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Ectopic expression of a combination of 5 genes detects high risk forms of T-cell acute lymphoblastic leukemia.
- Source :
-
BMC genomics [BMC Genomics] 2022 Jun 24; Vol. 23 (1), pp. 467. Date of Electronic Publication: 2022 Jun 24. - Publication Year :
- 2022
-
Abstract
- Background: T cell acute lymphoblastic leukemia (T-ALL) defines a group of hematological malignancies with heterogeneous aggressiveness and highly variable outcome, making therapeutic decisions a challenging task. We tried to discover new predictive model for T-ALL before treatment by using a specific pipeline designed to discover aberrantly active gene.<br />Results: The expression of 18 genes was significantly associated with shorter survival, including ACTRT2, GOT1L1, SPATA45, TOPAZ1 and ZPBP (5-GEC), which were used as a basis to design a prognostic classifier for T-ALL patients. The molecular characterization of the 5-GEC positive T-ALL unveiled specific characteristics inherent to the most aggressive T leukemic cells, including a drastic shut-down of genes located on the mitochondrial genome and an upregulation of histone genes, the latter characterizing high risk forms in adult patients. These cases fail to respond to the induction treatment, since 5-GEC either predicted positive minimal residual disease (MRD) or a short-term relapse in MRD negative patients.<br />Conclusion: Overall, our investigations led to the discovery of a homogenous group of leukemic cells with profound alterations of their biology. It also resulted in an accurate predictive tool that could significantly improve the management of T-ALL patients.<br /> (© 2022. The Author(s).)
- Subjects :
- Adult
Ectopic Gene Expression
Humans
Neoplasm, Residual diagnosis
Neoplasm, Residual genetics
Prognosis
T-Lymphocytes pathology
Treatment Outcome
Precursor Cell Lymphoblastic Leukemia-Lymphoma drug therapy
Precursor Cell Lymphoblastic Leukemia-Lymphoma genetics
Precursor T-Cell Lymphoblastic Leukemia-Lymphoma genetics
Subjects
Details
- Language :
- English
- ISSN :
- 1471-2164
- Volume :
- 23
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- BMC genomics
- Publication Type :
- Academic Journal
- Accession number :
- 35751016
- Full Text :
- https://doi.org/10.1186/s12864-022-08688-1