Multi-omics reveals immune features in immune and non-immune cells, an IFN-γ/IFN-α-B2M positive feedback loop, and targeted metabolic therapy in multiple myeloma

多组学揭示了免疫细胞和非免疫细胞中的免疫特征、IFN-γ/IFN-α-B2M正反馈环路以及多发性骨髓瘤的靶向代谢疗法

阅读:1

Abstract

Multiple myeloma (MM) is highly heterogeneous, with relapse occurring in the majority of cases, and recent advancements in single-cell RNA sequencing (scRNA-seq), sc-metabolism profiling, and bulk RNA-seq have facilitated the identification of cell subpopulations and metabolic reprogramming at the single-cell level, uncovering novel molecular mechanisms. This study aims to establish a multi-omics atlas of MM, characterizing the cell subpopulations and signaling pathways that drive immune evasion and disease progression. Additionally, sc-metabolic profiling identifies reprogramming patterns and informs therapeutic screening. We integrated scRNA-seq and bulk RNA-seq data using R to analyze immune and non-immune cell features and pathways in MM. Metabolic reprogramming was assessed via sc-metabolic profiling, and drug candidates were screened through multi-omics integration, with efficacy evaluated in vitro using CCK-8 assays, flow cytometry, Western blotting, and CalcuSyn software. Novel MM subpopulations were identified, including myeloma-activated hematopoietic stem cells and ISG15+ B cells, which correlated with survival and were validated by multiplex immunofluorescence. IFN-γ is primarily secreted by effector memory CD8+T cells, and IFN-α is primarily secreted by non-classical monocytes, driving an IFN-γ/α-B2M feedback loop. Multi-omics identified four drug candidates, each demonstrating anti-tumor effects against myeloma cell lines.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。