Integrating bioinformatic analysis and detailed experiments reveal an EMT-related biomarker for clear cell renal cell carcinoma

Yue Ge; Sheng Ma; Junbiao Zhang; Zezhong Xiong; Beining Li; Siquan Ma; Bo Liu; Xiangyang Yao; Zhihua Wang

doi:10.1002/cam4.6504

Integrating bioinformatic analysis and detailed experiments reveal an EMT-related biomarker for clear cell renal cell carcinoma

Cancer Med. 2023 Sep;12(18):19320-19336. doi: 10.1002/cam4.6504. Epub 2023 Sep 7.

Authors

Yue Ge¹, Sheng Ma¹, Junbiao Zhang¹, Zezhong Xiong¹, Beining Li¹, Siquan Ma¹, Bo Liu², Xiangyang Yao³, Zhihua Wang¹

Affiliations

¹ Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
² Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
³ Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.

Abstract

Background: Epithelial-mesenchymal transition (EMT) is associated with early recurrence and a poor prognosis in clear cell renal cell carcinoma (ccRCC). Studies have shown that EMT-related genes play an important regulatory role in tumor invasion, metastasis, and drug resistance, but the biological functions of EMT-related genes in ccRCC have not been specifically described.

Methods: The mRNA and clinicopathological data of 532 ccRCC and 72 normal samples were downloaded from The Cancer Genome Atlas as a training set. The gene expression matrix and survival data of 91 and 101 ccRCC samples were obtained from the International Cancer Genome Consortium and the ArrayExpress databases as validation sets, respectively. Univariate Cox analysis was used to identify and cluster prognostic genes, and multivariate Cox was performed to construct a prognostic signature. Moreover, CIBERSORT and CellMiner were used to assess immune cell infiltration and prognostic gene-drug sensitivity of the signature, respectively. Most importantly, we performed detailed experiments to verify the oncogenic function of a significant gene, OLFML2B, in vitro and in vivo.

Results: We constructed a prognostic signature including seven genes and divided patients into high-risk and low-risk groups. The prognosis of the high-risk group was significantly worse than that of the low-risk group through Kaplan-Meier survival analysis. Interestingly, significant differences were observed in clinical characteristics and immune cell infiltration between the two groups. In addition, a significant correlation was found between the expression of prognostic genes and the sensitivity of tumor cells to chemotherapeutics. Most importantly, OLFML2B was proved to contribute to the proliferation and metastasis of ccRCC through detailed functional experiments in vitro and in vivo, and its prognostic efficacy for ccRCC patients was affirmed.

Conclusion: We identified the prognostic signature of seven genes based on EMT-related genes as prognostic biomarkers for ccRCC. Besides, OLFML2B was validated as a potential diagnostic and therapeutic target for ccRCC by our detailed experiments.

Keywords: OLFML2B; biomarker; clear cell renal cell carcinoma; epithelial-mesenchymal transition.

Abstract

Grants and funding