Marker For Hepatocellular Carcinoma Research Articles

Interaction of STIL with FOXM1 regulates SF3A3 transcription in the hepatocellular carcinoma development

BackgroundDysregulation of SF3A3 has been related to the development of many cancers. Here, we investigated the functional role of SF3A3 in hepatocellular carcinoma (HCC).MethodsSF3A3 expression in HCC tissues and cell lines was examined using RT-qPCR. Changes in malignant behavior of HCC cells after downregulation of SF3A3 were assessed by EdU, colony formation, flow cytometry, wound healing, and Transwell invasion assays. Multiple datasets were combined to identify the upstream modifiers of SF3A3. The binding relationship between STIL and FOXM1 was explored by co-IP assay, and the effect of STIL and FOXM1 on the binding of FOXM1 at the SF3A3 promoter was detected by ChIP-qPCR assay. A xenograft tumor model was established to explore the changes of tumors in vivo, and the expression of Ki67, GPC3, and p53 in tumor tissues was detected by immunohistochemistry.ResultsSF3A3 and STIL were overexpressed in HCC tissues and cells, and downregulation of SF3A3 or STIL inhibited the malignant behavior of HCC cells by promoting the expression of p53. An interaction between STIL and FOXM1 regulated the SF3A3 expression in HCC cells. Knockdown of FOXM1 further enhanced the anti-tumor effects of STIL loss on HCC cells in vitro and in vivo, whereas SF3A3 overexpression overturned the impact of STIL loss on HCC cells in vitro and in vivo.ConclusionsOur findings indicate that STIL/FOXM1 expedites HCC development by activating SF3A3, which highlights the importance of SF3A3 as a promising prognostic marker and therapeutic target for HCC.

Migrasome-related prognostic signature TSPAN4 correlates with immune infiltrates and metabolic disturbances in hepatocellular carcinoma.

We aim to comprehensively analyze and validate the prognostic efficacy of tetraspanin 4 (TSPAN4) and several other migrasome-related markers in hepatocellular carcinoma (HCC). The expression, diagnostic, and prognostic efficacy of five migrasome-related genes in HCC were analyzed using several databases. Five pairs of adjacent non-tumor tissues and HCC tissues were used to validate the expression. The prognostic efficacy of TSPAN4 was validated in a HCC cohort. TSPAN4 was knocked down in Huh-7 cells, EdU, and CCK-8, and wound healing assays were conducted to analyze its effects on cell proliferation and migration. In addition, transcriptomic sequencing was used to identify differentially expressed genes. Compared with those in normal tissues, four genes (TSPAN4, PIGK, NDST1, and CPQ) were elevated in liver hepatocellular carcinoma (LIHC), but not TSPAN7. Of these, only elevated TSPAN4 predicted unfavorable prognosis of HCC patients. The expression and prognostic efficacy of TSPAN4 were further confirmed in a HCC cohort (97 patients); and patients in the TSPAN4high group showed unfavorable overall survival (log-rank P = 0.0055). Functional analysis showed that TSPAN4 knockdown significantly suppressed cell migration, but not cell proliferation. Moreover, TSPAN4 knockdown induced disturbances of the metabolic pathways, mainly pentose and glucuronate interconversions. TPSAN4 is a promising prognostic and therapeutic target for HCC treatment and may be involved in the metabolic pathways that affect disease progression.

Diagnostic Performance of PIVKA-II in Italian Patients with Hepatocellular Carcinoma

Background and Aims: Hepatocellular carcinoma (HCC) represents the second leading cause of cancer deaths worldwide. Six-month imaging along with alpha-fetoprotein (AFP) serum levels detection are the current gold standard to exclude HCC. Protein induced by vitamin K absence (PIVKA-II) has been proposed as a potential screening biomarker for HCC. This study was designed to evaluate the role of PIVKA-II as diagnostic HCC marker, and the correlation between PIVKA-II levels and HCC stage. Methods: PIVKA-II levels were assessed on serum samples of Italian patients. The study population included 80 patients with HCC, 111 with liver cirrhosis (LC), and 111 with chronic hepatitis C (CHC). Results: PIVKA-II serum levels progressively increase from patients with CHC to patients with HCC. In the HCC group, PIVKA-II values are higher in the more advanced stages of the disease, assessed by the Barcelona Clinic Liver Cancer (BCLC) staging system (BCLC-B vs. BCLC-A vs. BCLC-0). Youden’s index analysis identified a value >37 mAU/mL as the optimal threshold for the best combination of sensitivity and specificity (80% and 76%, respectively) and, at the best cut-off of 5.2 ng/mL, AFP yielded 53% specificity and 78% sensitivity. The combination of PIVKA-II and AFP reached positive and negative predictive values of 73.9% and 94.2%, respectively. Conclusions: PIVKA-II levels are increased in the HCC patients, compared to control groups. The increase is more evident in patients with advanced HCC. The diagnostic performance of PIVKA-II seems more sensitive than AFP while the combination of PIVKA-II and AFP resulted in the best diagnostic accuracy, reaching 73.9% positive predictive value and 94.2% negative predictive value, thus improving the diagnostic capability of the single marker.

Evaluation the Role of Lipocalin 2 as a New Non-Invasive Diagnostic Marker for Hepatocellular Carcinoma in Egyptian Cirrhotic Patients

Evaluation the Role of Lipocalin 2 as a New Non-Invasive Diagnostic Marker for Hepatocellular Carcinoma in Egyptian Cirrhotic Patients

Ezrin Polarization as a Diagnostic Marker for Circulating Tumor Cells in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third leading cause of cancer-related death worldwide, with no precise method for early detection. Circulating tumor cells (CTCs) expressing the dynamic polarity of the cytoskeletal membrane protein, ezrin, have been proposed to play a crucial role in tumor progression and metastasis. This study investigated the diagnostic and prognostic potential of polarized circulating tumor cells (p-CTCs) in HCC patients. CTCs were isolated from the peripheral blood of 20 HCC patients and 18 patients with nonmalignant liver disease (NMLD) via an OncoQuick® kit and immunostained with Ezrin-Alexa Fluor 488®, CD146-PE, and CD45-APC. A fluorescence microscopy was then performed for analysis. The HCC group exhibited significantly higher levels of p-CTCs, with median values of 0.56 p-CTCs/mL, compared to 0.02 p-CTCs/mL (p = 0.03) in the NMLD group. CTCs were detected in 95% of the HCC patients, with a sensitivity of 95% and specificity of 89%. p-CTCs were present in 75% of the HCC patients, with a sensitivity of 75% and a specificity of 94%. Higher p-CTC counts were associated with the significantly longer overall survival in HCC patients (p = 0.05). These findings suggest that p-CTCs could serve as valuable diagnostic and prognostic markers for HCC. The incorporation of p-CTCs into diagnostic strategies could enhance therapeutic decision-making and improve patient outcomes.

The survival prediction analysis and preliminary study of the biological function of YEATS2 in hepatocellular carcinoma.

Our study aims to develop and validate a novel molecular marker for the prognosis and diagnosis of hepatocellular carcinoma (HCC) MATERIALS & METHODS: We retrospectively analyzed mRNA expression profile and clinicopathological data of HCC patients fetched from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and The International Cancer Genome Consortium (ICGC) datasets. Univariate Cox regression analysis was performed to collect differentially expressed mRNA (DEmRNAs) from HCC and non-tumor tissues, and YEATS2, a prognostic marker, was identified by further analysis. ROC curve, survival analysis and multivariate Cox regression analysis as well as nomograms were used to evaluate the prognosis of this gene. Finally, the biological function of this gene was preliminarily discussed by using single gene Gene Set Enrichment Analysis (GSEA), and the YEATS2 overexpression and knockdown hepatoma cell line was used to verify the results in vitro and in vivo. Based on the clinical information of HCC in TCGA, GEO and ICGC databases, the gene YEATS2 with significant differences from HCC was identified. There was a statistical difference in the survival prognosis between the two databases and the ROC curve showed that the survival of HCC in both TCGA, GSE14520 and ICGC groups had a satisfactory predictive effect. Univariate and multivariate Cox regression analysis showed that YEATS2 was an independent prognostic factor for HCC, and Nomograms, which combined this prognostic feature with significant clinical features, provided an important reference for the clinical prognostic diagnosis of HCC. Next, we constructed overexpression and knockdown YEATS2 cell line in Hep3B and LM3 cells, and further proved that overexpression YEATS2 promote the proliferation and migration of HCC cells by CCK8, colony formation experiment, and transwell assays, and knockdown YEATS2 inhibited the proliferation and migration of HCC cells by CCK8, colony formation experiment, and transwell assays. Finally, the biological function of YEATS2 was preliminarily explored through GSEA analysis of a single gene, and it was found that it was significantly correlated with cell cycle and DNA repair, which provided us with ideas for further analysis. Furthermore, the knockdown of YEATS2 promoted radiation-induced DNA damage, enhanced radiosensitivity, and ultimately inhibited the proliferation of hepatocellular carcinoma cells in vitro and in vivo. Our study identified a promising prognostic marker for hepatocellular carcinoma that is useful for clinical decision-making and individualized treatment.

Cell-free DNA methylation-based inflammation score as a marker for hepatocellular carcinoma among people living with HIV.

People living with the human immunodeficiency virus (HIV) are at a greater risk of developing hepatocellular carcinoma (HCC), potentially due to the stimulation of inflammation by HIV infection. Inflammation-related DNA methylation signatures obtained in liquid biopsy, such as circulating cell-free DNA (cfDNA), may serve as promising minimally invasive biomarkers that can inform diagnosis of HCC. Using data from 249 individuals with HIV (114 individuals with normal liver conditions, 69 with fibrosis, 30 with cirrhosis, and 36 with HCC), we constructed a cfDNA methylation-based inflammation score (inflammation-DNAm score) based on 54 CpGs previously associated with circulating C-reactive protein concentrations. Associations of DNAm scores with HCC were assessed using multivariable logistic regression models. Receiver operating characteristic analysis was conducted to assess the performance of discriminating HCC between the inflammation-DNAm score and alpha-fetoprotein (AFP), one of the current screening biomarkers. A higher inflammation-DNAm score was associated with a 29% increase in the odds of HCC (OR = 1.29, 95% CI = 1.01-1.65). The association remained consistent in the models adjusted for cellular origin proportions. The DNAm score exhibited superior performance in discriminating HCC from controls (AUC = 0.94, 95% CI = 0.90-0.98), compared to AFP (AUC = 0.68, 95% CI = 0.51-0.85). Our findings suggest that cfDNA methylation-based biomarkers may aid in the detection of HCC in people living with HIV, a population at high-risk of developing HCC.

Telomere-methylation genes: Novel prognostic biomarkers for hepatocellular carcinoma.

Since telomere length and DNA methylation both correlate with hepatocellular carcinoma (HCC) prognosis, telomere-methylation genes could be novel prognostic markers for HCC. This study first investigated the interaction between telomere length and DNA methylation in HCC through Mendelian randomization analysis. Then, this study identified telomere-methylation genes in HCC by employing the TCGA-LIHC cohort, and explored the expression patterns of these genes in the tumor microenvironment of HCC and potential underlying mechanisms. Finally, the HCC risk-scoring model and prognostic model based on these genes were established, and the performance of the model was assessed. The findings revealed a bidirectional relationship between telomere length and DNA methylation in HCC. Fifty telomere-methylation genes were identified, and the prognosis-related telomere-methylation genes were closely associated with Treg and Tprolif cell subsets within the HCC tumor microenvironment. Telomere-methylation genes could potentially impact the prognosis of HCC patients by modulating chromosome stability and regulating the cell cycle. Additionally, the constructed risk scoring model and prognostic prediction model showcased compelling clinical applicability, as evidenced by the receiver operating characteristic curve, the decision curve analysis, and the calibration curves. This study elucidated the potential of telomere-methylation genes as prognostic biomarkers for HCC and paves the way for novel approaches in prognostication and treatment management for HCC patients.

Molecular and immune landscape of hepatocellular carcinoma for therapeutic development.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, with an estimated 750,000 deaths in 2022. Recent emergence of molecular targeted agents (MTAs) and immune checkpoint inhibitors (ICIs) and their combination therapies have been transforming HCC care, but their prognostic impact in advanced-stage disease remains unsatisfactory. In addition, their application to early-stage disease is still an unmet need. Omics profiling studies have elucidated recurrent and heterogeneously present molecular aberrations involved in pro-cancer tumor (immune) microenvironment that may guide therapeutic strategies. Recurrent aberrations such somatic mutations in TERT promoter and TP53 have been regarded undruggable, but recent studies have suggested that these may serve as new classes of therapeutic targets. HCC markers such as alpha-fetoprotein (AFP), glypican-3 (GPC3), and epithelial cell adhesion molecule (EpCAM) have also been explored as therapeutic targets. These molecular features may be utilized as biomarkers to guide the application of new approaches as companion biomarkers to maximize therapeutic benefits in patients who are likely to benefit from the therapies, while minimizing unnecessary harm in patients who will not respond. The explosive number of new agents in the pipelines have posed challenges in their clinical testing. Novel clinical trial designs guided by predictive biomarkers have been proposed to enable their efficient and cost-effective evaluation. These new developments collectively facilitate clinical translation of personalized molecular-targeted therapies in HCC and substantially improve prognosis of HCC patients.

The fabrication of phosphotungstate@UIO-Au/reduced graphene oxidation for electrochemical ultrasensitive detection of alpha-fetoprotein.

As an early multi-purpose tumor marker of hepatocellular carcinoma, alpha-fetoprotein (AFP) plays a vital role in early diagnosis and treatment. To achieve the early and accurate determination of AFP, the POMOF was fabricated by embedding H3PW12O40 (PW12) into UIO-66-NH2, further immobilized on reduced GO (rGO) and fabricated an innovative POMOF nanocomposite (PW@UIO-Au/rGO) as an electrochemical immunosensor (ECI-sensor). The PW@UIO-Au/rGO achieved 17-fold signal enhancement owing to their synergistic effect, enabling PW@UIO-Au/rGO exhibit high oxidase-like catalytic activity, facilitating their sensing performance. Under optimal experimental conditions, the proposed PW@UIO-Au/rGO ECI-sensor presented excellent sensing performance over a wide range from 0.01ngmL-1 to 500ngmL-1 with ultra-low detection of 4.0pgmL-1. Notably, sensing results in real serum samples were verified by the clinical enzyme-linked immunosorbent assay (ELISA) and electrochemiluminescence immunoassay (ECL) methods with excellent accuracy and consistency, indicating the excellent environmental tolerance of the proposed ECI-sensor. This work provided a promising strategy for designing feasible ultra-sensitive probe for sensing AFP in clinical test.

Preoperative prediction of Ki-67 expression in hepatocellular carcinoma by spectral imaging on dual-energy computed tomography (DECT).

The Ki-67 expression level, which represents the proliferation status of cells, serves as a prognostic marker for hepatocellular carcinoma (HCC); however, the immunochemistry method currently used to evaluate Ki-67 is invasive and is not suitable for patients who have lost the chance for surgery, such as those with advanced tumors or those with other serious organic diseases. This study aimed to investigate the value of quantitative dual-energy computed tomography (DECT) parameters in predicting the expression level of Ki-67 in HCC. This study analyzed the data of 123 consecutive patients with HCC who underwent both Ki-67 immunohistochemistry analysis and two-phase contrast-enhanced DECT imaging. The patients were divided into the following two groups based on the positive rate of Ki-67 (Ki-67%): the high-expression group (Ki-67% >20%, n=74); and the low-expression group (Ki-67% ≤20%, n=49). The computed tomography (CT) values in the 130 and 140 keV monochromatic energy images (HU130-140keV), normalized effective atomic number (NeffZ), fat density (Dfat), and water density (Dwater) were measured and calculated at the arterial phase (AP) and portal venous phase (PVP). A Spearman correlation coefficient analysis, a comparison of parameters between groups, a receiver operating characteristic (ROC) curve analysis for evaluating predictive efficacy, and a multivariable logistic regression analysis were conducted. The NeffZ-AP, HU130 keV-PVP, HU140 keV-PVP, Dfat-PVP, and Dwater-PVP were positively correlated with the Ki-67% (all P<0.05), and the DECT parameter values in the high-expression group were significantly higher than those in the low-expression group (all P<0.05). The Dwater-PVP [odds ratio (OR) =1.353, 95% confidence interval (CI): 1.204-1.521, P<0.001] and tumor diameter (OR =1.258, 95% CI: 1.08-1.465, P=0.003) were independent predictive factors for high Ki-67 expression. Dwater-PVP had the highest predictive efficacy with an area under the curve (AUC) of 0.810. The multivariable analysis combining the DECT parameters and morphological characteristics improved the predictive efficacy of the model in predicting high Ki-67 expression (AUC =0.857). DECT provides a non-invasive method to evaluate the proliferation status of HCC cells, and the predictive efficacy of high Ki-67 expression could be improved by combining DECT parameters and morphologic features.

The combination of serum lncRNA PTTG3P and mRNA PTTG1 serves as a diagnostic and prognostic marker for hepatocellular carcinoma.

Long noncoding RNA (lncRNA) PTTG3P has been demonstrated to participate in the development of hepatocellular carcinoma (HCC) by targeting the mRNA PTTG1. The present study aimed to investigate the diagnostic efficacy of serum lncRNA PTTG3P, mRNA PTTG1 and their combination for the diagnosis and prognosis of HCC. A total of 373 participants were enrolled in the present study, including 73 patients with HCC, 100 patients with chronic hepatitis B (CHB), 100 patients with liver cirrhosis (LC) and 100 healthy controls (HCs). The expression levels of serum RNAs were quantified by reverse transcription‑quantitative PCR. The association between serum lncRNA PTTG3P and clinical characteristics was further analyzed. Receiver operating characteristic (ROC) curve and area under curve (AUC) analyses were performed to estimate the diagnostic ability of serum lncRNA PTTG3P, PTTG1 and their combinations with other biomarkers for HCC. The results revealed that the expression levels of lncRNA PTTG3P and mRNA PTTG1 were markedly increased in the serum of patients with HCC and CHB compared with in the serum of HCs. Additionally, the postoperative levels of lncRNA PTTG3P and mRNA PTTG1 were significantly lower than the preoperative concentrations in 36 paired patients with HCC. Spearman's correlation coefficient analysis showed that serum lncRNA PTTG3P was correlated with aspartate transaminase (AST). ROC analysis showed that both lncRNA PTTG3P and mRNA PTTG1 had a significant predictive value for HCC. The AUC values of lncRNA PTTG3P and mRNA PTTG1 alone were 0.636 and 0.634, respectively. Furthermore, combining lncRNA PTTG3P, mRNA PTTG1, α‑fetoprotein (AFP), alanine aminotransferase (ALT), AST, γ‑glutamyl transpeptidase (GGT) and alkaline phosphatase (ALP) significantly increased the AUC value. The best performance was the combination of PTTG3P, PTTG1, AFP, ALT, AST, GGT and ALP with an AUC of 0.959, a sensitivity of 90.4% and a specificity of 98.0%. In conclusion, the combination of serum lncRNA PTTG3P, mRNA PTTG1 and AFP appeared to be a noninvasive biomarker with comparatively high specificity and sensitivity for the diagnosis of HCC.

M2BPgs-HCC: An Automated Multilectin Bead Array Indicating Aberrant Glycosylation Signatures Toward Hepatitis C Virus-Associated Hepatocellular Carcinoma Prognosis.

Regular monitoring of patients with a history of hepatitis C virus (HCV) infection is critical for the detection and management of hepatocellular carcinoma (HCC). Mac-2 binding protein glycosylation isomer (M2BPGi) has been used to monitor fibrosis progression and predict HCC. However, HCC prediction based on M2BPGi has not been optimized. Here, we identified HCC risk-related glycan signatures of M2BP using a newly developed automated bead array with multiplexed lectins. Among 955 patients with HCV who achieved sustained virological response following direct-acting antiviral treatment, we compared M2BP glycosylation from sera of 42 patients diagnosed with HCC during follow-up and 43 without HCC (control) by the lectin microarray. At the HCC observation point, we found significant differences in 17 lectins. Using an automated bead array with 12 of 17 lectins, a principal component analysis (PCA) biplot differentiated HCC from control, along the PC1 axis, explaining 75.2% of variance. Based on PC1, we generated a scoring formula for an HCC-related glycosylation signature on M2BP (M2BPgs-HCC), showing good diagnostic performance for HCC (p = 2.92 × 10-8, AUC = 0.829). This automated multilectin bead array improved the ability of M2BP to detect HCC, providing a candidate test for HCC surveillance in combination with other HCC markers.

SLC1A3 is a novel prognostic biomarker associated with immunity and EMT in hepatocellular carcinoma

PurposeSolute carrier family 1 member 3(SLC1A3), a member of the glutamate transporter family, is implicated in the progression of gastric carcinoma and the renewal of thyroid carcinoma stem cells. The purpose of this work is to use experimental validation and bioinformatics analysis to look at the possible involvement of SLC1A3 in hepatocellular carcinoma (HCC).Materials and methodsWe examined the levels of SLC1A3 within HCC and its implications on immunological and epithelial–mesenchymal transition (EMT) features using the TCGA, ImmPort, and Molecular Signatures databases. The relationship between drug sensitivity and SLC1A3 expression was investigated using the GDSC database. Real-time quantitative polymerase chain reaction (qRT-PCR), Western blotting (WB), and cellular function assays were performed to assess SLC1A3 expression and its carcinogenic effects in HCC.ResultsAccording to our research, SLC1A3 overexpression in HCC is associated with a poor prognosis. Elevated levels of SLC1A3 promote HCC cell motility and invasion and can affect the prognosis of HCC by modifying immune responses and epithelial–mesenchymal transition. SLC1A3 has emerged as a novel prognostic marker in HCC and is associated with resistance to certain antitumor drugs.ConclusionSLC1A3 functions as a cancer-promoting factor contributing to poor HCC prognosis by affecting immune cell infiltration and regulating the EMT process. Elevated SLC1A3 expression may also serve as a predictor of treatment response to specific antitumor drugs.

Non-Coding RNAs as Potential Diagnostic/Prognostic Markers for Hepatocellular Carcinoma.

The increasing incidence of hepatocellular carcinoma (HCC), together with the poor effectiveness of the available treatments, make early diagnosis and effective screening of utmost relevance. Liquid biopsy represents a potential novel approach to early HCC detection and monitoring. The identification of blood markers has many desirable features, including the absence of any significant risk for the patients, the possibility of being used as a screening tool, and the ability to perform multiple tests, thus allowing for the real-time monitoring of HCC evolution. Unfortunately, the available blood markers for HCC have several limitations, mostly related to specificity and sensitivity. In this context, employing non-coding RNAs (ncRNAs) may represent an interesting and novel diagnostic approach. ncRNAs, which include, among others, micro interfering RNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), regulate human gene expression via interactions with their target mRNA. Notably, their expression can be altered in HCC, thus reflecting disease status. In this review, we discuss some notable works that describe the use of miRNAs, lncRNAs, and circRNAs as HCC biomarkers. Despite some open aspects related to ncRNA use, the presented works strongly support the potential effectiveness of these molecules as diagnostic/prognostic markers for HCC.

Serum amyloid A level as a marker of hepatocellular carcinoma in HCV-induced liver cirrhosis

Serum amyloid A level as a marker of hepatocellular carcinoma in HCV-induced liver cirrhosis

SLC41A1 overexpression correlates with immune cell infiltration in HCC and promotes its malignant progression.

Solute carrier 41 (SLC41) has been identified as a family of magnesium (Mg2+) transporters that participate in various diseases, including tumor development and progression. Recent studies revealed SLC41A3 acted as an oncogene and predicted poor survival for hepatocellular carcinoma (HCC) patients. However, the potential function of SLC41A1 in HCC remains unclear. In our study, we focused on the levels and putative mechanisms of SLC41A1 in HCC. Using bioinformatics techniques, we found SLC41A1 was upregulated in HCC, which was verified by immunostaining of HCC patients. SLC41A1 was correlated with clinicopathological characteristics, and could be utilized as independently diagnostic and prognostic markers for HCC. By exploring MethSurv website, DNA methylation was identified in SLC41A1, and several methylated CpG sites might affect overall survival of HCC patients. Using Gene Ontology (GO) , Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), protein-protein interaction (PPI) network, we found SLC41A1 overexpression was related to several tumor-promoting pathways and molecules, such as degradation of extracellular matrix, cell adhesion and O-linked glycosylation, and expression of CXCL1, CXCL5 and MUC1. The results of single-sample GSEA (ssGSEA) showed SLC41A1 might regulate infiltration of multiple immune cells, resulting in the imbalance between immune suppression and immune surveillance. Cellular experiments showed that knockdown of SLC41A1 inhibited proliferation, migration and invasion of HCC, whereas SLC41A1 overexpression exerted the tumor-promoting effects. Collectively, our results shed light on new insights into expression, putative roles and mechanisms of SLC41A1 in HCC, providing novel diagnostic biomarkers and therapeutic targets for HCC.

Unveiling Tim-3 immune checkpoint expression in hepatocellular carcinoma through abdominal contrast-enhanced CT habitat radiomics.

Immune checkpoint inhibitors (ICIs) are important systemic therapeutic agents for hepatocellular carcinoma (HCC), among which T-cell immunoglobulin and mucin-domain containing protein 3 (Tim-3) is considered an emerging target for ICI therapy. This study aims to evaluate the prognostic value of Tim-3 expression and develop a predictive model for Tim-3 infiltration in HCC. We collected data from 424 HCC patients in The Cancer Genome Atlas (TCGA) and data from 102 pathologically confirmed HCC patients from our center for prognostic analysis. Multivariate Cox regression analyses were performed on both datasets to determine the prognostic significance of Tim-3 expression. In radiomics analysis, we used the K-means algorithm to cluster regions of interest in arterial phase enhancement and venous phase enhancement images from patients at our center. Radiomic features were extracted from three subregions as well as the entire tumor using pyradiomics. Five machine learning methods were employed to construct Habitat models based on habitat features and Rad models based on traditional radiomic features. The predictive performance of the models was compared using ROC curves, DCA curves, and calibration curves. Multivariate Cox analyses from both our center and the TCGA database indicated that high Tim-3 expression is an independent risk factor for poor prognosis in HCC patients. Higher levels of Tim-3 expression were significantly associated with worse prognosis. Among the ten models evaluated, the Habitat model constructed using the LightGBM algorithm showed the best performance in predicting Tim-3 expression status (training set vs. test set AUC 0.866 vs. 0.824). This study confirmed the importance of Tim-3 as a prognostic marker in HCC. The habitat radiomics model we developed effectively predicted intratumoral Tim-3 infiltration, providing valuable insights for the evaluation of ICI therapy in HCC patients.

Fibroblast Heterogeneity in Hepatocellular Carcinoma and Identification of Prognostic Markers Based on Single-cell Transcriptome Analysis.

HCC is a malignant tumor with high morbidity and mortality. Fibroblasts play a key role in the tumor microenvironment (TME). However, the transcriptional regulatory mechanisms of fibroblasts remained unclear in HCC. The aim of this study was to explore the complex role of fibroblasts in hepatocellular carcinoma (HCC) and to reveal their transcriptional regulatory mechanisms. The goal of this study was to discover potential prognostic markers for HCC by analyzing the genetic variations and differentiation process of fibroblasts. Single-cell transcriptome data from the non-tumor liver site and primary tumor site of HCC were acquired from GSE149614, processed, and clustered using the Seurat pipeline. The inferCNV algorithm was applied to infer copy number variations (CNVs) in fibroblasts. Subsequently, the mechanism underlying the interaction between fibroblasts and other cells in the TME of HCC was analyzed using CellChat software. The trajectory of cellular differentiation of fibroblasts from normal state to malignant state was examined using Monocle 2. SCENIC analysis was performed to identify key transcription factors (TFs) in fibroblasts and assess their correlation with HCC prognosis. Finally, qRT-PCR and Transwell assays were carried out to analyze the mRNA expression and cell metastasis. We identified a total of nine different cell types (B cells, cycling cells, endothelial cells, epithelial cells, fibroblasts, hepatocytes, macrophages, plasma cells, and T cells) based on the single-cell transcriptomic data of HCC. Among them, fibroblasts were highly enriched at the primary tumor site, and their number increased with advanced stages. In addition, significant deletions were detected on chromosome 6p of fibroblasts, and genes in this region were remarkably enriched in pathways associated with antigen processing and presentation. Intercellular communication showed that epithelial cells regulated fibroblasts the most. The differentiation of fibroblasts was mainly accompanied by a transition from normal to malignant state. Importantly, CEBPD and FOSB, the TFs most associated with the putative timing of fibroblasts, were under-expressed in human hepatocytes and showed a significant correlation with HCC prognosis. Overexpressed CEBPD inhibited HCC cell migration and invasion. In conclusion, our study revealed that fibroblast recruitment and differentiation, as well as copy number loss at chromosome 6p, were associated with a higher degree of malignancy and immune dysfunction in HCC. The current discoveries provided new insights into the clinical treatment and diagnosis of HCC.

Regulatory Role of Long Noncoding RNAs LINC00449 in Hepatocellular Carcinoma Mechanism and Prognosis Via Sponge miR-329-3p/KIF5A Axis.

Hepatocellular carcinoma (HCC) is a globally prevalent malignant tumor with high recurrence and mortality rates. Long noncoding RNAs (lncRNAs) have been utilized to investigate the progression of various cancers, including HCC. The objective of this research is to explore the mechanism and prognostic impact of lncRNA LINC00449 on HCC. LINC00449 and miR-329-3p levels in HCC were measured using RT-qPCR. The impact of high- or lowLINC00449 expression on survival was tested. CCK-8, plate cloning, flow cytometry, and Transwell assays were selected to assess the biological functions of HCC cells. Kaplan-Meier and multivariate Cox analyses were conducted to evaluate the potential of LINC00449 as a prognostic marker for HCC. The interaction between LINC00449, miR-329-3p, and KIF5A was investigated through luciferase activity assays. LINC00449 expression in HCC tissues was increased. Silencing of LINC00449 improved the survival prospects of patients with HCC. Moreover, LINC00449 targeting the miR-329-3p/KIF5A axis influences the progression of HCC. LINC00449 may become a biomarker for the prognosis of HCC, and the LINC00449/miR-329-3p/KIF5A regulatory network mediates the deterioration of HCC.