We compared the clinical performance of the novel GAAD (gender [biological sex], age, alpha-fetoprotein [AFP], des-gamma carboxyprothrombin [DCP]) and GALAD (gender [biological sex], age, AFP, Lens culinaris agglutinin-reactive AFP [AFP-L3], DCP) algorithms to deduce the clinical utility of AFP-L3 for detecting early-stage hepatocellular carcinoma (HCC) from chronic liver disease (CLD).

An algorithm development study (STOP-HCC-ARP) and clinical validation study (STOP-HCC-MCE) were conducted, recruiting adult participants with HCC (confirmed by radiology or pathology) or CLD in an international, multicenter, case-control design. Serum biomarkers were measured using Elecsys assays (GAAD and GALAD [Cobas]) or μTASWAKO assays (GALAD [μTASWAKO]) while blinded to case/control status.

In STOP-HCC-ARP (algorithm development cohort), 1,006 patients {297 HCC (41.4% early-stage [Barcelona Clinic Liver Cancer {BCLC} 0/A) and 709 CLD} were included. Area under the curve (AUCs) for discriminating between early-stage HCC vs. CLD were 91.4%, 91.4%, and 90.8% for GAAD (Cobas), GALAD (Cobas), and GALAD (μTASWAKO), respectively. The clinical validation cohort of STOP-HCC-MCE comprised 1,142 patients, (366 HCC cases [48% early-stage], 468 specificity samples and 302 CLD); AUCs for GAAD (Cobas), GALAD (Cobas), and GALAD (μTASWAKO) for discriminating between early-stage HCC vs. CLD were 91.4%, 91.5%, and 91.0%, respectively; AUCs were 94.7-95.0% for all-stage HCC. The GAAD and GALAD algorithms demonstrated similar good performance regardless of disease etiology, presence of cirrhosis, geographical region, and within pan-tumor specificity panels (p <0.001).

GAAD (Cobas) demonstrated good clinical performance, similar to GALAD (Cobas and μTASWAKO) algorithms, in differentiating HCC and CLD controls, across all disease stages, etiologies, and regions; therefore, AFP-L3 may have a negligible role in GALAD for HCC surveillance.

To improve the detection of early-stage hepatocellular carcinoma (HCC) from benign chronic liver disease (CLD), algorithms combining demographic characteristics and serum biomarkers, such as GAAD and GALAD, have been developed. GAAD combines gender (biological sex), age, alpha-fetoprotein (AFP), des-gamma carboxy-prothrombin (DCP); GALAD combines the same characteristics and biomarkers as GAAD with the addition of Lens culinaris agglutinin-reactive AFP (AFP-L3). Changing disease etiologies and treatment paradigms have raised questions regarding the utility of AFP-L3 in HCC surveillance. Our work demonstrates that the GAAD (Cobas) algorithm demonstrated good clinical performance and was as sensitive and specific as the GALAD (Cobas) and GALAD (μTASWAKO) algorithms in differentiating HCC and CLD controls, across all disease stages, etiologies, and geographical regions; therefore, AFP-L3 may have a negligible role in HCC detection. Our study provides supporting evidence that in participants with CLD undergoing guideline-directed HCC surveillance, the GAAD (Cobas) algorithm may be used as an effective method for the detection of HCC, potentially resulting in improved patient outcomes.

Serum tests have become a partial alternative to renal biopsy for diagnosing primary membranous nephropathy (pMN). However, urine tests, due to their non-invasive nature and ability to more accurately reflect glomerular diseases, hold great promise for the detection of pMN. However, the low protein concentration and the time-consuming sample preparation procedure of urine samples challenges the proteomic and glycoproteomic analysis to find urine-derived signatures associated with pMN. In this study, we presented a microparticle-assisted protein capture (MAPC) method to efficiently prepare urine samples. It was found that proteins and N-linked intact glycopeptides can be sensitively identified from urine samples of pMN patients and healthy controls by using this method. For comparison, proteins and N-linked intact glycopeptides from serum were also analyzed. Interestingly, discrepancy was found in the changing trends for proteins/intact glycopeptides between serum and urine. Moreover, urine derived proteins, N-linked intact glycopeptides, and glycans exhibited more pronounced changes between pMN and healthy control compared to serum sample. Notably, urine IgG4 not only up-regulated in pMN at global peptide level, its corresponding site-specific glycans were specifically identified in pMN urine with significantly up-regulations, suggested the potential of using glycosylated urine IgG4 for the non-invasive diagnosis of pMN.

Liver cancer has become a major global health challenge due to its high incidence, high rate of late diagnosis and limited treatment options. Although there are many clinical treatments available for liver cancer, the cure rate is still very low, and now researchers have begun to explore new aspects of liver cancer treatment, and nanotechnology has shown great potential for improving diagnostic accuracy and therapeutic efficacy and is therefore a promising treatment option. In diagnosis, nanomaterials such as gold nanoparticles, magnetic nanoparticles, and silver nanoparticles can realize highly sensitive and specific detection of liver cancer biomarkers, supporting diagnosis and real-time monitoring of the disease process. In terms of treatment, nanocarriers can realize precise targeted delivery of drugs, improve the bioavailability of liver cancer therapeutic drugs and reduce systemic toxic side effects. In addition, advanced technologies such as nanoparticle-based photothermal therapy and photodynamic therapy provide innovative solutions to overcome drug resistance and local tumor ablation. Therefore, in this paper, we will introduce nanotechnology for hepatocellular carcinoma in terms of tumor marker detection, targeted drug delivery, and synergistic PDT/CDT therapy.

Worldwide, hepatocellular carcinoma (HCC) is the second most lethal cancer, although early-stage HCC is amenable to curative treatment and can facilitate long-term survival. Early detection has proved difficult, as proteomics, transcriptomics, and genomics have been unable to discover suitable biomarkers.

To find new biomarkers of HCC, we utilized a spatial omics N-glycan imaging method to identify altered glycosylation in cancer tissue (n = 53) and in paired serum of individuals with HCC (n = 23). Glycoproteomics identified the glycoproteins carrying these N-glycan structures, and we utilized an antibody array-based glycan imaging method to examine all the N-glycans associated with the identified glycoproteins. N-glycans from the examined glycoproteins were used to create machine learning algorithms, which were tested in a case-control sample set of 100 patients with cirrhosis and HCC and 101 matched patients with cirrhosis alone.

Spatial glycan imaging identifies thirteen branched, fucosylated, and high mannose glycans as altered in HCC tissue and in matched patient serum. Glycoproteomics identifies over 50 proteins containing these changes, of which sixteen glycoproteins were selected for further testing in an independent patient set. Algorithms using a combination of glycan and glycoproteins accurately differentiate early-stage and all HCC from cirrhosis with AUROC values of 0.88-0.97.

In conclusion, we present the development and application of a new biomarker platform, which can identify effective biomarkers for the early detection of HCC. This platform may also apply to other diseases, in which changes in N-linked glycosylation are known to occur.

Liver cancer ranks as the sixth most common cancer globally, with hepatocellular carcinoma (HCC) accounting for approximately 75%-85% of cases. Most patients present with moderately advanced disease, while those with advanced HCC face limited and ineffective treatment options. Despite diagnostic efforts, no ideal tumor marker exists to date, highlighting the urgent clinical need for improved early detection of HCC. A key research objective is the development of assays that target specific pathways involved in HCC progression. This review explores the pathological origin and development of HCC, providing insights into the mechanistic rationale, clinical statistics, and the advantages and limitations of commonly used diagnostic tumor markers. Additionally, it discusses the potential of emerging biomarkers for early diagnosis and offers a brief overview of relevant assay methodologies. This review aims to summarize existing markers and investigate new ones, providing a basis for subsequent research.

Hepatocellular carcinoma (HCC) stands out as a significant contributor to cancer-related death. Traditional Chinese Medicine (TCM) offers several advantages in the treatment of HCC. Britannin, a pivotal compound in Inulae Flos, has demonstrated pharmacological effects against various cancers, yet research on its specific anti-HCC effects remains limited.

This study aims to explore the anti-HCC effects of britannin and its underlying mechanism.

MTT assay, clone formation assay and flow cytometry were utilized to detect the cell activity, proliferation ability and apoptosis of britannin against HCC cell lines. Cell migration and invasion abilities of HCC cell lines treated with britannin were evaluated by wound-healing assay and transwell migration and invasion assay. H22 xenografted tumor mouse model was constructed and britannin treatment was performed to observe the effect of britannin on HCC tumors. The expression levels of liver cancer biomarkers AFP, AFP-L3, APT and TGF-β were detected by Elisa, and the histopathology was observed by HE staining. Network pharmacology and molecular docking were used to predict the possible signaling pathway of anti-HCC effect of britannin. The surface plasmon resonance (SPR) experiment was used to verify the interaction between britannin and proteins. The cell kinase activity function experiment was employed to detect the effect of britannin on enzyme activity. RT-qPCR and Western-Blot were used to verify the effect of britannin on the mRNA expressions of key genes and protein levels related to GSK-3β/β-catenin pathway in HCC cells and tumor tissues in mice.

In vitro experiments showed that britannin could inhibit the activity, proliferation, migration and invasion abilities of HCC cells, while promoting their apoptosis. In vivo experiments revealed that britannin exerted inhibitory effects on the growth of transplanted liver cancer tumors, reducing the inflammatory infiltration and the expression levels of AFP, AFP-L3, APT and TGF-β of liver cancer markers in transplanted mice. Network pharmacology and molecular docking predicted that cell adhesion factors and GSK-3β/β-catenin pathway might be the related signaling pathway and had potential docking activity with key proteins. The SPR experiments elucidated the molecular interaction between britannin and GSK-3β. Enzyme activity assays indicated that britannin could modulate the functional activity of GSK-3β kinase. RT-qPCR suggested britannin could regulate the mRNA expressions of β-catenin, GSK-3β, E-cadherin and NCadherin. Western-Blot further verified that britannin could significantly up-regulate the expression of GSK-3β and down-regulate the expression of p-GSK-3β and β-catenin. At the same time, the expression of E-cadherin increased and NCadherin decreased, thereby reducing the occurrence of EMT and inhibiting the metastasis of HCC.

In conclusion, britannin could inhibit the growth, development and metastasis of HCC, and its mechanism may be related to the regulation of GSK-3β/β-catenin signaling pathway to inhibit epithelial-mesenchymal transition of HCC.

Hepatocellular Carcinoma (HCC) is a serious primary solid tumor that is prevalent worldwide. Due to its high mortality rate, it is crucial to explore both early diagnosis and advanced treatment for HCC. In recent years, multi-omics approaches have emerged as promising tools to identify biomarkers and investigate molecular mechanisms of biological processes and diseases. In this study, we performed proteomics, phosphoproteomics, metabolomics, and lipidomics to reveal the molecular features of early- and advanced-stage HCC. The data obtained from these omics were analyzed separately and then integrated to provide a comprehensive understanding of the disease. The multi-omics results unveiled intricate biological pathways and interaction networks underlying the initiation and progression of HCC. Moreover, we proposed specific potential biomarker panels for both early- and advanced-stage HCC by overlapping our data with CPTAC database for HCC diagnosis, and deduced novel insights and mechanisms related to HCC origination and development, such as glucose depletion during tumor progression, ROCK1 deactivation and GSK3A activation.

Hepatocellular carcinoma (HCC) is a prevalent and aggressive cancer that presents significant challenges for early detection. This study introduces the GlyExo-Capture method for isolating fucosylated extracellular vesicles (Fu-EVs) from serum. We analyze microRNA (miRNA) profiles from Fu-EVs in 88 HCC patients and 179 non-HCC controls using next-generation sequencing (NGS) and identify five miRNAs (hsa-let-7a, hsa-miR-21, hsa-miR-125a, hsa-miR-200a, and hsa-miR-150) as biomarkers for HCC diagnosis. The five-miRNA panel demonstrates exceptional HCC diagnostic performance, with a sensitivity of 0.90 and specificity of 0.92 in a combined cohort of 194 HCC and 412 non-HCC controls, significantly surpassing the performance of alpha-fetoprotein (AFP) and des-gamma-carboxy prothrombin (DCP). Notably, the miRNA model achieves recall rates of 85.7% and 90.8% for stage 0 and stage A early-stage HCC, respectively, identifies 88.1% of AFP-negative HCC cases, and effectively differentiates HCC from other cancers. This study provides a high-throughput, rapid, and non-invasive approach for early HCC detection.

N-linked glycosylation is a common posttranslational modification of proteins that results in macroheterogeneity of the modification site. However, unlike simpler modifications, N-glycosylation introduces an additional layer of complexity with tens of thousands of possible structures arising from various dimensions, including different monosaccharide compositions, sequence structures, linking structures, isomerism, and three-dimensional conformations. This results in additional microheterogeneity of the modification site of N-glycosylation, i.e., the same N-glycosylation site can be modified with different glycans with a certain stoichiometric ratio. N-glycosylation regulates the structure and function of N-glycoproteins in a site- and structure-specific manner, and differential expression of N-glycosylation under disease conditions needs to be characterized through site- and structure-specific quantitative analysis. Numerous advanced methods ranging from sample preparation to mass spectrum analysis have been developed to distinguish N-glycan structures. Chemical derivatization of monosaccharides, online liquid chromatography separation and ion mobility spectrometry enable the physical differentiation of samples. Tandem mass spectrometry further analyzes the macro/microheterogeneity of intact N-glycopeptides through the analysis of fragment ions. Moreover, the development of search engines and AI-based software has enhanced our understanding of the dissociation patterns of intact N-glycopeptides and the clinical significance of differentially expressed intact N-glycopeptides. With the help of these modern methods, structure-specific N-glycoproteomics has become an important tool with extensive applications in the biomedical field.

Lectins are proteins or glycoproteins of non-immune origin with carbohydrate-binding properties. They are found both prokaryotic and eukaryotic organisms. The most abundant source of the lectins are plants. Many lectins have anticancer effects by directly exerting cytotoxic effects on malignant cells or indirectly activating the immune system. Lectins also have antiviral activities. These proteins can recognise glycoproteins on the surface of enveloped viruses and bind to them. This creates a physical barrier between them and the corresponding receptors on the surface of the host cell, which prevents the virus from entering the cell and can thus effectively inhibit the replication of the virus. In this review, we focus on the anticancer activities of selected lectins and the underlying mechanisms. We also discuss different types of lectins with antiviral activity. We have paid special attention to lectins with inhibitory activity against SARS-CoV-2. Finally, we outline the challenges of using lectins in therapy and suggest future research directions.

Hepatocellular carcinoma (HCC) is the most frequent liver cancer, which account for more than 90 % of all liver cancer cases. It is the fifth leading cause of cancer globally and the second leading cause of cancer-related mortality in men. The availability of competent HCC preclinical models is fundamental to the success of mechanistic studies, molecular target identification, and drug testing. However, there are challenges associated with the use of these models. In this review, we provided updates on various cell lines, animals, and human HCC models, their specific preclinic use and associated potential challenges. Overall, the understanding of the merits and demerits of a particular HCC model will improve model selection for various preclinical studies.

Aim: This study investigates the altered expression and CpG methylation patterns of histone demethylase KDM8 in hepatocellular carcinoma (HCC), aiming to uncover insights and promising diagnostics biomarkers.Materials & methods: Leveraging TCGA-LIHC multi-omics data, we employed R/Bioconductor libraries and Cytoscape to analyze and construct a gene correlation network, and LASSO regression to develop an HCC-predictive model.Results: In HCC, KDM8 downregulation is correlated with CpGs hypermethylation. Differential gene correlation analysis unveiled a liver carcinoma-associated network marked by increased cell division and compromised liver-specific functions. The LASSO regression identified a highly accurate HCC prediction signature, prominently featuring CpG methylation at cg02871891.Conclusion: Our study uncovers CpG hypermethylation at cg02871891, possibly influencing KDM8 downregulation in HCC, suggesting these as promising biomarkers and targets.

Dysregulation of protein core-fucosylation plays a pivotal role in the onset, progression, and immunosuppression of cancer. However, analyzing core-fucosylation, especially the accurate determination of the core-fucosylation (CF) site occupancy ratio, remains challenging. To address these problems, we developed a truncation strategy that efficiently converts intact glycopeptides with hundreds of different glycans into two truncated forms, i.e., a monosaccharide HexNAc and a disaccharide HexNAc+core-fucose. Further combination with data-independent analysis to form an integrated platform allowed the measurement of site-specific core-fucosylation abundances and the determination of the CF occupancy ratio with high reproducibility. Notably, three times CF sites were identified using this strategy compared to conventional methods based on intact glycopeptides. Application of this platform to characterize protein core-fucosylation in two breast cancer cell lines, i.e., MDA-MB-231 and MCF7, yields a total of 1615 unique glycosites and about 900 CF sites from one single LC-MS/MS analysis. Differential analysis unraveled the distinct glycosylation pattern for over 201 cell surface drug targets between breast cancer subtypes and provides insights into developing new therapeutic strategies to aid precision medicine. Given the robust performance of this platform, it would have broad application in discovering novel biomarkers based on the CF glycosylation pattern, investigating cancer mechanisms, as well as detecting new intervention targets.

Serum AFP-L3%, AFP, and DCP are useful biomarkers for HCC detection, but their utility in assessing treatment response remains unknown. We aim to evaluate the accuracy of a biomarker model in the detection of posttreatment viable tumors.

For model derivation, recipients with HCC undergoing liver transplant from 2018 to 2022 who had biomarkers collected within 3 months before transplant were included. We developed a generalized linear model for detecting posttreatment viable tumors with the 3 biomarkers as covariates, which we termed the "LAD Score." An independent cohort of 117 patients with HCC was used for external validation.

Among 205 recipients of transplant, 70.2% had evidence of viable tumor on explant. The median LAD score was higher among patients with viable versus nonviable tumors (1.06 vs. 0.465, p < 0.001). The LAD score had a sensitivity of 55.6% and a specificity of 85.1% at the cutoff of 0.927, which was more accurate than imaging for detecting posttreatment viable tumors (AUROC 0.736 vs. 0.643, respectively; p = 0.045). The superior performance of the LAD score over imaging is primarily driven by its greater accuracy in detecting tumors <2 cm in diameter (AUROC of the LAD score 0.721 vs. imaging 0.595, p = 0.02). In the validation data set, the LAD score had an AUROC of 0.832 (95% CI: 0.753, 0.911) with a sensitivity of 72.5% and a specificity of 89.4% at the cutoff of 0.927.

Our findings suggest the utility of LAD score in treatment response assessment after locoregional therapy for HCC, particularly in detecting small tumors. A larger prospective study is in progress to validate its accuracy and evaluate its performance in recurrence monitoring.

Lung cancer (LC) is the malignant tumor with the highest mortality rate worldwide, and precise early diagnosis can improve patient prognosis. The purpose of this study was to investigate whether alterations in the glycopatterns recognized by the Hippeastrum hybrid lectin (HHL) in salivary proteins are associated with the development of LC.

First, we collected saliva samples from LC (15 lung adenocarcinoma (ADC); 15 squamous cell carcinoma (SCC); 15 small cell lung cancer (SCLC)) and 15 benign pulmonary disease (BPD) for high-throughput detection of abundance levels of HHL-recognized glycopatterns using protein microarrays, and then validated the pooled samples from each group with lectin blotting analysis. Finally, the N-glycan profiles of salivary glycoproteins isolated from the pooled samples using HHL-magnetic particle conjugates were characterized separately using MALDI-TOF/TOF-MS.

The results showed that the abundance level of glycopatterns recognized by HHL in salivary proteins was elevated in LC compared to BPD. The proportion of mannosylated N-glycans was notably higher in ADC (31.7%), SCC (39.0%), and SCLC (46.6%) compared to BPD (23.3%).

The altered salivary glycopatterns such as oligomannose, Manα1-3Man, or Manα1-6Man N-glycans recognized by HHL might serve as potential biomarkers for the diagnosis of LC patients.

This study provides crucial information for studying changes in salivary to differentiate between BPD and LC and facilitate the discovery of biomarkers for LC diagnosis based on precise alterations of mannosylated N-glycans in saliva.

The incidence of metabolic dysfunction-associated steatotic liver disease (MASLD) is continuously rising, evolving into a global health challenge. Concurrently, cases of hepatocellular carcinoma (HCC) associated with MASLD are also on the increase. Although traditional risk factors such as age, gender, and metabolic factors play significant roles in the development of HCC, it cannot be overlooked that MASLD, triggered by changes in modern lifestyle and dietary habits, may also exacerbate the risk of HCC, and this phenomenon is common even among non-obese individuals. Regrettably, MASLD often fails to receive timely diagnosis, resulting in a limited number of patients receiving HCC surveillance. Moreover, there is currently a lack of clear definition for the target population for surveillance beyond patients with cirrhosis. Consequently, MASLD-related HCC is often detected at a late stage, precluding the optimal timing for curative treatment. However, our understanding of the pathogenesis and progression of HCC remains limited. Therefore, this paper reviews relevant literature from recent years, delving into multiple dimensions such as pathogenesis, surveillance and diagnosis, prevention, and treatment, aiming to provide new ideas and directions for the prevention and treatment of MASLD-related HCC.

We aimed to examine the potential protective effects of Iraqi H. tiliaceus L. chloroform leaves extract on DEN-induced HCC in male Wistar Albino rats.

Rats were assigned to four groups, six in each group. Group I: rats were administered a daily oral dose of 1 mL/kg/day of distilled water. Group II: rats were intraperitoneally injected with 70 mg/kg DEN once per week for 10 consecutive weeks. Group III: rats received 250 mg/kg of chloroform leaves extract. Groups IV: the rats were administered 500 mg/kg of chloroform leaves extract, along with their food, for five days per week over 20 weeks, with a subsequent dose of DEN once per week for 10 consecutive weeks.

The results indicate that the extract demonstrated a significant reduction (p<0.05) in oxidative stress, pro-inflammatory mediators, and HCC parameters, the extract also had a beneficial effect on liver function tests, and there was a significant elevation (p<0.05) of antioxidant parameters in a dose-dependent manner.

This study supports the protective properties of the chloroform extract of Iraqi H. tiliaceus L. leaves in HCC.

Alpha-fetoprotein (AFP), a serum glycoprotein, is expressed during embryonic development and the pathogenesis of liver cancer. It serves as a clinical tumor marker, function as a carcinogen, immune suppressor, and transport vehicle; but the detailed AFP structural information has not yet been reported. In this study, we used single-particle cryo-electron microscopy(cryo-EM) to analyze the structure of the recombinant AFP obtained a 3.31 Å cryo-EM structure and built an atomic model of AFP. We observed and identified certain structural features of AFP, including N-glycosylation at Asn251, four natural fatty acids bound to distinct domains, and the coordination of metal ions by residues His22, His264, His268, and Asp280. Furthermore, we compared the structural similarities and differences between AFP and human serum albumin. The elucidation of AFP's structural characteristics not only contributes to a deeper understanding of its functional mechanisms, but also provides a structural basis for developing AFP-based drug vehicles.

Fucosylation is an important structural feature of glycans and plays an essential role in the regulation of glycoprotein functions. Fucosylation can be classified into core- (CF) and antenna-fucosylation (AF, also known as (sialyl-) Lewis) based on the location on N-glycans, and they perform distinct biological functions. In this study, core- and antenna-fucosylated N-glycans on human serum glycoproteins that hold great clinical application values were systematically characterized at the site-specific level using StrucGP combined with the recently developed fucosylation assignment method. The results showed that fucosylation was widely distributed on serum glycoproteins, with 50% of fucosylated glycopeptides modified by AF N-glycans, 37% by CF N-glycans, and 13% by dual-fucosylated N-glycans. Interestingly, CF and AF N-glycans preferred to modify different groups of serum glycoproteins with different tissue origins and were involved in distinctive biological processes. Specifically, AF N-glycoproteins are mainly from the liver and participated in complement activation, blood coagulation, and endopeptidase activities, while CF N-glycoproteins originate from diverse tissues and are mainly involved in cell adhesion and signaling transduction. These data further enhanced our understanding of fucosylation on circulation glycoproteins.

Cancer early detection and treatment response prediction continue to pose significant challenges. Cancer liquid biopsies focusing on detecting circulating tumor cells (CTCs) and DNA (ctDNA) have shown enormous potential due to their non-invasive nature and the implications in precision cancer management. Recently, liquid biopsy has been further expanded to profile glycoproteins, which are the products of post-translational modifications of proteins and play key roles in both normal and pathological processes, including cancers. The advancements in chemical and mass spectrometry-based technologies and artificial intelligence-based platforms have enabled extensive studies of cancer and organ-specific changes in glycans and glycoproteins through glycomics and glycoproteomics. Glycoproteomic analysis has emerged as a promising tool for biomarker discovery and development in early detection of cancers and prediction of treatment efficacy including response to immunotherapies. These biomarkers could play a crucial role in aiding in early intervention and personalized therapy decisions. In this review, we summarize the significant advance in cancer glycoproteomic biomarker studies and the promise and challenges in integration into clinical practice to improve cancer patient care.

Aberrant glycans are a hallmark of cancer states. Notably, emerging evidence has demonstrated that the diagnosis of cancers with tumour-specific glycan patterns holds great potential to address unmet medical needs, especially in improving diagnostic sensitivity and selectivity. However, despite vast glycans having been identified as potent markers, glycan-based diagnostic methods remain largely limited in clinical practice. There are several reasons that prevent them from reaching the market, and the lack of anti-glycan antibodies is one of the most challenging hurdles. With the increasing need for accelerating the translational process, numerous efforts have been made to find antibody alternatives, such as lectins, boronic acids and aptamers. However, issues concerning affinity, selectivity, stability and versatility are yet to be fully addressed. Molecularly imprinted polymers (MIPs), synthetic antibody mimics with tailored cavities for target molecules, hold the potential to revolutionize this dismal progress. MIPs can bind a wide range of glycan markers, even those without specific antibodies. This capacity effectively broadens the clinical applicability of glycan-based diagnostics. Additionally, glycoform-resolved diagnosis can also be achieved through customization of MIPs, allowing for more precise diagnostic applications. In this review, we intent to introduce the current status of glycans as potential biomarkers and critically evaluate the challenges that hinder the development of in vitro diagnostic assays, with a particular focus on glycan-specific recognition entities. Moreover, we highlight the key role of MIPs in this area and provide examples of their successful use. Finally, we conclude the review with the remaining challenges, future outlook, and emerging opportunities.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a progressive disease and comprises different stages of liver damage; it is significantly associated with obese and overweight patients. Untreated MASLD can progress to life-threatening end-stage conditions, such as cirrhosis and liver cancer. N-Linked glycosylation is one of the most common post-translational modifications in the cell surface and secreted proteins. N-Linked glycan alterations have been established to be signatures of liver diseases. However, the N-linked glycan changes during the progression of MASLD to liver cancer are still unknown. Here, we induced different stages of MASLD in mice and liver-cancer-related phenotypes and elucidated the N-glycome profile during the progression of MASLD by quantitative and qualitative profiling in situ using matrix-assisted laser desorption ionization (MALDI) imaging mass spectrometry (IMS). Importantly, we identified specific N-glycan structures including fucosylated and highly branched N-linked glycans at very early stages of liver injury (steatosis), which in humans are associated with cancer development, establishing the importance of these modifications with disease progression. Finally, we report that N-linked glycan alterations can be observed in our models by MALDI-IMS before liver injury is identified by histological analysis. Overall, we propose these findings as promising biomarkers for the early diagnosis of liver injury in MASLD.

Glycan structure is often modulated in disease or predisease states, suggesting that such changes might serve as biomarkers. Here, we generated a monoclonal antibody (mAb) against the core fucose of the N-glycan in human IgG. Notably, this mAb can be used in Western blotting and ELISA. ELISA using this mAb revealed a low level of the core fucose of the N-glycan in IgG, suggesting that the level of acore fucosylated (noncore fucosylated) IgG was increased in the sera of the patients with lung cancer, chronic obstructive pulmonary disease, and interstitial pneumonia compared to healthy subjects. In a coculture analysis using human lung adenocarcinoma A549 cells and antibody-secreting B cells, the downregulation of the FUT8 (α1,6 fucosyltransferase) gene and a low level of core fucose of the N-glycan in IgG in antibody-secreting B cells were observed after coculture. A dramatic alteration in gene expression profiles for cytokines, chemokines, and their receptors were also observed after coculturing, and we found that the identified C-C motif chemokine 2 was partially involved in the downregulation of the FUT8 gene and the low level of core fucose of the N-glycan in IgG in antibody-secreting B cells. We also developed a latex turbidimetric immunoassay using this mAb. These results suggest that communication with C-C motif chemokine 2 between lung cells and antibody-secreting B cells downregulate the level of core fucose of the N-glycan in IgG, i.e., the increased level of acore fucosylated (noncore fucosylated) IgG, which would be a novel biomarker for the diagnosis of patients with pulmonary diseases.

Primary hepatocellular carcinoma (HCC) is one of the most prevalent world-wide malignancies. Half of the newly developed HCC occurs in China. Optimizing the strategies for high-risk surveillance and early diagnosis are pivotal for improving 5-year survival. Constructing the scientific non-invasive detection technologies feasible for medical and healthcare institutions is among the key routes for elevating the efficacies of HCC identification and follow-up.

Based on the Chinese and international guidelines, expert consensus statements, literatures and evidence-based clinical practice experiences, this consensus statement puts forward the clinical implications, application subjects, detection techniques and results interpretations of the triple-biomarker (AFP, AFP-L3%, DCP) based GALAD, GALAD like models for liver cancer.

The compile of this consensus statement aims to address and push the reasonable application of the triple-biomarker (AFP, AFP-L3%, DCP) detections thus to maximize the clinical benefits and help improving the high risk surveillance, early diagnosis and prognosis of HCC.

Serum alpha-fetoprotein (AFP) has been used as a marker for the diagnosis of hepatocellular carcinoma (HCC) and its core fucosylation is associated with the early stage of HCC. However, current methods for the detection of AFP with core fucose are not highly accurate for early diagnosis. In this study, we established an enzyme-assisted mass spectrometric method for the quantitative analysis of AFP/core fucose with high specificity and sensitivity. We employed endoglycosidase treatment of AFP to improve the biomarker analysis. The accuracy and precision are within the US FDA-suggested value, and a good linearity (r2 = 0.9930) and a detection limit of 15.6 ng mL-1 can be achieved.

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.

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.

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.

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.

There is a need for new serum biomarkers for early detection of hepatocellular carcinoma (HCC). Haptoglobin (Hp) N-glycosylation is altered in HCC, but the diagnostic value of site-specific Hp glycobiomarkers is rarely reported. We aimed to determine the site-specific glycosylation profile of Hp for early-stage HCC diagnosis.

Hp glycosylation was analyzed in the plasma of patients with liver diseases (n=57; controls), early-stage HCC (n=50) and late-stage HCC (n=32). Hp phenotype was determined by immunoblotting. Hp was immunoisolated and digested into peptides. N-glycopeptides were identified and quantified using liquid chromatography-mass spectrometry. Cohort samples were compared using Wilcoxon rank-sum (Mann-Whitney U) tests. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves and area under curve (AUC).

Significantly higher fucosylation, branching and sialylation of Hp glycans, and expression of high-mannose glycans, was observed as disease progressed from cirrhosis to early- and late-stage HCC. Several glycopeptides demonstrated high values for early diagnosis of HCC, with an AUC of 93% (n=1), >80% (n=3), >75% (n=13) and >70% (n=11), compared with alpha-fetoprotein (AFP; AUC of 79%). The diagnostic performance of the identified biomarkers was only slightly affected by Hp phenotype.

We identified a panel of Hp glycopeptides that are significantly differentially regulated in early- and late-stage HCC. Some glycobiomarkers exceeded the diagnostic value of AFP (the most commonly used biomarker for HCC diagnosis). Our findings provide evidence that glycobiomarkers can be effective in the diagnosis of early HCC - individually, as a panel of glycopeptides or combined with conventional serological biomarkers.

Alpha-fetoprotein (AFP) is a commonly used clinical biomarker. Before 1970, the two-way agar diffusion method was mainly used, and the specificity of AFP in the diagnosis of primary liver cancer was satisfactory. However, its positivity rate was not very high. The diagnostic value of AFP is changing with the evolution of detection methods. Here, we performed a literature search to identify English-language publications. The search was performed from January 2015 to April 2023 using the PubMed database and the following terms in [Titles/Abstracts]: alpha-fetoprotein, clinical practice, detection, etc. The references of retrieved articles were also screened to broaden the search. Studies referring to liver cancer and AFP detection methods were excluded. In this review, several clinical application scenarios for AFP were systematically reviewed, and its potential detection value in the future was discussed.

Metabolic dysfunction-associated steatohepatitis (MASH) is one of the major risk factors for chronic liver disease and hepatocellular carcinoma (HCC). The incidence of MASH in Western countries continues to rise, driving HCC as the third cause of cancer-related death worldwide. HCC has become a major global health challenge, partly from the obesity epidemic promoting metabolic cellular disturbances but also from the paucity of biomarkers for its early detection. Over 50% of HCC cases are clinically present at a late stage, where curative measures are no longer beneficial. Currently, there is a paucity of both specific and sensitive biological markers for the early-stage detection of HCC. The search for biological markers in the diagnosis of early HCC in high-risk populations is intense. We described the potential role of surrogates for a liver biopsy in the screening and monitoring of patients at risk for nesting HCC.

Cancer serum biomarkers are valuable or even indispensable for cancer diagnostics and/or monitoring and, currently, many cancer serum markers are routinely used in the clinic. Most of those markers are glycoproteins, carrying cancer-specific glycan structures that can provide extra-information for cancer monitoring. Nonetheless, in the majority of cases, this differential feature is not exploited and the corresponding analytical assays detect only the protein amount, disregarding the analysis of the aberrant glycoform. Two exceptions to this trend are the biomarkers α-fetoprotein (AFP) and cancer antigen 19-9 (CA19-9), which are clinically monitored for their cancer-related glycan changes, and only the AFP assay includes quantification of both the protein amount and the altered glycoform. This narrative review demonstrates, through several examples, the advantages of the combined quantification of protein cancer biomarkers and the respective glycoform analysis, which enable to yield the maximum information and overcome the weaknesses of each individual analysis. This strategy allows to achieve higher sensitivity and specificity in the detection of cancer, enhancing the diagnostic power of biomarker-based cancer detection tests.

Hepatocellular carcinoma (HCC) is the most common type of primary hepatocellular carcinoma (PHC). Early diagnosis of HCC remains the key to improve the prognosis. In recent years, with the promotion of the concept of precision medicine and more in-depth analysis of the biological mechanism underlying HCC, new diagnostic methods, including emerging serum markers, liquid biopsies, molecular diagnosis, and advances in imaging (novel contrast agents and radiomics), have emerged one after another. Herein, we reviewed and analyzed scientific advances in the early diagnosis of HCC and discussed their application and shortcomings. This review aimed to provide a reference for scientific research and clinical practice of HCC.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide. Understanding the cancer mechanisms provides novel diagnostic, prognostic, and therapeutic markers for the management of HCC disease. In addition to genomic and epigenomic regulation, post-translational modification exerts a profound influence on protein functions and plays a critical role in regulating various biological processes. Protein glycosylation is one of the most common and complex post-translational modifications of newly synthesized proteins and acts as an important regulatory mechanism that is implicated in fundamental molecular and cell biology processes. Recent studies in glycobiology suggest that aberrant protein glycosylation in hepatocytes contributes to the malignant transformation to HCC by modulating a wide range of pro-tumorigenic signaling pathways. The dysregulated protein glycosylation regulates cancer growth, metastasis, stemness, immune evasion, and therapy resistance, and is regarded as a hallmark of HCC. Changes in protein glycosylation could serve as potential diagnostic, prognostic, and therapeutic factors in HCC. In this review, we summarize the functional importance, molecular mechanism, and clinical application of protein glycosylation alterations in HCC.

Both N-linked glycosylation and O-linked glycosylation play essential roles in the onset and progression of various diseases including cancer, and N-/O-linked site-specific glycans have been proven to be promising biomarkers for the discrimination of cancer. However, the micro-heterogeneity and low abundance nature of N-/O-linked glycosylation, as well as the time-consuming and tedious procedures for the enrichment of O-linked intact glycopeptides, pose great challenges for their efficient and accurate characterization. In this study, we developed an integrated platform for the simultaneous enrichment and characterization of N- and O-linked intact glycopeptides from the same serum sample. By fine-tuning the experimental conditions, we demonstrated that this platform allowed the selective separation of N- and O-linked intact glycopeptides into two fractions, with 85.1% O-linked intact glycopeptides presented in the first fraction and 93.4% N-linked intact glycopeptides presented in the second fraction. Determined with high reproducibility, this platform was further applied to the differential analysis of serum samples of gastric cancer and health control, which revealed 17 and 181 significantly changed O-linked and N-linked intact glycopeptides. Interestingly, five glycoproteins containing both significant regulation of N- and O-glycosylation were observed, hinting potential co-regulation of different types of glycosylation during tumor progress. In summary, this integrated platform opened a potentially useful avenue for the global analysis of protein glycosylation and can serve as a useful tool for the characterization of N-/O-linked intact glycopeptides at the proteomics scale.

Hepatocellular carcinoma (HCC) is an aggressive primary malignancy of the liver and is the third most common cause of cancer-related global mortality. There has been a steady increase in treatment options for HCC in recent years, including innovations in both curative and non-curative therapies. These advances have brought new challenges and necessary improvements in strategies of disease monitoring, to allow early detection of HCC recurrence. Current serological and radiological strategies for post-treatment monitoring and prognostication and their limitations will be discussed and evaluated in this review.

Human body fluids have become an indispensable resource for clinical research, diagnosis and prognosis. Urine is widely used to discover disease-specific glycoprotein biomarkers because of its recurrently non-invasive collection and disease-indicating properties. While urine is an unstable fluid in that its composition changes with ingested nutrients and further as it is excreted through micturition, urinary proteins are more stable and their abnormal glycosylation is associated with diseases. It is known that aberrant glycosylation can define tumor malignancy and indicate disease initiation and progression. However, a thorough and translational survey of urinary glycosylation in diseases has not been performed. In this article, we evaluate the clinical applications of urine, introduce methods for urine glycosylation analysis, and discuss urine glycoprotein biomarkers. We emphasize the importance of mining urinary glycoproteins and searching for disease-specific glycosylation in various diseases (including cancer, neurodegenerative diseases, diabetes, and viral infections). With advances in mass spectrometry-based glycomics/glycoproteomics/glycopeptidomics, characterization of disease-specific glycosylation will optimistically lead to the discovery of disease-related urinary biomarkers with better sensitivity and specificity in the near future.

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

Serum alpha fetoprotein (AFP) is a "gold-standard" biomarker for the diagnosis of hepatocellular carcinoma (HCC). Available pieces of evidence suggest that the ratio of AFP-L3 isoform in the total AFP may provide more accurate prediction for the incidence of HCC. In this work, we design an electrochemical aptasensor for high-accuracy assay of AFP-L3 ratio based on differentiated labeling of AFP isoforms in an orderly fashion. Specifically, total AFP is first captured by an AFP aptamer-functionalized electrode and labeled with quantum dots-functionalized DNA probes via mild reduction. Then, AFP-L3 isoform that strongly binds to Lens culinaris agglutinin is labeled with silver nanoparticles after the exonuclease-catalyzed removal of DNA probes. By tracing the electrochemical responses of quantum dots and silver nanoparticles, respectively, the amounts of total AFP and AFP-L3 isoforms are determined and the AFP-L3 ratio is accordingly calculated to favor the accurate HCC diagnosis. Experimental results prove the high-accuracy assay of AFP-L3 ratio based on the AFP quantitation in a linear range of 0.0008-40 ng mL^-1 and AFP-L3 quantitation in a linear range of 0.004-40 ng mL^-1. The aptasensor also displays satisfactory specificity and good recoveries even in the complex serum samples. Therefore, the aptasensor may provide a valuable tool for the assay of the AFP-L3 ratio and have a great potential use in early warning of HCC for clinical application.

The development of robust cancer biomarkers is the most effective way to improve overall survival, as early detection and treatment leads to significantly better clinical outcomes. Many of the cancer biomarkers that have been identified and are clinically utilized are glycoproteins, oftentimes a specific glycoform. Aberrant glycosylation is a common theme in cancer, with dysregulated glycosylation driving tumor initiation and metastasis, and abnormal glycosylation can be detection both on the tissue surface and in serum. However, most cancer types are heterogeneous in regard to tumor genomics, and this heterogeneity extends to cancer glycomics. This limits the sensitivity of standalone glycan-based biomarkers, which has slowed their implementation clinically. However, if targeted biomarker development can take into account genomic tumor information, the development of complementary biomarkers that target unique cancer subgroups can be accomplished. This idea suggests the need for algorithm-based cancer biomarkers, which can utilize multiple biomarkers along with relevant demographic information. This concept has already been established in the detection of hepatocellular carcinoma with the GALAD score, and an algorithm-based approach would likely be effective in improving biomarker sensitivity for additional cancer types. In order to increase cancer diagnostic biomarker sensitivity, there must be more targeted biomarker development that considers tumor genomic, proteomic, metabolomic, and clinical data while identifying tumor biomarkers.