Maria T Proetto1,2, Cassandra E Callmann1,2, John Cliff3, Craig J Szymanski3, Dehong Hu3, Stephen B Howell1, James E Evans3, Galya Orr3, Nathan C Gianneschi1,2. 1. Department of Chemistry & Biochemistry and Moores Cancer Center, University of California, San Diego, La Jolla, California 92093, United States. 2. Department of Chemistry, Department of Materials Science & Engineering, Department of Biomedical Engineering, Northwestern University, Evanston, Illinois 60208, United States. 3. Environmental Molecular Sciences Laboratory (EMSL), Pacific Northwest National Laboratory, Richland, Washington 99354, United States.
Abstract
In nanomedicine, determining the spatial distribution of particles and drugs, together and apart, at high resolution within tissues, remains a major challenge because each must have a different label or detectable feature that can be observed with high sensitivity and resolution. We prepared nanoparticles capable of enzyme-directed assembly of particle therapeutics (EDAPT), containing an analogue of the Pt(II)-containing drug oxaliplatin, an 15N-labeled monomer in the hydrophobic block of the backbone of the polymer, the near-infrared dye Cy5.5, and a peptide that is a substrate for tumor metalloproteinases in the hydrophilic block. When these particles reach an environment rich in tumor associated proteases, the hydrophilic peptide substrate is cleaved, causing the particles to accumulate through a morphology transition, locking them in the tumor extracellular matrix. To evaluate the distribution of drug and EDAPT carrier in vivo, the localization of the isotopically labeled polymer backbone was compared to that of Pt by nanoscale secondary ion mass spectrometry (NanoSIMS). The correlation of NanoSIMS with super-resolution fluorescence microscopy revealed the release of the drug from the nanocarrier and colocalization with cellular DNA within tumor tissue. The results confirmed the dependence of particle accumulation and Pt(II) drug delivery on the presence of a Matrix Metalloproteinase (MMP) substrate and demonstrated antitumor activity. We conclude that these techniques are powerful for the elucidation of the localization of cargo and carrier, and enable a high-resolution assessment of their performance following in vivo delivery.
In nanomedicine, determining the spatial distribution of particles and drugs, together and apart, at high resolution within tissues, remains a major challenge because each must have a different label or detectable feature that can be observed with high sensitivity and resolution. We prepared nanoparticles capable of enzyme-directed assembly of particle therapeutics (EDAPT), containing an analogue of the Pt(II)-containing drug oxaliplatin, an 15N-labeled monomer in the hydrophobic block of the backbone of the polymer, the near-infrared dye Cy5.5, and a peptide that is a substrate for tumormetalloproteinases in the hydrophilic block. When these particles reach an environment rich in tumor associated proteases, the hydrophilic peptide substrate is cleaved, causing the particles to accumulate through a morphology transition, locking them in the tumor extracellular matrix. To evaluate the distribution of drug and EDAPT carrier in vivo, the localization of the isotopically labeled polymer backbone was compared to that of Pt by nanoscale secondary ion mass spectrometry (NanoSIMS). The correlation of NanoSIMS with super-resolution fluorescence microscopy revealed the release of the drug from the nanocarrier and colocalization with cellular DNA within tumor tissue. The results confirmed the dependence of particle accumulation and Pt(II) drug delivery on the presence of a Matrix Metalloproteinase (MMP) substrate and demonstrated antitumor activity. We conclude that these techniques are powerful for the elucidation of the localization of cargo and carrier, and enable a high-resolution assessment of their performance following in vivo delivery.
We
have developed a method, termed EDAPT for “enzyme-directed
assembly of particle therapeutics”, for targeting nanoparticles
that accumulate and become locked in malignant tissues when they encounter
tumor proteases.[1−3] This platform technology targets tumors via disease-associated
enzymes acting on these responsive materials leading to a morphology
transition from small spherical nanoparticles to microscale accumulated
material within tumor tissue leading to retention and accumulation
of fluorescent probes and therapeuticsafter intratumoral (IT) or
intravenous (IV) administration (Figure ).[1,4] This approach, as with
other targeted nanoparticle technologies,[5,6] presents
a challenge in terms of determining particle localization, drug release
and distribution at high resolution within the targeted tissue.[7] Meeting this challenge requires that carrier
and drug are labeled, or are naturally predisposed for high resolution
imaging. Several techniques, including magnetic resonance imaging
(MRI), positron emission tomography (PET), and computed tomography
(CT), are available and widely used for the study of chemical systems in vivo, especially for whole animal imaging.[8,9] To obtain higher resolution, ex vivo techniques
such as fluorescence microscopy, scanning transmission X-ray microscopy
(STXM), Raman microspectral imaging, electron microscopy (EM), or
nanoscale secondary ion mass spectrometry (NanoSIMS) have proven useful.[10−12] However, these techniques vary in sensitivity, resolution, nanoparticle
labeling requirements, cost, availability, and sample preparation
needs.[13] Further, to fully understand the
relationship between nanomaterials and their biological behavior using
these techniques individually is problematic.
Figure 1
Polymer structure, assembly,
and characterization of labeled micellar
nanoparticles. Left: Pep-Pt-P chemical structure. Dialysis
of the 15N, Pt, and Cy5.5 multilabeled polymer (Pep-Pt-P) from DMSO to water yields well-defined micellar nanoparticles of
approximately 20 nm in diameter. -Amino
acid peptide sequence “GPLAGGERDG”
for and -amino acid sequence “gplglaggerdg”
for . As previously shown,
cleavage of the -amino acid peptide sequence
“GPLAGGERDG” occurs
between the italicized and , promoting the release of the hydrophilic peptide
sequence “AGGERDG”
which triggers the nano- to micrometer morphology change.[1] Right: TEM image (dry state, negative uranyl
acetate stain) of before
(left) and after (right) exposure to MMP, demonstrating enzyme-induced
morphology change. For TEM images of before and after MMP exposure, see Figure S3.
Polymer structure, assembly,
and characterization of labeled micellar
nanoparticles. Left: Pep-Pt-P chemical structure. Dialysis
of the 15N, Pt, and Cy5.5 multilabeled polymer (Pep-Pt-P) from DMSO to water yields well-defined micellar nanoparticles of
approximately 20 nm in diameter. -Amino
acid peptide sequence “GPLAGGERDG”
for and -amino acid sequence “gplglaggerdg”
for . As previously shown,
cleavage of the -amino acid peptide sequence
“GPLAGGERDG” occurs
between the italicized and , promoting the release of the hydrophilic peptide
sequence “AGGERDG”
which triggers the nano- to micrometer morphology change.[1] Right: TEM image (dry state, negative uranyl
acetate stain) of before
(left) and after (right) exposure to MMP, demonstrating enzyme-induced
morphology change. For TEM images of before and after MMP exposure, see Figure S3.One way to overcome the specific
limitations of each technique
is to image samples by multiple methods simultaneously. As an example
of this approach, correlated optical and isotopic nanoscopy (abbreviated
as COIN) has been introduced for multimodal imaging pertaining to
the nanometer length scale.[14,15] In one such application
of this approach, NanoSIMS, exhibiting high spatial resolution, sensitivity,
and mass resolution yielding some chemical information,[11,16] is linked with super-resolution fluorescence microscopy techniques.
Although methodologically complex, this combination of techniques
has been applied to great effect in the study of biological processes.[14,17]In this paper we describe the behavior of Pt(II) drug-loaded,
matrix-metalloproteinase
(MMP) responsive nanoparticles in vivo following
IT administration. These EDAPT nanoparticles were generated through
the assembly of amphiphilic block copolymers designed to undergo a
change in size following exposure to MMPs that are highly overexpressed
in tumor tissues.[18−20] This was achieved through incorporation of peptide
substrates for MMPs in the micellar nanoparticle shell. As previously
shown, upon exposure to proteolytic enzymes, the cleavage of a specific
hydrophilic peptide fragment on the shell of the small, spherical
micellar nanoparticles occurs, changing the amphiphilic nature of
the polymer. This trigger causes the polymers to pack differently,
leading to a phase transition, or morphology change to a larger, microscale
assembly, which locks the material within tumor tissue in
vivo.(1−4,21−24) As a negative control for this
process, analogous systems were generated using all -amino acids in the peptide sequence as they are not recognized
as substrates by MMPs or other proteases in the body. We employed
NanoSIMS correlated with structured illumination microscopy (SIM)
to study the distribution of a drug cargo and nanocarrier in tumor
tissues. This allowed a quantification of drug release from the nanocarrier
to tumor tissues and confirmed drug targets in vivo. This is an unprecedented study demonstrating the application of
such techniques in the elucidation of specific interactions and distribution
of drug loaded nanoparticles in tissues.
Results
and Discussion
We designed Pt(II)-loaded nanoparticles (Pep-Pt-NPs) using amphiphilic block copolymers containing
an oxaliplatin analogue
and MMP-responsive peptides (Pep-Pt-P, Figure ). These polymers were synthesized
through ring opening metathesis polymerization (ROMP).[25] The monomers were specifically designed to form
polymers that would self-assemble into particles with three important
capabilities: (1) retention in tumor tissue; (2) antitumor activity
in a murine xenograft of a cancer type that overexpresses MMPs; and
(3) contrast for optical (in vivo and ex
vivo) and isotopic imaging (ex vivo). These
polymers were synthesized using four different ROMP monomers: (1)
an oxaliplatin analogue monomer containing a norbornene polymerizable
moiety (Pt-Mon),[26] known to
be cytotoxic to a variety of cancer cells and useful as an isotopic
label because of the lack of Pt in normal tissues; (2) a 15N-labeled phenyl monomer (N-Mon) which serves as a isotopic label for the polymer backbone of the
nanocarrier; (3) a peptide substrate monomer (Pep-Mon) as an MMP recognition sequence (-amino
acid sequence “GPLGLAGGERDG” for and -amino acid
sequence “gplglaggerdg” for ); and (4) a cyanine 5.5 dye (Cy5.5) monomer (Cy-Mon) as a fluorescent polymer label for super-resolution
fluorescence microscopy (Figure S1). Copolymerization
of N-Mon with Pt-Mon in a 2:1 ratio to form the hydrophobic block, followed by Pep-Mon to form the hydrophilic block and Cy-Mon as a third block generated polymerPep-Pt-P (Figure and Figure S1). Nanoparticles were generated from Pep-Pt-P by dialyzing the polymers from DMSO into water as
drug-containing, enzyme-responsive, isotopically, and fluorescently
labeled (Figures and S2). Nonresponsive, negative control nanoparticles were synthesized
by incorporating -amino acid peptides into
the hydrophilic block of the polymers, yielding , Figure S3. Compared
to other previously reported oxaliplatin loaded micelles,[27−29] our synthetic approach generated functional nanoparticles with more
than 35 wt % drug loading without the need of post-polymerization
or postassembly conjugations.After confirming the ability of to aggregate upon MMP exposure in vitro (Figures , S2 and S3), we examined the capability
of the material to
be retained in tumor tissue in vivo and explored
their ability to inhibit tumor growth as a result. We utilized humanHT-1080fibrosarcoma subcutaneous xenografts for these studies as
this cell line overexpresses MMPs.[30,4] Mice bearing
HT-1080 tumors were injected IT with either or at
2.5 mg/kg with respect to Pt content and monitored over the course
of 12 days for retention and efficacy. A third cohort received saline
alone as an additional negative control, with a fourth receiving oxaliplatin
alone, which is the clinical analogue of the compound loaded in the
particles.Importantly, was able
to inhibit tumor growth relative to both the saline and controls (Figure ). Additionally, it performed as well as
oxaliplatin, suggesting that packaging the Pt drug in a nanocarrier
does not adversely affect its therapeutic potential. As previously
demonstrated for other EDAPT systems, a key advantage of this platform
is its ability to deliver its cargo specifically and selectively to
tumor tissues, while limiting off-target toxicity (Figure S4).[4]
Figure 2
Efficacy and whole animal
and ex vivo organ targeting
data. Left: Comparison of to , oxaliplatin at 2.5
mg/kg dose with respect to Pt and saline following IT injection. effectively inhibited tumor growth
up to 12 days postinjection with efficacy similar to oxaliplatin,
whereas showed no observable
effect. Right-top: Time course of live-animal fluorescence imaging
following IT injection of . Right-bottom: Ex vivo tissue analysis. Fluorescence
imaging of tumor, liver, spleen, and kidney excised at 24 h from animal
administered . White line
shows the outline of the organs. Highest signal was observed in tumor.
Efficacy and whole animal
and ex vivo organ targeting
data. Left: Comparison of to , oxaliplatin at 2.5
mg/kg dose with respect to Pt and saline following IT injection. effectively inhibited tumor growth
up to 12 days postinjection with efficacy similar to oxaliplatin,
whereas showed no observable
effect. Right-top: Time course of live-animal fluorescence imaging
following IT injection of . Right-bottom: Ex vivo tissue analysis. Fluorescence
imaging of tumor, liver, spleen, and kidney excised at 24 h from animal
administered . White line
shows the outline of the organs. Highest signal was observed in tumor.Further, live animal fluorescence
microscopy (Figure ) was used to monitor the retention
of both and postinjection by tracking the NIR fluorophore
on the polymer backbone of both systems (λex = 635
nm and λem = 693 nm). Fluorescence was observable
up to 5 days following IT injection of , suggesting that these materials were retained over a long time
scale. Importantly, fluorescence was only observed for the first 5
h following IT injection of , indicative of rapid clearance of the nonresponsive material which
had an efficacy comparable to that observed for saline (Figure S5). Furthermore, ex vivo tissue analysis of tumor-bearing mice injected IT with either , , or saline solution and sacrificed 24 h postinjection shows the
highest fluorescence signal intensity in the excised tumors, with
fluorescence observed to a lesser extent in the liver, spleen, and
kidneys (Figures and S6).Tumor tissue was additionally examined ex vivo utilizing a multimodal super-resolution imaging
approach that combines
optical (SIM) with isotopic (NanoSIMS) nanoscopy. Both techniques
have been proven useful for imaging biological samples.[15,16,31,32] SIM, a light microscopy technique capable of subdiffraction limit
imaging, has been widely used in the field of neuroscience, cell biology,
and microbiology to observe cellular and subcellular processes that
occur at the nanometer scale. NanoSIMS, on the other hand, has been
used in the field of paleobiology, microbial ecology, and cellular
biology to collect isotopic information and thus quantify the sample’s
elemental composition.[16] In our study,
the combination of these techniques is necessary to provide a complete
distribution map of the nanomaterial in the tumor tissue, with nanometric
resolution. While NanoSIMS allows determination of the distribution
of both the nanocarrier and the drug within the tumor independently,
SIM provides three-dimensional structural information such as a specific
extracellular or intracellular nanocarrier localization.Once
the nanomaterial aggregates in tumor tissues and the polymer
hydrophobic block are exposed to the tissue milieu, nucleophiles such
as chloride ions and water are expected to promote oxaliplatin drug
release from the nanocarrier by ligand exchange reactions on the Pt(II)
to displace the labile carboxylate ligands.[33] Ultimately, oxaliplatin binding to nuclear DNA is expected to trigger
cytotoxic effects in tumor cells.[34,35] To validate
this pathway, we performed super-resolution imaging of tumor tissue
and tracked the nanocarrier (the polymer NIR dye label with SIM and
the 15N label with NanoSIMS) and the Pt(II)-drug (NanoSIMS)
separately. Similar to the procedure used for efficacy studies, tumor-bearing
mice were injected IT with either , , or saline solution and
sacrificed 24 h later. The tumors were harvested and cryosectioned
into 5 μm sections and placed on indium-tin-oxide (ITO) coverslips.
Immunostaining was performed on the sections with an anti-α-actinin
antibody to label cytoplasmic dense structures (α-actinin, AF
488). Samples were subsequently stained with DAPI as a cell nucleus
indicator and then dehydrated for imaging (see Experimental
Section).Fluorescent images were acquired at different
magnifications as
part of preliminary investigations. Low magnification images showed
fluorescent signals from both the and polymeric nanomaterials
distributed mainly at the periphery of the tumor tissue (Figure S7). As previously observed in time-course
studies of fluorescence in live animals, only a minimal amount of
Cy5.5 signal was detected for the sample because of its reduced retention in tumor tissues. Increased
magnification revealed the polymeric probes preferentially accumulating
in the extracellular space, as the fluorescent signal associated with
the polymer backbone (Cy5.5) was only poorly correlated with intracellular
fluorescently labeled, green actin filaments (Figures and S8).
Figure 3
SIM analysis
of 5 μm thick tumor tissue sections of animals
pretreated with (top), (middle), or saline (bottom).
The samples were examined using specific fluorescent probes. The polymers
used to obtain the nanostructures contain a Cy5.5 NIR dye chemically
bound to the polymer backbone used to track the nanomaterials (red).
Actin filaments were visualized by staining with a mouse anti-α-actinin
antibody followed by AF 488 goat antimouse antibody (green). Nucleus
was stained with DAPI (blue). Although DAPI is known to bind and stain
DNA, some nonspecific binding to other subcellular structures was
observed. From these fluorescent images, it is clear that the signal
for both the responsive and the nonresponsive nanoparticles are not
correlated with nuclear and actin staining, suggesting an extracellular
localization of the nanomaterials. Interestingly, samples from animals
treated with saline solution showed fluorescent signals in the far
red channel, attributed to tissue autofluorescence. The dashed line
outlines a cell boundary. Scale bar represents 5 μm.
SIM analysis
of 5 μm thick tumor tissue sections of animals
pretreated with (top), (middle), or saline (bottom).
The samples were examined using specific fluorescent probes. The polymers
used to obtain the nanostructures contain a Cy5.5 NIR dye chemically
bound to the polymer backbone used to track the nanomaterials (red).
Actin filaments were visualized by staining with a mouse anti-α-actinin
antibody followed by AF 488 goat antimouse antibody (green). Nucleus
was stained with DAPI (blue). Although DAPI is known to bind and stain
DNA, some nonspecific binding to other subcellular structures was
observed. From these fluorescent images, it is clear that the signal
for both the responsive and the nonresponsive nanoparticles are not
correlated with nuclear and actin staining, suggesting an extracellular
localization of the nanomaterials. Interestingly, samples from animals
treated with saline solution showed fluorescent signals in the far
red channel, attributed to tissue autofluorescence. The dashed line
outlines a cell boundary. Scale bar represents 5 μm.The fact that tumor regression occurred (Figure ) means that Pt-containing
oxaliplatin analogue
must permeate into cells over this time frame. To directly visualize
this, tissue sections previously imaged by SIM (Figure ) were further analyzed with NanoSIMS (Figures , S9, S10, and S11). A secondary electron (SE) image was collected
together with four masses of interest to create elemental maps for
each sample: 31P as a nuclear indicator because of the
phosphorus-rich DNA; 12C14N as an indicator
for organic matter; 12C15N as a polymer backbone
indicator; and 195Pt as a drug label. A hue-saturation-intensity
(HSI) representation of the 12C15N/12C14N ratio map as a color scaled image was constructed
in order to specifically identify 15N-rich areas (Figures and S9). In addition to the tumor tissue, a sample
of yeast was imaged daily and used to calibrate the 12C15N/12C14N measurements relative to air
(Supporting Information). 195Pt counts obtained from images of samples of animals pretreated with
saline solution were used to set baseline counts and the 15N distribution was in accordance with 15N natural abundance
(Figure and Supporting Information). It is important to note
that fluorescence images from these saline samples (Figure , bottom panels) show signals
in the far red channel (Cy5) attributed to autofluorescence, since
no specific 195Pt or elevated 15N signals were
observed by NanoSIMS (Figure , bottom panels). This highlights the need for, and importance
of, multimodal imaging when studying labeled materials in complex
biological systems.
Figure 4
NanoSIMS imaging of tissue slices. Secondary electron
images (SE)
and NanoSIMS ion maps of dehydrated 5 μm tumor tissue sections
of mice treated with (top), (middle), or saline (bottom). 31P–, 12C14N–, 12C15N–, and 195Pt– ion maps were obtained simultaneously, and
intensities are shown in a fire scale, except for the 195Pt– ion map which is shown in white/black. HSI
images represent the 12C15N/12C14N ratio and highlight specifically enriched areas as can
be seen for and samples. The scales on the HSI images
were adjusted depending on the relative intensities for each sample.
Thus, the scale for is 0.0037–0.02,
for is 0.0037–0.11,
and for the saline solution sample 0.0037–0.15. Images, in
all cases, represent an area of 48 μm × 48 μm.
Figure 5
Quantitative analysis of 15N and 195Pt enrichment
inside or outside of 15N- and 31P-rich ROIs.
A: ROIs were defined according to 15N accumulation, as
high 15N/14N (ROI number 1–16) and low 15N enrichment (ROI number 17–32). A.1: 15N ROIs on the HSI image.
A.2: 15N ROIs on the HSI image. A.3: 15N/14N inside and outside
of 15N-rich ROIs. A.4: 195Pt enrichment inside
and outside of 15N-rich ROIs. B: ROIs were defined according
to 31P signal, as high 31P (ROI number A1–10)
and low 31P (ROI number B1–10). B.1: 31P ROIs on the 31P ion map image. B.2: 31P ROIs on the 31P ion map image. B.3: 15N/14N inside or outside of 31P-rich ROIs. B.4: 195Pt enrichment inside or outside of 31P-rich ROIs.
Note that Pt– was collected as 196Pt– for the saline sample. Pt counts on saline ROIs were
normalized to 195Pt by multiplying by 1.34, according to
their isotopic abundance (33.8/25.2). Enrichment values were obtained
from at least two independent images of each sample. For additional
images, see Figure S12. A summary of these
results and its statistical analysis can be found in Tables S1–S3. Minimum significant difference was defined
as a p-value < 0.05.
NanoSIMS imaging of tissue slices. Secondary electron
images (SE)
and NanoSIMS ion maps of dehydrated 5 μm tumor tissue sections
of mice treated with (top), (middle), or saline (bottom). 31P–, 12C14N–, 12C15N–, and 195Pt– ion maps were obtained simultaneously, and
intensities are shown in a fire scale, except for the 195Pt– ion map which is shown in white/black. HSI
images represent the 12C15N/12C14N ratio and highlight specifically enriched areas as can
be seen for and samples. The scales on the HSI images
were adjusted depending on the relative intensities for each sample.
Thus, the scale for is 0.0037–0.02,
for is 0.0037–0.11,
and for the saline solution sample 0.0037–0.15. Images, in
all cases, represent an area of 48 μm × 48 μm.Quantitative analysis of 15N and 195Pt enrichment
inside or outside of 15N- and 31P-rich ROIs.
A: ROIs were defined according to 15N accumulation, as
high 15N/14N (ROI number 1–16) and low 15N enrichment (ROI number 17–32). A.1: 15N ROIs on the HSI image.
A.2: 15N ROIs on the HSI image. A.3: 15N/14N inside and outside
of 15N-rich ROIs. A.4: 195Pt enrichment inside
and outside of 15N-rich ROIs. B: ROIs were defined according
to 31P signal, as high 31P (ROI number A1–10)
and low 31P (ROI number B1–10). B.1: 31P ROIs on the 31P ion map image. B.2: 31P ROIs on the 31P ion map image. B.3: 15N/14N inside or outside of 31P-rich ROIs. B.4: 195Pt enrichment inside or outside of 31P-rich ROIs.
Note that Pt– was collected as 196Pt– for the saline sample. Pt counts on saline ROIs were
normalized to 195Pt by multiplying by 1.34, according to
their isotopic abundance (33.8/25.2). Enrichment values were obtained
from at least two independent images of each sample. For additional
images, see Figure S12. A summary of these
results and its statistical analysis can be found in Tables S1–S3. Minimum significant difference was defined
as a p-value < 0.05.As seen in Figure , samples exposed to and show 195Pt localized
in areas
enriched in 15N. Some of these hotspots correlated with
Cy5.5 fluorescent signals on the SIM images (Figure S10). This suggests that, in certain areas of the tumor, the
three labels incorporated in the polymer are still associated with
the aggregated nanomaterials. To better understand the distribution
of drug and nanocarrier in the tissue, regions of interest (ROIs)
were defined. These ROIs were used to quantify the accumulation of
the nanocarrier and drug labels within or outside of the ROIs. Thus,
two types of ROIs were analyzed: within or outside highly 15N-rich areas defined from the corresponding HSI images and within
or outside of 31P-rich areas defined from the corresponding 31P– images, to analyze accumulation of the
labels on the aggregated nanomaterial (Figure top panels) and on the nucleus of cells
(Figure bottom panels),
respectively.By averaging the values for ROIs inside or outside
of 15N-rich areas (Figure A), it became clear that 15N enrichment
was significantly
greater in 15N-rich ROIs of than for either or the
saline control, which should have an 15N enrichment at
natural abundance (Figure A.3, dashed line at 0.0037). Interestingly, 15N
enrichment in ROIs selected outside the main areas of 15N accumulations was larger for the Pep-Pt-NPs than for
the saline sample, and again larger for the responsive compared to nonresponsive (Table S3).
This indicates that some of the material becomes delocalized from
the main 15N-rich areas. Although a similar distribution
was observed for 195Pt, with a higher concentration of
Pt in 15N-rich ROIs of samples than of and the
saline control, no significant difference was observed between the
Pt enrichment of ROIs outside the 15N-rich regions (Figure A.4, Table S3). This suggests a differential distribution
of Pt and 15N in ROIs outside the main 15N enriched
areas between samples treated with responsive and nonresponsive nanoparticles.
For both labels (15N and Pt), the higher concentration
of counts in samples than samples is in agreement with
the greater retention in tumor tissues of the responsive material
previously observed by fluorescence spectroscopy.In an effort
to study the differential accumulation of the nanocarrier
(15N) and the Pt complex on the presumed drug target (DNA),
a second set of ROIs was defined within or outside of 31P-rich areas found in the 31P– ion map
(Figure B.1). As expected,
the 15N enrichment inside and outside 31P-rich
ROIs is much lower than for the 15N ROIs (Figure A.3 and 5B.3). As previously observed, 15N and Pt showed a different
distribution, and in all cases the accumulation accounted for by the
labels was significantly higher than in the saline control sample.
Although no significant difference was observed for 15N
enrichment inside or outside 31P-rich ROIs, differences
between samples and between the local sample distribution was observed
for Pt, with a higher concentration of Pt in the nucleus and for the
samples exposed to the responsive system (Figure B.4).In summary, these results show a different enrichment of the nanocarrier
and the drug inside and outside 15N-rich ROIs, and, at
the same time, differences were observed between their respective
concentrations suggesting spatial dissociation of the species. The
larger concentration of 15N and Pt in the tumor sections
exposed to the responsive is in agreement with an extended retention of this material relative
to the nonresponsive . As
a consequence of this extended retention, inhibition of tumor growth
was observed for the system
but not for the -amino acid control (), indicating that the Pt-drug
is being released from the nanocarrier and binding to intracellular
targets. A higher concentration of Pt was observed in 31P-rich ROIs and with respect to 15N enrichment for samples
treated with the responsive nanoparticles, suggesting a specific association
of Pt with 31P-rich structures such as DNA.
Conclusion
This study serves as a demonstration of the potential
of COIN for
the study of nanomaterials in complex biological systems in general
and specifically for EDAPT nanoparticles. Fluorescence microscopy
allowed for the differentiation of cellular structures and compartments
with respect to the nanoparticle utilizing specific fluorescent labels.
NanoSIMS imaging produced data consistent with the retention of the
material in the extracellular space of tumor tissues, revealing the
dissociation of the drug from the nanocarrier. This resulted in greater
drug delivery for enzyme-responsive EDAPT particles than for a nonresponsive
control nanoparticles which were poorly retained. By comparing the
specific localization of the nanocarrier and the drug at the nanometer
scale, we could track the specific association of Pt with the nuclear
DNA of tumor cells from the in vivo sample. This
work establishes COIN as a powerful methodology for tracking nanomaterials
as delivery vehicles, where elucidation of the location of cargo and
carrier at high-resolution is desirable for optimizing and assessing in vivo delivery.
Experimental Section
Polymer
Synthesis
To a stirred solution of N-Mon was added a solution of the catalyst
((IMesH2)(C5H5N2)(Cl)2Ru=CHPh) in dry DMF and a solution
of Pt-Mon in dry DMF. The reaction was allowed to stir
under N2 for 2 h, after which an aliquot was removed and
quenched with ethyl vinyl ether for SLS analysis. The remaining solution
of N-Mon + Pt-Mon + catalyst was split into two separate reaction vessels. To one
reaction vessel was added a solution of in dry DMF (to ultimately afford ). To the second vessel was added a solution of in dry DMF (to ultimately afford ). After three additional hours, a small aliquot
was removed from each reaction vessel and terminated with ethyl vinyl
ether for SLS analysis. Then, to each of the polymer solutions was
added Cy-Mon and reaction was allowed to stir for an
additional 2 h, before the polymer solutions were fully quenched with
ethyl vinyl ether. The fully terminated polymers were precipitated
with a cold 1:1 ether/methanol solution to afford the block copolymers
as dark yellow solids (, ).
Nanoparticle Preparation.
(L-Pep-Pt-NP and D-Pep-Pt-NP)
Polymers ( or ) were
dissolved in DMSO, and DPBS (Dulbecco’s phosphate buffered
saline, no Ca, no Mg) was added over the course of 2 h. These solutions
were transferred to 3500 MWCO snakeskin dialysis tubing and dialyzed
against DPBS at pH 7.4 over 2 days with two buffer changes.
Intratumoral
Efficacy
Tumor-bearing nu/nu female mice
were randomly sorted into four groups (four mice per cohort) and treated
with , , oxaliplatin, or saline at the dosage equivalent
of 2.5 mg/kg of Pt as a single IT injection. Mouse weight and tumor
volume were recorded once daily over the course of the 12-day study.
Animals were imaged at 0, 4, 24, 48, and 72 h postinjection via live-animal
optical imaging. To assess efficacy, relative tumor volume was calculated
for each data point. The average relative tumor volume of each cohort
at each time point was then calculated, along with standard deviation
and standard error of mean. Animals were sacrificed at 12 days postinjection.
The tumor was excised from each animal and treated as in the above
protocol.
Fluorescent IHC Staining of Tissue Sections
Tissue
sections on a 18 mm2 ITO coverslip were fixed with acetone
at room temperature and washed three times with PBSt (0.05% Tween
in PBS). Sections were incubated with blocking solution. The primary
antibody mouse anti-α-actinin was added in blocking buffer and
incubated at 4 °C overnight. Tissues were washed three times
with PBSt, and the secondary antibody goat antimouseAlexaFluor 488
was added in blocking buffer and incubated for 30 min. Tissue sections
were washed three times with PBSt and were incubated for 10 min with
DAPI. The tissue sections were finally washed three times with PBSt
and then subjected to a series of dehydration washes with 30%, 50%,
70%, 80% ethanol solutions and three times with 100% ethanol (30 min
each).
Structural Illumination Microscopy Imaging
SIM imaging
was performed on the Elyra S1 inverted fluorescence microscope (Zeiss).
An objective with 10× and 40× magnification and 1.4 numerical
aperture and an oil immersion objective with 100× magnification
and 1.4 numerical aperture were used in this study. Three rotations
and five phases were taken for each SIM image. The pixel size in the
raw images was 80 nm per pixel, and in the resulting super resolution
images was 40 nm per pixel. The camera exposure time was 100 ms per
image. For every sample, three tracks were recorded sequentially for
(1) image the NPs (Cy5.5) using 642 nm wavelength at 7 mW power laser
excitation and emission wavelength longer than 655 nm; (2) image the
actin filaments (α-actinin) using 488 nm at 2 mW laser excitation
and emission band 495 to 550 nm; and (3) image the nucleus (DAPI)
using 405 nm 2 mW laser excitation and emission band 420–480
nm. These tracks were later processed to obtain super resolution images
using the ZEN software (Zeiss).
NanoSIMS Imaging
For the NanoSIMS analyses, the samples
were coated with 10 nm of Au prior to analysis to minimize sample
charging. Samples were presputtered with about 2 × 1016 ions cm–2 after which, images sized 48 μm
× 48 μm containing 256 pixel × 256 pixel were acquired
with a 16 keV ∼1.5 pA Cs+ primary ion beam (diameter
∼115 nm) using magnetic peak switching, where in the first
two planes, 12C14N–, 31P–, and 195Pt– were collected (13.5 ms/pixel). After the first two planes, the
detector collecting 12C14N was moved to collect 12C15N– , and in the second analysis,
two consecutive planes collecting 12C15N–, 31P–, and 195Pt– were acquired. Image data were processed using
OpenMIMS (National Resource for Imaging Mass Spectrometry, Harvard
University, Cambridge), which is an ImageJ plugin (U.S. National Institutes
of Health, Bethesda, Maryland) in which pixel by pixel deadtime and
QSA corrections were applied. Data from ROIs were further processed
in a spreadsheet. 15N data were normalized with respect
to air by analyzing a yeast standard daily (see Supporting Information). There appeared to be a minor interference
associated with 195Pt as evidenced by a small background;
however, Pt treated cells had hotspots that were significantly higher
in Pt than background.
SIM and NanoSIMS Correlation
NanoSIMS
images were transformed
using Matlab software to correlate with SIM images acquired on identical
areas. Thus, all three signals observed on SIM images can be correlated
with the eight acquired NanoSIMS images representing different ion
maps.
NanoSIMS Data Statistical Analysis
The first step of
NanoSIMS data processing involved correcting the counts obtained for 15N and 14N with the yeast standard, which was measured
each day before any of the samples. The yeast standard has a known
δ15N value of ∼0.34 ‰ relative to air.
That daily correction factor was applied to all the 15N
enrichment data obtained for the tissue samples. Those were called
“corrected 15N enrichment values”. ROIs counts
(as a ratio counts/area) were averaged for the different groups, leaving
out of the average of outliers (values higher or lower than IQR*1.5).
Additional statistical analyses were performed with Graphpad software
and these values were used to compare bars on graphs in Figure in the main text. The results
of unpaired t-tests are shown in Table S3.
Authors: Giulia Battistelli; Maria Proetto; Alexandra Mavridi-Printezi; Matteo Calvaresi; Alberto Danielli; Paolo Emidio Constantini; Claudia Battistella; Nathan C Gianneschi; Marco Montalti Journal: Chem Sci Date: 2022-03-10 Impact factor: 9.969
Authors: Marco S Messina; Kathryn M M Messina; Arvind Bhattacharya; Hayden R Montgomery; Heather D Maynard Journal: Prog Polym Sci Date: 2019-11-18 Impact factor: 29.190
Authors: Cuiwen He; Michael T Migawa; Kai Chen; Thomas A Weston; Michael Tanowitz; Wenxin Song; Paul Guagliardo; K Swaminathan Iyer; C Frank Bennett; Loren G Fong; Punit P Seth; Stephen G Young; Haibo Jiang Journal: Nucleic Acids Res Date: 2021-01-11 Impact factor: 16.971
Authors: Anton A Legin; Arno Schintlmeister; Nadine S Sommerfeld; Margret Eckhard; Sarah Theiner; Siegfried Reipert; Daniel Strohhofer; Michael A Jakupec; Mathea S Galanski; Michael Wagner; Bernhard K Keppler Journal: Nanoscale Adv Date: 2020-11-26