Table_1_Association Analysis of Somatic Copy Number Alteration Burden With Breast Cancer Survival.XLSX

The increasing prevalence of diagnosed breast cancer cases emphasizes the urgent demand for developing new prognostic breast cancer biomarkers. Copy number alteration (CNA) burden measured as the percentage of the genome affected by CNAs has emerged as a potential candidate to this aim. Using somatic CNA data obtained from METABRIC (Molecular Taxonomy of Breast Cancer International Consortium), we implemented Kaplan-Meier estimators and Cox proportional hazards models to examine the association of CNA burden with patient’s overall survival (OS) and disease specific survival (DSS). We also evaluated the association by considering patients’ age and tumor subtypes using stratified Cox models. We delineated the distribution of CNA burden in sample genomes and highlighted chromosomes 1, 8, and 16 as the carriers of the highest CNA burden. We identified a strong association between CNA burden and age as well as CNA burden and breast cancer PAM50 subtypes. We found that controlling the effects of both age (bound by 45-year) and PAM50 subtypes on patient survival using stratified Cox models, would still result in significant association between CNA burden and patients overall survival in both Discovery and Validation data. The same trend was observed in disease specific survival when only PAM50 subtypes were controlled in the stratified Cox models. Our analysis showed that there is a significant association between CNA burden and breast cancer survival. This result is also validated by using TCGA (The Cancer Genome Atlas) data. CNA burden of breast cancer patients has a considerable potential to be used as a novel prognostic biomarker.

确诊乳腺癌病例的持续攀升，凸显了开发新型乳腺癌预后生物标志物的迫切需求。拷贝数变异（Copy Number Alteration, CNA）负荷——以受CNA影响的基因组占比进行量化——已成为该研究领域的潜在候选标志物。本研究采用国际乳腺癌分子分类联盟（Molecular Taxonomy of Breast Cancer International Consortium, METABRIC）提供的体细胞CNA数据，运用Kaplan-Meier估计法与Cox比例风险模型，分析CNA负荷与患者总生存期（Overall Survival, OS）及疾病特异性生存期（Disease Specific Survival, DSS）的关联。本研究还通过分层Cox模型，结合患者年龄与肿瘤亚型，进一步评估了上述关联。本研究明确了样本基因组中CNA负荷的分布特征，并指出1号、8号及16号染色体为CNA负荷最高的染色体区域。本研究发现CNA负荷与患者年龄，以及CNA负荷与乳腺癌PAM50亚型之间均存在显著关联。本研究发现，即便采用分层Cox模型控制年龄（以45岁为界）与PAM50亚型对患者生存的影响，在发现队列与验证队列数据中，CNA负荷仍与患者总生存期存在显著关联。当仅通过分层Cox模型控制PAM50亚型的影响时，疾病特异性生存期也呈现出相同的趋势。本研究分析表明，CNA负荷与乳腺癌患者生存存在显著关联，这一结果也通过癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据得到了验证。乳腺癌患者的CNA负荷具备成为新型预后生物标志物的可观潜力。