No abstract

Signet ring cell carcinoma is a type of rare adenocarcinoma with poor prognosis. Early detection leads to huge improvement of patients' survival rate. However, pathologists can only visually detect signet ring cells under the microscope. This procedure is not only laborious but also prone to omission. An automatic and accurate signet ring cell detection solution is thus important but has not been investigated before. In this paper, we take the first step to present a semi-supervised learning framework for the signet ring cell detection problem. Self-training is proposed to deal with the challenge of incomplete annotations, and cooperative-training is adapted to explore the unlabeled regions. Combining the two techniques, our semi-supervised learning framework can make better use of both labeled and unlabeled data. Experiments on large real clinical data demonstrate the effectiveness of our design. Our framework achieves accurate signet ring cell detection and can be readily applied in the clinical trails. The dataset will be released soon to facilitate the development of the area.

Rationale: Glioblastoma (GBM) is the most common and aggressive brain tumor, characterized by its propensity to invade the surrounding brain parenchyma. The effect of extracellular high-mobility group box 1 (HMGB1) protein on glioblastoma (GBM) progression is still controversial. p62 is overexpressed in glioma cells, and has been associated with the malignant features and poor prognosis of GBM patients. Hence, this study aimed to clarify the role of p62 in HMGB1-induced epithelial-mesenchymal transition (EMT) of GBM both in vitro and in vivo . Methods: Immunoblotting, immunofluorescence and qRT-PCR were performed to evaluate EMT progression in both human GBM cell line and primary GBM cells. Transwell and wound healing assays were used to assess the invasion and migration of GBM cells. shRNA technique was used to investigate the role of p62 in HMGB1-induced EMT both in vitro and in vivo orthotopic tumor model. Co-immunoprecipitation assay was used to reveal the interaction between p62 and GSK-3β (glycogen synthase kinase 3 beta). Immunohistochemistry was performed to detect the expression levels of proteins in human GBM tissues. Results: In this study, GBM cells treated with recombinant human HMGB1 (rhHMGB1) underwent spontaneous EMT through GSK-3β/Snail signaling pathway. In addition, our study revealed that rhHMGB1-induced EMT of GBM cells was accompanied by p62 overexpression, which was mediated by the activation of TLR4-p38-Nrf2 signaling pathway. Moreover, the results demonstrated that p62 knockdown impaired rhHMGB1-induced EMT both in vitro and in vivo . Subsequent mechanistic investigations showed that p62 served as a shuttling factor for the interaction of GSK-3β with proteasome, and ultimately activated GSK-3β/Snail signaling pathway by augmenting the degradation of GSK-3β. Furthermore, immunohistochemistry analysis revealed a significant inverse correlation between p62 and GSK-3β, and a combination of the both might serve as a more powerful predictor of poor survival in GBM patients. Conclusions: This study suggests that p62 is an effector for HMGB1-induced EMT, and may represent a novel therapeutic target in GBM.