Innate immune checkpoint Siglec10 in cancers: mining of comprehensive omics data and validation in patient samples

Chen Zhang, Jiandong Zhang, Fan Liang, Han Guo, Sanhui Gao, Fuying Yang, Hua Guo, Guizhen Wang, Wei Wang, Guangbiao Zhou

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Front. Med. ›› 2022, Vol. 16 ›› Issue (4) : 596-609. DOI: 10.1007/s11684-021-0868-z
RESEARCH ARTICLE
RESEARCH ARTICLE

Innate immune checkpoint Siglec10 in cancers: mining of comprehensive omics data and validation in patient samples

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Abstract

Sialic acid binding Ig-like lectin 10 (Siglec10) is a member of innate immune checkpoints that inhibits the activation of immune cells through the interaction with its ligand CD24 on tumor cells. Here, by analyzing public databases containing 64 517 patients of 33 cancer types, we found that the expression of Siglec10 was altered in 18 types of cancers and was associated with the clinical outcomes of 11 cancer types. In particular, Siglec10 was upregulated in patients with kidney renal clear cell carcinoma (KIRC) and was inversely associated with the prognosis of the patients. In 131 KIRC patients of our settings, Siglec10 was elevated in the tumor tissues of 83 (63.4%) patients compared with that in their counterpart normal kidney tissues. Moreover, higher level of Siglec10 was associated with advanced disease (stages III and IV) and worse prognosis. Silencing of CD24 in KIRC cells significantly increased the number of Siglec10-expressing macrophages phagocytosing KIRC cells. In addition, luciferase activity assays suggested that Siglec10 was a potential target of the transcription factors c-FOS and GATA1, which were identified by data mining. These results demonstrate that Siglec10 may have important oncogenic functions in KIRC, and represents a novel target for the development of immunotherapies.

Keywords

innate immune checkpoint / Siglec10 / kidney renal clear cell carcinoma

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Chen Zhang, Jiandong Zhang, Fan Liang, Han Guo, Sanhui Gao, Fuying Yang, Hua Guo, Guizhen Wang, Wei Wang, Guangbiao Zhou. Innate immune checkpoint Siglec10 in cancers: mining of comprehensive omics data and validation in patient samples. Front. Med., 2022, 16(4): 596‒609 https://doi.org/10.1007/s11684-021-0868-z

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Acknowledgements

This work was jointly supported by the National Key Research and Development Program of China (No. 2020YFA0803300), the CAMS Initiative of Innovative Medicine (2021-1-I2M-014), the CAMS Innovation Fund for Medical Sciences (CIFMS) (Nos. 2021-RC310-003 and 2020-RC310-002), the Key Project of the National Natural Science Foundation of China (No. 81830093), the National Natural Science Funds for Distinguished Young Scholar (No. 81425025), and the National Natural Science Foundation of China (Nos. 81672765, 81802796, and 82073092).

Compliance with ethics guidelines

Chen Zhang, Jiandong Zhang, Fan Liang, Han Guo, Sanhui Gao, Fuying Yang, Hua Guo, Guizhen Wang, Wei Wang, and Guangbiao Zhou declare that they have no conflict of interest. All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975 as revised in 2000. Additional informed consent was obtained from all patients whose identifying information is included in this article.

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11684-021-0868-z and is accessible for authorized users. The supplementary material contains 1 supplementary figure and 7 supplementary tables.

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