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Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
TLDR
A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case and suggests a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.
MicroRNA expression profiles classify human cancers
TLDR
A new, bead-based flow cytometric miRNA expression profiling method is used to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers, and finds the miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours.
Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia.
TLDR
It is found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients and the databases from this study are widely available to serve as a foundation for further investigations of AMl pathogenesis, classification, and risk stratification.
Genome-wide analysis of genetic alterations in acute lymphoblastic leukaemia
TLDR
It is suggested that direct disruption of pathways controlling B-cell development and differentiation contributes to B-progenitor ALL pathogenesis and the power of high-resolution, genome-wide approaches to identify new molecular lesions in cancer.
The genetic basis of early T-cell precursor acute lymphoblastic leukaemia
TLDR
The mutational spectrum is similar to myeloid tumours, and moreover, the global transcriptional profile of ETP ALL was similar to that of normal andMyeloid leukaemia haematopoietic stem cells, suggesting that addition of myeloids-directed therapies might improve the poor outcome of E TP ALL.
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