The long non-coding RNA MALAT-1 plays an important role in cancer prognosis. The present research aimed to elucidate its precise predictive value in various human carcinomas. A quantitative meta-analysis was performed by searching PubMed, Embase, Web of Science, and Cochrane Library (most recently, January 2015) databases, and extracting data from studies that investigated the association between MALAT-1 expression and survival outcomes in patients of various cancers. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated as a measure of generalized effect.
The association between vascular endothelial growth factor (VEGF) gene polymorphisms and risk of cancer has been investigated in several studies published previously; however, the individual results are inconclusive. Therefore, we performed a meta-analysis to establish evidence for an association between the VEGF -634 G/C polymorphism and risk of cancer. We searched PubMed, Medline, and Korean Studies Information Service System databases and identified 29 case-control studies, containing data of 25,324 individuals, for this meta-analysis.
Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) has been identified as a potential cancer biomarker, yet the mechanism by which it influences the development of cancer remains unknown. In this study, we aimed to correlate MALAT1 expression with pathological features and prognosis in cancer patients. Several databases were searched using combinations of keywords relating to MALAT1 and cancer. After selection of relevant cohort studies according to strict criteria, a meta-analysis was conducted.
Epithelioid sarcoma is a rare, aggressive soft tissue tumor of unknown histogenesis showing predominantly epithelioid cytomorphology. We conducted a conventional and molecular cytogenetic study of a 27-year-old male with epithelioid sarcoma with angiomatoid features. Cytogenetic analysis of epithelioid sarcoma metaphase spreads by GTG-banding revealed a diploid chromosome complement with structural and numerical aberrations.