A miR-212-3p/SLC6A1 Regulatory Sub-Network for the Prognosis of Hepatocellular Carcinoma

Transcription factor ASCL1 targets SLC6A13 to inhibit the progression of hepatocellular carcinoma via the glycine-inflammasome signaling

Hepatocellular carcinoma (HCC), the most common primary liver cancer, typically arises from chronic liver conditions such as hepatitis, cirrhosis, or other chronic liver diseases, and is characterized by its aggressive nature and poor prognosis. The purpose of this research was to clarify the function of achaete-scute family bHLH transcription factor 1 (ASCL1) and solute carrier family 6 member 13 (SLC6A13) in influencing tumor cell behavior, inflammatory responses, and the regulation of inflammasomes. We analyzed the differentially expressed genes (DEGs) in the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) database, as well as in the GSE14520 and GSE67764 datasets, to identify the expression changes of SLC6A13 in liver cancer. The prognostic significance of SLC6A13 in LIHC was assessed through Kaplan-Meier survival curve analysis. Transcriptional regulation of SLC6A13 by ASCL1 was explored using the Joint Annotation of the Human Genome and other species by the Systematic Pipeline for the Annotation of Regulatory Regions (JASPAR) database and dual-luciferase assays. In vitro experiments investigated the impact of ASCL1 and SLC6A13 overexpression on HCC cell growth. Additionally, the effects of ethanol treatment and glycine modulation on the inflammatory response in HCC cell lines were evaluated. HCC samples showed reduced levels of SLC6A13, which correlates with a better prognosis for liver metastases. Elevated SLC6A13 expression correlated with improved overall survival (OS), progression-free survival (PFS), recurrence-free survival (RFS), and disease-specific survival (DSS). ASCL1 upregulated SLC6A13 and inhibited proliferation, migration, and invasion of HCC cells. Ethanol induced the production of inflammatory cytokines, which was enhanced by overexpression of SLC6A13 but counteracted by glycine. This study highlighted elevated expression of SLC6A13 in LIHC which has been correlated with improved OS, PFS, RFS, and DSS. Overexpression of SLC6A13 and ASCL1 in HCC cells enhanced inflammasome activation, which was exacerbated by ethanol and attenuated by glycine.

Identification and validation of functional roles for three MYC-associated genes in hepatocellular carcinoma

BACKGROUND

Aberrations in MYC underlie a large proportion of liver hepatocellular carcinoma (LIHC) cases; however, MYC is difficult to target because of its undruggable structure. We aimed to uncover MYC-associated molecular targets to provide new strategies for LIHC treatment.

METHODS

LIHC transcriptome datasets and clinical information were obtained from The Cancer Genome Atlas. A series of bioinformatics analyses were performed for 370 patients who were stratified based on the median MYC expression level (high-MYC group and low-MYC group). Correlation analysis was performed to determine relationships between the expression of key MYC-associated genes and prognosis, DNA promotor methylation, and immune cell infiltration. Gene ontology and Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analyses were performed to elucidate the functions of these genes in LIHC. Their expression and functions in LIHC were further verified using transgenic mice overexpressing c-Myc under control of the hepatocyte-specific promoter (Alb-Cre).

RESULTS

AURKB, CCNB2, and CDKN3 were overexpressed in LIHC patients with high MYC expression and were associated with poor prognosis. Upregulation of these 3 genes was significantly correlated with hypomethylated promoter status, advanced T stage, metastasis, and immune cell infiltration in LIHC patients. Functional enrichment analyses indicated that these genes participate in the "p53 signaling pathway" and "cell cycle". Furthermore, RT-PCR and IHC analysis revealed that their mRNA and protein expression levels were upregulated in an Alb-Cre;cMYClsl/- mouse model. Drugs that target these 3 MYC-related genes were identified.

CONCLUSION

Taken together, our results identify biomarkers of potential utility for managing liver cancer therapy owing to their significance in tumorigenesis, proliferation, and tumor immunity.

Overview of MicroRNAs as Diagnostic and Prognostic Biomarkers for High-Incidence Cancers in 2021

MicroRNAs (miRNAs) are small non-coding RNAs (ncRNAs) about 22 nucleotides in size, which play an important role in gene regulation and are involved in almost all major cellular physiological processes. In recent years, the abnormal expression of miRNAs has been shown to be associated with human diseases including cancer. In the past ten years, the link between miRNAs and various cancers has been extensively studied, and the abnormal expression of miRNAs has been reported in various malignant tumors, such as lung cancer, gastric cancer, colorectal cancer, liver cancer, breast cancer, and prostate cancer. Due to the high malignancy grade of these cancers, it is more necessary to develop the related diagnostic and prognostic methods. According to the study of miRNAs, many potential cancer biomarkers have been proposed for the diagnosis and prognosis of diseases, especially cancer, thus providing a new theoretical basis and perspective for cancer screening. The use of miRNAs as biomarkers for diagnosis or prognosis of cancer has the advantages of being less invasive to patients, with better accuracy and lower price. In view of the important clinical significance of miRNAs in human cancer research, this article reviewed the research status of miRNAs in the above-mentioned cancers in 2021, especially in terms of diagnosis and prognosis, and provided some new perspectives and theoretical basis for the diagnosis and treatment of cancers.

Integrated Analysis of DNA Repair Genes Identifies SLC6A1 as a New Marker for the Clinical Outcome of Patients with Colorectal Cancer

Colorectal cancer (CRC) remains an important malignancy worldwide with poor prognosis. It has been known that DNA repair genes are involved in the development and progression of various tumors. Therefore, the purpose of this study was to explore DNA repair gene-based prognostic biomarkers for CRC. In this study, the expressing pattern and prognostic values of DNA repair genes in CRC patients were analyzed using TCGA database. GO and KEGG enrichment analyses were conducted to clarify the functional roles of dysregulated genes. We observed 358 differentially expressed DNA repair genes in CRC specimens, including 84 downregulated genes and 275 upregulated genes. 36 survival-related DNA repair genes were correlated with CRC patients' five-year survival, including 6 low-risk genes and 30 high-risk genes. Among the 10 overlapping genes, we focused on SLC6A1 which was highly expressed in CRC, and multivariate analysis confirmed that SLC6A1 expression as well as age and clinical stage could be regarded as an independent predicting factor for CRC prognosis. KEGG assays revealed that SLC6A1 may influence the clinical progression via regulating TGF-beta and PI3K-Akt signaling pathways. In addition, we observed that SLC6A1 was negatively regulated by SLC6A1 methylation, leading to its low expression in CRC specimens. Overall, SLC6A1 is upexpressed in CRC and can be used as a marker of poor prognosis in CRC patients.

Immune-Related lncRNA Pairs Clinical Prognosis Model Construction for Hepatocellular Carcinoma

Background

Long non-coding RNA (lncRNA) plays an essential regulatory role in the occurrence and development of hepatocellular carcinoma (HCC). This paper aims to establish an immune-related lncRNA (irlncRNA) pairs model independent of expression level for risk assessment and prognosis prediction of HCC.

Methods

Transcriptome data and corresponding clinical data were downloaded from TCGA. HCC patients were randomly divided into training group and test group. Univariate Cox regression analysis, LASSO regression analysis, and stepwise multiple Cox regression analysis were used to establish a prognostic model. The prediction ability of the model was verified by ROC curves. Next, the patients were divided into low-risk and high-risk groups. We compared the differences between the two groups in survival rate, clinicopathological characteristics, tumor immune cell infiltration status, chemotherapeutic drug sensitivity and immunosuppressive molecules.

Results

A prognosis prediction model was established based on 7 irlncRNA pairs, namely irlncRNA pairs (IRLP). ROC curves of the training group and test group showed that the IRLP model had high sensitivity and specificity for survival prediction. Kaplan–Meier analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group. Immune cell infiltration analysis showed that the high-risk group was significantly correlated with various immune cell infiltration. Finally, there were statistically significant differences in chemosensitivity and molecular marker expression between the two groups.

Conclusion

The prognosis prediction model established by irlncRNA pairs has a certain guiding significance for the prognosis prediction of HCC. It may provide valuable clinical applications in antitumor immunotherapy.