Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma

Lihua Ni; Cheng Yuan; Changjiang Zhang; Yuandi Xiang; Juan Wu; Xiaolong Wang; Xiaoyan Wu

doi:10.2147/OTT.S251000

Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma

Onco Targets Ther. 2020 Jul 17:13:6975-6986. doi: 10.2147/OTT.S251000. eCollection 2020.

Authors

Lihua Ni^#¹, Cheng Yuan^#², Changjiang Zhang^#^{3

4}, Yuandi Xiang⁵, Juan Wu⁶, Xiaolong Wang⁷, Xiaoyan Wu¹

Affiliations

¹ Department of Nephrology, Zhongnan Hospital of Wuhan University, Wuhan 430071, People's Republic of China.
² Department of Gynecological Oncology, Zhongnan Hospital of Wuhan University, Wuhan 430071, People's Republic of China.
³ Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, People's Republic of China.
⁴ Department of Cardiology, The Central Hospital of Enshi Autonomous Prefecture, Enshi, People's Republic of China.
⁵ Department of Otorhinolaryngology, Wuhan First Hospital, Wuhan, Hubei, People's Republic of China.
⁶ Department of Dermatology, Wuhan First Hospital, Wuhan, Hubei, People's Republic of China.
⁷ Department of Urology, Research Lab/LIFE-Zentrum, University of Munich (LMU), München, Germany.

^# Contributed equally.

Abstract

Objective: Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer in adults. The 5-year survival rate of patients with advanced ccRCC is less than 30%. Lack of potential biomarkers for treatment and prognosis is a limitation for early diagnosis and treatment of ccRCC.

Methods: We collected microarray profiles of 39 ccRCC and matched normal samples to identify differential expression genes (DEGs). Then, a weighted gene co-expression network analysis (WGCNA) was constructed to identify gene modules associated with the metastasis in ccRCC. The Cancer Genome Atlas (TCGA) database and the Human Protein Atlas (HPA, https://www.proteinatlas.org/) database were used for verification set. Finally, we used biological experiments to preliminary investigate the impact of LTF on the tumor biological behavior of ccRCC, including proliferation, migration, invasion, and apoptosis.

Results: A total of 15 genetic modules were identified, and the light-green module is considered the most relevant to tumor metastasis. (P = 0.02, R² = -0.4). Protein-protein interaction (PPI) network was performed to identify the hub nodes in the light-green module. Finally, combining the results of PPI, WGCNA and DEGs, lactotransferrin (LTF) gene was regarded as "real" hub genes for cancer metastasis risk. LTF was subsequently validated using the TCGA database. Immunohistochemistry confirmed that the expression of LTF in ccRCC tumor tissue was significantly lower than that in normal tissue based on the HPA database. Intriguingly, patients with low expression of LTF had lower survival rates (HR = 0.66, 95% CI: 0.49-0.89, P = 0.0067), the expression level of the sample was negatively correlated with tumor stage (P = 0.0385), and patients with low expression of LTF gene were more likely to have distant metastasis (P = 0.038). Overexpression of LTF inhibited the proliferation, migration, invasion and promoted apoptosis of human ccRCC cells in vitro.

Conclusion: LTF might be a novel prognostic biomarker for ccRCC.

Keywords: LTF; clear cell renal cell carcinoma; metastasis.

Grants and funding

This work was supported by grants from the Fundamental Research Funds for the Central University (2042020kf0137), Hubei Province Health and Family Planning Scientific Research Project (WJ2019MB103), Zhongnan Hospital of Wuhan University Science, Technology and Innovation Seed Fund (znpy2017044), the Clinical Research Project for Wu Jieping Medical Foundation (320.6750.19089-58), and the Research Fund from Medical Sci-Tech Innovation Platform of Zhongnan Hospital, Wuhan University (PTXM2020028).