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J Cancer 2020; 11(9):2453-2464. doi:10.7150/jca.38747 This issue Cite

Research Paper

Integrative Analysis of Siglec-15 mRNA in Human Cancers Based on Data Mining

Qiu-ting Li1, Zao-zao Huang2, Yao-bin Chen3, Hong-yi Yao4, Zun-hui Ke5, Xiao- xiao He1, Meng-jun Qiu1, Meng-meng Wang1, Zhi-fan Xiong1✉, Sheng-li Yang6✉

1. Division of Gastroenterology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China.
2. Yangchunhu community Hospital, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China.
3. Institute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
4. Department of Rehabilitation, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China.
5. Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430015, China.
6. Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 JieFang Avenue, Wuhan 430022, China.

✉ Corresponding authors: Dr. Sheng-li Yang, Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 JieFang Avenue, Wuhan 430022, China. E-mail: yangshengliedu.cn; Tel: 15994284798; Fax: 027-656 More

Citation:
Li Qt, Huang Zz, Chen Yb, Yao Hy, Ke Zh, He Xx, Qiu Mj, Wang Mm, Xiong Zf, Yang Sl. Integrative Analysis of Siglec-15 mRNA in Human Cancers Based on Data Mining. J Cancer 2020; 11(9):2453-2464. doi:10.7150/jca.38747. https://www.jcancer.org/v11p2453.htm
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Abstract

Objective: Cancer is expected to be the leading cause of death worldwide within the 21st century and is the single most important obstacle to extending life expectancy. Unfortunately, the most effective approach to combating cancers remains a complex and unsolved problem. Siglec-15 is a member of the Siglec family and plays a conserved regulatory role in the immune system of vertebrates. Previous studies on Siglec-15 have focused on its function in osteoclast regulation. The purpose of this study was to explore the significance of Siglec-15 mRNA in human cancer mainly based on information obtained from online databases.

Method: Data were collected from several online databases. Serial analysis of gene expression (SAGE) and Virtual Northern, UALCAN Database Analysis, Catalog of Somatic Mutations in Cancer (COSMIC) analysis, the cBio cancer genomics portal, Cancer Regulome tools and data, Kaplan-Meier Plotter Analysis and the UCSC Xena website were used to analyze the data.

Results: Compared with normal tissues, Siglec-15 up-regulation was widely observed in tuomrs. Differences in Siglec-15 expression were associated with different prognoses. Siglec-15 mutations are widely observed in tumors and interact with different genes in different cancer types.

Conclusion: Siglec-15 is a potential target for the expansion of cancer immunotherapy.

Keywords: Siglec-15, cancer, immunotherapy, biomarker

Citation styles

APA
Li, Q.t., Huang, Z.z., Chen, Y.b., Yao, H.y., Ke, Z.h., He, X.x., Qiu, M.j., Wang, M.m., Xiong, Z.f., Yang, S.l. (2020). Integrative Analysis of Siglec-15 mRNA in Human Cancers Based on Data Mining. Journal of Cancer, 11(9), 2453-2464. https://doi.org/10.7150/jca.38747.

ACS
Li, Q.t.; Huang, Z.z.; Chen, Y.b.; Yao, H.y.; Ke, Z.h.; He, X.x.; Qiu, M.j.; Wang, M.m.; Xiong, Z.f.; Yang, S.l. Integrative Analysis of Siglec-15 mRNA in Human Cancers Based on Data Mining. J. Cancer 2020, 11 (9), 2453-2464. DOI: 10.7150/jca.38747.

NLM
Li Qt, Huang Zz, Chen Yb, Yao Hy, Ke Zh, He Xx, Qiu Mj, Wang Mm, Xiong Zf, Yang Sl. Integrative Analysis of Siglec-15 mRNA in Human Cancers Based on Data Mining. J Cancer 2020; 11(9):2453-2464. doi:10.7150/jca.38747. https://www.jcancer.org/v11p2453.htm

CSE
Li Qt, Huang Zz, Chen Yb, Yao Hy, Ke Zh, He Xx, Qiu Mj, Wang Mm, Xiong Zf, Yang Sl. 2020. Integrative Analysis of Siglec-15 mRNA in Human Cancers Based on Data Mining. J Cancer. 11(9):2453-2464.

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