【佳学基因检测】癌症的遗传现象分析：家庭和双胞胎研究揭示基因检测人群

国内肿瘤基因检测十大公司解释

小组讨论：癌的基因检测基因解码如何创新治疗以及《肿瘤个性治疗的方法与措施》，大家分享了《Cancer Epidemiol Biomarkers Prev》在. 2001 Jul;10(7):733-41.发表了一篇题目为《癌症的遗传流行病学：解释家庭和双胞胎研究及其对分子遗传方法的影响》肿瘤靶向药物治疗基因检测临床研究文章。该研究由N Risch等完成。促进了肿瘤的精准治疗与个性化用药的发展，进一步强调了基因信息检测与分析的重要性。

肿瘤靶向药物及精准治疗临床研究内容关键词：

人类基因组草图,基因信息,遗传学,基因检测

肿瘤靶向治疗基因检测临床应用结果

 在基因破密过程中，世界多国科学家包括中国共同协作完成了人类基因组序列的粗略草图，开启了分子遗传学研究的新时代，佳学基因等机构开始研究癌症等许多复杂疾病的基因信息基础。同时，所选择的双胞胎对比研究方法表明遗传易感性对许多肿瘤的作用有限。对许多癌症部位的家族和双胞胎研究的重新评估表明以下一般基因解码基因检测的研究结论：（a）所有癌症的家族性程度大致相同，只有少数例外（高和低）； (b) 早期诊断通常与增加的家庭有关； (c) 家族性不会随着肿瘤患病率的降低而降低——事实上，趋势是随着患病率的降低家族性增加； (d) 多因素（多基因）阈值模型对大多数癌症的双胞胎数据的拟合效果不如单基因或遗传异质型模型； (e) 与显性或加性模型相比，隐性遗传通常不太可能； (f) 罕见肿瘤的遗传力仅在多基因模型的情况下降低，而在单基因座或异质性模型的情况下不降低； (g) 尽管家庭和双胞胎数据没有考虑基因-环境相互作用或混杂因素，但它们仍然与对大多数癌症部位造成高归因风险的基因一致。这些基因解码基因检测的研究结果支持继续寻找所有肿瘤类型的癌症易感性中的遗传和环境因素。根据遗传易感性的基本结构，给出了最佳研究设计的建议。

肿瘤发生与复发转移国际数据库描述：

The recent completion of a rough draft of the human genome sequence has ushered in a new era of molecular genetics research into the inherited basis of a number of complex diseases such as cancer. At the same time, recent twin studies have suggested a limited role of genetic susceptibility to many neoplasms. A reappraisal of family and twin studies for many cancer sites suggests the following general conclusions: (a) all cancers are familial to approximately the same degree, with only a few exceptions (both high and low); (b) early age of diagnosis is generally associated with increased familiality; (c) familiality does not decrease with decreasing prevalence of the tumor-in fact, the trend is toward increasing familiality with decreasing prevalence; (d) a multifactorial (polygenic) threshold model fits the twin data for most cancers less well than single gene or genetic heterogeneity-type models; (e) recessive inheritance is less likely generally than dominant or additive models; (f) heritability decreases for rarer tumors only in the context of the polygenic model but not in the context of single-locus or heterogeneity models; (g) although the family and twin data do not account for gene-environment interactions or confounding, they are still consistent with genes contributing high attributable risks for most cancer sites. These results support continued search for genetic and environmental factors in cancer susceptibility for all tumor types. Suggestions are given for optimal study designs depending on the underlying architecture of genetic predisposition.