The Cancer Genome Atlas (TCGA) based m6A methylation-related genes predict prognosis in hepatocellular carcinoma

Mechanisms and clinical landscape of N6-methyladenosine (m6A) RNA modification in gastrointestinal tract cancers

Epigenetics encompasses reversible and heritable chemical modifications of non-nuclear DNA sequences, including DNA and RNA methylation, histone modifications, non-coding RNA modifications, and chromatin rearrangements. In addition to well-studied DNA and histone methylation, RNA methylation has emerged as a hot topic in biological sciences over the past decade. N6-methyladenosine (m6A) is the most common and abundant modification in eukaryotic mRNA, affecting all RNA stages, including transcription, translation, and degradation. Advances in high-throughput sequencing technologies made it feasible to identify the chemical basis and biological functions of m6A RNA. Dysregulation of m6A levels and associated modifying proteins can both inhibit and promote cancer, highlighting the importance of the tumor microenvironment in diverse biological processes. Gastrointestinal tract cancers, including gastric, colorectal, and pancreatic cancers, are among the most common and deadly malignancies in humans. Growing evidence suggests a close association between m6A levels and the progression of gastrointestinal tumors. Global m6A modification levels are substantially modified in gastrointestinal tumor tissues and cell lines compared to healthy tissues and cells, possibly influencing various biological behaviors such as tumor cell proliferation, invasion, metastasis, and drug resistance. Exploring the diagnostic and therapeutic potential of m6A-related proteins is critical from a clinical standpoint. Developing more specific and effective m6A modulators offers new options for treating these tumors and deeper insights into gastrointestinal tract cancers.

New horizons for the role of RNA N6-methyladenosine modification in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignancy, presenting a formidable challenge to the medical community owing to its intricate pathogenic mechanisms. Although current prevention, surveillance, early detection, diagnosis, and treatment have achieved some success in preventing HCC and controlling overall disease mortality, the imperative to explore novel treatment modalities for HCC remains increasingly urgent. Epigenetic modification has emerged as pivotal factors in the etiology of cancer. Among these, RNA N6-methyladenosine (m6A) modification stands out as one of the most prevalent, abundant, and evolutionarily conserved post-transcriptional alterations in eukaryotes. The literature underscores that the dynamic and reversible nature of m6A modifications orchestrates the intricate regulation of gene expression, thereby exerting a profound influence on cell destinies. Increasing evidence has substantiated conspicuous fluctuations in m6A modification levels throughout the progression of HCC. The deliberate modulation of m6A modification levels through molecular biology and pharmacological interventions has been demonstrated to exert a discernible impact on the pathogenesis of HCC. In this review, we elucidate the multifaceted biological functions of m6A modifications in HCC, and concurrently advancing novel therapeutic strategies for the management of this malignancy.

Multi-omic profiling reveals potential biomarkers of hepatocellular carcinoma prognosis and therapy response among mitochondria-associated cell death genes in the context of 3P medicine

Background

Cancer cell growth, metastasis, and drug resistance are major challenges in treating liver hepatocellular carcinoma (LIHC). However, the lack of comprehensive and reliable models hamper the effectiveness of the predictive, preventive, and personalized medicine (PPPM/3PM) strategy in managing LIHC.

Methods

Leveraging seven distinct patterns of mitochondrial cell death (MCD), we conducted a multi-omic screening of MCD-related genes. A novel machine learning framework was developed, integrating 10 machine learning algorithms with 67 different combinations to establish a consensus mitochondrial cell death index (MCDI). This index underwent rigorous evaluation across training, validation, and in-house clinical cohorts. A comprehensive multi-omics analysis encompassing bulk, single-cell, and spatial transcriptomics was employed to achieve a deeper insight into the constructed signature. The response of risk subgroups to immunotherapy and targeted therapy was evaluated and validated. RT-qPCR, western blotting, and immunohistochemical staining were utilized for findings validation.

Results

Nine critical differentially expressed MCD-related genes were identified in LIHC. A consensus MCDI was constructed based on a 67-combination machine learning computational framework, demonstrating outstanding performance in predicting prognosis and clinical translation. MCDI correlated with immune infiltration, Tumor Immune Dysfunction and Exclusion (TIDE) score and sorafenib sensitivity. Findings were validated experimentally. Moreover, we identified PAK1IP1 as the most important gene for predicting LIHC prognosis and validated its potential as an indicator of prognosis and sorafenib response in our in-house clinical cohorts.

Conclusion

This study developed a novel predictive model for LIHC, namely MCDI. Incorporating MCDI into the PPPM framework will enhance clinical decision-making processes and optimize individualized treatment strategies for LIHC patients.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00362-8.

RNA modifications in the progression of liver diseases: from fatty liver to cancer

Non-alcoholic fatty liver disease (NAFLD) has emerged as a prominent global health concern associated with high risk of metabolic syndrome, and has impacted a substantial segment of the population. The disease spectrum ranges from simple fatty liver to non-alcoholic steatohepatitis (NASH), which can progress to cirrhosis and hepatocellular carcinoma (HCC) and is increasingly becoming a prevalent indication for liver transplantation. The existing therapeutic options for NAFLD, NASH, and HCC are limited, underscoring the urgent need for innovative treatment strategies. Insights into gene expression, particularly RNA modifications such as N6 methyladenosine (m6A), hold promising avenues for interventions. These modifications play integral roles in RNA metabolism and cellular functions, encompassing the entire NAFLD-NASH-HCC progression. This review will encompass recent insights on diverse RNA modifications, including m6A, pseudouridine (ψ), N1-methyladenosine (m1A), and 5-methylcytidine (m5C) across various RNA species. It will uncover their significance in crucial aspects such as steatosis, inflammation, fibrosis, and tumorigenesis. Furthermore, prospective research directions and therapeutic implications will be explored, advancing our comprehensive understanding of the intricate interconnected nature of these pathological conditions.

KAP1 stabilizes MYCN mRNA and promotes neuroblastoma tumorigenicity by protecting the RNA m6A reader YTHDC1 protein degradation

BACKGROUND

Neuroblastoma (NB) patients with amplified MYCN often face a grim prognosis and are resistant to existing therapies, yet MYCN protein is considered undruggable. KAP1 (also named TRIM28) plays a crucial role in multiple biological activities. This study aimed to investigate the relationship between KAP1 and MYCN in NB.

METHODS

Transcriptome analyses and luciferase reporter assay identified that KAP1 was a downstream target of MYCN. The effects of KAP1 on cancer cell proliferation and colony formation were explored using the loss-of-function assays in vitro and in vivo. RNA stability detection was used to examine the influence of KAP1 on MYCN expression. The mechanisms of KAP1 to maintain MYCN mRNA stabilization were mainly investigated by mass spectrum, immunoprecipitation, RIP-qPCR, and western blotting. In addition, a xenograft mouse model was used to reveal the antitumor effect of STM2457 on NB.

RESULTS

Here we identified KAP1 as a critical regulator of MYCN mRNA stability by protecting the RNA N6-methyladenosine (m6A) reader YTHDC1 protein degradation. KAP1 was highly expressed in clinical MYCN-amplified NB and was upregulated by MYCN. Reciprocally, KAP1 knockdown reduced MYCN mRNA stability and inhibited MYCN-amplified NB progression. Mechanistically, KAP1 regulated the stability of MYCN mRNA in an m6A-dependent manner. KAP1 formed a complex with YTHDC1 and RNA m6A writer METTL3 to regulate m6A-modified MYCN mRNA stability. KAP1 depletion decreased YTHDC1 protein stability and promoted MYCN mRNA degradation. Inhibiting MYCN mRNA m6A modification synergized with chemotherapy to restrain tumor progression in MYCN-amplified NB.

CONCLUSIONS

Our research demonstrates that KAP1, transcriptionally activated by MYCN, forms a complex with YTHDC1 and METTL3, which in turn maintain the stabilization of MYCN mRNA in an m6A-dependent manner. Targeting m6A modification by STM2457, a small-molecule inhibitor of METTL3, could downregulate MYCN expression and attenuate tumor proliferation. This finding provides a new alternative putative therapeutic strategy for MYCN-amplified NB.

Based on the prognosis model of immunogenes, the prognosis model was constructed to predict the invasion of immune genes and immune cells related to primary liver cancer and its experimental validation

Background

Primary liver cancer (PLC) is a prevalent malignancy of the digestive system characterized by insidious symptom onset and a generally poor prognosis. Recent studies have highlighted a significant correlation between the initiation and prognosis of liver cancer and the immune function of PLC patients.

Purpose

Revealing the expression of PLC-related immune genes and the characteristics of immune cell infiltration provides assistance for the analysis of clinical pathological parameters and prognosis of PLC patients.

Methods

PLC-related differentially expressed genes (DEGs) with a median absolute deviation (MAD > 0.5) were identified from TCGA and GEO databases. These DEGs were intersected with immune-related genes (IRGs) from the ImmPort database to obtain PLC-related IRGs. The method of constructing a prognostic model through immune-related gene pairs (IRGPs) is used to obtain IRGPs and conduct the selection of central immune genes. The central immune genes obtained from the selection of IRGPs are validated in PLC. Subsequently, the relative proportions of 22 types of immune cells in different immune risk groups are evaluated, and the differential characteristics of PLC-related immune cells are verified through animal experiments.

Results

Through database screening and the construction of an IRGP prognosis model, 84 pairs of IRGPs (P < 0.001) were ultimately obtained. Analysis of these 84 IRGPs revealed 11 central immune genes related to PLC, showing differential expression in liver cancer tissues compared to normal liver tissues. Results from the CiberSort platform indicate differential expression of immune cells such as naive B cells, macrophages, and neutrophils in different immune risk groups. Animal experiments demonstrated altered immune cell proportions in H22 tumor-bearing mice, validating findings from peripheral blood and spleen homogenate analyses.

Conclusion

Our study successfully predicted and validated PLC-related IRGs and immune cells, suggesting their potential as prognostic indicators and therapeutic targets for PLC.

N6-methyladenosine (m6A) modification in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the deadliest cancers of human, the tumor-related death of which ranks third among the common malignances. N6-methyladenosine (m6A) methylation, the most abundant internal modification of RNA in mammals, participates in the metabolism of mRNA and interrelates with ncRNAs. In this paper, we overviewed the complex function of m6A regulators in HCC, including regulating the tumorigenesis, progression, prognosis, stemness, metabolic reprogramming, autophagy, ferroptosis, drug resistance and tumor immune microenvironment (TIME). Furthermore, we elucidated the interplay between m6A modification and non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs). Finally, we summarized the potential of m6A regulators as diagnostic biomarkers. What's more, we reviewed the inhibitors targeting m6A enzymes as promising therapeutic targets of HCC. We aimed to help understand the function of m6A methylation in HCC systematically and comprehensively so that more effective strategies for HCC treatment will be developed.

Establishment and verification of a prognostic model based on coagulation and fibrinolysis-related genes in hepatocellular carcinoma

BACKGROUND

Studies have shown that coagulation and fibrinolysis (CFR) are correlated with Hepatocellular carcinoma (HCC) progression and prognosis. We aim to build a model based on CFR-correlated genes for risk assessment and prediction of HCC patient.

METHODS

HCC samples were selected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases respectively. The Molecular Signatures Database (MSigDB) was used to select the CFR genes. RiskScore model were established by single sample gene set enrichment analysis (ssGSEA), weighted correlation network analysis (WGCNA), multivariate Cox regression analysis, LASSO regression analysis.

RESULTS

PCDH17, PGF, PDE2A, FAM110D, FSCN1, FBLN5 were selected as the key genes and designed a RiskScore model. Those key genes were Differential expressions in HCC cell and patients. Overexpression PDE2A inhibited HCC cell migration and invasion. The higher the RiskScore, the lower the probability of survival. The model has high AUC values in the first, third and fifth year prediction curves, indicating that the model has strong prediction performance. The difference analysis of clinicopathological features found that a great proportion of high clinicopathological grade samples showed higher RiskScore. RiskScore were positively correlated with immune scores and TIDE scores. High levels of immune checkpoints and immunomodulators were observed in high RiskScore group. High RiskScore groups may benefit greatly from taking traditional chemotherapy drugs.

CONCLUSIONS

We screened CFR related genes to design a RiskScore model, which could accurately evaluate the prognosis and survival status of HCC patients, providing certain value for optimizing the clinical treatment of cancer in the future.

Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients

Background

Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs (ARLncRNAs) on the prognosis of hepatocellular carcinoma (HCC).

Methods

We analyzed 371 HCC samples from TCGA, identifying expression networks of ARLncRNAs using autophagy-related genes. Screening for prognostically relevant ARLncRNAs involved univariate Cox regression, Lasso regression, and multivariate Cox regression. A Nomogram was further employed to assess the reliability of Riskscore, calculated from the signatures of screened ARLncRNAs, in predicting outcomes. Additionally, we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis, using consensus clustering to identify subgroups related to ARLncRNAs.

Results

The screening process identified 27 ARLncRNAs, with 13 being associated with HCC prognosis. Consequently, a set of signatures comprising 8 ARLncRNAs was successfully constructed as independent prognostic factors for HCC. Patients in the high-risk group showed very poor prognoses in most clinical categories. The Riskscore was closely related to immune cell scores, such as macrophages, and the DEGs between different groups were implicated in metabolism, cell cycle, and mitotic processes. Notably, high-risk group patients demonstrated a significantly lower IC50 for Paclitaxel, suggesting that Paclitaxel could be an ideal treatment for those at elevated risk for HCC. We further identified C2 as the Paclitaxel subtype, where patients exhibited higher Riskscores, reduced survival rates, and more severe clinical progression.

Conclusion

The 8 signatures based on ARLncRNAs present novel targets for prognostic prediction in HCC. The drug candidate Paclitaxel may effectively treat HCC by impacting ARLncRNAs expression. With the identification of ARLncRNAs-related isoforms, these results provide valuable insights for clinical exploration of autophagy mechanisms in HCC pathogenesis and offer potential avenues for precision medicine.

Decoding m6A mRNA methylation by reader proteins in liver diseases

N6-methyladenosine (m6A) is a dynamic and reversible epigenetic regulation. As the most prevalent internal post-transcriptional modification in eukaryotic RNA, it participates in the regulation of gene expression through various mechanisms, such as mRNA splicing, nuclear export, localization, translation efficiency, mRNA stability, and structural transformation. The involvement of m6A in the regulation of gene expression depends on the specific recognition of m6A-modified RNA by reader proteins. In the pathogenesis and treatment of liver disease, studies have found that the expression levels of key genes that promote or inhibit the development of liver disease are regulated by m6A modification, in which abnormal expression of reader proteins determines the fate of these gene transcripts. In this review, we introduce m6A readers, summarize the recognition and regulatory mechanisms of m6A readers on mRNA, and focus on the biological functions and mechanisms of m6A readers in liver cancer, viral hepatitis, non-alcoholic fatty liver disease (NAFLD), hepatic fibrosis (HF), acute liver injury (ALI), and other liver diseases. This information is expected to be of high value to researchers deciphering the links between m6A readers and human liver diseases.

Multilayered insights: a machine learning approach for personalized prognostic assessment in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a complex malignancy, and precise prognosis assessment is vital for personalized treatment decisions.

Objective

This study aimed to develop a multi-level prognostic risk model for HCC, offering individualized prognosis assessment and treatment guidance.

Methods

By utilizing data from The Cancer Genome Atlas (TCGA) and the Surveillance, Epidemiology, and End Results (SEER) database, we performed differential gene expression analysis to identify genes associated with survival in HCC patients. The HCC Differential Gene Prognostic Model (HCC-DGPM) was developed through multivariate Cox regression. Clinical indicators were incorporated into the HCC-DGPM using Cox regression, leading to the creation of the HCC Multilevel Prognostic Model (HCC-MLPM). Immune function was evaluated using single-sample Gene Set Enrichment Analysis (ssGSEA), and immune cell infiltration was assessed. Patient responsiveness to immunotherapy was evaluated using the Immunophenoscore (IPS). Clinical drug responsiveness was investigated using drug-related information from the TCGA database. Cox regression, Kaplan-Meier analysis, and trend association tests were conducted.

Results

Seven differentially expressed genes from the TCGA database were used to construct the HCC-DGPM. Additionally, four clinical indicators associated with survival were identified from the SEER database for model adjustment. The adjusted HCC-MLPM showed significantly improved discriminative capacity (AUC=0.819 vs. 0.724). External validation involving 153 HCC patients from the International Cancer Genome Consortium (ICGC) database verified the performance of the HCC-MLPM (AUC=0.776). Significantly, the HCC-MLPM exhibited predictive capacity for patient response to immunotherapy and clinical drug efficacy (P < 0.05).

Conclusion

This study offers comprehensive insights into HCC prognosis and develops predictive models to enhance patient outcomes. The evaluation of immune function, immune cell infiltration, and clinical drug responsiveness enhances our comprehension and management of HCC.

Investigating the clinical role and prognostic value of genes related to insulin-like growth factor signaling pathway in thyroid cancer

BACKGROUND

Thyroid cancer (THCA) is the most common endocrine malignancy having a female predominance. The insulin-like growth factor (IGF) pathway contributed to the unregulated cell proliferation in multiple malignancies. We aimed to explore the IGF-related signature for THCA prognosis.

METHOD

The TCGA-THCA dataset was collected from the Cancer Genome Atlas (TCGA) for screening of key prognostic genes. The limma R package was applied for differentially expressed genes (DEGs) and the clusterProfiler R package was used for the Gene Ontology (GO) and KEGG analysis of DEGs. Then, the un/multivariate and least absolute shrinkage and selection operator (Lasso) Cox regression analysis was used for the establishment of RiskScore model. Receiver Operating Characteristic (ROC) analysis was used to verify the model's predictive performance. CIBERSORT and MCP-counter algorithms were applied for immune infiltration analysis. Finally, we analyzed the mutation features and the correlation between the RiskScore and cancer hallmark pathway by using the GSEA.

RESULT

We obtained 5 key RiskScore model genes for patient's risk stratification from the 721 DEGs. ROC analysis indicated that our model is an ideal classifier, the high-risk patients are associated with the poor prognosis, immune infiltration, high tumor mutation burden (TMB), stronger cancer stemness and stronger correlation with the typical cancer-activation pathways. A nomogram combined with multiple clinical features was developed and exhibited excellent performance upon long-term survival quantitative prediction.

CONCLUSIONS

We constructed an excellent prognostic model RiskScore based on IGF-related signature and concluded that the IGF signal pathway may become a reliable prognostic phenotype in THCA intervention.

Bioinformatics analysis of the prognosis and biological significance of N6 methyladenine regulators in oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a common type of cancer. We performed the present study to explore the function and specific regulatory mechanism of m6A in OSCC and to find a new diagnosis and treatment strategy for OSCC.

METHODS

Using bioinformatics, we examined the associations between 20 genes associated with methylation and the epidemiological data about OSCC tumor samples.

RESULTS

We created two subgroup curves based on the gene expression levels related to m6A methylation. In total, 14 genes were found to be differentially expressed. Significant differences in terms of survival rates, Grade and gender were found among subgroups with different m6A expression levels. Nine genes had areas under the curves greater than 0.7. Therefore, these genes may be utilized for the clinical diagnosis and prognosis of OSCC. Because of their high individual predictive value, HNRNPC and IGF2BP2 were chosen as the two potential predictors. The two regulatory elements were used to create the prognostic signals for OSCC. The developed prognostic signals made it possible to discern between the samples with good and poor prognoses without potential confounding factors. Four genes (HNRNPC, METTL14, YTHDF2 and ALKBH5) combined well with compounds, which had an anti-cancer effect.

CONCLUSIONS

Our findings suggested that OSCC-related genes with m6A methylation could be beneficial treatment targets or prognostic indicators.

Novel insights into the regulatory role of N6-methyladenosine methylation modified autophagy in sepsis

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is characterized by high morbidity and mortality and one of the major diseases that seriously hang over global human health. Autophagy is a crucial regulator in the complicated pathophysiological processes of sepsis. The activation of autophagy is known to be of great significance for protecting sepsis induced organ dysfunction. Recent research has demonstrated that N6-methyladenosine (m6A) methylation is a well-known post-transcriptional RNA modification that controls epigenetic and gene expression as well as a number of biological processes in sepsis. In addition, m6A affects the stability, export, splicing and translation of transcripts involved in the autophagic process. Although it has been suggested that m6A methylation regulates the biological metabolic processes of autophagy and is more frequently seen in the progression of sepsis pathogenesis, the underlying molecular mechanisms of m6A-modified autophagy in sepsis have not been thoroughly elucidated. The present article fills this gap by providing an epigenetic review of the processes of m6A-modified autophagy in sepsis and its potential role in the development of novel therapeutics.

hnRNPA2B1 promotes the occurrence and progression of hepatocellular carcinoma by downregulating PCK1 mRNA via a m6A RNA methylation manner

BACKGROUND

N6-methyladenosine (m6A) is the most prevalent RNA modification. Although hnRNPA2B1, as a reader of m6A modification, has been reported to promote tumorigenesis in a few types of tumors, its role in hepatocellular carcinoma (HCC) and the underlying molecular mechanism remains unclear.

METHODS

Multiple public databases were used to analyze the expression of hnRNPA2B1 in HCC and its correlation with survival prognosis. We employed a CRISPR-Cas9 sgRNA editing strategy to knockout hnRNPA2B1 expression in HCC cells. The biological function of hnRNPA2B1 in vitro in HCC cells was measured by CCK8, colony formation, migration, and invasion assay. The tumorigenic function of hnRNPA2B1 in vivo was determined by a subcutaneous tumor formation experiment and a HCC mouse model via tail injection of several plasmids into the mouse within 5s-7s. RNA binding protein immunoprecipitation (RIP) experiment using hnRNPA2B1 was performed to test the target genes of hnRNPA2B1 and methylated RNA immunoprecipitation (MeRIP) assay was performed to explore the m6A methylated mRNA of target genes.

RESULTS

hnRNPA2B1 highly expressed in HCC tissues, correlated with high grades and poor prognosis. Its knockout reduced HCC cell proliferation, migration, and invasion in vitro, while overexpression promoted these processes. hnRNPA2B1-knockout cells inhibited tumor formation in graft experiments. In HCC mice, endogenous knockout attenuated hepatocarcinogenesis. RNA-seq showed downregulated gluconeogenesis with high hnRNPA2B1 expression. hnRNPA2B1 negatively correlated with PCK1, a key enzyme. RIP assay revealed hnRNPA2B1 binding to PCK1 mRNA. hnRNPA2B1 knockout increased m6A-methylation of PCK1 mRNA. Interestingly, PCK1 knockout partially counteracted tumor inhibition by hnRNPA2B1 knockout in mice.

CONCLUSION

Our study indicated that hnRNPA2B1 is highly expressed in HCC and correlated with a poor prognosis. hnRNPA2B1 promotes the tumorigenesis and progression of HCC both in vitro and in vivo. Moreover, hnRNPA2B1 downregulates the expression of PCK1 mRNA via a m6A methylation manner. More importantly, the ability of hnRNPA2B1 to induce tumorigenesis and progression in HCC is dependent on its ability to decrease the expression of PCK1. Therefore, this study suggested that hnRNPA2B1 might be a diagnostic marker of poor prognosis of HCC and a potential therapeutic target for HCC patients.

Comprehensive analysis of epigenetic and epitranscriptomic genes' expression in human NAFLD

Non-alcoholic fatty liver disease (NAFLD) is a multifactorial condition with a complex etiology. Its incidence is increasing globally in parallel with the obesity epidemic, and it is now considered the most common liver disease in Western countries. The precise mechanisms underlying the development and progression of NAFLD are complex and still poorly understood. The dysregulation of epigenetic and epitranscriptomic mechanisms is increasingly recognized to play pathogenic roles in multiple conditions, including chronic liver diseases. Here, we have performed a comprehensive analysis of the expression of epigenetic and epitranscriptomic genes in a total of 903 liver tissue samples corresponding to patients with normal liver, obese patients, and patients with non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH), advancing stages in NAFLD progression. We integrated ten transcriptomic datasets in an unbiased manner, enabling their robust analysis and comparison. We describe the complete landscape of epigenetic and epitranscriptomic genes' expression along the course of the disease. We identify signatures of genes significantly dysregulated in association with disease progression, particularly with liver fibrosis development. Most of these epigenetic and epitranscriptomic effectors have not been previously described in human NAFLD, and their altered expression may have pathogenic implications. We also performed a comprehensive analysis of the expression of enzymes involved in the metabolism of the substrates and cofactors of epigenetic and epitranscriptomic effectors. This study provides novel information on NAFLD pathogenesis and may also guide the identification of drug targets to treat this condition and its progression towards hepatocellular carcinoma.

Applying machine learning algorithms to develop a survival prediction model for lung adenocarcinoma based on genes related to fatty acid metabolism

Background: The progression of lung adenocarcinoma (LUAD) may be related to abnormal fatty acid metabolism (FAM). The present study investigated the relationship between FAM-related genes and LUAD prognosis. Methods: LUAD samples from The Cancer Genome Atlas were collected. The scores of FAM-associated pathways from the Kyoto Encyclopedia of Genes and Genomes website were calculated using the single sample gene set enrichment analysis. ConsensusClusterPlus and cumulative distribution function were used to classify molecular subtypes for LUAD. Key genes were obtained using limma package, Cox regression analysis, and six machine learning algorithms (GBM, LASSO, XGBoost, SVM, random forest, and decision trees), and a RiskScore model was established. According to the RiskScore model and clinical features, a nomogram was developed and evaluated for its prediction performance using a calibration curve. Differences in immune abnormalities among patients with different subtypes and RiskScores were analyzed by the Estimation of STromal and Immune cells in MAlignant Tumours using Expression data, CIBERSORT, and single sample gene set enrichment analysis. Patients' drug sensitivity was predicted by the pRRophetic package in R language. Results: LUAD samples had lower scores of FAM-related pathways. Three molecular subtypes (C1, C2, and C3) were defined. Analysis on differential prognosis showed that the C1 subtype had the most favorable prognosis, followed by the C2 subtype, and the C3 subtype had the worst prognosis. The C3 subtype had lower immune infiltration. A total of 12 key genes (SLC2A1, PKP2, FAM83A, TCN1, MS4A1, CLIC6, UBE2S, RRM2, CDC45, IGF2BP1, ANGPTL4, and CD109) were screened and used to develop a RiskScore model. Survival chance of patients in the high-RiskScore group was significantly lower. The low-RiskScore group showed higher immune score and higher expression of most immune checkpoint genes. Patients with a high RiskScore were more likely to benefit from the six anticancer drugs we screened in this study. Conclusion: We developed a RiskScore model using FAM-related genes to help predict LUAD prognosis and develop new targeted drugs.

Comprehensive analysis of m6A regulators and relationship with tumor microenvironment, immunotherapy strategies in colorectal adenocarcinoma

BACKGROUND

The N6-methyladenosine (m6A) RNA modification is the most prevalent and abundant type found in eukaryotic cells. It plays a crucial role in the initiation and progression of cancers. In this study, we aimed to comprehensively investigate the landscape of m6A regulators and their association with tumor microenvironment (TME), immunotherapeutic strategies in colon adenocarcinoma (COAD).

RESULTS

The differential expression, mutation, CNV frequency and prognostic value of 27 m6A regulators were systematically analyzed in COAD. Patients were classified into two clusters based on m6A regulators through consistent clustering analysis, with cluster A showing significant survival benefits. Most of the m6A regulators were negatively correlated with immune cells, except for WTAP, IGF2BP3, FTO, ALKBH5, which showed a positive correlation. We developed an m6A scoring system to calculate the m6Ascore for each patient. Patients with a high-m6Ascore had a better outcome, with the AUC of 0.775. An independent cohort of 416 COAD patients acquired from GSE38832 database was used to validate the prognosis prediction ability of m6Ascore. Moreover, the m6Ascore was negatively correlated with infiltration of anti-tumor immune cells. Additionally, patients with a high-m6Ascore responded better to anti-PD1 and anti-CTLA4 therapies, and those with MSI-H had a higher m6Ascore. Finally, we investigated the value of m6Ascore in predicting the response of patients to 15 commonly used drugs.

CONCLUSIONS

We comprehensively analyzed m6A regulators in COAD, including RNA expression, CNV changes, mutations and their correlation with TME. Our results showed that the m6A scoring system had significant predictive power for the prognosis of COAD patients, potentially leading to new personalized immunotherapy strategies.

Role of m6A modification in immune microenvironment of digestive system tumors

Digestive system tumors are huge health problem worldwide, largely attributable to poor dietary choices. The role of RNA modifications in cancer development is an emerging field of research. RNA modifications are associated with the growth and development of various immune cells, which, in turn, regulate the immune response. The majority of RNA modifications are methylation modifications, and the most common type is the N6-methyladenosine (m6A) modification. Here, we reviewed the molecular mechanism of m6A in the immune cells and the role of m6A in the digestive system tumors. However, further studies are required to better understand the role of RNA methylation in human cancers for designing diagnostic and treatment strategies and predicting the prognosis of patients.

Comprehensive pan-cancer analysis of PTGES3 and its prognostic role in hepatocellular carcinoma

Introduction

PTGES3, also known as p23, is a molecule chaperone of Hsp90 that is involved in the pathogenesis of malignant tumors. Increasing studies have shown that PTGES3 plays a nonnegligible role in tumor development. However, analysis of PTGES3 in pan-cancer has not been performed yet.

Methods

We explored the role of PTGES3 in 33 types of tumors and depicted the potentialimmune-related pathways among them. Using multiple databases includingTCGA, LinkedOmics, GDSC, and TIMER, we made a comprehensive analysis to explore whether there was an interaction between PTGES3 and prognosis, DNA methylation, copy number variation (CNV), tumor mutational burden (TMB), microsatellite instability (MSI), and tumor immune microenvironment (TME).

Results

Our study revealed that PTGES3 expression level was upregulated in most cancers. PTGES3 was also associated with a positive or negative prognosis in a variety of cancers, which was mainly associated with DNA methylation, CNV, MSI, TMB, andmismatch repair-related genes. High PTGES3 expression was related to the infiltration of Th2 subsets of CD4+ T cells and immune checkpoint-related genes in most cancers, especially in hepatocellular carcinoma (HCC). Enrichment analysis demonstrated that PTGES3 was involved in cellular processes including DNA replication and spliceosome. The relationship between PTGES3 expression and HCC progression was verified at the protein level through immune histochemical analysis.

Conclusions

Our research demonstrated theprognostic predictive value of PTGES3 in a wide range of cancers, which was alsoassociated with the process of tumor immune infiltration. As a result, it suggestedthat PTGES3 was a valuable prognostic biomarker in HCC treatment.

Biological function analysis of ARHGAP39 as an independent prognostic biomarker in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common subtype of liver cancer, with a high morbidity and low survival rate. Rho GTPase activating protein 39 (ARHGAP39) is a crucial activating protein of Rho GTPases, a novel target in cancer therapy, and it was identified as a hub gene for gastric cancer. However, the expression and role of ARHGAP39 in hepatocellular carcinoma remain unclear. Accordingly, the cancer genome atlas (TCGA) data were used to analyze the expression and clinical value of ARHGAP39 in hepatocellular carcinoma. Further, the LinkedOmics tool suggested functional enrichment pathways for ARHGAP39. To investigate in depth the possible role of ARHGAP39 on immune infiltration, we analyzed the relationship between ARHGAP39 and chemokines in HCCLM3 cells. Finally, the GSCA website was used to explore drug resistance in patients with high ARHGAP39 expression. Studies have shown that ARHGAP39 is highly expressed in hepatocellular carcinoma and relevant to clinicopathological features. In addition, the overexpression of ARHGAP39 leads to a poor prognosis. Besides, co-expressed genes and enrichment analysis showed a correlation with the cell cycle. Notably, ARHGAP39 may worsen the survival of hepatocellular carcinoma patients by increasing the level of immune infiltration through chemokines. Moreover, N6-methyladenosine (m6A) modification-related factors and drug sensitivity were also found to be associated with ARHGAP39. In brief, ARHGAP39 is a promising prognostic factor for hepatocellular carcinoma patients that is closely related to cell cycle, immune infiltration, m6A modification, and drug resistance.

Identification of acetyl-CoA carboxylase alpha as a prognostic and targeted candidate for hepatocellular carcinoma

PURPOSE

The de novo lipogenesis has been a longstanding observation in hepatocellular carcinoma (HCC). However, the prognostic value and carcinogenic roles of the enzyme Acetyl-CoA carboxylase alpha (ACACA) in HCC remains unknown.

METHODS

The proteins with remarkable prognostic significance were screened out from The Cancer Proteome Atlas Portal (TCPA) database. Furthermore, the expression characteristics and prognostic value of ACACA were evaluated in multiple databases and the local HCC cohort. The loss-of-function assays were performed to uncover the potential roles of ACACA in steering malignant behaviors of HCC cells. The underlying mechanisms were conjectured by bioinformatics and validated in HCC cell lines.

RESULTS

ACACA was identified as a crucial factor of HCC prognosis. Bioinformatics analyses showed that HCC patients with higher expression of ACACA protein or mRNA levels had poor prognosis. Knockdown of ACACA remarkably crippled the proliferation, colony formation, migration, invasion, epithelial-mesenchymal transition (EMT) process of HCC cells and induced the cell cycle arrest. Mechanistically, ACACA might facilitate the malignant phenotypes of HCC through aberrant activation of Wnt/β-catenin signaling pathway. In addition, ACACA expression was associated with the dilute infiltration of immune cells including plasmacytoid DC (pDC) and cytotoxic cells by utilization of relevant database analysis.

CONCLUSION

ACACA could be a potential biomarker and molecular target for HCC.

N6-methylation of RNA-bound adenosine regulator HNRNPC promotes vascular endothelial dysfunction in type 2 diabetes mellitus by activating the PSEN1-mediated Notch pathway

AIM

The regulatory mechanism of m6A regulators in vascular endothelial function of type 2 diabetes mellitus (T2DM) remains largely unknown. We addressed this issue based on the data retrieved Gene Expression Omnibus (GEO) database and experimental validations.

METHODS

Expression of m6A methylation regulators was evaluated in T2DM samples of GSE76894 dataset and GSE156341 dataset. Further analysis of candidate m6A methylation regulators was conducted in the thoracic aorta of db/db mice and high glucose (HG)-induced human umbilical vein endothelial cells (HUVECs). Ectopic expression and depletion experiments were conducted to detect effects of m6A methylation regulators on vascular endothelial function in T2DM.

RESULTS

It emerged that three m6A methylation regulators (HNRNPC, RBM15B, and ZC3H13) were highly expressed in T2DM, which were related to vascular EC function, showing diagnostic values for T2DM. HNRNPC expression in the thoracic aorta of db/db mice was higher than that in heterozygous db mice, and HNRNPC expression in HG-induced HUVECs was upregulated when compared with normal glucose-exposed HUVECs. Furthermore, HNRNPC activated PSEN1-dependent Notch pathway to induce eNOS inactivation and NO production decrease, thereby causing vascular endothelial dysfunction in T2DM.

CONCLUSIONS

HNRNPC impaired vascular endothelial function to enhance the development of vascular complications in T2DM through PSEN1-mediated Notch signaling pathway.

ZC3H13 Enhances the Malignancy of Cervical Cancer by Regulating m6A Modification of CKAP2

Sustained expression of zinc finger CCCH-type containing 13 (ZC3H13) in tumors is essential for cancer cell malignancy; however, our understanding of its clinical effects and mechanisms in cervical cancer (CC) is limited. In this study, we aimed to reveal the effect on CC progression of ZC3H13-mediated N6-methyladenosine (m6A) modification to stabilize cytoskeleton-associated protein 2 (CKAP2) expression. CC tissues and paired adjacent normal tissues were collected from 50 patients. qRT-PCR was used to clarify ZC3H13 and CKAP2 expression levels in the CC tissues. The functional roles of ZC3H13 and CKAP2 in CC were analyzed by detecting the changes in CC cell proliferation, migration, invasion, and tumor growth in vivo. The regulatory relationship between ZC3H13 and CKAP2 was investigated by confirming m6A modification levels and their expression correlation. ZC3H13 and CKAP2 were highly expressed in CC and linked with poor prognosis. We observed that ZC3H13 inhibition decreased CC cell proliferation, invasion, and migration, while its facilitation promoted CC cell malignancy. ZC3H13 mediated m6A modification of CKAP2 to enhance CKAP2 expression in CC cells. Furthermore, CKAP2 overexpression partially restored the malignant phenotypic promotion induced by ZC3H13 overexpression in CC cells. In summary, this study revealed that ZC3H13-mediating m6A modification of CKAP2 promotes CC development. This finding should be conducive to an understanding of the role of ZC3H13-m6A-CKAP2 in CC and should provide an effective therapeutic target for this cancer.

Dynamic regulation and key roles of ribonucleic acid methylation

Ribonucleic acid (RNA) methylation is the most abundant modification in biological systems, accounting for 60% of all RNA modifications, and affects multiple aspects of RNA (including mRNAs, tRNAs, rRNAs, microRNAs, and long non-coding RNAs). Dysregulation of RNA methylation causes many developmental diseases through various mechanisms mediated by N ⁶-methyladenosine (m⁶A), 5-methylcytosine (m⁵C), N ¹-methyladenosine (m¹A), 5-hydroxymethylcytosine (hm⁵C), and pseudouridine (Ψ). The emerging tools of RNA methylation can be used as diagnostic, preventive, and therapeutic markers. Here, we review the accumulated discoveries to date regarding the biological function and dynamic regulation of RNA methylation/modification, as well as the most popularly used techniques applied for profiling RNA epitranscriptome, to provide new ideas for growth and development.

Significance of Identifying Key Genes Involved in HBV-Related Hepatocellular Carcinoma for Primary Care Surveillance of Patients with Cirrhosis

Cirrhosis is frequently the final stage of disease preceding the development of hepatocellular carcinoma (HCC) and is one of the risk factors for HCC. Preventive surveillance for early HCC in patients with cirrhosis is advantageous for achieving early HCC prevention and diagnosis, thereby enhancing patient prognosis and reducing mortality. However, there is no highly sensitive diagnostic marker for the clinical surveillance of HCC in patients with cirrhosis, which significantly restricts its use in primary care for HCC. To increase the accuracy of illness diagnosis, the study of the effective and sensitive genetic biomarkers involved in HCC incidence is crucial. In this study, a set of 120 significantly differentially expressed genes (DEGs) was identified in the GSE121248 dataset. A protein-protein interaction (PPI) network was constructed among the DEGs, and Cytoscape was used to extract hub genes from the network. In TCGA database, the expression levels, correlation analysis, and predictive performance of hub genes were validated. In total, 15 hub genes showed increased expression, and their positive correlation ranged from 0.80 to 0.90, suggesting they may be involved in the same signaling pathway governing HBV-related HCC. The GSE10143, GSE25097, GSE54236, and GSE17548 datasets were used to investigate the expression pattern of these hub genes in the progression from cirrhosis to HCC. Using Cox regression analysis, a prediction model was then developed. The ROC curves, DCA, and calibration analysis demonstrated the superior disease prediction accuracy of this model. In addition, using proteomic analysis, we investigated whether these key hub genes interact with the HBV-encoded oncogene X protein (HBx), the oncogenic protein in HCC. We constructed stable HBx-expressing LO2-HBx and Huh-7-HBx cell lines. Co-immunoprecipitation coupled with mass spectrometry (Co-IP/MS) results demonstrated that CDK1, RRM2, ANLN, and HMMR interacted specifically with HBx in both cell models. Importantly, we investigated 15 potential key genes (CCNB1, CDK1, BUB1B, ECT2, RACGAP1, ANLN, PBK, TOP2A, ASPM, RRM2, NEK2, PRC1, SPP1, HMMR, and DTL) participating in the transformation process of HBV infection to HCC, of which 4 hub genes (CDK1, RRM2, ANLN, and HMMR) probably serve as potential oncogenic HBx downstream target molecules. All these findings of our study provided valuable research direction for the diagnostic gene detection of HBV-related HCC in primary care surveillance for HCC in patients with cirrhosis.

The emerging therapeutic target of dynamic and reversible N6-methyladenosine modification during cancer development

As a reversible and dynamic epigenetic modification, N6-methyladenosine (m6A) modification is ubiquitous in eukaryotic cells. m6A methylation is prevalent in almost all RNA metabolism processes that affect the fate of cells, including cancer development. As indicated by the available evidence, targeting m6A regulators may play a crucial role in tumor therapy and multidrug resistance. Currently, many questions remain uncovered. Here, we review recent studies on m6A modification in various aspects of tumor progression, tumor immunity, multidrug resistance, and therapeutic targets to provide new insight into the m6A methylation process.

The role of RNA modification in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a highly mortal type of primary liver cancer. Abnormal epigenetic modifications are present in HCC, and RNA modification is dynamic and reversible and is a key post-transcriptional regulator. With the in-depth study of post-transcriptional modifications, RNA modifications are aberrantly expressed in human cancers. Moreover, the regulators of RNA modifications can be used as potential targets for cancer therapy. In RNA modifications, N6-methyladenosine (m6A), N7-methylguanosine (m7G), and 5-methylcytosine (m5C) and their regulators have important regulatory roles in HCC progression and represent potential novel biomarkers for the confirmation of diagnosis and treatment of HCC. This review focuses on RNA modifications in HCC and the roles and mechanisms of m6A, m7G, m5C, N1-methyladenosine (m1A), N3-methylcytosine (m3C), and pseudouridine (ψ) on its development and maintenance. The potential therapeutic strategies of RNA modifications are elaborated for HCC.

N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma

Uterine corpus endometrial carcinoma (UCEC) is a malignant disease that, at present, has no well-characterised prognostic biomarker. In this study, two clusters were identified based on 28 N1-methyladenosine- (m1A-) related long noncoding RNAs (lncRNAs), of which cluster 1 was related to immune pathways according to the results of an enrichment analysis. We further observed better prognosis in patients with higher levels of immune cell infiltration, tumor mutation burden, microsatellite instability, and immune checkpoint gene expression. In addition, through Cox regression analysis and least absolute shrinkage and selection operator regression analysis, 10 m1A-related lncRNAs (mRLs) were employed to build a prognosis model. We found that people in higher risk categories had a poorer survival probability than those in lower risk. Low-risk samples were enriched with immune-related pathways, while the high-risk group was similar to the definition of the “immune desert” phenotype, which was associated with decreased immune infiltration, T cell failure, and decreased tumor mutation burden, while also being insensitive to immunotherapy and chemotherapy. This mRL-based model has the ability to accurately predict the prognosis of UCEC patients, and the mRLs could become promising therapeutic targets in enhancing the response of immunotherapy.

Heterogeneous nuclear ribonucleoprotein A/B: an emerging group of cancer biomarkers and therapeutic targets

Heterogeneous nuclear ribonucleoprotein A/B (hnRNPA/B) is one of the core members of the RNA binding protein (RBP) hnRNPs family, including four main subtypes, A0, A1, A2/B1 and A3, which share the similar structure and functions. With the advance in understanding the molecular biology of hnRNPA/B, it has been gradually revealed that hnRNPA/B plays a critical role in almost the entire steps of RNA life cycle and its aberrant expression and mutation have important effects on the occurrence and progression of various cancers. This review focuses on the clinical significance of hnRNPA/B in various cancers and systematically summarizes its biological function and molecular mechanisms.

N6-Methyladenosine RNA-Binding Protein YTHDF1 in Gastrointestinal Cancers: Function, Molecular Mechanism and Clinical Implication

Simple Summary

N⁶-methyladenosine (m⁶A) is the most abundant internal modification in eukaryotic mRNA and plays a crucial role in the occurrence and development of diseases. YTHDF1 is the most powerful and abundant m⁶A-encoded RNA reader. In this review, we summarize the evidence of the involvement of YTHDF1 in gastrointestinal cancers, its molecular mechanisms of action, and therapeutic implications.

Abstract

N⁶-methyladenosine (m⁶A) is the most abundant internal modification in eukaryotic cell mRNA, and this modification plays a key role in regulating mRNA translation, splicing, and stability. Emerging evidence implicates aberrant m⁶A as a crucial player in the occurrence and development of diseases, especially GI cancers. Among m⁶A regulators, YTHDF1 is the most abundant m⁶A reader that functionally connects m⁶A-modified mRNA to its eventual fate, mostly notably protein translation. Here, we summarized the function, molecular mechanisms, and clinical implications of YTHDF1 in GI cancers. YTHDF1 is largely upregulated in multiple GI cancer and its high expression predicts poor patient survival. In vitro and in vivo experimental evidence largely supports the role of YTDHF1 in promoting cancer initiation, progression, and metastasis, which suggests the oncogenic function of YTHDF1 in GI cancers. Besides, YTHDF1 overexpression is associated with changes in the tumor microenvironment that are favorable to tumorigenesis. Mechanistically, YTHDF1 regulates the expression of target genes by promoting translation, thereby participating in cancer-related signaling pathways. Targeting YTHDF1 holds therapeutic potential, as the overexpression of YTHDF1 is associated with tumor resistance to chemotherapy and immunotherapy. In summary, YTHDF1-mediated regulation of m⁶A modified mRNA is an actionable target and a prognostic factor for GI cancers.

Identification of KRBA1 as a Potential Prognostic Biomarker Associated with Immune Infiltration and m6A Modification in Hepatocellular Carcinoma

Purpose

Hepatocellular carcinoma (HCC) is a malignancy with high incidence, but its prognosis is not optimistic. KRBA1 is a member of the KRAB family and participates in the regulation of gene transcription. However, no studies have focused on the role of KRBA1 in HCC.

Patients and Methods

In this study, we first analyzed the expression of KRBA1 in HCC using TCGA and ICGC databases and validated by Immunohistochemistry in clinical HCC samples. The Wilcoxon rank-sum test was used to determine the relationship between KRBA1 expression and clinicopathological features. Subsequently, we used Kaplan-Meier online website analysis and Cox regression model to predict the prognostic value of KRBA1 in HCC patients. Furthermore, the functions of KRBA1 were identified by enrichment analysis. TIMER and GSCALite were used to investigate the relationship between KRBA1 expression in HCC and immune infiltration and drug targets, respectively. Finally, the relationship between KRBA1 expression and m6A modification in HCC was analyzed using the TCGA and ICGA datasets.

Results

The results showed that KRBA1 was upregulated in HCC and was associated with many clinicopathological features. High KRBA1 causes poor overall survival and may be an independent risk factor for HCC. KRBA1 tends to be hypermethylated and associated with poor prognosis in HCC compared with normal tissues. Enrichment analysis indicates that KRBA1 is associated with cell cycle and immune processes, and TIMER analysis shows that KRBA1 expression is associated with infiltration levels and immune characteristics of various immune cells. Silenced KRBA1 evidently reduced three chemokine expression in HCC cells. Drug sensitivity analysis showed that KRBA1 was sensitive to 39 drug small molecules. KRBA1 showed a strong positive correlation with five m6A related genes.

Conclusion

KRBA1 is a prognostic biomarker associated with HCC immunity and m6a modification, serving as an effective target for the diagnosis and treatment of HCC.

A multi-omics-based investigation of the immunological and prognostic impact of necroptosis-related genes in patients with hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common histological subtype of liver cancer and the third leading cause of death from cancer globally. Recent studies suggested cell death is also a key regulator of tumour progression. The purpose of this study was to generate a new predictive signature for HCC patients based on a complete analysis of necroptosis‐associated genes.

Methods

We extracted the mRNA expression profiles of HCC patients from the TCGA and ICGC databases and their clinical data. In addition, we used the IMvigor210 cohort to validate our model molecule's ability to predict the effect of immunotherapy. In the TCGA cohort, a seven‐gene risk‐prognostic model was constructed using univariate cox‐Lasoo regression. External validation was conducted using the ICGC cohort. The ssGSEA algorithm is used to determine the degree of immune function response. The CMAP databases are used for chemotherapy drug analysis and screening for drugs that reduce the expression of high‐risk genes. The cbioportal database was used to explore mutations in model genes.

Results

Survival analysis shows shorter survival for high‐risk patients. Immune function analysis revealed significant differences in the activity of immune pathways between risk subgroups. Varied risk scores result in dramatically diverse immune infiltration and tumour growth, as well as significantly different chemotherapeutic sensitivity. In addition, Apigenin and LY‐294002 reduced the expression of high‐risk genes, while Arecoline had the opposite effect. In the immunotherapy IMvigor210 cohort, risk scores were significantly different between the objective responder and non‐responder groups. By comparing the models constructed with published literature, it is suggested that our model has better predictive power.

Conclusions

We created a new prognostic signature of necroptosis‐related genes that can be used as potential prognostic biomarkers to guide effective personalized therapy for hepatocellular carcinoma patients.

Establishing a cancer driver gene signature-based risk model for predicting the prognoses of gastric cancer patients

Despite the high prevalence of gastric cancer (GC), molecular biomarkers that can reliably detect GC are yet to be discovered. The present study aimed to establish a robust gene signature based on cancer driver genes (CDGs) that can predict GC prognosis. Transcriptional profiles and clinical data from GC patients were analyzed using univariate Cox regression analysis and the least absolute shrinkage and selection (LASSO)-penalized Cox regression analysis to select optimal prognosis-related genes for modeling. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier analyses were done to assess the predictive power of this gene signature. A nomogram model for prediction of survival of GC patients was established using the CDG signature and clinical information, and a seven-CDG signature was identified. Risk scores were calculated using this signature, and patients were subsequently divided into high- and low-risk groups; high-risk patients in the training and validation datasets had poorer prognoses than low-risk patients. Cox regression analysis revealed that the CDG signature is an independent prognostic factor for GC. The signature and other clinical features were used to construct a nomogram for predicting overall GC patient survival. Calibration and decision curve analysis showed that the nomogram accurately predicted survival, highlighting its clinical utility. Thus, we established a novel CDG signature and nomogram for predicting GC prognosis, which may facilitate personalized treatment of GC.

The Detection and Verification of Two Heterogeneous Subgroups and a Risk Model Based on Ferroptosis-Related Genes in Hepatocellular Carcinoma

^#Background. Because of the heterogeneity of hepatocellular carcinoma (HCC) and the complex nature of the tumor microenvironment (TME), the long-term efficacy of therapy continues to be a clinical challenge. It is necessary to classify and refine the appropriate treatment intervention decision-making in this kind of tumor. Methods. We used “ConsensusClusterPlus” to establish a stable molecular classification based on the ferroptosis-related genes (FRGs) expression obtained from FerrDb. The clinical features, immune infiltration, DNA damage, and genomic changes of different subclasses were evaluated. The least absolute shrinkage and selection operator regression (LASSO) method and univariate Cox regression were utilized to construct the ferroptosis-related prognosis risk score (FPRS) model, and the association between the FPRS model and HCC molecular characteristics, immune features, and immunotherapy was studied. Results. We identified two ferroptosis subclasses, C1 with poor prognosis and a higher proportion of patients in the middle and late stages infected with HBV and HCV, having higher DNA damage including aneuploidy, HRD, fraction altered, and the number of segments, and higher probability of gene mutation and copy number mutation. FPRS model was constructed on the basis of differentially expressed genes (DEGs) between C1 and C2, which showed a higher area under the curve (AUC) in predicting overall survival rate in the training set and independent verification cohort and could reflect the clinical characteristics and response to immunotherapy of different patients, being an independent prognostic factor of HCC. Conclusion. Here, we revealed two novel molecular subgroups based on FRGs and develop an FPRS model consisting of six genes that can help predict prognosis and select patients suitable for immunotherapy.

Downregulation of ZC3H13 by miR-362-3p/miR-425-5p is associated with a poor prognosis and adverse outcomes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is notorious for its poor prognosis. Previous studies identified several N6-methyladenosine (m6A)-related genes that play key roles in the initiation and progression of HCC patients. In particular, the N6-methyladenosine RNA methylation regulator ZC3H13 could be a candidate as a novel biomarker and therapeutic target for hepatocellular carcinoma. In HCC, low expression of ZC3H13 was reported, but the molecular reason is unclear. In this study, we performed pan cancer analysis for ZC3H13 expression and prognosis using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) data and found that ZC3H13 might be a potential tumor suppressor gene in HCC. Subsequently, miRNAs contributing to ZC3H13 downregulation were identified by a series of in silico analyses, including expression analysis, correlation analysis, and survival analysis. Finally, the miR-362-3p/miR-425-5p-ZC3H13 axis was identified as the most likely upstream miRNA-related pathway of ZC3H13 in HCC. Additionally, miR-362-3p/miR-425-5p mimic and inhibitor results were detected by quantitative real-time PCR (qPCR) analysis and western blotting. We identified an upstream regulatory mechanism of ZC3H13 in HCC, namely, the miR-362-3p/miR-425-5p-ZC3H13 axis. Moreover, the ZC3H13 level was significantly positively associated with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression. Collectively, our findings elucidated that ncRNA-mediated downregulation of ZC3H13 was correlated with a poor prognosis and tumor immune infiltration in HCC. In conclusion, this study demonstrates that ZC3H13 is a direct target of miR-362-3p/miR-425-5p in liver hepatocellular carcinoma (LIHC) that regulates immune modulation in the microenvironment of LIHC.

Expression of IER3 in hepatocellular carcinoma: clinicopathology, prognosis, and potential regulatory pathways

Background

Immediate early response 3 (IER3) is correlated to the prognosis of several cancers, but the precise mechanisms underlying the regulation by IER3 of the occurrence and development of hepatocellular carcinoma (HCC) remain unknown.

Methods

The expression level of IER3 was examined by using in-house immunohistochemistry (IHC), public gene chip, and public RNA-sequencing (RNA-seq). The standardized mean difference (SMD) was calculated to compare the expression levels of IER3 between HCC patients and controls. The summary receiver operating characteristics (sROC) was plotted to comprehensively understand the discriminatory capability of IER3 between HCC and non-HCC group. The Kaplan-Meier curves and the combined hazard ratios (HRs) were used to determine the prognostic value of IER3 in HCC. Moreover, differentially expressed genes (DEGs) and co-expression genes (CEGs) were used to explored the molecular mechanisms of IER3 underlying HCC. hTFtarget was used to predict the transcription factors (TFs) of IER3. The binding site of TFs and the IER3 promoter region was forecasted using the JASPAR website. The relevant ChIP-seq data were used to determine whether TF peaks were present in the IER3 transcription initiation.

Results

A significantly increased expression of IER3 protein was found in HCC tissue relative to non-HCC tissue as detected by IHC (p < 0.001). Compared to 1,263 cases of non-HCC tissues, IER3 in 1483 cases of HCC tissues was upregulated (SMD = 0.42, 95% confidence interval [CI] [0.09-0.76]). The sROC showed that IER3 had a certain ability at differentiating HCC tissues (area under the curve (AUC) = 0.65, 95% CI [0.61-0.69]). Comprehensive analysis of the effect of IER3 on the prognosis of patients with HCC demonstrated that higher IER3 expression was associated with poor prognosis in HCC (HRs = 1.30, 95% CI [1.03-1.64]). Pathway enrichment analysis revealed that IER3-related genes were mostly enriched in the PI3K-Akt signaling pathway, cancer-related signaling pathways, the p53 signaling pathway, and other signaling pathways. Regulatory factor X5 (RFX5) was identified as a possible regulator of IER3-related TF.

Conclusion

IER3 may be a potential prognostic marker for HCC. The molecular mechanisms of IER3 in HCC warrant further study.

Analysis and identification of m6A RNA methylation regulators in metastatic osteosarcoma

Osteosarcoma (OS) is characterized by rapid growth and early metastasis. However, its mechanism remains unclear. N6-methyladenosine (m6A) modification and its regulatory factors play essential roles in most cancers, including OS. In this study, we screened out 21 m6A modifiers using the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, followed by the identification of the critical m6A methylation modifiers. The results revealed that the expression levels of three m6A methylation regulators, namely RBM15, METTL3, and LRPPRC, were associated with the low survival rate of patients with OS. We further studied the independent prognostic factors by performing univariate and multivariate Cox analyses and found that metastasis was an independent prognostic factor for patients with OS. Furthermore, we found for the first time that RBM15 was specific for metastatic OS rather than non-metastatic OS. Moreover, the significant overexpression of RBM15 was validated in metastatic OS cell lines and in actual human clinical specimens. We also revealed that RBM15 promoted the invasion, migration, and metastasis of OS cells through loss-functional and gain-functional experiments and an animal metastatic model. In conclusion, RBM15 has a high correlation with OS metastasis formation and the decreased survival rate of patients with OS, and this may serve as a useful biomarker for predicting metastasis and prognosis of patients with OS.

The Bright and the Dark Side of TGF-β Signaling in Hepatocellular Carcinoma: Mechanisms, Dysregulation, and Therapeutic Implications

Simple Summary

Transforming growth factor β (TGF-β) signaling is a preeminent regulator of diverse cellular and physiological processes. Frequent dysregulation of TGF-β signaling has been implicated in cancer. In hepatocellular carcinoma (HCC), the most prevalent form of primary liver cancer, the autocrine and paracrine effects of TGF-β have paradoxical implications. While acting as a potent tumor suppressor pathway in the early stages of malignancy, TGF-β diverts to a promoter of tumor progression in the late stages, reflecting its bright and dark natures, respectively. Within this context, targeting TGF-β represents a promising therapeutic option for HCC treatment. We discuss here the molecular properties of TGF-β signaling in HCC, attempting to provide an overview of its effects on tumor cells and the stroma. We also seek to evaluate the dysregulation mechanisms that mediate the functional switch of TGF-β from a tumor suppressor to a pro-tumorigenic signal. Finally, we reconcile its biphasic nature with the therapeutic implications.

Abstract

Hepatocellular carcinoma (HCC) is associated with genetic and nongenetic aberrations that impact multiple genes and pathways, including the frequently dysregulated transforming growth factor β (TGF-β) signaling pathway. The regulatory cytokine TGF-β and its signaling effectors govern a broad spectrum of spatiotemporally regulated molecular and cellular responses, yet paradoxically have dual and opposing roles in HCC progression. In the early stages of tumorigenesis, TGF-β signaling enforces profound tumor-suppressive effects, primarily by inducing cell cycle arrest, cellular senescence, autophagy, and apoptosis. However, as the tumor advances in malignant progression, TGF-β functionally switches to a pro-tumorigenic signal, eliciting aggressive tumor traits, such as epithelial–mesenchymal transition, tumor microenvironment remodeling, and immune evasion of cancer cells. On this account, the inhibition of TGF-β signaling is recognized as a promising therapeutic strategy for advanced HCC. In this review, we evaluate the functions and mechanisms of TGF-β signaling and relate its complex and pleiotropic biology to HCC pathophysiology, attempting to provide a detailed perspective on the molecular determinants underlying its functional diversion. We also address the therapeutic implications of the dichotomous nature of TGF-β signaling and highlight the rationale for targeting this pathway for HCC treatment, alone or in combination with other agents.

Circular RNA SOX5 promotes the proliferation and inhibits the apoptosis of the hepatocellular carcinoma cells by targeting miR-502-5p/synoviolin 1 axis

We aimed to explore the role of circ-SOX5 in the pathogenesis of hepatocellular carcinoma (HCC). The circRNAs in HCC were screened using the GEO database. RT-qPCR was used to detect mRNA expression. Targeting relationships were confirmed by dual luciferase reporter assay and RNA pull-down assay. CCK-8 and EDU staining were used to measure cell viability and proliferation, respectively. Cell apoptosis was determined using flow cytometry. Protein expression was determined by Western blotting. Circ-SOX5 expression was increased in HCC tissues. Inhibition of circ-SOX5 expression reduced the viability, proliferation, and colony formation, and increased the apoptosis of HCC cells. However, miR-502-5p inhibition or overexpression of synoviolin 1 (SYVN1) can reverse the effects of circ-SOX5 knockdown on proliferation and apoptosis. This study demonstrated that the circ-SOX5/miR-502-5p/SYVN1 axis promotes the development of HCC by regulating cell apoptosis. Therefore, circ-SOX5 may be a potential biomarker of HCC.

ZC3H13 Inhibits the Progression of Hepatocellular Carcinoma through m6A-PKM2-Mediated Glycolysis and Enhances Chemosensitivity

Objective

N⁶-Methyladenosine (m⁶A) is the most prevalent RNA epigenetic modulation in eukaryotic cells, which serves a critical role in diverse physiological processes. Emerging evidences indicate the prognostic significance of m⁶A regulator ZC3H13 in hepatocellular carcinoma (HCC). Herein, this study was conducted for revealing biological functions and mechanisms of ZC3H13 in HCC.

Methods

Expression of ZC3H13 was examined in collected HCC and normal tissues, and its prognostic significance was investigated in a public database. Gain/loss of functional assays were presented for defining the roles of ZC3H13 in HCC progression. The specific interactions of ZC3H13 with PKM2 were validated in HCC cells via mRNA stability, RNA immunoprecipitation, and luciferase reporter and MeRIP-qPCR assays. Moreover, rescue experiments were carried out for uncovering the mechanisms.

Results

ZC3H13 expression was downregulated in HCC, and its loss was in relation to dismal survival outcomes. Functionally, overexpressed ZC3H13 suppressed proliferation, migration, and invasion and elevated apoptotic levels of HCC cells. Moreover, ZC3H13 overexpression sensitized to cisplatin and weakened metabolism reprogramming of HCC cells. Mechanically, ZC3H13-induced m⁶A modified patterns substantially abolished PKM2 mRNA stability. ZC3H13 facilitated malignant behaviors of HCC cells through PKM2-dependent glycolytic signaling.

Conclusion

Collectively, ZC3H13 suppressed the progression of HCC through m⁶A-PKM2-mediated glycolysis and sensitized HCC cells to cisplatin, which offered a fresh insight into HCC therapy.

Non-Coding RNA m6A Modification in Cancer: Mechanisms and Therapeutic Targets

Recently, N6-methyl-adenosine (m6A) ribonucleic acid (RNA) modification, a critical and common internal RNA modification in higher eukaryotes, has generated considerable research interests. Extensive studies have revealed that non-coding RNA m6A modifications (e.g. microRNAs, long non-coding RNAs, and circular RNAs) are associated with tumorigenesis, metastasis, and other tumour characteristics; in addition, they are crucial molecular regulators of cancer progression. In this review, we discuss the relationship between non-coding RNA m6A modification and cancer progression from the perspective of various cancers. In particular, we focus on important mechanisms in tumour progression such as proliferation, apoptosis, invasion and metastasis, tumour angiogenesis. In addition, we introduce clinical applications to illustrate more vividly that non-coding RNA m6A modification has broad research prospects. With this review, we aim to summarize the latest insights and ideas into non-coding RNA m6A modification in cancer progression and targeted therapy, facilitating further research.

Declined expressions of vast mitochondria-related genes represented by CYCS and transcription factor ESRRA in skeletal muscle aging

Age-related skeletal muscle deterioration (sarcopenia) has a significant effect on the elderly's health and quality of life, but the molecular and gene regulatory mechanisms remain largely unknown. It is necessary to identify the candidate genes related to skeletal muscle aging and prospective therapeutic targets for effective treatments. The age-line-related genes (ALRGs) and age-line-related transcripts (ALRTs) were investigated using the gene expression profiles of GSE47881 and GSE118825 from the Gene Expression Omnibus (GEO) database. The protein-protein interaction (PPI) networks were performed to identify the key molecules with Cytoscape, and Gene Set Enrichment Analysis (GSEA) was used to clarify the potential molecular functions. Two hub molecules were finally obtained and verified with quantitative real-time PCR (qRT-PCR). The results showed that the expression of mitochondria genes involved in mitochondrial electron transport, complex assembly of the respiratory chain, tricarboxylic acid cycle, oxidative phosphorylation, and ATP synthesis were down-regulated in skeletal muscle with aging. We further identified a primary hub gene of CYCS (Cytochrome C) and a key transcription factor of ESRRA (Estrogen-related Receptor Alpha) to be associated closely with skeletal muscle aging. PCR analysis confirmed the expressions of CYCS and ESRRA in gastrocnemius muscles of mice of different ages were significantly different, and decreased gradually with age. In conclusion, the main cause of skeletal muscle aging may be the systematically reduced expression of mitochondrial functional genes. The CYCS and ESRRA may play significant roles in the progression of skeletal muscle aging and serve as potential biomarkers for future diagnosis and treatment.

Development and Validation of a Novel Mitophagy-Related Gene Prognostic Signature for Hepatocellular Carcinoma Based on Immunoscore Classification of Tumor

Emerging evidence suggested that mitophagy may play an important role in the progression of hepatocellular carcinoma (HCC), whereas the association between mitophagy-related genes and HCC patients' prognosis remains unknown. In this study, we aimed to investigate the potential prognostic values of mitophagy-related genes (MRGs) on HCC patients at the genetic level. According to median immunoscore, we categorized HCC patients from TCGA cohort into two immune score groups, while 39 differential expression MRGs were identified. By using univariate analysis, we screened out 18 survival-associated MRGs, and then, the least absolute shrinkage and selection operator (LASSO) analysis was applied to construct a prognosis model that consisted of 9 MRGs (ATG7, ATG9A, BNIP3L, GABARAPL1, HTRA2, MAP1LC3B2, TFE3, TIGAR, and TOMM70). In our prognostic model, overall survival in the high and low-risk groups was significantly different (P < 0.001), and the respective areas under the curve (AUC) of our prognostic model were 0.686 for 3-year survival in the TCGA cohort and 0.776 for 3-year survival in the ICGC cohort. Moreover, we identified the risk score as the independent factor for predicting the HCC patients' prognosis by using single and multifactor analyses, and a nomogram was also constructed for future clinical application. Further functional analyses showed that the immune status between two risk groups was significantly different. Our findings may provide a novel mitophagy-related gene signature, and these will be better used for prognostic prediction in HCC, thus improving patient outcome.

Integrated Analysis of DNA methylation and transcriptome profile to identify key features of age-related macular degeneration

Age-related macular degeneration (AMD) is a common vision-threatening disease. The current study sought to integrate DNA methylation with transcriptome profile to explore key features in AMD. Gene expression data were obtained from the Gene Expression Omnibus (GEO, accession ID: GSE135092) and DNA methylation data were obtained from the ArrayExpress repository (E-MTAB-7183). A total of 456 differentially expressed genes (DEGs) and 4827 intragenic differentially methylated CpGs (DMCs) were identified between AMD and controls. DEGs and DMCs were intersected and 19 epigenetically induced (EI) genes and 15 epigenetically suppressed (ES) genes were identified. Immune cell infiltration analysis was performed to estimate the abundance of different types of immune cell in each sample. Enrichment scores of inflammatory response and tumor necrosis factor-alpha (TNFα) signaling via nuclear factor kappa B (NF-κb) were positively correlated with abundance of activated memory CD4 T cells and M1 macrophages. Subsequently, two significant random forest classifiers were constructed based on DNA methylation and transcriptome data. SMAD2 and NGFR were selected as key genes through functional epigenetic modules (FEM) analysis. Expression level of SMAD2, NGFR and their integrating proteins was validated in hydrogen peroxide (H₂O₂) and TNFα co-treated retinal pigment epithelium (RPE) in vitro. The findings of the current study showed that local inflammation and systemic inflammatory host response play key roles in pathogenesis of AMD. SMAD2 and NGFR provide new insight in understanding the molecular mechanism and are potential therapeutic targets for development of AMD therapy.

Expression of N6-methyladenosine (m6A) regulators correlates with immune microenvironment characteristics and predicts prognosis in diffuse large cell lymphoma (DLBCL)

This study conducted a comprehensive analysis of the clinical significance of N⁶-methyladenosine (m⁶A) regulators and their relationship with immune microenvironment characteristics in diffuse large cell lymphoma (DLBCL). Consensus clustering was performed to molecularly discriminate DLBCL subtypesbased on m⁶A regulators’ expression. Using the Cox and Lasso regression algorithm, survival-associated m⁶A regulators were identified, and a m⁶A-based prognostic signature was established. The influence of m⁶A risk on immune cell infiltration, immune checkpoint genes, cancer immunity cycle, and immunotherapeutic response was evaluated. Potential molecular pathways related to m⁶A risk were investigated using gene set enrichment analysis. The m⁶A regulators showed satisfactory performance in distinguishing DLBCL subgroups with distinct clinical traits and outcomes. A six m⁶A regulator-based prognostic signature was established and validated as an independent predictor, which separated patients into low- and high-risk groups. High-risk m⁶A indicated worse survival. The B cells naïve, T cells gamma delta, and NK cells resting were the three most affected immune cells by m⁶A risk. Up-regulated (PDCD1 and KIR3DL1) and down-regulated (TIGIT, IDO1, and BTLA) immune checkpoint genes in the high-risk group were identified. The m⁶A risk was found to influence several steps in the cancer immunity cycle. Patients with high-risk m⁶A were more likely to benefit from immunotherapy. Biological function enrichment analysis revealed that high-risk m⁶A to be tended related to malignant tumor characteristics, while low-risk m⁶A showed trend to be related to defensive response processes. Collectively, the m⁶A-based prognostic signature could be a practical prognostic predictor for DLBCL and immune microenvironment characteristics affected by m⁶A may be part of the mechanism.

Effects of RNA methylation N6-methyladenosine regulators on malignant progression and prognosis of melanoma

Background

Melanoma is an extremely aggressive type of skin cancer and experiencing a expeditiously rising mortality in a current year. Exploring new potential prognostic biomarkers and therapeutic targets of melanoma are urgently needed. The ambition of this research was to identify genetic markers and assess prognostic performance of N6-methyladenosine (m6A) regulators in melanoma.

Methods

Gene expression data and corresponding clinical informations of melanoma patients as well as sequence data of normal controls are collected from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. Quantitative real-time PCR (qRT-PCR) analysis was carried out to detect the RNA expression of IGF2BP3 in A375 cell line, melanoma tissues, and normal tissues. Western blot, cell proliferation, and migration assays were performed to assess the ability of IGF2BP3 in A375 cell line.

Results

Differently expressed m6A regulators between tumor samples and normal samples were analyzed. A three-gene prognostic signature including IGF2BP3, RBM15B, and METTL16 was constructed, and the risk score of this signature was identified to be an independent prognostic indicator for melanoma. In addition, IGF2BP3 was verified to promote melanoma cell proliferation and migration in vitro and associate with lymph node metastasis in clinical samples. Moreover, risk score and the expression of IGF2BP3 were positively associated with the infiltrating immune cells and these hub genes made excellent potential drug targets in melanoma.

Conclusion

We identified the genetic changes in m6A regulatory genes and constructed a three-gene risk signature with distinct prognostic value in melanoma. This research provided new insights into the epigenetic understanding of m6A regulators and novel therapeutic strategies in melanoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02163-9.

Oncogenic role of early growth response-1 in liver cancer through the regulation of the microRNA-675/sestrin 3 and the Wnt/β-catenin signaling pathway

Early growth response-1 (EGR1) is a multi-domain protein and an immediate early transcription factor that is induced during liver injury and controls the expression of a variety of genes implicated in metabolism, cell proliferation, and tumorigenesis. Liver cancer (LC) is a highly malignant disease with high mortality worldwide. This study focused on the function of EGR1 in LC development and the mechanism of action. Two LC-related datasets GSE101728 and GSE138178 downloaded from the Gene Expression Omnibus (GEO) database were used for identification of key genes involved in cancer progression. A microarray analysis was conducted to identify differentially expressed microRNAs (miRNAs) after EGR1 knockdown. The target gene of miR-675 was identified by integrated analysis. EGR1 and miR-675 were highly expressed, whereas sestrin 3 (SESN3) was poorly expressed in LC tissues and cells. High EGR1 expression was associated with poor liver function and disease severity in patients with LC. Knockdown of EGR1 weakened proliferation and invasiveness of LC cells. EGR1 bound to the miR-675 promoter and increased its transcription, and miR-675 bound to SESN3 mRNA to induce its downregulation. miR-675 upregulation promoted the malignance of LC cells, but further upregulation of SESN3 reduced invasiveness of cells. SESN3 was enriched in the Wnt/β-catenin signaling. EGR1 and miR-675 activated the Wnt/β-catenin through downregulating SESN3. This study demonstrated that EGR1 promotes the malignant behaviors of LC cells through mediating the miRNA-675/SESN3/Wnt/β-catenin axis.