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P-2: Risk Prediction of platinum-based chemotherapy and Radiotherapy Outcome

P-2：铂类化疗和放疗结果的风险预测

基本信息

批准号：
7921399
负责人：
Xifeng Wu
金额：
$ 35.47万
依托单位：
UT SOUTHWESTERN MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-08-22 至 2013-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7921399
关键词：
Acute Adopted Alcohols Algorithms Alleles Apoptosis Apoptotic Base Excision Repairs Biological Assay Biological Markers Blood specimen Body Weight decreased Cancer Patient Cell Cycle Checkpoint Cell Cycle Regulation Cells Cessation of life Characteristics Chest Cisplatin Classification Clinical Clinical Data Clinical Oncology Code Combined Modality Therapy DNA DNA Repair Data Databases Development Dose Double Strand Break Repair Enrollment Environment Epidemiologic Studies Epidemiology Excision Family Cancer History Frequencies Functional disorder Funding Genes Genetic Genetic Markers Genetic Polymorphism Genetic Predisposition to Disease Genetic Variation Genotype Goals Hand Haplotypes Individual Inflammation Integration Host Factors Interview Journals Lead Lymphocyte Machine Learning Malignant Neoplasms Malignant neoplasm of esophagus Malignant neoplasm of lung Measures Medical Medical History Medicine Metabolism Modality Modeling Molecular Molecular Epidemiology Molecular Profiling Non-Small-Cell Lung Carcinoma Normal tissue morphology Nucleic Acid Regulatory Sequences Nucleotide Excision Repair Nucleotides Outcome Oxidative Stress P-2 Paper Participant Pathway interactions Patients Penetrance Performance Status Pharmaceutical Preparations Platinum Platinum Compounds Platinum adduct Predisposition Prognostic Marker Proteins Protocols documentation Publications Publishing Quality of life RNA Splicing Radiation Radiation Induced DNA Damage Radiation Toxicity Radiation therapy Recording of previous events Reproduction spores Research Infrastructure Risk Risk Assessment Role Series Site Smoking Specimen Staging Subgroup System Texas Therapeutic Time Tissues Toxic effect Treatment Efficacy Treatment outcome Trees Tumor-Derived Universities University of Texas M D Anderson Cancer Center Variant Work Wound Healing analog base cancer risk chemotherapy clinical efficacy clinically relevant clinically significant cohort cost design drug metabolism epidemiologic data experience follow-up gene environment interaction genetic epidemiology genome-wide high risk improved novel protein function repaired response success telomere tool treatment planning trend tumor uptake

项目摘要

The overarching goal of this project is to determine host epidemiologic and genetic factors that will be predictive of efficacy and toxicity of platinum-based chemotherapy or combined with thoracic radiotherapy in NSCLC patients. We will construct a well-characterized cohort of 1,200 NSCLC patients (Stages III and IV - receiving first-line platinum-based chemotherapy ¿ definitive thoracic radiotherapy). This cohort will then be studied for epidemiologic, clinical and a large number of rationally selected germline polymorphisms to correlate with the clinical outcome to allow us to construct predictive risk models for clinical efficacy and toxicity. We estimate there will be ~ 600 patients treated by platinum-based chemotherapy alone, and 600 Stage III patients receiving platinum-based chemotherapy plus definitive thoracic radiotherapy. There are three specific aims: 1) we will identify novel genetic loci that predict efficacy and toxicity to platinum-based chemotherapy and radiotherapy in all 1,200 patients. We will adopt a pathway-based genotyping and analyzing approach to evaluate frequencies .of about 8,000 SNPs in genes involved in pathways relevant to platinum and radiation response. We will examine individual SNP main effects, haplotypes, and the cumulative effect of SNPs in modulating efficacy and toxicity. Our hypothesis is that specific genotypes that alter the metabolism or action of platinum agents or relevant to the genotoxic effects of radiotherapy may impact the efficacy and toxicity of patients to these therapies. 2) we will apply machine-learning tools to identify gene-gene and gene-environment interactions influencing NSCLC outcome. We will develop algorithms to identify subgroups with differing platinum or radiotherapy treatment efficacy or toxicity. Our hypothesis is that therapeutic response is modulated by common, low penetrance polymorphisms, and that these polymorphisms interact with each other and/or host factors in determining response to therapy. 3) we will construct predictive risk models for survival and toxicity by integrating clinical and epidemiologic data with the genetic data from this project,and additional information from other R01 studies devoted to these cohorts such as a series of phenotypic assays. We hypothesize that the addition of genetic markers to the standard clinical and epidemiologic variables will improve the prediction of survival and toxicity of the final risk assessment models. We will compare the prediction accuracy among all patients, patients receiving chemotherapy alone, and patients treated by combined modality. The risk models resulting from this project may permit clinicians to identify patients before the start of therapy who are most and least likely to benefit or to develop toxicity and will have immense clinical benefit in terms of planning chemotherapy and radiotherapy for individual patients.

该项目的总体目标是确定宿主流行病学和遗传因素预测铂类化疗或联合胸部放疗的疗效和毒性非小细胞肺癌患者。我们将构建一个由 1,200 名 NSCLC 患者（III 期和 IV 期 - 接受一线铂类化疗（根治性胸部放疗）。这个队列将被研究流行病学、临床和大量合理选择的种系多态性与临床结果相关联，使我们能够构建临床疗效的预测风险模型毒性。我们估计将有约 600 名患者仅接受铂类化疗治疗，还有 600 名患者接受铂类化疗。接受铂类化疗加明确胸部放疗的 III 期患者。有三个具体目标：1）我们将确定新的基因位点，预测铂类药物的功效和毒性对所有 1,200 名患者进行了化疗和放疗。我们将采用基于途径的基因分型评估与相关途径相关的基因中约 8,000 个 SNP 的频率的分析方法铂和辐射反应。我们将检查个体 SNP 主效应、单倍型和 SNP 在调节功效和毒性方面的累积效应。我们的假设是特定的基因型改变铂类药物的代谢或作用或与遗传毒性作用相关放射治疗可能会影响患者对这些疗法的疗效和毒性。 2）我们将申请机器学习工具可识别影响非小细胞肺癌的基因-基因和基因-环境相互作用结果。我们将开发算法来识别具有不同铂或放射治疗的亚组功效或毒性。我们的假设是治疗反应受到常见的、低水平的调节外显率多态性，并且这些多态性彼此和/或宿主相互作用决定治疗反应的因素。 3）我们将构建生存预测风险模型通过将临床和流行病学数据与该项目的遗传数据相结合，以及其他来自致力于这些群体的其他 R01 研究的信息，例如一系列表型测定。我们假设将遗传标记添加到标准临床和流行病学变量中将改善最终风险评估模型的生存和毒性预测。我们将比较所有患者、仅接受化疗的患者以及接受化疗的患者的预测准确性采用联合疗法进行治疗。该项目产生的风险模型可以让临床医生识别在治疗开始前最有可能和最不可能受益或出现毒性的患者在为个体患者规划化疗和放疗方面具有巨大的临床益处。