【佳学基因检测】“绝望的管家基因”：缺氧的戏剧性例子

靶向治疗基因检测医保报销吗—揭密

讨论制裁华大基因会不会影响基因检测价格及基因检测机构自我培训教材《肿瘤基因易感位点列表及发生率分析》《Br J Cancer》在. 2010 Mar 16;102(6):1037-43.发表了一篇题目为《“绝望的管家基因”：缺氧的戏剧性例子》肿瘤靶向药物治疗基因检测临床研究文章。该研究由J Caradec , N Sirab, C Keumeugni, S Moutereau, M Chimingqi, C Matar, D Revaud, M Bah, P Manivet, M Conti, S Loric等完成。研究提出了基因检测不同基因的权重评估的重要性，指出了解基因检测的具体项目要比选则检测项目名称更为重要的可行性建议。

肿瘤是否遗传课题临床研究内容关键词：

基因检测技术,PCR,看家基因,管家基因,参考基因,参考组

肿瘤靶向治疗基因检测临床应用结果

肿瘤基因研究背景：正常或肿瘤组织和细胞系中的微环境条件可能会干扰进一步的生物学分析。为了仔细评估转录变异，通常使用稳定的看家基因 (HKG) 来标准化定量微阵列或实时聚合酶链反应（PCR)结果。然而，最近的研究认为，看家基因 (HKG)根据组织和治疗而波动。因此，作为在癌症领域常见的一系列条件下看家基因 (HKG) 变异的一个例子，肿瘤基因解码评估缺氧是否会对看家基因 (HKG)表达产生影响。肿瘤基因检测技术研究方法：在用四种细胞系处理的四种细胞系上测量 10 种常用看家基因 (HKG)的表达。氧浓度（从 1% 到 20%）。结果：在缺氧条件下观察到看家基因 (HKG)转录物的巨大变化，并且随着细胞系和氧浓度的不同而不同。为了选出最稳定的看家基因 (HKG)，肿瘤基因解码比较了基于 PCR 循环阈值变异系数计算或两个专门的软件的三种统计方法。然而，根据所使用的统计方法，最好的看家基因 (HKG)有很大的不同。此外，作为参考，使用靶基因（此处为蛋白酶激活受体基因 1 (PAR1) 基因）的绝对定量，佳学基因解码表明，根据用于标准化的所选看家基因 (HKG)，关于缺氧中 PAR1 变异的结论可能完全不同.结论：有效看家基因 (HKG)的选择将决定进一步解释结果的相关性，因此应认真考虑。佳学基因检测技术的研究结果明确证实，在针对每种情况进行任何实验之前，必须精确和系统地确定看家基因 (HKG)变化，以便在设计的实验设置中获得可靠的归一化结果。事实上，在扩展到其他实验模型（包括体内模型）之前，应仔细评估这种适用于所有体外系统的分析设计。

肿瘤发生与复发转移国际数据库描述：

Background: Microenvironmental conditions in normal or tumour tissues and cell lines may interfere on further biological analysis. To evaluate transcript variations carefully, it is common to use stable housekeeping genes (HKG) to normalise quantitative microarrays or real-time polymerase chain reaction results. However, recent studies argue that HKG fluctuate according to tissues and treatments. So, as an example of HKG variation under an array of conditions that are common in the cancer field, we evaluate whether hypoxia could have an impact on HKG expression.Methods: Expression of 10 commonly used HKG was measured on four cell lines treated with four oxygen concentrations (from 1 to 20%).Results: Large variations of HKG transcripts were observed in hypoxic conditions and differ along with the cell line and the oxygen concentration. To elect the most stable HKG, we compared the three statistical means based either on PCR cycle threshold coefficient of variation calculation or two specifically dedicated software. Nevertheless, the best HKG dramatically differs according to the statistical method used. Moreover, using, as a reference, absolute quantification of a target gene (here the proteinase activating receptor gene 1 (PAR1) gene), we show that the conclusions raised about PAR1 variation in hypoxia can totally diverge according to the selected HKG used for normalisation.Conclusion: The choice of a valid HKG will determine the relevance of the results that will be further interpreted, and so it should be seriously considered. The results of our study confirm unambiguously that HKG variations must be precisely and systematically determined before any experiment for each situation, to obtain reliable normalised results in the experimental setting that has been designed. Indeed, such assay design, functional for all in vitro systems, should be carefully evaluated before any extension to other experimental models including in vivo ones.