A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes

Amentoflavone reverses epithelial-mesenchymal transition in hepatocellular carcinoma cells by targeting p53 signalling pathway axis

Epithelial-mesenchymal transition (EMT) and its reversal process are important potential mechanisms in the development of HCC. Selaginella doederleinii Hieron is widely used in Traditional Chinese Medicine for the treatment of various tumours and Amentoflavone is its main active ingredient. This study investigates the mechanism of action of Amentoflavone on EMT in hepatocellular carcinoma from the perspective of bioinformatics and network pharmacology. Bioinformatics was used to screen Amentoflavone-regulated EMT genes that are closely related to the prognosis of HCC, and a molecular prediction model was established to assess the prognosis of HCC. The network pharmacology was used to predict the pathway axis regulated by Amentoflavone. Molecular docking of Amentoflavone with corresponding targets was performed. Detection and evaluation of the effects of Amentoflavone on cell proliferation, migration, invasion and apoptosis by CCK-8 kit, wound healing assay, Transwell assay and annexin V-FITC/propidium iodide staining. Eventually three core genes were screened, inculding NR1I2, CDK1 and CHEK1. A total of 590 GO enrichment entries were obtained, and five enrichment results were obtained by KEGG pathway analysis. Genes were mainly enriched in the p53 signalling pathway. The outcomes derived from both the wound healing assay and Transwell assay demonstrated significant inhibition of migration and invasion in HCC cells upon exposure to different concentrations of Amentoflavone. The results of Annexin V-FITC/PI staining assay showed that different concentrations of Amentoflavone induces apoptosis in HCC cells. This study revealed that the mechanism of Amentoflavone reverses EMT in hepatocellular carcinoma, possibly by inhibiting the expression of core genes and blocking the p53 signalling pathway axis to inhibit the migration and invasion of HCC cells.

Pan-Cancer Analysis of P3H1 and Experimental Validation in Renal Clear Cell Carcinoma

Prolyl 3-hydroxylase 1 (P3H1) has been implicated in cancer development, but no pan-cancer analysis has been conducted on P3H1. In this study, for the first time, aspects associated with P3H1, such as the mRNA expression, any mutation, promoter methylation, and prognostic significance, the relationship between P3H1 and clinicopathological parameters, drug sensitivity, and immune cell infiltration were investigated by searching several databases including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), cBioPortal, and The Tumor Immune Evaluation Resource (TIMER2.0) using bioinformatics tools. The findings indicate significant differential expression of P3H1 in most tumors when compared to normal tissues, with a strong association with clinical prognosis. A pan-cancer Cox regression analysis revealed that high P3H1 expression is significantly associated with low overall survival in patients with brain lower grade glioma, kidney clear cell carcinoma, adrenocortical cancer, liver hepatocellular carcinoma, mesothelioma, sarcoma, uveal melanoma, bladder urothelial carcinoma, kidney papillary cell carcinoma, kidney chromophobe, thymoma, and thyroid carcinoma. A negative correlation was observed between P3H1 DNA methylation and its expression. P3H1 is significantly associated with infiltrating cells, immune-related genes, tumor mutation burden, microsatellite instability, and mismatch repair. Finally, A significant correlation was found between P3H1 expression and sensitivity to nine drugs. Thus, enhanced P3H1 expression is associated with poor prognosis in a variety of tumors, which may be due to its role in tumor immune regulation and tumor microenvironment. This pan-cancer analysis provides insight into the function of P3H1 in tumorigenesis of different cancers and provides a theoretical basis for further in-depth studies to follow.

Identification and validation of biomarkers for epithelial-mesenchymal transition-related cells to estimate the prognosis and immune microenvironment in primary gastric cancer by the integrated analysis of single-cell and bulk RNA sequencing data

BACKGROUND

The epithelial-mesenchymal transition (EMT) is associated with gastric cancer (GC) progression and immune microenvironment. To better understand the heterogeneity underlying EMT, we integrated single-cell RNA-sequencing (scRNA-seq) data and bulk sequencing data from GC patients to evaluate the prognostic utility of biomarkers for EMT-related cells (ERCs), namely, cancer-associated fibroblasts (CAFs) and epithelial cells (ECs).

METHODS

scRNA-seq data from primary GC tumor samples were obtained from the Gene Expression Omnibus (GEO) database to identify ERC marker genes. Bulk GC datasets from the Cancer Genome Atlas (TCGA) and GEO were used as training and validation sets, respectively. Differentially expressed markers were identified from the TCGA database. Univariate Cox, least-absolute shrinkage, and selection operator regression analyses were performed to identify EMT-related cell-prognostic genes (ERCPGs). Kaplan-Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses were adopted to evaluate the prognostic utility of the ERCPG signature. An ERCPG-based nomogram was constructed by integrating independent prognostic factors. Finally, we evaluated the correlations between the ERCPG signature and immune-cell infiltration and verified the expression of ERCPG prognostic signature genes by in vitro cellular assays.

RESULTS

The ERCPG signature was comprised of seven genes (COL4A1, F2R, MMP11, CAV1, VCAN, FKBP10, and APOD). Patients were divided into high- and low-risk groups based on the ERCPG risk scores. Patients in the high-risk group showed a poor prognosis. ROC and calibration curves suggested that the ERCPG signature and nomogram had a good prognostic utility. An immune cell-infiltration analysis suggested that the abnormal expression of ERCPGs induced the formation of an unfavorable tumor immune microenvironment. In vitro cellular assays showed that ERCPGs were more abundantly expressed in GC cell lines compared to normal gastric tissue cell lines.

CONCLUSIONS

We constructed and validated an ERCPG signature using scRNA-seq and bulk sequencing data from ERCs of GC patients. Our findings support the estimation of patient prognosis and tumor treatment in future clinical practice.

The Emerging Role of Metformin in the Treatment of Hepatocellular Carcinoma: Is There Any Value in Repurposing Metformin for HCC Immunotherapy?

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. There has been significant progress in understanding the risk factors and epidemiology of HCC during the last few decades, resulting in efficient preventative, diagnostic and treatment strategies. Type 2 diabetes mellitus (T2DM) has been demonstrated to be a major risk factor for developing HCC. Metformin is a widely used hypoglycemic agent for patients with T2DM and has been shown to play a potentially beneficial role in improving the survival of patients with HCC. Experimental and clinical studies evaluating the outcomes of metformin as an antineoplastic drug in the setting of HCC were reviewed. Pre-clinical evidence suggests that metformin may enhance the antitumor effects of immune checkpoint inhibitors (ICIs) and reverse the effector T cells' exhaustion. However, there is still limited clinical evidence regarding the efficacy of metformin in combination with ICIs for the treatment of HCC. We appraised and analyzed in vitro and animal studies that aimed to elucidate the mechanisms of action of metformin, as well as clinical studies that assessed its impact on the survival of HCC patients.

The prognostic and immune infiltration role of ITGB superfamily members in non-small cell lung cancer

PURPOSE

We aimed to explore the prognostic value of integrin-β superfamily members (ITGBs) and their role in immune cell infiltration in non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

Study cases were acquired from The Cancer Genome Atlas database and The Human Protein Atlas. We then used R package and several online tools to analyze and visualize the roles of ITGBs in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC).

RESULTS

We found that ITGBs were differentially expressed in NSCLC. In LUAD, high expression of ITGB1 and ITGB4 was an independent risk factor for poor prognosis, and ITGB7 was an independent protective factor for overall survival; in LUSC, high expression of ITGB1, 3, 5, and 6 was associated with poor prognosis, and ITGB8 was an independent protective factor for disease-specific survival. Protein-protein interaction networks for the most associated co-expressed genes revealed the following target genes of ITGBs: PTPRC, ITGAM, and ITGB2 in LUAD and FN1, PTPRC, and ITGB2 in LUSC. Gene ontology analysis revealed that functions related to adhesion, junction, and binding were highly enriched in LUAD and LUSC. ITGBs were significantly associated with immune cell infiltration and the expression of immunomodulation-related genes in LUAD and LUSC.

CONCLUSION

ITGBs were differentially expressed in NSCLC. ITGB1, 4, and 7 and ITGB1, 3, 5, 6, and 8 were found as prognostic markers in LUAD and LUSC, respectively. ITGBs were significantly associated with immune cell infiltration and the expression of immunomodulation-related genes.

A Novel Oxidative Phosphorylation-Associated Gene Signature for Prognosis Prediction in Patients with Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common type of malignant tumor with high morbidity and mortality. The oxidative phosphorylation (OXPHOS) metabolic pathway produces adenosine triphosphate (ATP) by delivering electrons to transmembrane protein complexes in the mitochondria. This research was dedicated to identifying an OXPHOS-associated signature for the assessment of prognosis of HCC patients. A total of 371 HCC patients from the Cancer Genome Atlas (TCGA) and 231 HCC patients from the International Cancer Genome Consortium (ICGC) with RNA expression data and clinical data were employed as construction and validation cohorts, respectively. The least absolute shrinkage and selection operator (LASSO) Cox regression was applied to establish a multigene signature in the TCGA cohort, and the ICGC cohort was used for validation. The prognostic value of the risk signature was evaluated using univariate and multivariate Cox regression, Kaplan–Meier curves, and receiver operating characteristic (ROC) curves. The potential enrichment of biological functions was investigated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Meanwhile, we analyzed the correlation between the risk score and the tumor microenvironment (TME). A five-gene signature including ATP6V0B, ATP6V1C1, ATP6V1E1, TIMM9, and UQCRH was identified by LASSO Cox regression to classify patients into low- and high-risk groups. ROC curve analysis indicated that the five-gene signature is a prospective prognostic factor in HCC patients. Univariate and multivariate Cox regression analyses demonstrated that the risk score was an independent prognostic factor for overall survival (OS). Functional analysis showed that differentially expressed genes (DEGs) between the low- and high-risk groups were enriched in mitosis and the cell cycle pathway. In addition, the five-gene signature was associated with innate immune cell infiltration, immune subtypes, and tumor stemness. A novel OXPHOS-associated gene signature can be used for prognostic prediction for patients with HCC.

Ezrin expression in circulating tumor cells is a predictor of prostate cancer metastasis

Metastatic prostate cancer (PCa) remains incurable and fatal. Previous studies have proven that circulating tumor cells (CTCs) and Ezrin are involved in PCa progression, metastasis, diagnosis, and prognosis. Therefore, we aimed to investigate the roles of CTCs and Ezrin in PCa metastasis. The expression of Ezrin was measured by qRT–PCR and immunohistochemical staining. The migration and invasion of PCa cells were evaluated. Additionally, clinical data from PCa patients were collected to analyze the potential roles of Ezrin expression in CTCs of PCa. The results showed that Ezrin expression was significantly upregulated in PCa tissues and 22RV1 and PC-3 cell samples. The overexpression of Ezrin promoted the migratory and invasive abilities of 22RV1 and PC-3 cells. Finally, the clinical data revealed that the expression of Ezrin in CTCs of PCa patients was significantly upregulated with the metastatic degree. Furthermore, after radical prostatectomy, CTCs from Ezrin-positive PCa patients were susceptible to tumor metastasis. Therefore, these results indicated that Ezrin expression in CTCs may offer novel insights into the prognosis and management of PCa.

Knockdown of long non-coding RNA SNHG8 suppresses the progression of esophageal cancer by regulating miR-1270/BACH1 axis

The emerging evidence showed that lncRNAs (long non-coding RNAs) could regulate the progression and affect the malignant behaviors of cancers. LncRNA SNHG8 (small nucleolar RNA host gene 8) has been reported to participate in most cancers development. Here in this study, the role of lncRNA SNHG8 in esophageal cancer was uncovered by a series of functional experiments. The expression pattern of SNHG8 in tumor tissues or cells was first detected by qRT-PCR. Using a lentivirus knockdown shRNA is to repress the expression of SNHG8. Subsequently, the in vitro and in vivo experiments were utilized to evaluate whether the malignant behaviors of esophageal cancer were influenced by knockdown SNHG8. The results indicated that lncRNA SNHG8 should be a cancer-promoting factor with a relatively high expression level in esophageal cancer. Moreover, knockdown SNHG8 inhibited the cell viability and induced cell apoptosis in KYSE30 and TE-1 cells. In addition, based on the results of the binding site analysis and the luciferase reporter system, SNHG8 functions by the miR-1270/BACH1 axis. The follow-up experiments verified that lncRNA SNHG8 could down-regulate the expression of miR-1270 to increase the BACH1 expression. Finally, we confirmed that knockdown SNHG8 retarded the progression of esophageal cancer with a xenograft model. To sum up, our findings suggested that lncRNA SNHG8 is a cancer-promoting factor in esophageal cancer. Knockdown SNHG8 could suppress the progression of esophageal cancer, which implies SNHG8 could be used as a therapeutic target in esophageal cancer.

Exploration of the Key Proteins of High-Grade Intraepithelial Neoplasia to Adenocarcinoma Sequence Using In-Depth Quantitative Proteomics Analysis

Purpose

In this study, we aimed to provide a comprehensive description of typical features and identify key proteins associated with the high-grade intraepithelial neoplasia- (HIN-) adenocarcinoma (AC) sequence.

Methods

We conducted tandem mass tag-based quantitative proteomic profiling of normal mucosa, HIN, and AC tissues. Protein clusters representative of the HIN-AC sequence were identified using heatmaps based on Pearson's correlation analysis. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database, ClueGO plugin in Cytoscape, and the Metascape database. The prognostic value of the key proteins and their effects on the tumor microenvironment and consensus molecular subtype were explored based on The Cancer Genome Atlas.

Results

We identified 536 proteins categorized into three clusters. Among the biological processes and pathways of the highly expressed proteins in the HIN-AC sequence, proteins were predominantly enriched in response to gut microbiota, cell proliferation, leukocyte migration, and extracellular matrix (ECM) organization events. SERPINH1 and P3H1 were identified as the key proteins that promote the HIN-AC sequence. In the correlation analysis of infiltrating immune cells, both SERPINH1 and P3H1 expression correlated negatively with tumor purity, while correlating positively with abundance of CD8⁺ T cells, B cells, macrophage/monocytes, dendritic cells, cancer-associated fibroblasts, endothelial cells, neutrophils, and natural killer cells. Furthermore, both SERPINH1 and P3H1 expression positively correlated with common immune checkpoints and mesenchymal molecular subtype. High P3H1 expression was associated with poor disease-free survival and overall survival.

Conclusions

ECM-related biological processes and pathways are typical features of the HIN-AC sequence. SERPINH1 and P3H1 might be the key proteins in this sequence and be related to ECM remodeling and immune suppression status in CRC.

Absent in melanoma 1-like (AIM1L) serves as a novel candidate for overall survival in hepatocellular carcinoma

Identifying biomarkers for hepatocellular carcinoma (HCC) survival is of great importance for the early detection, monitoring, and predicting for prognosis. This study aimed to investigate the candidate biomarkers for predicting overall survival (OS) in HCC patients. Using RTCGAToolbox, top 50 upregulated differential expressed genes (DEGs) were identified. The least absolute shrinkage and selection operator (LASSO) and Cox models were used to select powerful candidate genes, and log rank method was used to address the survivor functions of potential biomarkers. Selected by LASSO model, ANLN, TTK, AIM1L and person neoplasm cancer status might be candidate parameters associated with OS in HCC patients. After adjusting person neoplasm cancer status, ANLN and TTK levels in Cox model, AIM1L was identified as a risk factor for predicting OS in HCC patients (HR = 1.5, P = 0.037). Validated in The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) series, AIM1L was significantly overexpressed in tumor tissues compared to nontumor tissues (all P < 0.0001). HCC patients with high AIM1L in tumor tissues had significantly unfavorable OS compared to those with low AIM1L in TCGA, ICGC, Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier Plotter datasets (all P < 0.05). Conclusively, AIM1L is upregulated in tumor samples and serves as a novel candidate for predicting unfavorable OS in HCC patients.

Constructing a new prognostic signature of gastric cancer based on multiple data sets

In order to explore new prediction methods and key genes for gastric cancer. Firstly, we downloaded the 6 original sequencing data of gastric cancer on the Illumina HumanHT-12 platform from Array Expression and Gene Expression Omnibus, and used bioinformatics methods to identify 109 up-regulated genes and 271 down-regulated genes. Further, we performed univariate Cox regression analysis of prognostic-related genes, then used Lasso regression to remove collinearity, and finally used multivariate Cox regression to analyze independent prognostic genes (MT1M, AKR1C2, HEYL, KLK11, EEF1A2, MMP7, THBS1, KRT17, RPESP, CMTM4, UGT2B17, CGNL1, TNFRSF17, REG1A). Based on these, we constructed a prognostic risk proportion signature, and found that patients with high-risk gastric cancer have a high degree of malignancy. Subsequently, we used the GSE15459 data set to verify the signature. By calculating the area under the recipient operator characteristic curve of 5-year survival rate, the test set and verification set are 0.739 and 0.681, respectively, suggesting that the prognostic signature has a moderate prognostic ability. The nomogram is used to visualize the prognostic sig-nature, and the calibration curve verification showed that the prediction accuracy is higher. Finally, we verified the expression and prognosis of the hub gene, and suggested that HEYL, MMP7, THBS1, and KRT17 may be potential prognostic biomarkers.

Exploration of the typical features of tubulovillous adenoma using in-depth quantitative proteomics analysis

This present study aimed to explore the typical protein features of tubulovillous adenoma (TVA) using proteomic and bioinformatic analyses. Tandem mass tag (TMT)-based quantitative proteomic analyses were conducted on normal mucosa, tubular adenoma, TVA and adenocarcinoma tissues. We identified 5,665 proteins categorized into seven clusters based on Pearson’s correlation analysis. The bioinfomatic analysis showed mitochondrial and metabolism-related events were typical characteristics of TVA and mitochondrial-, ribosome- and matrisome-related biological processes may contribute to carcinogenesis. PLOD3 was identified as a key protein associated with the malignant potential of TVA and promoted the viability of adenoma organoids. The Cancer Genome Atlas (TCGA) analysis revealed PLOD3 as a risk factor for disease-free and overall survival. Furthermore, the PLOD3 expression correlated negatively with the abundance of B cells, CD8 + T cells, CD4 + T cells, neutrophils, macrophages and myeloid dendritic cells. In conclusion, enhanced metabolic and mitochondrial reprogramming are typical features of TVA, and PLOD3 might be related to the “immune desert” phenotype and contribute to TVA tumorigenesis and colorectal cancer development.

Risk characteristics with seven epithelial-mesenchymal transition-related genes are used to predict the prognosis of patients with hepatocellular carcinoma

Background

Epithelial-mesenchymal transition (EMT)-related genes (ERGs) have been shown to play an important role in cancer invasion, tumor resistance, and tumor metastasis of hepatocellular carcinoma. This study sought to examine the prognostic value of ERGs and other pre-hepatoma genes.

Methods

Relevant data from The Cancer Genome Atlas (TCGA) were analyzed and synthesized. Specifically, 1,014 ERGs were downloaded and subject to a gene set enrichment analysis; 318 different EAG expressions were found, and the possible molecular mechanism of EAG was predicted by GO analysis and KEGG analysis. To determine the prediction of ERGS, a Cox regression model was used to establish a risk hypothesis. Based on risk patterns, patients were divided into high- or low-risk groups. Kaplan-Meier and receiver operating characteristic (ROC) curves confirmed the predictive value of the model.

Results

Seven prognostically relevant ERGs (i.e., ECT2, EZH2, MYCN, ROR2, SPP1, SQSTM1, and STC2) were identified. Using Cox's regression analysis method, appropriate cases were selected to establish a new risk prediction model. Under the risk model, the overall survival rate of the low-risk group samples was higher than that of the high-risk group samples (P<0.00001).

Conclusions

In short, we developed a risk model for liver cancer based on ERGs terminology. This model improve the postpartum treatment of patients with liver cancer.

Identification of the EMT-Related Genes Signature for Predicting Occurrence and Progression in Thyroid Cancer

BACKGROUND

The detection rate of thyroid cancer (TC) has been continuously improved due to the development of detection technology. Epithelial-mesenchymal transition (EMT) is thought to be closely related to the malignant progression of tumors. However, the relationship between EMT-related genes (ERGs) characteristics and the diagnosis and prognosis of TC patients has not been studied.

METHODS

Four datasets from Gene Expression Omnibus (GEO) were used to perform transcriptomic profile analysis. The overlapping differentially expressed ERGs (DEERGs) were analyzed using the R package "limma". Then, the hub genes, which had a higher degree, were identified by the protein-protein interaction (PPI) network. Gene expression analysis between the TC and normal data, the disease-free survival (DFS) analysis of TC patients from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) cohort, function analysis, and immunohistochemistry (IHC) were performed to verify the importance of the hub genes. Finally, a prognostic risk scoring was constructed to predict DFS in patients with the selected genes.

RESULTS

A total of 43 DEERGs were identified and 10 DEERGs were considered hub ERGs, which had a high degree of connectivity in the PPI network. Then, the differential expressions of FN1, ITGA2, and KIT between TC and normal tissues were verified in the TCGA-THCA cohort and their protein expressions were also verified by IHC. DFS analysis indicated upregulations of FN1 expression (P<0.01) and ITGA2 expression (P<0.01) and downregulation of KIT expression (P=0.01) increased risks of decreased DFS for TCGA-THCA patients. Besides, by building a prognostic risk scoring model, we found that the DFS of TCGA-THCA patients was significantly worse in high-risk groups.

CONCLUSION

In summary, these hub ERGs were potential biomarkers for diagnosis and prognosis of TC, which can provide a basis for further exploring the efficacy of EMT in patients with TC.