Hernandez-Boussard T, Montesano R, Hainaut P
International Agency for Research on Cancer Unit of Mechanisms of Carcinogenesis, Lyon, France.
Genet Anal. 1999 Feb;14(5-6):229-33. doi: 10.1016/s1050-3862(98)00030-8.
p53 gene encodes a transcription factor with tumor suppressive properties and to date, somatic mutation of this gene is the most common genetic event in human cancer. A relational database has been developed to facilitate the retrieval and analysis of these mutations at the International Agency for Research on Cancer (IARC) and it currently contains information on over 8000 individual tumors and cell lines. Many factors may influence the detection and reporting of mutations, including selection of tumor samples, study design, choice of methods, and quality control. There is also concern that several biases may affect the way data appear in the literature. Minimizing these biases is an essential methodological issue in the development of mutation data-bases. In this paper, we review and discuss these main sources of bias and make recommendations to authors in order to minimize bias in mutation detection and reporting.
p53基因编码一种具有肿瘤抑制特性的转录因子，迄今为止，该基因的体细胞突变是人类癌症中最常见的遗传事件。国际癌症研究机构（IARC）开发了一个关系数据库，以方便检索和分析这些突变，目前该数据库包含8000多个个体肿瘤和细胞系的信息。许多因素可能影响突变的检测和报告，包括肿瘤样本的选择、研究设计、方法的选择和质量控制。人们还担心，一些偏差可能会影响文献中数据的呈现方式。在突变数据库的开发中，尽量减少这些偏差是一个至关重要的方法学问题。在本文中，我们回顾并讨论了这些主要的偏差来源，并向作者提出建议，以尽量减少突变检测和报告中的偏差。
