应用Ridge方法改善肺腺癌免疫治疗反应和临床结果的免疫相关基因标记的发展。

IF 2.3 3区 生物学 Q2 MULTIDISCIPLINARY SCIENCES
PeerJ Pub Date : 2025-05-08 eCollection Date: 2025-01-01 DOI:10.7717/peerj.19121
Zhen Chen, Yongjun Zhang
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引用次数: 0

摘要

背景:肺腺癌(LUAD)是癌症死亡的主要原因。考虑到肿瘤浸润淋巴细胞在有效免疫治疗中的关键作用,本研究旨在筛选LUAD中与肿瘤浸润细胞相关的分子标志物,旨在提高LUAD治疗过程中的免疫治疗反应。方法:采用ConsensusClusterPlus方法对LUAD免疫分子亚型进行聚类。采用单样本基因集富集分析(ssGSEA)、肿瘤免疫功能障碍和排斥(TIDE)和免疫表型评分(IPS)评估各亚型的免疫细胞浸润和免疫治疗潜力。采用加权基因共表达网络分析(WGCNA)对免疫相关共表达模块进行分类。通过引入新的计算框架和10种机器学习算法(共101种组合)对免疫相关基因的测序数据进行综合分析,以确定预后基因,并使用stepCox和Ridge方法将其进一步组合以开发免疫预后特征(IMMPS)。标记基因的表达通过实时荧光定量PCR (qRT-PCR)验证。结果:来自癌症基因组图谱数据集(TCGA-LUAD)的样本分为两个亚型(免疫抑制亚组C1和免疫激活亚组C2);值得注意的是,C2亚组更有可能从免疫治疗中获益(p < 0.05)。基于7个免疫浸润细胞相关基因(SEMA7A、EFHD2、CHST11、SLC24A4、MAL、JCHAIN和SCARF1)开发的imps能够准确预测5个LUAD队列中LUAD的总生存期,平均c指数高于0.69。低imps值的LUAD患者免疫细胞浸润较高(p < 0.05)。此外,与154个已发表的基因特征相比,IMMPS表现出更好的预测性能,这表明IMMPS是评估LUAD患者总生存的独立预后危险因素。由于BTNL9是最相关的免疫检查点基因,体外实验表明,抑制BTNL9表达后,LUAD细胞株中7个关键基因(SEMA7A、EFHD2、CHST11、SLC24A4、MAL、JCHAIN、SCARF1)的表达与正常肺上皮细胞一致(p < 0.05)。结论:我们的结果有助于更好地了解LUAD的免疫学特征。imps可以作为改善LUAD患者临床结果的有希望的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of an immune-related gene signature applying Ridge method for improving immunotherapy responses and clinical outcomes in lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is a major cause of cancer mortality. Considering the critical role of tumor infiltrating lymphocytes in effective immunotherapy, this study was designed to screen molecular markers related to tumor infiltrating cells in LUAD, aiming to improve immunotherapy response during LUAD therapy.

Methods: The ConsensusClusterPlus method was used for clustering immune molecular subtypes of LUAD. Immune cell infiltration and immunotherapeutic potential in each subtype was evaluated employing single-sample gene set enrichment analysis (ssGSEA), Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore (IPS). Immune-related co-expression modules were classified by weighted gene co-expression network analysis (WGCNA) analysis. The sequencing data of immune-related genes were comprehensively analyzed by introducing a new computational framework and 10 machine learning algorithms (a total of 101 combinations) to determine the prognostic genes, which were further combined to develop an immune prognostic signature (IMMPS) using the stepCox and Ridge methods. The expression of the signature genes was validated by quantitative real-time PCR (qRT-PCR).

Results: Samples from The Cancer Genome Atlas dataset (TCGA-LUAD) were divided into two subtypes (immunosuppressive subgroup C1 and immune-activated subgroup C2); notably, the C2 subgroup was more likely to benefit from immunotherapy (p < 0.05). An IMMPS developed based on seven immune infiltrating cell-related genes (SEMA7A, EFHD2, CHST11, SLC24A4, MAL, JCHAIN, and SCARF1) could accurately predict the overall survival of LUAD in five LUAD cohorts, with an average C-index higher than 0.69. LUAD patients with a low IMMPS value had a higher immune cell infiltration (p < 0.05). In addition, the IMMPS exhibited better prediction performance in comparison to 154 published gene signatures, suggesting that the IMMPS was an independent prognostic risk factor for evaluating the overall survival of LUAD patients. Since BTNL9 was the most relevant immune checkpoint gene, in vitro experiment showed that the expression of the seven key genes (SEMA7A, EFHD2, CHST11, SLC24A4, MAL, JCHAIN, and SCARF1) in LUAD cell lines was consistent with that in normal lung epithelial cells after inhibiting BTNL9 expression (p < 0.05).

Conclusions: Our results contributed to a better understanding of immunological characteristics of LUAD. The IMMPS could serve as a promising tool for improving the clinical outcome of patients suffering from LUAD.

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来源期刊
PeerJ
PeerJ MULTIDISCIPLINARY SCIENCES-
CiteScore
4.70
自引率
3.70%
发文量
1665
审稿时长
10 weeks
期刊介绍: PeerJ is an open access peer-reviewed scientific journal covering research in the biological and medical sciences. At PeerJ, authors take out a lifetime publication plan (for as little as $99) which allows them to publish articles in the journal for free, forever. PeerJ has 5 Nobel Prize Winners on the Board; they have won several industry and media awards; and they are widely recognized as being one of the most interesting recent developments in academic publishing.
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