DUX Hunting-Clinical Features and Diagnostic Challenges Associated with DUX4-Rearranged Leukaemia

Deciphering IGH rearrangement complexity and detection strategies in acute lymphoblastic leukaemia

Acute lymphoblastic leukaemia is a highly heterogeneous malignancy characterised by various genomic alterations that influence disease progression and therapeutic outcomes. Gene fusions involving the immunoglobulin heavy chain gene represent a complex and diverse category. These fusions often result in enhancer hijacking, upregulation of partner proto-oncogenes and contribute to leukemogenesis. This review highlights the mechanisms underlying IGH gene fusions, the critical role they play in ALL pathogenesis, and current detection technologies.

Real-time genomic characterization of pediatric acute leukemia using adaptive sampling

Effective treatment of pediatric acute leukemia is dependent on accurate genomic classification, typically derived from a combination of multiple time-consuming and costly techniques such as flow cytometry, fluorescence in situ hybridization (FISH), karyotype analysis, targeted PCR, and microarrays [1-3]. We investigated the feasibility of a comprehensive single-assay classification approach using long-read sequencing, with real-time genome target enrichment, to classify chromosomal abnormalities and structural variants characteristic of acute leukemia. We performed whole genome sequencing on DNA from diagnostic peripheral blood or bone marrow for 57 pediatric acute leukemia cases with diverse genomic subtypes. We demonstrated the characterization of known, clinically relevant karyotype abnormalities and structural variants concordant with standard-of-care clinical testing. Subtype-defining genomic alterations were identified in all cases following a maximum of 48 h of sequencing. In 18 cases, we performed real-time analysis- concurrent with sequencing-and identified the driving alteration in as little as 15 min (for karyotype) or up to 6 h (for complex structural variants). Whole genome nanopore sequencing with adaptive sampling has the potential to provide genomic classification of acute leukemia specimens with reduced cost and turnaround time compared to the current standard of care.

Real-time genomic characterization of pediatric acute leukemia using adaptive sampling

Effective treatment of pediatric acute leukemia is dependent on accurate genomic classification, typically derived from a combination of multiple time-consuming and costly techniques such as flow cytometry, fluorescence in situ hybridization (FISH), karyotype analysis, targeted PCR, and microarrays (Arber et al., 2016; Iacobucci & Mullighan, 2017; Narayanan & Weinberg, 2020). We investigated the feasibility of a comprehensive single-assay classification approach using long-read sequencing, with real-time genome target enrichment, to classify chromosomal abnormalities and structural variants characteristic of acute leukemia. We performed whole genome sequencing on DNA from diagnostic peripheral blood or bone marrow for 57 pediatric acute leukemia cases with diverse genomic subtypes. We demonstrated the characterization of known, clinically relevant karyotype abnormalities and structural variants concordant with standard-of-care clinical testing. Subtype-defining genomic alterations were identified in all cases following a maximum of forty-eight hours of sequencing. In 18 cases, we performed real-time analysis - concurrent with sequencing - and identified the driving alteration in as little as fifteen minutes (for karyotype) or up to six hours (for complex structural variants). Whole genome nanopore sequencing with adaptive sampling has the potential to provide genomic classification of acute leukemia specimens with reduced cost and turnaround time compared to the current standard of care.

A dedicated caller for DUX4 rearrangements from whole-genome sequencing data

Rearrangements involving the DUX4 gene (DUX4-r) define a subtype of paediatric and adult acute lymphoblastic leukaemia (ALL) with a favourable outcome. Currently, there is no 'standard of care' diagnostic method for their confident identification. Here, we present an open-source software tool designed to detect DUX4-r from short-read, whole-genome sequencing (WGS) data. Evaluation on a cohort of 210 paediatric ALL cases showed that our method detects all known, as well as previously unidentified, cases of IGH::DUX4 and rearrangements with other partner genes. These findings demonstrate the possibility of robustly detecting DUX4-r using WGS in the routine clinical setting.

How to combine multiple tools for the genetic diagnosis work-up of pediatric B-cell acute lymphoblastic leukemia

This study investigated the importance of comprehensive genetic diagnosis in pediatric B-cell acute lymphoblastic leukemia (B-ALL). We analyzed 175 B-ALL employing karyotyping, FISH, MLPA, targeted next-generation sequencing (t-NGS), and Optical Genome Mapping (OGM). This approach achieved an 83% classification rate, identifying 17 distinct genetic subtypes. Specifically, within B-other subtype, seven different subgroups were identified (ZNF384, IGH, DUX4, NUTM1 rearrangements, PAX5 alterations, PAX5 P80R, and IKZF1 N159Y). Secondary genetic alterations were observed, with copy number alterations (CNA) present in 60% of cases and mutations detected in 70.6%. While these alterations exhibited specific associations with certain genetic subtypes, CNAs did not appear to significantly impact the prognosis within these genetic groups. HeH, ETV6::RUNX1, ZNF384-r, and PAX5 P80R exhibited excellent outcomes, contrasting with the poor prognoses observed in KMT2A-r, hypodiploidy, and CRLF2-r (5-year overall OS were 50%, 50%, and 52%, respectively). These findings underscore the value of integrated genetic diagnostics for accurate subtyping, risk stratification, and guiding personalized treatment in pediatric B-ALL. Therefore, optimizing diagnostic workflows for routine clinical practice is crucial. Our study confirms the utility of conventional techniques (karyotyping and FISH), combined with t-NGS and OGM, for comprehensive genetic diagnosis.

Diagnosis of acute lymphoblastic leukaemia: an overview of the current genomic classification, diagnostic approaches, and future directions

B-acute lymphoblastic leukaemia (B-ALL) is a haematological disease resulting from haematopoietic system dysfunction, leading to the unchecked growth of immature B lymphoblasts. The disease's complexity is underscored by the spectrum of genetic aberrations that underlie B-ALL entities, necessitating advanced genetic analyses for precise classification and risk determination. Prior to the adoption of next-generation sequencing into standard diagnostic practices, up to 30% of B-ALL cases were not assigned to specific entities due to the limitations of traditional diagnostic methods. The advent of comprehensive genomic analysis, especially whole-genome transcriptome sequencing, has significantly enhanced our understanding of B-ALL's molecular heterogeneity, paving the way for the exploration of novel, tailored treatment strategies. Furthermore, recent technological innovations, such as optical genome mapping, methylation profiling, and single-cell sequencing, have propelled forward the fields of cancer research and B-ALL management. These innovations introduce novel diagnostic approaches and prognostic markers, facilitating a deeper, more nuanced understanding of individual patient disease profiles. This review focuses on the latest diagnostic standards and assays for B-ALL, the importance of new technologies and biomarkers in enhancing diagnostic accuracy, and the expected role of innovative advancements in the future diagnosis and treatment of B-ALL.

Transcriptome analysis of primary adult B-cell lineage acute lymphoblastic leukemia identifies pathogenic variants and gene fusions, and predicts subtypes for in depth molecular diagnosis

BACKGROUND

B-cell acute lymphoblastic leukemia (B-ALL) is classified into subgroups based on known driver oncogenes and molecular lesions, including translocations and recurrent mutations. However, the current diagnostic tests do not identify subtypes or oncogenic lesions for all B-ALL samples, creating a heterogeneous B-ALL group of unknown subtypes.

METHODS

We sorted primary adult B-ALL cells and performed transcriptome analysis by bulk RNA sequencing (RNA-seq).

RESULTS

Transcriptomic analysis of an adult B-ALL cohort allowed the classification of four patient samples with subtypes that were not previously revealed by standard gene panels. The leukemia of two patients were of the DUX4 subtype and two were CRLF2+ Ph-like B-ALL. Furthermore, single nucleotide variant analysis detected the oncogenic NRAS-G12D, KRAS-G12D, and KRAS-G13D mutations in three of the patient samples, presenting targetable mutations. Additional oncogenic variants and gene fusions were uncovered, as well as multiple variants in the PDE4DIP gene across five of the patient samples.

CONCLUSION

We demonstrate that RNA-seq is an effective tool for precision medicine in B-ALL by providing comprehensive molecular profiling of leukemia cells, identifying subtype and oncogenic lesions, and stratifying patients for appropriate therapy.

Transcriptome Sequencing Allows Comprehensive Genomic Characterization of Pediatric B-Acute Lymphoblastic Leukemia in an Academic Clinical Laboratory

Studies have shown the power of transcriptome sequencing [RNA sequencing (RNA-Seq)] in identifying known and novel oncogenic drivers and molecular subtypes of B-acute lymphoblastic leukemia (B-ALL). The current study investigated whether the clinically validated RNA-Seq assay, coupled with a custom analysis pipeline, could be used for a comprehensive B-ALL classification. Following comprehensive clinical testing, RNA-Seq was performed on 76 retrospective B-ALL cases, 28 of which had known and 48 had undetermined subtype. Subtypes were accurately identified in all 28 known cases, and in 38 of 48 unknown cases (79%). The subtypes of the unknown cases included the following: PAX5alt (n = 12), DUX4-rearranged (n = 6), Philadelphia chromosome-like (n = 5), low hyperdiploid (n = 4), ETV6::RUNX1-like (n = 3), MEF2D-rearranged (n = 2), PAX5 P80R (n = 2), ZEB2/CEBP (n = 1), NUTM1-rearranged (n = 1), ZNF384-rearranged (n = 1), and TCF3::PBX1 (n = 1). In 15 of 38 cases (39%), classification based on expression profile was corroborated by detection of subtype-defining oncogenic drivers missed by clinical testing. RNA-Seq analysis also detected large copy number abnormalities, oncogenic hot-spot sequence variants, and intragenic IKZF1 deletions. This pilot study confirms the feasibility of implementing an RNA-Seq workflow for clinical diagnosis of molecular subtypes in pediatric B-ALL, reinforcing that RNA-Seq represents a promising global genomic assay for this heterogeneous leukemia.

Extracellular vesicle small RNA cargo discriminates non-cancer donors from pediatric B-lymphoblastic leukemia patients

Pediatric B-acute lymphoblastic leukemia (B-ALL) is a disease of abnormally growing B lymphoblasts. Here we hypothesized that extracellular vesicles (EVs), which are nanosized particles released by all cells (including cancer cells), could be used to monitor B-ALL severity and progression by sampling plasma instead of bone marrow. EVs are especially attractive as they are present throughout the circulation regardless of the location of the originating cell. First, we used nanoparticle tracking analysis to compare EVs between non-cancer donor (NCD) and B-ALL blood plasma; we found that B-ALL plasma contains more EVs than NCD plasma. We then isolated EVs from NCD and pediatric B-ALL peripheral blood plasma using a synthetic peptide-based isolation technique (Vn96), which is clinically amenable and isolates a broad spectrum of EVs. RNA-seq analysis of small RNAs contained within the isolated EVs revealed a signature of differentially packaged and exclusively packaged RNAs that distinguish NCD from B-ALL. The plasma EVs contain a heterogenous mixture of miRNAs and fragments of long non-coding RNA (lncRNA) and messenger RNA (mRNA). Transcripts packaged in B-ALL EVs include those involved in negative cell cycle regulation, potentially suggesting that B-ALL cells may use EVs to discard gene sequences that control growth. In contrast, NCD EVs carry sequences representative of multiple organs, including brain, muscle, and epithelial cells. This signature could potentially be used to monitor B-ALL disease burden in pediatric B-ALL patients via blood draws instead of invasive bone marrow aspirates.

Updates on lymphoblastic leukemia/lymphoma classification and minimal/measurable residual disease analysis

Lymphoblastic leukemia/lymphoma (ALL/LBL), especially certain subtypes, continues to confer morbidity and mortality despite significant therapeutic advances. The pathologic classification of ALL/LBL, especially that of B-ALL, has recently substantially expanded with the identification of several distinct and prognostically important genetic drivers. These discoveries are reflected in both current classification systems, the World Health Organization (WHO) 5th edition and the new International Consensus Classification (ICC). In this article, novel subtypes of B-ALL are reviewed, including DUX4, MEF2D and ZNF384-rearranged B-ALL; the rare pediatric entity B-ALL with TLF3::HLF, now added to the classifications, is discussed; updates to the category of B-ALL with BCR::ABL1-like features (Ph-like B-ALL) are summarized; and emerging genetic subtypes of T-ALL are presented. The second half of the article details current approaches to minimal/measurable residual disease (MRD) detection in B-ALL and T-ALL and presents anticipated challenges to current approaches in the burgeoning era of antigen-directed immunotherapy.

Flow cytometric signature of CD371-positive B-cell acute lymphoblastic leukemia

OBJECTIVES

Multiparametric flow cytometry (MFC) aids in the diagnosis and management of B-cell acute lymphoblastic leukemia (B-ALL) by establishing a baseline immunophenotype for leukemic cells and measuring minimal residual disease (MRD) throughout the course of treatment. Aberrant expression patterns of myeloid markers in B-ALL are also examined during long-term surveillance. Here, we investigated the utility of the newly described myeloid marker cluster of differentiation (CD)371 in MRD surveillance via MFC in patients with CD371-positive B-ALL.

METHODS

Eight-color MFC with standard panels (including CD371) was used to evaluate 238 patients with newly diagnosed B-ALL. Expression levels of key markers were retrospectively assessed at diagnosis, as well as days 15 and 33 of therapy.

RESULTS

CD371 was expressed in 8.4% of patients with B-ALL. CD371 positivity was associated with older age at diagnosis, higher expression levels of CD34 and CD38, and lower expression levels of CD10 and CD20. Residual leukemic cells demonstrated decreased CD10 expression and increased CD45 expression after therapy, whereas CD371 expression remained stable.

CONCLUSIONS

Patients with CD371-positive B-ALL exhibit a specific signature that merits further analysis, particularly because it has been associated with DUX4 rearrangement.

Modern Classification and Management of Pediatric B-cell Leukemia and Lymphoma

Although pediatric hematopathology overlaps with that of adults, certain forms of leukemia and lymphoma, and many types of reactive conditions affecting the bone marrow and lymph nodes, are unique to children. As part of this series focused on lymphomas, this article (1) details the novel subtypes of lymphoblastic leukemia seen primarily in children and described since the 2017 World Health Organization classification and (2) discusses unique concepts in pediatric hematopathology, including nomenclature changes and evaluation of surgical margins in selected lymphomas.

Design and Validation of a Custom Next-Generation Sequencing Panel in Pediatric Acute Lymphoblastic Leukemia

The molecular landscape of acute lymphoblastic leukemia (ALL) is highly heterogeneous, and genetic lesions are clinically relevant for diagnosis, risk stratification, and treatment guidance. Next-generation sequencing (NGS) has become an essential tool for clinical laboratories, where disease-targeted panels are able to capture the most relevant alterations in a cost-effective and fast way. However, comprehensive ALL panels assessing all relevant alterations are scarce. Here, we design and validate an NGS panel including single-nucleotide variants (SNVs), insertion-deletions (indels), copy number variations (CNVs), fusions, and gene expression (ALLseq). ALLseq sequencing metrics were acceptable for clinical use and showed 100% sensitivity and specificity for virtually all types of alterations. The limit of detection was established at a 2% variant allele frequency for SNVs and indels, and at a 0.5 copy number ratio for CNVs. Overall, ALLseq is able to provide clinically relevant information to more than 83% of pediatric patients, making it an attractive tool for the molecular characterization of ALL in clinical settings.

Multi-Cohort Transcriptomic Subtyping of B-Cell Acute Lymphoblastic Leukemia

RNA sequencing provides a snapshot of the functional consequences of genomic lesions that drive acute lymphoblastic leukemia (ALL). The aims of this study were to elucidate diagnostic associations (via machine learning) between mRNA-seq profiles, independently verify ALL lesions and develop easy-to-interpret transcriptome-wide biomarkers for ALL subtyping in the clinical setting. A training dataset of 1279 ALL patients from six North American cohorts was used for developing machine learning models. Results were validated in 767 patients from Australia with a quality control dataset across 31 tissues from 1160 non-ALL donors. A novel batch correction method was introduced and applied to adjust for cohort differences. Out of 18,503 genes with usable expression, 11,830 (64%) were confounded by cohort effects and excluded. Six ALL subtypes (ETV6::RUNX1, KMT2A, DUX4, PAX5 P80R, TCF3::PBX1, ZNF384) that covered 32% of patients were robustly detected by mRNA-seq (positive predictive value ≥ 87%). Five other frequent subtypes (CRLF2, hypodiploid, hyperdiploid, PAX5 alterations and Ph-positive) were distinguishable in 40% of patients at lower accuracy (52% ≤ positive predictive value ≤ 73%). Based on these findings, we introduce the Allspice R package to predict ALL subtypes and driver genes from unadjusted mRNA-seq read counts as encountered in real-world settings. Two examples of Allspice applied to previously unseen ALL patient samples with atypical lesions are included.

Genetic Biomarkers and Their Clinical Implications in B-Cell Acute Lymphoblastic Leukemia in Children

Acute lymphoblastic leukemia (ALL) is a heterogeneous group of hematologic malignancies characterized by abnormal proliferation of immature lymphoid cells. It is the most commonly diagnosed childhood cancer with an almost 80% cure rate. Despite favorable survival rates in the pediatric population, a significant number of patients develop resistance to therapy, resulting in poor prognosis. ALL is a heterogeneous disease at the genetic level, but the intensive development of sequencing in the last decade has made it possible to broaden the study of genomic changes. New technologies allow us to detect molecular changes such as point mutations or to characterize epigenetic or proteomic profiles. This process made it possible to identify new subtypes of this disease characterized by constellations of genetic alterations, including chromosome changes, sequence mutations, and DNA copy number alterations. These genetic abnormalities are used as diagnostic, prognostic and predictive biomarkers that play an important role in earlier disease detection, more accurate risk stratification, and treatment. Identification of new ALL biomarkers, and thus a greater understanding of their molecular basis, will lead to better monitoring of the course of the disease. In this article, we provide an overview of the latest information on genomic alterations found in childhood ALL and discuss their impact on patients' clinical outcomes.

Analysis of DUX4 Expression in Bone Marrow and Re-Discussion of DUX4 Function in the Health and Disease

OBJECTIVE

DUX4 is an embryonic transcription factor (TF) later silenced in somatic tissues, while active in germline testis cells. Re-expression in somatic cells has been revealed to be present in pathologic conditions such as dystrophy, leukemia, and other cancer types. Embryonic cells, cancer cells and testis cells that show DUX4 expression are pluri-multipotent cells. This lead us to question "Could DUX4 be a TF that is active in certain types of potent somatic cells?" As a perfect reflection of the potent cell pool, we aimed to reveal DUX4 expression in the bone marrow.

MATERIAL AND METHOD

Bone marrow aspiration materials of seven healthy donors aged between 3 and 32 (2 males/5 females) were investigated with qPCR analysis after RNA isolation for the presence of DUX4 full length mRNA expression. Samples have been investigated for protein existence of DUX4 via immunohistochemistry in two donors that had sufficient aspiration material.

RESULTS

DUX4 mRNA expression was present in all donors, with higher expression compared to B-actin. DUX4 positive stained cells were also detected by immunohistochemistry.

CONCLUSION

With these results, novel expression for DUX4 in hematopoietic tissue is described. Further studies on the function of DUX4 in hematopoietic cells can shed light on DUX4-related pathways, and contribute to the treatment of DUX4-related diseases such as B-ALL, other cancers, and facioscapulohumeral muscular dystrophy.

In vivo inducible reverse genetics in patients' tumors to identify individual therapeutic targets

High-throughput sequencing describes multiple alterations in individual tumors, but their functional relevance is often unclear. Clinic-close, individualized molecular model systems are required for functional validation and to identify therapeutic targets of high significance for each patient. Here, we establish a Cre-ER^T2-loxP (causes recombination, estrogen receptor mutant T2, locus of X-over P1) based inducible RNAi- (ribonucleic acid interference) mediated gene silencing system in patient-derived xenograft (PDX) models of acute leukemias in vivo. Mimicking anti-cancer therapy in patients, gene inhibition is initiated in mice harboring orthotopic tumors. In fluorochrome guided, competitive in vivo trials, silencing of the apoptosis regulator MCL1 (myeloid cell leukemia sequence 1) correlates to pharmacological MCL1 inhibition in patients´ tumors, demonstrating the ability of the method to detect therapeutic vulnerabilities. The technique identifies a major tumor-maintaining potency of the MLL-AF4 (mixed lineage leukemia, ALL1-fused gene from chromosome 4) fusion, restricted to samples carrying the translocation. DUX4 (double homeobox 4) plays an essential role in patients’ leukemias carrying the recently described DUX4-IGH (immunoglobulin heavy chain) translocation, while the downstream mediator DDIT4L (DNA-damage-inducible transcript 4 like) is identified as therapeutic vulnerability. By individualizing functional genomics in established tumors in vivo, our technique decisively complements the value chain of precision oncology. Being broadly applicable to tumors of all kinds, it will considerably reinforce personalizing anti-cancer treatment in the future.

Preclinical molecular models are useful that mimic a patient´s response to targeted therapy. Here, the authors establish an in vivo inducible RNAi-mediated gene silencing system in patient-derived xenograft models of acute leukemia to identify individual vulnerabilities and therapeutic targets.

Genetic Alterations in Childhood Acute Lymphoblastic Leukemia: Interactions with Clinical Features and Treatment Response

Acute lymphoblastic leukemia (ALL) is the most common cancer among children. This aggressive cancer comprises multiple molecular subtypes, each harboring a distinct constellation of somatic, and to a lesser extent, inherited genetic alterations. With recent advances in genomic analyses such as next-generation sequencing techniques, we can now clearly identify >20 different genetic subtypes in ALL. Clinically, identifying these genetic subtypes will better refine risk stratification and determine the optimal intensity of therapy for each patient. Underpinning each genetic subtype are unique clinical and therapeutic characteristics, such as age and presenting white blood cell (WBC) count. More importantly, within each genetic subtype, there is much less variability in treatment response and survival outcomes compared with current risk factors such as National Cancer Institute (NCI) criteria. We review how this new taxonomy of genetic subtypes in childhood ALL interacts with clinical risk factors used widely, i.e., age, presenting WBC, IKZF1del, treatment response, and outcomes.