Carroll William L, Bhojwani Deepa, Min Dong-Joon, Moskowitz Naomi, Raetz Elizabeth A
Division of Pediatric Hematology/Oncology, New York University Cancer Institute, New York University School of Medicine, New York City, New York, USA.
Pediatr Blood Cancer. 2006 May 1;46(5):570-8. doi: 10.1002/pbc.20722.
The recent sequencing of the human genome and technical breakthroughs now make it possible to simultaneously determine mRNA expression levels of almost all of the identified genes in the human genome. DNA "chip" or microarray technology holds great promise for the development of more refined, biologically-based classification systems for childhood ALL, as well as the identification of new targets for novel therapy. To date gene expression profiles have been described that correlate with subtypes of ALL defined by morphology, immunophenotype, cytogenetic alterations, and response to therapy. Mechanistic insights into treatment failure have come from the definition of mRNA signatures that predict in vitro chemoresistance, as well as differences between blasts at relapse and new diagnosis. New bioinformatics tools optimize data mining, but validation of findings is essential since "over-fitting" the data is a common danger. In the future, genomic analysis will be complemented by evaluation of the cancer proteome.
近期人类基因组测序以及技术突破,使得同时测定人类基因组中几乎所有已鉴定基因的mRNA表达水平成为可能。DNA“芯片”或微阵列技术对于开发更精细的、基于生物学的儿童急性淋巴细胞白血病(ALL)分类系统,以及识别新型治疗的新靶点具有巨大潜力。迄今为止,已经描述了与ALL的形态学、免疫表型、细胞遗传学改变以及治疗反应所定义的亚型相关的基因表达谱。对治疗失败的机制性见解来自于预测体外化疗耐药性的mRNA特征的定义,以及复发时与新诊断时原始细胞之间的差异。新的生物信息学工具优化了数据挖掘,但由于“过度拟合”数据是常见风险,因此研究结果的验证至关重要。未来,基因组分析将通过癌症蛋白质组评估得到补充。