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Exploiting heat shock protein expression to develop a non-invasive diagnostic tool for breast cancer


Abstract and Figures

Leveraging the unique surface expression of heat shock protein 90 (Hsp90) in breast cancer provides an exciting opportunity to develop rapid diagnostic tests at the point-of-care setting. Hsp90 has previously been shown to have elevated expression levels across all breast cancer receptor subtypes. We have developed a non-destructive strategy using HS-27, a fluorescently-tethered Hsp90 inhibitor, to assay surface Hsp90 expression on intact tissue specimens and validated our approach in clinical samples from breast cancer patients across estrogen receptor positive, Her2-overexpressing, and triple negative receptor subtypes. Utilizing a pre-clinical biopsy model, we optimized three imaging parameters that may affect the specificity of HS-27 based diagnostics – time between tissue excision and staining, agent incubation time, and agent dose, and translated our strategy to clinical breast cancer samples. Findings indicated that HS-27 florescence was highest in tumor tissue, followed by benign tissue, and finally followed by mammoplasty negative control samples. Interestingly, fluorescence in tumor samples was highest in Her2+ and triple negative subtypes, and inversely correlated with the presence of tumor infiltrating lymphocytes indicating that HS-27 fluorescence increases in aggressive breast cancer phenotypes. Development of a Gaussian support vector machine classifier based on HS-27 fluorescence features resulted in a sensitivity and specificity of 82% and 100% respectively when classifying tumor and benign conditions, setting the stage for rapid and automated tissue diagnosis at the point-of-care.
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Exploiting heat shock protein
expression to develop a non-
invasive diagnostic tool for
breast cancer
Brian T. Crouch1, Jennifer Gallagher2, Roujia Wang1, Joy Duer3, Allison Hall4, Mary Scott Soo5,
Philip Hughes6, Timothy Haystead6 & Nirmala Ramanujam1,6
Leveraging the unique surface expression of heat shock protein 90 (Hsp90) in breast cancer provides an
exciting opportunity to develop rapid diagnostic tests at the point-of-care setting. Hsp90 has previously
been shown to have elevated expression levels across all breast cancer receptor subtypes. We have
developed a non-destructive strategy using HS-27, a uorescently-tethered Hsp90 inhibitor, to assay
surface Hsp90 expression on intact tissue specimens and validated our approach in clinical samples
from breast cancer patients across estrogen receptor positive, Her2-overexpressing, and triple negative
receptor subtypes. Utilizing a pre-clinical biopsy model, we optimized three imaging parameters that
may aect the specicity of HS-27 based diagnostics – time between tissue excision and staining, agent
incubation time, and agent dose, and translated our strategy to clinical breast cancer samples. Findings
indicated that HS-27 orescence was highest in tumor tissue, followed by benign tissue, and nally
followed by mammoplasty negative control samples. Interestingly, uorescence in tumor samples was
highest in Her2+ and triple negative subtypes, and inversely correlated with the presence of tumor
inltrating lymphocytes indicating that HS-27 uorescence increases in aggressive breast cancer
phenotypes. Development of a Gaussian support vector machine classier based on HS-27 uorescence
features resulted in a sensitivity and specicity of 82% and 100% respectively when classifying tumor
and benign conditions, setting the stage for rapid and automated tissue diagnosis at the point-of-care.
Breast cancer management represents a complicated landscape, with therapy regimens often including a
mélange of chemotherapy, radiation therapy, and surgical procedures. Unfortunately, low to middle income
countries (LMICs), which shoulder most of the total breast cancer burden1, oen do not have the resources
to perform standard-of-care treatments, leading to higher mortality rates2. Moreover, access barriers to treat-
ment are higher in LMICs, leading to increased time between initial medical consultation and treatment2. In
high-income countries (HICs), when a woman presents with a suspicious lesion on her mammogram, she
undergoes diagnostic biopsy to determine what type of lesion is present by pathological analysis. is strategy
is not adoptable by LMICs, however, due to the scarcity of pathologists. For example, in sub-Saharan Africa the
pathologist-to-population ratio is 50 times less than in HICs at approximately one to one million3. e distinct
lack of reliable access to pathology in LMICs dictates a need for low-cost, automated methods for diagnosing
breast cancer at the point-of-care. Even in HICs there are opportunities to streamline breast cancer care. For
instance, in breast radiology, to ensure complete sampling of the lesion, radiologists currently take anywhere from
4–6 biopsies, which are then sent out for pathologic analysis, a process that can take up to a week. If the lesion was
not successfully sampled, the patient must return for a second set of biopsies, before nally determining diagnosis
and initial treatment. Similarly, in the case of Breast Conserving Surgery, evaluation of resected margins is always
performed post-operatively requiring a patient to come back for re-excision if positive margins are found.
1Department of Biomedical Engineering, Duke University, Durham, NC, USA. 2Department of Surgery, Duke
University Medical Center, Durham, NC, USA. 3Trinity College of Arts and Sciences, Duke University, Durham, NC,
USA. 4Department of Pathology, Duke University Medical Center, Durham, NC, USA. 5Department of Radiology,
Duke University Medical Center, Durham, NC, USA. 6Department of Pharmacology and Cancer Biology, Duke
University Medical Center, Durham, NC, USA. Correspondence and requests for materials should be addressed to
B.T.C. (email:
Received: 19 September 2018
Accepted: 12 February 2019
Published: xx xx xxxx
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ere is an opportunity for a new era of low cost, point of care molecular diagnostics to serve as an eective
alternative to routine pathology. Despite its low specicity for distinguishing breast tumors from benign condi-
tions, portable ultrasound systems are currently being used as a screening tool in lieu of mammography for breast
cancer in LMICs4,5. A number of groups have developed methods to detect extracellular vesicles6 and exosomes7,8
extracted from blood with potential diagnostic applications for pancreatic cancer9 and glioblastoma10,11. Another
example is the adaption of smart phone cameras to be used as microscopes for applications in global health1218.
Combining molecular diagnostics with low cost imaging technologies provides an opportunity to create low-cost,
point-of-carebreast cancer diagnostics for blood samples, cells, and biopsy samples.
Here, we investigated imaging Heat Shock Protein 90 (Hsp90) expression as a molecular diagnostic target
in breast cancer. Hsp90 is a chaperone protein that assists other proteins to fold properly, stabilizes proteins
against stress, and aids in protein degradation19. Hsp90 also stabilizes a number of proteins required for tumor
growth20,21, and is overexpressed in both DCIS and invasive breast cancers2224. Hsp90 is also found on the surface
of many cancer types, including the breast20,25, and this ‘ectopic’ surface expression is specic to tumors21. Hsp90
inhibitors including geldanamycin analogues 17-AAG and 17-DMAG, SNX-5422 and SNX-2112, and others are
currently in clinical trials2629.
We have developed a uorescently-tethered Hsp90 inhibitor, HS-27, made up of the core elements of SNX-
5422, an Hsp90 inhibitor currently in clinical trials, tethered via a PEG linker to a uorescein derivative (uores-
cein isothiocyanate or FITC), that binds to ectopically expressed Hsp90, and demonstrated its potential use in a
see-and-treat paradigm in breast cancer21,30. We found that HS-27 labels all receptor subtypes of breast cancer,
but not normal cells, and specically binds to Hsp90 expressed on the surface of breast cancer cells before being
internalized. IVIS and hyperspectral imaging aer systemic HS-27 injection revealed tumor selective uptake
in a xenogra model, with excised tumor cryosections verifying cellular uptake. We further demonstrated that
HS-27 can be used to treat aggressive Her2+ and triple negative (TNBC) breast cancers by degrading an Hsp90
client protein involved in cell metabolism, down-regulating both glycolytic and oxidative metabolism leading
to decreased cell proliferation. Finally, we demonstrated an ex vivo imaging strategy in clinical models of breast
cancer, showing all receptor subtypes of breast cancer take up HS-27 with increased uorescence from HS-27
corresponding to areas of invasive cancer. HS-27 is a suitable candidate for use in LMICs as it does not require
refrigeration and can be made inexpensively when made to scale.
In this study we focused on optimizing imaging parameters including post-excision window, incubation time,
and agent dose to rapidly translate HS-27 to clinical use by excising murine breast tumors (4T1) and staining
them ex vivo. With optimized imaging parameters of a 1 to 10-minute post-excision window, 1-minute incu-
bation time, and 100 µM dose, we then demonstrated the feasibility of our imaging strategy on standard of care
biopsies from patients presenting with a mammographic lesion, as well as a population of patients undergo-
ing breast reduction mammoplasty to interrogate HS-27 uptake by normal breast tissue. To determine potential
sources of HS-27 uorescence, we investigated correlations between HS-27 uorescence and the density of cancer
or tumor stromal cells to assess whether density of tumor cells and surface Hsp90 expression dictate uorescence
levels. We further examined correlations between HS-27 uorescence and the density of tumor inltrating lym-
phocytes (TILs), a positive prognostic marker in breast cancer, as well as breast cancer receptor subtypes to inves-
tigate whether or not surface Hsp90 is further up-regulated by aggressive tumors. Finally, we employed image
processing methods to extract HS-27 uorescence features to dierentiate tumor from benign tissues.
Optimization of HS-27 incubation parameters for ex vivo imaging. We optimized three distinct
imaging parameters in preclinical studies that could potentially aect the specicity of HS-27 uptake by clinical
samples. e rst parameter we investigated was the time between excision and staining (1, 3, or 10 minutes) to
understand how ectopic Hsp90 expression changes as time between excision and application of the contrast agent
is increased. e second parameter was HS-27 incubation time (1, 5, or 10 minutes), which when increased may
increase non-specic HS-27 diusion into the tissue. Finally, we optimized agent dose (1, 10, 50, or 100 µM) to
round out our investigation. For optimization, the specicity of HS-27 uptake was dened by the ratio of HS-27
(specic signal) to HS-217 (non-specic HS-27 analog signal) uorescence.
Representative uorescence images of HS-27 or HS-217 biopsies from 4T1 murine breast tumors treated
with the optimized parameters, shown in Fig.1a, demonstrate that HS-27 signal is signicantly greater than
non-specic HS-217 signal. Representative images from post-excision window, incubation time, and dose exper-
iments can be found in Supplementary Fig.S1. Curves of HS-27 to HS-217 uorescence ratio fractions (survival
curves dened as 1 minus the cumulative probability), clearly indicate the optimal imaging parameters (Fig.1b–d).
e ratio of HS-27 to HS-217 signal showed no signicant changes when increasing the post-excision window
from 1 to 10 minutes, as shown in Fig.1b. Conversely, Fig.1c shows that increasing agent incubation time from
1 or 5-minutes to 10-minutes signicantly decreased specicity. Finally, 100 µM agent dose showed the greatest
specicity in Fig.1d. For all groups n = 4 biopsies. A 1-minute post-tissue excision time, 1-minute incubation,
and a 100 µM dose were established as the parameters to use in the clinical studies.
HS-27 uorescence is greater in tumor than non-tumor tissue. Next, the protocol we established
in pre-clinical studies was applied to biopsies obtained from patients undergoingultrasound guided core needle
biopsy (USGCNB). Typically the rst biopsy from each patient was imaged to increase the likelihood of obtain-
ing biopsies with cancer. Images were obtained in 1 mm increments along the biopsy prior to inking to ensure
proper orientation for site-level pathology, as previously described30. Representative biopsy images from an ER/
PR-positive tumor, Her2-overexpressing tumor, TNBC, benign lesion (broadenoma), and normal mammoplasty
tissue demonstrate greater HS-27 uorescence in tumor compared to benign and normal tissues as shown in
Fig.2. Histology H&E images from the sites that were imaged are shown below for comparison.
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We next wanted to understand the potential sources of HS-27 uorescence within a biopsy image. ere
are three potential subsets of cell types present within a malignant biopsy – cancer cells, tumor associated stro-
mal cells, and surrounding benign cells. Our pathologist assessed each 1-mm site along the biopsy for percent
tumor area (PTA), tumor cellularity (the percentage of the tumor area made up of cancer cells), and stromal
area (1-tumor cellularity). e density of tumor inltrating lymphocytes (TILs) within the stromal area was also
provided. We began by investigating the relationship between mean HS-27 uorescence and tumor cellularity
and found that there was no correlation between the two endpoints, as shown in Fig.3a. Since tumor cellularity
did not correlate with HS-27 uorescence, we next examined how mean HS-27 uorescence varied with receptor
subtype, as shown in Fig.3b. HS-27 uorescence was highest in Her2+ tumors, followed by TNBC, and ER+.
Next, we looked at how the presence of various tissue types inuenced uorescence. Based on our previous study
suggesting surface Hsp90 is upregulated in particularly aggressive tumors30, we explored the relationship between
HS-27 uorescence and the percent of tumor inltrating lymphocytes (TILs), a positive prognostic factor in
Her2+ and TNBC receptor subtypes3133. Because TILs are given as a percentage of stromal area covered by
TILs, we took the ratio of TIL% to stromal % to provide a more accurate density of TILs in the biopsy. HS-27
uorescence is inversely correlated with increased density of TILs in the tumor stroma across receptor subtypes,
as shown in Fig.3c–e. ese results suggest that receptor subtype and the density of TILs more strongly inuences
the mean uorescence than tumor cellularity.
HS-27 uorescence features accurately distinguish tumor from benign tissue. One of the major
challenges of traditional mammography is the ability to distinguish benign from malignant conditions, hence
the need for biopsies and subsequent histopathology. We wanted to examine whether or not features from HS-27
uorescence images could be used to distinguish benign from malignant tissues and serve as a potential alter-
native for histopathology. Fig.4a shows cumulative distributions (CDFs) of HS-27 uorescence intensity from
the full stitched image for tumor vs. benign vs. mammoplasty tissue. Because many of our lesion images contain
non-lesion regions, we utilized distributions to test cut-o thresholds to include all pixels or only the top 25%,
top 10%, or top 1% of pixels to increase the specicity of HS-27 based diagnostics. Clearly, for the top 1% of
pixels, there is an increase in separation between the curves, reected by decreasing p-values determined from
Kolmogorov-Smirnov (KS) testing. ough not signicant, tumor uorescence is greater than benign across all
bins, and signicantly dierent than mammoplasty control tissues across all bins. Benign is only signicantly
dierent from mammoplasty at the 1% pixel bin level.
Figure 1. A 1 to 10-minute post-excision window, 1-minute incubation time, and 100 µM dose maximizes the
HS-27 to HS-217 specicity ratio. 4T1 tumors were biopsied and incubated in either 100 µM HS-27 or 100 µM
HS-217 for 1-minute either 1-minute, 3-minutes, or 10-minutes post biopsy prior to uorescence imaging to
identify the optimal post-excision window, or 1-minute post excision for 1-minute, 5-minutes, or 10-minutes
to identify the optimal agent incubation time. To identify optimal dose, biopsies were incubated in either
1 µM, 10 µM, 50 µM, or 100 µM HS-27 or HS-217 1-minute post-excision for 1-minute prior to uorescence
imaging. (a) Representative uorescence images of 4T1 biopsies stained with 100 µM HS-217 or HS-27 for
1-minute within 1-minute of tissue excision. (bd) Survival curves of the ratio of HS-27 to HS-217 uorescence
demonstrate no signicant dierences with increasing post-excision time (b), a signicant decrease in
the specicity ratio with increasing incubation time (c), and a signicant increase in specicity ratio with
increasing dose (d) by Kolmogorov-Smirnov (KS) test. For all groups n = 4 biopsies. Survival curves show the
mean ± SEM.
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We created 12 dierent parameters from our uorescence images that could be used as optical predictors to
distinguish tumor from both benign lesions and normal breast tissue from mammoplasty cases. e rst 6 were
calculated by tting a logistic curve to each CDF from either all pixels or the top 1% of pixels with summary
variables A, B, and C, as shown in Supplementary Fig.S2. Parameter A controls the slope of the CDF, reecting
primarily the variance of pixel values within each image. Parameter B controls the le/right shi of the CDF,
reecting primarily the mean pixel value within each image. Parameter C controls the vertical shi of the CDF,
reecting both the mean and variance of the highest pixel values. e remaining 6 parameters were calculated as
summary parameters, namely the overall mean, variance, and ratio of the maximum to minimum uorescence for
all pixels and the top 1% of pixels to report on the average uorescence, uorescence spread, and dynamic range
respectively. Boxplots of the summary variables across all pixels and the top 1% of pixels are shown in Fig.4b,c
We next explored how the CDF and summary parameters aect the accuracy of HS-27 based classication.
Since there are dierences (though not all signicant) between tumor, benign lesion, and mammoplasty tissue
types, we performed two sets of comparisons – tumor vs. mammoplasty and tumor vs. benign lesion. For the two
comparison groups, Gaussian support vector machine (GSVM) classiers were created and tested with 10-fold
cross-validation to create receiver operating characteristic curves (ROCs) using either the CDF t parameters for
all pixels, the CDF t parameters for the top 1% of pixels, the summary variables for all pixels, or the summary
Figure 2. HS-27 uptake is greater in tumor than non-tumor samples. USGCNB were obtained from patients
prior to imaging with our optimized parameters. Representative uorescence (top) and histology (bottom)
images of mammoplasty tissue, broadenoma, ER/PR-positive tumor, TNBC, and Her2-positive tumor.
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variables for the top 1% of pixels. e sensitivity, specicity, and area under the curve (AUC) for the ROC for each
scenario are summarized in Table1.
Looking at the AUCs in Table1 reveals an interesting pattern. For tumor vs. mammoplasty comparisons,
utilizing the CDF t parameters from the top 1% of variables achieved a higher AUC than utilizing the CDF t
parameters from all pixels. e converse was true for tumor vs benign lesion comparisons. Similarly, utilizing
the summary parameters for all pixels achieved a higher AUC than the summary parameters from the top 1%
of pixels for tumor vs mammoplasty samples, with the opposite holding true for tumor vs benign comparisons.
Figure 3. Receptor subtype and presence of TILs aect HS-27 uorescence levels more than tumor cellularity.
(a) HS-27 uorescence does not correlate with tumor cellularity. (b) Mean uorescence varies with receptor
subtype and is signicantly lower in mammoplasty than all other tissue types. (ce) Mean uorescence strongly
and inversely correlates with the density of TILs across receptor subtypes.
Figure 4. HS-27 uorescence is greater in tumor than non-tumor tissue. (a) CDFs of uorescence image
pixel intensities were created for each combined biopsy image of either all pixels or of only the top 25%, top
10%, or top 1% of pixels. Curves were stratied by histology type. Mammoplasty (black) survival curves were
signicantly dierent from tumor curves by KS testing across pixel bins. (b,c) Box plots of intensity summary
parameters mean, variance and max to min ratio for tumor (T), benign (b) and mammoplasty (M) biopsies
for (b) all pixels or (c) the top 1% of pixels. Sample sizes – n = 6 mammoplasty, n = 10 benign, n = 27 tumor.
*p < 0.05 by KS testing (CDFs) or one-way ANOVA with Tukey-Kramer post-hoc testing(box plots). Survival
curves show the mean ± SEM.
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We performed a sequential feature selection method to identify the optimal 2 parameters for tumor vs mam-
moplasty and tumor vs benign lesion comparisons, by testing all combinations of the 12 parameters using a
GSVM with 10-fold cross-validation. e optimal parameters were chosen as those that led to the highest AUC
for the corresponding ROC. A combination of a summary parameter from all pixels (variance) and a CDF param-
eter from the top 1% of pixels (CDF C) performed the best for tumor vs mammoplasty comparisons. GSVM
scores and the ROC for the optimal tumor vs mammoplasty GSVM are shown in Fig.5a. e optimal sensitivity
and specicity were determined by maximizing the Youdens index, and were 86% and 100% respectively, with
an AUC of 0.96. In line with the results from Table1, the same variables in opposite pixel bins performed best for
tumor vs benign lesion comparisons (variance of the top 1% of pixels and the CDF C parameter for all pixels).
GSVM scores and the ROC for the optimal tumor vs benign GSVM are shown in Fig.5b. e optimal sensitivity
and specicity were again determined by maximizing the Youden’s index, and were 82% and 100% respectively,
with an AUC of 0.93.
Comparison CDFAll CDFTop 1% SummaryAll SummaryTop 1% Sens. Spec.
T v. M 0.8 52% 100%
T v. M 0.8 93% 67%
T v. M 0.95 89% 100%
T v. M 0.85 78% 100%
T v. B 0.78 67% 90%
T v. B 0.74 74% 70%
T v. B 0.44 93% 20%
T v. B 0.72 44% 100%
Table 1. Summary of GSVM performance for tumor vs mammoplasty (T v. M) and tumor vs benign (T v. B)
classiers. e AUC is shown in the box corresponding to the parameters used for classier development.
Figure 5. HS-27 features distinguish tumor from both mammoplasty and benign tissues. Gaussian support
vector machine (GSVM) classiers were developed for combinations of CDF and summary variables for both
tumor vs mammoplasty and tumor vs benign tissues. (a) GSVM scores and an ROC for a GSVM classier for
distinguishing tumor from mammoplasty tissue based on the variance of all pixels and the CDF C parameter
from the top 1% of pixels. (b) GSVM scores and an ROC for a GSVM classier for distinguishing tumor from
benign tissue based on the variance of the top 1% of pixels and the CDF C parameter from all pixels.
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With the complexity of breast cancer care continually increasing, and the associated cost burdens mounting,
it is more important to streamline care now more than ever before. When establishing our ex vivo diagnostic
methodology, simplicity and cost were two major considerations. We have created an ex vivo imaging strategy
to image surface Hsp90 expression in breast tumor biopsies. We optimized HS-27 uptake in pre-clinical models,
and found that a post-excision window of 1 to 10-minutes, incubation time of 1-minute, and dose of 100 µM
resulted in the greatest specicity ratio. Translating this protocol to clinical biopsy samples, we demonstrated
signicantly greater HS-27 uptake in tumor vs mammoplasty control tissues, and found that both cancerous and
tumor stromal cells contribute to HS-27 uorescence. GSVM analysis achieved an AUC of 0.93 with a sensitivity
and specicity of 82% and 100% respectively.
Interestingly, we found that benign breast conditions like broadenoma, abnormal ductal hyperplasia, and
cystic tissue showed higher HS-27 uorescence than mammoplasty control tissue, suggesting the presence of
surface Hsp90 in these samples, though at a lower level than in tumors. It is possible there is some surface Hsp90
expression in benign samples as indicated by HS-27 uorescence signal. Surface Hsp90 in benign samples may
be a mechanism of immune cell recruitment, as there have been numerous studies demonstrating the role Hsp90
plays during immune responses, both innate and adaptive3437. For example, in innate immunity the presence of
Hsp90 extracellularly can signal a damage associated molecular pattern causing immune cell recruitment34. e
induction of surface Hsp90 expression to activate immune responses during benign conditions reduces the sensi-
tivity for identifying tumor lesions. at being said, we still found using a non-linear GSVM using both intensity
and spatial HS-27 uorescence based predictors yielded the highest sensitivity and specicity.
Our algorithm incorrectly classied 5 tumor biopsies as benign lesions. All of these biopsies came from women
with ER+ breast cancer, with one biopsy also showing over-expression of Her2. In our previous pre-clinical
studies, we have found that Her2+ and TNBC have greater surface Hsp90 expression that ER+ tumors30.
Even so, we still correctly classied 71% of our ER+ tumors. Deep learning techniques may be better suited to
address this limitation of our approach, however, due to the small sample size of this study, we are limited in the
machine learning techniques we can apply to our dataset. It is also important to note that the small sample size
dictates further larger scale studies to validate these results. In the future, we plan to develop more advanced
deep-learning non-linear strategies, like articial neural networks, to improve the overall performance of our
diagnostic platform. If there is insucient contrast between ER+ tumors and benign tissues, due to the relatively
low expression of Hsp90 in these tumors, a combination of contrast agents may be used to enhance sensitivity
extending the capabilities of our platform.
We noticed some heterogeneity in uptake both within and across biopsies. Each biopsy is comprised of many
dierent cell types that may have varying levels of surface Hsp90 expression (i.e. malignant cells, tumor asso-
ciated broblasts, tumor inltrating lymphocytes, and non-malignant cells such as adipocytes), which would
inuence HS-27 uptake and may cause some of the intra-biopsy heterogeneity in HS-27 uorescence. is is fur-
ther evidenced by the considerably greater homogeneity seen in the mammoplasty images, which are primarily
In our clinical study we found variable HS-27 uptake within receptor subtypes, which, when coupled with
the established relationships between Hsp90 and immune responses, potentially provides an endpoint useful
for guiding treatment. For example, surface Hsp90 expression may be a useful surrogate marker for tumor inl-
trating lymphocytes (TILs), which are of particular importance, as increased density of TILs in patients with
early stage Her2+ breast cancer showed increased pathological complete response (pCR) when treated with
standard-of-care therapies trastuzumab and/or lapatinib32,33. Further, increased levels in TNBC have been
associated with improved patient outcomes following treatment with anthracycline-based chemotherapies31.
Interestingly, when binning Her2+ and TNBC samples together, we found a strong and signicant inverse cor-
relation between HS-27 uorescence and the density of stromal TILs (r = 0.63, p < 0.05). Despite promising
retrospective studies demonstrating the prognostic signicance of TILs, there are some limitations to using TIL
involvement as a prognostic or predictive biomarker in a clinical setting. Although eorts have been made to
standardize the assessment of TILs38, this assessment is still subject to inter-observer variability. e evidence
of Hsp90 involvement in immune regulation combined with our own ndings in Her2+ and TNBC tumors
provides a compelling opportunity to explore how surface Hsp90 expression on carcinoma cells relates to the
immune cell milieu in the tumor microenvironment.
Other groups are exploring molecular imaging techniques for applications in cancer3941, including a group
performing ex vivo imaging of breast tumors for applications in margin assessment using Her2-targeted u-
orescent antibodies42. Utilizing a dual-probe approach with targeted and non-targeted antibodies at dierent
uorescence wavelengths allowed for highly accurate identication of tumors vs non-tumor tissue. Similar to the
optimization results in our study, they found that shorter incubation times yielded increased imaging specic-
ity. Other groups are utilizing quantum dots tethered to antibodies43 to identify protein biomarkers such as the
estrogen receptor as well as more ubiquitously expressed targets like EGFR44,45 for diagnostic purposes in estrogen
receptor positive patients. Our work builds on tumor-specic imaging by targeting surface Hsp90 expression,
which is ubiquitous to all receptor subtypes of cancer, increasing the potential population target from only Her2+
tumors (~20% of breast cancer diagnoses) to all patients with breast cancer. Additionally, by utilizing a small
molecule specic to Hsp90 rather than antibodies, our approach does not require any initial blocking steps to
prevent non-specic binding, reducing the required processing to tissue and imaging time. Finally, by reducing
the cost of both the molecular agent and imaging system, we are primed to provide rapid diagnostic information
to physicians even in settings where on-site pathology is not possible.
In high-income countries (HICs), tumor specic targeting with HS-27 will allow for rapid analysis of biopsies
during diagnostic biopsy and tumor margins in the OR. A careful examination of each tissue type (tumor, benign
lesion, mammoplasty) reveals dierent HS-27 uptake patterns necessitating dierent metrics to separate tumor
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SCIENTIFIC REPORTS | (2019) 9:3461 |
from benign lesions and tumor from healthy (mammoplasty) tissue. In the biopsy clinic, the possible tissue types
are either tumor or benign lesion, dictating use of the GSVM algorithm based on tumor vs. benign samples. For
margin assessment, the possible tissue types are either tumor or healthy tissue, dictating use of the GSVM algo-
rithm based on tumor vs. mammoplasty samples.
Performing our imaging ex vivo circumvents the need for the regulatory approvals required for in vivo appli-
cations in uorescence guided surgery, and decreases the risk of side eects to the patient. In our model, the pri-
mary tumor (or biopsy) will be rapidly assayed for the presence of disease, nding the equivalent of pathological
tumor on ink, normally necessitating a re-excision. Tumor cells will be selectively visualized using HS-27, and
localized by easily navigating back and forth between wide-eld and high-resolution imaging with our Pocket
mammoscope, a uorescence microscope adapted from our widely-used Pocket colposcope4648. When disease is
found on the margin surface, the surgeon will go back and take additional shavings from the surgical cavity. is
strategy will be repeated until there is no signal on the surface of the margins.
Fortuitously, the ability to image tumor immune responses may fill an important niche in cancer prog-
nostics as well. Currently, for neoadjuvant and adjuvant treatment decisions oncologists use a combination of
clinical factors determined from either a diagnostic biopsy (neoadjuvant) or surgical specimen (adjuvant)49,50.
Unfortunately, current clinical factors such as hormone and/or growth factor receptor status are insucient to
predict which patients are likely to benet from additional therapies51. Without predictive tests, patients may
receive unnecessary and/or ineective treatments, which increases costs on an already overburdened healthcare
system, and exposes patients to unnecessary toxic side eects. Genetic tests including Oncotype DX have been
developed to assess whether ER+ breast cancer patients are likely to benet from adjuvant chemotherapy, reduc-
ing the use of potentially toxic therapies for women with low recurrence risk. However, for the 30% of patients
with either Her2+ or triple negative breast cancer (TNBC), there is no well-established predictive test to guide
treatment, beyond standard hormone receptor and Her2 testing. Being able to use Hsp90 expression as a surro-
gate for TIL levels may allow for a way to extend the prognostication available to patients with ER+ breast tumors
to patients with HER2+ or triple negative breast cancers.
ere is oen signicant patient attrition when multiple visits are required to diagnose and treat breast cancer
in LMICs. Integrating diagnostics with an eective treatment strategy into a single visit will improve outcomes
for patients in LMICs where standard of care pathology and surgical treatments are not feasible. e combination
of HS-27 with a low-cost microscopy system will provide a cost-eective and easily implementable diagnostic
platform for breast cancer as a rst step towards a single-visit see-and-treat strategy.
Cell culture. 4T1 murine breast cancer lines were used in the pre-clinical study, and were acquired from the
American Type Culture Collection and cultured under standard conditions free of contamination at 37 °C and 5%
CO2. Cells were maintained in RPMI-1640 (L-glutamine) medium supplemented with 10% FBS and 1% penicil-
lin-streptomycin. All cells were used for experiments within one month of rst passage.
Animal studies. All animal experiments were performed in accordance with protocol A216-15-08 approved
by the Duke University Institution for Animal Care and Use Committee. Animals were housed on-site with con-
tinual access to food and water under normal 12-hour light/dark cycles.
Flank tumor biopsy model. 4T1 tumors were grown in the ank of 11 athymic nude mice for optimizing
ex vivo imaging parameters. Specically, on passage two aer thaw, 106 4T1 cells suspended in 100 µL serum-free
medium were injected subcutaneously into the right ank to establish tumors. Tumors were allowed to grow to
a volume of 1 cm3 (tumor volume calculated as 0.5 × length × width2) to form a mass similar in size to those
evaluated in clinical radiology. We have previously described our biopsy procedure in detail30. Briey, mice were
anesthetized with a maximum of 1.5% isourane in room air. Prior to biopsy, scissors were used to make a small
incision to remove the skin over the tumor. Biopsies were taken using a 12 gauge Achieve programmable auto-
mated biopsy system. ree biopsies were taken from random locations within each tumor for 10 mice, with two
biopsies taken from the remaining mouse, yielding 32 biopsies for analysis.
Pre-clinical ex vivo imaging optimization. We identied and sequentially optimized three parameters
that could aect the specicity of HS-27 uptake: (1) time between tissue excision and staining, (2) agent incu-
bation time, and (3) agent dose. Because HS-27 is a small molecule rather than an antibody, no blocking steps
or specialized washes are required prior to agent incubation. For parameter 1, time between tissue excision and
staining was varied from 1, to 3, to 10-minutes while agent incubation time and dose were xed at 1-minute and
100 µM respectively. For parameter 2, incubation time was varied from 1, to 5, to 10-minutes while time aer
tissue excision and agent dose were xed at 1-minute and 100 µM respectively. Finally, for parameter 3, dose was
increased from 1, to 10, to 50, to 100 µM while time post excision and agent incubation time were both xed at
1-minute. 8 biopsies were used for each group in each experiment with 4 biopsies receiving HS-27 treatment and
4 biopsies receiving HS-217 treatment. HS-217 is a non-specic version of HS-27 that does not bind to Hsp90 and
serves as a negative control30. Aer HS-27 or HS-217 incubation, biopsies were thoroughly rinsed once with PBS
to remove unbound probe. Images were collected using a high-resolution microendoscope (HRME)52 every mm
along the length of the biopsy and stitched together for analysis as previously described30,53.
Clinical ex vivo biopsy imaging. All clinical imaging was performed in accordance with Duke IRB
approved protocol number Pro00008003. Aer giving informed consent, 34 adult patients undergoing standard
of care ultrasound guided core needle biopsy (USGCNB) and 4 adult patients undergoing breast reduction mam-
moplasty were enrolled in our study. Breast reduction mammoplasty patients serve as a negative control. Of the
34 USGCNB patients, one biopsy was imaged from each patient except in three patients where two biopsies were
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SCIENTIFIC REPORTS | (2019) 9:3461 |
imaged: one from each of two masses. Of the 4 reduction patients, two biopsies were imaged from each of two
patients and one from each of the remaining patients, resulting in 37 USGCNBs and 6 mammoplasty biopsies
for analysis. Of the 37 USGCNBs, 27 were invasive ductal cancer, of which 17 were ER/PR-positive, 4 were ER/
Her2-positive, 1 was ER/PR-negative but Her2-positive, and 4 were triple negative. e remaining 10 were benign
conditions and all mammoplasty samples were normal breast tissues. Table2 summarizes the demographic and
histologic information from our patient population.
Each biopsy was received within 5-minutes of tissue excision and had 100 µM HS-27 topically applied to the
biopsy for 1-minute prior to thorough rinsing with PBS. Images were collected using the HRME every mm along
the length of the biopsy and stitched together for analysis as previously described30,53. Biopsies were then inked
in three dierent colors and sent for standard pathologic review by a trained pathologist. e pathologist (AH)
provided specic diagnoses every mm along the biopsy for co-registration with HRME images, including the
percent tumor area (PTA), tumor cellularity, and the percent benign tissue area.
HS-27 uorescence quantication. All HRME images were processed using MATLAB (MathWorks).
Both pre-clinical and clinical images were calibrated using a uorescence slide to account for day-to-day sys-
tem variations. Because the HRME camera uses an automatic gain and exposure time, HRME images were
post-processed to correct for dierences between imaging sessions. For pre-clinical HS-27 uptake optimization,
non-specic uorescence was assessed by calculating the mean pixel intensity from the HS-217 images corre-
sponding to each optimization parameter and variable. e specicity ratio was then calculated by dividing each
HS-27 image by the corresponding mean HS-217 uorescence. Cumulative pixel distributions (CDFs) for each
image were averaged across biopsies within a group and used for statistical comparison.
Image processing, feature extraction and selection, and Gaussian support vector machine clas-
sication. e 37 USGCNB images were binned into either tumor (n = 27) or benign (n = 10) groups based
on their pathological diagnosis. 12 dierent parameters were created from our uorescence images to be used as
optical predictors. 6 were calculated as the mean pixel value, variance of pixel values, and maximum to minimum
pixel value ratio from either all or the top 1% of pixels. To take advantage of the intensity distributions within the
images, a logistic curve was t to the cumulative distribution function (CDF) to either all pixels or the top 1% of
pixels for each biopsy with three parameters per CDF that represent the CDF slope (A), the le/right shi (B), and
the vertical shi of the top of the CDF (C), as shown in Supplementary Fig.S2.
Next, we created Gaussian support vector machine (GSVM) classiers using the MATLAB Machine Learning
Toolbox to distinguish tumor from mammoplasty samples and tumor from benign lesion samples. A sequential
feature selection method was used to select the optimal set of features for each classier by testing each feature
individually, and then all possible pairs of features. e feature(s) resulting in optimal separation of tumor and
benign samples then underwent 10-fold cross validation. A receiver operating characteristic (ROC) curve was
Characteristic Biopsies
Number of Patients
Ultrasound (US) biopsy 37
Mammoplasty biopsy 6
Patient De mographics
Average Age (range) 55 (25–79)
Average BMI (range) 30 (18–54.4)
Pathology Breakdown
Malignant (US only) 27 (73%)
Benign (US only) 10 (27%)
Receptor Status (malignant only)
ER+,22 (81%), 5 (19%)
PR+,19 (70%), 8 (30%)
Her2+,5 (19%), 22 (81%)
TNBC 4 (15%)
Menopausal Status
Pre-menopause 14 (37%)
Peri-menopause 1 (2%)
Post-menopause 23 (61%)
Breast Density
Fatty 4 (11%)
Scattered Fibroglandular 13 (35%)
Heterogeneous Density 15 (41%)
Extremely Dense 5 (13%)
Table 2. Demographic breakdown of patients enrolled in pilot clinical study.
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SCIENTIFIC REPORTS | (2019) 9:3461 |
generated for the optimized GSVM classier, and the optimal sensitivity and specicity were determined by
maximizing the Youden’s index.
Statistical analysis. A two-sided student’s t-test was used for experiments comparing only two groups.
A one-way ANOVA with Tukey-Kramer post-hoc testing was used for experiments comparing more than two
groups. CDFs were compared using a Kolmogorov Smirnov (KS) test. Pearson’s linear correlations were used
to calculate correlation coecients. Comparisons and correlations were considered signicant on a 95% con-
dence interval with a p-value of 0.05 or less. All statistical testing was performed using the Statistics Toolbox in
MATLAB (MathWorks).
Data Availability
e datasets generated during and/or analyzed during the current study are available from the corresponding
author on reasonable request.
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The authors would like to thank Dr. Rebecca Richards-Kortum and her lab group for providing the high-
resolution microendoscope. is work was supported by generous funding from the NIH National Institute for
Biomedical Imaging and Bioengineering (1R21EB02500801 and T32-EB001040). e funders had no role in
study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Author Contributions
Conception and design – B.C., J.G., A.H., M.S., T.H. and N.R. Development of methodology – B.C., J.G. and N.R.
Acquisition of data – B.C., J.G., R.W. and J.D. Analysis and interpretation of data – B.C., J.G., A.H., M.S., T.H.
and N.R. Writing, review and/or revision of the manuscript – B.C. and N.R. with input from all authors Study
supervision – T.H. and N.R.
Additional Information
Supplementary information accompanies this paper at
Competing Interests: Dr. Ramanujam has founded a company called Zenalux Biomedical and she and other
team members have developed technologies related to this work where the investigators or Duke may benet
nancially if this system is sold commercially.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and
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Supplementary resource (1)

... We have previously established a non-invasive point of care imaging approach to quantify Hsp90 expression using a FITC-tethered Hsp90 inhibitor (HS-27) that specifically binds to Hsp90 expressed on the surface of breast cancer cells [17,23,24]. In our in vivo pre-clinical studies, we found that highly glycolytic tumors had the highest surface Hsp90 expression, while non-tumorigenic cells showed little to no surface Hsp90. ...
... The reduced scattering level for all fluorescence phantoms was 20 cm −1 , previously determined by averaging the scattering level from 390 nm to 650 nm [29]. A fiber-based micro endoscope (HRME) [30,31] and a customized microscope as described in the previous section were used to image surface HS-27 fluorescence of mammary tumor biopsies and tumor-mimicking phantoms using protocols previous described [24,25]. The customized fluorescence microscope [27] used ex:488 nm/em:525 ± 7 nm and the HRME utilized an LED light source centered at 455 nm (20 nm FWHM), a 475nm dichroic mirror, and a 500 nm long-pass filter as emission filter [30]. ...
... Fluorescence imaging of HS-27 was performed within a 1-5-minute window that was previously used in the clinic [24]. To assess the effect of viability on HS-27 fluorescence, NMuMG, murine mammary epithelial cells, with no surface Hsp90 expression, were treated with 35 mM hydrogen peroxide (H 2 O 2 ) for 15 minutes to induce apoptosis [26]. ...
Overexpression of heat shock protein 90 (Hsp90) on the surface of breast cancer cells makes it an attractive molecular biomarker for breast cancer diagnosis. Before a ubiquitous diagnostic method can be established, an understanding of the systematic errors in Hsp90-based imaging is essential. In this study, we investigated three factors that may influence the sensitivity of ex vivo Hsp90 molecular imaging: time-dependent tissue viability, nonspecific diffusion of an Hsp90 specific probe (HS-27), and contact-based imaging. These three factors will be important considerations when designing any diagnostic imaging strategy based on fluorescence imaging of a molecular target on tissue samples.
... Consequently, eHsp90 can be considered a pro-invasive hub that activates a cohort of proteins outside cancer cells to enhance invasion and metastasis, and its inhibition may be of benefit in treating metastatic cancers. Supportive of this idea is that several labs have used eHsp90 inhibitors in animal models of cancer metastasis and have shown benefits for reduced metastasis and increased survival [4,9,[14][15][16]18,85,86]. This makes identifying new mechanisms by which eHsp90 makes the TME pro-invasive an important task to undertake to determine whether inhibiting eHsp90 may serve as a basis for anti-metastasis drugs. ...
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Simple Summary Breast cancer cells secrete Hsp90, a protein that, inside of cells, regulates the function of hundreds of proteins, but outside of cells, extracellular Hsp90 (eHsp90) can activate a subset of proteins that promote invasion, the first step of metastasis. Blocking eHsp90 in mouse models inhibits metastasis, and we sought to understand how this occurs. Prior studies have predominantly focused on eHsp90 in cancer invasion within the immediate vicinity of the primary tumor, specifically its role in invading outside the epithelial compartment. However, eHsp90’s role in cancer invasion across the extended connective tissue after the cells have crossed the boundary of the epithelial compartment remains unknown. We show here that eHsp90 directly binds to and aligns Collagen-1 fibers, a major structural component of connective tissues, which, when aligned, form highways that allow efficient cancer migration. Our study suggests that the Hsp90 dimer, in its open state, binds to Collagen-1 molecules to align the fibers, which results in enhanced breast cancer invasion through the Collagen-1 matrix. Knowing this could help us propose experiments to test eHsp90 inhibitors for therapeutically targeting metastatic breast cancer. Abstract Cancer cell-secreted eHsp90 binds and activates proteins in the tumor microenvironment crucial in cancer invasion. Therefore, targeting eHsp90 could inhibit invasion, preventing metastasis—the leading cause of cancer-related mortality. Previous eHsp90 studies have solely focused on its role in cancer invasion through the 2D basement membrane (BM), a form of extracellular matrix (ECM) that lines the epithelial compartment. However, its role in cancer invasion through the 3D Interstitial Matrix (IM), an ECM beyond the BM, remains unexplored. Using a Collagen-1 binding assay and second harmonic generation (SHG) imaging, we demonstrate that eHsp90 directly binds and aligns Collagen-1 fibers, the primary component of IM. Furthermore, we show that eHsp90 enhances Collagen-1 invasion of breast cancer cells in the Transwell assay. Using Hsp90 conformation mutants and inhibitors, we established that the Hsp90 dimer binds to Collagen-1 via its N-domain. We also demonstrated that while Collagen-1 binding and alignment are not influenced by Hsp90’s ATPase activity attributed to the N-domain, its open conformation is crucial for increasing Collagen-1 alignment and promoting breast cancer cell invasion. These findings unveil a novel role for eHsp90 in invasion through the IM and offer valuable mechanistic insights into potential therapeutic approaches for inhibiting Hsp90 to suppress invasion and metastasis.
... Hsp90 expression levels were found in all subtypes of breast cancer receptors [98]. TNBC was sensitive to Hsp90 inhibition in preclinical and in vitro studies due to the downregulation of the Ras/Raf/MARK pathway [99]. ...
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Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, having a poor prognosis and rapid metastases. TNBC is characterized by the absence of estrogen, progesterone, and human epidermal growth receptor-2 (HER2) expressions and has a five-year survival rate. Compared to other breast cancer subtypes, TNBC patients only respond to conventional chemotherapies, and even then, with limited success. Shortages of chemotherapeutic medication can lead to resistance, pressured index therapy, non-selectivity, and severe adverse effects. Finding targeted treatments for TNBC is difficult owing to the various features of cancer. Hence, identifying the most effective molecular targets in TNBC pathogenesis is essential for predicting response to targeted therapies and preventing TNBC cell metastases. Nowadays, natural compounds have gained attention as TNBC treatments, and have offered new strategies for solving drug resistance. Here, we report a systematic review using the database from Pubmed, Science Direct, MDPI, BioScince, Springer, and Nature for articles screening from 2003 to 2022. This review analyzes relevant signaling pathways and the prospect of utilizing natural compounds as a therapeutic agent to improve TNBC treatments in the future.
... In [15], the authors devised a strategy using HS-27, for determining Hsp90 expression from tissue specimens for the diagnosis of breast cancer. Findings revealed that the HS-27 value was the highest in tumour tissues. ...
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Lung cancer is a lethal disease, and early diagnosis with the aid of biomarkers such as HSP90α protein can certainly assist the doctors to start treatment of patient at the earliest and can save their lives. To analyse the diagnostic value of HSP90α expression in lung cancer patients by collecting data of patients through IoT devices to avoid delay in treatments, a study has been presented in this paper where the significance of HSP90α biomarker is highlighted in early diagnosis of patients suffering from lung cancer. The second objective of the research study is to examine the correlation between the appearance level of HSP90α biomarker and the clinicopathological features of lung cancer. It is also evaluated whether the changes in HSP90α index are indicative or noteworthy before and after surgery of lung cancer patients. An observatory study of 78 patients with lung cancer in Qinhuangdao Hospital is presented in this paper where the samples were collected from June 2018 to March 2020. Their data were collected through IoT devices used in the latest healthcare facilities of the hospital. The ELISA method was utilized to identify the level of plasma HSP90 and to analyse HSP90 levels between the lung cancer group and healthy group of people. The relationship between HSP90 and the clinical pathological features of 78 patients suffering from lung cancer was analysed. An electrochemical luminescence method was used to detect CEA, NSE, SCC, and CYFRA21-1 levels. ROC curve and box plots were used to determine the analytic value of HSP90 and other biomarkers used in lung cancer diagnosis. Forty-two patients with moderate to early stage lung cancer with surgical correction were selected, and paired sample T test was used to analyse HSP90 levels before and after surgery. The plasma HSP90 level of lung cancer patients was quite higher as compared to the group of healthy people as per the values depicted in the research study. Second, HSP90 levels are substantially higher in pathologic type, differentiation degree, stage, and the existence of the lung, liver, and bone metastases ( < 0.05). The level of HSP90 expression was largely impacted by a few factors such as sex, age, smoking, and tumour location ( > 0.05). The ROC value for HSP90 was 0.599, while the area under the curve of HSP90 combined with other four tumour markers was 0.915 in the presented case study, indicating the presence of lung cancer. Patients with lung cancer had statistically significant differences in HSP90 expression levels before and after surgery ( < 0.05). It is concluded that the expression level of plasma HSP90α in lung cancer patients increases remarkably; therefore, HSP90 can be used to monitor presence of lung cancer before and after surgery in the patients. 1. Introduction Historically, the diagnosis of individuals with lung cancer has created a dark chapter where people hardly survived out of this disease, and it is important to diagnose this disease at the early stage, so that the chances of survival can increase [1, 2]. It is inevitable to accurately identify the stage of the patients who are suffering from lung cancer as this eventually contributes to better prognosis and treatment options. Many techniques have been developed till date for the diagnosis of lung cancer at early stages or to describe the effective or current stage of the lung cancer with good accuracy [3, 4]. Lung cancer (LC) is the utmost communal malignant tumour that has affected the entire world badly in the current era, as per the global cancer statistics report. It has the utmost morbidity which is the greatest threat to humans globally [5]. It has the largest proportion of all cancer-related deaths, which is increasing every year and found to be the third most dangerous and lethal cancer next to breast cancer and followed by prostate cancer [6]. As there have been no distinctive symptoms and/or discomfort in early stages, most of the cancers are diagnosed in the middle or terminal stage [7]. Early diagnosis is very difficult because the indications of lung cancer are similar to other respiratory diseases or common colds. Therefore, biomarkers are used to diagnose lung cancer at the early stages to save human lives [8]. Lung cancer is classified as small-cell lung cancer and non-small-cell lung cancer based on the mass, form, diagnostic method, and prescribed treatment [9]. 85% of overall lung cancers belong to the non-small-cell lung cancer category. This is further divided into adenocarcinoma, squamous-cell carcinoma, and large-cell carcinoma [10]. Heat shock proteins (HSPs) are also termed as stress proteins and are known to be a group of proteins that are extremely articulated body cells which are easily stimulated by numerous physical factors such as fever, contagion, and tumour formations. Extensive research studies have been conducted on HSP expressions and their impact on human body that even vaccine development takes place on the basis of HSP expressions [11]. HSP90α and HSP90β are the two HSP90 isoforms in the cytoplasm in the HSP90 family [12]. HSP90 family contributes to getting rid of the diseases by balancing unbalanced proteins in the cell [13]. HSP90 family expresses at a higher level as compared to the ordinary tissues to alarm the body about the growing diseases and formation of tumours/cancers in the body. Proteins that contribute to the cancer cell growth are MMP9, Hif-1 α, Her2/ErbB2, v-Src, Raf-1, AKT, EGFR, Met, etc. These proteins are the client proteins of the HSP90 family. These cells generate the process of signal transduction that transforms the healthy cells into tumour cells. Major targets for cancer therapy are inhibitors of HSP90 [14]. Research studies have revealed that the plasma levels of HSP90α are considerably high in lung cancer patients. In [15], the authors devised a strategy using HS-27, for determining Hsp90 expression from tissue specimens for the diagnosis of breast cancer. Findings revealed that the HS-27 value was the highest in tumour tissues. Along with the Hsp90 expression, H-27 is also used as significant parameter for the diagnosis of breast cancer. The usage of HS-27 fluorescence in biopsy image was also highlighted in the paper. In past years [16], many studies have revealed that Hsp90 plays a remarkable role in determination of cancer cells and its values correlate with the presence of lung cancer. On the other hand, Hsp90 protein can slow down the cell proliferation. In addition to it, Hsp90 inhibitors can be devised in the therapies to fight against lung cancer. This paper summarizes the importance of Hsp90 expression in lung cancer study. HSP90 is a vital protein for clientele stability [17]. Therefore, HSP90 can be treated as a significant biomarker in the diagnosis and treatment of lung cancer patients. HSP90 inhibitors are developed in the recent years for producing clinical results. In this paper, the development of HSP90 inhibitors is discussed which may help in the treatment of cancer patients. 1.1. Major Highlights of the Paper (a)This study investigates the clinical usefulness of HSP90 expressions as a biomarker of lung cancer diagnosis. It examines the correlation between the expression of the HSP90 and other clinical factors of non-small-cell lung cancer.(b)This paper examines the diagnostic value of HSP90α for lung cancer patients by detection of HSP90α expression levels in the diseased patients, and comparison of HSP90 with the traditional tumour markers is also evaluated.(c)The proposed study detects the expression level of HSP90α in peripheral blood of lung cancer patients and analyses its correlation with clinical pathological characteristics of lung cancer.(d)The observational perspective study detects changes of HSP90α in patients before and after surgery.(e)This paper uses the IoT technology for easy diagnosis of the lung cancer patients and reporting the stage of tumours for providing remedial solutions. 1.2. Organization of the Paper This paper is organized as follows. The paper begins with introduction about lung cancer, followed by the need to devise new mechanisms for detection of lung cancer, and then highlights the contributions of the paper and existing works in the related field. The next section discusses methods and materials. Third section presents the experimental study and outcomes. Final section concludes the proposed research work. 2. Proposed Methods 2.1. The Patients First Diagnosed with Lung Cancer in the Outpatient and Inpatient Service of Qinhuangdao Hospital From June 2018 to March 2020, 40 plus healthy physical examinees were selected as research conductors. The 78 patients in the lung cancer group were diagnosed by pathological examination, with 53 males and 25 females, aged 31~80 years old, with an average of 61.6 ± 8.8 years, including 45 cancer cases of lung adenocarcinoma, 22 cancer cases of squamous-cell lung carcinoma, 10 cancer cases of small-cell lung cancer, and 1 case of large-cell lung cancer. Staging was performed according to the 8th edition of international TNM (tumour, node, and metastasis) staging system for lung cancer. There were 26 cases in stage I, 8 cases in stage II, 18 cases in stage III, and 26 cases in stage IV. 42 individuals with surgical reasons in the early and intermediate stages of lung cancer need to be examined for HSP90 levels before and one month after surgery. The healthy group consisted of 40 healthy physical examinees in our hospital’s physical examination centre during the same period, including 24 males and 16 females, aged 24~77 years, with an average of 56.5 ± 14.4 years. Before the experiment, the patients’ consent and approval by the Medical Ethics Committee of Qinhuangdao Hospital were obtained. 2.2. Inclusion Criteria for the Patients The enrolled patients are pathologically diagnosed with lung cancer.(a)The patients who had not received radiotherapy, chemotherapy, or targeted therapy in the first diagnosis.(b)The patients who had no acute and chronic infectious diseases or autoimmune diseases.(c)The patients who had no serious heart, liver, kidney, and other organ diseases.(d)The patients who had no other primary malignant tumour. 2.3. Exclusion Criteria for the Patients (a)Those who were unwilling to cooperate and with mental illness.(b)Those who had serious heart, brain, liver, kidney, or other organ diseases.(c)Those who had other malignant tumours.(d)Those who had other lung diseases.(e)Pregnant women. 2.4. Sampling The specimens were collected from all the patients in the morning with an empty stomach. Specimens were re-collected from lung cancer patients one month after the surgery. 5 ml of peripheral plasma was retained using EDTA-K2 anticoagulant tube, shaken well, placed in a centrifuge for centrifugation for 10 minutes with revolving speed of 3000 r/min, and stored in the refrigerator at −80°C for testing. HSP90 was detected by enzyme-linked immunoassay analyser and HSP90α detection kit. 2.5. Reference Range The normal reference range of plasma HSP90α was set to 0–82.06 ng/mL, the normal value of serum CEA was set to 0–4.7 ng/mL, the normal value of NSE was 0–17 ng/mL, normal value of SCC (squamous-cell carcinoma-associated antigen) was 0–1.5 ug/L, and normal value of CYFRA21-1 (cytokeratin 19 fragment) was 0.1–3.3 ng/mL. 2.6. Statistical Analysis The statistical evaluation was performed using SPSS22.0 to analyse the outcomes of biomarkers in prediction of cancer stages. The sampling data were expressed by x ± s, and T-test was used for showing the differences between groups of normal and diseased patients. One-way analysis of variance was performed for assessment among multiple groups with respect to biomarkers. The non-parametric test was conducted if normal distribution was not followed. The ROC curve was used to analyse the prognosis value of plasma HSP90α and other tumour biomarkers in lung cancer. 3. Results and Analysis 3.1. Detection Results of HSP90α in Serum of the Two Groups The expression level of HSP90α was (92.949 ± 57.741) ng/ml in the lung cancer group and (45.876 ± 12.062) ng/ml in the healthy control group, which showed statistically significant difference (t = 5.089, < 0.01). The more values in expression level of HSP90 indicate that the person is suffering from cancer or having tumour inside the body. The baseline HSP90 levels of lung cancer patients were expressively higher than those of the healthy group of people. 3.2. Analysis of the Relationships The relationships were analysed between plasma HSP90α levels and clinical characteristics such as different gender, age, smoking, pathological type, degree of differentiation, staging, presence of lymph node metastasis, lung metastasis, liver metastasis, and bone metastasis in 78 lung cancer patients. The results suggested that HSP90α level is significantly different in terms of pathological types, degree of differentiation, staging, presence of lung metastasis, liver metastasis, and bone metastasis, showing statistically noteworthy difference ( < 0.05); there is no noteworthy difference in HSP90α expression regardless of different genders, ages, smoking, and tumour sites ( > 0.05), as shown in Table 1. Pathological feature Number of cases HSP90α (ng/ml) Male 53 89.77 ± 55.03 0.2 Female 25 99.69 ± 63.76 0.2 Age ≥ 65 39 84.57 ± 58.52 0.4 Age < 65 39 101.32 ± 56.46 0.4 Smoking—yes 41 86.61 ± 51.75 0.88 Smoking—no 37 84.77 ± 54.31 0.88 Left side 34 93.95 ± 67.03 0.8 Right side 44 92.17 ± 50.21 0.89 Adenocarcinoma 45 85.03 ± 47.87 0.5 Small cell 10 147.67 ± 47.00 0.4 Squamous carcinoma 22 78.27 ± 53.64 0.6 Giant cell 1 225.39 0.621 Degree of differentiation (DoD) High DoD 17 67.90 ± 37.57 0.608 Moderate DoD 22 81.28 ± 47.49 0.624 Poor DoD 28 90.06 ± 55.37 0.689 Undifferentiated 11 154.74 ± 67.74 0.749 1. 26 64.98 ± 38.67 0.7 2. 8 64.91 ± 15.87 0.68 3. 18 89.15 ± 47.92 0.6 4. 26 132.18 ± 66.82 0.6 Lung metastasis—yes 11 113.75 ± 69.92 0.04 Lung metastasis—no 62 80.65 ± 49.34 0.04 Lymph node metastasis (LNM)—yes 44 89.52 ± 48.38 0.081 LNM—no 35 81.26 ± 57.67 0.081 Bone metastasis (BM)—yes 14 111.38 ± 51.02 0.01 BM—no 65 81.37 ± 52.07 0.01
... The protein levels of HSP90AA1 were significantly elevated in tumors compared to normal mammary glands (Vartholomaiou et al., 2017). This was also observed in a breast cancer diagnostic study; they used fluorescein HS-27 in combination with HSP90 to provide a cost-effective and easy-to-implement diagnostic platform (Crouch et al., 2019). The biochemical assessment may lead to savings of almost 50% compared with medical imaging techniques (Robertson et al., 1995). ...
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Aim We aimed to develop and validate a comprehensive nomogram containing pre-treatment plasma HSP90AA1 to predict the risk of breast cancer onset and metastasis. Methods We assessed the expression of HSP90s in breast cancer patients using an online database. To verify the results, 677 patients diagnosed with breast cancer and 146 patients with benign breast disease between 2014 and 2019 were selected from our hospital and were divided into cancer risk and metastasis risk cohorts. We focused on HSP90AA1 to elucidate the risks of onset and metastasis in the cohorts. Results Expression levels of HSP90AA1 , HSP90AA2 , HSP90AB1 , HSP90B1 , and TRAP1 were linked to disease progression. Survival analysis using the GEPIA and OncoLnc databases indicated that the upregulation of HSP90AA1 and HSP90AB1 was related to poor overall survival. In the cancer risk cohort, carcinoembryonic antigen (CEA), carbohydrate antigen 153 (CA153), HSP90AA1, T cells%, natural killer cells%, B cells%, neutrophil count, monocyte count, and d-dimer were incorporated into the nomogram. A high Harrell’s concordance index (C-index) value of 0.771 [95% confidence interval (CI), 0.725–0.817] could still be reached in the interval validation. In the metastasis risk cohort, predictors contained in the prediction nomogram included the use of CEA, CA153, HSP90AA1, carbohydrate antigen 125 (CA125), natural killer cells%, B cells%, platelet count, monocyte count, and d-dimer. The C-index was 0.844 (95% CI, 0.801–0.887) and it was well-calibrated. HSP90AA1 raised net clinical benefit of breast cancer onset and metastasis risk prediction nomogram in a range of risk thresholds (5–92%) and (1–90%). Conclusion Our study revealed that pretreatment plasma HSP90AA1 combined with other markers could conveniently predict the risk of breast cancer onset and metastasis.
Objective and Impact Statement: We developed a generalized computational approach to design uniform, high-intensity excitation light for low-cost, quantitative fluorescence imaging of in vitro, ex vivo, and in vivo samples with a single device. Introduction: Fluorescence imaging is a ubiquitous tool for biomedical applications. Researchers extensively modify existing systems for tissue imaging, increasing the time and effort needed for translational research and thick tissue imaging. These modifications are application-specific, requiring new designs to scale across sample types. Methods: We implemented a computational model to simulate light propagation from multiple sources. Using a global optimization algorithm and a custom cost function, we determined the spatial positioning of optical fibers to generate 2 illumination profiles. These results were implemented to image core needle biopsies, preclinical mammary tumors, or tumor-derived organoids. Samples were stained with molecular probes and imaged with uniform and nonuniform illumination. Results: Simulation results were faithfully translated to benchtop systems. We demonstrated that uniform illumination increased the reliability of intraimage analysis compared to nonuniform illumination and was concordant with traditional histological findings. The computational approach was used to optimize the illumination geometry for the purposes of imaging 3 different fluorophores through a mammary window chamber model. Illumination specifically designed for intravital tumor imaging generated higher image contrast compared to the case in which illumination originally optimized for biopsy images was used. Conclusion: We demonstrate the significance of using a computationally designed illumination for in vitro, ex vivo, and in vivo fluorescence imaging. Application-specific illumination increased the reliability of intraimage analysis and enhanced the local contrast of biological features. This approach is generalizable across light sources, biological applications, and detectors.
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The rapid development of fluorescence imaging for intraoperative navigation has spurred further development of targeted fluorescent probes in the past decade. Only a few nontargeted dyes, including indocyanine green and methylene blue, are currently applied for fluorescence guided surgery in the clinic. While no targeted fluorescent probes have been approved for the clinic, a number of them have entered clinical trials. These probes have emission wavelengths in the visible and near infrared (NIR)‐I (700‐900 nm) range. Among them, activatable probes and nanoprobes have generated special interest. Compared with NIR‐I fluorescent probes, NIR‐II (1000‐1700 nm) fluorescent probes exhibit better intravital performance in terms of increased penetration depths, reduced tissue autofluorescence, and higher signal‐to‐background ratios. However, more challenges are expected before the successful translation of NIR‐II probes from bench to bedside. This review provides a brief overview of targeted fluorescent probes under clinical evaluation and recent achievements in the field of NIR‐II fluorescence imaging. In addition, we outline key considerations concerning the design of fluorescent probes for clinical translation.
Conference Paper
We developed a portable, low-cost, handheld fluorescent microscope to perform rapid heat shock protein 90 (Hsp90) molecular imaging. The source of non-specific signal and diffusion kinetics of the probe is studied.
Conference Paper
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In the past several decades, a number of novel fluorescence image-guided surgery (FGS) contrast agents have been under development, with many in clinical translation and undergoing clinical trials. In this review, we have identified and summarized the contrast agents currently undergoing clinical translation. In total, 39 novel FGS contrast agents are being studied in 85 clinical trials. Four FGS contrast agents are currently being studied in phase III clinical trials and are poised to reach FDA approval within the next two to three years. Among all novel FGS contrast agents, a wide variety of probe types, targeting mechanisms, and fluorescence properties exists. Clinically available FGS imaging systems have been developed for FDA approved FGS contrast agents, and thus further clinical development is required to yield FGS imaging systems tuned for the variety of contrast agents in the clinical pipeline. Additionally, study of current FGS contrast agents for additional disease types and development of anatomy specific contrast agents is required to provide surgeons FGS tools for all surgical specialties and associated comorbidities. The work reviewed here represents a significant effort from many groups and further development of this promising technology will have an enormous impact on surgical outcomes across all specialties.
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Introduction We have previously developed a portable Pocket Colposcope for cervical cancer screening in resource-limited settings. In this manuscript we report two different strategies (cross-polarization and an integrated reflector) to improve image contrast levels achieved with the Pocket Colposcope and evaluate the merits of each strategy compared to a standard-of-care digital colposcope. The desired outcomes included reduced specular reflection (glare), increased illumination beam pattern uniformity, and reduced electrical power budget. In addition, anti-fogging and waterproofing features were incorporated to prevent the Pocket Colposcope from fogging in the vaginal canal and to enable rapid disinfection by submersion in chemical agents. Methods Cross-polarization (Generation 3 Pocket Colposcope) and a new reflector design (Generation 4 Pocket Colposcope) were used to reduce glare and improve contrast. The reflector design (including the angle and height of the reflector sidewalls) was optimized through ray-tracing simulations. Both systems were characterized with a series of bench tests to assess specular reflection, beam pattern uniformity, and image contrast. A pilot clinical study was conducted to compare the Generation 3 and 4 Pocket Colposcopes to a standard-of-care colposcope (Leisegang Optik 2). Specifically, paired images of cervices were collected from the standard-of-care colposcope and either the Generation 3 (n = 24 patients) or the Generation 4 (n = 32 patients) Pocket Colposcopes. The paired images were blinded by device, randomized, and sent to an expert physician who provided a diagnosis for each image. Corresponding pathology was obtained for all image pairs. The primary outcome measures were the level of agreement (%) and κ (kappa) statistic between the standard-of-care colposcope and each Pocket Colposcope (Generation 3 and Generation 4). Results Both generations of Pocket Colposcope had significantly higher image contrast when compared to the standard-of-care colposcope. The addition of anti-fog and waterproofing features to the Generation 3 and 4 Pocket Colposcope did not impact image quality based on qualitative and quantitative metrics. The level of agreement between the Generation 3 Pocket Colposcope and the standard-of-care colposcope was 75.0% (kappa = 0.4000, p = 0.0028, n = 24). This closely matched the level of agreement between the Generation 4 Pocket Colposcope and the standard-of-care colposcope which was also 75.0% (kappa = 0.4941, p = 0.0024, n = 32). Conclusion Our results indicate that the Generation 3 and 4 Pocket Colposcopes perform comparably to the standard-of-care colposcope, with the added benefit of being low-cost and waterproof, which is ideal for use in resource-limited settings. Additionally, the reflector significantly reduces the electrical requirements of the Generation 4 Pocket Colposcope enhancing portability without altering performance compared to the Generation 3 system.
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The excision of tumors by wide local excision is challenging because the mass must be removed entirely without ever viewing it directly. Positive margin rates in sarcoma resection remain in the range of 20% to 35% and are associated with increased recurrence and decreased survival. Fluorescence-guided surgery (FGS) may improve surgical accuracy and has been utilized in other surgical specialties. ABY-029, an anti-epidermal growth factor receptor Affibody molecule covalently bound to the near-infrared fluorophore IRDye 800CW, is an excellent candidate for future FGS applications in sarcoma resection; however, conventional methods with direct surface tumor visualization are not immediately applicable. A novel technique involving imaging through a margin of normal tissue is needed. We review the past and present applications of FGS and present a novel concept of indirect FGS for visualizing tumor through a margin of normal tissue and aiding in excising the entire lesion as a single, complete mass with tumor-free margins.
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Hsp90 has been studied extensively as a therapeutic target in breast cancer in pre-clinical and clinical trials, demonstrating a variety of roles in metastatic progression. The evidence to date suggests a compelling opportunity to leverage attributes of Hsp90 expression beyond therapeutics with potential applications in breast cancer diagnosis, prognosis, and recurrence risk assessment. In this study, we developed a completely non-destructive strategy using HS-27, a fluorescently-tethered Hsp90 inhibitor, to assay Hsp90 expression on intact tissue specimens with comparable contrast to in vivo administration routes, and demonstrate the feasibility of our approach in breast cancer patients. In addition to Hsp90 inhibition being most effective in glycolytic tumors, we found ectopic Hsp90 expression to be highest in glycolytic tumors reinforcing its role as an indicator of aggressive disease. This work sets the stage for immediately using Hsp90 to improve outcomes for breast cancer patients without affecting traditional care pathways.
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Rationale: Positive margin status due to incomplete removal of tumor tissue during breast conserving surgery (BCS) is a prevalent diagnosis usually requiring a second surgical procedure. These follow-up procedures increase the risk of morbidity and delay the use of adjuvant therapy; thus, significant efforts are underway to develop new intraoperative strategies for margin assessment to eliminate re-excision procedures. One strategy under development uses topical application of dual probe staining and a fluorescence imaging strategy termed dual probe difference specimen imaging (DDSI). DDSI uses a receptor-targeted fluorescent probe and an untargeted, spectrally-distinct fluorescent companion imaging agent topically applied to fresh resected specimens, where the fluorescence from each probe is imaged and a normalized difference image is computed to identify tumor-target distribution in the specimen margins. While previous reports suggested this approach is a promising new tool for surgical guidance, advancing the approach into the clinic requires methodical protocol optimization and further validation. Methods: In the present study, we used breast cancer xenografts and receiver operator characteristic (ROC) curve analysis to evaluate a wide range of staining and imaging parameters, and completed a prospective validation study on multiple tumor phenotypes with different target expression. Imaging fluorophore-probe pair, concentration, and incubation times were systematically optimized using n=6 tissue specimen replicates per staining condition. Resulting tumor vs. normal adipose tissue diagnostic performance were reported and staining patterns were validated via receptor specific immunohistochemistry colocalization. Optimal staining conditions were tested in receptor positive and receptor negative cohorts to confirm specificity. Results: The optimal staining conditions were found to be a one minute stain in a 200 nM probe solution (area under the curve (AUC) = 0.97), where the choice of fluorescent label combination did not significantly affect the diagnostic performance. Using an optimal threshold value determined from ROC curve analysis on a training data set, a prospective study on xenografts resulted in an AUC=0.95 for receptor positive tumors and an AUC = 0.50 for receptor negative (control) tumors, confirming the diagnostic performance of this novel imaging technique. Conclusions: DDSI provides a robust, molecularly specific imaging methodology for identifying tumor tissue over benign mammary adipose tissue. Using a dual probe imaging strategy, nonspecific accumulation of targeted probe was corrected for and tumor vs. normal tissue diagnostic potential was improved, circumventing difficulties with ex vivo tissue specimen staining and allowing for rapid clinical translation of this promising technology for tumor margin detection during BCS procedures.
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Translation of fluorescence imaging using molecularly targeted imaging agents for real-time assessment of surgical margins in the operating room requires a fast and reliable method to predict tumor depth from planar optical imaging. Here, we developed a dual-wavelength fluorescent molecular probe with distinct visible and near-infrared excitation and emission spectra for depth estimation in mice and a method to predict the optical properties of the imaging medium such that the technique is applicable to a range of medium types. Imaging was conducted at two wavelengths in a simulated blood vessel and an in vivo tumor model. Although the depth estimation method was insensitive to changes in the molecular probe concentration, it was responsive to the optical parameters of the medium. Results of the intra-tumor fluorescent probe injection showed that the average measured tumor sub-surface depths were 1.31 ± 0.442 mm, 1.07 ± 0.187 mm, and 1.42 ± 0.182 mm, and the average estimated sub-surface depths were 0.97 ± 0.308 mm, 1.11 ± 0.428 mm, 1.21 ± 0.492 mm, respectively. Intravenous injection of the molecular probe allowed for selective tumor accumulation, with measured tumor sub-surface depths of 1.28 ± 0.168 mm, and 1.50 ± 0.394 mm, and the estimated depths were 1.46 ± 0.314 mm, and 1.60 ± 0.409 mm, respectively. Expansion of our technique by using material optical properties and mouse skin optical parameters to estimate the sub-surface depth of a tumor demonstrated an agreement between measured and estimated depth within 0.38 mm and 0.63 mm for intra-tumor and intravenous dye injections, respectively. Our results demonstrate the feasibility of dual-wavelength imaging for determining the depth of blood vessels and characterizing the sub-surface depth of tumors in vivo.
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Objective: Barriers to cervical cancer screening in low-resource settings include lack of accessible, high-quality services, high cost, and the need for multiple visits. To address these challenges, we developed a low-cost, intravaginal, optical cervical imaging device, the point-of-care tampon (POCkeT) colposcope and evaluated whether its performance is comparable with a standard-of-care colposcope. Materials and methods: There were 2 protocols, which included 44 and 18 patients. For the first protocol, white-light cervical images were collected in vivo, blinded by device, and sent electronically to 8 physicians from high-, middle-, and low-income countries. For the second protocol, green-light images were also collected and sent electronically to the highest performing physician from the first protocol who has experience in both a high- and low-income country. For each image, physicians completed a survey assessing cervix characteristics and severity of precancerous lesions. Corresponding pathology was obtained for all image pairs. Results: For the first protocol, average percent agreement between devices was 70% across all physicians. The POCkeT and standard-of-care colposcope images had 37% and 51% agreement with pathology for high-grade squamous intraepithelial lesions (HSILs), respectively. Investigation of HSIL POCkeT images revealed decreased visibility of vascularization and lack of contrast in lesion margins. After changes were made for the second protocol, the 2 devices achieved similar agreement to pathology for HSIL lesions (55%). Conclusions: Based on the exploratory study, physician interpretation of cervix images acquired using a portable, low-cost POCkeT colposcope was comparable to a standard-of-care colposcope.
As global efforts accelerate to implement the Sustainable Development Goals and, in particular, universal health coverage, access to high-quality and timely pathology and laboratory medicine (PALM) services will be needed to support health-care systems that are tasked with achieving these goals. This access will be most challenging to achieve in low-income and middle-income countries (LMICs), which have a disproportionately large share of the global burden of disease but a disproportionately low share of global health-care resources, particularly PALM services. In this first in a Series of three papers on PALM in LMICs, we describe the crucial and central roles of PALM services in the accurate diagnosis and detection of disease, informing prognosis and guiding treatment, contributing to disease screening, public health surveillance and disease registries, and supporting medical-legal systems. We also describe how, even though data are sparse, these services are of both insufficient scope and inadequate quality to play their key role in health-care systems in LMICs. Lastly, we identify four key barriers to the provision of optimal PALM services in resource-limited settings: insufficient human resources or workforce capacity, inadequate education and training, inadequate infrastructure, and insufficient quality, standards, and accreditation.
Extracellular vesicles (EVs) are diverse, nanoscale membrane vesicles actively released by cells. Similar-sized vesicles can be further classified (e.g., exosomes, microvesicles) based on their biogenesis, size, and biophysical properties. Although initially thought to be cellular debris, and thus under-appreciated, EVs are now increasingly recognized as important vehicles of intercellular communication and circulating biomarkers for disease diagnoses and prognosis. Despite their clinical potential, the lack of sensitive preparatory and analytical technologies for EVs poses a barrier to clinical translation. New analytical platforms including molecular ones are thus actively being developed to address these challenges. Recent advances in the field are expected to have far-reaching impact in both basic and translational studies. This article aims to present a comprehensive and critical overview of emerging analytical technologies for EV detection and their clinical applications.
Exosomes have recently emerged as highly promising cancer biomarkers because they are abundant in biofluids, carry proteins and RNA reflecting their originating cells and are stable over weeks. Beyond abundance and stability, detailed exosome analyses could be clinically useful for diagnosing and profiling cancers. Despite their clinical potential, simple, reliable and sensitive approaches for rapidly quantifying exosomes and their molecular information has been challenging. Therefore, there is a clear need to develop next-generation sensing technologies for exosome detection and analysis. In this critical review, we will describe three nanotechnology sensing platforms developed for analysis of exosomal proteins and RNAs directly from clinical specimens and discuss future development to facilitate their translation into routine clinical use.
Pancreatic ductal adenocarcinoma (PDAC) is usually detected late in the disease process. Clinical workup through imaging and tissue biopsies is often complex and expensive due to a paucity of reliable biomarkers. We used an advanced multiplexed plasmonic assay to analyze circulating tumor-derived extracellular vesicles (tEVs) in more than 100 clinical populations. Using EV-based protein marker profiling, we identified a signature of five markers (PDACEV signature) for PDAC detection. In our prospective cohort, the accuracy for the PDACEV signature was 84% [95% confidence interval (CI), 69 to 93%] but only 63 to 72% for single-marker screening. One of the best markers, GPC1 alone, had a sensitivity of 82% (CI, 60 to 95%) and a specificity of 52% (CI, 30 to 74%), whereas the PDACEV signature showed a sensitivity of 86% (CI, 65 to 97%) and a specificity of 81% (CI, 58 to 95%). The PDACEV signature of tEVs offered higher sensitivity, specificity, and accuracy than the existing serum marker (CA 19-9) or single–tEV marker analyses. This approach should improve the diagnosis of pancreatic cancer.