Role of HDAC4 in the process of oncogenesis in human cells

The resetting of Epigenetics is a common feature of cancer cells. By contrast how epigenetic regulators can trigger the oncogenic transformation is mystery. Previous studies reported that the hyper-activation of the epigenetic regulator HDAC4 transforms murine cells. However, the transformation process is more complex in human cells that are relatively resistant to oncogenesis. In the present thesis we addressed the oncogenic potential of HDAC4 in human primary fibroblasts (BJ). The over-expression of an hyper-active mutant of HDAC4 in human fibroblast triggers a permanent cell cycle arrest typical of premature senescent cells after the exposure to strong oncogenes. The contemporary inactivation of p53 and pRb/p16 pathways achieved by the transduction of the cells with SV40 LT allows the transformation of HDAC4-TM cells. Transcriptomic analysis of HDAC4-TM and RAS transformed cells evidenced that both the oncogenes require the repression of the interferon-response to transform the human cells. Further we have compared our signature with other two oncogenes like RAS and c-MYC which favour in vitro transformation in BJ-hTERT SV40 LT/ST. The tumorigenic properties driven by the three oncogenes rely on the activation of some common molecular pathways, but not on the activation and repression of the same genes. Importantly, commonly dysregulated genes, both up-regulated and down-regulated during in vitro transformation contribute to a worst survival rate in some cancer types. To gain insight on the cellular pathways supervised by HDAC4 and responsible for the transformation of human cells we investigated the genomic instability of leiomyosarcoma cells knocked out of HDAC4. In this cancer cell removal of HDAC4 results in the induction of cellular senescence through the augmentation of the DNA damage and the activation of the interferon response.Ingles

The Histone Code of Senescence

Senescence is the end point of a complex cellular response that proceeds through a set of highly regulated steps. Initially, the permanent cell-cycle arrest that characterizes senescence is a pro-survival response to irreparable DNA damage. The maintenance of this prolonged condition requires the adaptation of the cells to an unfavorable, demanding and stressful microenvironment. This adaptation is orchestrated through a deep epigenetic resetting. A first wave of epigenetic changes builds a dam on irreparable DNA damage and sustains the pro-survival response and the cell-cycle arrest. Later on, a second wave of epigenetic modifications allows the genomic reorganization to sustain the transcription of pro-inflammatory genes. The balanced epigenetic dynamism of senescent cells influences physiological processes, such as differentiation, embryogenesis and aging, while its alteration leads to cancer, neurodegeneration and premature aging. Here we provide an overview of the most relevant histone modifications, which characterize senescence, aging and the activation of a prolonged DNA damage response

Insights into the function of HDAC3 and NCoR1/NCoR2 co-repressor complex in metabolic diseases

Histone deacetylase 3 (HDAC3) and nuclear receptor co-repressor (NCoR1/2) are epigenetic regulators that play a key role in gene expression and metabolism. HDAC3 is a class I histone deacetylase that functions as a transcriptional co-repressor, modulating gene expression by removing acetyl groups from histones and non-histone proteins. NCoR1, on the other hand, is a transcriptional co-repressor that interacts with nuclear hormone receptors, including peroxisome proliferator-activated receptor gamma (PPARγ) and liver X receptor (LXR), to regulate metabolic gene expression. Recent research has revealed a functional link between HDAC3 and NCoR1 in the regulation of metabolic gene expression. Genetic deletion of HDAC3 in mouse models has been shown to improve glucose intolerance and insulin sensitivity in the liver, skeletal muscle, and adipose tissue. Similarly, genetic deletion of NCoR1 has improved insulin resistance and reduced adiposity in mouse models. Dysregulation of this interaction has been associated with the development of cardio-metabolic diseases such as cardiovascular diseases, obesity and type 2 diabetes, suggesting that targeting this pathway may hold promise for the development of novel therapeutic interventions. In this review, we summarize the current understanding of individual functions of HDAC3 and NCoR1/2 and the co-repressor complex formation (HDAC3/NCoR1/2) in different metabolic tissues. Further studies are needed to thoroughly understand the mechanisms through which HDAC3, and NCoR1/2 govern metabolic processes and the implications for treating metabolic diseases

The co-existence of transcriptional activator and transcriptional repressor MEF2 complexes influences tumor aggressiveness

The contribution of MEF2 TFs to the tumorigenic process is still mysterious. Here we clarify that MEF2 can support both pro-oncogenic or tumor suppressive activities depending on the interaction with co-activators or co-repressors partners. Through these interactions MEF2 supervise histone modifications associated with gene activation/repression, such as H3K4 methylation and H3K27 acetylation. Critical switches for the generation of a MEF2 repressive environment are class IIa HDACs. In leiomyosarcomas (LMS), this two-faced trait of MEF2 is relevant for tumor aggressiveness. Class IIa HDACs are overexpressed in 22% of LMS, where high levels of MEF2, HDAC4 and HDAC9 inversely correlate with overall survival. The knock out of HDAC9 suppresses the transformed phenotype of LMS cells, by restoring the transcriptional proficiency of some MEF2-target loci. HDAC9 coordinates also the demethylation of H3K4me3 at the promoters of MEF2-target genes. Moreover, we show that class IIa HDACs do not bind all the regulative elements bound by MEF2. Hence, in a cell MEF2-target genes actively transcribed and strongly repressed can coexist. However, these repressed MEF2-targets are poised in terms of chromatin signature. Overall our results candidate class IIa HDACs and HDAC9 in particular, as druggable targets for a therapeutic intervention in LMS

The Histone Code of Senescence

Senescence is the end point of a complex cellular response that proceeds through a set of highly regulated steps. Initially, the permanent cell-cycle arrest that characterizes senescence is a pro-survival response to irreparable DNA damage. The maintenance of this prolonged condition requires the adaptation of the cells to an unfavorable, demanding and stressful microenvironment. This adaptation is orchestrated through a deep epigenetic resetting. A first wave of epigenetic changes builds a dam on irreparable DNA damage and sustains the pro-survival response and the cell-cycle arrest. Later on, a second wave of epigenetic modifications allows the genomic reorganization to sustain the transcription of pro-inflammatory genes. The balanced epigenetic dynamism of senescent cells influences physiological processes, such as differentiation, embryogenesis and aging, while its alteration leads to cancer, neurodegeneration and premature aging. Here we provide an overview of the most relevant histone modifications, which characterize senescence, aging and the activation of a prolonged DNA damage response

Unscheduled HDAC4 repressive activity in human fibroblasts triggers TP53‐dependent senescence and favors cell transformation

Expression of the class IIa HDACs is frequently altered in different human cancers. In mouse models these transcriptional repressors can trigger transformation, acting as bona fide oncogenes. Whether class IIa HDACs also exhibit transforming activities in human cells is currently unknown. We infected primary human fibroblasts with retroviruses to investigate the transforming activity of HDAC4 in cooperation with well‐known oncogenes. We have discovered that HDAC4 triple mutant (S246A, S467A, S632A) (HDAC4‐TM), a nuclear resident version of the deacetylase, triggers TP53 stabilization and OIS (oncogene‐induced senescence). Unlike RAS, HDAC4‐induced OIS was TP53‐dependent and characterized by rapid cell cycle arrest and accumulation of an unusual pattern of γH2AX‐positive foci. The inactivation of both TP53 and of the retinoblastoma (pRb) tumor suppressors, as induced by the viral oncogenes large and small T of SV40, triggers anchorage‐independent growth in RAS, HDAC4‐TM and, to a lesser extent, in HDAC4‐wild type (WT)‐expressing cells. Our results suggest an oncogenic function of class IIa HDACs in human cells, and justify further efforts to discover and evaluate isoform‐specific inhibitors of these epigenetic regulators from a therapeutic perspective

MEF2D silencing causes opposite effect in SK-LMS-1 and SK-UT-1 cells.

<p>A) MEF2D expression was silenced by lentiviral infection using two different shRNAs. Immunoblot analysis of MEF2D and CDKN1A levels in SK-LMS-1 cells expressing the control shRNA or two different shRNAs against MEF2D. RACK1 was used as loading control. B) qRT-PCR analysis of mRNA expression levels of MEF2D and of some MEF2-target genes (<i>KLF2</i>, <i>RHOB</i>, <i>CDKN1A</i>, <i>JUN</i>, <i>CNN1</i>, <i>IRS1</i>) in SK-LMS-1 cells expressing the different shRNAs. mRNA levels are relative to control shRNA. Data are presented as mean ± SD; n = 4. C) Analysis of the cells synthetizing DNA as scored after BrdU staining. Mean ± SD; n = 3. D) SK-LMS-1 cells expressing the indicated shRNAs were seeded at 2x10⁴/ml in plates coated with 10μg/ml fibronectin, or BSA; after 16h they were subjected to time-lapse analysis for 6 hours. Results represent the individual migration rate and the average (bar) from at least 140 cells from three independent experiments. Mean and SEM are indicated. E) Invasion properties of the SK-LMS-1 cells expressing the shRNA2 against MEF2D or the control. Data are presented as mean ± SD; n = 4. Invasion of the Matrigel was scored after 16 hours and was expressed as ratio between cells invading the matrix in presence (oriented motility) and absence (random invasion) of the chemoattractant. Cells were evidenced with Hoechst 33342 staining. At least 5 fields for each condition were acquired and the invading cells were counted by using ImageJ. F) Growth in soft agar of SK-LMS-1 cells expressing the indicated shRNAs, foci were stained with MTT and counted. Data are presented as mean ± SD; n = 4. G) MEF2D expression was silenced by lentiviral infection using two different shRNAs. Immunoblot analysis of MEF2D and CDKN1A levels in SK-UT-1 cells expressing the control shRNA or two different shRNAs against MEF2D. RACK1 was used as loading control. H) qRT-PCR analysis of mRNA expression levels of MEF2D and of some MEF2-target genes (<i>KLF2</i>, <i>RHOB</i>, <i>CDKN1A</i>, <i>JUN</i>, <i>CNN1</i>, <i>IRS1</i>) in SK-UT-1 cells expressing the different shRNAs. mRNA levels are relative to control shRNA. Data are presented as mean ± SD; n = 4. I) Analysis of the cells synthetizing DNA as scored after BrdU staining. Mean ± SD; n = 3. J) SK-UT-1 cells expressing the indicated shRNAs were subjected to time-lapse analysis for 6 hours as in Fig 3D. Results represent the individual migration rate and the average (bar) from at least 140 cells from three independent experiments. Mean and SEM are indicated. K) Invasion properties of the SK-UT-1 cells expressing the shRNA2 against MEF2D or the control. Data are presented as mean ± SD; n = 4. Invasion of the Matrigel was scored after 16 hours and was expressed as ratio between cells invading the matrix in presence (oriented motility) and absence (random invasion) of the chemoattractant. Cells were evidenced with Hoechst 33342 staining. At least 5 fields for each condition were acquired and the invading cells were counted by using ImageJ. L) Growth in soft agar of SK-UT-1 cells expressing the indicated shRNAs, foci were stained with MTT and counted. Data are presented as mean ± SD; n = 4. * p < 0.05, ** p < 0.01, *** p < 0.001</p

Analysis of MEF2D-HDAC4 repressive complexes in LMS cells.

<p>A) Quantitative analysis of the immunofluorescence studies. LMS cells were treated or not for 2 hours with 5ng/ml leptomycin B (LC Laboratories). After fixation of the cells, immunofluorescence analysis was performed to visualize HDAC4. Nuclei were stained with Hoechst 33342. Data are presented as mean ± SD (n = 3). B) MEF2D-HDAC4 complexes were immunoprecipitated using 1μg of anti-HDAC4, or anti-USP33, as a control, antibodies. Immunoblotting using an anti-MEF2D antibody was next used for the detection. The same amounts of cellular lysates were immunoprecipitated and the immunoblot were developed under the same circumstances. C) Chromatin was immunoprecipitated from SK-LMS-1 or SK-UT-1 cells using the anti-MEF2D and the anti-HDAC4 antibodies. Anti-FLAG antibody was used as control. <i>TK</i> promoter was used as negative control. The MEF2 binding site, the amplified region and the TSS are indicated for each tested gene, respectively with a vertical arrow, two arrowheads and a horizontal arrow. The TK promoter was used as negative control.</p

HDAC4 and HDAC9 KO in SK-UT-1 cells.

<p>A) Immunoblot analysis of HDAC4, HDAC9 and MEF2D in the indicated SK-UT-1 clones. Two different HDAC9 KO clones were selected. Actin was used as loading control. B) mRNA expression levels of the indicated atypical and classical MEF2-target genes in SK-UT-1 cells WT or KO for HDAC9. Data are presented as mean ± SD; n = 3. C) Turkey box-plots illustrating the mRNA expression levels of classical and atypical MEF2-target genes in SK-UT-1 cells WT or KO for HDAC9. Dunn's Multiple Comparison Test was applied to test the significance. D) Immunoblot analysis of HDAC4 and HDAC9 in the indicated SK-UT-1 clones. Two different HDAC4 KO clones generated by different sgRNAs were selected. Actin was used as loading control. E) mRNA expression levels of the indicated atypical and classical MEF2-target genes in SK-UT-1 cells WT or KO for HDAC4. Data are presented as mean ± SD; n = 3. F) Turkey box-plots illustrating the mRNA expression levels of classical and atypical MEF2-target genes in SK-UT-1 cells WT or KO for HDAC4. Dunn's Multiple Comparison Test was applied to test the significance. G) Invasion properties of the SK-UT-1 cells WT, KO for HDAC4 or KO for HDAC9, as indicated. Data are presented as mean ± SD; n = 4. H) Example of growth in soft agar of SK-UT-1 cells WT or KO for HDAC9. Foci were stained with MTT. I) Quantitative results of colony formation assay for SK-UT-1 cells WT, KO for HDAC4 or KO for HDAC9, as indicated. Data are presented as mean ± SD; n ≥ 3. * p < 0.05, ** p < 0.01, *** p < 0.001</p