Journal of Cancer Clinical Research

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Gene Expression In Cancer

Gene expression profiling has been used widely to characterize cancer, identify novel subtypes, and enhance patient stratification. However, it has largely failed to identify transcriptional programs that differ between cancer and corresponding normal cells and has not been efficient in identifying expression changes fundamental to disease etiology. Here we introduce a method that promotes the comparison of any cancer sample to its closest normal cellular counterpart, through acute myeloid leukemia (AML) as a model. Firstly we generate a gene expression-based landscape of the normal hematopoietic hierarchy, through expression profiles from normal stem or progenitor cells and later mapped the AML patient samples to this landscape. This permitted us to identify the nearest normal counterpart of individual AML samples and establish gene expression changes among cancer and normal.

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