NOP2-mediated m5C Modification of c-Myc in an EIF3A-Dependent Manner to Reprogram Glucose Metabolism and Promote Hepatocellular Carcinoma Progression

Mitophagy Promotes Hair Regeneration by Activating Glutathione Metabolism

Mitophagy maintains tissue homeostasis by self-eliminating defective mitochondria through autophagy. How mitophagy regulates stem cell activity during hair regeneration remains unclear. Here, we found that mitophagy promotes the proliferation of hair germ (HG) cells by regulating glutathione (GSH) metabolism. First, single-cell RNA sequencing, mitochondrial probe, transmission electron microscopy, and immunofluorescence staining showed stronger mitochondrial activity and increased mitophagy-related gene especially Prohibitin 2 (Phb2) expression at early-anagen HG compared to the telogen HG. Mitochondrial inner membrane receptor protein PHB2 binds to LC3 to initiate mitophagy. Second, molecular docking and functional studies revealed that PHB2-LC3 activates mitophagy to eliminate the damaged mitochondria in HG. RNA-seq, single-cell metabolism, immunofluorescence staining, and functional validation discovered that LC3 promotes GSH metabolism to supply energy for promoting HG proliferation. Third, transcriptomics analysis and immunofluorescence staining indicated that mitophagy was down-regulated in the aged compared to young-mouse HG. Activating mitophagy and GSH pathways through small-molecule administration can reactivate HG cell proliferation followed by hair regeneration in aged hair follicles. Our findings open up a new avenue for exploring autophagy that promotes hair regeneration and emphasizes the role of the self-elimination effect of mitophagy in controlling the proliferation of HG cells by regulating GSH metabolism.

NOP2 facilitates EZH2-mediated epithelial-mesenchymal transition by enhancing EZH2 mRNA stability via m5C methylation in lung cancer progression

NOP2, a member of the NOL1/NOP2/SUN domain (NSUN) family, is responsible for catalyzing the posttranscriptional modification of RNA through 5-methylcytosine (m5C). Dysregulation of m5C modification has been linked to the pathogenesis of various malignant tumors. Herein, we investigated the expression of NOP2 in lung adenocarcinoma (LUAD) tissues and cells, and found that it was significantly upregulated. Moreover, lentivirus-mediated overexpression of NOP2 in vitro resulted in enhanced migration and invasion capabilities of lung cancer cells, while in vivo experiments demonstrated its ability to promote the growth and metastasis of xenograft tumors. In contrast, knockdown of NOP2 effectively inhibited the growth and metastasis of lung cancer cells. RNA-sequencing was conducted to ascertain the downstream targets of NOP2, and the findings revealed a significant upregulation in EZH2 mRNA expression upon overexpression of NOP2. Subsequent validation experiments demonstrated that NOP2 exerted an m5C-dependent influence on the stability of EZH2 mRNA. Additionally, our investigations revealed a co-regulatory relationship between NOP2 and the m5C reader protein ALYREF in modulating the stability of EZH2 mRNA. Notably, the NOP2/EZH2 axis facilitated the malignant phenotype of lung cancer cells by inducing epithelial-mesenchymal transition (EMT) both in vitro and in vivo. Mechanistically, ChIP analysis proved that EZH2 counteracted the impact of NOP2 on the occupancy capacity of EZH2 and H3K27me3 in the promoter regions of E-cadherin, a gene crucial for regulating EMT. In a word, our research highlights the significant role of NOP2 in LUAD and offers novel mechanistic insights into the NOP2/ALYREF/EZH2 axis, which holds promise as a potential target for lung cancer therapy.

Elucidating the multifaceted role of MGAT1 in hepatocellular carcinoma: integrative single-cell and spatial transcriptomics reveal novel therapeutic insights

Background

Glycosyltransferase-associated genes play a crucial role in hepatocellular carcinoma (HCC) pathogenesis. This study investigates their impact on the tumor microenvironment and molecular mechanisms, offering insights into innovative immunotherapeutic strategies for HCC.

Methods

We utilized cutting-edge single-cell and spatial transcriptomics to examine HCC heterogeneity. Four single-cell scoring techniques were employed to evaluate glycosyltransferase genes. Spatial transcriptomic findings were validated, and bulk RNA-seq analysis was conducted to identify prognostic glycosyltransferase-related genes and potential immunotherapeutic targets. MGAT1's role was further explored through various functional assays.

Results

Our analysis revealed diverse cell subpopulations in HCC with distinct glycosyltransferase gene activities, particularly in macrophages. Key glycosyltransferase genes specific to macrophages were identified. Temporal analysis illustrated macrophage evolution during tumor progression, while spatial transcriptomics highlighted reduced expression of these genes in core tumor macrophages. Integrating scRNA-seq, bulk RNA-seq, and spatial transcriptomics, MGAT1 emerged as a promising therapeutic target, showing significant potential in HCC immunotherapy.

Conclusion

This comprehensive study delves into glycosyltransferase-associated genes in HCC, elucidating their critical roles in cellular dynamics and immune cell interactions. Our findings open new avenues for immunotherapeutic interventions and personalized HCC management, pushing the boundaries of HCC immunotherapy.

A Platelet-Powered Drug Delivery System for Enhancing Chemotherapy Efficacy for Liver Cancer Using the Trojan Horse Strategy

Optimizing the delivery and penetration of nano-sized drugs within liver cancer sites, along with remodeling the tumor microenvironment, is crucial for enhancing the efficacy of chemotherapeutic agents. For this study, a platelet (PLT)-mediated nanodrug delivery system (DASA+ATO@PLT) was developed to improve the effectiveness of chemotherapy. This system delivers nano-sized dasatinib and atovaquone specifically to liver tumor sites and facilitates intra-tumoral permeation upon release. Through JC-1, immunohistochemistry, and DNA damage analyses, the therapeutic effect of DASA+ATO@PLT was assessed. In vitro simulation and intravital imaging were carried out to determine the accumulation of dasatinib and atovaquone in liver tumor sites. The experiment demonstrated the accumulation of dasatinib and atovaquone in tumor sites, followed by deep permeation in the tumor microenvironment with the assistance of PLTs, while simultaneously revealing the ability of DASA+ATO@PLT to remodel the liver cancer microenvironment (overcoming hypoxia) and enhance chemotherapeutic efficacy. This system utilizes the natural tumor recognition ability of PLTs and enhances the chemo-immunotherapeutic effect through targeted delivery of nano-chemotherapeutic drugs to the tumor, resulting in effective accumulation and infiltration. The PLT-mediated nanodrug delivery system serves as a "Trojan horse" to carry therapeutic drugs as cargo and deliver them to target cells, leading to favorable outcomes.

Multi-omic validation of the cuproptosis-sphingolipid metabolism network: modulating the immune landscape in osteosarcoma

Background

The current understanding of the mechanisms by which metal ion metabolism promotes the progression and drug resistance of osteosarcoma remains incomplete. This study aims to elucidate the key roles and mechanisms of genes involved in cuproptosis-related sphingolipid metabolism (cuproptosis-SPGs) in regulating the immune landscape, tumor metastasis, and drug resistance in osteosarcoma cells.

Methods

This study employed multi-omics approaches to assess the impact of cuproptosis-SPGs on the prognosis of osteosarcoma patients. Lasso regression analysis was utilized to construct a prognostic model, while multivariate regression analysis was applied to identify key core genes and generate risk coefficients for these genes, thereby calculating a risk score for each osteosarcoma patient. Patients were then stratified into high-risk and low-risk groups based on their risk scores. The ESTIMATE and CIBERSORT algorithms were used to analyze the level of immune cell infiltration within these risk groups to construct the immune landscape. Single-cell analysis was conducted to provide a more precise depiction of the expression patterns of cuproptosis-SPGs among immune cell subtypes. Finally, experiments on osteosarcoma cells were performed to validate the role of the cuproptosis-sphingolipid signaling network in regulating cell migration and apoptosis.

Results

In this study, seven cuproptosis-SPGs were identified and used to construct a prognostic model for osteosarcoma patients. In addition to predicting survival, the model also demonstrated reliability in forecasting the response to chemotherapy drugs. The results showed that a high cuproptosis-sphingolipid metabolism score was closely associated with reduced CD8 T cell infiltration and indicated poor prognosis in osteosarcoma patients. Cellular functional assays revealed that cuproptosis-SPGs regulated the LC3B/ERK signaling pathway, thereby triggering cell death and impairing migration capabilities in osteosarcoma cells.

Conclusion

The impact of cuproptosis-related sphingolipid metabolism on the survival and migration of osteosarcoma cells, as well as on CD8 T cell infiltration, highlights the potential of targeting copper ion metabolism as a promising strategy for osteosarcoma patients.

The role of RNA methylation in tumor immunity and its potential in immunotherapy

RNA methylation, a prevalent post-transcriptional modification, has garnered considerable attention in research circles. It exerts regulatory control over diverse biological functions by modulating RNA splicing, translation, transport, and stability. Notably, studies have illuminated the substantial impact of RNA methylation on tumor immunity. The primary types of RNA methylation encompass N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), and N7-methylguanosine (m7G), and 3-methylcytidine (m3C). Compelling evidence underscores the involvement of RNA methylation in regulating the tumor microenvironment (TME). By affecting RNA translation and stability through the "writers", "erasers" and "readers", RNA methylation exerts influence over the dysregulation of immune cells and immune factors. Consequently, RNA methylation plays a pivotal role in modulating tumor immunity and mediating various biological behaviors, encompassing proliferation, invasion, metastasis, etc. In this review, we discussed the mechanisms and functions of several RNA methylations, providing a comprehensive overview of their biological roles and underlying mechanisms within the tumor microenvironment and among immunocytes. By exploring how these RNA modifications mediate tumor immune evasion, we also examine their potential applications in immunotherapy. This review aims to provide novel insights and strategies for identifying novel targets in RNA methylation and advancing cancer immunotherapy efficacy.

Crosstalk between Epigenetics and Metabolic Reprogramming in Metabolic Dysfunction-Associated Steatotic Liver Disease-Induced Hepatocellular Carcinoma: A New Sight

Epigenetic and metabolic reprogramming alterations are two important features of tumors, and their reversible, spatial, and temporal regulation is a distinctive hallmark of carcinogenesis. Epigenetics, which focuses on gene regulatory mechanisms beyond the DNA sequence, is a new entry point for tumor therapy. Moreover, metabolic reprogramming drives hepatocellular carcinoma (HCC) initiation and progression, highlighting the significance of metabolism in this disease. Exploring the inter-regulatory relationship between tumor metabolic reprogramming and epigenetic modification has become one of the hot directions in current tumor metabolism research. As viral etiologies have given way to metabolic dysfunction-associated steatotic liver disease (MASLD)-induced HCC, it is urgent that complex molecular pathways linking them and hepatocarcinogenesis be explored. However, how aberrant crosstalk between epigenetic modifications and metabolic reprogramming affects MASLD-induced HCC lacks comprehensive understanding. A better understanding of their linkages is necessary and urgent to improve HCC treatment strategies. For this reason, this review examines the interwoven landscape of molecular carcinogenesis in the context of MASLD-induced HCC, focusing on mechanisms regulating aberrant epigenetic alterations and metabolic reprogramming in the development of MASLD-induced HCC and interactions between them while also updating the current advances in metabolism and epigenetic modification-based therapeutic drugs in HCC.

RNA m5C methylation: a potential modulator of innate immune pathways in hepatocellular carcinoma

RNA 5-methylcytosine (m5C) methylation plays a crucial role in hepatocellular carcinoma (HCC). As reported, aberrant m5C methylation is closely associated with the progression, therapeutic efficacy, and prognosis of HCC. The innate immune system functions as the primary defense mechanism in the body against pathogenic infections and tumors since it can activate innate immune pathways through pattern recognition receptors to exert anti-infection and anti-tumor effects. Recently, m5C methylation has been demonstrated to affect the activation of innate immune pathways including TLR, cGAS-STING, and RIG-I pathways by modulating RNA function, unveiling new mechanisms underlying the regulation of innate immune responses by tumor cells. However, research on m5C methylation and its interplay with innate immune pathways is still in its infancy. Therefore, this review details the biological significance of RNA m5C methylation in HCC and discusses its potential regulatory relationship with TLR, cGAS-STING, and RIG-I pathways, thereby providing fresh insights into the role of RNA methylation in the innate immune mechanisms and treatment of HCC.

The functions and mechanisms of RNA modification in prostate: Current status and future perspectives

The increasing incidence and mortality of prostate cancer worldwide significantly impact the life span of male patients, emphasizing the urgency of understanding its pathogenic mechanism and associated molecular changes that regulate tumor progression for effective prevention and treatment. RNA modification, an important post-transcriptional regulatory process, profoundly influences tumor cell growth and metabolism, shaping cell fate. Over 170 RNA modification methods are known, with prominent research focusing on N6-methyladenosine, N7-methylguanosine, N1-methyladenosine, 5-methylcytidine, pseudouridine, and N4-acetylcytidine modifications. These alterations intricately regulate coding and non-coding RNA post-transcriptionally, affecting the stability of RNA and protein expression levels. This article delves into the latest advancements and challenges associated with various RNA modifications in prostate cancer tumor cells, tumor microenvironment, and core signaling molecule androgen receptors. It aims to provide new research targets and avenues for molecular diagnosis, treatment strategies, and improvement of the prognosis in prostate cancer.

Integrating single-cell and multi-omic approaches reveals Euphorbiae Humifusae Herba-dependent mitochondrial dysfunction in non-small-cell lung cancer

Euphorbiae Humifusae Herba (EHH) is a pivotal therapeutic agent with diverse pharmacological effects. However, a substantial gap exists in understanding its pharmacological properties and anti-tumour mechanisms. This study aimed to address this gap by exploring EHH's pharmacological properties, identifying NSCLC therapy-associated protein targets, and elucidating how EHH induces mitochondrial disruption in NSCLC cells, offering insights into novel NSCLC treatment strategies. String database was utilized to explore protein-protein interactions. Subsequently, single-cell analysis and multi-omics further unveiled the impact of EHH-targeted genes on the immune microenvironment of NSCLC, as well as their influence on immunotherapeutic responses. Finally, both in vivo and in vitro experiments elucidated the anti-tumour mechanisms of EHH, specifically through the assessment of mitochondrial ROS levels and alterations in mitochondrial membrane potential. EHH exerts its influence through engagement with a cluster of 10 genes, including the apoptotic gene CASP3. This regulatory impact on the immune milieu within NSCLC holds promise as an indicator for predicting responses to immunotherapy. Besides, EHH demonstrated the capability to induce mitochondrial ROS generation and perturbations in mitochondrial membrane potential in NSCLC cells, ultimately leading to mitochondrial dysfunction and consequent apoptosis of tumour cells. EHH induces mitochondrial disruption in NSCLC cells, leading to cell apoptosis to inhibit the progress of NSCLC.

NSUN2 promotes lung adenocarcinoma progression through stabilizing PIK3R2 mRNA in an m5C-dependent manner

It is well known that 5-methylcytosine (m5C) is involved in variety of crucial biological processes in cancers. However, its biological roles in lung adenocarcinoma (LAUD) remain to be determined. The LUAD samples were used to assess the clinical value of NOP2/Sun RNA Methyltransferase 2 (NSUN2). Dot blot was used to determine global m5C levels. ChIP and dual-luciferase assays were performed to investigate the MYC-associated zinc finger protein (MAZ)-binding sites in NSUN2 promoter. RNA-seq was used to explore the downstream molecular mechanisms of NSUN2. Dual luciferase reporter assay, m5C-RIP-qPCR, and mRNA stability assay were conducted to explore the effect of NSUN2-depletion on target genes. Cell viability, transwell, and xenograft mouse model were designed to demonstrate the characteristic of NSUN2 in promoting LUAD progression. The m5C methyltransferase NSUN2 was highly expressed and caused elevated m5C methylation in LUAD samples. Mechanistically, MAZ positively regulated the transcription of NSUN2 and was related to poor survival of LUAD patients. Silencing NSUN2 decreased the global m5C levels, suppressed proliferation, migration and invasion, and inhibited activation of PI3K-AKT signaling in A549 and SPAC-1 cells. Phosphoinositide-3-Kinase Regulatory Subunit 2 (PIK3R2) was upregulated by NSUN2-mediated m5C methylation by enhancing its mRNA stabilization and activated the phosphorylation of the PI3K-AKT signaling. The present study explored the underlying mechanism and biological function of NSUN2-meditated m5C RNA methylation in LUAD. NSUN2 was discovered to facilitate the malignancy progression of LUAD through regulating m5C modifications to stabilize PIK3R2 activating the PI3K-AKT signaling, suggesting that NSUN2 could be a novel biomarker and promising therapeutic target for LUAD patients.

Roles of RNA m5C modification patterns in prognosis and tumor microenvironment infiltration of diffuse large B-cell lymphoma

Genetic and epigenetic aberrations display an essential role in the initiation and progression of diffuse large B-cell lymphoma (DLBCL). 5-methylcytosine (m5C), a common RNA modification, regulates various cellular processes and contributes to tumorigenesis and cancer progression. However, m5C alterations in DLBCL remain unclear. Our research constructed an m5C prognostic model utilizing GEO data sets, which can efficiently predict the prognosis of patients with DLBCL, and verified the m5C prognostic model genes by immunohistochemistry analysis. This model was constructed using unsupervised consensus clustering analyses, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Cox regression analyses. Based on the expression of m5C genes in the model, patients with DLBCL could be effectively divided into groups with significant survival time differences. The m5C risk-score signature demonstrated a highly significant independent prognostic value. Results from tumor microenvironment analyses revealed that m5C genes altered the infiltration of eosinophils, Tregs, and M2 macrophages. Additionally, they regulated T cell activation by modulating the expression of CTLA4, PDL1, B2M, CD8A, ICOS, and other relevant immune checkpoint expressions. In conclusion, our study presents a robust m5C prognostic model that effectively predicts prognosis in DLBCL. This model may offer a new approach for prognostic stratification and potential therapeutic interventions for patients with DLBCL.

KHDRBS1 as a novel prognostic signaling biomarker influencing hepatocellular carcinoma cell proliferation, migration, immune microenvironment, and drug sensitivity

Background

Human tumors pose significant challenges, with targeted therapy against specific molecular targets or signaling pathways being a mainstay alongside surgical resection. Previous studies have implicated KHDRBS1 in the oncogenesis of certain human tumors such as colorectal and prostate cancers, underscoring its potential as a therapeutic target. However, the comprehensive expression pattern of KHDRBS1 in hepatocellular carcinoma (HCC) warrants further exploration.

Methods

Integrating and analyzing multi-omics, multi-cohort data from public databases, coupled with clinical samples and molecular biology validation, we elucidate the oncogenic role of KHDRBS1 in HCC progression. Additionally, leveraging HCC single-cell sequencing data, we segregate malignant cells into KHDRBS1-positive and negative subsets, uncovering significant differences in their expression profiles and functional roles.

Results

Our study identifies KHDRBS1 as a tumor-promoting factor in HCC, with its positivity correlating with tumor progression. Furthermore, we highlight the clinical significance of KHDRBS1-positive malignant cells, aiming to further propel its clinical utility.

Conclusion

KHDRBS1 plays a key role in HCC development. This study provides crucial insights for further investigation into KHDRBS1 as a therapeutic target in HCC.

Experimentally validated oxidative stress -associated prognostic signatures describe the immune landscape and predict the drug response and prognosis of SKCM

Background

Skin Cutaneous Melanoma (SKCM) incidence is continually increasing, with chemotherapy and immunotherapy being among the most common cancer treatment modalities. This study aims to identify novel biomarkers for chemotherapy and immunotherapy response in SKCM and explore their association with oxidative stress.

Methods

Utilizing TCGA-SKCM RNA-seq data, we employed Weighted Gene Co-expression Network Analysis (WGCNA) and Protein-Protein Interaction (PPI) networks to identify six core genes. Gene co-expression analysis and immune-related analysis were conducted, and specific markers associated with oxidative stress were identified using Gene Set Variation Analysis (GSVA). Single-cell analysis revealed the expression patterns of Oxidative Stress-Associated Genes (OSAG) in the tumor microenvironment. TIDE analysis was employed to explore the association between immune therapy response and OSAG, while CIBERSORT was used to analyze the tumor immune microenvironment. The BEST database demonstrated the impact of the Oxidative Stress signaling pathway on chemotherapy drug resistance. Immunohistochemical staining and ROC curve evaluation were performed to assess the protein expression levels of core genes in SKCM and normal samples, with survival analysis utilized to determine their diagnostic value.

Results

We identified six central genes associated with SKCM metastasis, among which the expression of DSC2 and DSC3 involved in the oxidative stress pathway was closely related to immune cell infiltration. DSC2 influenced drug resistance in SKMC patients. Furthermore, downregulation of DSC2 and DSC3 expression enhanced the response of SKCM patients to immunotherapy.

Conclusion

This study identified two Oxidative Stress-Associated genes as novel biomarkers for SKCM. Additionally, targeting the oxidative stress pathway may serve as a new strategy in clinical practice to enhance SKCM chemotherapy and sensitivity.

Eukaryotic initiation factor 3a promotes the development of diffuse large B-cell lymphoma through regulating cell proliferation

BACKGROUND

One-third of diffuse large B-cell lymphoma (DLBCL) patients suffer relapse after standard treatment. Eukaryotic initiation factor 3a (eIF3a) is a key player in the initial stage of translation, which has been widely reported to be correlated with tumorigenesis and therapeutic response. This study aimed to explore the biological role of eIF3a, evaluate its prognostic and therapeutic potential in DLBCL.

METHODS

RNA-seq datasets from GEO database were utilized to detect the expression and prognostic role of eIF3a in DLBCL patients. Protein level of eIF3a was estimated by western blot and immunohistochemical. Next, DLBCL cells were transfected with lentiviral vector either eIF3a-knockdown or empty to assess the biological role of eIF3a. Then, samples were divided into 2 clusters based on eIF3a expression and differentially expressed genes (DEGs) were identified. Function enrichment and mutation analysis of DEGs were employed to detect potential biological roles. Moreover, we also applied pan-cancer and chemosensitivity analysis for deep exploration.

RESULTS

eIF3a expression was found to be higher in DLBCL than healthy controls, which was associated with worse prognosis. The expression of eIF3a protein was significantly increased in DLBCL cell lines compared with peripheral blood mononuclear cells (PBMCs) from healthy donors. eIF3a knockdown inhibited the proliferation of DLBCL cells and the expression of proliferation-related proteins and increase cell apoptosis rate. Besides, 114 DEGs were identified which had a close linkage to cell cycle and tumor immune. eIF3a and DEGs mutations were found to be correlated to chemosensitivity and vital signal pathways. Pan-cancer analysis demonstrated that high eIF3a expression was associated with worse prognosis in several tumors. Moreover, eIF3a expression was found to be related to chemosensitivity of several anti-tumor drugs in DLBCL, including Vincristine and Wee1 inhibitor.

CONCLUSIONS

We firstly revealed the high expression and prognostic role of eIF3a in DLBCL, and eIF3a might promote the development of DLBCL through regulating cell proliferation and apoptosis. eIF3a expression was related to immune profile and chemosensitivity in DLBCL. These results suggest that eIF3a could serve as a potential prognostic biomarker and therapeutic target in DLBCL.

Clinical significance of RNA methylation in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a primary liver malignancy with high mortality rates and poor prognosis. Recent advances in high-throughput sequencing and bioinformatic technologies have greatly enhanced the understanding of the genetic and epigenetic changes in liver cancer. Among these changes, RNA methylation, the most prevalent internal RNA modification, has emerged as a significant contributor of the development and progression of HCC. Growing evidence has reported significantly abnormal levels of RNA methylation and dysregulation of RNA-methylation-related enzymes in HCC tissues and cell lines. These alterations in RNA methylation play a crucial role in the regulation of various genes and signaling pathways involved in HCC, thereby promoting tumor progression. Understanding the pathogenesis of RNA methylation in HCC would help in developing prognostic biomarkers and targeted therapies for HCC. Targeting RNA-methylation-related molecules has shown promising potential in the management of HCC, in terms of developing novel prognostic biomarkers and therapies for HCC. Exploring the clinical application of targeted RNA methylation may provide new insights and approaches for the management of HCC. Further research in this field is warranted to fully understand the functional roles and underlying mechanisms of RNA methylation in HCC. In this review, we described the multifaceted functional roles and potential mechanisms of RNA methylation in HCC. Moreover, the prospects of clinical application of targeted RNA methylation for HCC management are discussed, which may provide the basis for subsequent in-depth research on RNA methylation in HCC.

Hyperbaric Oxygen Boosts Antitumor Efficacy of Copper-Diethyldithiocarbamate Nanoparticles against Pancreatic Ductal Adenocarcinoma by Regulating Cancer Stem Cell Metabolism

Cuproptosis-based cancer nanomedicine has received widespread attention recently. However, cuproptosis nanomedicine against pancreatic ductal adenocarcinoma (PDAC) is severely limited by cancer stem cells (CSCs), which reside in the hypoxic stroma and adopt glycolysis metabolism accordingly to resist cuproptosis-induced mitochondria damage. Here, we leverage hyperbaric oxygen (HBO) to regulate CSC metabolism by overcoming tumor hypoxia and to augment CSC elimination efficacy of polydopamine and hydroxyethyl starch stabilized copper-diethyldithiocarbamate nanoparticles (CuET@PH NPs). Mechanistically, while HBO and CuET@PH NPs inhibit glycolysis and oxidative phosphorylation, respectively, the combination of HBO and CuET@PH NPs potently suppresses energy metabolism of CSCs, thereby achieving robust tumor inhibition of PDAC and elongating mice survival importantly. This study reveals novel insights into the effects of cuproptosis nanomedicine on PDAC CSC metabolism and suggests that the combination of HBO with cuproptosis nanomedicine holds significant clinical translation potential for PDAC patients.

Genome-wide functional integration identified MAZ-controlled RPS14 dysregulation in hepatocellular carcinoma

Chronic infection with Hepatitis B virus (HBV) significantly increases the risk of hepatocellular carcinoma (HCC), particularly in Eastern Asia. However, only a subset of individuals with chronic HBV infection develop HCC, suggesting the role for genetic factors in HCC etiology. Despite genome-wide association studies (GWASs) identifying multiple single nucleotide polymorphisms (SNPs) associated with HBV-related HCC susceptibility, the underlying mechanisms and causal genetic polymorphisms remain largely unclear. To address this, we developed The Updated Integrative Functional Genomics Approach (TUIFGA), an methodology that combines data from transcription factor (TF) cistromics, ATAC-seq, DNAase-seq, and the 1000 Genomes Project to identify cancer susceptibility SNPs within TF-binding sites across human genome. Using TUIFGA, we discovered SNP rs13170300 which located in the TF MAZ binding motif of RPS14. The RPS14 rs13170300 was significantly associated with HCC risk in two case-control sets, with the T allele as the protective allele (Shandong discovery set: TT OR = 0.60, 95% CI = 0.49-0.74, P = 1.0 × 10-6; CT OR = 0.69, 95% CI = 0.55-0.86, P = 0.001; Jiangsu validation set: TT OR = 0.70, 95% CI = 0.56-0.87, P = 0.001; CT OR = 0.65, 95% CI = 0.53-0.82, P = 1.6 × 10-4). SNP rs13170300 affected MAZ binding in the RPS14 promoter, resulting in allele-specific changes in gene expression. RPS14 functions as a novel oncogene in HCC, specifically via activating the AKT signaling. Our findings present important insights into the functional genetics underlying HBV-related HCC development and may contribute to personalized approaches for cancer prevention and novel therapeutics.

Glycogen metabolism-mediated intercellular communication in the tumor microenvironment influences liver cancer prognosis

Glycogen metabolism plays a key role in the development of hepatocellular carcinoma (HCC), but the function of glycogen metabolism genes in the tumor microenvironment (TME) is still to be elucidated. Single-cell RNA-seq data were obtained from ten HCC tumor samples totaling 64,545 cells, and 65 glycogen metabolism genes were analyzed by a nonnegative matrix factorization (NMF). The prognosis and immune response of new glycogen TME cell clusters were predicted by using HCC and immunotherapy cohorts from public databases. HCC single-cell analysis was divided into fibroblasts, NT T cells, macrophages, endothelial cells, and B cells, which were separately divided into new cell clusters by glycogen metabolism gene annotation. Pseudo-temporal trajectory analysis demonstrated the temporal differentiation trajectory of different glycogen subtype cell clusters. Cellular communication analysis revealed extensive interactions between endothelial cells with glycogen metabolizing TME cell-related subtypes and different glycogen subtype cell clusters. SCENIC analysis of transcription factors upstream of TME cell clusters with different glycogen metabolism. In addition, TME cell clusters of glycogen metabolism were found to be enriched in expression in CAF subtypes, CD8 depleted, M1, and M2 types. Bulk-seq analysis showed the prognostic significance of glycogen metabolism-mediated TME cell clusters in HCC, while a significant immune response was found in the immunotherapy cohort in patients treated with immune checkpoint blockade (ICB), especially for CAFs, T cells, and macrophages. In summary, our study reveals for the first time that glycogen metabolism mediates intercellular communication in the hepatocellular carcinoma microenvironment while elucidating the anti-tumor mechanisms and immune prognostic responses of different subtypes of cell clusters.

Characterization of the m6A/m1A/m5C/m7G-related regulators on the prognosis and immune microenvironment of glioma by integrated analysis of scRNA-seq and bulk RNA-seq data

BACKGROUND

Proliferation, metabolism, tumor occurrence and development in gliomas are greatly influenced by RNA modifications. However, no research has integrated the four RNA methylation regulators of m6A, m1A, m5C and m7G in gliomas to analyze their relationship with glioma prognosis and intratumoral heterogeneity.

METHODS

Based on three in-house single-cell RNA-sequencing (scRNA-seq) data, the glioma heterogeneity and characteristics of m6A/m1A/m5C/m7G-related regulators were elucidated. Based on publicly available bulk RNA-sequencing (RNA-seq) data, a risk-score system for predicting the overall survival (OS) for gliomas was established by three machine learning methods and multivariate Cox regression analysis, and validated in an independent cohort.

RESULTS

Seven cell types were identified in gliomas by three scRNA-seq data, and 22 m6A/m1A/m5C/m7G-related regulators among the marker genes of different cell subtypes were discovered. Three m6A/m1A/m5C/m7G-related regulators were selected to construct prognostic risk-score model, including EIFA, NSUN6 and TET1. The high-risk patients showed higher immune checkpoint expression, higher tumor microenvironment scores, as well as higher tumor mutation burden and poorer prognosis compared with low-risk patients. Additionally, the area under the curve values of the risk score and nomogram were 0.833 and 0.922 for 3 year survival and 0.759 and 0.885 for 5 year survival for gliomas. EIF3A was significantly highly expressed in glioma tissues in our in-house RNA-sequencing data (p < 0.05).

CONCLUSION

These findings may contribute to further understanding of the role of m6A/m1A/m5C/m7G-related regulators in gliomas, and provide novel and reliable biomarkers for gliomas prognosis and treatment.

Comprehending the cuproptosis and cancer-immunity cycle network: delving into the immune landscape and its predictive role in breast cancer immunotherapy responses and clinical endpoints

Background

The role of cuproptosis, a phenomenon associated with tumor metabolism and immunological identification, remains underexplored, particularly in relation to the cancer-immunity cycle (CIC) network. This study aims to rigorously examine the impact of the cuproptosis-CIC nexus on immune reactions and prognostic outcomes in patients with breast cancer (BC), striving to establish a comprehensive prognostic model.

Methods

In the study, we segregated data obtained from TCGA, GEO, and ICGC using CICs retrieved from the TIP database. We constructed a genetic prognostic framework using the LASSO-Cox model, followed by its validation through Cox proportional hazards regression. This framework's validity was further confirmed with data from ICGC and GEO. Explorations of the tumor microenvironment were carried out through the application of ESTIMATE and CIBERSORT algorithms, as well as machine learning techniques, to identify potential treatment strategies. Single-cell sequencing methods were utilized to delineate the spatial distribution of key genes within the various cell types in the tumor milieu. To explore the critical role of the identified CICs, experiments were conducted focusing on cell survival and migration abilities.

Results

In our research, we identified a set of 4 crucial cuproptosis-CICs that have a profound impact on patient longevity and their response to immunotherapy. By leveraging these identified CICs, we constructed a predictive model that efficiently estimates patient prognoses. Detailed analyses at the single-cell level showed that the significance of CICs. Experimental approaches, including CCK-8, Transwell, and wound healing assays, revealed that the protein HSPA9 restricts the growth and movement of breast cancer cells. Furthermore, our studies using immunofluorescence techniques demonstrated that suppressing HSPA9 leads to a notable increase in ceramide levels.

Conclusion

This research outlines a network of cuproptosis-CICs and constructs a predictive nomogram. Our model holds great promise for healthcare professionals to personalize treatment approaches for individuals with breast cancer. The work provides insights into the complex relationship between the cuproptosis-CIC network and the cancer immune microenvironment, setting the stage for novel approaches to cancer immunotherapy. By focusing on the essential gene HSPA9 within the cancer-immunity cycle, this strategy has the potential to significantly improve the efficacy of treatments against breast cancer.

Machine learning-enhanced insights into sphingolipid-based prognostication: revealing the immunological landscape and predictive proficiency for immunomotherapy and chemotherapy responses in pancreatic carcinoma

Background: With a poor prognosis for affected individuals, pancreatic adenocarcinoma (PAAD) is known as a complicated and diverse illness. Immunocytes have become essential elements in the development of PAAD. Notably, sphingolipid metabolism has a dual function in the development of tumors and the invasion of the immune system. Despite these implications, research on the predictive ability of sphingolipid variables for PAAD prognosis is strikingly lacking, and it is yet unclear how they can affect PAAD immunotherapy and targeted pharmacotherapy. Methods: The investigation process included SPG detection while also being pertinent to the prognosis for PAAD. Both the analytical capability of CIBERSORT and the prognostic capability of the pRRophetic R package were used to evaluate the immunological environments of the various HCC subtypes. In addition, CCK-8 experiments on PAAD cell lines were carried out to confirm the accuracy of drug sensitivity estimates. The results of these trials, which also evaluated cell survival and migratory patterns, confirmed the usefulness of sphingolipid-associated genes (SPGs). Results: As a result of this thorough investigation, 32 SPGs were identified, each of which had a measurable influence on the dynamics of overall survival. This collection of genes served as the conceptual framework for the development of a prognostic model, which was carefully assembled from 10 chosen genes. It should be noted that this grouping of patients into cohorts with high and low risk was a sign of different immune profiles and therapy responses. The increased abundance of SPGs was identified as a possible sign of inadequate responses to immune-based treatment approaches. The careful CCK-8 testing carried out on PAAD cell lines was of the highest importance for providing clear confirmation of drug sensitivity estimates. Conclusion: The significance of Sphingolipid metabolism in the complex web of PAAD development is brought home by this study. The novel risk model, built on the complexity of sphingolipid-associated genes, advances our understanding of PAAD and offers doctors a powerful tool for developing personalised treatment plans that are specifically suited to the unique characteristics of each patient.

Molecular characterization of cancer-intrinsic immune evasion genes indicates prognosis and tumour microenvironment infiltration in osteosarcoma

Cancer-intrinsic immune evasion (IE) to cells is a critical factor in tumour growth and progression, yet the molecular characterization of IE genes (IEGs) in osteosarcoma remains underexplored. In this study, 85 osteosarcoma patients were comprehensively analyzed based on 182 IEGs, leading to the identification of two IE clusters linked to distinct biological processes and clinical outcomes. In addition, two IE clusters demonstrated diverse immune cell infiltration patterns, with IEGcluster A displaying increased levels compared to IEGcluster B. Moreover, an IE score was identified as an independent prognostic factor and nomogram may serve as a practical tool for the individual prognostic evaluation of patients with osteosarcoma. Finally, GBP1, a potential biomarker with high expression in osteosarcoma was identified. The findings of this study highlight the presence of two IE clusters, each associated with differing patient outcomes and immune infiltration properties. The IE score may serve to assess individual patient IE characteristics, enhance comprehension of immune features, and guide more efficacious treatment approaches.

Uncovering the immune microenvironment and molecular subtypes of hepatitis B-related liver cirrhosis and developing stable a diagnostic differential model by machine learning and artificial neural networks

Background: Hepatitis B-related liver cirrhosis (HBV-LC) is a common clinical disease that evolves from chronic hepatitis B (CHB). The development of cirrhosis can be suppressed by pharmacological treatment. When CHB progresses to HBV-LC, the patient's quality of life decreases dramatically and drug therapy is ineffective. Liver transplantation is the most effective treatment, but the lack of donor required for transplantation, the high cost of the procedure and post-transplant rejection make this method unsuitable for most patients. Methods: The aim of this study was to find potential diagnostic biomarkers associated with HBV-LC by bioinformatics analysis and to classify HBV-LC into specific subtypes by consensus clustering. This will provide a new perspective for early diagnosis, clinical treatment and prevention of HCC in HBV-LC patients. Two study-relevant datasets, GSE114783 and GSE84044, were retrieved from the GEO database. We screened HBV-LC for feature genes using differential analysis, weighted gene co-expression network analysis (WGCNA), and three machine learning algorithms including least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF) for a total of five methods. After that, we constructed an artificial neural network (ANN) model. A cohort consisting of GSE123932, GSE121248 and GSE119322 was used for external validation. To better predict the risk of HBV-LC development, we also built a nomogram model. And multiple enrichment analyses of genes and samples were performed to understand the biological processes in which they were significantly enriched. And the different subtypes of HBV-LC were analyzed using the Immune infiltration approach. Results: Using the data downloaded from GEO, we developed an ANN model and nomogram based on six feature genes. And consensus clustering of HBV-LC classified them into two subtypes, C1 and C2, and it was hypothesized that patients with subtype C2 might have milder clinical symptoms by immune infiltration analysis. Conclusion: The ANN model and column line graphs constructed with six feature genes showed excellent predictive power, providing a new perspective for early diagnosis and possible treatment of HBV-LC. The delineation of HBV-LC subtypes will facilitate the development of future clinical treatment of HBV-LC.

Unveiling the role of regulatory T cells in the tumor microenvironment of pancreatic cancer through single-cell transcriptomics and in vitro experiments

Background

In order to investigate the impact of Treg cell infiltration on the immune response against pancreatic cancer within the tumor microenvironment (TME), and identify crucial mRNA markers associated with Treg cells in pancreatic cancer, our study aims to delve into the role of Treg cells in the anti-tumor immune response of pancreatic cancer.

Methods

The ordinary transcriptome data for this study was sourced from the GEO and TCGA databases. It was analyzed using single-cell sequencing analysis and machine learning. To assess the infiltration level of Treg cells in pancreatic cancer tissues, we employed the CIBERSORT method. The identification of genes most closely associated with Treg cells was accomplished through the implementation of weighted gene co-expression network analysis (WGCNA). Our analysis of single-cell sequencing data involved various quality control methods, followed by annotation and advanced analyses such as cell trajectory analysis and cell communication analysis to elucidate the role of Treg cells within the pancreatic cancer microenvironment. Additionally, we categorized the Treg cells into two subsets: Treg1 associated with favorable prognosis, and Treg2 associated with poor prognosis, based on the enrichment scores of the key genes. Employing the hdWGCNA method, we analyzed these two subsets to identify the critical signaling pathways governing their mutual transformation. Finally, we conducted PCR and immunofluorescence staining in vitro to validate the identified key genes.

Results

Based on the results of immune infiltration analysis, we observed significant infiltration of Treg cells in the pancreatic cancer microenvironment. Subsequently, utilizing the WGCNA and machine learning algorithms, we ultimately identified four Treg cell-related genes (TRGs), among which four genes exhibited significant correlations with the occurrence and progression of pancreatic cancer. Among them, CASP4, TOB1, and CLEC2B were associated with poorer prognosis in pancreatic cancer patients, while FYN showed a correlation with better prognosis. Notably, significant differences were found in the HIF-1 signaling pathway between Treg1 and Treg2 cells identified by the four genes. These conclusions were further validated through in vitro experiments.

Conclusion

Treg cells played a crucial role in the pancreatic cancer microenvironment, and their presence held a dual significance. Recognizing this characteristic was vital for understanding the limitations of Treg cell-targeted therapies. CASP4, FYN, TOB1, and CLEC2B exhibited close associations with infiltrating Treg cells in pancreatic cancer, suggesting their involvement in Treg cell functions. Further investigation was warranted to uncover the mechanisms underlying these associations. Notably, the HIF-1 signaling pathway emerged as a significant pathway contributing to the duality of Treg cells. Targeting this pathway could potentially revolutionize the existing treatment approaches for pancreatic cancer.

Revealing the role of regulatory T cells in the tumor microenvironment of lung adenocarcinoma: a novel prognostic and immunotherapeutic signature

Background

Regulatory T cells (Tregs), are a key class of cell types in the immune system. In the tumor microenvironment (TME), the presence of Tregs has important implications for immune response and tumor development. Relatively little is known about the role of Tregs in lung adenocarcinoma (LUAD).

Methods

Tregs were identified using but single-cell RNA sequencing (scRNA-seq) analysis and interactions between Tregs and other cells in the TME were investigated. Next, we used multiple bulk RNA-seq datasets to construct risk models based on marker genes of Tregs and explored differences in prognosis, mutational landscape, immune cell infiltration and immunotherapy between high- and low-risk groups, and finally, qRT-PCR and cell function experiments were performed to validate the model genes.

Results

The cellchat analysis showed that MIF-(CD74+CXCR4) pairs play a key role in the interaction of Tregs with other cell subpopulations, and the Tregs-associated signatures (TRAS) could well classify multiple LUAD cohorts into high- and low-risk groups. Immunotherapy may offer greater potential benefits to the low-risk group, as indicated by their superior survival, increased infiltration of immune cells, and heightened expression of immune checkpoints. Finally, the experiment verified that the model genes LTB and PTTG1 were relatively highly expressed in cancer tissues, while PTPRC was relatively highly expressed in paracancerous tissues. Colony Formation assay confirmed that knockdown of PTTG1 reduced the proliferation ability of LUAD cells.

Conclusion

TRAS were constructed using scRNA-seq and bulk RNA-seq to distinguish patient risk subgroups, which may provide assistance in the clinical management of LUAD patients.

The combined signatures of telomere and immune cell landscape provide a prognostic and therapeutic biomarker in glioma

Background

Gliomas, the most prevalent primary malignant tumors of the central nervous system in adults, exhibit slow growth in lower-grade gliomas (LGG). However, the majority of LGG cases progress to high-grade gliomas, posing challenges for prognostication. The tumor microenvironment (TME), characterized by telomere-related genes and immune cell infiltration, strongly influences glioma growth and therapeutic response. Therefore, our objective was to develop a Telomere-TME (TM-TME) classifier that integrates telomere-related genes and immune cell landscape to assess prognosis and therapeutic response in glioma.

Methods

This study encompassed LGG patients from the TCGA and CCGA databases. TM score and TME score were derived from the expression signatures of telomere-related genes and the presence of immune cells in LGG, respectively. The TM-TME classifier was established by combining TM and TME scores to effectively predict prognosis. Subsequently, we conducted Kaplan-Meier survival estimation, univariate Cox regression analysis, and receiver operating characteristic curves to validate the prognostic prediction capacity of the TM-TME classifier across multiple cohorts. Gene Ontology (GO) analysis, biological processes, and proteomaps were performed to annotate the functional aspects of each subgroup and visualize the cellular signaling pathways.

Results

The TM_low+TME_high subgroup exhibited superior prognosis and therapeutic response compared to other subgroups (P<0.001). This finding could be attributed to distinct tumor somatic mutations and cancer cellular signaling pathways. GO analysis indicated that the TM_low+TME_high subgroup is associated with the neuronal system and modulation of chemical synaptic transmission. Conversely, the TM_high+TME_low subgroup showed a strong association with cell cycle and DNA metabolic processes. Furthermore, the classifier significantly differentiated overall survival in the TCGA LGG cohort and served as an independent prognostic factor for LGG patients in both the TCGA cohort (P<0.001) and the CGGA cohort (P<0.001).

Conclusion

Overall, our findings underscore the significance of the TM-TME classifier in predicting prognosis and immune therapeutic response in glioma, shedding light on the complex immune landscape within each subgroup. Additionally, our results suggest the potential of integrating risk stratification with precision therapy for LGG.

GADD45B regulates the carcinogenesis process of chronic atrophic gastritis and the metabolic pathways of gastric cancer

Background

Gastric cancer continues to be a significant global healthcare challenge, and its burden remains substantial. The development of gastric cancer (GC) is closely linked to chronic atrophic gastritis (CAG), yet there is a scarcity of research exploring the underlying mechanisms of CAG-induced carcinogenesis.

Methods

In this study, we conducted a comprehensive investigation into the oncogenes involved in CAG using both bulk transcriptome and single-cell transcriptome data. Our approach employed hdWGCNA to identify pathogenic genes specific to CAG, with non-atrophic gastritis (NAG) serving as the control group. Additionally, we compared CAG with GC, using normal gastric tissue as the control group in the single-cell transcriptome analysis. By intersecting the identified pathogenic genes, we pinpointed key network molecules through protein interaction network analysis. To further refine the gene selection, we applied LASSO, SVM-RFE, and RF techniques, which resulted in a set of cancer-related genes (CRGs) associated with CAG. To identify CRGs potentially linked to gastric cancer progression, we performed a univariate COX regression analysis on the gene set. Subsequently, we explored the relationship between CRGs and immune infiltration, drug sensitivity, and clinical characteristics in gastric cancer patients. We employed GSVA to investigate how CRGs regulated signaling pathways in gastric cancer cells, while an analysis of cell communication shed light on the impact of CRGs on signal transmission within the gastric cancer tumor microenvironment. Lastly, we analyzed changes in metabolic pathways throughout the progression of gastric cancer.

Results

Using hdWGCNA, we have identified a total of 143 pathogenic genes that were shared by CAG and GC. To further investigate the underlying mechanisms, we conducted protein interaction network analysis and employed machine learning screening techniques. As a result, we have identified 15 oncogenes that are specifically associated with chronic atrophic gastritis. By performing ROC reanalysis and prognostic analysis, we have determined that GADD45B is the most significant gene involved in the carcinogenesis of CAG. Immunohistochemical staining and differential analysis have revealed that GADD45B expression was low in GC tissues while high in normal gastric tissues. Moreover, based on prognostic analysis, high expression of GADD45B has been correlated with poor prognosis in GC patients. Additionally, an analysis of immune infiltration has shown a relationship between GADD45B and the infiltration of various immune cells. By correlating GADD45B with clinical characteristics, we have found that it primarily affects the depth of invasion in GC. Through cell communication analysis, we have discovered that the CD99 signaling pathway network and the CDH signaling pathway network are the main communication pathways that significantly alter the microenvironment of gastric tissue during the development of chronic atrophic gastritis. Specifically, GADD45B-low GC cells were predominantly involved in the network communication of the CDH signaling pathway, while GADD45B-high GC cells played a crucial role in both signaling pathways. Furthermore, we have identified several metabolic pathways, including D-Glutamine and D-glutamate metabolism and N-Glycan biosynthesis, among others, that played important roles in the occurrence and progression of GC, in addition to the six other metabolic pathways. In summary, our study highlighted the discovery of 143 pathogenic genes shared by CAG and GC, with a specific focus on 15 oncogenes associated with CAG. We have identified GADD45B as the most important gene in the carcinogenesis of CAG, which exhibited differential expression in GC tissues compared to normal gastric tissues. Moreover, GADD45B expression was correlated with patient prognosis and is associated with immune cell infiltration. Our findings also emphasized the impact of the CD99 and CDH signaling pathway networks on the microenvironment of gastric tissue during the development of CAG. Additionally, we have identified key metabolic pathways involved in GC progression.

Conclusion

GADD45B, an oncogene implicated in chronic atrophic gastritis, played a critical role in GC development. Decreased expression of GADD45B was associated with the onset of GC. Moreover, GADD45B expression levels were closely tied to poor prognosis in GC patients, influencing the infiltration patterns of various cells within the tumor microenvironment, as well as impacting the metabolic pathways involved in GC progression.

Unveiling efferocytosis-related signatures through the integration of single-cell analysis and machine learning: a predictive framework for prognosis and immunotherapy response in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) represents a prominent gastrointestinal malignancy with a grim clinical outlook. In this regard, the discovery of novel early biomarkers holds substantial promise for ameliorating HCC-associated mortality. Efferocytosis, a vital immunological process, assumes a central position in the elimination of apoptotic cells. However, comprehensive investigations exploring the role of efferocytosis-related genes (EFRGs) in HCC are sparse, and their regulatory influence on HCC immunotherapy and targeted drug interventions remain poorly understood.

Methods

RNA sequencing data and clinical characteristics of HCC patients were acquired from the TCGA database. To identify prognostically significant genes in HCC, we performed the limma package and conducted univariate Cox regression analysis. Subsequently, machine learning algorithms were employed to identify hub genes. To assess the immunological landscape of different HCC subtypes, we employed the CIBERSORT algorithm. Furthermore, single-cell RNA sequencing (scRNA-seq) was utilized to investigate the expression levels of ERFGs in immune cells and to explore intercellular communication within HCC tissues. The migratory capacity of HCC cells was evaluated using CCK-8 assays, while drug sensitivity prediction reliability was determined through wound-healing assays.

Results

We have successfully identified a set of nine genes, termed EFRGs, that hold significant potential for the establishment of a hepatocellular carcinoma-specific prognostic model. Furthermore, leveraging the individual risk scores derived from this model, we were able to stratify patients into two distinct risk groups, unveiling notable disparities in terms of immune infiltration patterns and response to immunotherapy. Notably, the model's capacity to accurately predict drug responses was substantiated through comprehensive experimental investigations, encompassing wound-healing assay, and CCK8 experiments conducted on the HepG2 and Huh7 cell lines.

Conclusions

We constructed an EFRGs model that serves as valuable tools for prognostic assessment and decision-making support in the context of immunotherapy and chemotherapy.