Lack of MOF Decreases Susceptibility to Hypoxia and Promotes Multidrug Resistance in Hepatocellular Carcinoma via HIF-1α

The histone acetyltransferase Mof regulates Runx2 and Osterix for osteoblast differentiation

Osteoblast differentiation is regulated by various transcription factors, signaling molecules, and posttranslational modifiers. The histone acetyltransferase Mof (Kat8) is involved in distinct physiological processes. However, the exact role of Mof in osteoblast differentiation and growth remains unknown. Herein, we demonstrated that Mof expression with histone H4K16 acetylation increased during osteoblast differentiation. Inhibition of Mof by siRNA knockdown or small molecule inhibitor, MG149 which is a potent histone acetyltransferase inhibitor, reduced the expression level and transactivation potential of osteogenic key markers, Runx2 and Osterix, thus inhibiting osteoblast differentiation. Besides, Mof overexpression also enhanced the protein levels of Runx2 and Osterix. Mof could directly bind the promoter region of Runx2/Osterix to potentiate their mRNA levels, possibly through Mof-mediated H4K16ac to facilitate the activation of transcriptional programs. Importantly, Mof physically interacts with Runx2/Osterix for the stimulation of osteoblast differentiation. Yet, Mof knockdown showed indistinguishable effect on cell proliferation or apoptosis in MSCs and preosteoblast cells. Taken together, our results uncover Mof functioning as a novel regulator of osteoblast differentiation via the promotional effects on Runx2/Osterix and rationalize Mof as a potential therapeutic target, like possible application of inhibitor MG149 for the treatment of osteosarcoma or developing specific Mof activator to ameliorate osteoporosis.

MOF negatively regulates estrogen receptor α signaling via CUL4B-mediated protein degradation in breast cancer

Estrogen receptor α (ERα) is the dominant tumorigenesis driver in breast cancer (BC), and ERα-positive BC (ERα+ BC) accounts for more than two-thirds of BC cases. MOF (males absent on the first) is a highly conserved histone acetyltransferase that acetylates lysine 16 of histone H4 (H4K16) and several non-histone proteins. Unbalanced expression of MOF has been identified, and high MOF expression predicted a favorable prognosis in BC. However, the association of MOF with ERα and the regulatory mechanisms of MOF in ERα signaling remain elusive. Our study revealed that the expression of MOF is negatively correlated with that of ERα in BC. In ERα+ BC cells, MOF overexpression downregulated the protein abundance of ERα in both cytoplasm and nucleus, thus attenuating ERα-mediated transactivation as well as cellular proliferation and in vivo tumorigenicity of BC cells. MOF promoted ERα protein degradation through CUL4B-mediated ubiquitin–proteasome pathway and induced HSP90 hyperacetylation that led to the loss of chaperone protection of HSP90 to ERα. We also revealed that suppression of MOF restored ERα expression and increased the sensitivity of ERα-negative BC cells to tamoxifen treatment. These results provide a new insight into the tumor-suppressive role of MOF in BC via negatively regulating ERα action, suggesting that MOF might be a potential therapeutic target for BC.

Gene regulation by histone-modifying enzymes under hypoxic conditions: a focus on histone methylation and acetylation

Oxygen, which is necessary for sustaining energy metabolism, is consumed in many biochemical reactions in eukaryotes. When the oxygen supply is insufficient for maintaining multiple homeostatic states at the cellular level, cells are subjected to hypoxic stress. Hypoxia induces adaptive cellular responses mainly through hypoxia-inducible factors (HIFs), which are stabilized and modulate the transcription of various hypoxia-related genes. In addition, many epigenetic regulators, such as DNA methylation, histone modification, histone variants, and adenosine triphosphate-dependent chromatin remodeling factors, play key roles in gene expression. In particular, hypoxic stress influences the activity and gene expression of histone-modifying enzymes, which controls the posttranslational modification of HIFs and histones. This review covers how histone methylation and histone acetylation enzymes modify histone and nonhistone proteins under hypoxic conditions and surveys the impact of epigenetic modifications on gene expression. In addition, future directions in this area are discussed.

New sequencing technologies are revealing how cells respond to hypoxia, insufficient oxygen, by managing gene activation. In multicellular organisms, gene activation is managed by how tightly a section of DNA is wound around proteins called histones; genes in tightly packed regions are inaccessible and inactive, whereas those in looser regions can be activated. Kyunghwan Kim, Sun-Ju Yi, and co-workers at Chungbuk National University in South Korea have reviewed recent data on how cells regulate gene activity under hypoxic conditions. Advances in sequencing technology have allowed genome-wide studies of how hypoxia affects DNA structure and gene activation, revealing that gene-specific modifications may be more important than genome-wide modifications. Hypoxia is implicated in several diseases, such as cancer and chronic metabolic diseases, and a better understanding of how it affects gene activation may help identify new treatments for hypoxia-related diseases.

New progress in the mechanism of microenvironment-driven chemoradiotherapy resistance in digestive system tumors

Tumor microenvironment (TME) is the cornerstone of the survival of tumor cells. It generally presents unique physical and chemical characteristics such as hypoxia, immunosuppression, metabolic reprogramming, and matrix stiffening, which not only offer suitable soil to support tumorigenesis and progression, but also resist the effects of radiotherapy and chemotherapy. Here, we summarize new progress in the mechanism of hypoxia, immunosuppression, metabolic reprogramming, and matrix stiffness-driven chemoradiotherapy resistance in digestive system tumors, and discuss the new intervention strategy against matrix stiffness-driven chemoradiotherapy resistance, which underlines the contribution of physical and chemical characteristics of tumor microenvironment in drug resistance.

Correlations between DWI, IVIM, and HIF-1α expression based on MRI and pathology in a murine model of rhabdomyosarcoma

PURPOSE

To investigate the correlation between DWI, intravoxel incoherent motion (IVIM), and hypoxia-inducible factor 1-alpha (HIF-1α) expression in a nude mouse model of rhabdomyosarcoma based on imaging and pathological comparisons.

METHODS

Human rhabdomyosarcoma-derived (RD) cells were inoculated into the right thigh muscle of 20 BALB/c female nude mice. Mice were imaged using 3.0 Tesla MRI system. T₁ -weighted imaging, T₂ -weighted imaging, DWI, and IVIM images were obtained. ADW4.7 (GE Healthcare, ChicagoAQ34, IL, USA) was used for image processing of ADC, D_slow , D_fast , and f values. All parameter values were independently analyzed by 2 observers. Immunohistochemistry of HIF-1α was performed. We used a specific image-pathology comparison method to ensure correct overlap between the image plane and the pathological section. Mann-Whitney U test or independent sample t test, Pearson or Spearman correlation test, the intragroup correlation coefficient, Kolmogorov-Smirnov test, and receiver operating characteristic curve were used. The correlation between DWI and intravoxel incoherent motion parameter values and HIF-1α expression was determined.

RESULTS

There were 10 mice in the low-expression group and 7 in the high-expression group. The ADC and D_slow values were negatively correlated with HIF-1α with correlation coefficients of -0.491 and - 0.702 (P = 0.045 and 0.002). The f value positively correlated with HIF-1α expression (r = 0.485, P = 0.048). ADC, D_slow , and f were significantly different between the high-HIF-1α expression tumors and the low-HIF-1α expression tumors. ADC showed the best predictive performance among all parameters (area under the curve = 0.652, sensitivity = 83.3%, specificity = 63.6%).

CONCLUSION

The parameter values of DWI and intravoxel incoherent motion can be used to evaluate the expression of HIF-1α in rhabdomyosarcoma. ADC, D_slow , and f value showed correlation with the expression of HIF-1α.