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Kufe DW, Pollock RE, Weichselbaum RR, et al., editors. Holland-Frei Cancer Medicine. 6th edition. Hamilton (ON): BC Decker; 2003.

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Holland-Frei Cancer Medicine. 6th edition.

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Cell Proliferation

, MD, , MD, , MD, and , MD.

Mitotic Cycle: Percentage of Labeled Mitoses Curves

Mitosis, or cell division, is the basic biologic process that results in an increase in somatic cell numbers over time. The term growth applies to the increasing volume of a cellular population and is measured in units of volume (eg, cubic centimeters) or weight (eg, milligrams). Growth is largely the consequence of increasing numbers of cells but also can be influenced by the increasing size of the individual cells, edema, changes in the context of the extracellular matrix, hemorrhage, and infiltration by host cells, such as leukocytes. The term proliferation specifically applies to an increase in the number of cells, which is measured as cell number as a function of time. Cells divide by progressing through a sequence of steps that are collectively called the mitotic cycle. Other names for the mitotic cycle are the proliferative cycle, the generation cycle, and the cell cycle.

Classic autoradiographic techniques were first used to divide the cell cycle into four phases.1,2 The terms for these phases, described below, are still used today, although the method of assessment is now often biochemical or biophysical, not biologic as in the original usage.

The two key events in mitosis are the synthesis of DNA, which occurs mostly in the S-phase or S (for synthesis), and the actual division of the parent cell into two daughters during the M-phase or M (for mitosis). The M-phase is typified micromorphologically by the metaphase plate. The time gap between cell division and DNA synthesis is gap number 1, or G1. The time gap between DNA synthesis and cell division is gap number 2, or G2. Although the term mitosis is often used to refer to the M-phase, the adjective mitotic properly refers to all cells that are engaged in any portion of the whole process of self-replication. This whole process includes the submicroscopic events (G1, S, G2) that precede the M-phase, as well as the M-phase itself. This usage has the advantage of distinguishing cells that provide evidence of their intention to divide, from those cells, called G0 cells, that do not express that intention.

Cell cycle phases are best understood in the context of their means of quantification. The venerable mitotic index, the counting of metaphase figures in histologic slides, is of real scientific value. However, this is very labor intensive, so it has, unfortunately, decreased in popularity.3 An important variant of the mitotic index, also infrequently applied, is the stathmokinetic technique, in which a mitotic poison is applied prior to counting.4

Of all the older techniques, however, the most important, by far, is the thymidine labeling index (TLI).5 Here viable cells are exposed briefly in vitro to a radiolabeled precursor of DNA. The most common thymidine label is tritium (3H), but carbon 14 (14C) has also been used. The percentage of tumor cells with autoradiographic grains over their nuclei estimates the fraction of cells that were in S-phase during the period of thymidine exposure. Newer variants use monoclonal antibodies directed against proteins expressed during proliferation (see below) to allow mitotic (ie, cycling) cells to be identified visually.6–8 In all these techniques, the microanatomy of the specimen is preserved so that the microscopist can actually know that the cell being counted is one of interest.

The highest refinement of the TLI is the percentage of labeled mitoses (PLM) curve. This technique counts, as a function of time after exposure, the number of M-phases that contain radioactive label. This measures the cells currently in M-phase that had been in S-phase during the exposure to radioisotope. The PLM method formerly was used to study human disease, but this application has been prohibited because it requires whole-body exposure to a long-lived radioisotope. In spite of its limitations, the technique has been of fundamental importance in the field of cytokinetics because it directly estimates the durations of phases of the cell cycle. Its theory is illustrated schematically in Figure 43-1. In Figure 43-1A, tritiated thymidine is administered as a pulse to label cells in the S-phase. As time passes (Figure 43-1B), the labeled cells move beyond S and transverse G2. At this moment, no M-phase cells contain label, so the PLM is zero. Over the next short interval of time (Figure 43-1C) labeled cells enter the M-phase. The PLM goes from 0% to 100%, as shown in the graph at the bottom of Figure 43-1. The time elapsed from the pulse labeling to the achievement of 100% PLM is equivalent to the sum of the durations of G2 and M. The time required for the PLM to drop again to zero is the same as the time required for all the cells labeled during the S-phase to pass through their M-phase. This is the same as the duration of S-phase (Figure 43-1D). If we follow the population through a second generation, the PLM will again rise from 0% to 100% (Figure 43-1E). Figures 43-1C and 43-1E are the same except for a translocation in time, which is equivalent to one full cell cycle.

Figure 43-1. The mitotic cycle and percent labeled mitoses curve.

Figure 43-1

The mitotic cycle and percent labeled mitoses curve.

Actual PLM curves would be as sharp and as precise as is this hypothetic example were cycle lengths homogeneous and invariable, but, unfortunately, they are neither. Another complication is that because of the pharmacokinetics of radioisotopes and other technical considerations, it is rare for label ever to be present in all M-phase cells. Thus, sophisticated mathematic methods must be used to estimate phase lengths by model fitting.9 In spite of these limitations, however, almost everything that we now know concerning cycle dynamics has been learned from the PLM method.

It has been observed in animal models that the labeling index (LI) decreases with increasing tumor size, whether measured in cubic millimeters or milligrams.10,11 This is thought to be the major cause of the slowing of growth as a tumor (or a normal tissue, for that matter) gets larger. The fact the growth rate is a function of tissue size has major consequences, which are discussed in a subsequent section. The rate of decrease is slower for malignant than benign tissues, as demonstrated by the maintenance of high labeling indexes in large and metastatic cancers, illustrated below using specific examples.

The drop in LI, slow as it is in malignancy, is not irregular. In fact, curve fitting has shown that the logarithm of the LI is linear in the logarithm of the tumor size. This may be related to the histologic architecture of the cancer, which is lost to varying degrees, compared with the tissue of origin. Structure may be quantified as a fractal (or mass) dimension.12 Less structure (more anaplasia) means that the fractal dimension is close to 3. Total loss of structure (complete anaplasia) would mean that the fractal dimension equals 3. The rate of decline of the LI is directly related to the fractal dimension of the entire tissue, with more anaplastic tissues showing a slower rate of decline than the highly structured normal tissues from which they originated. Total lack of structure (complete anaplasia, which almost never occurs in nature), would be associated with a fractal dimension of 3 and pure exponential growth, with no decline in the LI. The link between fractal dimension and LI might be that the cell number (N) relates to the diameter of the tissue (L) raised to the fractal dimension (D) power, while the volume of the tissue (V) is related to L3. Hence, N/V is related to V raised to the (D-3)/3 power, which decreases as V gets larger. If LI were proportional to N/V, as would be the case were the probability of mitosis determined by the concentration of a soluble growth factor produced by the cells, this might explain the relationship between LI and tumor size.13 Also to be considered, however, is the possibility that the cell loss (or apoptotic) fraction AF might bear a power-function relationship with V. Should LI/V drop at a faster rate than AF/V, the rates of cell production and loss would eventually converge at a plateau value of V. These and related concepts are discussed below in the section on the Gompertzian growth model.

Cell Cycle Phases and DNA Content

At its birth, a normal mammalian somatic cell contains a diploid number of chromosomes, and hence diploid (2N) DNA content. Following a successful cell division, the new cell generally experiences a time gap before it begins to engage in measurable DNA synthesis. Some very primitive or embryonic cells enter DNA synthesis immediately, but these are exceptions to the usual pattern. We have termed this gap G1, but a new cell is properly called G1 only if it exhibits the biologic intention of entering the S-phase. Should the cell never actually progress to the point of starting DNA synthesis, it would properly be classified as G0. Since both G0 and G1 cells are diploid in DNA content, we avoid the presumption of prescience by considering the two phases together. In performing this grouping, we recognize that the lengths of the G0-G1 phases are highly variable, fitting a log-normal probability distribution that is skewed markedly to the right, that is, toward longer times. Since the cells on the far right end of the distribution will never divide within the life span of the host, they are the G0 cells.

This statistical distinction between G0 and G1 has biologic correlates. Between their M- and S-phases, cells prepare to enter the S-phase by progressing through defined stages that are dependent on protein synthesis.14 These stages are regulated enzymatically by processes partially sensitive to such extracellular influences as growth factors and the supply of nutrients. Cancer cells may be less dependent on these external signals and conditions than are normal cells, which may account for their ability to grow in suspension cultures without extracellular matrix. This ability may be related to the activity of oncogenes or to the deregulation of suppressor genes, such as p53 or the retinoblastoma gene. The potency of genes like simian virus 40 large T antigen (SV40LT) to transform cells is particularly relevant to this point.15,16 Recently, it has been observed that normal human cells can be transformed by the insertion of three genes—SV40LT, hTERT (which encodes the catalytic subunit of telomerase), and an oncogenic ras—all of which convey some element of growth factor autonomy.17

Cells in G1 have already progressed beyond several preliminary steps to prepare for the S-phase, whereas G0 cells need further time to complete early synthetic events so that they can enter the G1-phase. These differences can be exploited in the laboratory to discriminate G0 from G1 cells. G0 cells tend to be smaller, and have lower RNA and protein contents than do G1 cells, as well as specific, characteristic messenger RNAs and proteins.18–20 For example, the Ki-67 antigen is present in all mitotic cells (G1, S, G2, M), but is not found in G0 cells.8 Also, G0 cells do not metabolize the cationic dye rhodamine, which is thought, but has not been proven, to reflect the cells' relatively low mitochondrial activity.21,22 However, G0 cells, in spite of their distinctive biologic characteristics, can be stimulated by external influences to proceed through the sequence of events that leads them into the G1-phase and eventually into the S-phase. This phenomenon is called recruitment.

After the M-phase, but before DNA synthesis accelerates, the cell either commits to proliferate by entering the S-phase or stops dividing by differentiating into a nonmitotic cell. The ratio G1/(G0 1 G1) at any one time defines the proportion of cells entering their next S-phase. A particular restriction point at the G1:S interface, now called Start, may be regulated by the p34cdc2 protein, which may couple with different cyclin proteins (whose levels vary within the cell cycle) to permit, alternately, a cell's entry into the S- or its entry into the M-phase.23 Normally, the M-phase cannot take place unless the S-phase has been completed, and the S-phase cannot take place unless the M-phase has been completed. Abnormalities in this system could result in an unblocking of the normal “block to re-replication” which prevents parts of the genome from being replicated more than once during a single S-phase.24 Such abnormalities are one possible etiology for aberrant levels of DNA per neoplastic cell (see below). Once the cell enters the S-phase, its progression through the rest of the cycle is largely self-regulated.25 This regulation involves direct controls, in which a step must be completed before the next step commences, as well as indirect feedback loops.26

The S-phase, lasting between 12 and 24 hours in mammalian cells, is generally much less variable than the G0-G1 phase. Specific regions of chromosomes replicate at specific times, clusters of replication units initiating synchronously, with the whole complex process transpiring in a highly orchestrated manner.27 During the S-phase, a cell's DNA content should increase from 2N to 4N. A very small number of S0 cells may actually stop synthesizing DNA before completing the S-phase.28 Their ultimate fate is unclear, although it is likely that some can resume the S-phase, whereas others are prevented from proceeding by intrinsic blocks in their self-regulation. Cells completing the S-phase enter the second gap, marked by a dramatic diminution in the rate of DNA synthesis. G2 usually lasts for about 3 hours in mammalian cells, ending when the M phase begins. Rarely, a cell can rest in the G2-phase and not proceed into actual cell division.29

The initiation of the M-phase may depend on the same molecular trigger as Start, but in a complex interplay with different cyclins and other factors, which are beyond the scope of this chapter.30 The M-phase is composed of several parts. In prophase, the cell assumes the shape of a sphere.31 The microtubules and microfilaments of the cell's cytoskeleton rearrange, the Golgi apparatus disperses into small vesicles, protein synthesis drops, and the dispersed chromosomes (duplicated during the S-phase) cease metabolic activity and then condense into transportable units.32 During prometaphase, these units orient themselves linearly toward opposite ends of the cell and move to the midplane to form the metaphase plate. In anaphase, spindle fibers attached to kinetochores on each chromosome guide them toward centrosomes in opposite ends of the cell. In telophase, the nuclei reform, the chromosomes de-condense, and the cell normally divides into two approximately equal halves, one new nucleus per daughter cell. The M-phase is the least variable in length, lasting about 1 hour in most mammalian cells.

The total duration of the cell cycle varies considerably, but the average in human cancer is between 2 and 4 days. This is in marked contrast with the cell cycle in Drosophila, which may take minutes, or with that of mammalian embryos, which may take hours. Some normal cells, such as some human neurons, may never divide at all. Cancer is not always a disease of rapid proliferation, but it is always one of persistent proliferation. If a large number of cancer cells are dividing, even if they are dividing with deliberate speed, they will produce many offspring, which, by continuing to divide, will inevitably lead to an abnormal accumulation over time. For a given tissue, malignant or benign, the length of the cell cycle in vivo is fairly constant in spite of variations in the number of cycling cells in that population. However, subtle changes in cycle kinetics have been seen in cancers in laboratory animals that are allowed to grow large and phase lengths can shift significantly as cells are cultured in vitro.33–35 This is in addition to changes in the LI as tumor growth, discussed above.

Flow Cytometry

The variation in cellular DNA content during the proliferative cycle can be exploited analytically by a collection of automated methods called flow cytometry. Visual procedures, such as mitotic index, TLI, and static Ki-67 staining, are slow, laborious, and subjective. These negative features may change with technologic advances in assessing cellularity on slides and in the automated counting of visually distinctive cells.36,37 At present, however, flow methods are the most rapid and quantitative.38 The major disadvantage of such techniques as flow cytometry, in which the cells being analyzed are not visualized, is that normal stromal cells, normal blood cells, and tumor cells of various types and degrees of oxygenation are all counted together. Another disadvantage is that reliable flow cytometry requires meticulous technique and hence constant attention to quality control. Nevertheless, flow cytometry has become the most widely applied method of cytokinetic assessment in the modern clinic. Hence, it has been the most productive in terms of accumulation of literature.

In fluorescence-activated cell sorting, a suspension of individual cells is automatically counted by being allocated into bins by DNA content, RNA content, cell size, antibody label, or combinations of such factors.39,40 This can be performed on fresh tissue—leukemias, tumor cells in effusions or ascites, enzymatically dispersed solid tumors—or on cells recovered from paraffin-embedded specimens.41 Enzymatic methods of dispersing fresh or fixed solid tumor specimens have been shown to produce high single-cell yields, representative of the tissue as a whole, with low degrees of contamination by cellular debris.42

Flow cytometry can be used to measure RNA per cell, which, as mentioned above, is helpful in distinguishing G0 from G1 cells. Various techniques of tagging cells for the purpose of sorting are being employed. For example, cells can be labeled by the Ki-67 antibody (conjugated to a fluorescent dye).8 Unfixed, viable cells can be exposed to bromodeoxyuridine, which is incorporated during the S-phase.43 These cells will then react with an antibromodeoxyuridine antibody tagged with a fluorescent dye, a method that has proven reliable in studies of solid tumors.44 Bromo-deoxyuridine can also be administered intravenously (IV) to patients several hours prior to a biopsy. The tissue so recovered can then be examined for an S-phase label or can be exposed to tritiated thymidine to provide a double label, useful for examining phase durations, particularly in leukemia.45

The primary value of flow cytometry for cytokinetics is in its measurement of DNA content. DNA content is usually assessed by the use of intercalating or base-pair affinity dyes. The standard output of this technique is the DNA flow cytogram, also called a DNA histogram. Standardization of the G0-G1 peak for DNA histograms uses diploid cells from the same species as the tissue being studied.46 Human lymphocytes from normal donors are commonly used for many clinical applications. In the assessment of human breast cancer, for instance, lymphocytes are often obtained from normal lymph nodes removed at the time of primary surgery. The completed histogram graphs the relative proportions of cells with 2N DNA (ie, diploid cells in the G0-G1-phase), 4N DNA (ie, tetraploid cells in the G2-M-phase), and DNA content between 2N and 4N, called the S-phase fraction. Another cytometric term in common use is the proliferative index, the fraction of cells that are in the S-, G2-, or M-phase.

By measuring DNA content per cell, flow cytometry can also identify cells with abnormal amounts of DNA in the G0-G1 peak, termed aneuploid. Categories include near diploid (within 10% of 2N), hypodiploid (any value less than 2N), simple hyperdiploid (between 2N and 4N), tetraploid (4N), near-tetraploid (within 10% of 4N), hypertetraploid (greater than 4N), or combinations, called multiploid. Each aneuploid G0-G1 peak is expected to have a corresponding G2-M peak with twice as much DNA. The DNA index is the ratio between the fluorescence channel of the malignant G0-G1 peak and the normal diploid G0-G1-peak; < 0.9 or > 1.1 is often considered abnormal. The S-phase fraction may be impossible to measure in the presence of marked aneuploidy. This is especially true when a diploid G2-M peak overlaps with an aneuploid S peak. An overview of the literature suggests that ploidy can now be measured in more than 90% of solid tumors, and the S-phase fraction in about 80% of specimens. However, the classification of DNA histograms is not well standardized at present, so interpretations are highly variable, especially when paraffin-embedded, rather than fresh source material, is used.47

Mitotic Compartments

When a cell divides, the daughters either must remain in a mitotically quiescent state, enter the G1-phase, or die. There are no other possibilities. Entering the G1-phase means that the cell has positioned itself to divide again. Such a cell is thereby a member of the proliferative fraction, also called the growth fraction or the growth compartment.48 The second possibility is that the cell enters a prolonged G0-phase (or, rarely, an S0-phase or an arrested G2-phase), which means that the cell has joined the nonproliferative or quiescent fraction. Classically, the growth fraction is measured by dividing the LI by the ratio of the durations of the S-phase and the total cycle time.49

The S-phase fraction as measured by flow cytometry includes S0 cells in the quiescent fraction. For this and other technical reasons, the S-phase fraction is usually larger than the TLI. It correlates with, but is not equivalent to, the growth fraction.50 About 2% to 20% of cells in a typical cancer are in the S-phase at any point in time. Since the S-phase occupies one-quarter to one-half of the cell cycle, the growth fraction is usually 4% to 80%, with an average of less than 20%. Some normal tissues, such as bone marrow and alimentary mucosa, have larger growth fractions and shorter mitotic cycle times than many cancers, even cancers of those tissues.51,52

Nonproliferative cells fall into three categories. Some highly differentiated cells are thought to be permanently nonproliferative but might survive for the whole life of the organism. Classical teaching is that many neurons fall into this category, although this issue is still under investigation. However, most terminally differentiated cells, such as the polymorphonuclear leukocyte, have a finite life span. The third type of nonproliferative cell is in an unstable G0-phase, which means that it may be recruited into the G1-phase with the proper extracellular signal. Stem cells share with neurons the property of living as long as the organism. But, like unstable G0 cells, they can periodically, or on demand, produce viable progeny.53,54 Stem cells are also called clonogenic cells because of their capacity for unlimited proliferation. The signal for stem cell recruitment is often from physiologic changes in the environment, such as cell death or cell injury, or extracellular influences, such as by drugs or hormones. An operational definition of stem capacity is the ability to form colonies in soft agar.29,55 Cell culture experiments have found that from 1% to less than 0.1% of the cells in many common tumors have this property, but this may be an underestimate, since in vitro conditions may be more austere than those occurring naturally in vivo. Yet, even though malignant clonogenic cells are a minority population in a cancer, they are the prime targets of anticancer therapy since they constantly replenish the whole population. If chemotherapy preferentially kills mitotic cells, which is the mitotoxicity hypothesis, the ability of tumor stem cells to remain in the G0-phase for long periods may be one reason for failure of therapy.56

The third possible fate for a cell is death. Cells lost from any phase of the cell cycle are collectively called the cell loss fraction.57 Cell loss is important because the growth rate is the difference between cell production and cell loss. The common mechanism for cell death is apoptosis, which is under genetic control.58 Other mechanisms are desquamation and necrosis. Whatever the mechanism, a tumor with much cell loss may appear to be growing slowly, when, in fact, the rate of mitosis may be high. A well-known clinical example is basal cell epithelioma of the skin, which grows slowly in spite of showing a large number of metaphase figures.

The significant effect of apoptotic cell loss on growth rate may be illustrated by a hypothetic numeric example. Let us imagine a tumor with a growth fraction of 100%, no cell loss, and a mitotic cycle time of 3 days. This tumor will double in size every 3 days. In this case, the generation time is equal to the doubling time, the time it takes the cell number to double in size. If, however, cells are lost from the tumor at one-half the rate of cell production, a cell loss fraction of 50%, the tumor will double in 6 days rather than in 3 days. As mentioned elsewhere, growth fraction tends to get smaller as a mass increases in size. If the apoptotic fraction stays the same, or gets smaller at a slower rate, a plateau size will eventually be reached where mitosis equals apoptosis. The mathematics of these rate changes would result in the final tissue size, which relates to the degree of malignancy of that tissue. The importance of cell loss, however, goes beyond its impact on growth rate. Each mitotic cycle carries with it a finite probability of mutation.59 A tumor with a higher cell loss rate takes more mitotic cycles to double in size than a tumor with a lower cell loss rate. Thus, the rate of cell loss, especially the rate of apoptotic, physiologic cell loss, relates directly to the rate of mutations toward biologic properties of clinical importance.

Cytokinetics and Biologic Diversity

Since 1980, more than 2,000 published studies have assayed the cytokinetics of clinical cancers. There have been major as well as minor applications. One use has been in the screening of cytologic specimens for malignant cells. This exercise exploits the observation that with few exceptions (noted below), normal cells are diploid, whereas about 70% of clinical cancers are aneuploid. Screening, however, has been of secondary interest. The major use of kinetic measurements has been for correlation with clinical course. The S-phase fraction, the TLI, and aneuploidy have all been evaluated as prognostic factors. The S-phase fraction may be no higher in neoplastic than in some normal tissues. However, within a given histologic type of cancer, both a high S-phase fraction and the presence of aneuploidy are frequently associated with a growth rate that is relatively more rapid, a malignant behavior that is relatively more aggressive, and a therapeutic response that is relatively poorer.

The reasons for the consistent association of aneuploidy with high S-phase fraction are conjectural. One possibility is that aneuploidy is caused by high S-phase activity because it is the consequence of errors in chromosomal construction. The reasoning in this regard is that a high S-phase fraction implies a large number of mitotic cycles per unit of time, which provides more opportunities for erroneous DNA replication. Against this argument is the observation that many normal tissues, such as bone marrow and epithelia, have high S-phase fractions but do not normally become aneuploid. This leaves another possibility: High S-phase fraction is not the cause of aneuploidy but rather the consequence of the chromosomal abnormalities reflected in the aneuploid state. Such abnormalities may be linked with oncogene activation or suppressor gene inactivation. Some clinically benign tumors are aneuploid, so chromosomal abnormalities do not always mean frank cancerous behavior. Yet aneuploidy is clearly a step in tumor progression: DNA errors lead to growth stimulation, high cell turnover results in more opportunities for error, and errors produce increasing genetic aberrancy. The question of how fast mutations accumulate by this process is clinically relevant and will be discussed in the context of growth curve models.

Regardless of the rate of mutations, however, the neoplastic process is so closely related to spontaneous genetic change that tumor progression toward increasing malignancy is regarded as an intrinsic property of cancer.45,60 The clonal origin of tumors has been described.61 It has been stated that over 80% of clinical cancers are monoclonal by glucose6-phosphate dehydrogenase (G6PD) isotype or cytogenetics.62 Yet clonal evolution as the tumors evolve leads to heterogeneity in morphology, metastatic behavior, biochemistry, ploidy, immunogenicity, steroid and growth factor receptors, and drug sensitivity.63 Metastases tend to grow faster than do the primary tumors from which they arise.64,65 There is ample evidence that cytokinetics either underlies or is a direct covariate of tumor progression, that is, the mechanism relating aneuploidy to S-phase fraction also relates tumor progression to S-phase fraction. This will be illustrated in the discussion of clinical correlates of cytokinetics and further below in the context of the doubling time and the Skipper-Schabel model.

As discussed theoretically above, the third determinant of growth rate, cell loss, is also relevant to the generation of genetic changes. High rates of cell turnover are implicated in carcinogenesis. Elevated levels of thyroid stimulating hormone predispose to thyroid cancer.66 Chronic thermal injury with compensatory hyperplasia and hyperplasia secondary to solar damage lead to skin cancer.67,68 Hyperproliferation of the bone marrow in dysmyelopoiesis and in chronic granulocytic leukemia can result in acute leukemia.69,70 Hyperproliferation of the epithelium, as of the colon in inflammatory bowel disease and polyps, and of the breast in murine models and clinical specimens, is also associated with neoplastic transformation.71–74 Indeed, chemical carcinogenesis requires a growth promoter.75 It is possible that the hyperproliferation of cancer cells as a compensatory response to chronic antineoplastic drug treatment may predispose to the development of drug resistance in Hodgkin's lymphoma and gastrointestinal cancer.76,77

All the statistical associations among S-phase fraction, ploidy, cell loss fraction, and clinical behavior are of major scientific interest. It must be cautioned, however, that these associations are not always of practical importance, especially when kinetic parameters are highly correlated with more easily measured prognostic factors, such as tumor size. As is seen with any weak prognostic factor, small studies often have false-negative results. Conversely, false-positive reports may arise via data-driven subset analysis. For example, imagine that a population of patients is divisible into those with some arbitrary factor X and those without X, those with Y and those without Y, those with Z and those without Z, and so on. A small study may show that aneuploidy means poor prognosis for patients with Y but good prognosis for patients without Y, whereas both X and Z seem unrelated to ploidy and prognosis. Here the subset allocation (by Y) is chosen because ploidy seems to be useful within the subset, not because there is a biologic reason to suspect that ploidy and Y should be related. In fact, if ploidy carried no prognostic significance whatsoever, there is a real possibility that some other arbitrary division would distinguish the patients merely by chance. This other arbitrary division could be draped in the illusion of biologic tenability, but it would not prove reproducible in prospective confirmatory studies. Hence, purely statistical phenomena such as these should always be kept in mind when reading conflicting data concerning cytokinetics and clinical behavior.

Breast Cancer

Most invasive adenocarcinomas of the breast are of ductal origin. These have been studied extensively from a cytokinetic viewpoint. Ductal carcinoma in situ is thought to be a true neoplastic lesion that is not yet invasive but has a tendency to progress in that direction. There is some evidence that ploidy and proliferative activity can help identify lesions with greater potential for such progression.78 Regarding frank invasive ductal cancers, the TLIs of primary specimens have been shown to follow a log-normal probability distribution.79 This means that while the majority of TLIs are grouped about a median of 5% to 6%, some very large values are found in a few cases. Nuclear staining with the Ki-67 antigen correlates with TLI.80

As the phenotypic expression of genotypic abnormalities, TLI is a fairly stable property of a given breast cancer, that is, TLI values from primary specimens may correlate well with values determined from metastatic sites.81 High TLI predicts for the presence of necrosis in the tumor, low estrogen receptor content, anaplastic nuclear and histologic grade, and other predictors of poor clinical outcome. In node-positive breast cancer primarily treated with surgery and subsequently with adjuvant chemotherapy, a low TLI predicted for longer relapse-free and overall survival.82 In node-negative breast cancer patients not receiving adjuvant chemotherapy, a high TLI predicted for recurrence.83 Further evaluation of these 1,800 node-negative tumors found TLI to be of prognostic relevance for local and distant recurrence as well as survival.84 These data are highly controversial since another study with 8-year follow-up failed to show any association between TLI and survival.85 A higher TLI has also been associated with a greater sensitivity to chemotherapy in metastatic breast cancer.86 The safest statement is that the value of TLI has not been fully established, but that indications are that important biologic information is contained therein, and that further investigation regarding both the prediction of prognosis and response to chemotherapy is justified.

As described above, the most commonly measured cytokinetic parameter is now the S-phase fraction by flow cytometry (SPF). TLI and SPF show good correspondence.87 As for TLI, in many studies, high SPF in primary disease correlates with low estrogen and progesterone receptor content, high degree of nodal involvement, increasing nuclear anaplasia, and aneuploidy.87–90 The degree of axillary nodal involvement with cancer seems to correlate with high SPF in some studies, whereas in others, it appears to be independent of axillary nodal status, tumor size, and menopausal status.91,92 A few studies have reported a higher SPF in patients younger than 50 years of age, notably associated with a poorer prognosis.90,93 High SPF correlates, though weakly, with prognosis following local recurrence in a conserved breast.94

In node-negative breast cancer, the presence of either high SPF or aneuploidy has been correlated with a higher probability of relapse.95 This was only partially confirmed in a prospective series of node-negative breast cancer patients randomized to receive no postoperative adjuvant chemotherapy.91 In that large study, ploidy (measured in 79% of cases) had no prognostic value; SPF (measured in 73% of patients) did, with low SPF predicting longer disease-free survival. However, low SPF correlated so well with small tumor size that its value as an independent predictor remains to be established by further study, that is, both ploidy and SPF may convey prognostic information, but the clinical usefulness of the small magnitude of their impact, especially in light of more powerful covariates, must be considered controversial.96 Several studies with median follow-ups of at least 4 years have found that low SPF is an independent predictor of lower relapse rate or longer survival in node-negative disease.90,93,97,98 For example, one retrospective analysis of 195 patients with node-negative disease and tumors > 1 cm in diameter found that the relapse-free rate was 78% for cases with SPF less than 10%, but 52% for the others.97 A retrospective analysis by the National Surgical Adjuvant Breast and Bowel Project (NSABP) of over 4,000 patients with node-negative, estrogen receptor-positive breast cancer also found a significant correlation between SPF and disease-free and overall survivals.98 Similar data exist for node-positive cases. Yet, SPF does not consistently emerge as an independent factor in multivariate analyses.99 It is also of interest to note that for the patients treated by chemotherapy,91 treatment has a positive impact irrespective of the S-phase category. Hence, the data are not clear, and great caution regarding the clinical use of SPF must be exercised. In this regard, a consensus review of published data has concluded that SPF is associated with tumor grade, as well as the probability of relapse and survival in node-negative and node-positive disease, but that clinical applications remain indistinct.100 The American Society of Clinical Oncology (ASCO) has not recommended the routine use of SPF to determine prognosis or therapeutic options.101

Ploidy, for all of its theoretic attractiveness, is now known not to be clinically useful. In the subset of stage II patients with estrogen receptor-negative tumors, diploidy has been reported to be a positive prognostic factor.102 Aneuploidy is indeed more common among more poorly differentiated tumors.103 For analysis of node-negative and node-positive disease, ploidy has been shown by some to be a prognostic marker, whereas others did not confirm it.89,104,105 In node-positive patients, studies with a follow-up of at least 5 years have noted statistically significant differences in relapse-free survival and overall survival in favor of diploid versus aneuploid tumors.99,106 Several multivariate analyses found ploidy possibly to be an independent prognostic factor, whereas others did not confirm the findings.90,107,108 On the contrary, a consensus review of the usefulness of DNA index found that ploidy is a weak prognostic factor, which is not of independent value in multivariate analysis.100 As with SPF, the routine measurement of DNA content in breast cancer is not supported by the ASCO.101

Several studies have used less common techniques to evaluate the proliferation rate of breast cancers, including in vivo and in vitro labeling with the thymidine analog 5-bromodeoxyuridine (BrdU) and in vitro staining with anti-Ki-67 antibodies. BrdU labeling seems to correlate well with TLI, large tumor size, poor differentiation, aneuploidy, and high SPF, but not estrogen receptor status.109 One study using in vivo BrdU labeling failed to find an association of the values in normal breast tissue and in cancer.110 However, the labeling of the normal cells in premenopausal women was higher than that in older women. Nuclear staining with Ki-67 antigen correlates with TLI80 and is abundant in cancers with poor estrogen receptor content, aneuploidy, high nuclear grade, and rapid relapse after primary surgery. The relationship between Ki-67 staining and tumor size or histologic grade has not been established, although a large study found estrogen receptor status, Ki-67 content, tumor size, and nodal status all to be independent prognostic factors.111 A retrospective analysis by the EORTC in node-negative disease also found Ki-67 to be of prognostic value.112

The breast cancer literature is filled with reports of putative prognostic factors that correlate, to various degrees, with proliferative measurements. These include c-erbB2 (HER-2/neu), epidermal growth factor receptor (EGFR, HER-1), mutant p53, cathepsin D and other proteases, nm-23, urokinase-type plasminogen activator (uPA) and plasminogen activator inhibitor type-I (PAI-1), and other mutation suppressors. HER-2 is a protooncogene, located on chromosome 17q21–22, that is amplified in approximately 30% of primary breast cancers.113–115 It encodes a 185 kDa glycoprotein with tyrosine kinase activity that is involved in the transduction of signals for growth. Amplification and overexpression of c-erbB2 are observed at all stages of primary breast cancer and in lesions in all metastatic sites. Overexpression of c-erbB2 in node-positive patients correlates with high SPF and aneuploidy, but not with TLI.116–118 Moreover, c-erbB2 and SPF have been found in some studies to be independent prognostic factors for node-positive breast cancer,119,120 whereas other studies have not confirmed this observation.119–122 Targeting against HER-2/neu receptor with monoclonal antibody (trastuzumab, Herceptin, Genentech) is the standard of care in treatment of metastatic breast cancer with Her-2/neu overexpression and is being evaluated in adjuvant breast cancer treatment.113 EGFR is thought to be required to maintain normal breast epithelium, but it is overexpressed in 35% to 45% of breast cancers. Some have reported a correlation of EGFR with SPF, ploidy, and Ki-67 staining, but this remains unclear.117 The p53 gene is one of the tumor suppressor genes involved by deletion or inactivation in the development of breast cancer. Wild-type p53 protein arrests cell division at the interface of G1 and S, binds DNA in a sequence-specific manner, and is a transcriptional activator.123 Mutations of p53 result in the production of an aberrant product with a long half-life and the absence of all of these functions. The p53 protein has been extensively evaluated in the context of kinetic assays.124,125 In particular, abnormal p53 expression may be of prognostic value in certain subsets of node-negative and node-positive disease.126 Expression of p53 may also be related to therapeutic benefit of radiation in node-negative breast cancer.126 Cathepsin D is an estrogen-related protein that acts as a peptide growth factor and may facilitate cancer cell migration and invasion. Its expression does not correlate with TLI or other proliferative factors.127 Evaluation of uPA and PAI-1 as a prognostic factor is also under investigation. Some data have shown that node-negative breast cancer patients with low levels of uPA and PAI-1 have very good prognosis and may be spared from adjuvant chemotherapy.128 Other prognostic factors that are under evaluation are the role of type I insulin-like growth factor (IGF-IR) and cyclooxygenase-2 (COX-2) in breast cancer proliferation.128,129

Several investigators have evaluated multiple potential prognostic markers in single studies. For example, patients receiving preoperative chemo-hormonal therapy underwent fine-needle aspirations before and after systemic therapy for analysis of receptor status, c-erbB2, p53, Ki-67, SPF, and ploidy.130 A “good clinical response” was of independent predictive value for survival. Lack of c-erbB2 expression and a reduction in Ki-67 staining after systemic therapy predicted for a clinical response. These results lend support to a possible role for these factors in this setting. A retrospective analysis of patients with node-negative tumors not treated with adjuvant systemic therapy found PAI-1, cathepsin D, and SPF to be of significant prognostic value for disease-free survival in a univariate analysis.131 Other markers, Ki-67, p53, HER-2/neu, and ploidy were also evaluated in this study.

Recently, investigators have identified that high level of the low molecular-weight isoform of cyclin E, a regulator of cell cycle, correlated strongly with poor disease specific survival in node-negative and node-positive breast cancer patients.132 In this study, cyclin D1, cyclin D3, and HER2/neu were also evaluated. In a multivariate analysis, associations of death with cyclin E scores with levels of cyclin D1, cyclin D3, and HER2/neu did not reach statistical significance. It remains to be defined how levels of cyclin E correlate with various proliferative measurements.

All these data signify that the growth fraction, as estimated by a large number of currently available techniques, is positively correlated with some aggressive manifestations of breast cancer, but not others, and never strongly or consistently. Hence, factors other than growth fraction alone must be important determinants of the malignant behavior of this disease. As discussed in other sections of this chapter, apoptosis—paticularly the rate of change of the apoptotic fraction—is clearly a cytokinetic process of great potential in this regard. Numerous ongoing evaluations will aid in the identification of those factors of clinical significance. Recently, gene-expression signature has been found to be a predictor of breast cancer survival.133,134 These investigators used DNA microarray analysis to identify a series of node-negative and node-positive patients as having “good prognosis” or “poor prognosis” signature. Multivariate Cox regression analysis showed that the prognosis profile was a strong independent predictor of disease outcome. Many of the genes implicated relate to such cytokinetic events as mitosis and apoptosis, whereas others are linked to microanatomy, which obviously underlies the fractal dimension. The further development of is field is anticipated to eventually lead to a strategy by which we may select optimal candidates for specific postoperative adjuvant chemotherapy regimens, including no treatment at all for those with already superb prognoses.

With multiple determinants of the virulence of this disease, various modalities are being pursued to improve the efficacy of breast cancer therapy. One attempt to improve efficacy of chemotherapy in breast cancer is dose-intensification. The term dose-intensity is formulated as body-size adjusted dose (mg/m2) divided by time (per week). The most widely used method of increasing dose-intensity is dose escalation, which has been shown to be modestly successful for some drugs in some dose ranges, although regimens employing dose escalation only (ie, autologous bone marrow transplantation) have been disappointing as breast cancer therapies.135 The total impact of therapy could relate to the cell kill for each dose, the length of time over which the drugs are administered, and the rate of tumor growth between each treatment. If so, then cell kill proportional to the growth rate achieved at shorter time intervals should improve the overall impact of therapy. This concept is termed dose density, as distinguished from dose escalation, and is discussed below under the Norton-Simon Model.126 Recently, the application of the concept of dose-density has been proven to be superior to standard method of chemotherapy delivery. In CALGB 9741 sequential adjuvant chemotherapy delievered every 2 weeks with growth factor support is superior in terms of disease-free and overall survival to chemotherapy given every 3 weeks.136 The dose dense regimen was also less toxic that the conventional regimen, particularly in terms of granulocytopenia.

Prostate Carcinoma

Numerous studies have assessed DNA content by flow cytometry in prostate cancer.137,138 The majority of these analyses indicate that ploidy provides prognostic information for localized prostate cancer. Aneuploid tumors recur more frequently than do diploid tumors.137 Aneuploidy tends to occur in more advanced stages of disease.138 Aneuploidy and SPF were shown to be significantly related to both large tumor size and a high Gleason score.138 SPF has been assessed by flow cytometry,138 in vivo bromodeoxyuridine labeling, and Ki-67 expression, but the clinical value of such assessments is uncertain. Currently, the study of the significance of cyclo-oxygenase-2 (COX-2) and EGFR and Her2/neu overexpression in prostate cancer is ongoing.139–141

Renal Cell Carcinoma

Conflicting data exist regarding the prognostic significance of DNA ploidy in renal cell carcinoma.142,143 DNA ploidy has been correlated significantly with both tumor grade and survival.142 In a univariate survival analysis, tumor stage and grade, Ki-67, silver-stained nucleolar organizer regions (AgNOR), and proliferating cell nuclear antigen (PCNA) are associated with significant survival.144 One study showed that high cyclin E levels were associated with aneuploidy, high stage, high grade, and high erythrocyte sedimentation rate.145 The prognostic significance of IGF-IR is being evaluated in renal cell carcinoma.146 The predictive significance of cytokinetics regarding response to therapy can be resolved only by prospective studies.

Bladder Cancer

BrdU labeling has been used to assess the growth fraction in bladder cancer, but most studies have used DNA flow cytometry.147 A number of studies have noted an association between DNA ploidy, tumor grade, and aggressiveness of bladder cancer.148 Controversy exists over the significance of DNA ploidy. Some data show that DNA ploidy is not an independent prognostic factor.149 Few studies have shown an association between EGFR, c-erbB2, and c-erbB3 overexpression to tumor grade, stage, and survival.150,151 The significance of COX-2 overexpresion in bladder cancer is being evaluated.140

Testicular Carcinoma

It has been reported that a high DNA index in nonseminomatous germ cell tumors (NSGCT)of the testes is associated with advanced disease at presentation.152 Aneuploidy, however, did not correlate with histology or vessel invasion. In seminoma, aneuploidy is associated with a shorter disease-free survival.153 The significance of EGFR overexpression in NSGCT is being studied.154

Ovarian Cancer

Most studies have demonstrated that diploid tumors are associated with a better prognosis whereas other studies show no correlation between DNA ploidy and survival.155,156 A multivariate analysis has not identified that the aneuploidy population in ascitic fluid as an independently significant variable for predicting recurrence.157 Assessment of S-phase fraction by Ki-67 staining, flow cytometry, and thymidine labeling has produced variable results.158 Data are emerging on the significance of EGFR and c-erbB2 over-expression in ovarian cancer.159 One study showed that overexpression of EGFR was associoated with poor survival.159 The significance of COX-2 overexpression in ovarian cancer is being evaluated.140

Uterine Cancer

In endometrial carcinoma, with few exceptions, aneuploidy has been associated with poorly differentiated tumors and decreased survival.160 One study showed that overexpression of p53, Her-2/neu, and KI-67 correlated with more malignant tumor phenotype.161 A multivariate analysis has identified DNA ploidy, histologic subtype, p53 over-expression, and HER-2/neu overexpression as independent prognostic factors.162 However, other studies demonstrate that the significance of HER-2/neu is less clearly established.163 A recent study has demonstrated that tamoxifen therapy can increase the expression of progesterone and estrogen receptors in endometrial cancer. The effect is most pronounced in tumors with favorable clinicopathologic parameters.164

Cervical Carcinoma

DNA ploidy, S-phase fraction, and BrdU labeling have an unclear role as prognostic factors in cervical carcinoma.165,166 One study has suggested a correlation between SPF and BrdU labeling with survival.165 Yet, multivariate analyses have shown that SPF and DNA ploidy are not significant predictors of survival.166 One study has shown a correlation between the Ki-67 index and response to radiation therapy.167 The upregulation of the c-erbB2 oncoprotein has recently been shown to be associated with invasive cervical cancer and poor survival.168 One study has shown that COX-2 overexpression is asscociated with chemotherapy resistance and poor survival.169 Another study has shown that EGFR overexpression is correlated with poor disease-free surival.170

Colorectal Carcinoma

Both retrospective and prospective data suggest that aneuploid colorectal carcinomas, particularly those in stages A, B, and C, have a worse prognosis.171,172 This is not a universal finding, however. A univariate analysis has shown that stage, nodal involvement, intestinal wall invasion, and poor tumor differentiation are all associated with worse survival, but no correlation is seen with DNA ploidy.173 The significance of p53 accumulation is unclear, as well as the role of K-ras mutations.174,175 Recent data have demonstrated the upregulation of COX-2 expression in colorectal cancer and that COX-2 overexpression is associated with advanced stage, larger size, and nodal involvement.176,177 A recent study has shown the regulation of COX-2 pathway in colorectal carcinogenesis by the HER-2/neu receptor.178 Additionally, several studies have demonstrated the correlation between HER-2/neu upregulation with advanced stage and worse survival.179 The significance of EGFR overexpression in colorectal carcinoma is being evaluated.113,180 The first efforts to target EGFR in cancer therapy by Mendelsohn and colleagues used a monoclonal antibody (C225;Cetuximab, Imclone) to the extracellular epitopes of this receptor.113 The significance of vascular endothelial growth factor (VEGF) and its principle receptor, VEGFR2, is being evaluated.113 About a third of molecular therapeutics is directed against VEGF and VEGFR2. One such VEGFR2 inhibitor (SU5416, Semaxanib, SUGEN/Pharmacia) has been evaluated in metastatic colorectal cancer.113

Carcinoma of the Pancreas

The cytokinetics of this disease has not been well studied. One study showed a close correlation between DNA ploidy and the stage and grade of pancreatic cancers.181 K-ras oncogene mutations occur in 90% of pancreatic cancers.182 The overexpression EGF, transforming growth factor (TGF)-α and (TGF)-β 1–3, acidic fibroblast growth factor (aFGF), and erbB-2 and erbB-3 in pancreatic cancer is also common.182 Inhibitor of EGFR in pancreatic cancer (OSI-774, Tarceva, Genentech/Roche) is currently undergoing evaluation.113 High mutations of cell cycle control genes such as p53, p16, p21, SMAD4, and cyclin D2 have been correlated with pancreatic cancer, as well as abnormal expression of apoptotic genes such as bcl-2, bcl-XL, and bax.182

Hepatocellular Carcinoma

The prognosis of hepatocellular carcinoma (HCC) is dismal and molecular markers are associated with poor prognosis including DNA aneuploidy, proliferation markers (Ki-67, Mcm2, MIBI, MIA, PCNA, and CSE1L/CAS protein), p53 gene, cell cycle regulators (cyclin A, cyclin D, cyclin E, cdc2, p27, p73), oncogenes and their receptors (ras, c-myc, c-fms, HGF, c-met, and erb-B receptor family), and apoptosis factors (Fas and FasL).183

Gastric and Esophageal Carcinomas

Previous data have shown cytometric analysis to be of prognostic significance in squamous cell carcinoma (SCC) of the esophagus. Patients with aneuploid tumors show more unfavorable prognosis than those with diploid tumors.184 Highly significant correlation has been shown between results of cytometric study and p53 overexpression.185 COX-2 upregulation has also been shown in well-differentiated regions of esophageal SCC, the clinical significance of which is unknown.140 There is controversy over the role of c-erbB2 overexpression in esophageal cancer as a prognostic factor.186

There has been conflicting data on the significance of tumor aneuploidy in gastric carcinoma. Some studies have supported that tumor aneuploidy is associated with decreased survival.187 However, another study does not show a correlation between DNA ploidy with prognosis.188 Multivariate analyses show that tumor stage remains to be the most important prognostic indicator.189 Controversy also exists concerning the importance of p53 accumulation. One analysis reports that high p53 index is associated with poor survival, whereas another study shows that p53 overexpression is not an independent factor by multivariate survival analysis.188,190 COX-2 upregulation has been detected in gastric carcinoma and has also been correlated with lymph node involvement and stage.140 The c-erbB2 oncoprotein is also overexpressed in gastric cancer, but the significance of it is uncertain.186 Activated c-kit mutation has been identified as a pathogenic event in gastrointestinal stromal tumors (GIST) and an inhibitor of this tyrosine kinase activity has been approved as a treatment for GIST (Gleevec, Novartis).113

Head and Neck Cancer

There is disagreement in the literature regarding the prognostic significance of DNA ploidy in squamous cell carcinoma of the head and neck. Some studies identified a more favorable prognosis for aneuploid tumors, whereas others found a better outcome for diploid tumors.191–193 Several studies have reported increased radiosensitivity for aneuploid lesions.194 Only limited studies with bromodeoxyuridine and thymidine have been performed.195 The overexpression of COX-2 is seen in both head and neck SCC (HNSCC) and adjacent normal appearing epithelium,140 the importance of which is unknown. The c-erbB2 oncoprotein is also upregulated in HNSCC, but more data are required to understand its significance.196

Lung Carcinoma

Numerous studies of non-small-cell lung carcinoma (NSCLC) have found an association between aneuploidy and shorter survival times.197 However, other analyses have not confirmed this observation.198 Limited data are available concerning the prognostic significance of ploidy in small-cell lung cancer.199 Data have shown that p53 overexpression is associated with decreased survival.200 Emerging data on the upregulation of COX-2 enzyme140 and c-erbB2 oncoprotein in NSCLC seem to suggest a correlation with poor survival, but further analyses are needed.201 Recent study has shown correlation between cyclin E overexpresion, Ki-67 expression, and p27-negative expression with poor disease-free survival.202 The importance of EGFR overexpresion is being studied and several EGFR inhibitors are in development, with ZD1839 (Iressa, Astrazeneca) furthest along in evaluation.113

Brain Cancer

Determination of high growth fraction by BrdU labeling, Ki-67 staining, and mutant p53 expression (disinhibition of the normal G1-S blockade) was found to convey prognostic information in several studies of primary brain malignancies.203,204 A prospective study of 174 patients with intracranial gliomas found the BrdU labeling index to be an important predictor of survival for low-grade astrocytomas. This index, in conjunction with the patient's age, was also predictive of survival for glioblastomas and malignant astrocytomas.204 Aneuploidy has been associated significantly with atypical, anaplastic, and recurrent meningiomas.205 Significance of c-erbB2 over-expression and COX-2 upregulation are being evaluated in brain tumors.206,207

Thyroid Cancer

Although aneuploidy has been noted in both malignant and benign thyroid lesions, a multivariate analysis has suggested that DNA ploidy is an independent prognostic factor for survival.208 Aneuploidy is also correlated with advanced thyroid cancer with spread to extrathyroid tissue.209 A multivariate analysis has also suggested that p53 overexpression is an independent prognostic factor for survival.210 Nuclear p53 immunoreactivity is associated with DNA aneuploidy in papillary thyroid cancer. Presently, the role of c-erbB2, bcl-2, and p21 are being evaluated in thyroid cancer.210,211


Aneuploidy has been associated with more advanced disease, increased tumor recurrence, and the existence of myasthenia gravis.212 In a multivariate analysis, aneuploidy and high proliferative activity, measured by AgNOR are associated with a shortened survival.213 The AgNOR counting is also correlated with the invasiveness and stage of thymomas as well as the presence of myasthenia gravis. The signficance of EGFR overexpression in thymoma is beig evaluated.214


There is limited information on the role of DNA analysis for soft tissue and osteosarcomas. In soft tissue sarcoma, one study shows that aneuploidy is correlated with histologic grade but is not associated with survival.215 The presence of diploid or near-diploid tumors may be correlated with a more favorable prognosis for osteosarcomas and chondrosarcomas.216 In synovial sarcoma, a multivariate analysis has shown that aneuploidy, high Ki-67 expression, and stage are associated with a shorter survival.217 In peripheral primitive neuroectodermal tumor (PNET) and extraosseous Ewing sarcoma, one study shows that DNA ploidy and SPF are not found to have prognostic significance.218

Pediatric Tumors

In neuroblastoma, several studies have noted an unfavorable prognosis for diploid neuroblastomas.219 Amplification of the N-myc oncogene has also been associated with these diploid tumors.219 Aneuploidy is more significantly associated with lower clinical stage, younger age at diagnosis, and without N-myc gene amplification.220 In Wilm tumors, there is controversy regarding DNA ploidy.221 One study reports that aneuploidy is associated with poor outcome, whereas another shows that ploidy status has no statistical correlation with survival.221,222


Numerous analyses of patients with primary melanoma indicate a correlation between aneuploidy, more malignant melanoma, higher recurrence rates, and/or shorter survival.223,224 For metastatic melanoma, aneuploidy has been associated with a more favorable prognosis as well as a worse outcome. Evaluation of S-phase fraction by flow cytometry is also of prognostic significance for stage III and metastatic disease.224 In metastatic melanoma treated with chemotherapy, a multivariate survival analysis has shown that a high SPF measured in histologically verified metastases is associated with a higher response rate and a longer survival.225 For stage II melanoma, slow proliferation as measured by thymidine labeling indicates a significant advantage in relapse-free and overall survivals.226 In stage I cutaneous melanoma, there is a strong relationship between DNA ploidy and classic prognostic variables.227 The role of c-erbB2 in melanoma is being evaluated.228

Hodgkin's Disease

The few studies of Hodgkin's disease that have been reported have noted a low frequency of aneuploidy.229 This may be the result of the difficulty encountered in isolating malignant cells from a large population of benign cells of similar composition.230 A retrospective analysis of 137 patients with Hodgkin's disease found no correlation between aneuploidy and other prognostic factors, or with survival.231 Although tumors with a high S-phase fraction had a less favorable outcome, this prognostic factor was not independent of others.230 A study has shown overexpression of multiple proteins that are associated with increased growth in Hodgkin's lymphoma: cyclin E, CDK2, CDK6, STAT3, Hdm2, Bcl2, Bcl-XL, Survivin, and NF-kappaB.231

Non-Hodgkin's Lymphoma

Non-Hodgkin's lymphoma (NHL) is such a heterogeneous collection of diseases that it is not surprising that the role of DNA flow cytometry remains ill defined, with many conflicting data. Nevertheless, it is clear that aneuploidy is more common in lesions of high-grade or of B-cell lineage.232 As a prognostic factor, however, there is controversy regarding ploidy as a strong indicator of survival.233 In contrast, most studies have shown that S-phase fraction or other measures of proliferative activity are useful prognostically.234 S-phase fraction has been used to evaluate clinical course and to augment histologic classification. In gastrointestinal lymphoma, a multivariate analysis on 37 cases has shown that stage and DNA ploidy patterns have a prognostic value in terms of survival.235 Most low-growth fraction lymphomas are initiated by molecular events, resulting in inhibition of of apoptosis, such as translocation affecting Bcl-2 or Bcl-10.236 In high-growth fraction lymphoma, enhanced growth is due to the deregulation oncogenes with cell cycle regulatory functions, such as Bcl-6 or c-myc.236

Multiple Myeloma and Monoclonal Gammopathies

Aneuploidy is found in most cases of multiple myeloma, but it has also been found in benign monoclonal gammopathies.237 Several older studies have noted an association between aneuploidy and decreased survival but more recent studies have not.238,239 In these studies, hyperdiploid status is associated with better survival. Labeling of bone marrow cells with bromodeoxyuridine and the monoclonal antibody Ki-67 can be used to determine proliferative activity in patients with multiple myeloma and monoclonal gammopathies.239 The BrdU labeling of plasma cells is a well-established independent prognostic factor in newly diagnosed multiple myeloma.239 One study has shown that elevated expression of Mcl-1, decreased expression of Bax, and increased expression of Bcl-2 are correlated with cell growth in multiple myeloma.240 Another study has shown increased expression of VEGF in myeloma compared to nonmyelomatous cell lines.241


Flow cytometric analysis of leukemias has been used primarily for immunophenotypic classification, cytogenetic studies, and the determination of gene rearrangements. Regarding the prognostic significance of DNA content, several studies of childhood acute lymphoblastic leukemia (ALL) have noted that the presence of hyperdiploid blasts conveys a more favorable outcome and a better response to therapy.242 Also, lower DNA content in the ALL blasts in children has been associated with a greater frequency of late relapses.243 Flow cytometry could be used to monitor residual disease in certain subgroups of ALL.244

In ALL in adults, aneuploidy has been associated with a worse outcome.245 However, another study shows that DNA index does not correlate with outcome or response to treatment.246 Although several studies have used a variety of techniques to assess the cell kinetics of acute myeloid leukemia (AML) and chronic myeloid leukemia (CML), the prognostic value of these measurements remains unclear.247 Some have found that aneuploidy predicts a more favorable prognosis, as it does in childhood ALL, but another study does not confirm this.245,248 In CML the translocation between chromosomes 9 and 22, which results in the fusion between genes coding for abl tyrosine kinase and bcr, generates the distinctive Philadelphia chromosome.113 Targeting against the bcr-abl tyrosine kinase activity by inhibitor (Gleevec, ST-571, Novartis) is now the standard of care in treating CML.113 Bromodeoxyuridine labeling of leukemic promyelocytes revealed a lower labeling index and longer cell cycle than in other types of AML.249 These results were thought to be secondary to the marked expression of transforming growth factor-beta (TGF-β).

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