![Mean and standard error (SEM) signal intensities obtained at each time point for each drug and control. All three drug sites had significantly higher PI signal compared to the Control site, indicating drug response (p < 0.001). Both Sunitinib and Paclitaxel had higher signal at 8 h compared to Topotecan [p(sun vs. top) = 0.003; p(pac vs. top) = 0.01], which suggests higher therapeutic response at the delivered drug concentrations.](https://www.researchgate.net/publication/349146264/figure/fig5/AS:11431281210531504@1702051499594/Mean-and-standard-error-SEM-signal-intensities-obtained-at-each-time-point-for-each_Q320.jpg)
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cancers
Article
A Miniaturized Platform for Multiplexed Drug Response
Imaging in Live Tumors
Sharath Bhagavatula 1, * , Devon Thompson 1, Sebastian W. Ahn 1, Kunj Upadhyaya 1, Alex Lammers 1,
Kyle Deans 1, Christine Dominas 1, Benjamin Ferland 2, Veronica Valvo 1, Guigen Liu 1and Oliver Jonas 1, *
Citation: Bhagavatula, S.; Thompson,
D.; Ahn, S.W.; Upadhyaya, K.;
Lammers, A.; Deans, K.; Dominas, C.;
Ferland, B.; Valvo, V.; Liu, G.; et al. A
Miniaturized Platform for
Multiplexed Drug Response Imaging
in Live Tumors. Cancers 2021,13, 653.
https://doi.org/10.3390/
cancers13040653
Academic Editor: Fiona M. Lyng
Received: 7 January 2021
Accepted: 1 February 2021
Published: 6 February 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
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iations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
1
Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis Street, Boston,
MA 02115, USA; devon.thompson96@gmail.com (D.T.); wahn1@bwh.harvard.edu (S.W.A.);
kunj.upadhyaya@gmail.com (K.U.); lammers@bu.edu (A.L.); kyle_deans@dfci.harvard.edu (K.D.);
cdominas@bwh.harvard.edu (C.D.); vvalvo@bwh.harvard.edu (V.V.); gliu19@bwh.harvard.edu (G.L.)
2
Department of Pathology, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis Street, Boston,
MA 02115, USA; bferland@bwh.harvard.edu
*Correspondence: sbhagavatula@bwh.harvard.edu (S.B.); ojonas@bwh.harvard.edu (O.J.)
Simple Summary:
We have developed an implantable microdevice that is placed into a live tumor,
and can directly image how effective various chemotherapy drugs are at inducing cell death, with-
out having to remove or process the tumor tissue. Currently drug optimization is performed by
assessing tumor shrinkage after treating a patient with systemic doses of a chemotherapy agent;
this only evaluates a single treatment at a time and typically takes weeks-months before an optimal
treatment strategy is found (if found at all) for a specific patient. In contrast, using the technology
presented here, a personalized cancer treatment strategy can potentially be optimized and tailored
to a specific patient’s tumor characteristics within several hours, without requiring surgical tissue
removal or prolonged trials of potentially ineffective chemotherapies.
Abstract:
By observing the activity of anti-cancer agents directly in tumors, there is potential to
greatly expand our understanding of drug response and develop more personalized cancer treat-
ments. Implantable microdevices (IMD) have been recently developed to deliver microdoses of
chemotherapeutic agents locally into confined regions of live tumors; the tissue can be subsequently
removed and analyzed to evaluate drug response. This method has the potential to rapidly screen
multiple drugs, but requires surgical tissue removal and only evaluates drug response at a single
timepoint when the tissue is excised. Here, we describe a “lab-in-a-tumor” implantable microdevice
(LIT-IMD) platform to image cell-death drug response within a live tumor, without requiring surgical
resection or tissue processing. The LIT-IMD is inserted into a live tumor and delivers multiple drug
microdoses into spatially discrete locations. In parallel, it locally delivers microdose levels of a
fluorescent cell-death assay, which diffuses into drug-exposed tissues and accumulates at sites of cell
death. An integrated miniaturized fluorescence imaging probe images each region to evaluate drug-
induced cell death. We demonstrate ability to evaluate multi-drug response over 8 h using murine
tumor models and show correlation with gold-standard conventional fluorescence microscopy and
histopathology. This is the first demonstration of a fully integrated platform for evaluating multiple
chemotherapy responses in situ. This approach could enable a more complete understanding of drug
activity in live tumors, and could expand the utility of drug-response measurements to a wide range
of settings where surgery is not feasible.
Keywords: personalized oncology; miniaturized optical imaging; drug screening
1. Introduction
Understanding the effect of anti-cancer drugs on the tumor and its microenvironment
is central to the design of effective single agent and combination regimens. Currently avail-
able measures of drug response, such as tumor shrinkage, often take weeks to months
Cancers 2021,13, 653. https://doi.org/10.3390/cancers13040653 https://www.mdpi.com/journal/cancers
Cancers 2021,13, 653 2 of 14
to manifest and are not always representative of a tumor’s dynamic sensitivities [
1
,
2
].
An implantable microdevice (IMD) has been developed which could enable a clinician to
screen the efficacy of multiple drugs or drug combinations for a specific tumor in a specific
patient [
3
]. The IMD is implanted into a live tumor and delivers microdoses of drugs into
tiny spatially discrete tissue volumes. After allowing the drug to interact with the tumor
in its native microenvironment, the IMD and surrounding tissue are surgically removed,
processed (e.g., formalin-fixed, paraffin embedded, sectioned, stained), and imaged using
benchtop microscopy to evaluate cell death response. This method has been shown to pre-
dict and optimize cancer treatments in numerous preclinical models [
3
–
5
] and is currently
undergoing clinical investigation in several first-in-human studies [
6
,
7
]. One limitation of
this approach is that it requires surgical removal of tissue to allow quantification of cell
death caused by each drug. This can be difficult or impractical for many patients unless
they are already planned for cytoreductive surgery. In addition, this analysis only evaluates
tissue response at a single timepoint; delayed or serial assessment is not feasible once the
tissue is surgically removed.
An alternative approach is to image drug response directly in live tumors (in situ)
without requiring surgical removal or tissue processing. Recent advances in fluorescence
microscopy tools have enabled imaging of biological processes via miniaturized imaging
probes placed directly into native tissues [
8
–
10
]. In addition, fluorescent assays are capable
of detecting cell death and other physiologic processes within viable cell samples without
the need for extensive tissue processing [
11
–
14
]. For example, propidium iodide (PI)
is a fluorescent marker that is a well-established and accepted method to evaluate cell
death [
15
,
16
]. PI binds double stranded DNA, but can only enter cells that have disrupted
cell membranes; therefore, it accumulates in late apoptotic and necrotic cells that have
lost membrane integrity. There is potential for implantable microdevices, miniaturized
imaging probes, and live cell assay technologies to be combined to create ‘lab-in-a-tumor’
systems capable of in situ drug response assessment. Such systems can be used in pre-
clinical settings to monitor dynamic responses to novel treatment candidates in native
microenvironments, or potentially translated to a clinical setting to identify the most
effective drug treatments for a specific patient’s tumor.
Here, we describe the first implementation of such a system. Our “lab-in-a-tumor”
implantable microdevice (LIT-IMD) is placed into a tumor and locally delivers microdoses
of multiple drugs, along with a local microdose of PI (Figure 1). The PI preferentially accu-
mulates in non-viable tissues, resulting in strong fluorescent signal at the sites where drugs
have effectively killed tumor tissue. A miniaturized fluorescence imaging probe is passed
coaxially into the LIT-IMD, and determines the fluorescent signal from each drug exposed
tissue region, resulting in a visual ‘readout’ of relative drug efficacy. We demonstrate
proof-of-concept of this method to image the response to three commonly used United
States Food and Drug Administration (FDA)-approved anti-cancer drugs in live murine
tumors. This approach could enable serial assessment of drug diffusion and cell death
response over time, without requiring tissue removal and processing. It also serves as a
proof-of-concept of in situ fluorescence microscopy with local assay delivery, with potential
for broad pre-clinical and clinical application.
Cancers 2021,13, 653 3 of 14
Cancers 2021, 13, x FOR PEER REVIEW 3 of 14
Figure 1. Schematic (top left) and actual image (top center and top right) of the lab-in-tumor implantable microdevice
(LIT-IMD) containing multiple reservoirs for drug and assay release and a hollow inner lumen with optical window face.
Bottom row demonstrates overall functionality: 1—LIT-IMD is implanted into a live tumor; 2—LIT-IMD releases multiple
drugs into discrete confined tumoral tissue and in parallel, releases fluorescent cell death assay into drug-exposed tissue;
3—fluorescence imaging probe is passed coaxially into the LIT-IMD for real-time evaluation of drug diffusion and cell
death response; 4—correlation was performed to validate this method by removing and sectioning tissue at each drug-
exposed site and comparing in situ fluorescence imaging signal with conventional benchtop fluorescence microscopy and
immunohistochemistry of processed tissue sections.
2. Results
2.1. Design and Development of the LIT-IMD Probe
The LIT-IMD prototype is illustrated in Figure 1. It is a 7.5 mm long, 1.45 mm diam-
eter cylinder with a 0.8 mm hollow inner lumen and a tapered conical distal end. A 5 mm
long, 600 μm wide clear rectangular slot is incorporated into one side of the microdevice
body, and serves as an optical window through which images of adjacent tissue can be
acquired.
In total, three 200 μm diameter, 200 μm deep drug release reservoirs, or ‘micro-holes’,
are machined into one wall of the LIT-IMD immediately adjacent to the optical window.
These drug reservoirs are spaced 1.1 mm apart along the length of the LIT-IMD. Drug
formulations are loaded into these reservoirs in solid powder form as described in Meth-
ods and are passively released into spatially distinct microscopic regions of tissue after
tumor implantation. The reservoir dimensions and spacing and are optimized based on
prior studies evaluating drug diffusion [3,4,17], with sufficient separation to ensure that
there is no spatial overlap between drug release sites.
Additionally, four additional reservoirs are placed in parallel on the other side of the
optical window, 1.1 mm apart and with 550 μm longitudinal offset from the reservoirs on
the drug release side. These four reservoirs are for propidium iodide (PI) assay loading
and release, with spacing optimized to allow equal assay diffusion into each drug release
site. Both the drug and assay release reservoirs are angled inward 45 degrees such that
they diffuse into tissue directly in front of the optical window. Therefore, a coaxially
placed side-viewing imaging probe imaging in a radially outward direction can evaluate
fluorescence signal within drug-exposed tissue.
2.2. Miniaturized 2-Color Fluorescence Microscopy (M-2CFM) System Development
2.2.1. Customization and Set-up
A miniaturized 2-color fluorescence microscopy (M-2CFM) system (Doric Lenses
Inc., Quebec, CA, Canada) was customized to interface with the microdevice to image live
tumoral tissue (Figure 2). The system detects fluorescent signals in the red (630 nm wave-
length) and green (530 nm wavelength) channels. Fluorescence imaging is performed via
Figure 1.
Schematic (top left) and actual image (top center and top right) of the lab-in-tumor implantable microdevice
(LIT-IMD) containing multiple reservoirs for drug and assay release and a hollow inner lumen with optical window
face. Bottom row demonstrates overall functionality: 1—LIT-IMD is implanted into a live tumor; 2—LIT-IMD releases
multiple drugs into discrete confined tumoral tissue and in parallel, releases fluorescent cell death assay into drug-exposed
tissue; 3—fluorescence imaging probe is passed coaxially into the LIT-IMD for real-time evaluation of drug diffusion and
cell death response; 4—correlation was performed to validate this method by removing and sectioning tissue at each
drug-exposed site and comparing in situ fluorescence imaging signal with conventional benchtop fluorescence microscopy
and immunohistochemistry of processed tissue sections.
2. Results
2.1. Design and Development of the LIT-IMD Probe
The LIT-IMD prototype is illustrated in Figure 1. It is a 7.5 mm long, 1.45 mm diameter
cylinder with a 0.8 mm hollow inner lumen and a tapered conical distal end. A 5 mm long,
600
µ
m wide clear rectangular slot is incorporated into one side of the microdevice body,
and serves as an optical window through which images of adjacent tissue can be acquired.
In total, three 200
µ
m diameter, 200
µ
m deep drug release reservoirs, or ‘micro-
holes’, are machined into one wall of the LIT-IMD immediately adjacent to the optical
window. These drug reservoirs are spaced 1.1 mm apart along the length of the LIT-IMD.
Drug formulations are loaded into these reservoirs in solid powder form as described in
Methods and are passively released into spatially distinct microscopic regions of tissue
after tumor implantation. The reservoir dimensions and spacing and are optimized based
on prior studies evaluating drug diffusion [
3
,
4
,
17
], with sufficient separation to ensure that
there is no spatial overlap between drug release sites.
Additionally, four additional reservoirs are placed in parallel on the other side of the
optical window, 1.1 mm apart and with 550 µm longitudinal offset from the reservoirs on
the drug release side. These four reservoirs are for propidium iodide (PI) assay loading
and release, with spacing optimized to allow equal assay diffusion into each drug release
site. Both the drug and assay release reservoirs are angled inward 45 degrees such that
they diffuse into tissue directly in front of the optical window. Therefore, a coaxially
placed side-viewing imaging probe imaging in a radially outward direction can evaluate
fluorescence signal within drug-exposed tissue.
2.2. Miniaturized 2-Color Fluorescence Microscopy (M-2CFM) System Development
2.2.1. Customization and Set-up
A miniaturized 2-color fluorescence microscopy (M-2CFM) system (Doric Lenses
Inc., Quebec, CA, Canada) was customized to interface with the microdevice to image
live tumoral tissue (Figure 2). The system detects fluorescent signals in the red (630 nm
wavelength) and green (530 nm wavelength) channels. Fluorescence imaging is performed
Cancers 2021,13, 653 4 of 14
via an optical fiber coupled to a custom miniaturized 700-
µ
m diameter side-viewing
imaging probe, which can be passed coaxially within the LIT-IMD to image tissue next to
the microdevice. Further details for customization of this imaging system can be found in
the Methods section.
Cancers 2021, 13, x FOR PEER REVIEW 4 of 14
an optical fiber coupled to a custom miniaturized 700-μm diameter side-viewing imaging
probe, which can be passed coaxially within the LIT-IMD to image tissue next to the mi-
crodevice. Further details for customization of this imaging system can be found in the
Methods section.
Figure 2. (a) Experimental set-up for live tissue fluorescence imaging. An optical fiber (i) delivers
light excitation through a gradient index (GRIN) lens imaging probe (ii) into a tissue sample (not
shown). The resultant fluorescent signal is captured by an external charge-coupled device (CCD)
optical detector (iv) for 2-color fluorescence imaging. 4-axis (x, y, z linear and rotational) stage
system (v) allows precise positioning of the imaging probe within the tissue sample. (b) GRIN lens
imaging probe tip with triangular prism for side-viewing. (c) Imaging probe is placed through the
microdevice into live murine tumoral tissue to image fluorescent drug and assay signal.
2.2.2. Imaging System Characterization
Performance of the customized M-2CFM imaging system was evaluated using a 10-
μm thick tissue section containing fluorescently stained macrophage cells (Figure 3). The
optimal working distance of the M-2CFM system was 200 μm and the field of view was
~400 × 400 μm. The in-focus resolution was sufficient to detect individual cells as small as
10 um in diameter, based on correlation with a benchtop fluorescence microscope system
(Figure 3b,c). Fluorescent signal remained visible at up to 300 μm distance from the probe.
Therefore, in bulk tissues, the received images represent an accumulated effect of fluores-
cent signal excited within a depth of ~300 μm of the probe.
Figure 3. (a) Miniaturized 2-color fluorescence microscopy (M-2CFM) of stained tissue sections
placed on a slide (1) using a side-imaging GRIN lens probe (2). (b) M-2CFM of red-fluorescent
labeled macrophages. (c) Corresponding benchtop fluorescence image of the same slide used to
quantify M-2CFM imaging capabilities. In-plane resolution was sufficient to view individual 10
μm diameter cells, and overall field of view was ~400 × 400 μm.
Although the imaging system had high in-plane resolution capable of detecting indi-
vidual cells on a microscope slide, high resolution distinction of individual cells or tissue
structure in bulk tumor tissue was not possible, likely due to the lack of ‘optical sectioning’
Figure 2.
(
a
) Experimental set-up for live tissue fluorescence imaging. An optical fiber (i) delivers light
excitation through a gradient index (GRIN) lens imaging probe (ii) into a tissue sample (not shown).
The resultant fluorescent signal is captured by an external charge-coupled device (CCD) optical
detector (iv) for 2-color fluorescence imaging. 4-axis (x, y, z linear and rotational) stage system (v)
allows precise positioning of the imaging probe within the tissue sample. (
b
) GRIN lens imaging
probe tip with triangular prism for side-viewing. (
c
) Imaging probe is placed through the microdevice
into live murine tumoral tissue to image fluorescent drug and assay signal.
2.2.2. Imaging System Characterization
Performance of the customized M-2CFM imaging system was evaluated using a
10-
µ
m thick tissue section containing fluorescently stained macrophage cells (Figure 3).
The optimal working distance of the M-2CFM system was 200
µ
m and the field of view
was ~400
×
400
µ
m. The in-focus resolution was sufficient to detect individual cells as
small as 10 um in diameter, based on correlation with a benchtop fluorescence microscope
system (Figure 3b,c). Fluorescent signal remained visible at up to 300
µ
m distance from the
probe. Therefore, in bulk tissues, the received images represent an accumulated effect of
fluorescent signal excited within a depth of ~300 µm of the probe.
Cancers 2021, 13, x FOR PEER REVIEW 4 of 14
an optical fiber coupled to a custom miniaturized 700-μm diameter side-viewing imaging
probe, which can be passed coaxially within the LIT-IMD to image tissue next to the mi-
crodevice. Further details for customization of this imaging system can be found in the
Methods section.
Figure 2. (a) Experimental set-up for live tissue fluorescence imaging. An optical fiber (i) delivers
light excitation through a gradient index (GRIN) lens imaging probe (ii) into a tissue sample (not
shown). The resultant fluorescent signal is captured by an external charge-coupled device (CCD)
optical detector (iv) for 2-color fluorescence imaging. 4-axis (x, y, z linear and rotational) stage
system (v) allows precise positioning of the imaging probe within the tissue sample. (b) GRIN lens
imaging probe tip with triangular prism for side-viewing. (c) Imaging probe is placed through the
microdevice into live murine tumoral tissue to image fluorescent drug and assay signal.
2.2.2. Imaging System Characterization
Performance of the customized M-2CFM imaging system was evaluated using a 10-
μm thick tissue section containing fluorescently stained macrophage cells (Figure 3). The
optimal working distance of the M-2CFM system was 200 μm and the field of view was
~400 × 400 μm. The in-focus resolution was sufficient to detect individual cells as small as
10 um in diameter, based on correlation with a benchtop fluorescence microscope system
(Figure 3b,c). Fluorescent signal remained visible at up to 300 μm distance from the probe.
Therefore, in bulk tissues, the received images represent an accumulated effect of fluores-
cent signal excited within a depth of ~300 μm of the probe.
Figure 3. (a) Miniaturized 2-color fluorescence microscopy (M-2CFM) of stained tissue sections
placed on a slide (1) using a side-imaging GRIN lens probe (2). (b) M-2CFM of red-fluorescent
labeled macrophages. (c) Corresponding benchtop fluorescence image of the same slide used to
quantify M-2CFM imaging capabilities. In-plane resolution was sufficient to view individual 10
μm diameter cells, and overall field of view was ~400 × 400 μm.
Although the imaging system had high in-plane resolution capable of detecting indi-
vidual cells on a microscope slide, high resolution distinction of individual cells or tissue
structure in bulk tumor tissue was not possible, likely due to the lack of ‘optical sectioning’
Figure 3.
(
a
) Miniaturized 2-color fluorescence microscopy (M-2CFM) of stained tissue sections
placed on a slide (1) using a side-imaging GRIN lens probe (2). (
b
) M-2CFM of red-fluorescent labeled
macrophages. (
c
) Corresponding benchtop fluorescence image of the same slide used to quantify
M-2CFM imaging capabilities. In-plane resolution was sufficient to view individual 10
µ
m diameter
cells, and overall field of view was ~400 ×400 µm.
Cancers 2021,13, 653 5 of 14
Although the imaging system had high in-plane resolution capable of detecting indi-
vidual cells on a microscope slide, high resolution distinction of individual cells or tissue
structure in bulk tumor tissue was not possible, likely due to the lack of ‘optical section-
ing’ (limiting the optical input to a single plane at the optimal focal distance). Therefore,
in situ bulk tumor tissue images were composites of overlapping fluorescent signal from
multiple tissue planes, resulting in ‘blurred’ images representing total fluorescence within
a 3-dimensional ~400
×
400
×
300
µ
m drug-exposed volume of tissue to the side of the
imaging probe (Figure 4).
Cancers 2021, 13, x FOR PEER REVIEW 5 of 14
(limiting the optical input to a single plane at the optimal focal distance). Therefore, in situ
bulk tumor tissue images were composites of overlapping fluorescent signal from multi-
ple tissue planes, resulting in ‘blurred’ images representing total fluorescence within a 3-
dimensional ~400 × 400 × 300 μm drug-exposed volume of tissue to the side of the imaging
probe (Figure 4).
Figure 4. Miniaturized 2-color microscopy (M-2CFM) over 8 h in a live murine MC38 tumor. (a).
Microdevice drug and assay loading diagram. The three distinct drug release sites spaced 1.1 mm
apart contain Paclitaxel (n = 5), Sunitinib (n = 3) or Topotecan (n = 2), and Control (inert polyeth-
ylene glycol, PEG) (n = 5). Propidium iodide (PI) assay is loaded and released from four reservoirs
located on the opposite side of the microdevice optical window. PI diffuses equally into all drug-
exposed tissue regions (dotted boxes), which can be individually imaged. (b). M-2CFM fluorescent
imaging of each drug-exposed tissue region in red (assay) and green (drug) channels over 8 h.
2.3. Drug Response Assessment Proof-of-Concept in Murine Tumor Model
2.3.1. Serial Miniaturized 2-Color Fluorescence Microscopy (M-2CFM) of Drug Diffusion
and Response
In total, five LIT-IMDs, each preloaded with three drugs and PI assay as shown in
Figure 4a, were placed into five separate murine MC38 subcutaneous tumors. The drugs
were reconstituted with polyethylene glycol (PEG) and loaded in a solid-powder form.
The drug formulation was selected in a manner that has been previously shown to contain
local drug diffusion to within 100–400 μm radially of the drug release sites, and has been
shown to approximate systemic dosing at these depths (see Methods) [3–5,17]. Specific
drug responses to three chemotherapy agents could be tested in each tumor, since each
device had three unique drug release sites. A total of five tumors containing fifteen unique
drug release sites were evaluated in total. In three of the tumors, we evaluated response
to Paclitaxel, Sunitinib, and Control (inert PEG) agents. In two of the tumors, we evaluated
response to Paclitaxel, Topotecan, and Control.
Since our method did not require tissue sectioning or processing, we were able to
assess drug diffusion and response serially over time. We monitored drug diffusion in the
green channel for Sunitinib and Topotecan, which are intrinsically fluorescent. As ex-
pected, both drugs remained spatially confined to less than 500 μm of the drug release
sites at 8 h in all tumors. Importantly, there was no spatial overlap of drugs into adjacent
drug release sites.
We serially imaged PI accumulation in the red channel to compare cell death drug
response over time at each of the drug-exposed tissue sites (Figure 4). As described above,
the measured signal represented overall PI accumulation within an ~400 × 400 × 300 μm
volume of drug exposed tissue at each drug release site. Although evaluation of PI uptake
Figure 4.
Miniaturized 2-color microscopy (M-2CFM) over 8 h in a live murine MC38 tumor. (
a
). Mi-
crodevice drug and assay loading diagram. The three distinct drug release sites spaced 1.1 mm apart
contain Paclitaxel (n= 5), Sunitinib (
n= 3
) or Topotecan (n= 2), and Control (inert polyethylene
glycol, PEG) (n= 5). Propidium iodide (PI) assay is loaded and released from four reservoirs located
on the opposite side of the microdevice optical window. PI diffuses equally into all drug-exposed
tissue regions (dotted boxes), which can be individually imaged. (
b
). M-2CFM fluorescent imaging
of each drug-exposed tissue region in red (assay) and green (drug) channels over 8 h.
2.3. Drug Response Assessment Proof-of-Concept in Murine Tumor Model
2.3.1. Serial Miniaturized 2-Color Fluorescence Microscopy (M-2CFM) of Drug Diffusion
and Response
In total, five LIT-IMDs, each preloaded with three drugs and PI assay as shown in
Figure 4a, were placed into five separate murine MC38 subcutaneous tumors. The drugs
were reconstituted with polyethylene glycol (PEG) and loaded in a solid-powder form.
The drug formulation was selected in a manner that has been previously shown to contain
local drug diffusion to within 100–400
µ
m radially of the drug release sites, and has been
shown to approximate systemic dosing at these depths (see Methods) [
3
–
5
,
17
]. Specific drug
responses to three chemotherapy agents could be tested in each tumor, since each device
had three unique drug release sites. A total of five tumors containing fifteen unique drug
release sites were evaluated in total. In three of the tumors, we evaluated response to
Paclitaxel, Sunitinib, and Control (inert PEG) agents. In two of the tumors, we evaluated
response to Paclitaxel, Topotecan, and Control.
Since our method did not require tissue sectioning or processing, we were able to
assess drug diffusion and response serially over time. We monitored drug diffusion in the
green channel for Sunitinib and Topotecan, which are intrinsically fluorescent. As expected,
both drugs remained spatially confined to less than 500
µ
m of the drug release sites at
8 h in all tumors. Importantly, there was no spatial overlap of drugs into adjacent drug
release sites.
Cancers 2021,13, 653 6 of 14
We serially imaged PI accumulation in the red channel to compare cell death drug
response over time at each of the drug-exposed tissue sites (Figure 4). As described above,
the measured signal represented overall PI accumulation within an
~400 ×400 ×300 µm
volume of drug exposed tissue at each drug release site. Although evaluation of PI
uptake within individual cells was not possible with this imaging system, the cumulative
fluorescent signal at each site provided an overall assessment of cell death within each
volume of drug-exposed tissue.
Summary data from serial assessment in 5 replicate tumors and 15 drug sites is
presented in Figure 5and Table 1. There was significant PI signal increase at Paclitaxel and
Sunitinib drug sites over time (ANOVA F(3, 10) = 34.0, p< 0.001 for Paclitaxel and F(3, 5)
= 27.3, p= 0.002 for Sunitinib), with PI signal saturation at 8 h indicating very high assay
accumulation and cell death at both drug sites. PI signal at Topotecan and Control sites
increased over time but did not reach significance (F(3, 4) = 3.44, p= 0.13 for Topotecan;
F(3, 10) = 0.23, p= 0.87 for Control). None of the drug sites were significantly higher than
Control at 1 h, but all were higher than control by 8 h (see Table 1for mean intensity and
p-values values). There were no significant differences in signal intensity in comparing
Paclitaxel vs. Sunitinib (p= 0.53 at 8 h); however, both Paclitaxel and Sunitinib had higher
signal intensity compared to Topotecan (p(Paclitaxel vs. Topotecan) = 0.01; p(Sunitinib vs.
Topotecan) = 0.003).
These findings overall indicate a higher efficacy to induce tumor cell death of Suni-
tinib and Paclitaxel in the tested MC38 tumors compared to Topotecan, and as expected,
higher tumor cell death for all tested chemotherapeutic agents compared to Control.
The baseline PI signal at the Control site is likely from passive PI diffusion and physi-
ologic tumoral cell death; the additional signal at the drug sites compared to control likely
indicate PI accumulation from drug-induced cell death. These results were confirmed by
correlating with gold standard ex vivo analysis as described below.
Cancers 2021, 13, x FOR PEER REVIEW 6 of 14
within individual cells was not possible with this imaging system, the cumulative fluo-
rescent signal at each site provided an overall assessment of cell death within each volume
of drug-exposed tissue.
Summary data from serial assessment in 5 replicate tumors and 15 drug sites is pre-
sented in Figure 5 and Table 1. There was significant PI signal increase at Paclitaxel and
Sunitinib drug sites over time (ANOVA F(3, 10) = 34.0, p < 0.001 for Paclitaxel and F(3, 5)
= 27.3, p = 0.002 for Sunitinib), with PI signal saturation at 8 h indicating very high assay
accumulation and cell death at both drug sites. PI signal at Topotecan and Control sites
increased over time but did not reach significance (F(3, 4) = 3.44, p = 0.13 for Topotecan;
F(3, 10) = 0.23, p = 0.87 for Control). None of the drug sites were significantly higher than
Control at 1 h, but all were higher than control by 8 h (see Table 1 for mean intensity and
p-values values). There were no significant differences in signal intensity in comparing
Paclitaxel vs. Sunitinib (p = 0.53 at 8 h); however, both Paclitaxel and Sunitinib had higher
signal intensity compared to Topotecan (p(Paclitaxel vs. Topotecan) = 0.01; p(Sunitinib vs.
Topotecan) = 0.003).
Figure 5. Mean and standard error (SEM) signal intensities obtained at each time point for each
drug and control. All three drug sites had significantly higher PI signal compared to the Control
site, indicating drug response (p < 0.001). Both Sunitinib and Paclitaxel had higher signal at 8 h
compared to Topotecan [p(sun vs. top) = 0.003; p(pac vs. top) = 0.01], which suggests higher thera-
peutic response at the delivered drug concentrations.
Control Topotecan
(p-Value)
Paclitaxel
(p-Value)
Sunitinib
(p-Value)
1 h 170.9 ± 44 261.9 ± 81.3
(0.24)
293.8 ± 27.0
(0.063)
217.3 ± 27.9
(0.70)
2 h 191.7 ± 61.1 294.6 ± 37.7
(0.67)
507.0 ± 111.6
(0.028)
409.35 ± 149.6
(0.16)
4 h 191.5 ± 63.9 398.1 ± 94.5
(0.13)
645.4 ± 78.2
(0.0026)
761.2 ± 121.8
(0.0014)
8 h 210.1 ± 92.3 556.6 ± 154.6
(<0.001)
802.9 ± 55.1
(<0.001)
877.9 ± 28.9
(<0.001)
Table 1. Miniature 2-color microscopy (M-2CFM) of propidium iodide (PI) at drug and control
sites. Mean and standard error of the mean (SEM) are reported in arbitrary signal intensity units (aiu)
Figure 5.
Mean and standard error (SEM) signal intensities obtained at each time point for each
drug and control. All three drug sites had significantly higher PI signal compared to the Control site,
indicating drug response (p< 0.001). Both Sunitinib and Paclitaxel had higher signal at 8 h compared
to Topotecan [p(sun vs. top) = 0.003; p(pac vs. top) = 0.01], which suggests higher therapeutic
response at the delivered drug concentrations.
Cancers 2021,13, 653 7 of 14
Table 1.
Miniature 2-color microscopy (M-2CFM) of propidium iodide (PI) at drug and control sites. Mean and standard error of
the mean (SEM) are reported in arbitrary signal intensity units (aiu) obtained at each time point for each drug/control site. p-values
indicate comparison between signal intensities at each drug site compared to Control (p< 0.05 was used as a measure of significance).
Control Topotecan
(p-Value)
Paclitaxel
(p-Value)
Sunitinib
(p-Value)
1 h 170.9 ±44 261.9 ±81.3
(0.24)
293.8 ±27.0
(0.063)
217.3 ±27.9
(0.70)
2 h 191.7 ±61.1 294.6 ±37.7
(0.67)
507.0 ±111.6
(0.028)
409.35 ±149.6
(0.16)
4 h 191.5 ±63.9 398.1 ±94.5
(0.13)
645.4 ±78.2
(0.0026)
761.2 ±121.8
(0.0014)
8 h 210.1 ±92.3 556.6 ±154.6
(<0.001)
802.9 ±55.1
(<0.001)
877.9 ±28.9
(<0.001)
2.3.2. Correlation with Gold-Standard Cell Death Assessment Methods
Current gold-standard methods to evaluate cell death include conventional benchtop
fluorescence imaging of propidium iodide and immunohistochemistry (IHC) analysis. IMD-
based drug screening using IHC cell death quantification of resected drug-exposed tumor
samples has been previously shown to be predictive of systemic response [
3
]. Therefore,
if our live tumor imaging approach correlates strongly with IHC-based assessment of cell
death, this would indicate that it can be used for IMD-based drug screening in lieu of IHC.
Correlation with benchtop fluorescence imaging and IHC was performed in 15 distinct
replicate drug-exposed tissue regions (methodology illustrated in Figure 6and further
described in Methods). We observed a strong correlation with both benchtop fluorescence
microscopy (Pearson r = 0.96, p< 0.001) and immunohistochemistry (Pearson r = 0.88,
p< 0.001
) (Figure 7). The in situ fluorescence signal measured within each drug-exposed
tissue volume increased linearly with the overall percent of non-viable tissue within that
same region as assessed by IHC (Figure 7).
Cancers 2021, 13, x FOR PEER REVIEW 7 of 14
obtained at each time point for each drug/control site. p-values indicate comparison between signal
intensities at each drug site compared to Control (p < 0.05 was used as a measure of significance).
These findings overall indicate a higher efficacy to induce tumor cell death of
Sunitinib and Paclitaxel in the tested MC38 tumors compared to Topotecan, and as ex-
pected, higher tumor cell death for all tested chemotherapeutic agents compared to Con-
trol. The baseline PI signal at the Control site is likely from passive PI diffusion and phys-
iologic tumoral cell death; the additional signal at the drug sites compared to control likely
indicate PI accumulation from drug-induced cell death. These results were confirmed by
correlating with gold standard ex vivo analysis as described below.
2.3.2. Correlation with Gold-Standard Cell Death Assessment Methods
Current gold-standard methods to evaluate cell death include conventional benchtop
fluorescence imaging of propidium iodide and immunohistochemistry (IHC) analysis.
IMD-based drug screening using IHC cell death quantification of resected drug-exposed
tumor samples has been previously shown to be predictive of systemic response [3].
Therefore, if our live tumor imaging approach correlates strongly with IHC-based assess-
ment of cell death, this would indicate that it can be used for IMD-based drug screening
in lieu of IHC. Correlation with benchtop fluorescence imaging and IHC was performed
in 15 distinct replicate drug-exposed tissue regions (methodology illustrated in Figure 6
and further described in Methods). We observed a strong correlation with both benchtop
fluorescence microscopy (Pearson r = 0.96, p < 0.001) and immunohistochemistry (Pearson
r = 0.88, p < 0.001) (Figure 7). The in situ fluorescence signal measured within each drug-
exposed tissue volume increased linearly with the overall percent of non-viable tissue
within that same region as assessed by IHC (Figure 7).
These findings indicate that in situ measurement of PI signal intensity using the LIT-
IMD is representative of overall cell death and nonviability within a drug exposed tissue
volume, and therefore could obviate the need for ex vivo tissue processing and IHC anal-
ysis for IMD-based drug screening.
Figure 6. Methodology to correlate live tumor imaging with gold standard ex vivo fluorescence imaging and immuno-
histochemistry, demonstrated in a representative tumor sample. (a) After completion of live tumor imaging for 8 h, cross
sections of tumor tissue (dashed lines) were obtained at each drug delivery site. (b) fluorescent signal from M-2CFM imaging
in live tumor tissue (first column) was compared with corresponding conventional benchtop fluorescence microscopy (sec-
ond column) and immunohistochemistry (IHC) (third column), imaged after sectioning and processing the tissue. On the
benchtop fluorescence and IHC images, the boxes indicate the ~400 × 300 μm region of interest (ROI) corresponding to the
region of tissue imaged by the M-2CFM probe in the live tumor. On the IHC image, the ‘X’ denotes site of drug release; the
‘V’ indicates viable tumor tissue. (c) A trained image classifier enables quantitative determination of a non-viability index,
Figure 6.
Methodology to correlate live tumor imaging with gold standard ex vivo fluorescence imaging
and immunohistochemistry, demonstrated in a representative tumor sample. (
a
) After completion of
live tumor imaging for 8 h, cross sections of tumor tissue (dashed lines) were obtained at each drug
delivery site. (
b
) fluorescent signal from M-2CFM imaging in live tumor tissue (first column) was
compared with corresponding conventional benchtop fluorescence microscopy (second column) and
immunohistochemistry (IHC) (third column), imaged after sectioning and processing the tissue. On the
benchtop fluorescence and IHC images, the boxes indicate the ~400
×
300
µ
m region of interest (ROI)
corresponding to the region of tissue imaged by the M-2CFM probe in the live tumor. On the IHC image,
the ‘X’ denotes site of drug release; the ‘V’ indicates viable tumor tissue. (
c
) A trained image classifier
enables quantitative determination of a non-viability index, NVI (non-viable divided by viable tumor)
from the stained IHC images, which is then correlated with the experimental fluorescence images.
Cancers 2021,13, 653 8 of 14
Cancers 2021, 13, x FOR PEER REVIEW 8 of 14
NVI (non-viable divided by viable tumor) from the stained IHC images, which is then correlated with the experimental flu-
orescence images.
Figure 7. (a) Correlation between the M-2CFM live tumor fluorescence imaging and conventional
benchtop fluorescence imaging of corresponding tumor sections (r = 0.96, p < 0.001). (b) Correla-
tion between the M-2CFM live tumor fluorescence imaging signal intensity and a non-viability
index calculated from gold standard immunohistochemistry hematoxylin and eosin (H&E) stained
sections (r = 0.88, p < 0.001). n = 15 replicate drug sites from five tumors were used for this correla-
tion.
3. Materials and Methods
3.1. Design and Development of the LIT-IMD Probe
The body of the LIT-IMD is made from Delrin acetyl-resin (McMaster–Carr). Solid-
works (Dassault Systems, Solidworks 2017) and Mastercam (CNC Software, Inc., Tolland,
CT, USA) was used to develop CAD and CAM designs of the device body and a CNC
milling machine (MDA Precision, TN5-V8-TC8) was used to fabricate the part from the
Delrin stock material. To protect the optical probe from contamination when placed into
the LIT-IMD, a silica capillary tube with an outer diameter of 0.8 mm (Charles Supper
Company, Natick, MA, USA) is epoxied to the inner surface of the microdevice body to
form a water-tight inner lumen for coaxial passage of the miniaturized fluorescence im-
aging probe.
3.2. Miniaturized 2-Color Fluorescence Microscopy (M-2CFM) System Development
3.2.1. System Customization and Set-up
The M-2CFM system (Doric Lenses Inc., Quebec, CA, Canada) consists of a broad
band Ce:YAG light source and a blue LED source centered at 465 nm. The spectrum of the
Ce:YAG source is filtered by a narrow bandpass optical filter centered at 561 nm. The two
wavelengths or colors thus function as distinct excitation channels which can be con-
trolled separately. The two colors are combined and coupled into a 200 μm core diameter
multimode optical fiber. Light excitation for imaging is transmitted via an optical fiber cou-
pled to a customized thin 1 cm long, 500 μm diameter cylindrical gradient index (GRIN)
lens imaging probe, which fits coaxially into the LIT-IMD inner lumen. A metal sheath with
700 μm outer diameter and 100 μm wall thickness mechanically enhances and protects the
probe. To enable side-viewing necessary for our application, the GRIN lens is coupled to a
triangular prism at its distal end which redirects light 90 degrees (Figure 2b).
The probe both delivers light excitation and also collects the resultant fluorescent
signal. The system operates in an epi-fluorescence manner, and the collected fluorescence
images are received by two separate CCD cameras for both channels, one centered at 630
nm (red channel) and the other at 530 nm (green channel). The miniaturized optical imag-
ing probe is mounted on a 4-axis stage system consisting of three linear stages (Thorlabs)
Figure 7.
(
a
) Correlation between the M-2CFM live tumor fluorescence imaging and conventional benchtop fluorescence
imaging of corresponding tumor sections (r = 0.96, p< 0.001). (
b
) Correlation between the M-2CFM live tumor fluorescence
imaging signal intensity and a non-viability index calculated from gold standard immunohistochemistry hematoxylin and
eosin (H&E) stained sections (r = 0.88, p< 0.001). n= 15 replicate drug sites from five tumors were used for this correlation.
These findings indicate that in situ measurement of PI signal intensity using the
LIT-IMD is representative of overall cell death and nonviability within a drug exposed
tissue volume, and therefore could obviate the need for ex vivo tissue processing and IHC
analysis for IMD-based drug screening.
3. Materials and Methods
3.1. Design and Development of the LIT-IMD Probe
The body of the LIT-IMD is made from Delrin acetyl-resin (McMaster–Carr). Solid-
works (Dassault Systems, Solidworks 2017) and Mastercam (CNC Software, Inc., Tolland,
CT, USA) was used to develop CAD and CAM designs of the device body and a CNC
milling machine (MDA Precision, TN5-V8-TC8) was used to fabricate the part from the
Delrin stock material. To protect the optical probe from contamination when placed into
the LIT-IMD, a silica capillary tube with an outer diameter of 0.8 mm (Charles Supper
Company, Natick, MA, USA) is epoxied to the inner surface of the microdevice body
to form a water-tight inner lumen for coaxial passage of the miniaturized fluorescence
imaging probe.
3.2. Miniaturized 2-Color Fluorescence Microscopy (M-2CFM) System Development
3.2.1. System Customization and Set-up
The M-2CFM system (Doric Lenses Inc., Quebec, CA, Canada) consists of a broad
band Ce:YAG light source and a blue LED source centered at 465 nm. The spectrum
of the Ce:YAG source is filtered by a narrow bandpass optical filter centered at 561 nm.
The two wavelengths or colors thus function as distinct excitation channels which can
be controlled separately. The two colors are combined and coupled into a 200
µ
m core
diameter multimode optical fiber. Light excitation for imaging is transmitted via an optical
fiber coupled to a customized thin 1 cm long, 500
µ
m diameter cylindrical gradient index
(GRIN) lens imaging probe, which fits coaxially into the LIT-IMD inner lumen. A metal
sheath with 700
µ
m outer diameter and 100
µ
m wall thickness mechanically enhances and
protects the probe. To enable side-viewing necessary for our application, the GRIN lens is
coupled to a triangular prism at its distal end which redirects light 90 degrees (Figure 2b).
The probe both delivers light excitation and also collects the resultant fluorescent
signal. The system operates in an epi-fluorescence manner, and the collected fluorescence
images are received by two separate CCD cameras for both channels, one centered at 630 nm
(red channel) and the other at 530 nm (green channel). The miniaturized optical imaging
probe is mounted on a 4-axis stage system consisting of three linear stages (Thorlabs)
Cancers 2021,13, 653 9 of 14
for precise X-Y-Z movement and a fourth rotational stage (Figure 2a). The stages are
controlled electronically using commercially available software (Thorlabs). Control of the
M-2CFM system and subsequent imaging display from the CCD camera are also performed
in real-time using commercially available software (Doric). There were two microscope
cameras (Motic Instruments, Schertz, TX, USA) used to confirm satisfactory positioning
and alignment of the imaging probe, and to ensure that the microdevice does not migrate
within the live tumoral tissue during imaging.
3.2.2. Imaging System Characterization
A 10-
µ
m thick section containing fluorescently stained macrophage cells was placed
on a slide. The slide was moved in 25
µ
m increments away from the imaging probe
using a linear stage (Thorlabs) until optimal focus and minimal blurring was qualitatively
achieved; this distance was determined to be the optimal ‘working distance’ for the system.
Images obtained using the M-2CFM system were compared to gold standard benchtop
fluorescence imaging (Echo Revolve, San Diego, CA, USA) to determine the overall field of
view and resolution of the M-2CFM system with the custom GRIN lens probe.
3.3. Drug Response Assessment Proof-of-Concept in Murine Tumor Model
3.3.1. Animal Model
Institutional animal care and use committee (IACUC) approval was obtained. Murine sub-
cutaneous MC38 (colon adenocarcinoma) tumors were used for this study. Approximately
200
µ
L cell suspension (10
×
106 cells/mL) was injected into the subcutaneous murine
flank region under 1–3% isoflurane anesthesia, and tumors grew to 1.5 cm maximal diame-
ter prior to microdevice insertion. In total, five replicate murine tumors each containing
one LIT-IMD device were used, for a total of 15 unique drug-exposed tissue regions. Mi-
crodevices preloaded with drug and assay were directly inserted into live tumoral tissue.
After IMD implantation, the preloaded microdoses of drugs passively diffused into spa-
tially discrete tissue regions. The PI assay microdoses also passively diffused into these
drug-exposed tissue regions.
3.3.2. Drug and Assay Formulation for Localized Delivery
Chemotherapeutic agents Paclitaxel, Sunitinib, and Topotecan were used for our live
tumor experiments. All drugs were purchased in solid powder form (Selleck Chem, Hous-
ton, TX, USA) and reconstituted with 1450 g/mole molecular weight polyethylene glycol
(PEG) (Alfa Aesar, Haverhill, MA, USA) into a 50% w/w drug-PEG-1450 composite powder.
Propidium iodide (PI) was also purchased in powder form (Sigma–Aldrich, St. Louis,
MO, USA) and reconstituted with PEG-1000 into a 75% w/w assay-PEG composite powder.
A lower concentration and lower molecular weight PEG was used for the PI formulation
compared to the drugs, which allowed greater spatial diffusion of assay material into
adjacent drug-exposed tissue sites.
The chemotherapy agents were loaded into the microdevice in consecutive reservoirs
as shown in Figure 4a. The PI assay formulation was loaded on the opposite wall of the
microdevice into four contiguous reservoirs (Figure 4a). This formulation and loading
scheme optimized equal diffusion of PI into each drug-exposed tissue region, upon delivery
of the LIT-IMD into live tumor tissue.
M-2CFM imaging at each drug release site within the tumor was performed with the
imaging probe left within a tumor for 8 h after microdevice implantation. Images at each
drug delivery site were obtained at 1, 2, 4, and 8 h timepoints (Figure 4b). Fluorescence
images in the green (drug) and red (assay) channels were obtained using identical imaging
parameters at each drug release site: exposure time 100 ms; LED 465 nm excitation and
Ce:YAG laser 561 nm excitation. For each image, the average signal intensity within the field
of view was measured as quantitative indicator of overall drug diffusion (green channel)
and cell death (red channel), respectively.
Cancers 2021,13, 653 10 of 14
Red (assay) channel intensity was presumed to represent cell death from PI binding.
We performed statistical analysis comparing cell death at each drug site in the tumors at
each time point over 8 h. This assessment was done for three drugs and one control site
in 5 tumors (n= 5). We present mean and standard error of mean values for each site at
each time point (Table 1and Figure 5). A one-way analysis of variance (ANOVA) test was
used to compare signal means. The p-values listed in the table are pairwise comparisons of
drug exposure sites relative to the control site and indicate the degree of certainty that a
significant difference in cell death is observed relative to control.
3.3.3. Tissue Processing for ex vivo Correlation
At 8-h after LIT-IMD implantation, the tumors were immediately frozen at
−
80 de-
grees with the microdevices in place. After embedding into optimum cutting temperature
(OCT) media, 10-
µ
m sections were obtained at each drug site perpendicular to the long
axis of the LIT-IMD using a cryostat system (Leica, Buffalo Grove, IL, USA) (Figure 6a).
Hematoxylin and eosin (H&E) staining was performed of the same or immediately adjacent
sections for immunohistochemistry (IHC) analysis.
3.3.4. Conventional Imaging and Image Analysis
Conventional fluorescence imaging of the processed tissue sections was performed as
a gold standard measurement in the red and green channels using a commercial benchtop
fluorescence microscope system (Echo Revolve, San Diego, CA, USA). Images for analysis
were obtained at 4X magnification with 300 ms exposure time in red (586 nm wavelength
excitation, 603 nm emission) and green (495 nm excitation, 519 nm emission) channels.
A 400
×
300
µ
m rectangular region of interest (ROI) was selected at each drug site, corre-
sponding to a representative area evaluated by M-2CFM system in the live tumor (dotted
white box in Figure 6b). The mean PI (red channel) signal intensity within the ROI was
calculated using Matlab image processing software (Mathworks), as a quantitative measure
of cell death.
Hematoxylin and eosin (H&E) stained immunohistochemistry (IHC) slides were
imaged at 10X magnification. A 400
×
300
µ
m ROI at each drug release site was selected
in a similar manner as described above. Using QuPath software (QuPath) [
18
], an image
classifier was trained and validated, as described in Section 3.3.5, and used to segment
regions of viable and non-viable tumor. A non-viability index (NVI) was calculated at each
site as a quantitative measure of cell death: NVI = (non-viable tumor area)/(total viable
and non-viable tumor area)
×
100. The NVI was correlated with the corresponding mean
M-2CFM signal intensity.
Correlation between M-2CFM vs. benchtop fluorescence ROI signal intensities and
M-2CFM vs. IHC-based NVI were calculated using Matlab. For this analysis, we quantified
cell death drug response with each method at 15 distinct tumor sites (n= 15) in five
different tumors. Pearson correlation tests were performed, and correlation coefficients (r)
and significance values (p) are reported (Figure 7).
3.3.5. Automated Image Classification
Hematoxylin and eosin (H&E)-stained slides from separate MC38 murine tumors
were used for training, validation, and final analysis of the IHC images. The training set
consisted of 64 spatial regions of interest (ROI) in 10 separate tumors, with the total training
set consisting of 770,304 pixels and 1472 cells. The ROIs were pre-annotated as viable,
negative or empty space, or non-viable (based on standard pathological measures of necro-
sis and late apoptosis, including cell membrane disruption, loss of cellular architecture,
cell shrinkage, and nuclear condensation and fragmentation, as reviewed with a clinical
pathologist). QuPath [
18
], a publicly available software platform for immunohistochem-
istry analysis, was used to train an image classifier based on the annotated training set.
An artificial neural network model was used for this classifier.
Cancers 2021,13, 653 11 of 14
The model was validated on a separate MC38 tumor validation set consisting of
55 ROIs containing 665,500 pixels and 1265 cells. Each ROI was pre-defined as viable,
negative, or non-viable based on gold-standard pathology evaluation and compared with
the classifier prediction (See Supplementary Figure S1). For non-viable, negative, and viable
classes, respectively, the per-class precision was 0.92, 1.00, and 0.94; recall 0.96, 1.00, 0.88;
and F1-score 0.94, 1.00, 0.91. The macro-averaged precision, recall, and F1-score was
0.95, 0.94, and 0.95, respectively. This classifier was applied to experimental data images,
which were obtained using the same staining protocol and imaging parameters as the
training and validation sets (Figure 6and Supplementary Figure S2).
4. Discussion
This study demonstrates that localized drug-induced cell death can be assessed di-
rectly in a live tumor, and represents a unique approach compared to current histopathology
methods that require tissue removal and processing. This could enable IMD-based drug
screening to be performed more rapidly and efficiently, as there is no delay associated
with tissue processing, staining, and ex vivo analysis required for current IHC methods.
Since imaging is performed directly within the tumor at the precise site of drug release,
drug response assessment can be performed in tumors of any size, as long as the tumors are
large enough for the microdevices to be placed inside of them. In our study, we used tumors
of 1–1.5 cm maximal diameter, but our method would be applicable even in much larger
tumors. In addition, since tissue can be analyzed in place without need for surgical removal,
this approach may enable IMD-based drug screening and other similar applications to be
more safely implemented in a greater number of pre-clinical and clinical settings.
The current system was optimized for use in superficial murine tumors, and can
be used in its current design form for similarly superficial skin or subcutaneous tumors.
The small size and cylindrical shape of the microdevice also makes it potentially suitable
for minimally invasive implantation in deeper tissues, using a procedure similar to percuta-
neous fiducial marker delivery [
19
]. A potential design strategy for imaging deeper tumors
would be to place the LIT-IMD at the end of a longer imaging catheter, similar to currently
existing endoluminal and endovascular catheters [
20
,
21
]. This could further increase the
number of pre-clinical and clinical settings for which IMD-based drug screening is safe
and feasible.
The M-2CFM system imaged drug-induced cell death with strong differences in signal
intensity at sites of cell death compared to sites of viable tumor. However, overlap of
fluorescence signal detection from in-focus and out-of-focus tissue planes limited overall
resolution. Miniaturized confocal and multiphoton microscopy systems are available that
could allow higher resolution and optical sectioning, wherein a specific tissue plane at
a focal distance from the imaging probe is imaged without signal overlap from out-of-
focus planes [
9
,
22
,
23
]. However, these are currently limited by low penetration depth and,
therefore, less suitable for our application, which benefits from volumetric assessment of
drug exposed tissue up to 300
µ
m depths from the imaging probe. Further development of
miniaturized confocal or multiphoton fluorescence imaging with larger penetration depth
could enable higher resolution and optical sectioning in deeper tissues in the future. Label-
free microscopy systems such as optical coherence tomography and Raman spectroscopy
also could have the potential to quantify cell death in situ [
24
–
26
], but have not been
extensively studied or validated.
Local delivery of PI assay microdoses enabled detection and comparison of cell death
response among multiple drugs. With this approach, both drug and assay are confined
to tiny tumoral tissue volumes, obviating potential off-target toxicity from systemic (e.g.,
intravenous or oral) administration. Other existing targeted fluorescent imaging probes can
be used in a similar manner to more fully evaluate biological mechanisms of disease and
treatment response. Existing fluorescent probes can detect numerous biological processes
including apoptosis, immune response, and genetic expression in live tissues [
12
,
27
,
28
].
However, other than a few non-targeted agents such as indocyanine green and fluores-
Cancers 2021,13, 653 12 of 14
cein [
20
,
29
–
31
], the vast majority of fluorescent imaging probes are not FDA-approved
for clinical use and have not been used in patients due to concerns for off-target toxicity
with systemic delivery. Restricting the delivery of these agents to microdoses released
locally adjacent to the LIT-IMD, as described here for PI, eliminates systemic toxicity risk.
This approach could therefore enable more widespread use of labeled
in vivo
fluores-
cence microscopy in preclinical and clinical settings. Although we have demonstrated
utility specifically for cell death drug response, there is potential for this platform to be
broadly applied to monitor a diverse range of biological processes and individual resistance
mechanisms in native tumoral microenvironments.
This is the first study to our knowledge in which the three tested drugs (Paclitaxel,
Sunitinib, Topotecan) were directly compared in a syngeneic live tumor mouse model.
The relative effectiveness measured in our microdose study in MC38 tumors are congruent
with prior
in vivo
and
in vitro
published results. Previous systemic
in vivo
studies have
shown MC38 murine models to exhibit significantly greater sensitivity to Paclitaxel than
other commonly used tumor models [
32
]. Paclitaxel has been shown to be more effective
than Topotecan in MC38 organoid and slice culture models [
33
]. Though Sunitinib has not
been tested in MC38 previously, highly similar drugs that also target vascular endothelial
growth factor (VEGF) and platelet-derived growth factor recepter (PDGFR) such as Van-
detanib have shown to be highly potent in MC38 tumors [
34
]. High-throughput
in vitro
sensitivity results that are part of the Sanger and Cell Line Encyclopedia in MC38 and
other colorectal cell lines with similar mutational profiles (e.g., COLO201, COLO205) also
indicate that VEGF and PDGFR inhibitors such as Sunitinib are the most potent (z-score
−
0.84), closely followed by Paclitaxel (z-score
−
0.79), with Topotecan being significantly
less potent (z-score +0.77) [35].
Intratumoral heterogeneity remains a significant challenge in developing personalized
cancer treatment strategies [
36
,
37
]. Diagnostic and molecular information ascertained
from a small tumor sample may not be representative of the entire tumor, leading to
suboptimal treatments. Our platform could simultaneously evaluate drug response at
multiple spatially discrete regions of a tumor, either by redundant release of the same drug
into multiple sites from a single microdevice or by placing multiple identically loaded
microdevices into different tumor regions. While tumor biopsies are often limited by the
amount of tissue that can safely be removed and assessed, full in situ assessment may
allow interrogation of a greater volume of tissue and more fully evaluate heterogeneous
drug response. However as even this approach does not evaluate the entire tumor, it may
remain susceptible to the limitations of intratumoral heterogeneity. Therefore, additional
studies are needed to evaluate the ability to predict systemic treatment response in the
setting of tumor heterogeneity.
5. Conclusions
Our platform enables multiplexed drug response assessment directly in live tumors
without requiring surgical tissue excision, which could lead to development of more
optimized treatment strategies in pre-clinical and clinical settings. The combination of in
situ fluorescence imaging and local fluorescent assay delivery is a powerful approach that
could greatly expand ability to image biological processes in real time.
Supplementary Materials:
The following are available online at https://www.mdpi.com/2072-669
4/13/4/653/s1, Figure S1. (a) Hematoxylin-and-eosin (H&E) stained slide of MC38 murine tumor
demonstrating viable (V), non-viable (NV) tissue, and negative/empty space (N). (b) Propidium io-
dide staining confirms region of non-viable tissue (red fluorescent signal). (c) Trained image classifier
correctly identifies the three distinct classes, which are used to calculate the non-viability index (NVI)
in our study. Three example regions of interest (ROIs, red boxes) in this tumor sample are shown.
64 such ROIs were used for training the classifier, and 55 ROIs in separate tumor samples/images
were used for validation (this image is part of the validation set); Figure S2. (a) Hematoxylin-and-
eosin (H&E) stained sections of drug-exposed tissue in MC38 murine tumor after local release of
Cancers 2021,13, 653 13 of 14
Paclitaxel (a), Topotecan (b), and Control (c). Magnified images from Figure 6b show greatest cell
death drug response for Paclitaxel > Topotecan > Control in this tumor sample.
Author Contributions:
Conceptualization, S.B., S.W.A., K.U., A.L., and O.J.; Formal analysis, S.B.,
B.F., V.V., G.L., and O.J.; Funding acquisition, O.J.; Investigation, S.B., D.T., S.W.A., K.U., A.L.,
K.D., and O.J.; Methodology, S.B., D.T., S.W.A., K.U., A.L., K.D., B.F., V.V., G.L., and O.J.; Project
administration, C.D. and O.J.; Resources, C.D. and O.J.; Supervision, O.J.; Writing—original draft,
S.B.; Writing—review and editing, S.B., D.T., S.W.A., K.U., A.L., K.D., C.D., B.F., V.V., G.L., and O.J.
All authors have read and agreed to the published version of the manuscript.
Funding:
This research was funded by National Institutes of Health (NIH) grant #5R37CA224144
and National Institute of Biomedical Imaging and Bioengineering (NIBIB) grant #P41EB019703.
Institutional Review Board Statement:
The study was approved for animal use by the Institu-
tional Animal Care and Use Committee of Brigham and Women’s Hospital (protocol #2017N000003,
approved 3/15/17 and reapproved upon triennial review 3/11/2020). No human patients were
involved in this study.
Informed Consent Statement: Not applicable (no human subjects).
Data Availability Statement:
The data presented in this study are openly available in Harvard
Dataverse repository at https://doi.org/10.7910/DVN/XRYK3Z (accessed on 2 January 2021).
Conflicts of Interest:
O.J. is a consultant to Kibur Medical, Inc. His interest was reviewed and is
managed by BWH and MGB Healthcare in accordance with their outside interest policies.
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