新型焦亡-免疫相关长链非编码RNA特征在乳腺癌中呈现出独特的免疫细胞浸润格局。
Novel pyroptosis-immune-related lncRNA signature exhibits a distinct immune cell infiltration landscape in breast cancer.
作者信息
Kong Dedi, Cheng Hongju, Wang Meihong
机构信息
Shandong Qianfoshan Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Breast and Thyroid Surgery, Jining No 1 People's Hospital, Jining, Shandong, China.
出版信息
Front Immunol. 2025 Jan 21;15:1522327. doi: 10.3389/fimmu.2024.1522327. eCollection 2024.
INTRODUCTION
This study investigated pyroptosis- and immunity-related long non-coding RNAs (lncRNAs) to identify promising therapeutic targets for breast cancer (BC), and constructed lncRNA signatures to determine the prognosis and immunotherapy responses of BC patients.
METHODS
Pearson's correlation coefficient was used to identify pyroptosis- and immune-related differentially expressed lncRNAs (DE-pyrolncRNAs and DE-ImmlncRNAs, respectively). The Cancer Genome Atlas dataset was allocated to training and testing subsets. Prognostic lncRNA signatures were derived based on the training subset using univariate Cox regression analysis and Least Absolute Shrinkage and Selection Operator methods. Stepwise Cox regression was used to refine these signatures and to select the optimal lncRNA signature. The median risk score of the training subset was applied as a threshold to divide patients into high-risk (HR) and low-risk (LR) groups. The Wilcoxon test was used to reveal differences in immune scores, cell types, functions, and checkpoint genes between these groups. Single-cell sequencing data from GSE176078 were used to validate the immune cell infiltration landscape of the identified lncRNA signatures.
RESULTS
We identified a six-lncRNA pyroptosis-immune signature comprising MAPT.AS1, CTA.384, D8.34, RP11.561, I11.3, HID1.AS1, AC097713.3, and USP2.AS1. Patients in the HR group demonstrated inferior prognoses in the training, testing, and full datasets (P=3.622e-07, P=3.736e-03, and P=1.151e-08, respectively). Immune scores were significantly enhanced in the LR group, whereas tumor purity was elevated in the HR group. Fifty-eight immune scores showed significant differences between the groups (P<0.05). Immune function (APC coinhibition, CCR, and checkpoints) more significantly impaired in the HR group. Expression levels of 38 immune checkpoint genes, including KIR2DS4, KIR3DL2, CD40LG, KIR3DL1, and PDCD1, were significantly higher in the LR group. Conversely, the TDO2, PVR, and CD276 levels were elevated in the HR group. Single-cell sequencing data from GSE176078 showed sparse T cell, B cell, myeloid, and plasmablast clusters in the HR group, whereas the LR group displayed significant clustering of B cells, myeloids, and plasmablasts.
CONCLUSION
The six-lncRNA pyroptosis-immune signature effectively predicted BC prognosis and highlighted distinct immune cell infiltration patterns. This holds promise for evaluating immunotherapy responses and guiding therapeutic target identification in BC.
引言
本研究调查了与焦亡和免疫相关的长链非编码RNA(lncRNA),以确定有前景的乳腺癌(BC)治疗靶点,并构建lncRNA特征以确定BC患者的预后和免疫治疗反应。
方法
使用Pearson相关系数来识别与焦亡和免疫相关的差异表达lncRNA(分别为DE-pyrolncRNAs和DE-ImmlncRNAs)。将癌症基因组图谱数据集分配到训练和测试子集中。使用单变量Cox回归分析和最小绝对收缩和选择算子方法,基于训练子集得出预后lncRNA特征。采用逐步Cox回归对这些特征进行优化,并选择最佳的lncRNA特征。将训练子集的中位风险评分作为阈值,将患者分为高风险(HR)和低风险(LR)组。使用Wilcoxon检验揭示这些组之间免疫评分、细胞类型、功能和检查点基因的差异。来自GSE176078的单细胞测序数据用于验证所识别的lncRNA特征的免疫细胞浸润情况。
结果
我们确定了一个由MAPT.AS1、CTA.384、D8.34、RP11.561、I11.3、HID1.AS1、AC097713.3和USP2.AS1组成的六lncRNA焦亡-免疫特征。HR组患者在训练、测试和完整数据集中的预后较差(分别为P = 3.622e - 07、P = 3.736e - 03和P = 1.151e - 08)。LR组的免疫评分显著增强,而HR组的肿瘤纯度升高。两组之间有58个免疫评分显示出显著差异(P < 0.05)。HR组的免疫功能(抗原呈递细胞共抑制、CCR和检查点)受损更明显。包括KIR2DS4、KIR3DL2、CD40LG、KIR3DL1和PDCD1在内的38个免疫检查点基因的表达水平在LR组显著更高。相反,HR组的TDO2、PVR和CD276水平升高。来自GSE176078的单细胞测序数据显示,HR组中T细胞、B细胞、髓样细胞和成浆细胞簇稀疏,而LR组中B细胞、髓样细胞和成浆细胞有明显聚集。
结论
六lncRNA焦亡-免疫特征有效地预测了BC预后,并突出了不同的免疫细胞浸润模式。这为评估BC的免疫治疗反应和指导治疗靶点识别提供了希望。