Table_1_Unraveling trajectories from aplastic anemia to hematologic malignancies: genetic and molecular insights.docx

BackgroundAplastic anemia (AA), characterized by hematopoietic stem cell deficiency, can evolve into different hematologic malignancies. Our understanding of the genetic basis and mechanisms of this progression remains limited.MethodsWe retrospectively studied 9 acquired AA patients who later developed hematologic malignancies. Data encompassed clinical, laboratory, karyotype, and next-generation sequencing (NGS) information. We explored chromosomal alterations and mutation profiles to uncover genetic changes underlying the transition.ResultsNine AA patients developed myelodysplastic syndrome (seven patients), acute myeloid leukemia (one patient), or chronic myelomonocytic leukemia (one patient). Among eight patients with karyotype results at secondary malignancy diagnosis, monosomy 7 was detected in three. Trisomy 1, der(1;7), del(6q), trisomy 8, and del(12p) were detected in one patient each. Among three patients with NGS results at secondary malignancy diagnosis, KMT2C mutation was detected in two patients. Acquisition of a PTPN11 mutation was observed in one patient who underwent follow-up NGS testing during progression from chronic myelomonocytic leukemia to acute myeloid leukemia.ConclusionThis study highlights the genetic dynamics in the progression from AA to hematologic malignancy. Monosomy 7’s prevalence and the occurrence of PTPN11 mutations suggest predictive and prognostic significance. Clonal evolution underscores the complexity of disease progression.</p

Characterization of mutations.

(A) Mutations classified according to the categories of gene functions. (B) Circos diagram showing co-occurrence and mutual exclusivity of mutations.</p

Identification of <i>FLT3</i>- ITD by different NGS algorithms.

Identification of FLT3- ITD by different NGS algorithms.</p

NGS data analysis flow and bioinformatics tools.

NGS data analysis flow and bioinformatics tools.</p

Detection of recurrent translocations in DNA samples by different NGS algorithms.

Detection of recurrent translocations in DNA samples by different NGS algorithms.</p

With capture probes targeting intronic breakpoints, DNA sequencing could detect recurrent translocations.

An example of a case with PML-RARA fusion. The other part (mate) of each paired-end read is located in different genes in different chromosomes.</p

Visualization of copy number analyses.

(A) CNV analysis at the genic or exonic level was performed by comparison of read depths at base level. An example of a KMT2A (MLL)-partial tandem duplication is illustrated. (B) CNV at the whole genome level was estimated by off-target read analysis. Cryptic deletion on 7q was identified, and the case could be reclassified as AML with myelodysplasia-related changes after NGS analysis.</p

WHO classification of cases enrolled in this study.

WHO classification of cases enrolled in this study.</p

Germline mutations identified in patients with AML and MPN.

Germline mutations identified in patients with AML and MPN.</p

Genic and exonic CNVs identified.

Genic and exonic CNVs identified.</p