NCT02028403.

SUMMARY Long non-coding RNAs (lncRNAs) have been implicated in numerous physiological processes and diseases, most notably cancers. However, little is known about the mechanism of many functional lncRNAs. We identified an abundantly-expressed lncRNA associated with decreased melanoma patient survival. Increased expression of this lncRNA, SLNCR1, mediates melanoma invasion through a highly-conserved sequence similar to the lncRNA SRA1. Using a sensitive technique we term RATA (RNA-associated transcription factor array), we show that the brain-specific homeobox protein 3a (Brn3a) and the androgen receptor (AR) bind within and adjacent to SLNCR1’s conserved region, respectively. SLNCR1, AR, and Brn3a are specifically required for transcriptional activation of matrix metalloproteinase 9 (MMP9) and increased melanoma invasion. Our observations directly link AR to melanoma invasion, possibly explaining why males experience more melanoma metastases and have an overall lower survival as compared to females.

Polymerase chain reaction-based screening of childhood acute lymphoblastic leukemia (ALL) samples showed that a TEL/AML1 fusion transcript was detected in 27% of all cases, representing the most common known gene rearrangement in childhood cancer. The TEL/AML1 fusion results from a t(12;21)(p13;q22) chromosomal translocation, but was undetectable at the routine cytogenetic level. TEL/AML1-positive patients had exclusively B-lineage ALL, and most patients were between the ages of 2 and 9 years at diagnosis. Only 3/89 (3.4%) adult ALL patients were TEL/AML1-positive. Most importantly, TEL/AML1-positive children had a significantly lower rate of relapse compared with TEL/AML1-negative patients (0/22 v 16/54, P = .004). Co- immunoprecipitation experiments demonstrated that TEL/AML-1 formed homodimers in vitro, and heterodimerized with the normal TEL protein when the two proteins were expressed together. The elucidation of the precise mechanism of transformation by TEL/AML1 and the role of TEL/AML1 testing in the treatment of childhood ALL will require additional studies.

The structure of RiboNucleic Acid (RNA) has the potential to be altered by a Single Nucleotide Polymorphism (SNP). Disease-associated SNPs mapping to non-coding regions of the genome that are transcribed into RiboNucleic Acid (RNA) can potentially affect cellular regulation (and cause disease) by altering the structure of the transcript. We performed a large-scale meta-analysis of Selective 2'-Hydroxyl Acylation analyzed by Primer Extension (SHAPE) data, which probes the structure of RNA. We found that several single point mutations exist that significantly disrupt RNA secondary structure in the five transcripts we analyzed. Thus, every RNA that is transcribed has the potential to be a “RiboSNitch;” where a SNP causes a large conformational change that alters regulatory function. Predicting the SNPs that will have the largest effect on RNA structure remains a contemporary computational challenge. We therefore benchmarked the most popular RNA structure prediction algorithms for their ability to identify mutations that maximally affect structure. We also evaluated metrics for rank ordering the extent of the structural change. Although no single algorithm/metric combination dramatically outperformed the others, small differences in AUC (Area Under the Curve) values reveal that certain approaches do provide better agreement with experiment. The experimental data we analyzed nonetheless show that multiple single point mutations exist in all RNA transcripts that significantly disrupt structure in agreement with the predictions.