Circular RNA (circRNA) is a large group of RNA family extensively existed in cells and tissues. High-throughput sequencing provides a way to view circRNAs across different samples, especially in various diseases. However, there is still no comprehensive database for exploring the cancer-specific circRNAs. We collected 228 total RNA or polyA(-) RNA-seq samples from both cancer and normal cell lines, and identified 272 152 cancer-specific circRNAs. A total of 950 962 circRNAs were identified in normal samples only, and 170 909 circRNAs were identified in both tumor and normal samples, which could be further used as non-tumor background. We constructed a cancer-specific circRNA database (CSCD, http://gb.whu.edu.cn/CSCD). To understand the functional effects of circRNAs, we predicted the microRNA response element sites and RNA binding protein sites for each circRNA. We further predicted potential open reading frames to highlight translatable circRNAs. To understand the association between the linear splicing and the back-splicing, we also predicted the splicing events in linear transcripts of each circRNA. As the first comprehensive cancer-specific circRNA database, we believe CSCD could significantly contribute to the research for the function and regulation of cancer-associated circRNAs.

The ten-eleven translocation 1 (TET1) gene is the founding member of the TET family of enzymes (TET1/2/3) that convert 5-methylcytosine to 5-hydroxymethylcytosine. Although TET1 was first identified as a fusion partner of the mixed lineage leukemia (MLL) gene in acute myeloid leukemia carrying t(10,11), its definitive role in leukemia is unclear. In contrast to the frequent downregulation (or loss-of-function mutations) and critical tumor-suppressor roles of the three TET genes observed in various types of cancers, here we show that TET1 is a direct target of MLL-fusion proteins and is significantly up-regulated in MLL-rearranged leukemia, leading to a global increase of 5-hydroxymethylcytosine level. Furthermore, our both in vitro and in vivo functional studies demonstrate that Tet1 plays an indispensable oncogenic role in the development of MLL-rearranged leukemia, through coordination with MLL-fusion proteins in regulating their critical cotargets, including homeobox A9 (Hoxa9)/myeloid ecotropic viral integration 1 (Meis1)/pre-B-cell leukemia homeobox 3 (Pbx3) genes. Collectively, our data delineate an MLL-fusion/Tet1/Hoxa9/Meis1/ Pbx3 signaling axis in MLL-rearranged leukemia and highlight TET1 as a potential therapeutic target in treating this presently therapy-resistant disease.

Circular RNA (circRNA) is a group of RNA family generated by RNA circularization, which was discovered ubiquitously across different species and tissues. However, there is no global view of tissue specificity for circRNAs to date. Here we performed the comprehensive analysis to characterize the features of human and mouse tissue-specific (TS) circRNAs. We identified in total 302 853 TS circRNAs in the human and mouse genome, and showed that the brain has the highest abundance of TS circRNAs. We further confirmed the existence of circRNAs by reverse transcription polymerase chain reaction (RT-PCR). We also characterized the genomic location and conservation of these TS circRNAs and showed that the majority of TS circRNAs are generated from exonic regions. To further understand the potential functions of TS circRNAs, we identified microRNAs and RNA binding protein, which might bind to TS circRNAs. This process suggested their involvement in development and organ differentiation. Finally, we constructed an integrated database TSCD (Tissue-Specific CircRNA Database: http://gb.whu.edu.cn/TSCD) to deposit the features of TS circRNAs. This study is the first comprehensive view of TS circRNAs in human and mouse, which shed light on circRNA functions in organ development and disorders.

Summary Expression of microRNAs (miRNAs) is under stringent regulation at both transcriptional and post-transcriptional levels. Disturbance at either level could cause dysregulation of miRNAs. Here we show that MLL fusion proteins negatively regulate production of miR-150, an miRNA widely repressed in acute leukemia, by blocking miR-150 precursors from being processed to mature miRNAs through MYC/LIN28 functional axis. Forced expression of miR-150 dramatically inhibited leukemic cell growth and delayed MLL-fusion-mediated leukemogenesis, likely through targeting FLT3 and MYB and thereby interfering with the HOXA9/MEIS1/FLT3/MYB signaling network, which in turn caused downregulation of MYC/LIN28. Collectively, we revealed a MLL-fusion/MYC/LIN28⊣miR-150⊣FLT3/MYB/HOXA9/MEIS1 signaling circuit underlying the pathogenesis of leukemia, where miR-150 functions as a pivotal gatekeeper and its repression is required for leukemogenesis.

A B S T R A C T PurposeTo identify a robust prognostic gene expression signature as an independent predictor of survival of patients with acute myeloid leukemia (AML) and use it to improve established risk classification. Patients and MethodsFour independent sets totaling 499 patients with AML carrying various cytogenetic and molecular abnormalities were used as training sets. Two independent patient sets composed of 825 patients were used as validation sets. Notably, patients from different sets were treated with different protocols, and their gene expression profiles were derived using different microarray platforms. Cox regression and Kaplan-Meier methods were used for survival analyses. ResultsA prognostic signature composed of 24 genes was derived from a meta-analysis of Cox regression values of each gene across the four training sets. In multivariable models, a higher sum value of the 24-gene signature was an independent predictor of shorter overall (OS) and event-free survival (EFS) in both training and validation sets (P Ͻ .01). Moreover, this signature could substantially improve the European LeukemiaNet (ELN) risk classification of AML, and patients in three new risk groups classified by the integrated risk classification showed significantly (P Ͻ .001) distinct OS and EFS. ConclusionDespite different treatment protocols applied to patients and use of different microarray platforms for expression profiling, a common prognostic gene signature was identified as an independent predictor of survival of patients with AML. The integrated risk classification incorporating this gene signature provides a better framework for risk stratification and outcome prediction than the ELN classification.