Philadelphia-like acute lymphoblastic leukemia is associated with minimal residual disease persistence and poor outcome. First report of the minimal residual disease-oriented GIMEMA LAL1913

Early recognition of Philadelphia-like (Ph-like) acute lymphoblastic leukemia (ALL) cases could impact on the management and outcome of this subset of B-lineage ALL. In order to assess the prognostic value of the Ph-like status in a pediatric-inspired, minimal residual disease (MRD)driven trial, we screened 88 B-lineage ALL cases negative for major fusion genes (BCR-ABL1, ETV6-RUNX1, TCF3-PBX1 and KTM2Ar) enrolled in the GIMEMA LAL1913 front-line protocol for adult BCR/ABL1-negative ALL. The screening - performed using the “BCR/ABL1-like predictor” - identified 28 Ph-like cases (31.8%), characterized by CRLF2 overexpression (35.7%), JAK/STAT pathway mutations (33.3%), IKZF1 (63.6%), BTG1 (50%) and EBF1 (27.3%) deletions, and rearrangements targeting tyrosine kinases or CRLF2 (40%). The correlation with outcome highlighted that: i) the complete remission rate was significantly lower in Ph-like compared to non-Ph-like cases (74.1% vs. 91.5%, P=0.044); ii) at time point 2, decisional for transplant allocation, 52.9% of Ph-like cases versus 20% of non-Ph-like were MRD-positive (P=0.025); iii) the Ph-like profile was the only parameter associated with a higher risk of being MRD-positive at time point 2 (P=0.014); iv) at 24 months, Ph-like patients had a significantly inferior event-free and disease-free survival compared to non-Ph-like patients (33.5% vs. 66.2%, P=0.005 and 45.5% vs. 72.3%, P=0.062, respectively). This study documents that Ph-like patients have a lower complete remission rate, event-free survival and disease-free survival, as well as a greater MRD persistence also in a pediatric-oriented and MRD-driven adult ALL protocol, thus reinforcing that the early recognition of Ph-like ALL patients at diagnosis is crucial to refine risk-stratification and to optimize therapeutic strategies

Philadelphia-like acute lymphoblastic leukemia is associated with minimal residual disease persistence and poor outcome. First report of the minimale residual disease-oriented GIMEMA LAL1913

Early recognition of Ph-like acute lymphoblastic leukemia cases could impact on the management and outcome of this subset of B-lineage ALL. To assess the prognostic value of the Ph-like status in a pediatric-inspired, minimal residual disease (MRD)-driven trial, we screened 88 B-lineage ALL cases negative for the major fusion genes (BCR-ABL1, ETV6-RUNX1, TCF3-PBX1 and KTM2Ar) enrolled in the GIMEMA LAL1913 front-line protocol for adult BCR/ABL1-negative ALL. The screening - performed using the “BCR/ABL1-like predictor” - identified 28 Ph-like cases (31.8%), characterized by CRLF2 overexpression (35.7%), JAK/STAT pathway mutations (33.3%), IKZF1 (63.6%), BTG1 (50%) and EBF1 (27.3%) deletions, and rearrangements targeting tyrosine kinases or CRLF2 (40%). The correlation with outcome highlighted that: i) the complete remission (CR) rate was significantly lower in Ph-like compared to non-Ph-like cases (74.1% vs 91.5%, p=0.044); ii) at time point 2 (TP2), decisional for transplant allocation, 52.9% of Ph-like cases vs 20% of non-Phlike were MRD-positive (p=0.025); iii) the Ph-like profile was the only parameter associated with a higher risk of being MRD-positive at TP2 (p=0.014); iv) at 24 months, Ph-like patients had a significantly inferior event-free and disease-free survival compared to non-Ph-like patients (33.5% vs 66.2%, p=0.005 and 45.5% vs 72.3%, p=0.062, respectively). This study documents that Ph-like patients have a lower CR rate, EFS and DFS, as well as a greater MRD persistence also in a pediatric-oriented and MRD-driven adult ALL protocol, thus reinforcing that the early recognition of Ph-like ALL patients at diagnosis is crucial to refine risk-stratification and to optimize therapeutic strategies

Applicability of droplet digital polymerase chain reaction for minimal residual disease monitoring in Philadelphia-positive acute lymphoblastic leukaemia

In Ph+ acute lymphoblastic leukaemia (Ph+ ALL), minimal residual disease (MRD) is the most relevant prognostic factor. Currently, its evaluation is based on quantitative real-time polymerase chain reaction (Q-RT-PCR). Digital droplet PCR (ddPCR) was successfully applied to several haematological malignancies. We analyzed 98 samples from 40 Ph+ ALL cases, the majority enrolled in the GIMEMA LAL2116 trial: 10 diagnostic samples and 88 follow-up samples, mostly focusing on positive non-quantifiable (PNQ) or negative samples by Q-RT-PCR to investigate the value of ddPCR for MRD monitoring. DdPCR BCR/ABL1 assay showed good sensitivity and accuracy to detect low levels of transcripts, with a high rate of reproducibility. The analysis of PNQ or negative cases by Q-RT-PCR revealed that ddPCR increased the proportion of quantifiable samples (p < 0.0001). Indeed, 29/54 PNQ samples (53.7%) proved positive and quantifiable by ddPCR, whereas 13 (24.1%) were confirmed as PNQ by ddPCR and 12 (22.2%) proved negative. Among 24 Q-RT-PCR-negative samples, 13 (54.1%) were confirmed negative, four (16.7%) resulted PNQ and seven (29.2%) proved positive and quantifiable by ddPCR. Four of 5 patients, evaluated at different time points, who were negative by Q-RT-PCR and positive by ddPCR experienced a relapse. DdPCR appears useful for MRD monitoring in adult Ph+ ALL

Blast morphology in the diagnostic work-up of Ph-like acute lymphoblastic leukemia

Ph-like acute lymphoblastic leukemia (BCR/ABL1-like ALL) is a subset of B-lineage ALL with a gene expression profile (GEP) similar to that of BCR/ABL1-positive (BCR/ABL1þ) ALL, but lacking the BCR-ABL1 fusion protein derived from the t(9;22)(q34;q11) translocation. It is unknown whether BCR/ABL1-like ALL cases are associated with distinctive morphologic features of the leukemic cells

Systematic benchmarking of single-cell ATAC-sequencing protocols

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols

Systematic benchmarking of single-cell ATAC-sequencing protocols.

Acknowledgements: H.H. received support for the project PID2020-115439GB-I00 funded by MCIN/AEI/10.13039/501100011033. This publication is also supported as part of a project (BCLLATLAS and ESPACE) that has received funding from the European Research Council under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement numbers 810287 and 874710). This work was supported by a European Research Council Consolidator grant to S.A. (724226_cis-CONTROL), KU Leuven (C14/22/125 to S.A.), Foundation Against Cancer (F/2020/1396 to S.A.), F.W.O. (grants G0I2722N, G0B5619N and G094121N to S.A. and a PhD fellowship to F.D.) and Aligning Science Across Parkinson’s (grant number ASAP-000430 to S.A.). K.B.M. and S.A.T. are supported by Wellcome (WT211276/Z/18/Z and Sanger core grant WT206194). Computing was performed at the Vlaams Supercomputer Center and high-throughput sequencing at the Genomics Core Leuven. M.R.C. is supported by the National Institutes on Aging K99/R00AG059918. This work was supported by funding from the Rita Allen Foundation (W.J.G.) and the Human Frontiers Science Program (RGY006S; W.J.G.). W.J.G. is a Chan Zuckerberg Biohub investigator and acknowledges grants 2017-174468 and 2018-182817 from the Chan Zuckerberg Initiative and National Institutes of Health grants RM1-HG007735, UM1-HG009442, UM1-HG009436, R01-HG00990901 and U19-AI057266 (to W.J.G.). W.J.G. acknowledges funding from Emerson Collective. B.D. received financial support by Swiss National Science Foundation 310030_197082 and the EPFL. L.S.L. receives support from an Emmy Noether fellowship by the German Research Foundation (LU 2336/2-1), a National Institutes of Health grant UM1HG012076, a Longevity Impetus grant and a Hector Research Career Development Award by the Hector Fellow Academy. A.C.A. is supported by National Institutes of Health grants RF1-MH128842, R35-GM124704 and R01-DA047237 as well as a Silver Family Foundation Innovator Award.Funder: H.H. received support for the project PID2020-115439GB-I00- funded by MCIN/AEI/ 10.13039/501100011033. This publication is also supported as part of a project (BCLLATLAS and ESPACE) that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (grant agreement No 810287 and 874710).Funder: M.R.C. is supported by the National Institutes on Aging K99/R00AG059918.Funder: K.B.M. is supported by Wellcome (WT211276/Z/18/Z and Sanger core grant WT206194).Funder: S.A.T. is supported by Wellcome (WT211276/Z/18/Z and Sanger core grant WT206194).Funder: This work was supported by funding from the Rita Allen Foundation (W.J.G.), the Human Frontiers Science (RGY006S) (W.J.G.). W.J.G. is a Chan Zuckerberg Biohub investigator and acknowledges grants 2017-174468 and 2018-182817 from the Chan Zuckerberg Initiative, and the National Institutes of Health grants RM1-HG007735, UM1-HG009442, UM1-HG009436, R01- HG00990901, and U19- AI057266 (to W.J.G.). W.J.G. acknowledges funding from Emerson Collective.Funder: This work was supported by an ERC Consolidator Grant to S.A. (no. 724226_cis- CONTROL), KU Leuven (grant no. C14/22/125 to S.A.), Foundation Against Cancer (grant no, F/2020/1396 to S.A.), F.W.O. (grants G0I2722N, G0B5619N and G094121N to S.A.), Aligning Science Across Parkinson’s (ASAP, grant no. ASAP-000430 to S.A.)Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols