Data reduction techniques in gas chromatography-mass spectrometry-based untargeted metabolomics has made the following workflow of data analysis more lucid. However, the normalization process still perplexes researchers, and its effects are always ignored. In order to reveal the influences of normalization method, five representative normalization methods (mass spectrometry total useful signal, median, probabilistic quotient normalization, remove unwanted variation-random, and systematic ratio normalization) were compared in three real data sets with different types. First, data reduction techniques were used to refine the original data. Then, quality control samples and relative log abundance plots were utilized to evaluate the unwanted variations and the efficiencies of normalization process. Furthermore, the potential biomarkers which were screened out by the Mann-Whitney U test, receiver operating characteristic curve analysis, random forest, and feature selection algorithm Boruta in different normalized data sets were compared. The results indicated the determination of the normalization method was difficult because the commonly accepted rules were easy to fulfill but different normalization methods had unforeseen influences on both the kind and number of potential biomarkers. Lastly, an integrated strategy for normalization method selection was recommended.

Colorectal cancer has a common cause of morbidity and mortality. Therefore, it is urgent to detect reliable biomarkers to predict prognosis in CRC. Here, we determined the expression of TIMP-2 and MMP-9 in a  CRC tissue microarray by immunohistochemistry. We found that lower TIMP-2 or/and higher MMP-9 expression in cancer tissues was correlated with poorer overall survival (OS). TIMP-2 or MMP-9 expression was independent prognostic factors for CRC. Furthermore, TIMP-2 and MMP-9 expression had a synergistic role as efficient prognostic indicators for CRC patients. In vitro and in vivo, TIMP-2 could inhibit HCT 116 cells invasion and migration by regulating MMP-9. In sum, a combined expression of TIMP-2 and MMP-9 as efficient prognostic indicators was found for the first time.

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Background: At present, the expression of MOR1 and its function in gastric cancer remains unclear with evidence suggesting that it is to be involved in tumor progression and metastasis. The study was to assess the clinicopathologic relevance and prognostic value of MOR1 expression in gastric cancer. Methods: Real-time quantitative RT-PCR and immunohistochemical staining were used to detect MOR1 expression in primary gastric cancerous surgical specimens and adjacent nontumorous tissues. Results: High MOR1 expression was detected in cancerous tumor compared with their adjacent nontumorous tissues. In addition, the chi-square test revealed that high MOR1 expression was significantly correlated with depth of invasion (p = 0.006), lymph node metastasis (p = 0.001), distant metastasis (p = 0.017), and TNM staging (p = 0.027). Moreover, Kaplan-Meier analysis revealed a significant association between MOR1 expression and overall survival. High expression of MOR1 was identified as an independent and significant predictor gene of reduced postoperative survival. Conclusion: We conclude that MOR1 expression may be a useful biomarker for better prediction of the clinical outcome and management of gastric cancer patients. Clin Trans Sci 2015; Volume 8: 137-142