Försti Asta, Hemminki Kari
Division of Molecular Genetic Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Methods Mol Biol. 2011;675:375-85. doi: 10.1007/978-1-59745-423-0_23.
Attempts to find genes contribution to complex diseases, such as cancer, require new study designs which incorporate an efficient use of population resources and modern genotyping technologies. We describe here two approaches, used by us for the study of breast cancer, both of which take the use of biobanks. One uses a cancer registry as a source of case information, which is then linked to a biobank on blood DNA. The biobank provides also samples from matched controls. After genotyping, clinical data are retrieved from hospital records, and the results can be presented for genotype-specific cancer risks, or similarly for genotype-specific clinical and survival parameters. The second approach uses registered data on cancer in families or among twins. On defined groups of patients, paraffin tissue is collected by contacting the pathology departments of the hospitals where the patients were diagnosed. Tumor and healthy tissue is prepared and used for mutation, the loss of heterozygosity, or copy number analysis. We believe that in the era of whole-genome genotyping technologies, the importance of well-characterized sample sets cannot be overemphasized. Samples rather than technologies limit the rate of gene discovery in complex diseases.
试图找出基因对诸如癌症等复杂疾病的影响，需要新的研究设计，这种设计要能有效利用人群资源和现代基因分型技术。我们在此描述我们用于乳腺癌研究的两种方法，这两种方法都利用了生物样本库。一种方法是将癌症登记处作为病例信息的来源，然后将其与血液DNA生物样本库相联系。该生物样本库还提供匹配对照的样本。基因分型后，从医院记录中检索临床数据，结果可以呈现特定基因型的癌症风险，或者类似地呈现特定基因型的临床和生存参数。第二种方法使用家族或双胞胎中癌症的登记数据。对于特定的患者群体，通过联系患者确诊医院的病理科来收集石蜡组织。制备肿瘤和健康组织并用于突变、杂合性缺失或拷贝数分析。我们认为，在全基因组基因分型技术的时代，特征明确的样本集的重要性再怎么强调也不为过。在复杂疾病中，限制基因发现速度的是样本而非技术。
