Genomic Alterations of Leukemia
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Molecular Cancer Biology".
Deadline for manuscript submissions: closed (15 May 2022) | Viewed by 20016
Special Issue Editor
Interests: acute myeloid leukemia; acute lymphoblastic leukemia; genomics; functional modeling; targeted therapy; genome editing; single-cell sequencing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
During the past decade, our knowledge of the genomic and epigenomic landscape of acute leukemia, including both acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) has been tremendously improved with the identification of key germline and somatic alterations driving leukemogenesis, refining diagnosis and prognostication and providing novel therapeutic targets. Many of these studies from large cohorts of patients have highlighted the importance of detecting and combining patterns of mutations, complex genomic alterations, and aberrant transcriptional signatures of bulk and single cells to properly diagnose and predict therapeutic response.
The fast progress in genetic discovery has been accompanied by the rapid development of faithful cellular and in vivo models, such as genetically modified mice and xenografts of patient-derived cells in immune deficient mice, that have defined leukemia drivers and importance of cellular origin.
Recent advances in computational modelling techniques and machine learning offer opportunities to advance diagnosis, prediction of prognosis, and selection of therapy.
This Special Issue will highlight the current state-of-the-art in both ALL and AML and future perspectives for improving the functional genomic landscape of leukemia cells, their cell of origin, modeling by faithful in vitro and animal systems, clinical management and therapeutic targeting.
Dr. Ilaria Iacobucci
Guest Editor
Manuscript Submission Information
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Keywords
- Acute leukemia
- Functional genomics
- Classification
- Single cells
- Germline predisposition
- Mouse models
- Genome editing
- Machine learning
- Therapeutic targeting
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