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SAHMRI Acute Lymphoblastic Leukaemia Data Access Committee

Contact Information

Deborah D White
deborah.white@sahmri.com

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This DAC controls 5 datasets

Dataset ID	Description	Technology	Samples
EGAD00001009087	RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accelerated risk-stratification and therapeutic triage.	NextSeq 500	180
EGAD00001009974	Dataset contains four samples taken from a neonate with congenital KMT2A-rearranged Acute Lymphoblastic Leukemia patient (CHI-0391) with rare IKZF1 gene fusions. Sequencing was carried out using mRNA-seq sequencing on a Illumina NextSeq 500 machine	NextSeq 500	4
EGAD50000001111	Dataset contains RNA-sequencing data (fastq files) from 45 patients treated on the the Australasian Leukaemia and Lymphoma Group (ALLG) ALL06 study, an MRD-stratified Paediatric Protocol. Patient samples (bone marrow or peripheral blood) were taken at diagnosis. mRNA was extracted from blast cells and underwent paired-end sequencing (75bp) using the illumina NextSeq platform. Genomic data was used for identification of genomic drivers of acute lymphoblastic leukaemia (ALL).	unspecified	45
EGAD50000001395	Dataset contains mRNA-sequencing data (fastq files) from 2 patients with NUP214::ABL1 disease (one T-ALL and one B-ALL patient). Patient samples (peripheral blood or bone marrow) were taken at diagnosis (B-ALL) or relapse (T-ALL). mRNA was extracted from lymphoblasts and underwent paired-end sequencing (75bp) using the Illumina NextSeq platform. Transcriptomic data was used for identification of gene fusions, SNVs and InDels. mRNA-seq data for an additional B-ALL patient with NUP214::ABL1 disease utilised in this study has already been published (EGAS00001006460).	NextSeq 500	2
EGAD50000001603	Dataset contains RNA-sequencing data (fastq files) from 46 patients treated on the Australasian Leukaemia and Lymphoma Group (ALLG) ALL09 study (ACTRN12618001734257). All patients were diagnosed with CD19 positive B-cell acute lymphoblastic leukaemia and were negative for Philadelphia chromosome positive disease. Patient samples (bone marrow or peripheral blood) were taken at diagnosis. mRNA was extracted from lymphoblasts and underwent paired-end sequencing using either the illumina NextSeq (75 bp PE) or MGI DNABSEQ-G400 (100bp PE) platforms. Transcriptomic data was used for identification of genomic drivers of acute lymphoblastic leukaemia (ALL).	DNBSEQ-G400 NextSeq 500	46