Long noncoding RNAs as novel predictors of survival in human cancer

Expression of various long noncoding RNAs (lncRNAs) may affect cancer prognosis. Researchers from Stanford University examined all evidence on the potential role of lncRNAs as novel predictors of survival in human cancer.

The researchers systematically searched through PubMed, to identify all published studies reporting on the association between any individual lncRNA or group of lncRNAs with prognosis in human cancer (death or other clinical outcomes). Where appropriate, they then performed quantitative synthesis of those results using meta-analytic methods to identify the true effect size of lncRNAs on cancer prognosis. The reliability of those results was then examined using measures of heterogeneity and testing for selective reporting biases.

Three hundred ninety-two studies were screened to eventually identify 111 eligible studies on 127 datasets. In total, these represented 16,754 independent participants pertaining to 53 individual and 6 grouped lncRNAs within a total of 19 cancer sites. Overall, 83 % of the studies we identified addressed overall survival and 32 % of the studies addressed recurrence-free survival. For overall survival, 96 % (88/92) of studies identified a statistically significant association of lncRNA expression to prognosis. Meta-analysis of 6 out of 7 lncRNAs for which three or more studies were available, identified statistically significant associations with overall survival. The lncRNA HOTAIR was by far the most broadly studied lncRNA (n = 29; of 111 studies) and featured a summary hazard ratio (HR) of 2.22 (95 % confidence interval (CI), 1.86-2.65) with modest heterogeneity (I(2) = 49 %; 95 % CI, 14-79 %). Prominent excess significance was demonstrated across all meta-analyses (p-value = 0.0003), raising the possibility of substantial selective reporting biases.

The covariates used within the multivariable models fitted by each paper


This is a data microarray in which the studies run along the Y-axis and the covariates run along the X-axis. Only the factors used three or more times are shown in this figure for convenience. Rows and columns are ordered in descending order, based on how many times each covariate was included in the multivariable models fitted by each study. Where patterns were similar between studies or covariates, those papers or covariates were placed next to each other. It is evident that very few studies included the same covariates within their models and that less than half of the studies included both Stage and Grade within those models.

Green = Included in the multivariable model; Red = Not included in the multivariable model. LNM = Lymph node metastasis; T = Depth of invasion; M = Metastasis; KPS score = Karnofsky Performance Status score (a measure of functional impairment); LVM = Lymphovascular metastasis

Multiple lncRNAs have been shown to be strongly associated with prognosis in diverse cancers, but substantial bias cannot be excluded in this field and larger studies are needed to understand whether these prognostic information may eventually be useful.

Serghiou S, Kyriakopoulou A, Ioannidis JP. (2016) Long noncoding RNAs as novel predictors of survival in human cancer: a systematic review and meta-analysis. Mol Cancer 15(1):50. [article]

Leave a Reply

Your email address will not be published. Required fields are marked *