Applications of second-harmonic generation imaging microscopy in ovarian and breast cancer

Machine learning for automated classification of lung collagen in a urethane-induced lung injury mouse model

Dysregulation of lung tissue collagen level plays a vital role in understanding how lung diseases progress. However, traditional scoring methods rely on manual histopathological examination introducing subjectivity and inconsistency into the assessment process. These methods are further hampered by inter-observer variability, lack of quantification, and their time-consuming nature. To mitigate these drawbacks, we propose a machine learning-driven framework for automated scoring of lung collagen content. Our study begins with the collection of a lung slide image dataset from adult female mice using second harmonic generation (SHG) microscopy. In our proposed approach, first, we manually extracted features based on the 46 statistical parameters of fibrillar collagen. Subsequently, we pre-processed the images and utilized a pre-trained VGG16 model to uncover hidden features from pre-processed images. We then combined both image and statistical features to train various machine learning and deep neural network models for classification tasks. We employed advanced unsupervised techniques like K-means, principal component analysis (PCA), t-distributed stochastic neighbour embedding (t-SNE), and uniform manifold approximation and projection (UMAP) to conduct thorough image analysis for lung collagen content. Also, the evaluation of the trained models using the collagen data includes both binary and multi-label classification to predict lung cancer in a urethane-induced mouse model. Experimental validation of our proposed approach demonstrates promising results. We obtained an average accuracy of 83% and an area under the receiver operating characteristic curve (ROC AUC) values of 0.96 through the use of a support vector machine (SVM) model for binary categorization tasks. For multi-label classification tasks, to quantify the structural alteration of collagen, we attained an average accuracy of 73% and ROC AUC values of 1.0, 0.38, 0.95, and 0.86 for control, baseline, treatment_1, and treatment_2 groups, respectively. Our findings provide significant potential for enhancing diagnostic accuracy, understanding disease mechanisms, and improving clinical practice using machine learning and deep learning models.

Imaging at the nexus: how state of the art imaging techniques can enhance our understanding of cancer and fibrosis

Both cancer and fibrosis are diseases involving dysregulation of cell signaling pathways resulting in an altered cellular microenvironment which ultimately leads to progression of the condition. The two disease entities share common molecular pathophysiology and recent research has illuminated the how each promotes the other. Multiple imaging techniques have been developed to aid in the early and accurate diagnosis of each disease, and given the commonalities between the pathophysiology of the conditions, advances in imaging one disease have opened new avenues to study the other. Here, we detail the most up-to-date advances in imaging techniques for each disease and how they have crossed over to improve detection and monitoring of the other. We explore techniques in positron emission tomography (PET), magnetic resonance imaging (MRI), second generation harmonic Imaging (SGHI), ultrasound (US), radiomics, and artificial intelligence (AI). A new diagnostic imaging tool in PET/computed tomography (CT) is the use of radiolabeled fibroblast activation protein inhibitor (FAPI). SGHI uses high-frequency sound waves to penetrate deeper into the tissue, providing a more detailed view of the tumor microenvironment. Artificial intelligence with the aid of advanced deep learning (DL) algorithms has been highly effective in training computer systems to diagnose and classify neoplastic lesions in multiple organs. Ultimately, advancing imaging techniques in cancer and fibrosis can lead to significantly more timely and accurate diagnoses of both diseases resulting in better patient outcomes.

Molecular analysis of the extracellular microenvironment: from form to function

The extracellular matrix (ECM) proteome represents an important component of the tissue microenvironment that controls chemical flux and induces cell signaling through encoded structure. The analysis of the ECM represents an analytical challenge through high levels of post-translational modifications, protease-resistant structures, and crosslinked, insoluble proteins. This review provides a comprehensive overview of the analytical challenges involved in addressing the complexities of spatially profiling the extracellular matrix proteome. A synopsis of the process of synthesizing the ECM structure, detailing inherent chemical complexity, is included to present the scope of the analytical challenge. Current chromatographic and spatial techniques addressing these challenges are detailed. Capabilities for multimodal multiplexing with cellular populations are discussed with a perspective on developing a holistic view of disease processes that includes both the cellular and extracellular microenvironment.

Prostate cancer tissue classification by multiphoton imaging, automated image analysis and machine learning

Prostate carcinoma, a slow-growing and often indolent tumour, is the second most commonly diagnosed cancer among men worldwide. The prognosis is mainly based on the Gleason system through prostate biopsy analysis. However, new treatment and monitoring strategies depend on a more precise diagnosis. Here, we present results by multiphoton imaging for prostate tumour samples from 120 patients that allow to obtain quantitative parameters leading to specific tumour aggressiveness signatures. An automated image analysis was developed to recognise and quantify stromal fibre and neoplastic cell regions in each image. The set of metrics was able to distinguish between non-neoplastic tissue and carcinoma areas by linear discriminant analysis and random forest with accuracy of 89% ± 3%, but between Gleason groups of only 46% ± 6%. The reactive stroma analysis improved the accuracy to 65% ± 5%, clearly demonstrating that stromal parameters should be considered as additional criteria for a more accurate diagnosis.

Exploration of utility of combined optical photothermal infrared and Raman imaging for investigating the chemical composition of microcalcifications in breast cancer

Microcalcifications play an important role in cancer detection. They are evaluated by their radiological and histological characteristics but it is challenging to find a link between their morphology, their composition and the nature of a specific type of breast lesion. Whilst there are some mammographic features that are either typically benign or typically malignant often the appearances are indeterminate. Here, we explore a large range of vibrational spectroscopic and multiphoton imaging techniques in order to gain more information about the composition of the microcalcifications. For the first time, we validated the presence of carbonate ions in the microcalcifications by O-PTIR and Raman spectroscopy at the same time, the same location and the same high resolution (0.5 μm). Furthermore, the use of multiphoton imaging allowed us to create stimulated Raman histology (SRH) images which mimic histological images with all chemical information. In conclusion, we established a protocol for efficiently analysing the microcalcifications by iteratively refining the area of interest.

Deep learning-based high-speed, large-field, and high-resolution multiphoton imaging

Multiphoton microscopy is a formidable tool for the pathological analysis of tumors. The physical limitations of imaging systems and the low efficiencies inherent in nonlinear processes have prevented the simultaneous achievement of high imaging speed and high resolution. We demonstrate a self-alignment dual-attention-guided residual-in-residual generative adversarial network trained with various multiphoton images. The network enhances image contrast and spatial resolution, suppresses noise, and scanning fringe artifacts, and eliminates the mutual exclusion between field of view, image quality, and imaging speed. The network may be integrated into commercial microscopes for large-scale, high-resolution, and low photobleaching studies of tumor environments.

Types of spectroscopy and microscopy techniques for cancer diagnosis: a review

Cancer is a life-threatening disease that has claimed the lives of many people worldwide. With the current diagnostic methods, it is hard to determine cancer at an early stage, due to its versatile nature and lack of genomic biomarkers. The rapid development of biophotonics has emerged as a potential tool in cancer detection and diagnosis. Using the fluorescence, scattering, and absorption characteristics of cells and tissues, it is possible to detect cancer at an early stage. The diagnostic techniques addressed in this review are highly sensitive to the chemical and morphological changes in the cell and tissue during disease progression. These changes alter the fluorescence signal of the cell/tissue and are detected using spectroscopy and microscopy techniques including confocal and two-photon fluorescence (TPF). Further, second harmonic generation (SHG) microscopy reveals the morphological changes that occurred in non-centrosymmetric structures in the tissue, such as collagen. Again, Raman spectroscopy is a non-destructive method that provides a fingerprinting technique to differentiate benign and malignant tissue based on Raman signal. Photoacoustic microscopy and spectroscopy of tissue allow molecule-specific detection with high spatial resolution and penetration depth. In addition, terahertz spectroscopic studies reveal the variation of tissue water content during disease progression. In this review, we address the applications of spectroscopic and microscopic techniques for cancer detection based on the optical properties of the tissue. The discussed state-of-the-art techniques successfully determines malignancy to its rapid diagnosis.

PSHG-TISS: A collection of polarization-resolved second harmonic generation microscopy images of fixed tissues

Second harmonic generation (SHG) microscopy is acknowledged as an established imaging technique capable to provide information on the collagen architecture in tissues that is highly valuable for the diagnostics of various pathologies. The polarization-resolved extension of SHG (PSHG) microscopy, together with associated image processing methods, retrieves extensive image sets under different input polarization settings, which are not fully exploited in clinical settings. To facilitate this, we introduce PSHG-TISS, a collection of PSHG images, accompanied by additional computationally generated images which can be used to complement the subjective qualitative analysis of SHG images. These latter have been calculated using the single-axis molecule model for collagen and provide 2D representations of different specific PSHG parameters known to account for the collagen structure and distribution. PSHG-TISS can aid refining existing PSHG image analysis methods, while also supporting the development of novel image processing and analysis methods capable to extract meaningful quantitative data from the raw PSHG image sets. PSHG-TISS can facilitate the breadth and widespread of PSHG applications in tissue analysis and diagnostics.

Measurement(s)	Type I Collagen
Technology Type(s)	multi-photon laser scanning microscopy
Factor Type(s)	second order susceptibility tensor elements
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	laboratory environment
Sample Characteristic - Location	Romania

Comparison between Cylindrical, Trigonal, and General Symmetry Models for the Analysis of Polarization-Dependent Second Harmonic Generation Measurements Acquired from Collagen-Rich Equine Pericardium Samples

Polarization-dependent second harmonic generation (PSHG) microscopy is used as an innovative, high-resolution, non-destructive, and label-free diagnostic imaging tool to elucidate biological issues with high significance. In the present study, information on the structure and directionality of collagen fibers in equine pericardium tissue was collected using PSHG imaging measurements. In an effort to acquire precise results, three different mathematical models (cylindrical, trigonal, and general) were applied to the analysis of the recorded PSHG datasets. A factor called the “ratio parameter” was calculated to provide quantitative information. The implementation of the trigonal symmetry model to the recorded data led to the extraction of improved results compared with the application of the widely used cylindrical symmetry model. The best outcome was achieved through the application of the general model that does not include any kind of symmetry for the data processing. Our findings suggest that the trigonal symmetry model is preferable for the analysis of the PSHG datasets acquired from the collagenous tissues compared with the cylindrical model approach although an increased computational time is required.

Second-Harmonic Generation Imaging Reveals Changes in Breast Tumor Collagen Induced by Neoadjuvant Chemotherapy

Breast cancer is the most common invasive cancer in women, with most deaths attributed to metastases. Neoadjuvant chemotherapy (NACT) may be prescribed prior to surgical removal of the tumor for subsets of breast cancer patients but can have diverse undesired and off-target effects, including the increased appearance of the 'tumor microenvironment of metastasis', image-based multicellular signatures that are prognostic of breast tumor metastasis. To assess whether NACT can induce changes in two other image-based prognostic/predictive signatures derived from tumor collagen, we quantified second-harmonic generation (SHG) directionality and fiber alignment in formalin-fixed, paraffin-embedded sections of core needle biopsies and primary tumor excisions from 22 human epidermal growth factor receptor 2-overexpressing (HER2+) and 22 triple-negative breast cancers. In both subtypes, we found that SHG directionality (i.e., the forward-to-backward scattering ratio, or F/B) is increased by NACT in the bulk of the tumor, but not the adjacent tumor-stroma interface. Overall collagen fiber alignment is increased by NACT in triple-negative but not HER2+ breast tumors. These results suggest that NACT impacts the collagenous extracellular matrix in a complex and subtype-specific manner, with some prognostic features being unchanged while others are altered in a manner suggestive of a more metastatic phenotype.

Advances in nonlinear optical microscopy techniques for in vivo and in vitro neuroimaging

Understanding the mechanism of the brain via optical microscopy is one of the challenges in neuroimaging, considering the complex structures. Advanced neuroimaging techniques provide a more comprehensive insight into patho-mechanisms of brain disorders, which is useful in the early diagnosis of the pathological and physiological changes associated with various neurodegenerative diseases. Recent advances in optical microscopy techniques have evolved powerful tools to overcome scattering of light and provide improved in vivo neuroimaging with sub-cellular resolution, endogenous contrast specificity, pinhole less optical sectioning capability, high penetration depth, and so on. The following article reviews the developments in various optical imaging techniques including two-photon and three-photon fluorescence, second-harmonic generation, third-harmonic generation, coherent anti-Stokes Raman scattering, and stimulated Raman scattering in neuroimaging. We have outlined the potentials and drawbacks of these techniques and their possible applications in the investigation of neurodegenerative diseases.

Characterization of Collagen I Fiber Thickness, Density, and Orientation in the Human Skin In Vivo Using Second-Harmonic Generation Imaging

The assessment of dermal alterations is necessary to monitor skin aging, cancer, and other skin diseases and alterations. The gold standard of morphologic diagnostics is still histopathology. Here, we proposed parameters to distinguish morphologically different collagen I structures in the extracellular matrix and to characterize varying collagen I structures in the skin with similar SAAID (SHG-to-AF Aging Index of Dermis, SHG—second-harmonic generation; AF—autofluorescence) values. Test datasets for the papillary and reticular extracellular matrix from images in 24 female subjects, 36 to 50 years of age, were generated. Parameters for SAAID, edge detection, and fast Fourier transformation directionality were determined. Additionally, textural analyses based on the grey level co-occurrence matrix (GLCM) were conducted. At first, changes in the GLCM parameters were determined in the native greyscale images and, furthermore, in the Hilbert-transformed images. Our results demonstrate a robust set of parameters for noninvasive in vivo classification for morphologically different collagen I structures in the skin, with similar and different SAAID values. We anticipate our method to enable an automated prevention and monitoring system with an age- and gender-specific algorithm.

Influence of hematoxylin and eosin staining on the quantitative analysis of second harmonic generation imaging of fixed tissue sections

Second harmonic generation (SHG) microscopy has emerged over the past two decades as a powerful tool for tissue characterization and diagnostics. Its main applications in medicine are related to mapping the collagen architecture of in-vivo, ex-vivo and fixed tissues based on endogenous contrast. In this work we present how H&E staining of excised and fixed tissues influences the extraction and use of image parameters specific to polarization-resolved SHG (PSHG) microscopy, which are known to provide quantitative information on the collagen structure and organization. We employ a theoretical collagen model for fitting the experimental PSHG datasets to obtain the second order susceptibility tensor elements ratios and the fitting efficiency. Furthermore, the second harmonic intensity acquired under circular polarization is investigated. The evolution of these parameters in both forward- and backward-collected SHG are computed for both H&E-stained and unstained tissue sections. Consistent modifications are observed between the two cases in terms of the fitting efficiency and the second harmonic intensity. This suggests that similar quantitative analysis workflows applied to PSHG images collected on stained and unstained tissues could yield different results, and hence affect the diagnostic accuracy.

Multiscale anisotropy analysis of second-harmonic generation collagen imaging of mouse skin

SIGNIFICANCE

Morphological collagen signatures are important for tissue function, particularly in the tumor microenvironment. A single algorithmic framework with quantitative, multiscale morphological collagen feature extraction may further the use of collagen signatures in understanding fundamental tumor progression.

AIM

A modification of the 2D wavelet transform modulus maxima (WTMM) anisotropy method was applied to both digitally simulated collagen fibers and second-harmonic-generation imaged collagen fibers of mouse skin to calculate a multiscale anisotropy factor to detect collagen fiber organization.

APPROACH

The modified 2D WTMM anisotropy method was initially validated on synthetic calibration images to establish the robustness and sensitivity of the multiscale fiber organization tool. Upon validation, the algorithm was applied to collagen fiber organization in normal wild-type skin, melanoma stimulated skin, and integrin α10KO skin.

RESULTS

Normal wild-type skin collagen fibers have an increased anisotropy factor at all sizes scales. Interestingly, the multiscale anisotropy differences highlight important dissimilarities between collagen fiber organization in normal wild-type skin, melanoma stimulated, and integrin α10KO skin. At small scales (∼2 to 3  μm), the integrin α10KO skin was vastly different than normal skin (p-value  ∼  10  -  8), whereas the melanoma stimulated skin was vastly different than normal at large scales (∼30 to 40  μm, p-value  ∼  10  -  15).

CONCLUSIONS

This objective computational collagen fiber organization algorithm is sensitive to collagen fiber organization across multiple scales for effective exploration of collagen morphological alterations associated with melanoma and the lack of α10 integrin binding.

Emerging technologies provide insights on cancer extracellular matrix biology and therapeutics

Recent engineering technologies have transformed traditional perspectives of cancer to include the important role of the extracellular matrix (ECM) in recapitulating the malignant behaviors of cancer cells. Novel biomaterials and imaging technologies have advanced our understanding of the role of ECM density, structure, mechanics, and remodeling in tumor cell-ECM interactions in cancer biology and have provided new approaches in the development of cancer therapeutics. Here, we review emerging technologies in cancer ECM biology and recent advances in engineered systems for evaluating cancer therapeutics and provide new perspectives on how engineering tools present an opportunity for advancing the modeling and treatment of cancer. This review offers the cell biology and cancer cell biology communities insight into how engineering tools can improve our understanding of cancer ECM biology and therapeutic development.

Canine mammary cancer tumour behaviour and patient survival time are associated with collagen fibre characteristics

Precise diagnosis and prognosis are key in prevention and reduction of morbidity and mortality in all types of cancers. Here we show that changes in the collagen fibres in the main histological subtypes of canine mammary gland carcinomas are directly associated with the tumour behaviour and the animal survival time and could become a useful tool in helping with diagnosis. Imaging by second harmonic generation and multiphoton excited fluorescence microscopy were performed to evaluate the collagen and cellular segment parameters in cancer biopsies. We present a retrospective study of 45 cases of canine mammary cancer analysing 836 biopsies regions including normal mammary gland tissue, benign mixed tumours, carcinoma in mixed tumour, carcinosarcoma, micropapillary carcinoma and solid carcinoma. The image analyses and the comparison between the tumour types allowed to assess the collagen fibre changes during tumour progression. We demonstrate that the collagen parameters correlate with the clinical and pathological data, the results show that in neoplastic tissues, the collagen fibres are more aligned and shorter as compared to the normal tissues. There is a clear association of the mean fibre length with the dogs survival times, the carcinomas presenting shorter collagen fibres indicate a worse survival rate.

A biphasic response of polymerized Type 1 collagen architectures to dermatan sulfate

Collagen I, the most abundant extracellular matrix (ECM) protein in vertebrate tissues provides mechanical durability to tissue microenvironments and regulates cell function. Its fibrillogenesis in biological milieu is predominantly regulated by dermatan sulfate proteoglycans, proteins conjugated with iduronic acid-containing dermatan sulfate (DS) glycosaminoglycans (GAG). Although DS is known to regulate tissue function through its modulation of Coll I architecture, a precise understanding of the latter remains elusive. We investigated this problem by visualizing the fibrillar pattern of fixed Coll I gels polymerized in the presence of varying concentrations of DS using second harmonic generation microscopy. Measuring mean second harmonic generation signal (which estimates the ordering of the fibrils), and surface occupancy (which estimates the space occupied by fibrils) supported by confocal reflectance microscopy, our observations indicated that the effect on fibril pattern of DS is contextual upon the latter's concentrations: Lower levels of DS resulted in sparse disorganized fibrils; higher levels restore organization, with fibrils occupying greater space. An appropriate change in elasticity as a result of DS levels was also observed through atomic force microscopy. Examination of dye-based GAG staining and scanning electron microscopy suggested distinct constitutions of Coll I gels when polymerized with higher and lower levels of DS. We observed that adhesion of the invasive ovarian cancer cells SKOV3 decreased for lower DS levels but was partially restored at higher DS levels. Our study shows how the Coll I gel pattern-tuning of DS is of relevance for understanding its biomaterial applications and possibly, pathophysiological functions.

Human serum albumin gradient in serous ovarian cancer cryosections measured by fluorescence lifetime

Human serum albumin (HSA) is a depot and carrier for many endogenous and exogenous molecules in blood. Many studies have demonstrated that the transport of HSA in tumor microenvironments contributes to tumor development and progression. In this report, we set up a multimodal nonlinear optical microscope system, combining two-photon excitation fluorescence, second harmonic generation, and two-photon fluorescence lifetime imaging microscopy. The fluorescence lifetime of a small squaraine dye (SD) is used to evaluate HSA concentrations in tumor tissue based on specific binding between SD and HSA. We used SD to stain the cryosections from serous ovarian cancer patients in high-grade (HGSOC) and low-grade (LGSOC), respectively, and found a gradient descent of HSA concentration from normal connective tissue to extracellular matrix to tumor masses from 13 to 2 µM for LGSOC patients and from 36 to 12 µM for HGSOC patients. We demonstrated that multimodal nonlinear optical microscopy can obtain similar results as those from traditional histologic staining, thus it is expected to move to clinical applications.

Electrospun nanofiber scaffolds for the propagation and analysis of breast cancer stem cells in vitro

Despite advances in cancer treatment, breast cancer remains the second foremost cause of cancer mortality among women, with a high rate of relapse after initial treatment success. A subpopulation of highly malignant cancer cells, known as cancer stem cells (CSCs), is suspected to be linked to metastasis and relapse. Targeting of CSCs may therefore provide a means of addressing cancer-related mortality. However, due to their low population in vivo and a lack of proper culture platform for their propagation, much of the CSC biology remains unknown. Since maintenance of CSCs is heavily influenced by the tumor microenvironment, this study developed a 3D culture platform that mimics the metastatic tumor extracellular matrix (ECM) to effectively increase CSC population in vitro and allow CSC analysis. Through electrospinning, nanofibers that were aligned, porous, and collagen-coated were fabricated from polycaprolactone to recreate the metastatic tumor ECM assemblage. Breast cancer cells seeded onto the nanofiber scaffolds exhibited gross morphology and cytoskeletal phenotype similar to invasive cancer cells. Moreover, the population of breast cancer stem cells increased in nanofiber scaffolds. Analysis of breast cancer cells grown on the nanofiber scaffolds demonstrated an upregulation of mesenchymal markers and an increase in cell invasiveness suggesting the cells have undergone epithelial-mesenchymal transition. These results indicate that the fabricated nanofiber scaffolds effectively mimicked the tumor microenvironment that maintains the cancer stem cell population, offering a platform to enrich and analyze CSCs in vitro.

Recent Advancements in Optical Harmonic Generation Microscopy: Applications and Perspectives

Second harmonic generation (SHG) and third harmonic generation (THG) microscopies have emerged as powerful imaging modalities to examine structural properties of a wide range of biological tissues. Although SHG and THG arise from very different contrast mechanisms, the two are complimentary and can often be collected simultaneously using a modified multiphoton microscope. In this review, we discuss the needed instrumentation for these modalities as well as the underlying theoretical principles of SHG and THG in tissue and describe how these can be leveraged to extract unique structural information. We provide an overview of recent advances showing how SHG microscopy has been used to evaluate collagen alterations in the extracellular matrix and how this has been used to advance our knowledge of cancers, fibroses, and the cornea, as well as in tissue engineering applications. Specific examples using polarization-resolved approaches and machine learning algorithms are highlighted. Similarly, we review how THG has enabled developmental biology and skin cancer studies due to its sensitivity to changes in refractive index, which are ubiquitous in all cell and tissue assemblies. Lastly, we offer perspectives and outlooks on future directions of SHG and THG microscopies and present unresolved questions, especially in terms of overall miniaturization and the development of microendoscopy instrumentation.

Harmonic optical tomography of nonlinear structures

Second-harmonic generation microscopy is a valuable label-free modality for imaging non-centrosymmetric structures and has important biomedical applications from live-cell imaging to cancer diagnosis. Conventional second-harmonic generation microscopy measures intensity signals that originate from tightly focused laser beams, preventing researchers from solving the scattering inverse problem for second-order nonlinear materials. Here, we present harmonic optical tomography (HOT) as a novel modality for imaging microscopic, nonlinear and inhomogeneous objects. The HOT principle of operation relies on inter-ferometrically measuring the complex harmonic field and using a scattering inverse model to reconstruct the three-dimensional distribution of harmonophores. HOT enables strong axial sectioning via the momentum conservation of spatially and temporally broadband fields. We illustrate the HOT operation with experiments and reconstructions on a beta-barium borate crystal and various biological specimens. Although our results involve second-order nonlinear materials, we show that this approach applies to any coherent nonlinear process.

Optical imaging of collagen fiber damage to assess thermally injured human skin

Surgery is the definitive treatment for burn patients who sustain full-thickness burn injuries. Visual assessment of burn depth is made by the clinician early after injury but is accurate only up to 70% of the time among experienced surgeons. Collagen undergoes denaturation as a result of thermal injury; however, the association of collagen denaturation and cellular death in response to thermal injury is unknown. While gene expression assays and histologic staining allow for ex vivo identification of collagen changes, these methods do not provide spatial or integrity information in vivo. Thermal effects on collagen and the role of collagen in wound repair have been understudied in human burn models due to a lack of methods to visualize both intact and denatured collagen. Hence, there is a critical need for a clinically applicable method to discriminate between damaged and intact collagen fibers in tissues. We present two complementary candidate methods for visualization of collagen structure in three dimensions. Second harmonic generation imaging offers a label-free, high-resolution method to identify intact collagen. Simultaneously, a fluorophore-tagged collagen-mimetic peptide can detect damaged collagen. Together, these methods enable the characterization of collagen damage in human skin biopsies from burn patients, as well as ex vivo thermally injured human skin samples. These combined methods could enhance the understanding of the role of collagen in human wound healing after thermal injury and potentially assist in clinical decision-making.

A novel culture method that sustains ERα signaling in human breast cancer tissue microstructures

BACKGROUND

Estrogen receptor α (ERα) signaling is a defining and driving event in most breast cancers; ERα is detected in malignant epithelial cells of 75% of all breast cancers (classified as ER-positive breast cancer) and, in these cases, ERα targeting is the main therapeutic strategy. However, the biological determinants of ERα heterogeneity and the mechanisms underlying therapeutic resistance are still elusive, hampered by the challenges in developing experimental models recapitulative of intra-tumoral heterogeneity and in which ERα signaling is sustained. Ex vivo cultures of human breast cancer tissue have been proposed to retain the original tissue architecture, epithelial and stromal cell components and ERα. However, loss of cellularity, viability and ERα expression are well-known culture-related phenomena.

METHODS

BC samples were collected and brought to the laboratory. Then they were minced, enzymatically digested, entrapped in alginate and cultured for 1 month. The histological architecture, cellular composition and cell proliferation of tissue microstructures were assessed by immunohistochemistry. Cell viability was assessed by measurement of cell metabolic activity and histological evaluation. The presence of ERα was accessed by immunohistochemistry and RT-qPCR and its functionality evaluated by challenge with 17-β-estradiol and fulvestrant.

RESULTS

We describe a strategy based on entrapment of breast cancer tissue microstructures in alginate capsules and their long-term culture under agitation, successfully applied to tissue obtained from 63 breast cancer patients. After 1 month in culture, the architectural features of the encapsulated tissue microstructures were similar to the original patient tumors: epithelial, stromal and endothelial compartments were maintained, with an average of 97% of cell viability compared to day 0. In ERα-positive cases, fibers of collagen, the main extracellular matrix component in vivo, were preserved. ERα expression was at least partially retained at gene and protein levels and response to ERα stimulation and inhibition was observed at the level of downstream targets, demonstrating active ER signaling.

CONCLUSIONS

The proposed model system is a new methodology to study ex vivo breast cancer biology, in particular ERα signaling. It is suitable for interrogating the long-term effects of anti-endocrine drugs in a set-up that closely resembles the original tumor microenvironment, with potential application in pre- and co-clinical assays of ERα-positive breast cancer.

Multiphoton Microscopic Study of the Renal Cell Carcinoma Pseudocapsule: Implications for Tumour Enucleation

OBJECTIVE

To utilize Multiphoton Microscopy (MPM) as a novel imaging technique to characterize and quantify collagen at the Renal Cell Carcinoma Pseudocapsule, to assess for both intra-tumoral and inter-tumoral variation of collagen characteristics. MPM combines Second Harmonic Generation and Two Photon Excitation Fluorescence to image extracellular matrix architecture.

METHODS

Twenty partial nephrectomy specimen tissues were retrieved, cut into 5-micron sections, mounted on slides and deparaffinized. The pseudocapsules (PCs) were imaged with 2X and 20X objective at selected Regions of Interest. Corresponding clinical information was retrieved. PC thickness was determined. Collagen parameters measured included quantification by the Collagen Area Ratio, and qualitative measurements by the Collagen Fiber Density and Collagen Reticulation Index.

RESULTS

The boundaries between tumor, PC and normal renal parenchyma were distinguished by MPM without need for staining. In the thickest areas of the PC, collagen content and density were quantitatively higher compared to the thinnest areas. Median Collagen Area Ratio was higher in the thickest compared to the thinnest areas of the PC (P = .01). Clear Cell RCC specimens had a consistently higher Collagen Fiber Density in both the thickest and thinnest areas compared to non-Clear Cell RCC specimens (P = .02).

CONCLUSIONS

We demonstrated the ability of MPM to quantify collagen characteristics of PCs without fluorescent labeling. Tumor enucleation for Renal Cell Carcinoma along its PC remains debatable with regards to oncological safety. Even with a complete and intact PC, the PC is not a homogenous structure, and varies in its thickness and its collagen characteristics within, and between tumors.

Alignment of stroma fibers, microvessel density and immune cell populations determine overall survival in pancreatic cancer-An analysis of stromal morphology

Introduction

The aim of this study was to define histo-morphological stroma characteristics by analyzing stromal components, and to evaluate their impact on local and systemic tumor spread and overall survival in pancreatic ductal adenocarcinoma (PDAC).

Methods and materials

Patients who underwent oncologic resections with curative intent for PDAC were identified from a prospectively maintained database. Histological specimens were re-evaluated for morphological stroma features as stromal fibers, fibroblast morphology, stroma matrix density, microvessel density and distribution of immune cell populations.

Results

A total of 108 patients were identified undergoing curative resection for PDAC in the period from 2011–2016. 33 (30.6%) patients showed parallel alignment of stroma fibers while 75 (69.4%) had randomly oriented stroma fibers. As compared to parallel alignment, random orientation of stroma fibers was associated with larger tumor size (median 3.62 cm vs. median 2.87cm, p = 0.037), nodal positive disease (76.0% vs. 54.5%, p = 0.040), higher margin positive resection rates (41.9% vs. 15.2%, p = 0.008) and a trend for higher rates of T3/4 tumors (33.3% vs. 15.2%, p = 0.064). In univariate analysis, patients with parallel alignment of stroma fibers had improved overall survival rates as compared to patients with random orientation of stroma fibers (42 months vs. 22 months, p = 0.046). The combination of random orientation of stroma fibers and low microvessel density was associated with impaired overall survival rates (16 months vs. 36 months, p = 0.019). A high CD4/CD3 ratio (16 months vs. 33 months, p = 0.040) and high stromal density of CD163 positive cells were associated with reduced overall survival (27 months vs. 34 months, p = 0.039). In multivariable analysis, the combination of random orientation of stroma fibers and low microvessel density (HR 1.592, 95%CI 1.098–2.733, p = 0.029), high CD4/CD3 ratio (HR 2.044, 95%CI 1.203–3.508, p = 0.028) and high density of CD163 positive cells (HR 1.596, 95%CI 1.367–1.968, p = 0.036) remained independent prognostic factors.

Conclusion

Alignment of stroma fibers and microvessel density are simple histomorphological features serving as surrogate markers of local tumor progression dissemination and surgical resectability and determine prognosis in PDAC patients. High CD4/CD3 ratio and CD163 positive cell counts determine poor prognosis.

Third Harmonic Generation microscopy distinguishes malignant cell grade in human breast tissue biopsies

The ability to distinguish and grade malignant cells during surgical procedures in a fast, non-invasive and staining-free manner is of high importance in tumor management. To this extend, Third Harmonic Generation (THG), Second Harmonic Generation (SHG) and Fourier-Transform Infrared (FTIR) spectroscopy were applied to discriminate malignant from healthy cells in human breast tissue biopsies. Indeed, integration of non-linear processes into a single, unified microscopy platform offered complementary structural information within individual cells at the submicron level. Using a single laser beam, label-free THG imaging techniques provided important morphological information as to the mean nuclear and cytoplasmic area, cell volume and tissue intensity, which upon quantification could not only distinguish cancerous from benign breast tissues but also define disease severity. Simultaneously, collagen fibers that could be detected by SHG imaging showed a well structured continuity in benign tumor tissues, which were gradually disoriented along with disease severity. Combination of THG imaging with FTIR spectroscopy could provide a clearer distinction among the different grades of breast cancer, since FTIR analysis showed increased lipid concentrations in malignant tissues. Thus, the use of non-linear optical microscopy can be considered as powerful and harmless tool for tumor cell diagnostics even during real time surgery procedures.

Distinguishing metastatic triple-negative breast cancer from nonmetastatic breast cancer using second harmonic generation imaging and resonance Raman spectroscopy

Triple-negative breast cancer (TNBC) is an aggressive subset of breast cancer that is more common in African-American and Hispanic women. Early detection followed by intensive treatment is critical to improving poor survival rates. The current standard to diagnose TNBC from histopathology of biopsy samples is invasive and time-consuming. Imaging methods such as mammography and magnetic resonance (MR) imaging, while covering the entire breast, lack the spatial resolution and specificity to capture the molecular features that identify TNBC. Two nonlinear optical modalities of second harmonic generation (SHG) imaging of collagen, and resonance Raman spectroscopy (RRS) potentially offer novel rapid, label-free detection of molecular and morphological features that characterize cancerous breast tissue at subcellular resolution. In this study, we first applied MR methods to measure the whole-tumor characteristics of metastatic TNBC (4T1) and nonmetastatic estrogen receptor positive breast cancer (67NR) models, including tumor lactate concentration and vascularity. Subsequently, we employed for the first time in vivo SHG imaging of collagen and ex vivo RRS of biomolecules to detect different microenvironmental features of these two tumor models. We achieved high sensitivity and accuracy for discrimination between these two cancer types by quantitative morphometric analysis and nonnegative matrix factorization along with support vector machine. Our study proposes a new method to combine SHG and RRS together as a promising novel photonic and optical method for early detection of TNBC.

Quantitative stain-free imaging and digital profiling of collagen structure reveal diverse survival of triple negative breast cancer patients

Background

Stromal and collagen biology has a significant impact on tumorigenesis and metastasis. Collagen is a major structural extracellular matrix component in breast cancer, but its role in cancer progression is the subject of historical debate. Collagen may represent a protective layer that prevents cancer cell migration, while increased stromal collagen has been demonstrated to facilitate breast cancer metastasis.

Methods

Stromal remodeling is characterized by collagen fiber restructuring and realignment in stromal and tumoral areas. The patients in our study were diagnosed with triple-negative breast cancer in Singapore General Hospital from 2003 to 2015. We designed novel image processing and quantification pipelines to profile collagen structures using numerical imaging parameters. Our solution differentiated the collagen into two distinct modes: aggregated thick collagen (ATC) and dispersed thin collagen (DTC).

Results

Extracted parameters were significantly associated with bigger tumor size and DCIS association. Of numerical parameters, ATC collagen fiber density (CFD) and DTC collagen fiber length (CFL) were of significant prognostic value for disease-free survival and overall survival for the TNBC patient cohort. Using these two parameters, we built a predictive model to stratify the patients into four groups.

Conclusions

Our study provides a novel insight for the quantitation of collagen in the tumor microenvironment and will help predict clinical outcomes for TNBC patients. The identified collagen parameters, ATC CFD and DTC CFL, represent a new direction for clinical prognosis and precision medicine. We also compared our result with benign samples and DICS samples to get novel insight about the TNBC heterogeneity. The improved understanding of collagen compartment of TNBC may provide insights into novel targets for better patient stratification and treatment.

Metabolic mapping of glioblastoma stem cells reveals NADH fluxes associated with glioblastoma phenotype and survival

SIGNIFICANCE

Glioblastoma multiforme (GBM) is the most frequently diagnosed adult primary brain malignancy with poor patient prognosis. GBM can recur despite aggressive treatment due to therapeutically resistant glioblastoma stem cells (GSCs) that may exhibit metabolic plasticity.

AIM

Intrinsic nicotinamide adenine dinucleotide (NADH) fluorescence can be acquired with fluorescence lifetime imaging microscopy (FLIM) to examine its bound and free metabolic states in GSC and GBM tissues.

APPROACH

We compared the mean NADH fluorescence lifetime in live human GSCs and normal neural stem cells and validated those results by measuring oxygen consumption rates (OCRs). We also examined the role that invasive versus less-invasive GSCs had on tumor metabolism by measuring the mean NADH lifetimes and the relative amount of the longer-lived component of NADH and correlated these results with survival in an orthotopic mouse xenograft model.

RESULTS

Mean NADH lifetime, amount of bound NADH, and OCR were increased in GSCs. Compared with normal mouse brain, mean NADH lifetimes were longer for all GBM tissues. Invasive xenografts had higher relative amounts of the longer-lived NADH component, and this correlated with decreased survival.

CONCLUSIONS

FLIM offers cellular resolution quantification of metabolic flux in GBM phenotypes, potentially informing biomedical researchers on improved therapeutic approaches.

Label-free whole-colony imaging and metabolic analysis of metastatic pancreatic cancer by an autoregulating flexible optical system

Cancer metastasis is a Gordian knot for tumor diagnosis and therapy. Many studies have demonstrated that metastatic processes are inevitably affected by the tumor microenvironment. Histopathology is used universally as the gold standard for cancer diagnosis despite the lengthy preparation process and invasiveness.

Methods: Here, we introduced a supercontinuum and super-wide-tuning integrated multimodal platform, which combines the confocal, nonlinear and fluorescence lifetime microscopy with autoregulations, for label-free evaluation of fresh tissue and pathological sections. Based on various automated tunable lasers, synchronized and self-adjusting components and eight fast switching detection channels, the system features fast, large-field and subcellular-scale imaging of exogenous and endogenous fluorophores, nonlinear coherent scattering and lifetime contrast.

Results: With such an integrated multi-dimensional system, we searched the metastatic region by two-photon and three-photon excited autofluorescence, analyzed the cancer invasion by second harmonic generation and revealed the affected cellular metabolism by phasor-lifetime. We demonstrated the flexible measurement of multiple nonlinear modalities at NIR I and II excitation with a pre-compensation for group delay dispersion of ~7,000 fs² and low power of <40 mW, and of dual autofluorescence lifetime decays for phasor approach to decompose cancer-associated and disassociated components. This significantly revealed the metastatic and metabolic optical signatures of the whole colony of pancreatic cancers.

Conclusion: The synergistic effect of the system demonstrates the great potential to translate this technique into routine clinical applications, particularly for large-scale and quantitative studies of metastatic colonization.

NAD(P)H fluorescence lifetime measurements in fixed biological tissues

Autofluorescence based fluorescence lifetime imaging microscopy (AF-FLIM) techniques have come a long way from early studies on cancer characterization and have now been widely employed in several cellular and animal studies covering a wide range of diseases. The majority of research in autofluorescence imaging (AFI) study metabolic fluxes in live biological samples. However, tissues from clinical or scientific studies are often chemically fixed for preservation and stabilization of tissue morphology. Fixation is particularly crucial for enzymatic, functional, or histopathology studies. Interpretations of metabolic imaging such as optical redox intensity imaging and AF-FLIM, have often been viewed as potentially unreliable in a fixed sample due to lack of studies in this field. In this study, we carefully evaluate the possibility of extracting microenvironment information in fixed tissues using reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) endogenous fluorescence. The ability to distinguish changes such as metabolism and pH using intrinsic fluorescence in fixed tissues has great pathological value. In this work, we show that the lifetime based metabolic contrast in a sample is preserved after chemical fixation. The fluorescence lifetime of a sample increases with an additive fixative like formaldehyde; however, the fixed tissues retain metabolic signatures even after fixation. This study presents an opportunity to successfully image archived unstained histopathology tissues, and generate useful AF-FLIM signatures. We demonstrate the capability to draw metabolic interpretations in fixed tissues even after long periods of storage.

Application of multiphoton imaging and machine learning to lymphedema tissue analysis

The results of in-vivo two-photon imaging of lymphedema tissue are presented. The study involved 36 image samples from II stage lymphedema patients and 42 image samples from healthy volunteers. The papillary layer of the skin with a penetration depth of about 100 μm was examined. Both the collagen network disorganization and increase of the collagen/elastin ratio in lymphedema tissue, characterizing the severity of fibrosis, was observed. Various methods of image characterization, including edge detectors, a histogram of oriented gradients method, and a predictive model for diagnosis using machine learning, were used. The classification by "ensemble learning" provided 96% accuracy in validating the data from the testing set.

Second-harmonic generation imaging analysis can help distinguish sarcoidosis from tuberculoid leprosy

Sarcoidosis and tuberculoid leprosy (TL) are prototypes of granulomatous inflammation in dermatology, which embody one of the histopathology limitations in distinguishing some diseases. Recent advances in the use of nonlinear optical microscopy in skin have enabled techniques, such as second-harmonic generation (SHG), to become powerful tools to study the physical and biochemical properties of skin. We use SHG images to analyze the collagen network, to distinguish differences between sarcoidosis and TL granulomas. SHG images obtained from skin biopsies of 33 patients with TL and 24 with sarcoidosis retrospectively were analyzed using first-order statistics (FOS) and second-order statistics, such as gray-level co-occurrence matrix (GLCM). Among the four parameters evaluated (optical density, entropy, contrast, and second angular moment), only contrast demonstrated statistical significance, being higher in sarcoidosis (p  =  0.02; 4908.31 versus 2822.17). The results may indicate insufficient differentiating power for most tested FOS and GLCM parameters in classifying sarcoidosis and TL granulomas, when used individually. But in combination with histopathology (H&E and complementary stains, such as silver and fast acid stains), SHG analysis, like contrast, can contribute to distinguishing between these diseases. This study can provide a way to evaluate collagen distribution in granulomatous diseases.

Types of advanced optical microscopy techniques for breast cancer research: a review

A cancerous cell is characterized by morphological and metabolic changes which are the key features of carcinogenesis. Adenosine triphosphate (ATP) in cancer cells is primarily produced by aerobic glycolysis rather than oxidative phosphorylation. In normal cellular metabolism, nicotinamide adenine dinucleotide (NADH) is considered as a principle electron donor and flavin adenine dinucleotide (FAD) as an electron acceptor. During metabolism in a cancerous cell, a net increase in NADH is found as the pathway switched from oxidative phosphorylation to aerobic glycolysis. Often during initiation and progression of cancer, the developmental regulation of extracellular matrix (ECM) is restricted and becomes disorganized. Tumor cell behavior is regulated by the ECM in the tumor micro environment. Collagen, which forms the scaffold of tumor micro-environment also influences its behavior. Advanced optical microscopy techniques are useful for determining the metabolic characteristics of cancerous, normal cells and tissues. They can be used to identify the collagen microstructure and the function of NADH, FAD, and lipids in living system. In this review article, various optical microscopy techniques applied for breast cancer research are discussed including fluorescence, confocal, second harmonic generation (SHG), coherent anti-Stokes Raman scattering (CARS), and fluorescence lifetime imaging (FLIM).

Peptide Nanophotonics: From Optical Waveguiding to Precise Medicine and Multifunctional Biochips

Optical waveguiding phenomena found in bioinspired chemically synthesized peptide nanostructures are a new paradigm which can revolutionize emerging fields of precise medicine and health monitoring. A unique combination of their intrinsic biocompatibility with remarkable multifunctional optical properties and developed nanotechnology of large peptide wafers makes them highly promising for new biomedical light therapy tools and implantable optical biochips. This Review highlights a new field of peptide nanophotonics. It covers peptide nanotechnology and the fabrication process of peptide integrated optical circuits, basic studies of linear and nonlinear optical phenomena in biological and bioinspired nanostructures, and their passive and active optical waveguiding. It is shown that the optical properties of this generation of bio-optical materials are governed by fundamental biological processes. Refolding the peptide secondary structure is followed by wideband optical absorption and visible tunable fluorescence. In peptide optical waveguides, such a bio-optical effect leads to switching from passive waveguiding mode in native α-helical phase to an active one in the β-sheet phase. The found active waveguiding effect in β-sheet fiber structures below optical diffraction limit opens an avenue for the future development of new bionanophotonics in ultrathin peptide/protein fibrillar structures toward advanced biomedical nanotechnology.

Quantitative evaluation of redox ratio and collagen characteristics during breast cancer chemotherapy using two-photon intrinsic imaging

Preoperative neoadjuvant treatment in locally advanced breast cancer is recognized as an effective adjuvant therapy, as it improves treatment outcomes. However, the potential complications remain a threat, so there is an urgent clinical need to assess both the tumor response and changes in its microenvironment using non-invasive and precise identification techniques. Here, two-photon microscopy was employed to detect morphological alterations in breast cancer progression and recession throughout chemotherapy. The changes in structure were analyzed based on the autofluorescence and collagen of differing statuses. Parameters, including optical redox ratio, the ratio of second harmonic generation and auto-fluorescence signal, collagen density, and collagen shape orientation, were studied. Results indicate that these parameters are potential indicators for evaluating breast tumors and their microenvironment changes during progression and chemotherapy. Combined analyses of these parameters could provide a quantitative, novel method for monitoring tumor therapy.

Tumor Microenvironment and Models of Ovarian Cancer: The 11th Biennial Rivkin Center Ovarian Cancer Research Symposium

OBJECTIVE

The aim of this study was to review the latest research advances on the topics of the ovarian cancer tumor microenvironment and models of ovarian cancer.

METHODS

In September 2016, a symposium of the leaders in the field of ovarian cancer research was convened to present and discuss current advances and future directions in ovarian cancer research.

RESULTS

One session was dedicated to Tumor Microenvironment and Models of Ovarian Cancer, and included a keynote presentation from Anil Sood, MD, and an invited oral presentation from David Huntsman, MD. Eight additional oral presentations were selected from abstract submissions. Twenty-nine abstracts were presented in poster format and can be grouped into the categories of stromal cells in the microenvironment, immune cells in the microenvironment, epithelial-mesenchymal transition and metastasis, metabolomics, and model systems including spheroids, murine models, and other animal models.

CONCLUSIONS

Rapid advances continue in our understanding of the influence of the tumor microenvironment on ovarian cancer progression and metastasis. Vascular endothelial cells, stromal cells, and immune cells all modulate epithelial tumor cell biology and therefore serve as potential targets for improved treatment responses either in conjunction with or instead of current treatment modalities. Characterization of the underlying genetic alterations in both the tumor cells and surrounding microenvironment cells enhances our understanding of tumor biology. Model systems including both in vitro and in vivo approaches allow novel advances. Technological advances including sequencing strategies, use of mass spectrometry for metabolomics and other studies, and bioengineering approaches all complement conventional methodologies to push forward our understanding and ultimately the treatment of ovarian cancer.

Multiphoton microscopy for label-free identification of intramural metastasis in human esophageal squamous cell carcinoma

For complete removal of cancerous tissue in esophageal squamous cell carcinoma (ESCC), intramural metastasis (IM) should be identified preoperatively or intraoperatively. Here, multiphoton microscopy (MPM) was introduced for label-free identification of IM in the esophageal wall, by a combination of two-photon excited fluorescence (TPEF), second harmonic generation (SHG) imaging, and spectral analysis. Three-dimensional (3D) imaging of the IM region was also performed. Quantitative parameters, including 3D fiber orientation, were measured by 3D-weighted orientation vector summation. Overall, MPM showed the potential to identify IM. With the development of the advanced MPM endoscope, clinical identification of IM by MPM will be possible.

Epithelial Ovarian Cancer Diagnosis of Second-Harmonic Generation Images: A Semiautomatic Collagen Fibers Quantification Protocol

A vast number of human pathologic conditions are directly or indirectly related to tissular collagen structure remodeling. The nonlinear optical microscopy second-harmonic generation has become a powerful tool for imaging biological tissues with anisotropic hyperpolarized structures, such as collagen. During the past years, several quantification methods to analyze and evaluate these images have been developed. However, automated or semiautomated solutions are necessary to ensure objectivity and reproducibility of such analysis. This work describes automation and improvement methods for calculating the anisotropy (using fast Fourier transform analysis and the gray-level co-occurrence matrix). These were applied to analyze biopsy samples of human ovarian epithelial cancer at different stages of malignancy (mucinous, serous, mixed, and endometrial subtypes). The semiautomation procedure enabled us to design a diagnostic protocol that recognizes between healthy and pathologic tissues, as well as between different tumor types.

Identifying progression predictors of breast ductal carcinoma in situ

Ductal carcinoma in situ (DCIS) refers to neoplastic epithelial cells proliferating within the mammary ducts of the breast, which have not breached the basement membrane nor invaded surrounding tissues. Traditional thinking holds that DCIS represents an early step in a linear progression towards invasive ductal carcinoma (IDC). However, as only approximately half of DCIS cases progress to IDC, important questions around the key determinants of malignant progression need to be answered. Recent studies have revealed that molecular differences between DCIS and IDC cells are not found at the genomic level; instead, altered patterns of gene expression and post-translational regulation lead to distinct transcriptomic and proteomic profiles. Therefore, understanding malignant progression will require a different approach that takes into account the diverse tumour cell extrinsic factors driving changes in tumour cell gene expression necessary for the invasive phenotype. Here, we review the roles of the tumour stroma (including mesenchymal cells, immune cells and the extracellular matrix) and myoepithelial cells in malignant progression and make a case for a more integrated approach to the study and assessment of DCIS and its progression, or lack thereof, to invasive disease.

Mechanical properties of the tumor stromal microenvironment probed in vitro and ex vivo by in situ-calibrated optical trap-based active microrheology

One of the hallmarks of the malignant transformation of epithelial tissue is the modulation of stromal components of the microenvironment. In particular, aberrant extracellular matrix (ECM) remodeling and stiffening enhances tumor growth and survival and promotes metastasis. Type I collagen is one of the major ECM components. It serves as a scaffold protein in the stroma contributing to the tissue's mechanical properties, imparting tensile strength and rigidity to tissues such as those of the skin, tendons, and lungs. Here we investigate the effects of intrinsic spatial heterogeneities due to fibrillar architecture, pore size and ligand density on the microscale and bulk mechanical properties of the ECM. Type I collagen hydrogels with topologies tuned by polymerization temperature and concentration to mimic physico-chemical properties of a normal tissue and tumor microenvironment were measured by in situ-calibrated Active Microrheology by Optical Trapping revealing significantly different microscale complex shear moduli at Hz-kHz frequencies and two orders of magnitude of strain amplitude that we compared to data from bulk rheology measurements. Access to higher frequencies enabled observation of transitions from elastic to viscous behavior that occur at ~200Hz to 2750Hz, which largely was dependent on tissue architecture well outside the dynamic range of instrument acquisition possible with SAOS bulk rheology. We determined that mouse melanoma tumors and human breast tumors displayed complex moduli ~5-1000 Pa, increasing with frequency and displaying a nonlinear stress-strain response. Thus, we show the feasibility of a mechanical biopsy in efforts to provide a diagnostic tool to aid in the design of therapeutics complementary to those based on standard histopathology.

Real-time optical diagnosis of gastric cancer with serosal invasion using multiphoton imaging

A real-time optical biopsy, which could determine tissue histopathology, would be of extraordinary benefit to staging laparoscopy for gastric cancer with serosal invasion (T4) that requires downstage treatment. We investigated the feasibility of using multiphoton imaging to perform a real-time optical diagnosis of gastric cancer with or without serosal invasion. First, a pilot study was performed to establish the optical diagnostic features of gastric cancer with or without serosal invasion using multiphoton imaging compared with hematoxylin-eosin staining and Masson’s trichrome staining. Second, a blinded study was performed to compare the diagnostic sensitivity, specificity, and accuracy of multiphoton imaging and endoscopic ultrasonography (EUS) for T4 gastric cancer. In the pilot study, multiphoton imaging revealed collagen loss and degradation and cellular and nuclear pleomorphism in gastric cancer with serosal invasion. The collagen content in gastric cancer with or without serosal invasion was 0.36 ± 0.18 and 0.79 ± 0.16 (p < 0.001), respectively. In the blinded study, the sensitivity, specificity, and accuracy of EUS and multiphoton imaging for T4 gastric cancer were 70% and 90% (p = 0.029), 66.67% and 96.67% (p = 0.003), and 68.33% and 93.33% (p = 0.001), respectively. It is feasible to use multiphoton imaging to make a real-time optical diagnosis of gastric cancer with or without serosal invasion.

Second harmonic generation microscopy in zebrafish

Modern optical imaging has progressed rapidly with the ability to noninvasively image cellular and subcellular phenomena with high spatial and temporal resolution. In particular, emerging techniques such as second harmonic generation (SHG) microscopy can allow for the monitoring of intrinsic contrast, such as that from collagen, in live and fixed samples. When coupled with multiphoton fluorescence microscopy, SHG can be used to image interactions between cells and the surrounding extracellular environment. There is recent interest in using these approaches to study inflammation and wound healing in zebrafish, an important model for studying these processes. In this chapter we present the practical aspects of using second harmonic generation to image interactions between leukocytes and collagen during wound healing in zebrafish.