High Expression of HULC Is Associated with Poor Prognosis in Osteosarcoma Patients.
Vanessa Regina Maciel UzanAndré van Helvoort LengertÉrica BoldriniValter PennaCristovam Scapulatempo-NetoCarlos Alberto ScrideliAlberto Paiva de Moraes FilhoCarlos Eduardo Bezerra CavalcanteCleyton Zanardo de OliveiraLuiz Fernando LopesDaniel Onofre VidalPublished in: PloS one (2016)
Osteosarcoma (OS) is the most common primary bone cancer in childhood. OS is an aggressive disease, and metastatic patients evolve with very poor clinical outcomes. Genetically, OSs are extremely complex tumors, and the related metastatic process is not well understood in terms of the biology of the disease. In this context, long non-coding RNAs (lncRNAs) have emerged as an important class of gene expression regulators that play key roles in the invasion and metastasis of several human tumors. Here, we evaluated the expression of HULC, which is an lncRNA that is associated with the tumor metastatic process, and assessed its potential role as a prognostic marker in OS. HULC expression was evaluated in primary OS samples using real-time RT-PCR. HULC expression status was determined by receiver operating characteristic (ROC) analysis, and its association with survival was assessed using the Kaplan-Meier method. The HULC expression level was not significantly associated with the clinicopathological characteristics of the OS patients. However, our data demonstrated that higher levels of expression of HULC were associated with lower survival rates in OS patients, both in terms of overall and event-free survival. Elevated HULC expression was associated with poor clinical outcomes among the OS patients, which suggests that HULC could be a potential prognostic biomarker in OS.
Keyphrases
- poor prognosis
- long non coding rna
- end stage renal disease
- newly diagnosed
- gene expression
- chronic kidney disease
- small cell lung cancer
- prognostic factors
- squamous cell carcinoma
- endothelial cells
- dna methylation
- peritoneal dialysis
- transcription factor
- electronic health record
- deep learning
- climate change
- machine learning
- young adults
- postmenopausal women
- big data
- bone mineral density
- childhood cancer