Literature DB >> 28718365

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

Xin Zhang1, Jin-Xiang Wan2, Zun-Ping Ke3, Feng Wang4, Hai-Xia Chai5, Jia-Qiang Liu6.   

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.

Entities:  

Keywords:  Hepatocellular carcinoma; Kaplan–Meier survival analysis; The Cancer Genome Atlas; cluster analysis; driver genes

Mesh:

Substances:

Year:  2017        PMID: 28718365     DOI: 10.1177/1010428317708900

Source DB:  PubMed          Journal:  Tumour Biol        ISSN: 1010-4283


  12 in total

1.  Bioinformatic Analysis of Prognostic Value of SNTG2 with Immune Implications in Lung Adenocarcinoma.

Authors:  Jian Zhou; Yang Wen; Xiangtian Chen; Linlang Guo
Journal:  Int J Gen Med       Date:  2022-05-24

Review 2.  Chemokines and their Receptors: Multifaceted Roles in Cancer Progression and Potential Value as Cancer Prognostic Markers.

Authors:  Ha Thi Thu Do; Chang Hoon Lee; Jungsook Cho
Journal:  Cancers (Basel)       Date:  2020-01-24       Impact factor: 6.639

3.  CCL14 is a prognostic biomarker and correlates with immune infiltrates in hepatocellular carcinoma.

Authors:  Yurong Gu; Xiangyong Li; Yanhua Bi; Yubao Zheng; Jialiang Wang; Xiaoyan Li; Zexuan Huang; Lubiao Chen; Yanlin Huang; Yuehua Huang
Journal:  Aging (Albany NY)       Date:  2020-01-12       Impact factor: 5.682

4.  CLEC3B as a Potential Prognostic Biomarker in Hepatocellular Carcinoma.

Authors:  Xing-Wei Xie; Shan-Shan Jiang; Xiang Li
Journal:  Front Mol Biosci       Date:  2021-01-20

5.  The Role of CCL20-CCR6 Axis in Ovarian Cancer Metastasis.

Authors:  Wan Liu; Wenjing Wang; Ning Zhang; Wen Di
Journal:  Onco Targets Ther       Date:  2020-12-11       Impact factor: 4.147

6.  Role of chemokines in hepatocellular carcinoma (Review).

Authors:  Dongdong Xue; Ya Zheng; Junye Wen; Jingzhao Han; Hongfang Tuo; Yifan Liu; Yanhui Peng
Journal:  Oncol Rep       Date:  2020-12-22       Impact factor: 3.906

7.  C-C motif chemokine ligand 14 inhibited colon cancer cell proliferation and invasion through suppressing M2 polarization of tumor-associated macrophages.

Authors:  Na Li; Xiao Liang; Jiawen Li; Dongxu Zhang; Teng Li; Zuoming Guo
Journal:  Histol Histopathol       Date:  2021-06-07       Impact factor: 2.303

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

Authors:  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
Journal:  Front Oncol       Date:  2020-05-28       Impact factor: 6.244

9.  Gene Expression Profiling of B Cell Lymphoma in Dogs Reveals Dichotomous Metabolic Signatures Distinguished by Oxidative Phosphorylation.

Authors:  Ying Wu; Yu-Mei Chang; Gerry Polton; Anneliese J Stell; Balazs Szladovits; Michael Macfarlane; Laureen M Peters; Simon L Priestnall; Nicholas J Bacon; Kelvin Kow; Sarah Stewart; Eshita Sharma; Michelle R Goulart; John Gribben; Dong Xia; Oliver A Garden
Journal:  Front Oncol       Date:  2020-03-06       Impact factor: 6.244

10.  TMEM88 Modulates Lipid Synthesis and Metabolism Cytokine by Regulating Wnt/β-Catenin Signaling Pathway in Non-Alcoholic Fatty Liver Disease.

Authors:  Huan Zhou; Xingyu Zhu; Yan Yao; Yue Su; Jing Xie; Minhui Zhu; Cuixia He; Jiaxiang Ding; Yuanyuan Xu; Rongfang Shan; Ying Wang; Xiangdi Zhao; Yuzhou Ding; Bingyan Liu; Zhonghuan Shao; Yuanyuan Liu; Tao Xu; Yunqiu Xie
Journal:  Front Pharmacol       Date:  2022-01-04       Impact factor: 5.810

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