Developmental trajectories and cooperating genomic events define molecular subtypes of BCR::ABL1-positive ALL

ABSTRACT

Distinct diagnostic entities within BCR::ABL1-positive acute lymphoblastic leukemia (ALL) are currently defined by the International Consensus Classification of myeloid neoplasms and acute leukemias (ICC): "lymphoid only", with BCR::ABL1 observed exclusively in lymphatic precursors, vs "multilineage", where BCR::ABL1 is also present in other hematopoietic lineages. Here, we analyzed transcriptomes of 327 BCR::ABL1-positive patients with ALL (age, 2-84 years; median, 46 years) and identified 2 main gene expression clusters reproducible across 4 independent patient cohorts. Fluorescence in situ hybridization analysis of fluorescence-activated cell-sorted hematopoietic compartments showed distinct BCR::ABL1 involvement in myeloid cells for these clusters (n = 18/18 vs n = 3/16 patients; P < .001), indicating that a multilineage or lymphoid BCR::ABL1 subtype can be inferred from gene expression. Further subclusters grouped samples according to cooperating genomic events (multilineage: HBS1L deletion or monosomy 7; lymphoid: IKZF1-/- or CDKN2A/PAX5 deletions/hyperdiploidy). A novel HSB1L transcript was highly specific for BCR::ABL1 multilineage cases independent of HBS1L genomic aberrations. Treatment on current German Multicenter Study Group for Adult ALL (GMALL) protocols resulted in comparable disease-free survival (DFS) for multilineage vs lymphoid cluster patients (3-year DFS: 70% vs 61%; P = .530; n = 91). However, the IKZF1-/- enriched lymphoid subcluster was associated with inferior DFS, whereas hyperdiploid cases showed a superior outcome. Thus, gene expression clusters define underlying developmental trajectories and distinct patterns of cooperating events in BCR::ABL1-positive ALL with prognostic relevance.

Classification of Brain Tumors by Nanopore Sequencing of Cell-Free DNA from Cerebrospinal Fluid

BACKGROUND

Molecular brain tumor diagnosis is usually dependent on tissue biopsies or resections. This can pose several risks associated with anesthesia or neurosurgery, especially for lesions in the brain stem or other difficult-to-reach anatomical sites. Apart from initial diagnosis, tumor progression, recurrence, or the acquisition of novel genetic alterations can only be proven by re-biopsies.

METHODS

We employed Nanopore sequencing on cell-free DNA (cfDNA) from cerebrospinal fluid (CSF) and analyzed copy number variations (CNV) and global DNA methylation using a random forest classifier. We sequenced 129 samples with sufficient DNA. These samples came from 99 patients and encompassed 22 entities. Results were compared to clinical diagnosis and molecular analysis of tumor tissue, if available.

RESULTS

110/129 samples were technically successful, and 50 of these contained detectable circulating tumor DNA (ctDNA) by CNV or methylation profiling. ctDNA was detected in samples from patients with progressive disease but also from patients without known residual disease. CNV plots showed diagnostic and prognostic alterations, such as C19MC amplifications in embryonal tumors with multilayered rosettes or Chr.1q gains and Chr.6q losses in posterior fossa group A ependymoma, respectively. Most CNV profiles mirrored the profiles of the respective tumor tissue. DNA methylation allowed exact classification of the tumor in 22/110 cases and led to incorrect classification in 2/110 cases. Only 5/50 samples with detected ctDNA contained tumor cells detectable through microscopy.

CONCLUSIONS

Our results suggest that Nanopore sequencing data of cfDNA from CSF samples may be a promising approach for initial brain tumor diagnostics and an important tool for disease monitoring.

PATH-45. INTRAEPIGLIOM - RAPID SEQUENCING-BASED DIAGNOSIS OF BRAIN TUMORS

The intraoperative diagnosis of brain tumors remains a clinical challenge despite recent technological advances. The current clinical practice differentiates non-surgical brain tumors from those preferably treated with cytoreductive surgery employing intraoperative frozen section diagnostics. A detailed molecular diagnosis required for this classification task within the timeframe of a routine neurosurgical procedure is currently unavailable. We have analyzed a clinical cohort of several brain tumor entities using Nanopore long-read sequencing on two Oxford Nanopore Technologies sequencing platforms (MinION, PromethION). Since currently available molecular cancer classifiers such as the DKFZ methylation profiling classifier cannot be readily adapted to real-time sequencing analysis, we implemented a novel algorithm (MethyLYZR) to predict the underlying cancer type. Publicly available Illumina Infinium array data were used to train the classifier to distinguish 91 brain tumor classes. For validation of classification accuracy, we conducted a comprehensive validation strategy. Both nanopore platforms could sequence more than 5,000 pre-selected CpG within less than 20 minutes for most of our samples. When combining an optimized library preparation protocol with the time used for sequencing the minimal number of CpGs needed for classification, we saw sample-to-answer times of less than 1 hour – in many cases within 45 minutes - from receiving a fresh biopsy to a robust cancer type prediction. Comparing actual and predicted diagnoses resulted in a favorable error rate, indicating potentially highly clinical validity. Our real-time based molecular diagnostic algorithm enables, in most cases, a reliable diagnostic call within the timeframe of a typical neuro-oncological surgery. MethyLYZR as a predictive tool may allow us to adjust the surgical strategy and deliver the prognosis to our patients right after surgery, thus allowing for as-of-yet unexplored opportunities for the intraoperative application of individualized therapeutic modalities.