Loss of ARID1A Promotes Hepatocellular Carcinoma Progression via Up-regulation of MYC Transcription

Molecular and pathological landscape of the AT-rich interaction domain 1A (ARID1A) mutation in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, with complex etiological factors and a diverse genetic landscape. Among the critical genetic mutations in HCC, the AT-rich interaction domain 1 A (ARID1A) gene, a key component of the SWI/SNF chromatin remodeling complex, stands out due to its significant role in both tumor suppression and oncogenesis. This review comprehensively examines the molecular and pathological impacts of ARID1A mutations in HCC. ARID1A mutations, which occur in approximately 7.9 % of HCC cases, predominantly involve truncating mutations leading to loss of function. These mutations are associated with various aggressive cancer features, including larger tumor size, higher rates of metastasis, and poor prognosis. The dual role of ARID1A in HCC is context-dependent, acting as a tumor suppressor by regulating cell cycle control, DNA damage repair, and gene expression, while also displaying oncogenic properties in specific contexts by promoting early tumorigenesis through oxidative stress pathways. Understanding the molecular mechanisms of ARID1A, including its interactions with key cellular pathways such as PI3K/AKT/mTOR, β-catenin, and PD-L1, provides insights into its complex role in HCC pathogenesis. Furthermore, ARID1A's impact on cancer stem cell maintenance, metabolic reprogramming, and immune evasion underscores its potential as a therapeutic target. This review highlights the need for context-specific therapeutic strategies targeting ARID1A, which could lead to more effective treatments for HCC, addressing both its tumor-suppressive and oncogenic activities.

A mutational signature and ARID1A mutation associated with outcome in hepatocellular carcinoma

OBJECTIVE

The prognosis of hepatocellular carcinoma (HCC) is poor and there is no stable and reliable molecular biomarker for evaluation. This study attempted to find reliable prognostic markers from tumor mutational profiles.

METHODS

A total of 362 HCC samples with whole-exome sequencing were collected as discovery datasets, and 200 samples with targeted sequencing were used for validation of the relevant results. All HCC samples were obtained from previously published studies. Bayesian non-negative matrix factorization was used to extract mutational signatures, and multivariate Cox regression models were utilized to identify the prognostic role of mutational factors. Gene set enrichment analysis was employed to discover potential signaling pathways associated with specific mutational groups.

RESULTS

In the HCC discovery dataset, a total of four mutational signatures (i.e., signatures 4, 6, 16, and 22) were extracted, of which signature 16 characterized by T>C mutations was observed to be associated with favorable HCC prognosis, and this correlation was also found in the validation dataset. Further analysis showed that patients with ARID1A mutations exhibited inferior survival outcomes in both discovery and validation datasets. Mechanistic exploration revealed that the presence of signature 16 was associated with better immune infiltration and tumor immunogenicity, while patients with ARID1A mutations were away from these favorable immunological features.

CONCLUSION

By integrating somatic mutation data and clinical information of HCC, this study identified that signature 16 and ARID1A mutations were associated with better and worse outcomes respectively, providing a basis for prognosis prediction and clinical treatment strategies of HCC.

Identification of a DNA damage repair-related LncRNA signature for predicting the prognosis and immunotherapy response of hepatocellular carcinoma

BACKGROUND

DNA damage repair (DDR) may affect tumorigenesis and therapeutic response in hepatocellular carcinoma (HCC). Long noncoding RNAs (LncRNAs) can regulate DDR and play a vital role in maintaining genomic stability in cancers. Here, we identified a DDR-related prognostic signature in HCC and explored its potential clinical value.

METHODS

Data of HCC samples were obtained from the Cancer Genome Atlas (TCGA), and a list of DDR-related genes was extracted from the Molecular Signatures database (MSigDB). A DDR-related lncRNAs signature associated to overall survival (OS) was constructed using the least absolute shrinkage and selection operator-cox regression, and was further validated by the Kaplan-Meier curve and receiver operating characteristic curve. A nomogram integrating other clinical risk factors was established. Moreover, the relationships between the signature with somatic mutation, immune landscape and drug sensitivity were explored.

RESULTS

The prognostic model of 5 DDR-related lncRNAs was constructed and classified patients into two risk groups at median cut-off. The low-risk group had a better OS, and the signature was an independent prognostic indicator in HCC. A nomogram of the signature combined with TNM stage was constructed. TP53 gene was more frequently mutated in the high-risk group. Marked differences in immune cells were observed, such as CD4 + T cells, NK cells and macrophages, between the two groups. Moreover, an increase in the expression of immune checkpoint molecules was found in the high-risk group. The low-risk group presented with a significantly higher response to sorafenib or cisplatin. Finally, potential value of this signature was validated in real-world HCC patients.

CONCLUSION

Our findings provided a promising insight into DDR-related lncRNAs in HCC and a personalized prediction tool for prognosis and therapeutic response.

Identification of multi-omics biomarkers and construction of the novel prognostic model for hepatocellular carcinoma

Genome changes play a crucial role in carcinogenesis, and many biomarkers can be used as effective prognostic indicators in various tumors. Although previous studies have constructed many predictive models for hepatocellular carcinoma (HCC) based on molecular signatures, the performance is unsatisfactory. Because multi-omics data can more comprehensively reflect the biological phenomenon of disease, we hope to build a more accurate predictive model by multi-omics analysis. We use the TCGA to identify crucial biomarkers and construct prognostic models through difference analysis, univariate Cox, and LASSO/stepwise Cox analysis. The performances of predictive models were evaluated and validated through survival analysis, Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Multiple mRNAs, lncRNAs, miRNAs, CNV genes, and SNPs were significantly associated with the prognosis of HCC. We constructed five single-omic models, and the mRNA and lncRNA models showed good performance with c-indexes over 0.70. The multi-omics model presented a robust predictive ability with a c-index over 0.77. This study identified many biomarkers that may help study underlying carcinogenesis mechanisms in HCC. In addition, we constructed multiple single-omic models and an integrated multi-omics model that may provide practical and reliable guides for prognosis assessment.

Progress of delivery methods for CRISPR-Cas9

INTRODUCTION

Gene therapy is becoming increasingly common in clinical practice, giving hope for the correction of a wide range of human diseases and defects. The CRISPR/Cas9 system, consisting of the Cas9 nuclease and single-guide RNA (sgRNA), has revolutionized the field of gene editing. However, efficiently delivering the CRISPR-Cas9 to the target organ or cell remains a significant challenge. In recent years, with rapid advances in nanoscience, materials science, and medicine, researchers have developed various technologies that can deliver CRISPR-Cas9 in different forms for in vitro and in vivo gene editing. Here, we review the development of the CRISPR-Cas9 and describe the delivery forms and the vectors that have emerged in CRISPR-Cas9 delivery, summarizing the key barriers and the promising strategies that vectors currently face in delivering the CRISPR-Cas9.

AREAS COVERED

With the rapid development of CRISPR-Cas9, delivery methods are becoming increasingly important in the in vivo delivery of CRISPR-Cas9.

EXPERT OPINION

CRISPR-Cas9 is becoming increasingly common in clinical trials. However, the complex nuclease and protease environment is a tremendous challenge for in vivo clinical applications. Therefore, the development of delivery methods is highly likely to take the application of CRISPR-Cas9 technology to another level.

Effect of CRISPR Knockout of AXIN1 or ARID1A on Proliferation and Migration of Porcine Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is an aggressive disease lacking effective treatment. Animal models of HCC are necessary for preclinical evaluation of the safety and efficacy of novel therapeutics. Large animal models of HCC allow testing image-guided locoregional therapies, which are widely used in the management of HCC. Models with precise tumor mutations mimicking human HCC provide valuable tools for testing precision medicine. AXIN1 and ARID1A are two of the most frequently mutated genes in human HCC. Here, we investigated the effects of knockout of AXIN1 and/or ARID1A on proliferation, migration, and chemotherapeutic susceptibility of porcine HCC cells and we developed subcutaneous tumors harboring these mutations in pigs. Gene knockout was achieved by CRISPR/Cas9 and was validated by Next Generation Sequencing. AXIN1 knockout increased the migration of porcine HCC cells but did not alter the cell proliferation. Knockout of ARID1A increased both the proliferation and migration of porcine HCC cells. Simultaneous knockout of AXIN1 and ARID1A increased the migration, but did not alter the proliferation of porcine HCC cells. The effect of gene knockout on the response of porcine HCC cells to two of the most commonly used systemic and locoregional HCC treatments was investigated; sorafenib and doxorubicin, respectively. Knockout of AXIN1 and/or ARID1A did not alter the susceptibility of porcine HCC cells to sorafenib or doxorubicin. Autologous injection of CRISPR edited HCC cells resulted in development of subcutaneous tumors in pigs, which harbored the anticipated edits in AXIN1 and/or ARID1A. This study elucidates the effects of CRISPR-mediated knockout of HCC-associated genes in porcine HCC cells, and lays the foundation for development and utilization of genetically-tailored porcine HCC models for in vivo testing of novel therapeutic approaches in a clinically-relevant large animal model.