Dataset: COL11A1 promotes tumor progression and predicts poor clinical outcome in ovarian cancer.

Biomarkers that predict disease progression might assist the development of better therapeutic strategies for aggressive cancers, such as ovarian cancer. Here, we investigated the role of collagen type XI alpha 1 (COL11A1) in cell invasiveness and tumor formation and the prognostic impact of COL11A1 expression in ovarian cancer. Microarray analysis suggested that COL11A1 is a disease progression-associated gene that is linked to ovarian cancer recurrence and poor survival. Whole tumor gene expression profiling was conducted on tissue samples from 60 ovarian cancer patients, and characteristics and clinico-pathological features of the patients are provided. We used several steps to analyze the expression profiles of the samples to identify the genes whose expression values correlate with survival, recurrence and advanced disease stage. First, using hazard ratios from univariate Cox regression analysis, the top 200 survival-related genes were evaluated for intersection with the top 200 recurrence-related genes, and 44 genes were obtained. Second, we examined the 44 genes that met the criteria of fold-change values between advanced stage and early stage samples of greater than 2 or less than 0.5. Ultimately, 17 genes were identified. A heat map of the 17 genes is depicted in the associated publication. Gene ontology and pathway enrichment analyses of the 17 genes were performed using Database for Annotation, Visualization and Integrated Discovery (DAVID). The major cellular component, biological process and molecular function of the 17 genes are associated with the extracellular region, intracellular signaling cascade, and protein binding and bridging, respectively. Two genes, COL11A1 and COL4A6, are involved in ECM-receptor interaction pathways. Notably, COL11A1 displayed the highest fold-change value in ovarian cancer disease progression; therefore, we selected COL11A1 for further experimental analysis.

Species:

human

Samples:

60

Source:

E-GEOD-44104

Updated:

Dec.12, 2014

Registered:

Jul.11, 2014