通过综合转录组分析鉴定与干细胞相关的基因标志物,以预测肺腺癌的预后和免疫治疗。

Identification of Stem Cell-related Gene Markers by Comprehensive Transcriptome Analysis to Predict the Prognosis and Immunotherapy of Lung Adenocarcinoma.

机构信息

Department of Cardiothoracic Surgery, Dongguan Tungwah Hospital, Dongguan, 523001, China.

出版信息

Curr Stem Cell Res Ther. 2024;19(5):743-754. doi: 10.2174/1574888X18666230821104844.

Abstract

BACKGROUND

Cancer stem cells (CSCs) contribute to metastasis and drug resistance to immunotherapy in lung adenocarcinoma (LUAD), so the stemness evaluation of cancer cells is of great significance.

METHOD

The single-cell RNA sequencing (scRNA-seq) data of the GSE149655 dataset were collected and analyzed. Malignant cells were distinguished by CopyKAT. CytoTRACE score of marker genes in malignant cells was counted by CytoTRACE to construct the stemness score formula. Sample stemness score in TCGA was determined by the formula and divided into high-, medium- and low-stemness score groups. LASSO and COX regression analyses were carried out to screen the key genes related to the prognosis of LUAD from the differentially expressed genes (DEGs) in high- and low-stemness score groups and a risk score model was constructed.

RESULT

Seven types of cells were identified from a total of 4 samples, and 193 marker genes of 3455 malignant cells were identified. There were 1098 DEGs between low- and high-stemness score groups of TCGA, of which CPS1, CENPK, GJB3, and TPSB2 constituted gene signatures. The 4-gene signature could independently evaluate LUAD survival in the training and validation sets and showed an acceptable area under the receiver operator characteristic (ROC) curves (AUCs).

CONCLUSION

This study provides insights into the cellular heterogeneity of LUAD and develops a new cancer stemness evaluation indicator and a 4-gene signature as a potential tool for evaluating the response of LUAD to immune checkpoint blockade (ICB) therapy or antineoplastic therapy.

摘要

背景

癌症干细胞(CSC)有助于肺腺癌(LUAD)的转移和对免疫治疗的耐药性,因此癌细胞的干性评估具有重要意义。

方法

收集并分析 GSE149655 数据集的单细胞 RNA 测序(scRNA-seq)数据。通过 CopyKAT 区分恶性细胞。通过 CytoTRACE 计算恶性细胞中标记基因的 CytoTRACE 评分,构建干性评分公式。通过公式确定 TCGA 中样本的干性评分,并将其分为高、中、低干性评分组。对高、低干性评分组中差异表达基因(DEGs)进行 LASSO 和 COX 回归分析,筛选与 LUAD 预后相关的关键基因,并构建风险评分模型。

结果

从总共 4 个样本中鉴定出 7 种细胞,鉴定出 3455 个恶性细胞中的 193 个标记基因。TCGA 中低和高干性评分组之间有 1098 个 DEGs,其中 CPS1、CENPK、GJB3 和 TPSB2 构成了基因特征。4 基因特征可独立评估训练集和验证集中 LUAD 的生存情况,且接受者操作特征(ROC)曲线下面积(AUC)具有可接受性。

结论

本研究深入了解了 LUAD 的细胞异质性,并开发了一种新的癌症干性评估指标和 4 基因特征,作为评估 LUAD 对免疫检查点阻断(ICB)治疗或抗肿瘤治疗反应的潜在工具。

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