Nujiangexanthone A Inhibits Hepatocellular Carcinoma Metastasis via Down Regulation of Cofilin 1

Cytoskeletal gene alterations linked to sorafenib resistance in hepatocellular carcinoma

BACKGROUND

Although sorafenib has been consistently used as a first-line treatment for advanced hepatocellular carcinoma (HCC), most patients will develop resistance, and the mechanism of resistance to sorafenib needs further study.

METHODS

Using KAS-seq technology, we obtained the ssDNA profiles within the whole genome range of SMMC-7721 cells treated with sorafenib for differential analysis. We then intersected the differential genes obtained from the analysis of hepatocellular carcinoma patients in GSE109211 who were ineffective and effective with sorafenib treatment, constructed a PPI network, and obtained hub genes. We then analyzed the relationship between the expression of these genes and the prognosis of hepatocellular carcinoma patients.

RESULTS

In this study, we identified 7 hub ERGs (ACTB, CFL1, ACTG1, ACTN1, WDR1, TAGLN2, HSPA8) related to drug resistance, and these genes are associated with the cytoskeleton.

CONCLUSIONS

The cytoskeleton is associated with sorafenib resistance in hepatocellular carcinoma. Using KAS-seq to analyze the early changes in tumor cells treated with drugs is feasible for studying the drug resistance of tumors, which provides reference significance for future research.

The interaction of PRDX1 with Cofilin promotes oral squamous cell carcinoma metastasis

Peroxiredoxin 1 (PRDX1) is an important member of the peroxiredoxin family (PRDX) and is upregulated in a variety of tumors. Previous studies have found that high PRDX1 expression is closely related to the metastasis of oral squamous cell carcinoma (OSCC), but the specific molecular mechanism is elusive. To elucidate the role of PRDX1 in the metastasis process of OSCC, we evaluated the expression of PRDX1 in OSCC clinical specimens and its impact on the prognosis of OSCC patients. Then, the effect of PRDX1 on OSCC metastasis and cytoskeletal reconstruction was explored in vitro and in nude mouse tongue cancer models, and the molecular mechanisms were also investigated. PRDX1 can directly interact with the actin-binding protein Cofilin, inhibiting the phosphorylation of its Ser3 site, accelerating the depolymerization and turnover of actin, promoting OSCC cell movement, and aggravating the invasion and metastasis of OSCC. In clinical samples and mouse tongue cancer models, PRDX1 also increased lymph node metastasis of OSCC and was negatively correlated with the phosphorylation of Cofilin; PRDX1 also reduced the overall survival rate of OSCC patients. In summary, our study identified that PRDX1 may be a potential therapeutic target to inhibit OSCC metastasis.

Identification and targeting of metastatic biomarkers for hepatocellular carcinoma therapeutics using small molecules library of curcumin analogues

The understanding of the molecular basis of complex diseases like hepatocellular carcinoma (HCC) needs large datasets of multiple genes and proteins involved in different phenomenon of its development. This study focuses on the molecular basis of HCC and the development of therapeutic strategies. We analyzed a dataset of 5475 genes (Homo sapiens) involved in HCC hallmarks, involving comprehensive data on multiple genes and frequently mutated genes. As HCC is characterized by metastasis, angiogenesis, and oxidative stress, exploration of genes associated with them has been targeted. Through gene ontology, functional characterization, and pathway enrichment analysis, we identified target proteins such as Lysyl oxidase, Survivin, Cofilin, and Cathepsin B. A library of curcumin analogs was used to target these proteins. Tetrahrydrocurcumin showed promising binding affinities for all four proteins, suggesting its potential as an inhibitor against these proteins for HCC therapy.

Turmeric Inhibits MDA-MB-231 Cancer Cell Proliferation, Altering miR-638-5p and Its Potential Targets

Objective

Recent research suggests curcumin extracted from the turmeric plant may inhibit the proliferation of cancer cells by controlling the expression of microRNAs (miRNAs). The effect of phenolic curcumin on miR-638-5p and potential target gene expressions in the triple negative breast cancer (TNBC) cell line MDA-MB-231 was investigated in this study.

Materials and Methods

GSE154255 and GSE40525 datasets were downloaded and analyzed using GEO2R to identify dysregulated miRNAs in TNBC. To find differently expressed genes in breast cancer (BRCA), The Cancer Genome Atlas Program data was examined. Utilizing in silico tools, KEGG, GO, and other enrichment analyses were performed. The databases miRNet, miRTarBase v8.0, and TarBase v.8 were used for miRNA and mRNA matching. Real-time quantitative reverse transcription polymerase chain reaction was used to examine the levels of miRNA and its targets in miRNA mimic transfected/curcumin-treated MDA-MB-231 cultures and controls. The cell viability detection kit-8 method was used to assess cell viability, and the scratch assay was used to conduct migration assessment.

Results

Bioinformatics analysis showed that miR-638-5p was significantly reduced in TNBC patients. Experimental results showed that miR-638-5p was upregulated in MDA-MB-231 treated with curcumin, while the potential target genes of miR-638-5p, CFL1, SIX4, MAZ, and CDH1 were downregulated. Mimic miR-638-5p transfection inhibited MDA-MB-231 cell proliferation and reduced migration and expression of CFL1, SIX4, and MAZ genes was decreased in mimic miR-638-5p transfected cells.

Conclusion

These findings suggest that curcumin exerts its anticancer effects on MDA-MB-231 cells by modulating the expression of miR-638-5p and its possible target genes.

Identification of fatty acid metabolism-related clusters and immune infiltration features in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is a type of liver cancer which is characterized by inflammation-associated tumor. The unique characteristics of tumor immune microenvironment in HCC contribute to hepatocarcinogenesis. It was also clarified that aberrant fatty acid metabolism (FAM) might accelerate tumor growth and metastasis of HCC. In this study, we aimed to identify fatty acid metabolism-related clusters and establish a novel prognostic risk model in HCC. Gene expression and corresponding clinical data were searched from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) portal. From the TCGA database, by unsupervised clustering method, we determined three FAM clusters and two gene clusters with distinct clinicopathological and immune characteristics. Based on 79 prognostic genes identified from 190 differentially expressed genes (DEGs) among three FAM clusters, five prognostic DEGs (CCDC112, TRNP1, CFL1, CYB5D2, and SLC22A1) were determined to construct risk model by least absolute shrinkage and selection operator (LASSO) and multivariate cox regression analysis. Furthermore, the ICGC dataset was used to validate the model. In conclusion, the prognostic risk model constructed in this study exhibited excellent indicator performance of overall survival, clinical feature, and immune cell infiltration, which has the potential to be an effective biomarker for HCC immunotherapy.

Construction of a Novel Gene-Based Model for Survival Prediction of Hepatitis B Virus Carriers With HCC Development

Despite the effectiveness of hepatitis B virus (HBV) vaccination in reducing the prevalence of chronic HBV infection as well as the incidence of acute hepatitis B, fulminant hepatitis, liver cirrhosis and hepatocellular carcinoma (HCC), there was still a large crowd of chronically infected populations at risk of developing cirrhosis or HCC. In this study, we established a comprehensive prognostic system covering multiple signatures to elevate the predictive accuracy for overall survival (OS) of hepatitis B virus carriers with HCC development. Weighted Gene Co-Expression Network Analysis (WGCNA), Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine Recursive Feature Elimination (SVM-RFE), and multivariate COX analysis, along with a suite of other online analyses were successfully applied to filtrate a three-gene signature model (TP53, CFL1, and UBA1). Afterward, the gene-based risk score was calculated based on the Cox coefficient of the individual gene, and the prognostic power was assessed by time-dependent receiver operating characteristic (tROC) and Kaplan–Meier (KM) survival analysis. Furthermore, the predictive power of the nomogram, integrated with the risk score and clinical parameters (age at diagnosis and TNM stage), was revealed by the calibration plot and tROC curves, which was verified in the validation set. Taken together, our study may be more effective in guiding the clinical decision-making of personalized treatment for HBV carriers.