms, which are described in Altschul et al., Nuc. Acids Res. 25:3389-3402 (1977) and Altschul et al., J. Mol. Biol. 215:403-410 (1990), respectively. BLAST and BLAST 2.0 are used, with the parameters described herein, to determine percent sequence identity for the nucleic acids and proteins of the invention. Software for performing BLAST analyses is publicly available through the National Center for Biotechnology Information (hypertext transfer protocol://www.ncbi.nlm.nih gov/). This algorithm involves first identifying high scoring sequence pairs (HSPs) by identifying short words of length W in the query sequence, which either match or satisfy some positive-valued threshold score T when aligned with a word of the same length in a database sequence. T is referred to as the neighborhood word score threshold (Altschul et al., supra). These initial neighborhood word hits act as seeds for initiating searches to find longer HSPs containing them. The word hits are extended in both directions along each sequence for as far as the cumulative alignment score can be increased. Cumulative scores are calculated using, for nucleotide sequences, the parameters M (reward score for a pair of matching residues; always >0) and N (penalty score for mismatching residues; always <0). For amino acid sequences, a scoring matrix is used to calculate the cumulative score. Extension of the word hits in each direction are halted when: the cumulative alignment score falls off by the quantity X from its maximum achieved value; the cumulative score goes to zero or below, due to the accumulation of one or more negative-scoring residue alignments; or the end of either sequence is reached. The BLAST algorithm parameters W, T, and X determine the sensitivity and speed of the alignment. The BLASTN program (for nucleotide sequences) uses as defaults a wordlength (W) of 11, an expectation (E) of 10, M=5, N=−4 and a comparison of both strands. For amino acid sequences, the BLASTP program uses as defaults a wordlength of 3, and expectation (E) of 10, and the BLOSUM62 scoring matrix (see Henikoff & Henikoff, Proc. Natl. Acad. Sci. USA 89:10915 (1989)) alignments (B) of 50, expectation (E) of 10, M=5, N=−4, and a comparison of both strands.
“Nucleic acid” refers to deoxyribonucleotides or ribonucleotides and polymers thereof in either single- or double-stranded form, and complements thereof.
Unless otherwise indicated, a particular nucleic acid sequence also implicitly encompasses conservatively modified variants thereof (for example, degenerate codon substitutions) and complementary sequences, as well as the sequence explicitly indicated. Specifically, degenerate codon substitutions may be achieved by generating sequences in which the third position of one or more selected (or all) codons is substituted with mixed-base and/or deoxyinosine residues (Batzer et al., Nucleic Acid Res. 19:5081 (1991); Ohtsuka et al., J. Biol. Chem. 260:2605-2608 (1985); Rossolini et al., Mol. Cell. Probes 8:91-98 (1994)). The term nucleic acid is used interchangeably with gene, cDNA, mRNA, oligonucleotide, and polynucleotide.
A particular nucleic acid sequence also implicitly encompasses “splice variants” and nucleic acid sequences encoding truncated forms of cancer antigens. Similarly, a particular protein encoded by a nucleic acid implicitly encompasses any protein encoded by a splice variant or truncated form of that nucleic acid. “Splice variants,” as the name suggests, are products of alternative splicing of a gene. After transcription, an initial nucleic acid transcript may be spliced such that different (alternate) nucleic acid splice products encode different polypeptides. Mechanisms for the production of splice variants vary, but include alternate splicing of exons. Alternate polypeptides derived from the same nucleic acid by read-through transcription are also encompassed by this definition. Any products of a splicing reaction, including recombinant forms of the splice products, are included in this definition. Nucleic acids can be truncated at the 5′ end or at the 3′ end. Polypeptides can be truncated at the N-terminal end or the C-terminal end. Truncated versions of nucleic acid or polypeptide sequences can be naturally occurring or recombinantly created.
The term “amino acid” refers to naturally occurring and synthetic amino acids, as well as amino acid analogs and amino acid mimetics that function in a manner similar to the naturally occurring amino acids. Naturally occurring amino acids are those encoded by the genetic code, as well as those amino acids that are later modified, e.g., hydroxyproline, .gamma.-carboxyglutamate, and O-phosphoserine. Amino acid analogs refers to compounds that have the same basic chemical structure as a naturally occurring amino acid, i.e., an .alpha. carbon that is bound to a hydrogen, a carboxyl group, an amino group, and an R group, e.g., homoserine, norleucine, methionine sulfoxide, methionine methyl sulfonium. Such analogs have modified R groups (e.g., norleucine) or modified peptide backbones, but retain the same basic chemical structure as a naturally occurring amino acid. Amino acid mimetics refers to chemical compounds that have a structure that is different from the general chemical structure of an amino acid, but that functions in a manner similar to a naturally occurring amino acid.
Amino acids may be referred to herein by either their commonly known three letter symbols or by the one-letter symbols recommended by the IUPAC-IUB Biochemical Nomenclature Commission. Nucleotides, likewise, may be referred to by their commonly accepted single-letter codes.
“Conservatively modified variants” applies to both amino acid and nucleic acid sequences. With respect to particular nucleic acid sequences, conservatively modified variants refers to those nucleic acids which encode identical or essentially identical amino acid sequences, or where the nucleic acid does not encode an amino acid sequence, to essentially identical sequences. Because of the degeneracy of the genetic code, a large number of functionally identical nucleic acids encode any given protein. For instance, the codons GCA, GCC, GCG and GCU all encode the amino acid alanine Thus, at every position where an alanine is specified by a codon, the codon can be altered to any of the corresponding codons described without altering the encoded polypeptide. Such nucleic acid variations are “silent variations,” which are one species of conservatively modified variations. Every nucleic acid sequence herein which encodes a polypeptide also describes every possible silent variation of the nucleic acid. One of skill will recognize that each codon in a nucleic acid (except AUG, which is ordinarily the only codon for methionine, and TGG, which is ordinarily the only codon for tryptophan) can be modified to yield a functionally identical molecule. Accordingly, each silent variation of a nucleic acid which encodes a polypeptide is implicit in each described sequence with respect to the expression product, but not with respect to actual probe sequences.
As to amino acid sequences, one of skill will recognize that individual substitutions, deletions or additions to a nucleic acid, peptide, polypeptide, or protein sequence which alters, adds or deletes a single amino acid or a small percentage of amino acids in the encoded sequence is a “conservatively modified variant” where the alteration results in the substitution of an amino acid with a chemically similar amino acid. Conservative substitution tables providing functionally similar amino acids are well known in the art. Such conservatively modified variants are in addition to and do not exclude polymorphic variants, interspecies homologs, and alleles of the invention.
The following eight groups each contain amino acids that are conservative substitutions for one another: 1) Alanine (A), Glycine (G); 2) Aspartic acid (D), Glutamic acid (E); 3) Asparagine (N), Glutamine (Q); 4) Arginine (R), Lysine (K); 5) Isoleucine (I), Leucine (L), Methionine (M), Valine (V); 6) Phenylalanine (F), Tyrosine (Y), Tryptophan (W); 7) Serine (S), Threonine (T); and 8) Cysteine (C), Methionine (M) (see, e.g., Creighton, Proteins (1984)).
A “label” or a “detectable moiety” is a composition detectable by spectroscopic, photochemical, biochemical, immunochemical, chemical, or other physical means. For example, useful labels include fluorescent dyes, electron-dense reagents, enzymes (for example, as commonly used in an ELISA), biotin, digoxigenin, or haptens and proteins which can be made detectable, e.g., by incorporating a radiolabel into the peptide or used to detect antibodies specifically reactive with the peptide.
The tem) “recombinant” when used with reference, e.g., to a cell, or nucleic acid, protein, or vector, indicates that the cell, nucleic acid, protein or vector, has been modified by the introduction of a heterologous nucleic acid or protein or the alteration of a native nucleic acid or protein, or that the cell is derived from a cell so modified. Thus, for example, recombinant cells express genes that are not found within the native (non-recombinant) form of the cell or express native genes that are otherwise abnormally expressed, under expressed or not expressed at all.
The phrase “stringent hybridization conditions” refers to conditions under which a probe will hybridize to its target subsequence, typically in a complex mixture of nucleic acids, but to no other sequences. Stringent conditions are sequence-dependent and will be different in different circumstances. Longer sequences hybridize specifically at higher temperatures. An extensive guide to the hybridization of nucleic acids is found in Tijssen, Techniques in Biochemistry and Molecular Biology—Hybridization with Nucleic Probes, “Overview of principles of hybridization and the strategy of nucleic acid assays” (1993). Generally, stringent conditions are selected to be about 5-10° C. lower than the thermal melting point (Tm) for the specific sequence at a defined ionic strength pH. The T_mis the temperature (under defined ionic strength, pH, and nucleic concentration) at which 50% of the probes complementary to the target hybridize to the target sequence at equilibrium (as the target sequences are present in excess, at T_m, 50% of the probes are occupied at equilibrium). Stringent conditions may also be achieved with the addition of destabilizing agents such as formamide. For selective or specific hybridization, a positive signal is at least two times background, preferably 10 times background hybridization. Exemplary stringent hybridization conditions can be as following: 50% formamide, 5×SSC, and 1% SDS, incubating at 42° C., or, 5×SSC, 1% SDS, incubating at 65° C., with wash in 0.2×SSC, and 0.1% SDS at 65° C.
Nucleic acids that do not hybridize to each other under stringent conditions are still substantially identical if the polypeptides which they encode are substantially identical. This occurs, for example, when a copy of a nucleic acid is created using the maximum codon degeneracy permitted by the genetic code. In such cases, the nucleic acids typically hybridize under moderately stringent hybridization conditions. Exemplary “moderately stringent hybridization conditions” include a hybridization in a buffer of 40% formamide, 1 M NaCl, 1% SDS at 37° C., and a wash in 1×SSC at 45° C. A positive hybridization is at least twice background. Those of ordinary skill will readily recognize that alternative hybridization and wash conditions can be utilized to provide conditions of similar stringency. Additional guidelines for determining hybridization parameters are provided in numerous reference, e.g., and Current Protocols in Molecular Biology, ed. Ausubel, et al., supra.
For PCR, a temperature of about 36° C. is typical for low stringency amplification, although annealing temperatures may vary between about 32° C. and 48° C. depending on primer length. For high stringency PCR amplification, a temperature of about 62° C. is typical, although high stringency annealing temperatures can range from about 50° C. to about 65° C., depending on the primer length and specificity. Typical cycle conditions for both high and low stringency amplifications include a denaturation phase of 90° C.−95° C. for 30 sec-2 min., an annealing phase lasting 30 sec.-2 min., and an extension phase of about 72° C. for 1-2 min. Protocols and guidelines for low and high stringency amplification reactions are provided, e.g., in Innis et al. (1990) PCR Protocols, A Guide to Methods and Applications, Academic Press, Inc. N.Y.).
“Antibody” means a protein comprising one or more polypeptides substantially encoded by all or part of the recognized immunoglobulin genes. The recognized immunoglobulin genes, for example in humans, include the kappa (κ), lambda (λ) and heavy chain genetic loci, which together compose the myriad variable region genes, and the constant region genes mu (μ), delta (δ), gamma (γ), epsilon (ε) and alpha (α), which encode the IgM, IgD, IgG, IgE, and IgA isotypes respectively. Antibody herein is meant to include full length antibodies and antibody fragments, and may refer to a natural antibody from any organism, an engineered antibody or an antibody generated recombinantly for experimental, therapeutic or other purposes as further defined below. Antibody fragments include Fab, Fab′, F(ab′)₂, Fv, scFv or other antigen-binding subsequences of antibodies and can include those produced by the modification of whole antibodies or those synthesized de novo using recombinant DNA technologies. The term “antibody” refers to both monoclonal and polyclonal antibodies. Antibodies can be antagonists, agonists, neutralizing, inhibitory or stimulatory.

Biomarkers

Biomarkers may originate from epidemiological studies, animal studies, pathophysiological considerations and end-organ experiments. Ideally, a biomarker will have a high predictive value for a meaningful outcome measure, can be or is validated in appropriately designed prospective trials, reflects therapeutic success by corresponding changes in the surrogate marker results, and should be easy to assess in clinical practice.
Biomarkers can be used in conjunction with other diagnostic tools or used alone.
The term “surrogate marker,” “biomolecular marker,” “biomarker” or “marker” (also sometimes referred to herein as a “target analyte,” “target species” or “target sequence”) refers to a molecule whose measurement provides information as to the state of a subject. In various exemplary embodiments, the biomarker is used to assess a pathological state. Measurements of the biomarker may be used alone or combined with other data obtained regarding a subject in order to determine the state of the subject. In one embodiment, the biomarker is “differentially present” in a sample taken from a subject of one phenotypic status (e.g., having a disease) as compared with another phenotypic status (e.g., not having the disease). In one embodiment, the biomarker is “differentially present” in a sample taken from a subject undergoing no therapy or one type of therapy as compared with another type of therapy. Alternatively, the biomarker may be “differentially present” even if there is no phenotypic difference, e.g. the biomarkers may allow the detection of asymptomatic risk.
A biomarker may be over-expressed (over-abundant) or under-expressed (under abundant) relative to a control. The biomarker can be an allelic variant, truncated or mutated form of a wild-type nucleic acid or protein. The biomarker can be a splice variant.
A biomarker may be determined to be “differentially present” in a variety of ways, for example, between different phenotypic statuses if the mean or median level (particularly the expression level of the associated mRNAs as described below) of the biomarker in the different groups is calculated to be statistically significant. Common tests for statistical significance include, among others, t-test, ANOVA, Kruskal-Wallis, Wilcoxon, Mann-Whitney and odds ratio.
As described herein, a biomarker may be, for example, a small molecule, an analyte or target analyte, a nucleic acid, a protein, a metabolite or any derivative thereof or any and all combinations of these molecules, with proteins and nucleic acids finding particular use in the invention. As will be appreciated by those in the art, a large number of analytes may be detected using the present methods; basically, any biomarker for which a binding ligand, described below, may be made may be detected using the methods of the invention.
In various embodiments, the biomarkers used in the panels of the invention can be detected either as proteins or as nucleic acids (e.g. mRNA or cDNA transcripts) in any combination. In various embodiments, the protein form of a biomarker is measured. As will be appreciated by those in the art, protein assays may be done using standard techniques such as ELISA assays. In various embodiments, the nucleic acid form of a biomarker (e.g., the corresponding mRNA) is measured. In various exemplary embodiments, one or more biomarkers from a particular panel are measured using a protein assay and one or more biomarkers from the same panel are measured using a nucleic acid assay.
As will be appreciated by those in the art, there are a large number of possible proteinaceous target analytes and target species that may be detected using the present invention. The term “protein,” “polypeptide” or “oligopeptide” refers to at least two or more peptides or amino acids joined by one or more peptide bonds. A protein or an amino acid may be naturally or nonnaturally occurring and may be also be an analog, a derivative or a peptidomimetic structure. The term “protein” refers to wild-type sequences, variants of wild-type sequences and either of these containing analogs or derivatized amino acids. In various embodiments, variants of the sequences described herein, including proteins and nucleic acids based on e.g. splice variants, variants comprising a deletion, addition, substitution, fragments, preproprotein, processed preproprotein (e.g. without a signaling peptide), processed proprotein (e.g. resulting in an active form), nonhuman sequences and variant nonhuman sequences may be used as biomarkers.
In various embodiments, the biomarker is a nucleic acid. The term “nucleic acid” or “oligonucleotide” or grammatical equivalents herein means at least two nucleotides covalently linked together. A nucleic acid of the present invention will generally contain phosphodiester bonds, although in some cases, as outlined below, for example in the use of binding ligand probes, nucleic acid analogs are included that may have alternate backbones.
Biomarkers can also be bacterial nucleic acids or proteins. Over 700 species of bacteria have been identified to exist within the mouth. The presence, absence, or level of 16S rRNA from bacteria in a sample may correlate with a disease or condition. “Bacteria” refers to small prokaryotic organisms (linear dimensions of around 1 μm) with non-compartmentalized circular DNA and ribosomes of about 70 S. “16S RNA” refers to a nucleic acid component of the 30S subunit of prokaryotic ribosomes; the gene that encodes the 16S rRNA or the 16S rRNA itself. Bacterial strains of species or phylotypes have less than about a 2% difference in 16S rRNA. Closely related species or phylotypes generally have between about a 2% and about a 4% difference in 16S rRNA, whereas a genus often has between about a 5% and about a 10% difference in 16S rRNA.
To resolve the identity of bacterial populations, probes on a microarray can be designed, for example, to take advantage of conserved features of the 16S rRNA gene. For example, probes complementary to the more conserved features regions identify species in a large phylogenetic group, each group corresponding to a higher taxon (for example, domain, phylum, class, order, or family). Probes complementary to more variable regions distinguish genera and species.
Biomarkers can also include micro RNAs. “MicroRNAs” (miRs) refers to a class of small naturally occurring non-coding RNAs (18-24 nucleotides) that regulate gene expression. Many microRNAs are well conserved across species and they are present in a broad range of species: plants, nematodes, fruit flies and humans. MicroRNAs have partially or perfect complementary sequence to one or more messenger RNA molecules (mRNAs) and their main function is to negatively regulate the expression of genes. In particular, microRNAs bind to the 3′ untranslated regions of mRNAs (3-UTR) thus leading to down regulation of mRNAs in a variety of ways such as mRNA cleavage, translational repression and deadenylation.
A variety of experimental approaches and different techniques have been used to identify new microRNAs, as well as to study their expression pattern in the different biological processes. The cloning and identification of new microRNAs have been successfully done from size fractioned RNA samples using small RNA cloning approaches. Other approaches is as putative microRNAs homologues to microRNAs that already have been described in other species or using computational approaches alone or in combination with microarray analysis and sequence-directed cloning.
One of the first techniques used for detection and profiling of microRNAs was Northern Blotting, where hybridization is done with a complementary 32P, digoxigenin-labeled oligo or modified Locked-nucleic-acid (LNA) oligonucleotides after gel separation.
Other techniques that have been developed to specifically detect microRNAs are a modified invader assay (a synthetic oligonucleotide, the probe, which is in an appropriate overlap-flap structure is enzymatically cleavage by a structure-specific 5* nuclease) and in situ hybridization (using fluorescent-labeled complementary probes containing chemically modified nucleotides e.g. LNAs). Another widely used technique for detection and profiling of microRNAs is the use of oligonucleotide micro-array based detection platforms either with DNA capture probes or using modified Locked-nucleic-acid (LNA) oligonucleotides in which the ribose moiety is modified with an extra bridge that connects the 2′-0 and 4′-C atoms.
In addition, quantitative real-time PCR (reverse transcriptase/polymerase chain reaction using Taqman or SYBR green technology) has been used for detection and profiling of precursor or mature microRNAs. This technique is sensitive and requires low amounts of starting material for the detection of individual mature microRNAs. Taqman microRNA arrays have been developed that provide the sensitivity of the qRT-PCR, while at the same time enables the simultaneously detection of different microRNAs in one sample.
Biomarkers can also include metabolites. “Metabolite” or “small molecule” refers to organic and inorganic molecules which are present in a sample. The term does not include large macromolecules, such as large proteins (e.g., proteins with molecular weights over 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000), large nucleic acids (e.g., nucleic acids with molecular weights of over 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000), or large polysaccharides (e.g., polysaccharides with a molecular weights of over 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, or 10,000).
The metabolites of the cell are generally found free in solution. A “metabolic profile”, or “small molecule profile”, means a complete or partial inventory of small molecules within a targeted cell, tissue, organ, organism, or fraction thereof (e.g., cellular compartment). The inventory may include the quantity and/or type of small molecules present. The “small molecule profile” may be determined using a single technique or multiple different techniques.
A metabolic profile can be developed by analyzing a sample using for example, techniques such as GC-MS (gas chromatography-mass spectrometry) and LC-MS (liquid chromatography-mass spectrometry).

Biomarker Panels

Any combination of the biomarkers described herein is used to assemble a biomarker panel, which is detected or measured as described herein. As is generally understood in the art, a combination may refer to an entire set or any subset or subcombination thereof. The term “biomarker panel,” “biomarker profile,” or “biomarker fingerprint” refers to a set of biomarkers. As used herein, these terms can also refer to any form of the biomarker that is measured. Thus, if cystatin A is part of a biomarker panel, then either cystatin A mRNA, for example, or protein could be considered to be part of the panel. While individual biomarkers are useful as diagnostics, combination of biomarkers can sometimes provide greater value in determining a particular status than single biomarkers alone. Specifically, the detection of a plurality of biomarkers in a sample can increase the sensitivity and/or specificity of the test. Thus, in various embodiments, a biomarker panel may include 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more types of biomarkers. In various exemplary embodiments, the biomarker panel consists of a minimum number of biomarkers to generate a maximum amount of information. Thus, in various embodiments, the biomarker panel consists of 2, 3, 4, 5, 6, 7, 8, 9 or more types of biomarkers. Where a biomarker panel “consists of” a set of biomarkers, no biomarkers other than those of the set are present. In exemplary embodiments, the biomarker panel consists of 2 biomarkers disclosed herein. In various embodiments, the biomarker panel consists of 3 biomarkers disclosed herein. In various embodiments, the biomarker panel consists of 4 biomarkers disclosed herein. In various embodiments, the biomarker paenl consists of 5 biomarkers disclosed herein.
In various exemplary embodiments, the biomarker panel comprises cystatin A. In various exemplary embodiments, the biomarker panel comprises carbonic anhydrase VI.
In various exemplary embodiments, the biomarker panel comprises or consists of two or more of the biomarkers selected from the group of S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4, and CA6. In various exemplary embodiments two or more of the biomarkers selected from the group of S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4, and CA6 can be combined with 1, 2, 3, 4 or more additional biomarkers. It should be understood that in this embodiment, the biomarker panel can include any combination of S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4 and the remainder of these markers.
A biomarker can also be a clinical parameter. The term “clinical parameter” refers to all non-sample or non-analyte biomarkers of subject health status or other characteristics, such as, without limitation, age, ethnicity, gender, family history, height, and weight.
The biomarkers of the invention show a statistically significant difference in breast cancer diagnosis. In various embodiments, diagnostic tests that use these biomarkers alone or in combination show a sensitivity and specificity of at least about 85%, at least about 90%, at least about 95%, at least about 98% and about 100%.

Measurement and Detection of Biomarkers

Biomarkers generally can be measured and detected through a variety of assays, methods and detection systems known to one of skill in the art. The term “measuring,” “detecting,” or “taking a measurement” refers to a quantitative or qualitative determination of a property of an entity, for example, quantifying the amount or concentration of a molecule or the activity level of a molecule. The term “concentration” or “level” can refer to an absolute or relative quantity. Measuring a molecule may also include determining the absence or presence of the molecule. Various methods include but are not limited to refractive index spectroscopy (RI), ultra-violet spectroscopy (UV), fluorescence analysis, electrochemical analysis, radiochemical analysis, near-infrared spectroscopy (near-IR), infrared (IR) spectroscopy, nuclear magnetic resonance spectroscopy (NMR), light scattering analysis (LS), mass spectrometry, pyrolysis mass spectrometry, nephelometry, dispersive Raman spectroscopy, gas chromatography, liquid chromatography, gas chromatography combined with mass spectrometry, liquid chromatography combined with mass spectrometry, matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) combined with mass spectrometry, ion spray spectroscopy combined with mass spectrometry, capillary electrophoresis, colorimetry and surface plasmon resonance (such as according to systems provided by Biacore Life Sciences). See also PCT Publications WO/2004/056456 and WO/2004/088309. In this regard, biomarkers can be measured using the above-mentioned detection methods, or other methods known to the skilled artisan. Other biomarkers can be similarly detected using reagents that are specifically designed or tailored to detect them.
Different types of biomarkers and their measurements can be combined in the compositions and methods of the present invention. In various embodiments, the protein form of the biomarkers is measured. In various embodiments, the nucleic acid form of the biomarkers is measured. In exemplary embodiments, the nucleic acid form is mRNA. In various embodiments, measurements of protein biomarkers are used in conjunction with measurements of nucleic acid biomarkers.
Methods for detecting mRNA, such as RT-PCR, real time PCR, branch DNA, NASBA and others, are well known in the art. Using sequence information provided by the database entries for the biomarker sequences, expression of the biomarker sequences can be detected (if present) and measured using techniques well known to one of ordinary skill in the art. For example, sequences in sequence database entries or sequences disclosed herein can be used to construct probes for detecting biomarker RNA sequences in, e.g., Northern blot hybridization analyses or methods which specifically, and, preferably, quantitatively amplify specific nucleic acid sequences. As another example, the sequences can be used to construct primers for specifically amplifying the biomarker sequences in, e.g., amplification-based detection methods such as reverse-transcription based polymerase chain reaction (RT-PCR). When alterations in gene expression are associated with gene amplification, deletion, polymorphisms and mutations, sequence comparisons in test and reference populations can be made by comparing relative amounts of the examined DNA sequences in the test and reference cell populations. In addition to Northern blot and RT-PCR, RNA can also be measured using, for example, other target amplification methods (e.g., TMA, SDA, NASBA), signal amplification methods (e.g., bDNA), nuclease protection assays, in situ hybridization and the like.
In one embodiment in the present invention are biochip assays. By “biochip” or “chip” herein is meant a composition generally comprising a solid support or substrate to which a capture binding ligand (also called an adsorbent, affinity reagent or binding ligand, or when nucleic acid is measured, a capture probe) is attached and can bind either proteins, nucleic acids or both. Generally, where a biochip is used for measurements of protein and nucleic acid biomarkers, the protein biomarkers are measured on a chip separate from that used to measure the nucleic acid biomarkers. For nonlimiting examples of additional platforms and methods useful for measuring nucleic acids, see Publications US/2006/0275782, US/2005/0064469 and DE10201463. In various embodiments, biomarkers are measured on the same platform, such as on one chip. In various embodiments, biomarkers are measured using different platforms and/or different experimental runs.
By “binding ligand,” “capture binding ligand,” “capture binding species,” “capture probe” or grammatical equivalents herein is meant a compound that is used to detect the presence of or to quantify, relatively or absolutely, a target analyte, target species or target sequence (all used interchangeably) and that will bind to the target analyte, target species or target sequence. Generally, the capture binding ligand or capture probe allows the attachment of a target species or target sequence to a solid support for the purposes of detection as further described herein. Attachment of the target species to the capture binding ligand may be direct or indirect. In exemplary embodiments, the target species is a biomarker. As will be appreciated by those in the art, the composition of the binding ligand will depend on the composition of the biomarker. Binding ligands for a wide variety of biomarkers are known or can be readily found using known techniques. For example, when the biomarker is a protein, the binding ligands include proteins (particularly including antibodies or fragments thereof (F_abs, etc.) as discussed further below) or small molecules. The binding ligand may also have cross-reactivity with proteins of other species. Antigen-antibody pairs, receptor-ligands, and carbohydrates and their binding partners are also suitable analyte-binding ligand pairs. In various embodiments, the binding ligand may be nucleic acid. Nucleic acid binding ligands find particular use when proteins are the targets; alternatively, as is generally described in U.S. Pat. Nos. 5,270,163; 5,475,096; 5,567,588; 5,595,877; 5,637,459; 5,683,867; 5,705,337 and related patents, hereby incorporated by reference, nucleic acid “aptamers” can be developed for binding to virtually any biomarker. Nucleic acid binding ligands also find particular use when nucleic acids are binding targets. There is a wide body of literature relating to the development of binding partners based on combinatorial chemistry methods. In these embodiments, when the binding ligand is a nucleic acid, preferred compositions and techniques are outlined in PCT Publication WO/1998/020162, hereby incorporated by reference.
In various exemplary embodiments, the capture binding ligand is an antibody. These embodiments are particularly useful for the detection of the protein form of a biomarker.
Detecting or measuring the level (e.g. the transcription level) of a biomarker involves binding of the biomarker to a capture binding ligand, generally referred to herein as a “capture probe” when the mRNA of the biomarker is to be detected on a solid support. In that sense, the biomarker is a target sequence. The term “target sequence” or “target nucleic acid” or grammatical equivalents herein means a nucleic acid sequence that may be a portion of a gene, a regulatory sequence, genomic DNA, cDNA, RNA including mRNA and rRNA, or others. As is outlined herein, the target sequence may be a target sequence from a sample, or a secondary target such as a product of an amplification reaction such as PCR etc. In some embodiments, measuring a nucleic acid can thus refer to measuring the complement of the nucleic acid. It may be any length, with the understanding that longer sequences are more specific.
The target sequence may also comprise different target domains; for example, a first target domain of the sample target sequence may hybridize to a first capture probe, a second target domain may hybridize to a label probe (e.g. a “sandwich assay” format), etc. The target domains may be adjacent or separated as indicated. Unless specified, the terms “first” and “second” are not meant to confer an orientation of the sequences with respect to the 5′-3′ orientation of the target sequence. For example, assuming a 5′-3′ orientation of the target sequence, the first target domain may be located either 5′ to the second domain, or 3′ to the second domain.
When nucleic acids are used as the target analyte, the assays of the invention can take on a number of embodiments. In one embodiment, the assays are done in solution format, using any number of solution based formats. In one embodiment, end-point or real time PCR formats are used, as are well known in the art. These assays can be done either as a panel, in individual tubes or wells, or as multiplex assays, using sets of primers and different labels within a single tube or well. In addition to PCR-based solution formats, other formats can be utilized, including, but not limited to for example ligation based assays utilizing FRET dye pairs. In this embodiment, only upon ligation of two (or more) probes hybridized to the target sequence is a signal generated.
In many embodiments, the assays are done on a solid support, utilizing a capture probe associated with the surface. As discussed herein, the capture probes (or capture binding ligands, as they are sometimes referred to) can be covalently attached to the surface, for example using capture probes terminally modified with functional groups, for example amino groups, that are attached to modified surfaces such as silanized glass. Alternatively, non-covalent attachment, such as electrostatic, hydrophobic/hydrophilic adhesion can be utilized. As is appreciated by those in the art and discussed herein, a large number of attachments are possible on a wide variety of surfaces.
In this embodiment, the assays can take on a number of formats. In one embodiment, the target sequence comprises a detectable label, as described herein. In this embodiment, the label is generally added to the target sequence during amplification of the target in one of two ways: either labeled primers are utilized during the amplification step or labeled dNTPs are used, both of which are well known in the art. The label can either be a primary or secondary label as discussed herein. For example, in one embodiment, the label on the primer and/or a dNTP is a primary label such as a fluorophore. Alternatively, the label may be a secondary label such as biotin or an enzyme; for example, in one embodiment, the primers or dNTPs are labeled with biotin, and then a streptavidin/label complex is added. In one embodiment, the streptavidin/label complex contains a label such as a fluorophore. In an alternative embodiment, the streptavidin/label complex comprises an enzymatic label. For example, the complex can comprise horseradish peroxidase, and upon addition of TMB, the action of the horseradish peroxidase causes the TMB to precipitate, causing an optically detectable event. This has a particular benefit in that the optics for detection does not require the use of a fluorimeter.
In alternate embodiments, the solid phase assay relies on the use of a labeled soluble capture ligand, sometimes referred to as a “label probe” or “signaling probe” when the target analyte is a nucleic acid. In this format, the assay is a “sandwich” type assay, where the capture probe binds to a first domain of the target sequence and the label probe binds to a second domain. In this embodiment, the label probe can also be either a primary (e.g. a fluorophore) or a secondary (biotin or enzyme) label. In one embodiment, the label probe comprises biotin, and a streptavidin/enzyme complex is used, as discussed herein. As above, for example, the complex can comprise horseradish peroxidase, and upon addition of TMB, the action of the horseradish peroxidase causes the TMB to precipitate, causing an optically detectable event.
Detection of a target species in some embodiments requires a “label” or “detectable marker” (as described below) that can be incorporated in a variety of ways. Thus, in various embodiments, the composition comprises a “label” or a “detectable marker.” In one embodiment, the target species (or target analyte or target sequence) is labeled; binding of the target species thus provides the label at the surface of the solid support.
In embodiments finding particular use herein, a sandwich format is utilized, in which target species are unlabeled. In these embodiments, a “capture” or “anchor” binding ligand is attached to the detection surface as described herein, and a soluble binding ligand (frequently referred to herein as a “signaling probe,” “label probe” or “soluble capture ligand”) binds independently to the target species and either directly or indirectly comprises at least one label or detectable marker.
By “label” or “labeled” herein is meant that a compound has at least one molecule, element, isotope or chemical compound attached to enable the detection of the compound. In general, labels fall into four classes: a) isotopic labels, which may be radioactive or heavy isotopes; b) magnetic, electrical, thermal; c) colored or luminescent dyes; and d) enzymes; although labels include particles such as magnetic particles as well. The dyes may be chromophores or phosphors but are preferably fluorescent dyes, which due to their strong signals provide a good signal-to-noise ratio for decoding. Suitable dyes for use in the invention include, but are not limited to, fluorescent lanthanide complexes, including those of Europium and Terbium, fluorescein, rhodamine, tetramethylrhodamine, eosin, erythrosin, coumarin, methyl-coumarins, pyrene, Malacite green, stilbene, Lucifer Yellow, Cascade Blue, Texas Red, Alexa dyes and others described in the 6th Edition of the Molecular Probes Handbook by Richard P. Haugland, hereby expressly incorporated by reference. Additional labels include nanocrystals or Q-dots as described in U.S. Pat. No. 6,544,732 incorporated by reference.
In various embodiments, a secondary detectable label is used. A secondary label is one that is indirectly detected; for example, a secondary label can bind or react with a primary label for detection, can act on an additional product to generate a primary label (e.g. enzymes), or may allow the separation of the compound comprising the secondary label from unlabeled materials, etc. Secondary labels include, but are not limited to, one of a binding partner pair; chemically modifiable moieties; nuclease inhibitors, enzymes such as horseradish peroxidase, alkaline phosphatases, lucifierases, etc. Secondary labels can also include additional labels.
In various embodiments, the secondary label is a binding partner pair. For example, the label may be a hapten or antigen, which will bind its binding partner. For example, suitable binding partner pairs include, but are not limited to: antigens (such as proteins (including peptides)) and antibodies (including fragments thereof (F_abs, etc.)); proteins and small molecules, including biotin/streptavidin; enzymes and substrates or inhibitors; other protein-protein interacting pairs; receptor-ligands; and carbohydrates and their binding partners. Nucleic acid-nucleic acid binding proteins pairs are also useful. In general, the smaller of the pair is attached to the NTP for incorporation into the primer. Preferred binding partner pairs include, but are not limited to, biotin (or imino-biotin) and streptavidin, digeoxinin and Abs, and Prolinx™ reagents.
In the sandwich formats of the invention, an enzyme serves as the secondary label, bound to the soluble capture ligand. Of particular use in some embodiments is the use of horseradish peroxidase, which when combined with 3,3′,5,5′-tetramethylbenzidine (TMB) forms a colored precipitate which is then detected. In some cases, the soluble capture ligand comprises biotin, which is then bound to a enzyme-streptavidin complex and forms a colored precipitate with the addition of TMB.
In various embodiments, the label or detectable marker is a conjugated enzyme (for example, horseradish peroxidase). In various embodiments, the system relies on detecting the precipitation of a reaction product or on a change in, for example, electronic properties for detection. In various embodiments, none of the compounds comprises a label.
As used herein, the term “fluorescent signal generating moiety” or “fluorophore” refers to a molecule or part of a molecule that absorbs energy at one wavelength and re-emits energy at another wavelength. Fluorescent properties that can be measured include fluorescence intensity, fluorescence lifetime, emission spectrum characteristics, energy transfer, and the like.
Signals from single molecules can be generated and detected by a number of detection systems, including, but not limited to, scanning electron microscopy, near field scanning optical microscopy (NSOM), total internal reflection fluorescence microscopy (TIRFM), and the like. Abundant guidance is found in the literature for applying such techniques for analyzing and detecting nanoscale structures on surfaces, as evidenced by the following references that are incorporated by reference: Reimer et al, editors, Scanning Electron Microscopy: Physics of Image Formation and Microanalysis, 2nd Edition (Springer, 1998); Nie et al, Anal. Chem., 78: 1528-1534 (2006); Hecht et al, Journal Chemical Physics, 112: 7761-7774 (2000); Zhu et al, editors, Near-Field Optics: Principles and Applications (World Scientific Publishing, Singapore, 1999); Drmanac, PCT Publication WO/2004/076683; Lehr et al, Anal. Chem., 75: 2414-2420 (2003); Neuschafer et al, Biosensors & Bioelectronics, 18: 489-497 (2003); Neuschafer et al, U.S. Pat. No. 6,289,144; and the like.
Thus, a detection system for fluorophores includes any device that can be used to measure fluorescent properties as discussed above. In various embodiments, the detection system comprises an excitation source, a fluorophore, a wavelength filter to isolate emission photons from excitation photons and a detector that registers emission photons and produces a recordable output, in some embodiments as an electrical signal or a photographic image. Examples of detection devices include without limitation spectrofluorometers and microplate readers, fluorescence microscopes, fluorescence scanners (including e.g. microarray readers) and flow cytometers.
In various exemplary embodiments, the binding of the biomarker to the binding ligand is specific or selective, and the binding ligand is part of a binding pair. By “specifically bind” or “selectively bind” or “selective for” a biomarker herein is meant that the ligand binds the biomarker with specificity sufficient to differentiate between the biomarker and other components or contaminants of the test sample.
The term “solid support” or “substrate” refers to any material that can be modified to contain discrete individual sites appropriate for the attachment or association of a capture binding ligand. Suitable substrates include metal surfaces such as gold, electrodes, glass and modified or functionalized glass, plastics (including acrylics, polystyrene and copolymers of styrene and other materials, polypropylene, polyethylene, polybutylene, polycarbonate, polyurethanes, Teflon, derivatives thereof, etc.), polysaccharides, nylon or nitrocellulose, resins, mica, silica or silica-based materials including silicon and modified silicon, carbon, metals, inorganic glasses, fiberglass, ceramics, GETEK (a blend of polypropylene oxide and fiberglass) and a variety of other polymers. Of particular use in the present invention are the ClonDiag materials described below.
Frequently, the surface of a biochip comprises a plurality of addressable locations, each of which comprises a capture binding ligand. An “array location,” “addressable location,” “pad” or “site” herein means a location on the substrate that comprises a covalently attached capture binding ligand. An “array” herein means a plurality of capture binding ligands in a regular, ordered format, such as a matrix. The size of the array will depend on the composition and end use of the array. Arrays containing from about two or more different capture binding ligands to many thousands can be made. Generally, the array will comprise 3, 4, 5, 6, 7 or more types of capture binding ligands depending on the end use of the array. In the present invention, the array can include controls, replicates of the markers and the like. Exemplary ranges are from about 3 to about 50. In some embodiments, the compositions of the invention may not be in array format; that is, for some embodiments, compositions comprising a single capture ligand may be made as well. In addition, in some arrays, multiple substrates may be used, either of different or identical compositions. Thus for example, large arrays may comprise a plurality of smaller substrates.
Accordingly, in one aspect, the invention provides a composition comprising a solid support comprising a capture binding ligand for each biomarker of a biomarker panel. In various embodiments, the capture ligand is a nucleic acid. In various embodiments, the capture binding ligand is an antibody. In various embodiments, the composition further comprises a soluble binding ligand for each biomarker of a biomarker panel.
A number of different biochip array platforms as known in the art may be used. For example, the compositions and methods of the present invention can be implemented with array platforms such as GeneChip® (Affymetrix), CodeLink™ Bioarray (Amersham), Expression Array System (Applied Biosystems), SurePrint microarrays (Agilent), Sentrix® LD BeadChip or Sentrix® Array Matrix (Illumina) and Verigene (Nanosphere).
In various exemplary embodiments, detection and measurement of biomarkers utilizes colorimetric methods and systems in order to provide an indication of binding of a target analyte or target species. In colorimetric methods, the presence of a bound target species such as a biomarker will result in a change in the absorbance or transmission of light by a sample or substrate at one or more wavelengths. Detection of the absorbance or transmission of light at such wavelengths thus provides an indication of the presence of the target species.
A detection system for colorimetric methods includes any device that can be used to measure colorimetric properties as discussed above. Generally, the device is a spectrophotometer, a colorimeter or any device that measures absorbance or transmission of light at one or more wavelengths. In various embodiments, the detection system comprises a light source; a wavelength filter or monochromator; a sample container such as a cuvette or a reaction vial; a detector, such as a photoresistor, that registers transmitted light; and a display or imaging element.
In various exemplary embodiments, a ClonDiag chip platform is used for the colorimetric detection of biomarkers. In various embodiments, a ClonDiag ArrayTube (AT) is used. One unique feature of the ArrayTube is the combination of a micro probe array (the biochip) and micro reaction vial. In various embodiments, where a target sequence is a nucleic acid, detection of the target sequence is done by amplifying and biotinylating the target sequence contained in a sample and optionally digesting the amplification products. The amplification product is then allowed to hybridize with probes contained on the ClonDiag chip. A solution of a streptavidin-enzyme conjugate, such as Poly horseradish peroxidase (HRP) conjugate solution, is contacted with the ClonDiag chip. After washing, a dye solution such as o-dianisidine substrate solution is contacted with the chip. Oxidation of the dye results in precipitation that can be detected colorimetrically. Further description of the ClonDiag platform is found in Monecke S, Slickers P, Hotzel H et al., Clin Microbiol Infect 2006, 12: 718-728; Monecke S, Berger-Bächi B, Coombs C et al., Clin Microbiol Infect 2007, 13: 236-249; Monecke S, Leube I and Ehricht R, Genome Lett 2003, 2: 106-118; Monecke S and Ehricht R, Clin Microbiol Infect 2005, 11: 825-833; German Patent DE 10201463; US Publication US/2005/0064469 and ClonDiag, ArrayTube (AT) Experiment Guideline for DNA-Based Applications, version 1.2, 2007, all incorporated by reference in their entirety. One of skill in the art will appreciate that numerous other dyes that react with a peroxidase can be utilized to produce a colorimetric change, such as 3,3′,5,5′-tetramethylbenzidine (TMB). For information on specific assay protocols, see www.clondiag.com/technologies/publications.php.
In various embodiments, where a target species is a protein, the ArrayTube biochip comprises capture binding ligands such as antibodies. A sample is contacted with the biochip, and any target species present in the sample is allowed to bind to the capture binding ligand antibodies. A soluble capture binding ligand or a detection compound such as a horseradish peroxidase conjugated antibody is allowed to bind to the target species. A dye, such as TMB, is then added and allowed to react with the horseradish peroxidase, causing precipitation and a color change that is detected by a suitable detection device. Further description of protein detection using ArrayTube is found in, for example, Huelseweh B, Ehricht R and Marschall H-J, Proteomics, 2006, 6, 2972-2981; and ClonDiag, ArrayTube (AT) Experiment Guideline for Protein-Based Applications, version 1.2, 2007, all incorporated by reference in their entirety.
Transmission detection and analysis is performed with a ClonDiag AT reader instrument. Suitable reader instruments and detection devices include the ArrayTube Workstation ATS and the ATR 03.
In addition to ArrayTube, the ClonDiag ArrayStrip (AS) can be used. The ArrayStrip provides a 96-well format for high volume testing. Each ArrayStrip consists of a standard 8-well strip with a microarray integrated into the bottom of each well. Up to 12 ArrayStrips can be inserted into one microplate frame enabling the parallel multiparameter testing of up to 96 samples. The ArrayStrip can be processed using the ArrayStrip Processor ASP, which performs all liquid handling, incubation, and detection steps required in array based analysis. In various embodiments, where a protein is detected, a method of using the ArrayStrip to detect the protein comprises conditioning the AS array with buffer or blocking solution; loading of up to 96 sample solutions in the AS wells to allow for binding of the protein; 3×washing; conjugating with a secondary antibody linked to HRP; 3×washing; precipitation staining with TMB; and AS array imaging and optional data storage.
Those skilled in the art will be familiar with numerous additional immunoassay formats and variations thereof which may be useful for carrying out the method disclosed herein. See generally E. Maggio, Enzyme-Immunoassay, (CRC Press, Inc., Boca Raton, Fla., 1980); see also U.S. Pat. Nos. 4,727,022; 4,659,678; 4,376,110; 4,275,149; 4,233,402; and 4,230,767.
In general, immunoassays carried out in accordance with the present invention may be homogeneous assays or heterogeneous assays. In a homogeneous assay the immunological reaction usually involves the specific antibody (e.g., anti-biomarker protein antibody), a labeled analyte, and the sample of interest. The signal arising from the label is modified, directly or indirectly, upon the binding of the antibody to the labeled analyte. Both the immunological reaction and detection of the extent thereof can be carried out in a homogeneous solution. Immunochemical labels which may be employed include free radicals, radioisotopes, fluorescent dyes, enzymes, bacteriophages, or coenzymes.
In a heterogeneous assay approach, the reagents are usually the sample, the antibody, and means for producing a detectable signal. Samples as described above may be used. The antibody can be immobilized on a support, such as a bead (such as protein A and protein G agarose beads), plate or slide, and contacted with the specimen suspected of containing the antigen in a liquid phase. The support is then separated from the liquid phase and either the support phase or the liquid phase is examined for a detectable signal employing means for producing such signal. The signal is related to the presence of the analyte in the sample. Means for producing a detectable signal include the use of radioactive labels, fluorescent labels, or enzyme labels. For example, if the antigen to be detected contains a second binding site, an antibody which binds to that site can be conjugated to a detectable group and added to the liquid phase reaction solution before the separation step. The presence of the detectable group on the solid support indicates the presence of the antigen in the test sample. Examples of suitable immunoassays include immunoblotting, immunofluorescence methods, immunoprecipitation, chemiluminescence methods, electrochemiluminescence (ECL) or enzyme-linked immunoassays.
Antibodies can be conjugated to a solid support suitable for a diagnostic assay (e.g., beads such as protein A or protein G agarose, microspheres, plates, slides or wells formed from materials such as latex or polystyrene) in accordance with known techniques, such as passive binding. Antibodies as described herein may likewise be conjugated to detectable labels or groups such as radiolabels (e.g., ³⁵S, ¹²⁵I, ¹³¹I), enzyme labels (e.g., horseradish peroxidase, alkaline phosphatase), and fluorescent labels (e.g., fluorescein, Alexa, green fluorescent protein, rhodamine) in accordance with known techniques.
Using any of the methods and compositions described herein, a sample can be assayed to determine levels of a biomarker panel. Thus, in one aspect, the invention provides a method of assaying a sample from a patient to determine concentrations of a biomarker panel in the sample. In some embodiments, the method comprises contacting the sample with a composition comprising a solid support comprising a capture binding ligand or capture probe for each biomarker of a biomarker panel.
The invention further provides kits for use in determining breast health or breast cancer status for a number of medical (including diagnostic and therapeutic), industrial, forensic and research applications. Kits may comprise a carrier, such as a box, carton, tube or the like, having in close confinement therein one or more containers, such as vials, tubes, ampoules, bottles, pouches, envelopes and the like. In various embodiments, the kits comprise one or more components selected from one or more media or media ingredients and reagents for the measurement of the various biomarkers and biomarker panels disclosed herein. For example, kits of the invention may also comprise, in the same or different containers, one or more DNA polymerases, one or more primers, one or more suitable buffers, one or more nucleotides (such as deoxynucleoside triphosphates (dNTPs) and preferably fluorescently labeled dNTPs) and labeling components. The one or more components may be contained within the same container, or may be in separate containers to be admixed prior to use. The kits of the present invention may also comprise one or more instructions or protocols for carrying out the methods of the present invention. The kits may also comprise a computer or a component of a computer, such as a computer-readable storage medium or device. Examples of storage media include, without limitation, optical disks such as CD, DVD and Blu-ray Discs (BD); magneto-optical disks; magnetic media such as magnetic tape and internal hard disks and removable disks; semi-conductor memory devices such as EPROM, EEPROM and flash memory; and RAM. The computer-readable storage medium may comprise software encoding references to the various therapies and treatment regimens disclosed herein. The software may be interpreted by a computer to provide the practitioner with treatments according to various measured concentrations of biomarkers as provided herein. In various embodiments, the kit comprises a biomarker assay involving a lateral-flow-based point-of-care rapid test with detection of risk thresholds, or a biochip with quantitative assays for the constituent biomarkers.

Methods of Diagnosing and Treating

The compositions and methods of the present invention can be used in the prognosis, diagnosis and treatment of disease in a subject. The invention provides compositions and methods for laboratory and point-of-care tests for measuring biomarkers in a sample from a subject. The invention can be generally applied for a number of different diseases. In exemplary embodiments, the disease is breast cancer.
The biomarkers and biomarker panels disclosed herein can be used in methods to diagnose, identify or screen subjects that have, do not have or are at risk for having disease; to monitor subjects that are undergoing therapies for disease; to determine or suggest a new therapy or a change in therapy; to differentially diagnose disease states associated with the disease from other diseases or within sub-classifications of disease; to evaluate the severity or changes in severity of disease in a patient; to stage a subject with the disease and to select or modify therapies or interventions for use in treating subjects with the disease. In an exemplary embodiment, the methods of the present invention are used to identify and/or diagnose subjects who are asymptomatic or presymptomatic for a disease. In this context, “asymptomatic” or “presymptomatic” means not exhibiting the traditional symptoms or enough abnormality for disease.
In various embodiments, a method of determining a prognosis of a disease in a subject, diagnosing a disease in a subject, or treating a disease in a subject comprises taking a measurement of a biomarker panel in a sample from the subject. In various exemplary embodiments, the biomarker panel consists of two or more of S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4, and/or CA6.
The term “disease status” includes any distinguishable manifestation of the disease, including non-disease. For example, disease status includes, without limitation, the presence or absence of disease, the risk of developing disease, the stage of the disease, the progression of disease (e.g., progress of disease or remission of disease over time), the severity of disease and the effectiveness or response to treatment of disease.
A “subject” in the context of the present invention is an animal, preferably a mammal. The mammal can be a human, non-human primate, mouse, rat, dog, cat, horse, or cow, but are not limited to these examples. In various exemplary embodiments, a subject is human and may be referred to as a patient. Mammals other than humans can be advantageously used as subjects that represent animal models of a disease or for veterinarian applications. A subject can be one who has been previously diagnosed or identified as having a disease, and optionally has already undergone, or is undergoing, a therapeutic intervention for a disease. Alternatively, a subject can also be one who has not been previously diagnosed as having a disease. For example, a subject can be one who exhibits one or more risk factors for a disease, or one who does not exhibit a disease risk factor, or one who is asymptomatic for a disease. A subject can also be one who is suffering from or at risk of developing a disease. In certain embodiments, the subject can be already undergoing therapy or can be a candidate for therapy.
As will be appreciated by those in the art, the biomarkers may be measured in using several techniques designed to achieve more predictable subject and analytical variability.
The term “sample” refers to a specimen or culture obtained from a subject and includes fluids, gases and solids including for example tissue. In various exemplary embodiments, the sample comprises saliva. As will be appreciated by those in the art, virtually any experimental manipulation or sample preparation steps may have been done on the sample. For example, wash steps and/or fragmentation may be applied to a sample. In various embodiments, a biomarker panel is measured directly in a subject without the need to obtain a separate sample from the patient.
In one aspect, the invention provides a method of diagnosing a subject for a disease comprising taking a measurement of a biomarker panel; and correlating the measurement with the disease. The term “correlating” generally refers to determining a relationship between one type of data with another or with a state. In various embodiments, correlating the measurement with disease comprises comparing the measurement with a reference biomarker profile or some other reference value. In various embodiments, correlating the measurement with disease comprises determining whether the subject is currently in a state of disease.
The quantity or activity measurements of a biomarker panel can be compared to a reference value. Differences in the measurements of biomarkers in the subject sample compared to the reference value are then identified. In exemplary embodiments, the reference value is given by a risk category as described further below.
In various embodiments, the reference value is a baseline value. A baseline value is a composite sample of an effective amount of biomarkers from one or more subjects who do not have a disease, who are asymptomatic for a disease or who have a certain level of a disease. A baseline value can also comprise the amounts of biomarkers in a sample derived from a subject who has shown an improvement in risk factors of a disease as a result of treatments or therapies. In these embodiments, to make comparisons to the subject-derived sample, the amounts of biomarkers are similarly calculated. A reference value can also comprise the amounts of biomarkers derived from subjects who have a disease confirmed by an invasive or non-invasive technique, or are at high risk for developing a disease. Optionally, subjects identified as having a disease, or being at increased risk of developing a disease are chosen to receive a therapeutic regimen to slow the progression of a disease, or decrease or prevent the risk of developing a disease. A disease is considered to be progressive (or, alternatively, the treatment does not prevent progression) if the amount of biomarker changes over time relative to the reference value, whereas a disease is not progressive if the amount of biomarkers remains constant over time (relative to the reference population, or “constant” as used herein). The term “constant” as used in the context of the present invention is construed to include changes over time with respect to the reference value.
The biomarkers of the present invention can be used to generate a “reference biomarker profile” of those subjects who do not have a disease according to a certain threshold, are not at risk of having a disease or would not be expected to develop a disease. The biomarkers disclosed herein can also be used to generate a “subject biomarker profile” taken from subjects who have a disease or are at risk for having a disease. The subject biomarker profiles can be compared to a reference biomarker profile to diagnose or identify subjects at risk for developing a disease, to monitor the progression of disease, as well as the rate of progression of disease, and to monitor the effectiveness of disease treatment modalities. The reference and subject biomarker profiles of the present invention can be contained in a machine-readable medium, such as but not limited to, analog tapes like those readable by a VCR; optical media such as CD-ROM, DVD-ROM and the like; and solid state memory, among others.
Measurements of the biomarker panels of the invention can lead a practitioner to affect a therapy with respect to a subject. Thus, the invention provides methods of treating a disease in a subject comprising taking a measurement of a biomarker panel in a sample from the subject, and affecting a therapy with respect to the subject. The terms “therapy” and “treatment” may be used interchangeably. In certain embodiments, the therapy can be selected from, without limitation, initiating therapy, continuing therapy, modifying therapy or ending therapy. A therapy also includes any prophylactic measures that may be taken to prevent disease.
In certain embodiments, treatment comprises administering a disease-modulating drug to a subject. The drug can be a therapeutic or prophylactic used in subjects diagnosed or identified with a disease or at risk of having the disease. In certain embodiments, modifying therapy refers to altering the duration, frequency or intensity of therapy, for example, altering dosage levels.
In various embodiments, effecting a therapy comprises causing a subject to or communicating to a subject the need to make a change in lifestyle, for example, increasing exercise, changing diet, reducing or eliminating smoking and so on. The therapy can also include surgery, for example, mastectomy.
Measurement of biomarker levels allow for the course of treatment of a disease to be monitored. The effectiveness of a treatment regimen for a disease can be monitored by detecting one or more biomarkers in an effective amount from samples obtained from a subject over time and comparing the amount of biomarkers detected. For example, a first sample can be obtained prior to the subject receiving treatment and one or more subsequent samples are taken after or during treatment of the subject. Changes in biomarker levels across the samples may provide an indication as to the effectiveness of the therapy.
To identify therapeutics or drugs that are appropriate for a specific subject, a test sample from the subject can also be exposed to a therapeutic agent or a drug, and the level of one or more biomarkers can be determined. Biomarker levels can be compared to a sample derived from the subject before and after treatment or exposure to a therapeutic agent or a drug, or can be compared to samples derived from one or more subjects who have shown improvements relative to a disease as a result of such treatment or exposure. Thus, in one aspect, the invention provides a method of assessing the efficacy of a therapy with respect to a subject comprising taking a first measurement of a biomarker panel in a first sample from the subject; effecting the therapy with respect to the subject; taking a second measurement of the biomarker panel in a second sample from the subject and comparing the first and second measurements to assess the efficacy of the therapy.
Additionally, therapeutic or prophylactic agents suitable for administration to a particular subject can be identified by detecting a biomarker (which may be two or more) in an effective amount from a sample obtained from a subject and exposing the subject-derived sample to a test compound that determines the amount of the biomarker(s) in the subject-derived sample. Accordingly, treatments or therapeutic regimens for use in subjects having a disease or subjects at risk for developing a disease can be selected based on the amounts of biomarkers in samples obtained from the subjects and compared to a reference value. Two or more treatments or therapeutic regimens can be evaluated in parallel to determine which treatment or therapeutic regimen would be the most efficacious for use in a subject to delay onset, or slow progression of a disease. In various embodiments, a recommendation is made on whether to initiate or continue treatment of a disease.

Drug Treatments

In various exemplary embodiments, effecting a therapy comprises administering a disease-modulating drug to the subject. The subject may be treated with one or more disease-modulating drugs until altered levels of the measured biomarkers return to a baseline value measured in a population not suffering from the disease, experiencing a less severe stage or form of a disease or showing improvements in disease biomarkers as a result of treatment with a disease-modulating drug. Additionally, improvements related to a changed level of a biomarker or clinical parameter may be the result of treatment with a disease-modulating drug.
A number of compounds such as a disease-modulating drug may be used to treat a subject and to monitor progress using the methods of the invention. In certain embodiments, the disease-modulating drug comprises
The beneficial effects of these and other drugs can be visualized by assessment of clinical and laboratory biomarkers.
Any drug or combination of drugs disclosed herein may be administered to a subject to treat a disease. The drugs herein can be formulated in any number of ways, often according to various known formulations in the art or as disclosed or referenced herein.
In various embodiments, any drug or combination of drugs disclosed herein is not administered to a subject to treat a disease. In these embodiments, the practitioner may refrain from administering the drug or combination of drugs, may recommend that the subject not be administered the drug or combination of drugs or may prevent the subject from being administered the drug or combination of drugs.
In various embodiments, one or more additional drugs may be optionally administered in addition to those that are recommended or have been administered. An additional drug will typically not be any drug that is not recommended or that should be avoided. In exemplary embodiments, one or more additional drugs comprise one or more glucose lowering drugs.

Decision Matrices

The therapy chosen by a practitioner can depend on the concentrations of biomarkers determined in a sample. In various exemplary embodiments, the therapy depends on which category from a range of categories particular to each biomarker the measured concentration of each biomarker falls in. In various exemplary embodiments, the therapy depends on the combination of risk levels for different symptoms or diseases that are indicated by a biomarker panel.
With respect to concentration measurements of a biomarker, the term “category” refers to a subset of a partition of the possible concentrations that a biomarker may have. Each category may be associated with a label or classification chosen by the practitioner. The labels may be refer to, for example, the risk level of an individual for having or being subject to a disease state. The categories and labels may be derived from the current literature or according to the findings of the practitioner.
Each biomarker of a biomarker panel can thus be associated with a discrete set of categories, for example, risk categories. Combining one category from each biomarker forms a “decision point.” In various exemplary embodiments, the complete set of decision points comprises all possible n-tuples of categories, wherein n is the number of biomarkers in the biomarker panel. This complete set will have m₁×m₂× . . . m_npossible decision points, wherein in is the number of categories for biomarker i.
Every decision point can be associated with a condition or a disease state, which is not necessarily unique. That is, one or more decision points can be associated with the same disease state. The association of every possible decision point with a condition or disease state can be referred to as a “disease classification matrix” or a “disease classification tree.” Thus, by correlating a measurement of a biomarker panel with a decision point, the practitioner can classify the condition or disease state of a patient.
Every decision point can also be associated with a particular therapy, which is not necessarily unique. That is, one or more decision points can be associated with the same therapy. The association of every possible decision point with one or more therapies can be referred to as a “therapy decision matrix” or “therapy decision tree.”
Each decision point can be associated with more than one type of information. For example, both disease state and therapy can be indicated by a decision point.
The articles “a,” “an” and “the” as used herein do not exclude a plural number of the referent, unless context clearly dictates otherwise. The conjunction “or” is not mutually exclusive, unless context clearly dictates otherwise. The term “include” is used to refer to non-limiting examples.

EXAMPLES

The following examples are offered to illustrate, but not to limit the invention.

Example 1: Salivary Transciptomic Profiling and Analysis

Saliva Collection

Unstimulated whole saliva samples were collected with previously established protocols. Subjects were asked to refrain from eating, drinking, smoking, or oral hygiene procedures for at least 30 minutes before the collection. Lipstick was wiped off, and the subject rinsed her mouth once with plain water. Typically, patients donated approximately 5-10 ml of saliva. Samples were then centrifuged at 2,600 g for 15 minutes at 4° C. The supernatant was then stored at −80° C. until use. Of note, protease inhibitors cocktail, containing 1 μl aprotinin, 10 μl PMSF (phenylmethanesulfonyl fluoride) and 3 μl sodium orthovanadate (all from Sigma, St. Louis, Mo.) were added to each 1 ml saliva sample.
mRNA Isolation and Analysis
RNA was isolated from 330 μl of saliva supernatant using MagMax™ Viral RNA Isolation Kit (Ambion, Austin, Tex.). This process was automated using KingFisher® mL technology (Thermo Fisher Scientific, Waltham, Mass.), followed by TURBO™ DNase treatment (Ambion, Austin, Tex.) to remove contaminating DNA. 90 μl of extracted RNA (out of 100 μl) was concentrated to 11 μl and was linearly amplified using the RiboAmp® RNA Amplification kit (Molecular Devices, Sunnyvale, Calif.). After purification, cDNA was transcribed and biotinylated using GeneChip® Expression 3′-Amplification Reagents for in vitro transcription labeling (Affymetrix, Santa Clara, Calif.). Approximately 20 μg of labeled RNA were subsequently submitted for GeneChip® analysis using an Affymetrix Human Genome U133 Plus 2.0 Array. Chip hybridization and scanning were performed using the MIAME (Minimum Information About a Microarray Experiment) criteria. All Affymetrix Human Genome U133 Plus 2.0 Array data generated in this study were uploaded to the GEO database, accession number GSE20266.

Gene Array Statistical Analysis

The CEL files from all databases were imported into the statistical R 2.7.0 (hypertext transfer protocol://www.r-project.org) with same and ROC packages. The Probe Logarithmic Intensity Error Estimation (PLIER) expression measures were computed after background correction and quantile normalization for each microarray dataset. Probeset-level quantile normalization was performed across all samples to make the effect sizes similar among all datasets. Finally, for every probeset, significance analysis of microarray (SAM) was applied to identify differential expression between the cancer and healthy control samples. The probesets were then ranked by the false discovery rate (FDR) corrected p-values.

Screening of Biomarker Candidates

The biomarker candidates generated by microarray profiling were subjected to further screening by real-time quantitative RT-PCR (qPCR) on the same set of samples used for the microarray analysis. To accomplish this, total RNA was reverse-transcribed using reverse transcriptase and gene-specific primers using the following thermal cycling conditions: 1 min at 60° C., 30 min at 50° C., 2 min at 95° C., followed by 15 cycles of 15s at 95° C., 30s at 50° C., 10 s at 72° C. These steps were followed with a final extension of 5 min. at 72° C. and then cooling to 4° C. The preamplified product was cleaned using ExoSAP-IT (USB Corporation) and diluted 1/40 in water. 2 μl of the cDNA was used for qPCR.
qPCR was carried out in a 96-well plate in a reaction volume of 10 μl using power SYBR®-Green Master Mix (Applied Biosystems, Foster City, Calif.) for 15 min at 95° C. for initial denaturing, followed by 40 cycles of 95° C. for 30 s and 60° C. for 30 s in the ABI 7500HT Fast Real Time PCR system (Applied Biosystems, Foster City, Calif.). All qPCRS were performed in duplicate for all candidate mRNA. The specificity of the PCR was confirmed according to the melting curve of each gene, and the average threshold cycle (Ct) was examined.
Amplicon lengths were around 100-130 by for the outer primer pairs used in preamplification and 60-80 bp for the inner primer pairs used in qPCR. RT-qPCR primers were designed using Primer Express 3.0 software (Applied Biosystems, Foster City, Calif.). All primers were synthesized by Sigma-Genosys (Woodlands, Tex.), and the amplicons were intron spanning whenever possible.
Raw data were normalized by subtracting GAPDH Ct values from the biomarker Ct values to generate ΔCt. The Mann-Whitney rank sum test was used for between-group biomarker comparisons.

Primers for 11 Candidate Biomarkers and GAPDH

Gene symbol Primer name Primer sequences (5′-3′)

ATXN3

ATXN3-OF

GAAAAACAGCAGCAAAAGCA

ATXN3-IF

GGGGGACCTATCAGGACAGA

ATXN3-IR

CAAGTGCTCCTGAACTGGTG

ATXN3-OR

CCAAGTGCTCCTGAACTGGT

GRIK1

GRIK1-OF

CCGGACTGGTCCTTTCTGTA

GRIK1-IF

CCGGACTGGTCCTTTCTGTA

GRIK1-IR

AGCGTTGAAAGAGAGACACTG

GRIK1-OR

CAGTGAGATTCCCAGTTCTTCC

GRM1

GRM1-OF

GCAGGGAATGCCAATTCTAA

GRM1-IF

TGGCAAGTCTGTGTCATGGT

GRM1-IR

GCCACATATGCTGTCCCTTG

GRM1-OR

GCCGTCTCATTGGTCTTCAC

TPT1

TPT1-OF

TACCGTGAGGATGGTGTGAC

TPT1-IF

CAAATGTGGCAATTATTTTGGA

TPT1-IR

GATGACAAGCAGAAGCCAGTT

TPT1-OR

GATGACAAGCAGAAGCCAGT

RGS13

RGS13-OF

CTCACGGTGGAGCAGAATTT

RGS13-IF

CTCACGGTGGAGCAGAATTT

RGS13-IR

GGGACTGTGGCTGGATGTAA

RGS13-OR

TGGGTTCCTGAATGTTCCTG

S100A8

S100A8-OF

TCAGGAAAAAGGGTGCAGAC

S100A8-IF

TCAGGAAAAAGGGTGCAGAC

S100A8-IR

TGGAAGTTAACTGCACCATCA

S100A8-OR

ACGCCCATCTTTATCACCAG

CLDN15

CLDN15-OF

TTGTACCCCGGAACCAAGTA

CLDN15-IF

CGGAACCAAGTACGAGCTG

CLDN15-IR

CACCCAGGATGGAGATCAGT

CLDN15-OR

CTGGGTCCTCGTCAGAGC

IGF2BP1

IGF2B P1-OF

AGAATTTGACGGCAGCTGAG

IGF2BP1-IF

CCAGGTCATCGTGAAAATCA

IGF2BP1-IR

ATCTTCCGTTGAGCCATCTG

IGF2BP1-OR

ATGTCTCGGATCTTCCGTTG

CSTA

CSTA-OF

ACGGAAAATTGGAAGCTGTG

CSTA-IF

CATTAAGGTACGAGCAGGTGA

CSTA-IR

TTTGTCCGGGAAGACTTTTG

CSTA-OR

TTTGTCCGGGAAGACTTTTG

MDM4

MDM4-OF

GTGGCAGTGTACTGAATGCAA

MDM4-IF

TGGCAGTGTACTGAATGCAA

MDM4-IR

AAGGCCCAACAACGAAAAC

MDM4-OR

TCAGACGTGGAGAGAGAATGG

H6PD

H6PD-OF

GGCACAAGCTTCAGGTCTTC

H6PD-IF

GTCGTGGGCCAGTACCAGT

H6PD-IR

GTGGAAGCTGTCTGGCTTCT

H6PD-OR

GTGGAAGCTGTCTGGCTTCT

GAPDH

GAPDH-OF

CATTGCCCTCAACGACCACTT

GAPDH-IF

ACCACTTTGTCAAGCTCATTTCCT

GAPDH-IR

CACCCTGTTGCTGTAGCCAAAT

GAPDH-OR

ATGTGGGCCATGAGGTCCA

OF=Outer forward, IF=Inner forward, IR=Inner reverse, OR=Outer reverse. All primers were designed using Primer Express 3.0 software (Applied Biosystems, FosterCity, Calif.). The specificity of primers was checked using NCBI's GenBank BLAST search.

The data analysis for qPCR was performed using the 2^−Ctmethod, where GAPDH is used as the reference gene. The qPCR based gene expression values between two groups were compared using the non-parametric Wilcoxon test. To normalize for RNA input, qPCR was also performed for GAPDH. Raw data were normalized by subtracting GAPDH Ct values from the marker Ct values to provide ΔCt and then analyze with the stats, utilities packages from R 2.7.0 (world wide web.r-project.org) and the ROC package from Bioconductor 2.2 (world wide web.bioconductor.org). Statistical comparisons were made with the use of the Mann-Whitney U test with consideration of two different distributions for control and pancreatic cancer groups. Biomarkers that differentiated between groups of subjects (P value <0.05) were identified and compared by Area Under Curve (AUC) value. The AUC is based on constructing a receiver operating characteristic (ROC) curve which plots the sensitivity versus one minus the specificity. The AUC value is computed by numerical integration of the ROC curve. The range of this value can be 0.5 to 1.0. A value of 0.5 indicates that the biomarker is no better that a coin toss, while 1.0 indicates the relatively best diagnostic accuracy.

Example 2: Salivary Proteomic Profiling and Analysis

Protein Isolation and Analysis

Saliva from 13 healthy control subjects and 13 breast cancer subjects were centrifuged at 2600 g at 4° C. for 15 minutes. Saliva supernatant from the 13 health control subjects and 13 breast cancer subjects were pooled to form a control sample and a cancer sample for proteomic profiling. 250 μg of proteins in the pooled saliva samples were precipitated by methanol and then resuspended in 2-D cell lysis buffer (30 mM Tris-HCl, pH 8.8, containing 7M urea, 2M thiourea and 4% CHAPS detergent). The total proteins of each pooled sample, breast cancer and control, were labeled with the cyanine dyes Cy2 and Cy5 respectively. The two labeled sample sets were then combined and subjected to two-dimensional difference gel electrophoresis. After loading the labeled samples, isoelectric focusing (IEF) (pH3-10) was run following the protocol provided by Amersham BioSciences. The IPG strips were rinses in the SDS-gel running buffer before transferring to 13.5% SDS-gels. The SDS-gels were run at 15° C. until the dye front ran out of the gels. Gel images were scanned immediately following the SDS-PAGE using Typhoon TRIO™ (Amersham BioSciences). The fold change of the protein expression levels was obtained from in-gel DeCyder™ analysis.
Spots with fold changes larger than 1.5 on the gel were cut and then were washed multiple times to remove staining dye and other chemicals. Gel spots were dried to absorb maximum volume of digestion buffer. Dried 2D gel spots were rehydrated in digestion buffer containing sequencing grade modified trypsin (Promega, USA). Proteins were digested in-gel at 37° C. overnight. Digested peptides were extracted from the gel with TFA extraction buffer and with shaking. The digested tryptic peptides were desalted using C-18 Zip-tips (Millipore). The desalted peptides were mixed with CHCA matrix (α-cyano-4-hydroxycinnamic acid) and spotted into wells of a MALDI plate for MALDI-TOF MS (ABI4800) identification. Protein identification was based on peptide fingerprint mass mapping (using MS spectra) and peptide fragmentation mapping (using MS/MS spectra). Combined MS and MS/MS spectra were submitted for database search using GPS Explorer software equipped with the MASCOT search engine to identify proteins from primary sequence databases.

Screening of Biomarker Candidates

Four proteins (carbonic anhydrase VI, psoriasin, Transthyretin and Cyclophilin A) identified in the 2-D gel analysis (above) were subjected to Western blot analysis on the original sample set. Reduced protein samples (15 μs total protein per lane) were loaded onto a 10% bis-Tris gel and run at 150V in MES SDS running buffer for one hour. Pre-stained protein standard (Invitrogen) was used to track protein migration. The proteins were transferred to nitrocellulose membrane by using iBlot® (Invitrogen). The membrane was then washed in wash buffer containing 10 mM Tris-HCl, pH 7.6, 150 mM NaCl, and 0.1% (v/v) Tween®-20 (Sigma-Aldrich) before blocking for one hour in wash buffer containing 5% non-fat dry milk. After further washes in wash buffer, the membrane was incubated with primary antibody (mouse anti-human carbonic anhydrase VI (Lifespan Biotech) at 1 μg/ml, mouse anti-psoriasin (Abeam) at 1 μg/ml, mouse anti-actin (Sigma-Aldrich) at 1 μg/ml according to manufacturers instructions in blocking buffer at room temperature for 2 h. The membrane was then washed before applying the secondary antibody (anti-mouse IgG peroxidase-linked species specific whole antibody from sheep, GE Healthcare) according to manufacturer's instructions for one hour at room temperature. Finally, the membrane was washed and visualized using ECL Plus™ detection kit (GE Healthcare). The signal intensity of the bands was measured using Image J software (NIH, Bethesda, Md., USA). The intensity of a band representing the protein of interest was divided by the intensity of it corresponding (3-actin expression on the same blot for normalization.
The protein expression pattern of carbonic anhydrase VI and psoriasin was further tested by Western blot with a new subject sample set including 31 cancer subject samples and 62 control subject samples. All the samples were coded with a random number from 1 to 93 and used for blind testing by Western blot. The distribution of carbonic anhydrase VI shows significant difference in the cancer group as compared to the control group (p=0.009949).

Example 4: Screening Method

A patient undergoing routine dental care is screened during the visit. For example, a 62 year old female patient, and former smoker, prior to oral exam is asked to provide a saliva sample. A saliva sample is collected and analyzed either at the point of care or is submitted for analysis by a reference laboratory. The saliva sample is tested for the biomarkers of the instant invention and optionally other biomarkers. Results from the analysis are provided to the dental professional and the patient is informed as to whether she has breast cancer.

(S100A8)(NM_002964.4)

SEQ ID NO: 1

gagaaaccag agactgtagc aactctggca gggagaagct

gtctctgatg gcctgaagctgtgggcagct ggccaagcct

aaccgctata aaaaggagct gcctctcagc

cctgcatgtctcagtcagc tgtattcag aagacctggt

ggggcaagtc cgtgggcatc atgttgaccgagctggagaa

agccttgaac tctatcatcg acgtctacca caagtactcc

ctgataaaggggaatttcca tgccgtctac agggatgacc

tgaagaaatt gctagagacc gagtgtcctcagtatatcag

gaaaaagggt gcagacgtct ggttcaaaga gttggatatc

aacactgatggtgcagttaa cttccaggag ttcctcattc

tggtgataaa gatgggcgtg gcagcccaca aaaaaagcca

tgaagaaagc cacaaagagt agctgagtta ctgggcccag

aggctgggcc cctggacatg tacctgcaga ataataaagt

catcaatacc tcaaaaaaaa aa

(CSTA)(NM_005213)

SEQ ID NO: 2

tgctgtttgt ggaaaataaa gcattctata ggcggagcta

gtgaacgcct cttttaaaacacgagtctcc acacttccct

gttcactttg gttccagcat cctgtccagc aaagaagcaa

tcagccaaaa tgatacctgg aggcttatct gaggccaaac

ccgccactcc agaaatccag gagattgttg ataaggttaa

accacagctt gaagaaaaaa caaatgagac ttacggaaaa

ttggaagctg tgcagtataa aactcaagtt gttgctggaa

caaattacta cattaaggta cgagcaggtg ataataaata

tatgcacttg aaagtattca aaagtcttcc cggacaaaat

gaggacttgg tacttactgg ataccaggtt gacaaaaaca

aggatgacga gctgacgggc ttttagcagc atgtacccaa

agtgttctga ttccttcaac tggctactga gtcatgatcc

ttgctgataa atataaccat caataaagaa gcattctttt

ccaaagaaat tatttatca attatttctc atttattgta

ttaagcagaa attacctttt ctttctcaaa atcagtgtta

ttgctttaga gtataaactc catataaatt gatggcaatt

ggaaatctta taaaaactag tcaagcctaa tgcaactggc

taaaggatag taccaccctc acccccacca taggcaggct

ggatcgtgga ctatcaattc accagcctcc ttgttccctg

tggctgctga taacccaaca ttccatctct accctcatac

ttcaaaatta aatcaagtat tttacaaaaa aaaaaaaa

(GRM1)(NM_001114329)

SEQ ID NO: 3

agtgctgaag aaagagggca ctagtgtaca gcccagatcg

catccttgca ccgtctggat tagagctgag gcgtctgcaa

gccgagcgtg gccacggtcc tctggccccg ggaccatagc

gctgtctacc ccgactcagg tactcagcag catctagctc

accgctgcca acacgacttc cactgtactc ttgatcaatt

taccttgatg cactaccggt gaagaacggg gactcgaatt

cccttacaaa cgcctccagc ttgtagaggc ggtcgtggag

gacccagagg aggagacgaa ggggaaggag gcggtggtgg

aggaggcaaa ggccttggac gaccattgtt ggcgaggggc

accactccgg gagaggcggc gctgggcgtc ttgggggtgc

gcgccgggag cctgcagcgg gaccagcgtg ggaacgcggc

tggcaggctg tggacctcgt cctcaccacc atggtcgggc

tccttttgtt ttttttccca gcgatctttt tggaggtgtc

ccttctcccc agaagccccg gcaggaaagt gttgctggca

ggagcgtcgt ctcagcgctc ggtggccaga atggacggag

atgtcatcat tggagccctc ttctcagtcc atcaccagcc

tccggccgag aaagtgcccg agaggaagtg tggggagatc

agggagcagt atggcatcca gagggtggag gccatgttcc

acacgttgga taagatcaac gcggacccgg tcctcctgcc

caacatcacc ctgggcagtg agatccggga ctcctgctgg

cactatccg tggctctgga acagagcatt gagttcatta

gggactctct gatttccatt cgagatgaga aggatgggat

caaccggtgt ctgcctgacg gccagtccct ccccccaggc

aggactaaga agcccattgc gggagtgatc ggtcccggct

ccagctctgt agccattcaa gtgcagaacc tgctccagct

cttcgacatc ccccagatcg cttattcagc cacaagcatc

gacctgagtg acaaaacttt gtacaaatac ttcctgaggg

ttgtcccttc tgacactttg caggcaaggg ccatgcttga

catagtcaaa cgttacaatt ggacctatgt ctctgcagtc

cacacggaag ggaattatgg ggagagcgga atggacgctt

tcaaagagct ggctgcccag gaaggcctct gtatcgccca

ttctgacaaa atctacagca acgctgggga gaagagcta

gaccgactct tgcgcaaact ccgagagagg cttcccaagg

ctagagtggt ggtctgcttc tgtgaaggca tgacagtgcg

aggactcctg agcgccatgc ggcgccttgg cgtcgtgggc

gagttctcac tcattggaag tgatggatgg gcagacagag

atgaagtcat tgaaggttat gaggtggaag ccaacggggg

aatcacgata aagctgcagt ctccagaggt caggtcattt

gatgattatt tcctgaaact gaggctggac actaacacga

ggaatccctg gttccctgag ttctggcaac atcggttcca

gtgccgcctt ccaggacacc ttctggaaaa tcccaacttt

aaacgaatct gcacaggcaa tgaaagctta gaagaaaact

atgtccagga cagtaagatg gggtttgtca tcaatgccat

ctatgccatg gcacatgggc tgcagaacat gcaccatgcc

ctctgccctg gccacgtggg cctctgcgat gccatgaagc

ccatcgacgg cagcaagctg ctggacttcc tcatcaagtc

ctcattcatt ggagtatctg gagaggaggt gtggtttgat

gagaaaggag acgctcctgg aaggtatgat atcatgaatc

tgcagtacac tgaagctaat cgctatgact atgtgcacgt

tggaacctgg catgaaggag tgctgaacat tgatgattac

aaaatccaga tgaacaagag tggagtggtg cggtctgtgt

gcagtgagcc ttgcttaaag ggccagatta aggttatacg

gaaaggagaa gtgagctgct gctggatttg cacggcctgc

aaagagaatg aatatgtgca agatgagttc acctgcaaag

cttgtgactt gggatggtgg cccaatgcag atctaacagg

ctgtgagccc attcctgtgc gctatcttga gtggagcaac

atcgaatcca ttatagccat cgccttttca tgcctgggaa

tccttgttac cttgtttgtc accctaatct ttgtactgta

ccgggacaca ccagtggtca aatcctccag tcgggagctc

tgctacatca tcctagctgg catcttcctt ggttatgtgt

gcccattcac tctcattgcc aaacctacta ccacctcctg

ctacctccag cgcctcttgg ttggcctctc ctctgcgatg

tgctactctg ctttagtgac taaaaccaat cgtattgcac

gcatcctggc tggcagcaag aagaagatct gcacccggaa

gcccaggttc atgagtgcct gggctcaggt gatcattgcc

tcaattctga ttagtgtgca actaaccctg gtggtaaccc

tgatcatcat ggaaccccct atgcccattc tgtcctaccc

aagtatcaag gaagtctacc ttatctgcaa taccagcaac

ctgggtgtgg tggccccttt gggctacaat ggactcctca

tcatgagctg tacctactat gccttcaaga cccgcaacgt

gcccgccaac ttcaacgagg ccaaatatat cgcgttcacc

atgtacacca cctgtatcat ctggctagct tttgtgccca

tttactttgg gagcaactac aagatcatca caacttgat

tgcagtgagt ctcagtgtaa cagtggctct ggggtgcatg

ttcactccca agatgtacat cattattgcc aagcctgaga

ggaatgtccg cagtgccttc accacctctg atgttgtccg

catgcatgtt ggcgatggca agctgccctg ccgctccaac

actttcctca acatcttccg aagaaagaag gcaggggcag

ggaatgccaa gaagaggcag ccagaattct cgcccaccag

ccaatgtccg tcggcacatg tgcagctttg aaaaccccca

cactgcagtg aatgtttcta atggcaagtc tgtgtcatgg

tctgaaccag gtggaggaca ggtgcccaag ggacagcata

tgtggcaccg cctctctgtg cacgtgaaga ccaatgagac

ggcctgcaac caaacagccg tcatcaagcc cctcactaaa

agttaccaag gctctggcaa gagcctgacc tatcagata

ccagcaccaa gaccattac aacgtagagg aggaggagga

tgcccagccg attcgcttta gcccgcctgg tagccatcc

atggtggtgc acaggcgcgt gccaagcgcg gcgaccactc

cgcctctgcc gtcccacctg accgcagagg agacccccct

cttcctggcc gaaccagccc tccccaaggg cttgccccct

cctctccagc agcagcagca accccctcca cagcagaaat

cgctgatgga ccagctccag ggagtggtca gcaacttcag

taccgcgatc ccggattttc acgcggtgct ggcaggcccc

ggtggtcccg ggaacgggct gcggtccctg tacccgcccc

cgccacctcc gcagcacctg cagatgctgc cgctgcagct

gagcaccttt ggggaggagc tggtctcccc gcccgcggac

gacgacgacg acagcgagag gtttaagctc ctccaggagt

acgtgtatga gcacgagcgg gaagggaaca cggaagaaga

cgaactggaa gaggaggagg aggacctgca ggcggccagc

aaactgaccc cggatgattc gcctgcgctg acgcctccgt

cgcctttccg cgactcggtg gcctcgggca gctcggtgcc

cagctccccc gtgtccgagt cggtgctctg cacccctccc

aacgtatcct acgcctctgt cattctgcgg gactacaagc

aaagctcttc caccctgtaa gggggaaggg tccacataga

aaagcaagac aagccagaga tctcccacac ctccagagat

gtgcaaacag ctgggaggaa aagcctggga gtggggggcc

tcgtcgggag gacaggagac cgctgctgct gctgccgcta

ctgctgctgc tgccttaagt aggaagagag ggaaggacac

caagcaaaaa atgttccagg ccaggattcg gattcttgaa

ttactcgaag ccttctctgg gaagaaaggg aattctgaca

aagcacaatt ccatatggta tgtaactttt atcacaaatc

aaatagtgac atcacaaaca taatgtcctc ttttgcacaa

ttgtgcatag atatatatat gcccacacac actgggccat

gcttgccaag gaacagccca cgtggacatg ccagtcggat

catgagttca cctgatggca ttcggagtga gctggtggag

ccagacagag caggtgcggg gaagggaagg gcccaggcca

gacccatccc aaacggatga tgggatgatg ggacagcagc

tccttgctca gaagcccttc tccccgctgg gctgacagac

tcctcatctt caggagactc aggaatggag cggcacaggg

gtctctcttc atccactgca acccatccag tgccagatt

gagattgcac ttgaagaaag gtgcatggac cccctgctgc

tctgcagatt ccctttattt aggaaaacag gaataagagc

aaaattatca ccaaaaagtg cttcatcagg cgtgctacag

gaggaaggag ctagaaatag aacaatccat cagcatgaga

ctttgaaaaa aaaacacatg atcagcttct catgttccat

attcacttat tggcgatttg gggaaaaggc cggaacaaga

gattgttacg agagtggcag aaaccctttt gtagattgac

ttgtgtttgt gccaagcggg ctttccattg accttcagtt

aaagaacaaa ccatgtgaca aaattgttac cttccactta

ctgtagcaaa taatacctac aagttgaact tctaagatgc

gtatatgtac aatttggtgc cattatttct cctacgtatt

agagaaacaa atccatcttt gaatctaatg gtgtactcat

agcaactatt actggtttaa atgacaaata attctatcct

attgtcactg aagtccttgt aactagcgag tgaatgtgtt

cctgtgtcct tgtatatgtg cgatcgtaaa atttgtgcaa

tgtaatgtca aattgactgg tcaatgtcaa cctagtagtc

aatctaactg caattagaaa ttgtcttttg aatatactat

atatattttt tatgttccaa taatgttttg tacatcattg

tcatcaatat ctacagaagc tctttgacgg tttgaatact

atggctcaag gttttcatat gcagctcgga tggacatttt

tcttctaaga tggaacttat ttttcagata ttttctgatg

tggagatatg ttattaatga agtggtttga aaatttgtta

tattaaaagt gcacaaaaac tgagagtgaa aataaaaggt

acattttata agcttgcaca cattattaac acataagatt

gaacaaagca tttagattat tccaggttat atcatttttt

taaagatttt ccacagctac ttgagtgtct aacatacagt

aacatctaac tcagctaata atttgtaaaa tctttatcaa

tcacattttg ccttctttta atttttatgt tcatggactt

ttattcctgt gtcttggctg tcataacttt ttatttctgc

tatttgctgt tgtgtaatat ccatggacat gtaatccact

tactccatct ttacaatccc tttttaccac caataaaagg

atttttcttg ctgttttgat ttcttctatt atttgtggaa

tgaattatac cccccttaaa tatctttgtt tatgccttat

gttcagtcat attttaatat gatccttca tattgaagct

gctgatttct cagccaaaaa tcatcttaga atctttaaat

atccattgca tcatttgac agaatttaac atccattcca

atgttggagg cttgtattac ttatatttca tcatattcta

ttgccaagtt tagtcagttc cacaccaaga atgaactgca

tttcctttaa aaattatttt aaaacacctt tattgaaaag

atctcatgac tgagatgtgg actttggttc catgttttca

ttgtaagaaa gcagagagcg gaaaatcaat ggctccagtg

attaatagat gggtttttag taattgacaa attcatgagg

gaaagcatat gatctcttta ttagtgaatc atgcttattt

tttactata atgccactaa tatacatccc taatatcaca

gggcttgtgc attcagattt ttaaaaaatt aggatagata

aggaaacaac ttatattcaa gtgtaagatg atatcaggtt

ggtctaagac ttttggtgaa cacgttcatt caactgtgat

cactttatta ctctgaatgc ctactattat cctgattatg

gggtctcctg aataaataga gtattagtcc ttatgtcatc

attgttcaaa attggagatg tacacataca taccctatac

caagagggcc gaaactcttc accttgatgt atgttctgat

acaagttgtt cagcttcttg taaatgtgtt ttccttcggc

ttgttactgc cttttgtcaa ataatcttga caatgctgta

taataaatat tttctattt

(TPT1)(NM_003295.2)

SEQ ID NO: 4

ccccccgagc gccgctccgg ctgcaccgcg ctcgctccga

gtttcaggct cgtgctaagctagcgccgtc gtcgtctccc

ttcagtcgcc atcatgatta tctaccggga cctcatcagc

cacgatgaga tgttctccga catctacaag atccgggaga

tcgcggacgg gttgtgcctg gaggtggagg ggaagatggt

cagtaggaca gaaggtaaca ttgatgactc gctcattggt

ggaaatgcct ccgctgaagg ccccgagggc gaaggtaccg

aaagcacagt aatcactggt gtcgatattg tcatgaacca

tcacctgcag gaaacaagtt tcacaaaaga agcctacaag

aagtacatca aagattacat gaaatcaatc aaagggaaac

ttgaagaaca gagaccagaa agagtaaaac cttttatgac

aggggctgca gaacaaatca agcacatcct tgctaatttc

aaaaactacc agttctttat tggtgaaaac atgaatccag

atggcatggt tgctctattg gactaccgtg aggatggtgt

gaccccatat atgattact ttaaggatgg tttagaaatg

gaaaaatgtt aacaaatgtg gcaattattt tggatctatc

acctgtcatc ataactggct tctgcttgtc atccacacaa

caccaggact taagacaaat gggactgatg tcatcttgag

ctcttcattt attttgactg tgatttattt ggagtggagg

cattgttttt aagaaaaaca tgtcatgtag gttgtctaaa

aataaaatgc atttaaactc atttgagag

(GRIK1)(NM_000830.3; mRNA variant 1 of 2 shown)

SEQ ID NO: 5

agagcccctg caccaactca ccctgtaccc tctctccttc

ttcgttagtc ttctttcccc cttttccctc ctctgtctgt

gcctatcccc cgacttttgc atctgaccaa aggacgaatg

agggagacgt tcctgcagat cggggcagca actttcctca

gctggtctct gggctccggg agccagagag cgctgatcct

ccgcggtctg cggcccatgg aagaggagga ggaggagccg

tgatgggcta gcgacagcac tgaggagccc cgagagagct

cagccttgcc agccagctcc gcggtcccac gcgggttccc

tcgagctcgc tccgtgggga gcgcgcagcg tgcttggaac

cggagcatcc agagaggatg aggcggggac ccggcccaag

ttgggtgcat ctctcgggcg tccggcagcg gctgtatctc

ggcatgaatt aagaagctag gaagatggag cacggcacac

tcctcgccca gcccgggctc tggaccaggg acaccagctg

ggcactcctc tatttcctct gctatatcct ccctcagacc

gccccgcaag tactcaggat cggagggatt tttgaaacag

tggaaaatga gcctgttaat gttgaagaat tagctttcaa

gtttgcagtc accagcatta acagaaaccg aaccctgatg

cctaacacca cattaaccta tgacatccag agaattaacc

tttttgatag ttttgaagcc tcgcggagag catgtgacca

gctggctctt ggtgtggctg ctctctttgg cccttcccat

agctcctccg tcagtgctgt gcagtctatt tgcaatgctc

tcgaagttcc acacatacag acccgctgga aacacccctc

ggtggacaac aaagatttgt tttacatcaa cctttaccca

gattatgcag ctatcagcag ggcgatcctg gatctggtcc

tctattacaa ctggaaaaca gtgacagtgg tgtatgaaga

cagcacaggt ctaattcgtc tacaagagct catcaaagct

ccctccagat ataatattaa aatcaaaatc cgccagctgc

cctctgggaa taaagatgcc aagcctttac tcaaggagat

gaagaaaggc aaggagttct atgtgatatt tgattgttca

catgaaacag ccgctgaaat ccttaagcag attctgttca

tgggcatgat gaccgagtac tatcactact ttttcacaac

cctggactta tttgctttgg atctggaact ctataggtac

agtggcgtaa acatgaccgg gtttcggctg cttaacattg

acaaccctca cgtgtcatcc atcattgaga agtggtccat

ggagagactg caggccccac ccaggcccga gactggcctt

ttggatggca tgatgacaac tgaagcggct ctgatgtacg

atgctgtgta catggtggcc attgcctcgc accgggcatc

ccagctgacc gtcagctccc tgcagtgcca tagacataag

ccatggcgcc tcggacccag atttatgaac ctgatcaaag

aggcccggtg ggatggcttg actgggcata tcacctttaa

taaaaccaat ggcttgagga aggattttga tctggacatt

attagtctca aagaggaagg aactgaaaag gctgctggcg

aagtgtctaa acacttgtat aaagtgtgga agaagattgg

gatttggaat tccaacagtg ggcttaacat gacggacagc

aacaaagaca agtccagcaa tatcactgat tcattggcca

acagaacact cattgtcacc accattctgg aagaacccta

tgttatgtac aggaaatctg ataagcctct atatggaaat

gacagatttg aaggatattg cctagacctg ttgaaagaat

tgtcaaacat cctgggtttc atttatgatg ttaaactagt

tcccgatggc aaatatgggg cccagaatga caaaggggag

tggaacggga tggttaaaga actcatagat cacagggctg

acctggcagt ggctcctctt accatcacct acgtgcggga

gaaagtcatt gacttctcca aacccttcat gaccctaggc

atcagcattc tctaccggaa gcccaatggt accaatccag

gcgttttctc cttcctcaac cccctgtctc cagatatttg

gatgtatgtg ctcttagcct gcttgggagt cagctgtgta

ctctttgtga ttgcaaggtt tacaccctac gagtggtata

acccccaccc atgcaaccct gactcagacg tggtggaaaa

caattttact ttactaaata gtttctggtt tggagttgga

gctctcatgc agcaaggatc agagctgatg cccaaagctc

tatcgaccag aatagttgga gggatatggt ggtttttcac

cctaatcatc atttcatcct acacggccaa tctggctgcc

ttcttgacag tagagagaat ggaatccccc atagattcgg

cagatgatct ggcaaagcaa accaagatag aatatggggc

ggttagagat ggatcaacaa tgaccttctt caagaaatca

aaaatctcca cctatgagaa gatgtgggct ttcatgagca

gcaggcagca gaccgccctg gtaagaaaca gtgatgaggg

gatccagaga gtgctcacca cagactacgc gctgctgatg

gagtccacca gcattgagta tgtgacgcag agaaactgca

acctcactca gatcgggggc ctcattgact ccaaaggtta

cggagtggga acacctattg gttctcctta ccgggataaa

attactattg ctattcttca actccaagaa gaagggaagc

tgcatatgat gaaagagaag tggtggcgtg ggaatggctg

ccccgaggaa gacaacaaag aagccagtgc cctgggagtg

gaaaatattg gaggcatctt cattgttctg gctgccggac

tggtcctttc tgtatttgta gctattggag aattcatata

caaatcacgg aagaataatg atattgaaca ggattttgt

ttatttatg gactgcaatg taagcaaacc catccaacca

actccacttc tggaactact ttatctacgg atttagaatg

tggtaaatta attcgagagg agagagggat tcgaaaacag

tcctcagttc atactgtgta atcagtttaa a

(H6PD)(NM_004285)

SEQ ID NO: 6

tgaggcctga ggcctggggc ggggtggcgg ccgggctggc

cttggcctcg cgccttcccc tgcggccgcc gcgggctccg

cgggcggtat cggagtgtcg tgcggcgcgt ggccgcgtga

cacgcgcact tgtcggagtg acgggccctg cggaagagga

ggtgcggccc agggcgcagg ggagccctcg ggagcgggcc

cggccctcag cgccgccccg gccgtgtccc ggaggagcgg

cctgcgccgc cgcgcgagag gaagcaccca ggcatgtgga

atatgctcat agtggcgatg tgcttggccc ttctgggctg

cctgcaagcc caggagctcc agggacatgt ctccataatc

ctgctgggag caactgggga cctggctaag aagtacttat

ggcagggact gttccagctg tacctggatg aagcggggag

gggtcacagt tttagcttcc atggagctgc tctgacagcc

ccaagcagg gtcaagagct catggccaag gccctggaat

ccctctcctg ccccaaggac tggcaccca gtcactgtgc

agagcacaag gatcagttcc tgcagctgag ccagtaccgc

aactgaaga cggccgagga ctatcaggcc ctgaacaagg

acatcgaggc acagctccag acgcaggcc tccgggaggc

tggcaggatc ttctacttct cagtgccacc cttcgcctat

aagacattg cccgcaacat caacagtagc tgccggccag

gcccgggcgc ctggctgcgg ttgtccttg agaaaccctt

tggccatgac cacttctcag cccagcagct ggccacagaa

tcgggacct ttttccagga ggaggagatg taccgggtgg

accattactt aggcaagcag ctgtggcgc agatcctgcc

tttccgagac cagaaccgca aggctttgga cggcctctgg

accggcacc atgtggagcg ggtggagatc atcatgaaag

agaccgtgga tgctgaaggc gcaccagct tctatgagga

gtacggtgtc attcgcgacg tcctccagaa ccatctgacg

aggtcctca ccctcgtggc catggagctg ccccacaatg

tcagcagtgc ggaggctgtg ctgcggcaca agcttcaggt

cttccaggcg ctgcggggcc tgcagagggg cagtgccgtc

tgggccagt accagtctta cagtgagcag gtgcgcagag

agctgcagaa gccagacagc tccacagcc tgacgccgac

cttcgcagcc gtcctagtgc acattgacaa ccttcgctgg

agggcgtgc ctttcatcct gatgtctggc aaagccttgg

acgagagagt gggctacgct ggatcttgt tcaagaacca

ggcctgctgt gtgcagagcg aaaagcactg ggccgcggcg

agagccagt gcctgccccg gcagctcgtc ttccacatcg

gccatggcga cctgggcagc ctgccgtgc tggtcagcag

gaacctgttc aggccctccc tgccctccag ctggaaggaa

tggagggac cacctgggct ccgccttttc ggcagccctc

tgtccgatta ctacgcctac gccctgtgc gggagcggga

cgcccactcc gtcctcttat cccatatctt ccatggccgg

agaatttct tcatcaccac agagaacttg ctggcctcct

ggaacttctg gacccctctg tggagagcc tggcccataa

ggccccacgc ctctaccctg gaggagctga

gaatggccgtctgaggact ttgagttcag tagcggccgg

ttgactat cccagcagca gccggagcagctggtgccag

ggccagggcc ggccccaatg cccagtgact tccaggtcct

cagggccaag taccgagaga gcccgctggt ctccgcctgg

tccgaggagc tgatctctaa gctggctaat gacatcgagg

ccaccgctgt gcgagccgtg cggcgctttg gccagttcca

cctggcactg tcggggggct cgagccccgt ggccctgttc

cagcagctgg ccacggcgca ctatggcttc ccctgggccc

acacgcacct gtggctggtt gacgagcgct gcgtcccact

ctcagacccg gagtccaact tccagggcct gcaggcccac

ctgctgcagc acgtccggat cccctactac aacatccacc

ccatgcctgt gcacctgcag cagcggctct gcgccgagga

ggaccagggc gcccagatct atgccaggga gatctcagcc

ctggtggcca acagcagctt cgacctggtg ctgctgggca

tgggtgccga cgggcacaca gcctccctct tcccacagtc

acccactggc ctggatggcg agcagctggt cgtgctgacc

acgagcccct cccagccaca ccgccgcatg agccttagcc

tgcctctcat caaccgcgcc aagaaggtgg cagtcctggt

catgggcagg atgaagcgtg agatcaccac gctggtgagc

cgggtgggcc atgagcccaa gaagtggccc atctcgggtg

tcctgccgca ctccggccag ctggtgtggt acatggacta

cgacgccttc ctgggatgag ggcgcctgtg ccccttgccc

gcttcgctcc tgtgctttcc ttcgcccgtg tcttccctcc

cttctcggcc ccgccacctg cccagcgtgc cctggctctc

cagaaccttc tatcccacag tcaggcccca gagagggcag

gacaagcctt gtcccgatgc ctttgaccgg cagctctgtg

tattggtgga tagatgcaga aacaaggaag aaatggagtc

tgctcctgag aagcttcaaa ttcaggccag gagagaagtc

ttaagaaaag acctccagca gttacacatt catatcaacc

agcacaacac gggatggcgc ccaaactccg gcgttcacaa

gaggagacgt gacgtggtgg gctgaggtta atcagggaag

gtttcctggg ggaggtgatc cttgaactgg ctcccgggga

acattcagag catgattggt agacagaagg gtgcagaggc

gcccagggga gtacattgcc ccgtgcaaag caggggcatt

ggggactgtc ttgagaccct gagggggtca agcccctcct

tccccagctg cccctccttc tagaacctct gcacatctag

cctctggccc tcctcttcac tgcctccacc tgctcccgct

tgccatccct gtctcctcca tcctggctgt gcagtaggaa

ttccaggctc ctccctgtgt ctttgctgtt cttcagactc

catttataga gaatgagggc tgataacagg aatacagtgg

caaagactag actgtggaaa gggttccaga aatctttttt

cttttttaat taaaaaaaat atttgcagag atgagctctt

gctatgttgc ccaggctggt ctcaaactcc tgggctcaag

cgatcctccc atctcagcct cccagagtgc tgggattaca

ggtgtgagct actgcgccca gccccagaaa tctcagtgct

gtttggagct ccatttctca tttgatgact tgctctgcgt

ggggaggtgg ggtctcattc ccccaacttc ctcagggagg

acccctgccc tccgctgctc ctctgtcctg ctagccttcc

tccaggaagc acactgggtg cagataatca ggacattcca

gagatcccca atttaagagg gtcatttcca tctcagggga

ctcccggatg ggtgtttccg ctctcaatag cccctcttgt

tttaccagga aagatccagt taaatcaccc actgaggtga

cagctcatta gcggggagag agatggagca tcgagtgaca

ctgggccatc caggcggctc tgctcccacc agacaggagc

taggcctcac tggcaggggg gctgcccaca gccttttcag

gggctcgctt ggcgggtgac ggggccgcag ccaggccttc

tctccctgcc ccttggtgac cccgtggctt cctgtctgct

ggcctctcct gctacttatc acttcaccac gaactctctg

cctgagactg gggaagtaag cgggtatctt ctcagtgagc

ataggttggg gactgtgatc ttgagaagcc atgggccagc

aatacctgct tttctgaagc ccccaaggag ggctctgaca

ttctttttaa aaacaccaca aagcaaaatt cccaggacat

gtgtagtttt gtttgttcag tatcccacaa cttaaggctg

ggagatggaa ctcttggtta aggtcgattt ttctgtctgg

cttctccgca ccttccactt gctctctgga tcaggcagat

ataaactttc tagcgcattt tgagagaggg ctttcttggg

tgagggagca tggcaaagtc ggtttctctc tggactgttt

acacttcaag gcggtggatt tagaggaatc ctggattca

ttttcaatgc cagtctgaga catgttccca agccggggct

cttgttcaca ccacttactc tggccaccaa caacaaccca

ggccagacag agcatctat tttttttttt ttgagacaga

gtctctgtcg cccaggctgg agcccagtgg cgagatcttg

gctcactaca acctccacct cccgggttca ggcaattctc

gtgcctaagc ctcccgagta gctgcgacta caggcgccgg

ccagcatgcc tgtctaattt ttgtatttta gtagagacag

ggtttcacca tgttgcccag gctggtctcg aactcctgag

ctcaggcagt ctacccacct cagcctccca aagtgctggg

attacaggcg tgagccaccg cgcccagcca gaacatctgt

ttttacaccc agagagcgcc cctcgttagg acagaaccac

ggtgcccaga gccaggaagc cgccctcctg gcgcccagca

tctgagcttc tacacgtgat gggcgggctc aggagaggac

agggagtcgt ggtggaagtt ccacagctgg ccgcgtgggg

gggcccttgc accgcactgc cgcctcctga ctgcccctat

ccccgcagcc cctgtgccgg atttcatttc cctcctctct

cccagggtac ctggccccag cactctccca tctgttcttc

aggaaccgac tcctctccag ttgcaacacc agggagaaag

gggcctccac atgcccaagt acccctgcag gatgaagggc

aggccggccc ttgatgtgcc atttctgaat aatagtcact

gccgccgagt ctaggatgtc ctgttctaac tcagccctgc

ctcggatgca ccaccgatct gtgcagagtg ggtgtgggag

tgtgggtgag ggtcgaaatg ccaaaggtct actttccaga

atcaagtgcc ttctgcaaat catgttggaa aagtccaaac

ctggagatgt ccctgtgcct ccgcccctac ccaccccttt

tccttcagct gtgttaggaa ggagaagttt tcagaaccct

ctaggctggt ggctttcaaa cttcagacca gatctgcag

caagaaacgt gccttccatc ataaatcagt ccatttgttt

acaactgtgt ccaagcagg tttcataaag aaattcttaa

ccttagaacc tcggatatcc tctatgtttt agttttcatt

tttttaaaat gcttcttaaa attcactaaa ttgggctagg

tgtggctcat gcctgtaatc ccagcactat gggaggctga

ggtgagagga tcacttgagc ccagaaggtt gaaaccagcc

tgggcaacat agtgagaccc catctctaca aaaagtttta

aaaccaggta tggtggtgcc ctcctgtggt cccagctact

cgggagtctg aggtgggagg atcacctgag cccaggagac

tgaggctgca gtaaggtgtg attgcactat tgctctctag

caggaaaac agagtgagac cctatctcaa aaaaaaaaaa

aaaaaaaaag gaaagagtga tgacaacagc ccagggagca

gccccgctca gaacccaagt cccaagttcc agcactgtgt

tcccaggcag gctgtttgcc tcttcctggt ctggaagccc

ttgggtccta tggtggcggc agctcccaca tccaggttc

cctggtgggg accaatgatt ccatccgcat ggaagcccac

gtgtgcactt aggggcccat aaatggcaga agggcccctc

ctttgggaga ccttgtcagt cagcatctct agggcaaccg

tgattgccat ttgtagaggg gaaggaatca agggacttta

agctagatca aaatctgggg acaaattctc ctgctaactg

caagttaaaa taggcccttc ttactgaatt tccctgtttg

tttctctgca gacaatgctt tagccctact cttgggcccc

caagttagca gagtaatcaa agcttcctac cgtttggcct

actattccag actagtccct cgaggggttc ccttccaaaa

tatgcagggc tcaggctccc aattccgggc ctgtctgctt

tgcttgtgtt tctcctgtcc ctgttctccc ggagggccca

ggtggaactc acgacaggga gggagacgct tcccaaaaac

ctgcagggct atttcccaga atttggtttt caagtacaaa

actttttgtc ctgtaagata tatgcagcct cacagaagca

gcctctgcct ccactttacc agctacgttt ttatcttaag

cacatggggc tcccttagaa cttactccac tgatttaaaa

aaaaaaaact gcctggcagc atctcagtgt cagagtgagc

acggcacagg aaaggcccgt ggtgacgagg gtgaggtggc

cacagtgacc ggacgacaaa tgagactctg caaatgagac

tccagagggt gaagatctgc ggtctccaga catcataggc

catgtgaccc actaggggcc gcttacccct ggccgtccgc

tggctgaact gaacgcattc cctctctccg caactctccc

gtgaggctgc acccgtgtgg gtagcactgg aagcggcact

gtttgcattg tacataggaa ggaaggaagt tatccagcc

tcaccagcac ctggcagcga gtcagagcct gtgagggcat

ccgaagcagt gatgcagtgt caacctccca gctggtgcca

ctctgccctc gggggctcca agcattgtaa ctcagtcatg

ggagctgcct ctttggaagt gcagatttat tcctgtaata

atcctgcctg cttttacctc tcgtccactg accagcaagt

gtgagtcccg gtgtcagtcg gcacagtcca gtgtccatct

gcatttgctc atgcagaggg ggtgagttgg gcactccctg

ttgaggttt tccttttgca gcacactggg cagtctccct

ataaaacaaa aaccccacct tctgtgcctt ctgctttaga

gcagagctcc ccctcccatt tcctcagtct tccctgcaaa

atctgtccac cggggaaggc agcaggaacc ctgggcagcg

ggtgttctgg gaaggctagt gacagcagat gtcatccagg

aacagccaca cacggttctc caggccgccg tcagcagctc

aaggtggggt atgagtgaga agctgaggat ctcgcagctt

gttgctgagc aaggtgcaac cgggctcatg ctgtcatcag

cacaagacgg gatggcaagg gctttcagac gcatttccaa

gagtccagca agccaggggg aagatgatcc ctttgccgaa

gtgtaccctc tagccaactt ttgggagcgc ttctgtttgc

aaagcgctgg ggatgtgcct gtctctgtgt gacccacgaa

cgggaaggga gagcactgga gtaatgacac ttctgctgct

gctttgattc tcaaggctga tattaaaac cctcgccttg

ctgacaggtg ctttaaaggc agtctgcatc ttttatccc

ttggtgtggg agaggtaaac actttgattt gctgaaagct

gtatggagta tatttgaaca gctagtagtt agctttgaaa

gtggaagtgt gaacagacac tacttgtgtc gctttgggtc

cttcacttta cccccacaga agtctagagg cgtctgttat

aaagcgttac ggggcgcctg catgcaggag gaaggacctg

tattagctgg aaatcatcag gaacccagct tgcctccatc

tctctgagat gtgctgggta cagcctgccc ctcctagttc

tgtccaccgg gaagagccgg ctggcggcag atccccaggg

gcagagcccc tgctggatcc tgggagctca tctttacctg

tgccggagtg ggaactgtga ttccagccgg gcaggtcaga

gtggagcagt gctaagaggc tgttgcagga gaactagacg

ggcggggcct gctgcatctg gatcatgttt ctgtgctctg

ccccgcgcta gggactcagg gtctgggctt ctgccaggtg

aggagcagag agactgttcc cttgggtgga gaggtgtggg

catgagagcc acccattgcc aagcagcaag aatgttcgtg

cttttttcca gagaggggaa ccccactggt ttttgtggaa

acaatggaaa cttacagatg cctgcctggg atgatgaggc

acattcagaa caaatgcttt tttttttttg agacagagtc

tcgctctgac gcccaggctg gagtgcagtg gcgcgatctc

ggctcactgc aaactttgcc tcccaggttc aagtgattct

cctacctcag ccttccgagt agagggatt acaccaccat

gcccagcaaa tttngtgtt tttagtagag acggagtttc

accatgttgg ccaggctggt ctcgaactcc tgacctcagg

tgatccatcc gccttggcct cccaaagtgc tgggattaca

ggcgggagcc accatgcctg gccagaacaa atgccttttt

aaacctttta agaacatttt taaaatgtct ttttctatgt

caaatgtaac gtttattttt ttaaacaata aaattgattt

gccaaaa

(IGF2BP1)(NM_001160423.1 version 1 of two mRNA

speies)

SEQ ID NO: 7

atttagaggc ggcgccaggg cggccgcgga gaaacgtgac

acaccagccc tctcggaggg gtttcggacc gaagggaaga

agctgcgccg tgtcgtccgt ctccctgcgc gccgcgggca

cttctcctgg gctctccccg aactctcccg cgacctctgc

gcgccctcag gccgccttcc ccgccctggg ctcgggacaa

cttctggggt ggggtgcaaa gaaagtttgc ggctcctgcc

gccggcctct ccgcctcttg gcctaggagg ctcgccgccc

gcgcccgctc gttcggcctt gcccgggacc gcgtcctgcc

ccgagaccgc caccatgaac aagattaca tcggcaacct

caacgagagc gtgacccccg cggacttgga gaaagtgttt

gcggagcaca agatctccta cagcggccag ttcttggtca

aatccggcta cgccttcgtg gactgcccgg acgagcactg

ggcgatgaag gccatcgaaa ctttctccgg gaaagtagaa

ttacaaggaa aacgcttaga gattgaacat tcggtgccca

aaaaacaaag gagccggaaa attcaaatcc gaaatattcc

accccagctc cgatgggaag tactggacag cctgctggct

cagtatggta cagtagagaa ctgtgagcaa gtgaacaccg

agagtgagac ggcagtggtg aatgtcacct attccaaccg

ggagcagacc aggcaggctg acgaggttcc cctgaagatc

ctggcccata ataactttgt agggcgtctc attggcaagg

aaggacggaa cctgaagaag gtagagcaag ataccgagac

aaaaatcacc atctcctcgt tgcaagacct taccctttac

aaccctgaga ggaccatcac tgtgaagggg gccatcgaga

attgagcag ggccgagcag gaaataatga agaaagttcg

ggaggcctat gagaatgatg tggctgccat gagcctgcag

tctcacctga tccctggcct gaacctggct gctgtaggtc

ttttcccagc ttcatccagc gcagtcccgc cgcctcccag

cagcgttact ggggctgctc cctatagctc ctttatgcag

gctcccgagc aggagatggt gcaggtgttt atccccgccc

aggcagtggg cgccatcatc ggcaagaagg ggcagcacat

caaacagctc tcccggtttg ccagcgcctc catcaagatt

gcaccacccg aaacacctga ctccaaagtt cgtatggtta

tcatcactgg accgccagag gcccaattca aggctcaggg

aagaatctat ggcaaactca aggaggagaa cttctttggt

cccaaggagg aagtgaagct ggagacccac atacgtgtgc

cagcatcagc agctggccgg gtcattggca aaggtggaaa

aacggtgaac gagttgcaga atttgacggc agctgaggtg

gtagtaccaa gagaccagac ccctgatgag aacgaccagg

tcatcgtgaa aatcatcgga catttctatg ccagtcagat

ggctcaacgg aagatccgag acatcctggc ccaggttaag

cagcagcatc agaagggaca gagtaaccag gcccaggcac

ggaggaagtg accagcccct ccctgtccct tcgagtccag

gacaacaacg ggcagaaatc gagagtgtgc tctccccggc

aggcctgaga atgagtggga atccgggaca cctgggccgg

gctgtagatc aggtttgccc acttgattga gaaagatgtt

ccagtgagga accctgatct ctcagcccca aacacccacc

caattggccc aacactgtct gcccctcggg gtgtcagaaa

ttctagcgca aggcactttt aaacgtggat tgtttaaaga

agctctccag gccccaccaa gagggtggat cacacctcag

tgggaagaaa aataaaattt ccttcaggtt ttaaaaacat

gcagagaggt gttttaatca gccttaaagg atggttcatt

tcttgacctt aatgtttttc caatcttctt ccccctactt

gggtaattga ttaaaatacc tccatttacg gcctattct

atatttacac taattttttt atctttattg ctaccagaaa

aaaatgcgaa cgaatgcatt gattgctta cagtattgac

tcaagggaaa agaactgtca gtatctgtag attaattcca

atcactccct aaccaatagg tacaatacgg aatgaagaag

aggggaaaat ggggagaaag atggttaaaa tacataataa

tccacgttta aaaggagcgc acttgtggct gatctatgcc

agatcaccat cttcaaattg gcacaactga aatttcccca

ctctgttggg gcttccccac cacattcatg tccctctccc

gtgtaggttt cacattatgt ccaggtgcac ataggtggta

ttgaatgctc agcagggtag gggctgacca ctgtccctga

ttcccatcgt tctcaggcgg attttatatt tttttaaagt

ctattttaat gattggatat gagcactggg aaggggacgc

taactcccct tgataaagtc tcggttccat ggaggacttg

agtggcccca aaggctgcca cggtgccctc accccagccc

atgtgctccc ataagggctg gttcctagag gcaggggttg

tggggcactc ccagccacgg cactgttacc ttggtggtgg

gacttggaac ccaaccctga gctcccgata aagctaaagt

ccatcatctg gcaaattcag taaattggag agtacttgct

tctgtttgta tctgagagga atttttaact gacggcttct

gtctccatga atcattatca gcatgatgaa aggtgtgtct

aaaaaacaat tcagaatacc agcagcattg tacagcaagg

ggtaaataag cttaatttat taatttacca ggcttaatta

agatcccatg gagtgtttag cccttgtggg agacagaagc

catcagttaa atgaggttag gcctctcctc ctaatatact

gattgacaat gcatattagc caggtaatgc actttagcta

ccctggacaa tgctatcaag tgtgctggga agggaggaag

gcctctctac atatggaaaa gcccatgcgt ggagttcccc

tcctttcaac attgcaacaa cagtaacaac aagacaaccg

caacatgtgg gcgtagtcag gcaatgctgt gtgcgaagta

aactacctca aggtatgaag ttacctcagc aattattttc

ctttttgttc cccccaaccc cattaaaaaa attttttttt

gatttttgtt tttttgcagc ttgctgatat tttatataaa

aaagaaaagc aaagcaaaag agaagctgat agtcttgaat

attttatttt tttaatgaaa agaaaaaaca agaaagttat

gtttcataat ttcttacaac atgagccagt aaccctttag

gaactctcta tggagaacag gcctggtggg aaaggctttg

ggggctgccc ccttaggagg aggctagtgc taagagggaa

ggcccaggtt tgagagagcc cagaggggca gagcccagag

ccttgtttgg ccctgatctc tgacttctag agccccagct

gctggcggct gaggaatat cctacctgat aggattaaaa

ggcctagtgg agctgggggc tctcagtggt taaacaatgc

ccaacaacca accagctggc cttggtctc ctctctttcc

tcctttggtt aaagagcatc tcagccagct tttcccacca

gtggtgctgt tgagatattt taaaatattg cctccgtttt

atcgaggaga gaaataataa ctaaaaaata taccattaa

aaaaacctat atttctctgt ctaaaaatat gggagctgag

attccgttcg tggaaaaaag acaaggccac cctctcgccc

tcagagaggt ccacctggtt tgtcattgca atgcttttca

tttttttttt ttgttattgt ttcatttcag ttccgtcttg

tattatcc taatctatat ccatagatct aaggggcaaa

cagatactag ttaactgccc cacctctgt ctccctgtct

tctttagatc ggtctgattg attttaaaag tggacccaaa

ttagggaat tcttgattta gggtggctgg tggcaaggag

gggcagggga tatggggacg tgactgggac aggttcctgc

cttatcattt tctccctagg acattccctt gtagccccca

gaattgtctg gcccaaattg aatagaagca gaaaaacatt

tagggataac atcaggccag tagaattaag cctctccacc

tgtcccaacc ataaaaaggg tctcccagct ttccatctct

ggctctatat gctttatccc aaaacaaagc agataacgtt

cagacgtcgg ccatttagta atttaaagcg aatttccagc

agcaagcatg ctttgatatc tggttcagac tatcatcagg

aagaaaaaaa aatcccacag tacctgaaat gtgattgttg

cagtgttcag tttccttggg ggcctgctcc cttcacacct

tgagcccaag tccttttccg ttggctgatt cagctcccag

aagagacgag gaagtgtgtg gcaagggact ggaaaacttc

acttgcttgg attaggcaag gctccactca ttgttgatat

ttgcccagca ggaaaatcat gtaagttata ccaccagaaa

gcaaaaggag catggtttgg tggttaaggt ttagtgggat

gaaggacctg tcttggtggg cogggccctc ttgtgccccg

taggctaggt cttagggcaa ctccttgccc tcctgctcag

cacctccatt tccccatcct tggtgagata acaagctatc

gcgaaaagca cttgggagat ttggatgatt tgagaagagt

gacttaaaaa aaatgcttct gtgctctaag atatatatgt

gtgtgtgtgt gctacatata tattataag aaaggaccat

ctattagga tatattata aattattga aacacataac

caaaatggtt tgattcactg actgactttg aagctgcatc

tgccagttac accccaaatg gattaatcc cctctcgggt

ctggttgcct tttgcagttt gggttgtgga ctcagctcct

gtgaggggtc tggttaggag agagccattt ttaaggacag

ggagttttat agcccttttc tactttcctc ccctcctccc

agtccttatc aatctttttt cctttttcct gaccccctcc

ttctggaggc agttgggagc tatccttgtt tatgcctcac

tattggcaga aaagacccca tttaaaaccc agagaacact

ggagggggat gctctagttg gttctgtgtc cattttcctc

tgtgccaaag acagacagac agaggctgag agaggctgtt

cctgaatcaa agcaatagcc agctttcgac acatacctgg

ctgtctgagg aggaaggcct cctggaaact gggagctaag

ggcgaggccc ttcccttcag aggctcctgg gggattaggg

tgtggtgttt gccaagccaa ggggtaggga gccgagaaat

tggtctgtcg gctcctggtt gcactttggg gaaggagagg

aagtttgggg ctccaggtag ctccctgttg tgggactgct

ctgtcccctg cccctactgc agagatagca ctgccgagtt

cccttcaggc ctggcagacg ggcagtgagg aggggcctca

gttagctctc aagggtgcct tcccctcctc ccaacccaga

cataccctct gccaaactgg gaaccagcag tgctagtaac

tacctcacag agccccagag ggcctgcttg agccttcttg

ctccacagga gaagctggtg cctctaggca accccttcct

cccacctctc atcaggggtg ggggttctcc tttctttccc

ctgaagtgtt tatggggaga tcctagtggc tttgccattc

aaaccactcg actgtttgcc tgtttcttga aaaccagtag

aagggaaaca gcacagcctg tcacagtaat tgcaggaaga

ttgaagaaaa atcctcatca atgccagggg acataaaagc

catttccctt ccaaatactc gacaatttag atgcagaaca

tttctctgta ttcagactta gagtaacacc agctgaaaac

tgcagtttct ttcattgga tacataaggc ttctctatcg

gggtacggga cagggaggag gcctcatgtc tgaaggggga

ttaggggcg agagccccag ccctgaccct cggtcctgtg

caccgctttg gggcacagtc tgatggcgcc tttgctggcg

ccttagtatg gttgactccg gatggacaaa agaaaaaaaa

ttttttttct tgaatgaaat agcaggaagc tcctcgggag

catgtgatt gattaaccgc aggtgatgga tgctacgagt

ataaatggat taactacctc aatccttaca gtaagattgg

aactaagggc agggactcat gcataagggt atgaatccca

gccaggacaa gtgagttgag gcttgtgcca caaaaggttt

gtccttgggg aacaggcagg cctgccagga tcccccccat

atcgattggg ctgggagggc tggccatgag gtccccactt

tctgctttcc ttgcccatgt gtcacccctt tggcctccag

cttgtccctc tctcactttc tatagctttg ttggaccaga

tggtgaggaa aggaatggcc tcttcccttc tagagggggc

tggctggagt gagacctggg gcttggcctg gaacccacca

cacagcccca aagtcaggaa gcctggggaa accagagctg

agacctcttc aacagggttt ctttgagatc ctacacctcc

attgggccct ttttcagtct tcaatggggg cccagttggc

tctagaagga gaagaggtga agcaggatcc tttgccctgg

gggagtctga gggcgcggtc cttggactca ttcaggccgt

ctttgtagtt gggggagttc cactgggcga tcccagcccc

tccccaccca ccctctaatg gacctcctca tagaagcccc

atttcacttt tgttttatct acctcttagc aaaacaatag

ataaattagg tagtggcagc tccacttgct taggttaggg

ggggaaaaag atttcttttt ccaaaggaaa aaaatattac

cttgagaata ctttccaaaa aataaaatta aaaaaaaaaa

aaccaaaaaa aaaaattttt ttttaaaagg gagacatttt

ccagtgacca ctggattgtt ttaatttccc aagctttttt

ttcccccata aataagtttc actctttggc gattttcttc

acttgtttaa gataacgtgc tagctattcc aacaggtaac

agctttcaca gtctgcccct ggcctgtctc accccatccc

ccaccctatt cctgccagtg agtccttcct gtgcttact

cccttaccc ctcccagcca gctgacttca gtcacccctg

tcccccctcc cctgccaata agctccccca ggaataaagg

ctttgttttg gggatgctta aatcttgact ggcacttccc

ggctgtgggg gctggggagc cacttgtaac atttctgtgc

agattttatg ttagccactg ctatgtaaaa gcacgttcaa

aatgaatttc agcagattat gtgttaccat aatgaataaa

cgtcctctat caccatttgg agtctccctt ttctccagga

tcttgatcct ggtccccaaa accagagtga atcaaaagag

cttcctcccc tgaggcaaag tggatttgta agcagttctg

aaacatcact tactcagaag agggaacgat gtattttgat

gagtgcaaat tgggaagagc tggaggccta ctgcttggga

cagttttttt tttttttttt tttttaaata tgagtgctag

cttattctgt aattgcggca actttgaaaa ttgtatttta

ctggaaatct gccagccatc accacccgat tttgattgta

tccttcctcc catcctttaa tctgttcatt gctttggggg

aggtggggca gctggctcac acgttggagt ttgttctttg

atggatgaac gaacactcca gttttctttc ccgtgaaggt

tgtttcagcc acaaaccact tcattttgct gtttcaattt

caaaataaaa ggaaacttat attgaaagac aa

(MDM4)(NM_002393; protein is NP_002384.1)

SEQ ID NO: 8

gggaggccgg aagttgcggc ttcattactc gccatttcaa

aatgctgccg aggccctagg atctgtgact gccacccctc

cccccacccg ggctcggcgg gggagcgact catggagctg

ccgtaagttt taccaacaga ctgcagtttc ttcactacca

aaatgacatc attttccacc tctgctcagt gttcaacatc

tgacagtgct tgcaggatct ctcctggaca aatcaatcag

gtacgaccaa aactgccgct tttgaagatt ttgcatgcag

caggtgcgca aggtgaaatg ttcactgtta aagaggtcat

gcactattta ggtcagtaca taatggtgaa gcaactttat

gatcagcagg agcagcatat ggtatattgt ggtggagatc

ttttgggaga actactggga cgtcagagct tctccgtgaa

agacccaagc cctctctatg atatgctaag aaagaatctt

gtcactttag ccactgctac tacagatgct gctcagactc

tcgctctcgc acaggatcac agtatggata ttccaagtca

agaccaactg aagcaaagtg cagaggaaag ttccacttcc

agaaaaagaa ctacagaaga cgatatcccc acactgccta

cctcagagca taaatgcata cattctagag aagatgaaga

cttaattgaa aatttagccc aagatgaaac atctaggctg

gaccttggat ttgaggagtg ggatgtagct ggcctgcctt

ggtggttat aggaaacttg agaagcaact atacacctag

aagtaatggc tcaactgatt tacagacaaa tcaggatgtg

ggtactgcca ttgtttcaga tactacagat gacttgtggt

attgaatga gtcagtatca gagcagttag gtgaggaat

aaaagttgaa gctgctgata ctgaacaaac aagtgaagaa

gtagggaaag taagtgacaa aaaggtgatt gaagtgggaa

aaaatgatga cctggaggac tctaagtcct taagtgatga

taccgatgta gaggttacct ctgaggatga gtggcagtgt

actgaatgca agaaatttaa ctctccaagc aagaggtact

gttttcgttg ttgggccttg aggaaggatt ggtattcaga

ttgttcaaag ttaacccatt ctctctccac gtctgatatc

actgccatac ctgaaaagga aaatgaagga aatgatgtcc

ctgattgtcg aagaaccatt tcggctcctg tcgttagacc

taaagatgcg tatataaaga aagaaaactc caaacttttt

gatccctgca actcagtgga attcttggat ttggctcaca

gttctgaaag ccaagagacc atctcaagca tgggagaaca

gttagataac ctttctgaac agagaacaga tacagaaaac

atggaggatt gccagaatct cttgaagcca tgtagcttat

gtgagaaaag accacgagac gggaacatta ttcatggaag

gacgggccat cttgtcactt gttttcactg tgccagaaga

ctaaagaagg ctggggcttc atgccctatt tgcaagaaag

agattcagct ggttattaag gtttttatag cataatggta

gtacgaacat aaaaatgcat ttattccgtt cacttaccac

attatttgaa aatcaatcct ttatttaatt ttatttccaa

cctgtcagag aatgttctta ggcatcaaaa tccaaggtag

ctgtaagaaa aatactggag ctaacaatga agaacagaag

taatctgatt agtcaaatta ttaagtgcca tggattactt

tatgcagcag tcaggtacat agttaggtga acccaaaaga

aaaactcttg aaaacaagag atttcttcca tgcacattta

caatattgag gtataattaa catgataaag tgtttccttc

taacgagttg tagaaatctg agtaaccacc caaaaaagca

atagaatgtt tctgtcaccc caaaacactc ccttctgccc

ctcttcagac agtccttcag ctatttcatg gctctcaccc

tagttattt tttttttgca cttttttttt tccgggggta

taggggaggt gtggggcgac agggtctgtc ttgttctgtc

tcccaggctg aagtgcagtg cagtggtatg atcatggctc

actgcagcct tggtttcctg ggcataagtg gtatcccac

ttcagcctcc tgagtagctg agactataga ctagcataac

cacactggct aattttttgt ggagatgaag tctcactatg

ttgcccaggc tggtctcgaa ctcctgggct caaacaatcc

tcccgcctca gccttccaaa ttgctgggat tatagtcatg

aggcacctag tctggccctt ttgcaagact ttaatctgaa

atctaaattt ttaaaattta agtacttaca aaggatatac

tatccaacat attgcatatt atatatgtgc tttaaagttt

tttttttttt ttgagagacg gtctcacttt gtcatccaag

ctggagtgca gtggtgcaaa cacggcccac ctcctgggct

caagtgatcc tccagcctca gatccctca caggcattca

ctatcactcc cagctaatta aaataatttg tagacggtgt

ctcgttatgt tgcccaggct ggtctcgaac tcctgggttt

aagtgattcc cccgcctcag cctcccaaag tgttgggctt

acagccttga gccactatgc ttggctcaaa gatattttta

tgaaagccct gggactatag atttagctga ttaaatttat

agaaaaagtc ctgtcatata aactggcaaa gtctgttctt

aatttaatta gccaaatcag acttaacttc cgtcagaaca

tgtcttggtt ttaattcaga taaacacaca aacatacttc

tctggcacag ccttcagaag catcagtttt tgttttgttt

tgttttgat tttgagacag ggtcttgctc tgtcgcccag

gctggagtgc actggcacaa tcacagttca ctgcagcctc

gacctcccag atccaagcaa tcctcccacc taagcctccc

aagtagctgg gtctataggc gcgtgccacc accatgccca

gctgaatttt gtattttttg tacagacagc attttgccat

gttgcccagg ctggtcccaa acttctagcc tcaagcaacc

ctcctgcctc agcctctcaa agtgctagga ttgcagtcct

gagctactgc cccctaccct ctttgcgtct taggagtcat

ttagattttt tttgatcctt ttgtttagtg cctctggagc

tgcttacacc aaggcaatac gccttgatat actggatggt

tgagaggcag cctctttttt tttttttttt tttattttt

tttggaggat agggagtatg gctgttgtga aaagggaggt

aaagagaaat ggtagatctg aagaggcctc atcagagcac

atattttagg acaacacata tggaaattgg acatctttaa

gttggtttcc atagagctat gcatgtatcc ttacccccat

gggaaaatgt tggtgtgttc tcaagggtat gcatgtgtca

ttttgaagac caaggcccta gaattgtcaa acttaaggat

cataaaaatc atgagggttg cttgttaaaa atgtccaaac

gtgcagagac tgatattga gatctggacc aggaatttgc

atttgaacaa gtgttcctgg aatctctatg caagttttat

acagaacata cattggaat ccttgcccta gacaggggtg

tccaatcat tggcttccct ggtccacaat ggaagaagaa

ttgtcttgga ccacacataa aatacactaa cactaacaat

agctgatgag ctaaaaaaaa aaaaaaaaaa aatcgtggac

cgggcgtagt ggctcacgcc tgtaatccca acactttggg

agatcaccta ggtcgggagt ttgagaccag cctgaccgac

atggagaaac cccattttta ctaaaaatac aaaaaattag

ctgggcatgg tggtgcatgc ctgtagtccc agctactcag

gaggctgagg caggagaatc gcttgaacct gagaggggga

gattgcggtg agctgagatt gcgccattgc accccagcct

gggcaacaat agcgaaactg tctcagaaaa aagaaaaaaa

aaatcgcaaa aagaaaaatc tcataatgtc gttgttggtt

tttttttttt tttttgagac agtctcactc tgttgcccag

gctggagtgc aatggcatga tctctgctca ccgcaacctc

tgcctcccgg gttcaggtga ttctcctgcc tcagcctccc

agatagctgg gactacaggc acataccacc atgcctggct

aatttttgta tttttagtag agatgggggt ttcactgtgt

tggccaggct ggtctcgaac tcctgacctc atgatccaca

cacctcggcc tcccaaagtc ctgcgattac aggcgtgagc

taccgcaccc agccaagttg taatttttaa taaaacttaa

gaagtaaaca ttttacttat gtttataggt atttgatcct

aaatttgaca catcattgcc catgaaagaa tcctcttagg

ctgctcagct tcactcttcc tgcttgccca ccggggtttt

tcactgcttc tgttagcact aagtacttag acgatcctaa

gatatgtgct tgagccgaat ttcatcttta cttgtaggaa

actttaaact atttcttttc ttttcttttt tttttttttt

tacttgagat ggagttttgc tcttgtcgcc caggctggag

tgcagtggag tgatctcggc tcactgcaac ctctgcctcc

cgggttcaaa tgattctcct gcctcagcct cccaagtagc

tgggattaca ggtgtgcacc accatgtctg gctaattttg

tatttttagt agagatggtt tcaccatgtt ggtcaggctg

gtctcgaact cctgacctca ggtcatccac ccacctcagc

ctcgcaaagt gctgagatta caggcatgag ccacagcgcc

cagcttaaac tattttcttg gtctgttttt gattttcttt

taccttgcc actgcggtac agattattt tactcactgc

cactaaacta aagcaaggca tagatatat gtgaagtgtt

cagagtttac tgctataagg aaacttccaa atactgacat

ttacctata gctgtagtta ttgggaccat gtgctctggt

tttctggaga ctgccaaatt gctcccattt ttctgcatcc

cacctggttt ctttctgcat gtcccctttc actttcaaac

ctatcattt ggatgttaaa ttatatggtc acctagttat

aggtaagcct tgttcgagtt gatatcttga ttgtgaggaa

ggatctgtgt cattggagct tgtttctgct gcaacgtgct

gtagactatg aataatgaaa tcacaccaca ttaccatcag

atttcttgtt ttagttgtca aattaatatt tatgattgtt

atcttgggcg aaaagttcag agcagagatg acaaatcatt

agaacaacga tgaatttcag tattacggct aaaaagttct

tctgtctgaa tattaactca ctctccttcc agtgtacttc

acagtaattg gtatgctttt ttatttaatg cttaaatcaa

actttataaa aatcttagac cagatcttta atatggtatg

ccatttcccc agtctaccaa tggaatagta tgggtttcta

atcctaggct tgtacaatgg attggagttg agccatgcca

gcctccacac tgccactaac ttctgtaatg taagattgag

tcactgccaa gcatttgaaa tatgcagttg tgttttaatt

ataatttatg tatagttaga tgtatgtagt gcattgtgtg

gtattatttg gtttgtaaga atttattttt aagggtcaag

gtcatttgta acattttgtg tgtgtcaatt caatgcaatg

ttggctgcct tttgaagtct ttgatatatt ggtgaatatt

cttctgatct ataatacaaa gctatgtaat gttacctctt

gactcgcttt tgaaaggaag acaattgtta actagatatt

tgagtttttt cccctcagaa ttatgtgaat ttctgatata

tggctttaga tactgtgaat ctgttttcca tttagtcagt

tatctgctta aattgttcag aactatatcc taacgagcaa

ttagttctga tggttctccc agtcatgagt gtgcatgtgt

gcaagcatgt tttgatcctg atgctacctt tgctaaaaat

ggccatagat taggaactag ctatgttttt agaatcaaag

atgaaccggt aagctgtctc atgtaccaaa cgtgaaattt

acagtgttta caaatgtctg gaattttgca ctgccatagg

gaatgttaag gttacttggc tggaatttat cagacttgtg

agtaaacaag ttgaagttta gcagatgagg gggaatattg

aggcccctaa ggctaaacaa aataatcagt atctgagata

gtggctaatg tggctcccca ggcctaattt gggaacagtt

tttcctgatt gctttgagaa gtactttctt

ttgacagaaa ttttcattct gcttgccatt gctatattct

ccattatag gagccattgg atttattcc ttttgtggga

aatgtcccat tagcattttc agatatttg atgtgcacta

atgccattat tggtaatgcc gttattggtg aatacagcat

agttaaataa actgttacag taaatctaca cttggatttg

ctgcacctct accaatagcc ttttgaatga ctgaaagtgt

taacagagaa agaggcatgt ctgcagaaag agatagctaa

tattttttgg tactttatct gaaatccaag atgctgcttc

ccctgcaggt tgttttcctt cttacgatcc tcattgaatc

ccctctggga gcacaggaca gttagtagaa ctctccattt

cttttttttt ttttttagac ggagtctctc tctgtcgccc

cggctggagt gcagtggcgc gatctcggct cactgcaacc

tccgcctccc gggttcaccc cattctcctg cctcagcctc

cctagtagct gggactatag gcgcccgcca ccacgcctgg

ctaatttttg tatttttatt ggagacgggg tttcaccgtc

ttagccagga tggtatgat ctcctgacct cgtgatctgc

ccacctcagc ctcccaaagt actgggatta caggcgtgag

ccaccgcgcc cggccggaac tctccatttc ttaaggtaaa

gagggtcaag gatacctaaa aagggtcaaa taatgctaga

agagcaattc ctctttcaga gcagttgctg taatttggca

aatgctttat cgaagattga tattaggcta ggggcggtgg

cttacgcctg taatcccagc actttgggag gccgaggtgg

gtggattgcc tgagctcagg agttcgagac cagtctgacc

agtatggtga aaccctgtct ctactaaaaa tacaaaaatt

agccggtcgt ggtggcgtgc acctgtagtc ccagctactt

ggcaggttga gacaggagaa tcgcttgaac ctgggaggtg

gaggttgcag tgagccgaga ctgcaccact gcgctcccac

ctgggtgaca gagactctgt ctcaaaaaaa aggacattta

tcattataac atcttattag agcccctaat ttcttatctg

aaggcactgt tttttttttt aaacagttaa gtactgatgt

caacagacaa atatttctga tcagatagtc ccctgtcaac

agtagcaaat gtggtttcat aaagtgggaa gaaaacagca

ttttaaagta actttttggg agactgattt gagtaataat

aaaactctgg tctcccttaa gaaaaaaaaa cccttccacc

tttactgtgt catttatatc cccttagttc caaagttaat

tatatattt ctggatang atttatacc aaagaccat

atcagccat gtaactacag tatattaga taagattcct

ctttccagtc agtcctggga aatgtttctg ttgcagagtt

aggcggtaga tgggaagctg tgatggcaga

gctactatct aataaagtaa caactcgtag ttgaggcttc

ctttctgtgt gtgatggggg atagggagtt agctcccctg

ttgtctcagc actaagaaat tgaggtcagg ccaggcgcgg

tggttcactc ctgttattcc agcactgggg

tggccaaagt gggcagattg cttgcgctct ggagctcgag

accagcctgg gcaacatggt gaaaccctgt

ctctaccaaa aatacaaaaa aaaagctggg catggtgggt

gcatgcttgt cccagctact gaggaggctg

aggtgggagg atcgcttgag cctgggaggt ggaggttgca

gtgagctgag atggcaccac tgcaatccaa

ggtgggtgac agagacgctg tctcaaagaa attgaggtca

ggcttccttc ttacagaatt atttttttct ctgtagtttg

cctcattftt tcactttctt ttcaatgaga atcgaagtgt

ttcttttggg tttttttttc ccccttttaa aatcaacagg

aaatgtttca aaggagggat gaaatgcttc ttggatcct

cagcacttgg caaggtagac ctcatagcaa ccttgaatat

gactttcttt agtctctagc tatgcactat taagtgcctc

ttgggtagag gtagagttaa gtattgagtg ccagtcttga

cgtccgtatg cctcagtttt tctcatatat aaaaagcagt

atacatacct acccttttct acctcatcat ttgttgtagg

gattaaatcc gggagagcaa ttctgaagcc tataaatttc

cttgaagaga tctaagaacc tattatgctc ttggtgtacc

aagctctggg gtatatattc agaatacctc atgttctgga

agctgagcac tagctcccct ttattgcctg cctggcagag

cctgtttgat tactgcaggc ccttttaccc atgcttctag

tttaggtatt attattga tatgaggctc ttgaccagaa

aagagttctt tctctaggtg ttctgagaga agtttgtaaa

tttggatagt acattctatc ctgataaaac caccttgctg

tggtatgat gtacaaaaaa aaattttttt tttgagacag

agtatactc tgtcacccag gctggaatgc agtggcgcaa

tcttggttca ctgcaacccc cgcctcctgg gttcaagcga

tcctcctgcc tcaacctctc aagtagctgg

gactacaggc gtgcaccacc acacctggct aattttgta

ttttagtaga gacagggttt caccatgttg

gccaggctgg tcttgaactc ctgacctcag gcgatctgcc

cgccttggcc tcccaaagta ctgggattac

aggcgtgagc aactgctcct ggcccaaaac atctctact

acatacactt gagtaggtgg cataaaatgc

actgtcaata tatagaaaac atgaaatttt ccaaatattt

ccgatcagag aatcacaaga gcagcaaatg tggtttcat

aagtgggaag aaagcagcaa tttaaaataa ctttttggga

gactgaattg agtaataata aaacttcagt ctttcgctaa

taataataat aataataata ataacaacaa cttattgaat

gtggccagct cactagatga ggaaagagga aggcattttc

tgcattcttg cctagttttc cttataagca ccactaagtt

aatagctctg tctttttggt gtttgcacta tgtaatgctt

ttaatacttt ttaattgtgc ttttttatgt attaaatgtt

tttccttttg cca

(CA VI)(NM_001215)

SEQ ID NO: 9

MRALVLLLSLELLGGQAQHVSDWTYSEGALDEAHWPQHYPACGGQRQSP

INLQRTKVRYNPSLKGLNMTGYETQAGEFPMVNNGHTVQISLPSTMRMT

VADGTVYIAQQMHFHWGGASSEISGSEHTVDGIRHVIEIHIVHYNSKYK

SYDIAQDAPDGLAVLAAFVEVKNYPENTYYSNFISHLANIKYPGQRTTL

TGLDVQDMLPRNLQHYYTYHGSLTTPPCTENVHWFVLADFVKLSRTQVW

KLENSLLDHRNKTIHNDYRRTQPLNHRVVESNFPNQEYTLGSEFQFYLH

KIEEILDYLRRALN

All references, publications, patent applications, issued patents, accession records and databases cited herein, including in any appendices, are incorporated by reference in their entirety for all purposes.

Claims

1. A method for diagnosing breast cancer status in a subject, the method comprising:

a) analyzing a saliva sample from the subject with an assay that specifically detects at least two biomarkers in the saliva sample, wherein at least one biomarker is selected from the group consisting of the biomarkers S100A8 (S100 calcium binding protein A8) (SEQ ID NO: 1), CSTA (cystatin A) (SEQ ID NO:2), GRM1 (glutamate receptor, metabotropic 1) (SEQ ID NO: 3), TPT1 (tumor protein, translationally-controlled 1)(SEQ ID NO:4), GRIK1 (glutamate receptor, ionotropic, kainate 1) (SEQ ID NO: 5), H6PD (hexose-6-phosphate dehydrogenase) (SEQ ID NO: 6), IGF2BP1 (insulin-like growth factor 2 mRNA binding protein 1) (SEQ ID NO: 7), MDM4 (3T3 cell double minute 4) (SEQ ID NO: 8), and CA6 (carbonic anhydrase VI) (SEQ ID NO: 9); and

b) determining whether or not the at least two biomarkers are differentially expressed in the sample relative to a control; thereby providing breast cancer status.

2. The method of claim 1, wherein one of the at least two biomarkers is cystatin A (CSTA).

3. The method of claim 1, wherein one of the at least two biomarkers is CSTA and the other biomarker of the at least two biomarkers is transformed 3T3 cell double minute 4 (MDM4).

4. The method of claim 1, wherein at least three biomarkers are measured.

5. The method of claim 1, wherein one of the at least two biomarkers is anhydrase VI (CA6) polypeptide.

6. The method of claim 1 wherein the assay detects a nucleic acid encoding at least one biomarker, and wherein the nucleic acid is detected by mass spectroscopy, PCR, microarray hybridization, thermal sequencing, capillary array sequencing, or solid phase sequencing.

7. The method of claim 1, wherein the assay detects a polypeptide of at least one biomarker, and wherein the polypeptide is detected by ELISA, Western blot, flow cytometry, immunofluorescence, immunohistochemistry, or mass spectroscopy.

8. A method of assessing the efficacy of a therapy on a subject comprising:

(a) analyzing a first saliva sample from the subject with an assay that specifically detects at least two biomarkers selected from the group consisting of S100A8 (SEQ ID NO: 1), CSTA (cystatin A) (SEQ ID NO:2), GRM1 (glutamate receptor, metabotropic 1) (SEQ ID NO: 3), TPT1 (tumor protein, translationally-controlled 1) (SEQ ID NO:4), GRIK1 (glutamate receptor, ionotropic, kainate 1) (SEQ ID NO: 5), H6PD (hexose-6-phosphate dehydrogenase) (SEQ ID NO: 6), IGF2BP1 (insulin-like growth factor 2 mRNA binding protein 1) (SEQ ID NO: 7), MDM4 (3T3 cell double minute 4) (SEQ ID NO: 8), and CA6 (carbonic anhydrase VI) (SEQ ID NO: 9), thereby providing a first expression profile;

(b) effecting a therapy on the subject;

(c) analyzing a second saliva from the subject with an assay that specifically detects at least two biomarkers selected from the group consisting of S100A8, CSTA, GRM1, TPT1, GRIM, H6PD, IGF2BP1, MDM4, and CA6; thereby providing a second expression profile;

(e) comparing the first and second expression profile, thereby assessing the efficacy of a therapy.

9. A kit comprising a solid support, wherein the solid support comprises a capture binding probe selective for at least two biomarkers selected from the group consisting of S100A8, CSTA, GRM1, TPT1, H6PD, IGF2BP1, MDM4.

10. A kit comprising a first and a second solid support, wherein the first solid support comprises a capture binding probe selective for at least two biomarkers selected from the group consisting of S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4, and wherein the second solid support comprises a capture binding ligand for CA6.

11. The kit of claim 10, wherein the capture binding ligand is an antibody.

12. A kit comprising one or more primers for the selective amplification of at least two biomarkers selected from the group consisting of S100A8, CSTA, GRM1, TPT1, GRIK1, H6PD, IGF2BP1, MDM4, wherein each of the primers optionally comprises a detectable label.

13. A method for diagnosing breast cancer status in a subject, the method comprising:

a) analyzing a saliva sample from the subject with an assay that specifically detects at least nine biomarkers in the saliva sample, wherein the at least nine biomarkers are selected from the group consisting of the biomarkers S100A8 (S100 calcium binding protein A8) (SEQ ID NO: 1), CSTA (cystatin A) (SEQ ID NO:2), GRM1 (glutamate receptor, metabotropic 1) (SEQ ID NO: 3), TPT1 (tumor protein, translationally-controlled 1) (SEQ ID NO:4), GRIK1 (glutamate receptor, ionotropic, kainate) (SEQ ID NO: 5), H6PD (hexose-6-phosphate dehydrogenase) (SEQ ID NO: 6), IGF2BP1 (insulin-like growth factor 2 mRNA binding protein 1) (SEQ ID NO: 7), MDM4 (3T3 cell double minute 4) (SEQ ID NO: 8), and CA6 (carbonic anhydrase VI) (SEQ NO: 9); and

b) determining whether or not the at least nine biomarkers are differentially expressed in the sample relative to a control; thereby providing breast cancer status