A prognostic model for hepatocellular carcinoma based on apoptosis-related genes

Constructing and validating pan-apoptosis-related features for predicting prognosis and immunotherapy response in hepatocellular carcinoma

The study aimed to develop a prognostic model for Hepatocellular Carcinoma (HCC) based on pan-apoptosis-related genes, a novel inflammatory programmed cell death form intricately linked to HCC progression. Utilizing transcriptome sequencing and clinical data from the TCGA database, we identified six crucial pan-apoptosis-related genes through statistical analyses. These genes were then employed to construct a prognostic model that accurately predicts overall survival rates in HCC patients. Our findings revealed a strong correlation between the model's risk scores and tumor microenvironment (TME) status, immune cell infiltration, and immune checkpoint expression. Furthermore, we screened for drugs with potential therapeutic efficacy in high- and low-risk HCC groups. Notably, PPP2R5B gene knockdown was found to inhibit HCC cell proliferation and clonogenic capacity, suggesting its role in HCC progression. In conclusion, this study presents a novel pan-apoptosis gene-based prognostic risk model for HCC, providing valuable insights into patient TME status and guiding the selection of targeted therapies and immunotherapies.

The construction of a prognostic model by apoptosis-related genes to predict survival, immune landscape, and medication in cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma (CCA) is a highly aggressive and invasive malignant tumor of the bile duct, with a poor prognosis and a high mortality rate. Currently, there is a lack of effective targeted treatment methods and reliable biomarkers for prognosis.

METHODS

We downloaded RNA-seq and clinical data of CCA from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases as training and test sets. The apoptosis-related genes were obtained from the Molecular Signatures Database (MsigDB) database. We used univariate/multivariate Cox regression and Lasso regression analyses to construct a riskscore prognostic model. Based on the median riskscore, we clustered the patients into high-risk (HR) and low-risk (LR) groups. We carried out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of differentially expressed genes (DEGs) in HR and LR groups. The single sample gene set enrichment analysis (ssGSEA) was employed to analyze the immune infiltration of the HR and LR groups. The CellMiner database was utilized to predict drugs and perform molecular docking on drugs and target proteins.

RESULTS

We identified 8 genes with prognostic significance to construct a prognostic model. Results of GO and KEGG demonstrated that DEGs were mainly enriched in biological functions such as fatty acid metabolic processes and pathways such as the cAMP signaling pathway. Results of ssGSEA uncovered that immune cells such as DCs and Macrophages in the HR group, as well as immune functions such as Check-point and Parainflammation, were considerably higher than those in the LR group. Drug sensitivity prediction and results of molecular docking revealed that Rigosertib targeted the prognostic genes MAP3K1. HYPOTHEMYCIN and AMG900 effectively targeted JUN.

CONCLUSION

Our project suggested that the prognostic model with apoptotic features can effectively predict prognosis in CCA patients, proffering prognostic biomarkers and potential therapeutic targets for CCA patients.

Noncoding RNAs and programmed cell death in hepatocellular carcinoma: Significant role of epigenetic modifications in prognosis, chemoresistance, and tumor recurrence rate

Hepatocellular carcinoma (HCC) is the most common type of liver cancer with a high death rate in the world. The molecular mechanisms related to the pathogenesis of HCC have not been precisely defined so far. Hence, this review aimed to address the potential cross-talk between noncoding RNAs (ncRNAs) and programmed cell death in HCC. All related papers in the English language up to June 2023 were collected and screened. The searched keywords in scientific databases, including Scopus, PubMed, and Google Scholar, were HCC, ncRNAs, Epigenetic, Programmed cell death, Autophagy, Apoptosis, Ferroptosis, Chemoresistance, Tumor recurrence, Prognosis, and Prediction. According to the reports, ncRNAs, comprising long ncRNAs, microRNAs, circular RNAs, and small nucleolar RNAs can affect cell proliferation, migration, invasion, and metastasis, as well as cell death-related processes, such as autophagy, ferroptosis, necroptosis, and apoptosis in HCC by regulating cancer-associated genes and signaling pathways, for example, phosphoinositide 3-kinase/Akt, extracellular signal-regulated kinase/MAPK, and Wnt/β-catenin signaling pathways. It seems that ncRNAs, as epigenetic regulators, can be utilized as biomarkers in diagnosis, prognosis, survival and recurrence rates prediction, chemoresistance, and evaluation of therapeutic response in HCC patients. However, more scientific evidence is suggested to be accomplished to confirm these results.

Unleashing the potential of gene signatures as prognostic and predictive tools: A step closer to personalized medicine in hepatocellular carcinoma (HCC)

Hepatocellular carcinoma (HCC) is one of the growing malignancies globally, affecting a myriad of people and causing numerous cancer-related deaths. Despite therapeutic improvements in treatment strategies over the past decades, HCC still remains one of the leading causes of person-years of life lost. Numerous studies have been conducted to assess the characteristics of HCC with the aim of predicting its prognosis and responsiveness to treatment. However, the identified biomarkers have shown limited sensitivity, and the translation of these findings into clinical practice has faced challenges. The development of sequencing techniques has facilitated the exploration of a wide range of genes, leading to the emergence of gene signatures. Although several studies assessed differentially expressed genes in normal and HCC tissues to find the unique gene signature with prognostic value, to date, no study has reviewed the task, and to the best of our knowledge, this review represents the first comprehensive analysis of relevant studies in HCC. Most gene signatures focused on immune-related genes, while others investigated genes related to metabolism, autophagy, and apoptosis. Even though no identical gene signatures were found, NDRG1, SPP1, BIRC5, and NR0B1 were the most extensively studied genes with prognostic value. Finally, despite challenges such as the lack of consistent patterns in gene signatures, we believe that comprehensive analysis of pertinent gene signatures will bring us a step closer to personalized medicine in HCC, where treatment strategies can be tailored to individual patients based on their unique molecular profiles.

Development of a clinical scoring model to predict the overall and relapse‑free survival of patients with hepatocellular carcinoma following a hepatectomy

Hepatocellular carcinoma (HCC) is a highly lethal disease, and surgical resection is one of the major treatment methods used. However, to date, at least to the best of our knowledge, there is no effective prognostic scoring system for the overall survival (OS) and relapse-free survival (RFS) of patients following hepatectomy. The present study developed a low-cost and easy-to-use model based on the clinicopathological characteristics of patients with HCC for assessment of outcome prediction and risk stratification. A total of 690 patients with HCC undergoing surgery were included and randomly divided into two cohorts (n=345). Cox regression analysis was conducted to investigate the association between the clinicopathological and treatment features, and patient survival. Multivariate analysis revealed that ascites, vascular tumor thrombus, low tumor differentiation and extrahepatic metastasis were independent risk factors for OS. Extrahepatic metastasis and multiple tumors were independent risk factors to predict tumor recurrence. These variables were weighted to construct the ascites, vascular tumor thrombus, low tumor differentiation, extrahepatic metastasis and multiple tumors (AVLEM) score based on the cumulative incidence (CuI) of the aforementioned variables, and the patients were classified into grade 0 (CuI=0), grade 1 (CuI=1 for OS and CuI ≥1 for RFS), and grade 2 (CuI ≥2) subgroups, respectively. Kaplan-Meier analysis revealed that the OS and RFS differed significantly among the subgroups; however, the survival rate between the two cohorts did not exhibit any marked differences. On the whole, the present study demonstrates that with this AVLEM scoring system, patients with HCC with a high score had a poor OS and RFS; thus, it is suggested that such patients undergo imaging examinations following a hepatectomy more frequently.

Overexpression of SH2D1A promotes cancer progression and is associated with immune cell infiltration in hepatocellular carcinoma via bioinformatics and in vitro study

BACKGROUND

SH2 domain containing 1A (SH2D1A) expression has been linked to cancer progression. However, the functions of SH2D1A in hepatocellular carcinoma (HCC) have not been reported.

METHODS

The effects of SH2D1A on the proliferation, migration, and invasion of HCC cells and the related pathways were re-explored in cell models with SH2D1A overexpression using the CCK-8, migration and invasion assays and western blotting. The functions and mechanisms of genes co-expressed with SH2D1A were analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The relationship between SH2D1A expression and immune microenvironment features in HCC was explored.

RESULTS

Elevated SH2D1A expression promoted cell proliferation, migration, and invasion, which was related to the overexpression of p-Nf-κB and BCL2A1 protein levels in HCC. SH2D1A expression was related to the immune, stromal, and ESTIMATE scores, and the abundance of immune cells, such as B cells, CD8+ T cells, and T cells. SH2D1A expression was significantly related to the expression of immune cell markers, such as PDCD1, CD8A, and CTLA4 in HCC.

CONCLUSION

SH2D1A overexpression was found to promote cell growth and metastasis via the Nf-κB signaling pathway and may be related to the immune microenvironment in HCC. The findings indicate that SH2D1A can function as a biomarker in HCC.

Establishment of prognostic model of bladder cancer based on apoptosis-related genes, in which P4HB promotes BLCA progression

BACKGROUND

A variety of apoptosis genes have been confirmed to be related to the occurrence and development of bladder cancer patients, but few studies have paid attention to their significance in the prognosis of bladder cancer. Therefore, this study explored the value of apoptosis-related genes in the prognosis of BLCA by using the data in TCGA database.

METHODS

We downloaded the mRNA expression profiles and corresponding clinical data of bladder cancer patients from TCGA database, and obtained 2411 apoptosis-related genes from Deathbase database. Screening out differentially expressed apoptosis-related genes. Cox regression was used to determine the prognostic value of apoptosis-related genes, and then a prognostic risk model was developed. A nomogram based on risk model was constructed to predict the prognosis of bladder cancer patients. At the same time, immune infiltration correlation analysis of genes in the prognosis model.

RESULTS

A prognostic model composed of 12 apoptosis-related genes was constructed. According to the risk score calculated by the model, patients were divided into high-risk group and low-risk group. There are significant differences in the expression of immune cells, immune function and immune checkpoint molecules between high-risk group and low-risk group. P4HB may promote bladder cancer progression.

CONCLUSION

Based on the differential expression of apoptosis-related genes, we established a risk model to predict the prognosis of bladder cancer patients, in which P4HB promotes BLCA progression.

Gene body hypomethylation of pyroptosis-related genes NLRP7, NLRP2, and NLRP3 facilitate non-invasive surveillance of hepatocellular carcinoma

Programmed cell death (PCD) resistance is a key driver of cancer occurrence and development. The prognostic relevance of PCD-related genes in hepatocellular carcinoma (HCC) has attracted considerable attention in recent years. However, there is still a lack of efforts to compare the methylation status of different types of PCD genes in HCC and their roles in its surveillance. The methylation status of genes related to pyroptosis, apoptosis, autophagy, necroptosis, ferroptosis, and cuproptosis was analyzed in tumor and non-tumor tissues from TCGA. Whole-genome bisulfite sequencing (WGBS) data of paired tumor tissue and buffy coat samples were used to filter the potential interference of blood leukocytes in cell-free DNA (cfDNA). The WGBS data of healthy individuals' and early-stage HCC patients' cfDNA were analyzed to evaluate the distinguishing ability. The average gene body methylation (gbDNAme) of pyroptosis-related genes (PRGs) was significantly altered in HCC tissues relative to normal tissues, and their distinguishing ability was higher compared to the other types of PCD-related genes. The gbDNAme of NLRP7, NLRP2, and NLRP3 was reflective of the hypomethylation in HCC tissues, and methylation levels of NLRP3 correlated positively with its expression level (r=0.51). The candidate hypomethylated PRGs could discriminate between early HCC patients and healthy controls in cfDNA analysis with high accuracy (area under the receiver operation curve, AUC=0.94). Furthermore, the hypomethylation of PRGs was associated with poor prognosis of HCC. Gene body hypomethylation of PRGs is a promising biomarker for early HCC detection, monitoring of tumor recurrence, and prognosis prediction.

Detection of sFas, sCD137, and IL-27 Cytokines as Potential Biomarkers for Hepatocellular Carcinoma Diagnosis

Purpose

Hepatocellular carcinoma (HCC), a prevalent type of liver cancer, is mainly diagnosed in the advanced stage, leading to a high mortality rate. Recent advances have identified peripheral cytokines as a potential tool to predict disease outcomes and inform therapeutic decisions. Hence, in this study, we aim to build a predictive model for HCC based on serum levels of different cytokines.

Patients and Methods

We used immunoassay to quantify the concentrations of IL-27, MIP-1β, Perforin, sCD137, sFas, and TNF-α in the serum of 38 HCC patients and 15 healthy controls. Logistic regression was then used to construct classification models detecting HCC based on these cytokines. A nomogram of the best-performing model was generated to visualize HCC prediction.

Results

sFas and MIP-1β were found to be significantly higher in HCC patients compared to controls. Predictive models based on cytokine levels combining sFas, sCD137, and IL-27 performed the best in distinguishing HCC patients from healthy controls. This model has a bias-corrected area under the receiver operating characteristic (ROC) curve (AUC) of 0.948, a sensitivity of 92.11%, a specificity of 93.33%, and an accuracy of 0.925.

Conclusion

Our findings suggest that serum cytokines have the potential to be utilized in HCC screening to improve detection rates.

Systems Pharmacology-Based Strategy to Investigate the Mechanism of Ruangan Lidan Decoction for Treatment of Hepatocellular Carcinoma

epatocellular carcinoma (HCC) is one of the leading contributors to cancer mortality worldwide. Currently, the prevention and treatment of HCC remains a major challenge. As a traditional Chinese medicine (TCM) formula, Ruangan Lidan decoction (RGLD) has been proved to own the effect of relieving HCC symptoms. However, due to its biological effects and complex compositions, its underlying mechanism of actions (MOAs) have not been fully clarified yet. In this study, we proposed a pharmacological framework to systematically explore the MOAs of RGLD against HCC. We firstly integrated the active ingredients and potential targets of RGLD. We next highlighted 25 key targets that played vital roles in both RGLD and HCC disease via a protein-protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Furthermore, an ingredient-target network of RGLD consisting of 216 ingredients with 306 targets was constructed, and multilevel systems pharmacology analyses indicated that RGLD could act on multiple biological processes related to the pathogenesis of HCC, such as cellular response to hypoxia and cell proliferation. Additionally, integrated pathway analysis of RGLD uncovered that RGLD might treat HCC through regulating various pathways, including MAPK signaling pathway, PI3K/Akt signaling pathway, TNF signaling pathway, and ERBB signaling pathway. Survival analysis results showed that HCC patients with low expression of VEGFA, HIF1A, CASP8, and TOP2A were related with a higher survival rate than those with high expression, indicating the potential clinical significance for HCC. Finally, molecular docking results of core ingredients and targets further proved the feasibility of RGLD in the treatment of HCC. Overall, this study indicates that RGLD may treat HCC through multiple mechanisms, which also provides a potential paradigm to investigate the MOAs of TCM prescription.

Risk predictive model based on three immune-related gene pairs to assess prognosis and therapeutic sensitivity for hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) as a common tumor has a poor prognosis. Recently, a combination of atezolizumab and bevacizumab has been recommended as the preferred regimen for advanced HCC. However, the overall response rate of this therapy is low. There is an urgent need to identify sensitive individuals for this precise therapy among HCC patients.

METHODS

The Wilcox test was used to screen the differentially expressed immune-related genes by combining the TCGA cohort and the Immunology Database. Univariate and multivariate Cox regression analysis were used to screen the immune gene pairs concerning prognosis. A predictive model was constructed using LASSO Cox regression analysis, and correlation analysis was conducted between the signature and clinical characteristics. ICGC cohort and GSE14520 were applied for external validations of the predictive risk model. The relationship between immune cell infiltration, TMB, MSI, therapeutic sensitivity of immune checkpoint inhibitors, targeted drugs, and the risk model were assessed by bioinformatics analysis in HCC patients.

RESULTS

A risk predictive model consisting of 3 immune-related gene pairs was constructed and the risk score was proved as an independent prognostic factor for HCC patients combining the TCGA cohort. This predictive model exhibited a positive correlation with tumor size (p < 0.01) and tumor stage (TNM) (p < 0.001) in the chi-square test. The predictive power was verified by external validations (ICGC and GSE14520). The risk score clearly correlated with immune cell infiltration, MSI, immune checkpoints, and markers of angiogenesis.

CONCLUSIONS

Our research established a risk predictive model based on 3 immune-related gene pairs and explored its relationship with immune characteristics, which might help to assess the prognosis and treatment sensitivity to immune and targeted therapy of HCC patients.

Outcomes of adolescent and young patients with hepatocellular carcinoma after curative liver resection: a retrospective study

BACKGROUND

The risk of HCC is documented to be age-related. The outcomes of young HCC patients on postoperative prognosis are not well understood. The study aims to compare the characteristic differences between adolescent and young (AYA) and non-AYA HCC patients.

METHODS

We performed a retrospective analysis of the clinical and pathological findings and the survival of 243 HCC patients who underwent operations between 2007 and 2018.

RESULTS

The AYA group had a higher AFP level and a higher prevalence of family history of HCC or other cancers than the non-AYA group (P < 0.01 and P < 0.05). AYA patients had more unfavorable pathological characteristics including bigger lesion size, microvascular invasion, portal vein invasion, and hepatic capsule invasion. They also had a more unfavorable Edmondson grade and less tumor capsule formation (P < 0.01). Age was an independent predictor of survival in HCC patients. AYA patients had poorer disease-free and overall survival than non-AYA patients did (P < 0.01). Patients under 30 years old had an even poorer disease-free survival than those aged 30-40 (P = 0.047).

CONCLUSIONS

AYA patients exhibited a higher recurrence rate and disease-related death rate with more unfavorable pathological characteristics. Enhanced follow-up for young HCC patients should be applied.

A pyroptosis-related gene signature predicts prognosis and immune microenvironment in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a highly malignant tumor with a very poor prognosis. Pyroptosis is an inflammatory form of cell death and plays an important role in cancer development. The prognostic value of pyroptosis-related genes (PRGs) in HCC has not been studied extensively.

METHODS

Unsupervised consensus clustering analysis was performed to identify two subtypes based on the expression profiles of prognostic PRGs in the The Cancer Genome Atlas (TCGA) database, and the differences between the two subtypes were compared. A prognostic model based on four PRGs was established by further least absolute shrinkage and selection operator (LASSO) Cox regression analysis and multivariate Cox regression analysis.

RESULTS

Two subtypes (clusters 1 and 2) were identified by consensus clustering based on prognostic PRGs in HCC. Survival outcomes, biological function, genomic alterations, immune cell infiltration, and immune checkpoint genes were compared between the subtypes. Cluster 2 had a worse survival outcome than cluster 1. Cluster 2 was enriched for hallmarks of cancer progression, TP53 mutation, tumor-promoting immune cells, and immune checkpoint genes, which may contribute to the poor prognosis. A prognostic risk signature that predicted the overall survival (OS) of patients was constructed and validated. Consequently, a risk score was calculated for each patient. Combined with the clinical characteristics, the risk score was found to be an independent prognostic factor for survival of HCC patients. Further analysis revealed that the risk score was closely associated with the levels of immune cell infiltration and the expression profiles of immune checkpoint genes.

CONCLUSIONS

Collectively, our study established a prognostic risk signature for HCC and revealed a significant correlation between pyroptosis and the HCC immune microenvironment.

Breast Cancer Prognosis Prediction and Immune Pathway Molecular Analysis Based on Mitochondria-Related Genes

Background

Mitochondria play an important role in breast cancer (BRCA). We aimed to build a prognostic model based on mitochondria-related genes.

Method

Univariate Cox regression analysis, random forest, and the LASSO method were performed in sequence on pretreated TCGA BRCA datasets to screen out genes from a Gene Set Enrichment Analysis, Gene Ontology: biological process gene set to build a prognosis risk score model. Survival analyses and ROC curves were performed to verify the model by using the GSE103091 dataset. The BRCA datasets were equally divided into high- and low-risk score groups. Comparisons between clinical features and immune infiltration related to different risk scores and gene mutation analysis and drug sensitivity prediction were performed for different groups.

Result

Four genes, MRPL36, FEZ1, BMF, and AFG1L, were screened to construct our risk score model in which the higher the risk score, the poorer the prognosis. Univariate and multivariate analyses showed that the risk score was significantly associated with age, M stage, and N stage. The gene mutation probability in the high-risk score group was significantly higher than that in the low-risk score group. Patients with higher risk scores were more likely to die. Drug sensitivity prediction in different groups indicated that PF-562271 and AS601245 might be new inhibitors of BRCA.

Conclusion

We developed a new workable risk score model based on mitochondria-related genes for BRCA prognosis and identified new targets and drugs for BRCA research.

Cancer Progression Mediated by CAFs Relating to HCC and Identification of Genetic Characteristics Influencing Prognosis

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignancies, and although there are several treatment options, the overall results are not satisfactory. Cancer-associated fibroblasts (CAFs) can promote cancer progression through various mechanisms.

METHODS

HCC-associated mRNA data were sourced from The Cancer Genome Atlas database (TCGA) and International Cancer Genome Consortium (ICGC) database. First, the differentially expressed CAF-related genes (CAF-DEGs) were acquired by difference analysis and weighted gene coexpression network analysis (WGCNA). Moreover, a CAF-related risk model was built by Cox analysis. Kaplan-Meier (K-M) curves and receiver operating characteristic (ROC) curves were utilized to evaluate the validity of this risk model. Furthermore, enrichment analysis of differentially expressed genes (DEGs) between the high- and low-risk groups was executed to explore the functions relevant to the risk model. Furthermore, this study compared the differences in immune infiltration, immunotherapy, and drug sensitivity between the high- and low-risk groups. Finally, we verified the mRNA expression levels of selected prognostic genes by quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

107 CAF-DEGs were identified in the HCC samples, and five prognosis-related genes (ACTA2, IGJ, CTHRC1, CXCL12, and LAMB1) were obtained by Cox analysis and utilized to build a CAF-related risk model. K-M analysis illustrated a low survival in the high-risk group, and ROC curves revealed that the risk model could accurately predict the 1-, 3-, and 5-year overall survival (OS) of HCC patients. In addition, Cox analysis demonstrated that the risk score was an independent prognostic factor. Enrichment analysis illustrated that DEGs between the high- and low-risk groups were related to immune response, amino acid metabolism, and fatty acid metabolism. Furthermore, risk scores were correlated with the tumor microenvironment, CAF scores, and TIDE scores, and CAF-related marker genes were positively correlated with all five model genes. Notably, the risk model was relevant to the sensitivity of chemotherapy drugs. Finally, the results of qRT-PCR demonstrated that the expression levels of 5 model genes were in accordance with the analysis.

CONCLUSION

A CAF-related risk model based on ACTA2, IGJ, CTHRC1, CXCL12, and LAMB1 was built and could be utilized to predict the prognosis and treatment of HCC.

Secondarily estimated cure fraction and five-year recurrence-free conditional survival probabilities among patients undergoing surgical resection for hepatocellular carcinoma presenting with minor gross vascular invasion

BACKGROUND

Surgical resection (SR) has been selectively applied in hepatocellular carcinoma (HCC) presenting with minor gross vascular invasion (mGVI) which is defined when tumor invasion is confined to second-order portal branches or segmental branches of hepatic vein. However, little data of long-term outcomes are available for supporting the role of SR as a potentially curable therapeutic option for HCC presenting with mGVI. This study is aimed to estimate a statistical cure fraction and the improvement of recurrence-free conditional survival (RFCS) over time among patients undergoing SR for HCC presenting with mGVI.

METHODS

The literature search was conducted focusing on previous studies that investigated the long-term survival rates of patients after SR for HCC presenting with mGVI. The reference cohort was extracted from a study including patients undergoing SR for HCC without vascular invasion. A non-mixture cure model was adopted to estimate the statistical cure fraction. The 5-year RFCS probabilities were also calculated.

RESULTS

Three retrospective studies were secondarily analyzed. The probability of being statistically cured after SR for HCC presenting with mGVI was 7.3% (95% confidence interval, 4.4%-11.2%) in the mGVI group, lower than that of the reference cohort (hazard ratio, 1.81; 95% confidence interval, 1.59-2.05). The estimated 5-year RFCS probabilities improved with each additional year of survival. Moreover, 1 year after SR, the 5-year RFCS probabilities of patients with HCC presenting with mGVI was essentially the same as that of the reference cohort.

CONCLUSIONS

This study shows that a cure can be expected in around seven percent of patients undergoing SR for HCC presenting with mGVI. Furthermore, recurrence-free survival expectancy improves dramatically over time among those patients who do not have recurrence. Overall, these findings suggest that SR should be considered as a potentially curable treatment for patients with HCC presenting with mGVI.

Human nuclear receptors (NRs) genes have prognostic significance in hepatocellular carcinoma patients

Background

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality in the world.

Method

We downloaded the mRNA profiles and clinical information of 371 HCC patients from The Cancer Genome Atlas (TCGA) database. The consensus clustering analysis with the mRNA levels of 48 nuclear receptors (NRs) was performed by the “ConsensusClusterPlus.” The univariate Cox regression analysis was performed to predict the prognostic significance of NRs on HCC. The risk score was calculated by the prognostic model constructed based on eight optimal NRs. Then multivariate Cox regression analysis was performed to determine whether the risk score is an independent prognostic signature. Finally, the nomogram based on multiple independent prognostic factors was used to predict the long-term survival of HCC patients.

Results

The prognostic model constructed based on the eight optimal NRs (NR1H3, ESR1, NR1I2, NR2C1, NR6A1, PPARD, PPARG, and VDR) could effectively predict the prognosis of HCC patients as an independent prognostic signature. Moreover, the nomogram was constructed based on multiple independent prognostic factors including risk score and tumor node metastasis (TNM) stage and could better predict the long-term survival for 3- and 5-year of HCC patients.

Conclusion

Our results provided novel evidences that NRs could act as the potential prognostic signatures for HCC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02246-x.