WHITE PAPER

V1.0

Exploring TranslationalCapabilities of PDX Models across In Vivo, In Vitro, and Ex Vivo Applications

2

The Challenge: How to Expand PDX Use Across the FullSpectrum of Preclinical Research

Patient-derived xenografts (PDX) are recognized as the most predictive and translational xenograft model available for preclinical research.However, by their nature they are restricted to in vivo use, typically in immunodeficient mice. To fully benefit from the main translational features of PDX, it would be useful to utilize the models across the broad spectrum of preclinical research. As immuno-oncology continues to dominate cancer research, humanized PDX models could also provide a valuable tool for immunotherapy assessment and MCT population studies. This White Paper looks at the expanded uses for PDX models across in vitro and ex vivo studies, as well as within the immuno-oncology research space.

What are PDX and How Are They Used?

Unlike conventional xenografts which are derived from immortalized cancer cell lines, PDX are created from patient tumors that are directly implanted in immunocompromised mice (Figure 1). PDX models never undergo a tissue culture/ in vitro growth stage, therefore maintaining a closer fidelity to the parental tumor tissue, and preserving more characteristics of the original patient disease. This provides an improved xenograft model for translation into clinical trials, delivering highly predictive preclinical data.

PDX models are commonly used for in vivo drug development, typically for “classical” xenograft efficacy studies (exemplified in Figure 2). In these studies PDX-bearing mice are randomized into vehicle and compound dosing groups, with usually 8 to 10 animals per arm. The animals are then treated with the

experimental anticancer agent being studied, possibly in a dose response context. The final study outcomes are typically tumor growth inhibition (TGI) and/or the time to an endpoint (e.g. a given survival endpoint analysis).

More recently, PDX have been utilized in Mouse Clinical Trials (MCT; shown in Figure 3). These human surrogate trials use cohorts of PDX models within a randomized, controlled, and statistically powered setting to provide predictive data on responder and non-responder subgroups to:

• Guide biomarker discovery

• Advise on clinical strategies

• Allow appropriate downstream patient stratification

MCTs invert the normal xenograft study system, using only a small number of mice per arm across a large number of PDX models. This more closely recapitulates the human clinical trial setting, with each mouse representing a single patient. Typical study outcomes for MCTs include:

• TGI for studies with a comparator e.g. a 1+1 MCT setting where, for each model, one animal receives test agent and one receives vehicle

• RECIST criteria for those studies without a comparator e.g. looking at tumor progression, stasis, or regression vs baseline or pretreatment levels

Figure 1: PDX Model Development

3

Figure 2: How Classical Xenograft Studies are Performed

The Importance of PDX in Preclinical Research

PDX models are increasingly important in preclinical research as, to date, they provide the animal model system which is closest to human disease, and which more fully represents the heterogeneity and variability of the clinical cancer population. Based on the close resemblance of PDX to patients, the models can be used for “translational fidelity” in the development of personalized medicine.

For example, current cancer medicine employs a “one treatment fits all approach” (Figure 4). A cohort of patients is given a specific therapy with some patients responding, some showing no effects, and a subgroup of patients displaying adverse effects/worsening of disease. Clinical trials such as these provide no guidance for further research on why these results/responses occurredper patient.

Future medicine aims to become more personalized, providing the right drug to the right patient at the right time. If we can understand a patient’s specific disease and mutations, then therapies can be tailored to particular patients/patient groups such that everyone responds to their appropriate medicine. PDX provide a unique in vivo asset for the development of personalized medicine. With the ability to analyze PDX models within MCTs we can correlate specific genetic and genomic factors within each model to response/non response to a therapy. This allows the prediction of patient response (based on clinical genetic information) and appropriate patient stratification – providing the correct drug to the right patient ensuring greater response rates.

Using PDX models within MCTs we can also further explore translational capabilities through the utilization of different study designs. For example, the effects of different drugs for different mutations within one cancer type (e.g. a spectrum of oncogenic drivers for lung cancer) can be studied. Alternately if we understand the mutational profiling across a panel of PDX models we can study one drug targeting a common genetic mutation/lesion across a range of cancer types. This can help researchers understand how response correlates with the mutation across a range of indications (Figure 5).

PDX Models: Advantages vs Challenges

Many of the advantages of PDX have been discussed above – they maintain a close fidelity to the patient, and present cellular and molecular heterogeneity in addition to patient-to-patient heterogeneity. These models truly reflect the patient population, allowing preclinical insight into responder and non-responder populations.

The main disadvantages of PDX include the technical challenges inherently posed by model development. PDX models (consistent with their origins) often grow slowly, and are also maintained in serial passage in mice, both of which pose logistical challenges. Serial passage from mouse to mouse, rather than with an intermediate tissue culture step, requires a more specialized skill set and can prove more complex when setting up a large number of models required for one experimental procedure. Slow growth can result in increased experimental time and cost, as can the long latency periods post-engraftment observed for some models.

Figure 3: How Mouse Clinical Trials are Performed

Tumor GrowthInhibition (TGI)

PDX

Treatment

Vehicle

Data Analysis(Paired Survival Analysis)

PDX Treatment

Vehicle

RCT-MCT:”1” or”n+n

4

Figure 4: Current and Future Cancer Medicine Approaches

Current MedicineOne Treatment Fits All

Future MedicineMore Personalized Diagnosics

Effect

Therapy

Cancer patients withe.g. colon cancer

Blood, DNA,Urine and Tissue Analysis

Adverse effect

No effectTherapy

Effect

With mainstay PDX use being in an immunodeficient in vivo setting, early stage drug development and immuno-oncology research could miss out on the key translational information provided by these models. However, through the derivation of cell lines from PDX, the development of ex vivo assays, and the rapid enhancement of humanized PDX, model features can now be leveraged across the preclinical research continuum.

PDX-Derived Cell Lines for Human Disease Relevant In Vitro Assays

When using the term “in vitro” we are referring to things living in culture, such as cancer cell lines. A typical use for in vitro cell lines is to measure changes to cells over time. PDX-derived cell lines provide a primary cell line recapitulating clinically elevant features of the human disease, for more predictive early stage preclinicalresearch. Using these cell lines allows rapid transition to associated xenografts for PK/PD studies and parental PDX models for efficacy studies.

PDX-derived cell lines are developed from mouse stromal cell-depleted cancer cell cultures from PDX models, which undergo adaptation to grow within the in vitro/ tissue culture setting (Figure 6). Typically, PDX-derived cell lines are early passage

(<10), and maintain essential histopathological features andgenetic profiles of the original patient tumors including:

• Genomic mutational status (including rare fusions or disease subtypes)

• Biochemical signaling

• Response to tumor cell autonomously targeted therapeutics

Once developed, PDX-derived cell lines can then be used in a variety of assays, and treated with novel agents/drug combinations as required. Assays which are routinely conducted across the spectrum of oncology drug development are shown in Table 1. These in vitro experiments provide a range of informationfrom simple compound potency to cancer cell:immune cell interactions, immune cell mediated cancer cell killing, and in vitro drug combinations including synergistic effects.

Fidelity between parental in vivo PDX models and derived in vitro cell lines has been observed, ensuring that the in vitro cell line does recapitulate the original model disease and behavior. This is shown in Figure 7 for two NSCLC PDX models and their downstream cell lines. EGFR is an oncogenic driver in NSCLC, and

5

many factors around the EGFR gene infer tyrosine kinase inhibitor (TKI) sensitivity and resistance. For example:

• EGFR exon 19 activating deletion confers sensitivity to TKIs such as erlotinib (observed in PDX model LU1235)

• EGFR exon 21 L858R mutation usually confers sensitivity to TKI, but when accompanied by MET amplification a lower sensitivity/resistance to TKIs are instead observed (PDX model LU0858 harbors both genetic events)

The cell lines derived from these models show varying levels of in vitro response to erlotinib – with LU1235 being highly sensitive, and LU0858 showing a lower level of sensitivity. This can be

directly translated to low or high levels of tumor growth inhibition in the parental PDX model (Figure 7), showing that this differential sensitivity has been maintained during adaptation forin vitro growth.

Ex Vivo PDX Screening Platforms to Rapidly Progress Drug Discovery

When using the term “ex vivo” we are referring to things that were once living in vivo, for example cells which were growing in vivo which are transferred to short term culture for testing. Taking PDX models ex vivo can overcome some of the challenges seen with in vivo use (e.g. cost for large scale drug screening, lack of amenability to high throughput assays) while still providingPDX benefits.

Figure 6: Derivation of PDX-Derived Cancer Cell Lines

Human Tumor PDX PDX-Derived Cell Line(PrimePanelTM)

Commonly Performed In Vitro Oncology Assays Conducted at CrownBio

Antigen presentation and immune system activation assays

Immune cell mediated cancer cell killing assays

Ex vivo tumor burden quantification

In vitro drug combination studies, including CrownSyn™ service

Colony forming cell (CFC) assays

Large scale compound screening, including OmniScreen™

Microbiome sequencing

Adhesion, migration, and invasion assays

Cytotoxicity screening

Figure 5: The Translational Fidelity of PDX Models for Personalized Medicine Development

PDX

Vehicle

Treatment

Multiple Types of Cancer1 Common Genetic Mutation ( • )

1 Type of Cancer • • •)

PDX Models

1+1 Study Design Multiple Indications and Targets

Test drug 1

Test drug 1Test drug 1

Test drug

Different Genetic Mutations (

Table 1: Common In Vitro Oncology Assays

6

Figure 7: PDX-Derived Cell Line In Vitro Response Correlates to In Vivo PDX Tumor Growth Inhibition

Derived Lung CancerCell Lines

125

100

75

50

25

010-3 10-2 10-1 100 101 102

LU1235 Activating DeletionLU0858 L858R + c-Met Amp

Surv

ivin

g C

ells

(%)

Erlotinib Concentration (µM)

Lung Cancer PDX

800

600

400

200

00 5 10 15 20 25 30

Vehicle (0.9% saline) i.p. daily Erlotinib 50mg/kg p.o. daily

HuPrime PDX Model LU1235: EGFR ActivatingMutation Deletion

Days post Treatment

Tum

or V

olum

e (m

m3 )

1600

800

Vehicle (0.9% saline) µl/g i.p. weeklyErlotinib 50mg/kg p.o. daily

1200

2000

2400

HuPrime PDX Model LU0858: EGFR L858R +c-Met Amplification

Tum

or V

olum

e (m

m3 )

Ex vivo models are used to evaluate anticancer agent efficacy via a range of assays, shown in Figure 8. These assays allow the assessment of the cytotoxicity or proliferation of cancer cells, historically using clonogenic assays. As we move forward into an ex vivo 3D setting, such as 3D Tumor Growth Assay (3D TGA) compound screening, we allow for the rapid screening of large numbers of PDX models, and the more rapid progression of hits/leads from this screen into PDX model panels in vivo.

Similar to in vitro PDX-derived cell lines, correlation has been shown between ex vivo and in vivo study response. This is exemplified here by the 3D TGA, an innovative screening platform which also allows for the investigation of factors affecting drug response.

Briefly, the 3D TGA more closely represents the human condition than 2D culture providing a 3D assay platform that is both “humanized” and TME-aligned for profiling of PDX-derived cells and drug panels:

• Utilizing a low stiffness laminin rich extracellular matrix (IrBME, Cultrex®) to embed tumor cells

• Admixing hMSCs (e.g. IL-6, HGF) and cancer associated fibroblasts (CAFs) to provide the paracrine signaling present in the tumor microenvironment of solid tumors

• As well as hormone addition (e.g. DHT/E2), restriction of glucose (≤7mM), and maintenance of an acidic pH (6.8)(1)

Correlation has been shown between response to erlotinib for the NSCLC LU6422 PDX model in vivo and ex vivo using this platform (Figure 9). The PDX model harbors a L858R mutation in the intracellular kinase domain, related to hypersensitivity to EGFR targeted therapies such as erlotinib in patients. Cells derived from LU6422 are hypersensitive to erlotinib in 3D TGA, which correlated with complete tumor regression of the PDX model (subcutaneous implantation with MSCs) following erlotinib treatment in vivo(1).

The addition of CAFs to the 3D TGA platform dampened the ex vivo response toerlotinib, signifying that there is a potential interaction between the CAFs (or their secreted factors) and cancer cell response. This 3D TGA platform therefore allows us to explore the biology around this model further.

3D ex vivo PDX models can also be used for compound screening, combining PDX benefits with the advantages of high throughput drug assessment (Figure 10)(2).

The advantages of PDX models conserved in a 3D ex vivoformat are:

• Fidelity to the patient

• Cellular and molecular heterogeneity

• Patient-to-patient heterogeneity

7

Figure 8: Common Ex Vivo Oncology Platforms

Figure 9: 3D TGA Ex Vivo Response Correlates to In Vivo PDX Tumor Growth Inhibition

TumorTissue

Processing3D Culture

Methylcellulose Clonogenic

Soft Agar Clonogenic Assay

3D Tumor GrowthAssay (3D TGA)

3D Ex VivoCompoundScreening

Tum

or V

olum

e (m

m3 )

0 10 20 30 40 50 600

200

400

600

800

1000

Erlotinib 25mg/kg q.d.Erlotinib 50mg/kg q.d.

Vehicle q.d.

00

20

40

60

80

100

120

0.01 0.1 1 10 100

LU6422

LU6422 + CAF

[Erlotinib] (µM)

Viab

ility

(%)

The advantages of an ex vivo format for drug assessment include:

• High throughput capability

• lower costs with faster model development and study timelines

• Retention of human-derived stromal elements.

Utilizing frozen ex vivo tumor cells dissociated from freshly isolated PDX tumor tissues, we have developed a robust and reproducible ex vivo 3D assay platform to facilitate compound testing and screening. In this setting, a large panel of compounds can be rapidly assessed using low passage PDX tumor tissues. To ensure reliability and fidelity of studies such as this, parental PDX models can also be treated with the same agents in vivo, for a head to head comparison of results.

Figure 11 shows the comparison of ex vivo screen IC50 data with in vivo TGI results across the same selection of models and treatments. Analysis by Pearson plot showed 72% consistency, a good correlation between how cells respond in an ex vivo vs an in vivo setting, which effectively validates this platform(2).

Summary: In Vitro/Ex Vivo PDX Assays Expand Model UtilityAcross Preclinical Research

To benefit fully from the main translational features of PDX, alternative uses to traditional in vivo studies have been established. This includes the development of PDX-derived cell lines for more human disease relevant early stage drug discovery, which can be used across a wide range of in vitro assays monitoring cell behavior over time, including studying immune cell and cancer cell interactions.

In the ex vivo setting, we can now leverage a wide array of PDX models (with built in tumor population heterogeneity) to quickly and efficiently screen large panels of compounds. These results can establish responder and non-responder populations, which can be correlated back to parental model genetics, and help to fast forward drug development programs in to the PDX setting.

Adapted from (1)

8

Figure 10: Compound Testing using a PDX Cell Collection in an Ex Vivo 3D Assay Format

Figure 11: Correlation Between Ex Vivo Compound Screening and In Vivo Results(2)

PDX DissociatedPDX cells

FrozenPDX cells

7-daycompound

testing

Ex vivo 3D assayMethylcellulose

Soft agar

IC50(µM)0.001 0.01 0.10

20

40

60

80

100

1 10 100 1000

Tum

or G

row

thIn

hibi

tion

(%)

Ex vivo ana in vivo correlationby Pearson plot, 72% consistent

OV0

273_

Cis

plat

inC

R23

94_M

itom

ycin

CC

R23

94_S

uniti

nib

CR

2394

_Cet

uxim

abO

V025

0_Pa

clita

xel

CR

2394

_Irin

otec

an

CR

2394

_Sor

afen

ibC

R23

94_E

vero

limus

CR

2394

_Erlo

tinib

CR

2394

_5-F

UC

R23

94_D

ocet

axel

CR

2394

_Dox

orub

icin

CR

2394

_Gem

cita

bine

CR

2394

_Ifo

sfam

ide

OV0

273_

Etop

osid

eC

R23

94_P

emet

rexe

dC

R23

94_B

evac

izum

abC

R23

94_C

ispl

atin

CR

2394

_Tem

ozol

omid

eB

R12

82_T

amox

ifen

BR

1282

_Cis

plat

in

BR

1281

_Pac

litax

elC

R23

94_V

inor

elbi

neO

V025

0_C

ispl

atin

OVO

273_

Pacl

itaxe

l

100

10

1

0.1

0.01

0.001

IC50

(μM

)

100

80

60

40

40

0

Tum

or G

row

thIn

hibi

tion

(%)

Using Humanized PDX Models for Predictive Immuno-Oncology Studies

In immuno-oncology rather than drug treatments directly attacking cancer cells, immunotherapeutics stimulate the immune system to instead act against cancer. This means that a functional immune system is required for immunotherapy use and preclinical assessment.

Humanized PDX models are becoming a popular research option for immunotherapy assessment, allowing the evaluation of human tumors within a functioning human immune system. Humanization takes place either using PBMC for short term studies or CD34+ HSC for a longer term reconstitution.

These CD34+ HSC humanized models (which are detailed within this White Paper) have an enormous value in immuno-oncology research, covering multiple functions including combination therapy studies, and providing relevance to human-specific antibodies (when no mouse surrogate exists) and a variety of known and novel immune targets (Figure 12). Humanized models can also be used in an MCT approach to explore which cancers

respond to an agent, as well as which characteristics from a donor render them responsive/non-responsive to a given treatment.which correlated with complete tumor regression of the PDX model (subcutaneous implantation with MSCs) followingerlotinib treatment.

Humanization is needed to observe the in vivo efficacy of certain immuno-oncology agents. Figure 13 shows the effect of Keytruda® on a triple negative breast cancer cell line derived xenograft model implanted in NSG™ mice. In the non-humanized, immunodeficient setting no response is seen. However, following humanization, tumor growth inhibition is observed with humanized mice displaying disease remission.

A characteristic of a “true” immune response is a memory, and in this study humanized animals were rechallenged with the same treatment, with the rechallenge successfully rejected in the previously treated cohort, demonstrating a memoryresponse (Figure 14)(3).

9

Figure 12: The Value of Humanized PDX Models in Immunotherapy Drug Development

Figure 13: Humanization is Necessary for Keytruda Effect

Days

Tum

or V

olum

e (m

m3 )

00 20 40 60 80

1000

2000

3000

4000ControlKeytruda

Non-Humanized Mice

Days

Tum

or V

olum

e (m

m3 )

0 20 40 60 10080

3000

2000

1000

0

ControlKeytruda

Humanized Mice

Humanized PDX Case Study: Efficacy of Keytruda in a Panel ofSCLC PDX Models

Immunotherapy response is influenced by the immunological state of each subject, which helps to explain the wide variability observed in clinical response. Preclinical models and study designs need to reflect this variability to provide predictive data, and to help guide biomarker discovery for patient stratification.

Humanized PDX models can be used in Mouse Clinical Trials, using tailored study designs to reflect this variability, and to provide predictive preclinical data on responders and non-responders, both for cancer model and immune donor.

This Case Study investigates the response of a panel of small cell lung cancer (SCLC) models to PD-1 inhibition in a specially designed study, and investigates the immunological background to these results.

To select the models for this study, 30 SCLC PDX models were screened for PD-L1 expression (Figure 15). From this panel, seven high PD-L1 expressing SCLC models were chosen to move forward into pharmacology studies.

The chosen seven models were then arrayed across five CD34+

HSC donors in an n=1 checkerboard design, which tests the multiple PDX models across multiple stem cell donors to account for donor-to-donor variability. Each model/donor is a unique combination, therefore testing seven models across five donors results in 35 separate model outcomes, representing 35 individual patients which is indicative of clinical trials.

Treatment was initiated when tumor volume reached 50-70mm3, and each model was run with two mice:

• Vehicle: 1 animal; i.p., q.5.d.

• Keytruda: 1 animal; 10mg/kg, i.p., q.5.d.

The study readouts were TGI, tumor infiltrating lymphocyte (TIL) analysis, and histology, with TGI results shown in Figure 16. Each of the boxed graphs represent outcomes which could be evaluated, where the vehicle and treated animal were both available at the end of the study. Unboxed graphs show combinations where one of the two models falls off over time, potentially due to an immune reaction or GvHD which can be considered analogous to patient censoring within clinical trials.

HUMANIZEDXENOGRAFT MODEL

Relevance tohuman-specific

antibodies

Relevance toknown and novelimmuno-oncology

targets

Combination:immunotherapy +immunotherapy

Combination:immunotherapy +

targeted agent

Access diversityacross

population

10

Figure 14: Rechallenge of Responder Animals Demonstrates an Immune Memory Response

Figure 15: Flow Criteria for Low, Moderate, and High PD-L1 Expressing PDX Models

Days

Tum

or V

olum

e (m

m3 )

6040200 80 100 120 1400

1000

2000

3000

4000Keytruda cohort 1 previously treatedKeytruda cohort 2 previously treatedOriginal control New, age-matched controls

100 110 120 130 1400

200

400

600

800 Keytruda cohort 1 previously treatedKeytruda cohort 2 previously treatedAge-matched control 1Age-matched control 2Age-matched control 3

Days

Rechallenge

Tum

or V

olum

e (m

m3 )

Adapted from (3)

The results show a mix of responders and non-responders, with no consistent tumor responder across all donors, or one host immune system with which all tumors respond. For example, for donor 5 with SCLC #1 and #2 a good response was observed, but across donors C2-C4 with this model no response was observed. This emphasizes the need for a better understanding of who will respond to a treatment along with the nature of the host, as well as the cancer, as we progress with immunotherapy development.

Overall 36% of SCLC PDX in this study responded to treatment (TGI≥48%; Figure 17). This is highly comparable to the 35% partial response rate to Keytruda observed in the Phase Ib KEYNOTE-028 SCLC clinical trial(4), demonstrating the clinical translation of this study type.

These results were analysed further in an ex vivo immunophenotypic experiment, to look in more detail at the characteristics of responder vs non-responder subgroups (Figure 18). Firstly, the proportion of tumor infiltrating immune cells was investigated. In general, as expected, there were higher T cell populations within the responder vs non-responder tumors.

In contrast, following more specific marker assessment, for CD11c, CD16, and in particular CD56 there seemed to be a population of marker positive cells that were correlated with non-response. Potentially, there may be something inherent about this cell type that inhibits or prevents the response to Keytrudafrom occurring.

Negative Low Intermediate High

11

Case Study Conclusions

With the variability of response to immunotherapy depending on the immunological state of the host immune system, as well as the genetic/phenotypic traits of the cancer, preclinical immuno oncology models and study designs need to be specifically designed to mimic and reflect this variation. Humanized PDX models are predictive of response observed in the clinic, and can help to model clinical settings, with the aim of increasing

understanding around the nature of the immune and cancer cells that make up a response. Utilizing these invaluable models across highly tailored checkerboard studies can also help guide biomarker discovery and patient selection.

Figure 16: Variation of Anti-PD-1 Response Across aHSC Donor Population(3)

Figure 17: Variation of Anti-PD-1 Response AcrossSCLC PDX Models(3)

SCLC #7SCLC #6SCLC #5SCLC #4SCLC #3SCLC #2SCLC #1

C1

C2

C3

C4

C5

VechicleKeytruda

100

80

60

40

20

0

-20

-40

-60

-80

-100

-120

SCLC #7 C2

SCLC #5 C2

SCLC #4 C1

SCLC #7 C4

SCLC #3 C2

SCLC #1 C3

SCLC #4 C2

SCLC #2 C2

SCLC #2 C3

SCLC #4 C5

SCLC #3 C4

SCLC #1 C5

SCLC #5 C3

SCLC #6 C4

SCLC #7 C5

SCLC #3 C3

SCLC #6 C2

SCLC #7 C3

SCLC #6 C3

SCLC #2 C1

SCLC #3 C5

SCLC #2 C5

TGI%

TGI≥48%: N=8/22;36%

Figure 18: Variation of Anti-PD-1 Response Across SCLC PDX Models(3)

% T

IL C

ells

CD30

20

40

60

80

100

CD8CD4

CD25Foxp

3CD3

CD8CD4

CD25Foxp

3

RespondersNon-Responders

0

5

10

Perc

enta

ge %

CD11c

CD56

15

20

25 RespondersNon-Responders

RespondersNon-Responders

RespondersNon-Responders

0

0

20

Perc

enta

ge %

30

40

50

CD16

0

1

2

Perc

enta

ge %

3

4

5

Summary

PDX are highly translational preclinical models which, in a traditional in vivo setting, best represent the heterogeneity found in the human patient population. To gain the full benefit from these models for preclinical cancer research, PDX are now being leveraged across the wide range of in vitro, ex vivo, and in vivo studies, with PDX-derived cell lines and high throughput screens available to rapidly progress drug development programs.

Moving into the immuno-oncology research space, humanized PDX models are a vital resource for modeling interactions between drugs, immune systems, and the heterogeneity of both disease and immune system. These models provide data predictive of clinical response and are now playing a key role across many immuno-oncology applications.

References

1 Onion et al. 3-dimensional patient-derived lung cancer assays reveal resistance to standards-of-care promoted by stromal cells but sensitivity to histone deacetylase inhibitors. Molecular Cancer Therapeutics 2016;15(4):753-763.

2 Xu et al. 3D Ex Vivo PDX Cell Model Screening to Better Predict In Vivo Outcome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; 2018.

Abstract nr 3861.

3 Izadi et al. Evaluation of efficacy and immune response to PD1 checkpoint inhibition in human immune-reconstituted mice using patient-derived xenograft models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Research 2017;77(13 Suppl):Abstract nr 4707.

4 Ott et al. Pembrolizumab in Patients With Extensive-Stage Small-Cell Lung Cancer: Results From the Phase Ib KEYNOTE-028 Study. Journal of Clinical Oncology 2017;35(34):3823-3829.

SalesUS: +1 858 622 2900UK: +44 870 166 6234

Scienceconsultation@crownbio.combusdev@crownbio.com

www.crownbio.com

Get in touch