THE IN VIVO PROLIFERATION KINETICS OF HUMAN SOLID TUMOURS.

A thesis submitted to the University of Cambridge for the degree of Master of Surgery

by DAVID ANTHONY REW, MA MB BChir FRCS Pembroke College, Cambridge 1975-78

The University Surgical Unit, Southampton General Hospital, Tremona Road, Southampton S01 6HU

March 1990
The last decades of the nineteenth century were … occupied with the detailed study of the morphology of tumours, the separation of the varieties of disease, the elucidation of histogenesis and the writing of the natural history of malignant diseases. The twentieth century opens as the experimental era with the systematic study of tumours throughout the animal kingdom. It seems likely to become noteworthy as the period of specific aetiological investigations which promise to widely separate many neoplastic diseases formerly held to be closely related. It may, thereby, prove to be the era of successful therapeutics and prophylactics.

– James Ewing

in: Neoplastic Diseases. Philadelphia: WB Saunders and Co., 1919.

SHORT SUMMARY

The study of tissue and tumour cell kinetics is one approach to better understanding of human tumour biology and to the formulation of better treatment strategies. Past efforts to measure in vivo the duration of cell cycle phases has been severely handicapped by the need to use radioisotopes and to take sequential biopsies. The drug 5-bromo-2-deoxyuridine (BRdU) is a safe, ethical alternative to tritiated thymidine for in vivo labelling of DNA during the S phase of the cell cycle. The label can be detected by conventional histochemistry, and by multiparameter flow cytometry. The latter provides measurements of ploidy, phase related DNA labelling, and the duration of the S phase and of the potential doubling time (Tpot) of the tumour or tissue. These parameters have not been characterised in many types of tumour, nor have their relationships to prognosis or to treatment strategies been explored.

A series of 100 colorectal adenocarcinomas, 53 invasive ductal carcinomas of the breast, 35 gastrooesophageal carcinomas and a small number of lymphomas, melanomas, sarcomas and squamous carcinomas were studied prospectively. Hospital ethical committee approval and informed patient consent was obtained for a single intravenous injection of 250mg BRdU prior to conventional surgery for malignant disease. The DNA index, total and aneuploid labelling indices, S phase duration and Tpot were measured. No correlations were found to exist between these parameters and current prognostic indicators. Long term follow-up will be undertaken to relate the data to clinical outcome.

The Tpot of gastrointestinal tumours was typically less than ten days, whereas the actual volume doubling time from clinical experience is known to be of the order of 100 days or more. This discrepancy is largely produced by a high rate of cell loss by exfoliation and necrosis in these tumours. A validation study of the Tpot concept was undertaken using the
A study was undertaken of mucosal kinetics using tissue from resection specimens throughout the gastrointestinal tract. An original method is described for the calculation of the crypt labelling index and crypt cell turnover rate combining histological and flow cytometric data. A good correlation was obtained with previously published data. The method offers advantages over previous methods of studying mucosal kinetics in normal and disease states.

The counting of confluent features of interest such as labelled nuclei in stained tissue sections is laborious and prone to observer errors. An original application of the automated planar image analyser is described which allows automation of the measurement of the labelling index in peroxidase stained tissues. This has a number of uses in clinical research in histopathology.

A reliable intrinsic marker of tumour proliferation would offer substantial practical advantages over BrdU labelling. The “p62” protein product of the putative oncogene c-myc was measured by multiparameter flow cytometry in colorectal tumours and tissues. Results were compared with BrdU labelling in the same specimens. p62c-myc levels were found to be unexpectedly high in normal and polyposis coli mucosa, raising new questions about the function of the c-myc gene.

The combination of in vivo BrdU labelling and multiparameter flow cytometry has been demonstrated to be valid and practical in the study of tumour and tissue kinetics. The possible use of the technique in devising better chemotherapy and radiotherapy regimes are discussed. Future lines of research are considered.

STATEMENT OF ORIGINALITY

This thesis describes the original work and ideas of the author. Clinical material was selected and collected by the author with the exception of some breast tumours which were collected by Mr Ian Campbell, Research Fellow at the University Surgical Unit, Southampton. Flow cytometry of bromodeoxyuridine labelled tissues was performed under the supervision of Dr. George Wilson. The analyses of the p62c-myc protein were performed under the supervision of Dr Jim Watson and Miss Hilary Cox. Invaluable suggestions were assimilated from many clinical, scientific and technical colleagues.

STATEMENT OF ETHICS

Hospital Ethical Committee approval was obtained separately from the Portsmouth and the Southampton Hospitals ethical committees before the study. All patients studied gave informed consent prior to a single intravenous injection of bromodeoxyuridine before surgery.

All procedures involving animals were carried out humanely under ether anaesthesia. Animals were maintained under normal regulatory procedures in the Animal House, Southampton University.

PUBLICATION

The work described in this thesis has not been previously published other than in Abstract form in the British Journal of Surgery, Proceedings of the Surgical Research Society meeting in Liverpool, January 1990 (in press).

ACKNOWLEDGEMENTS

This Thesis would not have been possible without the support of the many clinicians and scientists who have given generously of their time, advice and resources. Mr. Paul C Weaver, MD FRCS gave his wholehearted support to the proposal for this project while I was his Registrar at St. Mary’s Hospital, Portsmouth and provided much advice subsequently. The idea was derived from a lecture by Professor Julie Denekamp PhD, Director of The Gray Laboratory of the Cancer Research Campaign. Dr. Nic McNally PhD, Head of the Department of Cell Biology and Dr. George Wilson PhD welcomed me as an ex officio member of their group at the Gray Laboratory and taught me the intricacies of their subject. Miss Christine Whitsed, BSc, Laboratory Scientist provided helpful technical support.

Professor Irving Taylor, MCh FRCS kindly guided and supervised the project with a generous freedom of movement from the University Surgical Unit, Southampton, and made available the resources and experience of his Department. Dr. Alan Cooper provided much help with the animal experiments.

Mr. Michael Thompson, MD FRCS and Mr. Colin Johnson MChir FRCS, provided access to their patients. Dr. Rose Buchanan, MRC Path, Consultant Pathologist and Mr Robert Stradling, MLSO, provided histological expertise at St Mary’s Hospital.

Dr Jim Watson directed the studies on the c-myc protein at the Hills Road, Cambridge Laboratory of the Medical Research Council. Miss Hilary Cox, Technical officer, provided much additional help. Ms. Elizabeth Adam and Professor Mayer provided advice and facilities at the Section of Human Morphology, University of Southampton for the studies described in Chapter 5.

vi.
Funding for my salary was provided by The Cancer Research Campaign. The Wessex Regional Health Authority Research Committee funded the purchase of drugs and other expenses with a generous grant. Additional costs were kindly borne by the Gray and Hills Road Laboratories. Dr Chris Dean of the ICRF Hybridoma Unit, Royal Marsden Hospital, Sutton kindly supplied the anti BRdU monoclonal antibody.

I am indebted to all patients who consented to partake in this experimental work. Without them no progress would have been made.

This thesis was prepared and typed by the author on an Amstrad 1640 Personal Computer with a Hard Disk facility. Word processing, database and spreadsheet operations were performed using the SMART software package Version 2, (Innovative Software Inc., 1986). Statistical procedures were performed using Statgraphics software (STSC Inc., Maryland, USA). The graphics were prepared using Harvard Graphics (Software Publishing Corporation, USA). Dr John Francis of Southampton University Haematology Department provided valuable advice on the use of the software. Other illustrations were prepared at Southampton General Hospital Teaching Media Department.

I am indebted to my wife Victoria for her help with the preparation of the manuscript.

CONTENTS

Title Page
Quotation
Short Summary
Statements of Originality and Ethics
Acknowledgements
Index of chapter contents
List of Tables, Figures and Appendices
Glossary of abbreviations

CHAPTER 1. INTRODUCTION AND LITERATURE REVIEW.

Sections 1:1:1-11.
Cell cycle theory and historical methods of measurement.
Sections 1:2:1-16.
The measurement of cell kinetics using BRdU and flow cytometry.
Pages 1:1-39

CHAPTER 2. IN VIVO PROLIFERATION OF COLORECTAL CARCINOMAS.

2:1. Chapter abstract.
2:2. Proliferation in human colorectal carcinomas
2:3. Materials and methods.
2:4. Results.
2:5. Discussion.
2:6. The Tpot in an animal model.
Pages 2:1-41

CHAPTER 3. PROLIFERATION IN COLORECTAL MUCOSA AND ADENOMAS.

3:1. Chapter abstract.
3:2. Introduction.
3:3. Materials and methods.
3:4. Results.
3:5. Discussion.
Pages 3:1-17

CHAPTER 4. THE PROLIFERATION OF GASTRO-OESOPHAGEAL CARCINOMAS AND MUCOSA.

4:1. Introduction and literature review.
4:2. Materials and methods.
4:3. Results
4:4. Discussion.
Pages 4:1-16

CHAPTER 5. AUTOMATED ANALYSIS OF IMMUNOPEROXIDASE STAINING.

5:1. Introduction.
5:2. Materials and methods.
5:3. Results
5:4. Discussion.

Pages 5:1-10

CHAPTER 6. THE IN VIVO KINETICS OF HUMAN BREAST CARCINOMAS.

6:1. Introduction and review
6:2. Materials and methods.
6:3. Results.
6:4. Discussion.

Pages 6:1-17

CHAPTER 7. IN VIVO PROLIFERATION OF OTHER HUMAN TUMOURS.

7:1. Introduction.
7:2. The brain and central nervous system.
7:3. Squamous carcinomas of the head and neck.
7:4. Adenocarcinoma of the lung
7:5. Malignant melanoma
7:6. Transitional cell carcinoma of bladder
7:7. Lymphomas
7:8. Other tumours, including sarcomas.
7:9. Conclusions.

Pages 7:1-10

CHAPTER 8. MEASUREMENT OF THE C-MYC GENE PRODUCT.

8:1. Introduction.
8:2. Materials and methods.
8:3. Results.
8:4. Discussion.

Pages 8:1-22

CHAPTER 9. DISCUSSION: APPLICATIONS OF IN VIVO KINETICS.

9:1. Introduction.
9:2. Cell cycle kinetic data applied to therapy.
9:3. Chemotherapy.
9:4. Radiotherapy.
9:5. Conclusions.

Pages 9:1-14

APPENDICES

Pages A:1-19

REFERENCES

Pages R:1-32

List of Tables

1:1. Comparison of BrdU and thymidine labelling.

2:1. Historical data on labelling indices of human colorectal cancer.

2:2. The numbers of multiple specimens studied from colorectal tumours.

2:3. Colorectal tumour kinetic data: results.

2:4. The kinetics of primary tumours and metastases.

2:5. Intratumour variation in kinetic data.

2:6. Tumour xenograft kinetic data from animals.

2:7. Volume growth and kinetic data for the MC28 rat sarcoma cell line grown in nude mice.

3:1. Historical data on the labelling indices and kinetics of human colorectal mucosa.

3:2. The crypt labelling index and cell turnover rate. Results from human in vivo data.

3:3. Comparison of the labelling index by crypt cell counting and flow cytometry.

4:1. Kinetic data results for the series of gastro-oesophageal tumours.

4:2. The kinetic data of gastric adenocarcinomas sorted by histological grade.

4:3. Kinetic data from gastro-oesophageal mucosa.

5:1. Example of data comparing planar image cytometry and manual counting of peroxidase labelled cells.

5:2. An application of planar image cytometry to measure nuclear size.

6:1. Historical data on human breast tumour kinetics.

6:2. Kinetic data results for human breast carcinomas in relation to node status.

6:3. Intratumour variation of breast tumour kinetics.

7:1. Historical data on the labelling indices of various human tumours.

7:2. Measured kinetic data from seven lymphomas.

7:3. Measured kinetic data on other human tumours.

8:1. p62c-myc in colorectal tumours and tissues.

List of Figures

1:1. Diagram of the cell cycle (after Tubiana 1971).

1:2. Concept of the potential doubling time.

1:3. Cell metabolism of pyrimidine analogues.

1:4. The principle of multiparameter flow cytometry.

1:5. Excitation and emission spectra of dyes.

1:6a. The gating of diploid histograms.

1:6b. The gating of aneuploid histograms.

1:7. The principle of BRdU detection with antibodies.

1:8. The concept of relative movement.

1:9. Cycle progression in a mouse tumour model.

2:1. Flow chart of colorectal tumour kinetic analysis.

2:2. Cytometry histograms of a diploid colonic tumour and mucosa.

2:3. Cytometry histograms of an aneuploid colonic tumour.

2:4. An example of intra-tumour variation in kinetic data.

2:5. The range of ploidy of 52 aneuploid tumours.

2:6. The intratumour variation of DNA content.

2:7. A comparison of the total and aneuploid labelling indices in colorectal carcinomas.

2:8. Intra-tumour variation in the total labelling index.

2:9. Duration of the S phase in diploid and aneuploid tumours.

2:10. Intra-tumour variation in the S phase duration of colorectal carcinomas.

2:11. The range of the potential doubling time in diploid and aneuploid tumours.

2:12. Intra-tumour variation in the Tpot of colorectal carcinomas.

2:13. The relationship of the total labelling index to tumour grade and Dukes stage.

2:14. The relationship of the potential doubling time to tumour grade and Dukes stage.

2:15. A comparison of BRdU labelling of colorectal carcinomas by flow cytometry and counting.

2:16. The volume growth curve of the MC28 sarcoma.

2:17. Photomicrograph of a colonic tumour labelled with BRdU.

2:18. Photomicrograph of a colonic tumour labelled with BRdU.
3:1. Diagram of the measurement of mucosal kinetics by flow cytometry.

3:2. Diagram of the comparison of kinetics of mucosa at various distances from the primary tumour.

3:3. Photomicrograph of BRdU labelled colonic mucosa.

3:4. Photomicrograph of a BRdU labelled villous adenoma.

3:5. Photomicrograph of BRdU labelled colonic mucosa from a patient with polyposis coli.

3:6. Photomicrograph of labelled colonic mucosa from a patient with polyposis coli

3:7. Results for the crypt labelling indices of mucosa compared with adenomas and carcinomas.

4:1. Cytometry histograms of normal gastric mucosa and a diploid carcinoma.

4:2. Cytometry histograms of an aneuploid gastric carcinoma and a metastatic lymph node.

4:3. The kinetic data for upper gastrointestinal tumours.

4:4. The kinetic data for upper gastrointestinal mucosa.

4:5. Photomicrograph of labelled squamous mucosa.

4:6. Photomicrograph of labelled gastric mucosa.

4:7. Photomicrograph of a labelled squamous carcinoma.

4:8. Photomicrograph of a poorly differentiated gastric carcinoma.

5:1. Flow diagram of the method of assessing the planar image cytometer.

5:2. The design of the image processing cytometer.

5:3. The processed images generated by the image cytometer.

5:4. Comparison of manual and image processed labelling indices.

6:1. The analysis of breast tumour kinetics.

6:2. Photomicrograph of a BRdU labelled breast carcinoma.

6:3. Photomicrograph of a BRdU labelled breast carcinoma metastasis.

6:4. Photomicrograph of a BRdU labelled breast carcinoma.

7:1. Photomicrograph of a BRdU labelled cutaneous melanoma.

7:2. Photomicrograph of a BRdU labelled rectal melanoma.

7:3. Cytometric histograms of head and neck tumours.

7:4. Histograms comparing kinetic data from various human tumours.

8:1. The staining procedure for the p62c-myc protein.
8:2. Cytometry histograms of tumour p62c-myc content.
8:3. p62c-myc levels in colorectal tissues and tumours
8:4. Results: p62c-myc levels in colorectal tissues and tumours compared with BRdU labelling.
8:5. Results: p62c-myc levels in colorectal tissues and tumours compared with the Tpot.
8:6. Photomicrograph of polyposis coli mucosa stained for p62c-myc protein.
8:7. Photomicrograph of polyposis coli mucosa stained for p62c-myc protein. 9:1. A theoretical model of conventional radiotherapy applied to colorectal tumour kinetic data.
9:2. A theoretical model of C.H.A.R.T. radiotherapy applied to colorectal tumour kinetic data. List of Appendices.
2:A. The histopathology data, DNA index and Tpot data on 100 colorectal carcinomas.
2:B. The labelling index, Ts, Relative Movement data and tumour sizes of 100 colorectal carcinomas.
2:C. The immunohistochemical staining procedure for BRdU labelled tissue sections.
3:A. The kinetic data for ileal, colonic and rectal mucosa, metaplastic polyps and villous adenomas.
4:A. The kinetic data for gastro-oesophageal tumours.
4:B. The kinetic data for gastric and oesophageal mucosa.
4:C. The kinetic data compared from primary gastric carcinomas and their associated metastases.
6:A. The kinetic data from primary and metastatic breast carcinomas.
8:A. The p62c-myc content and BRdU labelling data compared in colorectal tumours and mucosa.

GLOSSARY OF ABBREVIATIONS

BRdU 5-Bromo-2-deoxyuridine (Bromoxuridine)
CCTR Crypt Cell Turnover Rate
CEA Carcino-embryonic Antigen
CHART Continuous, Hyperfractionated, Accelerated Radiotherapy
DI DNA Index (ploidy)
EGF(R) Epidermal Growth Factor (Receptor)
ER Oestrogen Receptor
FACS Fluorescence Activated Cell Sorting
FAP Familial Adenomatous Polyposis
FCM Flow Cytometry/ Flow Cytometer.
FITC Fluorescein
FLM Fraction of Labelled Mitoses
5FU 5-Fluorouracil
FUdR Fluoro-deoxyuridine
GF Growth Fraction
IBAS Interactive Biological Analysis System
IUdR 5-Iodo-2-deoxyuridine
LI Labelling Index
MDR Multi-Drug Resistance
PBS Phosphate Buffered Saline
PCNA Proliferating Cell Nuclear Protein Antigen (Cyclin)
PDGF Platelet Derived Growth Factor
PI Propidium Iodide
PMT Photomultiplier Tube
RAMIG Rat anti-mouse Immunoglobulin
RM Relative Movement
SPF S Phase Fraction
Tc Cell Cycle Time
3H-Thy Tritiated Thymidine
TLI Thymidine Labelling Index
Tpot Potential Doubling Time (Apparent Cell Cycle Time)
Ts Duration of the S phase
Vd, Td Volume/Tumour Doubling Time

CHAPTER 1

1:1:1. Introduction

The unifying theory of cell kinetic activity is the Cell Cycle concept, which describes the life cycle of individual cells. Until recently, it has not been possible to measure cell cycle kinetic data in vivo in ethical clinical practice except in unusual circumstances using radioisotopes. The experimental work which has been performed in animals and in vitro systems may not always apply to human in vivo biology. Tumour growth occurs both in space and in time, at the tissue, organ and cellular level. Tumour growth can be measured in clinical practice by a variety of physical and radiological methods. A better understanding of in vivo cell growth is desirable, and may have unforeseen applications. The questions as to whether in vivo cell kinetic data might be used to improve chemotherapy and radiotherapy, and to calculate prognostic indices, have remained unanswered.

Malignant disease in all its forms is a major cause of human morbidity and unpleasant death. With few exceptions, the effect of recent improvements in treatment by surgery, radiotherapy and chemotherapy on life expectancy have been incremental rather than dramatic. The flourishing of molecular biology and computer technology opens new avenues for investigation of tumours at the subcellular level. One path to better understanding may be through cell kinetics. A technique has recently been reported by which tissue and tumour biopsy material obtained in the normal course of clinical investigation from patients with haematogenous or solid tumours can rapidly and safely be studied to obtain quantitative measurements of cell cycle parameters. This has clinical potential. The technique has been made possible by developments in a number of scientific fields. The flow cytometer (FCM) links computer and laser technology to enable the accurate counting, separation and collection of large numbers of fluorescent-labelled single particles from heterogenous cell populations in suspension. This has been
supported by the development of mathematical models and computer software to analyse the cell cycle and the behaviour of populations of living cells. Biotechnology has provided monoclonal antibodies directed against selected drugs and other organic molecules. Pharmacologists have produced substituted DNA precursor molecules, including the halogenated pyrimidines such as 5-bromo-2-deoxyuridine, (Bromoxuridine, BrdU). The use of these advances in a practical method of cell kinetic analysis will be described in this chapter. This method will be subsequently referred to as the FCM/BrdU method.

Using this method, I have elected to study in detail the in vivo cell kinetics of human colorectal, gastrooesophageal and breast tumours, all of which are common in a General Surgical unit. Preliminary studies have been performed on a range of other solid tumours, including malignant melanomas and transitional cell carcinoma of the bladder. The state of cell kinetic knowledge for each tumour type will be reviewed and discussed in the appropriate chapter. In this study a number of questions about the cell cycle in human solid tumours and non-malignant tissues have been addressed.

1. Are the cell cycle kinetics of human tissues and tumours of a particular origin, size or grade constant, or do they vary widely?
2. If the in vivo cell cycle kinetics are variable, do they vary from individual to individual, with pathological class, description or grade, with time during the growth of the tumour, at different sites within the primary tumour or between the primary tumour and metastases?
3. Can premalignant changes be detected in the tissue of origin of the primary tumour, particularly gastrointestinal mucosa, and are there changes in the growth characteristics of normal mucosa with anatomical site along the gastrointestinal tract?
4. Is the technique of practical value in clinical use to give an improved assessment of prognosis or to allow optimum planning of individual radiotherapy or chemotherapy?
   treatment schedules?
5. Is the technique accurate, reproducible and consistent, and what are the sources and ranges of error?
6. What other features of tumour cell biology are amenable to study using similar methodology? For example, it is possible to compare kinetic data derived from BrdU labelling with the expression of intrinsic proliferation associated antigens and oncogene products, such as the c-myc gene product.
7. Is it possible to adapt the technique to cell/tissue culture and animal models to study chemotherapeutic agents?

1:1:2. The concept of the cell cycle.

The theory of cell and tissue kinetics has been reviewed by Steel (1977), Wright and Alison (1984) and Pardee, Laskey, Murray, McIntosh and Hartwell (1989). An outline review of cell cycle theory and related concepts relevant to this project is described here. The concept and terminology of the cell cycle was introduced in 1951 by Howard and Pelc. All proliferating prokaryotic and eucaryotic cells are believed to follow a lifespan from inception to division through a series of stages known collectively as the cell cycle. The importance of the cell cycle concept is that cell populations become amenable to mathematical and statistical analysis. The phases are G1 (Gap 1) from which cells may enter the G0 (Resting phase), or the S (DNA Synthesis) phase, and then the G2 (Gap 2) phase, from which cells pass into the M (Mitosis) phase. Chromosomes are duplicated during the S phase. The timing of S, G2 and M phases is believed to be relatively constant for any one cell type, maximum variation being found in the duration of the G1 phase.

A cell in the G1 phase possesses a single, diploid set of chromosomes. Not all cells leave the G1 phase. Cells may become specialised in G0. Cells are also lost through malfunction, necrosis and external factors such as drug treatment. In most cell systems, the majority of cells

Figure 1:1. The cell cycle is often depicted in circular form. This diagram emphasises the change in DNA content through the cycle. Each daughter cell reenters G1 after Mitosis.

are in G0. DNA synthesis is greatest during the S phase of the cell cycle. The synthesising cell incorporates exogenous purine and pyrimidine bases or their artificial analogues into the cellular DNA. By supplying cells with radiolabelled or synthetic precursors of DNA, either by pulse labelling or by continuous labelling, it is possible to calculate the proportion of cells in a tissue sample which are in the S phase, the S Phase Fraction (SPF), the duration of the S phase (Ts), and the proportion of cells in the population expressing the marker of interest, or labelling index (LI). From this primary data the duration of the cell cycle (Tc) and the potential doubling time (Tpot) of the tissue or tumour can be estimated. These concepts are collectively
referred to as the Cell Kinetic Data of the cells. The ways by which this data can be generated and analysed mathematically will be described.

The basic concept of the cell cycle has been refined by different authors. For example, Ronot and Adolphe, (1986) have postulated distinct cell growth cycle and DNA Division cycles. According to their theory, the cell cycle may be subdivided into two distinct synthetic components, possibly under independent regulatory control. These are the DNA replication (Nuclear cycle) and the cytoplasmic and organelle replication (Growth cycle), measured by RNA and protein accumulation. These two components are usually closely linked, but cell growth through cytoplasmic expansion may proceed without cell division (Baserga 1984). The components may be “dissected” by selective block of DNA synthesis by drugs such as cytosine arabinoside (Ara-C) which induces S phase arrest, or by simultaneous flow cytometric analysis of DNA/RNA and DNA/Protein content.

Such studies suggest that there are subdivisions of the G1 and G2 phases according to the progress of RNA and protein synthesis, and that Quiescent, Transitional and Differentiated states may be further distinguished by their relative DNA, RNA and protein contents. However, the fundamental integrity of the cell cycle concept has not been challenged by such work.

1:1:3. The growth rate of tissues.

Three important parameters affect the rate of growth of a tissue or tumour (Figure 1:2). They are:

1. The growth fraction, which is the proportion of proliferating cells in the population.

Growth Fraction, GF =

1. The duration of the cell cycle Tc. If all cells are dividing, the time taken for the population to double its numbers will be the cell cycle time. The specific growth rate of a tissue or tumour is referred to as the Doubling time (Td or Vd), which usually refers to volume but may also be a mass or a linear measurement (e.g. cell/cell/hr).
2. The cell loss factor, comprising cell death and cell exfoliation into the bloodstream, lymphatics, body cavities or gastrointestinal tract. Cell loss from tissues and tumours may occur for a number of reasons, including natural cell death (ageing and apoptosis), cell migration or metastasis, immunological reactions, drug or radiation effects, or devascularity.

In any cell population, GF is usually less than 100% or unity. Because of this, the time taken for a population of cells to complete a cell cycle is longer than if all cells were active and dividing in unison. In other words, The Potential Doubling Time (Tpot), otherwise known as the Apparent cell cycle time is only equal to the Cell Cycle Time (Tc), if GF = 1.0. Td is the product of the cell cycle time Tc and the Growth Fraction (GF), if there is no cell loss.

The true pattern of growth of tumours from single abnormal cells to advanced disease is not known. In some experimental models, growth is initially exponential but decays with time, such as in the Gompertz Growth Equation (Laird 1964). The macroscopic growth rate of human tumours probably varies with time according to the interaction of tumour factors such as cell inhibition and host factors such as the inflammatory response, nutrition and the tendency to outgrow the blood supply (Denekamp 1986). The question of whether the Cell Cycle Time varies during the course of the disease is less certain. Deschner and Lipkin (1976) have provided evidence that Tc is relatively constant in gastrointestinal mucosa, ulcerative colitis and neoplasia.

Figure 1:2. The mathematical relationships of the potential doubling time, the cell cycle time and the actual volume doubling time are shown. n is the number of cells and t is the time (hours or days).

1:1:4. Controls of the cell cycle and of cell proliferation.

Howard and Pelc’s original model of the cell cycle has been refined by new experimental methods in biochemistry, molecular biology, biomathematics and flow cytometry. (Ronot and Adolphe, 1986). It is believed that the duration of the S, G2 and M phases are relatively constant. The control of cell cycle duration appears to reside in G1. The relationship between the active and quiescent states in G1 is uncertain. For example, Epivanova and Polunovsky (1986) propose that the transition between these states is the result of an interaction between intra- and extracellular molecules, according to the relative concentrations of various molecules. The molecular regulation of cell
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proliferation and differentiation is undoubtedly complex. It may involve both external signals acting at the cell membrane, and intracellular signals.

Certain “switch” molecules might control the duration of the cell cycle and the fate of the cell at various points, for example to proceed to meiosis or mitosis, to remain in a transient or permanent resting phase prior to the S phase, or to proceed to further differentiation. Progression to S phase may require a series of switches. Evidence for the existence of such switches has been reviewed by Prescott (1982) and Zetterberg (1982). Many molecules, for example Platelet Derived Growth Factor, (PDGF), insulin and glutamine will stimulate proliferation of cultured quiescent 3T3 cells. In order to prove that a particular molecule is a regulator of the cell cycle, it is necessary to demonstrate that it is synthesised by or available to the cell in appropriate temporal relationship to the effect. Experimentally applied, purified molecule should produce the same effect, either directly or by gene activation or deactivation. Mutant or drug-treated cell lines which lack the appropriate gene or molecular mechanism should be unable to pass to the next phase of the cell cycle. For example, when RNA Polymerase II is blocked by &-amanitin, BHK cells are unable to enter the S-phase. The list of candidates for these controls include molecules which may be present in very small numbers and with selective expression varying with time, such as:

-serum peptides, hormones and proteins acting as growth factors and growth factor receptors at the cell membrane, for example the Platelet Derived Growth Factor (PDGF) and Epidermal Growth Factor (EGF).

-endocellular molecules within the cytoplasm or cell nucleus.

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The role of growth factors, inhibitory factors, genes and gene products in the control of mammalian cell proliferation has been reviewed by Baserga, 1982, Denhardt 1986, and Lloyd 1987. Use has been made of the haemopoietic system to determine the controls of the cell cycle. Lord (1986) concluded that the proliferation both of stem cells and of maturing populations depends on inhibitory and stimulatory molecules (such as erythropoietin) which act through negative feedback loops.

1:1:5. Proliferation associated proteins.

Selective gene activity may be studied by analysing protein expression during the cell cycle. Such proteins may be used to measure the cycle kinetics, as indicators of the effectiveness of therapy and of prognosis. The Restriction point (R) model for cell cycle control in G1 proposes that commitment beyond R requires the synthesis of a labile (growth factor induced) protein (Pardee 1974). A number of PDGF induced candidate molecules have been proposed (Denhardt 1986). Lee and Nurse (1987) have identified a human protein acting early in G1 which commits cells to the mitotic cycle. Some proteins already have a well recognised cycle dependent expression and a defined function. These include:

• Histones, complexed with eukaryotic DNA.
• Enzymes of nucleotide and polyamine metabolism such as dihydrofolate reductase and Thymidine kinase.
• Cyclin, proliferating cell nuclear protein antigen (PCNA), a 36,000 MW acidic protein which increases in the late S phase. Garcia et al (1989) have reported the use of Monoclonal Antibody 19A2 (Ogata et al, 1987) on formalin fixed, deparaffinised sections of human tumours with successful demonstration of proliferating cells in tumours and gastrointestinal mucosa.
• Secreted proteins such as Interleukin-2, Collagen and Interferons. These substances may also affect growth by effects on the vascularity of a tumour.
  -Protein p105 (Bauer and Clevenger, 1985) is selectively expressed in G0 and M phases, and differentially between well and poorly differentiated areas of human colonic adenocarcinoma.

-DNA Polymerase alpha increases during the cell cycle, but is confined to the nucleus during the S phase. A monoclonal antibody is available, and has been used to evaluate expression in colon cancer cell lines by both immunoperoxidase staining and FCM (Alama, 1987; Stokke 1988).

-A labile proliferation associated protein recognised by the Ki67 monoclonal antibody is expressed in the nucleus of proliferating cells but not in resting cells. The antigen is maximally expressed in late S and the G2M phases. (Gerdes et al 1983, 1984). Sasaki et al (1988) showed that its activity in HeLa S3 cells was abolished by DNAse 1 but not RNAse, suggesting that it is bound to DNA. Expression was increased by blocking DNA synthesis with hydroxyurea and adriamycin. Its biological function remains unknown. The Ki-67 growth fraction or labelling index may be useful as a guide to treatment or prognosis in human malignancy, particularly breast carcinoma (vide infra). Ki-67 can be measured by immunohistochemistry and by FCM. For example, Schwarting (1986) determined the Ki-67 growth fraction of peripheral blood monocytes by FCM. The relationship between labelling indices measured by Ki-67 and by BrdU labelling in human tumours has been explored by Sasaki et al (1988). They compared the LI of 20 randomly selected human malignant tumours. The Ki-67 LIs were 1.9-37.5% and the in vitro BrdU LIs were 1.6-23.4%. In general the measurements paralleled each other.

Multiparameter FCM can also be used to study protein expression during the cell cycle. For example, Rice et al (1986) studied heat shock protein expression in the various phases of the cycle of CHO fibroblasts. BrdU incorporation and DNA content were measured in an assay of the response of these cells to cycle enhancing and delaying stimuli.

1:1:6. Control of the tumour cell cycle.

What kinetic features may distinguish malignant cells from normal cells? Tumour cells may exhibit uncontrolled growth, abnormalities of shape, metabolism, synthesis and distinctive surface membranes and antigenicity. The comparison of the growth of normal and tumour cells in culture is a way of identifying the molecular regulators. This plethora of abnormal traits may be caused by relatively simple or limited genetic changes. For example, Pardee (1982) showed that there is an accumulation of the labile p53 protein in the G1 phase in the SV40 virus transformed 3T3 cell line. This protein may be more rapidly accumulated or more slowly degraded. A single mutation in the ras oncogene in human bladder carcinoma cells, substituting a valine for a glycine amino acid in a 21,000 Molecular Weight protein, is believed to elicit profound changes in the behaviour of the protein in the cell (Weinberg 1983).

Tumour cells pass through mitotic cell cycles in the course of tumour growth as do non-malignant cells, although the specific cell cycle controls may be modified as a result of the malignant process. Quantitative measurements can be made on individual tumours using mathematical models of the cell cycle. Cancer cells do not necessarily divide more rapidly than normal cells, but their controls to growth may be abnormal. For example, Camplejohn et al (1973) and Wright et al (1977) have suggested that the cell production rate of colorectal and gastric carcinomas respectively may be less than in the mucosa of origin.

1:1:7. Tumour clonality and its significance.

Are tumours homogenous or heterogenous populations of cells? In general, the cells of solid tumours are believed to be monoclonal and derive from a single mutated stem cell line and share similar behaviour and antigenic markers with each other. Liu and Wright (1986) examined a mathematical model of cutaneous tumour growth which led them to conclude that clonal proliferation of a single neoplastic cell would
continue indefinitely. Camplejohn (1982) described the role of stem cells in colonic mucosa. Their existence and location in malignant tissues is difficult to prove. Stem cells may have “unlimited” proliferative potential, and be clonogenic in culture. Polyclonal tumours have stem cells with multiple proliferative characteristics.

Monoclonal tumour cells may undergo a series of transforming stages or stimuli before developing into a fully fledged tumour (Woodruff 1988). This has been demonstrated in a variety of human tumours by clonal analysis of cells in tissue culture. Woodruff observed that not all tumour cells retain unlimited proliferative potential, and that some may stop cycling temporarily or permanently. Normal stromal cells, such as fibroblasts and inflammatory cells may also modify the cell cycle behaviour and the antigenicity of the tumour cells. Polyclonal tumours may occur in multiple sites simultaneously or in response to chronic and disseminated stimuli such as chemical carcinogens or radiation (such as basal cell carcinomata). The flow cytometer may be used to distinguish clones in human tumours, if suitable markers are found.

1:1:8. Cell cycle kinetics and cancer metastasis.

It is often the behaviour of the metastases rather than of the primary tumour which kills the patient. Do metastasising cells have features which distinguish them from primary tumour cells? Are they selected subpopulations of malignant cells? If so, can any of these differences be identified through changes in their cell cycle parameters, or by changes in the secretion of proteins? (Nicholson 1979). Poste (1982) provided evidence that primary tumour cell populations are heterogeneous with regard to their potential for metastasis. He assessed the metastatic potential of subclones of tumours such as the B16 melanoma cell line. Some cell clones showed no metastatic potential. This suggested that metastasis may be a non-random process.
Clonal heterogeneity implied that appropriate treatment for one subpopulation of tumour cells may be inappropriate for another subpopulation.

1:1:9. Methods of measuring cell kinetics.

A simple method of study of cell cycle parameters is the direct counting of features in histological sections. The Mitotic Index is the proportion of cells in mitosis compared to the total population. These cells are recognised by their condensed chromatin. The mitotic index does not give an indication of the growth fraction or of the Tc, but is a crude assessment of the degree of proliferation. Colchicine, Vincristine and Vinblastine arrest dividing cells in metaphase. Stathmokinetics is the study of the rate of accumulation of arrested cells in serial measurements from in vivo or in vitro specimens. The method allows the rate of entry of cells into mitosis, the rate of cell birth, the potential doubling time and the duration of mitosis to be calculated. It is affected by the efficacy of the drug employed, and by sampling problems due to tumour heterogeneity.

1:1:10. Thymidine labelling.

The mainstay of the study of cell kinetics has been Tritiated Thymidine (3H-Thy) uptake. 3H-Thy is incorporated into synthesising cells in the S phase (Taylor 1957). Ethical considerations limit its clinical use. It has been important in the study of in vitro systems and in vivo animal models. The technique of autoradiography and film processing used, and the method of background subtraction chosen affect the results. Radiolabelled cells need to be counted manually. Large numbers of cells should be counted to compensate for local irregularities in uptake and to improve statistical accuracy. The autoradiographic plates take 10 days or more to develop. 3H-Thy experiments fall into two categories.
In Pulse and Double labelling experiments, the tissue under study is exposed to short pulses of single or multiple radioisotopes, which are taken up by S phase cells. This allows calculation of the labelling index and the duration of the S phase (Ts) if the cells are fixed soon after uptake of the isotope. In Grain count halving and Fraction of Labelled Mitoses (FLM) experiments, cells are allowed to proceed through the cell cycle after uptake of the isotope.

Grain count halving.

As labelled DNA divides at mitosis, so the grain count halves. The time elapsed from pulse labelling to the first mean halving is a measure of time(Ts + TG2 + TM).

Fraction of Labelled Mitoses, FLM.

Cells are pulse labelled in vitro or in vivo. Serial sampling allows calculation of the cell cycle and phase times from the peak numbers of cells in mitosis as the first and second cell cycles are reached. The method assumes asynchrony, and is confounded in a synchronous population of cells. Precise definition of the first peak is rarely possible outside closely controlled cell culture systems, and the second peak is often lost or blurred.

Human tumour kinetic data has been obtained from radio-labelling experiments. Young and DeVita (1970) calculated the Ts of three melanomas and three breast tumours by topical injection of 3H-Thy into subcutaneous tumours. Serial biopsies were performed, and the percentage of labelled mitoses were plotted against time after injection to derive a Tc of 19-24 hours. Frindel et al (1968) studied five patients with large cutaneous tumours by intravenous injection of 3H-Thy. Seven to 17 serial biopsies were taken from each patient to calculate a Ts of 7-19 hours and a Tc of 1-4 days. Bresciani et al (1974) studied five squamous head and neck tumours with an intracarotid injection of 3H-Thy to obtain a Ts of 18-34 hours. Chavaudra et al (1979) compared in vitro and in vivo 3H-Thy labelling indices of 16
squamous carcinomas and found a poor correlation between results in one third of their cases. The mean duration of Tc was 48 hours of 53 human tumours reviewed by Tubiana and Courdi (1989). The S phase duration was 18 hours and the Tc/Ts ratio was 0.4. A fuller review of clinical results using 3H-Thy was presented by Meyer in 1982.

1:1:11. Measurement of DNA content by Image cytometry.

The DNA content of nuclei can be measured in cell smears and tissue sections stained by the Feulgen method or by Ultra Violet spectrometry (Caspersson 1960). A correction is made for the total nuclear DNA content. The method is time consuming but allows selective and retrospective study of nuclei of interest.

1:2:1. The measurement of cell kinetics using BRdU.

BRdU is a synthetic Deoxyuridine analogue. It is one of a family of DNA base precursor analogues which include 5-Fluoro-uracil (5FU) and 5-iodo-deoxyuridine (5IUdR) and which were intended for use as chemotherapeutic drugs. It was developed as a tumour radiosensitiser, to be given as an adjunct to radiotherapy by intravenous injection in doses of one gram per day for up to 40 days. Cellular DNA containing BRdU is more sensitive to ionising radiation. The practical use of BRdU in this role, for example as a radiosensitiser for human brain tumours has still to be established (Kinsella et al 1984). However, it is useful in the study of cell proliferation and cell kinetics because of its particular properties. It inhibits cell differentiation in a variety of cell types, and has been used to study the molecular biology of differentiation (Wright 1986). It is incorporated into cells during DNA synthesis in the S phase in competition with thymidine (Figure 1:3). It quenches the fluorescence of the non-intercalating DNA-specific blue dyes Hoechst 33342 and 33258 (Crissman 1987). Early flow cytometric studies on cell kinetics used the quenching effect of BRdU on the fluorescent dye Hoeschst 33258. Latt (1977) reported the incorporation of BRdU into tumour cells in vitro by continuous labelling. The doses of BRdU required for these studies were too large for clinical use.

BRdU has been used in clinical practice, both at a total dose of 40 grams over 40 days (1gm/day) for patients with brain tumours, and at the smaller dose of 250mg as a single intravenous bolus for cell labelling studies. When this dose is given 2-20 hours before surgery, BRdU is incorporated in measurable quantities into human tumours and tissues (Begg 1985, Wilson 1988). It can be detected immunochemically both in cell suspensions by flow cytometry and in appropriately prepared formalin fixed histological sections.

In addition to its clinical applications, BRdU can be used as a DNA marker in a range of experiments. For example, Papa et
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al (1988) were able to monitor the physical separation of heterogenous populations of cycling and resting erythro-leukemia cells labelled with BRdU on a discontinuous Percoll Density Gradient fractionation system.

1:2:2 Clinical side effects of BRdU.

Proof of the safety of BRdU is essential for the acceptable use of BRdU in clinical research. Work has been performed on the effects of 5-halogenated pyrimidine incorporation into native DNA of experimental cell systems (Raffel et al, 1988). Ultraviolet light increases the damage to DNA containing BRdU in rat brain tumour cells in culture. Barrett (1978) reported neoplastic change in 50% of cultures of Syrian Hamster Embryo cells grown in a medium containing BRdU and exposed directly to near ultraviolet irradiation. This experiment was designed to demonstrate that a direct perturbation of DNA is sufficient to initiate neoplastic change. This observation has no recognised clinical parallel, but the possibilities of photosensitisation and mutagenicity attributable to BRdU must be considered in clinical practice although no evidence of this has been reported. Kaufman (1986) reviewed later work on the mutagenesis of BRdU in experimental cell systems. Serious or specific side effects with low dose BRdU have not been detected in clinical practice. Fine and Breathnach (1986) reported two cases of cutaneous papular eruptions in patients with brain tumours treated with high dose BRdU and radiotherapy.

1:2:3. Cellular handling of thymidine and its analogues.

The calculations upon which cell cycle kinetic measurements are based assume that the 3H-Thy or BRdU bolus is handled as a true pulse label following injection. This assumption may break down at the organ or cellular level. For example, circulating BRdU may be sequestered for gradual release in body tissues, thus being presented to S phase cells continuously rather than as a bolus. Impaired tissue perfusion will deprive some S phase cells of the label. At the cellular level, BRdU delivery requires trans-membrane and

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Figure 1:3. This flow chart shows the principle biochemical relationships of BRdU, 5-Fluorouracil and Thymidine synthesis via deoxyuridine monophosphate.

intracellular transport to the nucleus, where it will be in competition with endogenous thymidine for incorporation into DNA. Pulse labelling may therefore fail to identify all S phase cells. Hamilton and Dobbin (1985) examined the effect of the endogenous nucleotide pool on thymidine labelling. Fluoro-deoxyuridine (FdUrd) binds to the enzyme thymidylate kinase and blocks de novo synthesis of thymidine monophosphate from deoxyuridine monophosphate (UdR). FdUrd thus effectively blocks the endogenous pool of UdR and enhances the incorporation into DNA of exogenous (eg Tritiated thymidine) label. They found that the mean thymidine labelling index of the undifferentiated mouse carcinoma NT was increased from 27% to 46% by pretreatment with FdUrd. Labelling with repeated doses of tritiated UdR produced a

1:2:4. Monoclonal Antibodies

Monoclonal antibodies are derived from a single cell line and have a high degree of specificity against molecular epitopes and antigens. The secretion of monoclonal antibodies by tumours such as the myeloma has long been recognised. Their potential in research and therapeutics was realised when Kohler and Milstein (1975) produced immortal hybridomas which secrete monoclonal antibody of known specificity. Hybridomas are formed by fusing myeloma cells with lymphocytes from an animal which has been treated with the antigen to be studied. Those cells which produce the antibody can be selected and cloned in growth media or in vivo.

1:2:5. Monoclonal antibodies against BRdU

In 1982, Gratzner described the manufacture of monoclonal antibody B44 (Becton Dickinson Laboratories), which is specific for BRdU incorporated into denatured DNA (Gratzner 1982, Dolbeare 1983). Since then other antibodies have been raised against this compound by a variety of routes, each antibody having different affinity and specificity for BRdU. Vanderlaan (1985) at Lawrence Livermore laboratories described the IU-1 and IU-2 antibodies which label BRdU in denatured DNA. Gonchoroff (1985) described the BU-1 antibody which recognises BRdU in DNA which has not been denatured. BU-1 allows S-phase measurements to be made in intact cells. These antibodies rarely bind to BRdU in the free state. Miller et al (1986) suggested that the nucleoside sugar moiety and the DNA molecule are both important recognition epitopes.

1:2:6. Iododeoxyuridine

Iododeoxyuridine (IUdR) has similar properties to BRdU and has been used as an alternative for in vivo kinetic studies. It is cross reactive to the IU-4 but not the BR-3 monoclonal antibody. This difference may be of practical value for sequential in vivo kinetic studies. Shubui et al (1989) have demonstrated the ability to distinguish the Bromide and Iodide epitopes in double labelled human glioma cell lines grown in culture. Begg et al (1989) have used IUdR as an alternative to BRdU in the measurement of the Ts and Tpot of human tumours. They reported that the mean coefficients of variation of the Ts, LI and Tpot of six transitional cell carcinomas of the bladder and seven head and neck squamous tumours were 10%, 24% and 27% respectively. They concluded that the IUdR/FCM method can be successfully used in human tumours and has sufficient accuracy for predictive classifications of tumours based on proliferation data.

1:2:7. Flow cytometry

The history of the development of Fluorescence Activated Cell Sorting (FACS) has been described by Shapiro (1987) by Herzenberg et al (1976), and by Andreeff (1986). Mayall (1988) observed that successful flow and image cytometry combines four principal technologies, namely of sample preparation, the use of appropriate probes and markers, instrumentation, and data display and analysis.

The complexities of these techniques require caution in the interpretation of results, in the identification of artefacts and in the comparison of results between one laboratory and another.

A. Sample preparation; General principles

Flow cytometry has advantages in cell research in the analysis of heterogenous rather than homogenous populations of cells, such as malignant cells with variable amounts of DNA per cell. Flow cytometry requires a monodisperse suspension of cells or cell nuclei. Blood cells are naturally
suitable to this. Samples of solid tumours require disaggregation by mechanical or chemical techniques which can result in extensive sample damage. The demonstration that single cell and nuclear suspensions could be obtained and analysed from paraffin-embedded blocks of tissue was a major advance (Hedley et al, 1983).

B. Instrumentation

A range of flow cytometers with different technical specifications are in scientific use (Shapiro 1988). Two machines were used in the course of this study.

1. The Orthocytofluorograph linked to a DIGITAL (Digital Corporation) 2150 computer.
2. The purpose-built Cambridge MRC Flow Cytometer, linked to a Vax computer.

Although technical specifications vary considerably, the general principle of operation to make multiparameter measurements is similar, and is shown in Figure 1:4. Suspensions of fluorescently labelled isolated cells or cell nuclei are streamed coaxially through a chamber with a laser light source of known wavelength. The resulting light emissions can be collected, filtered to select specific wavelengths, amplified through photomultiplier tubes (PMT), digitised and stored on a computer disk for subsequent analysis. Light striking the particles is also scattered. Photomultiplier tubes can be positioned at various angles, for example forwards and at 90 degrees to the exciting source, to collect light at the exciting wavelength. This gives a measurement of particle size. Cells with a particular fluorescence can also be separated and sorted into separate collecting vessels. In this application, signals from light detectors are used to induce electrical charges on the fluid droplets containing the cells of interest. The droplets can then be manipulated in an electrical field into collecting vessels.

Figure 1:4. This diagram shows the principle of multi-parameter flow cytometry by which both the DNA profile and a nuclear antigen such as bromodeoxyuridine or p62c-myc are analysed. Coaxially streamed nuclei are excited by blue light of 488nm. The resulting fluorescence is collected in two or more photomultiplier tubes (PMT1 and PMT2).

3. The use of appropriate probes and markers.

It is not usually possible to measure a feature of interest, such as a membrane antigen or nuclear DNA content directly. Indirect probes include fluorescent dyes and fluorescent labelled monoclonal antibodies. The probe must react stoichiometrically (in direct proportion) and be excitable and detectable within the technical parameters of the flow cytometer used. Hoffman (1988) reviewed the physical characteristics of commonly used fluorochromes and their application to FCM. Examples of suitable fluorochromes are given in Figure 1:5.

Figure 1:5. This diagram emphasises the differences between the excitation and emission spectral peaks of a range of fluorochromes, particularly Fluorescein (FITC) and Propidium Iodide (PI). Others shown include Phyco-Erythrin (PE) and Algal Phyco-Cyanin (APC).

4. Data display and analysis.

The facility to collect and analyse light of multiple wavelengths and characteristics simultaneously gives rise to many applications. These include quantitative cytology, such as the identification and separation of lymphocyte subsets in immunological studies, using fluorescent labelled anti-T and anti-B antibodies. The measurement of time-dependent (eg enzymatic) processes linked to fluorochromes has been described (Watson 1987). A plot of nuclear numbers against fluorescence intensity of dyes which bind stoichiometrically to DNA (Watson 1987) yields a histogram from which the DNA content of cells can be calculated. Such dyes include
Mithramycin, which binds to G-C base pairs and fluoresces yellow-green, and propidium iodide, which fluoresces red.

When one fluorochrome is measured, the technique of data analysis is known as Univariate DNA Distribution analysis. It can also be applied to asynchronous and perturbed (eg drug treated) cell populations. The data derived from such analysis is insufficient to allow deductions about cell cycle periodicities (Gray et al 1986), but will yield a measure of the DNA profile and the S phase fraction of a population of cells. Modern FACS machines allow simultaneous measurement of two or more wavelengths of emitted fluorescent light. The use of three or more simultaneous fluorescent probes is possible. Dent et al (1989) have described the simultaneous paired analysis by flow cytometry of cell surface markers (such as the human transferrin receptor), cytoplasmic antigens (such as the myeloperoxidase enzyme), oncogene expression (using the c-myc oncoprotein) and DNA content in human leukocytes.

1:2:8. Limitations of flow cytometry.

Flow cytometer output must be controlled and interpreted by trained observers. Data collection and histogram presentation is markedly affected by photomultiplier settings, which need to be reset from specimen to specimen. The machine/operator interaction may introduce subjective error. Interpretation of histograms may also introduce error. For example, small aneuploid peaks may not be identified or merge into the G1 peak. Infrequent cell events or rare subgroups may be overlooked. Artefact is a particular problem in the analysis of formalin fixed archival material. DNA may be registered as aneuploid rather than diploid owing to the presence of artefactual peaks (Fordham et al 1986).

1:2:9. Multiparameter DNA analysis and the cell cycle.

The measurement of cell cycle parameters by analysis of two fluorochromes (Propidium iodide for DNA and fluorescein for BRdU) and light scatter is the basis of the BRdU/FCM method. Success is determined by a number of factors.

1. Fixation. Optimum conditions for specimen preservation are necessary.
2. Disaggregation. Nuclear suspensions are more difficult to prepare from tissues with high collagen and fat content. Nuclear extraction is achieved by using pepsin. Schutte et al (1987) reported the digestion of ethanol fixed cell fragments with pepsin. The conditions will be described in detail in the methods section. Cytoplasmic and cell membrane antigens are not preserved.
3. Denaturation. In order to measure the incorporation of BRdU into DNA by monoclonal antibody, the antigenic epitope in single stranded DNA must be exposed to the antibody. Double stranded DNA, to which propidium iodide (PI) binds, is then partially denatured (“unravelled”) to expose the BRdU to the antibody. DNA containing BRdU is partially denatured by acid or heat treatment. Dolbeare (1985) reported that optimum partial denaturing of DNA occurs by extraction with 0.1M HCl, followed by heating to 80°C in 50% formamide solution. Wilson (1988) considered that heat treatment produces unacceptable clumping of nuclei. Beisker et al (1987) reported a 5-stage procedure whereby chromatin proteins are first extracted with HCl and 0.7% triton. Cellular DNA is denatured at 100°C in distilled water. Houck and Loken (1985) described a disaggregation technique which also preserves cell membrane antigens, thus allowing flow cytometric analysis of three simultaneous factors, including nuclear and surface antigens. They tested this method on thymocytes and leukocytes; cells were labelled for surface antigens, fixed in cold 0.5% paraformaldehyde, then suspended in 2M HCl and the detergent Tween 20 before staining.
   The Anti-BrdU antibody is detected by a second monoclonal antibody (rat anti-mouse FITC) coupled with the dye fluorescein (FITC). Dolbeare (1983, 1985) demonstrated that this technique can be used to provide a quantitative measurement of BrdU incorporation into cells because antibody binding is stoichiometric.

Propidium iodide and BrdU Labelled nuclei are excited by light of 488nm in the flow cytometer. The resulting red fluorescence is collected above 620nm and green fluorescence between 510 and 560nm. Ethidium bromide, an alternative to PI, fluoresces red at 575nm under 488nm light excitation. Data are collected in list mode, and the nuclear doublets and multiples excluded from further analysis by gating on the DNA peak versus area signal (see Figures 1:6a and b). This technique has high sensitivity to low levels of BrdU. Bivariate DNA distribution analysis is used to obtain cell cycle kinetic data.

Figures 1:6a, 1:6b (overleaf). These diagrams illustrate the gating used to calculate the numbers of events and the mean values of events within fields of interest. They should be read in conjunction with examples of the histograms shown in subsequent chapters. Green fluorescent events (BrdU labelled nuclei) are indicated on the Y axis. The gating boxes must be reset for each specimen. Within each box the total number of events and the mean DNA content are calculated automatically. For example, the total labelling index of an aneuploid tumour will be the ratio of the contents of box 2 to box 1. The Relative Movement (RM) of this tumour would be calculated from the mean DNA content of boxes 7, 8 and 9. In general, events above Channel 20 were taken to be indicative of BrdU labelling. In exceptionally well defined histograms this limit was as low as Channel 5.

Figure 16a

Figure 16b

Figure 1:7. This illustrates the staining technique for BRdU labelled nuclei for flow cytometry. A similar method of labelling is used for histological sections but using the avidin biotin complex in place of Fluorescein.

1:2:10. The mathematics of cell cycle analysis.

The simplest model of the cell cycle assumes that:

1. All cells in the labelled population are proliferating.
2. The distribution of cell ages is rectangular.
3. The cell population is in a steady state.
4. No account is taken of stem cell subpopulation behaviour.
5. All cells in the tissue have the same derivation or behaviour.
6. There is no cell loss. If all S phase cells take up the BRdU label, the labelling index is the ratio of the duration of the S phase (Ts) to the cell cycle time (Tc).

Then, Tc = Ts / LI.
Begg et al (1985) described a method to measure the duration of DNA synthesis and the potential doubling time (Tpot) of mouse tumours from single samples labelled in vivo with BRdU. They used the formula [Tpot = L . Ts / LI] where L(lambda) is a correction factor for non-linear distribution of cells through the cycle, and varies between ln2 (0.7) and 2ln2 (1.4) (See Steel 1977). The movement of labelled (green fluorescing) cells through the S phase with time is related to the mean DNA content of the G1 and G2 cells. The mean DNA content of the labelled cells changed linearly with time until all have moved into the next cell cycle. It is possible to calculate Ts from a single biopsy at a variable time after pulse labelling with BRdU if three assumptions were made about the cell cycle. Firstly, at the time of labelling, S phase cells are evenly distributed with a mean DNA content in mid-S phase. At T0 the relative movement (RM) of S phase cells between G1 and G2 is 50%.

Secondly, labelled cells from the start of the S phase must reach G2, in a time Ts. At this time, RM = 1.0. This concept is illustrated in Figure 1:8. The time from injection of BRdU to biopsy, T(inj), is known for each specimen studied. If the RM is a linear function of time, Then,

[ text = frac{text{Mean DNA (S)} – text{Mean DNA (G1)}}{text{Mean DNA (G2)} – text{Mean DNA (G1)}} ]

Thirdly, DNA synthesis is assumed to proceed uniformly during the S phase. In an expanding population of cells, there will be a non-linear distribution of cells through the cycle, with more cells at the beginning than at the end of the S phase on the DNA histogram. This will weight the initial value of RM towards G1.

The mean values of the DNA content in each phase are calculated by gating on histogram (Figures 1:6a and 1:6b).

[ text{Then, } Ts = frac{0.5}{text{(RM – 0.5)}} times T(inj) quad text ]

Figure 1:8. This illustrates the concept of Relative Movement. At 0 hours, the time of injection, BRdU labelled cells are evenly distributed through the S phase. After the period Ts has elapsed, all labelled cells will have passed into G2/M and G1 of the next cell cycle. If the time of biopsy is less than Ts, for example 3 hours in this model, the Ts can be calculated if linear progression is assumed.

The BRdU labelling index is calculated as follows. The population of BRdU labelled nuclei is derived from labelled cells in S, G2 and M which have not yet divided and labelled cells which have divided and the daughter cells have reentered G1. A simple correction is made to adjust for this factor.

Corrected LI = Total (BRdU) Cells – (BRdU)G1 / 2
Total no. of cells – (BRdU)G1 / 2

Figure 1:9. This figure provided by Drs. G. Wilson and N. McNally illustrates the change of BRdU content with time in relation to the phases of the cell cycle. The SAF sarcoma was grown on the backs of CBA mice. When the tumours had reached 8-10mm in diameter, the mice were injected intraperitoneally with 0.1mg/gm BRdU. Animals were sacrificed at one hour intervals (marked on the histograms) for the next nine hours. The tumours were analysed by flow cytometry as described. One hour after the injection all BRdU labelled cells were in the S or G2 phases. With time progressively more cells pass through G2/M and reappear in the G1 phase of the daughter cell cycles, until by nine hours the majority of these cells have moved into the S phase of the next cell cycle.
It is not possible to calculate the number of unlabelled G2 cells at the time of injection which have since divided, thus leading to a probable underestimate of the true Labelling Index. It is assumed that all proliferating cells express the label. This may not be correct (Hamilton and Dobbin 1985), in which case the true growth fraction will be underestimated. The proportion of labelled to unlabelled S phase cells can readily be calculated by gating on the labelled and total S phase regions. However, because of the time lag between labelling and biopsy, some of these cells will have been in G1 at T0 to explain their lack of label (Wilson 1985, 1988).

Computers allow theoretical models of the cell cycle of varying complexity to be tested against experimental data (Dolbeare et al, 1985, Steel 1986). Yanagisawa et al (1985) described a “continuous maturity compartment model”, tested against the growth of CHO cells in vitro, and obtained good matches between theoretical and observed measurements of the durations of G1, S and G2M. Mann (1987) addressed the mathematical and statistical problems associated with multi-dimensional data analysis of multiple parameters measured simultaneously by flow cytometry, and with data reduction from large samples.

1:2:11. Immunohistochemical staining for BrdU.

BrdU can be detected in labelled tissues by fluorescence microscopy (Watson 1987) and standard immunohistochemistry using the same primary antibody as used in flow cytometry. This is an important adjunct to flow cytometry, because it allows the distribution of S phase cells in tissues to be seen. These patterns cannot be described by flow cytometry. Moreover, quantitative planar image cytometry can be performed (Chapter 5) and the labelling index, though not time dependent parameters, can be estimated. This meets Mayall’s criterion (1988) that information obtained by one mode of cytometry should be correlated with other sources where possible.
Wynford-Thomas (1986) and Hayashi et al (1988) described histochemical techniques for conventional microscopy by which pretreatment of formalin fixed, paraffin-embedded tissues with protease, trypsin or pepsin facilitates staining with anti-BrdU antibody. Many BrdU labelling studies have been performed on histological sections. For example, Kikuyama et al (1987) calculated the BrdU Labelling Index of human tumour xenografts serially transplanted into nude mice. Van Dierendonck et al (1989) studied the intranuclear staining patterns of BrdU and recognised three stages of organisation of DNA synthesis during the S phase of rodent and human tumour cells in culture.

Histochemical studies of in vivo labelling of human tumours with BrdU have been performed. For example, Kikuyama et al (1988) calculated the LI of gastric carcinomas using an infusion of one gram of BrdU in 100ml saline over 30 minutes, given one hour pre-operatively. They calculated the LI by counting labelled cells under the microscope.

1:2:12. A Comparison of BrdU/FCM and radioisotope studies.

Tritiated thymidine and BrdU are handled in similar fashion by living cells. Comparisons can therefore be made between cell kinetic data obtained using these labels. The measurement of the labelling index on autoradiographic slides can be compared with the BrdU labelling index from immuno-histochemically stained slides. The comparability between the labelling index of tissues which have been incubated in vitro with BrdU or 3H-Thy has been established in a number of studies. For example, Gunduz (1985), compared the labelling index of human breast tumours and obtained similar results by both techniques. Autoradiographic measurements can be compared with flow cytometric results. Wilson (1985) found similar results when human colorectal and cervical tumours were incubated in vitro with 3H-Thy or BrdU. Autoradiography and BrdU/FCM methods yielded similar values of the labelling index in 21 randomly selected tumours.
There also appears to be high concordance when the Ts, Tc and Tpot are calculated by the Fraction of Labelled Mitoses and BrdU/FCM techniques. For example, Trent et al (1986) compared methods for analysis of total cell transit time using rat embryo fibroblasts. Dolbeare et al (1985) collected cells labelled with tritiated BrdU using the cell sorter, and demonstrated a close correlation between BrdU fluorescence and radioactive labelling of nuclei in the S phase.

The type and quality of information derived from tritiated thymidine and BrdU labelling are similar when direct comparisons are made using experimental models and in vitro labelling of human tissues. The advantages that BrdU/FCM has over FLM are in the practical applications of the method. Firstly, the need to use radioisotopes in FLM renders in vivo studies in humans unacceptable on ethical grounds except in very rare circumstances. The safety of a single 250mg injection of BrdU allows in vivo cell kinetic studies of human tissues and tumours to be performed where informed consent has been given by the patient. In vivo labelling provides the optimum means to study normal biological processes. Moreover, it avoids the difficulties inherent in drawing conclusions about human tumour and tissue biology from animal and cell system models. It is thus the most credible of the methods of investigating human tumour kinetics.

Secondly, FLM requires multiple sequential biopsies to be taken from a tumour or tissue in order to plot a graph. BrdU/FCM information is obtained at a single biopsy. Thirdly, speed of analysis of the BrdU/FCM method allows results to be obtained within 24 hours, making clinical studies practical. Autoradiographic film requires several weeks for development. Fourthly, automation of analysis by flow cytometry allows counting of multiple parameters on a large number of cells at high speed. FLM requires manual counting of cells which is much slower, measures fewer parameters and is susceptible to larger sampling and counting errors.

Factor 3H-Thy BRdU

1. Applications

Cell culture models YES YES
Animal models YES YES
Clinical use NO YES

2. Static data obtainable

In vitro or in vivo (YES) YES
Distribution of S phase cells YES YES
(Histological slides)
Total Labelling Index YES YES*
*Manual Counting or FCM
Multiple parameters NO YES
Ploidy analysis NO YES

3. Time dependent data

S phase duration Ts YES YES
Cell cycle time YES YES
Potential doubling time YES YES
Multiple biopsies YES NO

4. Availability of data 10 days+ 24 hours
   Counting of events Manual Computer
   “Productivity” Low High

Table 1:1. Comparison of the advantages and disadvantages of BRdU and 3H-Thy Labelling.

Alternative methods of measuring dynamic cell kinetics by flow cytometry without BRdU or IUdR have been reported. For example, Darzynkiewicz et al (1986) observed that there is a close relationship between RNA and cell protein content and the cell cycle. By selective staining with the dye Acridine Orange, the DNA, RNA and cell protein content of CHO cells in exponential culture were analysed to give an indirect estimate of the cell kinetics. Other dyes such as FITC, Propidium iodide, Hoechst 33342 and rhodamine 640 can be used to obtain similar data. Pollack et al (1986) described a two-parameter cell cycle analysis by staining the DNA of rat prostatic adenocarcinoma cells with propidium iodide and the nuclear protein directly with FITC.

1:2:13. The limitations to kinetic analysis.

There are practical limitations to the scope of all methods of cell kinetic analysis. Firstly, isotope and BRdU/FCM methods take a snapshot of the growth kinetics of the tumour at the time of biopsy only. They do not indicate whether the growth rate changes with time. It may be possible to overcome this problem by studying a large number of tumours, excised at different sizes and stages of growth, or by measuring the Tpot serially on single tumours where the clinical situation permits. Such serial biopsies will require multiple doses of BRdU. The elimination rate of BRdU from tissues or tumours is not yet known. Residual BRdU may affect the calculation of the kinetics of subsequent biopsies. Data obtained from in vivo measurements of kinetics and tumour volume can also be fitted to theoretical models to test theories of tumour and tissue growth.

Secondly, FLM and BRdU/FCM provide measurements which do not take into account tumour and tissue cell loss during growth. There is a disparity between the actual volume growth of tumours as measured directly or by serial radiology and the potential doubling time. If the volume doubling time (Vd) of the tumour is known, the cell loss factor Theta can be calculated from the formula;

.
Thirdly, flow cytometry will not distinguish cells of interest in heterogenous populations of cells, unless those cells have a measurable distinguishing feature such as abnormal nuclear size. Tumour homogenates will include stromal, inflammatory and vascular cells with the tumour cells. This problem is less acute with aneuploid than with diploid tumours. In the former, all cells expressing aneuploidy can be assumed to be derived from the tumour cell line. Where the proportion of stromal tissue has been identified to be large by conventional histology, a correction should be made in the kinetic calculations. Fourthly, flow cytometry will not identify clonogenicity in tumour cell lines.

1:2:14. Clinical applications of flow cytometry.

The flow cytometer has been used extensively in clinical research in the study of DNA ploidy as a determinant of prognosis and in the measurement of the S phase fraction. Multiparameter analyses such as the BRdU technique have been less fully explored.

Ploidy is usually measured by labelling DNA with propidium iodide and univariate analysis performed on the resulting DNA histogram. Tumours are classified as diploid, or aneuploid if they possess quantitatively abnormal chromosome content. This excludes abnormalities of gene content or of chromosome structure such as balanced gains and losses in which total DNA content is unchanged. Cells containing an abnormal chromosome content may be identified as a subpopulation in the aneuploid histogram.

The DNA index, a ratio of abnormal to normal DNA content, and the S phase fraction of the population can be calculated from these histograms. Sensitivity is believed to be limited to gains or losses of more than one chromosome. There will thus tend to be an underestimation of tumour aneuploidy measured by flow cytometry. For greater accuracy, it is necessary to undertake histological chromosome analysis by methods such as
Feulgen staining. Ploidy studies do not give a measure of the duration of the cell cycle phases, but they do have the major advantage of being able to be performed on paraffin embedded specimens. The advantages, problems and technical aspects of ploidy analysis have been reviewed by Hedley (1983, 1989). Examples of diploid and aneuploid histograms are given in later chapters.

Abnormal DNA content is believed to be a conclusive marker of malignancy. Barlogie et al (1983) found that 75% of 3611 solid tumours had abnormal nuclear DNA content. Frankfurt (1984) reported that 430 of 656 human solid tumours contained aneuploid cell lines. A large number of studies have been reported where the DNA content of a series of tumours has been compared to other indicators of prognosis, such as the tumour grade, and to the subsequent clinical behaviour of the tumours (Hedley, 1989). These studies will be reviewed in greater detail in later chapters. The value of the ploidy data remains uncertain as a determinant of prognosis (Barlogie 1983, Tubiana and Courdi 1989).

1:2:15. BRdU/FCM Data from early clinical studies.

The validity of the BRdU/FCM technique was established in mammalian cell culture in vitro (see Miltenburger, 1987), and in animal models in vivo, such as xenografts of the KHT sarcoma in mice (Mitchell et al 1984, Pallavicini et al 1985). In vivo labelling of human tumours was reported in 1985 by Hoshino (brain), Raza (acute leukemia) and Wilson (seven assorted solid tumours). Wilson et al (1988) reported the in vivo measurement of the LI, Ts and Tpot of 26 evaluable assorted human tumours obtained by local biopsy. Riccardi et al (1989) reported the in vivo cell kinetics of 46 acute leukemias, 27 gastric carcinomas and 16 gliomas. Hoshino et al (1989) reported on the prognostic value of the BRdU labelling index of 182 intracranial gliomas (Chapter 8) The relationship of the in vivo kinetics of human breast, colorectal and gastric carcinomas to prognosis and to clinical outcome has not been studied in large series.

1:2:16. Conclusions

The purpose of this chapter has been to review the theory and applications of a new method of cell cycle analysis using bromodeoxyuridine labelling and flow cytometry. The method offers advantages over previous techniques for cell cycle analysis. It allows in vivo investigations to be performed on human solid tumours. In vivo BrdU administration has been used to obtain static labelling indices for tumours in a number of clinical studies, but little attention has been paid to the dynamic data which can be obtained. The use of BrdU to measure a static labelling index may have no advantages over in vitro techniques, whereas Ts and Tpot data may have practical value both as prognostic indicators and as guides to therapy. It is therefore important to evaluate the method in prospective series.

The work described in this thesis evaluates the BrdU/FCM technique in measuring the in vivo growth kinetics of human gastrointestinal and breast tumours and their metastases, and to relate data to clinical behaviour. Studies of the in vivo growth kinetics of human gastro-intestinal mucosa and polyps have also been performed on labelled resection specimens. Chapters 2, 3, 4 and 6 report on the studies into colorectal tumours, colorectal tissues, gastrooesophageal tissues and tumours, and breast tumours respectively. Each chapter has been set out in review, methods, results and discussion sections. Chapter 5 describes an original application of existing technology to facilitate the measurement of BrdU label in stained tissue sections. The kinetic data from a small series of solid tumours of various embryological origins will be reported in Chapter 7. The relationship of data obtained by BrdU labelling to the expression of a putative oncogene, the proliferation associated c-myc gene product p62c-myc, will be reported in Chapter 8. Clinical follow-up will continue so that full use can be made of the data described in subsequent chapters.

CHAPTER 2

The in vivo proliferation of colorectal carcinomas.

Chapter abstract.

The in vivo proliferation kinetics of 100 human colonic and rectal cancers are reported. 97 patients with colorectal adenocarcinomas were consented to receive a single bolus dose of 250mg BRdU between 2.4 and 16 hours prior to curative or palliative surgery. Tumour biopsies from the resection specimens were stored in 70% ethanol, disaggregated and analysed by multivariate flow cytometry. Cells labelled with BRdU were detected using a monoclonal antibody.

There were 48 diploid and 52 aneuploid tumours. The mean S phase duration was 14.1 hours. The mean total labelling index was 9.0%. The mean aneuploid labelling index was 12.0%. The mean potential doubling time was 5.9 days.

No correlation was found between measured kinetic parameters and the Dukes stage or histological appearance of the tumour. The correlations with prognosis will be established in due course.

2:1 Introduction. The importance of colorectal cancer.

In 1980 there were 23,250 colonic and 9,100 rectal cancers registered in England and Wales. 16,400 patients with colonic cancer and 6,100 patients with rectal cancer were recorded as dying of the disease. The recorded incidence of the disease and the number of deaths has gradually risen over 40 years, despite changes in diagnostic, surgical and adjuvant methods over that period.

Since Dukes (1932) showed the correlation between the extent of tumour spread and survival, much effort has been devoted to achieving early diagnosis of the disease. Patients with liver metastases have the worst prognosis. Surgery alone to the primary tumour and regional nodes guarantees cure in only

40% of cases. Current prognostic indices, in practice the Dukes staging and the histological grade of the tumour, are unable to discriminate patients at risk of recurrence from those with no residual tumour.

No adjuvant treatment such as chemotherapy and pre- or post-operative radiotherapy in conjunction with removal of the primary tumour has yet been demonstrated to produce a satisfactory improvement in survival. This may in part be due to insufficient activity and specificity of available treatments against colorectal cancer, and in part due to the inappropriate use of potentially beneficial treatments. A better understanding of the in vivo proliferation of tumour cells may identify cases suitable for adjuvant therapy, including immunotherapy (Durrant 1989) and better use of currently available treatments. The discovery of more specific and effective agents may stem from a better understanding of colorectal cancer proliferation and its molecular and genetic controls.

2:2. Proliferation in human colorectal adenocarcinomas.

The volume growth rate of tumours can be calculated in clinical practice by serial imaging. Camplejohn (1982) reported a wide range of values for the doubling time (Td) of human colonic tumours according to the methodology used. Using serial double contrast barium enemas, Welin (1963) calculated the mean Td of 20 primary tumours to be 620 days (range 138-1155 days). Bolin (1983) reviewed 27 patients with colorectal tumours who underwent repeated barium enemas, and calculated the mean Td of these tumours to be 195 days (range 79-2355 days). These tumours lacked a firm histological diagnosis at the time the first films were taken. Serial measurements can also be made of lung metastases by direct measurement and of hepatic metastases by ultrasound or CT scan. Steel (1977) calculated the Td of 56 colorectal lung metastases to be 95 days.

Tritiated thymidine provides a number of approaches to cell kinetic measurement. The thymidine labelling index (TLI) of colorectal tumours varies according to author and technique. Meyer (1981) showed no relationship between the TLI and tumour pathology or prognosis of 90 colorectal tumours. Using the Fraction of Labelled Mitoses (FLM) technique, Lipkin (1971) calculated similar cell cycle times (24-48 hours), S phase durations (10-20 hours) and G2 durations (more than eight hours) in both colorectal tumour and mucosa cells. Camplejohn (1982) reported that the cell generation time of colonic tumour cells was 3-7 days as compared to one day for normal mucosal cells. He studied 21 patients with colorectal tumours using the stathmokinetic technique

AUTHOR (YEAR)	METHOD	LAB INDEX (RANGE)	CASES
Wolberg 1962	TLI	6.0 (0-30)	14
Wolberg 1971	TLI	3.1	134
Bleiberg 1976	TLI	32.5 (24-50)	8
Meyer 1981	TLI	17.7 (2-40)	90
Camplejohn 1982*	Stathmo kinetics	20.5 (8-32)	21
Ota 1985**	TLI	2.2	47
Trotter 1986	TLI	12.8 (0.01-24)	50
Risio 1988	BRdU	21.7 (17-31)	6
In vitro
Khan 1988	BRdU	24.0 (15-41)	14
In vivo

• Cell cycle time = 190 hours

** Cell cycle time = 110 hours, Tpot = 39 days

Table 2:1. Examples of reported series of Labelling Index data measured in human colorectal carcinomas. All isotope studies were performed in vitro.
with Vincristine induced metaphase arrest. The mean cell cycle time was 190 hours. He cited the problem of tumour heterogeneity as one reason for the wide variation in results on tumour kinetics published in the literature. Aherne (1977) showed differences in mitotic activity from site to site in human colorectal tumours. Petersen (1978) showed that some tumours have a variable ploidy from site to site. A selection of the published data for the labelling index of human colorectal carcinoma is shown in Table 2:1.

Ota and Drewinko (1985) showed no difference in the thymidine LI of 47 tumours obtained from different anatomical sites in the colon and rectum. The median TLI of these tumours was 2.25%. They assumed a Ts of 24 hours and used Welin’s data (1963), volume doubling time = 620 days, to calculate a cell cycle time of 4.6 days, a Tpot of 39 days and a cell loss fraction of 94%. They also found that cell suspensions produced by enzymatic digestion provided a more representative result than did tissue fragments incubated with 3H-Thymidine.

Owing to the limitations of radioisotope methodology, few meaningful studies relating TLI-derived kinetic data to prognosis with adequate numbers of patients are available. Trotter (1986) used an in vitro 3H-Thy pulse labelling technique to measure the TLI of tumour cells removed at surgery from 50 patients with colorectal tumours. He found a significant correlation between TLI and Dukes grading (vide infra), and demonstrated a trend towards a lower TLI in advanced tumours, unlike Meyer’s findings (1981).

DNA ploidy measured by flow cytometry has been studied in archival human colorectal tumour specimens as a determinant of prognosis (see Hedley 1983, 1989, Barlogie et al 1983, Frankfurt 1984). Ploidy has also been studied in relation to the colorectal “Polyp-Cancer Sequence”. Giaretti et al (1988) reported the DNA ploidy of 64 colorectal adenomas and 49 adenocarcinomas biopsied at colonoscopy. All 105 normal
mucosal specimens were diploid. 20 of 64 adenomas were aneuploid, the ploidy correlating with size and degree of dysplasia but not with histological type of adenoma. 36 of 49 tumours were aneuploid, with a mean DNA index of 1.63. Polyps showing malignant change in the stalk had a mean DNA index of 1.52. Follow up was insufficient to correlate these findings with prognosis. The same team reported a significant correlation between seven of nine patients with DNA aneuploidy in colorectal adenomas and a positive family history of colorectal cancer.

The ploidy of colorectal tumours has been compared both with histological grade and with tumour stage (Dukes). Wooley et al (1982) suggested that diploid tumours have a better prognosis than aneuploid colorectal tumours. Frankfurt (1986) found no relationship between DNA ploidy and tumour grade in the 50 renal, 91 colorectal and 50 ovarian carcinomas which were studied. Armitage (1985) studied the ploidy of 134 archival colorectal tumours. 54% of these were aneuploid and had a markedly worse five year survival than did the diploid tumours. In a study of 24 colorectal tumours by Teodori et al (1986), eight out of nine diploid tumours were in Dukes A or B categories, whereas 13 of the 15 aneuploid tumours (DNA index of 1.10- 2.71) were in Dukes C or D categories. In a study of 123 human colonic adenocarcinomas, Jones et al (1988) found that while DNA aneuploidy is associated with clinical and pathological (eg Dukes grading) features of aggressive malignancy, the determination of DNA ploidy is an incomplete measure of individual tumour cell behaviour. They concluded that ploidy measurement is presently unlikely to influence the management of patients.

Flow cytometry may also be used to study the relationship between the DNA content of primary tumours and associated metastases. For example, Frankfurt (1984) showed a significant difference in the degree of aneuploidy between a single primary (colonic) tumour and its metastasis.
Proliferation data has been obtained from the study of human tissue biopsies labelled in vitro with BRdU. Risio (1988) reported that the labelling index of normal mucosa and metaplastic polyps was significantly lower than in dysplastic adenomas and carcinomas. In a pilot study, Khan et al (1988) infused BRdU into 14 patients with metastatic colonic adenocarcinoma. Biopsies of tumour and normal mucosa were excised two hours later. Labelling was of good quality and highly specific. The mean labelling index of the tumours was 24% (range 15.0-40.6%). Other markers of colorectal tumour proliferation have also been proposed. For example, Shepherd (1988) measured the expression of the Ki-67 antigen in 108 fresh colorectal carcinomas by immunohistochemistry. The tumour labelling index ranged from one to 80% positivity, and there was no correlation with known prognostic parameters. The authors’ conclusion that Ki-67 may be useful in selecting patients for treatment appears to be optimistic on the basis of this data.

The volume growth of human tumours is governed by the balance between cell production and cell loss. Studies reported in the literature have to date used only the total LI or the DNA S phase fraction as measures of proliferation. These are static parameters which give no information on the dynamic aspects of cell production. The additional data of the aneuploid labelling indices, the Ts and the Tpot provided by multiparameter flow cytometry (FCM) have not previously been evaluated in colorectal cancer. The combination of DNA aneuploidy and proliferation data may give a better insight into the factors influencing biological aggressiveness.

2:3:1. Materials and methods.

Informed consent was obtained from all patients for injection of a single dose of 250mg BRdU (Takeda, Japan). Hospital Ethical Committee permission was obtained prior to commencement of the study. A flow chart of the procedure is shown in Figure 2:1.

2:3:2. Patients and specimens.

One hundred adenocarcinomas of the colon and rectum were studied from 97 patients, 54 males and 43 females, age range 42-90 years, mean age 74 years. Three female patients had two synchronous colonic tumours, each of which was studied.

2:3:3. Anatomical site.

There were 23 tumours in the caecum and ascending colon, four tumours in the transverse colon, nine tumours in the left colon, and 13 tumours in the sigmoid colon, a total of 49 colonic tumours. There were 51 rectal tumours.

2:3:4. Histological grading.

Standard Haematoxylin and Eosin stained sections of tumour were assessed by one consultant pathologist and reported as well, moderately or poorly differentiated. Where the degree of differentiation varied within a tumour, the tumour was classified for study purposes by the least differentiated area of the tumour. Five were well differentiated, 65 were moderately differentiated and 30 were poorly differentiated.

2:3:5. Dukes Staging.

Tumour resection specimens were each assessed by one consultant pathologist and lymph nodes were sought and counted. In three cases, endoanal surgery was performed and the Dukes stage could not be assessed. Six patients had Dukes A tumours, 39 patients had Dukes B tumours, and 52 patients had Dukes C tumours.

2:3:6. Specimen selection.

In order to assess intra-tumour variability of the DNA profile and proliferation indices, and to improve statistical accuracy, multiple wedges of tumour were excised from the peripheral quadrants and the centre of a number of tumours, as shown in Table 2. Wedges of tumour measured 0.5cm or more in radius, and allowed for multiple flow analyses if required.

Figure 2:1. This flow chart illustrates the use of specimens in this study.

Number of Specimens Colon Rectum Total Tumours
1 17 21 38
2 12 13 25
3 6 6 12
4 7 4 11
5 5 4 9
6 2 3 5
——
100 Table 2:2. Multiple specimens were studied from 62 tumours in the series. This table shows the distribution of this data with regard to the number of specimens per tumour.
Four biopsies of liver metastases and two of a large adrenal metastasis were obtained. Kinetic data were available on 10 extra-abdominal late recurrences from eight patients for whom primary tumour kinetic data were not available. All specimens were stored in 70% ethanol or 70% methylated ethanol in a commercial freezer at minus 4°C. Shelf life with preservation of BrdU content has been established as at least one year in this mode.

2:3:7. Processing of specimens for Flow Cytometry.

Specimens were processed in batches of 28. Tissue was disaggregated by mechanical dissection, and fragments were incubated in 8mls porcine pepsin (Sigma) solution in 0.1M Hydrochloric acid (HCl) at a concentration of 0.4mg per ml for 45 minutes at 37°C while undergoing agitation. The resulting suspension was filtered through a 35 micron mesh and centrifuged at 1500 rpm for five minutes to select the nuclei. Nuclei were resuspended in 3ml 2M HCl for 13 minutes at room temperature so as partially to denature DNA. Nuclei were then washed twice in fresh Phosphate Buffered Saline (PBS). The concentration of nuclei was adjusted to approximately two million per ml.

2:3:8. Incubation with Anti-BRdU monoclonal antibody.

Nuclei were resuspended in a solution of 0.5ml of PBS containing 0.5% Tween 20 (Sigma), 0.5% normal goat serum (NGS) and 25 microlitres of anti BRdU antibody (Seralab). Incubation proceeded for one hour at room temperature. Nuclei were then washed twice in PBS.

2:3:9. Staining with goat anti-rat antibody-FITC conjugate

Nuclei were resuspended in 0.5ml 0.5% Tween/NGS/PBS and 25 microlitres of goat anti-rat antibody (whole molecule) fluorescein (FITC) conjugate (Sigma) were added. Incubation proceeded for one hour at room temperature. Nuclei were then spun and washed twice in PBS.
2:3:10. DNA counterstaining with Propidium Iodide.

Nuclei were resuspended in 2ml PBS with 30 microlitres of 1.0mg/ml Propidium Iodide (Sigma).

2:3:11. Data collection and analysis by flow cytometry.

Analyses were carried out as described by Wilson et al (1988). All analysis was performed on an Ortho Systems 50-H Cytofluorograph with a 5W Argon ion laser which excites at 488nm light wavelength. Green fluorescent light (FITC) was collected at 510-560nm and red fluorescence (PI) above 620nm. All data on fluorescent events were collected by the computer in list mode. The data were gated to exclude multiple nuclei on the DNA peak versus area signal. Data for 10-15,000 nuclei were collected from each specimen. Details of the mathematical analysis were given in Chapter 1.

2:3:12. Immunohistochemical localisation of BRdU.

Flow cytometric analysis provides a total tissue BRdU labelling index. Quantitative studies of cell labelling were also performed on selected tissue sections stained immunohistochemically. Details of the immunohistochemical staining technique are given in Appendix 2:C. Sections were cut and satisfactorily stained from 26 tumour blocks. The BRdU labelling index was estimated in each section by counting a mean of 2,000 cells per section (10 random fields, 200 cells per field) at x40 magnification using a standard microscope. The “visual” BRdU labelling index was the ratio of the BRdU stained cells to the total number of cells in each field. Examples of BRdU labelling of a colorectal tumour are given at the end of the chapter.

2:3:12. Immunohistochemical localisation of BRdU.

Flow cytometric analysis provides a total tissue BRdU labelling index. Quantitative studies of cell labelling were also performed on selected tissue sections stained immunohistochemically. Details of the immunohistochemical staining technique are given in Appendix 2:C. Sections were cut and satisfactorily stained from 26 tumour blocks. The BRdU labelling index was estimated in each section by counting a mean of 2,000 cells per section (10 random fields, 200 cells per field) at x40 magnification using a standard microscope. The “visual” BRdU labelling index was the ratio of the BRdU stained cells to the total number of cells in each field. Examples of BRdU labelling of a colorectal tumour are given at the end of the chapter.

2:4:1. Results

It was possible to measure BRdU labelling satisfactorily in at least one tissue block from every tumour studied. The DNA histograms were unsatisfactory for measurement of the Ts and the Tpot in only two tumours. In these cases, the DNA appeared to be unduly sensitive to disaggregation in concentrations of pepsin of 0.1-0.4 mg/ml over 15 to 45 minutes, and with denaturation in 2M HCL over five to 15 minutes. The reasons for this phenomenon were unclear.

Typical histograms obtained from diploid and aneuploid tumours are shown in Figures 2:2 and 2:3. In each example, the majority of labelled nuclei are still in the S phase of the cycle, between the G1 diploid and aneuploid and the G2 peaks, but some have already passed through G2M. Their label has reappeared in the G1 diploid and aneuploid populations of the next cell cycle. This label is clearly seen in the G1 peaks on the left side of each BRdU histogram.

Figure 2:2. (overleaf) The upper left histogram shows the ploidy profile and the upper right histogram the relationship of the BRdU uptake to the phases of the cell cycle of a specimen of normal colonic mucosa (code COL008). The lower histograms show similar data from the sigmoid colon tumour of the same patient. There is significantly more BRdU labelling in the tumour specimen. Histograms were printed from the computer at the time of analysis.

Figure 2:3. (overleaf) This shows two examples of aneuploid tumours with DNA profiles on the left, and their BRdU content on the right. The association of BRdU content with the G1 diploid and aneuploid peaks can be seen. The DNA index of the sigmoid tumour (COL026) was 1.53 and of the left colon tumour (COL001) was 1.54.

Figure 2:2.

Figure 2:3.
The mean DNA content and the number of labelled and unlabelled nuclei in any region of interest on the histograms were calculated by setting a gate. In the case of diploid histograms, gates were set around the total labelled population of nuclei to derive the labelling index, and around the BrdU labelled nuclei in G1. These cells have divided and shared their BrdU between two daughter cells in the time between injection and biopsy. The LI can be corrected to its true value at the time of injection by halving the number of labelled nuclei in G1 and subtracting it from the total labelled population. Regions were set around the total G1, total G2 and labelled S phase nuclei to measure the relative movement of S phase cells through the cell cycle in the period between injection and biopsy, assuming an even distribution of label through the S phase at time zero (T0). In the case of aneuploid BrdU histograms, both total and aneuploid labelling indices were calculated by setting further regions according to DNA content. Ts and Tpot calculations were made on the aneuploid population, thus excluding labelled stromal nuclei.

PARAMETER MEAN +/- SEM MEDIAN RANGE

Total LI % (100) 9.0 +/- 0.5 9.0 0.7 – 22.2
Total LI % (48) 8.5 +/- 0.6 9.1 0.7 – 19.4
Aneuploid LI (52) 12.1 +/- 0.8 12.0 2.0 – 25.5 TS (HOURS)
98 Tumours 14.1 +/- 0.5 13.1 4.0 – 28.6
47 Diploid tumours 11.6 +/- 0.6 11.1 4.0 – 20.5
51 Aneuploid tumours 16.3 +/- 0.8 15.0 5.5 – 28.6 TPOT (DAYS)
98 tumours 5.9 +/- 0.4 3.9 1.7 – 21.4
47 diploid tumours 7.1 +/- 0.8 5.4 1.7 – 21.4
51 Aneuploid tumours 4.8 +/- 0.4 3.5 1.9 – 15.4

Table 2:3. Summary of aggregated results of the kinetic data measured in 100 primary colorectal carcinomas.

Figure 2:4. An example of the biopsy procedure for multiple specimens is given in this diagram, with kinetic data illustrating variation at different sites within the tumour.

Figure 2:5. (overleaf). This histogram shows the distribution of the 52 aneuploid tumours in the study in relation to their ploidy. The X axis is marked at 0.1 (10%) intervals. One tumour fell in the range of values 2.4-2.5.

Figure 2:6. (overleaf). This plot shows the range of ploidy values for 30 aneuploid tumours in which multiple specimens were analysed. Shown are the mean and the range of the data for each tumour.

Figure 2:5.

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Figure 2:6.

2:4:2. The DNA profile.

There were 48 diploid and 52 aneuploid tumours, (range 1.1-2.4). Of the aneuploid tumours, three were well, 36 moderately and 13 were poorly differentiated. A histogram of the range of ploidy values is shown in Figure 2:5. Multiple tumour blocks were studied from 61 of the 100 tumours. 30 tumours showed diploidy in all blocks studied. In a further nine tumours, separate diploid and aneuploid populations were detected in different blocks. In these cases, the tumours were regarded as aneuploid and the overall tumour ploidy was calculated to be the mean of all ploidy values, accepting the limitations of this owing to sampling errors. The variation in the interspecimen range of the DNA Index of tumours from which multiple biopsies were analysed is shown in Figure 2:6.

2:4:3. The total and aneuploid labelling indices.

The mean total labelling index of 100 tumours was 9.0%, (Range 0.7-22.2%, median 9.0%). The mean aneuploid labelling index of 52 tumours was 12.0%, (range 2.0-25.5%, median 12.6%). This is shown on the histogram, Figure 2:7. A significant difference was found to exist between the total (100 tumours) and the aneuploid (52 tumours) labelling indices when tested by both parametric and non parametric methods. (The Student T test and Mann Whitney tests were used, p = 0.001). This is to be expected, because calculation of the total LI is based both on tumour nuclei and largely unlabelled stromal nuclei, whereas the aneuploid population is composed entirely of tumour nuclei. This difference also existed when the total LI and the aneuploid LI of aneuploid tumours alone were compared. There was no difference between the total labelling index of 48 diploid and 52 aneuploid tumours, suggesting that the proportions of non proliferating cells in each type of tumour are similar. Because the aneuploid LI in those tumours with abnormal stem lines was on average 25% greater than the total LI of those tumours, the data provide an indication as to the underestimate of tumour cell proliferation in diploid tumours due to the inability of
flow cytometry to discriminate tumour and stromal nuclei (see Steel 1977).

In aneuploid tumours, a further indication of the proportion of tumour cells in the aneuploid and diploid populations is obtained by measuring the percentage of hyperdiploid cells in the population. (This includes “diploid” cells in S and G2M.) In our series, this ranged from 43 to 90%. In those tumours with a high diploid fraction, it is likely that a significant proportion of the diploid cells are malignant rather than stromal, in other words that these tumours contain both diploid and aneuploid malignant cell lines. The range of intra-tumour variation in proliferation was studied in 62 tumours (Table 2:2). In 59 tumours the total LIs of multiple quadrant blocks were compared. Intratumour variation ranged from 0 to 20%, reflecting heterogeneity of proliferation. Generally, the greatest variation was between marginal blocks and more necrotic central tumour blocks. The range of interspecimen variation for these tumours is shown in Figure 2:8.

Figure 2:7. (overleaf). This histogram compares the distribution of the total labelling index of all 100 tumours and the aneuploid labelling index of 52 aneuploid tumours. The mean and median aneuploid labelling indices were significantly higher (p=0.001).

Figure 2:8. (overleaf). This plot shows the range of total labelling index values for 59 tumours in which multiple specimens were analysed. Shown are the mean and the range of the data for each tumour.

2.4.4. The S Phase Duration

The mean S phase duration of 98 evaluable tumours was 14.1 hours, (range 4.0-28.6 hours, median 13.6 hours), with a univariate distribution. A significantly longer Ts was found in the aneuploid tumours (two sample analysis of variance, p = 0.001), which reflects the longer time required to duplicate the larger quantity of DNA in these tumours (Figure 2:9). Interspecimen variation in the Ts occurred within tumours (Figure 2:10). This may reflect in part a variation in the proportions of different cell lines in different specimens. It cannot necessarily be concluded that any one cell line has a constant Ts.

2.4.5. The Potential Doubling Time

The mean potential doubling time was 5.9 days (range 1.75-21.4 days, median 3.9 days), with a univariate distribution. The Tpot of aneuploid tumours was significantly shorter than that of diploid tumours, (3.5 versus 5.4 days, two sample analysis of variance, p = 0.001) (Figure 2:11). Where multiple blocks were studied, intratumour variation of the Tpot (Figure 2:12) reflected the heterogeneity of the total labelling index and of the Ts. 40 of 59 tumours had an absolute range of variation of the Tpot of less than five days, but seven tumours had a range of variation of greater than 10 days. This reflected a high percentage variation in the Tpot in these tumours. Thus, reliance on a single biopsy to calculate the Tpot would result in mis-classification of a significant number of tumours as rapidly or slowly proliferating.

Figure 2:9. (overleaf). Histograms of the S phase duration (hours) of 47 diploid and 51 aneuploid tumours demonstrate the longer Ts in aneuploid tumours.

Figure 2:10. (overleaf). This plot shows the range of variation of the Ts in 57 tumours in which multiple specimens were analysed. Shown are the mean and the range of the data for each tumour.

Figure 2.9.

Figure 2.10.

Figure 2:11. (overleaf). Histograms of the potential doubling time (days) of 47 diploid and 51 aneuploid tumours demonstrate the significantly longer Tpot in aneuploid tumours.

Figure 2:12. (overleaf). This plot shows the range of variation of the Tpot in 58 tumours in which multiple specimens were analysed. Shown are the mean and the range of the data for each tumour.

2:4:6. The Kinetics of extra-intestinal metastases.

ORIGIN	DNA INDEX	TOTAL LI%	Ts (HOURS)	Tpot (DAYS)
COLO11
Rt. Colon	2.0	8.3	28.6	6.3
Liver Met.	2.0	10.4	26.3	7.1
COLO20
Adrenal met.1	1.0	4.1	12.1	9.9
Adrenal Met.2	1.0	4.3	11.2	8.7
T/S Colon 1.	1.0	20.0	14.6	5.7
T/S Colon 2.	1.0	10.2	14.2	4.6
T/S Colon 3.	1.0	10.4	12.5	4.0
T/S Colon 4.	1.0	4.4	12.1	9.2
COLO35
Rt. Colon	1.0	8.9	17.2	6.4
Node Met.	1.0	22.7	16.5	2.4
COLO37
Sg. Colon 1.	1.0	19.9
Sg. Colon 2.	1.0	11.2
Liver Met.	1.0	11.4
RCT004
Rectum	1.3	12.0	20.5	5.7
Liver Met.	1.0	2.2

Table 2:4. Five primary tumours with analysed metastases were studied. The kinetic data are given where available.

Figure 2:11.

Figure 2:12.
Four hepatic and two adrenal metastases were studied in association with five primary adenocarcinomas. The data comparing the primary and metastatic tumours are shown in Table 2:4. 10 specimens were studied from eight patients presenting for adjuvant therapy with recurrent tumour in the perineum, inguinal lymph nodes or subcutaneous deposits. In two specimens, only the labelling index was obtained. In the other eight specimens, the full range of kinetic parameters was measured. Kinetic data on the primary tumours were not available. Eight specimens were diploid and two were aneuploid, values 1.53 and 1.60. The mean labelling index was 10.2% (range 2.5-17.3%). The mean Ts of eight specimens was 22.1 hours (range 9.6-30.7 hours). The mean Tpot was 8.9 days (range 2.6-28.9 days).

2:4:7. Correlation of kinetic data with Histological Grade.

There was no relationship between the histological grade and the total labelling index in 100 tumours (Figure 2:13). In order to assess whether there was an increase or decrease in proliferation with grade, both parametric (Student t-test) and non parametric (Mann Whitney, Wilcoxson) tests were performed on the populations of 65 moderately and 30 poorly differentiated tumours. There were no significant differences by either test. There were too few well differentiated tumours for statistical significance. The same tests were performed to compare the aneuploid labelling indices of 36 moderately and 13 poorly differentiated aneuploid tumours, and again there were no significant differences by either test. There was no relationship between the DNA Index of the aneuploid tumours, the Ts or the Tpot (Figure 2:14) and the histological grade.

2:4:8. The correlation of kinetic data with Dukes stage.

There was no relationship between the total labelling index and the Dukes stage (Figure 2:13). In order to assess whether there was an increase or decrease in proliferation with stage, both parametric (Student t-test) and non parametric (Mann Whitney, Wilcoxson) tests were performed on the 39
Dukes B and 52 Dukes C tumours. There were no significant differences (p = 0.001) by either test. There were too few Dukes A tumours for statistical significance. There were no significant differences (p = 0.001) by either test when the Tpot of the 36 aneuploid Dukes B and 13 aneuploid Dukes C tumours were compared. There was no relationship between the DNA index of 52 aneuploid tumours, the Ts or the Tpot (Figure 2:14) and Dukes stage.

2:4:9. Intra-specimen variation.

The range of experimental error in the method was addressed in six randomly chosen tumour blocks from six patients. From each block six immediately adjacent specimen samples were excised and separately disaggregated for flow cytometry. Results are shown in Table 2:5. In two of the blocks there was a wide variation in data obtained, but in each case this derived from only one of five specimens. In general, greater variation of data was found between peripheral and central tumour blocks of large tumours, reflecting necrosis and poor vascularity in the centre, but this was not a consistent pattern.

Figure 2:13. (overleaf). The total labelling indices of the well, mod(erately) and poorly differentiated tumours have been compared. The mean values and the standard errors have been plotted. n = the number of tumours in the sample. For comparison, similar data relating to the Dukes stage (A, B or C) have been plotted. There were too few Well differentiated or Dukes A tumours for valid statistical comparisons.

Figure 2:14. (overleaf). The potential doubling times of the well, mod(erately) and poorly differentiated tumours have been compared. The method of presentation and analysis is as for Figure 2:13.

SPECIMENS MEAN +/- S.E.M RANGE

No 1, DI=1.0
TOTAL LI% 6.3 +/- 1.3 2.4 – 10.7
Ts Hours 9.5 +/- 0.7 9.2 – 11.3
Tpot Days 5.9 +/- 1.0 3.9 – 10.2 No 2*, DI=1.53
TOTAL LI 12.6 +/- 1.3 9.5 – 16.0
Ts Hours 14.6 +/- 0.9 8.0 – 13.1
Tpot Days 3.5 +/- 0.3 2.7 – 4.2 No 3*, DI=1.50
TOTAL LI 13.3 +/- 0.8 10.5 – 14.7
Ts Hours 11.1 +/- 0.8 8.0 – 13.1
Tpot Days 2.9 +/- 0.3 1.8 – 3.7 No 4*, DI=1.0
TOTAL LI 11.8 +/- 1.0 9.5 – 14.5
Ts Hours 14.3 +/- 0.9 11.6 – 16.8
Tpot Days 3.8 +/- 0.2 3.0 – 4.3 No 5, DI=1.41
TOTAL LI 10.9 +/- 0.6 9.0 – 12.8
Ts Hours 17.2 +/- 0.6 14.9 – 18.9
Tpot Days 5.3 +/- 0.1 4.9 – 5.6 No 6*, DI=1.35
TOTAL LI 21.6 +/- 2.1 15.7 – 26.7
Ts Hours 21.6 +/- 3.7 13.1 – 35.1
Tpot Days 3.4 +/- 0.7 1.4 – 5.2

• One specimen not analysable.

Table 2:5. This table shows the range of data within single blocks from six different tumours. Six specimens were separately analysed from each block.

2:4:10. Measurement of the Labelling Index in Tissue Sections

Most of the historical data on labelling indices have been obtained from measurements on histological sections. The correlation between flow cytometric and histological labelling index data have not been assessed. A limited study was undertaken to investigate this relationship. The BRdU labelling index was measured visually in 26 stained sections of different colorectal tumours from this series. Because of stain heterogeneity, areas of strong staining were selected for counting. These may have been unrepresentative of the entire tumour. The mean Visual LI of these sections was 17.6% (median 17.2%, range 4.3-33.7%). The results were compared with the uncorrected total labelling index measured by flow cytometry in nearby blocks from the same tumour specimen. The uncorrected LI is the nearest approximation to the findings on stained sections, because the figure includes G1 cells labelled with BRdU which have divided since pulse labelling. These are the cells whose labelled nuclei comprise a second generation population within the G1 diploid peak on the DNA histogram. The mean value of the FCM specimens was 11.3% (median 10.1%, range 4.1-24.7%). There was a significant difference between the labelling index measured by each technique by Two Sample Analysis (p = 0.01). The results were plotted against each other and the best fit line of the trend was drawn (Figure 2:15). Linear regression analysis gave a correlation coefficient between the methods of 0.53.

In all but five tumours the FCM-LI was lower than the Visual LI. This may be in part due to differences in the effect of fixative (70% ethanol vs formalin and paraffin embedding), but also to loss of DNA containing antigen during nuclear extraction in preparation for flow cytometry. Conversely, BRdU staining of histological sections may include either antigen binding to cytoplasmic proteins and nucleic acids, or unrecognised antibody crossreactivity. This would lead to an…

Figure 2:15. This shows the correlation between the flow cytometrically and visually measured BRdU labelling indices of 26 tumours in this series. Pairs of samples for FCM and histochemistry were derived from one tumour in each case but there was not exact equivalence between these samples. The line drawn is the best fit of the trend.

overestimation of the immunohistochemical LI. The findings imply that labelling indices calculated by FCM and immunohistochemistry are similar although not directly comparable. It cannot be assumed that either of the two methods measures the “true” BRdU labelling index, although flow cytometry is less prone to observer error and fatigue, and counts many more labelled nuclei.

2:4:11. Clinical follow-up.

Follow up as of 31st December 1989 was one month to 19 months. 12 patients have died in the intervening period. Three early post operative deaths occurred due to bronchopneumonia (1), renal failure with cirrhosis (1) and peritonitis (1). Nine patients have died of progressive disease. There have been four proven metastatic recurrences. Clinical follow-up is continuing so that the relationship between the kinetic data and prognosis may be established.

2:4:12. Clinical safety of BRdU.

At the time of injection, no acute events such as nausea, vomiting or anaphylaxis were reported or observed. The risk of anaphylaxis must be considered if patients are to have repeat injections for the measurement of the kinetics of metastases. The full blood count (particularly platelet count and white cell count) and renal function were monitored postoperatively. There were no abnormalities in any of these parameters which could be attributed to BRdU. There were two deep venous thromboses in elderly patients. Each of the early postoperative deaths not caused by tumour progression was fully explained by the course of clinical events and the previous health of the patient. Post mortems were performed to confirm the cause of death wherever the consent of relatives was obtained.

2:5:1. Discussion.

This chapter has described the application of in vivo techniques to the measurement of cell proliferation kinetics of human colorectal tumours. The method improves the quality and quantity of cell kinetic data by measuring both static and dynamic characteristics. All characteristics show both inter-patient and intra-tumour variation. As with all biological techniques there are sources of experimental error inherent to the methodology (Begg 1985, Wilson 1985, 1988). An attempt has been made to evaluate data obtained from a single biopsy by studying the heterogeneity of proliferation.
The mathematical calculations upon which cell cycle kinetic measurements are based make the important assumption that the 3H-Thy or BRdU bolus is handled as a true pulse label following injection. This assumption may not hold at the cellular level. BRdU delivery requires trans-membrane and intra-cellular transport to the nucleus, where it will be in competition with endogenous thymidine for incorporation into DNA. Pulse labelling may therefore fail to identify all S phase cells. Hamilton and Dobbin (1985) found that the mean Thymidine LI of mouse carcinoma NT cell line tumours was increased from 27% to 46% by pretreatment with fluoro-deoxyuridine (See Figure 1:3). This blocks the enzyme thymidylate synthetase and the de novo synthesis of thymidine monophosphate from deoxyuridine monophosphate. It was concluded that they had provided evidence for the existence of a large cellular endogenous nucleotide pool which could not be saturated with a single injection of 3H-deoxyuridine monophosphate. This work has not subsequently been substantiated, and it is not certain that BRdU uptake is competitively inhibited by local nucleotides. This would have the practical effect of reducing the proportion of S phase DNA labelled with BRdU. Disaggregation of tissues into constituent nuclei is an empirical and tissue specific technique. It is assumed that pepsin digestion shows no specificity for tumour or stromal cells, so that the nuclear suspension contains representative fractions of nuclei from all cell types. Labelling of non-epithelial cells with BRdU, particularly lymphocytes, can be demonstrated histochemically. It is not possible to distinguish tumour from stromal nuclei in the diploid histogram. The contribution of labelled non-tumour nuclei in any profile cannot be known with precision, but qualitative histochemical assessment indicates this figure to be 5% or less in most specimens. Where available, the aneuploid profile of tumours is used to calculate the Ts and Tpot, because this profile is assumed to be composed entirely of tumour cells.
Interpretation of the histogram is operator dependent and therefore subject to observer error. The setting of gates on the BRdU histogram may introduce an error of up to 5%. In particular, the late S phase merges with the G2/M phase labelled nuclei, which may lead to an artificially high calculation of the mean DNA content of the labelled cells in the S phase and hence of the Ts if the duration of G2 exceeds 2-3 hours. Where there was doubt about interpretation of either the DNA profile or the BRdU labelling, a further sample from the block was stained and analysed.

The range of tumour labelling index data measured by in vivo BRdU labelling in histological sections is broadly comparable with historical data (Lipkin 1963, Lipkin 1971, Aherne 1977, Bleiberg 1977, Camplejohn 1982). Multiparameter flow cytometry appears to offer no information gain in the measurement of a labelling index alone. Its advantage is to relate proliferation to the phases of the cell cycle. This reveals the differential labelling of diploid and aneuploid populations where present. The important feature is that it allows the analysis of time-dependent cell cycle progression. Time dependent data have been obtained by thymidine labelling of colorectal tumours only in limited studies. It appears that tumours have a much higher proliferative potential than is manifested in the actual growth rate. This may be for several reasons.

The first is cell loss by exfoliation. Exfoliation of both viable and dead cells into the bowel lumen has been demonstrated and can be used to diagnose gastrointestinal tumours (Oakland 1964, Rosenberg 1978, Umpleby 1984). Measuring the rate of exfoliation of tumour cells is more difficult in vivo. Exfoliation occurs from both mucosal and tumour cells, and the debris is incorporated into faecal waste.
The second cause of cell loss is cell death of both single, non viable cells and of large numbers of cells by infarction, by apoptosis and by necrosis, both due to stromal response and to avascularity. Central tumour necrosis is a prominent feature of many colorectal tumours, but the actual contribution of both individual and regional cell death is difficult to quantify. A third possible cause of cell loss is the failure of cell cycle progression by labelled cells. It is possible that a proportion of the labelled population, particularly aneuploid cells, does not proceed to normal mitosis, because of grossly abnormal DNA content.

The contribution of exfoliation to the discrepancy between Vd and Tpot, the cell loss factor, may be estimated in several ways. Clinical models which eliminate exfoliation include the subcutaneous metastases from colo-rectal tumours, invasive breast carcinoma and metastatic malignant melanoma. Serial measurements of the dimensions of the colorectal metastases studied in this series were not available. Secondly, in animal models both the volume growth rate and the Tpot (at sacrifice) can be measured. A colorectal tumour explant grown subcutaneously in the nude mouse is such a model.

Intra-tumour heterogeneity, both of mitotic activity (Aherne 1977) and of ploidy (Petersen 1978) is reported to be a feature of colorectal tumour growth. Tumour biopsies may not be representative of the whole tumour. Tumour heterogeneity in vivo has been studied in this series by measuring multiple specimens from both the periphery and the centre of a large number of specimens. The DNA index is likely to be the best indicator of clonality from the data measured. Wide intratumour variation may reflect the presence of multiple cell lines (clones) with differing proliferative characteristics. In the stem cell theory of tumour growth, proliferating stem cells give rise to non-proliferative end cells by clonal expansion. A monoclonal tumour would be expected to be less heterogenous than a polyclonal tumour both in terms of its DNA content and its proliferative

characteristics. Stem cells cannot be identified in situ or by flow cytometry. There is conflicting evidence for the clonogenic theory in this series. Most aneuploid tumours showed little interspecimen variation of the DNA index, but in a few tumours ploidy varied widely. Clonality may vary between the primary tumour and its metastases (Woodruff 1988). In a small group of five patients both primary and metastatic tumour were studied. In only one of these patients was ploidy variation found, in this case the rectal primary being aneuploid (DNA Index = 1.3) and the liver metastasis being diploid. The sample is too small to draw further conclusions.

The meaning of aneuploidy in the malignant process is unclear. It is postulated that chromosomal deletions may be responsible for malignant change. In none of the tumours in this series has conclusive evidence of hypoploidy been observed. This does not exclude the possibility of balanced deletions or deletions undetectable by flow cytometry, but does imply that in 50% or so of tumours, genetic deletions or translocations are accompanied by the acquisition of abnormally large quantities of DNA. It should be stressed that flow cytometry is insufficiently sensitive to detect quantitative changes in DNA content in only one chromosome, and there will probably be an underestimate of the true aneuploidy incidence in any tumour population.

The DNA profile derived from specimens stored in ethanol is less affected by artifact than the profiles derived from dewaxed, formalin fixed specimens. Failure to obtain an analysable DNA profile was rare, whereas in some series of analyses of archival formalin fixed material, failure rates of up to 40% have been reported (Hedley 1987). A wide intratumour variation in LI and Tpot data has been demonstrated in some specimens, and it is concluded that no attempt should be made to classify colorectal tumours as rapidly or slowly proliferating unless multiple specimens from multiple sites within the tumour have been measured.

The relationship between tumour cell proliferation, DNA aneuploidy and biological aggressiveness is not yet clearly understood. In a review of 11 multivariate studies comparing proliferation kinetics with factors such as sex steroid receptor status, lymph node status and histological grade in patients with breast carcinoma, Tubiana and Courdi (1989) showed that the tumour labelling index or S phase fraction has the best correlation with clinical outcome. This may also be true of colorectal cancer. However, biological aggressiveness also depends on other features independent of proliferation, such as the ability to metastasise. It has been shown that the Labelling index alone is not a sufficient indicator of proliferation, because the Ts also varies within a tumour. By combining the ploidy data, LI and Ts measurements to calculate the Tpot, the value of proliferation measurements as determinants of prognosis may be enhanced.

Differences between the flow cytometric Labelling Index and the histochemical labelling index may be due to the effect of fixation (70% ethanol versus formalin and paraffin embedding) or to loss of DNA containing antigen during nuclear extraction in preparation for flow cytometry. Conversely, BRdU staining of histological sections may include antigen binding to cytoplasmic proteins and nucleic acids, or unrecognised antibody cross-reactivity. This would lead to an overestimation of the immunohistochemical LI. It cannot be assumed that either of the two methods measures the “true” BRdU labelling index, although flow cytometry is less prone to observer error and fatigue, and counts many more labelled nuclei.

2:6. Evaluation of the Tpot in an animal model.

The volume doubling time of human colorectal tumours is difficult to assess, and the rate of exfoliation and cell loss from primary tumours is not measurable. The validity of the Tpot concept was thus assessed indirectly in an animal model. By growing tumour xenografts subcutaneously, exfoliation is eliminated as a source of cell loss. Cell death and focal necrosis still occurs, but by comparing the Tpot to the Vd of the tumour during the exponential growth phase of the tumour, the effect of cell death on late tumour growth, when necrosis increases as blood supply is outgrown, is minimised.

2:6:1. The kinetics of tumour xenografts in mice.

A preliminary series of experiments was undertaken to evaluate the suitability of different tumour xenografts in the nude mouse model for measurement of their in vivo kinetics. Such a model would be useful to study the concept of the potential doubling time as compared with the actual growth rate, and to form the basis for future studies of chemotherapeutic manipulation of in vivo kinetics.

2:6:2. Materials and methods.

Experiment 1.

The LS human colorectal tumour cell line was grown in cell culture. 10 BALB/C nude mice were given subcutaneous injections in the left or right flank of one million tumour cells. The animals were inspected weekly for evidence of tumour growth. After 37 days, three of the mice had developed visible tumours. On the 37th day of incubation, these mice were given an intraperitoneal (i/p) bolus dose of 100 micrograms BRdU 3.75 hours prior to sacrifice. The tumours were excised and were preserved in 70% ethanol. BRdU/FCM analysis was performed on the tumours as previously described, with the exceptions that disaggregation was performed in 0.1 mg/ml pepsin in 0.1 M HCl for 20 minutes, and denaturation in 2M HCl was for eight minutes.

Experiment 2

10 Balb/C Nu Nu mice were injected in the thigh pad with two million MC28 rat sarcoma cells in 0.1ml PBS. One mouse died and tumour failed to develop in another. The remaining eight animals were sacrificed after 17 days and the tumours were excised. Four hours prior to sacrifice each animal was given an intraperitoneal bolus dose of 200 micrograms of BRdU.

DNA INDEX	TOTAL LI %	ANEUP LI %	Tpot l.
LS Tumours (Human colorectal)
1.	1.0	11.6	—-	2.0
2.	1.0	6.0	—-	2.4
3.	1.0	10.5	—-	3.4
HT29 Tumours (Human colorectal)
1.	1.63	6.5	7.6	5.5
2.	1.60	5.9	6.3	4.2
3.	1.63	8.0	9.1	4.3
4.	1.63	8.3	9.6	3.7
5.	1.62	5.8	6.3	5.9
6.	1.63	11.2	12.0	2.6
MC28 Tumours (Rat sarcoma)
1.	1.76	7.2	10.4	3.2
2.	1.88	11.7	12.9	2.5
3.	1.89	10.4	12.9	3.0
4.	1.89	12.5	13.7	2.3
5.	Failed
6.	1.78	6.2	9.3	4.5
7.	1.92	6.4	8.1	2.4
8.	1.86	11.6	13.6	2.3
9.	1.93	6.7	7.9	2.6
10.	Died

Table 2:6. The cell kinetic data of three tumour xenografts, the LS, HT29 and MC28 tumours grown in nude mice.

Experiment 3

10 Balb/C Nu Nu mice were injected in the thigh pad with two million HT 29 human tumour cells in 0.1ml PBS. Tumour failed to develop in two of 10 animals. The remaining eight animals were sacrificed after 17 days and the tumours were excised. Four hours prior to sacrifice each was given an intraperitoneal bolus dose of 200 micrograms of BRdU.

Experiment 4

Ten adult Nu Nu mice were injected with two million viable MC28 tumour cells as previously described. All ten grew measurable tumours. Tumours were measured in three dimensions with calipers on the 9th, 13th and 16th days following injection. The mean tumour diameter and the tumour volume were calculated from these measurements. This method does introduce errors (see Fiennes 1988). These were considered acceptable for the purposes of this experiment because the ratio of volumes rather than precise volume measurements was required. Animals were sacrificed on the 16th day 4.4 hours after receiving 200 micrograms of BRdU intraperitoneally. Further analysis was as described above. Three tumours produced satisfactory ploidy profiles but failed to label with BRdU. This may have been due to unsatisfactory i/p injection. Subsequent calculations were made on the seven tumours for which satisfactory kinetic data was obtained.

2:6:3. Results

The data for experiments 1-3 are shown in Table 2:6. The results of experiment 4 are shown in Table 2:7. In all tumours the kinetic data were readily obtained, with good quality BRdU labelling and readily analysable histograms. The LS tumour line showed unsatisfactory development in the nude mouse model. Both the rat MC28 and the human HT29 cell lines showed excellent reproducibility of kinetic data from one tumour to another. Although the HT29 cell line was the favoured model for further experiments because it is a human colorectal tumour which grows well in the nude mouse, local difficulties with the stem cultures necessitated the use of the MC28 tumour for further studies.

Figure 2:16. The mean tumour volumes (+/- S.E.M.) of the seven analysable tumours are plotted on this graph.

Animal	9th Day	13th Day	16th Day	LI	Tpot
1.	5.0	10.6	12.6	15.4	2.0
2.	7.0	12.6	15.3	16.1	1.8
3.	6.6	9.3	10.3	—-	—
4.	9.0	12.0	16.3	23.7	1.3
5.	3.6	10.6	14.0	14.6	2.2
6.	4.3	9.3	12.6	21.1	1.5
7.	8.3	12.6	15.6	8.6	2.2
8.	4.3	7.6	10.6	12.3	2.3
9.	1.6	6.3	8.3	—-	—
10.	2.6	5.6	7.3	—-	—

Table 2:7. See text for explanation.
In Table 2:7, the mean tumour diameters are shown at days 9, 13 and 16. The corrected total labelling index and the Tpot are shown. The aneuploid labelling index ranged from 11.9 to 24.1%. The mean Tpot of these tumours on the 16th day was 1.9 days. The Ts ranged from 7.9 to 11.2 hours. The data has been plotted in Figure 2:16 to illustrate the volume growth of the tumour with time. At the time of sacrifice, the tumours had undergone between two and three volume doublings in the preceding three days, during which the tumours were in the exponential phase of cell growth. This is reflected both in the high total and aneuploid BRdU labelling indices of these tumours, and the short Tpot. Exact equivalence between the Tpot and Vd would not be expected, because this would imply a growth fraction of 100% or unity with no cell loss, which is unlikely. From the above data, the growth fraction of these tumours at this stage in growth appears to be of the order of 50%, a plausible percentage within the bounds of experimental error. This experiment provides good evidence to validate the theory and practice of the measurement of the Tpot in vivo. Furthermore, the reproducibility of xenograft tumour cell line kinetic data provides a sound basis for future experiments designed to measure perturbances to cell kinetics induced by drugs, hormones and other treatments.

Figure 2:17 (overleaf). A low magnification view of a BRdU labelled, peroxidase stained, moderately differentiated carcinoma of the rectum (RCT022). This tumour was undergoing rapid proliferation. The Tpot was 4.8 days. The stain is clearly seen to be nuclear in distribution.

Figure 2:18 (overleaf). A high power view of a moderately differentiated colonic tumour (COLO19). This tumour was also rapidly proliferating (Tpot 5.3 days).