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单细胞分辨率解析髓系细胞状态特征及其对癌症结局的影响。

Single-cell resolution characterization of myeloid-derived cell states with implication in cancer outcome.

机构信息

Laboratory of Bioinformatics and Computational Biology, Division of Experimental and Translational Research, Brazilian National Cancer Institute (INCA), Rio de Janeiro, RJ, Brazil.

Department of Microbiology, Immunology, and Parasitology, Federal University of Santa Catarina, Florianópolis, SC, Brazil.

出版信息

Nat Commun. 2024 Jul 7;15(1):5694. doi: 10.1038/s41467-024-49916-4.

Abstract

Tumor-associated myeloid-derived cells (MDCs) significantly impact cancer prognosis and treatment responses due to their remarkable plasticity and tumorigenic behaviors. Here, we integrate single-cell RNA-sequencing data from different cancer types, identifying 29 MDC subpopulations within the tumor microenvironment. Our analysis reveals abnormally expanded MDC subpopulations across various tumors and distinguishes cell states that have often been grouped together, such as TREM2+ and FOLR2+ subpopulations. Using deconvolution approaches, we identify five subpopulations as independent prognostic markers, including states co-expressing TREM2 and PD-1, and FOLR2 and PDL-2. Additionally, TREM2 alone does not reliably predict cancer prognosis, as other TREM2+ macrophages show varied associations with prognosis depending on local cues. Validation in independent cohorts confirms that FOLR2-expressing macrophages correlate with poor clinical outcomes in ovarian and triple-negative breast cancers. This comprehensive MDC atlas offers valuable insights and a foundation for futher analyses, advancing strategies for treating solid cancers.

摘要

肿瘤相关髓系来源细胞(MDC)由于其显著的可塑性和致瘤行为,显著影响癌症的预后和治疗反应。在这里,我们整合了来自不同癌症类型的单细胞 RNA 测序数据,在肿瘤微环境中鉴定出 29 个 MDC 亚群。我们的分析揭示了各种肿瘤中异常扩张的 MDC 亚群,并区分了通常被归为一类的细胞状态,如 TREM2+和 FOLR2+亚群。使用去卷积方法,我们确定了五个亚群作为独立的预后标志物,包括共表达 TREM2 和 PD-1 的状态,以及共表达 FOLR2 和 PDL-2 的状态。此外,TREM2 本身并不能可靠地预测癌症的预后,因为其他 TREM2+巨噬细胞根据局部线索与预后的相关性不同。在独立队列中的验证证实,FOLR2 表达的巨噬细胞与卵巢癌和三阴性乳腺癌的不良临床结局相关。这个全面的 MDC 图谱提供了有价值的见解和进一步分析的基础,为治疗实体瘤的策略提供了新的思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b406/11228020/b463d27531b4/41467_2024_49916_Fig1_HTML.jpg

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