e22637 Background: Most studies of pediatric cancer predisposition syndromes (CPS) are derived from Western populations, resulting in limited understanding of CPS spectra in low- and middle-income countries. We aimed to characterize the genetic landscape of CPS among children of Arab ancestry treated at King Hussein Cancer Center (KHCC), with a particular focus on the impact of consanguinity. Methods: We conducted a retrospective review of children (<18 years) referred to the KHCC Pediatric Cancer Predisposition Clinic between January 2020 and October 2025. Germline testing was performed using targeted next-generation sequencing panels (Invitae) covering cancer predisposition, immunodeficiency, and bone marrow failure syndromes. Patients were stratified based on reported parental consanguinity. Results: A total of 230 pediatric cancer patients underwent germline testing. Median age at cancer diagnosis was 5 years (range, 0.2–18), and 55% were male. The most common indications for CPS evaluation were a family history of cancer (59%), followed by tumor types suggestive of an underlying predisposition syndrome (46%). The overall consanguinity rate was 26%, increasing to 35% among patients with a positive family history. Overall, 76 patients were diagnosed with 24 distinct CPSs. Among children from consanguineous families, 27 of 30 (90%) had autosomal recessive (AR) CPSs, while 3 of 30 (10%) had autosomal dominant (AD) conditions. In the non-consanguineous group, 45 of 46 (98%) had AD CPSs, and one child (2%) had a mitochondrial disorder due to a heteroplasmic variant. The most frequent CPSs were constitutional mismatch repair deficiency (CMMRD, n=11), RB1-related predisposition (n=10), neurofibromatosis (n=8), and Li-Fraumeni syndrome (n=6). Variants of uncertain significance (VUS) considered likely contributory were identified in 17 patients. Genetic testing was negative in 54 of 230 patients (23%). Conclusions: Consanguinity profoundly shapes the spectrum of pediatric CPS in Arab populations, with a marked predominance of autosomal recessive syndromes. These findings underscore the need for population-specific genetic evaluation strategies. Future efforts should prioritize systematic reclassification of VUS through integrated tumor–germline analyses, trio-based testing, and functional studies. Broader implementation of whole-exome and whole-genome sequencing is essential for clinically high-risk patients with negative panel testing, particularly in highly consanguineous populations.

Clinical Characteristics of B-ALL Patient Samples.

B-ALL Xenografts Used in Current Study.

Differentially abundant proteins as quantified by label-free liquid chromatography mass spectrometry in KMT2A-r B-ALL xenografts.

Accurate molecular classification of hematological malignancies is essential for treatment and prognosis. Current diagnostic workflows include a range of tools, including flow-cytometry, karyotyping, NGS, RNA-sequencing and more. These can be time-consuming and expensive, leading to delayed or lacking targeted treatments. DNA-methylation based classification has reshaped molecular diagnosis of central nervous system tumors and sarcomas. Advances in nanopore-based DNA methylation classification have allowed for accurate intra-operative classification of CNS tumors within 90 minutes, assisting decision making during surgery. However, comparably rapid and precise diagnostics for hematologic malignancies have not yet been explored. We therefore set out to develop a clinically deployable framework that couples nanopore sequencing with machine learning to provide high-resolution, real-time classification of hematologic malignancies. To construct a reference atlas, we integrated >5,400 Illumina 450k/EPIC/EPIC-v2 methylation arrays representing 38 molecular subtypes across the spectrum of hematological disease. Specifically, the atlas spans 18 AML subtypes, 10 B-cell precursor ALL subtypes, and one subtype each of T-ALL, low-risk MDS, non-Ph MPN, JMML, CMML, BPDCN, B-PLL, and CLL, plus two non-neoplastic control classes. Nanopore-style sparse-read simulations were generated to reproduce the coverage and error profile of real-time methylation calling. Lamprey, a neural network with calibrated confidence scoring, was trained on these simulated read sets. We validated Lamprey's performance on a hold-out test set, and a validation cohort of 49 retrospective samples sequenced on the nanopore using adaptive sequencing. The model achieved a micro F1 score of 0.96 on the hold-out test set and predicted 47/52 retrospective samples correctly. Of those, 41 correct and 4 incorrect predications reached a confidence score above 0.95. We additionally ran nanopore-based structural variant and chromosome abnormality calling, confirming all the previously defined subtypes. The highly confident incorrect predictions consist of near-haploid/low-hypodiploid ALL, a PAX5 altered ALL with BCR-ABL1 like methylation and transcriptional profile, and a KMT2A-PTD AML. There is little training data available for KMT2A-PTD AML and near-haploid/low-hypodiploid ALL, indicating a need for further training data for rare/newly identified subtypes. Within our training dataset we were able to identify groupings within genomic subtypes that aligned with biological characteristics of the samples. For example, three groups of KMT2A-rearranged AMLs were identified, one of which is enriched in acute megakaryoblastic leukemia, and another that shows overlap with NUP98-rearranged and NPM1 subtypes. Furthermore, we are able to distinguish between closely related molecular subtypes, including DEK-NUP214, NUP98-rearranged, NPM1-mutated and KMT2A-rearranged AMLs. Methylation is also able to identify myeloproliferative neoplasms, including JMML and BCR-ABL1-negative myeloproliferative neoplasms, from control samples. Lamprey is a novel framework for methylation-based rapid molecular diagnosis of hematological disorders. Combining nanopore sequencing with sparse methylation profiling provides the possibility to achieve a fine-grained diagnosis within hours, using a single assay. This could greatly reduce the resources and expertise required for molecular diagnosis and also reduce the need for time-intensive workflows for identifying ‘like’ acute leukemias. Methylation profiling could also lead to the identification of previously undefined subtypes of malignancies, something that has already reshaped CNS-tumor diagnosis.

PURPOSE:Treatment stratification in ALL includes diverse (cyto)genetic aberrations, requiring diverse tests to yield conclusive data. We optimized the diagnostic workflow to detect all relevant aberrations with a limited number of tests in a clinically relevant time frame. METHODS:In 467 consecutive patients with ALL (0-20 years), we compared RNA sequencing (RNAseq), fluorescence in situ hybridization (FISH), reverse transcriptase polymerase chain reaction (RT-PCR), karyotyping, single-nucleotide polymorphism (SNP) array, and multiplex ligation-dependent probe amplification (MLPA) for technical success, concordance of results, and turnaround time. RESULTS:To detect stratifying fusions (ETV6::RUNX1, BCR::ABL1, ABL-class, KMT2Ar, TCF3::HLF, IGH::MYC), RNAseq and FISH were conclusive for 97% and 96% of patients, respectively, with 99% concordance. RNAseq performed well in samples with a low leukemic cell percentage or low RNA quality. RT-PCR for six specific fusions was conclusive for >99% but false-negative for six patients with alternatively fused exons. RNAseq also detected gene fusions not yet used for stratification in 14% of B-cell precursor-ALL and 33% of T-ALL. For aneuploidies and intrachromosomal amplification of chromosome 21, SNP array gave a conclusive result in 99%, thereby outperforming karyotyping, which was conclusive for 64%. To identify deletions in eight stratifying genes/regions, SNP array was conclusive in 99% and MLPA in 95% of patients, with 98% concordance. The median turnaround times were 10 days for RNAseq, 9 days for FISH, 10 days for SNP array, and <7 days for MLPA and RT-PCR in this real-world prospective study. CONCLUSION:Combining RNAseq and SNP array outperformed current diagnostic tools to detect all stratifying genetic aberrations in ALL. The turnaround time is <15 days matching major treatment decision time points. Moreover, combining RNAseq and SNP array has the advantage of detecting new lesions for studies on prognosis and pathobiology.

Background and aims Treatment stratification in pediatric acute lymphoblastic leukemia (ALL) is, besides clinical parameters, guided by (cyto)genetic aberrations. These aberrations include a variety of gene fusions, aneuploidy groups, and copy number alterations (CNA), requiring multiple diagnostic assays to yield conclusive data. Over the past decade, the number and complexity of aberrations to be addressed for stratification increased whereas the turn-around-time decreased. We aimed to optimize the diagnostic workflow with a limited number of assays while allowing detection of all relevant genetic aberrations in a clinically relevant timeframe. Methods In a consecutive cohort of 467 newly diagnosed patients (0 to <19 years) immunophenotyped as ALL, we compared the diagnostic yield of RNA sequencing, 7 fluorescence in situ hybridization (FISH) probes, 7 RT-PCR targets, karyotyping, SNP array (CytoSNP-850K), and multiplex ligation-dependent probe amplification (MLPA; P335-ALL-IKZF1) for conclusiveness, concordance and turn-around-time. Results To detect stratifying fusions (ETV6::RUNX1, BCR::ABL1, ABL-class, KMT2Ar, TCF3::HLF, IGH::MYC), RNA sequencing and FISH were conclusive for 97% and 96% of patients, respectively, with 99% (433/437) concordance of test results. RT-PCR for 6 fusion transcripts was conclusive for >99%, but false-negative for 6 patients who had alternative exons in their fusion genes. RNA sequencing detected fusion genes even in samples with a leukemic cell percentage as low as 10% or RNA integrity score as low as 2. A TCF3::HLF fusion was not detected by RNA sequencing due to the insertion of intronic sequences in the chimeric transcript. A KMT2A::USP2 and a BCR::ABL1 fusion were not detected by FISH because of an inversion and probably insertion, respectively, not causing a break-apart FISH pattern. RNA sequencing detected subtype-defining fusions not (yet) used for stratification in 14% of BCP-ALL and 33% of T-ALL as well as rare fusions in 2% of BCP-ALL and 8% of T-ALL, including a targetable ETV6::NTRK3 fusion which were by definition not detected by targeted FISH or RT-PCR. Moreover, RNA sequencing showed added value for classification based on expression profile and detection of expressed mutations. The turn-around-time for RNA sequencing (7-15 days) and FISH (6-13 days) were both compatible with the demand for diagnostic reporting by day 15 of high-risk genetics and ABL-class fusions for the ALLTogether01 protocol and of BCR::ABL1 positivity for referral to the EsPhALL protocol. Because KMT2A rearrangement should be detected within 7 days to enter the Interfant-21 protocol, the shorter turn-around-time of FISH and RT-PCR were needed in infants (<1 year). For the detection of aneuploidy groups (high hyperdiploidy, low hypodiploidy and near haploidy) and intrachromosomal amplification of chromosome 21 (iAMP21), SNP array gave conclusive results for 99% of the patients, thereby outperforming karyotyping, which was conclusive for 64% and mistook 2 cases of masked hypodiploidy for high hyperdiploidy. Based on the amplification pattern on chromosome 21, 13 iAMP21 cases were identified by SNP array. Using a combination of karyotyping and RUNX1 metaphase FISH, 9/13 iAMP21 cases were identified with the remaining 4 cases lacking informative karyotypes. To identify deletions in eight genes/regions relevant for CNA risk stratification (IKZF1, CDKN2A/B, PAX5, EBF1, ETV6, RB1, BTG1 and PAR1), SNP array was conclusive in 99% and MLPA in 95% of patients with 98% concordant CNA risk calls. SNP array was more sensitive than MLPA in aneuploid samples and samples with low leukemic cell percentage. Beyond the currently required detection of MLPA-based deletions, SNP array detected deletions in (single) exons and genes not covered by the MLPA assay as well as aberrations in low mosaicism. Conclusions Our assay conclusiveness for ≥97% of patients and concordance of results with classic methods of 99% in 467 consecutive patients has resulted in the implementation of RNA sequencing and SNP array as the primary choice in the molecular diagnostics of newly diagnosed ALL in the Netherlands with addition of FISH and RT-PCR to detect KMT2A rearrangement in the infant population only. Performing RNA sequencing and SNP array for all patients has the advantage of detecting new lesions and expressed mutations to retrospectively study their role in prognosis and pathobiology.

Supplementary results, figures, and table notes

Background: Hereditary spherocytosis (HS) is caused by pathogenic variants in genes encoding red blood cell (RBC) cytoskeletal and (trans)membrane proteins. This ultimately leads to instability of the RBC membrane and subsequent membrane loss, resulting in the transformation of the biconcave RBC into a poorly deformable spherocyte, which is susceptible to premature splenic clearance. The diagnosis of HS has substantially improved over the last years and new advanced techniques have been established, including osmotic gradient ektacytometry, eosin-5'-maleimide (EMA) binding test and next-generation sequencing (NGS). However, there is little knowledge on the applicability of these diagnostic outcome parameters as biomarkers for clinical severity in HS. Aim: To explore possible correlations between established and novel diagnostic outcome parameters and clinical severity in a well-defined cohort of HS patients. Methods: This monocenter retrospective cohort study involves patients diagnosed with HS upon referral to our department between 2012 and 2023. Clinical characteristics, routine and advanced diagnostic laboratory parameters, and genotype were evaluated. Clinical severity was classified as previously described, based on parameters such as hemoglobin, reticulocyte percentage and bilirubin 1. The following laboratory tests were included: routine hematological parameters (Cel-Dyn Sapphire or Alinity hq), EMA binding test, osmotic fragility test (OFT) and osmotic gradient ektacytometry (osmoscan, Lorrca MaxSis). The latter technique was also explored for other parameters than the commonly used EI max, O hyper and O min. NGS gene panel analysis was used for molecular diagnosis. Differences between groups were determined using either Chi-squared test, unpaired t-test or Mann-Whitney U test and correlations using point-biserial, Pearson's or Spearman's test via GraphPad Prism. Results: Eighty-two non-splenectomized patients were included. Thirty-five of these (42.7%) were classified as mild, and forty-seven as moderate-severe (57.3%)). Demographic characteristics nor genotype differed significantly, albeit SPTB variants occurred more frequently in the moderate-severe group (15 vs. 4 in the mild group). Expectedly, both reticulocyte count and EI max correlated with clinical severity. RBC distribution width (RDW) correlated moderately, suggesting greater RBC heterogeneity (r=0.606, p<0.0001) is associated with a more severe clinical phenotype. Similarly, EMA binding test results correlated with clinical severity (r=0.390, p<0.001), indicating more pronounced membrane loss in clinically more severe patients. We further evaluated three novel osmoscan parameters ( Figure 1): EI O290, the elongation index (EI) at physiologic isotonicity, which correlated with clinical severity (r=-0.500, p<0.0001), and also with EI max (r=0.856, p<0.0001). The O min-width and O max-width, defined as the difference in osmolality between the intersection points of y=EI min or EI max +/- 0.05 and the osmoscan curve. Thisassesses the effect of changes in osmolality on EI min or EI max, respectively. O min-width correlated with RDW (r-0.439, p<0.0001), OFT results (N=30, r=0.671, p<0.0001) and clinical severity (r=0.390, p<0.001). O max-width correlated with clinical severity (r=-0.375, p<0.001) and strongly with percentage of hyperchromic cells (N=76, r=-0.751, p<0.0001), yet weakly with RDW (-0.273, p<0.05). All significant correlations with clinical severity are displayed in Figure 2. Conclusion: In this study, a number of routine and advanceddiagnostic laboratory parameters were found to correlate with clinical severity in HS. O min-width and O max-width are novel osmoscan-derived biomarkers that correlated with RDW, hyperchromic cells (O max-width), OFT results (O min-width) and clinical severity. EI O290, another novel osmoscan-derived biomarker, also correlated with clinical severity, although not stronger than EI max and AUC. The biomarkers identified in this study, together with patient-reported outcome measures (PROMs), could be used to revise the previously established severity classification system and thereby aid in stratifying clinical severity and subsequent clinical decision-making. References: 1. Eber, S. W., Armbrust, R., & Schröter, W. (1990).

PDX targeted-sequencing tissue concordance

Supplementary Figures S1-S11

dPDX and dRI-PDX leukemia-initiating cell frequencies

Germline investigation in rare families with multiple affected individuals and large cohorts of pediatric patients with acute lymphoblastic leukemia (ALL) has resulted in the discovery of a growing number of leukemia predisposing genes [1, 2].A rare leukemia predisposition syndrome is caused by germline mutations in PAX5.Paired box 5 (PAX5) encodes for a paired box domain transcriptional factor essential for B-cell development [3].Approximately 30% of the pediatric patients with B-cell precursor acute lymphoblastic leukemia (BCP-ALL) harbor a somatic heterozygous loss-of-function alteration in PAX5 [4].Three germline missense variants in PAX5 have been described in seven families with a high incidence of BCP-ALL [5][6][7][8][9].The first germline PAX5 missense variant c.547G>A (p.Gly183Ser) was identified in four unrelated families [5,6,9].Functional testing showed that the PAX5 p.Gly183Ser variant has significantly reduced activity and results in deregulation of target genes, although the effect was milder than non-functional PAX5 mutants [5].A germline PAX5 missense variant affecting the same hotspot, c.547G>C (p.Gly183Arg), has been reported in one family [9].Two unrelated families were found to carry a germline c.113G>A (p.Arg38His) variant [7,8].Functional studies showed that PAX5 p.Arg38His is also a hypomorphic variant resulting in incomplete B-cell differentiation and is sufficient to predispose to leukemia [8].In all families, the susceptibility to BCP-ALL is inherited in an autosomal dominant pattern with incomplete penetrance.In the leukemia of the affected family members a second somatic alteration was detected in PAX5, either by loss of heterozygosity (LOH) or a second somatic mutation.We report a novel germline PAX5 alteration, a deletion including exon 6, in a boy who developed t(1;19)(q23;p13) (TCF3::PBX1) rearrangement-positive BCP-ALL at the age of 5. Somatic PAX5 aberrations are detected in ~20% of the cases with TCF3::PBX1 BCP-ALL [10].The patient was stratified in the standard risk group of the Dutch Childhood Oncology Group (DCOG) ALL11 treatment protocol and completed treatment without severe complications.He has been in follow up for three years.His father was diagnosed with acute undifferentiated leukemia at the age of 9 months.Cytogenetic testing of the leukemia of the father was not performed at time of diagnosis.

Patient characteristics and patient genomic analysis (WES and SNP 6.0)

Although hematologic malignancies (HM) are no longer considered exclusively sporadic, additional awareness of familial cases has yet to be created. Individuals carrying a (likely) pathogenic germline variant (e.g., in ETV6, GATA2, SAMD9, SAMD9L, or RUNX1) are at an increased risk for developing HM. Given the clinical and psychological impact associated with the diagnosis of a genetic predisposition to HM, it is of utmost importance to provide high-quality, standardized patient care. To address these issues and harmonize care across Europe, the Familial Leukemia Subnetwork within the ERN PaedCan has been assigned to draft an European Standard Clinical Practice (ESCP) document reflecting current best practices for pediatric patients and (healthy) relatives with (suspected) familial leukemia. The group was supported by members of the German network for rare diseases MyPred, of the Host Genome Working Group of SIOPE, and of the COST action LEGEND. The ESCP on familial leukemia is proposed by an interdisciplinary team of experts including hematologists, oncologists, and human geneticists. It is intended to provide general recommendations in areas where disease-specific recommendations do not yet exist. Here, we describe key issues for the medical care of familial leukemia that shall pave the way for a future consensus guideline: (i) identification of individuals with or suggestive of familial leukemia, (ii) genetic analysis and variant interpretation, (iii) genetic counseling and patient education, and (iv) surveillance and (psychological) support. To address the question on how to proceed with individuals suggestive of or at risk of familial leukemia, we developed an algorithm covering four different, partially linked clinical scenarios, and additionally a decision tree to guide clinicians in their considerations regarding familial leukemia in minors with HM. Our recommendations cover, not only patients but also relatives that both should have access to adequate medical care. We illustrate the importance of natural history studies and the need for respective registries for future evidence-based recommendations that shall be updated as new evidence-based standards are established.