Molecular subtypes predict therapeutic responses and identifying and validating diagnostic signatures based on machine learning in chronic myeloid leukemia

HIGHLIGHTS

SUMMARY

    With the development of next-generation sequencing (NGS) technologies, studies based on the levels of gene_expression and regulation have shed light on the pathogenesis and malignant phenotypes of many diseases. Novel biomarkers can be identified by systematically analyzing the differences in gene_expression profiles between CML samples and normal samples. Comprehensive analysis of gene_expression characteristics, signaling pathway activities and immune cell infiltration levels in CML samples may contribute to the understanding of CML pathogenesis and tumor microenvironment (TME). Estimation of immune cell infiltration CIBERSORT is a deconvolution algorithm that quantifies the proportion of immune cell . . .

     

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