TMEM88, CCL14 and CLEC3B as prognostic biomarkers for prognosis and palindromia of human hepatocellular carcinoma

Author:

Zhang Xin1,Wan Jin-Xiang2,Ke Zun-Ping3,Wang Feng4,Chai Hai-Xia5,Liu Jia-Qiang6

Affiliation:

1. Department of Radiology, the Fourth People’s Hospital of Huai’an, Huai’an, China

2. Department of Medical Ultrasonics, The Affiliated Huai’an Hospital of Xuzhou Medical University and The Second People’s Hospital of Huai’an, Huai’an, China

3. Department of Cardiology, The Fifth People’s Hospital of Shanghai, Fudan University, Shanghai, China

4. Department of Gynecology, Taihe Hospital, Hubei University of Medicine, Shiyan, P.R. China

5. Department of Oncology, Taihe Hospital, Hubei University of Medicine, Shiyan, P.R. China

6. Department of Oral and Cranio-Maxillofacial, Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China

Abstract

Hepatocellular carcinoma is one of the most mortal and prevalent cancers with increasing incidence worldwide. Elucidating genetic driver genes for prognosis and palindromia of hepatocellular carcinoma helps managing clinical decisions for patients. In this study, the high-throughput RNA sequencing data on platform IlluminaHiSeq of hepatocellular carcinoma were downloaded from The Cancer Genome Atlas with 330 primary hepatocellular carcinoma patient samples. Stable key genes with differential expressions were identified with which Kaplan–Meier survival analysis was performed using Cox proportional hazards test in R language. Driver genes influencing the prognosis of this disease were determined using clustering analysis. Functional analysis of driver genes was performed by literature search and Gene Set Enrichment Analysis. Finally, the selected driver genes were verified using external dataset GSE40873. A total of 5781 stable key genes were identified, including 156 genes definitely related to prognoses of hepatocellular carcinoma. Based on the significant key genes, samples were grouped into five clusters which were further integrated into high- and low-risk classes based on clinical features. TMEM88, CCL14, and CLEC3B were selected as driver genes which clustered high-/low-risk patients successfully (generally, p = 0.0005124445). Finally, survival analysis of the high-/low-risk samples from external database illustrated significant difference with p value 0.0198. In conclusion, TMEM88, CCL14, and CLEC3B genes were stable and available in predicting the survival and palindromia time of hepatocellular carcinoma. These genes could function as potential prognostic genes contributing to improve patients’ outcomes and survival.

Publisher

IOS Press

Subject

General Medicine

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