Petri Pölönen, David T Teachey, Charles G Mullighan
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引用次数: 0
Abstract
Relapsed and refractory T-lineage acute lymphoblastic leukemia (T-ALL) has a poor prognosis, emphasizing the need to identify high-risk patients. T-ALL classification has relied on immunophenotype, including identification of early T-cell precursor ALL, but few genetic alterations reproducibly predict outcome in T-ALL independently of measurable residual disease. Here, the biologic and genetic basis of T-ALL is reviewed, with an emphasis on large-scale genomic analyses that have shed light on the spectrum of genetic subtypes, their drivers, mechanisms of oncogene activation, and developmental stage. We describe how genomics-based approaches can improve T-ALL classification and risk stratification.
Significance: Whole-genome and whole-transcriptome sequencing enable biologically and clinically meaningful T-ALL subtype classification with greater precision than immunophenotype-based approaches. The genomic landscape of T-ALL is heavily influenced by noncoding alterations, posing a challenge for clinical applications, as their detection often requires whole-genome sequencing. Studies have identified genomic subtypes and genetic alterations that improve the accuracy of patient outcome prediction.
期刊介绍:
The journal Blood Cancer Discovery publishes high-quality Research Articles and Briefs that focus on major advances in basic, translational, and clinical research of leukemia, lymphoma, myeloma, and associated diseases. The topics covered include molecular and cellular features of pathogenesis, therapy response and relapse, transcriptional circuits, stem cells, differentiation, microenvironment, metabolism, immunity, mutagenesis, and clonal evolution. These subjects are investigated in both animal disease models and high-dimensional clinical data landscapes.
The journal also welcomes submissions on new pharmacological, biological, and living cell therapies, as well as new diagnostic tools. They are interested in prognostic, diagnostic, and pharmacodynamic biomarkers, and computational and machine learning approaches to personalized medicine. The scope of submissions ranges from preclinical proof of concept to clinical trials and real-world evidence.
Blood Cancer Discovery serves as a forum for diverse ideas that shape future research directions in hematooncology. In addition to Research Articles and Briefs, the journal also publishes Reviews, Perspectives, and Commentaries on topics of broad interest in the field.