Investigating ego modules and pathways in osteosarcoma by integrating the EgoNet algorithm and pathway analysis

Osteosarcoma (OS) is the most common primary bone malignancy, but current therapies are far from effective for all patients. A better understanding of the pathological mechanism of OS may help to achieve new treatments for this tumor. Hence, the objective of this study was to investigate ego modules and pathways in OS utilizing EgoNet algorithm and pathway-related analysis, and reveal pathological mechanisms underlying OS. The EgoNet algorithm comprises four steps: constructing background protein-protein interaction (PPI) network (PPIN) based on gene expression data and PPI data; extracting differential expression network (DEN) from the background PPIN; identifying ego genes according to topological features of genes in reweighted DEN; and collecting ego modules using module search by ego gene expansion. Consequently, we obtained 5 ego modules (Modules 2, 3, 4, 5, and 6) in total. After applying the permutation test, all presented statistical significance between OS and normal controls. Finally, pathway enrichment analysis combined with Reactome pathway database was performed to investigate pathways, and Fisher's exact test was conducted to capture ego pathways for OS. The ego pathway for Module 2 was CLEC7A/inflammasome pathway, while for Module 3 a tetrasaccharide linker sequence was required for glycosaminoglycan (GAG) synthesis, and for Module 6 was the Rho GTPase cycle. Interestingly, genes in Modules 4 and 5 were enriched in the same pathway, the 2-LTR circle formation. In conclusion, the ego modules and pathways might be potential biomarkers for OS therapeutic index, and give great insight of the molecular mechanism underlying this tumor.

Specific alterations in plasma proteins during depressed, manic, and euthymic states of bipolar disorder

Bipolar disorder (BD) is a common psychiatric mood disorder affecting more than 1-2% of the general population of different European countries. Unfortunately, there is no objective laboratory-based test to aid BD diagnosis or monitor its progression, and little is known about the molecular basis of BD. Here, we performed a comparative proteomic study to identify differentially expressed plasma proteins in various BD mood states (depressed BD, manic BD, and euthymic BD) relative to healthy controls. A total of 10 euthymic BD, 20 depressed BD, 15 manic BD, and 20 demographically matched healthy control subjects were recruited. Seven high-abundance proteins were immunodepleted in plasma samples from the 4 experimental groups, which were then subjected to proteome-wide expression profiling by two-dimensional electrophoresis and matrix-assisted laser desorption/ionization-time-of-flight/time-of-flight tandem mass spectrometry. Proteomic results were validated by immunoblotting and bioinformatically analyzed using MetaCore. From a total of 32 proteins identified with 1.5-fold changes in expression compared with healthy controls, 16 proteins were perturbed in BD independent of mood state, while 16 proteins were specifically associated with particular BD mood states. Two mood-independent differential proteins, apolipoprotein (Apo) A1 and Apo L1, suggest that BD pathophysiology may be associated with early perturbations in lipid metabolism. Moreover, down-regulation of one mood-dependent protein, carbonic anhydrase 1 (CA-1), suggests it may be involved in the pathophysiology of depressive episodes in BD. Thus, BD pathophysiology may be associated with early perturbations in lipid metabolism that are independent of mood state, while CA-1 may be involved in the pathophysiology of depressive episodes.