Uncovering Cellular Interactome Drivers of Immune Checkpoint Inhibitor Response in Advanced Melanoma Patients.

IF 3.5 4区医学 Q3 BIOPHYSICS

Cellular and molecular bioengineering Pub Date : 2025-09-08 eCollection Date: 2025-10-01 DOI:10.1007/s12195-025-00857-y

Shay Ladd, Anne M Talkington, Mary O'Sullivan, Robert W Barnes, Remziye E Wessel, Gabriel F Hanson, Sepideh Dolatshahi

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引用次数: 0

Abstract

Purpose: Despite the success of immune checkpoint inhibitors (ICIs) that target immunosuppressive interactions, treatment resistance remains a major clinical challenge. The tumor microenvironment is comprised of tumor, immune, and stromal cell types that communicate through secreted and cell surface proteins. This can be represented by a weighted, directed network where pairs of cell types communicate via multiple ligand-receptor interactions with varying strengths. Identifying interaction network motifs that are linked with outcome or evolve pre- to post-ICI presents a rational framework to identify combination therapeutic targets.

Methods: Interaction inference was performed on publicly available single-cell RNA-sequencing data from melanoma patients. The constructed patient-specific networks were input to multivariate statistical learning approaches to identify network motifs that predicted response pre-treatment and that shifted pre- to post-treatment. Relevance of interactions was validated by (1) differential expression of related pathways in single cell RNA sequencing (scRNA-seq) data, (2) survival associations in an independent bulk RNA-seq dataset, and (3) repeated analyses of scRNA-seq data in a second cohort.

Results: Immune-immune interactions with roles in T cell activation, chemotaxis, and adhesion were upregulated in patients who respond to therapy pre-treatment. Related pathways were perturbed in involved immune cells and expression of these genes was associated with improved survival. The interactome also distinguished pre- and post-treatment biopsies with high accuracy despite no significant differences in individual interactions. Analysis in the validation dataset with mixed responses pre-treatment recapitulated results from the discovery analyses.

Conclusion: Unbiased analysis of interaction networks and their evolution is a powerful framework to guide prognostic indicators and novel combination targets to improve patient outcomes.

Supplementary information: The online version contains supplementary material available at 10.1007/s12195-025-00857-y.

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揭示晚期黑色素瘤患者免疫检查点抑制剂反应的细胞相互作用组驱动因素。

目的：尽管针对免疫抑制相互作用的免疫检查点抑制剂（ICIs）取得了成功，但治疗耐药性仍然是一个主要的临床挑战。肿瘤微环境由肿瘤细胞、免疫细胞和基质细胞组成，它们通过分泌蛋白和细胞表面蛋白进行交流。这可以用一个加权的、定向的网络来表示，在这个网络中，细胞类型对通过不同强度的多种配体-受体相互作用进行交流。识别与结果相关或在ici前后进化的相互作用网络基序为确定联合治疗靶点提供了一个合理的框架。方法：对黑色素瘤患者公开获得的单细胞rna测序数据进行相互作用推断。构建的患者特异性网络被输入到多元统计学习方法中，以确定预测治疗前反应的网络基序，并将其从治疗前转移到治疗后。通过(1)单细胞RNA测序（scRNA-seq）数据中相关通路的差异表达，(2)独立的大量RNA-seq数据集中的生存关联，以及(3)在第二个队列中对scRNA-seq数据的重复分析，验证了相互作用的相关性。结果：在对治疗前治疗有反应的患者中，免疫相互作用与T细胞活化、趋化性和粘附的作用上调。相关通路在相关免疫细胞中受到干扰，这些基因的表达与生存率的提高有关。尽管个体相互作用没有显著差异，但相互作用组也以高精度区分治疗前和治疗后活检。在混合反应预处理验证数据集中的分析概括了发现分析的结果。结论：对相互作用网络及其演变进行无偏分析是指导预后指标和新的联合靶点以改善患者预后的有力框架。补充信息：在线版本包含补充资料，可在10.1007/s12195-025-00857-y获得。

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来源期刊

Cellular and molecular bioengineering 生物-生物物理

CiteScore

5.60

自引率

3.60%

发文量

审稿时长

>12 weeks

期刊介绍： The field of cellular and molecular bioengineering seeks to understand, so that we may ultimately control, the mechanical, chemical, and electrical processes of the cell. A key challenge in improving human health is to understand how cellular behavior arises from molecular-level interactions. CMBE, an official journal of the Biomedical Engineering Society, publishes original research and review papers in the following seven general areas: Molecular: DNA-protein/RNA-protein interactions, protein folding and function, protein-protein and receptor-ligand interactions, lipids, polysaccharides, molecular motors, and the biophysics of macromolecules that function as therapeutics or engineered matrices, for example. Cellular: Studies of how cells sense physicochemical events surrounding and within cells, and how cells transduce these events into biological responses. Specific cell processes of interest include cell growth, differentiation, migration, signal transduction, protein secretion and transport, gene expression and regulation, and cell-matrix interactions. Mechanobiology: The mechanical properties of cells and biomolecules, cellular/molecular force generation and adhesion, the response of cells to their mechanical microenvironment, and mechanotransduction in response to various physical forces such as fluid shear stress. Nanomedicine: The engineering of nanoparticles for advanced drug delivery and molecular imaging applications, with particular focus on the interaction of such particles with living cells. Also, the application of nanostructured materials to control the behavior of cells and biomolecules.