Breast cancer (BC) is a significant health concern for women, with its classification into multiple stages contingent upon the dimensions of the tumor, the extent of lymph node involvement, and the presence of distant metastasis. Despite the application of uniform treatment protocols to cases of similar staging, the outcomes are subject to variability due to the inherent heterogeneity of the disease, highlighting an urgent need for further investigation. The tumor microenvironment (TME) plays a pivotal role in tumor progression and metastasis, with collagen fibers emerging as a critical component of the TME that is implicated in these processes. However, the precise interplay between collagen fibers and tumor staging remains to be elucidated. Advancements in multiphoton microscopy (MPM), which capitalizes on nonlinear optical phenomena, have yielded impressive imaging capabilities, facilitating the real-time visualization of tumor histology and the quantification of metabolic activity within tumors. Recent studies have underscored the intricate relationship between collagen fibers and the dynamics of tumor evolution.
In this study, we utilized multiphoton microscopy to image three distinct tumor-associated collagen signatures (TACS) at the invasive front of the tumor. We then used MATLAB to extract the corresponding collagen morphological features and analyzed their correlation with clinical staging. Our results revealed significant changes in the morphological features of collagen fibers in TACS across different stages of BC at the tumor invasion front. Notably, the proportionate area and number of collagen fibers were found to be inversely correlated with the clinical staging risk group of the disease. Our findings offer new perspectives for the clinical staging of BC, providing valuable insights that may enhance the predictive accuracy of disease progression and prognostic outcomes.
The invasion and metastasis of tumor cells are not only related to the tumor cells themselves, but also closely intertwined with other components of the tumor microenvironment. The connective cells, including fibroblasts and myofibroblasts, play a crucial role in determining the remodeling of collagen fibers in the tumor microenvironment during the process of tumor invasion, which determinant of tumor migration. In this study, we used the multi-photon imaging system to identify two different prognostic tumor-associated collagen signatures (TACS4 and TACS6). Then, the multi-photon images were used to co-locate with HE images, and open-source convolutional neural network Hover-Net was used to segment, classify and quantifythe nuclear feature. Our results showed that the connective cells are opposed to tumor cells and do not mix with tumor cells in TACS4, while in TACS6, they are scattered promiscuously with tumor cells. The spatial distribution of connected cells in TACS4 is denser than that in TACS6. These differences in spatial distribution of connected cells may potentially have different prognostic information.
Tumor cell invasion and metastasis is closely related to various components in tumor microenvironment, and the spatial distribution of tumor cells may be linked to the tumor progression. The directionally distributed collagen fibers would lead to one-way migration of tumor cells, and misarranged collagen fibers allow tumor cells to multi-directional migration in tumor boundary, and therefore tumor cells present in different spatial distributions in the microenvironment. In this study, the open source convolutional neural network Hover-Net was used for segmentation and classification. After accurately segmenting tumor cells, spatial features were extracted. Our results indicated that there were significant differences in the spatial distribution of tumor cells in the two modes. These were further demonstrated to be potential different prognostic patterns.
Adipocytes are considered to be a critical cell type in the tumor microenvironment of breast cancer. Many studies have confirmed that adipocytes are not only found adjacent to cancer cells, but they also play an active role in the entire process of cancer development, progression, metastasis, and treatment response in breast cancer. Adipose tissue invasion (ATI) is a way of tumor cell metastasis, which not only indicates the poor prognosis of patients but also indicates the decline of survival rate. Multiphoton microscopy (MPM) with subcellular resolution based on second harmonic generation (SHG) and two-photon excited fluorescence (TPEF) is very suitable for real-time detecting morphological and structural changes in biological tissues without tissue staining and exogenous probe molecule. In this study, MPM was applied to identify the adipose tissue invasion in breast cancer patients. The results indicated that it is feasible to detect adipose tissue invasion with multiphoton microscopy, and to provide a new auxiliary tool for pathologists to quickly and effectively diagnose adipose tissue invasion.
The tumor microenvironment is now recognized as an important participant of tumor progression. As the most abundant extracellular matrix component in tumor microenvironment, collagen plays an important role in tumor development. The imaging study of collagen morphological characteristics in tumor microenvironment is of great significance for understanding the state of tumor. Multiphoton microscopy (MPM) based on second harmonic generation (SHG) and two-photon excitation fluorescence (TPEF) can be used to monitor the morphological changes of biological tissues without labeling. In this study, MPM was used to perform label-free imaging of the tumor border, the transition zone near the tumor, and the normal tissue away from the tumor sequentially from the center of the tumor in early invasive breast cancer samples. We found that collagen morphology varies significantly in different regions of breast cancer tumor tissue. The collagen content was further quantified and the results showed that the collagen content was significantly different in these three regions. The study of collagen remodeling around tumors may provide a new basis for optimal negative margin width of breast-conserving surgery and a new perspective for understanding tumor metastasis.
Psoriasis is a common chronic inflammatory skin disease with high prevalence, chronicity, disfiguration, disability. Real-time detection of psoriatic pathological characteristics by optical technology is of great significance for the diagnosis and treatment of psoriasis. We used multiphoton microscopy (MPM) imaging technology based on intrinsic nonlinear optical signals to image the skin of a mouse psoriasis model induced by imiquimod (IMQ). The changes of cells and collagen in psoriasis skin tissue were obtained and analyzed, comparing with the hematoxylin and eosin (H and E) stained image. We found that the MPM technique could clearly observe the differences between normal and psoriasis skin. This is of great significance to the pathogenesis of psoriasis and also provides adjuvant imaging method for the treatment of psoriasis.
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