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Correspondence to: Richard V. Benya, Dept. of Medicine, University of Illinois at Chicago, 840 South Wood Street (M/C 716), Chicago, IL 60612. E-mail: rvbenya@uic.edu
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Summary |
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We previously demonstrated that quantitative immunohistochemistry (Q-IHC) performed by measuring the cumulative signal strength of the digital file encoding an image can be used to determine the absolute amount of chromogen present per pixel. We now show that Q-IHC so performed can be used to accurately determine the amount of peptide hormone receptor of interest in archived tissues. To do this we transfected Balb 3T3 fibroblasts with the cDNA encoding the human receptor for gastrin-releasing peptide (GRP), and selected six cell lines stably expressing between 102 and 106 receptors/cell. These cell lines were fixed in formalin, embedded in paraffin, and treated with antipeptide antibodies against the GRP receptor, followed by DAB chromogen to identify bound antibody. Images were acquired using a 4.9 million pixel digital scanning 24-bit RGB camera, saved in TIFF format, and used for subsequent analysis. Q-IHC was performed after digitally dissecting out the relevant portion of the image for analysis, and processing using a program written in C (available at http://www.uic.edu/com/dom/gastro/Freedownloads.html). Under the conditions defined here, chromogen quantity as determined by Q-IHC tightly correlated with GRP receptor number (r2=0.867) in these cell lines. Using the conversion factor identified as a result of these studies, we then determined GRP receptor number on eight randomly selected, archived human colon cancers. Overall GRP receptor expression in colon cancer depended on the degree to which cells within any particular tumor were differentiated, with well-differentiated cells expressing the greatest numbers of receptors (55,000 ± 10,000 sites/cell). These studies indicate that Q-IHC can be used to determine receptor quantity in archived tissues and other samples of limited quantity.
(J Histochem Cytochem 51:205214, 2003)
Key Words: bombesin, gastrin-releasing peptide, archived tissues, receptor number
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Introduction |
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DIGITAL IMAGE ACQUISITION allows mathematical algorithms to be readily applied towards the computer file encoding any image or portion of that image. Images acquired using a digital RGB camera are stored as three separate N1 x N2 matrix files for images (N1, N2) pixels in size. We previously showed that calculating the mathematical "energy" of an image by determining the cumulative signal strength, or norm, of the digital file encoding that image could be used as the basis for accurate quantification of the amount of chromogen generated during immunohistochemistry (
Although our previously published algorithm for Q-IHC provided the basis for quantifying the absolute amount of chromogen present per pixel (
Here we provide an improved algorithm for performing Q-IHC. Similar to what we previously demonstrated, this technique relies on calculating the cumulative signal strength [or mathematical energy, EM (
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Materials and Methods |
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Reagents
We contracted with Research Genetics (Huntsville, AL) to generate a rabbit antipeptide antibody to the gastrin-releasing peptide receptor using the same epitope as previously described (
Creation of Stable Cell Lines Expressing GRP-R
BALB 3T3 fibroblast cells were stably transfected using a full-length human GRP receptor cDNA. The receptor was subcloned into a modified version of the pcDNA2.1 plasmid using Lipofectamine (Sigma) according to the manufacturer's instructions. Stable transfectants were isolated in the presence of 800 µg/ml aminoglycoside G-418 and ultimately selected by binding studies. Stable cell lines were maintained in DMEM containing 10% fetal bovine serum and 270 µg/ml G-418.
Binding Studies
[125I-Tyr4]-bombesin (2000 Ci/mmol) was prepared using IODO-GEN and purified using high pressure liquid chromatography as previously described (
Immunohistochemical Technique
Immunohistochemistry was performed using two different methods on six cell lines and eight resected colon cancers that were obtained between 1985 and 1997. In the first method, a three-stage indirect immunoperoxidase technique was performed on 5-µm-thick paraffin-embedded sections that were hydrated in graded alcohols and rinsed in a running water bath. Slides were incubated for 15 min at 100C in antigen retrieval buffer, followed by incubation for 5 min in a 3% hydrogen peroxide solution to quench endogenous peroxidase activity. Slides were washed in Tris-buffered saline (TBS) and the sections incubated for 1 hr with a 1:750 dilution of the primary GRP-R antibody. After rinsing with TBS, the slides were incubated with biotinylated IgG for 15 min, rinsed, and then incubated with streptavidin conjugated to horseradish peroxidase (i.e., ABC complex; DAKO) for 15 min. Sections were rinsed and incubated with Liquid DAB Substrate-Chromogen System for 5 min to identify bound antibody. After a final wash in TBS and distilled water, the slides were counterstained with a 50% dilution of Gills' hematoxylin for 1 min, dehydrated in alcohol, and mounted with a coverslip using Permount.
To evaluate the effect of direct conjugation, we eliminated any signal amplification as occurs in using the ABC complex, by using a GRP receptor primary antibody that was directly conjugated to horseradish peroxidase (HRP). In this approach, slides from cells and resected tissue were treated with a 1:800 dilution of the HRP-conjugated GRP-R antibody. The biotinylated anti-rabbit IgG and streptavidin steps were omitted and the bound antibody was directly visualized after a 5-min incubation with Liquid DAB Substrate. Sections were stained using a 50% dilution of Gills' hematoxylin for 1 min, dehydrated in alcohol, and mounted with a coverslip. As before, control tissues were processed simultaneously as the treated slides, with the exception that primary antibody was not applied.
Digital Image Capture
All photomicrographs were obtained using a SPOT RT Digital Scanning Camera from Diagnostic Instruments (Sterling Heights, MI) at x1000 magnification. Files were saved in uncompressed TIFF format so that their sizes ranged between 20 and 25 MB. When a portion of the original image file was selected for further evaluation, the size of the modified file ranged from 1 to 20 MB, depending on the amount of image being evaluated by Q-IHC. This camera captured light with a high signal-to-noise ratio (60 dB), significant temperature stability (±1C per 8-hr period), and minimal dark current (0.15e/p/s at -12C). These specifications indicate that there was minimal background noise over time and in the absence of light.
Quantification of Immunohistochemical Chromogen
The amount of antibody staining was quantified by calculating the mathematical energy (EM) of the image data file. In digital photomicroscopy each color (red, green, and blue) is stored as three separate N1 x N2 pixel matrix files. In 24-bit color, there are 28 or 256 separate shades of red, blue, and green that are represented as discrete variables. Therefore, each color is limited to being assigned a numerical value, or grayscale, between 0 and 255. Consequently, the color contained within a pixel within an image at location (n1,n2) is represented digitally by its three separate grayscale values indicating the amount of red, green, and blue contained therein. As previously described (
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After acquisition with a digital camera, the experimental image file was opened in Photoshop (Adobe; San Jose, CA) using a Macintosh twin 1-GHz G4 workstation (15 gigaflop processor; Apple Computers, Cupertino, CA). The image was then analyzed using two distinct algorithms. The first algorithm exactly recreated our previous approach (
In our new and improved algorithm, the "Magic Wand tool" in Photoshop was used to select the entire histological region of interest contained within the original image file in a manner analogous to that described by others (
The file for the control image is generated similarly. The control slide is acquired from a sequential 5-µm tissue section and treated identically as the experimental slide except that it is not exposed to primary antibody. The same parameters as defined for the experimental slide are used for the control image. As above, the selected region is stored in a new file in TIFF format. This new image is referred to as "CONTROL." Each image is processed by clicking and dragging the icon for the appropriate image onto the icon for our software program TIFFalyzer. The TIFFalyzer program outputs the result for the file EM in a TextEdit file.
The mathematical principles underlying this algorithm have been previously reviewed (
Statistical Analysis
All data reported here are valueless, and are reported as energy units per pixel (eu/pix). Statistical analysis was performed using StatView (Abacus Concepts; Berkeley, CA), with differences between tissue regions evaluated by ANOVA. In all instances, data are expressed as means ± SE.
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Results |
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The primary goal of this study was to determine if our algorithm for Q-IHC could be used to measure peptide hormone receptor number. To assess this, we created a number of cell lines stably transfected with the human GRP-R cDNA. The number of GRP-R binding sites present in each cell line was determined by competitively displacing [125I-Tyr4]-bombesin with increasing concentrations of unlabeled ligand as previously described (
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Using our old algorithm for Q-IHC we were restricted to selecting 100 x 100 pixel regions for evaluation. When this approach was used on the cell lines, a significantly higher coefficient of variation was observed, as might be expected when such small regions were studied (Table 1). In contrast, the coefficient of variance was extremely low when the larger areas studied in our new algorithm, were evaluated (Table 1). In large part, this low coefficient of variance is due to the fact that well over 2 million pixels were subject to evaluation using our new algorithm, whereas only 60,000 pixels were evaluated using our original approach (i.e., 100 x 100 pixels is 104 pixels each for three regions selected from the "EXP" along with three from "CONTROL").
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Irrespective of the algorithm used, we found that the correlation between GRP receptor number and EM was poor when a linear regression (r2=0.415; data not shown) was used. In contrast, a tight correlation between GRP-R number and EM was observed (r2= 0.894) when the modified algorithm was used and the data were fitted logarithmically (Fig 3A). The log-linear relationship between the image grayscale value and EM might be expected as predicted by Beer's Law (
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To evaluate whether reagent saturation could be contributing to the logarithmic portion of the curve as seen in Fig 3A, we created a smaller enzymatic complex by directly conjugating horseradish peroxidase (HRP) to our primary antibody. By so doing we eliminated the need for the avidinbiotin complex in the DAB reaction, for biotinylated anti-rabbit IgG, as well as streptavidin. Therefore, the primary antibody could be directly visualized after incubating with Liquid DAB Substrate (shown in Fig 4B). Using this modified antibody, cell lines expressing low amounts of GRP-R generated negligible amounts of chromogen (data not shown). However, this modified primary antibody allowed us to observe a tight linear relationship (r2=0.974) between cell lines expressing very large amounts of GRP-R and EM (Fig 3D). Conversely, the best fit for the data obtained using the original unmodified primary antibody was generated when only the three cell lines expressing the lowest amounts of GRP-R were studied (r2=0.954) (Fig 3C).
Given our finding that chromogen quantity correlates linearly with receptor number, we proceeded to determine the number of GRP-R binding sites in archived human colon cancers. Because colon cancers are heterogeneously differentiated (
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The nature of tissue processing, including the fixative used, the duration of fixation, and the size of the tissue originally fixed, all potentially alter the immunohistochemical signal. Although a complete evaluation of these parameters is beyond the scope of this article, our archived tissues nevertheless permit some of these issues to be addressed. Specifically, we evaluated inter- and intraspecimen variation for detecting GRP-R using our algorithm for performing Q-IHC. Our eight colon cancers had been resected and fixed between 1985 and 1997 and contained 24 separate regions of distinct differentiation. When these specimens were immunohistochemically processed, the amount of GRP-R chromogen (EM) detected varied only as a function of tumor differentiation, with the low coefficients of variation and standard errors reflecting the minor inter- and intrasample differences (Table 2). Because the protocol for processing tissues undoubtedly varied at our institution over the past 12 years, these findings suggest but do not prove that the method of fixation had minimal affect on altering GRP-R detection when data are generated at the same facility.
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Discussion |
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With the advent of high-resolution digital photomicroscopy, a number of algorithms for quantifying the amount of chromogen generated during immunohistochemistry have been proposed. Previous efforts, however, primarily relied on counting the number of pixels present within an image of defined "color" range. Using this technique, the number of pixels of defined color are simply counted (
These previous approaches suffer from two major limitations. First, any algorithm even partially dependent on pixel counting is inappropriate because such an approach is limited to providing information about the proportion of the image occupied by a particular chromogen and cannot determine the absolute amount of chromogen present. For example, it is conceivable that a particular specimen may have a very small amount of chromogen spread over a large area, whereas another specimen may have a large amount of chromogen concentrated to a particular region (i.e., limited to nuclei). In such cases, pixel counting methods would yield results that are inconsistent with the experimental results. Pixel counting allows the investigator only to determine the number of pixels within a predetermined spectral range relative to the total number of pixels comprising the picture. Pixels have dimension and therefore are unit measures of area. Hence, pixel counting algorithms can only provide information about the proportion of the image within a predefined color range.
Second, previously published techniques are not mathematically valid because they are not based on the basic principles of color theory. For example the "brown" generated using DAB, as perceived by the viewer, is due to the simultaneous receipt of red, green, and blue images of varying grayscale and is influenced by different -coefficients for each of these three primary color channels. Thus color-separated images require a priori knowledge of the exact color spectrum generated by the chromogen. Although it may be evident that the chromogen appears "brown" in a particular experiment, the actual color spectrum of the chromogen spans a wide range of wavelengths. The color spectrum of the chromogen is generally unknown to the observer. Even in the unlikely event that the color spectrum of the chromogen is precisely known to the observer, it is usually not isolated from the color spectrum of the original image specimen. Therefore, identification of the specific color of the chromogen is not sufficient to isolate those pixels in which the chromogen is present. Consequently, the pixels identified and enumerated using such an approach represent pixels containing the specific color spectrum specified by the chromogen (desired) as well as the original image spectrum (not desired). Once again, then, pixel counting algorithms provide semiquantitative information.
We previously described an algorithm for accurately quantifying the amount of color generated during DAB-based immunohistochemistry that was centered on determining the norm of the matrix files encoding a particular image (
Our previous report describing Q-IHC was flawed insofar as it did not demonstrate whether this technique could be used to determine the number of receptors to which the primary antibody is directed, and was limited to providing EM information for extremely small regions within the specimen under consideration (
In this report we also demonstrate that our algorithm can be modified to detect small or large concentrations of receptor as necessary. An intriguing observation is that the ABC complex, commonly used to amplify the signal otherwise generated by small amounts of antigen being detected by the primary antibody, causes EM values to plateau as receptor number (i.e., BMAX) increased beyond 55,000 binding sites/cell (Fig 3A). Based on our direct conjugation studies, this is likely due to the primary antibodyABC complex sterically inhibiting the binding of additional molecules (Fig 4A), but which can be circumvented by specially preparing primary antibody that is conjugated to horseradish peroxidase (Fig 4B). This finding is important because it allows investigators, by modifying their antibody preparation appropriately, to assess receptor number over a 104-fold range.
We used this technique to quantify GRP receptor expression in archived human colon cancer specimens. We originally showed that GRP receptors were highly expressed in well-differentiated human colon cancers but were not expressed by poorly differentiated tumor cells (55,000 GRP receptors per cell. With tumor cell de-differentiation, progressively lower amounts of GRP receptors can be detected (Fig 5).
It could be argued that, because fixation techniques vary within and among laboratories, antigen bioavailability in archived specimens makes our results difficult to interpret. However, we showed little inter- or intraspecimen variability for GRP-R expression in tissues prepared over a 12-year time span (Table 2). At the very least, this observation indicates that one antigen (the GRP-R) at one institution (ours) can be consistently and replicably quantified. Whether or not other antigens at different institutions can be similarly quantified is beyond the scope of this report and awaits further study.
Regardless, nonsubjective quantification of immunohistochemically generated chromogen will only become ever more important. For example, grading HER2/neu immunopositivity in breast cancer specimens has therapeutic implications: patients whose tumors are 2+ immunopositive are eligible for trastuzumab (Herceptin) treatment, whereas those with less staining are not (
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Acknowledgments |
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Supported by an ADHF Student Research Fellowship (to KAM) and by NIH grants DK51168 and DK54777 and a VA Merit Review (to RVB).
Received for publication April 3, 2002; accepted August 23, 2002.
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Literature Cited |
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Benya RV, Kusui T, Pradhan TK, Battey JF, Jensen RT (1995) Expression and characterization of cloned human bombesin receptors. Mol Pharmacol 47:10-20[Abstract]
Carroll RE, Matkowskyj KA, Chakrabarti S, Mcdonald TJ, Benya RV (1999) Aberrant expression of gastrin-releasing peptide and its receptor by well differentiated colon cancers in humans. Am J Physiol 276:G655-665
Carroll RE, Matkowskyj KA, Saunthararajah Y, Sekosan M, Battey JF, Benya RV (2002) Contribution of gastrin-releasing peptide and its receptor to villus development in the murine and human gastrointestinal tract. Mech Dev 113:121-130[Medline]
Carroll RE, Matkowskyj KA, Tretiakova MS, Battey JF, Benya RV (2000) Gastrin-releasing peptide is a mitogen and morphogen in murine colon cancer. Cell Growth Differ 11:385-393
Goldlust EJ, Paczynksi RP, He YY, Hsu CY, Goldberg MP (1996) Automated measurement of infarct size with scanned images of triphenyltetrazolium chloride-stained rat brains. Stroke 27:1657-1662
Jain AK (1989) Fundamentals of Digital Image Processing. Englewood Cliffs, NJ: PrenticeHall
Kohlberger PD, Obermair A, Sliutz G, Heinzl H, Koelbl H, Breitenecker G, Gitsch G et al. (1996) Quantitative immunohistochemistry of factor VIII-related antigen in breast carcinoma. Am J Clin Pathol 105:705-710[Medline]
Kusui T, Benya RV, Battey JF, Jensen RT (1994) Glycosylation of bombesin receptors: characterization, effect on binding, and G protein coupling. Biochemistry 33:12968-12980[Medline]
Kuyatt B, Reidy CA, Hui KY Jordan WH (1993) Quantitation of smooth muscle proliferation in cutured aorta. A color image analysis method for the Macintosh. Anal Quant Cytol Histol 15:83-87[Medline]
Lehr HA, Mankoff DA, Corwin D, Santeursanio G, Gown AM (1997) Application of Photoshop-based image analysis to quantification of hormone receptor expression in breast cancer. J Histochem Cytochem 45:1559-1565
Lehr HA, Van Der Loos CM, Teeling P, Gown AM (1999) Complete chromogen separation and analysis in double immunohistochemical stains using Photoshop-based image analysis. J Histochem Cytochem 47:119-125
Matkowskyj KA, Schonfeld D, Benya RV (2000) Quantitative immunohistochemistry by measuring cumulative signal strength using commercially available software Photoshop and Matlab. J Histochem Cytochem 48:303-311
Muson PJ, Robard D (1980) LIGAND: a versatile computerized approach for characterization of ligand-binding systems. Anal Biochem 107:220-229[Medline]
Nunes RA, Harris LN (2002) The HER2 extracellular domain as a prognostic and predictive factor in breast cancer. Clin Breast Cancer 3:125-135[Medline]
Oda M, Yamashita Y, Nishimura G, Tamura M (1994) Quantitation of absolute concentration change in scattering media by the time-resolved microscopic Beer-Lambert law. Adv Exp Med Biol 345:861-870[Medline]
Paik S, Bryant J, TanChiu E, Romond E, Hiller W, Park K, Brown A et al. (2002) Real-world performance of HER2 testingNational Surgical Adjuvant Breast and Bowel Project experience. J Natl Cancer Inst 94:852-854
Ruifrok AC (1997) Quantification of immunohistochemical staining by color translation and automated thresholding. Anal Quant Cytol Histol 19:107-113[Medline]
Shepherd NA, Saraga E-P, Love SB, Jass JR (1989) Prognostic factors in colonic cancer. Histopathology 14:613-620[Medline]
Spigel DR, Burstein HJ (2002) HER2 overexpressing metastatic breast cancer. Curr Treat Options Oncol 31:63-174
Steinberg SM, Barwick KW, Stablein DM (1986) Importance of tumor pathology and morphology in patients with surgically resected colon cancer. Cancer 58:1340-1345[Medline]