Long non-coding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. In order to delineate genome-wide lncRNA expression, we curated 7,256 RNA-Seq libraries from tumors, normal tissues, and cell lines comprising over 43 terabases of sequence from 25 independent studies. We applied ab initio assembly methodology to this dataset, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% (48,952) were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements and 7% (3,900) overlapped disease-associated single nucleotide polymorphisms (SNPs). To prioritize lineage-specific, disease-associated lncRNA expression we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light into normal biology and cancer pathogenesis, and be valuable for future biomarker development.

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Background Improved clinical predictors for disease progression are needed for localized prostate cancer, where only a minority of patients experience poor outcomes. We undertake an unbiased large-scale analysis of genes associated with aggressive clinical course. Methods Prostate cancer samples, obtained from patients treated with radical prostatectomy at three academic institutions, were analyzed for gene expression using a clinical-grade, high-density Affymetrix GeneChip platform, encompassing >1 million genomic loci. Nomination of prognostic candidate genes was performed on a discovery cohort (n=545) and validated on three independent cohorts (n=463), totaling 1,008 patients. Molecular assays were performed in a CLIA-certified (Clinical Laboratory Improvement Amendments) laboratory facility. Multivariate analyses were performed for the primary endpoint of metastasis. The top prostate-specific gene was evaluated in urine samples from 230 patients using PCR. Findings Among all known genes, the long noncoding RNA SChLAP1 ranked first for elevated expression in patients with metastatic progression by receiver-operator-curve (ROC) area-under-the-curve (AUC) analyses. Of the top five prognostic genes, SChLAP1 was the only prostate-specific gene. Validation in three independent cohorts confirmed the prognostic value of SChLAP1 for metastasis. On multivariate modeling, SChLAP1 expression independently predicted metastasis within ten years (odds ratio (OR) = 2·45, 95% confidence interval (CI) 1·70 – 3·53), death within ten years (OR = 1·93, 95% CI 1·31 – 2·85), and biochemical recurrence within five years (OR = 1·76, 95% CI 1·28 – 2·41) with odds ratios comparable to Gleason score. Evaluation of SChLAP1 expression in 230 urine sediment samples with either biopsy-confirmed cancer or biopsy-negative tissue demonstrated increased incidence and expression of SChLAP1 RNA in patients at a higher risk for disease progression. Interpretation We perform the largest high-throughput, unbiased study of prostate cancer prognostic biomarkers to date and discover SChLAP1 as one of the best genes for the prediction of metastasis. We validate SChLAP1 extensively using a clinical-grade assay in a CLIA-certified laboratory. We show feasibility of a non-invasive urine test for SChLAP1, and suggest that SChLAP1 represents a very promising biomarker for aggressive clinical course. Funding Prostate Cancer Foundation, National Institutes of Health, Department of Defense, Early Detection Research Network, Doris Duke Charitable Foundation, and Howard Hughes Medical Institute.