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ONCOLOGY. Vol. 10 No. 6
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DNA Ploidy and Cell Cycle Analysis in Cancer Diagnosis and Prognosis

By

Jeffrey S. Ross, MD

Department of Pathology and Laboratory Medicine, Albany Medical College, Albany, New York | June 1, 1996

This review focuses on the clinical utility and potential value of cell cycle analysis and DNA ploidy interpretation in the diagnosis of human tumors, the application of these techniques to cytologic diagnosis, and their capability for predicting disease outcome in human neoplasia. Methods of cell cycle analysis are considered, and the techniques of flow cytometry and image analysis are described. [ONCOLOGY 10(6):867-890, 1996]

Introduction

During the past 10 years, there has been considerable interest in the application of new technologies to identify human malignancy and predict disease outcome. Markers of cell proliferation and the techniques of flow cytometry and image analysis for the determination of DNA total content in human tumor cells have been at the forefront of these new developments. This review will focus on the clinical utility and potential value of cell cycle analysis and DNA ploidy interpretation in the diagnosis of human tumors, their application to cytologic diagnosis, and their capability for predicting disease outcome in human neoplasia.

The Normal Cell Cycle and DNA Ploidy

Human neoplasms actively synthesizing DNA replicate through a process similar to that of normal cells known as the cell cycle. Cells in the resting diploid state (G0) phase contain 7.14 picograms of DNA and enter the cell cycle as gap 1 (G1) cells. During the synthesis phase (S phase), cells increase their DNA content continuously from 7.14 to 14.28 pg/cell until they reach the tetraploid state with twice the diploid DNA content. The second gap (G2 phase) refers to the tetraploid, premitotic fraction of cells that undergo mitosis in the M phase to generate two diploid G0 cells, which may reenter the cell cycle or persist in the resting state. A DNA index of 1.0 corresponds to a 2N or 46 chromosome number characteristic of G0 and G1 cells. The G2 and M cells feature a 2.0 DNA index that corresponds to a 4N chromosome count of 92.

The distribution of a population of cells within the cell cycle generates a pattern known as a histogram and represents DNA ploidy. A DNA histogram is defined as diploid when the predominant or G0/G1 peak is equal to the G0/G1 peak of a known diploid reference cell population and the S and G2M phase contents are relatively low (Figure 1). In normal tissues and most low-grade or slowly proliferating neoplasms, approximately 85% of the cell population forms the G0/G1 peak and 15% of the cells are in the S phase and G2 and M phases.

DNA aneuploidy is defined as a DNA content of the G0/G1 peak of a cell population that varies significantly from the mean peak of the known diploid reference cell population. The DNA index of an aneuploid cell population may rarely be < 1.0 (hypodiploid) or > 1.0 (hyperdiploid). Aneuploid cell populations with a DNA index near 2.0 must be differentiated from diploid cell populations with significant G2M phases. Table 1 summarizes the terminology used for DNA ploidy definitions.

Techniques for Measuring DNA Content

Flow cytometry is a technique that features simultaneous measurement of multiple characteristics of single cells stained with excitable dyes moving in a fluid stream exposed to laser beam light. Computerized analysis of light scattering and cell fluorescence produces data analyzed by the on-board computer, resulting in the production of a histogram. In addition to the well-described immunophenotyping functions, when cells are stained with the dye propidium iodide, fluorescence is proportional to the nuclear DNA content. Requiring a cell suspension of individual cells, when solid human neoplasms are analyzed by flow cytometry, the tissue must be disaggregated by mechanical or enzymatic techniques.

Computer-based image analysis applies digital technology to quantitative measurements performed on static cytopathologic and histopathologic specimens. In contrast to flow cytometry, image analysis features simultaneous morphologic assessment of cells measured for DNA content by video imaging of nuclear optical density after Feulgen staining. A comparison of the histogram generated from the computer reconstruction of the digitized images of a population of cells measured by image analysis with that determined from a flow of similar cells through a flow cytometer is shown in Figure 1.

Technical Issues in DNA Ploidy Measurements

Various technical issues impact on the measurement of total DNA content in human neoplasms. Specimen volume is important; image analysis determination is available for as few as 100 cells, whereas flow cytometry requires a minimum of 5,000 to 10,000 cells. Specimens must be stored in a standard fashion and fixed in 10% neutral buffered formalin, the optimal fixative for the DNA ploidy study.

As mentioned above, flow cytometry requires tissue disaggregation, which is best performed by direct needle aspiration or mechanical techniques on fresh tissue. Retrospective flow cytometric studies utilizing enzymatic disaggregation of tissue can produce significant errors in DNA ploidy measurement.

The tissue section image analysis method has become a preferred technique for small needle biopsies of such organs as the prostate and breast. It should be emphasized that heterogeneity of DNA content is common in many types of human neoplasia, and sampling issues can be significant when searching for aneuploid populations in a large neoplasm. The proper use of diploid controls and standards, the expertise of the instrument operator, and the experience of the histogram interpreter are all critical issues in creating high standards of performance for DNA content analysis.

Flow Cytometry vs Image Analysis

Major reviews of DNA content analysis have highlighted the relative advantages and disadvantages of both technologies [1-5]. These comparative studies have highlighted an excellent overall performance of both techniques, with approximately 95% of samples showing similar diploid or aneuploid histograms when measured by either image analysis or flow cytometry (Figure 2) [6]. The selective nature of the image analysis technique has led workers to conclude that it is slightly more sensitive than flow cytometry [7]. A comparison of the two methods, including their relative advantages and disadvantages for the determination of DNA content in human neoplasms, is included in Table 2.

Determination of Cell Proliferation Rate

The earliest methods of estimating cell proliferation in human neoplasia were based on mitosis counting. During the past 10 years, various newer methods have been applied to determining the cell proliferation rate, or percentage of cells actively synthesizing DNA (Table 3).

In addition to determining DNA ploidy, flow cytometry and image analysis also provide estimates of the percentage of cells in the S phase by histogram evaluation and mathematic modeling. Although flow cytometry is more accurate than image analysis for this purpose, both techniques have serious drawbacks with regard to the accuracy and reproducibility of S-phase determinations.

Mitotic figure counting is the easiest method to perform. However, lack of reproducibility and standardization are important problems with this method. Human tumors that currently feature mitosis counting in the standard pathology report include breast cancer, smooth muscle sarcoma, and malignant melanoma.

Tritiated Thymidine Labeling--This method directly measures the S phase of proliferating cells but requires viable fresh tissue incubated with radioactive thymidine and interpreted after autoradiography. It also suffers from interobserver variation and is generally cumbersome and rarely used clinically.

Bromodeoxyuridine assay uses a monoclonal antibody that measures cells in S phase that incorporate the bromodeoxyuridine thymidine analog. Although considered an accurate proliferation marker when measured by routine immunohistochemistry or flow cytometric technique, this nonradioactive method is not generally utilized in most laboratories.

Ki-67 Immunostaining--The antibody Ki-67 was raised against a Hodgkin's disease cell line and detects an antigen in the nucleus associated with cell proliferation [8]. Ki-67 immunostaining has been applied to a wide variety of human neoplasms and has been judged to be superior to bromodeoxyuridine assays and tritiated thymidine uptake in the assessment of cell proliferation in human neoplasms (Figure 3) [9].

The original Ki-67 antibody could be utilized only in fresh and frozen tissues. The newer MIB-1 monoclonal antibody developed through recombinant techniques is reactive to a selective part of the Ki-67 antigen and can be utilized in archival formalin-fixed paraffin(Drug information on paraffin)-embedded specimens. Comparative studies indicate that the MIB-1 marker accurately reflects an estimate of the S-phase fraction [10]. Currently, the MIB-1 antibody is considered the most easy-to-read and widely applicable cell cycle marker available.

Proliferating cell nuclear antigen (PCNA), also known as cyclin, is a nonhistome nuclear protein cofactor for DNA polymerase-delta. Although this marker was originally believed to be an ideal cell proliferation label that could be applied to archival specimens, more recent studies suggest that it is less sensitive than Ki-67 [11] and subject to significantly variable results when specimens are exposed to microwave antigen retrieval procedures [12].

In addition to this marker, immunoreagents for the detection of cyclin A and cyclin D have recently become available. These may prove to be of substantial interest as potential indicators of aggressive neoplasms.

DNA Polymerase-Alpha is a cell cycle-related enzyme detected by monoclonal antibodies that requires fresh-frozen tissue sections and may be relatively insensitive.

p105 detects a nuclear antigenic epitope involved with RNA synthesis. In early studies, p105 has shown promise as a potential marker of aggressive malignant lymphomas and solid tumors.

Nucleolar organizer regions (NORs) are loops of DNA that encode ribosomal RNA production [13,14]. Nucleolar organizer region staining is accomplished by a silver impregnation technique that can be performed on paraffin sections; this technique has correlated with cell proliferation in a wide variety of human neoplasms.

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