Biomarker For Hepatocellular Carcinoma Research Articles

Prognostic Significance of Iron Metabolism and Immune-Related Genes as Risk Markers in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly lethal liver cancer with significant heterogeneity, which poses challenges in predicting prognosis and treatment outcomes. The impact of iron metabolism and immune-related genes (IMRGs) on HCC patient prognoses remains elusive. We utilized The Cancer Genome Atlas (TCGA) dataset to obtain mRNA expression data and clinical information from HCC patients. Through the application of LASSO regression and univariate/multivariate Cox regression analyses, we identified five IMRGs significantly associated with survival of HCC patients. We constructed a prognostic model comprising these five genes. The model demonstrated excellent predictive performance, not only within TCGA dataset but also when validated using the Gene Expression Omnibus (GEO) dataset. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses presented significant variations in functional categories, such as apical plasma membrane and collagen-containing extracellular matrix. Several pathways, including the PI3K-AKT signaling pathway and the calcium signaling pathway, exhibited significant variations among HCC patients with varying prognoses (P < 0.05). Immune infiltration analysis indicated significantly lower levels of various immune cells, immune functions, and immune checkpoints, such as B cells, CD8+ T cells, and TILs, in the high-risk group (P < 0.05). Immunophenoscore results suggested that the low-risk group may exhibit a more favorable response to immune therapy. Furthermore, the CellMiner database predicted anti-tumor drugs significantly associated with prognostic genes (P < 0.001). In conclusion, our findings highlight the predictive role of IMRGs in prognosis and immune treatment of HCC, indicating that ADAMTS13, CRHBP, VIPR1, FCN3, and CLEC1B may serve as potential prognostic biomarkers for HCC.

CircMYBL2 facilitates hepatocellular carcinoma progression by regulating E2F1 expression.

Circular RNAs (circRNAs) have been recognized as pivotal regulators in tumorigenesis, yet the biological functions as well as molecular mechanisms of the majority of circRNAs in hepatocellular carcinoma (HCC) remain elusive. We sought to unveil the expression profile and biological role of circMYBL2 in HCC. Initial microarray analyses were conducted to probe the expression profile of circMYBL2 in HCC cells, and qRT‒PCR analysis was then performed in HCC cell lines and tissues, revealing significant upregulation of circMYBL2. Subsequent experiments were conducted to evaluate the biological function of circMYBL2 in HCC progression. Furthermore, bioinformatics analysis, qRT‒PCR analysis, luciferase reporter assays, and western blot analysis were employed to investigate the interplay among circMYBL2, miR-1205, and E2F1. CircMYBL2 was found to exhibit marked upregulation in tumor tissues as well as HCC cell lines. Elevated expression of circMYBL2 increased the proliferation and migration of HCC cells, whereas circMYBL2 knockdown elicited contrasting effects. Mechanistically, our results indicated that circMYBL2 promoted E2F1 expression and facilitated HCC progression by sponging miR-1205. Our findings revealed that circMYBL2 contributed to HCC progression through the circMYBL2/miR-1205/E2F1 axis, suggesting the potential of circMYBL2 as a novel target for HCC treatment or a prognostic biomarker for HCC.

Serum Aldo-Keto Reductase Family 1 Member B10 (AKR1B10) as a Potential Biomarker for Diagnosis of Hepatocellular Carcinoma.

To evaluate the diagnostic performance of aldo-keto reductase family 1 member B10 (AKR1B10) in a Beijing cohort with hepatocellular carcinoma (HCC). This study included 521 subjects who visited Peking Union Medical College Hospital from June 2017 to May 2023, including 109 cases of HCC, 165 cases of healthy controls, 106 cases of benign liver diseases, and 141 cases of other cancers. Serum AKR1B10 levels were measured and compared across various groups. Diagnostic performances of serum AKR1B10 and other tumor markers were assessed using receiver operator characteristic (ROC) curves. In addition, a subset of HCC patients who underwent surgical resection were recruited for clinical follow-up study. We found that serum AKR1B10 expression was higher in patients with HCC relative to other control groups. The association between serum AKR1B10 and clinical features of HCC was not observed. Serum AKR1B10 showed a high diagnostic performance for HCC, and when combined with AFP, the diagnostic effectiveness was significantly improved. Specifically, serum AKR1B10 showed superior diagnostic effectiveness for AFP-negative HCC. The clinical follow-up study indicated a gradual decrease in serum AKR1B10 after surgery. Our study demonstrated that serum AKR1B10 is a promising biomarker for HCC, and when used in combination with AFP can significantly improve the detection rate of HCC.

The significance of HAUS1 and its relationship with immune microenvironment in hepatocellular carcinoma.

Background: HAUS Augmin-like complex subunit 1(HAUS1), as a controlling gene, which affected the production of spindle was firstly discovered in Drosophila cells. Although HAUS1 has been intensively studied, but its significance and relationship with the immune microenvironment in Hepatocellular carcinoma (HCC) remain unclear. Materials and Methods: All data of HCC in this paper were obtained from The Cancer Genome Atlas(TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Omnibus (GEO) and the Human Protein Atlas(HPA) database. The role and potential value of HAUS1 in the tumorigenesis and development of HCC were studied by applying plenty of bioinformatics analysis methods. Knocked down the expression of HAUS1 through siRNA and further investigated the function of HAUS1 in HCC Results: HAUS1 was highly expressed in HCC, which led to a poor prognosis. ROC curve analysis showed that HAUS1 had a excellent diagnostic value. It was also associated with clinical stage, pathological grade and AFP of HCC. Univariate and multivariate COX regression analysis showed that HAUS1 was an independent prognostic factor for HCC patients. HAUS1 was associated with immune cells infiltrate and immune checkpoints in HCC, and it could generate significative therapeutic results when combined with anti-CTLA4 and anti-CD274 treatment. In vitro experiments, HAUS1 was found to promote the proliferation, invasion and metastasis, participated in cell cycle regulation and inhibited apoptosis of HCC. Conclusion: These results suggested that HAUS1 might serve as a potential therapeutic target, as well as a diagnostic, prognostic, and survival biomarker for HCC.

The preliminary data of gene expressions and bioinformatics analysis of miR-146b-5p and miR-4510 in the Turkish population in HBV-related hepatocellular carcinoma.

It is reported that miRNAs play an important role in hepatocellular carcinogenesis and may serve as non-invasive biomarkers for hepatocellular carcinoma (HCC). MiR-4510 and miR-146b-5p expression levels have been found to be associated with HCC. However, their associations with hepatitis B virus (HBV)-related HCC (HBV-HCC) are yet to be explored. We aimed to assess the predictive value of expression levels of serum miR-4510 and miR-146b-5p in patients with HBV-HCC and performed bioinformatics analyses based on the miRNA expression profile. This cross-sectional study used the serum of 16 patients with Chronic Hepatitis B (CHB), 15 hepatitis B virus-related cirrhosis (HBV-cirrhosis), 15 HBV-HCC, and 16 healthy subjects. The total RNA was isolated from serum, and the expression of miRNAs was measured by qRT-PCR, calculated using the 2-ΔΔCt methods. MIENTURNET was used to predict miRNA-target gene interactions. The Network Analyst was used to build protein-protein interactions. There was a significant difference in miR-146b-5p between study groups (p=0.009). MiR-146b-5p expression was found to be significantly reduced in HBV-HCC compared to the HBV-cirrhosis group and healthy controls (p=0.005 and p=0.006, respectively). The serum miR-146b-5p levels might be a promising tool to be used as a non-invasive diagnostic biomarker for HCC. Our findings shed light on potential biomarkers for the diagnosis of HBV-HCC in terms of selected miRNAs. The target pathways of miR-146b-5p identified by our in-silico analysis to reveal the functional mechanism are "MAPK signaling pathways" and "Pathways in cancer."

Detection of γ-OHPdG in Circulating Tumor Cells of Patients With Hepatocellular Carcinoma as a Potential Prognostic Biomarker of Recurrence

Background and AimsBlood-based biomarkers for hepatocellular carcinoma (HCC) and its recurrence is lacking. We previously showed that hepatic γ-hydroxy-1,N2-propano-2′-deoxyguanosine (γ-OHPdG), an endogenous DNA adduct derived from acrolein by lipid peroxidation, increased during hepatocarcinogenesis. Additionally, higher hepatic γ-OHPdG from HCC patients after surgery were strongly associated with poor survival (P < .0001) and recurrence-free survival (P = .007) (Fu Y et al., Hepatology, 2018). These findings suggest that γ-OHPdG is a potential prognostic biomarker for HCC and its recurrence. To attain the goal of using γ-OHPdG as a biomarker in future preventive and therapeutic trials, we developed a blood-based method to detect γ-OHPdG in circulating liver tumor cells from HCC patient blood. MethodsWe first established the specificity of anti-γ-OHPdG antibody by determining its dose-response in HepG2 cells treated with acrolein. Then, HepG2 cells in spiked blood of healthy volunteers (HV) and circulating tumor cells (CTCs) from 32 HCC patients were isolated using a RosetteSep™ CD45 Depletion Cocktail and Ficoll Paque. The HCC CTCs identified with anti-asialoglycoprotein receptor 1, a surface protein expressed solely in hepatocytes, were stained with an anti-γ-OHPdG antibody. The number of total HCC CTCs and γ-OHPdG-positive CTCs, as well as the staining intensity, were quantified using a MetaMorph software. As an initial effort toward its clinical application, we also evaluated γ-OHPdG in CTCs from these patients along with certain clinical features. ResultsThe γ-OHPdG antibody specificity was demonstrated by an acrolein concentration-dependent increase of γ-OHPdG-positive HepG2 cells and the intensity of γ-OHPdG staining. The recovery of HepG2 cells from spiked blood was ∼50-60%, and the positivity rate of CTCs in blood from 32 patients with advanced HCC was 97%. The MetaMorph analysis showed a wide variation among patients in total number of CTCs, γ-OHPdG positivity, and staining intensity. Statistical analysis revealed γ-OHPdG in CTCs of these patients appear to be associated with multifocality and poor differentiation. ConclusionsA blood-based method was developed and applied to HCC patients to evaluate the potential of γ-OHPdG in CTCs as a prognostic biomarker.

Identification of prognostic biomarkers for hepatocellular carcinoma with vascular invasion.

Vascular invasion (VI) profoundly impacts the prognosis of hepatocellular carcinoma (HCC), yet the underlying biomarkers and mechanisms remain elusive. This study aimed to identify prognostic biomarkers for HCC patients with VI. Transcriptome data from primary HCC tissues and HCC tissues with VI were obtained through the Genome Expression Omnibus database. Differentially expressed genes (DEGs) in the two types of tissues were analyzed using functional enrichment analysis to evaluate their biological functions. We examined the correlation between DEGs and prognosis by combining HCC transcriptome data and clinical information from The Cancer Genome Atlas database. Univariate and multivariate Cox regression analyses, along with the least absolute shrinkage and selection operator (LASSO) method were utilized to develop a prognostic model. The effectiveness of the model was assessed through time-dependent receiver operating characteristic (ROC) curve, calibration diagram, and decision curve analysis. In the GSE20017 and GSE5093 datasets, a total of 83 DEGs were identified. Gene Ontology analysis indicated that these DEGs were predominantly associated with xenobiotic stimulus, collagen-containing extracellular matrix, and oxygen binding. Additionally, Kyoto Encyclopedia of Genes and Genomes analysis revealed that the DEGs were primarily involved in immune defense and cellular signal transduction. Cox and LASSO regression further identified 7 genes (HSPA8, ABCF2, EAF1, MARCO, EPS8L3, PLA3G1B, C6), which were used to construct a predictive model in the training cohort. We used X-tile software to calculate the optimal cut-off value to stratify HCC patients into low-risk and high-risk groups. Notably, the high-risk group exhibited poorer prognosis than the low-risk group (P < 0.001). The model demonstrated area under the ROC curve (AUC) values of 0.815, 0.730, and 0.710 at 1-year, 3-year, and 5-year intervals in the training cohort, respectively. In the validation cohort, the corresponding AUC values were 0.701, 0.571, and 0.575, respectively. The C-index of the calibration curve for the training and validation cohorts were 0.716 and 0.665. Decision curve analysis revealed the model's efficacy in guiding clinical decision-making. The study indicates that 7 genes may be potential prognostic biomarkers and treatment targets for HCC patients with VI.

Development and Validation of the novel Cuproptosis- and Immune-related Signature for Predicting Prognosis in Hepatocellular Carcinoma.

Background: Hepatocellular carcinoma often results in late-stage diagnosis, leading to decreased treatment success. To improve prognosis, this study integrates cuproptosis with immune risk scoring models for HCC patients. Method: We identified differentially expressed genes connected to cuproptosis and immune responses using Pearson correlation. A risk signature was then constructed via LASSO regression, and its robustness was validated in the International Cancer Genome Consortium dataset. Additionally, qPCR confirmed findings in tumor and normal tissues. Results: Eight genes emerged as key prognostic markers from the 110 differentially expressed genes linked to cuproptosis and immunity. A risk-scoring model was developed using gene expression, effectively categorizing patients into low- or high-risk groups. Validated in the ICGC dataset, high-risk patients had significantly reduced survival times. Multivariate Cox regression affirmed the risk signature's independent predictive capability. A clinical nomogram based on the risk signature was generated. Notably, low-risk patients might benefit more from immune checkpoint inhibitors. qPCR and western blotting results substantiated our bioinformatics findings. Conclusions: The genetic risk signature linked to cuproptosis and immunity holds potential as a vital prognostic biomarker for Hepatocellular carcinoma, providing avenues for tailored therapeutic strategies.

Circulating microRNAs as promising diagnostic biomarkers for hepatocellular carcinoma: a systematic review and meta-analysis.

Introduction: Hepatocellular carcinoma (HCC), the most common type of liver cancer, is a major global health problem, ranking as the third leading cause of cancer-related death worldwide. Early identification and diagnosis of HCC requires the discovery of reliable biomarkers. Therefore, the study aimed to assess the diagnostic accuracy of miRNAs for HCC. The protocol was registered on PROSPERO website with the registration number CRD42023417494. Method: A literature search was conducted in PubMed, Scopus, Embase, Wiley Online Library, and Science Direct databases to identify pertinent articles published between 2018 and 30 July 2023. Stata 17.0 software was employed to determine the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic ratio (DOR), and area under the curve (AUC) for evaluating the accuracy of miRNAs in diagnosing HCC. The assessment of heterogeneity among studies involved the use of the Cochran-Q test and I2 statistic tests. Due to the observed significant heterogeneity, the random-effect model was chosen. Subgroup analysis and meta-regression analysis were also undertaken to explore potential sources contributing to heterogeneity. Deeks' funnel plot was used to assess publication bias. In addition, Fagan's nomogram and likelihood ratio scattergram were utilized to assess the clinical validity of miRNAs for HCC. Result: Twenty-four articles were included, involving 1,668 individuals diagnosed with HCC and 1,236 healthy individuals. The findings revealed pooled sensitivity of 0.84 (95% CI: 0.80-0.88), specificity of 0.81 (95% CI: 0.77-0.84), PLR of 4.36 (95% CI: 3.59-5.30), NLR of 0.19 (95% CI: 0.15-0.25), DOR of 22.47 (95% CI: 14.47-32.64), and an AUC of 0.89 (95% CI: 0.86-0.91) for the diagnosis of HCC using miRNAs. Furthermore, results from the subgroup analysis demonstrated that superior diagnostic performance was observed when utilizing plasma miRNAs, a large sample size (≥100), and miRNA panels. Conclusion: Hence, circulating miRNAs demonstrate substantial diagnostic utility for HCC and can serve as effective non-invasive biomarkers for the condition. Additionally, miRNA panels, miRNAs derived from plasma, and miRNAs evaluated in larger sample sizes (≥100) demonstrate enhanced diagnostic efficacy for HCC diagnosis. Nevertheless, a large pool of prospective studies and multi-center research will be required to confirm our findings in the near future.

Microfluidics-aided fabrication of 3D micro-nano hierarchical SERS substrate for rapid detection of dual hepatocellular carcinoma biomarkers.

The simultaneous analysis of trace amounts of dual biomarkers is crucial in the early diagnosis, treatment, and prognosis of hepatocellular carcinoma (HCC). In this study, we prepared SERS-active hydrogel microparticles (SAHMs) with 3D hierarchical gold nanoparticles (AuNPs) micro-nanostructures by microdroplet technology and in situ synthesis, which demonstrated high reproducibility and sensitivity. Compared with traditional 2D SERS substrates, this newly prepared 3D SERS substrate provided a high density of nano-wrinkled structures and numerous AuNPs. Furthermore, a newly designed SERS-active substrate was proposed for the simultaneous microfluidic detection of AFP and AFU. The Raman signals of sandwich immunocomplexes on the surface of the SAHMs were measured for the trace analysis of these biomarkers. The proposed microfluidic platform achieved AFP and AFU detection in the range of 0.1-100 ng mL-1 and 0.01-100 ng mL-1, respectively, which represents a good response. Indeed, this platform is easy to fabricate, of low cost and has short detection time and comparable detection limits to other methods. As far as we know, this is the first study to achieve the simultaneous detection of AFP and AFU on a microfluidic platform. Therefore, we proposed a new simultaneous detection platform for dual HCC biomarkers that shows strong potential for the early diagnosis of HCC.

A one-pot CRISPR-RCA strategy for ultrasensitive and specific detection of circRNA.

Accurate and precise detection of circular RNA (circRNA) is imperative for its clinical use. However, the inherent challenges in circRNA detection, arising from its low abundance and potential interference from linear isomers, necessitate innovative solutions. In this study, we introduce, for the first time, the application of the CRISPR/Cas12a system to establish a one-pot, rapid (30 minutes to 2 hours), specific and ultrasensitive circRNA detection strategy, termed RETA-CRISPR (reverse transcription-rolling circle amplification (RT-RCA) with the CRISPR/Cas12a). This method comprises two steps: (1) the RT-RCA process of circRNA amplification, generating repeat units containing the back-splicing junction (BSJ) sequences; and (2) leveraging the protospacer adjacent motif (PAM)-independent Cas12a/crRNA complex to precisely recognize target sequences with BSJ, thereby initiating the collateral cleavage activity of Cas12a to generate a robust fluorescence signal. Remarkably, this approach exhibits the capability to detect circRNAs at a concentration as low as 300 aM. The sensor has been successfully employed for accurate detection of a potential hepatocellular carcinoma biomarker hsa_circ_0001445 (circRNA1445) in various cell lines. In conclusion, RETA-CRISPR seamlessly integrates the advantages of exponential amplification reaction and the robust collateral cleavage activity of Cas12a, positioning it as a compelling tool for practical CRISPR-based diagnostics.

DNA methylation-mediated epigenetic regulation of oncogenic RPS2 as a novel therapeutic target and biomarker in hepatocellular carcinoma

Ribosomal Protein S2 (RPS2) has emerged as a potential prognostic biomarker due to its involvement in key cellular processes and its altered expression pattern in certain types of cancer. However, its role in hepatocellular carcinoma (HCC) has yet to be investigated. Herein, we analyzed RPS2 mRNA expression and promoter methylation in HCC patient samples and HepG2 cells. Subsequently, loss-of-function experiments were conducted to determine the function of RPS2 in HCC cells in vitro. Our results revealed that RPS2 mRNA expression is significantly elevated, and its promoter is hypomethylated in HCC patient samples compared to controls. In addition, 5-Azacytidine treatment in HepG2 cells decreased RPS2 promoter methylation level and increased its mRNA expression. RPS2 knockdown in HepG2 cells suppressed cell proliferation and promoted apoptosis. Functional pathway analysis of genes positively and negatively associated with RPS2 expression in HCC showed enrichment in ribosomal biogenesis, translation machinery, cell cycle regulation, and DNA processing. Furthermore, utilizing drug-protein 3D docking, we found that doxorubicin, sorafenib, and 5-Fluorouracil, showed high affinity to the active sites of RPS2, and in vitro treatment with these drugs reduced RPS2 expression. For the first time, we report on DNA methylation-mediated epigenetic regulation of RPS2 and its oncogenic role in HCC. Our findings suggest that RPS2 plays a significant role in the development and progression of HCC, hence its potential prognostic and therapeutic utility. Moreover, as epigenetic changes happen early in cancer development, RPS2 may serve as a potential biomarker for tumor progression.

Constructed Risk Prognosis Model Associated with Disulfidptosis lncRNAs in HCC.

Disulfidptosis is a novel cell death mode in which the accumulation of disulfide bonds in tumor cells leads to cell disintegration and death. Long-stranded noncoding RNAs (LncRNAs) are aberrantly expressed in hepatocellular carcinoma (HCC) and have been reported to carry significant potential as a biomarker for HCC prognosis. However, lncRNA studies with disulfidptosis in hepatocellular carcinoma have rarely been reported. Therefore, this study aimed to construct a risk prognostic model based on the disulfidptosis-related lncRNA and investigate the mechanisms associated with disulfidptosis in hepatocellular carcinoma. The clinical and transcriptional information of 424 HCC patients was downloaded from The Cancer Genome Atlas (TCGA) and divided into test and validation sets. Furthermore, 1668 lncRNAs associated with disulfidptosis were identified using Pearson correlation. Six lncRNA constructs were finally identified for the risk prognostic model using one-way Cox proportional hazards (COX), multifactorial COX, and lasso regression. Kaplan-Meier (KM) analysis, principal component analysis, receiver operating characteristic curve (ROC), C-index, and column-line plot results confirmed that the constructed model was an independent prognostic factor. Based on the disulfidptosis risk score, risk groups were identified as potential predictors of immune cell infiltration, drug sensitivity, and immunotherapy responsiveness. Finally, we confirmed that phospholipase B domain containing 1 antisense RNA 1 (PLBD1-AS1) and muskelin 1 antisense RNA (MKLN1-AS) were highly expressed in hepatocellular carcinoma and might be potential biomarkers in HCC by KM analysis and quantitative real-time PCR (RT-qPCR). This study demonstrated that lncRNA related to disulfidptosis could serve as a biomarker to predict prognosis and treatment targets for HCC.

Identification of ABCC3 and its isoforms as potential biomarker in hepatocellular carcinoma

Liver diseases preceding the occurrence of hepatocellular carcinoma (HCC) play a crucial role in the progression and establishment of HCC, a malignancy ranked as the third deadliest cancer worldwide. Late diagnosis, alongside ineffective treatment, leads patients to a poor survival rate. This scenario argues for seeking novel alternatives for detecting liver alterations preceding the early occurrence of HCC. Experimental studies have reported that ABCC3 protein increases within HCC tumors but not in adjacent tissue. Therefore, we analyzed ABCC3 expression in public databases and investigated the presence of ABCC3 and its isoforms in plasma, urine and its release in extracellular vesicles (EVs) cargo from patients bearing cirrhosis and HCC. The UALCAN and GEPIA databases were used to analyze the expression of ABCC3 in HCC. The results were validated in a case-control study including 41 individuals bearing cirrhosis and HCC, and the levels of ABCC3 in plasma and urine samples, as well as EVs, were analyzed by ELISA and western blot. Our data showed that ABCC3 expression was higher in HCC tissues than in normal tissues and correlated with HCC grade and stage. ABCC3 protein levels were highly increased in both plasma and urine and correlated with liver disease progression and severity. The isoforms MRP3A and MRP3B of ABCC3 were significantly increased in both EVs and plasma/urine of patients bearing HCC. ABCC3 expression gradually increases in HCC tissues, and its protein levels are increased in both plasma and urine of patients with cirrhosis and HCC. MRP3A and MRP3B isoforms have the potential to be prognostic biomarkers of HCC.

The value of CDC42 effector protein 2 as a novel prognostic biomarker in liver hepatocellular carcinoma: a comprehensive data analysis.

The prognostic significance of CDC42 effector protein 2 (CDC42EP2) and its association with tumor-infiltrating immune cells (TIICs) have not been explored in liver hepatocellular carcinoma (LIHC). This study aims to assess the potential prognostic value of CDC42EP2 by conducting a comprehensive analysis of online databases pertaining to LIHC. We evaluated the potential of CDC42EP2 as a prognostic biomarker by utilizing online databases such as TIMER, GEPIA2, KM, OSlihc, HPA, and LinkedOmics. In LIHC, we observed that the mRNA and protein expression of CDC42EP2 were upregulated compared to normal tissues. Upregulated CDC42EP2 expression was associated with a worse prognosis based on the clinicopathological characteristics of patients with LIHC. Furthermore, CDC42EP2 was positively associated with TIICs. In the co-expression and functional enrichment analyses of CDC42EP2, 11,416 genes showed positive associations with CDC42EP2 while 8,008 genes showed negative associations. CDC42EP2-related co-expression genes were involved in protein localization to the endoplasmic reticulum, translational initiation, and RNA catabolic processes in gene set enrichment analysis-Gene Ontology (GSEAGO), and regulated the ribosome, spliceosome, and primary immune deficiency in the GSEAKyoto Encyclopedia of Genes and Genomes (KEGG) pathway. In a survival map, 23 and 17 genes that exhibited positive associations with CDC42EP2 showed a significant hazard ratio (HR) for overall survival and disease-free survival, respectively. Our findings demonstrated that CDC42EP2 is a novel prognostic biomarker and a potential tumor immune therapeutic target in patients with LIHC.

Machine learning and experiments identifies SPINK1 as a candidate diagnostic and prognostic biomarker for hepatocellular carcinoma

Machine learning techniques have been widely used in predicting disease prognosis, including cancer prognosis. One of the major challenges in cancer prognosis is to accurately classify cancer types and stages to optimize early screening and detection, and machine learning techniques have proven to be very useful in this regard. In this study, we aimed at identifying critical genes for diagnosis and outcomes of hepatocellular carcinoma (HCC) patients using machine learning. The HCC expression dataset was downloaded from GSE65372 datasets and TCGA datasets. Differentially expressed genes (DEGs) were identified between 39 HCC and 15 normal samples. For the purpose of locating potential biomarkers, the LASSO and the SVM-RFE assays were performed. The ssGSEA method was used to analyze the TCGA to determine whether there was an association between SPINK1 and tumor immune infiltrates. RT-PCR was applied to examine the expression of SPINK1 in HCC specimens and cells. A series of functional assays were applied to examine the function of SPINK1 knockdown on the proliferation of HCC cells. In this study, 103 DEGs were obtained. Based on LASSO and SVM-RFE analysis, we identified nine critical diagnostic genes, including C10orf113, SPINK1, CNTLN, NRG3, HIST1H2AI, GPRIN3, SCTR, C2orf40 and PITX1. Importantly, we confirmed SPINK1 as a prognostic gene in HCC. Multivariate analysis confirmed that SPINK1 was an independent prognostic factor for overall survivals of HCC patients. We also found that SPINK1 level was positively associated with Macrophages, B cells, TFH, T cells, Th2 cells, iDC, NK CD56bright cells, Th1 cells, aDC, while negatively associated with Tcm and Eosinophils. Finally, we demonstrated that SPINK1 expression was distinctly increased in HCC specimens and cells. Functionally, silence of SPINK1 distinctly suppressed the proliferation of HCC cells via regulating Wnt/β-catenin pathway. The evidence provided suggested that SPINK1 may possess oncogenic properties by inducing dysregulated immune infiltration in HCC. Additionally, SPINK1 was identified as a novel biomarker and therapeutic target for HCC.

MRPL48 is a novel prognostic and predictive biomarker of hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is one of the most prevalent forms of cancer and poses a threat to the health and survival of humans. Mitochondrial ribosomal protein L48 (MRPL48) belongs to the mitochondrial ribosomal protein family, which participates in energy production. Studies have shown that MRPL48 can predict osteosarcoma incidence and prognosis, as well as promotes colorectal cancer progression. However, the role of MRPL48 in HCC remains unknown.MethodsTCGA, GEO, HCCDB, CPTAC, SMART, UALCAN, Kaplan–Meier plotter, cBioPortal, and MethSurv were performed for bioinformatics purposes. Quantitative RT-PCR, immunoblotting, and functional studies were conducted to validate the methodology in vitro.ResultsMRPL48 was greatly overexpressed in HCC tissues, compared with healthy tissue, which was subsequently demonstrated in vitro as well. The survival and regression analyses showed that MRPL48 expression is of significant clinical prognostic value in HCC. The ROC curve and nomogram analysis indicated that MRPL48 is a powerful predictor of HCC. MRPL48 methylation was adversely associated with the expression of MRPL48, and patients with a low level of methylation had poorer overall survival than those with a high level of methylation. GSEA showed that the expression of the MRPL48 was correlated with Resolution of Sister Chromatid Cohesion, Mitotic Prometaphase, Retinoblastoma Gene in Cancer, RHO Gtpases Activate Formins, Mitotic Metaphase and Anaphase, and Cell Cycle Checkpoints. An analysis of immune cell infiltration showed a significant association between MRPL48 and immune cell infiltration subsets, which impacted the survival of HCC patients. Additionally, MRPL48 knockdown reduced HCC cell proliferation, migration, and invasion in vitro.ConclusionsWe demonstrated that MRPL48 expression may be associated with HCC development and prognosis. These findings may open up new research directions and opportunities for the development of HCC treatments.

Comprehensive analysis of m6A reader YTHDF2 prognosis, immune infiltration, and related regulatory networks in hepatocellular carcinoma

BackgroundN6-Methyladenosine (m6A) RNA modification is the most prevalent internal modification pattern in eukaryotic mRNAs and plays critical roles in diverse physiological and pathological processes. However, the expression of m6A regulator YTHDF2, its prognostic value, its biological function, its correlation with tumor microenvironment (TME) immune infiltrates, and related regulatory networks in hepatocellular carcinoma (HCC) remain determined. MethodsTCGA, GTEx, and GEO databases were used to investigate the expression profile of YTHDF2 in HCC. We performed differentially expressed genes (DEGs) analysis and constructed a PPI network to explore the biological processes of YTHDF2 in HCC. Kaplan-Meier curves and Cox regression analysis were used to assess the prognostic value of YTHDF2 and then a clinical prognostic nomogram was constructed. Additionally, ssGSEA was performed to assess the correlation between YTHDF2 and immune infiltration levels. The TISIDB database was applied to explore the expression of YTHDF2 in immune and molecular subtypes of HCC. GSEA identifies the YTHDF2-related signaling pathways. Finally, we utilized miRNet and starBase database to construct regulatory networks for HCC based on lncRNA-miRNA and miRNA-YTHDF2 interactions. ResultsYTHDF2 was significantly upregulated in HCC tumor tissues compared with the adjacent normal tissues. HCC patients in the high YTHDF2 expression group had poorer survival. Multivariate Cox analysis suggested that YTHDF2 may be a new independent prognostic indicator for HCC patients, with the prognostic nomogram exhibiting satisfactory results. YTHDF2 expression was significantly correlated with TME immune cell-infiltrating characteristics. Strong correlations were also shown in immune subtypes, molecular subtypes and immune checkpoints. Further analysis revealed that the combination of YTHDF2 expression and immune cell score was considerably associated with survival outcome in HCC patients. GESA analysis demonstrated that high YTHDF2 expression is associated with multiple biological processes and oncogenic pathways. Moreover, 14 possible regulatory networks were constructed, which are associated with HCC progression. ConclusionOur findings revealed that YTHDF2 may serve as a promising prognostic biomarker for HCC and may regulate the tumor immune microenvironment to provide effective therapeutic strategies.

Imaging-Derived Biomarkers Integrated with Clinical and Laboratory Values Predict Recurrence of Hepatocellular Carcinoma After Liver Transplantation.

To investigate the prognostic value of computed tomography (CT) derived imaging biomarkers in hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) and develop a predictive nomogram model. This retrospective study included 178 patients with histopathologically confirmed HCC who underwent liver transplantation between 2007 and 2021 at the two academic liver centers. We evaluated dedicated imaging features from baseline multiphase contrast-enhanced CT supplemented by several clinical findings and laboratory parameters. Time-to-recurrence was estimated by Kaplan-Meier analysis. Univariable Cox proportional hazard regression and multivariable Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to assess independent prognostic factors for recurrence. A nomogram model was then built based on the independent factors selected through LASSO regression, to predict the probabilities of HCC recurrence at one, three, and five years. The rate of HCC recurrence after LT was 17.4% (31 of 178). The LASSO analysis revealed six independent predictors associated with an elevated risk of tumor recurrence. These predictors included the presence of peritumoral enhancement, the presence of over three tumor lesions, the largest tumor diameter greater than 3 cm, serum alpha-fetoprotein (AFP) levels exceeding 400 ng/mL, and the presence of a tumor capsule. Conversely, a history of bridging therapies was found to be correlated with a reduced risk of HCC recurrence. In addition, Kaplan-Meier curves showed patients with irregular margin, satellite nodules, or small lesions displayed shorter time-to-recurrence. Our nomogram demonstrated good performance, yielding a C-index of 0.835 and AUC values of 0.86, 0.88, and 0.85 for the predictions of 1-year, 3-year, and 5-year TTR, respectively. Imaging parameters derived from baseline contrast-enhanced CT showing malignant behavior and aggressive growth patterns, along with serum AFP and history of bridging therapies, show potential as biomarkers for predicting HCC recurrence after transplantation.

Intelectin-1 is a novel prognostic biomarker for hepatocellular carcinoma.

The molecular mechanisms of hepatocellular carcinoma (HCC) are still not well understood. Gene microarray analysis showed that the expression of Intelectin-1 (ITLN-1) in tumor-adjacent normal liver tissue was 454.8 times higher than in the corresponding cancer tissue. ITLN-1 is a secreted soluble glycoprotein which has been reported to be associated with the occurrence and development of various tumor types. However, the prognostic significance of ITLN-1 in HCC remain unclear. Real-time fluorescence quantitative polymerase chain reaction was used to investigate 149 liver cancer cases for ITLN-1 mRNA expression. Immunohistochemistry and western blot analysis were used to ascertain protein expression of ITLN-1 in cancer and para-carcinomatous tissue, and further to evaluate the correlation between ITLN-1 mRNA expression and surgical prognosis after liver resection. The ITLN-1 mRNA and protein levels were significantly higher in adjacent normal liver tissues than HCC tissues. Real-time fluorescence quantitative polymerase chain reaction showed that the ITLN-1 expression was decreased in 78.5% (117/149) of HCC tissues compared with their corresponding adjacent liver tissues. Moreover, its low expression was significantly correlated with increased tumor size, tumor differentiation degree, degree of liver cirrhosis, capsule integrity, vascular invasion and tumor recurrence. Patients with high ITLN-1 expression had significantly better overall and recurrence-free survival after curative liver resection. Multivariate cox regression analysis showed that ITLN-1 was an independent predictor of surgical outcomes in HCC patients. The present study suggested that low ITLN-1 expression was associated with poor clinical outcome for HCC patients, indicating a novel biomarker for prognosis evaluation and a potential therapeutic target for HCC patients.