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John D FenwickJohn D Fenwick

Classical radiobiology Classical radiobiology ––an overviewan overview

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An overview of classical radiobiology

5 or 6 R’s of radiobiology and their impacts on treatments

R Impact/exploitable effect

1. Repair Fractionation – usually hyper fx �

2. Repopulation Treatment acceleration �

3. Reoxygenation Hyperbaric treatments, hypoxic sensitisers �

4. Reassortment Interfraction interval �

5. Radiosensitivity Treatment individualisation ??

6. Remote cell kill Bystander cell killing ? �

• Radiation damage to tumors and normal tissuesclassically viewed as being caused by radiation celldeath.

• Quite close to the truth for tumors and early reacting(fast-turnover) tissues such as skin, oral mucosa, andintestinal lining.

• Not really true for slowly (or not at all) turning-overtissues like lung, heart, brain, bone etc, but neverthelessprovides a useful initial conceptual framework formodelling radiation effects – especially fractionation.

Radiobiology and the cell kill paradigm

• Radiation-induced cell death has been studied for well over50 years, both in-vivo and in-vitro.

• Results from large numbers of experiments tell broadly thesame story, and can be characterised using some simpleequations.

• This being a study of biological rather than physicalsystems, while the equations convey a broad truth they aresubject to quite a lot of caveats, and so the orthodoxradiobiological model which I’ll outline does not describeevery situation and every experiment perfectly.

1. Repair: Radiation cell killing

• Radiation cell death has most often been determined in-vitro,by plating out equal numbers of irradiated and unirradiatedcells on two Petri dishes, and seeing how many cell coloniesgrow on each plate.

Radiation cell killing

Colonies of cells growing in a flask – from Barber et al 2001

Radiation cell killing

• Cell survival is often characterised as the ratio of thenumber of colonies containing > 50 cells derived fromirradiated cells to the number derived from unirradiatedcells.

• Why 50 or more cells? Because cell coloniessometimes take a while to die out – irradiated cells maybe fatally damaged but might still be able to divide afew times before dying. So 50 is an operational figure –if cell division can proceed to the point of producing 50cells, the cell is considered to have survived.

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Radiation cell killing

Radiation kills cells in different ways –

1. damaging DNA so badly that cells die in mitosis –mitotic cell death

2. damaging DNA more subtly, but enough for cells’ owngenetic surveillance mechanisms to pick up the fact thatthe DNA is damaged and cause the cells to enterprogrammed cell death – apoptosis

Cell survival curves look like this -

HX142 – neuroblastoma; HX58 – pancreas carcinomaHX156 – cervix carcinoma; RT112 – bladder carcinoma

From Steel: Basic Clinical Radiobiology

• These survival curves are linearish on a log plot –

• where N is the number of colonies (>50 cells) formed byirradiated cells, N0 the number formed by unirradiatedcells, S the ratio of the two (‘survival’), and D is radiationdose.

• But they have a rounded-off shoulder, and are clearlynot exactly linear…

Cell survival curves

DN

NlnSln

0

−

= toalproportionelyapproximatis

• Over most of the dose range,except may be below around 1Gy, these curves are describedby the ‘linear-quadratic’ modelproposed by Fowler and Sternin 1958.

• This equation has been themost influential component ofradiotherapy schedule designover the last 25 years.

Cell survival curves – linear-quadratic model

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NS −=

= lnln

Linear-quadratic modelling

• To appreciate the significance of the LQ model, it’simportant to describe another experimental finding (orpiece of dogma, as some slightly contradictory resultshave been obtained over the years).

• If you irradiate cells with a dose D1 which on its own wouldlead to a cell survival S(D1), then leave them for a while(say 24 hours or more) and irradiate them again with adose D2 which on its own would lead to a survival S(D2),the resulting overall cell survival works out around –

)S(D)S(DS 21 ×=survivalOverall

• So survival is multiplicative. Starting with N0 cells, after afirst dose there are N0×S(D1) survivors left, and after asecond there are N0×S(D1)×S(D2). The two doses actindependently of each other – the cell-killing effect of thesecond is not changed by the first fraction.

Linear-quadratic modelling

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• So survival after the two fractions is given by -

• working out as

• So, irradiating cells with a constant dose-per-fraction dgiven over a brief interval once every 24 hours, anddelivering a total dose D in F fractions, survival will be –

( ) ( )( ) ( )( ) ( )( )2121 DSDSDSDSS lnlnlnln +=×=

LQ modelling of a fractionated schedule

( ) ( ) ( )22

21210 DDDDNNS +−+−== βαlnln

BED- dDDdFdFS 2 α=−−=−−= βαβαln

LQ modelling of a fractionated schedule

• The ‘biologically effective dose’ (BED) of a schedule isdefined as

• so that log cell survival is given by

• and, more subtly, BED has the physical meaning of beingthe total dose delivered in a sequence of very smallfractions that has the same biological (cell killing) effect asa radiation schedule which delivers total dose D in afraction size d.

( )( )d1DBED αβ+=

( )BEDα-expS BEDαS =⇒−=ln

Log cell survival curves can have different curvatures

• The curviness of the survival curves is described by the α/β ratio, which has units of Gy.

• A high α/β ratio makes for little curvature, while a low ratio describes much more curvature

• The curvature has a big effect on the survival level after a sequence of many small doses.

• For a very high α/β ratio thequadratic β component isnegligible compared to α;log survival is pretty linear;and so the effect of two 8Gy doses is roughly thesame as that of one 16 Gydose.

Effect of cell survival curviness on the overall survival after a sequence of fractions

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• But for cells with lower α/β ratios, the survival curve bendsmore-and-more steeply down as the dose delivered in asingle fraction increases – and so one 16 Gy fraction will domuch more damage than two 8 Gy fractions.

LQ – an illustration

Consider two imaginary cells lines –

(a) α/β = 10 Gy, α = 0.289 Gy-1;

(b) α/β = 3 Gy, α = 0.190 Gy-1.

Then survival after a single fraction of 2 Gy works out as –

(a) exp(-0.289x2x(1 + 2/10)) = 0.50

(b) exp (-0.190x2x(1+2/3)) = 0.53 (higher than (a))

whereas after a single 4 Gy fraction survival is –

(a) exp(-0.289x4x(1 + 4/10)) = 0.20

(b) exp(-0.190x4x(1 + 4/3)) = 0.17 (lower than (a))

• At larger doses-per-fraction, cell lines with lower α/β ratios are killedrelatively more.

• Conversely, for smaller doses-per-fraction, cell-lines with higher α/βratios are killed relatively more.

Hyperfractionation and α/β ratios

• Tumors and early reacting tissue cells often have α/βratios of around 10 Gy.

• But late complications are often characterised by α/βratios (operational) around 3 Gy.

• So by hyperfractionating – delivering lower doses-per-fraction but more fractions – greater tumor control can beachieved for the same late complication risk.

• For tumors with high α/β ratios, hyperfractionation is avery useful radiobiological modifier of clinical treatments(~ 9% improvement in HNSCC local control at 5 years –Bourhis 2006).

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A practical issue – UK hyperfractionation

• While the UK CHART schedule is a pioneering example ofhyperfractionation and acceleration, hyperfractionatedapproaches are not really widely used in Britain.

• For some tumors (melanoma, probably prostate and breast)α/β is low and hyperfractionation will not be useful (thoughhypofractionation might).

• But for many (eg NSCLC, HNSCC) hyperfractionationwould be beneficial.

• CHART delivers 3 fx per day over 12 days, treats throughweekends, and is logistically difficult.

• But moderate hyperfractionation, achievable by delivering 2fx per day for at least part of longer schedules, withweekend breaks, would be easier to deliver and offer usefultreatment advantages.

Origins of the α and β terms, and an introduction to Thames’ and Dale’s

incomplete repair model of dose-rate effects

Directly lethal event – prob. per cell

= α × δD

Sublethal event –prob. per cell

= ε × δDSecond event converts sublethal damage to an indirectly lethal event –prob. per existing sublethal damage site

= η × δD

• It’s known that sublethal damage gets repaired, beingpretty much gone somewhere between 6-24 hours afterirradiation.

• It’s also clear that sublethal damage isn’t repairedimmediately – otherwise no sublethal damage would everget converted into lethal damage, and cell survival curveswould all be straight.

• The most standard modelling approach assumes that if Msublethal lesions exist at time t, µ×M×δt are repairedduring the next δt , so that sublethal damage fades awayexponentially ∝ exp(-µt).

Modelling the dose-rate effect – anoutline of Thames’ and Dale’s approach

• Consider a dose of radiation D delivered in a brief time T, sothat the dose-rate is R = D/T, where µT « 1 so that littlesublethal damage is repaired during the fraction.

• It’s easy to show that by the end of the fraction -

� the average number of directly lethal lesions per cell

= α RT = αD

� the average number of indirectly lethal lesions per cell

= ½εηR2T2 = ½εη D2

• So the average total (direct and indirect) number of lethal lesions per cell is αD + ½εη D2 or αD + βD2

Modelling the dose-rate effect –an outline of Dale’s approach

Modelling the dose-rate effect –an outline of Thames’ and Dale’s approach

• Binomial statistics: if there are S sites per cell that can potentially betransformed into (directly or indirectly) lethal lesions, and aprobability r that each one has been transformed, then:

� The average total number of lethal lesions per cell NL = S × r

� The probability p of a cell surviving is just the chance of there being no lethal lesions in it, so

• Poisson statistics: if S is very large, and r is small so that the averagenumber of lethal lesions per cell NL is a finite number, then

S

)r1(p −=

( ) ( ) ( )2S expNLexprSexp)r1(p DD βα −−=−=−≈−=

• Now consider a fraction of longer duration T, during whichsublethal damage can be repaired.

• Obviously the average # directly lethal lesions per cell atT, the end of the fraction, will still be αD.

• It can also be shown that at T the average # of indirectlylethal lesions per cell will be

• where

• Since g(µT) = 1 at µT = 0 and decreases with rising µT,the quadratic β component of log cell survival plotslessens as the dose-rate drops and T rises.

Modelling the dose-rate effect –an outline of Thames’ and Dale’s approach

( )µTD2 gβ

( ) ( )( )( )2μT

μT

exp

1μT

2μT

−+−=g

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• Consequently when the dose-rate is lower, larger doses(delivered in a single fraction) are needed to reduce cellsurvival by a constant factor, and dose-response curvesare straighter.

Dose-rate 150 cGy min-1 Dose-rate 1.6 cGy min-1

External beam or HDR brachy LDR brachy

The dose-rate effect

From Steel: Basic Clinical Radiobiology

Repair, fractionation and dose-rate effects summarised

• The curvature of cell-survival plots means that use of lower doses-per-fraction (hyperfractionation) tilts the balance of damage away fromendpoints with lower α/β ratios, towards those with higher ratios.

• This is useful, as many tumors have higher α/β ratios than those whichcharacterise late complications.

• Hyperfractionation is quite a powerful tool for improving the therapeuticratio, but is not used that widely in the UK.

• α is associated with directly lethal radiation lesions; β is associated withindirectly lethal lesions derived from sublethal damage.

• Inter-fraction intervals of at least 6 hours are required for completerepair of sublethal damage between fractions.

• The fairly slow rate of sublethal damage repair (T½ ~ 1 hour) leads to adose-rate effect: when delivered at low dose-rates (~1cGy min-1)substantially higher doses are required to have the same effect asdoses delivered at high dose-rates (~1Gy min-1) .

2. Repopulation – accelerated proliferation

• When some tumors are irradiated, their clonogenproliferation rate begins to increase.

• Mechanisms behind this effect are contentious.

• The effect itself is less contentious, though still not comprehensively characterised by clinical data.

Adapted from Withers et al 1988

• Analyses of HNSCC and NSCLC data have foundrepopulation compensating for around 0.7 Gy per day ofradiation cell killing.

• The effect is not clear cut though. For instance, the datashown on the last slide was just a collection ofprescribed doses plotted against treatment duration.

• When tumor control is plotted against dose and duration,time trends are far less obvious.

• Nevertheless, several analyses (Withers, Rezvani,Hendry, Roberts) of HNSCC data have foundaccelerated repopulation running around 0.7 Gy day-1,with some indications that it doesn’t begin until around 4-5 weeks into treatment.

Repopulation – accelerated proliferation

Repopulation – accelerated proliferation

Here are some tumor control plots for the Withers HNSCC data, broken down into group 2 (T1, T1-2, T2), group 3 (T2-3, T3), group 4 (T3-4,T4) and group 0 (other T-stage combinations). Time trends are not obvious, though detailed modelling finds repopulation running at around 0.7 Gy day-1

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Repopulation – accelerated proliferation

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• In a 2006 HNSCC meta-analysis, Bourhis et al found hyperfractionation to be beneficial, with an ~ 9% gain in local control cf conventional fractionation

• Moderate (1-2 week) schedule acceleration is also useful, with ~ 8% gain

• But nothing is gained from further acceleration, which still produces ~ 8% gain cf conventional fractionation

• Mucosal proliferation also accelerates during radiotherapy, allowing higher doses to be given using longer treatments without excessive early reactions

• So significant acceleration is usually accompanied by reduced prescribed doses, to avoid exceeding the tolerance of the oral mucosa

Repopulation – accelerated proliferation Repopulation – accelerated proliferation summarised

Accelerated proliferation runs at similar rates in HNSCC and oral mucosa. Sowhile improvements can be made by accelerating unnecessarily longschedules, further acceleration achieves little, since tumor repopulationreduction is offset by dose decreases required to avoid intolerable mucositis.

Mucositis discriminantanalysis, showing tolerable and intolerable HNSCC schedules in a plot of dose versus treatment duration.

The standard formalism accounting for repopulation is

BED = αD(1+(β/α)d) – λ(T-TK)

where TK is the onset point for accelerated repopulation, and λ is the dose-per-day offset by repopulation.

3. Reoxygenation and the oxygen effect• Oxygen very substantially enhances radiation cell-killing.

• The degree of enhancement is broadly independent of the level of cell-killing in the absence of oxygen.

• Dose is effectively increased by the oxygen enhancement ratio (OER),which approaches a factor of 3 in fully oxygenated conditions.

Figures from Steel: Basic Clinical Radiobiology

• Enhancement is due to fixation of free-radicals createdby radiation –

RH in absence of oxygenRH R˙ + H˙

ROOH in presence of oxygen

The oxygen effect

For enhancement to occur,oxygen must be present atthe time of irradiation, orwithin a few milliseconds

Figure from Steel: Basic Clinical Radiobiology

• Poor outcomes can be expected for hypoxic tumors, sincethe absence of oxygen might effectively reduce dose by upto a factor of 2 or 3.

• Hypoxia effects can be modified using hyperbaric oxygenor hypoxic radiosensitisers such as misonidazole.

• These approaches typically improve local control rates byaround 5% for HNSCC, bladder, cervix and lung patients.

• Substantially more patients are thought to have hypoxictumors.

• Why then don’t hypoxia modifiers have a greater impact ontreatment outcome?

Oxygen effect• Immediately after irradiation a tumor’s hypoxic fraction

rises sharply – because well-oxygenated cells arepreferentially killed.

• But in animal systems the hypoxic fraction falls againquite rapidly to a level around that pre-irradiation –‘reoxygenation’.

• Mechanisms are contentious.

Oxygen effect - Reoxygenation

Figs from Jack Fowler symposium 2003

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• So it’s plausible that trials of hypoxia-modifiers show only 5%improvements in local control because in many patients earlyhypoxia is moderated by re-oxygenation.

• A corollary is that very short schedules may run into problems withtumor control (as well as early reactions).

Data from a rat experiment (Moulder et al 1976), showing isoeffective doses (correctedto 2 Gy fractionation using α/β = 10 and 100 Gy) for 50% tumor control rates. For eitherα/β value, very short isoeffective schedules require elevated dose-levels.

Oxygen effect – Reoxygenation

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• Oxygen powerfully enhances radiation cell killing.

• So poor outcomes are expected for hypoxic tumors.

• Reducing tumor hypoxia by using modifiers such ashyperbaric oxygen or misonidazole leads to ~ 5%improvement in local control at several tumor sites.

• Methods for identifying patients likely to benefit fromhypoxia-modifying treatments (those with high initialtumor hypoxia and limited reoxygenation) would allowhypoxia modification to be deployed more efficiently.

• Very short schedules may not allow enough time forreoxygenation.

Oxygen effect - summary

4. Reassortment – cell cycle effects

• Like chemotherapy, sensitivity of cells to radiation varies with position in the cell cycle.

• Unlike chemotherapy, cells are at their most resistant to radiation in S-phase, probably because of enhanced DNA repair through homologous recombination, survival potentially being an order of magnitude higher than for cells in G1 and G2.

• So after radiation, an increased percentage of cells will lie in S-phase.

• Together with cell-cycle blocks at checkpoints following irradiation, this phenomenon has the potential to induce a degree of cell cycle synchrony amongst tumor clonogens.

• Synchrony might be exploitable by delivering a second cytoxic agent dose at an optimal time after the first.

• For instance, one cell cycle-time after irradiation many surviving cells will be back in S-phase, and if they are treated at that point using an agent with high S-phase sensitivity, enhanced cell kill might be achieved.

• But disappointing results have been achieved using this approach, perhaps because cell cycle times within tumors are quite variable, causing synchrony to be lost.

Reassortment – cell cycle effects

5. Radiosensitivity

• Studies have found correlations between tumor cellradiosensitivity (eg surviving fraction after 2 Gy) and tumorcontrol rates, exploring variations between both differenttumor types and individuals.

• Likewise, correlations have been found between normaltissue damage and fibroblast and lymphocyteradiosensitivities.

• Given the correlations, it’s intuitively appealing to explorethe potential of dose individualisation based onradiosensitivity assays.

• This approach is not yet very advanced, partly because cellsurvival can be difficult to measure rapidly for patients, andpartly because ...

• Dose response curves are sigmoidal

• Tumor response curves lie to the left of normal issue curves,and tend to be less steep.

• Unless dose-individualisation is smart, overall control andcomplication rates can be very similar to conventional dose-prescription, just distributed differently amongst patients.

Radiosensitivity and the therapeutic window

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• In particular, to individualise dose effectively, more thanjust a correlation (however good the p value) betweenoutcome and radiosensitivity is required.

• Tests are needed which could identify patients who areparticularly likely to fail.

• By targetting these specific patients with higher doses,their chances can be improved without raising thecomplication rate for the treatment as a whole nearly asmuch as if doses were raised for a larger, less focussedgroup.

• Work is ongoing.

Radiosensitivity and the therapeutic window 6. Remote (?) cell kill – the bystander effect

• Evidence is piling up that radiation damage is not acompletely local phenomenon – that is, some cells thatare damaged or killed after irradiation may have beentraversed by absolutely no photons or electrons.

• Data comes from elaborate low-dose and microbeamstudies which deliver such low or highly-targetted dosesthat only relatively few cells are directly irradiated; andfrom simpler experiments irradiating cells in one part of aPetri dish and exploring the effect on cells elsewhere inthe dish.

• Implication is that radiation action on one cell generateschemical messengers which damage other cells.

• This is a change in paradigm ...

• Physically, the impact on treatment depends on thedistance the messenger will diffuse through tissue.

• Belyakov et al (2005) has obtained a distance of ∼ 1mmin a reconstructed skin system.

• Biochemically, the agent(s) involved presumably presentfurther targets for radiation modifiers...

6. Remote (?) cell kill – teatment impact Classical radiobiology – summary

• The curvature of cell-survival plots means thathyperfractionation tilts damage away from endpoints withlower α/β ratios (often late complications), to those withhigher ratios (often tumor control).

• An HNSCC meta-analysis found hyperfractionation gives~ 9% gain in local control cf conventional fractionation

• Moderate (1-2 week) schedule acceleration usefully limitsaccelerated tumor repopulation, HNSCC meta-analysisshowing an ~ 8% gain

• Little is gained from further acceleration, which requiresdose-reduction and still produces ~ 8% gain compared toconventional fractionation

Classical radiobiology – summary

• Tumor hypoxia-modifiers produce ~ 5% improvement inlocal control for several cancers.

• Identifying patients likely to benefit from hypoxia-modifiers would allow more efficient deployment.

• Very short schedules may limit reoxygenation.

• Disappointing results have been achieved using cellsynchrony approaches.

• Dose-individualisation generally requires predictiveassays with good sensitivity and specificity.

• Bystander effects occurring on a 1 mm length-scale in-vivo will have limited physical impact on treatments.

TThank you for your attentionhank you for your attention

Classical radiobiology