Thyroid & Breast Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
Department of Oncology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.
Sci Rep. 2022 Jun 3;12(1):9311. doi: 10.1038/s41598-022-13499-1.
To date, there have not been great breakthroughs in immunotherapy for HER2 positive breast cancer (HPBC). This study aimed to build a risk model that might contribute to predicting prognosis and discriminating the immune landscape in patients with HPBC. We analyzed the tumor immune profile of HPBC patients from the TCGA using the ESTIMATE algorithm. Thirty survival-related differentially expressed genes were selected according to the ImmuneScore and StromalScore. A prognostic risk model consisting of PTGDR, PNOC and CCL23 was established by LASSO analysis, and all patients were classified into the high- and low-risk score groups according to the risk scores. Subsequently, the risk model was proven to be efficient and reliable. Immune related pathways were the dominantly enriched category. ssGSEA showed stronger immune infiltration in the low-risk score group, including the infiltration of TILs, CD8 T cells, NK cells, DCs, and so on. Moreover, we found that the expression of immune checkpoint genes, including PD-L1, CTLA-4, TIGIT, TIM-3 and LAG-3, was significantly upregulated in the low-risk score group. All the results were validated with corresponding data from the GEO database. In summary, our investigation indicated that the risk model composed of PTGDR, PNOC and CCL23 has potential to predict prognosis and evaluate the tumor immune microenvironment in HPBC patients. More importantly, HPBC patients with a low-risk scores are likely to benefit from immune treatment.
迄今为止，HER2 阳性乳腺癌（HPBC）的免疫治疗并未取得重大突破。本研究旨在构建一个风险模型，以期有助于预测 HPBC 患者的预后，并区分肿瘤免疫微环境。我们使用 ESTIMATE 算法分析了 TCGA 中 HPBC 患者的肿瘤免疫特征。根据 ImmuneScore 和 StromalScore 选择了 30 个与生存相关的差异表达基因。通过 LASSO 分析建立了一个由 PTGDR、PNOC 和 CCL23 组成的预后风险模型，根据风险评分将所有患者分为高风险评分组和低风险评分组。随后，验证了该风险模型的有效性和可靠性。免疫相关途径是显著富集的类别。ssGSEA 显示低风险评分组中免疫浸润更强，包括 TILs、CD8 T 细胞、NK 细胞、DC 等的浸润。此外，我们发现低风险评分组中免疫检查点基因的表达，包括 PD-L1、CTLA-4、TIGIT、TIM-3 和 LAG-3，显著上调。所有结果均与 GEO 数据库中的相应数据进行了验证。总之，我们的研究表明，由 PTGDR、PNOC 和 CCL23 组成的风险模型具有预测 HPBC 患者预后和评估肿瘤免疫微环境的潜力。更重要的是，低风险评分的 HPBC 患者可能受益于免疫治疗。
