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Background: This study sought to identify candidate biomarkers associated with gastric cancer (GC) prognosis based on an integrated bioinformatics analysis. Methods: First, the GSE54129 and GSE79973 data sets were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) identified between the 2 data sets were screened using the limma software package in R, and the intersection DEGs were obtained by a Venn analysis. Subsequently, gene clustering and a functional analysis were performed to explore the roles of the DEGs. The protein-protein interaction (PPI) network of the genes in clusters was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins. A survival analysis evaluated the associations between the candidate genes and the overall survival of GC patients. A drug-gene interaction analysis and an external data set analysis were conducted using The Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD) data set to validate the prognostic genes. Results: We extracted 421 intersection DEGs from the 2 GEO data sets. There were 5 gene clusters, and the functional analysis revealed that they were mainly associated with the extracellular matrix-receptor interaction pathway. The PPI interaction analysis identified the top 36 hub genes. The survival analysis revealed that 7 upregulated genes [i.e., platelet-derived growth factor receptor beta (PDGFRB), angiopoietin 2 (ANGPT2), vascular endothelial growth factor C (VEGFC), collagen type IV alpha 2 chain (COL4A2), collagen type IV alpha 1 chain (COL4A1), thrombospondin 1 (THBS1), and fibronectin 1 (FN1)] were associated with the survival prognosis of GC patients. The 20 drug-gene interaction pairs among the 4 genes and 18 drugs were obtained. Finally, TCGA-STAD data set was used to validate the expression levels of COL4A1, PDGFRB, and FN1. Conclusions: We found that 7 upregulated genes (i.e., PDGFRB, ANGPT2, VEGFC, COL4A2, COL4A1, THBS1, and FN1) were promising markers of prognosis in GC patients.
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Traditional macroscopic and microscopic identification methods of medicinal materials are economical and practical, but usually experience-based due to few chemical supports. Here histochemical evaluation on bioactive components of Coptidis Rhizoma (CR) in anatomic sections using laser microdissection and liquid chromatography-mass spectrometry (LMD-LC-MS) was developed to correlate the inner quality and outer features of materials from different growing areas. Results of a total 33 peaks representing potential different alkaloids were detected and 8 common peaks were identified as the major alkaloids, namely magnoflorine, thalifendine, columbamine, epiberberine, jatrorrhizine, coptisine, palmatine, and berberine. Six major alkaloids were quantified in the top and middle sections of raw materials and in their tissues and cells at the same time. Histochemical analyses showed consistent results with direct determination in raw materials and explained the reason why top sections of all samples contained higher contents of alkaloids by giving out attributions of each alkaloid in different anatomic sections. Besides, results manifested the distribution and accumulation rules of alkaloids in diverse tissues and cells of CR. This study demonstrates an effective and scientific way to correlate bioactive components and morphological features of medicinal materials, which is beneficial to future research, agriculture and application.