Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer

Meiliang Liu; Xia Liu; Shun Liu; Feifei Xiao; Erna Guo; Xiaoling Qin; Liuyu Wu; Qiuli Liang; Zerui Liang; Kehua Li; Di Zhang; Yu Yang; Xingxi Luo; Lei Lei; Jennifer Hui Juan Tan; Fuqiang Yin; Xiaoyun Zeng

doi:10.3389/fonc.2020.00847

Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer

Front Oncol. 2020 May 28:10:847. doi: 10.3389/fonc.2020.00847. eCollection 2020.

Authors

Meiliang Liu¹, Xia Liu², Shun Liu¹, Feifei Xiao³, Erna Guo^{1

4}, Xiaoling Qin¹, Liuyu Wu¹, Qiuli Liang¹, Zerui Liang¹, Kehua Li¹, Di Zhang¹, Yu Yang¹, Xingxi Luo¹, Lei Lei¹, Jennifer Hui Juan Tan⁵, Fuqiang Yin^{6

7}, Xiaoyun Zeng^{1

7}

Affiliations

¹ School of Public Health, Guangxi Medical University, Nanning, China.
² Key Laboratory of Longevity and Ageing-Related Disease of Chinese Ministry of Education, Centre for Translational Medicine and School of Preclinical Medicine, Guangxi Medical University, Nanning, China.
³ Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, United States.
⁴ School of International Education, Guangxi Medical University, Nanning, China.
⁵ School of Life Sciences and Chemical Technology, Ngee Ann Polytechnic, Singapore, Singapore.
⁶ Life Sciences Institute, Guangxi Medical University, Nanning, China.
⁷ Key Laboratory of High-Incidence-Tumor Prevention and Treatment, Guangxi Medical University, Ministry of Education, Nanning, China.

Abstract

Simultaneous identification of multiple single genes and multi-gene prognostic signatures with higher efficacy in liver cancer has rarely been reported. Here, 1,173 genes potentially related to the liver cancer prognosis were mined with Coremine, and the gene expression and survival data in 370 samples for overall survival (OS) and 319 samples for disease-free survival (DFS) were retrieved from The Cancer Genome Atlas. Numerous survival analyses results revealed that 39 genes and 28 genes significantly associated with DFS and OS in liver cancer, including 18 and 12 novel genes that have not been systematically reported in relation to the liver cancer prognosis, respectively. Next, totally 9,139 three-gene combinations (including 816 constructed by 18 novel genes) for predicting DFS and 3,276 three-gene combinations (including 220 constructed by 12 novel genes) for predicting OS were constructed based on the above genes, and the top 15 of these four parts three-gene combinations were selected and shown. Moreover, a huge difference between high and low expression group of these three-gene combination was detected, with median survival difference of DFS up to 65.01 months, and of OS up to 83.57 months. The high or low expression group of these three-gene combinations can predict the longest prognosis of DFS and OS is 71.91 months and 102.66 months, and the shortest is 6.24 months and 13.96 months. Quantitative real-time polymerase chain reaction and immunohistochemistry reconfirmed that three genes F2, GOT2, and TRPV1 contained in one of the above combinations, are significantly dysregulated in liver cancer tissues, low expression of F2, GOT2, and TRPV1 is associated with poor prognosis in liver cancer. Overall, we discovered a few novel single genes and multi-gene combinations biomarkers that are closely related to the long-term prognosis of liver cancer, and they can be potential therapeutic targets for liver cancer.

Keywords: data mining; disease-free survival (DFS); gene combinations; liver cancer; overall survival (OS).