Associations of Serum Tumor Biomarkers with Integrated Genomic and Clinical Characteristics of Hepatocellular Carcinoma

Using signal off-to-on strategy for designing precise and ultrasensitive biosensor towards hepatocellular carcinoma through protein variant detection based on biocompatible bimetallic MOF

The high mortality rate of patients with hepatocellular carcinoma (HCC) is an ever-increasing worldwide concern. Fortunately, the newest research has found that the proportion of a protein variant in total alpha-fetoprotein (AFP) over 10 % can accurately predict the incidence of HCC. Therefore, a signal off-to-on strategy was designed for developing a novel precise and ultrasensitive biosensor towards HCC through protein variant detection based on bimetallic metal-organic framework (MOF). In this study, the biocompatible Fe2Ni-MOF was used as an electrochemically immobilized carrier, which provided abundant active sites and exhibited a synergistic effect between Fe and Ni ions for dramatically promoting the electron transfer and improving the electrochemical reduction efficiency, prominently facilitating signal amplification of the biosensing platform. Then, we designed a novel ordered labeling method to distinguish AFP-L3 from overall AFP and introduced a signal off-to-on strategy for achieving highly efficient determination of AFP-L3 %. This proposed biosensor demonstrated a satisfactory linear range, along with a very low detection limit of 69 pg/mL for AFP-L3, which was far below the medically relevant threshold level. Furthermore, the adopted biosensor presented preeminent specificity, and favorable reproducibility.

Fatty acid metabolism shapes immune responses in chronic lymphocytic leukemia

BACKGROUND

Fatty acids serve as a crucial energy source for tumor cells during the progression of chronic lymphocytic leukemia (CLL). The present study aims to elucidate the characteristics of fatty acid metabolism (FAM) in CLL, construct a related prognostic score, and investigate the regulatory role and mechanisms of FAM in CLL development.

METHODS

Bulk RNA sequencing data from CLL patients and healthy controls were analyzed to identify differentially expressed fatty acid metabolic genes. FAM-score was constructed using Cox-LASSO regression and validated. Single-cell RNA sequencing was used to analyze the expression of key FAM genes in CLL immune cell subsets and investigate cellular communication. Functional assays, including cell viability, drug sensitivity, and oxygen consumption assays, were performed to assess the impact of fatty acid oxidation (FAO) inhibition on CLL cells.

RESULTS

Three FAM-related genes (LPL, SOCS3, CNR1) were identified with independent prognostic significance to construct the risk score. The FAM-score demonstrated superior prognostic performance compared to the Binet stage and was associated with established clinical prognostic markers. Single-cell analysis revealed distinct expression patterns of LPL, SOCS3, and CNR1 across CLL immune cell subsets. Cellular communication analysis highlighted the regulatory role of distinct B cell and Treg subsets in the CLL microenvironment. CLL patients with high FAM-score displayed distinct immune infiltration patterns, with increased FAO pathway activity. Inhibition of FAO reduced CLL cell viability, synergistically enhanced the efficacy of the PI3K inhibitor idelalisib.

CONCLUSION

The present study constructed a prognostic risk score based on FAM gene expression, revealing related immune phenotypic differences and exploring the regulatory role of FAO in CLL development. Targeting fatty acid metabolism potentially modulates the CLL immune microenvironment and synergistically enhances the efficacy of PI3K inhibitors.

Comprehensive analysis of protein post-translational modifications reveals PTPN2-STAT1-AOX axis-mediated tumor progression in hepatocellular carcinomas

Hepatocellular carcinoma (HCC) is a common malignant tumor. Although the proteomics of HCC is well studied, the landscape of post-translational modifications (PTMs) in HCC is poorly understood. The PTMs themselves and their crosstalk might be deeply involved in HCC development and progression. Herein, we investigated nine types of PTMs in paired tumor and normal tissues from nine patients with HCC using the label-free quantitative liquid chromatography with tandem mass spectrometry (LC-MS)-based technique. We identified >60,000 modified sites, and found that phosphorylation and ubiquitination were two most frequently changed PTMs between tumor and normal tissues. Crosstalk between malonylation-ubiquitination, phosphorylation-ubiquitination, and succinylation-propionylation were most significant among all PTMs. Further analysis revealed that Thr-160 of CDK2 regulated EZH2 via H3K27me3, and proposed a PTPN2-STAT1-AOX1 axis for HCC development through driver PTM exploration. In conclusion, our study provides a database of multiple PTMs in HCC, which might help to understand the biology of HCC and reveal novel targets for drug development.

Surveillance for Hepatocellular Carcinoma

This article reviews surveillance for the detection of early stage hepatocellular carcinoma, covering the rationale for surveillance, optimal selection of persons needing surveillance, methods and frequency of screening, strategies for addressing barriers to surveillance, and trends for future improvement in surveillance leading to more effective cancer control and improved patient outcomes. The importance of integrating liver cancer surveillance as a core component of national public health programs is emphasized. The impact of emerging technologies for identifying persons at risk, stratifying individual risk to improve the cost-effectiveness of surveillance programs, and improving the performance, accessibility, and convenience of surveillance are discussed.

HnRNPR-mediated UPF3B mRNA splicing drives hepatocellular carcinoma metastasis

INTRODUCTION

Abnormal alternative splicing (AS) contributes to aggressive intrahepatic invasion and metastatic spread, leading to the high lethality of hepatocellular carcinoma (HCC).

OBJECTIVES

This study aims to investigate the functional implications of UPF3B-S (a truncated oncogenic splice variant) in HCC metastasis.

METHODS

Basescope assay was performed to analyze the expression of UPF3B-S mRNA in tissues and cells. RNA immunoprecipitation, and in vitro and in vivo models were used to explore the role of UPF3B-S and the underlying mechanisms.

RESULTS

We show that splicing factor HnRNPR binds to the pre-mRNA of UPF3B via its RRM2 domain to generate an exon 8 exclusion truncated splice variant UPF3B-S. High expression of UPF3B-S is correlated with tumor metastasis and unfavorable overall survival in patients with HCC. The knockdown of UPF3B-S markedly suppresses the invasive and migratory capacities of HCC cells in vitro and in vivo. Mechanistically, UPF3B-S protein targets the 3'-UTR of CDH1 mRNA to enhance the degradation of CDH1 mRNA, which results in the downregulation of E-cadherin and the activation of epithelial-mesenchymal transition. Overexpression of UPF3B-S enhances the dephosphorylation of LATS1 and the nuclear accumulation of YAP1 to trigger the Hippo signaling pathway.

CONCLUSION

Our findings suggest that HnRNPR-induced UPF3B-S promotes HCC invasion and metastasis by exhausting CDH1 mRNA and modulating YAP1-Hippo signaling. UPF3B-S could potentially serve as a promising biomarker for the clinical management of invasive HCC.

Prediction of microvascular invasion in hepatocellular carcinoma with conventional ultrasound, Sonazoid-enhanced ultrasound, and biochemical indicator: a multicenter study

PURPOSE

To develop and validate a preoperative prediction model based on multimodal ultrasound and biochemical indicator for identifying microvascular invasion (MVI) in patients with a single hepatocellular carcinoma (HCC) ≤ 5 cm.

METHODS

From May 2022 to November 2023, a total of 318 patients with pathologically confirmed single HCC ≤ 5 cm from three institutions were enrolled. All of them underwent preoperative biochemical, conventional ultrasound (US), and contrast-enhanced ultrasound (CEUS) (Sonazoid, 0.6 mL, bolus injection) examinations. Univariate and multivariate logistic regression analyses on clinical information, biochemical indicator, and US imaging features were performed in the training set to seek independent predictors for MVI-positive. The models were constructed and evaluated using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis in both validation and test sets. Subgroup analyses in patients with different liver background and tumor sizes were conducted to further investigate the model's performance.

RESULTS

Logistic regression analyses showed that obscure tumor boundary in B-mode US, intra-tumoral artery in pulsed-wave Doppler US, complete Kupffer-phase agent clearance in Sonazoid-CEUS, and biomedical indicator PIVKA-II were independently correlated with MVI-positive. The combined model comprising all predictors showed the highest AUC, which were 0.937 and 0.893 in the validation and test sets. Good calibration and prominent net benefit were achieved in both sets. No significant difference was found in subgroup analyses.

CONCLUSIONS

The combination of biochemical indicator, conventional US, and Sonazoid-CEUS features could help preoperative MVI prediction in patients with a single HCC ≤ 5 cm.

CRITICAL RELEVANCE STATEMENT

Investigation of imaging features in conventional US, Sonazoid-CEUS, and biochemical indicators showed a significant relation with MVI-positivity in patients with a single HCC ≤ 5 cm, allowing the construction of a model for preoperative prediction of MVI status to help treatment decision making.

KEY POINTS

MVI status is important for patients with a single HCC ≤ 5 cm. The model based on conventional US, Sonazoid-CEUS and PIVKA-II performs best for MVI prediction. The combined model has potential for preoperative prediction of MVI status.

A Machine Learning-Based Clustering Using Radiomics of F-18 Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography for the Prediction of Prognosis in Patients with Intrahepatic Cholangiocarcinoma

BACKGROUND

Intrahepatic cholangiocarcinoma (IHCC) is highly aggressive primary hepatic malignancy with an increasing incidence.

OBJECTIVE

This study aimed to develop machine learning-based radiomic clustering using F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for predicting recurrence-free survival (RFS) and overall survival (OS) in IHCC.

METHODS

We retrospectively reviewed pretreatment F-18 FDG PET/CT scans of 60 IHCC patients who underwent surgery without neoadjuvant treatment between January 2008 and July 2020. Radiomic features such as first order, shape, and gray level were extracted from the scans of 52 patients and analyzed using unsupervised hierarchical clustering.

RESULTS

Of the 60 patients, 36 experienced recurrence and 31 died during follow-up. Eight patients with a negative FDG uptake were classified as Group 0. The unsupervised hierarchical clustering analysis divided the total cohort into three clusters (Group 1: n = 27; Group 2: n = 23; Group 3: n = 2). The Kaplan-Meier curves showed significant differences in RFS and OS among the clusters (p < 0.0001). Multivariate analyses showed that the PET radiomics grouping was an independent prognostic factor for RFS (hazard ratio (HR) = 3.03, p = 0.001) and OS (HR = 2.39, p = 0.030). Oxidative phosphorylation was significantly activated in Group 1, and the KRAS, P53, and WNT β-catenin pathways were enriched in Group 2.

CONCLUSIONS

This study demonstrated that machine learning-based PET radiomics clustering can preoperatively predict prognosis and provide valuable information complementing the genomic profiling of IHCC.

Biomarker discovery in hepatocellular carcinoma (HCC) for personalized treatment and enhanced prognosis

Hepatocellular carcinoma (HCC) is a leading contributor to cancer-related deaths worldwide and presents significant challenges in diagnosis and treatment due to its heterogeneous nature. The discovery of biomarkers has become crucial in addressing these challenges, promising early detection, precise diagnosis, and personalized treatment plans. Key biomarkers, such as alpha fetoprotein (AFP) glypican 3 (GPC3) and des gamma carboxy prothrombin (DCP) have shown potential in improving clinical results. Progress in proteomic technologies, including next-generation sequencing (NGS), mass spectrometry, and liquid biopsies detecting circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA), has deepened our understanding of HCC's molecular landscape. Immunological markers, like PD-L1 expression and tumor-infiltrating lymphocytes (TILs), also play a crucial role in guiding immunotherapy decisions. Despite these advancements, challenges remain in biomarker validation, standardization, integration into clinical practice, and cost-related barriers. Emerging technologies like single-cell sequencing and machine learning offer promising avenues for further exploration. Continued investment in research and collaboration among researchers, healthcare providers, and policymakers is vital to harness the potential of biomarkers fully, ultimately revolutionizing HCC management and improving patient outcomes through personalized treatment approaches.

Integrated Exploration of Epigenetic Dysregulation Reveals a Stemness/EMT Subtype and MMP12 Linked to the Progression and Prognosis in Hepatocellular Carcinoma

Epigenetic dysregulation drives aberrant transcriptional programs playing a critical role in hepatocellular carcinoma (HCC), which may provide novel insights into the heterogeneity of HCC. This study performed an integrated exploration on the epigenetic dysregulation of miRNA and methylation. We discovered and validated three patterns endowed with gene-related transcriptional traits and clinical outcomes. Specially, a stemness/epithelial-mesenchymal transition (EMT) subtype was featured by immune exhaustion and the worst prognosis. Besides, MMP12, a characteristic gene, was highly expressed in the stemness/EMT subtype, which was verified as a pivotal regulator linked to the unfavorable prognosis and further proven to promote tumor proliferation, invasion, and metastasis in vitro experiments. Proteomic analysis by mass spectrometry sequencing also indicated that the overexpression of MMP12 was significantly associated with cell proliferation and adhesion. Taken together, this study unveils innovative insights into epigenetic dysregulation and identifies a stemness/EMT subtype-specific gene, MMP12, correlated with the progression and prognosis of HCC.

Proteomics-driven noninvasive screening of circulating serum protein panels for the early diagnosis of hepatocellular carcinoma

Early diagnosis of hepatocellular carcinoma (HCC) lacks highly sensitive and specific protein biomarkers. Here, we describe a staged mass spectrometry (MS)-based discovery-verification-validation proteomics workflow to explore serum proteomic biomarkers for HCC early diagnosis in 1002 individuals. Machine learning model determined as P4 panel (HABP2, CD163, AFP and PIVKA-II) clearly distinguish HCC from liver cirrhosis (LC, AUC 0.979, sensitivity 0.925, specificity 0.915) and healthy individuals (HC, AUC 0.992, sensitivity 0.975, specificity 1.000) in an independent validation cohort, outperforming existing clinical prediction strategies. Furthermore, the P4 panel can accurately predict LC to HCC conversion (AUC 0.890, sensitivity 0.909, specificity 0.877) with predicting HCC at a median of 11.4 months prior to imaging in prospective external validation cohorts (No.: Keshen 2018_005_02 and NCT03588442). These results suggest that proteomics-driven serum biomarker discovery provides a valuable reference for the liquid biopsy, and has great potential to improve early diagnosis of HCC.

Significance of circulating tumor cells detection in tumor diagnosis and monitoring

To detect circulating tumor cells (CTCs) in the peripheral blood of patients with tumor, and to analyze the significance of CTC detection in tumor diagnosis and monitoring. In the present study, peripheral blood was collected from 125 patients with tumor, and CTCs were isolated and identified. Differences in CTC number and subtype detection were analyzed for different tumor diseases and stages. CTCs were detected in 122 of the 125 patients with tumor, with a positive rate of 97.6%. The number of CTCs increases in patients with vascular metastasis. The number of mesenchymal CTCs increases in patients with lymph node or vascular metastasis. The average ratio of epithelial CTCs in each positive sample decreases in the later stages of cancer compared with the earlier stages, while the average ratio of mesenchymal CTCs increases in the later stages of cancer compared with the earlier stages. The results showed that CTCs with mesenchymal phenotypes are closely related to lymph node or vascular metastasis. CTC detection can help with early diagnosis of tumor diseases. Continuous monitoring of changes in CTCs number and subtypes can assist clinical judgment of tumor disease development status and prognosis.

Oncogenic pathways refine a new perspective on the classification of hepatocellular carcinoma

BACKGROUND

Genetic alterations in oncogenic pathways are critical for cancer initiation, development, and treatment resistance. However, studies are limited regarding pathways correlated with prognosis, sorafenib, and transcatheter arterial chemoembolization (TACE) in hepatocellular carcinoma (HCC).

METHODS

In this study, 1928 patients from 11 independent datasets and a clinical in-house cohort were screened to explore the relationships among canonical pathway alterations in HCC patients. The molecular mechanisms, biological functions, immune landscape, and clinical outcomes among three heterogeneous phenotypes were further explored.

RESULTS

We charted the detailed landscape of pathway alterations in the TCGA-LIHC cohort, screened three pivotal pathways (p53, PI3K, and WNT), identified co-occurrence patterns and mutual exclusively, and stratified patients into three altered-pathway dominant phenotypes (ADPs). P53|PI3K ADP characterized by genomic instability (e.g., highest TMB, FGA, FGG, and FGL) indicated an unfavorable prognosis. While, patients in WNT ADP suggested a median prognosis, enhanced immune activation, and sensitivity to PD-L1 therapy. Remarkably, sorafenib and TACE exhibited efficacy for patients in WNT ADP and low frequent alteration phenotype (LFP). Additionally, ADP could work independently of common clinical traits (e.g., AJCC stage) and previous molecular classifications (e.g., iCluster, serum biomarkers).

CONCLUSIONS

ADP provides a new perspective for identifying patients at high risk of recurrence and could optimize precision treatment to improve the clinical outcomes in HCC.

Validation of combined AFP, AFP-L3, and PIVKA II for diagnosis and monitoring of hepatocellular carcinoma in Chinese patients

Background

In this study, we aimed to investigate the performance of GALAD, GALAD-C, and GAAP models in Chinese population in comparison to our newly build statistical model.

Methods

In this study, we built the AALP model based on age, α-fetoprotein (AFP), AFP-L3, and prothrombin induced by vitamin K absence-II (PIVKA II) to differentiate between patients with HCC and patients with CLD. We then compared the serum levels of AFP-L3 and PIVKA II in patients with HCC who were defined as remission or progression and showed the prognostic value of combined biomarkers.

Results

The AUC value of the AALP model for HCC detection was 0.939 and AALP model exhibited a sensitivity of 81 % and a high specificity of 95 %. AALP model also exhibited good performance in the subgroups of patients with CLD. Furthermore, we demonstrated the consistency between imaging results and serum levels of AFP-L3 and PIVKA II.

Conclusions

The AALP model achieved a good diagnostic performance and a high sensitivity for predicting HCC patients. Our research also showed that AFP-L3 and PIVKA II are complementary to each other but irreplaceable in the clinical detection and monitoring of HCC.

Diagnostic and Prognostic Value of Protein Post-translational Modifications in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor with high incidence and cancer mortality worldwide. Post-translational modifications (PTMs) of proteins have a great impact on protein function. Almost all proteins can undergo PTMs, including phosphorylation, acetylation, methylation, glycosylation, ubiquitination, and so on. Many studies have shown that PTMs are related to the occurrence and development of cancers. The findings provide novel therapeutic targets for cancers, such as glypican-3 and mucin-1. Other clinical implications are also found in the studies of PTMs. Diagnostic or prognostic value, and response to therapy have been identified. In HCC, it has been shown that glycosylated alpha-fetoprotein (AFP) has a higher detection rate for early liver cancer than conventional AFP. In this review, we mainly focused on the diagnostic and prognostic value of PTM, in order to provide new insights into the clinical implication of PTM in HCC.

Usefulness of Tumor Marker Score for Predicting the Prognosis of Hepatocellular Carcinoma Patients Treated with Atezolizumab Plus Bevacizumab: A Multicenter Retrospective Study

AIM

This study aimed to evaluate the ability of a previously reported tumor marker (TM) score involving alpha-fetoprotein (AFP), fucosylated AFP (AFP-L3), and des gamma-carboxy prothrombin (DCP) as TMs in predicting the prognosis and therapeutic efficacy in hepatocellular carcinoma (HCC) patients administered atezolizumab plus bevacizumab (Atez/Bev) as first-line treatment.

MATERIALS/METHODS

The study period covered September 2020 to December 2022 and involved 371 HCC patients treated with Atez/Bev. The values of the TMs AFP, AFP-L3, and DCP were measured upon introducing Atez/Bev. Elevations in the values of AFP (≥100 ng/mL), AFP-L3 (≥10%), and DCP (≥100 mAU/mL) were considered to indicate a positive TM. The number of positive TMs was summed up and used as the TM score, as previously proposed. Hepatic reserve function was assessed using the modified albumin-bilirubin grade (mALBI). Predictive values for prognosis were evaluated retrospectively.

RESULTS

A TM score of 0 was shown in 81 HCC patients (21.8%), 1 in 110 (29.6%), 2 in 112 (29.9%), and 3 in 68 (18.3%). The median overall survival (OS) times for TM scores 0, 1, 2, and 3 were not applicable [NA] (95% CI NA-NA), 24.0 months (95% CI 17.8-NA), 16.7 months (95% CI 17.8-NA), and NA (95% CI 8.3-NA), respectively (p < 0.001). The median progression-free survival (PFS) times for TM scores 0, 1, 2, and 3 were 16.5 months (95% CI 8.0-not applicable [NA]), 13.8 months (95% CI 10.6-21.3), 7.7 months (95% CI 5.3-8.9), and 5.8 months (95% CI 3.0-7.6), respectively (p < 0.001). OS was well stratified in mALBI 1/2a and mALBI 2a/2b. PFS was well stratified in mALBI 2a/2b, but not in mALBI 1/2a.

CONCLUSIONS

The TM score involving AFP, AFP-L3, and DCP as TMs was useful in predicting the prognosis and therapeutic efficacy in terms of OS and PFS in HCC patients administered Atez/Bev as first-line treatment.

A spotlight on the interplay between Wnt/β-catenin signaling and circular RNAs in hepatocellular carcinoma progression

Hepatocellular carcinoma (HCC) is one of the deadliest cancers due to multifocal development and distant metastasis resulting from late diagnosis. Consequently, new approaches to HCC diagnosis and treatment are required to reduce mortality rates. A large body of evidence suggests that non-coding RNAs (ncRNAs) are important in cancer initiation and progression. Cancer cells release many of these ncRNAs into the blood or urine, enabling their use as a diagnostic tool. Circular RNAs (CircRNAs) are as a members of the ncRNAs that regulate cancer cell expansion, migration, metastasis, and chemoresistance through different mechanisms such as the Wnt/β-catenin Signaling pathway. The Wnt/β-catenin pathway plays prominent roles in several biological processes including organogenesis, stem cell regeneration, and cell survival. Aberrant signaling of both pathways mentioned above could affect the progression and metastasis of many cancers, including HCC. Based on several studies investigated in the current review, circRNAs have an effect on HCC formation and progression by sponging miRNAs and RNA-binding proteins (RBPs) and regulating the Wnt/β-catenin signaling pathway. Therefore, circRNAs/miRNAs or RBPs/Wnt/β-catenin signaling pathway could be considered promising prognostic and therapeutic targets in HCC.

Evaluation of GALAD Score in Diagnosis and Follow-up of Hepatocellular Carcinoma after Local Ablative Therapy

BACKGROUND AND AIMS

Strategies for detection of early hepatocellular carcinoma (HCC) are still limited. The GALAD score is a serum biomarker-based model designed to predict the probability of having HCC. We aimed to assess the ability of GALAD score to diagnose early HCC and its validity to follow patients after local ablation therapy.

METHODS

This multicenter prospective study included 108 patients in two groups, 58 HCC patients (67 focal lesions) with local ablative therapy (study group), and a control group of 50 patients with liver cirrhosis. The GALAD scores of the study and control groups, and of the HCC patients before and after ablative therapy were compared.

RESULTS

Most patients were men (74.1% in study group and 76% in controls) with hepatitis C virus infection (98.30% in the study group, and 94% in controls). GALAD scores were significantly higher in HCC patients than in those with benign cirrhosis (2.65 vs. -0.37, p=0.001). Ablative therapy was successful in 94.4% of focal lesions <2 cm, and in 86.10% of 2-5 cm lesions. The GALAD score was also significantly lower at 1 month after ablation in patients with well-ablated tumors (2.19 vs. 0.98, p=0.001). The best cutoff values of GALAD score for diagnosis of early HCC, and for prediction of well ablation of HCC were 0.74 and ≤3.31 (areas under the curve of 0.92 and 0.75, sensitivities of 84.48% and 76.19%, specificities of 89.13% and 83.33%, positive predictive values of 90.74% and 94.1%, and negative predictive values of 82% and 35.7% respectively).

CONCLUSION

The GALAD score was effective for the diagnosis of early HCC and for follow-up after ablative therapy.

Ionic liquid functionalized trapezoidal Zn-MOF nanosheets integrated with gold nanoparticles for photoelectrochemical immunosensing alpha-fetoprotein

An imidazolium based ionic liquid was successfully prepared and used as an organic ligand to coordinate with Zn²⁺ to prepare trapezoidal metal-organic frameworks (Zn-MOF) nanosheets. Then, gold nanoparticles (AuNPs) were integrated onto Zn-MOF nanosheets surface to produce AuNPs@Zn-MOF nanocomposites by in-situ reduction of chloroauric acid. AuNPs with size less than 5 nm were uniformly dispersed on the entire surface of Zn-MOF nanosheets. AuNPs can significantly promote the photocurrent response of Zn-MOF nanosheets and supply an efficient photoelectrochemical sensing platform for fabricating an immunosensor for alpha-fetoprotein (AFP). For AFP determination, the photocurrent response of the immunosensor was linearly related to the logarithm of AFP concentration in the range of 0.005-15.0 ng/mL. The detection limit was calculated to be 1.88 pg/mL. The PEC immunosensor can be facilely fabricated, and provided some superior analytical characteristics such as excellent selectivity, sensitivity, stability and reproducibility for AFP determination. Practicability of the photoelectrochemical immunosensor was demonstrated by using it in assaying AFP in clinical serum samples.

Integrated Multi-Omics Data Analysis Reveals Associations Between Glycosylation and Stemness in Hepatocellular Carcinoma

Background

Glycosylation plays an essential role in driving the progression and treatment resistance of hepatocellular carcinoma (HCC). However, its function in regulating the acquisition and maintenance of the cancer stemness-like phenotype in HCC remains largely unknown. There is also very little known about how CAD and other potential glycosylation regulators may influence stemness. This study explores the relationship between glycosylation and stemness in HCC.

Methods

Gene set variance analysis (GSVA) was used to assess the TCGA pan-cancer enrichment in glycosylation-related pathways. Univariate, LASSO, and multivariate COX regression were then used to identify prognostic genes in the TCGA-LIHC and construct a prognostic signature. HCC patients were classified into high- and low-risk subgroups based on the signature. The relationship between gene expression profiles and stemness was confirmed using bulk and single-cell RNA-sequencing data. The role of CAD and other genes in regulating the stemness of HCC was also validated by RT-qPCR, CCK-8, and colony formation assay. Copy number variation (CNV), immune infiltration, and clinical features were further analyzed in different subgroups and subsequent gene expression profiles. Sensitive drugs were also screened.

Results

In the pan-cancer analysis, HCC was shown to have specific glycosylation alterations. Five genes, CAD, SLC51B, LGALS3, B3GAT3, and MT3, identified from 572 glycosylation-related genes, were used to construct a gene signature and predict HCC patient survival in the TCGA cohort. The results demonstrated a significant positive correlation between patients in the high-risk group and both elevated gene expression and HCC dedifferentiation status. A significant reduction in the stemness-related markers, CD24, CD44, CD20, FOXM1, and EpCAM, was found after the knockdown of CAD and other genes in HepG2 and Huh7 cells. Frequent mutations increased CNVs, immune-suppressive responses, and poor prognosis were also associated with the high-risk profile. The ICGC-LIRI-JP cohort confirmed a similar relationship between glycosylation-related subtypes and stemness. Finally, 84 sensitive drugs were screened for abnormal glycosylation of HCC, and carfilzomib was most highly correlated with CAD.

Conclusions

Glycosylation-related molecular subtypes are associated with HCC stemness and disease prognosis. These results provide new directions for further research on the relationship between glycosylation and stemness phenotypes.

A new preclinical model of western diet-induced progression of non-alcoholic steatohepatitis to hepatocellular carcinoma

Non-alcoholic steatohepatitis (NASH) results from the accumulation of excessive liver lipids leading to hepatocellular injury, inflammation, and fibrosis that greatly increase the risk for hepatocellular carcinoma (HCC). Despite the well-characterized clinical and histological pathology for NASH-driven HCC in humans, its etiology remains unclear and there is a deficiency in pre-clinical models that recapitulate the progression of the human disease. Therefore, we developed a new mouse model amenable to genetic manipulations and gene targeting that mimics the gradual NASH to HCC progression observed in humans. C57BL/6NJ mice were fed a Western high-fat diet and sugar water (HFD/SW) and monitored for effects on metabolism, liver histology, tumor development, and liver transcriptome for up to 54 weeks. Chronic HFD/SW feeding led to significantly increased weight gain, serum and liver lipid levels, liver injury, and glucose intolerance. Hepatic pathology progressed and mice developed hepatocellular ballooning, inflammation, and worse fibrosis was apparent at 16 weeks, greatly increased through 32 weeks, and remained elevated at 54 weeks. Importantly, hepatocellular cancer spontaneously developed in 75% of mice on HFD/SW, half of which were HCC, whereas none of the mice on the chow diet developed HCC. Chronic HFD/SW induced molecular markers of de novo lipogenesis, endoplasmic reticulum stress, inflammation, and accumulation of p62, all of which also participate in the human pathology. Moreover, transcriptome analysis revealed activation of HCC-related genes and signatures associated with poor prognosis of human HCC. Overall, we have identified a new preclinical model that recapitulates known hallmarks of NASH-driven HCC that can be utilized for future molecular mechanistic studies of this disease.