Compendium of primary head and neck cancer gene expression datasets with accompanying clinical data

We assembled a compendium of 30 primary HNC gene expression datasets with accompanying clinical data, representing the largest such resource for HNC. This resource was specifically built to identify genes associated with two outcome variables: patient survival and lymph node metastasis (LNM) status. Meta-analyses were applied to uniformly preprocessed gene expression data, as in our PRECOG resource (Gentles et al, Nat Med, 2016). Briefly, datasets were quality controlled, normalized, log transformed, and standardized to calculate gene expression profiles. Clinical data were manually curated and included survival and LNM status as well as variables relevant to HNC prognosis, such as tumor grade, tumor subanatomic location, and HPV status. The resulting 30 cleaned studies included 2,134 HNC tumors. 1,666 patients (across 17 cohorts) had survival outcome data and 1,490 patients (21 cohorts) had LNM status. Fully processed datasets are provided here as a resource to enable efficient meta-analyses of gene expression data in head and neck cancer.我们构建了包含30个原发性头颈部癌症（Head and Neck Cancer, HNC）基因表达数据集及其配套临床数据的汇编资源，是目前同类HNC研究资源中规模最大的一项。本资源专为识别与两类结局变量相关的基因而构建：患者生存情况与淋巴结转移（Lymph Node Metastasis, LNM）状态。本研究采用与我们此前构建的PRECOG资源（Gentles等，《自然·医学》，2016年）一致的方法，对统一预处理后的基因表达数据开展荟萃分析。简言之，我们对数据集进行了质量控制、归一化、对数转换与标准化处理，以计算基因表达谱。临床数据经人工审核整理，涵盖生存情况、LNM状态，以及与HNC预后相关的其他变量，例如肿瘤分级、肿瘤亚解剖部位与人类乳头瘤病毒（Human Papillomavirus, HPV）感染状态。最终得到的30项经过清洗的研究共纳入2134例HNC肿瘤样本。其中17个队列的1666例患者携带生存结局数据，21个队列的1490例患者携带LNM状态数据。本数据集已完成全部预处理流程，可作为研究资源供科研人员高效开展头颈部癌症基因表达数据的荟萃分析。