Duncavage, Eric J.

Abstract Introduction Ph-like B-ALL is a poor-risk B-ALL subtype defined by gene expression signatures that resemble the BCR::ABL1-associated transcriptional program in the absence of the BCR-ABL1 oncoprotein. Recent studies have demonstrated that up to 80% of Ph-like B-ALLs have recurrent gene fusions involving cytokine receptors or tyrosine kinases that can be identified via cytogenetics, fluorescence in situ hybridization (FISH) or RNA sequencing. However, the inability to rapidly and accurately identify these alterations in the clinical setting is a major impediment to developing therapeutic strategies that may have efficacy in this B-ALL subtype. Here we used 88 patient (pt) samples to validate a rapid, streamlined clinical WGS assay (ChromoSeq) for B-ALL and assessed the diagnostic yield for Ph-like-associated SVs in 136 pts enrolled in the Alliance A041501 clinical trial. Methods ChromoSeq is a clinical WGS assay for hematologic malignancies that uses rapid laboratory workflows and focused analysis methods to identify clinically relevant SVs, copy number alterations and gene-level mutations. We updated the ChromoSeq pipeline for use in B-ALL pts and validated it using 88 retrospective B-ALL samples (80 adult/young adult and 8 pediatric from Washington University School of Medicine and St. Louis Children's Hospital), 54 of which were analyzed via RNAseq for gene fusions and a 6-gene Ph-like B-ALL signature (CA6, SPATS2L, MUC4, JCHAIN, BMPR1B, ADGRF1, NRXN3 and CRLF2). The “ChromoSeqV2” assay was then used to analyze 136 pretreatment blood or bone marrow samples from the Alliance A041501 (trial NCT03150693). These results were compared to data from RNAseq obtained for research purposes (N=35), clinical cytogenetics (N=69) and Ph-like classification via low-density microarray (LDA) card analysis (all pts). Results ChromoSeqV2 was validated in a CLIA-licensed setting using cohort of 88 retrospective B-ALL samples, 45 of which had ICC and WHO class-defining SVs based on G-banded karyotyping, FISH or RNAseq. ChromoSeqV2 detected 100% of the non-Ph-like SVs (37/37), including BCR::ABL1 (N=20), KMT2Ar (N=9), ETV6::RUNX1 (N=3), TCF3::PBX1 (N=1), and rearrangements involving MYC (N=2) or MEF2D (N=2). Fifteen patients met criteria for Ph-like B-ALL via cytogenetics or RNAseq either due to rearrangements of CRLF2 (N=5), JAK2 (N=2) or ABL2 (N=1) or high expression of a 6-gene Ph-like signature (N=7). ChromoSeqV2 detected a Ph-like SV in 93% of these cases (14/15) with 100% specificity in samples negative by RNAseq (N=23). ChromoSeqV2 was then used to profile 136 samples from the Alliance A041501 trial, where it identified ICC and WHO class-defining SVs in 87 pts (64%; 95% CI: 55-72%), including Ph-like SVs (56/136, 41%), KMT2A rearrangements (N=5), TCF3::PBX1 (N=3) and SVs involving MYC (N=3), MEF2D (N=2), DUX4 (N=2), and ZNF384 (N=1). Ph-like SVs were dominated by CRLF2 rearrangements (N=45) and included SVs involving EPOR (N=4), JAK2 (N=3), ABL1/ABL2 (N=2) and PDGFRB (N=1). IGH was the most common CRLF2 partner (N=32), followed by P2RY8::CRLF2 (N=7) and other genes (N=5). Multiple CRLF2 SVs were detected in 4 pts, and 33% (15/45) of pts with a CRLF2 rearrangement had a co-occurring CRLF2 gene mutation. The yield of ChromoSeqV2 for SVs in pts with the Ph-like expression signature via LDA card analysis was 66% (54/82; 95% CI 55%-76%) compared to 24% (11/45; 95% CI 13%-40%) by cytogenetics when these studies were successful and 70% (12/17; 95% CI 44%-90%) vs RNAseq in pts with available data. The sensitivity of ChromoSeqV2 for Ph-like SVs identified by either cytogenetics, FISH or RNAseq was 100% (21/21; 95% CI 84%-100%) and the positive predictive value of Ph-like SVs for the Ph-like expression signature by the LDA card assay was 96% (54/56; 95% CI 88%-99%). Conclusions Genomic assessment of 136 B-ALL pts from the Alliance A041501 trial using the ChromoSeqV2 rapid clinical WGS assay was 100% sensitive for Ph-like SVs identified by other molecular methods and had a 96% PPV for the Ph-like expression signature via LDA card analysis. The diagnostic yield of SV pts with the Ph-like signature was 66% using ChromoSeqV2, which was similar to RNAseq and superior to cytogenetics. These results demonstrate that ChromoSeqV2 is an effective approach for identifying potentially targetable rearrangements in B-ALL pts suspected of having the Ph-like phenotype. Support: U10CA180821, U10CA180882; . Servier; Pfizer.

Abstract Myeloid neoplasms and acute leukemias derive from the clonal expansion of hematopoietic cells driven by somatic gene mutations. Although assessment of morphology plays a crucial role in the diagnostic evaluation of patients with these malignancies, genomic characterization has become increasingly important for accurate diagnosis, risk assessment, and therapeutic decision making. Conventional cytogenetics, a comprehensive and unbiased method for assessing chromosomal abnormalities, has been the mainstay of genomic testing over the past several decades and remains relevant today. However, more recent advances in sequencing technology have increased our ability to detect somatic mutations through the use of targeted gene panels, whole-exome sequencing, whole-genome sequencing, and whole-transcriptome sequencing or RNA sequencing. In patients with myeloid neoplasms, whole-genome sequencing represents a potential replacement for both conventional cytogenetic and sequencing approaches, providing rapid and accurate comprehensive genomic profiling. DNA sequencing methods are used not only for detecting somatically acquired gene mutations but also for identifying germline gene mutations associated with inherited predisposition to hematologic neoplasms. The 2022 International Consensus Classification of myeloid neoplasms and acute leukemias makes extensive use of genomic data. The aim of this report is to help physicians and laboratorians implement genomic testing for diagnosis, risk stratification, and clinical decision making and illustrates the potential of genomic profiling for enabling personalized medicine in patients with hematologic neoplasms.

Abstract The classification of myeloid neoplasms and acute leukemias was last updated in 2016 within a collaboration between the World Health Organization (WHO), the Society for Hematopathology, and the European Association for Haematopathology. This collaboration was primarily based on input from a clinical advisory committees (CACs) composed of pathologists, hematologists, oncologists, geneticists, and bioinformaticians from around the world. The recent advances in our understanding of the biology of hematologic malignancies, the experience with the use of the 2016 WHO classification in clinical practice, and the results of clinical trials have indicated the need for further revising and updating the classification. As a continuation of this CAC-based process, the authors, a group with expertise in the clinical, pathologic, and genetic aspects of these disorders, developed the International Consensus Classification (ICC) of myeloid neoplasms and acute leukemias. Using a multiparameter approach, the main objective of the consensus process was the definition of real disease entities, including the introduction of new entities and refined criteria for existing diagnostic categories, based on accumulated data. The ICC is aimed at facilitating diagnosis and prognostication of these neoplasms, improving treatment of affected patients, and allowing the design of innovative clinical trials.