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OBJECTIVE: Tumor heterogeneity renders identification of suitable biomarkers of gastric cancer (GC) challenging. Here, we aimed to identify prognostic genes of GC using computational analysis. METHODS: We first used microarray technology to profile gene expression of GC and paired nontumor tissues from 198 patients. Based on these profiles and patients' clinical information, we next identified prognostic genes using novel computational approaches. Phosphoglucose isomerase, also known as glucose-6-phosphate isomerase (GPI), which ranked first among 27 candidate genes, was further investigated by a new analytical tool namely enviro-geno-pheno-state (E-GPS) analysis. Suitability of GPI as a prognostic marker, and its relationship with physiological processes such as metabolism, epithelial-mesenchymal transition (EMT), as well as drug sensitivity were evaluated using both our own and independent public datasets. RESULTS: We found that higher expression of GPI in GC correlated with prolonged survival of patients. Particularly, a combination of CDH2 and GPI expression effectively stratified the outcomes of patients with TNM stage II/III. Down-regulation of GPI in tumor tissues correlated well with depressed glucose metabolism and fatty acid synthesis, as well as enhanced fatty acid oxidation and creatine metabolism, indicating that GPI represents a suitable marker for increased probability of EMT in GC cells. CONCLUSIONS: Our findings strongly suggest that GPI acts as a novel biomarker candidate for GC prognosis, allowing greatly enhanced clinical management of GC patients. The potential metabolic rewiring correlated with GPI also provides new insights into studying the relationship between cancer metabolism and patient survival.
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Purpose: Emerging evidence has shown that long noncoding RNAs (lncRNAs) participate in oncogenesis and tumor progression. We previously found a novel lncRNA p4516 which was closely associated with prognosis by preliminary study of lncRNA expression profile from paired tumors and nontumor tissues in 198 gastric cancer (GC) patients. However, the exact biological functions and the underlying molecular mechanisms of p4516 in gastric tumorigenesis still remain unclear. Materials and methods: The RNA fluorescence in situ hybridization (RNA-FISH) analysis, cytoplasmic and nuclear RNA isolation and qRT-PCR were applied to determine the subcellular localization of p4516. Expression levels of p4516 were assessed using qRT-PCR in both GC cell lines and in 142 primary GC tissues. Correlations between p4516 expression and GC patients' clinicopathological parameters were analyzed. Gain- and loss-of-function experiments were employed to investigate the role of p4516 in proliferation, migration and invasion both in vitro and in vivo. In addition, Western blotting and immunohistochemical staining were used to examine the protein expression levels. Results: LncRNA p4516 was mainly localized in the nucleus of GC cells and p4516 tended to have higher expression levels in GC cells compared to the normal gastric mucosa-derived cells GES-1. Furthermore, higher expression levels of p4516 correlated with worse clinical outcomes in GC patients and acted as an independent prognostic biomarker. Functional analysis revealed that p4516 participated in the regulation of GC cell proliferation, invasion and migration both in vivo and in vitro. Moreover, p4516 was involved in epithelial-mesenchymal transition (EMT) in GC cells. Conclusion: Our study demonstrated the oncogenic role of novel lncRNA p4516 in the gastric carcinogenesis for the first time. High expression of p4516 may act as prognostic marker in patient with gastric cancer.
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The Jiaosi Hot Spring Region is one of the most famous tourism destinations in Taiwan. The spring water is processed for various uses, including irrigation, aquaculture, swimming, bathing, foot spas, and recreational tourism. Moreover, the multipurpose uses of spring water can be dictated by the temperature of the water. To evaluate the suitability of spring water for these various uses, this study spatially characterized the spring water temperatures of the Jiaosi Hot Spring Region by integrating ordinary kriging (OK), sequential Gaussian simulation (SGS), and Geographic information system (GIS). First, variogram analyses were used to determine the spatial variability of spring water temperatures. Next, OK and SGS were adopted to model the spatial uncertainty and distributions of the spring water temperatures. Finally, the land use (i.e., agriculture, dwelling, public land, and recreation) was determined using GIS and combined with the estimated distributions of the spring water temperatures. A suitable development strategy for the multipurpose uses of spring water is proposed according to the integration of the land use and spring water temperatures. The study results indicate that the integration of OK, SGS, and GIS is capable of characterizing spring water temperatures and the suitability of multipurpose uses of spring water. SGS realizations are more robust than OK estimates for characterizing spring water temperatures compared to observed data. Furthermore, current land use is almost ideal in the Jiaosi Hot Spring Region according to the estimated spatial pattern of spring water temperatures.
