Identification of osteopontin as a novel marker for early hepatocellular carcinoma

Isoform specific regulation of osteopontin by AKT2 in hepatocytes and livers

Elevated levels of osteopontin (OPN), an inflammatory cytokine, are correlated with chronic inflammatory conditions and liver cancer. In this study, we explored the regulation of OPN in liver and hepatocytes by AKT1 vs. AKT2, the two AKT isoforms expressed in hepatocytes and livers. Using a mouse model lacking PTEN (phosphatase and tensin homologue deleted on chromosome 10), the negative regulator of phosphatidylinositol 3-kinase (PI3K)/AKT signaling, expression of secreted phosphoprotein 1 (Spp1), the gene encoding OPN, was found to be the topmost significantly upregulated gene in the liver. Using an add-back experiment in hepatocytes isolated from these mice, we show that PTEN regulates the expression of Spp1 mRNA as well as OPN protein levels. Exploring how PTEN regulates the expression of Spp1/OPN, we investigated the differential roles of AKT1 vs. AKT2 using hepatocytes isolated from mice lacking each AKT isoform in the liver. We showed here that levels of Spp1/OPN in hepatocytes are lost with deletion of Akt2 but not Akt1. Deletion of Akt2 significantly attenuated both basal expression of OPN and its response to IGF-1 stimulation. AKT1 loss, on the other hand, permitted more robust induction of OPN by IGF-1 stimulation. Furthermore, mice lacking AKT2 and PTEN exhibit significantly lower OPN expression in the liver. Together, this study showed that OPN levels are regulated by the PI3K/AKT signal in hepatocytes and that AKT2 but not AKT1 is responsible for its induction in response to stimulation of the PI3K signaling pathway.

A novel 5-differentially expressed gene (DEG) signature predicting the prognosis in patients with metastatic liver malignancies and the prognostic and therapeutic potential of SPP1

BACKGROUND

This study aimed to identify differentially expressed genes (DEGs) that are associated with hepatocarcinogenesis and metastasis in hepatocellular carcinoma (HCC) and to explore their value in predicting overall survival (OS). The methods used included bioinformatics analysis of gene expression datasets and in vitro experiments using HCC cell lines.

METHODS

Gene expression profiles from metastatic and non-metastatic liver cancer specimens were analyzed using the limma R package. Functional enrichment was performed using Metascape. A prognostic 5-gene signature was constructed using the LASSO algorithm based on TCGA-LIHC data. Kaplan-Meier survival analysis assessed the association of these genes with clinical outcomes (DFI, DSS, OS, and PFS). In vitro, Huh7 and Hep3B cells were transfected with shRNA for SPP1 knockdown. Cell viability was measured with CCK-8 assays, and migration was assessed with Transwell and wound-healing assays. Protein expression was evaluated via western blotting.

RESULTS

The analysis of gene expression profiles led to the identification of 11 DEGs associated with immune response, phagocytosis, and cell migration. From these DEGs, the LASSO algorithm identified a 5-DEG signature (MASP1, MASP2, MUC1, TREM1, and SPP1) that was predictive of OS in liver cancer patients. Among the five genes, SPP1 was the most upregulated in cancer samples and was significantly associated with poorer outcomes, including DFI, DSS, OS, and PFS. In vitro experiments confirmed that SPP1 knockdown in Huh7 and Hep3B cells significantly inhibited cancer cell viability and migration. Western blot analysis showed alterations in key proteins, with a reduction in vimentin and Ki-67 and an increase in E-cadherin following SPP1 knockdown.

CONCLUSION

This study highlights the pivotal effect of SPP1 on HCC development and underscores its potential as a biomarker for the OS of liver cancer patients. The identified DEGs may serve as predictive markers for OS and potential therapeutic targets for HCC treatment.

Application of immunofluorescence-based detection of AFP-L3 in the diagnosis of hepatocellular carcinoma

Alpha-fetoprotein (AFP) together with Lens culinaris-agglutinin-reactive fraction of AFP (AFP-L3) serve as the preferred tumor markers for hepatocellular carcinoma (HCC) diagnosis. The authors performed diagnostic value analysis on AFP along with AFP-L3 as individual biomarkers and together to determine the optimal biomarker option. Researchers evaluated 149 HCC patient sera and 70 healthy control sera using automatic microchip capillary electrophoresis and liquid phase combination-based analysis. They found the area under the curve value for the conventional marker AFP reached 0.844 and the diagnostic value of AFP-L3 was 0.923. The diagnostic effectiveness did not enhance as both biomarkers were combined for testing. The performance metrics of AFP-L3 increase during disease progression which leads to complete diagnostic sensitivity and perfect specificity and an area under the curve value of 1 during Barcelona clinical liver cancer and D stage.

Serum Osteopontin Enhances Hepatocellular Carcinoma Diagnosis and Predicts Anti-PD-L1 Immunotherapy Benefit

Background

Osteopontin (OPN), a phosphorylated glycoprotein encoded by SPP1, critical in hepatic inflammation and fibrosis, requires further investigation for its role on hepatocellular carcinoma (HCC) and predictive value for anti-programmed cell death ligand 1 (anti-PD-L1) immunotherapy responses.

Methods

Publicly available datasets were utilized to explore OPN expression in HCC. A retrospective cohort study involving 316 participants, recruited from January 2015 to March 2017. Serum OPN levels were measured by enzyme-linked immunosorbent assay. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves, a logistic regression model was developed for early HCC diagnosis. Prospective follow-up was conducted from 2017 to 2024 to evaluate overall survival (OS) and disease-free survival (DFS) using Kaplan-Meier analyses. The survival benefit of anti-PD-L1 immunotherapy for patients with OPN patterns was investigated.

Results

Serum OPN levels were significantly elevated in HCC compared to chronic liver disease and healthy individuals (both p <0.001). The area under the curve (AUC) for OPN was 0.903, with 88.2% sensitivity and 83.3% specificity, significantly superior to AFP alone (AUC: 0.707). A combined diagnostic model integrating OPN with alpha-fetoprotein (AFP) and aspartate aminotransferase (AST) enhanced accuracy further (AUC: 0.941). High OPN levels indicated higher tumor burden and predicted worse clinical outcomes (mean OS: 49.1 vs 75.1 months; mean DFS: 37.7 vs 60.9 months, respectively; both log-rank p <0.001). Anti-PD-L1 immunotherapy significantly prolonged survival (OS: 62.9 vs 38.0 months, p = 0.009; DFS: 48.7 vs 28.6 months, p = 0.033) in patients with OPN high pattern.

Conclusion

Serum OPN demonstrates standalone diagnostic value for HCC and enhances conventional biomarker panels when combined with AFP and AST. OPN high pattern identify patients likely to benefit from anti-PD-L1 immunotherapy, suggesting its dual utility as a diagnostic and predictive biomarker.

Peripheral blood proteome biomarkers distinguish immunosuppressive features of cancer progression

Immune status critically affects cancer progression and therapy responses. This study aimed to identify plasma proteome changes in immunosuppressive cancer and potential biomarkers predicting systemic immunosuppression. Mouse models of syngeneic breast tumors (benign 67NR and malignant 4T1) were used to collect plasma samples. Plasma samples from naive mice and both early- and late-stage tumor-bearing mice were subjected to liquid chromatography-mass spectrometry (LC-MS) analysis. 4T1-bearing mice showed systemic immunosuppression characterized by significant generation of myeloid-derived suppressor cells (MDSCs) as early as 7 days after tumor implantation, unlike 67NR tumors. LC-MS identified 1086 proteins across the five experimental groups, with 27 proteins showing group-specific expression in 4T1 blood compared with 67NR blood. Immune-related proteins osteopontin, lactotransferrin, calreticulin, and peroxiredoxin 2 were selected as potential biomarkers of MDSC-producing breast cancer. These markers were expressed in cancer cells or MDSC in the 4T1 model, and osteopontin and peroxiredoxin 2 were associated with low survival probability and high recurrence in patients with triple-negative breast cancer. Our findings suggest that MDSC-producing immunosuppressive cancers have unique plasma proteomes, offering additional insights into cancer immune status.

Identification and validation of a novel nine-gene prognostic signature of stem cell characteristic in hepatocellular carcinoma

Currently, cancer stem cells (CSCs) are regarded as the most promising target for cancer therapy due to their close association with tumor resistance, invasion, and recurrence. Thus, identifying CSCs-related genes and constructing a prognostic risk model associated with CSCs may be crucial for hepatocellular carcinoma (HCC) therapy. Xena Browser was used to download gene expression profiles and clinical data, while MSigDB was used to obtain genes associated with CSCs. Firstly, the non-negative matrix factorization (NMF) algorithm was used to cluster the HCC samples based on CSCs-related genes. To evaluate the predictive performance of the risk model, the receiver operating characteristic curves (ROC) and Kaplan-Meier analysis were used. The R package "rms" was used to construct the final nomogram based on risk scores and clinical characteristics. Based on 449 CSCs-related genes, a total of 588 HCC samples from TCGA-LIHC and ICGC-LIRI_JP were classified into four molecular subtypes with marked differences in survival and mRNA stemness index (mRNAsi) between subtypes. Univariate Cox regression, multivariate Cox regression, and LASSO regression analyses were performed on a total of 1417 differentially expressed genes (DEGs) between subtypes, and a nine-gene prognostic model was constructed with TTK, ST6GALNAC4, SPP1, SGCB, MEP1A, HTRA1, CD79A, C6, and ATP2A3. In both the training and testing sets and the external validation cohort, the risk model performed well in predicting HCC patients' survival. A nomogram was constructed and had high predictive efficacy in short-term survival. In comparison with the other two prognostic models, our nine-gene signature model performed best. We constructed a nine-gene signature model to predict the survival of HCC patients, which has good predictive efficacy and stability. The model may contribute to guiding the prognostic assessment of HCC patients in clinical practice.

Osteopontin: an indispensable component in common liver, pancreatic, and biliary related disease

BACKGROUND

The liver, gallbladder, and pancreas constitute a critically important system of digestive and endocrine organs in the human body, performing essential and complex physiological functions. At present, diseases of this digestive system have a high incidence in the world and is a more common disease. However, osteopontin (OPN) plays a crucial role in common liver, pancreatic, and biliary diseases, and its mechanisms of action merit further exploration and study.

METHODS

We performed an analysis to assess the role of osteopontin in liver, pancreatic, and biliary diseases, focusing on its significance in these conditions.

RESULTS

Osteopontin, a profoundly phosphorylated glycoprotein, can be utilized as a diagnostic marker for hepatocellular carcinoma and cholangiopathies. Additionally it assists in the treatment of non-alcoholic fatty liver disease and promotes the proliferation, migration, and invasion of pancreatic cancer cells. Furthermore, osteopontin regulates inflammatory responses in chronic pancreatitis.

CONCLUSIONS

This review offers a thorough analysis of the genetic and protein architecture of OPN, and elucidates the relationship between osteopontin and liver, pancreatic, and biliary diseases. Furthermore, exclusive focus is lavished on the potential utility of OPN as a biomarker and an innovative therapeutic target in the management of these disorder.

Targeting SPP1-orchestrated neutrophil extracellular traps-dominant pre-metastatic niche reduced HCC lung metastasis

Background

The mechanisms by which tumor-derived factors remodel the microenvironment of target organs to facilitate cancer metastasis, especially organ-specific metastasis, remains obscure. Our previous studies have demonstrated that SPP1 plays a key role in promoting metastasis of hepatocellular carcinoma (HCC). However, the functional roles and mechanisms of tumor-derived SPP1 in shaping the pre-metastatic niche (PMN) and promoting lung-specific metastasis are unclear.

Methods

Orthotopic metastasis models, experimental metastasis models, CyTOF and flow cytometry were conducted to explore the function of SPP1 in shaping neutrophil-dominant PMN and promoting HCC lung metastasis. The main source of CXCL1 in lung tissues was investigated via fluorescence activated cell sorting and immunofluorescence staining. The expression of neutrophils and neutrophil extracellular traps (NETs) markers was detected in the lung metastatic lesions of HCC patients and mouse lung specimens. The therapeutic significance was explored via in vivo DNase I and CXCR2 inhibitor assays.

Results

SPP1 promoted HCC lung colonization and metastasis by modifying pulmonary PMN in various murine models, and plasma SPP1 levels were closely associated with lung metastasis in HCC patients. Mechanistically, SPP1 binded to CD44 on lung alveolar epithelial cells to produce CXCL1, thereby attracting and forming neutrophil-abundant PMN in the lung. The recruited neutrophils were activated by SPP1 and then formed NETs-dominant PMN to trap the disseminated tumor cells and promote metastatic colonization. Moreover, early intervention of SPP1-orchestrated PMN by co-targeting the CXCL1-CXCR2 axis and NETs formation could efficiently inhibit the lung metastasis of HCC.

Conclusions

Our study illustrates that HCC-lung host cell-neutrophil interactions play important roles in PMN formation and SPP1-induced HCC lung metastasis. Early intervention in SPP1-orchestrated PMN via CXCR2 inhibitor and DNase I is a potential therapeutic strategy to combat HCC lung metastasis.

Targeting SPP1-orchestrated neutrophil extracellular traps-dominant pre-metastatic niche reduced HCC lung metastasis

BACKGROUND

The mechanisms by which tumor-derived factors remodel the microenvironment of target organs to facilitate cancer metastasis, especially organ-specific metastasis, remains obscure. Our previous studies have demonstrated that SPP1 plays a key role in promoting metastasis of hepatocellular carcinoma (HCC). However, the functional roles and mechanisms of tumor-derived SPP1 in shaping the pre-metastatic niche (PMN) and promoting lung-specific metastasis are unclear.

METHODS

Orthotopic metastasis models, experimental metastasis models, CyTOF and flow cytometry were conducted to explore the function of SPP1 in shaping neutrophil-dominant PMN and promoting HCC lung metastasis. The main source of CXCL1 in lung tissues was investigated via fluorescence activated cell sorting and immunofluorescence staining. The expression of neutrophils and neutrophil extracellular traps (NETs) markers was detected in the lung metastatic lesions of HCC patients and mouse lung specimens. The therapeutic significance was explored via in vivo DNase I and CXCR2 inhibitor assays.

RESULTS

SPP1 promoted HCC lung colonization and metastasis by modifying pulmonary PMN in various murine models, and plasma SPP1 levels were closely associated with lung metastasis in HCC patients. Mechanistically, SPP1 binded to CD44 on lung alveolar epithelial cells to produce CXCL1, thereby attracting and forming neutrophil-abundant PMN in the lung. The recruited neutrophils were activated by SPP1 and then formed NETs-dominant PMN to trap the disseminated tumor cells and promote metastatic colonization. Moreover, early intervention of SPP1-orchestrated PMN by co-targeting the CXCL1-CXCR2 axis and NETs formation could efficiently inhibit the lung metastasis of HCC.

CONCLUSIONS

Our study illustrates that HCC-lung host cell-neutrophil interactions play important roles in PMN formation and SPP1-induced HCC lung metastasis. Early intervention in SPP1-orchestrated PMN via CXCR2 inhibitor and DNase I is a potential therapeutic strategy to combat HCC lung metastasis.

Gut Microbiome and Hepatic Transcriptomic Determinants of HCC Development in Mice with Metabolic Dysfunction-Associated Steatohepatitis

Purpose

Hepatocellular carcinoma (HCC) related to metabolic dysfunction-associated steatotic liver disease (MASLD) is often diagnosed at a late stage, and its incidence is increasing. Predictive biomarkers are therefore needed to identify individuals at high risk of HCC. We aimed to characterize the gut microbiome and hepatic transcriptome associated with HCC development in female mice with hepatocyte-deletion of Pten (HepPten -). These mice present with large variations in HCC development, making them a powerful model for biomarker discovery.

Methods & Results

Sequencing of stool 16S and hepatic RNA was performed on a first set of mice. Among all liver histology parameters measured, the strongest association with microbiome composition changes was with the number of tumors detected at necropsy, followed by inflammation. The gut microbiome of mice with more than 2 tumors was enriched with Lachnospiraceae UCG and depleted of Palleniella intestinalis and Odoribacter. In contrast, hepatic transcriptomic changes were most strongly associated with tumor burden, followed by liver fibrosis. The 840 differentially expressed genes correlating with tumor burden were enriched in leukocyte extravasation and interleukin 10 receptor A (IL10RA) pathways. In addition, the abundance of Spp1-high epithelial cells is correlated with tumor burden. Association between tumor number and depletion of Palleniella intestinalis, and between tumor burden and circulating levels of C-X-C motif chemokine ligand 13 (CXCL13) and stem cell factor (SCF), was further validated in an independent set of mice.

Conclusion

We identified microbiome components contributing to liver carcinogenesis by inducing inflammation, and changes in hepatic gene expression and hepatic cells distribution that contribute to tumor growth. Such information can be highly valuable for the development of new prevention strategies as well as of new biomarkers for risk modeling in HCC.

Liquid Chromatography/Tandem Mass Spectrometry-Based Simultaneous Analysis of 32 Bile Acids in Plasma and Conventional Biomarker-Integrated Diagnostic Screening Model Development for Hepatocellular Carcinoma

Imaging tests, tumor marker (TM) screening, and biochemical tests provide a definitive diagnosis of hepatocellular carcinoma (HCC). However, some patients with HCC may present TM-negative results, warranting a need for developing more sensitive and accurate screening biomarkers. Various diseases exhibit increased blood levels of bile acids, biosynthesized from cholesterol in the liver, and they have been associated with HCC. Herein, we analyzed plasma bile acids using liquid chromatography/tandem mass spectrometry and integrated them with conventional biomarkers to develop a diagnostic screening model for HCC. Plasma samples were obtained from patients diagnosed with chronic hepatitis, hepatic cirrhosis (HC), and HCC. A QTRAP 6500 mass spectrometer and a Nexera liquid chromatograph with a YMC-Triart C18 analytical column were used. The mobile phase A was a 20 mmol/L ammonium formate solution, and mobile phase B was a methanol/acetonitrile mixture (1:1, v/v) with 20 mmol/L ammonium formate. After determining the concentrations of 32 bile acids, statistical analysis and diagnostic screening model development were performed. Plasma concentrations of bile acids differed between sample groups, with significant differences observed between patients with HC and HCC. By integrating bile acid results with conventional biochemical tests, a potential diagnostic screening model for HCC was successfully developed. Future studies should increase the sample size and analyze the data in detail to verify the diagnostic efficacy of the model.

Prediagnostic plasma proteomics profile for hepatocellular carcinoma

OBJECTIVE

Proteomics may discover pathophysiological changes related to hepatocellular carcinoma, an aggressive and lethal type of cancer with low sensitivity for early stage diagnosis.

DESIGN

We measured 1305 prediagnostic (median = 12.7 years) SomaScan proteins from 54 pairs of healthy individuals who subsequently developed hepatocellular carcinoma and matched non-hepatocellular carcinoma control individuals from the Nurses' Health Study (NHS) and the Health Professionals Follow-up Study (HPFS). Candidate proteins were validated in the independent, prospective UK Biobank Pharma Proteomics Project (UKB-PPP).

RESULTS

In NHS and HPFS, we identified 56 elevated proteins in hepatocellular carcinoma with an absolute fold change of more than 1.2 and a Wald test P value less than .05 in conditional logistic regression analysis. Ingenuity pathway analysis identified enrichment of pathways associated with cell viability, adhesion, proteolysis, apoptosis, and inflammatory response. Four proteins-chitinase-3-like protein 1, growth differentiation factor 15, interleukin-1 receptor antagonist protein, and E-selectin-showed strong positive associations with hepatocellular carcinoma and were thus validated by enzyme-linked immunosorbent assay (odds ratio = 2.48-14.7, all P < .05) in the NHS and HPFS and by Olink platform (hazard ratio = 1.90-3.93, all P < .05) in the UKB-PPP. Adding these 4 proteins to a logistic regression model of traditional hepatocellular carcinoma risk factors increased the area under the curve from 0.67 to 0.87 in the NHS and HPFS. Consistently, model area under the curve was 0.88 for hepatocellular carcinoma risk prediction in the UKB-PPP.

CONCLUSION

However, the limited number of hepatocellular carcinoma patients in the cohorts necessitates caution in interpreting our findings, emphasizing the need for further validation in high-risk populations.

Metabolomics biomarkers of hepatocellular carcinoma in a prospective cohort of patients with cirrhosis

Background & Aims

The effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited, due to inadequate risk stratification and suboptimal performance of current screening modalities.

Methods

We developed a multicenter prospective cohort of patients with cirrhosis undergoing surveillance with MRI and applied global untargeted metabolomics to 612 longitudinal serum samples from 203 patients. Among them, 37 developed HCC during follow-up.

Results

We identified 150 metabolites with significant abundance changes in samples collected prior to HCC (Cases) compared to samples from patients who did not develop HCC (Controls). Tauro-conjugated bile acids and gamma-glutamyl amino acids were increased, while acyl-cholines and deoxycholate derivatives were decreased. Seven amino acids including serine and alanine had strong associations with HCC risk, while strong protective effects were observed for N-acetylglycine and glycerophosphorylcholine. Machine learning using the 150 metabolites, age, gender, and PNPLA3 and TMS6SF2 single nucleotide polymorphisms, identified 15 variables giving optimal performance. Among them, N-acetylglycine had the highest AUC in discriminating Cases and Controls. When restricting Cases to samples collected within 1 year prior to HCC (Cases-12M), additional metabolites including microbiota-derived metabolites were identified. The combination of the top six variables identified by machine learning (alpha-fetoprotein, 6-bromotryptophan, N-acetylglycine, salicyluric glucuronide, testosterone sulfate and age) had good performance in discriminating Cases-12M from Controls (AUC 0.88, 95% CI 0.83-0.93). Finally, 23 metabolites distinguished Cases with LI-RADS-3 lesions from Controls with LI-RADS-3 lesions, with reduced abundance of acyl-cholines and glycerophosphorylcholine-related lysophospholipids in Cases.

Conclusions

This study identified N-acetylglycine, amino acids, bile acids and choline-derived metabolites as biomarkers of HCC risk, and microbiota-derived metabolites as contributors to HCC development.

Impact and implications

The effectiveness of surveillance for hepatocellular carcinoma (HCC) in patients with cirrhosis is limited. There is an urgent need for improvement in risk stratification and new screening modalities, particularly blood biomarkers. Longitudinal collection of paired blood samples and MRI images from patients with cirrhosis is particularly valuable in assessing how early blood and imaging markers become positive during the period when lesions are observed to obtain a diagnosis of HCC. We generated a multicenter prospective cohort of patients with cirrhosis under surveillance with contrast MRI, applied untargeted metabolomics on 612 serum samples from 203 patients and identified metabolites associated with risk of HCC development. Such biomarkers may significantly improve early-stage HCC detection for patients with cirrhosis undergoing HCC surveillance, a critical step to increasing curative treatment opportunities and reducing mortality.

Repaglinide restrains HCC development and progression by targeting FOXO3/lumican/p53 axis

PURPOSE

The recent focus on the roles of N-linked glycoproteins in carcinogenesis across various malignancies has prompted our exploration of aberrantly expressed glycoproteins responsible for HCC progression and potential therapeutic strategy.

METHODS

Mass spectrometry was applied to initially identify abnormally expressed glycoproteins in HCC, which was further assessed by immunohistochemistry (IHC) staining. The role of selected glycoprotein on HCC development and underlying mechanism was systematically investigated by colony formation, mouse xenograft, RNA-sequencing and western blot assays, etc. Chromatin immunoprecipitation (ChIP) and luciferase assays were performed to explore potential transcription factors (TFs) of selected glycoprotein. The regulation of repaglinide (RPG) on expression of lumican and downstream effectors was assessed by western blot and IHC, while its impact on malignant phenotypes of HCC was explored through in vitro and in vivo analyses, including a murine NASH-HCC model established using western diet and carbon tetrachloride (CCl4).

RESULTS

Lumican exhibited upregulation in both serum and tumor tissue, with elevated expression associated with an inferior prognosis in HCC patients. Knockdown of lumican resulted in significantly reduced growth of HCC in vitro and in vivo. Mechanically, lumican promoted HCC malignant phenotypes by inhibiting the p53/p21 signaling pathway. Forkhead Box O3 (FOXO3) was identified as the TF of lumican that transcriptionally enhanced its expression. Without silencing FOXO3, RPG blocked the binding of FOXO3 to the promoter region of lumican, thereby inhibiting the activation of lumican/p53/p21 axis. Mice treated with RPG developed fewer and smaller HCCs than those in the control group at 24 weeks after establishment.

CONCLUSION

Our results indicate that RPG prevented the development and progression of HCC via alteration of FOXO3/lumican/p53 axis.

Recent Advances in Biosensor Technology for Early-Stage Detection of Hepatocellular Carcinoma-Specific Biomarkers: An Overview

Hepatocellular carcinoma is currently the most common malignancy of the liver. It typically occurs due to a series of oncogenic mutations that lead to aberrant cell replication. Most commonly, hepatocellular carcinoma (HCC) occurs as a result of pre-occurring liver diseases, such as hepatitis and cirrhosis. Given its aggressive nature and poor prognosis, the early screening and diagnosis of HCC are crucial. However, due to its plethora of underlying risk factors and pathophysiologies, patient presentation often varies in the early stages, with many patients presenting with few, if any, specific symptoms in the early stages. Conventionally, screening and diagnosis are performed through radiological examination, with diagnosis confirmed by biopsy. Imaging modalities tend to be limited by their requirement of large, expensive equipment; time-consuming operation; and a lack of accurate diagnosis, whereas a biopsy's invasive nature makes it unappealing for repetitive use. Recently, biosensors have gained attention for their potential to detect numerous conditions rapidly, cheaply, accurately, and without complex equipment and training. Through their sensing platforms, they aim to detect various biomarkers, such as nucleic acids, proteins, and even whole cells extracted by a liquid biopsy. Numerous biosensors have been developed that may detect HCC in its early stages. We discuss the recent updates in biosensing technology, highlighting its competitive potential compared to conventional methodology and its prospects as a tool for screening and diagnosis.

Emerging and Clinically Accepted Biomarkers for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death and the sixth most diagnosed malignancy worldwide. Serum alpha-fetoprotein (AFP) is the traditional, ubiquitous biomarker for HCC. However, there has been an increasing call for the use of multiple biomarkers to optimize care for these patients. AFP, AFP-L3, and prothrombin induced by vitamin K absence II (DCP) have described clinical utility for HCC, but unfortunately, they also have well established and significant limitations. Circulating tumor DNA (ctDNA), genomic glycosylation, and even totally non-invasive salivary metabolomics and/or micro-RNAS demonstrate great promise for early detection and long-term surveillance, but still require large-scale prospective validation to definitively validate their clinical validity. This review aims to provide an update on clinically available and emerging biomarkers for HCC, focusing on their respective clinical strengths and weaknesses.

Molecular pathology and protein markers for pancreatic cancer: relevance in staging, in adjuvant therapy, in determination of minimal residual disease, and follow-up

The diagnosis and monitoring of disease through the detection of circulating protein biomarkers is a growing field in the practice of oncology. The search for more effective protein biomarkers to aid in the diagnosis and treatment of patients with pancreatic ductal adenocarcinoma (PDAC) remains a valuable area of study, given the aggressive and often occult nature of this malignancy. Liquid biopsies are attractive, as they offer a minimally invasive and cost-effective approach when compared to traditional biopsy methods and imaging modalities used for diagnosis and surveillance. Carbohydrate antigen (CA) 19-9 is currently the most commonly used serum protein biomarker for the diagnosis and monitoring of patients with PDAC, but due to its sensitivity and specificity, its utility remains limited. In this review, we examine how circulating protein biomarkers are used in the diagnosis, prognostication, and surveillance of PDAC. We also highlight protein biomarkers that are currently under investigation that have the potential to enhance our ability to detect early-stage malignancies, predict response to therapy, and monitor for recurrence, but these markers require larger prospective validation studies before they can be widely implemented. Continued efforts to identify and validate novel biomarkers will be crucial for improving the management and outcomes of patients with this challenging disease.

Integrative Multianalytical Model Based on Novel Plasma Protein Biomarkers for Distinguishing Lung Adenocarcinoma and Benign Pulmonary Nodules

Given the pressing clinical problem of making a decision in diagnosis for subjects with pulmonary nodules, we aimed to discover novel plasma protein biomarkers for lung adenocarcinoma (LUAD) and benign pulmonary nodules (BPNs) and then develop an integrative multianalytical model to guide the clinical management of LUAD and BPN patients. Through label-free quantitative plasma proteomic analysis (data are available via ProteomeXchange with identifier PXD046731), 12 differentially expressed proteins (DEPs) in LUAD and BPN were screened. The diagnostic abilities of DEPs were validated in two independent validation cohorts. The results showed that the levels of three candidate proteins (PRDX2, PON1, and APOC3) were lower in the plasma of LUAD than in BPN. The three candidate proteins were combined with three promising computed tomography indicators (spiculation, vascular notch sign, and lobulation) and three traditional markers (CEA, CA125, and CYFRA21-1) to construct an integrative multianalytical model, which was effective in distinguishing LUAD from BPN, with an AUC of 0.904, a sensitivity of 81.44%, and a specificity of 90.14%. Moreover, the model possessed impressive diagnostic performance between early LUADs and BPNs, with the AUC, sensitivity, specificity, and accuracy of 0.868, 65.63%, 90.14%, and 82.52%, respectively. This model may be a useful auxiliary diagnostic tool for LUAD and BPN by achieving a better balance of sensitivity and specificity.

Molecular Biomarkers in Cholangiocarcinoma: Focus on Bile

Hepatobiliary system cancers have demonstrated an increasing incidence rate in the past years. Without the presence of early symptoms, the majority of such cancers manifest with a set of similar symptoms, such as cholestasis resulting in posthepatic icterus. Differential diagnosis of hepatobiliary cancers is required for the therapy selection, however, the similarity of the symptoms complicates diagnostics. Thus, the search for molecular markers is of high interest for such patients. Cholangiocarcinoma (CCA) is characterized by a poor prognosis due to a low resectability rate, which occurs because this disease is frequently beyond the limits of surgical therapy at the time of diagnosis. The CCA is diagnosed by the combination of clinical/biochemical features, radiological methods, and non-specific serum tumor biomarkers, although invasive examination is still needed. The main disadvantage is limited specificity and sensitivity, which complicates early diagnostics. Therefore, prognostic and predictive biomarkers are still lacking and urgently needed for early diagnosis. In contrast to serum, bile is more accessible to identify biliary disease due to its simpler composition. Moreover, bile can contain higher concentrations of tumor biomarkers due to its direct contact with the tumor. It is known that the composition of the main bile component - bile acids, may vary during different diseases of the biliary tract. This review summarizes the recent developments in the current research on the diagnostic biomarkers for CCA in serum and bile and provides an overview of the methods of bile acids analysis.

Integrated plasma metabolomics and lipidomics profiling highlights distinctive signature of hepatocellular carcinoma in HCV patients

BACKGROUND

Early diagnosis of hepatocellular carcinoma (HCC) is essential towards the improvement of prognosis and patient survival. Circulating markers such as α-fetoprotein (AFP) and micro-RNAs represent useful tools but still have limitations. Identifying new markers can be fundamental to improve both diagnosis and prognosis. In this approach, we harness the potential of metabolomics and lipidomics to uncover potential signatures of HCC.

METHODS

A combined untargeted metabolomics and lipidomics plasma profiling of 102 HCV-positive patients was performed by HILIC and RP-UHPLC coupled to Mass Spectrometry. Biochemical parameters of liver function (AST, ALT, GGT) and liver cancer biomarkers (AFP, CA19.9 e CEA) were evaluated by standard assays.

RESULTS

HCC was characterized by an elevation of short and long-chain acylcarnitines, asymmetric dimethylarginine, methylguanine, isoleucylproline and a global reduction of lysophosphatidylcholines. A supervised PLS-DA model showed that the predictive accuracy for HCC class of metabolomics and lipidomics was superior to AFP for the test set (100.00% and 94.40% vs 55.00%). Additionally, the model was applied to HCC patients with AFP values < 20 ng/mL, and, by using only the top 20 variables selected by VIP scores achieved an Area Under Curve (AUC) performance of 0.94.

CONCLUSION

These exploratory findings highlight how metabo-lipidomics enables the distinction of HCC from chronic HCV conditions. The identified biomarkers have high diagnostic potential and could represent a viable tool to support and assist in HCC diagnosis, including AFP-negative patients.

Emerging biomolecules for practical theranostics of liver hepatocellular carcinoma

Most cases of hepatocellular carcinoma (HCC) are able to be diagnosed through regular surveillance in an identifiable patient population with chronic hepatitis B or cirrhosis. Nevertheless, 50% of global cases might present incidentally owing to symptomatic advanced-stage HCC after worsening of liver dysfunction. A systematic search based on PUBMED was performed to identify relevant outcomes, covering newer surveillance modalities including secretory proteins, DNA methylation, miRNAs, and genome sequencing analysis which proposed molecular expression signatures as ideal tools in the early-stage HCC detection. In the face of low accuracy without harmonization on the analytical approaches and data interpretation for liquid biopsy, a more accurate incidence of HCC will be unveiled by using deep machine learning system and multiplex immunohistochemistry analysis. A combination of molecular-secretory biomarkers, high-definition imaging and bedside clinical indexes in a surveillance setting offers a comprehensive range of HCC potential indicators. In addition, the sequential use of numerous lines of systemic anti-HCC therapies will simultaneously benefit more patients in survival. This review provides an overview on the most recent developments in HCC theranostic platform.

Osteopontin regulates the growth and invasion of liver cancer cells via DTL

Osteopontin (OPN), a secreted phosphoglycoprotein, has important roles in tumor growth, invasion and metastasis in numerous types of cancers. Denticleless E3 ubiquitin protein ligase homolog (DTL), one of the CUL4-DDB1-associated factors (DCAFs), has also been associated with the invasion and metastasis of cancer cells. In the present study, OPN was found to induce DTL expression in liver cancer cells, and the results obtained using luciferase activity assays demonstrated that OPN could transcriptionally activate DTL expression in liver cancer cells. Furthermore, the results of the present study demonstrated that OPN could increase the expression of DTL via PI3K/AKT signaling. In conclusion, the present study demonstrated that OPN, as an extracellular matrix protein, is able to promote the growth and invasion of liver cancer cells through stimulation of the expression of DTL via the PI3K/AKT signaling pathway.

Immunobiological signatures and the emerging role of SPP1 in predicting tumor heterogeneity, malignancy, and clinical outcomes in stomach adenocarcinoma

BACKGROUND

Immunotherapy, as a form of immunobiological therapy, represents a promising approach for enhancing patients' immune responses. This work aims to present innovative ideas and insights for prognostic assessment and clinical treatment of stomach adenocarcinoma (STAD) by leveraging immunobiological signatures.

METHODS

We employed weighted gene co-expression network analysis (WGCNA) and unsupervised clustering analysis to identify hub genes. These hub genes were utilized to construct a prognostic risk model, and their impact on the tumor microenvironment (TME) and DNA variations was assessed using large-scale STAD patient cohorts. Additionally, we conducted transfection experiments with plasmids to investigate the influence of SPP1 on the malignancy of HGC27 and NCI-N87 cells.

RESULTS

Unsupervised clustering of 12 immune-related genes (IRGs) revealed three distinct alteration patterns with unique molecular phenotypes, clinicopathological characteristics, prognosis, and TME features. Using LASSO and multivariate Cox regression analyses, we identified three hub genes (MMP12, SPP1, PLAU) from the IRGs to establish a risk signature. This IRG-related risk model significantly stratified the prognosis risk among STAD patients in the training (n = 522), testing (n = 521), and validation (n = 300) cohorts. Notably, there were discernible differences in therapy responses and TME characteristics, such as tumor purity and lymphocyte infiltration, between the risk model groups. Subsequently, a nomogram that incorporates the IRG signature and clinicopathological factors demonstrated superior sensitivity and specificity in predicting outcomes for STAD patients. Furthermore, down-regulation of SPP1, as observed after siRNA transfection, significantly inhibited the proliferation and migration abilities of HGC27 and NCI-N87 cells.

CONCLUSIONS

In summary, this study highlights the critical role of immune-related signatures in STAD and offers novel insights into prognosis indicators and immunotherapeutic targets for this condition. SPP1 emerges as an independent prognostic factor for STAD and appears to regulate STAD progression by influencing the immune microenvironment.

The Role of Mass Spectrometry in Hepatocellular Carcinoma Biomarker Discovery

Hepatocellular carcinoma (HCC) is the main liver malignancy and has a high mortality rate. The discovery of novel biomarkers for early diagnosis, prognosis, and stratification purposes has the potential to alleviate its disease burden. Mass spectrometry (MS) is one of the principal technologies used in metabolomics, with different experimental methods and machine types for different phases of the biomarker discovery process. Here, we review why MS applications are useful for liver cancer, explain the MS technique, and briefly summarise recent findings from metabolomic MS studies on HCC. We also discuss the current challenges and the direction for future research.

Interleukin-6 in Hepatocellular Carcinoma: A Dualistic Point of View

Hepatocellular Carcinoma (HCC) is a pressing health concern, demanding a deep understanding of various mediators' roles in its development for therapeutic progress. Notably, interleukin-6 (IL-6) has taken center stage in investigations due to its intricate and context-dependent functions. This review delves into the dual nature of IL-6 in HCC, exploring its seemingly contradictory roles as both a promoter and an inhibitor of disease progression. We dissect the pro-tumorigenic effects of IL-6, including its impact on tumor growth, angiogenesis, and metastasis. Concurrently, we examine its anti-tumorigenic attributes, such as its role in immune response activation, cellular senescence induction, and tumor surveillance. Through a comprehensive exploration of the intricate interactions between IL-6 and the tumor microenvironment, this review highlights the need for a nuanced comprehension of IL-6 signaling in HCC. It underscores the importance of tailored therapeutic strategies that consider the dynamic stages and diverse surroundings within the tumor microenvironment. Future research directions aimed at unraveling the multifaceted mechanisms of IL-6 in HCC hold promise for developing more effective treatment strategies and improving patient outcomes.

The extracellular matrix in hepatocellular carcinoma: Mechanisms and therapeutic vulnerability

The tumor microenvironment (TME) is influenced by a "disorganized" extracellular matrix (ECM) that sensitizes cancer cells toward mechanical stress, signaling, and structural alterations. In hepatocellular carcinoma (HCC), lack of knowledge about key ECM proteins driving the TME refractory to targeted therapies poses a barrier to the identification of new therapeutic targets. Herein, we discuss the contributions of various ECM components that impact hepatocytes and their surrounding support network during tumorigenesis. In addition, the underpinnings by which ECM proteins transduce mechanical signals to the liver TME are detailed. Finally, in view of the bidirectional feedback between the ECM, transformed hepatocytes, and immune cells, we highlight the potential role of the ECM disorganization process in shaping responses to immune checkpoint inhibitors and targeted therapies. Our comprehensive characterization of these ECM components may provide a roadmap for innovative therapeutic approaches to restrain HCC.

Hepatocellular Carcinoma Genetic Classification

ABSTRACT

Hepatocellular carcinoma (HCC) represents a significant global burden, with management complicated by its heterogeneity, varying presentation, and relative resistance to therapy. Recent advances in the understanding of the genetic, molecular, and immunological underpinnings of HCC have allowed a detailed classification of these tumors, with resultant implications for diagnosis, prognostication, and selection of appropriate treatments. Through the correlation of genomic features with histopathology and clinical outcomes, we are moving toward a comprehensive and unifying framework to guide our diagnostic and therapeutic approach to HCC.

A novel approach for the analysis of single-cell RNA sequencing identifies TMEM14B as a novel poor prognostic marker in hepatocellular carcinoma

A fundamental goal in cancer-associated genome sequencing is to identify the key genes. Protein-protein interactions (PPIs) play a crucially important role in this goal. Here, human reference interactome (HuRI) map was generated and 64,006 PPIs involving 9094 proteins were identified. Here, we developed a physical link and co-expression combinatory network construction (PLACE) method for genes of interest, which provides a rapid way to analyze genome sequencing datasets. Next, Kaplan‒Meier survival analysis, CCK8 assays, scratch wound assays and Transwell assays were applied to confirm the results. In this study, we selected single-cell sequencing data from patients with hepatocellular carcinoma (HCC) in GSE149614. The PLACE method constructs a protein connection network for genes of interest, and a large fraction (80%) of the genes (screened by the PLACE method) were associated with survival. Then, PLACE discovered that transmembrane protein 14B (TMEM14B) was the most significant prognostic key gene, and target genes of TMEM14B were predicted. The TMEM14B-target gene regulatory network was constructed by PLACE. We also detected that TMEM14B-knockdown inhibited proliferation and migration. The results demonstrate that we proposed a new effective method for identifying key genes. The PLACE method can be used widely and make outstanding contributions to the tumor research field.

Biomarkers for Hepatocellular Carcinoma: From Origin to Clinical Diagnosis

The incidence of hepatocellular carcinoma (HCC) and HCC-related deaths has increased over the last few decades. There are several risk factors of HCC such as viral hepatitis (B, C), cirrhosis, tobacco and alcohol use, aflatoxin-contaminated food, pesticides, diabetes, obesity, nonalcoholic fatty liver disease (NAFLD), and metabolic and genetic diseases. Diagnosis of HCC is based on different methods such as imaging ultrasonography (US), multiphasic enhanced computed tomography (CT), magnetic resonance imaging (MRI), and several diagnostic biomarkers. In this review, we examine the epidemiology of HCC worldwide and in Egypt as well as risk factors associated with the development of HCC and, finally, provide the updated diagnostic biomarkers for the diagnosis of HCC, particularly in the early stages of HCC. Several biomarkers are considered to diagnose HCC, including downregulated or upregulated protein markers secreted during HCC development, circulating nucleic acids or cells, metabolites, and the promising, recently identified biomarkers based on quantitative proteomics through the isobaric tags for relative and absolute quantitation (iTRAQ). In addition, a diagnostic model used to improve the sensitivity of combined biomarkers for the diagnosis of early HCC is discussed.

Serum osteopontin predicts the response to atezolizumab plus bevacizumab in patients with hepatocellular carcinoma

BACKGROUND

Combination therapy with anti-programmed death-ligand 1 and anti-vascular endothelial growth factor (VEGF) antibodies has become the standard treatment for un-resectable hepatocellular carcinoma (uHCC). We aimed to identify predictive circulating biomarkers for the outcome/response of the combination therapy in uHCC patients.

METHODS

This prospective multicenter study enrolled 70 patients with uHCC who received atezolizumab and bevacizumab (Atez/Bev). We evaluated 47 circulating proteins in sera before and after 1 and 6 weeks of Atez/Bev therapy by multiplex bead-based immunoassay and ELISA. As controls, we analyzed the sera from 62 uHCC patients before treatment of lenvatinib (LEN) and healthy volunteers (HVs).

RESULTS

The disease control rate was 77.1%. Median progression-free survival (PFS) was 5.7 months (95% confidence interval [CI] = 3.8-9.5). The pretreatment levels of osteopontin (OPN), angiopoietin-2, VEGF, S100-calcium-binding protein A8/S100-calcium-binding protein A9, soluble programmed cell death-1, soluble CD163, and 14 cytokines/chemokines were higher in patients with uHCC than in HVs. Among these, pretreatment OPN levels were higher in PD group than in non-PD group for Atez/Bev. The PD rate was higher in high OPN group than in low OPN group. Multivariate analysis identified high pretreatment OPN and high α-fetoprotein levels as independent predictors of PD. In the sub-analysis of Child-Pugh class A patients, PFS was also shorter in the high OPN group than in the low OPN group. Pretreatment OPN level was not associated with treatment response for LEN.

CONCLUSION

High serum OPN levels were associated with poor response to Atez/Bev in patients with uHCC.

An Overview of Hepatocellular Carcinoma Surveillance Focusing on Non-Cirrhotic NAFLD Patients: A Challenge for Physicians

Non-alcoholic fatty liver disease (NAFLD) is the most common cause of liver disease worldwide and it ranges from simple steatosis to hepatocellular carcinoma (HCC). HCC represents the first liver tumor and the third source of cancer death. In the next few years, the prevalence of NAFLD and consequently of HCC is estimated to increase, becoming a major public health problem. The NAFLD-HCC shows several differences compared to other causes of chronic liver disease (CLD), including the higher percentage of patients that develop HCC in the absence of liver cirrhosis. In HCC surveillance, the international guidelines suggest a six months abdominal ultrasound (US), with or without alpha-fetoprotein (AFP) evaluation, in patients with cirrhosis and in a subgroup of patients with chronic hepatitis B infection. However, this screening program reveals several limitations, especially in NAFLD patients. Thus, new biomarkers and scores have been proposed to overcome the limits of HCC surveillance. In this narrative review we aimed to explore the differences in the HCC features between NAFLD and non-NAFLD patients, and those between NAFLD-HCC developed in the cirrhotic and non-cirrhotic liver. Finally, we focused on the limits of tumor surveillance in NAFLD patients, and we explored the new biomarkers for the early diagnosis of HCC.

Circulating Biomarkers for the Early Diagnosis and Management of Hepatocellular Carcinoma with Potential Application in Resource-Limited Settings

Hepatocellular carcinoma (HCC) is among the world's third most lethal cancers. In resource-limited settings (RLS), up to 70% of HCCs are diagnosed with limited curative treatments at an advanced symptomatic stage. Even when HCC is detected early and resection surgery is offered, the post-operative recurrence rate after resection exceeds 70% in five years, of which about 50% occur within two years of surgery. There are no specific biomarkers addressing the surveillance of HCC recurrence due to the limited sensitivity of the available methods. The primary goal in the early diagnosis and management of HCC is to cure disease and improve survival, respectively. Circulating biomarkers can be used as screening, diagnostic, prognostic, and predictive biomarkers to achieve the primary goal of HCC. In this review, we highlighted key circulating blood- or urine-based HCC biomarkers and considered their potential applications in resource-limited settings, where the unmet medical needs of HCC are disproportionately highly significant.

Blood-based biomarkers for hepatocellular carcinoma screening: Approaching the end of the ultrasound era?

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, in part because of inadequate early detection strategies. Current recommendations for screening consist of semi-annual abdominal ultrasound with or without serum alpha-fetoprotein in patients with cirrhosis and in demographic subgroups with chronic hepatitis B infection. However, this screening strategy has several deficiencies, including suboptimal early-stage sensitivity, false positives with subsequent harms, inter-operator variability in ultrasound performance, and poor adherence. A blood-based biomarker with sufficient performance characteristics for early-stage disease could overcome several of these barriers to improving early-stage detection. However, prior to use of a biomarker for screening in clinical practice, a multistep validation is required in order to understand test performance characteristics. These steps include case-control validation, followed by validation in prospective cohorts of at-risk patients. Until recently, we lacked adequate longitudinal validation cohorts for early HCC detection; however, several validation cohorts are maturing, including the Hepatocellular Carcinoma Early Detection Study and the Texas Hepatocellular Carcinoma Consortium, which will allow for rigorous validation of candidate biomarkers. While there are several promising biomarkers awaiting validation, in order to supplant abdominal ultrasound, a candidate biomarker must show adequate test performance and overcome practical hurdles to ensure adoption in clinical practice. The promise of blood-based biomarkers is significant, especially given the limitations of ultrasound-based screening; however, they require adequate validation and several logistical obstacles must be overcome prior to clinical implementation.

Hepatitis B virus pathogenesis relevant immunosignals uncovering amino acids utilization related risk factors guide artificial intelligence-based precision medicine

Background: Although immune microenvironment-related chemokines, extracellular matrix (ECM), and intrahepatic immune cells are reported to be highly involved in hepatitis B virus (HBV)-related diseases, their roles in diagnosis, prognosis, and drug sensitivity evaluation remain unclear. Here, we aimed to study their clinical use to provide a basis for precision medicine in hepatocellular carcinoma (HCC) via the amalgamation of artificial intelligence. Methods: High-throughput liver transcriptomes from Gene Expression Omnibus (GEO), NODE (https://www.bio.sino.org/node), the Cancer Genome Atlas (TCGA), and our in-house hepatocellular carcinoma patients were collected in this study. Core immunosignals that participated in the entire diseases course of hepatitis B were explored using the "Gene set variation analysis" R package. Using ROC curve analysis, the impact of core immunosignals and amino acid utilization related gene on hepatocellular carcinoma patient's clinical outcome were calculated. The utility of core immunosignals as a classifier for hepatocellular carcinoma tumor tissue was evaluated using explainable machine-learning methods. A novel deep residual neural network model based on immunosignals was constructed for the long-term overall survival (LS) analysis. In vivo drug sensitivity was calculated by the "oncoPredict" R package. Results: We identified nine genes comprising chemokines and ECM related to hepatitis B virus-induced inflammation and fibrosis as CLST signals. Moreover, CLST was co-enriched with activated CD4+ T cells bearing harmful factors (aCD4) during all stages of hepatitis B virus pathogenesis, which was also verified by our hepatocellular carcinoma data. Unexpectedly, we found that hepatitis B virus-hepatocellular carcinoma patients in the CLSThighaCD4high subgroup had the shortest overall survival (OS) and were characterized by a risk gene signature associated with amino acids utilization. Importantly, characteristic genes specific to CLST/aCD4 showed promising clinical relevance in identifying patients with early-stage hepatocellular carcinoma via explainable machine learning. In addition, the 5-year long-term overall survival of hepatocellular carcinoma patients can be effectively classified by CLST/aCD4 based GeneSet-ResNet model. Subgroups defined by CLST and aCD4 were significantly involved in the sensitivity of hepatitis B virus-hepatocellular carcinoma patients to chemotherapy treatments. Conclusion: CLST and aCD4 are hepatitis B virus pathogenesis-relevant immunosignals that are highly involved in hepatitis B virus-induced inflammation, fibrosis, and hepatocellular carcinoma. Gene set variation analysis derived immunogenomic signatures enabled efficient diagnostic and prognostic model construction. The clinical application of CLST and aCD4 as indicators would be beneficial for the precision management of hepatocellular carcinoma.

Transcriptional level evaluation of osteopontin/miRNA-181a axis in hepatocellular carcinoma cell line-secreted extracellular vesicles

Recent evidence suggested the role of secreted extracellular vesicles (EVs) in the intracellular signalling within the liver becoming a promising candidate as biomarker in hepatocellular carcinoma (HCC). Osteopontin (OPN) seems to play a relevant role both for early diagnosis of HCC than on the mechanisms that drive oncogenesis but, to date, information on the expression levels of OPN in EVs secreted by HCC tumor cell line are missing. The study aimed to verify, by transcriptional and proteomic study, the presence of OPN in EVs secreted by tumorigenic (HepG2) and non-tumorigenic hepatocyte cell line (WRL68), and to analyse the expression variations of OPN, its isoforms and miRNA-181a in both these EVs. "In silico analysis" was also performed via the Gene expression Profiling Interactive analysis (GEPIA) and Hepatocellular Carcinoma Database (HCCDB). An up-regulation of OPN in EVs secreted by HepG2 with respect to WRL68 was found in line with the results obtained by the "in silico analysis". The study demonstrates, for the first time, the OPN isoforms and its modulator miRNA-181a expression in EVs secreted by both cell lines, highlighting high levels of OPN isoforms in EVs secreted by HepG2 and identifying OPN as a promising biomarker for HCC diagnosis.

Modeling and integration of N-glycan biomarkers in a comprehensive biomarker data model

Molecular biomarkers measure discrete components of biological processes that can contribute to disorders when impaired. Great interest exists in discovering early cancer biomarkers to improve outcomes. Biomarkers represented in a standardized data model, integrated with multi-omics data, may improve understanding and use of novel biomarkers such as glycans and glycoconjugates. Among altered components in tumorigenesis, N-glycans exhibit substantial biomarker potential, when analyzed with their protein carriers. However, such data are distributed across publications and databases of diverse formats, which hampers their use in research and clinical application. Mass spectrometry measures of fifty N-glycans, on seven serum proteins in liver disease, were integrated (as a panel) into a cancer biomarker data model, providing a unique identifier, standard nomenclature, links to glycan resources, and accession and ontology annotations to standard protein, gene, disease, and biomarker information. Data provenance was documented with a standardized FDA-supported BioCompute Object. Using the biomarker data model allows capture of granular information, such as glycans with different levels of abundance in cirrhosis, hepatocellular carcinoma, and transplant groups. Such representation in a standardized data model harmonizes glycomics data in a unified framework, making glycan-protein biomarker data exploration more available to investigators and to other data resources. The biomarker data model we describe can be used by researchers to describe their novel glycan and glycoconjugate biomarkers, can integrate N-glycan biomarker data with multi-source biomedical data, and can foster discovery and insight within a unified data framework for glycan biomarker representation thereby making the data FAIR (Findable, Accessible, Interoperable, Reusable) (https://www.go-fair.org/fair-principles/).

Potential Biomarkers for Liver Cancer Diagnosis Based on Multi-Omics Strategy

Liver cancer is the fourth leading cause of cancer-related death worldwide. Hepatocellular carcinoma (HCC) accounts for about 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients are eligible for curative therapy mainly due to the lack of early-detection strategies, highlighting the significance of reliable and accurate biomarkers. The integration of multi-omics became an important tool for biomarker screening and unique alterations in tumor-associated genes, transcripts, proteins, post-translational modifications and metabolites have been observed. We here summarized the novel biomarkers for HCC diagnosis based on multi-omics technology as well as the clinical significance of these potential biomarkers in the early detection of HCC.

Liquid biopsy: the value of different bodily fluids

Liquid biopsies have gained an increasing interest in the last years among medical and scientific communities. Indeed, the value of liquid effusions, while less invasive and more accurate techniques, has been markedly highlighted. Peripheral blood comprises the most often analyzed sample, but recent evidences have pointed out the huge importance of other bodily fluids, including pleural and peritoneal fluids, urine, saliva and cerebrospinal fluid in the detection and monitoring of different tumor types. In face to these advances, this review aims to provide an overview of the value of tumor-associated mutations, detectable in different effusions, and how they can be used in clinical practice, namely in prognosis assessment and early disease and minimal disease recurrence detection, and in predicting the treatment response or acquired-resistance development.

EMT and Inflammation: Crossroads in HCC

Hepatocellular carcinoma is one of the major causes of cancer-related deaths worldwide and is associated with several inflammatory mediators, since 90% of HCCs occur based on chronic hepatitis B or C, alcoholism or increasingly metabolic syndrome-associated inflammation. EMT is a physiological process, with coordinated changes in epithelial gene signatures and is regulated by multiple factors, including cytokines and growth factors such as TGFβ, EGF, and FGF. Recent reports propose a strong association between EMT and inflammation, which is also correlated with tumor aggressiveness and poor outcomes. Cellular heterogeneity results collectively as an outcome of EMT, inflammation, and the tumor microenvironment, and it plays a fundamental role in the progression, complexity of cancer, and chemoresistance. In this review, we highlight recent developments concerning the association of EMT and inflammation in the context of HCC progression. Identifying potential EMT-related biomarkers and understanding EMT regulatory molecules will likely contribute to promising developments in clinical practice and will be a valuable tool for predicting metastasis in general and specifically in HCC.

Identification and Validation of a Tumor Microenvironment-Related Gene Signature in Hepatocellular Carcinoma Prognosis

Background: Hepatocellular carcinoma (HCC) is a typical inflammatory-related malignant tumor with complex immune tolerance microenvironment and poor prognosis. In this study, we aimed to construct a novel immune-related gene signature for the prognosis of HCC patients, exploring tumor microenvironment (TME) cell infiltration characterization and potential mechanisms. Methods: A total of 364 HCC samples with follow-up information in the TCGA-LIHC dataset were analyzed for the training of the prognostic signature. The Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the IRGs was conducted to identify the prognostic genes and establish an immune risk signature. The immune cell infiltration in TME was estimated via the CIBERSORT method. Gene Set Variation Analysis (GSVA) was conducted to compare the biological pathways involved in the low-risk and high-risk groups. Furthermore, paraffin sections of HCC tissue microarrays containing 77 patients from Fudan University Shanghai Cancer Center were used for IHC staining. The clinical characteristics of the 77 HCC patients were collected and summarized for survival analysis validation via the Kaplan-Meier (KM) method. Results: Three-gene signature with close immune correlation (Risk score = EPO * 0.02838 + BIRC5 * 0.02477 + SPP1 * 0.0002044) was constructed eventually and proven to be an effective prognostic factor for HCC patients. The patients were divided into a high-risk and a low-risk group according to the optimal cutoff, and the survival analysis revealed that HCC samples with high-risk immuno-score had significantly poorer outcomes than the low-risk group (p < 0.0001). The results of CIBERSORT suggested that the immune cell activation was relatively higher in the low-risk group with better prognosis. Besides, GSVA analysis showed multiple signaling differences between the high- and low-risk group, indicating that the three-gene prognostic model can affect the prognosis of patients by affecting immune-related mechanisms. Tissue microarray (TMA) results further confirmed that the expression of three genes in HCC tissues was closely related to the prognosis of patients, respectively. Conclusion: In this study, we constructed and validated a robust three-gene signature with close immune correlation in HCC, which presented a reliable performance in the prediction of HCC patients' survival.

Diagnostic accuracy and prognostic significance of osteopontin in liver cirrhosis and hepatocellular carcinoma: a Meta-analysis

OBJECTIVE

At present, there is no definite suggestion about effective tumour biomarkers for the diagnostic accuracy and prognostic significance of hepatocellular carcinoma (HCC) and liver cirrhosis (LC). The aim of our research was to determine the value of the tumour biomarker osteopontin (OPN), which is encoded by the Spp1 gene, in the diagnosis, prognosis and development of HCC and LC through meta-analysis.

METHODS

A systematic literature search was performed in the PubMed, Embase, Cochrane Library and China National Knowledge Infrastructure electronic databases up to March 2021. Studies evaluating the diagnostic and/or prognostic value of OPN in HCC and/or LC were included.

RESULTS

From the systematic search, 35 studies including 9150 participants were eligible, 25 of which provided data on the diagnostic value of OPN overexpression, while 15 studies provided data on the prognostic value. OPN had high diagnostic accuracy in both HCC and LC patients compared with healthy controls, and the diagnostic efficiency was increased by the biomarker combination OPN + AFP.

CONCLUSIONS

OPN may be adopted as a promising predictive tumour biomarker for the diagnosis and prognosis of HCC and LC and may be a potential therapeutic target.

ANTXR1 as a potential prognostic biomarker for hepatitis B virus-related hepatocellular carcinoma identified by a weighted gene correlation network analysis

BACKGROUND

With high incidence and mortality rates, hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors worldwide. Chronic hepatitis B virus (HBV) infection is a leading cause of HCC, especially for Asians and blacks. However, the molecular mechanisms underlying HBV-related HCC are unclear. This study sought to identify novel prognostic biomarkers and explore the potential pathogenesis of HBV-related HCC.

METHODS

The gene expression profiles and corresponding clinical information of HCC from The Cancer Genome Atlas Liver Hepatocellular Carcinoma data set were analyzed by a weighted gene co-expression network analysis. Correlations between the co-expression modules and clinical traits were calculated. Next, key modules associated with HBV infection were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were conducted for the genes in the key modules. The hub genes were identified based on the protein-protein interaction (PPI) network via the Cytoscape. Finally, an overall survival (OS) analysis was performed.

RESULTS

The two modules (i.e., the brown and yellow modules) most relevant to HBV infection were constructed. A functional enrichment analysis revealed that the genes in the two modules were mainly enriched in HCC-related pathways, such as the phosphatidylinositol-3-kinase and protein kinase B signaling pathway, focal adhesion, human papillomavirus infection, the Rap1 signaling pathway, and the cyclic guanosine monophosphate-dependent protein kinase (cGMP-PKG) signaling pathway. Ten hub genes [i.e., COL3A1, ANTXR1, COL14A1, THBS2, ADAMTS2, AEBP1, PRELP, EMILIN1, DCN and PODN] in the brown module, and 10 hub genes [i.e., USP34, SEC24C, ZNF770, STAG1, TSTD2, PKD1P6, CCNK, GFT2I, NT5C2 and SMG6] in the yellow module were identified. Among the hub genes, ANTXR1 (Anthrax-toxin receptor 1) was significantly correlated with HBV-related HCC patients' OS.

CONCLUSIONS

ANTXR1 represents a potential therapeutic target for HBV-related HCC. This study offers novel insights into the molecular mechanisms of HBV-induced tumorigenesis, which needs to be further validated by basic experiments and large-scale cohort studies.

Quantitative Expression of Key Cancer Markers in the AS-30D Hepatocarcinoma Model

Hepatocellular carcinoma is one of the cancers with the highest mortality rate worldwide. HCC is often diagnosed when the disease is already in an advanced stage, making the discovery and implementation of biomarkers for the disease a critical aim in cancer research. In this study, we aim to quantify the transcript levels of key signaling molecules relevant to different pathways known to participate in tumorigenesis, with special emphasis on those related to cancer hallmarks and epithelial-mesenchymal transition, using as a model the murine transplantable hepatocarcinoma AS-30D. Using qPCR to quantify the mRNA levels of genes involved in tumorigenesis, we found elevated levels for Tgfb1 and Spp1, two master regulators of EMT. A mesenchymal signature profile for AS-30D cells is also supported by the overexpression of genes encoding for molecules known to be associated to aggressiveness and metastatic phenotypes such as Foxm1, C-met, and Inppl1. This study supports the use of the AS-30D cells as an efficient and cost-effective model to study gene expression changes in HCC, especially those associated with the EMT process.

AFP-L3 for the diagnosis of early hepatocellular carcinoma: A meta-analysis

BACKGROUND

The present study aimed to systematically evaluate the diagnostic value of an isoform of alpha-fetoprotein (AFP), AFP-L3, for early hepatocellular carcinoma (HCC) by a meta-analysis.

METHODS

Diagnostic reports of AFP-L3% in early HCC were searched in the PubMed, Web of Science, Cochrane Library, and Embase databases up to December 2019. The retrieved literature was reviewed, and eligible articles were selected. Data were extracted from the eligible articles, and the risk of bias was evaluated according to the Quality Assessment of Diagnostic Accuracy Studies scale. Statistical analyses were conducted by MetaDiSc1.4 and RevMan5.3 software. The sensitivities, specificities, and diagnostic odds ratios were pooled. The summary receiver operating characteristic curve was drawn, and the area under the curve was calculated.

RESULTS

Six studies with acceptable quality were included in the meta-analysis involving 2447 patients. No threshold effect was observed among the 6 studies, but there was obvious heterogeneity. The pooled sensitivity, specificity, and positive and negative likelihood ratios of AFP-L3% for the diagnosis of early HCC were 0.34 (95% CI 0.30-0.39, P < .0001), 0.92 (95% CI 0.91-0.93, P < .0001), 4.46 (95% CI 2.94-6.77, P = .0033), and 0.71 (95% CI 0.61-0.82, P = .0004), respectively. The diagnostic odds ratio was 6.78 (95% CI 4.02-11.44, P = .0074). The the area under the curve of the summary receiver operating characteristic was 0.755 (95% CI 0.57-0.94).

CONCLUSION

AFP-L3% has high specificity but low sensitivity for diagnose early HCC, suggesting that AFP-L3% is more valuable for excluding HCC in conditions with elevated AFP than for diagnosing early HCC. In addition, a hypersensitive detection method can improve the diagnostic accuracy of AFP-L3% for early HCC.

H/ACA snoRNP Gene Family as Diagnostic and Prognostic Biomarkers for Hepatocellular Carcinoma

Background

The H/ACA small nucleolar ribonucleoprotein (snoRNP) gene family, including GAR1 ribonucleoprotein (GAR1), NHP2 ribonucleoprotein (NHP2), NOP10 ribonucleoprotein (NOP10), and dyskerin pseudouridine synthase 1 (DKC1), play important roles in ribosome biogenesis. However, the potential clinical value of the H/ACA snoRNP gene family in hepatocellular carcinoma (HCC) has not yet been reported.

Methods

Bioinformation databases were used to analyze the expression and roles of the H/ACA snoRNP gene family in HCC. Survival analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes enrichment pathway (KEGG) analyses were performed using R software. Tumor Immune Estimation Resource (TIMER) was used to analyze the correlation between the expression of the H/ACA snoRNP gene family and immune infiltration in HCC. Finally, immunohistochemistry and Western blotting were performed to verify the protein expression of the H/ACA snoRNP gene family in HCC tissues and adjacent tissues.

Results

The expression of the H/ACA snoRNP gene family was significantly increased in HCC samples compared to normal tissues, and the area under the curve (AUC) of GAR1, NHP2, NOP10, and DKC1 was 0.898, 0.962, 0.884, and 0.911, respectively. Increased expression of the H/ACA snoRNP gene family was associated with poor prognosis in HCC patients (Hazard Ratio, HR = 1.44 [1.02-2.04], 1.70 [1.20-2.40], 1.53 [1.09-2.17], and 1.43 [1.02-2.03], respectively; log-rank P = 0.036, 0.003, 0.014, 0.039, respectively). GO and KEGG analyses showed that co-expressed genes were primarily enriched in ribosome biogenesis. In addition, upregulated expression of H/ACA snoRNP gene family was related to the infiltration of various immune cells and multiple T cell exhaustion markers in HCC patients. Immunohistochemical analysis and Western blotting showed that the protein expression of H/ACA snoRNP gene family was higher in HCC tissues than in adjacent tissues of clinical samples.

Conclusion

H/ACA snoRNP gene family expression was higher in HCC tissues than in normal or adjacent tissues and was highly associated with poor prognosis of HCC patients and, therefore, has the potential to serve as diagnostic and prognostic biomarkers for HCC.

The Role of Cytokines in the Different Stages of Hepatocellular Carcinoma

Simple Summary

Non-homeostatic cytokine expression during hepatocellular carcinogenesis, together with simple and inexpensive cytokine detection techniques, has opened up its use as potential biomarkers, from cancer detection to prognosis. However, carcinogenic programs during cancer progression are not linear. Therefore, cytokines with prognostic potential in one stage may not be relevant in another. Here, we reviewed cytokines with clinical potential in different settings during hepatocellular carcinoma progression.

Abstract

Hepatocellular carcinoma (HCC) is the primary form of liver cancer and a leading cause of cancer-related death worldwide. Early detection remains the most effective strategy in HCC management. However, the spectrum of underlying liver diseases preceding HCC, its genetic complexity, and the lack of symptomatology in early stages challenge early detection. Regardless of underlying etiology, unresolved chronic inflammation is a common denominator in HCC. Hence, many inflammatory molecules, including cytokines, have been investigated as potential biomarkers to predict different stages of HCC. Soluble cytokines carry cell-signaling functions and are easy to detect in the bloodstream. However, its biomarkers’ role remains limited due to the dysregulation of immune parameters related to the primary liver process and their ability to differentiate carcinogenesis from the underlying disease. In this review, we discuss and provide insight on cytokines with clinical relevance for HCC differentiating those implicated in tumor formation, early detection, advanced disease, and response to therapy.

Current and Emerging Tools for Hepatocellular Carcinoma Surveillance

Hepatocellular carcinoma (HCC) is a leading cause of cancer‐related mortality worldwide. Early detection of HCC enables patients to avail curative therapies that can improve patient survival. Current international guidelines advocate for the enrollment of patients at high risk for HCC, like those with cirrhosis, in surveillance programs that perform ultrasound every 6 months. In recent years, many studies have further characterized the utility of established screening strategies and have introduced new promising tools for HCC surveillance. In this review, we provide an overview of the most promising new imaging modalities and biomarkers for the detection of HCC. We discuss the role of imaging tools like ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) in the early detection of HCC, and describe recent innovations which can potentially enhance their applicability, including contrast enhanced ultrasound, low‐dose CT scans, and abbreviated MRI. Next, we outline the data supporting the use of three circulating biomarkers (i.e., alpha‐fetoprotein [AFP], AFP lens culinaris agglutinin‐reactive fraction, and des‐gamma‐carboxy prothrombin) in HCC surveillance, and expand on multiple emerging liquid biopsy biomarkers, including methylated cell‐free DNA (cfDNA), cfDNA mutations, extracellular vesicles, and circulating tumor cells. These promising new imaging modalities and biomarkers have the potential to improve early detection, and thus improve survival, in patients with HCC.