Abstract

Remodeling of the extracellular matrix in human ovarian cancer can be reflected in increased collagen concentration, changes in alignment within fibrils and fibers and/or up-regulation of different collagen isoforms. We used pixel-based SHG polarization analyses to discriminate ex vivo human tissues (normal stroma, benign tumors, and high grade serous tumors) by: i) determination of i) helical pitch angle via the single axis molecular model, ii) dipole alignment within fibrils via anisotropy, and iii) chirality via SHG circular dichroism (SHG-CD). The largest differences were between normal stroma and benign tumors, consistent with gene expression showing Col III is up-regulated in the latter. The different tissues also displayed differing SHG anisotropies and SHG-CD responses, consistent with either Col III incorporation or randomization of Col I alignment within benign and high-grade tumors fibrils. These results collectively indicate the fibril assemblies are distinct in all tissues and likely result from synthesis of new collagen rather than remodeling of existing collagen. We also implemented a form of 3D texture analysis to delineate the fibrillar morphology observed in SHG images of normal stroma and a spectrum of ovarian benign and malignant tumors (6 classes). We developed a tailored set of 3D filters which extract textural features in the 3D image sets to build statistical models of each class.  By applying k-nearest neighbor classification using these models, we achieved 83-91% accuracies for the six classes. This classification based on ECM structural changes will complement conventional classification based on genetic profiles and can serve as an additional biomarker.