The diverse landscape of fusion transcripts in 25 different hematological entities

Genomic alterations are a hallmark of hematological neoplasms and comprise small nucleotide variants, copy number alterations, and structural variants (SV). The latter can arise by events within one chromosome or between different chromosomes, and many SV were described to play crucial roles for risk stratification, MRD monitoring, and targeted therapy of the respective patients [1]. SV leads to the co-localization of remote genomic material resulting in two different scenarios: (1) breakpoints are located within two genes leading to a chimeric fusion gene and a fusion transcript. Well-known examples for this regarding hematological neoplasms comprise, for example, the translocations t(9;22)(q34;q11) or t(15;17)(q22;q12), leading to the formation of the BCRABL1 or PML-RARA gene fusions in chronic myeloid leukemia (CML), acute lymphoblastic leukemia (ALL) or acute promyelocytic leukemia (APL), respectively [1]. (2) Breakpoints are located outside of genes, frequently placing one nearby gene under the influence of the regulatory sequences of the partner, leading to a deregulated – usually increased – transcription, which is observed, for example, for translocations involving the MYC or the MECOM locus [2,3]. In recent years, RNA sequencing (RNAseq) was successfully established for the determination of gene fusion transcripts and was demonstrated capable of replacing classical diagnostic methods for fusion gene detection. In hematological neoplasms, RNAseq was in particular applied for the characterization of patients with ALL, for which it proved to be a powerful tool for genomic classification or for detection of cytogenetically cryptic rearrangements [4,5]. Moreover, larger studies analyzing the fusion gene landscape were also performed for AML [6,7] and multiple myeloma [8], however, studies on other hematological entities are scarce or comprise only a few cases, the same being true for studies focusing on the comparison of the fusion gene landscape between different hematological malignancies. Therefore, we aimed to determine the frequencies of fusion transcripts across 25 hematological entities including 3549 patients for the identification of recurrent partner genes across entities and to evaluate the specificity of fusion transcripts and genes involved in fusions for distinct entities. For this purpose, we focused on fusions arising from translocations with breakpoints located within two genes leading to a fusion transcript detectable on the RNA level. Whole transcriptome sequencing (WTS) was performed in 3549 patients diagnosed with 25 different hematological neoplasms (for details and for abbreviations used in the text, see Table 1). All patients had given written informed consent to the use of genetic and clinical data according to the Declaration of Helsinki. Total RNA and genomic DNA were extracted from lysed cell pellet of diagnostic bone marrow or peripheral blood of patients using the MagNA Pure 96 with DNA and Viral Nucleic Acid Large Volume Kit and Cellular RNA Large Volume Kit (Roche, Basel, Switzerland). Library preparation, WTS, and filtering of results were performed as previously described [6]. In brief, 101 bp paired-end reads were produced on a NovaSeq 6000 system (Illumina, San Diego, CA) with a yield between 35 and 125 million (median 50 million) paired reads per sample. FASTQ generation was performed applying Illumina’s bcl2fastq software (v1.8.4). FASTQ files were preprocessed with the “RNA-Seq Alignment Fast” app from Illumina. Whole-genome sequencing (WGS, data available for all cases) with 90 coverage was applied for fusion validation on the genomic level as described previously [6]. Potential fusions were called using three different callers (Arriba, https:// github.com/suhrig/arriba; STAR-Fusion [9]; Manta [10] with default settings apart from – min_FFPM for STARFusion which was set to 0. Only fusions called by at least two of these callers that were validated by WGS and contained at least one protein-coding partner were kept for further analyses. Reciprocal fusion transcripts were counted as one fusion event. Of note, 170 fusions