Qin Muping, Ma Yanfei, Wang Zifan, Fang Dalang, Wei Jie
Department of Hematology, Baise People's Hospital, Baise, China.
Department of Oncology, Wuzhou Red Cross Hospital, Wuzhou, China.
Transl Cancer Res. 2021 Jun;10(6):2991-3003. doi: 10.21037/tcr-21-783.
The role of immune-related long noncoding RNAs (irlncRNAs) in breast cancer (BRCA) is still unclear. Recently, studies have performed analyses based on the expression of irlncRNAs, however, in the present study, we used a novel method that did not require the specific expression levels of lncRNAs of BRCA patients.
We downloaded transcriptome and clinical data of BRCA patients from The Cancer Genome Atlas (TCGA), obtained immune genes from the Immport database, and extracted immune genes and lncRNAs for correlation analysis. Then, the differential expression of irlncRNA pairs (IRLPs) was determined and the prognostic signature was established by the IRLPs. The immune cell abundance of the TCGA-BRCA cohort was downloaded from the Tumor IMmune Estimation Resource (TIMER) database, and the relationship between the risk score of the IRLP signature and immune cell abundance was analyzed. Finally, we explored the relationship between risk scores and drug sensitivity based on the R package pRRophetic.
Univariate cox regression results showed that 33 IRLPs had significant effects on the overall survival (OS) of BRCA patients. Then 22 IRLPs were obtained via lasso regression for further analysis. Multivariate regression analysis obtained 12 IRLPs to establish the IRLP prognostic signature. The model showed that this IRLP signature could act as a prognostic biomarker for BRCA patients. Kaplan-Meier (KM) survival analysis indicated that low-risk patients of IRLP's signature had a better OS (P<0.001). Advanced status BRCA patients may have higher risk scores, and univariate and multivariate cox regression analyses showed that risk scores were independent prognostic factors of clinical features (P<0.001). The results of the relationship between risk scores and immune infiltration showed that M1 macrophages were higher in the low-risk group (P=0.00015), while M2 macrophages were higher in the high-risk group (P=0.0015). The high-risk group had a greater sensitivity to chemotherapeutic agents such as cisplatin, docetaxel, doxorubicin, and gemcitabine.
In present study, we used a novel method that did not require the specific expression levels of lncRNAs of BRCA patients, which can be used as a novel model for predicting the prognosis of BRCA patients.
免疫相关长链非编码RNA（irlncRNAs）在乳腺癌（BRCA）中的作用仍不清楚。最近，已有研究基于irlncRNAs的表达进行分析，然而，在本研究中，我们使用了一种不需要BRCA患者lncRNAs特定表达水平的新方法。
我们从癌症基因组图谱（TCGA）下载了BRCA患者的转录组和临床数据，从免疫数据库（Immport）获取免疫基因，并提取免疫基因和lncRNAs进行相关性分析。然后，确定irlncRNA对（IRLPs）的差异表达，并通过IRLPs建立预后特征。从肿瘤免疫评估资源（TIMER）数据库下载TCGA - BRCA队列的免疫细胞丰度，并分析IRLP特征的风险评分与免疫细胞丰度之间的关系。最后，我们基于R包pRRophetic探索了风险评分与药物敏感性之间的关系。
单因素cox回归结果显示，33个IRLPs对BRCA患者的总生存期（OS）有显著影响。然后通过lasso回归获得22个IRLPs用于进一步分析。多因素回归分析获得12个IRLPs以建立IRLP预后特征。该模型表明，这种IRLP特征可作为BRCA患者的预后生物标志物。Kaplan - Meier（KM）生存分析表明，IRLP特征的低风险患者具有更好的总生存期（P<0.001）。晚期BRCA患者可能具有更高的风险评分，单因素和多因素cox回归分析表明风险评分是临床特征的独立预后因素（P<0.001）。风险评分与免疫浸润之间的关系结果显示，低风险组中M1巨噬细胞较高（P = 0.00015），而高风险组中M2巨噬细胞较高（P = 0.0015）。高风险组对顺铂、多西他赛、阿霉素和吉西他滨等化疗药物具有更高的敏感性。
在本研究中，我们使用了一种不需要BRCA患者lncRNAs特定表达水平的新方法，该方法可作为预测BRCA患者预后的新模型。
