Investigation of Potential Molecular Biomarkers for Diagnosis and Prognosis of AFP-Negative HCC

Overexpression of ZFP69B promotes hepatocellular carcinoma growth by upregulating the expression of TLX1 and TRAPPC9

BACKGROUND

T-cell leukemia homeobox protein 1 (TLX1) has been revealed as a hub transcription factor in leukemia, while its function in hepatocellular carcinoma (HCC) has not been well described. Here, we investigated the regulation and function of TLX1 in HCC.

METHODS

TLX1 and its possible upstream and downstream molecules in HCC were identified using bioinformatics tools, which were then verified by RT-qPCR assay. CCK-8, wound healing, and Transwell invasion assays were performed to detect the effects of TLX1 knockdown on HCC cells. The interactions between TLX1 and trafficking protein particle complex subunit 9 (TRAPPC9) or Zinc finger protein 69 homolog B (ZFP69B) were further probed by ChIP and luciferase reporter assays. Rescue experiments were finally conducted in vitro and in vivo.

RESULTS

TLX1 was highly expressed in HCC cells, and the knockdown of TLX1 led to reduced malignant biological behavior of HCC cells. TLX1 bound to the promoter region of TRAPPC9, thereby promoting TRAPPC9 expression. Overexpression of TRAPPC9 attenuated the effect of TLX1 reduction on suppressing malignant behavior of HCC cells. ZFP69B was also highly expressed in HCC cells and bound to the promoter region of TLX1 to induce TLX1 expression. Knockdown of ZFP69B inhibited the viability and mobility of HCC cells in vitro and tumor growth in vivo, and overexpression of TLX1 rescued this inhibition.

CONCLUSION

These findings suggest that ZFP69B promotes the proliferation of HCC cells by directly upregulating the expression of TLX1 and the ensuing TRAPPC9.

Establishment of a multi-line immunochromatography based on magnetic nanoparticles for simultaneous screening of multiple biomarkers

Biomarkers screening is a benefit approach for early diagnosis of major diseases. In this study, magnetic nanoparticles (MNPs) have been utilized as labels to establish a multi-line immunochromatography (MNP-MLIC) for simultaneous detection of carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA 19-9), and alpha-fetoprotein (AFP) in a single serum sample. Under the optimal parameters, the three biomarkers can be rapidly and simultaneously qualitative screening within 15 min by naked eye. As for quantitative detection, the MNP-MLIC test strips were precisely positioned and captured by a smartphone, and signals on the test and control lines were extracted by ImageJ software. The signal ratio of test and control lines has been calculated and used to plot quantitative standard curves with the logarithmic concentration, of which the correlation coefficients are more than 0.99, and the limit of detection for CEA, CA 19-9, and AFP were 0.60 ng/mL, 1.21 U/mL, and 0.93 ng/mL, respectively. The recoveries of blank serum were 75.0 ~ 112.5% with the relative standard deviation ranging from 2.5 to 15.3%, and the specificity investigation demonstrated that the MNP-MLIC is highly specific to the three biomarkers. In conclusion, the developed MNP-MLIC offers a rapid, simple, accurate, and highly specific method for simultaneously detecting multiple biomarkers in serum samples, which provides an efficient and accurate approach for the early diagnosis of diseases.

Single cell glycan-linkages profiling for hepatocellular carcinoma early diagnosis using lanthanide encoded bacteriophage MS2 based ICP-MS

Early diagnosis is paramount for enhancing survival rates and prognosis in the context of malignant diseases. Hepatocellular carcinoma (HCC), the second leading cause of cancer-related deaths worldwide, poses significant challenges for its early detection. In this study, we present an innovative approach which contributed to the early diagnosis of HCC. By lanthanide encoding signal amplification to map glycan-linkages at the single-cell level, the minute quantities of "soft" glycan-linkages on single cell surface were converted into "hard" elemental tags through the use of an MS2 signal amplifier. Harnessing the power of lanthanides encoded within MS2, we achieve nearly three orders of magnitude signal amplification. These encoded tags are subsequently quantified using single-cell inductively coupled plasma mass spectrometry (SC-ICP-MS). Linear discriminant analysis (LDA) identifies seven specific glycan-linkages (α-2,3-Sia, α-Gal, α-1,2-Fuc, α-1,6-Fuc, α-2,6-Sia, α-GalNAc, and Gal-β-1,3-GalNAc) as biomarkers. Our methodology is initially validated at the cellular level with 100% accuracy in discriminating between hepatic carcinoma HepG2 cells and their normal HL7702 cells. We apply this approach to quantify and classify glycan-linkages on the surfaces of 55 clinical surgical HCC specimens. Leveraging these seven glycan-linkages as biomarkers, we achieve precise differentiation between 8 normal hepatic specimens, 40 early HCC specimens, and 7 colorectal metastasis HCC specimens. This pioneering work represents the first instance of employing single-cell glycan-linkages as biomarkers promising for the early diagnosis of HCC with a remarkable 100% predictive accuracy rate, which holds immense potential for enhancing the feasibility and precision of HCC diagnosis in clinical practice.

OHCCPredictor: an online risk stratification model for predicting survival duration of older patients with hepatocellular carcinoma

BACKGROUND

Although the elderly constitute more than a third of hepatocellular carcinoma (HCC) patients, they have not been adequately represented in treatment and prognosis studies. Thus, there is not enough evidence to guide the treatment of such patients. The objective of this study is to identify the prognostic factors of older patients with HCC and to construct a new prognostic model for predicting their overall survival (OS).

METHODS

2,721 HCC patients aged ≥ 65 were extracted from the public database-Surveillance, Epidemiology, and End Results (SEER) and randomly divided into a training set and an internal validation set with a ratio of 7:3. 101 patients diagnosed from 2008 to 2017 in the First Affiliated Hospital of Zhejiang University School of Medicine were identified as the external validation set. Univariate cox regression analyses and multivariate cox regression analyses were adopted to identify these independent prognostic factors. A predictive nomogram-based risk stratification model was proposed and evaluated using area under the receiver operating characteristic curve (AUC), calibration curves, and a decision curve analysis (DCA).

RESULTS

These attributes including age, sex, marital status, T stage, N stage, surgery, chemotherapy, tumor size, alpha-fetoprotein level, fibrosis score, bone metastasis, lung metastasis, and grade were the independent prognostic factors for older patients with HCC while predicting survival duration. We found that the nomogram provided a good assessment of OS at 1, 3, and 5 years in older patients with HCC (1-year OS: (training set: AUC = 0.823 (95%CI 0.803-0.845); internal validation set: AUC = 0.847 (95%CI 0.818-0.876); external validation set: AUC = 0.732 (95%CI 0.521-0.943)); 3-year OS: (training set: AUC = 0.813 (95%CI 0.790-0.837); internal validation set: AUC = 0.844 (95%CI 0.812-0.876); external validation set: AUC = 0.780 (95%CI 0.674-0.887)); 5-year OS: (training set: AUC = 0.839 (95%CI 0.806-0.872); internal validation set: AUC = 0.800 (95%CI 0.751-0.849); external validation set: AUC = 0.821 (95%CI 0.727-0.914)). The calibration curves showed that the nomogram was with strong calibration. The DCA indicated that the nomogram can be used as an effective tool in clinical practice. The risk stratification of all subgroups was statistically significant (p < 0.05). In the stratification analysis of surgery, larger resection (LR) achieved a better survival curve than local destruction (LD), but a worse one than segmental resection (SR) and liver transplantation (LT) (p < 0.0001). With the consideration of the friendship to clinicians, we further developed an online interface (OHCCPredictor) for such a predictive function ( https://juntaotan.shinyapps.io/dynnomapp_hcc/ ). With such an easily obtained online tool, clinicians will be provided helpful assistance in formulating personalized therapy to assess the prognosis of older patients with HCC.

CONCLUSIONS

Age, sex, marital status, T stage, N stage, surgery, chemotherapy, tumor size, AFP level, fibrosis score, bone metastasis, lung metastasis, and grade were independent prognostic factors for elderly patients with HCC. The constructed nomogram model based on the above factors could accurately predict the prognosis of such patients. Besides, the developed online web interface of the predictive model provide easily obtained access for clinicians.

Malignant cell receptor-ligand subtypes guide the prediction of prognosis and personalized immunotherapy of liver cancer

OBJECTIVE

Liver cancer is a prevalent disease with a dismal prognosis. The aim of the research is to identify subgroups based on malignant cell receptor ligand gene from single-cell RNA, which might lead to customized immunotherapy for patients with liver cancer.

METHODS

Based on scRNA-seq data, we identified the receptor-ligand genes associated with prognosis and classify patients into molecular subtypes by univariate Cox regression and consensus clustering. LASSO regression was performed to construct a prognostic model, which was validated in TCGA and ICGC datasets. Immune infiltration and prediction of immunotherapy response were analyzed using ssGSEA, ESTIMATE, TIDE, and TRS score calculation. Finally, qPCR and Western blot validation of key genes and protein levels in cell lines.

RESULTS

A risk model using 16-gene expression levels predicted liver cancer patients' prognosis. The RiskScore associated significantly with tumor clinical characteristics and immunity, integrated with clinicopathological features for survival prediction. Differential expression of SRXN1 was verified in hepatocellular carcinoma and normal liver cells.

CONCLUSION

Our study utilizes single-cell analysis to investigate the communication between malignant cells and other cell types, identifying molecular subtypes based on malignant cell receptor ligand genes, offering new insights for the development of personalized immunotherapy and prognostic prediction models.

Serum Aldo-Keto Reductase Family 1 Member B10 (AKR1B10) as a Potential Biomarker for Diagnosis of Hepatocellular Carcinoma

Objective

To evaluate the diagnostic performance of aldo-keto reductase family 1 member B10 (AKR1B10) in a Beijing cohort with hepatocellular carcinoma (HCC).

Methods

This study included 521 subjects who visited Peking Union Medical College Hospital from June 2017 to May 2023, including 109 cases of HCC, 165 cases of healthy controls, 106 cases of benign liver diseases, and 141 cases of other cancers. Serum AKR1B10 levels were measured and compared across various groups. Diagnostic performances of serum AKR1B10 and other tumor markers were assessed using receiver operator characteristic (ROC) curves. In addition, a subset of HCC patients who underwent surgical resection were recruited for clinical follow-up study.

Results

We found that serum AKR1B10 expression was higher in patients with HCC relative to other control groups. The association between serum AKR1B10 and clinical features of HCC was not observed. Serum AKR1B10 showed a high diagnostic performance for HCC, and when combined with AFP, the diagnostic effectiveness was significantly improved. Specifically, serum AKR1B10 showed superior diagnostic effectiveness for AFP-negative HCC. The clinical follow-up study indicated a gradual decrease in serum AKR1B10 after surgery.

Conclusion

Our study demonstrated that serum AKR1B10 is a promising biomarker for HCC, and when used in combination with AFP can significantly improve the detection rate of HCC.

Long noncoding RNA LINC00482 silencing sensitizes non-small cell lung cancer cells to cisplatin by downregulating CLASRP via E2F1

Long noncoding RNA LINC00482 (LINC00482) is dysregulated in non-small cell lung cancer cells (NSCLC). Herein, this research examined the actions and specific mechanisms of LINC00482 in cisplatin (DDP) resistance in NSCLC. LINC00482 expression was assessed using RT-qPCR in clinical NSCLC tissues and cell lines. Knockdown and ectopic expression assays were conducted in A549 and HCC44 cells, followed by determination of cell proliferation with CCK-8 and clone formation assays, apoptosis with flow cytometry, and DDP sensitivity. The association between LINC00482, E2F1, and CLASRP was evaluated with dual-luciferase reporter, ChIP, and RIP assays. The role of LINC00482 in NSCLC was confirmed in nude mice. NSCLC tissues and cells had upregulated LINC00482 expression. LINC00482 was mainly localized in the cell nucleus, and LINC00482 recruited E2F1 to enhance CLASRP expression in NSCLC cells. LINC00482 knockdown enhanced the DDP sensitivity and apoptosis of NSCLC cells while reducing cell proliferation, which was negated by overexpressing CLASRP. LINC00482 knockdown restricted tumor growth and enhanced DDP sensitivity in NSCLC in vivo. LINC00482 silencing downregulated CLASRP through E2F1 to facilitate the sensitivity to DDP in NSCLC.

Hepatocellular Carcinoma in Non-Fibrotic Liver: A Narrative Review

Hepatocellular carcinoma (HCC) in a non-fibrotic liver (F0) is considered to be rare, and there is a marked paucity of studies in the literature on this HCC type. A review of the literature shows some important clinical and tumor characteristics: (a) it occurs mainly in young female and elder male patients; (b) clinically, under normal hepatic function, alpha-fetoprotein level is often normal, and there are no risk factors; (c) associated with metabolic disease; (d) macroscopically, single large lesions are noted; and (e) microscopically, the lesions are well-differentiated and encapsulated. Radiological imaging results are straightforward, showing arterial hyperenhancement and later wash-out. The combined use of B-mode and contrast-enhanced (CE) ultrasound (US) is the most reliable and cost-effective diagnostic method. Few peri-and post-operative complications are noted and 5-year survival is not inferior to patients with HCC on fibrosis liver despite the lesion's large size. Most clinicians believe that HCC is unlikely to occur if patients have no symptoms and normal hepatic function. Although detailed clinical data are very limited, we expect that this review will help to improve the clinical management of HCC in non-fibrotic livers.

Decoding hepatocarcinogenesis from a noncoding RNAs perspective

Being a leading lethal malignancy worldwide, the pathophysiology of hepatocellular carcinoma (HCC) has gained a lot of interest. Yet, underlying mechanistic basis of the liver tumorigenesis is poorly understood. The role of some coding genes and their respective translated proteins, then later on, some noncoding RNAs (ncRNAs) such as microRNAs have been extensively studied in context of HCC pathophysiology; however, the implication of long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) in HCC is indeed less investigated. As a subclass of the ncRNAs which has been elusive for long time ago, lncRNAs was found to be involved in plentiful cellular functions such as DNA, RNA, and proteins regulation. Hence, it is undisputed that lncRNAs dysregulation profoundly contributes to HCC via diverse etiologies. Accordingly, lncRNAs represent a hot research topic that requires prime focus in HCC. In this review, the authors discuss breakthrough discoveries involving lncRNAs and circRNAs dysregulation that have contributed to the contemporary concepts of HCC pathophysiology and how these concepts could be leveraged as potential novel diagnostic and prognostic HCC biomarkers. Further, this review article sheds light on future trends, thereby discussing the pathological roles of lncRNAs and circRNAs in HCC proliferation, migration, and epithelial-to-mesenchymal transition. Along this line of reasoning, future recommendations of how these targets could be exploited to achieve effective HCC-related drug development is highlighted.

Value of XGBoost machine learning model for diagnosis of hepatitis B cirrhosis

BACKGROUND

The progression of chronic hepatitis B into cirrhosis is slow and easily ignored, and the construction of a noninvasive diagnostic model for cirrhosis based on routine clinical indicators has become a hot research topic. However, there is still a lack of machine learning models regarding the early diagnosis of cirrhosis.

AIM

To investigate the performance of the extreme gradient boosting (XGBoost) machine model in the diagnosis of hepatitis B cirrhosis.

METHODS

A retrospective analysis was performed on 1087 patients with chronic hepatitis B virus infection (CHBV) diagnosed for the first time at the Department of Infection, The First/Second Affiliated Hospital of Anhui Medical University from 2010 to 2018. The patients were divided into training and validation sets in a 3:1 ratio according to the randomization principle. Clinical data of all study participants were collected and prediction models were constructed using XGBoost machine learning model. Meanwhile, the aspartate aminotransferase/platelet ratio index (APRI) and fibrosis-4 index (FIB-4) scores were calculated and compared with the XGBoost machine learning model. Area under the curve (AUC) was used to assess the model discrimination, and calibration curve (CA) and decision curve analysis (DCA) were used to assess the model calibration and benefit.

RESULTS

A total of 1087 CHBV patients were included, including 817 in the training set and 270 in the validation set. There was no statistical difference between the training and validation sets for all predictor variables (P > 0.05). Cirrhosis occurred in 103 patients in the training set, and APRI and FIB-4 scores were significantly higher in cirrhotic patients than in non-cirrhotic patients (P < 0.05). The relative importance of platelets was the highest among all predictors. The AUCs of the model in the training and validation sets were 0.95 and 0.86 (P < 0.05), respectively, and the Kappa values were 0.78 and 0.74, which suggested that the model was reproducible. CA curve analysis indicated that the model predicted a high degree of agreement with the true situation fit. DCA of the training and validation sets implied that the developed model could result in a high degree of benefit for patients. XGBoost machine learning model was significantly more efficient for the diagnosis of cirrhosis than APRI and FIB-4 scores.

CONCLUSION

The XGBoost machine learning model constructed in this study based on common clinical information of CHBV patients has an excellent performance for the diagnosis of cirrhosis and deserves further clinical promotion.

Updating the Clinical Application of Blood Biomarkers and Their Algorithms in the Diagnosis and Surveillance of Hepatocellular Carcinoma: A Critical Review

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

Diagnostic Significance of hsa-miR-21-5p, hsa-miR-192-5p, hsa-miR-155-5p, hsa-miR-199a-5p Panel and Ratios in Hepatocellular Carcinoma on Top of Liver Cirrhosis in HCV-Infected Patients

Early hepatocellular carcinoma (HCC) diagnosis is challenging. Moreover, for patients with alpha-fetoprotein (AFP)-negative HCC, this challenge is augmented. MicroRNAs (miRs) profiles may serve as potential HCC molecular markers. We aimed to assess plasma homo sapiens-(hsa)-miR-21-5p, hsa-miR-155-5p, hsa-miR-192-5p, and hsa-miR-199a-5p-expression levels as a panel of biomarkers for HCC in chronic hepatitis C virus (CHCV) patients with liver cirrhosis (LC), especially AFP-negative HCC cases, as a step toward non-protein coding (nc) RNA precision medicine.

SUBJECTS AND METHODS

79 patients enrolled with CHCV infection with LC, subclassified into an LC group without HCC (n = 40) and LC with HCC (n = 39). Real-time quantitative PCR was used to measure plasma hsa-miR-21-5p, hsa-miR-155-5p, hsa-miR-192-5p, and hsa-miR-199a-5p.

RESULTS

Plasma hsa-miR-21-5p and hsa-miR-155-5p demonstrated significant upregulation, while hsa-miR-199a-5p demonstrated significant downregulation in the HCC group (n = 39) when compared to the LC group (n = 40). hsa-miR-21-5p expression was positively correlated with serum AFP, insulin, and insulin resistance (r = 0.5, p < 0.001, r = 0.334, p = 0.01, and r = 0.303, p = 0.02, respectively). According to the ROC curves, for differentiating HCC from LC, combining AFP with each of hsa-miR-21-5p, hsa-miR-155-5p, and miR199a-5p improved the diagnostic sensitivity to 87%, 82%, and 84%, respectively, vs. 69% for AFP alone, with acceptable specificities of 77.5%, 77.5%, and 80%, respectively, and AUC = 0.89, 0.85, and 0.90, respectively vs. 0.85 for AFP alone. hsa-miR-21-5p/hsa-miR-199a-5p and hsa-miR-155-5p/hsa-miR-199a-5p ratios discriminated HCC from LC at AUC = 0.76 and 0.71, respectively, with sensitivities = 94% and 92% and specificities = 48% and 53%, respectively. Upregulation of plasma hsa-miR-21-5p was considered as an independent risk factor for HCC development [OR = 1.198(1.063-1.329), p = 0.002].

CONCLUSIONS

Combining each of hsa-miR-21-5p, hsa-miR-155-5p, and hsa-miR-199a-5p with AFP made it possible to identify HCC development in the LC patients' cohort with higher sensitivity than using AFP alone. hsa-miR-21-5p/hsa-miR-199a-5p and hsa-miR-155-5p/hsa-miR-199a-5p ratios are potential HCC molecular markers for AFP-negative HCC patients. hsa-miR-21-5p was linked, clinically and via in silico proof, to insulin metabolism, inflammation, dyslipidemia, and tumorigenesis in the HCC patients' group as well as for an upregulated independent risk factor for the emergence of HCC from LC in the CHCV patients.

Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs

Background

Accumulating evidence shows that immunogenic cell death (ICD) enhances immunotherapy effectiveness. In this study, we aimed to develop a prognostic model combining ICD, immunity, and long non-coding RNA biomarkers for predicting hepatocellular carcinoma (HCC) outcomes.

Methods

Immune- and immunogenic cell death-related lncRNAs (IICDLs) were identified from The Cancer Genome Atlas and Ensembl databases. IICDLs were extracted based on the results of differential expression and univariate Cox analyses and used to generate molecular subtypes using ConsensusClusterPlus. We created a prognostic signature based on IICDLs and a nomogram based on risk scores. Clinical characteristics, immune landscapes, immune checkpoint blocking (ICB) responses, stemness, and chemotherapy responses were also analyzed for different molecular subtypes and risk groups.

Result

A total of 81 IICDLs were identified, 20 of which were significantly associated with overall survival (OS) in patients with HCC. Cluster analysis divided patients with HCC into two distinct molecular subtypes (C1 and C2), with patients in C1 having a shorter survival time than those in C2. Four IICDLs (TMEM220-AS1, LINC02362, LINC01554, and LINC02499) were selected to develop a prognostic model that was an independent prognostic factor of HCC outcomes. C1 and the high-risk group had worse OS (hazard ratio > 1.5, p < 0.01), higher T stage (p < 0.05), higher clinical stage (p < 0.05), higher pathological grade (p < 0.05), low immune cell infiltration (CD4⁺ T cells, B cells, macrophages, neutrophils, and myeloid dendritic cells), low immune checkpoint gene expression, poor response to ICB therapy, and high stemness. Different molecular subtypes and risk groups showed significantly different responses to several chemotherapy drugs, such as doxorubicin (p < 0.001), 5-fluorouracil (p < 0.001), gemcitabine (p < 0.001), and sorafenib (p < 0.01).

Conclusion

Our study identified molecular subtypes and a prognostic signature based on IICDLs that could help predict the clinical prognosis and treatment response in patients with HCC.

Clinically Applicable Homogeneous Assay for Serological Diagnosis of Alpha-Fetoprotein by Impact Electrochemistry

Tumor protein quantification with high specificity, sensitivity, and efficiency is of great significance to enable early diagnosis and effective treatment. The existing methods for protein analysis usually suffer from high cost, time-consuming operation, and insufficient sensitivity, making them not clinically friendly. In this work, a label-free homogeneous sensor based on the nano-impact electroanalytic (NIE) technique was proposed for the detection of tumor protein marker alpha-fetoprotein (AFP). The detection principle is based on the recovery of current of single PtNP catalyzed hydrazine oxidation due to the release of the pre-adsorbed passivating aptamers on PtNPs from the competition of the stronger binding between the specific interaction of the AFP aptamer and AFP. The intrinsic one-by-one analytical ability of NIE allows highly sensitive detection, which can be further improved by reducing the reaction/incubation volume. Meanwhile, the current sensor avoids a laborious labeling procedure as well as the separation and washing steps due to the in situ characteristic of NIE. Accordingly, the current sensor enables efficient, highly sensitive, and specific AFP analysis. More importantly, the reliable detection of AFP in diluted real sera from hepatocellular carcinoma (HCC) patients is successfully achieved, indicating that the impact electrochemistry-based sensing platform has great potential to be applied in point-of-care devices for HCC liquid biopsy.

Blood-Based Biomarkers in Afp Normal/Stable Hepatocellular Carcinoma: Diagnostic and Prognostic Relevance of Mir-10b for Patients on Liver Transplant List

BACKGROUND

As a diagnostic criteria of hepatocellular carcinoma (HCC), the exact threshold of alpha-fetoprotein (AFP) is controversial. In additional, not all HCC tumors are AFP positive or secrete elevated amounts of AFP into the serum. However, the diagnosis of HCC is quite important on the liver transplant list. Therefore, the purpose of this study was to investigate the expression of circulating micro RNAs (miRNAs) in AFP-stable HCC patients. Thus, we aimed to determine a diagnostic biomarker in these patients.

METHODS

Sixteen miRNAs were evaluated using a real-time quantitative reverse transcription polymerase chain reaction system in AFP-stable HCC and AFP-trending HCC patients.

RESULTS

In our study, 46.7% (n = 28) of the patients diagnosed with HCC had stable/normal AFP levels. We detected that high expression of miR-24, miR-10b and the low expression of miR-143 were independently and significantly associated with HCC in AFP-stable compared with AFP trending (P < .05). Additionally, we demonstrated that the overexpression of miR-10b was associated with poor disease-free survival in HCC (P = 0.001).

CONCLUSIONS

Although more clinical validations are needed for the diagnosis of HCC, our current results indicate that the coexistence of high expression of miR-10b and miR-24 may help clinicians adjust in the diagnosis of HCC in patients who are on the liver transplant list but awaiting biopsy for the diagnosis of HCC.

Tumor-Promoting ATAD2 and Its Preclinical Challenges

ATAD2 has received extensive attention in recent years as one prospective oncogene with tumor-promoting features in many malignancies. ATAD2 is a highly conserved bromodomain family protein that exerts its biological functions by mainly AAA ATPase and bromodomain. ATAD2 acts as an epigenetic decoder and transcription factor or co-activator, which is engaged in cellular activities, such as transcriptional regulation, DNA replication, and protein modification. ATAD2 has been reported to be highly expressed in a variety of human malignancies, including gastrointestinal malignancies, reproductive malignancies, urological malignancies, lung cancer, and other types of malignancies. ATAD2 is involved in the activation of multiple oncogenic signaling pathways and is closely associated with tumorigenesis, progression, chemoresistance, and poor prognosis, but the oncogenic mechanisms vary in different cancer types. Moreover, the direct targeting of ATAD2’s bromodomain may be a very challenging task. In this review, we summarized the role of ATAD2 in various types of malignancies and pointed out the pharmacological direction.

Diagnostic performance of serum exosomal miRNA-720 in hepatocellular carcinoma

Background/Aim

Hepatocellular carcinoma (HCC) is associated with poor prognosis, largely due to late detection. Highly accurate biomarkers are urgently needed to detect early-stage HCC. Our study aims to explore the diagnostic performance of serum exosomal microRNA (miR)-720 in HCC.

Methods

Exosomal miRNA was measured via quantitative real-time PCR. A correlation analysis of exosomal miR-720 and tumor or clinico-demographic data of patients with HCC was performed. The receiver operating characteristic (ROC) curve was used to assess the diagnostic capacity of serum exosomal miR-720 for HCC, in comparison with α-fetoprotein (AFP) and prothrombin induced by vitamin K absence or antagonist-II (PIVKA-II).

Results

MiR-720 was chosen as a potential HCC marker via miR microarray based on significant differential expression between tumor and non-tumor samples. Serum exosomal miR-720 was significantly upregulated in patients with HCC (n=114) versus other liver diseases (control, n=30), with a higher area under the ROC curve (AUC, 0.931) than the other markers. Particularly, serum exosomal miR-720 showed superior performance in diagnosing small HCC (<5 cm; AUC, 0.930) compared with AFP (AUC, 0.802) or PIVKA-II (AUC, 0.718). Exosomal miR-720 levels showed marginal correlation with tumor size. The proportion of elevated miR-720 also increased with intrahepatic tumor stage progression. Unlike AFP or PIVKA-II showing a significant correlation with aminotransferase levels, the exosomal miR-720 level was not affected by aminotransferase levels.

Conclusions

Serum exosomal miR-720 is an excellent biomarker for the diagnosis of HCC, with better performance than AFP or PIVKA-II. Its diagnostic utility is maintained even in small HCC and is unaffected by aminotransferase levels.

Insights into the Association Between QSER1 and M2 Macrophages and Remarkable Malignancy Characteristics in Hepatocellular Carcinoma

Purpose

Glutamine and serine rich 1 (QSER1), as a DNA methylation modulator, play a crucial role in transforming tumor cells. Previous studies have shown that QSER1 plays a role in regulating the progression of various malignancies and that QSER1 dysfunction is connected with precancerous lesions of hepatocellular carcinoma (HCC) as well as HCC prognosis. However, little is known about the detailed contribution of QSER1 in HCC.

Patients and Methods

Various statistical methods such as Kaplan–Meier method, AUC analysis, GSEA, and immune-infiltration analysis were used to evaluate the relationship between QSER1 expression and clinical features, prognostic factors, and potential functional mechanisms of QSER1.

Results

QSER1 expression was negatively correlated with clinicopathological features (clinical stage, pathological grade, TP53 mutation, lymph node metastasis) and clinical outcome (overall survival versus recurrence). Functional enrichment analysis further suggested that QSER1 is involved in multiple pathways related to DNA replication and tumor immunity. TIMER analysis indicated that high QSER1 expression was significantly associated with higher macrophage infiltration and poorer macrophage-related outcomes. In particular, QSER1 was significantly more associated with M2 macrophages than M1 macrophages.

Conclusion

Overall, elevated QSER1 is a potential prognostic marker for HCC and is associated with immune infiltration in HCC.

High expression of PDZ-binding kinase is correlated with poor prognosis and immune infiltrates in hepatocellular carcinoma

Background

PDZ-binding kinase (PBK) encodes a serine/threonine protein kinase related to the dual specific mitogen-activated protein kinase kinase (MAPKK) family. There is evidence that overexpression of this gene is associated with tumorigenesis. However, the role of PBK in hepatocellular carcinoma (HCC) remains unclear. Therefore, we evaluated the prognostic role of PBK and its correlation with immune infiltrates in hepatocellular carcinoma.

Methods

The expression of PBK in pan-cancers was studied by Onconmine and TIMER. The expression of PBK in HCC patients and its relationship with clinicopathological characteristics were analyzed using The Gene Expression Profiling Interactive Analysis (GEPIA), The human protein atlas database (HPA), The Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO) databases. Receiver operating characteristic (ROC) curve was used to determine the diagnostic value of PBK in HCC patients. The relationship between PBK and prognosis of HCC was performed by GEPIA and Kaplan Meier plotter web tool. The correlations between the clinical characteristics and overall survival were analyzed by Univariate Cox regression and Multivariate Cox hazards regression to identify possible prognostic factors for HCC patients. LinkedOmics was applied to investigate co-expression associated with PBK and to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The network map of PBK and related genes is constructed by GeneMANIA. Finally, TIMER and TISIDB were used to analyze the correlations between PBK and tumor-infiltrating immune cells.

Results

Multiple database analysis shows that PBK was highly expressed in many types of tumors, including hepatocellular carcinoma, and was significantly related to tumor stage (P=0.0089), age (P=0.0131), and race (P=0.0024) of HCC patients. The receiver operating characteristic (ROC) curve analysis showed that PBK had high diagnostic potential to HCC in GSE76427 (AUC=0.8799), GSE121248 (AUC=0.9224), GSE62232 (AUC=0.9975), and GSE84402 (AUC=0.9541). Multivariate Cox hazards regression showed that high expression of PBK may be an independent risk factor for overall survival in HCC patients (HR = 1.566, 95% CI=1.062–2.311, P= 0.024). The Protein–protein interaction network showed that PBK significantly interacted with LRRC47, ARAF, LGALS9B, TTK, DLG1, and other essential genes. Furthermore, enrichment analysis showed that PBK and co-expressed genes participated in many biological processes, cell composition, molecular functions, and pathways in HCC. Finally, the immune infiltration analysis by TIMER and TISIDB indicated that a significant tightly correlation between PBK and macrophages, neutrophils, as well as chemokines and receptors.

Conclusions

High expression of PBK is significantly correlated with poor survival and immune infiltrates in hepatocellular carcinoma. Our study suggests that PBK can be used as a biomarker of poor prognosis and potential immune therapy target in hepatocellular carcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02479-w.