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Application of Flow Cytometry forBiomarker-Based Cervical CancerCells DetectionJian Ling, Ph.D.,1* Urs Wiederkehr, B.S.,2 Spring Cabiness, B.S.,3

Kenneth R. Shroyer, Ph.D., M.D.,4 and J. Paul Robinson, Ph.D.5

The Pap test used for cervical cancer screening is subjective,labor-intensive, and has relatively low sensitivity and specificityfor the detection of underlying clinically significant lesions. Theobjective of this study is to develop a biomarker/flow cytometry-

based approach for cervical cancer screening. Immunofluores-cence technology to quantify cervical cell expression of two bio-markers p16INK4A and Mcm5 was developed and evaluated byboth microcopy and flow cytometry. The capability of using bio-marker/flow cytometry approach to detect rare-event dysplasticcells in a large background of benign epithelial and inflammatorycells was evaluated. The results indicate that flow cytometrycould detect 0.01% dysplastic cells in a background of normalcervical epithelial cells with the combination of the two bio-markers. Thirty-two clinical specimens were used to test the bio-marker/flow cytometry-based approach and the results were compared with the liquid-based cervical cytology. The experimentyielded 100% sensitivity and 93% specificity with reference to theliquid-based cervical cytology. This study indicates the promiseof using multi-color fluorescence flow cytometry for biomarker-

based cervical cancer screening. This molecular-based, poten-tially high-throughput and automated method is expected to pro-vide an alternative/auxiliary means of cervical cancer screening.Diagn. Cytopathol. 2008;36:7684. ' 2008 Wiley-Liss, Inc.

Key Words: cervical cancer, cancer screening; flow cytometry;cancer markers; rare-event detection

Cervical cancer is the second most common cancer in

women, with 500,000 new cases reported each year and

250,000 deaths worldwide. Eighty percent of the deaths

occur in developing countries1

due to the lack of wide-spread screening programs. In developed countries, the

death rate from cervical cancer has been reduced signifi-

cantly through the adoption of population-wide screening

programs. According to the American Cancer Society,2

the cervical cancer death rate in the U.S. declined 48%

between 1973 and 1993.

Current Screening Methods

The recognized leading tools used in cervical cancer

screening programs are the Pap smear, pioneered by Dr.

George Papanicolaou in the 1930s, and liquid-based cervi-

cal cytology, introduced in the mid 1990s. In both meth-ods, cell specimens are collected by gently scraping the

surface of the cervix with a sampling device, such as a

plastic spatula or cytobrush. In the Pap smear, cells from

the spatula or cytobrush are smeared directly on a slide

and then fixed and stained using the Papanicolaou stain.

In liquid-based cervical cytology, the sample is first

rinsed into a liquid fixation solution to preserve the cells

and, thin layer or monolayer preparations are prepared

using density gradient centrifugation or filter membrane

technology using automated systems. Both Pap smears

and liquid-based cytology slides are subsequently stained

using the Papanicolaou stain.

Cervical cytology slides are initially screened by micro-

scopic examination by either a cytotechnologist or pathol-

ogist. Federal regulations require that all potentially

abnormal specimens be reviewed and diagnosed by a

qualified pathologist. Slides that are screened as normal,

however, may be reported without requiring pathologist

review. Cytologic abnormalities that may reflect underly-

ing cervical dysplasia or squamous cell carcinoma are

categorized under the Bethesda 2001 system as atypical

squamous cells of undetermined significance (ASC-US),

1Medical System Department, Automation and Data System Division,Southwest Research Institute, San Antonio, Texas

2Cytolution, Inc., San Jose, California3Applied Physics Division, Southwest Research Institute, San Antonio,

Texas4

Department of Pathology, University of Colorado Health ScienceCenter, Denver, Colorado

5Cytometry Laboratories, Bindley Bioscience Center, Purdue

University, West Lafayette, IndianaContract grant sponsor: Cytolution Inc.; Contract grant sponsor: NIH

(National Cancer Institute); Contract grant number: 1R21CA125370-01.*Correspondence to: Jian Ling, Ph.D., Southwest Research Institute,

6220 Culebra Rd., San Antonio, TX 78238. E-mail: [email protected] 18 June 2007; Accepted 6 October 2007DOI 10.1002/dc.20763Published online in Wiley InterScience (www.interscience.wiley.com).

76 Diagnostic Cytopathology, Vol 36, No 2 ' 2008 WILEY-LISS, INC.


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atypical squamous cells suspicious but not diagnostic for

a high grade squamous intraepithelial lesion (ASC-H),

low-grade squamous intraepithelial lesion (LSIL), high-

grade squamous intraepithelial lesion (HSIL), and squa-

mous cell carcinoma (SCC).3 Figure 1 illustrates the

morphological changes that are characteristic of the devel-

opment of precursor lesions. A general feature of the

high-grade dysplastic cells is that they typically have high

nuclear-to-cytoplasmic volume ratios and this ratio

increases as the severity of the lesion increases (Fig. 1).

Current guidelines provided by the American Cancer

Society recommend screening for women 21 year of age

and older. The preferred screening frequency is annual

unless there are three consecutive normal, technically sat-

isfactory Pap tests but is often increased to every 36 mo

if the Pap test indicates an abnormality.4 About 50 million

Pap tests are performed each year in the United States

and about 110 million worldwide.5,6

Human papillomavirus (HPV) is the main cause of cer-

vical dysplasia and carcinoma. Although HPV vaccines

are likely to be highly effective in preventing infection by

HPV vaccine types, cervical cancer screening programs

will still play crucially important roles for the detection ofcytologic abnormalities in currently infected patients and in

the detection of disease associated with nonvaccine types.

Limitations of Current Screening Methods

The major challenge for cervical cytology is the need to

detect rare-events. A liquid-based cervical cytology speci-

men contains a minimum of 5,000 normal squamous

cells; most samples contain 50,000 or more normal cervi-

cal squamous epithelial cells, as well as benign endocervi-

cal cells, and inflammatory components. High-grade squa-

mous intraepithelial lesions (HSILs), on the other hand,

may often be based on the detection of only a very small

number of abnormal cells, frequently in the range of 10

100 dysplastic cells/slide.

Federal guidelines permit cytotechnologists to screen

up to 100 slides in a normal 8-hr workday.7 Assuming a

minimum number of 5,000 cells per slide, cytotechnolo-

gist would review at least 500,000 cells/day and be

required to detect as few as 1050 dysplastic cells in a

positive specimen. Since *90% of all cases in most diag-

nostic practices are negative for cytologic abnormalities,

most of the screeners time and energy is expended look-

ing at healthy cells.8 Fatigue and monotony can reduce

the acuity of the screener and increase the chance that

rare positive cells could be overlooked.7

Current methods of cervical cancer screening are not

only labor-intensive but are also highly subjective and

have relatively low sensitivity and specificity for the

detection of some high-grade clinically significant lesions.

With the liquid-based Pap test, the sensitivity of cervical

screening has increased to about 80% from the 65% in

conventional Pap smear,9 resulting in an improvement of

the overall clinical, economic, and patient outcomes.

However, the specificity of liquid-based Pap test dropped

from 95% with conventional Pap smear to about 75%.9

Recently, the FDA approved the use of high risk HPV

testing in combination with the liquid-based cervical cy-

tology for primary screening of women over age 30.

Biomarkers for Cancer Screening

With the significant advances in genomics and proteomicsover the last decade, hundreds of articles have been pub-

lished on the subject of understanding the molecular

pathogenesis of cervical cancer.10 Molecular changes

have been recognized to be the earliest indication of cell

abnormalities. The objective of the current study was to

develop a method that can achieve a true molecular mea-

surement using immunofluorescence technology and flow

cytometry technologies. Such a molecular-based cervical

cancer screening method is expected to have higher sensi-

tivity and specificity compared to the current cervical cy-

tology methods.

A large number of biomarkers have been identified that

are overexpressed in cervical cancer cells.11 Some of themarkers that appear to have potential for cervical cancer

screening include p16INK4A (a cyclin-dependent kinase in-

hibitor protein), Mcm (minichromosome maintenance) pro-

teins, Cdc (cell division cycle) proteins, topoisomerase 2

alpha, PCNA, Ki-67, Cyclin E, p-53, and Rb (retinoblas-

toma) proteins.10,1215 This report is focused on the analy-

sis of two of these markers, p16INK4A 1628 and Mcm5.29,30

p16INK4A

protein. The p16INK4A protein has been used as

an immunohistochemical and immunocytochemical marker

in several studies to detect cervical cancer. In cervical car-

cinomas, viral DNA integration into the host genome may

result in disruption of the E2 open reading frame, resulting

in unregulated overexpression of HPV oncogenes E6 and

E7, E7-mediated catabolism of pRb, and the reciprocal

overexpression of p16INK4A.26 Almost 100% of high-grade

cervical dysplasias and invasive cancers have been shown

to express very high levels of p16INK4A, whereas normal

cervical squamous cells do not test positive for

p16INK4A.31,32 Several studies16,17,2628 have demonstrated

the successful combination of p16INK4A immunocytochem-

ical assay with the liquid-based Pap test. In studies per-

formed by Bibbo et al.,16 very high levels of p16INK4A

Fig. 1. Morphological changes (the increase of nucleus-to-cytoplasm ra-tio) of precursor lesions of cervical carcinoma.

BIOMARKER-BASED CERVICAL CANCER CELLS DETECTION

Diagnostic Cytopathology, Vol 36, No 2 77

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were detected in almost 100% of high-grade cervical dys-

plasias and invasive cancers, whereas no p16INK4A-positive

stain was found in normal cervical epithelia using the same

antibodies. A study performed by Murphy et al.21 also

reported that p16INK4A identified dysplastic squamous and

glandular cells of the cervix with a sensitivity of 99.9%

and a specificity of 100%. A practical limitation to the use

of p16INK4A as a cytologic diagnostic adjunct, however, is

that sporadic expression of this marker is also sometimes

present in scattered benign endocervical glandular cells

and in tuboendometrial metaplasia of the cervical mucosa,

which could lead to false positive classification of test

results.31

Mcm5 protein. The MCM proteins form a hexameric

helicase that denatures DNA at the initiation of DNA rep-

lication.10 Mcm5 has been extensively studied as a marker

for cellular proliferation expressed during the normal cell

cycle and recent studies indicate that Mcm5 may be a

marker for the presence of cervical intraepithelial neopla-

sia and carcinoma but is also expressed in low grade dys-

plastic lesions and in some normal proliferating squamous

cells.21,29,30

Although Mcm5 may be expressed in a lower proportion

of high grade dysplastic cells than is typically observed for

p16INK4A the expression of Mcm5 has not been reported in

benign endocerrvial glandular cells. Thus, dual (multiplex)

staining of both Mcm5 and p16INK4A could theoretically

increase overall test performance because these two bio-

markers are complementary in nature.

Flow cytometry for cervical cancer detection. Flow

cytometry is an ideal format for the analysis of single-cell

suspensions, quantifying cell structural and molecular fea-tures, and for the detection of rare events. The potential for

the use of flow cytometry for cervical cancer screening

began in the 1970s and was widely reported during the

1980s and early 1990s.3340

Most of these studies focused

on methods that use fluorescent dyes to stain nucleic acids

and use flow cytometry to measure DNA content (aneu-

ploidy) as a prognostic indicator of solid tumors. However,

the use of DNA content as an independent prognostic indi-

cator is uncertain and remains controversial.

This study took a different approach in the use of flow

cytometry by including the evaluation of p16INK4A and

Mcm5 as sensitive and specific markers for the detection

of cervical dysplasia and carcinoma.

Materials and Methods

Sample Preparation

Control samples. The cervical cancer-derived HeLa cell

line, which has been shown to overexpress both p16INK4A

and Mcm5 proteins, was used as the positive control in

this study. HeLa cells were fixed and preserved with a

methanol-based fixative (PreservCyt1 solution, Cytyc

Corp., Marlborough, MA). A previous study41 has shown

that the PreservCyt1 solution will preserve both cell

morphology and cellular molecular markers for at least

30 days. PreservCyt1 solution is also known to permeab-

ilize cells so that fluorochromes-labeled antibodies can

penetrate cells.

Clinical cervical specimens. Residual cervical cytology

specimens from PreservCyt1 vials were obtained from

the cytopathology laboratories at the University of Texas

Health Science Center at San Antonio and the University

of Colorado Health Sciences Center at Denver, following

IRB application approval of the study protocol. These

specimens have been reviewed by experienced cytopatho-

logists and classified by Bethesda 2001 terminology as

negative, ASC-US, LSIL, or HSIL. The clinical

specimens were filtered with 70-lm nylon mesh filter to

remove cell clusters before flow cytometry measurement.

Fluorescence Labeling

Antibodies and conjugation with fluorochrome. Mousemonoclonal antibodies to p16INK4A (Clone ZJ11) and

Mcm5 (Clone CRCT5.1) from Labvison Inc. (Fremont,

CA) were selected in the study. These two antibodies

were directly conjugated with PE and APC fluorochromes

using commercially available labeling kits (ProZyme Inc.,

San Leandro, CA). The conjugates were denoted as

p16INK4A-PE and Mcm5-APC antibodies. Corresponding

mouse IgG1 and IgG2b isotypes were also obtained and

conjugated to PE and APC, respectively, as the isotype

control.

Immunofluorescence staining. Before staining, a sample

was washed twice with phosphate buffered saline (PBS)

to remove the fixation solution. The second wash used astaining buffer (PBS plus 1% bovine serum albumin

(BSA) and 0.01% sodium azide) to block the intracellu-

lar nonspecific binding sites. The sample was concen-

trated to 100 lL and then simultaneously stained with a

cocktail of p16INK4A-PE and Mcm5-APC antibodies. In

immunofluorescence imaging, 1 lg/mL concentration of

antibody was used to stain the samples. In flow cytome-

try, the optimal antibody concentration was about 0.1

0.25 lg/mL. Flow cytometry is more sensitive for detec-

tion of the fluorescence signal owing to the use of a

laser as the excitation source and a photomultiplier tube

(PMT) as the detector.

The staining tube was kept on ice or in a 48C dark re-frigerator for 30 min. Then the stained cells were washed

twice with the staining buffer to remove the unbound con-

jugates. The same procedure and same concentration were

followed for isotype staining.

Quantitative Microscopy

Before performing the flow cytometry experiment, micro-

scopic imaging was performed to (1) verify the effective-

ness of the fluorescence stain, and (2) verify whether the

LING ET AL.

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overexpression of biomarkers is correlated to the abnor-

mal morphology of dysplastic cervical cells. A Nikon

Eclipse TE2000E inverted microscope and computer sys-

tem was used for the fluorescence imaging. Three fluores-

cence filters in the FITC, PE, and APC bands (i.e., the

530-nm, 575-nm, and 660-nm emission bands) were used.

During imaging, the microscope was first set in differen-

tial-interference-contrast (DIC) video mode and visually

focused on an imaging area which contained multiple

nonoverlapping cells. Then, four images (three fluores-

cence images in the FITC, PE, APC bands, and a DIC

image) were obtained for each imaging area. The DIC

image illustrates the morphology of the cells. The PE and

APC images show the expression of p16INK4A and Mcm5

markers in the cells. The FITC image measures cell auto-

fluorescence in the FITC band, which is used to correct

the autofluorescence in the PE and APC bands on a cell-

by-cell basis (see Data Analysis below).

Flow Cytometry

A FACS Aria flow cytometer (Becton-Dickinson, San

Jose, CA) and an FC 500 flow cytometer (Beckman-

Coulter, Miami, FL) were used in the flow experiments.

Five parameters were measured: forward-scatter (FS), side

scatter (SS), and FITC, PE, and APC fluorescence bands.

The FS and SS measurements were used to gate out cell

debris. The cell autofluorescence measured in the FITC

band was used to correct the autofluorescence in the PE

and APC bands on a cell-by-cell basis using a postcompen-

sation method (see Discussion). The remaining fluores-

cence measured in the PE and APC bands reflects the

expression levels of biomarkers p16INK4A

and Mcm5,respectively, in each cell. Before each flow experiment,

the flow cytometer was calibrated using fluorescence beads

to minimize the day-to-day variation of optics. The calibra-

tion procedure ensured the measurement of different

samples under similar conditions.

Data Analysis

For imaging data, a MATLAB program was developed

to quantitatively compare cell-to-cell average stain inten-

sities in fluorescent images. The software automatically

segments the fluorescent images to locate individual

cells. The average fluorescence intensities or the fluores-

cence density in the FITC, PE, and APC bands were

determined for each individual cell. The fluorescence

density, calculated by normalizing the total staining in-

tensity by cell area, provided a fair comparison of the

biomarker expression among different types of cervical

cells, which usually have large variation in size (from 25

to 65 lm in diameter).

For flow cytometry data, FCS Express (De Novo Soft-

ware, Thornhill, Canada) was used to perform gating

and autofluorescence correction. Fluorescence pulse peak

instead of pulse integral was used to represent the fluores-

cence density or biomarker expression of each cell

because pulse peak is not significantly affected by cell

size, as is the pulse integral (see Discussion).

Results

Microscopy Imaging Experiment

Comparison of antibody stain and isotype stain. Fixed

HeLa cells were stained with a cocktail of p16INK4A-PE

and Mcm5-APC antibodies. Matched aliquots of fixed

HeLa cells were stained with a cocktail of PE and APClabeled isotypes. The dot plot in Figure 2 shows that the

antibody-stained cells (denoted by light quadrangular

symbol) have significantly higher stain intensities in both

the PE and APC bands than that of the isotype-stained

cells.

Comparison of normal and dysplastic cervical cells.

Eleven cervical cytology specimens, including five nega-

tive and six positive specimens (1 ASC-US, 2 LSIL, and

3 HSIL), were used in a pilot imaging study. Each speci-

men was divided into two parts. One part was unstained

and used to establish autofluorescence compensation coef-

ficients, and the other part was stained with the cocktail

of p16INK4A-PE and Mcm5-APC antibodies. About

70 cells, including cells with differing morphology, were

imaged for each specimen. The average fluorescence

intensities were computed for each cell in imaging areas.

Figure C-1 gives an example of the DIC and fluorescence

images of a normal and an abnormal HSIL cell from one

of the HSIL cervical specimens. The autofluorescence in-

tensity of the cells in the PE and APC band has been

eliminated based on their autofluorescence intensity in the

FITC band. Figure C-1 indicates that the average PE and

Fig. 2. PE vs. APC fluorescence intensities of the HeLa cells stained withcocktail of isotypes (dark triangular symbol) and stained with cocktail ofp16

INK4A-PE and Mcm5-APC antibodies (light quadrangular symbol).





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APC intensities of the HSIL cell are significantly higher

than those of the normal cells.

The experiment also shows that most cells in the eleven

specimens had low stain intensities in both the PE and

APC bands. Only a small number of cells in the ASC-US,

LSIL, and HSIL specimens had high stain intensities.

This suggests that the biomarker overexpressed cells are

rare-events, which is similar to the morphology-based

Fig. C-1C-3. Fig. C-1. DIC (upper left), FITC (upper right), PE (lower left) and APC (lower right) images of a normal cell (a), and a HSIL dysplas-tic cell (b), from a HSIL cervical specimen. The numbers under the cells are the average fluorescence intensities of the cells. Fig. C-2. The dot plot(left) illustrates HeLa cells (red dots) identified and separated from normal cervical cells (blue dots) after staining with p16

INK4A-PE and Mcm5-APC

antibodies. The scatter plot (right) indicates the linear relationship between the number of spiked and the number of p16INK4A and Mcm5 positiveHeLa cells. Fig. C-3. Dot plots of PE (P16INK4A) vs. APC (Mcm5) immunofluorescence intensities of the cells in a negative (left) and a positive HSILcervical specimen (right). Each plot contains about 75,000 cervical cells.

LING ET AL.




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detection. The experiment also suggested that the overex-

pression of both the p16INK4A and Mcm5 biomarkers is

closely related to the abnormality of cell morphology.

Flow Cytometry Experiment

Spiking experiment. This experiment was conducted toshow the feasibility of biomarker-based flow cytometry in

the detection of rare cervical cancer cells among a large

number of normal cells in a cervical specimen. Aliquots

of normal cells were taken from six Pap test negative

specimens and combined to create a normal cervical cell

pool. The normal cells were counted and divided among

seven tubes, with each tube containing about 77,000 be-

nign squamous cells. One tube was left unstained for ref-

erence. The other six tubes were spiked with 10, 20, 50,

100, 500, and 1,000 HeLa cells using the serial dilution

method. The spiked samples were stained with the cock-

tail of p16INK4A-PE and Mcm5-APC antibodies.

The dot plot in the left panel of Figure C-2 illustratesan example of the PE versus APC intensities in the 500-

HeLa-spiked sample. The HeLa cells highly stained with

p16INK4A and Mcm5 (red dots) are identified and sepa-

rated from the normal cervical cells (blue dots). The scat-

ter plot in the right panel of Figure C-2 illustrates the lin-

ear relationship between the number of spiked and the

number of detected HeLa cells. The discrepancy between

the detected cells and the number of spiked cells could be

due to the following reasons: (1) the number of HeLa

cells that were actually added into each sample varied;

(2) cells were lost during the poststaining washing steps;

(3) a small portion of the samples could not be measured

due to the dead space between pipette and test tube; and(4) some HeLa cells did not have a high staining of

p16INK4A and Mcm5.

This study indicates that it is possible to use flow

cytometry to detect as low as 0.01% cancer cells among a

large number of normal cervical cells. The outcome

exceeded the expectation of detecting less than 0.1%

abnormal cells among normal cells, which is considered

by pathologists as being an acceptable limit for a cervical

cancer screening method.

Clinical specimens experiment. Thirty-two residual cer-

vical specimens from routine cervical cancer screening

were involved in this study. They were categorized as 15

negative and 17 positive (2 ASC-US, 1 LSIL, and 14

HSIL) cases. Each specimen was split into two aliquots.

One aliquot was unstained and used to measure the cell

autofluorescence in the three fluorescence bands: FITC,

PE, and APC. The other aliquot, containing around 75,000

cells, was stained with a cocktail of p16INK4A-PE and

Mcm5-APC antibodies and then run on the flow cytometer.

Figure C-3 shows two dot plots of a negative and a

positive (HSIL) specimen generated from flow measure-

ment. These two plots clearly show that the HSIL speci-

men has significantly more cells with high intensities in

both PE and APC bands than the negative specimen. The

high intensity in the PE and APC bands indicates that

both biomarkers p16INK4A and Mcm5 are overexpressed.

The detection threshold was set arbitrarily in this

experiment to maximize the separation between negative

and positive (ASC-US) specimens. In Table I, the clas-

sification of the thirty-two specimens determined by multi-

parameter flow cytometry is compared with the classifica-

tion by liquid-based Pap test. Using the Pap test as the

reference, the sensitivity and specificity of the flow

cytometry method to classify cervical specimens into

negative and positive (ASC-US) was 100 and93%, respectively.

Discussion

Autofluorescence Compensation

One of the major challenges in the use of flow cytometry

to measure biomarker expression of cervical cancer cells

is the autofluorescence problem. Fixed cervical cells have

very strong autofluorescence. Figure 3a shows a flow

cytometry plot of FITC versus PE of an unstained sample

that was mixed with HeLa and normal cervical cells. The

autofluorescence is present not only in the green band but

also in the yellow and even in red frequency bands. Inaddition, the cell-to-cell autofluorescence intensities can

vary over a 1,000-fold range in a specimen. Without cor-

rection for such a large variance of autofluorescence, it is

impossible to detect biomarker signals in PE and APC

bands. This is illustrated in Figures 3b and c, the dot plot

of the same sample but stained with p16INK4A-PE and

Mcm5-APC antibodies. These two figures indicate that

the PE and APC staining intensities of HeLa cells are

much lower than some of the normal cells that have high

autofluorescence in the same bands. Although cell-to-cell

autofluorescence has large variation, the dot plots suggest

that the intensities between the autofluorescence in the

yellow or red band and the autofluorescence in the green

band are linearly correlated among different cells. Using

this feature, the cell autofluorescence measured in the

FITC band (from the samples not stained with FITC

dyes) can be used to correct the autofluorescence in the

PE and APC bands on a cell-by-cell basis using a post-

compensation method. The ratios between the autofluores-

cence in PE or APC bands versus that in FITC band can

be determined beforehand from the unstained specimen.

Figure 3d illustrates the data in Figure 3b and c after

Table I. Comparison of the Classification of 32 Specimens BetweenFlow Cytometry and Pap Test

Positive in Pap test Negative in Pap test

Positive in flow cytometry TP 17 FP 1Negative in flow cytometry FN 0 TN 14





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autofluorescence compensation. HeLa cells are clearly

separated from normal cervical cells based on PE and

APC staining intensities.

The Measurement of Cervical Cell FluorescenceIntensity in Flow Cytometry

Another major challenge in the study, which is usually

not involved in the hematological application of flow

cytometry, is how to correctly measure the biomarker

expression levels in flow cytometry when cells of large

different sizes are mixed together. Cervical epithelial cells

in a sample can vary from 25 to 65 lm in size. The fluo-

rescence pulse integral (or area), often used in flow

cytometry to measure fluorescence intensity, is not appro-

priate in this case to compare the biomarker expression

(indicated by fluorescence dyes per unit volume or fluo-

rescence density) among cells of different sizes. For

example, the pulse integral of a small-size cell with high

biomarker expression may be smaller than a large-size

cell but with low biomarker expression. In this study,

pulse peak was used to estimate the fluorescence density

instead of pulse integral. As the size (2565 lm) of cervi-

cal cells is larger than the height (9 lm) of the excitation

laser beam in the flow cytometer, the pulse integral is

more significantly affected by cell size than the pulse

peak. The flow cytometry applications to large-size epi-

thelial cells are different from the applications to blood

cells, which are usually smaller than or comparable to the

excitation laser beam. A better way of estimating fluores-

cence density is to normalize pulse integral by pulse

width (or time-of-flight).42 However, pulse width mea-

surement from most commercially available flow cytome-

ters has a large variance. A slit-scanning system with

small focal spot size43 might provide a reliable measure-

ment of pulse width. A system with Coulter volume mea-

Fig. 3. (a) Dot plots of FITC vs. PE for an unstained cervical sample that was mixed with HeLa and normal cervical cells. ( b, c) FITC vs. PE andFITC vs. APC of the same sample in (a) but stained with p16

INK4A-PE and Mcm5-APC antibodies. HeLa cells were separated from normal cells

because of the additional stain intensity onto the autofluorescence intensity. (d) PE vs. APC of the stained sample after the autofluorescence in PE andAPC bands were compensated. HeLa cells, with high stain intensity in both PE and APC bands, were clearly separated from normal cells.

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surement may also be used to obtain a better estimation

of fluorescence density. How to modify flow cytometer

for epithelial cells analysis is still a topic needs to be

investigated. As pointed out by Dong et al., it is a crucial

step to obtain an optimal flow cytometry setting suitable

for analysis of epithelial cells.44

Summary and Future Research

This study demonstrated the feasibility of (1) using multi-

plex detection of p16INK4A and Mcm5 to detect dysplastic

cervical cells by immunofluorescence, (2) using multipara-

meter flow cytometry to detect rare-event dysplastic cells

from large background of normal cells, and (3) using mul-

tiparameter flow cytometry to identify positive cervical

specimens. Although the results were based on a limited

number of clinical specimens, this experiment demon-

strated the promise of using multiparameter flow cytometry

for biomarker-based cervical cancer screening. This molec-

ular-based, potentially high-throughput and automated

method is expected to provide an alternative/auxiliary

means of cervical cancer screening. The method developed

for cervical cancer screening in this study can be extended

to the diagnosis of other nonhematological cancer.

Future studies will make this technology more robust.

First, the threshold or gating to detect dysplastic cells was

arbitrarily set in this preliminary study. A cell sorting and

validation experiment is needed to optimize the threshold

setting and to reduce the false negatives and false positives

in the detection of abnormal cells. Second, the fluorescence

contrast between the biomarker positive and negative cells

needs to be enhanced, especially for the p16INK4A

bio-

marker. Third, cervical cells tend to cluster together. Toprovide enough cells in single suspension for flow cytome-

try measurement, sample preparation must include a proce-

dure of cluster desegregation. The potential solutions to

these problems will be investigated in future studies.

Acknowledgment

We thank Elizabeth Branch for her assistance in the prep-

aration of this manuscript.

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