Download Slides

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Document related concepts
no text concepts found
Transcript
Genomic instability in cancer and aging
Jan Vijg, University of Texas Health Science
Center, San Antonio, Texas
DNA mutations
AGC
T CG
Point mutation
Transposition
Deletion/Insertion
Inversion
Role of genome instability in aging



Evolutionary logic of genome instability
Evidence for genome deterioration in aging
Association of DNA repair defects with
accelerated aging
ln mean fitness
Effect of deleterious mutations on fitness
in E. coli
Number of mutations
Elena & Lenski, 1997, Nature 390: 395
“The problem in this theory is that of
developing a quantitative measure of
mutations in somatic cells”
Howard J. Curtis, 1963
LacZ plasmid recovery
Spontaneous mutant frequencies with age
in heart and small intestine
Mutant frequency (x10-5)
40
Small Intestine
Heart
35
30
25
20
15
10
5
0
0
5
10
15
20
Age (months)
25
30
35
Spontaneous mutant frequencies with age
in mouse organs
30
-5
Mutant frequency (x10 )
small
intestine
25
20
15
liver
heart
10
spleen
testis
brain
5
0
0
5
10
15
20
Age (months)
25
30
35
Mutant spectra in vivo and in vitro
20
Mutant frequency (x10
-5
)
Point mutations
15
Rearrangements
10
5
0
E14
MEF
SI
SI
He
He
Li
Li
Sp
Sp
Br
Br
(3m) (32m) (3m) (32m) (4m) (32m) (3m) (32m) (4m) (32m)
Tissue (Age)
Point mutational spectra in organs from
Young (3m) and Old (32m) mice
Brain
4
Heart
4
Liver
4
Spleen
4
Small intestine
Mock recovery
70
4
60
3
3
3
3
3
2
2
2
2
2
1
1
1
1
1
Percentage
Mutant frequency (x10-5)
Y
50
40
30
20
10
0
0
0
0
0
0
Lymphoma
4
4
4
4
70
4
60
3
3
3
3
3
2
2
2
2
2
1
1
1
1
1
Percentage
Mutant frequency (x10-5)
O
50
40
30
20
10
0
0
G:C  AT at CpG sites
0
0
0
0
Del (-1) at reiterated sites, i.e. a sequence of 3 or more of the same nucleotide
Mutant frequency (x10 -5)
Mutant frequencies in vivo and in vitro
10
5
0
E14
MEF
Tissue
Population Doublings
MEF 6
25
20
15
10
Growth curve
5
0
0
20
40
60
80
20%
100
Days
Mutant Frequency (x10 -5)
3%
50
40
30
Mutant frequency
20
10
0
0
5
10
15
20
25
Mutant Frequency (x10
-5
)
Population Doublings
40
3%O2
Total MF
20%O2
30
20
spectra
10
0
4
20
3
9
Population Doublings
17
Point Mut
Size change
A:
T
in
s
+1
-1
N:
N
C:
G
de
l
>
>
0
G
:C
5
A
10
T:
15
A:
T
G
:C
G
:C
G
:C
A
in
s
+1
-1
N:
N
C:
G
T:
A:
T
de
l
>
>
>
>
+1
0
>
20
Mutant Frequency (x10 -5)
in
s
-1
N:
N
Mutant Frequency (x10-5)
5
G
:C
+1
A
C:
G
T:
A:
T
de
l
>
>
>
>
10
A:
T
in
s
-1
N:
N
A:
T
G
:C
G
:C
G
:C
15
>
A
C:
G
T:
A:
T
de
l
>
>
>
>
Mutant Frequency (x10 -5)
20
G
:C
A:
T
G
:C
G
:C
G
:C
Mutant Frequency (x10 -5)
Point mutations in MEFs at high and low
oxygen
20
15
10
5
0
20
15
10
5
0
Genome maintenance and aging
Growth &
Reproduction
Increased
Longevity
Somatic
Maintenance
DNA Damage
Apoptosis
Cell Senescence
Transcriptional
Interference
Aging
Cancer
Mutation
Altered Chromatin
Aging in DNA repair-deficient mice
Mutant gene
Defect
Life span (weeks)
Aging Phenotype
Xpa KO
Complete NER
100
None
Ercc1 KO
NER and
crosslink repair
3-4
Weight reduction, renal
and liver failure, cachexia,
sarcopenia, kyphosis,
neuronal degeneration
Ercc1 HP
Same
25
Same
Ratio of Intensity
Ratio of mRNA expression levels in old
v/s young livers (normalized)
72 Arrays
6 Old, 6 Young Animals
Total Intensity
M = log2(red/green)
A = 1/2 log2(red*green)
Ratio of mRNA expression levels in Ercc1/- knockout v/s wildtype liver
M = log2(red/green)
A = 1/2 log2(red*green)
Over-expressed genes*
Under-expressed genes*
Significant genes that
Overlap with aging*
*significant by SAM
Annotation of genes co-expressed in
aging and Ercc1 in liver
Function
Aging
Ercc1
Immune Response

Liver Regeneration







Genotoxic Response
Peroxisome Proliferators
DNA Cross Linkers
Oxidative Stress
Mutation accumulation in liver of Ercc1
and Xpa mutant mice
24 weeks
52 weeks
5
4
Control
3
Xpa -/-
2
1
other
del -1
A:T > N:N
G:C > C:G
G:C > T:A
0
G:C > A:T
Mutant Frequency (x10-5)
Point mutations in liver of 1-year old Xpa
null mice
other
del -1
A:T > N:N
G:C > C:G
G:C > T:A
G:C > A:T
Mutant Frequency (x10-5)
Point mutations in liver of 5mo Ercc1 null
mice
5
4
Control
3
Ercc1-/-
2
1
0
Conclusions




Different types of mutations accumulate with
age in an organ-specific manner
Liver-specific gene expression profile of mice
with defects in the repair of double-strand
lesions, i.e., Ercc1, is similar to normal aging
DNA repair defects cause shifts in the
spectrum of age-accumulating mutations
Genome rearrangements appear to be
associated more with aging than with cancer
Acknowledgements
Mutation Analysis
Rita Busuttil
Martijn Dollé
Wendy Snyder
Microarray
Felix Calderon
Debbie Muñoz
Prakash Nair
Bioinformatics
Brent Calder
John David Garza
Paul Lohman
Accelerated Genomics
Mangkey Bounpheng
Nathalie van Orsouw
Erasmus University
Jan Hoeijmakers
Laura Niedernhofer
Dana-Farber Cancer Institute
Frederick Li
Seoul National University
Yousin Suh
RIVM
Harry van Steeg
LBNL
Judy Campisi
Related documents