Metabolomic Profiles for HBV Related Hepatocellular Carcinoma Including Alpha-Fetoproteins Positive and Negative Subtypes

Metabolomics for searching validated biomarkers in cancer studies: a decade in review

INTRODUCTION

In the dynamic landscape of modern healthcare, the ability to anticipate and diagnose diseases, particularly in cases where early treatment significantly impacts outcomes, is paramount. Cancer, a complex and heterogeneous disease, underscores the critical importance of early diagnosis for patient survival. The integration of metabolomics information has emerged as a crucial tool, complementing the genotype-phenotype landscape and providing insights into active metabolic mechanisms and disease-induced dysregulated pathways.

AREAS COVERED

This review explores a decade of developments in the search for biomarkers validated within the realm of cancer studies. By critically assessing a diverse array of research articles, clinical trials, and studies, this review aims to present an overview of the methodologies employed and the progress achieved in identifying and validating biomarkers in metabolomics results for various cancer types.

EXPERT OPINION

Through an exploration of more than 800 studies, this review has allowed to establish a general idea about state-of-art in the search of biomarkers in metabolomics studies involving cancer which include certain level of results validation. The potential for metabolites as diagnostic markers to reach the clinic and make a real difference in patient health is substantial, but challenges remain to be explored.

The role of alpha-fetoprotein in the tumor microenvironment of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a prevalent malignant cancer worldwide, characterized by high morbidity and mortality rates. Alpha-fetoprotein (AFP) is a glycoprotein synthesized by the liver and yolk sac during fetal development. However, the serum levels of AFP exhibit a significant correlation with the onset and progression of HCC in adults. Extensive research has demonstrated that the tumor microenvironment (TME) plays a crucial role in the malignant transformation of HCC, and AFP is a key factor in the TME, promoting HCC development. The objective of this review was to analyze the existing knowledge regarding the role of AFP in the TME. Specifically, this review focused on the effect of AFP on various cells in the TME, tumor immune evasion, and clinical application of AFP in the diagnosis and treatment of HCC. These findings offer valuable insights into the clinical treatment of HCC.

Bioactive signalling lipids as drivers of chronic liver diseases

Lipids are important in multiple cellular functions, with most having structural or energy storage roles. However, a small fraction of lipids exert bioactive roles through binding to G protein-coupled receptors and induce a plethora of processes including cell proliferation, differentiation, growth, migration, apoptosis, senescence and survival. Bioactive signalling lipids are potent modulators of metabolism and energy homeostasis, inflammation, tissue repair and malignant transformation. All these events are involved in the initiation and progression of chronic liver diseases. In this review, we focus specifically on the roles of bioactive lipids derived from phospholipids (lyso-phospholipids) and poly-unsaturated fatty acids (eicosanoids, pro-resolving lipid mediators and endocannabinoids) in prevalent chronic liver diseases (alcohol-associated liver disease, non-alcoholic fatty liver disease, viral hepatitis and hepatocellular carcinoma). We discuss the balance between pathogenic and beneficial bioactive lipids as well as potential therapeutic targets related to the agonism or antagonism of their receptors.

Molecular and Metabolic Phenotyping of Hepatocellular Carcinoma for Biomarker Discovery: A Meta-Analysis

Identifying and translating hepatocellular carcinoma (HCC) biomarkers from bench to bedside using mass spectrometry-based metabolomics and lipidomics is hampered by inconsistent findings. Here, we investigated HCC at systemic and metabolism-centric multiomics levels by conducting a meta-analysis of quantitative evidence from 68 cohorts. Blood transcript biomarkers linked to the HCC metabolic phenotype were externally validated and prioritized. In the studies under investigation, about 600 metabolites were reported as putative HCC-associated biomarkers; 39, 20, and 10 metabolites and 52, 12, and 12 lipids were reported in three or more studies in HCC vs. Control, HCC vs. liver cirrhosis (LC), and LC vs. Control groups, respectively. Amino acids, fatty acids (increased 18:1), bile acids, and lysophosphatidylcholine were the most frequently reported biomarkers in HCC. BAX and RAC1 showed a good correlation and were associated with poor prognosis. Our study proposes robust HCC biomarkers across diverse cohorts using a data-driven knowledge-based approach that is versatile and affordable for studying other diseases.

Carbon-based biosensors from graphene family to carbon dots: A viewpoint in cancer detection

According to the latest report by International Agency for Research on Cancer, 19.3 million new cancer cases and 10 million cancer deaths were globally reported in 2020. Early diagnosis can reduce these numbers significantly, and biosensors have appeared to be a solution to this problem as, unlike the traditional methods, they have low cost, rapid process, and do not need experts present on site for use. These devices have been incorporated to detect many cancer biomarkers and measure cancer drug delivery. To design these biosensors, a researcher must know about their different types, properties of nanomaterials, and cancer biomarkers. Among all types of biosensors, electrochemical and optical biosensors are the most sensitive and promising sensors for detecting complicated diseases like cancer. The carbon-based nanomaterial family has attracted lots of attention due to their low cost, easy preparation, biocompatibility, and significant electrochemical and optical properties. In this review, we have discussed the application of graphene and its derivatives, carbon nanotubes (CNTs), carbon dots (CDs), and fullerene (C60), for designing different electrochemical and optical cancer-detecting biosensors. Furthermore, the application of these carbon-based biosensors for detecting seven widely studied cancer biomarkers (HER2, CEA, CA125, VEGF, PSA, Alpha-fetoprotein, and miRNA21) is reviewed. Finally, various fabricated carbon-based biosensors for detecting cancer biomarkers and anticancer drugs are comprehensively summarized as well.

Lipid alterations in chronic liver disease and liver cancer

Lipids are a complex and diverse group of molecules with crucial roles in many physiological processes, as well as in the onset, progression, and maintenance of cancers. Fatty acids and cholesterol are the building blocks of lipids, orchestrating these crucial metabolic processes. In the liver, lipid alterations are prevalent as a cause and consequence of chronic hepatitis B and C virus infections, alcoholic hepatitis, and non-alcoholic fatty liver disease and steatohepatitis. Recent developments in lipidomics have also revealed that dynamic changes in triacylglycerols, phospholipids, sphingolipids, ceramides, fatty acids, and cholesterol are involved in the development and progression of primary liver cancer. Accordingly, the transcriptional landscape of lipid metabolism suggests a carcinogenic role of increasing fatty acids and sterol synthesis. However, limited mechanistic insights into the complex nature of the hepatic lipidome have so far hindered the development of effective therapies.

Changing Metabolic Patterns along the Colorectal Adenoma–Carcinoma Sequence

Colorectal cancer (CRC) is a major public health burden and one of the leading causes of cancer-related deaths worldwide. Screening programs facilitate early diagnosis and can help to reduce poor outcomes. Serum metabolomics can extract vital molecular information that may increase the sensitivity and specificity of colonoscopy in combination with histopathological examination. The present study identifies serum metabolite patterns of treatment-naïve patients, diagnosed with either advanced adenoma (AA) or CRC in colonoscopy screenings, in the framework of the SAKKOPI (Salzburg Colon Cancer Prevention Initiative) program. We used a targeted flow injection analysis and liquid chromatography-tandem mass spectrometry metabolomics approach (FIA- and LC-MS/MS) to characterise the serum metabolomes of an initial screening cohort and two validation cohorts (in total 66 CRC, 76 AA and 93 controls). The lipidome was significantly perturbed, with a proportion of lipid species being downregulated in CRC patients, as compared to AA and controls. The predominant alterations observed were in the levels of lyso-lipids, glycerophosphocholines and acylcarnitines, but additionally, variations in the quantity of hydroxylated sphingolipids could be detected. Changed amino acid metabolism was restricted mainly to metabolites of the arginine/dimethylarginine/NO synthase pathway. The identified metabolic divergences observed in CRC set the foundation for mechanistic studies to characterise biochemical pathways that become deregulated during progression through the adenoma to carcinoma sequence and highlight the key importance of lipid metabolites. Biomarkers related to these pathways could improve the sensitivity and specificity of diagnosis, as well as the monitoring of therapies.

The Landscape Of Alpha Fetoprotein In Hepatocellular Carcinoma: Where Are We?

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and has been acknowledged as a leading cause of death among cirrhosis patients. Difficulties in early diagnosis and heterogeneity are obstacles to effective treatment, especially for advanced HCC. Liver transplantation (LT) is considered the best therapy for HCC. Although many biomarkers are being proposed, alpha-fetoprotein (AFP), which was identified over 60 years ago, remains the most utilized. Recently, much hope has been placed in the immunogenicity of AFP to develop novel therapies, such as AFP vaccines and AFP-specific adoptive T-cell transfer (ACT). This review summarizes the performance of AFP as a biomarker for HCC diagnosis and prognosis, as well as its correlation with molecular classes. In addition, the role of AFP in LT is also described. Finally, we highlight the mechanism and application prospects of two immune therapies (AFP vaccine and ACT) for HCC. In general, our review points out the prevalence of AFP in HCC, accompanied by some controversies and novel directions for future research.

Alpha-Fetoprotein Ratio Predicts Alpha-Fetoprotein Positive Hepatocellular Cancer Patient Prognosis after Hepatectomy

BACKGROUND

This study was conducted to investigate the effect of alpha-fetoprotein (AFP) ratio on the prognosis of AFP-positive hepatocellular carcinoma (HCC) patients after hepatectomy.

METHODS

We retrospectively included 879 HCC patients with AFP-positive who underwent hepatectomy from February 2012 to October 2017 and randomly divided into training cohort and validation cohort. AFP ratio was equal to the AFP level within one week before hepatectomy to AFP level within 20-40 days after surgery. The end point of follow-up was disease-free survival (DFS) and overall survival (OS).

RESULTS

AFP ratio was not associated with clinical characteristics in training cohort and validation cohort. According to the X-tile software, the optimum cut-off point was 17.8 for AFP ratio. Significant differences between AFP ratio high and AFP ratio low were observed in DFS and OS in both cohort (p < 0.05). Kaplan-Meier curves and receiver-operating curves were showed that AFP ratio was better than AFP level preoperation in predicting the prognosis of AFP-positive HCC patients after hepatectomy. The multivariate analysis demonstrated that AFP ratio was a significant independent risk factor for both OS and DFS in HCC patients with AFP-positive.

CONCLUSIONS

AFP ratio might be a prognosis predictor for HCC patients with AFP-positive after hepatectomy.

Combination of serum paraoxonase/arylesterase 1 and antithrombin-III is a promising non-invasion biomarker for discrimination of AFP-negative HCC versus liver cirrhosis patients

OBJECTIVE

α-fetoprotein is often used in the diagnosis of hepatocellular carcinoma (HCC). However, there are currently less efficient and highly specific biomarkers to distinguish AFP-negative HCC from liver cirrhosis (LC) patients.

PATIENTS AND METHODS

We retrospectively analyzed the data of patients who were treated in our hospitals. iTRAQ coupled with mass spectrometry was used to identify candidate serum proteins in a discovery set (n = 36) including AFP-negative HCC and LC patients. After Western blot detection, potential serum biomarkers were confirmed using ELISA in a validation set (n = 90). The diagnostic performance of the selected proteins was assessed using receiver operating characteristic (ROC).

RESULTS

PON1 and ATIII were selected as target proteins and were significantly higher in LC than those in AFP-negative HCC patients as validated by Western blot and ELISA, which was consistent with the result of iTRAQ. The AUC was 0.848 as PON1 and ATIII were combined (sensitivity: 80.0%; specificity: 73.3%), and performed much better than that of a single biomarker.

CONCLUSION

These findings suggest that PON1 and ATIII have the potential to serve as effective biomarkers for distinguishing AFP-negative HCC from cirrhosis.

N-glycan fingerprint predicts alpha-fetoprotein negative hepatocellular carcinoma: A large-scale multicenter study

Alpha-fetoprotein (AFP)-negative hepatocellular carcinoma (ANHCC) patients account for more than 30% of the whole entity of HCC patients and are easily misdiagnosed. This three-phase study was designed to find and validate new ANHCC N-glycan markers which identified from The Cancer Genome Atlas (TCGA) database and noninvasive detection. Differentially expressed genes (DEGs) of N-glycan biosynthesis and degradation related genes were screened from TCGA database. Serum N-glycan structure abundances were analyzed using N-glycan fingerprint (NGFP) technology. Totally 1340 participants including ANHCC, chronic liver diseases and healthy controls were enrolled after propensity score matching (PSM). The Lasso algorithm was used to select the most significant N-glycan structures abundances. Three machine learning models [random forest (RF), support vector machine (SVM) and logistic regression (LR)] were used to construct the diagnostic algorithms. All 13N-glycan structure abundances analyzed by NGFP demonstrated significant and was enrolled by Lasso. Among the three machine learning models, LR algorithm demonstrated the best diagnostic performance for identifying ANHCC in training cohort (LR: AUC: 0.842, 95%CI: 0.784-0.899; RF: AUC: 0.825, 95%CI: 0.766-0.885; SVM: AUC: 0.610, 95%CI: 0.527-0.684). This LR algorithm achieved a high diagnostic performance again in the independent validation (AUC: 0.860, 95%CI: 0.824-0.897). Furthermore, the LR algorithm could stratify ANHCC into two distinct subgroups with high or low risks of overall survival and recurrence in follow-up validation. In conclusion, the biomarker panel consisting of 13N-glycan structures abundances using the best-performing algorithm (LR) was defined and indicative as an effective tool for HCC prediction and prognosis estimate in AFP negative subjects.

Identification of Plasma hsa_circ_0005397 and Combined With Serum AFP, AFP-L3 as Potential Biomarkers for Hepatocellular Carcinoma

Background: Mounting evidence has demonstrated that circular RNA (circRNA) plays crucial roles in the occurrence and development of hepatocellular carcinoma (HCC). However, the expression pattern and clinical application value of plasma circRNA in HCC are still largely unknown. Herein, we explored the role of plasma hsa_circ_0005397 in diagnosis and prognosis of HCC.

Methods: The expression level of plasma hsa_circ_0005397 was measured by quantitative real-time polymerase chain reaction (qRT-PCR). The identification and origin of plasma hsa_circ_0005397 were confirmed by RNase R assay, Sanger sequencing and HCC cell culture. In addition, its diagnostic value was assessed by receiver operating characteristic (ROC) curve and prognostic value was evaluated by dynamics monitoring and Kaplan–Meier curve analyses in HCC patients.

Results: The expression of plasma hsa_circ_0005397 was higher in patients with HCC than that in patients with benign liver diseases and healthy controls (both p < 0.05). Moreover, it was closely correlated with tumor size (p = 0.020) and TNM stage (p = 0.006) of HCC patients. The area under the ROC curve of plasma hsa_circ_0005397 was 0.737 and 95% confidence interval was 0.671–0.795. Furthermore, the combination of plasma hsa_cic_0005397, serum AFP and AFP-L3 could improve the diagnostic sensitivity of HCC. Additionally, dynamic monitoring plasma hsa_cic_0005397 might help us predict recurrence or metastasis in HCC patients after surgical resection. Besides, the increased plasma hsa_cic_0005397 was closely correlated with shorter overall survival of HCC patients (p = 0.007).

Conclusion: Plasma has_circ_0005397 represents a novel noninvasive biomarker for HCC. Moreover, the combination of plasma hsa_cic_0005397, serum AFP and AFP-L3 might improve the diagnostic value for HCC.

New Blood Biomarkers for the Diagnosis of AFP-Negative Hepatocellular Carcinoma

An early diagnosis of hepatocellular carcinoma (HCC) followed by effective treatment is currently critical for improving the prognosis and reducing the associated economic burden. Alpha-fetoprotein (AFP) is the most widely used biomarker for HCC diagnosis. Based on elevated serum AFP levels as well as typical imaging features, AFP-positive HCC (APHC) can be easily diagnosed, but AFP-negative HCC (ANHC) is not easily detected due to lack of ideal biomarkers and thus mainly reliance on imaging. Imaging for the diagnosis of ANHC is probably insufficient in sensitivity and/or specificity because most ANHC tumors are small and early-stage HCC, and it is involved in sophisticated techniques and high costs. Moreover, ANHC accounts for nearly half of HCC and exhibits a better prognosis compared with APHC. Therefore, the diagnosis of ANHC in clinical practice has been a critical issue for the early treatment and prognosis improvement of HCC. In recent years, tremendous efforts have been made to discover new biomarkers complementary to AFP for HCC diagnosis. In this review, we systematically review and discuss the recent advances of blood biomarkers for HCC diagnosis, including DNA biomarkers, RNA biomarkers, protein biomarkers, and conventional laboratory metrics, focusing on their diagnostic evaluation alone and in combination, in particular on their diagnostic performance for ANHC.