Fibrocytes in tumor microenvironment: Identification of their fraction and novel therapeutic strategy.

IF 5.7 2区 医学 Q1 Medicine Cancer Science Pub Date : 2024-11-04 DOI:10.1111/cas.16385
Atsushi Mitsuhashi, Yasuhiko Nishioka
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Abstract

Fibrocytes were identified as bone marrow-derived myeloid cells that also have fibroblast-like phenotypes, such as ECM production and differentiation to myofibroblasts. Although fibrocytes are known to contribute to various types of tissue fibrosis, their functions in the tumor microenvironment are unclear. We focused on fibrocytes as pivotal regulators of tumor progression. Our previous studies have indicated that fibrocytes induce angiogenesis and cancer stem cell-like phenotypes by secreting various growth factors. In contrast, immune checkpoint inhibitor (ICI)-treated fibrocytes demonstrated antigen-presenting capacity and enhanced antitumor T cell proliferation. Taken together, these findings indicate that fibrocytes have multiple effects on tumor progression. However, the detailed phenotypes of fibrocytes have not been fully elucidated because the isolation of distinct fibrocyte clusters has not been achieved without culturing in ECM-coated conditions or intracellular staining of ECM. The development of single-cell analyses partially resolves these problems. Single-cell RNA sequences in CD45+ immune cells from tumor tissue identified ECM-expressing myeloid-like cells as distinct fibrocyte clusters. In addition, these findings enabled the isolation of tumor-infiltrating fibrocytes as CD45+CD34+ cells. These tumor-infiltrating fibrocytes demonstrated both antigen-presenting ability and differentiation into myofibroblast-like cancer-associated fibroblasts. Considering these functions of fibrocytes in tumor progression, molecular-targeting agents for the migration, activity, and differentiation of fibrocytes are promising therapeutic strategies. Furthermore, identification of specific cell surface markers and master regulators of fibrocytes will advance novel fibrocyte-targeting therapies. In this review, we discuss the multiple roles of tumor-infiltrating fibrocytes and novel cancer therapeutic strategies.

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肿瘤微环境中的纤维细胞:确定纤维细胞的组成和新型治疗策略
纤维细胞被鉴定为骨髓来源的髓样细胞,也具有类似成纤维细胞的表型,如产生 ECM 和分化为肌成纤维细胞。尽管已知成纤维细胞可导致各种类型的组织纤维化,但它们在肿瘤微环境中的功能尚不清楚。我们重点研究了作为肿瘤进展关键调节因子的纤维细胞。我们之前的研究表明,纤维细胞通过分泌各种生长因子诱导血管生成和癌症干细胞样表型。相反,免疫检查点抑制剂(ICI)处理过的纤维细胞具有抗原递呈能力,并能增强抗肿瘤 T 细胞的增殖。总之,这些研究结果表明,纤维细胞对肿瘤的进展有多重影响。然而,纤维细胞的详细表型尚未完全阐明,因为如果不在涂有 ECM 的条件下培养或不对 ECM 进行细胞内染色,就无法分离出不同的纤维细胞簇。单细胞分析技术的发展部分解决了这些问题。肿瘤组织中 CD45+ 免疫细胞的单细胞 RNA 序列确定了表达 ECM 的髓样细胞是独特的纤维细胞集群。此外,这些发现还能将肿瘤浸润纤维细胞分离为 CD45+CD34+ 细胞。这些肿瘤浸润纤维细胞既具有抗原递呈能力,又能分化为肌成纤维细胞样癌症相关成纤维细胞。考虑到纤维细胞在肿瘤进展中的这些功能,针对纤维细胞迁移、活性和分化的分子靶向药物是很有前景的治疗策略。此外,特异性细胞表面标志物和纤维细胞主调控因子的鉴定将推动新型纤维细胞靶向疗法的发展。在这篇综述中,我们将讨论肿瘤浸润纤维细胞的多重作用和新型癌症治疗策略。
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来源期刊
Cancer Science
Cancer Science ONCOLOGY-
CiteScore
9.90
自引率
3.50%
发文量
406
审稿时长
17 weeks
期刊介绍: Cancer Science (formerly Japanese Journal of Cancer Research) is a monthly publication of the Japanese Cancer Association. First published in 1907, the Journal continues to publish original articles, editorials, and letters to the editor, describing original research in the fields of basic, translational and clinical cancer research. The Journal also accepts reports and case reports. Cancer Science aims to present highly significant and timely findings that have a significant clinical impact on oncologists or that may alter the disease concept of a tumor. The Journal will not publish case reports that describe a rare tumor or condition without new findings to be added to previous reports; combination of different tumors without new suggestive findings for oncological research; remarkable effect of already known treatments without suggestive data to explain the exceptional result. Review articles may also be published.
期刊最新文献
Fibrocytes in tumor microenvironment: Identification of their fraction and novel therapeutic strategy. The prognostic significance of MYC/BCL2 double expression in DLBCL in the genetic classification era. METTL14 attenuates cancer stemness by suppressing ATF5/WDR74/β-catenin axis in gastric cancer. Camrelizumab combined with gemcitabine and apatinib in treating advanced PD-L1-positive biliary tract cancers. Integrated machine learning to predict the prognosis of lung adenocarcinoma patients based on SARS-COV-2 and lung adenocarcinoma crosstalk genes.
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