Prognosis Of Hepatocellular Carcinoma Patients Research Articles

Plexin domain-containing 1 may be a biomarker of poor prognosis in hepatocellular carcinoma patients, may mediate immune evasion

BACKGROUND For the first time, we investigated the oncological role of plexin domain-containing 1 (PLXDC1 ), also known as tumor endothelial marker 7 (TEM7), in hepatocellular carcinoma (HCC). AIM To investigate the oncological profile of PLXDC1 in HCC. METHODS Based on The Cancer Genome Atlas database, we analyzed the expression of PLXDC1 in HCC. Using immunohistochemistry, quantitative real-time polymerase chain reaction (qRT-PCR), and Western blotting, we validated our results. The prognostic value of PLXDC1 in HCC was analyzed by assessing its correlation with clinicopathological features, such as patient survival, methylation level, tumor immune microenvironment features, and immune cell surface checkpoint expression. Finally, to assess the immune evasion potential of PLXDC1 in HCC, we used the tumor immune dysfunction and exclusion (TIDE) website and immunohistochemical staining assays. RESULTS Based on immunohistochemistry, qRT-PCR, and Western blot assays, overexpression of PLXDC1 in HCC was associated with poor prognosis. Univariate and multivariate Cox analyses indicated that PLXDC1 might be an independent prognostic factor. In HCC patients with high methylation levels, the prognosis was worse than in patients with low methylation levels. Pathway enrichment analysis of HCC tissues indicated that genes upregulated in the high-PLXDC1 subgroup were enriched in mesenchymal and immune activation signaling, and TIDE assessment showed that the risk of immune evasion was significantly higher in the high-PLXDC1 subgroup compared to the low-PLXDC1 subgroup. The high-risk group had a significantly lower immune evasion rate as well as a poor prognosis, and PLXDC1 -related risk scores were also associated with a poor prognosis. CONCLUSION As a result of this study analyzing PLXDC1 from multiple biological perspectives, it was revealed that it is a biomarker of poor prognosis for HCC patients, and that it plays a role in determining immune evasion status.

PSMD9 promotes the malignant progression of hepatocellular carcinoma by interacting with c-Cbl to activate EGFR signaling and recycling

BackgroundMounting evidences shows that the ubiquitin‒proteasome pathway plays a pivotal role in tumor progression. The expression of 26S proteasome non-ATPase regulatory subunit 9 (PSMD9) is correlated with recurrence and radiotherapy resistance in several tumor types. However, the role and mechanism of PSMD9 in hepatocellular carcinoma (HCC) progression remain largely unclear.MethodsPSMD9 was identified as a prognosis-related biomarker for HCC based on analysis of clinical characteristics and RNA-seq data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and the JP Project of the International Cancer Genome Consortium (ICGC-LIRI-JP). PSMD9 expression was analyzed in cancer tissues and adjacent noncancerous tissues via immunohistochemistry and Western blotting. Multiple in vivo and in vitro experimental techniques (such as CCK-8, colony formation, EdU, and Transwell assays; flow cytometry; Western blotting; quantitative RT-PCR; Coimmunoprecipitation assay and immunofluorescence confocal imaging) were used to assess the functions of PSMD9 in the pathogenesis of HCC.ResultsWe found that the expression of PSMD9 was upregulated and associated with a poor prognosis in HCC patients. PSMD9 promoted HCC cell proliferation, migration, invasion and metastasis. Knockdown of PSMD9 significantly inhibited HCC cell proliferation by inducing G1/S cell cycle arrest and apoptosis. Mechanistically, we demonstrated that PSMD9 promoted HCC cell proliferation and metastasis via direct interaction with the E3 ubiquitin ligase c-Cbl, suppresses EGFR ubiquitination, influenced EGFR endosomal trafficking and degradation and subsequently activated ERK1/2 and Akt signaling. In addition, we showed that PSMD9 knockdown sensitized HCC cells to the tyrosine kinase inhibitor erlotinib in vitro and in vivo.ConclusionsCollectively, our results indicate that PSMD9 drives HCC progression and erlotinib resistance by suppressing c-Cbl mediated EGFR ubiquitination and therefore can be a potential therapeutic target for HCC.

Estrogen induces LCAT to maintain cholesterol homeostasis and suppress hepatocellular carcinoma development.

Hepatocellular carcinoma (HCC) is an aggressive disease that occurs predominantly in men. Estrogen elicits protective effects against HCC development. Elucidation of the estrogen-regulated biological processes that suppress HCC could lead to improved prevention and treatment strategies. Here, we performed transcriptomic analyses on mouse and human liver cancer and identified LCAT as the most highly estrogen-upregulated gene and a biomarker of favorable prognosis. LCAT upregulation inhibited HCC in vitro and in vivo and mediated estrogen-induced suppression of HCC in an ESR1-dependent manner. LCAT facilitated high-density lipoprotein cholesterol (HDL-C) production and uptake via the LDLR and SCARB1 pathways. Consistently, high HDL-C levels corresponded to a favorable prognosis in HCC patients. The enhanced HDL-C absorption induced by LCAT impaired SREBP2 maturation, which ultimately suppressed cholesterol biosynthesis and dampened HCC cell proliferation. HDL-C alone inhibited HCC growth comparably to the cholesterol-lowering drug lovastatin, and SREBF2 overexpression abolished the inhibitory activity of LCAT. Clinical observations and cross-analyses of multiple databases confirmed the correlation of elevated LCAT and HDL-C levels to reduced cholesterol synthesis and improved HCC patient prognosis. Furthermore, LCAT deficiency mimicked whereas LCAT overexpression abrogated the tumor growth promoting effects of ovariectomy in HCC-bearing female mice. Most importantly, HDL-C and LCAT delayed the development of subcutaneous tumors in nude mice, and HDL-C synergized with lenvatinib to eradicate orthotopic liver tumors. Collectively, this study reveals that estrogen upregulates LCAT to maintain cholesterol homeostasis and dampen hepatocarcinogenesis. LCAT and HDL-C represent potential prognostic and therapeutic biomarkers for targeting cholesterol homeostasis as a strategy for treating HCC.

Tumor Microenvironment-Responsive Nanocapsule Delivery CRISPR/Cas9 to Reprogram the Immunosuppressive Microenvironment in Hepatoma Carcinoma.

Cancer immunotherapy has demonstrated significant efficacy in various tumors, but its effectiveness in treating Hepatocellular Carcinoma (HCC) remains limited. Therefore, there is an urgent need to identify a new immunotherapy target and develop corresponding intervention strategies. Bioinformatics analysis has revealed that growth differentiation factor 15 (GDF15) is highly expressed in HCC and is closely related to poor prognosis of HCC patients. The previous study revealed that GDF15 can promote immunosuppression in the tumor microenvironment. Therefore, knocking out GDF15 through gene editing could potentially reverse the suppressive tumor immune microenvironment permanently. To deliver the CRISPR/Cas9 system specifically to HCC, nanocapsules (SNC) coated with HCC targeting peptides (SP94) on their surface is utilized. These nanocapsules incorporate disulfide bonds (SNCSS) that release their contents in the tumor microenvironment characterized by high levels of glutathione (GSH). In vivo, the SNCSS target HCC cells, exert a marked inhibitory effect on HCC progression, and promote HCC immunotherapy. Mechanistically, CyTOF analysis showed favorable changes in the immune microenvironment of HCC, immunocytes with killer function increased and immunocytes with inhibitive function decreased. These findings highlight the potential of the CRISPR-Cas9 gene editing system in modulating the immune microenvironment and improving the effectiveness of existing immunotherapy approaches for HCC.

Basement membrane-related lncRNA signature for the prognosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the main type of primary liver cancer. This study aimed to develop a basement membrane (BM) related lncRNAs risk signature to evaluate the prognosis of HCC patients. We screened differentially expressed BM-related lncRNAs (DE-BMRlncRNAs) for risk evaluation, and identified six DE-BMRlncRNAs (AC072054.1, NUP50-DT, AC026412.3, AC109322.2, POLH-AS1 and LINC00595) for prognostic risk signature. HCC patients were divided to high or low risk according to median risk score. Our prognostic model predicted that patients with higher risk score had worse prognosis. We also created a nomogram to assist clinical decision-making according to risk score and clinicopathological features. Meanwhile, we confirmed the expression of six lncRNAs in HCC tissue and cells. POLH-AS1 knockdown inhibited the migration and invasion of HCC cells. In conclusion, we established a predictive model based on BMRlncRNAs to predict the prognosis of HCC. Our findings offer a rationale to further explore BM-related biomarkers for HCC.

Which is the best TACE agent for patients with different NLR hepatocellular carcinomas? A systematic review and network meta-analysis

BackgroundTransarterial chemoembolization (TACE) is a common treatment for hepatocellular carcinoma (HCC), but the best therapeutic agent for TACE treatment has not been determined. The neutrophil/lymphocyte ratio (NLR) is a systemic immune system marker; however, the ability of the NLR to predict the prognosis of patients with HCC is unknown, and no studies have been conducted to determine the most appropriate TACE regimen for HCC patients with different NLRs. MethodsThe PubMed, Embase, Web of Science, and CNKI databases were searched through May 28, 2023. Comparisons of overall survival (OS) among cohort studies with different NLRs and different TACE treatment regimens were performed with a random effects model. FindingsThirty-five studies involving 9210 patients were included in this meta-analysis. The results showed that Group 3–4 (NLR<2.5) patients had a significantly longer OS than Group 1–2 (NLR 2.5–5.0). Among the patients, Group 1–3 (NLR 2.0–5.0) patients had the best survival after treatment with adriamycin (lnHR (95 % CI = 0.48 [0.31, 0.75] and lnHR (95 % CI = 0.41 [0.19, 0.91]). Among the Group 4 patients (NLR<2.0), the best outcome was obtained with platinum + adriamycin (lnHR (95 % CI = 0.59 [0.45, 0.78]), followed by adriamycin. A subgroup analysis of TACE combined with other treatments showed that adriamycin combined with sorafenib was the most effective and superior to the other treatment agents. InterpretationThe NLR can be used to predict the prognosis of HCC patients treated with TACE; the higher the NLR is, the worse the prognosis. Adriamycin may be the best therapeutic agent for HCC patients treated with TACE.

Prognostic and Immunotherapeutic Predictive Value of CAD Gene in Hepatocellular Carcinoma: Integrated Bioinformatics and Experimental Analysis.

Hepatocellular carcinoma (HCC) is a common type of cancer that ranks first in cancer-associated death worldwide. Carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD) are the key components of the pyrimidine pathway, which promotes cancer development. However, the function of CAD in HCC needs to be clarified. In this study, the clinical and transcriptome data of 424 TCGA-derived HCC cases were analyzed. The results demonstrated that high CAD expression was associated with poor prognosis in HCC patients. The effect of CAD on HCC was then investigated comprehensively using GO annotation analysis, KEGG enrichment analysis, Gene Set Enrichment Analysis (GSEA), and CIBERSORT algorithm. The results showed that CAD expression was correlated with immune checkpoint inhibitors and immune cell infiltration. In addition, low CAD levels in HCC patients predicted increased sensitivity to anti-CTLA4 and PD1, while HCC patients with high CAD expression exhibited high sensitivity to chemotherapeutic and molecular-targeted agents, including gemcitabine, paclitaxel, and sorafenib. Finally, the results from clinical sample suggested that CAD expression increased remarkably in HCC compared with non-cancerous tissues. Loss of function experiments demonstrated that CAD knockdown could significantly inhibit HCC cell growth and migration both in vitro and in vivo. Collectively, the results indicated that CAD is a potential oncogene during HCC metastasis and progression. Therefore, CAD is recommended as a candidate marker and target for HCC prediction and treatment.

Development of a Better Nomogram for Prediction of Preoperative Microvascular Invasion and Postoperative Prognosis in Hepatocellular Carcinoma Patients: A Comparison Study.

Personalized precision medicine can be facilitated by clinically available preoperative microvascular invasion (MVI) prediction models that are reliable and postoperative MVI pathological grade-related recurrence prediction models that are accurate. In this study, we aimed to compare different mathematical models to derive the best preoperative prediction and postoperative recurrence prediction models for MVI. A total of 143 patients with hepatocellular carcinoma (HCC) whose clinical, laboratory, imaging, and pathological data were available were included in the analysis. Logistic regression, Cox proportional hazards regression, LASSO regression with 10-fold cross-validation, stepwise regression, and random forest methods were used for variable screening and predictive modeling. The accuracy and validity of seven preoperative MVI prediction models and five postoperative recurrence prediction models were compared in terms of C-index, net reclassification improvement, and integrated discrimination improvement. Multivariate logistic regression analysis revealed that a preoperative nomogram model with the variables cirrhosis diagnosis, alpha-fetoprotein > 400, and diameter, shape, and number of lesions can predict MVI in patients with HCC reliably. Postoperatively, a nomogram model with MVI grade, number of lesions, capsule involvement status, macrovascular invasion, and shape as the variables was selected after LASSO regression and 10-fold cross-validation analysis to accurately predict the prognosis for different MVI grades. The number and shape of the lesions were the most common predictors of MVI preoperatively and recurrence postoperatively. Our study identified the best statistical approach for the prediction of preoperative MVI as well as postoperative recurrence in patients with HCC based on clinical, imaging, and laboratory tests results. This could expedite preoperative treatment decisions and facilitate postoperative management.

Construction of CDKN2A-related competitive endogenous RNA network and identification of GAS5 as a prognostic indicator for hepatocellular carcinoma.

Competitive endogenous RNA (ceRNA) is an innovative way of gene expression modulation, which plays a crucial part in neoplasia. However, the intricacy and behavioral characteristics of the ceRNA network in hepatocellular carcinoma (HCC) remain dismal. To establish a cyclin dependent kinase inhibitor 2A (CDKN2A)-related ceRNA network and recognize potential prognostic indicators for HCC. The mutation landscape of CDKN2A in HCC was first explored using the cBioPortal database. Differential expression analysis was implemented between CDKN2Ahigh and CDKN2Alow expression HCC samples. The targeted microRNAs were predicted by lncBasev3.0, and the targeted mRNAs were predicted by miRDB, and Targetscan database. The univariate and multivariate analysis were utilized to identify independent prognostic indicators. CDKN2A was frequently mutated and deleted in HCC. The single-cell RNA-sequencing analysis revealed that CDKN2A participated in cell cycle pathways. The CDKN2A-related ceRNA network-growth arrest specific 5 (GAS5)/miR-25-3p/SRY-box transcription factor 11 (SOX11) was successfully established. GAS5 was recognized as an independent prognostic biomarker, whose overexpression was correlated with a poor prognosis in HCC patients. The association between GAS5 expression and methylation, immune infiltration was explored. Besides, traditional Chinese medicine effective components targeting GAS5 were obtained. This CDKN2A-related ceRNA network provides innovative insights into the molecular mechanism of HCC formation and progression. Moreover, GAS5 might be a significant prognostic biomarker and therapeutic target in HCC.

Exploration of prognostic and treatment markers in hepatocellular carcinoma via GPCR-related genes analysis

BackgroundG protein-coupled receptors (GPCRs), the biggest family of signaling receptors, account for 34 % of all the drug targets approved by the Food and Drug Administration (FDA). It has been gradually recognized that GPCRs are of significance for tumorigenesis, but in-depth studies are still required to explore specific mechanisms. In this study, the role of GPCRs in hepatocellular carcinoma (HCC) was elucidated, and GPCR-related genes were employed for building a risk-score model for the prognosis and treatment efficacy prediction of HCC patients. MethodsPatients’ data on HCC were sourced from the Liver Hepatocellular Carcinoma-Japan (LIRI-JP) and The Cancer Genome Atlas (TCGA) databases, while GPCR-related genes were obtained from the Molecular Signatures Database (MSigDB). Univariant and multivariant Cox regression analyses, as well as least absolute shrinkage and selection operator (LASSO) were performed with the aim of identifying differentially expressed GPCR-related genes and grouping patients. Differential expression and functional enrichment analyses were performed; protein-protein interaction (PPI) mechanisms were explored; hub genes and micro ribonucleic acid (miRNA)-target gene regulatory networks were constructed. The tumor immune dysfunction and exclusion (TIDE) algorithm was utilized to evaluate immune infiltration levels and genetic variations. Sensitivity to immunotherapy and common antitumor drugs was predicted via the database Genomics of Drug Sensitivity in Cancer (GDSC). ResultsA GPCR-related risk score containing eight GPCR-related genes (atypical chemokine receptor 3 (ACKR3), C–C chemokine receptor type 3 (CCR3), CCR7, frizzled homolog 5 (FZD5), metabotropic glutamate receptor 8 (GRM8), hydroxycarboxylic acid receptor 1 (HCAR1), 5-hydroxytryptamine receptor 5A (HTR5A) and nucleotide-binding oligomerization domain-like receptor family pyrin domain containing 6 (NLRP6)) was set up. In addition, patients were classified into groups with high and low risks. Patients in the high-risk group exhibited a worse prognosis but demonstrated a more favorable immunotherapy response rate compared with those in the low-risk group. Distinct sensitivity to chemotherapeutic drugs was observed. A clinical prediction model on the basis of GPCR-related risk scores was constructed. Areas under the curves (AUC) corresponding to one-, three- and five-year survival were 0.731, 0.765 and 0.731, respectively. ConclusionsIn this study, an efficient HCC prognostic prediction model was constructed by only GPCR-related genes, which are all potential targets for HCC treatment.

Downregulation of GPX8 in hepatocellular carcinoma: impact on tumor stemness and migration.

GPX8, which is found in the endoplasmic reticulum lumen, is a member of the Glutathione Peroxidases (GPXs) family. Its role in hepatocellular carcinoma (HCC) is unknown. Immunohistochemical staining was used to detect the protein levels of GPX8 in HCC tissue microarrays. A short hairpin RNA lentivirus was used to knock down GPX8, and the main signaling pathways were investigated using transcriptome sequencing and a phosphorylated kinase array. The sphere formation assays, cloning-formation assays and cell migration assays were used to evaluate the stemness and migration ability of HCC cells. Identifying the GPX8-interacting proteins was accomplished through immunoprecipitation and protein mass spectrometry. The GPX8 protein levels were downregulated in HCC patients. Low expression of GPX8 protein was related to early recurrence and poor prognosis in HCC patients. GPX8 knockdown could enhance the stemness and migration ability of HCC cells. Consistently, Based on transcriptome analysis, multiple signaling pathways that include the PI3K-AKT and signaling pathways that regulate the pluripotency of stem cells, were activated after GPX8 knockdown. The downregulation of GPX8 could increase the expression of the tumor stemness markers KLF4, OCT4, and CD133. The in vivo downregulation of GPX8 could also promote the subcutaneous tumor-forming and migration ability of HCC cells. MK-2206, which is a small-molecule inhibitor of AKT, could reverse the tumor-promoting effects both in vivo and in vitro. We discovered that GPX8 and the 71-kDa heat shock cognate protein (Hsc70) have a direct interaction. The phosphorylation of AKT encouraged the translocation of Hsc70 into the nucleus and the expression of the PI3K p110 subunit, thereby increasing the downregulation of GPX8. The findings from this study demonstrate the anticancer activity of GPX8 in HCC by inactivating the Hsc70/AKT pathway. The results suggest a possible therapeutic target for HCC.

A preliminary study of optimal treatment response rates in patients undergoing hepatic arterial infusion chemotherapy combined with molecular targeting and immunotherapy.

This study aimed to examine the effectiveness of the best response rate (BRR) as a surrogate for overall survival (OS), using the modified Response Evaluation Criteria in Solid Tumors (mRECIST), in patients with unresectable hepatocellular carcinoma (HCC) undergoing hepatic arterial infusion chemotherapy (HAIC) with fluorouracil, leucovorin, and oxaliplatin (FOLFOX) combined with molecular targeting and immunotherapy. This study enrolled 111 consecutive patients who had complete imaging data. The median age of patients was 58 years (IQR 50.5-65.0). Among the patients, those with Barcelona Clinic Liver Cancer (BCLC) stage A, BCLC stage B, and BCLC stage C comprised 6.4%, 19.1%, and 73.6%, respectively. The optimal threshold of BRR can be determined using restricted cubic splines (RCS) and the rank sum statistics of maximum selection. Survival curves of patients in the high rating and low rating groups were plotted. We then used the change-in-estimate (CIE) method to filter out confounders and the inverse probability of treatment weighting (IPTW) to balance confounders between the two groups to assess the robustness of the results. The median frequency of the combination treatment regimens administered in the overall population was 3 times (IQR 2.0-3.0). The optimal BRR truncation value calculated was -0.2. Based on this value, 77 patients were categorized as the low rating group and 34 as the high rating group. The differences in the OS between the high and low rating groups were statistically significant (7 months [95%CI 6.0-14.0] vs. 30 months [95%CI 30.0-]; p< 0.001). Using the absolute 10% cut-off value, the CIE method was used to screen out the following confounding factors affecting prognosis: successful conversion surgery, baseline tumor size, BCLC stage, serum total bilirubin level, number of interventional treatments, alpha-fetoprotein level, presence of inferior vena cava tumor thrombus, and partial thrombin activation time. The survival curve was then plotted again using IPTW for confounding factors, and it was found that the low rating group continued to have better OS than the high rating group. Finally, the relationship between BRR and baseline factors was analyzed, and inferior vena cava tumor thrombus and baseline tumor size correlated significantly with BRR. BRR can be used as a surrogate endpoint for OS in unresectable HCC patients undergoing FOLFOX-HAIC in combination with molecular targeting and immunotherapy. Thus, by calculating the BRR, the prognosis of HCC patients after combination therapy can be predicted. Inferior vena cava tumor thrombus and baseline tumor size were closely associated with the BRR.

Long-term surgical outcomes of bile duct tumor thrombus versus portal vein tumor thrombus for hepatocellular carcinoma: a propensity score matching analysis.

Portal vein tumor thrombus (PVTT) seriously affects the prognosis of hepatocellular carcinoma (HCC). However, whether bile duct tumor thrombus (BDTT) significantly affects the prognosis of HCC as much as PVTT remains unclear. We aimed to compare the long-term surgical outcomes of HCC with macroscopic PVTT (macro-PVTT) and macroscopic BDTT (macro-BDTT). The data of HCC patients with macro-BDTT or macro-PVTT who underwent hemihepatectomy were retrospectively reviewed. A propensity score matching (PSM) analysis was performed to reduce the baseline imbalance. The recurrence-free survival (RFS) and overall survival (OS) rates were compared between the cohorts. Before PSM, the PVTT group had worse RFS and OS rates than the BDTT group (P = 0.043 and P = 0.008, respectively). Multivariate analyses identified PVTT (hazard ratio [HR] = 1.835, P = 0.016) and large HCC (HR = 1.553, P = 0.039) as independent risk factors for poor OS and RFS, respectively. After PSM, the PVTT group had worse RFS and OS rates than the BDTT group (P = 0.037 and P = 0.004, respectively). The 3- and 5-year OS rates were significantly higher in the BDTT group (59.5% and 52.1%, respectively) than in the PVTT group (33.3% and 20.2%, respectively). Aggressive hemihepatectomy provides an acceptable prognosis for HCC patients with macro-BDTT. Furthermore, the long-term surgical outcomes of HCC patients with macro-BDTT were significantly better than those of HCC patients with macro-PVTT.

A novel anoikis-related gene signature can predict the prognosis of hepatocarcinoma patients.

Hepatocellular carcinoma (HCC) is a major health problem with more than 850,000 cases per year worldwide. This cancer is now the third leading cause of cancer-related deaths worldwide, and the number is rising. Cancer cells develop anoikis resistance which is a vital step during cancer progression and metastatic colonization. However, there is not much research that specifically addresses the role of anoikis in HCC, especially in terms of prognosis. This study obtained gene expression data and clinical information from 371 HCC patients through The Cancer Genome Atlas (TCGA) Program and The Gene Expression Omnibus (GEO) databases. A total of 516 anoikis-related genes (ANRGs) were retrieved from GeneCard database and Harmonizome portal. Differential expression analysis identified 219 differentially expressed genes (DEGs), and univariate Cox regression analysis was utilized to select 99 ANRGs associated with the prognosis of HCC patients. A risk scoring model with seven genes was established using the least absolute shrinkage and selection operator (LASSO) regression model, and internal validation of the model was performed. The identified 99 ANRGs are closely associated with the prognosis of HCC patients. The risk scoring model based on seven characteristic genes demonstrates excellent predictive performance, further validated by receiver operating characteristic (ROC) curves and Kaplan-Meier survival curves. The study reveals significant differences in immune cell infiltration, gene expression, and survival status among different risk groups. The prognosis of HCC patients can be predicted using a unique prognostic model built on ANRGs in HCC.

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

Studies have shown that coagulation and fibrinolysis (CFR) are correlated with Hepatocellular carcinoma (HCC) progression and prognosis. We aim to build a model based on CFR-correlated genes for risk assessment and prediction of HCC patient. HCC samples were selected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases respectively. The Molecular Signatures Database (MSigDB) was used to select the CFR genes. RiskScore model were established by single sample gene set enrichment analysis (ssGSEA), weighted correlation network analysis (WGCNA), multivariate Cox regression analysis, LASSO regression analysis. PCDH17, PGF, PDE2A, FAM110D, FSCN1, FBLN5 were selected as the key genes and designed a RiskScore model. Those key genes were Differential expressions in HCC cell and patients. Overexpression PDE2A inhibited HCC cell migration and invasion. The higher the RiskScore, the lower the probability of survival. The model has high AUC values in the first, third and fifth year prediction curves, indicating that the model has strong prediction performance. The difference analysis of clinicopathological features found that a great proportion of high clinicopathological grade samples showed higher RiskScore. RiskScore were positively correlated with immune scores and TIDE scores. High levels of immune checkpoints and immunomodulators were observed in high RiskScore group. High RiskScore groups may benefit greatly from taking traditional chemotherapy drugs. We screened CFR related genes to design a RiskScore model, which could accurately evaluate the prognosis and survival status of HCC patients, providing certain value for optimizing the clinical treatment of cancer in the future.

Identification of molecular characteristics of hepatocellular carcinoma with microvascular invasion based on deep targeted sequencing.

As an indicator of tumor invasiveness, microvascular invasion (MVI) is a crucial risk factor for postoperative relapse, metastasis, and unfavorable prognosis in hepatocellular carcinoma (HCC). Nevertheless, the genetic mechanisms underlying MVI, particularly for Chinese patients, remain mostly uncharted. We applied deep targeted sequencing on 66 Chinese HCC samples. Focusing on the telomerase reverse transcriptase (TERT) promoter (TERTp) and TP53 co-mutation (TERTp+/TP53+) group, gene set enrichment analysis (GSEA) was used to explore the potential molecular mechanisms of the TERTp+/TP53+ group on tumor progression and metastasis. Additionally, we evaluated the tumor immune microenvironment of the TERTp+/TP53+ group in HCC using multiplex immunofluorescence (mIF) staining. Among the 66 HCC samples, the mutated genes that mostly appeared were TERT, TP53, and CTNNB1. Of note, we found 10 cases with TERTp+/TP53+, of which nine were MVI-positive and one was MVI-negative, and there was a co-occurrence of TERTp and TP53 (p < 0.05). Survival analysis demonstrated that patients with the TERTp+/TP53+ group had lower the disease-free survival (DFS) (p = 0.028). GSEA results indicated that telomere organization, telomere maintenance, DNA replication, positive regulation of cell cycle, and negative regulation of immune response were significantly enriched in the TERTp+/TP53+ group (all adjusted p-values (p.adj) < 0.05). mIF revealed that the TERTp+/TP53+ group decreased CD8+ T cells infiltration (p = 0.25) and enhanced PDL1 expression (p = 0.55). TERTp+/TP53+ was significantly enriched in MVI-positive patients, leading to poor prognosis for HCC patients by promoting proliferation of HCC cell and inhibiting infiltration of immune cell surrounding HCC. TERTp+/TP53+ can be utilized as a potential indicator for predicting MVI-positive patients and poor prognosis, laying a preliminary foundation for further exploration of co-mutation in HCC with MVI and clinical treatment.

A Novel Four-Gene Signature Based on Nonsense-Mediated RNA Decay for Predicting Prognosis in Hepatocellular Carcinoma: Bioinformatics Analysis and Functional Validation.

Nonsense-mediated RNA decay (NMD), a surveillance pathway for selective degradation of aberrant mRNAs, is associated with cancer progression. Its potential as a predictor for aggressive hepatocellular carcinoma (HCC) is unclear. Here, we present an innovative NMD risk model for predicting HCC prognosis. The Cancer Genome Atlas (TCGA) data of 374 liver HCC (LIHC) and 50 normal liver samples were extracted. A risk model based on NMD-related genes was developed through least absolute shrinkage and selection operator Cox (LASSO-Cox) regression of the LIHC-TCGA data. Prognostic validation was done using GSE54236, GSE116174, and GSE76427 data. Univariate and multivariate Cox regression analyses were conducted to assess the prognostic value of the model. We also constructed nomograms for survival prediction. Tumor immune infiltration was evaluated using the CIBERSORT algorithm, and the tumor cell phenotype was assessed. Finally, mouse experiments verified UPF3B knockdown effects on HCC tumor characteristics. We developed a risk model based on four NMD-related genes (PABPC1, RPL8, SMG5, and UPF3B) and validated it using GSE54236, GSE116174, and GSE76427 data. The model effectively distinguished high- and low-risk groups corresponding to unfavorable and favorable HCC outcomes. Its prognostic prediction accuracy was confirmed through time-dependent ROC analysis, and clinical-use nomograms with calibration curves were developed. Single-cell RNA sequencing results indicated significantly higher expression of SMG5 and UPF3B in tumor cells. Knockdown of SMG5 and UPF3B inhibited HCC cell proliferation, invasion, and migration, while affecting cell-cycle progression and apoptosis. In vivo, UPF3B knockdown delayed tumor growth and increased immune cell infiltration. Our NMD-related gene-based risk model can help identify therapeutic targets and biomarkers for HCC. Additionally, it assists clinicians in predicting the prognosis of HCC patients.

Pan-cancer analysis of ARFs family and ARF5 promoted the progression of hepatocellular carcinoma

BackgroundARF family proteins are a kind of small GTPases, which are involved in regulating a variety of basic functions of cells. In recent years, the role and molecular regulatory mechanisms of ARFs in tumor progression have received increasing attention, and research reports on most of their family members are increasing. However, research on the clinical and pathological relevance of ARF5 in cancer, especially in hepatocellular carcinoma, still needs to be improved. MethodsRNA-seq data in the Cancer Genome Atlas (TCGA) and genome tissue expression (GTEx) databases were used to analyze the expression and pathological data of ARFs family in Pan-cancer. Kaplan-Meier and Cox regression were used for prognostic analysis of ARF5 and Pan-cancer. Combined with ImmuCellAI database and TIMER2 database, the relationship between ARF5 expression and immune cell tumor infiltration in hepatocellular carcinoma (HCC) was analyzed. WGCNA is used to construct the co-expression gene network related to ARF5 expression in HCC and screen important modules and central genes. GO and KEGG path enrichment analysis were carried out for the genes in the modules with clinical significance. GSEA analysis was performed to take into account the role of genes with small differences. Finally, ceRNA network analysis was used to explore the molecular mechanism of miRNAs and lncRNAs regulating ARF5 expression. ResultsARFs family (ARF1, ARF3, ARF4, ARF5, ARF6) are generally highly expressed in Pan-cancer. ARF5 is significantly highly expressed in 29 cancers, and the high expression of ARF5 in HCC patients is significantly negatively correlated with OS, DFI, PFI and DSS, which may lead to cancer deterioration by participating in tumor immune infiltration of HCC. Through WGCNA analysis, the expression of ARF5 in HCC may be involved in many cellular processes that consume a lot of energy, such as ribosome formation, RNA and protein synthesis and lipids, as well as COVID-19, nonalcoholic fatty liver, neurodegenerative diseases and other disease pathways. ConclusionARFs, especially ARF5, are overexpressed in many human tumors. This study shows for the first time that ARF5 is significantly correlated with the poor prognosis of HCC patients, which may play a role as an oncogene, suggesting that ARF5 has the potential as a biomarker for the diagnosis and treatment of HCC.

Construction and validation of somatic mutation-derived long non-coding RNAs signatures of genomic instability to predict prognosis of hepatocellular carcinoma.

Long non-coding RNAs (LncRNAs) have been found to be a potential prognostic factor for cancers, including hepatocellular carcinoma (HCC). Some LncRNAs have been confirmed as potential indicators to quantify genomic instability (GI). Nevertheless, GI-LncRNAs remain largely unexplored. This study established a GI-derived LncRNA signature (GILncSig) that can predict the prognosis of HCC patients. To establish a GILncSig that can predict the prognosis of HCC patients. Identification of GI-LncRNAs was conducted by combining LncRNA expression and somatic mutation profiles. The GI-LncRNAs were then analyzed for functional enrichment. The GILncSig was established in the training set by Cox regression analysis, and its predictive ability was verified in the testing set and TCGA set. In addition, we explored the effects of the GILncSig and TP53 on prognosis. A total of 88 GI-LncRNAs were found, and functional enrichment analysis showed that their functions were mainly involved in small molecule metabolism and GI. The GILncSig was constructed by 5 LncRNAs (miR210HG, AC016735.1, AC116351.1, AC010643.1, LUCAT1). In the training set, the prognosis of high-risk patients was significantly worse than that of low-risk patients, and similar results were verified in the testing set and TCGA set. Multivariate Cox regression analysis and stratified analysis confirmed that the GILncSig could be used as an independent prognostic factor. Receiver operating characteristic curve analysis of the GILncSig showed that the area under the curve (0.773) was higher than the two LncRNA signatures published recently. Furthermore, the GILncSig may have a better predictive performance than TP53 mutation status alone. We established a GILncSig that can predict the prognosis of HCC patients, which will help to guide prognostic evaluation and treatment decisions.

Applying image features of proximal paracancerous tissues in predicting prognosis of patients with hepatocellular carcinoma

BackgroundMost of the methods using digital pathological image for predicting Hepatocellular carcinoma (HCC) prognosis have not considered paracancerous tissue microenvironment (PTME), which are potentially important for tumour initiation and metastasis. This study aimed to identify roles of image features of PTME in predicting prognosis and tumour recurrence of HCC patients. MethodsWe collected whole slide images (WSIs) of 146 HCC patients from Sun Yat-sen Memorial Hospital (SYSM dataset). For each WSI, five types of regions of interests (ROIs) in PTME and tumours were manually annotated. These ROIs were used to construct a Lasso Cox survival model for predicting the prognosis of HCC patients. To make the model broadly useful, we established a deep learning method to automatically segment WSIs, and further used it to construct a prognosis prediction model. This model was tested by the samples of 225 HCC patients from the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC). ResultsIn predicting prognosis of the HCC patients, using the image features of manually annotated ROIs in PTME achieved C-index 0.668 in the SYSM testing dataset, which is higher than the C-index 0.648 reached by the model only using image features of tumours. Integrating ROIs of PTME and tumours achieved C-index 0.693 in the SYSM testing dataset. The model using automatically segmented ROIs of PTME and tumours achieved C-index of 0.665 (95% CI: 0.556–0.774) in the TCGA-LIHC samples, which is better than the widely used methods, WSISA (0.567), DeepGraphSurv (0.593), and SeTranSurv (0.642). Finally, we found the Texture SumAverage Skew HV on immune cell infiltration and Texture related features on desmoplastic reaction are the most important features of PTME in predicting HCC prognosis. We additionally used the model in prediction HCC recurrence for patients from SYSM-training, SYSM-testing, and TCGA-LIHC datasets, indicating the important roles of PTME in the prediction. ConclusionsOur results indicate image features of PTME is critical for improving the prognosis prediction of HCC. Moreover, the image features related with immune cell infiltration and desmoplastic reaction of PTME are the most important factors associated with prognosis of HCC.