Classification of Microcalcification Clusters Using Bilateral Features Based on Graph Convolutional Network.

Breast cancer is one of the diseases with the highest incidence and mortality among women in the world, which has posed a serious threat to women's health. The appearance of clustered calcifications is one of the important signs of breast cancer, and thus how to classify clustered calcifications comes to be a key breakthrough in controlling breast cancer. In this study, the discriminant model based on image convolution is used to learn the image features related to the classification of clustered microcalcifications, and the graph convolutional network (GCN) based on topological graph is used to learn the spatial distribution characteristics of clustered microcalcifications. These two models are fused to obtain a complementary model of image information and spatial information. The results show that the performance of the fusion model proposed in this paper is obviously superior to that of the two classification models in the classification of clustered microcalcification.

TREX1 suppression imparts cancer-stem-cell-like characteristics to CD133- osteosarcoma cells through the activation of E2F4 signaling.

There is ongoing debate whether cancer stem cells (CSCs) could arise from the transformation of non-CSCs under specific conditions. In the present study, the role of the three prime repair exonuclease 1 (TREX1) in regulating CSC generation form human osteosarcoma cells was investigated. High, intermediate and low levels of TREX1 expression were respectively observed in low-grade, high-grade and metastatic human osteosarcoma samples, while the opposite tendency was observed for E2F4, a transcription factor associated with G2 arrest. Luciferase assay proved that TREX1 had a negative impact on the activity of E2F4 promoter. TREX1 was highly expressed in CD133- HOS cells (non-CSC osteosarcoma cells) compared to CD133+ ones; whereas TREX1 knockdown endowed the CD133- non-CSCs with CSC-like characteristics in vitro relying on E2F4 activation, as demonstrated by enlarged proportion of the subset expressing CSC markers in flow cytometry analysis, enhanced self-renewal ability in osteosphere formation assay, increased metastasis capacity in migration and invasion assays, together with improved chemoresistance to cisplatin. Furthermore, TREX1 knockdown and subsequent E2F4 activation could promote the tumorigenicity of CD133- non-CSCs in vivo. With respect to underlying mechanisms, it was found that in CD133- HOS cells, TREX1 suppression would allow the activation of ß-catenin signaling in the dependence of E2F4, thus possibly leading to the up-regulation of the transcription factor OCT4. These findings suggested that TREX1 was probably a negative regulator of CSC formation and hence worth to be further studied for developing new treatments in cancer therapies targeting CSCs.

Verification of TREX1 as a promising indicator of judging the prognosis of osteosarcoma.

BACKGROUND: The study aimed to explore the correlation between the expression of TREX1 and the metastasis and the survival time of patients with osteosarcoma as well as biological characteristics of osteosarcoma cells for the prognosis judgment of osteosarcoma. METHOD: The correlation between the expression of TREX1 protein and the occurrence of pulmonary metastasis in 45 cases of osteosarcoma was analyzed. The CD133+ and CD133- cell subsets of osteosarcoma stem cells were sorted by the flow cytometry. The tumorsphere culture, clone formation, growth curve, osteogenic and adipogenic differentiation, tumor-formation ability in nude mice, sensitivity of chemotherapeutic drugs, and other cytobiology behaviors were compared between the cell subsets in two groups; the expressions of stem cell-related genes Nanog and Oct4 were compared; The expressions of TREX1 protein and mRNA were compared between the cell subsets in two groups. The data was statistically analyzed. The measurement data between the two groups were compared using t test. The count data between the two groups were compared using χ 2 test and Kaplan-Meier survival analysis. A P value <0.05 indicated that the difference was statistically significant. RESULTS: The expression of TREX1 protein in patients with osteosarcoma in the metastasis group was significantly lower than that in the non-metastasis group. The difference was statistically significant (P < 0.05). Up to the last follow-up visit, the former average survival time was significantly lower than that of the latter, and the difference was statistically significant (P < 0.05). The expression of TREX1 in human osteosarcoma CD133+ cell subsets was significantly lower than that in CD133- cell subsets. Stemness-related genes Nanog and Oct4 were highly expressed in human osteosarcoma CD133+ cell subsets with lower expression of TREX1; the biological characteristics identification experiment showed that human CD133+ cell subsets with low TREX1 expression could form tumorspheres, the number of colony forming was more, the cell proliferation ability was strong, the osteogenic and adipogenic differentiation potential was big, the tumor-forming ability in nude mice was strong, and the sensibility of chemotherapeutics drugs on cisplatin was low. CONCLUSIONS: The expression of TREX1 may be related to metastasis in patients with osteosarcoma. The expression of TREX1 was closely related to the cytobiology characteristics of osteosarcoma stem cell. TREX1 can play an important role in the occurrence and development processes. And, TREX1 is expected to become an effective new index for the evaluation of the prognosis.