OLR1 is a prognostic factor and correlated with immune infiltration in breast cancer

Histone Lysine Lactylation (Kla)-induced BCAM Promotes OSCC Progression and Cis-Platinum Resistance

OBJECTIVE

Histone lysine lactylation (Kla) plays a vital role in cancer progression. However, the prognostic value of histone Kla in oral squamous cell carcinoma (OSCC) remains unclear.

MATERIALS AND METHODS

OSCC RNA expression data were obtained from the TCGA and GEO databases. We explored the prognostic value of histone Kla in OSCC via constructing a Cox model and determined the role of Kla in OSCC drug susceptibility and tumor microenvironment (TME). In addition, the biological roles of candidate biomarkers were identified.

RESULTS

A total of 1223 Kla-specific genes were obtained, with 228 DEKlaGs in OSCC. GO and KEGG enrichment analyses suggested that DEKlaGs contributed to inflammatory and cancer progression. A Cox model in accordance with BCAM, CGNL1, DGKG, and OLR1 could predict OSCC patient prognosis accurately. Subsequently, Kla-induced prognostic genes were identified to play a crucial role in OSCC drug therapy and TME. Moreover, BCAM was identified as a biomarker that promoted OSCC invasion, angiogenesis, and chemotherapy resistance.

CONCLUSION

Kla was identified to be associated with OSCC prognosis, drug therapy, and TME. Histone Kla-induced BCAM was identified to play a crucial role during OSCC progression, suggesting that Kla is promising to be a novel therapeutic target for OSCC.

Lipid metabolic reprograming: the unsung hero in breast cancer progression and tumor microenvironment

Aberrant lipid metabolism is a well-recognized hallmark of cancer. Notably, breast cancer (BC) arises from a lipid-rich microenvironment and depends significantly on lipid metabolic reprogramming to fulfill its developmental requirements. In this review, we revisit the pivotal role of lipid metabolism in BC, underscoring its impact on the progression and tumor microenvironment. Firstly, we delineate the overall landscape of lipid metabolism in BC, highlighting its roles in tumor progression and patient prognosis. Given that lipids can also act as signaling molecules, we next describe the lipid signaling exchanges between BC cells and other cellular components in the tumor microenvironment. Additionally, we summarize the therapeutic potential of targeting lipid metabolism from the aspects of lipid metabolism processes, lipid-related transcription factors and immunotherapy in BC. Finally, we discuss the possibilities and problems associated with clinical applications of lipid‑targeted therapy in BC, and propose new research directions with advances in spatiotemporal multi-omics.

Harnessing machine learning technique to authenticate differentially expressed genes in oral squamous cell carcinoma

OBJECTIVE

Advancements in early detection of the disease, prognosis and the development of therapeutic strategies necessitate tumor-specific biomarkers. Despite continuous efforts, no molecular marker has been proven to be an effective therapeutic tool for the early detection of cancer. The study aims to determine diagnostic and prognostic signature genes that may be involved in cancer pathology and hence, may serve as molecular markers.

STUDY DESIGN

Eight candidate genes were selected based on our prior study of transcriptomic sequencing and validated in 100 matched pair samples of oral squamous cell carcinoma (OSCC). We further utilized machine learning approaches and examined the diagnostic presentation and predictive ability of the OSCC genes retrieved from publicly available The Cancer Genome Atlas (TCGA) database and compared with our results.

RESULTS

We conducted qPCR analysis to validate the expression of each gene and observed that each gene was present in the majority of OSCC samples. The predictive ability of selected genes was stable (with an average accuracy of 84%) across different classifiers. However, on validation with our dataset, it showed 75% accuracy, which might be because of the demographic variation of the samples.

CONCLUSIONS

The present research outlines cancer-associated molecular biomarkers that might eventually contribute to an enhanced prognosis of cancer patient by identifying novel therapeutic targets.

Machine-learning derived identification of prognostic signature to forecast head and neck squamous cell carcinoma prognosis and drug response

Introduction

Head and neck squamous cell carcinoma (HNSCC), a highly heterogeneous malignancy is often associated with unfavorable prognosis. Due to its unique anatomical position and the absence of effective early inspection methods, surgical intervention alone is frequently inadequate for achieving complete remission. Therefore, the identification of reliable biomarker is crucial to enhance the accuracy of screening and treatment strategies for HNSCC.

Method

To develop and identify a machine learning-derived prognostic model (MLDPM) for HNSCC, ten machine learning algorithms, namely CoxBoost, elastic network (Enet), generalized boosted regression modeling (GBM), Lasso, Ridge, partial least squares regression for Cox (plsRcox), random survival forest (RSF), stepwise Cox, supervised principal components (SuperPC), and survival support vector machine (survival-SVM), along with 81 algorithm combinations were utilized. Time-dependent receiver operating characteristics (ROC) curves and Kaplan-Meier analysis can effectively assess the model's predictive performance. Validation was performed through a nomogram, calibration curves, univariate and multivariate Cox analysis. Further analyses included immunological profiling and gene set enrichment analyses (GSEA). Additionally, the prediction of 50% inhibitory concentration (IC50) of potential drugs between groups was determined.

Results

From analyses in the HNSCC tissues and normal tissues, we found 536 differentially expressed genes (DEGs). Subsequent univariate-cox regression analysis narrowed this list to 18 genes. A robust risk model, outperforming other clinical signatures, was then constructed using machine learning techniques. The MLDPM indicated that high-risk scores showed a greater propensity for immune escape and reduced survival rates. Dasatinib and 7 medicine showed the superior sensitivity to the high-risk NHSCC, which had potential to the clinical.

Conclusions

The construction of MLDPM effectively eliminated artificial bias by utilizing 101 algorithm combinations. This model demonstrated high accuracy in predicting HNSCC outcomes and has the potential to identify novel therapeutic targets for HNSCC patients, thus offering significant advancements in personalized treatment strategies.

Analysis of differentially expressed genes in dysplastic oral keratinocyte cell line and their role in the development of HNSCC

Dysplasia is the presence of abnormal types of cells in a tissue precipitated by over or diminished expression of certain genes. These cells act as a precursor to cancer. Dysplastic oral keratinocyte (DOK) cell lines have an aneuploid complex karyotype. They provide an opportunity to study the action of specific carcinogens on malignant transformations. This study aimed to identify the differentially expressed genes in dysplastic cells and their possible association with head and neck squamous cell carcinoma (HNSCC). These genes can be developed as diagnostic, prognostic, or therapeutic leads.The list of genes related to oral keratinocyte dysplasia and head and neck cancer was accessed from the GEO (Gene Expression Omnibus) database. Gene expression profiling was done between dysplastic oral keratinocytes and normal human oral keratinocytes. Gene expression and Kaplan Meier survival analysis were performed using the UALCAN database to assess the correlations between dysregulated genes identified in dysplastic keratinocytes and primary tumors of HNSCC. The GEO omnibus dataset identified numerous differentially expressed genes of which the top 10 up and downregulated genes in dysplastic oral keratinocytes were curated for further analysis. The expression profile of these genes was assessed using the HNSCC dataset (TCGA, Firehose Legacy). Among all the genes assessed, only one gene, the OLR1 gene encoding oxidized low-density lipoprotein, was found to be overexpressed in both the groups viz., dysplastic keratinocytes and HNSCC cases with a strong correlation with the survival status of patients. There was significant correlation between the gene expression pattern observed in dysplastic keratinocytes and the primary tumor of the HNSCC group, with an exotic gene that was seldom discussed in association with cancer, viz., OLR1. Exploration into other top-ranking differentially expressed genes in dysplastic cases would aid in identifying the candidate gene associated with both phenotypes.

Revealing the crucial roles of suppressive immune microenvironment in cardiac myxoma progression

Cardiac myxoma is a commonly encountered tumor within the heart that has the potential to be life-threatening. However, the cellular composition of this condition is still not well understood. To fill this gap, we analyzed 75,641 cells from cardiac myxoma tissues based on single-cell sequencing. We defined a population of myxoma cells, which exhibited a resemblance to fibroblasts, yet they were distinguished by an increased expression of phosphodiesterases and genes associated with cell proliferation, differentiation, and adhesion. The clinical relevance of the cell populations indicated a higher proportion of myxoma cells and M2-like macrophage infiltration, along with their enhanced spatial interaction, were found to significantly contribute to the occurrence of embolism. The immune cells surrounding the myxoma exhibit inhibitory characteristics, with impaired function of T cells characterized by the expression of GZMK and TOX, along with a substantial infiltration of tumor-promoting macrophages expressed growth factors such as PDGFC. Furthermore, in vitro co-culture experiments showed that macrophages promoted the growth of myxoma cells significantly. In summary, this study presents a comprehensive single-cell atlas of cardiac myxoma, highlighting the heterogeneity of myxoma cells and their collaborative impact on immune cells. These findings shed light on the complex pathobiology of cardiac myxoma and present potential targets for intervention.

Revealing the characteristics of SETD2-mutated clear cell renal cell carcinoma through tumor heterogeneity analysis

Background

Renal cell carcinoma (RCC) is the most prevalent type of malignant kidney tumor in adults, with clear cell renal cell carcinoma (ccRCC) comprising about 75% of all cases. The SETD2 gene, which is involved in the modification of histone proteins, is often found to have alterations in ccRCC. Yet, our understanding of how these SETD2 mutations affect ccRCC characteristics and behavior within the tumor microenvironment is still not fully understood.

Methods

We conducted a detailed analysis of single-cell RNA sequencing (scRNA-seq) data from ccRCC. First, the data was preprocessed using the Python package, "scanpy." High variability genes were pinpointed through Pearson's correlation coefficient. Dimensionality reduction and clustering identification were performed using Principal Component Analysis (PCA) and the Leiden algorithm. Malignant cell identification was conducted with the "InferCNV" R package, while cell trajectories and intercellular communication were depicted using the Python packages "VIA" and "cellphoneDB." We then employed the R package "Deseq2" to determine differentially expressed genes (DEGs) between groups. Using high-dimensional weighted gene correlation network analysis (hdWGCNA), co-expression modules were identified. We intersected these modules with DEGs to establish prognostic models through univariate Cox and the least absolute shrinkage and selection operator (LASSO) method.

Results

We identified 69 and 53 distinctive cell clusters, respectively. These were classified further into 12 unique cell types. This analysis highlighted the presence of an abnormal tumor sub-cluster (MT + group), identified by high mitochondrial-encoded protein gene expression and an indication of unfavorable prognosis. Investigation of cellular interactions spotlighted significant interactions between the MT + group and endothelial cells, macrophaes. In addition, we developed a prognostic model based on six characteristic genes. Notably, risk scores derived from these genes correlated significantly with various clinical features. Finally, a nomogram model was established to facilitate more accurate outcome prediction, incorporating four independent risk factors.

Conclusion

Our findings provide insight into the crucial transcriptomic characteristics of ccRCC associated with SETD2 mutation. We discovered that this mutation-induced subcluster could stimulate M2 polarization in macrophages, suggesting a heightened propensity for metastasis. Moreover, our prognostic model demonstrated effectiveness in forecasting overall survival for ccRCC patients, thus presenting a valuable clinical tool.

PRRX1-OLR1 axis supports CAFs-mediated lung cancer progression and immune suppression

OBJECTIVE

To investigate the mechanism by which cancer-associated fibroblasts (CAFs) affect the growth and immune evasion of lung cancer cells.

METHODS

Initially, datasets comparing CAFs with normal fibroblasts were downloaded from the GEO dataset GSE48397. Genes with the most significant differential expression were selected and validated using clinical data. Subsequently, CAFs were isolated, and the selected genes were knocked down in CAFs. Co-culture experiments were conducted with H1299 or A549 cells to analyze changes in lung cancer cell growth, migration, and immune evasion in vitro and in vivo. To further elucidate the upstream regulatory mechanism, relevant ChIP-seq data were downloaded from the GEO database, and the regulatory relationships were validated through ChIP-qPCR and luciferase reporter assays.

RESULTS

OLR1 was significantly overexpressed in CAFs and strongly correlated with adverse prognosis in lung cancer patients. Knockdown of OLR1 markedly inhibited CAFs' support for the growth and immune evasion of lung cancer cells in vitro and in vivo. ChIP-seq results demonstrated that PRRX1 can promote OLR1 expression by recruiting H3K27ac and H3K4me3, thereby activating CAFs. Knockdown of PRRX1 significantly inhibited CAFs' function, while further overexpression of OLR1 restored CAFs' support for lung cancer cell growth, migration, and immune evasion.

CONCLUSION

PRRX1 promotes OLR1 expression by recruiting H3K27ac and H3K4me3, activating CAFs, and thereby promoting the growth, migration, and immune evasion of lung cancer cells.

The association between oxidized low-density lipoprotein and cancer: An emerging targeted therapeutic approach?

Lipids play an important role in varying vital cellular processes including cell growth and division. Elevated levels of low-density lipoprotein (LDL) and oxidized-LDL (ox-LDL), and overexpression of the corresponding receptors including LDL receptor (LDLR), lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1), and cluster of differentiation 36 (CD36), have shown strong correlations with different facets of carcinogenesis including proliferation, invasion, and angiogenesis. Furthermore, a high serum level of LOX-1 is considered as a poor prognostic factor in many types of cancer including colorectal cancer. Ox-LDL could contribute to cancer progression and metastasis through endothelial-to-mesenchymal transition (EMT) and autophagy. Thus, many studies have shed light on the significant role of ox-LDL as a potential therapeutic target for cancer therapy. In various repurposing approaches, anti-dyslipidemia agents, phytochemicals, autophagy modulators as well as recently developed ldl-like nanoparticles have been investigated as potential tumor therapeutic agents by targeting oxidized-LDL/LOX-1 pathways. Herein, we reviewed the role of oxidized-LDL and LOX-1 in cancer progression, invasion, metastasis, and also cancer-associated angiogenesis. Moreover, we addressed therapeutic utility of several compounds that proved to be capable of targeting the metabolic moieties in cancer. This review provides insights on the potential impact of targeting LDL and ox-LDL in cancer therapy and their future biomedical implementations.

Unveiling promising breast cancer biomarkers: an integrative approach combining bioinformatics analysis and experimental verification

BACKGROUND

Breast cancer remains a significant health challenge worldwide, necessitating the identification of reliable biomarkers for early detection, accurate prognosis, and targeted therapy.

MATERIALS AND METHODS

Breast cancer RNA expression data from the TCGA database were analyzed to identify differentially expressed genes (DEGs). The top 500 up-regulated DEGs were selected for further investigation using random forest analysis to identify important genes. These genes were evaluated based on their potential as diagnostic biomarkers, their overexpression in breast cancer tissues, and their low median expression in normal female tissues. Various validation methods, including online tools and quantitative Real-Time PCR (qRT-PCR), were used to confirm the potential of the identified genes as breast cancer biomarkers.

RESULTS

The study identified four overexpressed genes (CACNG4, PKMYT1, EPYC, and CHRNA6) among 100 genes with higher importance scores. qRT-PCR analysis confirmed the significant upregulation of these genes in breast cancer patients compared to normal samples.

CONCLUSIONS

These findings suggest that CACNG4, PKMYT1, EPYC, and CHRNA6 may serve as valuable biomarkers for breast cancer diagnosis, and PKMYT1 may also have prognostic significance. Furthermore, CACNG4, CHRNA6, and PKMYT1 show promise as potential therapeutic targets. These findings have the potential to advance diagnostic methods and therapeutic approaches for breast cancer.

Clinical significance and immune landscape of angiogenesis-related genes in bladder cancer

BACKGROUND

Angiogenesis is a major promotor of tumor progression and metastasis. Nevertheless, it is undetermined how angiogenesis-related genes (ARGs) influence bladder cancer.

METHODS

The profiles of bladder cancer gene expression were collected from the TCGA-BLCA cohort. The LASSO regression analysis was used to build an angiogenesis-related signature (ARG_score) with the prognostic ARGs. Verification analyses were conducted across the GSE48075 dataset to demonstrate the robustness of the signature. Differences between the two risk groups based on clinical outcomes, immune landscape, mutation status, chemotherapeutic effectiveness for anticancer drugs, and immunotherapy efficacy were analyzed. A nomogram was developed to improve the clinical efficacy of this predictive tool. The expression levels of model genes in normal bladder epithelial cell lines (SV-HUC-1) and bladder cancer cell lines (T24 and 5637) were detected by qRT-PCR assay.

RESULTS

Four angiogenesis-associated gene signature was constructed based on the LASSO regression algorithm. The signature showed independent risk factors of overall survival for bladder cancer, validated using two external survival datasets. Additionally, we built a prognostic nomogram to improve the practicality of the ARG_score. High-risk individuals showed stronger immunocyte infiltration, immune-related functions, elevated expression of immune checkpoints, reduced TIDE score, and higher combined IPS-PD-1 and IPS-CTLA4 scores, suggesting a heightened responsiveness to immune checkpoint inhibitors. Furthermore, patients with low and high risk showed distinct responsiveness to anticancer drugs. The expression levels of 5 model genes (COL5A2, JAG1, MSX1, OLR1, and STC) were significantly increased in bladder cancer cell lines (T24 and 5637) compared with the normal bladder epithelial cell line SV-HUC-1.

CONCLUSIONS

The model constructed based on ARGs may have wide application in predicting outcomes and therapeutic responses.

Organotypic 3D Cell-Architecture Impacts the Expression Pattern of miRNAs-mRNAs Network in Breast Cancer SKBR3 Cells

BACKGROUND

Currently, most of the research on breast cancer has been carried out in conventional two-dimensional (2D) cell cultures due to its practical benefits, however, the three-dimensional (3D) cell culture is becoming the model of choice in cancer research because it allows cell-cell and cell-extracellular matrix (ECM) interactions, mimicking the native microenvironment of tumors in vivo.

METHODS

In this work, we evaluated the effect of 3D cell organization on the expression pattern of miRNAs (by Small-RNAseq) and mRNAs (by microarrays) in the breast cancer SKBR3 cell line and analyzed the biological processes and signaling pathways regulated by the differentially expressed protein-coding genes (DE-mRNAs) and miRNAs (DE-microRNAs) found in the organoids.

RESULTS

We obtained well-defined cell-aggregated organoids with a grape cluster-like morphology with a size up to 9.2 × 105 μm3. The transcriptomic assays showed that cell growth in organoids significantly affected (all p < 0.01) the gene expression patterns of both miRNAs, and mRNAs, finding 20 upregulated and 19 downregulated DE-microRNAs, as well as 49 upregulated and 123 downregulated DE-mRNAs. In silico analysis showed that a subset of 11 upregulated DE-microRNAs target 70 downregulated DE-mRNAs. These genes are involved in 150 gene ontology (GO) biological processes such as regulation of cell morphogenesis, regulation of cell shape, regulation of canonical Wnt signaling pathway, morphogenesis of epithelium, regulation of cytoskeleton organization, as well as in the MAPK and AGE-RAGE signaling KEGG-pathways. Interestingly, hsa-mir-122-5p (Fold Change (FC) = 15.4), hsa-mir-369-3p (FC = 11.4), and hsa-mir-10b-5p (FC = 20.1) regulated up to 81% of the 70 downregulated DE-mRNAs.

CONCLUSION

The organotypic 3D cell-organization architecture of breast cancer SKBR3 cells impacts the expression pattern of the miRNAs-mRNAs network mainly through overexpression of hsa-mir-122-5p, hsa-mir-369-3p, and hsa-mir-10b-5p. All these findings suggest that the interaction between cell-cell and cell-ECM as well as the change in the culture architecture impacts gene expression, and, therefore, support the pertinence of migrating breast cancer research from conventional cultures to 3D models.

OLR1 Is a Pan-Cancer Prognostic and Immunotherapeutic Predictor Associated with EMT and Cuproptosis in HNSCC

Metabolism plays a critical role in cancer. OLR1 has been implicated in cardiovascular and metabolic disorders, while its association with tumorigenesis and tumor immunity remains poorly defined in the literature. We conducted comprehensive pan-cancer analyses based on the TCGA database to examine OLR1 expression and its prognostic implications. Correlations between OLR1 expression level and tumor immunity and immunotherapy were investigated by immune infiltration, enrichment, and TIDE analysis methods. Immunohistochemistry detected OLR1 expression in HNSCC. We used the GSEA method to explore the potential signaling pathways in which OLR1 is involved, and a correlation analysis to investigate the relationships between OLR1 and epithelial-mesenchymal transition (EMT) and cuproptosis. In addition, the effects of OLR1 knockdown on the EMT process, invasion, stemness, and cuproptosis of HNSCC cells were examined by scratch, Transwell, CCK8, sphere formation, and flow cytometry, while changes in related proteins were detected using the immunoblotting method. OLR1 is highly expressed in most cancers, and it is associated with patient prognosis. OLR1 expression positively correlates with immunosuppressive cell infiltration and immune checkpoint molecules, while being negatively associated with effector T cells. Moreover, significant correlations are observed between OLR1 expression and tumor mutation burden (TMB) and microsatellite instability (MSI) in some cancers. In HNSCC, OLR1 expression is related to advanced clinicopathological factors and unfavorable outcomes. Patients with high OLR1 expression levels are prone to experience immune escape and benefit less from immune checkpoint inhibitor (ICI) therapy. Moreover, OLR1 expression may affect EMT, stemness, and cuproptosis resistance outcomes. OLR1 is an immune-related prognostic biomarker with potential as a prognostic indicator for immunotherapy, and it may also be involved in regulating the EMT process and cuproptosis in HNSCC.

Exploring scavenger receptor class F member 2 and the importance of scavenger receptor family in prediagnostic diseases

Scavenger Receptor Class F Member 2 (SCARF2), also known as the Type F Scavenger Receptor Family gene, encodes for Scavenger Receptor Expressed by Endothelial Cells 2 (SREC-II). This protein is a crucial component of the scavenger receptor family and is vital in protecting mammals from infectious diseases. Although research on SCARF2 is limited, mutations in this protein have been shown to cause skeletal abnormalities in both SCARF2-deficient mice and individuals with Van den Ende-Gupta syndrome (VDEGS), which is also associated with SCARF2 mutations. In contrast, other scavenger receptors have demonstrated versatile responses and have been found to aid in pathogen elimination, lipid transportation, intracellular cargo transportation, and work in tandem with various coreceptors. This review will concentrate on recent progress in comprehending SCARF2 and the functions played by members of the Scavenger Receptor Family in pre-diagnostic diseases.

Anti-Inflammatory Activity of Black Soldier Fly Oil Associated with Modulation of TLR Signaling: A Metabolomic Approach

Dietary intervention in the treatment of ulcerative colitis involves, among other things, modifications in fatty acid content and/or profile. For example, replacing saturated long chain fatty acids with medium chain fatty acids (MCFAs) has been reported to ameliorate inflammation. The Black Soldier Fly Larvae's (BSFL) oil is considered a sustainable dietary ingredient rich in the MCFA C12:0; however, its effect on inflammatory-related conditions has not been studied until now. Thus, the present study aimed to investigate the anti-inflammatory activity of BSFL oil in comparison to C12:0 using TLR4- or TLR2-activated THP-1 and J774A.1 cell lines and to assess its putative protective effect against dextran sulfate sodium (DSS)-induced acute colitis in mice. BSFL oil and C12:0 suppressed proinflammatory cytokines release in LPS-stimulated macrophages; however, only BSFL oil exerted anti-inflammatory activity in Pam3CSK4-stimulated macrophages. Transcriptome analysis provided insight into the possible role of BSFL oil in immunometabolism switch, involving mTOR signaling and an increase in PPAR target genes promoting fatty acid oxidation, exhibiting a discrepant mode of action compared to C12:0 treatment, which mainly affected cholesterol biosynthesis pathways. Additionally, we identified anti-inflammatory eicosanoids, oxylipins, and isoprenoids in the BSFL oil that may contribute to an orchestrated anti-inflammatory response. In vivo, a BSFL oil-enriched diet (20%) ameliorated the clinical signs of colitis, as indicated by improved body weight recovery, reduced colon shortening, reduced splenomegaly, and an earlier phase of secretory IgA response. These results indicate the novel beneficial use of BSFL oil as a modulator of inflammation.

Manipulating Histone Acetylation Leads to Antitumor Effects in Hemangiosarcoma Cells

Canine hemangiosarcoma (HSA) is a malignant tumor derived from endothelial cells. No effective treatment has yet been developed because of the lack of understanding of its pathogenesis. Histone acetylation, an epigenetic modification, is highly associated with cancer pathogenesis. Manipulating histone acetylation by histone deacetylase inhibitors (HDACi) or bromodomain and extraterminal domain inhibitors (BETi) is one approach to treat various cancers. However, the role of histone acetylation in HSA remains unknown. This study aimed to investigate how histone acetylation functions in HSA pathogenesis using two HDACi, suberanilohydroxamic acid (SAHA) and valproic acid (VPA), and one BETi, JQ1, in vitro and in vivo. Histone acetylation levels were high in cell lines and heterogeneous in clinical cases. SAHA and JQ1 induced apoptosis in HSA cell lines. HSA cell lines treated with SAHA and VPA upregulated inflammatory-related genes and attracted macrophage cell line RAW264 cells, which suggests that SAHA and VPA can affect immune responses. JQ1 stimulated autophagy and inhibited the cell cycle in HSA cell lines. Finally, we demonstrated that JQ1 suppressed HSA tumor cell proliferation in vivo although SAHA and VPA did not affect tumor growth. These results suggest that BETi can be alternative drugs for HSA treatment. Although further research is required, our study indicated that dysregulation of histone acetylation is likely to be involved in HSA malignancy. This article is protected by copyright. All rights reserved.