Evaluation of Collagen Alterations in Early Precursor Lesions of High Grade Serous Ovarian Cancer by Second Harmonic Generation Microscopy and Mass Spectrometry.

Background: The collagen architecture in high grade serous ovarian cancer (HGSOC) is highly remodeled compared to the normal ovary and the fallopian tubes (FT). We previously used Second Harmonic Generation (SHG) microscopy and machine learning to classify the changes in collagen fiber morphology occurring in serous tubal intraepithelial carcinoma (STIC) lesions that are concurrent with HGSOC. We now extend these studies to examine collagen remodeling in pure p53 signatures, STICs and normal regions in tissues that have no concurrent HGSOC. This is an important distinction as high-grade disease can result in distant collagen changes through a field effect mechanism. Methods: We trained a linear discriminant model based on SHG texture and image features as a classifier to discriminate the tissue groups. We additionally performed mass spectrometry analysis of normal and HGSOC tissues to associate the differential expression of collagen isoforms with collagen fiber morphology alterations. Results: We quantified the differences in the collagen architecture between normal tissue and the precursors with good classification accuracy. Through proteomic analysis, we identified the downregulation of single α-chains including those for Col I and III, where these results are consistent with our previous SHG-based supramolecular analyses. Conclusion: This work provides new insights into ECM remodeling in early ovarian cancer and suggests the combined use of SHG microscopy and mass spectrometry as a new diagnostic/prognostic approach.

Imaging Collagen Alterations in STICs and High Grade Ovarian Cancers in the Fallopian Tubes by Second Harmonic Generation Microscopy.

The majority of high-grade serous ovarian cancers originate in the fallopian tubes, however, the corresponding structural changes in the extracellular matrix (ECM) have not been well-characterized. This information could provide new insight into the carcinogenesis and provide the basis for new diagnostic tools. We have previously used the collagen-specific Second Harmonic Generation (SHG) microscopy to probe collagen fiber alterations in high-grade serous ovarian cancer and in other ovarian tumors, and showed they could be uniquely identified by machine learning approaches. Here we couple SHG imaging of serous tubal intra-epithelial carcinomas (STICs), high-grade cancers, and normal regions of the fallopian tubes, using three distinct image analysis approaches to form a classification scheme based on the respective collagen fiber morphology. Using a linear discriminant analysis, we achieved near 100% classification accuracy between high-grade disease and the other tissues, where the STICs and normal regions were differentiated with ~75% accuracy. Importantly, the collagen in high-grade disease in both the fallopian tube and the ovary itself have a similar collagen morphology, further substantiating the metastasis between these sites. This analysis provides a new method of classification, but also quantifies the structural changes in the disease, which may provide new insight into metastasis.

Two-frequency CARS imaging by switching fiber laser excitation.

To fully exploit the power of coherent Raman imaging, techniques are needed to image more than one vibrational frequency simultaneously. We describe a method for switching between two vibrational frequencies based on a single fiber-laser source. Stokes pulses were generated by soliton self-frequency shifting in a photonic crystal fiber. Pump and Stokes pulses were stretched to enhance vibrational resolution by spectral focusing. Stokes pulses were switched between two wavelengths on the millisecond time scale by a liquid-crystal retarder. Proof-of-principle is demonstrated by coherent anti-Stokes Raman imaging of polystyrene beads embedded in a poly(methyl methacrylate) (PMMA) matrix. The Stokes shift was switched between 3,050 cm-1 , where polystyrene has a Raman transition, and 2,950 cm-1 , where both polystyrene and PMMA have Raman resonances. The method can be extended to multiple vibrational modes.

Reorientation Motion and Preferential Interactions of a Peptide in Denaturants and Osmolyte.

Fluorescence anisotropy decay measurements and all atom molecular dynamics simulations are used to characterize the orientational motion and preferential interaction of a peptide, N-acetyl-tryptophan-amide (NATA) containing two peptide bonds, in aqueous, urea, guanidinium chloride (GdmCl), and proline solution. Anisotropy decay measurements as a function of temperature and concentration showed moderate slowing of reorientations in urea and GdmCl and very strong slowing in proline solution, relative to water. These effects deviate significantly from simple proportionality of peptide tumbling time to solvent viscosity, leading to the investigation of microscopic preferential interaction behavior through molecular dynamics simulations. Examination of the interactions of denaturants and osmolyte with the peptide backbone uncovers the presence of strongest interaction with urea, intermediate with proline, and weakest with GdmCl. In contrast, the strongest preferential solvation of the peptide side chain is by the nonpolar part of the proline zwitterion, followed by urea, and GdmCl. Interestingly, the local density of urea around the side chain is higher, but the GdmCl distribution is more organized. Thus, the computed preferential solvation of the side chain by the denaturants and osmolyte can account for the trend in reorientation rates. Analysis of water structure and its dynamics uncovered underlying differences between urea, GdmCl, and proline. Urea exerted the smallest perturbation of water behavior. GdmCl had a larger effect on water, slowing kinetics and stabilizing interactions. Proline had the largest overall interactions, exhibiting a strong stabilizing effect on both water-water and water-peptide hydrogen bonds. The results for this elementary peptide system demonstrate significant differences in microscopic behavior of the examined solvent environments. For the commonly used denaturants, urea tends to form disorganized local aggregates around the peptide groups and has little influence on water, while GdmCl only forms specific interactions with the side chain and tends to destabilize water structure. The protective osmolyte proline has the strongest and most specific interactions with the tryptophan side chain, and also stabilizes both water-water and water-peptide hydrogen bonds. Our results strongly suggest protein or peptide denaturation triggered by urea occurs by direct interaction, whereas GdmCl interacts favorably with side chains and destabilizes peptide-water hydrogen bonds. The stabilization of biopolymers by an osmolyte such as proline is governed by favorable preferential interaction with the side chains and stabilization of water.

Multi-modal label-free imaging based on a femtosecond fiber laser.

We demonstrate multi-mode microscopy based on a single femtosecond fiber laser. Coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS) and photothermal images can be obtained simultaneously with this simplified setup. Distributions of lipid and hemoglobin in sliced mouse brain samples and blood cells are imaged. The dependency of signal amplitude on the pump power and pump modulation frequency is characterized, which allows to isolate the impact from different contributions.