Department of Breast and Thyroid Surgery, The Second Affiliated Hospital of Fujian Medical University, No.950 Donghai Street, Quanzhou, China.
Sci Rep. 2022 Dec 24;12(1):22322. doi: 10.1038/s41598-022-26894-5.
Breast cancer (BC) is one of the most frequent malignancies among women worldwide. Accumulating evidence indicates that long non-coding RNA (lncRNA) may affect BC progression. Exosomes, a class of small membrane vesicles, have been reported to promote tumor progression through transporting proteins, mRNAs, lncRNAs and some other small molecules. However, the interaction between exosome-related lncRNAs and the microenvironment of malignancies is unclear. Hence, we proceeded to investigate the relationship between exosome-related lncRNAs and BC microenvironment. 121 exosome-associated genes were extracted from ExoBCD database. Then, the Pearson analysis was used to screened out the exosome-related lncRNAs. After that, 15 exosome-related differentially expressed lncRNAs were identified by the correlation with BC prognosis. According to the sum of the expression of these 15 lncRNAs, extracted from The Cancer Genome Atlas, and the regression coefficients, an exosome-related lncRNAs signature was developed by using Cox regression analysis. With the median risk score of the training set, the patients in training and validation sets were separated to low-risk group and high-risk group. Subsequently, the lncRNA-mRNA co-expression network was constructed. The distinct enrichment pathways were compared among the different risk groups by using the R package clusterProfiler. The ESTIMATE method and ssGESA database were adopted to study the ESTIMATE Score and immune cell infiltration. Eventually, the expression of immune checkpoint associated genes, microsatellite instable and the immunophenoscore were further analyzed between different risk groups. Different risk groups exhibited different prognosis, with lower survival rate in the high-risk group. The differentially expressed genes between the different risk groups were enriched in biological processes pathways as well as immune responses. BC patients in high-risk group were identified with lower scores of ESTIMATE scores. Subsequently, we noticed that the infiltrating levels of aDCs, B cells, CD8+ T cells, iDCs, DCs, Neutrophils, macrophages, NK cells, pDCs, Tfh, T helper cells, TIL and Tregs were obvious elevated with the decreased risk score in training and validation cohorts. And some immune signatures were significantly activated with the decreased risk score in both cohorts. Eventually, the exosome-associated lncRNAs risk model was demonstrated to accurately predict immunotherapy response in patients with BC. The results of our study suggest that exosome-related lncRNAs risk model has close relationship with prognosis and immune cells infiltration in BC patients. These findings could make a great contribution to improving BC immunotherapy.
乳腺癌（BC）是全球女性中最常见的恶性肿瘤之一。越来越多的证据表明，长非编码 RNA（lncRNA）可能影响 BC 的进展。外泌体是一类小膜囊泡，已被报道通过转运蛋白、mRNA、lncRNA 和一些其他小分子促进肿瘤进展。然而，外泌体相关 lncRNA 与恶性肿瘤微环境之间的相互作用尚不清楚。因此，我们着手研究外泌体相关 lncRNA 与 BC 微环境之间的关系。我们从 ExoBCD 数据库中提取了 121 个与外泌体相关的基因。然后，通过 Pearson 分析筛选出与 BC 预后相关的外泌体相关 lncRNA。之后，通过与 BC 预后的相关性，从癌症基因组图谱中鉴定出 15 个外泌体相关差异表达的 lncRNA。根据这些从癌症基因组图谱中提取的 15 个 lncRNA 的表达总和和回归系数，通过 Cox 回归分析建立了一个外泌体相关 lncRNA 特征。利用训练集的中位数风险评分和回归系数，将训练集和验证集中的患者分为低风险组和高风险组。然后，构建了 lncRNA-mRNA 共表达网络。通过 R 包 clusterProfiler 比较不同风险组之间的显著富集途径。采用 ESTIMATE 方法和 ssGESA 数据库研究 ESTIMATE 评分和免疫细胞浸润。最后，分析不同风险组之间免疫检查点相关基因、微卫星不稳定和免疫表型评分的表达情况。不同风险组的预后不同，高风险组的生存率较低。不同风险组之间差异表达基因的富集途径主要涉及生物学过程以及免疫反应。高风险组 BC 患者的 ESTIMATE 评分较低。随后，我们注意到，在训练和验证队列中，随着风险评分的降低，aDCs、B 细胞、CD8+T 细胞、iDCs、DCs、中性粒细胞、巨噬细胞、NK 细胞、pDCs、Tfh、T 辅助细胞、TIL 和 Tregs 的浸润水平明显升高。并且在两个队列中，随着风险评分的降低，一些免疫特征明显被激活。最终，外泌体相关 lncRNA 风险模型被证明可以准确预测 BC 患者的免疫治疗反应。我们的研究结果表明，外泌体相关 lncRNA 风险模型与 BC 患者的预后和免疫细胞浸润密切相关。这些发现可能有助于改善 BC 的免疫治疗。
