DNA

Guidelines for DNA FCM Analysis of Fresh and/or Frozen Tumor Tissue, and the Interpretation of DNA Histograms

Measurements

Check the linearity of the histograms (e.g., using liver cell nuclei as controls).
At least 256-channel resolution should be used, although 1,024-channel resolution is preferable.
Use CRBC and TRBC nuclei as internal controls or normal tissue counterpart of the neoplastic cells.
Collect at least 15,000 events without any gating condition.
Analyze at a maximum rate of 300 events per second.
Adjust the gain of the fluorescence detector to include all cell populations in the histogram and to ensure that the background region above the last G2 peak is visible

Evaluation of the DNA Histogram

If possible scale up the ordinate to facilitate the detection of small G0/G1 peaks. Caution! Small peaks may be caused by aggregates

A normal scaled histogram with a possible aneuploid G0/G1 peak.
C = CRBC; T = TRBC Histogram A with the ordinate scaled up, thus enabling detection of a small aneuploid G0/G1.

Scale up the abscissa to facilitate the detailed examination of the shape of the 2C G0/G1 peak with regard to skewness and bimodality. If the peak manifests bimodality the sample may be classifiable as non-diploid. The CV is calculated in percent, thus CV = SD/MV × 100, where SD is the standard deviation of the full peak and MV is the mean value of the peak.


Normal scaled histogram showing a diploid DNA stemline.	Histogram C with the abscissa scaled up. The G0/G1 peak shows a skewness on its left side compared to the symmetric TRBC peak

Normal scaled histogram showing a possible near diploid DNA stemline.	Histogram E with the abscissa scaled up, thus verifying a biomodal pattern indicating the presence of a near-diploid aneuploid DNA stemline.

Ploidy status

Definition of ploidy status (Hiddemann et al.: Cytometry 5, 445-446, 1984), one peak = diploid (irrespective of DI). Nota bene! In cases of diploidy the presence of cancer cells on the imprint should be verified.
Two or more peaks = non-diploid.
In the following instances ploidy status is impossible to determine, and a new piece of the tumor sample should be analyzed.

Cell-poor sample
Broad G0/G1 peak in single peak cases (CV >2 times the median value for the diploid G0/G1 peak of the laboratories´ own materials).
A skewed G0/G1 peak in single peak cases (see C and D; cf. with the shape of the TRBC peak).
Presence of a small but equivocal non-diploid peak (reanalysis can be performed without CRBC and TRBC if the equivocal peak is suspected to consist of aggregates).

Reanalysis of new tissue material

If no new tissue material is available, the results from the first analysis (according to steps 1-4 above) are considered impossible to interpret. If after reanalysis the CV is still high or the distribution of the G0/G1 peak is still skewed, the sample is considered to be diploid (though a note should be made of the shape of the peak). If the new sample is also cell-poor, or a small equivocal peak is still present, the histogram is deemed impossible to interpret.

Calculation of DI

Alternative I

Zero-point adjustment according to Vindelöv et al. (Cytometry 3, 328-331, 1983).
The peak closest to DI = 1.00 is deemed to the dipliod.
The DI of this peak is set to 1.00.
All other G0/G1 peaks are then related to this diploid DI.

Alternative II

Zero-point adjustment according to Vindelöv et al. (Cytometry 3, 328-331, 1983).
Relate all G0/G1 peaks to the DI of the DI of the TRBC control.

Alternative III

Relate all G0/G1 peaks to the DI of the normal diploid peak.

S-Phase Fraction ñ SPF

SPF should be calculated in the following situations.

If the G0/G1 peak for the population being analyzed for SPF represents 15% or more of the total number of events in the histogram (excluding CRBC+TRBC).
If the G0/G1 peak contains at least 1,000 events.
If no confounding debris function is present in the S-phase region.
If the G2 peak is visible.

Evaluation

At present no particular S-phase estimation method can be recommended, although the following two principles are available.

Parametric
a
ModFit LT(Verity Software House), MultiCycle (Phoenix Flow Systems) and PolyModel (Becton Dickinson). In these procedures the SPF is considered to be represented by a polynomial function of 0 order.
b
ACAS DNABase. S-phase represented by multiple 0-order polynomials with broadened Gaussians.
- All G1 and G2 peaks are fitted as normal distributions.
- Normal distribution is also fitted to any aggregate peak(s) present.

When the SPF for the non-diploid populations is calculated, owing to the fitting of normal distribution (the two steps above), correction is considered to have been made for diploid S and G2 nuclei for the aggregates (e.g. from diploid and non-diploid nuclei).
Together with ModFit LT, MultiCycle and ACAS DNABase it is also possible to compensate the SPF for debris.

Non-parametric; Baisch planimetric method
a
Manual procedure:
Expand the ordinate in order to more easily find a representative S-phase region.


Normal scaled histogram showing one diploid and one aneuploid DNA stemline respektively.	Histogram G with the ordinate scaled up in order to more easily find a representative region for the manual planimetric estimation of the SPF for the aneuploid DNA stemline

The S-phase is fitted with a rectangular distribution. Avoid any peaks representing aggregates or confounding debris. The rectangular distribution is preferably marked at the part of the S-phase region nearest to the G2 peak.

Extrapolate the rectangular distribution to the distributions for the entire S-phase region (from the G1 to the G2 peak).

b
Automatic procedure:
R_min (Stål and Baldetorp, Cytometry 33, 328-331,1998).

Interpretation

Mean SPF for near-diploid cell populations (near-diploid being defined as DI < approximaterly 1.3 and no separation of the corresponding G2 peaks).
Mean SPF for adjacent multiploid cell populations.
For other multiploid cases the SPF is estimated, if possible, for that non-diploid cell population with the greatest number of events.
Only one S-phase estimation in each histogram.
No estimation is made of the diploid SPF in non-diploid cases.

Extended basic rules for optimized DNA FCM with emphasis on automatic interpretation using ModFitLT™.

This continuation from “Guidelines for DNA FCM analysis of fresh and/or frozen tumor tissue and the interpretation of DNA histograms” is the result from experiments and discussions created by Dr. Bruce Bagwell (President of Verity Software House Inc, http://www.vsh.com) and Dr. Bo Baldetorp (Chaiman of the Nordic DNA User’s Group, bo.baldetorp@med.lu.se).

Part 1

I. Acquisition Rules

A. Parameter

The DNA fluorescence parameter should be either a linear integral or area type of the fluorescence intensity pulse signal. It is important to maintain a consistent gain setting. See further under point 1.F

B. Linearity

The linearity of the DNA fluorescence amplifier should be tested. (Plastic beads should be used for testing the linearity of the instrument. Testing the stoichiometry, i. e. the linearity of the staining, liver cells (DNA content: 2C, 4C and 8C) are preferable). Non-linear amplifiers should not be used for DNA analysis.

C. Discriminator

Events should be discriminated on the DNA fluorescence parameter only (e.g. red fluorescence for Propidium Iodide).

The discriminator level should be as low as possible without creating a debris peak that is greater than the highest G0G1 peak.

D. Gating

Gating should not be performed during acquisition. Gating is only recommended for multiparameter DNA histograms such as cytokeratin vs DNA or BrdUrd vs DNA. Gating on light scatter is not recommended due to the heterogeneity of the distribution. Signal processing gating, signal peak height vs signal peak area, to eliminate aggregates is only recommended if the aggregates are clearly and completely separated from singlet particles which is usually only true for experimental tissue culture cell lines.

E. Number of Events and Resolution

Simulation studies indicate that for accurate S-Phase estimates, there should be an average of approximately 100 events per channel between the lowest G1 and highest G2 of the histogram when the resolution is 256 channels. If a histogram has its diploid G0G1 on channel 50 and the last G2 of an aneuploid population is at 200, there should be at least 15,000 events between channels 50 and 200. If the desired resolution is 1024 channels all requirements should be increased by the factor 4.

F. Location of diploid G0G1

The position of the diploid G0G1 peak should be always placed in about the same channel. For 256 channel histograms the recommended location is channel 50. For 1024 channel histograms (not normally recommended), the location is channel 200. Thus, in most cases there will be sufficient numbers of channels, both leftmost and rightmost, containing signals from only debris and aggregates making it possible for ModFitLT to make a realistic fit of the total background.

G. Changing Gains

1. Normally change the gain to center the DNA diploid peak on a particular channel (e.g. 50 in a 250 channels histogram).

2. When a hyper-tetraploid population is observed during acquisition, it is desirable to reduce the gain so that its G2M and some channels consisting of only background are visible in the uppermost channels.

3. Note, after adjusting gain, acquisition must be restarted. Gain should be reset to the normal location when running the next sample.

II. Analysis Rules for ModFitLT 3.0 and upgrades

A. Run the whole batch of histograms in automode after you have set up the appropriate prerequisites for ModFitLT.

B. Reviewing the batch of reports and reanalyze, including the AutoLinearity function enabled, after adjustments according to below.

A: Model Selection Check

The most important step in analyzing DNA histograms in a consistent manner is checking the correct ploidy model for a particular DNA histogram. In some cases this process may require several analyses to achieve the correct and optimal fit, i.e. the RCS value should be as low as possible (< 3.0). Use the rules below to help guide you through this process.

1. General Considerations

a) If two model components are of similar shape and are highly overlapped (>75%) it may be necessary to add additional constraints to the model or, in the worse case, disable the model component of lesser importance.

b) If a G2M peak is clearly visible and well-defined, allow its mean to be fitted (float).

(1) If a floating G2M yields a G2/G1 ratio that is outside the expected linearity range (e.g. 1.2-1.8, or > 2.0), make the G2’s mean and standardard deviation dependent on G1 by the appropriate linearity factor (e.g. 1.95). We recommend the G2-peaks to be dependent!!!!!!

c) Always model S-Phase as a single, broadened rectangle.

d) After the appropriate model is selected, optimize the linearity settings in the cell-cycle analysis software to the data. In most situations the linearity factor is always the same, but may differ between laboratories.

e) Try to standardize the configuration, peak finder and autoanalysis settings optimal for your histograms. Thus, each laboratory will have its own settings which may differ slightly between different laboratories.

f) When choosing between two very similar models, select the one that gives consistent results with slightly different range settings.

An example of this rule might be when trying to use an aneuploid model with a near-tetraploid type of histogram. If the aneuploid model only works with very specific range settings, choose the tetraploid model instead.

2. Tetraploid Model Selection

a) Only select a tetraploid model if the DI is close to the expected tetraploid G0G1 and to the diploid G2/G0G1 ratio (should correspond to the linearity factor). Furthermore, there should be a peak that appears larger than an underlying diploid G2M population at 4C and a corresponding peak at (8C) that not only constitutes of aggregates.

If there is a peak at 6C that is larger than the peak at 8C, then there is a significant chance that the 8C peak is an aggregate.

If the diploid G2M after aggregate correction is equal to or greater than 15% of the estimated events of the diploid cell population and the number of events of the 8C peak > 6C peak, choose the tetraploid model.

If G2/M > 15% as above, and 8C < 6C, then choose the diploid model.

b) Choose a tetraploid model over an aneuploid model if the diploid G2M cannot be modeled properly because it overlaps too significantly with an aneuploid G0G1.

If there is doubt on whether to use a tetraploid or aneuploid model, try using the aneuploid model first and choose the tetraploid model if the diploid G2M is poorly estimated.

The most common manifestations of poorly modeled diploid G2M peaks are either under-estimation (zero SPF) or over-estimation (>15%).

3. Aneuploid Model Selection

a) Only choose this model if the potential aneuploid’s G0G1 cannot be explained as an aggregate or some other part of another cycle (e.g. G2M).

4. Near-diploid Model Selection

a) Choose the near-diploid model (DI<1.3) (also hypo-diploidy) if the two G0G1 peaks can be clearly distinguished, a bimodality is evident, and the resulting fit seems appropriate.

b) For very near-diploids, it may be necessary to force the standard deviations of the two G0G1 model components to be equal to yield an appropriate fit.

5. Hypo-diploid Model Selection

a) Only select when there are standards or normal controls that fix the expected diploid G0G1 position.

b) If the hypodiploid G0G1 overlaps one of the standards, disable the standard model component and re-model (see Rule A1a).

6. Skewed G0/G1 Peaks

Skewness may reflect a close near-diploidy, not visible as a bimodal pattern, where one of the two peaks contains a higher number of events than the other. To get an optimal fit, the near-diploid model should be selected and if necessary force the standard deviations of the two applied G0G1 peaks to be equal.

B. Range Positions Check

The most common reason for uncorrelated results between two fits using the same model is inattention to range positions. Do not change a range setting unless it is absolutely necessary to do so.

7. Debris Range

a) The debris range should cover the whole histogram. The beginning of the debris range should correspond to the channel with the highest debris counts (see Figure 1, Range: Debris for an examples of correct and incorrect placements).

8. Peak Ranges

a) Center range about the peak and make sure estimates appropriately fit the data (see Figure 1, Range: Peak G0G1 and Range: Peak G2M examples of correct and incorrect placements).

b) Exceptions to centering the range are for near-diploid and near-tetraploid G0G1 peaks. These ranges need to be displaced to yield reasonable estimates for the underlying peaks.

c) In case of skewed peak where the near-diploid model is selected, the peak range of the first G0G1 peak should cover the left flank and the second G0G1 peak range should cover the right flank respectively.

III. Figures

Figure 1

Rule Description	Correct	Incorrect #1
Range: Debris
Range: Peak G0G1
Range: Peak G2M

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Part 2

Evaluation of flowcytometric DNA analysis data from formalin fixed-and-paraffin embedded tissue:

The same general principles as for fresh/frozen tissue samples should be followed for DNA ploidy and S-phase estimation, as described in The Guidelines (http://www.sfff.se/dnaguidelines.html)

All laboratories have to determine their own settings or prerequisites for ModFitLT to work optimally. This is valid for all starting materials and applications.

Features one has to consider of formalin fixed and paraffin embedded cell and tissue materials: 1.) DNA may be partly degraded, 2.) The staining uptake by DNA may be less compared to in fresh and frozen tissue, 3.) A higher variation in staining intensity may be expected within a certain DNA stemline, thus generating a higher CV, 4.) Stoichiometry may not be the same as for fresh/frozen samples.

Usage of external standards in conjunction to the test sample is not recommended.

If the CV of the diploid G0/G1-peak exceeds 8% or the peak is with evidence skewed, the sample should be re-analyzed. If either the high CV or the skewness persists the analysis may not be interpretable regarding DNA ploidy status. In case of skewness caused by peaks having low CV’s a total S-phase may be considered.

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(All DNA histograms below, processed by ModFit LT 3.1, are illustrative for different DNA content distributions. The DNA histograms are available as FCS files and may be downloaded for examination with the ModFitLT or other FCS interpretation softwares as well, installed in your computer).

Directions on how to use ModFitLT™ on DNA histograms from formalin fixed-and-paraffin embedded tissue:

Fitting of Internal Standards should always be switched off.

AutoDebris function should always be switched on (use the single-cut mode).

Disable the AutoAggregate function for diploid and/or near-diploid cases (DI< 1.3). In all other cases this function should be active. (We are not able to define hypo-diploidy in formalin and paraffin embedded samples).

Analyze the histogram or the batch of selected histograms. Review the reports and do the necessary adjustments before a second analysis.

Finally, reanalyze the modeled histogram with the Auto Linearity function enabled!!!

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A typical DNA diploid histogram.

Diploid DNA histogram: The G2-peak at 4C<15% of the estimated events of the diploid cell population, and 6C>8C.

File: 001.fcs

In Modfit LT, choose the diploid model with Auto Aggregates mode switched off:

File analyzed: 001.fcs

Date analyzed: 29-Jan-2006

Model: 1Dn0n_DSD

Analysis type: Manual analysis

Diploid: 100.00 %

Dip G1: 83.73 % at 47.87

Dip G2: 9.97 % at 95.73

Dip S: 6.30 % G2/G1: 2.00

%CV: 4.82

Total S-Phase: 6.30 %

Total B.A.D.: 8.27 % no aggs

Debris: 30.97 %

Aggregates: 0.00 %

Modeled events: 16016

All cycle events: 11056

Cycle events per channel: 226

RCS: 5.997

Since the Auto Aggregate function is disabled, no fitting of the aggregates will occur, thus the estimated curve fitting will deviate more from the raw data and the RCS will thus become higher than if the modeled component of aggregates is considered in the total model. However, the S-phase fit seems to be of reasonable significance.

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Next histogram, diploid or…….?

This histogram (from an analysis of fresh-frozen breast cancer biopsy including chicken and trout nuclei as internal control) illustrates a pattern where 4C > 20% of all events in the diploid cell population, and 6C > 8C. One reasonable explanation for this pattern may be in this case that the patient received neoadjuvant treatment (chemotherapy) before surgery, resulting in a G2-block in the cell cycle. The histogram is deemed to represent a diploid pattern:

File: 002.ASC

File analyzed: 002.ASC

Date analyzed: 29-Jan-2006

Model: 1Dn2n_DSD

Analysis type: Manual analysis

Diploid: 100.00 %

Dip G1: 72.99 % at 49.98

Dip G2: 23.72 % at 98.96

Dip S: 3.28 % G2/G1: 1.98

%CV: 2.47

Total S-Phase: 3.28 %

Total B.A.D.: 8.13 % no aggs

Stnd 1: 6.56 % at 18.90 DI: 0.38

Dip G1 Ratio: 2.64 %CV: 3.04

Stnd 2: 6.61 % at 40.91 DI: 0.82

Dip G1 Ratio: 1.22 %CV: 1.79

Debris: 27.34 %

Aggregates: 0.00 %

Modeled events: 17163

All cycle events: 10829

Cycle events per channel: 217

RCS: 5.357

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When is a sample judged DNA tetraploid?

Below are two different DNA histograms where the peak at 8C > 6C:

In case #1, the peak at 4C > 20% of the estimated events of the DNA diploid cell population when processed with the diploid model. Because of the high CV’s of all peaks, the tetraploid model is recommended even if the DI-value (DI=2.08) of the non-diploid cellpopulation may be out of the tetraploid DI-range.

In case #2, the 4C peak < 10% when estimated with the diploid model. The CV’s of all peaks are relative low and thus the Aneuploid model is recommended.

Despite the small tetraploid population in both cases and the estimated high fractions of S phase events, the calculated S%- values seem to be significant because of the considerable high G2 fractions.

Case #1:

File analyzed: 003.fcs

Date analyzed: 29-Jan-2006

Model: 2DA0n_DSn_TSD

Analysis type: Manual analysis

Diploid: 68.68 %

Dip G1: 92.00 % at 47.80

Dip G2: 8.00 % at 100.10

Dip S: 0.00 % G2/G1: 2.09

%CV: 7.08

Tetraploid: 31.32 %

An1 G1: 53.83 % at 100.10

An1 G2: 15.44 % at 200.21

An1 S: 30.73 % G2/G1: 2.00

%CV: 6.97 DI: 2.09

Total Aneuploid S-Phase: 30.73 %

Total S-Phase: 9.63 %

Total B.A.D.: 26.71 %

Debris: 37.21 %

Aggregates: 5.65 %

Modeled events: 19354

All cycle events: 11060

Cycle events per channel: 72

RCS: 1.444

Case #2:

File analyzed: 004.fcs

Date analyzed: 16-Mar-2006

Model: 2DA0n_DSD_ASD

Analysis type: Manual analysis

Diploid: 85.24 %

Dip G1: 98.18 % at 49.01

Dip G2: 0.00 % at 94.11

Dip S: 1.82 % G2/G1: 1.92

%CV: 5.36

Aneuploid 1: 14.76 %

An1 G1: 48.21 % at 101.80

An1 G2: 26.69 % at 195.46

An1 S: 25.09 % G2/G1: 1.92

%CV: 4.07 DI: 2.08

Total Aneuploid S-Phase: 25.09 %

Total S-Phase: 5.25 %

Total B.A.D.: 25.30 %

Debris: 43.28 %

Aggregates: 4.92 %

Modeled events: 18623

All cycle events: 9646

Cycle events per channel: 65

RCS: 1.324

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S-PHASE estimations being illustrated in histograms from DNA FCM on fresh-frozen or formalin-fixed and paraffin embedded tumor tissue samples.

In case of near-diploidy (DI< 1.3), the total S-phase should be considered, regardless of the size of the individual G0/G1-peaks.

File analyzed: 005.fcs

Date analyzed: 7-Feb-2005

Model: 2Dn0n_DSD_ASD

Analysis type: Manual analysis

Diploid: 50.76 %

Dip G1: 98.64 % at 49.38

Dip G2: 1.36 % at 97.77

Dip S: 0.00 % G2/G1: 1.98

%CV: 2.62

Aneuploid 1: 49.24 %

An1 G1: 66.62 % at 59.02

An1 G2: 7.13 % at 116.85

An1 S: 26.25 % G2/G1: 1.98

%CV: 4.97 DI: 1.20

Total Aneuploid S-Phase: 26.25 %

Total S-Phase: 12.92 %

Total B.A.D.: 9.24 % no aggs

Debris: 28.56 %

Aggregates: 0.00 %

Modeled events: 19350

All cycle events: 13823

Cycle events per channel: 202

RCS: 1.427

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A non-diploid cellpopulation should contain at least 15% of the estimated events in the region from the first G0/G1 peak up to the uppermost G2 (debris and aggregates subtracted). If the CV:s are low ~ 3 %, and the RCS < 3.0%, the S-phase may be reported for even smaller non-diploid populations, ~ 10% of the estimated events.

Case #1

File analyzed: 006.fcs

Date analyzed: 7-Feb-2005

Model: 2DA0n_DSD_ASD

Analysis type: Manual analysis

Diploid: 82.08 %

Dip G1: 98.90 % at 50.83

Dip G2: 0.00 % at 100.65

Dip S: 1.10 % G2/G1: 1.98

%CV: 3.23

Aneuploid 1: 17.92 %

An1 G1: 69.55 % at 73.89

An1 G2: 9.93 % at 146.30

An1 S: 20.51 % G2/G1: 1.98

%CV: 4.90 DI: 1.45

Total Aneuploid S-Phase: 20.51 %

Total S-Phase: 4.58 %

Total B.A.D.: 14.48 %

Debris: 29.05 %

Aggregates: 5.55 %

Modeled events: 19372

All cycle events: 12670

Cycle events per channel: 131

RCS: 3.049

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Case #2 (fresh/frozen sample including standard cells (chicken and trout red blood cells))

File analyzed: 007.fcs

Date analyzed: 5-Feb-2006

Model: 3DA2n_DnD_HSD_ASD

Analysis type: Manual analysis

Diploid: 3.14 %

Dip G1: 99.76 % at 47.88

Dip G2: 0.24 % at 94.80

Dip S: 0.00 % G2/G1: 1.98

%CV: 1.85

Hypo-diploid: 80.54 %

An1 G1: 95.71 % at 45.11

An1 G2: 2.18 % at 89.32

An1 S: 2.11 % G2/G1: 1.98

%CV: 1.74 DI: 0.94

Aneuploid 2: 16.32 %

An2 G1: 91.27 % at 71.18

An2 G2: 0.96 % at 140.93

An2 S: 7.77 % G2/G1: 1.98

%CV: 2.27 DI: 1.49

Total Aneuploid S-Phase: 3.06 %

Total S-Phase: 2.97 %

Total B.A.D.: 3.23 %

Stnd 1: 2.96 % at 17.21 DI: 0.36

Dip G1 Ratio: 2.78 %CV: 2.98

Stnd 2: 2.59 % at 38.09 DI: 0.80

Dip G1 Ratio: 1.26 %CV: 1.56

Debris: 6.59 %

Aggregates: 0.33 %

Modeled events: 19692

All cycle events: 17309

Cycle events per channel: 184

RCS: 1.753

In this particular case of multiploidy the S-phase of the subpopulation with the highest DI should be reported even though it doesn’t contain the greatest number of events among the non-diploid subpopulations.

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Case #3 (fresh/frozen sample including standard cells)

File analyzed: 008.fcs

Date analyzed: 14-Aug-2005

Model: 2DA2n_DSD_ASD

Analysis type: Automatic analysis

Diploid: 87.85 %

Dip G1: 98.61 % at 45.63

Dip G2: 0.64 % at 89.44

Dip S: 0.75 % G2/G1: 1.96

%CV: 2.88

Aneuploid 1: 12.15 %

An1 G1: 70.97 % at 70.01

An1 G2: 11.92 % at 137.23

An1 S: 17.11 % G2/G1: 1.96

%CV: 4.91 DI: 1.53

Total Aneuploid S-Phase: 17.11 %

Total S-Phase: 2.74 %

Total B.A.D.: 6.68 %

Stnd 1: 5.55 % at 16.70 DI: 0.37

Dip G1 Ratio: 2.73 %CV: 3.30

Stnd 2: 1.61 % at 36.82 DI: 0.81

Dip G1 Ratio: 1.24 %CV: 2.44

Debris: 21.49 %

Aggregates: 2.61 %

Modeled events: 19673

All cycle events: 13824

Cycle events per channel: 149

RCS: 1.569

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In case of multiploidy (see below) and if the aneuploid G0G1 peaks having close DI-values, the Total Aneuploid S-phase should be considered:

File analyzed: 009.ASC (fresh/frozen sample)

Date analyzed: 30-Jan-2006

Model: 3DA2n_DSD_ASD_ASD

Analysis type: Manual analysis

Diploid: 43.16 %

Dip G1: 89.55 % at 49.64

Dip G2: 0.00 % at 94.80

Dip S: 10.45 % G2/G1: 1.91

%CV: 2.77

Aneuploid 1: 16.02 %

An1 G1: 87.46 % at 69.22

An1 G2: 12.54 % at 132.20

An1 S: 0.00 % G2/G1: 1.91

%CV: 1.97 DI: 1.39

Aneuploid 2: 40.82 %

An2 G1: 58.99 % at 74.92

An2 G2: 16.42 % at 143.09

An2 S: 24.59 % G2/G1: 1.91

%CV: 3.40 DI: 1.51

Total Aneuploid S-Phase: 17.66 %

Total S-Phase: 14.55 %

Total B.A.D.: 12.67 %

Stnd 1: 6.20 % at 18.36 DI: 0.37

Dip G1 Ratio: 2.70 %CV: 2.84

Stnd 2: 7.20 % at 39.93 DI: 0.80

Dip G1 Ratio: 1.24 %CV: 1.85

Debris: 23.27 %

Aggregates: 4.93 %

Modeled events: 18423

All cycle events: 11334

Cycle events per channel: 120

RCS: 2.122

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The next case of multiploidy has two aneuploid cellpopulations very close to the diploid population (the diploid G0/G1 peak appears as a left shoulder). The Total S-phase is reported.

File analyzed: 010.fcs (fresh/frozen)

Date analyzed: 22-Jun-2004

Model: 3DA2n_DnD_ASD_ASD

Analysis type: Manual analysis

Diploid: 20.49 %

Dip G1: 94.02 % at 47.61

Dip G2: 5.98 % at 93.79

Dip S: 0.00 % G2/G1: 1.97

%CV: 1.96

Aneuploid 1: 74.47 %

An1 G1: 96.28 % at 50.09

An1 G2: 3.67 % at 98.67

An1 S: 0.05 % G2/G1: 1.97

%CV: 1.98 DI: 1.05

Aneuploid 2: 5.04 %

An2 G1: 66.95 % at 56.69

An2 G2: 6.24 % at 111.68

An2 S: 26.81 % G2/G1: 1.97

%CV: 4.03 DI: 1.19

Total Aneuploid S-Phase: 1.74 %

Total S-Phase: 1.39 %

Total B.A.D.: 8.59 %

Stnd 1: 5.73 % at 17.25 DI: 0.36

Dip G1 Ratio: 2.76 %CV: 2.67

Stnd 2: 5.58 % at 38.67 DI: 0.81

Dip G1 Ratio: 1.23 %CV: 1.74

Debris: 19.77 %

Aggregates: 4.56 %

Modeled events: 15427

All cycle events: 10273

Cycle events per channel: 158

RCS: 1.485

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Importance of re-analysis:

The two DNA histograms below are from a formalin fixed and paraffin embedded sample (ovarian cancer) showing the advantage of re-analyzing a sample. The first analysis resulted in a broad and skewed G0G1 peak at 2C. The re-analysis of an adjacent 50 micron section resulted in a histogram showing an evident near-diploid pattern (bimodality in the 2C region).

First analysis