Clinical Significance and Potential Mechanisms of ATP Binding Cassette Subfamily C Genes in Hepatocellular Carcinoma

Role of ABCC5 in cancer drug resistance and its potential as a therapeutic target

Over 90% of treatment failures in cancer therapy can be attributed to multidrug resistance (MDR), which can develop intracellularly or through various routes. Numerous pathways contribute to treatment resistance in cancer, but one of the most significant pathways is intracellular drug efflux and reduced drug concentrations within cells, which are controlled by overexpressed drug efflux pumps. As a member of the family of ABC transporter proteins, ABCC5 (ATP Binding Cassette Subfamily C Member 5) reduces the intracellular concentration of a drug and its subsequent effectiveness using an ATP-dependent method to pump the drug out of the cell. Numerous studies have demonstrated that ABCC5 is strongly linked to both poor prognosis and poor treatment response. In addition, elevated ABCC5 expression is noted in a wide variety of malignancies. Given that ABCC5 is regulated by several pathways in a broad range of cancer types, it is a prospective target for cancer treatment. This review examined the expression, structure, function, and role of ABCC5 in various cancer types.

The xenobiotic transporter ABCC4/MRP4 promotes epithelial mesenchymal transition in pancreatic cancer

The xenobiotic transporter ABCC4/MRP4 is highly expressed in pancreatic ductal adenocarcinoma (PDAC) and correlates with a more aggressive phenotype and metastatic propensity. Here, we show that ABCC4 promotes epithelial-mesenchymal transition (EMT) in PDAC, a hallmark process involving the acquisition of mesenchymal traits by epithelial cells, enhanced cell motility, and chemoresistance. Modulation of ABCC4 levels in PANC-1 and BxPC-3 cell lines resulted in the dysregulation of genes present in the EMT signature. Bioinformatic analysis on several cohorts including tumor samples, primary patient-derived cultured cells, patient-derived xenografts, and cell lines, revealed a positive correlation between ABCC4 expression and EMT markers. We also characterized the ABCC4 cistrome and identified four candidate clusters in the distal promoter and intron one that showed differential binding of pro-epithelial FOXA1 and pro-mesenchymal GATA2 transcription factors in low ABCC4-expressing HPAF-II and high ABCC4-expressing PANC-1 xenografts. HPAF-II xenografts showed exclusive binding of FOXA1, and PANC-1 xenografts exclusive binding of GATA2, at ABCC4 clusters, consistent with their low and high EMT phenotype respectively. Our results underscore ABCC4/MRP4 as a valuable prognostic marker and a potential therapeutic target to treat PDAC subtypes with prominent EMT features, such as the basal-like/squamous subtype, characterized by worse prognosis and no effective therapies.

A Novel Affordable and Reliable Framework for Accurate Detection and Comprehensive Analysis of Somatic Mutations in Cancer

Accurate detection and analysis of somatic variants in cancer involve multiple third-party tools with complex dependencies and configurations, leading to laborious, error-prone, and time-consuming data conversions. This approach lacks accuracy, reproducibility, and portability, limiting clinical application. Musta was developed to address these issues as an end-to-end pipeline for detecting, classifying, and interpreting cancer mutations. Musta is based on a Python command-line tool designed to manage tumor-normal samples for precise somatic mutation analysis. The core is a Snakemake-based workflow that covers all key cancer genomics steps, including variant calling, mutational signature deconvolution, variant annotation, driver gene detection, pathway analysis, and tumor heterogeneity estimation. Musta is easy to install on any system via Docker, with a Makefile handling installation, configuration, and execution, allowing for full or partial pipeline runs. Musta has been validated at the CRS4-NGS Core facility and tested on large datasets from The Cancer Genome Atlas and the Beijing Institute of Genomics. Musta has proven robust and flexible for somatic variant analysis in cancer. It is user-friendly, requiring no specialized programming skills, and enables data processing with a single command line. Its reproducibility ensures consistent results across users following the same protocol.

Sarcosine dehydrogenase as an immune infiltration-associated biomarker for the prognosis of hepatocellular carcinoma

This study was aimed to investigate the prognostic value and clinical significance of sarcosine dehydrogenase (SARDH) in hepatocellular carcinoma (HCC) and to explore the underlying mechanisms. The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), HPA and CPTAC databases were adopted to analyze the expression of SARDH mRNA and protein between normal liver tissue and HCC, and examine their relationship with clinicopathological features. Kaplan-Meier analysis, Cox regression, as well as nomogram were adopted to explore the prognostic value of SARDH in HCC. Gene Ontology (GO), Kyoto Gene and Genome Encyclopedia (KEGG) together with Gene Set Enrichment Analysis (GSEA) were adopted to analyze the molecular mechanisms and biological functions of SARDH in HCC; while MethSurv, STRING, GeneMANIA, TIMER database data and single-sample gene set enrichment analysis (ssGSEA) algorithm were used for other bioinformatic analysis. Furthermore, immunohistochemistry was used to verify the expression of SARDH. Compared to normal liver tissue, SARDH expression was markedly lower in HCC. A lower SARDH expression was linked with Pathologic T stage (T3&T4), pathologic stage (Stage III&IV), and histologic grade (G3&4), which further indicates worse prognosis. Besides, results of bioinformatic analysis proved that SARDH expression was correlated with immune infiltration. In addition, SARDH hypermethylation was related to a poorer prognosis. SARDH expression was related to several key genes in the Ferroptosis pathway.

Targeting Glucose Metabolism in Cancer Cells as an Approach to Overcoming Drug Resistance

The "Warburg effect" consists of a metabolic shift in energy production from oxidative phosphorylation to glycolysis. The continuous activation of glycolysis in cancer cells causes rapid energy production and an increase in lactate, leading to the acidification of the tumour microenvironment, chemo- and radioresistance, as well as poor patient survival. Nevertheless, the mitochondrial metabolism can be also involved in aggressive cancer characteristics. The metabolic differences between cancer and normal tissues can be considered the Achilles heel of cancer, offering a strategy for new therapies. One of the main causes of treatment resistance consists of the increased expression of efflux pumps, and multidrug resistance (MDR) proteins, which are able to export chemotherapeutics out of the cell. Cells expressing MDR proteins require ATP to mediate the efflux of their drug substrates. Thus, inhibition of the main energy-producing pathways in cancer cells, not only induces cancer cell death per se, but also overcomes multidrug resistance. Given that most anticancer drugs do not have the ability to distinguish normal cells from cancer cells, a number of drug delivery systems have been developed. These nanodrug delivery systems provide flexible and effective methods to overcome MDR by facilitating cellular uptake, increasing drug accumulation, reducing drug efflux, improving targeted drug delivery, co-administering synergistic agents, and increasing the half-life of drugs in circulation.

Discovering the Protective Effects of Quercetin on Aflatoxin B1-Induced Toxicity in Bovine Foetal Hepatocyte-Derived Cells (BFH12)

Aflatoxin B1 (AFB1) induces lipid peroxidation and mortality in bovine foetal hepatocyte-derived cells (BFH12), with underlying transcriptional perturbations associated mainly with cancer, cellular damage, inflammation, bioactivation, and detoxification pathways. In this cell line, curcumin and resveratrol have proven to be effective in mitigating AFB1-induced toxicity. In this paper, we preliminarily assessed the potential anti-AFB1 activity of a natural polyphenol, quercetin (QUE), in BFH12 cells. To this end, we primarily measured QUE cytotoxicity using a WST-1 reagent. Then, we pre-treated the cells with QUE and exposed them to AFB1. The protective role of QUE was evaluated by measuring cytotoxicity, transcriptional changes (RNA-sequencing), lipid peroxidation (malondialdehyde production), and targeted post-transcriptional modifications (NQO1 and CYP3A enzymatic activity). The results demonstrated that QUE, like curcumin and resveratrol, reduced AFB1-induced cytotoxicity and lipid peroxidation and caused larger transcriptional variations than AFB1 alone. Most of the differentially expressed genes were involved in lipid homeostasis, inflammatory and immune processes, and carcinogenesis. As for enzymatic activities, QUE significantly reverted CYP3A variations induced by AFB1, but not those of NQO1. This study provides new knowledge about key molecular mechanisms involved in QUE-mediated protection against AFB1 toxicity and encourages in vivo studies to assess QUE's bioavailability and beneficial effects on aflatoxicosis.

Screening of co-pathogenic genes of non-alcoholic fatty liver disease and hepatocellular carcinoma

Background

Non-alcoholic fatty liver disease (NAFLD) is a risk factor for hepatocellular carcinoma (HCC). However, its carcinogenic mechanism is still unclear, looking for both diseases’ transcriptome levels, the same changes as we are looking for NAFLD may provide a potential mechanism of action of HCC. Thus, our study aimed to discover the coexisting pathogenic genes of NAFLD and HCC.

Methods

We performed a variance analysis with public data for both diseases. At the same time, weighted gene correlation network analysis (WGCNA) was used to find highly correlated gene modules in both diseases. The darkturquoise gene module was found to be highly correlated with both diseases. Based on the diagnosis related module genes and the differential genes of the two diseases, we constructed diagnostic and prognostic models by logistic regression, univariate Cox regression, and LASSO regression. Public datasets verified the results. Meanwhile, we built a competing endogenous RNA (ceRNA) network based on the model genes and explored the related pathways and immune correlation involved in the two diseases by using Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analyses. Immunohistochemistry was used to verify the different expression of ABCC5 and TUBG1 among the normal liver, NAFLD, and HCC tissues. Sodium palmitate/sodium oleate was used to establish high-fat cell models, and Real Time Quantitative Polymerase Chain Reaction (RT-qPCR) was used to verify the messenger RNA (mRNA) expression of ABCC5 in lipidization cells.

Results

A total of 26 upregulated genes and 87 downregulated genes were found using limma package identification analysis. According to WGCNA, the darkturquoise gene module was highly correlated with the prognosis of both diseases. The coexisting genes acquired by the two groups were only three central genes, that is, ABCC5, DHODH and TUBG1. The results indicated that the diagnostic and prognostic models constructed by ABCC5 and TUBG1 genes had high accuracy in both diseases. The results of immunohistochemistry showed that ABCC5 and TUBG1 were significantly overexpressed in NAFLD and HCC tissues compared with normal liver tissues. The Oil Red O staining and triglyceride identified the successful construction of HepG2 and LO2 high-fat models using PA/OA. The results of RT-qPCR showed that the lipidization of LO2 and HepG2 increased the mRNA expression of ABCC5.

Conclusions

The gene model constructed by ABCC5 and TUBG1 has high sensibility and veracity in the diagnosis of NAFLD as well as the diagnosis and prognosis of HCC. ABCC5 and TUBG1 may play an important role in the development of NAFLD to HCC. In addition, lipidization could upregulate the mRNA expression of ABCC5 in HCC.