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解析与细胞死亡相关的特征,以预测肺鳞状细胞癌的预后和免疫治疗反应。

Deciphering a cell death-associated signature for predicting prognosis and response to immunotherapy in lung squamous cell carcinoma.

机构信息

Department of Thoracic Surgery, Peking University Shenzhen Hospital, Shenzhen, 518036, China.

Department of Pulmonary and Critical Care Medicine, Respiratory Medicine Center of Fujian Province, Second Affiliated Hospital of Fujian Medical University, Guangzhou, 362000, China.

出版信息

Respir Res. 2023 Jul 6;24(1):176. doi: 10.1186/s12931-023-02402-9.

DOI:10.1186/s12931-023-02402-9
PMID:37415224
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10324233/
Abstract

BACKGROUND

Lung squamous cell carcinoma (LUSC) is a subtype of non-small cell carcinoma, accounting for about 30% of all lung cancers. Yet, the evaluation of prognostic outcome and therapy response of patients with LUSC remains to be resolved. This study aimed to explore the prognostic value of cell death pathways and develop a cell death-associated signature for predicting prognosis and guiding treatment in LUSC.

METHODS

Transcriptome profiles and corresponding clinical information of LUSC patients were gathered from The Cancer Genome Atlas (TCGA-LUSC, n = 493) and Gene Expression Omnibus database (GSE74777, n = 107). The cell death-related genes including autophagy (n = 348), apoptosis (n = 163), and necrosis (n = 166) were retrieved from the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology databases. In the training cohort (TCGA-LUSC), LASSO Cox regression was used to construct four prognostic signatures of respective autophagy, apoptosis, and necrosis pathway and genes of three pathways. After comparing the four signatures, the cell death index (CDI), the signature of combined genes, was further validated in the GSE74777 dataset. We also investigated the clinical significance of the CDI signature in predicting the immunotherapeutic response of LUSC patients.

RESULTS

The CDI signature was significantly associated with the overall survival of LUSC patients in the training cohort (HR, 2.13; 95% CI, 1.62‒2.82; P < 0.001) and in the validation cohort (HR, 1.94; 95% CI, 1.01‒3.72; P = 0.04). The differentially expressed genes between the high- and low-risk groups contained cell death-associated cytokines and were enriched in immune-associated pathways. We also found a higher infiltration of naive CD4 T cells, monocytes, activated dendritic cells, neutrophils, and lower infiltration of plasma cells and resting memory CD4 T cells in the high-risk group. Tumor stemness indices, mRNAsi and mDNAsi, were both negatively correlated with the risk score of the CDI. Moreover, LUSC patients in the low-risk group are more likely to respond to immunotherapy than those in the high-risk group (P = 0.002).

CONCLUSIONS

This study revealed a reliable cell death-associated signature (CDI) that closely correlated with prognosis and the tumor microenvironment in LUSC, which may assist in predicting the prognosis and response to immunotherapy for patients with LUSC.

摘要

背景

肺鳞状细胞癌(LUSC)是非小细胞癌的一种亚型,约占所有肺癌的 30%。然而,评估 LUSC 患者的预后结果和治疗反应仍然是一个待解决的问题。本研究旨在探讨细胞死亡途径的预后价值,并为 LUSC 患者的预后预测和治疗指导开发一种与细胞死亡相关的特征。

方法

从癌症基因组图谱(TCGA-LUSC,n=493)和基因表达综合数据库(GSE74777,n=107)中收集了 LUSC 患者的转录组谱和相应的临床信息。从京都基因与基因组百科全书和基因本体论数据库中检索了与自噬(n=348)、凋亡(n=163)和坏死(n=166)相关的细胞死亡相关基因。在训练队列(TCGA-LUSC)中,使用 LASSO Cox 回归构建了各自的自噬、凋亡和坏死途径以及三个途径的基因的四个预后特征。在比较了这四个特征之后,进一步在 GSE74777 数据集验证了细胞死亡指数(CDI),即联合基因特征。我们还研究了 CDI 特征在预测 LUSC 患者免疫治疗反应中的临床意义。

结果

CDI 特征与训练队列中 LUSC 患者的总生存期显著相关(HR,2.13;95%CI,1.62-2.82;P<0.001),在验证队列中也显著相关(HR,1.94;95%CI,1.01-3.72;P=0.04)。高低风险组之间的差异表达基因包含与细胞死亡相关的细胞因子,并富集在免疫相关途径中。我们还发现,高风险组中幼稚 CD4 T 细胞、单核细胞、活化树突状细胞、中性粒细胞的浸润较高,浆细胞和静息记忆 CD4 T 细胞的浸润较低。肿瘤干细胞指数 mRNAsi 和 mDNAsi 均与 CDI 的风险评分呈负相关。此外,低风险组的 LUSC 患者比高风险组更有可能对免疫治疗有反应(P=0.002)。

结论

本研究揭示了一个可靠的与细胞死亡相关的特征(CDI),它与 LUSC 的预后和肿瘤微环境密切相关,这可能有助于预测 LUSC 患者的预后和对免疫治疗的反应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c69/10324233/eae362d786bd/12931_2023_2402_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c69/10324233/0b40cbcb75b6/12931_2023_2402_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c69/10324233/2386704e3a98/12931_2023_2402_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c69/10324233/eae362d786bd/12931_2023_2402_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c69/10324233/0b40cbcb75b6/12931_2023_2402_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c69/10324233/2dff011edd1f/12931_2023_2402_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c69/10324233/bcede6ae1f7d/12931_2023_2402_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c69/10324233/27703cdfc892/12931_2023_2402_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c69/10324233/2386704e3a98/12931_2023_2402_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c69/10324233/eae362d786bd/12931_2023_2402_Fig6_HTML.jpg

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