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

Evaluating the diagnostic accuracy of heat shock proteins and their combination with Alpha-Fetoprotein in the detection of hepatocellular carcinoma: a meta-analysis

BACKGROUND

A growing body of research suggests that heat shock proteins (HSPs) may serve as diagnostic biomarkers for hepatocellular carcinoma (HCC), but their results are still controversial. This meta-analysis endeavors to evaluate the diagnostic accuracy of HSPs both independently and in conjunction with alpha-fetoprotein (AFP) as novel biomarkers for HCC detection.

METHODS

Pooled statistical indices, including sensitivity, specificity, diagnostic odds ratio (DOR), positive likelihood ratio (PLR), and negative likelihood ratio (NLR) with 95% confidence intervals (CI), were computed to assess the diagnostic accuracy of HSPs, AFP, and their combinations. Additionally, the area under the summary receiver operating characteristic (SROC) curve (AUC) was determined.

RESULTS

A total of 2013 HCC patients and 1031 control subjects from nine studies were included in this meta-analysis. The summary estimates for HSPs and AFP are as follows: sensitivity of 0.78 (95% CI: 0.69-0.85) compared to 0.73 (95% CI: 0.65-0.80); specificity of 0.89 (95% CI: 0.81-0.95) compared to 0.86 (95% CI: 0.77-0.91); PLR of 7.4 (95% CI: 3.7-14.9) compared to 5.1 (95% CI: 3.3-8.1); NLR of 0.24 (95% CI: 0.16-0.37) compared to 0.31 (95% CI: 0.24-0.41); DOR of 30.19 (95% CI: 10.68-85.37) compared to 16.34 (95% CI: 9.69-27.56); and AUC of 0.90 (95% CI: 0.87-0.92) compared to 0.85 (95% CI: 0.82-0.88). The pooled sensitivity, specificity, PLR, NLR, DOR and AUC were 0.90 (95% CI: 0.82-0.95), 0.94 (95% CI: 0.82-0.98), 14.5 (95% CI: 4.6-45.4), 0.11 (95% CI: 0.06-0.20), 133.34 (95% CI: 29.65-599.61), and 0.96 (95% CI: 0.94-0.98) for the combination of HSPs and AFP.

CONCLUSION

Our analysis suggests that HSPs have potential as a biomarker for clinical use in the diagnosis of HCC, and the concurrent utilization of HSPs and AFP shows notable diagnostic effectiveness for HCC.

Biomarker in Hepatocellular Carcinoma

Liver cancer is one of the most prevalent types of cancer and a major contributor to the socioeconomic burden worldwide. The pathogenesis of hepatocellular carcinoma (HCC) is contributed by various etiological factors like virus infection, excessive alcohol consumption, exposure to toxins, or metabolic disorders. Majority of patients are diagnosed with late-stage HCC, which restricts its management to only palliative care. HCC, if diagnosed early, increases the survival and quality of life. Currently available biomarker (alpha-fetoproteins) have several limitations, that impede the early diagnosis and staging of cancer. This warrants the continous search in pursuit of a novel biomarker. Several research works in diverse areas have contributed to the identification of various novel biomarkers that have shown multifaceted application in early disease diagnosis, which further aid in targeted and effective therapy that can prevent cancer progression. This improves the overall health status of the patient along with significant reduction in caretaker's burden. With the aid of novel technologies, several biomarkers have been investigated and validated in mutliple preliminary research works. Therefore in this review, we have outlined various novel biomarkers that showed promising outcomes in their trials and we have highlighted the developing areas that act as game changers in cancer diagnosis and management.

Evaluating the impact of PD-1 inhibitor treatment on key health outcomes for cancer patients in China

BACKGROUND

There is a lack of studies examining the influence of programmed cell death protein 1 (PD-1) inhibitors on the health outcomes of cancer patients in China.

AIM

This study aimed to evaluate prospective health outcomes associated with introducing PD-1 inhibitor treatment in China over five years.

METHOD

We constructed a partitioned survival model to assess disparities in health outcomes over a 5-year time frame between two scenarios: one involving the availability of PD-1 inhibitor class with standard of care and the other involving standard of care alone. The impact on various health outcomes were assessed, including life years (LYs) gained, quality-adjusted life years (QALYs) gained, progression-free survival (PFS) years gained, the reduction in the number of grade 3-5 adverse events (AEs), and the improvement in objective remission rates (ORR). A sensitivity analysis was conducted to assess the robustness and reliability of the model.

RESULTS

From 2023 to 2027, the incorporation of PD-1 inhibitor class treatments was anticipated to yield substantial improvements in health outcomes, with an estimated increase of 1,336,332 LYs (+ 24.7%), 1,065,359 QALYs (+ 30.3%), and 1,177,564 PFS years (+ 57.4%) compared to standard of care alone. Simultaneously, the number of grade 3-5 AEs decreased by 334,976 (- 13.0%), and the ORR saw a 19.1% increase (+ 105.6%) relative to standard of care treatment alone.

CONCLUSION

This study provides a analysis of the potential beneficial effects on health outcomes in the Chinese population after introducing PD-1 inhibitor class treatment. The findings suggest the PD-1 inhibitor class will significantly improve patient survival.

Identification of ASF1B as a prognostic marker for liver cancer by meta-analysis and its immune value revealed by a comprehensive pan-cancer analysis of 33 human cancers

Introduction

As one of the most common malignant tumours, liver cancer is difficult to detect in the early stage, with strong metastasis and poor prognosis. Anti-silencing function protein 1 was originally discovered in yeast as a histone H3-H4 chaperone, and studies have shown that ASF1B may be a target for inhibiting the growth of hepatocellular carcinoma cells.

Aim

To evaluate the diagnostic and prognostic significance of ASF1B expression in human LIHC on the basis of TCGA data.

Material and methods

A meta-analysis revealed that high ASF1B expression was strongly associated with better overall survival. A comprehensive pan-cancer analysis of 33 human cancers revealed the immunotherapeutic value of ASF1B.

Results

In this study, we observed a significant upregulation of ASF1B expression in LIHC samples compared to non-cancer samples. Clinical analysis showed that high expression of ASF1B was associated with age, tumour status, and clinical stage. Survival analysis showed that patients with high ASF1B expression had worse overall survival and progression-free survival than patients with low ASF1B expression. The AUCs of the 1-year, 3-year, and 5-year survival-related ROC curves were 0.672, 0.590, and 0.591, respectively.

Conclusions

Our study shows that ASF1B may provide new ideas for the diagnosis and prognosis of liver cancer patients, as well as providing a new direction for the application of ASF1B in tumour immunotherapy.

Immunotherapy in hepatocellular carcinoma: how will it reshape treatment sequencing?

The treatment landscape of advanced hepatocellular carcinoma (HCC) has broadened with immune checkpoint inhibitors (ICIs) setting a novel standard of care. With the increased number of therapies either in first or in further line, disentangling the possible treatment sequences has become much more complex. Yet, all the second-line therapies have been evaluated after sorafenib. After ICIs, offering multikinase inhibitors is a widespread approach, either shifting forward sorafenib or lenvatinib, or choosing among regorafenib or cabozantinib, already approved in the refractory setting. Under specific circumstances, ICIs could be maintained beyond disease progression in patients with proven clinical benefit, as supported by some data emerging from phase III clinical trials with immunotherapy in HCC. Rechallenge with ICIs is an additional attractive alternative, although requiring careful and individual evaluation as efficacy and safety of such a strategy have not been yet clarified. Still, a considerable number of patients displays primary resistance to ICIs and might benefit from antiangiogenics either alone or in addition to ICIs instead. Hopefully, the ongoing clinical trials will enlighten regarding the most effective treatment pathways. The identification of predictive correlates of response to immunotherapy will help treatment allocation at each stage, thus representing an urgent matter to address in HCC research. With programmed death ligand 1 expression, tumor mutational burden, and microsatellite status being inadequate biomarkers in HCC, patient characteristics, drug safety profile, and regulatory approval remain key elements to acknowledge in routine practice. Despite the tissue remaining a preferred source, biomarkers discovery could take advantage of liquid biopsy to overcome the matter of tissue availability and track tumor changes. Lastly, tumor genetic phenotypes, tumor microenvironment features, gut microbiome, and markers of immune response and systemic inflammation are all potential emergent predictors of response to ICIs, pending validation in the clinical setting.

The upregulation of CLGN in hepatocellular carcinoma is potentially regulated by hsa-miR-194-3p and associated with patient progression

Background

Patients with hepatocellular carcinoma (HCC) have poor prognosis, especially in advanced stages. Targeted therapy is the main treatment for advanced HCC patients, but the optimal targets for HCC remain poorly understood. The main purpose of this study was to identify potential novel prognostic markers and therapeutic targets.

Methods

Firstly, differentially expressed genes (DEGs) in HCC were identified from the Gene Expression Omnibus (GEO) database. The expression, significance in prognosis, and potential mechanisms of DEGs were analyzed using GEPIA, TIMER, HPA, Kaplan Meier Plotter, CBioPortal, miRWalk, TargetScan, and ENCORI databases. Immunohistochemical staining was used to determine the protein expression levels of potential candidate genes.

Results

The mRNA levels of MND1, STXBP6, and CLGN were significantly increased in HCC (p< 0.01). HCC patients with elevated CLGN mRNA levels had poorer overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and disease-specific survival (DSS) (p < 0.05). Higher MND1 mRNA levels significantly correlated with poorer DFS in HCC patients (p< 0.05). However, there was no significant correlation between STXBP6 expression and prognosis of HCC (p> 0.05). Further analysis revealed that patients with elevated CLGN mRNA expression in advanced pathology stages had poorer prognosis (p< 0.01). In addition, CLGN protein levels were elevated in HCC compared to their levels in normal tissues. The mRNA levels of CLGN had no significant correlation with the abundance of six common tumor infiltrating lymphocytes in HCC (COR < 0.5). Moreover, the mutation rate of CLGN was less than 1% in HCC patients (10/1089). Finally, the expression level of hsa-miR-194-3p in HCC was significantly lower than that in normal tissues (p < 0.05), and prognosis of HCC with low expression of hsa-miR-194 was poor (p < 0.05).

Conclusion

The upregulation of CLGN in HCC is significantly associated with poor patient prognosis, especially in the advanced stages, and may be regulated by hsa-miR-194-3p. These findings suggest that CLGN may be closely related to the progression of HCC, and is a potential therapeutic target and prognostic indicator for patients with advanced HCC.

Metabolomics in hepatocellular carcinoma: From biomarker discovery to precision medicine

Hepatocellular carcinoma (HCC) remains a global health burden, and is mostly diagnosed at late and advanced stages. Currently, limited and insensitive diagnostic modalities continue to be the bottleneck of effective and tailored therapy for HCC patients. Moreover, the complex reprogramming of metabolic patterns during HCC initiation and progression has been obstructing the precision medicine in clinical practice. As a noninvasive and global screening approach, metabolomics serves as a powerful tool to dynamically monitor metabolic patterns and identify promising metabolite biomarkers, therefore holds a great potential for the development of tailored therapy for HCC patients. In this review, we summarize the recent advances in HCC metabolomics studies, including metabolic alterations associated with HCC progression, as well as novel metabolite biomarkers for HCC diagnosis, monitor, and prognostic evaluation. Moreover, we highlight the application of multi-omics strategies containing metabolomics in biomarker discovery for HCC. Notably, we also discuss the opportunities and challenges of metabolomics in nowadays HCC precision medicine. As technologies improving and metabolite biomarkers discovering, metabolomics has made a major step toward more timely and effective precision medicine for HCC patients.

In Silico Analysis of MicroRNA Expression Data in Liver Cancer

Abnormal miRNA expression has been evidenced to be directly linked to HCC initiation and progression. This study was designed to detect possible prognostic, diagnostic, and/or therapeutic miRNAs for HCC using computational analysis of miRNAs expression. Methods: miRNA expression datasets meta-analysis was performed using the YM500v2 server to compare miRNA expression in normal and cancerous liver tissues. The most significant differentially regulated miRNAs in our study undergone target gene analysis using the mirWalk tool to obtain their validated and predicted targets. The combinatorial target prediction tool; miRror Suite was used to obtain the commonly regulated target genes. Functional enrichment analysis was performed on the resulting targets using the DAVID tool. A network was constructed based on interactions among microRNAs, their targets, and transcription factors. Hub nodes and gatekeepers were identified using network topological analysis. Further, we performed patient data survival analysis based on low and high expression of identified hubs and gatekeeper nodes, patients were stratified into low and high survival probability groups. Results: Using the meta-analysis option in the YM500v2 server, 34 miRNAs were found to be significantly differentially regulated (P-value ⩽ .05); 5 miRNAs were down-regulated while 29 were up-regulated. The validated and predicted target genes for each miRNA, as well as the combinatorially predicted targets, were obtained. DAVID enrichment analysis resulted in several important cellular functions that are directly related to the main cancer hallmarks. Among these functions are focal adhesion, cell cycle, PI3K-Akt signaling, insulin signaling, Ras and MAPK signaling pathways. Several hub genes and gatekeepers were found that could serve as potential drug targets for hepatocellular carcinoma. POU2F1 and PPARA showed a significant difference between low and high survival probabilities (P-value ⩽ .05) in HCC patients. Our study sheds light on important biomarker miRNAs for hepatocellular carcinoma along with their target genes and their regulated functions.

Neutrophil-to-Lymphocyte Ratio Can Distinguish Patients with Liver Cirrhosis from Healthy People but Cannot Distinguish Patients with Cirrhotic Hepatocellular Carcinoma from Patients with Liver Cirrhosis

PURPOSE

Identifying cirrhotic hepatocellular carcinoma (HCC) during liver cirrhosis (LC) stage is pivotal for improving the clinical outcomes of cirrhotic HCC patients. Inflammation-driven markers play a crucial role in tumorigenesis and tumor progression. Neutrophil-to-lymphocyte ratio (NLR) is an inflammatory response marker. This study aimed to evaluate the ability of NLR to distinguish cirrhotic HCC from LC.

METHODS

Data of healthy control (HC) people, LC patients, cirrhotic HCC patients, and non-cirrhotic HCC patients were retrospectively analyzed. Mann-Whitney U test and Chi-squared test were used to compare demographic and clinical parameters in different groups. Spearman correlation analysis was used to assess correlations. Receiver operating characteristic (ROC) curves were performed to determine diagnostic accuracy.

RESULTS

A total of 419 participants were enrolled in this study, including 152 HC people, 131 LC patients, 96 cirrhotic HCC patients, and 40 non-cirrhotic HCC patients. Level of NLR was elevated significantly in LC compared with HC (P < 0.001). No significant differences were found for NLR between LC and cirrhotic HCC (P = 0.083), as well as between cirrhotic HCC and non-cirrhotic HCC (P = 0.729). NLR was positively correlated with platelet-to-lymphocyte ratio (r = 0.33, P < 0.001). The area under the ROC curve (AUC) value for NLR to distinguish LC from HC was 0.759 (P < 0.001), and AUC value to distinguish cirrhotic HCC from LC was 0.567 (P = 0.083), and AUC value to distinguish non-cirrhotic HCC from cirrhotic HCC was 0.519 (0.415-0.623) (P = 0.729).

CONCLUSION

NLR can distinguish LC from HC but cannot not distinguish cirrhotic HCC from LC.

Mouse Models of Hepatocellular Carcinoma: Classification, Advancement, and Application

Hepatocellular carcinoma (HCC) is the subtype of liver cancer with the highest incidence, which is a heterogeneous malignancy with increasing incidence rate and high mortality. For ethical reasons, it is essential to validate medical clinical trials for HCC in animal models before further consideration on humans. Therefore, appropriate models for the study of the pathogenesis of the disease and related treatment methods are necessary. For tumor research, mouse models are the most commonly used and effective in vivo model, which is closer to the real-life environment, and the repeated experiments performed on it are closer to the real situation. Several mouse models of HCC have been developed with different mouse strains, cell lines, tumor sites, and tumor formation methods. In this review, we mainly introduce some mouse HCC models, including induced model, gene-edited model, HCC transplantation model, and other mouse HCC models, and discuss how to choose the appropriate model according to the purpose of the experiments.

SGK1 in Cancer: Biomarker and Drug Target

Serum- and glucocorticoid-regulated kinases (SGKs) are members of the AGC family of serine/threonine kinases, consisting of three isoforms: SGK1, SGK2, and SGK3. SGK1 was initially cloned as a gene transcriptionally stimulated by serum and glucocorticoids in rat mammary tumor cells. It is upregulated in some cancers and downregulated in others. SGK1 increases tumor cell survival, adhesiveness, invasiveness, motility, and epithelial to mesenchymal transition. It stimulates tumor growth by mechanisms such as activation of K+ channels and Ca2+ channels, Na+/H+ exchanger, amino acid and glucose transporters, downregulation of Foxo3a and p53, and upregulation of β-catenin and NFκB. This chapter focuses on major aspects of SGK1 involvement in cancer, its use as biomarker as well as potential therapeutic target.

Autoantibody Against Ferritin Light Chain is a Serum Biomarker for the Detection of Liver Cirrhosis but Not Liver Cancer

Purpose

Ferritin is a protein that plays an important role in iron metabolism, it consists of two subunits: heavy chain (FTH) and light chain (FTL). Elevated expression of FTL is observed in multiple malignancies. Recent studies have found that the frequency of circulating autoantibody against FTL (anti-FTL) increased significantly in hepatocellular carcinoma (HCC). The aim of this study is to verify circulating anti-FTL as a biomarker for the early detection of HCC.

Patients and Methods

A total of 1565 participants were enrolled and assigned to two independent validation cohorts, including 393 HCC patients, 379 liver cirrhosis (LC) patients, 400 chronic hepatitis (CH) patients, and 393 healthy subjects. The concentration of serum anti-FTL was measured by indirect Enzyme-Linked Immunosorbent Assay (ELISA). Kruskal–Wallis test was used to compare anti-FTL concentrations between HCC group and three control groups. Percentile 95 of anti-FTL absorbance value of healthy group was selected as the cut-off value to calculate the positive rate in each group. The area under receiver operating characteristic curve (AUC) was used to quantitatively describe its diagnostic value.

Results

The median concentration of anti-FTL in HCC patients was higher than that in CH patients and healthy subjects, but there was no difference between HCC patients and LC patients. Further analysis showed that there was no difference between early stage LC, advanced stage LC, Child-Pugh A HCC, Child-Pugh B HCC and Child-Pugh C HCC. The positive rate of anti-FTL was 12.2% (48/393) in HCC, 13.5% (51/379) in LC, 6.3% (25/400) in CH and 5.1% (20/393) in healthy subjects, respectively. The AUC of anti-FTL to distinguish LC from CH or healthy subjects were 0.654 (95% CI: 0.615–0.692) and 0.642 (95% CI: 0.602–0.681), respectively.

Conclusion

Anti-FTL is not a biomarker for the early diagnosis of HCC due to specificity deficiency, but may be helpful for the early detection of LC.