Development and validation of a CTNNB1-associated metabolic prognostic model for hepatocellular carcinoma

TuBG1 promotes hepatocellular carcinoma via ATR/P53-apoptosis and cycling pathways

BACKGROUND

As reported, γ-tubulin (TuBG1) is related to the occurrence and development of various types of malignant tumors. However, its role in hepatocellular cancer (HCC) is not clear. The present study was to investigate the relationship between TuBG1 and clinical parameters and survival in HCC patients.

METHODS

The correlation between TuBG1 and clinical parameters and survival in HCC patients was explored by bioinformatics analysis. Immunohistochemistry was used for the verification. The molecular function of TuBG1 was measured using colony formation, scratch assay, trans-well assay and flow cytometry. Gene set enrichment analysis (GSEA) was used to pick up the enriched pathways, followed by investigating the target pathways using Western blotting. The tumor-immune system interactions and drug bank database (TISIDB) was used to evaluate TuBG1 and immunity. Based on the TuBG1-related immune genes, a prognostic model was constructed and was further validated internally and externally.

RESULTS

The bioinformatic analysis found high expressed TuBG1 in HCC tissue, which was confirmed using immunohistochemistry and Western blotting. After silencing the TuBG1 in HCC cell lines, more G1 arrested cells were found, cell proliferation and invasion were inhibited, and apoptosis was promoted. Furthermore, the silence of TuBG1 increased the expressions of Ataxia-Telangiectasia and Rad-3 (ATR), phospho-P38 mitogen-activated protein kinase (P-P38MAPK), phospho-P53 (P-P53), B-cell lymphoma-2 associated X protein (Bax), cleaved caspase 3 and P21; decreased the expressions of B-cell lymphoma-2 (Bcl-2), cyclin D1, cyclin E2, cyclin-dependent kinase 2 (CDK2) and CDK4. The correlation analysis of immunohistochemistry and clinical parameters and survival data revealed that TuBG1 was negatively correlated with the overall survival. The constructed immune prognosis model could effectively evaluate the prognosis.

CONCLUSIONS

The increased expression of TuBG1 in HCC is associated with poor prognosis, which might be involved in the occurrence and development of HCC.

Identification of ASF1A and HJURP by global H3-H4 histone chaperone analysis as a prognostic two-gene model in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignancy with poor prognosis. Abnormal expression of H3-H4 histone chaperones has been identified in many cancers and holds promise as a biomarker for diagnosis and prognosis. However, systemic analysis of H3-H4 histone chaperones in HCC is still lacking. Here, we investigated the expression of 19 known H3-H4 histone chaperones in HCC. Integrated analysis of multiple public databases indicated that these chaperones are highly expressed in HCC tumor tissues, which was further verified by immunohistochemistry (IHC) staining in offline samples. Additionally, survival analysis suggested that HCC patients with upregulated H3-H4 histone chaperones have poor prognosis. Using LASSO and Cox regression, we constructed a two-gene model (ASF1A, HJURP) that accurately predicts prognosis in ICGC-LIRI and GEO HCC data, which was further validated in HCC tissue microarrays with follow-up information. GSEA revealed that HCCs in the high-risk group were associated with enhanced cell cycle progression and DNA replication. Intriguingly, HCCs in the high-risk group exhibited increased immune infiltration and sensitivity to immune checkpoint therapy (ICT). In summary, H3-H4 histone chaperones play a critical role in HCC progression, and the two-gene (ASF1A, HJURP) risk model is effective for predicting survival outcomes and sensitivity to immunotherapy for HCC patients.

The dual roles of circRNAs in Wnt/β-Catenin signaling and cancer progression

Cancer, a complex pathophysiological condition, arises from the abnormal proliferation and survival of cells due to genetic mutations. Dysregulation of cell cycle control, apoptosis, and genomic stability contribute to uncontrolled growth and metastasis. Tumor heterogeneity, microenvironmental influences, and immune evasion further complicate cancer dynamics. The intricate interplay between circular RNAs (circRNAs) and the Wnt/β-Catenin signalling pathway has emerged as a pivotal axis in the landscape of cancer biology. The Wnt/β-Catenin pathway, a critical regulator of cell fate and proliferation, is frequently dysregulated in various cancers. CircRNAs, a class of non-coding RNAs with closed-loop structures, have garnered increasing attention for their diverse regulatory functions. This review systematically explores the intricate crosstalk between circRNAs and the Wnt/β-Catenin pathway, shedding light on their collective impact on cancer initiation and progression. The review explores the diverse mechanisms through which circRNAs modulate the Wnt/β-Catenin pathway, including sponging microRNAs, interacting with RNA-binding proteins, and influencing the expression of key components in the pathway. Furthermore, the review highlights specific circRNAs implicated in various cancer types, elucidating their roles as either oncogenic or tumour-suppressive players in the context of Wnt/β-Catenin signaling. The intricate regulatory networks formed by circRNAs in conjunction with the Wnt/β-Catenin pathway are discussed, providing insights into potential therapeutic targets and diagnostic biomarkers. This comprehensive review delves into the multifaceted roles of circRNAs in orchestrating tumorigenesis through their regulatory influence on the Wnt/β-Catenin pathway.

TC2N Promotes Cell Proliferation and Metastasis in Hepatocellular Carcinoma by Targeting the Wnt/β-Catenin Signaling Pathway

Hepatocellular carcinoma (HCC), one of the most prevalent types of cancer worldwide, has an exceedingly poor prognosis. Tandem C2 domain nuclear protein (TC2N) has been implicated in tumorigenesis and serves as an oncogene or tumor suppressor in different types of cancer. Here, we explore the possible regulatory activities and molecular mechanisms of TC2N in HCC progression. However, TC2N expression was significantly upregulated in HCC tissues and hepatoma cell lines, and this upregulation was positively correlated with tumor progression in HCC patients. The ectopic overexpression of TC2N accelerated the proliferation, migration, and invasion of HCC cells, whereas its knockdown showed the opposite effects. Bioinformatics analysis showed that TC2N participates in the regulation of the Wnt/β-catenin signaling pathway. Mechanistically, TC2N activated the Wnt/β-catenin signaling pathway by regulating the expression levels of β-catenin and its downstream targets CyclinD1, MMP7, c-Myc, c-Jun, AXIN2, and glutamine synthase. Furthermore, the deletion of β-catenin effectively neutralized the regulation of TC2N in HCC proliferation and metastasis. Overall, this study showed that TC2N promotes HCC proliferation and metastasis by activating the Wnt/β-catenin signaling pathway, indicating that TC2N might be a potential molecular target for the treatment of HCC.

DNA damage repair molecular subtype derived immune signature applicable for the prognosis and immunotherapy response prediction in colon cancer

Background

The DNA damage repair (DDR) pathway is one of the pathways of tumor pathogenesis, but its relationship with the immunophenotype has not been clarified in colon cancer (CC).

Methods

We identified the differentially expressed immune-related genes (DEIRGs) between two DDR molecular subtypes, namely, C1 and C2, and used univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis to construct the risk score in the training cohort [n=1,009, a combination of The Cancer Genome Atlas (TCGA) and GSE39582]. Regarding the median risk score as the unified cutoff to classify the patients into high- and low-risk groups. Two independent cohorts (GSE17538, n=232; GSE38832, n=122) were used for external validation of the prognostic value of the risk score. The IMvigor210 cohort (n=348) was used to test the predictive value of the risk score for immunotherapy response. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were performed to discover the underlying mechanism. Immune cell infiltration was quantified by the single sample gene set enrichment analysis (ssGSEA) algorithm.

Results

The high-risk group showed significantly reduced overall survival (OS), disease-specific survival (DSS), disease-free survival (DFS), progression-free survival (PFS), and relapse-free survival (RFS) compared to the low-risk group, and the two groups differed significantly in lymphatic invasion, American Joint Committee on Cancer (AJCC) TNM stage, preoperative carcinoembryonic antigen (CEA) level, etc. The enrichment levels of pathways related to colorectal cancer, epithelial-mesenchymal transition (EMT), angiogenesis, hypoxia, P53, TGF-β, KRAS signaling, etc., were upregulated in the high-risk group, but DDR-related pathways were defective in the high-risk group. The immunophenotypes of the high-risk group tended to be desert and excluded, and the risk score of patients who responded to immunotherapy was significantly lower than that of patients who did not respond to immunotherapy. The higher the infiltration levels of gamma delta T cells (γδ T cells), immature dendritic cells, and T follicular helper (Tfh) cells, the more significant adverse impact on the prognosis of CC patients was exhibited and an obviously positive correlation with the risk score was showed.

Conclusions

An immune gene risk score associated with the DDR molecular subtype was built and verified herein; that is applicable to the prognosis and immunotherapy response prediction in CC.

Development of a prognostic model for anoikis and identifies hub genes in hepatocellular carcinoma

Considering the high fatality of hepatocellular carcinoma (HCC), current prognostic systems are insufficient to accurately forecast HCC patients' outcomes. In our study, nine anoikis‑related genes (PTRH2, ITGAV, ANXA5, BIRC5, BDNF, BSG, DAP3, SKP2, and EGF) were determined to establish a risk scoring model using LASSO regression, which could be validated in ICGC dataset. Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curve analysis confirmed the risk score possessed an accurate predictive value for the prognosis of HCC patients. The high-risk group showed a higher infiltration of aDCs, macrophages, T-follicular helper cells, and Th2 cells. Besides, PD-L1 was significantly higher in the high-risk group compared to the low-risk group. Several anoikis‑related genes, such as ANX5, ITGAV, BDNF and SKP2, were associated with drug sensitivity in HCC. Finally, we identified BIRC5 and SKP2 as hub genes among the nine model genes using WGCNA analysis. BIRC5 and SKP2 were over-expressed in HCC tissues, and their over-expression was associated with poor prognosis, no matter in our cohort by immunohistochemical staining or in the TCGA cohort by mRNA-Seq. In our cohort, BIRC5 expression was highly associated with the T stage, pathologic stage, histologic grade and AFP of HCC patients. In general, our anoikis-related risk model can enhance the ability to predict the survival outcomes of HCC patients and provide a feasible therapeutic strategy for immunotherapy and drug resistance in HCC. BIRC5 and SKP2 are hub genes of anoikis‑related genes in HCC.

A novel tumor 4-driver gene signature for the prognosis of hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC), the main type of liver cancer, is the second most lethal tumor worldwide, with a 5-year survival rate of only 18%. Driver genes facilitate cancer cell growth and spread in the tumor microenvironment. Here, a comprehensive driver gene signature for the prognosis of HCC was developed.

Methods

HCC driver genes were analyzed comprehensively to develop a better prognostic signature. The dataset of HCC patients included mRNA sequencing data and clinical information from the TCGA, the ICGC, and the Guangxi Medical University Cancer Hospital cohorts. First, LASSO was performed to develop a prognostic signature for differentially expressed driver genes in the TCGA cohort. Then, the robustness of the signature was assessed using survival and time-dependent ROC curves. Furthermore, independent predictors were determined using univariate and multivariate Cox regression analyses. Stepwise multi-Cox regression analysis was employed to identify significant variables for the construction of a nomogram that predicts survival rates. Functional analysis by Spearman correlation analysis, enrichment analysis (GO, KEGG, and GSEA), and immunoassay (ssGSEA and xCell) were performed.

Result

A 4-driver gene signature (CLTC, DNMT3A, GMPS, and NRAS) was successfully constructed and showed excellent predictive efficiency in three cohorts. The nomogram indicated high predictive accuracy for the 1-, 3-, and 5-year prognoses of HCC patients, which included clinical information and risk score. Enrichment analysis revealed that driver genes were involved in regulating oncogenic processes, including the cell cycle and metabolic pathways, which were associated with the progression of HCC. ssGSEA and xCell showed differences in immune infiltration and the immune microenvironment between the two risk groups.

Conclusion

The 4-driver gene signature is closely associated with the survival prediction of HCC and is expected to provide new insights into targeted therapy for HCC patients.

The Use of ctDNA in the Diagnosis and Monitoring of Hepatocellular Carcinoma-Literature Review

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and is one of the leading causes of cancer-related deaths worldwide. Despite advances in medicine, it is still a cancer with a very poor prognosis. Both imaging and liver biopsy still have important limitations, especially in very small nodules and those which show atypical imaging features. In recent years, liquid biopsy and molecular analysis of tumor breakdown products have become an attractive source of new biomarkers. Patients with liver and biliary malignancies, including hepatocellular carcinoma (HCC), may greatly benefit from ctDNA testing. These patients are often diagnosed at an advanced stage of the disease, and relapses are common. Molecular analysis may indicate the best cancer treatment tailored to particular patients with specific tumor DNA mutations. Liquid biopsy is a minimally invasive technique that facilitates the early detection of cancer. This review summarizes the knowledge of ctDNA in liquid biopsy as an indicator for early diagnosis and monitoring of hepatocellular cancer.

Updating the Clinical Application of Blood Biomarkers and Their Algorithms in the Diagnosis and Surveillance of Hepatocellular Carcinoma: A Critical Review

The most common primary liver cancer is hepatocellular carcinoma (HCC), and its mortality rate is increasing globally. The overall 5-year survival of patients with liver cancer is currently 10-20%. Moreover, because early diagnosis can significantly improve prognosis, which is highly correlated with tumor stage, early detection of HCC is critical. International guidelines advise using α-FP biomarker with/without ultrasonography for HCC surveillance in patients with advanced liver disease. However, traditional biomarkers are sub-optimal for risk stratification of HCC development in high-risk populations, early diagnosis, prognostication, and treatment response prediction. Since about 20% of HCCs do not produce α-FP due to its biological diversity, combining α-FP with novel biomarkers can enhance HCC detection sensitivity. There is a chance to offer promising cancer management methods in high-risk populations by utilizing HCC screening strategies derived from new tumor biomarkers and prognostic scores created by combining biomarkers with distinct clinical parameters. Despite numerous efforts to identify molecules as potential biomarkers, there is no single ideal marker in HCC. When combined with other clinical parameters, the detection of some biomarkers has higher sensitivity and specificity in comparison with a single biomarker. Therefore, newer biomarkers and models, such as the Lens culinaris agglutinin-reactive fraction of Alpha-fetoprotein (α-FP), α-FP-L3, Des-γ-carboxy-prothrombin (DCP or PIVKA-II), and the GALAD score, are being used more frequently in the diagnosis and prognosis of HCC. Notably, the GALAD algorithm was effective in HCC prevention, particularly for cirrhotic patients, regardless of the cause of their liver disease. Although the role of these biomarkers in surveillance is still being researched, they may provide a more practical alternative to traditional imaging-based surveillance. Finally, looking for new diagnostic/surveillance tools may help improve patients' survival. This review discusses the current roles of the most used biomarkers and prognostic scores that may aid in the clinical management of HCC patients.

Construction and comprehensive analysis of a novel prognostic signature associated with pyroptosis molecular subtypes in patients with pancreatic adenocarcinoma

Background

Treatment of cancer with pyroptosis is an emerging strategy. Molecular subtypes based on pyroptosis-related genes(PRGs) seem to be considered more conducive to individualized therapy. It is meaningful to construct a pyroptosis molecular subtypes-related prognostic signature (PMSRPS) to predict the overall survival (OS) of patients with pancreatic adenocarcinoma(PAAD) and guide treatment.

Methods

Based on the transcriptome data of 23 PRGs, consensus clustering was applied to divide the TCGA and GSE102238 combined cohort into three PRGclusters. Prognosis-related differentially expressed genes(DEGs) among PRGclusters were subjected to LASSO Cox regression analysis to determine a PMSRPS. External cohort and in vitro experiments were conducted to verify this PMSRPS. The CIBERSORT algorithm, the ESTIMATE algorithm and the Immunophenoscore (IPS) were used to analyze the infiltrating abundance of immune cells, the tumor microenvironment (TME), and the response to immunotherapy, respectively. Wilcoxon analysis was used to compare tumor mutational burden (TMB) and RNA stemness scores (RNAss) between groups. RT-qPCR and in vitro functional experiments were used for evaluating the expression and function of SFTA2.

Results

Based on three PRGclusters, 828 DEGs were obtained and a PMSRPS was subsequently constructed. In internal and external validation, patients in the high-risk group had significantly lower OS than those in the low-risk group and PMSRPS was confirmed to be an independent prognostic risk factor for patients with PAAD with good predictive performance. Immune cell infiltration abundance and TME scores indicate patients in the high-risk group have typical immunosuppressive microenvironment characteristics. Analysis of IPS suggests patients in the high-risk group responded better to novel immune checkpoint inhibitors (ICIs) than PD1/CTLA4. The high-risk group had higher TMB and RNAss. In addition, 10 potential small-molecule compounds were screened out. Finally, we found that the mRNA expression of SFTA2 gene with the highest risk coefficient in PMSRPS was significantly higher in PAAD than in paracancerous tissues, and knockdown of it significantly delayed the progression of PAAD.

Conclusions

PMSRPS can well predict the prognosis, TME and immunotherapy response of patients with PAAD, identify potential drugs, and provide treatment guidance based on individual needs.

Integrated analysis of transcriptomics and metabolomics in human hepatocellular carcinoma HepG2215 cells after YAP1 knockdown

Yes-associated protein 1 (YAP1) plays a critical role in hepatocellular carcinoma (HCC). Inhibition of YAP1 expression suppresses HCC progression, but the underlying mechanism is still unclear. In this study, we studied the effects and molecular mechanisms of YAP1 knockdown on the growth and metabolism in human HCC HepG2215 cells. Inhibition of YAP1 expression inhibits the proliferation and metastasis in HepG2215 cells, and differentially expressed genes (DEGs) and metabolites were identified in shYAP1-HepG2215 cells. Further, 805 DEGs, mainly associated with metabolism and particularly lipid metabolism, were identified by transcriptome sequencing analyses in shYAP1-HepG2215 cells. YAP1 knockdown increased albumin (ALB) levels by Protein-protein interaction (PPI) network analyses in HepG2215 cells. Metabolomic profiling identified 37 metabolites with significant differences in the shYAP1 group, and amino acid metabolism generally decreased in the shYAP1 group. Comprehensive analysis of transcriptomics and metabolomics revealed that the ATP-binding cassette (ABC) transporters play a central role after YAP1 knockdown in HepG2215 cells. Therefore, YAP1 knockdown inhibited HCC growth, which affected the metabolism of lipids and amino acids by regulating the expression of ALB and ABC transporters in HepG2215 cells.

N6-methyladenosine methylation-related genes YTHDF2, METTL3, and ZC3H13 predict the prognosis of hepatocellular carcinoma patients

Background

Hepatocellular carcinoma (HCC) is a common primary malignant tumor and cause of cancer-related death in humans. Increasing evidence indicates that an imbalance in N6-methyladenosine (m6A) methylation is strongly linked to the occurrence and development of cancer. We used comprehensive bioinformatics to establish a potential prognostic model of HCC based on m6A methylation-related genes. And case analyses were used to verify the results.

Methods

The clinical data and gene expressions were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The prognostic value of m6A methylation-related genes in HCC patients and their relationship with the immune microenvironment were explored by comprehensive bioinformatics analyses. We also collected pathological specimens from 70 patients with HCC from the Department of Pathology, Affiliated Hospital of Qingdao University, and performed immunohistochemical staining on the specimens. We compared tumor specimens from 27 patients positive for METTL3, YTHDF2, and ZC3H13 staining with their adjacent normal tissues and against 27 patient specimens negative for METTL3, YTHDF2, and ZC3H13. The influence of METTL3, YTHDF2, and ZC3H13 on survival was analyzed, and the prognostic model for METTL3, YTHDF2, and ZC3H13 in HCC was verified by clinical data.

Results

Most m6A methylation-related genes showed significantly different expressions between cancer and normal tissues. Three candidate m6A methylation-related genes (YTHDF2, METTL3, and ZC3H13) were significantly correlated with the overall survival (OS) of HCC patients. A Kaplan-Meier survival analysis indicated a worse prognosis of high-risk patients than that of low-risk patients. Immunological analysis showed that the high-risk group was more likely to have higher follicular helper T cell counts and lower resting memory CD4 T cell counts. The expression of YTHDF2, METTL3, and ZC3H13 was validated by other databases, including the Oncomine database, the Human Protein Atlas (HPA), and the Kaplan-Meier plotter.

Conclusions

Our prognostic model based on m6A methylation-related genes effectively predicted the prognosis of HCC patients.

A cellular senescence-related classifier based on a tumorigenesis- and immune infiltration-guided strategy can predict prognosis, immunotherapy response, and candidate drugs in hepatocellular carcinoma

BACKGROUND

Cellular senescence plays an irreplaceable role in tumorigenesis, progression, and tumor microenvironment (TME) remodeling. However, to date, there is limited research delineating the landscape of cellular senescence in hepatocellular carcinoma (HCC), and an improved understanding on the interaction of tumor-associated cellular senescence with HCC prognosis, TME, and response to immunotherapy is warrant.

METHODS

Tumorigenic and immune infiltration-associated senescence genes were determined by weighted gene co-expression network analysis (WGCNA) and the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm, and subsequently, a prognostic scoring model (named TIS) was constructed using multiple survival analysis algorithms to classify the senescence-related subtypes of HCC. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were conducted to identify the distinct hallmark pathways between high- and low-risk subtypes. Additionally, we carried out correlation analyses for TIS and clinical traits, senescence-associated secretory phenotype (SASP), immune infiltration and evasion, immune checkpoint factors, drug response, and immunotherapeutic efficacy. External experimental validation was conducted to delineate the association of CPEP3 (a TIS gene) with HCC phenotypes through assays of proliferation, colony formation, and invasion.

RESULTS

A five-gene TIS, composed of NET1, ATP6V0B, MMP1, GTDC1, and CPEB3, was constructed and validated using TCGA and ICGC datasets, respectively, and showed a highly robust and plausible signature for overall survival (OS) prediction of HCC in both training and validation cohorts. Patients in the TIS-high group were accompanied by worse OS, activation of carcinogenetic pathways, infiltration of immunosuppressive cells, exclusion of effector killing cells, overexpression of immunomodulatory genes and SASP, and unsatisfied response to immunotherapy. In response to anticancer drugs, patients in the TIS-high group exhibited enhanced susceptibility to several conventional chemotherapeutic agents (5-fluorouracil, docetaxel, doxorubicin, gemcitabine, and etoposide), as well as several inhibitors of pathways involved in cellular senescence (cell-cycle inhibitors, bromodomain and extraterminal domain family (BET) inhibitors, PI3K-AKT pathway inhibitors, and multikinase inhibitors). Additionally, four putative drugs (palbociclib, JAK3 inhibitor VI, floxuridine, and lestaurtinib) were identified as potential compounds for patients in the TIS-high group. Notably, in vitro functional validation showed that CPEB3 knockdown boosted the phenotypes of proliferation, clonogenicity, and invasion in HCC cells, whereas CPEB3 overexpression attenuated these phenotypes.

CONCLUSIONS

Our study provides comprehensive clues demonstrating the role of novel TIS in predicting HCC prognosis, immunotherapeutic response, and candidate drugs. This work highlights the significance of tumorigenesis- and immune infiltration-related cellular senescence in cancer therapy.

Mutational and transcriptional alterations and clinicopathological factors predict the prognosis of stage I hepatocellular carcinoma

Background

The prognosis of hepatocellular carcinoma (HCC) has been extensively studied. However, the impact on prognosis of stage I HCC has not been well studied at clincopathological, mutational and transcriptional levels.

Methods

Here we first characterized the influencing factors of prognosis of stage I HCC patients by downloading and analyzing the whole-exome somatic mutation data, messenger ribonucleic acid (mRNA) transcription data, along with demographic and clinical information of 163 stage I HCC patients from the TCGA database. The relationship between the influencing factors and HCC prognosis was studied in detail, and a prediction Nomogram model was established. Figures and tables were plotted using the R software.

Results

TP53, CTNNB1, TTN, MUC16 and ALB were the top mutated genes in stage I HCC. A series of co-mutations and mutually exclusive mutations were identified. Twenty-nine genes with significant stratification on prognosis were identified, including highly mutated LRP1B, ARID1A and PTPRQ. Patients with wild type (WT) genes unanimously exhibited significantly better overall survival rate than those with mutants. Patients with the top 10% tumor mutational burden (TMB) exhibited significantly worse prognosis than the rest 90%. Further characterization of transcriptional profile revealed that membrane functions, cell skeleton proteins, ion channels, receptor function and cell cycle were comprehensively altered in stage I HCC. Univariate and multivariate analyses were performed at clinicopathological, mutational and transcriptional levels. The combined analysis revealed sex, race, TMB, neoplasm histologic grade, Child–Pugh grade, MMRN1, OXT and COX6A2 transcription as independent risk factors. These factors were used to establish a Nomogram model to predict the prognosis of individual HCC patients.

Conclusions

The influencing factors of prognosis of stage I HCC have been characterized for the first time at clinicopathological, mutational and transcriptional levels. A Nomogram model has been established to predict the prognosis. Further validation is needed to confirm the effectiveness and reliability of the model.

Identification of chromosomal instability-associated genes as hepatocellular carcinoma progression-related biomarkers to guide clinical diagnosis, prognosis and therapy

Hepatocellular carcinoma (HCC) is a type of cancer characterized by high heterogeneity and a complex multistep progression process. Significantly-altered biomarkers for HCC need to be identified. Differentially expressed genes and weighted gene co-expression network analyses were used to identify progression-related biomarkers. LASSO-Cox regression and random forest algorithms were used to construct the progression-related prognosis (PRP) score. Three chromosomal instability-associated genes (KIF20A, TOP2A, and TTK) have been identified as progression-related biomarkers. The robustness of the PRP scores were validated using four independent cohorts. Immune status was observed using the single-sample gene set enrichment analysis (ssGSEA). Comprehensive analysis showed that the patients with high PRP score had wider genomic alterations, more malignant phenotypes, and were in a state of immunosuppression. The diagnostic models constructed via logistic regression based on the three genes showed satisfactory performances in distinguishing HCC from cirrhotic tissues or dysplastic nodules. The nomogram combining PRP scores with clinical factors had a better performance in predicting prognosis than the tumor node metastasis classification (TNM) system. We further confirmed that KIF20A, TOP2A, and TTK were highly expressed in HCC tissues than in cirrhotic tissues. Downregulation of all three genes aggravated chromosomal instabilities in HCC and suppressed HCC cells viability both in vitro and in vivo. Overall, our study highlights the important roles of chromosomal instability-associated genes during the progression of HCC and their potential clinical diagnosis and prognostic value and provides promising new ideas for developing therapeutic strategies to improve the outcomes of HCC patients.

Eukaryotic Translation Initiation Factor 5A Independently Predicts Poor Prognosis of Cholangiocarcinoma Patients and Regulates the Ferroptosis and Mitochondrial Apoptosis

Cholangiocarcinoma (CCA) is a hepatobiliary carcinoma characterized by the differentiation of bile duct cells, and the patients with CCA often have a poor prognosis. Eukaryotic translation initiation factor 5A (eIF5A) is reported to have multiple biological activities. Targeted activation of ferroptosis may be a therapeutic strategy for cancer. Nevertheless, the effects of eIF5A and ferroptosis on CCA are still elucidated. Our study explored the effects of eIF5A in CCA, and the mechanisms also are studied. In this paper, TCGA database analysis suggested that eIF5A was upregulated in CCA, and high expression of eIF5A might predict a poor prognosis. Moreover, FANCD2, SLC7A11, and HSPB1 were significantly overexpressed in CCA. The results indicated that eIF5A was overexpressed in CCA tissues and cells. Further experiments demonstrated that eIF5A silencing decreased CCA cell activity and enhanced ferroptosis and mitochondrial apoptosis. In addition, upregulation of eIF5A showed the opposite effect on CCA cells compared with downregulation of eIF5A. Finally, the silencing of eIF5A could restrain the growth of xenografted tumors and promote ferroptosis. Overall, eIF5A enlarged CCA cell activity and attenuated ferroptosis and mitochondrial apoptosis. The results suggested that assessment of eIF5A might provide help for the diagnosis and treatment of CCA.

Comprehensive analysis of metabolic pathway activity subtypes derived prognostic signature in hepatocellular carcinoma

OBJECTIVE

Metabolic reprogramming is one of the hallmarks of cancer, but metabolic pathway activity-related subtypes of hepatocellular carcinoma (HCC) have not been identified.

METHODS

Based on the quantification results of 41 metabolic pathway activities by gene set variation analysis, the training cohort (n = 609, merged by TCGA and GSE14520) was clustered into three subtypes (C1, C2, and C3) with the nonnegative matrix factorization method. Totally 1371 differentially expressed genes among C1, C2, and C3 were identified, and an 8-gene risk score was established by univariable Cox regression analysis, least absolute shrinkage and selection operator method, and multivariable Cox regression analysis.

RESULTS

C1 had the strongest metabolic activity, good prognosis, the highest CTNNB1 mutation rate, with massive infiltration of eosinophils and natural killer cells. C2 had the weakest metabolic activity, poor prognosis, was younger, was inclined to vascular invasion and advanced stage, had the highest TP53 mutation rate, exhibited a higher expression level of immune checkpoints, accompanied by massive infiltration of regulatory T cells. C3 had moderate metabolic activity and prognosis, the highest LRP1B mutation rate, and a higher infiltration level of neutrophils and macrophages. Internal cohorts (TCGA, n = 370; GSE14520, n = 239), external cohorts (ICGC, n = 231; GSE116174, n = 64), and clinical subgroup validation showed that the risk score was applicable for patients with diverse clinical features and was effective in predicting the prognosis and malignant progression of patients with HCC. Compared with the low-risk group, the high-risk group had a poor prognosis, enhanced cancer stem cell characteristics, activated DNA damage repair, weakened metabolic activity, cytolytic activity, and interferon response.

CONCLUSION

We identified HCC subtypes from the perspective of metabolism-related pathway activity and proposed a robust prognostic signature for HCC.

Early detection of hepatocellular carcinoma: roadmap for improvement

INTRODUCTION

Hepatocellular carcinoma (HCC) has a poor prognosis, related, in part, to frequent late-stage diagnosis. Improved implementation of effective HCC surveillance is critical to reduce HCC mortality.

AREAS COVERED

We performed a targeted literature review to identify intervention targets for improving HCC surveillance effectiveness, including enriched risk stratification tools, improved surveillance tools with higher accuracy for early HCC detection, and increasing surveillance adherence.

EXPERT OPINION

HCC surveillance has been demonstrated to be efficacious in several cohort studies but has lower surveillance effectiveness in clinical practice. HCC surveillance is currently recommended in all patients with cirrhosis, and improved risk stratification using clinical risk scores, genetic scores, and novel biomarkers are important to move from a 'one-size-fits-all' strategy to one more aligned with values of precision medicine. Current surveillance modalities, ultrasound, and AFP, miss over one-third of HCC at an early stage and are associated with potential surveillance harms, underscoring a need for alternative surveillance strategies with higher accuracy. MRI- and biomarker-based surveillance strategies have promising early data in phase II studies but require validation in phase III cohorts before routine use in practice. Finally, surveillance is underused in clinical practice, highlighting a need for intervention strategies to increase utilization.

Identification and Validation of a GPX4-Related Immune Prognostic Signature for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a commonly occurring histological subtype of lung cancer. Glutathione peroxidase 4 (GPX4) is an important regulatory factor of ferroptosis and is involved in the development of many cancers, but its prognostic significance has not been systematically described in LUAD. In this study, we focused on developing a robust GPX4-related prognostic signature (GPS) for LUAD. Data for the training cohort was extracted from The Cancer Genome Atlas, and that for the validation cohort was sourced from the GSE72094 dataset including 863 LUAD patients. GPX4-related genes were screened out by weighted gene coexpression network analysis and Spearman’s correlation analysis. Then, Cox regression and least absolute shrinkage and selection operator regression analyses were employed to construct a GPS. The ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and GSEA were utilized to evaluate the relationship between GPS and the tumor microenvironment (TME). We constructed and validated a GPS premised on four GPX4-related genes (KIF14, LATS2, PRKCE, and TM6SF1), which could classify LUAD patients into low- and high-score cohorts. The high-risk cohort presented noticeably poorer overall survival (OS) as opposed to the low-risk cohort, meaning that the GPS may be utilized as an independent predictor of the OS of LUAD. The GPS was also adversely correlated with multiple tumor-infiltrating immune cells and immune-related processes and pathways in TME. Furthermore, greater sensitivity to erlotinib and lapatinib were identified in the low-risk cohort based on the GDSC database. Our findings suggest that the GPS can effectively forecast the prognosis of LUAD patients and may possibly regulate the TME of LUAD.

Identification of a Tumor Immunological Phenotype-Related Gene Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the predominant subtype of primary liver cancer and represents a highly heterogeneous disease, making it hard to predict the prognosis and therapy efficacy. Here, we established a novel tumor immunological phenotype-related gene index (TIPRGPI) consisting of 11 genes by Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) algorithm to predict HCC prognosis and immunotherapy response. TIPRGPI was validated in multiple datasets and exhibited outstanding performance in predicting the overall survival of HCC. Multivariate analysis verified it as an independent predictor and a TIPRGPI-integrated nomogram was constructed to provide a quantitative tool for clinical practice. Distinct mutation profiles, hallmark pathways, and infiltration of immune cells in tumor microenvironment were shown between the TIPRGPI high and low-risk groups. Notably, significant differences in tumor immunogenicity and tumor immune dysfunction and exclusion (TIDE) were observed between the two risk groups, suggesting a better response to immune checkpoint blockade (ICB) therapy of the low-risk group. Besides, six potential drugs binding to the core target of the TIPRGPI signature were predicted via molecular docking. Taken together, our study shows that the proposed TIPRGPI was a reliable signature to predict the risk classification, immunotherapy response, and drugs candidate with potential application in the clinical decision and treatment of HCC. The novel “TIP genes”-guided strategy for predicting the survival and immunotherapy efficacy, we reported here, might be also applied to more cancers other than HCC.

Targeting Wnt/β-Catenin Pathways in Primary Liver Tumours: From Microenvironment Signaling to Therapeutic Agents

Primary liver cancers (PLCs) are steadily increasing in incidence and mortality in the world. They have a poor prognosis due to their silent nature, late discovery and resistance to common chemotherapy. At present, there are limited treatment alternatives, and the understanding of PLC molecular aspects is essential to develop more efficient drugs and therapeutic surgical and loco-regional strategies. A clear causal link with liver damage, inflammation, and regeneration has been found in the occurrence of PLC over the last few decades. Physiologically, Wingless/It (Wnt)-β-catenin signaling plays a key role in liver development, metabolic zonation and regeneration. Loss of functional homeostasis of this pathway appears to be a major driver of carcinogenesis in the liver parenchyma. In the hepatic microenvironment, molecular deregulations that exceed the Wnt signaling biological capacity can induce tumor initiation and progression. Indeed, somatic mutations are identified in key components of canonical and non-canonical Wnt signaling and in PLCs and precancerous lesions. In this review, the altered functions of Wnt/β-catenin signaling are considered in human PLCs, with emphasis on hepatocellular carcinomas (HCC), cholangiocarcinomas (CCA) and hepatoblastomas (HB). Based on recent literature, we also focused on liver cancerogenesis through Wnt deregulation. An overview of preclinical and clinical studies on approved and experimental drugs, targeting the Wnt/β-catenin cascade in PLCs, is proposed. In addition, the clinical implication of molecule inhibitors that have been shown to possess activity against the Wnt pathway in association with conventional surgical and loco-regional therapies are reviewed.

The clinical relevance of epithelial-mesenchymal transition and its correlations with tumorigenic immune infiltrates in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a cancer with extremely high mortality. Epithelial-mesenchymal transition (EMT) may play an important role in the occurrence, invasion, and prognosis of HCC; however, its relationship with immunity in HCC has not yet been studied. Therefore, we investigated the diagnostic and prognostic values of EMT and explored its potential connections with tumorigenic immune infiltrates in HCC. We first proposed a quantitative metric of EMT activity, the EMT score. After applying this metric to 20 datasets from the Integrative Molecular Database of Hepatocellular Carcinoma, The Cancer Genome Atlas, and the Gene Expression Omnibus, we explored the ability of the EMT score to stratify across sample types. We then applied the EMT score for survival analysis and to differentiate patients with/without vascular invasion to test its prognostic value. We also collected and calculated data on the abundance of immune cells and immune cell markers in HCC and investigated their correlations with EMT scores. Finally, we synthesized and analyzed 20 datasets and constructed an EMT-gene-immune linkage network. The results showed higher EMT scores in HCC samples than in cirrhotic and normal livers. The cases with higher EMT scores also showed poorer performance in terms of prognostic factors such as vascular invasion and overall survival time. Our research demonstrated a broad correlation between EMT and the tumor immune microenvironment, and we uncovered multiple potential linkers associated with both EMT and immunity. Studying EMT has clinical relevance and high diagnostic and prognostic value for HCC.

A Five-Gene Signature Associated With DNA Damage Repair Molecular Subtype Predict Overall Survival for Hepatocellular Carcinoma

Background: DNA damage repair (DDR) is an important mechanism for the occurrence and development of hepatocellular carcinoma (HCC), but its impact on prognosis has not been fully understood.

Materials and methods: A total of 904 HCC patients were included in our study, TCGA (n = 370) and GSE14520 (n = 239) were merged into a large-sample training cohort (n = 609). The training cohort was clustered into C1 and C2 based on prognostic DDR-related genes, the differentially expressed genes (DEGs) between C1 and C2 were identified by the Wilcoxon signed-rank test referred to criteria (|log2FC|≥1 and FDR< 0.05). The univariate Cox analysis was used to screen the prognostic-related DEGs, and Lasso penalized Cox regression analysis was used to construct the risk score. The patients were clarified into high- and low-risk groups based on the median risk score. ICGC (n = 231) and GSE116174 (n = 64) cohorts were used for external validation of the risk score’s prognostic value.

Results: The Kaplan–Meier survival analysis showed that the high-risk group had a significantly reduced overall survival (OS) compared to the low-risk group in the three independent cohorts, and the time-dependent ROC curve showed that the five-gene (STMN1, PON1, PLOD2, MARCKSL1, and SPP1) risk score with a high accuracy in predicting OS. The patients with AFP >300 ng/ml, tumor poor differentiation (grade 3–4), micro and macro vascular tumor invasion, advanced stage (AJCC III-IV, BCLC stage B-C, and CLIP score >2) exhibited a higher risk score. Subgroup survival analysis found that the risk score was applicable to patients with different clinical characteristics. GO and KEGG functional enrichment analysis revealed that cell cycle, p53 signaling, TNF signaling-related pathways were upregulated in the high-risk group. The higher infiltration level of activated CD4 T cell, CD56 bright natural killer cell, plasmacytoid dendritic cell, and type 2 T helper cells were found to lead an unfavorable impact on the OS of HCC patients, and these four kinds of immune cells exhibited a higher infiltration level in the high-risk group.

Conclusion: The five-gene risk score proposed in the research may provide new insights into the individualized evaluation of HCC prognosis.

A Ferroptosis and Pyroptosis Molecular Subtype-Related Signature Applicable for Prognosis and Immune Microenvironment Estimation in Hepatocellular Carcinoma

Background: Due to the heterogeneity of tumors and the complexity of the immune microenvironment, the specific role of ferroptosis and pyroptosis in hepatocellular carcinoma (HCC) is not fully understood, especially its impact on prognosis.

Methods: The training set (n = 609, merged by TCGA and GSE14520) was clustered into three subtypes (C1, C2, and C3) based on the prognosis-related genes associated with ferroptosis and pyroptosis. The intersecting differentially expressed genes (DEGs) among C1, C2, and C3 were used in univariate Cox and LASSO penalized Cox regression analysis for the construction of the risk score. The median risk score served as the unified cutoff to divide patients into high- and low-risk groups.

Results: Internal (TCGA, n = 370; GSE14520, n = 239) and external validation (ICGC, n = 231) suggested that the 12-gene risk score had high accuracy in predicting the OS, DSS, DFS, PFS, and RFS of HCC. As an independent prognostic indicator, the risk score could be applicable for patients with different clinical features tested by subgroup (n = 26) survival analysis. In the high-risk patients with a lower infiltration abundance of activated B cells, activated CD8 T cells, eosinophils, and type I T helper cells and a higher infiltration abundance of immature dendritic cells, the cytolytic activity, HLA, inflammation promotion, and type I IFN response in the high-risk group were weaker. The TP53 mutation rate, TMB, and CSC characteristics in the high-risk group were significantly higher than those in the low-risk group. Low-risk patients have active metabolic activity and a more robust immune response. The high- and low-risk groups differed significantly in histology grade, vascular tumor cell type, AFP, new tumor event after initial treatment, main tumor size, cirrhosis, TNM stage, BCLC stage, and CLIP score.

Conclusion: The ferroptosis and pyroptosis molecular subtype-related signature identified and validated in this work is applicable for prognosis prediction, immune microenvironment estimation, stem cell characteristics, and clinical feature assessment in HCC.

Construction and Validation of a Universal Applicable Prognostic Signature for Gastric Cancer Based on Seven Immune-Related Gene Correlated With Tumor Associated Macrophages

Background

Tumor-associated macrophages (TAMs) play a critical role in the progression of malignant tumors, but the detailed mechanism of TAMs in gastric cancer (GC) is still not fully explored.

Methods

We identified differentially expressed immune-related genes (DEIRGs) between GC samples with high and low macrophage infiltration in The Cancer Genome Atlas datasets. A risk score was constructed based on univariate Cox analysis and Lasso penalized Cox regression analysis in the TCGA cohort (n=341). The optimal cutoff determined by the 5-year time-dependent receiver operating characteristic (ROC) curve was considered to classify patients into groups with high and low risk. We conducted external validation of the prognostic signature in four independent cohorts (GSE84437, n=431; GSE62254, n=300; GSE15459, n=191; and GSE26901, n=109) from the Gene Expression Omnibus (GEO) database.

Results

The signature consisting of 7 genes (FGF1, GRP, AVPR1A, APOD, PDGFRL, CXCR4, and CSF1R) showed good performance in predicting overall survival (OS) in the 5 independent cohorts. The risk score presented an obviously positive correlation with macrophage abundance (cor=0.7, p<0.001). A significant difference was found between the high- and low-risk groups regarding the overall survival of GC patients. The high-risk group exhibited a higher infiltration level of M2 macrophages estimated by the CIBERSORT algorithm. In the five independent cohorts, the risk score was highly positively correlated with the stromal cell score, suggesting that we can also evaluate the infiltration of stromal cells in the tumor microenvironment according to the risk score.

Conclusion

Our study developed and validated a general applicable prognostic model for GC from the perspective of TAMs, which may help to improve the precise treatment strategy of GC.

Development and Validation of a Novel Metabolic-Related Signature Predicting Overall Survival for Pancreatic Cancer

Recently, growing evidence has revealed the significant effect of reprogrammed metabolism on pancreatic cancer in relation to carcinogenesis, progression, and treatment. However, the prognostic value of metabolism-related genes in pancreatic cancer has not been fully revealed. We identified 379 differentially expressed metabolic-related genes (DEMRGs) by comparing 178 pancreatic cancer tissues with 171 normal pancreatic tissues in The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression project (GTEx) databases. Then, we used univariate Cox regression analysis together with Lasso regression for constructing a prognostic model consisting of 15 metabolic genes. The unified risk score formula and cutoff value were taken into account to divide patients into two groups: high risk and low risk, with the former exhibiting a worse prognosis compared with the latter. The external validation results of the International Cancer Genome Consortium (IGCC) cohort and the Gene Expression Omnibus (GEO) cohort further confirm the effectiveness of this prognostic model. As shown in the receiver operating characteristic (ROC) curve, the area under curve (AUC) values of the risk score for overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) were 0.871, 0.885, and 0.886, respectively. Based on the Gene Set Enrichment Analysis (GSEA), the 15-gene signature can affect some important biological processes and pathways of pancreatic cancer. In addition, the prognostic model was significantly correlated with the tumor immune microenvironment (immune cell infiltration, and immune checkpoint expression, etc.) and clinicopathological features (pathological stage, lymph node, and metastasis, etc.). We also built a nomogram based on three independent prognostic predictors (including individual neoplasm status, lymph node metastasis, and risk score) for the prediction of 1-, 3-, and 5-year OS of pancreatic cancer, which may help to further improve the treatment strategy of pancreatic cancer.

Development and Validation of a Robust Immune-Related Prognostic Signature for Gastric Cancer

Background

An increasing number of reports have found that immune-related genes (IRGs) have a significant impact on the prognosis of a variety of cancers, but the prognostic value of IRGs in gastric cancer (GC) has not been fully elucidated.

Methods

Univariate Cox regression analysis was adopted for the identification of prognostic IRGs in three independent cohorts (GSE62254, n = 300; GSE15459, n = 191; and GSE26901, n = 109). After obtaining the intersecting prognostic genes, the three independent cohorts were merged into a training cohort (n = 600) to establish a prognostic model. The risk score was determined using multivariate Cox and LASSO regression analyses. Patients were classified into low-risk and high-risk groups according to the median risk score. The risk score performance was validated externally in the three independent cohorts (GSE26253, n = 432; GSE84437, n = 431; and TCGA, n = 336). Immune cell infiltration (ICI) was quantified by the CIBERSORT method.

Results

A risk score comprising nine genes showed high accuracy for the prediction of the overall survival (OS) of patients with GC in the training cohort (AUC > 0.7). The risk of death was found to have a positive correlation with the risk score. The univariate and multivariate Cox regression analyses revealed that the risk score was an independent indicator of the prognosis of patients with GC (p < 0.001). External validation confirmed the universal applicability of the risk score. The low-risk group presented a lower infiltration level of M2 macrophages than the high-risk group (p < 0.001), and the prognosis of patients with GC with a higher infiltration level of M2 macrophages was poor (p = 0.011). According to clinical correlation analysis, compared with patients with the diffuse and mixed type of GC, those with the Lauren classification intestinal GC type had a significantly lower risk score (p = 0.00085). The patients' risk score increased with the progression of the clinicopathological stage.

Conclusion

In this study, we constructed and validated a robust prognostic signature for GC, which may help improve the prognostic assessment system and treatment strategy for GC.

Eleven immune-gene pairs signature associated with TP53 predicting the overall survival of gastric cancer: a retrospective analysis of large sample and multicenter from public database

Background

Growing attention have been paid to the relationship between TP53 and tumor immunophenotype, but there are still lacking enough search on the field of gastric cancer (GC).

Materials and methods

We identified differential expressed immune-related genes (DEIRGs) between the TP53-altered GC samples (n = 183) and without TP53-altered GC samples (n = 192) in The Cancer Genome Atlas and paired them. In the TCGA cohort (n = 350), a risk score was determined through univariate and multivariate cox regression and Lasso regression analysis. Patients were divided into two groups, high-risk and low-risk, based on the median risk score. Four independent cohorts (GSE84437,n = 431; GSE62254, n = 300; GSE15459, n = 191; GSE26901, n = 100) from the Gene Expression Omnibus (GEO) database were used to validate the reliability and universal applicability of the model.

Results

The signature contained 11 gene pairs showed good performance in predicting progression-free survival (PFS), disease-free survival (DFS), disease special survival (DSS), and the overall survival (OS) for GC patients in the TCGA cohort. The subgroup analysis showed that the signature was suitable for GC patients with different characteristics. The signature could capable of distinguish GC patients with good prognosis and poor prognosis in all four independent external validation cohorts. The high- and low-risk groups differed significantly in the proportion of several immune cell infiltration, especially for the T cells memory resting, T cells memory activated and follicular helper, and Macrophage M0, which was also related to the prognosis of GC patients.

Conclusion

The present work proposed an innovative system for evaluating the prognosis of gastric cancer. Considering its stability and general applicability, which may become a widely used tool in clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02846-x.