A profound remodeling of the extracellular matrix occurs in many epithelial cancers. In ovarian cancer, the minor collagen isoform of Col III becomes upregulated in invasive disease. Here we use second harmonic generation (SHG) imaging microscopy to probe structural differences in fibrillar models of the ovarian stroma comprised of mixtures of Col I and III. The SHG intensity and forward-backward ratios decrease with increasing Col III content, consistent with decreased phasematching due to more randomized structures. We further probe the net collagen α-helix pitch angle within the gel mixtures using what is believed to be a new pixel-based polarization-resolved approach that combines and extends previous analyses. The extracted pitch angles are consistent with those of peptide models and the method has sufficient sensitivity to differentiate Col I from the Col I/Col III mixtures. We further developed the pixel-based approach to extract the SHG signal polarization anisotropy from the same polarization-resolved image matrix. Using this approach, we found that increased Col III results in decreased alignment of the dipole moments within the focal volume. Collectively, the SHG measurements and analysis all indicate that incorporation of Col III results in decreased organization across several levels of collagen organization. Furthermore, the findings suggest that the collagen isoforms comingle within the same fibrils, in good agreement with ultrastructural data. The pixel-based polarization analyses (both excitation and emission) afford determination of structural properties without the previous requirement of having well-aligned fibers, and the approaches should be generally applicable in tissue.

In this perspective, we discuss how the nonlinear optical technique of second-harmonic generation (SHG) microscopy has been used to greatly enhance our understanding of the tumor microenvironment (TME) of breast and ovarian cancer. Striking changes in collagen architecture are associated with these epithelial cancers, and SHG can image these changes with great sensitivity and specificity with submicrometer resolution. This information has not historically been exploited by pathologists but has the potential to enhance diagnostic and prognostic capabilities. We summarize the utility of image processing tools that analyze fiber morphology in SHG images of breast and ovarian cancer in human tissues and animal models. We also describe methods that exploit the SHG physical underpinnings that are effective in delineating normal and malignant tissues. First we describe the use of polarization-resolved SHG that yields metrics related to macromolecular and supramolecular structures. The coherence and corresponding phase-matching process of SHG results in emission directionality (forward to backward), which is related to sub-resolution fibrillar assembly. These analyses are more general and more broadly applicable than purely morphology-based analyses; however, they are more computationally intensive. Intravital imaging techniques are also emerging that incorporate all of these quantitative analyses. Now, all these techniques can be coupled with rapidly advancing miniaturization of imaging systems to afford their use in clinical situations including enhancing pathology analysis and also in assisting in real-time surgical determination of tumor margins.

Remodeling of the collagen architecture in the extracellular matrix (ECM) has been implicated in ovarian cancer. To quantify these alterations we implemented a form of 3D texture analysis to delineate the fibrillar morphology observed in 3D Second Harmonic Generation (SHG) microscopy image data of normal (1) and high risk (2) ovarian stroma, benign ovarian tumors (3), low grade (4) and high grade (5) serous tumors, and endometrioid tumors (6). We developed a tailored set of 3D filters which extract textural features in the 3D image sets to build (or learn) statistical models of each tissue class. By applying k-nearest neighbor classification using these learned models, we achieved 83–91% accuracies for the six classes. The 3D method outperformed the analogous 2D classification on the same tissues, where we suggest this is due the increased information content. This classification based on ECM structural changes will complement conventional classification based on genetic profiles and can serve as an additional biomarker. Moreover, the texture analysis algorithm is quite general, as it does not rely on single morphological metrics such as fiber alignment, length, and width but their combined convolution with a customizable basis set.

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BackgroundOvarian cancer remains the most deadly gynecological cancer with a poor aggregate survival rate; however, the specific rates are highly dependent on the stage of the disease upon diagnosis. Current screening and imaging tools are insufficient to detect early lesions and are not capable of differentiating the subtypes of ovarian cancer that may benefit from specific treatments.MethodAs an alternative to current screening and imaging tools, we utilized wavelength dependent collagen-specific Second Harmonic Generation (SHG) imaging microscopy and optical scattering measurements to probe the structural differences in the extracellular matrix (ECM) of normal stroma, benign tumors, endometrioid tumors, and low and high-grade serous tumors.ResultsThe SHG signatures of the emission directionality and conversion efficiency as well as the optical scattering are related to the organization of collagen on the sub-micron size scale and encode structural information. The wavelength dependence of these readouts adds additional characterization of the size and distribution of collagen fibrils/fibers relative to the interrogating wavelengths. We found a strong wavelength dependence of these metrics that are related to significant structural differences in the collagen organization and are consistent with the dualistic classification of type I and II serous tumors. Moreover, type I endometrioid tumors have strongly differing ECM architecture than the serous malignancies. The SHG metrics and optical scattering measurements were used to form a linear discriminant model to classify the tissues, and we obtained high accuracy (>90%) between high-grade serous tumors from the other tissue types. High-grade serous tumors account for ~70% of ovarian cancers, and this delineation has potential clinical applications in terms of supplementing histological analysis, understanding the etiology, as well as development of an in vivo screening tool.ConclusionsSHG and optical scattering measurements provide sub-resolution information and when combined provide superior diagnostic power over clinical imaging modalities. Additionally the measurements are able to delineate the different subtypes of ovarian cancer and may potentially assist in treatment protocols. Understanding the altered collagen assembly can supplement histological analysis and provide new insight into the etiology. These methods could become an in vivo screening tool for earlier detection which is important since ovarian malignancies can metastasize while undetectable by current clinical imaging resolution.

There is considerable interest in understanding prostate cancer metastasis to bone and the interaction of these cells with the bone microenvironment. Osteonectin/SPARC/BM-40 is a collagen binding matricellular protein that is enriched in bone. Its expression is increased in prostate cancer metastases, and it stimulates the migration of prostate carcinoma cells. However, the presence of osteonectin in cancer cells and the stroma may limit prostate tumor development and progression. To determine how bone matrix osteonectin affects the behavior of prostate cancer cells, we modeled prostate cancer cell-bone interactions using the human prostate cancer cell line PC-3, and mineralized matrices synthesized by wild type and osteonectin-null osteoblasts in vitro. We developed this in vitro system because the structural complexity of collagen matrices in vivo is not mimicked by reconstituted collagen scaffolds or by more complex substrates, like basement membrane extracts. Second harmonic generation imaging demonstrated that the wild type matrices had thick collagen fibers organized into longitudinal bundles, whereas osteonectin-null matrices had thinner fibers in random networks. Importantly, a mouse model of prostate cancer metastases to bone showed a collagen fiber phenotype similar to the wild type matrix synthesized in vitro. When PC-3 cells were grown on the wild type matrices, they displayed decreased cell proliferation, increased cell spreading, and decreased resistance to radiation-induced cell death, compared to cells grown on osteonectin-null matrix. Our data support the idea that osteonectin can suppress prostate cancer pathogenesis, expanding this concept to the microenvironment of skeletal metastases.

Summary Little is known about the diversity and function of adipose tissue nerves, due in part to the inability to effectively visualize the tissue’s diverse nerve subtypes and the patterns of innervation across an intact depot. The tools to image and quantify adipose tissue innervation are currently limited. Here, we present a method of tissue processing that decreases tissue thickness in the z-axis while leaving cells intact for subsequent immunostaining. This was combined with autofluorescence quenching techniques to permit intact whole tissues to be mounted on slides and imaged by confocal microscopy, with a complementary means to perform whole tissue neurite density quantification after capture of tiled z-stack images. Additionally, we demonstrate how to visualize nerve terminals (the neuro-adipose nexus) in intact blocks of adipose tissue without z-depth reduction. We have included examples of data demonstrating nerve subtypes, neurovascular interactions, label-free imaging of collagen, and nerve bundle digital cross-sections.

We report on the wavelength dependence of second harmonic generation (SHG) of collagen in scattering tissues over the wavelength range of 800–1200 nm. The study incorporates inclusion of the molecular hyperpolarizability β of collagen and optical scattering, both of which are wavelength dependent. Using 3D SHG imaging and Monte Carlo simulations, we find the wavelength dependence of β is not well described by a two-state model based on known absorption bands. We further find that longer wavelength excitation is inefficient as the reduction in scattering is overcome by the decreased β far from resonance and the optimal excitation is within the 800–900 nm range. The impact is larger for backward collected SHG.