Long non-coding RNA muskelin 1 antisense RNA as a potential therapeutic target in hepatocellular carcinoma treatment

LincRNA-miR interactions in hepatocellular carcinoma: comprehensive review and in silico analysis: a step toward ncRNA precision

The most prevalent form of primary liver cancer and one of the chief drivers of cancer-related mortality globally is hepatocellular carcinoma (HCC). Imminent evidence has indicated that non-coding RNAs (ncRNAs) play an integral part in the development and propagation of HCC. RNA stabilization, transcription regulation, chromatin and genomic architecture remodeling, enhancer-associated activity, and other varied properties set long intergenic ncRNA (lincRNA) genes apart from messenger RNA (mRNA)-encoding genes. Through a variety of processes, lincRNAs may generally be used to fine-tune the transcription of nearby genes with exceptional tissue specificity, underscoring our quickly developing knowledge of the non-coding genome. Through their binding with divergent cell targets, some HCC-related ncRNAs have been demonstrated to exhibit abnormal expression, contribute to malignant growth, evade apoptosis, and have invasive potential. Therefore, a better comprehension of lincRNA dysregulation might offer novel perspectives on the pathophysiology of HCC as well as innovative instruments for the early detection and management of HCC. In the present review, we provide an overview of the increasing relevance of lincRNAs as a major contributor to the pathophysiology of HCC, emphasizing their influence on signaling pathways implicated in the development, progression, and response to treatment of tumors. In addition, we go over the new approaches that target lincRNAs for HCC treatment as well as the possible therapeutic uses of lincRNAs as prognostic and diagnostic biomarkers for HCC.

Diagnostic and Therapeutic Advances of RNAs in Precision Medicine of Gastrointestinal Tumors

Gastrointestinal tumors present a significant challenge for precision medicine due to their complexity, necessitating the development of more specific diagnostic tools and therapeutic agents. Recent advances have positioned coding and non-coding RNAs as emerging biomarkers for these malignancies, detectable by liquid biopsies, and as innovative therapeutic agents. Many RNA-based therapeutics, such as small interfering RNA (siRNA) and antisense oligonucleotides (ASO), have entered clinical trials or are available on the market. This review provides a narrative examination of the diagnostic and therapeutic potential of RNA in gastrointestinal cancers, with an emphasis on its application in precision medicine. This review discusses the current challenges, such as drug resistance and tumor metastasis, and highlights how RNA molecules can be leveraged for targeted detection and treatment. Additionally, this review categorizes specific diagnostic biomarkers and RNA therapeutic targets based on tissue type, offering a comprehensive analysis of their role in advancing precision medicine for gastrointestinal tumors.

Lenvatinib and immune-checkpoint inhibitors in hepatocellular carcinoma: mechanistic insights, clinical efficacy, and future perspectives

Lenvatinib is a multi-target tyrosine kinase inhibitor widely used in the treatment of hepatocellular carcinoma (HCC). Its primary mechanism of action involves inhibiting signal pathways such as vascular endothelial growth factor receptors (VEGFR) and fibroblast growth factor receptors (FGFR), thereby reducing tumor cell proliferation and angiogenesis and affecting the tumor's immune microenvironment. In the treatment of liver cancer, although lenvatinib monotherapy has shown good clinical effect, the problem of drug resistance is becoming more and more serious. This resistance may be caused by a variety of factors, including genetic mutations, signaling pathway remodeling, and changes in the tumor microenvironment. In order to overcome drug resistance, the combination of lenvatinib and other therapeutic strategies has gradually become a research hotspot, and it is worth noting that the combination of lenvatinib and immune checkpoint inhibitors (ICIs) has shown a good application prospect. This combination not only enhances the anti-tumor immune response but also helps improve therapeutic efficacy. However, combination therapy also faces challenges regarding safety and tolerability. Therefore, studying the mechanisms of resistance and identifying relevant biomarkers is particularly important, as it aids in early diagnosis and personalized treatment. This article reviews the mechanisms of lenvatinib in treating liver cancer, the mechanisms and efficacy of its combination with immune checkpoint inhibitors, the causes of resistance, the exploration of biomarkers, and other novel combination therapy strategies for lenvatinib. We hope to provide insights into the use and research of lenvatinib in clinical and scientific settings, offering new strategies for the treatment of liver cancer.

LncRNA MKLN1-AS promotes glioma tumorigenesis and growth via activating the Hippo pathway through miR-126-5p/TEAD1 axis

The involvement of long non-coding RNAs (lncRNAs) in glioma carcinogenesis has gradually been identified. Herein, we aimed to explore the function and mechanism of lncRNA muskelin 1 antisense RNA (MKLN1-AS) in glioma cell oncogenic properties. Quantitative real-time polymerase chain reaction was utilized to test the expression of MKLN1-AS, miR-126-5p, and TEAD1 (TEA Domain Transcription Factor 1) mRNA expression. Oncogenic properties of glioma cells were characterized using 5-ethynyl-2'-deoxyuridine, flow cytometry, wound healing, transwell, and tube formation assays, respectively. Levels of TEAD1 protein, mobility-related proteins, and Hippo pathway-related proteins were examined by Western blotting. The binding between miR-126-5p and MKLN1-AS or TEAD1 was confirmed by using dual-luciferase reporter and pull-down assays. The murine xenograft model was established for in vivo analysis. Levels of MKLN1-AS in glioma tissues and cell lines were higher, functionally, MKLN1-AS deficiency could suppress glioma cell proliferation, migration, invasion, and angiogenesis, and induce apoptosis in vitro, as well as impede tumor growth in vivo. Mechanistically, miR-126-5p was targeted by MKLN1-AS, miR-126-5p directly targeted TEAD1. The suppressing effects of MKLN1-AS deficiency on glioma cell oncogenic properties were abolished by TEAD1 overexpression or miR-126-5p inhibition. Besides, MKLN1-AS/miR-126-5p mediates the activation of Hippo pathway by TEAD1. MKLN1-AS knockdown weakened glioma cell oncogenic phenotypes and growth via TEAD1-Hippo pathway through miR-126-5p, indicating a new therapeutic target for glioma molecular therapy.

Deciphering the nexus between long non-coding RNAs and endoplasmic reticulum stress in hepatocellular carcinoma: biomarker discovery and therapeutic horizons

Hepatocellular carcinoma (HCC) remains a significant global health challenge with few effective treatment options. The dysregulation of endoplasmic reticulum (ER) stress responses has emerged as a pivotal factor in HCC progression and therapy resistance. Long non-coding RNAs (lncRNAs) play a crucial role as key epigenetic modifiers in this process. Recent research has explored how lncRNAs influence ER stress which in turn affects lncRNAs activity in HCC. We systematically analyze the current literature to highlight the regulatory roles of lncRNAs in modulating ER stress and vice versa in HCC. Our scrutinization highlights how dysregulated lncRNAs contribute to various facets of HCC, including apoptosis resistance, enhanced proliferation, invasion, and metastasis, all driven by ER stress. Moreover, we delve into the emerging paradigm of the lncRNA-miRNA-mRNA axis, elucidating it as the promising avenue for developing novel biomarkers and paving the way for more personalized treatment options in HCC. Nevertheless, we acknowledge the challenges and future directions in translating these insights into clinical practice. In conclusion, our review provides insights into the complex regulatory mechanisms governing ER stress modulation by lncRNAs in HCC.

Identification and validation of a five-necroptosis-related lncRNAs signature for prognostic prediction in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is among the most prevalent digestive system malignancies and is associated with a poor prognosis. Necroptosis, a form of regulated death mediated by death receptors, exhibits characteristics of both necrosis and apoptosis. Long non-coding RNAs (lncRNAs) have been identified as crucial regulators in tumor necroptosis. This study aims to identify the necroptosis-related lncRNAs (np-lncRNA) in HCC and investigate their relationships with prognosis.

Method

The RNA-sequencing data, along with clinicopathological and survival information of HCC patients were sourced from The Cancer Genome Atlas (TCGA) database. The np-lncRNAs were analyzed to assess their potential in predicting HCC prognosis. Prognostic signatures related to necroptosis were constructed using stepwise multivariate Cox regression analysis. The prognosis of patients was compared using Kaplan-Meier (KM) analysis. The accuracy of the prognostic signature was evaluated using Receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Quantitative real-time polymerase chain reaction(qPCR) was employed to validate the lncRNAs expression levels of lncRNAs among samples from an independent cohort.

Results

The np-lncRNAs ZFPM2-AS1, AC099850.3, BACE1-AS, KDM4A-AS1 and MKLN1-AS were identified as potential prognostic biomarkers. The prognostic signature constructed from these np-lncRNAs achieved an Area Under the Curve (AUC) of 0.773. Based on the risk score derived from the signature, patients were divided into two groups, with the high-risk group exhibiting poorer overall survival. Gene Set Enrichment Analysis (GSEA) revealed significantly different between the low risk and high risk groups in tumor-related pathways (such as mTOR, MAPK and p53 signaling pathways) and immune-related functions (like T cell receptor signaling pathway and natural killer cell mediated cytotoxicity). The increased expression of np-lncRNAs was confirmed in another independent HCC cohort.

Conclusions

This signature offers a dependable method for forecasting the prognosis of HCC patients. Our findings indicate a subset of np-lncRNA biomarkers that could be utilized for prognosis prediction and personalized treatment strategies of HCC patients.

Roles of clinical application of lenvatinib and its resistance mechanism in advanced hepatocellular carcinoma (Review)

Lenvatinib (LEN) is a multi-target TKI, which plays a pivotal role in the treatment of advanced hepatocellular carcinoma (HCC). The inevitable occurrence of drug resistance still prevents curative potential and is deleterious for the prognosis, and a growing body of studies is accumulating, which have devoted themselves to unveiling its underlying resistance mechanism and made some progress. The dysregulation of crucial signaling pathways, non-coding RNA and RNA modifications were proven to be associated with LEN resistance. A range of drugs were found to influence LEN therapeutic efficacy. In addition, the superiority of LEN combination therapy has been shown to potentially overcome the limitations of LEN monotherapy in a series of research, and a range of promising indicators for predicting treatment response and prognosis have been discovered in recent years. In this review, we summarize the latest developments in LEN resistance, the efficacy and safety of LEN combination therapy as well as associated indicators, which may provide new insight into its resistance as well as ideas in the treatment of advanced HCC.

Construction of a prognostic model for disulfidptosis-related long noncoding RNAs in R0 resected hepatocellular carcinoma and analysis of their impact on malignant behavior

BACKGROUND

Disulfidptosis is an emerging form of cellular death resulting from the binding of intracellular disulfide bonds to actin cytoskeleton proteins. This study aimed to investigate the expression and prognostic significance of hub disulfidptosis-related lncRNAs (DRLRs) in R0 resected hepatocellular carcinoma (HCC) as well as their impact on the malignant behaviour of HCC cells.

METHODS

A robust signature for R0 resected HCC was constructed using least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression and was validated in an independent internal validation cohort to predict the prognosis of R0 HCC patients. Comprehensive bioinformatics analysis was performed on the hub DRLRs (KDM4A-AS1, MKLN1-AS, and TMCC1-AS1), followed by experimental validation using quantitative real-time polymerase chain reaction (qRT‒PCR) and cellular functional assays.

RESULTS

The signature served as an independent prognostic factor applicable to R0 HCC patients across different age groups, tumour stages, and pathological characteristics. Gene Ontology (GO) and gene set enrichment analysis (GSEA) revealed hub pathways associated with this signature. The high-risk group presented an increased abundance of M0 macrophages and activated memory CD4 T cells as well as elevated macrophage and major histocompatibility complex (MHC) class I expression. High-risk R0 HCC patients also presented increased tumour immune dysfunction and exclusion scores (TIDEs), mutation frequencies, and tumour mutational burdens (TMBs). Drug sensitivity analysis revealed that high-risk patients were more responsive to drugs, including GDC0810 and osimertinib. High expression levels of the three hub DRLRs were detected in R0 HCC tissues and HCC cell lines. Functional assays revealed that the three hub DRLRs enhanced HCC cell proliferation, migration, and invasion.

CONCLUSIONS

A signature was constructed on the basis of three DRLRs, providing novel insights for personalized precision therapy in R0 HCC patients.

A novel disulfidptosis-related lncRNA signature for predicting prognosis and potential targeted therapy in hepatocellular carcinoma

Disulfidptosis is a recently discovered mode of cell death with a significant role in cancer. Long non-coding RNAs (lncRNAs) have been implicated in numerous biological processes including oncogenesis, invasion, and metastasis. In this work, we developed an lncRNA signature associated with disulfidptosis for prediction of survival of hepatocellular carcinoma (HCC) patients. Detailed HCC expression profiles and clinical information were obtained from The Cancer Genome Atlas, and 599 differentially expressed disulfidptosis-related lncRNAs were identified through Pearson correlation analysis. Finally, by the least absolute shrinkage and selection operator method, we constructed an HCC prognostic model containing 7 disulfidptosis-related lncRNAs. We split patients into high- and low-risk groups based on the risk values generated by this model and showed that patients in the high-risk group had shorter overall survival times. In the training dataset, receiver operating characteristic curves for 1-, 3-, and 5-year survival were drawn according to the standard (0.788, 0.801, 0.803) and internal validation set (0.684, 0.595, 0.704) to assess the efficacy of the signature. Risk value was confirmed as an independent predictor and used to construct a nomogram in combination with several clinical factors. We further assessed the signature with respect to tumor immune landscape, gene set enrichment analysis, principal component analysis, tumor mutation burden, tumor immune dysfunction and exclusion, and drug sensitivity. High-risk patients had higher immune function scores, except for type II IFN response, whereas low-risk patients had significantly lower tumor immune dysfunction and rejection scores, indicating that they were more sensitive to immune checkpoint inhibitors. Drug sensitivity analysis showed that low-risk patients could benefit more from certain anti-tumor drugs, including sulafenib. In summary, we have constructed a novel signature that shows good performance in predicting survival of patients with HCC and may provide new insights for targeted tumor therapy.

Analysis of long non-coding RNAs associated with disulfidptosis for prognostic signature and immunotherapy response in uterine corpus endometrial carcinoma

Disulfidptosis, the demise of cells caused by the abnormal breakdown of disulfide bonds and actin in the cytoprotein backbone, has attracted attention in studies concerning disulfide-related cell death and its potential implications in cancer treatment. This study utilized bioinformatics to detect disulfidptosis associated lncRNA prognostic markers (DALPMs) with Uterine Corpus Endometrial Carcinoma (UCEC)-related to investigate the correlation between these indicators and the tumor immune microenvironment. The RNA sequencing data and somatic mutation information of patients with UCEC were obtained from the Cancer Genome Atlas (TCGA) database. Patients were randomly divided into Train and Test groups. The findings revealed a potential prognostic model comprising 14 DALPMs. Both univariate and multivariate Cox analyses demonstrated that the model-derived risk score functioned as a standalone prognostic indicator for patients. Significant disparities in survival outcomes were observed between the high- and low-risk groups as defined by the model. Differences in tumor mutational burden (TMB), tumor immune dysfunction and exclusion (TIDE), and tumor microenvironment (TME) stromal cells between patients of the high- and low-risk groups were also observed. The forecast model comprising long non-coding RNAs (lncRNAs) associated with disulfidptosis can effectively anticipate patients' prognoses.

Integrating bulk and single-cell RNA sequencing data to establish necroptosis-related lncRNA risk model and analyze the immune microenvironment in hepatocellular carcinoma

Background

The increasing evidence suggests that necroptosis mediates many behaviors of tumors, as well as the regulation of the tumor microenvironment. Long non-coding RNAs (lncRNAs) are involved in a variety of regulatory processes during tumor development and are significantly associated with patient prognosis. It suggests that necroptosis-related lncRNAs (NRlncRNAs) may serve as biomarkers for the prognosis of hepatocellular carcinoma (HCC).

Methods

lncRNA expression profiles of HCC were obtained from TCGA database. LncRNAs associated with necroptosis were extracted using correlation analysis. Prognostic models were constructed based on least absolute shrinkage and selection operator algorithm (LASSO) and multivariate Cox regression analysis. The differences of tumor microenvironment between high-risk and low-risk groups were further analyzed. Single-cell RNA sequencing data of HCC was performed to assess the enrichment of necroptosis-related genes in immune cell subsets. Finally, real-time RT-PCR was used to detect the prognosis-related lncRNAs expression in different HCC cell lines.

Results

We constructed a prognostic signature based on 8 NRlncRNAs, which also showed good predictive accuracy. The model showed that the prognosis of patients with high-risk score was significantly worse than that of patients with low-risk score (P < 0.05). Combined with the clinical characteristics and risk score of HCC, Nomogram was drawn for reference in clinical practice. In addition, immune cell infiltration analysis and single cell RNA sequencing analysis showed that a low level of immune infiltration was observed in patients at high risk and that there was a significant correlation between NRlncRNAs and macrophages. The results of RT-qPCR also showed that 8 necroptosis-related lncRNAs were highly expressed in HCC cell lines and human liver cancer tissues.

Conclusion

This prognostic signature based on the necroptosis-related lncRNAs may provide meaningful clinical insights for the prognosis and immunotherapy responses in patients with HCC.

Bioinformatics prediction and experimental verification identify cuproptosis-related lncRNA as prognosis biomarkers of hepatocellular carcinoma

Cuproptosis is a form of cell death caused by intracellular copper excess, which plays an important regulatory role in the development and progression of cancers, including hepatocellular carcinoma (HCC), a prevalent malignancy with high morbidity and mortality. This study aimed to create a cuproptosis associated long non-coding RNAs (CAlncRNAs)signature to predict HCC patient survival and immunotherapy response. Firstly, we identified 509 CAlncRNAs using Pearson correlation analysis in The Cancer Genome Atlas (TCGA) datasets, before the three CAlncRNAs (MKLN1-AS, FOXD2-AS1, LINC02870) with the most prognostic value were further screened. Then, we constructed a prognostic risk model for HCCwas using univariate and LASSO Cox regression analyses. Multivariate Cox regression analyses illustrated that this model was an independent prognostic factor for overall survival (OS) prediction, outperforming traditional clinicopathological factors. And the risk score not only could be prognostic factors independent of other factors but also suited for patients with diverse ages, stages, and grades. The 1-, 3-, and 5- years areas under the curves (AUC) values of the model were 0.759, 0.668 and 0.674 respectively. Pathway analyses showed that the high-risk groupenriched in immune-related pathways. Importantly, patients with higher risk scores exhibited higher mutation frequency, higher TMB scores, and lower TIDE scores. Besides, we screened for two chemical drugs (A-443654 and Pyrimethamine) with the greatest value for high-risk HCC patients. Finally, the abnormal high expression of the three CAlncRNAs were confirmed in HCC tissues and cells by Real Time Quantitative PCR (RT-qPCR). And proliferative, migratory and invasion abilities of HCC cell were restrained via silencing CAlncRNAs expression in vitro. In summary, we built a CAlncRNAs-based risk score model, which can be a candidate for HCC patients prognostic prediction and offer some useful information for immunotherapies.

Lnc-ZEB2-19 Inhibits the Progression and Lenvatinib Resistance of Hepatocellular Carcinoma by Attenuating the NF-κB Signaling Pathway through the TRA2A/RSPH14 Axis

Long non-coding RNAs have been reported to play a crucial role in tumor progression in hepatocellular carcinoma (HCC). Lnc-ZEB2-19 has been validated to be deficiently expressed in HCC. However, the capabilities and underlying mechanisms of lnc-ZEB2-19 remain uncertain. In this study, we verified that the downregulation of lnc-ZEB2-19 was prevalent in HCC and significantly correlated with the unfavorable prognosis. Further in vitro and in vivo verified that lnc-ZEB2-19 notably inhibited the proliferation, metastasis, stemness, and lenvatinib resistance (LR) of HCC cells. Mechanistically, lnc-ZEB2-19 inhibited HCC progression and LR by specifically binding to transformer 2α (TRA2A) and promoting its degradation, which resulted in the instability of RSPH14 mRNA, leading to the downregulation of Rela(p65) and p-Rela(p-p65). Furthermore, rescue assays showed that silencing RSPH14 partially restrained the effect of knockdown expression of lnc-ZEB2-19 on HCC cell metastatic ability and stemness. The findings describe a novel regulatory axis, lnc-ZEB2-19/TRA2A/RSPH14, downregulating the nuclear factor kappa B to inhibit HCC progression and LR.

Dimeric oxyberberine CT4-1 targets LINC02331 to induce cytotoxicity and inhibit chemoresistance via suppressing Wnt/β-catenin signaling in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a type of cancer characterized by high recurrence rates. Overcoming chemoresistance can reduce HCC recurrence and improve patients' prognosis. This work aimed to identify HCC chemoresistance-associated long non-coding RNA (lncRNA) and find an effective drug targeting the identified lncRNA for ameliorating the chemoresistance. In this investigation, bioinformatics analysis based on The Cancer Genome Atlas revealed a new chemoresistance index and suggested LINC02331 as an HCC chemoresistance and patients' prognosis-associated lncRNA that served as an independent prognostic indicator. Moreover, LINC02331 promoted DNA damage repair, DNA replication, and epithelial-mesenchymal transition as well as attenuated cell cycle arrest and apoptosis through regulating Wnt/β-catenin signaling, thus stimulating HCC resistance to cisplatin cytotoxicity, proliferation, and metastasis. Interestingly, we developed a novel oxidative coupling approach to synthesize a dimeric oxyberberine CT4-1, which exerted superior anti-HCC activities without obvious side effects measured by in vivo mice model and could downregulate LINC02331 mice model and could downregulate LINC02331 to mitigate LINC02331-induced HCC progression by suppressing Wnt/β-catenin signaling. RNA sequencing analyses verified the involvement of CT4-1-affected differential expression genes in dysregulated pathways and processes, including Wnt, DNA damage repair, cell cycle, DNA replication, apoptosis, and cell adhesion molecules. Furthermore, CT4-1 was demonstrated to be an effective cytotoxic drug in ameliorating HCC patients' prognosis with a prediction model constructed based on RNA-sequencing data from CT4-1-treated cancer cells and public cancer database. In summary, HCC chemoresistance-associated LINC02331 independently predicted poor patients' prognosis and enhanced HCC progression by promoting resistance to cisplatin cytotoxicity, proliferation, and metastasis. Targeting LINC02331 by the dimeric oxyberberine CT4-1 that exhibited synergistic cytotoxicity with cisplatin could alleviate HCC progression and improve patients' prognosis. Our study identified LINC02331 as an alternative target and suggested CT4-1 as an effective cytotoxic drug in HCC treatment.

Identification of a cuproptosis and copper metabolism gene-related lncRNAs prognostic signature associated with clinical and immunological characteristics of hepatocellular carcinoma

Background

The relationship between cuproptosis and HCC is still in the exploratory stage. Long noncoding RNAs (lncRNAs) have recently been linked to the progression of hepatocellular carcinoma (HCC). However, the clinical significance of lncRNAs associated with cuproptosis remains unclear.

Methods

Based on The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma (LIHC) dataset, we identified characteristic prognostic lncRNAs by univariate, LASSO, and multifactorial regression analysis, and constructed a prognostic signature of cuproptosis-related lncRNAs in HCC. The role of lncRNAs were identified through CCK-8, clone formation in Huh-7 cells with high expression of FDX1. Prognostic potential of the characteristic lncRNAs was evaluated in each of the two cohorts created by randomly dividing the TCGA cohort into a training cohort and a test cohort in a 1:1 ratio. Immune profiles in defined subgroups of cuproptosis-related lncRNA features as well as drug sensitivity were analyzed.

Results

We constructed a multigene signature based on four characteristic prognostic lncRNAs (AL590705.3, LINC02870, KDM4A-AS1, MKLN1-AS). These four lncRNAs participated in the development of cuproptosis. HCC patients were classified into high-risk and low-risk groups based on the median value of the risk score. The receiver operating characteristic curve area under the curve values for 1-, 3-, and 5-year survival were 0.773, 0.728, and 0.647, respectively, for the training cohort, and 0.764, 0.671, and 0.662, respectively, for the test cohort. Univariate and multifactorial regression analyses indicated that this prognostic feature was an independent prognostic factor for HCC. Principal component analysis plots clearly distinguished between low- and high-risk patients in terms of their probability of survival. Furthermore, gene set enrichment analysis showed that a variety of processes associated with tumor proliferation and progression were enriched in the high-risk group compared with the low-risk group. Moreover, there were significant differences in the expression of immune cell subpopulations, immune checkpoint genes, and potential drug screening, which provided distinct therapeutic recommendations for individuals with various risks.

Conclusions

We constructed a novel cuproptosis-associated lncRNA signature with a significant predictive value for the prognosis of patients with HCC. Cuproptosis-associated lncRNAs are associated with the tumor immune microenvironment of HCC and even the efficacy of tumor immunotherapy.

The Roles of Epigenetic Regulation and the Tumor Microenvironment in the Mechanism of Resistance to Systemic Therapy in Hepatocellular Carcinoma

Primary liver cancer is the sixth most common cancer and the third most common cause of cancer-related deaths worldwide. Hepatocellular carcinoma (HCC) is a major histologic type with a poor prognosis owing to the difficulty in early detection, the chemotherapy resistance, and the high recurrence rate of the disease. Despite recent advancements in HCC prevention and diagnosis, over 50% of patients are diagnosed at Barcelona Clinic Liver Cancer Stage B or C. Systemic therapies are recommended for unresectable HCC (uHCC) with major vascular invasion, extrahepatic metastases, or intrahepatic lesions that have a limited response to transcatheter arterial chemoembolization, but the treatment outcome tends to be unsatisfactory due to acquired drug resistance. Elucidation of the mechanisms underlying the resistance to systemic therapies and the appropriate response strategies to solve this issue will contribute to improved outcomes in the multidisciplinary treatment of uHCC. In this review, we summarize recent findings on the mechanisms of resistance to drugs such as sorafenib, regorafenib, and lenvatinib in molecularly targeted therapy, with a focus on epigenetic regulation and the tumor microenvironment and outline the approaches to improve the therapeutic outcome for patients with advanced HCC.

Machine learning-based construction of a ferroptosis and necroptosis associated lncRNA signature for predicting prognosis and immunotherapy response in hepatocellular cancer

Introduction

Liver hepatocellular carcinoma (LIHC), one of the most common malignancies worldwide, occurs with high incidence and mortality. Ferroptosis and necroptosis are critically associated with LIHC prognosis. Some long non-coding RNAs (lncRNAs) have been found to induce ferroptosis and necroptosis in hepatocellular carcinoma cells.

Methods

Cox regression analysis was used to construct a risk model for LIHC based on differentially expressed ferroptosis and necroptosis related lncRNAs (F-NLRs), and their expression in SMMC7721, HepG2 and WRL68 cells was detected by qPCR.

Results

Five F-NLRs were associated with LIHC prognosis, including KDM4A-AS1, ZFPM2-AS1, AC099850.3, MKLN1-AS, and BACE1-AS. Kaplan-Meier survival analysis indicated that patients with LIHC in the high-risk group were associated with poor prognosis. The combined F-NLR signature model demonstrated a prognostic AUC value of 0.789 and was more accurate than standard clinical variables for predicting LIHC prognosis. T cell functions and immunotherapy responses differed significantly between patients in the low- and high-risk groups. Additionally, immune checkpoints and m6A-related genes were differentially expressed between patients in the two risk groups. Furthermore, proteins encoded by the five F-NLRs were overexpressed in four liver cancer cell lines compared to that in human liver cell line WRL68. Pan-cancer examination revealed that expression levels of the five F-NLRs differed between most common tumor types and normal tissues.

Conclusion

F-NLRs identified in this study provide a predictive signature representing ferroptosis and necroptosis in LIHC, which correlated well with patient prognosis, clinicopathological characteristics, and immunotherapy responses. The study findings help to elucidate the mechanisms of F-NLRs in LIHC and provide further guidance for the selection and development of immunotherapeutic agents for LIHC.

Development and validation of an ECM-related prognostic signature to predict the immune landscape of human hepatocellular carcinoma

Background

The global burden of hepatocellular carcinoma (HCC) is increasing, negatively impacting social health and economies. The discovery of novel and valuable biomarkers for the early diagnosis and therapeutic guidance of HCC is urgently needed.

Methods

Extracellular matrix (ECM)-related gene sets, transcriptome data and mutation profiles were downloaded from the Matrisome Project and The Cancer Genome Atlas (TCGA)-LIHC datasets. Coexpression analysis was initially performed with the aim of identifying ECM-related lncRNAs (r > 0.4, p < 0.001). The screened lncRNAs were subjected to univariate analysis to obtain a series of prognosis-related lncRNA sets, which were incorporated into least absolute selection and shrinkage operator (LASSO) regression for signature establishment. Following the grouping of LIHC samples according to risk score, the correlations between the signature and clinicopathological, tumour immune infiltration, and mutational characteristics as well as therapeutic response were also analysed. lncRNA expression levels used for modelling were finally examined at the cellular and tissue levels by real-time PCR. All analyses were based on R software.

Results

AL031985.3 and MKLN1-AS were ultimately identified as signature-related lncRNAs, and both were significantly upregulated in HCC tissue samples and cell lines. The prognostic value of the signature reflected by the AUC value was superior to that of age, sex, grade and stage. Correlation analysis results demonstrated that high-risk groups exhibited significant enrichment of immune cells (DCs, macrophages and Tregs) and increased expression levels of all immune checkpoint genes. Prominent differences in clinicopathological profiles, immune functions, tumour mutation burden (TMB) and drug sensitivity were noted between the two risk groups.

Conclusions

Our signature represents a valuable predictive tool in the prognostic management of HCC patients. Further validation of the mechanisms involved is needed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10049-w.

CircMMP9 accelerates the progression of hepatocellular carcinoma through the miR-149/CCND2 axis

BACKGROUND

This study aimed to verify the hypothesis that circular RNA MMP9 (circMMP9) promotes hepatocellular carcinoma (HCC) progression through targeting miR-149 and regulating cyclin D2 (CCND2) expression.

METHODS

Expression of circMMP9, miR-149 and CCND2 was detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR) or protein blotting. Cell Counting Kit-8 (CCK-8) was used to evaluate cell proliferation. The HCC cell migration and invasion were evaluated using wound healing and transwell assays. The interaction among circMMP9, miR-149, and CCND2 was evaluated using luciferase, RNA-pull down, and RNA immunoprecipitation (RIP) assays, respectively. Cell apoptosis and cycle were examined by flow cytometry. A subcutaneous HCC xenograft mouse model was established for analyzing the role of circMMP9 in regulating the progression of HCC in vivo.

RESULTS

The expression of circMMP9 was elevated in HCC tissues and its high expression correlated with poor prognosis (P<0.05). Knockdown of circMMP9 restrained the proliferation, migration, and invasion of HCC cells and led to arrested cell cycle and increased apoptosis (all P<0.05). Furthermore, knockdown of circMMP9 attenuated HCC growth in vivo (P<0.05). Mechanically, circMMP9 acted as a sponge for miR-149 and enhanced CCND2 expression in HCC cells (P<0.05). Inhibition of miR-149 or overexpression of CCND2 abrogated knockdown of circMMP9-mediated alleviation of the malignant phenotypes of HCC (P<0.05).

CONCLUSIONS

For the first time, we demonstrated that circMMP9 exacerbated HCC progression through the miR-149/CCND2 axis, which suggested that circMMP9 could be potentially targeted for HCC treatment.