CAF Specific Expression of Podoplanin May Be Dispensable for the Malignancy of Malignant Melanoma.

IF 3 2区 医学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Molecular Carcinogenesis Pub Date : 2024-11-08 DOI:10.1002/mc.23841
Saskia Tauch, Bettina Kast, Sabrina Lohr, Lowis Kemm, Melanie Sator-Schmitt, Nicolas Gengenbacher, Hellmut G Augustin, Peter Angel
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Abstract

Within the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) were shown to be an active and pivotal cell population, supporting many protumorigenic mechanisms. Podoplanin (PDPN)-positive CAFs are of special interest since their abundance correlated with a worse prognosis for patients of different cancer entities, including malignant melanoma. In this study, we applied a loss-of-function approach in an in vivo mouse melanoma model to evaluate the contribution of CAF-specific PDPN expression to melanoma formation and progression. Surprisingly, despite its prominent expression in CAFs deletion of PDPN in this cell type did neither affect the onset, nor growth of MM tumors. These data imply that PDPN expression in CAFs represents a biomarker for poor prognosis but does not serve as a useful target for stroma-directed therapy of malignant melanoma.

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Podoplanin的CAF特异性表达可能与恶性黑色素瘤的恶性程度无关。
在肿瘤微环境(TME)中,癌症相关成纤维细胞(CAFs)被证明是一种活跃的关键细胞群,支持许多原发肿瘤机制。Podoplanin (PDPN)阳性的CAFs特别引人关注,因为它们的数量与不同癌症实体(包括恶性黑色素瘤)患者的不良预后相关。在本研究中,我们在体内小鼠黑色素瘤模型中采用了功能缺失的方法来评估CAF特异性PDPN表达对黑色素瘤形成和进展的贡献。令人惊讶的是,尽管 PDPN 在 CAF 中有显著表达,但在这种细胞类型中缺失 PDPN 既不会影响 MM 肿瘤的发生,也不会影响其生长。这些数据表明,PDPN在CAFs中的表达是预后不良的生物标志物,但并不能作为恶性黑色素瘤瘤体导向疗法的有用靶点。
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来源期刊
Molecular Carcinogenesis
Molecular Carcinogenesis 医学-生化与分子生物学
CiteScore
7.30
自引率
2.20%
发文量
112
审稿时长
2 months
期刊介绍: Molecular Carcinogenesis publishes articles describing discoveries in basic and clinical science of the mechanisms involved in chemical-, environmental-, physical (e.g., radiation, trauma)-, infection and inflammation-associated cancer development, basic mechanisms of cancer prevention and therapy, the function of oncogenes and tumors suppressors, and the role of biomarkers for cancer risk prediction, molecular diagnosis and prognosis.
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