Suppr超能文献

对具有完整注释临床随访的早期肺腺癌进行全外显子组测序和免疫分析。

Whole-exome sequencing and immune profiling of early-stage lung adenocarcinoma with fully annotated clinical follow-up.

作者信息

Kadara H, Choi M, Zhang J, Parra E R, Rodriguez-Canales J, Gaffney S G, Zhao Z, Behrens C, Fujimoto J, Chow C, Yoo Y, Kalhor N, Moran C, Rimm D, Swisher S, Gibbons D L, Heymach J, Kaftan E, Townsend J P, Lynch T J, Schlessinger J, Lee J, Lifton R P, Wistuba I I, Herbst R S

机构信息

Department of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon.

Department of Genetics, Howard Hughes Medical Institute, Maryland, USA.

出版信息

Ann Oncol. 2017 Jan 1;28(1):75-82. doi: 10.1093/annonc/mdw436.

Abstract

BACKGROUND

Lung adenocarcinomas (LUADs) lead to the majority of deaths attributable to lung cancer. We performed whole-exome sequencing (WES) and immune profiling analyses of a unique set of clinically annotated early-stage LUADs to better understand the pathogenesis of this disease and identify clinically relevant molecular markers.

METHODS

We performed WES of 108 paired stage I-III LUADs and normal lung tissues using the Illumina HiSeq 2000 platform. Ten immune markers (PD-L1, PD-1, CD3, CD4, CD8, CD45ro, CD57, CD68, FOXP3 and Granzyme B) were profiled by imaging-based immunohistochemistry (IHC) in a subset of LUADs (n = 92). Associations among mutations, immune markers and clinicopathological variables were analyzed using ANOVA and Fisher's exact test. Cox proportional hazards regression models were used for multivariate analysis of clinical outcome.

RESULTS

LUADs in this cohort exhibited an average of 243 coding mutations. We identified 28 genes with significant enrichment for mutation. SETD2-mutated LUADs exhibited relatively poor recurrence- free survival (RFS) and mutations in STK11 and ATM were associated with poor RFS among KRAS-mutant tumors. EGFR, KEAP1 and PIK3CA mutations were predictive of poor response to adjuvant therapy. Immune marker analysis revealed that LUADs in smokers and with relatively high mutation burdens exhibited increased levels of immune markers. Analysis of immunophenotypes revealed that LUADs with STK11 mutations exhibited relatively low levels of infiltrating CD4+/CD8+ T-cells indicative of a muted immune response. Tumoral PD-L1 was significantly elevated in TP53 mutant LUADs whereas PIK3CA mutant LUADs exhibited markedly down-regulated PD-L1 expression. LUADs with TP53 or KEAP1 mutations displayed relatively increased CD57 and Granzyme B levels indicative of augmented natural killer (NK) cell infiltration.

CONCLUSION(S): Our study highlights molecular and immune phenotypes that warrant further analysis for their roles in clinical outcomes and personalized immune-based therapy of LUAD.

摘要

背景

肺腺癌(LUAD)导致了肺癌所致的大部分死亡。我们对一组独特的经临床注释的早期LUAD进行了全外显子组测序(WES)和免疫分析,以更好地了解该疾病的发病机制并识别临床相关分子标志物。

方法

我们使用Illumina HiSeq 2000平台对108对I-III期LUAD和正常肺组织进行了WES。通过基于成像的免疫组织化学(IHC)对一部分LUAD(n = 92)中的十种免疫标志物(PD-L1、PD-1、CD3、CD4、CD8、CD45ro、CD57、CD68、FOXP3和颗粒酶B)进行分析。使用方差分析和Fisher精确检验分析突变、免疫标志物和临床病理变量之间的关联。Cox比例风险回归模型用于临床结局的多变量分析。

结果

该队列中的LUAD平均表现出243个编码突变。我们鉴定出28个突变显著富集的基因。SETD2突变的LUAD表现出相对较差的无复发生存期(RFS),而STK11和ATM的突变与KRAS突变肿瘤中的不良RFS相关。EGFR、KEAP1和PIK3CA突变可预测辅助治疗反应不佳。免疫标志物分析显示,吸烟者的LUAD和具有相对高突变负荷的LUAD表现出免疫标志物水平升高。免疫表型分析显示,具有STK11突变的LUAD表现出相对较低水平的浸润性CD4+/CD8+ T细胞,表明免疫反应减弱。肿瘤性PD-L1在TP53突变的LUAD中显著升高,而PIK3CA突变的LUAD表现出明显下调的PD-L1表达。具有TP53或KEAP1突变的LUAD显示出相对增加的CD57和颗粒酶B水平,表明自然杀伤(NK)细胞浸润增加。

结论

我们的研究突出了分子和免疫表型,这些表型在LUAD的临床结局和基于个性化免疫的治疗中的作用值得进一步分析。

相似文献

3
Female Gender Predicts Augmented Immune Infiltration in Lung Adenocarcinoma.
Clin Lung Cancer. 2021 May;22(3):e415-e424. doi: 10.1016/j.cllc.2020.06.003. Epub 2020 Jun 14.
4
Development of Kras mutant lung adenocarcinoma in mice with knockout of the airway lineage-specific gene Gprc5a.
Int J Cancer. 2017 Oct 15;141(8):1589-1599. doi: 10.1002/ijc.30851. Epub 2017 Jul 17.
6
CD73 expression defines immune, molecular, and clinicopathological subgroups of lung adenocarcinoma.
Cancer Immunol Immunother. 2021 Jul;70(7):1965-1976. doi: 10.1007/s00262-020-02820-4. Epub 2021 Jan 8.
7
[Immune Microenvironment Comparation Study between EGFR Mutant and EGFR Wild Type Lung Adenocarcinoma Patients Based on TCGA Database].
Zhongguo Fei Ai Za Zhi. 2021 Apr 20;24(4):236-244. doi: 10.3779/j.issn.1009-3419.2021.102.15.
8
Genomic Profiling of Lung Adenocarcinoma in Never-Smokers.
J Clin Oncol. 2021 Nov 20;39(33):3747-3758. doi: 10.1200/JCO.21.01691. Epub 2021 Sep 30.
10
, and Mutations Predict Tumor Immune Profile and the Response to Anti-PD-1 in Lung Adenocarcinoma.
Clin Cancer Res. 2018 Nov 15;24(22):5710-5723. doi: 10.1158/1078-0432.CCR-18-0163. Epub 2018 May 15.

引用本文的文献

5
Precision immune regulation in KRAS-mutated cancers: the final piece of the puzzle?
J Exp Clin Cancer Res. 2025 Jul 3;44(1):189. doi: 10.1186/s13046-025-03444-1.
10
AL365181.3 as a novel prognostic biomarker for lung adenocarcinoma.
Sci Rep. 2025 Feb 18;15(1):5853. doi: 10.1038/s41598-025-90008-0.

本文引用的文献

1
Genomic alterations in lung adenocarcinoma.
Lancet Oncol. 2015 Jul;16(7):e342-51. doi: 10.1016/S1470-2045(15)00077-7.
4
Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer.
Science. 2015 Apr 3;348(6230):124-8. doi: 10.1126/science.aaa1348. Epub 2015 Mar 12.
5
Whole genomes redefine the mutational landscape of pancreatic cancer.
Nature. 2015 Feb 26;518(7540):495-501. doi: 10.1038/nature14169.
6
Objective measurement and clinical significance of TILs in non-small cell lung cancer.
J Natl Cancer Inst. 2015 Feb 3;107(3). doi: 10.1093/jnci/dju435. Print 2015 Mar.
8
Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients.
Nature. 2014 Nov 27;515(7528):563-7. doi: 10.1038/nature14011.
9
The PD-1 pathway as a therapeutic target to overcome immune escape mechanisms in cancer.
Expert Opin Ther Targets. 2014 Dec;18(12):1407-20. doi: 10.1517/14728222.2014.955794. Epub 2014 Oct 21.
10
Comprehensive molecular profiling of lung adenocarcinoma.
Nature. 2014 Jul 31;511(7511):543-50. doi: 10.1038/nature13385. Epub 2014 Jul 9.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验