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R E S E A R C H A R T I C L E Open Access
Tumor slice culture system to assess drug
response of primary breast cancer
Kishan A. T. Naipal
1
, Nicole S. Verkaik
1
, Humberto Sánchez
1
, Carolien H. M. van Deurzen
2
, Michael A. den Bakker
3
,
Jan H.J. Hoeijmakers
1
, Roland Kanaar
1,4
, Maaike P.G. Vreeswijk
5
, Agnes Jager
6
and Dik C. van Gent
1*
Abstract
Background: The high incidence of breast cancer has sparked the development of novel targeted and
personalized therapies. Personalization of cancer treatment requires reliable prediction of chemotherapy responses
in individual patients. Effective selection can prevent unnecessary treatment that would mainly result in the
unwanted side effects of the therapy. This selection can be facilitated by characterization of individual tumors using
robust and specific functional assays, which requires development of powerful ex vivo culture systems and
procedures to analyze the response to treatment.
Methods: We optimized culture methods for primary breast tumor samples that allowed propagation of tissue ex
vivo. We combined several tissue culture strategies, including defined tissue slicing technology, growth medium
optimization and use of a rotating platform to increase nutrient exchange.
Results: We could maintain tissue cultures for at least 7 days without losing tissue morphology, viability or cell
proliferation. We also developed methods to determine the cytotoxic response of individual tumors to the
chemotherapeutic treatment FAC (5-FU, Adriamycin [Doxorubicin] and Cyclophosphamide). Using this tool we
designated tumors as sensitive or resistant and distinguished a clinically proven resistant tumor from other tumors.
Conclusion: This method defines conditions that allow ex vivo testing of individual tumor responses to anti-cancer
drugs and therefore might improve personalization of breast cancer treatment.
Keywords: Breast cancer, Organotypic tumor tissue slices, Tissue culture method, FAC chemotherapy, Ex vivo
sensitivity
Background
Breast cancer (BC) is the most frequently occurring type
of malignancy in women and also the leading cause of
cancer related deaths among women in high-income
countries [1]. BC remains a serious issue in current
healthcare, although diagnostic and therapeutic strat-
egies have improved over the past decades. In addition
to first line chemotherapeutic treatments, targeted ther-
apies for cancers overexpressing the estrogen, progester-
one and Her2 receptor already led to improved patient
survival over the past decade [2]. Nevertheless, a sub-
group of BC patients either does not respond to first line
chemotherapy, or develops resistance. Furthermore, no
tailored therapy is currently available for tumors without
expression of specific receptors. Therefore, improved
personalization strategies for BC treatment are urgently
needed.
The most important goal of personalized medicine is
to dedicate the most appropriate treatment to the indi-
vidual patient. This could lead to a situation where the
percentage of non-responders and the high proportion
of adverse effects of classical chemotherapeutics could
be minimized. The success of this approach depends on
extensive characterization of individual tumors and their
sensitivity to chemotherapy. The majority of preclinical
research for treatment efficacy in BC has been per-
formed using established BC cell lines and mouse
models. These models are usually not generated from
primary BC and resemble only a subset of the diverse
types of tumors observed in primary BC. In addition, BC
* Correspondence: d.vangent@erasmusmc.nl
1
Department of Genetics, Cancer Genomics Netherlands, Erasmus University
Medical Center, PO box 2040, Rotterdam 3000CA, The Netherlands
Full list of author information is available at the end of the article
© 2016 Naipal et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Naipal et al. BMC Cancer (2016) 16:78
DOI 10.1186/s12885-016-2119-2
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
cell lines have been in culture now for decades and have
acquired several changes that could affect their bio-
logical behavior and therefore they do not faithfully re-
flect the tumor of origin [3]. Hence, a short-term
primary culture derived directly from the tumor is ne-
cessary for better characterization and generation of
chemotherapy sensitivity profiles in breast tumors from
patients.
Various strategies have been applied to generate pri-
mary cultures from individual tumors which include: a)
2D culture of dissociated tumor cells, b) 3D spheroid
cultures, c) patient derived mouse xenograft (PDX) cul-
tures and d) organotypic tumor slice cultures [4–7].
These strategies all have their own advantages and limi-
tations depending on the specific research purpose.
Tumor dissociation and 2D cultures are suitable for
certain tumor types only, because not all primary tumors
grow in a monolayer ex vivo and dissociation strategies
are very challenging [8, 9]. Moreover, in 2D, tumor
architecture is completely lost and this method of cul-
turing causes high selection of tumor cells that grow out
[10]. Especially in very heterogeneous cancers, such as
BC, tumor cell selection limits the usefulness of this cul-
ture option for optimal drug response testing.
Primary tumor cells can also be cultivated ex vivo in
3D in a gelatinous protein mixture, mimicking the extra-
cellular matrix. The generation of 3D tumor spheroid
cultures can be applied to more tumor types and tumor
cells can be expanded in great numbers for high
throughput drug testing. The major disadvantage of this
approach is that this expansion of tumor cells takes
months of culturing and is therefore not optimal for
diagnostic purposes [5].
Another method to reliably assess responses to
cytotoxic treatments is the generation of PDX models,.
[11, 12] which are generated by implanting pieces of
fresh human tumor tissue subcutaneously in immune-
deficient mice [7]. However, the successful engraftment
rate of breast tumors is less than 25 % and outgrowth of
the engraftment takes months. Therefore, this method is
not optimal for studying cytotoxic drug responses for
personalized cancer treatment.
The organotypic slice method turns out to be ideal for
the purpose of short-term primary cultures. It can be
applied to most solid tumors and the tissue processing is
relatively fast compared to other methods which demand
much longer waiting times for ex vivo tumor prolifera-
tion [6, 13, 14]. It does not involve selective outgrowth
of tumor cells and short-term assays that could predict
clinical drug responses can be readily performed making
this method in principle ideal for studies on personalized
BC treatment [14–16].
Nevertheless, ex vivo assays for personalized treatment
based on the tumor tissue slice model are delicate
because it is a low throughput assay and methodological
developments are challenging [16]. Moreover, tumor
heterogeneity requires advanced analytical tools to faith-
fully categorize tumor responses to drug treatment, es-
pecially in the case of BC.
We improved on previously reported organotypic
tumor tissue slice methods and optimized it for the ex
vivo culture of primary BC. Using reliable markers of
cell proliferation and cell death we developed a robust
analytical system for breast tumor slices ex vivo. Using
these methods we characterized cytotoxicity responses
of individual breast tumor slices to chemotherapy.
Methods
Collection of tumor tissue
Fresh breast tumor tissue was obtained from BC patients
undergoing mastectomy or breast conserving surgery at
the Erasmus University Medical Center (Erasmus MC),
Havenziekenhuis Rotterdam or Maasstad Hospital Rot-
terdam, The Netherlands. After resection the tissue was
directly transported to the pathology department of the
Erasmus MC. After macroscopic investigation and deter-
mination of tumor areas for diagnostic purposes by a
pathologist, left over tumor tissue was used for research
purposes according
to the code of proper secondary use of human tissue
in the Netherlands established by the Dutch Federation
of Medical Scientific Societies and approved by the local
Medical Ethical committees. No informed consent was
needed for this study, which has been approved by the
Erasmus MC Medical Ethical Committee (number
MEC-2011-098). Research samples were kept at 4 °C
and transported in specific breast medium (Medium I,
Table 1). Specimens were coded anonymously in a way
that they were not traceable to the patient by lab
workers.
Tissue work up, slice preparation and culture
Tumor specimens were subjected to manual and/or au-
tomated tissue slicing. Excess fat tissue was discarded
using surgical tools and tissue slices of approximately
2 mm thickness were manually generated under sterile
conditions. Automated slicing was performed using a
Leica VT 1200S Vibratome with slice thickness set at
300 μm, vibration amplitude at 3.0 mm and slicing speed
at 0.6 mm/sec. Slicing was performed under semi-sterile
conditions; without the use of a flow hood. No contami-
nations were encountered under these conditions. Slices
were cultured within 6 hours after the tumor was re-
moved from the patient. Culturing was performed at 5 %
CO
2
at 37 °C and at atmospheric oxygen levels. Different
culture media were tested for quality assessment. De-
tailed medium compositions are summarized in Table 1.
Where indicated, culture dishes were subjected to
Naipal et al. BMC Cancer (2016) 16:78 Page 2 of 13
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rotation at 60 rpm using a Stuart SSM1 mini orbital
shaker that was placed in the incubator. When indicated,
FAC treatment was started directly after slicing the
tumor with the indicated concentrations in the culture
media. Proliferating cells were labeled using 3 μg/ml
EdU (Invitrogen) during the last 2 hours before fixation.
Also in case of FAC treatment, EdU was added on the
last day during the final 2 hours of incubation. Tumor
slices were fixed in 10 % neutral buffered formalin for at
least 24 hours at room temperature. Subsequently,
tumor slices were embedded in paraffin and 4 μmsec-
tions were generated for microscopy analysis.
Staining protocols
Histological tumor architecture was examined by H&E
staining. For immunostaining paraffin sections were
deparaffinized in xylene and subsequently hydrated by
incubation in decreasing concentrations of ethanol. Tar-
get antigen retrieval for Keratin staining was achieved
using Citric Acid buffer (2.15 mg/ml) pH 6.0 for 18 min
in a microwave at 600 W. Primary antibody anti-
PanCytokeratin (AE1/AE3) (Santa Cruz Biotechnology,
sc-81714, diluted 1/500) was incubated for 90 min at
room temperature and a secondary Alexa Fluor 488
antibody conjugate was used to detect the first antibody.
EdU incorporation was visualized using Click-It
chemistry (Invitrogen) by incubating samples for 30 min
with freshly made Click-It Alexa Fluor 594 cocktail
(manufacturers protocol). Samples were mounted using
Vectashield mounting medium with DAPI and visualized
using a Leica SP5 confocal microscope.
TUNEL assay
TUNEL assay was performed using In Situ Cell Death
Detection Kit (Roche Life Sciences). After deparaffiniza-
tion and hydration, samples were incubated with Prote-
ase K (2 μg/ml) diluted in PBS/ 0.5 % Triton X-100 for
15 min at room temperature. Subsequently, samples
were incubated with kit enzyme mix (manufacturers
protocol) for 60 min at 37 °C in a humidified environ-
ment. After washing with PBS samples were mounted
with DAPI.
Image analysis
From each tumor slice section multiple images were gen-
erated using a Leica SP5 confocal microscope. Image size:
512x512 pixels, pixel size ~0.7 μm. For each image field
two separate channels were used to detect keratin and
EdU signal. Keratin positive area and number of EdU posi-
tive cells were semi-automatically determined using a pre-
viously described MATLAB (Mathworks) algorithm with
minor modifications [17]. In brief, keratin positive areas
were detected by first performing a morphological recon-
struction that filled dark pixels surrounded by lighter
pixels. Then a Sobel edge detection operation with user-
defined threshold was applied. Detected regions are filled
after opening and closing morphological operations and
the number of pixels enclosed in the detected area were
used for computing the keratin positive area. Number of
EdU positive cells was estimated by first converting the
grayscale image in a binary mask with a user-defined
threshold and removing objects smaller than 10 pixels
from the image. Remaining objects were filled by morpho-
logical reconstruction. Finally, the image was eroded with
a flat structuring element and objects with more than
10 pixels counted and expressed as EdU positive cells..
Analysis of TUNEL staining was performed using FIJI
image analysis software. Separate image channels (image
size: 512 x 512 pixels, pixel size ~0.7 μm) for TUNEL and
DAPI were automatically thresholded using the Otsu algo-
rithm. In the Coloc2 FIJI plugin, an analysis for co-
localization was performed using the Manders co-
localization algorithm [18]. Statistical analysis and gener-
ation of graphs was performed using Graphpad Prism 6.0.
Results
Organotypic tissue slice method
The organotypic tissue slice method starts with the gen-
eration of several tissue slices from a fresh tumor speci-
men after surgical resection. We compared manual
slicing, semi-automated slicing (Campden Instruments
Ltd.) and automated tissue slicing (Krumdieck MD4000
and Leica Vibratome VT 1200S) in order to optimize the
processing and timing of the slice procedure and to
maintain tissue morphology during culturing of tumor
samples. Manual slicing (using fine surgical tools) and
Table 1 Overview of medium compositions
Medium I [19] Medium II [20] Medium III Medium IV
- DMEM: HAM's F12 = 2:1
- FCS 2 %
- Hydrocortisone 0.3 μg/ml
- Insulin 4 μg/ml
- Transferrin 4 μg/ml
- 3,3´,5 Triiodothyronine 1 ng/ml
- EGF 8 ng/ml
- Cholera toxin 7 ng/ml
- Adenine 0.2 mg/ml
- Antibiotics
- RPMI-1640
- FCS 10 %
- L-Glutamine 2 nM
- Hydrocortisone 5 μg/ml
- Insulin 5 μg/ml
- Cholera toxin 50 ng/ml
- EGF 10 ng/ml
- Antibiotics
- RPMI-1640
- FCS 10 %
- Antibiotics
- DMEM: HAM's F10 = 1:1
- FCS 10 %
- Antibiotics
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automated tissue slicing using Vibratome VT 1200S
(Leica) demanded less tissue processing than semi-
automated slicing and automated slicing using Krum-
dieck MD4000. As this resulted in shorter processing
times, we focused on manual and Vibratome VT 1200S
mediated tissue slicing.
To investigate whether the vibrating razor blade in-
duced anomalies in tissue morphology, we analyzed gen-
eral morphology and architecture of individual slices by
hematoxilin and eosin (H&E) staining at various times
after slicing. No difference was detected between manual
tissue slicing and Vibratome VT 1200S slicing, indicating
that the vibrating razor blade did not induce additional
artefacts (data not shown).
Optimal tumor slice thickness
We performed a labeling with the Uracil analog 5-
Ethynyl Uridine (EU) to investigate the optimal slice
thickness for good penetration of culture medium nutri-
ents in tumor slices. This compound was chosen be-
cause EU is incorporated into newly transcribed RNA
and transcriptionally active cells are expected to stain
positive after a two-hour labeling period. Cells deprived
from cell culture nutrients are expected to have less
transcription resulting in a lower staining intensity.
Manual slicing resulted in slices of approximately 2 mm
thickness, with a high level of variability between indi-
vidual slices. EU labeling of these slices resulted in a gra-
dient staining pattern limited to 10–20 cell layers
(approximately 150 μm) from the edge of the slice
(Fig. 1a). This indicates that penetration of EU and pre-
sumably also culture medium components was subopti-
mal within a two-hour period.
Automated tissue slicing using Vibratome VT1200 S
resulted in slices of precisely defined thickness. Although
not frequently observed, soft, mucinous and fibrous tu-
mors could not be processed into very thin slices of less
than 500 μm and are therefore less suited for automated
tissue slicing (data not shown). Since EU incorporation
was detected up to 150 μm from both sides of the tissue
sample, we generated standard slices of 300 μm thick-
ness. Indeed, EU labeling of these slices showed optimal
incorporation across the entire slice within a two hour
labeling period (Fig. 1a). Making thinner slices also had
the advantage that more slices could be obtained from
an individual tumor.
Optimal culture medium and culture conditions
To investigate the impact of different culture media on via-
bility of tissue slices we incubated them with four different
culture media that have been reported previously for the in-
cubation of breast tumor slices (Medium I-II [19, 20]) and
two generally used cell culture media (Medium III-IV; see
Table 1). As most classic anti-cancer treatments target
rapidly proliferating cells, optimal drug response testing re-
quires maintenance of proliferation rate during ex vivo cul-
ture. We investigated the maintenance of proliferative
capacity by quantifying EdU (Ethynyl-deoxy Uridine) posi-
tive cells after a two-hour labeling period following a previ-
ous 24-hour incubation in the four culture media. In
manually cut slices we identified low numbers of EdU posi-
tive cells, but incubation in medium I showed clearly more
EdU positive cells compared to other culture media
(Additional file 1: Figure S1A).
Subsequently, we investigated whether culturing under
constant movement on an orbital shaker (60 rpm) could
maintain replicative potential. Without movement, the
slices remained on the bottom of the culture dish during
incubation. However, continuous movement caused
slices to float in the culture medium, which may pro-
mote nutrient exchange between the slice and the
medium (Additional file 1: Figure S1B). Indeed, more
replicating cells could be detected using continuous
movement in all tested media compared to stationary
conditions, with the highest number of EdU positive
cells achieved with medium I (Additional file 1: Figure
S1C). Culture for 48 hours also resulted in more EdU
positive cells in the presence of movement for all culture
media, although a clear decrease in proliferative capacity
was observed compared to samples that were cultured
for two hours (Additional file 2: Figure S2). Similar to
the EU labeling results, EdU labeling of the manually cut
slices showed positively staining cells mainly at the edge
of the tissue over a time course of two hours indicating
that a proper replicative index cannot be determined for
the manually cut tumor slices (Additional file 1: Figure
S1 and Additional file 2: Figure S2).
Automated slicing did not maintain replicative poten-
tial in the absence of movement (Fig. 1b). However, con-
tinuous movement significantly increased the number of
EdU positive cells . Automated slicing even resulted in
similar numbers of EdU positive cells after 2 and
48 hours of culturing (Fig. 1b and Additional file 2: Fig-
ure S2A). The preservation of replicative potential was
detected in all different media, although medium IV
showed a much lower number of EdU positive cells than
the other media (Fig. 1b). A 96-hour incubation under
continuous movement with the four different media re-
sulted in the highest number of EdU positive cells in
medium I (Fig. 1c).
We conclude that continuous movement during incuba-
tion of these tumor slices is absolutely necessary and thin-
ner slices give superior results in case of extended ex vivo
incubations. For prolonged culturing, the optimal medium
composition is medium I. Using these optimized condi-
tions we could preserve tumor cell proliferation in individ-
ual tumor slices ex vivo for at least 7 days after surgical
resection (Fig. 1d). Morphologically, no differences were
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Fig. 1 (See legend on next page.)
Naipal et al. BMC Cancer (2016) 16:78 Page 5 of 13
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noticed in slices that were fixed at day 0 compared to
slices that were fixed at day 7. Also, we did not observe
consistent differences in tumor-stroma ratios after pro-
longed incubations of slices derived from the same tumor
(Additional file 3: Figure S3).
Tissue slice culture method preserves tumor cell
proliferation
Standardized analysis of proliferative capacity for indi-
vidual tumors is difficult to perform due to tumor het-
erogeneity, both between different tumors and within
the same tumor. Tumor-stroma ratios as well as prolifer-
ation rates varied widely within tumor slices (Additional
file 2: Figure S2C, D). Therefore, we developed an image
analysis method that allowed faithful comparison be-
tween different tissue slices and individual tumors. We
analyzed the number of EdU positive cells per Cytokera-
tin positive tumor area (Fig. 2a, b). This approach
allowed characterization of proliferation in tumor spe-
cific areas without being biased by excessive stromal
components or heavy infiltration of lymphoid cells, as
only Cytokeratin positive areas were monitored. Hetero-
geneity in proliferation rate was taken into account by
randomly imaging multiple image fields per slice
(Fig. 2c). This approach revealed that median tissue pro-
liferation rates remained similar after prolonged culture
Fig. 2 Assessment of proliferation in tumor slices by EdU incorporation. aCo-staining for EdU (red), Cytokeratin (green) and DAPI (blue). Scale bar
indicates 100 μm. bScreenshots of semi-automated measurement of Cytokeratin area and number of EdU positive cells using image analysis
software. cExample of tumor proliferation after prolonged culture of tumor slices. Multiple image fields were analyzed per tumor slice.
Heterogeneity in proliferation is visualized in this graphical representation by interquartile ranges. Each black dot represents one image field. Red
bars indicate interquartile range and blue bars represent median values. dProliferation rate of multiple tumors after incubation for up to seven
days. Maximum incubation times varied per tumor depending on availability of tumor slices. Black dots indicate median values and error bars
represent interquartile range
(See figure on previous page.)
Fig. 1 Improvement of organotypic tissue slice viability. aManually sliced tumor slices were incubated for 2 hours in the presence of EU (Ethynyl
Uridine) before fixation. During this time penetration of EU is limited to 10–20 cell layers from the edge of the slice. Automatically sliced (300 μm)
tumor slices display EU incorporation across the entire depth of the slice within a 2-hour labeling period. bConstant orbital movement (60 rpm)
significantly increased the number of EdU positive cells after 48 hours incubation compared to static culture conditions. cEdU incorporation after
96 hours of culturing under constant movement. dProlonged culture of 300 μm tumor slices from one individual tumor using continuous
movement and Medium I. Blue =DAPI, Red =EdU, Green lines indicate the edge of the tumor slice. Scale bars indicate 100 μm
Naipal et al. BMC Cancer (2016) 16:78 Page 6 of 13
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of different tissue slices. However, individual image fields
incidentally showed either relatively low or high num-
bers of EdU positive cells (Fig. 2c). We plotted the inter-
quartile range of EdU positive cells in individual slices
and found that these values did not significantly change
after prolonged culture of tumor slices, suggesting that
the intrinsic proliferative capacity of tumor cells
remained constant over time (Fig. 2c, d). We cultured
several tumors for up to 7 days and found that the ma-
jority of them showed near constant proliferation rates
over this time period (Fig. 2d).
Minimal induction of cell death during prolonged ex vivo
incubation
Depending on in vivo tumor necrosis, tissue transpor-
tation times and duration of processing, individual tu-
mors might already display a certain level of cell
death before being incubated ex vivo. Furthermore,
the cells at the edges of the slices are damaged by
the slicing procedure. This initial amount of cell
death was measured by TUNEL staining after a short
ex vivo incubation and compared to later time points.
Analyzing the fraction of TUNEL positive tumor nu-
clei by automated image analysis software is challen-
ging, because tumor cell nuclei are in very close
proximity in tumor tissue slices, precluding counting
of individual nuclei . Therefore, we counted the num-
ber of DAPI-positive pixels that were also TUNEL
positive in different image fields instead of analyzing
numbers of nuclei (Fig. 3a, b). DAPI intercalates in
the DNA and was regarded as an internal reference
for total numbers of nuclei present. As a positive
control, slices were incubated for 6 days with a high
concentration of the chemotherapeutic drug Cisplatin
(Fig. 3a, b). Some variation in initial cell death was
noticed among different individual tumors. However,
this initial amount of cell death did not increase dras-
tically after prolonged ex vivo incubation (Fig. 3c).
Fig. 3 Induction of cell death after prolonged culture of tumor slices is minimal. aRepresentative images of tumor slices from the same tumor
displayed similar TUNEL staining intensities at 2 hours, 4 days and 6 days of incubation. Tumor slices incubated with high concentrations
(10 μg/ml) of the chemotherapeutic compound Cisplatin revealed massive TUNEL signal. This specific signal was regarded as the positive control
for TUNEL signal. Blue = DAPI, Green = TUNEL. Scale bars represent 100 μm. bQuantification of TUNEL in different tumor slices. TUNEL signal is
variable due to tumor heterogeneity. Each black dot represents one image field. For each image field the percentage of TUNEL-positive DAPI
pixels is given. Error bars indicate interquartile range and blue bars represent median values. cTUNEL signal was determined for multiple tumors
after short and prolonged incubation. Incubation times varied per tumor depending on availability of tumor slices. Black dots indicate median
values. Error bars indicate interquartile range
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Ex vivo treatment of tumor slices with FAC chemotherapy
We investigated whether responses to the chemotherapy
regimen FAC could be detected using our culture system
and analytical methods. Because Cyclophosphamide de-
mands metabolic activation, we used the pre-activated
metabolite 4-HC (4-hydroperoxycyclophosphamide) for
ex vivo experiments. Also, clinically used FAC chemo-
therapeutic drug concentrations and dosing schedules
could not be translated directly into ex vivo treatments
of tumor slices, therefore we performed our experiments
with a single dose in which the slices were incubated for
several days. In all experiments we retained a clinically
used ratio of FAC components: 5-FU 500 mg/m
2
, doxo-
rubicin 50 mg/m
2
, and cyclophosphamide 500 mg/m
2
,
translating to a molar ratio of approximately 5-
FU:Doxorubicin:4-HC = 46:1:22 [21]. To determine opti-
mal dilution (dose) regimens for ex vivo experiments we
tested several concentrations of this combination treat-
ment with dilution #1 being the highest and dilution #10
being the lowest concentration (Table 2).
Cell culture experiments revealed turning points for
cytotoxicity between dilution #5 and #3 after three, four
and five days of continuous exposure to FAC (data not
shown). Hence, at least the negative control and the di-
lutions #7- #2 and incubation for three days were
performed.
Analysis of sensitivity based on tumor morphology
We first investigated whether the response to treatment
was notable based on tumor cell morphology, which was
assessed by H&E staining. The slides were scored for the
presence of aberrant nuclei. Specific nuclear morpholo-
gies that were regarded as a marker of cell death in-
cluded: karyolysis, pyknosis, karyorrhexis and apoptotic
bodies (Fig. 4a). For each individual tumor we deter-
mined at which dilution the aberrant nuclear
morphology appeared. That particular dilution was con-
sidered the threshold for tumor cell death (Fig. 4b). Five
of the 15 tumors showed cell death at dilution #5, seven
at dilution #3 and three at dilution #2. Histopathological
features of these tumors did not correlate with the dif-
ferences observed in drug responses (Table 3).
Analysis of sensitivity based on proliferation rate and cell
death induction
We also analyzed the same 15 tumors for EdU incorpor-
ation and TUNEL staining and detected decrease in pro-
liferation rate and induction of cell death after FAC
treatment in the majority of tumors (Additional file 4:
Figure S4 and Additional file 5: Figure S5). Arbitrarily,
very sensitive tumors were defined as tumors displaying
inhibited proliferation already at dilution #7, whereas re-
sistant tumors where defined as tumors where prolifera-
tion was not inhibited up to dilution #3. Dilution #2 was
found to be highly toxic as proliferation was completely
absent in all tumors (Additional file 4: Figure S4,
Additional file 6: Figure S6A, C). Similarly, cell death
was observed at FAC concentrations as low as dilution
#5 in more sensitive tumors, whereas more resistant tu-
mors only displayed a clear induction of cell death at di-
lution #2 (Additional file 5: Figure S5, Additional file 6:
Figure S6B, D). Comparison of the EdU and TUNEL
measurements revealed that tumors 072 and 102 were
always designated as most resistant regardless of the par-
ameter measured. Also, assessment of sensitivity based
on cell death detected by TUNEL or aberrant nuclear
morphology showed great consistency in tumors (Fig. 5).
Among the 15 tumors there was one tumor derived
from a patient who received neo-adjuvant FEC (5-FU,
Epirubicin, Cyclophosphamide) treatment before surgical
resection. The resected tumor was determined as having
very little signs of treatment response by pathologists
(Miller and Payne grade 2) [22]. In this particular tumor,
cell death assessed by nuclear morphology and TUNEL
assay was not induced until dilution #2 (Fig. 5,
Additional file 6: Figure S6 and Table 3). This tumor also
showed resistance when analyzed for EdU incorporation
(M072, Additional file 6: Figure S6), suggesting that the
ex vivo sensitivity assay can indeed identify resistant
tumors.
Discussion
We optimized the ex vivo culture system to preserve
tumor morphology and tumor cell proliferation, while
minimizing culture induced tumor cell death for up
to seven days. We did not characterize later time
points, but there are no signs of tissue deterioration
after six days, suggesting that extended incubations
may be possible if required for a specific functional
Table 2 Dose concentration of different FAC dilutions
5’FU (46)
a
Doxorubicin (1)
a
4-HC (22)
a
(μM) (μM) (μM)
#1 460 10 220
#2 230 5 110
#3 115 2.5 55
#4 46 1 22
#5 23 0.5 11
#6 11.5 0.25 5.5
#7 4.6 0.1 2.2
#8 2.3 0.05 1.1
#9 1.15 0.025 0.55
#10 0.46 0.01 0.22
#11 0 0 0
a
Indicates the molar concentration ratio for all different dilutions
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assay. We specifically found that the culture of breast
tumor slices is highly dependent on rotational move-
ment during incubation, most probably by increasing
nutrient exchange. Automated tissue slicing also in-
creases ex vivo lifespan of tumor slices, as thinner
slices allow better penetration of nutrients in the ab-
sence of active blood circulation. Finally, composition
of the culture medium is highly important to main-
tain tumor slice viability with sufficient numbers of
replicating cells for several days.
As traditional chemotherapies especially target cells in
S phase or mitosis, tumor cell proliferation should be
maintained during ex vivo culture of tissue slices to in-
vestigate chemotherapy responses. EdU incorporation is
probably the most reliable biomarker for proliferation
because it allows real time measurement of DNA syn-
thesis in very short time intervals compared to other
proliferation markers such as Ki-67, which remains posi-
tive for days after proliferation has ceased [23]. Cyclin A
is a slightly better marker than Ki-67, but it also stains
Fig. 4 Assessment of drug response by aberrant nuclear morphology. aNuclear morphology suggestive for tumor cell death included: Karyolysis:
nuclear fading caused by dissolution of the chromatin, Pyknosis: irreversible condensation of the chromatin causing nuclei to shrink in size,
Karyorrhexis: destructive fragmentation of a pyknotic nucleus, Apoptotic bodies: late stage apoptosis with fragmented nuclei. bAn example of
altered nuclear morphology (black arrows) observed in a single tumor after increasing dilution of FAC treatment. Dilution #3 was the lowest
dilution at which altered nuclear morphology was observed in this tumor. Scale bar represents 50 μm
Table 3 Histo-pathological features of analyzed tumors
Sample Histological subtype Tumor size (cm) B&R grade Mitotic figures (per 2 mm
2
) Receptor status FAC response
ER PR HER2 Morpho-logy EdU TUNEL
059 ductal 3.4 2 9 + - - 5 * 5
068 ductal 1.5 1 2 + + - 3 5 3
070 lobular 4.0 2 2 + + - 5 5 5
071 lobular 5.5 2 1 + + - 5 5 5
072 ductal 11.0 2 2 + + - 2 2 2
083 ductal 6.5 2 2 + + - 5 7 5
089 ductal 3.8 3 16 + + - 3 7 5
090 ductal 3.4 3 13 + - - 2 3 2
102 lobular 7.0 2 7 + + - 2 5 5
112 ductal 3.5 3 15 + + + 3 3 3
118 ductal 1.7 3 12 + + - 3 3 5
119 ductal 7.0 3 26 - - - 5 3 3
121 lobular 9.7 2 6 + + - 3 5 3
135 ductal 5.5 3 16 + + - 3 3 3
141 ductal 2.5 3 8 + - - 3 5 5
B&R = Bloom and Richardson grade, ER = estrogen receptor, PR = progesterone receptor, Her2 = Her2/Neu receptor, FAC response: the dilution at which a
threshold was observed. 1 being the highest FAC concentration and 10 being the lowest. * = data not available
Naipal et al. BMC Cancer (2016) 16:78 Page 9 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
G2 phase cells and would therefore also mark cells that
are blocked at the G2/M checkpoint. In our ex vivo
tumor slice culture system active EdU incorporation is
preserved for up to seven days, which is sufficient to de-
tect most differences in drug response.
As decrease of EdU positive cells may be reversible when
chemotherapy treatment has ended, more unidirectional re-
sponse markers such as induction of cell death are import-
ant to define cytotoxic response to the given treatment.
TUNEL staining is often used as a way of measuring cell
death, although quantitative assessment of TUNEL staining
remains a challenge. Measuring the number of individual
TUNEL positive cells is hardly possible, because of the
proximity of individual nuclei, which frequently even
overlap in thin sections of organotypic BC slices. As an al-
ternative option we determined the number of DAPI pixels
that are TUNEL positive. The major advantage of this ana-
lytical method is that it can be performed automatically in
a standardized high-throughput manner. This method may
not be useful to distinguish subtle increases but it is suitable
to detect major differences in TUNEL signal.
Similar culture methods have been used for ex vivo
breast tumor slices in previous studies [15, 16, 20].
These report that viability and proliferation was retained
for at least four to seven days. However, extensive valid-
ation of culture conditions for multiple tumors where
not performed. Also, comparative analysis of different
culture conditions is lacking from these reports. The
Fig. 5 Analytical methods to asses cell proliferation and cell death in response to FAC treatment. a3D representation of morphologic
examination, EdU incorporation and TUNEL analysis per individual tumor. For every tumor the dilution at which a threshold was observed was
plotted for each analytical method. Most sensitive tumors cluster in the upper most front part of the graph and most resistant tumors cluster at
the lower back side of the 3D graph. Red box represents the resistant tumors based on arbitrary limits. bScatterplots comparing two analytical
methods for therapy response. For every tumor the dilution at which a threshold was observed was plotted for each analytical method. The
resistant tumors based on arbitrary limits are outlined in red
Naipal et al. BMC Cancer (2016) 16:78 Page 10 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
tumor slice studies performed on head and neck, colon
and lung tumors also lack some of the characterizations
that have been performed in this study [6, 13]. Further-
more, the markers used as surrogates for treatment re-
sponse, such as Ki-67, may not be the most adequate
analysis for treatment response. Therefore, we propose
to use EdU incorporation as the most direct and sensi-
tive marker of proliferation in tumor tissue slices.
The responses to FAC treatment in our study were
quantified based on morphologic examination, EdU in-
corporation and TUNEL assay. Interestingly, sensitivity
classification based on the individual analytical methods
did not differ significantly: the two least sensitive tumors
always cluster together (Fig. 5). As morphologic examin-
ation and TUNEL assay both indicate tumor cell death,
one of these methods would probably be sufficient, but
more extensive characterization will be necessary to cor-
roborate this conclusion.
Therapy resistance was arbitrarily defined in our cohort
based on studies performed in BC patients receiving neo-
adjuvant chemotherapy, which report that 10-20 % of pri-
mary breast tumors are resistant to treatment [24–26].
Interestingly, this arbitrarily defined threshold is consist-
ent with the result obtained from one clinically proven
therapy resistant tumor suggesting that our thresholds for
therapy resistance may resemble the clinical outcome.
Actual clinical data regarding the response to FAC
treatment are not yet available for our collected
samples and it is therefore not yet possible to deter-
mine the predictive value of our ex vivo analysis
method. Clinical responses to treatment will be
monitored closely in the future in order to assess
the predictive value of the ex vivo assay. However,
this assessment may take years. Clinical data on the
response to neo-adjuvant FEC treatment was only
availableforthepatienthavingtheleastsensitive
tumor in our analysis.
Ideally, the ex vivo analysis should be done with biop-
sies obtained prior to neo-adjuvant treatment, because
this would enable determination of in vivo response of
the tumor in a relatively short time frame. On the other
hand, tumor heterogeneity may pose additional chal-
lenges to develop tumor biopsy based cytotoxicity assays
into valid predictive tests. Moreover, the currently de-
scribed methodology concerning this assay might not
allow direct implementation of this assay in a clinical
setting. Fresh tumor material is needed, timings are im-
portant and procedures are quite laborious. Therefore,
automatization and high-throughput possibilities should
be explored for this assay.
As this ex vivo assay does not take pharmacokinetics
into account, it can only predict intrinsic sensitivity of
tumor cells to a given treatment. In other words, an ex
vivo resistant tumor is likely to also be resistant in vivo,
but ex vivo sensitivity may not faithfully predict clinical
sensitivity. Therefore, this cytotoxicity assay is primarily
expected to be an effective tool to prevent unnecessary
treatment of patients that harbor a therapy-resistant
tumor, especially in advanced metastatic BC, where re-
sistance to FAC chemotherapy is much more frequently
observed than in primary BC. Similar assays can be de-
veloped to investigate other drugs, e.g. tamoxifen
sensitivity.
Conclusions
This study is the first to show extensive systematic
optimization of breast tumor slices ex vivo by comparing
different slicing techniques and culture conditions. Val-
idation of optimal culture conditions was also systemat-
ically assessed by examining morphology, proliferation
rate and cell death using robust markers. This culture
system allowed detection of differences in tumor re-
sponses to FAC chemotherapy, which was confirmed by
the observation that a clinically proven resistant tumor
was identified in this way. The culture system and
methods to analyze drug responses can be performed
within a relatively short timeframe which makes it an ef-
fective tool to identify therapy-resistant tumors. This
can prevent unnecessary treatment that would otherwise
mostly cause side effects and a more promising treat-
ment option can be started sooner.
Ethics statement
Left over tumor tissue was used for research purposes
according to the code of proper secondary use of human
tissue in the Netherlands established by the Dutch Fed-
eration of Medical Scientific Societies and approved by
the Erasmus MC Medical Ethical Committee (number
MEC-2011-098).
Consent statement
No informed consent was needed for this study. This
was approved by the Erasmus MC Medical Ethical Com-
mittee (number MEC-2011-098).
Additional files
Additional file 1: Figure S1. Title: Analysis of constant movement and
optimal culture medium at 24 hours incubation. Description:
Representative images of different tissue slices from one single tumor
indicating microscopic fields harboring EdU positive cells. A. Manually
sliced (approx. 2 mm) samples were incubated without constant
movement conditions in different culture media. B. Without movement,
the slices statically remained on the bottom of the culture dish during
incubation. However, continuous movement caused slices to dynamically
float in the culture medium which could increase nutrient exchange
between the slice and the medium. C. Constant movement (60 rpm)
significantly increased the number of EdU positive cells after 24 hours
incubation compared to static culture conditions. Incubation in medium
I resulted in the highest number of EdU positive cells compared to
Naipal et al. BMC Cancer (2016) 16:78 Page 11 of 13
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
incubation with medium II, III and IV, in both static and constant
movement conditions. Blue = DAPI, Red = EdU, Green lines indicate the
edge of the tumor slice. (JPG 2671 kb)
Additional file 2: Figure S2. Title: Analysis of constant movement and
optimal culture medium at 48 hours incubation. Description:
Representative images of different tissue slices from one single tumor
indicating microscopic fields harboring the highest number of EdU
positive cells. A. Control slices were directly labeled for two hours with
EdU after slicing during constant movement at 60 rpm. B. Manually
(approx. 2 mm) sliced samples were incubated without movement for
48 hours in different culture media. Very low numbers of EdU positive
cells were present in the samples. Manually (approx. 2 mm) sliced
samples that were incubated under constant movement conditions
(60 rpm) for 48 hours in different culture media displayed higher number
of EdU positive cells. C. Great heterogeneity in tumor stroma ratio was
observed between different slices from the same tumor. D. Within the
same slice also variation of proliferation indicated by EdU incorporation
was noticed. This variation was partly explained by tumor-stroma vari-
ation but also by intrinsic variation in proliferation of tumor cells. (JPG
3683 kb)
Additional file 3: Figure S3. Title: Morphology does not alter after
prolonged incubation for 7 days. Description: Tumor slices from selected
tumors were cultured for 7 days using optimized culture conditions. HE
images represent slices from tumors incubated for indicated days.
Morphologically no differences were noted between slices that were
fixed on day 0 compared to slices fixed on day 7. Also, no differences
were detected in tumor-stroma ratios after prolonged incubations. (JPG
2769 kb)
Additional file 4: Figure S4. Title: Proliferation rate after incubation
with FAC chemotherapy. Description: Tumor slices from each tumor
where incubated with increasing concentrations of FAC. For EdU labeling
samples were incubated with EdU for the last two hours of incubation.
The numbers of EdU positive cells per mm2 keratin positive area where
calculated. Sample M059 was not included in this analysis because no
labeling was performed. Dilutions indicated with an asterisk (*) were
missing because of insufficient tumor material. (JPG 787 kb)
Additional file 5: Figure S5. Title: TUNEL assay after incubation with
FAC chemotherapy. Description: Tumor slices from each tumor where
incubated with increasing concentrations of FAC. TUNEL staining was
performed for each tumor slice. Dilutions indicated with an asterisk (*)
were missing because of insufficient tumor material. (JPG 1881 kb)
Additional file 6: Figure S6. Title: Differences in response to FAC
chemotherapy in breast tumor slices. Description: Tumor slices were
incubated in different increasing concentrations of FAC chemotherapy
(Table 2). A. Tumor samples M072 and M083 display inhibition of
proliferation at different doses of FAC. Proliferation is completely absent
at dose #2. M072 stops proliferating at dose #3 whereas M083 already
stops at dose #7. Blue = DAPI, Red = EdU. B. FAC induced cell death was
detected by TUNEL assay. Massive cell death was induced at dose #2 for
M072 and already at dose #5 for M083. Blue = DAPI, Green = TUNEL. C.
Representation of heterogeneity in multiple analyzed images for
proliferation. Black dots indicate median values of observed numbers of
EdU positive cells per mm2 Cytokeratin area. Error bars indicate the
interquartile range. D. Multiple image fields per tumor slice were
analyzed for TUNEL signal. Black dots represent the median percentage
of TUNEL-positive DAPI pixels. Error bars represent the
interquartile range. (JPG 5390 kb)
Abbreviations
BC: breast cancer; DAPI: 4',6-diamidino-2-phenylindole; EdU: 5-Ethynyl-2'-
deoxyUridine; EU: 5-Ethynyl Uridine; FAC: 5-Fluororacil, Adriamycin,
Cyclophosphamide; H&E: Haematoxilin & Eosin; PDX: patient derived
xenograft; TUNEL: terminal deoxynucleotidyl transferase (dUTP) Nick End
Labeling.
Competing interests
The authors declare that they have no competing interests.
Authors’contribution
KN: Conceived of the study, generated the first draft, performed tissue
slicing, tissue culturing and immunostaining experiments, performed
imaging and image analysis. NS: Conceived of the study, generated the first
draft, performed tissue slicing, tissue culturing and immunostaining
experiments. HS: Performed imaging and image analysis. CvD: Coordinated
protocols for the use of patient specimens and collected tumor specimens
for research. MdB: Coordinated protocols for the use of patient specimens
and collected tumor specimens for research. JH: Acquired funding and
supervised the research group, conceived of the study, generated the first
draft. RK: Acquired funding and supervised the research group, conceived of
the study, generated the first draft. MV: Acquired funding and supervised the
research group, conceived of the study, generated the first draft. AJ:
Acquired funding and supervised the research group, conceived of the
study, generated the first draft, coordinated protocols for the use of patient
specimens and collected tumor specimens for research. DvG: Acquired
funding and supervised the research group, conceived of the study,
generated the first draft. All authors were involved in design of experiments,
analysis and interpretation of data and in revising the manuscript. All authors
read and approved of the final version of the manuscript.
Acknowledgements
The authors thank the entire team of staff members and technicians of the
Pathology departments of the Erasmus MC and Maasstad Ziekenhuis
Rotterdam for support in collecting patient tumor material.
The research leading to these results has received funding from the
European Community's Seventh Framework Programme (FP7/2007-2013)
under grant agreement No. HEALTH-F2-2010-259893 and from the Dutch
Cancer Society (grant EMCR 2008–4045 and a Ride for the Roses Cancer
Research Grant (EMCR 2011–5030)).
Author details
1
Department of Genetics, Cancer Genomics Netherlands, Erasmus University
Medical Center, PO box 2040, Rotterdam 3000CA, The Netherlands.
2
Department of Pathology, Erasmus University Medical Center, PO box 2040,
Rotterdam 3000CA, The Netherlands.
3
Department of Pathology, Maasstad
Hospital, Maasstadweg 21, Rotterdam 3079 DZ, The Netherlands.
4
Department of Radiation Oncology, Erasmus University Medical Center, PO
box 2040, Rotterdam 3000CA, The Netherlands.
5
Department of Human
Genetics, Leiden University Medical Center, P.O. Box 9600, Leiden 2300 RC,
The Netherlands.
6
Department of Medical Oncology, Erasmus University
Medical Center, PO box 2040, Rotterdam 3000CA, The Netherlands.
Received: 10 August 2015 Accepted: 4 February 2016
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