Clinicopathological and prognostic value of lncRNA PANDAR expression in solid tumors: Evidence from a systematic review and meta-analysis.
Hassan Mehrdad-MajdJavad AkhtariMonir-Sadat HaerianYalda RavanshadPublished in: Journal of cellular physiology (2018)
PANDAR (promoter of CDKN1A antisense DNA damage activated RNA) has been shown to be aberrantly expressed in many types of cancer. Considering conflicting data, the current study was aimed to assess its potential role as a prognostic marker in malignant tumors. A comprehensive literature search of PubMed, Medline, and Web of Science was performed to identify all eligible studies describing the use of PANDAR as a prognostic factor for different types of cancer. Data related to overall survival (OS) and clinicopathologic features were collected and analyzed. The pooled hazard ratio (HR) and odds radio (OR) with a 95% confidence interval (CI) were used to estimate associations. Ten original studies containing 1,231 patients were included. The results showed that in patients with cancer, high PANDAR expression is correlated with lymph node metastasis (LNM; OR = 2.57; 95% CI, 1.76-3.81; p < 0.001), tumor stage (OR = 2.90; 95% CI, 1.25-6.75; p = 0.013), and tumor size (OR = 1.79; 95% CI, 1.11-2.91; p = 0.018). However, sensitivity analysis further demonstrated a significant association between high PANDAR expression and OS, both in multivariate and univariate analysis models (pooled HR 2.01; 95% CI, 1.17-3.44 and pooled HR 2.62; 95% CI, 1.98-3.47, respectively), after omitting one study. These results suggested that PANDAR expression might be indicative of advanced disease and poor prognosis in patients with cancer. Further studies are necessary to determine the value of this risk stratification biomarker in clinical management of patients with cancer.
Keyphrases
- poor prognosis
- long non coding rna
- papillary thyroid
- lymph node metastasis
- prognostic factors
- dna damage
- squamous cell carcinoma
- end stage renal disease
- clinical trial
- systematic review
- ejection fraction
- public health
- electronic health record
- binding protein
- oxidative stress
- randomized controlled trial
- gene expression
- newly diagnosed
- peritoneal dialysis
- big data
- squamous cell
- case control
- phase iii
- deep learning
- young adults
- machine learning
- study protocol