Spatial proteomic profiling of tumor and stromal compartments in non-small-cell lung cancer identifies signatures associated with overall survival

IF 4.6 2区医学 Q2 IMMUNOLOGY

Clinical & Translational Immunology Pub Date : 2024-07-18 DOI:10.1002/cti2.1522

Vahid Yaghoubi Naei, James Monkman, Habib Sadeghirad, Ahmed Mehdi, Tony Blick, William Mullally, Ken O'Byrne, Majid Ebrahimi Warkiani, Arutha Kulasinghe

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Abstract

Objectives

Non-small-cell lung carcinoma (NSCLC) is the most prevalent and lethal form of lung cancer. The need for biomarker-informed stratification of targeted therapies has underpinned the need to uncover the underlying properties of the tumor microenvironment (TME) through high-plex quantitative assays.

Methods

In this study, we profiled resected NSCLC tissues from 102 patients by targeted spatial proteomics of 78 proteins across tumor, immune activation, immune cell typing, immune-oncology, drug targets, cell death and PI3K/AKT modules to identify the tumor and stromal signatures associated with overall survival (OS).

Results

Survival analysis revealed that stromal CD56 (HR = 0.384, P = 0.06) and tumoral TIM3 (HR = 0.703, P = 0.05) were associated with better survival in univariate Cox models. In contrast, after adjusting for stage, BCLXL (HR = 2.093, P = 0.02) and cleaved caspase 9 (HR = 1.575, P = 0.1) negatively influenced survival. Delta testing indicated the protective effect of TIM-3 (HR = 0.614, P = 0.04) on OS. In multivariate analysis, CD56 (HR = 0.172, P = 0.001) was associated with better survival in the stroma, while B7.H3 (HR = 1.72, P = 0.008) was linked to poorer survival in the tumor.

Conclusions

Deciphering the TME using high-plex spatially resolved methods is giving us new insights into compartmentalised tumor and stromal protein signatures associated with clinical endpoints in NSCLC.

Abstract Image

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非小细胞肺癌肿瘤和基质区的空间蛋白质组学分析确定了与总生存率相关的特征。

研究目的非小细胞肺癌（NSCLC）是发病率最高、致死率最高的肺癌。由于需要根据生物标志物对靶向疗法进行分层，因此需要通过高倍定量检测来揭示肿瘤微环境（TME）的基本特性：在这项研究中，我们通过对肿瘤、免疫激活、免疫细胞分型、免疫肿瘤学、药物靶点、细胞死亡和PI3K/AKT模块中的78种蛋白质进行靶向空间蛋白质组学研究，对102例患者切除的NSCLC组织进行了分析，以确定与总生存期（OS）相关的肿瘤和基质特征：结果：生存分析表明，在单变量Cox模型中，基质CD56（HR=0.384，P=0.06）和肿瘤TIM3（HR=0.703，P=0.05）与较好的生存率相关。相反，在调整分期后，BCLXL（HR = 2.093，P = 0.02）和裂解的caspase 9（HR = 1.575，P = 0.1）对生存率有负面影响。德尔塔测试表明，TIM-3（HR = 0.614，P = 0.04）对 OS 有保护作用。在多变量分析中，CD56（HR = 0.172，P = 0.001）与基质中较高的生存率相关，而B7.H3（HR = 1.72，P = 0.008）与肿瘤中较低的生存率相关：结论：利用高倍空间分辨方法对TME进行解密，让我们对与NSCLC临床终点相关的分区肿瘤和基质蛋白特征有了新的认识。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinical & Translational Immunology Medicine-Immunology and Allergy

CiteScore

12.00

自引率

1.70%

发文量

审稿时长

13 weeks

期刊介绍： Clinical & Translational Immunology is an open access, fully peer-reviewed journal devoted to publishing cutting-edge advances in biomedical research for scientists and physicians. The Journal covers fields including cancer biology, cardiovascular research, gene therapy, immunology, vaccine development and disease pathogenesis and therapy at the earliest phases of investigation.