Core and specific network markers of carcinogenesis from multiple cancer samples.

Cancer is the leading cause of death worldwide and is generally caused by mutations in multiple proteins or the dysregulation of pathways. Understanding the causes and the underlying carcinogenic mechanisms can help fight this disease. In this study, a systems biology approach was used to construct the protein-protein interaction (PPI) networks of four cancers and the non-cancers by their corresponding microarray data, PPI modeling and database-mining. By comparing PPI networks between cancer and non-cancer samples to find significant proteins with large PPI changes during carcinogenesis process, core and specific network markers were identified by the intersection and difference of significant proteins, respectively, with carcinogenesis relevance values (CRVs) for each cancer. A total of 28 significant proteins were identified as core network markers in the carcinogenesis of four types of cancer, two of which are novel cancer-related proteins (e.g., UBC and PSMA3). Moreover, seven crucial common pathways were found among these cancers based on their core network markers, and some specific pathways were particularly prominent based on the specific network markers of different cancers (e.g., the RIG-I-like receptor pathway in bladder cancer, the proteasome pathway and TCR pathway in liver cancer, and the HR pathway in lung cancer). Additional validation of these network markers using the literature and new tested datasets could strengthen our findings and confirm the proposed method. From these core and specific network markers, we could not only gain an insight into crucial common and specific pathways in the carcinogenesis, but also obtain a high promising PPI target for cancer therapy.

Role of RASSF1A promoter methylation in the pathogenesis of ovarian cancer: a meta-analysis.

OBJECTIVE: The aim of the current meta-analysis was to comprehensively assess the role of RASSF1A promoter methylation in the pathogenesis of ovarian cancer. METHOD: A range of electronic databases were searched: Web of Science (1945-2013), the Cochrane Library Database (Issue 12, 2013), PubMed (1966-2013), EMBASE (1980-2013), CINAHL (1982-2013), and the Chinese Biomedical Database (1982-2013) without language restrictions. Meta-analysis was conducted using the STATA 12.0 software. The crude odds ratio (OR) with its corresponding 95% confidence interval (CI) was calculated. RESULTS: Twelve clinical cohort studies with a total of 739 ovarian cancer patients were included in the current meta-analysis. The results of our meta-analysis suggested that the frequency of RASSF1A promoter methylation in cancer tissues was higher compared with benign, adjacent, and normal tissues (cancer tissues vs. benign tissues: OR=9.92, 95% CI: 7.67-12.82, p<0.001; cancer tissues vs. adjacent tissues: OR=68.15, 95% CI: 39.30-118.18, p<0.001; cancer tissues vs. normal tissues: OR=30.71, 95% CI: 23.12-40.80, p<0.001; respectively). Subgroup analysis based on ethnicity and sample types revealed that RASSF1A gene methylation was closely associated with the pathogenesis of ovarian cancer in all subgroups (all p<0.05). CONCLUSION: Our findings indicated that abnormal RASSF1A promoter methylation may be strongly correlated with the pathogenesis of ovarian cancer.