Significance In Hepatocellular Carcinoma Research Articles

Corrigendum: Integrated analysis of single-cell and bulk RNA sequencing data reveals a cellular senescence-related signature in hepatocellular carcinoma

Corrigendum: Integrated analysis of single-cell and bulk RNA sequencing data reveals a cellular senescence-related signature in hepatocellular carcinoma

Targeted Drug Screening Leveraging Senescence-Induced T-Cell Exhaustion Signatures in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the sixth most prevalent cancer and a leading cause of cancer-related mortality globally, with most patients diagnosed at advanced stages and facing limited early treatment options. This study aimed to identify characteristic genes associated with T-cell exhaustion due to senescence in hepatocellular carcinoma patients, elucidating the interplay between senescence and T-cell exhaustion. We constructed prognostic models based on five signature genes (ENO1, STMN1, PRDX1, RAN, and RANBP1) linked to T-cell exhaustion, utilizing elastic net regression. The findings indicate that increased expression of ENO1 in T cells may contribute to T-cell exhaustion and Treg infiltration in hepatocellular carcinoma. Furthermore, molecular docking was employed to screen small molecule compounds that target the anti-tumor effects of these exhaustion-related genes. This study provides crucial insights into the diagnosis and treatment of hepatocellular carcinoma, establishing a strong foundation for the development of predictive biomarkers and therapeutic targets for affected patients.

Reply: Correspondence: "Transcriptomic signature in hepatocellular carcinoma to predict immunotherapy response."

Reply: Correspondence: "Transcriptomic signature in hepatocellular carcinoma to predict immunotherapy response."

The Prognostic Significance of CTSV Expression in Patients with Hepatocellular Carcinoma.

Cathepsin V (CTSV) is a cysteine protease peptidase, which is typically upregulated in cancer and is associated with various oncogenic processes, such as angiogenesis, proliferation, apoptosis, and invasion. The study explored the role of CTSV in hepatocellular carcinoma (HCC) and its potential as a potential biomarker. This study collected tumor and peritumoral archived specimens from 180HCC patients who underwent surgical resection at Zhongshan Hospital, Fudan University (Shanghai, China) between 2009 and 2010. We extracted data from the TCGA and GEO databases and conducted differential expression analysis, univariate Cox regression, and Kaplan-Meier analysis. Ultimately, we determined that CTSV may emerge as a potential biomarker. Then, immunohistochemical staining for CTSV was performed on tumors and adjacent tissues of HCC patients, and a Cox proportional hazards model was constructed to evaluate the prognostic significance of CTSV expression levels. Applied functional enrichment analysis to reveal the underlying molecular mechanisms. Utilized ssGSEA enrichment analysis and TIMER2.0 algorithm to explore the correlation between CTSV expression and immune cells in HCC. In vitro and in vivo experiments were conducted using human liver cancer cell lines to further validate the clinical application value of CTSV. In this study, we observed that CTSV expression was notably elevated in HCC (P < 0.001), and identified a significant association between elevated CTSV expression and reduced overall survival rates in patients. In vitro and in vivo experiments indicated that CTSV knockdown could significantly inhibit the proliferation, migration, and invasion of liver cancer cells, and it was found that the combination of CTSV knockdown with PD-1 inhibitors might enhance the therapeutic effect of PD-1 inhibitors in HCC. CTSV serves as a standalone negative prognostic indicator and possesses clinical significance in HCC.

Low serum creatine kinase level is associated with poor prognosis in patients with hepatocellular carcinoma: A retrospective single‑center study.

Previous studies have reported low serum creatine kinase (s-CK) levels as a poor prognostic factor in various cancers. However, there have been no reports on its significance in hepatocellular carcinoma. The present study aimed to evaluate the association of the preoperative s-CK levels with clinicopathologic features and their prognostic impact on survival in patients with hepatocellular carcinoma. This retrospective study included 163 patients with hepatocellular carcinoma (127 male and 36 female patients; median age, 69 years) who underwent radical liver resection between January 2004 and December 2021. A cutoff preoperative s-CK level of 91 U/l determined by receiver operating characteristic curve analysis was used to evaluate the significance of s-CK in predicting overall and recurrence-free survival. In addition, the prognostic impact of s-CK was evaluated using univariate and multivariate analysis. s-CK level was not associated with clinicopathologic factors. Overall survival and recurrence-free survival of the low s-CK group were significantly worse compared with the high s-CK group (P=0.043 and P=0.029, respectively). By multivariate analysis, low s-CK was an independent risk factor for poor overall survival and recurrence-free survival (P=0.019 and P=0.014, respectively). This trend was the same for male patients, but no significant difference was observed for female patients. Low preoperative s-CK level might be a poor prognostic biomarker in patients with hepatocellular carcinoma.

Natural killer (NK) cells-related gene signature reveals the immune environment heterogeneity in hepatocellular carcinoma based on single cell analysis

The early diagnosis of liver cancer is crucial for the treatment and depends on the coordinated use of several test procedures. Early diagnosis is crucial for precision therapy in the treatment of the hepatocellular carcinoma (HCC). Therefore, in this study, the NK cell-related gene prediction model was used to provide the basis for precision therapy at the gene level and a novel basis for the treatment of patients with liver cancer. Natural killer (NK) cells have innate abilities to recognize and destroy tumor cells and thus play a crucial function as the “innate counterpart” of cytotoxic T cells. The natural killer (NK) cells is well recognized as a prospective approach for tumor immunotherapy in treating patients with HCC. In this research, we used publicly available databases to collect bioinformatics data of scRNA-seq and RNA-seq from HCC patients. To determine the NK cell-related genes (NKRGs)-based risk profile for HCC, we isolated T and natural killer (NK) cells and subjected them to analysis. Uniform Manifold Approximation and Projection plots were created to show the degree of expression of each marker gene and the distribution of distinct clusters. The connection between the immunotherapy response and the NKRGs-based signature was further analyzed, and the NKRGs-based signature was established. Eventually, a nomogram was developed using the model and clinical features to precisely predict the likelihood of survival. The prognosis of HCC can be accurately predicted using the NKRGs-based prognostic signature, and thorough characterization of the NKRGs signature of HCC may help to interpret the response of HCC to immunotherapy and propose a novel tumor treatment perspective.

Construction and validation of a prognostic and therapeutic cuproptosis- and immune-related gene signature in hepatocellular carcinoma.

Abnormal accumulation of copper could induce cell death and tumor growth, and affect tumor immune escape by regulating programmed cell death ligand 1 (PD-L1) expression. This study aims to establish and verify a risk signature based on cuproptosis- and immune-related genes (CIRGs) for hepatocellular carcinoma (HCC) management. HCC RNA-seq and clinical data were obtained from open databases. Least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were utilized to screen CIRGs and develop a risk signature. The signature's value for clinical applications, functional enrichment, tumor mutation burden (TMB), and immune profile analyses were investigated systematically. A risk signature was developed utilizing seven CIRGs, and it performed well in predicting the prognosis of HCC patients in both the training and external validation cohorts. The model's risk score was discovered to be related to important clinical features. Top 15 mutated genes in HCC were significantly different among different risk groups. High-risk patients showed higher TMB, and high TMB was closely identified with a poorer prognosis. Immune profile analyses showed that immune infiltration level was higher in low-risk patients than high-risk patients, and the level of immune checkpoint genes expression varied significantly between patients in two different risk groups. Low-risk patients responded well to immunotherapy treatment, whereas high-risk patients were more sensitive to sorafenib, doxorubicin, gemcitabine and AKT (also known as protein kinase B) inhibitors. The established risk signature based on CIRGs can not only well predict the prognosis of HCC patients but is also promising in evaluating TMB and treatment response to immunotherapy, targeted therapy and chemotherapy, which has the potential to assist in the clinical management of HCC.

Integrated analysis of single-cell and bulk RNA sequencing data reveals a cellular senescence-related signature in hepatocellular carcinoma.

The mortality of hepatocellular carcinoma (HCC) is on the rise globally, particularly in the Western world, with etiology gradually shifting from virus-related liver diseases to metabolic disorders such as non-alcoholic fatty liver disease. Early detection of HCC is challenging, and effective prognostic indicators are currently lacking, urgently necessitating reliable markers to assist in treatment planning and clinical management. Here, we introduce hepatocellular carcinoma senescence genes (HSG) to assess cellular senescence in HCC and devise a hepatocellular carcinoma senescence score (HSS) for prognostic prediction. Higher HSS levels signify poorer prognosis and increased tumor proliferation activity. Additionally, we observe alterations in the tumor immune microenvironment with higher HSS levels, such as increased infiltration of Treg, potentially providing a basis for immunotherapy. Furthermore, we identify key genes, such as PTTG1, within the senescence gene set and demonstrate their regulatory roles in HCC cells and Treg through experimentation. In summary, we establish a scoring system based on hepatocellular carcinoma senescence genes for prognostic prediction in HCC, potentially offering guidance for clinical treatment planning.

FRI-493 CLEC14A regulates neutrophil recruitment across liverendothelial cells and correlates with a neutrophil signature in hepatocellular carcinoma

FRI-493 CLEC14A regulates neutrophil recruitment across liverendothelial cells and correlates with a neutrophil signature in hepatocellular carcinoma

Correspondence to editorial on "Multiomics profiling of buffy coat and plasma unveils etiology-specific signatures in hepatocellular carcinoma".

Correspondence to editorial on "Multiomics profiling of buffy coat and plasma unveils etiology-specific signatures in hepatocellular carcinoma".

Identification of a novel matrix metalloproteinases-related prognostic signature in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer worldwide. Cancer cells' local infiltration, proliferation, and spread are mainly influenced by the protein hydrolyzing function of different matrix metalloproteinases (MMPs). However, no study has determined the relationship between MMPs and prognostic prediction in HCC. Expression profiles of mRNA and MMPs-related genes were obtained from publicly available databases. Cox regression and LASSO Cox regression analysis were used to identify and predict MMPs-related prognostic signature and construct predictive models for overall survival (OS). A nomogram was used to validate the accuracy of the prediction model. Drug prediction was performed using the Genomics of Drug Sensitivity in Cancer (GDSC) dataset, and single-cell clustering analysis was performed to further understand the significance of the MMPs-related signature. A MMPs-related prognostic signature (including RNPEPL1, ADAM15, ADAM18, ADAMTS5, CAD, YME1L1, AMZ2, PSMD14, and COPS6) was identified. Using the median value, HCC patients in the high-risk group showed worse OS than those in the low-risk group. Immune microenvironment analysis showed that patients in the high-risk group had higher levels of M0 and M2 macrophages. Drug sensitivity analysis revealed that the IC50 values of sorafenib, cisplatin, and cytarabine were higher in the high-risk group. Finally, the single-cell cluster analysis results showed that YME1L1 and COPS6 were the major genes expressed in the monocyte cluster. A novel MMPs-related signature can be used to predict the prognosis of HCC. The findings of this research could potentially impact the predictability of the prognosis and treatment of HCC.

Integration of Single-Cell RNA Sequencing and Bulk RNA Sequencing to Identify an Immunogenic Cell Death-Related 5-Gene Prognostic Signature in Hepatocellular Carcinoma.

Immunogenic cell death (ICD) can enhance the potency of immunotherapy in cancer treatment. Nevertheless, it is ambiguous how ICD-related genes (ICDRGs) contribute to hepatocellular carcinoma (HCC). Single-cell RNA sequencing (scRNA-seq) data were used to distinguish malignant cells from normal cells in the HCC tumor microenvironment(TME). Bulk RNA sequencing data was employed to acquire the landscape of the 33 ICDRGs. Unsupervised clustering identified two ICD molecular subtypes. The cellular infiltration characteristics and biological behavior in different subtypes were analyzed by ssGSEA. Subsequently, differentially expressed genes (DEGs) between the two subtypes were determined, based on which patients were classified into three gene clusters. Then, the prognostic model was constructed by Lasso-Cox analysis. Finally, we investigated the expression of risk genes in cancer cell line encyclopedia (CCLE) and validated the function of NKX3-2 in vitro experiments. ICD scores and ICDRGs expression in malignant cells were significantly lower than in normal cells by scRNA-seq analysis. ICD-high subtype was characterized by ICD-related gene overexpression and high levels of immune infiltration abundance and immune checkpoints; Three DEGs-related gene clusters were likewise strongly linked to stromal and immunological activation. In the ICD-related prognostic model consisting of NKX3-2, CHODL, MMP1, NR0B1, and CTSV, the low-risk group patients had a better endpoint and displayed increased susceptibility to immunotherapy and chemotherapeutic drugs like 5-Fluorouracil, afatinib, bortezomib, cediratinib, lapatinib, dasatinib, gefitinib and crizotinib. Moreover, NKX3-2 amplification in HCC samples has been verified by experiments, and its disruption suppressed the proliferation and invasion of tumor cells. Our study highlighted the potential of the ICDRGs risk score as a prognostic indicator to aid in the accurate diagnosis and immunotherapy sensitivity of HCC.

Single-cell profiling reveals the metastasis-associated immune signature of hepatocellular carcinoma.

Metastasis is the leading cause of mortality in hepatocellular carcinoma (HCC). The metastasis-associated immune signature in HCC is worth exploring. Bioinformatic analysis was conducted based on the single-cell transcriptome data derived from HCC patients in different stages. Cellular composition, pseudotime state transition, and cell-cell interaction were further analyzed and verified. Generally, HCC with metastasis exhibited suppressive immune microenvironment, while HCC without metastasis exhibited active immune microenvironment. Concretely, effector regulatory T cells (eTregs) were found to be enriched in HCC with metastasis. PHLDA1 was identified as one of exhaustion-specific genes and verified to be associated with worse prognosis in HCC patients. Moreover, A novel cluster of CCR7+ dendritic cells (DCs) was identified with high expression of maturation and migration marker genes. Pseudotime analysis showed that inhibition of differentiation occurred in CCR7+ DCs rather than cDC1 in HCC with metastasis. Furthermore, interaction analysis showed that the reduction of CCR7+ DCs lead to impaired CCR7/CCL19 interaction in HCC with metastasis. HCC with metastasis exhibited upregulation of exhaustion-specific genes of eTregs and inhibition of CCL signal of a novel DC cluster, which added new dimensions to the immune landscape and provided new immune therapeutic targets in advanced HCC.

Induction of the Inflammasome Pathway by Tyrosine Kinase Inhibitors Provides an Actionable Therapeutic Target for Hepatocellular Carcinoma.

During the last decade, tyrosine kinase inhibitors (TKIs) sorafenib and regorafenib have been standard systemic treatments for advanced hepatocellular carcinoma (HCC). Previous data associated sorafenib with inflammasome activation. However, the role of the inflammasome in sorafenib and regorafenib signaling has not been described in liver cancer patients. For this purpose, we analyzed inflammasome-related transcriptomic changes in a murine HCC model. Our data confirmed inflammasome activation after both TKI treatments, sharing a similar pattern of increased gene expression. According to human database results, transcriptional increase of inflammasome genes is associated with poorer prognosis for male liver cancer patients, suggesting a sex-dependent role for inflammasome activation in HCC therapy. In biopsies of HCC and its surrounding tissue, we detected durable increases in the inflammasome activation pattern after sorafenib or regorafenib treatment in male patients. Further supporting its involvement in sorafenib action, inflammasome inhibition (MCC950) enhanced sorafenib anticancer activity in experimental HCC models, while no direct in vitro effect was observed in HCC cell lines. Moreover, activated human THP-1 macrophages released IL-1β after sorafenib administration, while 3D Hep3B spheres displayed increased tumor growth after IL-1β addition, pointing to the liver microenvironment as a key player in inflammasome action. In summary, our results unveil the inflammasome pathway as an actionable target in sorafenib or regorafenib therapy and associate an inflammasome signature in HCC and surrounding tissue with TKI administration. Therefore, targeting inflammasome activation, principally in male patients, could help to overcome sorafenib or regorafenib resistance and enhance the efficacy of TKI treatments in HCC.

Identification of fatty acids synthesis and metabolism-related gene signature and prediction of prognostic model in hepatocellular carcinoma.

Fatty acids synthesis and metabolism (FASM)-driven lipid mobilization is essential for energy production during nutrient shortages. However, the molecular characteristics, physiological function and clinical prognosis value of FASM-associated gene signatures in hepatocellular carcinoma (HCC) remain elusive. The Gene Expression Omnibus database (GEO), the Cancer Genome Atlas (TCGA), and International Cancer Genome Consortium (ICGC) database were utilized to acquire transcriptome data and clinical information of HCC patients. The ConsensusClusterPlus was employed for unsupervised clustering. Subsequently, immune cell infiltration, stemness index and therapeutic response among distinct clusters were decoded. The tumor immune dysfunction and exclusion (TIDE) algorithm was utilized to anticipate the response of patients towards immunotherapy, and the genomics of drug sensitivity in cancer (GDSC) tool was employed to predict their response to antineoplastic medications. Least absolute shrinkage and selection operator (LASSO) regression analysis and protein-protein interaction (PPI) network were employed to construct prognostic model and identity hub gene. Single cell RNA sequencing (scRNA-seq) and CellChat were used to analyze cellular interactions. The hub gene of FASM effect on promoting tumor progression was confirmed through a series of functional experiments. Twenty-six FASM-related genes showed differential expression in HCC. Based on these FASM-related differential genes, two molecular subtypes were established, including Cluster1 and Cluster2 subtype. Compared with cluster2, Cluster1 subtype exhibited a worse prognosis, higher risk, higher immunosuppressive cells infiltrations, higher immune escape, higher cancer stemness and enhanced treatment-resistant. PPI network identified Acetyl-CoA carboxylase1 (ACACA) as central gene of FASM and predicted a poor prognosis. A strong interaction between cancer stem cells (CSCs) with high expression of ACACA and macrophages through CD74 molecule (CD74) and integrin subunit beta 1 (ITGB1) signaling was identified. Finally, increased ACACA expression was observed in HCC cells and patients, whereas depleted ACACA inhibited the stemness straits and drug resistance of HCC cells. This study provides a resource for understanding FASM heterogeneity in HCC. Evaluating the FASM patterns can help predict the prognosis and provide new insights into treatment response in HCC patients.

The m6A methyltransferase METTL5 promotes neutrophil extracellular trap network release to regulate hepatocellular carcinoma progression.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, it has a poor prognosis due to its highly invasive and metastatic nature. Consequently, identifying effective prognostic markers and potential therapeutic targets has been extensively investigated. METTL5, an 18S rRNA methyltransferase, is abnormally high in HCC. But its biological function and prognostic significance in HCC remain largely unelucidated. This study aimed to investigate the role of METTL5 in HCC progression, and elucidate its possible molecular mechanisms in HCC via transcriptome sequencing, providing new insights for identifying new HCC prognostic markers and therapeutic targets. The METTL5 expression in HCC and paracancerous tissues was analyzed using HCC immunohistochemical microarrays and bioinformatic retrieval methods to correlate METTL5 with clinicopathological features and survival prognosis. We constructed a METTL5 knockdown hepatocellular carcinoma cell line model and an animal model to determine the effect of METTL5 on hepatocellular carcinoma progression. Subsequently, RNA sequencing was performed to analyze the molecular mechanism of METTL5 in HCC based on the sequencing results, and relevant experiments were performed to verify it. We found that METTL5 expression was elevated in hepatocellular carcinoma tissues and correlated with poor patient prognosis, and in the analysis of clinicopathological features showed a correlation with TNM staging. In hepatocellular carcinoma cell lines with knockdown of METTL5, the malignant biological behavior was significantly reduced both invitro and invivo. Based on the sequencing results as well as the results of GO functional enrichment analysis and KEGG pathway enrichment analysis, we found that METTL5 could promote the generation and release of neutrophil extracellular capture network (NETs) and might further accelerate the progression of HCC. The m6A methyltransferase METTL5 is overexpressed in hepatocellular carcinoma (HCC) and correlates with poor prognosis. METTL5 accelerates malignant progression of HCC by promoting generation and release of the neutrophil extracellular traps (NETs) network, providing new insights for clinical biomarkers and immunotherapeutic targets in HCC prognosis.

RBM39 is a potential prognostic biomarker with functional significance in hepatocellular carcinoma.

RNA-binding motif protein 39 (RBM39) is a well-known RNA-binding protein involved in tumorigenesis; however, its role in hepatocellular carcinoma (HCC) remains unclear. The aim of this study was to investigate the role of RBM39 in HCC. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to analyze the differential expression of RBM39 in HCC and normal tissues. The prognostic and diagnostic value of RBM39 in HCC was accessed by Kaplan-Meier analysis, Cox regression, and receiver operating characteristic (ROC) curve analyses. Quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry were used to validate the mRNA and protein expression of RBM39 in HCC. Moreover, gene set enrichment analysis (GSEA) was performed to identify key pathways related to RBM39. The correlation between RBM39 expression and immune cell infiltration was evaluated using a single-sample gene set enrichment analysis (ssGSEA). CCK8 and wound healing assays were performed to investigate the proliferation and migration abilities of HCC cells with RBM39 knockdown. RBM39 expression was upregulated in the HCC tissues. High RBM39 expression was significantly associated with advanced T stage, histological grade, and pathological stage and predicted poor overall survival (OS), disease-specific survival (DSS), and progress-free interval (PFI) in HCC patients. The upregulation of RBM39 expression was an independent prognostic factor for OS. Moreover, GSEA enrichment analysis indicated that RBM39 was functionally involved in pathways associated with the cell cycle, DNA replication, the p53 signaling pathway, and primary immunodeficiency. RBM39 expression was associated with infiltration of Th2 cells and dendritic cells (DC). RBM39 knockdown significantly inhibited the proliferation and migration of HCC cells. These findings suggest that high RBM39 expression is associated with poor prognosis and promotes HCC cell proliferation and migration. Based on these results, RBM39 is a promising prognostic biomarker with functional significance for HCC.

Identification of a Novel Circadian Rhythm-Related Signature for Predicting Prognosis and Therapies in Hepatocellular Carcinoma Based on Bulk and Single-Cell RNA Sequencing

Background. Circadian rhythm disruption involves tumorigenesis and tumor progression. However, the influences of circadian rhythm on the tumor microenvironment (TME) and the prognosis of hepatocellular carcinoma (HCC) are unknown. Methods. Bulk RNA-seq and single-cell RNA-seq from TCGA, ICGC, and GEO were used to comprehensively identify prognostic circadian control cells and circadian rhythm associated genes (CRRGs) using R and Python packages. Besides, the circadian rhythm-related prognostic signature was identified and validated. The biological function, immune infiltration, and therapeutic response associated with circadian rhythm-related (CR) risk were detected. Results. A total of 252 differentially expressed CRRGs in HCC were identified, and HCC with a high CR score revealed poor survival. We annotated 11 major cell types in TME; immune cells (B cells, myeloid, CD4+ cells, CD8+ cells, NK cells, Tregs) with high CR score, and hepatocyte, bio-potent cells, fibroblasts, and endothelial cells with low CR score were identified. Moreover, five CRRGs (RPL29, PFKFB3, RPS7, SLC6A6, and RPLP2) were selected and validated as the prognostic signature in HCC. The risk score was calculated based on the prognostic signature, and patients then were divided into high-risk and low-risk groups according to the median value of the risk score. High risk is linked to several metabolism-related pathways and canonical cancer-related pathways and is negatively associated with immunotherapeutic responses and positively associated with some chemotherapeutic drugs. Conclusion. Our finding provides the novel circadian rhythm-related prognostic signature and represents a novel viable “time-dependent” therapeutic option for HCC treatment.

A novel mitochondrial unfolded protein response-related risk signature to predict prognosis, immunotherapy and sorafenib sensitivity in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common cause of cancer-associated death worldwide. The mitochondrial unfolded protein response (UPRmt) not only maintains mitochondrial integrity but also regulates cancer progression and drug resistance. However, no study has used the UPRmt to construct a prognostic signature for HCC. This work aimed to establish a novel signature for predicting patient prognosis, immune cell infiltration, immunotherapy, and chemotherapy response based on UPRmt-related genes (MRGs). Transcriptional profiles and clinical information were obtained from the TCGA and ICGC databases. Cox regression and LASSO regression analyses were applied to select prognostic genes and develop a risk model. The TIMER algorithm was used to investigate immunocytic infiltration in the high- and low-risk subgroups. Here, two distinct clusters were identified with different prognoses, immune cell infiltration statuses, drug sensitivities, and response to immunotherapy. A risk score consisting of seven MRGs (HSPD1, LONP1, SSBP1, MRPS5, YME1L1, HDAC1 and HDAC2) was developed to accurately and independently predict the prognosis of HCC patients. Additionally, the expression of core MRGs was confirmed by immunohistochemistry (IHC) staining, single-cell RNA sequencing, and spatial transcriptome analyses. Notably, the expression of prognostic MRGs was significantly correlated with sorafenib sensitivity in HCC and markedly downregulated in sorafenib-treated HepG2 and Huh7 cells. Furthermore, the knockdown of LONP1 decreased the proliferation, invasion, and migration of HepG2 cells, suggesting that upregulated LONP1 expression contributed to the malignant behaviors of HCC cells. To our knowledge, this is the first study to investigate the consensus clustering algorithm, prognostic potential, immune microenvironment infiltration and drug sensitivity based on the expression of MRGs in HCC. In summary, the UPRmt-related classification and prognostic signature could assist in determining the prognosis and personalized therapy of HCC patients from the perspectives of predictive, preventative and personalizedmedicine.

Multiomics profiling of buffy coat and plasma unveils etiology-specific signatures in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality worldwide. Despite identification of several biomarkers for HCC diagnosis, challenges such as low sensitivity and intratumoral heterogeneity have impeded early detection, highlighting the need for etiology-specific blood biomarkers. We generated whole-transcriptome sequencing (WTS) and targeted proteome data from buffy coat and plasma samples from HCC patients. By integrating etiological information on viral infection, we investigated the etiology-specific gene expression landscape at the blood level. Validation of differentially expressed genes (DEGs) was performed using publicly available RNA-seq datasets and qRT‒PCR with AUC analyses. Differential expression analyses with multiomics data revealed distinct gene expression profiles between HBV-associated HCC and nonviral HCC, indicating the presence of etiology-specific blood biomarkers. The identified DEGs were validated across multiple independent datasets, underscoring their utility as biomarkers. Additionally, single-cell RNA-seq analysis of HCC confirmed differences in DEG expression across distinct immune cell types. Our buffy coat WTS data and plasma proteome data may serve as reliable sources for identifying etiology-specific blood biomarkers of HCC and might contribute to discovery of therapeutic targets for HCC across different etiologies.