Transcript my talk - David Rasnick, PhD

Gene Mutation vs Aneuploidy
(competing theories of cancer)
“Wherefore by their fruits ye shall
know them.”
Jesus, according to Matthew, New Testament, 7:20 (00??)
From the Sermon on the Mount
High Magnification Explanation of Cancer
Subtlety is not a
Hallmark of cancer
Normal cells
46 chromosomes
Cancer cells
60-90 chromosomes
Poorly Differentiated Cancer of Cervix
78 Chromosomes, DNAindex=1.7
Hansemann’s Low Magnification Explanation
Virchows Archiv für pathologische Anatomie und Physiologie und für
klinische Medicine 123:356-370, 1891
David Hansemann
1858-1920
Theodor Boveri
…formulated the first
aneuploidy theory of
cancer in 1914
Aneuploidy is an
imbalance in the number
or composition of
chromosomes, hence an
imbalance in thousands
of genes
Boveri’s Mutation-Free Mechanism for the
Production of Aneuploidy
Autocatalyzed Progression of
Aneuploidy
is
Carcinogenesis
How Cancer Starts and Progresses
copies
8
Normal cell
(DNAindex = 1.0)
4
2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Chromosome Number
How Cancer Starts and Progresses
copies
Initiation & Pre-cancer
8
4
(0.5  DNAindex 1.2)
Low level aneuploidy caused by radiation,
carcinogen, bad cell division
2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Chromosome Number
How Cancer Starts and Progresses
copies
8
Early cancer
Tetraploidization
(DNAindex ≈ 1.9)
4
2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Chromosome Number
How Cancer Starts and Progresses
copies
8
Mature Cancer
(DNAindex ≈ 1.7)
4
2
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Chromosome Number
The Molecular Basis of Dominance
Kacser H & Burns JA. Genetics 97:639-666, 1981
“dominant-negative”
Mutation
of one gene is
undetectable in
multi-gene phenotype
DATE Applied to
Cancer
DATE analysis is a
modification of MCA
Rasnick & Duesberg (1999)
Biochem J 340:621-630
DATE Analysis Fundamental Equation
• Fa, aneuploid
phenotype
• ,
• ,
aneuploid
fraction
ploidy factor
Fcell
Fa
 1
Setting Fcell  1 and
1
m
n

1   
m

n
m
6
in Eq. 6 yields Eq. 7.
n


7
Fa
The general form of Eq. 7 is...
1
 1

Fa

 
Fa represents the phenotype of a cancer
cell relative to the normal cell.
Properties of
Aneuploid Cells
Massive change in gene
dose produces highly nonlinear (i.e. qualitative)
changes in the physiology
and metabolism of cells and
tissues.
 (aneuploid fraction)
 (fold change)
Fd (diploid)
Fa (aneuploid)
Live tetraploid births
Live triploid births
There is an infinite number of
combinations of  and 
but there are optimal
values of  and 
At equilibrium, =0.7
& DNAindex=1.7 for
mature solid cancer
Aneuploidy Diagnostic of All
Stages of Cancer
Normalized average CI=1.7
Normal cells on same slide
Confirm Bulten et al.
Chromosomes 7 & 17
equally useful for
detecting cervical cancer
percent of cells aneuploid for Cep-7
Our Results
percent of cells aneuploid for Cep-17
Hariu & Matsuta Confirm Bulten et al.
Chromosomes 1&17
equally useful for
cervical cancer
AND
Suggests the fraction of
aneuploid cells is
diagnostic of stage
0
N
CIN1
CIN2
CIN3
CI
CANCER
Hallmark of Cancer, Genetic Instability,
is Quantifiable
A measure of genetic instability is the
imbalance between overall metabolic
activity (Fa) and DNA content of
aneuploid cells.
SF=flux stability index
(0SF1)
Rasnick & Duesberg (1999)
Biochem J 340:621-630
Predicted Curve of Stability Index SF
1.0
Most unstable DNAindex is
halfway between diploid
and tetraploid
S
0.9
0.8
1.0
1.5
DNA index
2.0
Aneuploid Cells in Culture Confirm
Genetic Instability Theory
1.0
Colon cancer cell line data
from Lengauer et al. (1997)
show that the least stable
cells have DNA indices
halfway between diploid and
tetraploid values.
0.9
0.8
0.7
0.6
Rasnick & Duesberg (1999)
Biochem J 340:621-630
0.5
0.4
0.5
1.0
1.5
2.0
2.5
3.0
DATE Applied to Colon Cancer
Rasnick & Duesberg
(1999) Biochem J
340:621-630
…analyzed…
colon cancer data from
Zhang et al. (1997)
Science 276:1268-1272
Autocatalyzed Progression of Aneuploidy
Explains the Time Course of Human Cancer
Equation (solid line) fitted to data from Armitage & Doll (1954) Br J
Cancer 8:1-12. Broken lines are for best-fit 7-gene mutation model.



N t  N  

e kt





1

 1
 
  1 1

 
 0
 
Rasnick, D (2000)
Biochem J 348:497-506
lung
men
lung
women
breast
cervical
prostate
colon
men
Closing Comment
The “my-favorite-gene” approach of
molecular biology is hopelessly
inadequate when trying to understand and
explain multi-gene phenotypes. However,
dynamical methods, such as MCA and
DATE, provide powerful new tools for
investigating complex phenotypes that
span many orders of magnitude.