Identification of a histone family gene signature for predicting the prognosis of cervical cancer patients

Xiaofang Li, Run Tian, Hugh Gao, Yongkang Yang, Bryan R.G. Williams, Michael P. Gantier, Nigel A.J. McMillan, Dakang Xu, Yiqun Hu, Yan'E Gao

Research output: Contribution to journalArticleResearchpeer-review

29 Citations (Scopus)


Heterogeneity in terms of tumor characteristics, prognosis, and survival among cancer patients is an unsolved issue. Here, we systematically analyzed the aberrant expression patterns of cervical cancer using RNA-Seq data from The Cancer Genome Atlas (TCGA). We incorporated gene profiling, molecular signatures, functional and pathway information with gene set enrichment and protein-protein interaction (PPI) network analysis, to identify sub-networks of genes. Those identified genes relating to DNA replication and DNA repair-mediated signaling pathways associated with systemic lupus erythematosus (SLE). Next, we combined cross-validated prognostic scores to build an integrated prognostic model for survival prediction. The combined approach revealed that the DNA repair-mediated including the functional interaction module of 18 histone genes (Histone cluster 1 H2A, B and H4), were significantly correlated with the survival rate. Furthermore, five of these histone genes were highly expressed in three cervical cancer cohorts from the Oncomine database. Comparison of high and low histone variant-expressing human cervical cancer cell lines revealed different responses to DNA damage, suggesting protective functions of histone genes against DNA damage. Collectively, we provide evidence that two SLE-associated gene sets (HIST1H2BD and HIST1H2BJ; and HIST1H2BD, HIST1H2BJ, HIST1H2BH, HIST1H2AM and HIST1H4K) can be used as prognostic factors for survival prediction among cervical cancer patients.

Original languageEnglish
Article number16495
Number of pages13
JournalScientific Reports
Issue number1
Publication statusPublished - 1 Dec 2017

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