School of Medicine, Henan Polytechnic University, Jiaozuo 454150, Henan, China.
Genes (Basel). 2020 Feb 16;11(2):200. doi: 10.3390/genes11020200.
Breast cancer has the highest mortality and morbidity among women, especially in elderly women over 60 years old. Abnormal alternative splicing (AS) events are associated with the occurrence and development of geriatric breast cancer (GBC), yet strong evidence is lacking for the prognostic value of AS in GBC and the regulatory network of AS in GBC, which may highlight the mechanism through which AS contributes to GBC. In the present study, we obtained splicing event information (SpliceSeq) and clinical information for GBC from The Cancer Genome Atlas, and we constructed a GBC prognosis model based on AS events to predict the survival outcomes of GBC. Kaplan-Meier analysis was conducted to evaluate the predictive accuracy among different molecular subtypes of GBC. We conducted enrichment analysis and constructed a splicing network between AS and the splicing factor (SF) to examine the possible regulatory mechanisms of AS in GBC. We constructed eight prognostic signatures with very high statistical accuracy in predicting GBC survival outcomes from 45,421 AS events of 10,480 genes detected in 462 GBC patients; the prognostic model based on exon skip (ES) events had the highest accuracy, indicating its significant value in GBC prognosis. The constructed regulatory SF-AS network may explain the potential regulatory mechanism between SF and AS, which may be the mechanism through which AS events contribute to GBC survival outcomes. The findings confirm that AS events have a significant prognostic value in GBC, and we found a few effective prognostic signatures. We also hypothesized the mechanism underlying AS in GBC and discovered a potential regulatory mechanism between SF and AS.
乳腺癌是女性中死亡率和发病率最高的癌症,尤其在 60 岁以上的老年女性中更为常见。异常的选择性剪接(AS)事件与老年乳腺癌(GBC)的发生和发展有关,但目前缺乏 AS 在 GBC 中的预后价值以及 GBC 中 AS 的调控网络的有力证据,这可能突出了 AS 促进 GBC 的机制。在本研究中,我们从癌症基因组图谱中获得了 GBC 的剪接事件信息(SpliceSeq)和临床信息,并构建了基于 AS 事件的 GBC 预后模型,以预测 GBC 的生存结局。Kaplan-Meier 分析用于评估不同 GBC 分子亚型之间的预测准确性。我们进行了富集分析,并构建了 AS 与剪接因子(SF)之间的剪接网络,以研究 AS 在 GBC 中的可能调控机制。我们从 462 名 GBC 患者的 10480 个基因的 45421 个 AS 事件中构建了 8 个具有非常高统计准确性的预后签名,用于预测 GBC 的生存结局;基于外显子跳跃(ES)事件的预后模型具有最高的准确性,表明其在 GBC 预后中的重要价值。构建的调控 SF-AS 网络可能解释了 SF 和 AS 之间的潜在调控机制,这可能是 AS 事件影响 GBC 生存结局的机制。研究结果证实,AS 事件在 GBC 中具有显著的预后价值,并且我们发现了一些有效的预后签名。我们还假设了 GBC 中 AS 的机制,并发现了 SF 和 AS 之间的潜在调控机制。