Liu Xiaotong, Tian Guoliang, Liu Zhenqiu
Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, People's Republic of China.
Department of Public Health Sciences, Pennsylvania State University, Hershey, PA, USA.
J Appl Stat. 2021 Sep 11;50(3):691-702. doi: 10.1080/02664763.2021.1973387. eCollection 2023.
Triple-negative breast cancer (TNBC) is generally considered an aggressive breast cancer subtype associated with poor prognostic outcomes. Up to now, the molecular and cellular mechanisms underlying TNBC pathology have not been fully understood. In this manuscript, we propose a novel semiparametric model with kernel for gene-based analysis with a breast cancer GWAS data. The software of SPMGBA (semiparametric method for gene-based analysis) in MATLAB is available at GitHub (https://github.com/zliu3/SPMGBA). Genetic signatures associated with breast cancer are discovered. We further validate the prognostic power of the identified genes with a large cohort of expression data from the European Genome-Phenome Archive, and discover that SEL1L is associated with the overall survival of TNBC with the -value of .0002. We conclude that gene SEL1L is down-regulated in TNBC and the expression of SEL1L is positively associated with patient survival.
三阴性乳腺癌（TNBC）通常被认为是一种侵袭性乳腺癌亚型，与不良预后结果相关。到目前为止，TNBC病理学背后的分子和细胞机制尚未完全了解。在本手稿中，我们提出了一种用于基于基因分析的新型带核半参数模型，并使用了乳腺癌全基因组关联研究（GWAS）数据。MATLAB中的SPMGBA（基于基因分析的半参数方法）软件可在GitHub（https://github.com/zliu3/SPMGBA）上获取。发现了与乳腺癌相关的基因特征。我们进一步使用来自欧洲基因组-表型档案库的大量表达数据队列验证了所鉴定基因的预后能力，并发现SEL1L与TNBC的总生存期相关，P值为0.0002。我们得出结论，基因SEL1L在TNBC中表达下调，且SEL1L的表达与患者生存率呈正相关。
