WO2011072130A1

WO2011072130A1 - Methods for diagnosing or monitoring for recurrence of prostate cancer

Info

Publication number: WO2011072130A1
Application number: PCT/US2010/059694
Authority: WO
Inventors: Robert Graham Cooks; Allison Lisa Dill; Livia Schiavinato Eberlin; Demian R. Ifa
Original assignee: Purdue Research Foundation
Current assignee: Purdue Research Foundation
Priority date: 2009-12-10
Filing date: 2010-12-09
Publication date: 2011-06-16
Anticipated expiration: 2012-06-10

Abstract

The invention generally relates to methods of diagnosing prostate cancer or monitoring for recurrence of prostate cancer. In certain embodiments, methods of the invention involve obtaining a prostate tissue sample, and conducting an assay on the tissue to direct a presence of cholesterol sulfate, thereby diagnosing prostate cancer in a patient.

Description

METHODS FOR DIAGNOSING OR MONITORING FOR RECURRENCE OF

PROSTATE CANCER

Related Application

The present application claims the benefit of and priority to U.S. provisional patent application serial number 61/285,320, filed December 10, 2009, the content of which is incorporated by reference herein in its entirety.

Government Interest

This invention was made with Government support under Grant Number

1R21EB009459-01 awarded by National Institute of Health (NIH). The Government has certain rights in this invention.

Field of the Invention

The invention generally relates to methods for diagnosing prostate cancer or monitoring for recurrence of prostate cancer.

Background

Prostate cancer is the most common cancer diagnosis and the second most common cause of cancer related deaths in men. Currently, serum prostate-specific antigen (PSA) is the only biomarker widely used in the diagnosis and management of patients. PSA lacks diagnostic sensitivity and specificity, leading to false-negative and false-positive test results. There is an urgent need for clinically validated biomarkers that will improve the diagnosis of prostate cancer.

Summary

The present invention provides a putative biomarker, cholesterol sulfate, that is differentially present in the prostatic tissue samples of patients suffering from prostate cancer or precancerous lesions as compared to normal prostate tissues. The presence of this putative marker in patient tissue samples provides information that a diagnostician can correlate with a probable-diagnosis of prostate cancer or precancerous lesions. An aspect of the present invention provides methods for diagnosing prostate cancer or precancerous lesions in a subject (e.g., human) that involve obtaining a prostate tissue sample, and conducting an assay on the tissue to detect a presence of cholesterol sulfate, thereby diagnosing prostate cancer or precancerous lesions in a subject. Any method known in the art may be used to detect the presence of cholesterol sulfate in the tissue sample. In certain embodiments, the assay employs a mass spectrometry technique. In more particular

embodiments, the mass spectrometry technique is desorption electrospray ionization. In still more particular embodiments, the desorption electrospray ionization is performed in negative ion mode and in an imaging mode. The detected mass of the cholesterol sulfate anion is m/z 465.4.

Another aspect of the invention provides methods to detect and/or diagnose cancer in prostatic tissue that involve subjecting a sample of prostatic tissue to desorption electrospray ionization mass spectrometry imaging to show a spatial distribution of the compounds found in the sample, and identifying any portion of the sample evidencing the presence of cholesterol sulfate.

Other aspects of the invention provide methods for monitoring for recurrence of prostate cancer in a subject that involve obtaining a prostate tissue sample from a subject that has previously been treated for prostate cancer, and conducting an assay on the tissue to detect a presence of cholesterol sulfate, the presence of which indicates a recurrence of the prostate cancer in the subject.

Brief Description of the Drawings

Fig. 1 shows typical negative ion mode mass spectra of (A) human prostate cancer and (B) adjacent normal tissue in the range of m/z 150 to m/z 1000. CK) mass spectra of (C) assigned cholesterol sulfate (m/z 465.4) from human prostate cancer tissue and of (D) standard cholesterol sulfate samples. The insets show the isotopic patterns of respective cholesterol sulfate ions. Characteristic fragment ion at m/z 97 was observed for both the standard and molecule detected in prostatic tissue.

Fig. 2 shows DESI-MS ion images of m/z 465.4, assigned as cholesterol sulfate, in the negative ion mode, and H&E stained image of prostate samples (A) MH0202-37, cancer and adjacent normal tissue with PIN, (B) MH212-04, cancer and adjacent normal tissue with ΡΓΝ, (C) UH0003-31, cancer and adjacent normal tissue with PIN, (D) MH0211-06 normal and cancer tissue, and (E) UH0002-29M, cancer tissues with normal regions within the sections.

Figure 3 shows negative ion mode tissue imaging of prostate tissue showing areas of cancer and adjacent normal tissue with PIN in sample MH0107-17. (A)-(P) Ion images of m/z 465.4, cholesterol sulfate for selected serial sections. Numbered serial sections from 1 to 20 are approximately 100 μιη apart.

Fig. 4 shows negative ion mode tissue imaging of prostate tissue showing areas of cancer and normal tissue with PIN in sample MHO 107-01 (left and right sides, respectively, for each of eight images). (A) Ion image of m/z 788.4, PS(18:0: 18: 1), (B) Ion image of m/z 885.5,

PI(18:0/20:4), (C) Ion image of m/z 465.4, cholesterol sulfate and (D) H&E stained tissue sections of the tumor tissue and normal. Ion images of m/z 465.4, cholesterol sulfate, for 4 additional adjacent sections of the tissue pieces are shown in E-H. Numbered serial section from 1 to 20 are approximately 100 μιη apart.

Figure 5 shows imaging for sample MHO 107- 17 (A) PCA-developed images, false color plot of PCI, PC2, and PC3. (B) H&E stained tissue sections of the tumor tissue and normal with PIN.

Figure 6 shows negative ion mode tissue imaging of prostate tissues including areas of cancer and adjacent normal tissue of sample MH0301-17. (A) Ion image of m/z 788.4,

PS(18:0:18: 1), (B) Ion image of m z 885.5, PI(18:0/20:4), (C) H&E stained tissue sections of the tumor tissue and normal, (D) Ion image of m/z 303.3, FA(20:4), (E) Ion image of m/z 465.4, cholesterol sulfate, and (F) PCA-developed images, false color plot of PCI, PC2, and PC3.

Figure 7 shows DESI-MS ion image of m/z 465.4, cholesterol sulfate, in the negative ion mode, and H&E stained image of prostate samples (A) MH0202-37, cancer and adjacent normal tissue with PIN, (B) MH212-04, cancer and normal tissue with PIN, (C) UH0003-32, cancer and normal tissue with PIN, (D) UH0003-12, PIN and normal tissue and (E) UH0002-29, PIN detected within normal regions of tissue.

Figure 8 shows negative ion mode tissue imaging of prostate tissues including areas of adjacent normal with PIN and cancer tissue of sample MH0301-11; (A) Ion image of m/z 788.4, PS(18:0:18: 1), (B) Ion image of m/z 885.5, PI(18:0/20:4), (C) H&E stained tissue sections of the tumor tissue and normal. (D) Ion image of m/z 303.3, FA(20:4), (E) Ion image of m/z 465.4, cholesterol sulfate and (F) PCA-developed images, false color plot of PCI, PC2, and PC3. Figure 9 shows negative ion mode tissue imaging of normal prostate tissues of sample MH0108-32; (A) Ion image of m/z 788.4, PS(18:0: 18:1), (B) Ion image of m/z 885.5,

PI(18:0/20:4), (C) H&E stained tissue sections of the tumor tissue and normal. (D) Ion image of m/z 303.3, FA(20:4), (E) Ion image of m/z 465.4, cholesterol sulfate and (F) PCA-developed images, false color plot of PCI, PC2, and PC3.

Detailed Description

The present invention constitutes the recognition of a putative biomarker, cholesterol sulfate, that is differentially present in the prostatic tissue samples of patients suffering from prostate cancer or precancerous lesions as compared to normal prostate tissues. The presence of this putative marker in patient tissue samples provides information that a diagnostician can correlate with a probable diagnosis of prostate cancer or precancerous lesions. The invention also includes the use of a method of recognizing CS in prostate tissue based on mass

spectrometry, specifically desorption electrospray ionization mass spectrometry (DESI-MS). In particular embodiments, the presence of cholesterol sulfate in prostatic tissue samples when detected by DESI-MS imaging indicates the presence of cancer or precancerous lesions.

Cholesterol sulfate (CS) is an important sterol sulfate present in a variety of mammalian tissues and is known for its stabilizing and regulatory role as a cell membrane component. It is known that alterations in the lipid composition of tissues occur in various forms of cancer (Glunde et al. Cancer Research, 64:4270-4276, 2004; and Iorio et al, Cancer Research, 65:9369- 9376, 2005). CS has been reported as a potential tumor marker found in human uterine cervical carcinomas tissue (Kiguchi et al., Clin. Cancer Res. 4:2985, 1998). The same study showed that CS is coexpressed with transglutaminase-I and cytokeratin in the well-differentiated types of squamous cells cancer as a tumor marker. Increased accumulation of CS has also been observed in tumorigenic esophageal rat cells (Rearick et al. Cancer Res. 48:5289, 1988). Cholesterol sulfate has not previously been reported in prostate tissue samples. Thus, CS has the potential to play an important role in prostate cancer diagnosis since it is seen at significantly higher levels in cancerous and precancerous tissues as compared to adjacent normal tissue in which it is not present or present at very low levels.

Tissue samples may be obtained by any clinically acceptable technique. A tissue refers to a mass of connected cells and/or extracellular matrix material, e.g. prostate tissue, skin tissue, nasal passage tissue, CNS tissue, neural tissue, eye tissue, liver tissue, kidney tissue, placental tissue, mammary gland tissue, gastrointestinal tissue, musculoskeletal tissue, genitourinary tissue, bone marrow, and the like, derived from, for example, a human or other mammal and includes the connecting material and the liquid material in association with the cells and/or tissues. A tissue also includes biopsied tissue and media containing cells or biological material.

In particular embodiments, flash frozen tissue sections were sliced to a thickness of 15pm using a cryostat and thaw mounted onto glass slides, which were stored in closed containers at -80°C until the time of analysis. Each slide contained two pieces of tissue, one tumor and one adjacent normal. The glass slides containing the tissue samples were allowed to come to room temperature and dried under vacuum for approximately 20 minutes prior to analysis.

An assay is conducted on the tissue to detect the presence of cholesterol sulfate. Any assay known in the art may be used to detect the presence of cholesterol sulfate in the tissue sample. An exemplary technique for detecting cholesterol sulfate involves subjecting the tissue sample to HPLC and detecting cholesterol sulfate using a light scattering detector. See Grizard et al. (Journal of Chromatography A, 935(1-2): 259-265, 2001), the content of which is incorporated by reference herein in its entirety. Other methods for detecting cholesterol sulfate in tissue are shown in Kiguchi et al. (Clin. Cancer Res. 4:2985, 1998), the content of which is incorporated by reference herein in its entirety.

In certain embodiments, a mass spectrometry technique is employed to detect the cholesterol sulfate in the tissue. Any mass spectrometry technique known in the art may be used with methods of the invention. Exemplary mass spectrometry techniques that utilize ionization sources at atmospheric pressure for mass spectrometry include electrospray ionization (ESI; Fenn et al, Science, 246:64-71, 1989; and Yamashita et al, J. Phys. Chem., 88:4451-4459, 1984); atmospheric pressure ionization (APCI; Carroll et al., Anal. Chem. 47:2369-2373, 1975); and atmospheric pressure matrix assisted laser desorption ionization (AP-MALDI; Laiko et al. Anal. Chem,, 72:652-657, 2000; and Tanaka et al. Rapid Commun, Mass Spectrom., 2: 151-153, 1988). The content of each of these references in incorporated by reference herein its entirety.

Exemplary mass spectrometry techniques that utilize direct ambient ionization/sampling methods including desorption electrospray ionization (DESI; Takats et al, Science, 306:471- 473, 2004 and U.S. patent number 7,335,897); direct analysis in real time (DART; Cody et al, Anal. Chem., 77:2297-2302, 2005); Atmospheric Pressure Dielectric Barrier Discharge Ionization (DBDI; Kogelschatz, Plasma Chemistry and Plasma Processing, 23: 1-46, 2003, and PCT international publication number WO 2009/102766), and electrospray-assisted laser desoption/ionization (ELDI; Shiea et al, J. Rapid Communications in Mass Spectrometry, 19:3701-3704, 2005). The content of each of these references in incorporated by reference herein its entirety.

In certain embodiments, the mass spectrometry technique is desorption electrospray ionization (DESI). DESI is an ambient ionization method that allows the direct ionization of species from thin tissue sections (Takats et al., Science, 306:471-473, 2004). In certain embodiments, the presence of cholesterol sulfate in can be detected by DESI-MS imaging in negative ion mode and is indicative of the presence of prostate cancer or precancerous lesions.

Operated in an imaging mode, it uses a standard microprobe imaging procedure, which in this case involves moving the probe spray continuously across the surface while recording mass spectra. See for example, Wiseman et al. Nat. Protoc, 3:517, 2008, the content of which is incorporated by reference herein its entirety. Each pixel yields a mass spectrum, which can then be compiled to create an image showing the spatial distribution of particular compounds. Such an image allows one to visualize the differences in the distribution of particular compounds over the tissue section. If independent information on biological properties of the tissue is available, then the MS spatial distribution can provide chemical correlations with biological function or morphology.

In particular embodiments, the DESI ion source is a source configured as described in Ifa et al. (Int. J. Mass Spec/rom. 259(8), 2007). The spray solvent used for MS acquisition was acetonitrile: water (50:50) with a 5 kV spray voltage applied. The nitrogen gas pressure was 150 psi and the solvent flow rate was 1.5 pL/min. The tissues were scanned using a 2D moving stage in horizontal rows separated by a 200 pm vertical step until the entire sample surface had been assayed. The surface moving stage included an XYZ Integrated near stage (Newport, Richmond, CA) and a rotary stage (Parker Automation, Irwin, PA). All experiments were carried out using a LTQ linear ion trap mass spectrometer controlled by XCalibur 2.0 software (Thermo Fisher Scientific, San Jose, CA, USA). A software program allowed the conversion of the XCalibur 2.0 mass spectra files (.raw) into a format compatible with the Biomap software (freeware, htto://www.maldo-msi.org). Spatially accurate images were assembled using the Biomap software. It has been found that in resulting spectra from this method in the negative ion mode, cholesterol sulfate is seen at 465.4 m/z (mass to charge ratio). Cholesterol sulfate was identified by performing collision induced dissociation tandem MS experiments, where the molecule was fragmented to reveal the main fragment ion at m/z 97.0, the formation of the [HS0₄] ion. A purchased standard sodium cholesterol sulfate was subjected to the same experiments with the same results, confirming the identity. For further confirmation, the isotopic distribution of the molecular Ion at m/z 465.4 was examined and was in agreement with the presence of sulfur in the ionic species (Metzger et al, Analytical Chemistry, 67:4178, 1995).

When the data is compiled into an image showing the spatial distribution of the compound, the cholesterol sulfate signal can be selected and the intensity is shown in a false color scale. Figure 1 shows example spectra from tumor and normal tissue showing the presence of cholesterol sulfate only in the spectrum from the tumor tissue, as well as results from the CID experiments. Figure 2 shows representative ion images of cholesterol sulfate and the

corresponding histological hematoxylin and eosin (H&E) stained sections. The cholesterol sulfate is only present in the tumor tissue samples or in the precancerous lesions and is absent in the normal tissue.

Cholesterol sulfate correctly identified cancerous or precancerous tissue as determined from pathological examination of the H&E stained tissues in 62 of the 68 tissue samples. In six samples, low intensities of cholesterol sulfate were detected in normal tissues, possibly indicating the presence of precancerous lesions.

Data herein and described below show that detection of cholesterol sulfate by DESI-MS imaging diagnoses prostatic tissues as cancerous, containing precancerous lesions or normal.

Incorporation by Reference

References and citations to other documents, such as patents, patent applications, patent publications, journals, books, papers, web contents, have been made throughout this disclosure. All such documents are hereby incorporated herein by reference in their entirety for all purposes.

Equivalents

The invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The foregoing embodiments are therefore to be considered in all respects illustrative rather than limiting on the invention described herein.

EXAMPLES

Development of methods for the rapid identification of biological markers allowing for the distinction between cancerous and non-neoplastic tissues and disease diagnosis is an important goal in cancer research. To this end, cholesterol sulfate was identified as a novel tumor marker for prostate cancer, as detected by desorption electrospray ionization mass spectrometry (DESI-MS). DESI-MS imaging was applied to analyze the lipid profiles of thin tissue sections of 68 samples of human prostate cancer and normal tissue. Among the lipids detected, cholesterol sulfate was identified as a differential compound found exclusively in cancerous tissues and precancerous lesions.

Example 1 : Tissue preparation

Thirteen pairs of human prostatic tissue, obtained from 13 different patients were obtained from the Indiana University Medical School. All tissue samples were flash frozen in liquid nitrogen at the time of collection and subsequently stored at -80° C until sliced into 15 micrometers thick sections using a Shandon SME Cryotome cryostat (GMI, Inc., Ramsey, MN, USA). The thin tissue sections were thaw mounted to glass slides; each slide contains one section of tumor tissue and one section of adjacent normal tissue from the same patient. The glass slides were stored in closed containers at -80° C. Prior to analysis they were allowed to come to room temperature and then dried under nitrogen in a dessicator for approximately 20 minutes.

A serial section of each sample was formalin fixed and subsequently stained using hematoxylin and eosin (H&E) for pathological examination. The H&E stained slides were pathologically examined for tissue diagnosis.

Example 2: Desorption Electrospray Ionization Imaging

The DESI ion source used was a source configured as described in If a et al. (Int. J. Mass Spec/rom. 259(8), 2007). The spray solvent used for MS acquisition was acetonitrile:water (50:50) with a 5 kV spray voltage applied. Acetonitrile was purchased from Sigma-Alrich (St. Louis, MO, USA) and water (18.2 ΜΩ-cm) was from a PureLab ultra system by Elga Lab Water (High Wycombe, UK). The nitrogen gas pressure was 150 psi and the solvent flow rate was 1.5 μΙ7ηιιη. The tissues were scanned using a 2D moving stage in horizontal rows separated by a 200 μιη vertical step until the entire sample surface had been assayed. The surface moving stage included an XYZ integrated linear stage (Newport, Richmond, CA) and a rotary stage (Parker Automation, Irwin, PA). All experiments were carried out using a LTQ linear ion trap mass spectrometer controlled by XCalibur 2.0 software (Thermo Fisher Scientific, San Jose, CA, USA). A software program allowed the conversion of the XCalibur 2.0 mass spectra files (.raw) into a format compatible with the Biomap software (freeware, htto://www. maldo-msi.org). Spatially accurate images were assembled using the BioMap software. The color scale was normalized to the most intense (100% relative intensity) peak in the mass spectra,

Example 3: PCA Analysis

The DESI-MS imaging raw data were processed in Matlab 2009a, The Math Works (Natick, MA, USA). Each pixel includes a full mass spectrum covering the full mass range recorded in the original data. All pixels were re-sampled to unit resolution and normalized by calculating the median area under the curve for the full image and scaling each pixel to this value. No background adjustment or smoothing filters were necessary. Re-sampling

dramatically decreases the computational complexity of the calculation. PCA was performed for each image individually. Eigen values and eigen vectors were ordered in terms of decreasing component variance. Only the first three principal components are used in the data in the present work. Each eigen value set corresponding to all pixels for a given principal component (e.g., all eigen values calculated for the first principal component eigen vector) were scaled between 0 and 1. For images developed using only one principal component, the eigen value set was plotted over the range blue to red (corresponding to 0 and 1, respectively) using the web color (RGB) scheme.

For plots consisting of data from multiple principal components, each set of eigen values, corresponding to one principal component, was scaled over the range 0 to 255 and convolved with a hexadecimal value characteristic of a primary color RGB scheme. That is, PCI eigen values are convolved with red contribution, PC2 with green contribution, and PC3 with blue contribution. A full hexadecimal number is therefore generated for each pixel in the image and is characteristic of the first three principal components. This "web color" was then plotted to create the image. Contributions to the developed PCA images may be understood by analyzing the loading plots associated with each principal component. An example of this is given for sample

MH0301-17 in Figure 3. Cholesterol sulfate is (m/z 465.4) is a primary contribution to the variation in all three principal components, but most notably for PC2. In the mixed color PCA plot, PC2 is convolved with green, which is seen to correspond well to the existence of cholesterol sulfate in the single ion images.

Example 4: Cholesterol Sulfate as a Biomarker for Prostate Cancer

Data herein show that cholesterol sulfate is a potential tumor marker for prostate cancer, following its detection by desorption electrospray ionization (DESI) imaging mass spectrometry (MS) in prostate tissue samples shown by histopathological examination to be cancerous or precancerous. DESI-MS imaging was applied to analyze the lipid profiles of thin tissue sections of human prostate cancer under ambient conditions and to compare these images with those for non-cancerous tissue, typed as normal tissue in routine histopathological examination.

Cholesterol sulfate (CS) was abundantly observed in cancerous tissues and high grade prostatic intraepithelial neoplasia as determined by histopathological examination, and it was generally undetected in normal tissue by DESI-MS.

DESI-MS imaging of human prostate tissue showed that CS was found almost exclusively in cancerous tissues and high grade prostatic intraepithelial neoplasia (PIN), a pathology considered to be a precancerous lesions. This behavior of CS is qualitatively different to that of other lipids, including particular glycerophospholipids (GPs) and free fatty acids (FAs) which occur in both diseased and healthy tissue samples although with differences in relative ion abundance ratios. In addition to obtaining DESI-MS ion images, principal component analysis (PCA) was used to generate unsupervised statistical images from the DESI-MS data. Strong correlations are shown between standard histological hematoxylin and eosin (H&E) stained sections and DESI-MS acquired images along with principal component analysis (PCA)-derived images of human cancerous and normal prostate tissue.

Standard DESI-MS imaging conditions were used to analyze the tissue samples in the negative ion mode (See Example 2). Mass spectra and ion images from the analysis of 68 prostate tissue samples from 34 different patients were obtained by DESI-MS. Identification of the compounds responsible for the peaks observed in the mass spectra was made based on collision- induced dissociation (CID) tandem MS experiments and by comparison of the production mass spectra to reported literature data or to spectra generated from the standard compounds.

The main ions observed correspond to three major lipid classes; glycerophosphoinositols (PI), glycerophosphoserines (PS) and fatty acids (FA). A peak at mass/charge ratio (m/z) 465.4 was observed at high relative abundances during the analysis of cancerous prostatic tissues (Figure 1A) and undetected in normal tissue (Figure IB). This peak was determined to be cholesterol sulfate and when these ions were subjected to tandem MS experiments for structure elucidation, the main fragment ion was observed at m/z 97.0, assigned as the [HS0₄] ion (Figure 1C). The standard compound, sodium cholesteryl sulfate (Sigma-Aldrich Inc., Milwaukee, WI), was subjected to tandem MS experiments under the same conditions and gave identical results (Figure ID).

For further confirmation, the isotopic distribution of the molecular ion at m/z 465.4 (insets of Figures 1C and ID) was found to agree with the proposed molecular formula (Metzger et al, Analytical Chemistry, 67:4178-4183, 1995). The abundance of ions of any particular m/z value and the distribution of the corresponding molecule in the tissue sample was represented in the form of a DESI-MS image. Although the methodology can be used to generate an image of any ion observed in the mass spectrum, selected ion images from just four particular molecular species for each sample analyzed are displayed here.

The association of cholesterol sulfate, identified by the DESI-MS data, with diseased tissue is provided by pathological examination of the H&E stained sections. The latter information was used to label the tissue sections in the subsequent figures herein. In addition to displaying cholesterol sulfate images from individual tissue sections, PCA was employed to generate images of these sections representing the DESI data from the entire mass spectra. For each full image, PCA was performed after re-sampling to unit resolution and normalizing to the median area under the curve. The resulting PCA images represent a simple and unsupervised way to visually inspect the DESI data for identification of tumor and normal regions based on color-coded differences between the tumor and normal samples. Further analysis of the PCA- derived loading plots showed the peak corresponding to cholesterol sulfate to be a primary contribution to separation of tumor and control in the generated images (see Example 3).

Representative tumor and normal tissue section images from one patient, case number MHO 107-01, are shown in Figure 4 (tumor and normal tissue appear on the left and right side of the images, respectively). Similar intensities were observed for m/z 788.4 (PS(18:0/18: 1)) (Figure 4A) and m/z 885.5 (PI( 18:0/20:4)) (Figure 4B). The notation (X:Y) represents the number of carbon atoms and double bonds in the fatty acid chains, respectively. Remarkably, cholesterol sulfate (m/z 465.4) was observed exclusively in the cancerous tissue, allowing for clear identification of the cancerous tissue (Figure 4C). Within the normal tissue piece, only a small localized signal for CS was observed at the bottom of the tissue. Pathological examination of the H&E stained normal tissue section (Figure 4D) revealed that the specific region in which CS is observed contains precancerous lesions, or high grade prostatic intraepithelial neoplasia (PIN). High grade PIN is characterized by a proliferation of malignant prostatic epithelial cells in prostatic ducts and acini and it is a precursor to the majority of prostatic adenocarcinomas. Therefore, the data herein show that DESI tissue imaging not only allows for clear differentiation between cancerous and normal tissues due to the presence of the tumor marker CS but also allows for detection of precancerous lesions found within normal tissues.

To broaden the analysis, twenty additional serial sections for these tissue specimens (case number MHO 107-01) including the entire tissue pieces were analyzed. Ion images of CS for four of these sections are shown in Figure 4 (E-H) and the additional sixteen sections are shown in Figure 3. In all the tissue sections analyzed, CS signal was undetectable in the normal tissue region while it was observed as the main peak in the mass spectrum for the cancerous tissue section and the small region of PIN. Diagnosis was visualized by the PCA generated image which revealed clear differences between the tumor and normal tissues (Figure 5). Cancerous and normal prostate tissue samples for another patient case number MH0301-17 (Figure 6, tumor and normal tissue appear on the left and right side of the images, respectively) show the same relative intensity in disease and normal tissue for the selected PS, PI and FA ions. However, the cancerous tissue is clearly identified by observing the significantly increased intensity of CS, while CS signal is undetectable in the normal tissue piece.

A total of 68 tissue samples from 34 different patients were analyzed by DESI-MS imaging. H&E stained and DESI-MS image of CS are shown for 10 tissue samples in Figure 7. For the samples shown in panels A, B and C, CS signals are observed in certain regions of the normal tissue in the DESI ion images, which correspond to precancerous lesions as determined by pathological examination. The sample shown in Figure 7D consists of another case in which one piece of tissue is completely normal and the other has PIN, in which CS is undetectable in the normal tissue and present in regions of PIN. Figure 7E shows a case in which both tissue pieces contain PIN, with corresponding CS.

From the 68 tissue samples, 7 were diagnosed as normal tissue, 19 as cancerous tissue, 30 as containing PIN within normal tissue, 4 as containing cancer cells and PIN and 8 as probable PIN. Cholesterol sulfate detection by DESI-MS was correctly correlated to cancerous or high grade PIN tissue as determined from pathological examination of the H&E stained tissues in 64 of the 68 tissue samples (results for two more of these 62 samples are presented in Figures 8 and 9). In two of the other four samples, cholesterol sulfate was detected in localized regions within the normal tissues, indicating the presence of precancerous lesions.

Data herein show that detection of cholesterol sulfate by DESI-MS imaging can positively identify prostatic tissues either as cancerous or containing high grade PIN lesions. Data herein further show that the presence of cholesterol sulfate in prostate tissues serves as a tool for prostate cancer diagnosis.

Claims

What is claimed is:

1. A method for diagnosing prostate cancer or precancerous lesions in a subject, the method comprising:

obtaining a prostate tissue sample; and

conducting an assay on the tissue to detect a presence of cholesterol sulfate, thereby diagnosing prostate cancer or precancerous lesions in a subject.

2. The method according to claim 1, wherein the assay employs a mass spectrometry technique.

3. The method according to claim 2, wherein the mass spectrometry technique utilizes an ionization source that operates at atmospheric pressure.

4. The method according to claim 2, wherein the mass spectrometry technique utilizes a direct ambient ionization/sampling technique.

5. The method according to claim 4, wherein the direct ambient ionization/sampling technique is desorption electrospray ionization.

6. The method according to claim 5, wherein the desorption electrospray ionization is performed in negative ion mode.

7. The method according to claim 6, wherein the desorption electrospray ionization is performed in an imaging mode.

8. The method according to claim 2, wherein the detected mass spectra of the cholesterol sulfate is m/z 465.4.

9. The method according to claim 1, wherein the sample is a human sample.

10. A method to detect and/or diagnose cancer in prostatic tissue comprising: subjecting a sample of prostatic tissue to desorption electrospray ionization mass spectrometry imaging to show a spatial distribution of the mass spectra of compounds found in the sample, and

identifying any portion of the sample evidencing the presence of cholesterol sulfate.

11. The method according to claim 10, wherein the sample is a human sample.

12. The method according to claim 10, wherein the desorption electrospray ionization is performed in negative ion mode,

13. The method according to claim 10, wherein the detected mass spectra of the cholesterol sulfate is m/z 465.4.

14. A method for monitoring for recurrence of prostate cancer in a subject, the method comprising:

obtaining a prostate tissue sample from a subject that has previously been treated for prostate cancer; and

conducting an assay on the tissue to detect a presence of cholesterol sulfate, the presence of which indicates a recurrence of the prostate cancer in the subject.

15. The method according to claim 14, wherein the assay employs a mass spectrometry technique.

16. The method according to claim 15, wherein the mass spectrometry technique utilizes an ionization source that operates at atmospheric pressure.

17. The method according to claim 15, wherein the mass spectrometry technique utilizes a direct ambient ionization/sampling technique.

18. The method according to claim 17, wherein the direct ambient ionization/sampling technique is desorption electrospray ionization.

19. The method according to claim 18, wherein the desorption electrospray ionization is performed in negative ion mode.

20. The method according to claim 19, wherein the desorption electrospray ionization is performed in an imaging mode.

21. The method according to claim 20, wherein the detected mass spectra of the cholesterol sulfate is m/z 465.4.

22. The method according to claim 14, wherein the sample is a human sample.