Abstract
Abstract 3074
Poster Board III-11
Background
BCR-ABL1-positve Acute Lymphoblastic Leukemia (ALL) is the most common ALL subtype in adults and is associated with poor prognosis. The pathogenesis of this leukemia is related to the expression of the BCR-ABL1 fusion transcript, but additional recurrent genetic lesions are suspected to be involved in its development and progression.
Aim
A Next-Generation Sequencing Technology was used to sequence the whole transcriptome of leukemia cells from a BCR-ABL1-positive ALL patient at diagnosis and at relapse following tyrosine kinase inhibitor (TKI) therapy with the aim to detect acquired mutations cooperating with BCR-ABL1 in leukemia manifestation and drug-resistance.
Methods
Poly(A) RNA was extracted from leukemia cells and used to prepare double-stranded cDNA libraries for Illumina/Solexa Genome Analyzer. Obtained 36 base-pair (bp) sequence reads were mapped to the reference sequence of the human genome (UCSC hg18, NCBI build 36.1) to identify single nucleotide variants (SNVs) and to estimate reads density corresponding to RNA from each known exon, canonical splice event or new candidate gene. This approach allowed us to define a detailed Digital Gene Expression (DGE) profile. Reads that showed no match to the reference genome were subsequently mapped to a dataset of all possible splice junctions created by in silico pairwise combination of the exons of all annotated genes (UCSC knownGene file) to identify alternative splicing (AS) events.
Results
Whole Transcriptome Shotgun Sequencing (RNA-seq) analysis generated 13.9 and 15.8 million reads from de novo and relapsed ALL samples respectively, achieving approximately 90% diploid coverage and detecting transcripts from 62% and 64% of human annotated genes. The great majority of these active genes (78% at diagnosis and 73% at relapse) showed very low expression levels, with a number of reads per kilobase of exon model per million mapped reads (RPKM value) from 0.01 to 10, whereas 20% and 24% showed moderate expression levels (RPKM 10-100), as well as only 2% and 3% resulted highly expressed (RPKM 100-8000). Moreover, 6,390 and 4,671 AS events were also identified within 4,334 diagnosis and 3,651 relapse annotated transcripts, with the already described ALL-related Ik6 Ikaros isoform observed in both samples. Finally, 2,011 and 2,103 single nucleotide variants (SNVs) were found at diagnosis and relapse respectively, about 94% of which have been already reported in the dbSNP. Of greater interest as potential ALL-related mutations, 124 and 115 non annotated SNVs were also found at diagnosis and relapse, respectively. Of these, 43 affected both samples, while 81 and 72 resulted diagnosis and relapse private variants. In particular, the analysis was focused to the coding sequences of annotated genes, finding that non-synonymous changes were one out of the 19 shared between the two samples and affected a transmembrane receptor gene (PLXNB2). Six out of the 12 diagnosis private variants, affecting genes involved in metabolic process (PDE4DIP, EIF2S3, DPEP1, ZC3H12D, TMEM46) or transport (MVP) and 5 out of the 30 relapse private variants, affecting genes involved in cell cycle regulation (ABL1, CDC2L1), catalytic activity (CTSZ, CXorf21) or with unknown function (FAM116B). Most of these diagnosis and relapse non-synonymous private mutations resulted highly expressed, showing frequencies of mutated unique reads higher than 50%. According to this pattern, diagnosis private mutations may be carried by primary leukemic clones that did not develop again at relapse, whereas relapse private mutations have greater probability to be variants acquired during the disease progression. Interestingly, the T315I point mutation in the Abl kinase domain, that confers resistance to many TKIs, was found at relapse but not at diagnosis.
Conclusions
An accurate expression profile was obtained for the leukemia cells of the examined ALL patient, as well as the discovery of several new non-synonymous mutations affecting genes from different pathways and for which no correlation was previously found with ALL pathogenesis. These findings demonstrate that RNA-Seq represents a suitable and cost-efficient approach for identifying new genes potentially involved in ALL development and progression.
Acknowledgments
AIL, AIRC, Fondazione Del Monte di Bologna e Ravenna, FIRB 2006, Ateneo 60% grants, European LeukemiaNet.
Disclosures
No relevant conflicts of interest to declare.
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