Kristel Sepp1,2, Martin Lee1, Marie T J Bluntzer2, G Vignir Helgason3, Alison N Hulme2, Valerie G Brunton1. 1. Edinburgh Cancer Research UK Centre, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XR, U.K. 2. EaStCHEM School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Road, Edinburgh EH9 3FJ, U.K. 3. Wolfson Wohl Cancer Research Centre, Institute of Cancer Sciences, University of Glasgow, Garscube Estate, Glasgow G61 1QH, U.K.
Abstract
Stimulated Raman scattering (SRS) microscopy represents a powerful method for imaging label-free drug distribution with high resolution. SRS was applied to image label-free ponatinib with high sensitivity and specificity in live human chronic myeloid leukemia (CML) cell lines. This was achieved at biologically relevant, nanomolar concentrations, allowing determination of ponatinib uptake and sequestration into lysosomes during the development of acquired drug resistance and an improved understanding of target engagement.
Stimulated Raman scattering (SRS) microscopy represents a powerful method for imaging label-free drug distribution with high resolution. SRS was applied to image label-free ponatinib with high sensitivity and specificity in live humanchronic myeloid leukemia (CML) cell lines. This was achieved at biologically relevant, nanomolar concentrations, allowing determination of ponatinib uptake and sequestration into lysosomes during the development of acquired drug resistance and an improved understanding of target engagement.
Despite the identification of an unprecedented
number of potential new drug targets over the past two decades, and
an accompanying intense investment in the generation of NCEs with
improved potency and selectivity, currently only 1 in 10 clinical
candidates progresses to regulatory approval.[1] This major loss in investment by drug developers can be analyzed
from the viewpoint of the physicochemical properties of drug candidates,[2] but these studies do not provide clear indicators
for how to reduce attrition rates.[3] Some
of the highest pipeline attrition rates are seen in the development
of chemotherapeutics.[4] As a plethora of
new, targeted chemotherapeutics enter the clinic and, with the development
of resistance to these agents, alternative approaches are urgently
required to optimize their development and use. A shift toward determining
critical information through the use of relevant cell-based assays
at an earlier stage in the pipeline[5] could
result in a much cheaper and more effective development process.[6]Stimulated Raman scattering (SRS) microscopy
generates image contrast using the Raman active vibrational frequency
of a given chemical bond, providing information on the biochemical
composition of tissues and allowing label-free visualization for a
number of biomedical applications including drug interactions.[7,8] SRS is distinguished by a number of key features:Fast acquisition
speeds (orders of magnitude faster than those achieved with spontaneous
Raman), good photostability, and a lack of phototoxicity, which together
allow real-time imaging.A linear relationship between signal intensity and chemical concentration,
which enables quantitative imaging.Multiple acquisition wavelengths, which allows drug
distribution within cells to be mapped onto subcellular features providing
intracellular registration.Multimodal imaging (SRS and fluorescence), which allows image overlay
with cell- or tissue-specific markers.[9,10]Combined, these characteristics ensure that SRS imaging
provides a unique platform to understand drug distribution within
individual cells, thus distinguishing it from other technologies,
such as whole-body autoradiography and liquid chromatography–mass
spectrometry (LC-MS), that are typically used to monitor drug distribution.[11,12]Raman imaging was initially developed as a label-free technique
for visualization of biomolecules including lipids and proteins, and
more recently the development of alkynes (C≡C) as nonlinear
vibrational tags for imaging small biomolecules using SRS microscopy
has extended the applicability of this approach.[13,14] Alkynes are both chemically and Raman spectroscopically biorthogonal
as they do not react with endogenous biomolecules and do not exist
inside cells. The C≡C stretching motion can hence be detected
in the Raman “cellular-silent” region (1800–2800
cm–1). This also presents an optimal region for
drug imaging, as there is minimal contribution from endogenous cellular
biomolecules, thus improving detection sensitivity.[8,15] In
this study, we utilize the advantages of an alkyne-based imaging approach
to assess label-free drug uptake and distribution in cellular models
of resistance using ponatinib (1),[16] a tyrosine kinase inhibitor with regulatory approval for
the treatment of chronic myeloid leukemia.
Results and Discussion
Ponatinib (1) has an inherent alkyne moiety in its
structure providing the potential for imaging its cellular localization
in the Raman “cellular-silent” region (Figure a,b), without the addition
of bulky tags such as fluorophores, which can negatively impact on
the biological activity of drugs. In SRS, two synchronized lasers,
the pump and the Stokes beam are used to excite a specific molecular
vibration (Figure c). To visualize a chemical bond of interest, the frequency difference
between the pump beam and the Stokes beam is tuned to match the chosen
vibration (ωυ), allowing stimulated Raman scattering
to take place in addition to the inherently weak spontaneous Raman
scattering.
Figure 1
(a) Chemical structure of ponatinib; (b) Raman spectrum of solid
ponatinib. The following peak has been annotated: 2221 cm–1 (C≡C, ponatinib). Raman spectra were acquired at λex = 532 nm for 10 s using a 50× objective. (c) Energy
level diagram showing the working principle of SRS microscopy.
(a) Chemical structure of ponatinib; (b) Raman spectrum of solid
ponatinib. The following peak has been annotated: 2221 cm–1 (C≡C, ponatinib). Raman spectra were acquired at λex = 532 nm for 10 s using a 50× objective. (c) Energy
level diagram showing the working principle of SRS microscopy.
Predicting the Intensity and Frequency of Raman Signals by DFT
Density functional theory (DFT) calculations have previously been
used to predict theoretical Raman intensities (IRam),[8,15] while experimentally observed
Raman intensities have been compared with the intensity of the alkyne
resonance in the nucleoside analogue ethynyl deoxyuridine (EdU) to
give relative intensity to EdU (RIE) values.[17] We have combined these two approaches to give a series of calculated
RIE values (cRIE) to facilitate comparison of the predicted intensity
values for signals in the “cellular-silent” region.
DFT calculations have also, very recently been used to predict the
changes in Raman vibrational frequencies that result from primary
drug metabolism.[18] Thus, we have used a
series of DFT calculations
to establish whether the acquisition of SRS images at a single vibrational
frequency for the alkyne (Figure b, C≡C, 2221 cm–1) would provide
an accurate assessment of the ponatinib concentration within a cell
(Supporting Information (SI), Table S1).The piperidine unit in ponatinib means that it is susceptible to
lysosomal trapping through protonation.[19,20] However, in
our DFT calculations, both the parent drug and its protonated counterpart
were predicted to have very similar frequencies for the alkyne resonance,
with a slight decrease in cRIE value upon protonation (SI, Table S1). Hence, it was determined that
SRS imaging at a single wavenumber would allow assessment of ponatinib
concentrations across the whole cell environment, independent of subcellular
variations in pH. Previous studies have identified the primary metabolites
of ponatinib as its N-oxide and N-desmethyl analogues, together with dihydroxylated forms.[21−23] As the chemical perturbations in these two major metabolites is
distal to the alkyne vibrational motif, a large change in IRam is not expected. This conclusion was confirmed
by DFT calculations (SI, Table S1), which
show similar cRIE values to the parent drug, with only minimal shifts
in the predicted Raman frequencies for the alkyne absorption. The
formation of these metabolites has been shown to be catalyzed predominantly
by the P450 enzyme CYP3A4.[23,24] Western blot analysis
confirmed expression of CYP3A4 protein in both KCL22 and KCL22Pon-Res cells (Figure a). However, we identified ponatinib as the predominant
peak by LC-MS analysis with only trace amounts of the N-desmethyl and dihydroxylated metabolites present in the CML cells
(Figure b).
Figure 2
(a) Expression
of CYP3A4 in lysates from KCL22 and KCL22Pon-Res cells. β-actin was used as a loading control. (b) Ponatinib
and ponatinib metabolites identified by LC-MS. Cells were treated
with ponatinib for 1 h prior to analysis. Mean values from five biological
repeats expressed relative to ponatinib.
(a) Expression
of CYP3A4 in lysates from KCL22 and KCL22Pon-Res cells. β-actin was used as a loading control. (b) Ponatinib
and ponatinib metabolites identified by LC-MS. Cells were treated
with ponatinib for 1 h prior to analysis. Mean values from five biological
repeats expressed relative to ponatinib.Thus, given the relatively low concentrations of these metabolites
in the CML cell lines, and the minimal shifts in their predicted Raman
frequencies, their presence is not expected to affect SRS imaging
of the intracellular distribution of ponatinib. This conclusion is
in sharp contrast to recent imaging studies conducted on neratinib
using Raman microscopy, where metabolism directly affects the Raman
active motif in the drug and significant vibrational shifts are observed.[18]
Applications of SRS Imaging of Intracellular
Drug Concentrations
With the validity of imaging the alkyne
in ponatinib by Raman to assess its intracellular distribution established,
we conducted a series of experiments to demonstrate the utility of
this approach experimentally. CML results from expression of the constitutively
active tyrosine kinaseBCR-ABL and treatment with TKIs, such as ponatinib,
which target BCR-ABL, have been successful in providing improved life
expectancy, although resistance prevents long-term durable responses
in many patients.[25] There is currently
no information on the subcellular distribution and uptake of TKIs
in the context of drug resistance, and here we demonstrate the utility
of SRS for label-free live cell imaging of ponatinib in a model of
ponatinib resistance.
Direct Imaging of Ponatinib
at Biologically Relevant Doses
In a recent study, spontaneous
Raman imaging of the intense fingerprint peak for the TKI neratinib
(1386 cm–1) allowed visualization of the drug following
incubation at nanomolar concentrations; however, this process requires
extended acquisition times (>30 min) using fixed cells.[18] In contrast, SRS microscopy enables up to video-rate
imaging speed, allowing live cell imaging. Hyperspectral SRS imaging,
which enables drug signals in the fingerprint region to be extracted
from the cellular signals, can also been used to follow drug uptake
into cells, although as yet this requires incubation with micromolar
concentrations of analyte and successful imaging is dependent on 1000-fold
enrichment of drugs into lysosomes.[9] The
detection sensitivity is the major limitation of intracellular imaging
using SRS, with the micromolar concentrations required to detect the
molecule of interest often not being physiologically relevant.[9,10,13,14,26] To determine whether we could use SRS to
visualize ponatinib at biologically active concentrations, we chose
a concentration of ponatinib (500 nM), which is close to the GI50 for humanKCL22Pon-Res CML cells (SI, Table S2). The KCL22Pon-Res cells are a ponatinib-resistant cell line that was generated to
understand the drivers of resistance to ponatinib, as resistance to
ponatinib is a recognized clinical problem.[27]Cells were treated with ponatinib (500 nM) for up to 48 h
prior to live cell imaging using a custom built SRS microscope,[28] where optimal setup resulted in acquisition
speeds of around 45 s per image. Images were acquired by tuning the
frequency difference between the pump and Stokes lasers to be resonant
with ponatinib (C≡C, 2221 cm–1, SI, Figure S1) or intracellular proteins (CH3, 2940 cm–1) to provide cellular registration
(Figure a,b). SRS
images can contain background signals from competing pump–probe
processes such as cross-phase modulation, transient absorption, and
photothermal effects.[29] When the signal-to-noise
(S/N) ratio of the SRS image of the drug is low, these background
artifacts can be subtracted to remove the unwanted processes from
the image. This can be achieved by changing the pump wavelength by
a few nanometers, which allows off-resonance images to be acquired
(at a difference of 10–30 cm–1 from the on-resonance
image). This difference image can be used to distinguish true SRS
signals from these artifacts (Figure c).[30] When imaging with
drug concentrations over 5 μM, the SRS S/N is sufficiently high
that subtraction is not necessary to visualize ponatinib within the
cell (see Figure a–c).
Figure 3
(a–c)
Imaging ponatinib uptake in KCL22Pon-Res cells.
KCL22Pon-Res cells were treated with DMSO (0.0003%,
v/v) or ponatinib (500 nM) for 1, 6, 24, or 48 h (left to right).
SRS images acquired at (a) 2940 cm–1 (CH3, proteins); (b) 2221 cm–1 (C≡C, ponatinib);
(c) 2257 cm–1 (off-resonance). Images acquired at
1024 × 1024 pixels, 20 μs pixel dwell time, laser power
p300, gain 2 with false colors applied to different detection wavenumbers.
Scale bars: 10 μm. (d) Mean ponatinib intensity per cell quantified
from 2221 cm–1 in n = 30 cells,
three biological repeats. The Mann–Whitney test was used to
compare ponatinib Raman intensity values against the DMSO control.
Figure 4
Multimodal imaging and quantitative assessment of ponatinib
uptake in KCL22 and KCL22Pon-Res cell lines. KCL22
cells were treated with (a) DMSO (0.0003%, v/v) or (b) ponatinib (5
μM, 1 h). KCL22 Pon-Res cells were treated
with (c) ponatinib (5 μM ponatinib, 1 h). SRS images acquired
at (from left to right) 2940 cm–1 (CH3, proteins), 2221 cm–1 (C≡C, ponatinib),
2257 cm–1 (off-resonance), TPF image acquired at
861 nm (Lysotracker Green), overlay of ponatinib and TPF. (d) Mean
ponatinib Raman intensity. (e) Maximum ponatinib Raman intensity inside
the vesicles of each individual cell quantified for KCL22 and KCL22Pon-Res cells that were treated with 5 μM ponatinib
for 1 h, n = 30 cells, three biological repeats.
(f) Mean ponatinib Raman intensity quantified outside of the vesicles
of individual cells, n = 10, three biological repeats.
Images acquired at 1024 × 1024 pixels, 20 μs pixel dwell
time, laser power p200 gain 1 with false colors applied to different
detection wavenumbers. Scale bars: 10 μm. The Mann–Whitney
test was used to compare ponatinib Raman intensity values, ***p < 0.0001.
(a–c)
Imaging ponatinib uptake in KCL22Pon-Res cells.
KCL22Pon-Res cells were treated with DMSO (0.0003%,
v/v) or ponatinib (500 nM) for 1, 6, 24, or 48 h (left to right).
SRS images acquired at (a) 2940 cm–1 (CH3, proteins); (b) 2221 cm–1 (C≡C, ponatinib);
(c) 2257 cm–1 (off-resonance). Images acquired at
1024 × 1024 pixels, 20 μs pixel dwell time, laser power
p300, gain 2 with false colors applied to different detection wavenumbers.
Scale bars: 10 μm. (d) Mean ponatinib intensity per cell quantified
from 2221 cm–1 in n = 30 cells,
three biological repeats. The Mann–Whitney test was used to
compare ponatinib Raman intensity values against the DMSO control.Multimodal imaging and quantitative assessment of ponatinib
uptake in KCL22 and KCL22Pon-Res cell lines. KCL22
cells were treated with (a) DMSO (0.0003%, v/v) or (b) ponatinib (5
μM, 1 h). KCL22 Pon-Res cells were treated
with (c) ponatinib (5 μM ponatinib, 1 h). SRS images acquired
at (from left to right) 2940 cm–1 (CH3, proteins), 2221 cm–1 (C≡C, ponatinib),
2257 cm–1 (off-resonance), TPF image acquired at
861 nm (Lysotracker Green), overlay of ponatinib and TPF. (d) Mean
ponatinib Raman intensity. (e) Maximum ponatinib Raman intensity inside
the vesicles of each individual cell quantified for KCL22 and KCL22Pon-Res cells that were treated with 5 μM ponatinib
for 1 h, n = 30 cells, three biological repeats.
(f) Mean ponatinib Raman intensity quantified outside of the vesicles
of individual cells, n = 10, three biological repeats.
Images acquired at 1024 × 1024 pixels, 20 μs pixel dwell
time, laser power p200 gain 1 with false colors applied to different
detection wavenumbers. Scale bars: 10 μm. The Mann–Whitney
test was used to compare ponatinib Raman intensity values, ***p < 0.0001.We analyzed the ponatinib
Raman signal intensity (C≡C, 2221 cm–1) per
cell in a population (n = 30) at each time point
and compared it to the values of DMSO treated control cells. At each
time point, there was a significant increase in Raman signal compared
to the control cells, indicating intracellular accumulation of ponatinib
(Figure d). Ponatinib
puncta formed in the cells from 6 h onward, with the largest number
of puncta in cells at 24 and 48 h (Figure d). This demonstrates that SRS can be used
to image live cells treated with biologically relevant doses without
the need for any additional labeling or fixation. Many TKIs, including
ponatinib (Figure b), have strong Raman bands in the cellular fingerprint region, and
if one of these bands is sufficiently strong, it can also be used
for visualization, as has been demonstrated for neratinib using spontaneous
Raman.[18]
Determination
of the Intracellular Localization of Ponatinib
As ponatinib
was concentrated in puncta in the cytoplasm of the cells, it was important
to consider which cellular organelles these were, as the known target
of ponatinib is the cytoplasmic tyrosine kinaseBCR-ABL. Knowing that
ponatinib is a weakly basic drug with a pKa value greater than eight (pKa1 = 11.4, pKa2 = 8.0)[31] and hence is likely to be protonated in acidic
environments, we predicted that it would accumulate in lysosomes or
related acidic organelles in the cell. A multimodal imaging approach
was used to explore this. Cells were simultaneously incubated with
ponatinib (5 μM, 1 h) or DMSO (vehicle control, 1 h) and Lysotracker
Green (50 nM, 1 h), a cell-permeable fluorescent dye that stains acidic
organelles in live cells (Figure ). Cells treated with DMSO and stained with Lysotracker
Green (Figure a) showed
no SRS signal at 2221 cm–1 (C≡C, ponatinib
on-resonance), indicating that the presence of the fluorophore does
not give a background SRS signal. In cells treated with ponatinib
(Figure b,c), we could
see colocalization between the SRS signal at 2221 cm–1 and the two-photon fluorescence (TPF) signal shown in the merged
images, with evidence of lower levels of ponatinib in the cytoplasm,
which did not colocalize with the TPF signal. This demonstrates that
the majority of ponatinib is trapped within acidic organelles, most
likely lysosomes, upon protonation.There is evidence that lysosomal
trapping plays a role in resistance to TKIs by sequestering them away
from their intracellular targets and thereby reducing target engagement.[32] Using the TPF signal as a map, the ponatinib
Raman intensity was quantified in individual cells which showed an
increased ponatinib Raman signal in the resistant KCL22Pon-Res cells compared to parental KCL22 cells (Figure d,e). The mean intensity of ponatinib was
increased 1.9-fold in the KCL22Pon-Res cells compared
to parental KCL22 cells (Figure d), and the maximum ponatinib signal had increased
2.5-fold (Figure e).
There was also a significant increase in the ponatinib signal within
the cytoplasm of the resistant cells (Figure f).To determine whether differences
in lysosomal pH in the cell lines could be contributing to the increased
accumulation of ponatinib in the KCL22Pon-Res cells
we used Lysosensor Green, a dye whose fluorescence increases in acidic
environments. There was no significant difference in Lysosensor Green
signal between the KCL22 and KCL22Pon-Res cells
(SI, Figure S2a,b). However, we did see
an increase in expression of the lysosomal marker LAMP1 in the KCL22Pon-Res cells (SI, Figure S2c,d), indicative of increased lysosome number or lysosome size. To establish
whether lysosome biogenesis was differentially regulated in the resistant
cells at a transcriptional level, we looked at nuclear transcription
factor EB (TFEB), which is a master regulator of lysosome biogenesis.[33] There was a significant increase in nuclear
TFEB in the KCL22Pon-Res cells (SI, Figure S2e,f), indicative of increased lysosome biogenesis
in the resistant cells. This may reflect adaptation of the resistant
cells to allow them to respond to lysosomal stress.
Using SRS Imaging to Enhance Target Engagement Studies
To
investigate the importance of lysosomal trapping on ponatinib–target
engagement, we used chloroquine (CQ), which is a nonspecific autophagy
inhibitor that acts as a lysosomotropic agent, increasing lysosomal
pH and ultimately preventing fusion of autophagosomes and lysosomes.
It was hypothesized that chloroquine treatment could be used to prevent
the increased lysosomal uptake of ponatinib. Pretreatment of KCL22
and KCL22Pon-Res cells with CQ (20 μM, 2 h)
prior to treatment with ponatinib (5 μM, 1 h) significantly
reduced the ponatinib Raman signal in both cell lines (Figure b–e)
Figure 5
Multimodal imaging and
quantitative assessment of the effect of chloroquine treatment on
the vesicular uptake of ponatinib. KCL22 and KCL22Pon-Res cells were treated with (a) ponatinib (5 μM, 1 h), (b) chloroquine
(20 μM, 2 h) followed by combination treatment of ponatinib
(5 μM, 1 h) and chloroquine (20 μM, 1 h). Images shown
(left to right) 2221 cm–1 (C≡C, ponatinib),
overlay TPF image at 861 nm (Lysotracker Green) merged with 2221 cm–1. (c,d) Mean ponatinib Raman intensity inside the
vesicles of each individual cell quantified in (c) KCL22 and (d) KCL22Pon-Res cell line, n = 10 cells, three
biological repeats. Images acquired at 1024 × 1024 pixels, 20
μs pixel dwell time with false colors applied to different detection
wavenumbers. Scale bars: 10 μm. (e,f) p-CRKL level quantification
from Western blots where KCL22 and KCL22Pon-Res cells
were treated with (left to right) either DMSO (0.0003%, v/v), ponatinib
(10, 100, 500 nM, 1 h), or a combination of chloroquine (20 μM,
2 h) pretreatment and ponatinib (10, 100, or 500 nM, 1 h). p-CRKL
level was quantified against α-tubulin control and normalized
to DMSO using Image Lab Software. One-Way ANOVA (Tukey’s multiple
comparisons test) was used to compare ponatinib (10 nM) alone vs CQ
combination treatment.
Multimodal imaging and
quantitative assessment of the effect of chloroquine treatment on
the vesicular uptake of ponatinib. KCL22 and KCL22Pon-Res cells were treated with (a) ponatinib (5 μM, 1 h), (b) chloroquine
(20 μM, 2 h) followed by combination treatment of ponatinib
(5 μM, 1 h) and chloroquine (20 μM, 1 h). Images shown
(left to right) 2221 cm–1 (C≡C, ponatinib),
overlay TPF image at 861 nm (Lysotracker Green) merged with 2221 cm–1. (c,d) Mean ponatinib Raman intensity inside the
vesicles of each individual cell quantified in (c) KCL22 and (d) KCL22Pon-Res cell line, n = 10 cells, three
biological repeats. Images acquired at 1024 × 1024 pixels, 20
μs pixel dwell time with false colors applied to different detection
wavenumbers. Scale bars: 10 μm. (e,f) p-CRKL level quantification
from Western blots where KCL22 and KCL22Pon-Res cells
were treated with (left to right) either DMSO (0.0003%, v/v), ponatinib
(10, 100, 500 nM, 1 h), or a combination of chloroquine (20 μM,
2 h) pretreatment and ponatinib (10, 100, or 500 nM, 1 h). p-CRKL
level was quantified against α-tubulin control and normalized
to DMSO using Image Lab Software. One-Way ANOVA (Tukey’s multiple
comparisons test) was used to compare ponatinib (10 nM) alone vs CQ
combination treatment.Quantification of ponatinib
signal inside lysosomes demonstrated that CQ treatment reduced mean
ponatinib concentration in the lysosomes 2.7- and 3.8-fold in the
KCL22 and KCL22Pon-Res cells, respectively, compared
to ponatinib alone (Figure c,d). To determine whether the inhibition of autophagy by
CQ also contributed to the reduced lysosomal accumulation of ponatinib,
we used KCL22Pon-Res CRISPR-ATG7 knockout cells. ATG7 is a critical autophagy regulator and KCL22Pon-Res CRISPR-ATG7 cells have a defect
in the autophagy pathway. KCL22Pon-Res CRISPR-ATG7
and KCL22Pon-Res CRISPR-Control cells were simultaneously
treated with ponatinib (5 μM, 1 h) and labeled with Lysotracker
(50 nM, 1 h) before live imaging using SRS (SI, Figure S3). Quantification of relative concentrations of ponatinib
by Raman intensity in individual cells of both cell lines demonstrated
no significant difference between the cell lines, demonstrating that
autophagy does not play a role in ponatinib accumulation in lysosomes.
Therefore, reduction of ponatinib concentration in lysosomes upon
CQ combination treatment was likely due to the lysosomotropic properties
of CQ, which decreased the ability of ponatinib to accumulate in the
lysosomes.Having found that CQ treatment significantly decreased
lysosomal trapping of ponatinib in both cell lines, we looked at how
this affected BCR-ABL inhibition. BCR-ABL is a cytosolic tyrosine
kinase and phosphorylation of CRKL (Tyr207), a direct BCR-ABL substrate,
was used as a surrogate for BCR-ABL activity. Pretreatment with CQ
significantly increased p-CRKL inhibition at the lowest 10 nM ponatinib
dose (Figure e,f,
and SI, Figure S4). Thus, the reduced lysosome
trapping of ponatinib in the CQ treated cells increased BCR-ABL inhibition.
Interestingly, we saw a greater inhibition of pCRKL phosphorylation
in the KCL22Pon-Res cells than in KCL22ponatinib
sensitive cells which correlates with the increased cytoplasmic levels
of ponatinib in the resistant cells (Figure f) and supports a BCR-ABL independent mechanism
of ponatinib resistance.[26] This is in contrast
to the BCR-ABL dependent resistance to other basic TKIs such as imatinib
that are used in the treatment of CML, where CQ can increase target
engagement with combined CQ and TKI treatments resulting in enhanced
efficacy.[9,34]
Conclusions
This
study demonstrates the benefits of SRS microscopy in providing real-time
measurements of drug distribution in live cells with high sensitivity
and resolution. Use of SRS microscopy has allowed label-free imaging
of the TKI ponatinib at biologically relevant concentrations and provided
insight into changes in uptake and sequestration of drug that has
occurred during the development of acquired drug resistance. We show
that tuning the pump wavelength to the alkyne stretch within ponatinib
allows SRS imaging within the Raman cellular-silent region following
treatment with nanomolar concentrations of ponatinib. Although imaging
within the cell silent region increases sensitivity, the recent demonstration
that Raman imaging of drugs may also be achieved in the fingerprint
region when the drug is enriched in subcellular locales, opens up
the possibility of label-free imaging for a wider number of drug candidates
and metabolites.[9,16] Furthermore, the addition of
small alkyne tags or deuterium substitutions to enable SRS imaging
of drugs and small molecules in the cellular-silent region with increased
sensitivity, further extends the potential for this technology to
provide read-outs of drug kinetics and mechanism of action.[10,17,35,36] Combined with DFT calculations and LC-MS measurements, SRS imaging
could be transformative to the drug discovery pipeline by providing
important information on drug localization, mechanism of action, and
target engagement.
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