基于机器学习的免疫逃避特征预测胃腺癌的预后和免疫治疗效果。

IF 4.6 2区 生物学 Q2 CELL BIOLOGY
Frontiers in Cell and Developmental Biology Pub Date : 2025-09-25 eCollection Date: 2025-01-01 DOI:10.3389/fcell.2025.1656367
Wenwu Xue, Guanglin Zhang, Cui Yang, Tingting Tan, Weichun Zhang, Hongcai Chen
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引用次数: 0

摘要

背景:胃腺癌(STAD)仍然是世界范围内癌症相关死亡的主要原因。尽管免疫治疗取得了进展,但只有一小部分STAD患者受益于免疫检查点抑制剂,这主要是由于肿瘤固有的免疫逃避机制。因此,迫切需要强大的预测性生物标志物来指导预后评估和治疗决策。方法:采用包含10种算法的综合机器学习框架,利用101种模型组合构建免疫逃避特征(IES)。基于验证数据集的一致性指数(C-index)选择最优模型。通过生存分析、免疫浸润反褶积和多种免疫治疗反应指标来评估IES的预后和免疫学相关性。通过qPCR、免疫组织化学和体外功能分析进一步验证了关键基因。结果:通过LASSO方法开发的四基因IES在TCGA和多个外部队列中显示出强大的预后能力。IES评分高与生存率低、免疫细胞浸润减少(如CD8+ T细胞、树突状细胞)、M2巨噬细胞丰度升高以及免疫抑制肿瘤微环境相关。在三个独立的免疫治疗数据集中,低IES评分组的患者表现出良好的免疫治疗相关特征,包括更高的TMB,更低的TIDE评分和更高的应答率。此外,IES根据对化疗和靶向治疗的敏感性对患者进行分层。其中一个特征基因KLF16在STAD中上调,并在体外促进癌细胞增殖。结论:我们建立了一种新的IES,具有很强的预测STAD预后和免疫治疗反应的潜力。在临床实践中,这种IES可以作为风险分层和个性化治疗计划的有价值的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning based immune evasion signature for predicting the prognosis and immunotherapy benefit in stomach adenocarcinoma.

Background: Stomach adenocarcinoma (STAD) remains a major contributor to cancer-related mortality worldwide. Despite advances in immunotherapy, only a subset of STAD patients benefits from immune checkpoint inhibitors, largely due to tumor-intrinsic immune evasion mechanisms. Therefore, robust predictive biomarkers are urgently needed to guide prognosis assessment and therapeutic decision-making.

Methods: An integrative machine learning framework incorporating 10 algorithms was applied to construct an immune evasion signature (IES) using 101 model combinations. The optimal model was selected based on concordance index (C-index) across validation datasets. The prognostic and immunological relevance of the IES was assessed via survival analyses, immune infiltration deconvolution, and multiple immunotherapy response metrics. Key genes were further validated using qPCR, immunohistochemistry, and in vitro functional assays.

Results: A four-gene IES developed via the LASSO method demonstrated robust prognostic power across TCGA and multiple external cohorts. High IES score were associated with poor survival, reduced immune cell infiltration (e.g., CD8+ T cells, dendritic cells), elevated M2 macrophage abundance, and an immunosuppressive tumor microenvironment. Patients in the low IES score group exhibited favorable immunotherapy-associated features, including higher TMB, lower TIDE scores, and increased response rates in three independent immunotherapy datasets. Additionally, the IES stratified patients by sensitivity to chemotherapy and targeted therapies. KLF16, one of the signature genes, was upregulated in STAD and promoted cancer cell proliferation in vitro.

Conclusion: We established a novel IES with strong potential to predict prognosis and immunotherapy response in STAD. This IES may serve as a valuable tool for risk stratification and individualized treatment planning in clinical practice.

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来源期刊
Frontiers in Cell and Developmental Biology
Frontiers in Cell and Developmental Biology Biochemistry, Genetics and Molecular Biology-Cell Biology
CiteScore
9.70
自引率
3.60%
发文量
2531
审稿时长
12 weeks
期刊介绍: Frontiers in Cell and Developmental Biology is a broad-scope, interdisciplinary open-access journal, focusing on the fundamental processes of life, led by Prof Amanda Fisher and supported by a geographically diverse, high-quality editorial board. The journal welcomes submissions on a wide spectrum of cell and developmental biology, covering intracellular and extracellular dynamics, with sections focusing on signaling, adhesion, migration, cell death and survival and membrane trafficking. Additionally, the journal offers sections dedicated to the cutting edge of fundamental and translational research in molecular medicine and stem cell biology. With a collaborative, rigorous and transparent peer-review, the journal produces the highest scientific quality in both fundamental and applied research, and advanced article level metrics measure the real-time impact and influence of each publication.
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