【佳學(xué)基因檢測(cè)】癌癥易感基因的發(fā)現(xiàn)：研究設(shè)計(jì)、分析方法和技術(shù)趨勢(shì)

人體基因檢測(cè)需要多少錢—比較

開會(huì)學(xué)習(xí)基因?qū)嶒?yàn)室人員知識(shí)更新《腫瘤靶向藥物選擇的基因突變標(biāo)準(zhǔn)》,了解到《J Natl Cancer Inst Monogr》在. 1999;(26):1-16.發(fā)表了一篇題目為《癌癥易感基因的發(fā)現(xiàn)：研究設(shè)計(jì)、分析方法和技術(shù)趨勢(shì)》腫瘤靶向藥物治療基因檢測(cè)臨床研究文章。該研究由D J Schaid, K Buetow, D E Weeks, E Wijsman, S W Guo, J Ott, C Dahl等完成。促進(jìn)了腫瘤風(fēng)險(xiǎn)基因檢測(cè)項(xiàng)目設(shè)計(jì)的全面性與正確性，進(jìn)一步強(qiáng)調(diào)了基因信息檢測(cè)與分析在除低癌癥發(fā)病率中的重要性。

腫瘤靶向藥物及正確治療臨床研究?jī)?nèi)容關(guān)鍵詞：

癌癥，易感基因,腫瘤風(fēng)險(xiǎn),基因檢測(cè),設(shè)計(jì),風(fēng)險(xiǎn)

腫瘤靶向治療基因檢測(cè)臨床應(yīng)用結(jié)果

確定癌癥的遺傳原因具有巨大的公共衛(wèi)生益處，從預(yù)防到早期發(fā)現(xiàn)和治療疾病。盡管已經(jīng)成功鑒定了許多癌癥易感基因，但設(shè)計(jì)和分析問(wèn)題仍然挑戰(zhàn)著當(dāng)前基因發(fā)現(xiàn)的范式。一些例子是癌癥表型的定義和測(cè)量、中間終點(diǎn)的使用、樣本的選擇（例如，受影響的相對(duì)對(duì)與大的擴(kuò)展譜系）、分析基因解碼基因檢測(cè)的研究方法的選擇[例如，幾率的參數(shù)對(duì)數(shù) (LOD) score 基因解碼基因檢測(cè)的研究方法與無(wú)模型基因解碼基因檢測(cè)的研究方法]，以及基因-環(huán)境相互作用對(duì)連鎖分析的影響。此外，基于傳統(tǒng)病例對(duì)照研究設(shè)計(jì)或基于家庭的對(duì)照的關(guān)聯(lián)基因解碼基因檢測(cè)的研究方法是評(píng)估候選基因或篩選連鎖不平衡的流行選擇。賊后，基因發(fā)現(xiàn)的研究設(shè)計(jì)和分析基因解碼基因檢測(cè)的研究方法在一定程度上取決于實(shí)驗(yàn)室內(nèi)何種基因組技術(shù)是可行的。許多與基因發(fā)現(xiàn)相關(guān)的主要問(wèn)題，以及將影響基因發(fā)現(xiàn)的基因組技術(shù)趨勢(shì)，都從其優(yōu)缺點(diǎn)的角度進(jìn)行了討論，指出了需要進(jìn)一步開展工作的領(lǐng)域。

腫瘤發(fā)生與反復(fù)轉(zhuǎn)移國(guó)際數(shù)據(jù)庫(kù)描述：

Determining the genetic causes of cancers has immense public health benefits, ranging from prevention to earlier detection and treatment of disease. Although a number of cancer susceptibility genes have been successfully identified, design and analytic issues remain that challenge the current paradigm of gene discovery. Some examples are the definition and measurement of cancer phenotype, the use of intermediate end points, the choice of sample (e.g., affected relative pairs versus large extended pedigrees), the choice of analytic method [e.g., parametric logarithm of the odds (LOD) score method versus model-free methods], and the influence of gene-environment interaction on linkage analysis. Furthermore, association methods, based on either the traditional case-control study design or family-based controls, are popular choices to evaluate candidate genes or screen for linkage disequilibrium. Finally, the study design and analytic methods for gene discovery are determined to some extent by what genomic technology is feasible within the laboratory. Many of the main issues related to gene discovery, as well as trends in genomic technology that will impact on gene discovery, are discussed from the perspective of their strengths and weaknesses, pointing to areas in need of further work.