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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

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2018 Impact Factor: 1.847

Front. Med.    2019, Vol. 13 Issue (3) : 289-297    https://doi.org/10.1007/s11684-018-0667-3
REVIEW
Histone variants: critical determinants in tumour heterogeneity
Tao Wang1,2, Florent Chuffart1, Ekaterina Bourova-Flin1, Jin Wang2, Jianqing Mi2, Sophie Rousseaux1, Saadi Khochbin1()
1. CNRS UMR 5309, Inserm, U1209, University of Grenoble Alpes, Institute for Advanced Biosciences, 38706, Grenoble, France
2. State Key Laboratory for Medical Genomics and Department of Hematology, Shanghai Institute of Hematology, Collaborative Innovation Center of Systems Biomedicine, Pôle Sino-Français des Sciences du Vivant et Genomique, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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Abstract

Malignant cell transformation could be considered as a series of cell reprogramming events driven by oncogenic transcription factors and upstream signalling pathways. Chromatin plasticity and dynamics are critical determinants in the control of cell reprograming. An increase in chromatin dynamics could therefore constitute an essential step in driving oncogenesis and in generating tumour cell heterogeneity, which is indispensable for the selection of aggressive properties, including the ability of cells to disseminate and acquire resistance to treatments. Histone supply and dosage, as well as histone variants, are the best-known regulators of chromatin dynamics. By facilitating cell reprogramming, histone under-dosage and histone variants should also be crucial in cell transformation and tumour metastasis. Here we summarize and discuss our knowledge of the role of histone supply and histone variants in chromatin dynamics and their ability to enhance oncogenic cell reprogramming and tumour heterogeneity.

Keywords cancer-testis      TH2B      TH2A      H1T      H1.0      H1F0      linker histones     
Corresponding Authors: Saadi Khochbin   
Just Accepted Date: 28 August 2018   Online First Date: 09 October 2018    Issue Date: 05 June 2019
 Cite this article:   
Tao Wang,Florent Chuffart,Ekaterina Bourova-Flin, et al. Histone variants: critical determinants in tumour heterogeneity[J]. Front. Med., 2019, 13(3): 289-297.
 URL:  
http://academic.hep.com.cn/fmd/EN/10.1007/s11684-018-0667-3
http://academic.hep.com.cn/fmd/EN/Y2019/V13/I3/289
Fig.1  Histone-based malignant transformation, tumour heterogeneity and selection of aggressive characters. Pro-oncogenic events could lead to aberrant activation of silenced histone variants-encoding genes or histone assembly defects or histone under-dosage, leading to increased chromatin dynamics and enhanced genome reprogramming by oncogenic factors. The resulting heterogeneity would create a window of opportunity for the selection of newly reprogrammed oncogenic cells capable of surviving and disseminating.
Fig.2  Aberrant activation of testis-oocyte specific TH2A/TH2B in various cancers. (A) Expression of TH2A and TH2B genes in normal human tissues samples from RNA-seq data, provided by the Genotype-Tissue Expression (GTEx) project [56]. (B) Expression of TH2A and TH2B genes in breast and lung cancer samples. Breast cancer RNA-seq data are provided by the TCGA-BRCA project [57]. Lung cancer RNA-seq data are provided by the NCBI GEO GSE81089 [58], TCGA-LUAD and TCGA-LUSC projects [57]. For all plots, the expression level of genes is represented as a distribution of log-transformed RPKM values, after addition of a pseudo count of 1 (log2 (1+RPKM)). Breast cancer: NT Breast= non tumoral breast; Breast K= breast cancer. Lung cancer: NT Lung= non tumoral lung; L. ADC= Lung adenocarcinoma; L. SQC= Lung squamous cell carcinoma; other LK= lung tumours of other histological subtypes.
Fig.3  Aberrant activation of testis-specific H1T in various cancers. Expression of H1T gene in normal (left panel) and tumour (right panels) samples from RNA-seq data, provided by the GTEx [56], TCGA-BRCA [57] and NCBI GEO GSE81089 [58] datasets. The expression level of genes is represented as a distribution of log-transformed RPKM values, after addition of a pseudo count of 1 (log2 (1+RPKM)). Breast cancer: NT Breast= non tumoral breast; Breast K= breast cancer. Lung cancer: NT Lung= non tumoral lung; L. ADC= Lung adenocarcinoma; L. SQC= Lung squamous cell carcinoma; other LK= lung tumours of other histological subtypes.
Fig.4  H1F0 gene expression is activated in different cancers. Expression of H1F0 gene in breast and lung tumour samples with corresponding Kaplan–Meyer survival curves. Breast cancer RNA-seq data are provided by the TCGA-BRCA project [57]. Lung cancer RNA-seq data are provided by the NCBI GEO GSE81089 [58], TCGA-LUAD and TCGA-LUSC projects [57]. For all plots, the expression level of genes is represented as a distribution of log-transformed RPKM values, after addition of a pseudo count of 1 (log2 (1+RPKM)). Breast cancer: NT Breast= non tumoral breast; Breast K= breast cancer. Lung cancer: NT Lung= non tumoral lung; L. ADC= Lung adenocarcinoma; L. SQC= Lung squamous cell carcinoma; L. LCNE= Lung large cell neuroendocrine tumours; L. BAS= Lung basaloid tumours; L. SCC= Lung small cell carcinoma; L. CARCI= Lung carcinoid tumours; other LK= lung tumours of other histological subtypes.
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