The Prognostic Value of Lysine Acetylation Regulators in Hepatocellular Carcinoma

A novel mitochondrial unfolded protein response-related risk signature to predict prognosis, immunotherapy and sorafenib sensitivity in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common cause of cancer-associated death worldwide. The mitochondrial unfolded protein response (UPRmt) not only maintains mitochondrial integrity but also regulates cancer progression and drug resistance. However, no study has used the UPRmt to construct a prognostic signature for HCC. This work aimed to establish a novel signature for predicting patient prognosis, immune cell infiltration, immunotherapy, and chemotherapy response based on UPRmt-related genes (MRGs). Transcriptional profiles and clinical information were obtained from the TCGA and ICGC databases. Cox regression and LASSO regression analyses were applied to select prognostic genes and develop a risk model. The TIMER algorithm was used to investigate immunocytic infiltration in the high- and low-risk subgroups. Here, two distinct clusters were identified with different prognoses, immune cell infiltration statuses, drug sensitivities, and response to immunotherapy. A risk score consisting of seven MRGs (HSPD1, LONP1, SSBP1, MRPS5, YME1L1, HDAC1 and HDAC2) was developed to accurately and independently predict the prognosis of HCC patients. Additionally, the expression of core MRGs was confirmed by immunohistochemistry (IHC) staining, single-cell RNA sequencing, and spatial transcriptome analyses. Notably, the expression of prognostic MRGs was significantly correlated with sorafenib sensitivity in HCC and markedly downregulated in sorafenib-treated HepG2 and Huh7 cells. Furthermore, the knockdown of LONP1 decreased the proliferation, invasion, and migration of HepG2 cells, suggesting that upregulated LONP1 expression contributed to the malignant behaviors of HCC cells. To our knowledge, this is the first study to investigate the consensus clustering algorithm, prognostic potential, immune microenvironment infiltration and drug sensitivity based on the expression of MRGs in HCC. In summary, the UPRmt-related classification and prognostic signature could assist in determining the prognosis and personalized therapy of HCC patients from the perspectives of predictive, preventative and personalized medicine.

HDAC11: A novel target for improved cancer therapy

Histone deacetylase 11 (HDAC11) is a unique member of the histone deacetylase family that plays an important role in the regulation of gene expression and protein function. In recent years, research on the role of HDAC11 in tumors has attracted increasing attention. This review summarizes the current knowledge on the subcellular localization, structure, expression, and functions of HDAC11 in tumors, as well as the regulatory mechanisms involved in its network, including ncRNA and substrates. Moreover, we focus on the progress made in targeting HDAC11 to overcome tumor therapy resistance, and the development of HDAC11 inhibitors for cancer treatment. Collectively, this review provides comprehensive insights into the potential clinical implications of HDAC11 for cancer therapy.

COMMD4 is a novel prognostic biomarker and relates to potential drug resistance mechanism in glioma

Background: Glioma as the most frequently discovered tumor affecting the brain shows significant morbidity and fatality rates with unfavorable prognosis. There is an urgent need to find novel therapeutic targets to overcome the low chemotherapeutic efficacy of glioma. This research examined whether the copper-metabolism-domain protein, COMMD4, had predictive and therapeutic significance in glioma.

Methods: Using the freely accessible CGGA (The Chinese Glioma Atlas) and TCGA (The Cancer Genome Atlas) databases, we examined the function of COMMD4 in GBM and LGG. CIBERSORT and TIMER were utilized to assess the associations between COMMD4 and immune cells. The Gene Set Enrichment Analysis (GSEA) was employed to examine the functional data. Furthermore, the link between COMMD4 expression and predicted treatment response was evaluated via CellMiner Cross-Database. Meanwhile, qRT-PCR was conducted to examine COMMD4 expression in human glioma. Finally, Migration and invasion of glioma cells (U-87, U-251) were assessed using transwell assays. R was used to analyze the statistical data.

Results: According to our findings, COMMD4 expression level was higher in patients having grade-dependent glioma who also showed an unfavorable prognosis. Furthermore, qRT-PCR confirmed the high expression of COMMD4 in glioma tissues and cells. Additionally, using integrated correlation analysis, we acquired significant prognostic findings between isocitrate dehydrogenase 1(IDH1) and COMMD4. Meanwhile, a link between COMMD4 and many tumor-infiltrating immune cells was observed. GSEA and drug response analysis revealed the potential mechanism of COMMD4 in drug resistance of glioma.

Conclusion: The current findings validated COMMD4 as a novel biological marker, which might offer insights into the possible drug resistance mechanisms and the impact of the immune microenvironment on glioma. COMMD4 might be used to predict glioma prognosis.

TTC7B Is a Novel Prognostic-Related Biomarker in Glioma Correlating with Immune Infiltrates and Response to Oxidative Stress by Temozolomide

Background

Gliomas are one of the most prevalent malignant brain tumors. Hence, identifying biological markers for glioma is imperative. TTC7B (Tetratricopeptide Repeat Domain 7B) is a gene whose role in cancer in currently identified. To this end, we examined the TTC7B expression as well as its prognostic significance, biological roles, and immune system impacts in patients with glioma.

Methods

We evaluated the function of TTC7B in GBM and LGG through the published CGGA (Chinese Glioma Genome Atlas) and TCGA (The Cancer Genome Atlas) databases. CIBERSORT and TIMER were used to analyze the link between TTC7B and immune cells, while R was used for statistical analysis. In addition, Transwell analysis, including migration and invasion assays, was performed to identify the relationship between TTC7B and temozolomide.

Results

Low expression of TTC7B was observed in GBM and LGG. 1p/19q codeletion, IDH mutation, chemotherapy, and grade were found to have a significant correlation with TTC7B. Besides, low TTC7B expression was linked with low overall survival (OS) in both GBM and LGG. In the Cox analysis, TTC7B was found to independently function as a risk element for OS of patients with glioma. Furthermore, CIBERSORT analysis demonstrated a positive link between TTC7B and multiple immune cells, especially activated NK cells. Transwell analysis, including migration and invasion assays, revealed that temozolomide reduced the migration and invasion capacity of glioma cells and increased the expression of TTC7B.

Conclusion

In all, TTC7B could serve as a promising prognostic indicator of LGG and GBM, and is closely associated with immune infiltration and response to oxidative stress by temozolomide.

Identification of a novel histone phosphorylation prognostic signature in hepatocellular carcinoma based on bulk and single-cell RNA sequencing

BACKGROUND

Hepatocellular carcinoma (HCC) is the third leading cause of death in the world, characterized by high morbidity, poor prognosis and high mortality. Histone modifications regulate intracellular gene expression at the post-transcriptional level, and disturbances in the regulatory pattern of histone modifications at individual locus or across the genome can lead to tumorigenesis of HCC. In this study, we constructed a prognosis-related histone phosphorylation regulated (HPR) genes signature and elucidated whether HPR genes can predict overall survival in HCC patients.

METHODS

Differentially expressed genes were screened using TCGA, ICGC and GEO databases, and a new risk signature was constructed by univariate Cox regression and Lasso regression analysis. Predictive nomograms were established by multivariate Cox regression of risk scores and clinical parameters, calibration curve and decision curve analysis were used to evaluate the models. The ssGSEA methods were used to determine the effect of risk scores on the tumor immune microenvironment. Data for HCC single-cell RNA sequencing (scRNA-seq) have been downloaded from Gene Expression Omnibus (GEO) to understand the role of HPR genes in tumorigenesis.

RESULTS

Our analyses of nine HPR genes provided prognostic insights. Overall survival in the low-risk and high-risk groups was statistically higher, respectively (P<0.001). Cox regression analysis revealed that the risk score is a significant predictor of HCC outcomes (HR=2. 2.62, 95%CI: 1.248-5.514, P=0.011). In addition, a nomogram combining risk scores with TNM stages was constructed and tested from calibration curves and decision curves (AUC=0.780). MHC-class-I genes, iDCs, Macrophages, Tfh, Treg, Th2 were overexpressed in the high-risk group.

CONCLUSION

HPR genes risk score is closely related to the prognosis of HCC, tumor immune process and tumor cell progression.