BackgroundNonlinear optical (NLO) microscopy techniques have potential to improve the early detection of epithelial ovarian cancer. In this study we showed that multimodal NLO microscopies, including two-photon excitation fluorescence (TPEF), second-harmonic generation (SHG), third-harmonic generation (THG) and fluorescence lifetime imaging microscopy (FLIM) can detect morphological and metabolic changes associated with ovarian cancer progression.Methodology/Principal FindingsWe obtained strong TPEF + SHG + THG signals from fixed samples stained with Hematoxylin & Eosin (H&E) and robust FLIM signal from fixed unstained samples. Particularly, we imaged 34 ovarian biopsies from different patients (median age, 49 years) including 5 normal ovarian tissue, 18 serous tumors and 11 mucinous tumors with the multimodal NLO platform developed in our laboratory. We have been able to distinguish adenomas, borderline, and adenocarcinomas specimens. Using a complete set of scoring methods we found significant differences in the content, distribution and organization of collagen fibrils in the stroma as well as in the morphology and fluorescence lifetime from epithelial ovarian cells.Conclusions/SignificanceNLO microscopes provide complementary information about tissue microstructure, showing distinctive patterns for serous and mucinous ovarian tumors. The results provide a basis to interpret future NLO images of ovarian tissue and lay the foundation for future in vivo optical evaluation of premature ovarian lesions.

We used a multimodal nonlinear optics microscopy, specifically two-photon excited fluorescence (TPEF), second and third harmonic generation (SHG∕THG) microscopies, to observe pathological conditions of ovarian tissues obtained from human samples. We show that strong TPEF + SHG + THG signals can be obtained in fixed samples stained with hematoxylin and eosin (H&E) stored for a very long time, and that H&E staining enhanced the THG signal. We then used the multimodal TPEF-SHG-THG microscopies in a stored file of H&E stained samples of human ovarian cancer to obtain complementary information about the epithelium∕stromal interface, such as the transformation of epithelium surface (THG) and the overall fibrillary tissue architecture (SHG). This multicontrast nonlinear optics microscopy is able to not only differentiate between cancerous and healthy tissue, but can also distinguish between normal, benign, borderline, and malignant specimens according to their collagen disposition and compression levels within the extracellular matrix. The dimensions of the layers of epithelia can also be measured precisely and automatically. Our data demonstrate that optical techniques can detect pathological changes associated with ovarian cancer.

In this study we showed that second-harmonic generation (SHG) microscopy combined with precise methods for images evaluation can be used to detect structural changes in the human ovarian stroma. Using a set of scoring methods (alignment of collagen fibers, anisotropy, and correlation), we found significant differences in the distribution and organization of collagen fibers in the stroma component of serous, mucinous, endometrioid and mixed ovarian tumors as compared with normal ovary tissue. This methodology was capable to differentiate between cancerous and healthy tissue, with clear cut distinction between normal, benign, borderline, and malignant tumors of serous type. Our results indicated that the combination of different image-analysis approaches presented here represent a powerful tool to investigate collagen organization and extracellular matrix remodeling in ovarian tumors.

Second-harmonic generation microscopy represents an important tool to evaluate extracellular matrix collagen structure, which undergoes changes during cancer progression. Thus, it is potentially relevant to assess breast cancer development. We propose the use of second-harmonic generation images of tumor stroma selected on hematoxylin and eosin-stained slides to evaluate the prognostic value of collagen fibers analyses in peri and intratumoral areas in patients diagnosed with invasive ductal breast carcinoma. Quantitative analyses of collagen parameters were performed using ImageJ software. These parameters presented significantly higher values in peri than in intratumoral areas. Higher intratumoral collagen uniformity was associated with high pathological stages and with the presence of axillary lymph node metastasis. In patients with immunohistochemistry-based luminal subtype, higher intratumoral collagen uniformity and quantity were independently associated with poorer relapse-free and overall survival, respectively. A multivariate response recursive partitioning model determined 12.857 and 11.894 as the best cut-offs for intratumoral collagen quantity and uniformity, respectively. These values have shown high sensitivity and specificity to differentiate distinct outcomes. Values of intratumoral collagen quantity and uniformity exceeding the cut-offs were strongly associated with poorer relapse-free and overall survival. Our findings support a promising prognostic value of quantitative evaluation of intratumoral collagen by second-harmonic generation imaging mainly in the luminal subtype breast cancer.

In pulmonary acute respiratory distress syndrome, time-controlled adaptive ventilation led to more pronounced beneficial effects on expression of biomarkers related to overdistension and extracellular matrix homeostasis.

Abstract. We show that combined multimodal nonlinear optical (NLO) microscopies, including two-photon excitation fluorescence, second-harmonic generation (SHG), third harmonic generation, and fluorescence lifetime imaging microscopy (FLIM) can be used to detect morphological and metabolic changes associated with stroma and epithelial transformation during the progression of cancer and osteogenesis imperfecta (OI) disease. NLO microscopes provide complementary information about tissue microstructure, showing distinctive patterns for different types of human breast cancer, mucinous ovarian tumors, and skin dermis of patients with OI. Using a set of scoring methods (anisotropy, correlation, uniformity, entropy, and lifetime components), we found significant differences in the content, distribution and organization of collagen fibrils in the stroma of breast and ovary as well as in the dermis of skin. We suggest that our results provide a framework for using NLO techniques as a clinical diagnostic tool for human cancer and OI. We further suggest that the SHG and FLIM metrics described could be applied to other connective or epithelial tissue disorders that are characterized by abnormal cells proliferation and collagen assembly.

One of the promising tools to evaluate collagen in the extracellular matrix is the second-harmonic generation microscopy (SHG). This approach may shed light on the biological behavior of cancers and their taxonomy, but has not yet been applied to characterize collagen fibers in cases diagnosed as invasive breast carcinoma (BC) of histological special types (IBC-ST). Tissue sections from 99 patients with IBC-ST and 21 of invasive breast carcinoma of no special type (IBC-NST) were submitted to evaluation of collagen parameters by SHG. Tissue microarray was performed to evaluate immunohistochemical-based molecular subtype. In intratumoral areas, fSHG and bSHG (forward-SHG and backward-SHG) collagen parameters achieved their lowest values in mucinous, papillary and medullary carcinomas, whereas the highest values were found in classic invasive lobular and tubular carcinomas. Unsupervised hierarchical cluster analysis and minimal spanning tree using intratumoral collagen parameters allowed the identification of three main groups of breast cancer: group A (classic invasive lobular and tubular carcinomas); group B (IBC-NST, metaplastic, invasive apocrine and micropapillary carcinomas); and group C (medullary, mucinous and papillary carcinomas). Our findings provide further characterization of the tumor microenvironment of IBC-ST. This understanding may add information to build more consistent tumor categorization and to refine prognostication.

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