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DNA Ploidy and Cell Cycle Analysis in Cancer Diagnosis
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DNA Ploidy and Cell Cycle Analysis in Cancer Diagnosis and
Prognosis
Review Article [1] | June 01, 1996
By Jeffrey S. Ross, MD [2]
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
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
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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
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Ki-67 antigen and can be utilized in archival formalin-fixed 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.
Cancer Diagnosis and Diagnostic Cytology
In general, the use of DNA ploidy status as a stand-alone diagnostic signal of malignancy has been
unsuccessful. However, in a variety of body sites and human tissue samples, DNA content and cell
cycle analysis have achieved value in augmenting the standard diagnostic process.
The introduction of flow cytometric determination of DNA content to bladder washing and urine
cytology represented the first major application of this technique in daily diagnostic pathology.
Originally conceived as an adjunct for the diagnosis of low-grade transitional-cell carcinoma in
cytology specimens, flow cytometry ultimately proved to be no more sensitive or specific for this
diagnosis than conventional cytologic methods [15]. DNA ploidy has shown promise in differentiating
reactive atypia associated with intravesical chemotherapy from recurrent transitional-cell carcinoma
(Figure 4) [16]. The ability of aneuploid DNA content to predict adverse outcome in bladder cancer is
discussed below.
DNA ploidy analysis has not proven clinicall useful in the interpretation of Pap smears, in that it
cannot differentiate among the different grades of cervical intraepithelial neoplasia; cannot predict
regression, persistence, or regression of these lesions; and cannot specifically identify invasive
carcinoma [17].
DNA analysis can complement conventional cytology in the diagnosis of lung cancer, with aneuploidy
or high S-phase fractions serving as an indicator of malignancy. However, there has been little
clinical use of the technique for lung cancer screening [18].
DNA content analysis has achieved variable success in augmenting routine cytologic diagnosis of
malignancy in serous effusion specimens. Some studies have indicated high false-negative and
false-positive rates [19], whereas others have found DNA ploidy determination to be a useful
adjuvant technique [20]. It must be emphasized that certain diploid primary tumors, particularly
tumors of the breast, colon, and prostate, may feature diploid metastases to body cavities; this
provides an explanation for so-called false-negative DNA ploidy results (Figure 5).
Ploidy determination is a sensitive measurement of malignancy in spinal fluid; aneuploid populations
are highly specific for metastatic lesions [21]. Small specimen sample size generally limits this
application, however.
Application of DNA ploidy to the diagnosis of malignancy in fine-needle aspiration biopsy cytology
specimens has been limited by the frequent finding of aneuploidy in nonmalignant and even
nonneoplastic conditions (Table 4) [22-24]. DNA ploidy and cell cycle analysis has, however, been
useful in predicting outcome of malignant tumors diagnosed by conventional methods and assessed
for DNA content on fine-needle aspiration specimens.
DNA ploidy analysis has proved valuable in the confirmation of severe dysplasia and risk of invasive
malignancy in borderline biopsies of Barrett's esophagus and gastric ulcers (Figure 6) [25-27]. Cell
cycle analysis using the MIB-1 antibody has also been useful in differentiating dysplasia grades in
Barrett's esophagus [28]. DNA analysis has been less successful in predicting the presence of
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dysplasia in chronic ulcerative colitis [29].
Prediction of Tumor Aggressiveness and Clinical Outcome
The rest of this review will consider cell proliferation and S-phase measurements as prognostic
factors in human neoplasia, according to tumor type.
Breast Cancer--A substantial number of studies designed to test whether DNA aneuploid content
predicts disease outcome in breast cancer have
been performed during the past 8 years (Table 5). The results of these studies have been mixed:
Some investigators have found aneuploidy in breast cancer to be an independent predictor of
disease relapse and short survival on multivariate analysis, whereas others have found either no
independent correlation of ploidy status with disease outcome or, in rare instances, a complete lack
of correlation [30-45].
With regard to cell proliferation and S-phase measurements in breast cancer, a larger number of
studies have correlated disease outcome with high proliferative compartments on univariate
analysis. However, there has been a similar lack of consensus as to the independent status of this
predictor on multivariate analysis [38,46-50] (Figure 7).
Gynecologic Cancers--DNA aneuploidy has been uniformly associated with high grade and stage in
endometrial cancer. Patients with diploid tumors have a better prognosis than those with aneuploid
lesions [51-52]. For uterine sarcomas, DNA ploidy patterns have correlated with tumor grade and
size, mitotic index, and general overall survival [53].
Similar to endometrial cancer, DNA ploidy patterns have been predictive of disease outcome in
ovarian cancer and have achieved independent status on multivariate analysis as a predictor of
prognosis [54]. Large tumors may show heterogeneous ploidy patterns, which may be indicative of
disease aggressiveness in itself [55]. DNA content analysis has not been successful in predicting
malignancy in ovarian, sex cord, and stromal tumors [56].
Genitourinary Tract Cancer--Results of studies assessing DNA aneuploidy in genitourinary tract
cancers have varied. In general, ploidy patterns have shown a high predictive value for disease
outcome in cervical cancer [57] and less predictive value in vulvar, vaginal, and penile squamous
cell carcinoma [58,59].
Germ-Cell and Trophoblastic Tumors--DNA ploidy analysis has not proved valuable in the
prediction of disease outcome in germ-cell tumors. Although adult benign teratomas are generally
diploid, virtually all aggressive germ-cell tumors, including germinomas, embryonal carcinomas, and
endodermal sinus tumors, are uniformly aneuploid [60]. For gestational trophoblastic neoplasia, a
major clinical use of DNA analysis involves confirmation of the presence of partial hydatidiform mole
by the determination of a triploid DNA content histogram indicating a DNA index of 1.5 and the
fertilization of one ovum by two spermatozoa (Figure 8) [61].
Prostate Cancer--Virtually all of the major retrospective studies utilizing flow cytometry and image
analysis have confirmed the significant predictive value of DNA aneuploidy for outcome in prostatic
adenocarcinoma (Table 6) [62-79]. Recent studies have focused on applications of DNA ploidy to the
original prostate cancer needle biopsy; results of these studies have shown an excellent correlation
with ploidy patterns on radical prostatectomy specimens and independent predictive significance for
extraprostatic disease, distant metastasis, and disease recurrence [77]. Needle-biopsy ploidy status
(Figure 9) ultimately may be combined with tumor grade and other prognostic markers to stratify
patients into treatment protocols.
Bladder and Kidney Cancers--Although unsuccessful for the identification of low-grade
transitional-cell carcinoma on urine cytology due to its uniform diploid nature, the presence of
aneuploidy in urine cytology or bladder biopsy specimens indicates high risk for muscle-invasive
disease and adverse patient outcome [80-82]. Aggressive bladder cancers, in addition to featuring
high nuclear grade and aneuploid DNA content, have also been recently linked to mutation of p53, as
well as to various other changes in growth factors and invasion and metastasis markers [83] (Table 7
). In a recent study, Ki-67 and PCNA immunostaining did not independently predict disease
aggressiveness [84].
Early retrospective studies of flow cytometry and more recent prospective studies have shown DNA
ploidy pattern to have independent significance for outcome in renal-cell carcinoma [85]. Ploidy
findings appear significant for clear-cell renal carcinoma, and also tend to separate granular-cell
renal carcinomas, which may be aneuploid, from benign oncocytomas of the kidney, which are
uniformly diploid [86].
Upper Aerodigestive Tract Tumors--Early studies of DNA content by flow cytometry in squamous
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cell carcinomas of the head and neck showed variable results, with some studies indicating a
favorable and others an unfavorable implication of aneuploidy [87,88]. More recently, aneuploidy has
been associated with disease progression in these tumors [89,90].
DNA analysis of salivary gland tumors has received limited attention. Noteworthy is the finding that,
although aneuploidy may be seen in benign pleomorphic adenomas, its presence indicates a higher
rate of recurrence after surgery and subsequent malignant progression [91].
GI Cancers--Although earlier studies failed to demonstrate a significant correlation between ploidy
patterns and outcome in esophageal cancer, most of the more recent studies have shown both
univariate and multivariate statistical significance for the presence of aneu-ploidy and disease
outcome [92-94].
For gastric adenocarcinoma, the majority of studies have correlated ploidy patterns with disease
outcome on univariate analysis but have been less successful in demonstrating independent status
on multivariate analysis [95-97]. Ploidy patterns have predicted prognosis in gastric cancer and have
correlated with proliferation rates and growth factor expression [98].
For gastrointestinal (GI) stromal tumors, DNA ploidy has been found to predict tumor grade and was
an independent indicator of poor prognosis [99-101].
DNA content analysis in colorectal adenocarcinoma has generally correlated with disease outcome,
but the results of numerous earlier studies have not been unanimous. Similar to esophageal and
gastric cancer, ploidy patterns in colorectal carcinoma have nearly uniformly shown significance in
the prediction of disease outcome on univariate analysis but have not always achieved independent
status on multivariate analysis [102-105]. DNA aneuploidy has recently been described in normal
colonic mucosa in patients with colorectal cancer, suggesting that abnormal DNA content may be an
indicator of early transformation in the large intestine [106]. In diploid colorectal cancer cases,
elevation of the S-phase percentage has been associated with higher stage disease and decreased
patient survival (Figure 10) [102].
Although DNA aneuploidy is associated with significantly shortened patient survival in pancreatic
carcinoma, the clinical utility of ploidy patterns is limited due to the disease's virtually universal poor
outcome. In one study, patients with diploid pancreatic carcinoma had a mean survival of 17 months,
as compared with just 8 months for patients with aneuploid tumors [107].
Although inconsistent results have been published, most studies indicate that aneuploidy in primary
hepatocellular carcinoma is predictive of adverse outcome on univariate and multivariate analysis
[108-110]. Although the premalignant potential of liver cell dysplasia has been under investigation,
one recent study indicated a significant frequency of aneuploidy in dysplastic liver cells, which may
further support the role of dysplasia in the evolution of hepatocellular carcinoma [111]. However,
nondiploid patterns may be seen in chronic hepatitis and cirrhosis, possibly as the result of tissue
regeneration. Therefore, aneuploidy cannot be used to specifically identify malignant hepatocytes on
liver biopsies and aspiration cytologies [112,113].
Lung Tumors--For non-small-cell lung cancer, the association of DNA ploidy pattern with disease
outcome has been somewhat variable, although most studies indicate adverse outcome for
aneuploidy on univariate analysis [114-116]. For undifferentiated small-cell carcinoma, DNA analysis
has been of limited use given the nearly uniform finding of aneuploidy in these tumors (Figure 11)
[117]. For malignant mesothelioma, DNA analysis has similarly been of limited value in diagnosis and
the prediction of prognosis [118].
Bone and Soft-Tissue Tumors--DNA ploidy determination has generally correlated with survival
rates in bone and soft-tissue sarcomas [119]. In osteosarcoma, for example, near-diploid histograms
are associated with favorable prognosis and response to therapy (Figure 12) [120]. In general, ploidy
analysis has correlated with tumor grade for sarcomas, with diploid lesions denoting low histologic
grade and localized disease, and aneuploid tumors indicating high-grade disease and increased risk
of recurrence and distant metastasis. DNA ploidy and cell cycle analysis cannot, however,
differentiate between malignant and benign soft-tissue tumors, in that benign proliferations and
nonneoplastic disorders, such as fibromatosis and wound healing, can feature aneuploid histograms.
CNS Tumors--For gliomas, the results of DNA content analysis as a prognostic indicator are similar
to the results for pancreatic cancer; namely, aneuploid tumors have an extremely short survival of <
1 year and diploid tumors have a survival ranging from 2 to 3 years in some cases [121]. In
meningiomas, DNA ploidy status does not appear to correlate with recurrence rate and risk of
metastasis, although proliferation index may be helpful for determining aggressiveness and,
possibly, for planning adjuvant therapy [122,123].
Endocrine Tumors--DNA content analysis has not proved successful in predicting outcome for
papillary and follicular thyroid carcinomas. Aneuploidy may be seen in encapsulated thyroid
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adenomas, and both papillary and follicular neoplasms with metastatic foci may be diploid [124,125].
On occasion, high DNA index has been associated with progressive disease and death in
differentiated thyroid cancer [126]. Nonetheless, DNA content analysis has been ineffective in the
diagnosis of differentiated thyroid cancer on fine-needle aspiration specimens (Figure 13).
For adrenocortical tumors, aneu-ploidy may be identified in encapsulated benign lesions, and thus,
cannot be utilized to diagnose malignancy [127]. Similarly, for parathyroid and pancreatic islet-cell
tumors, aneuploidy may be identified in encapsulated benign lesions. Thus, ploidy status cannot be
utilized to predict outcome in patients with these tumors [128,129]. Likewise, DNA aneuploidy is
common in carcinoid tumors and is not useful in predicting metastasis or survival time [130].
Interestingly, for pheochromocytomas and paragangliomas, DNA ploidy pattern may be an important
independent prognostic variable [131]. For oncocytic neoplasms of the salivary gland, kidney, and
thyroid, diploid DNA content has generally been associated with a benign clinical course [132]. On
occasion, aneuploidy in these tumors has been associated with the potential for invasion and
metastasis.
Malignant Melanoma--Although surgical pathology microstaging methods have generally been
reliable predictors of outcome in malignant melanoma, a significant percentage of cases may fall
into intermediate-thickness level III lesions, which are of uncertain clinical potential. DNA ploidy
assessment has proved valuable in differentiating among this latter group, in that diploid
intermediate-thickness lesions tend to behave like thin lesions and aneuploid lesions act similar to
more clinically aggressive thick tumors [133]. Aneuploidy cannot, however, be utilized as a
diagnostic tool to differentiate atypical pigmented lesions from melanoma because benign
melanocytic nevi occasionally exhibit aneuploid DNA patterns.
Hematopoietic Malignancies--Table 8 shows DNA ploidy and cell cycle analysis distribution in
non-Hodgkin's lymphoma according to the Working Formulation. In general, the prognostic
significance of DNA ploidy patterns in this disease has been variable, and S-phase calculations or
direct cell cycle proliferation measurements have proved more valuable clinically [134,135]. In
leukemia, limited data are available concerning ploidy status and disease outcome. Similarly, there
is little information to suggest that ploidy status predicts disease outcome in Hodgkin's disease.
Pediatric Neoplasms--In pediatric round cell neoplasms, DNA aneuploidy has generally been
associated with an improvement rather than a diminution in survival. Similarly, for neuroblastoma,
abnormal DNA content has been associated with improved response to therapy and significantly
increased survival (Figure 14) [136,137]. Studies of medulloblastoma also have shown an association
of aneuploidy with favorable clinical outcome [138], although recent studies have failed to confirm
the improved survival associated with abnormal DNA content [139].
Summary
Table 9 summarizes the diagnostic and prognostic value of DNA ploidy and cell cycle analysis in a
variety of human neoplasms. This summary highlights the substantial clinical value of DNA ploidy
and cell cycle analysis in the diagnosis of cancer and, more importantly, in the prediction of
outcome.
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