The development of metastases involves the dissociation of cells from the primary tumor, penetrating the basement membrane, invasion and exiting from the vasculature to seed, and finally colonizing in distant tissues. The formation of brain metastasis (BM) in lung adenocarcinoma remains poorly understood. We examined the differential microRNA (miRNA) expression profiles of 5 primary and 3 brain metastatic lung adenocarcinoma samples by Agilent miRNA Microarrays. Five upregulated miRNAs (miRs-9*, -1471, 718, 3656, 720) and 3 downregulated miRNAs (miRs-214, -145 and -23a) were detected. The 4 most significantly deregulated miRNAs (miR-145, miR-214, miR-9* and miR-1471) were validated in the additional 43 samples (35 primary and 8 brain metastatic lung adenocarcinoma samples) using TaqMan quantitative PCR. By functional assay, we found that the expression of miR-145 can regulate the ability of proliferation of A549 and SPC-A1 cells in vitro, but is not related to lymph node metastasis, migration and invasion. These results suggest that miR-145 may have a cell type-specific function and play important roles in the process of BM from lung adenocarcinoma.

Hepatocellular carcinoma (HCC) is a common malignant cancer with poor survival outcomes, and hepatitis B virus (HBV) infection is most likely to contribute to HCC. But the molecular mechanism remains obscure. Our study intended to identify the candidate potential hub genes associated with the carcinogenesis of HBV‐related HCC (HBV‐HCC), which may be helpful in developing novel tumor biomarkers for potential targeted therapies. Four transcriptome datasets (GSE84402, GSE25097, GSE94660, and GSE121248) were used to screen the 309 overlapping differentially expressed genes (DEGs), including 100 upregulated genes and 209 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to explore the biological function of DEGs. A PPI network based on the STRING database was constructed and visualized by the Cytoscape software, consisting of 209 nodes and 1676 edges. Then, we recognized 17 hub genes by CytoHubba plugin, which were further validated on additional three datasets (GSE14520, TCGA‐LIHC, and ICGC‐LIRI‐JP). The diagnostic effectiveness of hub genes was assessed with receiver operating characteristic (ROC) analysis, and all hub genes displayed good performance in discriminating TNM stage I patient samples and normal tissue ones. For prognostic analysis, two prognostic key genes (TOP2A and KIF11) out of the 17 hub genes were screened and used to develop a prognostic signature, which showed good potential for overall survival (OS) stratification of HBV‐HCC patients. Gene Set Enrichment Analysis (GSEA) was performed in order to better understand the function of this prognostic gene signature. Finally, the miRNA–mRNA regulatory relationships of all hub genes in human liver were predicted using miRNet. In conclusion, the current study gives further insight on the pathogenesis and carcinogenesis of HBV‐HCC, and the identified DEGs provide a promising direction for improving the diagnostic, prognostic, and therapeutic outcomes of HBV‐HCC.

The high risk of postoperative mortality in lung adenocarcinoma (LUAD) patients is principally driven by cancer recurrence and low response rates to adjuvant treatment. Here, A combined cohort containing 1,026 stage I–III patients was divided into the learning (n = 678) and validation datasets (n = 348). The former was used to establish a 16-mRNA risk signature for recurrence prediction with multiple statistical algorithms, which was verified in the validation set. Univariate and multivariate analyses confirmed it as an independent indicator for both recurrence-free survival (RFS) and overall survival (OS). Distinct molecular characteristics between the two groups including genomic alterations, and hallmark pathways were comprehensively analyzed. Remarkably, the classifier was tightly linked to immune infiltrations, highlighting the critical role of immune surveillance in prolonging survival for LUAD. Moreover, the classifier was a valuable predictor for therapeutic responses in patients, and the low-risk group was more likely to yield clinical benefits from immunotherapy. A transcription factor regulatory protein–protein interaction network (TF-PPI-network) was constructed via weighted gene co-expression network analysis (WGCNA) concerning the hub genes of the signature. The constructed multidimensional nomogram dramatically increased the predictive accuracy. Therefore, our signature provides a forceful basis for individualized LUAD management with promising potential implications.

Reduced Gray matter (GM) volume is a core feature of schizophrenia. Mapping genes that is associated with the heritable disease-related phenotypes may be conducive to elucidate the pathogenesis of schizophrenia. This study aims to identify the common genetic variants that underlie the deficits of GM volume in schizophrenia. High-resolution T1 images and whole genome genotyping data were obtained from 74 first-episode treatment-naïve patients with schizophrenia and 51 healthy controls in the Mental Health Centre of the West China Hospital, Sichuan University. All participants were scanned using a 3T MR imaging system and were genotyped using the HumanHap660 Bead Array. Reduced GM volumes in three brain areas including left hOC3v in the collateral sulcus of visual cortex (hOC3vL), left cerebellar vermis lobule 10 (vermisL10) and right cerebellar vermis lobule 10 (vermisR10) were found in patients with schizophrenia. There was a group by genotype interaction when genotypes from genome-wide scan were subsequently considered in the case-control analyses. SNPs from three genes or chromosomal regions (TBXAS1, PIK3C2G and HS3ST5) were identified to predict the changes of GM volume in hOC3vL, vermisL10 and vermisR10. These results also highlighted the usefulness of endophenotype in exploring the pathogenesis of neuropsychiatric diseases such as schizophrenia although further independent replication studies are needed in the future.

In this study, we successfully prepared MPEG–PDLLA polymer micelles with two different particle sizes, A and B. DLS and TEM assays demonstrated that the particle sizes of the polymer micelles A and polymer micelles B were about 25 nm and 150 nm respectively. The stability of the MPEG–PDLLA polymer micelles in vitro revealed that the free Cy5.5 dye had been successfully loaded into the polymer micelles as a fluorescence marker and the fluorescence wasn’t quenched until 72 h. The cellular uptake of the polymer micelles was time-dependent and micelles A (particle size 25 nm) showed a higher efficiency to be internalized into the cytoplasm of MCF-7 cells than micelles B (particle size 150 nm). Furthermore, in vivo and in vitro biodistribution and tumor-targeting of polymer micelles MPEG–PDLLA were investigated in female MCF-7 tumor-bearing balb/cA-nu mice with an IVIS imaging system. The results showed that polymer micelles A (particle size 25 nm) had a time dependent biodistribution and tumor site accumulation in mice bearing MCF-7 tumors. Meanwhile, the NIR fluorescence intensity of polymer micelles B (particle size 150 nm) in tumor sites showed a pattern of a rise, a peak and then a decline. What’s more, the distribution of the polymer micelles in the tissue slices demonstrated the same results. Consequently, the results indicated that the micelles with a smaller particle size (25 nm) could be more efficiently internalized into cells and increase the enhanced permeation and retention (EPR) effect in tumor tissue. Therefore, a reasonable small size of micelles may be a key factor for a high-performance anti-cancer drug delivery system.