cell survival curve

1. CELL SURVIVAL CURVES
Presenter: Dr. Masthan Basha
Moderator: Dr. K.Dinakar

2. Cell Survival Curve
• It describes relationship between radiation dose and
the fraction of cells that “survive” that dose.
• This is mainly used to assess biological effectiveness
of radiation.
• To understand it better, we need to know about a
few basic things e.g.
– Cell Death
– Estimation of Survival / Plating Efficiency

3. Cell Death
Cell death can have different meanings:
– Loss of a specific function - differentiated cells
(nerve, muscle, secretory cells)
– Loss of the ability to divide - proliferating cells such
as stem cells in hematopoietic system or intestinal
epithelium
• loss of reproductive integrity - “reproductive
death”

4. Survival
• Conversely - “Survival” means retention of
reproductive integrity
– this is ability of the cell to sustain repeated
mitotic cycles (5 cycles)

5. Estimating Survival
• In order to determine the surviving fraction, we
must know the plating efficiency
• PE is the percentage of cells (in control batch) that
grow into colonies
– in other words, those cells that survive the plating
process

6. Surviving Fraction
• Equal to the fraction of cells that plate
successfully and survive irradiation (without
losing their reproductive integrity) to grow into
colonies
 
PE/100
seeded
cells
counted
Colonies
fraction
Surviving



9. ModesofRadiationInjury
• Primarily by free radicals (indirect) and ionization (direct)
mechanism
• Low LET (X- and gamma-rays) damage by free radicals
• High LET (protons and a particles) damage by ionization

11. Cell survival curves
For densely ionizing (high LET) radiations
like α-particles ,neutrons etc, the
curve is a straight line.
For sparsely ionizing (lowLET) radiations,
x-rays : Starts out straight with a finite
initial slope, indicates SF is an
exponential function of dose
At higher doses - the curve bends
At very high doses - survival curve
straightens again, i.e SF returns to
being an exponential function of dose

12. Models to describe mammalian cell survival
curve
• Single target single hit model
• Multi Target model
• Linear Quadratic (LQ) Model

13. Single target single hit model
• This model proposes that a
single hit on a sensitive target
with in the cell leads to cell
death
• This generates an exponential
survival curve which appears
as a straight line on a semi
logarithmic scale
• This model useful for high LET
radiation or if a low dose rate
is used.
• But mammalian cells have a
shoulder , not explained by
this model

14. MULTI TARGET- single hit
• To explain the shoulder of the
cell survival curve, this model
was generated.
• It proposes that a single hit to
each of n sensitive targets
within the cell is sufficient to
cause cell death.
• The generated curve has a
shoulder and decreases
linearly with increasing dose.
• But it does not model the
low dose region well as for
low doses it predicts no cell
death.
MULTIPLE TARGET SINGLE HIT ,
ZERO INITIAL SLOPE

15. MULTI TARGET –two component
model

16. Multi-Target Model
16
Dose, Gy
100
10-1
10-4
0 12
3 6
9
Survival
10-3
10-2
Initial slope measure, D1,
due to single-event killing
Final slope measure,
D0,
due to multiple-event
killing
Dq
n
n or Dq represents the size
or width of the shoulder
• Quantified in terms
of:
• measure of initial
slope due to single-
event killing, D1
• measure of final slope
due to multiple-event
killing, D0
• width of the shoulder,
Dq or n

22. Major problem with this model is that there are too
many parameters D1;D0;Dq
Need a mathematically simpler model with fewer
“unknown” parameters
The linear-quadratic (L-Q) model meets
these needs

23. Linear Quadratic model (LQ Model)
At low dose, two
chromosome breaks may
result from the passage of
single electron, causing
lethal lesion
Effect  D
The  term represent the
probability of inactivating a
target directly by single hit,
meaning two strands of DNA
are hit by single exposure.

24. Linear Quadratic model (LQ Model)
At high doses, two
chromosome breaks may
reault from two separate
electrons. The probability of
interaction b/w the two
breaks is proportional to
square of the dose.
Effect  D2
Double hit kill is similar to the MHE

26. Linear-Quadratic model
The linear quadratic model uses a polynomial equation (αD+βD²)
The probability of survival is equal to the exponential of this–
ie:S = e−(αD+βD²)
The generated curve is perhaps the best approximation of the
actualcell kill seen after radiation exposure.
It has the added benefit of two constants (α and β) which can
be determined for specific tissues and cancers to predict dose
response

27. α/β Ratio
Linear Hit
SF
Dose
Killing by SHE=Killing by
two hit event
Linear = Quadratic
D = D2
So  can be defined as the dose at which contribution by single
hit kill becomes equal to double hit kil.
It represent the dose beyond which the double hit kill becomes main
mode of cell kill and before that the cell kill is mainly by single hit.
  D2/D
  D
Quadratic Hit

28.  Ratio defines “curviness” of survival curve
Small / ratio indicate more curvy nature of
the shoulder As seen in late responding tissue
large / ratio indicate less curvy
nature as seen in early responding tissue
In late reacting tissue, the killing by MHE will surpass the killing
by SHE quicker and at lower dose as compare to the early
reacting
tissue. Dose Dose
Shoulder is narrow
Shoulder is broad
Responsible for late effect of radiation
Eg. Spinal cord, urinary bladder, kidney, liver
etc.
Late responding tissue / = 1Gy to 7 Gy (3Gy)Early responding tissue / = 6Gy to 15 Gy (10)
Responsible for acute effect of radiation
Eg, skin, mucosa, lining of intestine, bone marrow
etc.
D = 
D = 
SF

29. – the  value quantifies the sensitivity of a tissue/tumor
to fractionated radiation. i.e. it predicts how total dose for
a given effect will change when you change the size of
dose fraction
– The LQ model best describes data in the range of 1 - 6Gy
and should not be used outside this range
– Most useful means for isodose calculations with
fractionated radiation therapy

30. Dose
D1 D2
SFL1
SFE1
SFE2
SF
As dose /Fc increased the SF reduces
more in LRT than ERT or more cell killing in
LRT than ERT.
So increase in dose per Fc will damage
LRT more than ERT.
So be careful while changing D/F from
conventional Fc
Early Reacting Tissue
SFL2
Late Reacting Tissue

31. Calculated / ratios for some tumors

32. Values ofα/β
Reactions α/β (Gy)
1.EarlyReactions
Skin 9 - 12
Jejunum 6 - 10
Colon 10 - 1
1
Testis 12 - 13
Callus 9 - 10
2. Late Reactions
Spinal cord 1.7 –4.9
Kidney 1.0– 2.4
Lung 2.0 – 6.3
Bladder 3.1 - 7

33. Linear –quadratic model Multi-target model
 Neither the L-Q not the M-T model has any established
biological basis.
 At high doses the LQ model predicts a survival curve that
bends continuosly, whereas the M-T model become linear.
 At low doses the LQ model describes a curve that bends more
than a M-T curve.

34. Factors affecting cell survival curve
1. Mechanism of cell death
2. LET
3. Fractionation
4. Dose rate effect
5. Intrinsic radiosesitivity
6. Cell age
7. Oxygen presence

35. Mitotic death results (principally) from exchange-type chromosomal
aberration.
 survival is linear quadratic function of dose
Survival curve is log-linear plot with broad shoulder
 Characterized by dose-rate effect
Apoptotic death result from programmed death.
 straight line on log-linear plot.
 Characterized by exponential function of dose.
Survival curve is straigh & shoulderless
 little or no dose-rate effect.
MECHANISM OF CELL DEATH

36. LET
• Low-LET radiations:
– low dose region
• shoulder region appears
– high dose region
• survival curve becomes linear and surviving fraction
to an exponential function of dose
– surviving fraction is a dual exponential
36
S = e-(D+D2)

37. • High-LET radiations:
– survival curve is linear
– surviving fraction is a pure exponential function of dose
37
S = e-(D)

38. Survival Curves and LET
• Increasing LET:
– increases the steepness
of the survival curve
– results in a more linear
curve
– shoulder disappears
due to increase of
killing by single-events
38

39. Fractionation
• If the dose is delivered as
equal fractions with sufficient
time between for repair of the
sub-lethal (non-killing) damage,
the shoulder of the survival
curve is repeated many times.
• The effective survival curve
becomes a composite of all the
shoulder repetitions.
• Dose required to produce the
same reduction in surviving
fraction increases.
Showing ~28 Gy
in 14 fractions.

40. D1 D2 D3 D4
D4>D3>D2>D1
So as the number of fraction increases the
total dose to achieve same survival
fraction also increases
Total dose  no of fractions
1 fc 2 fc 3fc 4fc

41. 1 hr
2 hr 3 hr
D3>D2>D1
So as the time interval between two
fraction increases the total dose to
achieve same survival fraction also
increases till all SLD repair takes place
SF
D1 D2 D3
Dose
Effect of time interval between two fraction on
Cell Survival Curve

42. Dose rate effect
• Dose rate determines biological
impact
 Reduction in dose rate causes reduced
cell killing, due to repair of SLD
 Reduction in dose rate generally reduces
survival-curve slope (D0 increases)

43. Dose-Rate Effect in CHO Cells
Dose rate effect is more dramatic in CHO than in HeLa Cells
Broad shoulder to
survival
curve

44. Intrinsic radiosensitivity
 Mammaliancells are significantly
more radio-sensitive than
microorganisms:
 Due to the differences in DNA
content
 Represents bigger target for
radiation damage
 Sterilizing radiation dose for
bacteria is 20,000 Gy

45. • Cell cycle. Duration of each phase in the human cell cycle:
G1=1.5–14 h, S=6–9 h, G2=1–5 h, M=0.5–1 h.
• The responses of cells in different phases to radiation vary .
• The most radiosensitive cell phases are late G2 and M.
• The most radioresistant cell phases are late S and G1 .
Cell Cycle

46. D4
D1 D2 D3
D4>D3>D2>D1
As oxygen tension decreases the
terminal portion of the curve get
shallower.
So to get the same SF, the dose of
RT is to be increased with decreasing
ox tension.
SF
Dose
Effect of Oxygen on cell survival curve
Oxic
hypoxic
OER = D4/D1

47. Decreasing Oxygen concentration
The effect of oxygen is seen more in terminal portion
of the curve and less in shoulder region.
Or we can say that oxygen effect is seen more in high
dose region than low dose region.
Effect of Oxygen on cell survival curve
SF
Dose

48. Ans:
So in this region the cells are
capable of accumulating SLD
which can be repaired . So
Oxygen will fix up the damage
and repair get slowed down.
Ans:
So in
low dose region OER= 2( X or γ
ray).
Why OER Variation with Doses

49. Summary
– A cell survival curve is the relationship between the fraction of cells
retaining their reproductive integrity and absorbed dose.
– Conventionally, surviving fraction on a logarithmic scale is plotted on
the Y-axis, the dose is on the X-axis .
– The cell-survival curve for densely ionizing radiations (α-particles
and low-energy neutrons) is a straight line on a log-linear plot, that
is survival is an exponential function of dose.
– The cell-survival curve for sparsely ionizing radiations (X-rays,
gamma-rays has an initial slope, followed by a shoulder after which
it tends to straighten again at higher doses.

50.  At low doses most cell killing results from “α-type” (single-hit, non-
repairable) injury, but that as the dose increases, the“β –type” (multi-
hit, repairable) injury becomes predominant.
 Survival data are fitted by many models. Mainly : multitarget
hypothesis, linear-quadratic hypothesis.
 Cell survival depends on mechanism of cell death, radiation type,
fractionation, dose rate , intrinsic radiosensitivity, cell cycle phase and
oxygen presence.
Summary

51. Thank You