Department of Thoracic Surgery, Shanxi Province Cancer Hospital/Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/Cancer Hospital Affiliated to Shanxi Medical University, Taiyuan, China.
The Second Clinical Medical School, Shanxi Medical University, Taiyuan, China.
J Cell Mol Med. 2024 May;28(10):e18378. doi: 10.1111/jcmm.18378.
The efficacy of radiotherapy, a cornerstone in the treatment of lung adenocarcinoma (LUAD), is profoundly undermined by radiotolerance. This resistance not only poses a significant clinical challenge but also compromises patient survival rates. Therefore, it is important to explore this mechanism for the treatment of LUAD. Multiple public databases were used for single-cell RNA sequencing (scRNA-seq) data. We filtered, normalized and downscaled scRNA-seq data based on the Seurat package to obtain different cell subpopulations. Subsequently, the ssGSEA algorithm was used to assess the enrichment scores of the different cell subpopulations, and thus screen the cell subpopulations that are most relevant to radiotherapy tolerance based on the Pearson method. Finally, pseudotime analysis was performed, and a preliminary exploration of gene mutations in different cell subpopulations was performed. We identified HIST1H1D+ A549 and PIF1+ A549 as the cell subpopulations related to radiotolerance. The expression levels of cell cycle-related genes and pathway enrichment scores of these two cell subpopulations increased gradually with the extension of radiation treatment time. Finally, we found that the proportion of TP53 mutations in patients who had received radiotherapy was significantly higher than that in patients who had not received radiotherapy. We identified two cellular subpopulations associated with radiotherapy tolerance, which may shed light on the molecular mechanisms of radiotherapy tolerance in LUAD and provide new clinical perspectives.
放疗是治疗肺腺癌 (LUAD) 的基石，但放疗耐受性却严重削弱了其疗效。这种抵抗不仅带来了重大的临床挑战，还降低了患者的生存率。因此，探索这种 LUAD 治疗的机制非常重要。我们使用了多个公共数据库进行单细胞 RNA 测序 (scRNA-seq) 数据。我们根据 Seurat 包过滤、归一化和降尺度 scRNA-seq 数据，以获得不同的细胞亚群。然后，使用 ssGSEA 算法评估不同细胞亚群的富集分数，并根据 Pearson 方法筛选与放疗耐受性最相关的细胞亚群。最后，进行了伪时间分析，并对不同细胞亚群的基因突变进行了初步探索。我们确定 HIST1H1D+ A549 和 PIF1+ A549 是与放疗耐受性相关的细胞亚群。这两个细胞亚群的细胞周期相关基因表达水平和通路富集分数随着辐射治疗时间的延长而逐渐增加。最后，我们发现接受过放疗的患者中 TP53 基因突变的比例明显高于未接受放疗的患者。我们确定了两个与放疗耐受性相关的细胞亚群，这可能为 LUAD 放疗耐受性的分子机制提供新的见解，并为临床提供新的视角。
