Abbas Nasreddine
email: a.nasreddine@aerial-crt.com

Florent Kuntz

Ziad El Bitar

Absorbed dose to water determination for kilo-voltage X-rays using alanine/ EPR dosimetry systems

Keywords:

Alanine's relative response to kilo-voltage X-rays, compared to 60 Co reference quality beam, was studied in this work, in order to determine correction factors to be applied to alanine's response when irradiated with low to medium energy X-rays (up to 300 keV).

The relative response to kilo-voltage X-rays of Aerial's alanine dosimeters was determined by three distinct methods: experimental measurements using alanine dosimeters and a calibrated PTW Farmer 30013 ion chamber, Monte Carlo simulations using MCNPX code and finally, analytical calculations based on weighting of X-ray spectra by NIST's published mass energy absorption coefficients. Two sets of X-ray beam qualities, covering high voltages ranging from 50 kV up to 280 kV, were used to study the energy dependence of the alanine dosimeter's response. Obtained results were consistent within 2.1% (average standard deviation at k = 1).

Introduction

Nowadays, low to medium energy X-ray (up to 300 keV) irradiators start to replace irradiators using radioactive sources like Cesium ( 137 Cs) and Cobalt ( 60 Co) gamma sources [START_REF] Dodd | Replacement of 137Cs irradiators with X-ray irradiators[END_REF] [START_REF] Tadokoro | Problems with irradiators[END_REF], mainly in the fields of blood irradiations [START_REF] Seglam | Blood irradiation[END_REF], Sterile Insect Technique (SIT) [START_REF] Dyck | Sterile Insect Technique Principles and Practice in Area-wide Integrated Pest Management[END_REF] and food irradiations (Baraki-Golan and Follett, 2017) [START_REF] Moosekian | X-ray irradiation as a microbial intervention strategy for food[END_REF]. This drift towards kilo-voltage X-ray generators is mainly driven by the difficulty of acquiring and transporting radioactive sources, as well as the reassuring radiation safety that provides self-shielded X-ray irradiators to its operators.

Alanine/EPR (Electron Paramagnetic Resonance) dosimetry systems are well used for reference, transfer and routine dosimetry. Their very stable and reproducible measurement insures a low uncertainty on absorbed dose determination. Yet, for low to medium energy X-rays, it has been reported in many studies [START_REF] Anton | Relative response of the alanine dosimeter to medium energy X-rays[END_REF]) [START_REF] Waldeland | The energy dependence of lithium formate and alanine EPR dosimeters for medium energy Xr ays[END_REF] [START_REF] Khoury | Alanine-EPR as a transfer standard dosimetry system for low energy X radiation[END_REF] [START_REF] Zeng | The response of alanine to a 150 kVp X-ray beam[END_REF]) that alanine's response with respect to water is lower than unity, as it is for photon energies higher than 200 keV. [START_REF] Khoury | Alanine-EPR as a transfer standard dosimetry system for low energy X radiation[END_REF] determined the relative response of alanine dosimeters purchased from Aerial (Illkirch, France). A set of dosimeters was irradiated with 125 kV X-rays. Another set of dosimeters was irradiated with 60 Co gamma rays (average photon energy of 1.25 MeV). Results showed that the ratio of alanine's response to 60 Co with respect to X-rays is equal to 1.2, thus, meaning that alanine's response to 60 Co is 20% higher than alanine's response to 125 kV X-rays.

Anton et Büermann [START_REF] Anton | Relative response of the alanine dosimeter to medium energy X-rays[END_REF] carried out Monte Carlo calculations as well as experimental measurements, in order to study alanine's relative response for medium energy X-rays, with tube potentials ranging from 30 to 280 kV. Their work showed that alanine's response drops to 64% for an irradiation at 30 kV, compared to a 100% response in the case of 60 Co reference beam.

Waldeland et al. [START_REF] Waldeland | The energy dependence of lithium formate and alanine EPR dosimeters for medium energy Xr ays[END_REF] studied the dose to water energy dependence of alanine dosimeters. Monte Carlo simulations and experimental measurements were carried out with tube voltages ranging from 50 to 200 kV. Experimental measurements showed that alanine's response in case of X-ray irradiations with respect to 60 Co beams varied from 0.68 to 0.9 at 50 kV and 200 kV respectively.

Three different methods are developed in this work to study the alanine dosimeter's relative response to kilo-voltage X-rays, compared to 60 Co. Absorbed dose to water measurements with alanine dosimeters could be underestimated in case of kilo-voltage X-ray irradiations, if the EPR dosimetry system is calibrated with high energy photons (gamma or X-rays) and electron beams [START_REF] Waldeland | Review of the dose-to-water energy dependence of alanine and lithium formate EPR dosimeters and LiF TL-dosimeters e Comparison with Monte Carlo simulations[END_REF]. Thus, the goal of this study is to determine correction factors to be applied to alanine's response when irradiated with kilo-voltage X-rays.

Material and methods

Alanine dosimeters and EPR spectrometry

Aerial's commercial alanine dosimeters (Lot 09/11) [START_REF] Kuntz | Alanine -ESR dosimetry, feasibility and possible applications[END_REF] were used in this work. Alanine pellets have a 4 mm diameter, a thickness of 2.35 mm and an average mass of 36.05 ± 0.05 mg, with a composition of 93% of pure L-alanine and 7% binder.

During irradiations, 5 alanine pellets were placed at the surface of a PMMA (PolyMethylMethacrylAte) phantom having 10 cm in diameter and 1.5 cm in thickness. For some beam qualities, an additional 5 mm PMMA plate was added on top of the dosimeters.

EPR readout was performed using a Freiberg Instruments/ Magnettech MS5000 spectrometer (Freiberg, Germany) using the following parameters: magnetic field sweep width of 2 mT, sweep time of 5s, modulation amplitude and frequency of 0.7 mT and 100 kHz respectively, microwave power and frequency of 10 mW and 9.253 GHz respectively. Fig. 1 shows the measured EPR spectrum of an irradiated alanine dosimeter. Measured spectra were taken as input in the AerEDE2019 software, developed and commercialized by Aerial (Illkirch, France), in order to correct the dosimeter's response (EPR spectrum's central peak height per mass unit) with irradiation temperature. Absorbed dose to water can be measured by using a calibration curve that correlates the dosimeter's response to a reference absorbed dose to water. In this study, only the dosimeter's response was measured by EPR, in the case of X-ray irradiations.

X-ray irradiations

For irradiations carried out at Aerial, a 3 kW high voltage generator powered our BALTEAU-NDT TSD 160/0 X-ray tube, with a maximum applicable high voltage of 100 kV, in order to generate X-rays with a maximum current of 30 mA. The X-ray tube does not have any inherent filtration except the exit window of 0.8 mm of Beryllium.

A second set of irradiations was carried out at the National Physical Laboratory (NPL) at two high voltages of 135 and 280 kV.

Beam qualities used in this study are listed in Table 1. For each beam quality, high voltage and external added filtration are listed, as well as two different beam specifiers: first half value layer (HVL) in aluminum, and the beam's effective energy (E eff ) in aluminum. Effective energy is defined as the energy of a mono-energetic beam having the same HVL as its equivalent poly-energetic beam. Values of HVL and E eff were calculated with the SpekCalc software [START_REF] Poludniowski | SpekCalc: a program to calculate photon spectra from tungsten anode X-ray tubes[END_REF].

Many codes of practice (IAEA, 2006) [START_REF] Chair | AAPM protocol for 40-300 kV x-ray beam dosimetry in radiotherapy and radiobiology[END_REF]) [START_REF] Klevenhagen | The IPEMB code of practice for the determination of absorbed dose for x-rays below 300 kV generating potential (0.035 mm Al -4 mm Cu HVL; 10 -300 kV generating potential)[END_REF] recommend using the first HVL as beam quality specifier, for low energy X-rays. In this study, we used the effective energy as the sole beam quality specifier for the sake of good comparison of already published data. Effective energy can be directly related to the first HVL using the photon attenuation law and NIST's photon attenuation coefficients [START_REF] Hubbell | Tables of X-ray mass attenuation coefficients and mass energy-absorption coefficients from 1 keV to 20 MeV for elements Z = 1 to 92 and 48 additional substances of dosimetric interest[END_REF].

Correction factors

Three investigation methods were carried out in order to study the alanine dosimeter's relative response to kilo-voltage X-rays compared to 60 Co gamma rays. Based on obtained results, one can calculate correction factors that should be applied to absorbed dose to water measurement performed with alanine in the case of low to medium energy (up to 300 keV) X-ray irradiations. The correction factors can be directly related to the dosimeter's relative response by this equation:

= k f 1 corr Q Q Q Q , , 0 0
where k corr Q Q , 0 is the correction factor to be applied directly to absorbed dose to water measured by alanine dosimeters, f Q Q , 0 is the alanine's relative response to a specific X-ray quality (Q) compared to a reference quality (Q 0 ) such as 60 Co. Thus, true absorbed dose to water can be expressed as such:

= × D k D w Q corr Q Q w Q , 0 0
where D w Q 0 is the true absorbed dose to water, relative to a reference beam quality (Q 0 ), and D w Q is the absorbed dose to water measured by alanine dosimeters after irradiation with X-ray beam quality (Q). This method can be applied for irradiations at doses lower than 10 kGy, while at higher doses, the correction factor should be firstly applied to the dosimeter's response, due to the non-linearity of the latter versus absorbed dose to water [START_REF] Goodman | Radiation dosimetry using alanine and Electron Pramagnetic Resonance (EPR) spectroscopy: a new look at an old topic[END_REF], thus, absorbed dose to water can be then correctly estimated using the EPR system's calibration curve.

Experimental measurements

Two sets of irradiations were done in order to determine alanine's response per dose to water unit, for a set of X-ray beam qualities, with respect to 60 Co reference quality. These irradiations consisted on determining this factor:

= f r D r D ( / ) ( / ) exp w Q w Q0
where f exp is the alanine's relative response measured by experimental setups, r is the alanine dosimeter's response measured by EPR spectrometry, D w is the absorbed dose to water measured by a calibrated ion camber, Q is one of the X-ray beam qualities and Q 0 is the 60 Co reference quality.

The first set of irradiations was carried out at Aerial with tube voltages ranging from 50 kV up to 100 kV. The absorbed dose to water was measured using a PTW 30013 waterproof Farmer ion chamber, which is calibrated in terms of absorbed dose to water for X-ray radiations qualities, with a traceability to PTB's water calorimetry secondary standard. The measured absorbed dose to water can be expressed as such:

= D M N k k . . . w D Q T P , w
where D w is the corrected measurement of the absorbed dose to water, M is the ion chamber reading, N Dw is the dose to water calibration coefficient, k Q is the beam quality correction factor and k T, P is the air density correction factor. The irradiation geometry consisted of 5 alanine dosimeters placed in a PMMA holder, as shown in Fig. 2, irradiated with a vertical photon beam. In addition, 1 cm of PMMA was placed below the dosimeters, which were positioned in such a way that the distance between the Xray tube's focal point and the surface of the dosimeters was equal to 80 cm.

The second set of irradiations, carried out at NPL, consisted of placing 4 alanine dosimeters inside a solid water holder shaped as an ion chamber. This alanine holder was then placed in a 2 cm thick WT1 Solid Water slab. Solid Water slabs were purchased from Phoenix Dosimetry Ltd. Solid Water plates were added between the beam exit window and the dosimeters in order to have the alanine pellets at a water equivalent depth of 2 cm. A total thickness of 26cm of solid water slabs was added behind the dosimeters to ensure full backscatter conditions as shown in Fig. 3. Dose output was measured using NPL's PTW 30012 Farmer ion chamber, which is calibrated in air kerma, with a traceability to NPL's 300 keV free air chamber primary standard. Absorbed dose rate to water was determined using the IPEMB (Institute of Physics and Engineering in Medicine and Biology) code of practice using the in-phantom method for the determination of the absorbed dose to water.

A comparison between the two ion chamber readings (PTW 30013 dose to water calibration, and PTW 30012 air kerma calibration) was performed at NPL. Both chambers were positioned at 2cm water equivalent depth in the phantom showed in Fig. 3 and were irradiated in the same conditions (ambient temperature and pressure). Absorbed dose to water was measured by both chambers after 5 irradiations of 30 s each, at 135 kV and then at 280 kV. Results showed that there is a difference between the two measurements of both instruments. The average ratios of the PTW 30013 readings versus the PTW 30012 readings were 0.938 and 0.985 for irradiations at 135 kV and 280 kV respectively. Thus, in order to compare results obtained after irradiations at NPL, to the results of irradiations performed at Aerial, the absorbed dose to water, used to determine the f exp factor, needs to be corrected. This correction is needed to ensure that the alanine's response is always compared to a dose unit measured by the same reference instrument, which, in this study, is the PTW 30013 ion chamber.

Monte Carlo simulations

The MCNPX code (version 2.7.0) (D. B. [START_REF] Pelowitz | MCNPX Users Manual Version 2[END_REF] was used to calculate the ratio of the absorbed dose between alanine dosimeter and water. The electron and photon energy cut-offs were set to 1 keV. The true alanine dosimeter composition (93% alanine -7% binder) was simulated in the code as well as the same experimental irradiation geometries. Cylindrical alanine pellets, placed in PMMA holders inside the irradiation cabinet at 80cm from the X-ray source, were simulated in the case of irradiations carried out at Aerial. Alanine dosimeters placed inside a Solid Water phantom at a depth of 2cm of water equivalent material and placed at 77cm from the X-ray source were simulated to reproduce irradiations carried out at NPL. The calculated factor is:

= f D D MC dos w
were f MC is the alanine's relative response calculated by Monte Carlo Simulations, D dos is the absorbed dose in the dosimeter and D w is the absorbed dose in water. Firstly, calculations were done using mono-energetic photon beams covering the range of 1 keV up to 10 MeV. The ratio of absorbed dose (dosimeter to water) was compared to the ratio of the mass energy absorption coefficients of alanine to water based on NIST's data.

Another set of calculations, taking as input X-ray spectra calculated by SpekCalc (see Table 1), were done to determine the dosimeter to water absorbed dose ratio, as a function of the X-ray spectra's effective energies.

Analytical calculations

A C++ code was developed to analytically calculate the ratio of absorbed dose in the dosimeter with respect to water, taking as entry the energetic fluence distribution given by SpekCalc, and then weighting the distribution by mass energy absorption coefficients published by NIST. The average execution time of the code does not surpass 5 s, for a computer with a central processing unit (CPU) running at a base frequency of 2.3 GHz. The calculated factor was inspired by a factor calculated in [START_REF] Lessard | Validating plastic scintillation detectors for photon dosimetry in the radiologic energy range[END_REF] for a validation study of a plastic scintillator detector used for photon dosimetry. The calculated factor adapted to this study is: where f w is the alanine's relative response determined by analytical calculations, E max is the maximal photon energy of the X-ray spectrum, E is the photon energy at each integration step, μ en /ρ(E) is the mass energy absorption coefficient at the energy E, ϕ(E) is the beam fluence at the energy E, μ att is the average attenuation coefficient given by NIST and x is the dosimeter (or water) thickness.

∫ ∫ = × ( ) ( ) f E E ϕE d E E E ϕE d E e e
The first term of the correction factor calculates the energy deposition of an incident photon beam inside the dosimeter and water material, while the second term calculates the beam percentage that is actually being attenuated in the dosimeter and water volume, thus the percentage that is responsible of the energy deposition.

Reference beam quality correction factor

In most cases, the alanine/EPR dosimetry system is calibrated in terms of absorbed dose to water for a 60 Co reference beam (mean photon energy = 1.25 MeV). In other cases, alternative beam qualities are used as reference beam qualities such as high energy electron or Xray beams [START_REF] Araki | Comparison of high-energy photon and electron dosimetry for various dosimetry protocols[END_REF]. Thus, when measuring alanine dosimeters that were irradiated with low to medium energy X-rays, a difference of the dosimeter's response will arise from the difference of the irradiation beam quality.

This difference is taken into account in the case of experimental measurements (see section 3.1) where the dosimeter's response is evaluated in the case of both qualities (X-rays and 60 Co gamma rays). However, this reference beam difference is not taken into account with factors determined by Monte Carlo simulations nor by analytical calculations, thus, in case of EPR measurements with a different reference beam quality calibration, a second factor should be added to the ones described in sections 3.2 and 3.3, which is:

⎜ ⎟ = ⎛ ⎝ ⎞ ⎠ f D D Q dos w Q 0 0
where f Q0 is the alanine to water absorbed dose ratio for the reference beam quality, Q 0 is the reference beam quality, D dos is the absorbed dose in the dosimeter and D w is the absorbed dose to water. Therefore, the correction factors become:

= f f f / MC Q Q MC Q , 0 0 = f f f / w Q Q w Q , 0 0
where f MC and f w are the alanine's relative responses determined by Monte Carlo simulations and analytical calculations respectively, as described in sections 3.2 and 3.3.

Results and discussion

Experimental measurements

Alanine's response per absorbed dose to water (r/D w ), using X-ray qualities with respect to 60 Co reference quality, was measured. Obtained results are plotted in Fig. 4. Results are compared to ones reported by Anton [START_REF] Anton | Relative response of the alanine dosimeter to medium energy X-rays[END_REF] and Waldeland [START_REF] Waldeland | The energy dependence of lithium formate and alanine EPR dosimeters for medium energy Xr ays[END_REF]. A good agreement is noticed between the three data series over all the energy range. Waldeland's data were studied as a function of effective energy, whereas Anton's data were published as a function of the X-ray spectra's average energy. A study done by [START_REF] Butler | Absorbed dose determination in kilovoltage X-ray synchrotron radiation using alanine dosimeters[END_REF], using Anton's published data, showed a conversion of Anton's used average energies into effective energies, and these are the values that are reported in Fig. 4. Error bars in Fig. 4 represent uncertainties (at k = 1). An uncertainty budget of 2.5% (k = 1) was calculated in the case of irradiations carried at Aerial, and another budget of 2.4% (k = 1) was calculated in the case of irradiations done at the NPL X-ray irradiation facility.

Anton mentioned in his work [START_REF] Anton | Relative response of the alanine dosimeter to medium energy X-rays[END_REF]) that alanine's relative response drops down to 64% in case of low energy Xray irradiations, which one can notice in Fig. 4 at an effective energy of 15.9 keV. Waldeland [START_REF] Waldeland | The energy dependence of lithium formate and alanine EPR dosimeters for medium energy Xr ays[END_REF] stated that the experimental relative response of alanine varied from 0.68 up to 0.9 over the studied effective energy range (32 keV up to 99 keV). Results obtained in this work are consistent with Anton and Waldeland's data over the studied effective energy range (25 keV up to 168 keV), yet, one can notice that results obtained in this work are higher than published data. This difference is mainly due to the difference in size and composition of the alanine dosimeters between the three studies, as well as the difference in the used experimental setup.

In Anton's study, the experimentally determined relative response consists of the ratio of the measured dose by a 60 Co calibrated alanine/ EPR system versus the delivered dose, whereas Waldeland used Monte Carlo simulations as well as experimental measurements in order to estimate the same response presented in section 3.2. Both approaches showed very similar results, as presented in Fig. 4. However, it was reported in [START_REF] Goodman | Radiation dosimetry using alanine and Electron Pramagnetic Resonance (EPR) spectroscopy: a new look at an old topic[END_REF]) that alanine's response is non-linear versus absorbed dose to water for doses higher than 10 kGy, thus, one should be careful to apply the adequate correction factor to the dosimeter's response rather than apply it directly to the measured dose for doses higher than 10 kGy.

We can also note that a convergence tendency is observed in case of effective energies that are higher than 150 keV, yet, true water equivalency (relative response equal to unity) is not observed in the studied effective energy range.

Monte Carlo simulations

Ratios of the absorbed dose in the dosimeter with respect to absorbed dose to water were calculated using MCNPX simulations. The calculated ratios are represented in Fig. 5, as well as data published by Anton and Waldeland. For this work, presented data correspond to the Monte Carlo factor listed in section 3.4, which takes into account the reference beam quality difference between X-rays and 60 Co. The same factor is calculated by Anton and Waldeland using EGSnrc Monte Carlo simulation code [START_REF] Kawrakow | The EGSnrc Code System: Monte Carlo simulation of electron and photon transporttechnical Report PIRS-701[END_REF]. Error bars represent simulation standard deviations and experimental uncertainties (k = 1).

Obtained results are consistent with already published data [START_REF] Anton | Relative response of the alanine dosimeter to medium energy X-rays[END_REF] [START_REF] Waldeland | The energy dependence of lithium formate and alanine EPR dosimeters for medium energy Xr ays[END_REF]. Plotted values of all three studies represent the same calculated factor. A difference between results is noticed, especially at low effective energies ranging from 15.9 keV to 40 keV, where we can see that results obtained in this study are higher than the ones obtained by Anton and Waldeland. This is due to many factors such as the difference in the used Monte Carlo code between this work (MCNPX) and published data (EGSnrc), the difference of the size and composition of the modelled alanine dosimeters and finally the difference of the irradiation geometry (phantom material, surrounding environment).

Analytical calculations

The alanine to water dose ratio was calculated analytically based on the weighting of X-ray spectra by mass energy absorption coefficients given by NIST, while taking into account the beam attenuation inside of the dosimeter volume. Fig. 6 shows the comparison of these factors to ones determined in this study by Monte Carlo simulations as well as experimental measurements.

All plotted results in Fig. 6 represent the dosimeter's relative response in case of X-ray irradiations with respect to 60 Co reference beam quality. The error bars represent uncertainties (k = 1).

Results obtained by analytical calculations and ones obtained by Monte Carlo simulations are in a very good agreement with an average standard deviation of 0.7%, while an average discrepancy of 3.2% is noticed between results obtained by calculations and experimental results. Average standard deviation of the results obtained by the three correction methods is 2.1%.

A clear difference is noticed between results obtained by Monte Carlo simulations and calculations in the first hand, and experimental measurements on the other hand. This difference was also reported in many studies [START_REF] Anton | Relative response of the alanine dosimeter to medium energy X-rays[END_REF] [START_REF] Waldeland | The energy dependence of lithium formate and alanine EPR dosimeters for medium energy Xr ays[END_REF]) [START_REF] Zeng | The response of alanine to a 150 kVp X-ray beam[END_REF] [START_REF] Khoury | Alanine-EPR as a transfer standard dosimetry system for low energy X radiation[END_REF] [START_REF] Waldeland | Review of the dose-to-water energy dependence of alanine and lithium formate EPR dosimeters and LiF TL-dosimeters e Comparison with Monte Carlo simulations[END_REF], and it arises from the fact that simulations and calculations take into account physical dose deposition only, without taking into account the free radicals creation process that is the base of measurements done by EPR spectrometry. Thus, the ratio of free radical creation yield for X-rays compared to 60 Co needs to be evaluated and then integrated in the determination of alanine's relative response by Monte Carlo simulations and analytical calculations.

Conclusion

Alanine dosimeter's relative response to kilo-voltage X-rays, compared to 60 Co reference beam quality, was studied in this work. The relative response was determined by three different methods. Studied Experimental measurements were performed at Aerial and NPL to study alanine's relative response per dose to water unit for different Xray beam qualities. Obtained results were in a good agreement with already published data [START_REF] Anton | Relative response of the alanine dosimeter to medium energy X-rays[END_REF] [START_REF] Waldeland | Review of the dose-to-water energy dependence of alanine and lithium formate EPR dosimeters and LiF TL-dosimeters e Comparison with Monte Carlo simulations[END_REF] [START_REF] Waldeland | The energy dependence of lithium formate and alanine EPR dosimeters for medium energy Xr ays[END_REF]), yet a slight difference is noticed due to the difference in the dosimeter's composition and irradiation geometry.

Monte Carlo simulations and analytical calculations determined the ratio of the absorbed dose in alanine with respect to water. Results were in a good agreement with ones obtained by Waldeland and Anton, as well as with results obtained in this study by experimental measurements (average standard deviation of 2.1%, at k = 1).

Measuring absorbed dose to water with alanine dosimeters irradiated with kilo-voltage X-rays, using a 60 Co calibrated EPR system, requires application of correction factors to the dosimeter's measured EPR response. The three studied methods of determination of alanine's relative response to kilo-voltage X-rays ensure a good estimation of such correction factors.

Analytical calculations seem to be a simple, rapid and trustworthy method to determine correction factors to be applied to alanine's response measured by EPR spectrometry. Yet, the energy dependence of the free radical creation yield (G-value [radicals]/100eV) in alanine needs to be studied in order to integrate this phenomenon in both, simulations and calculations.

Fig. 1 .

 1 Fig. 1. EPR spectrum of irradiated alanine dosimeter. Resonance peaks between 325 mT and 340 mT are intrinsic to alanine radicals. Singlet resonance peak at 350 mT corresponds to the spectrometer's internal ruby reference.

Fig. 3 .

 3 Fig. 3. Side view of the experimental setup using Solid Water phantom for irradiations carried out at NPL.

Fig. 4 .

 4 Fig. 4. Aerial's alanine dosimeter response (blue) at different beam qualities, compared to published data (Anton -black) (Waldeland -red). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5 .Fig. 6 .

 56 Fig. 5. Alanine to water dose ratio calculated by Monte Carlo simulations at different X-ray qualities with respect to 60 Co reference quality.

Table 1 X

 1 -ray beam qualities. Table represents (from left to tight) high voltage, added filtration of aluminum, copper, tin, solid water, PMMA, and beam quality specifiers: first HVL and effective energy in aluminum.

	Irradiation site	HV [kV]	Al [mm]	Cu [mm]	Sn [mm]	Solid Water [mm]	PMMA [mm]	HVL1 [mm]	E eff Al [keV]
	Aerial	50	2.39	0	0	0	5	1.81	27.5
	Aerial	70	2.88	0	0	0	5	2.65	31.9
	Aerial	90	3.35	0	0	0	5	3.64	36.3
	Aerial	100	1.43	0	0	0	5	2.57	31.5
	Aerial	100	3.84	0	0	0	5	4.32	39.2
	Aerial	100	4.95	0	0	0	5	4.93	41.7
	Aerial	90	0.96	0	0	0	0	1.52	25.8
	Aerial	100	1.43	0	0	0	0	2.18	29.5
	Aerial	100	3.84	0	0	0	0	4.06	38.1
	NPL	135	1.2	0.27	0	20	0	9.01	58.9
	NPL	280	1	0.26	1.5	20	0	19.6	168

Fig. 2. Top view of the PMMA holder with 5 alanine dosimeters used for irradiations carried out at Aerial.

Acknowledgements

We would like to thank Dr. Anna Subiel and Dr. Peter Sharpe (NPL, Teddington, UK) for providing access to NPL X-ray irradiation facility as well as for their help and guidance during irradiations. A special thanks for Jakob Grünewald Hjørringgaard (Risø -HDRL, Roskilde, Denmark) for the use of the solid water alanine holder. We would like to thank the ANRT (Association Nationale de Recherche et Technologie) for funding this research work.


Rita Fior

Vanda Póvoa

Raquel Mendes

Tânia Carvalho

António Gomes

Nuno Figueiredo

Miguel Godinho Ferreira

Single cell functional and chemosensitive profiling of combinatorial colorectal therapy in zebrafish xenografts

Cancer is as unique as the person fighting it. With exception of few biomarker-driven therapies, patients go through rounds of trialand-error approaches to find the best treatment. Using patientderived cell lines, we show that zebrafish-larvae-xenotransplants constitute a fast and highly sensitive in vivo model for differential therapy response, with resolution to reveal intra-tumor functional cancer heterogeneity. We screened international colorectal cancer therapeutic guidelines and determined distinct functional tumor behaviors (proliferation, metastasis, angiogenesis) and differential sensitivities to standard therapy. We observed a general higher sensitivity to FOLFIRI than to FOLFOX, not only between isogenic tumors but also within the same tumor. We directly compared zebrafish-xenografts with mouse-xenografts and show that relative sensitivities obtained in zebrafish are maintained in the rodent model. Our data also illustrates how KRAS mutations can provide proliferation advantages in relation to KRAS WT and how chemotherapy can unbalance this advantage, selecting for a minor clone resistant to chemotherapy. Zebrafish-xenografts provide remarkable resolution to measure Cetuximab sensitivity. Finally, we demonstrate the feasibility of using primary patient samples to generate zebrafish Patient Derived Xenografts (zPDX) and provide proof-of-concept experiments that compare response to chemo and biological therapies between patients and zPDX. Altogether, our results suggest that zebrafish-larvae-xenografts constitute a promising fast assay for precision medicine, bridging the gap between genotype and phenotype in an in vivo setting. zebrafish xenograft | chemotherapy-functional-screening | colorectalcancer | KRAS | metastasis

INTRODUCTION

Chemotherapy regimens are developed and approved according to a demonstration of average efficacy and safety. However, efficacy rates are averages of individual responses. As result of this "one-size-fits-all" approach, treatments may prove to be successful for some patients but not for others. This is especially relevant in the metastatic scenario where oncology therapy guidelines reach branch points and clinicians face equivalent valid compounds i.e. with similar average response rates. Consequently, many patients go through inefficient treatments, being subjected to unnecessary toxicity.

The current gold standard in cancer biology for personalized screening is direct primary tumor transplantation into immunecompromised mice, also known as patient derived xenografts (PDX). PDXs can generally maintain both inter-individual and genetic heterogeneity of original tumors, mimicking disease responses in patients and thus reflecting the uniqueness of each patient [START_REF] Hidalgo | Patient-derived Xenograft models: An emerging platform for translational cancer research[END_REF]. However, mouse PDXs present two major drawbacks for routine clinical assays: the amount of patient sample required and the time-frame for engraftment and expansion of colonies (months), rendering them unviable for clinical practice.

Zebrafish xenografts offer speed, cellular resolution and the ability to perform large numbers of transplants [START_REF] Zon | The new age of chemical screening in zebrafish[END_REF][START_REF] White | Zebrafish cancer: the state of the art and the path forward[END_REF][START_REF] Veinotte | Hooking the big one: the potential of zebrafish xenotransplantation to reform cancer drug screening in the genomic era[END_REF]. They also allow evaluation of crucial hallmarks of cancer, such as metastatic [START_REF] Haldi | Human melanoma cells transplanted into zebrafish proliferate, migrate, produce melanin, form masses and stimulate angiogenesis in zebrafish[END_REF][START_REF] Marques | Metastatic behaviour of primary human tumours in a zebrafish xenotransplantation model[END_REF] and angiogenic potentials [START_REF] Haldi | Human melanoma cells transplanted into zebrafish proliferate, migrate, produce melanin, form masses and stimulate angiogenesis in zebrafish[END_REF][START_REF] Nicoli | Mammalian Tumor Xenografts Induce Neovascularization in Zebrafish Embryos[END_REF][START_REF] Zhao | A novel xenograft model in zebrafish for high-resolution investigating dynamics of neovascularization in tumors[END_REF]. Even though drug pharmacodynamics in zebrafish may differ from mammals, many compounds have been shown to block disease in a similar way. This has led to an increasing amount of compounds discovered in zebrafish screens that are entering into human clinical trials [START_REF] Zon | The new age of chemical screening in zebrafish[END_REF][START_REF] White | Zebrafish cancer: the state of the art and the path forward[END_REF][START_REF] Veinotte | Hooking the big one: the potential of zebrafish xenotransplantation to reform cancer drug screening in the genomic era[END_REF]. However, for zebrafish xenografts to be used as clinical assays, it is crucial that they provide sufficient resolution to reveal inter and intra-tumor functional heterogeneity, including differential response to therapy. Reliable methods to visualize and quantify human cells and induced cell death upon treatment and direct validation with mouse xenografts were also still lacking.

With the aim of testing zebrafish xenotransplants as a screening platform for cancer therapy, we used a panel of patientderived human colorectal cancer (CRC) cell lines to screen the NCCN/ESMO treatment guidelines for advanced CRC. We selected independent cell lines to investigate inter-tumor heterogeneity and isogenic clones to examine intra-tumor heterogeneity. In just 4 days, we could detect in vivo differential behaviors with single cell resolution, namely differential proliferation rates, metastatic and angiogenic potentials. These differences were present not only in tumors derived from different patients but also between different clones from the same tumor, even when mixed into a polyclonal tumor. We showed that early read-outs of response to treatment in zebrafish closely mirror the results obtained in the mouse. We also found that the zebrafish xenograft Significance Despite advances in targeted cancer treatments, we still lack methods to predict how a specific cancer will respond to a given therapy. As a consequence, patients go through rounds of trial-and-error approaches based on guidelines to find the best treatment, often subjected to unnecessary toxicity. Using cell lines, we used zebrafish-larvae-xenografts as sensors for cancer behavior and therapy guideline screening. Our data not only shows sufficient resolution to distinguish functional tumor behaviors in just 4-days, but also differential sensitivity to colorectal cancer therapy. As proof-of-principle experiments, we provide evidence for similar behavior response to therapies in zebrafish patient derived xenografts. Altogether, our results suggest zebrafish-larvae-xenografts as a promising in vivo screening platform for precision medicine.

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Fig. 1. | Implantation and histological analysis of human CRC zebrafish-xenografts.Human CRC cells (SW480; SW620; HCT116;Hke3and HT29) were labeled with the lipophilic CM-DiI dye (red) and injected into the PVS of 48hpf zebrafish. At 4dpi the number of xenografts with a tumor implanted was quantified (a-e), and the average (AVG) implantation rate was determined from at least 3 independent experiments. Immunohistochemistry for Ki-67 in paraffin sections at 4dpi xenografts (f-j'). Whole mount immunofluorescence staining at 4dpi, for Ki-67 (f''-j''), antihuman HLA in red and EdU staining in green (P-T). Representative images of mitotic figures in the corresponding xenografts (K-O), nuclei staining with DAPI in blue. Quantification of % of Ki-67 positive cells per xenograft (Z, p***<0.0001) and mitotic figures Z', p***<0.0001) in corresponding tumors (each dot represents one xenograft). Human CRC xenografts were generated in Tg(fli:eGFP) zebrafish to visualize blood vessels. Images representative of 4dpi xenografts induced neovasculature: SW480 (U); SW620 (V); HCT116 (W); Hke3 (X)and HT29 xenografts (Y). Quantification of total vessel density (Z'') and vessel infiltration (Z'''), **|*** refers to comparison with HT29. HT29 tumors displayed significant higher vessel density and infiltration than any other tumor, SW480 vs HT29 p=0.0264; SW620 vs HT29 p=ns; HCT116 vs HT29 p<0.0001, Hke3 vs HT29 p<0.0001). Infiltration potential (SW480 vs HCT116 p=0.0482; SW480 vs HT29 p=0.0025; HCT116 vs HT29 p<0.0001). Results in Z, Z',Z'',Z''' are expressed as average (AVG) ± SEM. The number of xenografts analyzed for Ki-67, mitotic index and angiogenesis is indicated in the figures. All images in the same row are at the same magnification.

model revealed a remarkable sensitivity to detect differential responses to Cetuximab treatment according to the KRAS mutational status.

Finally, as a proof-of-principle, we generated CRC zebrafish PDX (zPDX) derived from surgery resected human samples and treated them with the same treatment administered to the patient. Future work will be aimed at validating this model in clinical studies to test predictability. Altogether, our results suggest that zebrafish xenografts are a fast and highly sensitive assay that can be used to display multiple biological tumor traits and assess tumor response to treatment. We propose that this model can be used, not only in the research setting, but also possibly in the future for precision medicine.

RESULTS

Human CRC display diverse implantation and proliferation potentials in zebrafish-xenografts

Our strategy relies on the ability of zebrafish xenotransplants to unravel inter and intra-tumor functional heterogeneity. To address this question, we selected several human CRC cell lines isolated from different patients (inter-tumor heterogeneity) and isogenic pairs (intra-tumor heterogeneity) described in Table S1. SW480 was derived from the primary tumor and SW620 from the lymph node metastasis (6 months later) of the same patient, illustrating a history of clonal selection [START_REF] Hewitt R E, Mcmarlin | Validation of a model of colon cancer progression[END_REF]. HCT116 KRAS G13D tumor cells were isolated from a patient with colorectal carcinoma. Hke3 cells were generated from HCT116 by a somatic deletion of the KRAS G13D allele, reverting the oncogenic KRAS phenotype (10). This pair is considered isogenic and constitutes an ideal setting to study phenotypic heterogeneity derived from one single mutation (intra-tumor heterogeneity). Finally, HT29 cells were isolated from a well-differentiated metastatic tumor, belonging to the goblet-like subtype [START_REF] Sadanandam | A colorectal cancer classification system that associates cellular phenotype and responses to therapy[END_REF], serving as an outgroup.

To determine the implantation potential of these 5 human CRC cell lines, cells were labeled with a lipophilic dye (DiI) and injected into the periviteline space (PVS) of 48 hours post fertilization (hpf) zebrafish embryos [START_REF] Zhao | A novel xenograft model in zebrafish for high-resolution investigating dynamics of neovascularization in tumors[END_REF]. At 4 days post injection (dpi), we scored the efficiency of implantation (Fig. 1a-e, Fig. S1). With exception of SW480 cells, we observed high implantation efficiency in all cell lines (>70%) (Figure S1). One of the most fundamental hallmarks of cancer is the capacity to proliferate with no constrains [START_REF] Hanahan | Hallmarks of cancer: The next generation[END_REF]. To measure proliferation in vivo, we quantified mitotic figures and the Ki-67 index (specifically recognizes human cells, with no cross-reactivity with zebrafish) (Fig. 1f-j''). We found that the Ki-67 and mitotic index varied between cells derived from different patients (Fig. 1u,v). Direct comparison between isogenic pairs (intra-tumor heterogeneity) revealed that SW620 and HCT116 have higher proliferation rates in relation to their isogenic pairs SW480 (Ki-67 p<0.0001; mitosis p=0.0063) and Hke3 (Ki-67 p<0.0001; mitosis p=0.0003) (Fig. 1u,v). To further confirm that human CRC cells are actively proliferating in the zebrafish host, we delivered a 2h pulse of EdU prior fixation, labeling specifically cells that were undergoing DNA replication (Fig. 1p-t). edu incorporation demonstrates that human cells can actively proliferate in the zebrafish-xenograft model.

We also investigated whether the immunohistochemical profile and typical morphological features described for these cell lines were maintained in the zebrafish-xenografts (Fig. S2). As expected for more differentiated cells, HT29 formed tubular structures (Figure S2 E',O,T,T'), whereas tumors originating from the other cell lines showed a solid pattern with rare tubule formation, consistent with their "stem cell like" character (Fig. S2, [START_REF] Sadanandam | A colorectal cancer classification system that associates cellular phenotype and responses to therapy[END_REF].

We next examined angiogenesis, another essential hallmark of cancer [START_REF] Hanahan | Hallmarks of cancer: The next generation[END_REF]. The 5 cancer cell lines were injected into Tg(fli:eGFP) zebrafish line with GFP labeled vasculature [START_REF] Lawson | In Vivo Imaging of Embryonic Vascular Development Using Transgenic Zebrafish[END_REF]. At 4dpi, xenografts were imaged by confocal microscopy to study vessel 3D architecture (Fig. 1U-Y). SW480, SW620, HCT116 and Hke3 tumors showed a well-vascularized periphery, composed of large vessels that generally do not infiltrate the tumor (Fig. 1U-Y, Z''-Z''', . In contrast, HT29 are highly vascularized tumors, with formation of a dense vessel network that infiltrates into the core of the tumor (Fig. 1Y, Z''-Z''' MOVIE 6 and 7). This is consistent with HT29 expressing high levels of VEGF and high angiogenic potential in other models [START_REF] Xiao | MicroRNA-885-3p inhibits the growth of HT-29 colon cancer cell xenografts by disrupting angiogenesis via targeting BMPR1A and blocking BMPSmadId1 signaling[END_REF][START_REF] Lai | Diallyl trisulfide inhibits migration, invasion and angiogenesis of human colon cancer HT-29 cells and umbilical vein endothelial cells, and suppresses murine xenograft tumour growth[END_REF].

Our data conclusively shows that human CRC cells can sustain proliferation in zebrafish and present different proliferation dynamics in CRC tumors derived from different patients and isogenic tumors. In addition, human CRC cells maintain their general cellular characteristics and angiogenic potential in the zebrafish-xenografts.

Isogenic human CRC cells present different metastatic potentials

Another essential hallmark of cancer is the ability of cells to form metastasis [START_REF] Hanahan | Hallmarks of cancer: The next generation[END_REF]. At 4dpi, we could detect several small groups of cells in the brain, optic cup, gills, skeletal muscle and in the caudal hematopoietic tissue (CHT) region (Fig. 2 a-E). Cells in the CHT often extravasate from vessels (MOVIE1) and invade adjacent tissues, frequently the muscle (Fig. 2d,arrows). This "hot spot" region for tumor cell colonization provides an ideal location for quantification of metastatic potential [START_REF] Marques | Metastatic behaviour of primary human tumours in a zebrafish xenotransplantation model[END_REF]. Immunofluorescence for HLA (anti-human MHC-class I subunit) identifies unequivocally cells of human origin and delineate the cellular architecture of the micrometastasis (Fig. 2k-o). Ki-67 positive cells and mitotic figures at 4dpi suggest that colonization has been achieved (Fig. 2f-j, r).

Metastatic efficiency may vary and depends on whether a tumor cell can detach from the primary tumor, enter and survive in circulation and go on to seed cells at distant sites. We designed a simple assay to distinguish between early-stages (invasion of surrounding tissues and intravasation into blood vessels) and laterstages of the metastatic cascade (survival in circulation, extravasation and colonization) [START_REF] Nguyen | Metastasis: from dissemination to organspecific colonization[END_REF][START_REF] Valastyan | Tumor metastasis: molecular insights and evolving paradigms[END_REF] by comparing the micrometastasis efficiency when cells were placed directly into circulation vs when not. For that, we injected CRC cell lines either into the PVS alone (group a) or directly into circulation (group b) (Fig. 2p). At 4dpi, we analyzed the number of xenografts that presented a tumor cell mass (> 20 cells) away from the PVS injection site (CHT).

For tumor cells in group a to efficiently establish metastasis, they would have to go through all the metastatic steps (from early to late steps) whereas cells in group b only have to go through the later-stage ones. Thus, considering that maximum metastatic efficiency is achieved when cells are placed in circulation (group b), the reduction of colonization in group a would reflect the effort to undergo the early metastatic steps. Therefore, we converted our frequency of CHT colonization into Early Metastatic Potential (EMP) and Late Metastatic Potential (LMP) (Fig. 2p and methods).

Overall, our data shows that tumors differed both in their EMP (anova p=0.0044) and LMP (anova p= 0.028) (Fig. 2q). When comparing isogenic lines, we observed that SW480 cells have a higher EMP than SW620 (p=0.004) even though they exhibit similar LMP (Fig. 2q). These results agree with previous observations that SW480 cells are more invasive and migratory than SW620 in vitro and show higher extravasation potential in vivo [START_REF] Hewitt R E, Mcmarlin | Validation of a model of colon cancer progression[END_REF][START_REF] Stoletov | Visualizing extravasation dynamics of metastatic tumor cells[END_REF]

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Fig. 3.

| CRC xenografts show different sensitivity to standard chemotherapy.Human CRC zebrafishxenografts were treated in vivo with FOLFOX (f-j) and FOLFIRI (k-o) compared to non-treated controls (a-e). Zebrafish were sacrificed and fixed at 4dpi, 3 days post treatment (3dpT). Mitotic index (p-DAPI in blue) and cell death by apoptosis (q-activated caspase3 in green) was analyzed and quantified. Average tumor size (number of DAPI cells)normalized to respective controls was also quantified to compare between different xenografts in different conditions (r). All pictures are at the same magnification in the same row. Results in p, q,and rare expressed as average (AVG) ± SEM. Results are average from at least 3 independent experiments and the total number of xenografts analyzed is indicated in the images. ns -non significant, p values are indicated in the text, p***<0.001HCT116 and Hke3 polyclonal xenografts (1:1) were generated and randomly treated with FOLFIRI and compared to untreated controls. Xenografts were sacrificed and fixed at 4dpi, 3 days post treatment (3dpT). The % of each clone (U), cell death by apoptosis (V-activated caspase3), mitotic index (W) and the size of each clone per xenograft (X), was analyzed and quantified. Each The isogenic pair HCT116 / Hke3 showed different EMP (Fig. 2h, i, q, p***<0.0001) ie in Hke3 KRAS WT xenografts, we could only find metastasis when cells were directly injected into circulation (Fig. 2i, n, q, p<0.0001), highlighting the reported roles for activated KRAS in early metastatic events [START_REF] Valastyan | Tumor metastasis: molecular insights and evolving paradigms[END_REF][START_REF] Stoletov | Visualizing extravasation dynamics of metastatic tumor cells[END_REF][START_REF] Van Cutsem | Metastatic colorectal cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up[END_REF].

Finally, HT29 cells showed high EMP and LMP, frequently forming organized masses in the eye and CHT (Fig. 2 a,j,o,q). This high metastatic potential is consistent with the one observed in mouse xenograft models [START_REF] Ninomiya | Anti-metastatic effect of capecitabine on human colon cancer xenografts in nude mouse rectum[END_REF].

Our results show that is possible to further discriminate the cellular metastatic potential by comparing the efficiency of cells to metastasize when placed directly into circulation or not. Importantly, we found that the measurement of metastatic potential in our model match the previously described.

Zebrafish-xenografts discriminate different chemosensitivities in 4 days

To test whether zebrafish-xenografts can measure responses to therapy, we first assessed the main therapeutic options in advanced CRC guidelines: FOLFOX (5-FU+Oxaliplatin+Folinic acid) and FOLFIRI (5-FU+Irinotecan+Folinic acid) (Table S2, [START_REF] Van Cutsem | Metastatic colorectal cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up[END_REF]. These protocols are considered as balanced alternatives, since both treatments have shown equivalent average response rates (∼35%) in clinical trials performed on naïve patients [START_REF] Colucci | Phase III randomized trial of FOLFIRI versus FOLFOX4 in the treatment of advanced colorectal cancer: A Multicenter Study of the Gruppo Oncologico Dell'Italia Meridionale[END_REF].

To assess chemotherapeutic responses, all xenografts were randomly distributed between treatment groups (control, FOL-FOX and FOLFIRI) at 24hpi and then treated for 3 consecutive days. An average of 30 xenografts were treated per condition. Compounds were delivered directly in the embryo medium and replaced daily. After three days of treatment (and 4dpi), xenografts were processed for microscopy and assessed for mitotic index, cell death by apoptosis (activated Caspase 3) and tumor size (Fig. 3p,q,r).

FOLFIRI treatment induced a significant reduction of mitotic figures in all tumors (Fig. 3p). However, a significant induction of apoptosis followed by a reduction of tumor mass was only observed in HCT116 (apoptosis p<0.0001; 59% tumor reduction p<0.0001) and SW620 (apoptosis p=0.0021; 35% tumor reduction p=0.0026) (Fig. 3l, m, q, R). Remarkably, SW620 and HCT116 are more sensitive than their respective isogenic pairs. These results suggest differential sensitivities to therapy throughout cancer progression (primary vs metastasis) and in heterogeneous tumor populations (KRAS subclones).

Only in HCT116, FOLFOX treatment resulted in significant induction of apoptosis accompanied by a reduction of tumor size (apoptosis p<0.0001; 44% reduction p=0.0018) (Fig. 3h,q,r apoptosis or reduction of tumor mass when treated with FOL-FOX (Fig. 3i,q,r). These results are consistent with KRAS mutations increasing sensitivity to 5-FU induced apoptosis [START_REF] Klampfer | Oncogenic Ras increases sensitivity of colon cancer cells to 5-FU-induced apoptosis[END_REF]. As for HT29, as previously reported in mouse xenografts [START_REF] Priego | Natural polyphenols facilitate elimination of HT-29 colorectal cancer xenografts by chemoradiotherapy: a Bcl-2-and superoxide dismutase 2-dependent mechanism[END_REF], we could observe a significant reduction of mitotic figures (p<0.0001) and increase in apoptosis both upon FOLFIRI (p<0.0001) and FOLFOX treatment (p<0.0001) (Fig. 3P,Q).

In general, our results are consistent to previous mouse in vivo studies [START_REF] Chen | Regorafenib inhibits colorectal tumor growth through PUMA-mediated apoptosis[END_REF]25) with exception of SW620, which has been reported to respond to FOLFOX (25). The differences observed in our study are likely to reflect that our assay is designed to detect fast strong responses, given its short time window (3 days). This is particular evident in the study by Van Schaeybroeck [START_REF] Van Schaeybroeck | ADAM17-dependent c-MET-STAT3 signaling mediates resistance to MEK inhibitors in KRAS mutant colorectal cancer[END_REF] where HCT116 tumors stop growing as soon as FOLFOX treatment is initiated, whereas SW620 shows a delayed response.

In summary, we show that zebrafish-larvae-xenografts have enough resolution to measure inter-patient and intra-patient heterogeneity chemotherapy responses in just 4 days. These results highlight the heterogeneity of chemotherapeutic response and the possibility to measure this in a very short period of time in vivo.

To further confirm the HCT116 (KRAS MUT ) and Hke3 (KRAS WT ) opposing chemosensitive profiles we challenged them in the same xenograft host. For that, we co-injected the 2 cell lines (1:1), each labeled with a different lipophilic dye. Mixed xenografts (HCT116+Hke3) were randomly distributed into FOLFIRI and control groups. As expected, given their higher proliferative potential, HCT116 KRAS MUT cells outcompete Hke3 KRAS WT and become dominant in the mix, representing ∼80% of the tumor (Fig. 3S-S',U). However, upon FOLFIRI treatment, HCT116 significantly reduced its frequency (p<0.0001) (Fig. 3U). Consistent with the individual response to FOLFIRI treatment, we observed a significant increase in apoptosis (p=0.0023), a decrease in mitotic figures (p<0.0001) accompanied by a significant decrease in HCT116 tumor size (∼56% reduction p<0.0001) (Fig. 3V-X). In contrast, Hke3 clone size did not change upon FOLFIRI treatment, remaining at similar levels to controls (Fig. 3V-X).

These results demonstrate the differential chemosensitive profiles of both cell lines and how the KRAS mutation sensitizes cells to chemotherapy (25,[START_REF] De Roock | Association of kras p.g13d mutation with outcome in patients with chemotherapy-refractory metastatic colorectal cancer treated with cetuximab[END_REF]. Our data also illustrate how in heterogeneous tumors, KRAS mutations can provide a proliferation benefit, and how chemotherapy may disrupt this advantage, selecting the minor clone resistant to treatment, which then maybe responsible for relapses.

HCT116 and Hke3 NOD-SCID mouse xenografts show similar chemosensitive profile to zebrafish-xenografts

To directly compare the HCT116 and Hke3 chemosensitive profile determined in zebrafish with mouse xenografts, we generated HCT116/Hke3 double mouse NOD-SCID xenografts, controlling treatment efficacy and delivery in the same animal [START_REF] Iwamoto | Regulation of 18F-FDG accumulation in colorectal cancer cells with mutated KRAS[END_REF]. After 14 days, mice were randomly distributed amongst treatment groups and treated with 3 cycles of chemotherapy (Fig. 4).

Similarly, to our zebrafish-xenograft results, Hke3 mouse tumors presented a reduced mitotic index upon FOLFIRI treatment but not with FOLFOX (Fig. 4D-F', G) and no significant difference in apoptosis was observed with both treatments (Fig. 4H). Also in agreement to what we observed in zebrafish, both FOLFOX and FOLFIRI induced a significant increase in apoptosis in HCT116 cells (Fig. 4a'-c', H) and reduced proliferation (Fig. 4H,G) albeit FOLFOX to a minor extent than FOLFIRI (FOL-FOX vs FOLFIRI: apoptosis p=0.0017, mitotic figures p=0.029), closely resembling the zebrafish results (Fig. 3P,Q).

However, we were unable to detect clear differences in tumor size between control and treatment groups in our mouse xenograft study (Fig. 4). This contrasts not only to our zebrafishxenograft results (Fig. 3R) but also to previous mouse studies, where FOLFOX reduces the size of HCT116 tumors [START_REF] Van Schaeybroeck | ADAM17-dependent c-MET-STAT3 signaling mediates resistance to MEK inhibitors in KRAS mutant colorectal cancer[END_REF] Submission PDF Fig. 6. | Zebrafish patient-derived xenografts (zPDX) can be efficiently established using human colorectal cancer primary samplesCell suspensions derived from surgically resected human colon tumors were labeled with the lipophilic CM-DiI dye (red) and injected into the PVS of 48hpf wt or Tg(fli:EGFP). At 4dpi the number of zebrafish with an implanted tumor was quantified (A-E, F, each dot represents implantation % of each experiment). Representative confocal images of 4dpi zPDX showing neovasculature in Tg (fli:EGFP) (A'-E') and tumor masses with high cytomorphologic and architectural diversity (DAPI A''-E''). The number of nuclei (tumor size, G) and mitotic figures (H) in these tumor masses was quantified (G) each dot represents one xenograft Representative images of mitotic figures (A'''-E''', red arrows) and corresponding quantification (H). HLA and human mitochondriaimmunostained cells at 24hpi (I) and 4dpi (J). Tubular structures with luminal CEA staining (K, L). All images anterior to the left, posterior to right, dorsal up, ventral down. Scale bar, 50μm.

tumor growth kinetics. Thus, with exception of long-term tumor size decline, our results in mouse xenografts show higher response to treatment in HCT116 than in Hke3 cells, closely matching zebrafish-xenografts.

Differential sensitivity to Cetuximab and Regorafinib in CRC tumors in zebrafish-xenografts

Our results suggest that Hke3 KRAS WT tumors were refractory to FOLFOX and FOLFIRI standard chemotherapy. CRC guidelines further recommend that KRAS WT patients should be treated with a combination of chemotherapy and Cetuximab, a monoclonal antibody anti-EGFR [START_REF] Van Schaeybroeck | ADAM17-dependent c-MET-STAT3 signaling mediates resistance to MEK inhibitors in KRAS mutant colorectal cancer[END_REF]. KRAS WT status is an established biomarker for Cetuximab treatment [START_REF] Van Cutsem | Metastatic colorectal cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up[END_REF][START_REF] De Roock | Association of kras p.g13d mutation with outcome in patients with chemotherapy-refractory metastatic colorectal cancer treated with cetuximab[END_REF]. Consequently, patients with metastatic CRC who present a mutated KRAS profile (KRAS MUT ), such as in HCT116, are generally excluded from Cetuximab treatment [START_REF] Colucci | Phase III randomized trial of FOLFIRI versus FOLFOX4 in the treatment of advanced colorectal cancer: A Multicenter Study of the Gruppo Oncologico Dell'Italia Meridionale[END_REF].

To test whether Cetuximab therapy could induce cell death and reduce tumor mass in Hke3 tumors, we treated Hke3 KRAS WT and HCT116 KRAS MUT xenografts (as a negative control) with Cetuximab, FOLFIRI and with a combination of FOLFIRI with Cetuximab. Surprisingly, Cetuximab alone could significantly induce apoptosis both in Hke3 and HCT116 tumors (Fig. 5b,f,j). Combination of Cetuximab with FOLFIRI resulted in increased sensitivity of individual treatments in HCT116 tumors (Fig. 5d,H,j). This synergistic effect was also observed in the reduction of mitotic figures, but not in the reduction of tumor size (Fig. 5i,k).

We were surprised to observe the effect of Cetuximab in HCT116 (Fig. 5i,j,k), given the status of KRAS MUT . However, it was recently reported that a proportion of patients with KRAS G13D mutations, but not with KRAS G12V mutations, benefit from treatment with Cetuximab [START_REF] Iwamoto | Regulation of 18F-FDG accumulation in colorectal cancer cells with mutated KRAS[END_REF]. Thus, to further test the sensitivity of our in vivo assay, we treated SW620 KRAS G12V tumors with Cetuximab (Fig. S3 E,F,G). In contrast to HCT116 KRAS G13D , but as expected for KRAS G12V tumors, no significant effect was observed with Cetuximab treatment in SW620 KRAS G12V tumors (Fig. S3). These results demonstrate that the zebrafish-xenograft assay has a remarkable resolution to detect sensitivity to Cetuximab treatment, even in KRAS G13D reduction of tumor mass (Fig. 5I,k), suggesting that Cetuximab, is not very effective in Hke3 cells.

Regorafenib is a small molecule multikinase inhibitor recommended in refractory metastatic CRC, usually used as last alternative in the guidelines [START_REF] Van Cutsem | Metastatic colorectal cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up[END_REF][START_REF] Grothey | Regorafenib monotherapy for previously treated metastatic colorectal cancer (CORRECT): an international, multicentre, randomised, placebo-controlled, phase 3 trial[END_REF]. Regorafenib not only has been shown to induce apoptosis [START_REF] Chen | Regorafenib inhibits colorectal tumor growth through PUMA-mediated apoptosis[END_REF] but also to have antiangiogenic activity [START_REF] Grothey | Regorafenib monotherapy for previously treated metastatic colorectal cancer (CORRECT): an international, multicentre, randomised, placebo-controlled, phase 3 trial[END_REF]. Thus, to test whether Regorafinib could be more effective for Hke3 refractory and less proliferative tumors, xenografts were treated with Regorafinib for 3 consecutive days. Although we could not observe changes in the mitotic index of Hke3 (Fig. S4F), Regorafinib was able to induce apoptosis in Hke3 cells (p<0.0001) accompanied by a significant reduction of tumor size (Fig. S4 A,B,G, H p= 0.0041). These results highlight the possibility to detect response to therapy even in low proliferative and refractory tumors.

In addition, since Regorafinib is also considered antiangiogenic, we also examined this effect in HT29 xenografts (which we previously shown were highly angiogenic). We detected a reduction on the total vessel density in HT29 tumors (Fig. S4I C',D' p<0.0001) but not in Hke3 or SW620 (Fig. S4I,A',B',E',F'). Regorafinib also induces apoptosis in HT29 tumors, however this induction is not accompanied by a reduction of tumor mass as in Hke3 (Fig. S4G,p=0.0083, H). These results suggest that Regorafinib is efficient as a 3 rd line of treatment for Hke3 refractory tumors and that Regorafenib is also able to block tumor derived neovascularization in highly angiogenic tumors.

Overall, we show that it is possible to perform an in vivo screening of the main current options of the international CRC treatment guidelines from 1 st to 3 rd line, by utilizing the zebrafishlarvae-xenograft model.

Zebrafish patient-derived xenografts (zPDX) can be efficiently established using human colorectal cancer primary samples

Next, to test whether zebrafish-larvae can be efficiently used to generate patient derived xenografts (zPDX), we injected cell suspensions derived from surgically resected human colon tumors into zebrafish. We developed a protocol based on procedures for human CRC organoids derivation to maintain stemness and cell viability during processing [START_REF] Sato | Long-term expansion of epithelial organoids from human colon, adenoma, adenocarcinoma, and Barrett's epithelium[END_REF][START_REF] Fujii | A Colorectal Tumor Organoid Library Demonstrates Progressive Loss of Niche Factor Requirements during Tumorigenesis[END_REF] (SI text).

Selected primary tumors corresponded to adenocarcinomas of diverse tumor stage (Table S3). 24hpi zPDX were selected for the presence of a DiI stained mass in the PVS and left to develop for 3 more days. At 4dpi, percentage of implantation was scored as previously (Fig. 6F). We observed implantation rates ranging from 47% (zPDX#3) to 89% (zPDX#4) (Fig. 6F, A-E). For large primary tumor samples (zPDX#2, zPDX#4 and zPDX#5), injections were repeated and gave rise to similar engraftment rates (Fig. 6F), demonstrating the reproducibility of the procedure.

zPDXs were processed for whole mount immunofluorescence to assess angiogenesis (Fig. 6A'-E'), tumor size (Fig. 6G), mitotic figures (Fig. 6H), expression of colorectal cancer markers (carcinoembryonic antigen, CEA) and human-associated antigens (MHC-classI -HLA and human mitochondria) (Fig. 6I-L). Confocal microscopy analysis allowed us to observe differential vessel recruitment (Fig. 6A'-E') and tumor masses with high cytomorphologic and architectural diversity (Fig. 6A''-E''). Interestingly, even tumors with low cellularity induced vessel recruitment (Fig. 6C',G). Mitotic figures were present at 4dpi in all zPDX analyzed, albeit sparse and with low mitotic index (Fig. 6A'''-E''', H). We observed tubular structures with luminal CEA staining (Fig. 6K,L) as well as human HLA (to variable levels) and human mitochondria stained cells (Fig. 6I,J). We also compared directly the zPDX histology with the parental primary tumors with H&E (Fig. S5). zPDX derived from these tumors generally conserved their original features. They formed multilocular mucin lakes (Fig. S5A'',B'',C''), black dash lines delineate mucin lakes and red arrow heads for mucin), circumscribed by epithelium arranged as acinar structures with strips of cells or single cells (Fig. S5 A'',A''',C'', red dashed lines). Periodic acid-Schiff plus diastase (PAS+D) staining was used to identify mucus in the lumen of these structures (Fig. S6). Glandular structures accumulating necrotic debris in the lumen were also frequently seen (Fig. S5 A'',B'', black arrow heads), often CEA positive (Figure 6K).

Comparison of zPDX drug treatment with short-term patient treatment responses

In order to test our model as a platform to study response to treatment, we used available surgically resected CRC samples derived from patients that were subjected to FOLFOX adjuvant chemotherapy to reduce risk of disease relapse. At the time of initial diagnosis, almost two-thirds of patients with CRC undergo resection with curative intent. However, 30%-50% of these patients relapse and die of their disease. The majority of these recurrences occur during the first 2 years after surgery and most follow-up programs end 5 years after the primary treatment [START_REF] Guyot | Time trends in the treatment and survival of recurrences from colorectal cancer[END_REF]. FOLFOX postoperative adjuvant treatment has been shown to reduce chances of relapse improving disease-free survival [START_REF] André | Oxaliplatin, Fluorouracil, and Leucovorin as Adjuvant Treatment for Colon Cancer[END_REF].

Although not the ideal setting to study predictability, we sought to test if response to FOLFOX treatment in zPDX would anticipate a delay in relapse in the matching patients, or whether resistance to drug treatment in our model would associate with tumor relapse.

We generated zPDX from 5 different tumors and treated them with FOLFOX over 3 days. In the 5 zPDX, we could only observe response to FOLFOX treatment (induction of activated caspase3) in 2 zPDX (Fig. 7A & Fig. S7).

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to patients in which, at 6 months after surgery, the levels of CEA remain stable, with no indication of relapse. In contrast, of the 3 zPDX which we could not detect response to FOLFOX treatment, 2 are already in relapse after 3 months, with increasing levels of CEA and clinical evidence of recurrence (Fig. 7A,B & Fig. S7). Thus, we could anticipate relapse / no relapse within 3-6m after surgery in 4 out of 5 patients.

Our previous results on the sensitivity to Cetuximab treatment to detect responses in tumors with KRAS G13D mutations prompted us to test whether response to Cetuximab in zPDX would correlate with genomic prediction of response to the EGFR blocking therapy. As a proof of concept, in order to test this assumption, we treated 3 zPDX with a combination of FOLFIRI with Cetuximab and FOLFIRI alone. In the 3 zPDX generated, we could observe no added effect of Cetuximab in combination with FOLFIRI, suggesting that the 3 tumors tested showed resistance to Cetuximab (Fig. 7D, Fig. S7F-H''). We later sequenced the corresponding tumors and observed that all harbored mutations on either KRAS or BRAF (Fig. 7E). All these mutations highly correlated to resistance to Cetuximab [START_REF] Hsu | Mutations of KRAS / NRAS / BRAF predict cetuximab resistance in metastatic colorectal cancer patients[END_REF]. Thus, our results corroborated the genomic prediction (Fig. 7F).

Even though we have not yet gathered sufficient patient numbers to reach statistical significance, we performed proof-ofconcept experiments to set the ground for a future clinical study to test the predictiveness of zPDX in the more suitable neoadjuvant setting.

DISCUSSION

Recent genome cancer profile studies exposed unanticipated tumor heterogeneity. This heterogeneity has been observed not only between cancers (inter-tumor), but also within each cancer (intra-tumor) [START_REF] Vogelstein | Cancer Genome Landscapes[END_REF][START_REF] Almendro | Cellular Heterogeneity and Molecular Evolution in Cancer[END_REF]. Even identical CRC clones that share the same genome exhibit multiple functional profiles (including distinct responses to therapies) [START_REF] Kreso | Variable Clonal Repopulation Dynamics Influence Chemotherapy Response in Colorectal Cancer[END_REF], implying that the basis for heterogeneity is not only genetic. Most approved drugs lack known biomarkers and, even in biomarker-driven therapies, response rates are not full proof [START_REF] Almendro | Cellular Heterogeneity and Molecular Evolution in Cancer[END_REF][START_REF] Bailey | Implementation of biomarker-driven cancer therapy: existing tools and remaining gaps[END_REF]. Thus in the current scenario, we are currently unable to securely forecast which patient is likely to respond to a given therapy program.

Chemosensitivity tests are not a novel idea. However, the accuracy of in vitro tests has not been robust enough to support its use in oncology practice [START_REF] Burstein | American Society of Clinical Oncology Clinical Practice Guideline Update on the Use of Chemotherapy Sensitivity and Resistance Assays[END_REF]. Recently, Letai and colleagues [START_REF] Montero | Dynamic BH3 profiling-poking cancer cells with a stick[END_REF] showed a promising in vitro assay that bypasses serial passages and directly challenges tumor cells with therapeutic drugs, using BH3 profiling as a proxy of cell death. In this assay, there is a direct measurement of mitochondrial stress upon the applied drug [START_REF] Montero | Dynamic BH3 profiling-poking cancer cells with a stick[END_REF][START_REF] Montero | Drug-Induced death signaling strategy rapidly predicts cancer response to chemotherapy[END_REF]. In addition, in vitro organoids constitute a major technological breakthrough to study tumor biology, drug discovery and possibly also for personalized medicine [START_REF] Young | Organoids as a model for colorectal cancer[END_REF].

Although promising, in vitro tests will always lack the complexity of interactions of tumor cells with its microenvironment in the in vivo setting. The current gold standard for in vivo assessment of tumor heterogeneity and response to therapy are mouse PDX [START_REF] Hidalgo | Patient-derived Xenograft models: An emerging platform for translational cancer research[END_REF]. However, mouse PDX are not practical for clinical advice due to the time it takes to implant tumors, expand colonies and costs they entail. Here, we have taken an intermediate approacha fast in vivo assay with unprecedented cellular resolution -the zebrafish-larvae-xenograft model.

We set out to test whether the zebrafish-larvae-xenografts have enough resolution to uncover functional cancer heterogeneity to screen in vivo international treatment guidelines. Our study shows that zebrafish-xenografts are capable to discriminate, with single cell resolution, distinct proliferation dynamics and differential metastatic potentials, not only between tumors derived from different patients but also between isogenic pairs. Our ultimate goal was to screen the major therapeutic options present in the international guidelines for advanced CRC (20) using the zebrafish-xenograft assay. We analyzed the response of 5 zebrafish-xenografts (cell-line-derived) to the 2 most common and equivalent chemotherapy options FOLFOX and FOLFIRI [START_REF] Colucci | Phase III randomized trial of FOLFIRI versus FOLFOX4 in the treatment of advanced colorectal cancer: A Multicenter Study of the Gruppo Oncologico Dell'Italia Meridionale[END_REF] and observed an overall higher sensitivity to FOLFIRI than to FOLFOX. This is in agreement with the study by Sadanandan et al [START_REF] Sadanandam | A colorectal cancer classification system that associates cellular phenotype and responses to therapy[END_REF] that found that 70% of stemlike subtype tumors were associated with a clinical benefit with FOLFIRI treatment. Remarkably, we could also observe a clear differential response to therapy between isogenic tumors, illustrating differential therapy responses between primary and metastatic tumors (SW480/SW620) and subclonal tumor populations (HCT116/Hke3). We also reproduced polyclonal tumor scenarios and show differential responses to chemotherapy in the same xenograft and how therapy can select for minor resistant clones.

Following the next recommended therapy in the guidelines, we tested for Cetuximab sensitivity. Cetuximab treatment is a biomarker-driven therapy, recommended specifically for KRASWT tumors. Although not effective in all patients with KRASWT tumors (only ∼12.8%), the probability of response to Cetuximab treatment is still significantly higher (25). To our surprise, Cetuximab was effective on HCT116 KRASG13D. Consistent with our results, recent clinical reports revealed that a significant portion of patients with KRASG13D mutations, but not KRASG12V, benefit from Cetuximab treatment [START_REF] De Roock | Association of kras p.g13d mutation with outcome in patients with chemotherapy-refractory metastatic colorectal cancer treated with cetuximab[END_REF]. Thus, our results suggest that zebrafish-xenografts can measure responsiveness to therapy of tumors with different KRAS point mutations. Our study also illustrates the relevance of functional assays even in biomarker-driven therapies to further select the patients that may benefit from specific therapies, specifically in ones that do not have 100% efficacy and are expensive or toxic.

Although Hke3 KRAS WT tumors responded to Cetuximab treatment this was not accompanied by a reduction of tumor size. Thus, we tested the 3 rd -line option for refractory metastatic CRC -Regorafenib. In contrast to previous treatments, Hke3 tumors now responded to therapy with an induction of apoptosis accompanied by reduction of tumor size. Our results illustrate the possibility to screen treatment guidelines from 1 st to 3 rd line.

We also validated our results obtained in zebrafish in NOD-SCID mouse xenografts. This is the first study to directly compare zebrafish vs mouse xenografts chemosensitivity. As in zebrafish, HCT116 responded to both treatments, but FOLFIRI produced a significant higher induction of apoptosis than FOLFOX and Hke3 seemed refractory to both treatments. Our results suggest that, using apoptosis and reduction of mitotic index as surrogate as response to treatment in zebrafish-xenografts (4 days from injection to analysis) can be used as proxy of the response to treatment in mouse xenografts (minimal 1 month since injection to analysis). The disparity in time between models is likely to reflect the difference in scale of the models (>10,000 fold). On the one hand zebrafish-larvae allow for visualization of single cells and their response to treatment in multiple xenografts, improving statistical power. In contrast, mouse PDXs generally rely on large palpable tumors, long treatments to visualize responses and multiple rounds of expansion to provide statistical power. On the other hand, this longer assay permits the study of tumor evolution, emergence of resistance clones and overall progression of disease [START_REF] Hidalgo | Patient-derived Xenograft models: An emerging platform for translational cancer research[END_REF][START_REF] Kreso | Variable Clonal Repopulation Dynamics Influence Chemotherapy Response in Colorectal Cancer[END_REF]. Thus, we envisage that zebrafish and mouse xenografts models may complement each other: zebrafish as a fast screening platform, and mouse xenografts to accompany tumor evolution and relapse.

Lastly, we also demonstrate feasibility of using primary patient samples to generate zPDX with similar implantation rates as tumor cell lines. We show that zPDX can form tumor masses, induce vascularization and present multilocular mucin lakes, glandular structures and CEA expression. As observed with cell lines (SW480), patient samples (e.g. zPDX#3) also vary in their

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engraftment efficiency (being as low as <50%). To overcome possible low implantation rates, we may increase the number of injected fish and use immune compromised strains [START_REF] Tang | Optimized cell transplantation using adult rag2 mutant zebrafish[END_REF][START_REF] Moore | Single-cell imaging of normal and malignant cell engraftment into optically clear prkdc -null SCID zebrafish[END_REF] to dampen the possibility of rejection. As a proof of concept experiments, we also treated zPDX with FOLFOX and were able to anticipate relapse / no-relapse within 3-6m after surgery in 4 out of 5 patients. In addition, we sequenced tumors whose matching zPDX did not responded to Cetuximab, and found that all harbored mutations highly linked to Cetuximab resistance, corroborating our zPDX results with genomic data.

In summary, we performed proof-of-concept experiments that show that it is possible to screen the available therapeutic options present in the international CRC guidelines by using zebrafish-xenografts. We show that zebrafish-larvae-xenografts constitute a rapid model with high sensitivity to unravel human tumor functional heterogeneity. We also performed proof-ofconcept experiments using patient samples to set the ground for a clinical study to test the predictiveness of zPDX as a rapid in vivo screening platform for personalized cancer treatments.

Material and Methods

Animal care and handling Zebrafish (Danio rerio) casper, casper; Tg(fli1:eGFP), nacre fish were handled according to European animal welfare regulations and standard protocols.

Human tissue

All samples used for zebrafish patient derived xenografts (zPDX) establishment were obtained from Champalimaud Hospital or Prof. Doutor Fernando Fonseca Hospital with written informed consent. The study was approved by the Ethics Committees of both Hospitals.

Cell lines and culture

Colon cancer cell lines, SW480, SW620 and HT29, originally from American Type Culture Collection (ATCC) were authenti-cated through short tandem repeat (STR) profiling karyotyping isoenzyme analysis. HCT116 and Hke3 isogenic cell lines were donated by Angela Relógio and analysed. All cells lines were tested for mycoplasma. All cells were cultured in DMEM (Biowest) supplemented with 10% fetal bovine serum (FBS -Biochrom) and 1% Penicillin-Streptomycin (Hyclone) in a humidified atmosphere containing 5% CO2 at 37ºC.

Zebrafish-Xenografts injection

Dil labeled cells were injected into the periviteline space (PVS) of anesthetized 48hpf larvae [START_REF] Hanahan | Hallmarks of cancer: The next generation[END_REF]. After injection, xenografts were transferred to 34ºC until the end of experiments.

Zebrafish-Xenograft Drug administration 24hpi, zebrafish-xenografts with same tumor size were randomly distributed in the treatment groups: control E3 medium, FOLFIRI in E3 and FOLFOX in E3 (4.2 mM 5-FU, 0.18mM Folinic Acid, 0.08mM Irinotecan, 0.08mM Oxaliplatin) for 3 consecutive days. Using as a reference the maximum patient's plasma concentration of each compound (Table S2), we determined the zebrafish maximum tolerated concentration. Cetuximab monoclonal antibody was added to the cell suspension (20mgml) at the time of injection and then to E3 medium at 100mg ml. Regorafinib was added to E3 to a final concentration of 40mM .

Fig. 2 .

 2 Fig. 2. | Human CRC cells show different metastatic potential.At 4dpi it is possible to detect human tumor cells throughout the zebrafish body, in the brain (a), eye (b), gills (c), muscle (d) and in the caudal hematopoietic tissue (CHT) (e). Immunofluorescence for Ki-67 (f-j) and anti-human HLA (k-o) in the CHT region at 4dpi in the indicated xenografts. In order to distinguish between early and late metastatic steps tumor cells were injected into the PVS only a) or in the PVS and directly into circulation b) (p). Quantification of Early (EMP) and Late (LMP) Metastatic Potential (q) and percentage of Ki-67 positive cells in the CHT micrometastasis (r, each dot represents one xenograft). Results are average from at least 3 independent experiments. The number of xenografts analyzed for Ki-67 is indicated in the images. The number of xenografts analyzed for EMP and LMP are as follows: SW480 (EMP N=62; LMP, N= 66); SW620 (EMP N=50, LMP N=69); HCT116 (EMP N=73, LMP, N=57); Hke3 (EMP N=74, LMP N=250; HT29 (EMP N=31, LMP N=94) (q). Results in Q and R are expressed as average (AVG) ± SEM. Nuclei staining with DAPI in blue. All pictures in the same row (F-J) are at the same magnification. All images anterior to the left, posterior to right, dorsal up, ventral down.

  Fig. 3.| CRC xenografts show different sensitivity to standard chemotherapy.Human CRC zebrafishxenografts were treated in vivo with FOLFOX (f-j) and FOLFIRI (k-o) compared to non-treated controls (a-e). Zebrafish were sacrificed and fixed at 4dpi, 3 days post treatment (3dpT). Mitotic index (p-DAPI in blue) and cell death by apoptosis (q-activated caspase3 in green) was analyzed and quantified. Average tumor size (number of DAPI cells)normalized to respective controls was also quantified to compare between different xenografts in different conditions (r). All pictures are at the same magnification in the same row. Results in p, q,and rare expressed as average (AVG) ± SEM. Results are average from at least 3 independent experiments and the total number of xenografts analyzed is indicated in the images. ns -non significant, p values are indicated in the text, p***<0.001HCT116 and Hke3 polyclonal xenografts (1:1) were generated and randomly treated with FOLFIRI and compared to untreated controls. Xenografts were sacrificed and fixed at 4dpi, 3 days post treatment (3dpT). The % of each clone (U), cell death by apoptosis (V-activated caspase3), mitotic index (W) and the size of each clone per xenograft (X), was analyzed and quantified. Each dot represents a xenograft, Hke3 caspase3 p**=0.041, Hke3 mitosis p**=0.006, remaining p values are indicated in the text, p***<0.001. The total number of xenografts analyzed is indicated in the images. HCT116 was labeled CM-DiI (red) and Hke3 with the lipophilic dye DeepRed (green -false colour).

Fig. 4 .

 4 Fig. 4. | HCT116 and Hke3 mouse xenografts validate zebrafish chemosensitive profileHCT116 and Hke3 double mouse xenografts were generated and randomly treated with FOLFOX (N=5) and FOLFIRI (N=5) and compared to PBS treated controls (N=5). Hematoxilin and Eosin (H&E) (a-f) staining as well as immunofluorescence to detectapoptotic cells (activated caspase3, a'f') was performed in paraffin sections. Mitotic index (g-DAPI in blue) and cell death by apoptosis (h-activated caspase3 in green) was quantified in fields distant from the necrotic center of the tumor. ns -non-significant, p values are indicated in the text, p***<0.001. Results in g and h are expressed as average (AVG) ± SEM.

Fig. 5 .

 5 Fig. 5. | Differential sensitivity to Cetuximab in human CRC in zebrafish-xenograftsHCT116 (a-d) and Hke3 (e-h) xenografts were treated for 3 consecutive days, with Cetuximab (b, f), FOLFIRI (c, g) and Cetuximab in combination with FOLFIRI (cetuxi + FI, d, h) and compared to control non-treated xenografts (a, e). Mitotic index (i-DAPI in blue), cell death by apoptosis (Jactivated caspase3 in green), and average (AVG) tumor size (k-number of DAPI cells per tumor) was analyzed and quantified at 4dpi and 3dpT. Average tumor size and the % of activated caspase3 was normalized to respective controls to compare between different xenografts. Results are expressed as average (AVG) ± SEM. All images anterior to the left, posterior to right, dorsal up, ventral down.

Fig. 7 .

 7 Fig. 7. | zPDX treatment response may predict relapse and correlate with known genomic biomarkers of Cetuximab resistance5 zPDX corresponding to patients subjected to curative surgery and postoperative FOLFOX adjuvant treatment, were treated with FOLFOX for 3 days and processed for immunofluorescence. Cell death by apoptosis (A-activated Caspase3) was analyzed and quantified. zPDX#7 control vs FOLFOX p=0.037; zPDX#9 control vs FOLFOX p=0.016.B. Relapse and CEA levels information of the 5 patients analyzed. (C). Confusion matrix displays the number of patients with actual and predicted responses in zPDX ie responders are patients that did not relapse (R) and patients that relapse are the non-responders (NR). D. 3 zPDX were treated with FOLFIRI and FOLFIRI in combination with Cetuximab, cell death by apoptosis (activated Caspase3) was analyzed. zPDX#5 control vs FOLFIRI p=0.0043, control vs FOLFIRI+Cetuximab p=0.0084; zPDX#9 control vs FOLFIRI p=0.001, control vs FOLFIRI+Cetuximab p=0.012.E. Genomic information of the analyzed patients. E. Confusion matrix displays the number of patients with mutations predicted of resistance with predicted responses in zPDX.

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Acknowledgements

We would like to thank the Champalimaud Histopathology Unit (Dr. A. Beltran, L. G. Madruga and M. Castillo) and Hospital Prof. Doutor Fernando Fonseca, for immunohistochemistry and pathology support. Surgery Units of Champalimaud Foundation (Dr. J.F. Cunha) and Hospital Prof. Doutor Fernando Fonseca (Dr. V. Nunes, Surgery Unit B) for patient samples. Champalimaud Fish and Rodents Facility (C. Certal, S. Mello) and IGC Fish Facility for excellent animal care. We also thank the IGC and IMM histology units. We also thank A. Relógio for the HCT116 and Hke3 cell lines. We are grateful to B. Costa-Silva, C. Carvalho, L. Saúde and L. Patton for critically reading the manuscript and J. Escandell and I. P. Castro for helpful discussions. MGF is an International Early Career HHMI scientist.

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