scholarly journals Discovery of clinically relevant fusions in pediatric cancer

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Stephanie LaHaye ◽  
James R. Fitch ◽  
Kyle J. Voytovich ◽  
Adam C. Herman ◽  
Benjamin J. Kelly ◽  
...  
Keyword(s):  
Pediatric Cancer ◽  
Diagnostic Yield ◽  
Hematologic Malignancies ◽  
Rna Seq ◽  
Blood Disorders ◽  
Knowledge Based ◽  
Genomic Complexity ◽  
Genomic Landscape ◽  
Amazon Web Services ◽  
Superior Approach

Abstract Background Pediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions. Results Our Ensemble Fusion (EnFusion) approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and Amazon Web Services (AWS) serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a “known fusion list” prevents failure to report known pathogenic events. We have employed the EnFusion pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patient’s medical record, both known and novel fusions provided medically meaningful information. Conclusions The EnFusion pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.

scholarly journals Discovery of Clinically Relevant Fusions in Pediatric Cancer

2021 ◽  
Author(s):  
Stephanie LaHaye ◽  
James R. Fitch ◽  
Kyle J. Voytovich ◽  
Adam C. Herman ◽  
Benjamin J. Kelly ◽  
...  
Keyword(s):  
Pediatric Cancer ◽  
Diagnostic Yield ◽  
Hematologic Malignancies ◽  
Rna Seq ◽  
Blood Disorders ◽  
Knowledge Based ◽  
Genomic Complexity ◽  
Detection Approach ◽  
Superior Approach ◽  
Fusion Detection

AbstractBackgroundPediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions.ResultsOur ensemble fusion detection approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and AWS serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a “known fusion list” prevents failure to report known pathogenic events. We have employed the ensemble fusion-calling pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patient’s medical record, both known and novel fusions provided medically meaningful information.ConclusionsOur ensemble fusion detection pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.

scholarly journals Flow Cytometry Immunophenotyping for Diagnostic Orientation and Classification of Pediatric Cancer Based on the EuroFlow Solid Tumor Orientation Tube (STOT)

Cancers ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 4945
Author(s):  
Cristiane de Sá de Sá Ferreira-Facio ◽  
Vitor Botafogo ◽  
Patrícia Mello Ferrão ◽  
Maria Clara Canellas ◽  
Cristiane B. Milito ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Solid Tumors ◽  
Solid Tumor ◽  
Pediatric Cancer ◽  
Diagnostic Procedures ◽  
Hematologic Malignancies ◽  
Multiparameter Flow Cytometry ◽  
Diagnostic Screening ◽  
Pediatric Solid Tumors

Early diagnosis of pediatric cancer is key for adequate patient management and improved outcome. Although multiparameter flow cytometry (MFC) has proven of great utility in the diagnosis and classification of hematologic malignancies, its application to non-hematopoietic pediatric tumors remains limited. Here we designed and prospectively validated a new single eight-color antibody combination—solid tumor orientation tube, STOT—for diagnostic screening of pediatric cancer by MFC. A total of 476 samples (139 tumor mass, 138 bone marrow, 86 lymph node, 58 peripheral blood, and 55 other body fluid samples) from 296 patients with diagnostic suspicion of pediatric cancer were analyzed by MFC vs. conventional diagnostic procedures. STOT was designed after several design–test–evaluate–redesign cycles based on a large panel of monoclonal antibody combinations tested on 301 samples. In its final version, STOT consists of a single 8-color/12-marker antibody combination (CD99-CD8/numyogenin/CD4-EpCAM/CD56/GD2/smCD3-CD19/cyCD3-CD271/CD45). Prospective validation of STOT in 149 samples showed concordant results with the patient WHO/ICCC-3 diagnosis in 138/149 cases (92.6%). These included: 63/63 (100%) reactive/disease-free samples, 43/44 (98%) malignant and 4/4 (100%) benign non-hematopoietic tumors together with 28/38 (74%) leukemia/lymphoma cases; the only exception was Hodgkin lymphoma that required additional markers to be stained. In addition, STOT allowed accurate discrimination among the four most common subtypes of malignant CD45− CD56++ non-hematopoietic solid tumors: 13/13 (GD2++ numyogenin− CD271−/+ nuMyoD1− CD99− EpCAM−) neuroblastoma samples, 5/5 (GD2− numyogenin++ CD271++ nuMyoD1++ CD99−/+ EpCAM−) rhabdomyosarcomas, 2/2 (GD2−/+ numyogenin− CD271+ nuMyoD1− CD99+ EpCAM−) Ewing sarcoma family of tumors, and 7/7 (GD2− numyogenin− CD271+ nuMyoD1− CD99− EpCAM+) Wilms tumors. In summary, here we designed and validated a new standardized antibody combination and MFC assay for diagnostic screening of pediatric solid tumors that might contribute to fast and accurate diagnostic orientation and classification of pediatric cancer in routine clinical practice.

Multicenter Analysis of Genomically Targeted Single Patient Use Requests for Pediatric Neoplasms

2021 ◽  
Author(s):  
Himalee S. Sabnis ◽  
David S. Shulman ◽  
Benjamin Mizukawa ◽  
Nancy Bouvier ◽  
Ahmet Zehir ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Drug Administration ◽  
Pediatric Cancer ◽  
Drug Targets ◽  
De Novo ◽  
Food And Drug Administration ◽  
Hematologic Malignancies ◽  
New Drugs ◽  
Single Patient ◽  
Patient Use

PURPOSE The US Food and Drug Administration–expanded access program (EAP) uses a single patient use (SPU) mechanism to provide patient access to investigational agents in situations where no satisfactory or comparable therapy is available. Genomic profiling of de novo and relapsed or refractory childhood cancer has led to increased identification of new drug targets in the last decade. The aim of this study is to examine the SPU experience for genomically targeted therapies in patients with pediatric cancer. PATIENTS AND METHODS All genomically targeted therapeutic SPUs obtained over a 5-year period were evaluated at four large pediatric cancer programs. Data were collected on the type of neoplasm, agents requested, corresponding molecularly informed targets, and clinical outcomes. RESULTS A total of 45 SPUs in 44 patients were identified. Requests were predominantly made for CNS and solid tumors (84.4%) compared with hematologic malignancies (15.6%). Lack of an available clinical trial was the main reason for SPU initiation (64.4%). The median time from US Food and Drug Administration submission to approval was 3 days (range, 0-12 days) and from Institutional Review Board submission to approval was 5 days (range, 0-50 days). Objective tumor response was seen in 39.5% (15 of 38) of all evaluable SPUs. Disease progression was the primary reason for discontinuation of drug (66.7%) followed by toxicity (13.3%). CONCLUSION SPU requests remain an important mechanism for pediatric access to genomically targeted agents given the limited availability of targeted clinical trials for children with high-risk neoplasms. Furthermore, this subset of SPUs resulted in a substantial number of objective tumor responses. The development of a multi-institutional data registry of SPUs may enable systematic review of toxicity and clinical outcomes and provide evidence-based access to new drugs in rare pediatric cancers.

P2790Novel endomyocardial micro-biopsy device for higher precision and reduced complication risks

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
A Chireh ◽  
R Grankvist ◽  
M Sandell ◽  
A K Mukarram ◽  
N Jaff ◽  
...  
Keyword(s):  
Endomyocardial Biopsy ◽  
Diagnostic Yield ◽  
Molecular Data ◽  
Outer Diameter ◽  
The Novel ◽  
Rna Seq ◽  
Device Design ◽  
Biopsy Device ◽  
Different Parts

Abstract Introduction Endomyocardial biopsy (EMB) is the gold standard for diagnosis of several cardiac diseases, yet its use is limited by low diagnostic yield and significant complication risks. The size of the current devices allows only limited steering to different parts of the ventricle walls. In transplant monitoring, repeated biopsies with the current devices can cause scarring that makes it increasingly difficult to obtain adequate samples. We hypothesised that several of the shortcomings of EMB can be avoided with a smaller and more steerable device. Further, we hypothesised that the novel sampling procedure could be coupled to a low-input molecular analysis method, such as RNA-sequencing (RNA-seq), to provide molecular characterisation of the tissue without the need of large biopsy samples. Purpose To develop an EMB device with significantly smaller dimensions, for future use in diagnostics and research investigations. Specific aims were to test feasibility and safety of the procedure, as well as the quality of the generated molecular data. Methods 65 “micro biopsy” (micro-EMB) device prototypes were designed and evaluated in-house. The prototypes were evaluated either in an ex-vivo simulator or in acute non-survival pig experiments (n=23). Once the final device design was reached, an in vivo trial was set up using six naive Yorkshire farm pigs. Micro-EMB, conventional EMB, skeletal muscle and blood samples were collected for RNA-seq characterisation and comparison. In half of the animals (n=3), micro-EMB was the only intervention in order to prioritise safety evaluations. The animals were monitored for one week. Results The final device design has an outer diameter (OD) of 0.4 mm, compared to a conventional 11 mm device (in the opened position), Fig 1A. The device can be directed to different parts of the myocardium in both ventricles. In the in vivo evaluation in swine, 81% of the biopsy attempts (n=157) were successful. High quality RNA-seq data was generated from 91% of the sequenced heart micro-biopsy samples (n=32). The gene expression signatures of samples taken with the novel device were comparable with samples taken with a conventional device, Fig 1B. No major complications were detected either during periprocedural monitoring or during the follow-up. The tissue mark after micro-biopsy was markedly smaller than after conventional endomyocardial biopsy. A) Bioptome dimensions. B) RNA-seq data. Conclusions Our preliminary data suggest that the novel submillimeter biopsy device, coupled with RNA-seq, provides a feasible method to obtain molecular data from the myocardium. The method is less traumatic and has a higher flexibility compared to conventional methods, enabling safer and more specific sampling from different parts of the myocardium. In the long term, the procedure could open unprecedented diagnostic and research possibilities. Future studies should be directed to establish the capabilities of the novel method in a relevant disease model. Acknowledgement/Funding Family Erling Persson Foundation. The Söderberg foundations. KID (Karolinska Institutet). The 4D project. Stockholm county council. Astra Zeneca.

scholarly journals Whole-genome sequencing of acral melanoma reveals genomic complexity and diversity

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Felicity Newell ◽  
James S. Wilmott ◽  
Peter A. Johansson ◽  
Katia Nones ◽  
Venkateswar Addala ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genome Duplication ◽  
Structural Rearrangement ◽  
Whole Genome ◽  
Rare Form ◽  
Acral Melanoma ◽  
Mutational Signature ◽  
Genomic Complexity ◽  
Genomic Landscape

Abstract To increase understanding of the genomic landscape of acral melanoma, a rare form of melanoma occurring on palms, soles or nail beds, whole genome sequencing of 87 tumors with matching transcriptome sequencing for 63 tumors was performed. Here we report that mutational signature analysis reveals a subset of tumors, mostly subungual, with an ultraviolet radiation signature. Significantly mutated genes are BRAF, NRAS, NF1, NOTCH2, PTEN and TYRP1. Mutations and amplification of KIT are also common. Structural rearrangement and copy number signatures show that whole genome duplication, aneuploidy and complex rearrangements are common. Complex rearrangements occur recurrently and are associated with amplification of TERT, CDK4, MDM2, CCND1, PAK1 and GAB2, indicating potential therapeutic options.

scholarly journals Compendiums of cancer transcriptomes for machine learning applications

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Su Bin Lim ◽  
Swee Jin Tan ◽  
Wan-Teck Lim ◽  
Chwee Teck Lim
Keyword(s):  
Machine Learning ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Data Reuse ◽  
Rna Seq ◽  
Genomic Landscape ◽  
Source Data ◽  
Machine Learning Applications ◽  
Cancer Types ◽  
Data Source

Abstract There are massive transcriptome profiles in the form of microarray. The challenge is that they are processed using diverse platforms and preprocessing tools, requiring considerable time and informatics expertise for cross-dataset analyses. If there exists a single, integrated data source, data-reuse can be facilitated for discovery, analysis, and validation of biomarker-based clinical strategy. Here, we present merged microarray-acquired datasets (MMDs) across 11 major cancer types, curating 8,386 patient-derived tumor and tumor-free samples from 95 GEO datasets. Using machine learning algorithms, we show that diagnostic models trained from MMDs can be directly applied to RNA-seq-acquired TCGA data with high classification accuracy. Machine learning optimized MMD further aids to reveal immune landscape across various carcinomas critically needed in disease management and clinical interventions. This unified data source may serve as an excellent training or test set to apply, develop, and refine machine learning algorithms that can be tapped to better define genomic landscape of human cancers.

Genomic and transcriptomic profiling of localized sarcomatoid carcinoma of the lung to reveal association between immune activation and a lower risk of recurrence.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e20058-e20058
Author(s):  
Sahil Seth ◽  
Won-Chul Lee ◽  
Jianhua Zhang ◽  
Junya Fujimoto ◽  
Carmen Behrens ◽  
...  
Keyword(s):  
Immune Activation ◽  
Lower Risk ◽  
Sarcomatoid Carcinoma ◽  
Normal Lung ◽  
P Value ◽  
Cancer Gene ◽  
Rna Seq ◽  
Synonymous Mutations ◽  
Genomic Landscape ◽  
Cluster 2

e20058 Background: The sarcomatoid carcinoma of the lung (SCL) is a rare subtype of non-small cell lung cancers (NSCLC). The prognosis of SCL is poor with 5-year survival of ~20%. There have been only a few studies on genomic landscape of SCL. Comprehensive genomic and transcriptomic profiles of SCL have not been systematically studied. Methods: In this study, we performed whole-exome sequencing and ultra-deep targeted sequencing of 400 cancer genes on 21 resected localized SCLs and matched normal lung tissues. RNA sequencing (RNA-seq) was also performed to 17 SCLs and matched normal lung tissues for those with materials available. Results: On average, 688 mutations including 503 non-synonymous mutations were identified per tumor. Canonical cancer gene analysis demonstrated that the most frequently mutated gene in this cohort was TP53 (detected in 11 out of the 21 tumors) followed by KRAS (detected in 6 out of the 21 patients). The recently discovered potentially targetable MET exon 14-skipping mutation was also detected in 3 patients in our cohort. For the 17 tumors, for, whom RNA-seq was conducted, unsupervised clustering analysis using non-negative matrix factorization (NMF) led to two stable clusters of patients in our cohort. Of particular interest, all patients (7/7) in Cluster 1 have relapsed, while only 3 of 10 patients in Cluster 2 relapsed (p-value < 0.01). Further pathway analyses demonstrated that immune activation pathways are significantly up regulated in tumors from Cluster 2 compared to Cluster 1. Conclusions: SCLs seem to have similar genomic landscape and canonical cancer gene mutations compared to other types of NSCLCs such as squamous cell carcinoma and adenocarcinomas. Immune pathway activation may be associated with lower risk of postsurgical recurrence in patients with localized SCL.

Diagnostic yield of bronchoscopy with bronchoalveolar lavage in febrile patients with hematologic malignancies and pulmonary infiltrates

2007 ◽  
Vol 87 (4) ◽  
pp. 291-297 ◽  
Author(s):  
Margit Hummel ◽  
Silke Rudert ◽  
Herbert Hof ◽  
Rüdiger Hehlmann ◽  
Dieter Buchheidt
Keyword(s):  
Bronchoalveolar Lavage ◽  
Diagnostic Yield ◽  
Hematologic Malignancies ◽  
Pulmonary Infiltrates

scholarly journals Distinct Genomic Landscape of Chinese Pediatric Acute Myeloid Leukemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 38-38
Author(s):  
Ting Liu ◽  
Jianan Rao ◽  
Wenting Hu ◽  
Yuhan Liu ◽  
Huiying Sun ◽  
...  
Keyword(s):  
Myeloid Leukemia ◽  
Mutation Frequency ◽  
Chinese Patients ◽  
Rna Seq ◽  
Pediatric Acute Myeloid Leukemia ◽  
Genomic Landscape ◽  
Mutation Profile ◽  
Genomic Aberrations ◽  
Pediatric Aml ◽  
Acute Myeloid

Although comprehensive genomic studies have revealed key genomic aberrations in pediatric acute myeloid leukemia (AML), knowledge about Chinese patients remains lacking. Here we report the genomic landscape of Chinese pediatric AML by analyzing the sequence mutations and fusions from transcriptome sequencing (RNA-seq) of 292 cases diagnosed through 2009 to 2018 in Shanghai Children's Medical Center. Informed consents were obtained from parents for all patients. A total of 1831 non-synonymous mutations that were predicted somatic and/or associated to pediatric cancer were identified in 972 genes, including 1597 single nucleotide variants (SNV), 210 insertion/deletion (indels) and 24 internal tandem duplications (ITD), with a median of 6 mutations per case (ranging 0 to 15). Among these abnormalities, 7 aberrations occurred in more than 5% of cases in current cohort, including mutations in KIT (n=54, 18.5%), FLT3 (n=46, 15.8%), NRAS (n=28, 9.6%), CEBPA (n=23, 7.9%), ASXL2 (n=20, 6.8%), KRAS (n=16, 5.5%) and CSF3R (n=15, 5.1%). 444 potential driver variations were identified affecting 66 genes by a combined strategy of mutation pathogenicity and hotspot analysis. Each patient carried a median of one driver mutations per case (ranging 0 to 7). In addition, RNA-seq identified 227 fusions involving 99 genes in 203 out of 292 patients (69.5%), and CBL exon8/9 deletion in 12 patients (4.1%). The most prevalent fusions detected in current cohort included RUNX1-RUNX1T1 (n=82, 28.1%), KMT2A rearrangements (n=45, 15.4%) and NUP98 rearrangements (n=17, 5.8%). Furthermore, novel gene rearrangements were identified in current study, including PTPRA-FUS, ZEB2-ATIC, MSI2-UBE3C (n=1 each). Distinct genomic aberration profile was revealed while comparing our results to the mutation profile characterized in Children's Oncology Group (COG)-National Cancer Institute (NCI) TARGET AML initiative representing the Western pediatric AML cohort. A total of 16 recurrently mutated genes were identified with significantly (two-sided fisher exact test) different mutation frequency. Among these, 7 genes mutated more frequently in Chinese patients, including KIT (18.5% vs 12.8% in Chinese and Western cohort, respectively. p=0.027), ASXL2 (6.8% vs 3.6%, p=0.043), CSF3R (5.1% vs 2.4%, p=0.044), JAK2 (3.4% vs 0.0%, p&lt;0.001), DNM2 (2.7% vs 0.0%, p&lt;0.001), KDM6A (2.1% vs 0.0%, p&lt;0.001) and KMT2C (1.7% vs 0.0%, p=0.003). On the other hand, mutations in FLT3 (15.8% vs 33.0%, p&lt;0.001), NRAS (9.6 vs 30.9%, p&lt;0.001), KRAS (5.5% vs 12.8%, p&lt;0.001), WT1 (2.4% vs 13.6%, p&lt;0.001), NPM1 (2.4% vs 10.3%, p&lt;0.001), PTPN11 (3.8% vs 8.1%, p=0.016), TET2 (1.0% vs 5.2%, p=0.001), CBL sequence mutation (0.0% vs 3.0%, p&lt;0.001) and IKZF1 (0.3% vs 2.7%, p=0.018) were occurred less frequently in Chinese patients. Notably, the RAS signaling pathway as a whole was significantly less frequently mutated in Chinese patients (35.6% vs 71.0%, p&lt;0.001). Furthermore, distinct associations between mutations and FAB subtypes were also observed. For example, NF1 mutations were significantly enriched with subtype M5 in Chinese patients (p=0.003), which was previously reported as co-mutated with CBFB-MYH11 fusion with associated with subtype M4. Survival analysis revealed key genomic aberrations associated with patient prognosis. Variants significantly (log-rank test) associated with better event free survival rate included mutations in CEBPA (p=0.023), NPM1 (p=0.026) and GATA2 (p=0.016). On the other hand, CBFA2T3-GLIS2 (p=0.028), nucleoporin gene family related fusions (including NUP98, NUP214 and NUP153, p&lt;0.001), FUS related fusions (p=0.030), mutations in RUNX1 (p&lt;0.001) and FLT3 (p=0.003) were associated with worse prognosis. A revised risk stratification model was proposed based on these associations observed. Characterized a first comprehensive genomic landscape of Chinese pediatric AML, our results reveal a distinct mutation profile as compared to the Western cohort, in terms of both mutation frequency and patterns of mutation co-occurrence. These findings further reveal the complexity of pediatric AML and highlight the importance of tailored risk stratification for Chinese patients in clinical management. Disclosures No relevant conflicts of interest to declare.

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