Circulating biomarkers in the diagnosis and management of hepatocellular carcinoma

Dual toeholds regulated CRISPR-Cas12a sensing platform for ApoE single nucleotide polymorphisms genotyping

Single nucleotide polymorphisms (SNPs) are closely associated with many biological processes, including genetic disease, tumorigenesis, and drug metabolism. Accurate and efficient SNP determination has been proved pivotal in pharmacogenomics and diagnostics. Herein, a universal and high-fidelity genotyping platform is established based on the dual toeholds regulated Cas12a sensing methodology. Different from the conventional single stranded or double stranded activation mode, the dual toeholds regulated mode overcomes protospacer adjacent motif (PAM) limitation via cascade toehold mediated strand displacement reaction, which is highly universal and ultra-specific. To enhance the sensitivity for biological samples analysis, a modified isothermal recombinant polymerase amplification (RPA) strategy is developed via utilizing deoxythymidine substituted primer and uracil-DNA glycosylase (UDG) treatment, designated as RPA-UDG. The dsDNA products containing single stranded toehold domain generated in the RPA-UDG allow further incorporation with dual toeholds regulated Cas12a platform for high-fidelity human sample genotyping. We discriminate all the single-nucleotide polymorphisms of ApoE gene at rs429358 and rs7412 loci with human buccal swab samples with 100% accuracy. Furthermore, we engineer visual readout of genotyping results by exploiting commercial lateral flow strips, which opens new possibilities for field deployable implementation.

A compact microfluidic laser-induced fluorescence immunoassay system using avalanche photodiode for rapid detection of alpha-fetoprotein

Alpha-fetoprotein (AFP), commonly employed for early diagnosis of liver cancer, serves as a biomarker for cancer screening and diagnosis. Combining the high sensitivity and specificity of fluorescence immunoassay (FIA), developing a low-cost and efficient immunoassay system for AFP detection holds significant importance in disease diagnosis. In this work, we developed a miniaturized oblique laser-induced fluorescence (LIF) immunoassay system, coupled with a microfluidic PMMA/paper hybrid chip, for rapid detection of AFP. The system employed an avalanche photodiode (APD) as the detector, and implemented multi-level filtering in the excitation light channel using the dichroic mirror and optical trap. At first, we employed the Savitzky-Golay filter and baseline off-set elimination methods to denoise and normalize the original data. Then the cutoff frequency of the low-pass filter and the reverse voltage of the APD were optimized to enhance the detection sensitivity of the system. Furthermore, the effect of laser power on the fluorescence excitation efficiency was investigated, and the sampling time during the scanning process was optimized. Finally, a four-parameter logistic (4PL) model was utilized to establish the concentration-response equation for AFP. The system was capable of detecting concentrations of AFP standard solution within the range of 1-500 ng/mL, with a detection limit of 0.8 ng/mL. The entire immunoassay process could be completed within 15 min. It has an excellent potential for applications in low-cost portable diagnostic instruments for the rapid detection of biomarkers.

Transcriptomic Signature of 3D Hierarchical Porous Chip Enriched Exosomes for Early Detection and Progression Monitoring of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly lethal malignant tumor, and the current non-invasive diagnosis method based on serum markers, such as α-fetoprotein (AFP), and des-γ-carboxy-prothrombin (DCP), has limited efficacy in detecting it. Therefore, there is a critical need to develop novel biomarkers for HCC. Recent studies have highlighted the potential of exosomes as biomarkers. To enhance exosome enrichment, a silicon dioxide (SiO2) microsphere-coated three-dimensional (3D) hierarchical porous chip, named a SiO2-chip is designed. The features of the chip, including its continuous porous 3D scaffold, large surface area, and nanopores between the SiO2 microspheres, synergistically improved the exosome capture efficiency. Exosomes from both non-HCC and HCC subjects are enriched using an SiO2-chip and performed RNA sequencing to identify HCC-related long non-coding RNAs (lncRNAs) in the exosomes. This study analysis reveales that LUCAT-1 and EGFR-AS-1 are two HCC-related lncRNAs. To further detect dual lncRNAs in exosomes, quantitative real time polymerase chain reaction (qRT-PCR) is employed. The integration of dual lncRNAs with AFP and DCP significantly improves the diagnostic accuracy. Furthermore, the integration of dual lncRNAs with DCP effectively monitors the prognosis of patients with HCC and detects disease progression. In this study, a liquid biopsy-based approach for noninvasive and reliable HCC detection is developed.

Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway

BACKGROUND

The ubiquitin-proteasome pathway (UPP) has been proven to play important roles in cancer.

AIM

To investigate the prognostic significance of genes involved in the UPP and develop a predictive model for liver cancer based on the expression of these genes.

METHODS

In this study, UPP-related E1, E2, E3, deubiquitylating enzyme, and proteasome gene sets were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, aiming to screen the prognostic genes using univariate and multivariate regression analysis and develop a prognosis predictive model based on the Cancer Genome Atlas liver cancer cases.

RESULTS

Five genes (including autophagy related 10, proteasome 20S subunit alpha 8, proteasome 20S subunit beta 2, ubiquitin specific peptidase 17 like family member 2, and ubiquitin specific peptidase 8) were proven significantly correlated with prognosis and used to develop a prognosis predictive model for liver cancer. Among training, validation, and Gene Expression Omnibus sets, the overall survival differed significantly between the high-risk and low-risk groups. The expression of the five genes was significantly associated with immunocyte infiltration, tumor stage, and postoperative recurrence. A total of 111 differentially expressed genes (DEGs) were identified between the high-risk and low-risk groups and they were enriched in 20 and 5 gene ontology and KEGG pathways. Cell division cycle 20, Kelch repeat and BTB domain containing 11, and DDB1 and CUL4 associated factor 4 like 2 were the DEGs in the E3 gene set that correlated with survival.

CONCLUSION

We have constructed a prognosis predictive model in patients with liver cancer, which contains five genes that associate with immunocyte infiltration, tumor stage, and postoperative recurrence.

The chemokine CCL20 can assist AFP in serological diagnosis of hepatocellular carcinoma

The chemokine 20 (CCL20) is a member of the CC chemokine family and plays a role in tumor immunity and autoimmune disease. This work investigated the value of CCL20 as a serum diagnostic marker for primary hepatocellular carcinoma (HCC). Based on the data of hepatocellular carcinoma patients in the TCGA database, the up-regulated genes encoding secretory proteins were analyzed in each pathological stage, and the candidate marker CCL20 gene was selected. Serum concentrations of CCL20 in patients with primary HCC, benign liver disease, and healthy subjects were analyzed by enzyme-linked immunosorbent assay (ELISA). The ROC curve evaluated the efficacy of CCL20 alone or in combination with AFP in the diagnosis of HCC. It was found the expression of CCL20 in HCC patients was significantly higher than that in the benign liver disease group and healthy controls (P < 0.05); The AUC of ROC curve to distinguish HCC patients from healthy controls was 0.859, the sensitivity was 73.42%, and the specificity was 86.84%. After combination with AFP, the AUC increased to 0.968, the sensitivity was 88.16%, and the specificity was 97.37%. Although CCL20 was increased in the serum of patients with benign liver diseases, combined with AFP, the AUC to distinguish HCC patients from non-HCC cohorts (benign liver disease group and healthy control group) was 0.902, with a sensitivity of 91.67% and a specificity of 75.26%. Collectively, serum CCL20 is closely related to the occurrence of HCC, and detection of serum CCL20 can assist AFP in improving the diagnostic sensitivity of HCC.

Caffeine in Hepatocellular Carcinoma: Cellular Assays, Animal Experiments, and Epidemiological Investigation

The use of caffeine in treating various liver diseases has made substantial progress in the past decade owing to advances in science, technology, and medicine. However, whether caffeine has a preventive effect on hepatocellular carcinoma (HCC) and its mechanism are still worth further investigation. In this review, we summarize and analyze the efficacy and safety of caffeine in the prevention of HCC. We conducted a review of articles published in PubMed and Web of Science in the past 2 decades until December 6, 2023, which were searched for using the terms "Caffeine" and "Hepatocellular Carcinoma." Studies have found that coffee intake is negatively correlated with HCC risk, especially caffeinated coffee. Recent studies have found that caffeine has beneficial effects on liver health, decreasing levels of enzymes responsible for liver damaging and slowing the progression of hepatic fibrosis and cirrhosis. Caffeine also acts against liver fibrosis through adenosine receptors (ARs), which promote tissue remodeling by inducing fibrin and collagen production. Additionally, new studies have found that moderate consumption of caffeinated beverages can decrease various the levels of various collagens in patients with chronic hepatitis C. Furthermore, polyphenolic compounds in coffee can improve fat homeostasis, reduce oxidative stress, and prevent liver steatosis and fibrosis. Moreover, many in vitro studies have shown that caffeine can protect liver cells and inhibit the activation and proliferation of hepatic stellate cells. Taken together, we describe the benefits of caffeine for liver health and highlight its potential values as a drug to prevent various hepatic diseases. As a protective agent of liver inflammation, non-selective AR inhibitor caffeine can inhibit the growth of HCC cells by inhibiting adenosine and AR binding to initiate immune response, providing a basis for the future development of caffeine as an adjuvant drug against HCC.

Bioinformatics and machine learning driven key genes screening for hepatocellular carcinoma

Liver cancer, a global menace, ranked as the sixth most prevalent and third deadliest cancer in 2020. The challenge of early diagnosis and treatment, especially for hepatocellular carcinoma (HCC), persists due to late-stage detections. Understanding HCC's complex pathogenesis is vital for advancing diagnostics and therapies. This study combines bioinformatics and machine learning, examining HCC comprehensively. Three datasets underwent meticulous scrutiny, employing various analytical tools such as Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein interaction assessment, and survival analysis. These rigorous investigations uncovered twelve pivotal genes intricately linked with HCC's pathophysiological intricacies. Among them, CYP2C8, CYP2C9, EPHX2, and ESR1 were significantly positively correlated with overall patient survival, while AKR1B10 and NQO1 displayed a negative correlation. Moreover, the Adaboost prediction model yielded an 86.8 % accuracy, showcasing machine learning's potential in deciphering complex dataset patterns for clinically relevant predictions. These findings promise to contribute valuable insights into the elusive mechanisms driving liver cancer (HCC). They hold the potential to guide the development of more precise diagnostic methods and treatment strategies in the future. In the fight against this global health challenge, unraveling HCC's intricacies is of paramount importance.

Serologic Detection of Hepatocellular Carcinoma: Application of Machine Learning and Implications for Diagnostic Models

PURPOSE

The gender, age, lens culinaris agglutinin-reactive fraction of alphafetoprotein, alphafetoprotein, des-gamma-carboxyprothrombin (GALAD) score is a biomarker-based statistical model for the serologic diagnosis of hepatocellular carcinoma (HCC) that has been developed and validated using the case-control approach with a view to early detection. Performance has, however, been suboptimal in the first prospective studies which better reflect the real-world situation. In this article, we report the application of machine learning to a large, prospectively accrued, HCC surveillance data set.

PATIENTS AND METHODS

Models were built on a cohort of 3,473 patients with chronic liver disease within a rigorous surveillance program between 1998 and 2014, during which 459 patients with HCC were detected. Two random forest (RF) models were trained. The first RF model uses the same variables as the original GALAD model (GALAD-RF); the second is based on routinely available clinical and laboratory features (RF-practical). For comparison, we evaluated a logistic regression GALAD model trained on this longitudinal prospective data set (termed GALAD-Ogaki).

RESULTS

Models were evaluated using a repetitive cross-validation approach with the metrics averaged over 100 independent runs. As judged by area under the receiver operator curve (AUROC) and F1 score, the GALAD RF model significantly outperformed the original GALAD model. The RF-practical model also outperformed the original GALAD model in terms of both AUROC and F1 score, and both models outperformed the individual biomarkers. An online web application that implemented the GALAD-RF and RF-practical models is presented.

CONCLUSION

RF-based models improve on the diagnostic performance of the original GALAD model in the setting of a standard HCC surveillance program. Further prospective validation studies are warranted using these models and could be expanded to offer prediction of risk of HCC development over defined periods of time.

Proteomic Analysis Identifies GSN as a Noninvasive Circulating Serum Biomarker for Predicting Early Recurrence of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is susceptible to early recurrence, but it lacks effective predictive biomarkers. In this study, we retrospectively selected 179 individuals as a discovery cohort (126 HCC patients and 53 liver cirrhosis (LC) patients) for screening candidate serum biomarkers of early recurrence based on data independent acquisition-mass spectrometry strategy. And then, the candidate biomarkers were validated in an additional independent cohort with 192 individuals (142 HCC patients and 50 LC patients) using parallel reaction monitoring targeted quantitative techniques (PXD047852). Eventually, we validated that gelsolin (GSN) concentrations were significantly lower in HCC than in LC (p < 0.0001), patients with low GSN concentrations had a poor prognosis (p < 0.0001), and GSN concentrations were significantly lower in early recurrence HCC than in late recurrence HCC (p < 0.0001). These trends were also observed in alpha-fetoprotein (AFP)-negative HCC patients. The area under the curve of machine-learning-based predictive model (GSN and microvascular invasion) for predicting early recurrence risk reached 0.803 (95% confidence interval (CI): 0.786-0.820) and maintained the same efficacy in AFP-negative patients. In conclusion, GSN is a novel serum biomarker for early recurrence of HCC. The model could provide timely warning to HCC patients at high risk of recurrence.

CMTM6 promotes hepatocellular carcinoma progression through stabilizing β-catenin

CMTM6, a regulator of PD-L1 stability, has been implicated in the development of various cancers. However, the expression and role of CMTM6 in hepatocellular carcinoma (HCC) remains controversial. Our study revealed a negative correlation between CMTM6 expression and HCC prognosis through bioinformatics analysis and immunofluorescence staining. CMTM6 expression was also positively associated with alpha-fetoprotein (AFP) levels, supporting its potential as a prognostic marker for HCC. Using Cmtm6 knockout mice, we found that Cmtm6 deficiency inhibited HCC formation and cell proliferation in primary liver cancer models induced by DEN and DEN/CCl4. In HCC cell lines, CMTM6 promoted cell proliferation and interacted with β-catenin, stabilizing it by preventing ubiquitination. In conclusion, our study suggested that CMTM6 upregulation promotes HCC cell proliferation through the β-catenin pathway, making it a potential therapeutic target for HCC treatment.

Overexpression of Aurora Kinase B Is Correlated with Diagnosis and Poor Prognosis in Hepatocellular Carcinoma

Aurora kinase B (AURKB) overexpression promotes tumor initiation and development by participating in the cell cycle. In this study, we focused on the mechanism of AURKB in hepatocellular carcinoma (HCC) progression and on AURKB's value as a diagnostic and prognostic biomarker in HCC. We used data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) to analyze AURKB expression in HCC. We found that the expression levels of AURKB in HCC samples were higher than those in the corresponding control group. R packages were used to analyze RNA sequencing data to identify AURKB-related differentially expressed genes (DEGs), and these genes were found to be significantly enriched during the cell cycle. The biological function of AURKB was verified, and the results showed that cell proliferation was slowed down and cells were arrested in the G2/M phase when AURKB was knocked down. AURKB overexpression resulted in significant differences in clinical symptoms, such as the clinical T stage and pathological stage. Kaplan-Meier survival analysis, Cox regression analysis, and Receiver Operating Characteristic (ROC) curve analysis suggested that AURKB overexpression has good diagnostic and prognostic potential in HCC. Therefore, AURKB may be used as a potential target for the diagnosis and cure of HCC.

High-throughput intact Glycopeptide quantification strategy with targeted-MS (HTiGQs-target) reveals site-specific IgG N-glycopeptides as biomarkers for hepatic disorder diagnosis and staging

Liver disease is one of the leading causes of global mortality, and identifying biomarkers for diagnosing the progression of liver diseases is crucial for improving its outcomes. Targeted mass spectrometry technology is a powerful tool with unique advantages for verifying biomarker candidates and clinical applications. It is particularly useful in validating protein biomarkers with post-translational modifications, eliminating the need for site-specific antibodies. Especially, targeted mass spectrometry technique is particularly critical for translation of glycoproteins into clinical applications as there are no site-specific antibodies for N-glycosylation. Nevertheless, its limitation in analyzing only one sample per run has become apparent when dealing with a large number of clinical samples. Herein, we developed a high-throughput intact N-glycopeptides quantification strategy with targeted-MS (HTiGQs-Target), which allows the validation of 20 samples per run with an average analysis time of only 3 min per sample. We applied HTiGQs-Target in a cohort of 461 serum samples (including 120 healthy controls (HC), 127 chronic hepatitis B (CHB) cases, 106 liver cirrhosis (LC) cases, and 108 hepatocellular carcinomas (HCC) cases) and found that a panel of 10 IgG N-glycopeptides have strong clinical utility in evaluating the severity of the liver disease.

Centrosome amplification-related signature correlated with immune microenvironment and treatment response predicts prognosis and improves diagnosis of hepatocellular carcinoma by integrating machine learning and single-cell analyses

BACKGROUND

Centrosome amplification is a well-recognized oncogenic driver of tumor initiation and progression across a variety of malignancies and has been linked with tumor aggressiveness, metastasis, and adverse prognosis. Nevertheless, the significance of centrosome amplification in HCC is not well understood.

METHODS

The TCGA dataset was downloaded for centrosome amplification-related signature construction using the LASSO-penalized Cox regression algorithm, while the ICGC dataset was obtained for signature validation. Single-cell RNA sequencing from GSE149614 was analyzed to profile gene expression and the liver tumor niche.

RESULTS

A total of 134 centrosome amplification-related prognostic genes in HCC were detected and 6 key prognostic genes (SSX2IP, SPAG4, SAC3D1, NPM1, CSNK1D, and CEP55) among them were screened out to construct a signature with both high sensitivity and specificity in diagnosis and prognosis of HCC patients. The signature, as an independent factor, was associated with frequent recurrences, high mortality rates, advanced clinicopathologic features, and high vascular invasions. Moreover, the signature was intimately associated with cell cycle-related pathways and TP53 mutation profile, suggesting its underlying role in accelerating cell cycle progression and leading to liver cancer development. Meanwhile, the signature was also closely correlated with immunosuppressive cell infiltration and immune checkpoint expression, making it a vital immunosuppressive factor in the tumor microenvironment. Upon single-cell RNA sequencing, SSX2IP and SAC3D1 were found to be specially expressed in liver cancer stem-like cells, where they promoted cell cycle progression and hypoxia.

CONCLUSIONS

This study provided a direct molecular link of centrosome amplification with clinical characteristics, tumor microenvironment, and clinical drug-response, highlighting the critical role of centrosome amplification in liver cancer development and therapy resistance, thereby providing valuable insights into prognostic prediction and therapeutic response of HCC.

Decoding the roles of heat shock proteins in liver cancer

Hepatocellular carcinoma (HCC) is one of the most common gastrointestinal malignancies, characterized by insidious onset and high propensity for metastasis and recurrence. Apart from surgical resection, there are no effective curative methods for HCC in recent years, due to resistance to radiotherapy and chemotherapy. Heat shock proteins (HSP) play a crucial role in maintaining cellular homeostasis and normal organism development as molecular chaperones for intracellular proteins. Both basic research and clinical data have shown that HSPs are crucial participants in the HCC microenvironment, as well as the occurrence, development, metastasis, and resistance to radiotherapy and chemotherapy in various malignancies, particularly liver cancer. This review aims to discuss the molecular mechanisms and potential clinical value of HSPs in HCC, which may provide new insights for HSP-based therapeutic interventions for HCC.

Molecular profiling in the management of hepatocellular carcinoma

PURPOSE OF REVIEW

The purpose of this review is to both summarize the current knowledge of hepatocellular carcinoma molecular biology and to suggest a framework in which to prospectively translate this knowledge into patient care. This is timely as recent guidelines recommend increased use of these technologies to advance personalized liver cancer care.

RECENT FINDINGS

The main themes covered here address germline and somatic genetic alterations recently discovered in hepatocellular carcinoma, largely owing to next generation sequencing technologies, and nascent efforts to translate these into contemporary practice.

SUMMARY

Early efforts of translating molecular profiling to hepatocellular carcinoma care demonstrate a growing number of potentially actionable alterations. Still lacking are a consensus on what biomarkers and technologies to adopt, at what scale and cost, and how to integrate them most effectively into care.

Prognostic Value of Serum α-Fetoprotein Level as an Important Characteristic of Tumor Biology for Patients Undergoing Liver Resection of Early-Stage Hepatocellular Carcinoma (BCLC Stage 0/A): A Large Multicenter Analysis

BACKGROUND AND OBJECTIVE

According to the Barcelona Clinic Liver Cancer (BCLC) algorithm, tumor burden and liver function, but not tumor biology, are the key factors in determining tumor staging and treatment modality, and evaluating treatment prognosis. The serum α-fetoprotein (AFP) level is an important characteristic of hepatocellular carcinoma (HCC) biology, and we aimed to evaluate its prognostic value for patients undergoing liver resection of early-stage HCC.

METHODS

Patients who underwent curative liver resection for early-stage HCC were identified from a multi-institutional database. Patients were divided into three groups according to preoperative AFP levels: low (< 400 ng/mL), high (400-999 ng/mL), and extremely-high (≥ 1000 ng/mL) AFP groups. Overall survival (OS) and recurrence rates were compared among these three groups.

RESULTS

Among 1284 patients, 720 (56.1%), 262 (20.4%), and 302 (23.5%) patients had preoperative low, high, and extremely-high AFP levels, respectively. The cumulative 5-year OS and recurrence rates were 71.3 and 38.9% among patients in the low AFP group, 66.3 and 48.5% in the high AFP group, and 45.7 and 67.2% in the extremely-high AFP group, respectively (both p < 0.001). Multivariate Cox regression analysis identified both high and extremely-high AFP levels to be independent risk factors of OS (hazard ratio [HR] 1.275 and 1.978, 95% confidence interval [CI] 1.004-1.620 and 1.588-2.464, respectively; p = 0.047 and p < 0.001, respectively) and recurrence (HR 1.290 and 2.050, 95% CI 1.047-1.588 and 1.692-2.484, respectively; p = 0.017 and p < 0.001, respectively).

CONCLUSIONS

This study demonstrated the important prognostic value of preoperative AFP levels among patients undergoing resection for early-stage HCC. Incorporating AFP to prognostic estimation of the BCLC algorithm can help guide individualized risk stratification and identify neoadjuvant/adjuvant treatment necessity.

Combinatorial Gene Expression Profiling of Serum HULC, HOTAIR, and UCA1 lncRNAs to Differentiate Hepatocellular Carcinoma from Liver Diseases: A Systematic Review and Meta-Analysis

Hepatocellular carcinoma (HCC) presents a significant global health challenge due to limited early detection methods, primarily relying on conventional approaches like imaging and alpha-fetoprotein (AFP). Although non-coding RNAs (ncRNAs) show promise as potential biomarkers in HCC, their true utility remains uncertain. We conducted a comprehensive review of 76 articles, analyzing 88 circulating lncRNAs in 6426 HCC patients. However, the lack of a standardized workflow protocol has hampered holistic comparisons across the literature. Consequently, we herein confined our meta-analysis to only a subset of these lncRNAs. The combined analysis of serum highly upregulated in liver cancer (HULC) gene expression with homeobox transcript antisense intergenic RNA (HOTAIR) and urothelial carcinoma-associated 1 (UCA1) demonstrated markedly enhanced sensitivity and specificity in diagnostic capability compared to traditional biomarkers or other ncRNAs. These findings could have substantial implications for the early diagnosis and tailored treatment of HCC.

UTP11 promotes the growth of hepatocellular carcinoma by enhancing the mRNA stability of Oct4

BACKGROUND

Several publications suggest that UTP11 may be a promising gene engaged for involvement of hepatocellular carcinoma (HCC) pathology. However, there are extremely limited biological, mechanistic and clinical studies of UTP11 in HCC.

METHODS

To anayze the UTP11 mRNA expression in HCC and normal clinical samples and further investigate the correlation between UTP11 expression and pathology and clinical prognosis via the Cancer Tissue Gene Atlas (TCGA) database. The protein levels of UTP11 were checked using the Human Protein Atlas (HPA) database. GO-KEGG enrichment was performed from Cancer Cell Line Encyclopedia (CCLE) database and TCGA dataset. The levels of UTP11 were tested with qRT-PCR and western blotting assays. Cell viability, immunofluorescence and flow cytometry assays and animal models were used to explore the potential involvement of UTP11 in regulating HCC growth in vitro and in vivo. The correlation of UTP11 and tumor stemness scores and stemness-associated proteins from TCGA database. The mRNA stability was treated with Actinomycin D, followed by testing the mRNA expression using qRT-PCR assay.

RESULTS

UTP11 was highly expressed in HCC samples compared to normal tissues from TCGA database. Similarly, UTP11 protein expression levels were obviously elevated in HCC tissue samples from HPA database. Furthermore, UTP11 levels were correlated with poor prognosis in HCC patient samples in TCGA dataset. In addition, the UTP11 mRNA levels was notably enhanced in different HCC cell lines than in normal liver cells and knocking down UTP11 was obviously reduced the viability and cell death of HCC cells. UTP11 knockdown suppressed the tumor growth of HCC in vivo experiment and extended the mice survival time. GO-KEEG analysis from CCLE and TCGA database suggested that UTP11 might involve in RNA splicing and the stability of mRNA. Further, UTP11 was positively correlated with tumor stemness scores and stemness-associated proteins from TCGA database. Knockdown of UTP11 was reduced the expression of stem cell-related genes and regulated the mRNA stability of Oct4.

CONCLUSIONS

UTP11 is potentially a diagnostic molecule and a therapeutic candidate for treatment of HCC.

Circulating Tumor DNA Clinical Applications in Hepatocellular Carcinoma: Current Trends and Future Perspectives

BACKGROUND

Globally, liver cancers are the second most lethal malignancy after lung cancer (0.83 million deaths in 2020). Hepatocellular carcinoma (HCC) is the predominant type of primary liver cancer and is typically associated with liver fibrosis or cirrhosis. HCC diagnosis relies on histologic examination of surgical specimens or conventional tissue biopsy material. However, standard tissue biopsies are invasive and often do not accurately reflect the tumor heterogeneity. On the other hand, the use of liquid biopsies, represented mainly by circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs), has greatly increased in the past 2 decades. Indeed, liquid biopsies are a noninvasive, repeatable, and sensitive approach to studying tumor biology.

CONTENT

This review describes current clinical applications of ctDNA analysis in the management of patients with chronic liver disease, cirrhosis, and HCC. There is a substantial clinical potential of ctDNA, but interventional studies are still lacking for the moment.

SUMMARY

Detection of ctDNA in both asymptomatic individuals and high-risk patients (with chronic liver disease or cirrhosis) contributes to the early diagnosis of HCC. ctDNA analysis also offer tremendous information on the tumor burden and on the risk of early recurrence. The implementation of ctDNA analysis, in association with classical tumor markers (e.g., alpha-fetoprotein), may improve (a) HCC screening in high-risk patients, (b) stratification of the recurrence risk after surgery, and (c) prognosis evaluation of patients with HCC.

Circ_MAPK9 promotes STAT3 and LDHA expression by silencing miR-642b-3p and affects the progression of hepatocellular carcinoma

BACKGROUND

Aberrant expression and activation of circular RNAs (circRNAs) are closely associated with various cancers. The role of circ_MAPK9 (hsa_circ_0001566) in cancer progression remains unknown. This study aims to investigate the function, mechanism and clinical significance of circ_MAPK9 in hepatocellular carcinoma (HCC).

METHODS

Circ_MAPK9 expression on the microarray of tumor from clinical HCC patients was detected by in situ hybridization (ISH). Circ_MAPK9 knockdown was achieved with siRNAs in SMMC-7721 and SK-Hep1 HCC cell lines. The biological function of circ_MAPK9 was verified in vitro by CCK8 test, colony formation assay, transwell assay, PI-Annexin V staining, and in vivo by xenograft tumor in nude mice. Fluorescent in situ hybridization (FISH), subcellular fractionation assay, a dual-luciferase reporter assay and rescue experiments were employed for further mechanistic investigation.

RESULTS

The expression of circ_MAPK9 was significantly up-regulated in HCC tissues and cells, which was found to be associated with poor prognosis. Patients with high expression of circ_MAPK9 had a shorter overall survival and disease-free survival in comparison to those with low circ_MAPK9 expression. Functional assays showed that circ_MAPK9 knockdown suppressed cellular proliferation, migration, invasion and tumor growth in vivo, and promoted apoptosis in HCC cells. Moreover, we found that circ_MAPK9 knockdown could inhibit aerobic glycolysis by decreasing the production of adenosine triphosphate (ATP) and lactic acid, which was mediated by lactate dehydrogenase (LDHA). Mechanistically, circ_MAPK9 functioned as ceRNA via sponging miR-642b-3p and alleviated the inhibitory effect of miR-642b-3p on its target signal transducer and activator of transcription 3 (STAT3) and LDHA, thereby leading to STAT3 activation and LDHA expression.

CONCLUSIONS

Circ_MAPK9, as an oncogene, promotes HCC growth and metastasis through miR-642b-3p/STAT3-LDHA axis. Circ_MAPK9 could serve as a potential biomarker for HCC poor prognosis and diagnosis.

Targeted Analysis of Glycerophospholipids and Mono-, Di-, or Tri-Acylglycerides in Liver Cancer

The metabolic rearrangements of hepatic metabolism associated with liver cancer are still incompletely understood. There is an ongoing need to identify novel and more efficient diagnostic biomarkers and therapeutic targets based on the metabolic mechanisms of these diseases. In comparison to traditional diagnostic biomarkers, metabolomics is a comprehensive technique for discovering chemical signatures for liver cancer screening, prediction, and earlier diagnosis. Lipids are a large and diverse group of complex biomolecules that are at the heart of liver physiology and play an important role in the development and progression of cancer. In this chapter, we described two detailed protocols for targeted lipids analysis: glycerophospholipids and mono, di, tri-acylglycerides, both by Flow Injection Analysis (FIA) HPLC coupled to a SelexIon/QTRAP 6500+ system. These approaches provide a targeted lipidomic metabolomic signature of dissimilar metabolic disorders affecting liver cancers.

Analysis of clinical significance and molecular characteristics of methionine metabolism and macrophage-related patterns in hepatocellular carcinoma based on machine learning

BACKGROUND

Increasing evidence has indicated that abnormal methionine metabolic activity and tumour-associated macrophage infiltration are correlated with hepatocarcinogenesis. However, the relationship between methionine metabolic activity and tumour-associated macrophage infiltration is unclear in hepatocellular carcinoma, and it contributes to the occurrence and clinical outcome of hepatocellular carcinoma (HCC). Thus, we systematically analysed the expression patterns of methionine metabolism and macrophage infiltration in hepatocellular carcinoma using bioinformatics and machine learning methods and constructed novel diagnostic and prognostic models of HCC.

METHODS

In this study, we first mined the four largest HCC mRNA microarray datasets with patient clinical data in the GEO database, including 880 tissue mRNA expression datasets. Using GSVA analysis and the CIBERSORT and EPIC algorithms, we quantified the methionine metabolic activity and macrophage infiltration degree of each sample. WGCNA was used to identify the gene modules most related to methionine metabolism and tumour-associated macrophage infiltration in HCC. The KNN algorithm was used to cluster gene expression patterns in HCC. Random forest, logistic regression, Cox regression analysis and other algorithms were used to construct the diagnosis and prognosis model of HCC. The above bioinformatics analysis results were also verified by independent datasets (TCGA-LIHC, ICGC-JP and CPTAC datasets) and immunohistochemical fluorescence based on our external HCC panel. Furthermore, we carried out pancancer analysis to verify the specificity of the above model and screened a wide range of drug candidates.

RESULTS

We identified two methionine metabolism and macrophage infiltration expression patterns, and their prognoses were different in hepatocellular carcinoma. We constructed novel diagnostic and prognostic models of hepatocellular carcinoma with good diagnostic efficacy and differentiation ability.

CONCLUSIONS

Methionine metabolism is closely related to tumour-associated macrophage infiltration in hepatocellular carcinoma and can help in the clinical diagnosis and prognosis of HCC.

Exosome-Related FTCD Facilitates M1 Macrophage Polarization and Impacts the Prognosis of Hepatocellular Carcinoma

BACKGROUND

Exosomes are essential for hepatocellular carcinoma (HCC) progression and have garnered significant interest as novel targets for diagnostic, prognostic, and therapeutic approaches. This study aims to identify potential exosome-related biomarkers for the development of useful strategies for HCC diagnosis and therapy.

METHODS

Three datasets obtained from the Gene Expression Omnibus (GEO) were utilized to identify differentially expressed genes (DEGs) in HCC. Through Gene Ontology (GO) analysis and protein-protein interaction (PPI) network, overall survival (OS) analysis, Cox analyses, and diethylnitrosamine (DEN)-induced HCC mouse model detection, exosome-related hub gene was screened out, followed by a prognostic value assessment and immune-correlates analysis based on the Cancer Genome Atlas (TCGA) dataset. The hub gene-containing exosomes derived from Hepa1-6 cells were isolated and characterized using differential ultracentrifugation, transmission electron microscopy scanning, and Western blot. Ultrasound-guided intrahepatic injection, cell co-culture, CCK-8, and flow cytometry were performed to investigate the effects of the hub gene on macrophage infiltration and polarization in HCC.

RESULTS

A total of 83 DEGs enriched in the extracellular exosome term, among which, FTCD, HRA, and C8B showed the strongest association with the progression of HCC. FTCD was independently associated with a protective effect in HCC and selected as the hub gene. The presence of FTCD in exosomes was confirmed. FTCD-stimulated macrophages were polarized towards the M1 type and suppressed HCC cells proliferation.

CONCLUSIONS

FTCD is a potential exosome-related biomarker for HCC diagnosis, prognosis, and treatment. The crosstalk between FTCD-containing exosomes and macrophages in HCC progression deserves further investigation.

Semaglutide reduces tumor burden in the GAN diet-induced obese and biopsy-confirmed mouse model of NASH-HCC with advanced fibrosis

Non-alcoholic steatohepatitis (NASH) is emerging as a major cause of hepatocellular carcinoma (HCC), however, it is not resolved if compounds in late-stage clinical development for NASH may have additional therapeutic benefits in NASH-driven HCC (NASH-HCC). Here, we profiled monotherapy with semaglutide (glucagon-like-receptor-1 receptor agonist) and lanifibranor (pan-peroxisome proliferator-activated receptor agonist) in a diet-induced obese (DIO) mouse model of NASH-HCC. Disease progression was characterized in male C57BL/6 J mice fed the GAN (Gubra Amylin NASH) diet high in fat, fructose and cholesterol for 12-72 weeks (n = 15 per group). Other GAN DIO-NASH-HCC mice fed the GAN diet for 54 weeks and with biopsy-confirmed NASH (NAFLD Activity Score ≥ 5) and advanced fibrosis (stage F3) received vehicle (n = 16), semaglutide (30 nmol/kg, s.c., n = 15), or lanifibranor (30 mg/kg, p.o., n = 15) once daily for 14 weeks. GAN DIO-NASH-HCC mice demonstrated progressive NASH, fibrosis and HCC burden. Tumors presented with histological and molecular signatures of poor prognostic HCC. Consistent with clinical trial outcomes in NASH patients, both lanifibranor and semaglutide improved NASH while only lanifibranor reduced fibrosis in GAN DIO-NASH-HCC mice. Notably, only semaglutide reduced tumor burden in GAN DIO-NASH-HCC mice. In conclusion, the GAN DIO-NASH-HCC mouse is a clinical translational model of NASH-HCC. Semaglutide improves both NASH and tumor burden in GAN DIO-NASH-HCC mice, highlighting the suitability of this preclinical model for profiling novel drug therapies targeting NASH-HCC.

Mechanism-guided fine-tuned microbiome potentiates anti-tumor immunity in HCC

Microbiome, including bacteria, fungi, and viruses, plays a crucial role in shaping distal and proximal anti-tumor immunity. Mounting evidence showed that commensal microbiome critically modulates immunophenotyping of hepatocellular carcinoma (HCC), a leading cause of cancer-related death. However, their role in anti-tumor surveillance of HCC is still poorly understood. Herein, we spotlighted growing interests in how the microbiome influences the progression and immunotherapeutic responses of HCC via changing local tumor microenvironment (TME) upon translocating to the sites of HCC through different "cell-type niches". Moreover, we summarized not only the associations but also the deep insight into the mechanisms of how the extrinsic microbiomes interplay with hosts to shape immune surveillance and regulate TME and immunotherapeutic responses. Collectively, we provided a rationale for a mechanism-guided fine-tuned microbiome to be neoadjuvant immunotherapy in the near future.

Pan-viral serology uncovers distinct virome patterns as risk predictors of hepatocellular carcinoma and intrahepatic cholangiocarcinoma

This study evaluates the pan-serological profiles of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA) compared to several diseased and non-diseased control populations to identify risk factors and biomarkers of liver cancer. We used phage immunoprecipitation sequencing, an anti-viral antibody screening method using a synthetic-phage-displayed human virome epitope library, to screen patient serum samples for exposure to over 1,280 strains of pathogenic and non-pathogenic viruses. Using machine learning methods to develop an HCC or iCCA viral score, we discovered that both viral scores were positively associated with several liver function markers in two separate at-risk populations independent of viral hepatitis status. The HCC score predicted all-cause mortality over 8 years in patients with chronic liver disease at risk of HCC, while the viral hepatitis status was not predictive of survival. These results suggest that non-hepatitis viral infections may contribute to HCC and iCCA development and could be biomarkers in at-risk populations.

Multiomics characterization of fatty acid metabolism for the clinical management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a prevalent malignancy and there is a lack of effective biomarkers for HCC diagnosis. Living organisms are complex, and different omics molecules interact with each other to implement various biological functions. Genomics and metabolomics, which are the top and bottom of systems biology, play an important role in HCC clinical management. Fatty acid metabolism is associated with malignancy, prognosis, and immune phenotype in cancer, which is a potential hallmark in malignant tumors. In this study, the genes and metabolites related to fatty acid metabolism were thoroughly investigated by a dynamic network construction algorithm named EWS-DDA for the early diagnosis and prognosis of HCC. Three gene ratios and eight metabolite ratios were identified by EWS-DDA as potential biomarkers for HCC clinical management. Further analysis using biological analysis, statistical analysis and document validation in the discovery and validation sets suggested that the selected potential biomarkers had great clinical prognostic value and helped to achieve effective early diagnosis of HCC. Experimental results suggested that in-depth evaluation of fatty acid metabolism from different omics viewpoints can facilitate the further understanding of pathological alterations associated with HCC characteristics, improving the performance of early diagnosis and clinical prognosis.

Construction and validation of a novel lysosomal signature for hepatocellular carcinoma prognosis, diagnosis, and therapeutic decision-making

Lysosomes is a well-recognized oncogenic driver and chemoresistance across variable cancer types, and has been associated with tumor invasiveness, metastasis, and poor prognosis. However, the significance of lysosomes in hepatocellular carcinoma (HCC) is not well understood. Lysosomes-related genes (LRGs) were downloaded from Genome Enrichment Analysis (GSEA) databases. Lysosome-related risk score (LRRS), including eight LRGs, was constructed via expression difference analysis (DEGs), univariate and LASSO-penalized Cox regression algorithm based on the TCGA cohort, while the ICGC cohort was obtained for signature validation. Based on GSE149614 Single-cell RNA sequencing data, model gene expression and liver tumor niche were further analyzed. Moreover, the functional enrichments, tumor microenvironment (TME), and genomic variation landscape between LRRSlow/LRRShigh subgroup were systematically investigated. A total of 15 Lysosomes-related differentially expressed genes (DELRGs) in HCC were detected, and then 10 prognosis DELRGs were screened out. Finally, the 8 optimal DELRGs (CLN3, GBA, CTSA, BSG, APLN, SORT1, ANXA2, and LAPTM4B) were selected to construct the LRRS prognosis signature of HCC. LRRS was considered as an independent prognostic factor and was associated with advanced clinicopathological features. LRRS also proved to be a potential marker for HCC diagnosis, especially for early-stage HCC. Then, a nomogram integrating the LRRS and clinical parameters was set up displaying great prognostic predictive performance. Moreover, patients with high LRRS showed higher tumor stemness, higher heterogeneity, and higher genomic alteration status than those in the low LRRS group and enriched in metabolism-related pathways, suggesting its underlying role in the progression and development of liver cancer. Meanwhile, the LRRS can affect the proportion of immunosuppressive cell infiltration, making it a vital immunosuppressive factor in the tumor microenvironment. Additionally, HCC patients with low LRRS were more sensitive to immunotherapy, while patients in the high LRRS group responded better to chemotherapy. Upon single-cell RNA sequencing, CLN3, GBA, and LAPTM4B were found to be specially expressed in hepatocytes, where they promoted cell progression. Finally, RT-qPCR and external datasets confirmed the mRNA expression levels of model genes. This study provided a direct links between LRRS signature and clinical characteristics, tumor microenvironment, and clinical drug-response, highlighting the critical role of lysosome in the development and treatment resistance of liver cancer, providing valuable insights into the prognosis prediction and treatment response of HCC, thereby providing valuable insights into prognostic prediction, early diagnosis, and therapeutic response of HCC.

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.

Near-infrared imaging of hepatocellular carcinoma and its medicinal treatment with a γ-glutamyl transpeptidase-monitoring fluorescence probe

Herein, the Near-infrared imaging of hepatocellular carcinoma (HCC) and its medicinal treatment was achieved with a γ-glutamyl transpeptidase (GGT)-monitoring fluorescence probe KYZ-GGT which consisted of the typical recognition group γ-glutamyl and the structurally modified signal reporting group hemicyanine-thioxanthene. Compared with the recently reported probes, KYZ-GGT suggested practical and steady capability for monitoring the GGT level in the cellular, xenograft, induced as well as medicinal treatment HCC models. It realized the mitochondrial targeting intracellular imaging to reflect the GGT dynamics in the induction or medicinal treatment of HCC. In the xenograft and induced model mice with multiple factors, KYZ-GGT showed stable performance for visualizing the HCC status. In the medicinal treatment of the long-period-induced HCC model mice verified by the serum indexes and histopathological analysis, KYZ-GGT successfully imaged the medicinal treatment process of HCC with two marketed drugs (Sorafenib and Lenvatinib) respectively, with an applicative penetration depth. The information here was meaningful for investigating effective medicinal strategies for overcoming HCC.

Hepatocellular carcinoma surveillance - utilization, barriers and the impact of changing aetiology

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide. Surveillance for HCC is critical for early detection and treatment, but fewer than one-quarter of individuals at risk of HCC undergo surveillance. Multiple failures across the screening process contribute to the underutilization of surveillance, including limited disease awareness among patients and health-care providers, knowledge gaps, and difficulty recognizing patients who are at risk. Non-alcoholic fatty liver disease and alcohol-associated liver disease are the fastest-rising causes of HCC-related death worldwide and are associated with unique barriers to surveillance. In particular, more than one-third of patients with HCC related to non-alcoholic fatty liver disease do not have cirrhosis and therefore lack a routine indication for HCC surveillance on the basis of current practice guidelines. Semi-annual abdominal ultrasound with measurement of α-fetoprotein levels is recommended for HCC surveillance, but the sensitivity of this approach for early HCC is limited, especially for patients with cirrhosis or obesity. In this Review, we discuss the current status of HCC surveillance and the remaining challenges, including the changing aetiology of liver disease. We also discuss strategies to improve the utilization and quality of surveillance for HCC.

Development and validation of a model to predict the risk of distant metastases from hepatocellular carcinoma: a real-world retrospective study

PURPOSE

This study aimed to construct a novel clinical prediction model to predict the risk of distant metastases (DM) in hepatocellular carcinoma (HCC).

METHODS

We included 3869 HCC patients, comprising 3076 patients from the Surveillance, Epidemiology, and End Results (SEER) database and 793 patients from a hospital in China. Variables with a P-value < 0.05 in the univariate logistic analysis were entered into the multivariate analysis to determine the independent predictive factors for DM in HCC. A nomogram was created based on the independent predictive factors. The predictive performance of the model was assessed using the receiver operating characteristics (ROCs) curve, decision curve analysis (DCA), calibration curves, and clinical impact curve analysis (CIC). Additionally, we developed a user-friendly web-based calculator based on the model.

RESULTS

The multivariate logistic regression analysis revealed that tumor size (P < 0.001), type of treatment (P < 0.001), T stage (P = 0.001), N stage (P < 0.001), and grade (P = 0.043) were identified as independent predictive factors. A nomogram was constructed based on these factors. The area under the ROC curves (AUC) value was 0.845 (95% CI 0.815-0.874) for the training set, 0.818 (95% CI 0.774-0.863) for the internal validation set, and 0.823 (95% CI 0.770-0.876) for the external validation set. Moreover, DCA analysis, calibration curves, and CIC analysis demonstrated the favorable predictive performance of the nomogram. Finally, a more user-friendly web-based calculator was developed.

CONCLUSION

We developed a nomogram and showed its favorable predictive performance in predicting DM in HCC. Furthermore, we developed a more user-friendly web-based calculator, which has the potential to aid clinicians in individualized diagnosis and make better clinical decisions for HCC patients.

CENPB promotes the proliferation of hepatocellular carcinoma and is directly regulated by miR-29a

Hepatocellular carcinoma (HCC) is a significant global health concern as it ranks as the sixth most common malignant tumor and the third leading cause of cancer-related deaths. In this study, we analyzed the expression of centromere protein B (CENPB) mRNA in HCC using TCGA and GEO datasets. Immunohistochemistry (IHC) was performed to determine CENPB protein levels in 490 HCC patients. Our findings revealed higher expression of CENPB mRNA in HCC tissues across the three datasets. Additionally, as the pathological stage and histological grade advanced, CENPB expression increased. Patients with elevated levels of CENPB mRNA and protein demonstrated shorter overall survival (OS) and recurrence-free survival (OS). Notably, CENPB protein showed prognostic value in patients with stage I/II, AFP levels below 400 ng/ml, and tumor size less than 5 cm. Using multivariate regression analysis in 490 HCC patients, we developed nomograms to predict 1-year, 3-year, and 5-year OS and RFS. Knockdown of CENPB in Hep3B and MHCC97 cell lines resulted in significant inhibition of cell proliferation and invasion. Furthermore, bioinformatics analysis identified miR-29a as a potential negative regulator of CENPB expression, which was validated through a dual-luciferase reporter assay. In conclusion, our findings suggest that CENPB may serve as an oncogenic factor in HCC and is directly regulated by miR-29a, highlighting its potential as a promising therapeutic target.

Integrative analysis reveals that SLC38A1 promotes hepatocellular carcinoma development via PI3K/AKT/mTOR signaling via glutamine mediated energy metabolism

Although hepatocellular carcinoma (HCC) is rather frequent, little is known about the molecular pathways underlying its development, progression, and prognosis. In the current study, we comprehensively analyzed the deferentially expressed metabolism-related genes (MRGs) in HCC based on TCGA datasets attempting to discover the potentially prognostic genes in HCC. The up-regulated MRGs were further subjected to analyze their prognostic values and protein expressions. Twenty-seven genes were identified because their high expressions were significant in OS, PFS, DFS, DSS, and HCC tumor samples. They were then used for GO, KEGG, methylation, genetics changes, immune infiltration analyses. Moreover, we established a prognostic model in HCC using univariate assays and LASSO regression based on these MRGs. Additionally, we also found that SLC38A1, an amino acid metabolism closely related transporter, was a potential prognostic gene in HCC, and its function in HCC was further studied using experiments. We found that the knockdown of SLC38A1 notably suppressed the growth and migration of HCC cells. Further studies revealed that SLC38A1 modulated the development of HCC cells by regulating PI3K/AKT/mTOR signaling via glutamine mediated energy metabolism. In conclusion, this study identified the potentially prognostic MRGs in HCC and uncovered that SLC38A1 regulated HCC development and progression by regulating PI3K/AKT/mTOR signaling via glutamine mediated energy metabolism, which might provide a novel marker and potential therapeutic target in HCC.

Enhanced NIR-II Fluorescent Lateral Flow Biosensing Platform Based on Supramolecular Host-Guest Self-Assembly for Point-of-Care Testing of Tumor Biomarkers

Point-of-care detection of tumor biomarkers with high sensitivity remains an enormous challenge in the early diagnosis and mass screening of cancer. Fluorescent lateral flow immunoassay (LFA) is an attractive platform for point-of-care testing due to its inherent advantages. Particularly, a fluorescent probe is crucial to improving the analytical performance of the LFA platform. Herein, we developed an enhanced second near-infrared (NIR-II) LFA (ENIR-II LFA) platform based on supramolecular host-guest self-assembly for detection of the prostate-specific antigen (PSA) as a model analyte. In this platform, depending on the effective supramolecular surface modification strategy, cucurbit[7]uril (CB[7])-covered rare-earth nanoparticles (RENPs) emitting in the NIR-II (1000-1700 nm) window were prepared and employed as an efficient fluorescent probe (RENPs-CB[7]). Benefiting from its superior optical properties, such as low autofluorescence, excellent photostability, enhanced fluorescence intensity, and increased antibody-conjugation efficiency, the ENIR-II LFA platform displayed a wide linear detection range from 0.65 to 120 ng mL-1, and the limit of detection was down to 0.22 ng mL-1 for PSA, which was 18.2 times lower than the clinical cutoff value. Moreover, the testing time was also shortened to 6 min. Compared with the commercial visible fluorescence LFA kit (VIS LFA) and the previously reported NIR-II LFA based on a RENPs-PAA probe, this ENIR-II LFA demonstrated more competitive advantages in analytical sensitivity, detection range, testing time, and production cost. Overall, the ENIR-II LFA platform offers great potential for the highly sensitive, rapid, and convenient detection of tumor biomarkers and is expected to serve as a useful technique in the general population screening of the high-incidence cancer region.

Nuclear respiratory factor 1 drives hepatocellular carcinoma progression by activating LPCAT1-ERK1/2-CREB axis

BACKGROUND

Nuclear respiratory factor 1 (NRF1) is a transcription factor that participates in several kinds of tumor, but its role in hepatocellular carcinoma (HCC) remains elusive. This study aims to explore the role of NRF1 in HCC progression and investigate the underlying mechanisms.

RESULTS

NRF1 was overexpressed and hyperactive in HCC tissue and cell lines and high expression of NRF1 indicated unfavorable prognosis of HCC patients. NRF1 promoted proliferation, migration and invasion of HCC cells both in vitro and in vivo. Mechanistically, NRF1 activated ERK1/2-CREB signaling pathway by transactivating lysophosphatidylcholine acyltransferase 1 (LPCAT1), thus promoting cell cycle progression and epithelial mesenchymal transition (EMT) of HCC cells. Meanwhile, LPCAT1 upregulated the expression of NRF1 by activating ERK1/2-CREB signaling pathway, forming a positive feedback loop.

CONCLUSIONS

NRF1 is overexpressed in HCC and promotes HCC progression by activating LPCAT1-ERK1/2-CREB axis. NRF1 is a promising therapeutic target for HCC patients.

Construction of a Novel Cuproptosis-Related ceRNA Network-SNHG3/miR-1306-5p/PDHA1 and Identification of SNHG3 as a Prognostic Biomarker in Hepatocellular Carcinoma

The crucial role of competitive endogenous RNA (ceRNA) in the malignant biological behavior of tumors has been certificated. Nevertheless, the detailed function and molecular mechanism of ceRNA associated with cuproptosis in hepatocellular carcinoma (HCC) remains dismal. In this study, we first constructed a protein-protein interaction network and identified the module with the highest degree of aggregation degree. DLAT and PDHA1 were screened out of the module after differential expression and survival analysis. Next, we reverse-predicted the upstream miRNA and lncRNA from mRNA (DLAT, PDHA1) and successfully established the ceRNA network-SNHG3/miR-1306-5p/PDHA1. SNHG3 was identified to be an independent prognostic biomarker based on the outcome of univariate and multivariate Cox analyses. Subsequently, we implemented methylation, immune infiltration, and drug sensitivity analysis to investigate the potential biological functions of SNHG3 in HCC. In addition, SNHG3 expression was upregulated in liver cancer cell lines. In vitro functional assay revealed that SNHG3 knockdown significantly attenuated proliferation, migration, and invasion of liver cancer cells. In summary, SNHG3 exhibited oncogenic characterization via sponging miR-1306-5p to regulate PDHA1, which might function as a promising prognostic indicator and a potential therapeutic target for HCC and shed new light on the molecular mechanism of HCC progression.

Gut microbial signatures of patients with primary hepatocellular carcinoma and their healthy first-degree relatives

AIMS

The gut microbiome has been recognized as a significant contributor to primary hepatocellular carcinoma (HCC), with mounting evidence indicating associations between bacterial components and cancers of the digestive system.

METHODS AND RESULTS

Here, to characterize gut bacterial signature in patients with primary HCC and to assess the diagnostic potential of bacterial taxa for primary HCC, 21 HCC patients and 21 healthy first-degree relatives (control group) were enrolled in this study. Bacterial DNA in the fecal samples was quantified by 16S rRNA gene sequencing. We found that 743 operational taxonomic units (OTUs) were shared between patients with primary HCC and healthy controls. Of these, 197 OTUs were unique to patients with primary HCC, while 95 OTUs were unique to healthy subjects. Additionally, we observed significant differences in the abundance of Ruminococcaceae_UCG-014 and Romboutsia between patients with primary HCC and their healthy first-degree relatives. Besides, the relative abundance of Ruminococcaceae_UCG-014 and Prevotella_9 was positively correlated with physiological indicators including AST, ALT, ALB, or TBIL. Signature bacterial taxa could serve as non-invasive biomarkers, of which Romboutsia and Veillonella were identified as differential taxa in fecal samples from patients with HCC compared to healthy controls. Romboutsia showed a strong association with HCC (AUC = 0.802). Additionally, the combination of Romboutsia and Veillonella (AUC = 0.812) or the grouping of Fusobacterium, Faccalibacterium, and Peptostreptococcacae together (AUC = 0.762) exhibited promising outcomes for the diagnosis of HCC.

CONCLUSIONS

The composition of gut microbes in patients with HCC was found to be significantly altered. Differential taxa Romboutsia, Veillonella, and Peptostreptococcacae could be tested for identification of HCC.

HDAC11: A novel target for improved cancer therapy

Histone deacetylase 11 (HDAC11) is a unique member of the histone deacetylase family that plays an important role in the regulation of gene expression and protein function. In recent years, research on the role of HDAC11 in tumors has attracted increasing attention. This review summarizes the current knowledge on the subcellular localization, structure, expression, and functions of HDAC11 in tumors, as well as the regulatory mechanisms involved in its network, including ncRNA and substrates. Moreover, we focus on the progress made in targeting HDAC11 to overcome tumor therapy resistance, and the development of HDAC11 inhibitors for cancer treatment. Collectively, this review provides comprehensive insights into the potential clinical implications of HDAC11 for cancer therapy.

Identification of a brand intratumor microbiome signature for predicting prognosis of hepatocellular carcinoma

PURPOSE

Given that prognosis of hepatocellular carcinoma (HCC) differs dramatically, it is imperative to uncover effective and available prognostic biomarker(s). The intratumor microbiome plays a significant role in the response to tumor microenvironment, we aimed to identify an intratumor microbiome signature for predicting the prognosis of HCC patients accurately and investigate its possible mechanisms subsequently.

METHODS

The TCGA HCC microbiome data (TCGA-LIHC-microbiome) was downloaded from cBioPortal. To create an intratumor microbiome-related prognostic signature, univariate and multivariate Cox regression analyses were used to quantify the association of microbial abundance and patients' overall survival (OS), as well as their diseases specific survival (DSS). The performance of the scoring model was evaluated by the area under the ROC curve (AUC). Based on the microbiome-related signature, clinical factors, and multi-omics molecular subtypes on the basis of "icluster" algorithm, nomograms were established to predict OS and DSS. Patients were further clustered into three subtypes based on their microbiome-related characteristics by consensus clustering. Moreover, deconvolution algorithm, weighted correlation network analysis (WGCNA) and gene set variation analysis (GSVA) were used to investigate the potential mechanisms.

RESULTS

In TCGA LIHC microbiome data, the abundances of 166 genera among the total 1406 genera were considerably associated with HCC patients' OS. From that filtered dataset we identified a 27-microbe prognostic signature and developed a microbiome-related score (MRS) model. Compared with those in the relatively low-risk group, patients in higher-risk group own a much worse OS (P < 0.0001). Besides, the time-dependent ROC curves with MRS showed excellent predictive efficacy both in OS and DSS. Moreover, MRS is an independent prognostic factor for OS and DSS over clinical factors and multi-omics-based molecular subtypes. The integration of MRS into nomograms significantly improved the efficacy of prognosis prediction (1-year AUC:0.849, 3-year AUC: 0.825, 5-year AUC: 0.822). The analysis of microbiome-based subtypes on their immune characteristics and specific gene modules inferred that the intratumor microbiome may affect the HCC patients' prognosis via modulating the cancer stemness and immune response.

CONCLUSION

MRS, a 27 intratumor microbiome-related prognostic model, was successfully established to predict HCC patients overall survive independently. And the possible underlying mechanisms were also investigated to provide a potential intervention strategy.

An offline to online cognitive behavioral stress management caring program effectively improves psychological pressure, spiritual well-being, and quality of life in postoperative hepatocellular carcinoma patients

BACKGROUND

This study designed an offline to online cognitive behavioral stress management (OOCBSM) caring program, intending to investigate its effect on mental health and quality of life (QoL) using multiple scales in postoperative hepatocellular carcinoma (HCC) patients.

METHODS

254 postoperative HCC patients were randomly (1:1) allocated into OOCBSM (included a 10-week offline CBSM and subsequent online CBSM until M6) and normal care (NC) groups (10-week NC). Hospital anxiety-and-depression scale (HADS), Zung's self-reporting anxiety (SAS) and depression scale (SDS), FACIT-SP, European quality-of-life-5 dimensions (EQ-5D), and quality-of-life questionnaire-core30 (QLQ-C30) were assessed over 6 months (M).

RESULTS

HADS-defined-anxiety rates at M3 (P = 0.036) and M6 (P = 0.025), SAS-defined-anxiety rate at M6 (P = 0.049), HADS-defined-depression rates at M3 (P = 0.026) and M6 (P = 0.049), and SDS-defined-depression rates at M3 (P = 0.015) and M6 (P = 0.043) were all lower in OOCBSM group compared to NC group. Furthermore, FACIT-SP scores at M1 (P = 0.004), M3 (P = 0.003), and M6 (P<0.001) were higher in OOCBSM group compared with NC group. EQ-5D scores at M1 (P = 0.025) and M3 (P = 0.030) but not M6 (P = 0.128), and QLQ-C30-symptom score at M3 (P = 0.014) but not M1 (P = 0.198) and M6 (P = 0.058) were lower in OOCBSM group versus NC group; QLQ-C30-global-health-status scores at M3 (P = 0.027) and M6 (P = 0.001) but not M1 (P = 0.312), QLQ-C30-function scores at M3 (P = 0.005) and M6 (P = 0.001) but not M1 (P = 0.084) were higher in OOCBSM group versus NC group. Patients with younger ages or higher education benefited more from OOCBSM.

CONCLUSION

OOCBSM improves psychological pressure, spiritual well-being, and QoL in postoperative HCC patients, especially in those with younger ages or higher education.

Novel, high accuracy models for hepatocellular carcinoma prediction based on longitudinal data and cell-free DNA signatures

BACKGROUND & AIMS

Current hepatocellular carcinoma (HCC) risk scores do not reflect changes in HCC risk resulting from liver disease progression/regression over time. We aimed to develop and validate two novel prediction models using multivariate longitudinal data, with or without cell-free DNA (cfDNA) signatures.

METHODS

A total of 13,728 patients from two nationwide multicenter prospective observational cohorts, the majority of whom had chronic hepatitis B, were enrolled. aMAP score, as one of the most promising HCC prediction models, was evaluated for each patient. Low-pass whole-genome sequencing was used to derive multi-modal cfDNA fragmentomics features. A longitudinal discriminant analysis algorithm was used to model longitudinal profiles of patient biomarkers and estimate the risk of HCC development.

RESULTS

We developed and externally validated two novel HCC prediction models with a greater accuracy, termed aMAP-2 and aMAP-2 Plus scores. The aMAP-2 score, calculated with longitudinal data on the aMAP score and alpha-fetoprotein values during an up to 8-year follow-up, performed superbly in the training and external validation cohorts (AUC 0.83-0.84). The aMAP-2 score showed further improvement and accurately divided aMAP-defined high-risk patients into two groups with 5-year cumulative HCC incidences of 23.4% and 4.1%, respectively (p = 0.0065). The aMAP-2 Plus score, which incorporates cfDNA signatures (nucleosome, fragment and motif scores), optimized the prediction of HCC development, especially for patients with cirrhosis (AUC 0.85-0.89). Importantly, the stepwise approach (aMAP -> aMAP-2 -> aMAP-2 Plus) stratified patients with cirrhosis into two groups, comprising 90% and 10% of the cohort, with an annual HCC incidence of 0.8% and 12.5%, respectively (p <0.0001).

CONCLUSIONS

aMAP-2 and aMAP-2 Plus scores are highly accurate in predicting HCC. The stepwise application of aMAP scores provides an improved enrichment strategy, identifying patients at a high risk of HCC, which could effectively guide individualized HCC surveillance.

IMPACT AND IMPLICATIONS

In this multicenter nationwide cohort study, we developed and externally validated two novel hepatocellular carcinoma (HCC) risk prediction models (called aMAP-2 and aMAP-2 Plus scores), using longitudinal discriminant analysis algorithm and longitudinal data (i.e., aMAP and alpha-fetoprotein) with or without the addition of cell-free DNA signatures, based on 13,728 patients from 61 centers across mainland China. Our findings demonstrated that the performance of aMAP-2 and aMAP-2 Plus scores was markedly better than the original aMAP score, and any other existing HCC risk scores across all subsets, especially for patients with cirrhosis. More importantly, the stepwise application of aMAP scores (aMAP -> aMAP-2 -> aMAP-2 Plus) provides an improved enrichment strategy, identifying patients at high risk of HCC, which could effectively guide individualized HCC surveillance.

Exploiting targeted nanomedicine for surveillance, diagnosis, and treatment of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the cancers that has the highest morbidity and mortality rates. In clinical practice, there are still many limitations in surveilling, diagnosing, and treating HCC, such as the poor detection of early HCC, the frequent post-surgery recurrence, the low local tumor control rate, the therapy resistance and side effects. Therefore, improved, or innovative modalities are urgently required for early diagnosis as well as refined and effective management. In recent years, nanotechnology research in the field of HCC has received great attention, with various aspects of diagnosis and treatment including biomarkers, ultrasound, diagnostic imaging, intraoperative imaging, ablation, transarterial chemoembolization, radiotherapy, and systemic therapy. Different from previous reviews that discussed from the perspective of nanoparticles' structure, design and function, this review systematically summarizes the methods and limitations of diagnosing and treating HCC in clinical guidelines and practices, as well as nanomedicine applications. Nanomedicine can overcome the limitations to improve diagnosis accuracy and therapeutic effect via enhancement of targeting, biocompatibility, bioavailability, controlled releasing, and combination of different clinical treatment modalities. Through an in-depth understanding of the logic of nanotechnology to conquer clinical limitations, the main research directions of nanotechnology in HCC are sorted out in this review. It is anticipated that nanomedicine will play a significant role in the future clinical practices of HCC.

Nanoprobe-based molecular imaging for tumor stratification

The responses of patients to tumor therapies vary due to tumor heterogeneity. Tumor stratification has been attracting increasing attention for accurately distinguishing between responders to treatment and non-responders. Nanoprobes with unique physical and chemical properties have great potential for patient stratification. This review begins by describing the features and design principles of nanoprobes that can visualize specific cell types and biomarkers and release inflammatory factors during or before tumor treatment. Then, we focus on the recent advancements in using nanoprobes to stratify various therapeutic modalities, including chemotherapy, radiotherapy (RT), photothermal therapy (PTT), photodynamic therapy (PDT), chemodynamic therapy (CDT), ferroptosis, and immunotherapy. The main challenges and perspectives of nanoprobes in cancer stratification are also discussed to facilitate probe development and clinical applications.

Extracellular Vesicles in Hepatocellular Carcinoma: Progress and Challenges in the Translation from the Laboratory to Clinic

Extracellular vesicles (EVs) play critical roles in intercellular communication by transporting bioactive cargo to recipient cells. EVs have been implicated in a range of physiological and pathological processes, including tumor progression, metastasis, immune modulation, and drug resistance. The objective of this review is to present a thorough overview of recent studies focusing on EVs in hepatocellular carcinoma (HCC), with an emphasis on their potential utility as diagnostic biomarkers as well as therapeutic agents. Initially, we explore the utility of EVs as diagnostic biomarkers for HCC, followed by a discussion of their potential as carriers of therapeutic payloads. Additionally, we delve into the emerging field of therapeutic EVs for modulating tumor immune responses. Through this review, our ultimate aim is to provide a comprehensive understanding of the opportunities and challenges in the clinical translation of EV research in the domain of HCC.

Revolutionising hepatocellular carcinoma surveillance: Harnessing contrast-enhanced ultrasound and serological indicators for postoperative early recurrence prediction

This study aimed to develop a noninvasive predictive model for identifying early postoperative recurrence of hepatocellular carcinoma (within 2 years after surgery) based on contrast-enhanced ultrasound and serum biomarkers. Additionally, the model's validity was assessedthrough internal and external validation. Clinical data were collected from patients who underwent liver resection at the First Hospital of Quanzhou and Mengchao Hepatobiliary Hospital. The data included general information, contrast-enhanced ultrasound parameters, Liver Imaging Reporting and Data System (LI-RADS) classification, and serum biomarkers. The data from Mengchao Hospital were divided into 2 groups, with a ratio of 6:4, to form the modeling and internal validation sets, respectively. On the other hand, the data from the First Hospital of Quanzhou served as the external validation group. The developed model was named the Hepatocellular Carcinoma Early Recurrence (HCC-ER) prediction model. The predictive efficiency of the HCC-ER model was compared with other established models. The baseline characteristics were found to be well-balanced across the modeling, internal validation, and external validation groups. Among the independent risk factors identified for early recurrence, LI-RADS classification, alpha-fetoprotein, and tumor maximum diameter exhibited hazard ratios of 1.352, 1.337, and 1.135 respectively. Regarding predictive accuracy, the HCC-ER, Tumour-Node-Metastasis, Barcelona Clinic Liver Cancer, and China Liver Cancer models demonstrated prediction errors of 0.196, 0.204, 0.201, and 0.200 in the modeling group; 0.215, 0.215, 0.218, and 0.212 in the internal validation group; 0.210, 0.215, 0.216, and 0.221 in the external validation group. Using the HCC-ER model, risk scores were calculated for all patients, and a cutoff value of 50 was selected. This cutoff effectively distinguished the high-risk recurrence group from the low-risk recurrence group in the modeling, internal validation, and external validation groups. However, the calibration curve of the predictive model slightly overestimated the risk of recurrence. The HCC-ER model developed in this study demonstrated high accuracy in predicting early recurrence within 2 years after hepatectomy. It provides valuable information for developing precise treatment strategies in clinical practice and holds considerable promise for further clinical implementation.

Development and validation of a nomogram to predict the recurrence of hepatocellular carcinoma patients with dynamic changes in AFP undergoing locoregional treatments

Background

Serum alpha-fetoprotein (AFP) is an important clinical indicator for screening, diagnosis, and prognosis of primary hepatocellular carcinoma (HCC). Our team's previous study showed that patients with negative AFP at baseline and positive AFP at relapse had a worse prognosis (N-P). Therefore, the aim of our study was to develop and validate a nomogram for this group of patients.

Methods

A total of 513 patients with HCC who received locoregional treatments at Beijing You'an Hospital, Capital Medical University, from January 2012 to December 2019 were prospectively enrolled. Patients admitted from 2012 to 2015 were assigned to the training cohort (n = 335), while 2016 to 2019 were in the validation cohort (n =183). The clinical and pathological features of patients were collected, and independent risk factors were identified using univariate and multivariate Cox regression analysis as a basis for developing a nomogram. The performance of the nomogram was evaluated by C-index, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) curves in the training and validation cohorts.

Results

The content of the nomogram includes gender, tumor number, tumor size, lymphocyte, direct bilirubin (DBIL), gamma-glutamyl transferase (GGT), and prealbumin. The C-index (0.717 and 0.752) and 1-, 3-, and 5-year AUCs (0.721, 0.825, 0.845, and 0.740, 0.868, 0.837) of the training and validation cohorts proved the good predictive performance of the nomogram. Calibration curves and DCA curves suggested accuracy and net clinical benefit rates. The nomogram enabled to classify of patients with dynamic changes in AFP into three groups according to the risk of recurrence: low risk, intermediate risk, and high risk. There was a statistically significant difference in RFS between the three groups in the training and validation cohorts (P<0.001).

Conclusion

The nomogram developed and validated in this study had good predictive power for patients with dynamic changes in AFP.

Dysregulated microRNAs as a biomarker for diagnosis and prognosis of hepatitis B virus-associated hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignancy with a high incidence and fatality rate worldwide. Hepatitis B virus (HBV) infection is one of the most important risk factors for its occurrence and development. Early detection of HBV-associated HCC (HBV-HCC) can improve clinical decision-making and patient outcomes. Biomarkers are extremely helpful, not only for early diagnosis, but also for the development of therapeutics. MicroRNAs (miRNAs), a subset of non-coding RNAs approximately 22 nucleotides in length, have increasingly attracted scientists' attention due to their potential utility as biomarkers for cancer detection and therapy. HBV profoundly impacts the expression of miRNAs potentially involved in the development of hepatocarcinogenesis. In this review, we summarize the current progress on the role of miRNAs in the diagnosis and treatment of HBV-HCC. From a molecular standpoint, we discuss the mechanism by which HBV regulates miRNAs and investigate the exact effect of miRNAs on the promotion of HCC. In the near future, miRNA-based diagnostic, prognostic, and therapeutic applications will make their way into the clinical routine.

Low-Cost Full-Range Detection of C-Reactive Protein in Clinical Samples by Aptamer Hairpin Probes and Coprecipitation of Silver Ions and Gold Nanoparticles

C-reactive protein (CRP) levels can vary widely related to diverse disease contexts. However, expensive antibodies have impeded the clinical utility of antibody-based full-range CRP assays, especially in developing countries. Herein, we established a low-cost, antibody-free, 96-well plate-based full-range CRP detection method by combining gold nanoparticles (AuNPs), silver iodide (AgI), Eosin Y, and the aptamer hairpin probe (AHP) with Ag+-mediated cytosine-cytosine mismatches, that is, the Au@AgI/Eosin Y-AHP method. After binding the target CRP, the AHP released Ag+, which subsequently induced the aggregation of AuNPs on the surface of AgI colloids, resulting in a significant increase in the adsorption of Eosin Y on the surface of AuNPs. The changes in fluorescence intensity (FI) of Eosin Y in the supernate without and with CRP were proportional to the concentration of the CRP in the wide range of 0.01-40 ng/mL (r = 0.9969), and 96 samples can be detected in 96-well plates simultaneously by a microplate reader within 45 min. Remarkably, the CRP levels of 100 clinical samples achieved with the Au@AgI/Eosin Y-AHP had a good correlation with those obtained with the latex-enhanced immune turbidimetry assay (r = 0.986). Furthermore, the kit based on the Au@AgI/Eosin Y-AHP method costs only $8.1 for 100 tests. Therefore, the new method is beneficial for less developed areas where expensive assays are not affordable.

Dual Stealth Functional Immuno-magnetic Nanoparticles for High-Performance Isolation of Circulating Tumor Cells

As a biomarker of hepatocellular carcinoma (HCC) biopsy, circulating tumor cells (CTCs) are often used in the diagnosis of cancer and treatment guidance. For CTCs detection, immuno-magnetic nanoparticles (IMNs) are one of the most commonly used platforms. However, the nonspecific adsorption of proteins and non-tumor cells weakens the performance of IMNs to capture CTCs. In this work, we developed an IMNs platform which was constructed by a biomimetic protein corona precoating and a polyethylene glycol (PEG) spacer to form the PEG and corona-coated IMNs (IP-CMNs). Due to the dual stealth effect of protein corona precoating and PEG spacer, the nonspecific protein adsorption and cell binding of P-CMNs could reduce by ∼5.5- and ∼5.4-fold, respectively, compared with those of unmodified particles. Furthermore, the PEG spacer could not only reduce the interaction between IP-CMNs and leukocytes but also enhance the capture performance toward tumor cells. By using artificial blood samples, the capture efficiency of IP-CMNs toward rare CTCs was found to be 88.3%, while it was 70.5% by using commercial IMNs. Finally, CTCs were successfully isolated in all HCC patient blood samples (7/7) using IP-CMNs. These results provide insight into the use of the multifunctional nanoplatform as a useful tool for CTCs detection.