Identification of Novel Fusion Genes and Differentially Expressed Genes in Acute Leukemia through Transcriptome Analysis

Background

Chromosomal translocations in acute leukemia frequently result in gene fusions that are associated with leukemogenesis. Next-generation sequencing technology has opened up a systematic characterization of transcriptomes including gene expression, novel transcript, and fusion transcripts. We used next-generation RNA sequencing to identify fusion genes responsible for novel chromosomal translocations in acute leukemia and to find their differentially expressed genes.

Methods

We selected 10 acute leukemia (AML, 6; B-ALL, 3; and T-ALL, 1) patients with novel translocations by G-banding. Total RNA was extracted from leukemia cells and cDNA libraries were constructed with TruSeq RNA kit. Paired-end sequencing was performed on HiSeq2500. Reads were aligned with TopHat/BowTie, and deFuse was used to detect fusion transcripts. Transcript assembly and abundance estimation were done using Cufflinks, and expression levels were quantified by fragments per kilobase of transcript per million mapped reads (FPKM). The candidate fusion transcripts were validated with fluorescence in situ hybridization (FISH), and reverse-transcription PCR followed by Sanger-sequencing.

Results

We found 5 in-frame fusion genes exactly matched on translocation breakpoints from 3 AML patients and 1 B-ALL patient: USP34-ASAP3/t(1;2)(p36.1;p11.2), MAZ-MKL1/t(16;22)(p11.2;q13), MLL-SEPT6 and SEPT6-CDCA5/t(X;11)(q24;q13), and RCSD1-ABL1/t(1;9)(q24;q34).

The USP34-ASAP3 fusion produced a novel transcript between USP34 exon 2 and ASAP3 exon 18. The protein encoded by the ASAP3 gene promotes cell differentiation and migration and has been implicated in cancer cell invasion. Comparing gene expression in this sample to nine other samples, we found six overexpressed genes; CLEC3B, SNAR-A14, H19, HOTS, SNORD35A, and S100A1. CLEC3B is associated with human disorders affecting bone and connective tissue. H19 is located in an imprinted region of chromosome 11 and is associated with Wilms tumorigenesis. S100A1 is involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation.

The MAZ-MKL1 fusion transcript was composed of MAZ exon 4 and MKL1 exon 4. MAZ was a novel partner gene of MKL1 which had been reported in acute megakaryoblastic leukemia carrying RBM15-MKL1/t(1;22)(p13;q13). MS4A2, RPLP0, and ARP5J2 genes were overexpressed in this rearrangement. MS4A2 is related PI3K cascade pathway and immune response pathway. RPLP0 is responsible for RNA binding and structural constituent of ribosome.

AML patient with t(X;11)(q24;q13) had two fusion transcripts, MLL-SEPT6 and SEPT6-CDCA5 resulting from complex MLL rearrangement. While the MLL-SEPT6 fusion has been known in AML cases, the SEPT6-CDCA5 was a novel fusion. SNORD88B, MYL6, PTMA, MKX, NDUFAF3, and CNTN1 gene were more highly expressed than other samples. Among them, MKX and CNTN1 genes are related with cell adhesion function.

The RCSD1-ABL1/t(1;9)(q24;q34) in B-ALL was previously reported to encode an aberrant tyrosine kinase. This translocation had also reciprocal ABL1-RCSD1 fusion transcript which could result in an alteration of cellular function. Six genes were specifically overexpressed in this sample RCBTB2, SERHL2, MIR941-2, FAM150B, GPR110, and SNORA27. RCBTB2 encodes a protein that is related to regulator of chromosome condensation.

We also investigated leukemia subtype-specific expression profiles. The five significant genes were higher expressed in AML as compared with ALL (MIR4461, SET, RNU6ATAC, NINJ2, and ATP6V0C). Especially, MIR4461 was over 6000 FPKM in 5 of 6 AML samples, but was never expressed in ALL samples. B-ALL specific overexpressed genes were C17orf62, and MIR941-1, whereas T-ALL specific overexpressed gene was SNORD33.

Conclusions

Using next-generation RNA sequencing, we have discovered 5 candidate fusion genes in 10 acute leukemia patients with novel translocations, and identified 3 novel fusion genes to be predicted as oncogenic potential. Through the comparison of expression profiling, we were able to define differentially expressed genes in acute leukemia with novel fusion genes and leukemia subtype-specific gene expression. RNA-sequencing is a powerful tool for the discovery of leukemia-associated fusion genes and their related genes as well as molecular pathways.