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Most Variable Genes and Transcription Factors in Acute Lymphoblastic Leukemia Patients.
Interdisciplinary Sciences: Computational Life Sciences ( IF 3.9 ) Pub Date : 2019-04-12 , DOI: 10.1007/s12539-019-00325-y
Anil Kumar Tomar 1 , Rahul Agarwal 2 , Bishwajit Kundu 1
Affiliation  

Acute lymphoblastic leukemia (ALL) is a hematologic tumor caused by cell cycle aberrations due to accumulating genetic disturbances in the expression of transcription factors (TFs), signaling oncogenes and tumor suppressors. Though survival rate in childhood ALL patients is increased up to 80% with recent medical advances, treatment of adults and childhood relapse cases still remains challenging. Here, we have performed bioinformatics analysis of 207 ALL patients' mRNA expression data retrieved from the ICGC data portal with an objective to mark out the decisive genes and pathways responsible for ALL pathogenesis and aggression. For analysis, 3361 most variable genes, including 276 transcription factors (out of 16,807 genes) were sorted based on the coefficient of variance. Silhouette width analysis classified 207 ALL patients into 6 subtypes and heat map analysis suggests a need of large and multicenter dataset for non-overlapping subtype classification. Overall, 265 GO terms and 32 KEGG pathways were enriched. The lists were dominated by cancer-associated entries and highlight crucial genes and pathways that can be targeted for designing more specific ALL therapeutics. Differential gene expression analysis identified upregulation of two important genes, JCHAIN and CRLF2 in dead patients' cohort suggesting their possible involvement in different clinical outcomes in ALL patients undergoing the same treatment.

中文翻译:

急性淋巴细胞白血病患者中大多数可变基因和转录因子。

急性淋巴细胞白血病(ALL)是一种血液肿瘤,由细胞周期异常引起,这是由于转录因子(TFs)的表达中积累了遗传干扰,信号致癌基因和肿瘤抑制因子而引起的。尽管随着最近医学的进步,儿童期ALL患者的存活率提高了80%,但是成人和儿童复发病例的治疗仍然具有挑战性。在这里,我们对从ICGC数据门户网站检索到的207位ALL患者的mRNA表达数据进行了生物信息学分析,目的是找出导致ALL发病机理和侵略性的决定性基因和途径。为了进行分析,根据方差系数对3361个最大可变基因进行了分类,包括276个转录因子(在16807个基因中)。轮廓宽度分析将207例ALL患者分为6个亚型,而热图分析表明需要大型和多中心数据集来进行非重叠的亚型分类。总体而言,丰富了265个GO术语和32个KEGG途径。该列表以与癌症相关的条目为主,并突出了可用于设计更具体的ALL疗法的关键基因和途径。差异基因表达分析确定了死亡患者队列中两个重要基因JCHAIN和CRLF2的上调,表明它们可能在接受相同治疗的所有患者中参与不同的临床结果。该列表以与癌症相关的条目为主,并突出了可用于设计更具体的ALL疗法的关键基因和途径。差异基因表达分析确定了死亡患者队列中两个重要基因JCHAIN和CRLF2的上调,表明它们可能在接受相同治疗的所有患者中参与不同的临床结果。该列表以与癌症相关的条目为主,并突出了可用于设计更具体的ALL疗法的关键基因和途径。差异基因表达分析确定了死亡患者队列中两个重要基因JCHAIN和CRLF2的上调,表明它们可能在接受相同治疗的所有患者中参与不同的临床结果。
更新日期:2019-11-01
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