A Generalized Integration Approach to Association Analysis with Multi-category Outcome: An Application to a Tumor Sequencing Study of Colorectal Cancer and Smoking.
A Generalized Integration Approach to Association Analysis with Multi-category Outcome: An Application to a Tumor Sequencing Study of Colorectal Cancer and Smoking.
复制标题
多类别结果关联分析的通用整合方法：在结直肠癌和吸烟的肿瘤测序研究中的应用。
DOI：
10.1080/01621459.2022.2105703
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发表时间：
2023
影响因子：
3.7
通讯作者：
Hsu,Li
中科院分区：
文献类型：
--
作者：
Zheng,Jiayin;Dong,Xinyuan;Newton,ChristinaC;Hsu,Li
癌症是一种异质性疾病，测序和组学技术的快速发展使研究人员能够全面表征肿瘤。这激发了研究风险因素如何与各种肿瘤异质性特征相关的浓厚兴趣。癌症预防研究II（CPS-II）队列是最大的前瞻性研究之一，对于阐明癌症与风险因素之间的关联特别有价值。在这篇文章中，我们研究了吸烟与靶向测序获得的新型结直肠肿瘤标志物的相关性。然而，由于成本和后勤困难，只能测定有限数量的肿瘤，这限制了我们研究这些关联的能力。与此同时，有广泛的研究评估吸烟与整体癌症风险和已建立的结直肠肿瘤标志物的关联。重要的是，这些摘要信息可以从文献中轻松获得。通过将此汇总信息与具有适当约束的感兴趣参数相关联，我们开发了一种用于多分类逻辑回归模型的广义积分方法，其结果以肿瘤特征为特征。该方法在缩小参数搜索空间的约束条件下，通过最大化个体水平肿瘤数据和外部汇总信息的联合似然来提高效率。我们将所提出的方法应用于CPS-II数据，并确定了吸烟与结直肠癌风险的关联，其不同之处在于APC和RNF 43基因的突变状态，这两者都不是通过常规的CPS-II个体数据分析确定的。这些结果有助于更好地了解吸烟在结直肠癌病因中的作用。本文的补充材料可在网上查阅。
Cancer is a heterogeneous disease, and rapid progress in sequencing and -omics technologies has enabled researchers to characterize tumors comprehensively. This has stimulated an intensive interest in studying how risk factors are associated with various tumor heterogeneous features. The Cancer Prevention Study-II (CPS-II) cohort is one of the largest prospective studies, particularly valuable for elucidating associations between cancer and risk factors. In this article, we investigate the association of smoking with novel colorectal tumor markers obtained from targeted sequencing. However, due to cost and logistic difficulties, only a limited number of tumors can be assayed, which limits our capability for studying these associations. Meanwhile, there are extensive studies for assessing the association of smoking with overall cancer risk and established colorectal tumor markers. Importantly, such summary information is readily available from the literature. By linking this summary information to parameters of interest with proper constraints, we develop a generalized integration approach for polytomous logistic regression model with outcome characterized by tumor features. The proposed approach gains the efficiency through maximizing the joint likelihood of individual-level tumor data and external summary information under the constraints that narrow the parameter searching space. We apply the proposed method to the CPS-II data and identify the association of smoking with colorectal cancer risk differing by the mutational status of APC and RNF43 genes, neither of which is identified by the conventional analysis of CPS-II individual data only. These results help better understand the role of smoking in the etiology of colorectal cancer. Supplementary materials for this article are available online.