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Citation: Wu, D.; Berg, J.; Arlt, B.;

Röhrs, V.; Al-Zeer, M.A.; Deubzer,

H.E.; Kurreck, J. Bioprinted Cancer

Model of Neuroblastoma in a Renal

Microenvironment as an Efficiently

Applicable Drug Testing Platform.

Int. J. Mol. Sci. 2022,23, 122. https://

doi.org/10.3390/ijms23010122

Academic Editor:

Alessandro Attanzio

Received: 16 November 2021

Accepted: 21 December 2021

Published: 23 December 2021

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International Journal of

Molecular Sciences

Article

Bioprinted Cancer Model of Neuroblastoma in a Renal

Microenvironment as an Efficiently Applicable Drug

Testing Platform

Dongwei Wu 1, Johanna Berg 1, Birte Arlt 2, Viola Röhrs 1, Munir A. Al-Zeer 1, Hedwig E. Deubzer 2,3,4,5

and Jens Kurreck 1,*

1Institute of Biotechnology, Chair of Applied Biochemistry, Technische Universität Berlin,

13355 Berlin, Germany; [email protected] (D.W.); [email protected] (J.B.);

[email protected] (V.R.); [email protected] (M.A.A.-Z.)

2Department of Pediatric Hematology and Oncology, Charité-Universitätsmedizin Berlin,

13353 Berlin, Germany; [email protected] (B.A.); [email protected] (H.E.D.)

3Neuroblastoma Research Group, Experimental and Clinical Research Center (ECRC) of the Charitéand the

Max-Delbrück-Center for Molecular Medicine (MDC) in the Helmholtz Association, 13125 Berlin, Germany

German Cancer Consortium (Deutsches Konsortium für Translationale Krebsforschung, DKTK), Partner Site

Berlin, 10115 Berlin, Germany

5Berliner Institut für Gesundheitsforschung (BIH), 10178 Berlin, Germany

*Correspondence: jens.kurr[email protected]; Tel.: +49-30-314-27-582; Fax: +49-30-314-27-502

Abstract:

Development of new anticancer drugs with currently available animal models is hampered

by the fact that human cancer cells are embedded in an animal-derived environment. Neuroblastoma

is the most common extracranial solid malignancy of childhood. Major obstacles include managing

chemotherapy-resistant relapses and resistance to induction therapy, leading to early death in very-

high-risk patients. Here, we present a three-dimensional (3D) model for neuroblastoma composed

of IMR-32 cells with amplified genes of the myelocytomatosis viral related oncogene MYCN and the

anaplastic lymphoma kinase (ALK) in a renal environment of exclusively human origin, made of human

embryonic kidney 293 cells and primary human kidney fibroblasts. The model was produced with

two pneumatic extrusion printheads using a commercially available bioprinter. Two drugs were

exemplarily tested in this model: While the histone deacetylase inhibitor panobinostat selectively

killed the cancer cells by apoptosis induction but did not affect renal cells in the therapeutically

effective concentration range, the peptidyl nucleoside antibiotic blasticidin induced cell death in both

cell types. Importantly, differences in sensitivity between two-dimensional (2D) and 3D cultures were

cell-type specific, making the therapeutic window broader in the bioprinted model and demonstrating

the value of studying anticancer drugs in human 3D models. Altogether, this cancer model allows

testing cytotoxicity and tumor selectivity of new anticancer drugs, and the open scaffold design

enables the free exchange of tumor and microenvironment by any cell type.

Keywords: bioprinting; cancer model; drug testing; neuroblastoma; panobinostat

1. Introduction

Bioprinting has been attracting a great deal of attention as a promising technology

to produce three-dimensional (3D) tissue models [

–

]. It allows the production of 3D

constructs with high spatial resolution by successively adding material in a layer-by-

layer manner. Most commonly, cell-laden hydrogels are used as bioinks that are rapidly

crosslinked after the printing procedure to maintain the desired structure [

]. With op-

timized hydrogel compositions, bioprinted cultures can be maintained for an extended

period of time while retaining high cell viability for the duration of the experiment [6].

Bioprinting technology is particularly suitable for the creation of tumor models,

as the high precision and reproducibility can recapitulate the tumor microenvironment

Int. J. Mol. Sci. 2022,23, 122. https://doi.org/10.3390/ijms23010122 https://www.mdpi.com/journal/ijms

Int. J. Mol. Sci. 2022,23, 122 2 of 18

(TME) [

]. In most animal models, human tumors are embedded in a xenogenic animal

environment [9]. This arrangement may produce results with limited relevance to human

pathophysiology. Bioprinting may help to overcome this shortcoming [

]. For exam-

ple, Langer et al. modeled tumor phenotypes, in which patient-specific tumor tissue was

surrounded by several stromal cell types [

]. Extrinsic signals and therapies altered the

tumor phenotypes, and the printed model was used to investigate interaction between

cancer cells and their microenvironment, demonstrating the potential of bioprinting for the

development of new anticancer drugs.

The present study focuses exemplarily on neuroblastoma, which is the most common

extracranial solid tumor of childhood that derives from developing and incompletely com-

mitted precursor cells from neural-crest tissues [

–

]. Despite progress in the treatment

and the use of multi-modal therapy, survival rates of high-risk neuroblastoma patients

are still low [

]. Dysregulation of the transcription factor MYCN is associated with poor

prognosis [

]. Amplification of this proto-oncogene acts as a single oncogenic driver

towards high-risk neoplastic transformation [

]. Panobinostat is a potent histone deacety-

lase (HDAC) inhibitor approved by the U.S. Food and Drug Administration (FDA) for the

treatment of multiple myeloma and is currently under investigation against various other

cancer types [

]. As an additional important factor, forkhead-box-protein O3 (FOXO3) was

found to be an important regulator of homeostasis that promotes tumor growth under hy-

poxic conditions and tumor angiogenesis in late-stage neuroblastoma [

]. Further targets

in high-risk neuroblastoma include the telomerase reverse transcriptase (TERT) and the

oncogene ALK [

]. Phosphoglycerate dehydrogenase (PHGDH) is a suitable marker for

risk stratification, as it is highly upregulated in high-risk MYCN-amplified neuroblastoma;

however, its inhibition by small molecule inhibitors antagonized chemotherapy efficiency

in patient-derived xenografts in mice [

]. In a recent study by Almstedt et al., 80 targets

were found to be associated with the risk of neuroblastoma, and differentiation signatures

and candidates for the treatment of high-risk neuroblastoma were identified [24].

Neuroblastomas have a high potential to migrate and can metastasize to almost any

organ. Around 60% of patients with neuroblastoma develop metastases, most commonly in-

volving bone marrow or cortical bone [

]. Although renal metastasis from neuroblastoma

is rather rare, cases have been reported [

–

]. Especially for bilateral renal metastases or

multiple renal metastases, local therapeutic options for the kidneys, such as nephrectomy

and/or radiotherapy, are infeasible, as they can cause complete loss of renal function

in patients [

]. Over the years, little improvement in the treatment for neuroblastoma

renal metastasis has been obtained and progress in understanding of the disease and the

development of new therapeutic strategies are urgently awaited.

The aim of the present study was to develop a bioprinted 3D model that mimics a

tumor in a microenvironment exclusively composed of human cells. As neuroblastoma

cells have been shown to be well suited for bioprinting approaches [

–

], this tumor

type was chosen as an example. To the best of our knowledge, few studies exist that

have embedded the tumor cells in an environment of normal cells to test the efficiency

and specificity of cytostatic or other anticancer drugs. Our study describes the creation

of a renal neuroblastoma model, in which the neuroblastoma cells were surrounded by a

microenvironment made up of human kidney cells. It can thus be regarded as a simplified

metastasis model. The model was created with a commercially available printer to allow

simple reproduction by other groups. We demonstrate that it can distinguish between

cancer-specific drugs and substances with general cytotoxicity and can thus be used for the

development of new cancer drugs or personalized treatment strategies. It can also be seen

as a model to reflect neuroblastoma infiltration into the kidney, as this process presents a

major medical problem, and if patients are poor responders to chemotherapy, nephrectomy

can be indicated.

Int. J. Mol. Sci. 2022,23, 122 3 of 18

2. Results

2.1. Drug Treatment of Mono-Cell Type 3D Culture

The first step in the development of a cancer model was to characterize the individual

drug-sensitivity of the employed cell types. For the initial experiments, the neuroblas-

toma cell line IMR-32 and the human embryonic kidney 293 cells (HEK293) were printed

into simple 3D grid-like structure (Figure 1a) in a gelatin-alginate bioink as previously

described [36].

Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 3 of 19

2. Results

2.1. Drug Treatment of Mono-Cell Type 3D Culture

The first step in the development of a cancer model was to characterize the individual

drug-sensitivity of the employed cell types. For the initial experiments, the neuroblastoma

cell line IMR-32 and the human embryonic kidney 293 cells (HEK293) were printed into

simple 3D grid-like structure (Figure 1a) in a gelatin-alginate bioink as previously

described [36].

Figure 1. Schematic representation of the 3D printed constructs designed for the present study. For

the initial experiments a simple grid-like structure was used (a), while the cancer model (b)

consisted of a core of neuroblastoma cells (cyan) surrounded by healthy kidney cells (pink).

As a proof-of-concept of the bioprinted cancer model for use in drug testing, the

constructs were treated with varying concentrations of the cancer drug panobinostat one

day after the printing procedure. Relative cell viabilities were determined with XTT assays

(2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide) after 24,

48, and 72 h. Dose–response curves show a significantly lower sensitivity of HEK293 cells

towards panobinostat treatment compared to IMR-32 cells (Figure 2a,b). While the IC

values of IMR-32 cells were in the low nanomolar range, they were in the range of

hundreds of nanomolar for HEK293 cells (Figure 2b,d and Table 1).

Figure 1.

Schematic representation of the 3D printed constructs designed for the present study. For

the initial experiments a simple grid-like structure was used (

), while the cancer model (

) consisted

of a core of neuroblastoma cells (cyan) surrounded by healthy kidney cells (pink).

As a proof-of-concept of the bioprinted cancer model for use in drug testing, the

constructs were treated with varying concentrations of the cancer drug panobinostat one

day after the printing procedure. Relative cell viabilities were determined with XTT assays

(2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide) after 24, 48,

and 72 h. Dose–response curves show a significantly lower sensitivity of HEK293 cells

towards panobinostat treatment compared to IMR-32 cells (Figure 2a,b). While the IC

values of IMR-32 cells were in the low nanomolar range, they were in the range of hundreds

of nanomolar for HEK293 cells (Figure 2b,d and Table 1).

Table 1.

values of HEK293 and IMR-32 cells treated with panobinostat or blasticidin in 3D

constructs or 2D culture.

3D Bioprinted 2D Monolayer

HEK293 IMR-32 HEK293 IMR-32

Panobinostat

(nM)

24 h >1000 7.5 ±0.1 >1000 4.9 ±0.7

48 h 509.0 ±83.8 3.5 ±0.5 40.5 ±12.8 2.7 ±0.5

72 h 107.0 ±40.1 2.1 ±0.5 38.5 ±7.8 2.5 ±0.9

Blasticidin

(µM)

24 h 44.3 ±41.6 52.9 ±15.2 7.9 ±1.4 9.0 ±2.8

48 h 22.3 ±9.1 21.9 ±11.3 5.6 ±0.1 5.2 ±2.6

72 h 15.1 + 6.5 12.4 ±8.0 5.0 ±1.1 3.9 ±2.2

For comparison, we tested the effects of blasticidin, which is an unspecific antibiotic

substance that inhibits translation [37]. As can be seen in Figure 2c, dose–response curves

of HEK293 and IMR-32 cells were similar for blasticidin. IC

values of both cell types were

comparable and did not have significant differences at the time points under investigation

(Figure 2d and Table 1).

Int. J. Mol. Sci. 2022,23, 122 4 of 18

Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 4 of 19

Figure 2. Sensitivity of 3D cultured HEK293 and IMR-32 cells towards panobinostat and blasticidin.

HEK293 and IMR-32 cells were printed in a gelatin-alginate hydrogel (5 × 106 cells/mL) in 48-well

plates and treated with either panobinostat or blasticidin. Dose–response curves of bioprinted

HEK293 and IMR-32 cells after treatment with panobinostat (a) or blasticidin (c) for 24, 48, and 72 h

are shown. The calculated IC50 values for both cell types are compared for panobinostat in (b) and

for blasticidin in (d). Data are presented as mean ± standard error of the mean; n = 3. * p < 0.05, *** p

< 0.001, **** p < 0.0001.

Table 1. IC50 values of HEK293 and IMR-32 cells treated with panobinostat or blasticidin in 3D con-

structs or 2D culture.

3D Bioprinted 2D Monolayer

HEK293 IMR-32 HEK293 IMR-32

Panobinostat

(nM)

24 h >1000 7.5 ± 0.1 >1000 4.9 ± 0.7

48 h 509.0 ± 83.8 3.5 ± 0.5 40.5 ± 12.8 2.7 ± 0.5

72 h 107.0 ± 40.1 2.1 ± 0.5 38.5 ± 7.8 2.5 ± 0.9

Blasticidin

(µM)

24 h 44.3 ± 41.6 52.9 ± 15.2 7.9 ± 1.4 9.0 ± 2.8

48 h 22.3 ± 9.1 21.9 ± 11.3 5.6 ± 0.1 5.2 ± 2.6

72 h 15.1 + 6.5 12.4 ± 8.0 5.0 ± 1.1 3.9 ± 2.2

For comparison, we tested the effects of blasticidin, which is an unspecific antibiotic

substance that inhibits translation [37]. As can be seen in Figure 2c, dose–response curves

of HEK293 and IMR-32 cells were similar for blasticidin. IC50 values of both cell types were

comparable and did not have significant differences at the time points under investigation

(Figure 2d and Table 1).

Figure 2.

Sensitivity of 3D cultured HEK293 and IMR-32 cells towards panobinostat and blasticidin.

HEK293 and IMR-32 cells were printed in a gelatin-alginate hydrogel (5

cells/mL) in

48-well

plates and treated with either panobinostat or blasticidin. Dose–response curves of bioprinted

HEK293 and IMR-32 cells after treatment with panobinostat (

) or blasticidin (

) for 24, 48, and

72 h are shown. The calculated IC

values for both cell types are compared for panobinostat in

(

) and for blasticidin in (

). Data are presented as mean

standard error of the mean; n= 3.

*p< 0.05, *** p< 0.001, **** p< 0.0001.

2.2. Cytotoxicity in 3D Constructs

Cytotoxicity can be directly monitored in 3D constructs to assess the cytostatic impact

caused by panobinostat on bioprinted cells. HEK293 and IMR-32 cells were separately

printed in grid models and treated with varying concentrations of panobinostat. After

72 h, the ratio of live (green channel) and dead (red channel) cells in the constructs was

monitored by fluorescence microscopy using a cytotoxicity assay (Figure 3a,b). Percentages

of live and dead cells, resulting from quantification of green and red fluorescence signals,

were calculated by the software ImageJ (Figure 3c,d). More than 75% of printed HEK293

cells survived using panobinostat concentrations of up to 50 nM, and only the highest doses

led to an obvious increase of dead cells (Figure 3a,c). In contrast, panobinostat began cell

killing at much lower doses and resulted in death of almost all IMR-32 cells already at a

concentration of 10 nM and above (Figure 3b,d).

2.3. Cell Sensitivity in 2D Culture

To figure out the influence of the 3D arrangement of the cells, we compared the IC

values obtained in the bioprinted models with those from 2D monolayer cultures. The 2D

cultures were challenged with a single dose of either panobinostat at varying concentrations

and cultured for 72 h. During the culture period, relative cell viability was monitored by

XTT assays (Figure 4) and used to calculate the IC

values from the dose–response curves

Int. J. Mol. Sci. 2022,23, 122 5 of 18

(Table 1). As observed for the 3D cultures, IMR-32 cells were substantially more sensitive

to panobinostat treatment than HEK293 cells, and viability was significantly decreased at

concentrations in the low nanomolar range starting as early as 24 h post treatment. After

48 and 72 h of cultivation, the decrease in viability became even more pronounced and

at concentrations above 15 nM of panobinostat, virtually no viable cells were detected.

Accordingly, IC

values of IMR-32 cells challenged with panobinostat were in the low

nanomolar range and substantially lower than that of HEK293 cells (Table 1).

Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 5 of 19

2.2. Cytotoxicity in 3D Constructs

Cytotoxicity can be directly monitored in 3D constructs to assess the cytostatic impact

caused by panobinostat on bioprinted cells. HEK293 and IMR-32 cells were separately

printed in grid models and treated with varying concentrations of panobinostat. After

72 h, the ratio of live (green channel) and dead (red channel) cells in the constructs was

monitored by fluorescence microscopy using a cytotoxicity assay (Figure 3a,b). Percent-

ages of live and dead cells, resulting from quantification of green and red fluorescence

signals, were calculated by the software ImageJ (Figure 3c,d). More than 75% of printed

HEK293 cells survived using panobinostat concentrations of up to 50 nM, and only the

highest doses led to an obvious increase of dead cells (Figure 3a,c). In contrast, panobino-

stat began cell killing at much lower doses and resulted in death of almost all IMR-32 cells

already at a concentration of 10 nM and above (Figure 3b,d).

Figure 3. Cytotoxicity of HEK293 cells and IMR-32 cells in printed constructs after treatment with

panobinostat. Cytotoxicity assays of 3D-bioprinted HEK293 cells (a) and IMR-32 cells (b) after treat-

ment with panobinostat for 72 h (living cells in green, dead cells in red; all images were taken at the

same magnification, scale bar, 250 µm), and the estimated percentages of living and dead cells (c,d).

2.3. Cell Sensitivity in 2D Culture

To figure out the influence of the 3D arrangement of the cells, we compared the IC50

values obtained in the bioprinted models with those from 2D monolayer cultures. The 2D

cultures were challenged with a single dose of either panobinostat at varying concentra-

tions and cultured for 72 h. During the culture period, relative cell viability was monitored

by XTT assays (Figure 4) and used to calculate the IC50 values from the dose–response

curves (Table 1). As observed for the 3D cultures, IMR-32 cells were substantially more

sensitive to panobinostat treatment than HEK293 cells, and viability was significantly de-

creased at concentrations in the low nanomolar range starting as early as 24 h post treat-

ment. After 48 and 72 h of cultivation, the decrease in viability became even more pro-

nounced and at concentrations above 15 nM of panobinostat, virtually no viable cells were

Figure 3.

Cytotoxicity of HEK293 cells and IMR-32 cells in printed constructs after treatment with

panobinostat. Cytotoxicity assays of 3D-bioprinted HEK293 cells (

) and IMR-32 cells (

) after

treatment with panobinostat for 72 h (living cells in green, dead cells in red; all images were taken

at the same magnification, scale bar, 250

m), and the estimated percentages of living and dead

cells (c,d).

These results were confirmed by cytotoxicity assays (Figure S1), which clearly dis-

played differences in sensitivity of HEK293 and IMR-32 cells towards panobinostat treat-

ment. While HEK293 cells were virtually insensitive to the panobinostat treatment in the

concentration range tested, the fraction of green fluorescence from viable IMR-32 cells

drastically decreased at panobinostat concentrations above 5 nM.

The most interesting outcome of the comparison was that the IC

values of IMR-

32 cells for panobinostat were approximately one order of magnitude higher for the 3D

cultures than for the 2D monolayers. The differences were less pronounced for HEK293 cells

so that the therapeutic window was broader in the bioprinted constructs, i.e., the difference

in sensitivity between both cell types was more pronounced in 3D culture (approximately

two orders of magnitude) than in 2D culture (roughly one order of magnitude).

As the study intended to investigate the specificity of treatment for cancerous cells,

we also tested whether co-cultivation of both cell types in 2D influences the sensitivity to-

wards panobinostat. To this end, HEK293 cells stably expressing green fluorescence protein

(HEK293-GFP) and IMR-32 cells were seeded together at a ratio of 1:1. After treatment

with panobinostat, cells were analyzed by an immunofluorescence microscopy (Figure 5).

The green fluorescence emitted by HEK293-GFP cells was used to simplify this analysis.

IMR-32 cells

were labeled by immunofluorescence staining against human disialoganglio-

Int. J. Mol. Sci. 2022,23, 122 6 of 18

side GD2 (GD2, red channel), which is expressed on tumors of neuroectodermal origin,

including neuroblastoma and melanoma [

]. Nuclear counterstaining was performed

with DAPI (4

,6-diamidin-2-phenylindol, blue channel). As shown in Figure 5, HEK293-

GFP and IMR-32 cells occupied approximately equivalent areas in the untreated control

group after 72 h. With increasing panobinostat doses, the area with red signals, which

represents the GD2-stained IMR-32 cells, shrank gradually, whereas green fluorescing

HEK293 cells occupied the vacated area. Only at the highest concentration of panobinostat

tested (

50 nM

), was a decrease in HEK293-GFP cells observed, while virtually no more

IMR-32 cells were detectable.

Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 6 of 19

detected. Accordingly, IC50 values of IMR-32 cells challenged with panobinostat were in

the low nanomolar range and substantially lower than that of HEK293 cells (Table 1).

Figure 4. Sensitivity of 2D cultured HEK293 and IMR-32 cells towards panobinostat and blasticidin.

HEK293 (104 cells/well) and IMR-32 cells (104 cells/well) were separately seeded in 96-well plates

and treated with either panobinostat or blasticidin. Dose–response curves of HEK293 and IMR-32

cells after treatment with panobinostat (a) or blasticidin (c) 24, 48, and 72 h post treatment; and the

calculated IC50 values of HEK293 and IMR-32 cells for indicated time points, (b) for panobinostat

and (d) for blasticidin. Data are presented as mean ± standard error of the mean; n = 3. ** p < 0.01,

*** p < 0.001.

These results were confirmed by cytotoxicity assays (Figure S1), which clearly dis-

played differences in sensitivity of HEK293 and IMR-32 cells towards panobinostat treat-

ment. While HEK293 cells were virtually insensitive to the panobinostat treatment in the

concentration range tested, the fraction of green fluorescence from viable IMR-32 cells

drastically decreased at panobinostat concentrations above 5 nM.

The most interesting outcome of the comparison was that the IC50 values of IMR-32

cells for panobinostat were approximately one order of magnitude higher for the 3D cul-

tures than for the 2D monolayers. The differences were less pronounced for HEK293 cells

so that the therapeutic window was broader in the bioprinted constructs, i.e., the differ-

ence in sensitivity between both cell types was more pronounced in 3D culture (approxi-

mately two orders of magnitude) than in 2D culture (roughly one order of magnitude).

As the study intended to investigate the specificity of treatment for cancerous cells,

we also tested whether co-cultivation of both cell types in 2D influences the sensitivity

towards panobinostat. To this end, HEK293 cells stably expressing green fluorescence pro-

tein (HEK293-GFP) and IMR-32 cells were seeded together at a ratio of 1:1. After treatment

with panobinostat, cells were analyzed by an immunofluorescence microscopy (Figure 5).

The green fluorescence emitted by HEK293-GFP cells was used to simplify this analysis.

IMR-32 cells were labeled by immunofluorescence staining against human disialogangli-

oside GD2 (GD2, red channel), which is expressed on tumors of neuroectodermal origin,

including neuroblastoma and melanoma [38,39]. Nuclear counterstaining was performed

with DAPI (4′,6-diamidin-2-phenylindol, blue channel). As shown in Figure 5, HEK293-

Figure 4.

Sensitivity of 2D cultured HEK293 and IMR-32 cells towards panobinostat and blasticidin.

HEK293 (10

cells/well) and IMR-32 cells (10

cells/well) were separately seeded in 96-well plates and

treated with either panobinostat or blasticidin. Dose–response curves of HEK293 and

IMR-32 cells

after treatment with panobinostat (

) or blasticidin (

) 24, 48, and 72 h post treatment; and the

calculated IC

values of HEK293 and

IMR-32 cells

for indicated time points, (

) for panobinostat

and (

) for blasticidin. Data are presented as mean

standard error of the mean; n= 3. ** p< 0.01,

*** p< 0.001.

Similar to the 3D constructs, the sensitivity of the cells in 2D monolayers for blasticidin

was also tested. As previously observed, dose–response curves and calculated IC

values

were similar for both cell types and did not show significant differences at the time points

under investigation (Figure 4c,d and Table 1).

Int. J. Mol. Sci. 2022,23, 122 7 of 18

Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 7 of 19

GFP and IMR-32 cells occupied approximately equivalent areas in the untreated control

group after 72 h. With increasing panobinostat doses, the area with red signals, which

represents the GD2-stained IMR-32 cells, shrank gradually, whereas green fluorescing

HEK293 cells occupied the vacated area. Only at the highest concentration of panobinostat

tested (50 nM), was a decrease in HEK293-GFP cells observed, while virtually no more

IMR-32 cells were detectable.

Figure 5. Co-culture of HEK29-GFP cells and IMR-32 cells in monolayer treated with panobinostat

visualized by expressed GFP and immunofluorescence staining of GD2. HEK293-GFP cells and

IMR-32 cells (1:1) at a total density of 104/well were seeded in 96-well plate and dosed with pano-

binostat at the indicated concentrations for 72 h. HEK293-GFP cells (green) expressed GFP while

IMR-32 (red) cells were labeled by GD2 immunofluorescence staining. The nuclei were all stained

with DAPI in blue. All images were taken at the same magnification; scale bar, 250 µm.

Similar to the 3D constructs, the sensitivity of the cells in 2D monolayers for blasti-

cidin was also tested. As previously observed, dose–response curves and calculated IC50

values were similar for both cell types and did not show significant differences at the time

points under investigation (Figure 4c,d and Table 1).

Figure 5.

Co-culture of HEK29-GFP cells and IMR-32 cells in monolayer treated with panobinostat

visualized by expressed GFP and immunofluorescence staining of GD2. HEK293-GFP cells and IMR-

32 cells (1:1) at a total density of 10

/well were seeded in 96-well plate and dosed with panobinostat

at the indicated concentrations for 72 h. HEK293-GFP cells (green) expressed GFP while IMR-32 (red)

cells were labeled by GD2 immunofluorescence staining. The nuclei were all stained with DAPI in

blue. All images were taken at the same magnification; scale bar, 250 µm.

2.4. Induction of Apoptosis in 2D Culture

Panobinostat is known to be an HDAC inhibitor, so our next aim was to confirm

observation of this mode of action in our experimental set-up. This activity may result

in the induction of apoptosis. We therefore investigated whether panobinostat treatment

of HEK293 and IMR-32 cells in 2D culture produced cleaved caspase-3 (green channel

Figure S2

) by immunofluorescence staining. Additionally, cellular filamentous actin

(F-actin, red channel) and nuclei (blue channel) were visualized by phalloidin and DAPI

counterstaining, respectively. Staining of F-actin and the nuclei revealed that increasing

panobinostat concentrations led to decreasing numbers of IMR-32 cells but did not impact

HEK293 cell numbers, which was in agreement with the results of XTT and cytotoxicity

assays. Cleaved caspase-3 was not detected in HEK293 cells at panobinostat concentrations

below 25 nM, and even 50 nM panobinostat resulted in only weak signals. In contrast, sig-

nals resulting from cleaved caspase-3 were detected in IMR-32 cells, even at concentrations

Int. J. Mol. Sci. 2022,23, 122 8 of 18

as low as

5 nM

, and became more pronounced at higher concentrations in a dose-dependent

manner. This demonstrates that panobinostat is a stronger inducer of apoptosis in IMR-32

cells than in HEK293 cells.

2.5. Bioprinting and Drug Treatment of Cancer Model

After the initial characterization of the drug activity, a cancer model was fabricated

that consisted of a cancerous core (IMR-32 cells) surrounded by a shell of kidney cells as

illustrated in Figure 1b. In the initial experiments, HEK293-GFP cells were used for better

visualization, then HEK293 cells were included to provide additional immunofluorescence

evidence and in the final experiments primary kidney fibroblasts were used to increase the

physiological significance of the model. The diameter of the inner core was 3 mm, while

the total model was 6 mm in diameter and 0.4 mm in height (Figure 6a). A set of 48 such

constructs were produced by bioprinting and proved to be highly reproducible (Figure 6b).

Fluorescence analyses revealed a clear boundary between the IMR-32 cell in the cen-

ter and the green fluorescing HEK293-GFP cells (Figure 6c). The model was treated with

panobinostat for 72 h and dead cells were stained with ethidium homodimer-1. Pronounced

red fluorescence of dead cells was detected coming from the inner part composed of IMR-32

cells, while strong green fluorescence in the outer ring resulted from high GFP expression

of the stably transfected HEK293-GFP cells. Only at very high panobinostat concentrations

(1000 nM) was a fraction of dead, red fluorescent HEK293-GFP cells observed. The sig-

nificantly higher sensitivity of the neuroblastoma cells towards panobinostat was clearly

confirmed in the quantitative analysis of the red fluorescence of the inner and outer part of

the model, respectively (Figure 6d). Two conclusions can be drawn from these observations:

The bioink composition allows maintenance of the intended design of the model with a

cancerous core surrounded by a shell of kidney cells, and the differences in drug sensitivity

can be clearly seen in a 3D model composed of different cell types.

The experiments were repeated with HEK293 and IMR-32 cells, as this approach allows

the detection of living cells by calcein AM staining, which cannot be distinguished from the

green fluorescence of HEK293-GFP cells. These experiments confirmed the observations

made above (Figure S3). A concentration of panobinostat as low as 10 nM was sufficient

to kill a substantial fraction of IMR-32 cells. The merged images show a clear border

between the dead, red fluorescing cells in the center and green living cells in the outer ring

at panobinostat concentrations of 10 to 100 nM. Red fluorescence originating from dead

HEK293 cells was only observed at very high panobinostat concentrations.

The next experiment aimed at investigating the induction of apoptosis in the different

parts of the cancer model by immunofluorescent labeling of cleaved caspase-3 (Figure S4,

green channel). To clearly distinguish HEK293 cells from IMR-32 cells in the printed cancer

models, the latter were labeled with the neuroblastoma-specific GD2 antibody (red channel).

Nuclear counterstaining with DAPI (blue channel) revealed a homogenous distribution of

the cells throughout the constructs for all samples (Figure S4a,b). Starting at a panobinostat

concentration of 10 nM, green fluorescence indicating the induction of apoptosis became

visible in the cancerous core of the constructs. Signal intensity increased at higher drug

concentrations. In contrast, even at the highest concentration of panobinostat of 1000 nM,

only a weak green signal originating from cleaved caspase-3 was observed in the periphery

of the model containing HEK293 cells. Quantification of the fluorescence signals using

ImageJ revealed significant differences between the presence of cleaved caspase-3 in the

cancer part and surrounding renal environment (Figure S4c). Thus, induction of apoptosis

is significantly stronger by a factor of two to three in IMR-32 cells compared to that in

HEK293 cells.

Int. J. Mol. Sci. 2022,23, 122 9 of 18

Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 9 of 19

Figure 6. Cancer model and cytotoxicity assays following treatment with panobinostat. (a) The bi-

oprinted cancer model consisted of a core of neuroblastoma IMR-32 cells (diameter of 3 mm, height

of the construct 0.4 mm) surrounded by an environment of kidney cells (HEK293-GFP cells in these

experiments, HEK293 cells and primary kidney fibroblasts, respectively, in experiments below,

outer diameter is 6 mm). (b) Bioprinting can produce the constructs in a highly reproducible man-

ner. (c) The cancer model was treated with panobinostat for 72 h and subsequently stained with

ethidium homodimer-1. HEK293-GFP cells emitted green fluorescence, dead cells were identified

by ethidium homodimer-1 staining in red. The boundary between both cell types is indicated by a

dotted line. All images were taken at the same magnification; scale bar, 500 µm. (d) Quantitative

analysis of dead cells in HEK293-GFP and IMR-32 parts of the models by mean fluorescence inten-

sity based on the red channel results. * p < 0.05, ** p < 0.01, *** p < 0.001.

The experiments were repeated with HEK293 and IMR-32 cells, as this approach al-

lows the detection of living cells by calcein AM staining, which cannot be distinguished

from the green fluorescence of HEK293-GFP cells. These experiments confirmed the ob-

servations made above (Figure S3). A concentration of panobinostat as low as 10 nM was

sufficient to kill a substantial fraction of IMR-32 cells. The merged images show a clear

Figure 6.

Cancer model and cytotoxicity assays following treatment with panobinostat. (

) The

bioprinted cancer model consisted of a core of neuroblastoma IMR-32 cells (diameter of 3 mm, height

of the construct 0.4 mm) surrounded by an environment of kidney cells (HEK293-GFP cells in these

experiments, HEK293 cells and primary kidney fibroblasts, respectively, in experiments below, outer

diameter is 6 mm). (

) Bioprinting can produce the constructs in a highly reproducible manner.

cancer model was treated with panobinostat for 72 h and subsequently stained with ethidium

homodimer-1. HEK293-GFP cells emitted green fluorescence, dead cells were identified by ethidium

homodimer-1 staining in red. The boundary between both cell types is indicated by a dotted line. All

images were taken at the same magnification; scale bar, 500

m. (

) Quantitative analysis of dead

cells in HEK293-GFP and IMR-32 parts of the models by mean fluorescence intensity based on the

red channel results. * p< 0.05, ** p< 0.01, *** p< 0.001.

A completely different picture arose for blasticidin treatment. Here, no fluorescence

originating from cleaved caspase-3 was observed at concentrations up to 10

M (

Figure S4b

At higher concentrations, the signal became stronger in a dose-dependent manner in both

parts of the model. Quantitative analysis of the fluorescence by ImageJ confirmed the

blasticidin-sensitivity of both cell types is roughly equivalent (Figure S4d). The model thus

allows distinguishing drugs which are specifically toxic to cancer cells like panobinostat

from those that are generally cytotoxic such as blasticidin.

Int. J. Mol. Sci. 2022,23, 122 10 of 18

2.6. Cell Response of Primary Human Kidney Fibroblasts on Panobinostat Treatment

Despite the ambiguities about the origin of the HEK293 cell line and its derivatives,

they are among the most widely used cells in molecular biology, after HeLa cells [

]. To

improve the (patho-)physiological relevance of the bioprinted cancer model, we replaced

the HEK293 cells with human primary kidney fibroblasts, expecting them to provide a

physiologically more relevant human renal microenvironment for the cancer cells. Fibrob-

lasts are important regulators for the maintenance of tissue cohesion, as they are essential

for the production and degradation of extracellular matrix components [

]. In addition,

kidney fibroblasts also have endocrine activity [42].

For an initial characterization of their drug sensitivity, human kidney fibroblasts were

seeded in a 96-well plate and treated with panobinostat. Cell viability, as evaluated by XTT

assay, remained above 90% 24 h post treatment for all concentrations tested (Figure 7a).

Only at later time points (48 and 72 h after panobinostat treatment), was a dose-dependent

decrease in viability detected. The IC

values were calculated and found to be comparable

to the ones of HEK293 cells in 2D culture (Figure 7b and Table 2). Similar characteristics

were observed when primary human kidney fibroblasts were printed into a 3D structure

(Figure 7c,d). Compared to the IC

values of the printed IMR-32 cells (see above, Table 1),

values for the primary fibroblasts were approximately two orders of magnitude higher

(Table 2). Resistance of human kidney fibroblasts to panobinostat was also found in

cytotoxicity assay for 2D and 3D cultures (Figure S5).

Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 11 of 19

Figure 7. Dose–response curves for panobinostat treatment of primary human kidney fibroblasts in

2D and 3D culture. Monolayer (2D) cultured kidney fibroblast (a,b) and bioprinted (3D) kidney

fibroblast (c,d) were treated with increasing concentrations of panobinostat. Cell viability was eval-

uated by XTT assays after 24, 48, and 72 h. Dose–response curves (a,c) and the calculated IC50 values

(b,d) are shown. Data are presented as mean ± standard error of the mean; n = 3. **** p < 0.0001.

Table 2. IC50 values of human kidney fibroblast treated with panobinostat in 2D culture or 3D con-

structs.

2D Monolayer 3D Bioprinted

Panobinostat

(nM)

24 h >1000 >1000

48 h 120.3 ± 44.3 328.2 ± 98.5

72 h 35.5 ± 19.8 158.9 ± 40.5

Figure 7.

Dose–response curves for panobinostat treatment of primary human kidney fibroblasts in 2D

and 3D culture. Monolayer (2D) cultured kidney fibroblast (

) and bioprinted (3D) kidney fibroblast

(

) were treated with increasing concentrations of panobinostat. Cell viability was evaluated by

XTT assays after 24, 48, and 72 h. Dose–response curves (

) and the calculated IC

values (

) are

shown. Data are presented as mean ±standard error of the mean; n= 3. **** p< 0.0001.

Int. J. Mol. Sci. 2022,23, 122 11 of 18

Table 2.

values of human kidney fibroblast treated with panobinostat in 2D culture or

3D constructs.

2D Monolayer 3D Bioprinted

Panobinostat

(nM)

24 h >1000 >1000

48 h 120.3 ±44.3 328.2 ±98.5

72 h 35.5 ±19.8 158.9 ±40.5

2.7. Effect of Panobinostat on Printed Cancer Model with Neuroblastoma and Primary

Kidney Fibroblasts

In the final experiment of this study, primary human kidney fibroblasts were printed

in the cancer model described above, i.e., the center containing IMR-32 neuroblastoma cells

was surrounded by a ring of primary fibroblasts. The model was treated with increasing

concentrations of panobinostat, and cytotoxicity assays were carried out 72 h thereafter.

As can be seen in Figure 8, red fluorescence originating from dead cells appeared in the

cancerous part starting at 10 nM panobinostat and became more intense at increased drug

concentrations. In contrast, dead fibroblasts were only observed at high concentrations

of panobinostat.

Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 12 of 19

2.7. Effect of Panobinostat on Printed Cancer Model with Neuroblastoma and Primary Kidney

Fibroblasts

In the final experiment of this study, primary human kidney fibroblasts were printed

in the cancer model described above, i.e., the center containing IMR-32 neuroblastoma

cells was surrounded by a ring of primary fibroblasts. The model was treated with in-

creasing concentrations of panobinostat, and cytotoxicity assays were carried out 72 h

thereafter. As can be seen in Figure 8, red fluorescence originating from dead cells ap-

peared in the cancerous part starting at 10 nM panobinostat and became more intense at

increased drug concentrations. In contrast, dead fibroblasts were only observed at high

concentrations of panobinostat.

Figure 8. Cytotoxicity of cancer (IMR-32) and non-cancerous environment (primary kidney fibro-

blasts) of the bioprinted models after treatment with panobinostat. Cytotoxicity assays of cancer

models were carried out after treatment with panobinostat for 72 h. Living cells were labeled in

green, and dead cells were in red. The white dotted lines indicate the boundary between cancer part

(above the line) and non-cancerous environment (below the line). All images were taken at the same

magnification; scale bar, 500 µm.

Figure 8.

Cytotoxicity of cancer (IMR-32) and non-cancerous environment (primary kidney fibrob-

lasts) of the bioprinted models after treatment with panobinostat. Cytotoxicity assays of cancer

models were carried out after treatment with panobinostat for 72 h. Living cells were labeled in

green, and dead cells were in red. The white dotted lines indicate the boundary between cancer part

(above the line) and non-cancerous environment (below the line). All images were taken at the same

magnification; scale bar, 500 µm.

Int. J. Mol. Sci. 2022,23, 122 12 of 18

3. Discussion

Despite substantial progress in the last few decades, efficient treatment options are

still lacking for many tumor types and especially for metastatic cancer. In preclinical

studies, 2D monolayer cultures have greatly contributed to the basic knowledge of genetic

factors that drive transformation of somatic cells into tumor cells. These studies, however,

cannot mimic the 3D architecture of tumors and their interaction with their surrounding

microenvironment. To this end, animal models were developed which allowed studying

tumor development in a complex pathophysiological environment [

]. Although these

models made an enormous contribution to the field, they provide a xenogenic microen-

vironment instead of a human one, and therefore often have limited relevance to human

pathophysiology [

]. As a consequence, the average success rate for the translation of

insights from animal models to clinical trials is less than 8% [

]. In line with these data, a

comprehensive review revealed a failure rate of drug candidates in oncology of 97% [

Alternative strategies with higher predictivity for newly developed drug candidates are

thus urgently required.

Although still being a comparatively young discipline, bioprinting technologies have

already demonstrated their potential for cancer research [

] and the printability of neu-

roblastoma cells has been demonstrated in several studies: The Noguera group produced

bioprinted neuroblastoma models and investigated the impact of tissue stiffness, which

commonly increases in solid tumors [

]. Remarkably, they found stiffness to influence

expression patterns and cellular physiology. In a model composed of the neuroblastoma cell

line SH-SY5Y in co-culture with mesenchymal stromal cells and human primary umbilical

vein endothelial cells, the neuroblastoma cells formed Homer Wright-like rosettes and

maintained their proliferative capacities [

]. Another bioprinted tumor model consisting

of SK-N-BE(2) cells was used to investigate the infiltration of chimeric antigen receptor

(CAR) T cells into tumor tissues [

]. In further studies, neuroblastoma cell lines have

been used to develop neural tissue for studying neurodegenerative diseases [

]. None

of these previous studies, however, tested cytostatic or other anticancer drugs in the bio-

printed models. As the printability of neuroblastoma cells has been well documented, we

chose this tumor type as an example for our open design of a cancer model to test the

activity and specificity of anticancer drugs. Our model was produced with a commercially

available bioprinter and can therefore easily be adapted by other research groups.

The TME has a major influence on the solid tumor, as it provides cytokines, immune

cells, and vasculature that determine the tumor phenotype and encumber therapeutic

interventions [

]. Due to species differences, the effects of the TME measured in animal

models cannot be relied upon when translated into clinical settings. In contrast, bioprinting

can be used to produce a tumor in a human TME and to investigate interactions between

the tumor and its TME, as well as its influence on drug treatment, for neuroblastomas and

other types of tumors [

]. In breast cancer, tumor progression is strongly influenced by its

microenvironment and particularly by interaction of the cancer cells with adipose tissue,

which can be recapitulated in bioprinted models [

]. In another study, breast cancer cells

were printed in the center of a 3D model and surrounded by adipose-derived mesenchymal

stem/stromal cells (ADMSC) [

]. This model was significantly less sensitive to treatment

with doxorubicin than a construct that contained the cancer cells only. The response was

found to depend on the thickness of the ADMSC layer, demonstrating the importance of

the tumor environment. In a previous study, we found a bioprinted liver model to be less

sensitive toward Aflatoxin B1 than a monolayer culture [

]. The possibility of creating

sustainable long-term cultures allows the study of the long-term mutagenic effects of a

potential carcinogen. Heterogenous tissue models with high cell density can be produced

by bioprinting technologies, including spheroids [52].

The current lack of standards for models and their reproducibility makes it difficult to

compare the results from different research groups. For example, Langer et al. produced a

tumor model, as described above, in which cancer cells were printed in a stromal mix of

Int. J. Mol. Sci. 2022,23, 122 13 of 18

human fibroblasts and endothelial cells [12]. This model studied interactions between the

tumor and its microenvironment; however, the sophisticated model was produced with

a special printer of the company Organovo, Inc. to which other researchers do not have

access. In contrast, the model presented here can easily be reproduced with an affordable,

commercially available printer.

In our study, we evaluated the sensitivity of the neuroblastoma cells IMR-32 and

renal HEK293 cells, as well as primary kidney fibroblasts, toward the anticancer drug

panobinostat and the cytotoxic substance blasticidin in 2D and 3D cultures. IMR-32 cells

had comparable sensitivities for panobinostat in 2D and 3D cultures, whereas HEK293 and

primary kidney fibroblasts became more resistant, when cultured in the 3D model. Most

importantly, IMR-32 cells were substantially more sensitive to panobinostat treatment than

the renal cells. The difference was approximately one order of magnitude in 2D culture

and increased to roughly two orders in magnitude in bioprinted models. In contrast, the

effect of blasticidin treatment was comparable for IMR-32 and HEK293 cells and the IC

values increased for both cell types in 3D compared to 2D in a similar manner.

The bioprinting technology was then used to produce neuroblastoma in a renal en-

vironment. Fluorescence microscopy confirmed that the chosen bioinks maintained the

intended structure over the course of the experiments for 72 h. Cytotoxicity assays showed

that intermediate panobinostat concentrations of 10–100 nM selectively killed neuroblas-

toma cells, while leaving the kidney cells intact. Cell death occurred via the induction of

apoptosis, as demonstrated by measuring increased levels of cleaved caspase-3. In contrast

to panobinostat, blasticidin induced apoptosis in both cell types at similar concentrations.

As HEK293 cells are easy to culture and expand to large numbers, they were used

for the initial experiments. This cell line is widely used, but its exact origin is still contro-

versial [

]. While they have been considered kidney epithelial cells or fibroblasts, their

karyotype is unstable, and they are tumorigenic. We therefore used primary kidney fibrob-

lasts in further experiments. These tests confirmed findings obtained with HEK293 cells.

IMR-32 cells are approximately two orders of magnitude more sensitive to panobinostat

treatment in the cancer model than the kidney cells and can thus be selectively killed by

the anti-tumor drug.

As described above, the study of Grundwald et al. [

] used a bioprinted neuroblas-

toma model consisting of SK-N-BE(2) cells to investigate tumor tissue penetration by CAR T

cells. Our model, which consists of not only cancerous cells, but also normal fibroblasts, can

now be used to investigate the specificity of the treatment for the destruction of the tumor.

The next step will therefore be to use the model consisting of neuroblastoma in a microen-

vironment composed of non-cancerous cells, not only for cytostatic substances but also

for immunotherapeutic approaches. Another interesting option is to use patient-derived

tumor cells to develop a personalized treatment strategy. For example, Mao et al. produced

a 3D tumor model with patient derived intrahepatic cholangiocarcinoma cells [

], and

Flores–Torres et al. developed a patient-derived 3D bioprinted spheroid model with triple-

negative breast cancer cells [

]. These studies, however, used the cancer cells only, while

the strategy presented here will allow to study the patient-derived cells in a human TME.

While we focused the present study on the production of an advanced cancer model

involving a tumor surrounded by a human microenvironment, at the same time we aimed

to support the principles of replacement, reduction, and refinement (3R principles). Highly

sophisticated 3D organ models will help to replace animal experiments with

in vitro

stud-

ies [

]. It is our strong belief that only innovative new tissue engineering strategies en-

abling better transferability of research results to the human

(patho-)

physiology will bring

us closer to the ultimate goal to reduce the number of animals used for

experimental purposes.

4. Materials and Methods

4.1. Cell Culture

Human embryonic kidney 293 cells (HEK293, CRL-1573) were purchased from Amer-

ican Type Culture Collection (ATCC, Manassas, VA, USA) and the neuroblastoma cell

Int. J. Mol. Sci. 2022,23, 122 14 of 18

line IMR-32 from the German Collection of Microorganisms and Cell Cultures (DSMZ,

Braunschweig, Germany). HEK293-GFP cells were obtained from GenTarget (SC001, San

Diego, CA, USA). Human kidney fibroblasts were purchased from Innoprot (P10666, De-

rio, Bizkaia, Spain). All cell lines were cultured in Dulbecco’s modified Eagle’s medium

(DMEM, Biowest, Nuaillé, France) containing 10% fetal bovine serum (FBS; c.c.pro, Ober-

dorla, Germany), 2.5 mg/mL of glucose (Biowest, Nuaillé, France), 2 mM of L-glutamine

(Biowest, Nuaillé, France), 1% non-essential amino acids (NEAA, Biowest, Nuaillé, France),

and 1% penicillin-streptomycin (Biowest, Nuaillé, France) and maintained at 37

◦

C in hu-

midified atmosphere with 5% CO

. When confluent, the cells were washed with phosphate

buffered saline (PBS, Biowest, Nuaillé, France) and then harvested using trypsin-EDTA

(Biowest, Nuaillé, France).

4.2. Bioprinting

The hydrogel, consisting of 6.67% gelatin (Sigma–Aldrich, St. Louis, MO, USA) and

4.5% sodium alginate (Sigma, Shanghai, China), was prepared in DMEM under continuous

stirring at 37

◦

C overnight as described before [

]. Prior to the printing process, the

printable cell-laden bioink was obtained by mixing the hydrogel, CaSO

(Roth, Karlsruhe,

Germany), and the cell suspension, so that the final concentration of each component

was: 3% gelatin, 2% sodium alginate, 30 mM of CaSO

, and 5

cells/mL bioink.

After physical pre-crosslinking for 8 min at room temperature, the cell-laden bioink was

transferred into a pneumatic cartridge.

The 3D constructs were fabricated in a 48-well plate using a multi nozzle bioprinting

system (Bio X, Cellink, Gothenburg, Sweden) as the bioink was extruded from a 22 G

conical tip under pneumatic pressure. A double-layer grid-like model with a side length

of 8 mm was printed for single-cell type printing, while a concentric disc construct with

3 mm-diameter

inner part containing cancer cells, and 6 mm-diameter outer part con-

taining normal stromal cells was fabricated for the two-cell type cancer model. After the

printing process, printed models were submerged in 100 mM of CaCl

for 10 min at room

temperature. Afterwards, the 100 mM CaCl

solution was replaced with 300

L of complete

medium supplemented with 20 mM CaCl

per well, and subsequently the constructs were

cultured at 37 ◦C and 5% CO2.

4.3. Drug Treatment of Cancer Models

For monolayer culture, cells were seeded into a collagen (90

g/mL, collagen type I, rat

tail, EMD Millipore, Billerica, MA, USA) -coated 96-well plate at a density of

104cells/well

After culture for 24 h, the supernatant of each well was replaced by 100

L of medium with

the respective drug (panobinostat ((LBH589, Selleckchem, Houston, TX, USA), initially

dissolved in dimethyl sulfoxide (DMSO, Sigma–Aldrich, St. Louis, MO, USA)) or blasticidin

(10 mg/mL in 20 mM HEPES, Sigma–Aldrich, St. Louis, MO, USA)) at the indicated

concentrations. Complete medium was used for the untreated control group.

For the 3D bioprinted constructs, complete medium was supplemented with 20 mM

of CaCl

and drugs at the given concentration range were used to treat the samples. The

constructs cultured in complete medium supplemented with only 20 mM of CaCl

served

as untreated group.

4.4. Cell Viability Assay

Cell viability of the cultures was determined by XTT assays (2,3-Bis-(2-Methoxy-4

-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide, Alfa Aesar, Ward Hill, MA, USA)

that measured metabolization of the tetrazolium salt at various time points following the

treatment. Briefly, a mixture of 50

L XTT reagent (1 mg/mL in RPMI, Biowest, Nuaillé,

France) and phenazine methosulfate (PMS, 3.83 mg/mL in PBS, AppliChem, Darmstadt,

Germany) at a volume ratio of 500:1 was added to each well of a 96-well plate for 2D cell

culture and allowed to incubate for 4 h at 37

◦

C and 5% CO

. The absorbance was measured

at wavelengths of 450 and 620 nm (for reference) using a microplate reader (Sunrise, Tecan,

Int. J. Mol. Sci. 2022,23, 122 15 of 18

Männedorf, Switzerland). For 3D constructs, 150

L of XTT/PMS reagent mixture was

added for 4 h, and the absorbance of the supernatant was measured as mentioned above.

Cell-free constructs were used as a background. The relative cell viability was calculated

by the following formula:

relative cell viability =

Absorbancetest well −Absorbancebackground well

Absorbancecontrol well −Absorbancebackground well

(1)

Afterwards, half maximal inhibitory concentration (IC

) values were calculated based

on the nonlinear regression curves of the dose–response data (dose–response curves) using

GraphPad Prism 8 (GraphPad, La Jolla, CA, USA). All experiments were performed at least

three times.

4.5. Cytotoxicity Assay

To analyze the cell status and cell distribution, a cytotoxicity assay was performed

using a viability/cytotoxicity kit (Thermo Fisher Scientific, Waltham, MA, USA) in ac-

cordance with the manufacturer’s instructions. The 2D cultured cells were incubated in

RPMI without phenol red, which contained 2

M of calcein AM and 2

M of ethidium

homodimer-1 for 10 min, while the 3D constructs were incubated for 30 min. The stained

samples were analyzed by fluorescence microscopy (Observer Z1, Zeiss, Jena, Germany).

The ratio of living and dead cells in 3D printed constructs was also analyzed using the

software ImageJ (1.53e, National Institutes of Health, Bethesda, MD, USA).

4.6. Immunofluorescence Staining

At predetermined time points, samples were washed with PBS and fixed in 4%

formaldehyde (Carl Roth, Karlsruhe, Germany) for 30 (2D) or 60 min (3D) at room tem-

perature. The samples were then permeabilized with 0.1% (v/v) Triton X-100 (Carl Roth,

Karlsruhe, Germany) for 10 (2D) or 30 min (3D), and blocked with 5% goat serum (Sigma-

Aldrich, St. Louis, MO, USA) for 30 (2D) or 60 min (3D), respectively. Afterwards, the

samples were incubated with primary antibodies (anti-human disialoganglioside GD2,

1:400, BD Pharmingen, Franklin Lakes, NJ, USA; Cleaved Caspase-3 antibody, 1:1000, Cell

Signaling, Danvers, MA, USA) at 4

◦

C overnight, washed three times with PBS, and subse-

quently incubated with the respective secondary antibodies (goat anti-mouse Alexa Fluor

594, 1:1000, Invitrogen, Carlsbad, CA, USA; goat anti-rabbit Alexa Fluor 488, 1:1000, Invit-

rogen, Carlsbad, CA, USA) at room temperature for 2 h. Afterwards, samples were again

washed with PBS three times prior to nuclear staining with 1

g/mL of 4

,6-diamidino-

2-phenylindole (DAPI, Sigma–Aldrich, St. Louis, MO, USA) for 60 min. When indicated,

F-actin of cells was labeled with phalloidin (Alexa Fluor

™

488 Phalloidin, 1:400, Invitrogen,

Carlsbad, CA, USA) for 30 min at room temperature. Stained samples were analyzed by

the fluorescence microscopy.

4.7. Statistical Analysis

Results are shown as the means

standard error of the mean from at least three

independent experiments. Statistical analyses were performed using GraphPad Prism 8

software. One-way ANOVA was utilized for analysis of variance to compare between

groups. Statistical significance was accepted at levels of * p< 0.05, ** p< 0.01, *** p< 0.001,

**** p< 0.0001.

5. Conclusions

Taken together, we present a neuroblastoma model that can easily be adapted to other

cancer types as it allows replacing the cancer and surrounding cells with any cell type

of interest. It may also be used to test tumor cells from a specific patient and develop

a personalized treatment strategy. Two main conclusions can be drawn from our study:

Bioprinted tumor models composed of cancerous cells in a non-malignant environment

composed of human cells can be used to differentiate substances with a specific anticancer

Int. J. Mol. Sci. 2022,23, 122 16 of 18

activity from those with general cytotoxic properties, and the sensitivity of cells towards

cytotoxic substances differs substantially in 2D and 3D culture.

Supplementary Materials:

Supplementary materials are available online at https://www.mdpi.

com/article/10.3390/ijms23010122/s1.

Author Contributions:

D.W., J.B., H.E.D. and J.K. conceived and designed the experiments. D.W.,

B.A. and V.R. performed the experiments. J.B., M.A.A.-Z. and J.K. analyzed the data. D.W., J.B. and J.K.

wrote the manuscript. All authors have read and agreed to the published version of

the manuscript.

Funding:

This work was supported by the Chinese Scholarship Council (CSC, fellowship No.

201906780024 to D.W.). Financial support by the “Stiftung zur Förderung der Erforschung von Ersatz-

und Ergänzungsmethoden zur Einschränkung von Tierversuchen” (SET, P-075), the prize money of

the Prize for the Development of Alternatives to Animal Experimentation of the City of Berlin and

the Einstein Foundation Berlin (Einstein Center 3R, EZ-2020-597-2) is gratefully acknowledged.

Acknowledgments:

We are particularly thankful to Erik Wade for careful proofreading of the

manuscript and helpful comments.

Conflicts of Interest: The authors declare no conflict of interest.

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