【作者】 涂智杰；

【导师】 陈亮； 周建光；

【作者基本信息】 厦门大学 ， 细胞生物学， 2006， 硕士

【摘要】 人类基因组测序工作的完成使人们可以方便调用任何基因序列,但仅有基因序列并不能解释众多的生物学问题,这要求人们发展一种高通量的技术用于研究基因的生物学功能以及与其他基因相互作用的关系。DNA微阵列技术以其高通量的特点已经在肿瘤生物学的研究中逐渐被采用。由于癌症是源于基因表达谱改变的一种基因疾病,通过DNA微阵列技术研究代表肿瘤发展各阶段细胞之间的基因表达差异将会使人们更好的了解肿瘤的形成和发展过程。前列腺癌是引起西方男性死亡的主要癌症,而且也是最常见的诊断性癌症。通常,前列腺癌变的速度很慢。如果早期发现并治疗可以得到很好的疗效,然而一旦前列腺癌出现转移就很难进行有效治疗和提高病人的生存率。为了解决上述问题,关键是使用预测性标记物找出哪些前列腺癌病人在其有生之年会进一步发展为转移型前列腺癌。转移型前列腺癌经过了一系列的发展过程其中包括正常前列腺上皮细胞内瘤、局部前列腺癌、侵袭性前列腺癌和转移性前列腺癌。前列腺癌的这些发展阶段包括多个分子的改变,暗示这些发展是通过基因表达差异的改变进行的。一旦前列腺癌发展为雄激素非依赖性就意味着这些肿瘤细胞的生长不受控制,这个阶段是前列腺癌病人死亡的主要原因。然而几乎所有的转移型前列腺癌病人起初对抗雄激素治疗都有效果,但是在2年内大部分的病人就对抗雄激素治疗失去应答。基因表达的改变和表观遗传的改变被认为是前列腺癌发展为雄激素非依赖性的主要原因[1-4]。为了研究这种发展过程,我们选择使用微阵列技术来研究高恶性、晚期、雄激素非依赖性的前列腺癌细胞系C4-2和低恶性、初期、雄激素依赖性前列腺癌细胞系LNCaP基因表达图谱差异。获得了以下研究结果:1.选用涵盖18,000多个转录本,代表18,000多个明晰的基因,其中13,000多个为全长基因的美国Affymetrix公司的人类全基因组U133系列芯片,高通量分析了LNCaP/C4-2细胞中基因表达图谱的变化。2.通过Affymetrix、GenBank,dbEST,and RefSeq等网站对Affymetrix芯片数据进行大量的生物信息学分析和文献调研。其中表达量差异在1倍以上基因658个,表达量差异在2倍以上的基因有260个。175个基因在C4-2细胞中更多还原

【Abstract】 The vast amount of information available through the human genome project .However, the mere sequence information of the whole genome does not answer all our questions. What is required at this stage is a complete understanding of the function of genes and other parts of the genome so as to uncover how sets of genes and their products work together in normal and diseased conditions. DNA microarrays are some of the most powerful and versatile tools available, and there are several applications of microarray technology in cancer biology. Since cancer is a genetic disease arising from the progressive accumulation of many genetic alternations, identification of differences in the expression profile of tumor cells in comparison to their normal counterpart would provide a better platform for understanding the process of tumor formation and development.Prostate cancer is a leading cause of cancer-related deaths and the most commonly diagnosed cancer in men in the west. By nature, cancer in the prostate progresses slowly and can be treated effectively when detected early; however, the metastastatic disease presents a major challenge to improve survival rate and treatment efficacy. To overcome this problem, it is critical to identify predictors to distinguish prostate cancers that will progress and metastasize, and to separate them from those that will not progress during the expected lifetime of the patient. Metastatic prostate cancer proceeds through a series of distinct states such as transformation of normal prostatic epithelial cells to preinvasive primary tumor, androgen-dependent invasive cancer, and androgen-independent (AI) metastatic disease. These stages of prostate cancer involve multiple molecular changes some of which can be implicated to alterations in gene expression.Progression to androgen independence (AI) leading to uncontrolled cell growth is the main cause of death in prostate cancer. While almost all patients with metastatic prostate cancer will initially respond to anti-androgen treatments, the majority will fail hormonal treatments in less than 2 years. Both genetic and epigenetic alterations in更多还原