DNA pol error rate 10 9 per base copied How many errors in a typical somatic cell Most errors dont have detectable effects But some errors do oncogenes N dominant ID: 223737
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Slide1
Class 12 DNA sequencing and cancer
DNA pol error rate
~
10
-9
per base
copied
How many errors in a
“typical”
somatic cell?
Most errors don’t have detectable effects
But some errors do:
oncogenes
N
– dominant
if “activated”
tumor suppressor
genes
N
– recessive
2-hit hypothesis in inherited cancer
syndromes, BRCA, FAP
loss of
heterozygosity
in tumor DNA
Cancer nowadays viewed in molecular-genetic termsSlide2
Implications
for
therapy
Can inhibit some overactive oncogenes
with small molecule inhibitors (
imatin
ib
,
etc
)
often act
intracellularly
or with antibodies to cell surface receptors
(
panitumim
ab
,
etc
) that act in pathways
that stimulate intracellular oncogenes
But can’t replace function of inactive suppressorsSlide3
Example of pathway activating oncogenes
Extracellular ligand
(epidermal growth factor,
EGF) binds EGF receptor,
w
hich
binds another
p
rotein, which
causes
c
ytoplasmic t
ail of EGFR
to get phosphor
ylated,
which activates other
p
roteins (here
including
Ras
oncogene)…which
turn on
other
genes
t
hat stimulate cell growth. Antibody to EGFR may stop
process, but if
Ras
is mutated and constitutively
a
ctive,
Ab
to EGFR won’t work because
Ras
is “downstream”
Image from
Google search
“
egfr
kras
signaling
pathway”Slide4
Kras
mutated and constitutively active in
~40% of
colon cancersLarge effort has gone into whole genome sequencing of tumors and comparison to non-tumor DNA from same patient
What
are main results
?
several hundred oncogenes
several hundred tumor suppressor genes
organized in at least tens of pathwaysSlide5
Tumors are
“clonal” but continue to acquire mutationsWhen you sequence a tumor, do you get sequence of
majority of cells or of individual cells, with unique mutations?
What are “driver” vs. “passenger” mutations?
What are some clues to identifying
driver mutations?
occurrence in multiple tumors
mutated in inherited cancer syndromesSlide6
Do
you think there a more
tumor suppressor mutations or oncogene mutations driving tumors
? Why?
How
fast do tumors grow?
cell birth rate
b (# divisions/day,
~1/few days) balanced by cell death rate d cell doubling rate k, N(t)=N02kt k related to b-d
M
ore ways to inactivate a gene (stop codon nearly
anywhere) than to make it overactive,
so
suppressor mutations should exceed
activating oncogene mutations, but need to
inactivate both copies of a suppressor, so
answer not obviousSlide7
Types of cancer therapy
surgery – curative intent or for palliation radiation
chemo to kill rapidly dividing cells
-> toxicity from killing normal rapidly dividing
cells in gut, bone marrow, skin drugs or antibodies that target oncogenes
could be more specific but still often have major side-effects examples – antibody to EGFR (drug names ending in “ab” are antibodies) small drug inhibitors
(drug names
ending in “
ib
” are inh
ib
itors
)
Problem of “development” of resistance to
chemoSlide8
R
oles
of DNA sequencingResearch – find what genes are
involved in cancer big challenge – interpreting changes
passenger
vs driver mutations are mutations in non-coding regions (98.5% of total) important?
which mutations in coding regions are relevant?Patient care which genes are mutated in a specific tumor? is whole genome seq. necessary or would seq. of ~hundred known oncogenes and suppressors do?Slide9
Patient care – cont’d.
diagnostics – circulating tumor DNA akin to
pre-natal dx from circ. fetal DNA ?
useful for screening or just dx of already ill ? use to follow treatment – ? more sensitive
than
other biomarkers, e.g. CEA, PSA
do genetic assays need to be specific for individual patient’s
mutations or are mutations
sufficiently common that “generic” tests ok?Slide10
“Beaming” assay
emulsion pcr for particular oncogenes
-> copies single templates on beads
break emulsion, hybridize
flourescent oligo probes
to beads, different colors for
oligos matching wt, mutant, and common seq. determine bead color with flow cytometry
http://openwetware.org
/
wiki/
Image:Flow_cytometrySlide11
p
re-op
d
ay 3
d
ay 48
d
ay 244
What is plotted?
What do #s
i
n quadrants
i
ndicate?
Beaming assay for
Kras
mutations from VogelsteinSlide12
How sensitive is assay to mutations occurring
in fraction of tumor cells as tumors evolve?
What fraction of circulating DNA is from tumor? How many beads can you assay?
Use of sequence info in therapy
possibly
to identify unexpected mutations (e.g. uncommon in patient’s tumor type) that might suggest use of different drug – this is
hypothetical
identify drugs unlikely to be effective – e.g. Ab to EGFR in pts with oncogenic Kras mutations Slide13
U
se
of sequence info in therapyrelevance to patients – avoid (often severe) toxicity
in patients in whom drug won’t work (panitumimab
has lots of toxic skin, gut effects)
relevance to payors - @$1000’s/dose, cheaper to gene
test everyone to avoid use when predictably ineffective = “companion diagnostics”relevance to pharmaceutical companies – use in resistant patients weakens evidence for efficacy, lack of efficacy is major cause of failure to get FDA approvalSlide14
Questions from this paper
How fast do tumors (cells resistant to chemo) grow?
How sensitive are tests for tumor mutations?What is normal mutation rate?
What is probability that particular oncogene mutation has occurred?How many mutations -> drug resistance?
D
o resistance mutations pre-exist in tumors, explaining
usual drug failure after few months?
Implications for multi-drug
therapySlide15
How would you describe
the patients in this study?
What is progression-free vs.
o
verall survival?Slide16
Does prior
Kras
mut
ation predict poor response?
How long before progression in those w/acquired
Kras
mutations?Slide17
What do
p
anels show?
Do mutations
o
r CEA or
t
umor size
assays predict treatment failure sooner?What is doubling rate?
patient 1 patient 2 Slide18
If doubling time
t
is ~10d
and progression time T is ~
150
weeks
how much has mutant cell # increased in time T?
N/N
0 = 2T/t = 215 = 3*104Slide19
How much circulating DNA?
How many cell equivalents in 1ml @6pg/cell?
What fraction f is from tumor cells vs. normal cells?Slide20
What are these plots?
wt
mutantSlide21
How many dots?
What is the lowest % (or number) mutant detectable?
Suppose 1 mutant dot is reliable and 10
5
dots ->
min fraction of
mut
. tumor cells detectable = 1/(f*10
5)If f = 0.1%, 1% tumor cells is min detectableSlide22
How many tumor cells in a 100mm
2
(x-ray) tumorTumor v
ol = (area)3/2 = 1000mm3
Cell
vol
~ (10
m
m)3 => 109 tumor cellsIf 1% are mutant when mutation first detected, howmany were there before panatumumab was started? 107/(3*104) = 3*102Slide23
Is this consistent with
expectation if DNA pol
makes 1 base error every generation andyou have 10
9 cells => 109 genomes copied?
->
~
1 error in every positionIf 42 positions confer resistance to panitumumab
(their estimate), expect
~40 mutant cells to pre-exist; not too far off estimate of 300 givenlarge variance in rates of doubling, etc.Slide24
If 40 (or 300) mutant cells are expected to be
present, on average, by chance in small tumor,
what is probability that a tumor has no such cells?Poisson distribution p
i=e-mm
i
/
i!pi = probability of a tumor having
i
when average number/tumor = mp0 = e-m = e-40 or e-300 = 10-18 or 10-131Slide25Slide26
What is chance that at least 1 cell in tumor with 10
9
cellshas oncogene mutations conferring resistance to 2 different
drugs, if the mutations do not overlap and changes at 40 p
ositions
confer resistance to each drug?
(40/109) * (40/109
) * 10
9cells @ 10-6 Implication – multidrug therapy might avoid outgrowth of resistant mutantsSlide27
Main ideas
Mutations in cancer cells drive growth
gain of function = oncogenes
loss of function = tumor suppressor genesSome drugs target oncogenes by binding to them or their partners in cell signaling cascades
Mutations conferring resistance to individual
drugs likely preexist in tumors because they contain large numbers of cells
harboring mutations just on basis of DNA pol error rateSlide28
Multidrug therapy targeting different oncogenes/
pathways might overcome these resistance
mechanisms, but …DNA sequencing has been important for discovery of different mutations driving cancer
Often difficult to determine if individual mutations
are drivers or passengersGenotyping specific genes in patient tumor DNAs to
see if most tumor cells already carry resistance- causing mutations can prevent futile use of expensive toxic drugs Slide29
Not clear if routine sequencing of exons or
whole tumor genomes is useful clinically at present, as opposed to targeted
genotyping or sequencing“Beaming” is nice use of emulsion pcr and flow
cytometry
to detect not too rare mutations in tumor cells
HAPPY THANKSGIVING – work on picking a topic for
student presentations beginning 11/30