Carbohydrate Sulfotransferase 4 Inhibits the Progression of Hepatitis B Virus-Related Hepatocellular Carcinoma and Is a Potential Prognostic Marker in Several Tumors

CHST4 Gene as a Potential Predictor of Clinical Outcome in Malignant Pleural Mesothelioma

Malignant pleural mesothelioma (MPM) develops primarily from asbestos exposures and has a poor prognosis. In this study, The Cancer Genome Atlas was used to perform a comprehensive survival analysis, which identified the CHST4 gene as a potential predictor of favorable overall survival for patients with MPM. An enrichment analysis of favorable prognostic genes, including CHST4, showed immune-related ontological terms, whereas an analysis of unfavorable prognostic genes indicated cell-cycle-related terms. CHST4 mRNA expression in MPM was significantly correlated with Bindea immune-gene signatures. To validate the relationship between CHST4 expression and prognosis, we performed an immunohistochemical analysis of CHST4 protein expression in 23 surgical specimens from surgically treated patients with MPM who achieved macroscopic complete resection. The score calculated from the proportion and intensity staining was used to compare the intensity of CHST4 gene expression, which showed that CHST4 expression was stronger in patients with a better postoperative prognosis. The median overall postoperative survival was 107.8 months in the high-expression-score group and 38.0 months in the low-score group (p = 0.044, log-rank test). Survival after recurrence was also significantly improved by CHST4 expression. These results suggest that CHST4 is useful as a prognostic biomarker in MPM.

MDM4 was associated with poor prognosis and tumor-immune infiltration of cancers

MDM4 is one of the MDM protein family and is generally recognized as the key negative regulator of p53. As a cancer-promoting factor, it plays a non-negligible role in tumorigenesis and development. In this article, we analyzed the expression levels of MDM4 in pan-cancer through multiple databases. We also investigated the correlations between MDM4 expression and prognostic value, immune features, genetic mutation, and tumor-related pathways. We found that MDM4 overexpression is often accompanied by adverse clinical features, poor prognosis, oncogenic mutations, tumor-immune infiltration and aberrant activation of oncogenic signaling pathways. We also conducted transcriptomic sequencing to investigate the effect of MDM4 on transcript levels in colon cancer and performed qPCR to verify this. Finally, we carried out some in vitro experiments including colony formation assay, chemoresistance and senescence-associated β-galactosidase activity assay to study the anti-tumor treatment effect of small molecule MDM4 inhibitor, NSC146109. Our research confirmed that MDM4 is a prognostic biomarker and potential therapeutic target for a variety of malignancies.

CHST12: a potential prognostic biomarker related to the immunotherapy response in pancreatic adenocarcinoma

Background

Pancreatic adenocarcinoma (PAAD) is characterized by lower immunogenicity with a poor response rate to immune checkpoint inhibitors (ICIs) and exhibits the poorest prognosis of all solid tumors, which results in the highest tumor-related mortality among malignancies. However, the underlying mechanisms are poorly understood. In addition, diverse carbohydrate sulfotransferases (CHSTs), which are involved in the sulfation process of these structures, play an important role in the metastatic spread of tumor cells. Aberrant glycosylation is beginning to emerge as an influencing factor in tumor immunity and immunotherapy. Therefore, it might serve as a biomarker of the immunotherapeutic response in tumors. The purpose of the study was to evaluate the role of CHST12 in PAAD prognosis and its relevance to the immunotherapeutic response.

Methods

A comprehensive investigation of the interactions between CHST12 expression and the immune microenvironment as well as the clinical significance of CHST12 in PAAD was conducted. Data derived from the Cancer Genome Atlas (TCGA) database were analyzed using univariate and multivariate approaches, the Tumor Immune Estimation Resource (TIMER), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. Publicly available datasets were analyzed in this study. These data can be found on websites such as http://www.xiantao.love and https://www.proteinatlas.org. An assessment of the predictive value of CHST12 for PAAD prognosis was conducted using univariate and multivariate Cox regression analysis, Kaplan-Meier analysis, and nomograms. The TIMER algorithm calculates the proportions of six types of immune cells. The TIDE algorithm was used to indicate the characteristics of tumors that respond to ICI therapy.

Results

The mRNA and protein levels of CHST12 showed the opposite trend. CHST12 mRNA expression was significantly upregulated in PAAD. According to Cox regression analysis, CHST12 RNA expression acts as a protective factor for overall survival [hazard ratio (HR), 0.617, P < 0.04]. Functional annotation indicated that CHST12-associated differentially expressed genes (DEGs) were related to the signaling activity of receptor tyrosine kinases and the regulation of ubiquitin-protein transferase. These are usually involved in tumor development and may be related to the treatment responses of immune checkpoint inhibitors (ICIs). There was significantly higher CHST12 mRNA expression in PAAD samples than in non-malignant samples.

Conclusions

In PAAD, elevated CHST12 mRNA expression might regulate immune cell infiltration into the tumor microenvironment (TME) and may predict clinical outcomes.

An Efficient Binary Sand Cat Swarm Optimization for Feature Selection in High-Dimensional Biomedical Data

Recent breakthroughs are making a significant contribution to big data in biomedicine which are anticipated to assist in disease diagnosis and patient care management. To obtain relevant information from this data, effective administration and analysis are required. One of the major challenges associated with biomedical data analysis is the so-called "curse of dimensionality". For this issue, a new version of Binary Sand Cat Swarm Optimization (called PILC-BSCSO), incorporating a pinhole-imaging-based learning strategy and crossover operator, is presented for selecting the most informative features. First, the crossover operator is used to strengthen the search capability of BSCSO. Second, the pinhole-imaging learning strategy is utilized to effectively increase exploration capacity while avoiding premature convergence. The Support Vector Machine (SVM) classifier with a linear kernel is used to assess classification accuracy. The experimental results show that the PILC-BSCSO algorithm beats 11 cutting-edge techniques in terms of classification accuracy and the number of selected features using three public medical datasets. Moreover, PILC-BSCSO achieves a classification accuracy of 100% for colon cancer, which is difficult to classify accurately, based on just 10 genes. A real Liver Hepatocellular Carcinoma (TCGA-HCC) data set was also used to further evaluate the effectiveness of the PILC-BSCSO approach. PILC-BSCSO identifies a subset of five marker genes, including prognostic biomarkers HMMR, CHST4, and COL15A1, that have excellent predictive potential for liver cancer using TCGA data.

Differentially expressed non-coding RNAs and their regulatory networks in liver cancer

The vast majority of human transcriptome is represented by various types of small RNAs with little or no protein-coding capability referred to as non-coding RNAs (ncRNAs). Functional ncRNAs include microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), which are expressed at very low, but stable and reproducible levels in a variety of cell types. ncRNAs regulate gene expression due to miRNA capability of complementary base pairing with mRNAs, whereas lncRNAs and circRNAs can sponge miRNAs off their target mRNAs to act as competitive endogenous RNAs (ceRNAs). Each miRNA can target multiple mRNAs and a single mRNA can interact with several miRNAs, thereby creating miRNA-mRNA, lncRNA-miRNA-mRNA, and circRNA-miRNA-mRNA regulatory networks. Over the past few years, a variety of differentially expressed miRNAs, lncRNAs, and circRNAs (DEMs, DELs, and DECs, respectively) have been linked to cancer pathogenesis. They can exert both oncogenic and tumor suppressor roles. In this review, we discuss the recent advancements in uncovering the roles of DEMs, DELs, and DECs and their networks in aberrant cell signaling, cell cycle, transcription, angiogenesis, and apoptosis, as well as tumor microenvironment remodeling and metabolic reprogramming during hepatocarcinogenesis. We highlight the potential and challenges in the use of differentially expressed ncRNAs as biomarkers for liver cancer diagnosis and prognosis.

The Prognostic Model and Drug Sensitivity of LKB1-Mutant Lung Adenocarcinoma Based on Immune Landscape

Background: Lung cancer is the most common cause of cancer-related deaths worldwide. LKB1-mutant lung adenocarcinoma (LUAD) is a unique subtype of this deadly cancer. LKB1 mutations cause functional changes in a variety of cell processes, including immune functions, that affect prognosis. To date, the potential role of immunity in the prognosis of LKB1-mutant LUAD is not well understood.

Methods: We systematically analyzed immune-related genes in LUAD samples from The Cancer Genome Atlas (TCGA) database. ESTIMATE and CIBERSORT algorithms were used to explore the immune microenvironment. A prognostic risk model was constructed, and prognostic, immune function, drug sensitivity, and model specificity analyses were performed to identify the effectiveness of the model.

Results: Our results showed that LKB1 mutations suppressed immune function in LUAD. A three-gene signature was constructed to stratify patients into two risk groups. The risk score was an independent predictor for overall survival (OS) in multivariate Cox regression analyses [hazard ratio (HR) &gt; 1, p = 0.002]. Receiver operating characteristic (ROC) curve analyses confirmed that the risk score has better performance than clinicopathological characteristics. Functional analysis revealed that the immune status was different between the risk groups. ZM.447439 was an appropriate treatment for the high-risk group of patients. This risk model is only suitable for LKB1-mutant tumors; it performed poorly in LUAD patients with wild-type LKB1.

Conclusion: Our findings indicate the potential role of immunity in LKB1-mutant LUAD, providing novel insights into prognosis and guiding effective immunotherapy.

Dynamic human liver proteome atlas reveals functional insights into disease pathways

Deeper understanding of liver pathophysiology would benefit from a comprehensive quantitative proteome resource at cell type resolution to predict outcome and design therapy. Here, we quantify more than 150,000 sequence-unique peptides aggregated into 10,000 proteins across total liver, the major liver cell types, time course of primary cell cultures, and liver disease states. Bioinformatic analysis reveals that half of hepatocyte protein mass is comprised of enzymes and 23% of mitochondrial proteins, twice the proportion of other liver cell types. Using primary cell cultures, we capture dynamic proteome remodeling from tissue states to cell line states, providing useful information for biological or pharmaceutical research. Our extensive data serve as spectral library to characterize a human cohort of non-alcoholic steatohepatitis and cirrhosis. Dramatic proteome changes in liver tissue include signatures of hepatic stellate cell activation resembling liver cirrhosis and providing functional insights. We built a web-based dashboard application for the interactive exploration of our resource (www.liverproteome.org).

CHST4 might promote the malignancy of cholangiocarcinoma

Background

Cholangiocarcinoma (CCA) is reported as an aggressive cancer which leads to high mortality and no effective therapeutic target has yet been discovered. Surgical resection is the main method to treat patients with CCA. However, only one-third of CCA patients have the opportunity to accept the operation, leading to poor prognosis for CCA patients. Therefore, it is necessary to search for new therapeutic targets of CCA or core genes involved in the happening and growth of CCA.

Aim

In this study, we utilized bioinformatics technology and accessed to several medical databases trying to find the core genes of CCA for the purpose of intervening CCA through figuring out an effective curative target.

Methods

Firstly, three differentially expressed genes (DEGs) were discovered from GEPIA, and by further observing the distribution and gene expression, CHST4 was obtained as the core gene. Afterwards, correlated genes of CHST4 in CCA were identified using UALCAN to construct a gene expression profile. We obtained PPI network by Search Tool for the Retrieval of Interacting Networks Genes (STRING) and screened core genes using cytoscape software. Functional enrichment analyses were carried out and the expression of CHST in human tissues and tumors was observed. Finally, a CCA model was established for qPCR and staining validation.

Results

Three differentially expressed genes (DEGs), CHST4, MBOAT4 and RP11-525K10.3, were obtained. All were more over-expressed in CCA samples than the normal, among which the change multiple and the gene expression difference of CHST4 was the most obvious. Therefore, CHST4 was selected as the core gene. We can see in our established protein–protein interaction (PPI) network that CHST4 had the highest degree of connectivity, demonstrating its close association with CCA. We found that genes were mainly enriched in CCs in the PPI networks genes which shows functional enrichment analysis results, including golgi lumen, extracellular space and extracellular region. CHST4 was found very specifically expressed in the bile duct and was significantly different from that in normal tissues. The overexpression of CHST4 was further verified in the established animal model of TAA-induced CCA in rats. Quantitative PCR (qPCR) demonstrated that CHST4 was significantly overexpressed in tumor tissues, verifying the role of CHST4 as the core gene of CCA.

Conclusion

CHST4 was increasingly expressed in CCA and CHST4 is worth being studied much further in the intervention of CCA.

Diagnostic accuracy of circulating microRNA in hepatitis B virus-related hepatocellular carcinoma: a meta-analysis based on Asian data

BACKGROUND AND AIM

Hepatitis B virus (HBV) is the main risk factor for hepatocellular carcinoma (HCC). We performed a meta-analysis based on Asian data to evaluate the diagnostic accuracy of circulating microRNA as a non-invasive biomarker in the diagnosis of HBV-related HCC.

METHODS

A comprehensive literature search (updated to May 12, 2021) in PubMed, Embase, Web of Science, Wanfang Database, and China National Knowledge Infrastructure (CNKI) was performed to identify eligible studies. The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and area under the curve (AUC) for diagnosing HBV-related HCC were pooled in this meta-analysis. Subgroup analysis was performed to explore heterogeneity, and Deeks' funnel plot was used to assess publication bias.

RESULTS

19 articles including 32 studies were included in the current meta-analysis. The overall sensitivity, specificity, PLR, NLR, DOR and AUC were 0.83 (95% CI: 0.79 - 0.87), 0.78 (95% CI: 0.73 - 0.83), 3.9 (95% CI: 3.0 - 4.9), 0.21 (95% CI: 0.16 - 0.27), 18 (95% CI: 12 - 27) and 0.88 (95% CI: 0.85 - 0.91), respectively. Subgroup analysis shows that miRNA clusters with a large sample size showed better diagnostic accuracy. Although there is no publication bias, it still has some limitations.

CONCLUSIONS

Circulating miRNAs could serve as a potential non-invasive biomarker in diagnosing of HBV-related HCC in Asian populations.

Knockdown of carbohydrate sulfotransferase 12 decreases the proliferation and mobility of glioblastoma cells via the WNT/β-catenin pathway

Glioblastoma (GBM) is a common malignant tumor of the brain. Members of the carbohydrate sulfotransferase (CHST) family are deregulated in various cancer types. However, limited data are available on the role of the members of the CHST family in the development of GBM. The present study aimed to identify the role of significant members of the CHST family in GBM and explore the effects and molecular mechanisms of these significant members on GBM cell proliferation and mobility. In the current study, we demonstrated that CHST12 is the only member of CHST family that is upregulated in GBM tissues and associated with a lower survival rate according to the data obtained from The Cancer Genome Atlas. Similarly, the expression of CHST12 increased in GBM tissues than in adjacent tissues and had an important diagnostic value in distinguishing tumor tissues from adjacent tissues. The high expression of CHST12 indicated a lower overall survival rate, was negatively associated with the Karnofsky Performance Scale score, was positively associated with the KI67 expression rate, and was an independent risk factor for GBM. Knockdown of CHST12 significantly decreased GBM cell proliferation and mobility and inhibited the Wnt/β-catenin pathway. Restoration of β-catenin expression in GBM cells reversed the inhibitory effects of CHST12 knockdown on GBM cell proliferation and mobility. In conclusion, the present study demonstrated that CHST12 may be a novel biomarker for GBM; it regulates GBM cell proliferation and mobility via the WNT/β-catenin pathway.