Interactive gene identification for cancer subtyping based on multi-omics clustering.

Recent advances in multi-omics databases offer the opportunity to explore complex systems of cancers across hierarchical biological levels. Some methods have been proposed to identify the genes that play a vital role in disease development by integrating multi-omics. However, the existing methods identify the related genes separately, neglecting the gene interactions that are related to the multigenic disease. In this study, we develop a learning framework to identify the interactive genes based on multi-omics data including gene expression. Firstly, we integrate different omics based on their similarities and apply spectral clustering for cancer subtype identification. Then, a gene co-expression network is construct for each cancer subtype. Finally, we detect the interactive genes in the co-expression network by learning the dense subgraphs based on the L1 prosperities of eigenvectors in the modularity matrix. We apply the proposed learning framework on a multi-omics cancer dataset to identify the interactive genes for each cancer subtype. The detected genes are examined by DAVID and KEGG tools for systematic gene ontology enrichment analysis. The analysis results show that the detected genes have relationships to cancer development and the genes in different cancer subtypes are related to different biological processes and pathways, which are expected to yield important references for understanding tumor heterogeneity and improving patient survival.

Rapid Detection of Cysticercus cellulosae by an Up-Converting Phosphor Technology-Based Lateral-Flow Assay.

Cysticercosis is a neglected tropical disease caused by the larvae of Taenia solium in pigs and humans. The current diagnosis of porcine cysticercosis is difficult, and traditional pathological tests cannot meet the needs of detection. This study established a UPT-LF assay for the detection of Cysticercus cellulosae. UCP particles were bound to two antigens, TSOL18 and GP50; samples were captured, and the signal from the UCP particles was converted into a detectable signal for analysis using a biosensor. Compared to ELISA, UPT-LF has higher sensitivity and specificity, with a sensitivity of 93.59% and 97.44%, respectively, in the case of TSOL18 and GP50 antigens and a specificity of 100% for both. Given its rapidness, small volume, high sensitivity and specificity, and good stability and reproducibility, this method could be used in the diagnosis of cysticercosis.

PROTEOMIC ANALYSIS OF TAENIA SOLIUM CYST FLUID BY SHOTGUN LC-MS/MS.

Taenia solium cysts were collected from pig skeletal muscle and analyzed via a shotgun proteomic approach to identify known proteins in the cyst fluid and to explore host-parasite interactions. Cyst fluid was aseptically collected and analyzed with shotgun liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene alignment and annotation were performed using Blast2GO software followed by gene ontology analysis of the annotated proteins. The pathways were further analyzed with the Kyoto Encyclopedia of Genes and Genomes (KEGG), and a protein-protein interaction (PPI) network map was generated using STRING software. A total of 158 known proteins were identified, most of which were low-molecular-mass proteins. These proteins were mainly involved in cellular and metabolic processes, and their molecular functions were predominantly related to catalytic activity and binding functions. The pathway enrichment analysis revealed that the known proteins were mainly enriched in the PI3K-Akt and glycolysis/gluconeogenesis signaling pathways. The nodes in the PPI network mainly consisted of enzymes involved in sugar metabolism. The cyst fluid proteins screened in this study may play important roles in the interaction between the cysticerci and the host. The shotgun LC-MS/MS, gene ontology, KEGG, and PPI network map data will be used to identify and analyze the cyst fluid proteome of cysticerci, which will provide a basis for further exploration of the invasion and activities of T. solium.