Anair Graciela Lema Fernandez

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive tumor mainly affecting children and adolescents. It is driven by multiple genetic mutations that together define the leukemic phenotype. Interestingly, based on genetic alterations and/or deregulated expression, at least six genetic subgroups have been recognized. The TAL/LMO subgroup is one of the most represented genetic subgroups, characterizing 30–45% of pediatric T-ALL cases. The study of lipid and metabolic profiles is increasingly recognized as a valuable tool for comprehending the development and progression of tumors. In this study, metabolic and lipidomic analysis via LC/MS have been carried out on four T-ALL cell lines belonging to the TAL/LMO subgroup (Jurkat, Molt-4, Molt-16, and CCRF-CEM) to identify new potential metabolic biomarkers and to provide a subclassification of T-ALL cell lines belonging to the same subgroup. A total of 343 metabolites were annotated, including 126 polar metabolites and 217 lipid molecules. The statistical analysis, for both metabolic and lipid profiles, shows significant differences and similarities among the four cell lines. The Molt-4 cell line is the most distant cell line and CCRF-CEM shows a high activity in specific pathways when compared to the other cell lines, while Molt-16 and Jurkat show a similar metabolic profile. Additionally, this study highlighted the pathways that differ in each cell line and the possible enzymes involved using bioinformatic tools, capable of predicting the pathways involved by studying the differences in the metabolic profiles. This experiment offers an approach to differentiate T-ALL cell lines and could open the way to verify and confirm the obtained results directly in patients.

In myeloid neoplasms, both fusion genes and gene mutations are well‐established events identifying clinicopathological entities. In this study, we present a thus far undescribed t(X;21)(p11.4;q22.12) in five cases with myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML). The translocation was isolated or accompanied by additional changes. It did not generate any fusion gene or gene deregulation by aberrant juxtaposition with regulatory sequences. Molecular analysis by targeted next‐generation sequencing showed that the translocation was accompanied by at least one somatic mutation in TET2 , EZH2 , RUNX1 , ASXL1 , SRSF2 , ZRSR2 , DNMT3A , and NRAS genes. Co‐occurrence of deletion of RUNX1 in 21q22 and of BCOR in Xp11 was associated with t(X;21). BCOR haploinsufficiency corresponded to a significant hypo‐expression in t(X;21) cases, compared to normal controls and to normal karyotype AML. By contrast, RUNX1 expression was not altered, suggesting a compensatory effect by the remaining allele. Whole transcriptome analysis showed that overexpression of HOXA9 differentiated t(X;21) from both controls and t(8;21)‐positive AML. In conclusion, we characterized a new recurrent reciprocal t(X;21)(p11.4;q22.12) chromosome translocation in MDS and AML, generating simultaneous BCOR and RUNX1 deletions rather than a fusion gene at the genomic level.