Mutual information network-based support vector machine strategy identifies salivary biomarkers in gastric cancer.

PURPOSE: To determine the vital salivary transcriptomic biomarkers for the early detection of gastric cancer via comparing classification efficiency of multiple candidate genes. METHODS: We firstly identified 5 kinds of candidate genes related to gastric cancer, including differential pathway genes (DPGs) based on the attract method, hub genes in differential pathways based on mutual information network (MIN) analysis, differentially expressed genes (DEGs) identified by Significance Analysis of Microarrays (SAM), informative genes (DEGs in differential pathways), and key genes (hub DEGs). Then, the classification efficiency of these 5 kinds of candidate genes were assessed using support vector machines (SVM) model. The genes with the best classification efficiency were considered as salivary biomarkers in gastric cancer. RESULTS: Using the attract method, we screened 5 differential pathways in gastric cancer, in which there were 349 DPGs. Based on these DPGs, MIN with 345 genes and 1313 interactions was constructed, from which we obtained 26 hub genes by topological analysis. Meanwhile, we identified 374 DEGs in gastric cancer. Combining DEGs with DPGs and hub genes respectively, we selected 16 informative genes and 5 key genes. SVM analysis showed that the key genes presented the best classification efficiency with AUC=0.99, specificity=1.00, sensitivity=0.98 and MCC=0.95, which would be considered as salivary biomarkers in gastric cancer. CONCLUSIONS: This study successfully explored several salivary biomarkers for the non-invasive detection of gastric cancer with high specificity and sensitivity, which might contribute to the early detection and treatment of gastric cancer.

PRISMA-Compliant Article: Clinical Characteristics and Factors Influencing Prognosis of Patients With Hepatoid Adenocarcinoma of the Stomach in China.

Most previous studies have been single case reports, and studies with large samples are presently lacking. In addition, no studies have investigated the associations between the clinical characteristics and prognosis of hepatoid adenocarcinoma of the stomach (HAS). The aim of this study was to explore the associations of different clinical characteristics with the ages, serum alpha-fetoprotein (AFP) levels, and survival times of HAS patients. The present study was conducted using the CBM disc, HowNet, Wanfang and VIP data resource systems, and PubMed. According to the PRISMA Flow Diagram, certain case reports from the same center, those that did not provide patient age or sex, and those that did not report serum AFP levels or AFP immunohistochemistry results were excluded. A total of 131 relevant articles, including 124 case reports, 5 reviews, and 2 postgraduate Master's theses, were reported in the above-mentioned five databases. We applied inclusion criteria to case reports on the clinical characteristics and prognosis of HAS, which resulted in the ultimate inclusion of 180 patients from 62 case reports for statistical analyses. The main finding was that the age of the men was significantly higher than that of the women (P = 0.004). In addition, the serum AFP levels of the participants with antral disease were significantly higher than those with nonantral disease (P = 0.001). The median serum AFP levels and survival times significantly differed among the patients with the three lesion types (P = 0.001 and 0.019, respectively). The serum AFP levels of the participants with ulcerative-upheaval-type tumors and purely ulcerative tumors were significantly higher than those with upheaval-type tumors (P = 0.000 and 0.017, respectively). In addition, the serum AFP levels of the participants with ulcerative-upheaval-type tumors were significantly higher than those with ulcerative-type tumors (P = 0.019), and their survival time was also significantly higher (P = 0.000). The serum AFP levels of the participants without metastasis or liver metastasis were significantly lower than those with metastasis or liver metastasis (P = 0.000 and 0.000, respectively), and their survival time was significantly longer (P = 0.000 and 0.001, respectively). Finally, the survival time of the participants treated with surgery was significantly longer than those treated using nonsurgical methods (P = 0.046). However, survival analysis revealed that the survival time was only significantly associated with the presence of metastasis (P = 0.002) and liver metastasis (P = 0.036). The main limitations of this study are as follows: it was a retrospective analysis of published case reports, the clinical data were incomplete, and the cases included in subgroup analyses were different. Our study results have demonstrated that the prognosis of HAS patients is poor. In addition, the survival time is significantly negatively correlated with the presence of metastasis and liver metastasis.

Prenatal diagnosis by array-based comparative genomic hybridization in the clinical laboratory setting.

Array-based comparative genomic hybridization (array CGH), a method used to detect gains or losses of genetic material, has recently been applied to prenatal diagnosis of genomic imbalance in the clinical laboratory setting. This new and exciting diagnostic tool represents a major technological step forward in cytogenetic testing and addresses many of the limitations of current cytogenetic methods. Conventional chromosome analysis, the current gold standard in prenatal diagnosis, focuses primarily on the detection of common aneuploidies and is limited by its capacity to detect only those copy number changes that are large enough to be microscopically visible (typically 5-6 Mb in size at the 500 band level). In contrast, array CGH analysis simultaneously evaluates regions across the entire genome and allows for detection of unbalanced structural and numerical chromosome abnormalities of less than one hundred kb. Array CGH analysis also overcomes some of the limitations of chromosome analysis, such as the requirement for cell culture and longer reporting time, by using direct uncultured fetal specimens. With many diagnostic laboratories now embracing this technology, the past year has seen tremendous growth in the use of array CGH analysis for prenatal diagnosis. This review aims to summarize array CGH methodology and its current applications in prenatal diagnosis.