JP2020072705A - Urine markers for detection of bladder cancer - Google Patents

Abstract

To provide methods for detecting, classifying bladder cancer, and determining the stage of bladder cancer, using oligonucleotide, protein, and/or antibody markers in the urine.SOLUTION: Provided is a method for detecting bladder cancer, comprising detecting the accumulation of UBTM family members in the urine.SELECTED DRAWING: None

Description

Priority claim This application is New Zealand provisional patent application No. 534,289, filed on July 23, 2004, name "marker for detecting bladder cancer", applicant: Pacific Edge Biotechnology Ltd., New Zealand provisional patent application No. 539,219, filed April 4, 2005, name "Marker for detecting bladder cancer", applicant: Pacific Edge Biotechnology Ltd., and US provisional patent application No. 60 / 692,619, 2005 Claimed priority to application filed June 20, entitled "Urine Markers for Detecting Bladder Cancer," Inventor: Parry John Guilford, Natalie Jane Kerr and Robert Pollock. Each of the above applications is fully incorporated herein by reference.

TECHNICAL FIELD The present invention relates to the detection of cancer. Specifically, the present invention relates to the use of markers to detect bladder cancer. More specifically, the present invention relates to the use of urine markers to detect bladder cancer. Even more specifically, the invention relates to the use of urinary oligonucleotide, protein, and / or antibody markers for the detection, staging, and staging of bladder cancer.

Background of the Invention Survival of cancer patients is greatly increased by early treatment of the cancer. In the case of bladder cancer, patients diagnosed with early stage disease have a 5-year survival rate of> 90% compared to approximately 15-30% for patients diagnosed with an exacerbated disease. Therefore, advances that lead to early diagnosis of bladder cancer can lead to improved patient prognosis. An established method for detecting bladder cancer using urine samples is cytology. However, cytology is known to be only about 75% sensitive for detecting invasive bladder cancer and only about 25% sensitive for detecting superficial bladder cancer (Lotan and Roehrborn). , Urology 61,109-118 (2003)).

  Bladder cancer is divided into two major classes, invasive and superficial. The invasive type invades the underlying tissue layer, while the superficial type tends to extend into the bladder cavity, primarily as a polypoid growth.

  The identification of specific markers for cancer in urine can provide a useful tool for early diagnosis of cancer, which results in early treatment and improved prognosis. Specific cancer markers also provide a means to monitor disease progression, allowing the effectiveness of surgical, radiotherapeutic, and chemotherapeutic treatments to be monitored. However, for many major cancers, the available markers are of poor sensitivity and specificity.

  Currently, the most reliable method to detect bladder cancer is cystoscopy with histology of biopsy lesions. However, this technique is time consuming, invasive and its sensitivity is only around 90%, which means that about 10 percent of cancers are undetectable using these methods. Among the non-invasive methods, urine cytology, which detects detached malignant cells microscopically, is the presently preferred method. Cytology has a specificity of approximately 95%, but has low sensitivity (9-25%) for early lesions, is extremely dependent on sample quality, and is highly variable between observers.

  In recent years, attempts have been made to detect genetic markers in biopsies from the bladder. The most commonly used method is microarray analysis, in which an array containing oligonucleotides complementary to some of the putative genetic markers is added to an mRNA or cDNA sample obtained from a patient sample. To touch. Using these methods, several recent reports have identified many putative markers for bladder cancer. However, array technology is relatively non-quantitative and highly variable.

  Detection of blood or urine markers indicating the presence of bladder cancer is one potential method to improve the detection of this disease. Although little progress has been made in developing blood markers for bladder cancer, several urinary protein markers are available. Examination of these markers gives better sensitivity than cytology, but elevated levels of these markers are commonly observed in patients with non-malignant diseases including inflammation, urolithiasis and benign prostatic hypertrophy, thus Tends not to be the best. For example, NMP22, which detects specific nuclear matrix proteins, has a sensitivity of 47-87% and a specificity of 58-91%. The high variability of NMP22 means that it is not ideal for the rapid and easy detection of bladder cancer.

  Other urinalysis tests include RT-PCR amplification of gene transcripts, such as the telomerase enzyme hTERT from the cell pellet of urine samples. The RT-PCR test may be sensitive, but the specificity of existing RT-PCR markers remains unclear.

  There is a need for additional approaches for early detection and diagnosis of cancer. The present invention provides additional methods, compositions, kits, and devices to aid in the early detection and diagnosis of cancer based on cancer markers, especially bladder cancer markers.

DISCLOSURE OF THE INVENTION Using a combination of microarray analysis and quantitative polymerase chain reaction (qPCR), we were able to identify specific genetic markers selective for bladder cancer. In one embodiment, we have discovered markers that can be used to distinguish the stage of bladder tumors, and in other embodiments we have identified markers that can differentiate tumor types. .. In another embodiment, we have unexpectedly found that a combination of two or more markers allows for very reliable and sensitive detection of bladder cancer. In an even further embodiment, we have identified markers that are highly expressed in bladder cancer cells and not in blood cells. Thus, in many embodiments, tests for bladder cancer are unexpectedly better than tests according to the prior art.

  In certain embodiments, microarray analysis is used to identify genes that are highly expressed in bladder tumor tissue as compared to non-malignant bladder tissue. These genes, and the proteins encoded by those genes, are designated herein as bladder tumor markers (BTM). It should be understood that the term BTM does not require that the marker be specific for bladder tumors only. Rather, BTM expression may be increased in other types of tumors including malignant tumors. It should also be understood that BTM contains markers that are not highly expressed in blood cells. By taking a sample from urine, there is generally no expression of other types of cells present in prior art biopsy samples. The term BTM also includes combinations of individual markers that help detect bladder cancer.

  In another embodiment, methods are provided for identifying the presence of a marker in a sample, including immunohistochemistry and quantitative polymerase chain reaction (qPCR). The qPCR method has few common artifacts in the microarray method. Such artifacts include differences in the number of ligand oligonucleotides placed on the array dots, uneven and unpredictable binding of dye to hybridized oligonucleotides on the array spots, nonspecificity from array spots. Includes non-uniform cleaning of chemicals and other problems.

  Some of the genes disclosed herein encode proteins that are secreted by cells, exfoliated from cells, or released from cells upon cell death. These mRNA transcripts and their proteins have additional uses as markers for the diagnosis of bladder cancer or for monitoring the exacerbation of existing disease. These markers can be used alone or in combination with each other. In addition, other genes, RNA transcripts, and encoded proteins can remain intracellular or bind to cells and used alone or in combination with each other as urine markers.

  Strategies for treating superficial and invasive bladder cancer may differ. Invasive bladder cancer requires surgical resection more quickly and has fewer possible alternative treatments than superficial bladder cancer. In contrast, superficial bladder cancer can be effectively treated with either intravesical chemotherapy or intravesical BCG immunotherapy.

  At present, however, there is no easy and reliable way to distinguish between superficial and invasive bladder cancer classes without cystoscopy. If non-invasive methods such as urinalysis could be used to identify these classes, clinicians would not have to rely on cystoscopy, which is expensive, inconvenient, and often unacceptable to the patient, and appropriate It will be possible to choose a treatment strategy.

  We unexpectedly find that some urinary markers, especially those not found in high concentrations in blood, when used in combination or alone are extremely reliable, sensitive and specific for diagnosis of bladder cancer. Found that we can provide.

  The present invention will be described with reference to specific embodiments thereof and the following drawings.

FIG. 1 is a table showing the number and origin of samples used in qPCR analysis. FIG. 2 shows a table of markers and their oligonucleotide probes for qPCR analysis of the bladder cancer of the present invention. FIG. 3 shows a table of BTMs identified using the microarray method on invasive bladder cancer samples. FIG. 3 shows a table of BTMs identified using the microarray method on invasive bladder cancer samples. FIG. 3 shows a table of BTMs identified using the microarray method on invasive bladder cancer samples. FIG. 3 shows a table of BTMs identified using the microarray method on invasive bladder cancer samples. FIG. 3 shows a table of BTMs identified using the microarray method on invasive bladder cancer samples. FIG. 4 shows a table of BTMs identified using the microarray method on a sample of superficial bladder cancer. FIG. 4 shows a table of BTMs identified using the microarray method on a sample of superficial bladder cancer. FIG. 4 shows a table of BTMs identified using the microarray method on a sample of superficial bladder cancer. FIG. 5 shows a table of results obtained in studies conducted using quantitative PCR analysis for specific BTMs. FIG. 5 shows a table of results obtained in studies conducted using quantitative PCR analysis for specific BTMs. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6a: SPAG5, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6b: SPAG5, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6c: TOP2a, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6d: TOP2a, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6e: CDC2, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6f: CDC2, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6g: ENG, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6h: ENG, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6i: IGFBP5, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6j: NOV, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6k: NRP1, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 61: NRP1, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6m: SEMA3F, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6n: EGFL6, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6o: EGFL6, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6p: MGP, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6q: SEM2, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6r: SEM2, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6s: CHGA, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6t: CHGA, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6u: BIRC5, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6v: BIRC5, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6w: UBE2C, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6x: UBE2C, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6y: HoxA13, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6aa: MDK, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6ab: MDK, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6ac: Thy1, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6ad: Thyl, superficial. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6ae: SMC4L1, invasive. 6a-6af are histograms showing relative frequency versus log ₂ fold change data obtained from quantitative PCR studies on various tumor markers of invasive and superficial bladder tumors. Figure 6af: SMC4L1, superficial. FIG. 7 shows a table of results obtained in a study performed using quantitative PCR analysis for specific BTMs with urine samples. FIG. 8 shows a boxplot showing the relative accumulation of bladder cancer markers in urine of patients and healthy controls. Data are shown for each pair of 12 BTMs; the upper box of each pair represents urine samples from healthy control patients and the lower box represents urine samples from patients with bladder cancer. The boxes define the 25th, 50th, and 75th percentiles. All data are log ₂ fold change relative to the median of healthy controls. The dots represent outliers. FIG. 9 shows a bar graph of quantitative PCR analysis of total RNA extracted from whole blood compared to RNA from bladder cancer tissue. FIG. 10 shows the median overaccumulation of marker transcripts in urine of bladder cancer patients. Shown separately are the log ₂ differences between patients and healthy controls and between patients and non-malignant controls. FIG. 11 displays boxplots showing the excessive appearance of marker transcripts in the urine of cancer patients compared to healthy and non-malignant controls. The boxes define the 25th, 50th, and 75th percentiles. All data are relative to the median of healthy controls. Boxes filled with dots correspond to samples from healthy subjects. Boxes filled with shadows correspond to samples from patients with non-malignant urological disease, and boxes filled with notches correspond to samples from patients with bladder cancer: a. H0XA13; b. IGFBP5; c. MDK; d. MGP; e. NRPl; f. SEMA3F; g. SMC4L1; h. TOP2A; i. UBE2C. The dots represent outliers. 12a-12b represent histograms showing the number of markers with expression above the 95th percentile of the median normal expression for invasive and superficial tumor types, respectively. Results are shown separately for each tumor sample based on qPCR data for 12 markers. 12a-12b represent histograms showing the number of markers with expression above the 95th percentile of the median normal expression for invasive and superficial tumor types, respectively. Results are shown separately for each tumor sample based on qPCR data for 12 markers. 13a-13b show a table showing the effect of multiple markers on the ability to correctly distinguish tumor from non-malignant tissue. The table consisted of a normal distribution derived from qPCR data. FIG. 13a depicts the effect of multiple markers on the ability to accurately distinguish invasive bladder cancer tissue from non-malignant tissue with 95% specificity. 13a-13b show a table showing the effect of multiple markers on the ability to correctly distinguish tumor from non-malignant tissue. The table consisted of a normal distribution derived from qPCR data. FIG. 13b depicts the effect of multiple markers on the ability to accurately distinguish superficial bladder cancer tissue from non-malignant tissue with 95% specificity. 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14a: Invasive transitional cell carcinoma (TCC). 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14a: Invasive transitional cell carcinoma (TCC). 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14a: Invasive transitional cell carcinoma (TCC). 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14a: Invasive transitional cell carcinoma (TCC). 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14a: Invasive transitional cell carcinoma (TCC). 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14a: Invasive transitional cell carcinoma (TCC). 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14a: Invasive transitional cell carcinoma (TCC). 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14a: Invasive transitional cell carcinoma (TCC). 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14b: Superficial TCC. 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14b: Superficial TCC. 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14b: Superficial TCC. 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14b: Superficial TCC. 14a-14b show a table showing the sensitivity of marker combinations at 95% specificity for invasive transitional cell carcinoma (TCC) calculated from the normal distribution of qPCR data. Figure 14b: Superficial TCC. Figure 15 shows a table showing the effect of multiple markers on the ability to accurately distinguish urine samples obtained from bladder cancer (TCC) patients and urine samples obtained from patients with non-malignant urological disorders. A table was created from a normal distribution of data obtained from urine qPCR analysis. FIG. 16 is a table showing the sensitivity at 95% specificity of marker combinations in urine for TCC detection, calculated from the normal distribution of urine qPCR data. FIG. 16 is a table showing the sensitivity at 95% specificity of marker combinations in urine for TCC detection, calculated from the normal distribution of urine qPCR data. FIG. 16 is a table showing the sensitivity at 95% specificity of marker combinations in urine for TCC detection, calculated from the normal distribution of urine qPCR data. FIG. 17 shows a box and whisker plot showing the ratio of BTM in RNA extracted from urine of patients with superficial and invasive bladder cancer. The boxes define the 25th, 50th and 75th percentiles. The gray shaded boxes represent samples from patients with superficial bladder cancer, and the shaded boxes represent samples from patients with invasive bladder cancer: a. A combination of TOP2A / HOXA13; b. A combination of TOP2A / IGFBP5; and c. Combination of TOP2A / SEMA3F. The dots represent outliers. FIG. 18 shows boxplots showing the proportion of BTM in the urine of patients with various stages of bladder cancer. The boxes define the 25th, 50th, and 75th percentiles. Boxes filled with dots correspond to samples from patients with superficial bladder cancer, gray shaded boxes correspond to samples from patients with stage 1 invasive tumors, and lined boxes correspond to stages 2-3. Corresponding to samples from tumor patients of: a. A combination of TOP2A / HOXA13; b. A combination of TOP2A / IGFBP5; and c. The combination of TOP2A / SEMA3F. The dots represent outliers. FIG. 19 shows a boxplot showing the ratio of BTM in RNA extracted from superficial and invasive bladder tumors. The boxes define the 25th, 50th, and 75th percentiles. The shaded boxes represent samples from patients with superficial bladder tumors, and the shaded boxes represent samples from patients with invasive bladder tumors: a. A combination of TOP2A / HOXA13; b. A combination of TOP2A / IGFBP5; and c. The combination of TOP2A / SEMA3F. The dots represent outliers. FIG. 20 is a box and whisker plot showing one marker combination for application in bladder cancer detection. The figure shows the excess appearance of a group of 4 markers in the urine of cancer patients compared to healthy and non-malignant controls. The boxes define the 25th, 50th, and 75th percentiles. All data are relative to the median of healthy controls. Boxes filled with dots correspond to samples from healthy subjects. Boxes filled with grey-shade correspond to samples from patients with non-malignant urological disease and boxes filled with nicks correspond to samples from patients with bladder cancer: a. H0XA13; b. MGP; c. SEMA3F; and d. TOP2A. The dots represent outliers. FIG. 21 presents a box plot showing marker combinations for determining the histological type of bladder cancer. The figure shows the ratio of BTM in RNA extracted from urine of patients with superficial and invasive bladder cancer. The boxes define the 25th, 50th, and 75th percentiles. The shaded boxes represent samples from patients with superficial bladder cancer, and the shaded boxes represent samples from patients with invasive bladder cancer: a. A combination of TOP2A / SEMA3F; b. The combination of TOP2A / HOXA13. The dots represent outliers.

DETAILED DESCRIPTION OF THE INVENTION Definitions Before describing the embodiments of the present invention in detail, it will be helpful to provide some definitions of the terms used herein.

  The term "marker" means a molecule that is quantitatively or qualitatively associated with the presence of a biological phenomenon. Examples of “markers” include genes, gene fragments, RNAs, RNA fragments, proteins, protein fragments, related metabolites, whether directly or indirectly related to the mechanism behind the phenomenon. By-products or other identifying molecules are included.

  The term "sensitivity" refers to the percentage of individuals with a disease who test positive. Thus, increased sensitivity means less false negative test results.

  The term "specificity" refers to the proportion of individuals without a disease who test negative. Thus, increased specificity means fewer false positive test results.

  The term "BTM" or "bladder tumor marker" or "BTM family member" means a marker associated with bladder cancer. The term BTM further includes a combination of individual markers, which combination improves the sensitivity and specificity of detecting bladder cancer. In some sections of this application, the term BTM may conveniently include UBTM (as defined herein). Non-limiting examples of BTMs are listed in Figures 3 and 4 herein.

  BTM is used to extract RNA from a tissue sample of a patient suspected of having bladder cancer, add the RNA to a microarray on which a large number of oligonucleotides are present, and hybridize the sample RNA to the oligonucleotides on the array. Then, it can be identified by quantifying the level of the RNA to be measured bound to each array spot. If the abundance of a marker is above a threshold that is at least about 1.2 times the abundance found in normal, non-malignant tissues using microarray technology, then the marker is considered to be BTM. Alternatively, the threshold can be about twice the normal value, about three times the normal value, four times the normal value, or more than about five times. By "normal" we mean more than the 90th percentile of the normal population. In other cases, normal means the 95th percentile (ie, about twice the standard deviation (SD) from the mean), and in other cases the 97.5th percentile (ie, SD). Abundance level of about 3 times the number of), or greater than the 99th percentile.

  In an even further case, BTM can be selected which is present in the tumor tissue but not to a substantial extent in the blood. We define that the "substantial extent" is that the amount in tumor tissue is at least about 5 cycles more than that found in blood, as measured by qPCR.

  The term "UBTM" or "urinary bladder tumor marker" or "UBTM family member" means a BTM marker associated with bladder cancer found in urine, but does not include TOP2A, MDK, or BIRC5. The term UBTM further includes a combination of two markers, and a combination of three markers, which combination improves the sensitivity and selectivity of detecting bladder cancer in a urine sample. Non-limiting examples of UBTMs are listed in Figures 14a and 14b herein.

  In other cases, UBTM can be identified in urine, using the microarray method, or by the qPCR method, using a forward primer, a reverse primer, and a probe selected based on the marker to be evaluated. .. The detection threshold of bladder cancer in urine is about 1 cycle (2 times), 2 cycles (4 times), 3 cycles (8 times), 4 cycles (from the marker level in urine of a normal subject with bladder cancer). 16 times), 5 cycles (32 times), or more.

  The term "qPCR" means quantitative polymerase chain reaction.

  The term "expression" includes the production of mRNA from a gene or a part of a gene, the production of a protein encoded by an RNA or a gene or a part of a gene, and also the appearance of detectable substances associated with expression. .. For example, the binding of binding ligands such as antibodies to genes or other oligonucleotides, proteins or protein fragments, and visualization of binding ligands are included within the scope of the term "expression". Thus, increased concentrations of spots on immunoblots such as Western blots are included in the term "expression" of the underlying biomolecule.

  The term "expression rate" means the change in the amount of transcript or protein over time.

  The term "overexpression" is used when the rate of expression of a marker in one cell or cell type is higher than another cell or cell type per defined time period.

  The term "accumulation" means an increased amount of marker in a sample compared to a normal mean value. By "increased amount" is meant that the amount of marker is greater than the percentile in the normal range of 90th, 95th, 97.5th, 99th, or higher, as measured using the microarray method, Used to mean at least about 1.2 times, 2 times, 3 times, 4 times, or 5 times higher. When measured using qPCR, "increased amount" means at least about 1 cycle (2 times) 2 cycles from the 90th, 95th, 97.5th, or 99th percentile of the normal range. (4 times), 3 cycles (8 times), 4 cycles (16 times), 5 cycles (32 times), or higher marker amount.

  Accumulation can mean an increased number of markers in a cell (on a cell-by-cell basis) or an increased number of cells with a particular marker in a sample. Accumulation can therefore mean an increased total amount of markers (on a volume-by-volume basis) in urine compared to conditions that do not have the characteristics of bladder cancer. Accumulation may also reflect an increased rate of BTM expression in a given cell type and / or an increased number of cells expressing BTM at a normal expression rate. In addition, accumulation can also reflect free mRNA present due to loss of cell membrane integrity or cell death and destruction.

BEST MODE FOR CARRYING OUT THE INVENTION A marker for the detection and evaluation of tumors including the bladder is provided. A number of genes and proteins have been found to be associated with bladder tumors. Microarray analysis of samples taken from patients with bladder tumors and from non-malignant samples of normal urothelium revealed that in many bladder tumors a specific pattern of overexpression of a gene or accumulation of a gene product in urine was observed. It has come as a surprising discovery that it is linked to disease. Most surprisingly, it is present at high levels in urine samples from patients with bladder cancer, but is present at low levels in healthy individuals and especially those with non-malignant urological disorders, including those exhibiting hematuria. The marker that does so has been isolated. Detection of markers, such as gene products (eg, oligonucleotides such as mRNA) and proteins and peptides translated from the oligonucleotides thus suggest the presence of tumors, especially bladder tumors.

  Of course, the level of a particular marker or set of markers may depend on the amount of urine produced compared to the amount of marker present. Thus, in conditions characterized by decreased urine production (eg, decreased urine output), the marker concentration will increase, but it will not reflect bladder cancer. Thus, in some embodiments, the amount of markers can be corrected by the total urine output per given time. Alternatively, the marker concentration can be corrected by the total number of cells in the urine sample, and in other embodiments can be corrected by the total protein present in the urine. On the other hand, increased urine production tends to dilute tumor markers and thus mask the presence of bladder cancer. Such conditions may be associated with increased water intake, decreased salt intake, increased use of diuretics, or inhibition of antidiuretic hormone production or activity.

  In some embodiments, renal function can be measured using known techniques. These include, for example, measurement of creatinine clearance. However, it is known that there are many suitable methods for measuring renal function. In conditions in which abnormal renal function is found, appropriate corrections can be used to adjust the accumulation of measured markers. Thereby, bladder cancer can be diagnosed more accurately.

  Cancer markers can be detected in a sample using any suitable technique, which can include, but is not limited to, oligonucleotide probes, qPCR, or antibodies raised against the cancer marker. I can't.

  Of course, the sample to be examined is not limited to samples of tissue suspected of being tumor. The marker may be bound to cells that are secreted into serum, shed from the cell membrane, or lost in urine. Thus, the sample can include any body sample, including blood, serum, peritoneal lavage, cerebrospinal fluid, urine, and fecal samples.

  Detecting one cancer marker in a sample will indicate the presence of a tumor in that subject. However, it should be appreciated that by analyzing the presence and amount of expression of multiple cancer markers, the sensitivity of diagnosis is increased while the frequency of false positive and / or false negative results is reduced. Therefore, multiple markers according to the present invention can be used to enhance early detection and diagnosis of cancer.

General Methods for Cancer Detection The following methods are methods that can be used to detect cancer, including bladder cancer, using BTM or UBTM family members. However, it is not limited to them.

Hybridization Methods Using Nucleic Acid Probes Selective for Markers These methods include the steps of attaching the nucleic acid probe to a support and, under appropriate conditions, hybridizing with RNA or cDNA from a test sample. (Sambrook, J., E Fritsch, E. and T Maniatis, Molecular Cloning:. A Laboratory Manual 3 rd ColdSpring HarborLaboratory Press: Cold Spring Harbor (2001)). These methods can be suitably applied to BTM or UBTM derived from tumor tissue or liquid samples. RNA or cDNA preparations are usually labeled with fluorescent or radioactive molecules to allow detection and quantification. In some applications, the hybridized DNA can be tagged with a branched fluorescent label structure to enhance signal strength (Nolte, FS, Branched DNA signal amplification for direct quantitation of nucleic acid sequences. in clinical specimens. Adv. Clin. Chem. 33, 201-35 (1998)). After the unhybridized label was removed by thorough washing in a dilute salt solution such as 0.1 × SSC and 0.5% SDS, the amount of hybridization was determined by fluorescence detection of gel image or densitometry. To quantify. The support can be solid, such as nylon or nitrocellulose membrane, or can consist of microspheres or beads that hybridize in liquid suspension. The beads may be magnetic so that they can be washed and purified (Haukanes, BI and Kvam, C, Application of magnetic beads in bioassays. Bio / Technology 11, 60-63 (1993)) or flow site. May be fluorescently labeled to allow for metric (e.g .: Spiro, A., Lowe, M. and Brown, D., A Bead-Based Method for Multiplexed Identification and Quantitation of DNA Sequences Using Flow Cytometry. Appl. Env Micro. 66, 4258-4265 (2000)).

  One variation of the hybridization technique is the QuantiGene Plex® analysis (Genospectra, Fremont), which combines a fluorescent bead support with branched DNA signal amplification. Yet another variation of the hybridization technique is the Quantikine® mRNA analysis (R & D Systems, Minneapolis). The method of implementation is as described in the manufacturer's instructions. Briefly, the assay uses an oligonucleotide hybridization probe linked to digoxigenin. Hybridization is detected with an anti-digoxigenin antibody linked to alkaline phosphatase in a colorimetric assay.

  Additional methods are well known in the art and need not be described further herein.

Quantitative PCR (qPCR)
Quantitative PCR (qPCR) can be performed on tumor samples, serum, plasma, and urine samples with BTM-specific primers and probes. In controlled reaction, the amount of product formed in PCR reactions (Sambrook, J., E Fritsch, E. and T Maniatis, Molecular Cloning:. A Laboratory Manual 3 rd Cold Spring Harbor Laboratory Press: Cold Spring Harbor ( 2001)) correlates with the amount of template at the start. Quantification of the PCR product can be performed by stopping the PCR reaction when it is in log phase and before the reagents are rate limiting. The PCR product is then electrophoresed in an agarose or polyacrylamide gel, stained with ethidium bromide or a comparable DNA stain and the staining intensity is measured by densitometry. Alternatively, the progress of the PCR reaction can be measured using a PCR instrument such as Applied Biosystems' Prism 7000 or Roch's LightCycler, which measures product accumulation in real time. Real-time PCR measures either the fluorescence of DNA-intercalating dyes such as Sybr Green incorporated into synthesized PCR products, or the fluorescence emitted by a reporter molecule when cleaved from a quencher molecule. The reporter molecule and the quencher molecule are incorporated into the oligonucleotide probe, which hybridizes to the target DNA molecule after the DNA strand has been extended from the primer oligonucleotide. The oligonucleotide probe is driven off and degraded by the enzymatic action of Taq polymerase in the next PCR cycle, releasing the reporter molecule from the quencher molecule.

  In some embodiments, the forward primer, reverse primer, and probe set comprises SEQ ID NO: 1, SEQ ID NO: 14, and SEQ ID NO: 27, respectively. Alternatively, the set comprises SEQ ID NO: 2, SEQ ID NO: 15, and SEQ ID NO: 28, respectively. In another embodiment, the set comprises SEQ ID NO: 3, SEQ ID NO: 16, and SEQ ID NO: 29, respectively, SEQ ID NO: 4, SEQ ID NO: 17, and SEQ ID NO: 30, respectively, SEQ ID NO: 5, SEQ ID NO: 18, and SEQ ID NO: 31, SEQ ID NO: 6, SEQ ID NO: 19, and SEQ ID NO: 32, respectively, SEQ ID NO: 7, SEQ ID NO: 20, and SEQ ID NO: 33, respectively, SEQ ID NO: 8, SEQ ID NO: 21, and SEQ ID NO: 34, respectively. SEQ ID NO: 9, SEQ ID NO: 22, and SEQ ID NO: 35, respectively, SEQ ID NO: 10, SEQ ID NO: 23, and SEQ ID NO: 36, SEQ ID NO: 11, SEQ ID NO: 24, and SEQ ID NO: 37, SEQ ID NO: 12, SEQ ID NO: 25, and SEQ ID NO: 38, respectively; and SEQ ID NO: 13, SEQ ID NO: 26, and SEQ ID NO: 39, respectively.

Enzyme linked immunoassay (ELISA)
Briefly, in sandwich ELISA analysis, polyclonal or monoclonal antibodies against BTM / UBTM were applied to a solid support (Crowther, JR The ELISA guidebook. Humana Press: New Jersey (2000); Harlow, E. and Lane, D., Using antibodies: a laboratory manual. Cold Spring Harbor Laboratory Press: Cold Spring Harbor (1999)), or bind to beads in suspension. Other methods are known in the art and need not be described further herein. Monoclonal antibodies can be derived from hybridomas or phage antibody libraries (Hust M. and Dubel S., Phage display vectors for the in vitro generation of human antibody fragments. Methods MoI Biol. 295: 71-96 (2005). )) Can be selected. Non-specific binding sites are blocked with non-target protein preparations and detergents. The capture antibody is then incubated with a urine or tissue preparation containing the BTM / UBTM antigen. After washing the mixture, the antibody / antigen complex is incubated with a second antibody that detects the targeted BTM / UBTM. The second antibody is attached, usually to a fluorescent molecule, or to another reporter molecule that can be detected enzymatically or with a third antibody (Crowther, Id.) Attached to a reporter. Alternatively, in a direct ELISA, a preparation containing BTM / UBTM can be bound to a support or bead and the targeted antigen can be detected directly with the antibody-reporter conjugate (Crowther, supra).

  Methods of producing monoclonal antibodies and polyclonal antisera are well known in the art and need not be described further herein.

Immunohistochemistry Tumor marker identification and localization can be performed on bladder tumors, lymph nodes, or distant metastases using anti-marker antibodies. Such methods can be used, for example, to detect colorectal, pancreatic, ovarian, melanoma, liver, esophagus, stomach, endometrium, and brain.

  In general, immunohistochemistry can be used to detect BTM in tissues (Harlow, E. and Lane, D., Using antibodies: a laboratory manual. Cold Spring Harbor Laboratory Press: Cold Spring Harbor (1999)). .. Briefly, paraffin-embedded or frozen OCT-embedded tissue samples were cut into 4-8 μm sections, mounted on glass slides, fixed and permeabilized, and then primary moro for BTM. Incubate with clonal or polyclonal antibody. The primary antibody can be linked to a detection molecule or reporter for direct antigen detection, or alternatively the primary antibody itself can be detected by a secondary antibody linked to the reporter or detection molecule. Following washing and activation of any reporter molecule, the presence of BTM can be visualized microscopically.

  This method is used for immunological detection of marker family members in serum or plasma from bladder cancer patients collected before and after tumor removal surgery; colorectal, pancreas, ovary, melanoma, liver, esophagus, stomach, endometrium, and It can also be used for immunological detection of marker family members in other cancer patients, including but not limited to the brain; and in urine and feces from bladder cancer patients.

  BTM and UBTM can be detected in tissues or urine using other standard immunological detection techniques such as immunoblotting or immunoprecipitation. (Harlow, E. and Lane, D., Using antibodies: a laboratory manual. Cold Spring Harbor Laboratory Press: Cold Spring Harbor (1999)). In immunoblotting, protein preparations from tissues or body fluids containing BTM / UBTM are electrophoresed in polyacrylamide gels under denaturing or non-denaturing conditions. The protein is then transferred to a membrane support such as nylon. BTM / UBTM is then reacted directly or indirectly with the moroclonal or polyclonal antibody as described for immunohistochemistry. Alternatively, in some preparations, proteins can be spotted directly on the membrane without prior electrophoretic separation. The signal can be quantified by densitometry.

  In immunoprecipitation, a soluble preparation containing BTM or UBTM is incubated with a moroclonal or polyclonal antibody against BTM / UBTM. The reaction is then incubated with inert beads made of agarose or polyacrylamide with protein A or protein G covalently attached. The protein A or G beads specifically interact with the antibody to form an immobilized complex of antibody-BTM / UBTM antigen bound to the bead. Following washing, bound BTM / UBTM can be detected and quantified by immunoblotting or ELISA.

Computer-aided analysis of array or qPCR data Primary data are collected and fold change analysis is performed by comparing the level of bladder tumor gene expression to expression of the same gene in non-tumor tissues. Provide a threshold to conclude that expression is increased (eg, 1.5-fold increase, 2-fold increase, and in other embodiments 3-fold increase, 4-fold increase or 5-fold increase). It goes without saying that other thresholds can be selected for concluding that increased expression has occurred without departing from the scope of the invention. Further analysis of tumor gene expression involves matching genes that show increased expression with known bladder tumor expression profiles to provide a tumor diagnosis.

Use of BTM and UBTM to monitor the progress of TCC treatment In addition to rapid diagnosis and early detection of TCC, BTM and UBTM markers detected in either tissue, serum, or urine are used to respond to patient treatment. Can be used to monitor In these applications, systemic, intravesical or intravascular chemotherapy, radiation therapy, or immunotherapy initiation may be followed by occasional urine and / or serum samples. Reduced marker accumulation can indicate a reduction in tumor size, which suggests an effective treatment. The rate of decline can be used to predict the optimal therapeutic dose for each patient or treatment.

  The marker to be evaluated is selected from known human genes. The genes evaluated are shown in Figures 3 and 4. Included in FIGS. 3 and 4 are gene names, HUGO identifiers, MWG oligo numbers, NCBI mRNA reference sequence numbers and protein reference numbers. The full length sequence can be found at http://www.ncbi.nlm.nih.gov/entrez/.

  Markers identified as useful in diagnosing and assessing bladder cancer are displayed in Figure 2 and in the sequence listing accompanying this application.

Aspects of the Invention Accordingly, in one aspect, the invention includes a method for detecting bladder cancer comprising detecting the accumulation of UBTM family members in urine.

  In other aspects, UBTM family members are not substantially associated with blood.

  In an additional aspect, the UBTM is selected from the group shown in Figure 3 or 4.

  In yet another aspect, the detecting step is performed by detecting accumulation of BTM or UBTM mRNA.

  In some aspects, the detecting step is performed using a microarray.

  In other aspects, the detecting step is performed using quantitative polymerase chain reaction or hybridization methods.

  In a further aspect, the detecting step is performed by detecting accumulation of UBTM protein.

  In an even further aspect, the detecting step is performed by detecting accumulation of the UBTM peptide.

  In some of these aspects, the detecting step is performed with a UBTM antibody that is either polyclonal or moroclonal.

  In an additional aspect, the method includes detecting accumulation of two or more UBTM family members in the sample.

  In some of these additional aspects, the method comprises detecting TOP2A, MDK, or BIRC5.

  Yet a further aspect includes detecting one or more marker pairs selected from the group consisting of TOP2A-HOXA13, TOP2A-IGFBP5, and TOP2A-SEMA3F.

  In another aspect of the invention, a method of detecting bladder cancer comprises a combination of two or more BTM family members selected from Figures 14a or 14b in a biological sample from a patient suspected of having bladder cancer. The step of detecting accumulation is included.

  In some of these aspects, the biological sample is selected from the group consisting of blood, serum, plasma, tissue, urine, feces, cerebrospinal fluid, and peritoneal lavage.

  Still further aspects include antibodies specific for BTM or UBTM, and methods for their production, either polyclonal or monoclonal antibodies.

  In some of these aspects, the monoclonal antibody can be directed against a BTM or UBTM selected from the group shown in Figure 3 or 4.

  In other of these aspects, the method further comprises another antibody directed against another BTM or UBTM.

  An additional aspect of the invention is a substrate having thereon a capture reagent of a combination of BTM or UBTM, the combination being selected from Figures 14a or 14b; and a detector associated with said substrate, which detector is Capable of detecting the BTM or UBTM combination bound to the capture reagent), and a device for detecting BTM.

  In some of these aspects, the capture reagent comprises an oligonucleotide.

  In an additional aspect, the capture reagent comprises an antibody.

  In some aspects, BTM or UBTM is selected from the group designated in Figure 3 or 4.

  The invention further includes a kit for cancer detection, wherein the kit comprises a substrate; a capture reagent of a combination comprising at least two of BTM or UBTM, the combination being selected from Figure 14a or 14b. ; And instructions for use.

  Some kits include capture reagents that are BTM or UBTM specific oligonucleotides or BTM specific antibodies.

  In some kits, BTM or UBTM is selected from the group shown in Figures 3 or 4.

  In one kit, the marker is selected from the group consisting of IGFBP5, MGP, SEMA3F and HOXA13.

  An additional aspect is a method for detecting the presence of bladder cancer, comprising the group consisting of BIRC2, CDC2, HOXAl3, IGFBP5, MDK, MGP, NOV, NRP1, SEMA3F, SPAG5, TOP2A in a urine sample. A method comprising determining the presence of one or more markers of choice. Here, the marker is substantially absent in blood.

  Another aspect of the present invention is the accumulation of one or more markers selected from the group consisting of HOXA13, IGFBP5, MDK, MGP, NRP1, SEMA3F, SMC4L1, TOP2A, and UBE2C in the urine of said patient. A method for distinguishing a malignant bladder disease from a non-malignant bladder disease, comprising: determining; and a ratio of the marker in the sample, the ratio being associated with the presence of bladder cancer. Be done.

  In some of these aspects, the method comprises measuring the accumulation of at least one second BTM in urine.

  In some of these embodiments, the first marker is TOP2A and the second marker is selected from the group consisting of HOXA13, IGFBP5, and SEMA3F.

  In an additional aspect, the invention includes associating the rate of accumulation of the marker as indicative of superficial bladder cancer, invasive stage 1 bladder cancer, or invasive stage 2-3 bladder cancer.

  In a still further aspect, the invention provides for the abundance of one or more markers selected from FIG. 3 or 4 in a first sample from a patient to be present in a second sample from a patient after a treatment period. A method for determining the therapeutic efficacy of bladder cancer, which comprises a step of comparing the abundance of one or more markers selected from FIGS. 3 or 4 with each other.

As described herein, tumor detection can be performed by measuring the expression of one or more tumor markers. It was unexpectedly discovered that the increased expression of either multiple BTMs or UBTMs was highly associated with the presence of diagnosed bladder cancer. The smallest significant association detected had a p-value of approximately 0.018. Most of the associations were significant with p-values less than 10 ^-10 . Due to such high significance, it may not be necessary to detect increased expression or accumulation of more than one BTM or UBTM. However, the redundancy of the BTM of the present invention allows bladder cancer to be detected with increased reliability.

  The methods provided herein include more sensitive analyses. qPCR is extremely sensitive and can be used to detect very low copy number (eg 1-100) gene products in a sample. Such sensitivity allows for the very early detection of events related to bladder cancer.

METHODS Tumor Collection Bladder tumor samples and non-malignant urothelial samples were collected from surgical specimens resected at Kyoto University Hospital in Japan and other collaborative Japanese hospitals.

Urine Collection Urine samples from non-malignant control and bladder cancer patients were obtained from Kyoto University Hospital, Japan (Figure 1). Healthy control samples were obtained from Caucasian and Japanese volunteers.

RNA Extraction Tumor tissue was homogenized in a TriReagent: water (3: 1) mixture and then extracted with chloroform. Total RNA was then purified from the aqueous phase using the RNeasy ™ method (Qiagen). RNA was also extracted from 16 cancer cell lines and pooled to serve as reference RNA.

  RNA, urine samples were taken in equal volumes of lysis buffer (5.64 M guanidine-HCl, 0.5% sarcosyl, 50 mM sodium acetate pH 6.5, and 1 mM β-mercaptoethanol; pH 7 at 1.5 M Hepes pH 8). It was extracted from the urine by mixing with (adjusted to 0.0). Total RNA was then extracted using the Trizol and RNeasy ™ methods. RNA preparations were further purified using the Qiagen QIAquick ™ PCR purification kit prior to cDNA synthesis.

  RNA was extracted from the blood of three healthy volunteers by performing Trizol / RNeasy ™ extraction on cells enriched from whole blood using sedimentation in 3.6% dextran.

Microarray Slide Preparation Epoxy resin coated glass slides (MWG Biotech) were printed with ~ 30,000 of 50-mer oligonucleotides (MWG Biotech) using Gene Machines microarray making robots according to the manufacturer's protocol. ..

RNA labeling and hybridization cDNA was reacted from 5 μg of total RNA with Superscript II ™ reverse transcriptase (Invitrogen) containing 5- (3-aminoallyl) -2'deoxyuridine-5'triphosphate. I transcribed it. The reaction was then deionized on a Microcon column and then incubated with Cy3 or Cy5 in bicarbonate buffer for 1 hour at room temperature. Unincorporated dye was removed using a Qiaquick column (Qiagen) and samples were concentrated to 15 μl in SpeedVac. The Cy3- and Cy5-labeled cDNAs were then mixed with Ambion ULTRAhyb ™ buffer, denatured at 100 ° C for 2 minutes, and hybridized to microarray slides at 42 ° C for 16 hours in the hybridization chamber. The slides were then washed and scanned twice in an Axon 4000A ™ scanner at two power settings.

Microarray Analysis of Cancer Marker Genes RNA from 53 bladder tumors and 20 non-malignant (“normal”) bladder tissue samples were labeled with Cy5 and hybridization with Cy3 labeled reference RNA was performed in duplicate or triplex. Went to. Then, after normalization, the change in expression in each of the 29,718 genes was estimated by fold change and statistical probability.

Normalization Procedure The median fluorescence intensity detected by Genepix ™ software was corrected by subtracting the local background intensity. Spots with background corrected intensities below zero were excluded. Intensity ratios and total spot intensities were log-transformed to facilitate normalization. Logarithmic intensity ratios were corrected for dye and spatial bias using local regression included in the LOCFIT ™ package. Logarithmic intensity ratios were regression estimated simultaneously for total spot intensity and localization. The residuals of the local regression gave the corrected logarithmic fold change. For quality control, the ratio of each normalized microarray was plotted with respect to spot intensity and localization. The plot was then visually inspected for the presence of any residual artifacts. In addition, an ANOVA model was applied for pin tip bias detection. All normalization results and parameters were entered into the Postgres database for statistical analysis.

Statistical Analysis In order to improve the comparison of the measured fold changes between arrays, log ₂ (ratio) was scaled to have the same total standard deviation per array. This normalization reduced the mean intra-class variation. Log ₂ (ratio) was further moved so that each oligonucleotide had a median value of zero to facilitate visual inspection of the results. A rank sum test based on fold change was then used to improve noise immunity. This assay consists of two steps: i) calculation of the fold change rank (Rfc) within the array, and ii) subtraction of the median of normal tissue (Rfc) from the median of tumor tissue (Rfc). The difference between both median ranks defines the score for the fold change rank. Three additional statistical tests were performed on the standardized data: 1) Student's two-sample t-test, 2) Wilcoxon test, and 3) Statistical analysis of microarrays (SAM). The 300 most significantly upregulated genes, determined by each of the statistical methods (fold change rank, t-test, Wilcoxon test, and SAM), were given a rank score for each test. If a gene appeared in one list and not in one or more of the others, a weighting factor of 500 was added to the score. Next, all ranking scores were added together to give one total ranking score.

Statistical Analysis of Marker Combinations To determine the value of using a two-marker or three-marker combination to distinguish tumors from non-malignant samples, qPCR data from tumors and non-malignant samples were submitted for subsequent analysis. did. Normal distributions for non-malignant and tumor samples were generated using sample means and standard deviations. Then, the value obtained from the tumor expression data exceeds a defined threshold (eg, 50%, 70%, 75%, 80%, 90%, 95%, or 99% or more) in the non-malignant distribution. Probability (ie sensitivity) was determined. For marker combinations, the probability of at least one marker exceeding the threshold was determined.

  To show the value of the combination of markers analyzed in urine samples as well as tumor samples, a normal distribution analysis was performed using qPCR obtained from urine samples from TCC patients and non-malignant controls described in series 2 of FIG. Performed on the data. Values obtained from qPCR data in TCC patients exceed a defined threshold (eg, greater than 50%, 70%, 75%, 80%, 90%, 95%, or 99%) in the distribution of non-malignant samples Determined the probability.

Methods for Detecting Bladder Cancer Markers in Urine In some embodiments, BTM analysis can be desirably performed on urine samples. In general, methods for analyzing oligonucleotides, proteins, and peptides in these liquids are known in the art. However, for illustration, urinary levels of BTM can be quantified using a sandwich enzyme linked immunosorbent assay (ELISA). For plasma or serum analysis, 5 μl aliquots of appropriately diluted sample or serially diluted standard BTM and 75 μl of peroxidase-conjugated anti-human BTM antibody are added to the wells of a microtiter plate. After a 30 minute incubation period at 30 ° C., the wells are washed with 0.05% Tween 20 in phosphate buffered saline (PBS) to remove unbound antibody. The BTM and anti-BTM antibody binding complex is then incubated with o-phenylenediamine containing H ₂ O ₂ for 15 minutes at 30 ° C. The reaction is stopped by adding 1 MH ₂ SO ₄ and the absorbance at 492 nm is measured by a microtiter plate reader. Of course, the anti-BTM antibody may be a monoclonal antibody or a polyclonal antiserum.

  Many proteins are secreted by (1) cells, (2) stripped from the cell membrane, (3) lost to cells by cell death, or (4) contained in cells that have been shed. Therefore, it is natural that BTM is also detected in urine. Furthermore, the diagnosis of bladder cancer can be determined by measuring either the expression of BTM in the sample or the accumulation of BTM in the sample. Prior art diagnostic methods include cystoscopy, cytology, and examination of cells extracted during these procedures. Such methods have relied on the identification of tumor cells in urine, or in exfoliated samples of urothelium, or in other cases, biopsy samples of the bladder wall. These methods have several types of errors, including sampling error, inter-observer identification error, and others.

Quantitative real-time PCR
Real-time or quantitative PCR (qPCR) is used for absolute or relative quantification of PCR template copy number. The Taqman ™ probe and primer sets were designed using Primer Express V 2.0 ™ (Applied Biosystems). When possible, the resulting amplicon contained all possible splicing variants, conferring amplicon predominance on the region covered by the microarray oligonucleotides from MWG-Biotech. The primer and probe sequences are shown in FIG. Alternatively, if the target gene was displayed by an Assay-on-Demand ™ expression assay (Applied Biosystems) covering the desired amplicon, these were used. For analyzes designed in-house, primer concentrations were titrated using the SYBR Green Label protocol and cDNA made from reference RNA. Amplification was performed on the ABI Prism ™ 7000 Sequence Detection System under standard cycling conditions. When the products of a single round of amplification were observed in the dissociation curve, the optimal primer concentration and 5'FAM to 3'TAMRA phosphate Taqman ™ probe (Proligo) were used at a final concentration of 250 nM over 625 fold. A standard curve was generated over the concentration range. The analysis that gave the standard curve with a regression coefficient above 0.98 was used in the next analysis.

The analysis can be performed on two 96-well plates, with each RNA sample being represented by a single cDNA. Each plate contained a duplicate, reference cDNA standard curve over a 625-fold concentration range. The analysis consisted of the calculation of ΔCT (CT of target gene-CT of average reference cDNA). ΔCT is directly proportional to a negative log ₂ fold change. Next, the relative log ₂ fold change in median non-malignant log ₂ fold change was calculated (log ₂ fold change - median normal log ₂ fold change). Fold changes can then be clustered into frequency classes and graphed or illustrated in a boxplot.

Selection of Serum and Urine Markers for Bladder Malignant Tumors Putative serum markers are (i) the possibility that the encoded protein is secreted from the cell or stripped from the cell membrane, (the possibility of secretion is TargetP ™ ) (Based on analysis by Emanuelsson et al; J. MoI. Biol. 300, 1005-1006 (2000)) and (ii) its total rank score, which allows selection from array data. , Changes in the degree of overexpression in tumor samples are not only related to tumor heterogeneity but also to tumor samples in smooth muscle, connective tissue, submucosal cells (see US Patent 6,335,170), stromal cells, and non-malignant epithelium. It also reflects variations in the degree of contamination of "normal" tissues, including, in many situations, "normal" contamination ranged from 5 to 70% with a median of approximately 25%.

  We could therefore reduce these "false positive" results by analyzing BTM in urine samples that were not highly contaminated with normal bladder cells. Furthermore, by using the qPCR method, we were able to more accurately determine the mRNA levels in urine samples compared to the use of prior art microarray methods. As a result, we were able to avoid large contamination with other bladder cell types, thereby avoiding one of the more cumbersome problems in microarray analysis techniques for clinical samples.

  By measuring the accumulation of markers in urine and not depending on the prevalence in tumors, we have unexpectedly discovered many BTMs useful in detecting bladder cancer and determining its stage and / or its type did. Moreover, because one of the first signs a patient sees a physician for possible bladder cancer is the presence of blood in the urine, BTM, which is not highly expressed in blood, can be of great diagnostic value. I decided. These markers include IGFBP5, MGP, SEMA3F, and HOXA13 (see Figure 9).

  Measuring accumulation has advantages over defining "overexpression". As pointed out above, increased accumulation refers to true overexpression or increased expression rate (ie, heteronuclear RNA (hnRNA) molecule, mRNA molecule or protein per cell per unit time in the molecular biological sense). Increased number of). However, accumulation can also mean an increase in the amount of marker in a given volume, such as in urine, even though the rate of expression does not increase. For example, even if one tumor cell produces a normal amount of marker, the presence of cancer can be revealed by the observed increase in the number of such cells in the sample. Furthermore, the accumulation may reflect free or soluble RNA in the sample. In some cases, the tumor cells that produced the marker may die and the cellular contents may be released into the surrounding tissue. If the cell contents reach the urine, the free marker RNA can be detected there. These phenomena may be particularly useful in diagnosing superficial bladder cancer, which was usually difficult to diagnose with selectivity and specificity. Measuring the accumulation of markers in the urine may be one of the first signs of superficial bladder cancer. Thus, using the method and apparatus of the present invention, it may be possible to detect early bladder cancer.

  We also note that care must be taken in compensating for changes in sample volume when measuring accumulation. For example, in urine, the amount of marker per unit volume may depend on the renal function of the subject. Thus, in the presence of diminished urine production, cells in the urine (including tumor cells) are enriched, resulting in an artificially high measure of accumulation (per unit volume). Such artifacts can be reduced by making independent measurements of urine production (eg, urine output per unit time), urine clearance (eg, measuring creatinine or BUN). Conversely, in situations where urine production is increasing, such as during diuresis, cells containing the marker may be diluted to produce an artificially low measure of accumulation. However, diuretic use, fluid intake, and other factors that can produce variations in marker accumulation that are not associated with the true accumulation or mass of the marker in the sample can be controlled. In these situations, the marker amount can be corrected for the urine production rate.

  In this way, by measuring BTM in urine, we can reduce the occurrence of false positive results compared to the prior art methods, which are superior to the prior art methods. Was able to be shown.

  Urine markers were selected from the array data above, except that the criteria for secretion or shedding from the membrane were not applied. Thus, intracellular and membrane-bound markers that were not predicted to be useful serum markers are included as urine markers.

Examples The examples described herein are for purposes of illustrating embodiments of the invention and are not intended to limit the scope of the invention. Other embodiments, methods, and types of analysis are within the skill of those in the molecular diagnostic arts and need not be discussed at length here. Other embodiments within the scope of the technology based on the teachings herein are considered to be part of the present invention.

Example 1
Identification of markers for superficial and invasive malignant tumors of the bladder Hierarchical clustering of microarray data from gene expression patterns of invasive and superficial bladder cancer showed a number of significant differences. As a result, these cancer types were treated separately in the next analysis. However, a high proportion of genes are overexpressed in both cancer types. FIG. 3 is a table showing the results of microarray studies for markers of invasive bladder malignancy. Thirty-one of the 199 invasive markers meet the criteria for serum markers described above (denoted by "S" in the figure). FIG. 4 is a table showing the results of a microarray study of superficial bladder malignancies. 34 of 170 superficial markers meet the criteria for serum markers above. 3 and 4, the gene's HUGO symbol (“symbol”), MWG Biotech oligonucleotide number, NCBI mRNA reference sequence number, protein reference sequence number, mean fold change between oncogene expression and non-malignant gene expression, Maximum fold change between expression in individual tumor samples and median expression in non-malignant samples, original unadjusted Student's t-test results, 2-sample Wilcoxon test results, and total rank score, Is included.

The fold change mean value (tumor: non-malignant tissue) for 199 genes in the invasive bladder cancer marker analysis was in the range of 1.3 to 5.3, and the fold change maximum value was 2.1 to 60. It was in the range of 9. For the superficial bladder cancer analysis, 170 markers were mean overexpression in the range 1.1.3-3.0 and maximum overexpression in the range 1.9-144. For each of the markers shown, the statistical significance of their specificity as a cancer marker was found to be extremely high. Student's t-test values were all less than 10 ^-3 with a few exceptions. This indicates that diagnosis using these markers is highly associated with bladder cancer. It should be noted that the fold changes generated by microarray studies tend to underestimate the actual expression changes observed using more accurate techniques such as qPCR. However, for reasons noted elsewhere, microarray analysis can have one or more significant artifacts. Therefore, we have developed a qPCR-based method to more accurately detect the presence and stage of bladder cancer.

Example 2
qPCR Analysis A more sensitive and more accurate quantification of gene expression was obtained using qPCR for the subset of genes shown in FIGS. Messenger RNAs from 30 invasive bladder tumors, 25 superficial bladder tumors, and 18 samples of normal urothelium against 18 genes identified by microarray analysis (FIGS. 3 and 4). Was analyzed and the results are shown in FIG. Data for invasive and superficial forms of bladder cancer are shown for the markers SPAG5, TOP2a, CDC2, ENG, NRP1, EGFL6, SEM2, CHGA, UBE2C, HOXA13, MDK, THY1, BIRC5, and SMC4L1. The superficial type alone overexpresses only the markers SEMA3F, IGFBP5 and NOV compared to normal urothelium, and the invasive type alone overexpresses only MGP; these markers are overexpressed. In tumor samples that were not treated, they maintained similar expression to normal urothelium. FIG. 5 shows gene names, gene aliases, gene symbols, median fold change between tumor (T) and non-malignant (N) tissues, fold change between the expression of individual tumor samples and median non-malignant tissue expression. Maximums and% of tumor samples with expression levels greater than the 95th percentile of expression levels in non-malignant samples are included.

  Median fold change (tumor tissue expression compared to median non-malignant tissue expression) of the markers in Figure 5 was 2-128 fold for invasive bladder tumors and for superficial bladder tumors except CHGA. Was in the range of 2-39 times. Maximum fold changes for invasive tumors ranged 24-2526 fold and for superficial tumors 6-619 fold. The expression pattern of CHGA was striking because it was extremely high in some tumors (FIGS. 6s to 6t), but was not detectable in other cases. Expression was undetectable in 15/25 superficial tumors, 15/29 invasive tumors, and 9/10 normal samples. Low expression in normal samples precludes accurate quantification of overexpression levels in tumors as a ratio relative to normal, but if BTM mRNA accumulation can be measured and quantified, bladder cancer It can be used as a basis for diagnosis. For invasive tumors, the expression levels of genes SPAG5, TOP2A, and CDC2 were greater than the "normal" range 95th percentile in> 90% of cases in the tumor. With the exception of BIRC5, the remaining genes in FIG. 5 examined had> 45% of the samples with greater than normal 95th percentile expression in invasiveness> tumors. In superficial tumors, the expression levels of genes SPAG5, TOP2A, CDC2, ENG, and NRP1 were greater than the 95th percentile in the non-malignant range for ≧ 80% of cases in the tumor. With the exception of CHGA, UBE2C, and BIRC5, the remaining genes in Figure 5 examined in superficial tumors had> 40% expression in the samples with greater than normal 95th percentile expression.

Figures 6a-6af show the observed frequency of expression of each of a series of 18 genes (vertical axis) and the genes for both normal tissues (light bars) and superficial or invasive tumor tissues (dark bars). FIG. 6 depicts a histogram comparing log ₂ fold change in expression (horizontal axis). We have surprisingly found that for each of these 18 genes, an essential distinction in the frequency distribution exists between normal and tumor tissue. For example, FIG. 6c depicts the results for TOP2a expression in invasive tumors. Only two tumor samples were observed to have expression levels in the normal range.

  18 BTMs: SPAG5, TOP2A, CDC2, ENG, IGFBP5, NOV, NRP1, SEMA3F, EGFL6, MGP, SEM2, CHGA, UBE2C, HOXA13, MDK, THY1, BIRC5, and SMC4L1, in urine of patients and controls. Accumulation (FIG. 1: sample series 1) was measured using qPCR of total RNA extracted from an equal volume of urine. With the exception of EGFL6, 17 of the BTMs showed a large accumulation in the urine of patients compared to control urine samples (Figure 7). The median fold difference for 17 BTMs was in the range of 2-fold to 265-fold. Maximum differences between single patient samples and median control levels ranged from 26-fold to> 10,000-fold.

  FIG. 8 depicts the difference in BTM transcript accumulation for 13 BTMs, plotted as a boxplot and normalized to the median expression of control samples. FIG. 8 shows that MDK, SEMA3F, and TOP2A have no overlap in urine from cancer patients and controls. Moreover, high levels of transcript accumulation of IGFBP5, HOXA13, MGP, NRP1, SMC4L1, SPAG4, and UBE2C are almost always associated with bladder cancer. For the rest of the BTMs depicted in Figure 8: BIRC5, NOV, and CDC2, their expression in the urine of patients with bladder cancer is increased by at least about 3-fold compared to normal control samples.

The main clinical condition that triggers a test for the presence of bladder cancer is hematuria (ie, the presence of macroscopic microscopic levels of blood in the urine). Blood is usually detected visually, or by chemical detection of hemoglobin using a urine “dipstick”. Only approximately 15% and 4% of cases of macroscopic and microscopic hematuria are associated with bladder cancer, respectively. As a result, it is important that the level of marker expression in whole blood be low or, in some cases, undetectable for the bladder cancer test to be highly specific. Therefore, the expression of 12 of the 13 markers in Figure 8 was measured in blood RNA using qPCR to facilitate the identification of markers with high specificity. qPCR was performed on 5 μg of total RNA extracted from blood and bladder tumor tissues using the primers and probe described in FIG. Figure 9 shows the number of cycles above background for each marker. For the markers MGP, IGFBP5, SEMA3F, and HoxA13 no transcript could be detected in the blood, whereas the markers SMC4L1 and UBE2c were specifically expressed in blood. We note that the data showing the number of PCR cycles is essentially a log ₂ plot, showing that increasing the cycle number by 1 doubles the signal. Therefore, in assessing the difference in the presence of markers in tumor tissue and blood, a difference of 2 cycles indicates a 4-fold difference in expression. Similarly, a 5 cycle difference (eg for TOP2A) represents a ²⁵ or 32 fold difference in expression. Other markers such as TOP2A and MDK have detectable blood expression, but remain a good marker due to the large difference between blood expression and bladder tumor expression.

To further investigate the differences between marker expression in whole blood and bladder tumors and to improve the selection of bladder cancer urine markers, 9 markers were selected, an additional 20 patients, 13 normal controls Further analysis was performed with urine RNA from 26 and 26 non-malignant controls (FIG. 1: sample series 2). Non-malignant controls included 20 samples in which either occult blood or white blood cells were detected in their urine by cytology. All nine markers showed differences between control and cancer patient samples, and the median log ₂ overrepresentation of cancer patient samples compared to healthy and non-malignant samples was 5.4-10. 4 and 4.0-10.1 (Fig. 10). A boxplot showing this data is shown in FIG.

  As predicted by blood qPCR data, the markers UBE2C and SMC4L1 showed a marked increase in accumulation in urine of non-malignant controls compared to healthy control urine samples. NRP1 was also significantly elevated in urine samples from non-malignant samples compared to healthy control urine samples, showing a considerable overlap between cancer and non-malignant patient samples, and increased TOP2A and MDK However, due to their very high expression in TCC cells, a large difference was maintained between the accumulation of RNA in urine samples of non-malignant patients and cancer patient samples. In contrast, HOXA13, IGFBP5, SEMA3F, and MGP showed only a small increase in non-malignant urine samples compared to healthy control samples.

  Overall, six markers (SEMA3F, HOXA13, MDK, IGFBP5, MGP, and TOP2A) showed minimal overlap between cancer patient samples and non-malignant controls. The remaining three markers (NRP1, UBE2C, SMC4L1) showed a significant elevation in a subset of non-malignant controls, overlapping with cancer patient samples. Increased accumulation of RNA markers in the urine of non-malignant controls compared to healthy controls is consistent with expression of these markers in cells of hematopoietic or endothelial origin present in the urine of patients with non-malignant disease. To do. Thus, the use of individual markers to diagnose bladder cancer with urine samples shows increased sensitivity and specificity compared to prior art methods that do not consider marker expression in blood. This result was completely unexpected based on the prior art.

  The data show the surprising finding that the efficacy of using highly sensitive and specific urine markers for bladder cancer cannot be accurately predicted using only microarray analysis of oncogene expression data. It is necessary to take into account the expression of putative markers in cells of hematopoietic and / or endothelial origin. This includes: (i) qPCR analysis of blood RNA, (ii) expression database analysis (eg, EST library of blood and vascular / endothelial cell RNA), and / or (iii) RNA extracted from unfractionated urine. can be achieved by qPCR analysis.

Sensitivity and Specificity Based on the two series of samples analyzed and disclosed herein, the sensitivity for detection of bladder cancer is greater than 95%. The specificity in series 2, which included samples from patients with non-malignant diseases, is also above 95%.

Example 3
Use of Multiple Markers in Detection of Bladder Cancer Figures 12a-12b represent histograms of the number of genes showing significantly increased expression ("overexpression") in individual tumor samples compared to normal samples. The histogram was based on the qPCR data obtained from the first 12 markers shown in FIG. Twenty-seven (90%) of 30 invasive tumors in the PCR analysis overexpressed at least 4 genes by more than the 95th percentile (FIG. 12a). Twenty-three of the 25 superficial tumors analyzed (92%) overexpressed at least 4 genes over the 95th percentile (Figure 12b). These findings indicate that cancer detection can be very reliable in the context of multiple gene overexpression relative to normal tissue, thereby providing a more reliable diagnosis of cancer. However, in some cases, elevated expression of a single marker gene can be sufficient to diagnose cancer.

  The reliability of good discrimination between tumor and non-tumor samples using the marker combination is further illustrated by the statistical analysis presented in FIG. This analysis compared the normal distribution of qPCR gene expression data from tumor and non-malignant samples. The qPCR data are summarized in Figure 5. The analysis shows the effect on increasing the number of markers used to distinguish tumor and non-malignant samples on the sensitivity of the test (at a fixed specificity of 95%). Most of the 18 markers do not have a sensitivity of 90, 95 or 99% or more when used alone in this assay, but in 2 or 3 marker combinations, in many 2 or 3 marker combinations , It was possible to reach high sensitivity (FIGS. 14a and 14b).

  14a and 14b show the sensitivity of specific markers and marker combinations for detecting invasive and superficial transitional cell carcinoma (TCC) when the specificity was fixed at 95%. Only combinations with> 90% sensitivity are shown. Among the 15 markers shown in FIG. 14a, TOP2A, SPAG5, and CDC2 alone can detect invasive bladder cancer with a sensitivity of about 95%. The other markers shown show lesser sensitivity when used alone.

  However, combining two of the above markers dramatically improves the sensitivity of detection of invasive bladder cancer (FIGS. 13a and 14a). A sensitivity of 95% or higher can be found with 13 of 105 combinations of 2 markers. In fact, using two markers results in a minimum sensitivity of 90% for 42 of the 105 combinations of markers.

  For superficial bladder cancer (FIGS. 13b and 14b), no sensitivity greater than 90% was found by any of the markers alone. However, this threshold was reached by 11 of 136 two-marker combinations. A sensitivity of> 95% was reached with 22 of the 3 marker combination.

  The use of a combination of markers can also dramatically improve the sensitivity of detecting bladder cancer using urine samples. Figures 15 and 16 show the detection sensitivity of individual markers and marker combinations using urine qPCR data.

  As seen in FIG. 16, only IGFBP5 had> 95% sensitivity, but 8 of the 2 marker combinations and 37 of the 3 marker combinations reached this threshold.

Example 4
Different Transcript Accumulations in Patients with Superficial and Invasive Bladder Cancer From Figure 5, several BTMs including SEMA3F, HOXA13, TOP2A, and SPAG5 differ between invasive and superficial bladder cancer. It can be seen that it shows expression. To extend this observation, the accumulation of these transcripts in urine from patients with invasive and superficial bladder cancer was compared.

  RNA was extracted from equal volumes of urine from the patients described in Figure 1 and BTM accumulation was measured by qPCR. The accumulation of specific BTM combinations was then expressed as a ratio. The combination of BTMs consisted of one BTM with a higher overexpression in superficial bladder tumors than superficial bladder tumors and one BTM with a higher overexpression in superficial tumors than invasive tumors.

  FIG. 17 shows three marker combinations analyzed on urine samples from 20 superficial and 14 invasive TCC patients. The three sets of combinations shown are: (i) TOP2A and HOXA13, (ii) TOP2A and IGFBP5, and (iii) TOP2A and SEMA3F. It is found that the combination of these markers can distinguish between urine samples of superficial and invasive TCC patients. Other markers in FIG. 5, which show differential expression between superficial and invasive forms of TCC, can also determine the type of TCC based on urine sample analysis.

  Furthermore, Figure 18 shows that the use of a combination of two markers including TOP2A can distinguish invasive bladder cancer into stage 1-2 and stage 3 tumors.

  These observations indicate that measurement of the accumulation of several BTM transcripts in urine allows the distinction between invasive and superficial forms of bladder cancer. Moreover, the proportion of BTM in urine samples from patients with bladder cancer, measured by qPCR, gave a more reliable distinction between invasive and superficial types than the same analysis performed on tumor RNA. to enable. This is illustrated in FIG. It uses qPCR data from approximately 23 superficial and 28 invasive bladder tumor RNA preparations: for (i) TOP2A and HOXA13, (ii) TOP2A and IGFBP5, and (iii) TOP2A and SEMA3F. Boxplots are shown; the ratios of these BTMs still allow the distinction between superficial and invasive forms of bladder cancer, but there is a large overlap in the superficial and invasive ratios. This finding may reflect contamination of tumor RNA preparations with cell types that do not have the same BTM ratio as malignant cells, such as muscle and fibroblasts. Alternatively, it may reflect a stronger difference in BTM expression in malignant cells that are discarded in the urine than cells that remain in the body of the tumor. Regardless of the reason for its observation, we conclude that the process of detecting BTM accumulation in urine has substantial advantages over conventional microarray analysis of tissue samples.

Example 5
Antibodies to Bladder Tumor Markers In an additional aspect, the invention includes the generation of antibodies to BTM. Utilizing the methods described herein, novel BTMs can be identified using microarray and / or qPCR methods. Once the putative marker is identified, it can be produced in sufficient quantity to elicit an immune response. In some cases, full length BTM can be used, and in other cases peptide fragments of BTM may be sufficient as immunogens. The immunogen can be injected into a suitable host (eg, mouse, rabbit, etc.) and, if desired, an adjuvant such as Freund's complete adjuvant, Freund's incomplete adjuvant can be injected to increase the immune response. it can. The process of making antibodies is routine in the art of immunology and need not be described further herein. As a result, antibodies against the identified BTM or UBTM can be generated using the methods described herein.

  In an even further embodiment, antibodies can be made to the tumor marker proteins or protein cores identified herein, or to an oligonucleotide sequence unique to BTM. Glycosylation can occur in some proteins, but mutations in the glycosylation pattern can, in some circumstances, result in false detection of BTM types that lack the normal glycosylation pattern. Thus, in one aspect of the invention, the BTM immunogen can comprise deglycosylated BTM, or deglycosylated BTM fragment. Glycosylation can be carried out using one or more glycosidases known in the art. Alternatively, the BTM cDNA can be expressed in cell lines lacking glycosylation, such as prokaryotic cell lines including E. coli and others.

  A vector can be created that has an oligonucleotide encoding BTM therein. Many such vectors can be based on standard vectors known in the art. Transfecting the vector into various cell lines to generate BTM producing cell lines and using them to develop specific antibodies or other reagents for BTM detection or advanced analysis for BTM or UBTM The desired amount of BTM can be produced in order to standardize

Example 6
Kits Based on the findings of the present invention, several types of test kits can be envisioned and produced. First, kits can be made that have a detection device preloaded with a detection molecule (or "capture reagent"). In an embodiment for BTM mRNA detection, such a device may include a substrate (eg, glass, silicon, quartz, metal, etc.) on which, as a capture reagent that hybridizes to the mRNA to be detected. Oligonucleotides are bound. In some embodiments, mRNA can be detected directly by hybridizing the mRNA (labeled with cy3, cy5, radioactive label, or other label) to an oligonucleotide on a substrate. In another embodiment, detection of mRNA can be accomplished by first making DNA (cDNA) complementary to the desired mRNA. The labeled cDNA can then be hybridized to the oligonucleotide on the substrate and detected.

  Regardless of the detection method employed, it is desirable to compare the expression of BTMs tested to a standard measure of expression. For example, RNA expression can be normalized to total intracellular DNA, to the expression of constitutively expressed RNA (eg, ribosomal RNA), or to other relatively constant markers. In embodiments in which BTM is measured in body fluids such as urine, the standard can be an equal volume of urine obtained from a subject without malignancy, as shown herein.

  Antibodies can also be used in the kit as capture reagents. In some embodiments, the substrate (eg, multiwell plate) can have a specific BTM or UBTM capture reagent attached to it. In some embodiments, the kit can include blocking reagents. Blocking reagents can be used to reduce non-specific binding. For example, excess DNA from any convenient source that does not contain BTM oligonucleotides, such as salmon sperm DNA, can be used to reduce non-specific oligonucleotide binding. Nonspecific antibody binding can be reduced with excess blocking protein such as serum albumin. Numerous methods for detecting oligonucleotides and proteins are known in the art, and any strategy that can specifically detect BTM-related molecules can be used, Naturally, it can be considered within the range.

  In embodiments that rely on antibody detection, expressing the BTM protein or peptide on a per cell basis or on a whole cell, tissue or liquid protein, liquid volume, tissue mass (weight) basis. You can Furthermore, BTM in serum can be expressed based on relatively abundant amounts of serum proteins such as albumin.

  In addition to the substrate, the test kit will include capture reagents (such as probes), wash solutions (eg, SSC, other salts, buffers, detergents, etc.), as well as detection moieties (eg, cy3, cy5, radioactive labels, etc.). be able to. The kit can also include instructions and packaging for use.

Example 7
Multiple combinations of BTMs used for bladder cancer detection I
In one set of embodiments, unfractionated urine or urine cell precipitates for detecting bladder cancer, alone or in combination with reagents for testing the BTMs HOXA13, MGP, SEMA3F, and TOP2A. It can be incorporated into a product inspection kit. The extent of accumulation of these BTMs in cancer patients and controls is shown in FIG. Urine samples are obtained from patients diagnosed with bladder cancer, those with urological symptoms including macroscopic or microscopic hematuria, or asymptomatic individuals who are aggravated by disease or require monitoring of therapeutic response. collected. Approximately 2 ml of urine may be collected for testing from a patient or individual who is tested with a kit that measures BTM in unfractionated urine. For testing urine sediments, collect> 20 ml urine.

  Suitable kits include: (i) instructions for use and interpretation of results, (ii) reagents for stabilizing and purifying RNA from unfractionated urine or urine precipitates, (iii) dNTPs and reversals. A reagent for synthesizing cDNA containing transferase, and (iv) a reagent for quantifying BTM cDNA are included. In one format, these reagents are used for quantitative PCR and also include a specific exon-wide oligonucleotide primer, a third oligonucleotide labeled with a probe for detection, Taq polymerase, and other buffers. Solution, salts, and dNTPs required for PCR will be included. The kit may also include other methods for the detection of transcripts, such as direct hybridization of BTM RNA with labeled probes, or branched DNA technology; (v) β-actin, etc., which serve as a measure of quality control. , And oligonucleotides and probes for the detection of transcripts from highly transcribed genes; and (vi) serve as internal calibration standards and as a reference for upper limits of BTM transcript accumulation in healthy and non-malignant controls. , A quantified sample of BTM target sequence; The upper limit can be defined as the 95th or 99th percentile of the control range, although other ranges can be applied. In particular, for the diagnosis of superficial bladder cancer, a convenient threshold is above about 50% and in other cases above about 60%, 70%, or 80%.

  In this way, the methods of the invention can be used to detect bladder cancer, as well as stages and types, with increased sensitivity and specificity compared to prior art methods.

  In some embodiments, renal function can be measured using conventional methods (eg, creatinine measurement). In some of these embodiments, the magnitude of renal function (eg, urine volume, cell mass, cell number, or total cell protein in a urine sample) can correct marker accumulation.

  For tests involving qPCR, test samples that exceed a predetermined upper limit will be scored as positive if the accumulation of BTM in the test sample is more than one PCR cycle above the upper limit. For other detection methods, a result that is more than twice as high as the upper limit of normal (eg, 90th, 95th, or 97.5th percentile) would be scored as positive.

Example 8
Multiple combinations of BTMs used to detect bladder cancer II
In another set of embodiments, the combination of markers: accumulation of either or both of TOP2A / SEMA3F and TOP2A / HOXA13 in urine is used to detect bladder cancer using any type of urinalysis or blood test. The tissue type of bladder cancer present in a patient diagnosed with can be reliably predicted. Therefore, cystoscopy and histology may not be necessary to diagnose the type of bladder cancer.

  The kit used for the examination of these ratios comprises the components (i) to (iv) described in Example 7. Following quantification of BTM accumulation by performing standard qPCR, the TOP2A / SEMA3F and TOP2A / HOXA13 ratios were calculated. The range of these ratios in the urine of patients with superficial and invasive bladder cancer is shown in FIG. Using a qPCR test, if the difference between TOP2A and SEMA3F is less than 5 cycles and SEMA3F is the most abundant transcript, invasive bladder cancer is predicted, and differences over 5 cycles are superficial. Bladder cancer can be predicted. For TOP2A and HOXA13, differences of less than 8 cycles can predict invasive bladder cancer when HOXA13 is the most abundant transcript, and differences of more than 8 cycles predict superficial bladder cancer can do.

Example 9
Assessment of Bladder Cancer Exacerbation Using BTM To assess progression of bladder tumors, tissue samples are obtained by biopsy of the bladder wall or urine samples are collected over time from patients with bladder cancer. Assessment of accumulation of BTM, UBTM, or a combination thereof is performed on samples taken at different times. Increased accumulation of BTM or UBTM, either individually or in combination, suggests exacerbation of bladder cancer.

Example 10
Evaluation of Treatment of Bladder Cancer Using BTM To assess the efficacy of treatment for bladder tumors, tissue and / or urine samples are obtained prior to initiation of treatment. It determines the baseline level of one or more BTMs or UBTMs and also determines the ratio of various BTMs and UBTMs to each other. Treatment is initiated and treatment can include any known treatment appropriate to the type and stage of the disease, including surgery, radiation therapy, or chemotherapy. During the course of treatment, tissue and / or urine samples are collected and analyzed for the presence and amount of BTM and / or UBTM. The ratios of various BTMs and UBTMs are determined and the results are compared to: (1) baseline levels of patients before treatment, or (2) normal values obtained from a population of individuals without bladder cancer.

INCORPORATION BY REFERENCE All publications and patents cited in this application are fully incorporated herein by reference. The application includes nucleotide and / or protein sequences. Sequence listings in a computer readable format, and diskettes containing the sequence listings are included in this application and are fully incorporated herein by reference.

  Methods to detect BTM and UBTM family members include detection of nucleic acids, proteins, and peptides using microarrays and / or real-time PCR methods. The compositions and methods of the present invention are useful for diagnosing diseases, for assessing therapeutic efficacy, and for producing reagents and test kits suitable for measuring expression of BTM or UBTM family members.

Claims (36)

  A method for detecting bladder cancer comprising detecting the accumulation of UBTM family members in urine.   The method of claim 1, wherein the UBTM family member is not substantially blood related.   The method according to any one of claims 1 to 2, wherein the UBTM is selected from the group shown in Fig. 3 or Fig. 4.   The method according to any one of claims 1 to 3, wherein the detecting step is performed by detecting accumulation of BTM or UBTM mRNA.   The method according to claim 1, wherein the detecting step is performed using a microarray.   The method according to any one of claims 1 to 4, wherein the detecting step is performed by using a quantitative polymerase chain reaction or a hybridization method.   The method according to any one of claims 1 to 4, wherein the detecting step is performed by detecting accumulation of UBTM protein.   The method according to claim 7, wherein the detecting step is performed by detecting accumulation of UBTM peptide.   The method according to any one of claims 7 to 8, wherein the detecting step is performed using a UBTM antibody.   10. The method of claim 9, wherein the antibody is polyclonal.   10. The method of claim 9, wherein the antibody is moroclonal.   12. The method of any one of claims 1-11, wherein the method comprises detecting the accumulation of two or more UBTM family members in the sample.   13. The method of any one of claims 1-12, further comprising detecting TOP2A, MDK, or BIRC5.   13. The method of any one of claims 1-12, further comprising detecting one or more marker pairs selected from the group consisting of TOP2A-HOXA13, TOP2A-IGFBP5, and TOP2A-SEMA3F. A method for detecting bladder cancer comprising:
Detecting the accumulation of a combination of two or more BTM family members selected from Figure 14a or 14b in a biological sample from a patient suspected of having bladder cancer,
Including the method.   16. The method of claim 15, wherein the biological sample is obtained from tissue or urine.   An antibody specific for BTM or UBTM.   18. The antibody of claim 17, wherein the antibody is polyclonal.   18. The antibody of claim 17, wherein the antibody is moroclonal.   The antibody according to any one of claims 17 to 19, wherein BTM or UBTM is selected from the group shown in Fig. 3 or 4.   18. A mixture of antibodies comprising the antibody of claim 17 and another antibody directed against another BTM or UBTM. A substrate having thereon a capture reagent of a combination of BTM or UBTM selected from Figures 14a or 14b; and a detector associated with said substrate,
An apparatus for detecting BTM, wherein the detector is capable of detecting the combination of BTM or UBTM bound to the capture reagent.   23. The device of claim 22, wherein at least one of the capture reagents comprises an oligonucleotide.   23. The device of claim 22, wherein at least one of the capture reagents comprises an antibody.   23. The apparatus of claim 22, wherein the BTM or UBTM is selected from the group specified in Figure 3 or 4. Substrate;
A combination of at least two BTM or UBTM capture reagents selected from Figures 14a or 14b on the substrate; and instructions for use,
A kit for detecting cancer, which comprises:   27. The kit of claim 26, wherein at least one of the capture reagents is a BTM or UBTM specific oligonucleotide.   27. The kit of claim 26, wherein at least one of said capture reagents is a BTM specific antibody.   27. The kit of claim 26, wherein the BTM or UBTM is selected from the group shown in Figure 3 or Figure 4. A method for detecting the presence of bladder cancer comprising:
Determining the presence in the urine sample of one or more markers selected from the group consisting of BIRC2, CDC2, HOXA13, IGFBP5, MDK, MGP, NOV, NRP1, SEMA3F, SPAG5, TOP2A, said marker Is virtually absent in blood, the method.   31. The method of claim 30, wherein the marker is selected from the group consisting of IGFBP5, MGP, SEMA3F, and HOXA13. A method for distinguishing malignant bladder disease from non-malignant bladder disease:
Measuring the accumulation in the urine of the patient of one or more markers selected from the group consisting of HOXA13, IGFBP5, MDK, MGP, NRP1, SEMA3F, SMC4L1, TOP2A, and UBE2C; A method of determining a ratio of markers, the ratio being associated with the presence of bladder cancer.   31. The method of claim 30, further comprising measuring the accumulation of at least a second BTM in urine.   34. The method of claim 33, wherein the first marker is TOP2A and the second marker is selected from the group consisting of HOXA13, IGFBP5, and SEMA3F.   34. The method of claim 33, further comprising correlating the rate of accumulation of the marker as indicative of superficial bladder cancer, invasive stage 1 bladder cancer, or invasive stage 2-3 bladder cancer. A method for determining the therapeutic efficacy of bladder cancer:
The abundance of one or more markers selected from FIG. 3 or 4 in the first sample from the patient is determined by the above-mentioned 1 selected from FIG. 3 or 4 in the second sample from the patient after the treatment period. A method comprising comparing the abundance of one or more markers.

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