Tumor-Associated Immune-Cell-Mediated Tumor-Targeting Mechanism with NIR-II Fluorescence Imaging.

The strategy of structure-inherent tumor targeting (SITT) with cyanine-based fluorophores is receiving more attention because no chemical conjugation of targeting moieties is required. However, the targeting mechanism behind SITT has not yet been well explained. Here, it is demonstrated that heptamethine-cyanine-based fluorophores possess not only targetability of tumor microenvironments without the need for additional targeting ligands but also second near-infrared spectral window (NIR-II) imaging capabilities, i.e., minimum scattering and ultralow autofluorescence. The new SITT mechanism suggests that bone-marrow-derived and/or tissue-resident/tumor-associated immune cells can be a principal target for cancer detection due to their abundance in tumoral tissues. Among the tested, SH1 provides ubiquitous tumor targetability and a high tumor-to-background ratio (TBR) ranging from 9.5 to 47 in pancreatic, breast, and lung cancer mouse models upon a single bolus intravenous injection. Furthermore, SH1 can be used to detect small cancerous tissues smaller than 2 mm in diameter in orthotopic lung cancer models. Thus, SH1 could be a promising cancer-targeting agent and have a bright future for intraoperative optical imaging and image-guided cancer surgery.

Assessment of Raman Spectroscopy for Reducing Unnecessary Biopsies for Melanoma Screening.

A key challenge in melanoma diagnosis is the large number of unnecessary biopsies on benign nevi, which requires significant amounts of time and money. To reduce unnecessary biopsies while still accurately detecting melanoma lesions, we propose using Raman spectroscopy as a non-invasive, fast, and inexpensive method for generating a "second opinion" for lesions being considered for biopsy. We collected in vivo Raman spectral data in the clinical skin screening setting from 52 patients, including 53 pigmented lesions and 7 melanomas. All lesions underwent biopsies based on clinical evaluation. Principal component analysis and logistic regression models with leave one lesion out cross validation were applied to classify melanoma and pigmented lesions for biopsy recommendations. Our model achieved an area under the receiver operating characteristic (ROC) curve (AUROC) of 0.903 and a specificity of 58.5% at perfect sensitivity. The number needed to treat for melanoma could have been decreased from 8.6 (60/7) to 4.1 (29/7). This study in a clinical skin screening setting shows the potential of Raman spectroscopy for reducing unnecessary skin biopsies with in vivo Raman data and is a significant step toward the application of Raman spectroscopy for melanoma screening in the clinic.

Physiological model using diffuse reflectance spectroscopy for nonmelanoma skin cancer diagnosis.

Diffuse reflectance spectroscopy (DRS) is a noninvasive, fast, and low-cost technology with potential to assist cancer diagnosis. The goal of this study was to test the capability of our physiological model, a computational Monte Carlo lookup table inverse model, for nonmelanoma skin cancer diagnosis. We applied this model on a clinical DRS dataset to extract scattering parameters, blood volume fraction, oxygen saturation and vessel radius. We found that the model was able to capture physiological information relevant to skin cancer. We used the extracted parameters to classify (basal cell carcinoma [BCC], squamous cell carcinoma [SCC]) vs actinic keratosis (AK) and (BCC, SCC, AK) vs normal. The area under the receiver operating characteristic curve achieved by the classifiers trained on the parameters extracted using the physiological model is comparable to that of classifiers trained on features extracted via Principal Component Analysis. Our findings suggest that DRS can reveal physiologic characteristics of skin and this physiologic model offers greater flexibility for diagnosing skin cancer than a pure statistical analysis. Physiological parameters extracted from diffuse reflectance spectra data for nonmelanoma skin cancer diagnosis.

Raman biophysical markers in skin cancer diagnosis.

Raman spectroscopy (RS) has demonstrated great potential for in vivo cancer screening; however, the biophysical changes that occur for specific diagnoses remain unclear. We recently developed an inverse biophysical skin cancer model to address this issue. Here, we presented the first demonstration of in vivo melanoma and nonmelanoma skin cancer (NMSC) detection based on this model. We fit the model to our previous clinical dataset and extracted the concentration of eight Raman active components in 100 lesions in 65 patients diagnosed with malignant melanoma (MM), dysplastic nevi (DN), basal cell carcinoma, squamous cell carcinoma, and actinic keratosis. We then used logistic regression and leave-one-lesion-out cross validation to determine the diagnostically relevant model components. Our results showed that the biophysical model captures the diagnostic power of the previously used statistical classification model while also providing the skin's biophysical composition. In addition, collagen and triolein were the most relevant biomarkers to represent the spectral variances between MM and DN, and between NMSC and normal tissue. Our work demonstrates the ability of RS to reveal the biophysical basis for accurate diagnosis of different skin cancers, which may eventually lead to a reduction in the number of unnecessary excisional skin biopsies performed.

Raman active components of skin cancer.

Raman spectroscopy (RS) has shown great potential in noninvasive cancer screening. Statistically based algorithms, such as principal component analysis, are commonly employed to provide tissue classification; however, they are difficult to relate to the chemical and morphological basis of the spectroscopic features and underlying disease. As a result, we propose the first Raman biophysical model applied to in vivo skin cancer screening data. We expand upon previous models by utilizing in situ skin constituents as the building blocks, and validate the model using previous clinical screening data collected from a Raman optical fiber probe. We built an 830nm confocal Raman microscope integrated with a confocal laser-scanning microscope. Raman imaging was performed on skin sections spanning various disease states, and multivariate curve resolution (MCR) analysis was used to resolve the Raman spectra of individual in situ skin constituents. The basis spectra of the most relevant skin constituents were combined linearly to fit in vivo human skin spectra. Our results suggest collagen, elastin, keratin, cell nucleus, triolein, ceramide, melanin and water are the most important model components. We make available for download (see supplemental information) a database of Raman spectra for these eight components for others to use as a reference. Our model reveals the biochemical and structural makeup of normal, nonmelanoma and melanoma skin cancers, and precancers and paves the way for future development of this approach to noninvasive skin cancer diagnosis.

Combinatorial immunotherapy and nanoparticle mediated hyperthermia.

Immune checkpoint therapy has become the first widely adopted immunotherapy for patients with late stage malignant melanoma, with potential for a wide range of cancers. While some patients can experience long term disease remission, this is limited only to a subset of patients and tumor types. The path forward to expand this therapy to more patients and tumor types is currently thought to be combinatorial treatments, the combination of immunotherapy with other treatments. In this review, the combinatorial approach of immune checkpoint therapy combined with nanoparticle-assisted localized hyperthermia is discussed, starting with an overview of the different nanoparticle hyperthermia approaches in development, an overview of the state of immune checkpoint therapy, recent reports of immune checkpoint therapy and nanoparticle-assisted hyperthermia in a combinatorial approach, and finally a discussion of future research topics and areas to be explored in this new combinatorial approach to cancer treatment.

Conductive polymer-based nanoparticles for laser-mediated photothermal ablation of cancer: synthesis, characterization, and in vitro evaluation.

Laser-mediated photothermal ablation of cancer cells aided by photothermal agents is a promising strategy for localized, externally controlled cancer treatment. We report the synthesis, characterization, and in vitro evaluation of conductive polymeric nanoparticles (CPNPs) of poly(diethyl-4,4'-{[2,5-bis(2,3-dihydrothieno[3,4-b][1,4]dioxin-5-yl)-1,4-phenylene] bis(oxy)}dibutanoate) (P1) and poly(3,4-ethylenedioxythiophene) (PEDOT) stabilized with 4-dodecylbenzenesulfonic acid and poly(4-styrenesulfonic acid-co-maleic acid) as photothermal ablation agents. The nanoparticles were prepared by oxidative-emulsion polymerization, yielding stable aqueous suspensions of spherical particles of <100 nm diameter as determined by dynamic light scattering and electron microscopy. Both types of nanoparticles show strong absorption of light in the near infrared region, with absorption peaks at 780 nm for P1 and 750 nm for PEDOT, as well as high photothermal conversion efficiencies (~50%), that is higher than commercially available gold-based photothermal ablation agents. The nanoparticles show significant photostability as determined by their ability to achieve consistent temperatures and to maintain their morphology upon repeated cycles of laser irradiation. In vitro studies in MDA-MB-231 breast cancer cells demonstrate the cytocompatibility of the CPNPs and their ability to mediate complete cancer cell ablation upon irradiation with an 808-nm laser, thereby establishing the potential of these systems as agents for laser-induced photothermal therapy.

Optical properties of mouse brain tissue after optical clearing with FocusClear™.

Fluorescence microscopy is commonly used to investigate disease progression in biological tissues. Biological tissues, however, are strongly scattering in the visible wavelengths, limiting the application of fluorescence microscopy to superficial (<200µm) regions. Optical clearing, which involves incubation of the tissue in a chemical bath, reduces the optical scattering in tissue, resulting in increased tissue transparency and optical imaging depth. The goal of this study was to determine the time- and wavelength-resolved dynamics of the optical scattering properties of rodent brain after optical clearing with FocusClear™. Light transmittance and reflectance of 1-mm mouse brain sections were measured using an integrating sphere before and after optical clearing and the inverse adding doubling algorithm used to determine tissue optical scattering. The degree of optical clearing was quantified by calculating the optical clearing potential (OCP), and the effects of differing OCP were demonstrated using the optical histology method, which combines tissue optical clearing with optical imaging to visualize the microvasculature. We observed increased tissue transparency with longer optical clearing time and an analogous increase in OCP. Furthermore, OCP did not vary substantially between 400 and 1000 nm for increasing optical clearing durations, suggesting that optical histology can improve ex vivo visualization of several fluorescent probes.

Optical histology: a method to visualize microvasculature in thick tissue sections of mouse brain.

BACKGROUND: The microvasculature is the network of blood vessels involved in delivering nutrients and gases necessary for tissue survival. Study of the microvasculature often involves immunohistological methods. While useful for visualizing microvasculature at the µm scale in specific regions of interest, immunohistology is not well suited to visualize the global microvascular architecture in an organ. Hence, use of immunohistology precludes visualization of the entire microvasculature of an organ, and thus impedes study of global changes in the microvasculature that occur in concert with changes in tissue due to various disease states. Therefore, there is a critical need for a simple, relatively rapid technique that will facilitate visualization of the microvascular network of an entire tissue. METHODOLOGY/PRINCIPAL FINDINGS: The systemic vasculature of a mouse is stained with the fluorescent lipophilic dye DiI using a method called "vessel painting". The brain, or other organ of interest, is harvested and fixed in 4% paraformaldehyde. The organ is then sliced into 1 mm sections and optically cleared, or made transparent, using FocusClear, a proprietary optical clearing agent. After optical clearing, the DiI-labeled tissue microvasculature is imaged using confocal fluorescence microscopy and adjacent image stacks tiled together to produce a depth-encoded map of the microvasculature in the tissue slice. We demonstrated that the use of optical clearing enhances both the tissue imaging depth and the estimate of the vascular density. Using our "optical histology" technique, we visualized microvasculature in the mouse brain to a depth of 850 µm. CONCLUSIONS/SIGNIFICANCE: Presented here are maps of the microvasculature in 1 mm thick slices of mouse brain. Using combined optical clearing and optical imaging techniques, we devised a methodology to enhance the visualization of the microvasculature in thick tissues. We believe this technique could potentially be used to generate a three-dimensional map of the microvasculature in an entire organ.

High-resolution visualization of mouse cardiac microvasculature using optical histology.

Cardiovascular disease typically is associated with dysfunction of the coronary vasculature and microvasculature. The study of cardiovascular disease typically involves imaging of the large coronary vessels and quantification of cardiac blood perfusion. These methods, however, are not well suited for imaging of the cardiac microvasculature. We used the optical histology method, which combines chemical optical clearing and optical imaging, to create high-resolution, wide-field maps of the cardiac microvasculature in ventral slices of mouse heart. We have demonstrated the ability of the optical histology method to enable wide-field visualization of the cardiac microvasculature in high-resolution and anticipate that optical histology may have significant impact in studying cardiovascular disease.

Wide-field functional imaging of blood flow and hemoglobin oxygen saturation in the rodent dorsal window chamber.

The rodent dorsal window chamber is a widely used in vivo model of the microvasculature. The model consists of a 1cm region of exposed microvasculature in the rodent dorsal skin that is immobilized by surgically implanted titanium frames, allowing the skin microvasculature to be visualized. We describe a detailed protocol for surgical implantation of the dorsal window chamber which enables researchers to perform the window chamber implantation surgery. We further describe subsequent wide-field functional imaging of the chamber to obtain hemodynamic information in the form of blood oxygenation and blood flow on a cm size region of interest. Optical imaging techniques, such as intravital microscopy, have been applied extensively to the dorsal window chamber to study microvascular-related disease and conditions. Due to the limited field of view of intravital microscopy, detailed hemodynamic information typically is acquired from small regions of interest, typically on the order of hundreds of µm. The wide-field imaging techniques described herein complement intravital microscopy, allowing researchers to obtain hemodynamic information at both microscopic and macroscopic spatial scales. Compared with intravital microscopy, wide-field functional imaging requires simple instrumentation, is inexpensive, and can give detailed metabolic information over a wide field of view.