The current tumour-node-metastasis (TNM) staging system alone cannot provide adequate information for prognosis and adjuvant chemotherapy benefits in patients with gastric cancer (GC). Pathomics, which is based on the development of digital pathology, is an emerging field that might improve clinical management. Herein, we propose a pathomics signature (PS_GC) that is derived from multiple pathomics features of haematoxylin and eosin-stained slides. We find that the PS_GC is an independent predictor of prognosis. A nomogram incorporating the PS_GC and TNM staging system shows significantly improved accuracy in predicting the prognosis compared to the TNM staging system alone. Moreover, in stage II and III GC patients with a low PS_GC (but not in those with a high PS_GC), satisfactory chemotherapy benefits are observed. Therefore, the PS_GC could serve as a prognostic predictor in patients with GC and might be a potential predictive indicator for decision-making regarding adjuvant chemotherapy.

Accurate prediction of peritoneal metastasis for gastric cancer (GC) with serosal invasion is crucial in clinic. The presence of collagen in the tumour microenvironment affects the metastasis of cancer cells. Herein, we propose a collagen signature, which is composed of multiple collagen features in the tumour microenvironment of the serosa derived from multiphoton imaging, to describe the extent of collagen alterations. We find that a high collagen signature is significantly associated with a high risk of peritoneal metastasis (P < 0.001). A competing-risk nomogram including the collagen signature, tumour size, tumour differentiation status and lymph node metastasis is constructed. The nomogram demonstrates satisfactory discrimination and calibration. Thus, the collagen signature in the tumour microenvironment of the gastric serosa is associated with peritoneal metastasis in GC with serosal invasion, and the nomogram can be conveniently used to individually predict the risk of peritoneal metastasis in GC with serosal invasion after radical surgery.

Histopathology forms the gold standard for the diagnosis of breast cancer. Multiphoton microscopy (MPM) has been proposed to be a potentially powerful adjunct to current histopathological techniques. A label-free imaging based on two- photon excited fluorescence and second-harmonic generation is developed for differentiating normal breast tissues, benign, as well as breast cancer tissues. Human breast biopsies (including human normal breast tissues, benign as well as breast cancer tissues ) that are first imaged (fresh, unfixed, and unstained) with MPM and are then processed for routine H-E histopathology. Our results suggest that the MPM images, obtained from these unprocessed biopsies, can readily distinguish between benign lesions and breast cancers. In the tissues of breast cancers, MPM showed that the tumor cells displayed marked cellular and nuclear pleomorphism. The tumor cells, characterized by irregular size and shape, enlarged nuclei, and increased nuclear-cytoplasmic ratio, infiltrated into disrupted connective tissue, leading to the loss of second-harmonic generation signals. For breast cancer, MPM diagnosis was 100% correct because the tissues of breast cancers did not have second-harmonic generation signals in MPM imaging. On the contrary, in benign breast masses, second-harmonic generation signals could be seen easily in MPM imaging. These observations indicate that MPM could be an important potential tool to provide label-free noninvasive diagnostic impressions that can guide surgeon in biopsy and patient management.

Ultrashort peptide applications in bionanotechnology.

Multiphoton microscopy was used to study the extracellular matrix of keloid at the molecular level without tissue fixation and staining. Direct imaging of collagen and elastin was achieved by second harmonic generation and two-photon excited fluorescence, respectively. The morphology and quantity of collagen and elastin in keloid were characterized and quantitatively analyzed in comparison to normal skin. The study demonstrated that in keloid, collagen content increased in both the upper dermis and the deep dermis, while elastin mostly showed up in the deep dermis and its quantity is higher compared to normal skin. This suggests the possibility that abnormal fibroblasts synthesized an excessive amount of collagen and elastin at the beginning of keloid formation, corresponding to the observed deep dermis, while after a certain time point, the abnormal fibroblast produced mostly collagen, corresponding to the observed upper dermis. The morphology of collagen and elastin in keloid was disrupted and presented different variations. In the deep dermis, elastic fibers showed node structure, while collagen showed obviously regular gaps between adjacent bundles. In the upper dermis, collagen bundles aligned in a preferred direction, while elastin showed as sparse irregular granules. This new molecular information provided fresh insight about the development process of keloid.