The high mortality rate of patients with hepatocellular carcinoma (HCC) is an ever-increasing worldwide concern. Fortunately, the newest research has found that the proportion of a protein variant in total alpha-fetoprotein (AFP) over 10 % can accurately predict the incidence of HCC. Therefore, a signal off-to-on strategy was designed for developing a novel precise and ultrasensitive biosensor towards HCC through protein variant detection based on bimetallic metal-organic framework (MOF). In this study, the biocompatible Fe2Ni-MOF was used as an electrochemically immobilized carrier, which provided abundant active sites and exhibited a synergistic effect between Fe and Ni ions for dramatically promoting the electron transfer and improving the electrochemical reduction efficiency, prominently facilitating signal amplification of the biosensing platform. Then, we designed a novel ordered labeling method to distinguish AFP-L3 from overall AFP and introduced a signal off-to-on strategy for achieving highly efficient determination of AFP-L3 %. This proposed biosensor demonstrated a satisfactory linear range, along with a very low detection limit of 69 pg/mL for AFP-L3, which was far below the medically relevant threshold level. Furthermore, the adopted biosensor presented preeminent specificity, and favorable reproducibility.

Cathepsin D (CTSD) is a lysosomal aspartic protease with high expression in cancers. CTSD localized in different subcellular regions performs distinct roles. However, the precise regulation of its intracellular trafficking and extracellular secretion remains incompletely understood. This study showed that glycosylation modifications of CTSD determined its maturation and secretion in gastric cancer (GC) cells. Specifically, glycosylation at asparagine 134 (N134) dictated the intracellular trafficking and maturation of CTSD within lysosomes, through facilitating its sorting into COPII vesicles. Glycosylation at asparagine 263 (N263) was essential for the secretion of the proenzyme form of CTSD (pro-CTSD) via a novel pathway dependent on the small GTPase Rab3D. Notably, the extracellular release of pro-CTSD occurred more rapidly than its intracellular trafficking from the endoplasmic reticulum to lysosomes. This enhanced secretion speed may rapidly elevate the levels of pro-CTSD in the tumor microenvironment in response to extracellular stimuli. Ultimately, glycosylation at N134 and N263 regulated the autophagy and cell proliferation, respectively. These findings show the role of glycosylation in triggering the maturation and secretion of CTSD in GC cells. Through modulating its cellular trafficking, differential glycosylation modifications of CTSD defined the malignant behavior of GC cells.

Hepatocellular carcinoma (HCC) is the sixth leading cancer worldwide and has complex pathogenesis due to its heterogeneity, along with poor prognoses. Diagnosis is often late as current screening methods have limited sensitivity for early HCC. Moreover, current treatment regimens for intermediate-to-advanced HCC have high resistance rates, no robust predictive biomarkers, and limited survival benefits. A deeper understanding of the molecular biology of HCC may enhance tumor characterization and targeting of key carcinogenic signatures. The epigenetic landscape of HCC includes complex hallmarks of 1) global DNA hypomethylation of oncogenes and hypermethylation of tumor suppressors; 2) histone modifications, altering chromatin accessibility to upregulate oncogene expression, and/or suppress tumor suppressor gene expression; 3) genome-wide rearrangement of chromatin loops facilitating distal enhancer-promoter oncogenic interactions; and 4) RNA regulation via translational repression by microRNAs (miRNAs) and RNA modifications. Additionally, it is useful to consider etiology-specific epigenetic aberrancies, especially in viral hepatitis and metabolic dysfunction-associated steatotic liver disease (MASLD), which are the main risk factors of HCC. This article comprehensively explores the epigenetic signatures in HCC, highlighting their potential as biomarkers and therapeutic targets. Additionally, we examine how etiology-specific epigenetic patterns and the integration of epigenetic therapies with immunotherapy could advance personalized HCC treatment strategies.

Extensive exploratory studies have been conducted and promising progress has been made in the use of nanomaterials for the diagnosis and treatment of hepatocellular carcinoma (HCC). Here, we aimed to reveal the evolution and trends in this field through bibliometric analysis.

English-language publications (1999-2024) in the field of nanomaterials and HCC were retrieved from the Web of Science database, and eligible articles were selected for bibliometric analysis (data extraction, statistical analysis, and visualization) using VOSviewer and Citespace software.

A total of 1617 eligible publications were analyzed. The number of publications increased rapidly from 2012 and peaked in 2020. China contributed the most publications, and the United States had the most citations. The Chinese Academy of Sciences was the most influential institution. The "International Journal of Nanomedicine (DOVE Medical)" published the most articles, while "Biomaterials (Elsevier)" was the most influential journal. Jie Tian had the highest number of publications, and Dan Shao had the highest average citation per article. Keyword analysis revealed that nanoparticles for targeted drug delivery, therapy and imaging of HCC were research hotspots. Keywords with citation bursts in the last three years included photodynamic therapy, sorafenib, and tumor microenvironment. Nano-vaccines, nano-antibodies, and synergistic therapies were emerging therapeutic strategies. A total of seven clinical trials were published, but to date there have been no major breakthroughs in HCC therapy using nanomaterials.

Research on nanomaterials and HCC has shown an overall upward trend, with research hotspots and frontiers focusing on nanoparticle-targeted chemotherapies, photodynamic therapy, and related tumor microenvironment research.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer mainly caused by hepatitis viral infection. Early stage diagnosis is still challenging due to its asymptomatic behavior so there is an urgent need for effective biomarkers. This study aimed to identify effective diagnostic biomarker or therapeutic target for HCC.

Label-free quantitative mass spectrometry was performed to analyze protein expression in HCC and control tissues. Protein-protein interaction (PPI) analysis was done using the STRING database and hub proteins were identified by Cytohubba. The survival analysis and expressions profiling of hub proteins were performed by using GEPIA. Functional and pathway enrichment analysis were carried out using Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG).

A total of 1539 proteins were identified, of which 116 were differentially expressed proteins (DEPs). PPI network analysis revealed 10 hub proteins; EGFR, GAPDH, HSP90AA1, MMP9, PTPRC, CD44, ANXA5, PECAM1, MMP2, and CDK1. Among these, GAPDH, MMP9, ANXA5, HSP90AA1, and CDK1 were significantly associated with low survival rate (p ⩽ .05). Moreover, MMP9 and CDK1 were showed significantly increased expression in tumor tissues as compared to control (p ⩽ .05). The GO analysis based on biological process, cellular components and molecular function indicated that DEPs were enriched in stress response, vesicle and extracellular space, protein binding and enzyme activity. The KEGG pathway analysis showed that the thyroid hormone synthesis pathway is the most enriched.

The hub proteins GAPDH, HSP90AA1, MMP9, ANXA5, and CDK1 demonstrated significant prognostic potential, could be used as promising theragnostic biomarkers for HCC.

Metabolic dysfunction-associated steatohepatitis (MASH) is a growing cause of hepatocellular carcinoma (HCC) worldwide. The complex microenvironment of these tumors, characterized by metabolic dysfunction, hypoxia, steatosis, and fibrosis, limits the effectiveness of standard-of-care therapies, such as the multi-tyrosine kinase inhibitor lenvatinib (LEN). Salsalate (SAL), is a rheumatoid arthritis therapy that enhances fatty acid oxidation and reduces de novo lipogenesis, fibrosis and cell proliferation pathways. We hypothesize that addition of SAL could improve the efficacy of LEN in MASH-HCC.

We assessed the efficacy of combination therapy using clinically relevant concentrations of LEN and SAL in human HCC cell models, orthotopic xenograft and MASH-HCC mouse models. In addition, assays assessing fatty acid oxidation and lipogenesis, protein immunoblotting and RNA-sequencing were used to understand mechanisms involved.

LEN + SAL synergistically suppressed the proliferation and clonogenic survival of cells (p ≤0.0001), prolonged survival in an orthotopic xenograft model (p = 0.02), and reduced angiogenesis, fibrosis, and steatosis (p ≤0.05) in a MASH-HCC model. These effects were associated with activation of AMPK and inhibition of the mTOR-HIF1α and Erk1/2 signaling pathways. RNA-sequencing analysis in both Hep3B cells and livers of the MASH-HCC mouse model revealed that SAL enhanced fatty acid oxidation and suppressed fibrosis and cell cycle progression, while LEN reduced angiogenesis with regulatory network analysis, suggesting a potential role for activating transcription factor 3 (ATF3) and ETS-proto-oncogene-1 (ETS-1).

These data indicate that combining LEN and SAL, which exert distinct effects leading to improvements in the liver microenvironment (steatosis, angiogenesis, and fibrosis) and inhibition of tumor proliferation, may have therapeutic potential for MASH-driven HCC.

Although rates of MASH-HCC are on the rise globally, standard-of-care multi-tyrosine kinase inhibitors and immunotherapy have limited efficacy in this HCC etiology. Metabolic targeting with SAL inhibits cancer growth kinetics while also alleviating drivers of MASH by increasing fatty acid oxidation and reducing de novo lipogenesis and fibrosis. Combined LEN and SAL improved survival and MASH-HCC pathology in mouse models without adverse effects. Given that SAL is a safe, economical, and approved medication, this concept holds great translational potential that could provide a new treatment avenue for patients with unresected MASH-HCC.

Malignant tumors represent a significant worldwide health challenge, with elevated morbidity and mortality rates necessitating enhanced early identification and individualized treatment. Liposomes, as biomimetic lipid-based nanovesicles, have developed as a multifaceted platform for detecting and treating malignant tumors due to their excellent biocompatibility, stability, and membrane fusion properties. Circulating tumor markers, such as circulating tumor cells (CTCs), extracellular vesicles (EVs), circulating tumor proteins (CTPs), and circulating tumor nucleic acids (ctNAs), play a key role in early cancer diagnosis, disease progression monitoring, and personalized therapy. Liposome-based platforms enable effective molecular recognition, targeted detection, and signal amplification by targeting circulating tumor biomarkers, significantly increasing the potential for early tumor diagnosis and treatment. This review systematically summarizes advancements in the study of liposomes concerning circulating tumor markers, including applications in targeted recognition, early detection, and disease diagnosis, while discussing present problems and prospective applications of existing technology.

Drug screening of primary tumor cells directly assesses the drug efficacy on specific tumors, promoting personalized cancer treatment. The application of a microfluidic platform has realized drug screening using a limited amount of biopsy samples for cancer precision medicine. However, all the techniques face an inevitable issue of not all the primary tumor cells being cancer cells. Here, a system is introduced that integrates single-cell identification and drug screening on one semiconductor chip so that both drug efficacy on cancer cells and drug toxicity on noncancerous cells can be obtained simultaneously. An integrated circuit is built on the semiconductor chip for single-cell electric impedance sensing (IC-ECIS) of ultra-weak signals for distinguishing cancer cells from noncancerous cells without affecting cell vitality. Single-cell identification is validated using breast, lung, and liver cell lines as well as liver cancer specimens from clinical patients. The accuracy on commercial cell lines is ≈80%, and the diagnostic results of tumor tissues are consistent with clinical pathology results. Drug screening is run on the same chip after single cell identification for dual evaluation of drug efficacy and toxicity in both breast cancer models and clinical liver cancer patients. The on-chip drug screening is confirmed with off-chip counterpart experiments in breast cell lines. The effectiveness or ineffectiveness of a drug screened on the IC-ECIS chip demonstrated consistency in the presence or absence of specific mutations in the drug-related genes determined via exome sequencing of individual liver tumors, validating the method for precision medicine.

A significant proportion, ranging from 20 to 40%, of individuals with hepatocellular carcinoma (HCC) do not exhibit elevated Alpha-fetoprotein (AFP) levels. This study aimed to evaluate the utility of serum glypican-3 (GPC3) and protein induced by vitamin K absence or antagonist II (PIVKA-II) in an AFP-negative HCC (N-HCC) population, and to develop nomogram diagnostic and prognostic prediction models utilizing GPC3 and PIVKA-II.

Serum GPC3 and PIVKA-II levels were measured in this case-control study, followed by the establishment of a receiver operating characteristic (ROC) curve, restricted cubic spline (RCS), and Kaplan-Meier survival curve. Additionally, a diagnostic prediction nomogram was constructed using univariate and multivariate logistic regression. Furthermore, we utilized least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression to develop a prognostic prediction nomogram. The performance of these models was evaluated using ROC curve analysis and decision curve analysis (DCA).

Serum GPC3 and PIVKA-II expression levels were significantly elevated in untreated patients with N-HCC (especially stageI and tumor size < 3 cm) compared to those with AFP-negative benign liver disease (N-BLD). Derived from ROC analysis, the diagnostic cutoff points for GPC3 and PIVKA-II were set at 0.100 ng/mL and 40.00 mAU/mL, respectively. PIVKA-II demonstrated sensitivity and specificity of 84.62% and 90.38%, surpassing GPC3's 76.92% and 73.08%. The area under the ROC curve (AUC) for a diagnostic prediction nomogram incorporating GPC3, PIVKA-II, and gamma-glutamyltransferase (GGT) was 0.943 (95% CI: 0.912-0.974), superior to models using GPC3 or PIVKA-II alone. This model showed 95.20% sensitivity and 81.70% specificity in differentiating N-HCC from N-BLD. Stratifying patients into high-risk and low-risk groups using cutoff values established by RCS for GPC3 (0.124 ng/mL) and PIVKA-II (274 mAU/mL) revealed significant associations between these risk stratifications and patient survival. Finally, the use of GPC3-highrisk, cirrhosis, albumin (ALB), portal venous thrombosis (PVT), and surgical treatment as five parameters in the nomogram prognostic prediction model effectively differentiated between high- and low-risk prognostic patients with N-HCC with relatively high accuracy.

Serum GPC3 and PIVKA-II demonstrate clinical significance in the timely detection and prognosis assessment of N-HCC. The application of nomogram prediction models based on GPC3 and PIVKA-II stands as an important adjunctive tool for diagnosing and prognosticating N-HCC.

Digestive system tumours (DSTs) often diagnosed late due to nonspecific symptoms. Non-invasive biomarkers are crucial for early detection and improved outcomes.

We collected tongue coating samples from 710 patients diagnosed with DST and 489 healthy controls (HC) from April 2023, to December 2023. Microbial composition was analyzed using 16S rRNA sequencing, and five machine learning algorithms were applied to assess the diagnostic potential of tongue coating microbiota.

Alpha diversity analysis showed that the microbial diversity in the tongue coating was significantly increased in DST patients. LEfSe analysis identified DST-enriched genera Alloprevotella and Prevotella, contrasting with HC-dominant taxa Neisseria, Haemophilus, and Porphyromonas (LDA >4). Notably, when comparing each of the four DST subtypes with the HC group, the proportion of Haemophilus in the HC group was significantly higher, and it was identified as an important feature for distinguishing the HC group. Machine learning validation demonstrated superior diagnostic performance of the Extreme Gradient Boosting (XGBoost) model, achieving an AUC of 0.926 (95% CI: 0.893-0.958) in internal validation, outperforming the other four machine learning models.

Tongue coating microbiota shows promise as a non-invasive biomarker for DST diagnosis, supported by robust machine learning models.

DNA methylation carrying epigenetic aberrations could potentially serve as a non-invasive tool for revolutionizing cancer diagnosis and monitoring. Here, we comprehensively evaluated the diagnostic value of plasma methylated HIST1H3G, and constructed diagnostic and prognostic models aimed at facilitating early detection and improving the prognosis of hepatocellular carcinoma (HCC).

The level of HIST1H3G promoter methylation in HCC tissues was evaluated based on the UALCAN database, followed by validation through serum samples collected from HCC patients. We recruited 205 participants, encompassing 70 HCC patients, 79 liver cirrhosis (LC) patients, 46 hepatitis patients and 10 HCC patients before and after treatment with either transarterial chemoembolization (TACE) or radiofrequency ablation (RFA). Analysis of plasma HIST1H3G was performed using methylation-specific quantitative polymerase chain reaction (qPCR). Diagnostic and prognostic prediction models were formulated using the random forest algorithm, and the performance of these models was rigorously evaluated through receiver operating characteristics curve (ROC) analysis.

The methylation level of HIST1H3G was markedly elevated in both HCC tissues and plasma samples derived from HCC patients. HIST1H3G, PIVKA-II, total bilirubin (TBIL) and age were selected as the optimal markers and were included in the development of a diagnostic model. This model demonstrated superior accuracy in distinguishing HCC from high-risk populations, outperforming alpha-fetoprotein (AFP) in both the training cohort consisting of LC patients and the validation cohort comprising hepatitis patients. Additionally, HIST1H3G and albumin (Alb) were chosen to establish a prediction model for early HCC diagnosis, and this model exhibited a remarkable ability to identify early HCC. Furthermore, our prognostic prediction model proved effective in predicting the prognosis and survival outcomes of HCC patients.

Together, we identified and validated a diagnostic model that incorporated methylated HIST1H3G and clinically applicable serological indicators in HCC. The findings of our study established a pivotal foundation for the development of a non-invasive approach to identification and management in HCC.

Hepatocellular carcinoma (HCC) is the most prevalent liver cancer, with a 5-year survival rate below 20% and an average survival time of 3-6 months. Identifying new biomarkers is crucial for early diagnosis and prognosis. The function of PDZ domain protein 11 (PDZD11) in HCC remains unclear.

In this study, PDZD11 was investigated as a potential biomarker for HCC using bioinformatic analysis of the TCGA and ICGC datasets. Furthermore, we assessed the potential of serum PDZD11 as a clinical diagnostic marker by enrolling a cohort comprising 78 HCC patients and 62 healthy controls (HC) using the ELISA analysis and combining its expression with common tumor markers.

Our research found significantly higher PDZD11 mRNA expression in HCC tissues compared to tumor-adjacent tissues (p < 0.001), which was associated with lower overall survival (OS) rates (p < 0.01). Multivariate evaluation methods established PDZD11 as a standalone predictor of prognosis. A nomogram incorporating PDZD11 expression and clinicopathological factors predicted OS rates for HCC patients over various years. Patients with HCC exhibited notably elevated serum PDZD11 levels compared to HC, with these levels rising further in advanced disease stages and deteriorating performance status (PS). ROC analysis showed high diagnostic accuracy when PDZD11 is combined with AFP (AUC = 0.958).

PDZD11 is more sensitive than AFP in assessing HCC prognosis. In conclusion, PDZD11 is a promising supplementary biomarker for HCC diagnosis and prognosis alongside AFP.

SERPINI1 is a protein-coding gene, which has been reported to be related to malignancies, and the encoding protein is a secreted protein. Nevertheless, the specific effect of SERPINI1 on Hepatocellular carcinoma (HCC) remains unclear.

The expression level of SERPINI1 in cancers was detected by the Gene Expression Omnibus (GEO) database, the Gene Expression Profiling Interactive Analysis (GEPIA) database and the collected serum of HCC patients. The receiver operating characteristic (ROC) curve and area under curve (AUC) were used to evaluate the diagnostic effectiveness of serum SERPINI1 and the combination of AFP and SERPINI1 for HCC. The Kaplan-Meier (KM) survival was used to evaluate the prognostic capacity of SERPINI1 for HCC in GEPIA database. Furthermore, the correlations between clinicopathological characteristics and the level of serum SERPINI1 were analyzed. Besides, we detected the expression of SERPINI1 in HepG2 by qPCR and western blot, and confirmed the biological function of SERPINI1 through MTT, EdU, wound healing and transwell invasion assay.

The results indicated that the level of SERPINI1 was significantly increased in tissue and serum of HCC patients. ROC analysis displayed that SERPINI1 had a significantly diagnostic value for HCC, the combination of AFP and SERPINI1 gained the higher specificity and sensitivity. The KM survival curves indicated that patients with SERPINI1 overexpression had worse overall survival. Furthermore, we found the positive correlations between serum SERPINI1 level and some clinicopathological characteristics, such as tumor size, differentiation degrees and so on. In addition, in vitro experiments revealed that SERPINI1 could promote the proliferation and invasion of HCC.

Taken together, our study demonstrates that SERPINI1, which is highly expressed in HCC and closely related to cell proliferation and invasion, may serve as a novel biomarker for diagnosis and prognosis of HCC.

Although Cell growth regulator with EF-hand domain 1 (CGREF1) has been predicted to be upregulated in multiple cancer types, its definitive function role in carcinogenesis, particularly in hepatocellular carcinoma (HCC), remains poorly characterized.

Comprehensive bioinformatics analysis was initially conducted using the University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) and Gene Expression Profiling Interactive Analysis (GEPIA) databases to investigate CGREF1 mRNA expression patterns in HCC tissues and their clinical correlation with patient survival outcomes. Experimental validation was subsequently performed through real-time quantitative polymerase chain reaction (RT-qPCR), immunohistochemistry (IHC), and Western blot techniques. Functional characterization studies employing genetic knockdown and overexpression models in HCC cell lines demonstrated CGREF1's regulatory effects on malignant phenotypes, as evidenced by 3-(4,5-dimethylthiazolyl)-2,5-diphenyltetrazolium bromide (MTT) assay, colony formation assay and Transwell migration and invasion assays. were adopted to investigate the role of CGREF1 in the proliferation, invasion, and migration of HCC cells. Mechanistic investigations integrating bioinformatics predictions with Western blot analysis revealed CGREF1 mediated-modulation of the Wnt/β-Catenin signaling axis, elucidating its molecular underpinnings in HCC progression.

The results demonstrated that CGREF1 is highly expressed in HCC tissues, and HCC patients with elevated CGREF1 expression exhibited significantly shorter survival times. Upregulation of CGREF1 promoted the proliferation, migration, and invasion of HCC cells, whereas inhibition of CGREF1 expression suppressed these phenotypes. Mechanistically, CGREF1 activates the Wnt/β-Catenin signaling pathway through the upregulation of eukaryotic translation initiation factor 3 H subunit (EIF3H). Furthermore, partial inhibition of EIF3H attenuated the effects of CGREF1 overexpression on the proliferation, migration, and invasion of HCC cells.

CGREF1 is upregulated in HCC and acted as an oncogene through the CGREF1/EIF3H/Wnt/β-Catenin signaling axis. These findings suggest that CGREF1 may emerge as a potential therapeutic target for HCC.

Protein kinase C delta (PKCδ) is a leaderless protein generally localized in the cytoplasm and nucleus; however, its extracellular unconventional protein secretion occurs exclusively in hepatocellular carcinoma (HCC) cells (but not in normal and non-cancerous hepatocytes or other gastrointestinal cancer cells) via an autophagy mechanism, despite the lack of a secretory signal. Therefore, PKCδ is detectable in the peripheral blood of HCC patients. Serum PKCδ indicates cancer-related unconventional protein secretion of an inactive form of cytosolic PKCδ and can be a unique biomarker independent of conventional markers. To examine the specificity of serum PKCδ for HCC, its levels and positivity rates were compared between 226 HCC and 108 gastrointestinal cancer patients. Furthermore, we focused on patients with malignant or benign intrahepatic tumors (17 intrahepatic cholangiocarcinoma, 42 liver metastases, and 6 focal nodular hyperplasia). A sandwich enzyme-linked immunosorbent assay was used to measure serum PKCδ levels; the optimal cutoff value was set to 57.7 ng/mL. HCC patients had significantly higher PKCδ levels and positivity rates than gastrointestinal cancer patients (median, 51.1 vs. 34.6 ng/mL; 39.8 % vs. 4.6 %; P < 0.001 for both). Thus, the specificity was 95.4 %. Focusing on intrahepatic tumors, 2 (4.8 %) of 42 gastrointestinal cancer patients with liver metastasis were positive for PKCδ. Notably, all patients with intrahepatic cholangiocarcinoma and focal nodular hyperplasia were negative for PKCδ, irrespective of their intrahepatic tumors being malignant or benign. Serum PKCδ is an extracellularly secreted protein specific for HCC that can be a novel diagnostic biomarker because it distinguishes HCC from other gastrointestinal cancers and intrahepatic non-HCC tumors.

High-sensitive detection of circulating biomarkers is in high demand because many of them are found at low concentrations in bioliquids. Herein, we report an immuno-transcription-amplified single microbead (MB) assay (IT-SMA) based on the specific S9.6 antibody-DNA/RNA hybrid recognition strategy for the sensitive and universal quantification of protein biomarkers. This design rationally converts the immunoreaction events into amplified nucleic acid transcription to produce numerous RNA molecules, which can efficiently enrich fluorescent signals onto a single MB through a specific S9.6 antibody-DNA/RNA hybrid recognition mechanism, enabling sensitive protein analysis. This method exhibits excellent specificity and high sensitivity for protein analysis with a low detection limit at the fg/mL level. Furthermore, the S9.6 antibody-aided IT-SMA allows for universal detection of various proteins and even exosomes, testing target proteins in serum samples, and differentiating cancer patients from healthy individuals by directly analyzing the exosomes in human blood samples. These features make the IT-SMA strategy a promising tool for the quantitative detection of a variety of biomarkers toward precision diagnostics.

As a highly heterogeneous cancer, hepatocellular carcinoma (HCC) shows different response rates to the multi-kinase inhibitor lenvatinib. Thus, it is important to explore genetic biomarkers for precision lenvatinib therapy in HCC.

The effect and mechanism of AXIN1 mutation on HCC were revealed by cell proliferation assay, long-term clone formation assay, sphere formation assay and small molecule inhibitor library screening. A new therapeutic strategy targeting HCC with AXIN1 mutation was evaluated in humanized models (patient-derived xenograft [PDX] and patient-derived organoid [PDO]).

Based on The Cancer Genome Atlas (TCGA) data, we screened 6 most frequently lost tumour suppressor genes in HCC (TP53, ARID1A, AXIN1, CDKN2A, ARID2 and PTEN) and identified AXIN1 as the most crucial gene for lenvatinib sensitivity. Further study showed that AXIN1-knockout HCC cells had a more malignant phenotype and lower sensitivity to lenvatinib in vitro and in vivo. Mechanistically, the WNT pathway and its target gene c-Myc were activated when AXIN1 was missing, and the expression of tumour suppressor p15 was inhibited by transcription co-repressors c-Myc and Miz-1, resulting in the exacerbation of the resistant phenotype. Screening of a library of epigenetic-related enzyme inhibitors showed that a KDM5B inhibitor up-regulated p15 expression, leading to increased sensitivity to lenvatinib in vitro and in vivo.

AXIN1-deficient patients have a lower response to lenvatinib, which may be associated with suppression of p15 mediated by WNT pathway activation. KDM5B inhibitors can restore p15 levels, resulting in efficient killing of resistant cells in HCC.

Hepatocellular carcinoma (HCC) is a rapidly growing malignancy with high mortality. Recently, metabolic dysfunction-associated steatohepatitis (MASH) has emerged as a major HCC catalyst; however, signals driving transition of MASH to HCC remain elusive and treatment options are limited. Herein, we investigated the role of STE20-type kinase STK25, a critical regulator of hepatocellular lipotoxic milieu and MASH susceptibility, in the initiation and progression of MASH-related HCC.

The clinical relevance of STK25 in HCC was assessed in publicly available datasets and by RT-qPCR and proximity ligation assay in a validation cohort. The functional significance of STK25 silencing in human hepatoma cells was evaluated in vitro and in a subcutaneous xenograft mouse model. The therapeutic potential of STK25 antagonism was examined in a mouse model of MASH-driven HCC, induced by a single diethylnitrosamine injection combined with a high-fat diet.

Analysis of public databases and in-house cohorts revealed that STK25 expression in human liver biopsies positively correlated with HCC incidence and severity. The in vitro silencing of STK25 in human hepatoma cells suppressed proliferation, migration, and invasion with efficacy comparable to that achieved by anti-HCC drugs sorafenib or regorafenib. STK25 knockout in human hepatoma cells also blocked tumor formation and growth in a subcutaneous xenograft mouse model. Furthermore, pharmacologic inhibition of STK25 with antisense oligonucleotides-administered systemically or hepatocyte-specifically-efficiently mitigated the development and exacerbation of hepatocarcinogenesis in a mouse model of MASH-driven HCC.

This study underscores STK25 antagonism as a promising therapeutic strategy for the prevention and treatment of HCC in the context of MASH.

Among malignant tumors, hepatocellular carcinoma (HCC) is both prevalent and highly lethal. Most patients with advanced-stage liver cancer have a poor prognosis. Death-associated protein 3 (DAP3) is reportedly related to tumors and may hold great promise for the future.

DAP3 transcriptome data along with related clinical information were obtained from The Cancer Genome Atlas (TCGA), GEO, and ICGC databases. We assessed its prognostic value, clinical relevance, associated pathways, immune infiltration, gene mutations, and sensitivity to chemotherapeutics. A prognostic risk model was subsequently developed and evaluated using receiver operating characteristic (ROC) curves and Kaplan-Meier (KM) plots. Additionally, a nomogram was created and validated through calibration and decision curve analysis (DCA). Furthermore, quantitative real-time PCR (qRT-PCR), Western blot, and immunohistochemical (IHC) staining were performed to examine the expression of DAP3 in HCC. Finally, gene knockdown and overexpression experiments, along with cell counting kit-8 (CCK-8) assays, colony formation assays, and tests for cell apoptosis, migration, and invasion, were conducted to investigate the role of DAP3 in HCC.

The study discovered that DAP3 expression was linked to HCC subtypes, and its high expression was linked to a poor prognosis. There were significant differences in immune infiltration level, mutation level, prognostic value and chemotherapeutic efficacy. Subsequently, we constructed a prognostic model and demonstrated that high risk score was significantly related to a poor survival rate. A predictive nomogram demonstrated that the nomogram model was effective prediction tool that can accurately predict the survival rate of patients with different clinical characteristics. Additionally, DAP3 expression significantly increased in both tissue samples and cell lines. Elevated levels of DAP3 were correlated with larger tumor size and higher alpha-fetoprotein (AFP) levels, and Cox analysis confirmed that DAP3 was a clinically independent prognostic marker. Finally, cell assays revealed that the knockdown of DAP3 significantly impeded cell proliferation and metabolic activity and induced apoptosis. Conversely, the overexpression of DAP3 had opposite effects on these cellular processes.

Our study on DAP3 can provide a reference for HCC diagnosis, treatment and prognosis assessment.

Long noncoding RNAs (lncRNAs) are closely associated with tumor development, and increasing evidence suggests that small open reading frame (smORF) within lncRNAs also have the capability to encode smORF-encoded peptides (SEPs). Here, we thoroughly uncovered the SEP expression profile of hepatocellular carcinoma (HCC) from tumor and adjacent nontumor tissues of 154 HCC patients using high-throughput mass spectrometry (MS). A total of 208 SEPs were identified, with no significant difference in abundance and stability compared with coding region proteins. Notably, the peptide encoded by LINC01007 (LINC01007-33AA) was significantly upregulated in HCC tissues (p < 0.05) and could serve as an independent risk factor affecting prognosis (HR [95% CI]: 1.31[1.01-1.7]). This endogenous peptide was further confirmed at both the mRNA and protein levels, and its overexpression significantly enhances the invasion and migration of HCC cells. These findings highlight the potential of MS-based methods to identify novel noncoding sequence encoded functional peptides associated with tumor progression.

Long noncoding RNA (lncRNA) PTTG3P has been demonstrated to participate in the development of hepatocellular carcinoma (HCC) by targeting the mRNA PTTG1. The present study aimed to investigate the diagnostic efficacy of serum lncRNA PTTG3P, mRNA PTTG1 and their combination for the diagnosis and prognosis of HCC. A total of 373 participants were enrolled in the present study, including 73 patients with HCC, 100 patients with chronic hepatitis B (CHB), 100 patients with liver cirrhosis (LC) and 100 healthy controls (HCs). The expression levels of serum RNAs were quantified by reverse transcription‑quantitative PCR. The association between serum lncRNA PTTG3P and clinical characteristics was further analyzed. Receiver operating characteristic (ROC) curve and area under curve (AUC) analyses were performed to estimate the diagnostic ability of serum lncRNA PTTG3P, PTTG1 and their combinations with other biomarkers for HCC. The results revealed that the expression levels of lncRNA PTTG3P and mRNA PTTG1 were markedly increased in the serum of patients with HCC and CHB compared with in the serum of HCs. Additionally, the postoperative levels of lncRNA PTTG3P and mRNA PTTG1 were significantly lower than the preoperative concentrations in 36 paired patients with HCC. Spearman's correlation coefficient analysis showed that serum lncRNA PTTG3P was correlated with aspartate transaminase (AST). ROC analysis showed that both lncRNA PTTG3P and mRNA PTTG1 had a significant predictive value for HCC. The AUC values of lncRNA PTTG3P and mRNA PTTG1 alone were 0.636 and 0.634, respectively. Furthermore, combining lncRNA PTTG3P, mRNA PTTG1, α‑fetoprotein (AFP), alanine aminotransferase (ALT), AST, γ‑glutamyl transpeptidase (GGT) and alkaline phosphatase (ALP) significantly increased the AUC value. The best performance was the combination of PTTG3P, PTTG1, AFP, ALT, AST, GGT and ALP with an AUC of 0.959, a sensitivity of 90.4% and a specificity of 98.0%. In conclusion, the combination of serum lncRNA PTTG3P, mRNA PTTG1 and AFP appeared to be a noninvasive biomarker with comparatively high specificity and sensitivity for the diagnosis of HCC.

Hepatocellular carcinoma (HCC), the most common primary liver cancer, is a highly aggressive malignancy with limited viable therapeutic options. For early HCC, resection surgery is currently the most effective treatment. However, in advanced stages, resection alone does not sufficiently address the disease, so finding a method with a better prognosis is necessary. Anoikis, known as matrix detachment-induced apoptosis or detachment-induced cell death, is crucial for tissue development and homeostasis. Cancer cells develop means to evade anoikis, e.g. anoikis resistance, thereby allowing for cells to survive under anchorage-independent conditions. HCC cells often acquire resistance to anoikis, allowing them to survive after detaching from the extracellular matrix and contributing to tumor spread. This review discusses the mechanisms of anoikis in HCC, exploring the potential of drug-induced anoikis and targeting anoikis resistance as promising therapeutic strategies for treating HCC, analyzing the value of anoikis in the immune of HCC, and propose potential pathways in oncotherapy, which can provide background knowledge for subsequent related research.

The Sigma-1 receptor (Sig-1R), located in the mitochondrion-associated membranes (MAMs), is an important biomarker for endoplasmic reticulum (ER) stress and plays a crucial role in the advancement of metabolic-associated fatty liver disease (MAFLD). Despite its significance, current methods to monitor MAFLD progression and treatment response are limited. This study aims to address this gap by utilizing [18F]F-TZ3108, an effecient tracer targeting Sig-1R, to quantitatively assess MAFLD progression and the efficacy of a low-carbohydrate diet (LCD) as a potential therapeutic intervention.

The C57 BL/6 J mice were fed either a high-fat diet (HFD) or regular diet (CTR) for 12 weeks, and the progression of MAFLD was continuously monitored at 0, 4, 8, 12 weeks via [18F]F-TZ3108 positron emission tomography/computed tomography (PET/CT) and ex vivo assessment. After confirming successful induction, LDC intervention was administered in the HFD group for 2 weeks. And relevant post-treatment evaluations were also performed.

PET/CT revealed a continuous decline in the hepatic binding potential (BPND) of [18F]F-TZ3108 in mice in the HFD group during the induction period, when compared with the BPND in the CTR group. This reduction was significant after the 4th week of induction (p < 0.05). Furthermore, following intervention with LCD, there was a significant improvement in BPND (LCD vs HFD, p = 0.001).

The results of this study demonstrate that LCD therapy effectively mitigates MAFLD progression. Furthermore, the use of PET imaging with [18F]F-TZ3108 provides a reliable, non-invasive method for monitoring the progression and treatment response of MAFLD, offering significant potential for early detection and personalized treatment evaluation.

Gastric cancer (GC) remains a prevalent and preventable disease, yet accurate early diagnostic methods are lacking. Exosome non-coding RNAs (ncRNAs), a type of liquid biopsy, have emerged as promising diagnostic biomarkers for various tumours. This study aimed to identify a serum exosome ncRNA feature for enhancing GC diagnosis.

Serum exosomes from patients with GC (n=37) and healthy donors (n=20) were characterised using RNA sequencing, and potential biomarkers for GC were validated through quantitative reverse transcription PCR (qRT-PCR) in both serum exosomes and tissues. A combined diagnostic model was developed using LASSO-logistic regression based on a cohort of 518 GC patients and 460 healthy donors, and its diagnostic performance was evaluated via receiver operating characteristic curves.

RNA sequencing identified 182 candidate biomarkers for GC, of which 31 were validated as potential biomarkers by qRT-PCR. The combined diagnostic score (cd-score), derived from the expression levels of four long ncRNAs (RP11.443C10.1, CTD-2339L15.3, LINC00567 and DiGeorge syndrome critical region gene (DGCR9)), was found to surpass commonly used biomarkers, such as carcinoembryonic antigen, carbohydrate antigen 19-9 (CA19-9) and CA72-4, in distinguishing GC patients from healthy donors across training, testing and external validation cohorts, with AUC values of 0.959, 0.942 and 0.949, respectively. Additionally, the cd-score could effectively identify GC patients with negative gastrointestinal tumour biomarkers and those in early-stage. Furthermore, molecular biological assays revealed that knockdown of DGCR9 inhibited GC tumour growth.

Our proposed serum exosome ncRNA feature provides a promising liquid biopsy approach for enhancing the early diagnosis of GC.

The protein corona effect refers to the phenomenon wherein nanomaterials in the bloodstream are coated by serum proteins, yet how protein coronated nanomaterials interact with blood vessels and its toxicity implications remain poorly understood. In this study, we investigated protein corona-related vessel toxicity by using an all-humanized assay integrating blood vessel organoids and patient-derived serum. Initially, we screened various nanomaterials to discern how parameters including size, morphology, hydrophobicity, surface charge, and chirality-dependent protein corona difference influence their uptake by vessel organoids. For nanomaterials showing substantial differences in vessel uptake, their protein corona was analyzed by using label-free mass spectra. Our findings revealed the involvement of cancer staging-related cytoskeleton components in mediating preferential uptake by cells, including endothelial and mural cells. Additionally, a transcriptome study was conducted to elucidate the influence of nanomaterials. We confirmed that protein coronated nanomaterials provoke remodeling at both transcriptional and translational levels, impacting pathways such as PI3K-Akt/Hippo/Wnt, and membraneless organelle integrity, respectively. Our study further demonstrated that the remodeling potential of patient-derived protein coronated nanomaterials can be harnessed to synergize with antiangiogenesis therapeutics to improve the outcomes. We anticipate that this study will provide guidance for the safe use of nanomedicine in the future.

To provide a detailed pooled analysis of the diagnostic accuracy of microRNAs (miRNAs) in predicting the response to transarterial chemoembolization (TACE) in hepatocellular carcinoma (HCC).

A comprehensive literature search was conducted across PubMed, Embase, Cochrane Library, and Web of Science to identify studies assessing the diagnostic performance of miRNAs in predicting TACE response in HCC. Two independent reviewers performed quality assessment and data extraction using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic (SROC) curve were calculated using a bivariate random-effects model. Subgroup analyses and meta-regression were performed to explore potential sources of heterogeneity, including sample size, response criteria, specimen source, response evaluation methods, TACE efficacy interval window, and geographical location.

Seven studies, comprising 320 HCC responders and 187 non-responders, were included in this meta-analysis. The miRNAs studied included miR-373, miR-210, miR-4492, miR-1271, miR-214, miR-133b, and miR-335. The pooled sensitivity of miRNAs in predicting recurrence after TACE was 0.79 [95% CI: 0.72-0.84], and the pooled specificity was 0.82 [95% CI: 0.74-0.88]. The DOR was 17 [95% CI: 9-33], and the pooled area under the SROC curve (AUC) was 0.85 [95% CI: 0.81-0.88], indicating excellent diagnostic accuracy. Subgroup analyses revealed significant differences in diagnostic performance based on response criteria and geographical location. Meta-regression did not identify any significant sources of interstudy heterogeneity.

MiRNAs show promise as diagnostic tools for predicting TACE response in HCC patients. However, their clinical application requires further validation in larger cohorts. Future research should focus on standardizing RNA extraction methods, selecting consistent endogenous controls, and adopting uniform response evaluation criteria to improve reliability and reduce variability.

The insulin-like growth factor 2 (IGF2) and H19 are overexpressed in hepatocellular carcinoma (HCC). IGF2-derived miR-483-5p is implicated in the development of cancers. Here, we investigated the involvement of miR-483-5p in IGF2 and H19 overexpression regulation and its role in HCC.

Firstly, the effect of miR-483-5p on the expression of IGF2 and H19, and the binding of miR-483-5p to IGF2/H19 enhancer were evaluated in HCC cells. Next, miR-483-5p-mediated IGF2/H19 enhancer activation and its mechanism were investigated in HCC cells. Then, the mechanism by which active IGF2/H19 enhancer mediated by miR-483-5p activate IGF2/H19 promoters was studied in HCC cells. Finally, the effect of MED1 on the expression of IGF2/H19 as well as the malignant phenotype of HCC cells in vitro and in vivo mediated by miR-483-5p was evaluated.

Mir-483-5p up-regulated IGF2 P2 mRNA-P4 mRNA and H19 expression by binding to IGF2/H19 enhancer resulting in IGF2/H19 enhancer activation in HCC cells. Mechanistically, miR-483-5p increased recruitment of Ago1 and Ago2 at IGF2/H19 enhancer and then activated transcription of IGF2/H19 eRNA by RNA polymerase II and p300, which further induced chromatin loops formation between IGF2/H19 enhancer and IGF2/H19 promoters to activate IGF2/H19 promoters via IGF2/H19 eRNA-MED1-IGF2/H19 promoters complex in HCC cells. In this process, MED1 promoted chromatin loops formation as well as the malignant phenotype of HCC cells in vitro and in vivo mediated by miR-483-5p.

miR-483-5p-mediated activating of IGF2/H19 enhancer up-regulates IGF2/H19 expression via DNA loops, thereby promoting the malignant progression of HCC.

Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA).

Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC).

The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively).

We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Hepatocellular carcinoma (HCC) is a global health problem with increasing morbidity and mortality, and exploring the diagnosis and treatment of HCC at the gene level has become a research hotspot in recent years. As the rate-limiting enzyme of carnosine hydrolysis, CNDP1 participates in the progress of many diseases, but its function in HCC has not been fully elucidated.

This study firstly screened differentially expressed genes from the biochip related to HCC by bioinformatic analysis, and CNDP1 was finally selected for in-depth study. Then the bioinformatics analysis results were validated by detecting the expression of CNDP1 in human HCC samples and hepatoma cell lines. Furthermore, the effect of CNDP1 on the malignant behavior of hepatoma cell lines were assessed using MTT colorimetric assay, EdU staining assay, colony formation, wound-healing assay and transwell, and the molecular mechanism was also preliminarily explored.

This study found that CNDP1 expression was decreased significantly in human HCC tissues and cell lines, and its overexpression could significantly suppress cell proliferation, migration and invasion of hepatoma cell lines. Mechanistically the GeneMANIA database predicted that CNDP1 could interact with various proteins involved in regulating PI3K-AKT-mTOR signaling pathway. Furthermore, this study showed that CNDP1 overexpression could effectively inhibit the activation of PI3KAKT- mTOR signaling pathways, more significantly, inhibition of PI3K-AKT-mTOR signaling pathway could disrupt the anti-cancer effect of CNDP1 on HCC.

This study confirm that CNDP1 expression is decreased significantly in HCC, and has potential anti-cancer activity, this discovery provides a cytological basis for further understanding the biological function of CNDP1 and diagnosis and gene therapy of HCC in the future.

Hepatocellular carcinoma (HCC) circulating tumor cells (CTCs) exhibit significant phenotypic heterogeneity and diverse gene expression profiles due to epithelial-mesenchymal transition (EMT). However, current detection methods lack the capacity for simultaneous quantification of multidimensional biomarkers, impeding a comprehensive understanding of tumor biology and dynamic changes. Here, the CTC Digital Simultaneous Cross-dimensional Output and Unified Tracking (d-SCOUT) technology is introduced, which enables simultaneous quantification and detailed interpretation of HCC transcriptional and phenotypic biomarkers. Based on self-developed multi-real-time digital PCR (MRT-dPCR) and algorithms, d-SCOUT allows for the unified quantification of Asialoglycoprotein Receptor (ASGPR), Glypican-3 (GPC-3), and Epithelial Cell Adhesion Molecule (EpCAM) proteins, as well as Programmed Death Ligand 1 (PD-L1), GPC-3, and EpCAM mRNA in HCC CTCs, with good sensitivity (LOD of 3.2 CTCs per mL of blood) and reproducibility (mean %CV = 1.80-6.05%). In a study of 99 clinical samples, molecular signatures derived from HCC CTCs demonstrated strong diagnostic potential (AUC = 0.950, sensitivity = 90.6%, specificity = 87.5%). Importantly, by integrating machine learning, d-SCOUT allows clustering of CTC characteristics at the mRNA and protein levels, mapping normalized heterogeneous 2D molecular profiles to assess HCC metastatic risk. Dynamic digital tracking of eight HCC patients undergoing different treatments visually illustrated the therapeutic effects, validating this technology's capability to quantify the treatment efficacy. CTC d-SCOUT enhances understanding of tumor biology and HCC management.

Hepatocellular carcinoma (HCC) is a cancer caused by inflammation, which affects the immune response and treatment outcomes. Finding new immune-related targets could improve HCC immunotherapy. New research suggests that TMEM family proteins can act as either tumor suppressors or oncogenes, but the role of TMEM101 in HCC development is unclear. This study conducted an analysis of TMEM101 mRNA expression and its correlation with clinical outcomes in HCC patients using RNA sequencing data from various open databases. Additionally, differences in TMEM101 expression in HCC cell lines and HCC tissue microarrays were examined using RT-qPCR, western blotting, and in situ hybridization staining. The findings presented herein offer initial evidence indicating a significant upregulation of TMEM101 mRNA expression in HCC, which is linked to a poorer prognosis. Furthermore, TMEM101 expression was found to be positively associated with the histological grade and clinical stage of HCC patients. Moreover, a notable reduction in promoter methylation of TMEM101 was observed in HCC patients. Cox regression analysis indicated that TMEM101 was an independent prognostic factor for overall survival (OS) in HCC patients. A nomogram incorporating TMEM101 and tumor stage was constructed and assessed. Comparative analysis with four established HCC diagnostic biomarkers (AFP, EFNA3, MDK, and SMYD5) using ROC curve and time-dependent ROC curves demonstrated the diagnostic potential of TMEM101 in HCC. Gene set enrichment analysis (GSEA) revealed a correlation between TMEM101 and the cell cycle, DNA replication, and repair signaling pathways, which were differentially enriched in the TMEM101 high expression phenotype. The findings from CIBERSORT analysis suggest that TMEM101's pro-tumor effect may be due to decreasing the number of anti-tumor immune cells (M1 macrophages and resting memory CD4+ T cells) and promoting M0 macrophage infiltration in the tumor microenvironment (TME). Overall, our study indicates that TMEM101 could serve as a promising diagnostic and prognostic biomarker for HCC.

Since the emergence of the hot topic of "ferroptosis," numerous studies have explored its role in hepatocellular carcinoma (HCC), revealing its significance in the disease's pathogenesis, progression, and treatment. However, there remains a significant gap in the quantitative analysis of ferroptosis in HCC. Therefore, this study aims to comprehensively assess the research progress and evolution in this field through bibliometric and citation analysis.

On June 27, 2024, the author conducted a literature search, extracting relevant publications from the Web of Science Core Collection (WOSCC) Science Citation Index Expanded (SCIE) spanning from January 2010 to December 2023. Subsequently, the compiled documents were subjected to bibliometric evaluation and analysis using visualization tools such as R package "bibliometrix", CiteSpace and VOSviewer.

The search yielded 576 papers by 3,925 authors, encompassing contributions from 34 countries and 685 institutions, published across 250 journals, including 25,889 co-cited references from 2,600 journals. Notably, China leads with a significant publication count of 481 articles (accounting for 83.5%) and demonstrates the strongest collaboration with the United States. The multifaceted role of ferroptosis in hepatocellular carcinoma (HCC) has garnered considerable attention. In recent years, research into disease prognosis, the tumor microenvironment, and targeted therapies involving immunology has become key themes and emerging frontiers in this field.

This study meticulously compiled and analyzed the current discourse and emerging perspectives on ferroptosis in HCC. Identifying research trends and hotspots offers valuable guidance for future investigations and provides a basis for the development of novel therapeutic strategies to improve HCC prognosis and treatment outcomes.

Fragmentomic features of circulating cell free mitochondrial DNA (ccf-mtDNA) including fragmentation profile, 5' end base preference and motif diversity are poorly understood. Here, we generated ccf-mtDNA sequencing data of 1607 plasma samples using capture-based next generation sequencing. We firstly found that fragmentomic features of ccf-mtDNA were remarkably different from those of circulating cell free nuclear DNA. Furthermore, region-specific fragmentomic features of ccf-mtDNA were observed, which was associated with protein binding, base composition and special structure of mitochondrial DNA. When comparing to non-cancer controls, six types of cancer patients exhibited aberrant fragmentomic features. Then, cancer detection models were built based on the fragmentomic features. Both internal and external validation cohorts demonstrated the excellent capacity of our model in distinguishing cancer patients from non-cancer control, with all area under curve higher than 0.9322. The overall accuracy of tissue-of-origin was 89.24% and 87.92% for six cancer types in two validation cohort, respectively. Altogether, our study comprehensively describes cancer-specific fragmentomic features of ccf-mtDNA and provides a proof-of-principle for the ccf-mtDNA fragmentomics-based multi-cancer detection and tissue-of-origin classification.