RESUMO
Next-generation sequencing has allowed identification of millions of somatic mutations in human cancer cells. A key challenge in interpreting cancer genomes is to distinguish drivers of cancer development among available genetic mutations. To address this issue, we present the first web-based application, consensus cancer driver gene caller (C), to identify the consensus driver genes using six different complementary strategies, i.e., frequency-based, machine learning-based, functional bias-based, clustering-based, statistics model-based, and network-based strategies. This application allows users to specify customized operations when calling driver genes, and provides solid statistical evaluations and interpretable visualizations on the integration results. C is implemented in Python and is freely available for public use at http://drivergene.rwebox.com/c3.
RESUMO
<p><b>OBJECTIVE</b>To explore the expression of CD66c (CEACM6) in adult acute leukemia and its significance.</p><p><b>METHODS</b>Acute leukemia cell lines HL-60, K562, LCL721.221 and Jurkat were cultured in vitro. RT-PCR and multi-parameter flow cytometry were applied to analysis of CD66c mRNA and protein expression respectively in the cell lines and patient' s bone marrow leukemic cells. Cytogenetic analysis for 199 bone marrow samples from leukemia patients and Minimal Residual Disease (MRD) detection for 25 CD66c positive B lineage ALL were performed.</p><p><b>RESULTS</b>(1) CD66c expression both on cell surface and in plasma were negative in all the cell lines. (2) Four of 127 AML (3.15%) (mainly of M2 and M4), and 28 of 79 ALL (35.44%) (all of B linage ALL) were CD66c positive the subtypes of the ALL being common B-ALL (20/54) and pre B-ALL (8/11) including 8 Ph + B-linage ALL. (3) Six-month relapse rate was significantly different between the MRD positive and negative patients. (4) CD66c mRNA was strongly expressed in B-linage ALL. For the cell lines, only the HL60 cells weakly expressed CD66c mRNA.</p><p><b>CONCLUSION</b>CD66c expression could be a useful bio-marker for the MRD analysis in ALL, and is closely associated with its transcription level.</p>