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基于 BTK 和 DPEP2 的免疫标志物可识别肺腺癌的热肿瘤和冷肿瘤以及临床治疗结果。

An immune indicator based on BTK and DPEP2 identifies hot and cold tumors and clinical treatment outcomes in lung adenocarcinoma.

机构信息

School of Medicine, Anhui University of Science and Technology, Huainan, 232001, People's Republic of China.

Anhui Province Engineering Laboratory of Occupational Health and Safety, Anhui University of Science and Technology, Huainan, 232001, People's Republic of China.

出版信息

Sci Rep. 2023 Mar 29;13(1):5153. doi: 10.1038/s41598-023-32276-2.


DOI:10.1038/s41598-023-32276-2
PMID:36991102
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10060209/
Abstract

In lung adenocarcinoma (LUAD), immune heterogeneity of hot and cold tumors has been recognized as one of the major factors affecting immunotherapy and other common treatments. However, there is still a lack of biomarkers that can effectively identify the immunophenotype of cold and hot tumors. First, the immune signatures were obtained based on literature mining, including macrophage/monocyte, IFN-γ response, TGF-β response, IL12 response, lymphocyte activation, and ECM/Dve/immune response. Subsequently, LUAD patients were further clustered into different immune phenotypes based on these immune signatures. Next, the key genes related to the immune phenotypes were screened by WGCNA analysis, univariate analysis, and lasso-cox analysis, and the risk signature was established via the key genes. In additional, we compared the clinicopathological characteristics, drug sensitivity, the abundance of immune infiltration, and the efficacy of immunotherapy and commonly used therapies between patients in the high- and low-risk groups in LUAD. LUAD patients were divided into immune hot phenotype and immune cold phenotype groups. The clinical presentation showed that patients with the immune hot phenotype had higher immunoactivity (including higher MHC, CYT, immune, stromal, ESTIMATE scores, higher abundance of immune cell infiltration, higher abundance of TIL, and enrichment of immune-enriched subtypes) and better survival outcomes than those with the immune cold phenotype. Subsequently, WGCNA analysis, univariate analysis, and lasso-cox analysis identified the genes highly associated with the immune phenotype: BTK and DPEP2. The risk signature, consisting of BTK and DPEP2, is highly correlated with the immune phenotype. High-risk scores were enriched in patients with immune cold phenotype and low-risk scores were enriched in patients with immune hot phenotype. Compared to the high-risk group, the low-risk group had better clinical performance, higher drug sensitivity, and a higher degree of immunoactivity, as well as better efficacy in receiving immunotherapy and common adjuvant therapy. This study developed an immune indicator consisting of BTK and DPEP2 based on the heterogeneity of hot and cold Immunophenotypes of the tumor microenvironment. This indicator has good efficacy in predicting prognosis and assessing the efficacy of immunotherapy, chemotherapy, and radiotherapy. It has the potential to facilitate personalized and precise treatment of LUAD in the future.

摘要

在肺腺癌 (LUAD) 中,热肿瘤和冷肿瘤的免疫异质性已被认为是影响免疫疗法和其他常见治疗的主要因素之一。然而,仍然缺乏能够有效识别冷肿瘤和热肿瘤免疫表型的生物标志物。首先,基于文献挖掘获得了免疫特征,包括巨噬细胞/单核细胞、IFN-γ 反应、TGF-β 反应、IL12 反应、淋巴细胞激活和 ECM/Dve/免疫反应。随后,根据这些免疫特征将 LUAD 患者进一步聚类为不同的免疫表型。接下来,通过 WGCNA 分析、单变量分析和lasso-cox 分析筛选与免疫表型相关的关键基因,并通过关键基因建立风险特征。此外,我们比较了 LUAD 中高风险和低风险组患者的临床病理特征、药物敏感性、免疫浸润丰度以及免疫治疗和常用治疗的疗效。将 LUAD 患者分为免疫热表型和免疫冷表型组。临床表现显示,免疫热表型患者的免疫活性更高(包括更高的 MHC、CYT、免疫、基质、ESTIMATE 评分、更高的免疫细胞浸润丰度、更高的 TIL 丰度以及免疫富集亚型的富集),生存结局更好。随后,WGCNA 分析、单变量分析和 lasso-cox 分析确定了与免疫表型高度相关的基因:BTK 和 DPEP2。由 BTK 和 DPEP2 组成的风险特征与免疫表型高度相关。高风险评分在免疫冷表型患者中富集,低风险评分在免疫热表型患者中富集。与高风险组相比,低风险组的临床表现更好,药物敏感性更高,免疫活性更高,接受免疫治疗和常见辅助治疗的疗效也更好。本研究基于肿瘤微环境中热肿瘤和冷肿瘤免疫表型的异质性,开发了由 BTK 和 DPEP2 组成的免疫指标。该指标在预测预后和评估免疫治疗、化疗和放疗疗效方面具有良好的效果。它有可能促进未来 LUAD 的个性化和精准治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/473bcb8d2f64/41598_2023_32276_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/7135c3c8e3e0/41598_2023_32276_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/f2033f2650d0/41598_2023_32276_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/90b23481bd31/41598_2023_32276_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/1ee89e8fe877/41598_2023_32276_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/2dbd65a11233/41598_2023_32276_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/b0a5e9ed0656/41598_2023_32276_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/43101a5f11de/41598_2023_32276_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/473bcb8d2f64/41598_2023_32276_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/7135c3c8e3e0/41598_2023_32276_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/f2033f2650d0/41598_2023_32276_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/90b23481bd31/41598_2023_32276_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/1ee89e8fe877/41598_2023_32276_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/2dbd65a11233/41598_2023_32276_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/b0a5e9ed0656/41598_2023_32276_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/43101a5f11de/41598_2023_32276_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e4/10060209/473bcb8d2f64/41598_2023_32276_Fig8_HTML.jpg

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本文引用的文献

[1]
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