No abstract

Breast cancer (BRCA) represents the most common malignancy among women worldwide with high mortality. Radiotherapy is a prevalent therapeutic for BRCA that with heterogeneous effectiveness among patients. Here, we proposed to develop a gene expression-based signature for BRCA radiotherapy sensitivity estimation. Gene expression profiles of BRCA samples from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) were obtained and used as training and independent testing dataset, respectively. Differential expression genes (DEGs) in BRCA samples compared with their paracancerous samples in the training set were identified by using the edgeR Bioconductor package. Univariate Cox regression analysis and LASSO Cox regression method were applied to screen optimal genes for constructing a radiotherapy sensitivity estimation signature. Nomogram combining independent prognostic factors was used to predict 1-, 3-, and 5-year OS of radiation-treated BRCA patients. Relative proportions of tumor infiltrating immune cells (TIICs) calculated by CIBERSORT and mRNA levels of key immune checkpoint receptors was adopted to explore the relation between the signature and tumor immune response. As a result, 603 DEGs were obtained in BRCA tumor samples, six of which were retained and used to construct the radiotherapy sensitivity prediction model. The signature was proved to be robust in both training and testing sets. In addition, the signature was closely related to the immune microenvironment of BRCA in the context of TIICs and immune checkpoint receptors’ mRNA levels. In conclusion, the present study obtained a radiotherapy sensitivity estimation signature for BRCA, which should shed new light in clinical and experimental research.

We have evaluated the predictive ability of a simple method combing the efficient cluster packing model of metallic glasses proposed by Miracle, chemical mixing enthalpy and the normalized configurational entropy S config =R in rapidly locating the bulk metallic glass (BMG)-forming composition region, in four multicomponent alloy systems. It is shown that the BMG-forming regions are similar in the topologically and chemically equivalent La-Al-Co and Ce-Al-Co alloy systems. However, in the topologically equivalent Zr-Ti-Cu-Ni and Zr-Ti-Al-Cu-Ni alloy systems, the BMG-forming regions are quite different due to the difference in chemical bonding between constituents. BMG formation is most probably a compromise between topological and chemical effects. This method could be a new approach to rapidly locate BMG-forming composition region in multicomponent alloy systems, in which eutectic compositions are difficult to be measured in experiments.

No abstract

Background Papillary thyroid carcinoma (PTC) is one of most prevalent malignant endocrine neoplasms, and it is associated with a high frequency of BRAF gene mutations, which lead to lymphatic metastasis and distant metastasis that promote tumor progression. The molecular mechanism of PTC and the role of BRAF mutation in PTC progression and development need to be further elucidated. Methods In this study, a comprehensive bioinformatics analysis was performed to identify the differentially expressed genes and signaling pathways in thyroid cancer patients carrying mutant BRAF. Then, we confirmed the prognostic role of WT1 in thyroid cancer patients. Immunohistochemistry was performed to measure the expression profile of WT1 in PTC tissue. Lentivirus shWT1 was transfected into BRAFV600E (mutant) PTC cells to stably inhibit WT1 expression. CCK-8, EdU, immunofluorescence, colony formation, cell migration, cell wound healing, apoptosis and autophagy assays were performed to assess the biological functions of WT1 in BRAFV600E PTC cells. RNA sequencing, immunohistochemistry and immunoblotting were performed to explore the molecular mechanism of WT1 in BRAFV600E PTC cells. Results The results confirmed that “epithelial cell proliferation”, “apoptosis” and “selective autophagy” were closely associated with this BRAF mutant in these thyroid cancer patients. Knocking down BRAF-activated WT1 effectively inhibited the proliferation and migration of BRAFV600E PTC cells. Silencing WT1 significantly inhibited autophagy and promoted the apoptosis of BRAFV600E PTC cells. Mechanistic investigations showed that silencing WT1 expression remarkably suppressed the AKT/mTOR and ERK/P65 signaling pathways in BRAFV600E PTC cells. Conclusion All these results indicate that WT1 is a promising prognostic biomarker and facilitates PTC progression and development of cells carrying the BRAFV600E mutation.

No abstract

No abstract

No abstract