Validation and extension of the PREMM Model for mismatch repair gene mutations

描述（由申请人提供）：我们最近开发了MLH 1和MSH 2突变预测模型（PREMM 1，2），这是一种临床预测规则，旨在供医疗保健提供者使用，以估计个体携带MLH 1突变的可能性或MSH 2错配修复基因（Balmana等人. JAMA 2006）。PREMM 1，2被开发出来，随后在超过2000名林奇综合征风险升高并接受遗传评估的患者中进行了验证。Lynch综合征，也称为遗传性非息肉病性结直肠癌（HNPCC），是最常见的遗传性结肠癌综合征，也增加了几种结肠外癌症的风险。MLH 1和MSH 2突变是最常见的潜在原因。在一个家庭的子集中，在第三个错配修复基因MSH 6中发现突变，并导致较温和的表型。Lynch综合征患者的肿瘤表现出微卫星不稳定性（MSI），并且可以显示受影响的错配修复基因的表达缺失，这可以通过免疫组织化学分析（IHC）检测到。除了PREMM 1，2，其他两个预测模型最近已经开发出来，各种临床指南也可用于临床医生的风险评估工具。现有模型和临床指南的性能特征尚未与其他方法进行比较，也不知道哪种方法或方法组合是识别和管理Lynch综合征患者的最具成本效益的方法。作为我们之前工作的扩展，该项目的目标是（1）在多个现有的美国和国际结肠癌登记处验证PREMM 1，2，包括结肠癌家族登记处（CCFR）、EPICOLON和俄亥俄州队列;（2）扩展PREMM 1，2模型以包括对MH 6突变携带者的预测;（3）开发PREMMM 1，2，6模型的一个版本，其（i）允许并入关于MSI和IHC的信息以进一步改进种系突变的预测概率，和（ii）基于临床历史、MSI和IHC结果进行基因特异性预测;（4）比较PREMMM 1、2、6、Barnetson、MMRPro模型在（i）区分突变携带者与非携带者的能力;（ii）不同设置（iii）基于人群的子宫内膜癌病例系列;和（5）进行成本-效果分析，以确定PREMM 1，2，6模型和其他临床和分子策略在识别Lynch综合征风险个体中的作用。公共卫生相关性：这一努力的结果将实现PA-07-021的几个目标。它将（i）导致一个全面的临床和公共卫生方法来识别和管理遗传性结肠癌患者;（ii）允许更精确地估计与每个MMR基因相关的特定肿瘤，从而更有针对性地进行癌症筛查和预防方法;和（iii）汇集来自不同背景的研究人员，包括遗传学家、分子流行病学家、统计学家和临床医生，世卫组织将共同努力，分享现有数据和专门知识，以解决无法单独回答的研究问题。

DESCRIPTION (provided by applicant): We have recently developed the Prediction of MLH1 and MSH2 mutations model (PREMM1,2), a clinical prediction rule designed to be used by healthcare providers to estimate the probability that an individual carries a mutation in the MLH1 or MSH2 mismatch repair genes (Balmana et al. JAMA 2006). PREMM1,2 was developed and subsequently validated in over 2000 patients who were at elevated risk of Lynch Syndrome and undergoing genetic evaluation. Lynch Syndrome, also known as hereditary non- polyposis colorectal cancer (HNPCC), is the most common hereditary colon cancer syndrome, and also increases the risk for several extracolonic cancers. MLH1 and MSH2 mutations are the most common underlying cause. In a subset of families, mutations are found in a third mismatch repair gene, MSH6, and lead to a milder phenotype. Tumors in patients with Lynch syndrome demonstrate microsatellite instability (MSI) and can show loss of expression of the affected mismatch repair gene, which may be detected by immunohistochemical analysis (IHC). In addition to PREMM1,2, two other prediction models have recently been developed, and a variety of clinical guidelines are also available for the clinician as risk assessment tools. The performance characteristics of the available models and clinical guidelines have not been compared with another, nor is it known which approach, or combination of approaches, is the most cost-effective method of identifying and managing patients with Lynch Syndrome. As an expansion of our prior work, the aims of this project are (1) To validate PREMM1,2 in several existing U.S. and international colon cancer registries, including the Colon Cancer Family Registries (CCFR), EPICOLON, and Ohio State cohorts; (2)To expand the PREMM1, 2 model to include prediction of MSH6 mutation carriers; (3) To develop a version of the PREMMM1,2,6 model that (i) allows for the incorporation of information on MSI and IHC for further refinement of the predicted probabilities of a germline mutation, and (ii) makes gene-specific predictions based on clinical history, MSI and IHC results; (4)To compare the PREMMM1,2,6 , Barnetson, MMRPro models in (i) their ability to distinguish mutation carriers from non-carriers; (ii) different settings (population or clinic-based cases); (iii) a population-based series of endometrial cancer cases; and (5) To perform a cost-effectiveness analysis to define the role of the PREMM1,2,6 model and other clinical and molecular strategies for identification of individuals at risk of Lynch syndrome. PUBLIC HEALTH RELEVANCE: The results of this effort will achieve several goals of PA-07-021. It will (i) lead to a comprehensive clinical and public health approach to the identification and management of patients with hereditary colon cancer; (ii) allow for more precise estimation of the specific tumors associated with each MMR gene and therefore more targeted cancer screening and prevention approaches; and (iii) bring together investigators from diverse backgrounds, including geneticists, molecular epidemiologists, statisticians and clinicians, who will work together, share existing data and expertise to address research questions that could not be answered in isolation.