Integration-based co-expression network analysis to investigate tumor-associated modules across three cancer types / 生物工程学报

In case/control gene expression data, differential expression (DE) represents changes in gene expression levels across various biological conditions, whereas differential co-expression (DC) represents an alteration of correlation coefficients between gene pairs. Both DC and DE genes have been studied extensively in human diseases. However, effective approaches for integrating DC-DE analyses are lacking. Here, we report a novel analytical framework named DC&DEmodule for integrating DC and DE analyses and combining information from multiple case/control expression datasets to identify disease-related gene co-expression modules. This includes activated modules (gaining co-expression and up-regulated in disease) and dysfunctional modules (losing co-expression and down-regulated in disease). By applying this framework to microarray data associated with liver, gastric and colon cancer, we identified two, five and two activated modules and five, five and one dysfunctional module(s), respectively. Compared with the other methods, pathway enrichment analysis demonstrated the superior sensitivity of our method in detecting both known cancer-related pathways and those not previously reported. Moreover, we identified 17, 69, and 11 module hub genes that were activated in three cancers, which included 53 known and three novel cancer prognostic markers. Random forest classifiers trained by the hub genes showed an average of 93% accuracy in differentiating tumor and adjacent normal samples in the TCGA and GEO database. Comparison of the three cancers provided new insights into common and tissue-specific cancer mechanisms. A series of evaluations demonstrated the framework is capable of integrating the rapidly accumulated expression data and facilitating the discovery of dysregulated processes.

Advances in the research of extracellular matrix protein prediction tools / 生物工程学报

Extracellular matrix (ECM) proteins play an important role in a series of biological processes in the cell, and their abnormal regulation can lead to many diseases. The theoretical ECM reference dataset is the basis for efficient identification of extracellular matrix proteins. Researchers have developed various ECM protein prediction tools based on machine learning methods. In this review, the main strategy of development of ECM protein prediction tools that based on machine learning methods has been introduced. Then, advances and specific characters of the existing ECM protein prediction tools have been summarized. Finally, the challenges and possible improvements of ECM protein prediction tools are discussed.

Expression of CD147, MMP-9 and HER-2 in patients with gastric cancer and their correlation with clinicopathology and prognosis / 中国基层医药

Objective@#To investigate the correlation between the expression of extracellular matrix metalloproteinase-inducible factor (CD147), matrix metalloproteinase-9 (MMP-9) and human epidermal growth factor receptor-2 (HER-2) in gastric cancer tissues and clinical pathology and prognosis.@*Methods@#From June 2016 to June 2018, 80 gastric cancer specimens from the First People's Hospital of Taizhou were collected as observation group, and another 60 normal specimens of gastric mucosa adjacent to cancer were selected as control group.The expressions of CD147, MMP-9 and HER-2 were detected by SP immunohistochemical method.The positive rates of CD147, MMP-9 and HER-2 protein expression, the positive rates of CD147, MMP-9 and HER-2 protein expression in different pathological characteristics, and the positive rates of CD147, MMP-9 and HER-2 protein expression in different prognosis were compared between the two groups.@*Results@#The positive rates of CD147 (73.75%), MMP-9 (76.25%) and HER-2 (42.50%) in the observation group were higher than those in the control group (21.67%, 25.00%, 5.00%), the differences were statistically significant (χ2=37.233, 36.288, 24.797, all P<0.05). There were no statisticallysignificant differences in the positive expression rates of CD147, MMP-9 and HER-2 protein among different gender, age, tumor diameter and differentiation (all P>0.05). The positive rates of CD147 (93.88%), MMP-9 (95.92%) and HER-2 (61.22%) with lymph node metastasis were higher than those without lymph node metastasis (41.94%, 45.16%, 12.90%), the differences were statistically significant (χ2=26.462, 27.012, 18.142, all P<0.05). The positive rates of CD147 (96.15%), MMP-9 (92.31%) and HER-2 (69.23%) in the death group were higher than those in the survival group (62.96%, 68.52%, 29.63%), the differences were statistically significant(χ2=9.987, 5.484, 11.263, all P<0.05).@*Conclusion@#High expression of CD147, MMP-9 and HER-2 proteins in gastric cancer tissues is closely related to invasion and metastasis, which can become a new prognostic marker and therapeutic target of gastric cancer.